(* Content-type: application/vnd.wolfram.mathematica *) (*** Wolfram Notebook File ***) (* http://www.wolfram.com/nb *) (* CreatedBy='Mathematica 11.3' *) (*CacheID: 234*) (* Internal cache information: NotebookFileLineBreakTest NotebookFileLineBreakTest NotebookDataPosition[ 158, 7] NotebookDataLength[ 747384, 13262] NotebookOptionsPosition[ 740185, 13149] NotebookOutlinePosition[ 740519, 13164] CellTagsIndexPosition[ 740476, 13161] WindowFrame->Normal*) (* Beginning of Notebook Content *) Notebook[{ Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{ "correction", " ", "to", " ", "the", " ", "free", " ", "Hamiltonian", " ", "for", " ", "a", " ", "chain", " ", "Hamiltonian", " ", "for", " ", "a", " ", "chain", " ", "with", " ", "two", " ", "ends"}], "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{ RowBox[{"h1matchain", "[", RowBox[{ "tl_", ",", "tr_", ",", "\[Epsilon]0_", ",", "t0_", ",", "\[Epsilon]vec_", ",", "\[Tau]vec_"}], "]"}], ":=", RowBox[{"Module", "[", RowBox[{ RowBox[{"{", RowBox[{"ret", ",", "NT", ",", "i"}], "}"}], ",", "\[IndentingNewLine]", RowBox[{ RowBox[{"NT", "=", RowBox[{"Length", "[", "\[Epsilon]vec", "]"}]}], ";", "\[IndentingNewLine]", RowBox[{"ret", " ", "=", " ", RowBox[{"DiagonalMatrix", "[", RowBox[{"Join", "[", RowBox[{ RowBox[{"{", "0", "}"}], ",", RowBox[{"\[Epsilon]vec", "-", RowBox[{"Table", "[", RowBox[{"\[Epsilon]0", ",", RowBox[{"{", RowBox[{"i", ",", "1", ",", "NT"}], "}"}]}], "]"}]}], ",", RowBox[{"{", "0", "}"}]}], "]"}], "]"}]}], ";", "\[IndentingNewLine]", RowBox[{ RowBox[{"ret", "[", RowBox[{"[", RowBox[{"1", ",", "2"}], "]"}], "]"}], "=", RowBox[{"tl", "-", "t0"}]}], ";", "\[IndentingNewLine]", RowBox[{ RowBox[{"ret", "[", RowBox[{"[", RowBox[{"2", ",", "1"}], "]"}], "]"}], "=", RowBox[{"tl", "-", "t0"}]}], ";", "\[IndentingNewLine]", RowBox[{ RowBox[{"ret", "[", RowBox[{"[", RowBox[{ RowBox[{"NT", "+", "1"}], ",", RowBox[{"NT", "+", "2"}]}], "]"}], "]"}], "=", RowBox[{"tr", "-", "t0"}]}], ";", "\[IndentingNewLine]", RowBox[{ RowBox[{"ret", "[", RowBox[{"[", RowBox[{ RowBox[{"NT", "+", "2"}], ",", RowBox[{"NT", "+", "1"}]}], "]"}], "]"}], "=", RowBox[{"tr", "-", "t0"}]}], ";", "\[IndentingNewLine]", RowBox[{"For", "[", RowBox[{ RowBox[{"i", "=", "1"}], ",", RowBox[{"i", "<", "NT"}], ",", RowBox[{"++", "i"}], ",", "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"ret", "[", RowBox[{"[", RowBox[{ RowBox[{"i", "+", "1"}], ",", RowBox[{"i", "+", "2"}]}], "]"}], "]"}], "=", RowBox[{ RowBox[{"\[Tau]vec", "[", RowBox[{"[", "i", "]"}], "]"}], "-", "t0"}]}], ";", "\[IndentingNewLine]", RowBox[{ RowBox[{"ret", "[", RowBox[{"[", RowBox[{ RowBox[{"i", "+", "2"}], ",", RowBox[{"i", "+", "1"}]}], "]"}], "]"}], "=", RowBox[{ RowBox[{"\[Tau]vec", "[", RowBox[{"[", "i", "]"}], "]"}], "-", "t0"}]}], ";"}]}], "\[IndentingNewLine]", "]"}], ";", "\[IndentingNewLine]", "ret"}]}], "\[IndentingNewLine]", "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"g0matcrchain", "[", RowBox[{"\[Epsilon]0_", ",", "t0_", ",", "\[Omega]_", ",", "NT_"}], "]"}], ":=", RowBox[{"Table", "[", RowBox[{ RowBox[{ RowBox[{ RowBox[{"-", "I"}], "/", RowBox[{"Sqrt", "[", RowBox[{ RowBox[{"4", " ", RowBox[{"t0", "^", "2"}]}], " ", "-", RowBox[{ RowBox[{"(", RowBox[{"\[Omega]", "-", "\[Epsilon]0"}], ")"}], "^", "2"}]}], "]"}]}], RowBox[{ RowBox[{"(", RowBox[{ RowBox[{ RowBox[{"(", RowBox[{"\[Omega]", "-", "\[Epsilon]0"}], ")"}], "/", RowBox[{"(", RowBox[{"2", " ", "t0"}], ")"}]}], "-", RowBox[{"I", " ", RowBox[{"Sqrt", "[", RowBox[{"1", "-", RowBox[{ RowBox[{ RowBox[{"(", RowBox[{"\[Omega]", "-", "\[Epsilon]0"}], ")"}], "^", "2"}], "/", RowBox[{"(", RowBox[{"4", " ", RowBox[{"t0", "^", "2"}]}], ")"}]}]}], "]"}]}]}], ")"}], "^", RowBox[{"Abs", "[", RowBox[{"i", "-", "j"}], "]"}]}]}], ",", RowBox[{"{", RowBox[{"i", ",", "1", ",", RowBox[{"NT", "+", "2"}]}], "}"}], ",", RowBox[{"{", RowBox[{"j", ",", "1", ",", RowBox[{"NT", "+", "2"}]}], "}"}]}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"gfmatcrchain", "[", RowBox[{ "tl_", ",", "tr_", ",", "\[Epsilon]0_", ",", "t0_", ",", "\[Epsilon]vec_", ",", "\[Tau]vec_", ",", "\[Omega]_"}], "]"}], ":=", RowBox[{ RowBox[{"Inverse", "[", RowBox[{ RowBox[{"IdentityMatrix", "[", RowBox[{ RowBox[{"Length", "[", "\[Epsilon]vec", "]"}], "+", "2"}], "]"}], "-", RowBox[{ RowBox[{"g0matcrchain", "[", RowBox[{"\[Epsilon]0", ",", "t0", ",", "\[Omega]", ",", RowBox[{"Length", "[", "\[Epsilon]vec", "]"}]}], "]"}], ".", RowBox[{"h1matchain", "[", RowBox[{ "tl", ",", "tr", ",", "\[Epsilon]0", ",", "t0", ",", "\[Epsilon]vec", ",", "\[Tau]vec"}], "]"}]}]}], "]"}], ".", RowBox[{"g0matcrchain", "[", RowBox[{"\[Epsilon]0", ",", "t0", ",", "\[Omega]", ",", RowBox[{"Length", "[", "\[Epsilon]vec", "]"}]}], "]"}]}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"transmissionchain", "[", RowBox[{ "tl_", ",", "tr_", ",", "\[Epsilon]0_", ",", "t0_", ",", "\[Epsilon]vec_", ",", "\[Tau]vec_", ",", "\[Omega]_"}], "]"}], ":=", RowBox[{"Which", "[", RowBox[{ RowBox[{ RowBox[{"\[Omega]", ">", RowBox[{"\[Epsilon]0", "-", RowBox[{"2", "t0"}]}]}], " ", "&&", " ", RowBox[{"\[Omega]", "<", RowBox[{"\[Epsilon]0", "+", RowBox[{"2", "t0"}]}]}]}], ",", RowBox[{ RowBox[{ RowBox[{"Abs", "[", RowBox[{ RowBox[{"gfmatcrchain", "[", RowBox[{ "tl", ",", "tr", ",", "\[Epsilon]0", ",", "t0", ",", "\[Epsilon]vec", ",", "\[Tau]vec", ",", "\[Omega]"}], "]"}], "[", RowBox[{"[", RowBox[{"2", ",", RowBox[{ RowBox[{"Length", "[", "\[Epsilon]vec", "]"}], "+", "1"}]}], "]"}], "]"}], "]"}], "^", "2"}], " ", RowBox[{ RowBox[{ RowBox[{"Abs", "[", "tl", "]"}], "^", "2"}], "/", RowBox[{"t0", "^", "2"}]}], " ", RowBox[{"Sqrt", "[", RowBox[{ RowBox[{"4", RowBox[{"t0", "^", "2"}]}], "-", RowBox[{ RowBox[{"(", RowBox[{"\[Omega]", "-", "\[Epsilon]0"}], ")"}], "^", "2"}]}], "]"}], RowBox[{ RowBox[{ RowBox[{"Abs", "[", "tr", "]"}], "^", "2"}], "/", RowBox[{"t0", "^", "2"}]}], " ", RowBox[{"Sqrt", "[", RowBox[{ RowBox[{"4", RowBox[{"t0", "^", "2"}]}], "-", RowBox[{ RowBox[{"(", RowBox[{"\[Omega]", "-", "\[Epsilon]0"}], ")"}], "^", "2"}]}], "]"}]}], ",", "True", ",", "0.0"}], "]"}]}], ";"}]}]}]], "Input", CellChangeTimes->{{3.806906019156102*^9, 3.80690602666958*^9}, { 3.806906133492557*^9, 3.806906140997231*^9}, {3.806906249754401*^9, 3.8069062500302677`*^9}, {3.806906364194779*^9, 3.806906434729596*^9}, { 3.8069064772505417`*^9, 3.806906482223989*^9}, {3.8069066327901373`*^9, 3.80690670840663*^9}, {3.806906740709559*^9, 3.806906841200274*^9}, { 3.806906931872303*^9, 3.806907011453478*^9}, {3.806907064861312*^9, 3.8069070649816437`*^9}, {3.806907115491888*^9, 3.806907168230152*^9}, { 3.8069072729545927`*^9, 3.8069073945422897`*^9}, {3.8069074848260183`*^9, 3.806907585677292*^9}, {3.806910119861252*^9, 3.806910120793832*^9}, { 3.813394238747167*^9, 3.813394239135481*^9}, {3.813394283718623*^9, 3.81339430987991*^9}, {3.8218538085579643`*^9, 3.8218538438664627`*^9}, 3.831690761914152*^9, 3.832037152542651*^9}, CellLabel->"In[1]:=",ExpressionUUID->"444839ce-4487-4b36-91b4-b3030a262fd5"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"ListPlot", "[", RowBox[{ RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"w", ",", RowBox[{"transmissionchain", "[", RowBox[{ RowBox[{ RowBox[{"Sqrt", "[", "0.1", "]"}], "/", RowBox[{"Sqrt", "[", "2", "]"}]}], ",", RowBox[{ RowBox[{"Sqrt", "[", "0.1", "]"}], "/", RowBox[{"Sqrt", "[", "2", "]"}]}], ",", "0", ",", RowBox[{"1.0", "*", "0.1"}], ",", RowBox[{"{", RowBox[{ "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0"}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", " ", "0.007326447541946075`", ",", "0.007269560988958051`", ",", "0.007238948047382406`", ",", "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}], "/", "0.02"}], ",", "w"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"w", ",", RowBox[{"-", "1"}], ",", RowBox[{"+", "1"}], ",", "0.01"}], "}"}]}], "]"}], ",", "w"}], "]"}], ",", RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}]], "Input", CellChangeTimes->{{3.831690210002795*^9, 3.831690213149312*^9}, { 3.831690267788336*^9, 3.831690289193513*^9}, {3.831690393535852*^9, 3.8316904974360867`*^9}, {3.831690528734693*^9, 3.8316906274520283`*^9}, { 3.831690690176978*^9, 3.8316907104434843`*^9}}, CellLabel->"In[10]:=",ExpressionUUID->"741b7126-90be-46e6-884d-10385b5513e3"], Cell[BoxData[ GraphicsBox[{{}, {{}, {RGBColor[0.368417, 0.506779, 0.709798], PointSize[0.009166666666666668], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJxllltoVGcQx9P6YBoCKoiUFuIFtFYfLCpYmpqhTypSUGnBBxERDOKDRqhg tYItKiLICi2iUlRqKO3LqkEwgs0XTcSoSdi4mnhJdC/JZjd7OSmoqHipZ2bO fPjvByH7Y/fMmZnfnO87MzduW7Ppw6qqqhvv/sL/ssZd9Cm+LL1rajwwXhe7 +nTuOs81A2ealtZ4bq3bX1zdWjFu5OV5Kgf0HEaLXS0bb18aRvQ8PQxX57mn O1wl490c0PPnnKBnTm+gaMzh9ntexMtzWO2y9Jgxlxvz3MAFey5xuILxiePh 8rycA3p+Fpb7NG/cHKZ3xvMabqBnWXnwMQo+RsHHKPjIgY8c+MiBjxFjTq/J M4er88w6uofBxzD4GAYfWfCRBR9Z8JExPsIJZsBHBnykwUcafKTBRwp8pMBH CnykoP+Pod+PoL+PoJ9D0L9BY05nrud93J+HxhlO/wHU/wDqvQ/13YN6PMs8 DcD8eJZ56Yf5uAvz4JnT23XHuJ/DJY0Xst8k+LwN/vrAVx/4SYCPBPS/F/rd A/3tNk5xwjeNj3H/bhiv4oBdbtbB5Jb6H/6hau7Pddf07M9JP067Re3cj2tu 62h/om1Pkn7i+jvd/ENvP131x31azPV2uNrgyYrG2hRJfVdcrubwB1M2ZEnq aXevX3zfFz+VI8m/zcXu3lq7JFYgyfey66meffqr50WS/C65jpZft9a3lTWf i677s6GJn+QqtJPvf8FVt65seXE4oDzf77xrafh5bXYooHMcP+5WzOhK3HwZ 0BGO97cbPptb9OZtQHv5+mY3smPB8po3AbXz70+6a3M6Gk68ir7/zR39ZnB9 4+uI97kl9RM+nvPu+ve9jEffU/S9Xk/R9Rqf3o/fTNH9T0t+9K/mJ7+P07ea /7jURye1Prn+An2k9U+W/lDUH4l3iRLavy+kv9Sl/ZX4bfSL9v8v8UMTXoof ud8VSqm/L8UvTVS/0v9O2qj+dT4omg+dH4rmR+eLovnS+SOYT2OdX2Odb2Od f/CQMNbnx1ifL2N9/oz1+TSWeU4a35Pn21jm/47xDNkfjDtl/zDeLPuLca3s P8bnZH8y/k72L+Pnsr8Z/y77n/HXsj9CPz3r/gr9HTTW/Rn6PWSs+zv037Oe D+AjZaznC/jxrOcT+Eob6/kG/jzr+Qg+Pct5kgG/WeMDcj6Db8/z5HwH/557 5f0A5mEE+ulZ3z+gvzljfX+BfnvW9x/ov2d9fwIfefCRBx958JEHHwXwUQAf BfAxBj7GwMcY+CiCjyL4KIKPEvgogY8S+CiDjzL4KIOPCviogI8K+AjARwA+ /n9uRJ/+A8Ql8lk= "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{True, True}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{False, False}, {False, False}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotRange->{{-1., 1.}, {0, 1.}}, PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.02], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]], "Output", CellChangeTimes->{ 3.831690550608675*^9, 3.831690587120036*^9, 3.8316906310178556`*^9, { 3.8316906996067142`*^9, 3.831690711155562*^9}}, CellLabel->"Out[10]=",ExpressionUUID->"8a57fc09-71e6-469b-8437-56b2822c39aa"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Sort", "[", RowBox[{"Eigenvalues", "[", RowBox[{"Take", "[", RowBox[{ RowBox[{"h1matchain", "[", RowBox[{"tl", ",", "tr", ",", "0", ",", "0", ",", RowBox[{"{", RowBox[{ "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0"}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", " ", "0.007326447541946075`", ",", "0.007269560988958051`", ",", "0.007238948047382406`", ",", "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}], "/", "0.02"}]}], "]"}], ",", RowBox[{"{", RowBox[{"9", ",", "14"}], "}"}], ",", RowBox[{"{", RowBox[{"9", ",", "14"}], "}"}]}], "]"}], "]"}], "]"}]], "Input", CellChangeTimes->{{3.831692045400004*^9, 3.831692167317769*^9}, { 3.831692203356929*^9, 3.8316922463363533`*^9}, {3.831692294347076*^9, 3.8316922965071173`*^9}, {3.831694030504581*^9, 3.831694032648903*^9}, { 3.831694250372109*^9, 3.831694253395878*^9}, {3.8316943890133533`*^9, 3.831694391251053*^9}, {3.831694580024413*^9, 3.8316945910242167`*^9}, { 3.831694797389598*^9, 3.831694800997238*^9}, {3.831694997923871*^9, 3.8316950018085423`*^9}}, CellLabel->"In[11]:=",ExpressionUUID->"9c3f0776-c046-4a2f-bed3-e3ef5e801456"], Cell[BoxData[ RowBox[{"{", RowBox[{ RowBox[{"-", "0.7158741160765367`"}], ",", RowBox[{"-", "0.510872054653592`"}], ",", RowBox[{"-", "0.18512855870184186`"}], ",", "0.18512855870184183`", ",", "0.5108720546535919`", ",", "0.7158741160765367`"}], "}"}]], "Output", CellChangeTimes->{{3.831692156229991*^9, 3.831692167955037*^9}, { 3.83169220785712*^9, 3.8316922468961906`*^9}, 3.831692297052979*^9, 3.831694033008462*^9, 3.831694253843236*^9, 3.831694391648753*^9, { 3.831694583193408*^9, 3.831694591588584*^9}, 3.831694802112317*^9, 3.831695002595853*^9}, CellLabel->"Out[11]=",ExpressionUUID->"22d81a92-adaf-4cc4-9952-576afb5414fa"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Export", "[", RowBox[{"\"\\"", ",", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"w", ",", RowBox[{"transmissionchain", "[", RowBox[{ RowBox[{ RowBox[{"Sqrt", "[", "100", "]"}], "/", RowBox[{"Sqrt", "[", "2", "]"}]}], ",", RowBox[{ RowBox[{"Sqrt", "[", "100", "]"}], "/", RowBox[{"Sqrt", "[", "2", "]"}]}], ",", "0", ",", RowBox[{"1.0", "*", "100."}], ",", RowBox[{"{", RowBox[{ "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0", ",", "0"}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", " ", "0.007326447541946075`", ",", "0.007269560988958051`", ",", "0.007238948047382406`", ",", "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}], "/", "0.02"}], ",", "w"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"w", ",", RowBox[{"-", "1"}], ",", RowBox[{"+", "1"}], ",", "0.01"}], "}"}]}], "]"}], ",", "w"}], "]"}]}], "]"}]], "Input", CellChangeTimes->{{3.831690746008627*^9, 3.8316907880844717`*^9}, { 3.831690843560356*^9, 3.83169085106044*^9}, {3.831690912936379*^9, 3.831690917708632*^9}, {3.83169175561034*^9, 3.83169176411446*^9}}, CellLabel->"In[15]:=",ExpressionUUID->"9e701970-221a-4362-b8ed-b4f3d34099f7"], Cell[BoxData["\<\"test.dat\"\>"], "Output", CellChangeTimes->{3.831690752815103*^9, 3.8316907894396772`*^9, 3.83169085302011*^9, 3.831690918831396*^9, 3.831691765386685*^9}, CellLabel->"Out[15]=",ExpressionUUID->"7274b1a0-96a3-44e8-a6b5-1b257220087c"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Reverse", "[", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", " ", "0.007326447541946075`", ",", "0.007269560988958051`", ",", "0.007238948047382406`"}], "}"}], "]"}]], "Input", CellChangeTimes->{{3.831690512403409*^9, 3.831690514239038*^9}}, CellLabel->"In[5]:=",ExpressionUUID->"fe5609fc-1720-45d2-8af0-1aebf87d786d"], Cell[BoxData[ RowBox[{"{", RowBox[{ "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]], "Output", CellChangeTimes->{3.831690514992791*^9}, CellLabel->"Out[5]=",ExpressionUUID->"40d79cdb-6670-46fe-a9ea-cf0f40ac266f"] }, Open ]], Cell[BoxData[ RowBox[{"\[IndentingNewLine]", RowBox[{"(*", RowBox[{ RowBox[{"Tilmanns", " ", RowBox[{"parameter", ":", "\[IndentingNewLine]", SubscriptBox["\[Beta]", "L"]}]}], "=", RowBox[{ SubscriptBox["\[Beta]", "R"], "=", RowBox[{"\[Beta]", "=", RowBox[{ RowBox[{ "1", "\[IndentingNewLine]", "Spektrale", " ", "Kopplungsst\[ADoubleDot]rke", " ", "\[CapitalGamma]"}], "=", RowBox[{ RowBox[{"0.02", " ", RowBox[{"(", "wideband", ")"}], "\[IndentingNewLine]", "\[Epsilon]"}], "=", RowBox[{ RowBox[{ "0", "\[IndentingNewLine]", "Von", " ", "au\[SZ]en", " ", "nach", " ", "innen", " ", "in", " ", "der", " ", "Kette", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", "L"]}], "=", RowBox[{ RowBox[{"0.009999959154289148`", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"2", "L"}]]}], "=", RowBox[{ RowBox[{"0.00781394527921633`", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"3", "L"}]]}], "=", RowBox[{ RowBox[{"0.0074508497062710805`", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"4", "L"}]]}], "=", " ", RowBox[{ RowBox[{"0.007326447541946075`", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"5", "L"}]]}], "=", RowBox[{ RowBox[{"0.007269560988958051`", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"6", "L"}]]}], "=", "0.007238948047382406`"}]}]}]}]}]}]}]}]}]}]}], "\[IndentingNewLine]", "*)"}], "\[IndentingNewLine]", RowBox[{"(*", "\[IndentingNewLine]", RowBox[{ RowBox[{"Anpassung", " ", "wideband", " ", RowBox[{"limes", ":", "\[IndentingNewLine]", "tl"}]}], "=", RowBox[{"tr", "=", RowBox[{ RowBox[{ "t", " ", "und", " ", "t0", " ", "sehr", " ", "gro\[SZ]", " ", "mit", "\[IndentingNewLine]", "2", " ", RowBox[{ RowBox[{"t", "^", "2"}], "/", "t0"}]}], "=", "0.02"}]}]}], " ", "\[IndentingNewLine]", "*)"}], "\[IndentingNewLine]", RowBox[{"(*", " ", RowBox[{ RowBox[{ "optimale", " ", "Parameter", " ", "f\[UDoubleDot]r", " ", "direkte", " ", "Anpassung", " ", "der", " ", "SD", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", "L"]}], "=", RowBox[{ RowBox[{ "0.44798874545216505`", " ", "\[CapitalGamma]0", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"2", "L"}]]}], "=", RowBox[{ RowBox[{ "0.3720949697259449`", " ", "\[CapitalGamma]0", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"3", "L"}]]}], "=", RowBox[{ RowBox[{ "0.3666741914433289`", " ", "\[CapitalGamma]0", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"4", "L"}]]}], "=", RowBox[{ RowBox[{ "0.36586118013042696`", " ", "\[CapitalGamma]0", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"5", "L"}]]}], "=", RowBox[{ RowBox[{ "0.3656755715952492`", " ", "\[CapitalGamma]0", "\[IndentingNewLine]", SubscriptBox["\[Lambda]", RowBox[{"6", "L"}]]}], "=", RowBox[{"0.365617222323006`", " ", "\[CapitalGamma]0"}]}]}]}]}]}]}], "\[IndentingNewLine]", "\[IndentingNewLine]", "*)"}]}]], "Input", CellChangeTimes->{{3.813077806089095*^9, 3.8130778838556857`*^9}, { 3.8130783365291033`*^9, 3.8130784946916685`*^9}, 3.8130837482687016`*^9, { 3.8130837858872943`*^9, 3.8130837879147468`*^9}, {3.8130838404776754`*^9, 3.8130839105098515`*^9}, {3.813084006914996*^9, 3.8130840102371163`*^9}, { 3.813084045067868*^9, 3.8130840512755785`*^9}, {3.813084220234455*^9, 3.813084226120223*^9}, {3.8133847495577993`*^9, 3.81338479686889*^9}, { 3.81338491363939*^9, 3.813384968760747*^9}, {3.813385558298493*^9, 3.8133856362547626`*^9}, {3.813386704797917*^9, 3.813386763042193*^9}, { 3.8133890114049377`*^9, 3.81338901258523*^9}, {3.822021995846023*^9, 3.822022078688841*^9}, {3.822022205052333*^9, 3.8220222760421467`*^9}},ExpressionUUID->"d071d3b0-c4f3-4a2a-91e8-\ 3f5fa22b6b82"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", "0.", "}"}], ",", RowBox[{"{", "}"}], ",", "1."}], "]"}]], "Input", CellChangeTimes->{{3.821853766502349*^9, 3.821853768807015*^9}}, CellLabel->"In[25]:=",ExpressionUUID->"b740b859-d8ab-47ec-96a7-d14d70b5f1d8"], Cell[BoxData["0.00039991001799640033`"], "Output", CellChangeTimes->{3.821853769230338*^9, 3.821853818255076*^9, 3.821853864229348*^9}, CellLabel->"Out[25]=",ExpressionUUID->"5a826dcb-9943-43a6-8716-0814a2e03c8a"] }, Open ]], Cell[BoxData[""], "Input", CellChangeTimes->{{3.832037999548263*^9, 3.832038019321727*^9}, 3.832038137947199*^9},ExpressionUUID->"eda01849-39bf-4147-9e87-\ d90452d4acf7"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{ RowBox[{ RowBox[{"1.", " ", "Optimierung"}], " ", "\[Rule]", " ", RowBox[{"Arbeit", " ", "Tilmann"}]}], ",", " ", RowBox[{"Korrektur", " ", "am", " ", RowBox[{"7.6", "."}]}]}], "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", "0.", "}"}], ",", RowBox[{"{", "}"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{"0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{"0.009999959154289148`", ",", "0.009999959154289148`"}], "}"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{"0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007269560988958051`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007269560988958051`", ",", "0.007238948047382406`", ",", "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}], ",", "w"}], "]"}]}], "\[IndentingNewLine]", "}"}], ",", RowBox[{"{", RowBox[{"w", ",", RowBox[{"-", "0.02"}], ",", RowBox[{"+", "0.02"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", "All"}], ",", RowBox[{"PlotLabels", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\""}], "}"}]}]}], "]"}], "\[IndentingNewLine]", RowBox[{"(*", RowBox[{"2.", " ", "Optimierung"}], "*)"}], "\[IndentingNewLine]", RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", "0.", "}"}], ",", RowBox[{"{", "}"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{"0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{"0.44798874545216505`", ",", "0.44798874545216505`"}], "}"}], "*", "0.02"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{"0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.44798874545216505`", ",", "0.3720949697259449`", ",", "0.3720949697259449`", ",", "0.44798874545216505`"}], "}"}], "*", "0.02"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.44798874545216505`", ",", "0.3720949697259449`", ",", "0.3666741914433289`", ",", "0.3666741914433289`", ",", "0.3720949697259449`", ",", "0.44798874545216505`"}], "}"}], "*", "0.02"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.44798874545216505`", ",", "0.3720949697259449`", ",", "0.3666741914433289`", ",", "0.36586118013042696`", ",", "0.36586118013042696`", ",", "0.3666741914433289`", ",", "0.3720949697259449`", ",", "0.44798874545216505`"}], "}"}], "*", "0.02"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.44798874545216505`", ",", "0.3720949697259449`", ",", "0.3666741914433289`", ",", "0.36586118013042696`", ",", "0.3656755715952492`", ",", "0.3656755715952492`", ",", "0.36586118013042696`", ",", "0.3666741914433289`", ",", "0.3720949697259449`", ",", "0.44798874545216505`"}], "}"}], "*", "0.02"}], ",", "w"}], "]"}], ",", "\[IndentingNewLine]", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.44798874545216505`", ",", "0.3720949697259449`", ",", "0.3666741914433289`", ",", "0.36586118013042696`", ",", "0.3656755715952492`", ",", "0.365617222323006`", ",", "0.365617222323006`", ",", "0.3656755715952492`", ",", "0.36586118013042696`", ",", "0.3666741914433289`", ",", "0.3720949697259449`", ",", "0.44798874545216505`"}], "}"}], "*", "0.02"}], ",", "w"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"w", ",", RowBox[{"-", "0.02"}], ",", RowBox[{"+", "0.02"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", "All"}], ",", RowBox[{"PlotLabels", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\""}], "}"}]}]}], "]"}]}]}]], "Input", CellChangeTimes->{{3.806907591016699*^9, 3.806907646584033*^9}, { 3.806909728698367*^9, 3.8069097578707037`*^9}, {3.80690980668257*^9, 3.8069098220420437`*^9}, {3.8069098854805603`*^9, 3.806909895232012*^9}, 3.80691008444273*^9, {3.80691016187286*^9, 3.8069102521119967`*^9}, { 3.8069102823626842`*^9, 3.806910331422831*^9}, {3.806912698304428*^9, 3.806912723296521*^9}, {3.806912755950612*^9, 3.806912971959086*^9}, { 3.8069131596205797`*^9, 3.8069132376512957`*^9}, {3.806913328799663*^9, 3.806913376979063*^9}, {3.8069837688700657`*^9, 3.8069837863484497`*^9}, { 3.81338565945757*^9, 3.813385805528038*^9}, {3.813385845980076*^9, 3.813385911342453*^9}, {3.81338599633952*^9, 3.81338602686318*^9}, { 3.8133861141635857`*^9, 3.813386133031727*^9}, {3.813386812238212*^9, 3.813386956736246*^9}, {3.822022323032516*^9, 3.82202242779955*^9}, { 3.822022471954734*^9, 3.822022644216096*^9}, {3.822022761579287*^9, 3.822022763775576*^9}, {3.8220228699415207`*^9, 3.8220228731731*^9}, { 3.832037204489497*^9, 3.832037323871855*^9}, {3.83203737219198*^9, 3.832037437255291*^9}, 3.832037471965851*^9}, CellLabel->"In[5]:=",ExpressionUUID->"0cafabec-9ace-4856-87cb-9f2040807a27"], Cell[BoxData[ GraphicsBox[{{{}, {}, TagBox[ {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJw113dUzf//APAUWqQiDZV2aYiEtJ4tpb1LS7cpmiIpaYi050WRtpIGItqv JGn6tFRWblPzvhMNDb4v5/x+f9xzz+O87z3n/Xq+Xs/xEnT2NXOjpaGh2cSf f983BopOjASTUWZo+KQHDQX2fK1ZKA4kI96GVd05WgoUjHUV+V8io/YqT3a/ bRRoXvjJsdWHjHpc1XuvMFFgG7PaopgTGXHwP9yZtIcCUTD02EuHjCJUpv3f S1Dg1iMG3tXdZHQ3jeFHuikFYoPP/WEpS0MhLkvm9gUUcBxHDXNdqYjE0bYs 6zACfkn842mbKYhpT1iDIesoaGye0Tc9nIL4eZ+7D7wdhbFD8uUN5snI1/JN PkvKGITpC8/NMCah3kjJjwctxuFDI/3FKt0ENLSnfP+C9AQ8qX1yrSIlDolk cYYrbp+EvwoeZrASgzKe29Cu9E3CvLoev7RiNKqWLUziq/wOpl3KL0ruRaGd j9NlP9+aghPDi13WdDdRyd3E4SuW09AQ3DvsohuJxPtnzFIPz0BNRlM1bVkE 0rctihFfm4Gi6CpOui9hKJ0raW2+YxYoU/5vbHxCUBiaLIlImoPtRkZ0A0pB qMcwX/K44jycbQ85zN4cgGqiJj/Mjs1DpX7nz4u3/NGpP4/kHS9QgWsgMdgr yB+t3/jbmnmRCsEk0y1unv7IVOPan6EAKqgGDLBYGfujMBVFPcNgKrRkUQ4o cPqjlpFPpqKRVBj68ctxo/ACupWfE5dKpsLaXb7OGy1+KJr+FL3DSyqEtH49 JcXsg/TGAlgSl6iQzpHNn014oxUHCWb3FSpUOpN+sfd7ow4RpUTl31Sgboxm r2V6o/Cd6qITG1QgHZ5abjvojR7f5LglspUArXuLBR5mXmi+1OiBHTsBO7zo txRmnEdPjBs0imQIkKhuHeAOPY8u5qasGckScHJ7bGmC83lEbHqKLx0iIDRn x+kAqfMolEloWFmegIV+tida9efQFkn5Z9WKBPSr8DqMUTyQbJ54iIcOAZm7 DlcLSJxFN9vmpe86EkBxTav1ZjmLLPK84n+SCBCpWaqv+eWO9n0JiTJyJqDU tabJ4rU7inzUfYrGjYDaas3OaFt3JFj7bt3sPAGfXKy+LcS7oc8dOq0vLhHA XXV12+sfLmjJ1uPK2WgC7HcO07MMuaD13NqAOzEE5DirMdk1uCAmAyXa5li8 vp3bdi3FuiARNu93PAkEKDgnch0Qwf8fIv1+mULA6R25UilWzog5bq6i+B4B d0gtpk61JFS9Xq5/uYQAstF98xvZJGT8hnZPfCkBqcp+lkWRJDS3ybU/p4yA BC4em3l9Etquw7XR9IQAhtzPjYtVjuh2k+O7n88JGA+XHBZad0A7IsssttTh eNj3j3i8cUDnLP7jX8f+rBA6UR7ngOikxcV+1hPQu9Azp8jrgLjeSc5+RQQ0 koLWzVTs0fDpyyez3hDwQK2VKzLMFlmWZv9qaycgndeft03HFvXkMXoVdeD3 Xd0nsIvVFmnSPtkX2UlA/FNf8fs5Noj9UoTQ0fcEBAtwHnv++jQqoFFqiewh wIrG3XyMzhpZHikQ7xgkgKWRLlEz2hzpm0aF0ozh+JQSM0oW5qhHouBhBnZe +mcdeQFzVLBurHB4nIDjF55vEa0yQ9qR2dl2EwSQhFwCtk+ZIroVtQsPvhPw /EaTfZuOCXonr7/eP0vAH7/y6te7TdC+cfZ3FnMEJNfIy1xCxijdsGO9F7va czzHkjBCTryXs9vn8Xl9rxnNZWyIeA3LOwoJAp6l0lpnseghwmc1nf0nAdqe n1iTCnWRRuuOsSvYnzQr2sNUsf3n0r5ib11yUnXyOYV47VIP5P3C67V+LSry Xhtx7dQX5FomYFY249sed210NDQs6wJ2OMOFjG1/TiJ+1nsRbdjF1QI7v8uc RJ7te4MurRCwsS/8V3GCJtLY6i75ahW//y/r8nuimkjJfLOP7jcBol2yHnH1 GihO4fmoEbZR6LfPXvPqSMVJWJaCnUtRfSNrqIYUT1ZGEGsEePrLrKm1A3qQ MGkqu473T/irt9CaKiJISVHe2N9vKltO2Kgglp8bvBPY8Xrrwp7cioi3zXqj cYOAwIb4j86GJ9AYo8ziIrazHH+SbYQCEm1asRPexOedR31Nd/oYGiw+GheG LZzY+0Sd7xjiiUg0KcFmoXV1O2F6FM32FsZ8wB6fjuqWqD6CHkp/txL9Q8B/ DlxRAvNyCCZWZvSwa3qKlbgE5VDGi4xFH+zk6s5C+phDiFP0nH0F9rJtXdWf IFl0/UhkQw92l8Y3YeqIDHIMoicT2MHsomudzyRR6n3pDLG/BJis6bjVcR9A B3LrWwFbbPR8d0mEONptk+Fpjb3RlqB0f1oUWQtWRXhj9z57WhhrKoLyLfcw X8d+lNHHFlwthK79V0R/Gzs0YjnknKAgMp31Ciz897xXrvsZ+37ErXXG9iW2 Zd6VwuTRfYjmb+DTZuwt/g0hvhVcKIaxMqgHu0x9q7nRdQ7kVcP+8gu2DZve ARkzdqRxJ95tEpu5af9fTi0W9JYiEE3FdnUqKfkwRo/YDDv5lrDraI6fTovc gnKHE8TWsCXUbjLmaS83CNxwydvEfrqp8FZxx1hD1DGDlL//fr/bWUixr001 nfbUz39OpD8/MLhEqNLKWrX+wd77li/Vr3ZDNZMrkHUD+4hmZOZa/VaQWi3p WMH+lL9CKPMzw1L60u8f2Oq0L3MBscLxUsv7M9i35fw6SMRuuLnw/skI9rSz 5FLEfk6o3+NyfBBbOW2cP9+YB3Yp7JXrwE5+k3WqOYwP5DJnsuuxF4Okqxet BaB6fTy8HJs3ldGIbkEQsj4xfniArf14cnR3tDAwFjpkxmH7Nb0JFBEQhVf5 EwOB2M2L13JPmkiAZv3jh/rYVCa7Y1ZTByCV9deJI9hcwgod7uFSEDodp86N 7WW++OvW04OgN/LmMQWfl47K71oGIoegw/zSjiZsirpVksXCIfh2mTySi81k e0TELVoOzOa1J+2x90/m+nhbHIFg/3kOBWx5f9bqAAF5SBCVqmbDPhM7bxhV dRQEL6fbNuLz/qymKLBoSgFm9iczMWOvhke0/H17Ar4knMn4gPNJVceO43S+ IlSI81llYbf3sTxnOKMM3WWVNpLYo3MB1HN9AAfCEuKk/+XvxyJ+p9NqcL91 Z/wUzu9XdXu0d75Tg/a/YrV52JvXqWS3AnXwo7/+kA07Zlee3F5HTSjOe1D2 EdeT0kUW26YuTbBgzBa9hd394WqEj7IWvDJm6JLD3ptp2d3CfRJeMEU/voHr UZ4Eo09gvzb4ckbls+N6VaPuVzykqwdFPyaLBxcJ+CrytftGlR4YqmmIe2DT MOitHhLXh2+r+waWf+D9ey+sE7PVABbOTrSyYPfZDo6fQIbAxCdLfwDX2+UT +5MN75mA5Wo8Mz2u39ElH/Lze0xgm/XxF8EzuB/zxb/6zWAKnfVsKXPT+DzR /B5+GGgK96K5p9qnCLje0ivzx8IMjrkMs/pP4npjHtVRvssC1Iwyg8+PEGD6 Yu2mmaYFMHd5DHRScPw4fNWWL1vAqGJegQw295B1pcqwBVhEc2fMDOP5weFA dmepJeQ8svxu+oUAxbOd/jO61uBOnNEaGCDA7So7j9gNW4jPqvN/hfvjoy9R /W2vbIHeJCtsqo2AGZX1RO9ZWzgYXrCNC9uPZpyu0swOPB+yhfq/w/XpZuW8 pqA9lMcfEedoxvmQdPq1U4MDMFI4Utlwfx42NX5hFEICF7PzmVO4/7dM703V SydBXOfF/j48H5RFDPtqvyDBEoe+fj2eH0KeeUupzpHg2p1Py7HFBPCwxefJ 2DvB4uxvY7aHuB91tybvUHaGty2Dju33CXhvpOHdvu4CG3ZeaOEWAS8nGfVb OF1hx2ZfakEU7v+hPRJNR1zhNsf3Z1Y3cb6Uk8arPV1Bp+J9f+V1nA8sYXbF n12B/e9ateM1vL9dtbrRtW6wpifr7uxPANI/KqZ99SwIKEVGitnh/lTSqITu nAWDqoD6Ehu8PiYDU4WKs3DQV9VJ9vS/+uscIjl9Fszj5acOW+J4n0ruZbH2 AFurvzQixgS80JoNHZQ7Bz2j/7XVaeB4q+QOesycByM5knSzBAEpsjtj4mx8 wIA6JKqzQIXVqJULUhd9IDq3dCKWiufV4RHbjngfYBrjceqao8KhhJfSzI0+ UGaeHW80TYXuGcfuWDFfSHZRfKM+SgXWwgrO2J++4O2tyDnXRwUdFmnz5hY/ qD24q8Qcz89vb/SMNJH8QdHywbuYQCrcsm1jpfkUAGuKhR9/fJsHe6mcEk6u IBCf4Pchqc+D5A9CdeBkCAyx3W5WSZ+Duuy5sf6qMAg/9lx6o28Wnoq4rlld iQB7bc1Ky92zMOH9KG7sWCQ4S1ReeqI4A/nyX8y+Dt6AuquSY/qe0zAcYHDn sV8U3O7wiBF8MAVXpdJGOaWjQXHid4p63XfIO9PmutgWAw2S3/zez0yC1PYB wis2Dga+3+v7yDgJhyX2r9RoJEDxelyq3aEJaHxnLX/5ayIsRaT/8j83Dh+9 j9R7GCaDrXVl3dKdMbj7Um7dgC8FJATERqiDo5CmbLLCM50CtL89upSFRqFx Y2hFoSUVmHlC7la4jEDFVZu0BHIaXNscoBhUUYCvcnFELD0NLgwUdDlUUiCa Gneo8X4aGIUJK/hW4PugU0PXYl4ajK0bRKWVUmCHjjDD6WdpAPnr9KM5FHBn nw8Rep8G/5W9fXgnhgL7isPdX9GTwXPI0PuMHb5/jnJXmjCTofDZBZ6w0xRY 3PecboaFDIyJX07mWFKgNXEih3cvGXzLUjnHjSlw+ZLe5wgRMhhadhVe0KJA N+wxMVAnQ/SluMu4IIBSUFnWhBYZkl+eYuySpEBhhfZ86CkytAn58SyLU+Ca aFDsM2MyMJjQVekKUUCSebh57xn83MOWsryXAre1Anc/dSKD1+NYd2F8P6YJ ZXXWdSODTbKMpwkbBQYXNP5e9SKDnl0XUcJMAQ3JL4YcfmTQle/w/cRAgXKX gMzyi2TIvKPiw7idAtwPWGZ1Asngmikyq0BHgf+7v8P/39//B5T5LbQ= "]]}, Annotation[#, "Charting`Private`Tag$2743#1"]& ], TagBox[ {RGBColor[0.880722, 0.611041, 0.142051], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJw123dcze/7B/CEokRKO2lLaSJKXA3SknYptBCloXXaqc45Tc1DIVQihWS0 x90emqTI6NOifd4tLeF793j8fn95PB+n4dzv677u63VXIg7uJpcYGRgYrDYy MKz/S+7NURkMoKFfr3VmH9wthV3fy2ZySTTkWPBO/3BhKWQPt+d4etNQsdut a/TOUqifmefa5EZDHc5+tNLNZbCZVX1O0p6GdH5axzd5lgEVPuddO0VDH2+H Hxg2KYfIp1sElzlpSPQ7c9G+/ZXA+1Kgu5qdhjh5zA790KuEp4VyMdFsNPRl G9Wh/molNNeaLfMz09CzOA43ek4lbPme8fHYagpaEPv+85dEFUTtVLkZMZCC ZkXprUtSCGICrv7d/iIFUfcGh/15XA2KH519knNTUN7HwBgorYbPstemuJ6k oJUDwe132qph76DbF8GHKejAlUm/1PlqqD/lXSSdlIJKW3e+LNOsgX+7Qt20 fVKQS+9X1fIfNeD9ktYffCwF2ev6coVCHQhuvW2+QTUFqUrb822yqIM6h9Q2 snIKimMt1nx8rQ44uO+WxcqnoJuTB6LV7tbBy6CHt++IpKDr7eoRtYt1MKGb Z1i4OQX9OKx/TrewHmxHUNVUezL6s/XblLxuI2yzNbd59i4ZPRn9XV5u3wgl fRNLV5uSkVFZWJNjQCOwd3IpjlYnoxwb8uatzxuhttTl0eCbZES+mHj0GXsT iCfwRPXeSUZv1PtoTv81wZiKu3H1pWQkfi9mKiqlBWhvN9FDHJJR4oBVbffL FlCXvxtzzDYZHatkcj7e1gJ3xBvqyqySUauGf6bX5negt0NAuVA/GbGd8e+y 838Hz0ca+fMUk5Hu194dtk6t4JEgNJLyJwmJK1NiXp5rh71J5X0Oq0lIw0uq LTKoHfqTrToVl5LQXNTA77D0djh9O7mscyYJTYq8i/72rR2k7zMlsY4kIUHO NW5Z2w4YyaMfi3iHP//vgqmxcyecbaxK9UxNQo9rjos9bu8C9mabmxq0JLT/ isTxpv+6oLllOZw9KQm55QdX/57tAuV2Jbf8mCT0+8J/Yunc72HXxycnJoKT 0Fu5AwHldu+hYzB+1v5iErphpvw8aPk9aP65oG+smISeMPCjE8rdwG4ywfBV NgmlnnLrCDfohv+e+BRdlE5CM6RDZZ8cuiHIKE7ETywJmY4sazUmdEPRo9Kl B1xJ6PS/S9+KJrpBWm9X9tRKImJyZpWazP4IHKkta5G1iWhP5LP4UuleGFY4 mF9lmogm+B/oZgX2QdET0+gIo0QkMfj8TfWtPogR9LqoczoRPfMyvDT3sg8U trzm/6CdiDQ43J0TRvog5D/5yB8qiahxmM8n3/AL8MfL2G0TTkSJhT07vCS/ QlbvSfG3nxPQp+n50FvD3yBUX2xqYmsCCmHP2e98agB6qpm9SnRvolPxH3/U RY3Ay/KXwa+TYhHNK8U249EYZN9nfKUTG4skA1wZNr4eg7uh5iP95Fj0N+16 r031GJC1fuux+sUi+me2POLbGJxt1ea9eCEW6UXdeJ3ONQ4bv35/zSUTi16O PPs9Rx4Hy1XWMb/6GDTHcna1y3oCDL5dENhRFYPs+W7T65wmQLPqleHj4hiU IClWles9AfvDLQvf58WglRhe2un4CdjA8ihcOikG1cQFvZivnoBnfKq7v52P QX/vkHbliE3CvyNXTGApGiWeeKcg2T8JojWpm/VnopGaUu6e4xOToK3bVGIx Ho1yoy+May1OQvxZyT1uX6PR5q6ld7zbp0AwYGQyHUWjcyLTO36qTYFquR1l NTIazVr1XWRMnYILWolHmMKiUe+VFenZzCkIb0WTOwOiUZDBnqW251PQ8lXI ZN+1aBTKvydIv3YKrNa+CVkZRaPTcT0GjlNT4HvsbEkhbzTaskdGZFltGu42 RLnU7IxG9YPuPW+0p6HqdIlQO0s04vYyljtnNA2bL/BQRtaiEBfLar2n4zTQ QnqMOQejEH3yrW1x1DS8RsaTHrlR6IL9aNCDzmmY1tAT2q8ahR7k3TP/bUgH /m1ZgvkHohC72QR3tzkddHpX+BVko9Cy19Erd8/RIds5l+egcBRqUTT4tnSV DtYpW3aqMUUhNwMNRiKCDo0jjRsNPkSiN/2+Pb1v6bCQL8TY0RqJdim/2/S8 jA4i/r4MRg2R6IuaxOXr1XQIYpP8Y1oSiQ7/F0a0tdJBSZmyaPMgEv30Sw9q HqTDw0itcRfnSLREzt37nYWANuN7o9OOkah2swOtfAcBqwLzP9zPRyKXj7Hb YncRYFGQNeRlFIn80xnP/dlNwLa+Dd8ClSPRfSERaUUFAvykqztiGSNR/Ua9 u8PGBDxZ4GlnW6Mi77QGhS/mBHRXubcm/KKiRc+oT7VnCZAz3dOcMkZFyTUD 95ztCRgJDKm510FF7Q8vzHB5EGDcrvb22V0qOmk892QyhgDa40cXDWlUJGQU wrF2k4DPwSxcszepSE2zR5EhiQA7uc8+ymFUFOVZ0T18mwC3BK/DNU5UVHVg 60P+LAJeO30ZdbSnIg+/bY/eZRPwCzTSmGyoSNNfecoth4Cgme0r+oZUFHC/ IZX2nIBY47yy3oNURLotYGNRREDHvp0u/nJU9CZNLiGvhAAORj8BQSkqEudQ uD9fRsDd1yeD7AWo6NpbieSLiICnnIPHpjZQ0Si8IeqaCJiaPEWP/01BGfnt jDUtBMjX5z9Q/EVBNNNx6ptWAoq8g/75jlGQiQyvnH8nAQ09PDUbOilIagMf W3QvAVvyQ65nN1OQd29dxYHPBBhQf4icqqWgjzWVPh/7CPio/CY8rpCCSN9/ nFn+RsBQquEJnnQKmtimUN46RICkR+FC6S0Kiky1b5UaIeCqjuDjcwkUlNPl ERz0g4CZ5fHNWeHYumacW8YI+HeW0rT/KgU95E7ifz1FgKbSFKnTgYJ2G8gY Nk4TQGUxlfI8R0G2XCnl7+kEbC8Xji4+Q0H88lcTOmYIMEmJVLHWpaCo87cF qmcJuOVCH1/TpKBGfVbZ3DkCBAUr9DSVKUjw70YZhwX8/BZEf4/IU5DA8JZj Sr8IeNQW/SxyHwVVV9jvWcWWDrbc1i5IQem3Xz28voSfr3lVhTs3BQWyjzuI LOPnKyvhysFOQYt2s+ot2Cr9c+2WG/H6fI1I3bBKwPNzyn/d18hIvXdR4gG2 0Fd/uahfZBR0t6tG8TcBiWcrL2TQyeh8V3B4BTbjZ4aEklEyurv1UujxNQK8 LU6grgEyUrH73FmM/fNjJDHWR0YJ73ljpf4QYGXaumdDNxmZ6Vs2J2K/e7/d iK+NjJKuv3kwg61mZHJDsYGMNMuPSOj8JSC/41aBbhUZ1XUMe6ZiC5/uG7Av JqOBprsP+rGTWwV3BhSQUR+3Etr9j4BNenYayblklFrsNmmG7dv86HpeFhkZ jKyqkLHHtEcza++RUY/b9Zpn2NYN0h++0MioiNUqrRW7TcuNcf4mGeUNCfQM Yx+vfaXEGklGehwC8QvYBeq/HMRukJGzQVrfH2xRdCTlqD8ZHaxpav+HTTsW VGfqSUb1dypvrGIzVaB5Fxcy4nIM3ULH9lPdKE6+SEa8OisBX7AnS7TN0s+T UeMiAx1hXzgcQ35rQUbdAaakB9hdhe1v286QkVT6nf2+2JoHd/4Y0SGjwHw7 sVPYb1+bcf3RIKOtm0Wu78SWVEw7yXWUjBbkD8v04PVJe/nVR/YgGb0nT15O xmaR2/PkpCwZXeN0VtHFDnru0Htekow4NZqKV/D606WfMPnuIaN8zr+Lj7Dt cseV43nJqOn8LKsO9oknHqlVLGTUrMzJEoKfb5H426bejWSkqxEuyI4t9Whp ib4WgXgKDlqm4/rYlhFitYeIQFenq24/wvUUIlQbdXgsAu26t7VeCHsmfXPp mcEIFP7Hy5m2gvfnnTi+G90RyD3d0dMd1+f9lLtfBooj0M+Iwts/cX2zc/Sz rBREoO9VbYWHscMTRY7uzItAzCXPJyLw/rh88+k9jfQIlM20Nsg2j/tnZNG5 rBsR6G10LPcEQUBVwId+R1388bmvi7rx/lU9etx6TjMCcehucCJG8fv5ndtz Qy0CdTGKtDNj5weFtd2Xj0CeN1bn5PD+fxCiUPaJC///CeN9VoMEBIfH39If CkdXjp3jE8X9RS1Gz+BAYDg6yq+gTm8koESvqKnGOxw9crRSLWsg4CCrqJaR WziK/6MfRq4nYH/cioqrfTgSoTwV3VWL93v80705p8KRmIvJhHAlAb+TmDYK 7ApHKmvF/1ZeE1B2p7aU8UUY6ro5HzZ7n4CLDKyFTE/CUHOb/4OQdAJ2OJkW sDwMQ52MlodY7+HXD4484UgKQ317jf+KphHA1rmZJuoThm7LNO43TMbPd5Ou m+axMHTHU1QknUoAs3unaHj7DXSYPU7P2h33ix4eIWrjDcQ4KC834UrAOTU7 vhh0A42feFkRcA3vh62zO5Jf3UB/zCZW7l/F+ymb40/mrRuoUGhnx7QjAS/6 zD/VnL+BJmVDzpZaEZATVcKz8Vsoeq2h5yWvhevF08nToCMUZfmkhIxp4PPA hrv9VnUoolbMr2apE5An5x0u9TgUybjsshE8jp/HR/np026hKCm8QUNEBT8v 4ZzaNIZQFG2QV0KSJ+Awi8XuobkQ5BKtyKYnh9d/fpOfzI8QJGebJCAki9ev 0UG2qiUEmYx/9GmVJqDymlDacHIIOuhdHHdUkoD6kluuchIhyIz03Nsbn98n s040k3hCUFr4qsRFQQIaY+dFa7aGoJMbhN6ZCxDQfMH4syk9GC3vk1g6zkdA 6yY2Lf/iYMRHXlDex0XAByMyb71uMJIt+1hky0bAwJhn3Vm3IPQ68bnlpX90 3C893ybYByFP/iHuJ3/psLX++uMGsyB0vCmqaewPnkceekQqHg1CJbeYGb3X 6EAxd9PfuiUIGZwRXstcoYN07dXuksxAVPvvzdS5BTpUyV+tp9MCke/msycq 5+lgev9KoXhUIKpzOXl/D3aQn1NqolsgQmm95hOzdOiQu2Rz5WggOsXsu5BK 0MHrnt0wT08AShkOvGg2SYctW+0+nm4OQE7KnLw9E3RI97VtiCgPQN+SDvVY YjcaX8ghMgOQlZuKq+M4HXi3nHNpcgtAyh0U/pRROjz3sTn3xz4AvU5bEBbH 1hi2Pn3APAAFZwQoFf+kg3PVWfmHRwPQoBUPafgHHSq8Led9t+Dv/1A50myE DkZDFiPPf/sjZa4Do7+G6fDjjEXPEN0fOTUfNrmDvV3GvNiwxx99yh/W+TlE B/tBk0DJLH9k/H7L2zQ8vy0amlw7d8sfOXY1O+lhx1QYn0+O8kcSw//E/w7Q 4W2qEfx180cTrzPKXLCZDA039h71R3LaP3Rs/6PDMjPzwqKsP1IP+sktiD1e g0Z4hP3R5rR67a/9dGg7pNh4dpM/ElZ93GKHXUWMFwUs+qHUeRuBvdgvc7Ny 7o35oVpJqzbiOx2Sd++K/t7mh+T9lXWjsMmf2vz/Vvmh6LM0TitsnySK855X fkhnv7SqNPZl/eM26o/8EGlIrOLvNzpYbV7St7/lhwIcc9J6sPXQS7XwSD8k vNbRkY991P+K7CN/P8RBeXs+Bltoum/7j/N+iBY3HqaDzZ6T/G+zkR9SFtXm ksHeYK8/I6nph5zMvP7swJ7j3zR46qAf2nTrisrSVzqMfKx4f0XSDykFcDQP YPfG+9RG8/qhDX8sn7ZhN+nIvclj8UNBMrv7yrBLGEcfta6RkEvKkbPPsPMq HtKm6CQkuhK+98HX9fqxorANkvB83KSZgn1TYaevXDcJSR/uyI3BDplouXym gYSyT5y1IWN7ZIdbehST0NVocYsb2A4Xjuok5ZLQG5bhtBBsU96FI6/vkdCP q9qiodgnPjzf132ThDzrFmfCsJXjLvEvhJJQOMvtjZHYUtpCrFyeJFSgU2cV j83H8On3oYskNMDBSaRis5QlTFlYkBC/PV/DI+w1L53vJB0SShW37XuFTZfd 0JGmSkIKYteka7H/Gy2tKt1PQrHzqOgjdlem58svQiQkxdYdNI5dayOT8Zud hNiqBQMZ8Pq+5RpJFNxIQhY2LAV82I8708OO/fJFNPPN/Iewb0ebe14Y9UWn HlwvNsGO0truGNrni/6Lekn1xA7402ia0eqLyjl2UWnYLsWhJ2oqfZHG7qU3 JdiGMrMSG7N8UaWIE40Z14/6j1xucZovit98Q0sJW/GhA/NJqi86uleB3xZ7 F+fHMaqzL9INUjiMsJna4/pyzvkiySM//Oewl6gn3zUb+iJX+tK39Xr+slr0 jOWAL3pORWtp6/X/1j1dRsIXlS4UFH7ErnSTumnA44u4ubwjOfB+yRi64xb/ 2wcJv3/jSsN2ehekyFHvgy7tbmR7hffbtS3Ukj3FPmhb1heFZWxP7QSQzfNB e8Xa+TTwfg2qzTytk+iDPO/EKH/GTixrvBpyzgctpB93EcD7/9Zy50zsGR90 z0/tpgf2XeU+0h1NH4QWDzk1YT9+PUl5K+WDOkOmjgbgflKWx541seCNOBgs Dy3gfoPG+PYtj3qj+H/qIxa4H9VLihVs/uqN+Ks91MqxO7MOVQnXeCOldPbB KNy/Ru5af7G46Y06eG82HMb9bntsNkedhDd6qNqsNTRFB86WF3e6eL1Rr5H3 /QvTuB8yFwv3s3ojSVRx4xu2WESL3MqsF3oW3f31G50ORwLpevJVXijii2su MYPr2+VIxD0LL4ROGtbb/KJDoX7bvFekJ8r22Rd1HJ8XvL3xAdf8PZFQzSHu RewAO+MNl1w8UeOBt0IvGfC86tO73eKMJ0pN+p0swYjPqwcD+47weCL9qIo3 YptxHpxdsF17ch0R/zVKOLDi/Jq6u43c6IGyJ7+/e8+L58Hm7zoyrG6ouv6O dYMynh+5Hgo9JFyRTpBMTeVhAgod7BY4PrqiqsG+d0VH8Ly4NvRwNd0V8YgE l+Wp4nlCcWyxRc4VGe/nfXkHn9cn7s5lXzG5hq7L5LAlaeN58Brzhid3nNHp a7zRHRYEpO9QLBWWckKygvb+rSR8Pl5MKXfd7oTSud3ZavwIEC/7VVm2cBmx 94X4FfnjfHKxrNas5jISWZZqyQgkoLxUqy3K+jKyPUVi9Qol4IujxX8zcZdQ jGhDO2skAXwlgZtrZh3RkWs3z6zdwvMLWz/z9s+OSKPLqW4U598MB3UWmypH dOyFT8WHVDyPsG3e8SvGEZV16x/MuUPAEYd43n3ijgj93rKoi+ctq22ZMkkW Dki7Zn+GN87Ht+0aje3L7ZA3Z3j/aTyf0QzvmZIf2qGOrCPOh9/gfKLmYZ4T YYeOxRpvE35LwE1e/rPT+nboVrdqFL0Q59XMr9VzJbYoM7ljx41SnO9vSPeL /j6PVmh/6J7VeP5Vb+aNCLVG+4t3SlLa8fMQ9BRsOWWN3Dg0Dhl04O+3LCC8 g90aRV6f38yB83Bcgfveexln0amiI0N3uggIEOZRflNjhU4X3dK6202ABcNl 0+GNlshoMjDTBs+r26s3xmtFmaIfTT+c3g/j9/ecmDhqZoq86Ow7HHD+zUr7 euqgsCmqMHG7OIt9+PqbDRIlJsgy+Dnntp/4eYs6+jCNGaN872vWiniefkOu PddyygiNeFVpq+I8/Ncjv7SG0wh1vZEXLcROLDso643OIEqUzC05nI9LXUYy zAlDNF+fqrYb5+NtHVpRvGdOow4lLrdxPK+/Sma0fLBdD+n1Nhiq4Xle2+UL e8ITXfSz9jx7BvYXrdfvQo/roorjzywY8fy/6Zf9cXs3HbRjVMW1FtvCskZC vEMbCbdNPVZYxHlL/s5/uy5ro0Oj7R5R2De2XL+z+e9JlHE5sKQfO7dUmG1U 9iQankooo+L8vCZwYyH3phY6sXPOox7nkcQFy/y7Eloo9tDFrew4r0i0y1+J rdREQXEVPNbYhiH/fb02rYEmdZhSxrEzB47XyZ9WR2F50/RfOO+4eMquqr8D VE8NETmE8xFN7Lur6Opx9IFLpN4Te5SiZv7j7DHkz/LPYhw7Tu+3mAufKioV f59Zh/MVqSquz+G0Ckoy/a7zC9tBSSjBOuwIOv593lkC57Mj/BqruuPKqFFa XygMWyz+w0uN3cqIrT89/zn2dsaLl1SMDyHDJZ6SXuyRcWqXVOkBtHzvy0FJ nAc7z/NShaeVUM6gcY4+dtn73KO8IkpoNcIkyR07sbTtCXO0AqoKDH33GnvR uqLkr7882pW3xvsBu13zPzH6oCyKTXz0ncAO4JBYbXsljX6aH2uWxPnUaPXU pQq+fcjeImMa1vPqkHPXs7C9KEBhR5Ql9lrLzaP3xiVQhr5eqiv2h1cFT2KM xdGfJj6BcOynd7p3BpSKIorxKc5b2CFhi0FXRURQkFdm6JP11z8odb3i2IM8 LFZsi7DNs/yeJA4JIL73km/rsTd4VgW5v+ZF6Wc2Br3HfqGxydQwnAsVfXAv /oZ9dqfePlkTDtT0Q//yT2zW2j3/eE5sR047bkSt5/eL9s+e9QwzozGDX7t/ YVcwHLZKidiAbt5Ml1zP+1LqlK1Z2otVGauXs9bvBwr+HGlQ3TZcxWtpkLR+ P1DB6SCq2t1y3G6Hzvy645mdez/9Io5fYbVq/ovN3bA72aN87bgWEcK+hn1A KyJ9tXITZD9paF3C/vJoiVATYoWPHw+tzmJrMBZlAmKHmVf99yawbyl5tNoR nOB6tKdgEHvcQfpX2B4eiKuTU/mErZYyIvToDD88hC2H1u87Euse6NSH7gaO 3aHZldhz/vtL5yyFYflrSWQ+tmDyVsONMyIQpv6t/z62dt7PIc4oMVhS4cqL xfaorSOJC0uASXDyOAm7fi4486SRFMjJKzTqY9NZbJQtxvZBlU6t4wFsXrEj rZdvyIBLZJgvH/Y107mFyAI56Ki6tTaA66W1cPSEgbgCCPeGeNRiD2hYJJjN KADvuwrrrPX7C+sD4peilGBOhZpyHnvPz0w3V7MDIBPbMHQE+6Ane6mP8EFI OVyTy4F9IWb6NLXkEHwqCM6owfX+qiyHlDN2BDge/VVjw16+Edb4r0EFEo6h 3Z/xfjp+yobL6pEqsL7hOpSJ/a57+5stF9RAjXM/ixz20JQP/Wo3wG+vXnul 9f3blyNkb6UOVc6zLATe38UVu7TZmtShgosyk4v9J5xOu5StATpszt782NE7 spS4bbXgulUz6SfuJ8/ntlvXtmtBninn7lvYXT2BYW5qJ0BjmYNJE5s73byr ke8kPJQ4lHMb96Msqa1upI/a4BdwRksG96syDY/cz7p6ILCD2s+I++F38e9d 5BI9OHP3nubtOQIYtugtK+zVB16Rb2t7sbU7xE5FbzIAQ7q8v/YsAd3Wn0ZU 0GngbKYWu+N+u6iyJ/H0XSMYZk2I954kIOpZz6NH741g+VDYv+kJfJ7ujite 2WIMMnGK/Zew1RhW+h+TjIHp1flJo3ECwhs/yP41M4HTzBNeu0ZxvzGltubv MIOOjPQGkyECjN+uUky0zOCzm1lM1SBePy539UVfMyhZPL91HzbfZ8vCY/1m cDX7ldrqf/j8P7/vYdtzc/idwfL45ncCVJ3aPCd0LQGxMUz7fybgUiAHvyTZ Gkr/FUd64/Px6Tfqx5Zia2C6ZvdfWRsBE8d+x7tOWsMl79p9DNgeDCMbC01s IOtQ7IPId7g/UQqntUTOgUtAJcQ04f2QYFVjX3UeWIIVJe1qCOg3PvPWMMgO ovLvqZ7H53fjOHeyXpodcCmlfPTC5/uLsH537bd2kLNhb3g0Pv+DXrnKHJ+y A8Y7JWKvCwjg3xmXJXvOHuQOR3xYfo7Po67mxG1qDnA6epp04TEBHYaaru9+ O8KDYEXVDDyfIP1DktqBTjDeNrz40puAJHm26NizbhAeN3uE6SCuV+rSdRkv N+gr3xkpcgCfv/2D1q1xbvApvcP9mBIBCjeL9rNWu4HJ57sCJAVcTxO2XTGS 7sD85abE3H4C2J+85omZd4ffAyq6WyUJOLV9v2l9oweILWh2t+P5b1Ul8xSt 2wOGTHhJG7DzL3GrXRzwgLNqNGZlHlyPlQwSm1Y94LiEz3ImFwE/XXoWtWSv wzNRW1sKBwHUlpC7dSnX4bCw0NWgbQQ0kN8P1tp5goJGoKXaBtxPLt7szXHz BPeqc6sReF711tJtjQvyBIl0+e3teJ4VZax5a5HmCeemzGmOf3EeDC2InOj0 hHab9y5Zv3GeC0iQ5QAv0JyNa7q6iPPjWX3RJQMv+FAq8KEFz8sjR5h5vll7 gU3EtkAZ7OSlEIYnvl5QYrLxzfw8zm/ebt0q+V5w4qYWc9osHZ64n/a33+0N A2tbbivh+fyP4VY3bRlvGPni1/wCz/Nmcg0OMireIJl0p04am3FazeCXmTd0 ljELSU/S4YLz/j3Rcd6gkRmeexzngULdMU63u96wyyDEqXmMDtv2ZW8xfeoN rBf/bDDDLhsVmBOs94YXF2V6PXCe4L7E2lDw2xvenfx8rAbnEdcTTaW3tvrA tTeZotbY9WIR+QE8PrD9YdviAs4vnkOrqScO+MD93Xa+CtgdthPOn519QL3j xk40RAcJeGJb6ecDIek2BU7YQUIOZllUH5hMv2LEgS39ve/YtSwfGLz6LN0V 56lI6xZ2hi8+MHd4LkMN5693hQfdl3/6gGTamtwqzmvbd2a0z8z7gMHnpzGl 2LQm35hBNl/wGHB9dQz7s+jQWB+/Lzix1oQyYguEnD71Ya8vJDjuE23BeTDr oPimOg1foAVQx22wfyQkOJQb+kJcyu2dUthSk6vVb2x8ofzPPOcizpsvM98H Z/v4wuMvT16kYs+tqX1LD/eFK0PLp1ywla2eqt5K8IXM1eRadeyK7aFLlFxf SHS/fmEW518G5wnzkCJfODudHN6GrdVg/ta3zhdkD5fG5WJThWs43Lt84XiI TkgU9rvA/dedvvvC99Qsq6vYbJ9SO20nfIEhRHy3AbaR0kY5qyVfMPOTaFfA /jTWN6GzkwQiNgsL/3C+5z9xUldDiARut2zdJ7AvPCzIUZEhAUhEfOnFzlwV YFI6QgI24UeHG9bvU8wjL0qfJEFv7Z/IwvX7iFdztaImJOAc6mzLwXbZdkFE wJYE9lyGzOnY+U4toZzXSOC+8fmRZOy52oP9rP4kOFXK7bB+X3JIKENtE5UE xoNF5PX7Ej9/1ntrySQ4VvI6c/2+pOKj78rCQxLoKO0rW78v+Sc/ZDn9nATj pw91rlsz9nTRj1ISBM3PDK5/PPVnya7+RhI8qHCeX/96LRriXr3dJFixf7Mp Fnvb/YT3HQMkOF78nnv9/sZoeVW+aZoEr4LbpO9jp5hejkerJDh3N1Mjd/2+ KP/9VDGzH2xZ1jtXvL5eLMf0C3b5wTIdBTZhn7/0NPepiB8MVM5m9GFnVHNu yZTzA5O01rbp9fUSCL1856gflI4fYNiE138vaaI+SccPBC5tVxPEdv5gLhZj 7gdhKUfClLHzZWvCwh38wEsiumv9/mQ2av9AgLsfJOV8lL6OfXAk9bhXkB9c Cx5NTML2g433XaL9ILsyduNb7PK7br8db/tBV2pExGdsTeOTJWYFfrBB6HL+ XlxvlOcF3Kcr/eBPUYW1CXYzs6DPyXd+oKeiwROKfaZqTlF5xA/+VnnV9WOf k8l4xsPrD371T1aKcL17OU8/7hD3B//64S2z2DG5qhkURX/QeaXEK4v3T+ne Htq8nj+Y+fYdeYbNLc4S0hnsD+VqPTcR3p+yjpZ+1Bh/EKeZ527F+/dEVrbn sVR/EPr1r8kc20sYnJ4V+EP40syOBewuQW+jyGF/sPuw6b3OMB1GbWr0js/4 Q5TDi22PsP/e3X7y15o/SH5ROP0PW5YvV8WROwAmtyp/r8T9JYarXxR0A2B2 Z4+q6U+8n7br/FrMDwAxu4Af/bjfWZ++RbwoDwBVt363sxO4P8UNjV9sDgCF gE1r6/fFGSzB/R8GA0Db0Vu4B/fLNabXTfm7AoFtu2vUJO63Rf8E7l4OCATb iFpPvzk6tB+/StsdGQiWHoxbOHG/Hgkuiv+YEgg6cZZ3XmJzrhlFaL4IhNNn r7ygL9DBY5lyTWggECp3qVLIS7i/zRLHe08GwWLxisz2P/jzhyNUskyDwET6 3+bP2A96eQ662QeB6wRJPBufL5wVsI8pOAiuySRLaeHzaI2awKn8NgiuVHvs Sd+Iz2dB+bFbosHgpBqmWMJCgJeOW5L5v2Agd7/Pi+YnQO4oY5wIWwgczrKT TRMgYEz2NnWaPwSsBQ4+eypIwDnOqkCKcgjYJW6K6xTC81c/2+VC1xA4qZFM PSiG52HvF6pc30IgROeHkRU+nyseTg1/LAmFb+avaZOA8912BZ23DaFgc1TY RFCDgK3BXs9TPoRCrmqSpaEmniesV71NpkJB/1vOvqITBPixbNo4tuMG+FX8 vU7TJYCjYSftktYN8A3Kehhpis97Vdkiu7wbwM6h2ytxBecT8YurFn5hsLbY +nglmYCeQ7n7jUPDwDBdvc2NhucBbfoFfWoYVJpo5w7j+UTrql8d0MKge/fj c21pBPS+iIuTKggDfRGZgLQHeN5VLhRaHQ2DEdXuup15BOjpMmndtwyH2ena 0IPVBLhb6/ukXgiH1DrPqWg8X9FcEnOSLoVD9tqvyO+1eN66yb+N6hUOlQvM nKENBFz/INfjlhAO7fGXR3PxvJZmY+mk3hQOjS/+piZ9XP/5Tfod1Y5w2HCv iauuB8/nwYOtB3vCIWJm9MNsLwEyGS4K+4bDgSdSulW7j4CqkdCVnf/CQeru 36k2PE/+cH0aO6wcAUO8YzZHf+J5+ViDp9OxCDAOPG8nhedX/m1DZye1IuDv HvFdHGM4v+YJSM0bRUBhpNmZr3jerfgZX8/oEgF5AQYkrWkCPhU+e0a9HgHP x76e3UXHeYrcnMziFwEaFd3eg9hSYoz2HJQI2CLRy+0xg9+/rc8fkYcRMJzJ bn0ez+8v5ZJHHj+OgA0tXme2L+D88Se/dd/zCAi9ksVQjs2QPnZHsTQCHkw6 WTDj+V/AZXNYIYoAZv+mL0+wlVVFr6g0RkDx+5gvGjgvXPtso6zRHQH7Xn5i ccZ5IjLHb3dDXwTIjgXwL2Fn+d7apDsQAd93FzmGrhDweVfnB6PpCDi1eNgu DOeV+eHJ0o/zEXCNPDm7io3TUKbVagS0PeMIcMf554SxprsdMxluZD/ep4vz ka2wrcUIGxm+/u6Ry8cOIAKPXdlFBsXiDT/X89atqjTxKX4y9FJ6jl3BLrhZ yOohQoYDCRPildit5z7Mze8lQ7xPffQ2nN9+yhB9JDkySJzutbbA3vCbteb3 QTI8pgZR72ILvpN6GnqUDJky/1Y/Yx++czJhoyYZXtQmP1n/ebjJFQffSB0y rAjakE5gux4OPc96hgx7VRxsrmNHMaWfSDAng/+fbPU07Ec9JTKc58iwxL+N qxS7KruHI9WBDNJfnBu7sfu85lb4r5LhmRBZcwx7QXPH4AN3MvyZYyItYu/g 2N8s6kuGRwWJxut5XnpQ5+WTIDJ4qr5E63n/ZMGl29IRZPhk2Zu/fl9gFxoe nB+NX5fw3kZgBxo+vKiUSIbgsL6G9fuI27sr9Ituk2HT/TPNddivpj4rqd4n g58oy4bs9d9XKP/FV/WIDNdlpM8HY4/GcGzQzCPD1rONLWewGa3lxxoKyJCv 1H9AAHv3PoNO3WIyKKddjvoPr9eR5StF7ZVk6L6r9TYd27SJct+4ngyFHiez TbDdbmeRe96R4crjgyc3YD86+M3k+ycymPA/NFj/fYCnv8Yj1fvJ0DmfmzOE n/fzoqWKRyNkiPSVeO2z/vsBRzj3Os+S4YPzp1gKrpfyFeFz7UtkoIaJKjNi V5fJJSn8JUO6Dqs2CdfXOzW934ssFNiiZWugh+ux84+lgvVOCrQ1UnY/xfX6 serSpUoeCnQNVmz9i+u7Xz2sM0KcAhPdtmNJuP7nTpQ8Yj9OgWefHF9a4v20 tLnxs9cJCkjn6eh54/y71tjN9kmPAvmxhlejcP5l0iVI9y0pQHZ9Onob519W lj/PGS5QoNblP+EkvF/ZW1mGHC9SwPgkQ3I43t98pyUNpK9ToLDFv1MP52Oh 7QfDbpIoMH2a4iOC87Bop0bRTDAFDKq+MxG4X+w3Pi9cHEMBj8O5D9xwf1E3 py1oZVNA/jx/1J8BXA/cWfty8igguaToFo3zrt6nlxdYXlHg1ZnMx6z9BJid bW3uqqRAd+OV8rkvBFw5z3j//CcK/D3w4LIu7n+uQuwfqr9T4PB0XDnlAwGe /+1mFh+hwJv6O03FXTiP2qtcn5jB71eGpWQN59+ESx4nSSxU6FPnG2DG/ZUm GRLwhZ0KC1vfdhO4/6aNxr48xkMFKe6+kTbcr7Ou5vBtEqeC/vRVzssV+Hm6 9k8nHqPClbymOA6cf/t9DG7neVChv2jLVS3c/98mBuunkagg8XPngPI9AmKf 5TNQQ6gwfKdIXBCfF0cG2V3s46hwmE+0tDyJgGSDHuB9SoWRs/0RBmT8/pyY fm1+SYUkhoRvrTcIgPDDefOFVDh2n1FPLZiAqeI7uzrrqGB8tHPLjA9eP7EL 45T/qOAUr5KdcRn3g+MJD7x+UqH4lZfCEwdcD1bVpvbTVBDl/Lcn/QIBD+JF q9R+U+Gb+vIHKwucp1d+Js9zR8LDB1eVOU/i+u1yV7M3jIRTKwIz/nsICJ/M mDU0jwTKu0+zgfi8P8v04YnauUiY9zjG4YrzL5PawZ28zpHwb/DeRUFWvJ9z ln90UCIh3f+FyQucP3eFhCWoVUaC6y1XhegmOkykvT4hXR8JK4qD37xr6FDz ZniFpzUS9lzyumNYTge38ZMX5z9HQjaf/Za2fDxfmrGo5C1EAtcfpDRNo0Og TMoQz/4o4LRavFB5ng46m9INEpSi4PHLgdJ/Fvj7fc8uYlKJgkUxSpOiEZ6H 44tifp2MgiNhVl8vatJhYLZPqds2CgYmbbmZJPH8WCIcEZ8SBSQNm5PyE9Ow /WS+2ObfUcBwlLvm76Vp+LK7+GbQhmhQCTa3kj0/DTmLaGmeORp6mEbk9M2m Qf3p+9ahXdFwYqLvoZnmNHix/vKqlosG0bXCtge7p+Hz+6P1gQ7RcLRjhybn +ynIutByca4lGt5wL6U9lpkC9aRfhgtd0UDIsUZ+3TMF/XUiKoufomG4eRD9 5ZwC/n0BbKs/okH3koQR29okpMxLF21gjIGHGQdKDVongRwVx7xTNQYybPmy Ll6ehMuvz+TJ58WAK8rZnZgwATJMvcS1mFh4dny/HPFmDN5Kz+81TIqFxx77 C8Oyx0DtDLudfFosfDJe4tl6awwM0vS6Zh/HQqXwLNOSzxhck0YFvjWx0Prf wEvTw2Pw3PDp9RvLsVCruWlJsWQU5FID5lMux0HrnNXTtDc/QVFqz1KZ5k14 PCK4c/PdEahusjzo+z0egnmEPLYVDAD7Jo9Ml5F4WHlxLDLt4QDYqUdtt5+M h75Q9hiZhAH4V1Iypr8SD9+5giouuw3A8Ty++yJcCRDsejnnoOwAVMR93dxu kAB7XwSYR1n9B6XGtp/EKhKAVnb4U7r9d+hzPVB55XQi3KWcaZvM74M1ZxnD p0aJcF6pc0cqrQ+Eroj9N2qaCIzZl7vMA/rgogPnBifrRDDtk1hj0+6DGYv5 E5ecEiHWKcPIuf8zbFF/02YflggrklJnvnF8hiMcB75ZFyZC6Xy9U39ML9js kHG9W5IIp2YMvFi9eiFkm9jfvvJESH/0fMrAphfqmTiFz9YmAow2KLLt7wWj 33OOlp2J8FWO6UBERw9cGXk9aTqeCI0rUXdP8vRAapHSb4PdSTAZIj/MX9IN +fvFDgQJJ4FC3UwnPOqGxixOl2diSbD/WJO0X3w3LMYvfNkqnQSvdnJzi13q BgunorJG5SR44aq/z56zG7h5VQPUjZLgnu7QsJ/XB7jlr7FyICIJtquppQ1r vIfnhKKiIzUJxOVvql+Vfw/1l0SvJkcngd1708sbdr+HBeONfTMJSaAt4rzx 6nIXmEk3lLxITwK+X7quuwq6YNdXHb+9RUnguat1+YNoF6SoGS3xjyfBRloo 9wmZDjzfmbgnTCXBXAqX56Yt2OFmoxtnkiAik3HH9Eg73G62+jS1mASOjyBB +WE7pJnZF1dtSobsw5WKOVzt8OCaJ8lBOBmYuGZ7hra2QV46bSnXMhmYpfk7 vm1/B8/QbXchm2S4wmujeXmmBZ4PpY0mX0gGofSXvZwfWuCF1P1PgZeSITSh ovfLrRYoePu4+LQXft30nc+uPS1Q2FZEmo1PhsRt7lK8R5qheu3z0pHGZCgS r5nwiGiEir/aep4tybA/sibpt3MjlDAUpj9rSwalx/YLmSaN8HJTkoZQdzKY mvCFaIg2woNturEbB5KhayAzo7m2AYIES4U6VpLBJkhj339bGkBF7c5JR9kU +GzwoMz9aR0cPM6clq6QAgLPzwocS6kDBXWfiZ4DKUA9yNonGlIHUieME3RU U0AhcpzxsFkd8Bps7ZM9lQLi+c4qoRvqYNHG/9qyXQrMbs567mdXC68Dz6bc pKWA8VroBlv5GthdODcomZYClqsj337w10AUPVah+l4KbKr2kYpkqgFb+6r2 uawUSNE9FcvbXw3bToltsXqVAnksX4Y946vhMsd0kGhHClw20Gr7MIpAIPfG 5WJmGhBzHBYMWZVAHeIrNGKlwfRP7q+yoZUwJ/Bm48R2GgR2yDlFnauE5vgf GYLcNLi3pyO3jqcSfL31voaJ00DABwINEisAV5CRgQZ+Pe2zok90ORz1f/Hg xwkaLLZW7rW6Wg5PXmtPh+jQIKND8/ZF3XIIlvCPeXWGBr84JRhXtpaDNGt/ PfcFGtRf45VkuVkGt06QOAvsaZCzaYFQcisDhhB2B91LNHhJbwuPOFMGn2Y0 /wVeo8Fb/qMK9zjKQFP622kuDxqcf9U1aL9QCvmOPun5XjQwM3aJOdNbCnz3 t0+eIuGv1ye06FhSCv/391bw/39v9T+/FtD4 "]]}, Annotation[#, "Charting`Private`Tag$2743#2"]& ], TagBox[ {RGBColor[0.560181, 0.691569, 0.194885], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUmnk4lF0Yh2VNSpQiSRJliYQk0UMke5YQEYkU2Zeyj22YsS9JiyVrJCFr 5FiyJYlsJbuyzyikj+Q7/uq6rxkz857zPM+5f73vESsnfRtaGhqaRnoamq1/ Q/pyz455JyKhEw4TArvvAcfQm8W8e4moN3bk7EO4B1kTHbmu7omoefN2vK/z PXi3uLSP3jERmV9OY8/+fA8YWBR/HbuRiBoHPoTGpN0HIgzk372UiJglmS5O 63jDftW5G6dVElHnyKGKI2HekKP1j+ufYiLq7ij5bxx5Q7OJQFiMXCJSnGN7 RSvlA4zuzjdLxBJRoM05utHDvhD2fDvPn72JiJhlZWG3zx+4Xh38XMeWiBgk bjj2GfnD8zJxMmlXIiL9STWeSPaH1oYrf7iZElGFu1/2D94A2D6U3qOwloB2 bdO8bXWAAOHsZ6OCRxOQ2i8aDaQQCGTvO/9YXyagsP2W26I7g+FUj51HfF4C uh/QpP13MxgGxO7O78tJQEs8OaGLEiFwfMzxK09aAppQPCnlkhgC7y65l4vE JSAOJHOI1ioUNjkCHFU9ElBpmjn7LFcY5DgSvre5JCA6QbuAUP0w0GkNNNN2 TEA0qoddGyPD4KlPiMYV2wQkJL19TpwuHOTGScesTBLQQXWn/o3VcHB/lTjs p5CALttfFLhBFwE8zEmG2+QSkO61+nABtQhotHr4IUQmAfH360++jIqAPfsf v4k4mYAevVD15DkYCa9805IeHUlAqRzdL4sgCmbV83XKGBLQBZ2wE+wlMRCX +aJJlhZzWNWsLG0syG4UyNf8i0eE5lLVcdFYCCt6JdK4Go+yxinqOYRYEOAs Y+yaiUdSO2uF+STiwGIS1c53xKNZqfs0V57Hw04Lw2sv3sejI4EfFaP74qHy y+zqnZZ49Cpaa1qdIQHYOvedmqqLR7TL96o1rROgoco+c+x1PBrmutmaI5QI AjGc4X2P4tGBHLtXZz48gE/MLwUeJMUjjtVEcT26JPANuVBvkBCPLoke/M50 Lgl6vRzWPkXGIxEVz8YrBUlAtG682x4Qj0z79LSykh7C9FknvTqbeGR+Se/X z4hHkFhKT/G3ikeRiF2kv+MRKJ58TFawiEdzWftofNkewyOBpsY3V+NRvkOO GGvyY9DYfVCmTDMeVWXwrTwqegIFk83c+afi0SkdKbOHzKlw1cKs4rZ4PJqq U96TfzUV6L/+NDguGo+eIbkduc9TwbyTJypLAH/edFClvWYasL5x3UzljEde 0msc53TSwTmGdzJhIw7N87KLlVQ8g+Nx1V+s1uJQmcUco9mPZzAcf7Xz1Goc ipqe/hqzLwO0k+LfdC7GIYaoZy5PPTJAJIUxjmUyDml6N7/0kc+EyXyKQvD7 OBR706vsvx9Z8KQgQkq/JQ6F3bU8zn84G/QLhYSPvItD13fkeC4ZZ0N9sRUH ehuHpn+aGj5qz4bUyr7ZtaI45JifrCFRnQMmzbUPXR/GoWfiXReT3j4HttZr UUqJcUiSieOI5bY8aG37E8QWF4dsu1zp/7uYBzIdko6F5Di0qfU+PqMrDzh6 clRm/eKQ6GvRpCNL+fBxLPrnDes4hORTHK/ceAmhE6JTEjfikJp0QqnV65cg /73126Z5HEq6+B+rE2MhvJimbU0xxtcTc+pYzKtCCKd6pn7RiEPWwnQZgkxF cGHjuqbeqTikXc5YaUMoBjb9WZpBsThUfnI00aG8GEZyPMqtReKQTHEjp9hC MfjqRh65fzQOfTpFNRwyK4HyzKrV1H1xqPr71Viti69BRIMja/6/WNR2p2ig W74M/qSmmXj+jkVfHllxPQ0og5Ylkd00S7Hov1vsihqNZWCdouS9dz4WcR0N m7qhXQ6pi466csOxqKvb98SXuxWw52Hb37CGWBT0nfBpaLAKRueulLCjWMQr bO0cKv4GXimO2j6pjkXGL+/zqge9Aa3Z392FpbFoslXpm5RYNRAVBPJ6c2JR YY9AIV1cDaxN+BsejYhFpBUJwr5EBK2yO1hehsWiXhqWY2ZrCB5GPaiTCYlF NHEbMjSn6kD6TIGohl8scj28s7fqcR04kr9sc3GKRTvv3s6q96yHCQnpwlqD WKRYmfBJ1KARynMMSMG6seja3hfle6IbgczjZq2mHYs2i2NulrQ1gsT2Eu5u 1Vgk+zhvv4DyO/AfORn2/WwsUm6TcWWGJuCOFrXcyReLUt6el8o2awEKnea5 Lp5Y9EzZWndnVgvUe9ntTzoQi27SLQ9rzbfAbZu8D4f3xiIrZc0Qq4BWKJc/ flaKMRadHjdkO1DUBhl9FwVKB2JQwe3sKneFD6DeEPJVoTsGHan9UGOd8AEW XzbGtrTHoGtFfkPasx/gfKjSxtfaGCSqEP5+z5MO+CKl0LctOwadikljfbS9 E9jipMMvu8Sg9J13IkJ2dEGA5tH5WeYYNGaw8FzLvweuDJ3nn6WNQcOPYveq oh4QcTK9OrMejYQsL3z/QdMLPfFx76YWopHr6LEQXmIviHzdfDrZFY1o96Zz WSb3Qc/tb9rDj6KRy/mO9beDAyBCfPCqSzga+b7021fYOwQ0XMXfP/FHo195 1okjwsPQm/fh4KeD0YhzLXhXhP8wEDrowj/uikYKToRjysIj0Mvhatn+Mwqt m5E35pRGgZCpw95UFYXUSpQ5uLPHoLeOya1SPQolGLrvTvSbhDpLyWsDF6IQ wc5A8Gr+JBTQmCv/OReFzpSoROzqn4QgxZK9suJRiPng4rSixHeQqDMrrdgT hWzKQmq8xr5DJCpeKR+MRKWNbZJF8lNw3+LbUF9PJBpw9Ro+ZTsFNzcZm393 RKLI0z3q9+KmQA7MkmTqIpEizTX3C9+nYKqW8Ux5ViTqm7jjEkOahgu11+6X OUQiJtYXlz41zID4daJl761IVJgxaWc6PQMH/hWprVhEIjdq+K3AXbOwqMB4 4LR+JIr192dONZqFlLdFVaUykWh/8oH04YlZCDcffNZzMhJddz335iDjHLhv MJCXhSJRLh3d66njc6ChcM1U+mAkGnw7/+SY3Rz8qWFYf70ZgTxfR/3hmZmD STOJic9/ItApkr3kS6Z56Pxr2r70MwLVhe383SA4DznyRU+kJiOQ21n7cR/L ebhSYyr/ujUC9Q5EsrB/modX1a/8SuIiUOBbaYLHwwXISqEtVouIQN1BSrKZ BQvwOMBwcjgkAuVC0XOr+gUIUV7XYLkfgdTkS9sfziyASbsql/X1CLSb+svx uzQFdF4+0lwzjkA3un9N5KtSQCVm3j9WLwKxlhh7MFylgLhB/PcalQiUmEZw 9vWiAN3gUMk+0Qik7j5DCK2g4OuT+PFCIAJp35pXZWqmACU1+MAF3gjkW7xd QKCHAgNWwgRH9gj0vcWmUZJKgQ4V39f0LBHI7C/r7WN/KdBwrPPHY/oIJLvJ NF25nQovZ921W1bJaHBei1TLR4WMDy0E859kRBJ4Ui91ggrJhdylS7NkZPU6 iVbrDBWCXOu4+YbJKKTxKLOdFhWM11im778jozaxTi5fVypofbt+cHctGQnN Z1gI+1BxPRTrZFeQ0VWD3StBwVQ4EWRc1pVPRuwre35BAhWOWOdP22aR0Zmb Zz5nP6Zif9w4+C+FjCyTfFZqnlFh247MIJE4MtI5VM5I/4oKv+dWyurIZNTf zOgvU0aF+Q61GaMQ/Hu/fFY9XE2FvjjK5eB7ZKSwJ2+aq5kK7W5KwQdcyKjG VFDvRDsV6gwTy1/ZkRHNwl3h9U4qvDggd+ibORmdKslW/zRAhfT1SF1XYzJa 1qY58uUbFZKGRoK365GRrGciMWOUChFIsiJVg4z6LofViU1SgfAsdFZahYzK dTf3+k5RwSN44FC7AhnFj+xoip6lgp2NqN6NM2REp3R/v+0CFSwv+YesSpAR q1OYOuMiFQyFuyqiRMhoNXwtxeEXFTRYBOaOCpBR1JVavdRlKiguePK+OYTZ kObZo99UON3ZpqfLSUYLCtVNln+oIFLME/qDjYyaJZdXl/+jwuEEp0rfHWSk J6LhYLxOBQ6Phrk99Hj/snhMSH+psMN43+G8DRKaTZOaj9igwqbsbX1YJaHr wx1XLP9Rgb/+IYPmIgmZmYYM7N2kgqp6S6XRDAm5XxSgJGC26/ptbzVOQs8f TLOMY442OXbYcZCEFMw5szYxl4wZdnv1kBBdQY4ABXPvndDQ0A4S0j1vuVqI +c/PUtm4ZhK6aRwdqIyZx3ty7ikioZxT7AIv8fcr0nKkPa8koZQ7J84t4N9n TVbWLy0moUUtEi8D5vA9bgx1+SRkJcd15De+vhePMyrbM0lIfYA1rn6NCh/5 u+37n5JQTVt7xW28Hr/ytx2eeEBC5oXtX+ZXqSBXbRm6FkZCdrXczHF4fa8r x8oyBpIQ4WIT8TVe/6B2NMfuTUIiVrdHK/D+tA3y6gvfJaGIScMuu3lcbzd1 GE7bkBCb08+ig3h/2eb9KhWvk1C6uMBGCd7/q3+/8V7VJaHe7mDpR+NU7K87 u2+qk9C75zUwO4Lra6d8qNMFEjLan7cqOESFKZ4nc0RpEjqg/NDzRj8VPBVM Ksu4SKhK1/grHa7Xx03h9vXseH3Pjz1saqFCrXYlb8cOEpK8fCjR6x0VGK5z hk7+DUePJhPLqt9SIdG/V2/vWDg6tXg2DuF+KUF6c8554YjvyqadYzwVFpQ0 eE/IhaODzdbnuoyowL0zg6dQKhzJJyhmOhpQQa3vP24JsXA0W3hwhk2XCll2 eZzSfOGo6YbuBRt1KpgmbGeXZwxHYWXM+wzlqdA82Uyn1R2GtHlrH5COUmG5 kJf2Y3sYGvvs75SI58kRL08a3aYwlHj88Lbnh/B67Dq2YVAZhsavPNuc4aSC pEzo72upYeiRuPTK0E4qpIUpz9jbhSH1QbVfWX8o8EHvydTCzTDUZGLCqP2b AmsHl747mYehbZepc5tLFDAqyhh30w1D5pRtgUQ873Z+2fbNRyYMebATJ7im KCCXafJ142QYSst9m3LgOwVsHYoHAoTDUOYe/jLBCTwPt93oDeYJQx0Gv0Ut RyhwX6TuYwRtGGLvYDawGKBAzjJnx66/RHTLv4+zpo8Cn2ud2mNWiOjUGJkg 0Ls1rw+3JkwTkVUr7WWubgqYHbrXvG+ciHbknK3O/EQB0tTHdw8HicjaWnNA rpMCkz7+9U8+ElFBQrZQ5AcK7FHtQ4daiSj+VcU11XYKAJt4bVo9Ed24owI7 31PgcdbQm8xSInKQXmStbqFAq+PpKsFCInqtUrecief/b9moitxcIvrI7O2f 3EQBvQ750hePiUghXudOViMFErMzrXUSiWipu/p0XQM+H/x27PsZRUT2b/QO TtVTgMfIpSkhjIjUDizvOYDZUnzAQyaQiNZ4VjiM6iiQxQjHvngT0aIz+4FU RIGp4ew+H3ciYnL12/+zlgKOMW5n6m2JqDLDur/iLQVKbL9O3bxBRCkxz4ii mFdAKZnxGn7/r1LG/BoKyHI9V8u7QkRXx89pSWH2XWT9T1OHiEzemmm2VFOg rtUjj3KJiDyfNK7aYKZ/9s0kTomIytbSVXZjVvNS3iF9jojijGoEGt9QIEIv /02fNBFZsluTAzF/FGa39xInoo6DvrYamPfQ3j/II0RE5t/8Xh7CbPR1uL32 CBEZdrhrr1fh9S256HvjIBG17GWTncA8TC44Qb8Pf15vlHkv5iM39w7lsBKR Lkvvyy7M1ue8o9S3E9HyXxuuAczP944pzG/D++dpFzmNeX7uEiV6PRSFt+b8 ocXfd/JdYeqplVBEyUrUPI7Z9em+yz2UUCR+TsPNEHO5u++m53QoqlmIM4/C vKY18erAeCi6c2p49SPm84IaljWDociIUfckN77+oI0iNoveUHRypWHREXNT L2f9ts5QdJ7/jVAH5u2F/i5ZraHo+nWPRmm8vlrE70cuNYSiq+T5gmzMsde1 umeqQ1FzS/unw3h/emReB0WWhaLR3vvcmZi5dnNLnXwViszGeTxO4v29NkWY 6HoeivyPpbS/wzz+UEeF82kocmwK3r8D18cx57LlqgehaJzFZ6QK8x01nmyz mFAUNOSk7YrrafHPDENGUCjyMFqr/Yvrb9MktOXEnVB0tnu/jweu3wuS8/c6 rULRETnpRVtc38QdBkKuZqHonY+SvlUrBVir+UgVl0NR56EkP0fcDzw8NRoX ZPD3XUh/P/YR1+sy//rkyVCUY8NMy477LfMD6UWYcCh6f33XzUtdFBDxM97Z wROKvkrZKrR9psDZ4V8dxnSh6LCUexTvFwoUmMn8c/obgup+CWzL/EoB3kEv 8fCVEHTmTMWi+DcK0A7QxFROhSAJs+BaMzwf3nex6h74EIIYt9fb7/xBAdMm ke6viSHI/v4z59RlPK+UHWmXokKQb1pwPxnPq/MNxZIsYSFIgIf0xBfPM34k m3DOKwT9NWQtdsI+NlepeuWpeQjKnHXTjKXH87HAqs/8WAhaUgL6lH1UoIjk MHoeDkEf9i6zduJ5aZk3IxPNFYIM2L7r0HNTQSXH+WHtjhDEnGb9/R4vFXam +189TA1GhlykooDjVEhJePx1tCIYtfjd41k+i88P7+7hm+rB6MHl/OxwC3we njtv+utCMNIylQmpvEGF8vW8XoJ8MCpK50yfukmFQt/ADykng5FXWoKY8m0q pPpLvOnfF4z4mddW552p4BcU/UBzPAj9ZxKe8DsQn+8X1ti+DgYh93bB/btD qOBOdyvydm8QcoxLsBAkUuFuiEJwaGsQkj6rQtUgU8GMOO+MCoPQxtir3Hv4 fJIna2hJ+QQhy8BDly9mUKFSo7yl3j0I7QyetpLIooI0C7+yrmMQeqZ6+jdn DvbJyP/OOtwIQkeEa3W/5WGfiH5+PPdSEPq7S3vgTDEV1uMY6Q5yBKFdTO8Z RBE+X/Vd/fN2BSGWJyc6euuwH+wZ/u8MUxBaWbhG79tAhdmEssUra4GojMaR +KaJCl8fWA9Hjwai9LQLF//h8/jNo4Yq2peBSOjs8rdEfF5b07CUMeYEovOd ibt3faHCbluDoh1pgaivsX3B/yt+XXoyZ09cIGpoe+JxGZ/3uzoZEvk9ApFN fOWFDOwHlad1Yo45BqJBzTSLHxNUsHqaRBaxDUQ1ryMbjn7H+3HneKCkSSCK 3XNXnIz9wpJe3fGCQiB67SzrT499ZId93B1VmUBky1nwnB37ZVnXF2uNk4Eo jc3+PScFv55md03/SCAqHRX6zIp9ppThtZERdyBqj2nO38RscXddz3RvIFKi TpjO/MSvn41Us2IIRDmRZcK5S9iP0nuUb/0joB6Jb+d8sC8xMx0Cu1UCYsm0 2aW2gl/veXnadYaA9LItvrRjP91+7reE5zgBDZ/e9z4I+1bJs/MnvAcJ6B+l 9JYk9lUmp07+oA4CyuVjSfTBflbSy8lLbCaga97th/ZhfzOTtzxARgRk6BR3 MRczY+ZzjuhKAsLDdrsk9r0i5p+744sJiOkerU0ZZlPnsyxJ+QTkkOx79RT2 W4b+QMbHmQQU/Dx2LBuzadaejWcPCMhHduDVfeyP9CzX/mRHE5DWesRSH+ZX LplLeWEEpFTe3yaG/dN0YI7ykoCvr/STpB9mepCeLfYioOjnw+JNmAuzfb+X uRKQhAOqZcD+enVn02iVPf77HMLEecy0bru+vbXG1+8TmuqM+eUXw/56cwLy dw35+Xjr/Yqp3U1GBKTg5Tv8duv9uT862i4T0GntdtsvmAt2nWzrUCOgKy+5 YhcwG7nfe9elRED8Aoama5hpBhHqlSOgj3mdbVu+/UJpe/UXKQI6SN4/vrH1 /ue65UMnCGjwzp7c5a33735UPCZIQIoyP3kmMed7jBV85yWgtxNiah8wG34T fj7DSUB+y8liL7fer+yaucBGQG0fLnQTt96f9yb1JzMBHT8Tec4E8xU2uscr tAQ0Z8TjJID530KSyNJqADr9Z951Gq+PfvXxI+szAeiXnIx2Nubc8EpOum8B iPOYL/01zEKutq5aHwPQf9uGTrBgfn5tf8eDugAEdi8CS/F+CF9sOj5SEoDC VvqZjTHni7sHCWUHIJP6uA+/8H6Kch0dcnkYgAbMtLrCMBds6z5TTQpAJ6TL Du/HXNhzckHbMQBJ+/pX8eL6OFk7fOmhZQDyjnHa9wjXU1FuVMaofgDychX/ thNzifecsduZABSV0dIxiuuznC+3IZkmAPU/aLl0DtfzmR1Gh8Z/+SM/Mcq/ QFzvlUv090W/+6PKNnrHBtwPb5qtxGrb/JGSR06qBO6Xt3d5kyfi/dFwnW5A I5UK5406fp0I9UfkcX6RL7gfa8FX2/OeP3r7+OLUNO7Xuj1faZnN/FFjwMW2 33NUeFf5wEFc0B8Z1DhGdOB+v5ih0nqP0x/lP647VvYD+3bEEn89sz96WHBH 7iGeD63X9QYMKH4oOfoLjSaeH+30u5S9KvxQacS9KNdhKnTrhnC9U/dD2to5 0h8/U8FATsptl7wfSq2U/HOzmwo9R8c7jMT9kLEDkWflE87PvyF4Zo8fErrW 28T8kQpfnq4vsH7zRUfFfl35h/PH6LRro4mjL3oVWenPj/O2u5FracwNX2Si cOJjfBWeD+9cspuu+CK5IuH/Niuw36c5h50654v60oy5ukqpEGroqMm83Re9 yOtfv1yI82vDnc+Vz3xQ4rS2x4d0Krg9sZzg7PVGTIOhJ/nx+cGoo0PXd84L TbC9OnT5Ej5fmJiWf4t5obKW9cNyF6kwU48mOfm80J0UHR9BZSp8OH2q2YTe C4kMMvhvnKdC/CEO0tCH++iIEo1nqQwVeBe+sH43v4+YTCr/0zxGBZlIG+7l gHtIMJT3JZkR16cqL8s+13to4u/LB6n4PD5A079+2voe+nonvriUlgp/3dSG 7qndQ/238ium/uH8cE00fZ3tHqqce2ltt0oBHdGfgnQZnqjxyWeehWmcN977 ntrzzgNZ/KeZKIt95e52YuXhCg/EcHLD5R32f1fVGBDL90BCFdluBtj/fRue aavFeqBo6W4aH+w/sW+a7/ibeSCeuz2sP7E/vclny5hddkeCehU7AiopgKYP CP+Zckezz27dU6ygwLtjR4sYBt3RV/USd4ZyCnRmnK7lq3dHDcpU2cevcf54 bPrVKMod/XOQJ1ELsV9FZO1pFHRHz2zjaHVyKLC37eWjT1zu6HX1VTbNbOyD TBV8wyzuSG57P61WFgWOBreJ//fTDfW25eSaZGCf96FonKx1Q5OUg7ZZqRRQ qFrtki92Q5fim9jrU7DfrdKYaGS5ofCbbA1jTymg7bbX1obshhi+ylw4+YQC VvaywU+M3FBtuSD/+kO8XnlKO/LU3RBJnXpNFvPdKY24cnk39N8TxXKvJArc u2me1sXvhpptTwxsf0CByGtB1UxUVyS/2XTIJJ4CcY8iLuwbd0Xt6/vzKuIo kNSf2Mbf64r2Fc/e4cacbpDbr1DtirrduhLnYyhQpvlhyS3MFSUcam5pjMLX 2xftfdfLFXGzn6w7i9nbUm+bjb0rasvMqC6NxD7n0cdqdNkVWc/vaqyKwJ+3 mfxAR8kVbcxbdytjpiVf47kk5YpkfkfPdZMp0Jw6KizL6YoYgkoUaTALCWcW STC7ou8V+wNSSRQgv7Y5I7zugqKVuT4oYZ5XEKo9suCCDrx+IjQbToHLrbMq 3CMuSDXZ7sFDzCX6L9v3dLkgX1+RvRqYOYac9FkaXdA2/5sZ2zAP/Fy2+Jvj gmgWen4HhOH861vxYznZBYlZhNWoYn7K6O2wQHZBvWrPE/dg/hcrv/zd1wWd TD0eMEHEPn1w03vY0QU1aA74VGFuyK7f1m/pgi4vuJATMQtIhIR36rugWkNS vjtm4hvV3a0qLqgm+sGgCeYZFeakOhkXtOr3i0cFs1ZnO0+VkAvqYx91kMJc aBKdWcztgjaCvTqOY2ab1BXJ3+mCAjfr5I5gdnXcW5zxzxkZP0stPYy550/v mSeLzmg/fe/Zo5hlgpNrE8ad0RdT1jZRzMm7rl2M7HFGE9sHLc9iXnt46ENI szPi8s/Z1MRsxj+q71fpjBQsGjJvYq4tyPjike+Mtmfc1iRg5jtjY+n41Bk9 Kny1/AxzUP3xqVvRzmgO4lNaMU9qzjpYEJyRs8Ci8jJm1b6CZWNXZxRpG/Nd AK/fc0snH11rZ0S3Yw/BFDPL3CladSNnxLKDjv0BZkeP5XAlNWf0OaDrQQ/m T5vlu+XknNEuj06WA3i/JMleSZInnBG3vZSzFeZEDvlDorzOyO3M/roizL9T /2UeZcPf99r9Dx2uj6vC9SI8tM4o+rXEfjPMsr6RztwfnNC4WtsyN66vv7Hs /ixFToina7gwEHNddlLE3wQnZDbbqriAWb0zPWf4mhMq47Ab6sb1yjopWNoJ TujN8eBRLVzf3X/y6+uOOiEvWamCdsym/GXfMuYc0STjRmQ/7gfeM3KzCZ2O 6CJf+iPraJwHNdFqyGtH1C+8bP4bs71H2x5bH0eUu5C5fjwWz7PWITVRFkeU 8ZqNqRH3Z/K+NN40qgO6Rwqgd03A/WdlubynxwH9iW6/LZhIAcrf8bS1pw6o PWRG7xHub8tT07/bxB1QSLQcR1ky/jz/vA8Kex0QC9P1CuIjCjxqt8soXr2L Pow0JZk9xr/fZkH7Ud1dJCptt8SB543K419Zt/Xvoj9J//wq0vDnTb32/iZz F91v+888P50CftIeuroH76KMnJ/qz57hPP5xdf3MpD36NcR84kkm7le6DX0m T3skZZptUZtLgZ13mbblPLJD7z5PutcU4derWvsO+Nuh9xw94/PFFLjISC6I srJD/z7SzfPheeufvvOqh6gdYq3iLU4ow3m4h/2Vyts76Bwvt3Amzvc9Cjzm E6O30bPlJ7lWTbg/d5+q4hOyRacWZb8eG6LAqHVCtQOrLdqdIH4sbRj335uV t2+Wb6HR6MPpB0ZxfrV+03Cl/hbqE6zZ4JigQHWV8odw01vIZGnMR2CGAl9v Go0sRtogIxdlpbQVChyo9GGo/3kTMdPv7G3ZTYUky2a9G9WW6JPZ2MiMKhUS dZ4YhKRZIqOgfQIf1fD5Ke9smBtsicTa72uXaFAhiovbZEHTElUlWvF662Df fzZY96vSAqUOKFkwGlFhkiAyzL9ujsJzxGMZbXD+VGzlCg4wRcK2mwWXg6iQ zOPK03bJFM3dF2vkwud74p+DfLvZTBHxkNGZ0VAqRBY5HX+SboK4/XfusCNR wZuPU+Z1/VVE63+F9XYs9luaWwYTdMZo4fSAOV0qFVjr6KKVww1Q1ok3K7bY N64WUGfPXTFAtktylzsqqZCRPHhJms8AvVF+wCDxBvucy+ttgpX66B6h1Xah Bucp/psejNN6qOgfL+8lnP9ehzSYtV3SReJNSdZOH7DfOhdW1e/VRU7um+05 HVR8HkuLuaPLSIMiuHcQ+1GV/WS6IVUHMd7PPSrXhfP3R+VwrsvaKMU4itjV S4XieFrjVFYNZPE+28QC+5iq/Ve2mBx1ZHDxqd+NEZwvlUveB5xXR/s/fd9n OYrzxsqN8zcc1dDLL9oR+jgfGhnXCwp8VEWtAZLfWbD/zZ18NMJxSxVZ848z /sRM2O7yiOHfRZRX0OHYjX0xr4pv15TYRcQc+mOdNIN95SBhOS9KGfWW/PZq x3kxdtm48LGgMkJTjefisX8Kdpy8HfH2ArotdeagIfZTHf+RwbsLSkipjszX if312ej5xpPaiqim8ndLwi8q2LuKrSm+BySwEvWfHPbdxKNDDvxr59FzmT3H hjFPhcobfjdRQFeCtCy5sC9HaqwftT8gh6rZR35ew3nwXm3kFyvts4iu7cfq CGYrSd4Y00BZdHrMlmHrfoYst9Ka+owMmqxlF72C8+HR6O5XSodk0DuRBwqt mFlprW3O6p1GSQdUtGSxv0/OED8JVUkh1qhhg53Y9zvNuYh8C5Joh+voJWfM b7ryznEdkUTT7XLinzDHVn3IYSJJIIdoibZgnBd+m9ZU/vM6iaqmM736MXdc GDlKGRNDMxUHOY7j/OG9R3DtQ7EI2nu/e7MKs+7aJZuaA8Lo+IXn2huYj43b fXoReBy5OJT6y+M887ct6tyTGUGUVewTdw9zd3FRDllPAJ1xzgwp3Mo7jz6z e1fxo9njE0ZjmP0Df/veOXIEbVPYxcSG89TzbslPxXsOo+9TzIlyW/ks435O 7PhBpC0/8tcS8zbXWl+nEi7kWZqjGLyVL5XoDXSC9qEkk+TrzzCbsGsIi+nv Qbnv/hpWY2ZpOLzJqcKKHgjIH+vCbH3jxYveCSYU8Kfr49b9mxqaM1cTgrch mZ9XLy9iFlIMZc5Q/V3rJeyf+x/mog3ZJrmdE7UHxnb0/9t6/14rfrnPbeez 7caHtvJnNJNdX/8K9bzG7vXqv5j3Nx2Kd67+e54uw9ZlBbOUcvDTtbf0kCFs /G8G89fMVao8Lwvs3rfj5lfMSrTlzwCxwQfLobRmzA8kndstqXvB7opG2db9 ohkrkZXAw5zwouZrZjxm+YRJ3szL3MC6X/auK+bYxlS1dwGH4Cr34d06mH95 naj6ZcwHe4ztowS37i/FM+vQLR6BzGKW6T94vVXzf4zvDT8KVfM7+FoxOzc0 3hPgE4S6++EyCZjf/fJ7dlFXCEqzmegPYabsuCZjNC0MLSpNbwfxfnMdlW2/ RRCFG5SAa0mY7xr8Wg4rEgeVg67qm7h+2sumVLQEJKCGXjTlJeZRJaOYK4sS 0KUyMWi8df/NVErAJlwSQgNM+dNxPR7+8czR4YoUJMyZip/HLO3KVuXBJw0d dqNiA7i+r5MXtImVp8GlZZ2NBnPxm9x7udOy0KUe9eow7pc/hMDmzaazIL3v z6143E/nL13bdzVTDgT6BN1pML//zPp6+3V5+CHQkfYR9+P4vAflzmeA5zYm r6W2+vdLLu+Nq4qg57s9JhD3d0UNh+quFkUw43w78f4nFTaCKIk2WUogNHh0 p+4iFUi7MyT3WyiDV7zenACeHwW/WE0bOpSB+3Yu32U8Xz71+gQ6yqtAzcC2 NXecZ/c/NfzUfOAipJzyK3qN51GGELPjvR5VsH3K8GUD59c3Ss55A+oaMJgX /uX9EBWGBIY+hVRqALvDWf2Sb1Sg2a7xR+K4Juw6XPj1wSDev49HL5HotWCp PuSs3hcqfDbtnzyLtOFbMAPL4x7cz2cPx2o/1oUhD5aTPu/xvDAgthfuvgLJ 0uuo6jUV9ErXQvWVrwCr6rcF7RJ8/fucFH97XoGU+u7nI0U47w0YlykMX4Gv cU+m1l9SQcBcOO1DgSE87HP15HpOBTnbD66z6sbQ0ufjOPOECjY+e7iPhZjC bVajeGF8vg3rXS7V8bWE+o65hVOaOK/P7I/XSLYE+yrhMk113K+Bw06qpZbA 9Jrvug3Os77FDqLn5y1hCB0JS8b5lZs9MkPM7AYkTbbEb57D8/9Ta+xOeSu4 67LPZfAEFT7qXHB4v34T2ne0GPDh87v8B7NmM6c1PHO6ek5nFz5v/buEGqSs 4Ve7W4QfC67PQsvJKntreKIqmjjKhOuPNeBa3qA13CpwiqqiwevZUa0eXm0D ZRUUofpfOE9qnj6m6mMLQ3dSX7sP4Dz7ou4cSrIF2bEL9fN9FBjeoaUnW2IL bFOevra92DfbrHxFZmzhSrPZEZtunDfUYrtZjW/DtVZPkSCcb0tV5vz7Je9A uh2zuGY9BZSzPBN1de4AmRB44xfCvkZHm9925w44b9PrflpLgZ8NXL3V6XeA YZUYtV5NAXElVdF0Vjvo8z6jN4bz7HOFZ/23Z+1A23aJ0fAlBc6knFgYY7CH dxlT/VIFOG/9raC9dsQebnsN3dz/ggLfqz+KaV+1h90fgtp+PKcAv9zf4FPN 9rBd9VJsGc6zxY/CHuWP2YOzrfm/Eux7iv/teXV0wx6+Gn+8XorzrUWl8Nd9 0neB9K2PrRH74lMZY4m1Z3dBlT1zjg3nW9Gk8Ytub++CkMqpNHHsm29WHK7N D9yF+0G893Rxvv1SGkIc3u0A4S0BL9Kxr+6XKvnW4OcAuY/Fmtxwns2JV/h1 7pEDzMKJc6+x757+1cpUVuoAa/3MtKvYh68Uj0jmzjlAgc33pAjsy3End5Ei TBzhaO2q7Qz26z/EVRdRN0fYtIy0NsJsOTxm2h7pCPf165RbcL6ViCo/wVLn CDulrleWYj9Pnkzf9+KLIzR31l85hZlGPuKfxpIj3FF7O1aM/f7TrMUn8jEn kA8r/FqL/V/2gkaViKIT/K1g1tbEnP5IOuO9iRPEx3bXDOL84KzG7L4jygmS uLPTt2MeSFsyy89xAjvLUO5snDcUV4cuatQ5gVzR/ZSLmNlySjjJS05wNsOp LR7nlxp/HZoHjM7Q8KfoHmB2zm9ctt7rDMfPBZxdxPlHoE92RprPGey5Ndiz t/LttsIhejFn+P7Obtt1zJFiR7t7zjqDhLvIzoOYFU2Sm7NUncE4D0l928pn RUGvVCyd4SwMjNlhNvu2msnh4Aw/ZGzuymJm2+6QPOnlDBsmAwd3YH4nNR5Z SnQGPwrdrxGc9+5bGAeGJDiDcEnu4lYePhHxweNKujNcUXE6kIx5tFzJTuCl M0i+/uXgjTlxvPz6cpUzcEmWUS0xX2I9YfCu2RmmLx9P38qja2efXUr87Awn VXIIclt52Ga/vPWoMxB/esWLYbaKi5CQXnDG9d/VJ4B5/1saQfo1Z6jQ79Lh w/x+2uNAD6MLTMsHr2/lY3+OuV1Ze12gePfg0FY+llS0pHXnc4EJQv3vrXz8 w773t7KYCzwmbKjKYn78UGNur5wL8D7V6lTDrNOIRiZUXWCkRS/WHDMtVbrn tYELDFenkj0xl3PntwZbugBH08vaBMx2qoffGji4gLPHjxNlmHldE4uPervA ws2HvV8xd6cw5ywRXWBRh66KHq8nsc3/cWOCC1x20eqX3Pr/iJWl6IR0F7jq RJKwwUzhuxN886UL9D8pe/cEc4bW8D2pNy6gzv02oQ+z0X2Du3QtLiCLnFP2 4f3dkdVq+fmzC9zaFjd2FXNtp4Jh5qgLMDA1W6RjPnZc6Lzymgtsm8/ZLo/r 6at+iuReJldIMZGTjMUc7b/n+MReV1BrKEqYxvy79+/uYDFX+EMnur5Vr00h XWMNlq5Q8rteyQDXO491VF+uoyssXY2Q/ozZXVm9PdLXFXbXKO69ivuFn7a+ 1CjZFUzXZiOdcT/5BxSFzXa6wu+La6e/4X7svX7Xt3PIFV5OvNQOjsP1c17I pXTOFVCpCJzEefjr3zRTfyY38As6mPUA97eMd4zYHnCDHOKTw0/xfIgy0eRf 1XKD3Y57i+48pMCkLBPnN1M3EBJzpZHHeTh+1Z8mx9MNJPwfdFHwfKG4O34+ W+gGFYaljZF4PuU4aXvdOOQOL7IjF7OzKbChw+yoKuoOzaX+bm9z8HwRb7IS PesODfp9dl9wvqVdkNdaueIOQV2uabz5FLhud+IwKdIdchZ9PYcKcT3asDQV rbvDtKEk//EqCjiotFQ9YPYA5BtFCcJ59t3R4EJvTg+4FhHXOI7nt+v42kMV KQ+YChS8XYjn+0eLWbsBOw94WPam0v0dBcJM29hovnqAJenzStknXN9l0k5/ fnjAYlbRPil8nrCyp3csLnnAOd5SeP0Z91eLJ3lslyfwux+M33oeI0NagL5R yRN+Rnto/PqG5wlrwGponicc12omjeP8+6tBepjF6x5MWD+8/oCBCmai6S84 ubwgoLLE+ZcSFdzsFrI/CnhBPZO+61d8/pLz5NJDT3lBvlZzS8NFnO+O9yYu aXiBvtmvc4n4/N4vsMO/088L3mln/JDVw77D464bNuEFzP9l0ftbUkGZVW3l d6E3ZI8IMz/xp4Kp9gPqy2pvOPVZSsOdQAXXyPEZ61ZvmFsin9HCvpC+w2+4 e8wbbP0FRldx/v3LWNJSyOEDQ3l0U/JR+HzfPPj4lrcP0Mqplrpg3xD5ST3f d9EXbg6KZAuW4/wzEXw2w8AX+FmjVgdx/k3t45R2vOEL7Op0r6OrqLC3BoQZ /Xzh7I46vhmcd/8SY/bKlPrCatfbdadG7BM8J6cf8PtB1/mnuyo6qRC+u3H8 hoQfeHxQYDuB8+wFWuMhsfN+8ORvmuvTbuyHU/7dTSZ+kKZmx+mE8216ycea lVg/OBvJLPb1K15PNcc4w00/SPca0H4zSQXxc7SRR3b5g/nI16PD2PemxZKI C9z+wJ581v4vzq9me2t9QmX8wc7QnlMI+6Hq8K5bZQ7+wCR2zVkO+yVN1zPL QB9/GMldNJXA+fRN4+lr2iR/OFezoc2H8+nJPHPd71n+kDx0l4eC/ZTL/aXc vm/+8FOqdJfiMs5ft5ROj834A2fQ2AL9Vh416T35ctUfjpjYezVi3gYbAhf3 BgBT06StGPblmlNxh9mPBID5fsbyAcyeAoLcQ+IB8O3FRKgf9u1ZZu3dHhoB kCj0PPg1zqNZf0eZla4GwLkhUqrKlq9T3el33QqARw5c+zoxf+55+l9WYABE PG792Yn9PrpFYtk5JgCm5pCqKs4Dam/eUeRTAqBAiqu3DHNN2vxET2UAXFIw 9CfgfGHFKqFW2hQAWT++5vZiZvZzK0joDgDV5atdAjifFM2Vs7mNBEC5Of+K A2Yj0zV3/fkAsB6p3VWMeaNV4cup/wLA8NbCPspWHn1Sl7qdjgDuTxO2b+Uj QYNx3fvMBBhSHxg1xHx/Bz3d9G4C1P/c85iAub1esMx4PwFmfN6fzMbM63XJ toWHAELfG1IaMbtK3Dlw5igBIospI4OYm6bI7TnCBNDOJvzaun/JlVbgt1+C ALfEeru28uRdo48niTIEaE6K8N7Kj2jX4tiKPAEoL9xmtvLlnib2RBtlAqiO JB78g9nGV0q1V50AyRMyrHOYK6UM/6joEsDKpru2H/POOc/8UiP8+fO8orWY LTKSzQTMCWByi14vdet5RJM3rIk3CZAu+kr8PmZG9m91dHYEsM4lNGhu5eXW DVc3ZwKk1nKxHNi6/xpwWHDCkwCGu7SYRvF60ZxR6tf3I8D5XsnydMwGFCtS QzABZMb3cW7dz8zJDjknSSaAXSFJeDfmNbOchWexeP1OXFmowfulzdGaxv6Q AHOtHlbWmNPbZ/QCUwgwdvcMaet5xktyYuWW+QQo/925II33//FPndufiggg VWsp1ojrhfLcmVuxggABZbT8mpgTOUv9D78jQMi7ZAk1XF/TH3slYt7j9Q8B nbe4Hs8RV8f/fSKAgYOe0AnM48tyl4aHCHCn5fPBVVzPpwvM/tOexK8HUuQM MIff9H/xdpYAT807j+T9xv3UXb87ZZUADsfmr1zA/eH7Sm3gGnsgCPf614vg fNh5y47czhkIJb/qogxxPuTnjZQ/xxsI21ijVby3npeM7EznFg0E8q1/YcW4 X/fbGd35ohIIreKX2QZmqXDnyP2D6pqBYHWN60s37veagUcdlXqBsDGeiFqm qXDz0tCp5OuBcIqegz4dz4ciAes1o/uBcDF4TodlnAq9p/NO6AUEQhdryMe3 o3i9VSnXNYmBUH/WrPTOCJ6/d+43QmIgiLvpTL7E+bHvZWSkUFEg8C2kK8/0 4X6QKeNdmwoEJpHdT2RxPuRXW9NdpgSCe3IjY3grnj8mEExZCQS1b4SWrmYq xPq0TY3TBUGW5EjMFTwvBeqGitoPB4Ep7auLB/A81VBnVE4xDoIXQpa5RQVU cDLV9Hh4PQis0t77Febj/bKPzY2zCYKVxQJKLs6Pw1HcO4luQVDA5vQ3KosK Lt3ivY4xQVBDvGYp/JQKydeMbRVbguDWcDnDazIVvjs8j5iQCYaCp5HcH21w PSo0udoqBEN0zkzgo5tbz2+Om8wpB4Nh1pOd1jeooJt/UGhJNxieS1B+/jbD 6/sj+h2tfTCcr034uP8K/j0WHhtH0oLB3cy91/ACFVT0LjhZMoWAll0bMeYw 7h8+C6PJXSEgzAMiboeo4E31UbjNEQIHpk9dMzmI9yOqjMX5SAgsHfMYEOOk As97oecB50KgoEzbdo2VCssXdo+lOoWAd1jisXObFNi950Qrv2cINH/dI2q4 QQGRMbVXOb4h8HdgI8JtHeeVgCC/QlIIkNlo+t+uUuBD9cqB2swQcN/0rIlY pECm9Df9of4QeBx54N/W85rPV2bCFIdDwKe0QvDJGAUKyldrMidDwOVg7pn9 o9hXZfcet/uJr4dYHcI7hH1CXmP9945Q8On7lePdT4HODWMJU/ZQyB5tpufH /tBTa2PzljMUomePHP7Ug/OtYmBnsEAorFs9XFTE/vFLpTKT7XwonDnc2XWv gwKrDM0Dbiqh8GdoZsQY59u/zZ939WuEwgAtyQPaKcCoTr2XYhwKq5xCjwXb KMCyY6OA5noobPYcNxVoxXmjfcf4TetQ4Ln1kk60hQIHtI9pibiEQs6xm266 TdinWaUDo+6FAttz8TtO2I/4O5XKF/1C4VJ1cW5SI/ZHPXO+CnIo7CMsX/uH 8/SpPfaG3HGYMys2z2OW+Xyf7PcwFF7RKKiF1+E8ZJi4rJwVCpwFZ46cxnn7 4v4M4dz8UPCWmh1Kxj6m0f/q+o7iUPA/P/CQAfPl5LcJDhWh0FdJsvZ5i/3Q pL3109tQyDyrZLJWQwET7i8bUu9C4e3yX3IQ5uuDPyQfvg+FT/M+rByYbz5d tl37FAqPK8X/FGL/u21Om2Lej39/20UzA8wOvGzddUOhsCcyXWfblh+OHGIS mAyFeuX+8Ursj/fSReXDZkOBvF/0hDdm3xtnXWYXQ0Fl86HCRcyB/JdytFfx epfWCnNjJk5cGSzaCIVc+yXa/7CPkrOs2DjoiXBy7cTgGOYYG+eL93YQYb15 57sezInH/L2/shGB69Lgx63nOZOnIl4pcBJBltF35xfMKc8fTaYfIsJlNb+o WcwZd3IP0AsQIc6OzooRf1+uSJmOrQgR9sv3PjqBuWCuIfi9BBE8HbVVzDEX F3yqFDtDhJJFC+fkrec7HYYXYhWIYGmddGIYc7X4PP+yMhHmKnaHiW8970r9 z9hYgwgDx1yiSFvPcxYxRb3RJYJK84oWFfN7l30Nh4yJ0Fxo1m2B17dT8ugq wZwIYod/Cg9i7lmSODF5kwg/zXwtbuD9GvbQSsp3JsJyt3xcNN7P0lg/zeR7 RNDvydFQwfsf8aKQhuhPhDPDHzYZcX3IjrHZ34gkwnybasRrXD+sf5X4Lidg fp/pmdJAge/73XrlH+O/n20LS8T1F6/VC1zPiSAfFCOfj+v1ti3jCsMrIhQc TqO0NlMAgs7kL5URwcHl8sQyru/5ikccnY1EMC1NynV/j+vv6PWZ0BEiiPM3 z+3Fvs9zPibV7QcRYGkbc0oX7rerdQY3FogwEhPsIYV9PzWav1Z+nQgX/SbF w3G//vnvR/zS/jBIGY8M+YT7+yMHl9rYoTDwDKeGNI5QIPuk+sZHgTAIucX0 pBHPB32bF7b5kmGQqfD28+x3vF+fnORv6ISBjSP7m88UCgTNpf/UMQyDBNLI a7GfuL4Zu3PkzcLgtbzn6cQl3M/y0uxcdmEQH/XwLvEPnle5f75/DA2DY+hW 0l9aKnD4B8bIvw0DH4UxR3Zu7IfJJSoi78LgyGpOjgCen/WvJ/7jbMffV/J9 +wU+KjjOXLReGgiDJ7ecnR4fo0LrlR1n85fDoG7E9XS1FBV8RBPGOU+Ew2WL /YcJl7Ef0j/VipEMh82ipvgv+vj7hrLKGc+Gg0UC4/QZIyoURpeTVy6GgyNR fX2bORVGf36R/GwRDo+qL6Y02OH5XskXHJ0QDtwWS/ZZRCqwxQkvMDwOB41e vuEj+HwZuiNp7JceDjd19hxOxXnD86CK6N2X4dDOaiwcl0iFPH/bz+ot4ZCV xOVrkEEF1ouFRxnWw8HXvaKpE59/Xw9VRPluI8FzjzrmdUSF3N9odYmJBHIN xXw8+LxUfN7VPs5BgtHM6r0KbTgfsKy41YmTgEdh9PqPHvz65MbQmdMk0L7T k1HQj33uLaPaq3Mk4LoQtWKF80SOIxdPqhoJPo2vpD3F5/tA17l3PlYkaN55 VVAM+0NWvor40m38+e/r9pnP4fM0WDvZzokEdQ6XbDxxfthx2uKuiS8JLN/f C7qBfaV/1+2+T0EkYJ3hvXdqCf/9D2dFNRIJHEamuaZwXlBIDuI4k0SCz56Z 4ZvYj3a4RPgXPiUBjXuhhSX2qT71xGnBTBKcbWb8nYH9K5M/RT8ljwSXLNgu NWM/c17PruEoIsGN954abdjn5HsKj0WWk0DJ7PJy/pa/v6yIpXtLAgtjvtN2 2Bf7QuvWvBtJ8O/zxH9bzxNmXG+z/tWG1yeF+4QfZsW4FZ3lTyRYqK5r+ox5 uPHI2d/9JEj+pVa+db/F97f20T/DJPB99iXqN2ZuYe9da99JION6fABt+fK1 nNX1eRIIW3vyGG89HxjdPbaxRAInna6hN/j7l+v+tW+ukSAp4uiTGfz7EpZE yrfRkuGDtmbnGP79kseM0+mYybBt/eLPZ/j6Pl0NJjOwkaFN09hdCF+/Y8Qr dyZOMggj+VY3nI921g5eZ+Ylw35NOZMg7JP5i0zqLIJkeFRqEauP11ftqLTU rhNkiI2r+zyO9+OHoeWh3VL48+cDiKdwngsJj2RilyNDa6IUs8I89rPqyp97 lMhwrud3FR3e77qFyUEONTKwUhqXg3GevM7H3rz/MhnEiQ/21ozhfKuvUMRl RIbIz7WO+UPYp0PvPOY2J8P7bHZz7S9UkK18EMJjTYZlKwPpTFx/HocoV/lc yZAjKLdoiX2QQ5dbmd+LDNq2+/2a3uH8EKQqJkAgg7Tgd+W+WuzjU6nbhKLJ 0HItrGulGOdJ7vY54QdkCM1NUt72Audz7dVe0adkGFZqVC3JpMKtksv5J/PJ YKzEcvtfAhXov/skniomQ5jVe7zmeL85n/tLVZLB0qaap2Pr/oEvjcGZZjLk R331YXfe8u8TCmc7yECc/dh98Bbe3/Grx8/1kEGl9M6X2mtUML5UvH5+nAx0 7+17Wi9S4bfX0HfFGTKkS75qPiGHfa+A+dOFRTIYKavZHBXH+8dulaX6jwxH v3+eb+DA+/Ftj7YOdwR8flfWlvWNAj9Y4YzukQhIHrN+sOU7IUr2R/SFIoDB zcSzG58v9TmNK4YyEfDxpuH0wRQKyLm4p5rrR4B8p5D8qCEFBjLTwy1MIuCM +l2uvgsU8Oz74HrDMgK2O5lKaJ2kQMk5wUs2jhEw3fhCrJyRAqKMfdS75Ajo 6ekhO79agFKRpeM6cRFw21Vn27vkBZC/zGZ5MjkCZC8FXEkOXACtZI1PP7Mj wHTxSneD3gLcFUFFnvURwO4R9OHQ/Dws63ybNm6NAGctjyueXfPg6/Yf39nO CGhNy9ipWz4PkTVScevf8PeXtD0M95+HAp3nLoQ/EXDXXvrAIeZ5kHZryrux GQF1wJAaNTsHNQ/Hxy4wRsIgB79lSPscfBjl0WfgiISF8KKk7ZFzsOAaJ0k+ GYn96+R8BNMciD/0Xkq4FQknpbpr387MQHn1Q1EPh0iYTHfjOPVuBs6Plt40 co+EzLcr3MqpM6AjTP3MFRQJEyyDlZp6M+BUfbM0JSUS4u2sf4i9noaiES2P 3J5I0OcfFjS6PQWnhA6vvrkQBeJnTthwvpiEoh0ck4LqUeB8vLpDJ3ASxBe2 d8VejgKKZvMLH+NJECn5lX/LLAoEIOdHLd0k8Ms3X9/jGQX6PC3nRMwmcL07 NN/Ji4JDOseDvFjH4c+96gdcbNEw22DoLL9rBDxNi4KC90cDC/Hj77naYViW z3ai8ERD+c3Dpzach+Hnthj1d8LRcLO0oFSnbwhmI6w2nJSjYeZkLxM1+xt8 S2O2afGMhn+kB2ozpl+hrsVY2nMoGrrMfF5/EewDNnrnZ/aT0fC9JnDx01gv WCqGs96Yi4Zjf5pb76b2wmZl5bTmf9FQTHihn3CgF87nH0g5si8GOLjLWNI4 e6AmcpChQysG1vT7tj+Q7IadbUuuDQYxkL87YLXrTxeYMewcrTCNgX9HjusU oS5Y95N/k3E7BvRPJUTrXO4COacUx/shMcDlefrpX49PUKVn0X+0JgZuUWqe VtR1wPboeyoHGmPAfN+dokeWHXD1fUwx6/sYuKvQn/RsWwf8uVAX8V9/DBT/ e/npwKUPICt9RLFzKQYedZZ02428h2sRLlfe7ouFAFs5c2flVgjK29gheyAW 9OMU6+KWWyC/hVRfwhMLj/FwLM5pgTW6DPHnR2PhIAeDx+SuFnjs27094VQs VNo/EH0/9X8N1x4PdaJH24vYolpTbUqaT3ow00Mpxbp7sCLPRnkLyY7H7aGQ GY9VE6Vtit+LkHfqeiWNDIawSHqvaNHaik82TVqa3BDTvfPH3j/P53M+54/z +Zzv459zB/1HTG+HuRAwjVbM+Nxtw+y/uK4lPAInpiZPHRO3wSDM8OWbfQT6 ZTNV1rw2/HiQ9VWoLwHRo4rp+QOtGPf8aMsPJTCxKklXa/YXaFlVPwwSEdCO s1H86dcC7j/L/QuTVfpK9pIGTgtcLa789SqFwL9rL5V4TDSD2UYvOpBKwGij T3X59mawjaPcAy4TKG6U8vd03MZOXdMB3xoCOvYas+H6DfBbyD2SXUfg4oz6 hZcPZEjUNvzS30Cga5cwwiNBhva5LLZPK4FjSiNy+6t68GYUwV5PCMyO1JQf q65D2GvJu31vCeTbffHZeUYK8WBZAj1K4JD5UUeHH6SofFGk0z1GQMNgXhP3 H1JM9FGb934ioPwqiPI9XYNTjyKjeGok1NeI9n974RYuSbfOOK8koRh6cX+w VYLKDYamCWwS9VNZV+UXJegoYh0qNyRh9nRZ6CUfCT6lTjz/mkOin5e9v0dx E56hUlmHGQmBW3TplQ03sXSZRZwVj4SS1ZPUJbiBTakcScQ+EquSqg6cZ9+A nfoKeZ4nCdfevWLX+5WIGZ/xUe4nEetvZv2OXYnfOm+by8JJHOnrfqr3vALp sdbTpkkkxmw01MWxZagY27Il+CyJlbvDs4RbytDOXx1O/UwiYnhokZW8FBNu av3jaSRuZFsVuQWUwp1zp+56jkr/Ozl3G68Ei3/fLVwvJbGu4Og+mfc11f9o XuVZT8Kj4mmTzsprsL1rPHKmkYT2yT+GdYeuIrp6nvfrVhLBv/oJjY9eRY/4 4Y7CJyS8nZSdjqnFoC15k8vfkujRMLBLHS0CE7g3Im2UxGulb3SXVIVPu79R GyeRmycIahYVIaPTu3f0E4lX5nnWlF4RMt2DapvUKTRa9xx+xitE3uFIwUE2 hUuLAn8Yrc1Hflr02G+GFFw82VOtgfkokMSEOq2n4H/lY3aFVj4Kp+K8tm2i EBk/olHmn4fi5KQdcy0pOJo5dL9l5aIsh5ks9aLQPXWr5ufKbJQ3Z0QY+FH4 aGEQpOBno2Io8w0VQCE81fQbc4NsXDfK7Y3nUziUtrzfncxC1a2rtS5RFP78 3NwRI8pEzUOp4EMqhfr3ztXzUjIgHasb41MUNjV91pnvpMK6DaHP0ynEjBi6 Ni/MQJ13s1dbDoXVJ7lmFpfTIXt9d0d6GYX9a++fsJAxaJntm9zZQWEwxn86 eSmNxi92jpH3KPDXPTXVGaFQN6cmp/whBYozLF8so3BDnbQ26KYgD3C9kxNI IU/bQaz2isJdjxDlj1UkEvTrDR5PU/AoZMS5qlwLDdYf11Sq/Agp8oy0IhDN Tm+zmkPD24WbWaWaO4fWHA+rnksjJcqcey87Db4bjCWZLBppdNGHb6JSYW6Z tSt4Iw1BZjCZYn8B277XzMwxoaHpwLFw0LgAE6sT8memNIzilOP1bWIY2bql 7bag0b9O+2yBjRjLnL/u32hPg5p8me+kutM++cUenjpAg/Ncul54/Bwk8T70 RUbF70mxttt8BitrFIPrMmmQhmPnxqaTce4vsUnLZRo+WTxPkzvJCAxqeqQo Uvm0OUD7uH8ytO0Ntbxv0qgIq9RuZJIQovs+YfVjGuzBgPL/6J9Gl9PZBw1d NIyHNHfYjotgeWbVco9nNDpHt29c2C4Ca8qtNmWAhpJb4bn4iAgtf0g/jMpp 0CaCEkn7KawoPRVSq8kg1FQxs0D3JM4O6dXw5jMI0ZcvGe5IhGJFtZp8AQN3 L5bTuYREdKYOF+gvZbB17fk9G+Q/ISba8XfRGgbOBTaikscJ+FW1YZ2tGegV 89uEsjh8F3s9b9iWgXftgIlOfByuSezeJ+5mUDsc5eZkGYef1saev7mHwZMa 8b3Gllhw5r9oXxrA4Hqf+4Pvu4RItxWwqoIYaKkp+uQZQsxJXHTQgc/gvOcz 4RZ/IXrHbf4bf5hBwCPh3pR3AthwBlyWHGNQ+dJYm64WoDL4RE5lFIPPhQqv rQkC6OUueGcvYNBW3JsUvEuAv/vB8P9+sP8BOctBJw== "]]}, Annotation[#, "Charting`Private`Tag$2743#3"]& ], TagBox[ {RGBColor[0.922526, 0.385626, 0.209179], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUmnc8lV8cx5FRVgNRZJPxMypJ1ldWUWTvZO+VTda19x4NRZQosygiB0VK RkZWVCgj7lWIkH7HX17v133u85xzvuvzcR8eG089ewoyMrIJKjKy3b/RHx+e /RqcjUY2b3V4BokB88SL5bKAbNSceqAgdUAM7k93P/T2zUbfmxmSPomLw+vl FRZKj2x0OH0/F+u8OFDRKf0StM5G99vtPihLS0IsjDxyO5+NGtotMptGT8Bh 9R/Wp1WzESt6bmN58CSUXNph21HKRm2qhoxI4yR0mPLHpclmI5kNS5nOppNA 7etl+0QsG71NCxG/WH4K4kr3cmwwZaOT5P2LHU9PA1sV+0DLgWwUladt1rpx GkrrxBMTGLJR6ec/+hWK0tDZZrBxlCYbpfzSDXTqloa9E4WDCptZSJ2juH3w 9xmIP3g2JepLFrpdkspPFSoLbGyXVC9NZCEP+9fGxH5ZKOW8usU8loUsCYu9 tCJy0Cka41wykIVMLtwPXh6Xg33qH9TedmSh61Mv6ta1FSAx2HmHsSILzZm4 5CjLKcGJQRe/zLIs1Ko3PZvhpwQjYm6LLCVZ6NmwfGBntRIc/+oxxlGQhUaP nuHbEj4Hr8/7PhPJyELHb5yJmz+uDG73/MQqU7KQvNhDiW/OysC05X//RGIW 6tq7Xjtfrgw2lUGZMlFZSNnDu5JLWgX+MYd7qPtlocFx/7rXhqpQ4hHx7e21 LBTzZHRvcqEqaHcSLLQ8MEvSnotaVIX869GaBo5ZiNp38OnheDWQnUoQtDHN QrL7Dte49aiDb1X2ZKhCFnpa1hpNe0cDOPblGpLLZiHVp6WlCX814JVN3vto 6SzkfWiV6vZVTTh0+NaLJIks1Nbd5pghdBGqQgpyb/JkIek61daCnktg9LGQ 4Rgn3t9eh2eR8lqwI1EUXXg0C6XwVD07Xa4Fl6bvez9kykIDmnMvxTK0YUHj kXYdVRYS2XpjK35WBzKKH7fLUGQhkkLRj7EAHZD5Wy7ftJOJFoMZSrOe60Bc dZXIq/VMdFTo3W0FWV3gZ62j/jCfiY48vHGKUksPrs6g5sXuTEQ6MqOtWGEA 9FcNzR+/y0SMki/lWv8YQP3owrrzm0xUZ2HLF3beEA70spyYbclEqjx8Uk3f DaGtwbX469NMZNoggH5IGYOHFLlSYXUm6r9d89+XJGM4WpX7ybIiEx029RBU nDEGn/utLJ9KMlHAm8L3OjdNgD+NNf7jzUxkR7yVlspiBn37KvhzcjPRre8F J5IDzSAkWrlVPysTtbnmr4pMmMFQkPtmX3ImKl/IN3V5bA6xdq/cusIz0Q3v wyU9Fldg7qynbot9JvruTgo0SLGC7FpKYphNJlKnPvSxr9sKlCRuJSpczUTH FK8S7PZbw03+9lcvTDJRJPfkq+851qC5n1267mIm6s2b5FuutoHfCdX9Phcy kdYLfie0aQNFlOqeJ9UyUdSzyoV+NVvY+uNVWqWYiVYZ5pw+f7aF8pmOo49O ZKIVvtwxZX57MLlq8dxJPBMF/aPvmA20B8qxn/rHRTPR65J4IlWvPVzp5Ui5 z5+J5PtlJbrCHYDxhfe/u6yZqF2B+oP2qiN4pXHOZP3NQCwHfCR9JV3heEbj qM1mBrpYav1a9q4rTGaa9J5Yz0APFd8akBjcQCs380XvcgbiEudm01hxA5E7 1Bl0MxnIm8rt0ehHD/h6tzh27EsGul+6dl7Y0BNuFCqFlE1kIHmlY58ahjyB 5n6w4/nhDORWvTL9zcMLZh4RFaLeZaBF17WdiJhrcLs86ZTemww03xYQpt9z DfQqhYR5XmegJ+QCLwPYvKG1xoYZvcxA4a1iqK/aG+7Wf1zYrM5A02psFsm/ fMC0oznPOy8DPaJs9fnZ4g8HOs1TzmVnIDaKf+lOvAHQ+XYj8kBGBuKsnWR/ EhMA0t0nPSoTM9ARjUXLad1AYB4sUV0IzUBDs9cI4+TB0DWkItsQnIFMMsau k/sEQ+TwF4n4gAwUxf2qXut7MPwcO8oueC0D3T1scCdu4Dr0fE39aW2XgQbr +5c/vg2FmGnRWUnrDHR28DprlFYYyH/r/PTvSgY6EGgi8GIgDB7PUXTeMc5A ShTk9ORz4RBP8r87qpmBHKe2nnWwEUD5r+VF3RMZKFU8VNr4cRQc0FsgGxfL QHJC8cRJ+mj4XOL3zE4kA7XMzW1HeUVDiE4yTyAf3u8pK4KZYgw8K25Yv8uS gXJfdDxqXIuF6A3VCqFDmOluGlY6x4G+Vp/NE8YMdPT48i3JL3Gw/Pt7dzsN Pu8gvgz+oXgQ0WS+v/gnHZXRvJV8+CURNu4WmPr/Tkd9xRenll2S4M2KyH6y lXTkRKuoYbyRBHZ3zgUzLaajXw1Fgu84UuDusoeO7GQ6Yua+0ZmbmgZuaptU r8fSkVT72Xt7j6aD3K2YRq3hdKTgP1b42CMdRlTyBa370lGHUGzU4LEMOJT3 djuuLR0daLteyp2TCV9+GDw5iNKRs55bVuBGJlQpfXG83ZiOHMjnPvNaZsGl hd/9lbV4fQcpr5RLZkOsAn/ZUEk6uvW1YdB8NQcMMqssrxano0/Kvgv0brnA NyvLPF+QjlTY9zfnfc+FlnTd8O0b6ehm/6mquJk82JwOM+RLSkdVZte16Khv QacMLV1FXDp6qJZk0Zp7C/JSclqko9ORTFaN0qbIbZA6Uy6qGZqOxtbXZg0s 88EjcZT8mmc6uvDWPzNg5S7If7Z7vumajgrNUmv2FRcAndSyW7RTOkpNI+cO Ei2E0gnqkTzrdKT552Il1/dCmJaUqmzWT0cBP/Un+QKL4FmJfkKUTjrSnc6d 7xovgkQOH7sLWunIpTBq5u25YpDc++Rovzo+n+MfZilZ7kPYZ4m4b2fxfp3F 2OXGHoCe4WWbR9Lp6LYD9aK+XgkIdHkoeJ5KR+Zjny9c6C6B988qVjb+w9cT tgT3v38IR1NFrei501F/X5u5MqkMiHsuyn3gSEeHRUDYOuIRtAa5HM49ko54 NK8eJGN5DE72Ze+5mNKRKJchDbtGOTyTP372FHU6shlTzbj2uRISn6gzb1Dg eJi0KJ5Nq4IXOu8ng/6loWsTmqEPeKqBRkjzYsqvNHS45Snb1U/VUPRRjb92 JA013dYgMHk8AY226DGF/jR0G47ONI88geWKV+lvutLQS4skX1r1p6AYc+7v WHMaOkDHS/NGqBZGTyl8JH+QhtyEYu16DzyDCK6Q5KS7aejG3/1fvTOfgSBd ozLLjTQUZ3pa4SLrc/CdkqkSSkpDB3PXuZdE6uFAhlT85Wtp6GlkbahOyAt4 HuKjOOqCr18+9+bXkUawdHqyamOXhvRYmRuCGxuhHCSt/Y3TkFrr9eR82pdw gSgqe0chDf2R0UibHUdAGnVZFjyThuZeSqEGrRbIbS8rqZZMQwJoWWK0qgVm 8o8zveZLQybZG63m11sh/CLf4sK+NJR16WXTtuQrMJhQ5F2gSEOFP7UPrFS+ AhFPM5P5rVSU80DykpTkaxjMzHg9u5SKruU+ODIj3w4iY//yZz7gz5vJpg4T 3sA/V/aB6XepiJ2UvRrB3gmDf6X3Tb9KRbQhHa/6GjohnMfD72tdKpI+IWzg QfEOBp0+aU3exN8nsH2vaH8PjzbXoyYyU5G4UcSMHqEbwpOZXnxKSkXpFplJ nud6QKRaU3A8NBXRfCym0enthfD1+p1h61TkwvSVrCjjA4jE5lR9EE5Fen2m qzlmQ0DGVvOtjzcV8Y0YCH+ZHIKhsvfsfeypyNdfJvm+/UeI6N4T38OQiib/ Hr+fEjwMQ8zeVl0/U1DxL1tjmdZRiCjWPtjekII0jj5wP1g/CUMtND71GilI Kw+aJYdmoMXqpPmIcgo67m9wW+q/b1BOdkVlQy4FnWbSLJuM/AaRSk+YZMRT UNl8QGif+HeQbLGofX4oBe3N4hIfD5sFDqu4/GG6FLTyN5KmrW8WaMieRK9T piCb/87fKOWZg0mgMTyznoyS0//2HG+Zg2RUs/ZsPBmFsq7Nri3NQ+DVTxMf B5PRuM25rsnTC2D7j7rjd3cyQiYdyhCyALJgkSvdkoymWBxHT1L+AIHPsWFG DcnonR7JvVLtBxwIr3Hwf5KM+Mp8071jfsBsM/WZZ/eTEccnjs3qfz+g3/IE 18c7yahJllGKQ3YRmnfMaX7nJiNxyYiZGu9FyFasGT6dkIxctpsTNCcXQbnZ PLDOPRkVpqtWLd1dAnHLWKshh2SU5XUqxvrdEhzZqb6wdjUZPfmseev3yhIs K1AfOa2XjL7bfFfIPEeE8QlJcsOLyejmd5O2e/ZE6Ag1n/dVTUZ2iqbmM3FE uPOyuqFWOhn12huvcbwhQvyV8XuDEsmIhtG1gmeGCL5/qRJXhZJRnAJnr/8/ Ily9I+nNzJuM5EUtuQSOkEBTwdxMih1fP8Q8cfoECaQnYpQNmPF5OATUPjlP Ap7QahFfhmSUJCT29IEFCTaaqLae/ktCfy8e3WKNJMGMheT0wEYSYivdGivP JEHvtlnXys8k5D+o8WfqHgle5Mc8ZfqRhEaGCfntVSQoka++fWomCa2rVQpb NZEg89NYlP5EEjrLS8fe/IYEoSFUbj4fk1Ci0bvfCx9I4MQhaZDVm4SeSGyo /xojgUGTmfzTziQkN7CS/nmKBEoWMfwDrUloMPykdvM8CUS3q+hXXiQhr7Mp 326SSHA4f2z1UC3+fmv8/dBVElDIU02crEhCsmp5Db4bJFgal2jXK0lCPofL xRO3SDBy3azCuyAJbV7wnen8S4LX7DE5mTfw50WfUuT+kaCqsSr0SUYSEqeX KV/EfP8ORc2FpCRkFSsZvsu3wg1nJqOTUNIllYOGmNOsS1n9wpLQZG+KvfgO CaJVtjTpApOQUIWtbsQ2CYIEtMPuXUtCN8QzgvU2SeBBc6/mjGsSar3sZFS+ TgK7+ZWZbrsk5O5VL5SD12/apc5mZ5mEeBo59zD/JIF2xc2Lm8ZJqGw48rXE EglU0xbD0nWT0DhlAhtpjgTi+pnfmlSTUID8mqD3ZxLwnf7Gpq+YhDyy2GSU 8Xmyscpcmj+ThHZCShN6BkmwZ3ziCYso5r18riff7sZb8vtj/iQk0SvRxPyK BMS7UUeUOZPQiZi/fZ04fiM2whEeB3F8m19WNOD4Viz4ar1ZT0QP9zq/kssm gfEm3Vzg60S0nn/L9Zg5CS59ssSTPxFFyVndpDIg4fqo0X7wPBG12hbF/7lE gv8ijes+PEpEHEC1zQAkIKctjhTJSEQUAqNlfPwk+P1jra4lEXP2e5UHx0iw 2H1h3ig6Eakktssps5LgYwbxclRAIgqwDzwwSEuCx0dkj326koia9hWi4BUi FG4l63gbJ6I/BC+vrSUi5E58jtqrm4gaXa/0Fs4RIeJezIKUaiKy1udCFpNE 8IsaOdalkIg6i/qe+44SwcVeVNf6TCK6Sd4kUTtIBEPhD89TRBIRtfC3hsdd RNCk4//Bx5+IRKuZ6+xwPSot+XO+OJaIvmU+pjj/iggiNRwx3w8kIt745J74 RiJwZXnWh9AmoqPx9O/mnhOB2a/txyHKRCQUbcDkU0uEfzJOerCegJzyivfS VBKBtzWP6uJyAsp7qTXQ/4gI6hpv6o3mE1CKc1B530O8vg+/XW2mEtAtrtx4 sgdESDUV5PIYT0AXfG5ctikiwpOvhv1Bgwmokk5/Yq2ACEPOMTEx3QnI4ZIS ReMdImz8rJXJ6EhApvs+RNXcJgJH8MyPfJSAbhI4jo3exPuhYC4orU9A/geU w0/cIIJdoopebU0Ccpn7o/siF/efQz5ULY8S0O814imfHCI8vlVU31WcgB6I GjSaZxOhh7ffdTg/AX3jFPb3ySLCr0fkXNM5CUhz/f5CQyYRDp860U9MTUD/ mT/JE8cs22gVsxmXgJoQrPVlEMFSJV2GmpCACs7E+xZijuxCPw4GJ6Ajf9Ij 8jGX6JPuHvNJQK2pRmGvMb8d59QTdktAZHd5ulnx/RZttalO2ycgljN/OnIw H1gMrVeyxOu1f9aigNcj5Vvhesk4AanNBdDux+s12f7EaaKTgN52viHtxfsJ iabvt9VIQPwMxOcieL+F9PIxnsoJ6KfN8RKfPCK8znaVuS6XgPSJC3+m8PnM ctz+ESuVgDpNDpMCbhGB9sG7u5liCYghRrz5RD4RxMU2de8KJiDZ5zfz998l gr+CaX0dWwISNPDTlsLxutUe79p6MAFd9ewKC7pPhGates5uWnw9TUHg5xIi UFmyxsxsxyMbdNyZtpwIQt/VZZbX4tF9Q83H3ThfLnn4/9gixqOPb7e0KmuI kB02pMv0FX+OyGRf43yrp6ai4hqLR6e1Q9vWXxDhU6pUvchAPHK5dVJErZkI fAVZnMrt+PocdVqRdpw/SPeHV1k8sr0qwbAH5//H84S7IUXxKOlMS+7iMBE2 e6t142/HI4nLYiNz40Q492V/fUFKPHLKsfzBgudRH1lPdM+1eFTwee6c8BoR ls5pcv4ni69vJ1zwwPPoKH0RR+UpfH//LoW3uL4vfPxzVFIsHlls/tQT4sX9 1qWMVYo7Hu1Ps+dfFiGBWdbeg/LU8ejVd5aHWfIk6Jjp2HOpPw69982JuHmV BKuVnBQ9XXEo9p3RvjlbPM+C/Ml02uPQh4VbyZJOJAhhEPyrXx+HkJipfIUX CU5Kx/w2vxuHqPp+9KsRSFAQpzLv6hKH/MkWFCMKSfBe9/bskm0cCl36c0Di Pgk22Ve+eV6JQ/n60uO9D0lgVF005aMTh7b0Q598qyQB/Sj5p+vS+Prb38KN cb+ULTYd+ysRh4g5UsxJiASO7jUj4cJxyGzy8t2KNhK0kVsPRXHEIVuqKxrN nSQIFGnpSaKIQ9EzmllUuD+XrLJ2M2zHostjb8xKP5JgoNmzK20tFhWEknrO jO72e67OrLlYVLq91Mc+SQKLYwEdLFOx6ErXPMnzCwkSZnte543HooDB2Ykq PD9nroe13u6JRWSDPc6/vpPgkPpHdKwzFn1JvF69iucHHBBvLmiNRYl05axT C3i+3Z94UVwbi86/8mwIJZKg0+N0g0BlLLJjPloruoz7s0zK84cPYxHFoYjL r/F80u2Wr318KxY9JzfaW4fnV/aDYjvt7Fh0gpfZg/o3nh+htCw/U2LRwRXu LWU87ziMrrVnxcWi6ms1RS54PluJj/hJE/B6E1LNQv/g+FOD4GhwLKr5vnr0 Op6Xs5MPPl73xfffqJ60xfNb5Dl9HKdHLFo/Tl98Bs9XjzSfM62OsajV/Znj b8xPHMdmba1j0U/mz+KFeL6vwbkb1OaxWG/T/5XC81mGrfRCmUEsWpUXGq3F HLLM+Oeidiy6+T7wPRee5y2dfmXE87HIfCdzyg8z5b1Pphnn8HrHNYSfY74Q pEIrJReLKqtfVU9jTtJ99OKjVCzyXj+ftIW5R/iga5A4Pp9Tlt07mA9RBLJz CMWiJPHylCXMRmOTXc08+H5tczNvdvXEE7UQa/ZYJD3wdykF82Ri+X+ULLFI zL6xHTDz2DJNlDDGIusSuqQJvF47ueAUjb2x6KRom6Uj5lKmrwqL5Dg/zj2y ncD7Xfxxnpi6FYNucFs0A2aJ15V3T6zFoPNH3HJS8fl457NcHiTGICth9oPv 8Hk+8w355z8Xg+6kRZn/wue9eWm66shUDDLQu1ZIg1lRQNOqaTwGda+YMdDi +LQPsbaS98agx12mx4ZxfPdWhl273xmDLM568RWt4fkf+43nfFsMWloNZzXH +TAo/TQyuS4GmTHuL8zD+cK2/+gpiaoYRHbmajE7zifz2YjpD6UxyL/xlHcq zrepPG1V1vwY1HjvkeW5HyQQ9KpbbciJQXoRiWsErP+cL3A8sEiLQaOfL2s+ mSXB8sY8VVFkDBoKfP/f9DQJ/pnGvPnPOQYxQxZtyjjWHycXA3ptYtA4R8ZL PVw/sbT6Qt4W+Dzs36nTDpOAsZE74fnlGCRs93vjcj/OT44mTWVpfP+K+B4F XJ9nJ391G++JQbETPI0zNSQot5De8dyORmVfLaEM1z/neJB4/Fo0YturWWbz GOvPEbK0+tloFMTV2FyH+8e7D4w6R95Ho25G6aXZXNzP2kX6x7Kj0efBOJnB IJx/5TYfrwhGI7HaGzKhuL8RRUqo/bmi0Qft4zN3ZHB9lM1Lp7JFI10PuSgk hfVfiVdeM200GhLmWqUWw/2nMMyEixSF5t/KD1Xhfnon69bYl+dRqPik02oV 9gMHDk3S/qmOQvT2EgLU23iepvPIHXwUhVZ6Nk/bbBDBIaX09rn8KJT4SJRB 7CeeV3HPLIoiolBK5+A88zSeR8H9k7YaUcjvVaKuXSee13KKZr+UoxDDt/pe Nzwvnm2VDUXIRyEu1+oXoW1EqAwhvL8jEYUGabJDGpqIcDdM8sUwSxQaYr5O dQfPp6OQf9phfxQ6/ztGbQnPr9x/NDWre6OQkbO34Hk831IjPj88uB2J4s9J GLBhvRMamZpzcSoSjRcfJZ3a1S/KmwfGxiOR3fbJ94N43vrucUh2GopE+wYZ 1CPwPHaLVoiK6YxEQccTQtfxvLeIXfRClZFo8OTSO+ckIoyomyxqlUYinxkd W5sEIhjQvHb8dC8S1VPkXnHAfutS/G3LP9mR6MfTjHfpUUSQT9S8dOp6JDLS Xr59LQTPU81nb1p9I1Hy1KLlm2CsJ+h4VXQ8IhFL4WVm4SAi/Jf856y7dST6 LmyUdsCfCKWX7Ou2zCJRj2ueZ64vEfgZPkgmGkQi++iAACEfrL9SS48/PB+J 2uV+iFzzIsINbebi0+ci0aFtsh/HPbFe3B/B+Vo2Ep2lfLG14E4E+nRjlq9i kcj90bpErivWYzqv0j2PRyKZP7Q2YS5EoDwoQb/DHYmifi2Q+zgTYSuDeg87 cyRKPwWFBEesP/S8w8oYIpH174iHtx2wPjs0+ecMTSRqAHHxNuw/PQY0/DrI 8Pd/z0mv2RFhIatu2WCTgI5NPH4lhdnBgMdteoWARq2qhyJsiTDFnDJ7bYmA dtgy3UdtsH4b2rAhmyUgBynpJEXMYzl2k6lfCMgiclSs2poIRkZ9psfGCIjg yGggjrn/sPzQ4wECCvdu2aq3IoL28EMd2W4CKr8oxKuD+V0e0/vODgI6lzL3 auUq1sMm4eeNWwjocu7Gp2LMbWw/2r41ENBBhTInK8yKo0aKvk8JKICxwloY 84ubbQ0UFQREFc7StmOJ9SwZXR11CQEJdsokTGLe76hfTVuA788a2f8e84vu 248ZbxDQ/KPfWW93r5eaKTmUQUC+T1+2DWJmvP1f0eFEAiLLOKVPxFxP7nfn aBQBue0bkTmMn2fj9PIGZwgBnchwc7iEmaGXKpvXj4C+Nn3sTsdcf1o7TdAD r2/grNX07vX5uYkijgT0aN8KgyreL/2ezzHiVgQ0cSS14wnmZ87HCSdNCUh+ 6XOgBD4vqz7PEGk9AvoTuHzoBWa6M/UBshcJiEWNMVIPn7cVpYaHsgIBfTJd Si/H8aF1zXBWlyagvIRbNB44fnUfRu00JQjohfxJcgUcb9oCF3M9HgLKStzL twfnRy3VUyOjowT0oyWJYxPzVbctXTMmAjr7KlBuxwl/fjb5gg0VAQ3PxESL 4fyzLBxUcdiJQPucgoNN3Iiwj+YYuKxHoM5L0WLpOF8tBytOe89HoJQOHXMB nN80nr28kd0R6LuvXMm0H9abQ6ycsR0RSLPqmem1AFyv8lZHElEE2q9/epwW 11P1vp/7M2siEPMj1XYrXH9m9w/9vZcTgZjMKCOzcX1S0plvPEiNQBba/Wsh MUSoula8UhYXgWoNfPi8cD1TgtRCTVAEalIhY/PH9V8xajjceiUCQZSKwjbu DyZKd/vbjSLQ508qZtJY71M8/N799nIEulvKth2E+4mRb8DrD+cikJPsD5Fj uP+Q7b9Z81UgAqlPcZT0YH3+ML6edc+ncHQ1QuBiPfZ7Qt6O3pd6wtF3U6kB Z6yvS80Pd+e0hKMRbp5ZnlYiPBL3jRR6EI7EjYnkDzpwvxyUWNLyCEfcU27c vz7geHM/bLtBFo6GXXiPR8xjv1Gf4y4uEIauKKcE8rGTQK1ItTOANQzxNcgL aHFiPZy0wtu6Lwxxf6mKCuDBes1Sd0SfGIomj0zmdB8nQRclg0rQ81BUWBnV H4TnR79ONNtrjVAUL8fEWKZFgi9z3q9MPUKQq09J3rEwEvgaedemWYegOBDb 7osgwb7X1x60G4Sg5YpAqogorJ8LvOJOyIUgdx7uiL54EsQYelzctzcE/b7n EHwmC+uzNueB+nvXkZatYhU51svNEs6vidnXkeEpwQtWZSTQv+NUxx9/HbEz PMyox/MyJNAxL93jOtaPle2G1Vg/idubO8ldR8d/FD6BBhL43LaaZh0KRjTD 3/69eIv1xj6rQa3OYMSz11OltIsE+f5X26Mag1FA3c37Kd34PHQtH5LuBaMH h266KH3AemOvhesbj2A0MpnyTmUEz28/c4u/1sFIq9z9JQnrgXPTZlqnDPH3 O9sksrBecGk2lSiQC0aSB8m1WrC+bvI1XvHfG4xM3X/k18yQQGfKaKZ8KwgJ Cao2smI9/e2y0dAUMQj9Yoka88V6hFHU8Ln2UBC6yyv0nQnr6eIbBqXRnUHI 7fL+BkOsZ2SoDW6+aAxCt6tnTVMXSWD9Ve+6YFEQunXxxMg01j+/tfXcLHKC kLKGYSEZ1keJTbpXMuODUJX7IN3u/4Nq83RgxyMIFabyl3KuYD1KpSMpZROE Rjln3rBgvTXhfZnHxTAILbbPOO3BeoxaW3vPR7kgFKJz5VAb1msbNDSrv8WC UPVMy8X7WI/Pt6IZVu4gdHqKTu461uNj1wOHZA4FoY6xqVF1rPfenz7RYUoZ hCzS7vDu6sFm0vyz4N+BKHfc5EAT5qqyooe35zBX/Lhrj/Vk5jHmhIn3gYhj LCUjF+vN6OH3QTvNgYis6s/yMaxH/TJiXLhqAhFRdGb2JmaHi4rmSsWBqNbz vR8t1rMmVOsXrXMCkfzelVuemDVRlXxkXCDivadg8hazXJCTWHFQINrjYVPF ivXxf6d4OF+7BqLnMU1FZpg5l0YZv10JRG8XHE5nYj7wMPMflU4gqlGRdm3G TG59cVlQORB1Vjy48Bnzr6OUX89LBSKWyD/9q5hnBps+OAkGouhOtgP/MH9M 9WtLYAtEhJh71Lt6/s0F8aePaAPRtMuPlz8x11PMFndtB6AMpiWFMcyPmgqy F4kByLjgatquX8j3N4lh+BqARCVvNCZgTpE86C8+EIAO/Sp4r4M5bOGtw+X2 AGQeKd5Nj9nrfqSx1/MAxENX1PkS79fGUu5CRlkACgrZeGeLWZ9tVebJ7QB0 /vP0lx18fqr95cIDKQGoVOopaxpm6WT7o6vhAeiGm2EoM2YhdU46Fu8AxHLW njsNx+MI2fDWabsAxNlw4MA/HC/aF2mLRkYBiFdc0sIO87bPhYmACwFoz2Mx FoTjSxQj77khG4BUKVgv7cf8ebahueG/AGT5KeWQIc6PNnPRwq0DAUi+Iiuv FedTLctMOseeAMT/Vj9kDufbg958gsKaP8okrslTYY5XYbQNH/VHFx9fu8+N 81Vb9KfAniJ/lKV0xe0riQRK38oO82f7o6RZy+QGXA8nCmxo1GL90S9jMbn4 JRIwMw3Oxbr4o24z1dJ9uJ7GNp89pj3lj5yu5KUXfMP5WuuZLyrgj377FqyI 43p96SGUconVH6m+K3peh/1w4dRNj9QtP1RfQj1Y9hn783chJw699kNqPBSp ErgfuO2Nred67ocOU+Qa3ML+wFs9DcQe+aHbGdN2O0O4X7Xd07qQ7ocWB6w6 n2C/kP6iwznMwg9tXT3n1Yv70YtHB4oWVn3R9WWHh6Qm3A+S7h96JeCLVMTY udJvk4DpbcXNPjZflLatcNT0Ju5PNM+5J+l8Uc6J2WnOPBLwRb0V//PTB7Ef jzC7l4n7xXWipkSzD1LuvcgRk4DzwVUm6raRDzrh8OTUlD8J6i6+X/GJ80ZV LiOyr3Tw/T6mBrsFeaOlHa36/7RJEGylS27v6o3Y3uzvyb2I/ZzfR0ajy94o ruemrrs67pd3vwjLsHqjnJzUvOPYf4z8XL26XXINKd8otyHh+SEb8vz76o1r 6PqvnEZvAZzP1MHuS4nXUOU6T98GL/Yn7P+CJz2uoVtCNuUMeB7Nq+7LbZG+ hoIKVouvMGM/mXfsfXSHFwqrXxerISeBBe8XvdB6L2QnM1Dtgf1Jc3nRqN8j L5R1wr9H8i/2J63HZx1SvVDt+Ff1V9if0P04QaFh5IVU9KqY+JeJIBOS7HX0 vSeK1ngr8+MzEbbTD4bRVXsi+8VSv50JIrQ8yE3azvJE/xWsjLB+IoJGb2HJ pLknEmPXdb4ygvUDb92noh8eiG6UZ/M0nrchnRMXROk8UKk/36LYa6y/WQo4 C0juiOVB1Jen2M/U2VitHhp0RyXG4t+V8Pwmbk8VbOa7I0fDCisvPN+tTsz9 fivujh5E9+ULNuD7hZW9V2ByR8a2jaXfnxPhZpdLUc26G/qbzXWq8hnWu/ZL Wjdb3JApzYkV/VoiqN76dd9Jzw3FX6Iz36rC95t9GvxJ2g3Vh27lbWB/FCrl p6PD7oYYexrK/lZgfdCzvnVmxhUJ/7fmyYX9Uj97w4fHna6orbnxtPxjIpCc gh9yVbgi659fflk9wnpkz189Gn9XtHNy6lpbKX6eTrPQdTNX9GROVPkf9lfW d8J3iIquaGPPY0FVzLfOUDz6SOOKKhyl1b4/wM+LfhWuueiC2t4MJKpgHvgQ bdjc54LUdtq3Su9jvepGQ15y0wUdM/ntnVyMn9fQ+fFImAvi2Zkn0GJWo04s T7FxQfH/KrvTi7De1b8YSX7eBclp15tyYQ4rpDfxE3VBy1fEhZ/dw89f6hab 3++CaBb7FA0xP5dN23Nl1RkVTR+4s11IhME4ndG+EWekSk6mXo55efBglepL Z5SnbChnh5medyC6/p4zSjnpE8aPWdgz2+y/WGeU4G52YKkA+4cmQ8lCF2ck V/fy50vMNvtYqZkvO6OthXnePMxhRiPjcaecUW3Nl+JAzLeLb9ZssTqj7/fB 1wZz/bJZnOe2E9JS0ssywDyowHFl+osT8oylJ7uMeTlx4qRxuxPqkaRo0MXM MHJ3b1eZE3qxFtRkgVlEwGpSMdUJ+V222Ou1ux5vnton3k4o/9eZW0m760FT CYLGTugU5WXPKszh9Pev3pJzQm3ZsdHjmPNN7U8zcjuhYg+Hj/vx/upLBOki KZ0QR9tx60u757My+2VtzhEdbavhzsD8U6nsmXO3I3rnlXhgEjNjqkvyRI0j il+fEz2Fz1dkXNRGN9cRsShVuqdjVhdaOtMe7Ii4yu371jDb+lUynL3qiIYZ VbVtcbzy959o4BZyRIY0zyKNcHy/2GU1ujM6ojMxWyv9mPlfrL18seqAqCNr LYxwfpTbvWgzaHVAuWGwfQ3nz3IDR/u9hw7otLOOIC3Wz1L7w98QUxyQnbix eBnmxgaV9/FmDuipLVfTFs7HHcaSniElB6TFe+JUFc5fZbu9H3iPOyD6QyMu zmXYHzJ2DzWt2KMzkd+2fuJ8H7M1+rycbI9ahZOf6+H64Wyo/6rgY4/a7DPP y+H6smFkn0k0tUdVJyn0RKqxv63/PMcvaI+uGKVVsj8hwiaD8y8TZIdy/izb aeJ6VbTtWn3wwA7t1BqV2uN6jqwXW/+VZIf0s0QPxtVj/2T7ayvZxA753bHi //SCCEfqr1O1/rRFkzU+f7sR9jMMkzSMI7Zo+JzJ0SO4fxTaKNGaN9ui/Xlh f5xxfxFioNq/lmiLOr+TOjnacX+zSWUT5rdFvQIiwu3vsD+hvyeaYWSDLvGN CjMP4/O33iM+KW+DTLvGamtxP/vyzF5SlM8G9U3vMJmNEcHJWuR0O8kaMRs7 0z/F/TDg2VPFP/HWiHRany5/hgi5Vh261o1WqMl3eVR2hQjZ2rf1owusEKVc d7bGGhEy5b0MH0ZZoQiJM48t1omQwnbUdOmiFXrg/1982hYR9t4bb/lVfxXR vbFRF6DEeilCZJJ36wrq42zS2mQhwR2lTraocDP0hHqvY4ocCW5weHO8PW+G Yn5/DV5VIEH2Bjv3/gNmyPvgSJSFEgmSqz2P3y40RVWiU//E1fC84maVftpq guLYDjiN4fllROagP73HGMXqhu07YYPnacueVJV4ffTrc+R+Buw/TMpJC3IG +mjfvTv2JxNJUHRj/LwUtz5isKA3NUwmwZlrT8kF6vXQ96g7DVnpeF7x2vpR z+miOTnNftINEjyNbrN4e14H1a68kjmI/cmOV2VDK5MO2vPLMoHq8e58lxLz RZeRtEvLvt/lJGhwnSk0JGkjyK9V7sJ+hb5HJZ7tshYylpOXV60nQU0mhfFd Rk2Uf2uc0bKDBOquYwfSSjTQGH92CF0n1isqT96FK2qgUW3uD0+xn6Fcs1a0 9riAhvKYplff4/0atwrw96gjjcLgB9IDJPghcfMzs4M64nyhp9IwSIKIvddu Uu2oIYemDGnpjyQoa+BmmBVTQ7l3l0c4sX7ZZo9YLUtRQQ/y2+XLsH9JXzWu vCWggnhH2p9uY70j0C3hlPRSGcW9Z9zR+Ir1V9jncbelc0hRwa/vwzQJ7n1R fCWhpYTeKBwfzp4jgau32KbSO0D3N6x16+Zx/Pgm3Hk3FVH3hxWxXuxvZmPk Db+ZKiDVR/TjROxnkjW3+FyPyKIQt6jqT9i/BDQnj9ponUWGL1Is27B/sTnJ mWZGkEE2605G935hfXP03KbGvDTq/f1gWxPrQb7U/qpzx6TRqSvaN1iwf2Gk sLM/q3saRanom4xinpmP7RNqOIWOmKnxXcJ6s/cKWyz30knElz12bAvziw9l cmw8J5EjBQdHMfYz6Q3vS2gSJJG7ii71JNarv82a6neCJJBRgdWMF9az3cqf +YhfxdAci/ajbczBhwQ239eIoFfgOLSD9bDO5nn7piPCqF1CSMIP62fBKZe+ x4Tj6ErdhukM5u23KXK35wXQ7Pl5nUtYb/fXVJck6vKj3mH7/RWYS28OHAxu 4EWa8XwZ1Fi/hxF+hzjz8CDLCLF+k93/3/ef7Ks5xIWuc4z3FGM2LAosSZ9i R5P/fY6axUzu3Rzi+YQNDR6TJvJhf1BxjlJfO5IF5VKdpTPFbHpQU1hM7xBq uxc3EouZro3rH6sqI+Is5TCowGxn/fjx0DQNEr6tFPIecxPZGZOsKHI0Vph7 eQazkFLMviL1380Dmozdu/6n+q9Muyz9dDOF5o+Vv7vXM9nwyg68VRQ/+e7V rh9KpXH5OLxGUpRay5DfxHy4/VimV+O24pRjhOXu7xunVKLyN19SQiGZmMgo 5rHidZI8Jx0QKAILX2I+R/HsHqADcCz6ZtstzDknvbqsSEwQBnyZXpjnbUTW CFysYEu+dGD39w/5rBnO4stH4cTe/85RY05/dffC6/BjEHzYRqADn8+voP8a fhlzQ2OoY0sYZo7Mfdp7lnlAqdSBRRKz+qPvU0zxfDCYOH58DMfDq+1VAD+3 AHi6p2+F7L7/8Sv0npqOEJzal7NejuNJpDWXNpoThsZiFmFZzGx8Ml0OEaIg oaIs3oLzwU3/12pctTjEZYa8fYbzpatuVvUSvySEh6u5Hsf85ZxRmsGyJOw/ IrGRjvON1uwUv338SZiRVCFq43zk+n7Pw93gFEhFFNvjowEp7wMNftxSsHMg a2YZ+yPLxCWt2PrTIHn+E1sAzveaFw8DHs7JQNB/6ZoncL1sRBA6/rWfhTxN LUc5XE+K581ZTIplgTJn5r4Crrd3A4xP91rKwzHuyOciu7+nLPoRnQcAzDyS 20p363f0Iae1iRJ8vmXt6ofr+3kTszrDGyWYlSKWys6S4G8kMdv+/jnwYlXh q8L+KWF/0cnDV1WgQZ/x5zncP8p/MZq1datAmuahI0MTJOgbuk7wkFeFf4EG 1tafdt/HMezrOKIGf27N3rXH/ahIaJ9HwKA6qDXP/ubE/ezFOa+yEQ1NeJ4k YufYToIJ/om+6HpNcBerFMp9RQKyvZobkscvgnWJuw1qxfHr4TufQHkJgslK s8mbSTBgNjxzFmnB9lXy2+ef4Xo+y5WudUsHcs6w8i8/wP1CP7arcr8BXKFM 7nCLJIFu7WaMnooBvAsefa8SgffP4qn0298ATlerfGMLw354xLhOYdIAon6K PXoZRAL+K8IF78sNoXDvxuFVL+x/HN97L2gYw3FBGjHhqySwv37oqGC0GbAr RqiZ4flW+il28O1zM6g7KGrCc5YECwpbqe4/zODN5gPPeWmcb2Qze+r0zMHd 3WZf6EncX2LqllR4LGA7R9ulVhjnc5pJq3XzFdCbeFMVwEaCSd3LtdohVhDG WO04j+dvx/zhTM0bVnDo0tJ0P57PFYRJT/VaK2Cz3mpuwfM7pMZdVHHRCnzm 2VfLSEQ4ejC5SMzCGoKiw8jqZolg1NeZTi9vA9S1rxnbsF5QdEr32GtiA5v6 B1K2PxJBgMzkEqWvDXyBlFH5ISKsSszSbD+2AcEZUcle7I8y06jCf7DbgtFI Hq1CFxF6tJXd323ZwuCPFdDG+ubZ930XO1jtoKOG5z3xJRHuhH0QajtlB6PP k/Vym4jgVmk10+BqB+++/UjdxP6IljHcvGzcDm7QOgYfqSPCrwfqZx+s24G9 p2TaylMijCowst5jsgfphTHWIazHSt3v9N+4aA850YWNlVivqXc3asQ32oOo EkvjS+x/xO2jjkcP24P55QOfB7H/YfmrSRWxYg+BB899WsF6cOa/sZYAUQeQ flmSqoH14vvX9+76nHeAnD4wjcB68qmFc4inrQNQi/cdR1hvRiZvnHG87QD/ VkjrBliPuvC3sNg+d4DvRpL05Vi/6jbFrVgOOMDE8y4NOswyBpc/mJEcgPGT YoM31rvci4erjOgc4dlstc0U1sN7oyeT9Y47QsutRS0zzMvsJS7aKo6QV+wa OYb1NLp4WlD9uiOw8ClMr2C9rf24RQ7lOkK/7tB8KuZJ2ku6Mk8coSFbhvok ZneXYYeabkewUnivMIH1/PZbmxCReUcw0L6fk445WZiYUUzpBKvlEYd2/QB7 QtBDDm4neMrQW7/rFx7NUb7MkXMCc5Z7ybt+QvZCej+jsRPwkzVm7PqNtw/Z 5+K8nUAuMbpr14+Y0Dz8S5bqBHUehxR2/cqcw0mm4DIneJcuNL/rZwI6Xgqt vHYCFlnR/l2/Qy2ooej2xQnUtsU2tTHnxgzqf9tyghNmyza7fkng21VnS1Zn aJjvZ9j1U7WqP8KGTzrD7dS5rQDMKvf9s3W0naFpelosF3P/HopHb52d4WOE wP2mXX9km4KUY5xB/ORTyx+Yf7axDTUWOoMYo/IVXry/CN77C1JNzsDtxV9g jflApARZ5bAzXBSx5CvDXPD1BcvxFWco6M6a28Asfk5dtJDRBbIXmJZ08Pm+ LPygdETEBcfjo3gN5ktkV4wy1Vyg+KPv4yM4Xp+uzrnSWbvAiUOnrRIxuyIf QnSIC5yiotTcg+O7yfkv92+eCwiNedhHY04MSyz3f+oChqimkgHnR6nCvWGn BRfYPPKxQQbnz5k7/y19pXIFTjMH7zHMHdvPKcx5XCHAQEw9Gufft8YeMS0T V/h8c0xoGeenL7uZSoePK/RTFoo+wflLef2bCaS5Av19oxMhOL95ZbejTnS4 gsbTMGEhXA81N+NuPvrqCltF6/S77w8p/TlUxffXFS67hw+tYL5aLzzGIuUG L+5MrUxiv5QvbSy5ec8NQLvI/hCuR9HcKTWfl26wZJDhc7KWCC/W3M0XR9xA a7jpiBmu39Ha6NjJ/e7AbF9D3vJ89/2uJ5/aQt3BIth0eQbXf4YEQ0KSqQe0 xpsUxXUSYSN2/Zqojwc408X0/3tLBKvJr2ZdyR6wfSRoMhT3F8mUZ//RtXhA YDWVflIPEfoWrvYlCnrCtY0Z7oVBHM+SJ6yJK57g4ke+99EUEc4z/qf/usML tDNJPo3kJNg8e+989oAXSHSHve7dQ4JK+8Pydl/w5xLBaJYKz6eXZAKUm15Q LG5vyUtLgu+uQ79VxK5BUQHTCDpEgti3YbdeZV2DssXtjjh+ErRHf/jaZuUN g/8u3LingfWFXcrHhx7eAC77b0teIoGvikZXcog3lJBLa7dgv8JL0VprdMMb bhmzyX7Vx3ovvDpuodcb9mkIagtYkkA6OE3sEPhA2qf+o3neJEgxvci7fskH Fk0Fgrj9sL6VoWH9ZOYDoTwnNEoDSJC5HkZW4u8Dhky0j5+EYH3i6zFwttIH em/KuFbGkqDEUyvI+pgvbMc0e/LcwvNbe5+HuqgvXI3qyojIJ4GBeLuN6Flf mDliODR+lwQUS/KX1gx8wbUiTSy2GOsNl/+4EpJ9gWthH3cJ9jeH7enaq7d8 oZZL2WjlJQncVd805Ozzg2xz1eg9LVgv8UVVBrP6wZFs6WyGNhJ4T23mqZ7y g9quL72M2O/0XF1wGXHxA2Qw8re1mwRxZm8PkI35wd+CWzo941if1El5bnz3 g2b9Dw91sX5gPFjYvbziB6IFU9+7sV/JfuOf+JXBHx49p2qqxv6kSIqf8tU5 f8i8+V38GNYn39LSbBq1/SGdokzCHusXoR+bLU/N/eE/jv1XH2B9U3XvQ+h9 P3+w4bNeYcB+pIkxfD2mzB9ypspKQ7E+InNZMAx75g8nji/0R2P9pNJuWOv/ yh+2rS/GR2F99e76f9ccJ/zh2MleDUfsRxiG83qvLvgDjXLpiUtYj+mc3CNu su4PHJJ7LYSwXhueG124cDAAXvhqSHVgPXdUVU3jHGcAaKufao3Des+yoPrh WdEA2NKu0lbCenDGMM5ORC0ABA1kxHOxXhSq+dXGqxcAkwNdNqewvnSlt+Rh vxoA4wU7Fm8w/2qTmqQLCgA3Y2u3AaxHT3MWylPGBkB3dqvjRaxfA4Pobm9n BoCkg/haA+amQf8/qwUB0EOxtJcL699/ElPGS+UBYKjSkReMWTlJ69m3hgAg UZDlvccc+72eebIjALJf6W8zY3399hy/z8eBAJihpW3Wx0x/J+1Dz5cAGBAa 74/HrLOxKfFmKQBCBJhO1mLO0ndIRZsBYD3vOTC0+3tJ5YfF5zSBoNp7tmrX DxylVbhYzRwIbernmnffj7piX1pWyhMI+0eH/+z6icIWpr33xANhn9GQ+a6f mGEPd7gpFwhyz3ImFzAfD1h4nXEhEI4LUId+wOzSb8iXaBgIIsw3TlZirhRr JUTaBELaB9iKwPwz/r8vwZ6BoLYVPaCBWWomT9EnJBCcbgXU78UcCHvuuCYE wpuSyoe7v6803vLYss0NhI7TOgVOmHfWRk0tigPh0BGmu/t2z0tXrd6gGl8/ frp4932ymPLqw1ovA6GbGFMphrmThsNP7V0g2NdbtlTj+NDbxg0oDAfCE/nq UWHMl5t/nZCeCYRXx39s3dj9feyIZbr4z0CYzuYR3sHx/+j7lii4EwhaLd9t TTFbiBY+ZmULAqMVzf2/cP74uCw96OEPgkhlDr9TmBPLZAtjTgTBoAmzuSvO t4bjQ9krmkHgYKrT1Izzs8+BN+2RcRAIaFxUGcP5O/fAM8HaLgg/Z8p6cQXX Nz9tWG9oEBywJY9axfkvZmscGJsYBFbv3XIWcH2oFt33VsgLgtfRZ64Ok/Dz ucHxcXUQ3Iu2VsxZwvfn8NWJmw4Cm1Q17WJcf7PmrZqKy0HA2ikvp4Prc+cW o9radhDUjH07s/oN3/9I2Vnbw8EQNCieyzON188yyQsawXBOtPI6E65/FcYL a78rgyFbMO+kTS8JzLRySBWNwXBNQfNaHO4f3slT83adwZAiLdh3vwvnC23o ZP/XYAiJElHpfIP9N/WTN5XM1+FIXoFTLSLBs3/stxyCr8MfWsFr0pXY3ys6 Zx+Luw4egkwJc49xfoU+Sx3Mug45HcLq2WUkYNrWiVKuuA4GqYZco/exXt+I ceP8ch1yPVbc2W+TQOQnSfGjWgjoHnx0Px/325npqLNF+iEgLmS21hRFgrsf WaU8rENg+ErGvhHsL5iaQJg6NARYKt8J/AvG64tNY5KuDYGDBKopFk/cHzkk 5nJ4Q6GWXksg2Qif7wWPDMN/oVAfFFPwmY8E4nIUyTwMYbDmd3apihvHTyw3 duloGHyIP/su4hjOD6bm6zHSYeDh07zGz4r90SSDQ517GCzSnnUPwfOMzbdC luVTGBxD/+5n/iRCU8Hi9GB9ONxNKrpY2bb7/0/JC7Xt4VAQm3j5WAsR9oX6 lGf1hwML5bt/GVi/G5lt+uothoP4RtHv5HoiBNJS7pnbHwFfblSL7L5v3NUq UGd8OAKethaGu2P9wBl03vENRwSet7l3mLHebp9N7CoRjoC/B6WaA7CeOdR+ MNteJQICTpmo5+QTwT7klPqQRgQ0Cl656XmLCPWnDDdUdSLAUcG2VfcG1iNF Nyz4r0RAjun7A+LZRCgP5xKY9o8A/jv5xzSTiUB25tywXmgE7H1jkOSQSAR9 ok1CW1QEbObLdyTFY/1lUbJ0Lz0CfgRePvIzGusDWbFnVo8igEHwt5FIGBFu /dR26quOgDO6XvrpIUQglnodVXoeATe9C3f+BRMhm7U2jOt1BBxzDn23HYD1 bs+QZNq7CHBWnuBM9CeCXOz61E5fBMTwqCXw+BFhalX2/OREBOzvW6fw9CbC 6XKLP1ozETD/Ik1Z4BoR4m3DHr9ciACL+d6Nb55EkOhv3X9nPQLeZGzyx7lj v5Ew3Uq/EwGKXyveOLoR4aMSlW8IJQEOm8TJ6rtif1d1YcT8IAGubLF/03Qm Qq+DS2IXKwEMC2bUjJ2w3uNMlpfjJADFs++dHo5Yvyf3Fh4VJUB8j1kksicC h+pPvcQTBFgy+jOxYUcEr61DVJtnCFAmd7REAfNhFyPnUVUCGL2saJm3IYIz TyC7xkUC8FKekdLF3DRys7telwA5+v5Gr62x/kpvDBcyIQBlSKG0Cmbb8xMn blgSIGvYbbp7932lnZ1pGnsC+Fz+52KHmfYZd26AKwFm+zfGqDFfcVe+MHuN AOHtLkp1V4lQzW+3aRRIgKP/DT70xDx0uuw/3XB8fc/MwAnMm+pEy4uxBOAw XZChwMxpcipDLQWvryV95osl9gvOga8gmwCqTfXT3Zidgl+unb1NAAleT+Xd 97eSkyiEpIrw+Sn+ohvAXJN/3ky8jADpE881f2D+WJGcLFRNgIoW7b2H8P23 mj808z4nwCuBIK3zmLn7Dv/kaCaAyjAHbxJmta/mfKztBHgbqpoygdnlV6Hh wfcE+NPLmaOI95e253sc3QABXNjWFSsx1zKLvqAaI4BnBKT9h89rRMBr8d8X Amh+Dk5owPxXuo5zc5YA4+bnJQ3xefNe2NRZJRJg+4ldzD/M6qYQRVwjQHRp YUK9LfYbLtF1c9v4fv7D8hE4funX385O7YkEtnyqu0Y43nXJjEcnaCPBk1Pk sZwDEcbu6F8aPhgJXrYG1hI4P/hbJqq7uCKBm168Xhnnk8YH3ul2Qfz5E3Ft GxcieEw5srSIRYIwWU9AOs6/55S/gmrlIsGUu8aezYMImhrUKneMIyE6/HDm kA8RPM0u+uVZRgJ9LcUTJ1wP2a7pDzPsI0G6q5KWFtfPZMpR+lifSJg2OisQ gOvrWr/4kEdaJFCKkG9tELA/nPahcc6NBHG60JmtKOwvVuvP2t6JBPsxZyf6 WOxvWFXuGj+OBIXE9HFDXO83zI0dld5Egl7OTZ+4LOzX3PJvyvZEAtf8qvxq Dq7H0K9dUkORYFYt1uiO+4looauk8HQk+MZe04q9Q4TmmfA/B/9FwoexuHca 2D99cy9NmpaOgn9/uM7/Rri/KLR7OypEATkD49nvuF8epZ8y/aESBZEu7xYn 24mg84hdaEUnCiZn6RfnsV9p+p76msI1CrScOoysR/D+r/r95SmIgulSSZnH v4igqqvsaUUTDRGnRRkFRUlwlfuq0QxDNChfSunpFCdBMOm6ghNzNMy9Jgi7 nyRBdUodnRdPNJz+Z5fRcBb7jXdCpeFy0cAo2CJpeoEEq8r7v971jAYHRYPa a/YkKJb6pDcxHA0Pc3U3xrDeL12bj1OajIYYXc8/tIUkKH+23lQ8Ew2Eu2y/ TmK9/0yG6bjLz2jQe3MjyRnPv3fymlu/aWMgvKSoyqmOBL1/jSXNDsZA/PfL Ly/Xk2Cw2d7+JWsMcATSafzXSIJJJUJvFH8MVHRyFb3GfuCXan3xAcUY+Oz0 ctoZz+d1qo4RH9UYaA1icF7F83u7Y4BhWDMGloW4qb37SECtQQq4YxwDKSM2 lv/XcObRVH3//y+FBkmoVEiUopGkEp4qCpmHpIEkQ4VCKkN9jJc7uKMpMiSR IRkiRVEUaaSQKZF5ujKkSX33e63f78/nOvfs+9qv1977+Xitdc7Ra+BjhbGi kbJnGHYbmkXqEv6XFVULirwchqI1n+vtv5B+6t3e4rGrYfgT3jt2rouPTeYn 5B7QwuD2v+l0614+dKyjJvenhYHO3VHjQvhEb1mqUkZWGDjt1+MECL8YNt2z W5AfhmO3mNoMwjdWtq9q3j8OQx7tqtw5wkO2K5tntleF4XqF32A54SW71l7V 2Now1HdvShcgfO96QiDxRFMYvm6hyJoT/nKXFauvaA9D2Zyhi8cJz3t1yAiv 7Q5D2MrEMSvCb5dTNmqGD4YBnz1PaRDeC3DY7Tk4FoYGmb83RAgPBskfTDee DoPuZ9rFV0RTvlq15s2EYaPNhvJLhCdpaafEJOdSsO3DXStRwp8spwt6lxdQ EDn6RpRLdJTiNb8WMQr+zVv/cjbh2bg++j2t5RSUW293OEF04p3r3SkyFJg/ vlKcRnTqmYwVc9dSQLM+n9VEdIZykYmLMgWjUyly34nOGXoWUruNgm9Z9/7+ x+P5Oe9LNu+koOyq2aYpoovdP4+wtSiwXHmO9x/fl24Zlp/cT4Hhj9VyN/97 X4L/08bGkAJt5YIKG6Kf5wlHPjKjoDmyzOknibfWc+kzGRsKYgpWCFCIfqeq MB14ggJBgRnaDJnvx4ltm7odKQhMG5m2J7r5vrbDwbNkvks69t0l+fnsYxST dYGC3mkV1x6Sz/vsq4fiLlPAk+wpmiT5pmfnzqJco6BS1Ut+iNTj1IuOIu8w CiK0ZAtrSL12dYqdc2CQ+xmJFyIJL4v+2StnyqMgdGq7y25S355l3g2a8RSI DD9Nf03qzzVqgNQdCuZXrLXIJHzs6iI0JXiP5Lv/HX+crCcE78yaKKLAMWej xtpRPoYfXJd8V0nBW2NTB+1BPp7V174sq6Wgf82tyPWEj+NGfl/LqqOg9Git 4E/Cw3oKdgNhHRS8r9VLtSb9rbQ2K8m7l4LEA9fUOsn6Hz9SYekwQsHHNqNR 6zbCl0z5J5q/KVi8JeHz70Y+fvzs5U4sCwd6evP3kv32VlJKv1MmHMluks6y NXzc3mow83ZtOKblj+X3VvFh4ZTtkqUaDkY5L3LPE1Lv9+c1HUzCYTLaUTA7 j4/goZRvJtbh+FwhdewA6f9therTNY+HY2LO/T++d8h+1VRbInU2HAuf2Snk kfPkZMaPnrdh4Ygvc41wZvMheS2Ipfk4HMZv7uj7u/Phv5HXtXxTBAQzvh/v kedDf+4NI5ZqBPaMiS2jyZLft6cVC+2OgKfvoxrVlaR/YxbTpvQi0JTyoI67 hI8v35pVP9hHoDS5tTBlFom3tuuGoXMEqDwvzyt/RuF7a0jomVsE8lxoBbY/ CF9az7Tk+UaAxz0QvWeMnLclciFMXgS+Hb3QzP5CeIWjNCIYHwF6bE1mTdso 2s+o2lxNicBHM8cHi5tHcWmV7ka3uxHgzI5xf1s3isxrLh8MqiPA1aj3l68i 120uaD19EwGL9uiz/YSX923zzdj1MQJPl9odrSS83NZJ81/fGQH9qjyp0gej ENXLVRD8HYG/eusGnxM+bpF5EBkwm4o7Ea2PDxI+zvhePj0hTCX9iZdad8Yo dO7UveqSpOKQqtKL87dGsSioZcfRVVRkVv1vz8mb5H7br8l1a6hoGOgQ9kge hffCKe+KLVRIa6oc7E4g93fPtO/cQYXawSJBE8LTIo+F9O/toaLu55GCJuJ/ zdGLCxT3UUHfYDwSFDuKdA8p6SR9Knj2KlbGMaPwOriGstSUin8G24I1iH9C TnmMYU2FwHPnxYaEv0V+qh6de5yKKPFlnADit5/q9lT5n6KiWe/w9XruKNKy dLdMuFJxcWNHsRHRniHGcWfPU3Fi9RyfIc4otI8fFujyoULifzh2j+gFO+zd bAOomL1ZeySO6KZFro3vg6n4lkDJukN0Wu8FHX0qFdqNdqIdRF8o980qZ1GR WxXA0iTja8UFS+6MoaKirT75KdELPOnXcm9QYepyPMeDxNdoENW/7hYVmh7V 0rok/lvyiRaJmeR6yynLfdH/8e/tMsk8KlabxOecIfPX/JiryCimwjfi67VH JD/z7z5gz3lMxdkTh1fuuE7GC6v45VdJ6mPqXdNM8ptq9/L0+Esq9lx/8uoO 6Wd0OFMmk++p8DJ8m/A2ifBO5Zrd35uoeF6llqlI6hfw3Vjhx2cqCrpNlfNJ fVcq+S361UNF9/rvBh7ppP85lj79e5gKcc/PinaZpP9i1nfOTFAxIDTnQyBZ P7wJ5eLZAjTsMP+XaFc4ClVFm5Q582n4oxSfsIKst/dHQmiCYjQ0qhauFS4l 9XrSajdfloarhUeHrlSOImtM2GDhOhrUtIYof6pHoa+gtn3RJhruPua65r8e RWgEQ3iJBg3b9bOGchoJf5aWfBPfS0Ob/Q2z8dZRVIx0t0rq0yCc+yjQuXMU fyy08qQO0+BbmljfNDwKH5nRI3JeNMgICd+tECT722zlfnlfGmjab73tRfgo CD6weW0gDV6ht3wUJPgY7UuavYFJw3OL4C2Sa/hwLjDN2ppFQ55ybK+9Nh9z e/yjVPJpgNGTt2N6xL+W37m2vYSGt7JZiDYmfhAwy3LnCxpuTJS1i5zgw+Zg /m/tLhoWXFt1xzaAj+++7T06AzRY9DETlEOJX+bMf79vjIatpsMnx+l8vF9y Ku3AX5Kvz+miVqS/128TNzZZSQejLpxWT3inVxQ7zdbQETxhq/i2nI/QvefW WGyg4+J91dvRL/h4ml45Za1OJ31ayIT7B3IeNvM7bLTo+L7nQN+FZj7+LpSu tdWl41TobMG1HXxoeF5MOmFBh1iP+Df/AT4+3UqJsLelQy+JlipG/ONS42sv h5N0TPOT9+8YJ/mb//O4owsdhfeEFndOkfztWXfQyYOOJA3u9//evzPzMFdx 8aFD6cLatEzih6MpV1edCaDDsPKSXyHxT8aHTMFzIXQ48FJiZIkfbxRq5LvR 6DDXDar7QvR95Yn1Jhw63l+ZUfzv+WVNU7GTW+PoeJl8NMaQ6CrvzXFiyXQ0 5/vUdZHxjOIM33+7TUd52TOre+T/Ppa5zPuQQ8f+wxlnbxN/Pd4ZqnO/kA7l Cs7WR8Q/uwVTr0Q/okOTsi+mi/ilm3J53qWndDip+7n99zz8pElbv00NyV/g q5N7vxI+8v4pt/sdHTbh48IOraT+cctsVzbSkSDL+upcT+ZTtp3zu40O6Y/9 rgeJv0l2mr1s+0qHWkzMvOkyPm4Iesx+MkhHkJyq+lniZ2uV6buTv9Fxx3Ge Z3Qq8Q+TO56BP+iYTIKxO48PNe/nmQ7/6OjK2Hq1N5iPstiuzn1CDLxIobVO XeCTPvLfirWLGGD9eu3DJuvr9RdpC0FJBiQ73GKzCX9bCWrQelcycIQxu0GT 8Hqbks2z6jUMzDLqW65B/GzEi6NK28qAYxJb16KH+Eds7tlz6gxsN925/FjN KP6Wvko10mKAUjKnJZvsd1FBIYnFhxg4SF/9S4j0ZzFKCofGzBl4mE9vmrOf 9LsmOiF1Rxio+kR9sllmFFti/SZ4zmT899FVU69GUFwau9HHnYFqzq5QRsoI tL/cdzx8kYHVHOW0vd4jMFHif5AKZuD5pskDAhIjaDQWEfkVwcC3+0c7Fn0Z hp2Xkm4ri0H8dLn4ruxhnC91vJ+YyICZnGnDxJ5h/OgIHL6WxsAZpmJ75Oxh BM5NWnsym4E//ZXeNs+HwDb+FCX/kIHYn1c1Yw4OIa/DyCfjIwMuAx4HXu4c xK65Z+9GtJL5VMcRvBlAxYbwnjNdDEQuGjzjmz6A955PrTeNMSBDp6T5LR7A 2Bx19fyFkWiuvZsTUd8HlQ2rpx/ti0TQufNfMjb3IG+BZPc6g0jsOmQQ7NXW jS0j8+rYppG49fBe+T9aN5QLxrOcj0dC7FOcQHrfV8hrvrATvxSJ3KmE/rGU LnI+ub84kxmJAzm85w1yX8BVPVX48V4kLiet3qOW3gGxpTYpKI6E5YbwQFGR Dixq0fFbWhmJaa1lXcJt7RA6LbnlaVsk1EWF6v4wW/Hjcmm0lBgTVgUD/5KN mnDpaF5wyDImni1o8dr3phGTmrfPj0oz0d9xZt6kaSO+zWYZVCkx8ZdeWcA+ 1oBB+qmZ8/uZ8FH6deUT/QNcPWwGWwyYOBnp/Fxe5gN6zYya9MyY2FM6/i8w rx5fl6rnrzrBRELatlPn2+vQljzfqfoSE2u2WS0tNH2Po8F/zVWvMiEeouMd 2PUOn05PaCeGMOEvnOwUovQODUrtUt5sJrpeKscvrXyDt4V5r2WzmBg9eTd8 scIrGMXcfkjNY0Ll2K6x5aG1qL0Snz5ZzESNV5l8av9LVGuFBtZWMrEgYcBR oKwGFdU2apfaSTznxDba0F5AbO6Fm+e6mTDozIp5/es5TupEiDoMMSGt563Z 4PEc/0pK+g/9ZOKWTuqMpUMVtLNWJK5ZysJz14r47+7PwOxVWbBcmgXbfR2L pn48xWd5w8siCiyElnUe/EZ5iqsJfubT21gIfNmRmZBdgTJGq+AbIxZOmbyZ m7bxCUReTng9s2ShNWhsVa77YxwXFPny4CgL0aKtF2/dL8Pvq5qPUl1ZCIv3 P1ZvVgqN84keV0JZsOsOTZp4UgJadlGrO52F056CB4XWlaCl742+I5cFt9nX y6VYD+B38q+8SQoL8jLiw/UexXhobt+kUEbi0QlXa7S9j3nMy7orKlno/akt LtNeiCO1rHzRWhZM1s3OT3IsxI99FfSfTSyoarvQf/kWYJfaGp13Eyy4CKyx f/MyDxEXdt+t+sXCnaze6aTTeXBr3LCofRYbmhZDVfMF8lAmvtevXpiN6ZBf 4dURuThG97R6vJSNQvEqp5u12QjOnFmwawUbcllvclcrZiOrmvq0QJqNWI9E fm1YFn7NSd1yR4EN9Xj9RzvMMxEfUD+Pp8KGv2nOAqelGXgWb1e+aAcbrX0G vcasdAyWDPpE7GIjmkVt4YikQ2NK4OtVsLFkX4bVO7HbaHbf/tjVmPx/konL U61b+HN2o8kdMzaeV+domTelQtZVoaPPko2dAnYVmt6pOH1KYrbLUTYmpUrn D+XfxNjhCV0nF6JzTV4vN0iBhNVQQ9pZNoreH6QM9iVD3fyrc7c7GyxvE/Gg vckIOPQhwvEiG0+6dxl++ZeIeTqFrx2C2BCXHn/UnZ6AjVrZJ26GskEfa/ec kkqAicat0S/hbDTHtvZvZcYjSo0ndpLJhq2AZ+WHoOuQU/K2sktg4+7smqq3 9FjsVzzXk5jEhoF4v+WapbFwVnC81H6TDbV2Gn3RzRjkyFjGHb/DhqKXqpd3 RTR2iW9vO1rERp6b9dx3q6JwbPFG9/gSNtbvW1isV8LDNRGFv82lbITYKm3o PMxDlZCEnO0zNkrifz6wiOfC7Pe4o807Es+dLL+Xuzjw/jE4GVNP6qXjXyTS w0bMVFdYYwMbjmFy6Ut5bLTx6zOs29ioCv1lmdjPgmt3wZDlABuJBa48elQk 6J1ZAbxhNrYqrYvVECbn3ufURR/4bJzjKMu1BDAw+Ym71eI7GdeWsj39Ah2B b7y8zeZwUOk23Jd5hYrYYtXfRjIcWAZt87abCUPuJoXtAXIcmP7jzmm6HoYX qRLnshU4EPjhU6K3KwzfmZMt85U5OLVzu3yLXygOuxQ/eqHOQbaRrszjpSHw aE8fn9rNwe15Y0sqK4JBsYxVXqfFgaHhpnwP92AU40p8yH4OGn2jRXivgrBM SsNPx4wD9Zm8cLn4QGxhKhect+RgIvVF9CnzQByYu2ow6TAHEFpYKrwgEJfG ftvOHOfgsKHNqtK/19BY83j3ozMcaD9sku4cD0C0796f20M4yH3x7PCsQ77I 4auoOFI4kFIqbozpuIIqJ/kzXCoH96V4CkqXrmDSfE7zGIuDOQc2f1ueeRlW ys9L7t4g8SxKjV+w7hLcUorG2pI5WCfXsfhsjQ9Cl6VvELnFQc2N0ptX3H1w XyA87mwmB9uUrXICyy5CslX/yvpiDno7l5dau3tjk/nuvMMPOdi59OriAzLe 0K1W6g8r4yBKXf3w7bdeuFi44Ej3Mw6ylll95u3wwkf6650333Ew9lDC47yE J3iaZtMrBzh48u8ya4WEB6LsLc6zhjlQpLX8ZbDdERVs1TdnjINAjesDPmLu iKk50jT8nQMWv13p4nI3xFk5PHgyl4vBIkWHFzpncf2y49bt87jwjB+jhb8/ g/h4p4yMhVz8+ep/5cSpM0j4ciaWLc6F0sa5+tIMVyS5eV0+JcdFS01jUeV3 ZySzLvIbFbjIdn68RTjGGSkFl1wOrecSX1/+XHSnM27+8LNR28LFzUmDZQeu OSEtNGSnkCYX17WWtpySO42sG1HTmTZcGF/X/Wyb44Ds8pjzsse4UG/o1Zxz 2gE5XXF9XDsuOjS+Fk1KO+DuhsQmfycu5kZN+cdwTyLv/u0Hxt5c2K+7+cdK yh55TRlbn13iotI+Kb0u3g75vzIz1P240F6t5/C/1XYo0MmNXR3ERWhn06r9 W0+g6HXx5W9MLiS+iqUccjmGYn4J34nLRcGBINmtv46iWLzUpSWaC9M43YsT zKMoOVJuU3mDi63VaU6/HtviUXf1zugsLhK0f08vUjmCij+fpne94CIo/v60 zmlrlP09YOj1kgubmKC/75ZZo2RW0Y3s11wUGuj8iaq1wr25nL2yH7go03mU lr3DCkkiBvQ5X7g4lvomPWCFJeJFH7RrfuXiufrM7Y0NFogRW7ftUi8XSSov s/s5FoiUnN3QP8yF0CST4SdqgQDph7Jvf3LxosE/NljCHFdk13sKz3Bh+OnJ GsUmM1yUi67UmUXOoTY/y6IEM5xb6+laKMRDnETqJGW9GY5uUiqIk+BBeW2i +kqeCXZrXtdz3MwDh5cdIuV6CGrawnE3tvHwZ6hh3G3+IWzT8Rls2M7DPJkn Kso5htiga87S1+AhlCKRVj1lACmj+c2bD/Iwaqlaw4/Tx/djvm4/TvKgufnk d/OVBzB+ou+Jymkert/r0cp4p4dRe+sl51x4sL8WFSlO0UOPo0pxuzsPMXf7 E1Z818XHcwP/nvnxsLbTTtSraz8K/G15kVE8zH5wV+hN/17IFI13Ksbx0D5P IeJZ+l5EjNK3VSTwINSwbHOV017YOzx5M57Kg98DeevmXh2IHFSYdySfB7vd oto3BoDLgWWHv93n4adiq6qJD9D10Po2jZzjmX33b9YLAA83Rex7XM4Db8ma JdsVtOEsPhIg/5bkc6Dawf+KJuoOUV6V1vHwNUdXa2CJJjTDVq+0buBhj1Ml dyRnDyR+mD8Ib+OBf3mTTlKfBirai78ND/JQKSid1euxG6syA50fCEdh0V1Z xdxydVC6VhSZLYxCssaWKfp5dYyvKpwzKEq03/6fyXLqqGH2pEgvi4L9342q hyk7cOmiYWvQ2igUefhd9bRXw3tCvEZ7o9BXOpB4TFcVe3zvJvXoRqG8JbTM SVAV6QUHRq7pR6FSw3i1XbUKrq7zpeWbRmE09OWJBSYqUF74uWqZXRTUHu/c OOC0DdG6lyXyHKKQ/qXu6MzmbZh1TeyUgVMUggeMc5+PbEXT2L5//m5RkDIx fLNh2VbsU24zXnohCgXzz48U5mxBrqPPjVzvKOwR1I2v1t2CFYmiQwcvR+Fl m0Lcic+b8f++347///32/wPpCPfc "]]}, Annotation[#, "Charting`Private`Tag$2743#4"]& ], TagBox[ {RGBColor[0.528488, 0.470624, 0.701351], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUm3c81V8Yx6WQSEkiSRlRJJSEcKysInvvvbJH9t7rGi0hI4QyKlseNFDI iKLsTd2rEKH8zu+vXu9X7vd+z3Oecz7vx6vYLV01bcjJyMjqKMnI/v8zcqhY bNI/AygP+wY5U05KHR1tWCnxzYCJgUAzB5VJqcfT3cUeXhkgpMStlJAyKfVm ZZVxn0sG+N2IidY6OSVFQSP9i9siA2SaJvelKk5L3aXXKiGZZMDDYpkm9TvT UtzMtuZ1hhlwurRu03JmWkrhTGKPsnYGCO/cId6LnpGKRl9KnRUzgKZiQvDP 11mpYwrLFpflM8BHm7Z0z+U5qaIb/5j/SWfA16zTfakpc1LvDLhiUsQzIC2P 5rqt8rwUpZeb1XP+DDAepL3wsndBKubJftZNhgwIOGHPeeDydynmihMDLYcz wDt1g1Kl9LvUk+oL8XEHM0Av51LLffYfUh1t2pssVBnQV2zaEH+MKLV/NPeT 5FY6mO1NCfE4uCJ1f/pFAuVGOhhxp7KNq69InV16J/txNR2id/P/Bt1ZkVLa +F5p/iMdhDv8qB05fkrF0oslRUykw2mT6DPF139JMTPfkL8xmg5nfzxqU3/w S+oJm9n20ZF06NbLojJb+CXVwRflUDSQDvNO3xTfxq9KUSv0Xet8lw7H5ep5 IibXpOL9Hf7RPUuH0dhrx7NHN6SEPjl6p5Wkw8W/jCEk1U2pL/zO3xmL0kFe SsoiuGVTimfSZYT1UTq8mL95OuLpH6k3il41vKnp8FbfPTE9b1vKOc+bvzwp HSq23qxdPLMjxbDt81goPh1K7ZNq/cp2pCzL/dJEI9LBoKd5ULTlr9Tu0RAX Be90UOZOYD1OSYaKXEJnO93TYYTst6eZFhlS6wgzVnVJB0lDpg6xfDKUFRCp om2XDgRil2qP/B4kPhXHbWmQDp6FAsLBOeTIqyJjLEgyHYr6X3tuP6VArNR3 dfaI458/XW0txEyJXlve64oUSQdecbkvRVGU6MixzIYEgXTQVHD8FGlHhSoC H919wJ4O3K/avVKUqJHuUO7Bk2zpEJBSVCrTTo3+CeRH5rKkg4f7NY1CpQPo xvRjj2KGdNgsG+hu0aJBS8qlatUU6XDGxUyfLekgSi0oeytKng7ey2vyApx0 SPTvU4mmf2mgPrKNApvoUExlBe/rjTR4Nyx8lfnPIcTFVE3Zt5gGEGxTqKJG j8xmoPl7dxr8O3n0F5/6UURrpmNU9j4NAii0ao+/OIrqhpc2HNrTIOulbR4D MyM6/JFRaL4lDbhWDiKjBUbUVu9UMPkiDQwVfRPvFDAhF+E90rmVaZBIrxiG mwexVNz9ZvosDeZd9S8YpjAjz8etjN+K0mBXd/QsZ9RxxJXCFDv0IA0Y8irp 8gknUC/1M647d9Ng9mnjYiQLKwqMlG3VSk+DtuUTx/WKWdGg362t3sQ0oO8y tT70/iSKtn7t/CEkDXy7pQ8uspxGC2KuGi02afCxOL6Q+xsHyni5jxhsmQaV HenKvJKcSFogM17SLA18mA1V1HI50QOut68b9NPgu8JqAd8tLqRy6IRI9fU0 aDfUetfEwY1+x1X2eyphPtknIHuXG+XvU3C9eC0NvhQFNBrQ8qDtP25PKqTS QEyA0T6E7Cx6OvOOpVQoDejEddKCD/AifTPjWvsLafDK+kOrUwYv2jfyU4uH Lw0yJWxofNn5kMlH1qTHXGkwl6p+8Mq184iuwWM3hykN4rMa/j2uvoAahPdn mRxNA2mG+qZ2QwFkW5EtykqfBmuTW1UjewQRPO5wf3AgDfr9Gp+UVAoitxS2 mfS/qfi+qEwR4bmIeFIbhy23UmF0X+9Dq9iLaCxN/6PQRipk6ktPdC5fRKp3 0xo+rqSCyex91YD6S4g3mzKVZiYVuFRvJjJ7XEaTOQXRIxOpoLomU/Zi7jK6 nysdWDKKn3e+kYfCVARRPfa3U/ycCk+GimWP6FxBM6VEyYj3qbDy9bDhlK0Y evg04ZJmeypw7L2VKr4qhjTLz55jf5MKt1JMm2fCxVFrleVReJUKjYV7gmOe XkU5dUNLW5Wp4FcstnyHTwrpNnhOdD5LhQr3d6zUg1LoYNPhofulqXDjrmwQ IRyhQFBpFXmcChn3mZTPeEsjg3fN9zzupcJuVbNn74YMOtxhlCSTkQpdIz9K PUxlUUfnZvjh1FT42P245n67LBLpvuhSHp8K7y/2TFXnyaGjn4rkl4JSoTjM lCjqew19GJQTr/dPBZp8v29bq9dQ+OcJgVjfVLA94jMz7KmAfo6wnOB2T4U7 PZ9PKAYpop7J5J8W1qnQf965zbFeGUVN880LWqRCEYPyWLaGCpKY7fi2a5IK z1RTf1b8UEFlC+Qd2Xr48+NDDhNCN1AsySdnWCUVJr+Jm1f8UEPoJ0PGE8VU KHvJ4E//5Cb6/asyzlc+Fagy1W8/vqSObH4veTFKpUKvu8WO5ZY6kv1rel1D KBUkggaPHHyiiQ5rLpF95U8FSdYD6v5cWmi8yLvGmjcV9gTSbfg/1kKB6ons tzlTwXXpu0BZhTaqKajfyGFMhU89/qIXf+uiyE35Z2eP4Pc77yjzKE0Paan2 Wj6nSwWnSKbrhZf00crvue63VKlgkM1LfizSAPGqHH38/Q8BtKsD/9BYGaPN nEcGPr8JcEPioVHDWRPUvsp7iGyVACQVDn6jNRNknS3jz/CdAP+SD3WiHDN0 8VeXQPYCAUyYivb7SpmjPYr6s9yzBNApqV8XqjJHOSsu6uJjBKg9OFevlGeB nK9tUbwZIUDPM7kjU2yW6GpmVKPqZwIQ8y1uGOZaoi9yWdwWvQQwarM0da2w Qkfude7EtBFAWjqLhp/cFk0saz+nBwKIPz0aXpNviyqkJ+weNhJgvexxoKaS Hbqx9Lu//CUB5kKElm8X2CMWFB4rWkWACxEfJK0MHNBi+kGptmcEuJx39s8p RkcULclVMlhEgKXRTq/ZHCeknVZhalZAgLdZXj0mt5wR57z40cVHBLB12rMS I3sLtRA0QnbuE6BAsOf+4h5XtDUdrMOZQADOAEcGVhd31CF6gOZZDH4eZ05C 26o7upd0p0UkkgBXXlf4fAvyQMJXnvKpBBFgIthe/GiuJyJPvDI54EeAxaOH BRNEvVDfRNtdEx8CHN79+odnyAu5xA/vcXclwLW3ptsP2H2QxLh17ZYTATye 13z8/NEH0QivOEfaE0BZRmKSNtIXPRml/HLPggC3LzXnK+zeRtOCwuXNWgQY H9pmWFYMRDVFWnER6gRoNQiekD4ZhOJZPa2VVAnQ+O/sj3t/gpDg/ucs/QoE qHgeflijIwTtC+5bvytHgEeF9i9zTELR59WVXiNpAqzw2o2f+hqKgscFYmbF CODKsig3OhWGNHVuWpaKEEBkf5q7461wdOaDi6TrJQJkPHtb8ngnHHXVPFvd PE8AmDo/9+lcJGJJ5jOnPU0Ar+5Os9A30Yi49/rVPlYCRIuYs7/zi0Gtfo7H 7h7H+zFsVaR7ORbZ25R0nWIggGromx8aLXFI4mtH8cwhAmjc9JCTJsSjQxoL 4SW0BBgzH4dQuwRUI8EjdokSf5/9F4pT/Eko/rnC0U1yAqxJs7EysyajBvWu Mb/dFCA5dEhkMqQgqrMq15N+pYC39Mz+D8kElD90jevllxTYOEizd24gDSm3 RY5I9qeAKm3X4TKPdLTy7DWh/UMK7IsVv6jAlIGkomT+jjSnwPrlP9dXPe6g WbfQF9Z1KWB/xfFmNO9dlGgMDsSqFDgx/K3p58JdNHxJcmhPYQo0/AzR8gq4 j0JPBSYm5KRAXeV6F5f6A8RN0yjLeB+/j7dO1sT5TOQ1JVpxNiEFjpZ/KhjY fYgOpwrH3nRPgTO2E4+2D+Si2kBPqWHHFPCbuX0lOzMXmdo/X7O0TgEe5+vS nwTy0FMkaOGjlwIlcS7aG075SIvPlYlMIwXMJ+gzrBkK0Nax8u44lRSgeL1v 2aG1ACkR+cSzJVNgVmKdy/xiISINO65wX8HPI7R3L60XortvS4oqBVPAjJRq IdNahGayeBjecKZAgtvky6duT1DIdc7vS9Qp4FYidaZP4inSHpXiWCJPAaW9 nikLZs8Qr6uh/uJ2Mgy9eiAxnlKOPqWlvpn/kQwXHMQ6nRMrUSnXs625uWRg ZxyySherQiE1HYJz48lQ5KPh4kmsQrwju1kzfclg3fE2b8DtBdp1OjEw/T4Z +DfFSEzoJfr0V4R6+nUytIlSC+Ucq0Yh7C7ek9XJ4Ps1Xe/sdA3SfhFXNlGe DC76bxwYhmsR77XCyfHiZDgpvfSTbqQOfbL/pjr2IBmOviieEt1tQKVbGxGj acnwd2n/kCdXEwpJZGj4lpAMkT+qb37RfYV4K1W4vwYlQ1fOHuQ4C2hXxtZ4 xCcZ8mbKUqzzWtCngbC0YddkqF0+undErxWFbNT9+2yRDJePRf0wHW1D2nGf hD8bJkNp+4/mY89eI94TK45DWsngI2L8bSbqDfokxfP50zX8/CcFgxza7xBv 9J2KvnPJ0OnC+GLA+T0iY66a7eVIBtqzN2XHkz+gwZKuE70nkkFoLV6ooakL hXbvje05iNfj2G91XPIj0jE71dxNmQxUTTZHmJV6Ee9P8bWu3SRo9osvYN3s RYNHPcw//EyCjbwVeTLnflRalHT3/VISDL/MekUjOIBCRUu6OqeTYK/z2R/z WwOI13hCtGMwCeRXT+ucLxxEoQVq9G/rk8CtyDv4p8ow0rnsqPjmeRJcTatb fSk/gnjbo4JelyWBbNSt6/nyX9HgUtNiazb++WQtp1mdUcR7ka+tOSwJDFq+ s80OT6DBFirPOuUkECsVvtbqPotazC8afZFNAg11VtJ7sjn0lMxEbvNqEgh+ qW9WS55D4dLPGUQvJMF1Gvvv8gXzyGXi27YeTxIwcBn+3D63gAxCqWZ8TyeB 55akYt2zBSTYYvyy9gj+vs82Yr9KFxGreUzWZ5ok+FVWOTnIuYSoyJ5HbuxL gkcL7FaJ95fQGKLSubKRCIfoyW1jvJbR+3EhSb2VRKAMv/XR4esyqg4xPuO7 mAh6rid9jSS/o0SoWq/5mgjPEtuL9vz6jm6bfRsd+pQIm+OXL9yR/4Gsdinf /e5OxOsvy1xP/YHUHgmVH2tPBI7AK/NnRn4gcWR8V6QlEUZPG1wRPElEZ8aj g3XrE+H9+rrpGSMiOhxSZevzPBGoP0cZs2YQ0Q7bN7W7ZYlwq7CpXaiDiOab Ka/UPE4EZS8TsZgNIuo3FTo1lJ0IxcL0FbIcJNT8z4jq991EiO57/iNJiYRK cqJJjIREiNITnrvjSEIZUlWfL8clgv4B9ZPxsSQUOvYVdMIT4V83iSUrn4Sc gimfeAckgkPe6vi/OhLSZRMi3PFKhELWEZu5DyQk22x0u/pWIlQzC52N+UpC F0yjzQdtE8F9yrGOcYGEjv+rVFo3S4S9MevG736S0L6cr4KMBomQ2efe2LVJ QiuSlMcvayZCRvJuotFfEvo6KrhH53oi/M0zNX28S0LvgowWveQTgbv5if5n zM9PRvdlSCaCo2LuUc5/JJT9qrL+pUgiVHS4+LzcIqFYk695nwTwrrTEpNas k5DXX4r4tbOJoO1Rkq5JIiGzbEGPoxyJ4G00XVMxT0IqkkaGwicS4c1PW7HV MRISGY2S1T6aCOH0RAPpQRJiD6rk9TqYCCw/fxjUvSehzSaK7Re7CSB3+Qrf 4xckNGMsOD2wmQC5pr861ItJ6OOO4YfVnwkAlY83HmSSUJFE5cNLMwkw9yfj kVkoCWk3GUq86EgAb2Lb+JIKCUkbR3ENtCbA2c/9g42SJMS3U0G72pAAKFev p1GQhMglKEYvPkuA74k/5nyZSKiisSLoeWoCHO90JyMuENHjbPIqpYQEEKgf SiIbJ6LMEJ2ZscgE0NvWmvUZJKJIuW0VmtsJ4HrO/0X2ayLyO6MWnOeeAHX2 dIrajUTkQpVXdcUpASx//iH6vyAigw8KzNamCfA28OrAqUIiUnv24PqWXgI0 zWi/yc0hIvmU78EEDfz+b6Wl790nIjF39Jz7egLwFsW0700nogtaabNN8gmQ Rd+YNJdERJyXZ5m1pBKg5apSCIojImYm0RuLVxJAg+m4Al0UEdH9iQ8JEUqA 1V8xapphRLT36+hzRr4EmJ8K+nAgmIjrLThXxpUAIx++NogEEBExJ+K4LFsC fHr4Z+HTbSKaDh268YUpAQ6sZq1N+xDRF8tzoS70CaB+j0rT0puIuuUDX+yj SQDyWGc1NS8iauP+OJe5LwFuniw6UuRJRHX7OViE/sVDVO2ZIjvMz5a8VNs3 4qG/z/8nAXN+V3uoyc94yNZoajmFP3+/nOXl6lI80Hn8ekuPn59EuDUfNxMP ohMUD63x94d7tLCcHouHcEqKN4z4/Xy1GdRqPsdDgNWPSg5/InIWsQ270RcP rCfUIDaQiCyZ619OvY+HN4qSEtdCiEhvi2bh9pt40LzWaKMTTkQ3vpmeONQc D6VXlZ1rcL1km6vUCmvj4eyytpcNruf5cL3qvtJ4oH7JNJeXSkTs1qULdo/j Ia//kP25u0R0TOHviX/Z8dBJrcS2mklEew4UhPOmxsO93gQ6Gby/v5fXq1vi 4+Fu7StBKCWi791Ki7qR8eC72GvgWUlEQ6nEmxG+8VAsF+Pl3kREZcfFT34z iYdz522qXIaIKHc7Ud1DLx4O1MXsURwloruj4xH7NeKB4tmjQYkZIgrNi1oS lo8H+mu7u16/iEjnXF9tEm88zP6pcXpziIR2Re010UYccNUmvLK8TkIcrfco rq/EwQDDiY96WiSkoNxep7sYB7KjnySvGpFQsgH3KZevcWCPtLha8f3F6j+z nAVxUD0kfcMP31/S5EcfPamLg18vVn4TUkjIOl5O82VVHDw8pMMUdpeEyjLz 6z4UxEG6ZXrwZAEJiTeaR23FxAHLHZEPdk0kZCpHEKUMi4NbM9qmVG0kFP4B lun944C6dCXGtZ2EOr+yaZ5zjoMDj7UepfeR0HcrNYrLNnGA3mn03hgiocPf g+qkTeOATe8kW+cICenvfGPTV48DWpn8JsppEgqMpO23Uo6DJI+dM+/mSCiX ViLKVTYOjCNkR+WXSOhNhpNowNU4cGipEQz/QULzrA+Xo4XjwNc3PDZohYQO FL7PSeOPgwtzqbYiq/i+5d/SyOGOAzdqMdun+L7TrD5HUXoqDgw9J66Ob5CQ j6RBXTVzHCxfy3vZ84eEMt/GOrXSx4H8td1q/22cD6p1bN0H4kAnSVZyeoeE pgbn+77sjQOXJW6z/fh+pTBliprZiYXj5dyKS5jPzimIrqzHwtnVwCtx+D6+ 4eKzvE2MBfWHAzGzmN1+F+ZQLcTClq5m4S7mjOBBDYbJWGCS7KL/grmOkoLi 1Egs2Hz5ZemK+VuycB3vQCw0cdPKvsPPJ2OydhLpioVLQXucRnEecD5KZ5N9 Gwt72JbLqvH7KfC87lNtjgW1TLGZm/j9HSt+RRrUxsLnpb97n+H1JV/hELWp jIUIdWeaHrz+56Cx7FYSC2T6Y9QvcX2GFMNyAvNjIVdM7aQ5rt/Wx0qN2Iex 4JP50H0A15dNf2JfRkYshBLz0SEiCclMHKp7lBQLrkGPuo4u436yR05l0Xj9 mR4Oszg/Yldc2GpDYoHz/bZ7+AwJ9ZL1RPa4x4KJVqodzygJrcX+vTLiGAuv u1QkLg6TEBM9//KsVSzwNUerHML5YsqeqPFXJxYC+CNEFbpI6IeMCtt58ViI sSeUDuC8ZaHNZy2/FAvjB/J4fuO8URr6wyLIj/ej5En/djkJPXYsYRI+jdd3 /z1bzWMSMkzfTy9BieshyfKSFvf/u5l3e2/0x0DymuOUuzl+n3I28p4PMdBP vm/EwRDnm58PmfrbGOCl6vE21Mb9eZD7r1ZdDIRqnirjxb5wUSTqt1FODNjm /CkpESChRzFyi06OMWBQPsJ1dpeIujQezv+wigHvRBN7sT9EtHViddbVJAbM 5EqidFaJSLcyf8pTPQZ6tWc5n88TEe3wnm8BIjHQyTgXeayPiMQLDEb+CsTA qO6o9v0PRGR3q+pLyLkYqG9dOnL+Hb6v91gMRrDGgOS+k56JOK9u87b0JJDH QO143tlrxURUtMbUfXAnGg5X92w65hPRQLPrh5T1aHBa8rn5JPv/PDrVkb4Q Dd+nNL47YX+aCQhufdgTDePHZDi4I4joiMIQnOyIBlcnx2QmfP+iwxeaH7VG A6H8YgEXzpvMx6MNBS+jodC+3jkd54FGt8TLssxoMB/N+dJtQ0QZhQXWahnR MBfZnVNjifMn6ADjz6RooGI3zW4yIyLzC1+8RcKiwWSw8yK7Ic5rSsQ97B8N Rp9yL4fqYX8bKxwK8IqGJO01pb/aOI9TPK+02kVDaGm0oqY6ET23G5m3ssDP u/nPn1eNiNaRzH1Ko2g4Lx96k/0GEYkyP1Eq0Y4GkRrPMREVIgpcoftzXQ1/ 3uygpJMSEbV0eJcQFaPha5ltYLMCEe3L+2aQKhMNQzX+JYLXiEjJT+6A8NVo OOBk2N0qR0QJGqUNQ8LRMFlN8cNdloh6ztE7+V2IhuTbL6llZHC9yG+fYD0b De/5ak8LSOP9HRn70MweDZQSyXwSCNfr+bVAixPRYLPGddpeiojG4p+e38cY DRy/01eeS+J8smIYLaKLhjEV3wRWzNZX/ZOU90dDOvP7r48liOgJw6Tk9z3R UEVk7ryO+fuyIjF5OwrGblteoccs8KY8R2g9CrLvuVKtXyUijyzGm5+IUXA5 LO7YBuYar8Bdn4Uo6O3vlmLCP791Y7ri+FQUGJsc1dPBLHVGxbzpaxToqu2/ VIU5/G/lYbPBKOBwVizgxe/zdpCpdc/HKIgeuO7dinl/ebD7444oeHPrvqc3 Xs+N6Fl2xbYo0Jios1HA6yWY3uhfbIyC6hC1w8K4Hp9EXoQnVkeBUOixy1K4 XsyHWC4JVESB/8KRdGtcT6P50Om+J5gfBMwV4XpP3VOTZ8qKAjGVLfVgvD/c btVr9XeiwPLEhYEjeP8clFgLjVOioNmLi71NmYhWNhcp8sOjYCehdsRVlYiE +9Rr5AOjQE7CNvvWTXw+Smpt572jYCHw7EikBhHtGkS1n3eIgue3RXT/6WB/ uPjd96NlFDAnCYyY6RNR9AGtsx7GURDAGmcxjPuTrvF0XO3NKFg7dfb7EXMi YmVtUpEViQLBhwMPM5xwP69xbM8IRIGTP+V6qQsRFXTFlcWcw5+3oCMfcici 3iA92m7WKMhJIrtlj/1HbOxXt97eKHh1ZyjPPZqInhqL/HPdiYTDZL9q3OOJ iO2r34XY9UiQ3j5YG5VMRORfyFLq5iPB/Wfhyhz2l/d9dOrHuyJh1/7xlcAn RGT4lrd/JCMS+GPUh417cL8/tRwy4Y6EoJ0yK9bTJETkLaL0ORUJJ1rDbVXO kJB5yaJIMnMkUF/c0vLhJSH5Ird7zQciQeeLP/9bYRKizQ3WP0WKgJsb+7v5 lPE8kZ45MlEbASezxGpj3XCeHxk78KcyAg7HXTC/5o19gMB+lb40AvJ8XAnr fiRkm/TkoUxWBBztmLxwIQLncUyNcX5oBFBITkesZOB89e8fs1KOAL6ATgW5 auwbV6UMf8lGALXcwpM6fL/XbJcMhkpEgNp1B1xqEioPDOvKFoiAVT/22TLs HznBgg2fGSOAc/mz6lwPzgOUddn2UASIFZD8XmP/uLtLVbW2PwIuy1DrJX7C +Rc6Xky/Ew6+bx7yTOC8CQpPvnN9KhxocuM/x2H/2JTdOjzyNRyqQu7zN8/i +WivbaL9YDgs73BFfcN55hwpGRHVEQ7Orwj3hnDeLciX/GNoC4d7vMLUz7GP WFMw+uc3hoPQ1Y+LPnieMo7+7gbl4bCd+Siq6RcJfVHQ/676JBzPb2SHJNfw vEP1xu5bXjh4xRQUFOH87W0XmHZ8GA4ftjeE/vzG/hD70PRPRjgo58iUCeN5 sEOJaiQmORwqJhv3GuA8l6f21DkWi5/XHXDRFs93LZ1jvY/DwsGDGCtkjPNf Il7lxqWAcJiTrPwrjv2gTqWmvdUrHPblPbtLjv1BmIZDTt0lHPjvHd99jrny Q1LzmF046JOrSNzAvnE+8Y/YLYtw4AI33R7MT27YVG8bhkNvk6++GPYTroN9 gvHa4TB6j0U9CXNut8RTZrVwcNnXpfoeM2vyE55ixXCwrSqwXsF8X+1owWWZ cLCUCyn933+OHgpleyMeDh2n31zZxEz4uPxAUzgcBnSSeEYw0xL0GCf5wyHR MfheIeZY9dcEV55wOFXcUWyIeR+9AO2/0+GQ/+BkwB/8fqF9mTGJLOGQp1Em Eo55O5Vy74mjuB4vmMnX8fp8ND2CSw6GwzVnUypNzL+OjP25QhUOOn9HPR7g +rgMKHu/I8Pf76jg+QHXbym9ekV7KwzunUkVW8D1tdVmd55eDYPkzIVNEq7/ 1NGkefcfYfCNv2puCu/PyB3rseSJMLD69pI/Ae+frm6vwcmRMPC+e2VHGu9v /zGJwbIB/Hn2rOkp7Ffv7zF0dbwLg1n/a3+XsV8p6Ico6rWEwSFt95dauH/a mJfbZuvDoK7/RPIT3F8ND9rqyZ+FAWoXf8eCfdiajKaasigMpsQNXA4tkNAh O63KA4/w+0R63yDh/rUWnik6khoGWQf3inpMktDBjxQZHN5hsEeVmonwGffD ZbUUbpcw4K+OK13E58My6248r10Y2CcIgVA/Pn8OPGEXDcIgXWFOMAX7l/k+ ZRdZyTA4xv1iKqEF+7ZTqoOCSBh4cQqy274ioeq+YWsVgTDoHKuPv9iA//6R o5Emexio6B9uL8B+9lIsUcmSIgzodctt1gtJiMr1I0d4dyjYxZ9racPzyfNB Jrbod6Hg+fnrxp9IfH4kzI/HQyjcvLPMxxeG+5P656G0qlAYrKIOCcL3i+Hj I3/z7oTCr2QHb5IDCT0b1vncahIKFU5R854qJFQcW8e091sIpFDW3+M7iP3c w87jRk8ING9I7Nynxv1sdKz7TksI5JHF8NJRklDpBa/ws4UhwJtTLU2P/a38 k8APVZcQWDvkEBPxE+dr85jiPfMQSJX75StKJKLK4qT8Cc0QON8h82ZjCfuI /7Ke55UQ3D+aWXfxfFdzurjtPlkIONlc4jH5QkRXDuienPoVDO19TaPOg3i+ Xt13m282GIb95U/F9RNRwztL/ubOYNA4/kBioYuIXjmz3Z9OC4ZBsXhdxTac z7rdv85HBcP4qYS5ViCiZhSo6uMbDJFzM50qr7DPHBkhpzYOhtpjEzdj64jo Td2dWxfOBMOYMI9lbQURXcuX7/Blwt9XlplX8oyI3iWscrRSB8P5MJ+MsjIi 6jDV+KJFDAL5h9FnxrE/KiuRXcqeCIIKWcX99EU4b4Qqkub6g0CZJ4hH6zER fdh3UM6vNgjGqPPS9ufh/Cc2ZreVBEGivvSxwEfYfz87btJkBUFtSPk1shzs S6Udz3JCgyAl7CvF1YdEdDPDd/+CRxCUf8po/fmAiHqDuK2EbIJgY50hpP4+ EfWrRzK/UQ6ChGFh+UCcd1rilzwPSgTBsXIFR9872Cc4p7p1LwSBjCvbxwjs rzoHU8/mng4CCgq24Lx0PJ//RhGLR4Igmfd0WG8aEelNEEcvUgSBRUrQxGHM XzqzRQM3AkHhEE2BZSoR6b+4kf52MRAcTI/3vCUQ0XDW9g+6b4EA+yNtxDEb Rpcq6fcEwpGBB04tKUQ04mpQkNcSCE8fS0/qYTYy2P9v6XkglNB8fkuG+Zts rb5wYSAMDaszNeL8Njlv+yLoXiCECPP0R2MeY2Ska48LBLJ1+59WmM12X9sf DgyEnNfFLpqYJxY8Xhu4BMJbxCT7P3vperxMsQiEWBeaSgvM1G/cC99qB4LH 3kT2UMw5Qu53txUDwcf7Z+IzzBcfucUIXQ2E4+oJ84uY22ndbttdCATFuvtn LuP3M/Z3dchmDwTni9riKZhX5l0MB44Ggk7XT6ZNzFE6Ltep9wdCW0NehSte P8vrWxJoOwDIrsb9XMdcLniL35sYAHs3e7ricf3kcpzZyiYDYMykSODC//Wl cT40+SkAGmj5qSYwO/s5kTF1BADr3iyUi/dnz7zjzxuNARBgdfaNC94/3jaH gbq8AGglZBiI4P1uFnB4Q8wIgETBoxIC9/D+Z9tXc8UGwMn8tYMiuD8Cb9vd I7gEAFNbOfOtTCI6PGcb+84iAJLuPz2RjfurUMvWb0c7ANg7NfNHsnD/XbAx sr8aAFfcf70Jwv1pmWV9I+dCADQbfuacziWiDWpryU/sAZB8UzFRB89Lp2ct T0nvD4D+80d+mxcSkedD82mmQX9QYZixonuK/Zfa/JNqhz/kMPVd/4LPU5aP 2duIRn+wiWQ8XY7P2zsN02JSnj80KLWRAl9g391v7NTu4g+ULE7l+Xhea/LS W/XZ7w/bujq6C91EpD6lO/N02w9+R/1dN+4lotmbuoNTRD+gkQ6rHsH3Ax2f Tq3aoB90Dqd3rnwmIotJzQDufD/4c4/+YdgUEVGqqe0duuoHezlPtFHieXOT imrtN78fCIfqXRDeIaLFVphhOu0HPf9OqNn/P59eFnpnsM8PWpbmA6cpSCjt 5NG40a7bMFQ3cf0kA573fwzTzZrchuYHd78bXiAhkUQblrUQX7hQdGuxzwbf pwpsNIwevnDmEoWyFL5/j5N93r5s7Qu7m78Dip1JaMdTadRXyRee3ss47eqJ 88yIL3f7sC/IWBZ/eR9KQmp8P8/szfcBZgl5JvdMEpKeLTnGleED5B9p70Zn k5DQI0uqa9E+MEp3TDAjF/sCw6eFaEcfMH+omn23COftVk3ZgUs+IOUSPir4 nITs3gcKHXnjDRLOK4th7djX9kfXnar1hrhcRuXeThLyUEhB/KXeME7VpX0U 51lgW56qEsEb979RS2Av9o+Gdw7Bxt5gJ/MSvf9CQnc2P64k3PQGWcmjOq0j JJQpMuz7QNYbjvBPfnj6jYQKny9HvTzrDX+pUlTMJ3A+lx7OX1rzAr6/ms2X sS/CwvFzm/Ne8Kk05UAXzuc33JyVFF+94BB38lMdnN8f8y83n271gnZfwVBZ nO+fJqSuXXjpBQ2zbQGFRLw+NqWuq8Ve0Je+br6NfWAm03BEN8kLOqbtY0Ow Ty5+sbKwDvUCH7W47GfYJ4jHbi24e3pBIvcp2R7sl3/SQn4nGnhBVdva8hz2 kX+9sUGZN7zgd59O99gG9qdDafueIC9QbtD43YH9hS7h8ZHXZ7zAEZ2f8cS+ w9D57EEvsxccXg1MFsY+xExVe3qMxgt0n6tfn8fMdq2lePmfJ9xM1TqciP2J M6Lzwp+fntCfZPGJA/vV2db+aspZT7iUFJVShvnC7leJo188oZp2U5wb+9kl ydnX7B88YesGV18aZtEAoopAsyekP8hX/YlZsn6jT6LKE3RPX30mg31PdoPM QOWxJzjfXPwRgVnp8oEJvXueoHJ5gK4Os6ong51NvCck77l+eAyzZhUr0SPI E4LlP62uY9YnnfEOdfMEtXfHm/73TxN+gZ0kK0/48mXXeRuzpZNoxENdT1j3 i6RZxGxXInOgRNkTXmkNZ3dgdp5XSa2R8ITNcxp8mZg9zmgzvxHwhJwi5yYT zL5WJo/6ODxhp/WjIQPmwDxb7nFGTyBGiNE34vWEj7s++77fE5re3V/Wxhxz 0k94a9sDrrqt/p7A9Uk0Cm+kInnAJXUnGTPMqQ8SZBmnPCAuU2rkI67v3c8Z nRyDHsDz6H3fRcwPGXPUBTs8QLffXywW70euVvFnyUYPcLk2xNmL968wtdL0 erkHtGt5PT6AufRj/ax+ngcE31z/eAX7a/X1rlXPGA/oOhcQ4oj7gXko2d/Z zwMevmKvNMT94m+uscfGyQOmD28+uYr9Vcp7iE73pgf0xxnd7sX9l7t7/46a jAd89ejPiPxJQuTxRqyKlzxgNleHghf77LuciXOiTB5wYn9xoDLu77PnCioF qT1Ageb9wGs8P8W/sLlybtsd7qRHnRLE5+Fmx5I8y7g7OJkMyo7P4Xnp55rZ TpE72ElYNmWN4/kwsHZu7b47FLAJvigbJaEsSv9bP+LdoYbmMnP5V+ynJ3b9 x1zcYcPv198k7LeL8tR3W0TcgWe05UwLng+37p3sinznBg38fwVON2K/5JjQ DKpzA1fCT+tQPG82P80f9i51g5trQxWf8Twa3sozb5vsBtYxp+OdK0mIZlmI XFnXDbTi6MJEsL+KBia6sXS5AsX+IqvoJLzfHaNKfDQuIMKuQL1tiOcdxkds j0i3oPCnXF+vHq63pfnakU+3oEtgQqVIG5/XnalHW1m34O+AvZ6GGn5/oYXf nRduQQpJYLZcBs93mb8e22s6A9v3YBk4i/9+/oX/NxFnMI9uIy/H83uQsLe6 +gln4AoMNc/lwL7es7F9ZcYJoMJwlMCK6733ryaVjxO8OPb3YvFhPE85U+0p euAITq+UuUdwPpyt7xg6HuwI141GBE5uYD+kjH+aZOkIH/Vd5ezWiCg4l1bf m88RRkS6VOlJ2A8+0VfIv3KAkMg359uw39JyDETW5TkAj6VjhyzOn3OuGYbn ox0goJ5y7sM4zldqJsqjNx0g8aKyzuYI9jVJVpPpCXtgZPjysLkPPy9+9KLe W3t4/sVtJuYjER38krP/Q4k91NILbxjiPFTwYH/53MMejOb1Dp/qxL5cxE0T vs8e3j8U3+Roxc9bnZ9YX7CDbaWyYCnswz+lS2ocuu0gWSVkxhr7MO9XPkuN u3YwRKvT2V+P8/mQUP3ps3bAfqXmjAjO4wnr9MZbdHbATD/6820VEXE1rL9q WLOFRjaa32aVRPTUuqFNu9UWKKfq1p7jfF+pZ32bV2wLrvZVR51x/gsfCmkn JtnCnHFJrQD258Z6ua5YQ1sQS3Z5P/SEiP7RFfUMStvC1O0Iwwbs07LW+/s4 eGyBWMBV/uR/n6brHmxatYGbQ87Dhdin6awFvlCP2EBXG0vXywIi0qxPHdFt sQFXkmNdD/aRESvd8ZVEGxgfefuUE/s2W33dpKSnDXhfuv/eFPuLJd2JmXgD G4h/8PBgIfabIquguc/IBnYOUof8xv69VDe+wMVtA1XzgTxamC/QyS6709oA 5cwUXWM2EXlYPf7R/MsaXJqCJC5grqmjXKEZtoafiaSap9iftg46/NIHa2C8 yRUpglnK6sNaYaE10M64lHzAvhVex7/xK8Ea4tfc+JwxvztI+IM8rEF0gZuO GfMBq1/bifrWMC44qf0R+5panfa/YSlroJnWJE/DnHawloznjDX4Gwcym2Me sjy+14vGGj5GV98Xw3y8LoCi9acVVNx9FcGG2fjgGBXdFytYuVYwTIc511L6 gFGzFbj/bn9wAPNMbT7tk8dW0Jyy2kaP+exBikPr8VagdV9ciwuzs6Udvay7 FaSlnVCSxVxZ28mQomcF8nk2OU6Y12jPH/smib9vWkIzF7OoZTLzOS4rkBzk NZvAHFi7wuJzwApOvj7awofX10KrdfL1iiUY1VxyDce8z7L61OHPlpA8ctp2 BrNSLROHyStLsK3vy9bA9Uuk9ecqLbAEGdEcuveYey2+cW/EWYJs9sVKVVx/ fdo8vlRdS7Dxk7fwwfuVZbH3wpiEJVCpkJucwPs7UWMjyMdpCdEGqxYfMNtb 8F5+S7KAaT1agxu4P57WJF45MmQB59WdLp7E/bNCQxIza7KAum6X6U3MvjUv pP7EWsDx/oMZvbj/GmiOySi4WsAEFdG7C/vuP/Pbcuk6FtB8nWKtH/drNI2k Ej+HBdygqwrfxf191/ydhkWjOSyetvnzCZ+PDLWHWpGPzIFfRPu2NPbfNAk3 neIIc5C6Z9JSi89TEjOLwY/r5sDp90yqE5+//XlfW37VmUHQDdNurwZcr6Co N6JhZmDW6+d5tYmIdvUFOoKVzWDxjMwabTMR/T4c8fHAiCkwnFre/YjP/0wo 7xjHtgnET1907sf3w4Txp0n71yYgIfDk+PcPRPRVNHi2PMEEolcKww/14Hly pe+7OKsJJPl/X/TAPt1i7retKWkML2buPCj+SkTZ0h3MESGGkCoV9DQf33f3 WT1YOxUNoTP4opT8L7y+zROnDx02hI2GoM7v+H5MrHTleZhrACOGi5SaW0Tk f5pJ5EWrPoyn8d+xwz6tS2arNb1XD45cJhxLxfcxXcveZLlYLRhM+k3UU8U+ 8pS0dFVbCx6JX468qk5C+fe/Kgqf1oJzoVFMp7RI6Ir7iz1n6jTBaYzHc1Yf 3/8cVt6UCxogfS/jroM1Cb2IbDPuVFSHKHRMiisA+51beX0rgzpYVQTHrgT9 77PC/F5wEyISPzfUY9+ud5rJ1SGpwfLwNINsNM6DHrlY5puqMPqQV+lMKglV pZHr5dCpQBV9+xwN9msFp5HDKUXK8PLJHX7CE+yjcs/fh0gpQwb5uC1dGfbH dQspCxcloPLy+btRgder13qGq0cBXLLKFvzrSWhZ4MH4UVsFkO2rIHbivA3d 7/6A4t81yMjqi6dvJqGS+tMH5/mvQSZD/HhcG54XToSulSTJQZeafBLLB/z+ a3rlmWfkoOxv7MC5bhI60y1gn/BKFjwZ7dwFP+L5IXj8q/MPGWhT5j/FOUBC eRNSrwVUpaHon7pmJvZ1Jw/+Len3COjKBS3Msa9ncI7e4tiSgmMia89Yx0ho PkpCZ9ZAEir2xof6TmL/UtnmdDouDk3E30+fY3/3bU4ctlQVg8JipSOnF7Ef XmRLMQwThTpCtVAE9hVRFpkt5UURGDnue5UX+w1ncn+FzEkR7J/z67ewv9OR W9uIaVyGSOnHB4r/9/fF6N6z9Zfg76Nry5vYlz6aMEef/nER4q9xJNFjf2/o K7nKzH4RsoZlLp/C/k6o7yqiihMEyqvZN45jH/tt2FT3z08AJANX71FgX+uW HeckTvJD3UZj3hxm/yNntrqqeOFnU2hVNPY79S1Fm6bj5+Cp3tyDa9j/uKcc e8vCeOAJ9z2KP5h3OpOuPlw8Ayzb7fO52B/7qyqL4jW4gPVEnLAk9ssnDwbo /es5oJKleqIbc3DY70AHdnbYk/x38v/fnz7pv9hbdeQU8EiNX+jCrJN/u4gw dQKeBtQ3i2G/3ePRHOj6nBkSpWviHmJ+JrNPSy2cEb6VTsf+7/cG9Crn+DWP gPdexpqr2Jdp2k7tMsnTwblhclp/zNYWZWWD01RAZSMc/RRzE9kV/fSIPbA3 kZF9APNZ6SjqfIXfzX6c48M/MFf+FX0rTjvd/NaitHzn/59nsOQQH+iUSvvo lPO/7ydTOQ59XidJsXxaePIb87G3J9PcGnekKKrbeiYxX5KLyNp6tQ/J7QTT t2IeKdggSbDRoHnDW54ZmGXIa/IQHEb/pl5tGGG+c9HtgzmJAV04EZbPhHnR knc97BQTInSk3G7H65NIn2EruMmCOP2KQ5wwE17nKL0JOYkIl3Sa92L+5Xe+ /pfeaWTEuE+CgOvHmkattneFHa0q/ySjx6xQOjfFEMuJomMEjkXj+ru1vfbl On0GubQ9jiLh/XrzKyjvmvpZ5Om7k/MI7yfxgJGI7sI5dP56u/kc3n9mTtEP tqF8aF2q6Ck7ZmetX2sxlRcQtafZCR/cLx+q5+VvcAmiBM9c4xTcXxMyuina K4KITRWss7HvHzC8xGXz///LCKU7dB/356m5PJdb2pfQdtTKYCT2f2GPw/Xe p4WRw8cjz2xxP5vG/1CNrruM5lO+jFLjfq9qKPYtXhBF/lPUlb34/GyGhr3b fSuG8sS+qirjeVhK0YhRv0AcbVzSn6vGvv9+gO7FflMJRFyeSnKaJqGp795E hwGEaO8EPrjx//kdLmaz0JdG7oxHFuzx+a5tOqpwsF0axQXr6vrjef1vODHD 5rEMGgk+eDnoEwnFHcq/eMxMDlUQyR9R4Xn/6S86w7ZuOaTQVhHb10lCvYMB YS4S8ij9/J4fqe24H7J0et8dv4ZkTklO/sb3Uf5ZahffTwrIcp8z6OL7rEHG reSLsgqKH51OyXxMQqNco72RdSpo4jiby3QeCZHtV9kU5LmORJ5qbZ95hPev h1Mxbt8NxCl8cc+DByQ0YPh5RgxUkScdw6xEMj7PYqcIqpnqKIPys2m5D74v tKI/lB/SRqrHWww/XSMhjZdbUZpy2ogq8NTYhixeP6Or9G8fbXStxVqSVZqE jn/Rq5Yc00a6Os2q9uIkxGVy7lHXUx3EefXq+BEBPC/ZdXksKeshBa+dWyPM eF7okOZPDtJD+yc00tmPkVDLuep5oSo9ZFYW5u3MQELXvmcb+zHroxMULafo 6PD94e6qsH9eH5VNNbyJ2ktCNgFHWLgjDRFv0bFVR5yPT75Ff+qsNURl5GqN e35gv5TcTr61bIiG6EM+5SwRkRvZzN5qTSNkXf2L8H0W52NU9Q85dmPk9kzp 6sg3Ino1d+7JvLYxEnNwvFeM5wMypRzLhFhjFM5OZxf4hYiiDsR87icZo80a 4UWJT0RESNFvtWg2QTfkHzGd7CKigZWuAIpfJogH31zn3hPRMU0ZkZIzpkiR 5fxrqQ4ieniUt2wl0RQZXlZ/Hf4G+/CD7YwQIzNkczfCyhvPBwtbrjc5U8yQ H332TEcjEfEZz1C3t5mhVKuPzWewj+in2CIqRnNUtrI0s11DRGMaN1+qBZqj 3928hax4Xni3eCxN5b45Gj/rUpKLfedZ2JirwktzlC/zO06wHPth1S0+qe/m iPoHrYoXng+slS9Ti++3QOSOVcZnS4no+uTO3GUuC2TL+rpqAfsUC31iPr+x BVKTYQ5Nxr5FXqIVeu62BUoqbTvjhX1sUfqE6ZkMC3Ttb4atLfa1OrfS4ye7 LFDLiVPU7tjncvd7bDAvWKBXduaEOOx/Mblig0f3WaImvsm/5Xg+0O3tINBK WCJ2xN99GvuilD3BZb++JeJcSlW9hf3yDJn+jX1elkjCyPrnO+yftPdP8ZIR LFGJYO1bfsxrAvNUO2WWyDyqfSgP++q39vLZjXZLpDE6JsCJ+bWZz+vVaUvk tcfjaxX23dINyTzSriWaXqOaVsWclkIRsnzCCr1Mk7+5gf3Zn6fbeP6KFVpR nOEpx2wBGeLTWlaomKfZ0wOzkp4x87irFZptfC0qj1mQxPl7JMEKpe/fCODE zByzPDBUbIV+soTIHMa8y/aiqv+1FaqZSkj83//navxTesat0PkhV7MjmHvU ZG+937ZCTXTxjTyYa+aor79jskZqItp5Kpizg/vOtl2yRgbrpocDMEcee0DZ fNManaxXo6r/f14oN5+pd7JGhj9HIvbh9WgrnG2rjrFGaSL94SaYr46RHlUV WKPs9SNkbzBz+NQGPQNrZKyS9vsKrs8BuhCjkq/WyM3czLwe869CBbHCDWtU 9idFRAnXd1iSjimPwQaVSBq5z2BuGRxcyxKwQec2d6iS8f48uZXdf/+6DdpD 1rcij/ePQGFTmWFngxjfI3ZqvL++2eeTCRE2qI34NmkEs0J3o3Jsow2KzL+1 8Bj3xwWbCJ7IzzaI5ehMQzaeLxn/qlCErtqg4028aQW4n2bOj7T48tmirc6s g0O4/7re5OV4Ktoi5kPNyeS4P18YOwS6Wtmi07HpPVdL8LyXuHnF7qEt2p3k Ef+E+9uRq4XRqtYWRYoGX72E5wGNpphV0wFb1MfUUJSDz8Pp78cqdGns0DnV HaNMfH7g+mVuhQA75PzX0oejDs+DZS1X4a4d8rDobBzG8/rYgRsaos/t0Bm1 P7xZ+HzudFoG8i7aoZcXHtLL4nlfXInQT6dnj0r+19Z2Inopvxz8+aID+kA9 s5OI7w+5xz4Z6moOaL/tDZ95fL/07yUv7XRwQOyy4vMqo0T0s415sDHXAf2z vUN1fgrXR0aBL5fOERHD/oRofsf1lsz7bL/kiFr8Cr9RkWMfzz7/Y5LCCbnJ Dj34to+E3u3UkhuxO6G7WVuGtVQk3Kc9/Kr6TuidZuHR4IMkxCG+EyH0zgml VYV5qRwnoSwRPcGtPGeUeiMm7JkQCaUKHIxLMHBBlBYPr21a4XyM3nDn83RB NEYGZXO22PfHJg0/JLqgF8crXg04kJBgUs15mhYXVOVGzVDiivNryaw3ntsV bQY+eCKO/f9w0XOm+FVXBAeeV77HPt8UrEZ2h9INyefdGYzPwP5Q+nrNmsEN lT8N1VC4R0Jf9pSP7uN3Q8M/ywPKs7DPVYZXyJu7oW9U5yYli0lIke681pt3 bui8z7G/fNjft8TyFDMG3NDbtEjjuFckVG5zTMJ6wg09ayOfGwOcn6/Izuzb ckM038/Vub8hoTmnwd9y/O7o+V+lq0LY3zPvqSwziLsjclO29yr/+/trGJ9W cEfsymv0Rn0kVMNS2hFh7o46zrqxmQ2SUHRncObrdHc0zSwft4LzX3x9NTk9 1x25X/4h3oj9nXjaIcLqmTuKKEk1CJjA88dtLee97e5oXrVO/iv2hwOPO8wH BtyRZXboO/9ZEmr+KKlTMOGO5O59O3UI+z03z1kpuS13tBOj3cWIfX5EM/si A5UH6mtdGYlZxr4YfIRnmsED2ZnzihK/47we3DkUwe+BdugzTe9hvynd47FP S9wDSfzdvzS8gv2Hf36TQ9EDvcwMUzqM/ehtZN9km7kH8rYZodXHPs9qnTRU 7II/b/+jIeT/f38vp/whMdADz3W2Gfexf33goGhxj/dA8VYpfvnYzzjIW1/q 3vdAQomHbmRvkpDfZGDJ1SIP9MRxlhiLfa63RTTn9EsPFPXAQsEG+19wSGXM 0kcPxLeWXfa/Hw6aOgd+HPVA6o8o47KxP56XOuv+ctkDPbJxb7iK/TLi5IzN gz8eqHNOiu895pGdR4bBVJ4oNVmlQwn7qdA3o5tWjJ6Io2w5pBZzbCOTvBKn J6q3WJI5hn13PHNAlF/IE932J+xaYxbxT+E/gjzRiFBhWQHmJIPrHBs3PNHQ GT/xfswzolRM3ww9UW/QeN7//x7kKvNrmlZ7TxQecW74H+a0jWCyIh9PZEMr Ofy/vy8Oia/HR3oiW//YrCXM0jW/F13TPJHEQfJT//8+/t6d52PauZ5o7Juo 6R3MRC+XAbFyT1TLLm6gifmaNm8HW5Mn4uN4eXgXv3/Wpbmmve/x82Zmov+f R1aP5FctfPZE3ecTgQezyi+Tou5ZT8Tz93BLAa5HXt/xh89XPVG0uHnKIcyb lYMp9/Z4Ic6jO5edcD1vElIjAw95IeqLf17V4HoXuar6WZz0Qu9z9l36hffj rxq1iwKfFzoVrZt/ErP2hbeWfGJeyIOunkUM7x/5D4kb69pe6DlFpYM03m+D rk3pEUsvFEBfbHMe90Nl2cvL4OaFtqbdq/fjfjF1PH8qLtEL3VZUeJqG+6ta eYHBJdMLsb+ijZLG/k177vF+rSde6MgfKsZx3J8N8yd+sb7xQkX173r+799j NjRvK7e90AD/v7PG2LdvybfX36H2RqWH7wumz+B5gjOi3J/JGzUwffrbOEVC HlNb9+QveaNZ6aSEaXzeesyWHL84eqOHjXwXU4bwPI6KzF7d9kZXLz9nMcC+ HchmqZ0f7Y1O9IwJHusnId7RYUnnfG/UyrTy3BGf/xjDzsNkI97ILsF2Ofw1 9v1qYdfNOW+Ud58sirkV+y99bvfKqjeKN3rt8rgZ+267T/zkQR/0mungxiPs 3/nCXPtey/igvZ4p1nwV+H6jC9mIKvFBo/8e2Lbdx/NUm/AYjZ8vMun98zTa joQus+VK7Iv2RU8/h69oWJPQbT+ahztpvuh6Ll8fiwUJ7QpM6f146ovQlrhL kSGuX3ZKX8+EL/odnin1VJWEeHyX3qQq3UYBHMINZZdIyJgvt4yJ2Q/9y3mg KL+HhDwdfxT2cPkhSZOwMfV/RBRfIp4bJeSHDtQ7/bDcJqJ6nsGMVRU/NLUe p39/Hfsp14Hgj0F+qGxQPE0N+3Evq5d6zLQfirwFicyDRDRv1KoiteKHplmW H9ztJ6J/mXTX1nf8UI2GeMjJXiLiP14iZnXMH40af7mn8AF/H+MYB1L2R/Hm s9do2ogoT5vv5G8df+TNQmcyiPOxLv020zNLfyRiI99egn13jp6B9kSgPxqf mb3mgfNVjk5p/Xe5P6Klb3gYjfPYUPUO6VmjP3oSP71bjH3WI3Fq0brDH8m+ TaccxHmeeyBorH/SH1mkqd3RxP5aq/z+SxzRH03EIvsC7Ac9sUwD0tv+iKQQ 5klWjPOa8nl7+dEAtGLL3DKOfYNBYbfVhj0AFcr9uGaJfYT3v5rOPByq9/3j ZS0lklJIoY/ImqSIectSQqKUqEhlLSJrdsMMxmAWSQtJRWlDWUJCpdJCe9ki ezSTJaTt+3Rdv9+f72vMOc9z3/e536/bOQeaTbW8VgR2LZFMHSG84iTYX8TY HIHsa7qf9Anv+JvqXd3oEIFCh6mVXwkvJcXFXZraHwEN2avXiwhflf2VO+0R HgHK5FiX6ykenlO8M5YmRkCyYu8j6yzCM1FlaW+4ETiZtNvR4iRZT7Vgckpu BBoNFa7aZJL1/LKLN70egQuugy1uJ8h6NuRE/bgTgSiv+X8SMngwDR8KLWqI gGGWqHoZl6xninZEoTMCG39RJk05hK/XvfZ4OxyBxNH8mhw2Dzkhy92YPyJQ fEm8cxbRZaW+e8xEIvHx91LfOBZZ33jlzmmpSESbxoXMIrpnzSy74mWReOg1 Picnnazv2E4rL41IHO3RMDIlekFJnvkyg0i8n2qR/p5G1jfCp7yziIRXQXle GdE93fEGeTsiYSasz47/9/zHOxk9P7dIeDrtHv73fMjuJ1e1DI9GQneRQ609 0QuqoSYSFYnH+t0yO4h+ceO18itGJJ7Nd/rlTnTSeU+FnKxISAemBDOINs34 udgnPxI1H3uTa4n+RU9foH87EkxzO8ossr6y48rzBOojkaRjlulGtP+R8lkv miJhIX+N+4zoVa7WgqfbI2H9V2zdFrLfXvtPv92HIpE1sCXmPdG55oFTq39E wne40zuUxMt5nejYb5EoZL66PapK4iu96szXJ9JR8LiqJT1M9At57YETSlEo 7JN/VEvykSRx/7ObThR+lT8RKPiXLwHHdk1KFMaWTFXnkHyW90e/eugUBbPG jxH1JP/HWqSesz2jEG6idYhH6kPjef6jfcFReO2nxVH/d/+g5EX1d1YUbmwb DPpI6s350oHyupwo9F6LnmFF6nFh1kRx6rUoFOgeifn3+3ZGlELBf4+jIFem PzaD1HegpR97598oZK9zPq1Lrg+tDQJMRfFoUFZ03Vp5jcybmpn0r7LRZD8j zzUID+9dUBNB04+GXugvH48Swusd4h6lvtHY3KVRwyG8O+Pl+f1xEdEQiTbY J1jDQ+X9tXu2JkejzeDnOWotD9pX9tn1XoyGhmCY6bWHZB4Kum64sC0a0zvO T18i/eKVx8a1XYPRaOpzr6e95oHp9Fb7+mQ01L+t9Dj2joeZ+L3CYkEMIt5u oQSQefzL7K0SwVYxMBZacvf3AA/V54a731TEQLHKWXQ+4d0D83Qsbz+Mgfvy jmpXwruzowKvcV/FQH7wVEypGOEv5+mg7cMx8EwonRU8n/RbMSHBAYlYXJOw +LZhGR9SD+dnuJvFIuO9UfuFDYQvDTXL9hfGwm708wxqMOHDEVuv5qJYfGk8 Gi11nPj5ZX9Zk/JYvD0uqH4ukviBzO3oZQ9i8ffCJsbVeD4+jxtu7miPhfGB 4Twa4d3Im5Yf9syPQ9Q28b6Bq3w0efgwnsrEIUAsZu084hdKCkyjDQpxsDrz J1WthI8nzKZcWfU4aDZ1vDWpIP7os8v7o3kclnuzjPuJP3krhsltsY5DkMy5 bSUNxG8+nHpeYR8Hi9nTR/2f8HFwc/vqLJc4tNi88Hnwgvj1ikPTu8Li8Cmo 1r3uA+GvtVc07GPi8OTj+nabVsLPm3gu1vQ4NHyMbH7YzoeZd9h9ZMTB7n5N TDTxW6/wu98NzsRhH/etz13ix8wUAVW9vDjwKxbrDBC/fnedyVQtikOfQ3P1 X8KrP2te1iiVx+GptMX9IeLvy5sXjcjXxGGrkbJSPY8Pn9HcnfOfxeGOklCs BuGFdMG+xDmv45AgH9F8b4yP29LqlcItcXi967i8EeGL3/qlCtP9ccgKmufB +8efltN247w4pKj8eKJMeGWTE+J53+NwYEh3woTwzGGfhNKBX3EQOjFy0YLw DyviSf9nQSrkQ49zVxM+KmXOk20Xo+J1hhBV6B9fZu+weT+fCk/VL2tqiP57 Iyv65WIqoHH1qAvhrxW17UVPl1Fxyebnnx6it7xU6n6oQsUi/74b9oTn/D57 LqzVpOKe5d1t/95/5Yxd21ypR4VlCaW0jehyodHjtzdQIUU/Vzb97/2pheuu 3TCl4sEmutY/vpyxMrLj8hYqxHwtfvYR/d/6OskLdlRsrs7/c5toqy0iZtmO VNRI6yl4EX3U2Tr4pAsVmnQ5sxn/3tc6zCpgu1Ph37rJOYqs707k248pR6iI vuvn8InspyNVdi49kAp7lpyKCtGC51wpseFU7DjJfWRP4qFadNE/PI4Kv3ey aw+QeNnUDeYFJVERLvDMz5HEM+CV1lu/dCrMxO6ErSbxzuwOFPXOpCKA1eL8 jeSjcrzC4GA22U+XimIG4cNPwn8O77tIhUVnSqs8yZ+QjFmO41UqfuyVzGGQ /KqpJjXbl1Dx4nlqbDvhQ1uD5wI2d6iQTZh3biGZV7L2OHqaPKJifGqZtD6p n7tHzp4yfEGF8lR1mQKpr89RXU/13lJh9CZZ8yuZl9RzD+uodVOhW/pzjxGZ r+yKiw4of6FizeirmLtk/gqq/56xdIQKX7623X+EF2t6Yn7M/0vFX6RNXyHX Q/f3B+pzReJhqu+1/xGZ72aJirmIiMdjdNZRxjPCi9vVMuqnZeOh9G6P77/n jXt9L6d068djMG7Ngplkvpxh/PCYp3E8FI/Jf71Q9e/9r89OQ2bx2K10SEWP XL92hXKqY3bx+IQyOYVicr32pT0QOByPtY3ih5TySP5cg38rnouHnoWdxOY4 Pm5qcXouXYqHlei51zzSXxp/33iqdi0em8z1LjDCyPnODpxafScebjqRzrlk 3j7yYY/+xtfx6BZu3rJ9Hx/m9qZH94smoGlljvOmdXy4Lnfd1SOeAEer+xK+ unyE8yOMvaQTILT81x6WJukPqaVz/BUTIO9sIdKkTObBRtXLMRsS8ETiVo+R JB/jphJdOUcTIGAolOUyyIOElMZjpZAErI9q+ZrRQ/y0y/JmfmQCLF59tXj5 iYf9MdSoG8kJiDca3uNC+vmzqu9Lai4koJP+5HLLfR4u6LVtb3+fAOvKA84d hK8ufx9MNOlIwJFayQtNZ//dH56svtCTgIhUWVYT8cOy9QtW+owkYIvskMdv 4s+NRlY/J8Ro+FYhvWYZlYem3446zvNp0PFf9ZIbzcObGnf3uzI0BEaFSslF 8NBhEtcUv4KGM7SLBw8G8TBqXnFBkkJDxewa1QFPHiaFGz4EmtOwS1f39Z9D hCcaXou/t6KhPWTfPfUDPIhs4YdmO9Kwbe/P2Y17eZgj9vvaDBca/mudYWjk zIPkU7HPBw/RgJ4m2wZHHpZsVbFZFUDDwrUrbynv4EFhnl5caigNVzw970/a 8aDUtLHsWxQNKy4+Nui15WEla9vQjgQanB/ODhi2If5vv295OYOGRZHH68St eVgtdXinLJsGlTnCcVu28KD/OowRdZKGY77rBXM382CyM2Pc7CINxXq9rBxz HiwW5akVFNLQ9e6c/mYzHqze33QRK6ZBm+H2eo4pD9uy7nJ9y2mQdb1yfdiE Bwenp4+b79JQs0Nl9hcQ3pX9+HvNAxokfOtVhIh2ae3TPdlIwwbDRPMNFB4O nh33nG6mwUubk51uzIPXPoHsfe9puCM832cm0b4Kkq9q22kQa1j+iWVE+ObT UtEVPTQESHRqUYgOzVU3SvxCw+N43aTZREe6GQR8+UZDTmvnorENPMQpbc7f OklDcEeY4E+i6d0OrUW/afAN1Q9UJD/PuHhAUlqIDuOLgkkeRKe7+1uEitGx +pLL/kaiM1Siw1sk6XA/vEdmK1lPVn/KTWMZOuonIx/wiM6+fKondykdS048 jLhJ9pPnXbBEaAUdB7oYW9PJfgtWldp6rqJjcubxTWkkPteG6uMbdejY2JVw 9NpGHoqvNVdorqOjO+LJ80ESzzLfjq8sYzo4NNaBTST+VVrDSuNmdIg9tFSv t+Chlv/D0dGKjltPrBT3kXw9LBJNrbSjwznml4EMyWdjwML6pY508J5d8vhm RepZV3kydh8dzUt8MgZs/j1PpKPRc5AO01M61/6SeukItsks9KfjjbOqKoPU 121WlHVWKB3Cb+KfrdnFQ8rVGzPo0XRYmwdozHTiYX2X5GE3Jh3b6lR0RFx5 mPdr4/JtXDr0YqNtjEl99y4KfGt0mg72ePTCk+48cGzeYvFlOhw8HuwqPkLy 6ynyXfgmHQbnJ6QC/HkAdV3hWCkdK65FCG4n19Nw+Snppvt0WOq9vxscSepP 2WWQ9onEbyK9RJ/wuTwlPSewjw7luHl7Rwkvj+6u3eH2lY5w74qpRsK/OWlK NUY/yfGftrk2n+dh6kcfZ2xRIv6ep6fIlJP4Nx81crNN/OfDbq29PFCHckds dybiQq7WNpFhUq8ir/KN9iZirbfnLJNRcr0a6c1f7JMI76Igy1Yy/+4vmOp9 QUuEs7eARfpiPqSj49KN7ibCKOeA2WMbPr5klZivepCIsMf7zmzewUfdre4f Mk8TYcNYa1HrRPx90OLQ2IdE3Grd4HrSg4/HDmIGheOJmGXoFFgUw0eEOvez jEYSTLbJGijd4MNS6KxNum4SNo3tN5O/Rc7XfrFMxCAJA3NsR36U83EjrYzx 3SIJmbn9Pc51pB973hs/YpOE95M+9NaHhD9NHrv0bE/C9ScLEwwb+egc+aj7 2jUJjfLrj6QRP7rW+PmslUcSNG70P4t9x8fxC0Mi9UeScDvuTYhNC+HZnb9b io4n4VX3+0c+XcT/NUUsVGOTEL9Bd14V4berIhI3z9GTwJ1h1f6J+Kd5xfL4 NG4SaKJi5/K+8iHJVvsqfDoJ1StfeVOIH7d76zpG5SbhsQ7br5DwWqHphrrx /CRk71l7s3ecjxA5c/Uj15OwN9RwHZ/4v9m4zYnuW0kY9HaSb5gix3u+869z ZRLOH3oQ7U14ou2Si/er2iRknJlO/kB440q05+stj5KQ+0IuWOrf+1CO/sZ1 z8n6mn3iFxGeMdU5XrD+TRK+tdwR+sdfErOp84taksDRVdj17358WxcjYmVX EuY+UP387331y5Xc3pz+JIjeS1b8d389mHt22yIe0cpHzgz/e173yKU7qeNJ GBYf6c0lep7FDWXhn0koHy3Ml/t3f31peWrkzGSsutvK2UvOVzBxb3JMNBl5 YTL+B8n6gpoeux2elwyJDzHSOoSfTC6/fPpZOhnrKf951pP9ice1rHWWS8ar mJj9soSXWpy6z71UTMbeq2li6wkv5esOz96imozS8Mg4OcJHgXO+B9ZqJYMi nTH2gMTXpOd3+7q1yXCQPnlej8R/7l0Ry5sbknH+4fZPPiQ/H09IlKiYJkN7 acACL8JD+X6L5XMsk7GyoLRcg+Tz2GZF+sJtyfh4o9LpDuEhLF/1jbkzGYjd cHoe4aEPLzc8iDiQjI0bVrQvJPxzsdBca8wrmcx3FglPXhPei9+a5XM0GV3L GhZsaeJDbK3rEafIZCySvypZROrTOIsqvS4zGf0Dz7spReTzgJToG2eTsT2t 5PyxQjIPbMkY+O9CMh7vv5MZeZEP/5+XqqWLkkHd+qhuSRYfeS5PDo0+SYYZ 5XzY1SiyX/Z32/HmZAjlRKVohpB6va9oMPE+Ges+xkSy/AhPqYWLT/eS+MxY bCXkygd3bFXZTAEGNicUn52k8KGr4pgrOJuBip0OM9/o89G8O54hLMlAfd1P 8UItEr+aVpfZCgxIsJtG7BT4SEhiis43ZOBdYtIS3m/ix1UVI1IbGej58+bY z++kX3/taZW2ZIByOiZrGY/wwHbjosW7GJi/3a2+qoOH0zTv07L7GNgdfD1r w3vSXytOJMgfYmBmp1d7VxMPwUt5u5cfY2B6WuVscR0P0nayZkrHGbg4qLKw u5KHEuomzRWxDLyaJT5ldZsHXn/OTNU0BpwLRma/KCDzsOzTIbUTDCgu0zUe If1w1dbJt+pnGYjoHPjkTPjIo2RboXYhA6Xn8rfNJ/1UqDciY3UxAzEezCn3 VOJnMpej11QwUPj50EPJZMIHVm+81t5jYEn/LsZCGvGPyBk71jUw0PFzUjws jvjvTQ1jg+cMJPguFTUi/CT7effKDW8YsH8zIetO+KlCmjbfuJWBX+FnWybC eHDcXPyT8pmBNUn1teMhPEwcb+81GWQgf42o9r+/35JxbXaz6TcGQqUiDpsS f9D9tLbSfJKBuMV+2VmBPDTPP3Bx0x+id91p/Pf3W/zM09IshVPge2zodQnR c0Mrw6zmpiBGQTMgkny/8ErfAZsFKThkbKL1iBzfsk1qq61sCipn23qcCOWh bx7W2SmmYJ5sFQaP85Cw8bDidtUU/DkYUPCA+JFS0Mk5DtopeLc4zlotloe6 /Pvfd+qn4ETq3xOLE4g/fOR/cjROgWjneD43iYc/c+QbncxTIHHmsO0ZEs+z FMvbe6xT8OwMhHW4PBgGBOXs256C7lmqffanePhwITfJ1SkFK3Tn588gPBvy 7tkxt/0psHjjmrKB5LNkw3+b3f1SQNHUj7cjfmbnZ7/aMzgFi/bqXVapJfnP jZLzjkxBVipTIO4JD+oi7/hHGCk49de9/VY78fdVYytt2Smg7/7Zt22AB6Nt kvu1s1IwRAuQcB7jwSbLqnnkUgr6ltwKPSdG5oFV94pC6lJwtDWoZo4x4Xfb tgHHxym4plLy3NCKj8jAH8sNmlIg41bsxHQk83z1GvbPthS0yqZ57jlG/MX2 ckDsVApUb0UnVuTzoRf48Irb3xQ45+tqLiB+Vn3yc5epCBPXVwi3jdQQ/6j+ u2SFOBOKe5pVDYhfPeuU3y4szUTQU+H7T9/w4SBsyOiTZYKXYurNIPNXm5pj /SNFJh66enTuIP3qkG3Q9GVVJipOXecJ8fn4eoyty9Bm4nTHkFMY6Y8hJ2/4 HNZnwkN+7Rc66a9/qp7m2RgzoaKy9pgo6c/0zoEWTXMm2o/at7/418+FRRZI WDORP6/SrIjoTDVl62/25Od5niJRpH8r2JrEv9zNhHdO8ZgQ6c/5x/ZVlbgy 4fQwJnAR6b9aJ8PHuB5M7Csbvxs9wEdZ1Un1YF8mXmY1y4m18UHpvH1wVxAT D47sWJ1A5sEGoVdn1kUwoVu31qHiDpln1fivF1PJ+W5lDQdcIP1w69y500lM TA3M74pM5sPlmJp5azoTntzxufmH+ejL3BRZnclEc4RVXdUWMt9XHbydnc3E qrXHbNPIPDb1KXY4+iIT34denvg2xUOsUM6K/VeZGHB4er6C1Msstaq9G0uY aA0+ubH2BA+srR8ylO4wMe4gU9BL5pXFx74/E6xlYtOV/UJzl/GQmykl3NvA xPYVfsrybV9R9MkmuOANEz1L69SrN33FeiGf60mtTFB0RFIo48OoVU3s9f5M 1ns8LIx1dhjNAXU7Nb4xkfPpnmZb+xB2Z3akik8ysevC6HeR0CF0Vv58yPvN RLz+hN/BOUP4JqivXzwnFS6eZ/b7qnxBmOoOP45UKqj7TIyY1wcxY6t/fuCS VFR9bL5bozMIyczCRforU7HyXEAnU2MAq1WXTVaapmLgItdZXbAPRWLSPf9t ScVY3PEPZVG90Po66yVrWyridibOMprswaqS0UKPvakoF259fGSgG0pGDS5S Iam4EFPSUfC0C7kKVdZRkanQklZcZLKpCwozi9YPUFNxVk28TaK+E3INp6Rq 0lMh9eO/uQGRn0j/9m3wvpKKRfHb93ecaSXcceDWm5up0M9qbTS92QLJhY65 KEvFRfmRbTWPPkK8xSR84X3y/aBa/6uzPpDra61n7JNU+NU96ndb/R5i51Y5 DDWlYufg4ok7ru8gckhaq64tFc//jO9Jef4GCZtmy2l0pwLxI0ULxN9AQO2P 6MnBVGwJQdLe7a/x92t/15GJVJjUSdyU5r3EVGjVicWSaVgwW7hZ6OULhDgX UeMXpUFWKHqT1pXnGDe6dJQnT7RX0J6ylGcYmZm+5YFaGoR6VLLH/Brh3xOv r62ThrmpPnPVjz4BryFM+bR+GjSmkm40hD3Gl5QDv4+apYES4y2gUNAALz/H Ly1b0jDyfHu1/dOH6LOzeW9hl4aSMjW/lskH6F6oXyy3Lw19G+9SW7zuo+3c bPdHIWmo8PqrYnmhFs7UP/a6UWlwdsi//VagFh8OjVGy49Ow8KxsxZ6XNXir 1r44kJWGt88Md+Uyq+Ew95VwRybROln5thFVeMVrGLXMToNedPDuhqBKvLhV 9EyhMA3DrpoN3vQK2GReupNclAbLuRINT7LL0Rh2On+8LA2S/l4399SU4ZFx Qmzj/TTMPLdeK29JKWofOeqFtJN4dI64WGqXQFLI//zhnjTsp6dtbAgrxn6T pHluQ2mIPrtym1BjEf5WVAxY/0jD0u1OZ54K3YTt9+adG2ekI/mXRsuTl9eR s3qwXl80HWLJ/MtlV6+BUrgkW3FhOrY2j59clFCItL7VYjLy6Vj08ItAaNwV dChZhc5VTkf1fumFucmXEXUm3H5SJx2G2u5PPSvyUc1sFX5uk44bUXfMy+Mv YO6TsWP1O9KRvb53xtKnedgrPLez3Dkdlzp+1ArL5uFnlFFlnlc6Jt8nXpV6 ngurSoeVWUfT8W0pEk7p5OL0xJGM1JB0MA6daGzWOwfDo9l+YQnpkFJalMD9 exaMq6WtvinpeDwr9c6t72fQ0v/c8iAnHWeKggacJk4jfP8fJdvcdHyUedjo u/AU7ti7vleuTgfTUWv+pnsnMCst1HzJ/XQE6P3Wm/EnA7sb04vnNZLvB/3Q UDXPwJRpbcqP9+loo865SuvlwDLmwxSvIx0CZWaSKiYcZFV9c+/pTYfl+46S 2efZWK+naNI0lo6bRXlN3CAWkvwNrj+YTidzwQuzyOfpOPJOVbx9Bgt9TgvX e1SnoVpqY/grURZKxJc9NKtgYk9KgMPdhSxoO3coai8lHHrlt9j6JSwcqPS/ J2WdhMJHyXUl8izU71piz4lNxLRgntZlZRZGC1qbdWfSoaSk1au0kgX7zk8l 9dY0WJlUnslexUJoocSKZ2cTcDry1SzuahZoch7JVvbxqD/tck98LQuZBn23 LG5T8aXiS3DSehYmbjmdaZCnwvC7QHcUWNgz135v3O9YfPRdc9drKwtyrqnp 779F4ZePuu1lO3K++PX0cwuioOCl/Kl/Bws+H8sXHzeOxKEDC2Z6OpPjNzTq ul8KR6LrHE7+PhZcWTse//18HIV7BZX79rPwoeR3V5XKcXzbNWbu7smCS3+k QN29UCxwGHp70YeFjIh1lhekQ6Fv3+3R40vOf1bd86NfCCKtXycdJHHm7stc l6QbjFkmt565xbEg8yF4MUaPQd346r7zCSy8fqopIOB7DLaGF3idiSy8sfb0 bh4KQIYeV3J/GgsSGgGPRL77o3x1yvlzbBZ811m5acb4o0UrXvdTBguR7B35 bXP9sVwt0MHlDAuB0/eX1xzyg5nK4d7sHBamD5emjXF94aF8MKT9PAvyXb8C dj85gmtLd2TtvczC0PNbzj0Wh7Feak2bcykL+3ZuvfQy1gt7JNR9T1ew8Pl2 69jGNk9Ez1X+87GKhf82pEgGG3nigciC5U71pD7kDDYyxDxg93P0oGMTC6aj 96/SPx5E4NSX8cxX5HMdk/QljgeR+f0z7d1bFnRsPiTt/XAAbfxXBTvbWLDx n3cxutcNXj0lQzsGWUh3Cjc0WrkfKV2FkdxhEg9ZY9u8aFfc6MgTf81noVNq KyPltgvGP3C0t0+wIJIXbT2ksw+xz48F2gmyEb3MMcHJ0xkXGn2EWCJs7D8q 8ne41gkNjw6caJrNhk+4Uc7MZU6YW7+93FaSDeeOllKVAUecLNP9abOUjeUT nZN9hTtxQ0N5TeRyNriVDJEzK3eiIW/B4avKbIRX2b6tKHDARNp4y+xVbKiL SS1qKt6BXZ5llQ36bLgzhxLbv9jDrz1/9LsBG8NUFxP7WHvQd5xc9Z8xG27K LxUiF9ujDGGn483YWKk47V9oZ4dFiw3DTezYWH2O7dhRvRVaaatKju5g4+/E 4UlDia3YJCT3JWcXG44b+rt57jYI+fbT6fdeNu5cOq/Rs8wa7x7fNaj0ZiO3 iKrypd4SPMqNgMEjbOz5MqHYqWcJkdKcK4v92egaKnfZXrgZ+udjloSGsCEy 99ldm3ObcOL4xh9r4tnwYN17oHLTHNf4q1cfpLOhkEq1TzQ0xwN3JW9OMhuj 2to25Y/NMG4v+PFbOhtjAsPhhl9N4bDqYcX1s2wImMhltjtsxJHc0m9t59jo Hss+/HDcBAmL8lXnXmDDfIv/zbFME9wWSMzyucLG2sHBG033AelWy7CVZWzM UUPBZkVjaNgbFO26w8a2wd+OB6hGMH+kNkCrZiPq7d072v0bEHRLbHdPPRuW tKjN8VWGeJPybN35JjYOU6zDM5nrMTzz7tHmV2yI6i650zhrPYTCrhf8fUvi VfhIRzBpHfQOpcm4tLFRafDIRy9dH1wju0nZQTZsg1PZ2TV6yHDdfjR9mI2K PzuE6zcTTXXoF/zGhkRbx4znr9cg8/Hu98MTJH6P210sx3WR5eBWXiPEgYBx xXSTw2qcCj2ovWYWB//1tD5dNqaD06fdCwrmcPD2pWXcI64OznR6n2RJcZDX emZeXbk2co4cCz2wnAPTrgUTRnM0cS49iP9OmQO6cujmZT4ayC0J8bReyUGD gkDmi2fqOD8V7qinRY7v/9hgdfYqXEyIXydixMFHrklCqKcqLhXQboaDg2lJ 6zTNzyuR35i4km/KgdN+ycSfritRIMmU+bCFA/FpbxnWIRUUns2YvOLIwbC4 xJe09BW4ei/zqMIe8nnW6byx5Stw7XNWP8eFA7s3d9U/3VbGddXs9xHuHAQ9 6peY06OEotuXyrcGcjBxWF5B0kURRe8LtOtDOGROmbdKQEARxdNXCvTDOeiR zDMVubwcJSY3Ti6L4+C0XFCG0vgylD4rCx1J4+B7sItytfdSlPEr+O4cDu56 zy6TapZHmVSVZ8sJDr5Ojj1uNpBHxe57jvfPcuAi9fmQjowcKnserTtRyIFX +fHTOycXo0q08ebsGxzc+SLjVB2yGNWrnq2MLubAfY9g7ciUDO76N8t4VnDw 89nJJTRhGdT++jC5voGDKq0DXqnGC1H9Z5PVsScc6F98uanxgzQqZpSevfqM gxa/qWjxEGncFGJvVHjNQcF01JrwsgXImbslRbCTg+OZuTl1W6Vwel55u1E3 B2dFNa2EpuYjU/I/nZA+DqK7b1GmL8xHqvTMtwPDHNyzmhpqmTEfkfJ3FF78 4IDmVtzBOy2BMIWVAaK/OVjLqnxXOksCQctP3DeZwcWxuO/nnI7Pw+EVAV63 RLhQf68nOH1AHM4aaiVZC7j4MJQjKLBrDgyMTlkc1ORCOep6r9NNUehRRLPO 6nDxYkIv3M1cFDomwV/eruHiS9jJtsBWEaia26dbGnKxfNUS/TQJESy2mf1R czMXl6Ne+4WnCUHaNlTd04qLjkNhg+W6QpC0643K3crFLYd+n6IPghB1qFNa 4MCF9kfW9RtqgpjYc/zI1H4uvIpHxb51zMTovv6a1Ye4UPHbrS3Nmgme6875 hz25OHzqeXKR6Uz0Hlxd1u7LRfDg2pdrrs3Am8ODf+vDuQgs7jTTX/aXUhLh xE3N4GJJYsM3gxU/KUtLR7tUsrj4phj47fz5aUoSL0Wn9gwXuvfFuUWK0xRX t5rno3lclNlL1NHVflDmblaetbuYi6FWz07mrklKaGz1rpHbXGxXUIvN7p+g fL6z8xKjgouZfg17+8MnKHc0kkzv3uMiPLdp8nvBd4qH1NdIpRdcKGoV76uQ Hae8tKY/rXrJhfEFkyir6jGKEW2Z7M63XBzQrNOuch2jLJiyL09s42JgjvlD iWujlNr2spHhL1ykmVrnhTiNUOSuxHqUi2ZgE3VLb9+frxT65yWldnMyYG9U m2US/JUyKndL8Mu8DJyjOdma8YYpj9N6c+UXZeCZ9fNjcwaGKCFBVq1xKzKg FHHpr+aPQUrX9W41OdUMVFj3VDnED1Js+iPDbqtnYHlJ7+0qiUGKsvPNhf26 GdgTmrVTTnuA0kwmMpuNGdCfWremj95H2XD8ek4v4UrrC1HtLxX7KPklm75G W2Zg83s9+fyaXkrUf8cZxdsysOzLjKHO3z2UVXM6HixyyYDIBPXKSXY35YR5 6IIitwx8vOZmVGPYTZkRLXlgi3sG/NS2dMb3fqa8/2b6N+II0Zs2mj7FZ4rp qratC/0zIPyqrtuI30W5cTD47I3ADCSWmu/TzO2iLMmeN7Q5NAOO1kbzTmzv ovzf/9vC//+/rf8B3hytrA== "]]}, Annotation[#, "Charting`Private`Tag$2743#5"]& ], TagBox[ {RGBColor[0.772079, 0.431554, 0.102387], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUmnc41W8YxpGRRDIipEEKFUVInDcjocjee2fvveexZ0PJLKHMMisPQkiR QtlERpwjSUL1e39/dd3X0ff7vs+6P8/hqJWbli0VBQWFKR0Fxf//Rg89ujAd mAV/5+WI+3ozCGzjTaulfllAop3Tyj+ZSXjw5e0jT+8seGGn9PlAXCahffUH O7VrFryccauaVMki0DBcWhOwzIIMtdAvnAs3Cbf2a5eSTbPA16Vdikn3FkGA 086iwSgLnHJKRS+33yIoHU96p6KTBSJT0haPS28TYtGnMucrWeCimXqwPz2b cEDpm+V5xSxgvXboujLLXULxtb+cfy9lQXCKUo/7zbuETkP+uFTpLMisSD3L /OAegdbb3brmdBZ0vPtpqTZ7nxBXsptnkzULuBsNLHnCCwicldwfWpizgN+r qXrqcwGhpPZMQjxjFgR1GhmknS8kdLXpbHLRZQFDvXnixFohYfd4/kfZrUzo pJ+OjIh9QLjz5Wki7a9MiCBxXVhcfUA4udQp3/cjE7h/V768b/qQoPxrucpi JRP2W/c/5yMUE4j7LyRHTWWCcZX6TfFDJQROzmuK18YzoRA6ktPvlRBKeM23 2UYyIVW362Y1TymhSzjmRvGHTFgKfc0fcqKMQK/0/nJ3ZyZcKIn4Imj5hHD3 2uxO+qtM2NVUqxT96wlBSPvXU6OWTBCxqSaeTS8nqFocOrbcmAln/YnEwXcV hITAG3+ZyjPBJkCxrKepinD2o6NPRmkmMKY8/cPAU034dNp5mb04E1rTr2WV hlUTTky7jvDkZYJ5cUualHoNof2Kd51QeiZItEk89dvzjOBc4HO6IjkTfNYb 5R3DnxFYt30fnE3IhONJ5/cp/H5GsKoIyJCKygS7+rYPP3/UEv6xhbkq+WQC /w1Tpwf7GgjFruFz3R74vryhPfR5DQT1rggTNVd8n9LTJpTnGgk5QdGqOvaZ cIX2KAu9dRNBeiZewMowE74yuVJorL8gTF9MvD+nmwm2R4recRS9JBBvJrHd 0MqE2EraXmW9ZsKwciqV+9VM4Mn/useyBwjelVkTIbKZcKBopyvIt5XAQ39L l1I6EzaihQSUp1sJr6xu90ZL4PgcbST3qbcRWA7cbUoUyYQHrR86zM69IlQG 593KPpoJ5Rwf+GsPdRD0hvIZD/Fmwr+v4/VZ+R2EvyKF0flcmaD9ekr3s0An 4dqXB56PWDPBYi9V15rsa8KSSpl6LQ2OT85Oh2R2NyG96HGHFFUmNJEUju2V 7iFI/Xki8+JvBqz0UD3mnuwhxFVVCr36lQGeU+zH7SV6CfwctbTvFzNgVXh7 +tKhPkKve12IztcM2PY+8DHgSx/Bq6d+fXgmA1JOFxWE6vcT2kKaZiZGM0Ak 7tpbJPyeYD4LzctvM6DwPbXyn58DhL3musaPezLgLFWs81WHD4SGz0u/brzO AI1bu6hCxj8QmPvYz863ZIBA0LzAaP9HQlujU9H00wxQln8v9Hl8iOAqTnkp vyoDHnJVb2TdGCZwVd4aMyvPgIv5PGlzm8MErwet7GPFGaD7dKS87NhnAn8q B3EoOwOkTEi3ah+OEvrpy/lv3soA+K7KSa05RgiOlm/VzsT3ISqudlKMEwYD XLb6kzLgEPWXd4KuE4RYm1fOb8IyoP/tCANT2xTh3KQBfUJwBjTLeoabC08T JgxJD5UDMkDLoCjE//Y0QfL6wckOT/z+bA4VLf8ZwsIFN80W2wwwuUszSWE+ S8h6Rk0KtcoAqzOLN75OzRIuidxNkDXPgGu0+t+V7OYI2fwdr5oMMuBYo4Ta VNBXguo+bonaqxkgnVkh7TO4QNiIrxrwUs6AIbnCtDO+i4RCaiW3c5czwJn2 Su4V7iXC9m/3kkpCBoy86vrI4/WN8GS2k6vsbAbkWR9gEzYlEQzMTeodzuD4 D+V11fCTCdQj37VPCGfA+Vb66ebvZIJpH0/yA/4MOH5ArTP23SqBqcnzXy5H Buy1R22NuWuEJvHdOaZsGaDzeUGMivsHwa7yvhTP/gw4Nek233X3BwEedHlk 78kAXpfgw4SH6wT3VN7ZzD/p0B0jI7qxsEE4kf78s9VWOhToG4jJR/wiTGQY 9J39lQ4Wp7utBg5tEtRuZTT1rabDgfMHBBRtfhOE7tOmM8ymg/iCF4ua0A5h OrcodmQqHZj0ib6ZCzuEO/mXgkvH04GC+PfJ5Sd/CHQPAu2vDKcDY+qkQ7bi P8JsGUk2qicd9jmamFGaU6J7TxLFtF6nw+PvPNmaQ5RIq+Kk4NH2dJj5+cmA Q5MKtVZbscHLdAiMfn/AS3MXym0YWtqqSof7v3q9K8NpkF6T11R3eTrw/C55 uXiAFjG+YB66U5YODJu3eDOraVEwqLZKPEiHZPjF3bFOhww7m2973k6Htz5U 1t/q9iDmLuNkuax0qJqXWB/1ZkBd3ZuRzOnpkEUh4hAptRdJvD3nWpGQDpGF N7Oq3jMi0rs+65C4dIgyD9LOecSEHvY7G16LToeSJkE+2uh9iO1jseJSSDpU fquiuFPCjN4MKkg3BqbD5aoDIWeP7keRw1MiRL90+LzpTxFyfz/6PsLFLeCR DgtE7QclBSzo3XTKd0ubdBjkUVahH2NDMV+E50Ut0+HnturLGR92JDPXNfbP NB3kgzS3EtgOoMcLVF339dNhR/X8FNmCA1kt5b101sH38RPwoN7HibiWZZ5e 1EyH8McnGm63cSIi2Tf3s2o62NSgtB1pLoS+s2aVXME/Ly/ZJEbBjTbWquL9 FNPhtbfO6rM33Mh2Y8mbnZAOx2OahX19DyH5P2ZXNc+mw2IP33hX2hHErLVE MXo6HRKrFLq6uY6iyWKfOhuhdFBSLGt9UnoUBWskHfXnSweBs9tTI0PHkOpD jmHKI+mwi/sCT5IPHzq4VZiUyJMOk/kZL78d5Ed1RY2/ctnT4c74t1d3vY+j 6E3F8pMs6TCknBBqJSyAtNX6rWqYcPzdTsd1Lwig1Y2vbzvo0oHTt047yv8k ElJle7D8Ow10t7tflv8QRpu5eYa+G2kwZnZt0nb+FHr9Q2gfxY80ePCxbkZo 9jSyuS8XyLqcBn8F+/n0tkTQubVekfsLaXCgRZFZPkEUUV4xmBOYSwM3Olfv RzxnUe6qq4b0RBqc/dDiQNA6h5wvb9G0j6SBw6fWzq8/z6GLd2Oeqw2nwaZW pvWbPDH0SSFHwLI/DZ7sr3bVpTuPWG5378S1pcFp49arHqel0NQ3nZr9kAYJ zWMBK3suoMpLU/b3nqdBw+jEPbbvF9C1pY2BimdpEKHw8NKXTxcRF4okSlWn weUz90F3VAYtZjIS2srT4ONIXhH9giyKleUvHSzGz6/4w0y5/xLSyag0My9K g7J+otGhkkuIb16abTEvDZZynt5WvyyHWtI0w3bupIFJaZ8kTaY82voSqsuX mAYD9GHrB6Mvoy6pPQzlcWnAVrPmdURHCd1OvtkiEZ0GdHXZFztPXUHikk+E VUPSoNbcRj3mtzKiSpKc/hCQBkoT5EO+JBX0fqrtlqlvGhRQFrypXVFFrgmf KT3c0oBd3vc5E6Makpm0qd9ywpqJRuDMGXXEIL7qHO2QBn0F1Z6lxtdRyTjt p9uWaZDblmJCS9ZAX0TFK5q106D/+pEZ425tVFesHR+lkQYMYyp6CbE6KIHH y0ZZLQ3SCm8cjriqi0R313ANKKXBM1PH6+IkPUQd+v7nLQWcb65G+5pefTT8 Y7Xf+FIaZHKm1QU/M0ChkyJxcxfSoNQ8+3tVgRHS0r1uVSaB8w/6LrQlxuj4 G1dZN7E0kFPXHw9rNEG9deU/Nk+lgZjdRvrWPzPElSJssfdIGpiRmt4+ZbdC pF1XL77nSYOXF+4WxLy1Qq0BjgduHUwDGdZEuJFsjRxsS3sPs6aB0L0Jwl8B WyQz2vVodl8a3BSsXIqltEP7NBciS/emwQVeB44Pc3aoTubEBTHaNNCvV/It feuAEmqU2Dap0sD84XoAYeAGatLonQj4lwrU5f88y2ccEd1J1avJa6nAdm// oShBF1TBGk/JsZwK8uMTBHFLV6Tz73V9/lwq/HjFp6j7yA0VDl3mf/YpFa6d /ML7Q9QDqbRFj8gOpILy0peEzW8eaLX8VdrrN6ngNZrj/77SExFi5P6MNKcC Y9pNmTFtbzTnHv7UpiEV9u5qvMN03gclmcANUnUqlIV/tjpw1Bd9FpMdonyI n0cXpvOH2x+FHw5OSsxNhQ26AkHeUwFIgOG5PPudVLg4+Gfxjkog8p6RqjyZ mAoMp9fKkiuDEfc7P9ua6FTQ5Inoz/kdgk2wjlsmNBVELz4qOasThpjTxYnX PfD7+V2EtQ5HoPpgL8Jnx1Q4ImhqIrcQgcwcatatbFIhf+HgsvfzSPQEiVr6 6qcCi1HNEZqoaKQt7MZBoZkK0ZdW3B75x6CtAxVv41VTQW6/ZSNXUCxSJglL 35dNBdeTqly+pURE/uy4KiCZClUBn6f/DMWjWx2lxVWiqUAju/nsNlsims05 wdrOh+PV03t49FUySiTadasdSoXulre52ZKp6Jz3w7DhA6nAd0Lg4BvzNBR2 lW95iT4VJp5mWeTuzkA644RjS1Sp8IC9L7+AKhMJuRkZLG6nwLt73A1tDFno H4VvysJ6CrjOPK7Ydfwm+piR3j6/kgJVVPnCAddvoTL+8q2vX1Og54fcxNWk 2yisrkv062QKfC3koGoau4OERv7lzL5PgeqRBrHhl/fQPyfuD196UuD0dndr iOZ99PGPBP2XVykgcWLiYc3fXFSWqoVmXqSA3ZM/jvet81HYUVef6doUOMq7 cCVUrwDpPI1/PFWRAssLJgsUhoVI6PLD6clHKXApf8hP1rkIfXQYU5vIToGQ Jaob5d0PUdnWr6jxjBSIliz7FXLgEQpLYm0aS0wBb8pMSqWAEqTDK7I6Gp0C vlmah7J+lCKhKlWB0ZAU2PnHW8ga9xj9k7MzGfFNgTvn9kSlnC9HHz9EZHx2 SwEfI/oLZIpKFPar4e+wZQo8XX0qZhpUjXTiP4oPG6VAceomw3BGDRLiXnUc 0k6Bk6kPt9RfPkX/njAUDF5LAR0B1lNcO8/QR8KJ4Y+XU+BBfzsUadShsn55 xo+EFHDPmiS6vKhHYVZmCh8kU0BNM6KcWa4RCcXerHwvmAIVFvIpzfdeIArO 6rn+YykwYFDQ6+nTjAZLe7n7uVMALqnZlUq2oLKLC5p9bCkQYKfuU3e5FYW/ 3UV8x5gC1EWjQmu2bUjX/HDzW9oUmC5Wd/LLfoWEvkuv9/5LBuOvijMO0+1o kM3T4s33ZPiy9Id4/ulrVFacfKtnKRna9jOKO6BuFC5V2tv9JRl4ZX9SVc72 ICGTKamuwWRoMnVUWgx9hyhI266v3yXDndbetz+l+9FgGMfDztfJ4L+fgpn+ 8nsUXqS+v6MxGexj4/pUYz8g3fOOV9prksH3OMSQXn5EQq9jQl49TgbJ5Og4 apohNLj0YrH1fjJY/PU6/KPlExI6J9zWHJEMYomnHnNNTyCKdqXNl4HJcHSK oUpRYQoN6lqdeemVDBSm6ioOXNMoPCD77nPbZMitZNVgGZhBgy10Xg0qyaDp WHDugtJX1GJxzviTfDIcTO6KG+CcR08oTBU2LyYDe+q3FJ2v8yjyUg2r1Jlk 0CKwtai4LCLXqbFt/RPJINetfSqFfwkZhtPN+h3B9y3iX78xsIREW0ye1bPg 85r2vSMxLSMei7icYYZkGI/zOROWs4zoKGqif1EnQxy/sbQ/7wpayxtz5vib BNaMr/fVZq2gCUSnK/krCSRDAg9K/VtBPZNnZfVXkyDdU1zqpBkJ1YaZHPdb TAIaJV7et9UklH84jvH2TBJQ6VpyJm6RUBJU/6wbTYKtxbHICSky8jcfGx/6 mATsUfU8+i5kZP2PtnPjbRIc+LPslHmHjNTzzlYceJ0EhwYaTGSek5E0Mrkl 0YLPQ6N+nnKIjI5PxobqNSYBa73nRuYiGTGHVdv51iTBZaYR8eINMtrhHVO/ 9TgJ4kal3L7+IaP5ZlrJugdJUHncZerPPzIaMDt7eOh+Emi58nWl4M+b/xrT bdxKgmOeQYfFfpFRaW4smT0tCb5d+1YZtEJGWYTq4fPxSZD2xDqEPEVG4ROj oBuZBLfHfAIZBsjIKZS2xCcoCVC5h698KxnJNxv717okAeek9Ke798jojFms xaBdEvDGH95wjyOjg3+rlH+aJ4FrrqBhrycZrcrSHjyvlQT2KXxRPCpkNDou Sql7NQnOjMzvRIqTUWeI8aK3YhLY/hAhaB8ho/svqxqfSSTBe2NVp97fJEQ0 HS34KJIEmjWi2rXzJOT9hyZh/WQS9D34tU4cIiHz+6KebMeSwGOhp9O4k4RU ZY2NxLmTgJv+mwOhnoQkxmPkddiSoLa4hZZQSkJHQ6qEvBmTYD/V12qbHBLa e2iUJYsW5ysm9WljGgltvqDZfvovEe5q+Q/LxZLQrInolw+bicChk1T1L5iE +naM3vz4ngijo/uHfniTUFNOzFPWb4mg41HEfciVhIplqu6JzSZC1d0zr/wd SChjbCRKezwRGnrMy6hsSCgkmMbZaygRzgbveNZakJADj6hOZl8icA+LliTg etN5YSTztCsR9jrcmwg0JaFLJjH8H1oT4VUb1UAI1sI7lXt/NCUCbUZK+P8/ fyBnZJ3lWSKkuPTJ3cbPo5KhGT9Xnght9+bHsq1JaGVUpEOrOBEkbz67F2dP Qp+CjMo98/DPD4CJrjMJtXPH3My4kwjS40JFvzxIqPJ5ZUhNeiJcpPF5aOVP Qg/uU1UrJybCUr5ZFn0YCd0N052diE4EK3O516o4PtEK26oM/onwl3yszusW CQUcVw8t8MDndRM/fCWPhFzpCqolnRJBOPKHWFIJCRm+UeK0MUuEO9ER7vIv SEi9PPvqln4i7Kx/PZOH86eYuhyappkIxUsU7xXfk9AZ7Yy5F4qJoKB846E8 zv+u0fEaduFEULxrZbHBRsb5Ev36mD8R5ApC8+Nw/ZByow7K8yZCe7CWAPsp MvpkJRjuuj8RQmI+SVIpkFH5krfa618J8Kp8eJrgRkaFva/DTb8nQDzB+Mqb ADK6U8H17MdSApy8u+sSezQZRXq2cB2ZSICpU68ku26TkZ8Oq3rdcAJI1XmJ HS8gI2cJu4hr7xOAtfB184kyMtLfYljwb0+Au10RGvS4v6+NmXHva04AXnvn Y5Nt//dPtfrD+gTwraE7pNxDRpL51JEXqxNA8JBd6qX3ZHQqUr/2fVkCnMqK EegYJqOjNmUL9g8SIHrn9crAOBkdUPrD/fd+Aggw/Vaz/0JGe09qXM+6nYD3 G1vG8AUyotxTFCmUngB5eRHq3Li/N779rG1JSIC3TjKpkt/JaPmt8qJedAL0 uow/+rBORtOV93hWQhKAZ/erLhKeD0PppOtRfgnwaYUQQNwiozdeclEHPRLg /pTjzfwdMmrRzaqrdEyA/Y+Er0n+JaM6yfnFyzb4fs+NeNTw/Hl8UPrQmGkC FKkGDcxgnb+dpOGpnwD8NOKxv7G+NT4ZtVszAS5Ss9zOwDoRztXnqibAgnpb aSV+XnhBzJK4YgIE2Y8/0MLzyyfq06E3sglQ9WSsPGSbjBxthTUtJRNghyr4 uNhvMrK4Ehr9SzQBRnNiHvjg+agr+L4+WSgBKoxcN6/8ICNVBv5vfPwJ8Ca7 6nA5mYwurfjyNh1KAEaYUSr5Rkbn+7o1NTgSQFaJrl1mnoyEqnlivjIngHFD LJvrDBkdznRrCN6TAEadjp8Qjj+bT9s3FuoEiHWh7a/F+fkn5aCFfsVD/SPz 2ftvyOhY622aq6vx8GctPieunYyUVF436C3GA+eVD7c5X5JRiqHAYdfReOhw k315uZyMeAJnv+VAPBwpX5ewTcDno2LLK2mIh5qNyr4jEWRkk6Cg9aw6Hio6 Wy9W+uH43i1seFMUD/RP+o4b2WD/eG4RsxUXD6CruRokQ0ZmCmlStBHxcDlq 116rc7h+38C3/YHxIPsuRlHxJBl1j/JqCTrHw6mju8b34f4x2BnjNdCIh2pK v6BLyyQUHL13wFolHu5udbLEzGC/2ysT4yYfD69fV7AtfCKheZ5732LF4+FB 38YsB+5XX1nDhlrOeAjadd09uBDPhw6iU+v+eKCys+FgvUtCzWoNvG/3xEP2 xdXA6XQSojHjiJndIUJAiqa5SCQJnfyqJLX6kwi+sToBTwNJ6Jqr77dtEhEW au5G+nuRUFbooCbrNBF0KpmZ3tqSUAMtDc3hESKU/WXfZ2FOQmMp4g1CH4hA YtT+K21IQnx5mbzyHUSgljcUf6dGQkonXr1XaybCTvjUKlGZhBwr16IN64ng xXCUmKZAQjWg+c29lAjlf2XG4qVJaOhKRG5wIRFePThyMESChLb6qjSJ94jw Ts3qXMs5EuI1mKLOyiKC8FXvfG0REpKb2teQl0wE2d9aLZKnSMjGATk9jiXC D6WzH50FsX+tuvLWhxHhLb8M9Q8BEnrin/u+zZ8Iewx/m/Xwk1A/xbvodx5E 4P98aGTtGAmtE/9IjjgSofCdoLbzURLi2H/625w1EZhCe1IljpCQdLZJ7ncT Iqi93iZoHiYhs6NJmn90iZBqO7f5nJeEIkufU9NfJ8LyW7dLvlgXn/1Wz6aM 75fyMDIM655GLqcjckT4qRLPOYz1ipwq7ylpImgXEJWC8fO49hbyVIgRwVDv Q68xfp/y0G8u0dNE4L7yNS4En8c3X/NgjQARbqml1kzh8z5wLOUQP0KEQw9n A6LxfQbEKQ/UHSQC7dbUH3t8339/DdikWIlgROeimXCShE51V7E07SWCw1/u oCUhEjLK3L1fhpYIjSDkE3f6f7+32Nf8Lw5OmVw+YyGK+etEA+Ol33FwIiEo 3kuMhJhf2O9RXI6D73ptQZdxvgixsLtzLg6Gv9IWURJIyEmDg055Mg4uyuQn /5Ajoc7Zzl3XBuJg9rylhZcqjm8FL9W7N3Ewk2aQ+Fcd80CAL4VGRxwoorF/ jdq4/hkF/mg3xEHQvMTKc+y35yRiNoxz46BZUvpyK65HC4rx9fHbcWBJbLJ5 EEBCyT3iP8zT42DwZrPlY+yPC2azZOvoODjeGqnEm0RCeXEKi06OcRAqzbVm X0xCvZr35les4yDDPc5EuhzXF/ePOTfTOLjy6NSnY89ISK+qcMZLIw70ounH z7RhPvlMORYkEQd7LhhWUEySkL9Qy7tEKvz5tvfljYNkVLzO8ZZxJxZmc1uz NY+S0YdmtzepP2PhvYSNcjHu9zPah7syF2IhkJTeLS5JRrNBoa333sXCoSSj 1TptMtJ8K/Ps8d1YqFXI/zZPxDz4sMhGPSsWnEbn+DZSsH+G7GH/nhwLDE1f Wb5m4Xl75pOPREQswKy1vF0+GT2gRQKfA2OBmEh9dv0h5tGJh0NB3rHwxJFf zPwxGbmmekm22sfCoi/Lxa5aMqqxH5m3towF1mt6qL2JjH4iuTu0xrHwVthN JxvIKHiV6fdV9VjIskjkf9OF/abLp5R0JRY8rVjOC7wlI+qCMcN0uVg4tqeF Uh/7ZaJmWdOQeCyk7fPblPhMRu8E9zsFnImFPE7mj7NjZMRC5c/NczIWbK0l +2wx3+qNTLxpPhoLwQeuWDRi/7xbcznYkjsWXj7toJ/8SkYTCU9OUbPHQhMv rdEQ5u+j1qzjxUxYa938lrtMRiWs07LLlLGgq7XiX/i/n367QkrZjoF2jo25 Mew3Iu0VuWd/xgCNwG/f+Z9k5JnDfv0jKQZe+GRRtWF/rfMO/ue7EAPR3n5O zti/tq59qTw4EwMPinnyv2K/JRxXtXgxGgMzfq13RbHfRv6pYjYfjIGhi7aW qtgPOwY5Win7YqDkuzuNOPbL3RWhHg+6YuCL8/uiFayvxc4dvdIWA9BRbeOH /TXN7NrA4vMY+ORkFvQe648STyOTamNA7C+VwA7WnPu4xEQqYyA9o7L8F9bG 8+Ff3pfEwFfjLdt2rHNhPtO7EJ+HffSJFdYzt9UVOXJi4ArRb2kAv0/AvXa9 8WYMGCR+TmPH+oYyz0OT1BiYnuzjFsbnfXIkSvcfMQZ4JlOY2fB9VjcXaQoj Y+AlV86ffnxf8fcadYrBMXDjnVqgFY6Hf2m93bxPDPzMGBboxvF6EcHLkeAW A3n65Y9psL//M4x5fepGDJge9GvkxPwif27Zr88qBqx823fvWiOj2D3aJz1N cPzd7ht2YL9nen4kvv46/v+PnfkHl8hIKzPugpFKDByPLZbjx7x004m0uCMf A05jXsXqc9iPeV6oykvEQL3CkQGpSVzv68e2Z0ViwJ/7ufPWKBkV9cY/jhOM AbPUnp93P2FeCNHf+5YnBuget1cH43q8MLH2Vn9XDGTeqBmYwPvSExOJv247 0ZhfX0zoY//nHQ04Q/wZDcb7hMqeNpAR1SeK1IZ5rIX2bnNWklHPeyaNg73R EMPzxa31LhkZdQgNjGRFg6r1oZh2VzLqVXCl+pEcDe/KB34z38D10lZ9jiEu Ggjy3yL1rDF/gFTmxYBoEBc7IDegT0bfGpR0ckyjIVHNq6X6Eu6vJ1ZDpgLR sGfSV+gMK+ZloWJa38PRMNys/7uYEd+3dFEihTMa2sWWG0/tJiPFYvfbzXui YTtpTsv6D55H+aEGh8lRsPfIhHn2AgmF8rYRJRei4Gb/gsWtLyS0mkPTeH06 CrrRpETJBAl9zE46GP4hCuxE/T4xDpLQ/cy7I1P1UcBlTvHiF55vzCwTe35X RUFElYBJTTP2r7SjF/eXRcHkFTZmYhMJ2SWX3JPLiQLKlDjNuBq8vzAsvzG8 GQX+j/kO1VTgfS9BZMcjJQqi5av9t8rwvhBXZ1IYHgXJDM3MX4swv9BsJTUF RMFibb9OQj4JsUTLvhzwjILLzjuS6vdJaCO8/dAu2yhgzCzIl7iN97F/dOrc ZlHwQ37ol3EWCY2EXA0V04+Cs8s56YWYX5oDByasVaJA43LcfBae79IXCUZr 8lEgDub0DgkkVLddOhguEwVxTYunDYnYP16wa+6TiIIhVTmiA96XKoIjeu+L RMEduzylW9EkJCS7cuWUYBT8vB+dMYN5qPiPwaumY1EgwJCUphZBQsea2wkq PFHAd7LcYhj7S26oaNMwexTclefgDQ/Ffo1yztvti4JnP40mr4SQ0K1/dNXr u6Pg/NSNujN4X2Vp8ToVRRUFs01ZVeJBJJQSPvlo/04kPL9dOWSIeWuP3FW+ /J+RkM5LfToX+1ksZX3uGXIknLpg/ZQSa6q2Y1wvFyIh+95F22i8D4ZEpty8 OhMJ/7xuXxDAelN+i3lkNBJ28gT55v3wfr7LLslhMBIODVoyv8Z69dV7ul/v IoFBxPJbB9bO0bJRMV2REMAvffcL1guKpX9Z2yJhxK3872H8PBsa9sDC55HQ 1eu3EYj1VEf4T9HaSOBgUDJex9okdtkdKiJh+1IjVRI+3yclg2W1kkhoaEpo lsP30aFrtx8riISmOFcTdnzf/tciXxzvRYKhrVExLY7HNeI9s99Z+H0Oelbs OF5dynQjcSmRcDuvVksOx1OR3kv3ADESUAatRAKOt0yC6jWxoEhwaE1/6YHz 06Ba97rVOxKUWNp69+H8iTMcU9BwjYTmANqH3TGYb5J+X3CxjATgELJIjSeh kmu2tdtGkZDPeznjbiIJ8TO+F03QiYRV692nWpJJiCel5MSjK5HQR9nBbJhB QnfU2YrOy0VCjOTPtDe4/tj2hfO2S0eCloDCFz1cn3vT9NmnT0cCU/GcUl0O CW2n0+7iZsP5eEFtnYj3a18tz9BSxki4+/X5TP1jElpjmfgtSRcJywxPgn7j flnKrF3V2YqAg98aFhtrcX3ftJlImYoA6ZWF1iPtJNSU3dZIVR4B5ldOhtDN 4nxQMNTSFkdA3AX5O7m43/fZa1ftyYuAaJ8btxVW8Ofis8Us6Vg7b1M+2yAh xj6arGM+EeC5z9+BYw+eJ9QqrvKyEZD9yBIJ431kj1P6DSWJCHjqdVBaBvNI 7fvPNqoiETDw+VWSGt5f9uQ5GmsdjQCWP3EdLkpk9OxCkrIVTQTs4VP0SDIi Izq3vmORb8PBSUnoSAzej2oGOXhjO8Nh0+z74/OxZGQiY3EwAcLBYfra+c94 n6qi/74vozocSo2Q4EYmnqcPWP4U3AwHnRcoxRPzCjWD8ebDlHBIzf+38rCU jCo9in6UxoXDwtbeG514P6NG4kvVAeGQK/bp7xvML+WfdYdbTcOhp7Etfxjv dwaXcgc69MLhIaVwkyXmFapHX992X8fvf7Py/QPeB/W8/drfy4XDKE9cqusA GVGMAgxKh8NkWMrSzUG8z8ntfv5ZLBzurfmpF2E/odiXXT19PBx2FOs0XCfI qMxn+skcbzgQNT0ZhKfxfjsmWLLIEQ71C1y7ezG/lJU25X6nD4fV74tSjdjP dJh33f1JFQ5aRlJPqfF++3flltCPX2FAGUvaPrdCRo+IDRy7xsIAaSW1SGB+ Oelp73ntXRhcls622IX5pcT4wNubLWGQz7jZW4P9VfByx4nJmjDA22WfIvbf sjPekScfhgGXgaRkI/ZnYU6+cY/bYaAnRvy0D/v3E8oByefxYRDfx5SsjP39 9LfwDOrgMDCofypmjff3io8iK2quYcB6vbjKHPOASPPEldsWYfCPyWdFFvNC 1aPkwimtMNjPPv/pD9Zn02X+CF4Og4cNrPZ5mC9qAr/pe0mGAd1z4/RjmEfE bO7WvBAMgxFGI704rJ+pqTDS8oRBCttk41usz0tu2l9nCgO3WsqOn1jXHXnU dociDARvbcb8w1pyj96hmbVQqJE9zPwN64Yf1P7Cc6FgemY5qAHrC+NPB7yH Q8Ew48tXe6ybOq1ON3eHguznWK/f+DwXq/YT6V6EwrFFNRUXrF9kt8xoVITC 7qZbWa/w+WWi3GTv5ofCiddpsTv4vi+dee98yQiFLaUzupxYE/Terp2KCYXp 94cucuD4NKNgNV+/UGAxKfL7jeOJBIVL4EYoWJnfUYdNzMMsI1T0JqHQvKCy +waOv9wO0VRLPRSu7nb4voF5s21OsuHepVAI4P1tdAPnr73hpsuZ46HwNcR0 959VMrpcqNjlxxEK2xYLVIcxH3Um/jjWSh8KNApc3wRwfXSZaX7SJoWAiE41 zxKuJxVlCrH7UyFQF+x3sRjzcc/ZyuSvAyFg4G21pjJLRm+oGRUC6kPAt7Lg twrmpWuk5/fbSkNg+HGR9CPM373DjpsMOSHAojWyvvI/n5d1leeGh4Dx+crh Cx/JaEAjmrNdJQTmbFh3jbwmI21pMS9GmRC4Wu74IB3310e+mbd6Z0KA2Yl2 tyTmqaENFLXIEgLnP07ZquH94XPO9grTWDAE19vua8T7xtSC5ytD12D4KFip y55ERt56ns9SLYPhMN1JxQt4v6Fv93jYoRMMeW3kcd1oMjqX5x539mIwaBa/ PhEUTEYxuq5X6XcHA4kLiqKdMd+13fjQUBAE4eekd9Fdw/kRudFOygqCJ0Er tT+u4PPed6jlJwZBSqOt8rQC5it/+9tprkEQeWOTuvUivu8ZW2OHi0HgGtXk ni9MRl73LL5wDAZCwgzn7yt7Mb/TW3xU6wqEmtOiYUGYt3J8zTuingdCk7DO pXpqnB9Ns0fkgkA4SLTjUsH8xbnbxOm1ayDoydpaTJNI6ImPsckfy0AIE2/a sfxGQnJfjNTEdAPBiyS5sTJPQo7NhiJ5FwOB6RKzh+A0Cb3w1v/huzsQbIo+ n5P6SEIaM3qzT7YDIPJiqseh9yQ0d11vcIYUAHTcFs3M70iISVi3Xn0wAC6f 2ld/rIuELKe1ggQKA+Cvz5uTOy8wP6lrOZvcDAC/7K1FQ8xrCS80TTOIAfBB fZ78up6Ent3WQH9dA+AdfwUMYn6jVVffNXQxAOT9L9c1l2J+oKNb3zgdAIIf vl/2f0RCi60wy3EkAAx+LVFeeYj35fNnOw2pA2BbRHaWvwDzF3mxLnDDH2LK 5HzF80iosrTw0b0Ff6i/+JvBCPNcxiG2+PFef7is0bM1n01C0cO9AX+b/cHR nKNU4w4J+aTHOB6u9oflLVua/luYL68SjC8V+YMp8xUxu5skZEDz66rlTX/g /JiszYr9VxUqZSLj/GGf9dHoYezPFwMcThcF+ANpCU3VYB48JXaUt93J//+/ fwt/mEZCvCufmeZM/cGDajagMhXz7aOMfzQa/jCrvTbZn0JClJZXVwXk/YGr MriNHus1LurpK+L+4Mm+fsYI88DsxxfvHQT84eqFJZE2zJdDKT5t8Zz+cIlF 4a0c1q+Vzzwt2+MPdqln937GPNFANV/0ZscPrD/zkOOwLnuRl7VM8oMn14d9 1LHO8TWIYZz2A40rDvdPYZ0sut/3zAc/UNuSsDiGdehSt931Dj+gPU5bJ4K1 +4NIffd6PxD0IWfqYG1ldlE5vdQPrvNaLadhrc25LlVzzw8a3KUrZ7FWHHgi +CHZDxrDm7qv4/NJJNlyrYf5gd/ZYIEBrE8q8TKwe/qBRGFuuRO+30GK4e3z Nn6wEHRfkQfff09T6rKenh+kVAS9+4L1jpfyuJ+yH4z2PxRuw/EjnaZ8d0fa D/SS2KXrcXwn5xubG0/5AdMhucE2HP82Y+H8bWY/UKaQYz2E8/WMfTaNZ5cf JDe2WDjhfD7sy4mQ/ekLo9rX0vpwvokKTNZhn33h91fH/k+4PgL/dGrnv/GF iqAg/5B7JORUH6bY+tIXHjvVnpXE9aQu/P34rkJfKPnGvLKA94dLc6UH+LN8 IWVH0XuqkITO5lnRXY71heNf+w8sP8C8xvpxIdbRF4aFE/L+/33TyFbd4z1i vkD20p/pwvXf+8wtR/i4LxTtv+VriPnrpevJ5GscvnCbh29gG/dL/ky2a8q2 DyDiuRTvlyRk3xN8lqXdB87MdPue6sb8vDu24XC9D2hZRRbt7SUhT6VUdLrM B/x0Jsd+434NbitQU07zASlOVfEt3N9pTZ03Qk184O4ed7t43P9NZcyFS+ve UB9XEHlzB/d34gOWV8e94SH7UYt3mMdYu8uz+zm9QfxmgUY+nl+cdPVHJhi8 gboz3NYLkRFfVPeZ39+94FTTTT1uPP+kgkiqIs1esKD+stNOj4ysnKSi7ul5 QcXTy56p3mRkXyq3p1TFC7K1f56T9ycj53nV9DoZL4hes4olB5GRn7Vp3vtj XqAcYXpVKoqMkowjn9ORPSH5hOwFv3TMh1d7f3jFecKwFlOMzhN8nqGUQOcA T1AU5THuwPtyoIUmpa2TJyh9LKo8+RT7qc8Qk951T2CIc+ToaMTzM3dKUIrD E+YMlY+pdGLeESyqEqX3BObL40fku8ko4amtpOC2BxRd8NcX6iWj611LilyT HhDURbPWiff5T9/XzXeKPWCYi0h7AvuZdHD91/U7HlBGnJtMxXyWQxvospLg AQ4s6hfnpjDvcv8LnHD1gP4mBXWdOezHD1sphy08YPxVh5/LPBnxi0YT+7Q8 gCkD0XkuktGiIv2tFgkP4OoVMJbB/nut7w1P40kPsFHzLKHE/lxhmFJUzeUB D665uFRj/2ae1RAq2+sBfzM2fa6ukZGnK2t14V93+GVKk96H+e3j5qDkvVV3 uPgqJk0W84BE1J3mzBl3oJ9NVrmJ+W3r9qHe6E530DcQvUaJ+cLk2JRWSIM7 VPvevM6Oea35SeFnnzJ3SKSVC2fBPHJE0tbCNccd5tX2vNrEOrL1xLxdijtQ 3N9F0YX5Zfbqkot5uDtMt4ccC8e8ozT0ZF3f0x1utdMcPIp5qMTCLUjDxh1a NfQGy7Bm+HaWSkXPHYyuuV47hHnK1WedKKfsDvd80n39se7/V7dPWhq/v0Tm +guszyUE3Dp3Cr//y4nBBayz2GQOCfO6g/UbxT1/sd7I/VvEx+wOSZHPf2xj bSDYKsRD5Q5UW6Ts/3//5G1PZy244AYr3mG7a7CWCk5y5+p1AxPTU+qOWO+k 7Q9lqHIDZd1vwQxYtzy8lbiT6QZstAOlN/F5o5u4s1f83GC59PjKbqxV+vKL J4zd4A+vsJUtvi/T7PFnfcgNvAhWJx7jeAxslrW28LmBrZqE2QiO1y1G0b5q OjdwEjkt/APH1+hY7VjhN1cICe+q/YnjzyspvZTZ5wpZ074nZzDfzVyFX9FP XWHh9/2qBsx3Tj7dLPZBrsDreLmDH+dTNEH9iIG5K8zH9TQ14Xyv5344raLg Ctdjum9fxPUQ3DWuLMzgCs86gjb/ksjoDnsebx7ZBfLGDRVUcX3VWlmss3x0 AaW6EuFIvB+QdmbytnJc4BMz62QDrk+Lswsb3WdcwN4b3f6f54JDS3tlWV3g AKtPFOU4GWW/cSys/uUMR2S6jEpG8H1tV9SyW5zhsOgLzna8zyjeXXvgoOUM 5q+eG8ji/cdi/mngmIQz/I45wuGL96MQcR8NDW5ncE1iTMjvwDz+7te25KwT 3NibxtwLuD93/dGi83X6//v9CCLu573OdJTF2Y7gcGj0zfc7+PPGrqGDoY5w qNO/3Ocm5lnahCfJVo5w2KTx/Xc8L0Lz9xr4CDuC5htU8BHvf6sf91cqvrwB DTvaTzQw332U5TH9MuUAljYVN2PMcP/uO9t45KQ9nA72818/hvnRJvO5C5M9 UBt8iLh9GPdr08+XTet2oNen1IZ48H5j09Sm02oHcOnUqQJ2MnreqNBLNLKD e8Ky6lWY30as9SZXk2xBo5mOV34V80Bjw7Ssly3UWdg/NsH7shUT92yCoS0M 8hxljVjC+3jD5AK/gC280jfwXcD79hbjjTUDsAEGByUXqRESIli/WX/40AaC i2/UlQyTUGTD6V9riTZw3/lKB/8g9k/rte0kAxtIHT/HKteP/bUhiKb1uzV4 9mopML8mIRPGCTqmT9bgc/XqrVm83+dbXdpj3GwNd+fsr3W2YX9mpNn3M8Ea KkTi7/z//Zuzlf1+eQ9rEOiKjH2J+a6qvps1Vd8aMrgT4oYw30lZpXAK8lsD dc9uGzHsV8H1q1y+e6yBDDNJftjPWvZqH3q1agVW8d7WPU9JSLme45jpS6y7 Hz7MqSKhpL2B/GVFVmA4N6LNU0lC/ZZjAr/irUC0f178cTnmr70Fwul6VqC1 UUDzqwzzi+WuMxMyVtCx/vfUM+ynU3W2osJ8VtC74rkRXkJC/Hu7zvnTWwGj klOgKeZHB0uh8x1kS0ghjfepFGM+rkuSZBmyhKyL3nuVME+uMpAvmL+whMUM C0Ut7Nd+dU8Jv4mWEGCkunoX+3kTwwE5JTdL0Kx8EzOMefOvhb9Cpq4l1K49 M/yfP+XrRi5PXbSE7sTrARGYB2IZZJVPH7ME+bGQVRLm0R6LPNXA3ZZgzfO6 2xlrpjpKtdckC2CUVGHaziUhLQab62yDFmBS3diRjfUti05Ny+cWcO+H24Yy 1lnq97Sj8yxg33b99i6sM2TcdR9FWQClWJ3DAOaRNKHL+j32FuBybBY9wzqZ k8tw5aoFrNLPR5RinUBLNmIWtYCye4Gna7Amrr8yEWOzgHMNtugd1ns7zr58 smoOMVmJNX+w3l0w2rLWYA6u576HXcLvow6JaZeKMIcGpuLcW1j/MxDpClUx h3mN8V0U+D5b4p/ftO83B6bl2cJgrDeYo/r2jJjB7iNCLntxPNaWT33QKDQD W5tTWpVYr3QNDd1yNIMMliJki+O38CB8ZOycGVSLqBw9g+M9Gy40cWzbFHx+ ME/TF+H8mnycdnhlCmsT++w3sR6VCp2rSDQFSmn/7N84XwOr75eleUzhVZdo phjO97veoNXwWRMwZ2s95Izrobvk+HrnExPo2Y9G63C9tFgEbGvJmsDJrWTL yCd4/5Hh+3eHxgQu/eSbpKogoXrOt1STb41hUkTydxaux4r+I3uczIyh5Px7 gxXMa/cvdXFGhRlBcsmu5hu4/u/wePJ0XzGCEAYOfk/cH1mb3Ef2MRvB5oe0 hwm4f5Kq3E7cyzeEq3yTB7/h/go8wiHxtNUAODfElawxr/nutFz4HW8AL6ZS 9n/FvObxyVEWaRlA8d2QvX54/3JIa1Z8M6MPWvvFQtqGSEiPwk77yy59yFCg dfqF+U1rbJ++YK8e3LCcn/iC54VaQ6ORW5Ye/FRUFh/D+56iO6PVNr8ekHgK 5ch43pybeubOqqQLeYKEvptbuB5bdqUoELWhdlyXfBvPL4Mn5KWLOtogJZxt McFJRoV3Rq+IH9GG5OVKXSE87yQ9nlIeb9CCAfLexPd4Plocs/ahXdAEq8d0 sjqiZPQ0us2k+4oGSC9dez19lYz+ulc0trJqQOTsVIvhdTLmT/HT3nAdcstp KQa0yKjRaTZfl6wOcQc81loN8Xx/p0DkvK4G3ifVOG7Zk1F1BpV+LpMqCGX/ fdoWiXnCaYQ5tVgFSB/F6A7E4vmqUNMTRlABJ8opIZt4MqL+aUmwdFWGDQqK JHIqGenptx7nf6cE4nc+2TfmkNE3kexJNjslYDGZJH3OI6Pw3R7ZNH8vw8wy X9FaIRmVNh5hnD99GU7xWl9jKMU8wB2+XpqsAHuUMz/1P8PnX9evuHtcASL7 L+2U1pPR8bciDokv5cFgZHjAv4mM1EMnR51X5CBDcZ/zBvavginCKxG1S0BF cFS70YP92/P01qUeBA82JSgXMF9m8Y27HNsiQKPwc0GjPjKaj5HRnTOUhZHZ 230cHzH/qm7zOR2UBqqss77fMW/6NSd9tlK7AFcfHYjawrxpdY431ShCCjZo Nx/+xLwpxSW3pbIoAZ4WJ01bZzGfpwxUyh2SgMAPL5PSv2I+obKxvaB5HgjX Z3ZrL2BeW4ztP9koBg60zqdLsf/3mXLGHlk5B9lmY8GymA+a3pde5Dx6Dvps tu3aMD+kNfYW08WLAlnf2/H+d8xbRi8a/gaIQPA1K8kfmDfeyk/ykaZPQ9Sy AO2FdczjLMe3equFwExM71gW5k2NrSu2Lw4KwiplgGgp5hmBGcf+xxEn4K/X Wms55p2d7uSL9xaPgxK/wfMCzEMD1VXFCZr80HSYflcM5qWS7A/7AxuPAc1z jgh9zFOhERvBN44ehW0Vo8MHMW+VDJzrr2Y5DO8XbLq7sdYt9C9Om+EG9jd5 zjcwn1F6Nge71XDCiWXRzV9Yl8tRa6tHssO/fg5TH8xzhvtVBU9rsYD8iX0p 0//zadvhfxyKTNArUB0mg3nQxvLx48EvdHCXbHoyFusXFJIGmVGUwHdBN7wZ 65OXYugLlTaat1FexBzWVX+kOqT3fmnuXzp08n8efcFqdUz6QzfBJD3Z4//v G1PoHIeGf5IJ9Q0epmtYH+g4lOH+fIfAbnFq5cP/32cqROVsvaRGH+z/8D3A eqToF1mGlwEdI87TWmMtR1VXgIAZnZbpzWHG+uY59zcWZFYk4+NAeoLPv2gl 9DPiMAcq+i5BK4W1TOYsb9F1LuTBcnO1Gt8/7VWucnvYIfQIFT3nwnot4FTj mv4RVG+g7+eJ48eTQa++a/Uoepfher4Rx1up7OsMK5EPha+70ZNxPtzbXvnx HzmOrsoW7GbDun0tpOCyxkn0hffOV2GcT9IeYwm9BUE0EVG5yYvzzckn9cYu XBhV2xflUOJ6cNZeW4+rOoPOvM5jvYX59U3tvOI1flE0SFd0QhnX05ScXqrO qihi0ne9voT3nT1GYvy2xHPIQ8zO9R+uz8NfC1xddMSQHRQ+9VwmI3FP5kaf I+JIGF6UDC2RkVnCilpsw3l0MG74ugfm2eqmR36PFqTQ+vSnog3Ms5vhEZ3/ Oi6g9fh2wS7Ms4QrxuwGRdJIc/Kjd/woGfV8YHq620wG6fOkeY0NYR5f9iHd +IAQy+2+E724f+P3FZ47YK6Abkw0+HLWYR5cYzJqe6uABKObXuzBvNo/GBTh KqOIOi5SL3zH++mBHN3+zoOXEcsgn10+ni+FJ+ld/T4qoeXJf2FEPJ+a5NxL P6mook9fNH+NhpPROP94f3SDKrpZ+MlHNYSMKHarboqeuIryVWI5nwXgfLzj uxJPfQ0p2ji4BHqS0Qej4dkLoIYeWH4ZmrDG/XnhcJraXQ1EaeP4xUoJ9792 7JuKfTrI+OLBrtOMZKT5bCtGS0EHKZYEft61B88jdrdLG7466N1dlaYpWjI6 +Em/VnZCB5Vq9OyvosD8ayqY1/tEF/01+fTvyToJ2TffN3Sf0kXPWUMCWr+T UNlhFjY2Nj10Zevv9gSJhERmtojGQXqo+7rLCYlFEpK27/VcUtFHI1NV4iYT JBTSdel0Sog+2pS252wZxf4sWDt/tlof6fjS7hL5TEKXl++bBHAaoD3GxE9n /v9+0sNNafe8ARK6ztXwogfz0MAXiidchujx0AZjWBcJDYoZPL+uboj74g+/ eicJGW1cEr1da4h6Ir+bsmL/tQ1i4RKINkJGOy2nEPbvkrHYj931RshyVqXD uQHzt+x2iss3I+TXk5xSUkdC7hSzu2q1jNE7q4faVzG/1lgaNBvEGqOu4pCc mmoS+tnW67/TaIw+7T1SdRLzbGBM7YrCUROkwvjolRzm15dfBUvmdUwQ1UM1 2rnHJEShnGuVSDRByqmi2bcxz8bsiRseIJsgIcvnAsKYV7qcttN9+UzRpdx7 hnsxz+x563aNS98UNbTwqv3BvJqWatBq2WyK9gf1DDNh/vmw2htEs2aKKOhc c0QwHx3QkpMoPW6GlpzKgi0wTxk8rV29ZmiGWGo/JBZg3rrHJvR4NckMmb+c Gl3DPDbhk2ub1WKGnrl5huhgfWSY5YjUuhl6YtcY1ol5zloqbmT0hDnKbkpb Vca6OHs7K8zYHCmtO42NYh5c2HK7zpdqjuY6jdXDsBY2maV/3WaO0hmZNMSw dn1p0O64YY7M89sXf2G+NEi1Q3TsFihKx/HYW6y3IJ/n8xkLVE9y//c/n95b HfldpmyBjmutRP/PrzJH2YeDrSyQmFVybRXWE5rXn6kHWyBCa3pGF9adiwcy VO9YoJa5Gwo/sS6PmHBTemaBpiLn4s7/z88Hi9Xk+y3Q208bxvFYB1e7CBOW LdDu+2WNq1jbqJynl95tiQ47smQ74ftdnd75ep7fElX+1l39jfW5gPb2s5cs 0Wzcvaf3cHy49icVnjaxRIEFbIMaOJ5Updrhgv6WKHGB8fJBHO/FS9xmx7Ms kZDAm+/rWPd/mrl4tMoSXYl69PoLzk+De9nBQ72WyHeQsXoO5y9/t+cvzgVL pOJmd2sL5zcu/8IgG7UVevb6rNkxnH+9/q60vTJWKP2W0fEyzK8EhzTX3QZW yNbwzzw9rqfjFAbXqL2tUFv4XdZgzLPrIvN0O4+t0He71QO3Mb+Ova6Y+/Xa CrHGeBUiXK+vzH1f/fhihaK1iH9/Y57NSKUJ+8ZtjVjmvwYW4XoPPPHWZF7S GjU/q0AZuB/wpiT9Rdsa9c/T82bgfhEl822MJFojpfY643bMt+/U5V16tq1R FL3i1DLeL+u+0l/t5LBB9NQXos1wf94PfX+yTcwGUUxyBU5i3nWusJhtdLJB d+9L6TIN4PpmCjMuHbVBkvysFzjHSUjp7XMV4nNbpOVgdO/uTxI6Yxt1InrY FhVY7987uUlC7H9UacJ/2CKz88Krp3fwvnBqpMVP2A6xnj1XtEhFRpFJm5L2 9+yQvK6a0TtmMoKr5wWUguzRQce6mZ+nMZ89brkIt+zxXIwXLTxLRhN7rmlK 1dijFx49AVrn/+cPq2ChRXvEG1Jl9FKGjKSV0waY9B2QUEhqZRXm2WeK30KH z91A9Ew12hU3yEjhgW+WhvoNpCg43WzvgnllF1VZ940biKWF8jqvBxl9b+Mc fJ5/A11JbuaO8CejM3JKwvlMjshA5Bb7/jjMK7IFww5Ljig8NShyE/On5P1T K9M0TqjHNenp9WIy6typpzI+6oSuWrYduI/9Yu75u9NqBk5I1Ty0i7OKjI5J 70Sd7XRChxm1zYgvsL9lx2WXTTshZ8X4/BjMn5d+s1Ty/XFChkx8n3zayMi8 QXCEXdwZ5WzU557uIqMcCX3RrQJnxBcSwbU6QEbCt2Yue710RoaPzqcFDmI/ +ulivPzJGdFl9e37OUxGn59Fx07sc0Fdua8HGzCPOrAx5+gLuyDxivM+lP/7 qde96n4lF+T+uqNfahr7nVjNWFuIC+J7/CjKc46MijNk1y5mu6Bjho0K3tiP z6910dU+c0EK6Rnp1otkpFM9ee7RNxe0y+UW0GN//8LspHzkv5rOPB7KL2zj siZLimwJoexbSfFjbkIhZA1tdgrZ931fxxgzthRJthRJyB5CtgpZWpB9N4Ms pdJ7vJ/3/fP6POZ5zjn3fc71vWfOedC5wEG1Va5mxJ8ebtu37gu4gHON1bY1 4oEUaab4RHMXYChKULuH+OFnzI67uKcLNJwJaWxA/Gk5Pnm9B+sC/yx9gne3 yNB5rlfNqdAFxrCl5qcRj8gkVUswNLuAreFlMRXEK5kzuceefXGBN1Y2XZcR f1IoJe5p/3CB+oETrMqIb+4QveeXGF3hPC5nlg/xUN+SRV/CaVcIv8V2cg3p Cxe1a8VUXCH3YnlRKeKn3Ptyed3mriAdNXzLDPHVwXXeREdPV/j2fVp0DWk3 TXqvQ0mu4GnqsumF+Ozzox83SwpdochXtHgOaZWdMQ3tZleQEl2V1UB8V6zX KbX0xRXOWL4JwyPNUljBkfDDFXZMh6M79/kyRI8ijdYNXLIfyK0i7VbydtOW 1Q2MGV5G7H8/KjR8YVGO3w1uHF1x2N/v9/lA2Ri1pBucLrg1Poc0VlJwYFDB DbzMjKcakVYxz+zIv+QG+mVWHuFIb0Yx1XsZucHngqvJsvvtKY94oW7pBqXT okofUHtvju48YbvnBpInVEJMkWY5eC9zxh/paYFb71F/285OYStj3CBIKndK +u/++SjT8CiiG9y36OIOReMlkdjrbZzrBrVFi6z1aDwnqlUdhUrdQPBU2vg0 Gv/LzBJGbR1u4Gs7f+4PiteuwuPLqZ/cgFg3QlpG8SyzY1eynXAD9sRv/Z2I L9kbKU5R76Ln5XbHaKN86F7w5hqkdYcFp9x0MuLLELZlpnxWdzDrldKJQPXM nNPQtpqkO7xZpFByR/mWlaG9zKroDuEiyu3vEV/qvX3zffqSO9i+FSdwonqp mrukM9LSHXp+UD/3R/kc0xWS9ZboDqeOYS+6ovmguPUDR8x1B5P8OmU1xJck /ruRNqXuwP+NgpsO8eU1PyNnqnfuEOH5644F4svTwiIYtV13+HfCwdEc8WV7 VP9kq6UHsD1V+lBehXjcNmm4yMUDGl7M6VpWkMFLTasHG+SB6s5fCpSILwUo WyqvZXrAQ2dHRr5i1L/Q8tiljx4Q1nVvofM+GeQDkiWPgic8Uf8apR6I5qOr rr/VCS/YoBfRuqxIhr969C6XxL0gJSXEXkoezUepdmtxBS8QxkqGc5whA+Wq ks6WsRdc/U+1cl0U8bWjBF881guSMr6cGORC423H0F7+2wvCFynl3+yS4J76 u9o0em9YMb2acGCHBG2CkWUBHN6Q6z/1WPcHCTymdjPUz3rDL4rZReoV5CcW S46fHb1BXYqs/Af5Qez1LhaKr97wkib1rHMbCbqr5Fx/znnDfz8YfF60kID5 SO77tR/ecMKYnUTxBvn9O5+ESSYfcP8TXvCxlgR5ckLUb1V9oPjrn1VBxGez ycnW9Xo+0PpS5MkE4jOR5d3mVzd84B2VU2Up8tMXj/uD8719QPnc+Ul/5L8N zKE70U99wFjhSOsE4gEKxyWTkGofeFRj23Ia8YNau0mlz1sfMArsGwt5iNoX KOHuMOYDFS6cUvb3ScA0kvHRYskH+n+8atzKQPx6hkrKbMcHbrd2n8xMJ8HI wpclzSO+kKl1ioE9FfGFuoaWKq8vaEa3ja0TSHD7UXmRgrgv9Bf58e2fl3i8 e5z2zAVf+Jp0bWMaj/zPJNZWTMMXhC5H+uwmo/683GgVMPQFljm9biGknRhv nzxu4Qt14WyHbHAkKHPoCmV19gUqWjP9qiQSbLTKjTP4+8Lh0Zyq40if481V oo7xBQUqrH46lgR+/gwP/hB8Qcmn+9wppBsGfX5tPvIFZYWDfp2JJPgnPWW6 +twXYq/Ri4QhfTFRt3q21hcepeGNdZCOmathG+/wBfZ140OSSHepCnkOf/IF j/cixvu/NzNmJ/d/mPCF/86+Vtz/PVr/5670u1Vf6B3tbdNGmmhkj3uz6wul O/Q7wUgPl/WvvKbzA99p9sF2pLkPKV8pZ/MDOl38TQHUvlt2xU+LT/rB9Zhd HBHp3GbWg4+l/ICloteBa//39OOh9vf/84Nv9baTr5AW9l1qS9H0g6lpzk1r ND6OAyaCCSZ+4DTCn34ajV+ZZEt4hLUflGoS6veQXo+TmAhw9YOlMM9ry2j8 5WYyMJ5BftBJW35tBcXHD6iyneL9wMqQtuQAkQT1WS6/bdL94BelgJI4iu9F A40a43I/+CpR21yH4h/9vJxdt9EPch5+DeXPRPxPx+Ot0e0Hf+XZObJQ/lxt 2pCVn/EDGuqKq50ovwhct/FS635wvjT7eRDKv2GvLtLpPT+YoHpppo749KZ4 7jMOTn9YLGv6y4j40tNxteCDkD+E9+tcpyokQcJTxdxoWX9Ibw96zIDqjVrh odQf2v5QLqJ9wQDxI7vQoZCPwf6gZ17A9qyKBJI2pn4xCf4QeIbHShzxoHpe vodyhj/cPzi3VY940JMfHJ6V+4PE5twBpmbEuzxe+rHT/lAgy+Pv0EOC+Rst 2pg1f3AqsFy2/kCCvSxmja0//uDPlR/j3I/uz/VUwYY9APiH1aifjqD2HRsX AK0AYOLL02yaQfOLWXNruywAXF1G3ZkOkOG6bhq5tD4AGu5EZ7+lRjyAnVq0 7QyAj6WyRhEHkd8eCh4fmAwAn2nrOg7Ef39oK96VsQUillWuTOdD6/W/41n2 AYFwuKKiPALIILZOxgxrBIHVeuB4aygZZqYjFfKMgiAmZm31TyQZcoY55Fys gqAu9t8J6TgysDaAKG1wEHAf31Lzx6P7xySzylcGgSOtgxchF93fX5CZsjUI mox0rwXmI/91fn3ww8cgCLDQkTBF6/Gswfe/dstBwELxXmIWrdcfeKQX0gSC AejWmLSayBB3+O2UlUww2PDMcNbsn6+lNB2TxASDkim/xLF2MryeDxloNw+G MYOBYxk9qP9fj75PcQgG1sW1jroPyD/fF7675R0Mdjd6z3X3o/Go+NCwhQ8G C4VzPCWI364XWL9uyQmG5mDuCP+vZDiWuf0y6XkwtPU/jDiD/CkhmLfoVGcw iGlWXLWYIoO6W8Xj9aFgiFnmFRiYIcOe9aWHjdPB8Krz9AMJ5Heemi4pJv+C oUk34GU68kOp/yixJ5lC4OefRdcCxG8Lkukxq9whYNNyjyOLTIY8frHwWpEQ MHlPfdEL+e1N1qbAaPkQqJHMSzqL+I2d1tDHQD0EBn0UHo4gv+7/Oet2wjAE EmQ3WC2Rn2OX/Z0WLULgt6bUo17k95fGmeyr7oWA+1zxCs8+r/U/tgwPDIGT ZOwLfcQLdW/P3dCNDwH57bhHDognvKq7TLgyQmBkc8nPan+/4dNb+rP5IYij C//s7zdcerCu/bIiBKTEItf+IJ2Pi9YIbg6BD4cP8eUgnrkdzqWi9SEEOpbf mp7cPy/hVap4bDQEqvD8rvvfBw7Yq56bXAwBFc4szP5+Q6z5kHTpTgiwerfm 7+83vKRzV8yfJhQ05G7/737DA/BXSIM1FKT2tLqW9vlNNoXvyMlQaMY13X6N tI/QKe4xqVA46cGjYIe0DEctQoFQUH112mATtWeJXvewt3YoGHRu5tsinf9n gl7VLBQoIikuVKP23yZ7UTPZhwJugp11EfWXc+rgv8+eoUD5KlT9LxqPT4MP f+WHh0LXkx/fN9B44d7JbLolh4Kym/deFxpPzbo2klJ2KAyNpDdFIN6iLDVb PPgsFHx/GKqf2D+P8WhlerAmFOSjftbcR3xtzSyjWdkeCo4jbtLHUPzogz2f EwdC4byAea8P4q1r13e9DFdQf069lF9FfPW3U/mL7K9QKPr42ZkS5cvAg+ac g1RhsPKsJmtvCfHhIWqqhcNhkJ534NvzOTL0tJyqMmUPg0vHP3lboHzk9b/s 8I4nDNSLpLh2Ub3RPp/QUygaBqyqFZUL++d92o+k2qmFwTtVl7JKNB/sgs5e GtIKA5YvvZPlaL7UnDX5qa4fBprExz/255NFXuZNoVthMNqAtRRB8+15KN+p aZ8wOP66duT2a8SfipLVliWofdu3yMmZiA/X9e70lYfB/N9zHzxSEd8Vu3Gr vA6DYRX9h5pofUjlqAzhawuDK0b2Nh9RvTe1qXh5fCwMeNjupF33IUPQC83P N46EQ3kUe8GmARnKhWx3r/mFg4b+0cBhOjIMnXsqYRAaDoWsb4o3UX27e4l0 +0pMOFR8OifAs4fWx7t+byE1HPz7flxN2ER+UIrFipSHg7cWbeHuJAl+N/U3 CbwOB+OrWK0AxFP8fezrPE3hMCwz30D/BfndRq7Jkd5wmK1sl77RR0K+U8W7 Ox8OOzw10WOIpwQ0d/U3SeGwl2+wvVaP6nNziCRthUNV93lJbuQH+MCu+Smq CGi4WVtRjviqCsvMPXYoAtbrWm7wIb76mm2kM3IkAnQ+F4cWPiWBUPNYeQ9f BFRomL6jeEICrX6B6fbTEeCX1SA6tH8+fMrhWLNkBCz10kW1Ib97Tb3hX/lf BKRvzHluI78cPXb+ednFCLhZpy+qiPyUQjhovFgrAiySldgfIP/V1qJVyzaN gBr2guJq5P+u1694Z9yOAOmroToeCYgPnfBFKXYR4BtqIqQbh/wvaOhLonME rHSdy78cQ4LxJG7GGM8IMCES/rOOIgHVIwtMWEAEXPh7wiR7/3xqeb5bQDi6 Xjl77VcYCXRaFvO84iIgrYApzyeUBO4DUkMuyRHwWWKScCyEBOnTnnR30yPg hFZu2HAQCeo2axRssiMAoxTSWBtIgu80e0638iPAXSMp/U0ACag51HJMn0WA zakWowV/EoiKxPUZVKDxXSGel0NaT+E9pU5tBOzlGIQ+8UP+q3303KVmdF37 vbU80pk3TB1U3kWA2pHbbKu+JGh0fnhf8UMElHlVNO+fv5gKnuyRG4qAO3f+ 4TqQpk0+vSc1GgEcIo9zF5EWz3WSEZ2OgM6nV47Iovvpvyy3FlyKgMFLndsP kfZq3Uo9sR4BDFhKK0nUnvufFN9x/IyA4+83zKeQbpoJ/XXkXwSYPfWarUf9 md5qE2ekjYSkP5YH6lB/D9Iduk3LFAmmeTcKRtF4SHJexVOwRYLhUF+rIBov Q9HU1l3uSJD1WlJPRuPpq/hlc/NkJKyqeLLwhZPg4RVeYbJIJPSf/0T1CcVj 9l5x4rR8JOjwKNcXovhRKLd7OChHQpylP+3juP3zq1Pmy2qRcNt8TLIOxV+/ 5LjID/1IuL9bdk5zn4/9Lxz2NY2Ek2rFDxpQ/sRommzv3oqEu5+bFvRQfjXM 4doonSJBv9nsUC/isZGqZ89i3COB71SD4v55i42oTsIhv0hg6vlL34jyV0SQ 0upodCS8SM6j5EO8lWrh/ffko0igTGh8JFKJ6gspwkxBQSRk8F2XXnmN6oW/ ZT2izyOhd8jhfSeaXxQPF+7L1kYCzfAiTc9bEjh/viGv+ikSSDHCG1ODiL8M Lrpa0kXB8yOjDj2ovrLgt7g2wxQFO5S6ap/+kSCAHKh8hy0KTHA/aRcRH5Un VTG4nYyCDltSp+JhVD92ixSH/hcF/V9v1d8SQvX8xcOTOa5RUNDdvdJxlQyH j0p0CvhEgW1J1bn/TBAfTWq+KAyKAv7aOt/S62SwDI0ILouPAkLToFOsHRl6 67e4mp5EwcpWicR6ABmeyI0ajo1EgVel1e/0J2Qo3lqMVRmPguXqhVRNxD/P q3cansxEQajhb+O554iXLrAKO65HwYjtxrdJVN92K2n/3j4UDaa9LPZ1HWT4 +NdU5vqRaDCwuppc1k2GwSY7u0aOaPguuXw+Bq3f4yrhHyOFosGf7v78tyEy TB9Ipp4Xi4ZN7VsLpl8Qf7Q+VNCWjYbnDGk3XyE/2FCvecKCiUZxDnxLPU2G HZqOz57q0WDyhHLo5yziuY5PTCPa0aAQLZ3Zuf/+hLjJi4oG0WD+OV3ME/EN rRbZN9s0GoBm7cUO8iuGQ3+fU9yOBs838YYm+/vxeg5N2dhGwz3tQLVE5Hds WE6Od47RMDh6tD4T+SGX7mkdMfdocBT4+TMI8Qwvs1x4km80+Bg8Vz+P/FXg o2r1WnA03O8tWu1A/iuMv7psFIU+r/z+ijjyawmDW/yvE6LBKyz6jQ3yc9mj TibcKdGgWsJZ4Yr8Xv6TX0JwRjQofhZI19s/j5Aa82YiG7VnK3D+3/73SSap m2r50SBS1yQeiXhCgz1PtKgkGnid7myMIK098uL2oZfRcOEVz9D++2OuZjYS 772OhgWmVd9NpI3Nezr7GqPB7oRrfD3S5txf/p5ti4YqHpa3hkjf/jZ3JqM7 Gu7In1usRc+zebjpsNsXDbLhd3v2v++6c4sy+9ZINFxeIKrvoPbf42UZaB5D 8cUw/fce9c/j+wk6oZloePl9NtcD8YhvrrhS7FI0ZFK995xH4xNkpeC+tBYN RC3LRnHEH+EClwt1d6KB7KpFBMQfMdPG38r/onip8HIIIp5MtnPT8D0UA99Z JpfNEW+kng4J+MoSAzZ1yw2lKJ6Z84kvlDlioPOQuNIAinfe3SIuaqEY0BS+ 2ItD/FskVqXnIIauW3G9Ef6O8ne5NbJbJgY0lmSFiN9Q/t4bX8Urx8De5Ffc 9Ccy1EutCGyqxUAVOXSk6yMZmsm/TE21Y+CPlwxnNOKLbvdjrSdMY6BkeDM+ uBXlr7dOeolbDKi9SVpOKiNDJT74SqZvDBioE3Ma0XxJfFZGERMSA6t7s5ff 5pHhwiSLkxU2BlK2woSupZOBoDMEnMUx8Pu6WWJbIIqn4O3F6O8xYOtje05F Fc13THKO51wMrPE9qSQooPw3azayWkX9W5IRHJFF9Q1OoEnpdwykMd1gwQiQ 4eevOcIP9ljwyGeXe4N443mfq5KVXiw8cUQk10aCiOXcdT2TWJAezAqdbSCB Oe1AodLNWBDhKGB0RvUirZLcEU7HWFCnmQ9+g9Y/y6Kfsx+iYyE5nZ6xAa2/ 8q2iDxqwsdBjHtfIjPyVaey6fgkxFp698aGODUb+eLSxLvpxLIhTWHmtuZGA LSQ8WakxFnjZdCTHzUmwlFmhLtYWC3TtOtRpxiRoeTX9i6MnFvwV0ufCriJ+ WNSw/fE5FoQ5Jz7vaaD1ktqXa/J7LHTJJRilqpLgOF/xhw9zsSB5+UOpnTKq t40PKZRsxsLjD8eMW8+RIMf1P1LG71iwjA18qn+GBN4Jzk+iKeMgq0BrjV8a +X1BtpknfRwcwu0lyEkgPmr+wGTFEgdiQ37vsaIk+Pn1X6seRxww14f/ERMm wYctGT8l3jjgZPPUZTlFgnwWa0mxU3FwjTtgVlmQBIHixCkOiTj4/kn7S+VJ EmhSP9RJPhMHlTIDHPH8qP9j+dW0CnGgc//MTA4fCSarSvlDIA6+eX7b2uYl QRmuOmFLIw5m+dW2U5AOcHiz6awTB0d7roa5IX1ZpfP2jGEcGAlz8RORZuPq 77xhHod8XdFwF+mJ9S9nPlnEQSF2JLIQ3f9599RDbfs4YLNlOJqJnu//ZJm2 1TkO8jj0tD6i9l0K2nRT8IyDkkxlOx3U/qMmf7+W+8eBazUb/jDq37gkrYZI WBz8Z+42xYn6/4z28ItHMXEQUPPQ+g4aH7/vHFwcSXHwbtGaek8cxaeGPxJH jAN1OuviL1IkYEkRXaXJigML9fbjv2VJMHb3jGlwbhw4CGdyWKP4lFz8r2Wz MA54aCtUmBVI4HNcXdy5NA7cCaTT/5QQD2/qpE2/ioNEzR11ORRvlvcm/67X xYFfvPO/5ygfnoY4fNJ6Fwfhbnfv2aN88TF1U255Hwepmxn+BSifLsr4F10Y jIO3r5IHhK4j3pxMCBSejAM7Vk+OCTsSMGuUCdL8joP7LVTnTiH++3ridVLQ gXgwa3yXphZLgqLtNzs/6OJh6vBZhgwcCVSK+3um2OJhJLKsYCgb8RrDlmez VDxQ2k9X+zSR4HP/f22B1vFA3VjHwU6L6rcSdakfd+Jh9o3f4l3k1+6RupmO rvHQfMmds5OTDIfOWTibB8XDnXO259PEyaCcGcF2Pj0eRrfv0dOj+uGQe2JI 2cN4kMhqZriM/HpYK3Xh1JN4EBbMj3CzIYPb74IGtvJ4qI0mbnt5o/Xudpft Rlc8wOM0m54M5A8pW3qbffFwoa+8NDMXrU9vTypsj8SjeYh9LvSUDNyiAUy7 s/FQM5Rxw7oW1U83Cnd+r+w/f3DhYAuq73ADk39/xMOxKtdV004yEH+IVR+g TICAP5zvvyB/PnPaNJeKPgF6TwmfpER+3GcWmUDDkgCBMzSLjah+c0l84UXH kQBKJvYKB+fJwNj07TY9bwKoD3kajaL1umSNTovhVAJcDL1Ucg75raag3Fkm iQQwqiUuHEb+OmdieeLw2QT4KOy3ZY/8ISoOS3dEMQGuKL3YlUd+IlBfs35U NQEKVszvBu2/v2h15hubZgKYWn/+d3a/vuc/0sF+NQFsE4c/XN/fD26oXM55 DbV3PghDQjor+m4W960EUC7KYF3Z3z9ekxbFY5sAq9/yvfb9b3ipxYXXKQHa 9ARIfOh+3idIZvweCXCixNjXCD2PTZ9bTcA/AU7WhvqsIH+viLgkKRSWAB+a u9uW9vdHVXlwnI5NANoPAy/1kH+R5nMOiOASAIM5RsdFJgOWu2dZNC0B4oX2 Dl1B9bGY7s6Q+MMEMPwjFTmH6uHOUMFmyScJ0Nm5UL06Tgb7iqsl0iUJwGE1 6mbzmQzUs4Gpsi8TILxBmeIKqofzOIpDztYkALGWXrG4C8U7iMLofEcCbHBZ 5QzV7NenEsoK7xPA4L8rLOUvUPynzIT/G0Tj08JZx1ZIBtPLL39jphKAqfDV WnoKGbb9x2ZVFlF/W31HW2OQ3z6n77u4lgD6jNdq05A/9R2xzr+0lwA2H87r G9qi+I0e1dXjTgS79C0+qbMofsxwXv9kIjD1M11OO43ip+p00lAkEU77Lvhv cJGhpfDtlol8IjwvupnTSIF49Av5u6lyIlDKTmeqofp3j4Gn21w9EfIVd56Q 50mg6O6Vc8swEc53H85f+Yjm25PcOAvzRJBmyXQyRX7mM9zrYWWZCJ9oeL4c ryVBxX+nLtu5JEKcUsuz/fcF6LsYyDp4J4LbJ+NauiwSkHKDj98NSgSDgYVn ++ePsJ+e0jhFJkJZyYNBKlRviNMOk50T0HUzUfdfqH6pFPshrJeSCA44i+Md qH5SuspiKZ2ZCPRN/DRXPUjQ5imZyfIoEfTeSqnkOiN/ydTuWy9IhHu9vY/a HUgw2OBw8NNz1B56hmfdNiS4ORmlUvkqEVZUHHF1liSYocnzS6tLBOsmS4bc 26heEHtT7tOSCAuCJxyib5FgU290wbQzEbbPT1/zQjrI8xe/wsdE4On1WfJG f0+dyW7OPZwIZur2XgR0P2zD2ZTfo4kgFXzJtR89j21Sv2t0GrW3s8xS4Q6q v2hcDjQtJYLp+Nzrj/dQPS+WqPBoPREECLVPM72Qf+gVu4f9TETcPkuXgeo7 Oc/2p1b/EsH+ST1rbzSqpzKmJi/SYgE3L6xzHo2fesM/LiEmLDSfGjs3/IAE vRM8hjRsWFixUufNLyaBMY1iwhw3Fkh3aUbuV6P1WNS09d1JLMz0SDmVtpNg 1SPlTII0FtKD8MHbcyieGWWOTvJYCAmPE6b7hfKhvidPRxkLlZjaC8sMZGCm oWU9fAULm+N3b71C+SaVEfCDaI+Fc6qXNcpQvlbXZ4h738OCPrFfazKLDJiJ SptrXliIVZCLvor4rIN64MH5QCz4EbHeT5rJoCdK/sQZgQX70OXzIWg+Desy Mu7GYeFBmsNp3wm0nniIqn9LxsIjy52U/fevzaVfCmpIxwLz2et5JDTfXett KrOzsaBQZGq3vz/x5/ewlZB8LOKvSq79/YJh1DlCls+wkC17vZV+//0uovU3 VSuwcPmvFdMP9Hm87udUgVos/OfOm82E1gNOj61eqmYs0KjfbSoZJkNu+lGa 2Q4s3H72m8DZQAaRemnljvdY8O0OrM+/j+rD7zreRYNYSEibCnzkgtYzasfS uG9YUBTJv2GhiNZHkdjZu1NY+HtXVVbjD+IT3fwTVxaxwISTjWl+RYI+9xYT iTUs9OX9kjNG+WOWPp7EtIMFgVOXOB8cQHxR97ud9BcLqgY3s3UyVuHOd869 j9RJIC3NSKF6chXWqOTlXzIkwWOzom2vRyvgJ2LkQjiaBLcV/+EZj64Aha5b oSdXEpjLxR8z8V8GlvQSdnnhJPDpV2/YE16CzLp3ehxSSeC5fX78ndsi8H+f ifkplwS0mCvRjC8XQFaEb6fuYhKYhXU90uGZh/JDbDOntJLATsvJdMV0DqRW D/bjryZBvbnHCV78LIhVbJTY30wCVzW+PMvdaRBQ6rh91CcJ2PE0bXoDE5DL W38lOCgJcFLt+hjmCeA9UH5hISIJbpylPS/8cByOd9w/2pScBHf1fzhmvP6G 1vt7HXefJsFmKe15tNgA4Yz1q8EXSUBUeE6S0BgClmOmuVCdBLmI25lPDgLT V5WAY2+TwFbo5emCf/1oPp5zCOtKgt+GBke5KPvh0CMx4+WPSZCXOH+X7kgf 0NqySbWMJgF3SdhficJeiLpEf1xiOglElWaP7R7qAUrRPbqMxSRIn6BUHIvu gn+r85PO20lwbvaUgEtdB4T0jX4Y+YPuX33jq6FHO/yp6K+/SIWDket3rrQo tcFP3/o0ThYcfI8bP1xM0wo+18sjItlxoCv3T9+SsgU2lQpcSTw4uGzW1y3E 3AwefFk3zQVxEEKltq6p3wTrB5K12kRx8Lu+jyD+qAHcZiLlpWVw8PF7jYwL XT2QOvwEs+Rx8KDAeSc7thaWEq3/uqqh57uIteh2V8MdF9Olr1o4gIfTV5QS qmBOX2dEQx8HfU+K6jdvVoLtWdW28ms4CBR7HWWq+gqmj8m/PH4LB3YiT8eN 5SvA+qdYTowNDspTNDArii9h4itf4vpdHLj36baL65XD6CN6u3c+OCjNOkGj plgK1yP2DM4E48CctyjDtewZfLb9gcmOxEHZ80cXHBVKYEh0jNMTj4PTdAsp +rgiMGYcoBlPx0HFtU2uKpNCGCB1bGhm48DsiAJ5WKoAPrwq7+UtQe3LpXhw 7OgT0EkvqI0vx8FX/A86DHcedPtlFW5W4+DLrSuLF2QewzvlqLDutzjg3N1r bKF+BJf4/e+d68bB64ZfWxwB2dBG6XI9tw8HLf2LZDqah9D8zlTOZwwHq8Vq lCXX7gMLtdtjpxkcSD6WnZA/kAmWKnHMVss4sPz9PST1TTr8q6lZuPILBwIl fqvDHqmgt9VnokqRDOfX7bID7IiQI7vYKk+XDIoHTWbuOhAAU8KVffJYMvhT myq6p+EBNyd7iIMnGbJGv+4VhibDuIC2L6NgMgwKv5UTXkmC4AcBBjsyyaBA a3n+BW0i9I4QmlbOJ0P2yTwanop44GF7Jj6FSYafLXGaDG5x0ID9RvNeJxkm JmrXj/PFAGPXD49Wo2SwERIcxDBHw00axonX15Oh2OTkmxmGKPgdrFSXdycZ zJuamuykI0C7zlg40zUZZnIfHK8xCoesbefUJJ9k2Bg/ohUQGQaKrtkuflHJ 0GvA2+NHEwIJz6q+3UtMBvZKeiOuvCD4Ov9e04aArsfwin3WD4QAyz0Bvdxk OBjkeaBywg+6H7Lj1YqSQTbpx8bPN77A/UXq74WyZHiQlchRUuoDtQYWI4IN 6Lrr+xa5l15wEOerzvU2GSQlzvhnt3uCWXfyS+buZCD+DdZKnvWAnxebE3+N JEN3lfCvbA130Az9/JM0ngy5kKl6P8oNMuvX7GZmkyHCnu9pxX1XuCB3UuXj j2S4f3jliB/JGeLcFErbdpPhdwmd4Wa5EzgPizCNUeDhz8VYZ/sIR2g4qhow QIeHpHP+ASev3oEZmfcyugx4+DTPzU2h5QCMV83n3zHjoYbX79Genj3cSHQ3 bjyGByIoUq4F2ULE07+HLnDhoZ2x9UrrExsoeRffUsGDhx0NjIHHoDXsUuVJ FQviQXkD+y7IwAoEBKRmBYTxUL135sbaQ0vQVql7kC2GB+mz/dfnJiwgK2jg IFEWDz7/neY/e/MWtGbdfsN0Dg8yU066dNI3YalmyTvuAh4uNUhPHz18AxS3 KKeDAQ+3mJMz9DfNwJo1+f7Pi3jQImb7mf40hQTZ4/qel/Cg05F+E0NnCl/u nW28o4uHRMa8xkI1E/jjKK5XrI+Hl+7c73eCjYH3juD3eSPUnj37hwLNRmBr zXrA4ToeYgw9CKXXDSHWgoFQeAsPsQ/Du5wqDKDkJpXgnCUe+Mtz/d6wGMDa tR/qdg54SMH8vcvefBVYjZeH8h3xwNNS2LKbqwfyBtP2M/fwcHnMYGIdqwtB Vz7F2XjhgfV0cK9q1BU4qPKq1yocD/+iPIZKZi6DuPKzW4+j8DBhlITHHL0M eopPSBOxeKC8EPO6+vIlSJUjslji8FCpzX+XuUsdXssmPn6UggfLXjuSEZs6 fJWKPPM9FQ8t2NFQLXs14Bf1NL79AA/TzY995U5cBLXTTrPZOXggW6UwPw1X BXtBG5+xx3jwq4n80LOsAs9PGGXeLMZD45qnimsuwIWjZ0evV+Gh6Ek47nvR f3DjsPi9rBo8mAy1yLI1K0IIo+Del3o8hOZFCMVPKEAbLSu/eSsekp25L6xf uADzVAwvM9vxcPBVg+EVt/Nw6ADVxc+deOiQELN7VSYP+r83bEw/4uHZqQ7a bDgHnj+XNtMHUPy0Co2zU+QgfWsqengID+tGdV+LF8/CKHmgyGQUDwEYc7bf JWfgzkzFstEiHlK/fK5vdJaBxMmSIOIKHvKle7pcBqShbDyP6RMZD/e63tXo DUrB5meCtOE2Hj4Yb+jErUsAx3BCc8ovPPw+I3tYnVECFD9FGPT/wYNiy3HL cilxCHvv4alPlQIYvndjofGi8KTbkRpPmwLQPhN5s0UEOt5Zp32kTwHx6COu o/+EgbHV8LUeSwr0aOd0DCafhozqM791TqSA1A1TyqQtQSiTEDwbxJ8CR3Lq pPQsBKEjj9XpmWAKTKSxWo68F4Bt3OZXerEU+Gg5dOpBzUnEo7NHFSRTIOqE okKM3Ek4HTikfUcmBYS7SqSzKvnhmkN1XYd8CswvaBZdD+cDl7HCjS2FFCie 32Hry+SFGKMMsVPKKZC2clwh+vUJqAa/rEi1FPhZfsjoNT0PsHMqBqjoo/t/ pD+yvssJUjixClejFOgY+EOkv8QJl6iPL+VcS4Gg77GST9M5wGftt/nfmymg QPaYabvMDjj7lRQJyxSo7DWuWCg6BoWjo103bFD7g92/TjEeg+HORoW6uynA gZMUqZthBRKmzH3ROQVOmX55q23KCrRVOU853VLgP22PeM4PR0H+cSiXr08K sPmlvZp4dwTS/FV/nY1MgbyGZ9Rn+g/Dc7KsrE1MCtz6Of1ob4MZ2uwE7hLi UfvfUrkYH2eGTQOqL2vJKdCS/exxVwgjGIu115Q+TAEVndOpwYn04JxbtTb6 KAV0RXUCRUcPQhR7oQjjkxSQaOj4Nit7ECopYzMdn6ZABl3BjbVlWmD7pukn XJ0CO8+Wt+XTqUHCQKH8Wm0KcM/qGlxmoAb1d6IL0Q0p8MJL8JhWFBV4vTpk NtOaAn2zbM2F4ZQwmNh7/vHHFLBKqAgoKaSAlQONrn0DKN7Dqo68FyiA2q+0 6N9QCvx1dqy6ev8fRs4Wx3F7NAUWJOSXFP/+xRCV9He4F1PAJuBLsyndb0yq haFr8koKVOz1WG9f3sWkRhjPU62lQFf4uosG7hcmvdNsZGUbjV8We4WS+E9M prHV6yZqAig3VJiOPt7C3Pe1kT57kAAXnGh5gGELk5VlV1TEQICCVDzfQf9N zIOJuxn4owTwnIxhULX6gclx9vC15ifAOIvA7XrLdcyjZC/ysCAB7owrS1Yu rmFyK3wcrggTYM/aZ5fDZw3z+GeAqZwUAYiMCvlOsmRMflTkeVolAtRyHvl9 gmYFU1AU/SIACGB/+oTXf5rLmMLuWGHyRQL8uBpHLMMvYYpYsByftQgwJrF+ YENmEVPyMHXnqSkB+JLjZOtL5jDP3qS78t4gQB9pMFWLbQ7zfCpznnCbAL0y miq0EbOYUpHskUA7Atx1dJHA3p3BlFcWvNb1JEDmzCmTJLspTPlIkXSrDwFk RM0stVYnMS93nxbJBxCA2zY+76rfJKZCpSyDL5wApNeGB79kTGCqeqt913Ho efrSsbWbY5hqcg3ZjkCA70fHLNrOIn203uFrGgFErUwnD/iNYmrM3pi+fUgA wtyfr0GHv2HqZt6dTyshwNvSO4YJPp8x9XTdL+jLCBD757CpwrcRTINYr3DI SwJ4l1WE0qmPYBrd+jgcagjwb+N0QsLJYUzzn887FzoIwCXSl3eCfhDTsHdJ 26MLxWtbbu4X8ROmhqLq4bNeAhjz6z2rOPkJ84I6RZX3EwEan5h+v6cxgMlh 1EqkmiAA4z/5crbnfZgs5tdjStMEuNxhPf31Sh8mneWUjM8cARjaUh7PfvuI SWI7MLSwQoABium71e4fMEE8tbwffhHgyN5g0c+PPRg/XmF3ur8EiJjVXfSR 7cF48ae9VaEggiVrsG9dejfGScj9zitaImRHyfHLOHdhrkuIVmSyEiGrW/6F vso7zDWpDOoBdiKMGLNedW3swBjK0JgycBOhtbptIFe5A6MtN/k7mJ8Ipu2a MqRL7RgFpfsaNpJEoBqy5hIPfIuRw9BlPpQhgtGv98Qh5rcYGRXvpaGzRGAt PqVIVdCKEVE3SNZUJMKtI4mrxZ9bMJw69F8kLxPBgMY6JeBGM4ZNz1fcQZsI y/FuXJkHmjEs+rPBubpE8Gb44xpv9AZDZ9wiwGpMhLU+utsyFE2Y7Rv+zj8t iXCBcbGhOKYes3FrvknWlggWqrGOout1GJKFyREnByIkYhYUGS3qMLM2stVj 94igYjVgUqBeixl0WvzXGkAEsqg99Z7ca0zfPVPDP8FEMBvauWdbU43pdW3P PxdOBBNJxzOpmGrMW8/HWsWxRFA9JHCL0agKUxFoTkxKJcIgYVEmJ+sV5kTV xuTpTCL05B4wzjj9ChNHSpRpfoD6mx9m7lxVgbGwanq/kUeET4yzPbe+vcQw XhY8aPaSCFd4JY7bXyrH+IY1XFuvJELm/X+bkR9eYKZqTQoSaoigs+1RP8r2 AlMrEXex8Q0RtGr0infKSjH2R1eDBD4QQSEu2PH5sWeY/isxPfX9qL/fT9WA fwlGKZqP22SICNp+pznSJp5iWH8avI4dJcK1KEY/obpiTPNY9frKEhE+Tg80 6qUXYiQ49FViSETYYvBvtz9WiMnQX8TxbRAhulqOlJRRgHF5e1zC8BcRvted 0a7Pz8ccfxpm/5ouFRpalBPjJ/IwMVNcVfoMqXBM4pgHs08eZuP4K6ol5lSI v6QRc5Q5D9OJm83lYU+F9ey4OTONxxgfL+1v4UKpcD63OdM75xFmsnRa9LhI Kgx9lRMRIuVgdOaD/CrFU0H60pecBdUcjOD1F8fmz6TCIjw/prv1ENOHKnQd 1VQww1+YHY3LwvznX5ozq54Kv7OXnuO272MKKy6thmimQqeevXGWw31M8Cn/ hJdXUyHj9WU9Z6NMjBjDeBv77VTYFXfVGLyajklT92Utt0oF5ZY33GLDaRiK EBZrLbtUeI+dVlK1SMOMrF38F+icCq1hZf9c/VMxF8VGdY+5pYI2cyKFw6FU TJmN98MyT9S+lftM49lEDFc28/Jl31So/nZkov0sEfN//78V/v//t/4PvEbz qA== "]]}, Annotation[#, "Charting`Private`Tag$2743#6"]& ], TagBox[ {RGBColor[0.363898, 0.618501, 0.782349], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUm3c8Vn8Ux0VGVEakIjRIVEaFlPstGoiytzKz98rI3vtBimRVMkrITo5Z ZEX2KESiPI+VMsrv+/vL6/O697n3nPP9fs/nfR4cMnFQM6emoqL6Sk9F9f/P 4P7n5ya8kuC7d3jJ44uXCfax6oU8jyTw7ZKLE6m4TDz92vHc2TUJvPaGRKSL XiGaFpY5ttsnAVdme/CtE1cJWqaLSwLG+POMPfwJCvJEMqt6HsUwCVZDvn84 PSRPCOy7Y1SplwQ7b2+4atkqEFf5ozsVNJJA2fBqls9jRSIUDebbXksC+S2X lrWTysTeqz+Mz15Ogt1P9xXeHFUmcpT+7ft3MQnyUoWZlmJvEO90j4bFSSeB ZUNP+XsqFYLO1dG05GQSTH9Phro4VSLZK+iAt1AS3DMJ5G9eUyUEApK75Y4l wY0k8nb7O2rE1dga1MeXBI6qBf4r19SJsFwG7j97kqDN0E9k5qQmse8V16c6 liR4V/Ss4uArTSK37FRkxK4kMB5WzLp/WotoadD4c4A+CY6xqPZkX9UmGMYy e2XWE8FHa+/elge6xMOvr6PofidCwkn/+6ln9QjBuXeyXcuJMBTXddN5QI+Q //2zyGg+EdRe7h7OPGZAhLOeiwkaTwRwnHx15u8tYt8+pctKY4kwwVbxx7z2 NpHLc3uDfTgRli85JMrLGhEtwiFWOZ8SQdu5o0uUxZjYcbX7Suu7RPin7TC/ 3m5CpCpNbZIaE2Hna1DzlTMlhNR/v9arSwS+jUfS+96aEopGBw//rEqEO4GG kTNVZkSkl9W/3S8Tobd06bbv6B1CrNfaLSEvEWQbH/gXeFkQgydtf3LkJMLY 1Q292wctiWMT9sPcGYmQ+pEU+N3Rimi65louREoEHYumknQNW8I2y+1kYUwi HGoSdNzHZUfs2XB/KhaZCMmc4v1qM3aESaFnglRQIjx3jqCtIzkQW+x+9lfd EoFnB4/odIoTkWPvP93qlAhcTZSW93udiRstAQbK9onwbb+0suYDZyLNO1hR wyIRlFRySr89cSEu94XUD5gmwqUtYv6YqCvx41SYlL5RIkR+brgfW+dKSE9G CJjoJgIpJVVXjexGTJyPejytmQhfFrKu/IpyJ8LvR7NbqSXCZIqfnMIpD2JA Po7a8TquF/dpuccBdwnXV0mf78kkgpPP63fWFt4E945kzW3SiRBR7km7XcSH aDR50B4sgetBR3X8yaYPwbY3tTpKJBGmOTm1qvJ9iSqHR2LMJxKBKGY/9DDK jzBqTctNEEyEoxkX/z0750+88slITjmUCIMrjpxMJwIIrf7MXQd5EiHNjsWp Oz+A+CeSHZx5IBGKmaLG7p4MJJS+PnV+vicRjkTfqf5JBBFzCvk3ymgTwZZ8 ZOZscghBelLQLEWN42l/N/JBMpSQ+vviQs2/BHj261+T6edQIqzolVDj7wQw KVaruX4+nDjFWJx1dSUBxpROf1heDCf6TUv2fVhIgG87dtarFkYQRznL6Lpn 8f25a4eXpaKIdsfyexrfEuCmzfG0NPpowuVDxcrAZAIESF8wbxmNJhruVU9+ HkmAqG1z1mGPYonbU1D7syMBftTM8j2WIhE7b2vqF3xIAI5V7i6NUhJROTT3 2+p9AvTku3TWnE4gWLo4xGbqEsB9PsBkL5FI1CgUdDx7mwBa+wSrr7YmElZN F63NqhOALfv2nmc6SURDlc2TidcJoDj9UdUt+D5hf2bbxcyiBCjpzF48dSiZ OPAqefTWywSY4BBhzGlIJlye1nOM5iTA9N+lH1bsD4mjcZzh/SkJMHhCpWLi dyrxccfLo/eTEyDteibNPnhE+ATL1qsn4ngKxUJsotOIPk+79Y/RCWDd4zso KZ1OBK5QP4iLSIAp65E93FwZxCmHh6dvhCaAwt1SSa9tmUSoWaNtm18CtB2j rpVYySTEv+jsiPRJAL+ikszLLlnEZ13yM3nPBKjyPdZ1bTWLkLy5/0uzcwLs nP1mU8bwhPh+zkG1zjwBxFqaC/lNnxFJpdvJviYJIDChYN9Jm0NcFEmNlLmd AG/OPndLe5lDpBxtbqzWSQDp3eeO6e/KJa5m6Bl5auL8dpyWy2vOJZb2L2xK qiWAgfdmzkBQHqHIzCVRdh3nx/FB+AlbAbEaUdTjIp8AEhz7Jgq+FhDZ2686 iF9JgNr5ETnbNy+IjTXH3FdEAvD1eapu8y8kXky9O5AvlgBnAqtEzosXEzq3 DSosT+H1rVkUYa8qJrYPL6ofE06Asw58sRqXSwjDLu6Yp0cT4NPQxKs8y9cE o2LJcdNDCXCpl4RYqUuJ8qZr7w7xJIAjQ8xcSGYpsbvaeSudMwFSfM8VKM+X EdVnGNIM2ROggdnsAVVaOXHn1WMpbtYEWPxFOPqrVBDwtMUphRHXv+4g/Zu2 SsIxjmcq8S8JRN2kKvRZa4hjpDdDJuskaN34cOPQQg3xOUGnS+w3CQL0rttd 7X9LKCcnVHctkED5Vsjlmiogtj8UKUqfJ0GULO9cu34dUZPS/sxujgR2cseN /3yuI4Qe05GYpkjw/IjOraylemIi/Uno8DgJbjjJJjgGNRAPMy/65I2RgPFI 1Abv/kaC/qmXxbUBEqxcELXpVW8ipvLJMkEfSCAcmpL5g+k98ehF1Gm19yRg 2c7IvKP1PaFWKHj8UBMJfNh2Z2RFtxD1xSbs8JYEXE9OXTwn+IG4+3prR2w1 vt/8zXIlVRshWpa2ZVBBAsKNdLxsvI1Ir+yfWy8iwaBG64lLlR2EVrXLeOtL EshvVOywKOokdtWw9D/MJ4HFo13tZ4u7CB9QrJd4SgLtR+N0u2c+Errvah84 PyDBSNTmK3f0iWBp0Y+5lESCLxcsevZ8/US0tP4JZCGRIIvulkJgdC8h0SFu XxhJAsMQJ9bKxT6C3Nllei+MBGsPKp79ftlPPPtoq6sUTIIS0gelNccBgr03 5/LcPRKMPzl05+bOIaKtT066yosEQm++7RKbHiICB8ZFwj1IUKrP5ERpHiYW hw9wCTjhevV2cROZo0TnROyisRkJLn9Z3lNvNE6EfBWeETUmwZ/JtguKi+PE hemW0S1DEri4rXUIh00QBd+pWx5rk0DSck79U+MkYTKX8dZWA+dfF1C90+Yr ceDnhdfnVUkQ9Ej5aci+KSKc4p4+pEiC8KqtVamwaQIt7knKvUaCsaHGzxvy 34jVpaIIj8skeCu8I4iZbYYwX51z5SDw+jd/e6L/5jsh+/fWdVUxElhq82jm u/wkWNTmqEZOkmDprZrR47h54kuOW7mZEAnC9LzcPSrIhI9K9KG7R0hAG7yd PjR5gVB8xjmwjY8EZ0+2Rq/KLBL717Ojo7hJ0HE+627Az0Wi/EnV73QOEjRR XzsmYbRMBP+5/FKQjQS1fW92swmsEOrKH01KduP6fJXhsVtZIRZWv3U005Ng K0vSRPLFKiGkyP7051o83F/1CDFOWif+pGfouq/Gw3v6u7MG+RvE+2UhZqrl eDBiGpZJbt8kzB5f8trzMx7Ou8o95pbaIsSX2kUef48HRemYNY1LVGjbNZ1p gel46Lz2XW9jngqlL9irSH+OB0/yp0/9t6iR7ZV12qbheFi6qVzddYQGnU8N eaM8EA8t5sijaJEGDcqlCRh/jIf6LuqeH3m0KOfhsdG59ngwL7oQLHGfDrnN l5BcW+NBZmX0q0IUPWJ70LoZ1hAP2t4HN5dTdqDxHxolrBAPlXdf/Sl+zYhe XRy3ePQmHvLFQ6nCh5mQ0txqT2FpPJis3xQUUNuNDqDAcKnieGB4/ydU7ykz mk3cRTS8jAdLB365i0EsKFTmaF5fTjw0HJuUX/3HijQSXt26/SQewn4Ol3t9 YENHZqTZZzPi4RAT4f0mYw+qi1f123wYDxLeTzd8rDhQ7PTomdD7OP6TpByO 23uRobTlHHNCPEQxWpk/MuJE6199NY9ExQNt24TwWsR+1CLFyPQyLB5OWrLu PvX6AHoQc79OIhjHs9LwjfEHFzoj+UJY8V48pPZn9M1G8CDqaMmJT57x8J17 m2LmEi/qHm9INnTH9flKc7e0nA/ZRw5tc3KIh9qOfU7JNw6jC1/MKtZt4sHf MWK3gNARxHRmwTbYMh76powLvrIcRbljdIMPjOOBResXuw21APIQT4g5dCse XLcar8buPoauhh2UK9DD9VLKCU8UFERfRc8U1qrHQ4+8xQnHCCFUnqMeEaQS D9wersnhb4RRJLeLmbxyPFCfKbj+bPMEEmUoOdBzNR5ybA9WCr8SQdt9u38l y8UDf7r+6nGSKBpYXviofzEeHLbf8dpSF0O+X0TCps/FQ+CT2ba7v8WRmuZN k3yJeBjfbsVxdug04m+zl3E4HQ+aTsm1Zu/OoPbyl8t/TsTDfodtG6+aJVDm iY7Ot8fjoX8kz+7kkCRyyf6ZFygQDwmCtDe/rkuhA7HCRjv54mGdN6lDyvY8 ItNcP9/NHQ/MdtxfHr69gOo9rfcm78f7/bUCdSkfgSzN89p598SDmO3dzzzx F9GFkZbnU8x4vx66+dTl9iXErPo9MG9nPLwOVGOaPCeLyi8cO3eaLh6s6k48 e8V2GUWWXGX/Qx0Pp2NF2HzYrqBqlfbPnltx4NdwkJfgu4roBRWvxyzFwSbz 8wE6K3lUuCdiG+fPOOgsdDj59ZkC0th6X5E5HQeZ33dFmKwoouz+K0dLB+Ng WGJZIf+DMlJoCB6W6YkDpydL890aN9HCy8b4921x4OHNM1/opYKIkEt/h2vj QHv65v5cpIamHf1fm1XGAR3XnQPfzqqjaAOwIhfHgZy2YbWdtAYaOi3Tv+1Z HKDLg+92O2shf16f6Kj0ODCotsg+8VwbCTC9keV4GAe0swHxGWQd1LG69ied FAe5kzX1KQp6yHVS6pVgVBw84z6iYlqlj7g6PcxLguMgVqnklz4yRA1V5VwX fONgF0vJ3OboLcRCOhN+0ykOOtbjj/eKG6MKHxdiyDoO0i7dHOQSMkG3LEtW TMziIO6HMAeImiJajcX8n4Zx8IkvW7ztmhl6gUSN3bXjYJ7qabuxozlSF3bg pFKNg7P3zR2qC+6g9b2FHRGKcXDxR6zN0Q0LJE8Wln4sEwfpyTJpP0esEWXI ekFAMg4ktNx2uDjaouTmvJwiUVwv97NiRrz2SKb4u4G0UBwYq+n2PppzQFNp x/Y0HYkDyd+RUgfmHFFU+J1W5YNxQP/n1E0xihMSd33mN7A3Duyr1Qzf0bog v+tHfs7tiANqR9uhMls3pDFGHJ6jjoNi7/4t2zF3JOSgpzO7EQsuEz5Tb63u oi0q99jvK7FgEm47sbTHC/UmkJpm5mMhTbHwW9Rnb5R/9OX6t2+xcJJKqEeu /R7yK28R/fYlFkoP8uvuHfdDQsNbaVPdsaBB6hR4LReItmy4Pn39EAuqnT6b p0hBqPevxI6vjbFg56Y6Kr0WjPLj1NBkTSyMNLdliPiGIr9D9m4TZbFQMWdh lXk4HGm8jigYL4wFbtXlJqPZCCR05dnEl+exoDMSbBfVF4V6LUeVP6fEwnP/ Vq3de+NR/vrvoLGEWLDyaXMSv0lCftF7qkejYiGdUBP4nZ2ANHhEFkaCY4Fl hMd7bE8SEipSFBi5h/M9VvX7+dP7aOvSHYNh91igelNeaqzzAPV+CkgYcoiF kmE/kTviKcjvd+W/AeNYaL8kIxts+RhpRPSeGdCLhaTHtzzOdWQgIa4F6351 HM/OvfaNZ7LQ1gumrD6lWHB1Kc3xyMpGvcSxgd4ruJ5fyx43iTxF+R9ld/US seBoeItM9/UZ8jO5JfdJMhYEBPP6VmqfI40VT88e0VgouHmC6fn7PCQUev9V 9/FYIJ2LuJC97QWi2lc8/fFwLEjmSjBNOBWivrx2ro9csZBdsnqeEluE8s9/ V+1ij4XiFhf5j7QlyL+DJrxzVyx8YOCJn8h8jTRv89Z20MWCkpUNVb1pGRJa lF5p34qBbezSysZqFYgqSEuo/U8M9HAFLu9yqkJ97M5GbYsx8L7vFKN90xuU nxOT/GEuBqbkL5qEqNYif6m89tavMaAbmp46FFuHND80UbeOxsCRbQ9atDgb kJDBuFRLXwyIHyVJXmhuRFTkDfv3nTHg/MA+o+BRM+rz43z27n0MlH+/VD3y +D3yf3KDtbkqBsI8PLdMxNuR5lnra00lMTDc2BRE+dCJhN6H3GssiIGHK3xu 5R0fEZVu1uuGpzEAxKV4dvUe1DdXM1v/OAaWFByLrFY/oXyfQd765BgwprF7 dqSyD/nvXtGsi4uBfRG2CccfDiAhceGG2oAYUCCrvTV+NYKomq7+eesVA27d vlbVk2OoT9Pk1FuXGLi1+bAS7R1H/p4pqW/MY6CxE914dXcS9dXRu1QqxIB2 52f3C4ozqM5IXH9QNgbchW99lbX4jl5QGcr9OR8D9JHaPvbus+hBZpjwvrMx wJvwbqHLdQ4FXizZI3UqBqLWO1UWbv9A9uOjG9rHYsAXNbz5fvYn0vWnn/Lg iwFmGWFVx18/0WU+8fYH+2Mg4ypry5fH80i0zqC0gi0GNK7ekREWISNuo7C0 AaYYYKCvaP6UR0b0VCXBv7fHgGm37nLPbgpayhi15fwXDT8nnd8F3qagz4he U/J3NGRUO+oFP6agD1/EZLQXosEs1Eb7+QcKKvMz4PeYjYYQqTdZn75TUCZv 2K4Hk9Hw/OCS9OoaBUVD8a/ykWgoG7zburhFQXdvj47190ZDsNl8T8ImBZlu 0b1b7YgGiq/InbBFCrqRIVa493000Ex1ftQdpyBpZJAsURcNf57R9drh9/F/ CfXVqoqGj96eA1tFFMTiV3zHvSQaPtM9S+G/T0EztXSS5U+jIZ+OR7hDl4J6 bonx9j+OBoE7f7e1n6eg2n/69KvJ0XCf/ZHfLR4KyksPpXDERwOrhg7H320U lEQUD5yNwPFpeYbumCEj/88joBkYDfQhlILuDjKy8aXLdfOOhtXrp7dI5WSk xSMWf981GiQH2Oc8sshItlb/bpldNNxKsh18EktGp26FGvXdiYaaIxa7hH3J aP+/Ivlft6PBy7zo4n5HMtqePiLKoRsNd3ju0zmbkdGCDN3+s2rRsEb1h0Fc n4xGxkS3aV6Phh2T4ntVNMjo3T39WdfL0SBY82pH7U0yKjkY2p0kEw0vFkaS rJTJ6PHboqpSCfx8vuIfF7AONxzJ6hWJhsP+J3R58f2uf2kjVwSj4YpWce0v NTK6/VjUmf1wNFiFeFM/0SEjRRl9vTNc0ZAjO+PAYERGEmMhshrs0aCXLs9I Z0VGh+4VCbnuigaVqdcDXi5ktPPgCFsSXTQQQ/6HrviR0Z8a2o3XW1EgqjJc KBtNRlMGol8//YkC14s26yqpZNS1qde2vBgFiVYkE2W8/3IuFD06PRUF1BW1 fqGtZKRRo3fhdUsUbDEnLcgzU9BFg5Cjn+qjYLaf8OE8REHCm692LldHwTCD g0CnOAVRX6AdE38ZBb3V630BmhQ0PyLSrJYTBS/hMZ/CHQoa9NZ76ZwRBdsn ba7EuFPQqzev7pWQomA1xIheDO+Xp4+pi+WjouCPa+AZz2wKSvXTnPocHAUL /3ouM7yioDjjXE433yg4RD3X9rGagoLlNhSZ7kZBzbE/Ne+aKciT/4ZvllMU aJsF233poiB7+qxiSZsoWDN/+pB1iILMZpenOsyioJDh+S3NCQrSbbu6z+xW FBSgW3JP8Xm58TLl+rp2FKDUQ8JrZAq6HPfTN141CooOFqirrFDQOSdUInAd x9vKePP5Hwo6pZ4wXXM5CpKEbvzZ3KCgI2en96kTON4Cd2vVfxS0j1NKaVYy CsTu+C8/w+dt91qkn58Yru+sCf1frGlGxko4hPF1u3lRPaz/1Ih+KzgaBTpm NdQNfymInB60X5YnCuIst9NJ4+d/9e9XGuSMAon5/ryW37ieJsf97VmjgCOl VdRtmYI6Lvu83s4UBSXXIzKu4fgbBLq+pW6Pgqfhj/PkcX6VDIcPiP2LhE2K d0YAzv/lnKvy+9+R8Nx+Rn8T1ye7/b2/4WIkzNTdF2vspqCHhQdKl+ciYfRf 79B4CwUFOtcd4PscCRz1A9zKZRTkobHnRvlAJCDqK3El+RRkK3EnQKk7Eshc 20zTMihIe53p+92mSBD8eVT8RDgFKY3e4mKujQQajorSWW8KPp/FN55VREI3 bU+MngMFnQjULuvOj4RZ0QmTYLx/tjE+CRQiRULpTaZeUT4KWv3xq6wuMhKo ixrI9WwU9LNDflYrOBLuoaxmA1oK6ieRbwZ5RILSCyWib46MCvZLHxw1jIS7 0WIDjRVklLkRreKsHQkCqkKlDwrIKHnsSxCDaiT8sO7NK8/A/SUrZO7M5UgI y7DhpYSTkVvQ4ME2mUhg/HJGjh33C2tzYVVjyUiwy11ueYTPm+bx7ooYoUhg zRynmr6NzyvT0R9HjkYCXQLlyistMro4785TfTAS7H/k753H5/9sV6uqCmck pIR8/pR1hYyEirlDvrHg+EomQz7KkBFvokOlD2MkPGWUHPOWICN2t4YfbNvx +9UOSuRgv2DU5uDN+xsB/y44pKgeJ6MtKUs19DsCJLpO1fkdIaPD9Q9ory9E wAdhxezmg2R0VeF9pdZsBASaHdHN3Yfj7161MZmMAHVJ+VlBdjKK1RXgtR+J AOFnSb+useD+NaHZ49kbAVQOpxtod5FRn1VISEhHBPw47i9lwoj7yWKpFOld BPANFM0aMGD/8pr6kQYRcPqaCdsvOpwvNXtGbmUEOLnVPz6OtVmknFppcQRw t/gIrtHi/sfmQluXHwFVQTU0Jvh6QWp2ZduTCHjHbS5lQk9GnYd7bAbSIoCH KSriN37+Uv423q/3I4Cfi9+Dl4mM9p4W6yHH4vzqFS4N4Pik3xiFrIdFwKMp hzkuVjI+xfFSdAERoMO5Q3oO5xfYBj9YvSKgNMsSiP24v6lT0g+6RMD2sOZP HDxk1DrCo3bcNgKyjjem2eD6/TS9QXvWPAKYnoYzX8D1Zfl5r/LirQjQ72Bf CsT119kc5dFRiQB7GcMrJni9fIJ39pgqRMCrLFaHxct4f+28EOIgGwFvnZHf lBIZzXA/+hF6JgJOlVdKTBqSkbuMbmXZvghg83XKyw0io9TmcJt61gi4auFf 2hRDRrXKlTwdjBGwp+Zy/v6HZER7izNkajMc6pSGVbVfklGSb5/qnolwcJJ7 ed13iIwq6WhpeYfDoTlN9mvtFBmNxp6pFPoUDu6+Fi92LJDRkYxEHtnmcKgy eOCXQ0dBJaD6wzEvHEjyf/wMTuPzci0g3Sc7HCxy0saVCQpa7ypSDX8UDvk0 vNrcChR0aZy5MiMmHPY2Hs45fwv3T0tkUxAaDvZDVrcDLSkofMGep8IvHESU sn6RnCnoI1VncKdTOBjLCbCvhVDQSvhfyWHrcDiB6l9fi6MgTtaTP6ZNw0Hz b5uJ8kMKunUoWvWvZjgE9z/hts/D/SXvzfYdN8NBhe5ATUAxBeWI/ahglw+H x2EpD2SqsJ9cUuQ5IR0O6y9tfLLeU9CBndnchafD4e3JDpr+DgqS7187IHoy HCRKTqPSTxTknqm6v0QgHC4OPLghjfvbU+s8zjN84VDc4ed35zPmkTPb9pbv D4cBhzFlya8UtPVPh11qTzh0p380LZjB/ai1iK16J67nPpPU+h8UpJfIwHqB Lhw6Uw+t3aXg/A2NmGu3wkDDtqn84xLmr2OVuy6uhQFN9k2pll8UNLnIvLNh KQxii7RZb2O/YKmxYLz8MwyM/urT3F+nICIUGN5Nh8FC+92/Vpi/bFQ46eW/ hEHG4S9cn3H/f3jAgfbDYBhMj1FyFrGfvJt6R6PUEwZfQ9vY/veTlUIe6s62 MLCKPfDvD9aHPN2pVJrDQITjtBgZ6xtynf+6a8OAeZz7cQjWPrsE/qpXhgFj XYReHX5e/sC9jb5i/L50y9wM/L6BrL417YIw+Kz/bu4ojme77ck/Q0/DoJLv Rp4qjldcImRVPz0M9rEfiD2G8zGiGlsZexAGWqGfTXNxvjEfzizfJoWB+YoI Rz+uR3VS9OJEZBj074C8Elyv77emKKbBYWDMQ3P14k8K2nv8Ann6XhgwnOsW DMD+dHk58aeFRxgMlDLme0xRUEaY3KyNdRgYSKzqxo1QULvqo5l50zBQ/ngp p6wf71eu5WkHwzCQfTjd8gj7lVZR9qSLShicZTgWV/KOgnYObRv1lggDtYSS Td1CzK9PdIf/ioTBok6ibudzCrKwKx70Ox4Gii9jXu/Pwn65zbgviBvny/vT 51Ii5mOhus4oarxe2ns8hDCv5KxwduzaDAWFRy8KCuwp6FOtQ1vcr1AYSSNY uC3+5wHelsTvoUAXHiHTr01BU96+9Y86Q6HlydCRbecoSLXjQmlBaigUvUj5 krSJz/OzJ2Y3kkJBd6hkwOsXGQ3eY+RYjAmF9f2Vgp5kMjI6NegmERAKZ0Os v74bJyP7OBfJeotQOO0fTRp5h/u1xfCMqXEoMI3XJFXVkdEvdOkhnX4onBm+ alJbjfvTwu616zdCgbtjXEv2FRlFqeZX958Jhf5Y1iZdzH+dx1ltPE/h51EW XiXdJyM26rtc3IKhIHvNLJOKhPtTyRUfY65QaBwst3bAfvg58sWJ7RyhcCB7 jsE1GPOn6Z6xnN2h4D4ZcealPxnl7pmQ+bktFF6a8jDUeeJ++uMaOXYjBATf Vy6mupORSFNhutivECBOxv58gf3TOY3jZi85BDyoa51WMX+Xu/psuX8PAWUD 6h8e9mS0rvT11f7JEBgOfVQiZktGBL+iUc1ICLRbp+45ao37+98iltt9IeAm yqd405KMmvs467d1hQBV3s2g13fIiKHQ1+lpSwhonWkaUzEnI6XQ6UPXGkKA Rv+R1THM9/G3lHpm34TA+V1lgpKmZNQr8TowuiwEhFJadvubkNE+5gOnRV6F gMlw9zZqrPVn/L9254bA6439wzXGZJQOM4mu2SEwqeFiUoT15IMblznTQsDm 412dUawFHMtWqu7jz7vk2V7En7eS535mEBcCws/fyY5i/YIvSHMrPAS0Ncac XuH3L/yZpc0ODIFC+cLgKhzfmW6V8ss+IWBWm722huO/m1dxZ8YtBIbO6ck5 WpBRTQAPZ6QDjj8vqIULzwNbuiHvT1iFgOM/lakNXB9Z8Z8eXSYhEDxS9I3Z joxCGdUFnQ1CgO2yEbu2Axl9mKwaZNcKgYt12s8/OpHR7jd8ERU3Q2CjvKrT 25WM1BLDzukphEBNtfkrbQ8yum9Dnt2UDYGbX9dMTb2w/3PXKMpKhMAo84MA ugC8X1cOb0yJhEBp9Ar5Ed4fT9ojCsKOh8B0hMY5Q7x/hO5p7+zgDoG2R00M t+PJ6NznpQ5tmhD4NuwqirJxPQwk/jlsBsPl2eY9vs/JiGfE81T4r2AY89yQ mn5BRtSDVHGVM8FwxDLWhb8Sx9+9W2V/ezBs6pbOn/9IRnrNQj3DScGw0ryu zYV5sF3Onno5Jhi6r38o2LYT99uGYnGmsGAw7LnVtoj58TBIJZ73DIZdmqrn ZzBf/qi8qpFmGAzTE6mG8xdwv3xh0m8oEAxZAgzd6S6Yx4Vy6Nx5g0Hh7srr k164/+XNSsTuC4ZfXlS6Of64f+U4PqhlDAbR60JxyjG4/2T66vBSgqAn/+Ah 2WcU5MvTEC75PQj2S/HozGNeXkijrbo5EQSGH3cmuOL5uTcler//pyCIMXX/ y/KGgh4npg6PVwTBK+qzzHqd2D/YPjOuFQXBLtUiy7c92C/jD51nzQ+C0LUj VEu4H96JyX10KS0IDvCbpX7A/jbI9LNN934QCNxzemw7SUGKkSKbTrFBoLAj 6MvINO5XYeUG2f5BcGVrtJcH9+NM2vXoas8gYFKV2LmI5we2YJm3Pc5BQLOP OSpmEc9b1AHzczZBMPRMuXYZzxur/k0HacyDIDdy99EjqxRkuUV/g+tWEEzN 0ClxYX8Yvnfd97R2EMx1Sw6MrGH+34wtvK4SBCtxunfN8DxT69Xz2VQBx5cb tVyK/Ub6PKG3JBsE9dH9h2qwH5Vv5PX5XwgC7yNDpxOwX4nXcKgySwRBmPuu w5LYzwp9AtofiwRhv2FZysdaSGb+2onjOF6u2PJ5rHP+6jRWHw6Cc2ZLsVtY H65tIhS4g0B2f9rzcazTfUWrBziCwPSv6TkS1gdQ2tk7zEHwifdVBCvWyVv0 xSsMQXDQ/eScMX4/W53LiSBqHB/to8pAHF+s/5fnrJuBoE1VdMsVx8946fqR zF+BcJRUoyqJ8wvdVpF+ihIIz2p92dpx/tQNhw+8/R4INPLrJ07j+twLjL1/ fTIQZpYZpexw/f7IrrMMjwTCaLtsnxeeN11p7kRb9gVC/mxkkQH204XGbvrf nYFQvNnrt2cBz1vBMkEhLYGglUJNkzmP/fVy3r89DYGgFyBOQ4N5xYyWwyv7 TSC0rjWpyWB/NQj96QiFgfBn1xnN83g/DF7V+amci++ndhug+kJBGvRNFqNZ gWAuxXEtC/utUvijW2tJgWDD6DTh3ktBFyIVlU57B4LOA2PuhCY8TyqWv693 DYTJyNj563UUdIbpsJyKfSA0lRadmcX790T02jk7Y1wff5mOnhIK4o7NPfb8 Gv58p+j9IDwfbpDoaLjYA+EwPZ+7gxvmhZSGKuqXAXD34f3BE9w4fiqmMrqc APj0/n4k2ktBzBbqRYwZAVDhOETcYsHXz0zlsJECYFfBoz3N2yloVxdt0mG3 AFj6zVZjgP2z8uyNOAH7ALiQFr+2/J2MTNKSI4UsAiCiSV8l6yv2G6tjAeK6 AXBWxqhVFvO00XYFe1mZAKBwuj2vbcbzlg3J6qpEAOxvV35ytJ6MyrqHzBRF AmDES3M6twZfz7DWVzsUAKj+32vmUjIqpX2tpXUgAPrPm88sY7+9bbuhqrcn ALZiZAvX8LxZei5a3oQ2AE6O5EzZPsXzSmav3J1//sCjHlo2kklGO+gPIuvf /nA+PnLU/jG+3vvyrPOsPxzkiY7b/gD72flVUfdJf+h1WJdgSML+n0Wc8Brx hxFaFxtx7Nf0Dl2HAzv8QUdxl9pmFL7ex8kT+s4f2vvHh9IiyMjggtH+SPAH 9Ta6VPMwMqJ7ksseW+kPtpQnM1ohZFS0Y5E5odgf3v/WYHbC84me4zmm5Hx/ 2LV/r2Yp7u+0AwF0qU/8IW/cYIUP+32RzIdt6Wn+cHZMkq8Cz8d6T9n+Zt33 hxCaEzQe98hoO5P+n2ex/vDhsiEY+ZDRK6cny3lh/vD0+nN7V298/+AP8kt/ f1g98OBwCfaT7ejMXLGnP2wouk/tx7rwmc90mbM/KBc6lRVgntDZ2TxeZeMP pnX+sRZYU7vsGn1r5g+FTS+NlLF+OaQ5UG/oDxT+n+yG/99/Mb2nWcsfun/e jE7+//7n3zpab/pDKd/ezDWsX+wSae2Q9wdmrteHQvH7tFw9mrov+QNt5Jfh 8zg+qhGAPml/EHxTH3MAx19wieHN0Gl/8Kr8vHII56eVq1I+dgLXR1W5URXn T8WcUjzB7w9i5W+e5vmRUb7bxItpHn/wbwqTOY7rpzl6PHeW0x/ezg8JfQzE 98s5P5ln8YcfbK+p07Ff5udVpy/u8IeB4r/qCaFkpMFCk/qL2h9MukpyXmD/ /DefLLT82w/Wj697/4wko+fhlZw0o36Q3vMpfjiOjASdLZyVOv3gsp7FoFcC 5jH9vR336/zgw2A3rwzmu/xTroGCz/yg7rKCEv8jMhLed2TM6YEfkG6sLyqk 43ps65F8E+EHJofW9sVm4fr3iswr2/vBv9QXp5xzMb/Vfr72wAhro+ViFuzH Rc9jssfV/OCjf/uXNrzfS7x+aLtI+sER/o/C9yvw+eJ73vCQyg+O284wGraQ kSSj1sHJJV8IUOWO+dCOz+fy9rvC074w8cXv0I1uMqp+Z3KyttUXMqmTJxOH yeitLc/Drwm+kDJcn7U1T0ZNlfftTvH7QssQu7EPJwVdyb7c4sHpC78ZahIG cL94F7V8uH6HLzwsSP8ldZiCWm6pDqqT70HxpUZGxpMU1LZ9l5xnxT3oqxMy fS+L5z+V4H1NCvdgNOtV9ls7ClKXPu2y68I9WDjTfXQDz7O9RyY7tE7dA45P qnDyLp6XV1HQLNs9ILkVHrQPpKChtI353aM+IBXPeBYl4/kwNF9ep9MHOpJD D+14hP3PQfdJVp0PfOKgFq/D/W5UtkLnzDMf0E8folvKpaDx786NuvY+oLWZ Yne9Gvd7LefSOGMfGNs9pctbS0E7mpyeNWv4gMZb1ZHReux/GY5hYud94ByP JSdbKwW93+l41+KUDyiK06aGt+P+7uVg9fiQDxgwzlz61kVBIZr213cw+ABb o0+TBuaDA412F9CGN6zpjkeb4Xm4UNTupBvZG4hQXi3d0f95wZZ5otcb7Ozg H2UC+4unDRVnize8HWf6FY/nsW0z1otKb7yBLlfjAAeej4UarD5VZnnDmU/f 9Zux39SKWDWRk7zBkUXvzQL2I/XHlmVHw73hlJrMx7//z3+Mljl63t5QpntP 8SfmCZ+7Fg/i7b3B/xrN+BvMEyzf7oS/M/YGtjshSrZ4nnymfsdzU8MbwpMb Vf9if5SuN7cWl/eGnYahFfbYPztPmetbnvcGv5j71+uwv5qkmSmln/KGXNW2 iUU8r/7eYSbTe8gbnubzatBgf472MD3FyOENgh+yA1ew5ps24b3I4A2FTNHq zdjPy9RMWNw3vICaRui1G/Z7xTrjbS/IXrC4az2RFvPA55PGSxMTXsAUFEJ2 xdrlkdFXzj4vyBHxqW/EmmGHUa9yixd8E3zGuoR1mvvt5qA3XlA7+WH2f/4Q m7pVXlXoBc+Pf9H7n0/eqd56TsnyAkXFPO9qrPXA8CH/fS/Y0/LX0gJrygnD CP1wL3jFkn5lBccTnGrgRfL2AumFPdL/88g+BgOb9/Ze0GsJroU4/hdu+gZ/ jb1Aafb18VGc36WvesqnNb2giPV1whzmkX4VPcJK3gvqOXkpQ7g+1rW6Ihnn vWCDGoLycf3+Cevy9Z3yAgXWqVQDXN/EFB1WpsM4n3vHghdw/WtctZfdGbxA xzCBH/B6qUxqTb3Y8IRKicrkdbye0ze1+ibJnuBl/vH6fswnu4U1K270eYJA 3fvj1JgvnzzUyA1u8YQ36VLiHbMUJEWnkVL9xhOSGh7L3MP7yXhCzVsg2xNm SoWVYzGfrN5QszW47wlXaN+qL2A+iaxRNUwI94TM1k/G58YoqPSBCvpn7wnT LUFNgQMURHfjBk3/efw87dZq6jbMU/T0K6snPeHsPG2H6XsKmq2HKU4+T9gd usT9shHPB2fF3ulu94RZ/orGDcwrCQfZI8ba7wLXmCVtVgEF8cwP7Z42vAuv DFIe9oTh/fk8YYtW5S4ccTuozReEz4Px9QUB2bswN9qdY+aL5/3emm5Lgbuw X7uxpteVgvJrMpJ+kj2gMf8fi50xBUlEmx9Y8fMAoymq9BvSFCR4lYeJw9kD vqmfOel2loL2Uw1snDXzgK9a/7YyRSlo00V+zEPeA54Ken5lOkZBDfrCmRss HlCYvv/MVXacP8dUPDeNB9jsFA4sZMbnpSstQOaXO/BybBUfZqKgcLndpn5D 7uAm3NAmRk1BN4QX+Wmy3eGtkH/Z1gIZXZzO23s0yR2Y7lxZHflJRmIZJvRX Qt3B4ST7dCvmJfY9vd9Drd1hF0uh9dg4GQ2vlxcwnsbXDXMCV3C/bi91SBPm dweRX41vHDpxv7YXjFHidIffYuPO29rIKHMyxT52ww0YOuucrJvIyOKDjxhb kxuYMEVpGeH5zZYhtJK3wg34rPbGtZWRkfPVOHQy3w2yLXofKL8mI5+GLGX5 eDcoijLSeVBIRgFUBb2aQW5wMT0z5zb2n1CiVN/U3Q3ua04vonw8z1e/s/I1 cIPUWIcQhRw8r/7pWoi66QazWk3XXDBvpUoMeaTIusHTUbRRhufNTNfJfzln 3eCrKXMvK/a7ZyU/QkoF3WDyXTF1WAb2y4WVnQ1cbmBuLljKgf2x6NS/xK7d bvAr/wdrbRrmQVt6rrFtbrDJ8v6SP/bT6nyW7LkVV1D33nHHIJWM4Pv+439m XOFak/tjtRTsXwJHimhHXIFnjyiN6UM8v5qdkNzT6Qp7+XsKYzDfdWWfreWr d4UdTj6lPclk1DtOXDlV6goppgVHxbEe5pFvP//cFXT0jHa+wH7+xUBVXSHV Ff6yHHS7iPVUqt6wVowrHDfvMqNgPpwdNDU283eFPtm5sUqsyXvtvju5uELM TfcvaVivaLg7+N1xhWd8k2aPsF5L8FuN1nWFK/rid0qx/vcx/F6qkiv80aYb nMF6O3PC9lzkChneDgVn8ft2KD+KKhN3hZkggc7HWO+OesrWyI/jJ/sJ8eF4 97S+TPm4zxVOWek9r8F6H30F32cmV5BtlxV0wfnyXKl7/uOfC+TS346Rw/U4 EtR6am3RBZgTY16fxPUSrO8po5t2Acb9Kq5iuJ6ntkYusA+6gNLe8Wc3cL2l vMmKIrUukN+1+aQX87JM1e/uC8UuoCFVvFMGr5/sbypdxacuoCl8n6cW87Wy yx4L80gXcEs8qr4D7we1Ym6y8z0XoJj4/el5hnmRwu/m7+gCpaPhSqXP8bxg IxX0SMsFCjSFpmowv1vkXWLMU3CB06uTpK8v8f6dUSSVX3CBmognDXxFZORh apjRfRjHxztuNIbngWj9wDf0FGc4F88/qAlkREqJkuWYdAaLh6vrAg1klDyQ 1Hq4zxm2L52tZcLzRqb68wGZN85gdzLEfzc+P2XX25ddwpzh8QPtLz8HcP36 Y71sPZ0hXmbt0MMRMvIyUt1mbuMMSjVR57S+kBHh1r9b66YzhDSHWTPMkNG7 9PHjUpzOcH1wpF78NxkNLq7c3sxxgkRukTHaA9hPfSq+rTx0AqGnb1hiebBf 0XnZzUc6gZLi2vLBIxRkxLXl9dneCUw9XctVT+D+eXlHcp2EE0iFJ+st///7 ggcH24PfOcKqTYaTnRnmj8PjavcqHeGo2gMpNivMAy+yh9zyHSG7R/FfMear wPpjM3diHSFagl7jizsFMf0Qo1bQcoS+vIm14XAKsndbCb8kj59H/yX4UgwF fdwqZ5aWdoSRLt+mNBIFJbFfOCjM4wiO52u1TqVi//CJdjzQ7gAqi41zufm4 X8az+jIVOUDfu6jTmYUUVPcsOWoz0QGm78Wqh+L5U6ErM+ezvgNU+Orrc2Pe 0jtcNpr9wx7ai7J2GLbgfi8pPZfYZQ+jR1/ercT+MXkdfge/toeZdr+Uv50U ZOPWymbhbQ82K+NPZPswv7SMyQsz2cOx02df5Y5T0EOODJ4Mih2EiSQGSnzF PGFitMLWawfpWqz9+dMURN6czFhPs4Pe3HO6V+YoiFHxqZt9gB2wR15vsMb+ eOyB+fVJczswvfOYx42M6y/2fbX1lB0IlEzpSOL538c3r11mjx048J1/QMb+ m9JmnV382xaWlp5GRGBeKt934i7/qC18WeGYp/+N+dZ8XjmlzhbyGFODrLCf k0sKj+x6ZgulJUHshdjvmagc1/wjbIEjRN+2D/OAoLJY14qdLfCVshh+wbxw OXXpqaWaLfyVm3nbhnnCaOa116iELRjO37VJxbxx74ybigqXLbyx67t2HfNI aoCEQNOWDcjet5P+jHV55+8NySkbCLkmLKqOeaaHq6q7oMUGRhcsuP7/voZi 6fWc9yW+Pri2PIn1zvLz9xJJNpA7eKji/9+PC9L8VaN3t4GoXSEW61hfVqkV 9NazgSmh27uGsDZ+7PePTNhAk9XZ8hSsfecu9pocsYGdowxuF7BOlaTO76e3 gSvUR0zq/48nuNFP8ac16P49/0gQ60/dwZq1H61BIEBBzhnns8BzVVi8zBqM wpMD03G+O23pt+WkWAPd7oehL3E9BKta+vf7WsPy2cWADFyvK3SRL2JMrCE2 yv6F6//8qX49cNs1a3B07pY9ievtm7lTx03YGqrmf4e2Yn5Kne84OctsDT3z 8aCA16tCOo7GcMUK4icvSBXi9VzoZX11+a0VWCeNifBjftp5+FNwZZYVNJBI hlJ4Pxx3SNI7EWoFKVQJgmJ4v5js4KRjv2kFdn63+fswP/XKcBt+HbeEicCd cUuYjxYix8S1my1hdMTKgBihoF2D6QxteZbAVvv+pssgBV11PlRa4mwJrT5O Zak9FFSZI8AUuN0S8vZkJ5Kb8fOWZ8Z/fbeAQbHmmIQGClq8mFdu1WEBo+vW XEcB8/+IsIlqsgWw/ii6xVaJ+wezWBWfoAUoGXjTnczD841Z4hu73RbgtKI5 RXpGQUerf72tXrkD99+2HPiRhXnVrLpBo/4ObDM9/NYHn+c3VXLt4Xp3QOKz 2KUTUXh+MtX6shBtDscydMjnbPD5rKqckHExBxSkvOeYBc5/N9dUpK45zL+R jGY1paC5yi/fjwqYQ//FMBjXw/1pl9WSDpiB+nPlLQ9FzFeV3rT1i6Yw8Gi3 N50Q7le7PtPvHjQFlomEaSYBCso0ucioX2sKbTuUHTjx/Ci4i5b5V6QpLAcV U2Rxv5Qyid13/KgpBHjF1q4x4vNYsXDAndEU7l85epWgx/1mp/rBxgUTiPEJ noqmoSD5Cs7Dhm9N4OpFc1nFzf+/v8gSJmmZgFBsJb8amYzSjGlOfb5gAjRC yWwrc2Q0Xm4uKnzEBFR6ttKf4P5taSx0tpliDI1cJmdPTmB/KX9NrIUbw6zQ T6lfvZg3mPZeuupgDCfDzrEy92C/Nrorl6hpDBZno2LPdWE+YpKRP3nYGLwe 2n2sb8V+Y/RO1fiNETgtZmnnYj9KuvFIPTjDCJhzrZ/xvCWjhAuOms+DjOCf S6tNQTUZxew7oDt/3QgeqvCX7Sgno0g6ih6LqBGc0jo6NIL5LHyl0eA0uxEQ 0hEVzcVkxJA1UrdUeRsoJbIwgf1x+72QJqmA26Av9tKOHfPalo5Ii6/CbXha kT1+G/Pa+pmhtibW2wAjA6pNuWS0yhLUxTh8C87fd/l9Cfvv0s8Tn1Syb4Hs 202aIezP8y39/cnWt0CiJiAnAvv396f+w6Pit8AnQ5NR4wnmH3+hz4c3DIHd Q1FbCvPduEHvhGWjIXTeTi6WwHw3IuU7XRhlCERM87mbmAf62QVnV9QNocm5 Z2cg5oWehe6f0tyGQPeJ4XIX5r3Odu8F/ykDEL93/JcE1q25/CvvXhiAIc01 8SrMG03BXb93uhlAsln/Di2s64w8N9RkDIBZuDh0F9Y1F45sPaQ1gC11hqIv mBcr9nVQf+nQh75PThHtWJesuNPxJ+vDj/QJtl6sCz/yMdrc0gexf2Xyq1jn v/iwq1hAHyy3Xhw5jZ+XE+7K+pusB2Uskw8jsc424+GQqdADTv1vKZtYP77Y si/ITw86u1PZI3C8D7mduVuv6YG+m8WyCM4v6Q8XHzOLHgSzsBxcxDq+t/mI 5qAuBBm0ubbjekQXORx7lKkLsTqKw/W4XuHR+4UnLHXB3jT3eDeuZ5Bl46lj Yrog3e57fh3X24uPU+J1vQ5U7b37+yHmbffNunNrETowzqZwaTdeT6dBaxmk pgN0z5li0vLwfo6vvdw2qQ0R0m/kaPD+MLO1lGct0IblyY/iI5jvb8uzKWm7 aEN4w4kTbZintKjuqH+l0YbBFArfEuYptVFm7ePtWpBslxUiWIF5rrJKzyFJ C05SnXvvVkVGlx13mWwc1QLNzKo49VoyEh8vddxzVRMEajfl2fD+P1Vzy1V3 tyYMW3PCL8xXxx8y3M3o1wBveqGD83h+4VMx8BO20ICvVQ9HOfowz9bRxMqF q8Pt8id9spP4/L6gzJ3XUIfZMaGGe9O4/g9Hrp3hU4cCluL+d3heknR6vY2/ Ug2UJY51BFDIyOiwqRvdd1VY0/k6HPuXjF4HNxi0XlOBzKY26gwuCipOoNZO 360IRetVLJwGuB/bDLPE5SgArS0tn5AR7n9yJR/8CAU4++sKcR7z1fZfxoSx vTyEvna007SlIC3tev6jnVdBUhdt0/PB/MPlv5IXIwdXxXXkBB9RUPyKdmEq vxykwNj3oXQK4u8QsYx6KwuhPgKj/tl4HvT9MmI7fwm6PRUfvMD9OmucaBRR vgh3zUUP2FVg3nE+uX7xAwK2zYbxasxLSUfG7A6vExDlc3dx7S0FzYRc0JzW lYFJpQBmxSYKilbcOGKzXxqUwoaC+D9SkEdt9JCJ8jnQlpT+NYn9xUScJ04v QArSVa6MxmJ+kjpwaV1hVgL2M1FHFA1T0JHYnleXDkrAxnpcIj/2r93UZubn VM+CCVvq4zA8/0/Nhn4UrDoNtlnlmqxTFNRluC+Ub14ckoMlDaW+UVB1d975 fYfEIXpFkPP6d5x/VXsOfYQorG12uohjv1zVq6n85ykCLqH2oXTYTztkvxwh T5yEHXIWws0UCvJi419vLxaC6VGek9v+/35j/Zp5zf7j8FBpmtV3hYIEJq0/ FgQcg2km6ZQp7N+brTHnH83yg6XUtrgz//NWcVFOpOpRmCy2a7DD/p+b8onV q+ow6MzN0cZjPvANWPWxOnQInkdLiDzC/JDbI/6xmI0XuvQMOOMwX2hm382J n+QC8+7eVBvMH9uca30cSvbBfg+7FFHMJy8vbVe/EcgBbSL2q2NY67IqHj+p xgaJgz4PXTDPMDXwbnFe3g3rz+ut/v97ETPjgoK+r/SQztKjrY15qIZKUicx aBucZutS///vRwQvhuzIvrpaW5OpojaCddFfqWbpnV9rBfhsr6/9f/8ek8PS n1qJWaVW6f+/v4qlt+4f+EUhPDzv8f7//dXe5oMJjm82ibNR4psNWJ+WC0pb f7sdiRoeGPDHevjJb8oFHibE3NJfJYD1JeryLAQs6FTw/eJSHN99ccc2I8oe 1OS5s0sI61kToV8BvJyI7KkpEIHzu5A4xfPk5gH03Zi9qwvXI74xXb7J7yDi faA+9Q/Xa8nzRNWSNh9auJMUvBdr7oQdN2gWDqFjZdXde3F9r+Z/m9wT/v// Ne1e3MLr4djQ6HGUjx+9jT3K1IPXq2npXtYVFUEk7lkzKYbXk8yoL6H1/Tii LZjfVofXf98RqbY7/sJILEH2y//8bau+tBJWdAp9Oz9TPY33T1vZzGWlo6Lo fIPqGe55zDuXtOI0FkQRxfmPscwPzPd6p4+ah4sjvqM2ixcxn/F+y7K30ziN 3u289O0IngfOOLNUufGdQZPxN8qWJinoVuS8cmjlWbSkxXpM8zPuD9XPPZ5/ l0Klw8w9Er0U9Mc/4N1W8zk0eq/B/Go3BRHX9Dl0nkijSwtlKZfwfPLh0+7X DLcuoNOKn75vvsfzy083stUnhG6Kuf66j89vBHO2+N7bcog4+6PnYxrmr6Xd eg0dcshshOn16EM8b/V5B9hfuIx+jLU6jiXh9U3T/Phu/xXEWC3IWRdNQdmC O+w9eq8ia/ksJW7cb6ovOeYNKiiiVXHuN026FDR2dOxjcKUiuvg4V8VOk4Ko GBT/iB67jvYpe+pzqOL16DxyLWK7EvpEOeB1Rx7zt97A1DlQRmekNHV5JfH5 PMcbr5yqgvJp1MN9OCgovKDvyZNuFfRSpzHEmhXz28HoijUGVSS1L+qEyS68 P6jWPj/zUEUC7ZsfHWnxfPmu5+Q/DTV0yOdMENcq7t/qoW2FzBooREBrlHeY jFRL10PU5DRQ7beUv3x4nk7icLi46q6Bqh4GDYhhnto/qF0m81kDqTLz8Adj PzA41+4wwaqJqjoMr7/DfpGeelEo5IomsqC1jNuP/eSo4fGM9heaqPzG5NuV RjKyqH2s6ziuieZTlBTu1WP/5mVjZ2fXQp82b5/Zh3lLZHI9XN9bC/WmyauF Yr6Stmh3nlPQRr+fCFy7XkJG91ounoy9p40aL0542mP/qzteNiNWrI0cPwnx 5WB/vPLzsYHnPh10bMP8iXoB9mdlNs6DSjroghb391bsrx8KQ7vr/HRQ+6UR B03svypODlcZZnSQO1l/8wXmp4Ser1QvDugig65cDU/MT32ndd7cvKGLohgO PtDHfr7vfrvbcoAuyn6/d0Yd+73e6kXRB2W6aNPutrkJ5oHH2mVz0rO6iDWJ XzQM88J45fFnn7n10OYKrWkD5onDB9JvB6roIclTv/ayY23uzXZAIFgPWSrd MPHBPJI7GtrbWqGH6pfadTYwr8zJbMTa/dBDTKkRTCSsT2Y4KLDy6qMPVavh Mlg7Uk3RlKnp/1fTecdT+b9/vKKBjCREJKqPGSEt7stKspI9somQvfeex5lW JRlFWUlGGYWMQojQQFmJdI4tq77vHo/f78/rcc79Htf7uq/X83Xc9wMkxYwO 70BxhY3JS5M4c+i7YM/2BfHRSnNXwNYLc9D5xCz6j6fOHVeSyfllDsFv8iX+ 8VRQbNUvlWPXQXXQ5MgSihu+izyaNrgOf9wLloXReDvUs22TE64D7a1VhS+K lR+z80nWXwdccJnOJxTHMsYP9dGuw29JukZ9tP43LpskPyELSOA5tzGJYsZ3 7lo8xhbQsGpLxaH9ap+a3PMyyQJ0NzeTNFF+iASTJpuXFmC/712dAMpf/3xX 8O5FC6gsWri5H+WXU09J7vEJS5CTHwlmQfk3eVY1r2VqCbW6BgMn0fnc5RAt nsdZQlS9l7EhOr9R32yH1EZLMCl9/u024i2BIXaBc8uWEPTgp9Yy4uWC25up 4eZWcKpZSmoW8fWPDferQgQraPhddi0W8bfY9UmG9mYreGb1t+gMqicTwg3Y e8gaHhodVhhA/D567WqlTog1OB8yGmRA9dk2w0nWyLQGzriJ94H1VCiNHHVX q7QGheU8/A5UzyFPb4lhc9ZgQ1wZ122hAs8BXJ7EdRuQ/J5pvoj8x67H+hEi ATZQ+Sh+hLmfCjOKvJYnUm0gSQe3Jj9IheceRYf5umzg65mvAh+GEe/1viHu l7eF1NqR/o/ID2FORLd9JrawVvb6eTTySyd2mGjR+9hCJTETsEUqLEtO790q tgXCysDfr+uovgm7w3/y2sHz+RbNNgYadOso3+rYtIPAzpGBNDHk/78zaLZx 2cNgsm7SkiQN7oW9F26WsYdT3F9XjGRRfy+znnzhYg9OhUGS4gqof7OEmz/+ Yg+1a+fjt3RQ/3pXdyWhzgFOyRjPUbxocMoh+r+YIQe4d6ezcc2PBoe2NXZH LDmAZQuh3TAY8Yr450Z/sRsg1h0VvB2N+hPu91nHuzfA7MaLndOov77SPHNS LdgROo+I+EdWIh4rbrz4Kt0Rmi2VawWQnx5l1Lp2rsIR2Bk+hzyp+8cbtiGi M47QUdPDcBv58QvqxD4WYyfAH5xMSe6hwdtC3h/xXk5QbSXLkI54y2Rv4fYO vBMkvrxolox4y7+tQXipxQk8CrWsZb/QoFL1Z9iQ9E2oLeOc90R6pPLAL1VX 5yYs5xittSC96qPbVfT25k1g7I1b/TOD/H8z90Bdzk3YusB79iTSvwjBB7Oy 9Tfh7elL5ezzNGCLktxRNnQTtPuOkiYXUH6U1MRyWJzhutkPkbNIXxty3ise FnWGSRdLhZpVGmjtsDAiX3KGvMUy93/PCw1b/XBhsnEG77e+QXaIl1xeeUfG hDiDBE3iCAHp+Qb/3/TtDGfIPCXNnY30PiksqcTvmTPoLVDliIgPDo8eaqZ1 OwNud/clB8QPjxRyh5xmnSEix4OLD/HF2Xviv8Z2u0BVRUh0zb/nabdqdpkf cwGpHTM3ZBGfGF1X4f4g7wKvz0/mU1A8VdctoW3iArZ9Y8cGUOzDa6bS5u0C 44wP3v173pY+eMoECC7AWah2+w+KKZ893J4XucCs9NWQ7/+eN7qwFX26zQWi LeO9y1H89Hb87aIxF/hsLRF5HcWK6+xPhLZdQGjfXMksWk+vSXZLFrcrmDG3 0pmj2Oq5yOdDsq5g8Usgs/Tf+yBcVTT8VVfQyv0QOY72G+avuHufiytcPrpn dB3lg3mokycyzhVUhhR6llC+suSMpTZyXeHbkFpoL8qnWPr4Je8GV8i+an2I iPJdu3LLfO6jK9A3jryVRjykYbju4bDsColGTn3P0Xl9qoyJG2W9BUl971wE Ef86cbBlGYvdgr2d+z66Ix767X33aa/aLcBoXJa56Pw5ZSqGm0NvQU/kzNxT xNsFZIXFi7dvgSstNYs0S4Mzi2/2VlXegmfk3mdGiM8Nnn6VLvx5C3IpEXfJ EzQgSTInJpu6wd9R7onhj2j8uDVPMW83kPFuPHFykAbWo2NmnTg3SFXtUjHv p4FUSrU4U6MbGGu31Ca9Q/mbtepNOukOcc7bfYxNqB4LKriSltxB0XT/pY0H iGfDdHak7fEAIUaDtHO5iAeLXi/bH0Rx81m88z0afNxZNkIv4QHvwzqri9NQ /ZRHPVG19oCf8s3fKmJpcJlFXL+lzQNEf120NkF+bON87uXUfg8olxpc5kR+ rcyBU97+mwc0HXIt7DNH+WjYcYJ+wwN0E09+UtGnwXeXgVUVCU/w7dsi8SvT IO5t2J3XFE8w9W0NVBBA9/PKEp6S4wnZ/BmznEfQeQvcjLYr9YRnKutH1rhQ fQbou9K1e8J4qTRHNyvyI/8JYyobnrC1f0zo+18qtMa8H2u29gJecirpHPKr R+xTBgvdvICJWDfqO0oFH5UrnbgQL4g2wUu0Ih4S3NVUaZTpBQrVGtJZqD+H hZfHz/Z4QZhh48eLbYgPLF1Deka8gPbfEfXDiG/EMWHPyp9ewBrlLcrcSIXP W/fNwvZ6Q7R9veIFpBdyQQQJdvAGHaJJdfUTKqSYagquaXnD0W2hjwbI70+e 28s1bOYNq+JP/+xH/EJeC9tR4OcNVpYWn7uQns0MXlhJivEGVd+6SwNI/xSr V2fcyd4wYCgiuI70kurj1n++zBuG7y/dSkV6e8lA9A1/vTcodL/w2o/0OEvm ez1dhzfQ57kdzEV6v8Se9/THkDcon5Ii6t2lgsaiRcG7KW8YO/Tz+LE7VMh9 f/huxZI3JIefY2C+TYXf5QOEjJ0+4HBA04MzkwpXiaSYEFYf4HbYlaiQgfTV XTvQhs8H2rw+hkalU2Fbh8FNTcwHHGV6fKbSqGBwqtVW7LwPPI0JINxAcTFz pDHbZR/gyZyZ3Y3iXb/ktVYMfOCXyLP7r1OpYNr1W/GzrQ/smhhtuo/i8uLK M688fEBBbNr6Dor3JnuIPgjzAdLHqvhnKLZ0Fj+aiPMBvueZ8j9RXHXlx0G3 Oz6w9kY7UgmNv1/kwT79Rz5g7NivV41iu33W22erfaC1Mv/xFbTe2mnexSMt PrAyFxS4ieID7UPfd/b5QO8D/6edaH9OBZQv37/6QLzSn4u1aP+vYq/2dv7y AbJa1Z82lB9OB6bW8k0fuO365PMCyt8t1fYXaQy+8PbKsZILKN8tQtFlQVy+ INpYpJGL+ImXDvKtTvhC2g32xBPovLzGNzJUZXxBuiD4TDvio7dN1TgRJV+I 91A+HIfOVyDXK5Llqi/k19Ov26Dz77aadf7o7AtKJY6F7ohnT0CBVUOAL3Tv zZ3OQXwTwm9rkBfnC/rPuPdSEd+IjnxScM3zhRgVEcpnxDPxZm/Zdnz2BZ7i 7QeLiF86qmTdf3/3BYNiWmQL4heWAznv5pd8wa3990ZxM/ID7X5JY8x+wNeY d672DRXyZI/Tv1byAzMKxeHNABXqWcLXYh/7wd9dXaWqS4gfnWcNw6r9YP9J AcOLa1RQaTWs9HvtB1uaO1ZhE80XLO7pOOIHibIfuj3oaDD049Os+gF/oG56 /7TiQP61WXaUKdAfdN4tD00g/3OGP0eePs4fzifaFLvJ0yAgkOnuFtkfZLLV /24p0uCv5LjxrxJ/+INtKB7ToMH+e4T33d/8wa4jN877Og3+859tIakHwFuT iwbpETRw7jMUSjIMgAbHmuy/Mag/STRFRtkGADXXwsg6EfnPyQzMOyQAmGfV t+jJNFC+dum5QXkAiIpc7mrNo8F1sZxiLu5AqOXsuhyG+qm386+H3ccDIdKJ 2LXYgvT38YWc2NOBkDTo3aP/hgYv/htIXdIIhAHyeNdH5Ed7bwgSiowDgffO d9wm8qs/Hron2tgHwtkmHaN9iEc4jzOG9YQGgoXlsacjn2kgYWccEJcUCNkC rwQejtBANe+Bl0JGINx6bWNk8A3NLwCOxeWB0EI+suaIeCXJCmdj2xAIKXv9 LDoRr+RlfzI/3BEIJZPpERxIb3qP+OjGTwTCZqmegBHilWnzJg1sPhDwhmYv tJFe/bnDcmllKxBm6cTVRZCecX42hxKGIAiv0bnxA/l/icOPz9txBoE9PV1F EtJDVZNVGR6hIBhZ0+5mRXp5PUPl1HvJIBDMl7PzR3rqPUgUTpAPgs+KbXxN SG+TDo0KwpUgKNkvWj6H9DjXQIxv1TAIWo++fv9Pr59TArhKbYPAxFQefiA9 7+lrPWDvHgSNmaW1NUjvvx84uJ83JAj4XmcyOSEe2Na13tOXEAT5rsx/f6OY g1i6IzEtCPCzLxydEU+I92xsQF4QCOfP89WjWIVFfWW1LAgyOuv//vu9xkw7 jVZaFwSPaxfn//2e44Ubn7F/EwRqQie//HsfPLFTcpJ3IAhOT06W/nueKYcx dLRvLAgKtuMsfVFcc6XjYyI1CAJr7H7sQXF3Ale/4mYQjBtXaAWg9Uy1279b 2xsM+eEl5Ldo/Vt7KtrLOIJBYyO2fQPt76Da3yaHY8Fwbe7WHyYUi8Zq1R85 FQy6cvG62yg/yi23q/svBEPlDtaRbpQ/U7rp8qTLwRCWz/I24t/vN8qyxUoG wTCTmQUHUf4TIiMf/rYOhomQFs+4f3///Mt750ZQMOjdsZ1lRef5DruZyhcf DDRdxfKT6LwnQ6vxHyjBsBTlJnUU1cPBLd1o5dJgqBs8nl2N+Fb0Ynbo+otg SBb/ec4I1ZNy0E//8rZg4OuP//FxEs3/O9aV/1swPI2I4Uv8SoP4s/03BubQ eg4dDqkZpkG2n4ANbj0YZt/fye34hOZfrjXcYA+BU4dWxHMRr4gu0LDBSyHw 4WNmJ18bWs9E9Pk8/RAoHH61LoV4PnuQS9bNJgQG5J1URF6i9dWDyJ7QELh2 NNeyqwrlM45wUK4yBB5Wz1ks56P8H5H8kSYYClFinjWZISgfrK/HbaRC4Uo/ 5ZyTP1r/LuMRCSwUVh5zdIkhv1IzHdbXahoK+AAuO4ojOt+K7voVYih0mK/p 7NJD9avuRjL8GwoSsiRm/ZOI3y/uwh1jDgN3LFZzCvHJD4n0uF88YbCg/Xs7 hBfV/8GXwbFyYTAERw81sSF/NMp8o+pWGIgHkXbXov63432udWRwGDwpLJxO W0X68/qMuXZiGHyS534RvkAFyccWulMPwuDHQsnFyGkqcPuUXjg0HAYsCW5E 4w9U6LuhdGZsJgwIq709L5GfxJkOSJauhcH5Fc93FzupsBO2j186GA5FJ7Yf BKH+XX+adPTAsXA4c5njEvaSCn7HT/CMnAqH7yy+kryIT2YZtFl9NcIRt48r HK+gwoOtbwxKJuFwc9SSTg/5YUuaDz3zjXAo/FJpmIX0pf9D1vqDyHAQvx1T koj8ef39uYkPz8OBpfel2hekn7YsUuqVreEgg99KPI30mCHUu4TSFw5VxSXu D0nIz5pt+OjNhcPoiU7GHzjEC28UPp1eD4ek8bZHNUlof3cbs/fRRcB01ZHa ggQqBDDS0/1gjQCudt/+yRgqdDadqDLmjABNH6d7stFU4A+87Nh+JAKe8SZZ PoxEeip18/BZoQiQaVB1ORuB+G86qbNAJAIozd/Yf4ahfN4vCeWUigCT+YD7 jaFUcDXqloyTiwAp1nnD5yFI35nnx1bkI4ClqNa3L5gK7K0HUh1UIkBClfM8 K4odQmTUBq5EgLxdzwe3IOTXZQx/q+pGQNrShYCFQMQbP/2KKo0iQK5ISDsD xVZ5mdePW0TAobo2f2sUV5jWsqTaRUBk4jvOf89n7zkw3EjnHAEbC6dV/j2f bfpm28vbIwJe3lRiI/17Hjv86IkJPzTe+5DkHyjecVZpSC80AiS/ldX/e99I n2qb2BwdAX0rVQ93ofUVPIy5KJ0UAbJHS5RbUbxxveBXLjECjg/nJRaj/Wlz vLl/ICMClEz7navQ/nM6Z65F3kP5dHPrHUf5WY5iol/IjwCri3ezZVD+Ll+Q qLYuioDHldHPClF+7yzoOPWWR8D2uZPTGMo/9ZEHj2INWk+sK9M6Oh8la3LX k4YISHHlnhuIQ/zAVRl2tCUCPMy7dAbQef7oHpAidETArDhtcRWd98W4tfE/ vRHgfiqHdCGFCuPLFy6PjkQAYUs35iSZCmdKrq9rT0aA+gNLsW5UTwl2YcUN sxGguvO8dzriM8m+JtZ7axEQandSLR7xVcgT9Y/mByJh5Mg2NoLqteeGc1In VyQEGApbhqJ6FuTHyV/kj4TDalLyF1C9v8X15PCIRQLHC9+uveh+4HQ2uvlJ NRJY6vbt/daB+PO4/YZRQCS8CzKS/DqP+P/MY/Fr4ZGw3ReTb4/u3w01qqVm XCQwLwhi2+j+VrkZ8BpSIyH8IcOy7V4aDJbicMLlaLzH+84P8yO9kqvi35hG 35fd1ta9ivyw+obuMjUSHrlz3LphiPqFKURTVyKh7mLFf4HILxGD306P00VB SfuoGB71p+ONI+WdR6PAp6aUWyMc+dMre1TuGUfB7ePYh/xiGribafpmWEaB jnY8tJbTINWFWEhyiAKafdnKW9QvR1N49sd5R6F5ymT8X9GA7r4VFhEUBePU 5cYjiF+Eyx94BEVGQfGY9MP7iF88+04NuBGigMJn33wW8Ur6hPfem+lRoLLZ fkYD8Urt8vPzdveiQCGS3k8W9Xd6LpVs4+Io8GXaJ5mM+EREOKH3WkUUpFs+ El5Bflbn/LtdWi+iYFR5c+E00pNMc2NHxfYooP9u73z0Fw0aXLNuX+iOAr36 /oV3NBqMh451yg5Eweu86Q0NpF97CCf/nBqOAsHTwqQ05L/FclykRCZQLPji XckqDXSfltsKzUbB1PGgIQLSR5/mlVS+hSjgvPBoQgHp6e3+C+1cv6OgVVhN rvrf+1aT4esH/kaB7gkzwd9IfydWWsT274kGTSKekQ7p9769jJZ7mKPBp93O ZhDFEtxXiTs4okHQC/fYE+m9nkhq8wZPNDDFXfP7gGL/C5+Wl49Fgyil2eXf 7x9Zmvz/0YSjwWiKBWgobrxuZzojGQ2W5s+qC/79nnLrUfKEXDQU2jYUHUfx DoVWL0cFNJ9R/AX/P//e5x43/akSDR/DRnAZiB/OfPmj6K4RDasFN4pj0Xp1 i3iFl3SjgZuxrlQJ7ccl8Byrv3E0+I0Kv+hEvBCnbri6YRENjFk/dhxH+cjl 8hoJs48GLWPhNo1/zy9/x7fscokGEfd3xooon0NVxcVxntFwTLOLfTfK92LM GzJjQDS0FvfZ3EbnwWwwFYgPi4ZZTsOG7TlUL0K7bNhjo4FZP7hYGvGlyiK/ enpyNNBr7mw8h87XsumiJA85GvJ2MGWxIV5ItfLdPnY/GkZi93idQzz75BR5 8uHDaCjvk5xPRPXTsV3WKVISDV9/SWPlqL52ZP24ffpFNESa7h4Ne0cD14/m ckr90fDC5tY3qEO8URjA1/opGt57GcnpVyPe9Uujv/INnV9kZ7XKUxp85Ojp 0/0VDfFvBM40FSBevabsbr03BjwElyT1iTSwErAymmSOATnzbxk+STQIogUr OHHEQG1M6MEw5A/KU6qYPI7FwLDDqP7VABoc6RB+FH4xBjiv5TVyWtFgWZl1 LNs9Bu6OJfUVitKAlV38jaBfDFgP7uRkOo74Zkz9SUFIDLwW4W/14KOBdXhU aFliDJjcPqKtgfigq27l8Mv8GLhxd/H0DdRP8mWH9UaGYiB58KlcfSsVHq3M xCuOxgAub2TXqUakB9Vr9fmTMSB/07+sDvWr6nMH/3NeiAHDXdPmUuVUqFsX uP5uLQb0lN+J8hRTobH2FEnqTwwI2ZK9ThQg/yWvsbnKGAs/aWIvHyJ/2rNt LGV2IBZkW96Z8CF/++Glg0MDVyy8C1C4XUehwqhiZE/08VhYjeOa9EimwsRO Av20aCwcX2dRS4pH/bw567zG6Viw+BK01Y30YFH1eT4bFgt8zaxVo0hv1na3 ffRWjYUjRdD+732lrbZ+5iGNWHjRoqv9yA/xSsKY8oVrsbD56bfcgDfSwys0 /3vGsRB+7MlNGU8qMDFul+ywjAWRsITG125UYOtkHLezj4WspiWmeFcqcOC4 udqdY+HNZOKBMGcqHNY+qSXqGQukqefJj50QH7DIRqb4x4LcRoUIoyPq/z1K 1fOhsYDT20PIcaDCf8SrP/VjYsHjxB39W/ZUEL9mIVCTFAuTDPJ0nnZUOM3u YshDigVPzhC+ElsqyPUHJIVmxEJNV9mhoyi+mBr36tu9WHh/Tluvw4YKioap yyoPYkH+9UGJMhRf4swTKSyKBfaptMV/n2sMPbFkfBoLnUri4wLo+quZDZRb NbGAr66QKEexgWnnm96GWBgJVFoPQPOb8nzalmlB+VA6aB6M1mf55bt0Rkcs 5LXKm9eg9dtlLTtu9MYC5b/QJXG0PyeLXfcshmLhgc9B1mG0/1v8bH2NI7Hw ajMwqQXlx+sr397jk7HgH2Es8x3lzz9HTD5+NhYS/xx8o+iO9NPmvOfsfCxw Putd60f5jxS8XKC9Fgsyima2932oEDdh8KV8OxZyTqVl5PlTgeDgccmfMQ5e /tilr4P4IfVkWNBntjhgsDd4vIJ4IXM6+YkCVxwkvTJ17oulQt7NwsP0x+OA zuoZtwieCoWiVTqOonFgSbTVy0V6X/KzObpDKg5cfa0Imkjfq2+N/iIqxAE5 n3HxdC6q71NzgssqcXDIkjDsguq5kbZubKwRB7W+1fr9qN47PA818xnHAZ+U QOWJmn9/H9JKL/KIg6z6AMZyxMuVxFDNTP84CC1P29kwSIXk4rIdcWFxUHTf j2NhhArnxthcbHAoHksQaJ2jAllrALgfof2MeQ8OMNHgkpDlTOzXOPhm4B7H q436AUbI9v4eB80yPlF6SL8XTRr1bX7Fgf70F89IC+Rf8IIv5TfjIOyuEeuL WzT4vf6dvMQZD8pv02+IpiC/wsGtPsYXD8S+e1H1qTR4KHllu/t4PKxlyqaI ZCF9cSh2LJKOB5+U9sLYIhqU9LrL2+jEw5R6sMNXpNdRP3MWdAzjoX7hif94 B/KHe/oK5K/HgzRugZjfSwOpY3TXRe3ioc95Tv3oINJPedkD3M7xwCDIraH3 hQbDRg5tuz3RevKsDM4jvX7mmR685B8Pmj9T4T3q10m4dqmxsHjwL9+5zYn8 oHXh76nu2Hjkk9Lv7EV6LdcscrceFw/5+ypVc5CfZB4x0y2ioPW/yFAfXUJ+ bi15d+adeCg/Q+Z8hfSmlr2hNjY3HrpvOaoqIn0iSlDdvR/Fw68sIFgh/XJU P3rC5kk8HMX/HeFBeofZ6X7WqY4HPp4TKh7//H1YJEG+IR4Mcqv/WCC9nM2s UBVtiYci7tSIf8/LNj2bWOfqjAcptaqbWyjO7OZ4srsvHuTi9uD/PV/rNnPJ fuljPBj+NVn9icZTpfc/PPY1Hjz8FcZeofl4jz7q7v6O8nflXcsJpK+L5z9F 1/+Kh5tx5Vf5ED+8MWA8X7SM8qOm61yA/Ha2+0VqxmY8THqHn21C+umb5Jof uysByoRND7kt0EDr4T0Tb4YEWDlMn12K8iXY2M1sw5YA2qZfCiNQPn9//tus w5UAzvONl36gfHevSAXI8yfA69649inkp4PFKONc4glwsfvQ5KMPNFCnz9Ii SCfAhZHUgK/dKB8jD6r3nE+AhIG7PI2I18rw1UkrlxKg7dOe8nikj0GOr5Zd tRIgWp37hHclDS4rvrGc1EuAp3iNxwdKafBt4ZN0v1UCENZZn3jdQ/XVMZ6l cSMBHCSWti6k0SAw/+eeZtcEYM8voTXhaMBuuP25PDABlL8trnEHo/w9F4jG UxKAleO701VU/2wkkV+77yRA1yffB+6aNBi5KW0cmpMAs6PL4q5KNPDjVRVz LU2AvdYddEwSNHgc5th/pR2tP29K2YyOBiyXyoR2byaAAcOHeEWkZ5/5alJC diYCm6VfHKD7vXD11drS3kTQZX3KbI/0S/HR+85xjkRY3rxjKpVIBebIz2fM eBNBXHbBZCwcXW86cf/9sUSY5jPR60B648204t14KhGSoq4fMUL9U3Fye+Ts mURwi9mq2WmB/FvDHvUnFxPBJXzP2KoB8lNu3Eey1RNhYjghs/sS6p+Xj8Ud upoIl0vOaL3AqAACovM4w0SIZuvo3z5LhY/vL7YE2yZCU+5wXL4Y8tNFqqeW nBLhuUvPJtNJKnhGa2c6uyfCDP/Wh2EBKmDXjXaN+yZCt/Eph8NHqMB4xsrV NCQRHtTTvrRwUWGI2WmwNyoRUm11VcYPovG+eyiqJybCwxSPMB82Kni8Cix6 RUgE+3TK5TBmKihkRnGcTU+EjO2YU7uY0HieyWFlWYkgU/c2fRcDFQavpP44 kZ8IdawtVZF7EW8I3tO79zgRjm+ykiL3oPE2H9ZzlCfCnKLaFh2K5T+UncRV o+t9wjMYUcxQWkOka0iE0djWrnQUD8Y2bgS9ToQrNr3dj9F4eZZv7RffJoIj A3O6KppPkbSis9ybCE+dD43eResZfX3s/OoQGs9R8UAqC9KbVW2h36NovUVJ PhLsVOARCWLemEoE84aweUdO5K/NC9Y25xIBq1ViUeGlghG+b2x7KRFqXuos NaD8LTf+6fy7kQh4ETarIZRfypJo9c5dSfAi70BBigQVpE8a59AxJIHbU/on o7JU6DWJTtrNlgRt2jK0dnl03i+/WDLwJ0EkLeiekc6/95v2XmE6kQTXujyy l42poC4kK8MsngR+zH9WeJE+xyTg9h64kATl71XVF5H+CdY9X2BXSoKWykvN aYh/Gn9NfuFQTwIbsfHkYgLiHT2Fcm6jJBCe8GY+8JgKvnxUEwGvJDCDNMNP X6lwo+JqkWRREsgVlX46Z4D801Rw6umnSaBtHaTlZ4t4lutRmMzzJEj95tXg 7YH8W8gO/bNtSSB/KqrDK5mG/K64wvl36PrR8N1GmcgvjJv8d/FDEpgGT2XX P6CB8eWnm9h4EsSsS2YOon6wGjgypTiTBA7mA6kubYjHSxh6leeTQOnHoPFl pBfSX8/Uqq4lwSY+zdoc8XjvAdsHan/Q/HHD+bfHUP9UxePVdydD6OGwh8s/ aLDfvzZAY38ymKn7pVkhf1D0+Lut1sFk2NqwcOlG/VB9mF1bhycZduTp08mh fv+dBc7qHkuG26EyF3Gov8YouRzTE06GqB0LLG9QPxb0yWAykEyGsgm6yrF/ /bzg9YqhXDLEJfRW9aHY+hPtq7ECGl9plSUdff8P05EOU9VkuIrboyKMxsvC 1CvNNZMho6TFJx75nQuePtkWeslAVS0Nfob06GN+ToKVaTK8kb6x9q8f+w12 edlYJ8Ovffusgr6jfsqwft3OMRlCcrZY+UdpUHHxxGUHt2RY3mlnnIP6r67b tdOOvsnAziwRzIj0lpoTynszJBnMj67WO75EfnTPIM01KRkeHDVOlUb5rxRd +k+HlAx5ZwZGdqfTQP4qm7VkZjKc9Epl44hH+pCp0bvwMBm+gOUJaeTvXUVf lfs1JQPDEc34PYLIX+gM/zB+kwyvXY6nnUF+IcR7XeB8TzKsrF8QvvmHCrh6 GdLmcDJ8ZXNdMPuCeHhM9+3wRDI8XuyeNu2gQtZut50vZ5Nhfb49d/QF4iud R54Rv5OhhbmyceddKsh6tz62+ZsMZ13oRaZwVKjPGB9T3oODcM5DjB9R/1St /3v4ODMOlhpvbG0hPu/6dkRvNwcOcB8tdPxuIl7dfSHpOw8OvrAodjtYU2FY xLi5/RgOkhz5iHMmVLDX8dl4JIyuFyguEdWnwi8vknSSJA6yrSbWsKtU8Mso c3aRw0HJ/FCJmjYV/tR15mkp4OBozxKLBYrjvv34LKGKg+r7jzfvoO+z7N5z kFUTB61Grc6cqD+niwhpzl/DwbVhj89jZoj3dRSj35vg4GPKoQdMiJcLvCzq Kqxw4LxbReYe4ttTGUFLlBvo+tVsvjuhiC/rMsR8b+HARIr10N8U1I+/VdoZ +eDAN3f/k8YcKrTR9909G4yD356K22+rqKAjQuvnjsLBKJ/TwkYX6n/a+/dv JKD9XfFIOPkd8bmXiOoXAg4Sedqfs+2kgXudXeW9ezhYoWwkDF1Aev81Yi7s AQ6wh+t0X0xoEEGffdy6GAdtzw4fmfKjwT6RuutKFTh4q9xXexnxIFH7Y6rg Cxx8KqKcOFNOA26vlS66RhxIXPQ53vCWBjnp7Lun2nCQF5SY3IF4QbhOUqHt HQ4sTGf8jiH+KP+q5Vv4AcW1+wiW6P44R+9cmvAFByH65M61f79HCMdP3RzH AWuopiQgvlHXfsCnOYPOMzV5jxPik17PJkPxeRyQBMvECZ00MEkfTWFew8Hg FPF1Wzbih9rNVuo2DnIVC/NO2NDA6Sv3nx76FNhn4ez2GdXrPJ2c3FOmFBA/ JPVTqYQKAcL6bmT2FDD/8CXt72kq7ND2KPA+nAJ/2bMYuXJ/QYJnyqiBQArU K7qeo1+fA7b0Ik65/1Lgzix+V+/5OcisbdfhOpUCV/fPjvHb/wSBr5Nxv2VT gP5G1uWzgbNwWvjoWq1yCpgWinvOuPyAckaOyRNXUuDpNHeci+00nPq17z3x agpI/PBM9b/6HUQrFotuXE8BlqmIpjjuSXiUOp3x3jYFOpy162FjHE76D8fI 30yBGksmu7qRMRCUb7Nk90uBGHICCDh+hRz+Os3QkBRwd5ed+qk/Avw7y8/9 iEqBew8nYvQMvgBv2232l4QUmD+nkPg2cwjuPML/FU5Pga6Ds/bPviJvkRw9 R8lKgVssLwf2KX4ADt1bbTcfpwC/mnLVYe33QJa2ffbhSQp0a7z7umexB9gO GedANcrfz+TOZ4HvAL+mmVJUnwLZtIdfFSU7gfmzYtCh1ymAW+419WF7i/rD GceItyngNa4V8pOnHRjvixr87EGfb8wsSWi1wh57jlNNwylw3EyNW/BwM8So MfCKT6TAh2+HnJaeNMIukT97M2ZS4KDRxemX7S8hgmlpeed8CgxMrI1aOtTD 31/TY66rKUCYkr+TJlsLYb3D3UNbKYDfvr3gefo5bFW8r1Omw4MB9RC3qkk1 /PavS+Nmw4OTRsKGDucz8DMrj4rmxIOsmFy0Y+FTWJZ/6E49goebmJeblFE5 eB29c91UCA+h5KhwQ8UyWNhJuNIigoeJgWhrrj0l4DEZLScphYfgaxfcvdYf A7UtQOiOHB6sPrhJp3A+gtlk2213FTwccl7MOdf4AJzcjGc/X8GDcets/321 fPiuqzV0SRcPH0j7XjnO5oK9jFJLuREeYslsV488zoGJQ3JPeS3w8OXsqvqO nffB9rdodpwdHlQObpewjmTBt89Hkxdu4qFNrlOyePwODN9ncGj3w8Mqr2mq lEUGmEX9uSYdigc8NVnyZFcafLRfwu5F48G17ZtHhUkqGF3+IbYvCQ9PXy33 ++6gwIDICLc3EX3e/4Om2kQCg/19u0fT0Xw1uh1Ct4nQR21bVL+Hh3Uha9no /QToflbexV+E8nee5YiHTDJopT98kViOB/7yNiatoEToCLhTsFyNB5F8f0Ya 8jnq5gSKVQMeMjsGq3fYxkG7QkxEx2s86Nty8pn9iQE1gcBbZzrwIDTy0Xbn s2ho2eVmltOLB+X7mf0nwqKgsd1Y1m8ED30TY/uuX4sANnqPXJdJPNAze4af jQkDa8UEFpufeGA87vXHExcC5SE5wUaLeFh45rLb9nkQ/H3+/IfmOtrP3Y5A ld2BoLPSa6i0gwDEhtamFA9/yD490yy3lwDy1Z+sqWu+gBUdvnfsEAHMCh8/ uKPnDfjvpxm5jhDAKyoo5KSgF4wKavjvFyLAXsmyUKU9nnDKynZypygBFGte sfdsuEPo3aBra1IEWLpmJeS43w26hsgv584SII1+auQF5gpHOIrFxjECULf4 v9wkOEM97svud1oor+RnQYbRjrD/7ZJXsz4BptpiWCoFb8D13fu/1ZgR4BXD 7r6yj/ZQonRcu9SGAISKSd6n+XawGSpfm+dEAI4dsyuqUbagUWvwX6Y7AWSk m7LYvG3gzqpraoofAfylFU9/8LGGC+733AJiCHDbLDrGU9sCkoqrvtxKJoAl 2ycWymNz+Dz9Tt2OTIC/HsUz14+agejx71UmtwnwpJb1Ek+pCQRZ/xHUySFA 5+rRnjPXjKEji5OoUkiA93mTSmcZjYDn06ntc2UEKMkSFGwaNIAX16yGhOoJ MEOXyuj1UA/24f1VD78mgF6LvYPew2tg0kF4ytJBgJ/jx8JFK3Xht3Jj8voQ ARYr+/KZVrVBPfzjb+ooASJKnjAX2mpBZt28w+QUAY43HRc0/q4B52SPKfYs EYDzKFOhnoQ6JHicL23ZIMAjzvrUfVQ1cB0UZh7ZQUQ+gr/mQeMlqGdXCurb S4Rk6ll+9QwVmJR6J6XNRASz2zzsJreVYf9V0+l2FiLs3yVxxOKxEpgnexo0 HCKCwk61gV3fAKIebzOeO0yEefxmL6aBQVF7YlPFESK4+PRJX++Qhw26vFOP hIhwS806S3bvBRAUPDUl+B8RyNiybXbTOdBQrL17T5QIH3XP2aqmnIU7IX37 KKeJsPdsaYutwRlovmP5ivkMEVqbOeZYdWRh9vmsb8I5Inj1TA1aG8rAhZVd E6FAhKEgi6SZxNNge5Bw+7cyETYOJm7XVUlB0mleXW81IhwYT+Hp+igJn27J NDhpE6GfaPa5kyYOW85iOo90iTAzacl+r1QM+J2Evk7rEyHzpvUwOUgU7G0P 7nQ0I8JAt9vEJCYM8VZM5AILIugdjn80JPsfFF2nE/puTYR7CXSfeM6ehHmj JVUHRyI8v/Z+7YTlcTho8HPggTMRtq9/VuiKFAK5axM3Jm8R4cO1maKwJ4IQ otmfYOdDhGwm+qBD/x2D++qdh/P9iVBzl36UzUMAmi+9LhoPIsKNBxSv5Kij sE/xWZdNJBG6d7Y/pawcATGFYovcGCL63syR2hZe0LmQT/0WT4TrZ+tZbHN5 IFWWwmaNJ0JwE92BkghuqDmdnHufRIQLAjIhfFFc8PlUtPTXVCIQX8djZXhO EBDxNrC8SwSj5PdNfO0coHLSZepeNhEqE9zn6RcPwg0hO7+RXCL0RkU/5D15 EEr49DOvPyJCLatXhsijA3COXWbYrIoIl/r/s1JnZwFzVrFbd54TgfFgaazv 1H4I2y/051MdEZTCLoartjJBy56DAqbNqB6/NuskPGKAaTqmp5mtRLAOrI6n Fu0Dxp10yh/fEEGy6UTBx5q9oLu5aGfcQ4R1r12PrGi7wfv37HJ6HxFxXeMu /sO7IX1lPHZwgAjFJMeHeZr0MEzrKzQcJoLg8DOBwLe7wGmy4qf+DBH+Kwj4 8ph/BySPFYVQ5lA9tbySxzH8xcpG85j7aUQo26zbeXB8G1v+SJbUW0X1+3JR frVqE+MaTGokraP8KLiqGJdvYBf6o6693yLCnKczH2vVOhbxzstbl44Ex/hq a958WcPyO5zpiXtIgE2qZqxvrWJt7bZpPQwkkEqWYvl6chXb36xXo8NGAlXW T77GlGUso1p6U4uPBEe71s50tC5gZeJCMiECJNj19bad28kFrC3voEuxEAmq 7r3AM6XMY6v45c8MoiQwGcxXDh2kYiy7p9jPS5CgTLKz4HXLL+xk8ICGkxQJ dDVTXkg1zGFGjtW1bXIkkDd3z5vumMXcRgoWV86T0P0sEOXxdQaL088QPaFA gi6fu3X3tn5g1RBwJ1qFBCC+KYe/Oo1xcl8IUtQlAVdPZcd/VyexU3jRCnd9 EkTtHCngzpnA1Oh5Z7ONSHDefqeF4do45je/abp9nQTlZJXEhpoxDH9jjiRu TQLLhdkeH4ExrGB4+K25HQkCePwtCPhv2OCbhvO1N0mgmevSp7A8ilGxMs8Z VxKwanVM2FJHsD1V2Y+5PUjgzHdOsWVhGJPLDT/s70cC+uin61/Yv2BpgUrr MtEkOLlBpAuvGsJKaKdP28WRoF2dVTp5fhBrcRC8SU4kwREsQMtJehBbvkb3 aZ5AAp71HFL62w/Y/jdLbAIUEpz6wJ7lxv8BO45Nql9NJ8GXJ+WsJwL7MQPR 1uelWSTo5dy1qQ99mGtO1fzwfRLcC6TndCh6j8VwFgjvzyfBjdNlpbE877HK XfGZzo9JUGkl3HWRoRfj+KIe8F81CUK7VAQpZ7sw8Wvny41ekIDCqPtZwrAT U20X+RFbTwJlshyvcVAH5vOM0WSymQRhCv+JXvr8BsOJbBIOtpHALDNIN4Hj Dfbg/s925bf/6mvD28iwHfuQ3HU2t4cEag5hWkUzrdjczgb33j50PrVbzxrl WzH6gNLCvwMkuJQ9fSk6rQWTtcdzWQ6TIJ5e01HV+DVGkddd45lBn5P7x7M5 m7BUKz13whwJJG52b4zGNWKpUQbTdPMkaE6/y6Hx+xWW/sZkaG6VBONvlC7v n23A0n+aXbXZIMH1uO/p+Pl6LIPFon1gmwR/nT1Zq/7WYZkGNjUv6cnAUhCh ViJXi932t5OU2UeG30KvWicsXmB37jgUFjKRgRzPk4HDPcfufruZQWQnQ6qT Bnb0bzWW7erlbytAhotaEZP60pXYfYIPbVCIDHFtX/mY8c+wnAo/R83/yPCo 4n7KNVoFlvs7yFj2FBk49s3PVjQ9xfJ4Q3senSZDqObcvLs0irHwy3xnyPBM g+HS78Jy7EFM9Nk98mS4P7OQHaL0BHtYGPskCMjIr/Gm6V8uwwo64v+jKZOh Xe7SlL9hKVbIhuP6eAVdr5DsEJFYjBVlpa49NiaDVPDUxv4rj7DiV+nu/OZk 2CHYcrA6sRArGc+cJluSwaVKLTW7twArFb43FOxABsUq4RA9j4dYmeb9q/NO ZFjRu6xc9eYBVuaW227vSgbhSq3F2JMPsPLKhzXa3mSYe9IuU7mQh5UPFUo2 +5GhlGXTv8YyD3u68bhQLogMNeMTHD69uViFYlnG0Ug0P2O/jF9TDlbVVe2/ gCeDHKdfBa3oHlZNe05zIJMh7Jq4gcibLKyavc7xcxoZetRvChDn7mLPTV4Z v84ig+ye76oLV+5gz4Obes7mkEG3QpXJP+o29iL79eWSfDI8/dZ6V7EpE6ud bD+bVkQG7tP90526GVjd3o4nDGVk2DktgBPOTcfqRbv+C3tKhkmGyM9/VtOw Bo9eLsfnZMipv/XDuiIVa9z6uHaujQw4sembV+3IWP0fNQ2vt2TIu4YbbZwg Yc93VGUVd5GBPnvB5IsjCXtCT1Li7yeDiXJY/p0gIpa9/0oy3TeUP8e99PX4 FOwOS82I/AQZBKrDZE1bcFg62wkpv+9kuE5p0Hj6NxlL4dg58GOODAtC/iMT cUlYyJEX/N3rZPhEupj5uS8eC+D/z3PvNhn2lrlJdZ2Ox3wE0l4rIp8gv5Px p0JaHOZy3NPp2R4KOLEyx/PcjMXMxEUqMg9SoNSRl1VJKRozOpVB38dJgQdw p+dZYxSmJ7XbmImHAvtyz1hXqERhGrJjm6ECFDgvn9s2ox+JnZe/fclOggJ2 Z1J8+c+EY7LY3swsKQoEJ77s0XEMw6QUfWcHZJBPuWoiw3M/FBNWvUZQv0CB xeo831H+EIxbi+GTxGUKOJyOmZoyC8Q4dPzFHDUo8Eji0JuyqgCMTXcqNEeb AvpLEQEzHAHYXoMmwYMGFEjAqYvIfvPDVs0DXX9bUyDtJBvv+wIfbNFi+uVp ewrI1IWIfDjmg1GtDA+4OFKgVYuJzTrHG5uyO109cosC6Y7OCaWFXtgHl5m/ zUFof7LP98UPe2C9t4z1tkIpQGgefibt6YF1ubc+OBNJge0elbkn+zyw1965 Vx7FU4Cz+caz++FuWEWwKSUllQJDLa8apG+7YHxVi2MnMynwXEwv4u6QM5ZA TZZqvEuBw9Ovvt7jdcasbF6+W8yjwKfTq01Nz5yw/ZeF9pk8pcDLGDMch8AN zD+i3mihkgKGFtKa7+IcsPEXhg+TnlNgx0XdrO8L9tgL8QTlhlfoPDm/q1d9 sMNusP8KEeymwMZS4aD+WxvsvWZcZ917Chw1PXH7zlUbTD72KI/hAAXesj2V 1v1kjR38fa0mfpgCNRObVoq/rLDGkeqFuVkKxCZmfTcouY6Jc+kqxlEpEC9w Rclz1hzL0J3BH12kwLLWN9llCXPM7TWvuN46Bb58/WyX0mKK8T6OuFGzNxVs w7clZ8SMsbjxw1W6TKnAXcpdz0IywhZ5n9HNsqTCgxALK/8NQ+wNfirnCGcq BIYdckr9ZID5+Wh8iTyeCg+Pr802t+phY6UTIrzCqXBgVq3h1RU9TGs6JKBS LBVmpkxpvO+vYUJmTw5NS6dCe77UQ+KMLtYLHLpaSqlw32nW622oDnYxsDR7 SjUV3Lg6jPKqtbGCCrVfYeqpwNN1fWZgWQsLPRGY9PRqKjhplmZVRGhiokyj LZyWqSA2XrBHu08dS1P1P1hukwpBpwQObZ5Wx3aEsdlecUiFJQEj/rm0y9jQ vPLfYNdUSJx7ZcnnrIYpiw5rH/JIhUvOiQpCny9hZXa+WWXeqdCi9lZiTfsS dvgey8/L/qmQqW3FEdaqiv3f/4eH////8P8DveJPsQ== "]]}, Annotation[#, "Charting`Private`Tag$2743#7"]& ]}, {{}, {}}, {{ GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.5000500204077585}], Offset[{0, 0}, {0.020833332482993197`, 0.5000500204077585}], Offset[{0., 0.}, {0.021233332466666664`, 0.5000500204077585}], Offset[{0., 0.}, {0.021233332466666664`, 0.5000500204077585}], Offset[{0., 0.}, {0.021633332450340135`, 0.5000500204077585}], Offset[{0, 0}, {0.024033332352380952`, 0.6067145507846637}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.6067145507846637}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.6067145507846637}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.6067145507846637}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.5000500204077585}], Offset[{0, 0}, {0.020833332482993197`, 0.5000500204077585}], Offset[{0., 0.}, {0.021233332466666664`, 0.5000500204077585}], Offset[{0., 0.}, {0.021233332466666664`, 0.5000500204077585}], Offset[{0., 0.}, {0.021633332450340135`, 0.5000500204077585}], Offset[{0, 0}, {0.024033332352380952`, 0.6067145507846637}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.6067145507846637}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.6067145507846637}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.6067145507846637}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.6067145507846637}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.6067145507846637}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.6067145507846637}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.6067145507846637}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=1\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.6067145507846637}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.10001557722780403`}], Offset[{0, 0}, {0.020833332482993197`, 0.10001557722780403`}], Offset[{0., 0.}, {0.021233332466666664`, 0.10001557722780403`}], Offset[{0., 0.}, {0.021233332466666664`, 0.10001557722780403`}], Offset[{0., 0.}, {0.021633332450340135`, 0.10001557722780403`}], Offset[{0, 0}, {0.024033332352380952`, 0.5047927282048853}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.5047927282048853}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.5047927282048853}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.5047927282048853}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.10001557722780403`}], Offset[{0, 0}, {0.020833332482993197`, 0.10001557722780403`}], Offset[{0., 0.}, {0.021233332466666664`, 0.10001557722780403`}], Offset[{0., 0.}, {0.021233332466666664`, 0.10001557722780403`}], Offset[{0., 0.}, {0.021633332450340135`, 0.10001557722780403`}], Offset[{0, 0}, {0.024033332352380952`, 0.5047927282048853}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.5047927282048853}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.5047927282048853}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.5047927282048853}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.5047927282048853}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.5047927282048853}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.5047927282048853}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.5047927282048853}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=3\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.5047927282048853}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.0056296769096873325`}], Offset[{0, 0}, {0.020833332482993197`, 0.0056296769096873325`}], Offset[{0., 0.}, {0.021233332466666664`, 0.0056296769096873325`}], Offset[{0., 0.}, {0.021233332466666664`, 0.0056296769096873325`}], Offset[{0., 0.}, {0.021633332450340135`, 0.0056296769096873325`}], Offset[{0, 0}, {0.024033332352380952`, 0.4029065603667774}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.4029065603667774}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.4029065603667774}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.4029065603667774}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.0056296769096873325`}], Offset[{0, 0}, {0.020833332482993197`, 0.0056296769096873325`}], Offset[{0., 0.}, {0.021233332466666664`, 0.0056296769096873325`}], Offset[{0., 0.}, {0.021233332466666664`, 0.0056296769096873325`}], Offset[{0., 0.}, {0.021633332450340135`, 0.0056296769096873325`}], Offset[{0, 0}, {0.024033332352380952`, 0.4029065603667774}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.4029065603667774}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.4029065603667774}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.4029065603667774}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.4029065603667774}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.4029065603667774}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.4029065603667774}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.4029065603667774}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=5\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.4029065603667774}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.00022487153483115893`}], Offset[{0, 0}, {0.020833332482993197`, 0.00022487153483115893`}], Offset[{0., 0.}, {0.021233332466666664`, 0.00022487153483115893`}], Offset[{0., 0.}, {0.021233332466666664`, 0.00022487153483115893`}], Offset[{0., 0.}, {0.021633332450340135`, 0.00022487153483115893`}], Offset[{0, 0}, {0.024033332352380952`, 0.30102497717142807`}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.30102497717142807`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.30102497717142807`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.30102497717142807`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.00022487153483115893`}], Offset[{0, 0}, {0.020833332482993197`, 0.00022487153483115893`}], Offset[{0., 0.}, {0.021233332466666664`, 0.00022487153483115893`}], Offset[{0., 0.}, {0.021233332466666664`, 0.00022487153483115893`}], Offset[{0., 0.}, {0.021633332450340135`, 0.00022487153483115893`}], Offset[{0, 0}, {0.024033332352380952`, 0.30102497717142807`}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.30102497717142807`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.30102497717142807`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.30102497717142807`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.30102497717142807`}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.30102497717142807`}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.30102497717142807`}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.30102497717142807`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=7\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.30102497717142807}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 8.118196929703124*^-6}], Offset[{0, 0}, {0.020833332482993197`, 8.118196929703124*^-6}], Offset[{0., 0.}, {0.021233332466666664`, 8.118196929703124*^-6}], Offset[{0., 0.}, {0.021233332466666664`, 8.118196929703124*^-6}], Offset[{0., 0.}, {0.021633332450340135`, 8.118196929703124*^-6}], Offset[{0, 0}, {0.024033332352380952`, 0.19914478765583804`}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.19914478765583804`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.19914478765583804`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.19914478765583804`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 8.118196929703124*^-6}], Offset[{0, 0}, {0.020833332482993197`, 8.118196929703124*^-6}], Offset[{0., 0.}, {0.021233332466666664`, 8.118196929703124*^-6}], Offset[{0., 0.}, {0.021233332466666664`, 8.118196929703124*^-6}], Offset[{0., 0.}, {0.021633332450340135`, 8.118196929703124*^-6}], Offset[{0, 0}, {0.024033332352380952`, 0.19914478765583804`}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.19914478765583804`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.19914478765583804`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.19914478765583804`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.19914478765583804`}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.19914478765583804`}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.19914478765583804`}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.19914478765583804`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=9\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.19914478765583804}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 2.8009879594166*^-7}], Offset[{0, 0}, {0.020833332482993197`, 2.8009879594166*^-7}], Offset[{0., 0.}, {0.021233332466666664`, 2.8009879594166*^-7}], Offset[{0., 0.}, {0.021233332466666664`, 2.8009879594166*^-7}], Offset[{0., 0.}, {0.021633332450340135`, 2.8009879594166*^-7}], Offset[{0, 0}, {0.024033332352380952`, 0.09726518017467915}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.09726518017467915}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.09726518017467915}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.09726518017467915}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 2.8009879594166*^-7}], Offset[{0, 0}, {0.020833332482993197`, 2.8009879594166*^-7}], Offset[{0., 0.}, {0.021233332466666664`, 2.8009879594166*^-7}], Offset[{0., 0.}, {0.021233332466666664`, 2.8009879594166*^-7}], Offset[{0., 0.}, {0.021633332450340135`, 2.8009879594166*^-7}], Offset[{0, 0}, {0.024033332352380952`, 0.09726518017467915}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.09726518017467915}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.09726518017467915}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.09726518017467915}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{43., 7.00000000000001}, {0.024033332352380952`, 0.09726518017467915}], Offset[{43., -6.99999999999999}, {0.024033332352380952`, 0.09726518017467915}], Offset[{10., -6.999999999999997}, {0.024033332352380952`, 0.09726518017467915}], Offset[{10., 7.000000000000003}, {0.024033332352380952`, 0.09726518017467915}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=11\"\>", BoxRotation->0.], Offset[{26.5, 5.88418203051333*^-15}, \ {0.024033332352380952, 0.09726518017467915}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 9.430761575366949*^-9}], Offset[{0, 0}, {0.020833332482993197`, 9.430761575366949*^-9}], Offset[{0., 0.}, {0.021233332466666664`, 9.430761575366949*^-9}], Offset[{0., 0.}, {0.021233332466666664`, 9.430761575366949*^-9}], Offset[{0., 0.}, {0.021633332450340135`, 9.430761575366949*^-9}], Offset[{0, 0}, {0.024033332352380952`, -0.004614203040904809}], Offset[{5., 1.1102230246251565`*^-15}, { 0.024033332352380952`, -0.004614203040904809}], Offset[{10., 2.220446049250313*^-15}, { 0.024033332352380952`, -0.004614203040904809}], Offset[{10., 2.220446049250313*^-15}, { 0.024033332352380952`, -0.004614203040904809}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 9.430761575366949*^-9}], Offset[{0, 0}, {0.020833332482993197`, 9.430761575366949*^-9}], Offset[{0., 0.}, {0.021233332466666664`, 9.430761575366949*^-9}], Offset[{0., 0.}, {0.021233332466666664`, 9.430761575366949*^-9}], Offset[{0., 0.}, {0.021633332450340135`, 9.430761575366949*^-9}], Offset[{0, 0}, {0.024033332352380952`, -0.004614203040904809}], Offset[{5., 1.1102230246251565`*^-15}, { 0.024033332352380952`, -0.004614203040904809}], Offset[{10., 2.220446049250313*^-15}, { 0.024033332352380952`, -0.004614203040904809}], Offset[{10., 2.220446049250313*^-15}, { 0.024033332352380952`, -0.004614203040904809}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{43., 7.00000000000001}, { 0.024033332352380952`, -0.004614203040904809}], Offset[{43., -6.99999999999999}, { 0.024033332352380952`, -0.004614203040904809}], Offset[{10., -6.999999999999997}, { 0.024033332352380952`, -0.004614203040904809}], Offset[{10., 7.000000000000003}, { 0.024033332352380952`, -0.004614203040904809}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=13\"\>", BoxRotation->0.], Offset[{26.5, 5.88418203051333*^-15}, \ {0.024033332352380952, -0.004614203040904809}], {0, 0}]}]}, {}}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{True, True}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{False, False}, {False, False}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}, {Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->{{All, 75.80000000000001}, {All, All}}, Method->{ "DefaultBoundaryStyle" -> Automatic, "DefaultMeshStyle" -> AbsolutePointSize[6], "ScalingFunctions" -> None, "CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotRange->{All, All}, PlotRangeClipping->False, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]], "Output", CellChangeTimes->{ 3.8069103337157297`*^9, {3.80691270003312*^9, 3.8069127266070843`*^9}, { 3.80691286142306*^9, 3.806912975481896*^9}, {3.8069131647173634`*^9, 3.806913241142002*^9}, {3.806913352879383*^9, 3.8069133837912493`*^9}, 3.806983794607871*^9, 3.8133859167556763`*^9, 3.8133860326592216`*^9, { 3.8133861196960163`*^9, 3.813386139695586*^9}, 3.813387158804915*^9, { 3.8218537317546797`*^9, 3.821853746401569*^9}, 3.821853881016809*^9, 3.822022659937346*^9, 3.822022782239375*^9, 3.832037529863328*^9}, CellLabel->"Out[5]=",ExpressionUUID->"fe303ab2-60c7-4daf-93af-21f70cb22469"], Cell[BoxData[ GraphicsBox[{{{}, {}, TagBox[ {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJw113dUzf//APAUWqQiDZV2aYiEtJ4tpb1LS7cpmiIpaYi050WRtpIGItqv JGn6tFRWblPzvhMNDb4v5/x+f9xzz+O87z3n/Xq+Xs/xEnT2NXOjpaGh2cSf f983BopOjASTUWZo+KQHDQX2fK1ZKA4kI96GVd05WgoUjHUV+V8io/YqT3a/ bRRoXvjJsdWHjHpc1XuvMFFgG7PaopgTGXHwP9yZtIcCUTD02EuHjCJUpv3f S1Dg1iMG3tXdZHQ3jeFHuikFYoPP/WEpS0MhLkvm9gUUcBxHDXNdqYjE0bYs 6zACfkn842mbKYhpT1iDIesoaGye0Tc9nIL4eZ+7D7wdhbFD8uUN5snI1/JN PkvKGITpC8/NMCah3kjJjwctxuFDI/3FKt0ENLSnfP+C9AQ8qX1yrSIlDolk cYYrbp+EvwoeZrASgzKe29Cu9E3CvLoev7RiNKqWLUziq/wOpl3KL0ruRaGd j9NlP9+aghPDi13WdDdRyd3E4SuW09AQ3DvsohuJxPtnzFIPz0BNRlM1bVkE 0rctihFfm4Gi6CpOui9hKJ0raW2+YxYoU/5vbHxCUBiaLIlImoPtRkZ0A0pB qMcwX/K44jycbQ85zN4cgGqiJj/Mjs1DpX7nz4u3/NGpP4/kHS9QgWsgMdgr yB+t3/jbmnmRCsEk0y1unv7IVOPan6EAKqgGDLBYGfujMBVFPcNgKrRkUQ4o cPqjlpFPpqKRVBj68ctxo/ACupWfE5dKpsLaXb7OGy1+KJr+FL3DSyqEtH49 JcXsg/TGAlgSl6iQzpHNn014oxUHCWb3FSpUOpN+sfd7ow4RpUTl31Sgboxm r2V6o/Cd6qITG1QgHZ5abjvojR7f5LglspUArXuLBR5mXmi+1OiBHTsBO7zo txRmnEdPjBs0imQIkKhuHeAOPY8u5qasGckScHJ7bGmC83lEbHqKLx0iIDRn x+kAqfMolEloWFmegIV+tida9efQFkn5Z9WKBPSr8DqMUTyQbJ54iIcOAZm7 DlcLSJxFN9vmpe86EkBxTav1ZjmLLPK84n+SCBCpWaqv+eWO9n0JiTJyJqDU tabJ4rU7inzUfYrGjYDaas3OaFt3JFj7bt3sPAGfXKy+LcS7oc8dOq0vLhHA XXV12+sfLmjJ1uPK2WgC7HcO07MMuaD13NqAOzEE5DirMdk1uCAmAyXa5li8 vp3bdi3FuiARNu93PAkEKDgnch0Qwf8fIv1+mULA6R25UilWzog5bq6i+B4B d0gtpk61JFS9Xq5/uYQAstF98xvZJGT8hnZPfCkBqcp+lkWRJDS3ybU/p4yA BC4em3l9Etquw7XR9IQAhtzPjYtVjuh2k+O7n88JGA+XHBZad0A7IsssttTh eNj3j3i8cUDnLP7jX8f+rBA6UR7ngOikxcV+1hPQu9Azp8jrgLjeSc5+RQQ0 koLWzVTs0fDpyyez3hDwQK2VKzLMFlmWZv9qaycgndeft03HFvXkMXoVdeD3 Xd0nsIvVFmnSPtkX2UlA/FNf8fs5Noj9UoTQ0fcEBAtwHnv++jQqoFFqiewh wIrG3XyMzhpZHikQ7xgkgKWRLlEz2hzpm0aF0ozh+JQSM0oW5qhHouBhBnZe +mcdeQFzVLBurHB4nIDjF55vEa0yQ9qR2dl2EwSQhFwCtk+ZIroVtQsPvhPw /EaTfZuOCXonr7/eP0vAH7/y6te7TdC+cfZ3FnMEJNfIy1xCxijdsGO9F7va czzHkjBCTryXs9vn8Xl9rxnNZWyIeA3LOwoJAp6l0lpnseghwmc1nf0nAdqe n1iTCnWRRuuOsSvYnzQr2sNUsf3n0r5ib11yUnXyOYV47VIP5P3C67V+LSry Xhtx7dQX5FomYFY249sed210NDQs6wJ2OMOFjG1/TiJ+1nsRbdjF1QI7v8uc RJ7te4MurRCwsS/8V3GCJtLY6i75ahW//y/r8nuimkjJfLOP7jcBol2yHnH1 GihO4fmoEbZR6LfPXvPqSMVJWJaCnUtRfSNrqIYUT1ZGEGsEePrLrKm1A3qQ MGkqu473T/irt9CaKiJISVHe2N9vKltO2Kgglp8bvBPY8Xrrwp7cioi3zXqj cYOAwIb4j86GJ9AYo8ziIrazHH+SbYQCEm1asRPexOedR31Nd/oYGiw+GheG LZzY+0Sd7xjiiUg0KcFmoXV1O2F6FM32FsZ8wB6fjuqWqD6CHkp/txL9Q8B/ DlxRAvNyCCZWZvSwa3qKlbgE5VDGi4xFH+zk6s5C+phDiFP0nH0F9rJtXdWf IFl0/UhkQw92l8Y3YeqIDHIMoicT2MHsomudzyRR6n3pDLG/BJis6bjVcR9A B3LrWwFbbPR8d0mEONptk+Fpjb3RlqB0f1oUWQtWRXhj9z57WhhrKoLyLfcw X8d+lNHHFlwthK79V0R/Gzs0YjnknKAgMp31Ciz897xXrvsZ+37ErXXG9iW2 Zd6VwuTRfYjmb+DTZuwt/g0hvhVcKIaxMqgHu0x9q7nRdQ7kVcP+8gu2DZve ARkzdqRxJ95tEpu5af9fTi0W9JYiEE3FdnUqKfkwRo/YDDv5lrDraI6fTovc gnKHE8TWsCXUbjLmaS83CNxwydvEfrqp8FZxx1hD1DGDlL//fr/bWUixr001 nfbUz39OpD8/MLhEqNLKWrX+wd77li/Vr3ZDNZMrkHUD+4hmZOZa/VaQWi3p WMH+lL9CKPMzw1L60u8f2Oq0L3MBscLxUsv7M9i35fw6SMRuuLnw/skI9rSz 5FLEfk6o3+NyfBBbOW2cP9+YB3Yp7JXrwE5+k3WqOYwP5DJnsuuxF4Okqxet BaB6fTy8HJs3ldGIbkEQsj4xfniArf14cnR3tDAwFjpkxmH7Nb0JFBEQhVf5 EwOB2M2L13JPmkiAZv3jh/rYVCa7Y1ZTByCV9deJI9hcwgod7uFSEDodp86N 7WW++OvW04OgN/LmMQWfl47K71oGIoegw/zSjiZsirpVksXCIfh2mTySi81k e0TELVoOzOa1J+2x90/m+nhbHIFg/3kOBWx5f9bqAAF5SBCVqmbDPhM7bxhV dRQEL6fbNuLz/qymKLBoSgFm9iczMWOvhke0/H17Ar4knMn4gPNJVceO43S+ IlSI81llYbf3sTxnOKMM3WWVNpLYo3MB1HN9AAfCEuKk/+XvxyJ+p9NqcL91 Z/wUzu9XdXu0d75Tg/a/YrV52JvXqWS3AnXwo7/+kA07Zlee3F5HTSjOe1D2 EdeT0kUW26YuTbBgzBa9hd394WqEj7IWvDJm6JLD3ptp2d3CfRJeMEU/voHr UZ4Eo09gvzb4ckbls+N6VaPuVzykqwdFPyaLBxcJ+CrytftGlR4YqmmIe2DT MOitHhLXh2+r+waWf+D9ey+sE7PVABbOTrSyYPfZDo6fQIbAxCdLfwDX2+UT +5MN75mA5Wo8Mz2u39ElH/Lze0xgm/XxF8EzuB/zxb/6zWAKnfVsKXPT+DzR /B5+GGgK96K5p9qnCLje0ivzx8IMjrkMs/pP4npjHtVRvssC1Iwyg8+PEGD6 Yu2mmaYFMHd5DHRScPw4fNWWL1vAqGJegQw295B1pcqwBVhEc2fMDOP5weFA dmepJeQ8svxu+oUAxbOd/jO61uBOnNEaGCDA7So7j9gNW4jPqvN/hfvjoy9R /W2vbIHeJCtsqo2AGZX1RO9ZWzgYXrCNC9uPZpyu0swOPB+yhfq/w/XpZuW8 pqA9lMcfEedoxvmQdPq1U4MDMFI4Utlwfx42NX5hFEICF7PzmVO4/7dM703V SydBXOfF/j48H5RFDPtqvyDBEoe+fj2eH0KeeUupzpHg2p1Py7HFBPCwxefJ 2DvB4uxvY7aHuB91tybvUHaGty2Dju33CXhvpOHdvu4CG3ZeaOEWAS8nGfVb OF1hx2ZfakEU7v+hPRJNR1zhNsf3Z1Y3cb6Uk8arPV1Bp+J9f+V1nA8sYXbF n12B/e9ateM1vL9dtbrRtW6wpifr7uxPANI/KqZ99SwIKEVGitnh/lTSqITu nAWDqoD6Ehu8PiYDU4WKs3DQV9VJ9vS/+uscIjl9Fszj5acOW+J4n0ruZbH2 AFurvzQixgS80JoNHZQ7Bz2j/7XVaeB4q+QOesycByM5knSzBAEpsjtj4mx8 wIA6JKqzQIXVqJULUhd9IDq3dCKWiufV4RHbjngfYBrjceqao8KhhJfSzI0+ UGaeHW80TYXuGcfuWDFfSHZRfKM+SgXWwgrO2J++4O2tyDnXRwUdFmnz5hY/ qD24q8Qcz89vb/SMNJH8QdHywbuYQCrcsm1jpfkUAGuKhR9/fJsHe6mcEk6u IBCf4Pchqc+D5A9CdeBkCAyx3W5WSZ+Duuy5sf6qMAg/9lx6o28Wnoq4rlld iQB7bc1Ky92zMOH9KG7sWCQ4S1ReeqI4A/nyX8y+Dt6AuquSY/qe0zAcYHDn sV8U3O7wiBF8MAVXpdJGOaWjQXHid4p63XfIO9PmutgWAw2S3/zez0yC1PYB wis2Dga+3+v7yDgJhyX2r9RoJEDxelyq3aEJaHxnLX/5ayIsRaT/8j83Dh+9 j9R7GCaDrXVl3dKdMbj7Um7dgC8FJATERqiDo5CmbLLCM50CtL89upSFRqFx Y2hFoSUVmHlC7la4jEDFVZu0BHIaXNscoBhUUYCvcnFELD0NLgwUdDlUUiCa Gneo8X4aGIUJK/hW4PugU0PXYl4ajK0bRKWVUmCHjjDD6WdpAPnr9KM5FHBn nw8Rep8G/5W9fXgnhgL7isPdX9GTwXPI0PuMHb5/jnJXmjCTofDZBZ6w0xRY 3PecboaFDIyJX07mWFKgNXEih3cvGXzLUjnHjSlw+ZLe5wgRMhhadhVe0KJA N+wxMVAnQ/SluMu4IIBSUFnWhBYZkl+eYuySpEBhhfZ86CkytAn58SyLU+Ca aFDsM2MyMJjQVekKUUCSebh57xn83MOWsryXAre1Anc/dSKD1+NYd2F8P6YJ ZXXWdSODTbKMpwkbBQYXNP5e9SKDnl0XUcJMAQ3JL4YcfmTQle/w/cRAgXKX gMzyi2TIvKPiw7idAtwPWGZ1Asngmikyq0BHgf+7v8P/39//B5T5LbQ= "]]}, Annotation[#, "Charting`Private`Tag$12701#1"]& ], TagBox[ {RGBColor[0.880722, 0.611041, 0.142051], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJw123c81W/YB3ChzCQUSRIalC0/IRcZ2VnZZUSyOfY+tuxVSYrsbLKV21ZJ RnYiUrZTaGl4bs/ref7yer++x3Hc3/u+rutzDiesXHRtyMnIyFwoyMh2v4aP Fl6Y9UtDF7cmoj4cLwGW901fnninoUfuJxMopUsg72NfIcEjDXloGqRcNiiB zi+bhyid05DS8/NCZ+NLYC+d3MYpyzR0FxH3OP0pgUgYL3a8nIYuUyh//Puh FKKKqDl+MqehD0M3eL06yoGt4ujbVsY0RFNzo+LFXDkU1QrG3N6fhhSM6QlA XgEv2vV/slOloQXuWb0M+Qqgfp89fHE7FSlYjMbRtldA9MEL8WEfUtHYsZej /6wrIcbP7h9DWSpK/ss+2+pfBSLD9p4pT1LRaUm5DKvEKhgXcFw9VJCKCmJ+ SxzLrYLTs86THFmpKMPQI+f9qyrovOxRx5+civINRf8lHK2GHZZgZ2XPVNRo nqo01FYNHhVp04EXU5FlnX3OOHcNcNDcvbpHKhUxq463vbtQAx1W916HS6Qi 0liO0R/tGmA6nNEUK5SKCAZJsXeDa6AiIOvu/ROpqO/kASex6RpYVi3Wqt2b iubC9m2LPq4F83nUstqXgsj+ac8ToB7oza+alrxKQe8yaR8VG9VDw8TyD7ue FEQKVKwhI9QDY/8hkYXWFGT1OCGeOr8e2hsdcmefpiCnXHmuWPoG4E1kjR69 n4J64vvrA2cbYPGCi06rTQqy4atgEclrgrQayvUgqxSkwdU8RmxrAjmhjJiL 5ilojImLcmu6Ce7zdnU0GaUg2lQqZSX2ZlA7cFSiVj0FFXNziKWnNEPpfDd7 sUgKcpu7bXcq5hm4JnLOp/5NRuYbIvt47rbA6eTmCavtZFR7fzEgtr4FplOM +kV+JKMwmsGgoxMtoHk3pan/SzIa9pl+V82BgP/hvmS6+WQkzficujMfwXzx +sWwV/j5/GQTXpu3gnF3yz3CvWS0EljYVH67DRhfmMbLpyUjq42XcTQP2+DF y5+hjMnJKDvy0mn/yjaQ6BN1Lo9JRoVPlNlzx9qAZbhAcTkwGZG0BxD16XZ4 M5vw1dI6GVX0jXnLv2qHS3+vq+uIJCN//SLR4zydwKi7TPZOIBmNFxw1d5Tu hJkCzzpr/mRk4YQkxvU6IUA77oQPTzJq3yxyo4/ohLrcxh+PDiWj3uiYmeXF TuBXY8lb/ZWEWDmHDj6q6wKmey//RLUnoZePJePe2vfAhxX96oMoCVWc/jZ0 IaoHKuQ+2D5oTkK3b8ic6cjtAY3l70PlNUmIu3whFt73QORF3icjBUkI6B4f +qjzArY/Bl3liU1CvBB0YEv+JXwUFi9v0UtCLeLeZqKyvVBXoHc7TDsJcZ35 7y71tV6I4XC3VtFMQt26esf3BPSCMHU1+5ByEvpCSYgzbuqFoBmhqE8XkvD6 rXcXS74G9oSzFvRcScgVvtJ+lu6DnFEl3prxRJRvPdblfq0fVNvDJy8OJaL3 VyX8u4n98KWsI6mnNxFVz/oVy+b1g2yE/N/JlkRE8VNxMGulHybELo7uyU9E 018PjTHLDgBjsnj0FbdE5PRPREh4aACC1XlWl2kSkdS9k8I71EOg/16We5k8 EYVsePN3cA4Bv4uJ0dLvBHRDYur2I/EhGE5J7lxYS0C3+PY/eGCBr0/uZM4P JqBmO/YvFY34+q0pzen7CYjWj+ftZde3wB95p2KQLwFZ2W/uMyYNw0grlXuD ajxyPHn2Ed35cWi1EDUdvxSPxDdmyqW1x6GU7JrCT+l4dE/n8FaIwziEylUz SwrGowXN9TntnHEQbjWrqWeKRxlSy4XfGScgDlV9q3sXh7hOhs3rbkzApRZT n1qnOMQTW6zxrPMdVDRXBFYnx6Itzm5dspwZ2JG8pQs/bqOApIORgeUfYU1e jfOcVDS60vj57sbYArDT53CUi0UjdSbq/JLPC6Ay+otdWCAa1W28qTb9tgB5 9k9Yxbmi0be9NXrZTItgkkp9UGZfNFr8JWXZoLEI3fPdFBpDUYjqydIPGrQI WVEKSw72UWjOgk7J9cESvNZ5sLB2IwotFNxkGCpagu2jm59crkWhYiM+59N1 S2BQmTPnrh2FKuxfp5YOLAH9xJ4pf4koVM3I+PvY3mXw4W99E0sehYbkzRRi HJZBp0+mpiQjEvmBXzSZ4Aqk5edaa6VFIs0NsQHChRUYD6Q99DU+Em3bSSyO Kq6AheC4p0RIJBKRnbnqYboCzonu/7XZRiJ5haeD5NErEKtT3DQqHon852vT radXoGuEtW1PfwTadvEt/Bu8CtTlQW55LyKQDOOPkbu3V0Ej8tOJy+0RKPZd Xh9X6ioMSzwNjauNQBSrBXRUBaswd09LkTUzAhlIq/hw9K7CjnFEzzm7CLTw fKnGjmkNLkxv9BlSRKCPnwTMku+sQamZxD+XP+Goz1YkYOnhGnC+8xWM/haO 3NpeTwgVrAH5OFliw0I4uktubRdVtwavBhm0j7wORy1zzOVWo2tg0sU/NJkW jhp+pHoPMq3DawVn8s34cKTST250kH0dZNurROmiwhHvL3EauRPrwI0kU6V9 w1GTJNN+e6F1WGlQ1s+8Fo62HstufVVbh4BSq9Frp8LR6clLi1NB67DOX7DP 63g4gk25xQMR62DxZEkigS0cdZm0pIrGroNigeu9Flr8+gfkzl2+tw702UFG x0lhaPBIwJmK8nV4mJox+aE+DKWaXTt+e3IdGJmmaX9VhiE1EktBy8w6hCad kD5YHIaUPjmszM+vw834ogfymWGoz3PpDwVpHQSj6sxyiGHI9PWQdgI5CVr8 hqZvqIYhoYOiM/OnSCAlLWuycSkMBT88of+ZnwR1v5+MEGXCUPq1iZR3giQo Dwh5/VAoDH3f4a96LEGCR0HCTWOHwtBjPiOtR0okCAxNuKM+F4q4v+rw3bIk wc9L24yT70LRKMeKSrk1CTwobsbdGglFkU7rl5dsSeAYfjEs4kUoqiu9cVbW mQRmkauuqDwUcW3eD7DxI4FMjJqGmH8oEo8r2duURIIGtbqeNo9QdGp7Kdwg lQTidNwK2s6hKKiljWLpDgnOxf264GQZioYz51S+ZJCAI6HodOHlUBSP1tdu 55EgXYsl97x8KPrmM35zvIAELAeInJ1SoWh9qcv12BMS0CcZHpoVCEWbolbE 2DIS/E7eR3GUJRTdeDUc86uWBF66hKAn+0MRcUUs+l89CTaYpn/9RxWK3tpX Fm43kmA5tfaL/nYIytwre2f8OQkm71hPJ3wIQZP92jwCXSRout/eSF4Wgt60 zjSpDJHAmoyudl9BCIp5pce5+JYEB2z1KmmzQpD5oNutoBF8XXy+gCk5BClz n6dNGifB/v69adyeIaiBILqpOo3X47xW4innEHTE5fnvnBkSWGXejeG3DUHC 5U6Zmx/w/bM7HSJqHILuhj3/6/+RBBaUqs6XLoag6/p12WcXSUDrkGynLBGC hAw8exWWSFA7OGGtJhSCjvr6S+sv4+tZ9qa6J0LQxBhB7voqCWr2PjUwYA9B XvdadwzXSGDu+FvHhDkE0YXSGqut4+sX4lSs9oag80dNBI58IcH17GGFm/+I SCiEYegbNg3VMbD/QURnHh217v2Krw+XnScsEZGKa06O5SYJqFz6uUP7iOjD jXNdMt9JUD3CyhnZTUT3BX8zfsQ2k7E4EoOI6EtD4mroDxJU0nw9kFJFROSz rjkVP0lg4nqB7m4xEfm0SuTJ/CLB3rGQfRm5RMRVXRnegW2Sx/T38R0iSmfJ EkLbJKCkM/2Zn0BE5yXauMR/k6DCLXfzSRQRUVBvXMzFNhlfWS8jElElm2oG /R/8eBBfrvIlolP8bSqu2OX5AZ9qCUS0X0/W7A22EX3Xh0YHIvq0E75w6i8J yiaujrVdIyJTSprKHmwjuUdDXQZE5JejwcT4jwTkhZ/7Xl4hoikdBwk97NL9 Qi/7VIjoF2+RYDK2gYd356A8EcX5cO9/hU32DqERKSIqer/08S92iTx184QY EdluLnSe28GPL9Kue3+OiB582mozwCY7cL9q9iQRdbS1r/pjF3vOln7iJKLj TGsGmdhXp/iKlliJiH/8x8GG3ccrEHLXGIno3SUFof7dxz9pevSVhoioGdla Z7H1GSkyvpETUSdF1ggJ+9/aXf7NH8GImmuF+Atbt/n0id9Lwei/lrWhf9iF 0Q2sFFPBSNYxaGoH+wzBlqDxJhidrhzs/oNdZHq4705rMPo6p1z5DZtPqev0 THUwMhsOKFre/fmCHqFn8oORkMf3lnfYZ9l43rvdC0aGPCcoXmKX7hn6r/l2 MDpAph5ejS2wQkyhDAhG5s8KdNKxy4eF1jSdg9F6krafH7ZQy/TlexbBSDVU Zb8xdmVhfM4H3WBkEO9+RBxbJFnmL59SMKpTe1hGh13tt2Lo/l8wmn3jOT6D 11vMOqP6GV8wupyfXFSJXaOpun8fRzCyoXQ4F4Rdx1XYnk4WjFhT26MPYP9H a3BsbiMIPbepDHyL73/DJqXP2U9BaIsczNOwm7qtBFpeBiH1L7+P78eWrjwY TfUsCIV5drN34f307H7rnHZ5ENrMs7/gh/3ckTP9Y0oQkue8yjaF96esQd/G uYgglGpnvRmN3QIBml7eQWgm/P1pMexWpklyGrMg1Pc3eDAY7/fOhjtOgieD 0M2SnqTf+Lwo5Si+8GYNQg+kBB6nYXfHbnK30QQhQxtht7PYL67rjOutByIS lXSILj5vvZT7FXzrA5F5y9jTqG8kGNIOZ+tUDUTcPmk56fg860mJue+XCUSL YzelmLGHeeb6DAQDkXzJe7U4fP5Hv0PYElMgCrsTTOZHIsFE5u81hqkAlKDY Na+I68mHRUKHsXMAKqviIzzG9cnDgFCTaBmA0scPPGfCpul0y+/SD0AfotRk wxZIIJrlGiUiHYAuFSbtsfpMgoirzuo01AEo1MXTiHWeBPztdm8bHvujcJXf Xra4Pro/sPjIOuKHzv/n59WL6ys1jcWw5gs/NFBw4JkwdqaXeVdYsx9S7TPb d3cYr4fO9ULSYz80Wl3VYoHrMxu1mUOPsx/6SJzS+TGA74+H4aYXtR/Sr1p1 EnhNgn1aWhSj0r7oyIzM7Pt23P+oqLa+C/iiJi27D3LYS21onpXLF/09Pp2Y 10aC1+dFuo0pfVGuBReTcysJUo6x3H7/2gdJ/U07QdtCAs61CYZP13zQGsV/ XPa4vzAWpuzs1fZBMX0N/JMNJNhjqf7l1CUf9Lyk7LQ69vzws8Fbp3xQ0gZQ CeP+VPwsK2113Rs9XiU834v7l0ScDftWsDcS/8439rESn0dlTrpDBG+kG8py xxr7CNnY7/PW3miCJ9X7cwUJ/rirvPdW8UavS4dq1spJ0G56Nvs3ozeiW+gx oMX9Uevs15MUOV6I2r9DNgj3T7lPTw7zpnmhf9S3rJmwRbKsqJQivdDvFaeh wiLcb5mHFyPtvVBI0bOE0ULcH7frSmjFvNBEf229Au7Htq8CRJg6PdGzerJj 13PxfEAd2XC83hPZ+fjCfmyCciIIFHsigSS6tOc5JAhof6ypkuSJuv99Hj2B ndTUbRdk5onCKvwmfmaT4M7P/i+xVzxRTTNZbhV2hsSE9/1LnijT6V6eA3Z+ 9UpEzRlPdPW1se7HLHweixlzlrc8UFQuve3sIxKgxSN8Pxc8ENK5QJaH3XmK p3LvOw+0GWA3Yovdn3O+havNA9EJy5/ffIjXP8Nk0iDeA93r+DvEhr00fsPS muiB2Hob9T9lkmD9sNOim7sHEsiNY3mK/Ssl+HucsQeynF3W0sVmiM1j6jjp gRJqIyuzHpCA+WXZ/QE2D1QtSXXSC5uNqp5rms4DdV35NKaJzRP2UvDXV3ek M2Xykwz7TNtQ7b5P7kh1rcZmCs8/gjvvZFjG3dHMmXXGRmxJ/3U1oRZ3VDMo zeWFfbHxx6BMlTuy+TkVZoB96QeZsVqeOxpx8uWVxNZ0Z7a1iXFHAXV+R3fu 4/pexbFOCHRHaVRSbvPYRqSTnkRXd9TrW0zei23lIBn2wMAdPS5hH3uAbftE nvaJqjsyeaxwJBLbcUEtuU7GHan3eN5xwyac1GfrFHJHTqT/1K9je9+4ljXI 7Y5ybemkNLADHt88NXPIHbmbO1hKY4fOuJStUrujEz19rWexo475im//JqA9 bnmGx7DjTEObqUgElJRieJIRO/l+7KVDcwR0xU6DjxL77ljaS+4RAko//tHq VzoJHhx6pC38goDWOTwHSdjZeoVjF5sJ6Px9Q48F7Pzkyuvq5QQUmjGh9gG7 uL/xk9FjArJcV9SfxK7c3+F4M42Ahq98SBzBrlV/vekeRUCv5z//GcRmG03w c/QlIN1FE89+bD8LnT02DgSkeDhE9w321DJz9LVrBDRRqJ26a1nPUQaDKwQE EU0SA7uvZyf9jpY8AZ1jypd+i00eY8pxWYyA/hV/zx7DtmbhzIWTBLQWEGHz Hrv70Qc+SVYCkhM+Gz2PfYYvt1KYhoBYlqup1rBjntr8x/fbDcU//Tz3HXv1 4pmWE2tu6M50BBs5Xp8rL5YV2Wfc0PkSzUIG7Grdsl6mQTdUlfElngOb5b2L Ll2HG2osPNa7u/7jX7fM/xS4oX17qhW0sKUC6j9vpbuhmkXDAEvszH1+Tmsx bujkOuU+L2yLozt+085uqOFAyb5c7Pb8tj1jFm5ovbzWrxmbVzg8ul/XDSnV zl8YwV5SpLnbKuGGWqTiUunxftTo7+VoPOOGNriX+Pmxy40TcqvY3ZDh1XNU qtgEZ+aqnH+uSO/GelQM9va9Y6/Du13RzfxFfw58Psy4P+gGNrgi46Qz9IrY LaU5E57FruiT4OhbR+zQttMLNxNcUQ2LEXk7Nt2KCLmqgSuiUD3yxA+fT2fP rWh5FVc0HUzWXoI9sFN3QErKFRGqMimmsdNYZI6d5XRFypOXfinh8y8ZEOfK /toF2VpaePPgevEn6WAQXaULEjx4Pusadmv+3dg/qS7Ih25xJh1btT+7YNrU BZ1yrMplwvXIhLt2KmfFGW35WGwz4XoV8OK9ylk6Z2S7cJ1SCde79ENZnFkk J7TQzXAtAbvWymKLadgJ2aQJ5I5jr/+Zy9rOdEKly8dILrh+Wogsfn8p6IQ2 a7pUnuA8pJixkXdL1xF9/nuLSQnXY3pHqj0F9+0RX9/XX4y4vp9pfDF6JMge tbSx5bpjK+2LKY23skdC/UxfRrGDsumNPM/aozLvTocs3B++DB+sUHxuh8wy pvL/w/1k+CLHtY8fbiHyOYt/oU/xfjgg0sh1xhb5s2iNuTfhfm+d2uzEYItk No+ETmPzNn173rR1E8naaXipNuP5zrqpXb/tJrI5XiXK9YwEzY0Kr6NNbiKB /763DezmqxsGM1/ibFB9SamzDO6nRxr897Z9vYE4KhNLhF7g827RrWPZbIHm iIpVLKP4/mg90AvPskCBGpLLMdgpMq5XC8Ms0BuDnTmyMRLEs7Ebr6lboLIl L9pVbOrH71o3GszRNYep9ZYJXN+J/NPcv6+hQ4Oz5Fffk+Ch3Au2sGATRMF3 N1wUzxvpHASOl5dNkPnXaOVM7LSfR7kOMJogyZPNxL2fcH2qdDn9INsYVSjk Xx3F9uNilXjaZoQIP5GKG55nDMhu6n2kMES0uYrpMTh/MbRSJChE6yH2yajq i3h+MiolLUvr66EglyTueOyc9HeXxbn00HMHtPgO+z+3p3tONugiSj4Dgjee vyy4b3juW9RB169aGxRskOBpeLvZy8vaqPLKUY25LTy/u5Y3tjFrI7sTfVGn vu32T3EBD3QF2ZKx77PHbnSYz75K0kIsUQzd69j0bxSi2a5oojzCljgJ57Gq FHLDRwxqSLqb/PMrPC8qO0wyJhaoIvvowtfkOG9NKlS/CpZVRZGlGZ8uYFN+ s5S1dFZBteq9xfnYBoZtJ3nfKCN//w927ng+XRG6P8NyUxnZKRu+ysMmUrvd 3/tPCWVTgMEI9pNGrv0LAkro1qzY2u58++cocetJvALyIJcnX8BO2jIszzip gAhxtUUH8bx8sk/oVuzzS+jG0Yce0thaQTPvHNfk0brbYb847McfZDuENOXQ ctx1Pl48fzsQBLblXgG6Wcy5dBk7jee9E/e2LNKfkXtpj70QIXP1k/FFFHzB drEMO07tN4/DESn097FAKh+e971b4iasNC+gIabnDUrYVqKciSYhkugOqw2F JbYku/y26pIEsr2puu8ONk/CUIX8MQnE1lz7vAybgdza5oLOecQVei+9C3t+ KXLgTKMY4k9RrN/A7r/GFsm1JoqGpEy2qXA+aRp8Is12QhTNM/mbc2AnNb4u oLotjOjlHyVcwv5u8qzhn68QuhRGbaSP3Xdphmd9VgBJv1W/ZIPtx3Ry+3UV Pyof0fMJx9bevmzz7Agf6jd/0JGCfWrOfqAk5DS6ld8hmI3952W89IOlk0jV Ja2xFHuoqrIgRocXfY19f2M3Pxbdf3vQr5EbfUl3EejADgr5HmB34gSq0Dl+ uG/3+pDoQBXTcfRJuvPY6G7+zPEpSJo7ir4clFacxt5DaAlwqWZDB0Stbn/C LpOn1NMKPYQymI+vrWAbH1TjE9BlQgOV+i5fsenaj++wKjKgRXfSge/Y1pYl JSMfqZCMz+Sb3Tz6jOw/o9SwPWjwP5rS3bx5Ri6CJkf5e8s1e+fC3Xxa+Vey S4r+Y0sbO0Xbbj59xmzFLfX2pWygRcfPXSdQ2Y+OfSPJXrpeprXrw13HUlyb /8iaoPb2v9hiCmGZ288pgVmQ/upv7MncHyQZTjoQv5e89ye2PHndY0CMsChr MbyJfUfUtdeCxAyMSTFt69hLVvzfQo6zAq0qT98itkzqPGfuFXZgvqjwYzdv J3U8UukMPgauwZRyk9gbvucaNwy5wG4hsnAQmyOFRoviywkYsVgTeIGtXPx5 jjmaB0R8rr19ju3a3uHNy3USuiZ27u3m486NwMdK2mdgD+W94PvY67SmEgaL fOCesJ4Ti83GI9l7k3gWmJgUPgdgO+ptbEVVCsLv0v4+M+ze2gVFDV5hMCyJ Jqhjf5A3SNT/IgzjRDnJC9i0JmK8NtGiwEfqP82EffzzY2cnfTHIcVDU3X2/ QpzA2OjJJQ6HCr48WsC+HrOmGdlwHngzNLIbsauaCr0LFyXBRNVPc/f9kJ/E kO6drgtA1ZsldB5b9rLpIaNcKfh7lMB4GPvVW4an1NdlwN7UeWAYn8e5Vc91 u7cAFpP7TJV3z+9EIaelkRzwslQrcGHXP2NR3t8jB1Rs/MK/8Pn/G7qeZpMn D3+4LFmLsG8fyBE9bK4AelVX8VyJ+88Gg0l7nwKIld7Xfo09MOIf4iyjCC4O m14PsQ9nXh3oPqIEam7Wn2Swc87QOHsPKwOLZrmVK65XTfKuT8ZV1eDNS7XG Ylwf3/O+HwhvUIMNYbolJ2wyarWfwqfVwbL/k6jwbv18w3P5NqUGdP0XcaQa 5+23JmPzF5AmbLGW65Xgevv9wvEkzQxtUKOvT/XA9Tu6ZCQ3d1AbNHztfvJh HzkWV/+LWgdmRR7ETm/i/UT2azrfWwdMHp1WUMIO7R4S+KevC0bC/sdpcD9g 0IvsLT+gDy6J49MOOI/r1GxH6CrowxRz9lN27LRDLnLfvfRB21Vw4cU6fv5x w9qL0/rwrY3alQeb9xpf1uvSq6DzhE1ocBXPf7avCcuqhvBMdO4RI+5fNv5M 7KfCTWCIfLSKD/fDaZ0rNVoBFtD0hbhxHPfX7qXDKWrpFjDKqhD9BPfjspBp F+UaC3ANLJ4SxQ6ocjoru2oBP88y9SrifM5+MC5HwMwSdEoek9/Eedxg4EUS vYwVbD1q3JvdT4I3WpecXv2+AUoD7H8pcP+v+0yj3s1qDfLZX6RjenC/Dho8 0y5mDQycl2IYsR3LLeYbHaxhcP2F+bFuvH8Zgk2fvLOGVwGN/0l24vvR16wa 3WwDij+5Fz1wPkfq508p+9uCL5s2HkRxPylplUZ3bWH6qO/ZUpy/p2k1dCSr bcEFvq5IN+zWS6sA/iVbsDj75p4ZzuNSKklDDIa3QP4y72wOzuM1iitBY6J2 kC1zz1apmgQKeV5p2lp28O9c8o93Vbi+UpAXv7Szgz0zqQfcsb+2s400Z9uB TkLkbA6erwTllc9mM9jDiuljHRqc14suPh67tWwPt/jSQjdL8Dzw8Nza7F4H WHghWZ+K3f2nntz0hANwFD7IEMf+1PxGQNPIAQQLD3n7FJOAW+pPmEi3A2yp tb2gxvk9U8JQePuxIzyqYxzXxPn87N05JffnjiBqMcu4nY/39zcn09VxR8gS dztWiD1REx45fcAJqmN6miiwD4tVT7UHOgGvqptiD54/k4X23441dgZq2qMB vo/x+Y784XbW3RnkP3Y+lMS2mJ416Y1zhjuzOXd287twfN05ulZnyFGuYvDH Hlg2H4g55QLDRW76MXg+lryk1sgv5wLscUIG2tjZ98VzXhm7QKeYujQrtqsK jQdtvAvsIW7VFuL5mrGgmjVm0wXyeUTvv8Xz+bMgLbI7+1yhuuHHbDa2a3HH ljWzKxTl3mF3wR7fU/6eUsAV6gesLRmwiypDKxQtXOFn0DtnIzzvm039yGVx coXpYnoLAWxGaqf0eV9XeEI5rkGB7WNuGBKe6got4nOc1ThPXGY4p9fZ7Qoy hKTeo9jbFx5fTnvrCsohnq0/d/OMzWEZ6w+usHNqsXkU+/BzspOU267A4lrW ewf71aLnkeF9bhB74M7cbn4PYlnZn8fsBq10QnuNsT87jHxXEHCDPNsQAhd2 xj21FWYpN9h2LkN7sbU60MxHZTfQZPI9torzVR178YswCzc43vr0wDNse+Xj z/Wc3GCfr29BPjYnIa2Kx88NDkzE6iZhR74MyuhIdYMtS27Srd28920zITXb DZaPTM0aYK9z2YXdKHOD3su660rYORrT3mJNbsDccO+QBLaBj54jRY8bqO80 GJ3Gps17YfH2LX4+P9RwBLul/+LV3A9uwL9TIbF/9/2B39Wq7mtucH84+u0e 7FOnz8gqbLuBu5Bq0g+cXyd1H4oyUxHgfs9np3XshCCm0x+ZCeA2pe/0GftS cdTRp1wEQI/CEmewv4/8ORAmQADrGdORid08v4dAqSdFgNiaTtjN79cFFn5y XybAcenM/t38zmRstrahRwCtso6I3fzeFT44225BAKa3DDd28zqHdfxooTMB 7AeMvHbtoaDaGxdAgNvmzZ93H9/LvbfVLYYA5L/P1w5hc5O31RikE8BvqWNu FNt3NuCJdAEBDv4ycJ3CHmiVfMRVQ4AlscnrH7FPZ2+l7G0ngBGtaMUKdlBw ZdRyPwGoo2WtvmGPXHcM6H9PAE+Vtz5keH3OyZ5xq1khgEVq+yY9dtixeZv7 vwjQz/32LTv25J8skyAqd5go6DrCjy0yZXrlxiF38C+82i2FHd3MqqjC4w7J 185P7r7/IuGXKMAE7uCqHS7liR1vrM79Q8Md5t+JRsdiz0tSsU6ZuIN+aQXs 5vmUH0FkBV7uQP1PYn10N7+PSn2LCXeHnBcKnzew5eq+L7mkuENgJKcaI96P 6x7Oby+Uu8MTl2WDK9hK+vwvOJ+5w629D8jcsDPFPj+jeOUOrRQPWdOw1Tau FfR9cgetu9UJ09gFLpq+lsc8IG/nemE4Pk9/tWiclc96wD6HrbYqbH3BLquz FzzghKuy+gds8jUZjW/6HnDwkmCxPD6f1+3PHb8d5wFrgsR7h/D5rlVdZHbO 8ICUY4WntLDp+fKo9Yo8gGqtgScau2nh6AZHpwe0noy6SYbryWEbuq7K3x6Q eO07JTmuN06KPY13aDyhafTTLyXsTp6wcj9WT5D5l2Aci02Y276nKOYJR7aK DdhxPXtjvmw/bu8JGj+szqvi+hdl8pKRbNITrmt87l3C9fJVrbjLz8+eYFNO QSmL8zrDwey+L5ueYM4x5pCKndbjFTO73wvoaYO75XG9zRHnpeyQ94IC3d/R pbheP2MI/hHxxAtY428LNOJ6Tma/fDWozguY3RSGjuN6r9B1tcarwwv+0yNP icJ+5X/Ozfa9F2zSMpqZ4P4wtjixrHLQGy4Kji7T47y/0S4+TefrDWl0efp5 uP+c58yWoYz0BkMj0uBR3J98fOke/EnxBuuWHPU07B2hOcO1Um+4IcV5Nhr3 N/qHiYNvPngDU+sZI/8avL+9lzuTVXwgEepF43G/NDubXcLK5gvqIlkNajjP u9uv5b/h9YXh4YyMCeyYJ1LZESK+8J3lMrNdO86np0fSNtV8QcFDq+l2B74f vLRB/YG+MJrk6T3Yhc8Th4d21EdfKGd/qez9Cv++DCrfvpf7wfk3pvAPzw8m mndIZc1+8KDGnDJ9GN+fuLkl6xd+oLGi91YEzxvZtIHTQ7N+kEOGfG3wPPJn X3VPOYs/tDed0n49juvnztGMm37+8M9or0DqexLwfyXJjioFABV/ft3kZ3w+ PoZdyNELADdBahcvnO8fjbKKO1sGwE1NYeWDiyRgfgZ8+wID4NwV4bOKS/j5 IxOZJWoCIOWoaMfDFbw/OIQW73AHwqQJtScrzvfRBzrmLIUD4fKSSFA29iVy w/cCsoGw9caX8gzO+/ULQUNdxoEwoRZuJornu+zqN8++JQVCiOhBcjE8H7qr OCdf3QmEgx+4aCfxfCkoTR53Yn8Q8KibxSnh+XNR4G7kGnsQiFTeGyjHNmNu 8Y+QCIKS+jJHP5zXD+/T9dJRDAJ+ikMlU9iDPz+5HtMNgnTJOz4yeN5Vnt5/ s9YpCBzkJuO2sMkGH1uE+AcBOZt+owaej5s6zptq3g6Cij9X5XKwhZ5c0/6U FwS9ryXOKOH5e/nBV7Wq6iBYCd50SsHOS4hQCmwNAuadb2NT2GweZVKHpoKg 56vF7C08zw/dlD8/uxQEluOvrYt387jxiFDZjyB4KhA3vIitrGHH77s3GDY7 TLh5cV7YA395lZiDgSxrGsywn4kkHz94IhhCJrM5dz9v9eI9yf5eMBiu0tNX tmMv02ge8FQLBgluhsqjOM/k/flAI28UDB16v8gUsK+TPCj33wwGrgmRlzd3 89Mc9c64ezB4lGb9isR+O5z5Ky8kGC660Yfl7ubJHuEt18RgiH7Ja/AMW6Wp c13mYTDMMwbe2M1z5GVGS9QlwTBgmfhgbjePZq1+HG4IhpTJuvXdz1utGIRV arqCga899PVuvqQJdC9NHQqGR08Xzv5vnl2pY3SfCQZHka87u3nVwGTbQ3c1 GP79TJfevf73xcUJkV/B4HK6c3D3+4cetD6ipiDCZzK52t3nP6k3p+1DQwTu lz3juz/fh5aSYvEAEa7b7hMa2s1/bSdrDQ8ToZ3xdvFuvuT0vWzbw0GEXNeh i/nYBGG7I//xEEH7g+q7aOyuhZjeAj4iODaoeN7aXZ+s0sDDwkSwBvp/u+vn aPBGKFKCCH0sPba764v2f5n9JkME09DEvHW8/kxdB9NsFIgwMupQ8BzbJkBM eUSVCPeGr5hHYzeIXf2pqE0Ed3SkTQubfsWruMaACJEmac93P183z0k3471G hHeC7spv8H6oNm5iSLuBX/8/M80o7H0Hp1op7IlwN2e6Qxq7NPj4yY9eRDiS k9h1F+83sv/kx3QDiZC+HSB2EVtv3ep2exgRLJ2DRqfx/t02K1h7nESEYTUf IjO2JsuLrIP3iLCvMMmuAO//7N4lnZCHRMhcYdQQx74sJVBnUUwE0oHGVjl8 fjK+at0aqCSClaynOMLnbb3IlV2uHq+fZr21JHYaa03Q8U4i1MTxPWfH53Xx zYhw4isinAgz7Q7DeVA68sfcvwEiNNmzaC18w/l3S+ry9HsinNwxyniIz/v5 UrNfmvNE+P3ZEL7g/Bd9I6jk+TIRej9181zEFhpqO/DwBxFGuw47dOH6EVCh Mm56MASanx4UScD5rv+mfUwvawj8uh90oGoNzy+ccTLSnCGg9Jy8tA/nvZdx /dnsZ0NA5DLh/SbOe4ftDewmFEPwvs/R2cD1z+6Ez1FV9RDgrPigPfsJ7+fx +30NOiEwlbAd/RLnwRuX34ukXw+BTAVGi4g5vH95rbcNfEJAPYqmrwjX05Hz T87pBIdAB8WlBoUpvN7K69fVI0Mg5QoF7egkrud2Ph2QFgK97ZPRH3CeHC2L iztTGQIvc+wiYwZJ8LtlsIW7PgQ6L/yWnMb5kGvg8FeOlhCwRr+zzrzB8+5G 9tWDr0Mgz1dM5DHuD38lajm3F0LgQaz+AifuJ9wq29pb6yEQNB7XeRL3H2Vj CFv/FgJhzz5mcyMSJPm/XJijCIVrIiG//+6+f936vrL3eCgYpNPXS+J+p6a6 T+GhYSjc8Xh/uhjPCy4m6p73rocC98ALsX27nxc4JBUm24TCvf6nb3bn5+l4 dvpI91BgLFO6OpJKArchwRHnxFAYunPtuFI0CdJNDW3lekLhyY2UqHfOu38P kHlf6k0onlu/Nno64PsfONsrPhIK9Z8V6Clu4byW7SDM9zEUrmhK1X23wPP1 fPCvgzuhEPRnogh0cf5zKor9KBEGoh3ecYqieL9f7CLYXgyDZxQ5+VqCOG/T zxmvKITBVTVDHQ1+EmgXHz2zqR0Ge+wa2Lm58f38nNBJ7oCvu1WknD+Ifx9z z78nssLgDXPWlbXVdagQTJnPzw+DASHP9DOL6/Dqb3kvX2kYuB2Ru2XwcR3I MhfvizSGAb/aw2u3J9bBcdxUQv5tGNQ+XFtV61oHRZ1LLhZU4dBmYhUglLEO 5lzmBvP7wwHSPh6OS1sHP5L/xVss4VASQK4xmbAOlfG1dK4nwqGQy1xbPWwd OF6dKQqWDodk9xN6QQ7rsHXpwOwjl3DYwyl689iFdcgVn9J9PxYOB9Q+mW++ WIOib0tRctPhQBca/zqlbQ1K6348y50Ph6HmOW6epjWok2Q+bf81HJwECtwP l6zBKxm1399pI8AzMYTyctwabCg25DLKRkDVzbonveprIHc1bUshLwJCmV+0 aaFVUDqcw1dYHAGLxnKHKOtWQW2s4jptVQR8C0+lLi5dBX3j3hcDzyMgr+/g eM/9Vbh1jfzhtbEImMtpcVB3X4VEG1clb9pIEPzDuezJswrTnhp3i10jYck/ UybcZwVqkgLV070jgZujp9nacQViS8rJIoMigW5p6Yy4xQpIzjI6WMZFgixv EW325RVI0RgBtqJIyF5IrS47tAJKPNeXImYiIeZY6OnK8mUoHXCRsdSKgrE1 7qaPw0vgfzZ1jvVcNDCE7+8Y/rEAOddfWm+8vA1Gls4f64/Nw9l9oyTHmFho GBUyHuqYgRr+zdNaybGgxuSZOJQ7AzJXGC2E0mPh1784v9mwGdBIVxv4mh8L mdvkQucUZ8CRH1V6tcWCx/0rQn5d01CqVeRG/BkLL5iv3z/e+x4E7/ltpt6M A2pHHZrij+9A5MzxH02X4mHuLx9bpfY4VNKyzJ9UjYeL4v3aWv+Ng+Aa9WDS lXhY/qqytnNsHPirN4pvmsVDzFxqwMOVMeCW6b7O5BUPuddo9ndEjQGLtlO3 3ZN4SHqVkIk6RuGnd/MdNsYEeKZ3urlYbQS8TCpDww4ngPrcma8dYiOwJZPv ss6RALHcdIpfOUbg655E1U6+BEgZf6cQTRqG5Virvy4KCVB640NN4Z1hmMqi senxSgCLvQtDJZ/eQmuPobjX+wS4wqFm2pA2BIyUro8d5hOAncp4MSNoCCzk ohksVxKA9e65p2m3hmCnoWFR/VcCMCWrzvXJDIFs8ZGHJw4lwi05oaarnwfh Wdy7vX0aiUCyCxV4enEQGnXMx3ieJcLVC1oK1dv9QJ3grXikIxGuzHc3HR/u B6NXiVUMrxIhi9Q631DWDz8vtcb+GkuEhbqNGSfLfpAUPyHXv5kIlTkXdGde vQHTWDf954eS4NU9XY3u/D6YcBJ7fkszCWKUzRxe+fXCH/uzWkXaSTCvwfml yLQXOG/xzCzoJYEIq9iJYplesLZi3mNrkgRXlzmOsOy8gi8Gm4o2tkmQxeKh ExbxCqjlnr62DEkCnZuMInXpL0GSSWzKpDYJYlfPM+aP9YDpgbNOGQ1JwPOm jz7nWQ8E0fP8m2hOgv4yGq6Wxz3QuY+Zy7g9CcL4Ew7pOfaA9u+NG4b9SfAt UpV2jbwHbs1Xr+gt4ddrdzKq53w33KsT/a1xLBmMRXS61ao6ofwcj1gAVzIc H5bQsc3ohO4cZocSnmQgv5UOj8I64XvC1iQNP76u/WXSxKATDGzrmrolkgEt nT9K/7cDDrNJ+clpJwP/vU/m/13pgDu+8r/EwpJhesPX4+fedigliYjciEwG oytZ+wU32qDThtsu5XYyMNIMt/tNt8GWDsXEl8RkuHBEh8O4vg30+bsayjKT IWH1bO8p+zZgeafic7ouGe4+J9P88rYVUmW0f7AvJUPjSQl1bheE66+uS+Jq MmTm7NQdUMMO1V+g+JIM++S+3Th3EsHdF0Zjq9+TwZykenfjXQuk61vWt1Cm QFXs2+0S9RZ45EjwtuJKAS+Xz7bZYs+hODPtxxPDFBi42ypPzdsMJeiuC6dp CjA8CfnnQtkMpXPpCynXU6Dicyw92acmKDvzcMzfJgWOEf5ppBc0QWVNfr2m ewr0d5Wi3LNNUPu6zvtrQgqY6Szxbss0Quuf8R+S3SnQlKvDrOVfD8/+KasR XqbAKG1d2lmremggq80seZ0Cm7Pdy6dU66GCMlme820KFEXmhXqx1sMjetVY ig8pME2laO9ZWwcBHI2cb36lALuUwfzQ91q4IHNf6YZAKjQ0BuywJ9SAuCxV eqZwKpAbbwm4+NSAsJzn8ohYKmg/cl+esqqBM4o6iSpSqUCz+iqBUrIG2DRo JgQup8LS1w+HQj4+he+mvo4/LVKBtHCXkwWeQrW/cWp8Wio4xjrHDFJVw7Ha jdlT6amguJCh+HWjCqLXY4VbH6SCq6rrhXPTVWBu2dK3kYOdViS9WVMF9Jd5 qI2qUuHhrf9ut92ogptMawHcb1LhcEr1aeiuhKNPiDfrqdKAMDVzLlG6AiLn jtRq06VB662XPw+yVcDG0acUywzYsW3B7Vvl8CLhUzbH4TT4Uq3fWlJeDl4e au9CeNOAu4ySP523HAZwhdOQT4P77SMVOWxlIO1b9uiTYhqUN1Ayzv8ohYJq 5bUglTQwzNswujJWCoEnfWOqrqSBywr3s5y7pcBPN915+HoaVAs89pdgLYU7 it7MlZZpMMIq97b1RwmQBTFaqdqkQQoTn5r7eAmMfbm04++YBhNKHPVXMkrg Ev+U5iHXNAhNSpT19S+B8huemeXuaWA7zEv9yqwEjjxkWLnsnQYKk1rv5WVL 4P/+vw3+///b/gcJEGwG "]]}, Annotation[#, "Charting`Private`Tag$12701#2"]& ], TagBox[ {RGBColor[0.560181, 0.691569, 0.194885], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwc2nc81d8fB3DJKEWkoojyVRnRkuy3kJBkZCZ7z+w978W1d0MIiUhWCJVj N2xRVISUee+1iqj8jt9fPZ6Pe+/nns/5nPM+r3fuUQtXbWtaGhqaCToamq1/ iR8KJcf909CD+1zWp/PMYd9I/UKRTxqqLrvs+r3VHPK/dRW6e6ah2uMd7lNT 5tC6sLyfziUNZSnHWAyKWgD9Lvml4+Zp6HHYhYsujRYQCUPFTpfTECWWNHNp 2RIOKM+Zn1dKQ48qFuIEuKygQP0f5z/5NHSY24TDWtEK2g35oxKl0pDUhK8z Nc0KGDxvWVaKpKFdjWdCLGSsIerxDu419jR0xrKyOT3LBjjLuN43suLr/yhN j+ywgcfVojHRzGlo9DsqG/ttA2+ar68dYkxD1LbXSwP6trBjJGdAdj0VsV0d XfzMaQckNsl4wlgqUngQz25Wbg8x/vb/WJ6mohEinemgrDOcGXDwSilKRV6P XdLsQ51hSMRpfn9BKgoyEKUranGGE+Mun7gfpCKZ3+lXzqi7QOtlzxqh5FRk r+X6PdvaFTb3hbgoe6WipSn3wK8jt6DAJfT7W7dUlJYzMPuXzg003oQZX3VJ RUXN/30PP+kGmQFEteu2qehAwZnzbYFuIDURfdzCMBWdc6rivcrnDp5laaNB sqno670A3chwD+DeeVt3mxS+HwlLrYflHtBicaeTKJ6KxMvWk6W/esDeAxn1 sadSEYNZW9E3WU8oC3xw+97RVMRrotYovc0LZlWLNarpU5HtO/Jtu1xvMJ1E DfNdKej1sMGxJh1/2G2qe+PJuxSUUD5wWTDJH2qHZ1ftX6cgxng9A9Euf2Dt 2X9mqjEFHVj87nhANQCa6xwfjj9LQXf4H6FklUDgT+QgfbiXgmTy1EUmbYOh d+dT/vTbKSgoOtHlX2kwBBIVmnRSU5Bl4tzOwV/BMOjnvN4bl4IIDJJ7G0kh EGnV4tQRgscjOiH0wygUpiVdtRqtU9C+qkcMtvfDIK2KjhJskYKYMzzPWbSF gfypjBhZ0xTkHKff100Ng3v8bS31BimoR6q8eZtyOKjt4RKvvpKCogbcBH+u hkPJZPuh4jMpqP9d2xF9DyLcSuSZTP2bjCL7lNsU3kfBieQXwxbrycj5Lc87 aWYSjKYY9JxZTUZmdifbBy6T4OrtlPqehWSkMXLGktJAAqEshuRdk8nI+6Pj 2GpVNEwWU2QJ75JRhW20oURzLNwviT2n/ToZCcv8ij3BGAfapQKCR1uTUfvA 3e9D6nHQVGGxD71KRn5FOwtiP8VBdu2H2fXyZGQ6tHHdezMeDNsb7rjfSUb3 ZMTv9EskAeubG/EX05JRbOVOzRXzJHjzdi2cNTkZ5XrPX4uLTQLxrrMupTHJ KN7Z/NCxsSTYN1CgNBuUjIKe7HnBn5gM3eMJi+ZWyai1/Q6hjT4VIr4JT502 T0bip/dN7LyQCjLf33zZvJmMkt4tz43apcKTado3Wfp4fj7ev6XQnQokqnf2 sFoykpu50cCfkwYKf02uaJ1JRoPM0k8OWtwGVu1Zms8iyWhGia7IMu82fC3w qrESSkYNCQwzwd9uQ6Bm3FHf/5JR0ZfI/eft7kDNw7rV7P3JKCFNiu5XwF0Q UtuXP/87CT14Sxea15MBa9kPDL1/JaHoBDbpEJ778HpZaA/NchL6Hfgg0cLl PlhlXfRnn09C5U3eoM6WCdkLLppSo0mIr5332UGrLNh75+2fqOYk1JCqtTP3 SA6MzV2vZENJaI2VeFFSKwfK5Mds779IQku8pj+9w3NAffZXf2lVEtpv1Zo+ /yMHImX5iwYLkpBhWrgWY20urH8L1v0vNgm53gik0w56CG8kmHY9jUpCwnRc ZYF1D+FOfHqjODEJ1WsSke+vhyB2oURYLSgJxZ8Tz1t0zweXmOFtbq5JaJ9g g9hF70fw7bRYaYNOEhrhPXnRqKgQagp0ogmaSWhyzy8QpBZCDLeHlcrVJERn 55r29fxjOL2j8lC/Mp6P5irDPe2PIfjrqajvkkno+cmQ3uHFIjiUIGy2+wh+ f+Mqh6R/CVC2X5Hu48b3q6tnfbS3BJr8HA7cPpiEUndPOQufeAp21kWdvOxJ qMDrn2T10FOokTkheY4hCRl0Ok8cUCuDvA+X+KuGElG30zllmvMVoNpM/CTb n4gSVehGmRwqYOFpS9LrjkS0i9K6v+NBBchFXPz7qSER3cx70+bNXAnD52Q/ bHuUiFQOyH1uW6wE1mQx0jW3RJSmi+xrx6rgeaCH3LBDIho3p9Gx46sGE7vK FQurRPT82uOeDatqKIHT5t76iej4MNX+03w1qFCEpbJkE9HblubhfsbnEHLl v/nZnYmIa7e/0QvnOrg+Isc3S5uICgfXMnna60DI1chgZiMBZV0uFuzlrYeB lOTWKXICGjY+Jn/2Yz0IfdrMnOxLQI1M4SPhei9h05Hr/bd3CSib9Md3uu4l DPwV3/mtJQF5SExcbed5BSFHXbzGqxNQk0D+MA35FQzYfbk6ei8BSVT232bN RFC8vkoYSUlAj+YHtefoGyEkjr3+S2wC8nRPIebKNYJQudrxz0EJaDQ3LTq1 Er++Wvvvo3kCKrSZbp/MbwKhyPSyPsEE5NWjqc5U0wI0nBXfe/kSEL3ci/f3 /7TAYFEnVy9XAjpIv+ksptQKoV3bSd3MCWhtvKSO9KEVBve5m3UsxqNzjxIH eXe0Q+hDDba2unhUVnku/1jeG9A973C5tTIecVRsr+hdfwNCryOCWp7EI/53 ph9eXH8Lg7MvZ5qy4hHK4uwy2/0OhM4KNzeExaNwTnZ31dgOGGxk9KhVjUde ySd6H77rhkazszeGFOIRy72BK1TxHiihuam4Jh2P6q/6MObn90C4fCW7hGg8 aqU9aimk0AunG42rnu+NR35BD4WThPogDlX8rPkch3ovEJUu8r4HX9MvIx8G 4tDT495HVM3fg+UmQ/uvrji0a/DjM4789yAFxrfFG+PQGuiQdp0cgKkGhgs1 +XHo9xqz+o1Lg6DQcMO32jkO5Zw4vu1V1kcQNYk0G7TB11OWP3tt/iMc/Feu 8tM0DtFYMX4olB6CBVmGg+e145DoXHTe4y9DkPWqvK5KPA5pbpuTaT/xCdZe 0m8824xFrsMLjHNjX6DsRVlQZXIs4lE5fkTCehzys2grVGJjkaf8Rq1C6jhk hOhOjhJjkYZu7U+vpnEgKm6o7fKNRaKCKQHqPBNg2KHMaWUSi/LS9si4DU/A 9s8jlfuFY5EC0cj+uM4k6K/vmvZtjUFni5uUteWmQP2LCdeehhj0Nmmtu95x Ct9fhcaj5zFINj3339TdKTgZrl/dVxyDJPW29YQvTcE2pofhQskx6DZVbcY4 bxqeHJQ6/OVmDDLtOWvxYXEGcjbiNN31Y9BSq+Qe+kOzcHvkK2GHVgxqemqe 335xFkJzI2bFlGKQiMmd7WuJs6Ar2Pc8XigG2VUvneo+PgebEnbasBqN3NFN RguZeeBrukN/ZSEa8dqxmJibzoOy6utavZlopOAucrw+bB4SDI/zunyORpbX 3YbcWueB239yLhNFozMHTBYGL5JBnnbfg8e10ej0htfuQFMyWMUoaldVRKP8 soBq90AyPMnIq+14GI3otD+1Xasig9QLs4j1qGj008KgrZmLAiaKSRIMYdHo vPJfmR/nKBDegebY/KPRM/8/jYZXKPD2M4+2oFM00miW3DzrS4F5Sw3689bR SIfnLVNGPAVY54Nq5U2i0bBZX4tOHgUM/nzhMdCMRo49z1lb3lJwXtndb6ka jZKy2rr9v1AgZ7dMhKtCNBoxPxofTaHAFPf9uUgx/LrNIccKViowPXqXnSKC P7/s5tF1hAqiIuta2cfxfJg+v6J8mgresoa11ZzRqKrIl0/3KhUy2kiOTWzR aFd46hOKERUartbydDFFo3mZ7ZzztlSgN+GImPxDQglBkU6HQqkg8ENZYuEn CcmUP7C8FksFdRfvuQ0KCfU5iBstpFMhLXhQi32chIpnqleDi6hQy0BPz/uJ hP5eKdvnVkmFLwlitULvSejLD2uuoXoq0HBYOYp3klDvuUXTmmYq/PcglUeh jYR+hn2RY3lHBeUTLX1XG0hI+roj90QvFRzKloiGz0lIsDfHUuwjFRIu8ElY l5MQ3cf4CMYRKlQirblbRSSk/zd07eYEFT5cDssOzCMhqRjNC1JTVFjvKdci 3SehhadxjdlzVOAxGKNLSyOh2K7X+xOoVLg4tqf2QTwJiXp9qmdapoKVHTg+ iSQhOyO98xy/qEBacOF5HkJCV4vbdtWsUaHEN7uv2ZeEPhUyt82sU6GXppvY 7UZCRtG9U1V/qLBC+nvhkwMJF+Zvvw/+owIHm8jcd0sSYpF/EsK1SQWpe8bZ i8YkdL7q0cYLbJOjcVp/dUmoxrOD/Bc7vOgF3c5rJCR/TeP9N+yCM3PP96mQ 0APvF8duYb+rO+R45CIJnWFYMnqEr0++qMZzUoqEYu65T0b8pcKh3XncpedI 6FJ4svwpPB6VD78PnRYhoVMxrJMpeLzeOVoHK4+T0NGFP6gS30++QxGH2BES klhiaErC99svtu1AzUESur3TqEd0hQqb/wz2SbDj8VMVuhMWqWCUuoNNhoGE DrxX2ZuJ55N002xPw2YUOv7Bje7qNBWqT9Qyy/+OQidPMVx8PUkF1pe2TErz UWj/+4QaHvy85CLRjvbvUcjyq5vr5hAVHDU5GFW+RiF2gr17+QAV2ifbt6v3 R6HbF8fZYzrwfJby0HZ3RCGp37rbatqpcNTPm0azLQoNER5/qG2iQiDz8b86 tVFoxM89SfU5Fc6KR/y6kR2F/Ey+iTfnUOFBlOKMo0MUcvjtpajtQoVOrftT ZMsoVPWJXiULr/d1ruXvrjejUDY3XdqgGRX0yvMmPDSjkB5fwbO9OlTYPbzt S4B4FILPyhGj4lTwFWrsjqWNQm8m3J4//EMBrS6ZqicZkegex7QKNZICaY8e WmmkRSJr/ajiLyEUGApi2r8YH4nGDH0T+3A9MBMd8hIPi0RSX7s63jtQwCXR 40KTbSTiz7DKVL5GgVit4voPYpFoYrdTk9whCnQLsjn6iUaiKxmHDT+wU2Av rS8Xt0AkYjpiFhvATIGMykuB5lyRyM6q7ROVhgKP2cdl57dFokyVWc2oaTK0 DXI0beuJQOJfOjfy6smwozTYLf9NBFpt4FM7XU0G9cjvRy83R6B9huuk7jIy DIg/C4+rjkDGfAaWco/IMHFHQ4kjMwLR6xWvUJLIcPxW9UpdegTaOK0rxxhH BnsV7kfGiRFo5WSk+ZkoMiyszdDnhUcgxLgZ/SKIDJuGEa9P2kegv4S7tkWO ZFA4O+/TYxGB9P99iNO2JUMkk46Au3EECkeRbCyWZGB5cST6+bUIxPtz0uKl ERm4uV+qKYhHoBzcqq+qkcFshW9j8lQE0huvYRW7TIaHndFPogQjkITV6zKC IhmEgvR3d3FHIH7PZxVGMmSQHF3q0t8egVr739VOiZKhxFj8n+sfInr5jZve S5gMPJ/9REk/icjTbycfpwAZaIdoEmuniGjFYbHswVEyeOopod4xIvqyzWwP kYcMPwaiqNPDRDTZrMMdzEWGd30smgc7iShqly7rs/1kkNHUDj3TRkR7nteN kPeSobQ7vVy1gYgYJ6yPybGSIaWDm82/nIg4FUR/8Owig1GbUP+nNCLinx3U /LqNDJ2KLrTL8UTUoM18qHVzHuSaK87uisLXX37Q9eovPv+QRKq0HxEZHkjI ov6ehzTZwBYddzy+bo74E2vzwPASLTs6EtHBaCtmz1/zMFerfD3zJhENxjwx VVueB5MLMcQqPSKSuzu8+X5xHnqru6o6rxFR+reLXW4L86AgxvZ9UoWIdvOm P/2POg9Vldf3/71IRFz5fyNmyPNw/MzdS/uliUitike6ZX4e7pZ99hIRIyL3 6/wV5XPzEFhi8eHmcSJ6I7ndpX1mHihCBQzevES06NLlT5meB7OiGfEETiJy E7UYEMTuPyFiW8BGRDZXsox9p+ZBqeDWnQYmIjJm31wZ/jEPNfxVrz9sJ6K8 1thgDWyBh6urlD8EVDT8a3jw+zxkHJUWYPxFQMgtdsoVe3dOsAEvlYBOL52P 4sYO5mkmXZgmIH7d1LufJ+dhIZO+7to4Aa3TjKyXYFtwqc7YfiKgoD208UnY A/fiDoa+JyCRhXSRSGxlzl7Vu50EdMfre308du1tdv/yNvz62MLeQmyh/frF bxoIyA7Zs/djZ6VmfBp7jj334h4L/n7WvaNMv8sJiHWZlWCMHZ50VJqtmIAO 8WqXvMBeYbF2FHxIQPdKuJeE8f3ZxD++fzGTgKojvpx+ij20a77DMJ2Aktjq lQDPj1rMqT9uCQQUbFa0cwL75Q6PkzFRBBTfaHEjHc+naFSNcV4oATnct9lv iOc/h349rt6PgEZOMLCLzM7DXqLsq353AjI4dOMUG35ev0JbD2+3xvcjXHFq J36+dpuMGlwmBBSyTPuWmzIPn4KuBJ/Tx+ONLJoDvB4a/PtHLVXx683d56vw +pGSljNaUiCg/I4NFsoSfl4bRYOhMgTE8GJxXmxlHkoDwzqzThEQZSZKagav x+zg0/Uf9xPQrIdo6fSfeTgEmedt9hCQ2ZSIfNS/ebi9yVixsoOAnqec+XyG hgwJoV8L2f6Eo4aU1yXF28kQFJ6QfmUiHP3bqyB3Au+fNYV11k+fwxGL8Ne7 fMx4v263ibMbDEcVR+Y3BPaQwYkoS4h4E47G2ZYM9djJYBw5fwuVhqNY5q8z p7jxfo1RUz8XEI7OWf4ZaTpFhlq1mtdNnuEo+/QgweQsGcR28SlquoQjGp8/ AnTnyXAy7reks3k4YvVRoNhL4fqU8PhE4eVwFPxJo/f+JTJsJDNs59oXjv54 f9YNvEmG+nvNdbRPw9DDHMNi9RScN2l2VTMUhCEP3/0G+2+TYY+tTjnTgzC0 Ud3U/+0efl1ssmBvchhq4P0Yn5xLBuYe+jQ+rzD04+dSrXAFrn90qi4KsmHI f5DurEQfGRhde/jCu0LR+c9Zgg/x+VA5yMET2R6KDsfRtgxzUMBYxuxgDApF 6QRNczZuCpTvXNyTUhGKiKkfeAj8FDDK3/s3Nz0U9b7cfON0ngJPh3U/Nt0M RSZXW+ak9ClQSKrl2P4lBK1GP7H7eo8CAu627urdISje+RL/tyx83tw40JXe GIKSz1fTT+ZSoFjUM1zgUQh6dcGq/0sRBUoHTpGvuoQgR96hzsI6CtQcKWy+ SxOCUsf6tyUMUaC1Nt1Z9Fgw8ifbvaRhp8KlPKU3PhzBKMjO1CXwAM4Dsct8 TTuD0bTryztLB6nwxkRrSIcShNICo/Z047zbQces6Pc8CJ0b9xkBUZxfNImc rapBqJKZXptWhQpj0+4thi6B6MYj0/RSbyqu5+5VieaBKCkzI/KMHxV2tro9 arseiFSpHxxLA3B+eHAr6ox0IJJ4Vv8vHeffCF2XKzt3BKJsUH3HFUMFoWb7 97W5Aejsb/WRf/dxfj5l30pJC0BvC8bkeLOpoJNlV81PCkBT99jNJXH+CPS1 vZPkEoB21DlMGOVToVvU+oaddABiLHvbrF1CBY/7Zt84Bv0R282hv/tfUGHH TrOBq2/80cnneir9L6mQ6W3aRnjhjwbX0w1IDXg+tEwKqbn+6J7TUP84zj+c O4wdX7v4o7OMaZ5qb3A+9bph/NfcH4UPrJwZfIvz7Tejq+d0/dEl9t0dhjhP OTQYnnog7Y8kfSnZmt1UeOmpv+y9wx8Z2urK/nxPBc0JvcmSDT/ERKS/fG2Q Ct+v6Q1OUPyQ4upRjYcfqMAirPtcY9APVV7usJMcpoL5uHbA8Tw/pHWYxoZn lAq/NLSdjNP9UNUurgWVr1SIeal1M4Xkh/yt+PKdx6hQdUcT/rn4ocGI8w8f 4bzOoKGx/YO0HzpwSr6m9wcV1hgZV36J+KFruvWWEzi/zzShSY4jfsj1tqAn GefLzvNn2g3p/FBD2o5J6iwVUg7vix7p9EXSzln7CilUIH7s9PvX4IvYTl8n E3G+90qOcOCtwK+n9fgZL1DBgH71inm6LzLvrBpew3mWhzzM8v2mLxqi8FKn cN5lLUzZpNf0RR1ZndlpP6mwzfzKwnEFX+RTZHpTGufjyYGXfXbHfZHOk8QL Pqu430jwao7m9EWnu7Icd+M8/VpF9Fkxky9ymIv4eh+7+OWDtHmKD7LkO1xX 9HvreRpEMI/7oNR0kBDAeTz+NJu36HsflGnMIZSLfSs/XP/Wcx+k+oQhI3yD ChYm0irJRT7I1srx7By2DueKROV9H8SZLOCugfO9eJz1oZUQH3SebHSYHud/ AWWeXfvdfdBh0+mHBtgHaT5unLfyQTZfVxgLsZnqE+f19HyQ/mll/QXsPx4q Iz4qPmigoOKBGO4nKCLbuu9K+SC6WX6qB/bXqbqGupM+iDqcpVOK3ZvrXvaJ xwclKAl+/obdfEM4Z4PVB9nXUVL34f6kav9kEvd2HyR0jCdOHvtRT2aY7E9v 9Cz4d58t9u1oXXeTKW+U+K/fIwabpMhiGTLsjYK2sYY+xvb/266T0+GNxAQO 0DdjOz4PUWp65Y14J2zZPmIbu0mcnyjzRr9uxjybwtYQXjy2Pc8b6ZSxri9j y38vOsCf5o1UptOXN7DPPLBgvBTpjSSkWks3sfkMudasfb2Rqaqq1Jb3sQ9M Rzp4o8rl8fx1bIauuOFCY2/UtU/97yL2auSld280vFHRu+va37Gn5f/Vz8h7 IwuOlsoB7E/rNU+Yznmj/gR3kUbszirXTOFj3ig27EJfIfYrF4F4dQ5vlKZN LYnFLhUYD3Le6Y2Snwf1OGLnTNxzSdjwQvlj7ZdVsFMytU3LyF7oZeNT/qPY RL1dmr1fvVAO4bDXLzzftu8Cz+xt9UIW2lIlt7GddkTW8j73QrdjF7Stsd2V E0Gk2At1+6nsP4Md2Jx7VSXJCyVRjQ434ucdRvNkQJfghcauXg0gYEfKVd2w 9PZCidJXjylhJ9W32wcbe6EC5q74V3h9pa/1LMRe80INlg5W3tgZ4sM+9xS8 UK+uzvOT2I8q5yKqBLzQgCkvbQpen/XFrHmzK57oxAjyl8frGU0fFFyb8kTs 2tyEH3j9tx7/r5z+syeinVa1jcHuyTvfcKTJE9XPGi914P0ymWH0SS/eEzlk XDO+gPcXS2z+3pZjnuiNTWZhHe7P2d8+vdfL6YnCj8R/U8DmZHx+ZHSXJ2ru mH/2bokK/xHeiv5e9ECNlTFyH/D+lgigqJ1q8ED6HR6nR3E9sHCUINzX80Bs qzM0L3D/Wn2lc9kjyh0VlVmMLeB6xPkhwd/Jzx0tFKXz6mL7m2lts3Z0R/9x XxKrG8f9q9cHFr1r7qjBcWNXGK5n7dljghIc7ij9cHUZK65/Q4srpn8K3NBa YZjCVn2UCnz+Y+WuG9KF/n8PcL+byeDvTI5xQ5dTjkgzYptxbfqPurghtlo1 o4+4vs4o7bzdKO6G3rTaSIXgfnj9zuFOYvstFNP9zOBnD17/fGPaQbW3UNC1 EzfssBtK8oa9im8hhWsMDl9wPQ9vOjFlk3ALKdYPdLzuosKuuTO0qnq3kFfA 01sluP5LBMbdOtTpimrNFE2fvcb7P4kteFe5K3pwdpMghd346Hbsn1RX9GRa kK8F99uqPTkFozdc0QJTw/hQG+7/+aq/5M25IKayYEaOVry+3oyoCO9yQeOd XjoTjVS4u/8BzwOqMzq0k1MsArvawmxl74AzWrQ81yGITfkz8WA90xm5xkkJ +yJ8/2emf70VdUYDaqWsQvh8Cwwu6pRld0ZPUkXpPr+iwr0Oh7yKVSekkrn+ Oh6735p89V6jE5L4dr1jDZ+PShlL+XbaTig5sJPhOz4/zaae+X8Rd0JW55Rb 8rGDxLw0Nbmc0HZnsoUNdk336saFSUf0gldQh1qPr8dV1/fkjSMSNDtdWINN tfMv5H3qiBgNVb+HYAts/6vN6O2IaoWdjnFiK2k2CAQYOaL+kX1CU3X4/MsK +UeRc0S8F5h4arEzLtAWf2B0RGHu6x9NsWuILSFq8w5ob3HzA3Hs931E3YZe B/Rgv7vRHuzdTozbCu45oOZo9ifttfj76t58OBjsgApY6RUeYV9iiCmJt3BA SgpTXRHYFjpXwrdddkA2xFUNO+zgnN0GXsIO6BmjdZs6dga5S2RmjwP6YC1z 5hz2c6nE7TdX7NFIkH8KF/ZAlOZw75A9Il//N02PvTDAVqb0yh4dX0wUW3qO x8P3nliba48s1sY9x7AFXdOMTkbaIyFEKurFVn6pezrHwR5F+zD1N2Nb7ORg 2HfNHtEyd5BrsIP1hj5HnbNHm+tH/5Rg3394r2KDwx7pRiv/yceuXTCKcv1j h17m3iRnYw/Ict/8NmaHjO/7dGdgL8SMnNVvs0OKVcTsu9jMQ9k7OorskESp vfGWhY6Zjcol2CGlCArD1vuV3Y9WVbrbofunWjKztsaDJqKP69uh2Gcx3A+x Q3bnm2ZI26FZagexGDvT0Po8yxE79Er35/tnW+MpOL4rnM4OKfNY7kBb41me Gvs5bYuenjE/0om9KF9UY99li97C4UOfsVkSHOJGKmwR//Pq5bmt8XwWttC6 bYv+Gp598m9rPALkC23+tmjXdJQcO55fS69SZklTW/SjN/WJIHbmnjN1RwRs kfoEdacx9phV6gtnFltU9dx0hzc2f/3PV/UrNugcx4n7ydglVvXN15tsUBs1 2qtr63nVcbflFtqg83rfa8nYYntCXlPibVBpKhdpaz29qFPsJBnZoDLB7U36 2P9YCroH5W3Qm3D648HYClY7+vhO2KCjQwTmAux3LF2DL5et0XofrdE69idL va8Lcdbo4QWLnCq83nnqasdlPaxRExdT3w9sCxauyRhDa3R6H8XlEN5Ps7Vf p/mPW6N51d4fEdjrzPZLBsgK9Q/rezjj/Sln2bHy6JEVKmYOrC/GDq8VWV2K tUK5w/56M9hMlksbcQZW6LXRnxAHvL8P1gbQNy1aou1qmtKBuB4YM48ysgxZ IlvSSEcLdo6FPNONBkvUpsR2ezeuHwLM9Ht+xliiaPe9b3OxJSwSOAX5LVFc 2RuFT7jeGOzOFU7Ws0B5TJ2nQ1vw/JtvFx2VsUCPFU3uDWOP1VifFv7PAnlF /vx7DtczO3Oh821Uc/SkvKJ4Dtun5pncb5I5WuTddtgG18PbZu1a5i/M0Gu2 ffkEnK/TNO7rEB+YoaeXRKKWsVNkbukWEsxQp9l7eat3ON9xHjIkXzFDHq6P j6jg+rsj93PjUq0puhyxROXE9XkyVGiUb+MmklR//2i4lwpZ8m84CSFG6I1L kd1TfD7c5XbnfnvZCK0QdmaexOdJ2hrXkT2sRmjpwp4fT7Djyl1P3M8xRCnp 1Y+KP+Hz6giH+LMmAyR+LlTw8Rcq6NHY6Hzbro9KyI0bWfi8YmncnqBI0kHZ X/TNr+A8bVBCnZW+roPGrv9mqMfOu/v5stgRHTQlE3BYYIYKF9yebTtWq40Y +51jaXHeNuOz9GKY1kIKWi8WyvD5+YzYbPz2siY6uGx5fAbn73+3Suua2DXR e3+VD+rUrTwhJuKJrqHHu548K8Ouc5zM0aVqoBQX0Sl3nMd3dyuSOK9dRbRz Z9so+LyuSKHVz2ZRQydknnHX4Tyu7PiJNbFAFRGJWWPMOI9/Uqx8FyKniq5o xN0xx6b7aS5n7qKC7j272EeP87meftMx/m5ldG1R8NBFnB/mTt37us9GGene /M0Vjx26w+0e/b9LiOtg0upH7KK6I8xTIpdQWdPV0w44f/zhCl0pildE9Q0a BqE4nySt6JdmHFNEUexXh5qxj3Wdsot9pYC8u1q56HC+0Qj++tmJfBHNE9cm wrFzx+RaTl2VR18YMkXccB5ydBdZl38HSOauE7EIO+2/EWe+dTkEx+7FjmFP RcjofjeURUwVrnlqOE/FqW3853hQCgWEfatlwXnMpyFu2OKqJKoYYfKRxrY4 y5NoFCaBtI96frPBljh0cV11RhxJHY9prMP+L6G/7OJhcfRB+qDoODYLrZW1 pNZ5RHlYrMiI8+DkTGSvQN059IZb0Pwads9Nzsgj5LOo5bCpjRt2fV+RNOfR s8jwmwBLCnZSXWcBY/RpNNCXLd+D/cvoZe0/v1NIqmPzzRx2l8LX/yjjIiip zJDKsJXf9x5b76wQQrZPltgksTXXL1u/PCiIxlc1dmtiH59w6H0SdgLxVo7n WGP/eRsvfX/mGIp+8aHbD7u/orwgRosf3Ui5lR6H/fjeezb/Oj7Earm2nIUd HPYr0P7oUZR08/XM063X+8/2VuzlRQltF71fYuvm+RYkTXChOuPRu2+xt7k3 BLpWcqIdSdxag9hPL9LpaITvR6OkxOyv2IZsaoIi2nvRPYee0GnsXc28mxxK LCh4KHqVim1l/uTJ4DdGJJ7qQfsL+yXNBYNUwjZUc1Mvd6tfEJCP2Jmn/KuB I3r7wNbfb8r/SrRJ7f7W0PjIOGOrv3jJbsEn9f6t3NJunZUtJzA6fPj4kyqn XPt1/B/2gbbDKbde/JErbdxt+Qf7nCIhc/0VHfh5/PJZ2+ovHq5SZXh2QTKx 4chWf3ORtiYXECtwWd69OY+dfvZWhxmVHTJw7p3EnrEQ+hnGywHqLffTPmHL pE7yPLx2CGjZXBJ7sJNaslVaQw5Du9Rj3hbsJb+TdUv6R8Bxe+ulamzulJ0a 2xeOwqCXMm0BtnLxjwl20n9gSteim459q7nFh//IMZihGZInYLcuBeVe0hSA 5HN3xoywKUw3xPWmBaGwreW2EjbnfxIdNqHC8E81beoktpPO0kpUuSjcDXth /Buvn47qKSV1/tPweYmWMII9dlEv8frCaSj/3X25EZvJ6By/NeksVHdaVYRh 8/7IdXG+fg4oe6MNzLDF3FnrvI6IgfrxmTxZbJMY8tXI2vNwYvbu8RW8/ivq C30KpyXAm/Eumxb2WmhY+2abJNxXfHLyKLbc5Rv7DR5KgZiO4wsq3n/v3rM8 22EiAyjvrQwJe2Lei2L/HiAroZS1cGv/DhfymBvIw257EyZH7Ocv9ykzv5aH NoXTsSLYf8Mpadb5FyEIiYiU4noQvSfv7AFTRTiVK6GYjetHyRKLUXOXIniu 7WzXw+4dDAhzkVEC7YqCKWbsA5m6ve0HL8Eo7ZV9vrge5QnsdPEZUAb9sg03 GVyv6i/eKhpSVYO7zN9sSLg+jvCP9BJr1eCmmGfQSWyaHWprp09cgXaVz849 uD9S7v7vcjSdOryMnJhnw35v9HFSEl2FEb3Pn6Nxvf0lyZt0NUMTHP30bVVx /WbRiewo3XMdNDo//RCYooJW1XqEtuJ1iBOVla77ge9/v6v8L+/r4NtKw6GK fXBIv1p29Dq8dUjxtv2O88tNwQedJbpwY1Ds+oNvuP+x7XSfVdUHxK8Rt/mV CtYBew8dJxpBxlHngTx8vj3+Ejnw9rkRLFmfYRPBnpXdSHCeM4JElTnH5x/x eqOZ3F6tfQM8KfkJnbg/8o+oJiseNQZ6cTq237g/Sko0aDJvuAk0bnyXTfuo MKp1rUoj0Axyf4tzh+Pzt33mQIraXTOwp1MpZcV+GjbqqlxlBssl8hw5+LwO rHAWlps3A5NveyKa3lDhEFtcnoixOZjN7nHbg/shvd43SbtlLMCy/433F5wX 5OySXHYYWEDXOIUnAPsYjYE6nacFTL9gWT2EvXJqivHPEwtwJwiomzTjPJBI HzLHZQnkus2DKziPdGsoOL/bsARaSclsM5xnan7svNLOYQWRYx9y92FnBfcJ NJ+zAoUDlf+9w3nIqdRsss7RCk78G3wmic3EEnKj6LMVINPQYGGcn5YeKUs+ WrWCj9sOkudw/hqWZeHIZbeG5+ldG0+xHztn9d+9Yg2TLrDzArZy1wtV0gtr 2CPZqXET5zlRa8IJ4kdr2HzOIyiMvf+vGn3osjXE/lNp2sqDkyc/NfoI28DY Yr7EA+zO1txsj8s2kHjOmccT+5mxfaCrpQ0cyBDvUcMOj1u7YHvfBlouCGX/ xfnUgb9xv+VzG9A8oNU8jK31MmrZ5L0NPrfdXz3Hlrh+rc+IagP3Thqn3ME+ Mn+gTG+XLbi4tin6Ye8gjsZpn7CFgQDNga28vMBV4KChaAuMrknKCtjoyvnj ygG24M7xe3gvtsaTRml02xac3KaNt/L4KJO6lkSlLcg0HK/byuvODh9tKrps 4XdZ/cKn51vnj0Wg0IwttPDdod/K+3GClOSHdHZQe/X+7wZsrmi/Qu4jdqBU mtq91S8UT9O9Spe2g8gfZyO3+gkplaR+Fn07+KrIxbfVb7wt5JqOcreDue+D D7f6EQPGwr80CXYg/Onj7q1+ZdrmLLt/kR3UXSOabPUzPu2vBJZb7UA162jG lhmOq8o5jdlBSf9k49b7b0cM6HzfsIPqG9T3W/3Sse+m9iYc9kA7rzSw1U9V Kc0FfzxrDyqbn5q3+i3FfO80TQ17kO4g5Wz1Y/3baYvf2ttDlA+7y//7Nct4 pBBhDzUVx09u9XOLzZyDL3LsYfSh8eev2KF8+bNiL+2BzHI6cBGbNfwUTelH exDcu2vPVr/4YLx+/4lle0gMl0k7hC16UVk4h8UBrj3Y2HUW+1VOn/xBIQe4 vGbvfQVbneamXsolB7B9kfDeBtsReYQRAx3g0qlH1g+x13k2b/+94wA5uScz WrFjgmNKvJ85QLhiRuMU9mPZ3I92sw4gUw7j5/D6upB1kjxO7wj0jy9/MsZu //Oc9sZRR7hr97E5Cvv7i26RqwaOYEyz3/QbtieXkWK7hyP0Tb9l3YfXN13A dwNIdARrlz2lyth8Un8IZ9od4bi4SkEFdsW9qHvF445w3sT13wy2/O+9Zf/9 dQTu3AwZfrx/TGsFP+0Xc4L8N4pW2diZ4vqn13OdYM7t4skivB+Fb09c8njl BH/HY0MXsOt/Ot+YH3KCK39fFm/t3+EqYuToHmcotun17sM+cK7yS3OQM3jb mucewP1L8inm6FhDFzBssg9facLnVeSqm7CHCzDVSrJr4XpiNjpu1BHnAuSh k3vKsE/H15zc1egCWuLPpVxx/emdNe2NOe4KjQosG5u4f2EtqOSIWXaFQwfE y0xxfbvMclKntf0WJOSEDK/24PmXzL2c9v4WvEDaRD/cf5RaH5CxGrsFjQ6K tH+wD7yiOUa3fgsK0qpNtvdT4Yfj4C9FETfgFFqYOoTrb+Tb4IyWVDfQPXff yhbX7zZi33izmTuw5iUuKozjPGEV/6HQxR2SvJ57jWB7Kqp2xAW6w6WMwSGf CTz/tE1Venfdgd7t0J4SfF4Eh5RHzfa4g2of8x9WfL6I+yeK7AUPeHiJP7IZ 9x/xhlf4VtU9gIlzKVwX9x+TEowcX4w8oJf544Mp7JTVYJoCbw/QLBpn2EnG ecTT5b1kqQdY0dkeAdx/FLhe9TM/7Anb2YeoTvg8/Kux00VZ2BNCZZnezmFf F22zEJb0BN6Lh8h2+DylJcuo/7zuCR/l10Zu4n7DxOEkb3ScJ5RMWQ6dxudx teo0u0uGJ1QbFATnYO8WzN+h89gTDP6S/jHj87t+imuJu9UTBphTtSawD1jv aivf8IRV8ZhSF5wPnJVe16Xv9IJF+X1xHdit/xFK/Tm8YMm8u/sYzhPuE+t3 lM55gQ1Np0o/9tummjjBi15wvivcgh/nkyO57mEs17wg57RSgQd2t+msw5CD F2ywB93aifPNMSgwfeXrBWvtwsPXsAN5LK7nRXoB9BidTsUWGhmWdcrzguH9 gS6sOD+FvUw/q1XuBf/swi+oYQ/d1zoh3oDHQ5F6FoodZfSWleaTF7DL90Ru /f//u2ox17UfXpCelja3G+c7FracroVlLxCgt5Q5h63ltOvkDI03xJzd5ayH nfbaO2ac2Rt8CkzdvLGH+Camhw95w+WD52RTsbmCr17uP+ENT48ZtJZs/T5q uPbROzFvMHUtXN/6e0CeGD9dy0VvSOBce7+V578nJlq80PCGRi8Bpa3/nxeY W298dsMbJAI5Yev/752UbXhL7LxhTrCs9jd2WW5fUL6XNzhoDOZv5e+lPzJf MsPx9RP8VrfyubjBY6n0RG9g5k/K38rzfs/Y78VneoOQKkfO6laeZwlZjSjy htwwtlEyNo3DrG5wjTdEvSVqj2ErtulWebd4w2Rp1GI3duSRpr2uvd5wfsfp srqt328FnHSzHcHjZ8sPycFm/ninx3TWGwpiWfW38rTm2e2iBqve8OFbkaDF 1nzFu8Rp0vnA3vqKORnsj9PDsypsPrC20yuZHfuQ0iXVizw+YBl4dc+Prfz7 oLxQUtgHkGGWYRV27joXw1kJH1BWHbIK3ur/dKOshC75gNq4zzElbIGKpWY+ bR9YP7UniR7bcbfJUS5THzDePHOvGa+PpWax0V1+PlCX8tXwFPZ5nhwZukgf OHp3dn0Urzdfv133/6T4gKhcAnMM9uapCX1yiQ8I5Onc2FqvCrFXa77X+cBo CCnUFTvyR+2+0XYfmNrjNMeIvTsrsa97zAe+3ZCxFcLrX3Nt/dRrsg9w0723 qMJ5OFXHJgGt+0BwkbufJPYhJtkr5ft8wbp5Z7cY3k8nfGZbk1V84Udc7E8K 3p8O/br/xej6Av16ZZEmdqlIU1i4hS9ciOo78RTvZ7HJO3Iegb6g+M/ghh7e 7wpal2qvl/uCrjbvHbsFKkSUlB+4+soX+stXkh/gevGGkdvr0jtfENQw392H 8/G1hqUz4pO+IPuI/eZ/uL4YC+c84eD0A1Yf/VDiDBU8HMiPuvn9QO3ehGvq ND7PiqRyIs74gdmuUx8ycZ6uOzGYtqzmB6qLgrPZOC8f4GcK7gnyg6HY706m uD6KWOr7Rsb4gdGXzxoXx6iglJfvLnvHD9xWbrgdxvnZ4wjYPin3g9GDMaat X3C95/bUjPrmB+Ybl+U6cV6eutGkJrfgBzdWuMNCcF7+l8Fy6ecfP+gPLvh4 chBf/2CRpOUBf3imGljihet5zP5RPlD1B/XiKm/Uidcvi8rPX6X+oDUkK3wa 51Wjq+nUpy/84daYb0M4zqfucRMzVm/8oW7gn3APPt9ymIJG+8f9oWluR4Iu Pm//MFS+Lt0XAGV9phc5K3G+3eTKsPEPgPqFxULPPCp0ydmnHY4KAN0n8jes cvB6DKpJGEgNgGuHrMauZlOB/Y8mQeFpALB8d7BmycD5fy3CiWcsAPKOtsRc Ssb1apEq9+FSIPRWd4ckBOPPfyNI5ukEAp3Vqb4fAVTI/sAh5mIeCHPWHXsl /PD1XoIgQ1Ag3DebCGnzwOOLTGQXrwoE77Lcljg7XC+5T02n8wWBAuNr9gFN PL8qLsm6m0FgWG8glsSN8400bdxR5mCwDmeY5TyI85vI7UjyoWAYUdf5fX8/ fv7sDQER4sEQLHLQLpkF5+tRZptq52DoMqlzlabB/a/nU6n9X4Jhf317eOYE BV4+mP82UBsCwkrvTh3Pp4AFy2mVqrYQkM0JfGudQ4GdQR4lqf0hMLDs0peX SQE9o3VP7fkQcCImhO9Pp4AvE9326T2hsJz7t/9rBAX2trGlWSuGQlBw+FFu WwpclhKpMSsOBXbuBLkRAQpkLGrY9ZaHwhrTD8U1fgpQHt86JP88FFxPl79l P0qBNI6qYN7WUGi+596qfpACEytSl0dHQiF129+QtzspEFimMnSDLQwsj9b0 MMyRoZzfal3PNwyIZ6/F3Swjw+D5opNaIWFAn3HgnfsTMqwrU0yuRIbBHrpT K3GFZFC0922BtDDoZJAv6X1Ahg9P4+IEysOgqkWeKSOJDH/Fq3nWp8JgEN41 6XuQgU9lXXOFEgZaNwLudruSQdkQCJSfYZDJt3dC3YkMSQFvpya2h0PGT2l3 M2sy8DeOlHfwhsM7gXrGaX0yqKkyKGbph8PsNV6xLDkyuBpd8bpjEg4OlZdT sqXJkOaYVJhsHQ7t0hd+F0mQYTT+0O5Ij3BQK62L+nqWDG79ooMuieHQlpR8 9t0JMtz+5sFofzsc+JddLY4cI0P9Sq2kZVY4+HqZTIXxkYGOQzFb/0k4aHld uG17mAx3b+jbyr8Oh7yXWSzN7GR45ZR5T6o7HJL/fHX2YSPDRNB4h9hgOKTT 9TtJ7iGDcI7jacFv4UCMOEj5xkQGzYpyi/9mw0G+xqu5cwcZPJt/ph1eDAf7 m6RPzQxkaJgM+c22GQ73B1j8PtKS4dvPVuHdDAQ4ajyr+YuGDDsYmUwYmAlw 0+fKnv8250FbMK15/RABfKRtxgs25uG78+PYb+IEOJ7+5KLxz3mgkW1zt5Ul gJXdT3eGlXk4tHvCcE6RAO+0bgy9WpoHzWIugWVNApDX2RuvL8yDo5/EHh99 AnRV3QoXo85DpIrur/WbBJBb+7l2lDIPL38ktNI6EoDtg0TY8fl5+Fj95Emk GwEcX/3rk52bhyXimxQmXwKspNLoWs7OA/P1734JwQRg33AUvDMzDwL/0Zrv jSCAULm8y/D0PCgu8ajcjiVA+ayFghC2SZP0qUMp+P78Sa3RU/Pgl2RwIPsu AYY8ZNjXfsxDmqnX36MPCNCTMKbuhV0mmjL56BEBZrfnJ27Dfve3tEOwhACE 6aTfmd/xfHR2VD6txH4U8PgyNk3m9L0zdQQ457tZtw2by5E+rBrh+ZJKvdIx OQ/iUnx2ku0E+HjdzT8fW2snXHvVSYA/PPcst34f6DR0Q/ziewJ8l/z039bv B6MKfQ+3DROg+HbDxwTsPO90OtUxAjwNyL6/9fvBV5cq5zp/EMDsQ0JsL/bQ vp5+TTIBttHatOzE37/8ba5uYJkA6qnPTHSwWZ7tyDVYJwAkdPg+xRYMP0b6 QkOE0fLKk5z4/pS0FFzNGIlweOeJ9FRs0yOmepPMRFAXye7kxfPlTw2QtdtH BIk4BfJL7PSGu/zzh4gweH2G1RHPb3l89a5bR4nAZHBASwg/jw7j/qXlE0Qw Vfjdvo79Q5g67CNKhF+DTrFf8PPjfifwOESaCMLXHpsP4Od94d6lxO0KRDC+ pv1wlozXn52Fd5QKEd71Xk/di9cLiSFTKVGXCI9ph4bvLM7Dw8FaYXZjInzf x3HzJ15vDfmDe+9YEKE1i2PaCq/HFYU949mu+H4U6B38V+dhz96Tb/i8icCa whlz5Pc8CI2rlBUEEsGwSppueH0ezELCg0qj8feXROuE/ZuHAI0HVmeTiBDN +OmqG94ftw+/vFJzmwiko4HzHnj/dL74ebDhIRFW674bVeD9NRWzd5tCMb5/ W50r83j/0Rqdmm4rJ8Ii4dpRqV1kkFizq+l6RQQRkVu1LKxkeCj2RXvkIxFU znMzZh0iw+OfM1Hyo0SQWoqRtcD1oKRm9eXDSSI8Yyr9I3mEDDUS7CccFvH3 33YUP3qcDO9k1DZ+MUXA/nd/dXtw/en5q3/aiC0C3MJl0wXFyTDQYG39iiMC wg+eiL0tieuVfFgPgT8COosKch/Lk2FJqfYhq1wEZB/jc396jQyr9O1DHkr4 eukvrLN0yPCn/T3zR7UIIHtEbs/B9ZFBleqTpR8BFU+V/hsxJcPBq8fVhdwi oOCW/+p5NzLI66atKOZHwLzAtUHdO2S4dCBPsLA4AlqcVSscMnF9/VhmwlQR AYcTK8W2fp943bDjTe+rCJA5K/ZybwkZ7G7SZt38GAHS83pnJ5vIkGh965IP UyR43/9OyFrA4/dSv118KxKuKNUWDhtQoCop6Mpdn0hwEPabMTCjQOyTUprI 4EiouPAp7Bs+zyTGWR3N4yLhX1+nD6cPBVLUB4HzcSTImrjkLeDz8NJ/JjMR XyOhi+OoetMABbjlErM9fkQCuwHRs/ALBZYMGnXMyZFwufCfZ/wkBbIT+Bpk NiLhc/qZy7orFFj7/SNl+UAUKIhYPallp0JJr6uMuUYUuB5RdPqE80D4XM6i hm4UjDDHN4EBFQwZ+gtkjKOAZtivMcWUCgwyYmycDlHAT/OX+48z7s8L1753 R0TBl86E48+icT/RLHj/ZVwU9DLmDBkn4bw/YqRZnIqvH7SDe/o27g/3vqqP yI0CtdvMjzMfUmFfcFiizKsoqG/3FLy69ffVu5VKQq1R8ColYLUf57GmZ99+ c3REwUvRHQdPtlPBZeaS1fIQfv/j1nRN3K8r0fkcHP8aBSclCRscOO9x8T7u 7v4RBYFNF94VD+M8e51JsnglCmYk1E2EcP+d7SpNubMRBXvPfSTvxf22V4zT wwhaEnyeZQ1owHlW/VGWgcdOEsx6cg8J4bzL19jNbM5KAhX5zz26OC+vfdps 1uAgwQyT4HFZnKe7f572leEhwRnlg3dHcf7OZ7UQETpGgvtRgl8u4LweIJw6 wXGSBB9CM/KUcd5XoctUTzxLgoc3S7aTcT+wbyS/hkGSBM9ODSZo4H5jvPrp kWAgwbGCeF173J+UJtTE/LxEAkvaEGvprb832aIVJ3USFP56+WarP7ws/8Zk Uhv7LGfkVv+272DfmxuGJJg7rJY7gz22OHz2vSkJhJAlVwR2ybuJTDUbEpwc 4F/uwtf3ezjH0OxEgsxX/Me2+h/lwJVbkh4kcPinU2KK+5u9un8/lfuRILlH PTwfj39UhOGSQCgJTpQVPUjA9/eEYU/Zg0gSnLsa8YfrF+6PvnIc5IgnQedI e5Ianh+l2iOEhFT8/oGM65x4/liTBcn0GSQQPDEuT5inwoj9Wf2gHBLcfp95 LRr3D8UK0k0rBSQQCw8NFJikgjeXkrDTUxKUD6m3meB+QHFFPf3bMxKwSFkI CX3C1+vS3TSqJ4GEgVwZaYAKRcG271Vfk2DRcFFi9TX+vP4t2aYuEhRwHzTc 3oT7n9N+hRIDeD7iW3ozcH7/Mh4TcGKcBHJ9VZJWRVR4XJ/6PXuKBEUBZ7xS cF73Ss28doBCAgKpN0vpDu73L5X+R79BApkmo1wRAhU+HX4eH7gtGhwmfHeY +1Lxc0Gry4zREKvm4M2G94f8476OiX3RILnEuDhxHe+HsE/njbii4UDn4lca Ffx5w28P+o5Gw2fj4PvpUjiP7/rp0SgaDcJTIh2HefDnJ/+OXDgfDVqn+OJY 9uD+8RWDSpl0NNz+h6pubVKgwIWTO1slGl5krYYSRykw1CfdGmARDc5iBjmd uF7kFyuJLttFg9wLvW6hcAq4Ea7edXCNhqh1iRdLzhRgOm/qZBgYDb/iTJxf KVJA9m74vgu3o2GUbe7U2WkyMLnFBpdmRsMTQ8nWvh6cZ1XTpo89jIac77kJ QzVkuLXx6OW+8mjYtcwrw00gQ57JW6ult9HgpmCfRdyH62vyT42V3miYaeGz pOLzbbTlqOSvj9Fw4pbNRPEAzl+C/szr36Ohs/btS86UeUhdFqrZRhsDgxUh Hmt080AkxTGyScWA5/0LKiGds8D3onZx78UYODLh+PJd3iw0kic/71OJAWN3 K41o31n4oy1bzqkXAy3VnK1OfLPgdZhicMQ9BpzC398TuTUDNpXXik8Vx8Cm henw1K8poPsekHamIgbc6UK7udqnII/jcfC52hhQXL8+QJM+BaOBNDoX2mNw 3jxaRD0zBfqXKzbkJmJgmPfq1Be7H6DyZe9VjUOx8PjDI8HR7kkQZvhAdYqJ BWenm8Gu98ahSmj5hEZyLHi/3ZRktBsHmWusZqfuxsJpTsNrveLjoH5XrXfx USzI7che2DY4Bk5CqNy7KRZ6ouv4RfeNQYnGY7fQtVhwCGf67QEjIObRVmS+ GQtnDzg84/3+BV7emRhXYIgDgjm9nlfsF+gc49am3xcHx1Zljgh9+gxk9+Sz Mafi4L8D3OrbQz+B6B3/5VSbOOjsSKqWo36Emhd3hL2c4yCovF/zbs5HkBur stTzxK87nbGp0/4IGoLU95zhcfDrInpwve4DuL6wrMrKigMtnxXNjcRBKP+q 7lU4EAc9QSDKbvkeJOgcnpI+x4GIqYDkxpH30CgQ9d1+Ig5uNI6Sir72Q69b k+7JhThg49Vo0DXth4Xt4uIVu+JhR/uZ4H7bPjgjwLtarxAPoyGJV5okeqCc ad/kMdV4sMtUTcx43w2i5B19SdfiISXbQKLEtRuEKpeKbYzj4WnSg1mXJ13A J9Nustc7Hk7k2PyvhjMNp3rRwnhFpEyFJkO0m0gSTlHqpaOSImwhOoZtDHGK yFwKdbH3fxIVEpVZhmxjKMqQhlNJJCedJJI56aqc/eHej+t5n2c9a31Z6/19 eZU3bmmDrPnxh8dyEnCgu3Wtln8LKC1O6cvbCUiatzDfXrkF0nI26eAnoOaX nDH9pBkSXQYhcg0JqIx5n6Oi0QwRV1mNe90JmMgUPnT8+0NMB1UnLpfmIjBK rpdd24hAu6Koc0u5Ak7zTV4S2ohJ/Zt+wwpcqKxyOFqq24ixubz9japcbK07 bEvwGzAYx/np9zsXNhIdir4199F9TcytKZCL557tGkHD9bCL+mWhFc7F7cgv uUoV9XjtOrEr9RwX4z69fpFR9WhXfbvcn+BCjT1p5bKiHk9Ki9qUcrm497nq 0se0WtQ32egEvuXi94HJ1OCyakgL/3nd+wMXO8p/8wy2roaTwQVJ589cWD7P 2d85XYXZiopPB75zYVj+oPOGYRV25a5IVZHjIXOx+Mm/31egJv7N/McHediW 8dyg0pEP8ZaJk/fZPERIiRedkuXj6Hzxd+V2PMx9JE3tay3DTLh+VYYnD9fE c1nyemXY7pfqe/o8D4XaxQPSrDuotHDsYNXw0E0PGvSuKcECbpDRigYebofD cfVAMWxbecWSrTx03ie0dhYWY3p3fdz3Dh7eWUv3jG8vhq6OisHTCR6MBYA7 36EI9nEnrO7KEfhjybVuE6IAUTk/F+quILCz+qcTa0sBcpsu3itRIOB1i9Cy eJGP/wplaGSzCDBJybrJ8vm4EvZ8Ab2FgGJsDWlcnYvO49p3PU0JJJcG7F2m nY0fXhvNss0JPKhNGRMbyoKSJ+vvfjaB8+brjT/ezIIrR2auhx2BuV0/xswU sjBqPWHk5iHoP/KVHytzCwsMStuczxLII8zvTG+4gY078/64fl4w76so3rKR TJhtzxx+FyvQuyj1sbJMMDq0tBOXwKzkZZfWPZlQVvW3crhKgCfm9/bJ8Qzo LtHutisj4HFl3VXJt+mwl9p4/EoFgYaboisrCtIRIc761VlNIPbpHdNvEelo FJFRPnKfwGb9klINVjrMZ8ZdbJ4SUDJViWQ+pMHzQ8ln9gCBZWEHJ1jsFMT1 5obRQwQWX3OVcJ2fgsKeDIkXIwLd0XuWqbiKydfUZsspAtNG+kSNylWceXzS 31yIhJKy1M/WX5eRxNeaOahI4mqpVLxZbxIK1VnaYcokYkJmH5zMSMLDDBnv PBYJs61JoxauSZjiTnaJqZFIm1ceum3wEqw9+FUPt5KgOyKFHH4lYuny7SEG 5iRyFK9ZbtjLQIOrVuLHJuFiN2AztJjBXmH5wTRrEu3NitHGPTQCR2eO/DxK Ip5fkHPvNI1XzXf1qo6RcHxa+zLqDoXEYMPv2udIsOU/RpXuIZE/smWLSwyJ SvddCiorSTS6rT5GXSRxYKftgkWCvScthDpHeSSkVNSKTa8QsFJ7UFGQQqJN M+l28xAPsm+MT6/nkyBssyw0YxOgbqFXZF1Jgre7s1ZvVwKMmlQ/RdeQkM3r XiU1FY+A0oW2H+6T4Ky93y7jGY+XcW3brj8lcSYzgTI8HAda3/zbygESHosL MtUtLwr43tKPN0TChM31vi0lqKOs+oVGSXQPFxV8E/iaS822HUNTJITX9vk+ EfjCZCvn8lphCnt6EHeIHYs0n5NBHGUKVgWJstTZaFzjBYy8YlFYfVBsnqmA k9JLAj0OrKfQ8WyQyJaJxvXpEBsdDQoDvUYBetnnceP8uW0i+hTS2XUSca8F XJ/CfMuxofAgR7h3v1UU8uou+SnZUzB473VLdV0U8t8n91MOFMgj/Tfjp8+i YENqR6gbhYlahZftaWdRdOdmuak/hY3ia4qNx86grI0fNMalIH7rpUW9bST4 IxUjbhSFvnCnD0GLBPWSao+uRApOJT1NInURqLCts2lIofDMe9vi9A0RqPrQ tC0xl0JbaFJc8Pxw1P94/U33IQVpzU9vcv8JEdz1vSYnWyhEtFkPzssKQcWc spS8NgrGOqEXvnqF4LYwaaj0gkLyWE5y5mQw0sT3xwm9o1Anobx1UjIYYQqV Sk++UzApnUme6xCE00rrT4j+pGB/tzIHakEIUE5sMJhDCxx7ntrsVCC815zw LBWhMeFR1PWDDISdumpJsgyNVX6P/Nsen4Ke/uU9LptoxOix5C/ZB0Bnl2hy iiYN726RRyabA6BpcGqwXZuGv9TinT5CAdhgZMEz3k7jxdL2e6P5/lh+UKxz 0z4aIdrxF98J+2PKPthn2olG+CONAY+mEygJPUInMDSe6/LVdin7QbFsvHdd Mo28yNQj6PDFheE4zfqrNDYZtoXO5fnC0bn28XgGDUtp2Zq6Ob4Q38daYFtM g/1GJLd/yAfuS76ErX5CQ07TM2PZRy/8dSDmUfVfNH5r7WOrZ3tBP3rVysPt NBC9nOn18oLMtEV5bDeNS4mHzq8bP4b6t/yxoUEawrLpdz+JHoN8zhn3clEG X1pEndrNPBDzfkWZ+SIG7nc4nLUrPTAuXyo0KMlgZ+DA6Zk+dzRz+9IVljI4 ur1lUjvSHYEBJm/OrmGgIJWTW1DuhmeCD3/QkEEfpySFC1fsCC5I6zNiYP7V xChpiStulez9EmHM4NcwZ4/0RxeErw3+T/EhBkTWnAAzrgvUFvU0LnVg0JLf rNX1DweJRkEyRc4MruxbtsOoioM5EdKc/W4MLIYndsiRHHSM7p4N9WFQXjFb 2Q8Odqt1m8r9ySBa+POC/mUcFLqcSin0ZxCh0j5hPOqMFamSn/cFMei3aPYW b3HG//Lg8P88uH8B3kk7tQ== "]]}, Annotation[#, "Charting`Private`Tag$12701#3"]& ], TagBox[ {RGBColor[0.922526, 0.385626, 0.209179], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwU2nc8lm0UB3CvNEVFMpJKkogkIeGgkojslT3aZK+s7L1biiQpQpJdOTaF 7BlCZD+PUCTlvfzV5/u5ue/7ucY5v+vJfvNbGla0NDQ0GzfQ0Kz969/54uSQ ezxO+tEZzvnthJ39JbPpLvE4X3vVxh93Quq3xhf2jvFYMjyo1f5nJ1TNzrPQ 2cTjrfGSlUJnFlhPLzvHaxaPdIdz3HqcdkEgdGfcPBePR6O77v19xAa7FKbM TpyJx6BHWdeLR9gg7cI/tn+y8Sj17qq+mRA71OjzBEVJxiO9YmyWbxU7bHC0 tcgVjEd5oRL66yscEPRyE+cSczxeep23lZq4B9he724r2x6PPg4Fn5gW98DL fKHQEIZ47AzzdjJS54K6Cq0ljo3x+CPngbrr5r2wqT+5XXo5Dgvl9kdyndkH wTtORvgNxmGOwGYD2uH9wMZ24cyF/jgcEhum72HjhpdcJn929sbhzL+U6qtq 3FAnEHAtrS0OLwlZ0ZeWc8NmhZazH2viUF2I93JE1gEIdb/2jzErDl29oiPU Mw/CsfbrTrHpcTgZZDrd9PMgdAvenGZJi8P4hIUGU1leODRk08v5JA5FL/wp ru/mhapzjgX8MXGYRid1QoGVD24+dRLMjojDzgCzbd3X+ID5j3PqsdA4ZKz9 0fj0Ax+YZ7vFSvjFYX9dhfyPq4dhdae3jYITub9qmxhzEz+k2fiMfrSLQ5Un JZW/BARAte6OoYpNHLZuHxKXDhWAx7f9lbSuxOF6C3HxLcpHQHI4hNdcPw7Z Jb/tVx0QBMfX8QOe0nFoIbDlTfxLYeDcfE/7P0ly/w/3xh5+E4ZK8/sN/mJx SNNP/ydg7zFg2pVQEnY0DpmLDFS5E47Ba48n9x7uj0MzfpmOvgQR0OlMZtjD FYd7E3nSQvpF4N/RFP9kjjh8uiBtK7P/OFz4lmr/gjkO/1Cer7S8Og6T5zNU 89fHoVLmpd08n0Uh5tmragnaOHxwYOh8HPsJkPibKfX+XyzufCLfKnz5BATl vOavXIxFLleBYfp1YsDDmr+hZSIW4/eWyPYqi4PJCJZON8aiSVeP6gKXJGw1 0b706lMsbmY8nnPbTRKKeiYXr9XG4rEhcQPjDknY3sRybKwsFhlFjty9EHMK KopvPBt6G4sz++rnHTikwUb0P9nknFgcc44Q9fCRBo7X9/qMs2Jx4e3XjO3j 0uCQWs7SlxaL9jKNfUvvZIAnijW482Es3v9i9K3ylCw0b87iuXsvFt0Pswno O8mCh798uWZcLLrU7eppfi0LHW7Wy83hsfjntEKH8yE5CLSsvFnvHYs7zlUZ MnDLw/jJW+plVrHYb2OXyqt4BuLz6Che5rH48DVvXU/MGZA9mhAqbRKL44PR IgV9Z+AhT3VliV4srouzylx1OgtK23aL5SvHYs23SxE3CxXgV0hOq4MiGb+B wYc09OcghU7hlsjZWCxnlZWdNDkHf37bvnwtE4tWUr8SOhkUIXOkhiPjWCwG HU2lrXI/D3omhoVXhWLxx0GJqLye80DX+0PzkEAsSvbOXhWSVAKjJs6IVJ5Y ZO5y1+ldVQLGEvvVJNZYFKP5qTOUdAFso7hG4v7GoPSh4iVVdjU4FPOux3w5 BtevE3iQoa0GA7F6TccWY1BYTuwkbZwaqNyLLWmajcGxvy2thdvVgT9xQwz9 SAw+TP3VXc6mAUNJzwJ7B2PwteEGU18jDXiQLOuR3h+D1LJrmy4/04CNqe5X znXF4MnTspKZIpowkkGR9vsUg8ej1d43m2jBo8yw4xq1MZjbEXxMIVsLNLL5 Du+vikGO7u0FW/9pQfkb8534IQaXaPYKpz3VhqSizsnlnBg00b/LU/lbB/Rr Su/b34/Bm3UcmQPz+rC97lKEXDx53yNyos8NDKDu45Lv9pgYTF36mipSaQBi jSI22aExOCnkYFv98BLsbE87M+kZg22W/72rNzKC+o7TksXuMXiQa7fGxzYj 8O0aPBrsEoPi7/hVe5SN4Ucvx25euxicOhUmYCBvAp+HIn+YWcag75k9Rzc9 N4WAbwJjwmYxqBlwXXZ83BSkRuv6Vo1i8MTXHNV/gmbwapy2LlE3Bmei7giO vjODYKpzUo9SDH5VMVTTHDMH+b/GyurHYrA5lS+p19cKtmtM0nwRJO+Xb3xg 26gVfE1zKrDkj0FnkTGK5PnL4KEWvt/1QAxWKZxLfc56BQqeFS8mscSgtdP7 1zs/XwX/pTNZfEwxSE8/VqAqdw00VZrNcxlj8FP2Vo3hgmsw++t7Y/VG8nk6 N3uqpF8HfqWdqdO/o3E8YOTkp8ybsJT0RN/5VzSKcIoKWIlaQ+08/zaa+Wj0 de340FJqDZaJcu7M09Eo+/yniUWfDSTN2qhJDkSjZoTodcEkW2C6/3ElqCIa W47flLRUc4DBKa3cHRiNLlZv9oi+doDXsoNXHr2Lxm0LLqw7tjvChclfrdl5 0ejt4Jd4sNsRAqV50jvSorGG8c3v437OoBX72tjkWTQG32bQGZ13hgNjkjsn nkRj1cyhBeYrLlAWre698iAaz9qPPubTdoXlb17aB8Ki8ceNfVYbNNyhTmIL fVZQNJrERpc4dbvD/Yi7ZWL+0Xg+xqx8xuw2iIpnCih5RmNvyPFT57w8wCa0 5z+7W9F4aGzZYWrAC6S+WhYu34jGXV8yz457ewO96OxN/6vRaDUW8EeFyQde 9m/ovm8WjRk/TXKq3/vAN2HR7FLNaNTr7nx7gt8XCtI0Q/zUolFwhVbf2d8X QjkdLBVVotGPQd327aAvCG/K5WhViMa9WefTtZ/4gdfXo0GjJ6PxV0+B3Bux ANDQvmieIRaNB2ozBZVSAuBgvY30rePR+DXYOUF1eyA0FGTNLx0h79+1h6dn PhA4IgVMt+6LxqBwi9q63mCgrFM+1cIZjX2ZcqmRl0Kg3O36rnvs0fiSdy5D 6WsIXLVKb9jLHI3VUYMXF6ihUCB16OTxDdHYLbhspicRAaG5CjuXaKNxcctN hV1tEVCi1jDgthqF9m9vKrnaRcJGPiXliLkojNurciK8OApSOs/y5HVHoaPx o31TUjFwvsK/V7o1Cmlo9gWfT4iB2azK6Nr6KLyYP5s29jsGZALk/vaWRqH+ zw1z+8tioee4dOd/z6Ow0olByvx6PPjs9QgPS4pCSea2xsgv8cBL/06e5UEU DoWz0QRevAuOwxKv+cKisIS1TIhH9h5sjxENvmgXhQXpPWfsFR5AoYeDTM/1 KJyj++cs3/wAjK/mLphbkp9X/coWafQQMkHYzFk3Cv9lPX7+1zcBFCkCkonS UbiebdOdEyuPgdpzfZZXPApj/ti8aktNhHvV6Wk5wlH4PohLq0k9CUYeH2Ku OhCF1/LmWsyKn4C38oHpyc1RKCE0/M/U7Clo9ctwT9JG4YXIBK2ulqfAf8tA b+JPJEoJlWuEnk2B9tiYqrGZSDx9db5yh/gzyODJWv7+PRK/ewmqc+U/A++C OuHvXyNxQT6ioUssFfh7Vx+PtETiF9aPow1nn8Pqjd1t3z5F4onhg+OKbc+h /a/Y5m+Vkej7pjx/zjINvPfbOA3lR6K64oi60d0X0H61T2XgYSTuifR7kC+U ARnLi379sZEY8unBfziUAd7hzCV9YZG4uvjggGjCK+DPUeL94hmJ194WGXFy ZsGq3GXDXudI/LW5enl2NAva2+7E9tyKxIL3ji4L+dngvVj0r8ssEv+rTDv1 WjQHtELaRbsMIpFJ87ttQloO8O+evd6pGYlOBbsZGDjfQLvMoa72s5Eonx9l uY4pF/gD775uORyJCS79FY2CeUDD9ma0mTsS3bfGugdiHnSkN+xu3h2JOgrX n/do54NP47rgzwyRmE7lGKdGF4C2yd7Sxg2RGK4umbRBrBD4f0guNKxG4PWz wTtNBguhY6e9af2PCDxZfqAr7GwxZKRF3Ps0GYFM8+VMSFMCPhLpDR+/RaDu voU/P8pLgN9wUKKuIwLrnOh0D+q+B59nqjuqiyPwxfBoJrYiaJ+4fq4qNwLH pRvjf5iVAX9tgGflqwj8JzWienmgDDom30+UJ0YgM//KPbdv5ZDh0b23/B55 H42leIObFeDDuKBdFhWB3YptV5/9rgB+EYGK0jsROHvO4sfv/VVAU6Ww9ME9 AkPetR5S+1AFHdrmQh8cIjDM7tShJ0bV4OP2MOGdVQRyjptWY1YNdJRtdCg6 H4EXNuk3a0R/hDJTkUvd8hF4gD0omkbrE2TSGJ1eOhWBVzy85l7uqQdf2Vxm CaEIVB95XOVb2QDCZYZ5hUwR6OtXlvFBqBk4TYMed9FHYOXcvYrIjGbYSJPr v0gXgdEHN+nOHm6BAdioLb4YjsbvGUKfH2+FcHzzs+BLOB62vCxzxbEdXE36 +jvbw7F//dcVVcYOsFjdUPOrMRzbRa9fF8jsAEkwvCdWFo45VfVCXfOdMFa6 QbwgNRwpHX3SW9/2gHzpJdd863Dc3vf1TsfYVxAyDjTtuByO32QGTb4YDwL7 vxzFnybkqY3U+zL1gzArvYH9hEY4nuX1Elx4MQSJH3KK88TCsS2m2KXI+hss vV//5+1qGMZwinHu3jQGI4bC39qWwlD9ap+BjNsYNK0Y1M//CMOww/8lnJoY gzSpnEfHR8LQPrhEYrZqHLTeG0i9rQvDujsmmZFWkyBrGMDTVh6GtfrvQ1tr J0Fg5fXW+ZIw/HYmKdzo0BTQSq3vF8kKQ/r6t2JP+qdg5svRao20MOQz+VW/ UXQaum8bZNk/CUNxGqMvu4Om4fW71565MWHo8D7oUCP3DKQm0r5RDAvDQ8+4 3Jwvz0CCt/bIgH8YKhitPzCUNgNRZi9ZnbzCsOlgutHqtxnwP/1Hid41DN2y +87U7KGA20FVr6d2YRiYntMlqEUBm41P34jfCEPnSO954SAK6NcrsFkah6Fe 7ZDyum8UUM16qLysG4ZFxYJ7O+mpcCZq2itaPQwl1J66Kx+jwkk7yOVVDsMZ bfXIG5pUENKMHX1/JgxN6YqGZO2pcODEKJumTBi+qmES7o6gAhurxIUJ8TB8 ZscgL5tGBcbfod7ex8Lwc8e/6pB3VFj3pT+XRSAMlwwO8NY2Usn8CH9/xROG 69idjbf2U4GS5McuzxWGVatuLTYTVPjm03mhmzUM38fm71k/T4Vu88M+NjvC 0MN73fz331RoPOPxlo4+DDWDfo0f+UeFCt6m7wl0YahrK68zu0qFok3cHMf+ hSJ/3f3DysRZk44qtYuhOGcpUqW7QoWUhlofox+hWBC42CG8SIUH2Rx585Oh SJncK/WDSoWIaOuxkJFQdGGJHnr7nQq+9mUc+wZCSV549zTuCxVctJhVC7pC MWBfo+Crz1S4KXb5zoWWUAwWrJrfWUYFc7bivOFPoRhY8WTT1Gsq6C7Tj7tW heIHkwHmc0lUuNBnvHtbaSgOK5yXkQ+jkvX/RvV5YSi6us7t/+lMhSO+uvkt GaG48e3Jy0NKVNhvmTF+JTUU++N2VCoep8Iuhb+7/yWGopEAa1klBxX+2/LM lz8mFLsVRsMVxyjwa+pnflloKH6V/n3VvYEC042KEzr+oZjEPbS07Q0FOmMo F/1cQtHtUE16lisFXrFL7ukzCsWeV5nNt9dRIPlPuJq9bigKmeU7PBydgXv9 X/02qYdi8kWGoru1M+DzNGBS9EwoSm5YztIPmwHtwy2FEfyh6Hty9Yw48wys SlzVgMUQTGc8xJwoMA3c5ffXK8+GYPTFl8/TGKZB4Xxtkc5ECG79fmT77tkp iNTn3WvzJQQ9xPucdAumgNN9ZOoxhiCNH3t1mOIUyNLufPKyKATftXIPGgpN gWXoaY28NyG46dGQT97OKXiVkFJU/ywErxVGV/0bngTJd6YBy0EheCfzrObB wEkwPh0tseFOCFI0PIs0bCfBtx6ndriHoKTgX9dtlybh4xcujcM3Q7B6MrJN XGQSpi1U15+wCsGELDunZ1yTsH3as0jWOAQxfCwoiX4S9Fb6uPTUQtDw2L08 ubEJcv7c2mpxPgSFc8vHxjsmIHmrVMAt+RDM6qku31M9AWOcj6YCRUOQJ0Hy heDzCXCW1i/KZwvBt59/MTTdmICE6uAb5TtC8Kfi1okG4wkoVSniatwSgnOS PUrqGhOw3pg1YGQlGOPNHh2ZkJwAvu8KErM/g/HazSSj5aMTcMHGeeoPJRhf fBNwizg4AfFeHerMQ8E44RIaLso0AUUb1q/f2xuMuT8bNihsnoC+SNEi/rZg rE0qs2unmQAaVssbYg3BeGo4MGBgaRwOPInjkq8ORt7RxEXzH+OgcKiyRaU0 GJOCTW6bTo7D9ddz/vqFwTi/zayi49s45KL6lG16MMljCgbc3ePQee5OkkdK MCrK7N282DoOy0056sGPgpGGsVpc5vM4cOkN0sXHB2O4+7X4Xx/HQW5wW9GT iGD8dd64katmHCyvwo1XgcEooqcZk18xDsGzNlyF3uTzugZFFeM4ZLomtVS4 BuMZqRGXwx/GoZnms/9nu2DkoBX8s+7dOCwE/xXvvR6M7AW76s8VjwPrDsGp UYtg3HzIKmG+cBwkHxom/TAMRp9Ixj0biI33h6v/1SbXGQ5t8ioYB9/0d3Sb Lwajrb8kkwFx2rGpwp2KwUj3c2buAfGnYo4b++SC0dfX1eIk+f0ZOSWuI5LB OCahyiVZNA4cW1M4s48Ho37YUpw3eb5i528OYcFgXM/4vW0XeT/nZHX2XN5g FG263/3v/TikXk9nFd0XjHGGkYli5PO1iv63q4CdjHfPlb0fysdh9Z/eTgnm YMzoy7oUQ/rTkY85TCVbyfhyr1fPrR0Hg7hNO6Q2BKPemd//uOrJeBmZbitd DUJH/R2XO8l45x8qYpD9HYR6T94HdZH52P7+ypYz00H4aH6R7u2XcZAJxE01 o0H488OLK2GD43BDjXWj4tcgfKbJG5c+Og41IzXrLrQG4UC/8KW3s2R8s7lo P9cHYUnkO7rEX+Ow382ZRq06CL8o/oyuWxkHDwbev5pFQWhz7YvdEFlvImIB vy4lBeFLaT2NVd4JMKXpX+i/H4Sq2+Y29wtNQMQn0XmTmCA8vlRNXRCbgHHj EaqFfxBulOS3azo3AU+CTk/cuB6EgebZ3jtvTkCD+qOxGYsgdO8r/PLSaQKW d8+P3jIKQtb9Ux9ueU+ATk7KsINaEB7JHIWYuAnY2vNf322xIHzHqmG4qXQC XPnLPofRBuGO9d4sVI5JSFtgbWRYCcREw24NiUOT0FZ6qz7qZyDWbut4knp8 kvS/vXVx44G4IrPBc/jCJIzc9ip/9DkQXRzbCrp8JkG9USrvVUIgGptKynya mYT4588sVeMDUUaQdU/Qn0no9tzC8iMiEC+s+2Sjs3kKTIW6ncTuBCKFovaU 7+AU2EQ5iJdfCUS1rl9FPkZTEKaeUdIpGogGOa3qAs1TUN3BWv5fUwD2JKy/ 2VkwDZuyvexS6wLQOeTkhm3V03AhcHT/uYoADOObM5Zqm4Z2sbe+4fkBGLJd qtOOOg3D91XPsD4OQL0DHluFD5H6rB9Qe+RaAMrUP6aTj5sBeZFplybzANxx Qm7ZPHkGArdo8tkbBmDhvl8tN7JmgPHdvpDCiwEY/+Klkgip/5yc75XkxQKQ J7KA1vv3DJwcmGvUXReAkh/GbgXpUSDTUOzfrRV/rE1MWai3pADXFzeh4J/+ ON3MoDVuSwHabpqoojF/1NG9ypkWTIFPLYxq7A3+KM6naXSwgAJSaho+x6r9 sccndDdbOQWyP9/NOV/qj4OXvU4O1FMgtp5zh3uOP/76uKtqeJACBtX8rb3x /shl3ZVRvokKDadtaOcj/DFuXVL7aSYqyFS8EaEP8sd3V8d07u2mAjdKxJ1y 88f/Crk1XglSYapIQeuxkT+e2D41HXmRCsbiof55Ov54c0TQPUKXCs35jXkN F8nznjq2G5hQIS9Xi+WvnD9KMj58aGZDBY9M804jXn+0PHX9PFcoyTP8aRuc 9/rjxtLupZhoKpimT4hFsvnjvr+hl9rvkbyVZnu/dIs/hll53KtOoUIBT15t 5zryvooN6Y4vqcD3bHGRsuKHxoVG3+eyqLA12UtvL9UPPc+1hRgVUcGLqyJY fNwP059f11L6QIXZx+uLLw754QU5520bK6jQ/jCc3afND/cNrNP88YkKCmzN 5x80+CHtjy1We5tIPrrH7J5T7YeMt+3cudqokBiX0DtY6IeJWt/nonupsJ1p YMvvHD/8paBMu36A5J/o/ad2ZPhhtZq/tfIQFRYYrW4cfuaHKd/fxVuOUOFy xMtHco/98NMJmj61MZLX6Kfr9e/6Iav69lfbJ6mgFHp0xS7SD7+1qFunTpM8 GVRgmOLjhx4OB0PP/6BC8vrl8BI3cn9dj4ZLJO8x+Ut/aLX3Q3cTuZbTP6ng T3tnZvKGH07/O7GTluS1Xz5Ve9ZZ+eFfxT/M95eocHV1o+puYz9EYNBYt0yF Xk9lr+O6fkj3Mljj3B+St1Yis5XV/PC2tcxjC5L/St1bByzO+6FQp26R3l8q SJ6SMZiT90Mvz0txHCRPFvxJ7/CR8sM/2xpl3hGLvGdR3yZGxnvA4+gpkiez Pe40JB71wy0lWV8SiPmlZ84dOeyH2/6efNdLnPZXr7KE2w/vXj977g8xd2mV zHlOP1xcUl5eIU7yEi7pYvFDa/M/FweJOeDxicvb/HD0n3j1c+J7qxvfLGzy Q+HY6S4VYqYyhyN+tH7Y506zsYe8T6TP1xc7VnzxX6Vu6zniLXLKB5J/+qJ3 UnJJAvk8gf8VJglRfXHxlK5cK/m8tBXcHB/GfTGc8nKcQsbD0zfyrvKwLxYy 2B7/QcZrSX55e+8XXxTXoXveQ/K147rL4Vc7fLGvXK38JRnf2cqWjYuffbHG 6tFWEzL+N/2l/QLqfDEo/TH9XzI/42fS/zFX+KJBxdnTfgtUsFzP4p7yzhd3 NVZJzM1RwTBw2hazfXHTvmH7cJKvuxX0plVe+mIZ752KohkqaG2sutL3lNw/ tXm0aYrMV/Aj49/xvugZIvyhjKwnqVClC8dv++LbjNxT78h6LFIqqC139MWT 9n/zL/RRQZSe+7SajS+KjbXxNfaQ/Bz++6S1mS8ydxxbl9hOBc7Il4denPNF 1Y2/CwM/UuFPzIZ1u3f6YrKn74kfOVRw1rD3SmfwxTm1qD3ZZL/NMQ38Ft/o i9zlLzvMMqgwGZc/q7V8B2uHUsNePyPr667lQOTgHVSev/5i9i4VSh5WFNNm 3cGa7kWP627k89PQ529Iu4N4/lOPuxMVtl3RzNny5A5a5g/bBtuR66IjaUwx 5H7/RUsnXqMCQ9P6eG6nOyguaudYok/qBd15G3npOxh5w0+QV5LM742Yawpi d3DWa4+6rBgV8lt6LJWO3sH0Wr8oYxFy/cn1Sxr776Bq/eGWl/ykPp0MVzRf fwez0oKPeJF6t/FWE7dvow8mlp0ScvxHgdwOVq7AGh/MckktXFymgKGUKXso +qDGoc2a/osUyNn8Y1vsGx+cKj71oXiW1NdUpr9P7/qQfiE7/YicH+noLy09 j/RBCb7aJBtSf1/bPZtPD/LBQyzKxy70k+sgOvnGzQcd3fd+4OuiQFaPdle5 kQ9u0X7mf5PUbz3ZpNZqHR+cNr2p+6iO9IMX3xs/XvRBm/j/bDqrKaDj6FLV IueDT/QKl+3KKECz7eGboYM+6H4tSlme9IcMp6HMUS4fZBFqoul6SwHtvsMv J1jJ8841/nEl55uM9JKkH5t9kOdyId9oJgVeBBexruvzxlXPml7TVArw2V+x v/DZGwVY1dxvpFDg5aVdjXfLvHHD85ZAv2Ty+0KOvnzPvVG20HFv32MKCLAd 6Le7741fH+yu5nxE+tt/reLvQrwxQbRyy42HpD+1H51RsfFG14rPj4XvUeBo 6cC5+6beKHq+6/eLeDKeLyJSBjW8kW39CTbBODL+7lO6DuLe6MP3ONs0mgLH LRNy3x/2xlfmU0LboiiQp3KeYQMnef6G3XfqIyhQsO9FxQMabyzKK0+2DqOA +BadPcNzXmiSH22jGUqBonk6V4FRLxzaT7vtXAgFTva/bXXs8sLoS5PeiqS/ ltSYC5Z+9MLDjEKlukEUOJWzI3jjey8cP9dQ7RhIgfcPy4bVsr3wUeFwzJMA Cny4yfXgW6wXvo6+bcLlTwEZnca5IwFe2CXyVcPejwKl4KHi7OKFdde8KW2+ FIDDAi/xmheOFIsfPk1cxtRLu9mQvM/NHb/xDgXkVoKNNFS98AC9kqYSccWo eNEjWS+MeXrpyLAPBU43fWcaFfHCnwLTLkHEVUV3rYUOeuHHbAqfJPHZlDN1 LqxeeDE86tiyNwVqwua5yzd7oQ0D+NUSn3NK8dyy4olOzbmMKcR1xurdmhRP 3L93tjKE+LwizfHEQU/s1lCM9SL+dOx1xPdWT7xorXPVh1hpt/H40WpP3N3K IBpFXE/HcNqt0BNz75UMZxBfoLxLrEj3xAuDNGZtxA1d15foH3ui3FBPwiby firl7JrakZ6oIpd2W4n4c0ZdVpKPJ3bt5qc8IL4Y77Jp3N4TY7ND+uaJmz15 LY5ZeeIuHhXhS2Q81K90fHDX9UQZbdfWz8Stav5sVec9sYbj2itVMp6akscd GKQ8UUN9KaWXuP3AcKOOkCeKfbJPXpsPbYYYvuR9nhix4UHoLjJfnb/Ab4LJ E3XfPjtXQ6w7SOkXWe+J1oeVPtwh89v9MVHCY9EDjTKxWZHMf8/jPzOMfR6Y sdHB4jdZHwaBGYp6nz0wyiEtY5isn95b+s+elnng99Jne7vI+uqTL9QTfe6B 9vdb9gyR9Tg4bl+pb+OB29sXuZzJenbUsc+LMvNAnRzx3CcxFNhcZfe8WssD 9d4fFmiNpYDIE9ugY6c8cKyt3FL9LgUCtG2UN2/ywM+xmzYUJFCAo9JaCv7c xkdsfN0HyP7LFrYWdKLcRjY6m4KHieT96W9uG2q/jb8HWXkTyX7lr7jWVvT0 Ns4wCWWuppH1efRaFSX+Np7juPsu4yUZv8Sr+TzBt/F54WaqYQYFPFyv3I+2 uY2eXjeVOrPIfAlZXbp6ivy8ykN/9nwKODwy/cba4Y4Fqnc5a6sosGmzabtK nTveuW7I0VlDgcfOJtV+79zRq7tWZZLUrxp14xfUp+4o1WrXub+RAmybDG/U 2rjj1wtOPz52kP3lqDvvvMkdPWYH5YbHKLBBVXVd5yk3/HqMf1CDkfTfjRsX fgm6obJU+F6aHVSYKMcR1n1ueCzE/3M2M8mzJ47V6NO5oXkS78A2dirE7tkZ 0t/gimzKDb59B6jANdPDOGrkinnxvEFeJ6kgFm7FseDtgs+qZMTHLUieVOCi Z7F3QSaxqrLbl6nATtP154SlC4YoRahsJf1nxUGx30XRBZMz7v0+QPJsxSWB 5D/bXfDNx2EbflcqqAr8OLguxRmbJBgbb4dR4conj2NMVU7Idiz8d1A2yQOb Aov2Fjrhh0APhaukn9orRIFghhM+/eXuejqX5OOKpyqK0U54/j3VYDKfCtEl Nde8DJ3w4eMTvUvvqXB3qWk27KITjnjZMrwupUKCWI/LQ3knDPt44bNJGRWe 504F5PE54R+6+PacStJvM7anTC44os5B5S3bSb7FcfbDS2OOaB0+V/qwngpV vAdy1n9xxPXmgRV7GqnQlHKidF+5I/KY3Uza2UyFkQSDXp0IR1Rrkd71oYMK jGGpTJUHHXHW4uCrn1+pwPwx62EzmyPSchSf5SZ5l21j4b4Bekdse5exrDhM hQN+H4V+/3BA6Yf6b/1J/pW4TVE6WuqA0feT7PLHqSBdvNgi9cYB94MiJXeC CvKLNPpKqQ6YJ9QckUHysIoD8xWrUAf8ygOywSQPm9+Q8Huk44APdqs1/yX5 6Eq63Jb08w4oKa2NDbNkfMeUYgqkHNA1SIJ6l+RlFwujJy3cDuh9+CUvK8nL Hk8v835lcUANBo+TTcS+X29lTW9ywMaosmd3SB4Lv+T7biPVHiP7HR90kLwW 8zBMnmXYHvMuBwu7/CJ5syv+I3eHPb701z/FTPJdsuaLLul39hi4cK9WkuS/ 5zE5xsrZ5Oc7Z/RqiDOaikf1ntrjrHWdxwWSF/OVG+YdguxR4m1LkiLJk2yd ke433exJfQu+WEfsbqr+n9UNe6zZs7VBjuRPGadORp2L9qjlx2DATfJp8uqD u6py9sgUtzcgZC2vhl7iPHfcHsV3nng9SVyTNHhYgtUebXJpxR+RfMt3+FmO 8GZ7HAvsz5kkDn1rJX74jx2yeVHNREkenpbmK90/Y4cqszT6rsQX6ybPcHy1 w3SLw88LiHM1suqZWuxQSOyDNpV4Z/8tDfpKO6R9ZeDOTfK28xWRnnX5dpjS NsKtRtz9Y8FkJc0OG1m8TFyJJT0Kvy88sMMtjcGyj4gfb3C3ngm1w7uiTzuL iP9FSy2MethhT0uySAux6e5V9wEbO1zPkGA1QlzxvPy/LlM7dFYY8pkj5hH2 D27SsMPF4fm7a+eFwBKFbXVn7FBMO6RglXjizOZ7ZWJ2eI4lbOEf8YWmes5i Pjv8Wcph/nvtPKIf+ewNhx1e83ffQSXePqLGn7HVDuOHeVjWzhf2NsxvUv7Z opp/mXcDcftSh/ijWVtsOLjLMo9YzO9BadywLf5i391xn/gBw6Wz4e226G07 O+pMvHx/T4N/jS3m1TSnqxMbcg9qeBbZosyJPaJ8xKWZKT1OGba4cdH0wTIZ z33iVqY2j23RQ+/kZB2xb/mhscuRtriL4Yp0HPGI8qS1iY8tttdUPdcnVujM XNC1t8Wvi6rinMT0U8doz+vY4pvv+3nvkfm1cVoIllO0xddb61+pEDevFmyT lLRFOWXtV/8Rx++U2iPAZYtLWnevmZD1IuERbsvRcAtp2y7vWyDrbyV6hxd9 zi1cR6eSG0Nc9vxe2ErcLRwa1jc/Qny+KTlt4NItvFb64pY+Wc8G3Pl9KVM2 2Jp43jee7AePun5FAXobDI3kvJtM9tcDlidcT6jWmDr2V5CTON/cdIGp3Rp5 vQ9L3SPnHcrK8JPlx9a4IJ1MF0j2q+mx8V8fhazx3JsSHR2yv88kzKVe1biJ oRpvxT+RerD15sb/0h5ex1gGY1t3Um/4ius62b2uo7mZ7f2xQSqc3RCaGWF+ Hf2iLxpqE3slb9VzEriO6pOMyyKkXs2273h95sM13GD1hGWJnIfapTmNvg1e xd9C1Of53eR6aL+IbvVVFN+st/84MUN30qb69KsY67GdMbeLjL/9/rxc+6vo 9Hzial4nOV+l8dL70l3FyzEvdRrI+enxtmPF+/iuoGH8vzH1FioMWsa9s2a8 goH76/jmSD3lKfn5oWThMrryKojEE2dallRolV/GKom7Rf1NVHhXfLoh2OAy Rj9ZkQj6TPYHY9rnDlniJcErYsTylptauA9dxkM/BsPGSL3+xNjY8X7eCpM/ aTZcJO610Pk6G26F+s9ZXko0kH5XXDQk7WCFwX1ntiyRem/OuHskVN8KY7LN AoqJJ4u+jvPwWiGn2dF2eWIhRvkpu61WqJZmmL2F2N4idaZ0zhJNcy9nt5P+ scxwbU4PLfHWdzaBW8QyFvULz59bYr5EUyYQ+xYJLs6FWaIaxd+YiXiLxdyf cD1LzDzKZVBKzpOqRVr/emQskZ4l58V94liGQppDBy0xSvn+EQdi9qLb68t/ WCB9/OchYWJDhoGNjN0WeCPXdiczcbK57JZLpRZ4k+6P72Id2R+FKVtfplqg KC2/0AAxH8P6bT9DLTDVImBXLfFN8ys75O0sUEDARSqXOKfwI3OUrgUyxJ5I fkK8sPXIrj5pC7xgXScXRSxhHsl2mMcC1Tfs2n+H2KNwlsN5iwUGsvRIOxGX bdXcUzlrjquuifdvENOZ5+/d3mWOQ5N1gpbEioWs3EYfzJFe5d6qMXH4Vnee jGfmSAnl3GpI3GzWx7sYYo4u0/Ial4h3FsocPmNrjiuONc1r1/W2PhWI0THH 8fJzgabEj83WCQ1ImSMOidtdJh4ssBIWOGCOr9O6o2yIebbWibhuNkeHUM1B V+KrZvwnqqlmWGibaBpAnFkQLs7UaYYWO6IZ44ln6aknTd6bYeyWjrFUYlEz danMFDOkT/g9UUjsUvBW5newGQLoMDUSl9DvklO4ZYauckLGI8T/TF1Px2mb YevKvU9/ieULes8OnjLDGZM7WuxkfgLppRUFuc2Q1qxkSYz4k+kTJfdNZtj1 a+atDjFjwX8qtRRTXOV+5utKfM+0Rt3snSk66P9QriCOV32k6f/EFLWP5r2d WVsfUrbaL/xMkc1z3G03WU8RbBz6M8qmmJK7a6sXcegGqsF2YVOsyac05BIH L1QaHt9pih9Yv3RMEG96+qVsrsgEC2yLXhiT9UznGVAlcccEa9bttnxMvKp3 tM7rvAnKd9++2Ef8a7tf05ZeY/yZoPrAnOyfER/+Ae4/RqjrN3ckmOyvQcP2 oauVRlhz83hiJ/EXCa/R7DAjlKG5R3uI7M/W2ZZpSU4jHA2lj2gkLjN1+6Mh bYiWG+ZKhMl+T5StY/PzNsDcRxND59pIfeS05/x4zgDPBs+8eEMcv7R737bt Bng0N6WDk9ST8Jxbhx4l62PZ1VnZRWL3faxib8v1sOVpJ7wj9UeH5rLmt3W6 +FGtcti5l4xv2brI08GaGLDjeoMdyV96mdTJU1qaKOn45vEUccqDL+dE92ni TYFqD6tvVBC3e/vfwSINtDUWUNQn+cyU28Jpw7g61kU/3ib7nQpv/SsMP55T Q7+HvRG0pP7+s80uLmdWQ638xENuk2v5VFTQES+iVfhPeSpx8Y2RZG2qKiat //GlZ4rU68+ng9kuquBYx9jLFzNUeBNLq5vEqISj35qvc5F6r3Cjd3tU2nks jTQ/FkLcezr3k7fMeaxjMfw1R0z300zGzEYRw0S3GlWSfqGjW36Q57MCHnSe aNAheW3q6MOvOy8rYNmB+PwiYp9Ndg/X/zuLk1dnzNhJfksv3scwJngW/Y2X JjqJV3b7LKRHnEZLw95lOdKvohd0sxMOnsbd1o2nHxIfbDx6NeyDPPpERe2m Eqt6ff1yc0YOTTU4TO6RPPd0UKbyqIosBr/pjG4l/e+GveCy7CdAqXL9jD2k P8Yf6LfmXpbBzt/3ea4QjwVIaY/qSyMUmvD+JA5X+nPgBrskSm4ralsh+c6l NLzHXOUkGuknnjhJ+rG5CFeUwR0JhGsm3xzW+jOH3PL5CTEM33SHaYT4QGTr a7k9YiiuJhLOTvo5I62l1Un1E/jjlan8Wr8fmQhs5is+jj6+R3VeEzcZsQXu mxHB4QW2rH7ikpb0U2z7RfDezR3Ht5D8EF3ckLYxRBhjPx4sMyL+ZfC+6J/b UZyQjSj3J26U/3qAMiSIs2fufk8ndmc6uNzwhh/Tf/jFUIjVls9ZvWc/jO/o i5gYSb7hHb7e/OrOIZzDI9kCxCsfI049mjiIb4s6zc4Rt77JSQtV58EjbF0C ZsQvH7btcC/mxqnVK1vciL3u/PK4tn8/NuWN/4lcu94q0vyGaS+2Xej4l0Ks neKaFj28G4Xb23fkE/9nX+pxK5cNr9anHa9e+/sFOTpNVV8W3H1G3KKNWH+H 0mFBDSaU+BT05CsxfcXeVdYzjKjWXT02QWxp9upVx7eNuMPr5Km1fPmeRlwv zu8/NHPWebhEzCcbsDlF4VfpY62M//4S5/yVqJbc+q20wmvMYS1vvmc255Zs +yizf2aMuubIjdc7u35SZeLqE53W8ueu6j2xtu9WZC5c516/llePn/Z7vPyB DgKKCpN+Evc+W6RKcdFDVH2BPIVYjrbgKeB2SBVJ/rGWf++K2NabUpnhQQZn Zs9avjXn/3lnLyt81ZiyX8unUnEjXM8ucsCH2l8KH4ijK5MUq7z3QM3js4cz iefcjhTP6e6D197rdz8k5ozdrLpudj/U//bb40+skPF9mDn4ALDmCItYE9tW VLrw7DsI2qMPDLSIq+Y8n55V4wOr33EznMSULZfEdMYPw1bOmUv/yPyzHZCo v+wjAGd4H472E9/UnFsIyhGC7I4xzfvE9fljZy7wCIMlp7G0HfGgnE6U1qww HItvVD6/9n28wXEeq2AR6Mh4NjxP1ufe709trLWOQ0TskG0Nsaj99mKnfaLA sv7T0fvExqEzKoFFJyDaJ/HCceI3JS9cXoxLQL11nqUO2R9LPndqVqtPwpK1 YBELscy5Syx6zyRBmfskQxvZb5/aGN9uMpYCBqPClrX/7xiedqJcawNoyBmy 5Fjbvz0vuMz0ZOF7zWXLT2R/F77fqcBQKwvrBKjxrsR/fSnxVqlyoBzy8FkT qQch21JEdpmchuXa/JPXSL3InGM0qGg8DUk+Ab70xM0dt+/YSJ2Bx2+lT2SS 8+Oux9rNNexngdH11uI4qUcpfJttXNoVwJddqUmN1K8SOdv07vNKkKGQITpE zrP9PP3N/kVKcOlJ7Ko1Mc0mpSXhQ8oQaixd+pvkY4XPB86F0F0AhdUFKUbi NoOukZOoAp3yCRePkHr76+TeaJUENejorA06S87XjJqB9dnbtGA47Z3yCZKf 1fOWAzROa4Hwzv3j70lejme5JfvLWQtSi7d+OEPM3q2bLz2gBVwP+o5rk/zM Y3T4SUOmNrjeCr3g3k/Od1ca7CfP68IbtcjOvh4qeNbJCkZ66oLFsdvsN4nL DuePHXujC+E8bvtWSJ4+O51o6MamBy/aYh9zEavZ3VLYNKYH7zynxW1IP7O6 zcTB628A5joWB4H0w5d9ge0fCw2gaiQ5aKCV5FXpP5HWUwZQzmx01JvYlmZk Xb7GJZA+fs26iuRt94D8mdP7DUHP/ZC9Cem3H74ffjmmZQicD480bSamUUwy Dws2hIQrDa/ySd4O2BLU1Uo1hP8W5Vd3EEdH6ZWblRpBqPyrj/2kv7fNNtxe P2cEI3nFA/HEuzTkxNIPGkPkvZwXKsSPdvK/mg03JueuCOsqkhcGnJKs4suM Qd/hgrMv8b4upn0SC8ZwxzdBSZ447eGfeO9LJqBRYHqzluSN8eVbFw9EmcAV q8qqcGIBw5HNtRUmQMW4f5rEelGXYSOLKbCNrvCPr+VvTObsETKFY/bhh/KJ H832/s5QNAX/dfbs/sQD6hfzVD1Mwa+plnqIuGZiV6zSA1MwWLit95vkqaw7 A7cU8kyhbp3vgca1vMWepiLfbApK0Uw6z4g93lgLyEybwm53+Hmb2PL8ic2S m8yAftfIel1i5aGV7yd4zKChJi9clFjErarqmKwZ0HXwRe4k5tgRniJoaAa3 ewIZ1/I5bbqmz2FXM7iWPb2jj3hCdrfxwXgzKH4q9rhyLQ93D5/an2MG6uks b7KIi2wz2Pc0mIHkoc1aCcTJm+wX2cbN4PdXteAQ4qDkkx076cxh3P+f2m1i G4n/3m7fZw5GulM5t4h1muuit0qZQ/p4WcZaXpa5Gm2zSc8cCp3HZNfy9EEa vQt0juYw73/faS1vb32wl58m2hw4739UWsvjC0fHNq68Moeg3+cr1q731WaP Ltaaw6vgxP613680ca6c/2YOVtZcSVeIMxaln1JXzeFg6gidHXFs1Hrvqd0W sK+5icmT2P1Qo+GYuAXcUwysCyM2w3jJb5oWUBxpx5u4dl7QNWT7essCQr5U HXlDLEw98Ks3zALcOW59WTu/sAVNtXW+sIDLykdFhohXud6+aa20gO8CnsJr +ft7gXvU568W8Lz1ccduMv6fVeWtP/2xAK3XEfukiQu+b1auYbUE2dhd282I E71a+CqOW4LZdEVKEPHNbNOR4hvkuohDRh+xlgJfRX6QJbQe09pNT9bPqQHq kzfPLKGzd9shqbXzHKP3pfQvlrBx4iBdGvHcc4WTzxfJ/XKvNA0Q90gzsj5l toJr7AaHOcj6fWmd2PpA2QqSHQ3cHxArNL47H/zOCjZtyOd4S/aDkJXfIf8u K5jfNPF9lZjlr9J6n3kr2FobtmftPDtypLfMReAyNJ0/8naB2Dd8SfzKo8ug FVXUcons1+s8ZSwWhZdB+FjXmXfE6u+D5o3bLsOzlT0UTrLf903veq1DfwXM W05WfSdG5RO8CrevwJN2vwdxpH6ovio7hfeuwGNmvdr/SL0Z2HJBXSL3CtxY kum0a1vLL+Ye/BNX4Fp99C1dkr8lFaNbGXWvguHjBl9xUq/yzkx5dYlcA7cx PTp5kr9fSj/tujp5HdSkqHMCa/k68cjM0Pob8IZ2XKaMuGalkPbS/hugI7Ch X4vk7dF3nwVV9G5A1IehZq9RKnBLrvgdq7kBgu/1OtvGyPlPTFd4+elNoDI8 b3KYJvXh3vBZhw834UtoduR6Ut9Lflpfmu6+CVHbZ2PvEffk+QcObLOGa4vi BwoopF4dz+2r8LQGfRoeqwnSP2KOMoSE6dtAgk+c8HbSf5YCF+0EHGxAb785 BBCbDgwZ1IfbgDrypC8RC0cUHKEvswG7YywXe0n/ap40aQ7lvQWyS68Fg0j/ k5BXKuaXvQXRXyOMZoiTH4qmfNK/BW6rndfVSb+0VdzsuCXiFnxRDBtgIv11 e1oua+j8LfD96WTnRvrvey9VmrsbbMG6zKmtgdg2o3LBktkWjF1+xe8h/bv7 v+x+OkFb4H/Yu1hAHC54oLX9pC0ErKd1XyWW1X9Qk6pgCztlxPecJXngZY7v 6zOmtsDLXRlcS2zYt/hsp7UtmH4/IUJH8sb2TdYPRtxsgeXnj1Jp4qrjw+F5 gbbgtvXFXkdiVxPdO/5xttDuy372BfGRsAYnrWRbuMvLsa9rLb8UyF3nybIl /SH26TqSh+KHC4wXim3hua9ryRHic4xHNKtqbOFbTv8ljbXvA08+PRffZgvJ Rd+dHde+f7TaJWU5aAthB5tXYonNY8KERWdsIf7w94Gstbz4geYg3bItbH/y iHEtz34ad2Jv32AHdyOdPbvX8vHOKYZUZjtwctu5Z5xYRNaU1nGfHSzwSX+d J/5+o+PXaUE74IyqzF/Lmwn3laaYJe2g5NfL2LV8qlqJX78p2IH8jvVX10xL FW1/q2kHj3+y8a39fAFHRp2fqR0UTMpUr+Xh6wp7P2ha28GMzN9j34m57OPf HHC3gz1ic6Yda3k+cXPafCC5P9/imbK172M/eiVUxtkB/dP55rS1739/zkfG JduBL8umpeC1/Ljvmp9Flh1kBjtnXSZOuTDgcrzEDv6G5IwAsY6r5s11tXYg Zq8Ss5N4S2qdaVubHclrLC9GyPiXNklrPxu0gyPHl9lziHkP8cmcXraD3j0d YxLEvRqJIswb7SF+JVngF5n/SC+mQ9+Y7aGRTTwpm/hXx8o2P0F7sMtI/Lad OOM/ezpNSXu4QhlILiHryVhwbIn7nD08mqg2W/t+tNq/ZajC1B72M3RXPyTr k9MyovOFjT3w67Ts5iV2PH2+PtzDHirLT1hlkvXNTVuep/PAHkQFdz1LI+vf bcgj/VSaPTxo6fThIG4uk0jal0feR9uPJ5jsFy/vnKDJJnvg2z0bp0byYofx TY+mfntIZy9UfkX22xEZPru8KfK8Gp+nq2Q/9q48MfDa6AA9FofX3SV5Ucw9 SpAJHGC32N8iO3JejtBX5l684ABmm5RdH5D9PiKxkbXPwAHOmo3cLyL5MHbR iybN2QFcWHIHR0i9oDjatJ3MdgDTnF8MMyQfntXir+N67wB/SxrkBsZJ/Tn+ /f26Tw7wLC05t47UI6U5o7TGUQfItB6UCyH1Ku2WipvZHke46HGNWkTy4l/V zTYKAo7QIeA06EDyopZQtbnASUdgLfi2kW+ArLcZqQs/tRzhWGvU6u0vZLyv H9kbEu4IY0eH21s7yPq3oq/O+eMIYUvs9UD6kfWZ2uK7m53Atul3U1Qt2a8H /LLdWZ3gWcf+Sz3VVLAfXr5/5rgTHFxuPqxfQfqfyeT17utOoD6Z1bD1HckL Bh+30/Q6gf+1vb9UX5H9lC96a+m7ExxvL1AwTSd5eEdy4+y8E0yw3nt58wXZ z7XOoUMMzqDOJtTj/IysT1Eeuko5Z0gd/huj8YjUK0bvxYB0Z2C8a4QnQkn/ qxAdoHdzgQ0i/f+ErahwgitZii7QBbwyP2+sNSf1xI3+0UqsC/zaaJ5gYEr6 99Fh3ZlMF/DlySh3v0TyR2JUy+dBF3gbvzLzVJ0Kh1wmq2IUXaFlbpfKM2lS vwSSX7GyuUFrA5/bKRYqOFyfef6Zxw3abOouVDNRITRdMjngmBsEdFuD2nYq FB/qiJ9XcoOHNsf+XKMn48mzxavJ0w3SziXy5PxH1h+no1rQNzc47JmkkkKh wNilciWZWTdICtXzvjBNgX8JjGd/rriBuduest8TFBBkTz9pscsdTqiMThuN UiCUZYAbzrtDp9ORK2p9FDjNqPjzV7Y70JYZef3+RAEDlbvUrHfuIIRd17/V UcA+fHjCss4dakIdjVtrKJC8xXOgdcgdZl1WurCCAisbcmuzd96GxypZbn0l FGBWWC232n8bZE6fXz9XRAH+gAvvOYVug7VuQBRDIQX0143lhJ67DVyRn9l1 31KgYHV3wmX327Bf5rKmeCYFGmWuxe8Jug0fVdu4fTIoMOJZENkedxuW+vcP Nb0k919R85PPug23Z/CJ/3MK2C4F3OQavA0hxj8vKjyhQJB42+WO6dug/726 4mMiBZKc95mF/yb3dzm9Rfsxuf9CifYykwc0dJgE+j0k7/eDKtN51gPe7vl1 9HQ8ed43v5Mpmh7Q92rH4Ews+f1OVlEbMw+4zBf8MSWGPP89HN7g6QFG+Sca BKIo8Dm77UBrqAfcGTzLSxNJgeCnV7iSHnjAvSGzU1/DyfgERjGL5XnAc5pV 5tJQ8nndDjDSVniAAi89S2kIef+bhZs+N3mAlI7ohY/BFBhV//rXasoD7Me3 tf0XRMb7jMPSsd8eQN/zwvBoIJkf8Y3zfzd4gmXfweirAeT5nEfH73J7wt7I 8xb//Mjzt1UOmwl7wsb6NolLxPK0uv2CMp5wcZqDp8qXvM/CZNdvZU/4F1Ai c5K4cMyrtVrfE/J+lD8tuUPmu5epMeaKJ2Qyl1opEh9pTKs1cvIE7dd3U9b+ fuU7SlYc9vOExEfPb4UQJ+d+fv8z2hNY/NO+SREbPDcvLE/yBNrEqp1/vSnA 8uDXm4hMTwiu92b7RNwcGpqpX+IJX6B4XSpxqCfXi4N1njDf83oylPiMbe7T Hx2ekBz1Y3Dt71f+mSs8/vDNE97M2vz2Ji7S7r0X8sMTiorNFSKJHRRtYrRX PSFS8WJPOrHQKdrw/Qxe8GQzQ2Ur8bjgvcAZDi9wf1XAvJm8X8o+/jvFfF5w zux17wViQ+bS2wFiXtB87SFvEvGuDRrO6me84F+35vq/xC1Lo7Z7NLxg/a1l v2tkPMKn3G5MmHiB8++R7G/ECgMMl/OtvaBc7UHMDTKeNC1PTe/c9oKUS01i /5HxL6k8cUklxAv8Wm1ephI7FnzUZr/vBbNPwqja/hQ4mm6kNprqBaJXjHay kPmcfPRD6U2uF2R5S3MNE6dGBpz1LPOC74deMH8g88/mmCXJ0ucFj87c73xM 1kvrZbkTQxNeAAsRmU/JegrX7ziategFvqM/vPLIevsP/vKcZfYGrp/P99JF UOD9sZi9O/Z7w3n6LxRZsl6deQ5y9At5k/eTeh9G1vPkZpVtTkre0BRtpahM 1n/qyuBmOT1vUDu4laYsjgLGVEc6hsve4Dwa/kL+LgXa2h//Tr3jDZq1mpl2 D8j9n0x/ay/yBv9yqwQnsh/NGYUV86q94eYzeXaJpxTY7OmQGdfqDfql6Y4b nlFAx2DZUWPaG3RfL0bWpFHAdQvduvFtPiAhcxpbsylQX34wX3eXD4QqKN6b y6EAl9u5K7WcPiDMpNW4h9SP6rHQ+rTDPsAa+23LPVJfmKp3xFud9gG5Uzt1 6cspYOVxXKHjvA+MvFOq86sk6+e49tIZNR/wf5nTv4HUM5OUB4Y8Rj4gH7XZ 70g9BTK99x785uwD7EHShnMdFDgnKVhgmuEDxgc4Xp+foUDCD9WrzTk+cOZb ZY7hLAUoL205ZAt9IGO0Z7PrPAXiWfO89lb5QN/BVbra3xQYXpA8N/B/TWce TeX3tvGSNFFIRUqGypCUQoZ0ydCXksg8ZA5FhmRIFOcYDoczGSuUSIYIZYgG lEIpTWTMPHNkSKXh97TW+/55rbPuZ+997332/bn2s9d6ukJRp++YX81F+PN7 up+t+cKQ+pvZMiPGRtF2559mgWHQkssQiiPqySfFXFmjK2G4KsZQi7Aj+PPI lO2xyDD4W5yWD3FiQ+tM4DMkhOFtiXLDWXc2WgpiY6WKwuDb4cfac4mo30ql Ij+Hw/DtQFDV9FWCZ3R/Gs5NheF3+vbJ/DTCv1mCPDUfBrnypm7bDDYYlxqG +5aR0H9ma3VuDhvbq7uKXm0j4a5sq+mzMjb03on31+0kIWNos6dsJeHX+1w3 VO8mIXRuyXXKYzbKOWcuPlAjQf2bWu2m5wRf6HFppZmTEGEdPHWF8GteVsf8 km1J2Op77ZT3v/cj7ow7zNMkvNbe2WdA+K/uuM3ckb5E/Im2lA8ETyy7YXco NIiELj/alUCCN6SKsryDwkjI5eAfXNnLhs97uU+edBJcTvvRRgl+Ser3XXEm iYSKB8tIygTvVM5VqDilkTBhN2rsPcYG5yatdPN8YnyxwlPJhJ+SlqI0G5WQ EOt81SmS4CsDlSYO/YckKH7n5LeeYSPF2txV4yUJbxNKfR8QvPbYI/Wq6hsS IpucPh4g+K4vpPeVwicSykNWN6QT/MdF3/lHrpOEga07ckcIPtx1032vdD8J FkaVrwUIvjQsLnKUGCNB3s4u9t/9jwu18wlbv5Lgv8PpMB/Br1c/qL7c9J0E unafTg+hnwxc+cH3l4RDBc1zNIKH++ef7+LmIkPSRSnv3/ntyhWrbbl4yMi0 kn32j8d3C55gLBEgQ+z4mvT3hD4pnVD7czMZ56Mir/27LxGg2jY3J0bGd+1y oX/n36nHRCTZUmTcqDG73Enoahsny9E9ZPwRLZX9dx9i8FwOtV+JDEb2Uuo/ P7REve68qzoZPrZttdlEfzZz91mOa5GhN2vk+5for2LHHw2vo2Tc0RmUUCK0 YZ6w1KwhGWsDPp46SozX/aLyugBzMhp3b7mrRuQjUtf0289TZMjmZ1xfRfB2 xqbzXZedydjJf6TqPpHPR0O05xzuZLzh6LiuQuS7tTQ/P9KHjJa1/s3XiPmY Ca9nrQ4k45afxVTLLBs8JoMXaZfJqHfijZsk+FlKgsOBP4LQdPKRboKXtWZE dJOoZGjryJbnELxsW6O2ZzOLDGH+PyH648R6tPP7LXaDjOCvTskiQ2zck2MN 3L5NxusqP0V9wu83/i58JX2XDHv3yWojgo+XpI5clX9IRqLcLvP+NjaE3ZeH lT4l8l2nV/fv/FNJVdxN5QUZe86lDTe/Z8Pjs7XS4Q9kLPjt2y/4iuDZO4Fb 69rIqJEQa//1guBT/0ROvR4yVAsa95YT/PtZ4O17w0kyvnTeW3f3IRvaRppe 9ivCwfe2zpR5mw07UTuzAZ5wXNtXIyFyk40g9iV1N4FwlI+46V25RuwncaVr vMXCodh1XO0JjfA7jVI5V9QI3WyxbLcfGweu6tCXaYaD4TtfZeVJrBc3R/8o 3XBoPW0MsnFlg8KVqk03DUfIsy7FTgs25jTX9aZ7hYN8jtT0RoWNdfyy9eL+ 4chYHHqWLs+GTK/uvezgcAxk5MRpSbNhf4UUUhgdjj9uQlbcgmwij/NCTzLD sfaOzaYMYn/MVOg82dUajmNHGtIFif0/Z340SqM7HNOaGbqxRP24W7bwKHMg HDdjAqw6/t0HVl4vefZrOO6bCZB4AqfQePDo4rfVETAYlLB6e3QKM9oVmbyH InAmcXHo8NgkNEwT5rSyInD1tLPu6Q2T0Nl4S/pOXgQsRVVvu6+YxNHWe7ar iyOgljKf7vhjAiaWr+qbH0eA6czTvKNrAm6nONJOtUagXMX0tFDWBOinvXUC VkeCvndjXfDeCXT76SfleUdCOMphulBvHA8YIcdSAiKhX1fWba46Dmp+4ZLI y5HQvXH4Kt+ucSj38ro7xEZC+XWz+SPucbD0P0EwJxJXqXvk+d6NQUfCdjTi SySC7juM1NuOYcsherrvUCT2HXSp5zUaw4xFtbHDZCSCld27g7XGkE4Tf3Jw MRJ/XB5ceCE1hu8/hlizG6OQ2e2foTE/irvNXgcdDKJwTdWzqS1pFKTxm18N TKPg3rDbYJY6Ckuu99kHbaLgYT08oBU2Cq6DCnyCZ6Mw82Xfb5rHKOzvfB98 ExGFS3HR5yZ1RqFUK339UWwUEjn6FXoOjoKny8owLz4K5xhLHdYrjKKS/3Fl REYUYtRi6ZAYhcDlMPrBx1GA79+Jt5yjGEsp0ZZ5HoXfY0JhQ79HUHO//8em V1GQkxl+f2RhBJ6jOs6zn6MQ+Wbo9OjYCLQ5A4R6v0SB5rqOU25wBMLbct68 GYpCccuiUM2XEdSbrFbJm4tCrnisd+unEaR7qU0lL0bhzH9GG069G4FfjEdm BAcFaYc1fyo2jUD/dpqF7yoKzt4XN3FqGIF49RseB14K5Iw6LIbqRvC9/W+t wSYKoudpqK4dwZv5vYEHRSgYlsrUmHk6gixex90yOyi4ur42MeTxCC7tiu/b JEuBjzz7olPVCHQ5U/Xp+yhIWmhfU/1wBAJdWWVcKhTQVnolnqsYQW9pgehl UDASPS10rnwEhbSymHkdCjbTK9Oelo0gyPXpnIc+BeQ3u3a6EPo/jXrbgZMU ILTyoQOhBYTe1VtbUpByoMHuPqF7vrbt+2BHQe39N6I2xPPuNvalHnWh4K26 Ftcpor2LmeNctR4U7NkSurmc6M+R4DlvFV8Karwa3NyJ/vKb/m4vukhBPEnt dxAxnu7dXDpSoRQwjB4NDBHjzedad+9GJAXSwoOyRUQ+Ar9sEtoURwGFZ66/ lciXdoUomRZPwZPWDEE7Ip+8TOnJ5dcoUBbY0H6EyHfXmX3mITcpKJAuP8Ag 5iNPU61mLpsCkU/bDh9sGYG/sPYujwIK1Bbbl+t3jEBrTj+x/z4FUx16idU9 xPOaTP9aVVLQvdX2z7WhEeRedv2g95KChk07kiJmiXhzb/WaJgqC/N52J/8c gebei3eUP1JwUfaKggDHKDp7Yy5J9lLw4qmzzAn+UeRUxg+mD1PgVt3ask54 FH7xqSc2TlHAvXtjzqHto1irUyixfJECd+OuorEDo2jfWh4XvDQacdtT289o juLOt6cLsyuicTk8nNv6+Cg0ct696hOIxr2yEKVkZ+L/ENauaCUcjditdfP9 3kS8Zf+Nd2LR8LitdDQ7ZBS+a+Z9q+Wi8YTvwgQthYgf+N11QDEarMqEp2XZ o+B+zKV7Ty0aXuc+7DUvHUW2p+CWdN1oFBcMXOL8OIrP79SeX3KMRkCofuC2 TWPIytOWm3WLhoLgcV1h6TH4kI+nnPWKxgbdNqV4tTGsVrTzsAyOhhB5umzB YQzqKSSBA0nRKDmpqEd/QPzuQ71cmBqNI0kTmW6NY2jRSxjZkRkNl//+5FT1 jMF78fYjgaJoRIfIv2pcO45btg3OMw3REG7/UOLqPQ4N5rzBXHM0Xi2R/sYb O47uZ2Iq31qjYTq0kaKSM47N0kE8Pwej8bLj3bGfveOIn5UpW8oRA9fmH4ef WE0gnBK7gk81Bg66XZMV1pMQr6r4yn84BsYbwupuBk+ienKgQ0A3BnteXwul p03i10n1IkGzGOjzZR4++mUSflunLETPx0DUZ6jikv0UBAw3a4lfjEFciGfE MOH3SkhHdm8PjUEAj03xu3SCz4fTl0rRYnCgOKi2vp3wR5tfjUsnxqCO1zUn e4Hw/8cXPu1KjYFNk/hU1no2XEpO5O3Ji0HWlZ6TKboEPw5eSpAvjoHPtFCK qQNRrzflXN5fEYOpndVXnwWyoXH0o5vi0xh4/93a9Yyot93BS4wPvIjBr/c7 fypl/uN9WXWVphisuFhe8KuU4Kc+C0m1jzFQY/qyZ4n6XyEQwafeEQN19/nV i5/YMP+vePFQXwyut9Y/Yvex8e1i16DGaAzY2RHG9wh+Sbi7qllzOgbOIokf N35jY98XxUrthRgcVancvozgrWY+x6wjf2LQssZT8d/9VU9tGk13ORV3ehIU ugnNHVAZeJSbCnKGbU3Uv/PT3CFH/fVU6MR3SsgS/KXbyX/cYDMVnU1BUXkE Pw2txQFDMSqqvo8q9xM8FH7YXeykFBVPcj8Mln8k/MWF5DUme6h4Q7LuXkPw S032s3lTJSr2CceYP88neKCN/cVcnYo9LzkK65ls/FmzpdFSm4o8yfEcjgsE jx7SfWB9jIoWoxWVtifZUPW5kH7qJBVem7jVX8sSPJR5k2JnSUWH3IMS9WVs +Le8Pu9gT4WeQvdCDuHPBFb9sHFypeLenGDgiixi/tV2/Hfak4o/275YmHlO wdDTSN7Vj4rLNybTkxSI9XAzRPhMMBVNA5rHmr5NYhdXC9sjhgrftZqqR7wm 8UBmVtKASYznzOVDKyQncfAEr/2eFCpWSgnoi3RMQD/laPPX21RUs/s7ipUn 4CHztMi/hgrRSGeu0ddjmDPoHDGvp2Ixqcum4uwYgn1/iKq8pYLSbrXyx/Ix xD7az1zspMI8v2cNTZGo1wY5PqHfqRA/JpCQcHkYCr51uQ5/qZDszgx05xnG o+S+Xk2uWBx/UGpvcH0Ir3u2nFwuEAuOjHaeVaWDmDzP3BezJxYWvLynmgb7 IZccNBvvEgufDtUTnY49KKtK3uV3LhYD3AdlUthfcKjngZPZhVic3uCcG7Pl Cwyk2R8ESbEwq9l8+1hoF7yqnB6kpcVi6ISRQNX5dnz/EjpxOSsWi6+N5d5X tCGUM327fX4sTl6YlvzI0QbG8c8J4g9jUfEix/bxrVYUfdH3u/MxFnEn2ftJ /J+gzHm2gNIRi81uu+1cAj+iWipq8ExfLBxiWYIqfR/Q7FNjKjsdC/k1XifI Ne8xvUxJqXhNHEQWbrjoFzQjUMrYk8Ufh/f0kHhj+WYsOe6d7SsUhxO6Kz3L fd6CNylvo5JkHHbMLJafyGqCvNS2hUrNOHDb/5k2Mm9E0WqBgR16cVDckRnm fLMBcpMr3zFOxOGuZe962lQ9ZEpm8lxs4lCvOT+ae/UlxA++sOX3j0No9WPh XMk63BSpOhYSHIcrOuPKgknPIbK0SHmEFIdehTyruyufQ/jFVf4ndCJeWfvV ux+1xH507sWZ3Di82ZllwruqBqx9jvc/3osDk2fKPjOxGrwbzG+iLA73pfL3 ReyoBk+7RtCGZ3EIUhb9k5P2BFzOAnI1nXFYRj5rqhpThfAjq4Rl++NA31/B VPtQCQ7pPyuSR+MwMUAy8ROrxN/J4V6Pb3FoVXDfNf+6At8DqhIFeWlI3bOv T8CmDP5WRSTyRhqi/Sy1axpLMXfwttfUFhrseJa8iFQvxdeldL3n0jRMaO7T 65F7gDGq428vLRrEZzv6EtVL4OZpPtauR8Nsi8OapoZiDBnqt+oY0nCMPu+n almM/g1KxcKnaDhVcRFmYUXovLHq9Et/Gvx2LvsmPFIAK9Ifo30hNNTkNs53 yBXgs/PsoTQyDZ87nm7LDrqLT9Jdgr4MGtJM2qqqRfPx5n7Ra5E8GqyrOX12 ZuZAP+n2w+giGrqFZnSPrM1BY+C17LkyGrxyNs7YhNzBS/Xw0MZnNBjkpqR8 d8lG9UtzBf8uGhwUkhp7nLPAy+md4T5Ag86XZu28vkzYa1DWOozTMLCK89Q2 50z8ragYOfaDhoKTT9am+NzCoTyhNLENdFyNM3ZtvH8TtCH51Zu20CGac8Fl +thNdIsfDeCWoKPrS51mX9MNhFwPMlrYS8dXxgtrk6PpeBTbsbxJn44fRje/ eYReB3fD7PlaYzoama9N3rVdg81y7p5yKzraL+VR7h64hsWQg5W33OgIr08n zOVVqHqleQaG03F6nUm8Y00SYvJLO85RifbmpHb8Vk1C+3CTrhOLjp7DLcGb KxIRZP9H3OAmHYdHtzr6PUrAQyO7VolHdIw0279fMs7CSlqAttAzOmYcGoSW XGbBopFevLaRjiwJA50X61n4rllN/dFKx+3LCz1m/zGhrCCm8XaWjkPF7klf U+igeKsUPP9Jh4Ci6W6FYRo8WqR4upYwYHRrpKxXhYZH/IeD3q9gwK0x7/GS iVhYU31MHm9gYM/d2FpBog6Tcn+vVhZigO9Fx4DfVDTyXkbXlGxhQGfCO9Xa Pho/l92Sy5Fg4JICXcPOgIJrwe9XxsszIOh9L+m5YSRqr9k+5VFk4MzCUrHu zxEYqxjzoygzcPjcCN9bpwioznP0h4CByweXU8fCwtF2bv9jt+MM2Kx6arC2 i4RfZ3cZ5BgyUPTwDcstlAQRN4kvw8YMjLk07H6+gwRnx/VLXa0Y6Kh2X2rg H4Zps1nt064M9AbHBTjvDsV6k/FPWWcZcH5w6/afJ1egZNTvMnCOgb1pH6vC dl5B8LEPFKcLDDDKtjuK/g3BSo37rx3CGFAquVVV+PESdqnnn8oIZ0BojW6J qtElGKhmTvVEMRD1WOpGWHMQEhTiee1pDGRRArv+tlyEqLSvie11BhwLOuT5 OAKhzL+/06qUAbNh0yOWzy/Aet2uc9cqGKAmL8q+PX0Bl7kl/rRVMWBCWAip VRfwnGu9qGUtA6R62m0rU18YLs44mb9lwGvyvMkNjvPw/T42l/SeAeOdm8z4 SnyQNN8X0fKJgczBwrRNTj7oZL+/Y9rJgOQWt/bHDd5wGygZNx5lQNfs1zke Iy9Qe/OC4yeIeJ685bYvPVHYfYvnA5sB2yNDwqYanpj7zNpz8hsDP6c/9/9S OYfQpvO+hsuYyOThv1101B3JZfsW9bcyUXBB0fZ6iysKZSX2B4sy8T6Lpbjb 1xUvbq13z5dgwjtL4SuNzxXfaHPtq2SYOJTWm59q7AIz17LKF0pMUNPzPg6N O8OzK3tmXoUJR7Mnw4uJzog0TpbZoc7E6p8aGtcPO6MMgdfIWkykWluGWaY5 YaOgapCGIRP19hfmOVwcIUeTKfEyZoLDXOpWsrAjjnAKj6WbMbE58JdF8HsH +E8vWv62YWKDmeYDYW0HtNQ/Vqk8w0Tluq4kDiV7JF48/GM/mYmWG2e316bb 4C5bXt4pkgln2a6nJnI2eH5a/AwrmgmDdTmBH55aY85oWds0nYnIqq3i3iNW MJGpqyhIZeKjoYnY7hOW8LhZOt15g2jPPnzFzkkLhG/MluLOZOL1NpMbdbEW eMARlXI2l4lrvzhD25rNIdChGyhZxsSgbo1MmLsZZI1UisweMmEx9jOhY4MZ tF9Kj0Q8YiJLjGcqo8YUF+6vthioZYLcXPvGfKspPlJfH8h4y8SabFG30gFj xB80XNg8ysSNkZfklYVGSLA76UWfYIIz50v0IxdCk0yGl00zMX9pY9M9USMk 1Vu0Tnwj8tnJDFFLMUSKiUP5E04WtCpa70TInMDVAKc9+1ey0Dv3/UBSoQGu XTt9584aFmZPvIxuUDDA9Z4zyQx+FuhVOqu9/juOdI/zAY6iLKQbKCbfCD+G G/QL7BYJFiKVV90vFDyGmyX+rsckWXBuDd8RX3gUGd+DzBXkWLgp48398Ise ssLJB7gOsuCy3+NZnJku8lITFnLNWTB7KWoTS9dB/tMkLxFrFt4zzO/vUdfB 3b6UYZYtC/6pLof3TGijQCqt9dJpFu5KSjZIG2ij6MHt8uO+LIS+uzfhKKaF otY7e2r9WTjz6qePepsmin/m3lEKYkF6QbpXm6WJEo3C5G1hLPCMCyypW6GJ 0tdlAV9pLGiDlvfjrwbK2BXs0ywWZCQLxPKqCc1f5dqeyELCtJGsHUkDFRZP zZ+lspC46smt5ys1UDnw8kBiHgtLtwquW6Z5CNW/Pi8ov2Chok59ufmCKh79 OXL0fAML7m09vK3XVVGxpDQ1/zULUvS0NwWHVXGPk3lY5AMLwgEHPPWYKkjn 1qMu62GBw6R6IQvKCN7yUOTNDxZsecSlkj4qIlBE0mfFbxYyXLz3botVxAXR xGcaS+JxqYt1tlhbEe7bfdzuc8VD/0drT0+FAqxkpUtS1sdjc6vgo8W7+6Fy 8KqO0+54mNa8+9BaLQ+FQytSUvfGI3/61qGdUfLYq+E39ml/PE7tU5fQMpCH lLYRXVc1HndUjJ50dO+FoP6qtt3/xaM9vWdg36q9+GZ90eO7fTyUWQHzU39l MXNq+Im8czyKXo3bXc+UxZSdKZ+7azxeN9+WourKYtBJvqzrXDwa3q6OEkva hY/uo39rg+IRLcV1LxsyKLlkGR+XEI9Pf6UUVeslsbV0pndnSjzm1q/P9PKT BGWKurf6ejy28PLV90pIws7hSdPMLWI80vnJruE7wf2fxEqL4njUaQ1zehrv gAv/ZLD4m3icSDlx0niHBN4di3xV9Y7Qx8ssNw2I42DEts2mn+Lh8A72bzPF sf67UXlUZzwosfpDa3aKo7qr7OvEWDxikgfGjyuKQTg31KV8RQI0+bItXyyI ILJPqNRwTQI4Mj2ongwRzAjfXza2NgE23CfmGTIiqKcN3tyyMQGFzb7jsk5b 4X/haEfY9gRwOpnpiA8Ko5kgUv3DCTC3fvrQXFIIahcL0ge1E5A+8atx/SdB ZJccmbysm4CRSpu8b2RBhOy4GFN8IgGM/bIDIoObILOm+/lG2wTslaj4cOXB RiRqB6wvckjAsiV3rb+f3Ygll3kd9U4n4HuDWbGf+Ea0Tmv+veSRgMDeQ+u9 EjZAU6bz+AbvBEju4PPqN9iAQie/1ELfBMw/CjtwfPUGCKWtHf8vIAFFBrKP cl4I4P++L4D//77A/wDt+n15 "]]}, Annotation[#, "Charting`Private`Tag$12701#4"]& ], TagBox[ {RGBColor[0.528488, 0.470624, 0.701351], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUm3c8lV8YwFVWpCKVyt4poiQV9ygje+/Nj+y99957NTSsUiihyCiPUSKU bKKMa3a5KiEpv+OvPt/Pe933vOc84/u8xGXtpm27m4KCYpSagmLn3+jBRxcn A7NB/CuHHCHhHYF5vH6lxC8bZkuvlGdNvyM8mO5+5OmdDf8pV4yZo3bCm5Wf hylds2H+ee4D9z/tBCp6mR/8VtnQmTKegmLfE24w6pSQzbLhUo/s323SewI/ y3XLWuNsWDymUumi10lQ4Ev+oKSbDdFxgxfcTnURYtFwqfO1bJD8ebN3ltRN OKLwzeq8XDZcnNa4S7L6QChW/cfyTyYb1GjJJyaGPxDajHjj0i5lw3Y/hePz ro8Eam/3/6qEd+7nmRYz20OIe0zLunEoG36VxVxLYu0jsDw70dd0MBs0vhTw NNj3ER5XiyQmMGQDoVFw5WxNH6G9RXfjOE022Fp4nmHS6yfQjuf3S29mAXHy CoN00QDh1vTzJOr1LFi6L6tktDlAEFxsu/rxZxaQzxsZrGgPEhTXSRWWS1nQ smDeVko7RIhnvJgSNZEFt2ZVe07EDRNYWFTlVMezIOiKY+bw4jDhMbvFH+bR LFg0/p6rojlCaD8V41DclwW6/14f8eEcJexV+CTf0ZYFImqjoq2DnwmJgQ7/ 9j/NAk+qz10qRV8JYv2OPpklWVA71fFigmWCMCzsTDpcnAXs4pwBvlYTBIFJ 11HWvCzYXyCe9HFtgvDmmneNUEYWzPj+cN97borgXOAjXJ6SBVvNimGkmCnC oT++D8QSs8CjdoHbfnSKYF0ekCkZlQXnGcx1VOKnCdvMYa4KPvh+J097NWwQ CcWu4TMdHllQV0T1z8RohqDeHmGq5poFopclSr40zBDuBkUr69plQepClNTz 2FnCpakEfmujLLh+s8rujfg8wftZ9pcQaXy/JvXjNVvfCKx7b+jtupQFXcUV S23hJEKr9c2uaIksUHnXZB9Es0RgOpJbn3QmC1wYNZjp2JYJz4LzbtzmyoIb tnEZEudXCPqD+Qxs7FlwMsKFWBS5Qvh3pjA6/3gWCKgvBBZ+WiGoTj/wfHQo C6jpP33w9f5OWFQqVa+mwud3oKUk7MMPQkZR2VvJ3Xg/8hTlAk7+JEj+fSL1 6l8mSFtK3tKM/UmIq3gm1LqeCbMdzFyt8qsE3qPV1J8WMqH/pJ/K97FfBAsi NJK6M0EmWERH2O83YZ+FnknZ+0z4Z/+EinvpN6F2ZHHd4V0mfGWiSLe33SQc /HhYbK4pE8asV9jZzf4QWuqciiafZ0LGB/f4fMe/BFfxXTL5FZnwmuau+83V v4Tjz26MmT/NhFt7Dh5Tj/hH8HrQfHisOBMsRJXnLhRtE3jTjsYP3s4EI6e7 ly2odqGevU95c25kgp/YEs1F/V0oOPpqs05WJgj++t3z4vEuNBDgstmTnAmd VoropfZuFGvT6twZlgmbbcaX1hr2oPmLblpNtpkw53ZN4D6JGmW/oFwOtc4E muGmAntTGiRzJjdR2iITgrw6dWM+0KDbvG9b6w0z4X7yJ/tvdbRI+cAJiWqV TGiLFhZfL6dDawkVvV6KmcB8k1vqy1l6VEip4HZWPhNORQelJNfRoz+/3R8/ I2TCwyC28vCP+9ATYtvxUrFMONh0Gko4DiBDC9OX9iKZkPCHXqKs4QCiHP2u I3AqE0yEzC9ECB9EZh9ZUx7wZkI2BeORXb0H0f56z+37RzNBtZBvz3tRJuSe xk7M+psBJRs6DYUah5FARsOI9WYGzKlIDlxvOIy+ZBp+FFvPgGsMFquhJ48g tRuZ9R9XMkDWrX9get9RJHSPOoOemAHvnjHOcf5gQZP3i2JHJzJAuK0gg8fz GLqVLxNcMp4BtJuCpr9WjyGaB4F214YyYLeVcb3KnhOIWLosHfU+A2w27hq1 yrGhO0+Szmm/y4CfRWL9l8fZkHa54EmuNxlwUfFfxfEAdtRcac0MrzNgWIKD 2qqBA92vHVzcrMgA7TZWR1kJLqRf7zXR8TQDWsb/VmpncCGGVwcHb5VmwLEb k66ey1woGJSbJR5kgPH+68dZnnEjo7bGm543M0DjfZZBpAovOthuknIlOwNI SiIct2t5UXvHRuTBjAwo6JLuPyfIhyS6z7qWJ2ZAxtzRFIkD/Ii5v1huMSQD imeIo3r/BFDngOylukD8PGObDS4RgihyaOJMvF8GGKpfZrpNcxJ9Hz1+gt8j A3gsud8GsQmhD5Op361sMmBrW6Kr2+M0ipk+NSdqlQGuXyV4Rw8II6mZ9rFt swwouj7L/rRSGJXN726/Z5ABZXuuCDPsOoPiyb73R5Qz4PDNIzcH5kUR+n4o +/G1DDjTkVLmqiiG1n5UJPjJZYCTQaqDSakYsl1b9D5MyABw8OVy9zmLrv41 V9ESy4CbqUnq/wmJo4PaixSfhfF5ibRYOj0WR1+LfWpshDJgM+Xh4vDJ8yhY M5nLnycDVpvPBapekEA1RXXr9w9nQOFJoR/3wyRR9IbcU0EmfP+M4VeDJy4i HbUe66r9GeB937zH5NVFtLI22/2WJgOSzOdb++kuIyFl5gek3+nwqeG3j9ek NNq4n2fku5YO6YcpSNtFBPTup9ABip/p0FbZv5/GGSGbe1cCD5HSYfA6X0Nu rAy6v+KqeelLOhxhz9S8p3oVOctvUr0ZTYd5SmUjs7ar6HJuTIPaUDqMiin9 ypOVRcOyd/mtetIhMHz7HqeSHGK62bEV15IOxNjFUO8oBTTxTbeKEdIhfn3I 9xHrNfRMZsLuTkM6CB18s8eq/hpSXVzrLX+RDh106gd2USqh4ygyXrIyHQI4 /hRdqFBCC1kMhJan6XDo5++jOVbKKFaat2SgOB0iLA7Y+fSrIN3MZ+YWRenw +L9nr3VvqCKeuUvMC3npUHF6hZ7ZXA01pWuFbd1KB8KjbYrtbXW0OR2qx5OU DtqPz757q6SF2iXp6J/GpcN9z4jvYm+10M2UnCaJ6HSY/nfnPx85bSR+4ckp 5ZB0KBBJek6voYN2J1+Y7AtIh5ahyIriUR30aaLlhplvOugUP9EscdRFrokj uzzc0oHlb/WDmFt6SOqrzctNp3TIZHxp9lxCH9GLrzhH26cDHy/9/MqIPno8 Tj180yodSkknDfRFDdG0qHh5ow7en3vZztrcJqimWCchSjMdztUdO1A8YYIS Wb1sFNXSYbdF/oHeB6ZIlLbqeK9COnxTcMuPROaIMvTTrxuy6bAGMt+8jlig oZ8rPSYy6dDPJSZ+dNUChX49EzdzEcdHUk3C2SlLpK2nYV0qkQ7myhNs70ys EF+nq7TbuXTY2OI3Ozdihbpqnv7cOJ0OPK2v0zgmrNHx1FOW+zjTQTGTLOHO bYuW96hc/sSaDjkdaxNTjbaoOcDxyI1j6XCvNuWfi+V1ZG9b0sVxKB2umqta pD63Q1Kf2x8RD6TDyn367Xhbe3RAaz6yZF86fLnS/vs6mwOqkRK4eI4a74de 661neY4osUqBeWM33v+PCwEZjk6oXrPrS8B2Gig+P+4gL+WMaASVVVJ+pMFH r8o4kV8uqHBQnvfFcBos2PQRg6bckVJL9Kh0bxr8eURW4rPzQCtPW9PfdaZB 0YSMoNOKByLEXPk72pgGKe+W4+MYvdCMe/hzm9o0YGJcGW4q8ULJpuCwXJkG n6rtPE2veaORc9KDux6mgXSmGOF2lg8K5whOTrqfBgE+sqwVV30RP33D1cO3 0sCa8/Zn5g1f5D0l+UwwKQ2+zYVMfvL1RwczxOM1PNJgKfdY9MGuIPQy2Isw 4pgGMao3ZQKrg5G5fdWqtU0aSNWMM917FIKeIFErX4M02Ft0ejr5URjSOeV2 lEIrDRy3LFyYTMLR5pHy7gTlNGhxEjodOxeOFJdPXbonnQZXqqMpug5GIvKI 4wr/hTTIceKtZimPRDfelhRXiKbBDGdNfaRWFCLeFTj0hicNIg3PPmwri0Zh Kjykxb1pcDufeT68Jg7pjhO4F3engQonV6N7XjwScjM2XPiTCnIbiov5mQmo PzPjzdxSKvCx0pUN3U5CpbxPN2dnUyE56PXGn/JkFFbTLjr7NRXK3j2hvNeT goRGt+8SP6XCHV2xgnW2dLTtdKJv+n0q0PqNj0e2pqP+vxJ7p1tTwU/ysnWV ewYK43L1maxOBaO3Z47kT2ci3ecJZRPlqXBKNL6HUJqFhOQfTn59lApRvJ/q ZQOzUb/9mNqX26mwi5b/fJrkDVS6uR41npkKNNrDId8FbqKw5EP1Y0mp8Omn RcgP7ltIqEKZ/3NIKtC9bqFyIeSi7SvXTUd9U4HYvU1St7yD+vsiMkfcUqFn Q6SmIP0uCluv/TdklQqXDY3HljjykG5Cv/iQcSoIWvkWGMnkI6ETK46DOqkg rsrV3Pw7H/UTBIb65VOhXEBwoDWhEJX2XGXoJ+D1MU19iLYqQmHW5rJ9F1Kh fde/4Fy5B0goNufZp5Op8L3CozbiTDGiYKmc6eFOhUd5hRIfJR+hgZKuEz0n UoHFQn7OUfMxCu/eE/+BIRUK7BQfHykvRXoWHI3d1Knwi9o7mnGtDAl9v7Ta tZ0Cd38Qpc5qPkUDzJ6Wnd9TwNc/1/QVRwUqLU658X4xBcyfdj9L/laBwiVL ujqmU+Cj5zQ7qaUSCZlOSLYPYA77V6J28zmiWP7j+u5DCiTCY9JCzgs0EHb0 Ydu7FOhO1+ZUKapG4UXqjG/rUmA1pnbh1PJLpHfe8dqbqhSgZDR5VC9ch4Te xYS0lqXAPGFTXiS8Hg0svlpovpcCLKryhwusX6PS4GGO5hspcGXr74L0r0YU vn9VryktBYbEOU7802hCQmdPtTRGpADVvqngTa4WRPFGYeN1YAoISXuXXOBs RQN61iKvvVLgz9yI/1vhNyg84HZug20KsCn1DkYFtiE9+uqeevMU8Gnyy3vQ 8A77Vg91vUEKXNWlWl490IEGmmi8apVSIPDfuVbDtU7UZHnWZPhqCmyUXUj4 G9mNnlCYyW5cxvvRsvD1Iv9HFClTdUhSJAWWPRwYZYw/IdeJsT8GAinwmDjb /kqzFxmF0xD9OFPAc8byoLtuHxJtMn3xkgmvd5hSizpmALFaxt0dok8BRduB wbiqQURDURW9TpkC21N0I97LQ+gLotG7sJ4MwXZdda0ZoygZKn/VfE6G5fNV RqVoAvlbjI0P9ifD/MU9Gj/3TaL/tqnb1rqTYWzL6rb910l0CZnekGhKBrqK UocX6dNorpH6Qs2DZHget1wbSTOHes3FOAbvJYOQn6vNyuQcavxnQrN2IxmU hbxPcNXOo2xC5dD5hGTYEJ1WzdVaROFfPoNeZDKUTT4408/4DTmFUj/2CUoG zxhR87Z335A+u1h6jncyPOA042LzJKGrjSb+1S7J8GaIUrHkwBISMY+1HLie DD6Bt+7a5S2hY/8qFH9ZJMMt9pHZWM5lRHn/s+hho2S4zHVU3DlzGa1IUx87 r50M7k8uilWvLqPP46K79FSSwWbELF3yGhm1hZgseMslg9mIXAxlIhlVscV+ ypZOBrKpZ5LJazK697qi7oVEMqwXfH75bJKM4s0+F/SfSYbU/+iX7q6Tkfdf qsRVwWSgomRXndomI4t7op7M3Mnwmp1CxuQPGSlLmxiLn8DPQ3HRf2ORjCTG Y67qMidD3ZEPrHUfyYgrpELImyEZGJgqAh6UktE+ts9M2dTJsLImpfQmmIw2 XlH9eb6dBMOzzI0ceL1EU9Hpvo0k8IwtMnpJR0Yft4w7f35PArPGodSI9mVU LFVx5xwxCTT5OEIVJJZR5tholM54ElCa72ecn1tCIcFUzl6DSTDGwUZDe3MJ 6b4ylnrengTc7S5lpisk9KzhWUhVRhJQkH/vOmu0iB7c212pmJQErb/obQ8z LqLcMD3il+gkcEZPxPPfL6Bo2T/K9P5JALqUxlSyCyiATz20wCMJemzSvXbt XkCuNAWVF5zw97PLhy20zCOjTgUWG/Mk8DIUdLijPI/Un95W2TRIAsaDZzpd GOeRXBopNF0rCcxnivqkR+eQiE7mzCu5JCD7jin2esyhPZ/Hqw6fSgJScxu9 Te0s3h/R2TLeJOgm3trbnjqLlu9HHbvKngQ5D07JUNrNomHrk+GujHh/MlMX ZlhnUbdc8HNK+iSwvH2RImhzBrXwf5zNpcTr/9Lw+t3IDHq66K32bj0ROuAl x/V7M6iw61242fdE2DgQX10cMYNulR9/8XMxEa6+j1wItptBKekucwnERGg8 vWgwoT6DIj2bjnN+SYT7Wi9q2y/MID/dQ+o1Q4nwZrKWKMw9g5wlrkeofkoE KmW+UZr9M8hgk37e/00i2Pu+WthcICLVMfMTBxoTIWhf+BDlKBHHf6X6w5eJ YLEYdNG2k4gu5FNGXq5MhLe5dCvMjUR0OtKg+lNpIljrmO9jqCIiLpvSebsH iUATNdSj8IiIjij8PfHvXiJkX39Q0XCPiPYJampk30wEp905GrY5RLSLrihS KCMRXn6RiZBOJaK1b7+qmxITwUxSWZEQT0SkbsUF/ehEOP3YYcAqiogmn91h XQpJBEtlqtjCMCIazFjWiPJLhIKnR6Y3g4mo0+tK1DGPRDiQ8zbPNoiImvSy a545JsKJB79vjgcSUc2FuQV5m0RQsn30wQxfLzt2iW3MLBEq862cJ/HP5/9J 1vQ0SIRZyZrX/+HvvzH+NYpWKxG8+wLEJiKJKAnOvryvnAjHo/kMtOOIKLwg ZlFcLhEYHHnGq5OJyCdqmK1TOhESVU6nUWcRkaPtKS2rC3h/WoN1ZXKJyPJa aPS6aCJolfKJWBQSkd7JTy9ThBJhhtf3vEUZESnT837j4U2E6mOcuVLVRCSz 5Mtez5YIccqk/J9AROc/dmhpHk0EUR7XgnB8HkKVrDGzBxPhorwA1cQQEXFk udUG0yVCvqaI/P4ZImL2afnGRJkINUuyCzQ/iWhb0l4brSdAzP72Og3GGcTd fJNKZSUBsrreB27j+FBQelerv5AAAh/mZFLPz6BUI34O188JMKE4KiRpNoOq JvV6A/oTQPb6b0oVzxk04BATE9OdAIcvFKiejp9BrIHEb3chASrYmYqVamaQ zG7mvMe1CZBWpeUV8mEG2STKar+oTICv3ke43OZmUFluYW1nUQLIS1zWDTox iy41WMZsxiXAEUkVOUiaReay6ZLUEQkgxWRl71gyiyI74RtjIL6fmsaNinez qOMzu/ZJ5wS4sNXp+IdqDhlujbEbaiZAeEzuoz0Jc8hX2qi2miUBoh5y2Wo/ mEe5b+OdmhkT4DRBnEmtYx41qtWyd9MlgFzHk2/Jy/OIyvxoDHErHmI2aNZb Li6g7NABrUOT8aB+TCFBu3cBVYHWN/eSeIgMenGDmvobGrwWcT+4MB6E5Pmm RE9/Q5sfK7Ti78SD8CzN0bPa39CViQO1eSnxEPf8xr67976hHooP0R884iGz 5VD9VTESWrqizH76UjxcpHR5+UR+CR3fV8hafi4eKJupLD79t4QUB38fFxWO h0CTN7ReEUvogWPJUXHOeJg9nJp/vGEJGWfRMkpRxwPtGS6VcIFl3B8sDzRu x4HK+7UQxivLqFqglkHmdxwgRz/Pf0bL6OArOzo5UhyOz3c+XxKWURuxbY9q L/68VP6F65PLaLWcffeHzjiYO8LhHvVrGXEF+FJovo0DwzM9cXO0ZBTMwP9X pzYOCAdLaEKFyah0KOTPQGUc0OcKjzwlkNFQwcBvg7I4KAx5YMqhQUZnJWLW TO7HwUiv6Ns3LmRkSTG+On4zDmijX35ZDyKjlPfiPy0y4kDgTA6TUwIZ1Wcn f59MjINsaoM49htkNG9OJP8XHQc+6t25TIVkdOSk1PJMSBwwQfnEtadkJPcz i2Tnh39esZcLXpJRXpzsgpNjHFTWWzf4vSejLq07c0v/xcGPKLYHDb1ktHni 54ybWRxwG9AVK4ySkeCsMvG7fhzo52aFH8f9Vb+icMpLMw6MdEU4L86RUXTg 5sQvpTg40Bh09wGJjCrltL/6ycaBjf+WhMV3Mvqyv3T8t1QcpAz+MXT6hfvn yK6xIIk4uPN7IaNzg4wuFRmN/j0TBzlFwTmRuB/buVQOh52Mg4LEyotZf8ko +8LeoV08cbDHXsyHAvfvll1WA1GscRA5ccisG/NKZ20f1ZE46Kuk5vmLme3G wd64A3FQlpFyKAuzsqV9z969cVAxWp2V+Y+M/IWaPiTtjgOq8+4c21tkVLx6 tJthKxaMDt25NrZJRn2Nbp1pv2Lh+kz9M2G8PoqEdx2M5Fi4JJS3b32VjPsd R3vWfCxI1B/hlsLPZ8rm13Z4KhaAR62ZYomMEuY+vLn5ORZmq4htivNkVFPJ 33psIBYUaRSPsUxjPwgKbb7zIRbe//1c7DlORkwKg8DWHgt280Y2pkNkhA6K NOY1x0KpxyGVkR4yyn0wXl/0IhaGPvDH320ho3bX83V85bGw5vd6dLGejNYk U14+ehQLvD7aqmNVZKTVLfWiLDcWgoyDPWoL8P49LLJRz46FfwKFNiO3yGg4 hO7w95RYoI3/IVqRhuNNZNhHIiIWLvg9Xk3BPuOa5nWh2S4W6qyE7rnqkFGS Vmn9oHgshGWOhrduLKMPJxmdAkRiYcL77+8p0jJi2u1/glUQ75cTsXBpYhnl VskHW52IBZ4rxnMfse88PjQpTdoVC3qJoibMt5bR24Gjzbs+xsBrrfZT77D/ 0JaHejxojwGn/WzkLqFlpBo7w3WtJQYW1BUXp9mXUb/E88jk6hh4rsHXpUqz jKZuqssdvRsD+WOfay6OLCF+9+rVuhzM7UXcv7uXkIMi60PTtBgYpmJrGWxZ QisbC1SFkTGQrMxL+ePJEto2inl32iEGvitWe3ZGLqGrZ0l+H61jYFnhZ2Oe /xKKpdMR9DSNAedRiuo7rktofwNnwkuNGNC4kuy432QJsbK+Ur4qEQO0DDL0 6+eXkOUq9x/imRg40HNhH5fwEirqSiiLOxkDQ4pCpwN4l5BQiMG+btYYKOj1 l6o5tIQufvnRbbAnBtJSvr/0XCWhJ6YS/9y2osG2LqAljERC7J8DROJ/RcP5 cuOP74gktHuYIq12Lhr0Dp96SDdIQt76ctAzEQ1T7Zwi1B9JaLY/jjw/Eg2n I2guEdpJ6P2n/ZrHuqLB94o3yaaBhKQ0tcPF3kZDyiFVSt1qEir/kFOh1BgN Ix9NIsOfkVBmJytjYEU0BAhdOZv5gIQolS2vZJZEw23zhTS/PBLybS/yKC2M BlH+3rLcXBIyfivUO5odDf1d3zlyM0ioS9Z198+UaIhZc7jum0JChJbKs/Rx 0VB5XF0xPYGEKmR+WfOER8N/RtplczEkxA2SWZcDokH46HPX4EgSypYObtXx jIb3F846qYeREPUr+OnkFA0smp5eZsEk5H9pD2+0TTRQSu3VLQkgoW+1Crp3 zaJBe09bn5gfCZlfSIx+oR8Nz3e9fL7mTUI91d0vujSigWN38rP1nflEnHGG qBgN49/jQsQ9SOhFle7hv1eiYbWw9cMTNxLiF7slf/hyNLyVU9OwdCWhW88+ +wiLRwPDZ7NidRcSohPhKJYXjgZzXSNfP2cSCn5iPWjGHw3GRBazUScSWhYq pvbliIYf7tM/fTFblixIpLJEg/fI04+qmHsFhO2KGfF+lvNEmGCWK3a/2UgX DWWFX7MLMdfwvng3uCcaeHP1s7jw9wsWra8vb0XBai3PrmHMuVyXBWnWouCa wT6Lt3g9+/JDDTnIUfCp4ZDQAl5vKHtL/IX5KPC5Wfb5qjsJrdylqtOYjIL3 B54sfMLPa31CacFuNAqi1MLacrxIqP928rHwvigIuMs/meJDQgosPUq3uqIg +4Tdwzq8n7U3DgVWvI2CK5KdQSyBJHQvK3d04mUUuDnEfHfG53OQ6Qvd74oo 6PJK17bC5xeZznWZsTQKLrOqK8Xi872e8vjOlbtR8NLTwsQimYSG6UmdRjlR wPLxDhdTOgkpJ57Z8kjF3y/l0/cji4RE4mpMC8Oj4NmrnrOX75JQPtVmcn1A FAQy+fsW5JMQU7T0617PKPjGfLz37EMSWgt/w7bHNgq4ua9P95WTUGNg75f/ lKJA1PGA62YrCV26TDD+cTUK7H6Ya17twPv7p2QgXAqv9zeXf+kHHP/BEV33 zkSB7iOGXSMjJHQ/VLR+6HAU0F/fl3T3OwmFRKbmqExFgtLjG9t8/Eto4+rm wdHPkVBj+mRmJ7+991xPth+IhPXnloLnxJeQc7R0VEx7JKTuqZvNvLqETGNJ 7lAeCWULu4+es1xCUonKqueCIkH1xeV9OveXUK1yzbtm70iIcGCtVCteQuL0 3LKarpHAzZpCrV2+hE4n/77oYhUJYxTferwbcb1JfSzw6FokxJ25prH/6xL6 k0G95wRzJFCUCGQv4Xm6/nZL3e6nEXBS2CfZqXAZ2VDQV1MXR0Cq8VrcZOky OmCnU0GXFwHbzvTTis/xdXFiMVNGBCw+C3k+37qMGD5SZXP7RMDU51I1Q+Iy sqRUcr0qHQEP75zntuAiIzqnDAcFiQiQ320QdlOQjKo/jdgon4mApoq3DTVn 8PU8RxNtrgigAnLdI2kyenExWdGaKgKc474xKhiSkXl+v+z1f+GwLG+W+cic jPbSsCHH9XC4SGw7S7LB1/ufnvdcCAexVnYlNg8yonH7yB3ZHQ4vxMRoDsfj eX/gKHtsWzgQtOIKY1Jwv5WyPJYI4UDvpdcymElGFXu/H8isDId4v8ncY/fI yNj9Iv2N0nAYEFKZocM+RDUUQZ1bFA79FwKHPhfj6w+Y/hbkhINoSigdawUZ UdKbbDxMDQfXP293J70go2ceRT9L4sKhL+AZ40gtvo7EFysDwsHnafNhpmYy ejqiN9RsFg6UFt4n1z6SkaHM/d63+vh+B20ETfvIaPej2e4OjXDo1gr5nT+I fcnb782nK+FgNTUt924M+8RngIFL4cCcpTr9+CsZlV2hbRg5Fw5sxI07DlP4 +oHblZN8eD0vbvXGY78q9Zl8MsMeDvk+yzlzC2SkN3by8cLRcOAZlfnHh32L QtazaOlgOKTZCUnKLePPl9Tf/743HMoqWbyvrpCR7sE9ub92h8O+vCuznD/I 6N/SDaGf62EQPHyz7etPMnoUX3t0z1gYlChptm6vYd/ztPNU/RAG0T8sRU2w /zw2OdKd0xQGTV6dgrd/k9FJ+bcCX6vCID6i7nsd9qVSEe9IwYdhoOWv3vca +9spFp5xj5thoGFwn+Uh9qsnu3ovNCSEwZJvzAF37HPC38IzKYPDgFfpIS0H 9rHy/jNLaq5hsN4hZ1CF+Uzjl2s3LcPAIumalhD2t4pHKYUT2mHAcIdBIw6z WIbU35PyYcCyy7KsA3NV4DcDrwthEJNi2/od8zmb3KpXJ8Ngzy//tW3ML9SU GKhZw4D7BEfxKubzFzbsNPaHQXv69vkezDWcj1puUYRB4bkX9Du+eIFOn23q RyhYK7xJlcZc+5PS/9RMKPRSxgn24PVdHH/e6z0UCmnVh+RUMNe3WQs3doSC fYWA+jP8fJcrGONpXoUCWzdD9RZ+/le3m6Y0y0NBNy5n/hxmqSg36dz8UDie RDLSw/v12pn91nRmKJznzwiywvtJ0O/+cTomFJYjZJsN8X43omA1X79QEDsx lXcZn0cT0+juvaahcO/OM4o27NNXtuLNtNVDIXaw0MMV+2nLzIXaOzKhMPZ0 wZASn++b2hwXEb5QGHpf5L5JJiP5Qrl2v6OhwHtuKMcEx0tb0k/u5r2hoO/4 8PgTHE/t5lrDOsshsCz1RYwNx1snJYNswMsQmHW5LaKG/V91ueFeS0kIULEv EyVw/HYNOW7Q3w0Bx/KR8UPYZz+Utj+9Hx4CH2I8EkqGyahXM5rljVIIZBvt NdDC+aJz6ZwXg1QIaAuyV011kVE/z1S3vkgI3CWYnHLC88jgGopaYML3T6Iy ++8tGY3c/bO0fywY1D9NDf7Fvjsx79lq5BoM5JkF/isPydiHPF+kWQXDSJGY TRnO971vPB6+1Q2GNIv7HMz5eL7Kc48TuxwMer9+XJ/KJaMYPVeVvbTBkO6x bBSUTkZCLQ59tQVBkO494kLE81bjGYc3y9lB8PIVe5BpAF7vPftq3vggGK5z nx7yxfOdv93NdNcgGPge3j+C69UHEVsT+8tB8MR1w4LRnoy87lhOHx0IhLL4 VvVoPTKi3WvZr9YeCF06uhoa2Kfv+lq8jWoIBDVrSyMuLbz/WuaPyAWBMPpo WumzKhmx0Jo6vXMNBCsFqpwyOZw/Piamf60CAZyYp59fxec9bax2Ti8Qrmu/ vv1GhowcG43O5F0OhB+/Goa3pXC8eRv89KUNhFAazrDJ82SkOaVPfPInAJxq krdExcloRkN/YGo5AHr36f1IOEtG+0/pvVQfCICClbaXhrieF93SfRzdHgDi 74dffcDzqyS17u36hgBonON5qH6ajKwmtYP4CwNA/cDFEOeTeP5Q13Y2zQkA NyvK23S4PyS+0jLLjA+A+G3mlSp+nH83NdE/V3y/Aw53uHnJiFpdfc/g5QA4 f8/gZRgHGW3Q0KyuCQdAiZmrgAk7GS00A/EoJ75//Q9RWTYcX+fF2owoAyCN dPvqxRP4fMgLNYFr/nCd+YLlteO4XpcUProz7w/73itetT5GRplszAnjXf4Q cGDctfEonk+HugL+NfoDInq3bh8hI5+MGEeOSn9QZy5YUcN8XYVgIlPkD2wX fq0/PozrOdW6ilWOP7BY1Y4cxKwMz6Qi4/zhS0NTdgwzzu8Ae+GiAH9onH7K T4P59Dku9jdO/pCu3JyUc4iM2JdG9s+Y+QNH5VqjKOaDjzK3qTT9QfUbQ/0w ExntslJZ4b/qD+eDXX1SMP84Tjl5TdwfbOVt5tUxE/tffbLn9wehS3O0bJgH U31aElj8geFJW+c6Ixm9UxR5XkrnD1z+JbxfMdfunivq3PKDI5VrVH2YS1/l ZZOW/YBWYq/VDt/1NYxhmPSD8Pe7+Ccwp4gy+or0+UEhaUn2N+bQxY7rGm/9 IM3v7WN2fD/3B5EG7i/9YCrX4YomZmvzy4oZJX6QaJ//e2e9OiyrklV3/IBa TPzVEGa53icn+1L8YCBxylMYP69Esu3x1TA/2HhoQp2GWVCBnf6wpx+0Llmb b2E+RjH057yNHySnvLDywftHV59G0tf3A4E07rXfmLe8FMf9FP1A/mI0RSLe /2XhXR9uXfIDyyefbPjweX2dq2usO+0HhDBm6i7MLSan8v8c9INvVRfjLrHg eDtMTGfd4wdbDF8Fd+N4ePjxboT0L194xf8vsR9zvOz+/8JGfGFPHz/9bRxP gX/bdPI7fSGR34OYyEpGTi/D5Jpf+8IYT99qLI4/9VPf+fYU+oLPD66T93C8 ysyUHOHN9gWaU967X3LifpRnTSMf6wtnJKpCRrEvMR/qn4919AV9Tc3X0jje RzdryujO+YIql9WaO86Xrhdud0/x+cIfjWX/PiFc/10FU1SP+gLDSIkuAedX /tRt19Q/PvDP9Yf9aZyPdu+DxZje+MC4jSCPLc5nZ9rYWo6XPmB7ju7OggQZ eSqkIeFSH6gM+8bpLYnrU0uBmmK6D9BlrLzOvUxG6fVtDqGmPiB479huIVw/ 6ksPFi6uekM5SeK8iCbO/6QHTK183nB6QtrhuSsZHep4eruHxRvYhvbUP3HH 9YjmJecXem9wORJz7JEnGfFEdYj8/u4F32cjr9/H9VAyaFn5TKMXGL7iJWeG 4nhxkoy6o+8Fvx78PumZin1RpeunV5wn9F96Rb/vKf6+wdRA5wBPuJerrUv9 DO+/pdYuWydPeD3/7+kW9jGCz+B+fQ1PEKvr2jOOfazt/sRJyaOe0PTYwdH+ FRkNf1+12Cr2gPfjNw6l4n5xKfjl7OotD+Dnjv15EfeTu9SBLkuJHhDlFLr2 tZuMLE9sB35x9QCdIWWq459wfZHbe6NJwgOOHuDskx0io82bbF3Rbe4gEEbU McP+Zco9oR1S6w43Ym8MFUzjevOkcMSn1B2qYu+YfyWSUWSzwNz1VHc43qCk Ko/9jP6b2G4lfXfwP81a3vCNjFx9VuOvKLrD/u2D6u9wP+3Zrjlw6ZI7tIeM VHUukVE2sxTbKXZ3uHT7bkMj7seSwcnux7vcoE7jU7Ia7tdb6Yyh9BVuYPch 4SAH7udND28kbWW5wbjqK40FzEof84u/mLgBM5covT32tf1EvhcfkRsI8Zen sq7jfrtR2tzE4wbvU46NdWA25q4eK/zmCv8annzbj32C/cKlxayPrkBRzt5Q jHlKBdajn7vCXCeb2wXsH04+HUx2Qa7Ab2n3SBb7iWiiOqehhSvU7+ogAObV +33CSrKuoNk0N7HjM8Ht44qn6F2B5Su3Fy32n1uH89jzyC5AU9HceR1ztbXl KlO/C8Rmh9xvxNz7jOt9bK0LMLxM3DiA/Wl5aypv864LyI/cmzPGTKf8wMc1 wgXaTOgD8zAL3LRVmbJ1geKH1Y3jmOWI/Fz6yi7Qb7T37WHsZ5Zi82sdIi7g YkB77xrm4NCSLulDLpDne8bAC/PtTsfCynVnyGmOoLy943ssp/35xpxBUTyr phZzr+2S2u0mZ/Aqvx7Wi3m5qpyH4aEznAiI9ZjFTE/h/js8wRk0FGfzdvxR UE3s46oLZptd7DvvG+Vyfzyw13aGpAvN2zu+aTn3PHBMwhmKJryNdq6HiPto ap5whs+rU+gX5twICf43207wWUC8fW5nPR/W/1wgOsGvxD80AzvrOVH3qazd CU5fFz78GjPZPvARx1MnGGbjoM7HvK/mckhWhhM0fQ37HrKznj1/tWl8nWDz jtay/s56NBsFg4ydwHfs96FTmK3uhf1bJjiBDLtA4Oa/nXov02/N4wR/m0Yl 32LOvbC7dJDGCar3GdgnYa6Jbg1TJjlCy9PzXGqY+z5F6zX2OIJRmHwwHeZ9 zjS7im87QmlJVYg/Pk/BuvbBY6GOwO6won8Sszx14pMUa0dQcTgrOYjjIzR/ n6HPKUeQrOgO5MW80s/4TO61A5wr1J7OwfG2j7svurbAAQa3voyfxHzSLdv4 dKwDCFaOv6jH8Wm99yg1s4YDtC8v2fRh/+2XZjWbnrAH6SvU76dx/K8kjp81 eGsPv0SlHlhhZhi+T9tZYg9cFR3nx7EfK3hyvajytIf7Ah2kbpw/tcX89JGU 9uCtVFN6C89Ddw+I1XEK2kHsW+fz33B+TthkNbjstwO7vsgHJph563+9rl+9 DlVZYimdOJ+f2NS36DZfh2e70jhKcb431Ml2xRtfh9o9Zik22JdH/9P/upJs C8FZjUITuF6w19VOSnvZgs2zwAYtzNb7TxATjWwhlLp/9xtcXxZrv87z8tuC slDo31JcfzYZHH4Ygg0sv85JjZ7A/bI2iKr5+3/AKW/52BvPj6YMX2j2D/8H f0y4s35/xv3CWobOpPE/0D9kfyEcsyAD1YFfif+B+LfY6cxRXF+sU1lO8v4H 128KXfqIfTz45cpxX7r/gIft6n//YW7ap8PWumINiuXLZb9xPVR8eZTb7LU1 WAhzdpzGbLiv4FSGvjXYPSg3LR/A+2W1R+SLlDW8f25brot5osZW9BSPNRRQ +3v87Scjeyuh82/JVnB8ws1VH/OTmuQLTINWcMp2sJYa8wo9+aLFKyuwWrqX U4fnZb+a54Tf8Vawm6qcRwBzPf2RKwpuVhCT925qshfPq5b+sll6VkDg/KaR hzmWXlpRmNsKgrmkVLkxv7fMUw6ktQKB1uTZOVzf99fsUnu3bAk2k0LyFZhv WLZpWTVYQmdEr5US5mz1OzrReZYwekhF4wjmTCl3vUdRlkBKSc+Y7cH9Ukje 4L2dJfyo7D1djzmF5bjRkoolhFN95c3AnEhNNj4oagmGdPtCnDDHr7aanmO2 hD2Xz0gqYd73Vuz1kxULcNrzzFAIM23B56YftRbQXhcxsR8zZUjMG8kIC6Ct Yv208/5g2/BMe6iSBXxkTjg1hXlTfKTzDaMF/FY2XunBvHYw6iPdqDnwKbzg aMX8g3S6T7PQHGQWLtfVYl5qHxy84WgOqy8vvarEPP8gfHTsrDkwfHARKMdM DBf6wv3HDKgHzv5+innCtH/SvtUMPOcCzux8/rNk6Ex5khkcsKp99xLzILPg wqqOGfA0/2tsxty78ol0idUMvo7OMH7E/KEraCWcaApp449efcXc8Zhvte2J KfCw0DX8xPwm+uP6Ph9T8OZ2oqXHz9tkGfBHW9oUmiWa8/gwv5Li2b5FZQoT gTlBsphfsnTv/tptAvNPGG7YYK5a9aXmu2EC6zqz8/GYy3s46ZzMTYCOKtil AnPpk/cMlfwmUB3dwfoZc3G8N+P6sjGEPTIl0+LzvCfTzhIVZgzdFe1fXDDf YvVk7bhmDGkKc4sPds5/4wTngYPG0Lg2sfEFc3KFm8CdfCOQjd5YNcHxFJ98 7NSkvRE4qUd8vI85yr5VREDMCFad66OJmAM5j0o8bzYEnzUzXX8cr75bTRd/ JxgCt2yYYRtmj2FHaaRtCN/meuiO7uRDeqNc55QBsAT9U2rCrE9xXWd6jwF8 aCR+Eh0kI+2xAwYnu/QhpezQQiZmtdo6Y7dsfXAwX1RYxyznzmD9h1cfFjKe 3WvD+Xh24oX7IQU9qPzy+EToCI73pj2psvE68PBDUutVPH8bPiEvXtbVgUpF meI6zIW3Pl8T59SBU3zkErEvZHTB4/kuvlptYDI6NsaL53dL7v98qOe14K9p pNkRPN8/j24x7bimCeV+pwSPzeD8cy+vaz6kCQlztOZ3ZnZ8UlzYGzSgJTC8 i22WjOqciPl6ZHWgNJg8yoN9aN8H2XgWDTW4oX6rQxjXw8rM3Qb39yvDSc/6 GglcTxWcRg+mFStBSLZdSjXmUdmq92EEJbDfB1XnlnF+/LIiWLkqQnnErkph 7Ef6Bs18vB8UoDdva+3IdzL6dub2V+brCpCsbvA6FXM4rcdtqn/ykH33Pxsq XM9L6jgZ5oTlQY1mjIOMeetE+GpJiiy06ThOV+H6n75qUJ7LJwsNfRnynLg/ 8HWfsU96fRXy16a5kzGrh3797Lx0BVSCwjgscD8pmCC0nlGTAb1KvvEV7FNO nsKbMu8RnG8379fE/SibZ9yFe5MAMGJHKsc8FyOlN2MkDZ81IvRscf9KVv7D 43TsEoh7BaztvC/za0wesVa7CEuF3zVpsU9Zn2VPM46QhNhcphxdzJLHr2wq LUjA8uzJ+lnMPKm9z66wSQBryqOk07h/7t9tY3tR6zzc5RwQcMdMXIjtEaw7 BxPE6aIVzB/NWGI5l85CQ7OQrzDux/WfSi6zcJ0FFeGVdTvM6XVdxTQJoqDL 5v99APOa8avafwFnQG78ntle3N+7r37lWZ4UhnLGf1aXMAcy8W12VQqByMZf 9hzMmpvXbF8dOwm7i6k/NGLmn3LsKYsQgI7/OHfPYt7qSLl8Z4EP1CK4XtLt +ExlRXGiFi9EfD+zcBrz49t9jIF13ODbVpatijk0Yi3YgYsLPp6QrnHYud57 tqeSiQOkkzqVozHrFfoXp0+dgLgbKRp3Me/ybAx2q2KB1NLV5krMT69Q6qhH HoYor7a8N5iNGJVPCmszgfnc5mz/jr+1cGwfldsPUWITOTt//2VjVVY2ME0D e/z+li5hfkVxwTArahc85T7Dt7bjUzIxewsV1hpbLibs2dp5//hX8u2lfdON Am/c5Xf87tUha+5LfR0EcaeMxR1OpXEcHPpFJlir9P3Y8b0jb9ky3Ru2CCe5 HM1/77yPlI26u/maEn0ijAr/wDxatE6WYqdH5zW/WM1jvrK7pgDBQRTNH/bn M+acs+6dluRDqOIs81YX5gVroV8RHEeRepGQbQNmqSwie5HGcfTBs1DyEeb0 1vuKb8LYkA7htn865h8Bp+t+GHCi7rMBAn6YWTP3qu9Z4UJXecjXTDArlM5O HYrnQQ3fSWNSmN1bWv14OflQzdbDhROY3/wIKZDXFERqJbH+vTt+TmcioT9/ EqlJOe8uxczCI9l5PfwU+pJ841AYZmedH6txFSLIqoflCxfmzuo5OVVeUaRS oFpAxvE1cUU/TXdFFEm/8N+ux0xnfI7XNv4sKhu5UKSMmWO2wNVF9xxqTX+y uh+zuOfBOh9OcRS2++tGD45n88Qltdja80jEde6cOubK+kd+j+YlUU6tw2UR nB8b4RFt228vou76MDxr4/nxmslhw6JLSMbUpz8K8/u+/c9pzaUQA6vL2Med eYfks+zQh9Ax8omHqjhfEw4Unj1iIYs+HAqlJeL68OTHfuOWbln0+YD2u533 qT0DQRGuUnJI+HkecR3PZ0fu6vW0HZNHI0MpvlSYCwX3uvr1KyBmZ+HiA7ge 1V9xLxlWUkaslZmXl7EvjvOO90TXKqPnEwevXd95X0+rvCEqoILqVP1fjGN/ VPjAcy2BUhXdcHLcfL+Ifdt4iHgR1NDRC+ZsBfM4Py9ypKvlaiJ63lmCCvbH +LKBoqJPmihn/G9pM/bHY2zJL3/TaqEXKRLZkpilKH5/eeinhdYFNngFsU9G tvUK/9PVRhafzYUPYp/crxPbWX5AFw1NaFIdwj6p9WIzRltWFzFGl4UXYH/M Puwms+ari9o7W/TFMB8bNqiW/qKL9iSYXtPDPslrdjKv64kekjm4lfcM+6Nd 4z0j9wk9hBuSgTLmUg4mZmZmffRsW+LjLO5XZ6Y2402C9NHl6Oen+DBfsuvy XFQyQHeox8ZrsT+GtMsIp4YYIKLDrX5rzE0nq+fEKg1QEN0kcT9medI90wAW Q9T4wS/IBffPeDWmo2yqhsh2mHyYE/P78thPTWGGqHzh8o9+3H81PdwUaOcM UVG61A15zJm90xRPjhuhvKfX3HdhHjhn2KChboQM3L5WAO7nxmsyojerjVCi 0Ps4Wcz3DKoXLy0YIYE98SJ7MU/Unnz4hdUYqa2Wm37CvmAbxHScP9oYGdhL uDhgfjwW29/x0hgNOG+YXcS8KP0n1eWbMbJm/fqDHrNwnpsSI4cJ6ldwOjuJ fcWdgrinWtsEmfGMcNft+I6VYaNhrAn6mnHifRbmXy1d/lt1Jijk7aywB2ZJ 3ivn8pdM0PBUjo4W5sCY6iVZLlOUYqckI4759ezJx3O6pmjsV9fGMcwUivet k+JN0cGnRRG7MV8tYWI788oUVRXTfF3CfhZDFzfUSzZFN5tHmccwtzv9yfDl MUPCjK383Zjput1UjxuYoQRRapYd/1MTIVI3Jpoh3sNF33b8MD3NsNmq0Qxd t1d+sOOPfStdQVQ/zND6Y0O5Hd88on1FooTPHHFf/dy945uGz6tXVI3Mkftw 4tUKzHeYhcpWks1Rr1lXUTXmLz73bbObzJHLZuOP15g5h5g4JVfNkcad46Id mP+TjBv9LGCBks/rmg5hLr79JzvMxAKJLEb6ze/47qabBk+aBXI0cI7YwnzK lLj3XYsFuvIrMuAQfn7X14ZvHNcs0OMenACYDdOuI5rDlkhgSE5UGfMm5LOO iFgiEz1ekgPmOyujv0sVLZFiR3Z6MuYvWhov1IMt0eSLsYRRzG0LRzKVb1ki F4O+O3vx+T6N+OKm8MISNb/ipJfCHFzpcopAskRHtnKWSzHbKJ3fe4nWCh2o pDLcmU9UJrdmz/NaoUg1k70COL6OMyYXCptaoXs3NwUrMO8u0Qk/6W+FmpLb 4n9jXpA5Yc6XbYWO5dofUsDxW+teeoytywrZOv6Jnces39Oevk/KGsVV84xr 4Xwh2Ke70hpao43IyeTnmPkoDFUpva2RayQcYcE+uXpmjmarzBrpCmXFLWDO TKMK+3biP6TLpu30BOfvB/WrLu///Idu2TKfeYjrQ83sXpW2ozbozlfzLmHs k/dCPwm2nLNBmrV0KrWYncstiXVONsiy1CGvF/sl3f4wk5LPNmhSPsVz5+/F FLoblOIbbFHj06N/prE/gsp5foUgOzTlSnPiJfY79bKmy3DDDm39vCqitoL3 m05VS7LKDuWfbOKbWtnxCetgoQXMah/1abHPXVJM791vYI+6yvZ8uorrc8ej E/NxnvYoX272yM58b0jz6C9Fqj16r2jroId9zq/tteDPN/ZoHum92/G5F3Lf QofOOiAHt2InQ1z/ZR/4ZmuqO6DN1NsnejD37tld2uHggGys9f/J4X7xvYVl oCHfAc1cWyHz4X4Szv1gUfyVAzLxGWvPwHww8gxF+ZADimpvtN/ELHJF4VT+ fkfUlXc3s3nn93v5n2SOCTmi8uqUOQ7cv1QpzPQz5R0ROJveDsTsBF4R0cGO 6FmxWBkv7n+b7Ns3/t50RNuFnkNemBNDE5/4PndE+Z4sv3fenz2WLhiyX3RE r1rRS0Xcby/cO700SeWECv2ruOIwt2293G3C5YS6uj3ZmjHrm8qy9Es5IYpy lsw1zDMNH4TVDJ0QaSzBTgD3e+8TxrJtXk4o9c5KjA5myqAZQ5TmhFTevh0I xJw16u5aW+qE7Fs/o3uYuS9tRYm1OaHDoypP6zFX3o67XTrphD00maYPs8xv pmc8f52Q/jt/yZ33Zz2G99/cZXFGWkRJoZ33Zxa1J0cPizuj1vsW73b8avlo NTlVwxnR8sxs7vhUqJ8MFa2TM9JgEqjY8SmGoc7jEbHOKJ2F3Lvz/uyuhIHo ZgG+ft9JY8efTt2Ykvd67Yxe62oz7bw/q//lYkIadkbLw1W0r3b+/k/vt7vt qjO6mSDAubP+kRfRsV8OuKD6h/UK/pjtmQ/eNTjlgm6p/nFUw7zhdaeyR8EF nT/7PYgVc1wf/zslaxf0NUfIYQbv35FzVWMtIS7I5n0L92PMxZnSPy7fdkFX sjVu22A+/6OdpvqFC/rLvqvxOOY3WrpsIj0u6GdfXOR7fH66lV/PPvrmgrJz zo/snO/0QSdFThpXxBW28OIIZk/3NbPb3K6ITerQ3uc4PjLOMCQkGbmiS+O3 vg3t+E7suscpL1dkJmL0wB6z5ZdJ485kV6RxmS3hJ44/0ZSa0/RNruhDrXbt Oo7fW8T8w2UjrsiR6t2qO2YKqaR/yj9dUZu8+hUijveeRYueRH43tE5zabUW zzeSV5XrhGTc0IvsR5rHMeffFi98b+SGHukalfjg/HFX3OtNl+KGTv42uHIc 59fB4qqjiT/dED1T8LvjOD9fhapT5FC7o8d/4bUK9iH30tZVm0PuyN/jUqEv zufhXeXjlMLu6NOY5sV6PO89roh8JmfpjtQE7gzv/P8L07H1ImYXd2THIOjz G8+PB2ldbhED3FGBwdfDq9iH/C0MIqKz3JHp9TcBQ3j+vLb/tM6bNnf03d48 1mDn/dnFgmvZfe7osBndH0Fcf8ptj0jZTLgjvTTJZ6t43j3ymoKPctMdabJ/ /xeI69es08CarLAHIpXnBcnh+hfbEZrbmuWB0kiGg4NduN78+pmale+BIonq 17Q7cbxyOkT999QD0YcWf23vwPnlr+O8550H0uF82f+oDc9DAoIE2U0PdP9L C9OZJjJ6G/1pssXSEzVzKNf5VmEft0kZfOTqiWJE/eXiK3D+ySp1Jgd7Ig9C ynBOOc6v3c0v9G95IgF5utKHpTgfwiriFj96Iqa/IVt3CslIIjBNmAl5oX9l K8VUmTj+3NQCrNi80dQnKttNNzL6q77XVeGUNwqZvHx7zAXHm8hb61MXvVGa RYZCkxPuL0tSqr90vZFem35vsh32a8fTHAnJ3gj4i9llLPD+2NK/rfjjje4s HTe6rEFGLnLv6nL2+iD2daZIVTUczzxR5YFHfZCAOLectQqO16nNm3LnfFD5 SoHx3Wu4f1gsOg47+iAD5UuXNWVw/hh3HKQY9UEcclu2k2exr1WLu23M+qB3 SuZaLmLYRxnzu1d++qDNR4TP22ewf77zTZxk8EUty9inhLFfi/NStl7xRcFl e5l3C+L6lZZm3aDuixqQ+mIbP57Xvm02PTfxRUfbI4Kz+MjoWcGnkAc+vqgj eNpEjgfH4/6w9ZgSXzTL63yflgPHv+OiXmiNL+IslSTvZ8f1/63eC99WX2Ty Z/QvGxteX9BpD7txX1TtNdCpf2Kn/tz8aLHoiw5cdH4bfhz75dk9Iobrvmiw Rfb782NkNDQ/sqjI6IcmlerUJFhwP5eTV7rC7oe024eexxzF+/t/TdcdT+X7 /qPQUElCSDIKDRlZ1XlLlJ2KKGWUvaXslT2OM6xQRElSRoooIhENKmUVoo4R 5zhKycin79Pr9fv9+X49577u+7rua7yv+37O67lWfktjuz+a3KQfDgiykT8v yq2k7o/bym+9DxCYYR5nL6/rDz4O07mSDYQ+9340Sh7zh+bVUGdpArvxWm8R tfGHyNTFzgIBwp+dXoSvd/fHjvmSEwoE/tGoMrAq0B8tnH0cTeuJ/COet29Z rD8+Jy9lniVwQOCqK39S/NG40lmOl8C1H/zmfl4jxsvHtdXzs/FX4YsF6y6x HuNtE6EE1k4yrhquIfSpP5B2iMCxI9UCA8/9EWz9X+9GAr84IO3b9d4fwxUv X/+7j+bNob5rH/RHA1Mu5N/9sunsvEILyx+7Vo7P/Lt/Tj3uSKmf98eWBoZB B4G7St8xH/IEIEpEPuYTgUVW7jcsFwjAjBzzHpvAZxyKbhdtCUDQb/++NcR8 eQ3rl+fvCgDLQH2txr/7cdFwx6y9AThvfue4J4G3+Y830fUCMN3sW1FKYNcO c6lE8wB0f4fyPIFLdz69FHk2AKZ8zX2mhP7f43cMBnkFwO3UmwcVBFZhXCb5 hgTAul+1YTNhzwAszXFLCEC+VztnJoEfZ3sunMsIQDqvb7gosR/aR3WrzcoD YGXsulOH2L+Yu+WCxnUBuBvnYvONwK08Yhd1XwaghtL1OovY/yNPfiiqMgKQ cePvEbF/7ydstKbt+h6ARZqw9SSBuy68mNz6XwCmHIwyXxH+dXp73h0h4UCM U7su3hJjw9eVdbNdOhAnLVeN5xH+mXhbMy9GMRCXtDIWCgj/rdnWmTZtEIhH T2xfv5Yg8rmjJLXYIhB/HXt8p7YQ/PimV4KdfSAoZIEEcSIeBKVXhr0JDYSH htvTLCJedp6zCIhNDETuhs1NI0Q86VwvOL//ciASsuqn9xPx5isBpzvlgRis bySv3E7IF7tgGvc1EDvedhuKEPE7avXUgDRFzH8i61wVEd//Za/R/fUnEM/v N09ZqRDyN97WOCcYBF/pe3ONasT6NwxIQj8Igf6DToskIv7W6P2aKQ1C12bL 3mVEvjllnM4ueRyEiYe6obJHifxC/vLNvjUI3Dv6dI4fJ/xhZehAx1AQnnLz R9RZEPyQu6KlVCAY61d5yH62JfjqX9Fsx6BgmD5pNth2gQ3572xSl24Int8t EeXNIfzna5TG9eMh8CFbcfdeYyO3S0jF0y4EkU/TrhYQ+XV9LeS4Q0MgHcQr plpEyI+lrld9EAJStu4x1fuE/ECpNZyNIeAXsqQwK4n65v5wefubEORa1c3k VBP56ejnRYcJ4vfVOf5TdUQ+FFMYS5cMRbaFieLhVqJ/Xfvsi93uUDwtDXnz 4iXhT5wW/TtJobgeVN5zsI2Nh6NhHc0nQ1ER/WyfGMH/8yraa3/RQvHkksZ1 U6IfP3Xz7MOnuaG4rzA8HUHUrw2ZM/eS74ZijyKluYCob4mh4rdkWkNhudKB 9e9+yVfPk27+NxSy7pruJycIfrqXk7xldRi097X1CbEI/9iZEcsSCQNvhVV3 M1GPT69/EhyjGgY1+0++k0T9FuQ+5ndUJwxxbo9FnafZeDc77L3pWBis2q+d fEPw7UMDqx0rPcKw9Tmt2J7gC0ve5dteCg4j8s/OF3SCXzx6tsfKOCEMm7Q2 pxcT/ONC1QvzjZfDoF+Tk1FK8BWF22dMhwvCUHps9kQOwWfGr3w3uFcRhodd D2z9CP5TQInRDW0IA5/KdWgQ/Mj60kYt/fYwiGn9iBgmsPCFEs0NfWEQsDW+ H0TwrQ7HA3uGvoXhTU+/4yyBySc7FUp+h8FfL3Cn9b/zLyMX+UCucKx7cz/7 zr/zRCxK664Px8fjXw4O/jvfU6RvXrclHAI7TzQsENhPWkakf1c4Ih0P3v7H R3cL1Qjc3hcO022c2cMEHl9hvPaiQTg+qKzdfZ/ABX8GVxywDMc5a4VVjgS2 Zl9YttoxHDu0XNsW/52ffVn+t8c3HFUchqL/1vv+w9W5gkvh8DDruvKR0IfS svunNzUcCXp5s+IE1nvUNLkvJxzedr/7DxH24Cyx/Lb8DiEP0/NHCXvVXmN+ /VAdDpnNXhxa8//uF3frPWgOB7f8E4YMYe8Vob53UzvCsefm1bnvxP6UT1Tx +X4OR4n5fZ4Cgs+dODV/4RgzHAxL3t69BJ9bbN3fqzgXjmi9PZo1xH53XGnI Xb40ApvyhOdFCX4XsHLZ0rG1EbjwbM1nGuEvr57KVFoIRuDynk1l15lsiAce dmoRi4DotuUqWQSfax5NfFUoFwE/Dse3ygRfE752N1RwdwQOvGQUdRP+6X6i XSFWNQLm+9yrbQi+xt+8Ls3hYAQom+niYkT/6RCifKhTPwJMqWpj016i/1U2 n9UxjcAWaw4HZ6J/tbmeeVr6TASOu94T1yH687vhm2W++kVApuqa0u1Gwh/V DnQfC41AQaotx58nbByfPJvQGBWBhRf3ypUeE3zxdCErnxYB6n67CUMivg9r 7qyyLY5AbThLajeRD7K/mzi/LY+AfV6QcgGRPyaLvEW0HkbA1DGb/SeT4CtC D8I2N0WgRGatwBkqG19+ah4e6I/Ann2lp/qD2Agp0+uxWncJlsdXuq0n+NMb R9fEV0KXwCxJfss8RPA9cfK+veKXMPt5B1cZwZdekN/kiWy/hNsjqyzZykT8 uZ5w6dW5BIaEb40rUS/Kpe3nTwRcQm7YupnSwUl07rm942j4JXx1d99a1DOJ +UOT1oaxl9B5U7uS8nYSB10CniHtEuT1X9dubZhEVwmZLFt+Cdu+jrdn5E5i UbVSfH70EuqpIzekTk7CQJ/7YI5FJMZW7QzueMmC1ynDi5etI1F50P4FVyML aW60W3SHSHj+5xxyoIaFgWQR3ljfSKS9+vS68xYLPh27Oj2pkfipXKxLjmEh 08rCSaslEp8E21s4dFioc7+apdkeiUf3dM5u38fCl9ChVyqdkdhAsdV2V2Fh e57bbrmvhPxg3gA1GRaeMMLn1v2NxHTDyUXe5Sx8/dW0nZc7Cq0OS9au5GBh Oc9Ka+7VUfDdnkiXmWfimFxa47xIFDhtqhweM5kY9ihK+qoaBRuNFZZB75lY sr/5vNP+KJyZHFgx2saECO+XkxMHo8AXtiB7oZUJ02JR2WnTKIhtjrD8UceE W6D6Wn+LKCRx9dQwqpmI1TOfmT8TBZXTyvLz95moHaE0cbpFQW9qSSutmInu yjt3Yn2isPa8nMb6QiZ+RLemrAyIQodKg9bjfCZkpTjt+GOiwNuwGBuWxcTB H+J6GUlRWFPwZT47nQnrp3sVRFKi8NyT6vWZzkSazcXFLdeioCyqXv4lkYmy XSmMmzejsKs6NP96HBMvF0tfyd0l9LWWHiBHE/q+flVRUkFgs6Dp/EuEvlfH shRrovChme7+JYwJUTeuS5X1UXhfZdhhEsKEqqaks8bzKORz7rgzGsjE0RU4 Uvc6CvzrjgSX+DPh3mOleuB9FHKO+jXlXWQi7lbApubeKKT0vuJq9GXiul/6 Mv3BKIw2rapdd56JOt2KidcjUQiMO2RH82aiR+BNhykrCgtiU+4kLyamv07U fJiOwvaYsuNinkysub8833I+ClxywXHyHkzIRcrE9y2JRoT1KX8XdyZ0jmp7 2fJEQyfbk9rrxoSNhM0JxupoRFV1qwcTOIgdvN9ZIBrV78t7TQic/iRTmikS Def0gQ9mBC5PrlzlvSUaInO8ickEfnW648f0tmiw32WbzxF4ZDu7139XNG4t iaNlEvNxLKx6uqASDYlGE5obsR6xl7JF4XujwRT6WHieWK9ali51qXY0jpDP SpYS+hxzPusXpxcNx6XuxuI+THiohZ9ZdSQaSyXDPZ8R9ojnvqpDNY/Gjdi9 rTkXmLjRWb19/eloFO3YmVXix8STgk7+y2ejYR+dIzodwESv7485EZdodDUn xXgGM/FTe+1Qrlc0Ub9Dl0sQ+7eWf0erpF80KmJc3vEQ+ys/pFdWGBKNALu8 5VuJ/bcNjwwtTYiGu5u/AXcSE8Em1+yVaNF42tRBbqUwkbGp1rAqIxpbHpbe fZrCxOvHvzY+uRGNPo/0GssrTIwm8nNoF0ejLpBZMXONCc5TCmPN5cTz+rH8 VwVMqM86V7XVEfZySFATKSP0Uek71t8djT8ZxysPP2ei6Ne3OK2BaJwlG1QF vWbibtXv2hsMYn7vP2lDHUxUqa/f5vo9Ghq37n3XHyT8d5/BwszKGGR99CkN WWTizaLF7lPrYjCSq338EBcLH544ONQJxYAVsSB0YDWRb7QuvYmSjkEcS2hp 6yYWfuhU3+AjxWCPxaTtqgMs/OZ63uOrEwPHcDttEwMW/jx/v7rbIAa0rFij uuMscOuz/XMsYmCT9C1bzImFjcZbjeR9YpDw0m7gOZUFLfO0nwcLiOcLicnd oyzoCl6Xu1UcA4nTWc5np1kw6C6zXnkvBofFPJq4/7JgdvJV69u6GFjdUPNM F5yE8xnOnDPdMdjv2rU769AkqA7euv4rY9HnUnQ1qGgSaVvDgj7yxeKY7ETw wweTyBxNKtsvFItooeiDTCI/X3e5tXGZdCzu6F/7qNQ7iSqPARZtfyzMlvLf HF5O9CO7mJI/D8bCxrKuNpXoTxrYcxYWBrEoDK65I0nw/5c+Gxo3WcRim6Gm ZZfqv/N1o4xi71jAjq9a/SwbD2ihhpn+BD5enODlwUbSndIlsWHE+JTuersA NtSH+NzsyLHo6V+5zDGZ6M//HJA4khqLpWa2zZ6XCX4r6Nu5LzsWT/grzCTy iX7GqBPCRbHIP0JqcyXqp7MT9y+uslj4d2mKzhP1FZFqxdOVsVgnwb1scxNR z3KcbYZqY7HYY1v64RUbzIdZAm+exWL81wMIvmejsePli9qXsTD0kBkYIOp9 JmshrPhdLITSzlfIDbLhuXynSmZPLHI5TMe/D7OhK2X9LeZzLNSYDo+UCH4r RqLm+o7EQvdVv+0om+iPLRuO27FiMW8ctW0VwVdbfb8vP/IzFvyRxo5ZBB/K pUg+2bcQC9n8hZhkgj9duH3cV54zDq4/5Ti/EnzLsClaVnhFHPqn7rr/u/+W /FzZz8UXh3VBZl7/3sebnRtJmRaMg/uPU2/+nV+2CwjrDW2Kg7GkrVcZgW8q 6C+2S8ehddnDY3eI8SEGQRW12+OgJVF+jU3IP+Zwx6lYKQ5raJHXA4j5ZSP6 xDI14rA4PPBGm1jf3+zVHTFacRihk1sMCD7WVUmK8z0cB8swdYtkgn/dfeu1 z84kDvQTXSE839iInMj7bmJOrMdFy6XqCxsnuTsK952OA3XxWuRlon/YvWXp aflzceA/1u5YRNibe5/KOmHXOGR3prBGiH6k74TDcy4fYv31zfJHn7Jx3ycj eNo/Dk+bH3sPV7Fhe2t2uD0mDnOBdvmxRP+k2ih3pZYch8MHxQPoKWys7j9l WpxKyGelKzVGE/yfv+5RTH4cjv6+vi3NkQ3azkkv36I4iH2ri9hzgg0nvc0y dmVxKJ3y+/NHhw2BsEvUfXVxWE0908hB+PN4ZoWOfFMc/mgGBB3gZePp/a9z Qq/i8EhMVPHu70l4ftO1n+6Jw9tTH4pXvp5Eq9lKjeKfcbBi77VScZtErtfe ycsLcSg72x3Kf3QSFxPdb8RwxqPiV72osuokJBvaV9vxxSPfnnnb6D8Wgren fhHaEY/9aZ8a7WNZ0Ft21YiqFI9XbefGfzuzINBfUMWtEY8V1W2Gyw1ZKKVU Jf7SjYfhhQOcD4j8NPi9V+m9TTzRq4Ssak4m6le1RBQlNR6uwcOO5NAJ8NHl WFzZ8egcZVPcTk2g30XJIjQvHtULeyM3q03AT1Rnu3tJPGxq32pvmhrH7TCn 9/ot8RhXXPdzvd041uiWSnEtxMOi8Wrx9MFv+LjpYXIIRwKOMr27OyS+4dZM /e9pngScZq7jHFocg1bRu1dfBBJwn8fnY271GHxX/fJt2EXg8zt/bFcknjMW +9X2JEBOY3xyDd8YeOu49cr2JuB2aPPYYfYoCj2FxXL1ErD5LVdLW+koet7t bQo+S2DjxpPXlUZRUKyza9qZmO/bXY4ygVH4RBlnunolQMlwabTy7xGs3GPj fjIkAeNG6vn360awPzNSQC0jAS7LT4XOmRLPfZLCSq8moGkxvWaX2gi69NPG ZG4k4EwY1Wpu0wi8F27WCpQnQPjP0aLTrGFct35h/+NFAsgPSZGPUoehRf9l 8vNtAiTPNA7ohg5j4NkWjZluYn23cyvznIYhIhe0en44AX/qKio6ScOotir8 vcAk1ufqdKR6+zBOUDqGFqcTcDL9sUXwxmGkTstXcXAmQm6Y8fX+bwaUtlrk LV2RiDmPeAmlMQbeWkYlcvElouDKIVzvZcAzqewCj1AiHLR+PVv+mgHeJ5+s V4gnArX+h1zrGSie4tFfJZMI0XN6F1/dZ0BPSkV59Y5EjI6JCiveZmDE3HbT WuVELFRI8uddYyA6nsyzTjMRGbHT9psuMyD5uPo7/4FE/BgfViqlMtDAYnwS 0EuEWUnfU4sEBqwl1j0XPJKINHZL6OZoBv4c218ufIIYv8R8YWUEA9kxLtki ZxLhpZ0+vzmUAfXq9Ggx+0RYnL3uYh/MQNf4U09xt0SwTu52Gghi4OKmSUuJ 84mYNpTUTSOeC5iKHJQMJH7ftjaJTIyviDy0UzoiEe/7ns22EfJNK88LbY1L hP7j5HibGAYmR3M5ZCmJ4PAJ8tFLYoAs8mpCLj0RjTNUOVoKA/LGvzu3X01E WGCoE+kKA63hUg07bySCa0OctNVNBhwrjhQrFCcideRlzmQ5A8uGg9MU7yXi zVVHc44nDFwXKgpTrk7ExlG19VcJe2sZfHDeU5+Ig/KLjJY+BgZClhxXe56I ndJC4pRJBtF/7div0ZYIlSexJ2Y5CH/4Yrlt74dEDD7d78InNAyLw/cWSF8S Yf9QqOX8oWHMBPYPa31LRLBr5Nw722Gk3V3xVnsqEQJTd14sJ/zr7bqzBYf+ S0TyUOoqucfD8NShUPS4knA+4HCBbP8weP0fBRjwJqHz7tvVOzhGoNfHb2wi kgRXBjXW9cgIRtZAzXRLEoKN07UfB44g+oDblmOyScjfYTetWTiCp4XPfpmr JqFSXUplkmsUtr3szxb7k2A5XR+lrDGK/1aJvTypkwT8NGW89ByFps+F3DPH klA+90OYZ4iIzxt58TYnkxBhXOV8f9MY/Lpen7ezTcL0oI5Aw+kxVOyVOezg mYQT85Oe7KExbOfuYrsnJuHYLM9SCs84HshPbzOhJ4Hbd4XCE7Nx7DvCZ6uQ mYQER5NPVTfGYZRp8Pb7zSQoGFhWmh6agLt8fbnf0yQc6qYma10m+KpJ35hF axIRZ05hCxNMhPjOSWi8ScLe9VKTK7RYINcq0xf6kiBEW3F44iuRT4dMX/R9 TcLs4QtlQUqTuMrlyfFkPAkUh9bxztBJSMsnaVz7ngRlAWaHYvMk7poU+UTM JuH1h22e93nYUPFtvm33l7BHFEvSh6gftZe/DGlzk/FJ6BztAtF/69T+3Si9 moyYW9c21RWx8XpQ7BiXABlrS0yPHGxnw4xLM3FEhIzQOR3mH6J+9slZNLZs IWPxTRNriKjH9iYX5otkydAqL1T89/4W6zxdKVGBjM8m79v//R/T73Kpq5sq GSd3eg0NEfX2v8evrhvtJyOf0ZguVc9G7ODYx506ZDBOucmcIxN8iot7/VpD Miqkkrx3GLCRISdlOHWUDGfxiz2as5MQN9GKemdJxg5dniVhGZMoPH/mcYUN GT7NNkKbZCax63LQdKojGeBKOR9QwELV48vbL3qQoS2tpi63gQXS4INzJy6Q IeZjIPiX6N9M5NjvhSPJKI5a72giPIEuY17e+XgypEOvO+hbjsP6vJzOJyoZ naqHb5ymfoPX43MPcnLIuOJKHhscG8Xs5whmWAEZnPmvR9zWjCJiWa607R0y hj8buSsqjoBm3JMmWUOG+8OFT7suMFD+2ejirQ9knFBoYifzD0F9mWtJ/Ccy Lopxfl3UGUSDbNywyxcyXlzc+NFzfgBvfZ6a75giY6zl86sujj5YZgwkr/5N hs7GMh6J7I8YfLTQPLlIhuiUSnKZVi+mlqqq3luVDLf62Dadmi4EyB73TOFP xo1ejVHtpE4sMfYu9N2YDOFxWlak2wfwZRQLqm5LhrVtSPtV8w5kPmoxEdqV jJ6fxjeqrd9B4jMjdlYlGa16t7jzLryFouzm34+0k5GgmRDcltCG8pUCDBl9 Qr5VkneC4GvsYi1/RzuSjANj+p5SVS8hX/Gj2PF0MvYz/XbnybeiKG308ruz yVAQ4Lw8uPgcW/37ove5JKO5pXy0drAZkvueW/P7JaNCKyBSo+MZ8sQfG4aG JOMC/V673edGiHOUq49FJqNKIY+hOvcUos+z+J9QkyFmuFNI17QB2UWUv7IZ ybgl5tAZJlwP4aQoZurVZOyVetP3rqCOyNcez11uJ6NtqUOh2swjpCidvf+h LBl7lCvTUFMDvg0WeahKhtqFYBcquRqrP2oFbXiWDKvCMY1LtlVEfO5xiniR DFWJv2VhNpVYeU3ebOJNMhqF+H4Fuj0At73Arqd9yYg7RS7NvlWB6EMrRHd8 TcaVD+KJPl33wCn3H8/lb8mQytH/e2vtPfxljQ65zyQjX2tz4fT+MoS97Wvv /pOML+dz24THSvCn4t1j7aUUeAtvVu+5fhez/o/ThfkokD/94XD+oWL4nSqP jBKk4EVNec7yXbfxc99Nr0kxCsSWlW5ukizCdw6qfpMcBbsuWsFbsRDejChV hd0U9CpdNhI0uInJ5wFS2aoUWEVaqAV5FGA86eyi10EKBLeUNul1XIezp8X4 R30K5Mznikr4r2PE1Khb15SCl68//31mlY+vG1TviZ6hIMz8wflD3Hk4Oyuf G3uOQvDIndbNbbkY/Lg56bsLBVvObHi5OScHfddWOLT4UXDh509n33NXcCry v6NKoRSMJvFqbDmZjR77aVJOFAWShTMCJ09loVOuX9iXRsFwd2jGrtDLMOPt 4BrIoCC748GyZzkZ6Jh8/kMvh4LGlFqF9pZ0tN8vfy1eTIH6Dd+ECNU0GGXc rEkop8DBTyv5WFAqXgZkF/6sosB/XZ7+VHMKWvZHR7x8RsFKoRmZzb50NLRY qPj1U0DXrNTyV6eAb5l3vhuDAtUbZAt5gWTYasWvsZugYDxuQtb1TxL+VleP Gc5RoOnavGr7VAJMfr01P7CECpITfRVlPh65it8aVXmosA3ULtVaGw9S8cac LRuo0DWaCS8yjwVlRHGlkBgV9/oi4/1jYzAgaeDPK0XFxXFl+Rf10Qi9EnT0 924q3nHmPnM0iEIt+RNXmxEVvYkuqK+MAO+L6fONx6ko+PRRokwiAqe5eAcf nqIiLczC8I9kOBZC9z267kzFoPGzegeeUBg8MtuW6UVFnc+Yv+aKEGTPuKcl +1FhQ5u0/SwQDE2vHM+AaCrEo0vuTBwOROKdyk8eSVSElov1xHsG4ONom965 FGI+tYQDdjn+CLL9T9IkjwpatqPaWX4/1By16ZaqpULE/fupj6a+WE7x19n4 jIrh7zVPHcvPw/Il9d6al1T89ZvIa9twHrPaDUlz3VQYZ7sy1b97Qy+8Z3Zy gAqd4yZqrxy9kfl4yoExTIVb0ObhwkYvqKts0XozTcVNET7BuVYPxHtrlDTN UyGkv78mpNcd7l2yq/uX0PDNwTrP64cbavkPBHXw0AA+GdPj+1xhleRjVreB hqxq8p2ibU6IvL24Un0jDQJcz8okfB1R3JLwtEKMhlW/jm6tb3LA/NLru4qk aJhOOjMSGWgPScldw5LbaAiqzBBW7zsHA61HV3LkabhUMmWmrHMO2SEdy1MV adBUkQtXkTqLxmzr+tV7aOC+X9nxKcsO49XjF+PVadAdTny9aoMdNH9xfg0F DeKcMyvOCNui10O5ztmYhglXbocVOafxx3W7SZEpDdFLlOr5eqwg7iz1efQ4 DWXKs6T/hK1gf3Y9h9MpGrZY+j1uunMSUyemdRycaPjREa/4Y60F1ptNdBa4 0rDBvuvc2osnoHr0qyPDg4aDxws/lA+YI8Twffy5CzSsKNh1kvnEDMu17r+2 u0RD2E77PxFlx7B9/50z+dE0pD9+qvxd5RhMNG9MDsbRYNRVZNZfdxRpKql8 thQaptz7JR71mkJCztfM+goNP/XDHth4mODgVrfhnFwa2rLOyegUG8NR6pxf fz4Na+SUVVKYRri76Xjm6SIaNEg33zRGGEKdX7nvVCUNpGjeetmverBau90j u5qGAD2KHOdhPYTxSv3X+5iGq8aHPwuWHUYT93qJk400/DVa1eyTdAimCz/O WbyhYdz47eoCHx34zo7/zOgg9iuyMID750Fk/PoS09VJw+dDRb9rAw+ij91x y7yPBrcjQfRnFG04Myomjn8j/GPQ+lNZnxaShopDUpk0rH2flivjr4XSgeur 37NpsHqm5LJfQAs/e1IUjs3QcFv2/o3Vd0mIaDvva7qUDqsOPksh5l7ceOm6 jMZNh7LNf20Kh/fiecvZ9Dcr6BA8+9csoFATvI3HHprw0VFy2pQt6aOBy1VK C0ab6IhM0dR+p6yG0h1SyiESdNx+srrzR5kqnl9f73ZHio5n171PGymoYoby 8+MKeTpGQiprjqjtwQmnqkfPVelYWZXcYu6qDM/+wh+/NOg4ZOBhPLWohNjj l+Vl9tNB0nhsLpWmhCoEZEcdpOOzo2HN6lZFCAprBmmZ0iHe8MZF3mg3dlHk K7yO03EgYu2I/7ACDi0THc89QYfitgyvN6oK8JtaOLl4mo4Tl1x+lAzvRFdr ncYjFzq6DyioHvXZjklSqc83dzpUdoU80eyXB3dl7m1hbzpuLAmqpxrJQzU/ fKO/Hx3hzy46Se+RQ3rggTnlKDqWhzlw3d++DXfZiornYukYda2LLS3fiiYH SZeUBDoCzsm1XVDfip9Hl/ZOUelwEUo3FjWVgZl8c3XJVTpuHnidtZgjBfe8 yqm+a3RwZvKqB6pJIVqwUJb3Bh1UfiMq6b0kHnDGZbreJuYXzmnyWCcJgU96 Aduq6Ai96mk6UiiBHUc1yk/U0BH0Zd+MylEJ6LTIjcXU0rFs8BD55fxmXLi/ 0pLRSEejwC6loCpxfEh6rZb/hg5tvcyHShZiYHLUeb3tIPRXb26LaRHFsoCS W3876XDQ2Pl4WlMUKvYUIes+OjjCqe2d8iJI3Wf6W+QbHZcPZd1t2iGMNJtj XlQmHZ8YG9/33BZCWqTZ6NIpOuKX+Xz9LieEjFbLbuYMHXP6fS3DSoLINLN7 +GRZCsz6W3S7HASQ5X9OQXl5CsS25CevnVuP7GyHW7dWpeBxvEZeA2U9rgy6 XKbxp4A35aqu0VN+5Lqf9z8rkYIl3e+FvA6swzXqBXaXVAr4E+O3vRjhQ16F n5PhthTMZ73ykKPwIX82yEJlVwq8nnU4pjevRUF0lBr3vhT0LAqeStBZjZu3 YsqCkELwNb+NXCW8KHwZt42tnYLP9z4/6RTmxS0+slCPfgqePcCY9PxKFF9N +33bIgXyzfoedkPLcac+w0vcKgV/3jmSnM4ux90vmaMp1ilY9Hsps3OEByWy Od3BDilQzKuPfviLG+UPbj409k3B7FVJ8jplLpR331Jo9EvBaBTfgk3rMtyb v31LNSgFJbdeO/2yWUbwzNLLmy+lIN5ZrKg+fSkqX1f5f6cQ+sePynqIcKKK Xc12SEkBt76GO7mBA1X8j50+phPjDb62UZ05UG1Zb/HsagqypuY3Cj1ZgkeM FrX04hRoJo3U8Pz5j9Twp+e3+vMUzGRwCy1LmSfV/nfI4PyLFFQbqZuvFJkn VS+pvHrndQrk/jZctSqYI5Utox8Qf58CnWUHVpTVz5JyefWTlg6mgCza4NO1 9jcpe83D/n1fUyBlzC00VTRDyuCT2e03kgIZSuPM/MEZUrIAR+cYMwXTM7X8 teG/SCFiNeLtc4R907kz+3l/kgLEt/nwLKaAZTFp6vNgmnRBIv2Z1pJUDP0K 23TnzDTJTdrH+T53Kpg7+rewH/wgndohV5G5PhWxdfLHuy5+J2nsy9I9tzMV tASzIaWLkyQVEk/m1d2p6C022zr8nUXarXVxvFOZkLfv4fkFbxZJVucoVU8z FX9aRo9J+zFJwkYrenceTsUyqofV1ivjJAET/+1OBqkI855QrpIbJ/GZDofm GaeCkr76kemjbyQes6eS681ScUVOJDh0aIw0YxXoPmubihqNK8zCQ6OkH2dG nyjap+K3WP/7YMYIadLGfJ2bUyom9vr/XBs9Qho+p1jV75GKgnnepuOtw6QP bt/+NhI8UGvW2sfenkGqCD6ZmpyWissndv3iYQyRNlX+GNqamYqmWsWGm/Qh Uvxk0u6GK6nIyxf80qc1RLKxe9L243oq2h9ZSf+6MUjiPSy13PJeKizS1bZ+ +D1A8o+oPfH9QSpWvayT+eQ6QPpSY34zsToVM0vvIGOwn1SzI167rj4VHaGn Ftjv+0iO/KwQyfZUbKVU6FT2fCS9M4x99fhdKiSHv8YN2Hwk7YvZLGLemQrD xkfix771ktbPHn0Y15cKDjGhxjHOXlJDf9V35ngq4gpOOKQf6SaJ3o5wfMiT hrS2rLh63Q+k2C8bK01XpcG+7eliMPM96Yfo/aXja9KwnZ324nPae1IrZThP TDANp0oHeoLHO0h+Fww+XZJOw+WdDwRkit6Rhkq+yonKpqG4+aSgptU7ktFo SMCD7WnYcbOo8+HadySpU2UbRpXSkN/IZfYu5C3pLdFhGR1IQ1Y5X0FoWztp b2BJ7rAOIR9Ujyq9dlJhxSFWmF4aVnyZlbd43kYKlQlMvHckDds8KjvyWl+T 5FcNNAlap4F73eh7gbGXpHQd//XldmlQT3Y9Y3jxJWlJGN9ZfYc0dOxQqqAt e0nqntL+G+yehmCRMdfNci9I2vJ9xhu80zC3fYOc+ZNWUum5i1dLfdPg6Z3g eN68lbQxZ83EYf80vP4u+85jsoX0f99jw/9/j+1/RWTREA== "]]}, Annotation[#, "Charting`Private`Tag$12701#5"]& ], TagBox[ {RGBColor[0.772079, 0.431554, 0.102387], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUmXc81l0YxmVLGSFCqJDxRkkoPKdQ2XuvkFVmZvbee6TIyCwaUrIqN0IK 2Sl7VuZjlaJ4j798vp/feM7vPve5ruscx6xctG1ISUhIYqhISPb+hn9+eH7S Nx1u/eoqfrjgS2AerVsp9U4Hu3/2ReKOfoSi6c6Hbh7p0BQ0f02D6EdoXlln IXdOh76vOdk2//wJFLQX1/gt0+HRs7cNjy8EETIYdUqJZukQrtQhJt0TROBn s7WoMU4HefWZVbtzwYQrfPGflHTTQYGvrK+4L5gQib6UOV5NB9G+V0K1J0IJ h68sWJ5TSIdI3cFRKv9QQonqDtvOxXRQYmur5fkcSmg14o1KupAOD5b0c78k hREoPVyvvziVDhMld+XC2SMIUY+oOX8zpUNQe/HHqoxoAls5R18DQzrUM+zG 9zLEEB69EomNOZgOtMiC1jMhhtDWpPubnSodpnWbjKISYwnUow/6ZbfS4OBj s52IinjCvemXcZSbaSDjxXjL51ICQWC+Va5rPQ3uiHZZuPQnEBQ3F59bLKUB Hbt71UOyJEI04/mEsIk0YPeM0S1oTiawsakqqI6mgbz1+nT+kRTCI65r28xD aSDsPqrk5JpCaBOOuFHSlwY+n9evppxIJdBc6bn8oRVfd+Siv5ifRshSnfmb 8i4NHD26yz5RpBOEdDZfGjekweplXxTmmE5Qtjh6fLE2DZKKJAeTL94hxPre 2KF7mgYqbf3T5eR3CWf6b3qmlqYBI53BDmnkXcKXU46LLCVpIPq6Rdl8/z3C yUnnIc68NBgzz3vkx5lJaL7qUSWUkgZP/sRIpdrfJzjme556lpAGvkjbzJo8 m8C07VV0JjYNFtNVVOYKswlWz3xSpcLSIM2/nMtxOYewyxzkfMUzDWic+83o jR8QSpyDZz/cSoO7Th+P8Nc8IKi3hZiqOacB/8iBt0Fs+YRsv3BlXbs0MKhj uSM5kU+4MBXDb2WUBurn9pe7JxQSJqXjcmb10qCaSVbKaLeQEH0nnvmGdhrU P55OJPcoIgwqJpG6qqTB2mQ5+aZNMcGjPH0sQDYN9BX0ZlydHxI4aTL09l1I gznfMy4Pfz8kvLO62xEukQYuOqJPrkQ+Ihw6nFUXJ5oGkcXQzfGklFDun5eR eSwNMiOVOz7xPiHof35w8ChXGnxYo/HY6HhC2BEtCH/Angat57OZ1H2eElSn i9weMqVB7uDOP4bxZ4R5pTL1VxRpkFwZ+pt19TkhpfBxixRpGhSxXWAuNqgg SP17IvNmJxV6ve7btzdUEKKelwu920yF3fpuu//uvyDwsr6i7JlLhbq5C4nG bpWEDteqAN1vqTCQeuVrG7GS4P6xemNwKhXcraslXV1fEZoC6qbGhlMhAUkX tvhVEa7NQP1iZyqkad1aO/O2hnDgmp7J44+pINxB31GrWkuo+Tq/eeN9KvS7 Z1HAeC2BoYvlzPeGVFh1FTTKY3hNaKp1KJx8mQpc/xzeOz54S3AW33fxwfNU cMhf6U1Wryewl2eMmD9NBZoI8aJdEiC4FzWyjJSkwsbqlHLm+QYCbxJr9OfM VDj1tKP1ZFsjoZvmKe+djFQYOpR5jkmsieAfLteok5YKwTpWxkW5TYQBH6et 7vhU8FZ8sUsS/I4Qaf3OsT0oFYZtPQSabFoIYuOGNLH+qWAk+u/6r28thDGj 5WJFn1QwDaeUuuXQSpDUODLe4pYKWux9BRmB7wk/zrtoNdikgnyStoty9wdC eiX5cqBVKkzwZAoZOX8kXBTNipW9lgoiUWHTtxnaCZm8Le/qDPH1LzEy1yw7 CMr0HBKvVFLBOpZZgfd8F+FXzPNed0Vcj5blw4e2uwgF5FdcxC6nwsdkO0Rt 2U3Y/uP6qJyQCksunF9+iPYQnsy0spedSYUFBZkVHWIvwfCaabW9SCpInxJ7 XGbbRyAfWtU5KZwKJF+3HwlP9hHMujgTinhToWhz8R7NRD+Brs5tN5c1FSKo fALmqQYJdeLU2WbMqUC2nf1d/v4gwbY8R4qTMRXex1x9dUfsCwGK2m5l7k+F AoltnUynrwTXJK6ZtH8pMGnQN3GHbYRwMuX1V6utFNj5m/8huH2EMJZq2HVm MwXcKtmYzoeNEtQyUuu6VlIgPUX/WP6+cYJQDmUK7UwKMOhpIFnuScJkbmHk 0EQKMFfOaW4lTBLuPbjoXzqaAv4Bc6NvdicJVEW+dlcHU6CVe+W/Z4tThJmy Zdmwjynw/J/+m6XlGcL9J3Fntd+nAE8UKVvg7VmC9jMBwWPNKdCJGErGKb4R GiusmOFtCvBu/jSP/+87Ibfm8/zW8xQQUlAj/HsyR9Cvc5/48DQFDFZMqEMN 5wkH3zB8vleWArahhxPHqBcI/qDcKFGUAp9JtG9W314kGLXW33W7mwLbP1MV TTOJBIY2k4RL6SlwfiwgjEJqhdD24XcoQ0oKDHW+bXMrWSFIdIo5P4tNgdF/ rw+vxa8SmPtLFOYDUkBSwp/9Rtg6oX1A/kKtbwqI5l6u1Ni/QQgdnBCN9k6B Q4NusYJ3NgirQ+wc/LdSgFPytopU9U/Cp8nEVUvrFDDO3wmOO/2bEDEt/P20 ZQoUPdo2+DT0myAz2zaya4bf97XwGH/sH8LjH6RtOQYpsMb8z7b+9xbBaj7v raNuCjxLF0sxqNkmsC/KvJTWSoH75Vu81QF/CdFEr9yvyinAJM2WHc++Q0Cr TOmPrqZA6YCZlf3aDuHX2vMYb4UUqOEy8v3cvUuw+TXvwUJIAenjkvv4ekiQ 3D9zFa0zKdBk6xJ6qIsUMWjPkwyfSgHKXZ5gO2syNF7iWWUtlAJXDZrY3++Q IX/N+GO3T6RANr9ynI08BVIuZh3cx5MCZrdbxqmXKdCRrYL4OE483pfUm0G5 lKiqsHYzlyUF1sXsbn5gpEbhvxWeChzC9erudGUcoEY6at1WL+hSILOs/T1b Hg1a+fWts4UqBWj4GMkdFWmRkDJz0eKfZDidP/d6eZMO/c7NM/L6lQwiwlSB 87/p0ft1IXqS9WR4lUD0CwphQNY5l3yZFpOB3E+jcTmTEYmtdYjm/EiGebdA j5enDqF9Vw1n+WeTYfGs9P7m1kMod8VZ88JYMnxcuqSbR8OMHC9vUTQPJYN7 xcD+4ZfMSDor4rXaYDKodOeNKFizoC/y2fyW3ckgS/X57oMvh9Ghux/+RjUl Q0Y/vSI1KzuaWNB9wQh4fG6PXpzdYkflFyfs7r9OhvXqX7SDsxxIdf5X77PK ZGj34721MHgUsaPQaKmKZKAkee53ZJwLzaUdJDQ9TYYUQ5Hh8yvcKFKWt3Sg JBm0K7aO77AdQ7qp5ebXCpNBicxjASqOoRPfLzDP5SWDt6RaganmcdSQrBX0 914yVNCzz/E9OIG2pgP1TsQlw4SJ0oXsFH7UJrWf9mlUMliw2ne/tziJ7ibc aZAIT4YclaVaHikBJC75RFg5IBnSQ7ivfCQRQqTxkpN9PsngsbM8MLomhHom mjLMvJLBJTB1f/GyMHKO/brvlksyZJ3gObCfQgTJjFtXbzkkw5HGPkIajyii FV9xDLdPBpNI5zd9J06jR6OUX+5aJoM4iTDZZbMzaPq0+LN6nWRovtPwu/KY OKoq0YkJ00yGP0wtivpfxFEsp7u1oloyMHJq8vJknEOnqV+w915JBiNptXpn AUlEHtjzM0M+GSzTi9tz/kmiwfWVbpOLycAjcMlBeVgKBY6LRs2eT4Z9Yy78 DyouIG09DasyiWQQUDGnY30sjfjanWVdzibD+9jrBQ+fyaCOqqfrv/9LhqYX ZRELAwTEnihscYAnGcg+HNK68/USWiZTke7hTIZKzgyKNxFyqNHn5uGMI8mQ rSqbfeS8PLK3Ke3gZkqGvov5PwaqFJDMcNvDGfpkkJbvObccchnRa/0ILT2Q DIIEpyMVeldQlczJ82cpk+E6a1fpJJsiin1xhfk3aTIE+xDpz9IooTrNjjGf 3SQYYpf7b5NMGVEJKKskrCVB19L6gVl2VVTw+TJv5Zck4HzO1SfkoomUmsKH ZHuTgObCB1PqI1po5em75PftSSASsmae/lELESIu/RuqTwLyKDYdlSs6aNY1 +KV1TRJUa247qjPqonhTuLFckQTzg3f3V8zqoq9nZT/vK04Cvl/vC+Kf6KNg bv/4uNwkMNa8vsb0wADx076WY7mXhP1V05otzxB5TEmVC8QlwcX0HF7GJmPE 8cnb5kV4EiR887Yx+m6CmmqrOGQCk0BIhHL9PbsZYkgRj9a4lQRW+TNuEuXX ULW/O+HrTcyfRsTWoi2Quf2LDSvrJPjP+7kwrbwleoJOW3oZJMGt3odygX1W SEfYhZVEKwmmfqrQzJddR1uHn3XGKOPxKfy7JJNgjRSXhS/kyCbBJTkjP05P W0T8enOFXzIJTh/t46bxt0MZLaUlz0/j+rwNo76fbI9msk8yNZ9IArJA06jV 2ZsoLtr2g9rRJBBVUMv0FXBEYh7FQYOHk+ClgDCZuL8TClI5sThPkwSOX/ff qD3linRHCcfnSZMg9bHxmxaKW0jIxdhwbjsROppDEsvnb6FdEq/EHxuJ8FuU T1h/1A31p6Y0f19KhA1uRFE25o7KeJ9uffuWCEUPdc8+I3qgoKq209/GE8HU wJXOl9ELCQ3tZs/0JIL7YIe1RPxttOvA0Tf9MRHGR4oH27/7oP5/EjTT7xIh WWbe0dvID5UlaaOpN4lwX9vZon/KHwUdc/acfJUIMmLLK3kRgUj3ZczjiWeJ kHaW/OrYsWAkdLl4cvxhIlxvcirLog9B/fYjamOZ+PdJbN2LOcJQ2dZm2Ghq Ikghh+PeMuEoKJ6pbiQuETjoP3mR3opAulyiK8PhiXDytI5Yf10kEnquzD8c kAiHj0sVZHNEo91LtqZDXokAgmznzt6JQf19IalfXRIhlbjjnSUYh4I2a3YG LRNhOeQB2ZfHiUg3pl980DgRCj/OtxprJCMhjpWbn3USQbf+4V+CSQrafUKb P6CaCO3Hp1P+80tF/YSTg/2XE0HVV69/7HkaKuuWO9hPSIShna43MjvpKMjK XL5PMhEGDSsazGwykFDknfIewUSIKP1pZBybiUjYKma7jycCvyG7UJzafTRQ 2sHRzZEIDo0VRMlzOahM+odWF3Mi2ErfHvygkIeCO8miPx1MhOajrQpkDQ+Q 3jXu+k7KRLwf0vRN+JmPhFYvbHTsJoBoSfwrncuFaIDZzaJ9NQFKTnVRcxNK UFlJQsbH+QTYWqJx4V96iIKlSjs+TCeAompvXnBTKdL72Ez6YSQBIvkOOx1u eoyETCek2gYSQNZ5uuDSylNEsrzt/P5TAlArqAovCTxHA0Gsxa3vE4BAbtJz 3KsClTGeHW5pSIBRfrb1pqkXKLhQnbGlFj9fV6jA71aJ9M7dvNr8IgE8FjyL KQWqkND7iIB3jxOgL8XIN4a6BpEY5b9sKkqAr6Ufs5XZ6tDA/Ju5xpwEOBtZ VmZn+gaV+X/hbsxIgP1nzlvGDdWjYLoNvYakBPgg/FHWv6MB6T2gj4foBNAz 2nqipNGEhMSEm+pDEiBao7nc4887RNJ85fdb3wRQ1Vi9yN7Vggb0rETeuicA 6cvxuCf971HZ9wDrN44J0Nmqn75E9xEF+2RmvbZJABPa4h/ToR1Ij/ZVd515 AijQXBd8f64LCeV0U9YZJMCnb5NDrod7EInookytZgJorMmeelHViwYaqNxr lBKAR0sTMQf2owYLMZMvcglw+eurg8jmM3pCYib/WzoBXMd0MnM9v6DQiy+Y pEQSoH8sweEH0yhynhjZNjiZAC5PK94s5o0jo2CqGW+eBIirHtQ3FphEpxtM K6sPJcCrWraaYvIZxGkRlT1ImwClTRoCE0GziIrkRfgmeQJE0DErsP79htby RhxZd+JBbsO6Q9TtBxpDVHqSm/Ggzx5cpj00hz6On5E1WIkHdd7pDwb/LaBX QaZ83nPx0OpSO61isYgecEcdvDsVD2cEVe6RuiyheKj4WTUcD4W6/DL52svo 9rWR0c/98UB4c7DlIBURXd+lbP3VGQ8Zz1VEz8QSkXremWeH38fDM1KzHvIR IrqATDMkGuJBJ1l1wmGHiPjGIwP1a+PBumbJfHqDiBiCKmy9XsTD0sqBS2zN RPSXa0Q943E83J1nmfO4RUTf6yklq4ri4YIXxUIlKRH1mp/h/pwTD1lPKd1j ApZR/Y4J1a+MeGiqvXRf5/sSSidUDJ6LiYfvm8M2NVmLSK7e5PYrp3jQGpYb XJmaQyLmkRYDtvHg2cLdqSMzh47sPFf8eS0eOhdfVjjf/4FWZCmPnNOOBxcy 93PZTt/R8OjpfXoq8XDaJPRi0OQ31BpgMuehEA/8DErtfabfUM7b57WVEvGQ SCqPOm/Momiz4fx+0XjYFKTNv7A9gzz+UcRuCMTDhxt8A6/SZtC1nNNuzMfj QVGT+zzF2RmkLGtiLM4RD5lL12HuyzSSGI2Q02XG8/ORxuBYxDQ6FvBcyONg PJQm5TfaS06j328otl/uxoGjdz8j59MpNGN6errvdxwc9aCVoHSdQl1/jdvX V+PggQz37D/JKVSXHfGSaSEOzFj4b7SRT6ESmef3z87EwfpRdzKRz5ModWQo TGc0Dqr7aCi3Hk+iAH8KR/fPcRC3r+XrVsQksuc8rZvWFQe05Z2/9llPIt03 xjIv2+LAWJWrd/ryJLpoGsHb1xgHV2pW3nkLTyLhv+UH1uvi4N3l8bm7zJPo cPbQxqHKOAh8101+bN8kIpWhGBV7GgdJAR16aysTaGlYtEW7JA5ehlT5LE1P oC9+xk/d8uKAYeyHwq+vE6iZI+JO6r04YPHWylvrnUDlr8sDXqTEASffecuP nyZQUQ5phWJcHCS335W/0TmBsoL0ZsbC42D+UIqcBb6eZPmI1TMwDvpzIury eiZQuPy2Mu3tOFBJ/8ZzZHAC+fCpB+bfioP9D4yI9WMTyJkqv0LSIQ40iZNJ 4T8mkPXc+kyndRzOK6BkvjGBjNqvsFmbxwHP2KLIJdJJpP40U2XLIA4K2of2 nzg0iRSSFgOTteJg1eeN5taJSXT+FnrBrxIH1MkLtPWSk0hEJ3X2jUIc+HkJ d9moTaIT52bZdAhxoEy2UjyH68vGKqU6J4nnY32YXC5wEpENj75gEY4D8z9v ZnWqJvH8n/72mDcO0N/TY7v9k2g5N+yIHFccLDWynLb5OYm+WAkGOzPGQVQr 23M56SnUqeD/kpw2Ds4mvHN5ZjGFmvi7vmWRx8FHn2cpdVFT6Om8h9r7zViQ KxF7kzU0hQo63gebrcaCev+LDkvKaXTvGXvl+nwscNGRS5SfnUahbg3sPGOx cIiqJ7EhdRoZbNH+uN0cCzUUVCGTljNIdcScg74+Frr/2dPuy5zB669Cvbg6 Fq5QZx693jOD/gs1eNVTFgsXJCNbmi7Pon37C0OFUmLh4TGrs+nS39DjIxeO jpjFwofrx1zI1X+gB9vxmm4GsUD6hVQ6LvUHyhgdD6PWioXJe5I+ioM/UHB+ xLy4Qiwoi4frUVrOIT3BnuoEoVi45fFI9KPbPFKm5V04wRsLuZQvJS5XzaOL S15cdUdjgW7igeLJP/NIqIIz4htDLDhuF7lV+C+gXSl7bbQZA87p7s393ovo eONdCpWVGDhx/+htn5pFdEXpfY3+XAy8vhTw23ZzESUa8XM7D8dAEUWDcA7W yxeTer0+/TEwNLcaUPpoCQ3ciIiI6IwBCckyicjxJcTpO7OQDTEgsCZHpXxl GV0kZc57VIN/70xLOqnXMrKOldeurIiBh5/oakUKl1H0IXeKhrIYSPjIUvim cxk9ziqoaS+MAS1p/4nsn8vo0/Feh8HsGHCpTndtYieitbJ93NN3YqDg/cve 47JEdPjsmd7lxBi4m8nDUGWK9fi1RcRWVAy0K26Alw8RmcsnS1GGxEBXNB2l VRoRhbbDAqNvDBT/iUrwLiOiEh1i7lH3GPA+qhhQW09EH4a5tAUdY6AkK9P+ v24iWryuTnHOJgaWfn6QHhzDer4YUHPRPAb++yJ+4t08EYl7PHVQNYiBqbA2 1+11IjL8O8JlqBkDH77y+CdsEZF/+IHe60oxMLvWEBKN/eHBAZkIF7kYiFBt Dvy3S0TN6Q5SftIx0EFyjXYXX//OeX8hUhzXQ/bB2fxtItpf/DE39VQMgNRr jT8/iUjk1JZWLn8MuB+NGz66TETarwQpyrhjQI3tqjr/DBF5yRrVvGKLgcuP 8taEvhBRVku0QyNjDGgPtIHCRyKqV6vh6twfA/e4Z8QS6ohoauB7zxeyGPB7 0iPEVUpEFOasETN/o4GaoryZMYOIBL5dkVr5GQ1pNGHSoSFEpOrstbC9HA0m uV/fxzgQUXrggBbTZDSgfkONVmkiqqGkoOAeigY6m7IakeNENJIoXiPUFw2S O5dn07GfnshL45JriYaupMN5b7qW0QvQWnAtjYbfMZbklIbL6PPVkFz/gmj4 clBMelFqGW11PdeKvh8Nv/KrhcKOLKNLE/Q1eQnRsMIgpkk3tIS6ST6Ff7oV DaxvxOV9jJfQ0iVlrv8uRMOE8KbwH+tFxH6ggPPZ2WhgFn1csaG0iBQ//2E/ fSoanLbspi1EF1HRzVJWcZ5o4H6aJ1OwvYCM06gZZSij4XYun6t21gL2Owv6 +t0oCNLVI1iE4TxxsubgxT9RID50MIDUaQExvLHbr7AYBV4V9o/p5RZQ60wr mWpvFBSFKm7Gr8+jjWdcpJ/a8f21DhXBk/PomI8XiWZLFFAON42ydc8j/4P8 /3RqoqDiF7n2hfJ5VDYYsD1QEQWP3z6macmbR4P5A38MHkfBoxe6bJvJ80hM IuKXSW4U6IftGGl7ziMLktGN0btR8L6N2ORnP48SPoqvX0uJAoWeG+uqpvOo Lj1+dTI2Cm6vK1W1aM6jH+YzxOvhUbDJwls3e3keHRaUWZ4NiIKo9MbUJ9Lz SGE9bdHOOwo41XrrjojNo7wo+TmHm1EweuqDywzPPOrQuv996XoU8JBShF48 Mo+2ONZnXcyioHB6/yo6NI/7RXlmVT8KNPpUuiZp55H+84Ipd80oCN5m5eKj nEfhvlsTP5WiwKFF+RP1vnlUoaA97i0fBVn/5TTG/Z1DY3Rlo39koiDcU6z9 ye85dODrvhE/iSjgHgp/fvPnHLpQaDT0TxS/X51SqHltDtk5VXwJEowCv6DG 6eqVOZQuSTO470QUVFZyBSoQ51DTPsuBMM4oaCBKJdovz6GV9po+isNR8C9Y L/c45qMZDL1R9FHA7J4mcguzsoV9Nw0Nnp+N7Upt/PxtoYZPcaRREMN+ILcF v79kg7Xz4N9I8FE8oNaGf7+v3qU96Wck5Fzf4TDC4yOJef+BkRgJNPs0TL3w +EV0uNvSfkSCoEmuPhf+PtOj3q0sU5FwsEpQRYNkHsV8/9R8dzgSZIpab1FR zKOqCv53RwYiYaH02JbC/nk04xfYeP9TJMQ3ldFSMsyjQ1c+w9G2SDA497FF 8fA8Qgwi9XmNkdDfXIVoj86jrKLRusLKSHgaL/yI6r951OZ8rpbvWSR8iNif Iys+j35JJVQ/fBgJax/8zBdk5pFWp0zl46xIsFwc2SrWmEfpxYXW6umR4LHy YsfXaB59CdjPspoQCQfmWOheX8f9JvLFUyIkEkikqMk8fOaRc5K7ZKNdJHD+ aPZNKJ1HL+yGvl+3jATvm66Xg7Af/USX7lGaRAKT22jVx3e431fo/qioRwLk aynYjM+jOK2yus/ikVA0nHbRln0BfRJkdPARiQRbImXFlOACOkR6m4NTIBL+ rlZYFZ9fQFkvLvtbckTCiY+OhHWjBfSIaVJ2cR+u738GrHY5C6hlgLVxX1cE VH6SMFE6tYionwXeKmqLgHOCgW2zaBGpRs4eu9oUAQatyoeytRdRv8TL0PhX EZDAbKqvfHsRTd1VV2DNjgD1V5+zjJoX0a5RxPv/bkTAxDvpN9mmS0hObNG7 yyoChI8Z+ThhP4zcryPgZhoBDy+Y958MXUJ0r3liqjUiIEqnOVHtIfZDzjfK chIRwK2elEm7soTOj611GpBFgOD0U7Gp28voianEjsvfcKAc0ErQi11GXMM+ ItE/w6GA7oSd3/1lRPqFJKnmezg0ncxj7nuzjD720Gke6QiHlvdHuOy2l5GM pnbwmZZwoL9il3d8PxE9+3TnuVJ9OMwIJZzxZyOi1HZORt/n4UBDH2axT5yI jFuEeofSwwGSZ8KP2RJRh7wz6XpCOMS7PDDNwvsRQlOFGG1UOCgbj3AX+RPR cZBKk/YJB40T1y7YpmC9l/V/p+MWDp8tnDs57xMR5RtYd3AIh4SD+e8sioho oeaKbrZZOLSXVdUnvsL+KxkbXqkfDtOVG9S33xJR96vOyg6NcJjYnri4hPdD cuKMszOK4VB1h9xkuZ2IKl/osvy7FA66v6Qc/XqJiP/Mvcss0uGQFcpdmo79 7F75sOcp8XAQPLFkcwH78X4R7pLLp8JBUyadxWka++0Tq89m/OHA3pOmdOoH ES0LlVB6cYeDGNf+Cr9FIrIonZNIZMP1zTdiM1rB+62Tp+xKGMPBqeaifSv2 b4US17v1+8OhUcWkuPkXEVXxVr7/TBYOr7ypibp/sB8Wbm4u/w2Dt8uLgbex P2cdkxag+hUG/yxXH57+R0QHHgQachPDoIvVfCAQ+3kgV1O05I8wIG08EmuN /X4lm6JWYzIMBOlir01jtuJQmrMbCoPP3Y3ke3mgPzP+SHBfGLzcsZR9ifkK W7fSvY4w8JX7OkGFuSaDyfd5SxjscAp//Yt/T4jFoKytPgxE3u87nv6XiHLS soYmqsNgmeH++y6cPxgOje3/8zwMLo98na34jfNP8jFpxrIwQI6iD2Xw923Q 2TgIFobBjICbvBv+ftuER/cvZYeBoefBXV1cny+0i+1Gd8Jg/89hwe+4fsqx on9vJYbBtRenuITncB6JqjItCA4Db6aYrZ4JnG8otuLrfMLg0KkrTefx/vhQ uOzbXrcwkPg9wWA2SES/gpuPktmEgWP2y8sTHTiP+PaOXVcKg9bdC0Ru3C8X pAnGa3Jh8CM2tJO9HNd/u3QgWCYMio/rpy08wv3tH9KRIxoGSj6aHKzZRJQb eLpukCUM+i4GZnQFE1FAaOIdlalQKH463h15mYh+y20xDA2Hgl6rL3kvzose ZLbx9gOhoMBwIv2QBBE5hsuGRbSFwhDngSlffiIyjVx0hWehEL6+qsmG84pM rLLqWb9QyBZnO7zUtoxqlKveN3qEwvCBqhXtxmUkTntcXtM5FGTei6y21i6j /+L/nHeyDAUyBWWHsbJlxJn46OTDq6Eg9mkkfjFhGd1TZy48dykUHkzncc5G LiNm+mCu5guhIPrj79+NoGV0INmAZfJUKHi8JeSZuy2j7RRKMg7mUNie7T3i jvORl7ZbYOnBUGi8ncpxUXsZrR0a+yNJFQq07b63hFWX0XzaqxXdrRCYmG3Z uXZxGQ3dsR5LnAiBMqVhfh2hZaSv3210dCgErLkp4/j4llHvYZmBx30hINLv I8fBg/XlLlNHW2sIPNf0ve92eBnVZTbVkj4NgdukzX9GyHF+J6F9RVkSAsWk SVYhJMuI3k7n+f68EPAqrTig83cJWYvPlBxKwfenUYYGbWA9vP9fweHYEBja 7Z8dwvpXs88zhz0sBMYpQ99YLy2hg10U6cc9Q4BDkfwu+Xd8/Zx6Er9zCNyQ hBX2mSVklZ0RK2QXAp2hvjcsJpfQAbLxCBGLEOC2CmcbGFtCVTdOhogZhcBp 2uyDPiNLyKLbxV9COwTe7vzTVMX5kFayxvuCSghI6j6cVv+C788hcScohIDQ hjEEf8b3kys5y8mGAIPXxOfJ/iW03yHlxhWJEDBMYDns1reEXvV8tVYWDYHB n9xWZ3rx/VLHLdQFQmD+mGsmdw++P++mifaxEPC5eyBdpnsJVVK81NdnDwHt pHsnoruW0DXHbS1jphDQHfdhIsW8v09ezfxACPzrXRco+4TvPx+vaEURAr/o dE8EYzZ/0C9vuxMMRUpkb8Iw01AdRTc3gyEs6WVJ5d79TjYXnFeCQfyQbcoh /D7z/qfn3OaCwbiznDcHM7X0r9NeU8Fg9qGMTBeP50U+4T/f4WA4yHK+QwKP 15Q66mRgfzCMm/4+fBl/D5VL1/HQzmCo8kjyDsTf+2KAlSuyNRhcjPP9p3A9 TGUsjsRCMPzqp3ruiutFWfiIObEmGEqEP2QI4Ho+p1mlT60Ihl3e6xU0uN7G rudpM8qCQbSnxo8JzwfFYAhlVmEwxDooO13G82VcdOhf/p1gOKNdlsg9vYTI aU1+FycGQ/gMutc6u4TKbxWul0YFw+bSjH/aD3wdic9X+ARDDDW6lr28hJ4V +8++csPPPw1kHVxdQoYHWiZqHYKh9Nc+nnM/l9DTr3qDjWbBQF1Q52KI+9Hw Ym5vi34waNQb63HifiV9+K3zgwb+nnTrNhLcz/oe3s09l4LhwZlOV4EDy4iE PrNiki8YyMy7xkaPLqMyz8kns1zBkDcoYJxyfBnpjQg+mmMNhpPnXqpfO4mv l9blrtIEgwHFgxtXzyyjh9E1rGQjQZCxcvLaGbz/FXCzc1P9FAQV9OI00SrL 6JHJ4c47DUFwzDCqd1UTPy/iESpQHARkYoHB2ybL6Fm/6JKacxCYy5Vf6Mbr v4rnYdM9kiC4dKn5bHPBMmquueMkwhcITKJvZrYoiOhygUKbN2sgmJRudx45 QEStcevHG2kC4Wd3/t0zh4iozVzri85yAOyuWnUpchFRO/lBeZ/qAEjq5Xbf h/WvVzOcrVkpAM48oJved52IdC6cdT8oEwDFDQJTxvbYj05MdeqLBIBB0xRn gRMRff6FwuYOBcD4w4RDf7yJ6Gv29hLdiD9kWh/xrYvD+SKyTNHwkz8UCQhX eyUT0ZCLUWF+gz8khqacPXoH7wflqg3Fi/1hX9A+mZO5RDTxw+2dkbM/ZFy+ CbxY7z303SqTLP3hWyvD3ekXRETTfKu4RdcfAu8qkCRUEZFYnmvUGWl8f8Ny Ti7OE+8PuN62E/GHRweDbCkbsX77utzIOeYPuRu9PwxwvojQc1ahofaHCKm5 G9V4/8v+zkkGbfvBRwP6Iy2d2E9OO53yXPYDJ5WGqdfde37nSD/Z7wemrAVq 1p+xvzbd6KvJ94OtrfC/Odjf6kVvNC+n+8FRtaKp1Slcrxz7V7zRfjAuvK0m Movzx227u8nO+PnPhMcW2B8ZvtlGt1r6wWFDvnz9BSIq1rH1+avrB+SkHLzn lojok4iNib20H6TcfP3vMfZbq2xr1VwRP6Arr3ZTWCOiTRpr2f5jfsB4z7qi BftzvPd1kf0seDwyI92iP4mIZ9aK+yK1H7wYMVsIxX7+StuKwWvbF5J5TnHB JvbrBst9T5Z94dyzzJgZ7P9jpyzXJid9gSFqTHMd5xn3+xbTrAO+QDXKn7WA 8wI1jUW/Wpsv1M3eTuzE+Sbb61pL2GtfOOyWa5SJ88WZGfOq2me+cPIXQUgD 549WLfOHxHxfYNmfcIaI2RjM7vHd8YVbTZ6FPjj/EP8zizGJ9oUJCf+qZczh Waa+KX6+0CJ1p1Ad5xk2alOH986+sF5xviQT8xNPE9N/lr4Q8FfybxfmS9PG amf1fEGK4+3sKubPmsaEG4q+oGqKincx36w3Es2T9gXDLdWgP5h3hI14BkR8 Ie5sed045rRMQ0ba477w0FTiwQvMAlSGpJdYfIFZsNzXDfMbD4N1L2pfmN7t yuDGrDmlP/Nk2wfoGU/J1+HxzmroD0wt+0DfokC3HGbft3qtbFM+4Dk0nlSL v5dOWK9afcAHBFO3BrgwF97TfRTe5gPenb2bbrheUpS6mXWvfSABnVetwvW0 nNT24y/wgS7qnWVaXO9f6tqOpnd8oLD1yyoXno/YN1pmqdE+oG53NPk4nq/K u5pox9kHdr2oWP7h+Vak0DwtbuUDP1Msavs3iGjUTePYTT18v4C9Ry7uD0p1 dbLP0j5wwWD7Jc0qzj9UVBu/TvnA8Rm6/gQiEc01wgwrjw/wFZ1xIVvG+f/c mVYjch9QrV5naZnH+4WjzDGjHbch+c+O3HOcp8MHO3x26m/Dz4xR7U+TROSZ EnGTu+I2+KYkzk2OE5EhxaaK5Z3boBQvWLUwTERcS1/pZs1ug9NBQ4Z7fbj/ H6buUmjeBslHh7Nce4hon6XKCr/cbRBMVq+T6yKimf43Pfb8+Pp/Q28H8Pos e5OXvrjsDWd8sgua8XqWiLdh3wjyhsw/rRJnsD4IXOGiZXHzhvNnXp8afUJE R0gGt89ZewPpWTP52DIi+uuuOOqt6A2/A/gC54qJqMlE+ME2A35+ePH1e5wX K1lmkjnJvGHwUohsdBZej13ZIbI/vWCo/Aer2j0iipanux701QtSYhq1ZtOI SF14lY+swAu+x59rNcL6dnG29DBvuhf4Mv1HfTUGr4c8K6rLkV6QdrfYWjqK iJiZ+n9E3vSCuDHhhxfCsP5tVT3ef9YLflGQuN/3w/WudMkW5vMCV97P1R98 iOits0CCKqsXhJVT6+67jfPzVKZz4rYnfHhEGZ3gQUR2H/3PHGr2BKPOg+w8 zjivUkfWcFd7QqAkQ3mNIxG5XUlCp8o8oZB8ZszYAetPU76aYrInVH8LyH2D 9TuE5HG/XpgnjFZO3vK3I6JIQqXJdS9PuPf+it0VvP9Lrmu9EWjqCRUm/536 g/X/zu+ulTgNT2CbYxWfssL7G4mv3plynsA0MvVhwBLX68VCRKWAJ5BZHPs3 cg3P18rGgSYOT2jI2de8Yk5Ez0V20rroPOFJS5UjPea6MoaC+Q0PkGj8XuRk SkTw44jg7+8eMLNfVOupCRE18594TjHsAXb32tl+GxPRR+v/JJk+ecBTGglK dcxdBefqeRo94E7grePlRtiPJgiXRSo9IIltwoMD8xCXYof0Qw9gM3MlSzMk onFTLR2lLA+YU0/rZcE8k2U8pJ/gATVe4rOFBrj/v1y3tA72gKqcDzKymJcP O/245e4BAePXv07q4/2QrpdLkK0H6N+MqU3B/Cc16Fe8kQdkVJkPqWLe6Y4O yFL1AFreckkmzOT0qeSPkAf8Ymhun9HDfqV2P+6VmAcUP7qT1IiZLq7o0Ds+ D0hXbvMtxcz04WlmN5sHZIulhWVjZqOq5hmj9YCXad9yszBzXW54uLDjDhxm 5g2FmE+EfRD5s+oOiuoaQ9WYBRp7X1HOugM19bvRz5hFdodlmL+4wz2z8DoS PJ6zsrPvjrW7Qwcpz7VzmKX8lpVF692hD+ZqPDDL1m72yFS4w30d0sp6zHKb JEbKRe5wbc5cmgnXQ/Hc/gmDu+7QefujlBtmNXcmO5tYd6Dqm00fxqxdwbns FuAOa77nJDVwfQ2JfJ7Bru5wXo6PshOzlYNU2H19d+jpuVz/Dc+PXeml/aVK 7kA2+Ns5FM+n43fllCoZd0jptB4+ieff+7pZXs9xd3iG96FJuD/88235x1nc oc4nQl3LDO9Xx12eLlK7g/RikiMn7qd4k9DXVEQ3GI4x/9SJ+y8lM06OZcoN 0MDNjy8tiChjMP3D8QE3OFe3360A9+sDnYeDsq/d4H6+o3Am7u9XKh3r7lFu 4Hn16Mp3vB7YPif6Ovq4gUqu2q+TN7C+W2jts3Fwg94Nj1LXm0RE8PxMp6/h BjxCMZIcOP+05k4ISrG6wUk/jyef3HBeWN249rfkFjzjeZ/uG4T3r/7V3zbu 3QKL/9p7BEOwf1L6Oi3F3gKixumN0VAisuDY9R1zvgWPCsK/60TiflSgyWiQ uAUeayzuLglEtHX3aEd4qyvosA6e+w/rlenxCe2AGlfYZ+ZtQ4vzUv2Tgq+e Za6g8a7MeSEP16fx5HfbRFe4tzlM/7SQiGgXzpAq6buC392AF6KP8fz7x7uy d7jAxfL6S/9qsT4mMwbSPncB29owhc7XRNRQnBH3N80FHq1ctcnCeUqp60HJ mIkLjJ2YFhTG+mt8/NVIwYIzzLyZoj/WhuenbVRRmNYZEoeat84OENE9ljyu PKITzIcwBVTjvPTKymLjUL8TkEnl25/7gtfX36m8rWwniDnbt8yN/cHizI9f H0Sc4EJ8N+cTnKf8A0s7ZJmc4JHvmau72F8y228WVGw6Qv+/oTEV7D+9Nktq mQ2O4DFpt9yN85VC1lqRvbYjfHnnvh2F/cri+0vfEQlHYOeS/VmI81WAuKem JocjsHSZPKlZJKKqT5vbkjMOoJE8wtiB/a6Xo7bncZsD1Kb9K/iI/ZBo7/uQ +6kDPJgnVjXi/CVA9k+byssB2ss1L2Ti/KWgWS/gZ+wAYbGWGT7YXy1zgnaW CQ7ANxWoro39N0uStOwzlQOsDRTVLmJ/rgp/F6S8eBOIfkeuP8N5rK8nXK++ +yb4rDro2eM8dsCRal9J5k04a/eDrgX7u0Bt2+cjgTfhTNXhz3bY/y9Txj5J sLoJVUby30hxPgh8cMDQU/gmtAX7Lx/bO29a6jw1R38TvO2IxGLM1ReSyMw2 bsCVHh614zhvrPQzliu8vQF5jj/Ok++dRx3vC6/JvwGNCTPDNzALuqQb/xd5 A+raVHbeY77yRu/0g5s3YPsa3VMunG+saFgpmTVuwKlZ2p9Oe+dX+l+Go87e AINQ1ZlXmO8XZlZss94A45vNMb8w16wYR7n8tYfHDe4/RffOr2Q5zaYn7MHb x0TKau+8K3ZUzKDFHs5fMbNOwHzwSy51e6k9bOo4xFdgFuKzGCMk2oOurlbz p73zLrdjlS/c7OFIdwPP7N75GEzF8BvYQ0+aTfUG5qADRdeypO3huWRN7t55 WbaRzTk6HntwqyFb3suDNSX8tKHk9kA3fOvt9t541r9P/PxhB6yTJPx7+XH1 YmnVjU47aMqyuTSBmS7xZvxohR18unNC6MPeeIaFrbQy7OAOuG8/3huPwJJk i68dCAuq9URjvu757OD5a3aQ8Vet7Rrm4CaX6SfydnBl+tO/03vjoT9TyyNg B94UkPQX12fCOu21E50dTJgWPm7FzFv3823dhi0EExmY4jHb0xs2UA3bwvhC 87gq5ifWdU26jbbgrDkmTIN5pZazJf+hLcytTzM24vkSpw96v5xgC6d53j3x wPy6Vr4j2tgW6sWTnLvw/O/QlXwauGgLikyMnV6Y5aype46ftAXumiQNdswf 6ToH3qzbAEPOgbP6uH+GruuPr8TbQK0/bVER7j+u2ppJWXcbMHpqpnkasxUd x0yskQ1oss/Q1uJ+na8Z/8HLbwNrPs8Fm3A/bx28sWYI1uCxrmVQhfv/SI0f RePqdZilL7G+hPOn6cExKrov18FNQv3aE7y+Hlhd3G9Sfx3INdp0Du+tt4MU 9D9jr4P3gcTC73h9SlklsgnyXgcbLoWTYXj9Gh7IF07Rt4IQLSWr6u+4vpZk ImMyVqD6TbWbG/NElc1p4RNWIHn9PUXMN1xPS6FzLURL0JPbOW2O9cK76iXh T7QlhDVYGB7GepJh0apl+doCPngwc/WNEVG6+n2d8DwLUF5V+62IOVXGVe9h mAWkmMT4NI4SUQIbu9GSigVUcBD660ZwPqckGjOctoABp5pRaczRG+9MzzJb QNTJg8uA9Y06f7hhreYaPBvS9esZwvkgIKJZKuQarJB5Hr+GeddQtC1Q6RpE TLbxrnzF+Z8hrGv/kDk4awtFcWKeCRYaO75tBmX2AU8eDOLvM+2ftH9nBp1S MpwqmIelAmefxZnBv/6LDn+w3vau9Cxe4DSDbo4zQ5aYP3X4rQTPmAKFYgkj J+YPj/g2Wp+YwqNRV4MhrNcNFj7b2rKmUJwoJ34d8xuZE7v3KEyBTd9s5BTm arZO0vFOE2Cq+V35t5+IXmx4UfJlmMC+9xnNXZifdfPsdzA3gXetKwwPMZc9 +Xiwgt8EbtWu5YZiLon2YNxcNoYPUU/drDAXWHOxyFYbg8awZ9IVzDkX29jC gowha/b1pgjme5xunB+uGkPyP+mnHJjTf3Pw0DMYw7/Kr88PYE7ubzmh98UI 6jifkZJijn/ucvL+AyO4v0lfsI33F9HxR4Qn7Y3gpHJ4wh/MYfbvRE6eMQJl zvamveuBCk5iTn8MgaRzgrD3vC8Pq8TLRkNYTSLb2Xu/19+G839iDMFnPmt7 7/dvfbkpi7QNgZvPVkwUs2Ml86UIdkNgLzTI3hu/fXK9QvuUAahfyRXb+z5r R3tFxscGIJT1eikE8zXFQ6oG7gbA+MappRizMe8bjRxpA0gxe/O8E7M+ia3O NJkBWBiRlfzBrD1CbyDYoQ/Hz49lCeL6q9XUGruk60OAGiHcDLNi+nXzV6b6 QFp8Q/8OZgXXg1bbvPrgufmHvAfzRdVqm0tLetC2ORjKgOdbWsDyRtQrPcjt NG3SwSw2UenKdEUPOvVFVGcxi7wx9zCi04P68T/eZ3E/Cd6jvp33WRdknFUE IjDzaJoGCdvpAmX4bK8Y9m+6BrJE+WgdsLce1X+F+9PwCXFeWlcHKu67PzuM +7ng3vBVcR4dOJKxdMcXs+Stl/v4arSBYZK2W2nP749f96T8oQUOqwI7ZHg9 vQxvMv1wVRPWxl+Wfsb+v+P6rLaRSRMe/2bQMpzc24+In/IADfBVvaMzjLnW YeaBHlEddn+mMs9OYT/7JB/NpqEG3xg/nqTA67sildQgl04ZjHmKkfUc1muH IYakEiWYZruht4p5SP7FxyCCEjwXCrcOxHmB/KclwdJZEZqbyVju4bygb9DI x/vpCsydqFF/v4TzEUfwRmmCPDwQiibuw/6fvGHwLItPHj7fen05HDNfp6h9 3Fs5uFXlf4EC5wH1wPFhx6VLoHiUspwU54H8CcI7UbWL8Nm1LXsO66GD26mt ix8RHHs7XG+O80D6iVGn41sE0GKbmunB/D1CRm/WSBaGpfb9rMB6Gq+8fcLh yAUYn/GQM8D6610f/9VK7Twce2daUbOnx2JcScYhUvBVgruaFecDKfZLW0pz EuB0K0b9E+YTib3ll45KQPtUfzMf1nc6Umub81rn4LqA7H1fzDNzkd0CtWch 2nPrHCf2gy4ztkieJTHYV80xZY+5rqdUmu2YGFRdXnv7AnNybUcJVcxpyB75 90UW+80v4zc1Oz6icMLcliwIc6fc+InlyVNwz2367FvMvof4tjoqhGBlyDL0 NPYvza2rNm+OCMK0PG+SDWb+qZvdj0NOAst8eNBdzH8/JEjfn+MDGSoK1T1/ 7K14XhKrxQvPFZ8urWJ+lNnH6Ft7HJDvTzN27K+BIb/8bxw7BtODvRkI86Ne se6KQ9xwUPdZqiVmvYLbJclTHMC94KsajHmfW72/yws2eBl0H+5jfnqJXEc9 lAWKX+5+3/v/mhGjsuAp7UPwQI2kqQ0zbRP3LqsCHfwMiFQewmxt+fjxwDQV eBosBv7YOy8ikTRMC9sHVUHsZut750kXI2gKrvyqF7rpOL2F+fk/qZYLB6br 2+XfMezlkTdMVscv9H0glDqGz+xxItXNz4M/iYSrZdHme/nlcMvRVNfXfwln DESDNjGflQ/L3npLjoxNr19dxjxUuEmU4aJFXF/8aib3zsNIq/IRMKDkU0b9 PZjviLm2WxCZUIqadU495jkroZ8h3Kxo0tT98CPMMmkzXIUa7Miy/odcIubk d7mKzUFHUUB8Nv8tzGs+/9WuGfCgZKWFFk3MnKk06mQrx1D/kad8p/byT9m3 KaboE4iD9ZwKJWbXpnfevDx8yHpETWYEz0/zWkD+ZU0BlPRrLGvv/53L+00k 9H8IIhUL7cMqmNlOSLXbBgujuT4jH2bMjjprG1HPRVAUnSxrLu6X9lffFVR5 TyMWrU/XzTFPXNJP0l05jS7rmL7mwLzf+CyvTbQYYvle9zIB9yP3t3xnJ92z KPFx5w05zOJuDLWePOIoifaa3gbub/PYJbXImnNo8zv7Xw3MFXUPvR/+kEIX rwjMfcfr53dwSOtuy3nE8YTdKggz4aoJi2HhBfRr5AsdM+aPfXQvqc1lEAsJ peY5nHemFj2Xb/QhVM9dkm+E12sMfYHY4WvyqELkoasM1oMna3TGTZ3yaKHm BUkFzjvdA34hzjIKiHwhhp8X8+Fsve7WI5fR3/cM9yhx3ikQoHH27r+CrBmo xuux3tRdci39oqSM9hns/82E9WqUd7Q7vEYZlScmMgb+ICISauXfp0+qoCem zrY/cN658unE1RhyVcS7oSpSj/NOn/HgzHlQQybZtQK3ZvD6lFU48O2UOtr5 w0M/gfMO+7GKs6nZ6miD/BqV5vTefik2dN5HA3FE3ss4i/X013nuZLUsTTSp W0RxAOtx9OOBwsIeTcRNnaYVOY7z3NH46j/UWujBoWv+pJhlSP6MFXtrIYP7 pt0kOC+Ftvae2tHVRhko4wAbzkPMUjGXdOO10dVV2sVCrP/FpUiv7J02yiwW txHD3Bb/xF9fTAd91BjxNcB+QacT2f6MXhcFCCt5NWO/0arcitCW10V6xz5G OmFOZ3G5+MtLF929+M7mCOYjXwxeyY7poiLLtTYf7Fem5ztcJhn1UKLurr0I 5tysi0IRl/WQiJcC/Tfsd7xmgnkdT/SQna1lvjlmu/ocI9cJPfRtMqeYG3MZ 9yFmZmZ9dKi8Z2Ia++licOSn6qv66GQqlfljzKJTW9EmfvroXXbPSS/MbvIu 8rvP9PE+4LKiAubKoul/BVP6KF/7XxsL5k0Kw5orhw2QdDT9y3ns7xfsOtzm lQxQszIr/TvMAW0XTyUGGKBfb8/M5mJuEHz1/UyFAXqe+E0mEDNpnGDBwIwB Unp06agl5suLOaY+bIZoUKg//irmaLVDrEdVDdGaQVrKGcwfn0X2NAQZIu+p xdPcmA8ybMdZvzREk3RdLgyYNW+5XKH+boj+y4nXpsCc2jtN8oTdCBWqrI38 w/lo4Kzhaw11IzTVKntoCzPbnQ7P9RAjFCXM/nMvTxn/unj67isj5HwxL2rv /hyDV/MX5ozQ/B+ddnL8vokaweIxTmNUvybWSI/5OHvutVBNYzRdnH6DC7ON 3yF2/nBjNE52tfk05kcjkf0fqo1R89/g7r08NS+7nei0YIxa7KfjLTCfynNR YuQ2QW2PPDcDMLuSzJC90jZBlwweHszby6OWhvWGkSZIaVejY6+eP5s6bv+t NUGMdTWii3v5LuLVkvwxU2R8pLn3Kp6Pt98EH33XNUWUjutUfphJFHOt4qJN kfhbYkcF5oj9UYO9RFOUWd07L4j7oc1hO8XrhBlieR4s7oB5f6eLKruBGXon EEIsx5ycZNhoWW+GLomFpMvjfutb6fCjWDND7K5RN1MxH9a+JFHKZ46yPVZi ZjDfZxZ6vBJvjjYoPb1Scf+WZG6nB5lcQ9ThlPlMuP9/bLlonEi6hv478dnC D7Ow6QzN+6ZraDdRZmcWs2GSLaJisUDbY3wp7/D6GdPSqFT3t0B/X8SI5+I8 1Tp3OFX5ngV67/8rlQ+vx6chYy5XKi0QeEwWlWP2r3ASJixaIGPrFd92vH7Z GeMLTplaoloh81UuvP71u9uSD8hYIbIu3l12rC8E+2RnakMr9Hpg50ADZj4S Q1VyDyvkxFE9a4P1aEP0O9Xfx1ZoR+TZzZdYr1KTKIIWOK6jS9THurXwfu2T upzTx+3rqPL1PmU/rH9V32hUWlmtETnnWh0H1sucwB6BprPWqPKkzP06zI7P LGZqHazRAbGztOs4T+2nCzIpHbZGCVmd6spYb9eKr5wv3rRG45ppk18xf5Wl Y81nskGqEg+KbXFeeuSU03tPxQb9URc64Y31+krna6Xo1zaojeT8Ixech0Rs wk6GD9qgjSfPbs9gZvmnTBG8boN+S7nL6e3lof+GGryFbdHNkHtCQthPOprz c92v2qKFu9I7e37z0vSGv8t1W5RxvfbcEubQ+N+Sdvdtkaa+BMrB/nSTt4Hl erUt8n7d82EJs9abqHXzPlvE/Cpe8Dz2OyldjR5joi0aytuUDsLMs3i4XJ/W DkV5nx0HzNThY/HaJ+0QC3FpdWtvv89RclNd3g5FhAfo7J0nfHnppKh8zQ45 XPg4vXfeACrn+K/42aGOYI+wGMzqjxukIeP/ms48nsovWuMyNaCBQlIZ+pWp RFKK95FUhpJEIqVS5nmeM0/HcMxShESGSkIqEiqRhEIDZc54ThlKSt3d/dz7 5/PJeffea6291/fZ5xULsP3I8Skm+tOyw8d2l1pgrl8u4N99hp11l/ndVxYY eHLR7d99x+/G875SoxY4Va6i+u8+JFqSEX+d3RIjF52f/7svWRfplS8sYon0 msD/vU8pHGGvTt5riULWG9f+8coeDXr7ckNL7OBi1P67j2nMXzcS7myJqR45 6t99zcnF+QsssZZIGxf98+8+Z8Rcns+7wBIPNfQn/t33eDyvlph+agk2R9mZ f/dBnJs1KdteS3iKLmU1Izol9O3xoV+WEDouySZH9H9DplZnBKwg/rZ86AeJ T5n6uH+XvBVKNLvT7hO9P9c9SVfHCppJd7kd//EjG2tho5UVROaOyYv+u88y i6lRC7UC18oPv5pIfr7VCXY8yrLCjIiziR3RAWK5YwpVVniRCI0lRK8MkmW5 3WWF0fnQsisk39v2HZTOWm6Nz9nlI0WkXqqz2lTXSllD801AlgTRh1lOn0g4 YA12scDKDFJfNjUugSG+1sikpGcdCU/Mb/ibspBqjaibBbyvSX1G+UcVu9+z xo45waD/iL6pkt1lOWaN33PSBo9Ife/KkJns47DBmztzD+eJf3j++z7rKVEb TERwecgTPfSoZeuRkzbYO+3ARiP7RWzP72C55zZQY30j1cckvHM5/HJhnw30 47nnBhjEH/7kvSO+YIOdBl9Pfya8YVop+WGNgi20Ty5IPyH+56qi4fb5bFvk iO/Ikib7XTql/4BLtS1qOWbnZoi/ejhrd2rinS2kFGu97xO+eF8WEvZphR30 S2pPSvT/e/++tLvOzw6utUdOVZH+Hy/LE0kzsscD5z9bX7QS3gr74STtYo/T YlGSR14T/vjUZ/wy2h6yj+MZr14xsT2mQobriT1qrhWdqm8i/DRm2hq12QED AnsvBz4l+cgrFYiadkBt3/Es2/tMHFouc/zpc0ec7NV+LH6VxFcp+1DSG0dU 86oJOqQzcfsiv/KFXkdc1KqNfZRG5lfN8h/7vCPWNgYln0xmYtim4/v+rU7I fpbvcDOWibBG//T6RCc0bn1zpymQ1PfsdGxilhMSkvN+UgGEZ0Wsgs1uOaGh YNDtvj85Lz2P27I1OMH2gvyLch/iZ7ZIUPvnndByvEFg0o3wul6GPN9iZ2SO cuyJcCW878+7ZYDPGSp6qdySLoS3On6vCN7qjC3CSj6+jkw8C2nrqzvrjLK6 y04ONoS/L8R05ts7Y4wy9he3ZsJ1v+bLaF9n+Cq2Dny2JPlmrS07keYM7l61 OGdzJrz6fAv25jnjCasJpXmRxO/J7kyRMmcUq1OCkheIX7pUEj722hniE96r Oc6Tfn/G1vd1D9FslmmLzjEhQ0k4lY07I7J297IlZ8n8f18z9l/sgtc/ljrs OMOEXPepo2ZrXLCRturRydOEPx4JqGuIu2D7y+G8CBMmFL3jtvLCBcq7f7Au PcVEjJG22I/DLvD8kVxnZEzO192LBbqNXfBl5YMn5UZM7BWs56q1dMHg2gbR 9UQn/PBnyXN3gVxAxxL6SeJfOvfMRoW4INEgLXU50aoV30cdElzAtD3KSDNk IjW59JN+lgt6brZLy/77/s7V/o3SbReYszjatZ0gvKQv9WJDlQtkr7C+vkT0 1R3DVWxNLhDd02u9h+hp3py7I10uqN5bYbSIaK2p03mvhlxwUK2i9K0B8e9t a6+UTrugXOYirYzouZKOuNRFrmBrzfmRRfRRenyI7wpXyOy4sfTf93V5Dke8 zq13hWrZXNs1ohd0ltoflHZFY84F01Ki9bc9Oy+t5Iq0/tnHbUQX8QQarjzk Cv6KmV8LRLNOKh+e1XfFL72PG3eR+Rg1z6l+OO8Kgfzj8n5ElxSV7axxdMXd H1uVWoleTHOUyvV3RXmR6e7tZP1nrGU2Rka7wv3Kd7kMoss1R/js011x+MV/ mwVI/Lglc5ccv+mKUgkBvkyizZacXdhV4Qr6DuFZORL/h1/WTQk/dcU1X0Ly RK9q6Bpe1O4KQ/GMSwEkf5Z5iR+HP7viTGoN/16SX/6LXM9KfrnCYrn47U6S fzv1hgfJS90gf6uDfp/Ux1Px4NveAm4Qdbflv0Hqx7l/PlV9hxv2GG6uvEHq q7G2IlpynxuMdqzIqyT1J5LtHLj8qBv2vVT70EXqs8V0zPqdtRtO3s3K3kPq +T/kmVZ7usGi3XzWj9S774bz+jlhbvDnLV/5yoIJqZ73KrY5bnC6ork4luyX cOPGlSwf3HC0UfBUCtlfTeUKDnPDbrD6czxZwJn4jVVZr75Ou+H2d6FP2WQ/ JjW4R/XxuIN96sxIqzvxZwqb2Ov3uWObkn5Goh/x78sv/QgtcMeljXxsvtGE H63HDPwr3FHF41blRs6P/c8Mytzr3cHT3DLnSifj+cg4WfS44/EZgc9BSUx0 jbwf01jlgcolajpvyXk1VafwicvLA4df1uksuc3Ezg1ZyuxhHlgatmx+ZwkT nl5cV34neGD8sdbqC6VM/JXtN5ws9sBB079iTypIPjPi2lp6PXA5pETTroaJ LR5jT+M1PMHU35p8gJy31u0G4lEGnjjgLF96uJ2ch1trA4POeyIgyXKxDuFj hcFUysXXE10Rj8pUCI+qHTtQqV/iCerjzKVnhA9Di0v4j1R7ottFsyGhj/Dw YmG3A02euB1sP3OC+Mejj6fkFAc9Edqy2qCO+E8T6awiAUEvRDpw09aS/uJi PXmjZZMXBLR5VtBI/4kq2JMVKucFVbbOvK+kPz3Y0pE0reWFIx/fRqYQ/ms1 F4srNPSC4EI+byfpZyM3HCLPXfCCk16e1BLS7/g3LfN/7eeFPawRNDXCe1vN DD3DorzAttZaUIv0T/WcXGeVVC8M+EVUqZF+a9L3zXbmuhc4ey4Iy5B+7CIC i6IS8vnwoh4O0q+jTKPPna/2wpkJhfzXROdkvj+1tonocXHRSNLvH/RsPtHa 6YWNLV9m5AgPtAq76oYPeMFHwexVI9FfTtVqUV+9oCA5e0KX8MWf9OUHZn97 wX74Ep4Rzf/hFIqXeiN6TbiiBOGXrWsLlMz4vcF9QG3Sk2j1k993CIl7g5/v Cv99ok1S929rk/XGg5uGFv1Eu3TSJSKUvUHr35jy7z4pas0nMWh6Q9KDfuof j2XrS6//buANjShN56//vu9K9BS4dd4bHJbzKa+Ift3+bNUFB2/Urw6JSCF6 eBUf9zpfb/hyTy3WJnpB9yxne4Q3Hk6nvxsj811Nv8USmewNlxNyT9yIlnk9 P48cbyhtehE2Tta7f7nG7Pfb3vC88uW79r/3u44kM2898obDhWs9KSReztH9 oxdeeINFKGJZM4ln5EvZwXUd3ljjyDz6732yrGV+n9r7vOEmUBM0Q/JzX7Pp XSTDG9ekS7y/kPy1RAi8Uf3lDT3uHbxPSX5/c5Y23F7tAyVJmTQlkn++g39r L4r6QD+RRaud1IdU6OEq4W0+aKnbK6ZP6seI7UtJ1CEfvBp6NslL6stRTaFo n74PtNZnVh0l9RgRGHhj7qwP/J5IWrkR3qn4uy7d3NsHQ2E6O30I77yirJLW h/vAR2dW8xThnUG/iti3iT5QCfXbvInUO99v3WC1Wz4kD1kHHImfktqb6ffz AdH3H6ROEz+m5j3uUfLcB1LSn1pN35Px50JtN/T6oMLXXXma+OXwXW/MOyZ8 cNDl1mWhNiYy3UXORf/0gaOJ0Q7pFjL+zEODeV5fJKWdSF3ygjz/G5PqPOCL tXof1SofkvkMBCvlHPeF/QTtwmey/zM7BRTsz/miONNXa5KcD3xVkOT080Xz dAD98b/3n8Li+BTLfMHB6qqpepnEV1h2JFnMDx/1rhasJedfxIr6/nPb/eBt 8nvyvS2ZP6thz1bKD8t09KvCyXl6/4t/+zMjP8xUj6jcJud7VmlL1SzdD+s/ 6l/ddZDUp4Z9vMFfP5i/25r4ip/w8V7WaFEef8z5CCiXriT7d2tK2KSQP5za MoTjlpH65nvsE6roD5EphxSFPwwc/MRjXm7nj4JzlRfUhxgQdL21Z023P6I8 KzdsvcdAu/m+nX2j/rh14pD2bDED0UYdsrd++OOc66cndXkMLMLCpgN8l5Cs ZjrlmM7A2NIjK9y0LkHW/rqdfBADVdcmBt5WXoLRHs1LS/UZOL98u0bZs0so cFxlOKbDwFI/l+LE9ksw0NFN/qjJwAnjeVe9iUu4suX39Dcw4LmMnW1kRQC8 mN/rWLYy8LL2v3JD/gB0Py867SHBwAavQxYNwgFo6ZfNYNvEwLMvUS/zJAOw tVgnznQdA7zPViVd3B8AfqXfgYpcDFz03XGwQzMA2sJxcTaLGajcYTCnrhsA jevq6x+xMWCak2ay6XQA3N3CFhX/nkSp0cPlSWYBWPT2jbvOz0lwrup+wmYd AHu7jAKe75MovrTxvwH3ADAqom0GmZNg2bWvS88vAHtve3EuTEziOON8ZF1w AIypQ+4KY5OYN8mbzKYHYMuDrNeLhiZxZPWLa6tSA2DH2nQnrX8SWS9HjwVm BGD+J7eebu8kDu3ZWnG2MAD7HlwuFO+eRPo3HcvWkgD8ZNFWVf0wCcZNRyHV +wHwG7p34tK7Sew7m9B8pzoAMa73DPo6J5EkUOa/8WkA8v2+ZZt3TGKkpWN7 XFMAzgVWX13xdhJ7w370/2kNQKflr+vd7ZOIVVmbbN8VgPtPN/C2tE2if2bP oU89AVhhJU4Ntk5iZ7HJzyODAVBo1fTZSHSEmX9R9VgAwkUPrQ14PYluoazT W78FQOYt04yTaNn22hUZPwJQfN74emnLJIIiB2q5/wSAb8m9daFEd6pyuPqy B2JSbjOPP9GSc5s3TywLJLzRei+DaN87Gu9OrQqEtdH9Q4NEvza3jnopEIin F6/9PkaeL7YhWnnvhkDYtyxi/UK0e8ctRuGmQLDNsgRfJ/NrjH6dJSQdiEW/ lfPCyXqE1b/pRckFQvHvu5hEsl7HX7wc87sC4bRTy7DhzSTqSxXuW1GBuLtg sE6cxIvf+oTVe/VAuOrNTeaReFqJeq7T1A5Epx71SY/Eu+rd5VeVxwKR0q/z fTPJx0r6o0sSJwMxm7pp7798mR3qkUs7Ewj/6hvFh/79fsSfPwOLLwaiaMTi QBLJ77IKkRQPm0CI19+fXzIwiZJNF+ZPeAZis9FjV+uRSXTsLJA5dikQInJJ T1PHSf0cZJzRDgvEEDvtyTRjEvutPOuRFIhh45gxRVKPlt7Vs0pXArG7uDh9 /fwkommsEgo5gdByfzsv94fE+1Z0tERJILRVdjr1czLw63HbY7H7gfiWvvyp H9kfIq3834QfB0K2i031wEoGrKeyDFY1B6LQ2bbhhBADC4rlG+a/BILT6Uy4 63YGxDTmdWcYgejdv6/znCI5T4wQzJgNRPoaRU93ZQboPo1f+tmCwF0RHcFL 9vemJz0lLzcGIXPDhwMLZgxoaXLuzzAMwmIq7um9aww4GGu7pZ4JQmGnLE9W PgNJNvT8+ItB4BzP7M6+w8CnGCHuMJcgtBxavKi3hgGn9m0d9nFBCLlffXRt HwNppwwtVBuCkI0zIl83MVFte/XynpYgvHjRuNN8KxP9fn0vFTqC8McpWf7t TuKvs2y2Sw4Ewfps8LdYcp4+Hrz0c9XfICQ+8HhLkfN3YPapNDdnMPqCs2t2 ODCxZPGyM5w8wYhb31bL48GEnmRS3bxQMKL27VlmEcbEkN1N2oBiMBpS3xha XCd8qvLM2UIlGDHaa86+LGBCiLvfaHx/MBT+O7mdk/ClbuE6iWndYBSWmqT9 eMSEjdfuFR6GwZD7qDxcUEv8sIbB9/nTwdD7am0l1UD4dzj2KatNMGSljwTG kP7VVV5UFOYUjG5+kTf/7kenQl4kLPMMxnWbLx0rSD/k0R/yivUPhtF8moMH 4UkJcdZzvKHB4NpjGJVF+un+qQ0aKbRgaA7Ir4kk/fdM7V5ZoYRgZLa3ssuS /uxFP8mfmRYMX9o+fTrhxyRTtwXRa8Fw+5zMUfSNiTvbEgZv3AiGB2ulmN8M 4e2F2y8li4Pxapf2Y3bCD0PNL0tvlQaTdSjMgPAGy9WRy3IPgrG3ymVMhvDJ OhuOwPKaYLBOL21vJPyiuEfMUul5MKa+5X/59/3UsaU4Wt0cjGoxE1duwku2 704p7nsTjJqJ0JbbRIfne65/9p7M/6iN8T8+y3FPZtfsDcYXTRnaJNHVB0rH m4fJeDMmA2H/7u9Wv27XnQyGsuan2afk+dMD4w/eTgeD/bCDed6/98fvLck+ OU/0xI0xSTIfyaD/IrpZQiCkaK6lQ/hJ/Ziaw9nFISiNLDnLS3jJVMT0xCBP COZeqAm7ET7yZvqoWK4OgXyqfoAb4aHkx2mbJoRC0By++MY/HiqJKedyFA3B SlPeSm0S35cm7VPTW0JwT9J84d/7M8PSzPce20LQp3LrdWw/E8JNEjcv7Q1B j5TEvBLxB7suH4hjUwuBjmuInxvxE3qW593DNUJwbUF4SLOZ8ATnVfU4gxDE nz/xvOoxE9c7KqX5TELQ8UJK/tR9Ut+5Hbyp50OgGfzLPOEOEzNqK/oyHUKw xXJaujmTiRW8Mi/E3EPwjKPU73Uy4Z8+jTt5viH4sXxmnR3xW2cvBfndjgzB TEFyv5cnk3DatQvy9BB4yspfG7NjImV9lXZFSgiW6N1unSP+sfnR7NrH10Mw qfL7/TdtwutRvIvUCkNwwFSZ/zOI3zaWHXlWEgJVI3qc/Q4mds9ZVryqDkH9 x14B77Vk/grdej1dIWhxbOhzIvv75uxouOqnEKx/s7tvtJ2B4oofVdcHQ3DM b43umqcMVOzm22L9LQTR3w/di73BQJOy1q/vy0LhuTdsjeZFBqbUK6+vpEJB fQi/v/B+EqoGSTP7c0Ph1+tT9LFoAgf4cyTzC0NR/e4SX13aBLS67pxZdjcU Cx+KdctCJ6Bv9PJFa3Uo3u4u9HlhOgHL06wZp7tCwdXkqcS+ZgJ2G1a2P+kJ hVHv/O8M1gk4f16/eNNgKMyEWlNPfR2H7zklp7GvoZB6v+vnkeZxxF10POCx LAwOPlyXTcPGkbTZ3/vDyjDo7Q2xtnQbR9oX2h0VgTAonJ4vL7owjhyr/LXs m8Kg7ikVOrF/HBV2nybpKmGIup3dlcUxjkfbJsRm9ochTaA+oOH7GJ4wfxoa aoVB48qwtcrIGJqc1tStNwxDda5os0jzGD65HU4pdAxDQOxSnyVpYyij+2mn eYRhWU3Un9GoMdCKbrOE+Yfh4/uPi+E/ht19K23ORYfhcLlGl475GJb/3idy NDEMbjI+AitOjWGI36VDOT0Mu4K+th3RHUPC4Q4I3gyDaC9d/pjyGCwtOGc5 7oQhWTL0t9COMSBoV+F0eRg+1zpH2EmNgT/D0rSvKgypUx+PaIuNYeL+5dWv 68NwR6zuQYXQGOramxqrmsJgZ/hsWynfGNImf/kXtoXBXJObQ5VnDPZLtiqk vQvDy4MGUecXj+GA+JnR0M9hYNp2LBJmHYMwFZfpMhwGn9/qufYLo5g6+eT4 uckwjFbeumbycxQvXL4tOToTBls3bYGR2VFkxoo9Vv4VhskDseJ806NwLTju IsUaDsFGh7bPX0eh/TREQnBpOLxZBsR0maMQ+1zew7EyHIsOvOIxZ4xi7udw wjR/ONZPqfuKE92yWlCjb304WC4UaUcRfUNWc6FlUzhGL8Uevko+76vlXVol HY6O5cx9p76NQu9ikUWhfDi26z7sfUHGlwjoFk5TCsfRJ1yvh7+P4m86T3uo ajhgbHK9Yn4UneVUuMuhcGy2fDeg9HcUxa0Oyud0wiFFU+JwZh9D0HjWNx2D cDj4DVmdXTYGI872PGWTcAxYFZ/lXDWG7aJsJlJm4eBdny9+UXAMnMoKqwSt w2HaUtHpJzKG7hMXn3M4hcNae0vYMckx3HNK8Zn2CMerqB3/9cmP4Wz+3FBL aDiyPXPddmmMQbFO8kpVdDjOpE/5/z0+Bp4eY93CRPL807riYWfH8JC3+mFo djh0gzZ7tvqMgb6V4eByMxyXn/ZfSCL1Z6Gx8b9zd8h688pNBdLHsNo/ME65 Ohz7HL4uN3o0hrG0UnWpp+F4UPiGxv9qDLX3Bn4KvCTr98/Jon8m9TB64ML0 u3AUlPXmlnOO44X+MqXCmXAoJh5Oij89jkyHvYzUX+H4FOfbwkb2m1uU7fVQ 1ghYX+TfJxozDrEnLTznVkagVupwnk7NOHykE/sFZCLwjVm6/5vUBDTYrx6O k4+AsO1qoxMHJrC6J7eCUykCBQdAyZydwO3YiqjZAxGQvKTuuSp1Ar3f3su/ MY2AoOE6jbklk1CvFAmOTYzA+rVjb3fMEn6Ml5zkSI+A/C0jowJeBnqs5A39 siIQe7BpJ0OWAfd16tK2tyIgIyk0d9OKgf0zh5MH7kVgs4LXhz+hDKx8ZfDX +GEE0tJz+QazGSjwt3ij2RCBFaGJ4vzvyOcNHVVqX0Xgxe+7DtQUA2rbvfJ3 v42Afasp9y0uJrr7ony29EXgz5Qnc7kyEzcfJg5lfolA0U2rtR/0mHBLvHqU nxGBZCd/tyuWpF8euC3O8SsCWzLWuN769/uF6+/H+C6KhNyxpuVvc5jI/17z Y3pxJF7Fn5y6eo8J19cvztksj8ShK0V803VMqN5se9m/OhJ2H9/SalsJrwR+ 2Gm8LhKW2fYl093keUYD19pEI9H4oVnajfTHPPmJpZoSkTisfFdA/ivxv1yz Lk+2RYKrzFZAgPCG6uBCz66dkThZfNBlFenf3NWcGnf2RiL4KN/OFaT/v09e UbpZLRLxM2b7/93f5NkLCmdqRKKwN92vjfCA8yHRsDVHI8HYOPHOnfAJRKS+ RhtE4u6Vy159pL9z/5Q3ZjeJBDvL1xZ2wkPv2vY+9TkfCQ6LN0UdhKdyC9W3 TVtG4mCa8xmtLiacgo+kWTtEwu2IRYPxCyYokxOs/W6ROFZractC+vGynaa2 Rr6ReNLtSVMkvNjFY9nZGhSJPdVNkvOk3+YOO6pqRJL1ur0T0XJlwrHGq7Am LhLn7Se2bDFiQiUtaPWulEjcuGb8MXEveZ4Tzf/21Ujkbm2qSVrHRKdm0sh/ 1yNx0TpLbftPBvE7N6pWl0TC6qzeMeNbDCi/vb05uiISKSm/Bf8GEz9+6z6d rToSH1RMeq1PMpBzpvHCVGMkFqiH+7qIn1CNn9WZaY3EFt/WDQ+eTuJTvajS 965IiNwNFDKInoSQpDfP/FAkMgZ+D0qvmUTitFTFItYovC09GF69cgIhEdGL V+2JwmL3luuPX5Hz8lHlN959UXCvu12YFzSKJ5ODH1drRGHf1OsBy12j+K2n UiJ4IgopdUWLWLJH4LaecVLEOQo2I8+W9Xh8gXnp0ULZwigIplekXdMeAvuQ T5Lc3SiM/KmbOcE1hByBm/47KqMwd0Y9wbV5EJ98WY7veh6Fwh1r0tYfHyT+ UkZF6VUUzgms3/lUcBBC/Se37H0bhb0SJhmLewdgeOjuL6o/CoNsmR4JLgP4 7tUzpDoahbrLPELEHSCpeGmr2tcoHIy6wsO3fACtq87nHvwTBRblohsdd/ph rx4bq8FBg0B/YV1ocD+4PR56anHTwNbToyFi1A+Nbt4jOkI0fP7qr7BzWT+G l2OXrigNR9IjX9YM9SFkn42ongQN9tYlhgb1fRBzTeXSl6UhPn/91j85fajN q581UKRBVM+gpy6kD2ffMz8bqtDwkV3+cLFlH/5wCTcZqdMwI9z+rF6nD1cp jbJT2jTU5Xut5tvVhz1Orpmn9WjoXHUqNVe0D++uZ0WYGtHw7scm4+DlfXDv bHY+d5aGNyolMo8WerF66U8TMwsalDhNq04ye1G6979DF+1pqLzrcctqoBe6 9sfkLNxomFMJrfj9vheMLL91Vr407Jr8+Ej0TS+i3xRw2ATTwFt5eHK0pRfS nJ1M2ygasmJMBy1e9aJManqLTjwZr3Xpoevk35WPrjwrm0YDu9t78+vtvXjq sjVt5TUawhtmYv3J8w+nabV+u0FD93Phd4fJ+G+rLJa8KabhSVGdlsTXXpj0 haiW3aNh2MmEdStLHwY5cjyTH9JQXLv1mBdfH2ylakrca2lw1l45tFWqDzM6 3SOGL2jg6k8Yt1Pvg6/LTxGl1zQIBdXsND3fB/Y0fiOhThoGeWqMpEi8o6t2 xP/qpkGj6HLbfEEfVvfpNnYP0DD9Rm7N3zck3hz2ix6P0WCln11sydqPTaQR X/tGg+voz922O/tRrHPTKWCOhpbkJvt9dv1QcHlWcO4vDdYqtgtihf2oSu3v U+OMRo+f2WmdiX6oV/1du4knGp1Xxn3ZFAbQ3Cusx7E6GtzB0vtCAgegz7En algoGk2Xm1v4OgbQLWlY1yAajVJmfeTstkFMOsfLR8lGY72P3f3y74NwT71t baMYDWkvm2iei0P48+hlzmGVaDRL+nflfhjCcg5OvhXa0UiU7jNd0z2MFElx 7a/HojFpuD71j8UXbNBRDW47GQ2v0ApJpV9fsC3VezrRPBpbervWqCiOouJR qrSbXTR2TfQ313ePguotMzvhGo2lC9Lc8+Fj0JFkvhEMisbZRY2sssPj6DzC zT0fEQ3vy+s43iVN4IyzpPrHuGiwFI3fN8MkhlMO+lalRCN1pY2vbP8kHB6Z lWVkRCPOPe3SrCcDc58DJvxzo3Fabt+bjj8MBLBnbjpbFA2pS/kSjvbEv0s+ MtlXStabyyXES/oP/ci7JLEH0ZhhVTrxe5oJQefZZrYn0UgbCfhS/e//h0vh 5Rh6Hg1xbkfLrB7inx/Jqjx/RdYvJjQsFEP83OfDbvlvo2FwNCBGmfTP3ezW tyI+RkPiSObUgiEDTyTCh6z6oyE4ufi7pdskNI7krtcejQZ91dDHaIsJtDrV Gsh8jcah42l/lRXGcTLlUwzPj2jYvn1wKad/FL0Pfz1jLETjlC2f+13vEXxl U1S8yxWD2t0B22UjhuApcdw+gTcGJ0+EfbzGPQiWI455LmtjMHu1K35JWj9W phTyK26JwR+f/cTCfEbawwYdgW0xUP5srl2ysQcinwfD5hRiYPY8YX/Cww+Q k9j446FaDG76FB5/aNeJkmWrB//TjMGhtKFgoRtvsW1ySRv9aAyWfdX12fO3 HcWvF6p/GcRA867ndLh3G6RKpwrNTWLwMWP/Ltk1rbiZ9CW17XwMdD74fLBP f4XNHt0hylYxWP6A/8X2fS+Ra9TmlO8QA4dix4JkoUaIKT8/w+tOPv/SWe6m WAOyNjzS9vONwb0Tk2ZXDZ5hw6KS3SNBMdh9lPP7+zv1uDqQ+9/xyBjYzuoe Zd1Wh3XPL/M+jouBtb7GkenmJ0i/GftXIiUGYof8jOL4aiBIC55IvEricYwr vai+Cil2nu//5MRghZFmkfGNh1ita/fcqiAGQfVrdCTKKpEgf/7e2zsxWNi4 poljogIr1xhmoSIGXin7MtU0yxH7QzumsCoGCrvrNoe+uAeeD6rea+pJvMY6 LerNS8n5sNMioDEGafvcNymL3sWya1L6469j8EFo6mbv2B1wXli9rbY7Bqd3 r3ph87QIIQeXrpMZiEHm3pwTNZMFYJX8szh1NAbdqIvt2nMTAVzTM4u+xoBr X39+/s08/J380mf7PQb16/hdbBRuwL+1u6XrdwzedEaqZ328jt+lbY/U2GKx Wa+Z9udKDuY8HiULrowF7Wrl9Q1ns+BuXBIUzB+Ln9mlR+OeZGJG+YYDQzgW wgpbD9YMXoXzxnQTI/FYLNolLT4reQXfFsVpPpWMhY4f/WtazGU4DgYrym6P xbLWuMLDPGlgPPcUT1eMxRq9jJrhvBSM0c4vOOyPxdtsgeqVIkmwtDcc+6AZ iz+7MnIkfydgWPdw1wHdWDDkylV3jMfjwo59T0tOxGLqxbBS4zgdA2sU7647 HYu45IwhjZ9xOD8nlRlmFgvdLrUP25Vi0fthI+2bVSwO7/FtEU2ORve1pRcb 3GPhtV0u3uByJIyD/hyT9yM/Hyb7fTUVgXcXpqmM4Fi48Ki/ff0jDCcOjUgv iYqFfcEJAYFnoeiQ7BF0ocei9EdydWpuCPS52zk+pcTiWLSzu2ByMNoZz6c0 MmIx7Srq75EchJZ7Jc0bCmNh3pgbc682AIdTbjyILIlFW0YOz4WuS2jyTM+b qYjFUv8r8hn7/dGgEhLQVB+LSzLsqXfO+OCgiJfdzqZYqCQP89cv88ZTVnvj rNZYlGdtYQ1u9MSTBkMF955YPGBoNvp5u2Mlu2O2zWAsLGlieyz03XBWNWL5 ufFYbNk7M6YBV/ytrBzR/kl+3m451/X9ztCZbTXYxxIHTfs7NeKnnJApN1qn uDgONRxSYoWXHEEVrs0QXRMH13yJI2Lv7RA7LLdMQDgOT8ys66fNbfFJTMuD WzwOEd782RNLbOB3xfvYj+0kDz8O2AWEWKK5K+HxxK44cFUumRs8ZQHh1UXS /VQcFMePrV603xxV0R85Xh2OQ3Jx1q8K5Qvgbpx2rjseh3dXxLRyjpjBhIO7 975xHDJi5tiGrc/jl5/ywxzLOGx3NXIpbDgLrYf6W9Ic4lD6rvFAH8dZpH+3 TYpxj8OvFw76FVfOYI9Dhr1nSByMXA+V9H47haii8o92tDhc7o9tXFthjA9f XmmYJcSBJYWj6WOkEbzP/hHTyYqDaejHxTkmhmi6yk/fnx+HHaZ3uYSMT0Do /baF3bfJeF+3tbNcMMCDY6Zd4lVxoJsVefilH8eSWA/1tfVxSEhaL9LzTA8n m+LuLm+KQ9i3kR6VX8cwp/aE9rMrDi9XXjWfCdSFxqV3c4xPcbh00/hKUe5R pD36enFwKA6FIQqbMgx0sFtBVPX1dBy2Pt0++XJQGxGOSreezpN8dOm+D63V gm2nBE8PCx25bBn25kWaqOLd592+mI6N56pPc+QewuD2V9uPcNExlVwsEHf3 ILiPGn1pWE4nvspKoqPxAE7RnPSr19BR4ztcHSKojqCChWW719LxftFmvh9H 9qOwIbK2VJiOM7wPohSj1TDPlrPtpjgdF5aqHXUR3QcxsW1DYlvoeGy/+GaB hyq0VB9eyZCio6+Nf6dKIZDu274kUY6O1DNPjd9rqKAu/UwNz046zJLvf9KU VsZY5ZhbxG461Nz6xO+t3Ys9s6wDfqAjUuJ4opqgEt7b7ai2PEJHuoTiQ3rs Tvy2lta5qUvH6ltVmataFbDBUvzzl+N0fFoSrPRSUAEXzvMtsjAm83vW0Fz5 WB7hplwJeafpiDt1xeH0OnkUmrCJD5+lI/Z49fN1/nL4emJa/aIFHSph839H 9LeDT3+8I9eajnXSj2QWxctC8diA+aAdHdGB5kvDgrbBV/tNhJkrHYVOQgHj QTJYonqv+VwgHTGP+jsuMyQgrVJ0OjuEjj8F9+wb1ktAZ891Rm84HUvbg6bs 9LcgSSFx5dlYsv4GN7Y/nf/hvhwt+1o8HRFetEunxP7Dh23B8p+T6PCQqfZd 67oJIpIu+meu0FG6u1nmsaQ49m+2GcrIpKPqwVHGthgxmIubufdkk/ktKVy9 +rsoitcfTzO5ScfTtvdFVl0i2M27o9u4nJyTrQ6rZ26sx6kV0nbplXRcPPRf o/UDYfhzi/95/4iOxvPWSmNv1+EpJ5+IUR0dDW539TvFhPCFjetu2jM6/juz a1GZ/losW8Sm9u4FHWPa6VK+MYLQ/TVlZviaxEP4sWIzrwBc5sZmUtrpOD57 JeDDGX6kzPaHdnbQIaLJ1/e5ZA26me35Bt108NJZeb9fXA3LwdLx46N0SAss qWlZzgtaX6Fv4gQdSe2WfOyhq3D7Uw7PGyYdPBud+u78XYmZdwmyet/pMMnV 6n25aCUEOqOexP+kw9oyN6t31QrseRN0rO03HfbpDtu+bFmOgFfOLrps8VDr da8QtubG9SZrdjpnPDiPXK1tTObC84bzya+XxiPrdZj59hfLwF2nd19nZTxy OH+cU1VditQK+V+H18cTbuUO9fbgxG0Z8R2+IvFYwS4TKNbJgec5fDZF4vHI x6RKqRIHvsfOfFgqFY+GBYPdQ8vZCR8P8SptjYepTbj8ngA2bPbp0LLcHo+4 oTzND7OsOGFR8fC5YjwsuvRY7CcXwb4nb2pWKR4FJ9na1jssQtjxVKn/VOIR WfJgcfwMCyrgmR68Px56pTnFB5exgF9wj7eqbjxWhfCNpj76TW2LlSp1OB4P KT3VLe9mflEH2deNZZ6IR+dKuenhHb8o96+/jBZM4jF11h8VdT+pzhfVSg+t 4rE0ea2oyYYfFIO67TRqGw95dnbdA4HfKc7yzAJBx3hstZL3vTMySylmX1rr 4R6P1+JOF7yezlDJXvt+7ggm6x3Z8fxA8RRVzJSTMwuLxw1qWJcuO0U9vShm lRAZj6CWxKzTFd+omWNs77/GxeNeobvl6pavlL7Us8pbV+NJ/vmdTx1kULZZ 5V+7r8Vjl6dDTeilSSqEP0+C+3o86MsvTMg+nqDKWMPTrAvicVM+98pp7XFq 9UcNzy0V8djf0VT5IWuEkjmmVHLiAXn+lKhfxaIRSr1BciS0Kh7VrDqTQ+Zf KNd7y04O1sWDdptxsEZlmHpLa96V/ToeR9fKnFghNEhNLKp2aG2Px/a+rdoK 6QMUu+et/L8d8eB1HPV4un6AUrgQK3Cmm9TL4KvSum39VKKy7g+h0XhMrgqc u+HWSyWZ6jnETZD8bMyumOAgOkj/C9vXeJQW3Cx+Jv+ZSnlxsmviO4lHbXXq TEIPlaZ/7v5j9gQsPl10Kz31A3XZw0x2x5IEbOJ6xWQZfk+lp1/Mz+dKwPFd cYHnlN5TV3qtUum8RHsEX/ZidFGZts4e50UScC5cxF4ktoO6FufK7BRPQNN+ 0TZrlg4qq9TdQntLAsxlvupluL+lsue8DRW2JcBgBav7Afs3VG5I8C5OZTK+ vMHstfA26kZ+6B1vJODT+BJJMf42Kq8pfAtTLQHZwVpxlfmtVP7KaIF3mgkQ XXJXNjb/NVV4NelHgWECBoyTu6XSm6mimhSHDacSoNIynFc18JIq7k/7knAm AZkOxs+3yr+kbklkdPlcTMAcu1aASE8jVVJ24/4RFzLf72GGuRYNVElXvmyd ewJsjc6Khb59Tt2dL8hX9E5ATvurXPUDz6lS1dupGwMTIPnzvOQ3uWdUeXOF x7fYBKwJlhfasrOeqmBWMi8mJEDrbZjuhsd1VAXvI4sPyQlIv/ZAU1qrjqo8 WWNYfzUBwkoy+bI2tdTDwYZdyYVk/sUFVloZNdSjxU13lt5OwFeN25mruh9T VVLNW/zvJuCX8W/TFxsfU9WOrQIWlQmYmQ2/6lNeRT35/e7H7uck/lq0vU78 D6mqPwe1nBsTIPF7hU1U8AOqkqX8alFzAkI30tQFZyqpO+zx+za8ScD6+vf3 lD7fpzK5NWlsvQlwkAwa0PxYTqUvv9+jPEDioaXs8fBcOZWy8r/t7sMJcC3T KlsYK6NiVi/qGJlIwC71I5zlHGWUr/CDDS0/E/Dhzbq7y41LKc8NW5wWLyQg qY2ndvfsXcpVJLlelSURuYcG6koT7lI2m5ws73EmwnCyjfP02xLKWEayNI0v EXNLWr8J9t+mTmxLZW/nT8SjvuXrrPfcpvS2cxhyCSVCa4YnNDzlFqWl0PfL TyQRN+tN7zUaFVNKypcPmG1NRFn6fMLfpYWUArU47er2RFyPqGVT8y+gtqu6 jXXsSMQiney+3NmblIT6sTiNPYl4LlQnEjCZTwkeXvp+66FE8E2/XJr09wa1 WsdD2kIrEQa0jKmeqBvUSt0hv6wjZD5XfdyqBG9Qi/Vrxfj0E/Hw8uO4n3tz qe+nvGznzpL1TRjrv8vMoaZOf3ksdyERNY86n0uo5FAMU4NVNhaJcPhzvuZK TzY1ZCZX0WOXCOmTF8sqNmVTb21G/9Z5J2Lgo9aG3qRrVKudod5vv0SoN/M4 sX3LpJodnuXuDEwEbZvJyru6mVS9S7bmzfBEeO5Z73ZSKIMq9TFKjElKxFgr z407b9Op9eVTfZvTEnEmc++nzXvTqQgGbfuTKyQ+14U3H7xxmTI99/jVVE4i Blk0Lm8ISaO4D4kvOXk3EV03W9OfW6VQHgFVJ76VJSJz2c/XS8aTqf4HBjei KhMhMsqudtAhmXogE6FWXZOITsWeVRYBSZQ576SvWEsidkT5rtCsT6DatMNe PmpLxG55QxVr4wRKOXSjkEFHIjr8d5z/NR1P8c0dux/enYjL8tmnt2+Lp570 VHybGCPx8TpTftU7jpIR0FUNYyRCz83gZFFzLJWqOxq7cSoRsozJykqxWMq+ fp2M3s9EeIQEl9l+iKbWFQSY31+chJnzg5p5blFUWP/acl2uJCRFrTXjG4qk ptbdYxtbnoSLMSMNLwwjqRexQ1nC/EngkQl99+hgBOXuqvUxcFMSvtNCJoo0 wqi+WwOS6ySSkDN0SkC1NZQ6/MXXs0w6Ccreh3dGGIdS4sZ31nyRT0JK/Y22 KfcQqpU48sP7krDzy3CI36sgaq/Xrcwh9SSoai8cn7cMovJKD076ayThPM87 zVLOIMrvP6+ou0eTUGCryJ+pEUhJcX16yn8mCU1tkTOsTZeoZHUPvpJzSYi+ FPSiT/QSxeK/8rzmxSRcab8X7uTnT3V9VfvrY5uEVfKVuw7Dj1KT6j6yxjEJ ixjXH9ve8KVum7ldve2ShLJnXMajy32ptRnLxw95JEGi+OSm2z4+1P/9/WH8 /98f/h9r+lvo "]]}, Annotation[#, "Charting`Private`Tag$12701#6"]& ], TagBox[ {RGBColor[0.363898, 0.618501, 0.782349], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUmnc8lm0Ux2WWVVZGRlQSFZWQuC9KkpAtkWSnsvfeezxGqKxUispMRnKM QpmZZRPZzyOJovFe718+3889r3PO9fud89yELRx1rampqKh2b6ei+v9v2MCT U5M+qeCYPT2p2nSU4BytWSnwTIXqyrffeV0liUdfOp64uKVCTUUxSzSHFPF2 5TsXrUMq/HxT47PcIUXQMSmtil5Phc9a2/ZSrh4n0tj0CihXU8EscOzst5bj hCiPjXnVlVS4S69p7i19glA9ENd5QT8V/t7TD7zKJU1EoE+Ft86ngur3mH8G P08Su1UXr59USQXyrQ02Oy8ZIl/jL89fpVRgaPCoT9iSIZqN90cmyqeCj0KM uT2THEHv5mRZdiQVbpg2MRbpyRNpPqF8vuKpoKtVJPKSLE+IBqd9PHsQM3Um JSD+NKGaUIv696aCMnoZ9W5AgYh8up3/J0cqbPnupWzcQwRP8Z7e+l2pwHHM jSVQQol4WnE0JpolFZxjY4iPsUpEa6P+Tz6GVLDevf4mV0+Z2D6a26e4mQK9 eejLy21niYwv5bH0GymQeZ+2Yt31LCG20Hym63sKHG668YZ1/iyhtrFUYr6c Ahs3lgVYR1SIKLZT8aETKbBletoheFaV4OHRUNEYTYGCd5+Gn7qcJ54KXtvi HEqBS66GWlrb1IhWifAb+b0p4BXUZuN66AKxQ/XjuffNKRAyMjUy9+QicU9j +ndSUwoorTwn6nU0CHG9jfIr9SngYycjNvtPg1A3FxBZqk4BkfsTJ+7f0CJi fG78ZX2RArLz2wwYXmsTx/rs3ZMLUuDqrvE/TRI6xKcjt5a48lOAfWRn/6Mc HeLgpMMQf04KaCWIpx1P0iXennd7JZ6UAozP/pqcy9Ynbj1wP1IUnwKs40XT M+IGBMeWx6NjMSmQnh24L+C1AWFR5J0sF5oCD4yDDXbNGxL/OAMdVN1T4DzN 7c4L3sZEvkPQzHvnFOhaozt77NAVQqs12FTTIQXIIudKhcauEJm+Yer6tilw dINHv8jIlJCfiha1ME6BfoOtoAMJ14jJ07FZMwYpwHeSI8v2pDkRdSeO84Zu ChybVjxLzjcnBtUSqZ0upoD73ziJ9ZTrhFtx6pi/Ygps09zL8CXDkuDfkWaw TT4FvB1ebZTvsyKaLNLbw2RSoPzx8bfpZVYE++57NbGSKZDna6LJN2pNVDve P7bzcAockh6S++NlQ5i/z3yaLJYCXLbeu315bYliv5y0u8I4f+/HC0bs7AjD gVwWAcEUaPooMs7Cc4P4K5kXlsuXAnVPPOTc228QGl8euTzhSIFoQ5XVxHM3 iYULhVoVdDi+T3QVFvwdiKSHz97JUaeASdfJU1UmjoTcn+cKtX+Twbe/Om7P XicisqRYvGkjGUQskBD7TmfiKGPpA9W1ZEhXefmFOs6ZGLAs4/mwkgz5DVMa wOxC7OeuoP84nwxP5tNiePlciXanV/76X5OB8bDTkV/5roTrh8q1walkKNke aSgm50Y0+tdMjQ0nA0lO/SGdnTtxbRrqljqSQfXq2/CNbV4E8zUDk2cfkoFr 7EKhW4EXUfV5YeNGSzKMO9DcbjPwJnZ1cR2brU+GczxdSzlvfIjG6psPJ8uT wTpw56frnf6Eg/Q2pdwS/LyOS0+FHwQQfMVpI2YvkkFF49VbNp9AwvVRA9dI fjI8lRM79DgniNifyB01cDcZ3nofkPVMCCG6d7zYfyctGerEXzP7cYQSfmFn GvRSkoGXrlbdMzOU6Pe+vdkdlwwH7+xw7KkJI0LWqNMTo5Oh7S59j7t2OHHU MeOEVkQy9NFUFKcthBMRVk232gKTQVaYp3r6cCRxfPzyjhi/ZAg6dmLFrD+S GDMmP1bzToacja6vKyFRhOwl3vF3Lsnws0fhMB05mpg75ahTb50MVH9FZSa3 xxOpL2nJARbJUEX9/S71eDyhJHkvRvFaMlw9n8r36nUCcXf/u6aay8kgYenp 9kmFRKjmXDH3NkiG/u215Io3JGKVd+W3rG4yJOtsHdKWTyLUd+6RqbiYDOoc zORTKJlYjy7pcVVLBjdzt4a2lmQij1bV8fi5ZDjSoseVo59CbP1yelpMJMP9 wGraTN9U4vl0M1/hsWToOVKuLkOTTly+ZlppdzQZFALtNtjL0gnaoW96ByWS YXU6d8DLJoO42sUf/2h/MvwTnuR7MHGXYFQvO2QpnAw0Xnw6rfn3iFdvzzcL CybDXngWesb1PsFa4/IvmzsZsmZo9rHuzSJqpLdnXuXE1xd2veulyiZsirPk +NmSgfvSj9W+uWwCHrU632VMhqG7V+Xe2eYSTomC0yl/kqDmvciu/MA84mDS 688Wm0lw1PxtfzfLQ2Is+XLXsY0kcLw7VhCT+5DQTEuu6VpJgqfDNK81+h4R tBmSJdnLSaAwkHixwP0xUXu3/fHthSQgzzNkKfLnE+JZ9ElM00mwY+dKS4v3 E2Iy+2HE0EQSGDnfpBY69pTIyFXyKxhNgtF7BWQn8lOC4ZGP7fnBJNj0fUs7 4ltITBeSFUM/JIFkC1vIgbkXxP3nsSd0W5IggeVv6v3+IkK3SOyQ8Nsk8JXl +bv6oZhoKLXghDdJ8Gh6QOfEbAnhVf5vR0JNEkzspBaMdyglpCoy/5lWJsFr vz9UjpulRHbVwMJmSRKI+Ap9dtlbThjWuE68f5EEljQtr5ZqygmW2l0DGYVJ cITPNSv7ykvCD9QbZB4lgUNCePbtwgrCuLku3SU9CeZDnVx8kqqIXa0m8cqp SSCkGrNob1JNtL7/GbIrKQmy94omaR2uIWQ6jjsUxSTBFZvaCz+/vCbInV2W /pFJ4B5+9uqFtlricfctY42wJMjrm/n8sOYNwdmXr7LgnwRLCh/CC8uAaOs/ K1/tkwRyT03Tfl+tJ0IGJySjPJPAoCtJ5uJsPfFtiG+PqHMS9J1ouJGyvZHo nEz4dt0qCU7TdnIcjn1LhH+RmJW6ngSpbOd/mcm/IxRmWkf+XU2CjL21NQOU d8SzOerWLKMkEDdM7o13aCEsFnLe3NJPArOtov3acq0E35JC+WmdJOBfOBN8 dcd7Iorikf1ZPQmU8rqkAxo/EOgbR+rT80lwcEH5ucSzNmJ9tSTaUyUJnG3v lFzObCes1xfcuIgkmDW18I+520mc+WN2UedYEtgqyb1oCftI7NJdoBo+kgTa 7Qq8eUd6iPF891dW4vh81f0iBqM9hJ92nLDXviSInjcL9NHtI9Qfcw9u25sE 779ZlJF4+gnezby4WP4kaDs7da/laz/x6mH1RjZXEsx4qZcwZQ0SYT9VXoix 4/jE1DGOhX8i9DS7LcpYk+Asz+5fJl6fiZX1rx3vGJIgbvbvrj1+w4S4Ouej pV8kkJSW9mWnnyB+ZucYe6yTYDcV+7tPTyaIlu/iO6m+k4DeOJw/VHuSsMpS 9uFYIsFX0f4r7ZVTxPHVdsmsORIoHIqu4vX8Qmw7f3lGdIYE87xeMU+JaSJ7 xUFbfowEikcmg3jnZohb5zbp3g6R4KYmY3/Xh6/E6XvhrzUHSdBN1Ac4Vc4S n85mil7vJsFIhBGXUck8wZ7+/ndkIwk0HgymO0qSiYlF/TI2IIEg+1v7HU4U olhpwvb+axIss0jMRVxbITQW1nuKXpJgjWXsZvq7bwQfComSKyVBLnl9YzZs lZhPYSEaX5Dgb79cz6rGdyJCcX9Bfz4JCrbrOm78XCP0k4vNrj0kwWI5i97E 6A9i36w853wOCfi/SwVbdKwT9SSdwN8ZJPC4XBxt0vmTSJgZkY64Q4I2tYO9 vyZ+EVfl7RZ2JpPgCfW1A8FUW8TmlwCDfbEkcLVRTNiw+0O0yjEyvYgkgbSu 16J++V8iPf5OvUwYCZT1aiNq6amQtOxzCXV/EuhL7tGW9tmGqONkJ3u9SdBp VPLdX5kafZxoTLvqQYIsf+ckV3Ya5BDzeZuzIwmuvRN46d5LixTGrSo3b5Lg fKnQv+y3dIhJeuVWmB0Jqk2EWosa6NHTUfpP6ddJQLlOJbJnajvyPJ4cL2xG AjP+f1sj9IxINVLg7LMrJGBgvXBER54JfZGSLqrTIwFPcmDjnW4W9CpfLzpU mwQRCRcOdvLvRDH8rlZqmiSISb924qbCLiS1vYyvR5UEb0r3GQ6UsiHagI8/ 0s7i9dRGnxLxYUeD31e6TZRIcI64mrRXgwMFjEtGzpwiQWbjjSvqO7mQrsEl i0IZEpS9WJVN3bYbHWhzUHQ8QYIQvy6Tzn+7UfurF99/HiZBK/9hl1IRXpR7 uKPzzSESGHSr2TWq8SHXvKWCEFES/H6wuJnqvwfxJUiYM+8lwXjWdG/bbkFE prl4+iM/CV6H/Wle9xNCDd72u9N4SZBRTCdd7bMX2VkXtAtxkMCft/XQu10i SGG49cn0ThJcaiOGyxdF0E6duZACZlw/dRKCLD370CuFg6dO0JNg3WxYqaDp AIopU+X8SU0C1rztmqbdoqhGu33M+18ixIvf7jRZPIgYxNQvxq8mgqPrbEbB JXFUxBG9jXspEZSPJOl035NA+v9aKnNnEiHzE63z+sZhlDdwbv/LT4nAwvxE Mn9JEl1oDBtS7EmEO3Sbg2pNUmjlRROppS0Rxo/tS3pw/xgiwpX/DNUlAnfd xC0D5xNoximo3KoKXx/DVqvgJI3iTOEGuTQROiWJ8w/8T6LPJxQHtj1OhF+d 54h7LbIoSMgvLjY7EXa9s16Qpj+FRJlen+HKSISPRYPrJkbyyG1KrlgsNhF6 Lr+nOiGjiPZ0elqXhSUCGLatxDcTqLH61R6FgETIsPK6aSurhHYlSUddck6E p5lsYXX0Z1Clnyvx2T4RIs+11tbQnEVmdmVrFlaJUHxIs1h2lwqi0/9WuHQ1 EUgXt4mcO3IOPUdS1z2MEoEv+fYjBlNVpCfhyE2lkwga6y81a7LOo83dRR3R 6olgdm6puOS7GlIjS8hnKSYCXf1paWLqIqJ8tl8RlU2EBaucX4wBmijtXUF+ iVQiNOsLccdJX0KKpXOm8uKJIFY+NfQ5VBtNZx7keLsvEYwffzPt9NNBsVE2 7zUFEiHtT4nC+QhddNztceDg7kQo0ZO9FfRADwVe3Le0sCMR6M/tri5kN0T6 o4TIAnUiTI2u1iVHGyFxxyuX57cS4FXxNu9H/MboH5VHwtxaAiw2tfSqdF5B fclJb2eXE6BQLT+V44EpKtz/YvPr1wRwezJR+S3dDAW+apX6Op4AescsztOa mCPxoX+Z0x8T4PwSn9iu1xbo3809vV8+JMC7hW59rl1WqO+PzI4vTQngNCzM 2hZkjQoTddFUbQJEcY8PNey0RYHCDu6TFQkQ5Ktp2wV2SL88+tlEUQI0TVs1 7061R+LnHk+OP0mAm403m9lIt1Cf3Yjm2N0E8O9isgqIdEKFmxuho8kJIFsZ etevwxkFxnHUjMQmgOIuqRZHKVekLyi5MhyWAC/DqGs1y92QeIm66LB/Ahx8 RtBbG3ugf8o2pkMeCeDA/f2tnagX6usNTv7siOOTUU4ECPqgQuus1k92CXBU xI6koeqHAjeq/g5eT4DGf5mNrA8DkH50n/TglQTY6Zttop8VhMT3rNgP6CVA 6v2C1+M7QtC/50wP+jUSwPyRYcnCvVDURxwc7DuXAC9Yh0Mq9MNRYfcZlj4i AcYLSI3sCpEo0MLsbK9sAmgW0VX4G0Yj/TVv7x4pfD6zX5Z0YSwSj7hT/PFQ AlgJbBUaEQmIiqd0plskAeJ614si4kmov6B9T/eeBOjrD68f2J+MCk/P6XRx JsCRaE1an4UUFNRBE9XJkgA6bgEl2dN3kME1oboO+gSgWz21y5YvA4l/k19r /xcP0smsxzlT7yGqUEPx9p/x8Kir47OcSRbq53Qxb/sWDyMtT4/6Kuaiwvz4 tA8L8ZDdVdckQpWHguQK2t9/iYdWr2vfRP88RAYf3lK/H4mHky+eHbdVzEfi phNyrf3xsJHg7KDZ9hRRkbccWjrj4WvJETbe8meoP5D7cXNLPFi4H6yVoylG hWwnht/Vx0OXu3HAFZtSFPRQi+1ddTwIiNw4MZhUjgxO2p9/WxYPDJ8N7v3c +QqJt4T7Nz2Lh15/8bouchWiMn5Q3vgoHoRiNUJ/ErWof6F2viErHugpd39R MdajQr9PQg1p8ZBSJRR860wjCmJdM6hPjIcLp67Tcg28RQa5O+MgKh6Uz41/ 0elrQeLHJRrrguNhscePw0+rDVG9Vf35xiceLKsaskuMulC/gcXRN67xwMxH v8lJ3YMKZ/2tam/Fw736hJO/yvtQkPfde6+t44FX2jdN+8MgMmCq6K4xi4ep 8b/zM+rDSDyrm77GKB7k5SRfbpwcR1SSSwrV2vFArc4W79MwifrrGVyrLsTD WbqNN+6s06je/LjJpzPxIDdh7JBv9RU9p7p69ufpeDjlYVbaVTGH0nMjJXhO xkPM4XwFxS8LKESpjEPuKI5/Se6jrrYl5DAxsmV0MB5OrMXdN9IhI+MghmnP vfEwI2Wjd9qMglT2Hm9P542H8c8/0e15CpKqN31ZyR4Pbka1Lec2KIjfPDJz kAnnq+mu7tF0CmKgKgvboI2HfX+HNA3HyWg1Z+QW9984YP951UlobhmNIQYD 2Y04sDt19n5Y6xL6MH5M0WglDh5//iD5K2URVQSaHvCcj4PPkzpp2cYLKA5K f7wajgO6vQVNeVuzyOvayOhAXxxEejzrG//yFVn+o29e74iDr6T1qZjxGaSV c6xod0scXDX7E5FJmUbyyDRNph5zSMs2Ds5pdGA8IsCwOg5Wczkva2l8QbsC S208yuKgYFK2Uid9Cv0WHNFKexYHHxocNVe+T6LZOnrZV4/iIFeujnHRfBL1 mB0TGsiKA6k9Dk9pRidQ3V8ThvW0OIhuZT633XYCFWRHULhIcaAiXb9RvjWO UonSwZPRcWDLZ2U4oTSOgsaGwSAkDvSPSB4rvz+GbgbQP3X3jQMP/ZJAL8Yx ZCh4jHTHLQ78fpkVP40dRWfqTLwqbseBYhbqmhEYRUfNIsz7beLA/scF3Z8w gnj/lqj9uBYHmjtSXrU5jSDa7GEpLuM4kFAclL8pOYJWFOl5T+rGQcOETf3f zWE0PCq1zeBiHOwoPjDd0jOMmv1N5t1U4oATnTEUejWMygQiPqYqxgGHk5ST y6NhlPWmpPqlTBwIzEkzKGcNo6irww/6JPFxZpLHntxh5PaHLmZNLA6eRDqM 5D4fRteypFw4ReKg3+xEmH/jMFJXNLkivScORPl7vW9MDiOZ0fAz+pxxcIPz JHFwxwgS9i8Rd2PB98uMvx9yagQxCwyzp9LHwb65vUmXXEbQz1q6rfJ/sRDx 5KH+jfIRNG0q9aX3ZyyUfvO2Lv09grp+X2n7/i0WfrQJPmfVGkU1meHlHIux WK89Ht16MoryFUrun5iOheJSqcSa7WMoeWQoVG80FlZpDJ8sOI8hfz+6W64D sZB6NM3429QY0q+9olDeGguPH6WHXhkZR0qm4ft7G2Ihm/L2k/7xCSTxu5j5 e00sdAyaPtDzmUDUCnSjx1/EgmXsKe5arkm0PCz5Tjc/FsKsWwI4b0yiT75X XrjkxEKTkEHm3vpJVPy62L8sKRaG61UHuLyn0KMs6lK12FgIes2bf6hvCt0L NJgeC4uFwMQ8p2PHv6Cws1vqTF6xoB64kV6x/gUZt6nyWJnFwi8tfuGWLFzv L+5e3DSKBYUHf/LeM39FKolLASSdWHD5qr/Xw/8rOqqXPFOrEgtfPz8aqreY RTTDo2VcErFgNbtuFSQ9j+Mr9fXZfhzP/R2FFk/nETk7lPeMYCww6qZrn9uz gD5ZHApyYIsFqTvvz5v/XkAdKn7ltEyxsKF1UfXNjUXUKNr19R5tLNBniP+y 7ltELxbcNFs2YuDjQbb0yZwllNfeEnT1Wwwo25wKG/23hDKK+F5+X4gBwxnv Qm+TZRRPuj0bPR0DT7k3cw3KllGISz3f3rEY+JR/Op+blow89Tm0Xg3GAEsP +9vb2mR0S8YmWONjDBwtPj/Mmk5GFjzVL6c+xMBtpUjS60EyMtpkmvN6GwP2 JspsiJ2CNEbM9uysi4G/lT1FjqoUvJ9KtR5XxkDO4ucLkm4UJJtLG3K6NAYS GK3ibt6noMMhRhUfC2Og5TXLqkAtBQlbFc7ZPooBniivnIsDFLRb9c+ev1kx UC7SuZ1ugYKYxbQvpabHAJMFp6M11sNtjA9DxJNioPTFXenkvxS0vvijoj4m BvIlK9lq/lHQUofavGFYDOguKR/l3KKgyeL7/Mv+MXD3SfmB8RUKGkgiXwr1 jIH6VeZ/1yYpqM1VOZTXOQb6JlMFJtspqN4g9VWxfQy84TaQKi2noFeys/Pn rGKAho1eVCSNgp7xyguMXI0BPYMciSi8vtytOG0Xoxhwtf5YJXeJgtJGx0O3 68TA5IVXz6NFKSjoQfiCtEoMvBJrjbreTkbuoZ8E2hRjIDR81jTxPhnZW0vo XJeNAS0RQ6VCOzIyOPSxMl48BpymRZiH/iwjdab9i/v2x8CqaqtMUPMyUlr2 EKwRiIE6Bi6XkwnLSLyUP/zrrhhY3qylNO9ZRv/k7HTRRjQsrydmBJ5cQiIN 6XQXV6Jhkd9hx8rGIlK90FJlOB8NB1svfxV4vYgSjEWFHIajwZhqf7WByiIq mzTo8e6LBmkNg758xkXUfyM8PLwjGmh77I6q9Cwgfp/pxUyIhgC2eM1W6wWk RM2Z87QqGuy+6+p+PraArGLO6r4sjQbFRyt3Y//No2f38qraHkYDz+gfHcbc edQp0nNzMDMaWMJpNJdc5tFq4TahL3eiIatnhfn++Xkk/9o8fDMyGoQPmse5 r88hs7MkOfrgaKg+pLfytHsOhbTBIptPNMi/+1Re9XwO5etRsgVco2HGRfzJ 45g59H5YUPfQrWjYnR7/yNF+Di1ZatGdtI6GJeMHRVwac2jXkn+Vklk0bPuZ wZgmOYcu/x4RvKwdDTazPi/2/J5FfmHMPZYXcHwy57P4ZmZRLrNCuOOZaJhi uXd5tmsWvU29Ked7Ohr41cpK/Wtn0Sz//cUI6Wgo7xU79rlwFjE+/pCdfCQa 9n37K/jj3iw6emRTJ1s0GjqUW+Pb42aRbsUhukKhaLjZ2Wd5JWgWeSgaV1Xw REMPhc/yrvssuvcu6mYDWzSs69NKhd2aRXWaVYIdjNEQ9AsMuaxn0VT/7MdP NPh+2ae0z1+bRXRm3OHTv6OgpyYunNNkFol9VZVb+REFTfzP9DwvzyINB4/F LXIUSBxMZ7Y3mkVO64+zGeaiwJa2+9dXzKkB/Tock1EwbrRgOmc8i6ro6eiE hqKgpHPM0e7qLBpJkK4S742CKP6L1texvlFxW92UaY+CRwwlth12s2hfTorg mXdRIC77PCPfaRapHmz6qFkXBa0dwTtnvWeRffFqmHFlFIjNpA1Ghc2iBFkR OeuSKHiu30QOJ82iMtBZdCqIgsdTpWc+Zc2igfPB2X55UeDh9qPI+/ks2uwq 0Ym6HwUvP+tuWuJ4C16eoE1NjQL6/Z97SR2zSHliZ1VOfBRsY6Hv/jU+i6zs 0M1nEVEgZLJsnfF9FkWtOAhWBuJ4/D62ZL19DnVTdYZ1OkeBOjn3tsvJObQW 9Ud2yD4K5DLOGT7UnEPcbEcWZyyj4Gb3FZpZG1x/wnE6fwyi4IhYTHhU5hxa VlYXPCyP431Q84ABxzziY87jLzoRBaf/lLHwHptHagO/+KSORIFow8PzKZfm 0SP7Am7pvVHwWujjSmzCPLqSsp1NgR7HN1ayppBjATVPN9No9EQCw6qFRuvx RbRWJEjd2RYJ488bLKaMFpGwtweV9rtI8BFr8hP0X0R+LKJ/9Koi4biZaGF3 yyI6LhO+bpKNjyso/JwwXUI5kWfnb9pHwpjWDOcd32XUrnN/dtkyErZiRvd6 ZS2jzT3fZxyvRkKAQ0Vec90yMizJm3LVjoT00HtMvv+WUZjP5sSPC5Fwb/05 R7sgGZWq6I57no2E2Y0nU2aKZMT8eduIr0wkHMqrd9vnRUbyD42H/khGwtP3 gitnUsnI9nbpp8BDkWBzKbkksJiMGrdd7w/ljwS/QiXqY1/IaKWtqpdudyT8 4eJ5k7ZFRgJpu3oid0YCT3nrnt/YT7zE6ztjqSNh5ZdS/guCgvLXuDtYfkfA v0N+AhRdCuqtc2xL/BEBDWXMA3w2FEQV3fKejRIBYYZW44e9KNiPhVpT5iLg okTxqHA0BZkKeDZzTUUAdYIk80YGBUXPdr5NH44Azp3dioVPsL6Xijbx9kfA g+/No6cqKGjaN6DhfmcEtBw/R3nUQEHsqgMg0BoBlr96mRexP6BdR+tyGiJA tT3VhnmQgm4NhdcKv46AYaf5+h0TFHTv0WjNw5cRUNrj6Dw9S0GtDierDxRF QEEEu2k2GfuVXHzlkycRsNz0hHJqjYL208xUHHoQAbKkVuGanxSk06Hw8tk9 /D4+FvYivyko9fFDK63UCKDN63l8G/vdJ39Grm/xeL1xzYPl2O/4DZ3fpURG gIrURuovzOZHP7nLBEfAHWO+wbOYH9Ej0c8+EcDQFrOe/oeCZsceD/i6RUAM q/zjrU0KEq9kjhR0iAA7G885N+yvDomusg22EVA38J2d8TsFldkOzVpej4BR qdK6hmUK+oGUM+hNIsA/sbE5D69PjuepWoF+BMiQFZRf4vX7rbD+uqiF16vz xevPJ+ynre4F5PMR8Ej4xGx4NwXRPhgxTlKOgN1MHEcNWigoVqewZkA6AsI5 et1myyio8xDbTe+jEXDqm75WDc4PO7XXHn6xCEjtT336HfcP98rO+V3fEwEH tVcUa0Io6CnHpOLStggYYzu85a2O/X/xPDlhKxyUlvi9LU9TkOTbouxjP8KB TYFt5rsEzreb3z+PuXB403TpuRgzBb3r527Y1hUOpuG6hRXvyWh7UYDzo9Zw qAvtGSmsIiONiBnh843hcP7laaaQJ2TUJ1MeElcRDsfu+bB/CyOjqXQtFe7M cHi+ex9DKCIjUaeKteo74eBqeNNH/igZ3VDjf2yaGA7sIk8qaAVw/f+cp8sL CYdkaUa7r5vYr43DWw7fCAflBCd3m6pldOb4kmeXRTiEUqfKKD5dRhGMemIu puEQJ6JedDFjGbG+3htdeSkcAuR3Ngp6LyN+/lr1MzL4/bWtB38rLiPzNZGt aclweJAzTPkmuYwetkc/izwUDvuoSVflRHC/4G/E3MEfDjTWvFRNDMvo1Nhq hxFNOKQ3UOqZBpfQc1OZv46/w0DjAsni04clJDjsfTTqRxjsjZh+zA1LiPoT VWLVbBjI7G//s/Z0CbkZqkD3RBj4ricJp2Uvoa99kZS5z2GQU0q3vSQVz58f WbV528Nglu9zsm7IElLQ1g069i4MOHIkeUa9l1BR552SC3VhENB+Z/+08xLa q/l54nplGBRIftezs19CyW38bD4lYYCCTUXsLZcQrbq5cnJBGNgnGC3PY73z aH3oXJgXBty/U9ZmDZfQnOrsg8b7YZBnJWFipbOErrwT7xlKDQPLQD+xaxpL qP2sA/X3+DDItv+n9un8EiIaS48zRYbB5Kh9YtfZJVSi9MNiX1AYVHnuq1BR wv0TyKWc9g6D9hvWJrKKSyhV0a9JzyUMQlgbmJ7ILyH6Wvh+82YYGPesyaXI LSEveZr9YVZhkCGcirZkltBilap+5tUw2DKosxnD/ZiZbEzYS8MweFrnM3Ea c3dFx8v2S2HAb139gR3zGWm2mWm1MPD8YS9pgfllmT7XH+Uw6PqjS3cI30/0 WMY5rtP4fObLUjayuN8vHnY/Ih0GFUbHQ3hOLSHGo0L5546EwYBPXA1xegn5 PbcYuCoaBkR0Y+Qgfn+yeD69h1AY2AiTIybx+swL5mUSePB6DyWrmKgsoZ6D R2zz2XD+U+oVzqotIZV8p/Q6xjBQIqcNp+P4vdr/smWAJgyGv1r4G+H4ij3c 2CD/DgVlPQHHIBx/5tyAy0KUUBirKhVnsFhCAYKNUbJzoVBw8fvZ63ZLaCWT rvrSZCiEz9/WEHBcQn1343iDekPh9KzBkXL/JaTK030hoz0UDETqpqPCl1BV GodPybtQcGt7eaEqfgllpdwbmqgMBY3frBf24PlnF/sY46+SULjW8ddYHddj CEn4NFthKByiHKf/ULqEbOKf3lfODIU5Kev00ndL6GjkK9O8oFBIH49aHl5Z Qrl0m3E13qHAhk4Eqv9eQuxhim96XEKhyT/Z+AfeH+tBbwVorEMBt7G/14SW UZ1Pz5jlhVDg9LLO1dRdRvKniSurZ0Ih7z2PhpPZMnq1VdAfpBAKPFxWk+X2 y6jIL7g9SzIUbrYdF0sNXUbZAVI1g1yhMJgTQ3F7tYz8QxLuXJwKgcgZx/J4 7Lc/z2zuGhoOAfoWl6AMCTJyo7GJs+sPgTdDao2Zcng+C1MMDW8Ngb7y658i dcnINGLJCYpCoFjVN+9ROBkpxKhrnPANAfLuhB2Ur2RUpf6qpcEtBHSeMzZ6 rJKRNJPIWW2HEMjaU/uw9w8ZHY77der29RDwC23YQ8eJ/STh6cEn50PgpKCq EQf23wwtzocnlUPAzlYrcJcaBXHuDBJ8K4+fn6P7rE8Hz2ckI67JIyEw/Xon /3MrCtpKoqfZwxkCmZoB9s6RFOSh6xJQwBIC1pP6mkGJFLTKPvZLliEEmlf/ sGikU9BCSsWK/mYw6JY63dqdT0E2+sK3vnwPBuokCROOFxQ0xRk/67wcDCn7 ye/f43ls6I7VWMJEMAyW99w3r6cgQ8NuY4GhYFBg9J5HzRTUs1uh/1lvMNRE C8cNtFGQ1uATbfmOYPhy/eKh/R8p6EM6R3trczBYpP72FsPzpurlwPNG9cGw +UVV/csQBTXyLDbOVAdDXbKft/44BdXcbaymfhEM2ml53cbY76yomCro84NB QGLwuewiBe201SthzAmGHKf3WoD9vabj/jPWDHz9aBr9t2/4fOnpfPakYGgX HlfowH7Pev9w3u6YYHgVXueij/22apt7Fl9oMASobypF/qIgC7s3GYJ+wcBf 1GZkg+dXli66VBH3YHAy4wtYxf1A1UmtRFGHYLj4nCHpMO4HLDLTYsRtgwH+ KIRyYb9nphkPP2oeDEjB0rQI86sbB4OPGweDkaK53M//+4NuRz8Z3WDYJvxA dQ0zk2yVp/zFYDCWDXn/8P/zs6hcCZVg6LpnxrX9//NpLzicUcTxV2EiieDn Md5MuqEqEwyeV4aK1/D7VHz8bKUuGQxqu5m3AvH7msuJmGuJBYOfXBV9M14P Y469ia5wMFT7KXi04vW+pCs3NOQLhrVZk82oHxR07daWzhWOYHjPZKq9A/cb jL1nNc2Yg4GHVk75Ip7XX56KU7Ogw+sXHM7Vxv2HWW7fWZu/QbCiIae5Z4GC djAIIPuNIEj8EXvkxVd8vO/FSZf5IOhIkdU+ivO3/fS6lMdUELC5zUQKD+N+ 5gFx2Gc4CATe3xv5gvPP4NglEtIRBAbfXOjHOvDxfm7BiOYgYOns2OR9j/tH BXPeGAiCYe0fakfeUlDJjm87k0uDoJnGUGuqmoKuPGL/8+AOfl6Z8Iv6hxT0 4rPBYMPVILh3nEpwrysFPYmq4qYZCYQLU8rKDKwUJOZi66LRGQiUXr4Xwttx /2Kyu+NOfSDEvxwla1JTUOFRtxCxx4HwIXTnr4l1Mirqk1zWdAgEnhxCgn2S jCTrxs6nmwfC38eBcSPDZFTyJD5vQjcQrB8xdTcMkFGZz6KRq2wg8E9WvZ9o J6NXe580ZlAFgrpn41pUDRnJMhoKTK0GQFraF76zr7A+fKf1kpgJgGCZbW8E y8ioptniSN37AFjfHGFULCSj0yVsUQy1ATDF2zcflE9GtXfrp7SLAkBE5eaz uTwyenNLMONLcgAIXqgcOJBJRoRhx+rh8AB49rH70O8MMqpDfpoengGwR/3G 8Z93yAgdkngKNwIASvu1+FLIqJ59iHqHaQDcY0nqsyCRkfLvqKu6WgFA9ePW rp54PD/MyFbdVwoApZNlqnaxZPS26s7towcCQHkPdTRjJBmdy1Np9eQOgEWu tO+7sf41x34XadgRAEcvveW6GEpG593z/Bl/+8MBfT/GJ8Fk1Gqm80mP7A88 NS+mxYPI6IIa1YmsCX+ImyAVDwSQ0YdjxfFfe/xhhC/eodCfjNT3mM1JvvMH Pn1PgXw/MmqjZTnrXekPiXerSt774v6Q/DqrscAfDGQvcXFhbh+0/8mU6Q9/ JH9JRfmQkWYDr55Bgj+I+F+bEsHcWdj6IjvIH7jj9m2b8SajS6me2+dc/OEZ 8eNqJ+Zuf1HLY9b+oKbe2TiGWce2/42PkT/sqNnxnQtf36MdxvP2gj94RVk+ c8WsJ3/ClUXBH8x3Hs3bwNy3b6rD8Ci+fi4u8gF+HwOWJLHcvf4w+cKSzhm/ /8A6Cp1n94cfzyPBGq/PaII8epzOH6aGl/QC8fo/vc+S89vwg9XksitvAsno crlGyrt5P2Dq07QRwvH7nLm1zDriB9uon9I8DiGjKxGFapc7/UCNVrJGE/fD Q47GDx/U+8GHY7zMvBFkNHKm8rL0Yz/wcp534ooho6uHbcr90/3gTfc7h3Nx ZDTGxcXaEu0HPPclx+4kkNHEnEuTsYMf8GccLr+D68PN0OVl4nU/2LHd4gVn GhnteOv8+J2+H3RohTa/wPV1PMcp8thpP6D7cO7E4WwyCjdwuLhjux/o3Ra1 UMf1y9d0WwFt+ULF+7v9MS/wfpK6fcSd7AvcI88+T5Tg9TLd2jnZ5wstdaV7 2irJSLzxRm/VA18wV3jyNqIZ16/kjbfkVF+Qfa/GbPEBxzvLrmJ/lC/8ymMB zU4y8vOyTSc5+ALVdq9SPbz/Oo9am9id9oUfB66R6GfJyPW++Rfufh844TMj dZMR69EO8z7NVh9IF13o/oX1INPj2rvQ1z5Qq3k3N56Dgpp1zJ5QHviAWiP6 0cBPQTzbTW+2OPiAH8eX9AuSFFTrZvTdY7sP7MizvyenT0HaU4bTz7e84UcP w4nmyxQ0c8mwf4rsDQWPLLc0r2K/kTCo1Or3BqX7IYkX8Lx8fVLXVzTPG9h6 yxzGPSmIXkuLZuA0vv7ehQKauxT0k4Fhbf2INzTctP+tlEVB8w0wzb3XG1wI gd5bDyio/eSxZmNab+h9QVsZX0BByQKc0aPtXiDI5icyU0VBYYPt3n/rvODw 1KZ8ZC0FuSeF2wuVegG//VYZB/bry3QbF6/f8YIg9zjOBezXgsufWWeuesFd q/o9Ib0UtOtJ8j86bS9wB5moW1ift12/uCJ6xgvERt/HEZ/xfN5X+9FO1Ate vJqwzRijoIEE98ZoHi/s96SPQpMU1KJ2tLyQ0QsOrlB+xX/Belqbk7pE9oQa Vbplgbn/4305nGXSEx6eDvdG2D/ipdg8jvZ6gtl2QbXzSxTk9CjEyKnSE25Z BjnswP5jYXZaLanAE2yezFc0YT/X41mTK7vvCVocBYJW2K9k4qz51gI9IUmE 19loHeu7qiATl4snVN/Y8ijEfsdLNbh10soTNgYcB77g+Z6xJnHJ0NATVmD7 Mxo8f/92VRv1VPME0cMBXIzYP8lHtnVmyHvC5mbL6Q3M47PVddWHPQGKp9Ta sN92P3ApHhL0hGMjdbci8DzfaCKRu7ULry9PZUQM+/NLrmkSPw1+PsH9sQzz 467MYMUfHrDrfkj0fuznadEGLmazHtB8xFUtAHPUWVbLwM8e0LZHz6Aes8+f Zr3cNg9Yu9+6tYD5ZmWgSsMbD9huNR77F7Ops9zJqWIP3P/kGG9h1pL4doAm zwMWHITeTGJWminYvT/VA5ym1NjLMB/LsWA4F+EBvuMfq25hFjHe89PaywNW vX9ysGPm5Oibi7D3gAgrUkwefl/6jrjPT0w9wOhgfoQg5o2Icx9atTxgpD3T /f/1zin9rZlX8gDHO7UtQzgeQ5uvnjGewOcjp5U9mNtfOmZKHPCAkIhGa3Uc vzcOYvEa3B4QLeKZa4PjXSQ26X97hwdMOQ3sccb9Se7UXYeELXewFYoysMf5 Sc7UvVa87A5RW6Ydujh/YYZM2t3j7rDxQptOAufX9oPfMfa37rBaOdP8HOf/ 1vaIKqFKdzDagASHVQpyUU1ERwrdgTaJaWsfrhe/xgeaaiR3CNMWDb2J+0NS TfONAFN3ONhm2+2N6/HOz66V2Evu8Jyp9fgM7l/uyXz2vHvGHZQ15D6en8H5 K1sMfynmDr1uVulruL5rCnflLay5wWqzk/Av3K/CHO+hn7NuoPr1sbwE3h9v RfeV0A27gf4y+dTlQQrqyjtZt7fBDWaiTV4/wvtr+t6VIcN4N9gw6L7K2Y71 IfYRe9MBNyhcPbOnBO9Xjvcv7nbzuAFNXZzPuxqsPwyVe8eY3OAZs0LuCN7f +0LfH/31zRVey663s1VQkJwvWV2yzhX8NWhl83C/rli98VGh1BU4JqPMup9R 0JkNKmP1R64glHmDoCmkIE1XDlvrGFdA5zkCvXC/b3FTLvS+oSuUmxv8K8jB 8S1QZiy44Armyyyr9Nk4vrPqSa8UXKFL8QjfzUwK8rS8mvNRxBVcUodE1LFe xZmEvGaguAD7gUU1+xQKSrobe4ZrygVGTbTEtifjeh9MfS/S7wKnRxlkikk4 33pPBhVfu8ClEv9i3gTcv15s/+4a6QK3Ky2srKPxegcSfG55u0BPpUDk6Si8 H8x1tlnfdIFks8G9gnieIdwHWA0vuUBmV9CNHeH4fv8y7mgpu4CleLsdexgF UceY8J8/4QIrBt8DxUKxnmdPHJLjdoHUh6VufsFYHw49LJHa4QLfnFViaoIo KKbcWvbQljNw7k88SI95SVGsTnjZGRr0/phfC6SgS60LKnzjznCkcbtacwDu T3VftLF/dIZgTaFFecyco466TE3OsJe30+CNP563bI9/pqlwBrPNVyRNzJ++ rV37ne8MlwSSHyz6UZC8X+XXtQxniD4oH5uOOZPe5/ZyjDMUq5Vo6mD+S1JY m/FzhkQ7wa88mM33/PMZc3AGb/d1LbIv1pvHDdsGzZ1hF99s4EfM+6XCorp0 nUHu79TtRswRNao7W1Wcoa5IjKkB87zKjrR6GWfIMb92vgOzRlcbf7WYMyg9 Sd05i7nIOOFhKZ8zbCIpLVb8vF3T2uKFzM4g2S68eAaziwNHad5fJwjxnGkL w9z3s1/2/ooT+Ke79vZilgnNqEuZcoJ3/LZTkni9GSwm5+L6nMBWkXEwA/Nm ukB7WLMT7HBQjmfF8TIVmdD1r3KCiifVYyTMdc/zPrsXOsGM5688IRzvvbLW 5g6ZTjAvplpcgzmk4eCsTYITfLr4YeA6zs/0xYXb14KcQP/b8wVOnE/Vgedr Ri5O0LqPtaYXM9PiMeoLhvj9zi28ccX5d3Bfi1JWc4KNGZZIfVwf3f9e7ZSX dwJzZq6TSrh+UjkVBCQEnYDbKslAFteXnF+cE1+7I2jfvzWTFYv9gcQWwFTi CCSGOKGuOAqqf5wW+zvFEdJ1kpV34Pq90JWbP2biCDl39fan4/q+IlIxkrfo AObyqu5saVh/WkfVJJgc4HZGfpliHo4PV45gDuU2SFhvTPbgeaXCwnyNve82 vPZaZ7j1GPvP76mczczbMMxIS1PwFOf/2Nz6+6O34ePtcvlzxRSkcm/1kZ3u Lbj9vZW/CeuF+Wy5z4jMLaD6Xh/nWkdB/tLu2tp7bsFN4XsS+7Dfv+rc2JKd vgl1kdd7Appw/dP80WXwuAnS7LAh9AHPq7cYtuXftYfp7Cy9Tuz3YtWtA7wB 9sBa3mej84mCztHHPI+3sAd9TpnYLqxvAbnMl90l8Pn24uK1IxS00sdWrPLm BgiwBzPoTOH7ifSGVT24AeEpzyfysf8fcky9cjjiBpie3pBdn8Z6s4ObnvPS DdgZ2VURhOf5PkX+q18m7MBt9VaOEvb/lZjR40bv7GBk97GdZnjeZPmUvb2t wA4k0+72umL9VnURflnmYgcSd0RnI//vD2AqWtTIDl4i020RWO8DmR9du3fa Dq6bnKf3w35QlS/KFEJrBwwiXj6X8Pzf93124secLTAdSm86jOffb0oFr250 2EK9OdWzbdhfxIclLHTSbGGbZTN/MvYfVbFl2Xc++PiBrkRN7E+W7kUsp67Z QvFbNxcq7F+ZO49V7xWzhUpuq1sa2N8mrFJe32a1hXDe477DmPfX/HhTs2YD BR2sDJbYD+12Xq5nGLaBDyxsu75gfm5V06jfYAMZzx+km2D/XKnmf/fgiQ0k VYbmtmOW3hnYQo63ga2MT0dlsP++rj7bHnXFBop+/15dxfyXNb+zX8kGGOmy ZFWxX5+x2v5R5KANCHJoCf3/fT6i2r7XkcUGPDaevxzA/IG1o7/2uzVwD+XS cGL/Z7WS/LRjyBpCJ2R51THrVicNGdZbQ2v3Rxrv//sV1rWRh/nWcEeL3JOL ecjScHwlzhpq8s+kN2AWrK6aVHS1BqeqQothzBase6ZjjK2BdPqQGhlzvqX/ 10FkDWYzXSabmBeqxuf2i1qDz5uxsn+Yj7KeWXRmtoaf1OmW//c3LpaPlutW rSBF+Xz4+v+/h1TRrzB9toLATxpSc5g3WW6sXgYruHKd4t+LmbBsW3v82ApO PAiNqsIcUnVkYzXWCu6FnLuZjrmZhfQLuViBfYLJGSfMjJarW3GXrYB3tF38 /+8zWlX6fz8TVtBxLurMLszJLJVUBw9YwV3+s08HcbwGLHhp3JisgPGbv+9d zLxVvnQN3ywhQDp1xACzKcsYA+snSwi/nrrEjDnXQonRpM4SQptPdtTh/Iix 0O38EWMJPAyjMRyYb1nYsp1xtoS5mqqiVzi/JZXvORKNLCHLul/KALOcRQLP of2WIHzg9ZcwXB9+lSt8HoyWkHRy4tpuzPXMegJNKxYQ9PVD90NcX2qV3CJX 31jAeBLpcDmux8vMDySSDC2A78cv4ae4fjOv0xwdU7CA64Oi6QKYJ15ZS0ns swC2e7+USLje7a6Ln3xHuQ5bWeaDt/F+8HxVTvyKug4Dp0PSWHF/lWberHP9 tTlI9jAVMOL9l6p1Xy8sxxzMf3z9fRnvz2QFJ4MnoebwstuO/Qnev/E8fMbL F80hlX5M4+winrceDNevVl0DrSY/x2Dcb9H6h7+VC74GLQ1WZ3rx/v93WbI1 4MI1UJHxNhPFvL4rtItxyAyyudYPfcT913SQ+JjI1lUIjjw3r4j1ZMK0b9Ku 6SrMnfWcycZ6MywXMFMUexVefdAOp8bcs/JxSZ7/KjQEaGj0TOB4mXtv6Sqa wsFuRbr/55VahX3/MuhMYekb5wl2zJU8HdTjHSbA428kQhrFfti9l/GmmQl0 UilBOta3LKVWntDAK9A5zbb9M+73Mvhd+N+fvwIBHP5mbphTf+7Zu3PXFQih FFzkxEzqe7fP4JMx7OOB6Sqsl3Eljgfv5xrD7vuPFS0wR8XxSkzaGcPrc+t2 uzCH2jUdPXjMGP49pPVqwnrrs5dbprzhMmj2qQTJYfb4XX/qV/RlWHF5eGcT 95POn+wVke5luBNzuKXh/++fLzmVw/kug++JCqEEzHakOpW2KSNQCqp9eg2z 1S07NbZnRuA8HW4vg/maGruGkasRHIvcuMmO+cr+2ktZp43gCEdR2Xes/4ZU NnpfaIzgr/LvM0OYdUd2Gh1qN4QktXGhZsyaVdVXHFMN4aUv48VKzGqplmYV poZAalh4+wKzihOLxdZ+Q+CXeBRXgFlJo9JaedkAshZocwsxnxa7fiOywgDE 9Su2SjDL0DLd7vA3gFO6q/dqMR+feOnEoWoAm279nh2Yj9aauRmzGkDuzMnY /38vPJSx3StnQB/MFPPb/2Le71bmO5OtDyxvE44L4fXs1TYNlLDVB1q1nWUq mPkP04c6S+rD2h0p5IiZe3tJROWGHrjth/ZszOzTxjF/QA92y1lo9GJmradJ OBulB8FLD4qYcfwvP6csnNbXg/GfTzNVMedlDJ+X3qsHI9S0JWGYZZ3Ltx2o 0oXt8rt2sOB8hlzNMRMI0wXle5QjRpjbL8S+5tLWhUM1QTKPMZuLWLrTz+mA VpbfUw1cL4Wsl3r+luuAwvtvC48x/9iUl9wI1IHr/aebqIdxf9rLPj/LrQPp 32PGmzGXhzWavj+vDXc4JNU9cL3+dSqqbuDQxvtVpWl+9P/5RvqIG1wCgQ8S u81xfVffnM41oGhB7sr5if9/T2fuPBvFc0kT3B7SMJrieaY0mdoom1UdpjvD HVrwflO9ObQrMf8C/Ex/cd4Ez0NDZ8s+BBIXIPrIddEVzLQ/rhPXHdTAzlre nR/vZ0OjhgP7O1VBuF7nky+e53/vCVoriD8LlvZscaco+H3WjIruHTgLF/Yd qerEfKBD0i72zRk44qS/YIH9WytgfPjWsjKcmmibjsT+/WCCaJLUVILabTUj 9Vh/4tS39t3klYffUT66/Vi/POviPltonoJtajUl6tiPLY4LJl4JloPnz/zs 32CW41PevDAvA7p3Tt25h/VwX0JPsbKADMT//vmZFuslK7WV9Smdk/B6qEH4 Fubp+YhuseoTcP5CgN0xrK9dV3ki9i4fh3gSjVIi5pqPBad5hI+D8evqtnnM pOr2fIZoKfjBKliVivV6/Upt1V9vSdhAL9anMXecGd9HnjwC8VRHHx/Deu/D fmCzvVQc5vITueoxa2+et67lPQTlZX9rtmG/EJ2y734WfBBa9BLTEebf7+NP 358/AJVL49nemHtKS/JjdPbDapvNu2LMT+/2svlUi8D9UzpUU5gDgtf9bggL w3bn++f+96+nPce7S9mFYF2MNk4es0GeVz5pag/EcR5oM8e8zaXOz7GMB4ae G26FYH6hTKunFcIFNae6uR5gNmZTP3RElx3WIJLz9f/fJxqF/nGrsMLeQb3V bsxW15896//CAForXYVTmGupZC+nhG6Dkb++8iuYxZTCd+SprtdVBeVl//// ECV/5N7JM3+po5436//f32s5LETke98TNz+Vjv7v/wkM9gODPyiEdIVx5W/M u98JJDu9/k0ERGxZ/MB84mxo5uYbWtS/j2tq/v/+4+EGRUGQCQn+/iozhFmZ +tUDBLtQN0eyVTPmO8ed2swpHIho5HL8//vLvIX4j2AhbsQbJmGSjFkhZVrw 4SU+1DbrdtQFM6kpW+1toAC6ympE0cS86n24etVoL6Kf2/X4wP//35G8Q4tm RRhpfHhm9AvHW7Xw6xRH1D70L59q13vMTo1Nnvv3HkB5O54OpmJ+u+r/4Jy2 GHp5yRv2YiYzmsgYzh1Ca3+a1ydw/nn2ybXZBEkg9Xy4mfV/P6C3uhZZchRx aWqfY8LcVjGrorFfCpXc4m6pxfU0oWyYqL8ihb4JjtTbY2a8cmK/ddRx9ESN ZFaL61Ho6wOH2/on0IMq/QPmmKVddlW775VG/VWvC6gwm8Usa0ZUnURqhsZy crjeS2ueeD6Zk0NyB2oLQ/F++RkU3Pzv3Sm0sB/l0GEmzptwXX4oj94c+xIZ hvfbh17W8u1mCqg8f7XYG/cLU0vu5Bu9CD2Lifysgvvp6J15x3dfO4u6X/y9 7Yf39/NV1iuNHWfRoozt6VHcL3T3+wY7KKigyC++BxUx78406G7mPYeyx3et beJ+IU9sh4NnnyoS0qhJccH6UaPsVPDpgjpa/FvT6or1aHT/aHdYlTpiPJEf /wnPD1Tb1X9KHbyIFngpgwRm1c5956NpNZCWpU3SLtwf9F4ZnD4Fmujyjv13 2rH/ryuqMH89ooVU0neEKWPmEy49kZyJudqWu3r8//kpJmTB+xIavD5TWoL1 cv2UEEnznjZiIhjRO+z/Uc/6Hz78qI2eLneN6WLmFYir/LVdB9F0PxWcxnqs QPVr7LGnDrIVSyOzYe50Ll7dKtJB3q+TXxZhPb/2xZpe96sOeqjmGnEJc0hz z5G/+rrIuZe1JAv7AadctLJ+nC4a+6+C846n+gvjeIVKoUIUDVG/bFEpyveh ENl7JHtm7703F/daaRAlK2TvTZLKlhGy53WvUIrU7/jz/XK/53vOeZ7zfD7P 93uv7KfCcohf54JGXqsqQODT//a+vyPM+tNy344qBLrQJpUi7sDl+2gKqcHM 8bUkO8S6f43x+VZqYKYkcpsf8Yr96cwDGWrw8VnPk3WkZz5T3ZXaw2pQwZDc WLunb2phHwuPqcOnw2r1kYhVyrZDVe+qwxuxRt89v5B40l78p5s6QE9fjAji L24z20/y1ME4tWWLGfHpYa1ysQl14Lk137aN9FdP5JP91AkNYCp6vTuFOO2p OHeolAbErKXn7un31E7ZLKenBjzLc+uu39Prh1wvPuVrAAVp1qUEsUVDqo7D pAY8udOR9gZx3nl6RkZGTfhMolHZ8w/EgLCuynuacEjrbeze3wWmtyMeeGuC nVe9zt71Tnft7/4r1ISRfPXSvfHLMmd2X05rgpVSxrO9+29RaVdJM2lBKGpU pxGLWnxyWpbVAtlYYcYdxL4d4nyxvlrAn3k2/RRaXxNX+YJgsRbgtAaKRREf iOZ6OTirBRFl9ZJGiKWIqXqep7SR7qiq4RBHKNAzn5XXhp7h3S97+9tZGNbb 5K8NByxEO8iIlR3tpQ8vaANx7nmPKYpPfN/MvnwWHbBTXeh/jXjwqnatkqIO XBM4c3ZlL54/xa88LteBO400SkEoH1K1ypdFl3Tg6/X7ZwYQT1ZxvZ44owva DoG/uFA+mXnTs/wXogs/fD2fTyHOGQsb+FCpC14/70rcRfm4LLYTa7uiC6yq TG9zEDvsm6UoV30AdipdSX4on71Cy1fvXtCDBPVaPnWU//XzXDkL6nrQ2WLc 2It4n0yacXSEHjB9umeiis5L6JHwoT6yHugKaLnpofOEj9NuNmp4CN/i5Arw yH/3r33yplp/CLZ5TjUc6DwyqUoI517Sh331ZFIV4meM3G/WcPpQLZB9fwmd 36wnO4n+DwyAw0+HXh/5/wkVpTJFH0OoMNy45IHqQ/sSU/z9FENgt4oc50b9 RkHghL10mSHwK0WZjCP2KbblwYiGIGl486gEqj8sJ3Av+fSMoLj84pFd5CcO 5KoFcHkYgVTOiEfOOtIDcVb9S4lGUHTY+pgq8hdVDnmnz34yggNzr8bTUD3T 7OnA09w2BscVjgunUf3DLPF2h7WNwT4wcf0t4kv7tOUpXYxhSwYvfhfVy02B hUN/3hjD2hG+AH3kN8beF85tvTeG8tlW6nnErQZurRszxqBGXgArVH/j46j8 V1hNwCX367wRqs9elz/rLdwwAXG2xI0viI0aE0Vn1EzA7Wv7rDSq9zJaeqe+ 2ZuA8mG6qGLEV8gcP0ejTYC1taiUaU9Pwlf6v2SbAN2PESE3xP/OlRb3tZoA 1mQ30o24S/GObeeOCZheubTkgPSoYp5arp3ZFB7crNquRJzq18vZctUUfOF9 yC/EIUxPDjYomUJS3zl9IaR/NoWGs9XWpqAbkqtvhlhdmrOlPByxgI8BAfGt CfKL4lemsLD2RbRi7/2CW6VvQaMpeCzc+rTXnx+h83+Q+9UUKrQC1/b0e/21 tMjrLcSrNaF734cYEaNjzmAwgx4JW+s9P9A0OLj5XMAMbI87Bu35hRzb1L4U OTN4cfxSwZ4fwFOZFSVamEEpTq17FrF7Km8sPtgMvPpVuj4i1r++aY17YQYc O//weYilP9fKRtSagdaNiX8Be88bzIIvhwyZwUf8OqUS4pO796kCNswgmJIW t/c85E8i/Yz3MXOozY4I6kX7Mcs72uTOYw5HVZ4MhSL+1JaR5nzPHBa+0PoI Ii7Vs/KxNzEH7bQ44wG03083r+ha+5vDxu8YfzvEQbhfNyyemYNZmcyHfyh+ jy42nTSpNAdD+y83IhCr1IVv6Pebg/T1i+8OIWYjMr3VPGoBS7MCfESUL4dD JnCqly1Ak0WcSgXxGmvWI8W7FmDT0vkzH+VXo9z1/6S9LeBBBIfwnh9WfNN0 qzHZAhwb/p6PQ/k6cURe5WaJBTAYacZ+/LnnL419uJcsoMORfJEH9fs4LhLh FaUlKEodt1RE+c8a6Zl9hs0SYNfCzAqdD1EZfB+dliW0ueUM7z1f+5DNuhju ZAlOvy94RCL/rn0oe3dfrCUIqREvhqDz595ez7nRZgnG+ZW0xuh8lkmu+A0J WcEsTkmtFfULdzPdEpUVraCm5mN4JDrvfRQH8j5YWYEGjX27DOovvrecGqxN t4LlvNL9pahe8EtI86TTPQKBXQ5ulGuQI5YxZLn8CCZOWGJSfaj/SuVdnaKy hkNzqidLelC9+FN54MEFa2Dha+Vk7SbDXG0Xn4K2NUR7Hzow8xHlp+ifYMF2 axjX+/ta+R0ZngtrXdnOsIGjT+XPTlaSgSd5Wsq53gYuZpyxu1KB/MgP2wfE YRso03qlG1iG8rUsJGzimC0I9cxd/68Y1berJWMtvrYQGMWsFJJHBoIAbWS0 jh0IOJfcGkxF/ipsy5HH2Q4kTveSbJ4jvzExpfsRZweUPQFy1M/QeY6p4D3a ZAfJPyg2lFOQX1o26In6zx7KDj32Yk9A/cyd+9Xc4vbARcj4M0cgQ/qTay87 deyB5ezw7t77FAcZapcjMfaQVRGipx1LhuNZJcxRG/YwmdHgvi8K+W0/xX1J Bx2g7SHl7G4E+nxe66YpgwPQvs9yp0A8vL9wnJLPAUwxmaHLYSgf+Dj6BkQc 4Ppk2f57oah/10lpz5R2gCIaveP2IWj/i4LeSho6QNZ8WNRoENL/sa1XjLYO ICXJLXcO8fHDtimzng7AEszx1DoQ+eGr07iyMAcIE/iY1hJABg8DrcCQBAf4 r/CsPwdi3uhPrurpDshXVBnE+u89n5J4dLHAASRd+k0oECdOV+hvVjsAuzdX QZAfGe7R8aq1tTvA98GjejSIt0Uy7iX2O8DcCBaX7kuGQjOm26aTDmCkQImK GuoPCdFXrq2i+Z9f+7Hog+JVv+8S5bYDbMxxGKQi7lx0PT1w0BFu2NNV6SH2 Y1yhzWRwhLANE+bLiIXEDQ+4sDlCX6lW/B9vMsxbD/68y+cId+h4b48jfvr4 /gqDqCOMnon/7wNixdbGbzPSjvCyw8ioCfEB8rWBUjVHCP5Ysr33fqaCJa8j 2NARIi42/+1B/Ej6fL2arSNsBuy4LyM+55RYzOGF7vd8zu4Yun9fKnXWRpgj /Mq6vQyIwz74PW1NcAR6eEPy3nuf9GMjNiHdEXqvMPm3IiaxWQWbFDjC5Qzt 50xo/S/lJ9yv1jiC9paxlCtiTQ81G4r3jqDcyOr+DfGRzA7D/n5HEBF059XY ex/TLabxatIRSH6a+l8Q/3eZE7u77QhrHadO7KB4jKqmCjEccoIfnLGeaSh+ sX70l2cYnIB4tZBPAcX75+CfY8F8TuA6dkPwE8qHvP1OlGqiThB/MErreTCq z3wLv9jvOcFa5W13d5RP70J6p1oMnQA/8EhEEeXfGdOYL9l2TkBZ/0/bIJwM LndlP+J8nEA2Djfgg/KV/UBzmWaKEzQ3VvKMofz28y8KX+52Asei6A//ofMw qG/j0z3uBFuOXfJJ6LzwYpyOZStOMOVs5E6HztPonxe6foecof/m+aLzychf e8Xx0YMzKIecjC1H5zNGR459S94ZznnbYo5pqP7fPMQ8pusMdMnE/66nI/3e 8tuX5eYMK5beVwdeof12sesXKXSG01c+vTF9g/yMvYKn0VkXOHV4UcWplgy7 itR20jwucOafkHtgPdJP/nfGPCIuwJBbsy++EeXH6m35H+ou8HL+KJS3ov15 xHs+EucC/2WJ//uB6lW57CKD3VMXGJWpWt7fRQYarszDajku4PF2iPYoqnc1 C6zrZ9pcQP8G50f6AZTfZkffFe24wAfmmeeLyO/ZSr6vTqJ2hZaAtA9d4+g8 cgQXejG7gpxRY1UB8nNO09uPJa+6wmD0sydqqN5+aK7AcUm4wiVesuVp1H+x ZTgF0im5gjTvVvkgqs9dBsuPhh+5QtllujAB1K9dgiyDeg9XYNEkLH5cQX7s nLH6yzBXeKxwIEIP1X/u8RExm5euYOJ1VVIb6UVgXZKQSpErqKgQpFuQngw/ U7ks3OAKfm1uKueQ3oTrfji+b9QVhmUydPKQPnWWX7P/Ne8K0Ob04h3SL7oT 6Z/XNlxBq3pyoQ/pm4rNUd6lfW5woGryfS/Sv8T3blFTtG7gtTY32Iz0cZh9 enGExQ0u3mTMe4n0k9VP4V7fZTdQ1BeZcN7rj0eqXndecwMuiYN015H+vrx2 kbJVwg1a5hiG5hDPxcUZ1yq6gYDlsZHQvef5K9tNpQ/cwEe6oZwR6b+NtPn5 fEs36Hxz9cTe+5a3Gb2+ma5u8Firg7CLeP3P7bHnQW6w6KgwqYn8hbB2jmhS nBvwPGXMSUXsWcrwJOa5G3xeuPS4d+/5CJ3/VmiuG8S8uaq/jnjfo2UNvwo0 P+rKoj1/dPedRplbqxt461+R2nu+EsbWTG/f4wZHJfcPTiDu9OZ1tBh3Azx1 1ZkixLRDj7sNlt1gQpxmbO/7H8pCFPzaW27QH7c+uOd3EmPscMqU7pAnW9GT jeY7tDiyLHPCHQTzWZMvIWaRlJKVOOcOadrmGzFo/fovirJFeNyBe9ewehLt T8Y260Ghm+5QjSXWnUU8qxFuyi3lDlWWXIOSaH85i9db2FXdwT/oyjcNtP/W NPoXWA3cwfCtW40yis96y7WJo57uwD9E60GB4nn9XPptyjB3aK1c4atF8ffw PPrsT7w71Ngb6Okhf/JPYFprNd8dFhTEtnRR/tyJVqiYq3aH0BYL7SrkP8Lm qxgn2t0hKwPH+g/lH01qXG/XpDtQD5hOyqB8Vf61LfB+1R1oM6/8lkN+JEHN PLZx2x1Ke+HlTZTfLEfE5IoYPYAHq6LoniLDZfflNoKMBxR4msdvoH7uUZ8G R5SGB/BVNT6XHkR6w9ccGGTsAeX7v1uEID9ybfYx5uzjAbs0GXzNn9D8VKSq 1Is8YOkW8vNNqH/KL2JSqPeAnGPOUlt1qJ8/dMZVqtMDRCyrihOryaDUsC4o POsBH/XyOVJKkL7ypL9hPuUJ1u4P8Z9QvXF+tPq666InrFWnrVGgehSVK5oe KugJ/76vy/Gi+lV9eTBx474nTFG+6FRJRPXg4hG/bl9PuJ9DGbCL6m/PGRfl 8BlPCDz2LULRCOUTncyPn4Ve8OD64W/HTqH+UyGJXFDrBROjLwL9GFB9wE0v mXZ4wSFrzfjvdMh/HPGd6JvyguG1I58WqJCfPFjyvpDRG550Xb3HuUkCBul/ zWYXvMHPp+jvZzIJuEPl687we8PnbN9G3xUS6FAsFEXd8wZ+WLn4d5oEFf9Y n5p7eYMzxc6HpD4SfMasEs+GewPfRBLLiy4SzPpWxA4keANz/RKxshON/0c5 +E6BN9hsd9SxtJLA4VeozblJb0jspxGpLCNB+I1+80GiN/BcIfQoFpMgzY3N CPfbG6K/7afeKUDjb9ZobNP7wPkPdu0J2Wh+38nYFykfGLjA1PflGbrfTLDI SzUfmPkrKrKcgq7/wnzNzsgHaNd/6rAmo/vXAddBXx9QyPpoN4InQVdhP0df lA90lSq+sYglQUSGxbm0FB8YCz8oxIQjwZ+wOAbhMh/o26z1+RKO1uvJQXeg xQc4Ds6YLIWi+dtUHu7q9oHmNwpfz4Wg+RjIUTwd9wHLK2sW7kEkmFP5tmu2 4gMqMnciNwJIkC7p/Evwtw80pdhVJ/iTQPfGoY3dg77w9M9vG20/EjByP1v9 wOgLhs1V9Hd80fzOCCwmsftCs0Img4oPmt+x1mmjK77AgavvC/UmwZ0DWuN8 mC80XTxaMOmF5ru5PPRbzheO1lz/bYS4csGv752OL/zcSj90BLHTKP1nggUa z1ucfcSTBLyfs94/dPUFPtpHuG7E842iLVzBvpCyXBe0iji9pKvuB94X1FnW RK+i63VfG1c2p/lCF8vmTDrikyk/i2PyfYH1uMNrYTSfnqiofJ0aX5CJWn+x iTjK91z2pQ5fsGh+SxxF85d0KMn4PugLb38Ypi6h9f01ln5eP+MLnxgl6tjQ flRpjCZHfveFssc9cgFov5xl7Aga/3whd6dY+jDaT/5bB3AXaP3gy+HaF1XB JFjkSw5bZfGDAB68BAHF4yUbd2A1px8YUH+gi0fx0mNo8A4V9gO7/MqpmkgS MB1UdVOR9AOpfGHcURTf3l9zDmdV/cAWVzwUjOIvPUFrXm7rB9LyB+WXE0iw rzfDMNDbD5LWro0Nofypab3+QCHSD1qvd31deUICgdyHynOZfuAwey8pNJ0E p1wKRE+O+QFFgfKU01sS9JlLXJ9a8oPpRw9Yw0tJgNMZFCjY8oOroXZ59ZUk 2A+7F6UY/KGDn40qrokEy9QKx1zv+4OcAlmooJ8EmX8mqSW0/eEQW8i3hmES 6JNdKGnN/YFlyVaXOE6C/oHnvzMD/UEgebU6eZEEdS+IMwNV/vBXp27yyD8S GNNdkSl75w8nUr1TPSjJQO3rnJ/Q5w/yIVzvflIjP6m77aJK9Ac3Vk1GtpOo Xh+hpFg8FgAaSq6Kh3jJQP/uRKLZ3QCoLxGdP/mADGY+V6UHZQMgonF9fceQ DFVXNX5JKgdAqYY8TJiTweBlit7FhwGQp5NZQnAiQ77/+UszbgGQkblcERmJ /L8oX4VhXgCMObMO6aN+7Ol3RcueogDY/pgZqYTqJynHgUW8MgBo7+eLcTQg fWMu8zvfFgBC0/9O274nw2LX4JW4zgDQN5nb+Yb81a2wrem/PQGw9kdeTQD5 qelN0XsT4wHQvqazoDeM9Chf77fCbACI/q4j3th7Hmzi96Z+OQAkeKW2F5F/ GmNJf8j3PQBeXafwtUP+SaCv+VjqVgDU2sTMtyM9CYqcaab5GwA+pc4Fa0tk +CJO5eJDGQgS220Ky0Tkl97KDD84EQhMSY+57q2Todv8UdRH5kBQr0/3zUZ6 x34Od/vWuUCQPS803ov8j9tgASnvYiDYMzEstiG/8wHXnc7CEwilq53S/khf z0h+V40SDASTw7ff/EP667BDT7V9IxDefmPvlUT63VpyrdIKC4TUzHI/BaTv TI80rUYkAyHgEEPoKeQHrC54sMrKBcIjs8GmzD0/Mvzkc5VKIIgVFLF8R3wc X+vPqR0IXd9rwvfe15jcGxdM0Ufr8eY6svf+peLv35lDZoHQUJxdLL/3/KeC LdndOhBs9DefxaH7PbS9I7PgGAhbkVd/7PmJooum25oegXBY1/XX3vOuweu5 vCr+gTC6cU03Ca1nW5qkLxcWCN6zOyl4tN5z2lcJUjGB4Bbx7dcNtB93rTxa ITEQxp+UD0Qh/2jpVf9D5FkguIx+S4tAfhMXfYDz2stAoLPMn7qC/EDx83u6 /LloPydmIHgvHgU4HGdRIMgdZXb1R353p6G3gb0yEHLPL2tcQvrP1sP0/UxD IMDr2h4XFP9H6+kaJz4FwvnPH7uOI72Po5gPP9ofCDfXcoseIr0vY+SpoRoN hLxa3mX1duT/hcvPbS8EwqEUOUlJlJ/sMtvKm6RACCyIfSyG9F1aB4JJPwKh 6Ulr9kweGfDeHxamKYIgPPtMhMgz5P9xdCzjR4Lgt0KW/ko86l9S1eSHTgRB O4XJXwXU/1xsGi/6eD4I/iM2tXB7kEG2l33m3X9BIBJNXZttRwa7aYuTTXxB 4B7DxfHVlAyVlOueZbeCYLWHfctamQz3ZQ/eTdUKgnxpnnyri2Sw15VzfayP 2GvJ6TPyA4nW+GyCWRCovfqrs0VDhokYFpow5yA4SHq7koX03rGPf9AuLgj4 zeSKappJkPJAy0L8fRAsdQccZNBA+mWbEz0jHAwjPn1ePq6rsE/snZOFWDB4 OSjS7ViuAgvNtM7K3WDoDsHzPNFbBeU8Vs4NZfR5JdUVMclVqJuPbTtgHQwu 9prltidXYaj8zZswx2DQOL+1yHtkFdZDOuKPeARDVFfr7Ll/RODkOGBEHxoM wRQE7cwlIiQauO5eeBEMzG/2ezk3E+Etf/zs69fBcPh7quWhKiJ07hZ+5MoP hg56keRvhUTY93zxiWB1MHRe+NlmmkoEVmuqwPLGYCC1NlefTCKCsCi7pUh7 MCTjwgboY4hgM/xAWKI/GBLyWbZ++RJR3DzOvhsJhrsW4y/n3Ijw0i2JUnYy GMykbtZdciBCvVTJyqf5YKhkqN+usSLCMGN3n/JqMKhQsxzNNiHCxsxK9cBG MDjfn45deUgEutLDGdrbwRCpaXYmSpsIkip37A0PhcCJwzwuXxWJYMBmoDlL GwKDNoNXCPeJ4EX2FrNkDIHCtBdfs6SJkNSQcpHIEgLreMPus3u/r40pP+pw IQT8/qrpbgER+cy+9Y3LIWBQ/K/+mhgR5nnII+78iHX7+YdEibB/52jzzrUQ +FX/o//bTSKc6eTM8b8VAtWdK+1KN4hw44lUHMWdENg212PgFCaCqqWxW7gM +nzkxwqr60SwveH/8KhSCLy9fTL9JOKIg88l4zRCwGbT4C0v4leDVTwMeiHg yO9X/hZxQ+Yg/WPjEIjSKXR+gcYbcV7/zWIVAnR3eZ79QffbvHNsKs0+BFa+ lnx6L0KEY/S8HexuIbDVKpCy/zYRuKdk3mb5hMBvods+eRgRpIrMkrmDQ4Bc qz/XIkEEQ/8g38LIEMCN/eWTkyKCt+ILUyF8CFx8p5V6V5YIyWfr5CqSQ2Dq vYlFvgIRionDQqKpIVBb3/cmVJUIn2p/nG54FQKqDimu3VpEWIii338nLwRk WE1qIlG8DugKLL4rCoFgmTydMhTPm78sKz7Xo/36wlqq40gEtfehqSptISDx Xqyy34MIdskvQwY7Q6D0jXlOXQDaj2tjquNDIXCzn6ZrmECEnB9L4eITIaC0 eUDp61Mi5Fds1b2aDYHoDy4hUplEqLjJcPnR9xB4X9FFpbCXz7fv7/w8EgrN 04xDVHNE6N7VuqJ7IhTcaaw4L34nwkCDmVk9cyi4uJ848WKXiPrCwO7gi6HQ Gni+4CUzOk+SVa+OY6Ew8PYRZ4bSKmxRtQ87S4bCl9vaImb6q/CnvZ926H4o ZB5foHeyXYWDsmT3VK1QeHv+9U0d3CqcVvhPntsxFC69BNXfn1ZBXCNx825m KJyQlSvqQPVAiuklV3ZeKMjOUbndsCDB/aG3+keKQ4H5VOPDLA8SqOt87Oip D4WgsNkRa+THLR8eSH04hMYz+2oy8Y0EtueO9zWNhwKQzjinrCE/+u3soYuz odD+6NmbM/uRnhqJOC6vhUKUnMlzswuoPps5SLkfCQMXj7+tbPqonv3n5zV6 PAy06Z/4qtuQIWUh+q0YcxiYK1k8YfBC/b9V9mnKi2FAbZh7gwH1T9nc5YoW 3GHwqlJF+S7qt/JXWoI7r4TBy917+yfeIL2znVjFi4WBlZ/FY6FmMtTyE9k3 74bB3dQnD8Y6ydBE/q2ldT8M3i9eCOzpJ8O7okMxNcphsOopKXoI6Umn48mW s1phIO+QMeGB/EO3EMdWwMMwwM2pfD+7vPd91Su8syZhwFdHcZlM3nv+jBnd exQGHxwSbeaQP5hwlU/OcwgDmYV9q7+RPpbhfeVS3MNA9DTlAUOkp9FvCveF +YWB9e5kY/7e71Xbv5U7h4ZByaPup8NIn29OHbc2woWB+7eBgLG974P+kWBT SkD3tx6eLkafn2NyHrz9NAzCK3XrVdF4dYKZUdwZYbDdpJdevfd7DflBOJUT Bk9nGCun9vTX4uAPqrdov8o2u9uR3kLQjbyN8jDAxpyMzZAfYkq1NJiqCwOV ud6kmnEyECufMHa3hoGCL590G9qflr7OD3WdYSD28wV1YAeKz+qOX15vGPxo nb66Vov07DDftZThMOD5UTJyopAMUhz6S6HfwiC992T/fBryP1hcmvN8GOiI k+ocYsmwrt2kZrQaBp82A34X+5AhLZa94fYOisdC9ScLDTK45Ko5cx8Ih5Rp yj+zQAa5thDOU9ThQHD7k8fNRYZfv+fjN5jCIcojYYzzF+qnGE/JTJ0Nh8MW Zz+TkX9+LSC723UxHJ6PAu3zFhKomr2xyBMKh87CjYSOCBLk99jfNlIMh/ey 2t2x1CQIWkn/rqgRDqEGjREpC6ugc7Av67ZeOGjfnG4ab0Pn6fa1E6cehcMt dmUWRd9VMMz+NdcVGg6k8wwNYgtEYPQLjLtdj8ZfOdUW+2YFllNKJLnbwkF2 9N1wefAKNJfO/Gb+GA7xMtmkzQcrYLckZboxHA7/BGPN1mhWoEP9iEjeZjjQ cDh9lHRahjT7W6THO+Ggfm+fX5L8MrhG2bwKPRABP86oehpfXgb2pi5ao+MR cJ3kqZA2sQTePAnTzLwRUMZ8WaBDfQlkKJ/LxwlFgGvO8wJF4SVgHM+sOCgS AWaLxs0Rp5agMLYi6odUBNxvHdm49m0RvCwaN23kI4BA0ShS3roI98Q79GdV I0COO8mcKncRJr+PCPUbRMB89LlaAbdFyO+cfn7fPAI8q6aeMOkvguerlYMt NhFgpGbfOy+9CPQau6NFnhGgfy/w8APWRZjgOyjFGRABvwf+xh05tAhvDh57 +yIsAnJqfEJqNhZAsootODYhAjiHj7kJ9izAcQLXKtXTCChhPs9A0bQA41ZC Wr7pEZB+189ouWgB8u7cat7MioDKJHUv4ssF1OdI8tgURIB8rbMpXfIC3N2U T5opjYD2BWcmjSg03meNf7o1EaBx64rHO/8FGHutb9XXFAFJBafMTN0WINfP ol/2fQQ06IoWCNuh8bQcxJo/R0D+DCOzhMUC3LnimX1zIALCg6wNI4wW4Bh1 0Imi0QjY960HTuz9P6ipKO/LUxHwn/J/ZpM6C2hdCXNpCxGgE2Puta21AK4J z5WYSGg80iKHKeI7Nq+rYzYjYJTbYR+79gLQSRVyUO1EAK8Mfe5N3QUYPVsZ 47M/EnRfiBflo/GzfzZubRyKhCXn/zKCjBfApbvDyJouEpLsuP42WC6AeE7v x2nGSHjGNYiZOywAbeDodV3WSDhOv/nZxxONpzPzovdCJOQuUh48FLIAWUJE alnOSNgIteWnxi+A89Efzk38keBJ0+AWnorGm90dv3E9EnCsk99D8xeApv6g zNtbkdBTsYs/XL8AI0nHSv67EwmcVqpnGLrReHanzqTJRIJ56zxP7vQCON27 EHZSKRLWTi6d79paAGDjXsNpRIIw78rJULpFGO691eZtHAmmW1w/SsUXITNP kn/DMhLOJOs8uqK3CI7BCimP7CPhb875iXuei3DkuoGNjk8kSGuFJ8hVLcIQ reWXnqBIkNBaELo5iq6fdxCXiYyEozyHTZp2F0EsJYjxRnIkVH2KiX8muwRH HKP9Cp+j+Vsx8S46LsEX2cTFS68iwVGUTaX12RLqx17XMRZFQnSD6IWjm0vw Uv+D6fqHSCgGTKyvfBnECT8UN3siQWqrjJ20ugwTrRdEfg5FAse5DAGryyvA wuVFuz0XCdyEUuxQ2gokbHBX7D8QBcndyj1tyJ8K/aeVTkEdBW82Xi/2DRCh Rzs4iup4FEj6hGRPMawCTcNXfepzUUA9Sp/5Hb8KIRG4QydEo6DXytjuhh8J 2GurvtNLRIEpddFYdxkJmlZnvzLKRIG2RGdV/SIJ9NlOtDMpRUH0088xyafJ 8EdVrOiUZhTUNgWeWJVG/Xio1VOWh1Hw2cP2pKoD0peqpJAzplEw9UH2hUYS 6reWm+3OWUdBYATzpYhyMrieJWmzOUWBEQ0T0Rv134zKLHfZPaPgQMT+0HbU j5UESfNdDIgC53wwOPCDDMrlTsz/hUdBqbaldQ/qH0kLafs5Y6PghvVI6wjS LxzLxxWupCi4uC6v3Lv3/5UUtgZ5nkdBMeVBbVcSGTr8OZr4XkUB38GlLfwo GcxLlPIE8qJAd83YbreBDJRz3omCxVEQVZMj+Ar1Xy+Zc/yuVkWBTahluxda j/j9AcvrjVFAqassHyOG9Ndnn9qN9ij4/TendvPAXj/PKybyOQqWl3k+f20i Acu09uVbA1FQP6ga5+tOgirG0BNiX6PAwfHX64uXSaB1r3gHm0Y8sh/j7lmF n57jc+JLUSDkeK9m02kVEvOpe+6soes7xf77eWwVek4YZ0r/jQJapYHSJOTP ZcboFRRZooHbn0xhZrQM83RwQ/lCNGj8uSBbPLsEIRLWF1Q5o6F4i/wwynwJ mrNaf2gIR0N32s+3fy0WQdTRJe2hajSohbOIK9jPw/Cr9AgDnWgwGPXM9t6c A7cvn5yMDKMh4Ft3WoX3HJTcunTPzC4aHI9Tp3gSZoHn4BeyTVQ0uN9U10yc nIYy7o3LioRo0PE78xLvNw23lY4bCqREw0Y9Uzc12zTIp9zv+f46GsJq1/ze 207BQJ3F4f78aIh0xPHysUyB3lSIeFlpNKTkDzKrdU6CDXdjkVtzNJx4KhBN KTwJm4pji1od0SjfDyfenvkGPs6/2US6o8HqCF6Ex/gbUKYw6bB8iYbqxdre icUJwNVdJeyMRUPSpueyofsEME4pfxibiYYW9mNZtbQT8JzKbn/DcjRkzKqH bb8Zh4vc0SIvvkdD0NHDN3hUxyFfMccx4BcaX+60pv6+cbjm/C7X6F80SMkx QU7FGNQ9np66cxAHQd+6Ri64joFk3b/TF2lxIKgd4bB0aww+TZ5RpWLEwZej +XiOo2OgTiUaNc+Cg8x/jVs7019hjEur5f0FHBQP/yBktX4FU0WX7RxOHNDb NcYYFnyFVSeCUJQADpzX9SIc07+C2+PCR9bCOIgIxw3xpn6Fv7UfX8qL4QAT lt1af/UVwiYXR/kk0fWeaueuln8FOqqDDMfkcHBst2Cfbe9XSObikFtTwQH3 mHOb0O+vcE5RPLhXGweBhWsCPHxjkOX0sLbEAAfKFEfpGe3GgP+x10aCOQ5Y nY+vtNWNQUXtYx5XWxzk/uDrF2QZB2yyzETTBQdZ/aVP7MLHoZ2y79kNbxyM WW8eK6GaAEUucv+pIBwMHcgx10megC8KNDTbETiwuDlstyL6DfSduCS/xuHg 5iK/G+uPbzCfLO1Tl4zuTzWaaWYyCfa1JmWpqTjwtIkdoBqZhF/fAoh+mTgw 3HalidGbggDKtIuGb3DgFfIA4yNPwWGuWj2JEhzMneyguxQ/DXiF4UT2ahz8 VrttWCY9A6ecfnyiaMLBFgNFIDXdLKQn01PNtePgRkpACcfSLHDWCoi1f8bB tSadt1nDc1D0Td41ewAHtvfk6p6MzcNNykcFEV9xsHxCiZlmcwGaOMPnrKZx 0Mg69y/lDPJDCpln5ZZwkBpfUNahsgw9js0avGs4uL7m+FENtwLayRMxtFs4 oLN+p67fTITJmp13pF0cRLfV2YxOrYLlt1N/uylj4N8+IJuMkmCNQli4+GgM vCm69o4S9SMenGp28fQxcG31cI7iTzLsU3DIcj6N/k75xZGM+oUIx5gJdbYY +CLIPC1lTIbjyXlMwpdjIECE70u5FglSat4rMvPHgL8awzVapA9s32bDfl2L ATL3yLMa4jLkUBxoHLkVAwLhHecnGxdBkPP8Vs2dGFjw/9GUbzcPRUcYZy/J xgCDyGh3N8wC/+rhXrxSDNyVLQ95jM53fvdu/Y5GDLQNV5vXnp8E7pL1PHO9 GPjZWGY8iBuDnMSFx73GMeA61N6iIjQC/7mPhdy2igFSrpTNvOAXyNTpdcy2 jwGHvNTXjRH9wH67XZ/eLQauH3N4zCrYC+nnauV8fWLgYZ0hrcW9Lji3v+jm YlAMfFttWLYu7oTnM5mX1CJj4Ak1ZeZn/HtgbX9C3xAXA8xvVGK2v7TB05zY f5zJMSB4XTgh260FTkUHExOexwBNxJ2NTZMmSLb1GPn7MgYOzjWpjHPWIz2y bbfKjYHP6/wv13arIV7IuHTgbQy8fP8t+eGNSjh+UisdKmJgaPj3dPT7Mojd kovJq4uB5hhRq08vS4B2VNzrZGsMNPqy6Z1qLEL16LpFwIcYOL/D/jT/ciEc ecGtvtIdA0l0P9vkrr6BiMDzEppfYoC78LObaWIOHDRl5G8eiwE2UsKxk+JZ ECJNzco7EwOOM8SUfXyZcIDr76HHSzHwnjnuxkm1lxBwdGNz/1oMnC17IP/g TTr8W12YsvmJ1pPH+vuxQRr49Yx1Df2JgQeBn3n0Kp7Bn5Le2jsUsXCAeipj TeUJeCW15xRQx4Lb6djbDtyP4Zd7bdKp47HwMTLv8a+bSeCmWxQUzBQLtsHH PoS6J8Dm7df2pDOxcDxkIL5/kgBO55/q6XDEgs2sNe9dBzx83x8n28YVC5Sd yQORd2PBYTZYWOBKLAhbkJSjUB0mtXtwPBWOhScyfms3aiLBJtf2OJVYLCgS zkr9bQ6H5WjjXXt0nZSDryzxRyhY2mktj8rGQlK5WukLlRCYV5YfklKOhahm G46rvUFgelWirUgzFshroU38joEwc1K4mPVhLHR/nJzz4g8A41/caWEmsXAm eJk7l8YPJkfPR3+3ioVM4tn5MKI3jL2gNnvvFgvyaaR7QTweoBv0V0XINxao Ghq8mYLdYNh0A0sNjoWpDTrR3B0X0Ly3yHM4Khb+650O0Yx3hkGu8VPO+Fho Fi+fCJJ0AnWaPqqJ5FiQmbC16j/mCH2k9nWZ1FiI3X69qTBrD12lRZ/O5cWC 6ZOc76mL1iCf/Lo6sgjtb/6Z2WcXHkGnx9OszYpYcOcTp7zpbQkyD+ISDOpj 4flpS7X+dXN4LxYS0NkaC19VDBePhJmBNJun7fXOWBCUurNbLGQKbQfsdNN7 YsHPVD/t009jaHqvdc1tHMWn6++GZIMhHKd0yLCejYXos0qBZmoGYCgeQWe0 Egv9ef2vOFUfQpFPurfmeizoF30/nub6AP5VVS3K/Y6FlmCplpEaHVD80aMh sS8OfNKlawTPa0Oa4FKL8KE4YD31NfFGuiZgeadTL5yMA4OBB/HPyGoQOy94 hPlMHGyNzGNMNaowwX7fnYYjDsx9h/6zf6IC/AbGs/u544BrW3CNCacMvs+8 VLauxIEc3z0n7IISfBqKbyDeiAP6sWMi9nIKcIbxDc80Fgezf713NBLloA73 leqzfBxw6os24z1lgObDhlOLWhyUEunqt07cAz0qmslK3Tg4xlVx9mqzFORL XFQoMIqD/WW/tXJDJWHH93bNS8s4oCw/7Dz58C7cr1G/nGIfB29O5Bp5y9yB pz9tEmPc4gBn3U64ISkBovapdh4hcfBu81jj/kEMot6Uf7WNjoOXO7iFzUti MLrwWcYkPg7mq3o9BvG3gPvifLn2kzggZRjgiQyi4GX4l10xPQ42hzpYXxXc hM7nTPi72XHQlLml4a93A1hG+HdvFsbBrQNmHuznhaFaxWCIoy4O3OyzxupG r8LhWHfJ061xICqJc7XuFQLtzrhius44oLrudEd+SBB+3WmK/j0UB3MCTj9m aa6AjP/wL9JEHNhk3DD86MoPKbVrZrNzcTD0+U6L0hIv3Lx2Qbx7Iw6kJTap b57ghggHkYK27TgYe2VwnKKVE2y+cNKO78PDFe+QXtbwy1BHL+HVdwgPuTxn /yxIXILZK5+vKBzFA51ztXe68EWgUdJZeE+HBwP2T2aFIhzwINpRvf4kHoyV jDd8LS5AUO7ukZun8bAm1xdSg2eDvPeRzSVn8HBvsPlYYNR52KZ4yZ/DgYcK 6uamW8/OADs7/xz7ZTyo/hCxIIizwn3xmmep3HjIbneSeLd1Gp769B1OEMRD iXnwp8HHzNDyVL+R9joe+KiexX3zY4LlqmXXiJt4wAYuFJ53OQmiPw7M+AIe yL+C/ATCGMCYIe7Jrzto/J7ER/EZ9BAlyKrsLI2HtA82BcodJ2DE9mq9pQIe WEhGHa7Xj8OfRzyKOcp4uP83j66c9hics+T4tqCGh37+Q6kOTbRgasyw30IX Dxkm5zvTVY9CuMHR+KyHeIh7dx7LuHIE8vQoOOYN8fBunlI0j5Ua1jQ3JM0s 8HAm8fKOOtMhYFBfGcx8hIebS5k3Pl48CMIqM+aztmi9lX0b38WowEeuP8LE BQ/0ZeP9crEU8ELm4+lX7njw6WQi4doOQItUa960Fx7YbrC/e0JxAA6Ll34y CsQD4wnfWuen+4BH7M3DjBA8VJ9/IPB7+h+mKPqKNBmOh8T+Bxz4F3+xxGsJ xw1j8SB7arQgU+IPVikYnfGCgIf5+NLe6Us72Ch/sNC3RDx0ZOub/Me0jbFx OavrP8PDtduTcvGnfmF3/7OeS03Dw6PanPZyri3MnMPEbTwD7c/udbkByZ9Y /lm1FL0c9PeGv123Hm9iN+mvjumW4+HfblKmXcZ37MExHtunVXg4WOpV/Pvn GuZHw/F3pBYPl3apZF3U1rC2gwxsOi14uMwi8JxanIQtUBwtTnmHh+iCaWbG 86vYkf0Ud4Y78JA35yNYQ03ElHfWTbS68aDfKvt5/N8S5vxreTO5D61/ro7L 5sgSlvxjOvTLIB6GPKXvVZ5bxMbIfdkaY3gI2slI+2Y8j1nOlqyoLeFBPDut 4K/iDBY9leeTQMRDCsfQsYHn01jhxEvafjKa74n2qrjvU9jmcLyA6k88cFSr Eh4XTmLMX6KaCL/x0L5b90yXaRIT7Q9S6f2DB1fVC6XTh75hAZ+dnJUpCHBW tM1S6dsY9qrzESX+IAHWfRrTc0e/Yu3vjZO6qRGLKzZMfhvFaFpUKxWPE0Cd Us5f+eAI9rhCaEf+LAG+YI6bx6oHsUJejqs+bASYFn33q/7PANb+ksH6DQcB Nqc0xyXuDWA/YzdHqbkJsG9oiKuB3IfRUc3Ri/AR4OcJKrKwQh/2n/fgfcsr BEigCT4RVtSLaVpU1LQLE8D3QOTJtvAezG48a/2HCAF2B7wFY392Y2Fqj7kv iREgLOEIFWGhC6sAj6fBdwnwyIlRhWb+E8Z0StRLXJkAt5JfGV2W+4Dxx3KX 2KsR4PRFCxpJjw5MmpJ1OU2TAA0zdZ7V+e8xt7UdnV09ApzU0NV5wt2OxZoT CbyGBKiwmD0U4PwOyxob+/DAhADMstFllS1t2JeOepEaKwLcy1Jj5HduxUhY oeOSDQGy538m/+lvwQ6Wp+WeciDAjy9c3rdEWzDhDP/T7m4EyAqSU5RgasaS PCV+Xw0mwP0S9txCugYsnywoaBJGAK/xtZjDZ+uxNjN2q/hIApid3lfuc7UO 21ShGFmLI4AbKW8lxr0Go+nYOM6WQAA2N2faF5nV2EVsVkYpmQAdTMZ3S4ar MHXud1UFzwmwetuHf0a9ErNJL18be0GADHdFcsTzCiyEKYuT5hUB6cnOC/Hl cqzsQHjKo1wCdLX96Kd9XIYxfpXxuFxBgOKjJj2ZV0owXhWRIs1qArzJbrqq /KoYk3zPtRhah8Y/SX06lqUYcyk9oj3bQoAXBQ05F5iKMBzXThxDOwEOdaly aF57i2W+WHl/5wMBmqM6yvUkC7GB6E83MrrR+pnwzYLe+Rhxf719Tx8B3ste aPTJeINRehRk/xskQLuQvnhZVx52zTSWWX+MABBVJb5zOxdLuK28xbJEgB2P Rfpx4yws0UDVPo5IADHL5VeG+a+xxCD1BYo1AjQJ08ox/MnEkju0h4g/CdC6 3EB9seAVlryiq2S0TQCccmwUE90r7DHdw/eDuwTwPLrZa+jyEktRN6psoIyH uwzroreUM7An7iYCVw/HA4dw7237d+nY06dm2dlH4+HM7/mwO5COPZu0eoyn jwcty6dadwLSsDQbJ3djtnjQiDDJZ5x7ir2IcyF/4YgH+4GvHN+PP8XSS9ws 5C7HA5tkdn/j3SdYxi8vrWv88SBlrEQH9Y+xl6y+3TmC8XDL8kidFwVizP/e 2evxIKzzublBKRnLDAm+cfB2PARea9jB/U7EXmeHvvWCeLCgXowo0UzEsjrD L5PvxANBeZfMVJ2AZR/HMQ/LxkPszVcB87h4LO954lauVjxs8ChJ7LfBY28a k+3PPYgHvqempTNjcVj+dMpCvH486DOqfahZisUKOFOHvM3i4W/rC95bLDFY odwLpTXLeOC6cbTZWAyHFdplvDe1iQeP7RPhPhbRWFHZ60oF53hw8tacf9Yd iRUNZQu0uMXD03vtxwRpI7Hi7dxsYa944M18kTGkHIGViBc+Ph8YD4zVYg9j lsKw8k8V7t9j0f1motUfPQjBKshVZLP4eKSXxvnybcFYBX2txWhSPAgdFJYb EAzGqrQbtVqfxwNth8FnEZYgrMq7uftGejwo2OSJdSUGYtVprffyX8VDa+6t OReGQKxm9v2NpLx42H1QbON8JgCrPdT5lrowHsJfdBUwKfhjddyfLvsVx0MA V4yotaUfVu/Qw2xRFQ/8gV9jnpT6YE1/hrdutscjnz1ew5rsidX9lb7v9CEe Tjj/9k9b8sCq9pU/f/MJ7cf+n7NrEh7YW0qCxLn+eNi/m+zjss8dS6ORjaaY jIdTPX8e3il2wZ7SVY7fnomHYWJ5U+hlFyz5+KUrbvPxcLCQvzshwxmLYdw/ uEiMh69vZ8pfpDthPmeqz3X9jod9xky/Et87YB7nLjse2kXxbntyVUrHAXNh S2oV35cAzE4h00tf7THri46WpQcTION7waOfYIfp8nKVpDAkgH/Jxot3MtaY Jv9jyj6mBNj3/NWH+MePMNUrVFpHWRIgjfeO8YUVK+z+takdX7YEiHn21fn3 C0tM5PYTKRO+BLhaLPOcTswcu4YdSnl+JQEW8BeGtQrNsCvirsuDVxNgt0zA 1orDDOOUVImTEU2AEqEsEa9TptgpeeoRvnsJ8Jlw4S6OxxhjVHTnsbifAFKa D0fkq4yw48pzvukKCeBiTU1NL2OEHVJvZmdQTwAN4epQDQdD7OcDT5tfhgmg D83JF1ofYusPFxoETRNg5fqh9uDDDzGSgcYJa4sEuD5volGjqofNmQhWjNsm wNKJkdvnfuhiA9ZL/1q8EoDrZDatvJ021mOrpfrHNwHMxGv+9n/Rwj7Zv8u8 HpgALXe56m7d1cJanTNkc8ITIH5WOFv8siZW4q2TEJOYAN9jtUYNT6tjZ8vX p/5LSQBh1lfGB/BqWAQp+krTswQY4J46EnxEDTMwavi8/jIBArvai/OPqGI0 9zgOaxcngNGw16eMa8qYe0Cd5veyBAi7mWPwKFYJm67WeB1VheaXf9Y5p1oR q+aNuFPfmAA8P2VvlF9QwMzpV33YuxLA7l30CYur97FeubCPtb0JkD0zcCIx RBa7HXqeRWMwAVwlNzPiRmUwhl8qleFj6PpvSQOmifewpvGK78TlBLC4tQqz t6QwXmZl8TBSAkw+s6EdfSuJPVZeij2/ngAVbOqlqZclMbtWVl7V3wlgSdMq x8Z+F2PNDTCvPJQIdclKj0TEJbCw6dPlykcTgV3s8rPGbnFsnbWUYpkuEYzN U2bvG4tjHbFz6WeYEiGpH7d2lQ0wN5f7XwMvJsKffKHQ2lO3samCGS5WzkSY zjQNeWxyC5Nf8PEo40kEQ0I9y51SUYxD9+3JBaFEqE4w+ullKIL1AKOyvEQi GPnWvP5JEsZueRakzUkmgvSlPpo6PWEsq0R61U8mEfjkvk9odV3HfC95RhUr JYL6qRnDrLprGPfRiTYm/URIZXF/PdIihCVJujMUGaH1nG6xCpEXwvb5HTeW NUuEue4RG4kRQWxo7c4/b5tESLzma/d85wp2h3tM4aRDIqTz+OueIFzBCk1c nxc6J4K4mRm7NNcV7HQq3co990RQgiZlpQgBLORLtsiUVyLYp81OSbfyY/8D 0soJGg== "]]}, Annotation[#, "Charting`Private`Tag$12701#7"]& ]}, {{}, {}}, {{ GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.5000500204077585}], Offset[{0, 0}, {0.020833332482993197`, 0.5000500204077585}], Offset[{0., 0.}, {0.021233332466666664`, 0.5000500204077585}], Offset[{0., 0.}, {0.021233332466666664`, 0.5000500204077585}], Offset[{0., 0.}, {0.021633332450340135`, 0.5000500204077585}], Offset[{0, 0}, {0.024033332352380952`, 0.6067085207487306}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.6067085207487306}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.6067085207487306}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.6067085207487306}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.5000500204077585}], Offset[{0, 0}, {0.020833332482993197`, 0.5000500204077585}], Offset[{0., 0.}, {0.021233332466666664`, 0.5000500204077585}], Offset[{0., 0.}, {0.021233332466666664`, 0.5000500204077585}], Offset[{0., 0.}, {0.021633332450340135`, 0.5000500204077585}], Offset[{0, 0}, {0.024033332352380952`, 0.6067085207487306}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.6067085207487306}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.6067085207487306}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.6067085207487306}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.6067085207487306}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.6067085207487306}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.6067085207487306}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.6067085207487306}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=1\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.6067085207487306}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.05297757776586607}], Offset[{0, 0}, {0.020833332482993197`, 0.05297757776586607}], Offset[{0., 0.}, {0.021233332466666664`, 0.05297757776586607}], Offset[{0., 0.}, {0.021233332466666664`, 0.05297757776586607}], Offset[{0., 0.}, {0.021633332450340135`, 0.05297757776586607}], Offset[{0, 0}, {0.024033332352380952`, 0.5047894865590723}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.5047894865590723}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.5047894865590723}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.5047894865590723}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.05297757776586607}], Offset[{0, 0}, {0.020833332482993197`, 0.05297757776586607}], Offset[{0., 0.}, {0.021233332466666664`, 0.05297757776586607}], Offset[{0., 0.}, {0.021233332466666664`, 0.05297757776586607}], Offset[{0., 0.}, {0.021633332450340135`, 0.05297757776586607}], Offset[{0, 0}, {0.024033332352380952`, 0.5047894865590723}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.5047894865590723}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.5047894865590723}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.5047894865590723}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.5047894865590723}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.5047894865590723}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.5047894865590723}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.5047894865590723}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=3\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.5047894865590723}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.002152533074752452}], Offset[{0, 0}, {0.020833332482993197`, 0.002152533074752452}], Offset[{0., 0.}, {0.021233332466666664`, 0.002152533074752452}], Offset[{0., 0.}, {0.021233332466666664`, 0.002152533074752452}], Offset[{0., 0.}, {0.021633332450340135`, 0.002152533074752452}], Offset[{0, 0}, {0.024033332352380952`, 0.40290496106995327`}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.40290496106995327`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.40290496106995327`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.40290496106995327`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.002152533074752452}], Offset[{0, 0}, {0.020833332482993197`, 0.002152533074752452}], Offset[{0., 0.}, {0.021233332466666664`, 0.002152533074752452}], Offset[{0., 0.}, {0.021233332466666664`, 0.002152533074752452}], Offset[{0., 0.}, {0.021633332450340135`, 0.002152533074752452}], Offset[{0, 0}, {0.024033332352380952`, 0.40290496106995327`}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.40290496106995327`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.40290496106995327`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.40290496106995327`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.40290496106995327`}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.40290496106995327`}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.40290496106995327`}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.40290496106995327`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=5\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.40290496106995327}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.00007826010460522363}], Offset[{0, 0}, {0.020833332482993197`, 0.00007826010460522363}], Offset[{0., 0.}, {0.021233332466666664`, 0.00007826010460522363}], Offset[{0., 0.}, {0.021233332466666664`, 0.00007826010460522363}], Offset[{0., 0.}, {0.021633332450340135`, 0.00007826010460522363}], Offset[{0, 0}, {0.024033332352380952`, 0.30102393620020557`}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.30102393620020557`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.30102393620020557`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.30102393620020557`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 0.00007826010460522363}], Offset[{0, 0}, {0.020833332482993197`, 0.00007826010460522363}], Offset[{0., 0.}, {0.021233332466666664`, 0.00007826010460522363}], Offset[{0., 0.}, {0.021233332466666664`, 0.00007826010460522363}], Offset[{0., 0.}, {0.021633332450340135`, 0.00007826010460522363}], Offset[{0, 0}, {0.024033332352380952`, 0.30102393620020557`}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.30102393620020557`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.30102393620020557`}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.30102393620020557`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.30102393620020557`}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.30102393620020557`}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.30102393620020557`}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.30102393620020557`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=7\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.30102393620020557}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 2.8057225174258318`*^-6}], Offset[{0, 0}, {0.020833332482993197`, 2.8057225174258318`*^-6}], Offset[{0., 0.}, {0.021233332466666664`, 2.8057225174258318`*^-6}], Offset[{0., 0.}, {0.021233332466666664`, 2.8057225174258318`*^-6}], Offset[{0., 0.}, {0.021633332450340135`, 2.8057225174258318`*^-6}], Offset[{0, 0}, {0.024033332352380952`, 0.1991440688792867}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.1991440688792867}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.1991440688792867}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.1991440688792867}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 2.8057225174258318`*^-6}], Offset[{0, 0}, {0.020833332482993197`, 2.8057225174258318`*^-6}], Offset[{0., 0.}, {0.021233332466666664`, 2.8057225174258318`*^-6}], Offset[{0., 0.}, {0.021233332466666664`, 2.8057225174258318`*^-6}], Offset[{0., 0.}, {0.021633332450340135`, 2.8057225174258318`*^-6}], Offset[{0, 0}, {0.024033332352380952`, 0.1991440688792867}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.1991440688792867}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.1991440688792867}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.1991440688792867}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {0.024033332352380952`, 0.1991440688792867}], Offset[{37., -6.999999999999992}, {0.024033332352380952`, 0.1991440688792867}], Offset[{10.000000000000002`, -6.999999999999997}, { 0.024033332352380952`, 0.1991440688792867}], Offset[{9.999999999999998, 7.000000000000003}, { 0.024033332352380952`, 0.1991440688792867}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=9\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {0.024033332352380952, 0.1991440688792867}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 1.002867775073644*^-7}], Offset[{0, 0}, {0.020833332482993197`, 1.002867775073644*^-7}], Offset[{0., 0.}, {0.021233332466666664`, 1.002867775073644*^-7}], Offset[{0., 0.}, {0.021233332466666664`, 1.002867775073644*^-7}], Offset[{0., 0.}, {0.021633332450340135`, 1.002867775073644*^-7}], Offset[{0, 0}, {0.024033332352380952`, 0.09726470347104098}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.09726470347104098}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.09726470347104098}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.09726470347104098}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 1.002867775073644*^-7}], Offset[{0, 0}, {0.020833332482993197`, 1.002867775073644*^-7}], Offset[{0., 0.}, {0.021233332466666664`, 1.002867775073644*^-7}], Offset[{0., 0.}, {0.021233332466666664`, 1.002867775073644*^-7}], Offset[{0., 0.}, {0.021633332450340135`, 1.002867775073644*^-7}], Offset[{0, 0}, {0.024033332352380952`, 0.09726470347104098}], Offset[{5., 1.1102230246251565`*^-15}, {0.024033332352380952`, 0.09726470347104098}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.09726470347104098}], Offset[{10., 2.220446049250313*^-15}, {0.024033332352380952`, 0.09726470347104098}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{43., 7.00000000000001}, {0.024033332352380952`, 0.09726470347104098}], Offset[{43., -6.99999999999999}, {0.024033332352380952`, 0.09726470347104098}], Offset[{10., -6.999999999999997}, {0.024033332352380952`, 0.09726470347104098}], Offset[{10., 7.000000000000003}, {0.024033332352380952`, 0.09726470347104098}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=11\"\>", BoxRotation->0.], Offset[{26.5, 5.88418203051333*^-15}, \ {0.024033332352380952, 0.09726470347104098}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 3.5812613006575185`*^-9}], Offset[{0, 0}, {0.020833332482993197`, 3.5812613006575185`*^-9}], Offset[{0., 0.}, {0.021233332466666664`, 3.5812613006575185`*^-9}], Offset[{0., 0.}, {0.021233332466666664`, 3.5812613006575185`*^-9}], Offset[{0., 0.}, {0.021633332450340135`, 3.5812613006575185`*^-9}], Offset[{0, 0}, {0.024033332352380952`, -0.004614464316979633}], Offset[{5., 1.1102230246251565`*^-15}, { 0.024033332352380952`, -0.004614464316979633}], Offset[{10., 2.220446049250313*^-15}, { 0.024033332352380952`, -0.004614464316979633}], Offset[{10., 2.220446049250313*^-15}, { 0.024033332352380952`, -0.004614464316979633}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.020833332482993197`, 3.5812613006575185`*^-9}], Offset[{0, 0}, {0.020833332482993197`, 3.5812613006575185`*^-9}], Offset[{0., 0.}, {0.021233332466666664`, 3.5812613006575185`*^-9}], Offset[{0., 0.}, {0.021233332466666664`, 3.5812613006575185`*^-9}], Offset[{0., 0.}, {0.021633332450340135`, 3.5812613006575185`*^-9}], Offset[{0, 0}, {0.024033332352380952`, -0.004614464316979633}], Offset[{5., 1.1102230246251565`*^-15}, { 0.024033332352380952`, -0.004614464316979633}], Offset[{10., 2.220446049250313*^-15}, { 0.024033332352380952`, -0.004614464316979633}], Offset[{10., 2.220446049250313*^-15}, { 0.024033332352380952`, -0.004614464316979633}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{43., 7.00000000000001}, { 0.024033332352380952`, -0.004614464316979633}], Offset[{43., -6.99999999999999}, { 0.024033332352380952`, -0.004614464316979633}], Offset[{10., -6.999999999999997}, { 0.024033332352380952`, -0.004614464316979633}], Offset[{10., 7.000000000000003}, { 0.024033332352380952`, -0.004614464316979633}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=13\"\>", BoxRotation->0.], Offset[{26.5, 5.88418203051333*^-15}, {0.024033332352380952, -0.004614464316979633}], {0, 0}]}]}, {}}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{True, True}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{False, False}, {False, False}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}, {Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->{{All, 75.80000000000001}, {All, All}}, Method->{ "DefaultBoundaryStyle" -> Automatic, "DefaultMeshStyle" -> AbsolutePointSize[6], "ScalingFunctions" -> None, "CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotRange->{All, All}, PlotRangeClipping->False, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]], "Output", CellChangeTimes->{ 3.8069103337157297`*^9, {3.80691270003312*^9, 3.8069127266070843`*^9}, { 3.80691286142306*^9, 3.806912975481896*^9}, {3.8069131647173634`*^9, 3.806913241142002*^9}, {3.806913352879383*^9, 3.8069133837912493`*^9}, 3.806983794607871*^9, 3.8133859167556763`*^9, 3.8133860326592216`*^9, { 3.8133861196960163`*^9, 3.813386139695586*^9}, 3.813387158804915*^9, { 3.8218537317546797`*^9, 3.821853746401569*^9}, 3.821853881016809*^9, 3.822022659937346*^9, 3.822022782239375*^9, 3.832037543335478*^9}, CellLabel->"Out[6]=",ExpressionUUID->"3d21af26-9c89-456e-8f28-70d671c109e3"] }, Open ]], Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{"direkte", " ", "Optimierung"}], "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"diff", "[", RowBox[{ RowBox[{"wtg_", "?", "NumericQ"}], ",", RowBox[{"tl_", "?", "NumericQ"}], ",", RowBox[{"tr_", "?", "NumericQ"}], ",", RowBox[{"\[Epsilon]0_", "?", "NumericQ"}], ",", RowBox[{"t0_", "?", "NumericQ"}], ",", RowBox[{"\[Epsilon]vec_", "?", RowBox[{"(", RowBox[{ RowBox[{"VectorQ", "[", RowBox[{"#", ",", "NumericQ"}], "]"}], "&"}], ")"}]}], ",", RowBox[{"\[Tau]vec_", "?", RowBox[{"(", RowBox[{ RowBox[{"VectorQ", "[", RowBox[{"#", ",", "NumericQ"}], "]"}], "&"}], ")"}]}]}], "]"}], ":=", RowBox[{"NIntegrate", "[", RowBox[{ RowBox[{ RowBox[{"(", RowBox[{ RowBox[{"HeavisideTheta", "[", RowBox[{ RowBox[{"wtg", "^", "2"}], "-", RowBox[{"w", "^", "2"}]}], "]"}], "-", RowBox[{"transmissionchain", "[", RowBox[{ "tl", ",", "tr", ",", "\[Epsilon]0", ",", "t0", ",", "\[Epsilon]vec", ",", "\[Tau]vec", ",", "w"}], "]"}]}], ")"}], "^", "2"}], ",", RowBox[{"{", RowBox[{"w", ",", RowBox[{"-", "Infinity"}], ",", RowBox[{"-", "wtg"}], ",", "0", ",", RowBox[{"+", "wtg"}], ",", RowBox[{"+", "Infinity"}]}], "}"}], ",", RowBox[{"MaxRecursion", "\[Rule]", "20"}]}], "]"}]}], ";"}]}]], "Input",\ CellChangeTimes->{{3.822285401764361*^9, 3.8222854768222847`*^9}, { 3.822285571744907*^9, 3.822285707780545*^9}, {3.822286053564761*^9, 3.822286062525536*^9}, {3.822286643182988*^9, 3.822286648618248*^9}}, CellLabel->"In[8]:=",ExpressionUUID->"6f3ae69e-9c75-4c42-ba15-7d44efad2c61"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"diff", "[", RowBox[{ RowBox[{"0.75", "*", "0.02"}], ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", " ", "0.007326447541946075`", ",", " ", "0.007269560988958051`", ",", "0.007238948047382406`", ",", "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.009999959154289148`"}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.822286064811063*^9, 3.8222861189331408`*^9}}, CellLabel->"In[9]:=",ExpressionUUID->"156db52f-3a22-4dc3-b6e5-1d5a4d050205"], Cell[BoxData["0.0010628365142953539`"], "Output", CellChangeTimes->{3.822286121452591*^9, 3.822286655982646*^9}, CellLabel->"Out[9]=",ExpressionUUID->"4e2eb27f-9c99-4d93-a68f-1e21c91df774"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"NMinimize", "[", RowBox[{ RowBox[{"diff", "[", RowBox[{ RowBox[{"0.75", "*", "0.02"}], ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "\[Lambda]6", ",", "\[Lambda]5", ",", "\[Lambda]4", ",", "\[Lambda]3", ",", "\[Lambda]2", ",", "\[Lambda]1", ",", "\[Lambda]1", ",", "\[Lambda]2", ",", "\[Lambda]3", ",", "\[Lambda]4", ",", "\[Lambda]5", ",", "\[Lambda]6"}], "}"}]}], "]"}], ",", RowBox[{"{", RowBox[{ "\[Lambda]1", ",", "\[Lambda]2", ",", "\[Lambda]3", ",", "\[Lambda]4", ",", "\[Lambda]5", ",", "\[Lambda]6"}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.822286133631102*^9, 3.822286195323123*^9}, { 3.82228623029062*^9, 3.822286238744589*^9}}, CellLabel->"In[10]:=",ExpressionUUID->"03ec2bcd-6f55-4aed-984e-7b3429dbb205"], Cell[BoxData[ TemplateBox[{ "NIntegrate","slwcon", "\"Numerical integration converging too slowly; suspect one of the \ following: singularity, value of the integration is 0, highly oscillatory \ integrand, or WorkingPrecision too small.\"",2,10,9,16321148811635565211, "Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.822286249343987*^9, 3.822286676710826*^9}, CellLabel-> "During evaluation of \ In[10]:=",ExpressionUUID->"c8f2dbe7-75ac-48fb-beaf-7fa727078358"], Cell[BoxData[ TemplateBox[{ "NIntegrate","slwcon", "\"Numerical integration converging too slowly; suspect one of the \ following: singularity, value of the integration is 0, highly oscillatory \ integrand, or WorkingPrecision too small.\"",2,10,10,16321148811635565211, "Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.822286249343987*^9, 3.822286693148843*^9}, CellLabel-> "During evaluation of \ In[10]:=",ExpressionUUID->"85548cc2-78a8-44ba-9d45-9901a1eb52da"], Cell[BoxData[ TemplateBox[{ "NIntegrate","slwcon", "\"Numerical integration converging too slowly; suspect one of the \ following: singularity, value of the integration is 0, highly oscillatory \ integrand, or WorkingPrecision too small.\"",2,10,11,16321148811635565211, "Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.822286249343987*^9, 3.8222867230058403`*^9}, CellLabel-> "During evaluation of \ In[10]:=",ExpressionUUID->"17347db3-d2a3-41b3-ac1a-5313612d9892"], Cell[BoxData[ TemplateBox[{ "General","stop", "\"Further output of \\!\\(\\*StyleBox[RowBox[{\\\"NIntegrate\\\", \ \\\"::\\\", \\\"slwcon\\\"}], \\\"MessageName\\\"]\\) will be suppressed \ during this calculation.\"",2,10,12,16321148811635565211,"Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.822286249343987*^9, 3.822286723062702*^9}, CellLabel-> "During evaluation of \ In[10]:=",ExpressionUUID->"1e262895-5071-4647-89fe-e2631dad9957"], Cell[BoxData[ RowBox[{"{", RowBox[{"0.0005040800034696907`", ",", RowBox[{"{", RowBox[{ RowBox[{"\[Lambda]1", "\[Rule]", "3.0474653711824247`"}], ",", RowBox[{"\[Lambda]2", "\[Rule]", RowBox[{"-", "1.1612881965805946`"}]}], ",", RowBox[{"\[Lambda]3", "\[Rule]", RowBox[{"-", "0.4286598205548415`"}]}], ",", RowBox[{"\[Lambda]4", "\[Rule]", "1.066290253346536`"}], ",", RowBox[{"\[Lambda]5", "\[Rule]", "0.03163361777640106`"}], ",", RowBox[{"\[Lambda]6", "\[Rule]", RowBox[{"-", "0.0099609897622874`"}]}]}], "}"}]}], "}"}]], "Output", CellChangeTimes->{3.8222866506924963`*^9, 3.8223097931890583`*^9}, CellLabel->"Out[10]=",ExpressionUUID->"55009182-6a57-4ae0-9368-6c6f50d18513"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{ RowBox[{"compare", " ", "same", " ", "level", " ", RowBox[{"transmissions", ":", " ", RowBox[{ "they", " ", "both", " ", "approximate", " ", "the", " ", "rectangular", " ", "limit"}]}]}], ",", " ", RowBox[{ "the", " ", "first", " ", "scheme", " ", "is", " ", "better", " ", "at", " ", "the", " ", "edges"}], ",", " ", RowBox[{"the", " ", "second", " ", "better", " ", "in", " ", "the", " ", RowBox[{"center", "."}]}]}], "*)"}], "\[IndentingNewLine]", RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", " ", "0.007326447541946075`", ",", " ", "0.007269560988958051`", ",", "0.007238948047382406`", ",", "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.009999959154289148`"}], "}"}], ",", "w"}], "]"}], ",", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.44798874545216505`", ",", "0.3720949697259449`", ",", "0.3666741914433289`", ",", "0.36586118013042696`", ",", "0.3656755715952492`", ",", "0.365617222323006`", ",", "0.365617222323006`", ",", "0.3656755715952492`", ",", "0.36586118013042696`", ",", "0.3666741914433289`", ",", "0.3720949697259449`", ",", "0.44798874545216505`"}], "}"}], "*", "0.02"}], ",", "w"}], "]"}], ",", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.0099609897622874`", ",", "0.03163361777640106`", ",", "1.066290253346536`", ",", "0.4286598205548415`", ",", "1.1612881965805946`", ",", "3.0474653711824247`", ",", "3.0474653711824247`", ",", "1.1612881965805946`", ",", "0.4286598205548415`", ",", "1.066290253346536`", ",", "0.03163361777640106`", ",", "0.0099609897622874`"}], "}"}], ",", "w"}], "]"}]}], "\[IndentingNewLine]", "\[IndentingNewLine]", "}"}], ",", RowBox[{"{", RowBox[{"w", ",", RowBox[{"-", "0.03"}], ",", RowBox[{"+", "0.03"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", "All"}], ",", RowBox[{"PlotLabels", "\[Rule]", RowBox[{"{", RowBox[{"\"\\"", ",", "\"\\"", ",", "\"\\""}], "}"}]}]}], "]"}]}]], "Input", CellChangeTimes->{{3.822022876397216*^9, 3.8220229452057533`*^9}, { 3.822022984835977*^9, 3.8220230116562634`*^9}, {3.82231057327883*^9, 3.822310574094569*^9}, {3.822310612522004*^9, 3.8223107559459047`*^9}, { 3.8223107924416647`*^9, 3.8223108202124577`*^9}, {3.822310872237495*^9, 3.822310873045576*^9}, {3.8223109165194798`*^9, 3.822310939867735*^9}, { 3.822310988519943*^9, 3.822310991159363*^9}}, CellLabel->"In[16]:=",ExpressionUUID->"795c8c6c-fedf-45a2-a33a-f6348f3280a6"], Cell[BoxData[ GraphicsBox[{{{}, {}, TagBox[ {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwcV3c8l+/3ljKSJEQJWYmMIkXleW6ZJTuE7FVk77333pum0eRjj3SUUchK ZiojM95vqWTF7/n+/nq/rtf9vM997nOf+zrXxWPhpG1NSUFBIUtLQfG/3/Y3 fkNadYVQ39I/dOzPEcxzsGrr2ctCkP7Y8lC/lRUTWFjmpi4qhIKxgNCMPDYs itHsbkNKIVyos+G1sjyGSfPnJLNEF4Ir6XdSkg47Ni/1sdoxsBB+LtppCWgc x66aKlDw3S0EPddR3i5zTmzdNeBkgHkhHHEutSj35cJKI2tUhm8WQuXiNGdp 4Qls/0vBjDiFQnjbUfY1ax8P1rlNf/o3ZyGcO5TVGdLIh/kyKmmosxQC3sp9 oMKXHzvNH+ReSlcIdtsmpzyvnMTirv98bfS3ADLPmF74MSuAWQ0m9MesFsCz 9lFKH91TmIzp6e81ywXg2fhJXr79FLbkarn/8PcCCGpK+5r0UhBTzR280dZX AE8D5mtV8k5j/PyuNqtdBTDKvvqwiEMY237B4HPiXQHEjDitpd4Xxl68US70 aSqAOLJCjka5CMawUD8v+rQApJmObBz6KYb1ShUGZIYVwKnoi3mulBKYCs5d fiuQyI+PWbzOQgJrVXg4xe1TAHmSr7u52ySwBq1i5WeOBTAhazRvmXwOK777 8nCzQQF88BDfNJc7j/G4nlWI0CkAvY7ShG9V57F87wpPFY0CuOXx1H1S6AKW GlHz+ZNCASjaXpN9c1wKC7z3umjhTAEoOPJxaXJfxDaKZEdeni6AL2FFBiWl FzH352/p3E8S51NmGKGSvITZ1bc77bAXwN698aVcOpcxvYGei8zUBVB7qCiu uxHD+kc17UcoCuCyyhOqWyY4pjrxsbBgKx/ubwxXJ+5DmNzy0F7Bn/mQzKld dVRMFhOj+dYtM54P2T+3h/wLrmBPDppTUA7nw4Agt3P0zhWMn2Va4l1/Phza 4yD23lwOY+eZy9J6lw/luz4bVGfkMerLZHObinwIpxtgYpxVwEKuuKQLv8gH 6huDFEcNFbFt5V/tKyX5wLSfldTWp4it6vwV9ivIB9Va5RmsXQn76rj7Jyk6 Hyzlb2yVDFzFDDxCBHXD8iFjdXs70+Qa9slv7y32wHy4flsspGTpGtYZTdP8 2C0fhJl6+8uZrmM1Dw/F1pvkw6sXJbhOtBom/iTlVaBBPoiWHtb4LqaOPS9j Jsvr5IOPyFL8tVF17OErNp2ea/nAWMlyZpNDE0scOsE1LZkP+eZ+1J2ZWlgy A8X+PWfz4bRkvRHrby0sTWniF5dwPvDU/BOzvaGNZdfc7zDkyYe77vdGlY/e wB5k8nh8PJgPN/rzm0xe6WCPe/aYrdDmg22ottkZYV2smHpKhWFfPpQUCQna 5utiTz0fcqts5kGtygyFbqQeVqXH9+HNbB6sQ9SxRh99rCZxb+23yTwoXnhD Ff1PH6tvn37wbzwPnO3P6kuGG2CvLzz2ujiQB+rufOUJuYbYO9aTfP9BHiS9 HX9Nu2yEdapTMfQ25AHTGb/QjRhj7EPkzPpSdR64ZbMHm582wfrWinoEn+fB QWNhi98eptjYkIDv/ew8EBAKd1bhNMfGGWisX6flQbntq7BxX3Psm9Kcxnhi Hpybr1mNHDPHvteUnDwakQeheW6FqvctsOVMwf4klzwYzLv2Q1LZClvpoX31 wj4PTJi7lMg1Vtgq9UJx1+08sI9IPX1WyBpb83ziT2OSBwW1T5I8jthgFDdP Cwap5MHeNj7ZJYY7GGUSHXOBYh5UnTF/E55+B6N6t/ivQTYPuv6GjvJz2mJ0 Us8G1i4Q9bo/xNktZYcxs4kEOfIR69drWHvT7TFWDXq7eK48eFqYw/ZB0gE7 GrWk8/RYHtwvVf7tMuKAcfx9fnr2UB5s1H24eEjYCRMYFh0y3s6FS0nuG5wU Lli9QY5S+t9c8NlM2uIxccFUx/fVdq7mwomdqPlrr10w18nPWVILuSB8tunc 6QhX7PWPGIPDQ7nwZ0HaqEbMHdNy/NOh3J8LJxe9Ry/dc8e+r5hdCvyQC8d/ 8qmrMXlgdGtSx3+8zQWdz86xZhSemC7F7HhrWS5Y3zpGwbnjhc2HaqltPc2F m20qRT/DvTFfqqYm8WIiv6YDtuMMPth9uvTCwvxcEKSiiVMV8cWWWOTMvGNy oWtISu1Nkj8WlPWi72V4LmioSL9LFA/AmNiPXZkJygWeODE4PhyASZ9Y4dH2 zIVRZ/utj6JBWLhQ4bSwZS4EYkv6ktQhGNvz/ToWJrnwkuncutPtEOypmEdr tkEuJE2dkVjtDMH6zqkWUWnmggWnTN+/7FDsOL5p800mF5wvGEbPaIdjL5ut h49I50L40JFLK+/CMVn5fmXVc7ngXRWc3YQiMJurpYL1QrlQc1VD4btUJFah rbeYykrs3zlAY6EajSkOvjHsOJwLjTV/ugNGo7GRm6Jdu/S5kCxk0frLNgbb Mdr33H4vUZ+UiS7FjFhM5XaFg9JKDpjYmJ7/xZaAfVng/Or/IwdGtg2u679N wJztY9QrZ3Og822Dab9zIpbpYnaG+0sOhCpTy9uNJWGTfgw/Nzpy4KT+6YCn LikYq59pyPvWHNg6+vZO/GQKpupbfjgLckD/Hg+3qU4qVuetLSFZnQMFK4e1 BeTTsGSPTDfH+zkQf3W186VyBtbuPrcXy8uB5y/YLDz6M7BtN+n0A5k5UHlP TH3aJBO77TpWVRqXA/47a0PHI7Iw3IlrbcozB86/89ShpszF3B2dIv9zyQEj y9uHqJ/nYk8dmlmD7XPAx9WLP9UwDztibyHFaZEDnsEOth/b8rGlO8XeN9Vy 4PSv1F/tI/cw3jt/aQWu5gBHn9mmj+59TP/21ZzfcjlQQmH4+M6b+1iL9WJ9 inQO/Al3lj3+8AGWayG21cWXA3IsZ94oxzzC+syD4nK5csDSbtvC78BjjNq8 77jtMaJeF6+dvpTyGHMxdZWhPpQDLLNZNp0lRdhVo5oA2c1ssAi4YYPtK8UC b9EwHPqTDQvLD12nikqxKkP9wi/kbCg2ta/Yuv4EO2Gw+dp3Jhuij3LPHC5+ iq3p4hTVfdkw0HSmuCjjBSaim5Qc1pUNX/kHBlpMXmIWOhPc2u3ZYH3BXztQ tAzr1g69Qm7Mhm6GnzznHMuxxxrtoUIl2fBB/Zaov1wFNqbOxrz+IBtSdD8G TUEFxqh+51F7fjY0fKIe6ZWtxPxU6VotU7OB+/XJQ8/VqjDta+pUhQHZ0PZa dTAmswY75PtPrc07G6bMfgc/F6zFPjx9nrnklg1pEk+MXr6uxZToDwhetsuG 7EtzzrBWh13ufacyopcN5rflxHVyG7H1Xc+0Xa1sSLzCbFCs/gqrOSswLqCW DYWKv1I+0DRhZ1PDHTzks8Fk6eiPEzGvMX7dK8lMZ7MhhD1FZ3OmGZuMWBm5 KJwN7Nc+4566b7DCmns85gLZ8NTP8c3auzfYsaM7FWUc2cBvJx9gWPMWY/jc MKi6Pxsonm+uoMZWrOuAHZf7vmyYHPaVtlFsw6Jljt3O280C+Y0Th7UH2jDK Qq/1hT9ZcLco++TSZjv210zyeNRUFqR+Fr9s49+BVaVMW778kgWNYv/9+X2q E3N9m/p8cCQL5AooytBIJ7bE9xPj782CTvmULznKH7CJ2Rdmbxqz4Hfoq3Un 616sgM34yXxNFnyY7eHy4+zDDK/Srx6qyIL5kK5u6bg+bPCJXZhJaRb0QKfI P6d+rNP+VPFWehYcSzzKcdV8AIsqGCLxJmfBZxPeJ56zA5hCT4SUSlwWPDop /87G6RP2+sz399khWfB32tvjX/wgVrl6/8d5xyzo/rHvrMHmMObMpylpbJsF 13UrNSbvj2BiOrv+4VZE/BnR14Kqo1hptTHDgGEWRB42y4n8b4zQZ+zizspZ 0Nx65OHbxi/Y9smynDNyWTDcZ2OHFX7FjAbkKckyWfC+PuXih6hvGIeYw4CD BFEP42D/+LoJzP/zHhlR0Sx4fb2554n0JDYenfl46VQWCHvmdfW8msTyp8Hj LmcW/Fktp6nvn8K2k3W+nj6aBQtHLlxut5jGjPAFpUWmLNDfec9qtz6NceQw HbWlzYK9RcFDLBIzWL66dYPNr0w4aDPzMnV6Dtve2uAVIGXC5tXU6aWCeczo SWLczHwmiHkEqiGTBYxjX52R1ddMmDj7zbjg5yLm/59qG99oJrh+Eg1nafuB jZtMik4PZIIQJDEZ31vC8uvpds07MkG2vmhBw5aEbdvcu83TmglrCfmyngZk zIhFsm/idSY8UXrmXCm4gnE4GT8wrcqE29eDVL6I/MTy+cvlje9lQoCWNcsx u1/Ydr/Cc47cTPCjkJq/QfUbMwoaZRlPzwT7OrPK0qLfGMcY5axhbCbcq68s 01n7g/lHZamzR2TCFrO/4YGSNWxcUqR2NCgT+tTk7uQY/8Xyk3Sj9T0yoZa6 J+TQl3VsW2Zxhc05E07u0emyKt7AjBYDDYbtMiHx5JmXDp6bGIdi6Wk9s0yY m6/3jxPexvI3Nz/cuJ4JnJLW1Ud/7mLbJUnnmZWI7z9QaCb4UeBGuvyFH2Uz 4fx2tdoG5R6co1zNSetCJvDHSutXnaDE/Y2nhhnFM8HKN2fzZjUlPk7nJdsn nAk6BqybhzT34vnW9w9r8GSC27u0cp+Mffg203lfBo5MWHS5fS1Blgo3au6Y 6mbNBA9bC0+fn1Q4x/Fflar0mWDj+sWqxpoGz+9T1FP5mwHVG9eaTxXS4fHv rRV4VzPgWddciKTvATygOUJicykDsn+wH28ypsdNytsYnk5lAKmmw1pPhgFX L53ZDvmSASn8Gx/+Sh3C0X2qHwYjBL5R7HecixHnTlZ8t78nA27XmXPOnzmM M0ZbV0++z4D91Roj83AY3xMc8ai+JQMKk480Tegw4VNObUG29RkgTBlU5pTI jBdpKEp3PM6AUCq5xmhFVjxT2Vrgwb0MmFO9nlNFyYZHoggWn9wM4PszPBzQ zobfOdO2IpicATczQx5OWxzD9U/NfKWIywDvF3B4nww7fu0EVfdIRAY0ltud 6OQ4jp8+pPgk2i8DRMfpE+6uceDsNNZZZp4ZoPO8zHyCzIkf2A2PkHbJgNQF 5vNiq1z4EqnVfN6GiN9qEKkbw42/7FFgv6qdAWwfJzvuz/Lihe1WtNxqGRCt ph/7Jo4PT3odvvZXOQNotb6MDVzgx51ftn4swTKg1ehTUvW9k7hZ8ffmIOkM GOJuur9rLIBrFe4ru3kuAxQDZ+vO8J3CJRIV4miEMiB9t+fWjRZBnDfSyucb XwaM+5YLDxUK4cyB4bdruTKAs/3JI+PQ0/hvh1b52ywZ4JLL/qLBQgSvUVPY bt9NhzItmhOHr53FixWtFgs300H8a2RP5uezeBYWPuL5Jx2MnR71x7mJ496i rVUCP9KBZlu/5V6VBH7n5PeHOzPpkGIjriFhcg434NyXMjSRDrZKl3OOM0ji lw4qOEQOpcNbL43t3yHn8dNUVrdM+tPhApZJ76B0AT/+L+zahQ/p0BLTIK7K JIVvL7WcnH2TDgKsav85vZHG4YP8V8UX6fBJzE1dL1IGv7D2JtyzlPi/uqfz tD+GvzwhK1zyKB3uaSkbXPbH8UJXGW/a3HR4rWZcr3ldFmfNb+C6mJEOPkyZ TeKjsnhim3SbbXI6yOIPKoTtr+CBR88zdUWmQz9jLlnioRy+dqWybiskHaKV 66ieKMrjjnfFTUUC0mE//X4tOrI8bvJa9HmCWzpoN1ooe+so4riVgJKmWTp0 OkhMkZ2v4jUJj5eCb6WDXaXxlUKVa7hYLW/af3rpYEh5jl9dRAXnojsxwaSW Dmpbnau/aFXxzHMFkfJX0+E626eF1H1qOIPxcVF3+XTgmb+9ELFfHd8pY/Md vJgOrjbONc5HNXHP0Qxu6vPpwJKsq0H7VBMnUbK8u3CWqHfU5wnGK1r4V11G lmyBdPhIsZikHayNN23RvjRkJuo7UOMloaKLS56M0oljSIet3uNfPh/Uw5+r U2017k8HXvuC3V8jenj+gz1XOSnSobdZ9G5RpD7O0hVEUttKg7KQW1cnbQ3w +N//0gPX0uCxgI5lv64h7q+8OfltKQ0mcuu8Ll8zwn87e0czzqfB08aWRA8t Y9w+d03synQaPPoz9ea7pQlutLzq93A0DQr+sf2I1jHDZdJ+HLFuT4OOCotf zRMWeNUr21cZb9LAaTxE+HC6JS4yO2fR/ioNbt1YT3JQt8I5Ln4vO1WZBmks m+d9R63xdAsLPf2XabC3SSSu86kNTh8/sR39JA0EGt5H3Q6/jW9/Hb+2eC8N 1JqOUaxo2eLutLdW2PPSYEgrujdHyQ5fEh/NvJ6ZBpu5B3QPKt7Fx8MHp5/H p8H933b1O2YOeOPpngAnnzTok5xnIDO64EN94grS7mnwp/msMvbOBV/xzKDb 45QG0knKogURrrhAi1FWqhVx/velzuwc7vgV22bjW6Zp8PMKfpL2jztudIif n98wDRTPCW+UDnvgqbd+lFdrpAH5CfOFiUYv/MUeDa9AlTS4E59+wP21N/6+ pAJTVkyDlklvVPPBB//3y6dz5FIaOJy5vBzD4I8fzf2S/OA8sR+P+K6GfAAu IXvlpt3ZNDjwXc5XLDIQvxNP+33rZBrYxLnJ+ecH42ES9k9budOguJ1kJKYb gheO9DonHE+DXyHf161ZQ/EB/qx/XIfT4NVBSUXWqjCc1LnZMncgDQ6emHT1 SAnHaV1MYsup0+CqOGvTKZ8IHG86ySa3nQo7V2mas2yjcAPLmC90f1NBpeyy iLNbNO6+f/nRwM9U2N/h09IfE4M/0a06az2XCoyGCcONX+Pw1i22v6JTqWCT xtx8jysB//rAr2ltPBUyCtS7Wh0ScRaSnEr0x1TYR2f+16cwGT+TXsyo1Z0K rK/c+XVNU3CVS3TDx96nQuCdwqwAoVQ8KLLf8llTKvjo3rIq+pyG54qcP+1e lwo6Sq6cL1rT8aqP2SsylalAdRj1MNdn4ItcZgE9pakwZ0KRZtGehVO1tchn PUoFKS8J7tSJbJz77ik6s8JUWPVfry+nzcV1a0mZP9NSgUxXW1ERkY87G2sb NySmAqa60y8yXoDH7q3hC4shzpdfld0qfw9v1ggoZwlKhZhicYVd/gf45z8T nl98UoE+tSxG7c8DfC1PASt2T4UrBUcXT/Y9xIXnD3RK2aXCK5nhnLclj3Gl RKdkCutUaOOJPtlSVISbSQ7odZimwvH5q+fflRfjmcG504a6qdA13D7ZuFKK /yew84RPMxUm+pMjpE89xT98MHdeUkkFTqMFjo8Oz3DKY0L/AmRToXPF4eqm 2EucE+JblC6ngoidkLHvszJc2nol5tCFVPCCNvadgnLc4b9a1gfCxP6kN0kd 6hU4Y4xPxluBVPDb7yv3WLASrzC7zPKdJxWihlN+axyswtcOweFTR4nvtWzs HDaq8ey54OSrzKmwtSo/wUlZi18CuUN2DKkgP/JfB+fROjzQsZ3+xb5UEDC1 oll1bMC5laLjenZT4IpYpKLOf434W04VupXNFPCnv0vPt68Jp+nupjn3MwVO /riQU/wV8KePkyJ1llLgb9e1foGqZlzVX4vKcy4F4lzF6vjC3uDJwoOU9V9S YHdWXmbiSgsusTcrZGwkBUZJQoMjEq34pzF9iu2BFOAzLvrscLYNPxo7/g/v TIFsKu3XKjrv8AbzQn+zthRo63rPyun/Hje6aLYV0pwCskvS8g8rO/AH89Pr rTUp8E9Hd8pS9wOu0FzkNftfCkzqqV5Oe9ONz2bdXqN5kQK8ZqF8xld68dPK P36pPEoBr4oH/cKy/fgHrheu9oUpYHTC9Q0Fz0fccc3xZ0JOCpBoqPw5GQbw iqJVUl9SCqjM7pk4xjiI6wRUOazGpkDB2t2/8QJD+JqO5xJzJBHPzEXeWXUY v7xvc0HPPwWiqwKd5TpH8a+fG+94e6WADrWO0nn+z3hwZcBcjmsKxKjUaT9M GcdbLfbMjN9JAWvB2K7KZ99wm0stljuWKVBWOWvu9WICp2WKmDphmgJFH5d/ 2KZM4qpvaCcsdFNgPiiyxyJkGidld5qEa6aARhf3LZak73iyc/yXouspoPw+ 6pLb8xl88ATj5/krKVAt1Ex/nn0e9/7bb0CHpYBaxb2bb+wXcPbetBFh6RTI S3QT0BxYxF8V695UO5cCHN0Jaqc0lnCTQLYhR7EU6H/B/+3h5DJOoTeqkyyU Aqe7BQcuxJPxh6J5A//xpwCP0ns76dIVfHacq/83ewqsOz5+q5q5ikdXTWiw sqYA7ae7M+yPf+Gn4x/2SB1OgT1Z15fuvv2Nf7C0UjOgTwG3cIcmvdU/uNNl gQ++NCmQ9fAgI/X5vzgT87xKPmUKmD2z/FEft45XLT7paPqXDD5BTnodfzfw 9RzRdxS/k8EufCjy05F/uPAr365L5GRgEQjBT77dwU2+vut1X0wGhsu+mQkK FCiZ4sinlzPJkELfZSV7YQ9q4bUYmZ9IhtEX1hPcUpRoTaFsnHc8GUJ2hXov XN2LBG9vTxgNJ8NbJyaVArt9KPFZ5kJfdzIcb/FTlJinRm+6p5fpOpLB++co HbUSLfpNPruq0JoMujs0Zd4N+5EAU+BaICQD0zrPwxPKB5CBZNdmXUMyWD15 faxsmR7F6x3dXa1OBvvlHbftMgb02tt6r+h/ybCv2D2C4ioj4m/aPfCgJBn4 r7/IWNZnQje/qTJ+fkicj36u6KI/M4rdk8typDAZuo8ZZ5+qZEGv+OaOauQk gwFrqNCp3SOIrCjJGZOeDDy2z7A2czbEeyeEpyUpGayDXW1fjh9FOrE9J//F JgP7E6zsPxd21NBzR8wlJBleZfP3UKxyoqWVaoln/skgLf+It3LyBDrBvFdq xisZhHcv7Dm9yY20z2tePuFG1HdE/O1VVl4UfrMAGTgmQ6lOrP8TJT5U67Mo n2ZL/H9vPMO3eH60mCd1tdsqGVYZbloVLp5EGhP9mlduJYPMkUfm138LolDK E7p+esmwZCIxaff4NKritzeo1kqGiNJ/bUHuImhOqd6YrJoMyg99FrhuiyF2 W2oLoavJIDI0+zwOnUWqcTdsLOWTIeNW0kajqTgKenHfrgBPBofmZ62dGRLo +89LbofPE+vi/MI/Vc4jNpZor+tnk+EyWYZCtOcCUrkw6BchnAxfD43GZztJ I3993mAQSIaanFHm9+KXUJmvU/gGTzII0F9OSWCTQVP5r6LPcSbD7+5C2l0+ HLHA/gSHo8kwtX7qLS4qi3z3Ps6YZEgG+XhDKZuncujFyZ85x+mSQexz2Y1k RgU0oYwX6lIR+StM/1RPV0RMdnEPkyiSIY4SndOWVkaxR/9TS/ubBDdyfSYT d6+iFaPrejSkJPh9lmNZcVkF6T6YMfH7ngSdI/XD9FRqiPs0u7NlfxIwL1/T CJ7URJGOVd7D75LAann+i8hFbfSjQj3k+uskyJU6J8ZedgNp/p2PgaokOJF5 Keyiki6quRyWeu5ZEnwxrR3+sOcmOh7MmVfyIAncHVhvOc/oo+DW2kfHs5Pg lka+0Mk/hmiWVvt5UmISyITImxqfN0bX1Zaq9kYkAQ9++cP+Z6ZoLVbrX4lv EqyEBk4lqJqjh+9rFFWdk2C3jadKetECqVFzJK5YJ0F1t/KDlQortC4fMpR+ Kwmeak5Tlz+zQY9CZrkuaiVBz7URGZaxO0gdrt/+opQE8xR1/u4Kd9HGdnlZ iEwSXPClVdn+6YAeX2JdPymRBEuBan+tPJyRhrefbOepJFC93PaZlsMVbVZP RDtyJkESlYI536obKvql2M/EnAR5p8K4i/55IE3xZ8dqaZNgeapEREvRG205 Mlrc2kmEppXyxfE+X1T83OPp7q9EoGiq4T7yJABpL46tPlpIhI3anJh99sHo 3ynZy1e/JcKjn2amhZKhqNS6KGzpUyJMUYf+91MyHOk8ovuQ3JkIpaEHv6e4 R6LdCSeW882JEPXZhXxuOxo95Ro0Gq1OhNR9fV3jg3FI1+hSUcCzRCh5GJTG djAJUeTeW+Z5kEi8zxbZ3Jsp6NnwvgvtmYnweYuGq8M6DekdsQu0i08Ear0w y436DLTnRm87Q2giNFO6TTmaZKPnyZKHKr0Soa16s4nWNA/d7Mm5edMhEVCj zMHQjkJESb97b8siEfawa6Z80XuAXlyzmr+nnwgjP8xHqJIeIf2ojrMK6olQ H1pc38NWjPa1ifnMyyeC7VGxXZt/paiMMv1N/MVEqHIZDelUe44MZTf2i59J BKGqr8G+9OWIOtBEe5A/EVhXFvSipSvQf40tuT7siSCqsLVXrboKGW0ITnMy Et+HvP0tlViLaKQShd9SJcKXwzfPTfY2oAr3X242WwnwhkbCfC7qNTKu0H9F 9zMB+rCg6zoWbxDtStO+stkESDNnp7HqbEGVonxqN8YTgKaYz1k6rB2Z3I3O +NufAAOJF27xpXWg/U+Wv+S9SwDWhrwD/3Y+oKpZbQHZpgS4rCyjft+qD5ny 1zl+r0iA4cbisFDvj4jOgrM2ujQBnvH+7vao+4TMv8wp96clQPzWFf+9j0cR /XG1ZI+YBAirq10fvTyO6vQrRo4FJcA3k/W2opGvyDKTjee1ewLUciXLmlRP IIZP/rYWdgnAa83zeXdlEtUfnvqP2ozIb44s8pRtGllpKG8+1U2AuHHRWWq+ 7+hQwnM5jesJcP2q4c8whhnU0Hk47pdsAlQr6UrdG55B1rReA1kXEoBvd0xg IWAWMSqNH5cRSQB0pu3aO8o51Bh2xWqCJwGcQiwv0dvOIZs3xc/D2RLg0oEG 5sCqOXR498AfwYMJIDBML2i+MIdeybhg3ZQJYD3/yeMI/Ty64zsU4bIeD2O8 9Xbd3POIue5yzxFSPHytOSNtIjyPPugbR939Hg+Dt9/z0p+ZR5EbgbJvxuKB KWuIX5jAsrn3N1j742Hgz7vFStF5tHnpbYX9u3iIm07iVRKZR1Wfp+++bYqH UtEsL3ECO/pTnTxaFQ9Pehnjg8TmkSDnqa8OT+NBVj5x7t+5eTTVdDWr5X48 MOe9vKyMzaN8EzvNY1nxcODnl9IulXmktxu33ykhHpS0KWeHjeYR4/0Xb1vD 4uE0arua5zaPOmV7/dh9ifhWB1tEkuZR+OSKpLNzPBg83PcrsWwe4aFMpDab eJA8XWZV+WkerfNKlhw3jgebklyBgJ15VNGia+ZyIx6aHnf2vxVZQPZWXsfe XSNwkzOXpukCEqDK+cghGw8OphXccxkLKFdpXOG9SDykmhjtZ2RYRDpz//5x 8sXDlsXn9n/qi4gh+kSt27F4oJAtFHyZuohCOiyETlDHQ0HL5c/vuH+gS3bh U+7bccAbYZlnZPcD/aYrzutcjQOdPXoS9NU/0B3VhYOe3+Lg0c3VoPnrS0iz 12n1Q10clFkHJ/q7LiM655RnvGVxcGt8tXSldhm1MlZaeRfFQSVvQdTg5jIK /O8TZ09eHITX8XG0XCIhae21Ib7UOJhb/x6p70VCq6tsyT7RcbBs1qyMlZPQ 87SL13oD44COLkaLd4aEbCRvUZ70iIOdgyFbb4+Q0YlB/0bfu3Fwkv5M68wV MhrxKHTvM4+D9rtDM0a2ZJTK2iwqoB8HThN1VdTxZKRaOznrpx4HY6Otrd1P yIhaf+/9foU4mLGlHit9S0bN6/wGpy4T57e8ez93iIx8c5SYAsTjwHHkpfh/ M2QkeelO18dTcZDS3+pItUJGpLGYcEEuIr8U6TMNf8io1O8ZFsgSByU3/tPe WiMjC47utQG6OBDeEa3d/kVGHE2kMqE9cXB8VIJnY4mMhowZbYP+xsKx1tBj 4lNklLwjzju4HAvuYd3vFwbISOXejc+nv8cCzY/10btEfvtkPdKDx2IhIfah DeVLMno9kak21BcLYjf+rG5kkpF3SB21yLtYQFljAfcCyEiCdwxCmmKhe7Oy BFmQUbElp4To01hgZb14OF+AjBJmH7GGh8WCabKzie8jEooPTj5E5xMLPRfH psYCCcweQJvsGAupgb6R6oYEVtfbzDOIhX1erYq2TASel/vFoxELX9rfcwST l1Fc6JmlEoVYoLMor4npXkaxNbRfK8/EwrcqzgiOBAJr/hm6eDIWqo+ZZS47 LqOYxcleYI8FLswj/4r2MooO73mvyBgL9lkL3eJSBOZqfNNFReS7xyJhgJPA dSUNWlsxkNay81SaehlFaadXDq/EwFnfvMdOK0socin4ufFsDGRWlEyHjRM4 0qFo+jOBnb+uB3QSmNuw0LY/Bv5uaHyybFhCEQ1KWeT2GPhE829D+vkSCtc5 l+zxKgYOJw9U7NwjMOlEzNZ/MfCap+dSVQaBo+lDQ0pi4MGfm4t6CQTm3fCl KYgBw5xqo6lIAr+acUtIjYEMsY9pmqFLKEzvoz1zdAxEJF1iyw1aQqErr61z AmLA4uDM4ZpAAsc+MznhFgNhk+L2/7/On32z6E4MIIHB6cvE/0Nfh2sKm8TA qcEWnkQifqi+y7X/bsTAiana7rD4JRSyaiwndS0GPqpk3GdIX0LB8SqXm/AY aPFrdD9RQGABKUl5yRi4eW6vXnEJgZv5RDuEYqB1azIptXIJBRkyCmiciIHo J8WNH5uXUODvba5BlhjIvefYrdNL4MQFtlt0MfDLw5GH+huBBYcYJ3ejoZD3 dfQAmcBv3+6//ScawpwO6j3Zs4wC1vK2XCeioflYtwKn4DLyT47+vT4YDTnX uulSZQh82mM5sCsayqx2815pEdhE/VtsTTQI3K2N+xKwjHzbKVoexkcD7bdD X36OEdhsuVEwNBo2QjI0GlaXkc/maNVLr2j41DDVEE9HQt5ilcUNFtFwwUgz d/siCXlmWsd+lI4G8cVc4a8ZBD6rHaYvFg35Os2Wnc9IyKMT9//KFw2M/FJ7 hd6QkPsOm+MiQzRUV+Q82V0gcPa+2877omFlrk/i1j8CS/w0XduIgm/ra3Ir h8jIzaZTi3ImCnwOFDzPkSCj9Ixu3fqxKFjU83TWkiOjqtY+A+e+KMhoilnj 0yKjwV8Dxqfao4BuXPkpnSkZrfEOm39tjAIKyWo2CnsyYtUes874LwrGufWX dr3ISCrki61qSRTwCmBr1GFkpF8+4bC3IAry6PV5mBOI9/1t2qUhNQpMTIPd +Ij3nsMw5+ESHQVcXGLU0oVk1IAt+ggGRkHAjtOuVhEZjdkvB3xzI+Ktcca4 PSOjrbyVkEzbKFirJrXfKyf4qOtXhJppFGRRHOsaqyIjmc21mH26UaBoQh0r VEdGxkKbCY0qUQCUJt0pDWQUqP8vxVU2Cv7EVpxkf0VGhVEUmUIXooCW4u/n DgJDzd7cCeEomL8mO1VK4IkZ6sIsnijInLNohUYyojhC91CdLQqilH9lsRHx eBQOFlMdjAKxpYNL9bVkJOfG+PQVZRT8DFNsKCfysXjI/NJtPRL+te7Ro/6P jML6WStOkyIBk7Y1bntORo8p2GsmpyOB58/fJ+slZNR6hrMhezQSRFU2rjx7 SPB7It9b6rZI0KV9+reBqJdAk0B7U0MkvPZpDhNLJiPlJaFO9/JImB37xqUe Q0bRKmc/TuVFwqpczkCTLxk98Tk3lJMSCY9EvzfxuZFRZ+mFMc2oSPC/Iqlo fpeMDtBgU69dI0Hy6ung+FtklNhybTX3WiQ0XILJqstk9HJVdU0LRcJc8DnP xXNk1MujuUl7PhLkTsWfkRMhI8ZgPUov7ki4dS7XxZOTjMTLDKjFWCPhv5r7 J81ZyUj7qxHdzIFI0Lk1pBVL9F+ajCXTjb8RUHLNoLeMkui3uzasdMsRMDRI s1KzTUKfcm3Z30xFwFjvi1NMf0noT4c9l/dIBAQcOd3X9pOEWDeceM/0RECy iePI4BIJXRB0E5htiQB2yvk2xXkSunnT83RBfQRMNWVVH/1OvK9IHzGdsghQ ch421pogoexqf4kDRRFQnHmAcXWchOq/B114mxsB/SaGDdujJDTGHHbJJzkC aILGFlyHSWhTLhI/GxkBFPc7PugOktBx1xi5Ob8IIIukShYPkJDMg3ilQpcI 0OuxzLb6SEJGfUkqurcjIOajK1tKPwkF7Kaq0xtHQOf6Iz9hAheKZWq3aEfA fV5amXME7mnWfSd8jcDCl5XyCfxP+4hMOoqAYdOLbRZEPJGZT+Xb5yOAaVUp LYLYz8gr/aS1SAQ8+DZ1Yy+RT/x+ndxuXqKezeAxNkRCjXnMhy4ciwBvjhzJ /cR5FkUHwgoPRYCYin1ewmcSYm9OXaemjoDQR66R1l9JSEVb28FpOxxyJCiK EidJyOf74anh1XBYdBrxoyb0Sqlnv57sQjjwcFLf7iTqO0Kb0lX6LRyK7c/m DxP1p8nTlD08FA5FV1NFhIn7uSDKWO3zIRze+UnQvP1DQhlaSYUq9eEgbo/q n++SUOu0OnNlWTgM6l4f3thHRr89GKKPF4cDg+ulfn86ol9yE1yWUsPBoL1k +AjRP4zTcQqJ9uGgc3Y6/fQZMop3j17sPxEOhRMcPg7WZPSK+qrpJdZw4P7G 5qlC8NGPbJpPD+kJvBH1g4vod5WmyCa3jTCoXio8cC+YjGipI5KPDIQBV0Fe U0YuGUlnK1AFdoSB7A/f9nf3yej26X2+sxAGa43mO5+KyahdPcyy9nkYdB5/ 2eFeQUZ/JuRGTjwKgy+vzmTuIfiF341SLTqHWK8WoDFpIt53VsgFg8gwyMuO +uj3jowqhK48e+NPxI+yjpP+QEZTjRTcp93CIJBrs6Sxj4wOqzenp9qGAY3s lMzeQTKSnQjav2UaBgJFjDEHR8nI2RUFWuqFgbG499rIOBnd27e72qUaBkG1 +exWE2TUk/n6tqR8GCScYat9MU1GO4KB4/kXw+C+N31D1SwZiTViWlRnw2DF RBL3XiD4UO1fm4NAGHwu5Yv7+4Oo57dXl4Y4wmAil+WIBImop4t/Gc4cBuej 1vxPEfpwaa8Mf8n+MEi59DFp+CcZHc/cyj5EEQYvbeuV5Ag9qCLYeNB7LRSY aSnbb/8m9GaDb+jEUijUFD01ukroSbIilZTPVCiwNXblkghs1Z/04/BIKFTj rYKKhL4cNWK//7Q7FD6+bmBQI7D6/GMd+ZZQODvoEUtD4Ba3M/vH60IhBHM5 6En8X3q3vsn9ZSi0bJ+6nEvs9zJWwfXg41D4ZLA860Hkw8faK1CcEwpcFPcP H1glo+wHBp/xpFCYmUubu0Wch0H0e9JweCh4v9tssiPOG1bnqODsGwrO8qGM lwg9uy6/sU7rHAo0qhD4gaiXQ2/YiwfWoZC4/14H/xxxf4YMFpduhcK6wIs+ xe9k9MGFr+uuUiiMFT1gJ30hoyv/XgTtkwkFI8XsAr8xMqqJlpYsEA+FD+4W N78Sevz+PbWCHo5QcNTSf322l4w8ur2cxH+FgJ5vBJPtazLiEvrA/PdeCHx6 WaYpTvRnWpXe+6SMEBCgGTj6IoPoX9lJf8G4ENj8Y2wimUJGq3prMwaeITCq bfrYJZro36ng3NW7IWDtwpEiGk5G4w4HNOLMQ6Dah6mfguj/d+Hcda9UQ4Ar 6DPHOjGvZRif2evKhUD+sV4NHneiX/PO85CkQkCqW5bX3pmM8itUYk/whUB9 XMcrJ8KPHMYH8bqjIUDrdbFNxIaMIjtMf2kyhIDkvZglZkuiXyfcjUI3guGF ShrcNiajmbu7jMfJwZB2jO3lsCEZGf6Naav8HgyVrzllvfWJeRLK4qs6FgxB aWdbVfTISIHhnthMbzC4wNnbmjpkVJ8jNB3QFgwFsiKSsdpEP5+symJtDAal HYxlQ5OYn+W4all5MIjtCe0p0CCjYzIdFFeLg6G1moPWR52YZ+9uVE/kBRN8 hyvEqRH+48ZXW5+UYLD6d/37J1Uy8vl6h4spKhh8En+d0iMwyfbXx6f+waC7 HSB6iMCWfwKi5F2J7wPWf+5eJ/xZMK3M+O1g+B4QpiVIrKvRp624GwcDpdh7 mmgCv83iLDp4Ixjyw0XLuYj9lCKtOm9eC4bpBlvHcQJ3uj8jP0DBsMA+ydxB 5KduucqydD4YGn+fpPpO5P9R6+KlCyLBsKPQniRC6C892WDTYN5gmKweWnxA nH9M7F1459FgyB1VkZIn6mPCyfCU5VAw6LMnBB8i6jd5QLfXhCoYcJ+eV1RE fTt/Sy1o/Q0CK/Gubn6i/h/7287NTgfBk3TmkLtGRD/HTb5naAoC4aOmj+3M yWjxjhPzoydBcDSsRJPbiugvxX/GUplBECoudmyduO89FMd+mToFQfyBmjoa B6IfvxRjv28Fgei5egUZol8YGySjo68GQW2ah348wb/c7pqc//EEwWZ686QX oUdk56OUKT8FQmGRlYYyoVcC+9byHksHQobnx6ydUqKfXoTPSp8MBKn900d3 CH2UGMsk3n04ENBnNul1Qu8VKoi1/1kMgNtih+IHCP5tqrNeUSoIgFkZqq4F gm9bM35d+hwTAG4xYUEhXcT7dA2JcPIMgOVVmUpK4r2NixSwZ2sEAE/vXFw9 wbff9wtbi8gEwAP2Lwo/Rgi+m60raxYMgP1KR0p2PpPR9v1PCgt7AiB9Ufxo yyTRP4EWSQEkfyCTzR45E++f/tbK6OHP/lCuee7jOsG3LNKB/MXv/CEf+4/O kOCP40fonS5V+YNbgX5rKsG3vKs59T33/UGUbjH6wTIZne49tc8ywR9Cp078 CScTfvd5tfpfHyIeiqi/TPDtpRj5nDgbf8g9RM5tJfhMzqZ/+sQNf1Bxs3Dj IvhPRd5UrAr5g2W8l8T/+Fabe9n7qog/IOqlL7IEfxr+820ZP+oP+2jxVJq/ hB4do2VwofKHnUq6sDwC29Vm6lOt+sFxcd+tLQK7pvM/yvnqB5T0aSaC68T7 cKlYFu3yA6m9oae4CUx/ZaiWt8YP1r6rW3wmvr/PuBnC9sAP+p5Rrt4k8LkJ TlX6eD/YepCelEHs3152hXWPlx9QBwiwphP5GQRZT/wx9wPXF3RhN4j8l9Rj ni6qEvu/mv0zQJwviOuF+zcpP7DQ1ys/QpyfidSHf+L1g/O2r44cI+pT1PSb tuMgEc9677OvBF9LJxwdaFr3BRMNHtbbi8R9G8kUVEz7QuWVNM5Kgq9NRcxu l/T4woLHl5IW4r5Wt8LE8+t9Yat3pSGHuM/IrpKt5Me+0Hrvkt+Fr2T03I6c 5OvrC7IB+053EHyNLjEbOln7Qmb1pV9vPhLvZ78Uv5WmL+wM63FG9ZDRRmlg nZqAL7i7qTgFtBHvfe7gJPdHH/BOp8A1CL0/WiP+7EiTD8TsHg/9RvgX+0hd D7pSH6C8p8GvSuiLtJMF+38HENi880cLwfcTliIS74R8oNUmwdg1lPBr5zS3 G1l8YOWFyrKQP+EH9rq3l+96w3jA1Zl+DzISfdhomDvoDUc2FCr+3SHm74RK mEOIN9iqpIwfIvjkYLmjmoW9N0iUMORnXCXuKyiV7eZNb7ikuHqGh/B777jG nsmKeoOa4EUbnfNE/xrbfmIe9YJRnfgENw4yKhFJKKRt9YJfXLdjnQk9dmm7 /M6/l14QZv2vPIqRjMzz1rdnw70gY6L060EqQs/Zcbz77OQFmbcveYQQei/6 kmxKn6EX0Kj90T66SUIvR6NONpz1ghH7CqM6MgldefKM/PK4F0xW1uW1LRL6 37u3/hG1F4wXVintEPpzk41NPWHcE2QfdcpvEHo9Ye7S0dB3nqB0Xv8ojJAQ d63JlGeFJ0Sw/DCq/URCynrFnmbRnmB4PMFcsZuEODT/6tW6eQLzx1bz5Q4S Wr12VYrB1BNuRU1Ed7WT0Dv5HDZrFU/wOepHOdlCQvnY4t/G854QZTs1I0b4 a1epyyNMPJ5gp/HlfM1rIr54fJ0tvScMH7CZ8HpFxBf+kt381wOUeApfuzcQ 8fnFfNimPeDUmHn6izoSes8VZODY4wERllqMfLUkVHC072JbvQe4Oft3DVYT 8Zl42DmKPKBXyv1aexUJXaV33XRN9oCaY9t/f1eSEBd1y1iHnwdQsrGdsSDw r13mRu7bHtC8f/4sA4Hfb1jleWl7wCh9vNBGBeEvflX79WAeILIreoaPWHdf pjY6KeQBnvUUcvEEvjZ3U8afxQOObtCrShL7cU2WcgzsuoNwhi/PcSKf32Mb 20I/3IGb93qwbA0JdXxS+RI85A4xwumMj4n8C3vymobfuMNzy1grxXoi/vul ArEX7lBhZLbO10jEf4sFRmS7gxDXMwnURMR/lWgyHuYOdf4iVplAxK/+hp9z cocPEnzvBd8S8cvOnog1dIfFLJvwP61E/CchuxOK7vC62e3J1jsi/qOP36TE 3cH1zTOJS11E/AK+5kQOd7j6OIq6vIeIl9wWLPPLDWblw5plCP/TGctqnvbV DWQ0P9FrjZHQvfDbVxY73ICnNNc5639+x3s/ZfZ9Nzg7IelcNUesm6qF/VJz gydzys0UhP90Nyi0VLnoBvGKYu1eewh+vUGWf8DvBjPStNNMNER/K6Xs09hy hYruvUdeMBHrYoMRT0tdoTjZd+qcMDHvBAVs9qS7gu9q0f1EccIv8Hgp6Qe5 wofpl8ZbUsT7O3KMhlrPFfqTI/spFIn1baNo872uQIFlmLqZEutd32OPmriA b6rSi4I0gh/iXqp+VHGBV/aTbi45BF9d92aIl3IBnYwrT87cI/ik60DqLqML 0KoWRVk8JfgubvBG/T9n4G6Z7vlYRsyD6/eOuC06Q6ssdwt/NcGXXRI5sy3O 0O70+Yw1kJFw3Lbh/XJnOPzggK9GK6E/r7dzGBY4w/lJQ1bmDmLedRnc7/Z0 Blu9++pcBP/9jeWziLJ0hkcxPXQWBD8uqizzXdF0BsWQfbe8CL3b2xlcUiXk DGbno0IPTRF6KFbF1pHVGeZ9B6YSZ8ioWoVFWHCvM3TpPFkcmScjzSOvRlu+ OUGXbiLVEjEfL2RoGEvVOwFf1WxZO6HPOY5MTzxNdYIZkw9et4l5QJnhacVl 7wTqnsH/PhB6f56Fbj5F0Qlcz9z8/YeYL93pBXepTjjBHpsjfJPEPKpgESd7 rzvCBdVGq4QNwg+kt7ou9TtCV9JO6cYmoT9Y9NdMnznCSm/Zb/5twp+k//AZ CHeE+KvWFgz/iPtlCfqnZOIIDLQ9vNUEPpvOFNIg5Qh8bKcDju6QEStL8T6x w45Q65HcK0Xg7bSL0Q8WHWAX109iIvAUc/eBI60OIDKtca2U+P/7NLOk6AIH 6J5Zf7BO7PeS+TfTtqcDeLGC7l4Cp6dFZTppOsDjNe6L74n8fJmPs08LOcBN vnJpZSJ/s7SXBXp7HUBPTd4gmDifErMcT+e4PdjEddW6EecXTht8jNXYw7+z djE8RH0YmW0F/0uyB94Y7eOxhP9ZS91+xm9rD04WhR9fEPpjnCn5TLacPXy2 ExZJIObn21S+ygMc9sC478YrQWJ+ljLVXgj6cxdieuvEQgh/mZiq0rDacxdO tS0pZn0j9EWqy5vRkLvgBKFfdol+kGWiUlS7dRfU8o20dYh+EUjNft8seRcE v+/Tsesm5m8K9JbM2cHfwbGeb28JPX34xo3jb+zgAVf61BXCP79OmR1KzLUD q+1DtXa1ZBSTcvCrh5odfHn7pJiVmJ+Ohx+YLwjYwXXnGnL+YzLSSZGcMaKw g57GtRsrBcT7S7m1JF9pC2sVFn5UyWRUl/xk8/AxW2CmU2zgdCWjqj93ApTI d+DU5ZG6DMLP/GcoSOHXdge2vpjLfTcjo6f8JVTfXe5ARITx5P/mZ0HdY8aa ztvQ9ImXckWIjEIn7gkY+ttA5uXzYybEPApSNH2SqG0D4mKcSZkfScj/KZdI i6ANjB8J5Bt4T0Ie7gXiIoPWcOvRMX8bgl/v0ObJ7IhaA6uwirViEgmpnc3U fvjNEqgf79975SrBTxm6g0PVllB9ejL3kCwJKW2y6B+ItwSnWYcVemkSkm1N M3aXtoRIRe3QfEESkhG6MVHKYAnfvwktS/CQ0MVEJssv3y1AdGzLhYKdhCT0 U+4opVjAe7luh6v0JCTWpPnD97YF+Mt5xLVTkZAwL6NjGWYBup+nDoXtLiP+ pUS3o4vmkPtsdrDp1zLi0VJfU202B+1hITFEWkZcNQd9QjLNYTjxIjvVwjJi C44PXJQzB7EJewarb8uIZeb6nhPHzOHsz8ys3bFlxKhyIPwG2Qyc3xvVfB9a RgfLOqmj28xAyTLWj2VgGdGxxMa8yjODRtOw70m9y4ja5xr9TxczKL+p//nm h2W09ytt0smrZqDb+98Fh45lRCH//rAhlxl0BGbV97Uvo3WNQ0KcC6bwZj6T Oax1Ga0eSxSLzDAFyaqMifC3y+jHNL0k+YopOI50lA41L6PvL+Iu6pNMQF6v ZMIbltFXLzr0JtcE5G7Nz999vYyGr8QonFY2Ae6SAIbypmXUd4BWJe2XMUQe DopVJHDnYKTG9j1j+NYqECpC4JZ7VLrWqsZQX/KJ2prAEqG3Jwx2jMCSX+/2 NIEfWnXcVS83AtHA012lRHwmZeG/chZGwE1tebia2D9EKCFUisUIvg//3k/7 ZhmtHCAfFGm/BZQ7jz0eEPmbkTRzuL1vgcQBeuoQ4nx9fRX8R07fAvrOVONi 4vyokqV8/7ghbLmHHTpM1OdlhuflnQRDYO9dvtfcRdyX90j7KjIEBZGGsKqe ZZRoeEl77qcBcJ58xr3Uv4z+yeR/+fzIAARYzLptBpeR/YmdO326BpB34Vo/ 3+gyGt9j9ruVxgD2anVa8X5ZRo3tfAde3tUH7GVF38TMMjr9JCLzIac++Ndm 9hQuLqPcuDmerN6bsJ+WuSSXvIx8NJ9JB5+7CeUqnonKm8toXuJgq/uMHqgE xV5fI/pN/4iThm2WHpiXfkBfiX6UGpOw0d7ShVtVLdE6TCRU/Cr9p9ILXcjd fMs6cZSEWO+t+V821YWBl2/V750goT+WDWn8LTrQ3pWfWiFKQpXLV96sxd4A l5T7MjvXSYi375HqD5kbYJW7pbVxg4RSK6hGvpG0IWYev8VuREIuXh2k99ra cL26y7PdnoTO7NHiyGPXAlDG3ROI96kn1EwK1FEDnZq/+vOE3jxPCqO6U6cK Qn+yL16ZIiGWSmUOLQ5VUJKxO5j/g4Q+yvRe4/uuAn9/afup7ZCQuubXx+/c rsJUwxCzPh/B117bhoxp8iCmzfDyA8E/FxKF+Og25UDxlMz5BReCL4v0fuw1 lwOFvGcJEz5kRDNQ7vdX7Aqc9YZUPcIvry98kf+ZIQvDWjWtfQS/9e1hPTq0 geC1BfaJI5uMUow7pZsyMJhySaPiJfyFaxx/R7mlDGxsle8ZJvy0dn2gwWPx yyBtWZCiW0no/SPnfOO6paH2xf7qEkIP/JZLoAvKk4LaTplUL8LPDDrP5bra XoAX/hez9xN+OvNDXqMBlSSo08ndcSD8s+fmn+tqAxKQyqayT4aY/zcFNcdl H4jD22eJju2En5LWe2ov6XQWVG9oyB4g5sdZ2v2bGr5i8Oqswqn9xHz5adnE LsUqArnJCrOviflTAS6XuSqE4G4M6AoT89/9uIARlfop2B8jZ6VGzP/zXmP+ Swv8kNLDysZP+Me1j4kFAxG88NwuKfYl4TdrxeRfN/BwA+VG5OoPwq+usJCb 5P2OA5Vxc+5nYp66fbi5e7iSFQZqpeb8iXn7J6xZdmLxMMR+N9bpJeYz2VN7 n7EiHXwW8fL6SMzv3zN8URtVFDBz78VOxC7hz24MntJPXXod8fnGfwsE5pjo yLlrMoDfbx13+kfgnZzeCfP1v/iPuSOSbwi8aZzpkB5PhXwd9hw+T+A1Uuvi X45D6I/NtIQBEX8dNipf6LGgc+cvfBMl9vekTXH9xnUMxVvauf9fxeYdT9Ub x3GyRSSkQrYyyso+56s0rIwSZW/Ze++9uTbXzMhokIRsIkIlW0ZSRsa9QqKh 3/n9+X2dc5/nOd/zPJ/353Ndz39j82ufEz++wgEvKSbt1jD+vxz65PNAnxt0 Bly1RjH+77sK6ze38EJ0eNxbZ4z/0iw+0qNnBSCWP7qsDcvTXi+7WTYizsHv 4+GPO7H8XG987Af5qhC0mH0e88Xy8w6pwRiHhiicm//Bu4L5MYmH5c+lay/C tWrLBjrMr9314ZSTUpQAl5ATUeGzRPBV7alUcpaEax0E6/FJImSfsWe7WSwF Y/JKI18x3k90vPhpTS4DkWJebtCP9TfV0NZdWhYUA+a+JmG8Z7YinQy+Lwel ISaWRa1EuE19syF7SAE+jil3MNVi+/XjNn/ZoSJc8wyw8K0iQtrjnMxaMRTU Nt7iK0uIcP+ce7OVmhKUls9tuWZg+XSoLTfo6RVwZ64bn8XysBH357EQXWVI KIii4HHC/I83OWP4L2WYUQ89hlhhfuqsenT09WuwIZleSHKLCBruU+4p8zdg 0gJmmESw/XJyR/3BsZtw+JSE5OQcAcocWWNK629CcH1uxLlRAtzrkusuN9AE jzh8nxKWJ7vtQ2WrH2pBSk7j3VSM7wPz0Wn3zuqA24olKRmmHwXizCEWjbfB XGjlaNQNAuzPlOdb0uqC7PYFogYQ4Fa0TLOVsS6cyH147ZoMAShnDH7YkN0B UtrauveCBDCL2mC6r3cHPPKNPlhzEaDlYrCYXRV2nX3XXeoUAVwjHzg4aOmB e2JzQvhRbP4LknGOJXrgWXkQQIHpKd90z0OnH3pwlunDQt/hJkyLrn52ydOH fb71C8cxvktN+f1zJejD25+Bf/CbGB/Cj3K4X74LPxLPUtmvbsKVyQt3PVfu wmtLj8HZ+U3ID+v08pK/B0Im8CEc4/ue8K1076R74LMh8dgd47v2xJdan4V7 cIZJ/taTkU14FOr1zlfSAAKO/iyX/J/vwlQbftEGIAnV3pQY383Gc2gCpg3g mSISKoDxqzlESDBQxBDUA6QdMjC+MQu1Xg0KMQTdzrIhbYx/zmM3LYJHDCHJ QFrACONjf/CnkBB+I8iqkV9uwPjOc96tINQXq+cibM0xvgaNHmkJGzQChcOI 74YYf6eCMqbCOY2hikO16eH/vD4nsBfhZgxaol6zl7E6caTxRFSPMXCrajqI YvVyoKp49EkTQLIbTez+5/+x/f7fViZAkkFo/4bVT4sfmrnVmQD3EvlqDTZ+ msSd/eV/JlDzO6SiBZvfp4cMZ3TTFK5KK7fSYXw30qsTHMGbwukb5RMl2PqV Vs06bqyagmuNcU4Q9nxMbTGP5k+bgWlXYUY+9vzklKY+uZfNYCPopPa/fqzf mtLKuvfNIED5r1I5xvfVbHoGhhQzKJtlfp+E8f3jwtePb16YQX98x+0mjO9D 51sfRs6agSzD/ik+jO/t7unuQGYOIp/cTYanNqG2xR79dd4cjOsearXObkLG zVMTLj7mELb6t1oL43t01tYDoUJzeHTWSPgH5vd8P/U5LfWYgxxuJ3IC84NG bt4UhkwW0A5LeioHm6DZfPMDi5wFZLMaeU9g+02JjL9g2NQC+Jtz2/LIsf2Y OSp1/YkFaFUvBr5mxHg+X01COmYBVBHpYudPEoBaMHyo5ZcFBLZWRbRxEGCj ScxKXMUSVjopvnsKE6B+Nimd/YslZMuq475jfvkhv7XpJI0VbPk6X6nXJkCO s6JwmpgVUHKRCeXdxfw4yXo3VbAVxFnjaN/dJ8BVPpXtbTZroKJL38TFE2Dc 4YjOG00bcPsl8r7+AwH666fZI71sgCjCT937kQDNf2tX0XwbULM+cXfyCwEK U0xD679h1ynKlvZ/EMDmeWtNUaQtfFGd2dw8hen7L+9j3s33oYCCaTvNhAgf THhmXL7eh2uM+f53bYnwuPtthd0xO8gOnFvedSGCZTzfZWMLO+hERvEVoURA Ce/p9RPtYOHkSmFTLBFO3wr4qN1gB6dtNkmz/uf9qRGPq7T24JFrcPIxlv8f BQUpoVL2IHkq4cQCxvvoz+foZU3sQRSJIZ98QgSkKuShcJ09rC/ZXadoIQIb vbAH/6w93NhdTpftwvjiOgFnKR3gGd7qg0Afln9kRaeZDBzA0hwvIYrpeVT+ VDldpAMMnKAWvILpvRlJpDvlUwdg78A9PYrxQNHqIpBMOYAtfsc/doEIJ/s/ Hv1F6gjbYilGjf9/3yocPbUj7Aiul4WVszG+vEsRL9+84wgFc/aoIMafqp1Z t5UQR7j9wS7YBuNTpH4s+rnKEWLXeHR1MX6ZtkgenRl1hBieMfEtjPfyZz9N jv11hLh/1x/JYfxjjYgveyfoBDp9TN5iGB+/L19y69dxAo0jrXZjGO+H1D4j 3QFOUPK8J4Qf433l00Ta1nIn4F97McqL8TaCSXbyxXsneEP7o+R//pt4fymt OXCChfvdGucxPst9THat4nUG7StDOuJYzYzKI6U3naF2+ITuKnb/1oMlmgIf ZyCtusWqhdWDFKkTWQ+coZu9JcAGm++hnWIpbtAZOnR0Yy5iPA9/u+IS/8MZ jrRaGj7C1mssnq4YedYFZLpey/7/fbpsJkoTrOoCTKaywZ0Yz08cfBv38XAB JcfcCiMszxOMMkvcClwgzuebxjMszw90Krk49LmAxY1E7k4sz5fzbShYf3eB o3fu7cRjfkqpRz2yht4VZoXtqk5gfuuC9wP7xzyu4BElo2yE+TGajxoyDzVc gWzjVPqlGWz/JpRwlJq7gmvXm8YBLM9/RfbJir1dQWmeNe8cth86H5QO5xa7 QtdvBS0VjO/edr/sknZdIfKq1aBJHRGszmhrx9O4QUN9S2Mo5jd13pZLx3C6 wStcrlIotj9FxHXIwlTcgN+lxY4XT4Qv+xX5nvlu8PWnyHk1bP8nhw47Mjxz A331tE99mP+Vpz5QrO51gxUq5Qh5DyLgTqrNfSK4gYI2VxiNDXZepDc41C+7 gw3+4BRenQhrbcyEpTvu0JL3ivToNSJkXkPaQ+3dQS4kUDEaJcKGbrJJAyaB Kl5jE+XiRMB7iBVxL7uDz5dbYe/YMH/++65L6y930Das4phkwvZTeBjoM3iA +Y97Cn/piKCSNvIpUdYDfkjnZ1aTYufn1O8awZseoO7av3/pDwGKHvCGdpt7 QLpmxvmVPQLs1Xpy7cd7gBb5u4TuDQKUyBZspRV5wKRwofHWCpb/O3s7Res9 wGJ6RlEd05ey96zmlnMe8GlwNi8Z0x9tfRA//O4B9Atwzn+CAL/nbUlzKT1B 3bH1Y84I5h8ITQ/eXfQEec7dHc9BAhx6fXazu+oJP+uM30j1E6DqL80V8nue gE/sfiDSSwDdKAmmIidPyE7mCjPuJgAJveGiXLgnpPs80OvvIMDjjIi6sSxP 4Au7+cepjQD67I/DXR55Ar06g4xWCwGOlI3dou30hMMxrwbHlwR4KvyXp3zM E+LY05j7Gglg8Jx/B755wsxTkgmTBgJQKGi++vjXE3YVntlJYf6otts73YvJ C9xJ5s6p1BPASK3IklHQC6gN6PTxzzH9H+mTfKTgBTKJR3iEsfr5vS2y69pe 4CNf+uBXHQFMPrONLVh5wYgl3xQ1dp3W7nJZgJ8X7G18fHYHqxu27DxZk70g 1NqU4jNWm/umXX1W4gUDXpnp1dh8dCQtzBqNXoDbbaCqw9bTFPPl6/KgFzxi tfm5h63XioHuRdiCF0zbflj0bSIAQ7ZUFPsPL2DNfSIl04zxgNP4TiONNxCP JV0Rb8X0/2EU/y1Ob+D3GtCwaScA04WnPzYkvMGueDV4vJMAbS8memNueMMl rkRi0CsC3Ef+ZfIYeYPX+GyxyWssP/YK2rS5eoPqL3yoN+YnOzS0pe9GeUNh YNT9niEC2I/5Uu7kYp83deO8MUyAri9vHp575Q36c8nVS5NYviz3yzSb8AYW qYrchhkCzNqcj8z55g27BK2y2k+Y3/wWa07N6ANXFm9Mnl4lgNjWDfZVIx8I WLxlXvyLAO3PftJyufqAfWw5kv6PABoeFQf6ET7w+1pjaCk55rf3KCf7qnxg 9b11OAsDEYr/9KZW7PlA5VcHxWP8mJ60e4V+ovGFA/Fbti1CRGgN4Xc5yeEL x9RfZPqIEWHqSJRGjLIvWFvlSLMoEoGB5iqVLc4Xfv3Q2nlymwjBLN2BAkJ+ cN2aUJkcTgS6STcHE8QPztMG2Slg/MPncBtkafuBF4kucSKJCA1nwmQoffxg 7HWi5wiWdwncSttLr/xg0k6C9yHGu8AvxAWOST+Q9ed8lI7pEW150fs7a35w Wu8Sn3kjlq/P/Xvcy+gPtP0zqpmdmP5eaLctN/aHmkRWNpkPmH4QnfTmXP3B CXcxcX8MyzvPOK6xRPrDKzYKmeQpIlB6vJW8me0PF26Kb+5hepkhFcQTVe0P rTu2WeKfiMCzJ3K8rc0fBD1FLiCLRKhtnP23O+wPtR3aPWxYnhqSV5yz+ukP Ej4/0hUxfTb4sz6YTxsAx+I89CMwHq625TWPcQRA8DPuC9lY/vUOUa+iE8fq w9cZPpjek1/+nX31agD8+0J5lg/jY9qRR9GB+gFA2dTmk4/xgavHwKvePgCY tcB84f/fx0TRWm0EBcAgi+kLIsYTxRvNt/hSA+Ab94j1AJaXUdaxrt/lAVAr 9fN0IMafy0ubYqPNAcBuY3V2C6uv1lMVV78PALrlug4BLE9fj+BmCP8aAFeu mNj9//dglVsKwfcOAgA3a1U9h92vzn1nU+xYIFB+OytuitWaW85G1LyBMHyr b7Acm0+7I3bwk0wgsPzjv1/3/9+rk0vkGzUCYWN0nSkaW+8d49aqZPNAuDXF 8fP/76/vikyw2XgHgveauXEMlv8NfhNjkIRAMBjWe9SI+QWjAZqfzMWB0G+Y bFGP8c80l9dmoz4QGOm+nw1Zx3gko381bz4QvqlBSdQyEWwo3Z677wSC/O/a s70Y/+zG43nUqINAw4mG6SPmX5w92kkOxINAVQHaEz9i77+Gv00vKghO/slU 0R3C8mMwiFzAB4H3uN18EMa/oJv38ihqgoBP6nxMSg/G9/VEv/qpIPhgqWPv heXbJMHdS0wiwTA+tv4w8xHGrz368m9KwXCh3OWxagX2/noFmbvuBIPxSPPp 31i+zbE03HYJCQbGh/w05hgfS4q6n74dCQZFTxqlyDgilDnPcpSvBIO9oX2e cxSWf5G9xMA/wTDiERrhEIb5y5nzDsICIcC7n7TwEONnw8lUwTi/EDA72bxn 7UCEpuXqLLPkEKCl0xERvE+Elhc9FLKlIbDQ5s5Db02E9sh5T4amEKC71j94 ygLj/e39L8tDIUCztUauZUqEbh6m2+2fQ+Cg/1b6UyMi9H4X7s7cCwHOizZ8 8gZYvxdKchooQkHbPUtjR58IS30XtXkYQzGuZkfP3MH6X9NKlXw6FBrJfSR2 sfO/mqXaccAXClfIiBkolsftgie8rS+GQqyoz0SLNnYerS0vfJALBeUPn444 aRHB4ebWkuLVUDj5yIT6tibGc6mggkrNUIiiOt/ofBN7f+y0d5jvhcK5yeLO Tg0iEMmy6UItQ0FulqRRFastYm1vyzuFAlvlt2Q6rB6jk8XveodCopLZ+v+/ 77meSv35aWgo4JqsfvJi15tYpgXt4kPhwyWBXl+sFsJXOfNmhILLMZubh1hd wOn/Yq4gFM54ZbrUY/Mzlqr9ya4IhckP/t/x2PrCBc8o33oWCjTnToc8w9a/ +2g9jq4lFIiROdU/seezFWsdft0TCkrdYhuO//++pz7xZNi7UAhrYith1CWC hpyxicJUKNxrjWVcxPrX3iZa/uNzKBxrHTVfwPorfuVwvWY9FIbDzB/SYv1n VS/y4/sXCuPS1gPzWP6Ife/SOU8dBlfEk9SizYnw+7YSVS5TGBQ2f/una0WE BaPPGfQCYVDZICtrYY/5f2fe2j2NMAg0F52l9yUC+87OXq1eGDTribzoCiBC ik8P4mAWBpdbfVuSQ4jgGWo9+MkjDGbODFc5xGB6klax3I8PA3JER38rG9M/ Vl/RiLIweFJBCBLNJwJvnoon8jQMGBUVn7sWE4G67BtpXVcY8GUJ5P3/+5+R F8IceathYH2d0mr9JaY/8n8s72yHAWuP5326diI0tg9VM/wJgxfpcsoc3UTI 73OSjWQIh6ULbvRkA9j+mq657SQdDlS6reEpmF5PGYfiBZXC4cPW9swnTK/V F7U/f1YNB4F7s1U0mF6323Cfy78dDmJsZWq0mF6LrX931jMOx3yGpcgnLL+U uHS/YLQNB5fx1XdRmH9m2U37M+AaDpqrD3t/f8P662upHOUfDjKjKy9RTL9/ /ZGMh8hweF1l6qiB6bdjGPmHg6RwkFa93ciD6fcnivGT9dnh0PXZANeB6dmt +HIT5wfhIBF/ifZ/ves55l1+7lE4xK9k6V3D9FA6/frGYn043Hsz3SeE6WXV yZOSBe3hsCjUPfIeq9nzV/z0+8Mh6tUagySmr8lcTZ3HR8Lh274fchurFxjc /+BnwoFCarlIDKvF/wnL8i2FA+HXP/wg9vlwwpLHE0I4hDrtuvBi9dhcUY30 fji0XJWNkcHmF3h7b72DNAJMm9PdqLD1+bSeEFQ9GgEn/71ZTcPW3//orcUI cwSQ2jsPT2N6fDovptCQMwIupVRIz2J67Bh/+eNXwQiovmKli8f0uM3vN4uz eAToTm8kMWP9O2b3QuenPHY/1xkPdUyfze66JIVejYCvCbkdgOnzsxvn39Bo RkC2aJXBNva+jsh8IU/XjwAP+tv6Vlj+LGfRDyy3jwC3+qLcBIzXe+THmy54 RgBcTZ5VHsb4tDuw0xgUAV9O+Ph3DWJ6MoI6DOAiwPz5cAIztn/EcAIGxIYI YKcy/nsXyyvhIQuZvp0RMP9CbNkPyyujzvgPpAMRYFgykOSB7Vfvm8dUmeci gNHi3d2/6Zjfod2TkSOLBHJumWevMb099qvGo5suEqqjGPyosbxi+s2uRp01 EkrX1U6hjtj6++cETM5Hgivj1vd07HzeiOplidCKBA/y0zt3lDH99wzRobsX CQIuiZsPML+0ZimXlGmBjR/G2UciTYTEK0/IK70iISpC8gPleey8/MvYGcqL BD6ypoViRiLwETUv6pVHwpHwCbctWiJ4zVM7fHoaCW1LtFZuFFj+bwtc/N4V CVy2+FiW35i/fCzNGTAYCWwiAimw9//vx7fukY9HwjLvAL7yO+a3/a0+sK5G whnNBPmr3zD/bsdJX/w9EtpNbVoClwhAem9K5fzvSLBce8FKsojlEZW0yDry KDCRe/hteB7LMzIanQrHouD4V4rq75g//SFA+afnZBS8XL1UZjVNgOusnTKa 3FEw1n3qQBjzszkU/h6TQlGQUS+YrzpOgG+7kjVmUlEwI5mo0zFKgN01nkcv 0SjII14l+GL5h+Tz8Qom1SiQUA8dL/iA+ftJklKH21GgdfFmwEWsZntLLOwx jgI5JQGq/2u+V/N4jvtR4OYzqP3//Rdfvs3ydo8Cw8OIOX9sPPma1rT3gVHQ bNk614fNd738UfK5mCiQ8WUTisTWcysPHx+WGgXLT/eUarD1mqTGRX/MiwJ+ xVllFSyv2cf4hks+jILeWNMfN+cI4BVkG5xYGwVJ6uca2hcIEOqh57/UHAX0 Tn4ROV8JkGh3zRvtjQLa8LrdKcyf55hKuWe/j4ILaKhc0CbWvzu8zlvTUVCj QsMWvo31X53JXvVrFLjIua9/+UmA1sukNiWEKLB/61hS+JcAo6KfjHXJosF7 pVqHDnv/87zv7j2hj4Z4/DLJC2x/rJ1qu0PJFg3D5ydISk5i+5Ey72aTSDS8 85jIvyiA7d8/carHZaLhpDxLQLcodp63fa/ZX44Gm+UtseBLmH7M6yHsetGg em+RQRvL12YNTKKhIdGgJ86oZIv5B8fHpOen46JB+e9y6k0nzD+VbPFJZEQD x/vMn0xeGD+S37F/rYyGWweMQoyRmL+PbGNDnkeDqMVlMokEIjz0f8yc1RYN LZrn2anS/tfneDqVkWg4/v5fYUEhEQaM/KgfzEaDZbeRhEoZEcZv3Sf/tRwN zvuI2/9/L1hQ0Se5/T0anCJ8aXmfYv4Avf7n0e9oWL+hPqyI5YF9qUv75JQx 0H3dsa/5Beanhfl2jRljgJn/onRaE8Zv7hNbDadjoCkwsb6pmQhnTh7ZYOCP gVKFNQU+zM8J0H9fuX8xBkYlu2UGsVqCbOFLl1wMRKfvZZZhNXrw7tPpqzFw 1XRjoqKFCGrEthkPzRi47WDK+Rbjmd7S48mhuzGYtMVcocfyiPlM3ii/ZQwk /703a/4c69+H+PfBTjFQwPXrTi+2ft8+v8FJnxhI9x7dl8CeL7Ltfp9YeAz0 LBj+foj5Rdxz/VdxiTFQrjCUyJmH8bDqesdiVgzMzVsuZGP9qyi61KLwIAZE qB/IMGH+sS6TrzHjUQxo6lGuJQVj/U048XzzRQwoDF51pMP0asLne3XRQAxc ej1qxXEP0z9aPukbYzEg9/RmbwPmj4YL9LoIczHAS4ywDkew9/GqZRL5HgMV f65p9nMSoU+PYLH0KwZo8NXPtI9hPPvGRUgkjwWO0dlwQWx/tjNEk8+ejAV6 XdaXS1OY3pQ0pURwx0ImnWD9514sj19aPy0sHAuhOcfk7mB5v85QW9wfjYVN RvFPo3EEKK84bcJmHQv3eCTyKqUIUCJ/81uHcyy8OxJVN8ZJgMK3IZ62vrGg z6vUvUqNnaedr/ENCbHw6mzLeZq5TUiEmkbduljwTLU2/xW9CXEjn6/8aYmF 9Seq3yTcNyHamvldaW8sSP+cz50y3oTQBL+v21OxMDJmt/ZUehOCOB+74Bdj IZml8JCEbxP8n83/urwRC9k1PAxkTJvgOal8PPUfNt/rmEP9rQ1ws/fOl6WJ A/T59IOBhQ1w/lspuMAUB3xnh5pERjbAATdTF8MeB4Vcn+4k9WzAfd5j6EWB OIjq/n3ud+MGWDcovZm4GAePBOe9Ix9vgIWqh26wXBz8PePMKFOyAaaz5Z/4 lePgNWqoxpW7AUYuU/ZvNeLgDbX2jkbqBtw7cnTPUy8O6Ieq1N/Eb4BeJhLG bhYHlvfP/yqO2oDb51zpeuziIAxlI/sUtgHaLSXZDh5xYCYk15IUsgE3Ncd5 TgTFge5V8bb//99T7TPV0+ZorK7jm7HArl/3lJezwMVB/epzRjz2eWUqpx4a fByMimV7WGLjK+GLtJ6VxkGN6RJ3Lza/oujIx7tP4uDKgOXFHmx9cp3kNiSN ccD44XyqFX4DpG/LfK/ojAPNvCHKqrINkFy2C9QaiAMe3PUj6bUbIOaXT/Vz NA6Gc48l8bRvgCjd+7TCuTiQJu8W1nu7AUJFpJzXV+KAP3WoXWh+AwQlpKo2 t7D1aCeZ52Hvg6/XRirzVxzE7dDceEC+CZzrg2pf6eOBx49X9ob4JpwJPhxP OBkP+DXy3neqm8B2XNxckjsemh5NX2m23AQmmSyfcKl4GHcsDHfJ24Q3w3+7 D9B4WL9kU5nRgu0Xe+tjbqrxwJZzQWVjdhOIBVLlpibxoPGt43ciDwGGyEdH FGPjQUDK6DHxOQEiCuU569Mwy+jhz8aPnQd52RI74YJ4iF1slGrB+Lz9geZF SUU8mKirF5th56vKwY3kdF08uJ4Fvw7A9JdiWj21NR5CVLPng7B8xlaklE3d Fw80gsK5aBAR3stWLoZ8iAc3jeK1BzlEiB5huPBzJh4kF/uirj8jAuLo4+e8 HA+sqVs1A6+xfELxqWdpKx4Gj7fEvMX88+Oi64zGv+Ohw1DObQvzZ5ZyTw3H KBLgXQ190RTmZ0+PslSoMybA7Vd+df/7yxHHoO3u0wnwaMPAoRqr4yiXEHn+ BHhP1nmXZJsISsUacc8uJoDLklL4T8xP/5SrHzsnnwB019l/mWHzPR09w1V8 NQGssv+pnXmF+XmnCIeTWgng0frm+QksH3BQrTck30sAHNlXvhtY3hgrvnWE 0ioBLK0kd7vNMH8k33wzyDkBFK4ZoeVSRFAe487d9U2ArptK39nJMH/uFPfV ISIBbGua/e2GCPCM6vvFL0kJcHYqlfsjjgD3H9wNMMhJgNhuM+q32gSYHBNk Un2SAKTDPeG7PZtQr/AaBCYTwHeul1CeiJ3fcdGEgs8J0FaZz8eisAE8LpkT zBsJYNGpwqD1bR1SS6ycyEgToai0wjPsxjqoKA41+R9NhLKm0pgH+2tAMiFJ vs2SCB6SN8enHq2BMw1Z3oJQIjjSZzwpOr0G/KX2y/qXEkH7EU8C/+Q3mFUc EX+Pqdg7odykJ9nfIGNCLui6WiIIlpymyDf6BuquD/rbdBOxeQrc1QS+wRFa GuZLpokQe1bOgPLHKjSXupo+tksEkwd3+xjerIIbMlXN65kIWcwaptklq1hu hj18cCJcYu6cbQlbhU+uFZeZ4hJBfze3N9pmFbJoGZLi0hOB+73n+VXtVdAs 854iKUyEPsOf4s+UVoECnef1rUwEEeJ11aRLq9A6ec2FWJcIXzuOlR5cWAVP tyfNNm2JIFr695+8yCoIH2WhnO9LhO/MncU6WL1YFqhzZyQRkg36c9dFVyF+ RlDkzGwiRJ542K96cRUkmUYpPy8lglzz4n4vNt6sSvDnh8REyMPbWasIrUJk yPlWx4NEGBQgfNM9uwoiDWNZEmRJWN8y1GmPrsL4RojbPl0S0A+zcQqtrUAw r7BGO2sSvCB9MSPycgUEDCYEIrmSIH5Ht8zacwXe4cJI1YSS4HuIP7Ms2wr4 9InMMkglgeGBmYzZg2XgOpxsGEeS4MGF5V4V+mXol4pIzbuRBHqDuas2Bkvg 6nDB0VwnCQaOvJpOiv0Kp0qmrwsaJgHxmXjb+dwv0D0Vyb1plQRlBymLOimL YM8g9qfOOQm+yr6zq3T5DEzXZyZ8fZOg01pdmUppAVoCo5+h4UnwT4Wq7+ix eaBbm7UZyEyCGsaHijqC01DPFXsZV5QEymS0rK8HJsBYX5JdryoJunav8JnH j8HTnrgPn1ux53Pwp+7yHga931KPK14nQfqrwTEz3bfwT3wh2mk4CQwYXxEs GAag8n6CueTHJLgt7BXawt4H2kXSigdfkiDkfTD3A98e2B//zNqxmQQRArYv /3J0QzFd0vfIn0lwYupi0yFlJ6goyw6pkSZDM/+T29SGrfDd78tDxqPJkBPZ 1bXI+hLwtclhE8zJAFGeH/ouNcCVFTmjfM5kIIQK8Dx+/BzWOJakLc4lw0Pa M2JWbs8gTRd3/JxEMtwb1iOx+/EU5BMUNjYVksHf1VqyPPQRfOlafv38WjKI OchqN3lVQuJ+6gM/rWQILRIwwvWVg9RFJBDuJUMB27JYtX0pzFqv6lFYJoPg q1m5dd0HEJWfLj7omAwbW85Je78K4cIoSpfqnQy7u//olV7mwQTN2rJeaDLc eU3BIz2ZA8FKmV3s8clAK9w+zKKaBYI+SvmL6clQHf9OrZA8A4afrHtXFiSD pZuK+SeSNPD9mqXjXJEMOi7jQ/TSOOA6c0VE6hn2fKfJa1/KJ8EbnU3KX83J wE7n2fHSPB7cY3M+d/Qkg0GNmmXrRAyc7lBujXqXDHU4JZ8aXBR0/yBkqU8l w/6VVbQkJgIcRPBuxxexftKG2hbVhwGz5TWNyfVkaD9DeyHxeCi05m4JFPxI BnN8+LeTEkFgNZxHavkvGS7M85q+T/QHeqobs+doUkA2kAO+C/lCA7LdQGBK ge1fPDPCFN5g4lmQWs+eAna1+640LJ5A+UjF0R+LjnnF9uljuu5Q83nnupJY CoxGlIiGdrjCXbYibkr5FIgkw/vwP3AGEi21P4PK2PhBQi7nqB0hdmt+0Oxm CvzuF6K70mQHDGkeeT/0UjBfcjR+tsAWsiSpHeLNUmAzn/Lps+fWwDmeL3/W PgXEs12ij/6whHJvcdp6jxRISH8+8dzYAkTYXk+rBKXA34cOEUvfzKD+pUHV XHQKCKgnpIeImIKCIdHXHZcCL20uUHl3GEH3nwgVKnwKGAnahCIxBqBWyMaW X5oCAZclOLaD78IHeLIi9iQF86MkWaIlenD38+XG3oYUeKzHVXWwoQsL4RPR Bp0pIK3GcKrH8DbY8jnoEd+kQJO/Eo3uug5422b8YJtLgY8mX5aGuzXhkPp8 75PlFCjJZWcej9KAqOq2jCtbKeBhSPoc9VYDOo1bVpMHKdC+YywlgFOBAe+d Uw2kOOiUek9DOnwdkvvawkIpcfDmhPytHIlroMMW+03tKA4YRVNjSF4ow9RL 9pefmHFwP8o8Z/HYZcinXeGqPoWDc5xzKsGvAMwMn8V6cuKAyKjteDMLAb7H AVsoLw6eJP+iS0hTgJU/1+7SnMNBd31CyOd6Oai+ydg5KoKDF4y8itd+yYBz 4UfBQnEcMAR82900lYY9cPkpoYCDHO/kcLZwSWjGyZn+BRyUe0y94ZOXgODP ZH19V3GgRPx1K4xGHK5IvLuQpooD/5OJ7X2zF4EiIifLSBMHK1r6YtrvRKF/ 1OJQ4DYOxmOvGed8FYZEPlGb7/o4eGQ2WzLDLgTMr7suRZtjzxeTK2X4TQCm WBMLtG1wEDbs++uUHz/k2+pRnHHAwfHAcIFhbj4wa+JyWnLBwZF3CW+qP/MA L836WI0nDh4cHiv73cANy/deKPr74WDrJAONdDEXVFeHlF0NxkHfmzu8UzJn QUKD2XM6Bgd1x956KCacgb38+ZnSRBwsCekdRi6egubNSmXnVBzMjL3SMb7D BsGoxyPZLBwgBQwnpj+zwuUU5ARZHg7a4of6xKJZgHyBKuBtEQ7ofWYm2pWY oV9sZDG7DHv+Q8OvfxhOgPaITZ3IUxzknfu1/GeZEZh5xU//rMNBu2LhjNsU A0x6/A7rasRBUoYAInTkGOB7er8ltOLAhRhJPKpKByYsOB29LhwkHJG7KvCI FnhsDF5yvcaB/FAC4ZEADSw38HGvD+BAG3eovvWSCpzuvtwKGcMBy9ZBajY3 BSSLFMrWTWPjHa2ncPxIBk9JIkK/zuNAw0x/3L/yCLwfs+1n/YoDPmuwVYsn ha1KDUbVbzhI2X0uGhRMAseDxO8GELD9ZnJ7vpDqHyqhw1r8ZAcHAjxnnYUk /qKeB58uMh3iQM46jcJl/gDNfNvjc5UsFbZ9ms9cN9pHGx5UdXhTp8L5qG5b +e09dMIrmaqKPhXM378fqCn8gf5U9dCaYUoFn5wnkYJmuygb591serZUGLZ9 vItc2kFltxU/AUcqLLR/SK9k30b98ZQuZYKpILNn697NsYXmOa83TIikgs1j 2tJ0ewLaemX4kFoiFZJC7rCUv9hA51hfXFeQSYW5dlqejdPr6OFabrKTYiqQ 8feiLTnf0LMdwRNFl1OBoUhFKlx0FVVKt+QcuZ4K4z/pvg9OLqNhCqJPpXVS YXqtoTfF9itawsC0d18vFY6XPKjKUvuCdn/ZQ/IMU0H6YUmXNLqIkid2vv1n nQqcP33apW4voPxm5SwSDth49t9EHJfm0etS8cZWrqmQp7VsLITOobGztzf7 /VOBSdyzsVr6I1pVK3vpd0gqEBgzTmeOTqEDkRxBolGpEJgotR8TOYnSia7Q paVg9zf87BrgGEdFSYd0ezJSgeXCfd0NsjFUc7w2fy83FeqiuFgbD0bQlCB/ EcOyVJBQ8+YoZfyA1uqYeiZVpcLomywWVrFhdJj/amvH01SI5jKxrGh8hzK9 o9fge5kKN2cE5VuqB1HJku10vfZU2A0eanqpPIDqek/OxL5KhUSLLEPWrX40 i/OBw+bbVPgYMGAdH/wabdyOen52NBW43FdZ80160anX9r91plJhzS1M8/Bm D3rKRSqhYRF7P3fF69T1u1F55VOjqyupYDSevlji0oUanDw8fWYzFcxyJKm4 MzrR/I6+6pCfqZAVZN357m8b2pb+ePvZH6yf1VT3lmNa0XnbVPmvpGnwKjy/ QJ+/BeViNBxQoUuDDNljf1mzmtDLX4Ep4HgaIC7Hsz1sG1GLJj6DJ6xpsEK1 v3NVpQEtNSN8O86dBnI4OeYDqXpUkczLb50/DQqaiT3aWs/RifLf1L1CadAW 5Xwy0LMOpV6nPucrlQbvj1yeFpqrRUuSUhp15NLg5qz966dna1EFMdYbwmga JIV/46KfeIo6e/HazN9Ig5+NHR7bUo9RarbqH40aaRCf1Sib+LsafdAsFpWq kwZfZteCM4ar0LF/SNlVwzSg7l0nOV9agTqX9EhymqUBrvb5qftFD1Gqa+qv flqlAdmPj/n+FeWofPzdxWrnNPjbcNZ6eqoUHRP55BbpkQbZmXu1J0lLUaf3 1qQmvmkQqHE3n06yBC1m9uA6Hp4GCgmrytfrilH5xoOateg0OG//TtD0bxE6 ei8UehLSoJL+FbvYw0KUsijJxCczDV6rT38f4ctHiy8zE7TxafBj5YUuHOBR ua/4IKGiNGi96PZ77mMu6ni+Mn+uMg2MveqErr7KRimHLog0PkmDrk8Rz1b6 s9Ai5xctuLo0mIz5Pew5nYmOPO/+qNyaBiM7zS81T2Wgjnqq9hxdadDzKjLx 8Y10lOLg/cFeLzYepaAoS0gaKovOsVW/x9bLY/POmioVHVmwrIwYSwPaXqba OH0c6hCxJmM8nQahhx43TE1S0ML+n3qMX9IAT/H0rN5KIirrELz8bSUNuJ28 Uts7EtAP9BTerzbS4O7fItXysniU/DZTpvdeGhxTeHP5ZWosaj8nMjpLkw6e mV82v69FouShzy0ajqWDwt3nOMZTkWgBj/x2yol0uK6ROPNZKwIdtr1xXJkj HWi2LBTOTISh9rTvitl50oGn6mL7W74wlOyJrtieQDrEOKdo9fmHotLb5lpV YumgdXx3s9g7GB3OWJ0Pv5QO0cwvd9PUglA7GRdnI/l0+MjaItokFIjmBwYm MVxNhyLPH4Hx9P4oKVX2oJd+OryyUG88oe2N7ovIKjQapQNZiveNJBsvlHBr unrfPB3O0px+dybGE50tPBMf4JgOZi/ajCu+uqMjPa0HrW7pwEzKSDPA5Y6+ WTO2O/ROh4P8dgMNaze0QbpYJSwsHXJHceTbFK7oY6PLTd3R6UB3wvf+q25n tDR8UZA8MR26QmnN02KcUNw7PqqYrHTgYJ76GCfrgNrbVPUmPkoHGXGqk7Ln bFGzRLVL72rTIa1GsrgetUH169bLGBrSQfaGJu+SiTV69VA0Mq0zHcKFG6Xr my1RBb73O6O96bB98jdl7A8LVELN1ZJlMB0STNJO+8taoGez6q7kjKeD7SM/ Dd1xM5S19Xbd9Md02KXYds24YIbSLe5yn1lIB92WJtOrHKboL1EZ0sK1dHAL qb3995UROtbb0lH6Lx16PFfE6/LvogPrRheXMJ/f/vTT+Ikn+mjX8cNCAdoM KNrWZGHs00OfGisFVzFngPN+OT/Kegctj/i8uXYqAzR9nLmequmi+VXhxiJn M+BEKfczqZjbaNyPHsWa8xkgWma0cuHkLTT0jM3jrQsZ8EWzq5PEXgf1vkzF LiGVAeH3qTfKXmmjVkmqv+vRDJiRuLybyKyFovzvXjbfzoA/z90oIlrUUCl1 l/N/7mZADtkF49cdqqiwG2MuYpIB9BvD5ANvVVC2tlu+nfczoOF+omMIxQ2U 4cvOCqkzNn/s+Vr3C9dRSppMfWWPDDCw5/xZaXoN3dGdlH4dlAE8limMidPK 6Jq/70OqiAxIKpt+mMOtjC4Un2JVjc2AjRt2VRWuV9B3G4Y/BtMyYC/7vUAt z2W0MnLh+YcKrD/vSjMSCxH0mNlewa/HGcAv5Bp4LlMR9VSgi+WtywBu9hKv +EwFVGlbxsirNQP0TT1juOvk0Idvb14v7MqAwUNO9+K3sihdlaVY32ts/fyc XH7fZdAp0xTyUx8ygMmt6cG2tjSKKpQTLk9kgJPfqPJBwiW0jLVlyn4mA4Q5 3RP43kmhrm+XH7cuZcBcSLzvuI0kSqOA3jH7lQHaV+qlHy2Koa6suhD3LwPW K1MuvtUSQye+252vI8+E7KeuP4wiL6IllZl/yRgyQeL824S3DqIodeSjFRHm TDh7Ucak3UkEdTbt+nDnVCZkGedEPPMVRuVZN8sreDOBKoqopl55Hi3+fgQ3 fC4TKiF4VWvoHEr5ls3/QDQTJndsKU/sC6IjEVc11WUz4cGTgX911gKo/fe8 PYJGJnj6/F0jTeNFh4eeLZy8lQmf4xR+JW/woNKVfQNK+pmgcEdqalqDBz1i ulOYZp4JGj6iI2Mc3Oh9eZq4FptMSDfx5eBK5kLfsZz1+OqQCSpfuf6ZkHGh eUNqN6S9M6GguEyYfJ8DPVJpJm4akAnBJIMvzh6yo/cjvM/EhmYCSbajQj8d OyolX0Kcjs8End2PTHFXTqNDFQfZQUWZoG7edPEr1UlUIoIh/GFZJvxxvIM6 qbGiOSb8ju+rMsH95h8Ww3QW1IpFR4m7PhMCIkZPhMowowNbNkJqL7H+aseU qaadQMWGApk92jNh5V8fTcE2E/onvHK1pz8TJN+HUp95dRy1MGkf2XybCT16 ETMrEsfRfrmxVtbRTHjTEFsQVsGIZmz9w92fy4RrPs1+S4oMqKiJvhzddiao mXVd/x50FKWjZnCY3cuEyF6WRYlaWnTt2ev8x78zoem0JaFnlQatpJAmuUmR BT33BljpHKnR6JpNcQ7aLGgY5/cxaaBCre+VW24ey4JYZa1teUoqlOcJc18S WxbEJyWMLLygQEn1h/aNObIg80W7620WCnSBJFLoAk8WHBWkO1PmR44W6O4k vRPOgrahh4Qr2mQo258PugyQBT7nnLLcxEnRn+Vx0Z+Us8BNlPx833MSdELr clONShb8qujwWpAjQdNLa89o38oCu71bn4ceHCLuN+/f5NLPgmuvhUYlXv1F tH+eDdkyzAJrcjgpv/4HOaaesoizzgKyEtxFA83fyMbudWZz+yyQElP4Sx/3 CxksPLwm7pIFGXbVyblvDpDYbaeqD75Z8OMsjj/EcB8hw2u4MiVmgfjqd/uh th/IojJ5ySIuCzoZneX9eX4gnZsto3WZWQCIOtQn7CLBl4VlbhdlQdRjQxHE YQfZX6U5TK/LgnkjyjOUht+RybSui1aNWfBzjo/SbmELaVD0M5dqzQLCCUv+ u3ZbiAdutWesNwvM/ExV52iJCEGmL4FlOgs074QYG/StI28/B7ctzWVBcPgX W5RiHXmcIE18sZgF+Ww7UbUqa4jdp/JbehtZEBNMeiHz0yryNTryVPa/LNie tP54VHUZ6RZTVLclz4ZaZX/xf0+XkAcfdwJlaLLhtPbpIc1TS4jJBcuFSaZs OKS8Wh386wsyPX65gk0gG3h1Uu72rn9GmMmYX2oLZ8PVHrhIZfsZ0RZbHogV y4bi5/z/NJcXkP74eMK+fDbgX3VTLyx8QsibjEjElbIhtE+pg2VvHlFausBk dy0bzohcUTFjmkeaYPTStFY2nGqYO3bTdBbZdSy/cfxONuhJWFhGpMwgYnif e6oG2TBB+Zxvt/cjUrF7JuilVTbs3L3Q0nZ1GsmqsurJ9csGGwm2ic+RE8jI hPTEh+BscC6rVhv8PI4cI6dZpYnMhldjwoJxyuNItMmTo/7J2WCosMpCYB5D vE7s3TIozYZbdD0PXdY/ILVK/VZpldmQ8qxZ/YTDB2TDCe898AQbT0BCzJ8w jFj1o3j5pmz45PMngp1kGNENivl8+m020NPJtBlnDyG46ns7t0aywfus3nLv 0CAyNClMkTCZDWxs56joqAeRqxLD535/zoaFKbfmiJQ3iOQKm+vMXjbcebW0 5T73GnFmXg878ScbChtHbgoir5Hqy23p6qQ58KcqIN7jQS/Ck2/e2HI0B/J5 KO6p+vQgTDrVh3lcOdBtrHTujm43ohkcyDjGnwPPueQ5Rce7kPhHmjx0wjlQ rPDzTvG9LoSUcuda4KUcqAjourjp2IlsNSskGanlgO2zRfZSzzZEZJW+KEMr B147FlPbVrci91kWaod0c4BTRuvo9FILsuASOaZoiq1nqmnxlFMz8p7v7RkO T+z+Wa7R1qZGJJLrstcf3xy4761NfoqnEZFlf/FuJigHppMElo1SGpDiEwVh +Jgc0DLht7rk9QJxP+K0cjIvBxyvJUoaOTxHBA4XlH4W5cC3T8wx4t/rkJkD XfxEGfZ8PKQ9wv51yNXvijczn+aAe7d5gHTmM4R1ge45U3cOfHoy+nb2Yw0y MBNKt/06BzYuiU/dYq5BQiZ3rT8M5oCCxpfrE7eeIqvvZtlw4znw5k43R8T8 Y6S57XEw/bccaG2jPj4vUo04v+Sa2tjMgYna7ibZhCqE90WG+NB2DrB4ThVX bFYiiY8Dv8b/yYEjE33zt9srEJM8DTVqxlw4jH5lzJZYjjBld5auMOeCwJSM nzx1OdKXJvX39alcyC3z96mKKUPE4tlro3hzQbKJV/sErhQ54rfBQiaTC8U7 6NxkzwOkwdPMZVEhF+IoAs8w3XuAOLiO9Xcp5YI3Y5LxPrEYGbNtDQhVy4Xg US35cP5ipFwv8fNf41wYUr3x0d6wADG4RaIwZ5ELWe8fCX2vzkeOaXpmtNrm At3tC18GDvMQ72tGNwLcciEIcvIYn+MRFSmRJ/uRudBlEWS+qJaD/LlYTDkV lwsE58hsruZs5Jkws1ljci4YZFnVfxXJRk7z/mHyzsmFHbaFL0XsWcjG8SHf nUe5IDI/V5jDk4EwvqrXaK7NBfWgCp3dJ+mIlGcBV9iLXGApLVs9rpiOBE44 9x/ryIXfTYRhLbM05GjecTahkVy4tF0WTNmHQy5o/FrfmsgFdDTyTbkNDrn1 d7GjcQbrX5ZUSgw1DsGb1tteW8qFvaBOzfryZESIT7/RbD8XSF1iZDJJEhHN cUgQ/JsLf6jLXjGYJyDu0edMCaR4YLXTrkV645Hm1QPKwKN4uMTqSWOWE4eo PcnXy+bEw3WdU94mtjGIs0mUkAkvHmZscVw8X6KRNAbnQ75zeNj5nme/aR6N fHSDh3XieJj4mPnp/v0oxE568cfbq3i4L6kqMpcVgSSuDLzJUMWDJIFBi+l8 BFKb87zAUBMPQxuykYNt4cj+r8hr3/TxMO3IwR9LCENiOwQzyR3wEPWGJh3v EIo8dmW0G3TBw+Dsd1JtxlBkmPtAMc0TDw01oSxCziEIW+TA17PBePiZfkPw FkswUqniJKWQigcatee/xVIDkKGDO9RHsvAgFUsJ3Af+yFY1OtuPx4Nqp9CZ cCt/RJaeMVKvDA8OhG5Z8Wt+SN+HulG3Rjx8dW9WUBDxQdbC8ypkW/HwdtFW 0f6JN3JMKjLgXyceODtoZNzEvRG9rDu8SQN4EJQN+9Nw2QtZNth3r5zDA+lN 9TueYR6IbcpvgclFPKgNbKQ/POaBrL46/Eixioeua89v5xa6I2siFMqW23hA DL1uh7x2QwiHx09wUuWBH3/7V18pV8RFkqVPgy4PCib5kd5HLsiWLVtAwPE8 mGMldeHYcUa2hzm/TJ3JA4Qg9/RjshPys0T4ebpYHuif3jis/GmP+E5esO2+ lAfTdjRNOEN75NdRiTPf5fPg8PS1LwKv7JA/nrIRmtfyYGqflYG84D5CcuPa bRoD7PPOAhlcfjZIWIAKlaxpHjgWrQif3rdGjtSqt9hY5YEtxWn+0/7WCPmp W7w9znngdFd8bDbaCqFeN9kJjsiDsOE/FFFdFkjcWYuKJ7F5YPzOV6BezwKh 1bU2nE3Kg839+5wmBHOErs3hlVwO9nzjAq+X+MwRxhTf9N3HeXDGMvSpjYEp kvoq4AZvXR7c+8rOpVRlgjDtB//WacyDCw3trjJ/jBFm8yjLmq48iD1Vguw/ MUJOSaZJ2k/kgXv1c6PrqAGCt81cyZnJg0vrtrhLj+4h7Pk5eX0LefDOJTjA 88w9hJOiiIx/PQ92QnavdVDcRXgmH41++pcHjL2ovN6/O0jp0ZqYYxT5QPeU k+Nf5B2ET6lOAaHNh7nKw3se9HcQgaqmUjxzPoxR6cTaCOgiQgG9HnfO5wNS 3Js+5H0L4Qu2dxG+kA+2Vyyny0/eQjjDGBxIJfNhEPfTPbxZBzkec8/iiWI+ tDG/5zhKqYPsp21qU2jng6DkkTN+NlrIdmaaxoxuPiQGPaIf6dVE1nNkVJ7d y4f7Bm9+Rp/TROYLw8DYMh+ShUrzG35qIL3VLBdeeOdDx/OOTJEWNaT9SfP5 hIB8oGLakDeVVEOaak35zUPzwY4ZVXB5qoo8bqhip4/PhxHHvzJ1j1WQtG7k qHVBPrTsxOTo9l9HzD5arzL35MOWKH7B0VUZMZij/brWnw+bFjyS9AzKyO2F mk+db/PBjCzrzJOaK8j15YMJx8l8uKqpkFa/dxkR3U7q7VnDrrPkqk/hlRCB HxJdeGI+jFvvbSqpKCFc+5OtrrvYeN98tEsJgDAfctezH+aDz0v5R931KPKL pqHE83gBKFQ6v+exUUR26QwL1VgLQN3jxr3haQWEwECC5zpTAGmX7bTuaysg n1nUUof4CuD9eyuSqmvySD/3fAifbAFoXZ/wrtCSRTLlKI3HTArgONMd2vBx KaSBYeOWvFUBrD5cnL5pJYVMLH1QKbYrALffBxQ5PyQRtrQCKUfPAoiLolUM OCuJ5K9J0ZHHF0CtXpLoerI40tZ5+oh9SgHYqW+OK4qJI/NZJPvvMwrAtn8M ikbFkLPKQ1/yigpgk6Wx+T6XGFKSZ9ki+aIAClQ5BP89EEVeuak+y20ugNOR rw3NyESRrzcuVvzrKIDt836FivdFEP7dX2mDAwXA3sZStKogjFRqpNlbLhTA +uuPO2E055E3PL5mb5YKwGDwU4F35Dlkbd9Y7+J6AVyvGe5SPXIOES4/f+X3 jwJ4iec+YUQpiDz923kq/WghxMZwmUld4Efejz5kOGAshBP1fzhD2vmQrapE ClPWQhigsIgV1OFDxPXufhfiLoTa2GKcexAvUv+U2N8tXQh1XhU++VvcyJ5B S33y5UK4sNewWiXNjchQxRQbaBSCD67LOC2SC2k25fTdNi+E3d2XmmedOJE/ R9cs2x0LQbz51gSFFAeCNL3QivcphF/BQ1vHqdmRTsabgjxJhVA9GJ95dvwU cqSN7QQhuxDW6u6XML9lQ5Ttvh6+LCmEiPpEM9bhk0gkS+1a1JNCCF7iEEia Y0VedwVM6DQVwstXHyZO/WBB/gNPheda "]]}, Annotation[#, "Charting`Private`Tag$8997745#1"]& ], TagBox[ {RGBColor[0.880722, 0.611041, 0.142051], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUmHk8VV8XxpUh4SdTKpmnyFBSRM7ZKikis5B5liHzPM+za56VilAkiaJa RJRkSElIpozXvVIpQ/We96/7+X7OOWvvvfZez7P2FbK9pu+wk4aGRpmRhub/ v13tIcN6j8sgkP+bf58fHSa+uCLIUFEGgzeY3a5v0WMJbNauLZllMJDjoUe5 vgs7KVpI4kosgxPXPC6IhTNiC4rvHnmEl4HKhuTbHQ67sQtWajQirmVQdEzl fbw2M/bbO0wszKYMLA4yT23psGBV8U2aHy+XQffYQmm8+X/Y7jqJ3BS1Msgc jN3gzd2D9WyzHP7BVwYHf7JcLLvAgQWzqetc4ioDLlGWs39/cWCHRSN8q5jK 4Ewv3ym1Ok4s5eK35+a/SuFTkI90yNG9mIrV4dmmlVIIOs9NYfizFyN72+1m ny0FadGDvfcHuTGtog8GLwdKYZ9a58/wnP3Ydi1rkEB3KTj7nMpzjDmA1baf Lwt6VgrckUf3d4TwYKyLTxZkakrhV06vYEkyL9avWBaWF1MKb1PcDijkCWKd ajenBYNKwQhdULx1Xghr0as8f9ejFHgEWmRe0whjla517G2mpaC/I2rXaIoI JuR9VC3OsBTk7W7U7fwhgpUENvhr6pTCnP1Bcw9LUSwrrmnsvVop3JPZlWeu LIaFX39esXikFAIiuwcf7DmEbVSojtQdLgXW7a1jkSmHMN97L5h8xUrhytjB BgYmCezqk65rf3lKgVdkXCt4jyRmPNSnxMlQCkfeDJa/x6Qw2V1f3qqMl4Cw yhf+XbxHser/bGh2fiyBcbf9af0+RzFRrplj3YMlQB5IUMt8exTjEZrP1+su gbcOzHk8CXIYwymqjWNDCfTI6lxq5JTHok575UjVloChTLGXd6g8tn3+e9fq nRJgKm0Iz5iXx9YMf0mFlJZA85ToIu3L49iEx7+fGYkl0FQnEFVbpoCZ+kVJ GMWUQNB22sFPBxWx9yG0V3jCS2CQgTX/TbEi1pO4q+22TwlcaqKYJNw+iTXd 3JP8xLIExNwSf2+OKmNy1ZlPw01LQFxdI/mJ5yns3n1O6llDYv5hc2GTu1Ww m0/3GfZplEDKu7TnreoYlj4swD9zvAR43sHK/hWEkVhpdu84WgKOrYOPVDVV sWz1ye/8UiXwVfrjofbrqlhB043XZkLEeidUF9R0T2PleUJ+7/4rgQW9ipjy V2ew2307rFcZSwDfE3t4VOosVskwrclKR6w3KCn1eOZZrMb/pqDmZjFMeNam xtiqYY3GIr3tc8VQuONpGq2QOtaUTtv8ZaoY2FqL7r/KU8eedM2U/xkvBhSY KL13z3nsucLtAKWhYmhQNhsq33UB6+YWE3kAxfBQYHsXM48mNjosHnyjoBg+ fLhnbDh0CRtn3eXwPLsYvuTvGfoYpIN9UZ/XGU8vhiN5roa0HLrYbNMdsf1x xbDDeu7JWLsutpInMZjhVQzKlgdfZSnpY6t9jE9r3YohZ03jX0eJPrbGsFj5 xqkY5sl/u6V2GmDr/tWhuyyLgX4Ds+wZMsBoLh+WiNAshmukB8Oj2UbYzgwm ztJzxaB1p/mzHJMxRt+99KdFtRjS615GycYYY0yKd4fWFYqB07HX3CHsMsa5 TzrCQ6QYfndTdobnmGLcOixXU/mLof9wRNyskBm2P4FsWHOgGEosvFJDG8ww 3l/3Ds/tKYYXbDQRKZ+vYOIfZYYttovg2Wfz654WltgT00L1nF9F8DdN/Q1G a4VpjdM196wVAUNL+7POe1aY99RYvuJiERg7CIdej7PGni8nmbIPF8HvvedU zmzbYHoeP1+fHyyCxN93K3ErW2x21Vo5vLcIWLZyW7w7bTGmdcWDyy+K4JCU lG5rrh1mRDM33nm/CAp4x/mvGTlgC9F62ls1RaBBjjN8+cYBC6Z/9kyusgiG G16xdak5YjeYcsrKSoqAVuKhFQ9ywshcZ6wDk4qg40Fo86ixCxaRXztQF1sE 938gi9hZF4yD58DprxFFoE5vyufqdxU7KbAqpO9fBAJZJzNQuSsWK1k2I2VX BM3WZjt1RTywffd2G9paFsGLZQWJQ289sBpZv84C0yJ4+Dvn4HLwNWxAXquC XrcIQrrl/lP38sQO4puOX1SKoCKBtD99zQura3P4uPdkEayuj/2LNfHGVM8O nteSL4LwIBvBsTZvzPFClcQTySJw7TuNTRT4YA36xktZ3EWgy+Tku+rkh537 0G72mr0ImBTflaZP+2Ejl2Xe/GMpgm7pWHlma3/srzndPTfaInjsfDqKbBeA aTo1uKuvFsJwlqaBRWYQ9nmRbyJ0uRByrYeZmcSCMU+3pEsP5wpByAICjj0N xvK8rI8Ifi6EHp+uVr2fIdhUCOu3jdeFMJNxss4pNxzjDrGKetVZCNU/S037 jSMwreB69nwohDu2rK0lrJHY40D9Y8cfFUJcRV7V2/FIjOSX5+NxoxB0n1Lp TIqisS7feVqsuBAe1Mg3crDHYNs+J3OY8wqhM2tpcT45BnPyHm2sSimETzfT HygkxmL4Nf71af9CoDBVpK3cjcd8Pa7FP/AqBOTD/GcTS8Bq3Nu4I90KIdbO TWZ6KAHb62aryGdbCDfmMxmrmZMwsnNl4GXtQkgwXmu7VJeCCTv/YhS/UAhc HjzGurapmInThcIfZwqhWIzjCf/BNKzDYelJ5slCyBly3XujOB0rspXdeiNS CJK49gthCgkbsIlIKeIvhEEWQYmLFpkYg83AQZcDhcB4KC3SvT8T87LyVmHY Uwjft2T20DzLwi6YN4WpbhaASOqtZ58hBwu/sot1z88CUOTk2HdVIxdrNDMp +0wtgLEO+icPhnMxAdPN58FfC4CGJjt6ajsPWzfCaR4NFMAsb8KF1eBCTNoo gxTzpgAaXZZ3RooVYbaGk4L6XQVgdDFy/fn7IuytfvRpamsB3J+Vbn5zugS7 rdMVLXmHiNcdtl/O7Do2emkf5+/yApga7z3Ote8GxnbJ+VZXCfG937+7f2Nu YCFaTJ12WQVQgrc6bjiWY/oal+jLwgrg6DGFA5yGt7A9wX+0XwYWQEIr51+x /ltYb829PLJPAeTIVyl5aN/G1FmYJU5dJeabUEG3YVCBnerv1hwxLgCrxZWW 0pQ72O9//tn/9ArgF4sa92/hKqzpqPi4uHYBDLkVFF96XoUdzYp19ztbACfp Kq7a7KjBRI1OkziOFsDcOf0pt6f3sKm41RElqQLIPlJpsOJfi5U1XReyES8A 20SWInuFOuzA/r8N93kLIDL2R3J7532Mdazlg9Zu4nkEF9RmPsDeMF/l96Ur ALbq+yeH6BqwRJUDTsX/8uEql0DrnpAGbGdZwO/Fn/lwOK9lVNLrIfbL+vjB hOl8aG0y1g2Lf4Q1Zs7Y1X3OB59FSdN1ribM+0XWvQ8jxPuNEKx1pwkji3zD RPvz4YnoOSb6kWZscq7Wur01H/wTPqXNurVgpfssqheaiIp5dImazteKmV1g WdvTkA/BaU7rbEOt2IfqqzGWVflQzpi4KKX9DOtxO1S5lZNP6EXr0++qbVhC 6TBFmJQPPXdj9jypa8PU+uIUNVPyIULGVClJoB17fmT2VUFUPliGnjp7i+kF 9nDtxvIJj3yQe3Ci3353J+YponvcwiUfemOLaviyOjFZw3+hsfb5UFIMYTX8 L7GqRxasQ2b5wCbIcL/hbBfRP/HIeZ7Phx07yOLjba+wbbH7hUfO5EPeG+Vq luDXmPnQ2Z1UlXwIUzRcWD7Zg/HKug+5H8sHC7OJdL9Xb7DQsR0qMjL5sCGE 50YX9mLjiXm3yYfy4aX09VVar7dYyQz4ufLlw+ejtW2njvdj2yTDicP786Fb Oei+HNsAZo4vqi9xEOs7qkSmJg1gvIUc+10Y80EhJCpoIXEQK7nk0OL4PQ+O pXzZ7/h4CNve2hAWp+SBaH+/kqPOe8y8Oj3l60IeWL8oPi62/B7jpXtsbj+R B3xf8L/RcsNY6AOtlyKf8uAoMpPyGx/Gxi2nZGaG8qC1upfUn/oRK3nC9M/m dR4IxQjU+f0dwbYdrzsJdeZB15n6HKG2T5g51/GByed5sEOuYWw9YRTjvWZR btWYBwc4Yvh/HB7HSkTrz1pcz4NiJt48984v2Pag2j3eojxQiB4o7bGcxMwj PnGN5+RBvJjAL5svkxjv6M45s+Q8mPGIXRFfmcJCE/Iv8cQR4//8tb8seBob Py7d/CmCmJ989NMalhmsJMMo0cQvD0bW8OpDaBbbVlla3eeZB+bVl3uXv8xi 5kvhph+v5sHJyyNdlLivGO+5qsPG1nnw7Y/obZfpOaxkc7PX4GIeONPfnq6e XsS272Sc4FTPg6AEeZrehiXM3Ei07J1qHlhuHJzvS1rGeOu1r+kp5IH8A0qZ u/YKFmox/ZFNLg+Es9nVk5Up2DhTgOqAVB7Y1fmpJh2hYiUON9h1hIj8Jv9Y EC9cxbY5TgSz8ubBwwXXKQPBb5h52+vpt9x58PeQ4a5d975hvAe/P9RiyYNJ 6TtDFYNrWMnAOWPNX7lwSzogu9jsJ5b6ykFNeC0X7M2qPON3rWNhbXHHNsm5 0P+TRkm+ZR2zrH/JWjOdC1646MFbcr+xS1Vft6M+58KnS4vL79Z/Y+gG/bLp SC54T4c2lb3YwARJ57p39+XC2TO6f7c8tjC2RIdHU69yYWDg/Ecm3W1sR2Tc rScduaDlaLj04OQfbPraywiXJ7nwj7lZ4IvQP6xC59zJ17dzIen0kZYftTvw vPMO4uXXc4EcIVNGUd2Jx6M4rqCiXDiPeT6njuzEnY+8XJUg5cKyHd9I+346 3OTQ1wmalFy4EZI/9KONDtcQoH87EpcLoztYZL970OOH95yrTgzJBQZTivbh zww4zy6HfGv/XNDR4Kl+X7oLZ/4XG3fSi1ivj3atjAMjTqZ02iw45sJm4c6M BUYmvK5PjeeCfi7UfCmI+3b3P7ysy55RUDsX9B42VvtUs+IZz2PXf53PhdPx bNpT9/fgnnWd7+5guRDb/DXbhcyGW1fOtkWczAUlK4Z79OHsuF4Z3f3L8rlQ oXfMooeLAz+WrpaySzIXGLHMoFx9Tlw43j7oi0guBH2k+NJtcuKc4bFOzfzE /N6nHna/w4X/cO8868SVC07zlyhce7nxJm217a5/OWCa9Muu5MwBvPKc/VLZ Zg5EF8rfvSvIg+djsSP+P3OgIPy7YhfDQTxQprNRfDkHnjEnsV0h8+LOYrM3 /37NgQFFSyyUzIeb8tFlDk/mwKUgn6L1n/y48n9q7vHDObB76mTxiWxB/DC9 /RXLwRwQSm315TokhB/8E6Oh0JsDYf1mFXZtQvg2uUNsrj0HGoQjpqTpRHDo PTtxrjYHYk9G9UwPi+EK6+2x/lU5cJeJnUkiQxyvE1CVunMrB6axsvph7UN4 mbdKIGNRDmjPlDnYfZHAuUta+JVycyBV561qe4Mknv7y5EsXUg7sl3sRn5B2 GA/ff4LjTXwOnKCvfeBiJo2vn374eCsqByjkpt4D2jK4h6uclXQYsX7mVxtX Lsjils9l7qX55MBefrLgqvRRHLcXV9e1zoGz4pNbRkHH8Ka02+TIK8T8emQp vQfkcdlm4ewHxjlQFctSSdcmj/MzCUxyaOfA+oZYYj7/CTxPvjT+7IUcMN8W +eT88QTOanFQxvdsDuj8WX00n6eA/72/L/iDUg6grtTJH4dP4v6fcgUZTuTA 097dpP9olHDKTq5uhaM58CYgYGRhXAmfMGLjKhDPAdU/K7U890/hz7YY68w4 c0BJf+tE1nOEHxdLMExhJd7PeVXt5K6K37tEv9W6Owc6bdp5X9GcxkvKd1zg o8kBLfmhGJGTZ3CuNxEU7a1ssGJ/r5w+fgZP/fEnJ3w9GxrTpUp4Es7ioec3 p76Qs2Hkgt9QFlUN/+EZmMi2kA1MCnv4dtadw92K1mVPz2RDcEdxSpGPOm6+ shZy81M27J/cw+e+9wKukr2816ErG64euDJn+vQi3vjU5WluezYkWhXxwlMt XHpu3rbraTZw+jB8+9aljfMqzd4/9DAbPjy9VGa2qYPn2Noam9RlQ5jdhu7x LF2cJXVyO7E6G/KGP0dsSuvh2xPjGkvXs4F3iIGh2Vcf92W8sspTTKxHavuC jLABTpb7lHcxLxsGPQM6bYcN8PHYDzP3UrOh/fzm18OGRnjr4b6wa0HZ0Kf2 K7S91gQfHpBTO+mbDScj3Oho60zxVf9cph3XskEbcno1npjh4h3m+Vn22SCV TC6jrpnjp13aLK5YZQP3z/kgW2FL3HyPqKioWTZ8dj9FXN+s8Kwry/WPdLLh YPAGEtphg9fu0AkI18yGW6mzxvse2eCv7jRg589lg13WIY01T1v8z/egnhHl bDBQp5cY2mGPO6cyzm6JEfnaP9T5ONsJjznmVtMpSOTz37eZo1nOeNlIv2fa wWyYaj8W/V+JCz4kmv+Hnz0bRNMS5kTfu+KUns2OeeZsuCi/spBE644zelkm 1zNkwynus/VVqh44/kxs35ntLCAVBp2x8vHETe2SPjP9ygJNNZEykoQX7rt7 5dbQtywYcBD/xDTnhVcbNR51mM8ClTBG7pAQH7xza98vmekskP2uLqFj6ItP lIc8Wx/PArs/dPMSin44F+WMZuK7LDg/JpW3zBuAH8mpZNN7mwXuuvnps4KB uKYy08cDr7Jg33NqI61cEB4RP2h391kWeHy/+0E8MAQvkj5x2PdxFny42eYZ WB+KN74rWFV5mAWvv5Jfpv4Kw5f4rcP6qrKg69fjlAizSJz+ZcfZ/FtZIFLl ORLCHYULuh5isi7LgtSxgte+Y1G4UTMl71t2Ftys385TiI7BPS30LVrSs4Cj ka1t2z4WT6ZtEolJyoKpHTkdLfpxeJtOWD1XBDF+m7Oms14CPvZz0v9zUBZ8 Fr69SbJLxNeL1bBK3ywwp/6bE41JwqUWmHsUr2ZBVvKItP1KCq6efo1E45AF ERub5GylNNz6+JDxa6ssqPnT3HEyLx3PiyyaMTPKgkuOfW/kX5DwB+J/q0V0 s4Bpf67KUkom3ttr40nWzIKHtBe+PrfKwncekPwTppoFwdMnS34cysH5ILVD /VQW/K0//TSaLxc/6bCatEchC868bceSBfJw9wfN3OVSxHqlss53XCzA2ZKC cl+IE/uxtv2T2a4Qb7A+xTUrlAXboaOTjxOK8PU9wH5ofxY40JeXMGyX4AXz kaQLnFlQt3vCVUS7DFeGM3uusmbBkf0nKkrrruPhHl0stXRZUHu16+J/BuW4 oHpiSt+/TFAoChXc5L+Jv+DTZFrdzISqjvfqKz9u4rvevt0l/y0T4q+Zs+xu v43X3M6INyRnwt33kurGjytwrVA9ev/5TDi+JLf1vbUSJ0l92PnkcybkX39s 8XqpCj9Gmx81OpIJAfNRr9331eDvR01otocywaygzQgzuIvvTx7/g/dkgsND R5r6rVq8xaYs1PplJojb6h05ePU+bq5kvRXVlgnqbVLZ5X71ePnCzO/Opkz4 r1Hcf4OrAVdrqwiYe5AJLHNhdmM/GvC5fKf1XbWZsE/n04DJ5EP88Pnl75q3 MmHOqHK9Y/wR3stf6+1Wlgnjn54/PkBtwj3WPb6lFWZCbses+fiex3hDxRpl ICMTeNc2NH5GtOCGYY3ua8mZEMzdZ8kx2IqvG/qTOeMzQSn3UILU8Wf4KbrN RePQTAg9t5dVlacNnxhrdQ4MyARqp+quv4tteOTDsPlC70xw0im9vdXZjnfa 7vg67pwJQiJ+fRbXO3BH5Q67v3aZ8IZ/QlLuRifOyBE3LWCVCZnuRkoi91/i Wu2Mk7ZGmWDtsHyoe7MbpxT0WMbqZsKtINO72kqvcZJn6ueKi5nAM5/AXpbU g38QYBtbOJ0J3XQq6j/s3uKBvwZNmbBM6HAPMjBY7cN5+rNHpE5mQkrVvesF GgO4Zfi+YQ/ZTKh2/3CUhv0dTmP8yZAkmQmDOIdYKOMQflOmeOiBaCYscXj8 Rqzv8blx/sEfPJnw6bd556kLw3hi46QON3cmFJ2LPeIS/hE/nHqzT5E9E45s cha+6RrBr50S7w3elQnsb/7JT2aN4RycC5olOzNB90BYEf+Bz3jjUvXrZ39I kK3ak1zbNIH/LpTppvlBgvoYXz4K/xQu9TT4jTKVBMyt3ENX2aZxy4nuft8l EqhzHrusxTaDk2j2vq/7SoIpsQnhSIFZvEPYdmRhkgT5B24epUNf8XW1++PC 4yRg/zd/fuHaHC7htD1p/pF4zqGuqfNwHk+/m7c48JYETjP72Ir8l/D2tzMr TK9JECI7M3F0Yxn/QT26ptZJAuWOIbXG7BVcnCN8PRxIoHtzHxOcp+Kmx99s Pm4hwcOu+u+xKat4qvH+f2uPSMBwsWe0Keob/jzQgVbmAQlk91B2+ySs4aLP /jGX3yHBOTqLjsmXP/DLX7TYxm6SwGa06MM3mnU8eUcR194yEgjUslbo6P7C n4rM79cpJAGq5ZRyfPQbp547zpeUQ4LnN4OZn8lt4sLOUUIdGUR+nEWWNrq2 cMPkPrE/ySSY72n9Ou3/B2/pc5b1iiIBSVZS6Uw+DSKvPjp2N5QE9/hXKs+U 7kACnLSKXwNIIP5Vp3u2cSfSP6F7SsCHBOYB7hM+X2hR7OVSZOpBgtab5veM +OlRc9DS2WwXEoyb1L5g8WFAS8WKF97ak+DzNUWGU192IZ3JQd3TV0hgNNt3 4hg9M4reKWAUYkwCoXjViZ8vWFCjqJvpIz0SrHO8F5O5wYrm1Z9YULVIYPqS /P2mDhvicWGwlbxA5OsM+ayXDTvSSjFwtDtLArHUbGdqPAeKqL1xtRQnwe2M t5U17Zxo9puyD/sJEnh1t156GsaN9nElBlw8SoIjJaoiczv3I02FDyFxUiSo ytV237p9AIWaCEeCOAl2HFbcaep4EN0Pvha7IUQCzarTO7I0+NB0ydNEeT4S SLyqO+KnJ4C4YHea+34SsOlFeSe1CaJg2tu5U6wk4J2dqMo/JoJqxb4VHmQi Qdy86dMakiiaPI+XGdGT4LB8O9dFJnHEcTXlZgYNCZxFXZgmyg+h5P0PtLN/ ZcCkOuMErZkkWjW/aLyLkgEHVCXXSk9IIaPyr5YhsxkwzPLo9QdFGSR4mMfT bjADChppo2W/HEXxHo2BH7szoCvKxN1U7BhabrgUdfF5Bry9Ksw8Gy+PdH8t JEFjBjQeSWE3ZziBmk7FZMnfzQCa8LD1rEoFdDCSr/hOeQZcDyltrrh6EkV2 Nt86WJABEYbFlfTGymiOUf9eRnoGtAuwXYx2U0EXtcmNtHEZgF13vW7YgKP1 ZL0/d4IzgI/9tfWlBlV081XTOS3PDHgu55PlLHMGaTPwpq86ZABJJI6k2HcW /T4bNZxzJQM+NyVcXS04h25FzfEr6WVAdRg/5VLWeXQJLjp9Vs8AzVNSsVWg gTa26+9HqWTAn1412p2HtNBtZe7fYscyYMSb+6dE/yWkExii2nMoA5hNpgIX vuiizUeTiR58GTBTaTg7GqmPKr6fG+TgzICT9/lrbHQMka7c3QPNjBnQwqzJ JKxnjLY82Gyv/E0HpXqfzympJqjynl/Nv+/pxHk6Vb3BeAXpL42u3VpMB2qE nv1wnwX6c0j11IUvBDMpMX31sUZVDhUx5PfpRP7n9QOO2CLDW0y9pJ508JbF zRIE7dG/yWtcJ9rSwV20QzrwkiOq4f9g/ulROsTvyND42O6MjMyVK8LupkPi V8MzWbGuiKbo+opQeToICAQoK970QHc/0il05aUDreXuq0JcXsh479Xwq6np MF/1QANx+qAdBv1drNHp0NlBP/Xksh+6Rzq+52FAOqQZ/B0NIQegy32Fly+7 p8NGNceq60Qw2sny7/qWbTqM3bUbGVYJR7Ua9gvXTdIhloNfZoMlCpkkvD6q dikdWOzJnG3nYhDdS9mghbPpcE6FL7f3Qxy6vzOnPVUpHdKpYhrDvYnITHVj t9yRdGB+MVMziaUihnBL/Q+i6SBRu2xDK0hCD1o7ioJ40mHgsQ0OAVnIfENi ho8tHVoa+ZG3Yi7apZgu9YI+HepqAoJ8fAtQg+93H8etNGAXOxqqoFGCLBpM njJ9S4PeoZfJJq43EOPqM7r7c2mwUPDoFrfILfRQRkTbYDwN7Kw5J947VCJL 18TcX4Np8HEPpAcb1qDd1Sufi7vTwOuN56GJ/fdR45y+uOqzNNCRv35P3rcB WYk+9phtSAPdOF7zx7RNiMmWrzmxKg0uP1Id63BsQU3Xo/9Jl6WBYK6y/fkP gGw+z58fzE6D9Me1D/kvdiCWg9okv6Q0kOf4uiUT1Y0emzSMHIhIA+UVEtb0 ohfZ5e0Teu6bBpbx62zfKgcJywx1sb2aBkt7FL92P/iAnrBPP2CwTgPbG182 e0tGkb3O+c0aozTwK1ja4jg5ifak3TujczENrqd+a8TjZ1BLD3vKd9U0CFgp lW3bPY8cGAOG8hXSAPnzCfl7LCE29fGDKtJpUKsvkZx+fgW1xpy2nxRKA+OQ 70w35KjIsb3yXuy+NDjyGwvQ2KQi9n/MPyX+S4N5R/0q4QdU9FTFC3u7Mw2m JEq8ZPMpyDl4OM7rdyrUOC6Tv/4hI87Hp/r2UlLB5bZs4IT0Muo1sUhwnU0F wYPnHjzxW0TxG+Gq7aOpkNjJ6xU6NI9Ui25scA+mAqXSLtLRYA5tKr9ocOsm +B/z8fHNWdQ4NuP64lkqfO97z5/eM4M8QunF9jemQqCHLtxsm0YSfIcm3GtS wdf0bi/b6BSafnYhv+NGKrSnuoq4cE6hEsurugfyU+Hud+cqNZdJZPwvZfe1 tFSorSqq/1n/BbHdqH3RGZMKPzeMT3g9nUA9qv0hPMGpQPVrDGBe/Yxip1aP e3qmgkl1EEPM+c8Ij+agvHRMhaThLTsFGEe/hY/fOWiRCpbrDvwchuOoocPI 2ssgFRZeabwMpx1HbvYBB7o1UmGXFjeH7psxJE5f+I5XNRX2vd/se1Q9hiYr WlK8FVJh0vpvsWzpGCpSH1d7JU2sT3gsOPT2GDKc//OHTyQVCv3FvxU9H0Os iQLNPgeIfM8KJDYtjaFXEqc9X+8h4l15fk1MYhxFvbaVFGBIhRAPDVYb/3Gk fDV22nc7BRggRZPmwzj6wVRZ3LOWAspO6/YNZz+jurvdhoKLKfDyU5uC8ovP yFlr8T//LykgMDve6KI7gYRXmLrffEiB9mfT+XyUCTSeJh0p1JsCsYiDVan4 C9Ltv7bW+zgFXjQ9bS7JnERMnpl3he+ngHimQjLl7yTqZHtoH1iRAvmW5L11 PlPopP76sEhWCrDV/8ld8J5Ga2v7SEGJKdBSoPnkz/Y0upetpNEfngL1b1Iu 3k+bQQIfQluDXVOgZ2TziXH7LBrxK/MdsEmBfi8lIQ27ryiLu01G3CQFDnNg Sr275xCDCe2NQbUU0JtT+KdpM48oo0mxEvwpsI9D6x8L3xKqCrmLhXOlQKpt euPl7iVky/t2fYgpBRLPtBqvuS0j3meU+5I7UkAj2vasDQsZDVuwuUT8SoaU z1nlUrfJiPRXTvjDSjKsdf99OntsBWleNxg7PJsMd5RIbSeaVxCdql9O5Ggy vPg0pTN/hIKeT+ZpDw8kQ3TmdMhSMQUFRj1mkO5OhswNUZL1JgUdEx6FqGfJ kDh240y5JhWRX2wFfnyYDEO5PUt4KhVV2vEdk6lJhodKtTGMQEXWdGg5+kYy LAQwue2eoSKeCuvbI3nJoJac/CP+NxW9PxdtIZuWDKcv7t7c+kdFaXO3uGNj kuG57NEZDqKeUyNJe5iCkiF/OmdvwleCecIYSR7JcK3hRKBfB8GNLju47ZNh JH7F9kQuwZeMN4tNk+Gl21jSMXOCF858F9JJBvzE+xdTB6goJfoI+Y4aES81 dE9zPwUlNzFOPDySDAY8P4Y9JAnW/TmsJJYMj490FHzrX0FJS1P9wEM8P9J7 6Z3PCkrkb21/Q58MeddO3vzUTEbx8e4VM2NJYO4al3TkwjKKFzQrcxlMgj7B 6Z8V35ZQXIt6PrUrCd6ZTZAkypZQLEUgaetBEjTddE2I30FwIkt01J0kCNlg 4hl+vIhihTeCd5UmAe31+xz8vosoxvidG2diEhjXqF+g+bWAolefOxSGJcHr ju9cLc8JTr5rKeCTBBxcdH9qkwkWLbhc4ZwEfEJC5uNmBD+P1ZWyTIKYVvlj p48QbOKl8cAgCQquS6y+37WAotYszihqEOPrHj2UNjuPIlM1Tz3Dk2Dxyi9e i5cEiyseP3s8CQp5SRcUaghuE5F5LZkEqT/snjBmz6MIMzZxHYEkkOE3deuI mEfhP7b5P3Algd9sX4ahJ8Hpi/uuMCXBzuPdT6rtCZYYZpv6lwjGV6PY680J fvFit9PPRBBg/e1uaEKw+f2dK0uJcMHDxzXm8jwKWy/e8p5MhCJT90BJs3kU Skr88ftDIrQfmBo7Zk3wYb+V8DeJcFY4/FGKC8GdNnN07YlwQN78t4A/wZaX viQ3JcK/Byy2Y3EE/1YeYbuXCCcqLNyqC+ZRSNahwbzyRIiflsT96uZRsDRX D29+InRYpuVLdhPcRdNxMzUR7hw78qx+mmDrlVaJaOL5OzWbHzQLKGjzU2Nd QCJYXhhK+Sy0gAJlH1a22CYCU3HuPVVXgl9dv65qkgjPNxUiE7MXUIBtakGX NvG+Q5MdO7F//nkOye9OJkL1G2YJ/wOLyP+ofoyJbCLcM257xa25iPx68NAJ kUSo4GUbigpdRL5/93kssSbClNchDbm5ReTj2KO382sCfP2zK/n3qyWUk/vW 6MloAjCW/6ab3bmMGjsHTD0HEuDaS8cEW2wZrQt/tJloTYCQGw5WHg+XUeCX Ga+WrAToEzm+NFtGRoWs835eiQlw7EvtmbwRMmrBloIkwhOg8/DrNW/2FbRV vBqV55IAS1IPvq5HrKBwkz+Z3qoJIPq58Y/hRQoqS6DJk1RIALnDD/5LC6Ig aKItmpRKgMzgXtKNCgqa/MpQli+UAMXbnuIeRP3R7GW6eWlfAtzxeYN9XKcg IbX/Kun/S4AVlZ06bQep6IwPW83TnQmwm51vDztORbY3Oet8fseD7QP7okYL KooZ5G44TImH9uyN/MJgKrpNw9M0NRMP6ecWDRpyqKjzCF9Lwad4SJI0Hvhx l4q+Wgo+1+mPh13Js71mbVTEkC7yguFlPLhGP+qcGqQi8WfiXc9a4kHq6I6Z 5EkqOk+W7PGtj4fLGWsUMzIVOR+U6ZOqjIdUeQ5Zs59UlKh59N10cTwYbnSh nC0qqg6SHy7MjIdsw97VfYSe9VQpjOomEPHyexl/Ebz0UWliVxgxnm0Uh/pf KmLehU0/944HPL2bn5fQO2kF1Tk/53iwcTwRl/WdirQczi5JW8ZDEXmyvHOJ itxz1CkzBvHQIxiU2f+FitI7NNaKNOJhed1+ZfAdFdWtaa3roXjQ/nMmcZnQ x34h3U3GE/EQt0teCntIRau6Bn/hcDw8518xWrhBRWyRxjsDBOMhiPqKZk8a FcndN2WQ5Y4Hu9JM26EAKtKfMGf6yhwPz/QuP7lsQ0XZKnYcBr/iYKXDSFGC 6L8aXR25mVbi4N6/fxeb9xF6XuTC0z4dB9cTgyZT/lAQ98Y14SN9ccD8Q7cs ppuCCh6FHmOuiAMdaRwtXKagJ7MRCi+K4qBgxSN75hQFjXLGKAeR4mBc+Osd OkEKOuiddGY+JA5C3FTPsy+uoDLZPP0O/TiQaiuxDYtcQX1tRt1SGnHA9+Bw aKjLCvqjv1clB8UBdgF35jFYQeYBOWIO0nHAu/x3/IrECkrdbVj0VjgO5itj yexcRD9ZzLlH4UAcvI4pX0qhWUE8bVm/GRjiwC10p+XCGBlp6uu7X9uOhf/e IqePPWQUNMs+/XEtFuy6GPNutZBRlf+gsepiLLxdPZCjd5eMRhgz31R9iQW9 V0NeX0vIaFexrir7cCwUh7DU2maQkYIM26Og3liIClpQ7I0mI0fol5x+EQu3 M89FiAaQUa5eRpnmk1j48HHZ092NjDpnLnE+vB8LqirNUVW2ZPTDjzXxYGUs cBWTG4ZNyUiEsW87piQWMg5R83/rkZF+UZoXOSsWFAsoZqwXyShaWnvOMCkW diUIvth3jowePGe58iwiFg7HjMlzqZLRpG5vv5h/LITKMbfuVCEjtpkUtXS3 WDjY9Y1p+iQZqfpdfLJuGwsvzVei6xXI6NouZlkrU2I+4f1ybifIqKyw52a3 Tiz4le75xEFwn1TyvqPqsTDdX0gtJ/jvM43UApVYGEi+f5tbkYxkdHfv2CEf C78Hzk+7K5GR+fQrPxfJWBjst9a5TYyf6pu4NCgQC25LsvpNxPyeMlywUuaO hUCe/zhuEPNfLtj1/iZLLPQ5GQZZEOvjkeq+wEwbC1p/2BWXiPVrPot/5rMR AwoXa9tOE/kJ1lE/Nk6NAZc+LQMrGzKqnqK/ozYXA+eTXH9iV8mIkSGOtHco BtZLIgMlw8noZIEaffjrGKCfeGEtlURGTofpgucgBjQnulxGcsio61KMXfO9 GLAMlHl3sI6Mfk6eGRG4FQPvMrqaK1rJSNRnp3ZiYQyYj5m8bX9NRjH5UQqm 8TFwmfP5o9x5MmqQPH23PTQGft7Z2YJ+kdF0K43gYZ8YWJUJM7TetYJUJyN2 b1nFQPXvEO4F4rz+lQgfL1GKAbbvN8xwzxUU3BIcPUmOBje7AyM8uymIeo5e MWg6GnwnpM7J8VOQ/WDGMvtINBzp0MYxeQq6tHDb8GxHNOi8uxfKYkFBItz9 4pWF0UAe5tnvXkfUY7npGJ4RDeyn/TK4XlAQq8xsxsfYaBh55ptj+4GCfp/d +M3oGQ39nMkdfUT/1+sl8sZVPRr2nR/LoFGlotN/aiPoVKLBL+hL4XcdKmpK PHm8VC4aXrWfWr1kRUU3rmuX9vFGg4whjImHUtFeqRE9J45oYNEqelGQRCX6 L1sGGsZowBL+XrfIoyK/twHX5L5HwR0T/MhALaGXJjtFexaiwEqfgyfgMdFP zqaO2E5EQVebn6fdCyr6cG1f2tZQFNyoC92b/YaKNLfKT+e8jgInq9xrdO+p COKl16UhCvY2ejs3jVHRcY7mmpeNUaBkLuZWNU3odelpK8uaKGi8nOc0ukBF /JK9nL+uR4HoEn23FoXQu0bjVxm5UfDXxcSHhtBjRtWpUImUKNDejOpfX6ei sDeucu2RUcCxR/+RHKHfa8brX039o6D0RZnXw20qcpqOLFpzjQKj42Zt4YTe j7sz66TYRIHk4xOv8gg/0N/IpRW9TDwPn9v7j+DuWMHHT7WiYHCYN7+VYBW2 u25GZ6KA/F0gd4D4vqH4hBBFMQquuKXfP/OHig4davsQLxMFs3eqh7kJ/ylp 0EwWECFY1f6cPtFfs+Mf8Mf7o+BBQWDI5g8qin9t9V2XNQo4peMU936joi3D pTuLtARPL3pWEf7mOelrHr0RCZvRT/Va5gm/dP3HdpAaCfERr4/qEfky+5X0 8uFsJFQF2aX4jFORGut12a/9kXCkmfa8Xz8VPSmUnAl7GQnWBvlHbF9RkaxY Yz53ayRUGuXn/yT89oDKa5oLlZFw88piqhRxP0/vNng0WRwJPKe7f45VURGd wYRLUGYknPN0SLlE+BPF5fu7mtBI2JevUJ+bTkUv8vkq/jOIhBMjXaecXahI Pd6+57JGJATcfbcnyZrwW9+71HIUCQ+WjhSWX6aid3pKygrSkUDD+8X37Tkq mmI26rekj4QJDzGJbGHi/R+Ki3q/ImC6mlflJ3E/eDf4Un5uJgJOtf1j9mGn oumUqVeszyKgenXv2UEaKtpBc+C71bUIsA5esAiZoiDGz5XYjysRcIcvu1Jg lILYWo4nJl6IgBktnqjNdxQk6KvL90AoAvCbMq6WLylIQm/C6RxrBLyv+nmZ /JyCjsq6NXzaDIeWKf/MlscUpLqQcH7n+3AQ/q/0t0AtBV14uTcrry0cDlo6 vm25Q0G6N2+NH64NB/zOTrz0JgWZRMgdgsJwaNRYgVelFGRlDl4G8eFw13b7 Fl5IQY5K2k/nvcOhnKaOmyaXgjy4xxhCrcIhXKtekDWTgvy/O+uxaYVDm0HJ HZc0CgofWC++fTIc3BYNPDiTKSi+NnbupFg4RMU+3MuSQEHpyRxyb9nDoerm MT7DWArKc7oRYvM3DDL+uc0sRxH9n5ps18+lMKjUGK4ciqCgSqGnbMkfw+A6 vW48czgF1f3VuMLfGQZP34xFZYdSUNPYx4qG+jBoD8VDXEMo6Nljh1X10jCY zLqlkB1MQZ2535XHksLg00WNK0wE93pHxV3zD4PGARXfAaK/fK+zZ4DWLgw0 BDdXZwkely7lKdAJAz13ZvHzxPuzu6UcpFXCYIthTHudYPLc4/ttEmHQ9fps 0jdivB8d6puGe8MAYzadVAyjoO0b79UWd4SBiDfT2VfEfOnCbTPCKKHw8c5o UnkkBbFcWf3EPhYKF29n+b+IpiCuk+Gild2h0FCz3SgZR/Qre1muKTeGEue7 YOwDkS/htcInfTdC4VehrttLIp+H+w/R2aWFQmalzId1It/KSWcLUxxDgV6v JXE/sT9nHAdnBAxCIVBiVJ+e2D/Ns1ayjSgUdo/F/5Qm9tfsT3DH+P5Q4AlJ ZxGrpCDbUUZWL/pQaKE3jfhWQ0FXm/NM6NdCAMP3vV69T0FBXg0rMm9CIG8o SSOihZj/6eFm4aYQcA14XBDdRkE32Daj9pWHgGRlDV1zFwV13T/NvSMgBL5n JdjeGaIgDsoA/l44BLxPeIjrUSno3lVqRnBwMGz5PWpnkqIipMxpds0hGKTs TTtqjxH1s1tR1F43GAqSepl0lalooyr8sbZ4MHA7cUvFaxD1Ov/flOC7IBA8 oqTr4ERFn5rk7u59FgSs9W8pdR5U5BZv5MdUFQTpuWvZk36E/oqV7v4RFgQx e7PCvsVQ0aSd9LFuySCQ+/VMNK6MinzkdbdbuYJgQmJ06PVtop+n9e2q/xcI fzd/jMzUUJHMzVazog+BMK7CaUFqoqI2ry+iGW2B8Gwr1lzgKRUZnqalxtwN hMVu3sbQdioKntSMcY8KhP0kpTslhJ/8V++hbesWCL2vs2vMBwg/i8jad/ly ILwcchn+SvhLN//oXVWZQPC9YN6p85nQR8ofvxP7A+GYc/mU7BShX8+EVA/T BsJMCM3E0CwVcVm4vOf8FABpTXiY+zIV3ZFOK2PsDAC3Ki8vG8JvlLfrnf/U BcCywpe5A4Q+9715f2ytMAA6Hg0P5hH+Y1P8e3suNgAwSQG1EeL+8eMqb/fY tQDQaex1m/hF3EeUVTMHzALAqiA4v3qDig4y2V95eS4ABs7vkFYm/KHuU4JY y9EA6HkTX0si/Ol09V1q3cEA2Grd11JL+Mn7wP4ntxgCYPZwxe4swm+cLnyP KfjmDymJPu444Ueb+/ZdShv3B8dpwf6H//+/Zl55f3S3PwgKPT3ynWDBZstp /wZ/8ItlufOH4Mb46Huupf5AW3DW9j3B540r/a0T/cFXzuJWIMG8ur+Mm338 wc7wzXMKMd6axgVFVit/KDv/u1+B4O6zhfscNP2hYqLulD4xvxJs6VfrCX/Q eLTkd4aYv7fiqREOIX/o9h2n2U2s77xc6mMXFn+QKhx1vUOsn1fqc0HbLz/Q lgrRFyD8cE1UNmjfjB9Yexpd8Sb8+xV/hKlHnx9It4gp3iT8sXT/gNLLJ35g rEu6Xr9GRRdYvDe9SX7AobJX1JPYH36GjtHXIX7AY2vzUZTwy+//OFsFnfzg pvXzs7BIRWXfH4X0YX7QGre76h6x374rDOZikn5QrlJhTEv4p8b8ZZVQLj/I 2Z0ueZ64v/0Y3diWXPYFtx+nHpR+Ip6/wMLjCnwhvjGFp+Ut8Zz0MlLluw8s 306aV31E+FUyt032hA/ETGj+d6aBiq7HOp1eeu0DrxPfsmndJ/qfwN07C274 QDltfERkNRUJeJtNU1J8gN7oR2NtJRHP9e6LcwE+sN7dc2XxFvG9lXbMd20f uJRfxZRJ1JOvaZmdppIPxHvWBv4rJuIZUM+Wi/pA98vbIlGFxPfqmXQ6W97w vlXR+QVxv+5RnZ6tmPOGsBXmrZgsIp6y/MvtQW+o56c8NScR38t+iKup8gbG YBvRy6nE+ZAQd9yR4w0pq7hecDIV/RQKUDeJ8IZ96HZrcyIR7+Ar8ftXvcE9 k5WWLYGot70HdjEYE89nvR/HxBH94Z6r8+anvaFW/qIlZywRf3dr90Npb2Bm qXGGaCI+LUsV035v2LaTxBKjiPjb5ok2tN5wrERW3iOSiL9e6/yY4gUFJ0ay vSKI+Kt/L+wZ9QKGbOWirHAi/pKOpONLL3DWcfQZDCPiz97Y/azeC65y1OCy BAtOfFvkLPECG+36/6qJfvbnxzM9VxO8oE+1ePY0wT2D2TXt3l5wYtOj5XcI Ef/NbPJ+Sy9IWaILektwdkqd1jtNL2gJd/0FBMdfDGRNVfSCSGUupV6Cg5jP DJwT9YI/r6+xrhHs9oY56x+bF0Qd+IjLEfGtUj4YPPnjCSWCiYlJBOtfvL7X Z8kTBC4eLt8k+Byzy0fpj56wM7HtRCwx35NvjhXOdXiC8SWWZTFifVIp22Y3 6j3haWyVxReC+S928ZqVekK3rIdwPZEPdmbSBGeyJ/ioR3XlE/mie2N6462/ J8Dl+v5cIp+/kkVsE+w84YdS29NqIt9Lmisip3U9wSbTn36I0Of+nsg7jZKe gBu+craLJ/q1ZE0XD25P6GDSNnhN7OcjTS4pCVpPaDcYUDpD9P8KuToWik+u QeLZBPOrxPl4m1PqSi9wDdx1X2ZFZhP9LpccNfC3B7RJDQm45lJRQU6nN3nQ AzQKT63b5lORfc5y0FCsBxC9qWUAcV63s5USy5fcYXX59GNewg+mOd8y7+10 h7sFt9AV4vy/yrbOSCx1hymXl0U3iH4zJzsh75quO4TOFASrEPcNqewPt7Em N9hqyawpJ/zCLMur/VOUK/x36XK962sqUuWgP6d9xRXoM8puPSL8QTyr4FXb cVdQZCtp2iDqdS0T+u/MX4WHP5m93N9RUVLmfxN+2leBWdKvdnWUijzYy20W xa/CZgn592+ifzbMPP7VnOYq2ApHaa1PEOcr8wr57EMXuJj1Ye4toRePSdWb 7AdcYOaLq/IMoS+NP53D1KnOINN1MLmK8I8HZhI0IS+dwadbqtx8hYpqRO/Q z3o5Q/LXj/4Zq4S/JDkm7r9AvN+r4f8foWe3KWLM2vzOMKMx+jyQ8JPSx7fZ mnqc4Gi7/X5uQg+L+Oyzl244AfMF38fnCT/JixbhFghwgiVsBRwI/cyeny4w 0HaC/vk5Vk9CX0laNw8mijhBnIp+huP//69/YFP2dMMR5hnHjmsQepzELST0 rd8Reoteb+8j9Do+ZPKWWKUjmIQurrwjOHryurhZqCPI3ojeH0zoe8Q5q+p0 fUdweMyS9x+h/6E1/NIdEo6QSXMqKY3gwD0Tdb/+OgBTXTnfJsF+vqVy0h8c YNCgIsGA8BPvT+aN1ncdIOonTldEsAfOq5gb5QCbzc0jbwl2vTX25PVlB+C7 GqlPJdiZsVjlr4wD/EvZ6PpLsL27GRyjc4B1S4bsbYJt3h044zRqD7uef+dZ JNhS8VNncb09tOsc7ukk2Kyk4PxAvD1srL3hIBF8eYdJD52FPRgvhrlfJNjQ cZ+2krw9eL1gM/1FzFf3zXC/+257WOUTN8shWPtonv7NL3bQNrywKUywZq7R h+FHdlAw9bDnFpEP9U0uE+ZUO9DkbLHYR/BZq/ejyNYOMPG7WuFE/lQ7sy18 T9oBLdgd/0TkW0XSYLKK1Q46jsY9kiBYKZ3D7vOsLVQ18/i6E/tzzCTTWT3T FupuUi58IvZT9pnucrCTLQATerSDYClhNo/7mC2oBbsyCRP7L0pO99m/ZAOF P6lHtIl+Y19kavjSGRuQVm6esCb6E66vF3cIHLABpzKdrSvEeWPTZI41oFqD rh5fhiGVipi4kpOeFlsDR3fPmCpxPn/r7JHkW7QCyjHayf3EeV47kC4bn2sF WXPR2RzE/Xt5huU49bQV0J3SpN9D3D8nAphQe5ElkByrMji+UlHHdXojBy0L MJSf0jck+qtj0U6Tpn/NgUS+1RM9SUU37V+7Xqo3B2peSEAz4a9RkmnRilzm 4Pgobe04UV+rzNT/pLuuQPTtgIBwol+zpugWCgZeAZ28tLJ+oh7RQ6763eNm cOCcFlvyGNEv5fqf+ptmBgal7JTvRP3yB450rSEzEJfaleNIcLqZsv78N1N4 67uKpgn//qNS8nnslino/3l22IlgN4G/zgNGpmD61D3x5whx/99h/aNzlyl0 dAkmphGsNdse8eSJCfSH/zE4QnBrlwhznasJHNiSZB/7SEWHq+PybvKZgM6D vi8kgotS5oXy+y9D2c3tUV2CmTw0alOiLkP8x779BwkO0r17MlL+MnRnGNZQ h6lo4dh/nb5fjSGZObm4j2CTvdd0XPKN4VFg+Pdmgl/9Ghi10DAG/bBjjXcJ Vhw95qi/ZQR+1O7RaoIrn+Z8U681AnoGe6sGgrmvr4eesjIC5lT7Ey8Jjo8y YTzKbgRLDKoXpwn+adeSLdphCD/8u5J3E/OxV+cVOOBnCB3vGD8pE/xeIrzm v0OGcKfOj9ufYDXmyRM7PxmAjBurQCvBD1dOt68nG4CHvlbPbiIfwgO3tJZV DIAu3GDZhuCsBvqRLxR9uMHLoddB8M5cJ7v3N/TBplWtS4bIt1fAa8orfX3I GalgLyd40lQq+BmdPlit7VrnJfZLVyWNvqFJD/Ycv3qsnOAjO/R4i3n0QKh8 T2k7sd9lMw13Mnp1YWY0WdGCOA+sXVzyseG6IObcvZOGOC+jex9kj3bqgN1k y6QpcZ6MJdso4YbaIFcxymFEnMcTlBh658dasFEbcFOQ0G+uh+d59Xi1YHd6 YtIqwe9U+jVEZjVh5J/Oq2KiP7ykO3G72+cCmKxs3eAizr96wLYZW/ZZULIS fiVH1I9CuqQI0+YZWPp8fIaFqC/xCuNlWpszUCdR8/IrwbuG6kN+yZ4GRt4C kwxC3zMtek4+y8XgkTtZu5moV+8U0df1dirwue/FcX9C3/WfhJveljsFX6jP t48Q9c21Vz445e1JuP+gciaLqP8fZ9KYIooVgZJda3uK0PcPnvNF3i4KgN5c iflMcF5vcasp/XEQMppO/I/QF//Nnxe1h46BdNf32SKCL0vojquWywF50ntQ kNCnk8Y1bsevHYX8T+Ic1wk+yrh7UydYFkQSdDz2Enr2ze4ZjyK3NISo9dTH ENwAXqf4GyTBZJitapFg34Pi5vSXDkGnvJ74eUIfTwSMhpIXReHiyZIdJQSv v0svHYoTBod/HzgXCG6WPfu8RUgQek5+UpYi9HeVi/rsbMhB0FWIMXEg2Kf3 8j/2h9xQcL9D////v/2MaVOdXGKH0LRczucEU/316SzOMcHiC6mkcYJ/fBVJ 2GikAXeF4YpvBE8afDhkkkV+/mpb1Pr/9xveydeFrpZDOG9DT8P//7/7W9g/ afP7F878oavk9//vSxZ57jmp9OheoqrQAsHrlM6lX7x7kFpi4fk+gn/DxsNa Yy7U2Opz8C7B/oyZ3l/4D6CzGqR74f8fX1dCjn2eD1F5Zlk1CH7S+yWg/LIQ yjgTbMb0/+89pS63tIqgh3/9774g1q+wN0BhSEAcHT2wS9j7//745MVecowE 6ikzmN5PcKMF60+6hcPIp8eFq5nI7/cdZu/5tGTQ9dJTs1oEH6useKhQfwTN GrtH/a9C646nsg3DKWSvJFLKSkNCynzfm1B2GVllZY/svfcexzj2yghZJSGR PUIqO3uVfYwkpPre78/rd8553ue5n/u+xjlnHLsvbTc2USEJQdjt4vk5hd2v u3x7saTtTbgjzIloYDiF1YpZOVcIWKxUbrVh+jLS9OaXKbEwUOxcRqOxflEn U65J6ROHl8U+yQNY/zmO73AX/JWA6wVivP/7jYSyVPxLfhTm1sz7NbB+tbjs WG+iIAkvGORT2jF/UtTXmOZTcQce/L0u4471+2P2uSE/DWnQc43OiMLmg86V mC7wUBqkepvSM7F85nlBMTT0riws35jAvcXymZLjmGPc9D2YUDiI3cDm61jX 7/L4YDkQrvZQOsL05Q3rhZXEq/KQ6RfVQoVhtg5Tg1RXBQhUURsTwvRm68wP xWc0ymDnLpVbic13gQ1TWH61MtDpniEZx/RGp0W0tVBXBfzO6J+kwHCrlb/I i+f3wVz9Q4U3xg8NM19ENS89AKuWFoFmjD+YIo21tDweAA9iRU2J4Z7p0ASd C6rgI/jJpA7jH64I5pe6jqow60yUx4phv5svPj7qUIX6X0r1YRhfjU+Jrz1m VoNSz+0TfzB+Ewr/SKZvrQY+O4GfvTAcK2hwyeC9GoRUrtsQY3h5ckvakF4d Xr0SZE/B+PJOWKCRkYk6iNkK8QthOEuA0e9JrTpYTVWP/q83+xOFmcYUGqDG 9O9+LIbVQoXrTfQ04B/Vcq8ihsv4P4yavtQASrsMd0YMk07o/jQ78RAiT4T7 LGP8bxiyzmCh+RB0+ASPujD87oYvv2XJQ3jdKEL3+n/9GKdVsTp6CE+WqD79 ry/2wc+sre9rQlw1o1wZhnv4bkbY5GmC3V/b4HoMc31tf/70pyb4/iSEDmHY N0iz3VZOC5KfcyodYvjr9eU5uwwtyPZg77mG7UdozOOfPUEL9OdKtiwwHBtI ed5RShvETpOVvMLwMm+WmFOSNtjF046Q/F+PUT5t5yVtqE68rWGK4cyAZhcX MR24SrA/+IThvWtqia4xOlCxq4+Xxer5YGThpdusDjh0C213YLjU36Xf/aYu dHROf3qA3Q/ptZPrHqG6sJF4uPENw4bDqeReX3XBT/j48RDsPhmvNsj4+D0C +5nrXTOYvtgOKT/xHXgExk5HnelYP3T7zvj5cT+GGGsjXX2sf3wGj78L6H0M XFxbaX8wP/PdW14g9Iw+/K7VmYtbwOpFs9/920QfevzTCh0xPanIfW7oUKUP EuOFmTpY/7q1n8A9VjaAXzzPVQWx/iYmNXBLkzKEky2N7kRYfthTuS2tYWEI PgW/ovcxvJxCTUsbZwjH1E+tbmLz03el4XnwpCEkZ+ENprD5SlJmGbFzM4Kk U9eoCzC9CU3eenY12wgIF+yUYrF5dZ/pevqt3QgWdL64Oe9i8+rgSvKI4Qmc ULmmK4jNu0q98pfTok/A2tzwJxmmP5InuLM+GzwBpicfZL/+7zfxg0J3y5+A hPruiAnGH0zTL44RDT0BtSXkxAWMX8h4AvveHT6BmYcqDZ8xfGink+rKbgxV VOzeHhgfrdfxmwjIGUN/4+R7Zoy/ponI+NdtjaFUn+pEBYY/K8z8fo43Bt/K 2Q8iGN+1JtZ0GTUYw+UFo5Q6DFdPxiSeWzCGtp43O7wYXz7nNjUYJTeB+Ywn ZngMp9pKXEvgN4Fjt8P9tzEcWXvql5KWCeT0nRmUxPjY+9ha60lfE5DWJ94N /D9/yLfGthaYAK7pmU8thg0T0nR9ek1gSqaUZvr/338m7C+J7JiA9ud8hT0M y3DJ7ewwm8L+2PLX//Xk9tML78vBFKzbKK0OMXy5Zi/CwswUuCmmyr9h+Oy/ jw85Y0xBMKJerwXDVHKF7NOvTaFVoVY45n89wnlvpI6bwoRQ2T+5//Xwq/pb dSIzYHRK8dvF9j/PcS2E5rIZGN1JDIvD8LD1cdUPKmbw5SMNgQXD3dVfzwW7 mIHp2mFcIlaf+j8vl9FMMxgw+frgCKtn2d3w6oNWM+hGv53VwHB2nIF/9YoZ XP/KNvO/H8CN3VayozMHSb14/P/3FchOw3xV2Bxqes4hP7H7NXvdUJkTbA7n 9BZ8KTH/oX2U6KVbag7XPueK/cH6RUHW+t7pAXO4HJR3dRrTB75RlpnICxbw gYtIzBbrt4sXt1/I3rXA+uFT9XmsHxksu12PPbWAaaHWs42YXuwdutK41luA 0ERyRR+WP77oc0zYLVrAcPUHJVasv8taPxZZ0ljCt3FzW+3VTTCO5JLSe2IJ XoItF3K/Y/3CMuAkQ2EFmQgS5IzNY6mPjyQqZAVc2plwF5vf0LnL1CL6VrDZ onuLEpt3pMTv+bUqK9DtYuh1GMbyuMj1rwy61sDxl024u3cTQjLHCqmCrWGO ueKswgesH44FO5JWWIOWp8JGRyeWr7rHKQ+JbICBzpK/smUTgrXC0bkSG1gd Mf1mXIvlT9eF/MqDp2BWr2yA5mP5bjzWvoTTFipoGIi/5mL8gooh+cq2MPGa hs83exN6SeJHkp/Zgnun0L31NKyfLSXycb22cGxwQ6E2BbuPj0t2kT9tQXts /TcOj/k1PEruK28HMblxFs7xm3DqYGXYzckOPMgjz/rHbQLhMT7PIcsOVnos TbNjNqGQa13cdNsOOg4fuDFF/p9HFYMrqe0B/wY56RiO3ZfrM6syDnvYeLfR vBC6CeTjSsLPlexhl49olyoYu5+ovPP5RvYwdEHmsCNwExaR/RO5rvZAJS0g nRqA+eVN5dXMKHu41k3mF+y/Cc3P8j+n5doDa9cTjSg/jO/UD2qS39iDqdmM QbnvJmSQ3M9K7LGH6ZSUm2s+mxBeWxCEm7GHWMV9TVkMu1oeWsbs2kPhmPjd Bm8sn7A+eBBJ7gA4HzbHBxhW/Vh4O4zNAVrOuMJxDKN+v88F33QAn3/rpANe m8AroHoiQM4BHlBUMTZj+OzC8xUfPQdYHb1c/P/3d2T4o0+ejg5A4RLz4xeG 9+6q1biFOcAx7Q+sd7D1FvaLMp0zHUB6l0qkFMOx/p9taF85wKtz+Fh+bH9i ZAcSLzocIIuKt2kQw9/i2Kllxx1AKYK7Lgk7H+6MwtQMwQFuu6G6Ttj5JXIc yz1POIIuocTdDqvP0qUMn9PMjtB3s2ns/+8/EyralF/yOsI236zA/9+PorfX zytKOcKGkv51Bqz+q42MhG8PHeHBtLdZQMgm4GWR9/5WjlDQwmNFFYbxqUas fk2iI0TrxzU6YfebOlnDp1rsCMPa5TMq0ZsgbTLzd63BEZ4VkDlIx2L51Ik/ h/27I5wYyFl2ScDyzG9tu4ZDR2B6Pcb3//+xtgMDQIvWCYg1HxUQY/0nlzAw Ey3iBBdqSu8sZ2D1eul8cT/SCUR8TmlEP8f4kVD3rP+GM/yY2n93/T3GZy5z DpYyzpD/7rEmis1HyR/yO8Q6ztDd+uff/XbM31E/mhcNdIavtNyddj1Yf1z7 w1E45Ax1VrZu9phf0H3N/QNWnIGR7TuXDqbfJOIqbeN/nCEgNuGDEDbPjxVy jOl4XCBZxjijEfN7FJZSBV4eLrA1z1Ewh+ljzZalM1OsC0g4ypnzYXpo5J4g 8yrPBS7ndVobYHxDdewdo1KtC8wV8353xPioLmxh8XuvC1B7d9CZY3poQkv1 JmDWBVCSIl4xjN9oU4RCzv10AfG/SYGrmP7Vs+k9rCV3hdoy1MT1f358HsKt xuYKHdFk1ycx/mTgq/i5LugK6F8l6bMY3za+GekIu+cKYQa8LDcwfrZA/uE5 HruCaFHL9f/5m7GDx6zR3hV4hY+oRzHcpPTgtnaIK+iZDD00x/TAasid9Eea KwQkUb7qxjDT42cjMRWuwMZvOnmA4ZaFD88vt7lCeOHj5/9jlUIPvOGIK3SP De32YnjS7Epw6oorpCODng7/r3f5q+PnI1cgxz+3XcGet78SbkRG5wZJJS+Z bmI4tFTkgSSnGxwX3/+gjO2X8eky6n7bDR7xfNoSwc6Tx5d6/aW8G2zdFiLZ xc7Lv3Xv3PJjNwjKcUr0xerx/tUviov2bmAWGC82htVLyanoQCvIDWbni8uO YfUcF9Jajkt2A8d1u8pfmD5Y7JGOdpW4QWml57nGbay/ams6/jW4AUto9twD LD8Ee5hVC392g95yMaLXmB7kHnXEF+25wYK1Xss8xv987138Z8jdoeaawaeX mN9q8OO2O3PeHeRzGE6pYH5/7HiIUpi0OygqsRHtY37RrF1IvEnTHSwqp9pI MP7fDVm88svSHb4p0mwsfsbum1zmpDnOHUiubsae7cb8Zs+Pn9n57tCp49zj 2LYJV6PzF0dq3IHOY3E7B+v3u7QnWu9OuQMTlaOtTzXmf0+3el+66gEN9ReN LTB+pxp1sNZHPKDPyLUiMhWbv1R23eQHHqDE+L06Gpu/GtYAYVI3DxAV5K+5 jfEvgV1y51ubB2xKcxg+tNkEPb735oV6nqC/66wVcAvjg82nmlP2ntA5GjoQ xof5uVfnZU8He0KzkypLHA/m/4R8OEJeeEKSN2NsCQvmD8Ukpkx+eUIYo5at 6l8C6B6t9WZSeMG9DjW3Z78IsNyYUT903guO3txMINkmALHU7xQZGS/IcWx7 dmqRABL36tW44r2ApWFgKqKXACjTUMvvQi9oeOiLk+oggNS3Df7Bei9IH0wV 5WkiwN0gdtrARS/4IEPTEfaaAHJq4r46B17gfBTMT1ZBAEX2hxv8NN7AoQl5 LcUEeNAU3jsj7A3MTbeOVrIJoBabJ1ar5A2Wx9eX9dIJ8FCvoSTWyBt2D0Pn GZMJoM07wmzm6g3iaKMIfQJ2nt+bYUiUNwSZinA/jCXA4x7yX4y53hDCf69n PpIABmmcZuvV3lAWxibYEEaAJxbIcNsHb+gWsFNeCCaAibCWTMa0N/SqlO7o BBLAjNThteMPb7jn3z/J7k8Ay+FIDgUyH8hqc3wh4UsAm4KCePbzPiB+qX2y 1JsAtk7vjx0I+ICPkv2IvRcB7O+M2X2+6wOeMb3j0Z4EcKLfmS565ANNhdlU RBh2naVU8bP3AZ5V86f9HgRwr+Ru1AzxgcHes5M/MezpC7x86T5w6bghozv2 fh9lnQySSh8IKIotf4it73/OiWKqzQfi81NY4rDnB65Fe1SP+YD9jmQBF7a/ kPrny1EbPoBG7TswYfsPj2jWMj7uC+5vzvuZYOeL1B7vFDvjC3901rJpQggQ w7N7i4HXF1JoUj0ZwwmA26MuXJH0BbM37jiXKAIkdPAwtjz0xeq7LygQRwB8 klRQqpUvZPX+CLubSIBU40c7dn6+YP2oMKw6hQDpgi5G95J8gfXBv98emQTI Ior7zFbiC0mJL/zwzwiQl9Na8XHAFxQoKm50lxGgwHbyfOGSLyy+PsyeqCJA EbIX7X3kC73hkIe8JUDZxBXra5f84MLDtdaFTgLUnInnifDwg9UHTg2W3whQ 9/1FsmGsH+TLH3kXbBDg3Zt2EpF8PyjnCVQ4vUeAZvX9he99fmBqvb0UfhLT 664bDzjo/KEmUmNBnHcTNk+kUPkb+wPVNZhSdt+EJ+Hm6mJP/WFwKEqYCNPn ISqR9F1Xf7ChIDmZFoHpxemvPJaR/uAeMKdgmI7xQXqJLWeSPyRkctQF52F5 nc3zzVSWPzD7lsS7vcD8Gw+rtNorf3gadPffq7cY35SuRVC984fqqy+lCM2b YM7f8Lmz3R90fPvU57swfqyOPhPQ7w/U12Liwvsx/hTV0xcf84f1hmjNiSGM XxuvF/6c84dxdcLpYczPCtz5u1a55g9dyZwK9hjfFXT2C1r99AcT8mtBRVi+ ZFLM8eD65w/qfvYWLph/Dv9k1zxNFgBqulKNQ5g+/laXPJnGEABsJTsmzZge 2o7RqaifCwAl8vPmNzG+nn08l0R9KQC4gs7uXsb4XW3u1UTXjQAgPS5imYnl hw7TQI5A0QDYvMj4MALTC5FVNUsJ6QCo5Cd4rWF68sKW8+WeUgBYjg9P/P/9 3bkfP/ZeagZAQdLky//zU5xbO2JtGADJ8Mv9BYaPHyUFc1sFwAUJ0f132Oed /U17Z5wCgG5CVUIAW/878W2GdJ8AOGkgnHsSe75OBKmORlgAmHi++ySB5ZM+ 6tEcmvgA4D/l09OP6TmaUPS9Oz0Awl5yL73D9P8lk/v1oIIAeM85N3wc0xPO DDlnpCIAAtuO5+dhepJ8geXdr9oAcE2/8DYdqydZwQpRVUsA1JiNzK9ifsTz cr2cTW8A9H8PU0oc2ISNssi4S8PY5+vtQ5IwPzPw5tr5jOUAeKFwFV9Yh+VF sSPjhzsBUCfO5VdXsQm17/te0B4FQFtuvf7VAkxfup6KBNMGAoM0h+MtzK/T KKF+KEsgyN7ZGx7C/GLAZ5rOfY5AaJXviZ5xwvTra6X609uBQNZ22/aeNqZv ev7pPJKB8HjWrL5cfhMU5x/MzckHQnugU0q8GKbPa9u2mnqBUJdy6tfSWSyP H92MhOBAUBYq/+AxQoDYi3XN9AOBsPPqCZ82EGCW1vEofSIQgjti6Zl5CSDw 75oI1zfs8098rT8wE2BoKqfy9n4g+F2qCb+4swFnM8KyH7EFAfM7ebLAwg2w iZQaX+QJAktT1/aKhA1o9Ph92lYgCJ41M8lS+2+AobZdjL9MENz/dErc79EG FJ7W8i60CoLeUIZ7dEwbsEdMX8fnHAQRx3Q6C0g2QG6350etTxB8VM6iK/65 DqsDqHUPLggG32WZnRldB4nW/efq6UGgYW4uF9+9DjGvquYn84Pg7/2dLHz9 OvDjLulu1gQBg4FsrlbuOgT6zeLdm4Ng7hX/HHvSOgzapn8h6gkCvt0n7+LC 14FLX4M6ajAIBKoIZEU+6+CqTCPPOIW97jzn/NRpHboluoOzvgeBs8CEx7Ll OrDwBjZf2goCvOWo4XmjdbBilTiqPAiCn8m/gF5nHRoo9oRFTwTDSIHIQbfq OtAcVjq1UgUDy6uTovKK62CwYlmpyBQMt3a2nZNl1+HlGOfa0AUM+5xdrZZc h+PdU5f0rwRDU9b7jGKJdVCvTXmyJBgMbh99VV1E16HguWq2vUQw3OfMxrMJ r8MennL8QDYYJLTpXxfdWod7IR2ng+4HA6mR8+tTGE519lOl0gkG3s7Wx6YY XjUWjcE/CYYB5Adfzu11EFf/0c1mEwzuU/JGbSLrEH2nnLjYJRjI7hTODIqv w7SAuaSAXzBkPtK+NwDrcIOd3bs+PBiceocXmmTWwZ9uolY6IRg0LiqVZims w8C/pB99GcGQ/S9fzAY7P9emyg3NwmCoEaz6cg2rj8s0mfVMRTDk5RarTGL1 6/zY+tyiLhi0LuCv+FivA3Oj9/x2SzC8a3Wyo3bF6lt2m82rNxj+nD9oiApY h3cZWzrEw8HwrZpXdC9mHfQ9Tb4wLQfDKx++1ZASrJ6WbNS528Gg7yO3VlC3 DkQ6Y3JXfgeDUerE83ysXwqElZrFaUJgdOZu+fW1dfh5ifSo/UwIBM+xsVb8 WYe7TM3CKuwhkENM67VPtwEruzcrDYVCgM76cPmj6AbsrnKUvkVDwC/HxI5L dQOOzdEXMciHQKhVyUkpyw1g/riZ3a4XAt6Kr7uSMzbgbmFp7OWwEKiSleQ4 JMX8TkZ6ZEB8CJQ2U0b0cxBAPz4idDwjBCIk+PunUAK4+Jj7Rr8MAZLyzB8q bphePuS03foaAlsXjLKefSfAS0UGK/nFEAifcinyJsL8rxSRWR4hBM5wnFWr Yd2EweszehonQuHgtP33VuVNmObs1ymnDgV79vZCNVPMT7I0PiRlDoWi0Ljf 9VgePk6aoVzHGwoly4sqkRg/0RxFyNMLh0KYFppRWoPl6R13WSupUCDNYIk8 i+nVpWVzqTbFUMD3fmN7g/lpgWlN5JxmKHB/+MClO4/l3yFZURfDUOjoDHVc wfhWrkfoVr9VKNjW51yX+bkJGs2cAjwuobBK2kavjPG5YQ3DdX+/UGjgnXnz /+9FNmVEV75GhMLZfJGB/3/Pcc/b4hJMCoVNouIgF+z14NSZi1HZobDUJxkj juWRuNj+c4vFofC6lB6PYvkiPbiRGXkdCvOOFY/tVzbhuWcZY3JjKPxk7/rR geXJKvsMus2uUCCvLVoQ/ojpq1kkldxAKAgKWKm31m9Cz2MPsmeT2PoP5ThN CzdhWM2C+PA7Vh9Zxn+cGF/PymkdU98OhWkWVXNSRyyPo3ePSn+Hgsa7o8oz Gli+Erq1T0waBip/YM/s5iYQX+Pa1aMLg1CZKMqTdJvAeub4Oi13GFxJDalK biHAJertJYsbYeDQTXGzEfO7gidmF1pEw2CeRvbwmSUBFDYbJ5xUwrBckZQi RI75xy6P3lG3MOgLOFc8c3MDRty2X+T0hEHM3I8bz/XXYJCC6/a9oTCgeH2L 35dnDT5nabYQpsIgJedSUPPWKvS0vRtFtsNga/RnH3XIKnRpEp58OwwD+zzV a48erEL7ykVCNHE4GP6TjE85twrvaUOJJ8+Eg/o2Q7Zm3Qq8y6uLC2IPh6mP t1hPha9A3a21s9euhYNBub6yoM4KVD16IOCJhkMEcWz8sWMrUEkIbGCXCwcm CYHN2eFlKAt4c++DajjU7aiXh5YvQ2HRWX1m03DYZyt29nyyDHliyitNtuHw dLHAfQeWIfujn7O5ezjkJhK2gy4sQ4Zh1T+awHBIV8BR3CFahtQfi5E1UeHA F6B0H74tAT70DJM+PhzOaNo0x/QuQQKLwjOSnHD44f14Dq1egrgyb97y4nA4 r9/9wThnCaKhslajKhy+tW7epI5ZgoiBuTtH78KhwL44StFnCUJNGfvzO8KB nlL6N5/9EgTt39VR/BQOocsSbl2mS+Af5bG4MxYOvvanurn0l8CHrcwufT4c 5FfqEzR1lsDz1fSh1Ho4xKid07PRWgI3GfrQlZ/hkCjqHe+ivQTOo9L08f/C 4RbLVZ+Ax0vgYOWaKUIeAcP3nZVyjJfA9k8xzyxDBHRKlxJNP10Ca9xEVdi5 CND96Wmu5LUEFpw06I1LEXDsXfyf/aglMK2R/DByIwL+kZZMb2PneyLvpOEr GgF1uvo5MrVLYDBZOMMtHQFX2d5x/f2yBI/txqw+KkWAseIX+6tbS6BznHLP WTMCKoVemA7RL4MmHgk4ZxgBs5+NPEmEl0H9sj1Vu2UEeNZeMe0wWIYH7/JS rJ0iYGcn/jVL9DIoqwxznPKJgBSPBA2ShmVQmDtZUR8aAU9iRWjCN5dB+uTT dvL0CNCp/K6KGq2AZHrO/Vf5ERBuPF34KGcFJK4PjGuXR8BSke/B3OwK3FYX 3i5qjoDd9iLdN09X4WoOEdvdpQiw12LPES1ZAx5BoZKNrQj4SkEdF/5nDbg6 zITwhxHglZhAKqG+DmxrvQqL1JGwJNjyq/7YBrD6/h2OOhMJb6/etVbSwvia XsDoJnskUNiKjPeVbQCDcLJboFAkWFW7XFVUJcCHz39aD9BIkN/ODnhbgOUx K1MaB/lIsLlieeixQwAR4o86y+qREJEhPX9VFMsXWUKFBvqRcGGSz07PDeMf 4cytEYtIiNFKRbJKN0H/ywkJFadIcFdMsfHA/P1pa+uwDp9IoCsO5/r//2F9 xIMDEuGR4CVcxf//7xtB2WJs1QmREJrJxm+B+WExkTzLa1mRgIqHVTFh/Lrz hfxNXlEkcIvwhqx/2IQSa4djZ6siwdF70MQ7GeNXkq+K8Q2REDV6W6VIdROY cyRTyLoiQcT1U1/ubwJ8Eime9/sSCY8opD9vJhEgdICW79cEth/RrSlrNgIg Nm4ett8jge2bztvbaZj+kcy0f9uKBHGT19+rSDfAWLTi0RBJFBQr9oRJN6/B 2cHTRYp0UQAh5yI2aNdgwMZnp/VsFJx49EJSS2cVJHOVIl7diALutucKw7PL 8Eu0euiyWBQMvCgJtudYhopB1ou5MlFQqHx2uMtkCc6fXKuJ1YmCdkNd53vb 32AoV+04qUkU8C5PiY0i3yBarF7ZxzYKrGr6NbbjFuHwacSidVAU8HlV3xq9 twCvTm7fWIiJAlk9CrqhinmweKbtpZsaBe+VJNbbz8/DRfHmzi95UZBlAzG/ k+ZgdIiHQb48CvJ3e/9UM85BrG2cXnNtFDx09W09nzULd8l+FQu3Ys+7jlt6 yDcLf57p71b0RQH1hRvvVnAzUC3eCZdGoyCc7PG9s6PTYD18PSprLgpUknyD DG5MA4cdfoRxPQo00TPiM2lTME72hz16LwqMlOVtPjBNQXyeydMTRNFAqdz4 Wv/5JMhJ9NV5UkZD4MXiwT25STg2cpN453Q0pLK+jTj5bwJq7TLuW16MBqsD svVrHybAlvxExuzVaBiRYY3lLZ4A7nyr71q3ouF+7ps6sqwJmJQYEPiEsd7m hBAZUckEJI2I+txViIaCOtv+/I8ToGj/rLtRIxp4FhmzJ6gm4TgFOeMtg2j4 t/DS8JjlJNTn2xuUWUbDWzMy5bXFSXBAxl5wOkdDa9SNcergKbg8CnvpvtEw 6d6gF6UwDTP2RVIMEdGgI6NDrYHMQDIFbUxEYjTWdyd5LgjMgkqB69ix7GgQ onVeopydBRJ0mtO9OBpyI2pGHlTOQcOorN1mVTTQlv78diN/HpwdyuvNGqOh qbBBnKx5Aa5Rniad7oqGzmSn6y3k32C+wFv14UA0nO+yZC8O/A6REzy8rJPR YEN3N4yVahluMgySzn2LBrnoJSbO2hWYlPOde74ZDXXJxD6hzmsQ7HelweYg GjjSPv8mv7wBvDVDyYInYoCkJ/HGJ2z+h9f9HPapYmCrEl+VUb4JvpzXlN4z xQDPxrk/r7H5vKQ7cin4Ygy8H9f5+/HxJvTjAogUrsaAk8uRkETdBrh18U7S CsWA8fVHFz4KrMHFv6M1w0gM6NLLmzGcWYZuoaD4jHsxQNsz8VCwYxHsrfls jFRjYHZukPooag5Y8r7e5XkUAz+zD26xo1PQOhbMvmESA2Z3nvEx846BFS3/ UZVtDES6+7R3Lg8Cw92JEXd3bL1PgV7qJp/hnXfoKzQwBlrsqX86U/SCyWuB aOLoGBhGHLKkDTuBanXSrAcfA1Gkig1uKa1QfTFcCpcTA5QpjB8YyZtAT+vm Oc2SGAhUcT1FerIeSGOn91hfx0DONIdzHuENVLRHfJlriAGFOr/4kPgq0Pwt VFbUGQN/+dj/tOEr4Z/AbOjTzzHwgWW178rvF1BsEWV0czwGpJUuN57iLoIH ObclDhZiYOJ0t/AkIR/2h+eYmjZiIEaC5qaa+DPIpYrZDv4VA0GnRU6Lfc8C OWmRPgWiWDj76I3jL9J02PZYeE5HGQvPDj7bpdQnQ/rL2IARxlhYxeUPxC4n wp0l0ceZbLHQb8Q+PO0dD6vnv91+cjkW1oiPtar3x0KCBo7+smAsRLu8td+7 GQViUeLrG+KxUP9AY9GaMRwWWr53vpaNBT/xMxMymM+P3o9/5nE/FlKPyQ1d +hcIQjcQb9CJBbbzRdziG/4wabqsSWIcC29D2LZcRH0hJDNRoNcmFkoGo3c4 yb2AbxClinfFnqcj+49bzB1GyFe/a/rHwq9Ein6XJhfwlcS3nIuMhcWltug/ MU7A4yaZOZ8YC8Zf3G3uZjrA5/I11+KsWCwH2YRYt9uB+2Kyqm1RLHQFFA+X vrKBi6x3eIVexYIQ5W8D1V1L+KC6QXpYHwsWC88Wjgeag2N46lxTO7Z/7RDJ XlVTONsk3RCC1YEjZalp8ZExtP4kJCuOxYIWPnU1Os0IrHnTHejnY8Fu4cbj GWJDYDSWVRpdi4ViQ9y4jYAeNKRtXcr6GQtP+scM2J/pgsnnDCLjf7FwmEe+ uPtAG6hP3pu8TB4HB8NRwj9FNaEG2akhMMRBioBkM7GmBug7Z8VXn4uDDyK1 Ce9z1IC0VM7G81IcFKnoJOgzqELl3I+7kvxxkK33tlNH/T5oM+ewk4rFQXIM RdhYmxIcu69w1CsdB3miiwl4OwUI35ruNVSOgyprs7hBXTmgTXDK+KkZBzpx F8gMne9C8k0y60jDOHgeHsrfVysDbMOZYhes4qDvE4/LRXZpKHQVoKh2ioMn Zb8/9ZdJAS9z51c5nziobPXofq4lCeKPNt0dcXFAbnPK+/4/cWg9CpI7mR4H uGd1ySOboqCQzcycmR8Hd7Payo8oROALlC/xl8dBWvdK12+l26A9J1XbURMH LDPkj62rhGA2cCRUtzkOJLxPet8WuQnmXNaamx/iYH/nKUvihAC4mif9ZJ6K AwENuR935vngL9mVjvLvcXDlU+7D5UZeCHnRmHRnKw7eVPPonG+7ClRKaiaj B3Ggrkmp50i4DD2uP1hqiHCYXw/51inBA7FdjQH+pDgwqjOblSrlBlXm8BUF ShxUKLa9UxDmgrG3597OMOJgjYdjsCWbHTIpli6+YMHB23eG81SuF8Hw0atw ZzYcKGcLUPF2sAFXmdcWyokDdeFJbZuOc7B0JKtNfhkHt0LstgZXzsILZbrm QV4cdLnitzJvsIBt9jhPtgAOzr3FuUgknYE9sPslKI4Dv5kWkYmXjFCPEzX4 AziI7GD0em9yCnznTnR1yeDgsSpKK3KDAe4I9vMlyOOAS+8aVTYNPZAEpSY/ VsFBwv0PThZEdNA9+OTvJXUcCDGfin5MRQPRXNfNtrVwYJVy772sMBUwdrbc CjXCgfY1mqmeJTIYY4rOemCGgzjX6ZpLlich01yThNUaBzicl4n2CVIwrLv4 9JsdDvYqp2TzqomBk3xtqNIZB763R6wtvE7Ad503Ep4eOCgmkH++rnkcXrzw K5DxxcEPfv7peGkiEFRidP4ahgO3J/gqi7y/6F7m9ER+NA5Yyj9ZaE8fofUb xdK28Tg4vfx83fj2b9QXdSoVScZBdFaMUknxASoVh5w6kYHVW7vzoeXNfZR4 9qTXxxysPtsS/cTDe2g3/8B8SgG2f3wuy2HUT/TBgFkVbwUO2r71nHEU+oEy cgqc/VWFA9LLrQQHzh101Ol3QEstDgq1DkVbObbR9PaOlagGHJCco2vRFNhC 9U/jVDVbcMBuThtnnUlAOcx0317sxIH5KzDc2FpHv9dwsa/14EBXXMsiQH8N far9dstvCAdhDNv0pb7LaCxvtkjVVxxMnqDUH2ZYQiuOBfkvTuPgXRL9q5LG b+inIfNupkUcTHh4xhX4LKJbxUp08is4oM78x6+vuoDS+whoexFwkLTLax4u PI8KqjLllv/AAWvpy5x1vjnU+WDmBsNfHIS7Ep1ZSZtG8R/b3WROxAO+aXuV c2ESrXlW0uRKFg+MLYGLr+9OoCMusSdLqOPB7Fv62eXWr+gveaf7Ewzx0Ebv oHddcwxlZtNOoWaOB1km72NU/0ZQkR2JGTgfD6J0vAvcDcOoZzqpXQFPPNyb FvQ8aTuIZtiu1YzwxkOLkG1CoOEA2nDn818ywXjIpI8tyXzyBf27mhb7VCIe 8lek3zdxfkIvNPmO5Ehh68m9dk70/IhKJhqzDdyNB/F84sr8lV40QPx6xW3V eEh+NixRRvEBzaNl2LPQjIel33sqB2+70NaFPSTjUTzwu54XuOLdiRJHN3/8 ZxoPQr4sM++F2lFuw8LTgtbx4KlZhDJfaUPvCkXqmdjHQ6A0M68obysaPqm+ 0e0ZD96RX/dNHjWjJS9Fbv32i4eeHO7pGsomtCf4vM/1kHiY89Yqn3JrRKmu L1ElxMXD+/hHGdG4evQ6UZ9Ge1I8RHfSi+aJvUVVhl9m7qXFw6c0rhMUv2rR OB9P3kcF8eCixWpXlfcGfalq4BxTEg8xLN9qKXHV6GdumYaminhoHDdz/B71 GmXop1biehsPtUZ0squlr9CbeTuJmu+x/V9fqU3uf4lquI5OhLfFg2NndVji QSWazPbMeuNjPJQqk6/47ZShtTshry8MxsOPO6Gyr6JL0bFOq9+qY/GAJLvl Sou+QFnshKJq5rH1VsxupXQUoWLSLIPLS/Fwe70nMzD/Oap75u9Z1o14ECM3 L2bHFaKZTV0v/H7Fw4QF2+ajhHy0MbFs59VRPLSe+8sW/DwPnTaPF1skSgB/ tXwD985n6EW6Rz1yVAmgzbI7osSTi0otAoMXfQLMPVCep+7PRp/UcemWMyWA fURvmZ9hFppvSFihZ0+AMM6kJLv6dFTihIvHGncCvMs5cyspKQ0dKfxN1nE1 Acxafj684J2Kkq2RXXYXSoDTcIV83D4ZzYuJq1UVTQD98J/jI954VJyf6d41 NAHkaTM6BxOTUFsXTrPpewmwtFPhXT+bgJIxv/hZq4St94nuZunpBPRZPX9I vGoCqNTzXylRj0eH/iEFMo8SIPrijRuiA3GobV77TTbDBHBkGwuM9YtFT8oq tv0ySYCOc8TCA+IxqFik9vwL2wTAS30INJ6ORId4ZxyCnRIg5kfYDbO2CPTp J1MiffcEeGz+Rb+5OhzNZXS6SB+YAJ/y8jbE6kNRsdqDytXQBKi59zFK6WMI OqjjD+1RCfC7Xs4tZTUYJc2J0XfDJ4Dy+uTKsTtBaK4UI+FBegKozvxxkfIK REUX032u5iSAbduPsr8NAajNleLMqeIE8AvakbLW9kcHXreOSzdg59FICB/p 8UJtNOWtzrckgNNcrlHKK0+U5ODTwV5HApBTuX4+V+CBiqBTzC8+JYDkU4dm sxdu6MCscXHQUAKUxjWz3Wx0Ra2DVoX1viaAR/tJvsGvLmh29y9NuoUEMGm7 Rz7B54yKWPt+X1lKAJfk+hQXMyf0CzWJa9t6AgQNXB+Te+6IEqsz4F33EqAk 4/IaP+KAWk3xDk6SJ4K511lLet+nKLH/6yc1NIkQLu96PlnfBs3iENuJO5UI nmEfBMsVrNHP5vfopc8ngkIHd1qutCVqRdGfe44jEd6FtH+Nv2+BnijX4N+7 lAiszz41oKbm6O0do/sl/IlQORKL5y0zRT8nLU8H3koE+26FgJJJE9RS2M72 sVgivGRdz9Q5bYJmenvH0Mokgvanv5oHWU9QopMpvS5aiTA2r/8v6oQhus8r Il77OBF6e6gPyFr0UYLa1xf7RomQcpDs9SJcD53MZo30skkE2vDZ6jT0ETrQ 3nDQ4JAI0f6vQzqv6aIfVvUs/7pi56uuUjHi0kFrbufKBQQkAo1sQMy3W1po 2WOputbQRNiieUM5q6yJ5gfO8xBHJ8J5D4bPlnYPUVw/18mw5ET4TT7MEfZR HbUyK+mILk0ELnzxsO3aA9QwWuFW/8tEuEykOi4j+wDVqloroK1JhMBv118U Kd5HZf5eD05oToQYxn2tnz+UUHGuTz8GOxKhCEe+zzCuiAoq2Buf7k2EQ/MO Nd9eBfRCctWd1OFE+Pr9E41uvxzK1KBe9XU8Eb5L2Kl8n76HUs3vsrPOJsKO L+/Pvf276OF1YaLs1US4wXX1BoOcLDrU8a4p/18ilH2yz2ORu4P2rD2+8Y04 CRi/8rDg0qXQFvq/2ZcokkDQcPlM/w9JtEJP0reEMQkcXscco3YCtDBobmOV JQmekvHF7imgaGZJoB7vhSSgz4ny1eZD0Iif7RKVV5JgXLg8tvS0OOrPala2 xZcEb9QP8xuYxVBXqZPnBIWSYFUBfyKEWxQ1iZH/XY0mwU6Y7q8KXWEU5e5/ W6+eBBy4xlrLK0KokKLdlSPtJNiP2ms4a38TveZAl4boJ0FPUnRdX6Mgytyo 5t5skQRs2xzCLE8FUNqFH0tEtkngrVVxjK+fHyUlx2tJOyWBooeViMgtfvSH xujtTp8kYBJpova5zIeuero/PxmUBEvEXIqJZ66js7ksTPLhSXDyioTZZzpe tH/90c/ehCRArT2deC9eRYuDZ19/KUqCM6fyTZSLL6E0hntZh2VJQFaOz/s1 x406i1OFc1YlgZRoI107BzcquSP82KUhCSI5LMOr6jjR5x+V72a3JIH713Fv NWpOlKrEmL+rMwmyp2/l0FlwoGMGccQsX5KgRGB1AMukKCpeSJAaSQLffb0n zekX0QKmd2NWE0lwY7c9r5XyImr/8XtZw7ckEBujTws9OI+Si6MPDQ+T4EpT 5G3Ta2dReyYNiPiXBMJLY2oDSizoyLbllSpiPKg9uhVF4sqM5hXj/5ygxYNB r0d8xjQTShZcusTLiAeZGJMgl/NMqK1By5eHLHiouX2vlsj4NCrGtFFYxIkH 3c5oQzEiRjR3+zju82U8uBcSb9rrnEJJPzJ7HlzHw62Y49y2tQzoQJCMiqII HrQyKkNXguhRq+2MPYISHmz/OD6jfE2Dfu57NXtGDQ8s1nyc1G+o0dvFXT2S Wnh4c8OEp6KJCj1u8CM7wQgPAWrDn5I3KFALMfKId2Z4UBqpRhXoKND+0xec Fq3x8OmGQI+TGDma0adw77YrHtxODbidLziJHi82FDDwwoNQrOPe+QVS1CLI lTXcHw+HV6aE8JdJUSGxvM2vkXjY2Z+SJ+okRvuKDlJ8cvCwzC3+6qfMcVQw iDbweQEeUiubkNZXRGiqPrfNpxKsHmxrk9acRKjJaVVJ9mo84D/QxZcyHkN7 tsyuKrzFQ8/hovQszz+Ev8+b0ek9HvZjGoin+P4iR4HFy+3d2OdDnY7IHh4h T/TfD2x8xIN9CatEmdNvpFt0qIFpEA+hRkcpxWmHSNLWP5zFFB4EblncqDzc R67ra4lS7eAhulzgyIViD6Eio7We3MMD3b+94B6Ln8jqq87Mst94WBR85PG7 dxcpJrl9TJkkGZL551S1cn8goZUbAucpksFwWbJMmP4HYqpTaLxBg72eOvhG P3QH4Shn7IphToaeoLEfh97bCJFW377e+WSQfv7Gnu/vFjJ7LPgqH0cy7AOD 7qWgLSRL40dM/7VkWAgt+/X1xibCfPRFgxaSQcL3ZUbs4BryqzAidEY6GV6h o12nqdaQkftSdZVyyZDvXzjmrrCKJOa/ZH2glgz2FmNOrGPLCI1i3DzONBkm SGj2Lgp+R9Z37zIaWSVj8/3TtCfpG9Kb/VdWwC4ZurjaZkmOFpHwnaclX9yT wUkkV6dgdAE5ka5kzxCdDPeN0NjZpjlkXpo4bx6XDLPa30fspOeQ5o13g1X4 ZKj43q+Y0DOL+EpdE1bPSYYm4trEO50zyP4y+d/EqmSIyX6ij7hMIqMJLTdM apPh7v3tz7OVE0iNhIeRUEMyrDWpxLNtjSNOuOX2oY5kEHz590qr/1eEINwV dfprMpC4PvdWnB5BPs75Nn6bSoZvTErsT6RGkLKo25tv5pPBbOiF0VzxMGI5 U6imuZ4MNSGRUUnBQ8hiaDBLyr9k2Hjhl2JrPYC08ksomhOngJPqpIE+4Qvy bPyHtzB5CthW+p/sdv6C6PMZz44ypMCXJiPiZ1Gfka/DUkXMl1KgRlfqTmLj R4TxBOPbB9dS4CDnGRfntz7kAf/3nnD+FHhdPyLDdaoP6Y6MJOyLpQCMPl59 GdCDENc9PiYgmQI2Yhf3vrZ8QCS/8TFYyqZg5+96XHXyA1IHg7e+3k+Bh6vE uLf5XciuTeE9+ocp4DJekZN40Inwp7vpyOumgH+e0FN7jU6kaJfV561JChye oYhJYu5AkktM2tM8UoDmWmBu6EgrMjBye+SLbwrQzUyesXjQitAQky+TB6dA QFTTW/7+FiRUv5zSMzYFsl8zGh8fbkZcTu2p6eanQHpHaiANy3vkpWS3SUJx CvSxfs+klm1E1p+mu/aUY+eHmvbLbg2ISTeaLlaXAm9ZsvJ+rdcjGj5hc2c/ poBw7vEG7rN1CO6Fzg+1gRTgMvBnu+pYi/SNXiOJGk2BLNvG13v9NYiM4OfL v+dS4L2F6aZe8hvk5hKz/cReCpwzIB7J036N2DKuBZw6SgG9BdlmwcEq5IVU Y6IiUSpM39DTClGtQjgyjWrfUaaCozap2gmdVwiD6ou/GRdTgb2Ktv/fxUpE xdebbog7FRZ2BxS9lCqQyFIVDqprqRDNWi246FOOEJH+kPW+lQry7xvsBrdL ka168ZjHCqlwOFbEksJSgvAuU+ck3U8FdaW7H3ftihGL07Mv+zRSocaV7e/x 3iJk1i54SMIgFXrO5zvnxT5HPnF9ZD3vnArW2w0GT+UKkOCLUi5H7qlAqZzm kfkhHxE596Z/wicV9krdm0+q5CO5p7IC0sNSIaO9+RcY5iGOx58unclIBaov fQUbRbnIpb+zkr9yUmHdv+xCo2QuMnGgkT5SkArLv+2yNOpyEJltCWV8RSr8 5TKO5rmVjTDNUr1maE2FzMBljmLzDKRnwp9qpzMVEj6SS1o1pSN+o7umX3pT 4arUDWZj1nRkuX+SGTecCqKCzCdxM6lIfWOZL/UKdn7qFc85fDJi+/bi2PpG KrDSe/m5USUjnG+SBPp2UqE6ir3dLRSPRJd5L0YepcLruL70R8FJiH6GkgIZ XRoYWq10GhcmIAwpzflLjGkwFvJvaksoAelKEPrTyZIGNa/u8Ml0xSP8kede hnCmAd4y7uzWDxxy3GP99AnhNLjFc3WDfDQWqXE2tJsXT4OVtlum5WyxiLX9 UHeLZBp45kwvf7GKQYbMG7z8FdKAX1uX6zJdNFKoGT33Ry8N5AnSI0dREYiu 2jHxqSdpcGZSuC1tNxyhUXFOajBPAz+bDJ4pw3DEVfbxPS+HNCAk7uqelAlD 5IR4y/eD0yD02ZluQ8EQ5OhGLulYRBrkUF9UGnkTjLy6xmhYG5sGYdeFN+Qk gpGznEcMrqnY+9caKYdUg5B1+j73H6VpcOoM99mcrACErq1aqf5lGgi2cZ06 EglAhJyzLga8SYODOEX3VyP+iPeIbTdNUxrsna3j3WD2Rygz6JmvDqRBibh4 m5ytD8KndLi2NZIGtq8eyoZ2eSNqf+abaifSwDfPIS+byxtJN6g2l/2WBo+d xNeIVj2Rq1xatYb7aWB++qkGZ447ojIMUTx/0oBMWJy2ndEdcQy9bEAgSoc1 2nbe2Bg3pH75gNSbMh1m7/M9fBzuiiiUZ2qmsKVDXABl+XiuM2KrH3JVnzMd kpMva49fd0YSaG3/cl1Oh3WS/mCHRidk3AGeVwmkw0Zj1l/pRUfE8vb8z48y 6WDQzbdapuKARC/1fEiSTwdVMZ3GbYI98jL1ddYjlXQoFL36zijeHtk/DJZd 0UoH5aty/ZRv7ZDwJh48sXU66F40F+c5/RQps6ez7LVLB0bJJak4FxvkM/uB RIJzOsw1J3EHf7VGmIN7Fi/4psMb0S31yVIrpFjuqZB4fDqQvzgbueBmgfQd PCQ7npwO+REW3IU75sjWC3SyOz0dPn7lczKyN0dEqOmCNQvSoW1V1sjO2Qzp +lI16FCbDu/8BUUvZ5kgq4EZRSIN6fCHtnW+/boJQiMU7PWvOR1mnMwKvzYb I5rJDzljetIh/heFGifhCfJdd9+xeCoduqrjGbqNjRDzuN+XRufTISn55Wb1 X0Nkue3vOMlyOox+v6xAmmmIrPKSSBvvpMOpN/h0iXcGCOEv/Sm2kxlwgT4n gHPvMWJ383SXElUGeGfq3b92/zGyZc7s5UWfAVTLtutcZY+Qnc9sC2OsGWCX ddXXzUEX+ZV37XUifwbIGd95ys2jjbiP8pm33sqAVZZrRpRZWsghpSDrtlgG yLifzb7EpIUcOYsEqchmAGm9Mulbek3k2D1ZdXLdDMiovCBynVcDCfCSOyli kAEis+Tr79+qI8dfKr4zM8mAJCUZ8315dYSYRY2z3TYDrI9/fXTGUQ0hW9P/ 4RuUAUpeFjlPZh4gEReeFJWHZ8BESN28rf8DhELD9NFkTAbk5jTlFXM+QKga rdtEUzNg0JojYnpWBaGLc0/cLcuAMMm1mzPSSkh8m9c9zqoMmKSyek72XBFh 2Pf9rVqLPe+njsAApSLCaBRiXNmSAfKDMTc/zskjLDcTblqNZIBb97co9M09 JN0cv5Q6kQEfW5MQgsA95FxmakbXbAa8yjr7M/jVXYSNJOcE91oGuO/L0z56 K4twjJYOzvzLAOVvpB4NK9JIPmVlGA1JJrDk73Wi3tIIl2SVOEKRCTSoRp04 vTRyqaQuP50xEzbSDL4/uHMHuerV4fTwSiZ4v6at9WmSRLh8reyu8WUCz5gi 6yUrSYQtgNaa6GYmuJ25tJTGJInQh+k8KZfIhDZBdyalFRTZT9h4QPIgE/Jb bf41hUsgO/gEpQmNTFhBlV2N98WRtVRhuVc6mUDykLf9mLU4Mp0dAHrGmVCQ LHWeoC2GdLw4zffGNRPcOWztmx+KIO/L669EeWVCcVGTtOeEMFL30oDbyD8T eAcqdNqNhZGympJz1JGZcCXb4Gu8120koRWhNM3KhM61MLqlTiHEcNx0mbE9 E0y2NL2EWgUQ3SmKxdXuTFiwZ3otZCWAqM9WzjR/zATnq2/P/DslgNz9fjBi M5oJbLoRwfU2/Mj1nZiO9tVMAI+akjVjPuTST8GW9E3sPIeaOIP+68jF/dEG +91MmC4PWuwUv44w/mWvPvc3EyhnQdzhAi9ySF6T50yfBRqzl1IoyK4iu1SP shWYsqDbYi2vNfwKQqA9ln6RNQtOtaa4sVFdQeZOK8T3cWXB1MhMH9nZy0g3 +7Qfl0gWbGTOqVxWu4TgRUn1hvSzwDUFnWu/zInU0K6riZlkgeDdy6/ft3Ag I9++yOVaZgGI6FnvPOZAmBOyhGycs4C38DBwJ40dyVwVoiKOzAK9s2UNC7wX kenkY/ufkrLg0EMCf5X4AnJBum8hIycLyh/2XGRuPI/kZRi/u/kmC/JruZJT tFmRxXs3iv41ZcEbmZ7wZdGzCPfuYUJvD/Z+cldlfR4WpFgpwcp4NgsYpvsG 17jOIBV/mlkSKbNBr2jXKzXzFLJVEk1iwJQNc8atT5a/MCACmtrbV9mzgXt+ ubyUlgGprtjsbr2dDQUfWt48yadD9nTfVcdKZUPtczYOzm1aRPhkWK6uUjbE 1RpRfCmhQeoN2Nx3jLJB+G6KfKA0FXJEuWr83iYbdr5TjVlzUiJI3Zv7kW7Z MK2mzyFPS4E00ynzcMRkg8qtfaUGMjLkeCPzKUJKNihRuDE+On0SkbZc/Ps2 Lxvc3DeI6XlJkeDTL1dDyrPh+3mV8+pKJEhni9eIal02uLNtu/a7ECP/ARaf Du8= "]]}, Annotation[#, "Charting`Private`Tag$8997745#2"]& ], TagBox[ {RGBColor[0.560181, 0.691569, 0.194885], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUmnc8Vl8YwJXIKElIkohESiVlRA8qIrKiyEhJ9t57vsZrvPZeZZRKlJTV McvMCElCWYX3vUKUVL/z+6vP93PvPfee5zznPN/nleBNR93bm+no6FgY6Oj+ //d1o++QzstcxHhxh9qYFAvkXuL5FvAsFx3+008Vv8UCHoOVvx+W5SLHO3wP BxJYQOQbVYCxKBf1cfVGyi2yQAT7DduahFx05/DEnH0FK1w0O08nZJuL0vbR Wx1W2Q4C3yY4tC1zkbIdb2i0z3b46eJ/0N88Fx1N+r2h+2Q73CdVqb+/mosS lD8WCfCyAXOZaAr5fC76IfPIvW2FDTo2th1e2ZeLjNNPWsSbscNd0gN5wT25 KOBMUYWcPzv4sKtoXebMRdvmKVOCWexwWDjQ7T5LLiqrLOQofs8O5EvfXxmv 5SCP1xb+yXo7QSNzUK+1NwddtBEyCb/KAT3Suf6poTlo7lp83EQSJ6ifFSi/ HpCDdkTSPpjXc0LL+btfBLxzUPDsIR/FWU6o0SlWfeiQgxRMrl7fI88FxbZl OxsMcxC5NDFPb44LAvJeFX07loPQjZfFTYa74VeR4nDZ4Rz0UaYrnxy1G9we NbG4HcxB/T9rHjRW7wab6teOf3lzUJqNqIz3Xh4wePdWdhdjDpLMjRM4NcUD ElvHu+VHs9G7Be4Tn8m88GC7Od3m99nobNz2r5ubeUGYc1LyTV824gt3MS5c 5wVewdk0nTfZqDe2OtfWdi8wniHMLZ9mo1WxCDiuxwdjDv9+xEdmo0ybE+wt 8vwQN7Sff1IqG5149vXlWSVBoLDRMW86no2qme2dq28JQpLKxDK/eDaSOfCS K5gkCOlV+e1GgtlIoC1s73qXIBSkCrr3b89GrxwOWtw3OQCVBkJdjTNZyK/Y lLckTgiq4uhfjH/OQqytOyUvVwlB9evJgj+jWUjApZJTa0wIXp0u9JR9l4WM y82bzI8Jwxvug0IVKAvxfF1bnxwUhpEhEZ/89CwkvuwuIHFKBEbZtt5+lZSF GnwO/pm4KQLjKrNao3FZiD9uZX6DIgJTVSUHecKzUNy0wwk3mghQU0X74p2z 0P1pb5OAskNAd/WwaKB6FtpDDJj9PicGIu+PDplsZKKNhFN1u7uPQLVhhkry Wia6bruh94fpKGiMbnnRsZSJvBfLpR0uHAWXzx/TpL9lIpF3nqFr6Ci8mo8y 3DmUiSr2F7n11kqAPt3MaMuTTGQ98378x53j8DVER/N3aSb6IjTfkhV9HHwY 6utPFGci0tIQKenxcchnSc7Nzc5EnOp7/vquHIcFTuUbXlGZSOKrdNdF0gkI E8udFL+ViZzq6AczayRh9yPmKzdNM5F0N2t+2xdJKJVwb0k3zESCR+imDVhP Qu9JjSIG7Ux07/LEZLrJSdh7dt1yXD4Tebypo/QwSsFTXYO5RO5M1OkbX/HT 7hR89mX7/qs9A4X7/xFwpcgAt69ZcFtLBir+43ghrFMGNHzKd6ahDHRe4Gec 1FZZeOmlKyn1PAMxMX9j8gmSBYp7qqtDfgaa5n5x5q2PHJx15F/94pGB5gYY 9ppS5MHNwZFU4ZyBVGs3Vi4PyUOpfQN3kF0Gum71+e0/PgXgsrspve9mBlKk FVaUPlKABatir6uaGei2/J5TdwbPQuZNid+dQhnocOEVdr0SReg1DyRn8meg O4GLxZ96FYHRvHev9Z4MNPlnq9/ouiI4m7nIM+7IQI6iy7Hy2kpw0bjKX3E9 HfXcdNrzhE4ZVvXP0j3vTUcaJxyYn3ufgyP68ZTQznR03IxeTebhObh5ZUJA 93U6Ojp3bPDip3PQrRuiRNSmI1F551Gec+ehUOt1iFhJOrJJNb9QwnUBdNUu M+T6p6OJjb1rh4ZVYIfPH81Wr3QUbvrB5s4OVegqfZS64Iqv36Qsyquqgso2 VtEzNulo6/YQrYqXqnCm5436sEE6uhGX77t09yII6ytROI7j7zm8KBWWqg6f wxeHZcXTkffDMJGtw+qQW5UnaC6SjgZWpEKA9xLs4fn79AlfOppvFjz7If8S sH2sGdRgTkeUxsOfiCoNWLshtTfiSxrK0iu6U8ekBZUJk7fKPqWh4LWvPo8N tMClKfHR4HAaKjxZ+synSAsWhL4rCPekodyre+RGDmjDxMzjG421aciitajM u00bOuwOFf9OTkM1n/PS0g/rQkTOEO0AJQ01csrl7jfUhfNvw6XVyWnoatix xiORuvDq2FRbenAaylxY5p+Y1YVnS/nzpxxwRnV4Tn58rAfZXrwnnFTx872q 7xv19WHj4JOMY8ppKLnjO1UqUR+M353bTMinoTN/hAmrHn3gk7B/Zy+Zhgza 5b35NQwgexK52+5LQ/ocbIHbta5C9uXbNZbLqcjD4jvE+xvCxu9fB0RoqeiE 58entm8MwfhBHHn6ayqSXl29I8thBHxbXhpbjKUipgJbq6pSI8iuZvln3p6K /ItiSZmz1yFbuPycSV4qkh9f8zJKNoWNvvOP+DJTkcoax9pWwhSMAz9wjian Iqnl4v4pdTPgG9k8YxSdipooydL76W9Adrx+5DX3VJRYu//nz1bM6+tdepdS 0ROhKoNe25uwURJ/apdKKpo+4XWu8d5NMNYXzu1XTEXGxe+2uIzeBL5yTUed 06mINUQigV/7FmTfzt+pJZiKLpzYarqmaAHZvRcM1NdSUJKYGcXxkiXEtN0+ f2ApBVXulmGJjbcE/4ZwyfWFFMQ4qliVMmAJpuWtbKVfUtBidv1XD/M7IEC5 8Ib5bQpaOj6yOk6ygiKtCzLthSnoK8f+6jp6W0hVvS1SkJeCxle/fTO6Zgsk COf0zkxB0+f3zQuX2YLVsdZFUUoKqk0bZ9EysYPDOy48iPRNQWXbbjCGdthD 2dvzvBd1UxD/lyIXDxcnyH1twSSgmYI64t906JY4QfyrsNU11RR084e1LzHq BE5lLf0lCilIhPTglIe6M0jGnSdvFUtBQQmP9DiOuUCV5vmN1/+SEbu2VVuQ oBsUX7CYy11PRqdat1cv3XKDNIWwYY8fyUjv5GNxkxI38DraUikyn4y+Mnou iZ9wB7nt5+1JQ8lo/JR60yEdD0Bd58YuPE5GCRsBRMJrLzi92hjmcT8ZdcdE ei1yekPZfkXxknv4efKr3VYW3pDrIu/FlJmMfrntvFrJ6AMBPKc4OknJ6NAF U1clQ184ayGion0jGdWoeGz1lguAqtjChaDrycjm7vHP97MDQOLFgaQKg2TE apmTqUwXCPws+yc4NJMRueazSGdnIPx9sttnUDYZ3dBS8bWvCYL630xlRruS 0ab1iad60SEgdTDiCpktGYUVBbvLtIXAo8sMv2uZkxHPHqJj69ZQyC7YdHEf XTJaMNEccI8IBT/V9c/jC0no2F7tzZuSw2DFySuS/WsSmhHsDX74IQzsMlcl lCaT0H5SQ5+5QDgYU5d8735IQm99vDZtqQgH+aR5rtuvk1DBjb3Kd8dJUFln XZfSmIQYzy8ZSEhEwJGZ2Zuv65LQKhtf44J/BPDJTj059CwJEWwFmVyCkbAx Nqo2l5eEfI6SxMo9oqD28Ft/R+8ktPIhTEPMIgaGek+cl3FLQruvhZB29cXA okcKyybHJPRlychyGGJBpNk4LdEiCaWwZnhxC8VB4vX58udaScik9eqLKjoK PN6k5RmgnoQq1fJjeYECbSVPFVQvJKF/rK+eJAZQ4M+yd8ewXBLyjX11dZAu AaximKZ+H0xCuoWf5ZV2JUKopF1pi0ASCitZeT5plAi5wz1OsXuTkLzer9S2 e4nwTjjtD//OJGQZz8jsKpsEZ+sP7lbeSET/iq62bXFPBk6asnpkfyJyLLAf sjmZBseSi9l1uhOR0eFzFwIS00BdjuX9nrZEdF9K8eWl5TQIJPXdelifiGz3 VeXK1KTDHP8N/7f3E9HDMJcb5qaZwNDafC7tXiIKZzyfrN6VCQK2h1hu5Cai XNlsrjPyWaD/gpb6PSkRHTVUGTA+kA0NWv7lnIGJKHn4WuYoUy58/DHh8ck7 EY0ZzP2VjsyF1azzCsVuiejaqdKeVeY8EP/K2iFtk4jSW79MW7HkQ2pQ5qSR fiIa5PgcWS1cAPYVL7gLxBMRn6+TVUzOPWCP8k5pEklE3QZ3Ksep9+DpjTOc U4KJyNTKk6UYCmF1B9p5iCcR0TVSLR/MFkKAw+ttj7ckIoMjQRU31YtBQCWS /PZfAop7c5j7YEkxNO1TZ1lcT0D3aQwfMxhKYGt399aT3xNQBKnNvv5NCVDE BzdXf0pAAzV0bvPmD0CSPi14ZDgBpaqWmZ7tfgADI9foNt4loIduJ63j5EqB J3r0z9mOBLT4KpZFa+9DKPg6+bOlKgFpfOYfDVh9BE+Llmi98Xj8abqosbhy uOJfab8UjbmC3Mn9vhxWr3gs7CIloHlTZf/HAhVwZsv6NwO/BLQvf/Yex8sK aLm5aXrUKgHdc15VJv98CpZyzbf+3kpA0fudLodrPAMmjvAv+80S0I7C+RDe u89Ao5Fp4qY+fr+x5wNp3UoY3M/+8atSAqpdSeqSePMcvNb6DFkUEtAeaeNv S6JVwNuTNCwuk4Bi8xV/psdUgWnA7iEHiQRk4+MeVWH4AmZG+ftWeBPQF8ep x0e2VcPPjKNv6FYoaHih93DRxzoQr/PplCMoiOOGtFGnST2Yjr3pcZujIIrn riPWX+qh+cDN4a8TFOT9PFb0zPIriHuY+q23m4L4ZAw4VTMboLF7ksrSTkGb du+f/zLdACvE8aXzLRREWMudWpBsBEOpzvWXNRT0yZcIMu9rBOH6f6wFJRSU erywPkmgGa6Oa7B/vEtBvYzOt656NUP0pkxOrlwK8lF6vRf1NQNxQWpfVDIF XTxO0UuLaoGat1YSzsEU1Fjj/ewU22vQmujTVrpOQWNrX3PynNshZPN+fV8D CgJ3OkOO2XaoFLYzfK5DQfvSCjjzTDuA15rxpthFCqp4tm9B6EonTH2Xc915 ioK4T2ZLFRl2w27OSM9LxykoSP7p2acT3aB+etA3XJyCXtZ+3s5h8xae+DiG /RKkoIOJbepToT3gQ1+Y8pmNgt4oxG9WmuuFxwe/Z+xloSCJvydtbKT7YEL1 bK4+AwUlmL/hHgzvg2ieCs2ktXhUU/vsl6dIPwgc5nW61RePCsI8NY95voNL mguV9OHx6OHl7nd5V4dgNVrnT4lPPCKIUFWGpiG421Z1QcMpHp2KiCxcO/oe fp4LHkq+Ho/ad7Bf8WMZhkI57p8HJePx/Crlawc/wJ9DimcujschdcaqivXy T/Bkc3JjjGwc4hXp0XzJNwlGir+YTxyLQ1+ruozLb00CY4Cp7qBwHNK7z2PZ XDoJxr9EJ/exxyGZF18L2WWngGmxfsuTmViUqeNwmkd/Gsw/zar2JcXi88Vm Ny1oFrbt1aS4R8WiS9tSVsxbZuHltafDewJjUVWCnKL81q/ANuBnfdMmFpnf lYxZi/4KNR07ycuKsej4IbGZ61HfYNfLM2+5aDHIuVPPyNhwHrqumUTYTsWg fo5LFnTkeSD9ClBsHIlBLwSq5/Nr52Fdrump3ZsY9L29jqt1zwJ8qb+Y1pwf g3x9Fz8dbV+AbFMb7T1pMWj59TEj1aUFMPhHZnaMjUGTKqvyyrxU6FDs8eX1 iUEqpXWvBy2p8LRZ/4azXgzaNrxse32JCnYWnnveqMWgkBopwoKDBiIMGf18 ijGIw07EUOMEDTJVRs+3HYlBFjwOBdW2NLgy++fPPqEY1DCkV6IcQQO2yP0v XPfEoPtc2Z+eFNAguP2m2H7GGNTFQWes+I4GcjZhX9w2yKh+ZucO6zkarLAU Z3UskVFHz7mmIDoCrDS+bfcYJyNH2csPosUIOEBledM5SEa82cOHwuQJGI09 EiTYRUaJ4qKnfC8ToN3juNT1kowYy4NKXRwJYHFKeHjgCRmlcr/v9w0goIX9 mYVXERnNMn2jT44hIKBiYN/bLDLiD+f5iTIIkNFdHRJKJKN4b6bILcUELC3t pnhHktH3wMgSywoCHiXJqvUEkFGus8nN+VoCLKWubz7oTkYlz+0/pLUSsH/Q r9bHlozkyjPA+S0Bw+65br3mZKRziPO93xABidwNR0WukdF+3SQa+kSAxovP M76XyYgUFj8GUwQwXqPP7ztPRhq2w4yb5who+ClseOgMGXHb7+liJQjwyVDh 8D9BRg8/6qfcXCZASs6qs/8QGV1znG1nXSOANhIVJspPRmsxx3q2rRNw3/eh QgAnGdVUlTHabhBwk6979R0LGenr0zrF/xLAV097IraJjHI8Rl2u/CNgyITd OnAtGn2O3a4yh5ny98SBQWo0mlbjCF/CrJ6n9/HwVDSaeLdx0wXzFkX35KCR aFTVvp/BEY/3aiJVc6g3GkVKJQRT8fu8gl8yHnkTjXzIe8eW8PdIHhhBwfXR SJFdaEfYTwIWmn57vX8WjT5uKVwt+kFA8a19kkdLo1GQ5PlbJksE3NgC8yH5 0eirMWnHExoBvEU3CodTo1GsAXdBHo5P7Mw97rDQaJR6LDzX8TMBMUGUHSze 0WhIdb5l5iNmXn8mikM00q6Z3rkJxz/mssF6lmE0YruBTKXaMX9VXhbUikbZ MnSPrjYRQA45tlByPhr93cVUI4nXN7qKaezZsWh0uln+vNAjzNo/hmQPRiOu Ss/NyoUERM197kG80UihuYhBPJuASP7axk4GHC9DI8KOTACJZF80+TEK+XQ/ KROwwixglGvdF4WMFVvHN5sREF6jkka8jkJpajsl3+oTEEbbH/W7IgqJK7bp Hj1HQKhBv92uyCg0FrDy6uY+AoJEpKXOSUUh/Zqrjr/6aBDUIHS0XSwKFaDH wXVtNAg0YhfR2h+FTg9rNVEQDQLivu2+zhKFUtqjo10f08B/Neu3y0Qkyk/6 wKAZTQM/SuTKz8FIlFppu9gSjPmwOzWgMxJtVKbGG3pjNr08Hl0ViaQ/rJl9 sqKBz2u65rsxkWhXqyGPrRrmG9Ra0ZBItJDiS51SooH3+ofKMs9I9EhPaSxE jgZeEs+Ka25GIjZZutajR2jgkXo7ul8mEgkzc/7S2on5uG7oNYlIlGird/U3 Cw3cO876jQlFIp7J1Z09W2jg9ne3wxxbJJpklv69+JMKrpYdOpunIxDvy9+X RCapkJzSrV89EoHu7PaoPDlGhcqWXkOn3gjkDn0D1h+osHrgvflYbQQ6yvo1 U7uXCty6I7dTKiLQ7D/JG5u6qCAd/MlaoyQCjUV84fv4hgpe45PONYkRSN15 iz9zAxUy2GbdnSMjUD2ZtMu0jgo1CnPeogERqPndRsTHl1T4nbUYnGodgQJ/ HqnVfkoFvs7lcE2zCBQ+81bl4hMqyK+vRm3Rj0BZx6PUrR5RIeDanwQXxQh0 RmariGAJFXIj6FLFTkeguPH1B9WFVEBV9JkT4hHInO3JX++7VJiYZsxNE8Tz M5H5bp5PBToulruXd0eg/jC1S865VBA8v72YYXsEcg648q4kmwrKruyldZsj kOTbKg2GLCrcvLurzPUnCTl7dXpGZVAhtI/76WEaCS1XbuOQSqdCIR1v1edJ EpJUOTK0JY0KLcf21aR/IKEdQdJ+v1OoMG0q8Eqrh4TYdpZV78bMGCfUxNhK Qv3ZCUqGyVQQqRd5XV9DQqL+MS0oiQqqC2IdbuUkpH+M7rs6Zqu9R9+KF5OQ 4WsB1/VEKkSqH+//kkVCiWyMP7oxP/A+OZSRQEJGTIi/FXPH/dMj2hEkZNDj nDqOee697NhWfxKytblFtw+Px7pV4csrFxJqWmT654f5yGnFGXcrEqr0FD75 D7PG7XNzR0zx+4nOM/fw99knq9Am9UjoWgWpygp/f1yz2lKmGglx8WqAVioV ypY0VnWAhC6V5zkZ4Pn3CGqvM50iIQmLgkl/HJ9Fbb2/6DAJudHvON6K48ce ZLDZU4CExkpuLYjj+J54YsgowU1CxxiGH1fg+OuOGbNMs5KQ3LQrkwFenyT5 Wxx6a+Eo6lvJu58FOD9tLblZqOHIuaTfcvUeFQYyrXkbv4QjRlPTYfZinJ+/ HA8cexuOfjdTKZmlVDgt6ioy0xyOHIzGlpgeU+HqVY/DOdXh6FP+HutEnF/p z/0kWYvCEcVcF61UUqF6KvB0U2Y46tT48qzrBRVGdoXKeVPCEdHya7q+hgp7 XaKUZ33D0ePLScJzOL9zJVJ1m3XDkRbHlmHjt1R426D/RlwtHH1PFuN61keF P7pc8smAv38wZhPfIBWMPZMP3j4Sjlb+1l8VHqUCb0PiT0bGcFT1XvUX/TwV UnTic9Wrw9Dtmfcuxaw0aJm8vOvZkzC0zGWr9XMHru/ubJF7i8PQyZGRcANO GuhmxjovJIYhEYFcq9P7aMA+ST4fZxeGWEf1Jr2O0SDGLXKub38Y0rjKtLlc nwZ1jBfN5LjD0N9fTESaEQ3m07cO3N0WhgwLamfCzWigXk+qd/0VilzJaTYu 1jRgYgyncL0LRWJ/FbeG+tMgNC34tCEpFLVsW9suUYzPrxqfkImFEDSYGHFM aI2GfZtB2vtLCJLx0nwXtEEDi774+Z3DIeh56cNjw5sIuPy18Mq55hB00Zcj 2GUbAULcPSLFGSHok7rokLogAV3OQp22KiGIx05NUVaNAKU/jwO3yOP7G1Uk GbGfVEXKSOWcCEGSBmHSb3QJyM/TzHnLF4K2JpmrCBsT4N7t6XhiORixDvga KTsQwC/WtWstLxj9+8K/3B9PQFKlQVt8SjAiB21RakgigEnxs58oORi5rLTH 5qRhXzFYnTb0CEb3NG5eP5RHwJswgZd1GsGoPmh7mctjAuTZH9rpKwejidKd b0fKCXiadUqQJh2MYg6eij5RSUD2U/Xo/ULBSC6jRLW0hgCnCTfjkF9BaHqp S6f1NQHTtv/Y9xJB6MbGq4ZcXD+N1qJan00FoaGqc6O3uwg4z5YnMd0ThJhY DZrr+giozhCb9G8NQkHOEVYaAwRIHKxM464NQpH3wuzbcT3eI99Od7E4CE1F JJmQcb2Oe6P3fCIrCF1wNjrei/1oi96YtXdCELroaiS5eQL7jfVyf6lfELJ9 FlB8FPtSU9q+ou16QciLdmiiYJ4AFZJFx1W1ILT452XhSSoBHW4PiQIIQmXh vmuV2B/6dWTlTh8JQkurLkak7wQYKAaZBR0IQisM7J5D2DdGJN6EdfAEoYBT L+W4Vwj4zKrfY8oQhJoChD5ZrOLxVqS/6awFopR7PX2u2Lf6+1pPzkwGok31 ahku2GdGyvQCfHoDkWCRpZL5LwK+kD+3sdUHIk9mzg+A/WfOynHXvQeBaFlO x4ntN16vC39MpFMDEX23Ck835vUD5PudIYGo+ZTApC/2p010e5bNHANR/tED U7x/8Hp/KlZYuY7fn5N6rBQze41UZOTFQPS5un9EDPsXT1pTP9+pQGTz5MhG BmYBN+19FYKBSExvtXQds6jO2J0LbIHIUSr83yXsb8cl7J5+WA9AGX0Cu+Iw y7Cub9jPBiDlzs10jZgVv0aobh4IQJZXdT5PYb7YypWY2hCAapj2v/uFWfvu vdHDjwOQlIfF0j/M1wJPHEIZAchTcNV4DbOZMXLWIwWg55TYExOYLWU162Zd AtCkW0V8DWYH7o+MfmYB6MSfxjQSZo9lKx12jQDUaUizOY85oHc1q1AmAIm8 Oya+gr+f9DhsRuYgfp8S/E7BHBfNcaJ7ZwBiWs/++//8U+/k+5r/9UeiIsGG 5Tg+ueclXv+Y80dPBT4dF8NcLFjHHv3eH8Vf0i1NxvEt+6t2nb/FH+1SPrmw hONf//L2okqOP7of1Xg7Eq9XS8qy3McofzSzS4WK8Hp2uQSHO3r4I56wqdE5 vN6jR3J407X8UZbTo8y9OB+mmMVvH5H3RwF8N+oFcb4szLx80iDqj/TkT3zf i/12I3/g/LdN/igwnvEMFefbloCb8f40PzRNfvCgBefjtuuLH3Z+9EOxhXkj lEUC9nJtc5Sr9EMOfs9kmXD+ykWdyyBb+iGzUwf/en4lQNmyb3K/nh96f3Q0 dn0G+/k5M4lK8EP0ofsNXKfx/vzj0zzKg+/f80jn4hcCvJ2fUo92+qJ0peOa 4Xi/bVMaenGgyhc9H6jLTf+AzyP29eDdBb5IxPms6t33BLx+osS9ydMXHf++ mJXxjgAOWu/ZgQO+SPTBlyv7O3E/ZEPE+/j4IPK5e0boJQETt45IvhHzRm4Z 7CYcFAJcT2pv1HJ6I3M9QW+7WNzf0Lu9Lv/nhUJ+/RtoiSbg6N1ao8xBL5R6 iU3OORz3NxPqofbBXijA64gQ8iGA08R6YNcHT6S3kqlsfpsAVYNijxuRHuhu duxxSdz/8WmvGbxw9UDDdNtRuyzeT2oXpdnMPNDZ3TrDt6XxeaYwt1Z7ygMR ww/VHkni68IS3rsn3dHRTI7rHrifzF1+7vtWwR2Vlin18vMQ4EZlND4o5o5c yjQN2bkJUJu9Ku/H6Y62fq/NY+IkYGXk14bYvBvar5DxcTs7vt6kEBCe7oZM 374Rd2DC1ymtQfLLrujt81ubctZp0BHNbZ405oqYmYf+Mf6iQV7YHaW5dldE kWC47I3rjboX8+b0fFfkKXVF1HMFXzfTDF3WdEUXf78d/kDD/muYe0tdFt+v 2WgSScX36xHnCoRd0f57HQgWcD1VSdii9dsFFbQdMmj/hq9LDIaX3ndBp1kC VNWmaSAgKmK5KdkFfavvkVKcosEPQU+Va4EuyOZ+4W3FSRrkc+3Zymjggtjz K6qNP2P/3mEza6zkgvylbxJeE3g85to3z464oL6ykNjccfz8hnGkOb0LWn+U K8g4hue3+tjqJc0Z3Ta4c/DiJzze4t+LO0acUYfBucdJo3i8OS0xy1ZndODQ o1dfP+LxpvKZ68ud0Y5N4aaqmAXGvn/ble2MaN4iCU9G8PjvlTtsIpwRg4KB kSDm/M6paB5TZyQuUlgn+IEGSeQyjX51Z9R8Y+3+i2EakC55scVIO6Mmlec/ 9DF7syr3XhB2RtNba+5tvKeBXSdr4j92Z9Qg4v3sIWYz8qBe9R8nJCi4JnwL s+6lPC7XOSd0ZOvbtQOYL7Bavz/yHl+/KSs+P0QDmU7JjJlmJ9S4d/OrWszi 5A2j/HInFMIQV5aMmf/Saz6jHCckVzm57o55JytlbFe0E6pTSsk3w7yl0zC/ 28MJzaUPZetgXosWuhlxywlZ+XsuXMI8p04VUtJ2QvcvfyZfxjzK8mJ6Xd4J FZrwehpi7ukIKqkUc0Ltds0P7DA3RatbO3A7IVZ//v2RmJ+rc4qL0juh+Ygt /Q8xa3PVfWged0RdAyt17zGfTtEyka52RMYNjCOseH58XJMTpYmOSHF6+cBF zJtTPCz47RwR2s2bEIP5KyfL14QLjmhd23nfB8zdyTm2DPsd0WhzYsNRHN+n nCcIr58OKMq4wSUac3pyi8tCnwPibvogTmAO4Ly2avbQAd1SMJ+8jtfLInne +12YA1p38Kf0YlbnDPyjYuqAyvb+EdPE63s8mSO4RtoB9bdoFvdh3kiSjSyY s0eqIbf2L+H8+LKrm5WrxR5VW6htjcP51JZ0Iz4yxx7x/FC6fwLnW3JSRKqj tj2ydRufjcf56LNrL++kmD1y/TfjoI7z9UZSWY4BvT3qF2wL3IbzWTxpsFCh yg4dYRTcVoLznX2XtWhFvB06VKZrH/iFBquJGw+Fre1Q20S3kBneH02JQs9Y +ezQuQfB16TwfjJKdG78EGyLol6BihTeb4ocDBc0r9si7x1W1RfmaCCSmN7W IGWLirTcmU3nabCUgHpKZm2Q917Zv3fx/o1K2D7mrmmDKvd2XvdbosFLyoP1 nXus0e8rkfQmf2hQ+cPKX4WwQn/a6luX/9KgwkiUzrfVCklJHZNLoCOgVLiE YcrZCtkICvWM0xOQ87KQvarjDgoNnH3YxkJAyESeiJGfJdrmd1y2fA8BmsdT de+O30Iv1rtH/8nh+pCiPzj0/Bbq/FcVdVIB+9I65zXWmFtITvXtVhvA9b4l ycRN5hbqqXNcGDtHgOS1BCuVhJuoveR08JQGAbuDYgLmlM3RLh42BGYENOcx 6N/WMEFjGj25smH4/pA7E4Z/jZHXVXPH6yQC7lq0214uN0a/Z7M6fCMJCBaL DZHmNEbma0sPX8QQAM84y5lHjVAdaWiOJ4WA2tdCrGW215BjtrqEVREBhx+E p97ddw29tiwSuF1CQCZ5VjCt5yqKXng5YPoA1zPthzJBJ6+i35fMOS9iv5Ue kbTU/a2P8gacftOwzz6jKjWuRushxbkefc9mAg703tOYl9dDwknn50+2EpD4 lGF4nKaLgmb47s5jv3X2bKe16eqisPJnuzQ6CDi2SYcvi1cH9ceGur7txfVi 8mlJfJc28mfQCTTvJ4DtNefJsABtdIbKsEzD9XGEqyJppEUL/Vyvr/mJ/dZA rIEWcEUTSUaxebeOEnCKFspg9VIDja1RHMXGcH17psqnw6eBtu2/eihiHPuk fI+a0JQ66jkWG3sM1+vL2mOFb1wvova8CXHJWVwvue7Wlr9XRbHj/oI3cf3f NnK7P+OMKup2ElUlf8N+eov6z5ZeBXkprU+0/e/DnhtG7EnnkLxLahpBEHA6 TkyIZV0ZnfxcF/kF+4VIkcE8vbkyWppR9n6L/WPru3LfNQklxH77qEjCMgE/ v3069z1FEd0Zu9FxB/tw7yZunqFfgA4/SlSQxj6TYNIhU5+igLRq2ywasO+4 kIXby2/Jo7R7D+h9sA/pVgcYFp44g3QY1FSPYF/i5DrpQ+6WQe35vak+2KdW lGNZArOkUVVQNYUb+9ag02ymi/VpJFpmzfoQc2pXVq0hgxQSqAq/VY/9zGP9 xyXNd5Lo4OvDkmewv10V1R5VLDiB+lOZLSowyxiU2kk5Hket7k1L+7HvHWdi XtfykUBaRabDJMzfb9XzSnMfQRvjujtmMD9Fzmf4n4qhhv0BiQrYH932ihgz XD6EmPaKmMRiPuU54rfwTRhJ3PtjM4h5tT8u5134AaT7U/AlF/bTFxLnXtUI CqBxx71KlzEvchL153z3Ikf+T5sDMbt2Xf238xk3UptqWS/B/CO0QXFibica HM8SacdMeOhuMbnAgsJ5s8K+YF6ZFor4VUmH7LnNdq1gntAbPHQtceHVxOSv vj+Y+SbaM2xN3521tvyC/vftvxk9E+Y/184mV9J9+t/H101S7ZNjGOCi7j2x BcyrtJa5Nb4d8NwyrHgI80/069ljA06Q2jF4pfp/32ZKcBnn3wO1dMKnk/9/ v7boiZ2z+6Dzl7vGHczVXeOeBVcF4eueU5mS/z/vJH61plYIpP7IHljF8TjN 5Xn63X4R8Jl+M1uB2b26iWshVBQeGsXSbmOuNGH7seXrYZjLLJDjwLy8yWhg n8ZR4AuP6a3C8ZcsLnp2uvwYqHyRfq6H+Zonv6yUvCTcuZcb5PH/78dqLfcV HU7ChPoF1w28/ml7bXg086WgST6iywfzEHq+dnuLNCR4nei5gfPlR8L1Oy6n ZYDOqz2iDecXp8Wm9wFWsrC33rBVFLMek2ZVWtcZkLp2aqkf56fLyNLBwr/y MKz4ZZkPc+Kj9JTy42fB47hmnhnOZytRlxoLdUU4ciCArwfnf0lXfYZ/mTI8 tXowfRXvF2PBzwOBV87BvOilZj28n9g9trCHrJ8DhzwJO9X/f6/ff4lEUrkA kR4/b3HjflTDZdglfkwVmPnlp6/g/Uv35vfjhLCLcFBgjWMn3t/P9+7/lnRY DRw9LxS0Yn/nb71tlu6hDrzdlid5JnF+7V6+VMCmCTyP6xJu4/640I474l6l Jryo6xKexT5v2CjbVGR0GTRHnnSaj+D+2CZIprRYCxR/dVcpY5/vGCMlGu7X gX+X/7Y+x+dZzgnOwJsv9OAD09ZDXk14fT8WZd9iuQJJjbHyaQ14/5KkayxM rkA384k9Fa+wv380+mFJrw+2Eq75g///PhBWYGurZQBNaPrc9FPcj7yXuOY2 ew1iJzXuyt0lYMZP7QRptykQO9o3lQTg97P9bPttYQrKzaIM4X64/8ovvuH8 1BQKgpn4b2Lf92yhpxhrmsFJ1xV6Xg/cHzGaeWYo3QDxmKDOUHsCkjX3DDl6 mgP1T0rxNWOcX6OxSXyTt+DSvq7dfbi+FR+8bfae2QJu+hvltcsQkO4gL554 3ALGBl51t5wmwI9uvmlrgAXo+9LIzbgfOC98cWmJ5za8SHAPmj6Mzx/bzTrt ly2hzj7RrH8vAW2VH/jC3C0hTmGubRMvATV/yr+ezbaEs/yDPqdwv5AbbxZU +c0SvA0LeEtxf2D5rO4Jdnw4v5RG69iO99+6B5tHjRXkmEQa/MP1u8/0wEfH KStYDjxiZPqPBo+aukus2awhSnYTTwuu/7eihZVMblqDAn3IkULcP/Tu6Xc9 z2ID2QKdMdW4P3jo7694VsoGbptKyugsY//9LLpdxtQGbDYPWS1+p4HCg8Bi 8ac2MPtR9OUFggalMkc/cBjZguZSQ8xl7Cfh2cNF28JsYaYh64sw9pcbdGEu jGW2cKe7x5H+Kw12t42wrm+yg2eP7wR/wL6zJE4aXha3g+/CGkf7cP/wNv5E EVXfDsoSQsz6sB+FXY08+/mBHZjWMhfMY58yqz3J+vGdHVB6tAYYMMvtH38/ 8McO9KY6BkWxf32fOeXcpmMP6R+VSVHY17rUPys0+drDX1aS/hvsc/fLYljq iuzBoS/6JBtmU4/Je09+2UNjpMjVF9gHZUfinB4IOUBGhkz1HsycZ+UU7mk6 gP7fnzfDsT8uFkwz53g6wBizrfk69s1OhoSh1AIHYPq9s9ELc7G1/D1KpwNE XV6NpcMc0j3rGP3DAW5EZb9LwP5qciJJPmy/IyROMOccwSyTcpY5QM0R7K1q VnqxD+/69W3Q09URZufLpgIw04xT7jrnOMLh56YepzF3NCg62r5xBNayV0/X sH8XCS+cuf3dEcJ2yt9twqzYcinsyXYn8JOp10jDLOFRYPPogBPcDy2o/r9/ 4BNd034g7QRv778iTDAzj2hIF2s4Qd6s6Q8tzKvku/vumTvBQxPl3v/7hymF n/T5Hk7AKZ8X/n9/0U9ozmWTneBGxD5ec8wNBfd6M/KdIP7DSIIP5jK9X1Wp z52gze/GYg7mLAatnKQOJwjLeiLTiTnyRWEoZdwJlhIl7Tfj+XhYr1vHrjjB tcjO+HOYLfZqa0czO8NO6caCOMw63UWnI/idgXH17b1JzGcDf/OFnXQG4UHe VGUcvyMndOiDLzqDoL6U10PMvJPF3/xNnEG/ikeNH8efKWWjx8fFGQ5tHNua hXnyZ0m2W7YzDF/OUXqK1zMuqNduR4UzsMVCjxpebzmmX/Klrc5QmWDyZQ4z Zbf6p3GaM+xTOhWhhvNFPs/lsQ+9C8wnFbFtxfk1K5Llz8XjAk+frTC+xXz2 9MK+S0ouMCh15dj//e1cPSdtWt8F7nXGaF/H+ZpyQeFVkI0LRA2vtKjifmDh SpxpVZIL3PaRC5XH+Z/pejxPcMYFPv3okknG+0Xl9zXHunUX4NhNHmnA++l7 SDBc3eEKXgJiXqt4v11M7B+PkXEFO0URJz/s/6vlbgI/o11hbptOxXfs/3dl chYT81xhJtM12QLvb82G1oajlZgfsK6O/6BBYQ+3+a1PrvAs7toc8RP3q7SX BW+PuYGJg629Cz4//rp/drY+7wZuww78hzYR8OAPs/IWQzcYSXd+MLkZ15ft 17/IhrjBTk5/wpURn7fifw4UDbgBqyN7BA2fTyzWSoW+3u6w8zj7KSl+AqoW rd2449xhtvuarJEAAeZeiecr7rpDbVr6VdIBAl5GTE7NdLqD9EMl40URfN4V hx/U5feAr8eja7ceJ6Bxsr1YtNkDBnfG+gnh/uFykXfKjSEP8JHnvud4gYBR S7Gw9G8esD3twjak+r9fRpozsXtCHNfxvXdwf3F8UZXvq7EnuDZsKA/rE5C/ 0ZpQsuoJLkNP9/BbExDA1eQnctgbHnvpGfBTsP++d7Y1VfAGB8/U0ohE3B+k CxqlanvDpO5xUSIZz2dvsDSjpzeM+xrPvMgggCaouDTd7A2DOR064vcIMJF4 dafIxAdY8il6Ts8JmCPsDT45+UD35Be+4hfYPyr2XeAK84Ff3/Q531fj+iPl fyC81Afcfqy3i+F62CUn/8lizQdYmzqXYnD/IK9aoyuc4Atf9L7Bfuz/Z7kH Gn8X+YIPh9r07mEClKapx9/V+EKO7YDiVlyfVUIFd4RM+cKN9+FC7biea6PI znFpPyjdS0z2T+H6G3dX7oWGHzAUKpB8ZgjQN6l7EGfuB8s1L9a4sT8Y/SYi FMh+wHVyxOgo9n0L6avns8b84JHw+fp27COWjM7PXJb9IMjirvPOJQKsB6MP qDP5w665DBEN7PcOrq/ofp3wh4fz/M8zsM87KQ879qr4w46mPMFH2H9cdy6N lVz3h55DDyvLsR95PTlYbxDuD5q/nvnGY5/yCYAjEpn+4GR36KI19i9/TcMs hif+sPZRzE4K+1kQnyvLp2Z/0BX9/HwRc8h8jHflsD+k8emt5Gz8//fv4q9k qj/YrOivncH+FxnVcPXW5gBI+3Y3vgNz9LWR13K7A0B4aSxODftj7KGVUxxH AmDLfNKbl5gpq9uLvikGQKLape082E8TWw9xNuoHQGGgv9T//pqSrBSabhMA uW3lHMWY029dX3IMDABOVduAAcyZku7mqskB8O3qJa3//39Dzqb4Xv4HAfAr dN3kf7/O770Pq/UB4PfsYthvzHfzmsq6+wOgZMeBnBnMhQ6j+4pmA2DVKS+s AXOJwmqM30YApA8w8ERhLt3GvqG3MxDetg6fUsT86KOYrbhIIJSodddP4+8v Kz03svlMIPhYTFG8MVd4m6iNaAWCi6VZwm88/8qLni8rLALB8HnPXVvMVbsT DkV5B4LW8oHSdhy/lzOlqTfiAqHtSEYsF+ba5y0MMvcCQWV1UEoLx/tV2Jjb jpeBsLt0LNIDr0+D3s/Jma5AcFMQdiPj9Ws6wKH36nMgbE5L+BKL+7PW7+JN KauBIBPr2+iP13v6zTHtA+xBwDGdGXsQ54flk7qtcbxBYMbyx/gTzp+vqWro l3AQbJO9ZB6C82vu9i2JPtkgkChc+JSE/ddWc3Fa/nwQrOjOn6ejEbAg5Z9z /3IQGNYfeGW4gPsf+rRtQbeC4F6x4tA7nM83I+/oydkHQWGy5xwn9uGBbTKZ Kx5BIFrj5HUB+/BLrg+HrKODYN7/K5P7Z5xPh/ae060IAm5WLU+2D7h/eTgf ta02COwZObo68f67c7yu93VLEOhfYev0GsD+LWtiemY4CBT6BH4V9BDAfSnP W/hfEFy86VAr2Yrzr8exYYwpGMzOXP/rgH34t57i1gyOYJgzv++chXA/Zvw5 ebtIMIjddFZpxedBqYNQ+apGMCyNqAWbPcb7PbFkpi0zGARm1EntCQSUc3sd DS0MhgzdLQnccQQIZV10UygLhj7d5XH9aAKYCr9tetoYDD2SJ/49DMH9/3Px fVlfg+GJ9++AWhcc7w9P9OxPh4Bs88yTFG0C4gReNuzsDwH9d1Kj37bg79nh spH5MQTUO8fPMmG/PPFPXEZ4OgTs3u8UEvxNg4FPeU9O/wyBm2677p/Dfsib FZF7nT8UtI5YG1/B9bKI66pfkU0olIaZ9i1U0qCOZVValj4MhHrpm80taMC2 /sS1aVsYdPWhbHcz7HffrJ9c4g6DwbU8tngjGmxu+yRiKhYGcfckFAe0aaAa 3soVqhUGmy2/UJ4qYB/5l7zclRUG9VKbLLn20ECYuHzMoCgMSjb058o5aeA+ xmQ7XhYG0bmLp6+x04Cn3u/L98YwmA/Jqe7civ3Px6KP+2sYlP1jNdJZo8K3 lZNPbkiFQ2xwarjEByqszB14WH02HOdLc7rNIBXoPu8s4VALh89lL+Zr+6jA 003ktpiEQ4X9F5X8DioIN49l7rMKh6ft7GpSb6hwrLo71cMlHA54jAaMN1NB pehhnGhEOKw6cLj511NBNyszOjghHDSVw8Wca6hgmhBFGskKhzrexL/+L6jg 7n8nIKY8HEqTvy1MVVAhyNXAZ7omHGyUJdfgCRVirC94nG0NByTBSF/1iAqF +kIOix/CwaVp26+VEiqUX+KwUZsKhxO/mN++KqJCndImy7u0cBjcut2n6B4V 2qQXzX//DId+bVmnBwVUeHd03OQKPQmoOysOdOZRYUzoreHj7SSokaFsZs2l wtyeen1GHhIImE0EWmdTYXXHIx2zAyRQEo5gns2kwmbGLM2XR0ig8U1he1gG Fdg2otR2SpNAWS50TTGdCrxLXhdslEiwyBZ/kj+NCiJf7yg1XyLB0O4L4nyp VDgxZqDAZ0CC6Op9qmdSqCA/cEHW/QYJDv8RofkmU+Fih9SptzYkeCH2KXws iQpXGoROHHInwYFuWZdbmG9UcRwNCiRBQnsYFytmu0ebxD5EkYBL5UrvYCIV vO4uCksmk0A1xWtTC+aw9HEBci6+nj/OMIQ5Pu4t39R9EsztSJPZhp/PDKvn UXhGggCW9CVLzMU+jzhT60mQXz0QPYP5qVMWO/GGBAPOWwzI+PteWUZvu9hP Av6cwmJ9/P0dxt5MBaMkYHN713UBz29Q12rL+gwJkKsstzGe/8TFq3R630mw t225Ox3HZ+GsysbD3yTI8vGW38Dx+yl16ucWxgjgoPmXkLKosEVceMWEPQI8 y4d0ZHKosHf35oUdByPARKv1BgdeP5Ht32etjkVAwY30M2fw+krST0w2ykbA 8J9VpRi8/upE/UfXyxHw6NC19JJSKhhMP3rfdS0CFHdkKbs8poL5x6x3B29F QMBsXtftchyvN96d7z0jIPhwIVNbFY5XvdWb4yER8NJCfOU0zlfKs6vNUTER EKF7WrIH53NJ3qnaMwUR4ED3YNq3lQpDnt9L8zoigOmlftvrIZxfLMKnVQci YODI5VKJj1TozTFopH2KgD3xFN+acRyv5tr3Ct8joMuNOVbhG47nDtKW0d2R sDsz7BH1DxVq776MDxWMhIM2njbO9DR4eWqeV1w8ElSMLnXuZqbB0+vaJ3zO RsKDS5+MO/H+LyrhNeW5HQlPhP7GtRzFPiyn+Q05RAKdcaDpFSka5HYHut3x wuOVrE/Sn6FB+vJUdBUZj7dVaUvDRRrEwJMXV55Gwg+dnRezb9PA7f25nQn/ IqE9MMNSqZAGzjYe2TLMUYA2N73zeUQDhz/3D01wRAFjr+j+N/i8sxJiO3tM JAoujai4JbXSwNhx2KZbIwoyBdPGBmdpcG6rfQtzZhQkmPM13jtKgGJmnlbF vSg4NO7749pp7HtH+0euPY6CDoPac4xAwGk96e8lDVGw5fCndcDn9eG8Tfwq s1Gg+tF/YM6ZgEOSUg+oi1GQdNLVgs+HAOFWS6mU9ShoXmzwOYHPf/75TvWp 7dEw/eXKxXVcPzikUz1DpKJhST235PETAtp7/zT9OhsNK/RHs05jPw2yuc3m rBYN5HTPgQDso0SOVJGZaTRM2u7aJNdFQLF09uKQVTTUX3PnutdPgGkfvfxl 12hYQ1uevsA+2rXlXb98ZDS83nbu+ttJAkJz5fgrE6PhWyR/aCuux3Iyd63F c6KhzCbDRpdKwFIf8/O7JdFgsqis4/gd9xu2znS8T6MhaHP7NW7sBzcYPlxK qIsG7d1EuBL2CZ48xTSmN3h8u5TGOewfPTL3vwT2RcODM/8+sGKfIfXvkFj7 GA1G/gxhudh/FOw8vR1mooHfvto4+//fIxnGW6YXo4FN8evc3//9KU+F3eR3 NHySZy1AmG/Jll0fYCCDnaTw+Hv8PO87rpJL7GTIqXm9oojH77fzX2riJcNg UKHQCn5/FOO0gtxBMjiOVRfMYb9RzNeIqjhGhvsdvNn7VghYk60cEJUjg8P+ ZlkS9peyd3sF8s+TQUfKO3ffHK7H9qG2u7XIUMi9jTaK47Vv63xVnCEZmqmp WvWj2FfydTczWpDhd/2u7y+wb8TI1Wj6O5BB234T6+tOAs4NCGaseJFh5235 qYlGAtbto6ZsQ8kQYr8wuAmvZ8XW78cmY8lwzKNT68BDAqwKrvkapZOh85De 6JlcAgTONLzuu0sGfnPJgxdx//N+4BCH2mMysJbPrCkGYz9wiDdpeEGGpXg9 dQGcbypMa/elm8hA350AE2bYJ8+8BpH3ZGCansiZl8V+NniUnPMZX5+YNDpy kIADjilDnAtkSD0YZyezg4CEuxb29Jti4MdLtl3547ifle966cMaA4153oeX 8X6hGzq5ZYkrBja+uhbRPcT7i5k+a+JwDKz/KQ1ScKbBwXs2M1dPxUC0SN3R O7o0GJXvP9GDd61jyr8JkKTBJaeCtvorMfBy5yPHNSquTyzMnKfMYkDggwDx rp0KNfeczB5Zx8CM6rdmo0IqiL6H1cyAGEg72vDujj4Vxp1KlDiiYuDpaWsf QpwKqSw7YqOSYuAb/28d4U1UYDg7JuR1Pwbsdp7/kVOyAF8K/XT0+2NgT6Fc ouj0PER/PHRk72gMuOfWa09VzsNJjneMn6djwIiPLj0xdB7CAsXq7H7FQJC6 47ORffMgYjQkEiYQC5/vnuarVpkDmx3HN546xAK32PuAJsev8N17spidNQ7O GN1Uark+BZnlccFDnHHQKrP3TAHPFCjPyhpn88fB7LtW3YDBSUi8QtkpKhkH y5rvXhhrTYLUMQU/MIyDeb+317LOfwGvqVQdh5I4WBUca1g5MwECe5WPSFXE wUmrjNTTv8ahXYfKuF4TB7afAl47+Y4DLzpXF/42Dn5YZ+8fChmDuoxFkZwf ceCrwnrJJncU6LTUNzrPxUPWJqcuiR0fIHJxrPOGZjwsiT6ukCoahh2Jrlk/ DOJhn6uGerj8MPAPZsvtt4kH26EH9uyO7+HMdcLLhRIP67seXfk3OQhNG6EX t2bGgx5PqHNc2CCo5/LwZN+LB83Zt3SuIoNw7bPSi9aqeLh1uub7GYcB8LiT /IPnUzwMFfdtqd3+Dv4yibU+nokHg09aj6df9kN4aX2y8iL+PvEvFqa3+6HD Y3lP1SYKfD/9VEWyqQ+Gq/mqxzkpUPnxg5MwuRdWwXFN8gwFmv/OKsY+6YIa iqzZH6BAWMIpwbNHuyDgM/2bN+cp4HJDS/XY405gCE1PNb5MAZNzVyjPn3UA 5+vGUyRzClTleqqFjbTBMHdMjrYlBf4cWL5gY90G2XcMGPbaUiBo1uKq/vob EGKeH3jiRoEa5eEwvgNvQFKD0+1DBAUWDZN7syJbYTV77OO9GArsiRY3ei/S CjXU++ccEigwnDA8+vF1CyjFK+yiz8L3U7XUDmxrAe1+y6dHyijgxUylDpc2 gf216sXAAQrIhfU+bJJsgLgjuTJPP1Dg703fe+fbEJTRhQZNjVHA9UrUhRMS CBbva7CrfaNAfd3DRl36V+D2a/wYx18K6M4vWzP01UJKd4vnefoEfJ5pJvtd qoWqggfIgykBbmVz1Je01cCamqvWR44EWNm85efnjmrwyWR0LDyUAKUWRfy2 1BeQ5TBfNXQkAdbHvCkMfi+gTrn3L5NkAtSdEeSb2/YC/s5lxNnLJ4B/zDVW 81NVEHzmaNlpnQTYetVrGOVVQuSoHrXNJwE+fgvf97q3Ah6Uy5z6HZgAdhu7 37UHVEBH2D7/o+EJIPlDmtVRogK2HZ3dlhifAElvMwmfxHKI9/c5cr0wAXhc mS4YfSiDch0zt9gH+Cz7aGaer1kGvQfP16GyBLguPmFX3PIYON5u1xCuToC2 lJHjL2oeQSp/gS0Vn33bow5uMmsthRdL4c/2v0sAJ17eUa7LpTD82ua3znAC 7Ia7evwfHsAeRyly1Rc8/8nzDks/7kM2elMauJYAgYz9EUZq/9VwXoFYP/4X T0ZlE6UkVBSisqLSIXwfUbKiEBEySiozo0LI9nm2ZxDJiBKRlEg0zBDaRoUQ RUkp/Vz8/5fn5pz33ft1bk4+co9OfJZQJBDeerKKsv8qdvEGhY0pEciquXNt YC4XPXlzSxtVCWQIsyayrudi6djSTaHaBOwjZ+TsxHLhH7Te6z2JQOh6J963 Q1ewVKbox519BISYlZXTWVdwpXrrpQxrAicbHZNJjlfw4p/BVRMnAsqGnnFJ ndnYkXhosMifgHjV9eLGK1kLnNZ3OvYsAR2+3cWnlbNwst2TxyWUwB4JmTs7 S7jIljqrIBFNoCa6U4LnIQcCWSkuIVQClv0/THcvYqOzvP618X0CBZ8brqV2 M3DCfq+v3EMCS3Oo1KoQBvh/tf+aaSSwTv2S4FlZBvR2v5Mpaicw0b1MNOI4 HdynP+3FPxDoqlKwlZGgQc8vaujzMAGb1ECdfw+o6BDhD340TiAudcUR+FPB ZytJDZ4h8Oj0Gu+y5xT4vtvc9XYZGZ/od+5VXyWD70K5e6UoGa7Ddhr1zmRw 1u2YSltORri9+OtpaTKeHydJGMuRscSgPKIuiYDulNuBwq1kmNMqVp6KzQDP EnpzkAMZKhqR9iMWaZjdrLfzzoIP/83GIz5dqZiweVU060aG39HjpJ/OqXjL lU0MP0GGQo/pesngFFTqZptdvEjGj+12i3bUJqHY2aiqPo6MmzX2mSvsk5Ab PbiRL5kMsQrRPxUTiUhv27AknkZGqnVDhqxSIny9ChuTr5OBKZm32XkJOJps rtNWSoZ3sTTp1t4EOJSNXRWrJIPJJN81nYyHybx6LFFHRlzjB7P3u+MhTyvb w+gm49wN0hKxyUt40XivNvcfGfUO1xifUmLQNOa85RMfBf5fVy5SIcXgocQ8 V1mQgqnJmL4UnhjcOGIYVShFQbhAyZn8sGhc/tGw66YKBfe+bgpKC76IC7Je xV81KNBl3fCx1buIYKMlazS1KaCZbdaVnLsAj5S9c7d3U3Cj6Xujf8wF7FZq u1ttS0HSpqhpx93noW1xSuXPIQoIHpf0nOdRUDstzjRwoaC/2uo1xyNqob/b hNZ5U8C7cdAjIyMS03a9uo8jKWia8mq7Mh+Ogtj+8o58Cl46G0nGyIdB9OgM 53cxBcdpoUvsmkMRuFM4YX0ZBYe0MuqPhYbCcGq7c9B9Cq6mP0lV7QnBS9c0 vlUdFLRUBQ8/yQrGsp27Dx79TUHpuCJJ/nggAlbY4fI/ClxeTHbTNgSi55uP ShkfFcdetXjxfjiLnALqX14xKm6M1fZddz+LHSu+5OWvpyLsR43h8xNn4PuN NTOxj4r3r35e2F8YgOctt/pX2lAhN+8U7BYYAN2CJ02GDlQYKHrJahkGYLHr NJdwo2KKVERacvsUWC3mJN1gKmKWr2Au3+yPlvxf9MgsKlidzTHXHP2gGSMW fe0qFS/tlBKn+P3AcFE60V5IhWCOraVXmS88pK0NFW9T4Wq2S6Fc1Bd/ogtG Gp5SQVKSjfN+4Q11Fwd94SkqhjTbtcvSvSC8VMzv7QwVVl/C8iStvTB66zG7 eI6K+1RBPQNJLxTw6y7az09Dys49rE80T6wrkXqSIkNDp1Jx9vZCD8j86bAT Aw1ndbtOX510x8+8y3F9xjQEedV3nbznjp4DRlU3zWiY+/HF6lW8O8i5pbJW NjSEsBf3p6xzh6hF2mC6Jw0qzqLft7m6gTdzX4BkMg19vnNJe4ddMWjMlzOY TkP2myEL7QxX1H2511VGpYHNt81jwy5XRBmpbbfNokH5X8JLAaoLZkeWzZPL aHi2i6YTYnMEE9ufJEm/omGpSVSG4S9HtA5E1Xx6R0PLJ+uVf285ojhJd7Ji kIbRl8OWKX6O8OnLs7Efp+GgXv6o3MBhfIyLXUX/R8PDt9+yK7oP4VW3Ub6M Mh36NWVqyYP2kOKVumulRse2+2kNh3PsYbV1qClhKx0yCsGl39zt8TQxcWJ2 Bx12Jk6BQUMHUYUunVcH6LBfrXvl4owdaIUeDcwwOnT4fVYH6dmis0e3pyOK jhsXqj1v8dpClG/ZyLJYOvr3WFult9sgzqVE6FwqHTFLntup+9ggaPmMjWMu HU7xbNnCXGvYRcYPrG6lwztdbXJEywrpRYenbTrpSDsV8tFxqRVaetX4k3rp IA4zfLKrD8BE8/mmuYEFvzXt0hESB6A1LBPwZoaODAFm52TTfkhaF82zFBjY 8/lbPb+vBSyjIsRfKDFA+haV2KlogcTrluuE1Ra0wcnYwNfm4BGYNo3QYSBp zT1VdUtzfK3emeJszkAUR0RxI/aifUOrrFwgA0ezlykKmZIQq2AU9CeUgdXr G+ImhUnQW1PR9iaSgfM1fHF+3f8heznnYmY8A+wuy53rvf/DmcUnh1eyGDDC sIobxRQr+oXLJesZsOQpz7gmYIKmNxeEpx4zoEJ2IXb2GuN873fPjmYGBvRK rS0LjDHS9lYmfeFPaV5SNxu2MEZ1TXGUyGcGtmzjr65l7IELa5/5UnEmulP2 eL4nGUGSXpc7LMWE54H7tOvyRnhCaP99vIqJ4EeMswM/DbE1cU3ppfVM5D50 CosuNMTisHFp3u1MWAT1JYZJGCLPPnng7xEmTl8t104eMsC4REvo9HUmGms9 gm9M6EP80e191aVMSIqEyyZU6EM7kKNwsYKJZ/2/aBMR+ojo8X8qWsvElvJM SWcRfQixJGRUO5lYtzFEPl1bD6obHO4cnWUiqcT6zjqWLiy7kbTxLxM2yxP6 1/rq4kzcJtcJnkxEixZ2Zujronrkl0CEUCaOlPuv6n2lA/MStj19bSb8y+Q0 a+R14KM7+KPVJBPJrHHh6VotJA83PaPszcS5jc0/W6laKGWUc5wsMxGQ4OAs ckILs79jTT87ZKKIuTigYpUWEmo3Uvn8MvEmtjMkNUwTBWYntXdmZKLcRHV1 kvk2DDnOnil4lwmGSQTzo70GjqfNKfcOZuKZ5stdHZIaGHk0/5p/JBOl/F4u 3u3qGN3Mb3xsKhNze7m1qebqmJiXWL52CQtb1pQXXDbbjJ85auXkrSw8V1nx r9JNFaG9GsfrdVjIqJ5tDduoit9CmrLfdrAQXXRJpOWLCv4E6sVYmrIg1zL7 RCZCBYtIprbLHFl4ahoUr5K1aYG3XKajYljgPVhj/fmvMi7Lu+eXJLCg09md 9qNZGYJ2nk5vU1jwHLbrOZepDOEav0f6DBaeXZE6NaanDPG0UPL3YhbE1l7D nnAlrNIitHx7WHDZ9TqoRmoDVMMbzx5UYePv64jflmRFbIjyPaWmwcb3m6NS DwMUsfaimB+PFhtf0smfoiwVIRF/2L1kFxujSn9aXwsqYpb4YsVvxUaINI/S ongFNBZJa1QEs9E1YnT4hYw8HpRUqySFs9H6tDsi6e1aVJW6KrldYEPeiv9F Q/ZaFFcWrhFJZOPDtmGTu6prQdQbCHly2Bg3KfgbbyKHo689R6Qa2Dikt2lN TaosHN8Jfhx9ykb0h4kkYUdZ2Pbf7KtrZSNvc61Gi5Is/hv61XOidyFvNPwr /cFqqE+lNDaMsjEk8FLD9Mcq/F5WmRMowQEPn4K+XLAMqPoCR164cOBJ+GwP qpVGpdi4zQ4PDoLOX++1IKTR86nDLNuHgyfez3sTPaUhQ3C0TwRycLv6X4eB iDTYo9rCfIkcRFV9NnFyk0IO69g9rQoOzqv5fmXKLl/gwr23mNULuhkfz3+X xEfSlvx/tRzspTe/f9AqCaXvv4nmJg762m/7mVyURME+wvdYPwd6L+r57ccl cONv3SqyEBfnbjPr3nSIo73rmtgvcS7a+secJ26K42thMr/rCi7yD+9YuT9V HNvsD31TVeTCwC1yZsxCHLdvTD6t1+XitFlcrC5VDNWua0On3LjQHsupMS8S wRsdPv9Dx7lwuD2WaHFKBH+ERo89OMHF010jbW3aIjCoqjiQGMLFk0t5jQ4P hVEnvn/juhQupt33nbHuF8LAkKZcAsFFj8xAv3GhEBbXyCyfoHNB6lPaevOM EIx9Ps7fzeEi0mj1wJiAEDzQ9F2+YOE+r5LF9zoEEStdOnppgevLjSJj59mC yBuj9o+VceFzZHB/hbcg/m+PEP+/R/g/M6LV1g== "]]}, Annotation[#, "Charting`Private`Tag$8997745#3"]& ]}, {{}, {}}, {{ GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.031249998724489796`, 1.9502111502554127`*^-14}], Offset[{0, 0}, {0.031249998724489796`, 1.9502111502554127`*^-14}], Offset[{0., 0.}, {0.0318499987, 1.9502111502554127`*^-14}], Offset[{0., 0.}, {0.0318499987, 1.9502111502554127`*^-14}], Offset[{0., 0.}, {0.032449998675510204`, 1.9502111502554127`*^-14}], Offset[{0, 0}, {0.03604999852857143, 0.10054143700944271`}], Offset[{5., 1.1102230246251565`*^-15}, {0.03604999852857143, 0.10054143700944271`}], Offset[{10., 2.220446049250313*^-15}, {0.03604999852857143, 0.10054143700944271`}], Offset[{10., 2.220446049250313*^-15}, {0.03604999852857143, 0.10054143700944271`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.031249998724489796`, 1.9502111502554127`*^-14}], Offset[{0, 0}, {0.031249998724489796`, 1.9502111502554127`*^-14}], Offset[{0., 0.}, {0.0318499987, 1.9502111502554127`*^-14}], Offset[{0., 0.}, {0.0318499987, 1.9502111502554127`*^-14}], Offset[{0., 0.}, {0.032449998675510204`, 1.9502111502554127`*^-14}], Offset[{0, 0}, {0.03604999852857143, 0.10054143700944271`}], Offset[{5., 1.1102230246251565`*^-15}, {0.03604999852857143, 0.10054143700944271`}], Offset[{10., 2.220446049250313*^-15}, {0.03604999852857143, 0.10054143700944271`}], Offset[{10., 2.220446049250313*^-15}, {0.03604999852857143, 0.10054143700944271`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{34., 7.000000000000007}, {0.03604999852857143, 0.10054143700944271`}], Offset[{34., -6.999999999999993}, {0.03604999852857143, 0.10054143700944271`}], Offset[{10.000000000000002`, -6.999999999999998}, { 0.03604999852857143, 0.10054143700944271`}], Offset[{9.999999999999998, 7.000000000000002}, {0.03604999852857143, 0.10054143700944271`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"first\"\>", BoxRotation->0.], Offset[{22., 4.884981308350689*^-15}, \ {0.03604999852857143, 0.10054143700944271}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.031249998724489796`, 9.086145902352729*^-15}], Offset[{0, 0}, {0.031249998724489796`, 9.086145902352729*^-15}], Offset[{0., 0.}, {0.0318499987, 9.086145902352729*^-15}], Offset[{0., 0.}, {0.0318499987, 9.086145902352729*^-15}], Offset[{0., 0.}, {0.032449998675510204`, 9.086145902352729*^-15}], Offset[{0, 0}, {0.03604999852857143, -0.0045970750246197714`}], Offset[{5., 1.1102230246251565`*^-15}, { 0.03604999852857143, -0.0045970750246197714`}], Offset[{10., 2.220446049250313*^-15}, { 0.03604999852857143, -0.0045970750246197714`}], Offset[{10., 2.220446049250313*^-15}, { 0.03604999852857143, -0.0045970750246197714`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.031249998724489796`, 9.086145902352729*^-15}], Offset[{0, 0}, {0.031249998724489796`, 9.086145902352729*^-15}], Offset[{0., 0.}, {0.0318499987, 9.086145902352729*^-15}], Offset[{0., 0.}, {0.0318499987, 9.086145902352729*^-15}], Offset[{0., 0.}, {0.032449998675510204`, 9.086145902352729*^-15}], Offset[{0, 0}, {0.03604999852857143, -0.0045970750246197714`}], Offset[{5., 1.1102230246251565`*^-15}, { 0.03604999852857143, -0.0045970750246197714`}], Offset[{10., 2.220446049250313*^-15}, { 0.03604999852857143, -0.0045970750246197714`}], Offset[{10., 2.220446049250313*^-15}, { 0.03604999852857143, -0.0045970750246197714`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{52., 7.5000000000000115`}, { 0.03604999852857143, -0.0045970750246197714`}], Offset[{52., -7.4999999999999885`}, { 0.03604999852857143, -0.0045970750246197714`}], Offset[{10., -7.499999999999997}, { 0.03604999852857143, -0.0045970750246197714`}], Offset[{10., 7.500000000000003}, { 0.03604999852857143, -0.0045970750246197714`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"second\"\>", BoxRotation->0.], Offset[{31., 6.8833827526759706*^-15}, {0.03604999852857143, -0.0045970750246197714}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {0.031249998724489796`, 0.000049984964000451867`}], Offset[{0, 0}, {0.031249998724489796`, 0.000049984964000451867`}], Offset[{0., 0.}, {0.0318499987, 0.000049984964000451867`}], Offset[{0., 0.}, {0.0318499987, 0.000049984964000451867`}], Offset[{0., 0.}, {0.032449998675510204`, 0.000049984964000451867`}], Offset[{0, 0}, {0.03604999852857143, 0.20568613151836504`}], Offset[{5., 1.1102230246251565`*^-15}, {0.03604999852857143, 0.20568613151836504`}], Offset[{10., 2.220446049250313*^-15}, {0.03604999852857143, 0.20568613151836504`}], Offset[{10., 2.220446049250313*^-15}, {0.03604999852857143, 0.20568613151836504`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {0.031249998724489796`, 0.000049984964000451867`}], Offset[{0, 0}, {0.031249998724489796`, 0.000049984964000451867`}], Offset[{0., 0.}, {0.0318499987, 0.000049984964000451867`}], Offset[{0., 0.}, {0.0318499987, 0.000049984964000451867`}], Offset[{0., 0.}, {0.032449998675510204`, 0.000049984964000451867`}], Offset[{0, 0}, {0.03604999852857143, 0.20568613151836504`}], Offset[{5., 1.1102230246251565`*^-15}, {0.03604999852857143, 0.20568613151836504`}], Offset[{10., 2.220446049250313*^-15}, {0.03604999852857143, 0.20568613151836504`}], Offset[{10., 2.220446049250313*^-15}, {0.03604999852857143, 0.20568613151836504`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{38., 7.500000000000009}, {0.03604999852857143, 0.20568613151836504`}], Offset[{38., -7.499999999999991}, {0.03604999852857143, 0.20568613151836504`}], Offset[{10.000000000000002`, -7.499999999999998}, { 0.03604999852857143, 0.20568613151836504`}], Offset[{9.999999999999998, 7.500000000000002}, {0.03604999852857143, 0.20568613151836504`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"third\"\>", BoxRotation->0.], Offset[{24., 5.329070518200751*^-15}, \ {0.03604999852857143, 0.20568613151836504}], {0, 0}]}]}, {}}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{True, True}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{False, False}, {False, False}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}, {Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->{{All, 84.8}, {All, All}}, ImageSize->{1121., Automatic}, Method->{ "DefaultBoundaryStyle" -> Automatic, "DefaultMeshStyle" -> AbsolutePointSize[6], "ScalingFunctions" -> None, "CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotRange->{All, All}, PlotRangeClipping->False, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]], "Output", CellChangeTimes->{{3.8223107558554363`*^9, 3.82231077565624*^9}, 3.822310833681052*^9, 3.822310886489955*^9, 3.8223109535386953`*^9, 3.822311005095648*^9}, CellLabel->"Out[16]=",ExpressionUUID->"52bf8e80-e33c-466a-a77e-03ecfb2fa225"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Export", "[", RowBox[{"\"\\"", ",", RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"w", "/", "0.02"}], ",", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", " ", "0.007326447541946075`", ",", " ", "0.007269560988958051`", ",", "0.007238948047382406`", ",", "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.009999959154289148`"}], "}"}], ",", "w"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"w", ",", RowBox[{"-", "0.02"}], ",", RowBox[{"+", "0.02"}], ",", "0.0001"}], "}"}]}], "]"}]}], "]"}]], "Input", CellChangeTimes->{{3.821859448950233*^9, 3.8218595146586237`*^9}, 3.821859600380082*^9, 3.821859680428216*^9, {3.8218597375983963`*^9, 3.821859756496582*^9}, 3.821859866192789*^9}, CellLabel->"In[44]:=",ExpressionUUID->"cfc65b7b-0c05-4955-b381-78e82bef63d9"], Cell[BoxData["\<\"test.dat\"\>"], "Output", CellChangeTimes->{ 3.821859515511661*^9, 3.82185960109886*^9, 3.8218596813412437`*^9, { 3.821859738353854*^9, 3.821859757880114*^9}, 3.821859867972911*^9}, CellLabel->"Out[44]=",ExpressionUUID->"3f195e23-3834-4bb7-8a87-2b3d763f8925"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Export", "[", RowBox[{"\"\\"", ",", RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"w", "/", "0.02"}], ",", RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{ RowBox[{"{", RowBox[{ "0.44798874545216505`", ",", "0.3720949697259449`", ",", "0.3666741914433289`", ",", "0.36586118013042696`", ",", "0.3656755715952492`", ",", "0.365617222323006`", ",", "0.365617222323006`", ",", "0.3656755715952492`", ",", "0.36586118013042696`", ",", "0.3666741914433289`", ",", "0.3720949697259449`", ",", "0.44798874545216505`"}], "}"}], "*", "0.02"}], ",", "w"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"w", ",", RowBox[{"-", "0.02"}], ",", RowBox[{"+", "0.02"}], ",", "0.0001"}], "}"}]}], "]"}]}], "]"}]], "Input", CellChangeTimes->{{3.8220259669299726`*^9, 3.822025975574121*^9}, { 3.822026015205662*^9, 3.8220260205159283`*^9}, {3.822026085524934*^9, 3.822026094983859*^9}}, CellLabel->"In[14]:=",ExpressionUUID->"592cf244-c9e0-441a-9140-234a2bad516e"], Cell[BoxData["\<\"test.dat\"\>"], "Output", CellChangeTimes->{3.822026098392877*^9}, CellLabel->"Out[14]=",ExpressionUUID->"c21d3d19-d64c-40d1-96ac-8143059ffffe"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Sort", "[", RowBox[{"Eigenvalues", "[", RowBox[{"Take", "[", RowBox[{ RowBox[{"h1matchain", "[", RowBox[{"0.", ",", "0.", ",", "0.", ",", "0.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", " ", "0.007326447541946075`", ",", " ", "0.007269560988958051`", ",", "0.007238948047382406`", ",", "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.009999959154289148`"}], "}"}]}], "]"}], ",", RowBox[{"{", RowBox[{"2", ",", "14"}], "}"}], ",", RowBox[{"{", RowBox[{"2", ",", "14"}], "}"}]}], "]"}], "]"}], "]"}]], "Input", CellChangeTimes->{{3.813389797311977*^9, 3.813389902963969*^9}}, CellLabel->"In[54]:=",ExpressionUUID->"7d89f0bc-7957-4569-8eec-16807055849e"], Cell[BoxData[ RowBox[{"{", RowBox[{ RowBox[{"-", "0.01482162284781889`"}], ",", RowBox[{"-", "0.014196943843564085`"}], ",", RowBox[{"-", "0.012577491983658652`"}], ",", RowBox[{"-", "0.01023250177622813`"}], ",", RowBox[{"-", "0.007255261224137862`"}], ",", RowBox[{"-", "0.003771694357740243`"}], ",", RowBox[{"-", "1.793639648706543`*^-18"}], ",", "0.003771694357740246`", ",", "0.00725526122413786`", ",", "0.010232501776228125`", ",", "0.012577491983658652`", ",", "0.014196943843564088`", ",", "0.014821622847818888`"}], "}"}]], "Output", CellChangeTimes->{ 3.813389819016448*^9, {3.813389849558824*^9, 3.813389903638837*^9}}, CellLabel->"Out[54]=",ExpressionUUID->"5db81ab0-f57e-4dc2-b50d-150ac5f5b490"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Plot", "[", RowBox[{ RowBox[{"transmissionchain", "[", RowBox[{"1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", " ", "0.007326447541946075`", ",", " ", "0.007269560988958051`", ",", "0.007238948047382406`", ",", "0.007238948047382406`", ",", "0.007269560988958051`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.009999959154289148`"}], "}"}], ",", "w"}], "]"}], ",", RowBox[{"{", RowBox[{"w", ",", RowBox[{"-", "0.02"}], ",", RowBox[{"+", "0.02"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}]], "Input", CellChangeTimes->{{3.813387160152753*^9, 3.813387194627912*^9}}, CellLabel->"In[20]:=",ExpressionUUID->"68811056-506e-4818-9152-69039a8354f1"], Cell[BoxData[ GraphicsBox[{{{}, {}, TagBox[ {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUWnc4lW8YtoWUolRKVjKKSiHxvRmpkOxNZsnOzN57HSMtEaJQRrbkiRCy QyrJzDznSFJR+b2/v7ru6/vO+z3vs+77dsVv7apjR0dDQ7PATEPz/78Rw49P T/ilw8WWsYhVRRWC63P9cqFPOjh3Mkln1aoQj6a6H7t7psOlZ0H7hU+cI1qW v+9icEmHT9Q5ax4JVYKR7eyKsFU6VBzbfNGufoHI2KFbSDVPh79rrUTCpwuE 8J6rlrUm6UB9t6Ax4HKRUD2U0HNRLx0UlXh/KD9UI6LQSJHT+XR4+0Vy2un4 JWK36qLVKZV0WCxI9135coko0Pi359/ZdDijyHCnLVWTaDMWik6WSwfzgdr1 r3RaBJOnm83zo+mA9N4rGKVqExl+4fv8xdKBKz3ie+AfbUI4NKNf+XA65Ag7 xF68rkOoJjWgIb50mNHJnt2rrktEP9my/xdnOsw15X6uOK5P7CnlefeKIx2i wyqK91ToE0+qJOJi2dOh6FJ8+ysZA6K9We/XPuZ0WDvg73lS3ZDY8vnhoMJ6 GvTat1kqPjAm7kxVxDP9TINtyUUTumdMCJGFNqXe72kQc6kFuXw2IS78XCqz JKfB6MP0K2ISZkTMjtOJ4eNpsM/ceuEvwxVizx4NFY3PafD+Xr1XdNsV4gnv lQ2uj2mQIoeIaFVLol088nrBuzTYfjGIsZ/LimBR7T/X0ZYGVHMFSZ8Ba+Ke xvSflNdpwPBIUE3mog0hpvuzwuRVGvDfLDXneG1DqFkeEFiqSwOPOwxddq9s iTi/6/+2PUuDfitzFvHpq8TxQQev1MI0kDYJq3kedo0YOeq0tKsgDeakI/e2 HrInDk+4fNyfnQbjO+5RuP2uEy3nPavFUtJgSuqX5t0rToRTjtfRksQ08BQP LU8VdiY4N7wfHY9Lg8Ort7R1vjsT1iW+qbLhaWAzkF/5KcuV2OQKdlH1SgOu v36x1Tk3iAKXkJmOG/g8MSH277zuhGZ7qNkllzRwdEJOY9nuRKZ/hJretTTg mElgl33mQagMRTa9t0kDpbmTdNOnPYlFiWhZU0v8fdrJXfWdnoTcZKywtXEa KNZ/j3X87UVMnIl/MKOfBnJpIpKJt72JmFsJXNd10mD16pqHnZwP8f5CMp2b Os53+qPid0k3Cc/S9LFAhTSQmVKfE/TxJ/azZOjTyqXBhc9/x1xRAPHa+nZX hHQaZLUczuhgDyR27r5XHy+J40tUpTi/DCLqXO8f334kDdwPdrDzZwcTlh2Z T1JF0uDS0VaND8ohRGlAdsZd/jSwFWxbF5MJJQyGH7If4E0DzVHNcNfqUOKf ZG7Ew31psK6VVnbvdBihMfXI/TFnGvxmVus5rBFOLFws0qxiTAMz0vCxlfxI IiWvuFWWLg2+Kmlknb4QRcj+fSrf8C8Vgh9akROoUUR0WanY65+pEE+ZodJp xhASrOU5qqup4KpVfjWYMZYYtnm+p3M5FVj231N40RxLCHFXMfXPp0KqCnuU 9OV4osutOlDvayqczS35NsqbQHh01qy+n0yF25LHNzl+JBDNgfWTY59SodPy DYmhOom4Mg2NS92pQOXMMbW8kEJsvaJvWtyZCpspISnQkkLUflj4ef1NKry4 xSU0rJJKcPTuOj77KhUc7o2dzNNKIxouFnfnv0yF9kfR+++OphHXW8462Nan Qh+YmbY6pRPNdY55ExWpwPj4zCf1e7cIl5O0Zx+WpUIug0QmRSaD2FeaMWrx LBXmWPUrjT5mEB6PmnaNFqTCvsRv3/kl7hBCydwxw3dTIX1tVEpy932ij+WZ 0K2MVJCW295ZNHafCIhQatJNS4XZXJYA7WeZxJCv83pfQirwpfWbLJtnEWGr dLeTY1PhWmncWf2z2YSE6x0pzahUGHlhbfeF6yERZfva6W1wKlSpDxqfZ8kh TnwxYokLwO8/2flJNjaHGDOm5F/wTQXnZB8/UfZcQuby3i+t7qmgaakklcKf R8yddtV+ZZcKzw494A8JySfSKxkoQdapINRQ6mcvVECclbwXp3AlFY69VGaN 6C4g7gq1vq43wvUsvMDPeuwJoZptYumrnwrEt+fu7+afECt7l//I6KTCSQ+t osTCQkJtO490lXoqBCg2Qv6ZYmIttmzA40IqBIVRut22PSVyGVRdT5xLhUBz JRvmuafExm+3J6VEKkzv3rM1pqyEeDrdtq/oeCp0ubYUrGmWE0ZXzGrsJVKh o6VDdNv7coLh4zfdw+KpoLtpdfa+zXPCvHd/4iOhVLhgIMFdE1dBsKo9F7Xh T4VbIWNb7x2qJKpbzrfx86aCKFla6H5rJbGt3n0zizsVBJ7GMT3fVU3Un9yS ac6VCuDeZiLaVk1cLX0gu39HKuRVPmIJC6gh4FH7jbusqXD3TfDN0o1awi2Z dzrtbwrMfuiyM1JrIA6nvPhgvZ4CPdsLAjPEXxJjqUa9x3+mwMqflptaXI3E pYzU+t7lFBj3jfVT+wsEwx3JsixyCmyrFedmD35FNNztyndeSAHLbK+CZvom QuwBUwrbdAqIMX4SqN7XTExk5UV9HE8BtMzjdf5ZM3Hn4dmAws8p8IL3gEe3 ymuC+ZHftfPv8fsl8qZu4S3EdBFFIbwzBYbbvP9Gq7wh7j+Nl9J5kwIaV3il RBnaCZ0SEVH+lhRY8KY7Y9PZTjSVW3PByxT4waZekOnYSdys2GRJqk+BvI0b jQfPvyWOVWVumtWkwMxvk+PKYl1EVu3wwnpZChycek6QtvQQBvUe4x3PUoDZ uv+xLkMvwd7AMXynKAXmdWfzvRj6iABQa5J+lALp8pTva7v7CeO2xtvut1Ng inHS/PnNdwRHu2miYjqOT+1d6BLvINHe8SuMIyUF7qud6OF+O0hId59wKYlL gRymX0JHpYcJSk+vTWB0Ckzs3fY59ccwkd/nZKwRkQICFqy6Ey/eE1yDBSoL gTjfFoqzGhYfiLdDynJ1finwet3McUPuIxH2flwyxicFut2q66sOfiK+fdzH I3wD18NrkjON7jPRM5H0zco2BTrXQ926748TkVPis8esUmCMKdCBV3KCkJ9p H900T4GK3wPDC28miOI5uvYHhinwYOBo5AjrFGG9kP3SSS8FYoZ+CdyomiL2 LclXnNFOAYexXYc8r04TMVTvrA9qOP+1741bR2cI9I0z/cn5FFgf4Zp8mPuV WFspi/VRSQH76B31tG6zhN3agucuIgVEqcknUgTmCaW/Furax1OAP8lt0Wp5 ieDQWaD5dDQFOMVfXF7eSSG+FHhV24qlgN6WtIbXilQiQCuB/6ZgCuxKbshV mFom1PK539PypUCcyv2f7UnfiL3ruQnx+1PA6JRwfaHiClGdV/cza1cKSCl5 GHc0ficifqk8E9mZAuGf2TebYlcJ3Ut91s+3pQBdpIpQhPkPYnnta3crcwqo BSYXs/P/JMTUuB4t/SYBITX+leXQBvErK9vYe40EXSZN2nTKf4g338W203wn 4XqGkUqd/xK2DxT9OJdI4JTDte3h4iZxYqVL8sEcfr8xtmfvQxpEe95oRniG BN0R0l3bdGhR1rKLltwYCRaMd7EF9tAhp3PrjC0fSfCP0u/UcpcenbkX+eLS exKokl4N6LowoBHlTGGrPhIkyfo+OnSKCRXcOTy60EUC+qEEPzsRZuRFfp7i 2UECdTft2TnhLWjn7Y4/0c0k+KyqXEN/gRWNL+o93wEksAqrLHrnyIZKz45f u/+CBFxSh88aP9iKNBbWBkoqSZCWdLLB6Mh2tA+FxciWk8BYzKui6BwHmk9j J5qf4fPS3slE/+VAUQpChUMFJOjhvX6DJ2Yn0ksttbiSRwKhQU3V16acSHBW jms+mwSmd1h1ik5zoVck7eA/d0jwu9POx3b3bpQ0M3oy6hYJPL1M+qx3cyNz OfuF7akkGKccG/4psAetTwXpC8aToHQxOzvbdh9ql2VlexZNgjiphTKR+zzo duKtV9IRJLj6PcFIemI/OinzVFwtkATfXqzeUMs+iOgSZCbe+ZKg9+rWm2kJ fKh/vDnD3JsEan9gep8uP3KJ+0B7w5UEG+72Z/dvCiD5L7Y1644kcGjji2uc EURsJ5edIuzx93P6e9RHhNCTz0wjt63+r/8DrvEpYeRzIjWR34IEnXHJNhb/ DiPV6APKxSYkeJXPVl9zWBRNHTtZ0qhLgvrballuReKoukA3NlyLBHwwumOZ fATF7fewvXCJBAl75W6kKEqgY1ue7xtQJYHY0d3NtknHEENQ/48MZRJc40xg PaR7HL3/vtxnepYEu15cZp3gP4GCvkhGz5wmgXPuqeW4L1JIR/+ydZE0CZ73 VQiV9J5Eh966KLhKkSCkSuidbNcp1FX97PuvIyQ4RF4qNSPLoIdHunteipLg dqP9mSDO08gjd6kwTJgEOvM04XsvyqF9SeKWW/lIYBbW9NX0qzyi0Kuf6d9P guQsDsGflwnU5OuwO2MvCV5+XrNZ60LI3q6w6yAnCWTlnrNPhCki+U/tj6e3 k4CmoyOH2VoJbdeeCyvcSoIaHx8V60vKqFr+8GkpJhJo1r/JeKZ+DsU9V+X6 RUeCmYodQ3KWqqheq2vMdzMZ4l6J7JaJOI+YRdTUE1eSgeVFeoz+v4uohDOW lnspGUxXmumSDNSR3uabmoczyXCKdjHZtlkD5Q6fE6ocSQbdtqMBSx8uo4vN ER8VBpIhtsiRKtaihZafvSa9eZsM6nWHLeYeayMiUvHvx8ZksLptuFv5ji6a cQupsK1NhiSRougnBXoowQyuU8qT4U2hg4loqz76IKUwTJufDLfmD/x6K22E Qg4GJMRnJQO9Q9Cd8wnGSJjthdKuO8lghkIDbq2ZoO6137+yUpLBW0TGe7+P GfKclC0ViU+GR8Xl8+bbLRBPj4/d84hkcHaS+P7z1RXUXFfNIx+EvydEN/Gu zRJxpJyMuXwjGVpZg/hWwRrVBHgQHxySQXLfDst3gzbIwv75qrUtvj/dbn+X DVvEqPetaMk8Gb5+GDjHfOoqeoqOWXkbJkOC0lLNr7BrSFfclZtGOxmMmd+z 1321R+u7S7pj1ZJh4yWv4KiVA7pAEZd7oJAMt8nLtQr5zoj6wWFZWCYZ/ELL TLRuuKKM1sKCsmPJwGOoJi1X4oYUyufM5MRwvup6W4Mqb6DpzMOcLYLJQD59 QL62yx3Fx1ztuHQgGeha1V4p//JAJzzzg9/vToan4XnP7st6oWB1waUFlmRI pu/2lv/ng/Q+EwILdMlgxHqN7mKhLxJzNTGa30gCsywlvUgvf7RJ4500t5oE Z+wr7vXYBaLB1JSWWXISNATevX0+MBgVCT1b//o1CVQSTKdLv4Sg4Or2Y1+/ JIGe85ViMncYEvu4mTndnwSXggJEvIYj0KYjz7upziR4zqnWGWIVhQb/SrNM vU6Cb5sMVpfYY1BRsg6abEiCSuHAE59HY1Ewv4vXRFUSuP4KyQ9+F4/0KmKL x0uSIGj3Tv8Pq4lI7Fz+xJfHSbDiNL3sLUBCg/ajl8buJkEvBDtXNqWiovWf 4Z9Tk+CGzRN2ZiIdBSdw1o/GJ0HdX7/bdKO3kB6v5PKniCQI3dtZv5h1G4mV qQl/CkyC13alWeZxd9Gm4lWzj95JoB/BNqaTex8NvgtN/eCaBF0HBvUlFx+g IrsH7SP2+P7UqmszJx+i4J+1/95bJYHISOzZxpQcpBc7ePK9SRKkcceWc27P Q2I8yw7DukmQmbDtmWDZI7T5lC1nSAM/P50VFHyzAA0Sh98PnksCuUjF3zud nqCiPiX2QQLHy/GxWTy5CAVbWyi/k0mCBw1Pb4d8fYr0Vn19B44lAaiclpX1 KUViUbdK+0WT4P06dcxHsBzR7Cmf6RNIAp2VnbNfnj1HQ4VdPH08+H5Hmbbz WVSiojNz2r1cSUDSH1FqkalGId30MT3sSfAmL8bwNlGL9K8cbOxmSoJJFanM bO96JPZNbrVrMxHUGE+57ZluQDThBmJdvxJhIs+c0z4e0BCXu+Xbb4ngs3HA NEa2CRUVJGZ0LiRCizPbUndXMwqRLezqmEoEO5Ww6xDRgvQ7W+g6RhNBOUqp 39+6DYmZjcu2DyWC4TO/8OVr7YiGsuHypicRvhRItzdmdKKhYO78tjeJ8OeM e+/+5S4Ukqe5o7UuEdoVSLvldvYj/VMO51ueJ0Jl0NFB+eABJPYmMvB1cSL8 Pib10YlmEA0tNMw3PUgEx/wcuQey75HYCfHmxtBEENnNK68hMYZoWlR/vfRL hDt5bjQD1C9oSN9a4qVHIuz/cO9e0eA4KpoNtG1wSoT+JpdlctEECvG9e++F Hf49l95h/ZuTSJ+tqq/eIhEyItN+vJCbQmIP+pjqDRNh8tzTTs3lKUQjuSRf p5UIdFZRZZm3p9HQK2aP2ouJcPaJcESu5Ax6ZXnCdEQpEcauOo/7VM2gpzTm yr/OJILta69H0+Jf0e2H0eJ7TiWC1sbHw8JpX1HY2eecshKJ8GLZ0bpr8Sty GR/dMDycCN2p/7iKpWeRcQjztA8frg/toZ4Oz1mkwnei6/beREjKeLZT7/Es OvbKrLJmZyLsuK1cGNc7i/ZbRme+Z0uE3qc+1dWUWcRM8zziJ0MiTA1lMx9k mkMr2aNO3P8S4Nj98sLN3XNoDDHry/xMgO1mn8rDBeZQ55fjCobLCXCXpoS+ SXQOVQWbHfKZT4CMDKf2qqNz6OHBaPbbkwkgxy+qel5yDiVA+Y/qTwlw/btT uyLGN6+Mfh4eTADRsnIdY4k5ZLPJ1LbWnQBT24RHxfDvNbOPl+x+kwAXTox9 VTgyh+SQWYb0qwToqJE7x4TxoS9RQQZ1CZCuJ7MygzFHcPlV7+cJMCvyakYC n/+Hd1QzozgBdgunDQlJzaHZRiaZ6kcJwO68OPJPdg4NWBw/OPwgAVxW3s7P nZ1Djf9MmdcyEkB+27WzjOpzqDArirqLlABr71ljnQ3nUDpR/v5UbALcuO+/ KnV1DoWMfQL9sARY3rf9sK3PHHIMYnri5Z8AX0pEmBji55AB73HSLc8EoGmE 61w5c0ip0fRmlXMCqBzSqUipm0MSFlGWQ1cTIPa0gKbn4Bza+6/swo8rCZDz SIen/NscWlZg2ntKJwGanvGd+HtiHn36fIxWXz0BRARees8azKO2QNN5T5UE 2O+7ZjQZMI8evCyrq5ROgNa3Ae/ye+ZRjPmnnEHJBHh568MZmfV55PmXMW5V JAGEM0r5HQ8vIDUFU5OTPDi/bn84ZKMW0K8Gxo2KzXhoa6SRDdFeRNNmx6be /YqHL3dKL2tELaLePyZvv3+Lh5orxaUpLxZRgXzZfanpeFAs3Kv2RXgJ6TWY yFe0x8P5Wtnano0ldNYsUuhdUzxc3xG3tUqSjMT/lG79Xh8PGoxdPi+tyYhO nvHziWfx4PY7SojUSkalL0oDn6fEw14mbRYWPwp69ICu/EJ8PHybcjDf95CC 7gXrT49FxINtH+d19xYKSrZ6wu0VFA/vql8Wb3yloAjlDTW2m/GwwqpQl8tM Rb6HNINybsTD719hWgbCVOTCnFMu4xgPrVYP3ZiVqch2/vt0t208WJhEXis0 pyLjt6p7bC3iYePSwuhxbyrSfHZXfd0wHgwjKCN3EqhIJXkpiKQdD6zTDa9H HlLR6RvoubB6PPjqGthSnlORhG7qTINKPBRGsQ6PNFOR4KmZPbpEPHwYDQ28 20dFe7hlNeZl4iGq4/ua1CgVbfsdFxx8PB7SzSm0JTNURP/p8/Nd4vHAfdbZ fjuZiutx7GuxUDw0hf+dslqhIkpW+F4l3niozWr4V/aDiqZChjVGuONBbP78 d5afVDRiLRrisiMe+FIyY/3XqKhbJaCCgS0eWn4vfd+1SkXNwr1f7zHg+uoM P1mgUlHtFoF9x//Fgf1lJ2LrAhU9W/C89OZnHOj8tFNJmqSi3K43Iebf4uCo WDxv5AcqulOyr/L7Qhz0+XiMM/ZSUSLJeTZ2Og4EP4yICL+mojD3V/v4xuLg j/ra5kYVFfnocWpWv48DVp/XVQ8eU5GT9NVQjf44uLPVtJn/DhUZrrPN3WyJ A7uk05/EcL41Ri14tjfGgUzf8ZxRGyqel3LN/Jo4aLwSQtOpRUVHwgyr+ovi QPTn8MdnIlREy5oXJpYSB9dc1m98GqCgtcUfVa/i4oDt58HCZw0UtNR9Yd4g Ig4+b5oKmxRQ0HAK5XK4Txzc2C61HuFLQcV75Q6MmsfB14SdWd18FPRwI0HL 3TAOaH3+1QmwUVDG5y/hW7TjwJnFq63lBxmF5EQunFSJA++wwn/7usjIK3zk wFuFOIi5PLl9qoaMHOzEta1k4mDD//TMwUdkpC/aX5MoFgfPvbW09gSRkRqb 0KKgUBy4TuxInnQko7Nkb976A/g+fVZUwoSMxMr3R37liIOQeo/fLbJkdDDN tTaANQ48bgi//CVCRlxezYs7GeJgr73vxMBeMtqUtddBP2OBjyWHNfbvEhJo us2ovhwLNldEpIyoS0j14ptag/lYKOgVX/49sYQc+tccrSdjYcwy+oPb0BJK MhY+6PIpForVn9JCxxJ6PqE/4DsYC4ERan9mGpfQ0PXIyMjuWMiWDJz5WrmE fn2rlE1pi4W9o0+uNRcvof1+04uZEAunnIaabubheafjyn5SGwtTWUHdLJlL yDZOWaeyPBZGv87Te91aQjE7PRhfFcXCWbEL4XXJS6j4Xm7t27xY0Ho1yzkc t4R6BAYc32fGwr4U+yMdUUtopYj24NStWEhSXPtBCl9Cu6WOD1CSYoEU2KMl HrqE5F5YRq5HxwK3cun7W8FLyEKZJMsUGgudytemuoOWUNhbWNzhh5/z+yX1 YVygS8064BELxo/6au7h9zs+8eqIOsWCTHw1oyg+b8lGk/GUXSzQUGXmffD3 OJYCa89axAJqq84Ox/Gc9HzmqGEYCx8IDekLOF6jP6O8RlqxkLJyLb4paQkF RGwdsLkYC7e0vLQX05bQw63yka5K+DwnH46mu0uoJd1R1v9MLKjrZIoQD5fQ 7P77i1EnY4GTL/yd+eMlxJrfmZV6NBZ+WPkI85QuIYmj69pZwrEAUSxcN2qW kLeCcW3Vnlg4IiD+tR/X615rjGPTjljIMaTZOfBuCTVequXtZo2Fr/0cDvpj S4jRgjty+k8MZBDGNL2rSyg9aEibcyIG3DhjnBaEyaiWiZHx4McYqBBts7U6 SUajSSdrxd7FQKTINfEjSmQkmJ3Gq9QaA3PkO2cfWZDRc9BedCuMAR6Rs8Eu 98ho+HxoVkBuDBR4uaoMFpLRem+Zdsz9GBD83uZlWkdGiuPba7MTY0DAp/Nr 5QgZ9dH0RPTciIH8M6TYGW4KIiuq8R6Ri4EildMZtGkUtG9r7v4SqRhgCu8N Lcf7/sLw733HjsZAmIOCvEQJ5gOHQu6TfDFAqYmqCWqnIJO0LTvkmWLgDXqa x71OwXxnub1xMxp8vOO2dDBSUdXhWvazv6Nh6PULwSM7qIij4RqrylI0TO2I nPiD+aBtuo1eYyAaeumSGqI1qWi1hJeu5200TKY0rkQYUhG/rzeNVms0cAsu CwpaUlEAu/Bf3dpoMCyx9lZwo6Ki94EbQ+X4vA8CcTU+VPQ+Z+i3YXE0mGcn BfYEUdEJ6cg106xo8E7O/9wXT0WWNJ9XP9+OBhXxm49fpOD92Xny+5WUaFDO zWBVuk1F9ekJ3ybiokH8QLuAbSYVzVlMU20iomH3+Ii0QA4V7RaVp8wERoOm 28/qgHzMR9/Tlq75RMP+G5zynoVU5P5ycWHeLRrOSD2KYnlGRdnRyvOODtGw x7c6UKGMirq078+SbaLhfEb+0R0VVLTO833G1TwaDmfSv4nE+1rkq9r0N4No cNeifZBZQ0UGZbmTHlrR8NOIJGRYR0URfuvjPy5Gw7E1uZXqeioqV9H54qMc DWtlznUvX1DR2Laiz7/loyF9Ol/NuYGKtn6gHfWXjoZz6d9T3mAsl2f88a9k NKjvsrrVg/E15/KRYNFoGI+194jAOF2G5T2tYDSotSRZLeLzmmmthsL3R8M/ 89giRoyX39a+Y9wdDYUfsp8O4XgOZHAMRG+PhgZ6vxHzWipSs7TvY2GJhicH N0seVlPRTbFXPfF00RB5f/+rh5VUVLDK3c3+Jwp8xNQKLTFfv2t0fZv8IwoM TPQ4p0qpiCb2TccOahTcS+4uF3v2P58fbE+biwLxlqdn5YqoyOyAT9uuySjw 3+cQzoX5LHa2p+X2J/zcVEq5IY+Kpv2Dmu73REHUnxKPYFy/narDcKA9Cl7u z4t+iPkOcUg0ZjdFQZuAjtm9dCq69+hzfV5lFHRFkZIEsb7Q7pavLL4XBbYe X3U++uJ85OfZaqZHgRyP08/DXpjfA1l3fUuMAsUOxt12uP8sJUa8pEOjIPao R0nNVaxvkj1kmq5FgZhkaR6tLhU9v/Zx1sYqClbmwh9vw/39AyneYTKNgvpf jZQDF3E/L2/7ra4ZBRWrSe3qiIritYvqh09GwRu9KJEDR6ioR3SHo69EFMwl avB7Hcb3obvJs18kCoROiVLGBHD8z88FWPFEQcTErnLKXlz/uKdHGHZFwVe5 +uHbu/D82HB+LtgWBXGcFpLGeP6ecE4oLNFGgfnT4+JiLFS0tHiekrQRCd71 VsHyeF4lW0qyjv+IhPLvrfZOtFRU7Rmw6T0XCZflNEpE8Xyva0yV7p2MhIyR W/J1axREHFKzbPgUCYubxi0O3ymodYi7ibY3EvZ+O3BThkxBW0qCbjxqj4Qh DT5jvQUK0oia4T/fHAknummyMmYpiGShMTD/IhK0DnNv/JumoEHpirCEqkgQ LLu7K2mSgvZs3yclWRoJDB9pIlTGKch0NmSq/0kkmKUx9giMUVAWzKZ55kbC 7dfvnERHKWjytqYKdybG91XfGn2kIGG3qtW6W5EQx/f3XPkIBV2/sD/fLDkS AleqxKXeU9BTvnD9zZhIiBjSfzk2REHLv+YZc8MiIZd6WaJykIJO9mtVqwRE QujPe48q3lHQzcKaq7NekSB1TP70Z6x3GkJ5ueNcI+FVkdCvYxhvGke+OXI9 EhRmC8dL+ilI6cSST691JMRwvZwxwDiKVVfE3SwS+h/SUkQw7pysG+EyiARJ HjQohPG2F3yxNZcjYc+YzjU1jHXSok+bXIyEMzytDncxvuVImf+jhN/fM5Cx A39vRFn/XrZ8JHA7PLnzHOP9+xvUlKQjwU7m1c4AHK/lqsDGtGQkhM9xPHDG 98nrii2OFo0Ezzc6rVH4vl8fLZuKCUZCY4jY9jfDFCQWaLi1e38khHzPWT2K 8+Wi39jguhvn58zRr/UfKOj50UPOOzkiQf7kbnXnTxR0emyl25A+EtyVvL6g LzifZtL/XP9EgGPgrHvSBAXxfvKViPkRAZdY+AcZcX3pRmiSa2cjgMM5eKvj PAV5GqhA33gEDBw912ewhOMZjKbOfYiAIyrVZ65RcX76t2nt7YoAv2Nb/b79 oCB5LZ2Q460RMLnkQrX/TUElPbfKLjZGgOJdAx2avxSU+nb/Dr+yCFg+db03 loGKTFrFBj6mR8DhPt/qSS68f5Vd6L4nRoAOvPxyEs8L0Vx+gi06AkgyEycy D1CRAMimnfGNgGBbj1uPMD8t1qrqZZpHAM/KlK7HaTyvT62HzYUjICwz0f4F 5iOKWAGT98EISDx3S6/UDu+DwnnppD0RUBTP/fqhA+aHArfbjawRIHjKw8rb E+/jh0FGB6nh4OD57EBrNBUF8TbHyMyFg+/t3vBAvH+WMxnrLk+Eg8vv7wYi mJ8G7ybsDXkXDvoj/Ie07lHRg7R7H8drwiHSKIevrRjz6c4x1t9l4cBV4xtG xfszjMR/ZkdROFwcjPlEi/ft1cQn9xUzw+HOrznTz3h/j7AtvTW+FQ662h+S HwHe13GSf24khcPiEAxqYf8gEV1tlhsSDhFaO3j0O6noIeN6Qr1vOBwtoAso 7sb7J0Lh5YB7OFDIxs+msJ9aC2k5QG8XDtkT+vVrw1Rkv8msyWMRDhN8jJf7 sF/5GKgeJGUYDreFHYRjsd9q9BsYs7kYDq1nKckZE5iPzhAmK0rhYCt4we31 FN43G4VDIfLhsFeABQ1gP3aiYZf2dulw4JnsqWyepaKSgNCuB5LhsOphlZY+ T0ViCuTzR0TDofh2Wf75Rcwvf41e1wuEg8TOx/BpCdezsYW4uD8cHj9ybdSi UFFW0LH697vCQYxfIKYA+699KPPU1e3hoEa/yPZ5mYoyNpnLV7eEg9YzsuLq N3zfVx5HwunCIZZbWHwJ+7+kkC+Pd/wJg4Bun/6W71TEqqgu+PBHGOxSdD4f hP1dFG1NlgQ1DIwzJJ/swf6Qrllg38u5MLh+JZw7HePAsKRb6pNhIKEd2LSM 8S+ldY6Pn8KgtDfqowT2i570VxPsh8Jgq41AtibGy6/7mX/2hIF9/RtdLYyd IhTCI9vDwCBjXuUkxnMqhf84m8MgNsS1bR2fZ8u4yy/3RRhcejIq9Qjj8daQ H8eqwqCykWX5GMZmUUtuUBIGr2YHbXNwvCOqRkuXnoTB+WwJ+jV8Hz3mlmuj OWGQWElSksS4743klMP9MLg4LZlzCd9fI+a+xe90HN+gVZ42zk/7BeaP0Ulh sHy+9N0ZnD8VFg/93TFhYHHvevNWnF/5ODUNKf8wOLb8UNYO16NWrfpNk2cY WKPtf8jY755kE1DWcgmDMzEOP67geh5J+H3a2QrnI+efNN1XzFcadlUbJmHA Pf50XGqaioTY+4/F6YUBsac2TBv74/1JTw4/Ph8GMHXsge4Y9seaXHmnFMOg K/B1+mncb1zbQ3hb5MLgIK9l2LaPeP5IhrsmjoYBR+hN85ghKtpIYaLn4QqD E0+mrgy8pSJvHfegQvYw6FlsRKodVLSyc+y3DHMYKN+JCS9to6KFtKplvfVQ +L4eEGXXhPv7lu1Y0ngouF2+XuuN9U793eY6umeh8CJ4Nf5rNq4HDVsVU0Eo JMk++zWM9cj2a7plrNmhEFz4VrPzLn5+crpgZ0oonP5Oe/tlGhWx9zKmC3iF QvbH8C/LeD/UntJMFnYJhUOGtms7I6nIOjMjTuxaKMTE/tBAYXherh8OPWEc CtzeD9jrA/D+YbjooqQQClcNXtNruuP+dEy5riqNf+9BsRxxxXq8/4OtmmQo cH5a2OPhjJ9nO5jq8IeCWa6B7Kg9FVUyVhgY7AsFK4mFL8VYz1xx2tA24QwF zyh56yRb/Px0wgVrxlBg4991PAnvP4uHg8pX/4XAaPmZuKcWVMTCfAA5/AwB Qfrz77+Y4eeDz065z4cAp/X2A9HGVLTlzNox78kQ0PX+sbSB9f3zHOKI36cQ sKqkvRJtQEXMrr0CYd0h8NAzLGHqf/00xM0b1RYC03Iec5U6uH/lLfdidw7/ 8rUOZ2lTEVPeE66k2hCwo98Sk61FRWUs37anlofAb7VKpbrLeP+7nWbLKAoB eopXzCLWX4zvQ5nu5YVADltsuDTGZQqdtFmZIVCqbWF47xJ+/9HOvzm3QkDl njMfN8YMbKa/8pNCIC/WZPWpBhWV3sj7XhgdgvUS86QpxiYji5RnISHw40/0 N0GMGdDJhXLfEGBjOCzEiHFJfsBMlXsIRCvEe26qU5HR1tbxOkd8nvGt4Z34 OZ0H++hL2xAoZCmWQRg/+6D/vsk8BASko4IiMDY6mzXQahACXXb28ZP/v//4 a3fHZZy/BWFZYxzfU3bJju4LIcBxTtJoDmMDT5+WfsUQ0BK/V5uM70fzCWBI LgTOrmjzXcb5KFbc8uKDVAg4HabREsb5MniiVf35SAj0CKvS7cL5pNl+t3zi EI73SOPiPpzvIq+JpzO8IcDDz/1CBtdDf1T0yTx3CJzMkdrrqIefF9ZnfWPB 9f+YsIUL11OPg/7eD7oQEC852htjREX/yBli338GA2vB4+SdJlT0OKaWm340 GHTfph61Mcd+x/2au0ZPMCQf6svku4Ln3XR3961XwSDgfMl5GfdXkYRnmEh+ MDgHSEu24v4rGZQkX3IJBlXjq1Incf9KNo6dv20ZDGV7H3d44f4ue5yYO64T DPDszeXWG7h//BYNPWSCQT/ycVG8N54XvsfNd2jw9yZszfNCqEiG1eDA5EoQ cD5nv6wUjuftO8NN8Zkg0PJXH5vH81bfZn20sSMI5i01f1/G/vGlE++dqdQg eJf5qNAmg4paam85SxwKgj/n4hAN9ivnclXafbiDII2D80Mv5uO2+O8CTSxB sJjM//c+9jvtFtojupRAmP+Q3CuM/dJbBnZl35pASKQ9IfWtGe9XyosHzYWB MEvzvTK5FeuV9w6/2DIDwbO6o1SoHfuBovZnWSGB4NjRIiiJ+XhAK2JPy8VA WN/8wfAc86+unJQHu3wg7D9Jo7I8gvWD4GS3gUQg/KCrszz4iYqG11D4/M5A eJHDnXnpCxUZjlM+n2AMhL05Mz7qmI9HOh7IBvwMAOrNv8UymI8/ZG6Qt40G wIXQbU0jeB+bRBVdMOoJAEk/haCEObz/XI3zcl4FwJbMMI0jeJ+bGm/5t/A8 AM4vfnxUg/l4VKnG6GR+ABQ/nmGQIFOR+ZGrFYG3A2BynpGahPl4bNeubW9i A0BvT/DCB8wX43Pur41dAuCtjY76Ecw3ngbulclWAeDUuTjFj/mIpeVGfqte AKweZ/lJh/kr6/iNjI3zAdAZayrTi/GJbLfo42cCoGm63zQK892brW43r0kE wKe88IMimC/N/FyvP+APgMYTnxUr/+fXWReTd1wBcGkzN0rsJxVF6ruos2wJ gBG1zao4jPe9dpZHG/7AmxqROYhxyTHno14UfzAmKbJt+UVFyllOvMUT/vAh Z+q90K//9ZXT9olBf5BoDR4Vw9jJ15GGu90flNgmfu7FmHbW4ZvGC3+gtbRh X8HnZeg5TIaV+MPF7D8MFRiLNV9/V5vjD15MVm/NMG6UvN5CSfeHigcD2lQc r+4D+yqhGH+w5DVPcvif/1ntC0z8/aGt4K5/D75vwM1rt0ku/sBAT9nDgzHH 16sxbVb+EOKp7qCF85Ove9X3j54/bLG3uOmC8ynXZOdw4oI//GMO0vLC+e6R sDO1P4Pv257OYPftf76x1ciS8IfCS6LFCpjff7LYKgzy+4N9ldGVTVw/vhnr g2e3+MO7vgIPAvN7lY41h/eGHzC1kvgacD+ovbKifUrxAyfdbE9BzO8e9y2n uIf8wIL/4Ggp1ndbWCwHL7X7waKv5ZUh3G+Z3ldaw1/4Qayp5PUZ3I9t2haP qTl+0DKgytv2mYr2bDFzfOPiB+nRypqpg3j/eZma/bXyAyT/SoRrgIoUp0wu Sen7gVbUIbbwXipyaDSWzD7jB0u/J11EsZ5t8DT87r3FD+Su5B981EhFWpMG 0083fKG6LjfxLtbHM5cNhiYpviBeTXc1GM/nNnH9Gs0hX2jYvI948fxaTej4 C+f6QkFpbXT1I8w/mpr0w2d8oaJhl3A75utfzMyra0d94TTzqnIZ3ifzTTDN zecLNdZi8qRgPM+njrcZM/hC4Q9ukPOhotQDXLGfu25CQsgji8uYb3nJH7bN mN+EvVOfdwmq4Po9Tt1k1LoJ6noModMI94+V+rKw0k2olvtHU3SGiqYHG/rt hW9CpqwwUpHC+7IhO32J4gMtPX1WnQJUJJ1gt2812AfK7nx600CP960qL9su dx8wqLFZ2kVDRXtp3m+csvUBOec29aA/FPTH48Jnnws+4JpGLxmM/VazqfjD DQ4feHirkkFnjoIqd02T9tP7QEdzQcqpGQrK780MVfjhDfd3nqccwX49Rnmb TfAHbxC9+IbPGPtxTfFvh+hzvSH95cfpSuxfz84U7hZK9wZ+ptVQlV4KOp5t zXwuyhsuv1DPXeyiIC7OwbkoB29Yf7Djb2g7BTF1J3x4bOYN5WMFP260UdDP qHOd7ZreMPK3muzXQkEf16uLWaW84VyUiviHVxTUVemaKX7IG6pefGOXBAp6 6SKSqMHtDZLnVcWyX2K/KDIR6MziDf4X1FpEGyjo4eRdl6QNL9BjqOXprcf+ MVPnSinZC/h0VxyT6ygowoBNq++LF1Rw7VtyqKUgb46Ws9/6vWC6e6nHqoaC rnUGHN/Z4gWBb1uUPKspyGlLVO3BGi+o8WxMKq2iIHfVZHS0yAv2abMK0GPs E3GnTe6BF7hP0u9xraSggOacSxdIXvCx/EHM9woKCqUpHtQP9wIt5ZAYEsZR RKWpjbcX5MqPiqhiHB/wctLtuhcIXYv34cKYVN92PcjMC+JKtgVvPKegW796 l+Mve0FUtKPq//ie9Aefu0peULyg28+J33/oOfmv4BS+zwcevnMY5z9fjKwU 8YKunnTJZIyLlle3NvN4gc854vc3jMsk/qX1bvOCiQ05D2ccb5UTM89nWi+4 pHiERIvvU1/Ekbuw6gk/L1mhEoxhbq/or1lPyKDvdvLA+WgRFixj/OQJP77N 0WjjfHXaHpHh7PGEhfPD46o4n725pxr5mjyBWeQaRQ/ne3CcOCdR6QkX81aZ /XE9PvJe6Drz2BOKr8VuqXtBQdP3TD4aJHpC+aDivoBGCpofsbGyDfEEfaaa Phpcf8pu57kbHp7AfY6uLrOJgn6nBq8lGHvCWYI4t7eVgv71xQTe0/CEN5mS nr9xPzFsT2V4gjzB/N3gAhX327b4RztfH/KE7Ttu5vB2UxBnx7O7fXs8YdUn VMcA9+se5hq+MTZPeHLU4Wge7mfB8A6J3988QMSBkc9/mIJk/Slqko0ecEqB O3LfBAUp1P3sly/3gD9vKYdXpihI6SeNsdojD9i9Q0Bw9CsFXfLgvGYX5wG0 YushM0sUZO0oG37fwAO+9Lv3NP3G/VWoyFp40QNIXnIKfH9xf82qpVTLe4Cd zaRPIp5fHxvz7H4BDzj2+bxhKjMVJZiGvWCmukOU9ZKFzG68j9W7vntEu8My 7di8xym8P4eT/Jx83WFqVPj50Gkq8rPUprVzdIfRPRbqBEFFhNfwNoPL7qCw qvOK7zzev1njorLc7kBvMfSNE+v3kW+rV/4U3ICMf50Cv7DfkAuo+bp65wY8 Y03tswnF+5vJz5kcdwOS3ud9acf6yZJn02/M5QYsj4kW+yfhfajCkvFK+gYc ECnvdMT+aP32ga6INjf4FkxvX4P3sZnAuE5grRtkzg9V6GA91Pg094NXkRvk T3d9+4D1UFjT4dmrSfj9f0dECrvw/lNfcL4SgnHp3F0q3veqw09XDd3doKK0 cZn3HRWxLR6nu2jgBhvmnTanPlCRi9dqjOIFNwiSY+biwf6wb7N6u5wcxpx1 /V+xf0znkj8gzot/P3G5/Sj2m2tZ//IEOdxA2Opw1WOsf4xEm8T207lBl1Eh NyPmM9mABLd9Xa5wd8Xh/TWsb/6QdgSxlbnCrGUYuxPWM6/yM+L/pLnCj/MX Hf/3yxH1PHfJPq4QyT93nRvz78XehwVjpq7Qt78i+iXm523Thyp7kStoFmVf UMb8PvCrqOmVoCsIOzFJP/lfL7Af6y1ndgV3d8Yvi1hPmAhUjeYuuoCsUeQI +zrmDxm5hbReF3jSoPqSfYOKJtXhZ0SFC4iy75JYxLjAUoXR+7YL2HC/78// Q0WOXh07r/m7wO5t9/QV/lLRsThNPqMrLoBQiVM5xqtZ745eVHYBodquPtp/ WB9XGJ2RO+wCgZ5sShIYB7R/viDO5gK0Q6zR0hjf2ZXNm011holJF2UejKus LVd3DjrDRe3KtlF83kApf2dUrTPoJEmS/TCm/JnMXs90hhVR9bs/cDysao+8 XEKdIbW2oUID48O37dQn7Zxh93iEeAiOX2VamN9AzRnujkz/SMb3tTw+t9Yh 4QyjnL7bAn7jeIIKuxQ4nSHY94CPCs7P3bcOueU/ncCMui4zj/NZvefIzUOj TnA1L+eKA9ZHA3bkS3dfOUFf2hBdO64H5XmJIHu+Exx+WSxPh/UQG43b75BY JwjLuy6x9/+/b9xbeWSv4wSdp3aMfcb61nK2wm9U2gnWryX8jcf9EHjSS0uL xwmmWLbf4Z7F3+v5uSEz7Qg59Nwq7VjPDPDU9Re3O0LtatAsGfcb1d7v8cFn jrDjaYroCtbnIvR/dZi9HSE3wpp8ewh/T6tRxN/EET6OHZGUw/rG6kHwPwrh CBc1fJIbeqjongxd0TCzI3z/sXjN5g0VbXVipi246wBWshrNqjX4vLr24b1B DmDR58PzE+uXc0xxTxOtHeBT7+/k+BIqCnq41chL3AH4dk4L2uRjPTy4o1Tl 5XWwqdmpN/b/3x8V9ptPjdvD9zsukplYnyzHfT5h2GoPLrfWG0exP2Mfydry ttAeno0x+m81xfPnzl/53N0ezBp6c+Wx36wtEGYLY7CHK87iymvSeD9sP17H J3INHq+j5WgGrPdt0144b7sGjTFSNfH/KEio/sfL+tWrkGEnb5Dwi4Ke2tY3 6zVdBaGEldEovB9f1Cl3xZhchaC/5chzEPODjcGX5QQ7OCw+w9f+iIJ462on FDzswO++7cpCFt6n23im44ztoDq+z3DXXQpaqP0yJyRsB11OD6+HJ1LQOvv1 FSOwhfcvTIWGvSlob60/Y9M3G/gyZa82qk5BZuxjzNtGbOCshrhakyrmT+uz rKaNNrCwo1GlRpGCRNgZt/+IswHrs1xoRAbvf+ukPaJCNsC0qmT6Rwjze83y Pm9WG8jhd9f14aOgV1t1D7xetga3ygsnmfdT0IUabgHzl9ag49Lie42Tgoy2 5oinGFgDO+0wuzQ9BWVa0UuMyVvDVwsWA9tNMhqvtjsmLmgNXQ91PhRtkJG9 ldipVqoVlAR2sYStktHT6gSZncNW0JZd5sT5jYyW2ainrzRYQZz2Nu9GMhn5 VFcQv2OsYCbUo9N6lozq2XYrqrpaQWXkxyqzaTL6Z3lTOU3fCjosgmJuTJBR FJvChaMC+P1WHybyJzLqtMxW89tiBY/Sg+X1PpDRtmraS28olvA2n9/1/TAZ ZVi2aVu9sIRtVIOmEwNklK55Xzci2xIEiv1kxnrJKFXeTf9xuCUcP3mkuLib jEhi5ww7r1nCuqiT+f23ZJS4Z58xWd0SQm75xj/rIKM4JqoJxzFLKBWoc5l8 Q0Yxq6/NpLgs4fdQnrxcGxltbT3+8unyFRDNHhGuaiGjLTmfXq3UXgGRewdN dV+TEUNgZIts6BVgWlCj39VMRptGku1BF6+AVK3+ufVXZLR+8sPblh1XYK5c S5ke4zWO8F7WjxZwr9CB5xiQ0crSkXdauRbQFfdxNqSRjMjtw8MZDhZguZMV frwko7lHIR9HT1hAw1aDiiSMp0PExgQ2zOGq6vl36hiPmw1O2L82B++vN0WP YvxJNmimJN4cYo0SG05gPMwlMr+qaw48OcrJZhgPLPcvye03B/UJ84dFGPd0 +S+HTJtBy7fmhf34+x1PDq22PTWDAj8TuwqMWyJ6f271MoOxJH56FxzvK0vf DR0FMxCeFq7QwPdpkBfcvMNoBsG1wZaXm8ioZk833ZduU/jWoL/ihfPxfNWb 6VCGKZglf1Z/hfNV0sfH6mhhCm6/rmhItJJR0dNO9nJhUwg7KdULON8FMZ47 flJMoCzpebFnOxk9ONu+JzzYBILlk16c7yKjO/vd93ecN4F+3dVYux5c/188 fNs5TMB6kG8uv4+MEspcD99/aAzRT1ItEodwPRP2ik/YG0PFRbsVqREyCrd/ LXH4uDEIru1h//ORjPz4uKUrmoygei9XHnWcjLz/vDr9O9YIcraH++3D/Xpj xEEB6RgBH69Mih3uZ3tSo8rbSUPgPzXIYkohIwOaq7pT9IbAfXjjSO1fMtIZ 3W4o2mUANblk3o+0WH/V1pm4phtA4L97THuZKEjFjd16Q8gA6B2aOha3UdCJ 8Uo3TlV96Gn61DPMj/XhK/ok5RhdCGqMUFbRwPP6lLpwRk8XeFqvzadqU1Du nU/nT/LpgvtoTcmKAQXJ3KigPVSrA+Y5ippTVhRkKWDjxTSnDV5HDI1u3qSg iohms47zWlDrffjTzGMKKk+lM8zapga073zesLLhfer4kSO54CKEpinZyu2g oo/KzzuDiYvwatLrqB03FTH8sCKsXC6AitZLmUJBKjIwbDok1KMKSrt3dAxh f/iHJ2S1MFEZtvbGk3Y7UBFp1bDk3iFlULaLq3vgSkWHuiXt418qwetmm3+c XlSkGfTlkxNZEfaNifzqxH41Z5x4LXnpLBi+PD6omY71gvvR9bOdCDpzNtbl 7mK9JPjZWWCdgP5B38ccWVQ0GymvP2OsACWmUctej7EeVdsQdNwrB0bjap67 67BebUz4YH3pNHCY2l4WeUlF1id4k01CZUFKxbPrYBPWU/sU1y/OS8P3P48S X7ZTkWDSQKniAWn43J7VaY313jY6W7vT2qfg1kXH+4tY703PR/WJ1EnBBHMc R8EwFfWa74niI5+AtVyuzmGs9+r7C8/s4T8B59JYlOax3iPVdRUwxx4DydNc zeWTWN+ZNNT+85WEabuCf1dnqKhb6YsgZeIotLm8sP6D+dtv56H1rnIxeHnC RrZtiYq01s/bNewVBbb30jTrFCoSnnToKw49DK2nz2ZuxfruT0fimfvzh+C9 aHXzX6wfBsrLCuK0hWCA4YZEN9Z3T+6+2+FXJwCaX95n+WE9EhS6FnCdnx/M eOlGGLFeeTJwoq9850EYVavOdcF6Rj/3ZgFpkgcSZeO7KrHeoXVvDHB9vgfE +4cOj2A99EyRQVczbBeUlfXHj2C9ZLxDTfSozk6oDosarML6iq354Ca3yjYQ rV6ZdMV6zNaquHhoihm8xFYymTapqIFGxigtnBZiiuzIvhiLnI1kyVVda9Tl 39fSgXHZX9lWua1Tjc80B3et/f8+p7WA3LsOIp9kO/oP4yRmh+H3P6jEDrmw 3dMY7249kOr24g8hV7/6Jh9jKeXwzPWXDGgqN+K3MsYf835S5XnZ0M28qdpG HI8iXXUOAg70UOnNnt0Y3zrh9taSyolsfs8cU8Pxz1uL/Qg9yI3yvboOmOL7 yadN8+Zd3odq05loL+L7k15nXWgJPoAOy6zRcOH8rPgeqVsx5EOWMRMXGnA+ 96eyaNIv86NU7dEtSlg/qxZ9neSMEURFHC1e+Vj/uTW/9hHiO4QkXx7u+Ir1 X8tKYM45LREkpYP4GbDeo7CaShvMiaIgd9Oycazv9wjKvr0aIo7uTLyQy8T6 z0l3ZTW6TAKFbTyKLsf+4G3VrIqG0DFUm6r7iw37h3FFg2S95WPoofr1V6pY /7GaSAnZxZxA4qZ5ExZY7x38muPirCeFLi9cZ1UYoaKT7hx1Xnwn0Z7+KtG/ g1RkEUe+FFV7ChU+PbL7ENZ75fWPfR7PyaJ3I+/+8gEV/QoJbdtsPY1mRVJT X9dj/3bedJdRnhw61vkz+Hw1FXW+21axxUIe3Wvmk197iv3Akhfl+juERtfP /KHH8xu7PffE7ivKKLzUZUuqExU9Xdlm0tytjKQSfXsLsN7rG/IPdZFXQVfE c/oLsd7bnanf17b3HNrRoLk7SI+KckVYXHwGVVEG3cTQTbxv6hXdCkcuqiGL U9op4diPfhb63BdRq4Yi4+I757Bfpdmi9uvYYXV00y+vX22dglR7BM/HMmig 1ErlpS1kCnpn8n76NFxCGrNfk6P+//+kpw+SLt3TQgP+NmsaWM/FFA/l5fVr oYXZ68Hzt7FeO5BQ83uLNlqMo20gpVCQPM3vsXwfbUSq+RhOF0lBYW0DR//p 6aCBw6EisU54f+tGvS3ZrocqEv+atRMUpF25HqmjrId2R0zebj1NQem7XM+u eeshUwV1oeGT+PwRwyqFMT10R4h6TEoc61Nz0eyup/qo0ZE1bGEP9ueND4zd xvWRW03g62QuCio6uJOLi8sA/Vb24tDgoCDJyfUYU38D9MTtnTfbFgqSu9bl vnDREAkOvA8u+0VGge1njyYFGiL2IJYze39g/hatmj1eboh6zmqwZ2L9dm7p gZnvnv9quu54Kr/4LzMzIYSEVDaRQnk+ViUryiZblL333vPeiyhJUiGEZI8y ykpZSQpl73spM6nf+f5ev9+f75fnOc85n8857+HeB2OQqfO7sr6E9FKbheOY ljEcLQ3SfYv0rqcsdqAlzBgOJ9VXViI91PVwu3xw3hhqWEqfTU0gvzU4TVbK ZQK35ONaBMdWYVjGuPGajgmMf9xUj0L+zXRLSSqr2gSOaopmZX5Cem5UvaSw aALJxlT9msi//agTfjbBYwpdBbnmvEi/7YNYuE5Fm0L+A43zPEjvi8ZiP3XX msJYmOrklZ5VWFLcS3VZNgUaztZMAvIH4o/crh4+bgYDch6hu8g/uJPNUFRf NwNTKc6mMOQvKq2NXxvHmsEzNYK7IPJvm229/n/qzYBA+bV+HvkTOUFlmbxV M3DU36jsRv4lMKZ6VZXfHCSHGbx7kL9pnhMumtc3h1AeU5Yl5H/I1HNtkuLN IdH4TJ4QwirPWY5JNpmDMvZXLBb5pRi6uJFBkjkcXr3wjhzhLqc9gu+Jm9D4 Cu+Zi/wW3Qc3LS6jmxCyU3DBBGFtiRnq14no54zagjII43HGrdavb4KzwB1x MYSH1nqDqH7ehCapfX01hNmvK597ftICIv8czwxC2PhV9ZqWiQU8+ECxOIDw AzaRkrVkCzgrv6lyBT1/wifXPqPFAnouOWZ+Q5hvhIVPbsMC5DZHB1PR/G3l 4r5+O20JG7iNGSu03oL7exlhZpbQ+iSgRg/VY+G327UTOEv4FKEuYY3qJWo+ Q9vZZglvyOylcMjPuTYbv72zZQmRcQsPv6H6GuNuAc0RK2id4De4jPrx+00e z6iEFQRb3TnTh/z1g7Wvu8XqVqAboE3vi/z3hN61Kp1gKyiqfUd/DPn1jkX2 NI17ViDEdunQVeTnX0RMuF2usoJpeUmXrIFVCH7pIoqtWMGw0h5fNsoDdldl aRUOWoMmW+qkNtpvmpN/5mQFraFTamVAAO1HrsPJ+eLm1uBtXr0iMbUK5M9v hAv7W4N72oKN/ewqLCpxW5zMsIaYYoe8xoVVqHMvPnqs1xqO9XydeEdC/q6/ C89w0Qa0ZtozLqF8hDniXQ8a28BRP1ySK8pPJ8mMtSi9beBMgFz7KxoibEjO 0/wpsYG94o/LeHQ+03BUYcvctnA4Y5Az7gQRPuqouPTs2cJbdtcL37WJUDNH q9nBYQdsfX/X4m4Q4WHogFCbjB3YM5ifVTUhgnOZ1Uy9kx18jeGOJ9oRgY4p zOz5NzsY/a3UQhGC+O1D49X4RnvQf520FlhOhDeasqcuBzmAgiCPTSfybzol LRfeZDrApUauF+y8JJig09KTq3SAxb71MxaC//kJm2CRRQfIyD6SNihFAgV1 /CCTkSO8VGMNlL9Kgu5C7oU4T0eo38mzkEF525imcJ8s1RHoaA4u8hogv9XR LPTrrSNIfvv1phPxd5XacuiI9G0YnfLO1vAjgepT3wxdndvQeVqlszEY+RUK 8uLu27eByq/HizOSBOttnMONebfhkqXEHUIyCSSUL4vmMd0Bx2uz113zSNCc N6B0VOQONIY2rZ1+RgItspuGaZfugDSNZn7nc+QX33hFRAffAavA3wM1lcjf KD4ecVy6A+Kqizpq7SQ4/1BsdZLKCbyZbpvydpKg408tuRm/E8Re9GL+2kOC 2caP4trGTmBEupe/MUACb25T1Q4vJ4gbmsq9Poz8b9CsMeCcYLBfKxaP9FNA 4U/UmQ4nSORXTCueQHp5P+5+8aQTzAT6ksci/VXaZSk/se8EczmRm4D02bJO +OuRs84QVRCnoLOI9J6jmpR6zRl86nyo85G+h/opUR10coYfjWeuDiH9zzln JPX7sTNUKvY7fkB+TzRz6pJXszPcvjFCuov8Q8Omi9nKF2covbKifAH5Cw2D XXf7DWdw6IpWbUZ+b7QqOnbikAusS6h850b+xJGNOcdI1AU2fA9SGyG/t+P1 4GX/ZRfoXpsvc0V+Jm7oVOdVGxdI9jo/YoP8DrtM5VhbiAvs/UqPlEF+qCBN 8eeF+y4wsdfW8ANh2Z9dNNVVLjBzfgR3B/mnt3r6xyT6XUCcg5pzAGH9l9+l C5ddgPZ5lxsb8lvTzE7qfDSuIMRYU38WYU/3rZv3BVzB41sgrzTC5P0RXiyY K/ASvvUyIEyQZExIMnGFbf2C3bdovJ3YbQ9RL1eYcuI/Youw1cSk6ftkVyht 50ifRvPpku1VdSpwhXRN3dLLCEul1IjRt7gCTefqw2S0nnszeUdKRl2hssz9 eTVaL9nFpL8av1zBXeo+Wxuqh2O6z/wSgxtUljoIV6J69S9Z9ieecoO+AYpz scjPyalo1IsoucHz1MxkDNU37/7Z/B4TNzjg7BP1Dfntg+u8SXe83MDiUJP3 TdQfd3Vab7oUNxDUi3n9FvXvy6Nf5sUFbsCWX9l2GPk9pe3xSxotbvB3YXhO Dfl75oJKjsRfbmDlceu85RLyv6E6ZHep3cEgflDpygIar7h9w47VHV6/ohLk QP7vy4GycUpxdzjg4mHojvZbUUVkuZqVOxiNyUmyj5DAfGz7CZuLO9z+R/tK A/k75oMu92YC3GE6zpbbCe1vf0ujiOh0dyjLdhn0eE+CK0xiN952uMOZr+xz Ba9J8Fv+8ZWMIXdwuKkZr9FIgjJ79ot2P9zB9qRu3UQt2h/NZCcpf7vD6V4X +W8VJJhzGt5SFfeA+mBrg3P5JIjtDs1uT/eAdbcOeqooEryLHphss/KEHF7j tvvKyC/bpXwudPWE52H0tucV0XlTvfo+OdgT9viB65scOl/krVWG9zwh2nNv 4jzio9CwirilPk/AZU6+MztOgmEL5+C+cU8ou+kmBtwkEMOEPKqWPWEwqRsv gfju659HpqE0XlCnscJ69hAJzgXixFnACzZT6PJX/hEhxURTYFvLC/wp3IpU /hBhRo6GY8zUCxSOvBh/voP4ejuUrMDXC/LtjkiUrROB6O06JF/mBQPDMody Z4hwSV+ki7fJC1ab6rRSJomQIzPXRNHjBfWCxQxpE0TQ+Hmz4MOsFzqnlJvj X4hQ4KYdYH3MG8hv1VUkfSTCvg6t62VRbzBZDbaX6SWCvsQ7G1F5bzi4sbD5 q5sI5KsXtTb1vaHNx5mm9R0RTHp3lL7aeEOn0Uuxj+1EqCipkn3j7g2BlMs+ m61EsLgjdjwh2RvimLhS0l8TofrqAqtrtjf4/7s/RtdMBAbhpwdvFHkDn+OB Gw8biWB70Gr/fI032LryntJsIELDPPdPnrfoebIQx1ZPhMOdI3MHBr1hOEfj yW4tERwL0r/NffeG2eCS/N81SF9irvW/X/UGvPuV5xwIs9vTv6vY8waZy6Wf dauJ4KLWWX+X1gf+MbVdKqgiwtsTUWWBHD5g0cTOyIkwNwU8sTzpA5H72VjB KyJ4Tv3OUpPxAemjn+Z1Ee5urUkWVvaBeFL9YU6E+R57RjBd84HJE+0t/33e 6Bcu4fvL3Ad29JY2/sMfLZfufLnjg/Qk7/l/15+EAstmfx9YNv46rIdwMK+N fn6sD2iYMDsXIjy0f+xqXIYPaEcomB5F8xEZH1V0zvcBQbbRhEKEI5ruSutV +ICk7sx3PbSeLw/0Tp977QMB3RsXOdF6pYIYebh7fcDpMWfIf/WIM+1mJvvq A0/rKfx3/vv8sfqs286cD/Repnf5W4fywOG8D2u/fEB2lE6RB9Vbz5lebJHM F5zah5r0UD8yOn0TJxl9QfToRHNuE3qewNTCKJcvlCxbMFGgfnKHal8ZPO0L Xu/PBoS+IUL+WUHKdmVfMPpyqr6+jQizOJxNo44viEv2swa8JYLQ8u+WV2a+ 4GGynK7TQYTyxwMhT318ge1+yIpCDxGamMK2Y577wosa+ULmISKQ3VkyCK3x heBN2xX/YSKovjOo8m33BQV/l88bI2g9QWIeDuO+cGzS/fipcSKMLIwuqR/2 g1cSGwTbBSJwqV26qszrBzVS1sctltF+fFRRKC/qBw6JckduE9H5MoizE7nk B+t8NY5lG0T42XZ2gj7ADy7NWjsuHkB6wpt3kTLWD84Y+1KZUiF+CqB/8CfN D94cbBAaOUiCf5JTRqulfiCYcnN2A51nhoe4gY8//ODlWi9ZOfIzp/2W3hLU /UGOURhyEZ+Yi+aVcHAGwOfW1hrREBJ43Vl99lEwAA4e2dzZDidB4nOFvJgz AVCtE/mhOZoE9aeHM35poOv/ZEzIIP/BLkgX2hcSADfZVl/VZ5NA3NbIPzYx ALwffclUySWBWv5TT8WsADjf7pLS8hiNzwcOJRUBwLnRlXa/COkHj7du3HQA CM4Y+L+sJsG8WasGthYAxx1EHT7VkeBvNtOlzT8BYNErZbqA+FX86HN5W/ZA yLvM7jnZiuZ3ZEIArgaCblUoHcMHEjzWFz22ZRAIU8Vviov7SFCX7s/xwiYQ tl+bzp4bRPx7mJWBOzgQUi/OV/zH/6pM6ptbZYFAVczFtfSdBKbad0kvGgOB RYSCtIz0wjN5atGuKxB8PnG9/zKN9IwuZGJwMhDEmFTuec6ToPZqz5cEYiB8 FxBkPY78ysd4jiGlvUD4sU32vBrp0x/qys4ytiB4QOHikIf8Cuvlf632/EGQ F/ngwgbSM5EYrSYeiSBwrWaMPIP0TuXt/ZohhSDoOHOX2xjpoQnFfEXilSCQ lFRfdfiJ9E3lbImyfhDYl/T+sEL6GR8R8WzHKggENbRnVJC+Pmr5+KjcJQh0 eW4vMSK/U/OPO/tWYBDIdFsstSL8AbudcSwuCBhvjX63QPo8E1KT+ik9CKIV hd7PIPyniSIhKS8I5j3PvryB9Jz1j26UyosgyOyze1Dy3/ehLuSG7NYHQbBx ZdYKwiqBy34VHQirN9axIz9gUi/n6TAUBLyL8Uf++76V+06MM++PIEi49br7 FMJx54duDa8Egdfh5E0GhHN9+ayTd4PAbCymeQyNV1PtYqZKHQzX7rZpZCL8 YaPB4DdLMFB2NfbIIzwjc1D35fFgmHa0dev8b76eBhqOYsEgP7ThCgizVuar HZcPBkmHNYp8tF6RdRL2+VIwJIbyuZBQfWamo+TzbwQD3V/nv/+9/5v7meOs q3Uw4llFLUFUT+PuEgkFt2A43W5by4XqzdoEwtQhwbB5nrdgF/XnY9nQicHE YLgeJBvdSkL1f+zAm3svGMovVLV5on7+icWxnqsKhobbOpCO/GpNwAkm8rZg EKmTCaBA+8Hdufbgxz40flYvnSXyK7N63/ftl4PBtyDD+ivyvx95JBfuCoRA md4G3c8xNP6h9ilrqRCgf6jD9OErqje50bg4FgKHex2l7iF/XTsfOvjOJAQu m1YFH0D+Ja/yY9MmPgSkV1TuyyC/7qXuSjD4FwKclJXm9VUoL1wgT+ZnDIXY B+RUKy9JsCCeGbvKFQoOnvqZXOWID1hfB8WcC4U5edn7rigvXJ5gvFXtEgo2 bftiB9F55vR+oXBkLBQoMuhxFXEon9xSlp1cDAX1f+FJ/xA/JJsMS77YDgVn OZtOQ5RXDsC+4CXWMFheFvjOh/hliVb7kI9GGOCru06d9yLB0z8/aJWNw+AM 3cmOb+4ksCB5UzLeCgOtcLHjqa4kGPqUs/s0IgxUpNxCee8gv/doZfpTXRhc FW3N+WtNAhsmKfWqd2Gwos4opozyFG2IV2n6YBi411wtTLcggaHpb+/rK2FA 3JX6d9uMBPtdiqNndsOgUKLuMdEEzf9BS+5BinBwePeiMdoY8SkdJcXCoXCg OdZdN4fy2vvWk9VG7OGgUJ6t+kqfBLwBVxw6ecKhnkfwbtoNxA9St4+ePxEO U6lK29HXkX+bT3xfIBwOKkol5Yl6qF6PSkPYpcKh8vDWvye6JHA2/CgZey4c Xl8MPjmA8uEbxrXJzYvh4P5X1IQFYZZ3hzPsVdH1/Y19DjoksA+WuTx8NRzY 7nrWD2gjPpMx2FHTDQfHPD4VXYQZln2LqwzDYZCFjjCthfJT/j1zwZvh8OvS XFcSwpUmDUwZtuEgljRGcxVh6sNjLRR3wiG+z96BG2GTrn1PL/dwCCnU/0OO cGnY8ZPTvuHwOKDy83/fjyY7rzxyPSQcjnV8PfDf96NvEG0S2qLCAU9Qj5ZH uOBZ9AXpxHCkT82Wvgj/Ni9YfYwPh5d6FIQuhLXZuh4dzgqH2YJjzFJovnnv F/UiHoYDyfB4fynCG5H0lOtPwkHmu/AbDK33ioJ4jVVxOAjgIjpmEc5e13Hs rwgHkUrrnseoPsQidy6lWnR/PHuxJ6qnslVab3lzOBAHfoIxqncGR1Xo8bfh 8NPB1Po66sfCx2EpXE847KiVT1ihfl2I3Z762x8OEuWXoqJQP6c2FK5MjIfD 5gNaI0ojpK+l5rvaM+HQK81FaYP2Q7xtaEnzUjiMStp+GkT7RXKw9dDDbdRf WuKTFXMSRCZMtzL8DQcjzurdDLTfPitReQdTRsB1l9rj1/57P7Zc/YvZ4Qg4 xsOlv21Lgr5bdxLfc0TA3wTbtBl75N95ky9e4I0Af6desikHEnQn9+VxiUZA 8le5bHpnpK93DG+PqkVAQArfFr0PCSoE7X4b+kdA7TXfPrUE5O9ln4vphUXA 2ef6NyWRHv++TLTQjI2Al46b5AI4pG+3/dshIwJ4J37ucN9F83uRnCxUEQGc xFordaTH++eqeX/PR0B9hCChoB7NR/237gYxAmrIZRdym9D5N4Eo4iYaX9rQ A/eGBPig7vkpikggS8uc1H9HAsGW8Yr3xyPhk0tEy41+ElwdEJh+dyoS+iNN ZdaQ3rpOORxpEY+EwlLegOBhxFeUPwOqLkTCtak5JyvEZ2NHzpeWqUSCxx8N jhrEd2SngyeKrkYC1QXx9O0JlNevUqs+NIoElg45PgWkv26mmj5ZFpGQLq+i Iz+L+u2ELyTYR4Lj2dNxfEiP64OHR5OcI+E05fAsEfHrRAoXQ6xXJPhc+5T4 BPEvxSNLLDwwEv6ZluYorpBAqOKpe2BEJEixWqs3IX3Wal3M946PBPen2a28 iN89BiWGXXGR8LlUUtXuv/eRpr1obmdGwtwHs0PJSJ8bNurkbR9GAolWwP0u 0ovvVH+dbj6NhLDYktowpCeUHKq5RiWRkMNcpaSB9EZYKL5frzISGNiiXDcQ 1pH/QK5VHwmu8kUvQpBeeWmwyF5uiQSHi0e9ZxG+Z2bkoNQZCY3X/ZRFt/77 vnvOfYWPkcBbq/i/7yNNhUy+PzscCW987fivIUyNO/VXYiwSNo1Fb4khLJrn JCU8HQmUn7rZ59B4ui8rbE4sRUI0tc58EMLebZsZx9Yj4cIebdYqms/9IYVO jp1IyB1uX1NA+PVM2O7hf5Hg9aKxxxatZ3rzrSgDdRQ8XuekcUTrPUhDZ0HN GAXm+zPpV1A9xDmv4cnYoiDVQM6JHNXrunBG22+uKGgfs0+/h/TRT2F0Y4M/ CvgXyY/T/ff7G03e0yShKHjjRC9uhPRy1qUoafpcFDx7EZoYjfpJpvjO00Ex CgrjFm4non5zMUyZLKtGofMxq+mB9oNuMbfQL90okKOL1Z5G+8UpQO6Qn1EU nK7aOu6G9lOsusHW75tRIMzhaDo+ivRjLvUtuVMUFFe6fbJBejlSXVIS6xEF tHdrDgehvP8zuiuNzh9dv6Na6fcR7Y8T5NYsMVFgo5AfzNeF9pulzz7/oyh4 9ySvWaWBBOUSaTPPnkWBkFmtGf6/z3f2y94Ll0YBu+utvc5KNP+chftn6qPg SKD4851ixP9fzM4pD0XBjiDvxQDkl9X0VNysaKLBrP/Cwy++iL/5LA1nGKOh rvNFjoInCQJJQYqObNHw5p+sYJYLOv8p1fTu/NGg2cicpWZHAp4eoaKwC9FQ nFN0Ph3x3/n7l3AUKtHwcV8qYRnx73VHG9849Whw5po7r66O+Iw6Rw1nEA1t zzxfsQLiX5VDk7lu0eB3staQXZwEh1jEugR8o6Hpx5HmKiHknybVywuCo6Fs /muMtSAJrMIiQ8oSoqF576rwMjcJehs3j75+gsbjXcP/oEf+PZHlgEpxNAhW ShNZUR4hN5VceFcRDcfGe89aUpJAbsexBgUJ6OMf2VLeJ8KTs2PXx0eioWci 3MNwjQhFm4txShPRUCnO2eGzSoTSmu2mJzPRcJchlKdqiQg1cqyn76xHg5yx qyZhlgiNu3zmH7bReOXD/WemidDSIEGQ+hsNv1/zvNz4gfLYRY29LboYIKao xs+MEaFv30jK9HAMYA/frLJ8I8Kn1/b2zRwxMMFWknhrlAijYV7ZfLwxwFxc QvYD5bkJpYi+KMEYGFHWWQj7TITpAzjKeZEYIJ++138Z5b+Fthx5jTMxsNNP AbKfiLAaVez64nwMhImQl2uivPhTre4JMxYDrbkfCImDRNim6vjipRYDW00a Oj8HiPCnY4hxRCMGBg+GKEUhfCB+UkVBLwaoL6fXKyJMfZXk99AoBqSzPf7x I0xPt19KZhED3hyxWlIIM7+nm7K1i4EU7ug+R4TZkjk5Ou/EgEqSZMl7hI9q n9IS8YiBh4JUW8bo+bxMZyNS/GKAu/lEw395VqBPuWYtJAbqL05v/ET4NP7a 8o3oGAj3/pD5D61HTO8mX21iDJg5iEadQ+s/w+JkwEWIgcvyY7gsVJ9zQ/6J IVkxoPXoZowAqt+FjNg3Px7GwDXaE7wjX4mgZJCxofo0BmoqGqmrUf0vsecL FxbHQFX7nfHG/37/M1JuQfcyBm5vHZZeRv3SN3nf1d8cA7POaZqtqL8mXKP7 Mm9jIJvJcu4Wys8W3+aks3piYBOrL5ZG+dnxJvnDmyMx8CZotEp+nQguvMyD LeOofy8vG3qh/Oz5/RiN4EwMNNrc/NK3TYRga3mPpbUYGPJMjV/9SwScvfsl P7pYED1cZ5PDhM73qdDAr8yxUEZFp/yRBfHvfFK5IkcsCJTUeh3lIEH+7cKj lIKx0HPaYWLzOPL3LhOreMVYMD5gGXNfGumNj1ZmsXss7K0jd4b8QhU+RPOe XywkVZ911bEkQVJJGVlsaCzwX4siFaDzKzfJ7GSdHAu9NbfGzruRIE1rGDiL YmFkPr4nPIoEjg7Um1TlsUBOXzN0PZ4EEHm++Fc1Gv+lYhRlCglWau+z9bXH gpXiM9VdpO9tgz3dTT2xsNq3FyaL+OXe6l5o8UAsfJcYaVJF/v3SCYvFmO/o +j3GsK5niD8wXK7XXCx0XDkuLof8/k/jlhvWq7FA+7dNyrmUBF1e6wevbcRC 7eUfotYoH+SmCry+uBcLGdczulkRv3k/v+ElQh4HQdes34SjfKH5NlqIkzYO 7Ogf9z9FfCjwvXqcijkODGwV+oJRnt/ZnUv7xR4HTZqjuVSIPz+ycapPHosD tULLcxdRvn8meXX/o2Ac7C8l5B9D/iNYI7CySTQOPuwu0xQifN2+xKFYOg52 TYyeDSMsFD7Gc08ejWf9bbgA4X/ZjIMxSnEw+u8fCyfCn6uxOK8rcSCiLLB9 Co1f2u920VonDmzM7WAA+Z3I5bx1HYM4aNA++JENzc+EerDgonkc0P2SLyVV k0CKn8JcxDYOhKTtGaxeIX29ePYw55042FRv1bSrQP7F0L6DyiMOnnY/2PiN 6vXKIzPol18crK9faBFA9UxM7pSaDI0DztXZrK9PEX8W7sx+jIkD1ViTLP48 EpxrE37QlBwH07gPjNuoX4zjprrF6XFwSyUizBT1c2Y7iepedhx40+wUaCI/ 18DS3BDzOA5S6XR8e9B+wIsT3byK4qB7l4xzJIIEDurHT1qXxwFeiH3NI5AE bKERuIvNcSCfbbGlj/LT0r1KNZG3cdB3En/4EcpPra+mdzneo/5wVisGIb/r unjJ7teXOPBJ5jyzpob6r08nX7wRB/QFdWbUR1H/3S4Qs/biwAV3SfwoIwl8 Ep2fxJDHw48XL0f7yVC/Wz4yWjPHgw/zYduL80QIEk2f4hCLhzK4xeRWQQR1 yhwtnHQ8ZKof4qF9gvhq/GkNtTzCQ99eud0lQllqTeLmpXiQv7FqXRlAhB/r o9JDlvGQ8YBNJEqJCGp1fFGp6fHgodSP13y/CswE4VWq7HgoWC2hft20CuO3 pY1C8uKh7aDEm8tlq+DLrSbq/CIe5o7vKZcTVuF5qMPQ1c546Htym9nJFP3c yF2x9UM8JPI9WD2mvYpyZkCh3Kd4kHBMeHFIaRXGJhODTk/GAxYQPt1+ahWY LpWdoNqLB8vwgpDd7RX4eqw2JfhAAjyg9V0VX12Bwq03279oEuDfZQrVrqkV UCoaeD/FlgBKQkFsyn0rwBjxVdaUOwF0M048FOpA95tMPxrgT4BBZz+B+OYV 8KLf9GqRSICgN5dMW16g+2f2x8/LJsDBbSPXxwUrwNBMrV5+IQFaxPOU6PNW YPTuocpTKgnQ//di+4HsFShw5eTJVU+Au1LtvfEZK+B5hT/2yLUE0JMi53yK WwHgE1lLNkiAeMEjykZJaLxdaVNKczSfD9rvnsWtwJeBC2+DbBLgYh8cSI9e gafFahK/HBNg+wKfpEDkCnhEad+745YA7HuUtwzDVwAzNySf8kkAE5mfmdJh K0Ana+lsEpwAiTHSyfWhKzDC6Pi5PzIBxGn351YRfjrnrqSekABn0quPDaLr 3d8EFL/BJQCBsSjAMWIFFO9Fsp3PROtT2WN7FYXG80gKLctJgPZSrS+vYlfg 89WMhZNPEsA+SdjfOXEFngg8vP7weQJcn33gOZGKxtt71sRWgearyMBAj9Z/ 8VPZqeSaBOAdeqn16/4K0L6oxVM0J0CM5Pc/Wah+n2Nafge2J0DsglX+buEK 5Ft02/3sToDj3SeDOStQ/QmbOhv9CXBjx2WgoX4FJtr55bdGEmD0uPaQwtsV CN7SPrEzkQC2N9yys1B/uYQDGX/PJoCIG0tn37cVqDMr2N5bSQAfhpeBkwsr YJg6OLn/KwEEmER0e7ZWIP2XSM0B8kTgUHEmP3JkFaRPGeVR0CYC+8uD0m4n V6HfOCqRijkRWKpjjxLOrQLD628WtLyJoLbv53vEbBWi45NpDiskgkfbbx3j 0lUQaKxbZ1FOhEyHuiKxtlVoWZ35xqaeCN/qyxjivqzCn+uKFZyGiVC6M+2W Q00En2NEYz7PRJjzdfxZcwudR10uVYGARBhk5w2XDCNCZeRlccHwRKi6edWr IosIxPncA0KpifCBOvqJfxcRblVeK5YsRvPzxtP89/c5KGeDMs68TITr7p13 Fy8iveQoCpWpS4QtJgo2f5THlTQ+Ocq+SQQjzZzXMijvTgST3TjfkQhi0QcV yYL+y8tiivIfEsFUx+xNC9I3rinj0xc+JQL/F2p+40ckqGOLOaz4LRGuMvcy Pkd6ZHTl5R42lQg/pyVFM1+TYCtgfFZpMRFknterkfciPS+l7VdZS4QfyfHB /SMkkP4u26C2nQhjttIhM5Mk6D9s8/Ty30SwKAqpEED50FUtNVWdKgnmHNx9 3FF+YfBr8NdgSALxyU3Tqo3/3q+es9FiTYIRPiGTzyhfqY+xaOtwJcGLIxwM LQjPMcF5Xf4kaDmUQjRH10crO/FfF0oCp/XPadkoTwp4Z9HrSybBk2/yo44o n7YWtG8anEsCiy77kw0ov1iNkr4bKSbBc4vjqVEoP/+l5+kxUUPPv+tM19yO 8hKmXmWmmQQJFvFZ1kh/FTy8c29eTwLBQBVTN6TvX57kxVuaJEFt+af6+TgS +H7u9bS2SoJEP6JHnyvSA9pdc1uHJBAT9ngk8d/7/BdOXrF3TQIqkfw2ZlmU p1z1zjj4JEGchlRTNBsJiHkh3LeDkyBgev11DvJXotSfSc6JSbDkcqTr8DMi VIn8Oq1DSIJRu9Jhx2AiXLzGbCV5LwnadU/Zj+sRQeueRv/6syTItvnAmLu9 Cs4ibyp8W5Pgpleq6G3pVdjQGVsw6koC4a0Ls9F/0Xny2uWT70uCtS7K6KXu FUhukiHsjSXBRPNCOliuQKlOkUf4ThK4K1O49scvw1mvd8+t/yUB/TIj/eaN ZWjKmppUoU4GXTGDpIbjy9D7g+c6FVsyPPVqFuyuXwJ9KoXEOa5kOPMxYd4y fgnGhI3aOvmTgYJhOk/aeAlWPQnSiZLJ4L3+zIzzzyL4ZpXdcTqXDFm5Tx66 9C/C38b3+VqKyfBszUMgqmARYn8sfBVXSwbmLI88n9BFYKKiZj2kmQzpqRPD lsaLkCl8QnNNLxn0tWkcTM8uAq8OsvnGyeB33KUuiGURJLICf6XfSgbWa5uf woYXoKYxS9THJRneKXjcimxYAOxHla2hdzJsnNauX3q8AB2Ugw/OByWDkAgh viVpAXSESUOckclQdPp5No3/AnzWZmD4HZ8Mf9Jbld/cWgALT2G1b7hkkDie +3bSaAHmMi8HN2Umg528eJmt5gK4NdpWPXyYDIXBwf+klRdg53v4SujTZLg3 NKF8Tn4BwilzBa1KkqF1PNxXU2YBDgo3mitXJoPsQvSPy5ILgNf+kiFQnwwc 6GSsiy0Ap+dmL0VLMqz+wFsfRDgvk4VqtiMZOnPvGssjLNQoqdjxIRm6xay+ C4gvQMV3LZ/CT8lALhDqriexAHKUd17Ef0uG1EXBEUU0fotQ3OztqWTopUi4 pYmwuvbTY5qLyVB1acuqA93f79FqILaWDEru52unhBfAOHMihXEb1ZOeQ69R YAF+NOy9I+4nQ+zE2vHrHAvg+J3zbx9lCphJiioRqBdgjeLcuZf0KXCOMSRI mzQP/kI3XNNYUuBlA1mQRv88kGm7F3gdTQHBdfZtpaJ5iPdImdDnSwFVwRae eZ95YM4sZj93OgUkyAIU987Pw72GTh0OiRS4a/OsSnd1Dvi+z8TunE2BQa63 uRMZc1BEQf5m9EIKdK7nN/SJz8EZoePbDSro+TGVPmm1s1BBxzZz8moKzAhf eXfzwixIrB4cwF9Lgegr7/IHX85Aad9+855BCtx7sX/YkHsGRCp/Ft8yT4GG IHL/h/7TUJQxnzVgkwJkTN3/Snum4JTfWPTF2+j+qbGKAZYpELjYYcHimwIF oy6CjUk/II+3UTMkOAUWTsTIngv/DrwHKuQWIlPA0Urgy9XpceDuuM/yGpcC N9iYa58UfkX64NJx+3kK6G9GT/yO+QRp0javPpWnQKi3UYcB7xAwHzHKg5oU GDtcYCXSOQCp25opxU0p0PY1af9WRD8wflUKPNKeAq+2KKLPPPiIzresQ3g3 qleFbQPRqBfoHonoL/elgOn1havTcj1Abccm0TqWAnk3Vv8U2nVA9GVabrHp FOC5T9CSf/EWyIX/0mQtpoBLn+mjsiPtEE7/a+PAWgqE8W8U3s5phX+r85PO W2i9Y7JyNdACof1jH0f+pMDZN2ecS/ea4U/lQKMKRSoc5Q67yV7cCDt+jXc5 mVPhPUvZcAeuFnxNKyKj2FPh5JRpanRLNWxcfOZG5EmFHRZdW0f2KvA8nm1u ciIVgo40NeFTK2H9AO7qW+FUEHihWKB+6iW4z0Sdk5RKhS0uUhdzTTkQO/xP ZJ9LhdKuAyeX9F/AUpLNvptqKkhIyOrG8D8HR1ejpa9XU8E1UoIx6kohzOlq jVzSTQWnR5FCGunPwE5G+W2FYSpwrxDrXx14CtNHzr3kvpkKCksC177h8sFm RyQ31jYVZEq55bguPIYfX48nrd9OBROsfJP8QB6MPaK17/RNhcLVjwpQ9ABM I//qSYekQkb3lbrvDffhi90v7GFUKjw0F/4m+ysLDK8siB5MTIXnVGK6p3Uy YVh4nNMLnwqUuY9UJroyQJ9hkGoiMxWC2R67tFulwyCx46f6w1SQ/kss9mdN g4+vKnp5i1MhnaJNqzoCB1qZz+oTKlKhO8BQLsgtBXr8sws2alKB4eAXluKo JFA3w6VbNqP7V5JUFRoToFMxOrynPRW007Ja7Fnj4TJfgItsTyq0dDxUzk+I hbfkrqZ5/anwM8vx5wPuGGjpNDrrO54KBw5Y+zglRgIzpftjp5lU0Ntql8zU jAArpXgm6+VUkMu0pzMTDIeK4Lwgw5+pILVfcjP/ZCj8q6tb0NxNhXbb96w+ IsGgs9lvoEyGg+vAkvfvRiDknllsO0eDA/IEvTaTR/6AFR99yH8EBzW8cuJH CD6QOneGjoMHBx/6DK59lPaGCQENP4YTOGijdHr6Z8UTJCxtZg6I4MCEO3yp tdkDQh4E6m1L4eDGt9uxDk/coXck7fXKeRwcMBz/Uy3nBjxsJaJTGA7uKqjF Gei4QFPyN6oPWjiQb3n/0/jrbWDo/uXZdgMH0zz/rjBpOYI5FcOPWlMcPPQ/ eYj9yy0oVRbUfmGNg5CytfCEYHvYC7nYkO+Ig6uHe+iLztuBRoP+6XtuOFDR auX6RGML2VvOGSm+OHgzc4gPv2wNCm4PXf2jcTBC++/m035LSCyp/uaShINx l2OVvfs34ev8B3XbNBwUJXP8VlM3BxHBuWrj+zjQdeKhpC8zhUCrvwI6eThY GeqdURE3gZ4cdrxqIQ64DA/PyLw1Aq5RiX25Mhx4WE4WX/IwhHo9y5ETTTiw 4RFd+UOjDwdT/dSOtuPAzxd3d594HYx7cC+ZenBwjlLw0sCcHhRRF/FSDuBQ 3lrksCTqwo5KS9LuCA7oVMMZ8il1QT3syw5xAu271NfbOno6cK9xzX5mFgdO 93KcuF9pgdxZfqW+X+h57Q0HYpuvQrw7YpXfOKg8y7knZasOzp+FGMfJ8BAd rsf4iucKNLEoBw7S4KF9pLHKqkMNZqQ+SGnT44Ebkz5zvUoVGK6ZzHcy4SHg RtD9Jy9VwCzJQ7/5CB5UvCKnaj4rQeTzfTq5o3h4bcfHgtsFKO5MaK3kwcOz xoWfBTcx+E2RL1F0Ag9uB8szuBwvgICAxKzAaTyI8ju0fadXAA2lhgcPRfDA Sy4r59QmB9nBgwfTz+Chetn6dpTtOWjLtnjDKIuH8VmHYBYtWViqW/KJl8ND l0WdzB3Vs6CwST4dAni4c4R15JiZNNiw4u7vqODBdn45lhRwBhLPcOt6XcZD 2uSNEq+nUjDqItPsqI2HZfGtA7syEvDnjqhOkS4eBGQcMuW+iwGv44nv8zfw wL5VfrcpWxTsbFgPOJjioWroIZ8KCEOcJX1awU08DDIQyOtPCUGxOcWJOSs8 2Kuo3LvJfRrWDH+p2TvgIfIsX1iy8Elg1V8efnoHDyNd0b+/KQvCOb3pWzMu eDDMp3OasjsBwZpD8bbeePASOEHa7uKHR+rvjz7xw4N+19hnOlp+aLvUXjwV iIfJvwv4b3p8cFDpVa91BB5GF1jkaHeOgahiyc3H0XiQzTlpL1jPAzoKT4g/ 4vDQ+4/tT2o8N2ScTWe2SsUDDw8NTda1o1B7JunxIwIeGii3NFcvccJXiSjp 7xl4OOkmk0uhzgF8wl76Fg/w8KlrvVrB5QionnKafZiLh0ad2PjrODa4dcLW d/wxHnxK7do4Glmh9NiNe+ZFeChtzlL6Ls4CfVyawjklqN/7qyp03ofhJ4dq w7cyPGjTNqXKtDGDHIvMmGk1HtoyHkizLzGB2SFRl+w6PLjyab5nrWSEUIYT f0cb8UAmTSV1LY4B3lKz8pm04UGkhAPHY0QH8xT0L++9w0OcUvsTnC4t0B2g UPnShYcw+3+/DhgcBN29n7ZGfXgwMgj+TgqmBq+dpY3MQTxoGkfKhj+igszN qZjPw3iUp1eeyr2nhDHSYKHBGB4WHW88ib1IAY4zlcs3FtF+kTvCYxVMBkmT xcHpK3gwkRrcK2r8h5VN5DMOkfCQ8v4Pu3nSX2zjS5rk9S08sEwfIqzr/ME4 Pie2EHbR/n7lzdGrvIcpDEXqDfxB/fgwWmoFv7HwD55euhQEuJhB0Fkw3sGe 9NyhxFMT4NnGgSIy722so9Pmbh8tAZ60d588dm8LY2i7XqvDjH7eejxicncD y6qR3tM6RoCeNHPavaM/sTKxEzLBfAT4fR7TKvVdxzryWZ1KThBgYsGLM350 DdtK3fhKK0IA9XqpI7HWJIyJapZFXpwA3xuUsw2uErFTQcMajlIEIGz2ncy5 sIoZOtQ0dJwjQFHfNGlOcRlzHS/4uSlPgFsDnysFtJew2BtZIicVCdAdUsOh Zr+I1YB/dpQqAXbZZT8Mlc1j7JwKgUq6BKAR9xiTzZ3BJFJFKt1uEJAfZSAj LE9jlym5l3INCRBTO2FqC9OY79qeyb45AahWW33cdyex1FsrBDErAnQKhbDI WE5iBWNj3Wa2BCALf+kY3PMD+9zVLN9wmwAeN5Zos62/Y0SszGPRmQD4gDOq 44YTGHV17nNOdwIohzCNZBqMY+cehx318yUA+3kXZnLXb9jdAOVdmSgCmE9L yaQd+IKVks6csY0lgFzJk8ZL8iPYW3uB22kJBGAwyjFc9/uMbehRjK7hCJD7 x6RKhHYYY+j6xcyXTgDOxLWpC2afMEFsRv1aJgGeMzyr0Xw1hOmLvKt7kYPq qbHMEu89iDnnVa+NPSLAzHE7Z43xASyavUCI4QkBPpGd/XJOcwCrIo+7d+c5 AdTWOr36ZPsxtm/q/qdrCGBsE19pHtmLienJVxjWE+BXrtV6e857TK1TeCGm iQDvmnUZJ173YN6v6Ixn2ghQfFnuHNvRbixZeA/H2kEAOwbb0BLdLuzpo+VO lW4CvG7MnVhO7cQ+JfWef9xHgHUaM+YA3g5s5UCzW/8gqgfFWyp9t3cYpf+L wn/DBKgJusm38e4tdtYulcNijAAvyh/01ES1Y+kXdbe5Fglg6Hyj8vDFVizD 8robbgX1D296OK+4BcuI1J+nWCPA7QKr5+q8LVhml/HIyhYBzt4v97wm9BrL XDa9Zv2bABwnO/cpxZqxLKabncP7aL65EcQwuSbsnr517WvKNBiIFIgKudOA 3fezlZQ5mAbKAg7rtrh6LDvbvrCQPg3UBX0oRhrrsAc/bmfhWdJgvL3vj4ZI LZbr7Olnw5cGLH7VP/UNq7BHOG/S5xNpoGi8dNe34hWWV+nroHk6DXT6+7Zl mV9hj3cCjc5KpAG3NpN16/eXWD53SF/RmTTo5KyZFr2GMBZ25ZhsGlQ/PUbm 0V6BPY2OOk99MQ1+vaAxrfUqx54VxpQHQhq8KD1iYeZXhhX0xJ0mqaTBn+5D VLeiXmCFzMkcX66mQfzyXefIVyVYcU7G9nOjNMil39U651yElbzJdOM1S4NQ luVp45JCrHTq3nyaRRoIMkXK964VYC+EHo4E2aeB9SO+8o6UZ1iZ5qNra45o /IHByumZp1iZ6+NOO+c0YC93owxRfopVVD2r1fZKg1Xjc9z2dE+wipFCyTbf NLAsfWdu7JuPvfz9vPBcYBo8TfRcZJ5/jFUqlWUdj0iD/TsqeWKf87Dq3hq/ 9dQ0KMriDKj+8BCrIdWR7NPSgJ9cvcZzMQerYWl0+Ho3DXoz6EpdGHKwOuM3 Ru05aUARVPH1pEM2VhfU2nc+Lw2SFpP4XXLvY/W57VdKn6RB5GThPtXYPaxh pvP83WK0Xq+mT4a3s7BGmp5y2rI0kBu6n1FUl4k1ifSeDn2ZBo1h9qFhjJlY s3s/h0NdGlgIq12h6MzAWv582ZbrSAOqckXvYu80rOnvZQ3P7jSQd1i96bxB wOrIqnNKetPgy7qX3oQfASunJCjzDqXBVHCyj1UCHstluJpE8QP10+Pi2+nC FCybqXb84nQaPEmrN4waS8YymU9K+c6lgeSr/h/z7MlYCtuB4YWVNIjNilu9 lpOIBfPU837cTQOzAMm0o7NxmD/vaQ+a/TRwpOIh3FCNw7z57rYrkaXDBYkt EltBLOYk6OH4ijod+B/J3n7mH4OZiglX3mNNh1V+X3yoThRmKJFFOcieDv9o Lgk5f4jErktRGdFzpYNZYk/X0rVITOPs5F4IXzqsc5OJnrGMwOQv3r9kK54O P1aFHAzUw7CzGM29HKl0mG/u13wbEIpJKfksDcukA56uonu4IgQTUtPDqSuk Q7SlydsLksEYpxbtqPiVdJBloPn9yTEAY9PxE3XQSIfJWn7Rw+3+GLPubEie djocl//49C2/P0aj3yrAqp8OvtxiocwrvtiWWYDzDspFdx2WHy9UeGM/b86/ PmOXDpHfpi7HiHpjREuDw04O6fBcZLe57LkXNmt7pmbcJR2+l/0oU6nwxD45 Lf5rC0yHp0PePoPT7li/i9H1PyHpIJGznSjj7471ur17KhuRDp7tDGy3D7lj 7V6PrxbFpcN0xPF2imRXrDLIJD0lIx1qOL5F1Txxwo5V/5w8dS8dqFyCrhZM 3sHiiUlSLQ9Qve1zF86evINZWr/+8DM/HULWVrjCmxwxhisnDhq/TIccsy0O o9O3ML/wJsP1qnRgVfXcaEixx6bqDZ4l1qXDsLMpW9SOHVYvFq/S/Ab1A9fQ U//VFrvFshos8DEd/t40Oa7z0Rob0Ix93ziQDtg17dsm+tbYxZjjXAbD6RBU dOjE53ErjHVHrzZuLB0C/Y/6+G1aYi3jNesrS+lQvWEYwPHKHBPj0FWKJaaD /rHUyh9rZliW7mLq8Z/pQO8qIMZ21gxzbecWu76bDsTljNecPSYY9/PwW7U0 GSD8pL/eXcoIi506Wq1LnwFvAsjMze8aYj+5X1EsMWXAaS3ZgpS/BlhX6mwe D3sGHPzzXUN1XB/z9db4FiGYAd4FR62au65jky+mhbmFMqDT/+/BNK3rmNZ8 sH+VaAZk6tvNdg7pYSdMy4/MS2fAP/4Ops1lXawf2HS1lDNgqI1d/H6EDnYh 4EXurFoGKEWGvlNo0MYKKi+vhqpngOu0Ubr8jhYWcjIg8eW1DDD4ub73KkoT E6GfeMtukQEUyxujTz6pY3fV/FgrrDOAKahbWOysOkYWymxz1T4DqFkvX9jN uoKNrKn8C3LOgDUi6+N5p8uYisiY9hH3DJiZrPP++O0SVmbrk1PmlQHN1flf o69dwo4+ZFq+4pcBdvxlj0kdatj//T96+P//R/8/zqNHlg== "]]}, Annotation[#, "Charting`Private`Tag$979050#1"]& ]}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{True, True}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{False, False}, {False, False}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}, {Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{ "DefaultBoundaryStyle" -> Automatic, "DefaultMeshStyle" -> AbsolutePointSize[6], "ScalingFunctions" -> None, "CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotRange->{All, All}, PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]], "Output", CellChangeTimes->{3.8133872003971567`*^9}, CellLabel->"Out[20]=",ExpressionUUID->"f902dacc-93e9-481a-b84f-d1efa9f28d1d"] }, Open ]], Cell[BoxData[ RowBox[{"\[IndentingNewLine]", "\[IndentingNewLine]", RowBox[{"(*", RowBox[{ RowBox[{"for", " ", "simplicity"}], ",", " ", RowBox[{ "we", " ", "hardcode", " ", "the", " ", "some", " ", "additional", " ", "sampling", " ", "points", " ", "manually", " ", "by", " ", "throwing", " ", "40", " ", "points", " ", "over", " ", "the", " ", "interval", " ", "plotted", " ", "above"}]}], "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{ RowBox[{"entprod", "[", RowBox[{ "\[Beta]_", ",", "V_", ",", "tl_", ",", "tr_", ",", "\[Epsilon]0_", ",", "t0_", ",", "\[Epsilon]vec_", ",", "\[Tau]vec_"}], "]"}], ":=", RowBox[{"Module", "[", RowBox[{ RowBox[{"{", RowBox[{"ret", ",", "cur"}], "}"}], ",", "\[IndentingNewLine]", RowBox[{ RowBox[{"cur", "=", RowBox[{"NIntegrate", "[", RowBox[{ RowBox[{ RowBox[{ RowBox[{"transmissionchain", "[", RowBox[{ "tl", ",", "tr", ",", "\[Epsilon]0", ",", "t0", ",", "\[Epsilon]vec", ",", "\[Tau]vec", ",", "w"}], "]"}], "/", RowBox[{"(", RowBox[{"2", " ", "Pi"}], ")"}]}], "*", RowBox[{"(", RowBox[{ RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"+", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}], "-", RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"-", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}]}], ")"}]}], ",", RowBox[{"Join", "[", RowBox[{ RowBox[{"{", RowBox[{"w", ",", RowBox[{"\[Epsilon]0", "-", RowBox[{"2", "t0"}]}]}], "}"}], ",", RowBox[{"Table", "[", RowBox[{"x", ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{"-", "0.02"}], ",", RowBox[{"+", "0.02"}], ",", "0.001"}], "}"}]}], "]"}], ",", RowBox[{"{", RowBox[{"\[Epsilon]0", "+", RowBox[{"2", " ", "t0"}]}], "}"}]}], "]"}], ",", RowBox[{"MaxRecursion", "\[Rule]", "20"}]}], "]"}]}], ";", "\[IndentingNewLine]", RowBox[{"\[Beta]", " ", "cur", " ", "V"}]}]}], "\[IndentingNewLine]", "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"uncrel", "[", RowBox[{ "\[Beta]_", ",", "V_", ",", "tl_", ",", "tr_", ",", "\[Epsilon]0_", ",", "t0_", ",", "\[Epsilon]vec_", ",", "\[Tau]vec_"}], "]"}], ":=", RowBox[{"Module", "[", RowBox[{ RowBox[{"{", RowBox[{"ret", ",", "cur", ",", "noise"}], "}"}], ",", "\[IndentingNewLine]", RowBox[{ RowBox[{"cur", "=", RowBox[{"NIntegrate", "[", RowBox[{ RowBox[{ RowBox[{ RowBox[{"transmissionchain", "[", RowBox[{ "tl", ",", "tr", ",", "\[Epsilon]0", ",", "t0", ",", "\[Epsilon]vec", ",", "\[Tau]vec", ",", "w"}], "]"}], "/", RowBox[{"(", RowBox[{"2", " ", "Pi"}], ")"}]}], "*", RowBox[{"(", RowBox[{ RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"+", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}], "-", RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"-", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}]}], ")"}]}], ",", RowBox[{"Join", "[", RowBox[{ RowBox[{"{", RowBox[{"w", ",", RowBox[{"\[Epsilon]0", "-", RowBox[{"2", "t0"}]}]}], "}"}], ",", RowBox[{"Table", "[", RowBox[{"x", ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{"-", "0.02"}], ",", RowBox[{"+", "0.02"}], ",", "0.001"}], "}"}]}], "]"}], ",", RowBox[{"{", RowBox[{"\[Epsilon]0", "+", RowBox[{"2", " ", "t0"}]}], "}"}]}], "]"}], ",", RowBox[{"MaxRecursion", "\[Rule]", "20"}]}], "]"}]}], ";", "\[IndentingNewLine]", RowBox[{"noise", "=", " ", RowBox[{ RowBox[{"NIntegrate", "[", RowBox[{ RowBox[{ RowBox[{ RowBox[{"transmissionchain", "[", RowBox[{ "tl", ",", "tr", ",", "\[Epsilon]0", ",", "t0", ",", "\[Epsilon]vec", ",", "\[Tau]vec", ",", "w"}], "]"}], "/", RowBox[{"(", RowBox[{"2", " ", "Pi"}], ")"}]}], "*", RowBox[{"(", RowBox[{ RowBox[{ RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"+", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}], "*", RowBox[{"(", RowBox[{"1", "-", RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"+", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}]}], ")"}]}], "+", RowBox[{ RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"-", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}], "*", RowBox[{"(", RowBox[{"1", "-", RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"-", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}]}], ")"}]}]}], ")"}]}], ",", RowBox[{"Join", "[", RowBox[{ RowBox[{"{", RowBox[{"w", ",", RowBox[{"\[Epsilon]0", "-", RowBox[{"2", "t0"}]}]}], "}"}], ",", RowBox[{"Table", "[", RowBox[{"x", ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{"-", "0.02"}], ",", RowBox[{"+", "0.02"}], ",", "0.001"}], "}"}]}], "]"}], ",", RowBox[{"{", RowBox[{"\[Epsilon]0", "+", RowBox[{"2", " ", "t0"}]}], "}"}]}], "]"}], ",", RowBox[{"MaxRecursion", "\[Rule]", "20"}]}], "]"}], "+", RowBox[{"NIntegrate", "[", RowBox[{ RowBox[{ RowBox[{"transmissionchain", "[", RowBox[{ "tl", ",", "tr", ",", "\[Epsilon]0", ",", "t0", ",", "\[Epsilon]vec", ",", "\[Tau]vec", ",", "w"}], "]"}], "*", RowBox[{ RowBox[{"(", RowBox[{"1", "-", RowBox[{"transmissionchain", "[", RowBox[{ "tl", ",", "tr", ",", "\[Epsilon]0", ",", "t0", ",", "\[Epsilon]vec", ",", "\[Tau]vec", ",", "w"}], "]"}]}], ")"}], "/", RowBox[{"(", RowBox[{"2", " ", "Pi"}], ")"}]}], "*", RowBox[{ RowBox[{"(", RowBox[{ RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"+", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}], "-", RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"-", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}]}], ")"}], "^", "2"}]}], ",", RowBox[{"Join", "[", RowBox[{ RowBox[{"{", RowBox[{"w", ",", RowBox[{"\[Epsilon]0", "-", RowBox[{"2", "t0"}]}]}], "}"}], ",", RowBox[{"Table", "[", RowBox[{"x", ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{"-", "0.02"}], ",", RowBox[{"+", "0.02"}], ",", "0.001"}], "}"}]}], "]"}], ",", RowBox[{"{", RowBox[{"\[Epsilon]0", "+", RowBox[{"2", " ", "t0"}]}], "}"}]}], "]"}], ",", RowBox[{"MaxRecursion", "\[Rule]", "20"}]}], "]"}]}]}], ";", "\[IndentingNewLine]", RowBox[{"\[Beta]", " ", "V", " ", RowBox[{"noise", "/", "cur"}]}]}]}], "\[IndentingNewLine]", "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"uncrelid", "[", RowBox[{"\[Beta]_", ",", "V_", ",", "wmin_", ",", "wmax_"}], "]"}], ":=", RowBox[{"Module", "[", RowBox[{ RowBox[{"{", RowBox[{"ret", ",", "cur", ",", "noise"}], "}"}], ",", "\[IndentingNewLine]", RowBox[{ RowBox[{"cur", "=", RowBox[{"NIntegrate", "[", RowBox[{ RowBox[{ RowBox[{"1.", "/", RowBox[{"(", RowBox[{"2", " ", "Pi"}], ")"}]}], "*", RowBox[{"(", RowBox[{ RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"+", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}], "-", RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"-", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}]}], ")"}]}], ",", RowBox[{"{", RowBox[{"w", ",", "wmin", ",", "wmax"}], "}"}], ",", RowBox[{"MaxRecursion", "\[Rule]", "20"}]}], "]"}]}], ";", "\[IndentingNewLine]", RowBox[{"noise", "=", " ", RowBox[{"NIntegrate", "[", RowBox[{ RowBox[{ RowBox[{"1.", "/", RowBox[{"(", RowBox[{"2", " ", "Pi"}], ")"}]}], "*", RowBox[{"(", RowBox[{ RowBox[{ RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"+", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}], "*", RowBox[{"(", RowBox[{"1", "-", RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"+", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}]}], ")"}]}], "+", RowBox[{ RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"-", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}], "*", RowBox[{"(", RowBox[{"1", "-", RowBox[{"1", "/", RowBox[{"(", RowBox[{ RowBox[{"Exp", "[", RowBox[{"\[Beta]", RowBox[{"(", RowBox[{"w", "-", RowBox[{"(", RowBox[{ RowBox[{"-", "V"}], "/", "2"}], ")"}]}], ")"}]}], "]"}], "+", "1"}], ")"}]}]}], ")"}]}]}], ")"}]}], ",", RowBox[{"{", RowBox[{"w", ",", "wmin", ",", "wmax"}], "}"}], ",", RowBox[{"MaxRecursion", "\[Rule]", "20"}]}], "]"}]}], ";", "\[IndentingNewLine]", RowBox[{"\[Beta]", " ", "V", " ", RowBox[{"noise", "/", "cur"}]}]}]}], "\[IndentingNewLine]", "]"}]}], ";"}]}]}]], "Input", CellChangeTimes->{{3.741399000773799*^9, 3.7413992118646317`*^9}, { 3.741399247265094*^9, 3.741399356680442*^9}, {3.741399386993614*^9, 3.7413994211363564`*^9}, {3.741399612032144*^9, 3.741399630405959*^9}, { 3.7413997083320103`*^9, 3.7413997282559853`*^9}, {3.741399776336993*^9, 3.741399887402698*^9}, {3.7414001232986*^9, 3.741400221120504*^9}, { 3.741400319319743*^9, 3.741400401835511*^9}, {3.741400436150742*^9, 3.7414004636022243`*^9}, {3.7414006487892714`*^9, 3.741400651752099*^9}, { 3.7414009054128113`*^9, 3.741400909223486*^9}, {3.741403158336048*^9, 3.741403168693706*^9}, {3.741403255313004*^9, 3.741403293053425*^9}, { 3.741403505510769*^9, 3.741403507292301*^9}, 3.74140398766269*^9, { 3.741404037602809*^9, 3.7414040486158113`*^9}, {3.741404340425055*^9, 3.741404340510391*^9}, {3.741404488992735*^9, 3.741404495558049*^9}, { 3.741405314350218*^9, 3.741405330054545*^9}, {3.741405409859784*^9, 3.7414054146892853`*^9}, {3.74141409390038*^9, 3.741414120871573*^9}, { 3.741414161504464*^9, 3.741414266528366*^9}, {3.741414373712119*^9, 3.741414402072097*^9}, {3.741414480687353*^9, 3.741414537063621*^9}, { 3.741414590833652*^9, 3.741414624542634*^9}, {3.741414683600891*^9, 3.741414793195939*^9}, {3.74141491092715*^9, 3.741414911517025*^9}, { 3.741415070350471*^9, 3.741415070628324*^9}, {3.741415233827322*^9, 3.741415247216281*^9}, {3.74141549661854*^9, 3.741415528878632*^9}, { 3.741415824967671*^9, 3.741415833765435*^9}, {3.7414183852248363`*^9, 3.741418448231412*^9}, {3.741418665944347*^9, 3.741418734477927*^9}, { 3.741419109828761*^9, 3.741419143779109*^9}, {3.741419711713408*^9, 3.741419715584497*^9}, {3.741419785844281*^9, 3.741419788528838*^9}, { 3.74141982208923*^9, 3.741419865425785*^9}, {3.741484690478331*^9, 3.741484711400423*^9}, {3.741484842214473*^9, 3.741484844040276*^9}, { 3.741486447652164*^9, 3.7414864529791183`*^9}, {3.775476660761258*^9, 3.77547669159341*^9}, {3.775476727783059*^9, 3.775476737134575*^9}, { 3.7754767734128447`*^9, 3.775476783158518*^9}, {3.7754913434529247`*^9, 3.775491361891247*^9}, {3.775491399303211*^9, 3.775491453049204*^9}, 3.7754914872369633`*^9, {3.775491584511034*^9, 3.7754916679380407`*^9}, { 3.775491743324073*^9, 3.775491811050045*^9}, {3.775491846327732*^9, 3.7754919469594517`*^9}, {3.775491987880679*^9, 3.775492096334772*^9}, { 3.775492143320347*^9, 3.7754921456367273`*^9}, {3.775492219197735*^9, 3.775492256994869*^9}, {3.775492305844977*^9, 3.775492309259933*^9}, { 3.775492343991362*^9, 3.7754923660912933`*^9}, {3.775492398045282*^9, 3.775492400893779*^9}, {3.7754924407472887`*^9, 3.775492486879077*^9}, { 3.7755281750033407`*^9, 3.775528202475025*^9}, {3.77552826076967*^9, 3.7755282646099787`*^9}, {3.775528308455035*^9, 3.7755283831014442`*^9}, { 3.7755284481324377`*^9, 3.7755284563298903`*^9}, {3.775529059716078*^9, 3.775529073877391*^9}, {3.775530857606963*^9, 3.775530953751676*^9}, { 3.7755310533676643`*^9, 3.775531138321248*^9}, {3.775531179073814*^9, 3.7755312323737173`*^9}, {3.775531265524177*^9, 3.775531441237535*^9}, { 3.775533804253027*^9, 3.7755338733611593`*^9}, {3.775534897098913*^9, 3.7755348977062693`*^9}, {3.775534927799266*^9, 3.775534949955924*^9}, { 3.775534985158752*^9, 3.775534988306843*^9}, {3.7755352571274652`*^9, 3.7755352603792*^9}, {3.775535484125352*^9, 3.775535514249139*^9}, { 3.775548052102312*^9, 3.775548057531993*^9}, {3.775549947077388*^9, 3.7755499521578207`*^9}, {3.775556569220346*^9, 3.775556575395039*^9}, { 3.775556659086998*^9, 3.775556681226671*^9}, {3.775557170283599*^9, 3.775557198588031*^9}, {3.775557454310219*^9, 3.775557459161366*^9}, { 3.7755577780581083`*^9, 3.7755577868022747`*^9}, {3.775639375215246*^9, 3.775639504231311*^9}, {3.775639550278245*^9, 3.775639611402252*^9}, { 3.775639659496326*^9, 3.775639798895458*^9}, {3.7756402615085697`*^9, 3.7756402618567657`*^9}, {3.7756403577462482`*^9, 3.7756403584699917`*^9}, {3.775808625343927*^9, 3.775808652818988*^9}, { 3.775808683054881*^9, 3.7758088067220182`*^9}, {3.7758088640703297`*^9, 3.775808864193536*^9}, {3.775823137491633*^9, 3.7758231712198467`*^9}, { 3.775823242898649*^9, 3.7758232675115747`*^9}, {3.7758324709105377`*^9, 3.775832474020175*^9}, {3.775832612224766*^9, 3.7758326140697737`*^9}, { 3.775832678399241*^9, 3.77583274608634*^9}, {3.775832839435981*^9, 3.7758328578206673`*^9}, {3.7758737496254187`*^9, 3.775873752381505*^9}, { 3.775873826697558*^9, 3.775873828583634*^9}, {3.775888090459485*^9, 3.7758881854600163`*^9}, {3.775892061593099*^9, 3.775892070601062*^9}, { 3.7758943556358347`*^9, 3.775894402509877*^9}, {3.775894744116366*^9, 3.775894749025321*^9}, {3.7759088335403967`*^9, 3.775908845707205*^9}, { 3.7759088994909782`*^9, 3.775908904918255*^9}, {3.77595928117833*^9, 3.77595929191107*^9}, 3.77595936857132*^9, {3.775959446149539*^9, 3.775959524724196*^9}, {3.775959586151182*^9, 3.7759595862817507`*^9}, { 3.775959683619676*^9, 3.775959686985086*^9}, {3.775959735341753*^9, 3.7759597374606447`*^9}, {3.77613221361793*^9, 3.776132274563534*^9}, { 3.776132342534336*^9, 3.7761324829164886`*^9}, 3.776132544102717*^9, 3.77838175269458*^9, {3.7783818609706097`*^9, 3.778381910053507*^9}, { 3.7783819416712017`*^9, 3.77838208520471*^9}, {3.778382156737095*^9, 3.778382173395859*^9}, {3.778382465738529*^9, 3.7783827158234673`*^9}, { 3.7783837046431932`*^9, 3.778383879582621*^9}, {3.778383929381536*^9, 3.778384139405056*^9}, 3.7783849812203903`*^9, 3.778385054596054*^9, { 3.77838513027026*^9, 3.778385137117569*^9}, {3.778385569166342*^9, 3.778385610493721*^9}, {3.778386074079629*^9, 3.778386088032878*^9}, { 3.778386196863307*^9, 3.778386207681836*^9}, {3.778386703953154*^9, 3.7783868703019543`*^9}, {3.7783870376425333`*^9, 3.778387042883621*^9}, { 3.778387103550248*^9, 3.778387183141417*^9}, {3.7783873210270777`*^9, 3.778387414396179*^9}, {3.778387470213356*^9, 3.7783874742571573`*^9}, { 3.778387664823515*^9, 3.7783876747481937`*^9}, {3.778914781179606*^9, 3.7789148254858828`*^9}, {3.7789148656226387`*^9, 3.778914870854496*^9}, 3.7789149091837053`*^9, {3.77891493961561*^9, 3.778915092491601*^9}, { 3.7789181159150543`*^9, 3.7789182053721733`*^9}, {3.778918278603237*^9, 3.778918297451068*^9}, {3.778918380759494*^9, 3.778918397161456*^9}, { 3.7789277515144033`*^9, 3.778927790332883*^9}, {3.778927822314761*^9, 3.77892789787184*^9}, {3.778927929220806*^9, 3.778928006547934*^9}, { 3.778928095446528*^9, 3.778928176264041*^9}, {3.7789283113635073`*^9, 3.778928321170567*^9}, {3.778928357442027*^9, 3.778928403595484*^9}, { 3.778928722892103*^9, 3.778928868816072*^9}, {3.7789289360588713`*^9, 3.7789289436165733`*^9}, {3.778929195837963*^9, 3.778929199038453*^9}, { 3.7789920808040447`*^9, 3.77899218816278*^9}, {3.7789922826010857`*^9, 3.778992304861311*^9}, {3.778992343513769*^9, 3.7789926443567343`*^9}, { 3.778992798129435*^9, 3.778992900368164*^9}, {3.778992941497724*^9, 3.778993012201408*^9}, {3.778993064677774*^9, 3.778993065266224*^9}, { 3.7789930982215967`*^9, 3.778993127480955*^9}, {3.7789938879022837`*^9, 3.7789939813555717`*^9}, {3.7789940161852837`*^9, 3.778994017100397*^9}, { 3.7789940806455917`*^9, 3.7789940815726547`*^9}, {3.778994249723433*^9, 3.7789942721371603`*^9}, {3.778994315270116*^9, 3.7789943177033587`*^9}, { 3.778994371567761*^9, 3.778994389827325*^9}, {3.778994462887651*^9, 3.7789945244315567`*^9}, {3.7789946046703453`*^9, 3.778994607018485*^9}, { 3.778996388029747*^9, 3.778996433666307*^9}, {3.778996464028112*^9, 3.778996514236106*^9}, {3.77899667029469*^9, 3.778996683178014*^9}, { 3.7789967968532457`*^9, 3.778996800873588*^9}, {3.778996864739649*^9, 3.7789968729383287`*^9}, {3.778997105754201*^9, 3.778997107978217*^9}, { 3.778997351011883*^9, 3.778997359739008*^9}, {3.778997427011182*^9, 3.778997427505829*^9}, {3.77899827982336*^9, 3.7789982799347277`*^9}, { 3.778999054781885*^9, 3.778999060989085*^9}, {3.778999110428919*^9, 3.778999176518248*^9}, {3.778999212718878*^9, 3.7789992318704453`*^9}, { 3.806905322367742*^9, 3.806905358135169*^9}, {3.8069059957590647`*^9, 3.806906131142159*^9}, {3.806906209588202*^9, 3.806906248252055*^9}, { 3.80690628489338*^9, 3.806906332581408*^9}, 3.806906393986281*^9, 3.806907013598888*^9, 3.806907113759864*^9, 3.806907271774782*^9, 3.806907482551235*^9, {3.80691351466539*^9, 3.806913696934181*^9}, { 3.806913729835767*^9, 3.806913854143488*^9}, {3.806913976864106*^9, 3.8069139851736383`*^9}, {3.80698516474431*^9, 3.80698518171346*^9}, { 3.8069862340813923`*^9, 3.806986246409711*^9}, {3.8081929623839006`*^9, 3.8081930135046597`*^9}, {3.808193045489153*^9, 3.808193126505465*^9}, { 3.8133861794513197`*^9, 3.813386180949646*^9}, {3.813387312056724*^9, 3.813387326037409*^9}, {3.813387360605673*^9, 3.813387474250001*^9}, { 3.813388272869897*^9, 3.8133882853630247`*^9}, {3.8133883164308977`*^9, 3.813388331998171*^9}, {3.813390489306218*^9, 3.8133904986403227`*^9}, 3.813390606177122*^9, {3.813390652353413*^9, 3.8133906969767942`*^9}, { 3.813390733528467*^9, 3.813390743637507*^9}, {3.8134039501764507`*^9, 3.813403954638276*^9}, {3.821857231189453*^9, 3.821857322915674*^9}, 3.821857360234686*^9}, CellLabel->"In[17]:=",ExpressionUUID->"573ba7d8-4cdf-4004-b0e2-aa13225400f3"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Export", "[", RowBox[{"\"\\"", ",", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "V", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.0099609897622874`", ",", "0.03163361777640106`", ",", "1.066290253346536`", ",", "0.4286598205548415`", ",", "1.1612881965805946`", ",", "3.0474653711824247`", ",", "3.0474653711824247`", ",", "1.1612881965805946`", ",", "0.4286598205548415`", ",", "1.066290253346536`", ",", "0.03163361777640106`", ",", "0.0099609897622874`"}], "}"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30"}], ",", RowBox[{"+", "30"}], ",", "0.2"}], "}"}]}], "]"}], ",", "V"}], "]"}]}], "]"}]], "Input", CellChangeTimes->{ 3.8220233616606503`*^9, {3.8223110674183064`*^9, 3.822311087887403*^9}}, CellLabel->"In[20]:=",ExpressionUUID->"45037692-087d-436c-a3e0-d11cdc17253c"], Cell[BoxData[ TemplateBox[{ "NIntegrate","izero", "\"Integral and error estimates are 0 on all integration subregions. Try \ increasing the value of the MinRecursion option. If value of integral may be \ 0, specify a finite value for the AccuracyGoal option.\"",2,20,13, 16321148811635565211,"Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.822024540245204*^9, 3.822311844821748*^9}, CellLabel-> "During evaluation of \ In[20]:=",ExpressionUUID->"560e08e9-f028-44b7-8f06-83ccf5ff0e89"], Cell[BoxData[ TemplateBox[{ "NIntegrate","izero", "\"Integral and error estimates are 0 on all integration subregions. Try \ increasing the value of the MinRecursion option. If value of integral may be \ 0, specify a finite value for the AccuracyGoal option.\"",2,20,14, 16321148811635565211,"Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.822024540245204*^9, 3.822311846131835*^9}, CellLabel-> "During evaluation of \ In[20]:=",ExpressionUUID->"d4855474-b1a3-4bdc-8089-3b04aecdaa43"], Cell[BoxData[ TemplateBox[{ "Power","infy", "\"Infinite expression \\!\\(\\*FractionBox[\\\"1\\\", \\\"0.`\\\"]\\) \ encountered.\"",2,20,15,16321148811635565211,"Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.822024540245204*^9, 3.822311846137973*^9}, CellLabel-> "During evaluation of \ In[20]:=",ExpressionUUID->"e1a6fb3d-0ec2-451c-b1c1-e435176f0de3"], Cell[BoxData[ TemplateBox[{ "Infinity","indet", "\"Indeterminate expression \\!\\(\\*RowBox[{\\\"0.`\\\", \\\" \\\", \ \\\"ComplexInfinity\\\"}]\\) encountered.\"",2,20,16,16321148811635565211, "Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.822024540245204*^9, 3.822311846143895*^9}, CellLabel-> "During evaluation of \ In[20]:=",ExpressionUUID->"cc45334f-6a4b-4382-bff9-ae7b9b0c0dad"], Cell[BoxData["\<\"test.dat\"\>"], "Output", CellChangeTimes->{3.822025715148944*^9, 3.822312614567958*^9}, CellLabel->"Out[20]=",ExpressionUUID->"c261e3d2-c12d-415e-b8f0-22fe857d05b8"] }, Closed]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Export", "[", RowBox[{"\"\\"", ",", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "V", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007269560988958051", ",", "0.007238948047382406", ",", "0.007238948047382406", ",", "0.007269560988958051", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30"}], ",", RowBox[{"+", "30"}], ",", "0.2"}], "}"}]}], "]"}], ",", "V"}], "]"}]}], "]"}]], "Input", CellChangeTimes->{{3.82185391273317*^9, 3.821853993824554*^9}, { 3.821855385963361*^9, 3.821855398893317*^9}, {3.821855932402298*^9, 3.821855950270746*^9}, {3.821856456315846*^9, 3.8218564748139563`*^9}}, CellLabel->"In[34]:=",ExpressionUUID->"2a97de18-a149-4199-8706-4ace0c232c6d"], Cell[BoxData[ TemplateBox[{ "NIntegrate","izero", "\"Integral and error estimates are 0 on all integration subregions. Try \ increasing the value of the MinRecursion option. If value of integral may be \ 0, specify a finite value for the AccuracyGoal option.\"",2,34,13, 16318320008530930714,"Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.8218542349088707`*^9, 3.821855654278162*^9, 3.821856166851078*^9, 3.821857448840424*^9}, CellLabel-> "During evaluation of \ In[34]:=",ExpressionUUID->"10cb7338-ff70-42c8-b796-fbbc3ac4ae73"], Cell[BoxData[ TemplateBox[{ "NIntegrate","izero", "\"Integral and error estimates are 0 on all integration subregions. Try \ increasing the value of the MinRecursion option. If value of integral may be \ 0, specify a finite value for the AccuracyGoal option.\"",2,34,14, 16318320008530930714,"Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.8218542349088707`*^9, 3.821855654278162*^9, 3.821856166851078*^9, 3.821857450434534*^9}, CellLabel-> "During evaluation of \ In[34]:=",ExpressionUUID->"cf8f1728-1eae-46c3-8ae5-e28058c98744"], Cell[BoxData[ TemplateBox[{ "Power","infy", "\"Infinite expression \\!\\(\\*FractionBox[\\\"1\\\", \\\"0.`\\\"]\\) \ encountered.\"",2,34,15,16318320008530930714,"Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.8218542349088707`*^9, 3.821855654278162*^9, 3.821856166851078*^9, 3.821857450440131*^9}, CellLabel-> "During evaluation of \ In[34]:=",ExpressionUUID->"c734c845-b7e2-4472-a6f5-6c50ccd462cb"], Cell[BoxData[ TemplateBox[{ "Infinity","indet", "\"Indeterminate expression \\!\\(\\*RowBox[{\\\"0.`\\\", \\\" \\\", \ \\\"ComplexInfinity\\\"}]\\) encountered.\"",2,34,16,16318320008530930714, "Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.8218542349088707`*^9, 3.821855654278162*^9, 3.821856166851078*^9, 3.82185745044551*^9}, CellLabel-> "During evaluation of \ In[34]:=",ExpressionUUID->"4d311d1b-f793-4b3d-a744-18ae8803d99a"], Cell[BoxData["\<\"test.dat\"\>"], "Output", CellChangeTimes->{3.821853936206032*^9, 3.821853985077752*^9, 3.8218544774559526`*^9, 3.821855915760283*^9, 3.821856387596072*^9, 3.821858429141879*^9}, CellLabel->"Out[34]=",ExpressionUUID->"808790eb-7a63-4854-857a-4803f7a0d804"] }, Closed]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Export", "[", RowBox[{"\"\\"", ",", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrelid", "[", RowBox[{"1.", ",", "V", ",", RowBox[{"-", "0.015"}], ",", RowBox[{"+", "0.015"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30"}], ",", RowBox[{"+", "30"}], ",", "0.1"}], "}"}]}], "]"}], ",", "V"}], "]"}]}], "]"}]], "Input", CellChangeTimes->{{3.821857378652828*^9, 3.8218574464598627`*^9}}, CellLabel->"In[38]:=",ExpressionUUID->"09b89b6f-9070-4862-90dd-e551471b903b"], Cell[BoxData[ TemplateBox[{ "NIntegrate","izero", "\"Integral and error estimates are 0 on all integration subregions. Try \ increasing the value of the MinRecursion option. If value of integral may be \ 0, specify a finite value for the AccuracyGoal option.\"",2,38,17, 16318320008530930714,"Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.8218591455740137`*^9}, CellLabel-> "During evaluation of \ In[38]:=",ExpressionUUID->"43b67acd-6da8-4180-9eec-18bd9f579d1a"], Cell[BoxData[ TemplateBox[{ "Power","infy", "\"Infinite expression \\!\\(\\*FractionBox[\\\"1\\\", \\\"0.`\\\"]\\) \ encountered.\"",2,38,18,16318320008530930714,"Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.821859145579172*^9}, CellLabel-> "During evaluation of \ In[38]:=",ExpressionUUID->"dd04e3e7-7dc3-4271-923c-228e09fd07f5"], Cell[BoxData[ TemplateBox[{ "Infinity","indet", "\"Indeterminate expression \\!\\(\\*RowBox[{\\\"0.`\\\", \\\" \\\", \ \\\"ComplexInfinity\\\"}]\\) encountered.\"",2,38,19,16318320008530930714, "Local"}, "MessageTemplate"]], "Message", "MSG", CellChangeTimes->{3.8218591455840597`*^9}, CellLabel-> "During evaluation of \ In[38]:=",ExpressionUUID->"2fd07e79-1ab5-432d-8bb4-fd9bd06c4a5d"], Cell[BoxData["\<\"test.dat\"\>"], "Output", CellChangeTimes->{3.821859147026663*^9}, CellLabel->"Out[38]=",ExpressionUUID->"d4bec91f-7889-4770-a6bc-5d17d5bedc59"] }, Closed]], Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{ RowBox[{ RowBox[{ "we", " ", "do", " ", "not", " ", "exactly", " ", "have", " ", "the", " ", "wideband", " ", "limit", " ", "with", " ", "\[CapitalGamma]", RowBox[{"(", "\[Omega]", ")"}]}], " ", "=", " ", RowBox[{"2", " ", RowBox[{ RowBox[{"\[Tau]", "^", "2"}], "/", "\[Tau]0"}], " ", RowBox[{"Sqrt", "[", RowBox[{"1", "-", RowBox[{ RowBox[{ RowBox[{"(", RowBox[{"\[Omega]", "-", "\[Epsilon]0"}], ")"}], "^", "2"}], "/", RowBox[{"(", RowBox[{"4", " ", RowBox[{"\[Tau]0", "^", "2"}]}], ")"}]}]}], "]"}], " ", "but", " ", "for", " ", "large", " ", "\[Tau]0", " ", "it", " ", "works"}]}], ",", " ", RowBox[{ RowBox[{ "which", " ", "roughly", " ", "corresponds", " ", "to", " ", "\[Beta]", " ", "\[CapitalGamma]"}], " ", "=", " ", "1.0"}]}], " ", "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"tab1", "=", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "V", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", "0.", "}"}], ",", RowBox[{"{", "}"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30.001"}], ",", RowBox[{"+", "30"}], ",", "1."}], "}"}]}], "]"}], ",", "V"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"tab3", "=", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "V", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{"0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{"0.009999959154289148`", ",", "0.009999959154289148`"}], "}"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30.001"}], ",", RowBox[{"+", "30"}], ",", "1."}], "}"}]}], "]"}], ",", "V"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"tab5", "=", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "V", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{"0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30.001"}], ",", RowBox[{"+", "30"}], ",", "1."}], "}"}]}], "]"}], ",", "V"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"tab7", "=", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "V", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30.001"}], ",", RowBox[{"+", "30"}], ",", "1."}], "}"}]}], "]"}], ",", "V"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"tab9", "=", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "V", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30.001"}], ",", RowBox[{"+", "30"}], ",", "1."}], "}"}]}], "]"}], ",", "V"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"tab11", "=", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "V", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007269560988958051", ",", "0.007269560988958051", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30.001"}], ",", RowBox[{"+", "30"}], ",", "1."}], "}"}]}], "]"}], ",", "V"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"tab13", "=", RowBox[{"Monitor", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{"V", ",", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "V", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007269560988958051", ",", "0.007238948047382406", ",", "0.007238948047382406", ",", "0.007269560988958051", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"V", ",", RowBox[{"-", "30.001"}], ",", RowBox[{"+", "30"}], ",", "1."}], "}"}]}], "]"}], ",", "V"}], "]"}]}], ";"}], "\[IndentingNewLine]"}]}]], "Input", CellChangeTimes->{{3.806913987325574*^9, 3.806914085073751*^9}, { 3.8069204992163467`*^9, 3.806920500902422*^9}, {3.806920830158525*^9, 3.806920840703759*^9}, {3.8069208996469927`*^9, 3.806920956366558*^9}, { 3.806983813627509*^9, 3.806983834820455*^9}, {3.8069839096085777`*^9, 3.8069839795131407`*^9}, {3.8069840545952387`*^9, 3.8069840670550137`*^9}, { 3.80698410048223*^9, 3.806984103368228*^9}, {3.806984527067987*^9, 3.8069845550517282`*^9}, {3.8133862260537033`*^9, 3.8133863184577427`*^9}, { 3.813387485602544*^9, 3.8133875526416693`*^9}, {3.813404502223351*^9, 3.813404600433907*^9}, {3.813404631838293*^9, 3.813404635609602*^9}, { 3.813404702549706*^9, 3.8134047370593567`*^9}}, CellLabel->"In[69]:=",ExpressionUUID->"8de30f42-77e7-41a5-ab87-15425c69aba1"], Cell[BoxData[{ RowBox[{ RowBox[{"tabor1", "=", RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"-", "30"}], ",", "1"}], "}"}], ",", RowBox[{"{", RowBox[{ RowBox[{"+", "30"}], ",", "1"}], "}"}]}], "}"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"tabor2", "=", RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"-", "30"}], ",", "2"}], "}"}], ",", RowBox[{"{", RowBox[{ RowBox[{"+", "30"}], ",", "2"}], "}"}]}], "}"}]}], ";"}]}], "Input", CellChangeTimes->{{3.8069845581773853`*^9, 3.806984585983239*^9}}, CellLabel->"In[32]:=",ExpressionUUID->"54261a7b-424d-415f-bca0-90c93c4115d3"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"ListPlot", "[", RowBox[{ RowBox[{"{", RowBox[{ "tab1", ",", "tab3", ",", "tab5", ",", "tab7", ",", "tab9", ",", "tab11", ",", "tab13", ",", "tabor1", ",", "tabor2"}], "}"}], ",", RowBox[{"Joined", "\[Rule]", "True"}], ",", RowBox[{"PlotRange", "\[Rule]", RowBox[{"{", RowBox[{"0", ",", "3"}], "}"}]}], ",", RowBox[{"PlotLabels", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\""}], "}"}]}]}], "]"}]], "Input", CellChangeTimes->{{3.8069140873302517`*^9, 3.806914089644253*^9}, { 3.806920461185422*^9, 3.806920471339512*^9}, {3.806920971448783*^9, 3.806920980256905*^9}, {3.8069838565693007`*^9, 3.806983857685369*^9}, { 3.806984574710742*^9, 3.8069845785329523`*^9}, {3.813388402113594*^9, 3.813388406017151*^9}, {3.813388933288951*^9, 3.813388959555901*^9}, { 3.813396923404004*^9, 3.813396923786726*^9}}, CellLabel->"In[76]:=",ExpressionUUID->"a5a76b0b-0d22-462a-833a-ac51784db1d9"], Cell[BoxData[ GraphicsBox[{{}, {{}, {}, {RGBColor[0.368417, 0.506779, 0.709798], PointSize[0.007333333333333334], AbsoluteThickness[1.6], LineBox[{{-5.181379898481573, 3.}, {-5.001000000000001, 2.9339664514140056`}, {-4.001000000000001, 2.6150151884003776`}, {-3.0010000000000012`, 2.3536980963927734`}, {-2.0010000000000012`, 2.1596574358008325`}, {-1.0010000000000012`, 2.0403011177402557`}, {-0.0010000000000012221`, 2.000000040332089}, { 0.9989999999999988, 2.0401406839155576`}, {1.9989999999999988`, 2.159342203643318}, {2.9989999999999988`, 2.3532399490926172`}, { 3.9989999999999988`, 2.6144315813827412`}, {4.998999999999999, 2.933278008390148}, {5.181302244619848, 3.}}]}, {RGBColor[0.880722, 0.611041, 0.142051], PointSize[0.007333333333333334], AbsoluteThickness[1.6], LineBox[CompressedData[" 1:eJw10mtIk2EUB/B3r5vvoIXlbGp5n5fSpc7Lllo8p8IuluSlBNEuSFEfTE3E zJTCEhFFzGulX4qEikWUWmamT0glhsO7aWTCrPxgNtnmdG57e+t9PPBw+PF8 Ouf8fbNyUy7QFEUpufevX2M05UWsGlP/Swyfjqkr91Nq7D61rHIVMMQqbIgP uF0ncCSOxsX02GwqLSKOwg3y74fKHITEkXhme/9MusiBOAL/YPTjKjFNrMQv h0oX2iQC4nA8vS0wrURKQU1zjvMtKhS360a6THF2xFuBM0MnDfYMK3EwTl5a lDdWW4h34vrPOTdeT6wSB+LLZS8uDh8wE/tjwYBX06DOROyHswqfLvppjcQ+ eLAirqXC04g8wr75Owo8cFzCxIq7wUDshn9uzb/ZdmXj3wUX51W27u0wEW/B 2aOnUpp7zGjPme6jElqMxybuVevSLcQUfhKSPZ4otaG8noJ6N6G+z3yufOms kkUUXh5NzErqm/N/o2dZFvlUyKa15j8o9a2WUUSwqPZgVfavdRa9zxyNbnWx oYEH8a8MNgZ6UZLoRIaF2Ak07ptWtO/MaH7Y7+uaXQrtKfMSWaeJ2BW6ZbFr snwj8Q7QDFu6FNx8vL0hYUF9/zg3f/6lO79LWF8IfgROmqENywFZS5uCuP3x DgDPx7ovm7n98g6Cu7mn52bHV4l3gdfJDxnPqizEIeASYpqXcPfjvRvEzfs+ WmPtxGFQ0GiuszlTENMxUNjLhkN/0frDAC4fvJWQ3pJc18nQxBEQ3xJjmBI6 EEfCVe/zRpYWEkfB5PMjh0cEIuJocC5SYCcuv7xVMEVfT2ugGKilpDVc/mEj /38BDmhtvg== "]]}, {RGBColor[0.560181, 0.691569, 0.194885], PointSize[0.007333333333333334], AbsoluteThickness[1.6], LineBox[CompressedData[" 1:eJw1030s1HEcB/AjIrFajhOX52fO88N5/H1vMRNGbVgkjUkpKaxV06xJGEk0 0oY1Dz2plol1E5+rPGw1yi6GmRRyHs4d59ndde0+98dnn73+eP/z2edtkZJ1 Kk2dRqMFKeb/7o/wLeHQgiGB+dpc00hGKR0ENbM6z0MZUnQg5P8R55UZ7qED ICU4PmLSYBftDy+r2yaCDHbQfvDCsT2kk76NZsOoh31fPH0L7QsCp6ln3vRN tA/MzhxryaFvoL0hsdGAG2awjvYCXlPRNU2GBO0JgiztWpbxGtoDUorf9BWa raLdAcxX0gLsxWg32KGzTzB8RFR5zZUjBTQXCD9fvlFRI0Q7Ay+rOaFufAnt CL1RQ0ZMziLaHkSb9dp5ewK0LWh1mCR9mJ5HW0Poemp8dYzKltBVwze9H6yy OXyLtzL+uk9AMV0nrferMcGltj66Y2YBbQQCk89qgY5CNB2EkbJHnLti9GE4 KU3QquJKKPZZbriuujbwxu1HWTe20DSYK+ZFVTrsUVe7cquMNEQ99bkFpclr MooG4uGolJiejLcjy3K5nDIvMhwb3Fyh3Mb0uBclMqrieOnlv7tyyteqPDba aY8aeBrasSbVIp3D0jM2t7bQh0hzskZRapeEmvluObEt0yfd+SXMjkIxmkHq Bm+GRzsL0SYkMk9zRH1uAW1GppOMZ7M1BFT2hYfLeXILMhrb9+C94j5KW5FS WXLjuRiVbUhm4lArZ1plO2KZXmH7c1eVdyCa6SWsOLKIdiLQ25DJG1tCs8hk 7mRYS7UQ7UoCun8crPMWUX7tA9e75W5EN21x8aOdGO1OpsouuexX/I/SHkRU m9PQenQN7Ume3ONXFhhK0F5kvj8zrJe+jvYmMBXCF+lvoH3Il/mdx236m2hf 8k47sIKvv4VmE8pmZt1T0Q+l/cjuku5tLn0H7U/YcU2/Tyv6pXQAyeD+0jug 6J/SgWSsf9Xrk6EUHUQYpjqv7jBk1D+mZN2q "]]}, {RGBColor[0.922526, 0.385626, 0.209179], PointSize[0.007333333333333334], AbsoluteThickness[1.6], LineBox[CompressedData[" 1:eJw102lQzGEcwPG/ozJCh7KOdEmbwtbKXrU9TwfjyJUZIruZtlyLilRjMjom HUw5pglDE8aUcW80UXjqRRYj2mFQZGuvtt20VxOWXX/zf/4vnnnm8+b34nm+ v6CM7JSsyQRBCMnz/365nlsVT8ShRf7Gpi3icUBZiOaHW+65NtuwYxEjoj24 y2zFjkEb03I7K2JoC5BCIcgRlVuw+Yh56uuR5HdmbB6SDfRuksyjzUW5gqPP 2iQmbA5yt99fo9w1hr0SDV7XeZdYR7GjUXOpC9tx2oi9AkkMA7FipgGbjVqW MN2iX+qxo5CjtGW29tAwdiT68Da5lRGgAzX1h73LiOWoO6ypOl6pwV6Kzi4U 51Y/UWOHozYVfGBrVWGHobWPewVm/RB2KNrhpcxLl9IOQVUpj6cMiGgHo9qT 26ummGgHopSK1ssFIjXwY30LcZ3kh+J8mZs6jVrsuehMWINWoRnB9kEJ7JlZ jUITtiealdqxzfO9FfDET9fOmDwN1Uy/o6rWTGATSPbRTSIdsoOcjrwLc6ea XuQVKq+eVDoAgcyKDRmbX6RLG4xOpxMEVsz50jMxBiYYD2VXBh3gbOLpgzq7 E5T5vJm3Tm0H8murWq1/3aD7+B73u7oJbA+4vdAr00NhBer3wf2/HLOhue7n siRgwmbAxIIgfcLwCPYCeCDneN/eH1rsAOgtNrTni9XgyL5zo0XOIPiVU2kv Jt+H8iJ4viSw3C6ivRi69HL4PCltJjx3xlN1SU97CbTMB0lF5P9QjoC7u/zq 7W30/GVwa9armze+a7BZsFYmV2T76wD/kTz/uTMS+j0ducgl+6AcBetY3wUl 3XpsNrz9OqGxOdSAvQLuH17ftZrsj3I0HLpfeUxuGcVeCbnJcfpQsl/KHBiV WvwujeybMhc2nPAVuJL9U+bBwc8ocayHNh9K/vyOJMj9oSyA/TmWgnByvyjH wPjs54pMM+1YyCrv23mryYYthJ8I4RabaBz8A3jP52U= "]]}, {RGBColor[0.528488, 0.470624, 0.701351], PointSize[0.007333333333333334], AbsoluteThickness[1.6], LineBox[CompressedData[" 1:eJw103tIU2EUAPDryJIy0rK58JHa1Ob7/b7eT9TsobAZaUJaGeH7nQklmgia ZWaMtIcZajIpSAc+osx9pqVRDpMITSudXufmYxNFUWlrsXP/+Dj8/jjnwDnn s03Oib3KIgiC1L3/ceiMf1UYEYrpqC7DiLpVSm8Snybd6kmCcQgO3thqJtPV 4GA8eTH29/02FTgIW5uKfg4Wr4ADccidRwoXwTI4AAsEOedo+yWwP17nvFda 7CjBfjiezTPhfFOAfXG/x3jPybYFsA+mrSRNCWVysDd22h6oOZs4D/bCEjLh xVeSBnviV/uNCz3s58AeuPe5SsMzn6Vq6rMPlhNu2DXa4jJ5RAZ2wVMOeU+a vWfATthK6WJamD8NPo7FTdVbQukfsAP2zwocTYljzMVG/Llqtw+M7TDLpoii e5h8G2wYz9V0ZMgoS/df3N0Glrgzf29FZjgN5uBtzphtZKUCbIZHNBJlYZoK bILt8yrVz7LWqICkt6eMWUY4XizqlIk2wQRukEXtKxvcoXJ7rwk5u9SSiUuL sbXjGorAq2MxyXxJOtt8SavVUjaV7Anppq5ukTiha0JD1YbfzZTvaKmnh6sX sz7tUMNNkd1rf/egGzczPrNfboIPIGnql9sdOWvU3Kjd5JbmEFoyWuHQmSqw OZo532gwVaUAW6ACY1Z/QCQNPorkCrPW75kyKj/1wXKx1hYVCYbIijfT4GNo dqPAsV03P73tUQRf8yMxjrEjcje8R/CkjHnIkeYHW+cz+c6os+GEo69uf3q7 oqR18QDmMP3cUffYWEwLe5YK7By+3qf1QLntH61buHNgT2SoKVoL0t2P3l6I O9K4R3JhHuyNhH3N4QO35GAfFDb5mCcWLYB9kTwltK90VAH2Q+9a4y3Kt5Vg fyRQSn2jdfevdwAqyZbWCfnL4EDUV8JPcdb9H72DkORKbNyGSAUORqyC7HF1 mhocgl47lA6rtYxJlIPSfDYfrlL/AIk84LU= "]]}, {RGBColor[0.772079, 0.431554, 0.102387], PointSize[0.007333333333333334], AbsoluteThickness[1.6], LineBox[CompressedData[" 1:eJw102tIk1EYwPFl1tQkKyUVh85rOnXzMi9z0/dYmXbRRCmJsoVdFBUXZQkW 9aHyii5JHSjeYNjAoJbmQESPGakFpi/LS9PpdNbysmlvOsPceuM9+3A4/OD5 9PB/PLNEaTetaDRaLPn+/0Nno8rjaXHwl+y64Uq6AaMcC29Vi2V+SXpkAbzk z76xK1hD5sMqbl63LnQVOQbOf/AQ//ZbQeZBcdj0m3DGMnI0bGh0fDZ4+Cdy FHRwZ9nidB1yJNzMwA3tpu/IETC7MLNNvrWEzIXMmY7a5nUtcjiUKGqkRWuL yGHQY2CxXalfQA6Fl0cfDXgbNcghkBlPTDnaabBqScGRJzQ27Ldy1rGD55GD oAO4mJg3rkZmQWbD9r3Wmllkfxjx3qXzXN8Msh9sz9nnPVJusQ+0UbK6fWMs 814Qb8lQtQbPITPhRtp0WHaBBmNwZn3272HAgCZpvTlXi+wCU55+MmiVOmQn mJk8pfNR65EPQc/Ou3W1fAKLvtpz2t7KBnr+ncyoKzMi0+BBvHE89d0Odru3 8IWL9Xp/Q0P8UJnShNHgBp6cldov4+ErZrMZY5YenR41GrCKSv2E/KsJe36i Mv/HjhkLPC5eOKnYwYbbErqJXTqQ5QpL8AojsgP4JilhyGMJTDvmpfpjcgTZ Q6o4mUaP7AweSELqxZM6ZDdA71KY1PlaZA9woTRF1CTSYHdyatYemj3BZ7sd azpnDtkbBBU79YyQ+6PsC7YPTOxdIPdL+RjgEfVs6z6LAwBuk7vtVGOZDwT1 vaeEb8fUyMGg45WCNxg0j8wBogSWfbOtBuN1Dd/vM4cAqbA46eWWxaHAardt NJ3sh3IY8OvaTxCri8jhoNWRa+dK9keZCxo/Pl5ikX1SjgCzi0UiD7JfypEg kf/F7gzZN+UosJbsH8kn+6ccDaSvq9gdbsvIPEC4+67mkfdDOQaEe8lNQvK+ KPPBlOv5lkLy/igLQHvpNVVToh45Fgg4mwxlmgH7B8vf5Fg= "]]}, {RGBColor[0.363898, 0.618501, 0.782349], PointSize[0.007333333333333334], AbsoluteThickness[1.6], LineBox[CompressedData[" 1:eJw103lI02EYB/CZ3dgdZniktaXmXB7Tbbr5vppmVh4UGVq5EC2LWmllK+2w mRKVOUwqLS+wlnRQ626st4gyOihLSLe5pfPcoSK5ZOn6xe/xj4eHDzx/PXy/ PpkHNmVPYTAYImr+7/cbeOeiGVEkPaXaX+9pQbRF5NK6nKQzLDNYSD45Xz4R EmgCR5IIZW+yjTsAjiDtkUUqrbAfLCDFu9Plv2P7wHyiEP5MECf2gnmkoiXV EZ/aAw4njbrQcpu4GxxGqvMqFbq9RjCX8PE2v1tHu8ChpL8q8EJGaSc4hNRp FjRcr/4FDiZ7krfO/vbEAA4iObLMz2nP9ajsimShjMEhbqMNngWsDjCb3L3Z LpG/0YJXERWb+dmu0ID9yK4farXX33bwSiKvkybkWifNJFlNZ5nsd5P3y8lm 5f3aN790YG8Soz6ldNYZkMdqHXO6kwd50RhtfGvtAruR/VJ/aZGkD7yYWBao pwWWWcHziSkva0TjNYL4GS8SXKbMJIPHBQ038m1gBtmb4D569Y4dHVQdrnCb OvQq9cN7Fb9lAjHIcEtiZsqruodNJofDgbxLXdu+2AbR+jlrPbO+T6DyNef3 9dodiLuz1ld+z46a6+OejIzPwK6tLrMNUht4Hq7XuXAmvEeQ8etyzdjEIpy8 scTyUm4FL8GStGIpL7cP7I4bczhJ94e6wMuwYNPHqtgOA8rLkVsKHT7YLzro oqhLB16BW1eOFxip/9Fm4TtzKwNqqP/S9sUPjSKnAfuk/bHWzLPKFJP3AThb MDTL/FoLDsQ1D8qCnzI7wKvxWDfnatEzPRI8as5XO4LwbfYhlEHlg3YwFm6P P8Ki8kM7BNf82VFsLOkEh+KY4ZNrA6j80eZibeK1yzupfNIOw3HJa54eo/JL OxyneCxVfNjSA+bhFpe2esPGXjAfNzzXPM6n+kFbgAdkiOyg+kM7Ap82t0VJ qX7RjsStKE2sZJvAQlxS+NPXmeonbRFO0TePi6n+/gPoN+Wx "]]}, {RGBColor[1, 0.75, 0], PointSize[0.007333333333333334], AbsoluteThickness[ 1.6], LineBox[{{-30., 1.}, {30., 1.}}]}, {RGBColor[0.647624, 0.37816, 0.614037], PointSize[0.007333333333333334], AbsoluteThickness[1.6], LineBox[{{-30., 2.}, {30., 2.}}]}}, {{}, {}}, {{{GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 1.880738895533687}], Offset[{0, 0}, {31.250020833333334`, 1.880738895533687}], Offset[{0., 0.}, {31.850030833333335`, 1.880738895533687}], Offset[{0., 0.}, {31.850030833333335`, 1.880738895533687}], Offset[{0., 0.}, {32.45004083333333, 1.880738895533687}], Offset[{0, 0}, {35.26122872500218, 1.8807711971264536`}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 1.8807711971264536`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.8807711971264536`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.8807711971264536`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 1.880738895533687}], Offset[{0, 0}, {31.250020833333334`, 1.880738895533687}], Offset[{0., 0.}, {31.850030833333335`, 1.880738895533687}], Offset[{0., 0.}, {31.850030833333335`, 1.880738895533687}], Offset[{0., 0.}, {32.45004083333333, 1.880738895533687}], Offset[{0, 0}, {35.26122872500218, 1.8807711971264536`}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 1.8807711971264536`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.8807711971264536`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.8807711971264536`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {35.26122872500218, 1.8807711971264536`}], Offset[{37., -6.999999999999992}, {35.26122872500218, 1.8807711971264536`}], Offset[{10.000000000000002`, -6.999999999999997}, { 35.26122872500218, 1.8807711971264536`}], Offset[{9.999999999999998, 7.000000000000003}, {35.26122872500218, 1.8807711971264536`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=5\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {35.26122872500218, 1.8807711971264536}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 1.3354380772944319`}], Offset[{0, 0}, {31.250020833333334`, 1.3354380772944319`}], Offset[{0., 0.}, {31.850030833333335`, 1.3354380772944319`}], Offset[{0., 0.}, {31.850030833333335`, 1.3354380772944319`}], Offset[{0., 0.}, {32.45004083333333, 1.3354380772944319`}], Offset[{0, 0}, {35.26122872500218, 1.493452507043762}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 1.493452507043762}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.493452507043762}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.493452507043762}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 1.3354380772944319`}], Offset[{0, 0}, {31.250020833333334`, 1.3354380772944319`}], Offset[{0., 0.}, {31.850030833333335`, 1.3354380772944319`}], Offset[{0., 0.}, {31.850030833333335`, 1.3354380772944319`}], Offset[{0., 0.}, {32.45004083333333, 1.3354380772944319`}], Offset[{0, 0}, {35.26122872500218, 1.493452507043762}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 1.493452507043762}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.493452507043762}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.493452507043762}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {35.26122872500218, 1.493452507043762}], Offset[{37., -6.999999999999992}, {35.26122872500218, 1.493452507043762}], Offset[{10.000000000000002`, -6.999999999999997}, { 35.26122872500218, 1.493452507043762}], Offset[{9.999999999999998, 7.000000000000003}, {35.26122872500218, 1.493452507043762}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=7\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {35.26122872500218, 1.493452507043762}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 1.0991127059278616`}], Offset[{0, 0}, {31.250020833333334`, 1.0991127059278616`}], Offset[{0., 0.}, {31.850030833333335`, 1.0991127059278616`}], Offset[{0., 0.}, {31.850030833333335`, 1.0991127059278616`}], Offset[{0., 0.}, {32.45004083333333, 1.0991127059278616`}], Offset[{0, 0}, {35.26122872500218, 1.2183379451850307`}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 1.2183379451850307`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.2183379451850307`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.2183379451850307`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 1.0991127059278616`}], Offset[{0, 0}, {31.250020833333334`, 1.0991127059278616`}], Offset[{0., 0.}, {31.850030833333335`, 1.0991127059278616`}], Offset[{0., 0.}, {31.850030833333335`, 1.0991127059278616`}], Offset[{0., 0.}, {32.45004083333333, 1.0991127059278616`}], Offset[{0, 0}, {35.26122872500218, 1.2183379451850307`}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 1.2183379451850307`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.2183379451850307`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 1.2183379451850307`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {35.26122872500218, 1.2183379451850307`}], Offset[{37., -6.999999999999992}, {35.26122872500218, 1.2183379451850307`}], Offset[{10.000000000000002`, -6.999999999999997}, { 35.26122872500218, 1.2183379451850307`}], Offset[{9.999999999999998, 7.000000000000003}, {35.26122872500218, 1.2183379451850307`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=9\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {35.26122872500218, 1.2183379451850307}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 0.9788609090405553}], Offset[{0, 0}, {31.250020833333334`, 0.9788609090405553}], Offset[{0., 0.}, {31.850030833333335`, 0.9788609090405553}], Offset[{0., 0.}, {31.850030833333335`, 0.9788609090405553}], Offset[{0., 0.}, {32.45004083333333, 0.9788609090405553}], Offset[{0, 0}, {35.26122872500218, 0.9432517301195629}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 0.9432517301195629}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 0.9432517301195629}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 0.9432517301195629}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 0.9788609090405553}], Offset[{0, 0}, {31.250020833333334`, 0.9788609090405553}], Offset[{0., 0.}, {31.850030833333335`, 0.9788609090405553}], Offset[{0., 0.}, {31.850030833333335`, 0.9788609090405553}], Offset[{0., 0.}, {32.45004083333333, 0.9788609090405553}], Offset[{0, 0}, {35.26122872500218, 0.9432517301195629}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 0.9432517301195629}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 0.9432517301195629}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 0.9432517301195629}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{43., 7.00000000000001}, {35.26122872500218, 0.9432517301195629}], Offset[{43., -6.99999999999999}, {35.26122872500218, 0.9432517301195629}], Offset[{10., -6.999999999999997}, {35.26122872500218, 0.9432517301195629}], Offset[{10., 7.000000000000003}, {35.26122872500218, 0.9432517301195629}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=11\"\>", BoxRotation->0.], Offset[{26.5, 5.88418203051333*^-15}, \ {35.26122872500218, 0.9432517301195629}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 0.9098358113032905}], Offset[{0, 0}, {31.250020833333334`, 0.9098358113032905}], Offset[{0., 0.}, {31.850030833333335`, 0.9098358113032905}], Offset[{0., 0.}, {31.850030833333335`, 0.9098358113032905}], Offset[{0., 0.}, {32.45004083333333, 0.9098358113032905}], Offset[{0, 0}, {35.26122872500218, 0.6681646554055629}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 0.6681646554055629}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 0.6681646554055629}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 0.6681646554055629}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {31.250020833333334`, 0.9098358113032905}], Offset[{0, 0}, {31.250020833333334`, 0.9098358113032905}], Offset[{0., 0.}, {31.850030833333335`, 0.9098358113032905}], Offset[{0., 0.}, {31.850030833333335`, 0.9098358113032905}], Offset[{0., 0.}, {32.45004083333333, 0.9098358113032905}], Offset[{0, 0}, {35.26122872500218, 0.6681646554055629}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 0.6681646554055629}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 0.6681646554055629}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 0.6681646554055629}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{43., 7.00000000000001}, {35.26122872500218, 0.6681646554055629}], Offset[{43., -6.99999999999999}, {35.26122872500218, 0.6681646554055629}], Offset[{10., -6.999999999999997}, {35.26122872500218, 0.6681646554055629}], Offset[{10., 7.000000000000003}, {35.26122872500218, 0.6681646554055629}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=13\"\>", BoxRotation->0.], Offset[{26.5, 5.88418203051333*^-15}, \ {35.26122872500218, 0.6681646554055629}], {0, 0}]}]}, {GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {6.390443561151144, 3}], Offset[{0, 0}, {6.390443561151144, 3}], Offset[{0., 0.}, {6.390443561151144, 3.}], Offset[{0., 0.}, {6.390443561151144, 3.}], Offset[{0., 0.}, {6.390443561151144, 3.}], Offset[{0, 0}, {35.26122872500218, 2.5873817711230793`}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 2.5873817711230793`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 2.5873817711230793`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 2.5873817711230793`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {6.390443561151144, 3}], Offset[{0, 0}, {6.390443561151144, 3}], Offset[{0., 0.}, {6.390443561151144, 3.}], Offset[{0., 0.}, {6.390443561151144, 3.}], Offset[{0., 0.}, {6.390443561151144, 3.}], Offset[{0, 0}, {35.26122872500218, 2.5873817711230793`}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 2.5873817711230793`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 2.5873817711230793`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 2.5873817711230793`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {35.26122872500218, 2.5873817711230793`}], Offset[{37., -6.999999999999992}, {35.26122872500218, 2.5873817711230793`}], Offset[{10.000000000000002`, -6.999999999999997}, { 35.26122872500218, 2.5873817711230793`}], Offset[{9.999999999999998, 7.000000000000003}, {35.26122872500218, 2.5873817711230793`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=1\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {35.26122872500218, 2.5873817711230793}], {0, 0}]}], GraphicsGroupBox[{ {GrayLevel[1], AbsoluteThickness[4], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]], CapForm["Butt"], JoinForm[ "Round"], BSplineCurveBox[{ Offset[{0, 0}, {25.197953550359514`, 3}], Offset[{0, 0}, {25.197953550359514`, 3}], Offset[{0., 0.}, {25.197953550359514`, 3.}], Offset[{0., 0.}, {25.197953550359514`, 3.}], Offset[{0., 0.}, {25.197953550359514`, 3.}], Offset[{0, 0}, {35.26122872500218, 2.8624586482576895`}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 2.8624586482576895`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 2.8624586482576895`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 2.8624586482576895`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], BSplineCurveBox[{ Offset[{0, 0}, {25.197953550359514`, 3}], Offset[{0, 0}, {25.197953550359514`, 3}], Offset[{0., 0.}, {25.197953550359514`, 3.}], Offset[{0., 0.}, {25.197953550359514`, 3.}], Offset[{0., 0.}, {25.197953550359514`, 3.}], Offset[{0, 0}, {35.26122872500218, 2.8624586482576895`}], Offset[{5., 1.1102230246251565`*^-15}, {35.26122872500218, 2.8624586482576895`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 2.8624586482576895`}], Offset[{10., 2.220446049250313*^-15}, {35.26122872500218, 2.8624586482576895`}]}]}, {EdgeForm[None], FaceForm[{GrayLevel[1], Opacity[ NCache[ Rational[2, 3], 0.6666666666666666]]}], PolygonBox[{ Offset[{37., 7.000000000000008}, {35.26122872500218, 2.8624586482576895`}], Offset[{37., -6.999999999999992}, {35.26122872500218, 2.8624586482576895`}], Offset[{10.000000000000002`, -6.999999999999997}, { 35.26122872500218, 2.8624586482576895`}], Offset[{9.999999999999998, 7.000000000000003}, {35.26122872500218, 2.8624586482576895`}]}]}, {RGBColor[0.6666666666666666, 0.6666666666666666, 0.6666666666666666], AbsoluteThickness[1.25], EdgeForm[None]}, {}, InsetBox[ RotationBox["\<\"N=3\"\>", BoxRotation->0.], Offset[{23.5, 5.218048215738236*^-15}, \ {35.26122872500218, 2.8624586482576895}], {0, 0}]}]}}, {}}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{True, True}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{False, False}, {False, False}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->{{All, 71.06684623590911}, {All, All}}, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotRange->{{-30.001, 30.}, {0, 3}}, PlotRangeClipping->False, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, {0, 0}}, Ticks->{Automatic, Automatic}]], "Output", CellChangeTimes->{ 3.806914336747793*^9, {3.806920464278989*^9, 3.806920472247993*^9}, 3.806920787877467*^9, 3.806922277943427*^9, 3.806984512974063*^9, { 3.8069845794323463`*^9, 3.806984588978162*^9}, 3.813387090195758*^9, { 3.813388924408916*^9, 3.813388960006165*^9}, 3.8133922647373962`*^9, 3.813406983008119*^9}, CellLabel->"Out[76]=",ExpressionUUID->"3f85fe64-3ff3-45be-acbb-89f2a3276c47"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{"Tilmanns", " ", "Ergebnisse", " ", RowBox[{"vs", ".", " ", RowBox[{"FindMinimum", ":", "\[IndentingNewLine]", RowBox[{ "Die", " ", "jeweiligen", " ", "Minima", " ", "der", " ", "Unsch\[ADoubleDot]rferelation", " ", "mit", " ", "den", " ", "dazugeh\[ODoubleDot]rigen", " ", "Parametern", " ", RowBox[{"(", RowBox[{"3", ",", "5", ",", "7", ",", "9", ",", "11", ",", "13"}], ")"}], " ", "Quantenpunkte", "\[IndentingNewLine]", RowBox[{"{", RowBox[{"1.2458788244725605`", ",", RowBox[{"{", RowBox[{ RowBox[{"\[Lambda]", "\[Rule]", "0.009999959154289148`"}], ",", RowBox[{"V", "\[Rule]", RowBox[{"-", "7.221064554765229`"}]}]}], "}"}]}], "}"}], " ", RowBox[{"vs", ".", " ", RowBox[{"{", RowBox[{"1.2458788229026372`", ",", RowBox[{"{", RowBox[{ RowBox[{"V", "\[Rule]", "7.221067702630215`"}], ",", RowBox[{"\[Lambda]", "\[Rule]", "0.010000199061175588`"}]}], "}"}]}], "}"}]}], "\[IndentingNewLine]", RowBox[{"{", RowBox[{"0.7554305430129272`", ",", RowBox[{"{", RowBox[{ RowBox[{"\[Lambda]", "\[Rule]", RowBox[{"-", "0.00781394527921633`"}]}], ",", RowBox[{"V", "\[Rule]", "9.393004827858011`"}]}], "}"}]}], "}"}], " ", RowBox[{"vs", ".", " ", RowBox[{"{", RowBox[{"0.7558164712527939`", ",", RowBox[{"{", RowBox[{ RowBox[{"V", "\[Rule]", "9.391065913646672`"}], ",", RowBox[{"\[Lambda]", "\[Rule]", "0.007813725282389295`"}]}], "}"}]}], "}"}]}], "\[IndentingNewLine]", RowBox[{"{", RowBox[{"0.572847683176261`", ",", RowBox[{"{", RowBox[{ RowBox[{"\[Lambda]", "\[Rule]", "0.0074508497062710805`"}], ",", RowBox[{"V", "\[Rule]", "10.386440207427597`"}]}], "}"}]}], "}"}], " ", RowBox[{"vs", ".", " ", RowBox[{"{", RowBox[{"0.5726255406381631`", ",", RowBox[{"{", RowBox[{ RowBox[{"V", "\[Rule]", "10.38777281253604`"}], ",", RowBox[{"\[Lambda]", "\[Rule]", "0.007451002109568454`"}]}], "}"}]}], "}"}]}], "\[IndentingNewLine]", RowBox[{"{", RowBox[{"0.48965280097811276`", ",", RowBox[{"{", RowBox[{ RowBox[{"\[Lambda]", "\[Rule]", "0.007326447541946075`"}], ",", RowBox[{"V", "\[Rule]", "10.91473000281113`"}]}], "}"}]}], "}"}], " ", RowBox[{"vs", ".", " ", RowBox[{"{", RowBox[{"0.48959177828867484`", ",", RowBox[{"{", RowBox[{ RowBox[{"V", "\[Rule]", "10.915141270700905`"}], ",", RowBox[{"\[Lambda]", "\[Rule]", "0.007326444792376225`"}]}], "}"}]}], "}"}]}], "\[IndentingNewLine]", RowBox[{"{", RowBox[{"0.44564368710726454`", ",", RowBox[{"{", RowBox[{ RowBox[{"\[Lambda]", "\[Rule]", "0.007269560988958051`"}], ",", RowBox[{"V", "\[Rule]", "11.22239888748624`"}]}], "}"}]}], "}"}], " ", RowBox[{"vs", ".", " ", RowBox[{"{", RowBox[{"0.4455816929554629`", ",", RowBox[{"{", RowBox[{ RowBox[{"V", "\[Rule]", "11.222846950721534`"}], ",", RowBox[{"\[Lambda]", "\[Rule]", "0.007269559371554312`"}]}], "}"}]}], "}"}]}], "\[IndentingNewLine]", RowBox[{"{", RowBox[{"0.4197865144938278`", ",", RowBox[{"{", RowBox[{ RowBox[{"\[Lambda]", "\[Rule]", RowBox[{"-", "0.007238948047382406`"}]}], ",", RowBox[{"V", "\[Rule]", "11.41449491980886`"}]}], "}"}]}], "}"}], " ", RowBox[{"vs", ".", " ", RowBox[{"{", RowBox[{"0.4197209743172402`", ",", RowBox[{"{", RowBox[{ RowBox[{"V", "\[Rule]", "11.41499238569322`"}], ",", RowBox[{"\[Lambda]", "\[Rule]", "0.00723894298148576`"}]}], "}"}]}], "}"}]}]}]}]}]}], "\[IndentingNewLine]", "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "7.221064554765229", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{"0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{"0.009999959154289148`", ",", "0.009999959154289148`"}], "}"}]}], "]"}], "\[IndentingNewLine]", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "9.393004827858011", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{"0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}], "\[IndentingNewLine]", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "10.386440207427597", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}], "\[IndentingNewLine]", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "10.91473000281113", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}], "\[IndentingNewLine]", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "11.22239888748624", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007269560988958051", ",", "0.007269560988958051", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}], "\[IndentingNewLine]", RowBox[{"uncrel", "[", RowBox[{ "1.", ",", "11.41449491980886", ",", "1.", ",", "1.", ",", "0.", ",", "100.", ",", RowBox[{"{", RowBox[{ "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0.", ",", "0."}], "}"}], ",", RowBox[{"{", RowBox[{ "0.009999959154289148`", ",", "0.00781394527921633`", ",", "0.0074508497062710805`", ",", "0.007326447541946075`", ",", "0.007269560988958051", ",", "0.007238948047382406", ",", "0.007238948047382406", ",", "0.007269560988958051", ",", "0.007326447541946075`", ",", "0.0074508497062710805`", ",", "0.00781394527921633`", ",", "0.009999959154289148`"}], "}"}]}], "]"}]}]}]], "Input", CellChangeTimes->{{3.806984110861792*^9, 3.806984129776105*^9}, { 3.806984758917955*^9, 3.8069847630417967`*^9}, {3.806985020883215*^9, 3.8069850216544743`*^9}, 3.806985502755382*^9, {3.8133889682391872`*^9, 3.8133889754728603`*^9}, {3.8133890178090477`*^9, 3.8133890943060017`*^9}, {3.813389128493636*^9, 3.813389171076812*^9}, { 3.813389206517851*^9, 3.813389274992371*^9}, {3.813390120175561*^9, 3.813390148892539*^9}, {3.8134037333272*^9, 3.813403796959988*^9}, { 3.813404314671091*^9, 3.8134043163758907`*^9}, {3.813405935735318*^9, 3.813405973392948*^9}, 3.813408375796029*^9, {3.8134084070497227`*^9, 3.8134084320760508`*^9}}, CellLabel->"In[78]:=",ExpressionUUID->"17cc0c31-09ca-4ece-965f-479cdfacaaa9"], Cell[BoxData["1.245878824481107`"], "Output", CellChangeTimes->{ 3.813388976129075*^9, {3.8133890582655697`*^9, 3.813389096191885*^9}, 3.813389277784792*^9, 3.813390154188449*^9, 3.813392266965725*^9, 3.813408435339848*^9}, CellLabel->"Out[78]=",ExpressionUUID->"6246ea1b-73b0-4d63-ab37-469cda43f429"], Cell[BoxData["0.7557977386406182`"], "Output", CellChangeTimes->{ 3.813388976129075*^9, {3.8133890582655697`*^9, 3.813389096191885*^9}, 3.813389277784792*^9, 3.813390154188449*^9, 3.813392266965725*^9, 3.813408437707*^9}, CellLabel->"Out[79]=",ExpressionUUID->"80b0ef8f-0d4e-425c-a671-b94451c5a7db"], Cell[BoxData["0.5726315811883969`"], "Output", CellChangeTimes->{ 3.813388976129075*^9, {3.8133890582655697`*^9, 3.813389096191885*^9}, 3.813389277784792*^9, 3.813390154188449*^9, 3.813392266965725*^9, 3.813408439910328*^9}, CellLabel->"Out[80]=",ExpressionUUID->"e7b1d9fe-3733-4602-b432-d11f0aa177e4"], Cell[BoxData["0.4895968585267795`"], "Output", CellChangeTimes->{ 3.813388976129075*^9, {3.8133890582655697`*^9, 3.813389096191885*^9}, 3.813389277784792*^9, 3.813390154188449*^9, 3.813392266965725*^9, 3.813408443082065*^9}, CellLabel->"Out[81]=",ExpressionUUID->"cc0ccce8-451f-4fd5-a436-cdd9fd81bdf9"], Cell[BoxData["0.44558674847976387`"], "Output", CellChangeTimes->{ 3.813388976129075*^9, {3.8133890582655697`*^9, 3.813389096191885*^9}, 3.813389277784792*^9, 3.813390154188449*^9, 3.813392266965725*^9, 3.8134084479619293`*^9}, CellLabel->"Out[82]=",ExpressionUUID->"ca68ad74-dd71-4950-af0a-77c9ace0598f"], Cell[BoxData["0.4197263768278229`"], "Output", CellChangeTimes->{ 3.813388976129075*^9, {3.8133890582655697`*^9, 3.813389096191885*^9}, 3.813389277784792*^9, 3.813390154188449*^9, 3.813392266965725*^9, 3.813408454706954*^9}, CellLabel->"Out[83]=",ExpressionUUID->"3ca1a8a9-afc8-4a91-85a3-2845087f5618"] }, Open ]], Cell[BoxData["\[IndentingNewLine]"], "Input", CellChangeTimes->{ 3.813389407927348*^9},ExpressionUUID->"f8fd0333-9451-4b7d-934e-\ fc10b42f9b31"] }, WindowSize->{1920, 1029}, WindowMargins->{{0, Automatic}, {0, Automatic}}, FrontEndVersion->"11.3 for Linux x86 (64-bit) (March 6, 2018)", StyleDefinitions->"Default.nb" ] (* End of Notebook Content *) (* Internal cache information *) (*CellTagsOutline CellTagsIndex->{} *) (*CellTagsIndex CellTagsIndex->{} *) (*NotebookFileOutline Notebook[{ Cell[558, 20, 8648, 222, 423, "Input",ExpressionUUID->"444839ce-4487-4b36-91b4-b3030a262fd5"], Cell[CellGroupData[{ Cell[9231, 246, 1945, 43, 124, "Input",ExpressionUUID->"741b7126-90be-46e6-884d-10385b5513e3"], Cell[11179, 291, 2708, 60, 251, "Output",ExpressionUUID->"8a57fc09-71e6-469b-8437-56b2822c39aa"] }, Open ]], Cell[CellGroupData[{ Cell[13924, 356, 1623, 33, 124, "Input",ExpressionUUID->"9c3f0776-c046-4a2f-bed3-e3ef5e801456"], Cell[15550, 391, 669, 12, 35, "Output",ExpressionUUID->"22d81a92-adaf-4cc4-9952-576afb5414fa"] }, Open ]], Cell[CellGroupData[{ Cell[16256, 408, 1864, 41, 124, "Input",ExpressionUUID->"9e701970-221a-4362-b8ed-b4f3d34099f7"], Cell[18123, 451, 256, 3, 35, "Output",ExpressionUUID->"7274b1a0-96a3-44e8-a6b5-1b257220087c"] }, Open ]], Cell[CellGroupData[{ Cell[18416, 459, 433, 9, 31, "Input",ExpressionUUID->"fe5609fc-1720-45d2-8af0-1aebf87d786d"], Cell[18852, 470, 364, 7, 35, "Output",ExpressionUUID->"40d79cdb-6670-46fe-a9ea-cf0f40ac266f"] }, Open ]], Cell[19231, 480, 4454, 105, 630, "Input",ExpressionUUID->"d071d3b0-c4f3-4a2a-91e8-3f5fa22b6b82"], Cell[CellGroupData[{ Cell[23710, 589, 339, 6, 31, "Input",ExpressionUUID->"b740b859-d8ab-47ec-96a7-d14d70b5f1d8"], Cell[24052, 597, 218, 3, 35, "Output",ExpressionUUID->"5a826dcb-9943-43a6-8716-0814a2e03c8a"] }, Open ]], Cell[24285, 603, 175, 3, 31, "Input",ExpressionUUID->"eda01849-39bf-4147-9e87-d90452d4acf7"], Cell[CellGroupData[{ Cell[24485, 610, 10663, 217, 630, "Input",ExpressionUUID->"0cafabec-9ace-4856-87cb-9f2040807a27"], Cell[35151, 829, 215890, 3598, 198, "Output",ExpressionUUID->"fe303ab2-60c7-4daf-93af-21f70cb22469"], Cell[251044, 4429, 220080, 3666, 198, "Output",ExpressionUUID->"3d21af26-9c89-456e-8f28-70d671c109e3"] }, Open ]], Cell[471139, 8098, 1858, 48, 78, "Input",ExpressionUUID->"6f3ae69e-9c75-4c42-ba15-7d44efad2c61"], Cell[CellGroupData[{ Cell[473022, 8150, 941, 20, 78, "Input",ExpressionUUID->"156db52f-3a22-4dc3-b6e5-1d5a4d050205"], Cell[473966, 8172, 191, 2, 35, "Output",ExpressionUUID->"4e2eb27f-9c99-4d93-a68f-1e21c91df774"] }, Open ]], Cell[CellGroupData[{ Cell[474194, 8179, 1073, 24, 31, "Input",ExpressionUUID->"03ec2bcd-6f55-4aed-984e-7b3429dbb205"], Cell[475270, 8205, 498, 11, 23, "Message",ExpressionUUID->"c8f2dbe7-75ac-48fb-beaf-7fa727078358"], Cell[475771, 8218, 499, 11, 23, "Message",ExpressionUUID->"85548cc2-78a8-44ba-9d45-9901a1eb52da"], Cell[476273, 8231, 501, 11, 23, "Message",ExpressionUUID->"17347db3-d2a3-41b3-ac1a-5313612d9892"], Cell[476777, 8244, 472, 10, 23, "Message",ExpressionUUID->"1e262895-5071-4647-89fe-e2631dad9957"], Cell[477252, 8256, 750, 15, 35, "Output",ExpressionUUID->"55009182-6a57-4ae0-9368-6c6f50d18513"] }, Open ]], Cell[CellGroupData[{ Cell[478039, 8276, 4018, 83, 308, "Input",ExpressionUUID->"795c8c6c-fedf-45a2-a33a-f6348f3280a6"], Cell[482060, 8361, 124253, 2073, 659, "Output",ExpressionUUID->"52bf8e80-e33c-466a-a77e-03ecfb2fa225"] }, Open ]], Cell[CellGroupData[{ Cell[606350, 10439, 1486, 32, 124, "Input",ExpressionUUID->"cfc65b7b-0c05-4955-b381-78e82bef63d9"], Cell[607839, 10473, 284, 4, 35, "Output",ExpressionUUID->"3f195e23-3834-4bb7-8a87-2b3d763f8925"] }, Open ]], Cell[CellGroupData[{ Cell[608160, 10482, 1474, 33, 124, "Input",ExpressionUUID->"592cf244-c9e0-441a-9140-234a2bad516e"], Cell[609637, 10517, 164, 2, 35, "Output",ExpressionUUID->"c21d3d19-d64c-40d1-96ac-8143059ffffe"] }, Open ]], Cell[CellGroupData[{ Cell[609838, 10524, 1208, 26, 101, "Input",ExpressionUUID->"7d89f0bc-7957-4569-8eec-16807055849e"], Cell[611049, 10552, 757, 15, 40, "Output",ExpressionUUID->"5db81ab0-f57e-4dc2-b50d-150ac5f5b490"] }, Open ]], Cell[CellGroupData[{ Cell[611843, 10572, 1162, 25, 78, "Input",ExpressionUUID->"68811056-506e-4818-9152-69039a8354f1"], Cell[613008, 10599, 43079, 724, 241, "Output",ExpressionUUID->"f902dacc-93e9-481a-b84f-d1efa9f28d1d"] }, Open ]], Cell[656102, 11326, 24921, 524, 469, "Input",ExpressionUUID->"573ba7d8-4cdf-4004-b0e2-aa13225400f3"], Cell[CellGroupData[{ Cell[681048, 11854, 1439, 33, 124, "Input",ExpressionUUID->"45037692-087d-436c-a3e0-d11cdc17253c"], Cell[682490, 11889, 520, 11, 23, "Message",ExpressionUUID->"560e08e9-f028-44b7-8f06-83ccf5ff0e89"], Cell[683013, 11902, 520, 11, 23, "Message",ExpressionUUID->"d4855474-b1a3-4bdc-8089-3b04aecdaa43"], Cell[683536, 11915, 387, 9, 50, "Message",ExpressionUUID->"e1a6fb3d-0ec2-451c-b1c1-e435176f0de3"], Cell[683926, 11926, 422, 10, 23, "Message",ExpressionUUID->"cc45334f-6a4b-4382-bff9-ae7b9b0c0dad"], Cell[684351, 11938, 186, 2, 35, "Output",ExpressionUUID->"c261e3d2-c12d-415e-b8f0-22fe857d05b8"] }, Closed]], Cell[CellGroupData[{ Cell[684574, 11945, 1575, 34, 120, "Input",ExpressionUUID->"2a97de18-a149-4199-8706-4ace0c232c6d"], Cell[686152, 11981, 569, 12, 23, "Message",ExpressionUUID->"10cb7338-ff70-42c8-b796-fbbc3ac4ae73"], Cell[686724, 11995, 569, 12, 23, "Message",ExpressionUUID->"cf8f1728-1eae-46c3-8ae5-e28058c98744"], Cell[687296, 12009, 436, 10, 50, "Message",ExpressionUUID->"c734c845-b7e2-4472-a6f5-6c50ccd462cb"], Cell[687735, 12021, 470, 11, 23, "Message",ExpressionUUID->"4d311d1b-f793-4b3d-a744-18ae8803d99a"], Cell[688208, 12034, 282, 4, 35, "Output",ExpressionUUID->"808790eb-7a63-4854-857a-4803f7a0d804"] }, Closed]], Cell[CellGroupData[{ Cell[688527, 12043, 715, 19, 27, "Input",ExpressionUUID->"09b89b6f-9070-4862-90dd-e551471b903b"], Cell[689245, 12064, 500, 11, 23, "Message",ExpressionUUID->"43b67acd-6da8-4180-9eec-18bd9f579d1a"], Cell[689748, 12077, 365, 9, 50, "Message",ExpressionUUID->"dd04e3e7-7dc3-4271-923c-228e09fd07f5"], Cell[690116, 12088, 402, 10, 23, "Message",ExpressionUUID->"2fd07e79-1ab5-432d-8bb4-fd9bd06c4a5d"], Cell[690521, 12100, 164, 2, 35, "Output",ExpressionUUID->"d4bec91f-7889-4770-a6bc-5d17d5bedc59"] }, Closed]], Cell[690700, 12105, 8813, 214, 465, "Input",ExpressionUUID->"8de30f42-77e7-41a5-ab87-15425c69aba1"], Cell[699516, 12321, 703, 23, 55, "Input",ExpressionUUID->"54261a7b-424d-415f-bca0-90c93c4115d3"], Cell[CellGroupData[{ Cell[700244, 12348, 1114, 23, 31, "Input",ExpressionUUID->"a5a76b0b-0d22-462a-833a-ac51784db1d9"], Cell[701361, 12373, 28116, 520, 220, "Output",ExpressionUUID->"3f85fe64-3ff3-45be-acbb-89f2a3276c47"] }, Open ]], Cell[CellGroupData[{ Cell[729514, 12898, 8604, 201, 469, "Input",ExpressionUUID->"17cc0c31-09ca-4ece-965f-479cdfacaaa9"], Cell[738121, 13101, 313, 5, 35, "Output",ExpressionUUID->"6246ea1b-73b0-4d63-ab37-469cda43f429"], Cell[738437, 13108, 311, 5, 35, "Output",ExpressionUUID->"80b0ef8f-0d4e-425c-a671-b94451c5a7db"], Cell[738751, 13115, 314, 5, 35, "Output",ExpressionUUID->"e7b1d9fe-3733-4602-b432-d11f0aa177e4"], Cell[739068, 13122, 314, 5, 35, "Output",ExpressionUUID->"cc0ccce8-451f-4fd5-a436-cdd9fd81bdf9"], Cell[739385, 13129, 317, 5, 35, "Output",ExpressionUUID->"ca68ad74-dd71-4950-af0a-77c9ace0598f"], Cell[739705, 13136, 314, 5, 35, "Output",ExpressionUUID->"3ca1a8a9-afc8-4a91-85a3-2845087f5618"] }, Open ]], Cell[740034, 13144, 147, 3, 55, "Input",ExpressionUUID->"f8fd0333-9451-4b7d-934e-fc10b42f9b31"] } ] *)