(* Content-type: application/mathematica *) (*** Wolfram Notebook File ***) (* http://www.wolfram.com/nb *) (* CreatedBy='Mathematica 6.0' *) (*CacheID: 234*) (* Internal cache information: NotebookFileLineBreakTest NotebookFileLineBreakTest NotebookDataPosition[ 145, 7] NotebookDataLength[ 60154, 1081] NotebookOptionsPosition[ 59671, 1061] NotebookOutlinePosition[ 60013, 1076] CellTagsIndexPosition[ 59970, 1073] WindowFrame->Normal ContainsDynamic->False*) (* Beginning of Notebook Content *) Notebook[{ Cell[TextData[{ StyleBox["Visualizer for MPSM Rossler Results\n", FontWeight->"Bold"], "Just put one of your estimated cycle points in for an initial condition \ (red text)." }], "Text", CellChangeTimes->{{3.4323054295360003`*^9, 3.432305483946*^9}, { 3.4343818084556*^9, 3.4343818437335997`*^9}, {3.4343819769316*^9, 3.4343820061085997`*^9}, {3.4343821187046003`*^9, 3.4343822417736*^9}, { 3.4343841860466003`*^9, 3.4343842874695997`*^9}, {3.4343845198386*^9, 3.4343845594336*^9}, {3.4343846813986*^9, 3.4343847155506*^9}, 3.4343848164706*^9}], Cell[BoxData[ RowBox[{ RowBox[{"(*", "parameters", "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"a", "=", RowBox[{"b", "=", "0.2"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"c", "=", "5.7"}], ";"}]}]}]], "Input", CellChangeTimes->{{3.431077326914*^9, 3.431077327276*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{"state", " ", RowBox[{"equations", ":", " ", RowBox[{"Rossler", " ", "Flow"}]}]}], "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"dxdt", "=", RowBox[{ RowBox[{ RowBox[{"x", "'"}], "[", "t", "]"}], "\[Equal]", RowBox[{ RowBox[{"-", RowBox[{"y", "[", "t", "]"}]}], "-", RowBox[{"z", "[", "t", "]"}]}]}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"dydt", "=", RowBox[{ RowBox[{ RowBox[{"y", "'"}], "[", "t", "]"}], "\[Equal]", RowBox[{ RowBox[{"x", "[", "t", "]"}], "+", RowBox[{"a", "*", RowBox[{"y", "[", "t", "]"}]}]}]}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"dzdt", "=", RowBox[{ RowBox[{ RowBox[{"z", "'"}], "[", "t", "]"}], "\[Equal]", RowBox[{"b", "+", RowBox[{ RowBox[{"z", "[", "t", "]"}], "*", RowBox[{"(", RowBox[{ RowBox[{"x", "[", "t", "]"}], "-", "c"}], ")"}]}]}]}]}], ";"}]}]}]], "Input", CellChangeTimes->{{3.4310288465109997`*^9, 3.4310289391140003`*^9}, 3.431029560666*^9}], Cell[BoxData[ RowBox[{ StyleBox[ RowBox[{"(*", RowBox[{ "enter", " ", "one", " ", "of", " ", "the", " ", "cycle", " ", "points", " ", "you", " ", "found", " ", "with", " ", "the", " ", "MPSM", " ", "alg"}], "*)"}], FontWeight->"Plain", FontColor->RGBColor[1, 0, 0]], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{ RowBox[{"{", RowBox[{"x1", ",", "x2", ",", "x3"}], "}"}], "=", StyleBox[ RowBox[{"{", RowBox[{ RowBox[{"-", "5.798444864026705`*^-17"}], ",", "6.302598854074691`", ",", "1.1551009587648406`"}], "}"}], FontColor->RGBColor[1, 0, 0]]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"sect", "=", RowBox[{"{", "}"}]}], ";"}], "\[IndentingNewLine]", "\[IndentingNewLine]", RowBox[{ RowBox[{"runtime", "=", "40"}], ";"}], "\n", RowBox[{ RowBox[{"sect", "=", RowBox[{"{", "}"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"sol", "=", RowBox[{"NDSolve", "[", "\[IndentingNewLine]", RowBox[{ RowBox[{"{", RowBox[{ "dxdt", ",", "\[IndentingNewLine]", "dydt", ",", "\[IndentingNewLine]", "dzdt", ",", "\[IndentingNewLine]", RowBox[{ RowBox[{"x", "[", "0", "]"}], "\[Equal]", "x1"}], ",", "\[IndentingNewLine]", RowBox[{ RowBox[{"y", "[", "0", "]"}], "\[Equal]", "x2"}], ",", "\[IndentingNewLine]", RowBox[{ RowBox[{"z", "[", "0", "]"}], "\[Equal]", "x3"}]}], "}"}], ",", "\[IndentingNewLine]", RowBox[{"{", RowBox[{"x", ",", "y", ",", "z"}], "}"}], ",", "\[IndentingNewLine]", RowBox[{"{", RowBox[{"t", ",", "0", ",", "runtime"}], "}"}], ",", "\[IndentingNewLine]", RowBox[{"MaxSteps", "\[Rule]", "Infinity"}], ",", "\[IndentingNewLine]", RowBox[{"MaxStepSize", "\[Rule]", "0.01"}], ",", "\[IndentingNewLine]", RowBox[{"Method", "\[Rule]", RowBox[{"{", RowBox[{"\"\\"", ",", "\[IndentingNewLine]", RowBox[{"\"\\"", "\[Rule]", RowBox[{"x", "[", "t", "]"}]}], ",", RowBox[{"Direction", "\[Rule]", RowBox[{"-", "1"}]}], ",", "\[IndentingNewLine]", RowBox[{"EventAction", "\[RuleDelayed]", RowBox[{"{", RowBox[{"AppendTo", "[", RowBox[{"sect", ",", RowBox[{"{", RowBox[{ RowBox[{"x", "[", "t", "]"}], ",", RowBox[{"y", "[", "t", "]"}], ",", RowBox[{"z", "[", "t", "]"}]}], "}"}]}], "]"}], "}"}]}]}], "}"}]}]}], "\[IndentingNewLine]", "]"}]}], ";"}]}]}]], "Input", CellChangeTimes->{{3.431028925541*^9, 3.431028975013*^9}, {3.431029113184*^9, 3.431029116432*^9}, {3.4310294852720003`*^9, 3.431029496466*^9}, 3.43102956912*^9, 3.431077187815*^9, {3.4310773197130003`*^9, 3.431077324723*^9}, {3.431078293208*^9, 3.4310783147539997`*^9}, 3.4310783746870003`*^9, {3.431078406422*^9, 3.431078407469*^9}, { 3.4310792782460003`*^9, 3.431079301133*^9}, 3.4310793435150003`*^9, { 3.431079499317*^9, 3.431079513809*^9}, {3.4310797287530003`*^9, 3.4310797604119997`*^9}, 3.4310801440109997`*^9, 3.431080213416*^9, { 3.431080365908*^9, 3.4310803953929996`*^9}, {3.431082179719*^9, 3.431082189199*^9}, {3.4310829760550003`*^9, 3.431082994874*^9}, 3.431083088293*^9, 3.4310839160030003`*^9, 3.431088727301*^9, { 3.4310891187060003`*^9, 3.431089139825*^9}, 3.43109183944*^9, { 3.431091884608*^9, 3.431091908678*^9}, 3.4310919448459997`*^9, 3.431102708975*^9, {3.4319046585769997`*^9, 3.431904687689*^9}, { 3.431904782701*^9, 3.431904863954*^9}, {3.432037290689*^9, 3.4320372950950003`*^9}, {3.432124609731*^9, 3.432124633308*^9}, 3.432124663376*^9, {3.4321440446289997`*^9, 3.432144069867*^9}, { 3.4321441240690002`*^9, 3.432144124568*^9}, {3.432144155031*^9, 3.432144167552*^9}, 3.432145608082*^9, {3.432145854415*^9, 3.432145867907*^9}, 3.432147596259*^9, 3.432148497818*^9, 3.4321485394300003`*^9, 3.4321486037130003`*^9, 3.432148989755*^9, 3.432149470749*^9, {3.432302414874*^9, 3.4323024629700003`*^9}, { 3.432306122797*^9, 3.432306148767*^9}, {3.432306373198*^9, 3.4323064053310003`*^9}, 3.432306542218*^9, {3.4323066817139997`*^9, 3.432306702134*^9}, 3.4323068473859997`*^9, 3.4323068979960003`*^9, { 3.4323069316809998`*^9, 3.4323069456219997`*^9}, 3.432307087657*^9, { 3.4323071672200003`*^9, 3.432307191566*^9}, 3.432307224999*^9, 3.4323073925*^9, {3.4323074232349997`*^9, 3.4323074360360003`*^9}, 3.43230763713*^9, 3.432307682491*^9, {3.4343838073966*^9, 3.4343838288826*^9}, 3.4343838670486*^9, {3.4343839712036*^9, 3.4343839907726*^9}, 3.4343844303356*^9, 3.4343844860626*^9, { 3.4343846390386*^9, 3.4343846463726*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"ParametricPlot3D", "[", RowBox[{ RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"x", "[", "t", "]"}], ",", RowBox[{"y", "[", "t", "]"}], ",", RowBox[{"z", "[", "t", "]"}]}], "}"}], "/.", "sol"}], ",", RowBox[{"{", RowBox[{"t", ",", "0", ",", "runtime"}], "}"}], ",", RowBox[{"BoxRatios", "\[Rule]", "1"}], ",", RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}]], "Input", CellChangeTimes->{{3.4319047028570004`*^9, 3.431904768549*^9}, { 3.4320372579890003`*^9, 3.432037280388*^9}, {3.4323061813570004`*^9, 3.432306250041*^9}, {3.432307132385*^9, 3.432307143102*^9}, { 3.4343838943966*^9, 3.4343839361156*^9}}], Cell[BoxData[ Graphics3DBox[{{}, {}, {Hue[0.67, 0.6, 0.6], Line3DBox[CompressedData[" 1:eJwUmHc8198Xx22y1wcfPh8+HysyUyKpezOSXQgVRTJDJBJ9y0xl75UysxNS st5XKbOsMiJZyd5k+/n99X48no/zeN1z77nnnHve5Bu3jWypKCgo9OgoKKgP vjVGMrZ9T/rrLHF2dYOKeBgomVus6bsMxAzU5u4Yv8cmNyZeiWrioT9nJu8/ tSVg96K/79ipRuzWqNjeRWM85H1Jfm4ssAiY4j7mm7P0Yoca/PRtnPHw2Y2c o0c3ZgBTbe8Zr4pB7Dp57YjOPTy0UalZnaWbBkclQ3NHJUewQQt+DYI/Hnaz PRrrV5gEW/bMTR5VE9gFh/xfj6Px8Fh+J1PTr3EQd0Hj9YUHU1j3xKVH5KQD nY3fvv5XxkD8cOaAtMosRiv+M6MwDQ9Fx3o1hhdGQNIDPuWTq/OY18JvYfFM PGz3EXFGz4dBmkJC4sUfi9jGEue36Bw8NPXTuECJhkA426pFi+wy1lB879pC Lh425iJVevdBIKGVp5jyeAWDLJWPQD4e/i4bXLXW+QmW8YpY1+AqZtR+sz3g gIuBn42z2n3g5fyl1cCj69hPn5NDH/LwcOaWT0aUSw8gVJQo1wT9w7iI1kf/ vMJDlxSx65rl34ETenjzSc8GZtaTr06bjYfDL4IXOPHdoKOgsmNFfAujcy5+ zJ+Oh65HIwFnWifgnbawYfDaxuRvL9iIpeJhLc+tXZfTHcBvSPnFt087GNrZ Pi0ej4d/tjUlvyx+Bb8VDIv12fewm/pe7sQIPBwZdWIJSGoFAonnL3wxokBp ZRVg8cFBfDmotHPdGoGnZqfZkX8U6NAlzkdtd/AQ1m0YM6V+BmrLd6hXUijR X8bhG+n2eDi9+X1fceYTUL5i4/V2mArxCezpyRvgIWnjaIDLMgIK61Xlszdp UZtGtewmKx6yECMmed5VgurnIMOVhg49lRwnp+7wQSop9ecPRt+BxwK2BIMs OvT8yW2gNMUHWwNw9RlKFcCCdU5A4Dc9ElbGu1/H+CBi/GrpYlgGaq43XI41 YEQiTxkP+V7ngy2P5U78+FYI3NfiJQsmGdHl4KjITQ0+mGTeac6EKwA2X4Jf UQUwIf/f1TWeknxQRr59eDYwD/gXvG6zK2NGLYGG6o4LvNA2JPy/N19zwDuZ z3+9DrGheyuRyga3eWG2RsB6Y20GaGxffMibxoao4L2tFj1eeEdf0rJmJR1s jtJZT/GyI8Pxsxk6krxQ4KGDf7ZqOnhk4LZzNp8dnYA5g5d+88DnTlKECIoX YP3Rh2uELxyoyul57VvAAzODm9P8dFOAl0aZExMzJ5pJeEGwxvFALaMh353o ZHCs1/un+0VOdPmoRBvvNA5yn/GplplKAiszSVnJPzkRdQMIyovCwdNCLOxS nxJBoUTkAO0EFzqu16fh3cUNu2nXiiUpEoDQx/IT/dLcSMnpNMPV59yQJbA9 xvRFPJDL41ddusONxizWiiRsuaG31urfTo14QLdaTjmyw43WuZa/hK5wwZhy QrNUbhx4G/Xe2YKeBxVn/bR6Rc0Fg0Xx5K7iWPAum31vSYsHebOlr3J/5oQ1 TifnqXxigaVUn9CbEB509bk+8WEwJ1TstjWJ0I4FErYcLkk0vGi7rIJKm5oT UhrWnrBaigGeZ59zVa/wojHeqm+UK+xwtHFWOdsiBiT8tBw/IcOHUk3WLYOL 2KGIkOcKvWoMCLvu8hrZ8qH1gNCHPLbs0F9xeXyBEAP49pq9lrr50E0uitbe V2wwVfUMRedoNBge4qpxy8YjkzUTjWs6LDDiXmH18QfR4PBsy64ulwBagbiL qoABDthD3z+9UeBoecSKqqoAEnyWw5uaQA+/lpKG3L5EATrNx4YsNwWQa/RI pMcsHXz93FQxoSIKPL7qQKX2RgCdrBK1LYqlhdN12onP46PAnnKWyTsVAjI1 bmXZ66CCKnTGlPIWUaAkd1PW8goByWt/kpsmUEGwzc0kZBgFuM8kyXd4E9Cg 2ZFvIfaUkMVEBReuFgWC3jMucpQR0KboycGppX1gbTdZ8utIFDjS1MregiOi yRrcXif/Fhi3Y08SpIwCOv4f/BKliEjE2NjT9uUG+CZpmZW1EAk03mQskSAR XTt6z/8H+R/4k56aP/crEsT379RY2RLRy8rI4WekVVCovBcgUhsJTlytL+Ly IqK3wdIGi8+XQYVRjw7T64PaFK/V5BtMRK/2g4Lu8C6BJs87T7+9jAQ3m7k0 bdOJSCcvYojIOgt6kt4tDwdHAjbu5wVjhUR05un+s7iNSRD8RUFRxicSTNQW a3C8IyKgUqzf/PsPsCOLCBjejgT+2eHVd78QkdiRE36T2r/B4F2CCZtFJLiW usea10ZEu6aNspZ0/cBhvaWk0DgS1K34BgV3EpHiuc+Z12q7QDpHQh1eLxIM SfRtM/0gIg6qH0o3h5oA5WnnJnPNSPBK6b2NSi8ReUUcw3m6VYKjosfkHEAk EBVzPM/cR0SvHWc6cjkcgI3nJ4oklUjwGGcV9ubA/rP0OPeLvXdYAGdgyYMT kSBh3OyueA8R/d57KMZl14h9Eq9awx2LBLYDERdcuomIAblNNeV3Yq+1VNJt 5CMBiGt5ENRORHFZEsaFWb2YvzE5wlY2EoSy37S61UJEjplal7zSf2H5haVv BGQigZ+OuSu5gYgenbVO/tc+gk1snmR6LB0J+Pivib2qISI+SdZ7cx3jmMhX 5vLsA649NMW2WU5Eyv9Gxfa7/mJ0/Tbt9w50arpPNOALiCiRTWaatWcaKzI1 Tt4/WFdqxGSc/iURHea7MbPXP4fV/mi5qnrQe6hqTgt+iiEiy9qYFPPbi5i0 ba6H7PFI8ORMn5TuQdztA1QHqZeXMC7xUsMepYN7lb7X9fLgnqRI3hFfvruC eahmuR1XjQSzNjfPvr5ERN/qZLWu+q5jF0z+G8JpRYKiZ5Ed9uoH+80LrHq/ 9w8bWosMSdGPBN2Y6NM5OSJSspF35w/YxF4Xs8r2mUQCkfaiUEtaIqry03Wv eLKDuYr+t+5vGwnygtZx3RkExPZ+PbdZmxKZyhLliiIjwfl50RDTDAHU2zpg oqBNj2qre1shTRRoSzF+Ou8rgHSFcn/dpWdAsd/n52NZokC1YVmK+SUBVP7W I/PMZwbE7XqE35A3Coh7K+Je0QighJby4vOAEa11aE9QSkcBAon7PLjEj5TK VgItpFnQWawq2udKFGD57wu8gvEhi7P3h366c6DljhaPubYoUOSyZXi8nhu1 fZzxqWriQRese6vKuGOAkJHz/vx9blRlZEl7npcXuf76b/atTAw4FfhJ+d1R bnRcI7RM3JYXrUo+vH9ZKwbo3epcvfOCCy1s16w07/GistqbYQkPYoBFmV/k uDMnekVJkaAjiUfr92iYzi7EgB1TY+ogjA2dyGBvvmwugM6ozAt83IgFMWEX imq52VC8CB/d7RQB1FnGG1ZEjANXeh3ZrzuwIoG/zl8zBgTQB++dGF/1OMCv mG6/wMiCPqw2ThlfJSBe3lfnf0XHgYzEyO2J04zIy2bIIdHwIM6rDLbGKvFg bbKk8I4VDXII9TEgHBJCtjMjm6NYAlDTn5iefUGNBG5/MCw5JYQWJ9iK+dYT gM13tlD5QSr0/CbYVnARQlwrV+uzZRLB7SeSxbLGlMgBfD1B9VUICQX+1pxI TwRFh8hnn9nvYO8PBWC1gISqrRqyZZOTgE+JnUp01xbG9yHeKdeEhIqkH3Mo DiSBmOfeuORTm5jMUXzjvgMJaaV3g0nBZLCc/f7dOP06tnhflbARSUL5h0IU nxQmg0S66gu0PAuYYX4R1VQPCR1/GmmnMJAC7rjntOq3z2B1uffHJP+S0Je/ /EVC0qngWnXim4DgSaz7eip95zoJMfq8N5V9lApYIk/PHpkawZTLKjUMuMko wYjrzZrUcxDqzREL1T9i6pliM9NaZKTI0cdyJjMNTPj/lTXXz8K0zn/i1zAm I6cHRu/U6V6Ak4NPBZl1SgGjw0O3HUsyGsrbvcXo8gKsLoZUhPZ0gnENBccQ dzL6qvDY6pT6SwDJgsnigRPg1p2Mr0tRZHR9vikh6Fk64FlYP5J0YhrYxSGa kkQyYi+67Wr2LR00N04yGM/MAVfGdvm8NDK6Ov5JVZ87A3zr4TXYK1wGoy+P muvmkpH3n7ngjVcZgOm3uUtryCoY96obXikgI/XyK/SDKxkg9PDF2kmbdVBj 2eH9o5iMaK96FJ5RzwT6p1JnINwAtYtqDxZKyEhYEVmoxGeCpmGumDrCFrhN FWN4tpSMKsz0DaanMsGtvDwlvc1t8C5w/HrLAT9FamK5dTYLWPfKXfz+Yxf4 7LGLPDvgUXxh8T9Ts4BQKI/a2bJ9YFxWwev3hoz+WzluY76ZBX6Wxbw+00gB +4TPfS58TUY/7+6H017JBu8TC++crKCEYR+Ya5iLDvg5+UGaumxwqleDni6L CrqpwfjMPDKi36j95SOWA96wSUxM/kcD0zgq/W69JKM4dZZ2u/0ckJ09f3bK 6aDfxzsupyWTkXhyyme5O6/AB8Ph6EgzOlj8N4SWJpaM/lpW1uGmXgEp9YmF DDkGOH5L/phTIBkdrQyk2xjLBU4jWu9z+5mgjtbZ3JQrB+f8SJv2L1cB0N4O f1obzAHzbib5PBsloS479uuv4kuA0jz98e51DsgoV+S62E5CD2rVm2OPvQFz 5Wzohj0nDLvN2PGshoR4Ojy689LfgJNaq6z957ggHsducS2WhMxVcrbfPikF ukEt7sF73PCaxKtz4UokNPPMqdcisRyc3zFvX9Hlg4HP5i6SKgTRrNzsSZe1 SuDx4jEfXRkfjKmIWNvxEkQf2xKaZ758AB/34pyUefHwSEjQHTMlQRQ0c2nP IbMK3OC9lzUxhIdTXMNr4Qd9ibh7JaP4fg1Y9OS+23pDAKbvLYSeTiEg4cJi vh+WCKil6uEwJUF4Kb1O55swP5qPNDv9S+QLuJp6WMYvRBDiG2UHLLrxKCLs sZPL9hfwJVhqXbZHEC4vj63UBeBRbSvO7tevRvDU5uEtNTchKP1MyI9hiA+l SGwwjH9uBr2uAhYWuiRI+giYKEJ4kQP073p44hsgP3hXWOJKgmH3ZN3vy/Ii 52fZvp+924HCmrOEXTQJ/pKtyPz1nQedgiIZzHYdQDv/ttXydxL8M0Z9xUOQ B0UU0I1sfj+Y105cWjptQoZBs1yfFXK40csmjzaJoz9AZHv+jtUdMiz8+PKd lQY3Iv1jooPiPUBV+cibzkgyFPzvhlr8KBey6JY+0SLRC2rE2O9ENZHhu6bW x2QCF0qNTD9663I/KBGOLZE9Kgxxd/b3TgRxIB1e2eF1/yGQm0bz0klbGOIN q+4cInCgwdKwfo/t32DU3u/cgJUwtHftuUtdzo7GCRppLJ+HwY7qw0a9cGFI aF9/TVHLhgKTTVNnPUeBYi+H3KFBYXgyHQJNc2aUTjNsUewxAe7tKrMHzQlD F9ftH7d8mVBBafk8ddJf4CWnP8e9JwztJO5hcmmMSLvUsKShbRJEl1MO2BFE oHmy/lzVIAOiy719XPjWDMgw5C0SPCIC9fXlApO26FG01U7kq55Z0L5ya73/ hAhsy5Pjgrz06PVcttFN03nwxIVYfE5fBH79BioI+rTImd5Y4GbrIqjd+Bk4 ZyoCs+yztZzsaFBf/PnDXUVL4GmSaU7AdRFo8qGhv+whNdppHAqJSVkGi1P5 BhT2ItBIrdmFOoEKlX8o7jodvwIKaKyeWbmIQD8mXnPHIkpEcPYJcktbBc+v 6cul3RGBpYfXzy7XU6BNprOJLeVroHkn5HeJlwi861Jvbl68jwk/oaZe6FsH Jgp36WPui8CQiTMTOj92sXtxl8UDWTbACV2jX6q+IlDJH/+yf3sbqzxVwiZr tAm8o0nW+QfcszzjnTB5C3M+SShIzN0Ci5yYRYePCIw2ihPX1NzAGESlWu1Z d8DMccubBd4i0EzJusLKYR3jNaYhaIbsAqZOn145zwN/bFl34p+tYrys1j+7 OfeBm3HyqLmbCCQc071FV7SMbabFqvw0p4DVttf9iU4isLmu78L3tkXs+i2n fahACTvvaQebXxaBxW/LL0jzT2NzIm+u4mioIX/G2KE6AxEo9lnZ9dXlCUyI rtCQYZcaNsfWOqWpiUDhIp3t/aRRzKE5T3OLghYevXXqzSsxEfjqjL8I7mgP NraiPJ5whB5GjKI7M73C8OyF5ugjw3XAse2Z3X16Zii0+luMt04Y5k9oXsBF t4N2wYR6PW8WePldXLpYpjAsVORZZ+3uBRr6yW6q66wwatRotN5GGDZv1jQd mxoDn++/tlxi4oAb2gJ3NlrJkE2yh9jcuwSu8wY17N7mhp4jy20n08lw7FTn HdnmFTAao/OBzQQH6WZqwwQP8vGii+wP/Ps1EImbd9c6xQPvSpsyNbKSIWHD U8czZBO4Gd36PsPGB6s2yz5nSZHgbJIKk+N9CnjG5YlX+jsByP9X8zbrTyFo 511328+KEuKsVm+IJBPgwKWaPwbmQpA2n5ryqwYV1Df16D3tRYTNoY9hnpYg PBX2ni2IhgZqRP34iviFoO6xj1epPxBhf25VaMlvGuioVrBv8VsIcqZmJFmI E6Gyj753zHtaaKdw7JCfHgm+br7e1rAmANnEVryZLOlhZn196/QyCf4+kfrg tLkAVJbNF7p1hAHeTr7aJn+KDG25CeYh7/nhBdr4NNwqAyy9wPbO3JcM7bcd 1Ea5+OFafejdlQ+HoPJuFGtXGRnGxI2uRrvg4b/pFz/nfRlhyGOvJv4RMvRZ GQ391cAHa0qlO1dOMkFTYSrLetqDurOYy8rGzwdZ41hOL64wwalyv247kjBs E9ScvOPCCyUkGra785lh+zZnOJIXhnpGhItmGA98pby+EHWVBZbziT5LPiEM 6WojKpjYeSBDVQurwCFWyLPtF9J9UO+6Lbe5hq/jIMmMztGhjBXq1a1U2gsL w6n9T2aiJdxwVr/liLsZGzyqzzlqxyAM45n4Kg7vcUG1Q6rP5TbY4KFyRbA5 RoZ3GrpplPW5YPLUS9YLOuxQten3jmUFGbaPPDiS8ZwTTvKQwqwS2OGj6Xye 6Qdk+He4Gqaf5oDKcdV0zBIc0JWu1/DoIgniIrfJWCQ77Chd0ihw4YCFNx7t rz0nwUEhsYzIL2xwo6v+yOFSDhj+031p8SwJ9qzayKwLssCqcY6WtqOc0FPk tKH9vCDMUR8TkaNmgNdViTqW/FwwnyWpReecADTYL/mb3UQHrcZPPPAz5ILs k6/tfunww8bTV+gexNLCf2yl4mUBXLBvp4rCQRcPD8tXJn8/SQ035ArFrMe4 4AcHveFJTV5Y3FLeXRe/C5KCfNj7I7ihBSNh75Q6F3yr3raU0zED/i7tfgiL x8EfHfv4j8YM8PLsHx8qw0lAp+zqS1WCgyev2nV69tDBh46Jq1eHxoFUTVwD VyMOyvDsbdE60kJO9+tqflcGwVnm9BHSCg7++9ukJFNHBb87dZyZCsoFx7xC 7f87yKs86ylClt4OIF3PCKXTz8eCbSl9HXV4oLXEuCiT/hYwrGrGpV7+iHX7 mXfgzXngmrLmxXCnDZDpdOLl+PJ3zPuBQ1jPbR6Y4vQo/OLmKrjmJ1G5++0P JhUbyyAYzQMLZuU4heLmQen6Q+21yEksbOlTc2gCD0wPMudQlp8FsxsOKm+0 ZzAt2zX/nhQeGFcs1Kq/PgVunXbxTt6Zw+auSVlTvOCBkmPXNFXH/wKXZIbg ZyaLWNzfxy5M6TwwqqclauLfHzAbssWOcpewVNJc8OYBf6ye//Ck3Djo42ZN 49tYxga/5t9sO+CFOW83ZJ6MAnnneuEazVVs2swoM/glD1znu9/XQjECHBnF Xduj1rBLWWaV4mk80OZVz6Ke7G/gHR957G7/OkZouE1dmswDi0utcR0xg4Ai RU+uWWgDc7VW/CIWzwPrro6tRUn9BJJ93OrTNptYxfWnUo8jeaBsST8QX+sF y5LmUYs5WxhHRN357ic88I9S9Cu92R+A6ft08vKfbSwlelSI1Z8HzvfiTf6y fAefGP7cpBE96FvevzOUvHkgbegeA4VZFyh5rRKemrKPPaIbFrpiwwMDc0QN D+d/A25Wbk0vHClQfaj6BxMzHviD3sf4E30biJ1SdeOmpUQYqj919iC+V5ob eXLSm0HAqE3wo5NUKGPsaeeyNA8sean6uOD2Z/C1zKzct4sKTf65Az8QeGDl xf8iy9I+AdZGJZECJ2r0+ry70V0mHoh+VOQ1rNUDc71zs5lJNMjpo/xSyx8c PMdz8wxZpg5E+e0fdZWlRQoNxxrsO3FQkquvSb2sGsi9Syxw+USLgj/MNW1X 46C4MaD8eucDyP2r/5Vmhg4ZJTPtM0XgoF/QRWWqmApQWtQqe1X+ELJp99n6 LYaDDAOEeIWMEvB7sPdaLHYIOefPymkfwsEc4Z23Z24VAyNjJ6pZfUb0osxP vmSGG7o33/t91qUQMKhWOM/bMyGZp6Vf7xZzw8kBbOkhTR4QDNOd+RDFgrhe tDXviXLDeYNvs950WWDn3HLnfT5WNGYb52NHwQ3Zk1xxplyZQP5txPPjL1mR 0xUWta6fXJCBc+3RV+UMIG2spBucz4bYdHvsqsK4YExn7mBsyEsQxtpY7NvH jl6pHLk7N84JjfzW56rUU0FEIlmgiosDmStTP0uq5oTivfambn4poLUS99TD gAN9y5f67BbNCXnziGIc7clAK3JrQf8jB8oauq9YrMIJHbuOW+BTk8DFaxcd r2Vxoo4ut/B7gRyQ2ryZ/cSXBLB8psJV4ScnMt4tEi025oA3OALqfzgkgJlU 1vuu7FxIvcGwBS/CAXcflIoIciWADnkjGZwvFwrK6u1Mw9jhfTjOmeUbD5Je 9EUOnOdGsSXfZVeG2KBuwXtkFRoHutWlZF/7cCP9ZI8rJI+D+mp/QSPwchwI Gb2u0lPIjbi+yMZ207LBX1EJM0tH4sCDy9yxRGYc6i0YvtIvzgo7Cy9pefbE gkOWr3d0GnBoNf4Y10czZqiWUsVM0I4Fu9m0X89w8KJrs3frVLwZYAGnjn/D vRjAc65U1UaJF/0Y+aPkuU4PjyaK21jfiAFef9phtQUvcs1AWe4e9BAzlL3Z pR8DOtctLfayeVE1Wcqm3pEOmgcKCu2Lx4CJGYmS51J8iE3+CknpPA1kMXPJ dhmJBu57XjcldflQfmDAze0aaljE/En6WWc00BQ/wzjgyIfSJY2O5shTw1Tq MK7jH6NBKdvqlVfZfGjmIrNKDTcVbONRGBLIiQaGFkn8JWx4FJNAiN9N3weJ 706Sm92iwbXLslKKEnjUQ1a8NXN/D1xXC1rvvxkNnh6WN+sGeDS+JGq2fGEX 1PFnd1y5HA3OXWI+YuSMR6llGZfvbm4BS6X5+iz1aLCv1JiqUIVHe7dUPzgr roP1+DgzIWI0uPfm/FGjVjzy3ESq5yjWwE2Kh1a+3NFAXCiP/tEAHgVM+eDC D95df0YQWYU5GhTSBuVtb+BRd69SSoTZEvilGBY1sBMFzke0bFpJ8KNUCYU+ +c+T4KUHSTR+NApIM3DaPFPgR46UV6XXWSaAPGvQxXuDUSCjxYo67BQ/yqld ohwyHgN6UPjP554oMFvPrMSlw4+0d9REeEsGQNy1QwU5bVHg9JflqARDfnRd 5s8/vFQPoFp/Ua3YFAVqfvGVzBnzoydDuqEXMjvAtRDxZbmGKJA6lhnHa8aP 4j8fo12Q/ALi5iPGY1EUCBnOu8h1mR8ljSYEyrG8A7rVPMrWtVFA0EOJeviA i4hWdG3fNcJwSgUvE6uiQOtjm+4HB7wmLvmu4pt3mJ6m88CJyijQL+e2OXmg 79Kf4fww5gs2VmtdeeZdFDh6+tsHkUsH/niAw21THdgLb3r2krdRoJRF2k76 Ij/yN5R+5Bneg7lH0DeFlEcBm8UUSyo9fjTT1nBm59gglv2TpaupLApM6UUw 52jyI62Y5PCo+WFMZyNI6s4Bp/7v7yzXGX7EuOgEjRrGMKanjr8CD/j+af7H Bor8KAqP6YikTmBiFKd2dg94xICUi4kUP7r0pSpt7M4UJpX/PXf4YF37nSoN MRI/Cg4RZ/TQncVCey8xSVdEAa4y4VrExY+quFPPloouYNL0hy2HD/Yly+AT J07Hj9S7KGbP7C9igr//Du0enENTXWKC6T88ejkYIGzhvIwZRNj9CqqOAmcu TURy9+ARTeH+7ua5NYzXW7Smoz4KNK5L3sz8hEeCt3l+Xn67jqUvG7gmfD7Q l/MmbpXgUVIMN0cJeQOr/nj0bGNzFNjYIMTSB+PR+un1wH/bW1gB/00n5+4o cHZUauolCY/0nL5yJZlSIBpDa9AzEwWQRemoPw0e/ei2dlJkpkSdJk5EupUo sK7u1yv3lw8xkGbWntVTIv93ztGvtqLAjOzR1qU8PjTyt1fhtBQ1mjRr/qXK FA22wxwzhAT5kNGt/cTuTVr0IHHeYOBoNPggOU893M6D2Ck/yrg/YEKrVq5L 8/HR4OFlIfqhdB5UqenJny3JjAw6cJdLs6PBdz/qgXduPIjVvP/MoR5mlDA5 eWKz/CDfa6mf7zHzIAWt6fnz0qwI57tTSvoeDU4110tyKONQStkY54AdO/rw 9d9xOoEYcK7ULvHzZS40FiYrFTHPiRZ/vGmW/BwDGnd5Yp4SudDEQIbHCyUu pDp3PjV/IAaE9o4L2g9zopsX5/0IflxIWajdBFuOAQM9JGMvG07USfOF7xIb N6rOwlG9F44Fh22ZBQSucyC5B/9srovjkLXGcInYs1gw9uIVXZoFK2ImnxMh HedFS8ifveF+HKg2Y5FUbWZBb6LIYvF3eJHSzecGbKlxAAtYjzQ6zoJChAtK z73hRbmXB4bEag+45kL3Bi0z0jRd7DKW5EObf3A2X6jjgSP9Ykdl4iEk+q/Y 9gsHHglnm7OZpcaDPCWmxeL7NEh63rEw6wM/0n8k9dhwIwF4mLw+fryDGm33 c/TFTPOjtqAjt15LJAIvA9+bT8SokZK6sEwsvwC6/fZ21tEriUBbn+hb1kaJ 5qnmPGvvCSCktHT5I0oEkg5pmu4Ce5hXZpWepzgB/ZHfPD/5PAkcYs0MkkHL mP2lDN67xkSkHjFXxp2cAmZ+TNt16y1hF0/q+Fy/S0RluDNnan+ngDFkbtNQ soBpNV/xUo4jorvnWFfIEqmA8qM01VjXFHYRrxVf2EFEH1fdSozqUkGiS5eb 58IApv+fAKuNqiCqZd1g66BMA8cVfUxumH4HXGFWgmm/BNFk6+ahreWXgGL6 Esngwk9QIPYZpz0riI5XV45Ly6SDS+X5oe7iw2B5V8X++6Ygmm1sVTh2Ix2k 0539ECM+AUSeXjIP4hBCci2VNq4d6eDJx4/m8hJTgPS9tfSVgBCy/GS38eFQ Bngd7Oz05sgs0PUU7s8SFUL72IDDU40MQPjWfmaZbwmc6zfzPnJMCNUt7GtP 1GWAzp+d6nKpy2CQRWavVFkIDR4PkI/YywAvcrVDs4ir4Nv+Pxf200KIdFlm eh5kAlm7c/dg+hrwvRExpQGFkCIJx8wbmAl4pEct/wn/AzLPnqcZqAmhqobv CNeUCZT2Pjz9kLMBGnEV9dLqQijRTat9izULnIU3VbwltsBj2htJQwf26FdJ Ro9ZFhChHcsWLdwGHE0qt23OHuzLLUG/KjMLqLsLr5bI7IK8kLkXVWeEEEv1 +dT3C1mg1sBDm+nNHuCZ1wkdUxFCc+79LCNnsgGPi/8QF54CSpqbZP1SFEIm F8tmtKOyQektQ/63KZRQa/WbjrqEEJL2HWKSUskBTN4KCUdTaWCAnX1m054g ciizG4stegXUXorWRl+hhRUJKU2uS4KIrlPDg8CeC5opNHUT8HSw4rCA9Nio ICLTn2l44ZULeN7euuCaQA/tCSS2Ex8FUaNDO0apnweO7oZ5BD9jhIac+zEB dwQP6tPz6pfCBWDnrqDF8XNMMNGIKj3pqiD6ONl0TT+jANBVHh7XoWSGXfmv xx+oC6KdZxVfN0UKwfNHy2ZRniywpaZl5Q3bgZ/fC57MKxaBTKroN91H2OHh Wr6R9mQikuAj6zNFvwYuGhOoeJ0Tqq5M3zH1JKAgi9slORJlIGvCUHTzYO7u fH0PH6hLQBOkGxZesWVA5+8D7+psLnjXK27xMYmAsJYnfAxU5SC8hqUr/gI3 7H9yVYCvUQDtsX7T4pwpB0XzGRlKGTiofQIf/JBOADm/EDQuWKoAL9mzYieE +eBtG6VAT0M80m7nIIzsV4HkzSsB1734YH9HBnUAKx4V/Mz6I91eDa4OG4ov NvHBCc5bV3Xa+BAdb/nQqdwaIHU76JXmLTxkquRN4tU44M7zXNc96sBlA/Ho 09n8UNM1U/uvKC+SHWPdT9CoByqHGcUWF/jhS0cCG+4nD/omeSx96Uc9+HZN sTFORQBeEbzgzxnBg05zH22qcfkIbicq3s9oE4BCH7uyQ5ZxaITw4sNS6Sdg NvbvP80xApy7FGxeXMyNOr2GrGcSvoBu7k1bWnEiVKnI9S64zI36i9y+NNg2 gsJ/quPR9kToc5r5cSQNNypnOesgcqYJaLav9u9OEGGJVuwvQTMuVLnGymnF 0gJ+81rnp/UIQt3oZ8VvFzjQMjvtXtPxb2DRalXSQYUEW99EDuPGWVCeyepF ndTv4Il3oiPbRRIUFRwJ9iewoFRTdi8Zjx8giXrcad2OBKMA++OTxsyIanBJ 9dqlHsDwlyb8fhQJ/iZQ7ZRVM6IYgueXLJU+sKOjvsD0kwRTqPAe3ffpkQKd TnF54iBI5ubZd5gmwf+8XCPzcujQIF2eXE/HL+AoZ9a/uEmCU4+e0fJ20CLG JDrDOr7foP749G9PHjI8i+sumCLRIJGHd9RrZobBgs7VflpNMjTjvn8ztpwC XSobohzkGAcK1SX8TgZkSDc8YYYV7GOHnsjuU62Mg/eOz3lGTclw+wNtnMrs Loal9SdcHvoDLj54uUFhS4bHApgIyo5bWFQBgLw//gKipGJmhhMZSjn5/5nO 3sD6QnrF4cgksPIpDNe+TYYfXr2/PDK0juXbs/kIbE4BJdHRwLU7ZMjEZ/Xu OO8a5oxfkzhEnAH4cGONTE8yzOJbydjTX8FOv7ButdefBXcHXwXr3Tvwc9Bc +nLgEhZ2t4gu7tkceDBkur54wKUWBNJrXRcwN7qQ0b/f5wGxwvN02AHvTXn3 1+T7DPauxYnakmcRqNOXbPN7kSE18X3Pa6VJzPmwqbds8yKgu+LaluxBhnXn 7RaokscxA2dFJrbAJcDAKa9F60aGv+yWop9uDGPEPb57whrLoL0vLSLu4Bxq v7amSth1Y4FnDLFrgyugv53WV/46GfKozazPH2vGnLmHX+JyVoF7A7bXYUaG n9913vsm/x4rlrY/7Xh3Dbwxre/lPkeGYURnc2odDOQElvswH/4HDhUiRsuD OIYbf3GvfzICqjs/RAoObgGPAnburkASXCy3MD1rsA4q/jO+nfGOEpryc8xF OJPgxfGbQ1e3/4FqehncaV0qWCk8lixjQoIdN7XuSOduAjcbZsXmESpI/8oH x0IiQYOF7vu+Wzsg4+aU9WsuGphnUKqVZCIE5yFe1uALJXQaKxhUCaCDESat PxS4iPDcNz2LRGEGWJt7hmLgGBN8M5rp51BPgINK3xo3/jJA7T+K+/S1TJBK eD4jzuWAp77ubis8BI/3mZq+OMsMI6/b5G5iB/n+6bp6giwTdN3AlGdVWKCu wYa/tp0AVLiYsek2xwRft5ejxNcssJihvqqWUQA+epRF8bSAGT5xunw3QYAV 1qxNL+sY8MMX7A8P2g4r/MnkMBD5mxU2/+gY85/Dw8i0eP6GHlZowBHwO0GR DUZZB9DgQ/HQjBQsbxrGBuseub9hCmSDAj+ijhbV88GvJ/7Mf/Bmh8X0R5AB JTv0n0KEtit8kOMkDbdnBzt0usFotY9nh1ptM72xy7zQ9OJpXfJhDvg3cImx SIYdfl+zrON5ygv3czdbPzzggLFf/8opqLLDumzaFw6CvPDLlAaDSicHHFpb H7qryQ5/fK/JTivjgbvFTq/TRDnhvOQlQUvtA54iqNeiyQPpczkKhr04oWsa m/RPLXbY59quQd2Hg8nneMX2GzlhwdmHpSOQHRrqX7G2dMRBBiP1J2u8XDAt JWX69nF2SL323G9ukxuClwO+yI4L/ptG9SHC7FBfr+Ve01NuWD3e/9fiLRfs q+jrU2Bih4VcHyNLc7kgQzOi3dflhvwXS/C4ZDZ4T+ud/aQiF5z4IvhpP54b MtJLFPTosEHnlfKr1Z84YUaOH2vTEDdU0wp+G7HMCv9KpWUFDHHAFC8h+jxn HEwRV6U5KcYKI9Of0kdzssNQ6jTOR/d5YPXQRj5RhBk2x2X/RyXNBlULpqcm 6nhgzpbOdcVAJtifyNGneowVduTVcPyg4oXC8bbN3wcY4VDOxIKmOjM8hAhW 6o95IW/+pXsZ9w/Bk4/XPBudGeC/VZbXzr58UPN5zFr3AzqoSPnv3e4aBYQ/ 8d/ihPihgLX7yZxzFFDOUT7zHzMFPF88xZqqzw8ZMl4XdbPsg8YPP5Kf6uyB dKrQ/WM+/HCx+YECS/wueCh1Ki61fAtscl9nEmnnhynmCbihqi3AdtNKnzl7 BdyzKeXhcxCAohxFdmZea+DWk3OUXHW9gJEuhFPbjACVldPeym1PgZ4ifr2P tJ0g52PO6q4rAda0KGzgNSbBrZjtzd+5DSDDNiLCJJgAG+f8OgyzJsC19xtc ijO5GLVrbchkMQGy8QR3/socA85s8SIrKp+wDWJ8pDgiwJKoBGlZtVHAzSEa fkS5A9OnrM+g7yTANa/pN3VrwyAq6ny1+bVfWP2bxefl8wR4oVJ/nSD7C3Bk UQyT10YwwbT7nx5uEyB1xcbwCN3AwbywRvNd+Q/2nlnZfY6OCLd3zsZVUfWD /yIH79Z/mMHuSlk6V+CJ0N2hFN9q+QNMsQhxkP7NY3z9OgWsZCJciXqRzVTV DUxDjqxD/BJW65NpxHSYCN8eh7Zex7qAMuO41GbFMsZBta1fKEWEF/pFLkc3 dQBy13O22ourmMDhCL95WSKsyiQUfV34Bi6QwlsiZ9ew1mnd1u/yRHj+7Jwj q18bCHiQre/x+B8mNjXMfO0oEd7Sbc7nBi3grlK/mYPQJrZnWyv87MD+tUxV P/lIE6BTnXjk+n4L++TAM21+oM/DVioXeuYLsAjfPxVksINdujwEW44QYdvS RFz1/QYgqTY7/Wp8F/Nmr6IbEiPCU25cJxX7P4Ld7dnfXff3Maetv8Q4ISLc FBXJiLlSD05NqbyjDKFA0zsizrO8ROhKVDBg+4eBmzgnz+QLlKh5J2hggpUI tSjirjd41ILS7SDbYjwVMurTvBpIQ4ScJr5d3IerAV0sZ6RKATW6nH3WPnOG AD/r4Om6ye/BO0GMVOhOg+4fjl4W/UWAYT8c305bVwBulpyXj5VpkefIp3Dt rwQYn9Juv9hcDmY+JQk6NtAhBo5Nvfv5BDjzw4L9Im0pMH1SxN8WTI+sxRLU /sQTIOOMG0fImxKQc/x96NNzDCjmnIAPhT8B6podKtENLwa3wkcub38+hBae 6T3XNCZAT6eSHsf+fGAl9XIpM4gRvS805nNTIcCzmZ3xQTAPGO6rPwhVY0Kd QpWbOiQCNLlSabn19RW4rlnTTV3DjLp9lcK4JgWgotvggziDbKD2Zcc9+B4L klhXlKJqEYDFOWUnC05lgTvhLsVSCqzIvaubKatAAHJrEuTW1TJBUK3riaZs NgSfhPzbtReAa3clzKMS0kHY6ycTioADefbOE6W7+aFjyaKEvMJzcDH2X5Vg MgeSOM/Miwr44ReTKknhU6ng/bskSt9lDkRNNeXF7M8P8ZsNjVJXU8Atg5PT /2Vxoga7Pv8uSX4oZlIVdK03CWh2iqeq7nGhr0XhD4854+GALhXz69AEoIdu pVww5kbDN8dpC07iobrWk4J9ngQw1rY+8D6XG5UqsceN0uLhflu5yWphPGBn kDrkZoBD+cr7OS9T+KDRTu6nnvk4cEq54CNPLA86Wb677FnBC0E+A8OVj7Eg uHkqyGSUB/G+uvxC4j4vXEk4L4ECYwFZ0zL5szwvcsTUQgtO8cKMI6fbJbVj wW+bAmaFVl4U9a2zX6SWB2a8E315bygG7PnYpTWu8SEhucwzYmW4g3psxGFy JAYM7ma8ThAUQE/4Uu9fPugXl2av9f7AR4N1xsoL8LoA+pmdaU3DxwVTUqQe +u9GAYnFlZiRFwJI0k2kMquJExZe3zgvMxoFovG3yLv8BHTDdGS4RZwTBlWf 69N9HQUg0T3pJB0RTVV4XGPuZYdPTvm62FyIArQ9PteWcwRRr7pnIJmbGbI5 JmtccIoERtRfzrl3CiKnN2U2IbZMsPLkpzw63UiQWzcFh7YFEafqsK9HBSMs 8SmzKJaOBO2WoSb39YXQzeqncWsXDsHSXzn3K5cjQNj5vuteY0JoeZeO+vw9 OviJavvihacRgP1M5z4XNQm9I89jwbW08EeIAuRwjwAX39qdGuAiIfjVefM+ FS002QwwybocAeRuEqlKj5FQnN6axssn1HDk0q9wOZkIYK2Yfvq6MwldYQi+ G/OYAv6Y7DPL+BUOMht6K9nvk9DkkkKJ++N9IJxleCarNRz4j1mpSgaTELNk lFzc7i5gctc3tKkKBziWSyxhqSTUGcRNFf1nC7TeP/2VJyUc3Hxe/ZOqnoSM 6gzz5tNWQf6EYp/gjXDw8G3OvZ4mElK50HrYhX4F3LX8OT1+KRxY/VpjYuog ISlz24Cjt5eA74LRNUudcCDPm+sbN0hCgXPXXod6zILURl1pa8VwQHxdiJsc ISHWLjdZu5NToH82JnVaKhyIqXmKpkyQUP57PZ+zO3+AvbhbnLBIOHh1h86S d56EhAhkOLY8BBaCdYRTucKB38h7j5FFEppxvklL69AHWrJabX8yhwPnLVw/ /QoJTagc9ufr6wQTyDHyM1042PIy5Xy2SkJWLHvHKh5/ARXF0qIWlOHgGndW gf0aCS14WsgI55WBH1m01Wk7YSBShXws/YCrlJq2Uqq8xLx3s3aeboQB02tb ascO+Kz48t7HI/XYEoNxFmktDNAh+3ukA/3Ch5d+b3l+wwKm//pYL4eBhluV HvbLJFS2VeihOP4Dy6XIsdJbDANtK5dG6A/85+MaaGyJGsRG+UjqI/NhQD20 9TblHAmdy7SRB+kj2KOLisKkA36s4dt34ykSsvUp8HqyOY7d46dhO3TA5+5q t+2Nk9Cmmasz2WQSM3mzKvX8gEeLWvBRDZPQ5e9fxadLZjB44nVR/0IYqPSx 8bf8SULVun6pH5kXMIlQ/p76pTDA6s83I/CVhAoWVbeixpex+2NG4bH/woBT 0Fzqw88kRDDJ4jset4opXOrd/m87DIxPMrco15LQusKsi6DGOjbNlv6dmyIc bD47rFFecHDf7LKCQrI3sbzoQS0dpnDQQsx/if1HQnrMCWKLChSIvdro3ZRk ONi4e3pv0I2E/Pfzjm0yUiINAY6HesfCQR1XddtFGxJ6am/JMz5KiZhrqsJv nA4HlGW6MmrnSCjct4J4JoYaHcsrMy02Dgc3Kltj1WhI6OjPzC78PB16x3ky bexJONAe3m4WHBFCFTxTfTd66FH0H7kq0+RwYDG6FC9XKYQ8+sz2lOsYkK1V bH5BQTg4Rcex9MFaCF15Su61DmNERyh6A/baw0GztX1yWKYgYr4f8+M+mRU5 aQ5lvhSLADX29rdVBwmoK2E6tCyGEx1nUOMK2o8ApldYH3U8J6B87caFWgou RMmR7W4vFAneTB1mXLpKQKNPvruquHKhxRf9IdYwElB0+13//UMAvdrOSHXX 4kb8stMDRcGRgPtV1tPCSn40bRzhpbmMQ/O7gqu8bFGgS/EtJ7sqH+p8lft3 XRSPeO6c+ML8JQqoyXon+0zwou7+14yZIXi0sMhWxDAcBf5TfNiRFMmL7KPr i25N4dE1Fb+yj1tRIJG23mfnFw86liTx7FwBP2pILvUOUIgGq9Lvn3+4hUNN vbdpokkElDAZ+bW8MBootOXv0BtwIpHPwSznBgSRjAk+JqE5BkxU9Q+o/uFA hCrDF3EyQqjQhUFleCkGeMh9Cbb05UAXGtQ7Kh4KoSNhuo80BGLBc0MvhzvZ 7Gi9+MvxElYSSjkm+vaBeywQWpkfr/3OgmrNzUP/5pCQ9qb40nPpOCB1POeO TAwdgmMSaw1vyUjosdlf24l4MBh8zUqkjBYlPXHT+a+TjC7fYuhPJyUAL7WV 6PIOGjTZ/3Anfo6MbF8SmB0sEkC3enXBx0PUCMt4/GRURBi1mvXktvUlgMQy H9u9vj1M+ITIHPZEGL1qOslvN5EIYtoWnE1odrEk78o3RunCaHDt7pV7sklA ZoDW5obMNtZy/3yQynthJMZGSXrsnQTcY3tvT3v/w3wEy8k0Y8Lo8tLtr8Oc yaDq8Fk18sICNuTauHxVQQQxWeaEx99IAWpXxR/gxGaxKdWAFg8NEXSKKK+b XJMCuPC/A6LNJrFmWv5fPZdEUNYfra/K+FQAPnY9KS0bxkY+CwEfLxGkwvNp rPBnKmCsYCkUupyNiXUInOQrEUGijL4VWv5pwEJL13R85C0wUZ3fvVUtgmRS XSHDShqgeabf6k7ZAgSkQT1Vowh6Y2z/TtPhBbi9VXJsOW0Q1FgcyVkbEEHx 4nZJHy1fgvy7p0nelPPgxlk8rn9HBL0X+i3gU5MObghs1HVtLIIjKWKd0tSi SGLgGbU1bQZQ6oq/6720DCSz+OlqGUTRIQeKxvwLGUBs1TAleXoViJ7wo37K Ioqa5HqzXF5kgEPd48HC4+vgbI0cKYpDFI1JnhBqnM8AJ6JYfPZ/bQD1Iuuq Tm5RpP1ACN91NhPIqDDkEvq2AI0RpqTPK4o+C++OFCZmAttWFSm7rh0gJOpE S4UXRYc1Eww9FjNBBfc3rqa2PcBLR5u0cMCtKoq6z+tlAS2ddNlEGwq4fBjd wvGLoqDHxXEGhVmAsLh+/6MVJZQYdaTxOLAnnbJ+mseSDegijH4OWFLBAWrv OXo+UcTO0Bb3wCMbKPmkn+i/Qg3lAlmrunGi6BHGn7U8mA1SzFNc35jRwFYh RtoeTlH0MC2k+bhODrg2Q3/VzIQWmsqyubOyiSJ9fIvj7eocoNtyOnZGjx4u hM5ZkmhFkXSL4m5owSvQR3fereE8A9y0P6+7uSeCbpM8H3dL5IKGe82iGhqH IBb/WYF+QwTtHMll/l2YC3DYh3VWFSbo8i+OVP9XBAn7/D0nW58HqjLx+qVC bLDow52w/FoRhJsYZZ6SKwQFsz9Jh2y54Iq/FdN5dRF0V7Jdlar8DYjpkHrU /pcLGp04L9smK4LYFMu4i4+Xggr2cLV9R25YlXMm4AZeBPkuLP2JrikFAvp7 h/0O5nBJ51KLxhlhlHgu613ocBmQC3WU13XkhTJ1SW2PgoVRDz050SK4ApR+ NXyaPsEL31fp8WY5CqPcbFuxbxrvQGOfko2kDR/0/epG90tPGD1VruQ+z/oe qDJ63K66jIdn3/xcSGQXRkLd0RZL9ZXgSfz7QX5VAchcOuCiFk5Gy/Z5fxTr awDb8csa+mUC0DSRTHfMiYxkzoeHfvxTCwhMwPrBYQK80vK+7uw5MlKm7Wum EsBAWO3psbcH81KdorJq3TYJ9YlGK5OHEJDRfHm4pV0QFtYL/TW1IKGt8G/3 Pu1/AsVGn6X5mcjQZdrB9/k0EUn+tGt3ZfsKtINmu51UyXBO4veJqKdEtJjx 4hFT2DcwwDE8vudMhp80el4uiRNR1Uneb5QcHSDSVLRvuJUMo9ai3rNYEtCu w6/Lcx2d4IqRwmFuP2FolpKXJvKeH029E28t5+sBVzp5ihkKhWFezev4HW1+ 1P9mr5Jk0QuMFsxOEH8IwzOlvnT2A3i0bTZ71eddH4h/sncyRlwEBq65ddBs 8aEGMzUttfcDIEHWQgVXJwJLtpdJO+K8yCEvX/xJzAhgMTq84TEiAhWOplJv vOZB2qJF1x4UjwJNPRbDz9Si8OzyzfAyRR6UwFI9ffvXGLCxClIX1RSFP/11 4v8DOOTlSAdxgRNg0+r9eZGbovBxq2di6kduJJo5lu+78xcITtvk/vMXhVz/ GRnEanAjGQPstmHMFMBVty3ufRCF+wsiN2U0udBOJ1+jAWEOWNxZWxP6Lgqz fSolf3/iRGGPqipccQvguFrhveVZUXjY/Pe9p2c5UbxORvXdlEVgHRB/MYBf DBILayKmTnIgDpajv+9uLgP5aUdDupti0JHmblMxYEWPm2/L2PzZAHqedBby d8RgVMPWWtQxFtTr+sqXInMLGBdvv3/3UAxOfaZoYhJnRoajlAFXHu0Alv+O Uj97KgYHxd5+OcbLhJp52MxLHu2B90+wjeQYMZhbsWUpRM+I5i46aRUZUUCd 8D82P5LFoHDwj+k/awwH7xpqXtv7lDDV2Zr3yEsxKPDtWePLMXokfFfT53wF FRSZaBoLyhSDnt7yV+w66FD5GUPOPHoa6MgYFtGZdWCPXRA1qaFFH92F1X+7 08KMZ4e+bh3YU/xU7QjKpUGxupPSF9foYGHqEJg+0Ce7OEDcwXupJTpAyS6W AXq/1b39JEUMFvmnp4s8oEKkaGXap/qMsGPP9mvNgf+cE0se7baUB3NkbaWw GDNkqPercnkiBklqZVknDSnQoXGj2P//F+XLXwv18xWDXXHR5EPue5iag4e5 IJ4ddnDKm1hcFoPsV7mTUnm2sFlBmZzoG5xQJ+WG6Yy6GJxVmTI+Ov0PU8w1 KezI4IKtwYxhDlJiMKId7VTVrWESiYV/LFe4YXfHJipbFIWnQtfVKJ2XsAyr vK38b7zw5zlbZrGLorAw3sh17+MIlm4dzDduJwhlOzplWoVEIe7wAwlagQHs isuk/zqBBPvTBAPcpkXgs9anDntYF5Zaf64xl5UM7/ArfTP3EIH13Dp51nSZ mHjuP+HP9CKQ0BZYUHFRGF6/SRHQ9foXkP/ycGX02GFYeBM/Z7VHhvXpN/7L LR8F3j/oX/eoSUCW0Y7c0ldkGL502dXPbwJYZ34IGTCUhFO9R189mibBG6eP V5yYnAOKkc4MHVelYNEfvQyZxyRIMskPTEWLgMekf0zHVBpangw5PkYkwdwX 1zLCA5dBkq+e2o6mDMy6qidwJkgQfhkFrOwza4BTMqPHflsWLmnkVMm8IMLK pX93OyP+gU97v4asa+Tgqc4zi0ulBKjd2/PO4fAmqKBvVYw/Lg9VDk9oiSAB KJbBIfPo7RZYnRdU6X4kD+9EunA4NPNDmYUnZl8Ud0BZiFblep081H366/ed /1F03WE9fm+4veenvT8toZ1QwnOiKEmhULREVEaTlCiZadNOW5u2VPIe7aGl 9U1FaWihvcfv8/v3vs71PM99P+c9z7nf672ut0UIWdsPhKxkbcKEVXfO7lkV pJssWEPVJohqzrqW9/Jsw0jkFjPBp4o0u7Tkeyj9MRSn/SGiQYX+CrfpKiqo IjXXvsdfmvjR6duXbi3+pEK4cWBFRF0V9ZB0eoLq+NBVek6Soy810jebzbVR VEU3upvFOKt4kZlaTamrKA1KuabKzSCoioSPtuVyETyI2fAxZs2nQTZ/2ZO1 F1SQkQFflsUnEvqda/ZLHWjRh5dRsfcrVZCFEMmltJwbnf6wT3iplhad4rml dNJPBTFPMbj/qOBC2c8+O1zUo0N7cp953tqvgtjOvblnH8OO8kfKSOYaFD/+ eHszbU0JXRVXNNEsYUV13XXyUun0KOIyzT0bKSUkdMRR2vkHM4rXPCo9xcmA bHaS5Eiaish3p4tbjBEDqqDuH6FrY0Buasa7BA/JI17eys4dcdugdyGu+RkH E5pz1a+pGt6BJAT53jN2bIBwZbY4vyET+vTkr3dwryxSCrCdvS+1BsWfo/ke PmNCC6k8qWfaZNCeTqswgmUR1CvoC5xmmNAeGbsvUCuFftd8j9f8+xsUt2Uv 5EYwI/1cs26PETGkYHJpyqNzGDTcrZT/ljCjDFmhmCRxUZSR73OkoOEn3P+4 qiXczYx2c9+ecLIXRgJVA4F5621AnSLIVsjMgmpIfw8+2SOA5A9MRF12qST0 Ano5F41ZEMNROsnIRG40pXnX/qxeC3HUs7u/4BIL0tIQzPl8nQtx68U9qujs JDyf/WxSsWNB166byQc+5kA+e84mkk59J97cEvrid5MFBeibdnmasaHCvg2S 5qufRJ1vjzvhwoIsJU/+OGLEgg4B0L4++4s49U7Md8mdBVnXKy/WXWFCOYMx pRa1I8TLzzPWB+6yoPnF6JX/ohjQ+r1sspn0b+KT1qZf7B0WdNGEw2zfJB0a NtzxottxglAfPWC6y40FBT5anIw4T4t8vVvK+JOmiNaz0cfnbrMgsOXjzPlJ jWrqWctPVP8hUpcThmgdWFBod+dxWV8qlPupruhV9z/i3wJR73CZBcXY28XY uW/BxsDTp77TM8RYnEazmhkLGp65a8LHvwGZt3SNDcdmiXskyyW7UyxIoymn tmloFYqenX6+o3eOCORTCOI+woL+VKe5cHQvw/vvciFfshcI8h+nL/9kWJDk QNONDKUF+GJEX3o6YJEIu7UvSZ2XBRlezx+5ETQHYwabLwOuLREV+34GkmhY 0M3Fic8x7LPwUkTB/hznCqHe4b9c3MuM2PzclKSqp2E62OqRT/8KkfEl2v15 FTNKtfg5wX5tEtCXC1sv364SzqPlvBw5zOir1fk5X81xSAt6cFdbYZ24WL1X Xu8eM/JQb2HrsRqBmWmDh5cm1wkmjWUvBktmxOOrFhVNuSfc+1ISrPV2gwi1 3H7/UpsZVZzdV5kqPgTOX876rXBvERK2QnLrdMyIoc39YiDuB0Wq49GVV6lw eowPT6c3ExrYIa46qdMJSRfCdq2XUuHy9COgasaENqrH90+/+gYSSQrJouzU WFkxPNJpDxPSODQewcfUDnJsqruO5lHjHddCTieOMCIbcbcNnYyvwFdpFUs7 RYN9lIkKxgOMKEqs8Mno9WoouuAk57yfFo/6uPKXszEiwcEqo+j6ShASSWGm 9qPF4YoNerY/GJDIM7fgEMMvkJxlIxchQIdHuq+ZxzxgQKL7JqeT3Svgbu+X 2P599Hjn958XvhfQo49ehc2recWAGh/fefiIHt/rd00f9KBHSoYJLOfYi2C2 JOibSjM9jvv1/h5xiB6lWHH7hb8qAN2BByuEFQMOofG5xFVNhz6b/Pw5zp4H +rxNh/3uMWLmSOnnR6toESm63/vApwyQtJP2DqlgxAwJInZnfGhR1mbqm1zT dDDeFyCTRsWEVcLe+hsepEW7ssJ9snnSgP0Ap/GwHxPWNrNaJVHOz+IzQmd7 /6bAH+5VGocHzFgwRjRYJoganb0WrF3Ymgj3S+LLfMqY8QX16OCfR6iRe+u6 t5QGBberFQ5aZMZS+SevxS1RoSAl9bRVqwRoi5O78+g6CzbnppGWu0iFrpY4 FjgEv4HAGC/xZ9qsmIYpC6erbsGlVi6/wN8xUKNtQM/szorb++cbBl9uwuP1 tn9xV2PAgXNL6UY6K2Y8yzJgOLIBly2qcx1mosFuOtqliYkNNzz4uT4QvA6v tx4nM8tFw6uOPcHJFWx4p3iXQMi3FSBfprGYX4sE5R5ti+HfbLjc379RSmIF slh3dt3AkbC9aqI6w8WOx1TjAyQclmHMRy1498tIKLEcaLS1YsdDSgXTruuL YCES9vScUiQUM8mP3vzDjv8JsqSbss3Dplz+75SECCiDreYGdg7s0uz1hd5w DghSf8PSowgQwO/v/VDgwOZi4fcuBswCQ9MtFHw9Ah5dbji26xoHvvSySEiA cQYGhnqcP2lGwGzQ0WTmrxy4Mny2wKJvAtRNHqg7/AuHww/kD84MceCjip3i 3XrjkPS2i0Z4MBwmdTM1Hy5x4Ni4G2SRojGI6VImj7SHQ7Ozxe5gEU4sUedm derxMDhbX3jk/jEcxhUH37IpcOI1J41Cy4kh+MKiGyv0Lhx0Sn6Gy2tx4g/O c3UPTw6C6ds/O0OTwyFwpMLnuCknHqM7XuQq/B0iL0zq1QeHw/DJrDva1py4 WVR3daqrG8K1FQ64PAuHiNXgnm57TjycP3+aFNQBZ91dOKsfhkPZUbpjDC6c +K9Oii/L0TZIuLXRU+wRDj1xGa4tHpz4ZM8HrtmJBjhR5BOMXMKBWdlcUukB J2ZPP3GUWq8KGrjM6SxvhMO+/v0SMo84sQ/jAIuYdimMT378zHQtHLana07m PubE1lFF9c9b02GgR3ta63I4DEqKRrc84cTP5cSzDpXcJd4s7jg1bxEO78pF PEMp+DerLANXxhyi7srE3Wvm4cBKd8SXjxLHxP40c+KrMsIjmfWf3vlwqAx4 umjmy4mjMgsenguvIlwvc5iEm4TD7TPLuyy9OXHAcNOS2kgD8VncIejEGUpe xypvSQqvxoPnJnlE2ogm7r01dsbhUKtucCnFmRPLdookeOl2EOWZJRfGT4XD 2VSNQ8MU3dYYdP1VnbuJyw1t/c2G4cCk9zJ1kKLz9q8ML/74XqIjC/PwU/DS gnip2HOcmMM+QZr1az8RZOAzQZwMh+jG/SYkA4r+czt4Z9Z+EiJLJbcbKfhE fPQv3cOcuIR2c/BM+BBxRfzAd3VKnLK6ML+9Kpz4o8zAkaeKw4Q5baPXFgWv XHy4OkjmxPMjUadoKHOV97FC1Q6jcBB7eY5Hj4sTTxch/hLLMWI9PFnjHYVX U+vCO70pDrws8GPEP2SCiPHW1e6g6HMiUZrtVzcH3sHI1vVi1xRhpZhy2oWi 50Vt7oZ9XzjwWGaXiW/lNLHvPdezWxT9OeLc00hhHJja2uCq0MI/otm9ROSB TTi0Vg0URMlw4EYOtiae3fPEhxnuneuu4XDF8lS8Ejs7Tt1D41Z2f5XYyDc4 8SaLgsu9pUoaYcOzn0vbFXXXiF/1x23JheEwB+yfusrYMLldtUOYfZ040bCj m+5TODw/p179wpYNn9q/NoZiN4iN2m3BhZZwoCtXT9yfxoq/Mgo86cndJrzy qKe9V8PB74ePW/4sM47W1RT166XBV5IltcdsIuA/12j7tWx6TLqdO+rhxoSb KzS6vj+NhHYZg92TVvTYMzaHqrWWCQc9G/esi4sE558+2n0kerzCcrTRXpBy 7mp6flctjISk4aiKRnc6nK5ldsSqlBlzdDmMPhmKhMbBJjMpFVoMW1m9v2dZ cJiVjfQFnSgQIBv9mPOgwpuPeQZdDrBj+1aVg8oy0SBy47OgrDgV1mY3+H7n ITu+LEY2qT4SDTvVEs3on2wTel2Cj19UsePmbq/rCzbRIM93KTKSMpe3ukQN WvQ4sJtumZNScjTkyxn3dAusE5mZniwPj3PiiWzxMwa7Y8BiVmjq3I8FwifD TdX5BRdW9jsfbnMxFhhzX3UKci8QQuyZaYUpXPiditV0y+NYWFCLOBJ9ZJ7o +JrOZlfBhb1t5V2oc2OBJU6XbS5plvhlcNue7x8XpjJqrq+kj4PhlQGG2LfT hKtxTJqnATdm67g1wFMRB+VnhH5ijh9E8Wzro9O/ufF70+JGoXPxIOCRYqoR +Z1AJUVPt5e5sZpDtbVPYDy0FhxMeSnaQxSIJZWyMJFwj4+h5HhNPKwclujX FW8jclLnitV3kLBtW7dss2YCBNPrCiWxJRJy50yffzIn4TJu7ZsaAonA5hDW Uf4xCkI5Aiw07UiY7cr4gOr+RHCrPLS527EIXiiWM7M5k/B1/f37iPOJYBTv noUe1ENUo1tW7mMSnj8wdDwxJhEqJ6Z1PWK/A6f09sfvKSRsqna+tkEuCfZ0 Z/qrPf4BTr0DIzeySPjM/SjtXqMkECfXefHuH4IzwSbflfNIOHQiczvfIwkS ClrzIxWGgamVp1WqmIRbhXOpLyQngU3XkYoAqVGIqYug1i0l4bv7X1q1fk0C VkmS1YDgb5ipP1wa/omE/+O9rie6kgQqH4/quHJOQM9ni2O8BAk/OUiiPSqT DI06swwaDFMgGaRFgzEJq8wd+3v8dDLcDRRX5tuchqcHlY2ivpBw5pv9vsoP kyGgPHvPwvxf2GmUExVHwVms/hpsvUsGF653h6zcZ4C6VufsV0qc6NSw5Y8D yeBV0v3+vdMsZGgRGzsoeaOqR45d4UiBHZF/uAcc52BbT040h1LnI+Ysfsrt CAwvTND9tJsH5sSv2hcpvEyLxywSXVKATP1aItNmAaIjTRnVKTrsemqopJWW ApPneTmvn1sCmuZSRhuKniIFypqPuVLhzIelFV3jZbA6uJJaRNG/61OkxKHj qeDz7tXez/or4PmGLl0ljoRzzTp+szxMhZRu71QjrTXIDmJnTPInYQ/F9az1 2VToNrN6VyiwBcFuR0OsLEiYlWFQrnv0LTRMPkoq7KJBofrybue+c+PggLil GZYMOHoj4faXk7Qo/mNatXwtN+ZXpBPpNc2ACzhZFVHuc+EHI6J253PjAcGL GYeSM+Ds+Tep997TIa6WS45pj7nxvqcu49GQCW9fbV4+6M2AXj7/fCpVkhsn 0dkE3gnMApOvJUnsy8woMuSdxTF1LgyHdfvb77+DV5NN7OnCXMhjP0+w6hNW HGD9mFPWtQAURja7/9PhQhUGysN2Kqw4UO3F6dLCAiBn7WnzucWFpoiT/Jbf WfBXPW50fbEAbufFnZbHXChJQ6I4bjcLdvIwyZK6XwinT1E7F17iRspWDGoZ n5jww9IQ8qXIIsjp0Cwa9SChNtkfYyGZ9Lj200NVFsYSoBYpvvYqmoRet11y giP0mDYVonzNS+B6k55xdCkJzbRYhg/20mFP5RP0+3JLgF4hYiZtmYTin9l9 ZGKgw39MQl3OX/oI12YLl2McedDQyhEL0zM0OKuhQuJOTSn8bYsYeqLKi1bb jr+zub9J3GTKGCfaP8Fy6Z/EpWO86F5y85vg4A3ijGJA2H2NCoju3c2afpEX pWquKoknrRPR7rGjxokVEPdAMunLI140Gcut/ZBYJX7olLnscP0MXncLM8rq eJH4BtsBnclFgjOpe9OUhOGkBtVV+h5e5KibnWE/u0CYVKacydDHQD34jOXp KC/ydKFf27s8T6Rd5OS84otBctCCkKHiQwfzDcZ/b80ST6UzprZnMZDLok6V y/OhfU53JR23p4hRa4satp4vMM9V+CZKnQ8Zl5obKqxNEHfqOF1nuCrhRbMU bepBPnSge2do+9xv4pa5cRStQSWUj/HUaJ/gQycqBHbw/xgmsj7UOr8iKiEx YH/oNyM+VPb3TnZ/2xBh9Ig9dWO1Eq5WiJ0NMuFDEK1gle33k9hBU6t3S70K BlX0V/wu8qGsj6W/LA71EAvYkQSZVZDqIBL2yYIPXbhy4f0tvg6CncpT9dlw FXwUmw8Ss+JDfAPXdrF0NRNUU2wfM8WqwTBuzjqNgh9gTQ17da+GsOc2YY05 Xw2r7s/9zlFwOqPe9gjVMiIyd5+UQWg1SE76eyla8qHrFvYBnF+Tie3ZF09z G6sB/9Ht2X2JDy30npH3K38DrWmHz5fS1oD2aoDSKTM+1EDymLl/8iNs2Zef MD9YA5bMrVKRpnzo3DEPap7oamiafZDv51YDt3zCLkcb86Guw2qtF2qaYa6/ MqEhrwbmzlhciKHotueE4liNZwc4PdlZbjFdA3fGAxQjtfhQYdZ0Dn1eP7z+ L/mMhE0tkNloX4Wp8SHycPCaVdogtG5aCknH1IJD/Oeylzv50E9tr5snF3/B JaWpAslvtXDwy/vFO9x8KK7K/4jd69/g/LT4XcnhOtCg0d66TseHuDQa5y+N TADpivZtKdc6mJJYKLywxIveHV1+7a4+DVebzL8rpdXBHDvVO1XKfvPQKjhq 5DAD5U9frrQx1kPP89b4tgBepONGyh9hWgReGj/fwg/1IGzw4M6Hu7xoRTZc alR5Cc6EngtNG6iHOscCzzgbXrRQO9/57BzlXGxas/WjaYCTnv+dd1TjRevj FhfuJ6/Cr/gf+5N0G0DDdM7LVIgXLSanmxTUrcGZRrv0D7YNoFXy9fKRbR4k Evp14sz0OoTm7ei3fNgAz568yZKr50EmoxKacXu24NWUrDV/bgPFy7vVSWbz oHWx47K7zm3DhbDUtq3KBmifyBOXCuRBOmd+PlvQokKGT045K3Q2AMt8Z96u WzzobkIr27WvVGiXY83vwF8NkH+FPUDzFA+6OnlS/eolatQw0fuN9LcBBvdy fj2jyIPCznznGZ+iRsmfmwaylxrgKMNo9B1WHmT1Zrtq3JMGRXH9aj+x0QCF 2gPyaeMk9Kkgy9qamRYJ0gRm/dpqAN4sy5pf1SR0oOgls14kLTIak02/RsEv SuZ+UEwkIS9Hx19RMnSoQTbcvHWtARJ6ei899yShgh8veU7m06F22Y8VXAsN wHb0vuTCWRI6pEbdaE7x+x6P4w/LTDYA6/RTTxcFEpqjo9P4XE+PvjLqN9MO NMAna9FJOjoK7mMcfvssA0rbbzCV9bUB/DLPb+V850aZdl4S1wcY0IfmpyX8 pQ0w3OX/TOcJN6KN7W/l+ceIBjKQpObzBjj03v/MfjNutF/nSmjpHSb0ujbB bs6BwmtH2c1jCtzIv5Ch5OUmE/rkEF/sfqIBtkfulOJWLrTMvFkUw8SCTtXz 0M9v1wOU75gyY+NC4847prJ52CjP688/Pbr1EJraYVFbwImM2L6ybL5iQyM0 tS4jnPXAMCQuo2LAiXatmLkf42FH08a/2YV76mDPnbuSwnc50PyI7tcMDg5U n3ExyNiiDg7cdr2Py9lQBtctuY1lTsTKqXDK2aAW3ujRyJ7aYELF1zrcquq4 UeVYjvV2bRUsh+rvP+jDhOobKCJsciMzs/nHds5VcNzr1vceGibkteEuwKlG QkscNMUtwlWgfjhjZTcdIxoXDBCIocyfZ07j1nKOlTA4bTddv0yHHI/nvxO2 5kEOvvuyYum/QE9tA4teOhVaPzVS+bqeF2VYOG989fwETl3U65cFqdAno0RX pjle9Enf4xFuLgc7wRu3V7m2YW3JZV+6MB/aWX9a+IFUOQh5O7x83LQBUu7l XP//bvrJPzkutm+lQFP/8q7V7hXYX7cz7uYGH0oZGVlrNywBmef7uoTV/sDR J02OF5b50Z+H7ka83wrg40DojjI8Cf1ye/b5kQTQz5QXGganC8C6cjm38uQ4 5fk3VytVEEBMOwpWfnfkw2GmiX4ni2GYXh2fA0sBpP2R87LVcB70w2zPZN03 KH4/uuFfLICODU9b6Z97D20mDMd1HjXB97GWB0P1AkjAm7Fywf8d/N1bvd/9 5hfYpXPFf1+fANqIfvhYvTYHYtToY1UfRRD/zCCxe0MAsWRYG/EaZ4NBxgi1 XX0X4dehltiwRxDZsQTrar/PAA0BHOE29p04xHqU/t9hQURus+QO482AZ06d G4dpB4m7XHIVTPqCKKis5uVjn3QouPtfeqfsKLF0mqmF11wQuXUtCpZcTwOx 5EIj5Y+/CctDi3z0NoLIWlXMMnPkLZAN9SuEDSYJOrOioFE7St4+McHkq29B gf9D416XfwTVVbdrrrcF0epXcTmGO6nQ+ukAvQDtLBG5U5tdwkUQUc0b1ZPp U2H66/xOGcM54qncu9slroKom32wMjEqBagVis6oR84TCuYuzVpugmhuo4Lb UiUFzrjm39EcWiCyPZ84ZVPWa6/Esal+TYZDQ2VesvJLhGDsvvf0lPh7dJie zDkmAx/PL61Jt2VC6uDR3/qUeo6ffzToxZkMqhx7ntz7vELcE+57dtdREF36 x6Cc/iEJxqnPC9cwrhF+O8sZgyi8sjQPISObJAjouOCfcGCdULbIFd20FkSf CXJPKW8S2Cu3M8nd3CDK7iy+8qDo5lqlljLTmAjBCudfc7RvEdU3Vq++OiGI RE/uJp+FRDAefZkkT02FLQLN9qppC6LXQsmpoWsJEKlhJRUcTYVLo2yM+/dR 8BrhkENeCVB4vljmfgM1PhfbV3xaQhBxev+6wOUfD/1tTMOr1jRYdFy3QpQk iFiP/LfcIxAPNyWXdSRWaPDb9kv+c7QUPT9bpidlvoEvJxwv6svSYQ3r4yaf RwTQs5WKtqD/4uCJj6m7uycDDo4Mr+qJEUC5p6OuuFnFgseY6rY/ByOW42nq XH0igF7/etU5whQLCqekpwWTGfFNm93mck6U/W/Sz72zOAYCtbqMn9YxYetb 7I1vtQXQ6BiXbg5fDGwzXdlDw8qKh22o/DV7+ZG+fOP9N/NRECej7XnpNifm pL//T7aPDz3L7DMp44iEMyZTt/evcOJB36YO1RI+9GlbO+9VbwQYT1an8SMu zKCaE3k6jA+pev+QG3wbAWLTt25n1nLhsPIfMm26fOh12huRuCMRULOtKD/f zI07tyr2DSfxIr2GJ4P6L8OhN+So5ttKHuxyWE/dSJkHZTN9oso2fg3csY4d UVs8+LWD11vSJgktRzTRRyi+BppjT5/90eTFaxsyXesNlDlzXSX4IutrqGaI z8p9z4st6iwUdW1I6I16v7dlwyvwtpvoNgzhw/kl7X8HKPPBuHuT692pV2Da 61tdqiqAGxv/s1E8zYnGq3e0u3mGgSf7B9VkOwHcMpf4RKmeA13UCrKusQ4D kdbu24kxAjgmtE/31iEOZNl/+FTN8TDYoqaP/rYtgG99LJ+tkGJHX48EZVUL hIGJ5DS54rMgJrb1rqj2sqCLFv812xKhcBK67uqyCePIdDWLU2v06MCVTNe3 u0MhSrY696CqMN55Wdqz8Tw9KppozX0gHAo3Wf0GxE2Fcf2m2afBQjr0Q0Vj qI8lFKZMLtbGRAvjPQEuPovXaNHBtdO9wn9CYPbKiT+qfCJ4iaqD8x6mQmZZ bBb3S0Lgy1/zk2xdIlj8R5PnD+cloLuoVxJ6OQQyFXckFPwWwfBIZ+ouwyIE +HjtWTQLgYQDJV3SqyK4RCv+hGz0PIRPLFyrOx0CgxIXwq0FRbHB/RPPVj7O QENEfnnRkRAg5xmTdu0QxeLh1QKeAX/hQmb4pRatELCSFLz4QU0UD32zj36b MgWTHsEfz+4NgRgLrXohPVHs8lXioE39KOxy+K6csCsEtj3YTvwxFsWT5LMv VLp/wdxSv8oVmRA4sLfgjM8FUbzSUaKnXfkTghNnSsIkQmCzLK2g3VIUt+h9 v5TyrRfehbeZ7hYJAb9yNr1BW1HsJ8m+UTfQAWyHptN2C4TA9xeftrKuieK8 YfY7g3VNwCpx5OwrnhBwX7zVpuIgit/YZBrfCSfgFDrPcYUrBAK4G6qdHEVx 4ckePXHZeCinFoyMYw8BzbErs/YU3Ctf6lLlqzwi8FNZyUHWEDi4unpPhBIn LSLh+SnrakL6NqGrwxwCclUOIY8peeN6bihxQhvRN9kvWcgYAndZG9xSKXUq +HMyXz3dTVS+m9z/giEEhKO83D0pvBJi6tRG7foJ9Z3jD2rpQ4DjleE/eooO oy6LfW9hiKCvXFxxoODfSm4ZHqPo9tt2ZPduwxFCtVi38A4FN38Xzqx1XBSP 7As7PHDxN9Fnvbt2goIr+XLnDB8UxafH/LPiHCeJsr/CptWUvE8Ga5pAVRQH F+34qXv/D9FAkx3EwBQCAu/0OYxkRHFf1A2+vmMzRPZ4Qk4ehZfem8W+Jwyi WKD0vLGK2Txx14e3+BBHCHDuX141KhfByXF3r/g9XCWuZ90y0hWlxHdsVqxM E8G6L1jofvxdI0K5/lL5kCn1PGnJ4Q4VwYd7j5XwWW4Qzsp1uwRlKfXL/5bU vyyCayKv2/zS2iauC15avKwcAqsr+o/Jy8KYqjioNuceDTa0dmZ21QuB0asX l5omhfDayekWTykmnG7H0SYZSOnvu6STB6uF8IezXnVvu5hwwNdKg6eRlL70 DPqGxgnhnPGMcyeeM2ML7MtkmhwClVRv6f7qC+HFIo9fv6ZYcPvkrrm9pSHw mSnM1D9SECc4MUU9zmbH3fdLFnZOU/reSeVpuM2Plc2yHHj9uHF9I0u78PVQ CHnZvCegjh9bmakG4W5uTHXb/3PjvVBgvbuxXBnEj1Mjb134t4uEGc+drd18 GQrfx/PWxYX58e67V+JqW0iYFhw9F/NDIebV2jQhw4cz/5xKX+Hmxf86z/Tb 04VByonEOW1WHnz9QZ7qJS9+/IiurD+uJgxcT9Dl1F1gw3snot4HVwpj3fYM n63W14DI8QccC1jxoYU9DRVbwrgvVFyOdvk10B/oaY1jYcWZ6UFp7AdEcO4v C8MF8XAIs938TXxgxiXnh+IY34vgGDfxsALncFBx5/RN3mLApzQWkwVfimL/ y37Kx6UjIG2/gMLiaWrcynLs4nUBccxsZE80foqEf216yvKRVPh3dxHXHR1x 3Kzns521GAluDz2l4z5sE8psdTn3ncTxZ6+2sSnlKGj/fTp4HG8QLKKy9xxr xPE76xMuHzKi4L+7btkLFUtE5yr7rdDLEjhw6qpAWE40hLPsirVuGiEYXte7 8auTcVd6n+F3xjhIT7tmvZE+RBzV/Lk8ok3GJ4aYnspcigPjXj06GroBYpk3 HUsYkbFCmP5UbEEc3PijXOJs0UaUIa4v3dfImNu3ne2C3RvoV70klHC8EoIi M//uCSNjnqEf83xT8ZASlSuhI9IKvBq3/hjGknH1zLnIrjMJ4LkY7Ni41gWl BkMLzSlk3Hs947pNRQKkaOud57s9BGbhnlc2C8jY4uql5/GGidByzZ/3sM1f iO8pH2dsJGOaJn3ixuEkSp1MYbxtM8B36s0u1ELGjD8FakceJEFky83ekdtz ELX1NKS3nYyPs33QVfmSBNeouI9ScS2A5+qjmI5OMv7jqJZgRZ8MBzP8pM/n LcKv1xaNij1kfFO4dczPIBmm25u+9BovQ/Z2Tsbv/8h4ruHp9PtXyRDtMXTe Y3YFjlB/r6L6TsaZz5R15weS4XiAHI902Bo4v9id50HBe9WvmFzZnQKPA0d5 G9U24KjpV0YjCu7cx3We/14KsNz+6mLRsQkGwb0Ofr1kvK7w/qZ4YwrcFXLb 3+y6DV/MrB/yUfLys91JDxNLhdVYx3w6fyq0v99hlq6b0i98isPfNRWGVq8s UplTo/80WFxPd5BxmcKfQtGvqbDzTLlFxy4a1E1t+WmtlYwPfZInbOXegk7v 3z7XVRoEgVEvqb6S8bkIn3v3nrwFvzqXxq1IOjR7kLeDXEnG+cphcj4n0iDj 65em2x70KOCR7beCcjJeNmD8GF2WBps8H3gfXqBYrI9KV/yKyDict/pCsFI6 sCj6/j4lwISkDzBE/6T019llm6NMKgOeNqqEBwexop1ltim+98hYxjzigZZ2 FiRGz5buVeRG6Re1ll2pyNhU7mHk+Re58FT9gsmfSG5UsevNm74+CXy1gPrG pZ158M+28SiZhoQqKroOGRVL4IRHbEdXgvMgrFFDcLiThATk33uU2krgGzcb lIsd8yHsrqaVvisv+n1NYbrwvThWONI1rHWxEG5VW3FQBQugJO7//hpuieKQ ccaxx6YfoYuZKnrprwASjDppV/NFFE/XH6jL5SuFZAUmP95Tgoh5Vrex3U8U 3312ecjjRyn471t7kc8shIZH62TyaUWx+0KszJeX5ZDdELMx4C6MGGXP/K6e E8Yt1gIvqmwJ2E7SF/BuEUYz5dvU4tnCuDfAVzRDC8OJ6MRSoR0i6AiKDRO7 LIztf4UobDdhYGbRiN/3TQR9dJQ6LvxVCJvtyOD7j7oS7jh9qHQUE0PKOTuj TUMEsZNP187G5mqQq9dbs70phkwtqj0UDwvivNy9Wy8ia2C/IU2o8icxpF2b p1g5KYCrDvhm3nashWeY/Yn8OXHU+EafUEIC2OB08RFa9XqImsf/SXhJoJ0b Oc+c+/mwp5i8XpH5V/jQ37CLt5KMJIMrNhoGSJihL/0+W18H6EzI6bsMkJHN Fn1D/0MSPp7hW5uS2wm5OaeKd6yQUdPErzMskiQcaZn2aDWoC+IOnfd5Li+J VtRFoNqaGz8xCHBVc+qBvNEbIuMvJBHXm5d5Wjmc+OAQofq1pQ9qyqK58hMk kVbH/NTgLw5sO3aoXJB1AJxq6i6WF0miItGhyVUBDlyk+iIt5vwPuO96P/B5 vyRaczQ7lOnNhrcm9DVOhw2CyVN6qQIpKXR/ZrZ0YT8zrsgPcDzbOQyJEnlj ampSqF2F8ZGSLROuIfJGyHgE1NNKH/UjKXTdOOa5TCAj9u6jn/lXMgpXdphF xV2UQuYTPKs3Buhx2/djEePNv2FA+gpDzjUptKobW9hBS4+LNmdX9f+Mg6rw klq3ixTyHn9kLLGLDntqlBiKikzCsU3JbMenUkg9PpAnxIkGC6Bm6dLUaUjP 0t3VGiSFbkbbqDeFUeMTuuL2Q9R/oV7obcOhCCm0zTKgLFBEhfkWdB7udfoH y5aXbAvjKLjxAbntjG1iZOen4X0eM2B3a2+BfLIUmnq2foY8vkl8U6NvTNae hZc7Tc8lp0mho1pyc5myGwTp+79jFbxzUCpD20nKkkIcyu5hRTZrhNOeOaqx 2TnQSXvxyiNHCvFvRRw1i1shHjNeYvbunYc1qWtDLe+k0MbIenR+1xIh/GXm 6q+mBVjzy/jL9V4KTRsW5/ewLxLZO48HuDcswoFvLu2alPWn73mqjulQ7kWy dM2vvy3B2e+fnuhkSyHb64uGK56zhKQHY07c72X47Wb7Vz5DCtXna0Wftf5H hCqx7/jNtApZFRHdkylSyObwCTalhinCl2VktHHfGujaBsx7xUuh8hTBb6Uq 48RLq4NXY5zXQf6hPmwHS6GxYYeqbxuDxOzApVJ5zi0Qe0D9cIyif98+HavC qu9EkPDmPTeXbYA/aSL+96UQl7zFNEtgB6F33fPId2cqdFhrSmrGVgoVjxjF Xn1QROj4x2VeXqFGJRr8o7GUfWXI4vBW+V0P/JN5+u/5RXoUszN1rpFDCqkN +1zV//4Dar+afhY+xoDyqOxL/VclkVjz9OIE9TBwGn/2i9zPiJLXY99nNEoi 1iw7qUWZSXCZT8uOVGJGyh9l2obMJdHnlzcfmsssAG1c7VLLFXaUH3Un870K GR3ulx3Wn6FC+06fMidp8yDZcIYH/lRk9Gh0+8XDHmpUYVn4+PQgD/rxZvvZ zjcSyMRJLrz4Ew16c+fDzB9vXjQvtpcquFEcjaOC+jIfOmRJ29dnkc+Hol4s 5stsiKL84dCKy9OMSF3Uyu3FMMWXv/EccvMRRe5dFgydmAl1DswtOlkLItet Jdkv1KLofig9tU8YM9qZSK/j3SWI7kRta3WuC6MnCufrVBRZkfd9uYmZVCF0 s6rp74ibMFpTrpJlW2JFNAEhVMObQiiuiG//kykhxJV4wbe1nA09VE4Q4z0p jH4s2BdKfRNEHyTjX9VS/OaJR485u2qEkaoT34LXEUF0OLjSvHeVA8ktPU+w nhFG63eKbUXz//9eIPhiWAEnOihl5L+DQwQZxXZ+2ysugDq+dAnP7eFC5J5I 3CMugjo3hjjWX/Cj8WX6G0MBXOip9aUTB6VE0MSp4KCEBT7E9eRoFfcIF5I4 v6qoLiiCnN2bRM9b8iFbI+9bDzQpc8y7fr2ESgTNi5x+ZFrHiy5xfbCXDuRG 7/t7D/T2CaPDgfxKLcq8KDbTznLzBzc6LFuHKjOFkbqbyuB8JA/ylYhOYlYm obdTvzKKHYTRv6VEk5VtEjLffKB2zJuEqKa1s9klhJFtcISfRRsln/OYqwEv D1Jm2TdaaSuEmotO2f34y4FMX3yee6rAi676srOY3BJAFyTJo99q2VGByKfT 3Ld40eLFrOzm7/zIN/HnIb4kNjSiqG3Z/o4XpTv9imVD/Mj0bIf5NQsWtMmm 6bslx4eKio9eN1nhRbRVHEq7KP58wtxnyJWRH11r7SdeapCQf9+zgcG8dXhA 4/n6wx3K/vB5a+x7lhk9vXZmYrluFYzzlr89eSOA7D7fSDvNwIRG/qzINo0u A1llwq29UgDdqhruNP3CgO4+6Cxm2bsA66LqFjNMgmgxvZj+9Rk61Muue/6d 5iT8ZXB8VesniOhMzkr4DGzDXL0hefGBN5El2V8lvF8IZaQr5PJfngPyWToW EbdSwsGudOr+MSFUbtHarSI3C0w2i29f3a4nslj8DSpMhNB0RNDOorV/cPbt 4f7hxh7i+c8NrZ83hdDO19dsY4ungP8kzXPrxwNEPX5XX+UhhHrqiyxpKycg 9epJ9pnoIUL0WM+zgEdC6P5hF/+9079BUu2fg6vWb6Jn3tSlNUwINd48JqAf PgL5tSoJ7+gnias3q74aRAsh7XNCbE3cw/B0T6JLd9M0Eb7/VVlevBB68z0O LqUPwdyNoS2JoH8ElYuB+HayEHoQI/C+2WQQjl0NM7+0Y5YYOtZetz9NCMmb GPwcU/0BMa89Ckf95gh353r3ixlCaO1zFfPJ0T545U/OJH7OE/t//e12yBRC bS+E1p9+6YV9x8giG5qLREPx85d2//8/2q2z/dbVPaA8eUg9O2yJSJgp2WFE iWOb+O5x/lQX8HEEu/dNLBO1zHXKspS8rrfTBq33UuZ7H31lNKwShbXXpSco dR5dYpe5nvANjF+fvzn7ao2YMt1yi6Xw0slae/tNrh04tsNOTI+tE8GujcEH KTo0qoeLeke3QvaXqLIwjU0iT5v/v68U3SYsuYvLBJthJXV/2dTzLWIjTT/n 5EshJC2v82y8oRF2tX66MhpGhX/6814UvSeE1p0O7aMvroUpHmYNBU1qLO8X 8OPGLSF09cijW63j1fBIU3i14wc1/iEXqv3+shCivXtEHh2pAhd9offHd9Li stHKMTo9IfSa82yex0UMP7xNP7wvpMeZSVWvWBiE0EbpTQOpxhI47Mtc+c+E AbszRdJNzQki0vH140/oP0Cpf2z780UG/C1Sf/3zD0F0sWFqktq+CJzM3hmW qDPhXInDLEcLBZH3OYEU39h8OLbwHVKzWLDOw7S2OiNBtAszmNBXZkHu5VaT Y8dY8fejDu7G6oLoptLd960imXAsVtdaaogVGxt2mLcJCKI2gXYqrjfpIMV8 yM6dlx0PvHDR/9gngBZfjd8UZnoLi5MauWtOnHg110BZ67wA2hbfF7RLKQn6 dtrFzdBw4THbTrGQPQLo0OVUM53biUDMXtObPsmFJ1ZXpoc4BFBmvKPKyuME MK1Jy3D+yYWzypvSH1byo2wqG9sulTewqLbYemWLG2+mtdF8FuNHEgEDYjNF 0TA0q/hfkw4J+1x4upN3jg89pLt85idDNKg7eF9I9SfhfAVu8u0aPkQs9Ja+ uB4FZ+KBOZ6XBx8eNtHUsOdDmcNLvp0mkdDOMcV4WZIX02Yd1jrwlhdVmVj0 pr0Lh4rBirUyG1480vxoYcCFFy377j4mbx4ONyM0PNySeLGkV592DPCijDNd KST2cDhP1ya1Jc6Hq+JnNC5386A95jQq/n6v4bmTyhEyiR/fC6hiNFslob2R BS3rqa/A9MkUz8luAXzZ7QQ6yc+NXm01H6+8GQbqWQ9ybrAK4vOO/uf3dnOh rounn5GMwmBPNam6CgTxXkPu8tPhXEha9sFkqWoYyPjkR7GmCWI/xR4TBW4u pOLMzJS+FgpHxG/ofr4uhG8kZT7T2WZHeq9f3i+PCoWpOyKnM6qFsZa6N8uc CzNyHaLp71gNgcWya5X808L4Ay0OVexjQrtN9M98Hg+BuzpHTkSSRPDKMadZ /iNM6IOIfIfafyGgMXr8Qe0lEXyoiu0UIxsjiukUT8/4GAJ/6kPOpY2K4KK4 Yee/IXSoTe1auu3DEHhoRb/jFr0ofmeSor3zHy3Kkc+g3+8SAuETmW80ZERx x5XSZM2TtOjN+5HHnldDoNLphmOLpSi+/oqDtEpDg8omBlL1DUMgcYI/t7lO FH+/aC/PWbcFVLG3lXokQ0DxulOh509R7GopNavusgks0zJrKwIhsJTnxim2 JIofyRyOuSKyAW88Bxe8OUJApOB3mxZZDP8ullznur4Kx5j2MpmvBsOTqjuv S6+J4TsylUb/puZhf43sAlN5MEyG+KtO3BHDtsUuzUXP56Bl2kBK710w5M50 S9A+EcNzX5sej0rPQs1ecTtIDIbq/2KlZ9+I4XGbHzvvZE/D+J5U9dPPg+ES zYOpygwxfGRc6PPcfxMwVBXhbe8dDPuPhNh7Fojhx08hKJv2NwRQ553b6xoM Du/ULkZUiuH1ny5PNU8PQXD01x0j1sEwRDiI32kQwxfy/zLI3OiHhfRD4WIX gmF638M1ulYxnJsTE31KpRvW89o8dxgHw4eEia/aHWJYIfT2wo0frcDRPM+7 pRcMGlT3feW7xfCJ7tJgOFMFWx0xZSlHgiFM/zbpS48YbsmKOuoxlwW8zFl9 /IeCIbA+6Dn1f2KYu26q6cOzdKLsSBrVeY1gaBU4sj5FiRNNHpLufV5JFOQd brRVD4bSgfCQh51iuOwZy5+o/a1Emu3vmf//RyzE64p3eZsY7tPo8Wlb6iIu fPyg80spGCKQLX1CkxgOOR10Ws20n3Dmknl3VjEYBFJkvXbViOGqoNZo04tD xNOF6p2hCsHArXIEmVeI4ZtZdpyegSNE1pUTzTEU3Pa+bY1KkRj2sDId+IV/ E0rd9nVOlDhM2sf8czLF8OFbKyo3FieJmz5F5jzKwZCW1yvWTOmXtHsEaW73 X2LAPmfoEaXOmwYm4mEhlLztN/Zk5M0Qh8TamwkKr7F7iprrvmK4M+KIh+rJ OcI3KCC9kaJDUoSGPJMLhW/Evwya8XmipducI5WiGzP5VhfbKTHMZJZVs4e8 TChomLnX6AdD+cE8e2JRFNv/55PZErJJHMo/6dDvGAx72SXWdPpFsf4Xf69w hW2idPtSi9udYJiLJ9+99UUUj4VkOzJdocJTfc1sI77BcO4Us+P7Z6LYM+DW uT9b1NhrWInTMDYY3F0aRP/SimKutfie86r0WDfUyN/jv2CQvt32JP6nCBZf vL3GuEmP6XQ73JcmgqFhW/XnUqkIVuS0Dzxez4DXhu50mG1Q+C7fDEt2EMFx izJORhZM2DKTUfwPdwhYmnh82S4XxpAswODlw4rV4z920kEIWOGJ9A4JIXx2 WCf7STsXzrztWj2aFwLZaWcV1JZ58RmpmJ9sAfxYJ9rVbo46DGK0bMLLc3nx f5drDWT7+fGE36R2s3AY7L7n9ED/Gi/G+p9+BcgLYFe3FNOT6mHw3COo0KuD Bw/YaHho1Qvga0+MD+nYhwHQMp30TCRh+kPBWUUrgrjiky2dd18YmN0WoGXm 5MKl+zrPi+4RwVnaYzsDRl6BV2aIybIzJy5bXHj98o4Ipil1jnVjfg3rs7OB +6o5cG2ykygvRY/kvaIFOsqvwWjx7n+9tpQ5eC7u9hUtUaxzVHJHgfdrYGfe 88UshAUrbqr5ZauLYaMmk3b7HeHgkvU6/V0KHV6jsc/avyyOufNkfx5/FwEM y18cOAZpcbv3mnr7bgksEu8p+3k4AlwUVESVRGhxUs/mLlMLCVzsQ/0mRCQS aCwLaGoDqSnz93YtNyGBr/s8vOocHAnj6wLiWo0bxEa41bb/ATIePUbjfOJF FAQO/ll2V1knpKLi7QeMyJg7PYW5vikKHp0yGUl8vUr06qavxFwhY5OjVcVr nNFQ4dp5leb8EiHptvz9TAAZP2yyVS96Ew21gdzKe1/+IwpHVRQjOsmYl2FA gKktBtJdDzgva04TycKCAlKjZMz1a9u6XDIW1h1OeQeOjhPGogHmXItkDBtU qnHusVB7smOgYM8volTc5R8njyTORD5ZSjJxIGvopONdUUm0/pKI9Dkuie9+ V8ooj38DDyZ++OT6pRL4UPsNurOSuL9tp+Y6bTx4iImlvmXKh8WIfXuGLSRx a5d6F/uNePhr5qpxZb4dXAbwyffOktg55IEpl24CBDKI2yNiDBQ2LpKvhkpi y6pvI5VBieDEUeur+mASzml4nt8VJYkXfFd8AzoS4Z6LY7LT4b8gxJpTJBMv ibnjni08E06Cxko76YntGdBwuOF4LkUSj68882+yTQJRnjsWfENzUFlB+7Ei XRLTCiRm3MpNApuSsxzplQsg0Bb90yxbEhcfnul9sZkENPBN6XnqEpj/0FDZ /V4SW0d9+7HvVDLMfLmUnPx0BWztx6mU8iSx0pdBIiQpGZoYG/YPXl+De9oV +VfyJfHlY62DhcvJwHpbJ2u3wQbc7+/LbqbgAiwapM/GKTBQxJLsqLgFEWth NtcpeHeKT0ZLTgqwa8eZ1zJSIalK+1PqlPj9bufCGNhSYa7uQlH5ChWauim5 rEKppzBI9dbzW6lQ7OkY5T9BjdQ+t05YUOo/S7X41qMzFRg25EvlvtMgOrGp ijIK31fZrS82D72FOEML04QyOmRSqhtJQ9Ftk6m69LpoGpw4O8htm0WPbG4U rk1HUvi+vqeQFpoG7l30QXXRFB/2Y3GdntKXdML6vx2s6fDiwQSt7l0mpLWQ sVnpI4ltaErYylkzgMag8n6bPBtiGleVuXpOEuPD9juN9LPgiHxL4POP3Ki7 9/BNg+9kXLl7cSZiLhdclYbiK3aTkGb3fgvhOjKOCyat6V7Ng+rhjRy7OBLa 0opfFiwkY/rL/vMNXXnwvLDm4aY3D1IK02xJe07GS1EKIzY1+TCjayIXq0m5 L96fLCDtJuPmyooc47FCOOcVNf8gUBC5mafmugeK4xa2hYkEz1K41Fmcrbkg iOR9/lSEG4rjrpD0IAnTMvC9fvwgq7kQqjRSipNnE8dRzI4bWgfKYfnwrpd9 UhSfrdqq9+WxGMbNcTfrd1SA5LwJfWCGCDJ+2BjTaSuKx1N167xaMOiu/rvK +lAcffhXfW+kTwhzllte/DNcC2eZ8ljHvomj05KtR3c+FcJqe5b3SHTWQe6L 968ey0ogs8+htsLKlPXHzp473V4PjHy3NxZrJRCTwdgsv7cg1pCLvzO/2AhL 2637aLzJyJ2852AHswDe19UzsETVBuduvTbMSSKj9jEV7qlMfrx9Rw3Xl7bB 9EWd84k1ZETuYBJt0ePHX6UKOkS926E+2DzejFUStSU5rNL78eEi0SNXl2Q7 QOVnKS4OlETWhjP7Cid4cHYx4RbJ1wMDY1JuJjmSCJPk78f48OB9h1xybfb/ B7MVA45SjZKoa+lr021+Hiz4puEDOPTCBemOwEO0UojDI2ds+TAJbx/8XPyS sR8kj2xfoneUQsw9Yd9YH3Nh1ga92MOSQ7AW+s6p8JEUSv0l5zlDovgPZZ11 A8ZfQASpsThHS6H75zprerU5sQnzi6ey67/gjRjXB6ZqKVTBzmP23I0dx66Y TyZyjsJEkWO7FLs0Gk8gPinWMmOfOxGvmBkm4Xeg97daUWl07hXDfzXdTHjL +cKWl9sUiOz8tHRaXho99zzeMjvKiC8xHdpbsTIN/NKmf+l1pdGtlySvQ1QM GBl+QC3SMzBd4HFBylgaqdv9UvBkpcc3n9ly2bPMQt9zfw52c2kk20YuecxH h1MCah8+2poFwS2XOVUHafTU8ucD7R002HqLRo2ZtAASCrQNFk7S6KeEfQ+P IjX+dOWhyj+1RfA/b6ap5S6NNretjy2oUeGgfGElnStLcE3J/XalhzSSuzk+ +Pv2FmFdsT+sJW0ZDE9Sn5nylEanvEV/6XlsECJaD4zOr6/AW/Zy33de0ijk pXyF8sM1Yp7qRXvG5TU49OSHGRUFFxPzjv3yeIWgtWL9FDiwDuaaSTPfKfGf 1T7IlnmxRFiw23m13tgE4117BdUp9RR7vdvlE7BATFxziFTn3gYUsNeGhlJ/ t2u73UbQHJGAtB2Iq1QoN9tX7KC9NLrW4ttaGTJDPPmU9FL9FDXKn67gbTwn jcju29KFshNEWFgj640jtOiEX3+mkpg0+lM2ZvjkwjdCzlJEapVgRKVj+Uqa LNJI+usd0tfP1YS1cnNz1DYT+iHgmXVxUQrxaibz6ZxIIcLtaD1PnmRB0bHL ap9rpNCJo3tYdf80gsnT8bVPbOyopSOib8BQCsmSnBkD74wBY6/MSkQoN+LU 7X+2qSCFxv7bN2YsOAn6FRdcXExIiN4wl1BjkUK7nnv2lhb/AUm5yNx3Ijyo 8t/H3rrPksisj/P3otMchD85bJtbTPGdnCUGKlySiK7jiuxZz1UQp6t3f84s iH6XjmkG/CQjD8NXVgfU14H3DsfPW0OCqCzBJGcih4zuKptsXJjcgHv2L1Sp Sv//nkPjSrE2Ge3Wef5urywVurDjqWW2rQiisrDfuJshjiyP3h4gO9CiT0YH O/YGiKPDl1ipA3eKo2De5VnyXjp00+bDuY1jEsgtjclz11sxFNBzt95lkw5p nim0ursqgRSTpSTvvxZFwYc7VPKeMKD5r42P3ySSkYUGXd59RlGUVXSDykmX EUWSrs7tmSQjXkdp/ei7IuhEltiB3TRMKCttiDpAURLdWOU889NIGN1wGefX pvhT5irl/ckJkkjq/H7bGx+FkKxMs7SnLAsakovuftosiWz+eh3rFxdCjRJh r+y6WNB/JS083vOS6OOZu5N2foLog8vU52VfVvR1/EmmOrcUCq6bkDg2JoAC 7tKbkynzhErg+rbDDin0dWDjcPFxAfSf/m6fzjY2pDn/R3VaTQrlzTfWzqTz ox4urs/MruwodjJ67tU+KfQw6c3SXkZ+ZOmnK1jCzYE+i70mn1KVQi8ZJq5U XuVDo9/HOLpyOFB6q4qUgLQU8go6EN5RxYtaXlsnWOhwonpPesYNVim0Jz8z ME2SF7Ep7dc5+R8n2jgY7iw8LYkcmQ/Q+Q6Q0IDrvecZnlzIPTXrd2OYJBr1 cr+7oUVCbVyvS9UILtQxsDth7H8VnXk81F8Xx+3KEsMYZsSYQimSskR0rlL5 FZE2RJSyVkqFkqwtsjQj2bMTpRQhke9FkbUQKSFrlizZSTzz/Pt+3Xvu8jrn fO79495jwUCqfgE/5eJIiNUfozDGSUJFxc9OGlMZKLq/5bO6lSjaxG1mvexH Qh0XWuST/eXQ6dMeawS9RZC9gWboCYKE0rll9b1U5NBSsKWyv8EaNFD09MXw IgkFquj2jqXR0dlY/SDVDkFUFckVV39eDEVkpD3ipbH1RuS5XJYuP1osfV7A pyuOSGMvi9IyaeiqmmHkATofEn89IpTtIo70W+1z+gkqolw4ZO7Px4uOUVu3 5cWII/sH12lOX6RQ4L36HuFeLiS67QKV4484uv0x/eupBQqy28R8evDZP+hw sjU9EEpGL44dO6BkzO4nThJTsRuDa9q3ko39JdDh0m4i9NJqlCUYoTNePQz3 FZodpR5LoLPrAxSMe/nRC3I1b9TuX+CaR796uUACvSksaqHb86GNbnNMwv4n dHYGz/3qk0BmZcurquO5UXYz8bBfrRgGrCs7g9QoqP6spIRu3D8I2yWR/ITP H2SONc246FNQu+DKymf/v3BNZp2n76EC4p5FpMAqUwoiTRzpKby3AMo6UZba UY2E/MmKrFtOFGR5V37D4sgMvN7+fUXAvI94s7yvqyaUgrijXiyEDY6D7wxZ MVThF5Fwbx9330MKYgoYWGvaj8JjbxNN55Ehoj8jpbYxmoJ6jz0p4RYdAS6j mnLy09/Esp1HRGQ8BWXlTbqW9A7C6/MkofnT48SA5ZYQ9UQKCn7Mkbi5awAE nooKl6z+Q7z3iyp4nkRBL9Pp1goc/fDhXcaEp80kUcG5MM6dTEEdZWkQZNAL TKp3jnXuFJGg8mZ8x//rl71WemLwtBukb0f2s7hmiH///8o6gYJYscHMo6o/ YcQoe0jbdJbwVe303BtHQQtXDGdDUztgeINIv3vcHPGwDjXRoyhIo6zD1JPe Dv9Shyft++YJ5E2O6mRRUB6X+XhDQxt4kA32KGxeJO45R437B1PQkNfmr/QX rbDVv1qrxvUvkcPzfUw4kIL0FLQPMd5+AeXSS7ddcpeIxuTVj3y9KMgtcLtO 7ngTnDA95T6qtkJ40p7elnOgoDDeVc7MqE8wpsWR7a7FgfduUbhtcpKCik6q MrK+1cENBe1N5BYOHFPqE+N0iIK27Uvh+2teA1UZ0jeKhbnwm7Yri6fZ/lBb IP6waOkD3OfS+lyXyYXftzTk6jMoSNHD526E1HuQppLbBfZw48rFEEsRUQrq uqi8zte2HL7jb/Li13jw5ZG59R7DEkjl2cPe1LpS+PHm1PNOIV4sVrw5WqxV Ar2UEEt33VkCGwU9I7+l8uK366VSE7AE8uF6YGM6WAQX46+5Wnziw27JazcH h0ugx8nHi5V+5YOKfv+Y4drV+IKZp3e1kgQ6dU6QxjOTA73aDy6dfL4ap+T6 0P4JSaA564GVbS+fg/NkuFuQngCWCVCkbBgnozyzGY1L6c9gx5Li/g0nBbGC WN2t0y/JSDrgu7XzxkyQOx2MBu8L41BLZc0gRTJqLjc5e5mUCi25NePHyWvw 77DCwnucZHTFmqv4LC0FFE3PmbyNX4ODsmvX3WkXR8ulBmuTdZMhMMTkveFT EWyXsVHVJ0QcJax8ep52OxGmDyUH/2kXxb+7PIngHjG0in5rd5tWHPz+9+3c b0kS9tRM9E18I4Yuf/Md23UlFp7ZLMWcOkLC+2t45r+HiiHqYy2ZARwDBlx9 OxI/krCilM77eg0x9K/f+WN5cDS8McvbYpQthsu77Bo+eJEQt250dGBBJERJ cdSU9IrhQYm1XDoHSchYJPP0QYtI0Kz9wc2iiWMRy3L9n1QSMoqx7vvIHQle EUp3LO+I420PHr3++FoU7a81SGo+/wjOdPMUqxwnYwnXwnmHchH0K+1V03vv CLDiN9PwuEfG5ByV+g9HRdCk6FWN7UYRsG0fLyfpLRmH36p5m9S/Bvm4SF4c kYmAgkxuFWVpCewksyurnWsNcjxcrrZQ/RCO7FzZjb9IYOGahOVqtn5ZimXm hOg9BFUFGe3z6yWxkmRL5k+dVUh47Uv5OxfCQYR30DD7P0nc+e7Mus8F/Gh+ 2K7JwDwcKEmxj6muklh9vsDSS40fJZ28Gde6Jxz0NxVuvlooiT3V2nso6/lQ 5qFDH3bLhMPv60kcU3pSeNMalNozx41c9mx3VGljQafkzi0O1lK4qvP5nCr7 /FC30fCy00cWlOzJvrvgJYV9lQMMT7VzoUC7dPPtRSz4Z2RDXC6Qwh/1ciIu v+VEWSlGStbxLNiXJcvjJ0fFCSu2xStfl+HAd+XUGEcW/M3dKVO4g4q7JbzP V7B1wDlXe32jFQsC9iurL5tQsbDD37ex3kugbuMwff0wC9atD7Qt8qLi5vyP yy+kF4G/68ICRZcFjZJEfnEVFRvaZJsl7p6Bx9UPq40oLEiPLrt9uI2K1/nF 2G9dNQ2VsRTHdmEWpKnE7hr9RcVXU9x1VeomYVaTw7WBlwUOd2PvqfHQcEL+ V95okwl4Lnc+rmOWCYrOcyb1W2k4Miru2fj9AWBsSzC+18GEamLLvKE2Dcum EvdVhPpAJYAreWcbE/6OHWmoRTQc4KB2iRLcDd4/+q7+18wEqQR6QK8RDbeP ZRsF8XwDPfdHlW41TNj6xb7Q/TANl9T9mHOdaQapyoRroZVMmFpZei98jIZL zcJ8q9/Xw0eFUD7OCibcMNAcfXKChou+P3qqHFUBD74+U64nmLCq/+YNAwsa HhDlT2h4nwuCbpvS/5QwQYPPBveweYbJgjqfghcRxKjSvPiWCWGtSdL+bK7h pzizV7OAsPp479XuN0xw3GUwyTCn4d/fJAqU7D4QCpzXxy4WMEFrnJVX9v86 ZSyFmB8vPxGdaU6fJl8zobdQvs3WjIa5Wo7mjXK2EMUd73c15DHBOWuue9mY hoUkzYt6VL4TTUYOqpxsLh921SrOkIZZti1Na626iKxHvvHBuUwIOuL5Q2M3 DfOb8Sdp7Osh8mwvB11gc7l1VhwNOjTsNR5491BXH3Fsfx7nEzb/e2LF1e7/ deK2pIWh67+IPrtKqR1s+7YHWn/MbKThLfWvhabEhwnagQ3Dcux5FsRMct6W peHtktd3G+f8JnYW7Yk5nc8EhzX8aaLiNMwRKnZS8+A4ERzveniRvV77EldW NB8NJym6FdRMTRDKSt17R9j7Y/xnx5v4YSqOSk4uymROEX4uPV9b3zGBZrtY KsW+t3v7n6bt6pomflSe5m7CTPBNa3vGrKHi2qGEvT9UZomXDKG7iu+Z8EH9 1K6rGVQcKcJ5nqN2nmCO7xboqGVC1z/leCEzKpYhwj0CuZeJA2JSo8FdTEhv K+5z0qHilc6iX0umKwS6duuBdT8TuGyPM94zqFico2uTkAkH9ttptDdkhAnt f0+9vTQqhdN4JV394zix/C+6I/cCE3J3kK/le0rhhp3JpxXVeHCMtUOvixQL PEXNtOxtJLFL19PjWf+txvTbKe2dTiyQTb3oWK8lidvqLeOvD6/GD1qyjnZd Y8HDUariThFJXO2a6fT6vgDudXGiHPRngf7BP4JbiinYLa50zKRaEAs81HBx YucByY5HYmH8FHzx7wF7l11r8I2wZ3kDLew4XXVOUfcKGd/wDZ867EfCZycO u++wCQf+oHHbHi0y7pXs6GlrJOFNZh/0DK+Gg1x+mNKNv+LYg0divJYhhn+N ubVOB4WDzBaN03d8xPErlWMxA4QYlrzTcFK1MBx0tV00jbzEMOebRxW+0+JY YLB3rxf1IfgNB5WF7RHFz+/lz//eScG9rteVjnFEgMx+K8VXEyK4Tc7opr0f BW/+uWcsRy4CHKJHIq6Yi+BT6Z2HRCopuMeu5mOXfgRE91xXj1u3Bq/VOOPz 00gSO8ut2DfeiYDtrEpnyRRBzHCXn5cxlcIRNtake9JsHYmoN5E7wofHasbU +DbR8HqLRgvda5Fwa3v20qUUXsxX+k28xZaGuwbIoR7/f/eRlfDg6AQPbomK OPI4kh0HCxk+g62RUJ6n5jlxlxsfShBIF16h4Y0+JUPBelGwTVn7gMETDpxl e7eGWiGNFz1YbrW0aOBIgaWPFjNEcGrq0bMSMli1XXRrl0wsLPfXpDxvnCIc GXoKF3Vk8HQmV9zouVjobFO3eLp/kpCuNeTYe0oGGxs/ud+eEwtknY4JS6sx orTxpIlpigy23Hn95YP/4qC0NmSHeUM3odLQZ/lYWhb3+QceEo6MB4XlsYDN 6BMI6ife3Nkoi2/P/7u/OTUR7EgGCh+etYCnDK5b+imLqb/U/Yd5ksBDXjDH 6m07NJNHWiPHZfFlcsalSO0k6Mk66JY93gttDI1VpqvpuCTxSzz9SRJ4Hd+a lLo4AI4hbWXnyXRcmmhcI/4zCd72HX8YzTcMadyvLa1l6fh1yhOxUFoyfLNI EPEXnQADwa9V+VvoOLXadVY/Ihm8LGKMEqP+gN7ar3ekNei4UqnOIro5GZzB 8dCK7BTMzT1ZNNWh4xmZritZ5BRQkigfDs+YhoMiderHdtGx3hYzgcATKcDL 4TZ8YMssXC+UN9ugT8f1d8q8tOJTQFjw82qpgjnYLifgVbmbjn9Mkauae1JA vEh/YVhvAQg+6161PXR8xms03GlzKuzUKLd+/WERsl89qHFkt7+WMKIu4J4K 6OWZxrPGS3DgQb6XM6JjyMkvqipPhR//VfX+/vIPSP6Rxpp6dHyVkjX6mpQG ZcYpND2rFTiu9iGldgedrUt77fvPpEGj6OLYX3VOlGNxPd5UmY4jX4wnnBFK B2auTRpjnhMNLbjqgzwdb92+rfb72XTQJjceECrmQr8HSpxnaOz1VnhvGiXS IXFTmCwJ8aCVwEufCnjo+MoW6UH9WxnsfGv0WJqLF5nap7mUzcliu9yk2MLu DHD45PGytoIX5WkOGYcPyWJCZvWeLYZP4FjwNsl/e/lR9+gL5TvVstiae1UL SzYTZKIkl6sMBBBfa9a/vBuy2NDbqTFlOguuitYZreMWRAIC6fQxO1ncVLtd P+jKU9iq946rFwui/IrHFmMH2XYmZM95zT6Fwmz+aQ8dYSTo9HNEX4rtV/1n ZBRXZwPd+QRnkJgous6xorSL7c8VJfvnPOxfwGSnsFLIoBgq1vH4ueC1Ft94 NTVcJpkLHU20gyR9cbSxQ3jm4+G1uO62VOC5gFwgHblzVIB9701w6tztoLgW a9Z/vt0xmQtaMpmnDfeTUb3Ll0cSddL46ufkt1MdeWCqdSPwTrwE0lC6u9d8 tTR+0ygpUD+UDwVWXvpJilJositDMdaIiptesAx+rSoGGgSZiHhJoR45VYd6 ASrWHtT0Xt9eDI2svo3MBimkNTKEX1dJYdG7tQ9sCkqA75puep4bFUVW75XL Yp/v/CbMS9KCSoHWXfp3/gUNHZkuU79Ik8THybde5ZqXga45d+iFvzT03G/l 7N0GCrZIEogr/V0GGj+je+r2SaP62tXGTux8yDBZleN6txyMlrUu7vgujbam lU6G90rgC5suu8s0VUCx/lP5nVNrEV/4pFNzDBlXuh25ol5VCR+izo16a8og m97R7LsGZPy9xpL5PbYKSmheKYGeMmhfJnNIZkwc+9J2NNl4fgTDiKVjNfMy SIJke3xZTxzrC8qtFT1SA3IF12aeD8miiRP6J2c+k3DI5C/TksgG6KY/80MG cijzcZOPdZgwXm3aW8Q19wUyWl1o3yzl0OEk3qWECiEspapFW2lpgXcfWtKe XZJDem9CjynOCeJdqdevlBGt4MeSX5mKkUNfXcSeKFsI4ANHXfhz8tvgxNxP h8oeOfTuTL/VZgF+PGzbTprW6YCBq7OHeyfl0B45TZ0X2/iwaW3d6nKfTqDe 7z4qz8VAPaOal6ssePG1/ZVrhL50gWCF0Vp+WQaSD3kaMJjKjXnE/4oMHu+G SxPCn5cOMNDXWsVqOSUOvM6LpUV93Ae+v6U6fx1hIMftHbcZD5aJS5T1xs53 ++FNd/ho50kG4hoJOTVQvUTs1Pkx6HhzAFbUwnX7HBkoLe60kb/2AmG752b/ yt1ByHRXnxu5wEA3+6dVQy7OETY+8tqnE4fAt3A0a/IyA5VZb4v+mTxD3Duf wslZMQwZR/Pnp68ykLg0bTGmeYqoXveiXn9qBJqSeW6NuzPQy8RA7WbuSeJy qItZ4NZRcGkKqe30YCBSfX7Wk20TxB5NyRJFrzHoc+F0Idg8c9FBxh7/JtxI 74cDmsfhsLtgVyjbTs7hQb311CEi8bPuwYX4CZgV803bxx539z/gx679RKhv oeaZE38gY2Px9oFLDFRIVc1zf99NpA3ahKyjTsJ2S3Uup/MM1B4wXMOj+oNQ 3DDHsuqZhPy3TFUBWwZaEDaf2jBQQ5Q3SWe+Cp4GcvSnhUYbBqpaar1w8FoN 8U41PtMwfBpoF3x8Y9hciOeDwEWeGoJUp3qpO3oa3p2hVmxg8z/fy3Jfrqsm dM/wHpNi5/1q3ftr9U8x0KvN/CObbaqIvbaxnnF4GgZf/KM5WDHQlQVur79f K4jxgDE0NzMNlJ7t0r7mDKSyOXorJbyI2L0nN5j3zAx8O/LMAdjce87TTvnl G6KDMy2lxXEGknw+uS6fYCBPXfH/9BsKCYdHZQFPXGdA9wFvnhebrxHS13EQ KCDu63xJM/Wegf1HvXmuHGegvhM0iTT/XCIuIPXsm+gZoG3c23D0KAM9HnJ2 qu7PIJK53YY7Ps3AwZlnTSJsnvh96ewnRjoxNVmeXdM6A+OCp8Jr2P4meGiN RrN1KpGsuVunqGMGZD8F7wE2b5VV6Mh8lkgIKv0riBuZgXnC7ryCGQPtqMsk 3wxmEU7FpTvc+WchdeTGgc7DDFRqavG6ni+E+H3ox7HLa2ahpTm7N5LNM9Zd uxQ3G0gYigfvuigxCxcfGu7nZ3NRjrbnPuYuxERsvduF9bMQtz+DRJgyUMBU xngYWQa0JW6Uum6ahZ7LfFHubD6YZUYbULoADSpDLVfUZiGdw+6rCpvXBYad S8m/CVvQhqLrO2bhv578pj4TBrLaHcG31eU2tD1Bjn4wC/8D+h13Hg== "]]}}, Axes->True, BoxRatios->1, ImageSize->{360., 383.7433325456768}, PlotRange->{All, All, All}, PlotRangePadding->{Automatic, Automatic, Automatic}, ViewPoint->{-2.6957256078819203`, -1.711803724316359, 1.119281669833958}, ViewVertical->{-0.27329035357222264`, -0.11340061999714979`, 0.9552238910478692}]], "Output", CellChangeTimes->{3.4343839597406*^9, 3.4343844333546*^9, 3.4343844892785997`*^9, 3.4343846491076*^9}] }, Open ]] }, WindowSize->{616, 594}, WindowMargins->{{227, Automatic}, {Automatic, 45}}, FrontEndVersion->"6.0 for Microsoft Windows (32-bit) (June 19, 2007)", StyleDefinitions->"Default.nb" ] (* End of Notebook Content *) (* Internal cache information *) (*CellTagsOutline CellTagsIndex->{} *) (*CellTagsIndex CellTagsIndex->{} *) (*NotebookFileOutline Notebook[{ Cell[568, 21, 567, 11, 47, "Text"], Cell[1138, 34, 320, 9, 72, "Input"], Cell[1461, 45, 1188, 38, 92, "Input"], Cell[2652, 85, 4939, 105, 452, "Input"], Cell[CellGroupData[{ Cell[7616, 194, 685, 16, 52, "Input"], Cell[8304, 212, 51351, 846, 399, "Output"] }, Open ]] } ] *) (* End of internal cache information *)