(* Content-type: application/vnd.wolfram.mathematica *)
(*** Wolfram Notebook File ***)
(* http://www.wolfram.com/nb *)
(* CreatedBy='Mathematica 10.0' *)
(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[ 158, 7]
NotebookDataLength[ 331416, 5967]
NotebookOptionsPosition[ 266606, 4673]
NotebookOutlinePosition[ 323325, 5834]
CellTagsIndexPosition[ 323245, 5829]
WindowFrame->Normal*)
(* Beginning of Notebook Content *)
Notebook[{
Cell[CellGroupData[{
Cell["", "SlideShowNavigationBar", "FirstSlide",
CellTags->
"SlideShowHeader",ExpressionUUID->"8bda16c8-8161-41a0-869e-f5cfbbfdf7f8"],
Cell["\<\
Building the Automated Data Scientist:
The New Classify & Predict \
\>", "Title",
CellChangeTimes->{{3.448190122176695*^9, 3.44819012385317*^9}, {
3.485609127497636*^9, 3.485609133015955*^9}, {3.514308355088097*^9,
3.514308374696691*^9}, 3.5146594348020153`*^9, 3.5146601881617107`*^9, {
3.717416719012639*^9, 3.7174167406766043`*^9}, {3.7174405961433268`*^9,
3.717440596455831*^9}},ExpressionUUID->"00e36f01-9348-4f94-aa29-\
323cc3d758e3"],
Cell["Etienne Bernard, Wolfram Research", "Subtitle",
CellChangeTimes->{{3.485609136120798*^9, 3.4856091511532907`*^9}, {
3.4856091945334663`*^9, 3.485609199379443*^9}, {3.4951031489375*^9,
3.49510314984375*^9}, {3.495106455296875*^9, 3.495106455453125*^9}, {
3.5143083846926413`*^9, 3.514308395249558*^9}, 3.5443793532699003`*^9,
3.621626517580729*^9, {3.621626691998458*^9, 3.6216267186543407`*^9}, {
3.621695156698331*^9, 3.621695160632772*^9}, {3.622213306499199*^9,
3.622213328771823*^9}, {3.717416747724378*^9,
3.71741677814684*^9}},ExpressionUUID->"a60c62de-85fe-4d5b-a531-\
415918ca4968"],
Cell[TextData[{
Cell[BoxData[
GraphicsBox[{InsetBox[
GraphicsBox[{},
ContentSelectable->True,
ImageSize->{480, 360},
PlotRange->{{0, 480/360}, {0, 1}}], Scaled[{0, 0}], Center,
Scaled[{0.5, 0.5}]], InsetBox[
GraphicsBox[
TagBox[RasterBox[CompressedData["
1:eJztW7uO20YUXSQpUuoTmD9QmZIG0qQTHKSfNWIbaRzBDhCkY+HCQGBrbe9m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"], {{0, 68}, {65, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
BaseStyle->"ImageGraphics",
ImageSizeRaw->{65, 68},
PlotRange->{{0, 65}, {0, 68}}],
Scaled[{0.49333580155497714, 0.5717682253254397}],
Center, {1.1979558513699555, 0.9210339753942228}, {{1., 0.}, {0., 1.}}]},
AspectRatio->1.0295620437956206`,
ContentSelectable->True,
ImageMargins->0.,
ImagePadding->{{0., 0.}, {0., 0.}},
ImageSize->{74., 77.5},
PlotRange->{{0., 1.3333333333333335`}, {0., 1.}},
PlotRangePadding->Automatic]],ExpressionUUID->
"e10bc11d-2b27-48d8-bf0a-d2d6820b8574"],
StyleBox[" ",
FontColor->RGBColor[
0.5019607843137255, 0.5019607843137255, 0.5019607843137255]],
StyleBox["Join the Conversation ",
FontColor->RGBColor[
0.9019607843137255, 0.9019607843137255, 0.9019607843137255]],
"#WolframTechConf"
}], "Text",
CellFrame->{{0, 0}, {0, 1}},
ShowCellBracket->Automatic,
CellMargins->{{80, 80}, {100, 165}},
CellFrameMargins->{{0, 0}, {0, 50}},
CellFrameColor->RGBColor[0.886275, 0.364706, 0.427451],
CellChangeTimes->{{3.6216253798451433`*^9, 3.621625396205482*^9},
3.6216255185076437`*^9, {3.621625573653562*^9, 3.6216256020928392`*^9}, {
3.621625635821653*^9, 3.621625645324601*^9}, {3.621625678952072*^9,
3.62162572395792*^9}, {3.621625867660451*^9, 3.62162588677988*^9}, {
3.621625982321312*^9, 3.621625984476396*^9}},
TextAlignment->Center,
FontFamily->"Arial",
FontSize->24,
FontColor->GrayLevel[
1],ExpressionUUID->"9940dca6-90d5-4d58-943d-3773b318f845"]
}, Open ]],
Cell[CellGroupData[{
Cell["", "SlideShowNavigationBar",
CellTags->
"SlideShowHeader",ExpressionUUID->"4a0379b0-5018-4d40-a382-1eaf4d20f80d"],
Cell[CellGroupData[{
Cell[TextData[{
"Automated Data Scientist ",
Cell[BoxData[
GraphicsBox[
TagBox[RasterBox[CompressedData["
1:eJzsnQmcTfX7x+v3+5V938YwYzerQZaskTUqKUKpfiiypA1F1iJbRLIVQpay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"], {{0, 200}, {
304, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSize->{103.01874999999762`, Automatic},
ImageSizeRaw->{304, 200},
PlotRange->{{0, 304}, {0, 200}}]], "Input",ExpressionUUID->
"5901a4ca-5b93-4821-87be-9c43fd936399"]
}], "Section",
CellChangeTimes->{
3.483202458955147*^9, {3.514308340990994*^9, 3.514308352103572*^9}, {
3.7174168716794567`*^9, 3.717416875199505*^9}, {3.717416950713819*^9,
3.717416952094675*^9}, {3.7174347357471*^9, 3.7174347457742567`*^9}, {
3.7174355706775827`*^9, 3.717435596228953*^9},
3.717437599915228*^9},ExpressionUUID->"6d5c40bc-43f4-4592-9d2c-\
fc8c046877d4"],
Cell[TextData[{
StyleBox["Human:",
FontWeight->"Bold"],
" \[OpenCurlyDoubleQuote]",
StyleBox["How many croissants are we going to sell next Sunday?\
\[CloseCurlyDoubleQuote]\n\n",
FontSlant->"Italic"],
StyleBox["Computer:",
FontWeight->"Bold"],
StyleBox[" \[OpenCurlyDoubleQuote]According to your recorded data and other \
factors such as the predicted weather, there is a 90% chance that between 62 \
and 67 croissants will be sold.\[CloseCurlyDoubleQuote]",
FontSlant->"Italic"]
}], "Text",
CellChangeTimes->{{3.717434517884185*^9, 3.717434533705785*^9}, {
3.7174347546616163`*^9, 3.7174347568037777`*^9}, {3.7174348358888617`*^9,
3.7174348390226297`*^9}, {3.7174349127987947`*^9,
3.717435007935177*^9}},ExpressionUUID->"e9e24cf8-09f3-4ecf-a320-\
391998062cba"],
Cell[CellGroupData[{
Cell["Human understanding", "Item",
CellChangeTimes->{{3.7174171881841793`*^9, 3.717417235014893*^9}, {
3.7174344236036663`*^9,
3.7174344343717318`*^9}},ExpressionUUID->"8a0c5ff2-a12b-4f51-b5b8-\
97fcb2e209b3"],
Cell["Data understanding", "Item",
CellChangeTimes->{{3.7174171881841793`*^9, 3.717417203520605*^9}, {
3.7174172388147306`*^9, 3.717417247087435*^9}, {3.717434458213766*^9,
3.717434464975917*^9}},ExpressionUUID->"682390a8-068b-458a-9606-\
2d3e33c4a337"],
Cell["Accessing external data", "Item",
CellChangeTimes->{{3.7174171881841793`*^9, 3.717417203520605*^9}, {
3.7174172388147306`*^9, 3.7174172814654427`*^9}, {3.71743447385319*^9,
3.717434485043709*^9}, {3.717436363315249*^9,
3.717436364979492*^9}},ExpressionUUID->"2a135abf-8c46-47b3-b2e2-\
8ebf9be88cd7"],
Cell["Automatic modeling", "Item",
CellChangeTimes->{{3.7174171881841793`*^9, 3.717417203520605*^9}, {
3.7174172388147306`*^9, 3.717417289104718*^9},
3.71741795028379*^9},ExpressionUUID->"580f36ec-956b-4252-a5ee-\
bbc2ede148ac"],
Cell["Communicating results back", "Item",
CellChangeTimes->{{3.7174171881841793`*^9, 3.717417203520605*^9}, {
3.7174172388147306`*^9, 3.717417326304555*^9}, {3.717434496647623*^9,
3.717434497116364*^9}},ExpressionUUID->"44add79d-81d1-4775-ab40-\
2df463f0ffc4"]
}, Open ]]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell["", "SlideShowNavigationBar",
CellTags->
"SlideShowHeader",ExpressionUUID->"9950165c-2a91-4f6a-b8df-d4f0183ef671"],
Cell[CellGroupData[{
Cell[TextData[{
"Classify & Predict ",
Cell[BoxData[
GraphicsBox[
TagBox[RasterBox[CompressedData["
1:eJztffmTJVd1JjPzy/w4/4CjQ4oOKVoKKURIhICwCIED0IBkBwg7QCCHkUB4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"], {{0, 309}, {355, 0}}, {0,
255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
BaseStyle->"ImageGraphics",
ImageSize->{93.27552083333313, Automatic},
ImageSizeRaw->{355, 309},
PlotRange->{{0, 355}, {0, 309}}]],
CellChangeTimes->{
3.705189005301854*^9, {3.705189065107217*^9, 3.705189120702427*^9}, {
3.705189189280822*^9, 3.705189198446656*^9}, 3.7058823734187193`*^9},
ExpressionUUID->"2e813565-1551-457b-8eb2-7eb3256d8c62"]
}], "Section",
CellChangeTimes->{
3.483202458955147*^9, {3.514308340990994*^9, 3.514308352103572*^9}, {
3.7174168716794567`*^9, 3.717416875199505*^9}, {3.717416950713819*^9,
3.717416952094675*^9}, {3.717417150213079*^9, 3.717417152579282*^9}, {
3.717437588762929*^9,
3.717437595923511*^9}},ExpressionUUID->"697f8473-e998-4e85-a312-\
973ad4e761a6"],
Cell[CellGroupData[{
Cell["First version in 10.0 (3 years ago)", "Item",
CellChangeTimes->{{3.7174179247656317`*^9, 3.7174179521327457`*^9}, {
3.71741801495715*^9,
3.717418027540369*^9}},ExpressionUUID->"1df1a20c-3cea-4dcf-b267-\
74efa440c91f"],
Cell["Automatic modeling", "Item",
CellChangeTimes->{{3.7174179247656317`*^9, 3.7174179521327457`*^9}, {
3.7174180143815536`*^9, 3.7174180143816757`*^9}, {3.7174183556674347`*^9,
3.717418355667573*^9}},ExpressionUUID->"07270b16-c810-411f-8165-\
ddd1bc1be1a2"],
Cell["Supervised Learning", "Item",
CellChangeTimes->{{3.7174179247656317`*^9, 3.7174179521327457`*^9}, {
3.7174180143815536`*^9, 3.7174180143816757`*^9}, {3.7174183563475103`*^9,
3.717418358699514*^9}},ExpressionUUID->"5f99b212-bebb-40e8-82ce-\
892b6df38ba3"]
}, Open ]],
Cell[BoxData[
RowBox[{"c", "=",
RowBox[{"Classify", "[",
RowBox[{"{",
RowBox[{
RowBox[{"1", "\[Rule]", "\"\\""}], ",",
RowBox[{"2", "\[Rule]", "\"\\""}], ",",
RowBox[{"3.5", "\[Rule]", "\"\\""}], ",",
RowBox[{"4", "\[Rule]", "\"\\""}]}], "}"}], "]"}]}]], "Input",
CellChangeTimes->{{3.71741800045323*^9, 3.7174180333244133`*^9}, {
3.717426413989749*^9,
3.7174264763606787`*^9}},ExpressionUUID->"911aba43-4d15-4f9d-a105-\
75ab444b8065"]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell["", "SlideShowNavigationBar",
CellTags->
"SlideShowHeader",ExpressionUUID->"5403f1cd-7206-4437-ac04-dc8c94ceca25"],
Cell[CellGroupData[{
Cell[TextData[{
"Training Progress Panel\t ",
Cell[BoxData[
GraphicsBox[
TagBox[RasterBox[CompressedData["
1:eJzsvetblHea78s+vNgv9z+wr7X3XLPWTB+SN3uvWTN9Smb2dNKrk07SmUMO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"], {{0, 344}, {544, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSize->{110.74583333333337`, Automatic},
ImageSizeRaw->{544, 344},
PlotRange->{{0, 544}, {0, 344}}]], "Input",ExpressionUUID->
"a7a9c22c-0003-4cbc-ae3d-8b1c24e69aca"]
}], "Section",
CellChangeTimes->{
3.483202458955147*^9, {3.514308340990994*^9, 3.514308352103572*^9}, {
3.7174168716794567`*^9, 3.717416875199505*^9}, {3.717416950713819*^9,
3.717416952094675*^9}, {3.717417163452755*^9, 3.7174171661067457`*^9}, {
3.717418163354713*^9, 3.7174181691446333`*^9}, {3.717436959768865*^9,
3.717437024275795*^9}},ExpressionUUID->"9d42ffc9-95cd-4ef9-b9d0-\
a9123bb5c43e"],
Cell[CellGroupData[{
Cell["Progress bar", "Item",
CellChangeTimes->{{3.717437008091358*^9, 3.717437030594296*^9}, {
3.717437065037292*^9,
3.7174370805880623`*^9}},ExpressionUUID->"cf4258a5-415c-43ea-b94f-\
da474301bf7c"],
Cell["Current values", "Item",
CellChangeTimes->{{3.717437008091358*^9, 3.717437030594296*^9}, {
3.717437065037292*^9,
3.717437101045416*^9}},ExpressionUUID->"e2c5b189-1e14-477f-a3ae-\
40b69043b44c"],
Cell["Learning curves", "Item",
CellChangeTimes->{{3.717437008091358*^9, 3.717437030594296*^9}, {
3.717437065037292*^9,
3.717437103542698*^9}},ExpressionUUID->"609e6dc2-1129-491f-883d-\
f1d1415e7985"],
Cell["Stop button", "Item",
CellChangeTimes->{{3.717437008091358*^9, 3.717437030594296*^9}, {
3.717437065037292*^9,
3.717437089755745*^9}},ExpressionUUID->"3e612234-9ff1-4f12-a04b-\
385354eb16b1"],
Cell[TextData[{
"Controlled by ",
StyleBox["TrainingProgressReporting",
FontWeight->"Bold"]
}], "Item",
CellChangeTimes->{{3.717437199226438*^9, 3.717437224774023*^9}, {
3.717437481091551*^9,
3.717437500384099*^9}},ExpressionUUID->"df29bf42-69d1-4c90-b327-\
357a83dc8adc"],
Cell[CellGroupData[{
Cell["\"Panel\"", "Subitem",
CellChangeTimes->{{3.717437206453617*^9,
3.717437242480679*^9}},ExpressionUUID->"1d237fa8-a1ba-4f0e-a95e-\
ea4eb187c13b"],
Cell["None", "Subitem",
CellChangeTimes->{
3.717437206453617*^9, {3.717437254513844*^9,
3.717437267769102*^9}},ExpressionUUID->"f1b90eee-8e49-4b67-a3fa-\
8294486a355b"],
Cell["\"Print\"", "Subitem",
CellChangeTimes->{{3.717437206453617*^9,
3.717437247080372*^9}},ExpressionUUID->"c4277496-93af-4a69-9209-\
96830f68f00d"]
}, Open ]],
Cell[TextData[StyleBox["TimeGoal",
FontWeight->"Bold"]], "Item",
CellChangeTimes->{{3.7174409775915194`*^9,
3.717440981053927*^9}},ExpressionUUID->"d7e1c06d-5fee-4a47-9dc5-\
69d1898241d9"]
}, Open ]],
Cell[BoxData[
RowBox[{
RowBox[{"mnist", "=",
RowBox[{"RandomSample", "[",
RowBox[{
RowBox[{"ResourceData", "[", "\"\\"", "]"}], ",", "10000"}],
"]"}]}], ";"}]], "Input",
CellChangeTimes->{{3.717436540054159*^9, 3.717436558883461*^9}, {
3.717436621765764*^9,
3.717436622909513*^9}},ExpressionUUID->"2c0181ab-0dee-421b-a990-\
15a6b703e226"],
Cell[BoxData[
RowBox[{"c", "=",
RowBox[{"Classify", "[", "mnist", "]"}]}]], "Input",
CellChangeTimes->{{3.717436570627335*^9, 3.717436572851177*^9}, {
3.717436627739452*^9, 3.71743666097248*^9}, {3.717436775939783*^9,
3.717436776337797*^9}, {3.7174373024109983`*^9, 3.717437311090568*^9}, {
3.717437406691833*^9, 3.717437432900508*^9}, {3.717510066548934*^9,
3.717510069122342*^9}},ExpressionUUID->"e92be1a5-3f35-4df8-992b-\
da30f0a72d97"]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell["", "SlideShowNavigationBar",
CellTags->
"SlideShowHeader",ExpressionUUID->"d5886e6f-1aec-43d0-bc77-c5e0a432cfd6"],
Cell[CellGroupData[{
Cell[TextData[{
"ClassifierInformation / PredictorInformation ",
Cell[BoxData[
GraphicsBox[
TagBox[RasterBox[CompressedData["
1:eJztvWlUHFea98nMvB/m43yec+bDzOmeri63/e3t6VPlKnvOvGX3uFy2S109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"], {{0, 260}, {538, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSize->{151.6635416666678, Automatic},
ImageSizeRaw->{538, 260},
PlotRange->{{0, 538}, {0, 260}}]], "Input",ExpressionUUID->
"05af675b-60ff-41ce-9cbe-b602a9fb1f33"]
}], "Section",
CellChangeTimes->{
3.483202458955147*^9, {3.514308340990994*^9, 3.514308352103572*^9}, {
3.7174168716794567`*^9, 3.717416875199505*^9}, {3.717416950713819*^9,
3.717416952094675*^9}, {3.717417163452755*^9, 3.7174171661067457`*^9}, {
3.71741817771391*^9, 3.717418184208457*^9}, {3.717438115951744*^9,
3.717438120923253*^9}},ExpressionUUID->"167406a6-39ae-4757-b9c3-\
f8846682e0cf"],
Cell[CellGroupData[{
Cell["\<\
Input type, number of classes, number of training examples, etc.\
\>", "Item",
CellChangeTimes->{{3.717437737743347*^9, 3.717437745390829*^9}, {
3.717437783304038*^9, 3.717437842278512*^9}, {3.717441427095022*^9,
3.717441427787765*^9}},ExpressionUUID->"68c74b27-335f-4ba7-8a01-\
411c278791d3"],
Cell["Quality of the model:", "Item",
CellChangeTimes->{{3.717437737743347*^9, 3.717437745390829*^9},
3.717437783304038*^9},ExpressionUUID->"1b425a1b-8004-4374-9974-\
381061d5824e"],
Cell[CellGroupData[{
Cell["Loss, Accuracy", "Subitem",
CellChangeTimes->{{3.717437206453617*^9, 3.717437242480679*^9}, {
3.717437753696278*^9,
3.7174377583931427`*^9}},ExpressionUUID->"abc873d8-bb53-4b2e-9259-\
648a0ecbfb7c"],
Cell["Evaluation speed", "Subitem",
CellChangeTimes->{{3.717437206453617*^9, 3.717437242480679*^9}, {
3.717437753696278*^9,
3.717437766471499*^9}},ExpressionUUID->"e39c198a-8e88-43e7-afb6-\
eea3b1be26e3"],
Cell["Model memory", "Subitem",
CellChangeTimes->{{3.717437206453617*^9, 3.717437242480679*^9}, {
3.717437753696278*^9,
3.717437791679892*^9}},ExpressionUUID->"56e7e08f-d5aa-4fc2-9837-\
8354a50f5f9e"]
}, Open ]],
Cell["Method and hyperparameters", "Item",
CellChangeTimes->{{3.717437737743347*^9, 3.717437745390829*^9},
3.717437783304038*^9, {3.717437815063118*^9, 3.7174378256229486`*^9}, {
3.717437870304577*^9,
3.71743787030497*^9}},ExpressionUUID->"363a8069-ee6c-456d-9336-\
a5c168b2faed"],
Cell["Learning curves", "Item",
CellChangeTimes->{{3.717437737743347*^9, 3.717437745390829*^9},
3.717437783304038*^9, {3.717437815063118*^9, 3.7174378256229486`*^9}, {
3.717437870821672*^9,
3.7174378734856367`*^9}},ExpressionUUID->"c724ac4c-891f-49cc-b4c8-\
7a7ee140f687"]
}, Open ]]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell["", "SlideShowNavigationBar",
CellTags->
"SlideShowHeader",ExpressionUUID->"d20a6431-3da4-4796-9240-2394732efa48"],
Cell[CellGroupData[{
Cell[TextData[{
"Methods ",
Cell[BoxData[
GraphicsBox[
TagBox[RasterBox[CompressedData["
1:eJzsnQm8lfPWx+saMqU5NGjQnDQXGiQpmjTPkkaVSkiGTGWIVISM0YAIIaJo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"], {{0, 295}, {1042, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSize->{197.27437500000022`, Automatic},
ImageSizeRaw->{1042, 295},
PlotRange->{{0, 1042}, {0, 295}}]], "Input",ExpressionUUID->
"727c4203-10f5-4a03-a9e7-08d01b221ff0"]
}], "Section",
CellChangeTimes->{
3.483202458955147*^9, {3.514308340990994*^9, 3.514308352103572*^9}, {
3.7174168716794567`*^9, 3.717416875199505*^9}, {3.717416950713819*^9,
3.717416952094675*^9}, {3.717417163452755*^9, 3.7174171661067457`*^9}, {
3.71741817771391*^9, 3.717418190550376*^9}, {3.7174390144028387`*^9,
3.71743903802026*^9}},ExpressionUUID->"2a049373-674e-4937-ab00-\
36de3e252f55"],
Cell[CellGroupData[{
Cell["All methods are documented", "Item",
CellChangeTimes->{{3.717418247089527*^9, 3.717418251771468*^9}, {
3.7174184997667522`*^9, 3.717418505520686*^9}, {3.717438173589657*^9,
3.7174381741301813`*^9}},ExpressionUUID->"4b881169-14e4-4e57-92a4-\
5c93d1d4988f"],
Cell["New methods:", "Item",
CellChangeTimes->{{3.717418247089527*^9, 3.717418251771468*^9}, {
3.7174184997667522`*^9, 3.717418504062482*^9}, {3.717438179162071*^9,
3.717438181121991*^9}},ExpressionUUID->"f62a28e3-8a7e-426b-ab5c-\
2503c900e3d6"],
Cell[CellGroupData[{
Cell["DecisionTree", "Subitem",
CellChangeTimes->{{3.71743819060181*^9,
3.717438193050145*^9}},ExpressionUUID->"537a996f-a351-47bd-82f7-\
1cbdfe1d0879"],
Cell["GradientBoostedTrees", "Subitem",
CellChangeTimes->{{3.71743819060181*^9,
3.717438197793503*^9}},ExpressionUUID->"bb0f532a-439e-4da7-b4cd-\
0fbbe6ec4d37"]
}, Open ]],
Cell["Improved methods:", "Item",
CellChangeTimes->{{3.717418247089527*^9, 3.717418251771468*^9}, {
3.7174184997667522`*^9, 3.717418504062482*^9}, {3.717438179162071*^9,
3.717438181121991*^9}, {3.717440790404043*^9,
3.717440795803617*^9}},ExpressionUUID->"b8ebb412-9aaf-4d8a-be45-\
ffc0c8babd13"],
Cell[CellGroupData[{
Cell["NeuralNetwork", "Subitem",
CellChangeTimes->{{3.71743819060181*^9, 3.717438197793503*^9}, {
3.7174408036999702`*^9,
3.717440808499609*^9}},ExpressionUUID->"5b6a948b-aa59-40b0-9bc9-\
ac3ac2195bae"],
Cell["LinearRegresion & LogisticRegression", "Subitem",
CellChangeTimes->{{3.71743819060181*^9, 3.717438197793503*^9}, {
3.7174408036999702`*^9,
3.7174408277453957`*^9}},ExpressionUUID->"88eaa068-3c3e-4aaa-80c0-\
cf6506af84a6"]
}, Open ]]
}, Open ]],
Cell[BoxData[""], "Input",
CellChangeTimes->{{3.717440781203051*^9,
3.717440781978572*^9}},ExpressionUUID->"24deabd0-9e5f-4367-bc78-\
4827e8c53ec6"]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell["", "SlideShowNavigationBar",
CellTags->
"SlideShowHeader",ExpressionUUID->"c75a4f09-68d7-4fff-b1b2-b6a893272d3c"],
Cell[CellGroupData[{
Cell[TextData[{
"Under the Hood... ",
Cell[BoxData[
GraphicsBox[
TagBox[RasterBox[CompressedData["
1:eJzsfQd8E0f2/ya5mstdkuu/5BIgIcmRnksgBdJJSEJCL6EmgOnNVNsYsGmu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"], {{0, 326}, {
500, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSize->{138.7062500000003, Automatic},
ImageSizeRaw->{500, 326},
PlotRange->{{0, 500}, {0, 326}}]],ExpressionUUID->
"2e3873a8-4c3d-4bd5-8131-4a69911daaf4"]
}], "Section",
CellChangeTimes->{
3.483202458955147*^9, {3.514308340990994*^9, 3.514308352103572*^9}, {
3.7174168716794567`*^9, 3.717416875199505*^9}, {3.717416950713819*^9,
3.717416952094675*^9}, {3.717417169498444*^9, 3.717417171586392*^9}, {
3.71741831738483*^9, 3.717418317669423*^9}, {3.71743913861837*^9,
3.71743914023248*^9}, {3.717439186053809*^9, 3.717439194762368*^9}, {
3.717440719294141*^9,
3.717440726610342*^9}},ExpressionUUID->"286bf549-c6a4-488b-b633-\
8de124892c6f"],
Cell[CellGroupData[{
Cell["New automation procedure", "Item",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392261145477`*^9,
3.717439226114744*^9}},ExpressionUUID->"97d7eafc-c595-414a-b80f-\
c7c8f7c7b240"],
Cell["Goal: find best configuration (method + hyperparameters)", "Item",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.7174393706284313`*^9}, {3.7174414548069277`*^9,
3.717441457398869*^9}},ExpressionUUID->"c642da4b-4446-429c-989a-\
d592b5f35ea4"],
Cell["Procedure:", "Item",
CellChangeTimes->{{3.717439399101318*^9,
3.7174394036874638`*^9}},ExpressionUUID->"9a311fc9-a8dd-4694-968d-\
a3f143d379d9"],
Cell[CellGroupData[{
Cell["Start with a set of configurations", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.717439417854246*^9}, {3.717439844521407*^9,
3.7174398454018383`*^9}},ExpressionUUID->"abbfc901-7e73-4919-9a43-\
9dda974a85b3"],
Cell["Train configurations on a small dataset \
(\[OpenCurlyDoubleQuote]experiments\[CloseCurlyDoubleQuote])", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.7174394814844093`*^9}, {3.717440679826009*^9,
3.7174406811758337`*^9}},ExpressionUUID->"d5c10663-fae8-46e1-9aba-\
dde45fd5dc4f"],
Cell["\<\
Predict how well the configurations would perform on the full dataset\
\>", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.7174394814844093`*^9}, {3.717440679826009*^9,
3.7174406803383093`*^9}},ExpressionUUID->"cdfe4ced-459d-4d71-b744-\
c032f2242f27"],
Cell["Give more data to promising configurations", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.717439483003414*^9}, {3.7174398585599813`*^9, 3.717439917740547*^9}, {
3.717439965139497*^9, 3.717439985241075*^9}, {3.717440663873505*^9,
3.7174406721302223`*^9}},ExpressionUUID->"0e728ad5-32f3-4d33-b3df-\
3273bfd0ff14"]
}, Open ]],
Cell["Training time at least linear \[Rule] experiments are almost free", \
"Item",
CellChangeTimes->{{3.717440006916462*^9, 3.717440077285934*^9}, {
3.717441496236433*^9,
3.717441497386632*^9}},ExpressionUUID->"bb1b0121-7837-4bec-bc11-\
fb2c2ae5272b"],
Cell["Side effects:", "Item",
CellChangeTimes->{{3.7118401879760427`*^9, 3.7118402206191053`*^9}, {
3.717440882350272*^9,
3.717440899950816*^9}},ExpressionUUID->"5469fc6e-a9e3-4f91-9dd6-\
d9dd2432c85d"],
Cell[CellGroupData[{
Cell["Progress bar", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.717439483003414*^9}, {3.7174398585599813`*^9, 3.717439917740547*^9}, {
3.717439965139497*^9, 3.717439985241075*^9}, {3.717440663873505*^9,
3.7174406721302223`*^9}, {3.717440904985751*^9, 3.7174409116922703`*^9}, {
3.717441253146841*^9,
3.717441261317498*^9}},ExpressionUUID->"0c24741c-dcc5-464d-8a95-\
57c33c320783"],
Cell["Abortability", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.717439483003414*^9}, {3.7174398585599813`*^9, 3.717439917740547*^9}, {
3.717439965139497*^9, 3.717439985241075*^9}, {3.717440663873505*^9,
3.7174406721302223`*^9}, {3.717440905208583*^9, 3.717440913925981*^9}, {
3.7174412413488092`*^9, 3.717441248682768*^9}, {3.717441282052005*^9,
3.717441298657494*^9}},ExpressionUUID->"9b62392e-cf5e-444d-bf1e-\
40419a8c73ab"],
Cell["TimeGoal", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.717439483003414*^9}, {3.7174398585599813`*^9, 3.717439917740547*^9}, {
3.717439965139497*^9, 3.717439985241075*^9}, {3.717440663873505*^9,
3.7174406721302223`*^9}, {3.71744090536077*^9, 3.717440915949671*^9}, {
3.717441319451826*^9,
3.717441321168453*^9}},ExpressionUUID->"d44f6bf0-a4c0-4f89-bfd7-\
f1dffc4d08a8"],
Cell["\<\
Works even when method & hyperparameters are specified by the user\
\>", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.717439483003414*^9}, {3.7174398585599813`*^9, 3.717439917740547*^9}, {
3.717439965139497*^9, 3.717439985241075*^9}, {3.717440663873505*^9,
3.7174406721302223`*^9}, {3.717440922285528*^9, 3.71744092315353*^9}, {
3.717441331216494*^9, 3.717441344671789*^9}, {3.7174415301360817`*^9,
3.717441534121237*^9}},ExpressionUUID->"b2e3184b-e26c-4e04-9bd3-\
5d5c3cac7dbd"],
Cell["Model performance estimation", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.717439483003414*^9}, {3.7174398585599813`*^9, 3.717439917740547*^9}, {
3.717439965139497*^9, 3.717439985241075*^9}, {3.717440663873505*^9,
3.7174406721302223`*^9}, {3.717440922285528*^9,
3.7174409349921494`*^9}},ExpressionUUID->"4b420ff9-33fc-40eb-bc7f-\
0adb805c41d2"],
Cell["Learning curves", "Subitem",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9},
3.717438808376582*^9, {3.717439153677747*^9, 3.717439161073928*^9}, {
3.7174392280987263`*^9, 3.7174392325857563`*^9}, {3.717439325100257*^9,
3.717439483003414*^9}, {3.7174398585599813`*^9, 3.717439917740547*^9}, {
3.717439965139497*^9, 3.717439985241075*^9}, {3.717440663873505*^9,
3.7174406721302223`*^9}, {3.717440922285528*^9,
3.717440939910954*^9}},ExpressionUUID->"44c35e4d-b612-4668-ac41-\
1fb89d377a5a"]
}, Open ]]
}, Open ]]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell["", "SlideShowNavigationBar",
CellTags->
"SlideShowHeader",ExpressionUUID->"645f0393-acc3-47a9-9994-f29e46e0bcd5"],
Cell[CellGroupData[{
Cell["Future of Automation?", "Section",
CellChangeTimes->{
3.483202458955147*^9, {3.514308340990994*^9, 3.514308352103572*^9}, {
3.7174168716794567`*^9, 3.717416875199505*^9}, {3.717416950713819*^9,
3.717416952094675*^9}, {3.717417169498444*^9, 3.717417171586392*^9}, {
3.71741831738483*^9, 3.717418317669423*^9}, {3.717438761005207*^9,
3.7174387642589493`*^9}, {3.717441078851926*^9,
3.717441116691937*^9}},ExpressionUUID->"f9989c77-4308-43e8-b830-\
91537ff675aa"],
Cell[CellGroupData[{
Cell["Include pre-processing in the procedure", "Item",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9}, {
3.7174387705276833`*^9, 3.717438788175097*^9}, {3.717440509897855*^9,
3.717440540653863*^9}, {3.717441053817747*^9, 3.7174410538178873`*^9}, {
3.717441100909816*^9,
3.71744110783418*^9}},ExpressionUUID->"f5b1ed4c-7d12-43cb-a31f-\
b7703d2febe0"],
Cell["Method combinations", "Item",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9}, {
3.7174387705276833`*^9, 3.717438788175097*^9}, {3.717440509897855*^9,
3.717440540653863*^9}, {3.717441054133934*^9,
3.717441056528709*^9}},ExpressionUUID->"27d28bdc-c422-40eb-818c-\
98df92917325"],
Cell["Meta-learning a.k.a. \[OpenCurlyDoubleQuote]Learning to learn\
\[CloseCurlyDoubleQuote]", "Item",
CellChangeTimes->{{3.717418511515278*^9, 3.7174185139807243`*^9}, {
3.7174387705276833`*^9,
3.717438862051723*^9}},ExpressionUUID->"f4727104-6f02-46fc-9bec-\
46daa495bf61"]
}, Open ]]
}, Open ]]
}, Open ]]
},
WindowSize->{1310, 1106},
WindowMargins->{{Automatic, 0}, {Automatic, 0}},
TaggingRules->{"SlideShow" -> True},
Magnification:>1.25 Inherited,
FrontEndVersion->"11.2 for Mac OS X x86 (32-bit, 64-bit Kernel) (September \
10, 2017)",
StyleDefinitions->Notebook[{
Cell[
StyleData[StyleDefinitions -> "Default.nb"]],
Cell[
CellGroupData[{
Cell["Style Environment Names", "Section"],
Cell[
StyleData[All, "Working"]],
Cell[
StyleData[All, "Presentation"], MenuSortingValue -> None],
Cell[
StyleData[All, "Condensed"], MenuSortingValue -> None],
Cell[
StyleData[All, "SlideShow"]]}, Closed]],
Cell[
CellGroupData[{
Cell["Notebook Options Settings", "Section"],
Cell[
StyleData["Notebook"],
CellBracketOptions -> {
"Color" -> RGBColor[0.739193, 0.750317, 0.747173]}]}, Closed]],
Cell[
CellGroupData[{
Cell["Styles for Title and Section Cells", "Section"],
Cell[
CellGroupData[{
Cell[
StyleData["Title"], ShowCellBracket -> Automatic, ShowGroupOpener ->
False, CellMargins -> {{100, 100}, {14, 50}},
CellGroupingRules -> {"TitleGrouping", 0}, PageBreakBelow -> False,
CellFrameMargins -> {{20, 20}, {20, 20}}, DefaultNewInlineCellStyle ->
"None", InputAutoReplacements -> {"TeX" -> StyleBox[
RowBox[{"T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "LaTeX" -> StyleBox[
RowBox[{"L",
StyleBox[
AdjustmentBox[
"A", BoxMargins -> {{-0.36, -0.1}, {0, 0}},
BoxBaselineShift -> -0.2], FontSize -> Smaller], "T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "mma" -> "Mathematica",
"Mma" -> "Mathematica", "MMA" -> "Mathematica", "gridMathematica" ->
FormBox[
RowBox[{"grid",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
"webMathematica" -> FormBox[
RowBox[{"web",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
Inherited}, TextAlignment -> Center, LineSpacing -> {1, 0},
LanguageCategory -> "NaturalLanguage", CounterIncrements -> "Title",
CounterAssignments -> {{"Section", 0}, {"Equation", 0}, {
"Figure", 0}, {"Subtitle", 0}, {"Subsubtitle", 0}}, FontFamily ->
"Arial", FontSize -> 45, FontWeight -> "Bold", FontSlant -> "Plain",
FontTracking -> "Plain",
FontVariations -> {
"Outline" -> False, "Shadow" -> False, "StrikeThrough" -> False,
"Underline" -> False}, FontColor ->
RGBColor[
0.8156862745098039, 0.07058823529411765, 0.07058823529411765],
Background -> None, FontVariations -> {"Masked" -> False}],
Cell[
StyleData["Title", "Presentation", StyleDefinitions -> None],
CellMargins -> {{55, 3}, {14, 125}}, LineSpacing -> {1, 5},
FontSize -> 48],
Cell[
StyleData[
"Title", "SlideShow", StyleDefinitions ->
StyleData["Title", "Presentation"]],
CellMargins -> {{100, 100}, {52, 105}}, FontColor -> GrayLevel[1]],
Cell[
StyleData["Title", "Printout", StyleDefinitions -> None],
CellMargins -> {{2, 0}, {0, 20}}, FontSize -> 24]}, Open]],
Cell[
CellGroupData[{
Cell[
StyleData["Subtitle"], ShowCellBracket -> Automatic,
CellMargins -> {{0, 0}, {0, 5}},
CellGroupingRules -> {"TitleGrouping", 10}, PageBreakBelow -> False,
DefaultNewInlineCellStyle -> "None",
InputAutoReplacements -> {"TeX" -> StyleBox[
RowBox[{"T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "LaTeX" -> StyleBox[
RowBox[{"L",
StyleBox[
AdjustmentBox[
"A", BoxMargins -> {{-0.36, -0.1}, {0, 0}},
BoxBaselineShift -> -0.2], FontSize -> Smaller], "T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "mma" -> "Mathematica",
"Mma" -> "Mathematica", "MMA" -> "Mathematica", "gridMathematica" ->
FormBox[
RowBox[{"grid",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
"webMathematica" -> FormBox[
RowBox[{"web",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
Inherited}, TextAlignment -> Center, LanguageCategory ->
"NaturalLanguage", CounterIncrements -> "Subtitle",
CounterAssignments -> {{"Section", 0}, {"Equation", 0}, {
"Figure", 0}, {"Subsubtitle", 0}}, FontFamily -> "Arial",
FontSize -> 27, FontWeight -> "Plain", FontSlant -> "Plain",
FontColor -> RGBColor[0.4, 0.4, 0.4], Background -> None],
Cell[
StyleData["Subtitle", "Presentation", StyleDefinitions -> None],
CellMargins -> {{58, 0}, {0, 5}}, FontSize -> 36],
Cell[
StyleData[
"Subtitle", "SlideShow", StyleDefinitions -> StyleData["Subtitle"]],
CellMargins -> {{0, 0}, {0, 5}}, FontSize -> 27, FontColor ->
RGBColor[
0.9019607843137255, 0.9019607843137255, 0.9019607843137255]],
Cell[
StyleData["Subtitle", "Printout", StyleDefinitions -> None],
CellMargins -> {{2, 0}, {0, 5}}, FontSize -> 18, Background ->
GrayLevel[1]]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Subsubtitle", StyleDefinitions -> StyleData["Subtitle"]],
CellMargins -> {{0, 0}, {30, 5}}, FontSize -> 24, FontSlant ->
"Plain", FontColor -> RGBColor[0.4, 0.4, 0.4]],
Cell[
StyleData["Subsubtitle", "Presentation"], FontSize -> 24],
Cell[
StyleData[
"Subsubtitle", "SlideShow", StyleDefinitions ->
StyleData["Subsubtitle"]], CellMargins -> {{0, 0}, {10, 5}},
FontColor ->
RGBColor[
0.9019607843137255, 0.9019607843137255, 0.9019607843137255]],
Cell[
StyleData["Subsubtitle", "Printout"], FontSize -> 14]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Section"], CellFrame -> {{0, 0}, {0.2, 0}},
ShowGroupOpener -> False, CellMargins -> {{60, 50}, {7, 25}},
FontSize -> 36, FontWeight -> "Plain", FontColor ->
RGBColor[
0.8156862745098039, 0.07058823529411765, 0.07058823529411765]],
Cell[
StyleData["Section", "Presentation"],
CellFrame -> {{0, 0}, {0.2, 0}},
CellMargins -> {{58, 50}, {7, 35}}],
Cell[
StyleData[
"Section", "SlideShow", StyleDefinitions ->
StyleData["Section", "Presentation"]],
CellMargins -> {{58, 50}, {10, 35}}],
Cell[
StyleData["Section", "Printout"], ShowGroupOpener -> False,
CellMargins -> {{2, 0}, {4, 22}}, FontSize -> 20]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Subsection"], CellDingbat -> None, ShowGroupOpener ->
False, CellMargins -> {{60, Inherited}, {0, 15}},
CellGroupingRules -> {"SectionGrouping", 40}, PageBreakBelow ->
False, DefaultNewInlineCellStyle -> "None",
InputAutoReplacements -> {"TeX" -> StyleBox[
RowBox[{"T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "LaTeX" -> StyleBox[
RowBox[{"L",
StyleBox[
AdjustmentBox[
"A", BoxMargins -> {{-0.36, -0.1}, {0, 0}},
BoxBaselineShift -> -0.2], FontSize -> Smaller], "T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "mma" -> "Mathematica",
"Mma" -> "Mathematica", "MMA" -> "Mathematica", "gridMathematica" ->
FormBox[
RowBox[{"grid",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
"webMathematica" -> FormBox[
RowBox[{"web",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
Inherited}, LanguageCategory -> "NaturalLanguage",
CounterIncrements -> "Subsection",
CounterAssignments -> {{"Subsubsection", 0}}, FontFamily ->
"Helvetica", FontSize -> 24, FontWeight -> "Plain", FontSlant ->
"Plain", FontColor -> RGBColor[0.4, 0.4, 0.4]],
Cell[
StyleData["Subsection", "Presentation"], ShowGroupOpener -> True,
WholeCellGroupOpener -> True, CellMargins -> {{60, 50}, {0, 20}},
LineSpacing -> {1, 0}, FontFamily -> "Helvetica"],
Cell[
StyleData["Subsection", "SlideShow"], ShowGroupOpener -> True,
WholeCellGroupOpener -> True, CellMargins -> {{60, 50}, {8, 12}},
LineSpacing -> {1, 0}, FontFamily -> "Helvetica"],
Cell[
StyleData["Subsection", "Printout"], ShowGroupOpener -> False,
CellMargins -> {{2, 0}, {0, 17}}, FontSize -> 16]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Subsubsection"], CellDingbat -> None, ShowGroupOpener ->
False, CellMargins -> {{60, Inherited}, {0, 15}},
CellGroupingRules -> {"SectionGrouping", 50}, PageBreakBelow ->
False, DefaultNewInlineCellStyle -> "None",
InputAutoReplacements -> {"TeX" -> StyleBox[
RowBox[{"T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "LaTeX" -> StyleBox[
RowBox[{"L",
StyleBox[
AdjustmentBox[
"A", BoxMargins -> {{-0.36, -0.1}, {0, 0}},
BoxBaselineShift -> -0.2], FontSize -> Smaller], "T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "mma" -> "Mathematica",
"Mma" -> "Mathematica", "MMA" -> "Mathematica", "gridMathematica" ->
FormBox[
RowBox[{"grid",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
"webMathematica" -> FormBox[
RowBox[{"web",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
Inherited}, LanguageCategory -> "NaturalLanguage",
CounterIncrements -> "Subsubsection", FontFamily -> "Helvetica",
FontSize -> 20, FontWeight -> "Plain", FontSlant -> "Plain",
FontColor -> RGBColor[0.4, 0.4, 0.4]],
Cell[
StyleData["Subsubsection", "Presentation"], ShowGroupOpener -> True,
WholeCellGroupOpener -> True, CellMargins -> {{60, 50}, {0, 20}},
LineSpacing -> {1, 0}],
Cell[
StyleData[
"Subsubsection", "SlideShow", StyleDefinitions ->
StyleData["Subsubsection", "Presentation"]]],
Cell[
StyleData["Subsubsection", "Printout"], ShowGroupOpener -> False,
CellMargins -> {{2, 0}, {0, 22}}, FontSize -> 14]}, Closed]]},
Closed]],
Cell[
CellGroupData[{
Cell["Styles for Body Text", "Section"],
Cell[
CellGroupData[{
Cell["Standard", "Subsection"],
Cell[
CellGroupData[{
Cell[
StyleData["Text"], CellMargins -> {{60, 10}, {7, 7}},
InputAutoReplacements -> {"TeX" -> StyleBox[
RowBox[{"T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "LaTeX" -> StyleBox[
RowBox[{"L",
StyleBox[
AdjustmentBox[
"A", BoxMargins -> {{-0.36, -0.1}, {0, 0}},
BoxBaselineShift -> -0.2], FontSize -> Smaller], "T",
AdjustmentBox[
"E", BoxMargins -> {{-0.075, -0.085}, {0, 0}},
BoxBaselineShift -> 0.5], "X"}]], "mma" -> "Mathematica",
"Mma" -> "Mathematica", "MMA" -> "Mathematica",
"gridMathematica" -> FormBox[
RowBox[{"grid",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
"webMathematica" -> FormBox[
RowBox[{"web",
AdjustmentBox[
StyleBox["Mathematica", FontSlant -> "Italic"],
BoxMargins -> {{-0.175, 0}, {0, 0}}]}], TextForm],
Inherited}, LineSpacing -> {1, 3}, CounterIncrements -> "Text",
FontFamily -> "Helvetica", FontSize -> 12],
Cell[
StyleData["Text", "Presentation"],
CellMargins -> {{60, 50}, {10, 10}}, FontSize -> 17],
Cell[
StyleData[
"Text", "SlideShow", StyleDefinitions ->
StyleData["Text", "Presentation"]]],
Cell[
StyleData["Text", "Printout"], CellMargins -> {{2, 2}, {6, 6}},
TextJustification -> 0.5, Hyphenation -> True, FontSize -> 10]},
Closed]]}, Open]],
Cell[
CellGroupData[{
Cell["Display", "Subsection"],
Cell[
CellGroupData[{
Cell[
StyleData["Item", StyleDefinitions -> StyleData["Text"]],
CellDingbat ->
Cell["\[FilledSmallCircle]", FontWeight -> "Bold"],
ShowGroupOpener -> False, CellMargins -> {{84, 10}, {7, 7}},
ReturnCreatesNewCell -> True,
CellGroupingRules -> {"GroupTogetherNestedGrouping", 15000},
CounterIncrements -> "Item"],
Cell[
StyleData["Item", "Presentation"],
CellMargins -> {{124, 10}, {7, 7}}],
Cell[
StyleData[
"Item", "SlideShow", StyleDefinitions ->
StyleData["Item", "Presentation"]]],
Cell[
StyleData["Item", "Printout"],
CellMargins -> {{39, 2}, {0, 6}}]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Subitem", StyleDefinitions -> StyleData["Item"]],
CellMargins -> {{108, 10}, {7, 7}}, ReturnCreatesNewCell -> True,
CellGroupingRules -> {"GroupTogetherNestedGrouping", 15150},
CounterIncrements -> "Subitem"],
Cell[
StyleData["Subitem", "Presentation"],
CellMargins -> {{146, 10}, {7, 7}}],
Cell[
StyleData[
"Subitem", "SlideShow", StyleDefinitions ->
StyleData["Subitem", "Presentation"]]],
Cell[
StyleData["Subitem", "Printout"],
CellMargins -> {{67, 2}, {0, 6}}]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["ItemNumbered", StyleDefinitions -> StyleData["Text"]],
CellDingbat -> Cell[
TextData[{
CounterBox["ItemNumbered"], "."}]], ShowGroupOpener -> False,
CellMargins -> {{84, 10}, {7, 7}}, ReturnCreatesNewCell -> True,
CellGroupingRules -> {"GroupTogetherNestedGrouping", 15000},
CounterIncrements -> "ItemNumbered"],
Cell[
StyleData["ItemNumbered", "Presentation"],
CellMargins -> {{124, 10}, {7, 7}}],
Cell[
StyleData[
"ItemNumbered", "SlideShow", StyleDefinitions ->
StyleData["ItemNumbered", "Presentation"]]],
Cell[
StyleData["ItemNumbered", "Printout"],
CellMargins -> {{39, 2}, {0, 6}}]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData[
"SubitemNumbered", StyleDefinitions ->
StyleData["ItemNumbered"]], CellDingbat -> Cell[
TextData[{
CounterBox["SubitemNumbered", CounterFunction :> (Part[
CharacterRange["a", "z"], #]& )], "."}]],
CellMargins -> {{108, 10}, {7, 7}}, ReturnCreatesNewCell -> True,
CellGroupingRules -> {"GroupTogetherNestedGrouping", 15150},
CounterIncrements -> "SubitemNumbered"],
Cell[
StyleData["SubitemNumbered", "Presentation"],
CellMargins -> {{146, 10}, {7, 7}}],
Cell[
StyleData[
"SubitemNumbered", "SlideShow", StyleDefinitions ->
StyleData["SubitemNumbered", "Presentation"]]],
Cell[
StyleData["SubitemNumbered", "Printout"],
CellMargins -> {{67, 2}, {0, 6}}]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData[
"ItemParagraph", StyleDefinitions -> StyleData["Item"]],
CellDingbat -> None, CellMargins -> {{84, 10}, {7, 7}},
ReturnCreatesNewCell -> True,
CellGroupingRules -> {"GroupTogetherNestedGrouping", 15100},
CounterIncrements -> "ItemParagraph"],
Cell[
StyleData["ItemParagraph", "Presentation"],
CellMargins -> {{124, 10}, {7, 7}}],
Cell[
StyleData[
"ItemParagraph", "SlideShow", StyleDefinitions ->
StyleData["ItemParagraph", "Presentation"]]],
Cell[
StyleData["ItemParagraph", "Printout"],
CellMargins -> {{39, 2}, {0, 6}}]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData[
"SubitemParagraph", StyleDefinitions -> StyleData["Subitem"]],
CellDingbat -> None, ReturnCreatesNewCell -> True,
CellGroupingRules -> {"GroupTogetherNestedGrouping", 15200},
CounterIncrements -> "SubitemParagraph"],
Cell[
StyleData["SubitemParagraph", "Presentation"]],
Cell[
StyleData[
"SubitemParagraph", "SlideShow", StyleDefinitions ->
StyleData["SubitemParagraph", "Presentation"]]],
Cell[
StyleData["SubitemParagraph", "Printout"]]}, Closed]]}, Open]]},
Closed]],
Cell[
CellGroupData[{
Cell["Styles for Formulas and Programming", "Section"],
Cell[
CellGroupData[{
Cell[
StyleData["DisplayFormula"]],
Cell[
StyleData["DisplayFormula", "Presentation"],
CellMargins -> {{60, Inherited}, {Inherited 1.5, Inherited 1.5}},
FontSize -> 17],
Cell[
StyleData[
"DisplayFormula", "SlideShow", StyleDefinitions ->
StyleData["DisplayFormula", "Presentation"]]],
Cell[
StyleData["DisplayFormula", "Printout"],
CellMargins -> {{39, Inherited}, {Inherited, Inherited}}, FontSize ->
10]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData[
"DisplayFormulaNumbered", StyleDefinitions ->
StyleData["DisplayFormula"]], CellFrameLabels -> {{None,
Cell[
TextData[{"(",
CounterBox["DisplayFormulaNumbered"], ")"}]]}, {None, None}},
CounterIncrements -> "DisplayFormulaNumbered"],
Cell[
StyleData["DisplayFormulaNumbered", "Presentation"],
CellMargins -> {{60, Inherited}, {Inherited 1.5, Inherited 1.5}},
FontSize -> 17],
Cell[
StyleData[
"DisplayFormulaNumbered", "SlideShow", StyleDefinitions ->
StyleData["DisplayFormulaNumbered", "Presentation"]]],
Cell[
StyleData["DisplayFormulaNumbered", "Printout"],
CellMargins -> {{39, Inherited}, {Inherited, Inherited}}]},
Closed]]}, Closed]],
Cell[
CellGroupData[{
Cell["Styles for Inline Formatting", "Section"],
Cell[
CellGroupData[{
Cell[
StyleData["InlineFormula"]],
Cell[
StyleData["InlineFormula", "Presentation"], FontSize -> 17],
Cell[
StyleData[
"InlineFormula", "SlideShow", StyleDefinitions ->
StyleData["InlineFormula", "Presentation"]]],
Cell[
StyleData["InlineFormula", "Printout"]]}, Closed]]}, Closed]],
Cell[
CellGroupData[{
Cell["Styles for Input and Output Cells", "Section"],
Cell[
CellGroupData[{
Cell[
StyleData["Input"], ShowCellBracket -> True, ShowGroupOpener ->
False, CellMargins -> {{103, 10}, {5, 7}},
CellBracketOptions -> {
"Color" -> RGBColor[0.734936, 0.713848, 0.694041]}, Evaluatable ->
True, CellGroupingRules -> "InputGrouping", CellHorizontalScrolling ->
True, PageBreakWithin -> False, GroupPageBreakWithin -> False,
DefaultFormatType -> DefaultInputFormatType,
"TwoByteSyntaxCharacterAutoReplacement" -> True,
HyphenationOptions -> {"HyphenationCharacter" -> "\[Continuation]"},
AutoItalicWords -> {}, LanguageCategory -> "Mathematica",
FormatType -> InputForm, ShowStringCharacters -> True, NumberMarks ->
True, LinebreakAdjustments -> {0.85, 2, 10, 0, 1},
CounterIncrements -> "Input", FontWeight -> "Bold"],
Cell[
StyleData["Input", "Presentation"],
CellMargins -> {{110, 50}, {8, 10}}, LineSpacing -> {1, 0},
FontSize -> 17],
Cell[
StyleData[
"Input", "SlideShow", StyleDefinitions ->
StyleData["Input", "Presentation"]]],
Cell[
StyleData["Input", "Printout"], CellMargins -> {{39, 0}, {4, 6}},
LinebreakAdjustments -> {0.85, 2, 10, 1, 1}, FontSize -> 9]},
Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["InputOnly"], ShowCellBracket -> True, ShowGroupOpener ->
False, CellMargins -> {{103, 10}, {7, 7}},
CellBracketOptions -> {
"Color" -> RGBColor[0.734936, 0.713848, 0.694041]}, Evaluatable ->
True, CellGroupingRules -> "InputGrouping", CellHorizontalScrolling ->
True, DefaultFormatType -> DefaultInputFormatType,
"TwoByteSyntaxCharacterAutoReplacement" -> True,
HyphenationOptions -> {"HyphenationCharacter" -> "\[Continuation]"},
AutoItalicWords -> {}, LanguageCategory -> "Mathematica",
FormatType -> InputForm, ShowStringCharacters -> True, NumberMarks ->
True, LinebreakAdjustments -> {0.85, 2, 10, 0, 1},
CounterIncrements -> "Input", MenuSortingValue -> 1550, FontWeight ->
"Bold"],
Cell[
StyleData["InputOnly", "Presentation"],
CellMargins -> {{110, Inherited}, {8, 10}}, LineSpacing -> {1, 0},
FontSize -> 17],
Cell[
StyleData[
"InputOnly", "SlideShow", StyleDefinitions ->
StyleData["InputOnly", "Presentation"]]],
Cell[
StyleData["InputOnly", "Printout"],
CellMargins -> {{39, 0}, {4, 6}},
LinebreakAdjustments -> {0.85, 2, 10, 1, 1}, FontSize -> 9]},
Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Output"], ShowCellBracket -> True,
CellMargins -> {{103, 10}, {7, 5}},
CellBracketOptions -> {
"Color" -> RGBColor[0.734936, 0.713848, 0.694041]},
CellEditDuplicate -> True, CellGroupingRules -> "OutputGrouping",
CellHorizontalScrolling -> True, PageBreakWithin -> False,
GroupPageBreakWithin -> False, GeneratedCell -> True,
CellAutoOverwrite -> True, DefaultFormatType ->
DefaultOutputFormatType, "TwoByteSyntaxCharacterAutoReplacement" ->
True, HyphenationOptions -> {
"HyphenationCharacter" -> "\[Continuation]"},
AutoItalicWords -> {}, LanguageCategory -> None, FormatType ->
InputForm, CounterIncrements -> "Output"],
Cell[
StyleData["Output", "Presentation"],
CellMargins -> {{110, 50}, {10, 8}}, LineSpacing -> {1, 0},
FontSize -> 17],
Cell[
StyleData[
"Output", "SlideShow", StyleDefinitions ->
StyleData["Output", "Presentation"]]],
Cell[
StyleData["Output", "Printout"], CellMargins -> {{39, 0}, {6, 4}},
FontSize -> 9]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Code"], CellMargins -> {{103, 10}, {5, 10}}],
Cell[
StyleData["Code", "Presentation"],
CellMargins -> {{110, 50}, {8, 10}}, LineSpacing -> {1, 0},
FontSize -> 17],
Cell[
StyleData[
"Code", "SlideShow", StyleDefinitions ->
StyleData["Code", "Presentation"]]],
Cell[
StyleData["Code", "Printout"], CellMargins -> {{39, 0}, {4, 6}},
LinebreakAdjustments -> {0.85, 2, 10, 1, 1}, FontSize -> 9]},
Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Print"],
CellMargins -> {{103, Inherited}, {Inherited, Inherited}}, FontSize ->
14],
Cell[
StyleData["Print", "Presentation"],
CellMargins -> {{70, Inherited}, {Inherited 1.5, Inherited 1.5}},
FontSize -> 17, Magnification -> Inherited 1.5],
Cell[
StyleData[
"Print", "SlideShow", StyleDefinitions ->
StyleData["Print", "Presentation"]]],
Cell[
StyleData["Print", "Printout"],
CellMargins -> {{39, Inherited}, {Inherited, Inherited}}]},
Closed]],
Cell[
CellGroupData[{
Cell[
StyleData[
"WolframAlphaShortInput", StyleDefinitions -> StyleData["Input"]],
CellMargins -> {{98, 10}, {5, 7}}, EvaluationMode ->
"WolframAlphaShort",
CellEventActions -> {"ReturnKeyDown" :> FrontEndTokenExecute[
EvaluationNotebook[], "HandleShiftReturn"]},
CellFrameLabels -> {{
Cell[
BoxData[
DynamicBox[
FEPrivate`FrontEndResource["WABitmaps", "Equal"]]],
CellBaseline -> Baseline], None}, {None, None}}, FormatType ->
TextForm, FontFamily -> "Helvetica"],
Cell[
StyleData["WolframAlphaShortInput", "Presentation"],
CellMargins -> {{107, 50}, {8, 10}}],
Cell[
StyleData[
"WolframAlphaShortInput", "SlideShow", StyleDefinitions ->
StyleData["WolframAlphaShortInput", "Presentation"]]],
Cell[
StyleData["WolframAlphaShortInput", "Printout"],
CellFrameLabelMargins -> 3]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData[
"WolframAlphaLong", StyleDefinitions -> StyleData["Input"]],
CellMargins -> {{100, 10}, {5, 7}},
StyleKeyMapping -> {
"=" -> "Input", "Backspace" -> "WolframAlphaShort"},
EvaluationMode -> "WolframAlphaLong",
CellEventActions -> {"ReturnKeyDown" :> FrontEndTokenExecute[
EvaluationNotebook[], "HandleShiftReturn"]},
CellFrameLabels -> {{
Cell[
BoxData[
DynamicBox[
FEPrivate`FrontEndResource["WABitmaps", "SpikeyEqual"]]]],
None}, {None, None}}, DefaultFormatType -> TextForm, FormatType ->
TextForm, FontFamily -> "Helvetica"],
Cell[
StyleData["WolframAlphaLong", "Presentation"],
CellMargins -> {{107, 50}, {8, 10}}],
Cell[
StyleData[
"WolframAlphaLong", "SlideShow", StyleDefinitions ->
StyleData["WolframAlphaLong", "Presentation"]],
CellMargins -> {{107, 50}, {8, 10}}],
Cell[
StyleData["WolframAlphaLong", "Printout"], CellFrameLabelMargins ->
3]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Program"], CellMargins -> {{60, 4}, {6, 8}}],
Cell[
StyleData["Program", "Presentation"],
CellMargins -> {{60, 50}, {8, 10}}, LineSpacing -> {1, 0}, FontSize ->
17],
Cell[
StyleData[
"Program", "SlideShow", StyleDefinitions ->
StyleData["Program", "Presentation"]]],
Cell[
StyleData["Program", "Printout"], CellMargins -> {{2, 0}, {0, 8}},
FontSize -> 10]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["CellLabel"]],
Cell[
StyleData["CellLabel", "Presentation"], FontSize -> 12],
Cell[
StyleData[
"CellLabel", "SlideShow", StyleDefinitions ->
StyleData["CellLabel", "Presentation"]]],
Cell[
StyleData["CellLabel", "Printout"], FontSize -> 8, FontColor ->
GrayLevel[0.]]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["ManipulateLabel"]],
Cell[
StyleData["ManipulateLabel", "Presentation"], FontSize -> 15],
Cell[
StyleData[
"ManipulateLabel", "SlideShow", StyleDefinitions ->
StyleData["ManipulateLabel", "Presentation"]]],
Cell[
StyleData["ManipulateLabel", "Printout"], FontSize -> 8]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["GraphicsLabel"]],
Cell[
StyleData["GraphicsLabel", "Presentation"], FontSize -> 14],
Cell[
StyleData[
"GraphicsLabel", "SlideShow", StyleDefinitions ->
StyleData["GraphicsLabel", "Presentation"]]],
Cell[
StyleData["GraphicsLabel", "Printout"], FontSize -> 8]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["Graphics3DLabel"]],
Cell[
StyleData["Graphics3DLabel", "Presentation"], FontSize -> 14],
Cell[
StyleData[
"Graphics3DLabel", "SlideShow", StyleDefinitions ->
StyleData["Graphics3DLabel", "Presentation"]]],
Cell[
StyleData["Graphics3DLabel", "Printout"], FontSize -> 8]},
Closed]]}, Closed]],
Cell[
CellGroupData[{
Cell[
"Styles for SlideShow", "Section",
CellChangeTimes -> {{3.514665148412793*^9, 3.5146651505550737`*^9}}],
Cell[
StyleData["slideshowheader"], ShowCellBracket -> False,
CellMargins -> {{0, 0}, {0, -2}}, Evaluatable -> False,
CellHorizontalScrolling -> False, PageBreakBelow -> False,
CellFrameMargins -> 0, ImageMargins -> {{0, 0}, {0, 0}},
ImageRegion -> {{0, 1}, {0, 1}}, Magnification -> 1, Background ->
GrayLevel[1], CellPadding -> 0, CellFramePadding -> 0],
Cell[
CellGroupData[{
Cell[
StyleData["hidefromslideshowgraphic"], ShowCellBracket -> False,
CellMargins -> {{0, 0}, {0, 0}}, Evaluatable -> False,
CellHorizontalScrolling -> False, PageBreakBelow -> False,
CellFrameMargins -> 0, ImageMargins -> {{0, 0}, {0, 0}},
ImageRegion -> {{0, 1}, {0, 1}}, Magnification -> 1, Background ->
None, CellPadding -> 0],
Cell[
StyleData["hidefromslideshowgraphic", "SlideShow"], ShowCellBracket ->
False, CellElementSpacings -> {
"CellMinHeight" -> 0, "ClosedCellHeight" -> 0,
"ClosedGroupTopMargin" -> 0}, CellOpen -> False,
CellHorizontalScrolling -> False],
Cell[
StyleData["hidefromslideshowgraphic", "Printout"], Magnification ->
0.6]}, Closed]],
Cell[
CellGroupData[{
Cell[
StyleData["slideshowheader2"], ShowCellBracket -> False,
CellMargins -> {{0, 0}, {0, 0}}, Evaluatable -> False,
CellHorizontalScrolling -> False, PageBreakBelow -> False,
ImageMargins -> {{0, 0}, {0, 0}}, ImageRegion -> {{0, 1}, {0, 1}},
Magnification -> 1, Background -> GrayLevel[1]],
Cell[
StyleData["ConferenceGraphicCell", "SlideShow"], ShowCellBracket ->
False, CellElementSpacings -> {
"CellMinHeight" -> 0, "ClosedCellHeight" -> 0,
"ClosedGroupTopMargin" -> 0}, CellOpen -> False,
CellHorizontalScrolling -> True],
Cell[
StyleData["slideshowheader", "Printout"], FontSize -> 8,
Magnification -> 0.75]}, Closed]],
Cell[
StyleData[
"ConferenceGraphicCellSlideShowOnly", StyleDefinitions ->
StyleData["ConferenceCellGraphic"]], ShowCellBracket -> False,
CellMargins -> 0,
CellElementSpacings -> {
"CellMinHeight" -> 0, "ClosedCellHeight" -> 0, "ClosedGroupTopMargin" ->
0}, CellOpen -> False],
Cell[
CellGroupData[{
Cell[
StyleData["SlideShowNavigationBar"], Editable -> True, Selectable ->
False, CellFrame -> 0, ShowGroupOpener -> False,
CellMargins -> {{0, 0}, {3, 3}}, CellOpen -> True, CellFrameMargins ->
0, CellFrameColor -> None, Background -> None],
Cell[
StyleData["SlideShowNavigationBar", "Printout"], PageBreakAbove ->
Automatic]}, Closed]]}, Closed]],
Cell[
CellGroupData[{
Cell[
"Styles for Slide Show Environment Documents", "Section",
CellChangeTimes -> {{3.559592561220532*^9, 3.559592575768806*^9},
3.559652073182283*^9}],
Cell[
StyleData["FirstSlide"],
PrivateCellOptions -> {
"PagewiseNotebookBaseStyle" -> {
FrontEnd`BackgroundAppearance -> FrontEnd`CurrentValue[
FrontEnd`EvaluationNotebook[], {
FrontEnd`UnknownOptions, presentertemplt`firstslideimage}]}}]},
Closed]]}, Visible -> False, FrontEndVersion ->
"11.2 for Mac OS X x86 (32-bit, 64-bit Kernel) (September 10, 2017)",
StyleDefinitions -> "PrivateStylesheetFormatting.nb"],
presentertemplt`firstslideimage -> Image[CompressedData["
1:eJzt3UmudOtVreFDUqBIF5BL0AKqFKkaIcq2MBYVI9lIiF7QEMDkeZ7n0CNz
flmW5eO9IlYykzHmfAuTey+6hR0r9ol4/jHm9+2f+uqvfflXfvSzzz771k98
/j++/JXf+LlvfvMrv/kLP/n5/+MXv/GtX/36N772yz//jV//2te/9s2f/eqP
ff6//K0f+eyzX/r8//+Pf/5//853vvPZp/+DYRiGYRiGeTbfc9Vvf+lnmID5
nS/99OH87pv59pv5vRfz+yfmDz7/+d7NH76ZPzoxf3xy/uTC/OmF+bOL8+c3
5y+C5i+D56+Y1ol+P6N+z+78jl/9b+nTXPlv9ex//2c/U858Pn2ad59zZz4r
z3zmHn1ev/us//aJ74uj75nu70Dmu4OtYsfVVe8+a7pcdeVzuspVeIrpcJaT
sTJ8FW0sfMVkDraKG0VXVWVVZ13lmlWpearbDEfz1wLT/QwqrLXZWPgKXzkM
toqZqa46Y6vOrGqLqbpNoOKmSQZTcZaSsaIzrAhfnTHWE1+dMRa+8hts9Xxw
lb6rOro/V091m6d7HJ3lkGN1ZVgOvnqaX73a8+3+ftw62OrZ4KpZpurOqTCU
5mxyloqxqjtCdV/dza7wVc9gq/sz1VWqWZWyqdQ91W2TqaPsrGpjTciwInx1
xlh3+0F85TPY6t7gKlylbKpuc2wcVWdNMNYmX7F7NWOw1fW5e4fVBldhqh5P
dbvibwSn+5lMc1aWsVw7QnzFvBpsdW0cXeW6WzXFVBMs1e2kCf7aaKzpGRa+
Yo4GW12bjC5wi6u6syp3U2GoOd7CWBq+ijhDiK+YjwZbnR9cpeMqZVNFugpH
6YyDs6qN5ZBh4St81THY6tzgqtwOUC2rmuapbpdMHVVrTTAWvsJXzoOt3k/1
mUBchamwlN9MMRa+mucrbFU/2Or1THPVmc8P5w7QzVRYau64O8vNWFU7WBF3
NOCr+YOtjgdX5blKJavqMNVET/3t57+fatP9TLKsNc1YjhkWvmLeDbY6nsq7
FnCVflalYCr8NMNeW4ylnGFNvZ+B3SuNwVYfD67q6wDVsqptnuo2T/e4OWuS
sab56p2x7toKX+kPtvrhwVXXbOWSVbnkVBhKbxyctc1YER3hmTtmuvtBfOU5
2OoHp/KuBVyl6aqppur2yaRRdha+0vMVu1f7Blt9f3BVj6s2mwpLzRmM5dsR
4it8FT3Y6vsT3QXevRsUVz13VVX/p5RRdduC0XRWlbEcMqzu/St8tWew1XdH
Zccq21Vn/n2m5CrlrErBVN2G+OL8nch0P4dsZ00yFr7i7ODEwVY6rnpnq25X
Ve9WTTHVFE91e2mKvbqdpeirs8bCV7W+6v5udp7ttnLZsZriqu4O0NVUGGqm
uxxzrCkZFr4iu8ocbFWzY9W5u+7kKsWsqqv7w1Ea4+QsRWPhq9q7Gdi90pjN
tprgKoX9KnVXOZkKS3kMxtLIsPAVvlKdrbba4KqK84AdHWB2VjXJU90G2TKq
zlIzFr7S8BW7V/mz0VYqO1bdZwInu8phpwpLzZwJxlLKsPAVu1eOg61w1VVX
TewAnU3VbYnvzd8LTfezyLTWFGPhK3w1ebbZSqELxFX7TDXBU91emmCvLcZS
7gjx1TNfdX+Huwy20tqxwlWarlIwFY6aZS43Y03KsJR9pb571f0d7jLbbaXU
BeKq665SNVWUq3BU/zg4q3IfC1/t8hXZ1b3ZZKvuzKrzroVuVylkVS6mwlHa
o2ysJ85S6AnxFb6aMltshatyzgO6dIAO/R+e8hxFZzlnWJt8Vb17FXnvVfd3
uvpstZXLjhWuwlRYymu2GcuhI9zoK7IrbKXkqju2wlXeruow1URP/YPYdD+P
Cc6alGF1+qrr7CC+wlYKrnLZW59iqk2ecjNUt4umW6zbWkrOmmSsrv2r6H4Q
X2GrK656Zasp+1WdrpqcU3WaCkfN9tZUY3XmWE/3sKb5KjK/4k7R3ba6ekeo
Smbl6qrOvErRVBGuwlJ6o2wsfFWXX23fv8JW2GqLq97ZCld5ZFV4ymswlnZH
iK9yzg6SXe20laOrMnesnrjqna0ie0BMtdtS//iF6f55FKzlYKzJvlI9P6iw
e4WvdtkquwvsOBOIq7RdpWKqbld85KOO6X4GE4yVlWEp+sr1/CDdoPZssJV6
ZtW1Y1XhKpcOsNJUzp7qdpOrvbqN5Zph4St85TqTbIWrcNUGU+Eob3O5Gcsh
w1L31YTdK7rBnbbq7AI7dqy6zgTiqpmm6naN4mCs/AwLX/XtXpFdYau7tpq6
Y7XJVdtNhaW0RtVZ+MrfV87dINnVTFtdyawcukDFuxZUd9azXdXR/2Epj1Ez
lmqGpbqDha/oBrHVdVspd4FZO1bdZwKn5VXVrsJTvrPRWJ0Zlnp+lbXbrpBd
HX230g3OstUVV72y1dXMSm3HCldhKgVP/ZPAdD+DaGsp94TuvlK9W1TZV1dt
tdVXzraK2l936AKVzwQq94DKe1Wunuq2k5u9MFafr84Yq8tXDrvtZFfYKjqz
UnLVk8zqiavO2KrSVZkdoJupcJSftzqNtdlX2flVx+7VXVu98lVUN0h25W2r
rszKyVVPdtcrXbUlq1I3Vbdv1EbdWe7Gwle7usFuM2Cr+7a6mlm5d4G4yiOr
UvVUt13cRtVZFcbqzLBUfLV594pucIettnSBWTtWuKrGVYqm6vbJlMFX+Kpq
9yrjXoaKc4Pbu0E3Wynur6t1gdtcld0BVmdVWMpvFJx1d/8v01iOvlLcbSe7
8psJttqWWXWdCXR3lbKp8NSccTSWi6/OGqszv5q8e0V2NdNWmZkVrqqxFa7K
cVW3Jz6afy6e7te7zVhdO+4O+ZXL7hV77djqyFad++vsWM1zVZWpJmRU1XZy
tleXsVwzrM2+mpZdbfWVi63IrGa7SmFn3cVVOMrXWy7G2uKrabvt0b7CVjtt
lb1nNcFV2V2gqquyO8DJpur2Tve4OEvNWPhKe/cqKrs6+m7FV362inLVR7aK
zqxwVY6rVLKqalNhqf6ZZiyVDAtfeWRXUb7CVnpDZhXfBTq5KiuvynaVqqm6
reI8qsbKzrCm++qprSb4iuxql63UMqsJrnq6Y0VelecqPOU1SsZy7Qin+Mpl
90otu5rqq0m2ogvc6SolU9111TRP/UvD4Cy9DEvRV3SD7LVvt1VHZkUX+MxV
72zVmVcpZlXunuowlLq78BW+UveVWnbVbQ1sRWaFq/Lzqoqsys1U3TZyNZeb
sbI6wmm+ctm9IrvCVk9cpbq/PsVVlV2gm6s6TYWjvKw11Vj4quZehkl77djK
w1aT9tff/XeXZStc5eMqPOVtrS5j4Su6QbKr3bZyyaw2dIFnbKXoKkyFpdSd
1WEsBV+dNRa+6u0GI2y1+cygu62uZFZ3bEUXiKvuugpPzR4lY6lkWBt9lbF7
RXblP2q2IrPyuW9hk6vu7LgouKrbHxtGxVhuvqrsB5/Yqmv3SiG7OvJVZnbV
bRBsFZNZbd5ff/d5kn0mcKqr8NQPzr8mT/fri3aWsrGc86st3WDVXjvZlY+t
lDKr6P11NVdlZlbKrlLdrXI2VbadXO3VaSwFX0VnWOrdYIavlLtBsquZturK
rBy6QHVXnbVVp6ucsiocpe2tLmM5+SqyH1TdvSK72uUrFVuRWWl0gbjKI6vC
UX7emmasqfmV0+4V2ZXuONpqSmal5qp3tqraXXdx1TRTddtGaZSdVWEs9R33
ibtX6nvtZFd+tnLPrCr317u6QFzV6yo8NdNa+KqvH6QbJLvCVmRW7l2gsqsq
OkAlU3U7xX3cjYWvPH1FduU13bYis8JVLq5yNlW3R6aOgrEcd7DoBsmusJWO
rZwyqyld4CtbVd+1sMFVkz31b5//PkRN92vJNJZ7R+jkq3effWrZVfReO9nV
HltNz6zoAnHVVFNF2snZX13GwldzfKWcXUXYakN21Wkrh78b6J5ZPXFVRWal
7Kq731UdrtpsKFVzORkLX/V0g47Z1dF3K9nVLFtdcdWRrVwzK/cucLurXEzV
bSF3a3UYy8lXZ3ctI3y1ea+d7GqHrcisPLtAXDXfVN3W6R5lYyllWIq+ohus
uU80O7vCVr22mp5ZqbnqjK0UXaW0W6Vqqm7PqI6qs/CVnq+qu8GqOxnIrnxs
5XDvAplVTma1Na9SNFW3W9wGX2n4ynn3SnmvXW3vClvl2iqzDySz8u0Cu/Oq
qqwKT2mOo7HwlXY3qLzXTnblaavJmVX1/nrGuUBcVZ9V4SmPUTFWZoaFr/qz
q6q9drIrX1uRWc3LrNRcddZWqrtV20z17y+m+2frcBa+ivPVpHODkdmV2pnB
ifcxONqKzMprf10xr8o01V1XTfHUKytlT/dr7zaWi6/O7lQqZ1dP9to3ZFfb
e8FKW5FZ9eyvb3FVVl6FqfQM5WAufKWRXb3z1dbsSm3vClv5ZFZXbaV8NlAx
s1LrAje6CkvpW6vDWPjKuxvcmF1N6wWrbPXRs+noAyMzKxVXkVn5ucrBVN3+
mWatSRnWNF+p2cpt74qddi1bTc2s2F/f46rqrApP+VtrSoal5qtp3aBqdqWy
095tp622itph796zmtoF4iodV3U7RnlUjbXRV67d4LTs6qqttmZXFbZS2WE/
stXEzApXablKzVTdZnEcd2Phq93ZFTvt2CrLVVdtRWbV0wXiqp2m+o8vTPfP
U+ksxQwr2lebd6+2Z1cb72PYZCvFHfZJmVXVjtXZfyfjqn5TfdFLWbPdWPiq
ZveK7Oq1rciu6mylssNOZvVsf31yF6jkKkdPVflJ2Vzdvrqz++fsK8fs6p2v
VLMrekFs1ZlZVe5ZOXaBuGqGqbqt5OAtJ2PhK49u0Cm7Yqe9x1avzlhO3GFX
yqyU99dxla6pui3k6Cx89dxXFd3g5Owq+z4GesE+W03rA9mz6suscFWtqbrN
M8VaXcbq9pXL7pXTnQwV2ZXrTnu3o6bbSi2zumMrNVe9sxWummOqbteojZqx
8FVON3jXV2RXZFcqtoq402rCDrtSZvXEVSpdIK7CUxirzleOu1fTs6up9zFg
K6/MSnWHXW3PKjuzqt6xmuAqTDXDWfhKa/eK7Kpup33LXVcbbeV470L1nQvT
usBuVymYqtslk8bNV1eNVe0rsiuPvSvuY+i11ZYddoXMynXPSrELnOqqbod8
b/4zeLpfj4KxJuVXZFf12VXXfQzYysNWajvslfcuOGZWuGquqaL95OIulwyr
01cV3WDmXrtDdtV1l2jETvu0XhBb9d+7oJZZPXFVhK2qu8BprtrmKCVvdRnL
pR9U8FVHN+iYXdELatlKxVVdfSCZFa56aitlV3X7yMVZ6r5Szq9cd6/Us6uo
nXZstdtWXecDo+9dULqD3akLdHSVoqm6DeTurGpjOWRXFbtXTra6m1117bRf
tVW1r7pNha127rA7Z1YOrqrOqvCUh7NUfXXFWHSDPdmV4k472VW/rZRclW0r
lXsXHDMr1S5QOa/CVF7OUvWVaze4xVaKO+3YqtZWGzIr5x12MistVymYqtsv
DqNgLHyl5avqM4NqO+30gtiKzMo/s1J3VVVWhan6xy3D6vKVSze4Mbtip93f
Vkqu6rLV9MzKaX9dZceq01XdNpkw+KrWV122yvLV1p12bEVm5brDnpFZZdsK
V9W4qtsjR/NfJ6f758x0lquvpnSDZFd6vSC2wlaV9y5My6y2dYHbTHXWTVHj
bKztvlK1VdbeVVV2RS/obavNrorOrJRc9cpWLq7aaKqpdnKxV7Wzsozl1g9O
8ZVTdpXpK2y121YKXeBdW6l2gbhK01TdNnJy1jZfTc+vlLpB9q48zguq2mrq
PeyVZwMnZ1YdPWCmq5Szqm4HOTurylcO/SDZ1czsStlWnb7KsBWZlX4f2JVZ
uXaBV7+7rthK0VTd3pnkLHxFduW2d4Wt+m1FH6h5NnBzZoWr8NRWY6l3gwrn
BquzK3rBnb0gttKwlVIfeDezmrq/jqv2joqvFPKrDdmV0n1X9ILe2VW3rba4
KqMPrL7Pisyq31V4CmPhK7IrbDXbVmRWZFa4ys9V3U5xHnyl0w0qZleVO+1d
vSB3MWArd1sp7bBPyaxwVe/8d9B0vw4HX5Fd+e+0K/aC1bZy3blSs1XH3QtR
rqq0VUYfqHw2UDmzynSVq6miDKVuri5fkV35ZVdTekFHW3X4qsJWKplVtq3U
+0DFzCpifx1X9Zqqy1Eq1iK/Irsiu6IXzLSVeh/oZKspfaBKZtXZBU51Vbeb
1Jw1Jb9y6wax1XxbHflqoq0Udq3cXaV0p1XHDvuGLnCaq7p9pO4sfKWXXXFe
cK6tlHeulGxFZqXXBz6x1eTMKqsLVDRVt4McnbXFV2RX/dkVttLMrrJtRR/o
vcP+ylaTMitctc9U2caq9BXZ1Yzs6tW/tzf5Cluxa6ViK7U+kMzK11Xdxuke
fOXpq7vZ1bt/W9ILamdXk2zFrtWOHfaszOqMrXAVpuoefBXbDU7MrugF+22l
unOlYisyqx5bTe4DcRWm2uYrsqv47EqlF+w8LzjFVpW+6rAVfSA77Aqu6j4X
2O2qbrd8mv85Md0/o4KxHHw11VZkVzq+2marDbtWrncvkFlpZlabXHXGT0/G
zVj46pmv6AWx1URbKe9aHdlqa2bVYavsHfaOzEqpC3QwVbaluq01yVeOtnLL
rtx6QWVbOe2zK9hKPbPaaCsyK70uUNlV3Z7qcJa6r1yzq2k77RvPCyrvXGEr
X1tt7QNdMivHLlDRVd1uUnBWh686u8EJ2ZX7XVcOtrrqq4n77NW2Uti1csus
qm01fYd9k6u2e6rCWBN8RXaFrVx6wS22UtljV8msVPpAtTutpmZW2V2giqu6
PTTdWE7dINnV/F5Q2VYuO1eqtnLtAx1spdgHkllpuqrbP27GqrRVtK+mZVfV
d11tPS+oYqsjXznYil2rnF2r6X1gxQ67cmbl6Kpu7zgba4OvVLKr6l7Q4byg
ei+4ZZ+90lYKu1ZHtpqUWU07H6iYWeGquePmK7Krub3gRFtd9RW28rgzlD5w
Xh9IZhXjqm7TKA2+mm+rbb2gq61c99mf2Io99lm2UuwDyaxwlbOxqnzlnF25
9YLbzwsq2Mphn13RVq67VndsdWfXSqkPJLOKs1WHq7rt4jAOvjr7O0l2RS9Y
aSuVnStlW7HH7pFZTbKVc2Z11VZbXfW/J6b7Z+zyVWd2Femr7p12bJVvK8c7
RLEVe+z0gfdtNTmzcnLVGUPdGSdjkV3pZVcZtqry1bsz6Vd8pWKrSfvsVbZS
2GPHVlq2UuoD3TIrdVdlWUrBWviqPrtSs9Xm7KrDVo777NG2ytpjj3AVtoq1
lXpm5bDDPs1VXaaqNpaqrbr22tV32ukF5+2zT7WV4x57hK1cXTXNVhNcdcdW
iqbqdlSXs1R95Wqrp9nV3fOC2Cq3F9x6VrDLVh194BVbkVnRB6plVmqu6jaT
grHwVV12pdYLRt9z9e7MuKuttp4VPGOrKXvsH9mKPjA+s1I4HzjNVXdthany
jVXlq669KxVbZfWC7Fxp7bNjKz9bsWtFH+hqKwVXdZtomq82Zlf0grq2OvIV
ZwV1baVwH7uaraLvDL3rqg5bqfSBuGqnq7KMpeYrRVvRC/rZavJZQWylbatt
mVWmregDtWzVbR98pZFdqdhKrRes3LlSshVnBWttNf3+BfrA/l2ryj4QV+2a
ib5SzK46e8E7tlLPrpRsxVnBZ7aafv8Cu1a+faByZoWr9KfLV2RX9IKV2RVn
BWfaijOCsbtWU2w1vQ/MthWu0vHV5uwKW+nbSuWs4GZbcUawdo9dJbNStNWm
PrAjs+o2jdJMyq7oBbGV21nBLFtV7rNPs5XSGUH6QE1bkVnhKnzV2wtusdUr
XznZSuWsILbKPyOoYit2rebtWrllVrhK11fTbOXSC96xlUp2ha2wVcUZQZX7
F9hj37NrtSmz6raLw2zylVIvyM5VzFnB6n12t3sYttqKM4LYSrEPnJBZdZvF
aZR9RS+IrTafFVS94+qqrbLuX8BW984IbrkzlMyKLrB7sFVsL4itNHeu3Gyl
eseViq24f2F2ZoWtyKwmzAZfTekFsdXus4LYivsXNthKYddqUh+Iq/x85WIr
pV4wy1Z3fPXq8/Sur7BV/T0MU2016W4rdq00+kBVWylmVt0umTBV2ZWyrap6
wXdni6dmV4q2mnJWEFvp3L/AHru2rbb1gWRW/aOWXV3JUpVsRS9Yc1YQW9Wf
FXxlK9V7Q7l/od5W7/J1bHXfVmRWnqOUXUXbKqoXxFYaO1dZtuIehh5bud1t
pXhG8K6tXDKrKlsp71rhKs9xza7YudpnK+64wlbcv6CXWSn3gVG2is6ssNWO
mZxdYStsFb3Pjq1m20rxjCC2mmUrXLVjNtuqap/9la/O3P1y1VevPh9f+crR
VtV3XKnaKsNXEbZSvn/BxVbKu1bKtqrctSKzYpR95bpz9cRWLtnVq89xxbOC
bveHYitsha2wVaWtut2xYVRsdcVXSraiF9SzVfUdV9jKz1Yd94Z277FjK489
djKrOeNmK3au9G31ylfYSv9u9iu2Urh/QcVWymcEK211Zt/hrquqbDV116rb
G5tGJbvCVtjK0VYT/+4Nttplq3d7mkqZFbbCVk6jYKsrvnLaZ8dWO+8PxVb9
tsq6N9TRVlv6wEpbde5a0Qd6zERbqeyzYyts5fZ3b7CV7p3s786WbLeV8x47
mdV35/9OTPfPmGmrK77CVvH3MEyzVcfd7I5/9wZbYSvlXStsRR+YaSpHZylk
V4o7V6r3MBx95r3yFbbqv5vd2Vb8LUFsNcFW1WcEo201rQ+8ayoXY2Erzewq
0lbT7g/FVthq6t+7cT0jOMFW6nvsU1wVZSp1X2ErbIWtsBW2wlbYqt5W2/rA
DFcpG2vaztXks4LRtrrrK2xVa6uPfIWtsBW28j4juMlW2a5S9NU0W6nsXGEr
bJV5Nzu28rSVwt1W2Gq+rbpd0eGqTbaK7gWxlYatjnzlbKsjX2GrZ7Y6+/du
jmwVcW8otsq11Zmzz1n3hiqeEYy2FZmVp6+cbOV0VhBb5djqyFfYCltdsVXE
vaHYKt9W3L/gbatqV7n7ClthK2yFrbDVPFu9+oxx7QOx1S5XYStsha2wFbbC
Vtiqd9cKW82zlYqvuvfZsRW2wlbYClthqy22mn5GsNtV2ApbYStsha3m2Srq
TnZspXFG0MlW3Z7AVtgKW9XdH4qtsBW20rDVnT12bIWt3Gyl4KtuW13xlYqt
3vkKW82w1ZGvsBW2wlbYClthK2yFrbAVtsJW2ApbYStsha1cbfXEV9jquq2O
fIWtsBW2wlbYap+rsJWmrTp3rrAVtsJW2ApbYStsha2wFbbCVtgKW2ErbIWt
VKb7WWArbIWtsBW2wlbYCltN8lX3c8BW7FthK2yFrbAVtsJW2ApbKduKc4Kc
E8RW2ApbYStsha2wFbbCVtgKW8221StfYStsNcVW3c9AwVZnf2exFbbiXnZs
5WCrI19hKz1bnfWVi60UfNXtKmzla6usXStnW7363sBW2ApbYStsdd1XjrZS
8FX368dW2ApbYStsha2m2iqqF8RWPrbqfu13bXUlz8RW2ApbYSts5WGrV77C
VtjKxVfdrxtbYStsha022urIV9gq3lavfPXuc/SdrxRtFb1z5WyrDl91v967
rsJW2ApbYasqWx35Clvp2OpJdvXUVpVnBbts5XpWsMNW3a/V1VZnz8piq7m2
unJvKLbqt9VHvtpsq1e+2mgrlX32abba6qvu11llqzO/X9jKz1ZX71/AVtgK
W2Erd1tF71xtslWFr7pf33RbnTlvi62w1ZN7Q6/a6qNeDFthK2y121ZXfDXB
Vlm+6n5N1a5StdXZ3ccNtqq6NxRbPbPVR77BVjm2OvJVha2OfIWtuOPqznf1
Bl91vxZlWynusWMrbIWtjn2lYKsjX2ErbKWwcxVtq0nZVYSxun92bNXTByrZ
qmqPPdpWV84IYitstdVWr3yFrdhn7zZGpLO6f8ZMV6nvWjnY6sxdMFdtpXBG
0MVWV/bYsRW2euerClvdza622IqzgjN8NWUUMquptsrIrCbaKupuKxVbnT0j
iK2wVfc+O7by22efnl1NmYm2mnxGEFvNt9XZM4LY6vo+O7Z67qsntnrlqzM9
ALbCVg6T3Qc671phq3hbZd/JfmSrp3dbYascWx35ytFWr3w1zVbK2ZXiWUF6
wX2j4Cpsha1cbfX03lB3Wx35StlWH/kq21ZHvsJW2Irsat6oZFZXbKW0a4Wt
+u5fmGKrp/eGYitsha3mnBUku5oxKraKzqxU9tgn2OrdmW81W2X9vRtsVWur
I19tshV3XLHPjq38RsVVGbZS2WPPun/hyFavPh+n3RtabauI+xc22erIV6q2
Uvy7N9hqlq3w1Y7ZbCuHXatXtlLuA93vZHezVbSr1G1V/XdvFG31ylcTbMXO
FbZynQpXue9addtKoQ/caKvMe0OxVd49DFm2UrybXSW7evUZ1Z1dVe5cdfeC
+EpnJmdW7LHPstWkv3czwVYf+UrBVpv+7o2KrZR7QXdbVWVX+MrLVcp9ILbS
s9W0e0Oz/t4NttK/4wpbadhKtRfMshXZlaersjKrK7aKyqyq9tjf7RNMtZXi
/QtTbFWxx95hqy33h3IPQ5ytXHeurnw3kl35DLby37VSsZXiGcEpd7Jjq113
XL3y1WRb0QvqZFf4St9VnbaKyqyUbaXgKmw19+/dKNmKexj072FQ7gUn2Koy
u8JXuEq9D8RWs+62yro3dIqtptwf6mQrJV+p2kq1FyS7mjFPHTvJVlWZFbby
vH+BO9k9bMU9DNiK7IrsClfts1XWnaETbfXqe4i7rerPCEbaqvr+0Op7GDgr
OOMO0Wm2wlezXKWeWU2+e0HFVoq7VlPOCGIrH1u98hW2mt0L4qvZ8/SZklnR
B2IrbJVlq+l3XE29h0GxF4yyVUd2lb13ha/8XdWdWWGr/sxK1VZuZwQdbPWR
rxxt5XIPw52zgk7ZlcvO1cbsCmP5uKojs3LpA7EVZwS777bqspXKHVecFdSy
ldLOlaOtonzVbRt3Vyl1gYp9ILbqt9WUM4LTbDX9HgbOCs7fuXLoBTt9tdFY
Xa6alFlN7APVbdWxa3XVVllnBFXvtoq2VfU+e7WtOCtIL1idXeErH1OpuWpi
Hzhl18p9j33K/QvYSttW0fvsd3au7tpqYi+ofF7QLbua7is3V7lnVvSB/X2g
6xlBp7utqmxVvc/uYCv37GpLL4ivZhor+tnceX+mZVbqfSC28jgjOOH+ham2
mnpW0MVW9ILzusFJxsJVnjvsan3gNFtV77FX379Q2QeetdVHvppiK84Kzty5
muiru9/hGb5yNFbGM6hy1YTMalMfGH1n6B1bqeyxbzwj2Gkr9XsYpp0VpBf0
t5WirxyMlfW63V0VmVnRB3pnVpwR1LHV1nsYnH01yVaRvSC+mmes7Neq6qqp
mVVWH4itOCPoYiuVs4JHvsJWHr2gc3a12Vfdzqp4bXefvVtm5bTDzq4VZwS3
2kpl5wpb6dhKKbs68z2TlV1V+6rSWNnOqnwduCovs3KzVfSuVfSdoa577FPO
CGIrdq7O+OqurTbvtFdkV06+emqu7p9V3VXKtnrqKvpAnczK9Yygsq0+8pXj
PnuErZTvEM3IrrpsVd0Ldu5dbfWVwzx5vnddRWaVn1lhK84IbrNV5v3sarai
F5ybXV21VUc3iLH8XRW9vz5ph/2urdT7QDVbVe9aqZ8RfGqr6rOCEfezYyuy
q4m+ijBWt2OUJsKrVa6KttWWzCrDVu86BUVbXXGViq3U99izbFV9VpB99t5e
kOxKw1ZkWLjKLbOiD/TKrDps5bhrVW2rSfvsR756d3YjaueKXpDsCl/pmara
VZMzK8U+EFv57Vo52OojX7HPrpldbesFO7Kr6b7aYqyoZ7XFVRMyK/rAOFup
7Fop7bEr24p9dq+7GMiu5vpqsrEUXHXXVpO7QPrAXlup9IGue+wRtlLfZ//I
V262mtALkl3dzyZUfDXFWNHP5Mn7k+2qrZkVfaBmH7hljz3TVuxcaWdXir2g
a3al7qsMYzk6K+MZdLiKzEqvD8RWPnvs2MrXVvSCObZS9lV2N6jqK3VjZb3m
ja5SslVGZkUfyB77NFuxz+5zFwPZFb5St1b263v6HlS4SrkLdNxhd+gD2bXS
yazu2OojX6nss7vcc6WSXWX0gpuzq4puMMJXVcaqclbVa5nmKtfMymmHnT5w
565VlK0m3SE6LbvK6AU777qKtJVrN+jmqwh3df+sEc8bV+W7Sm2HHVthq0pb
sXMVayu17Cq7F5ySXSn4SsFY6oOrzv23pGAr+kDutcJWz3y10VZK2dWUXhBf
YSxVU111FZkVfeDkzMppj/2urT7y1aSdK2Vfqdhqa3Y13VcYK/ZZPnlfyaz2
ZVbYasYeO7aaYyu1XlAlu3LpBp/6CmNpmQpXzc+ssBX3WlXYip2rOFuRXc3o
Bq/aStFXG4yV8cwqXaXeBSpnVhv7wKu2Us6ssBU7V929YMddV5Ozq22+mmas
rGf09L1zcpVLZkUf6JVZTdi1emKrj3xFLzizF3xlq83ZlbKvMo3l6qzM5xHh
qju/J+quIrOadz5QyVaqmVW0rRz/brOqrZR6wSe2isiu3vkqMrtS2b1y8JWD
sypef0dWdcVWV/+9sCWzwlY+tnLrA6tstX3nSuW84PbsyuncYKSvqoylYK3K
14mrntnq7L+rslz1ylbssOu4Clt59IIf/a6oZldKd12pZ1cO3eBdX7kaK9tc
na8l6v3IdNX0LpDMClup7lphK21bOWVXT2ylmF3hKybTVGquUuwCn9pKKbNy
PB+oYivHzOqpra74arutXHbaN2RX+ApjdZpquqsmZ1bb+8AjWx19Bx/Zanof
WGkrfKXTCzpnV/gq/nu+2y3Ko2Kqba5y3LPa0AdetZVCH4itdttqw077lm6w
wlcYy8tUuIrMakIf6GirDldF2OojX2Er/ezqbi+ocGYQX+X5aruzXE2V6apJ
XaDLDvuEPlDBVdNspX4Xw9HvTXd2pbTT3rV3FZVdKfjqyvfik+9fjKXnKXVX
uXaBbpkVfSC2UrPV1OwqoxdUy66m7l1t9dVUZ2U/rypX0QV6Zlb0gXP7QGz1
3FbstOOrSF85GMvVWRXP5ampHF1FZrU3s1KylVJmFWWr7b5y3rvCV3r7V1HG
qnKWir86X2u1p1z2q6ryqi5XTduzmpRZYSt/W6l0g9X3XW33lUOGpWCsKHt1
/7wZpsJVdIGumdVVV224LzTDVh/5SslWatmV0t6VcnaFr+Yby3Gi3g9XV7n0
gJszKzVbbcqssm2l5islW1WfGXySXb36bHLKrlT2r7p9hbE8TbXRVY6Zleue
FbbCVp22IruKPzeIrzCW8kQ+76qsqtNVLpmVUx/46t/oSpkVtsqx1Ue+UrLV
lOzqrq2csysHX7lmWDhL11S4Kmd/3clVkZkVfeAcW6n5asNOu2J25doNVuRX
KhkWxsoxlbKrVHfXyazoA7HVXFtNzK6UbTXFV9UdYZaxNjkr6/k9eU+numpq
F7h9h13FVt2mmm6rI18d3X+WbSuyK+9ucLOvJjor+1lVmyrTVW5dIJkVmZXC
RNtKyVeZtnLeae/cu6rsBrt9dfc7Ut1Yrtaqei64al8XWJ1ZcQ87tnKxleNO
+9TsCl8991WlsRStVf3au0x1x1abXfXEVnddpZBZZdsq875QbNVnq67synmn
fZOvznw/qPrK0ViV7up+XU/fm6eucsmr6AK9MqsoW23NrLJs5ZpdOe60u2ZX
irtXk32lYqxJ02kqXBWbWWV1gZWZFX0gtuq2FdmVhq8isisnX2Es/4l4/sod
4FlXqXWBZFb5O+xRmdWGPjDTVh/5yrkXVMiu3M4MqnWDU3wVZSyc5Weqja5S
7QK3ZVb0gbq2UsquOnfaya76ukF8hbGqPeXQAWa4yqELJLOiD8RWunddbd67
cuwGVXylaKztzop+lh1Z1SZXkVnN3WF3vC9U0VZkV7rZ1VNbbfJVV4aVYawt
1sp6bh2mcnGVwo7V9MyKHfa5tlLKrpx22juyq2xfRXSD+KrXWFOclfl8oky1
3VUVXeCE+6ycMits5W0rp532jOwqqxt89xmFr3Q6wgpjOXmr6jlEvnfZpsJV
9a5yzazYYde01Ue+mtoLup8ZVOgGo3bbnX3laqxuc3W8xsj36W5WtS2viugC
79oqy1VVmZXSPezYyi+7yt5p35pdTe4Gp/uq01hP/dX9M1aYClfFuUoxs7rr
qo2ZFbaqtZVLdlW5d6WYXeGrWF9lGEvVWQ6jZConV7l0gWRW7LA72Uopu4ra
aZ+cXbl0g26+UjQWzurxlKqppruKzKo+s8JWs2x15KurtnLOrt75Kus+UXzl
5yucVeMpXOW3Y0VmRR84xVaZ2dXR70v3XaLTsqsoX535XO72VXVHWGGsjc5S
9tQdU21y1bQusCqzirIVmVWfrbZlVypnBtV9FZVdOfrKxVhTrVX13J6+x9mu
uvrfxCZXkVk9s9XWzMrRVmrZlcreVcdeu2M3ONFX1cZytVbHM+owFXmVdxfo
llmxw95vqyhfdey0T9676s6upvlqm7HUzNX9+iPeR7UOMNpVKjtWXfvryplV
VB/40fc0tvKz1YbsyvXOq2pfZfWDFRlWlLFUnBVpsO6fV9lUG101sQtUPRvY
lVlhqxxbbc2u1Pba330+KfoqK7+64qu735GRvnIwlvt0mwpXzd9fd9uz2t4H
dtjqqq9csqs7O+1O3WCEr6JsFe0rxR2sDGPhLD1PPTUVrqp3ldL++oQ9K2zV
Y6sJ2ZXTXrtLNxjdDyr7KsNYOKvXU+qmmu4qp8zqjqvIrPqnw1ZXfdVxH0PV
3pVTduXqq8z8CmPNn4xnjqv6dqyyMiuH/XUyK2xVdR+Da3bl3A3iK01jYa08
S3WYyslVZz4PpnaBCncucFfoHFtF+Wp6dpXVDW70lcqOu4uxtlgr+/lFvM8V
WZV7XjWtC1S9c4HMaoetyK7ybIWvPDKsKmNNcVbVs4pylVJWtdVVSl1g1f56
V2aFrXJ8pbbTrp5due9e4atYY1U6y8FcHc+iI6eqyKpwFZkVd4X62io7uzr6
fVHIrrL22id0g52+quoIJxir0l7drynDU3dMhavuu8qtC+zOrLgrdKatpmRX
bt3gk+wKX/UbS81Zkyb6fbr7+7LVVZ07Vkr761WZ1ZGt2LPSs9VVX23OrvCV
p6+UjIWz9Dw1wVSOrnLLrKruXCCz2mmrDdmVYjf46vNpm6+qM6wsY+GsXk9V
mwpX+brKLbPavGelZKurvnLKrrbstU/wlXqGlWksnFXnqSemmu6qqh2rd7Z6
4iqVLpDMCltdtdX27ErVV2c+76b5aqKxtlqr4pmqmwpX9exYKd8T2rVnha16
fDUlu+rYa8dXOr5yMNZEa1U+tyfv7xNTKWRVbq6a0gUqZlab+kBnWylmV1P2
2lV2r/CVrrPcvNXxbFxMNclVnTtWDvvrLplVt0Wm2eqqr7qyqw3d4GRfYax5
9up+nVGeemoqXDXHVZX76+xZYavK7IpuEF/d9ZWCsdScNXmmmypjt8rFVZu7
QPasZttK8e8MTsmu8JVmfhVtLJyl6alprlLMqzp3rCZ2gWRWnrY68tX27Apf
afhqgrFw1gxPuXaAk1xFZkVm5WSrq766kl0d2apyr736zqvsexkm+Eq9I8x0
FtaqsZSTqTqzKlxFZjVhJtiqM7va0A2esVXl3QxXfDUxw8o0Fs7Ke65dplJx
VbStnrpKsQusvMvqzv76R7Yis/Ky1VVfZWdX27vBquxqg69cjLXBW9nPLfJ9
VjOVc17l5iqFLpDMaqetonwVnV1Vd4PdvpqSXzkaq8pZjt6qfC7R72lF/4er
6ALJrPbY6qqvyK7m7F5t8lWGsaqdpWKurtesYqoKV3V1gFGuemWrTFc5dIFk
Vthqw167Yjeo6iuljlDNWJ3Omj5Z75eiqXCVTxdIZtU/6raK9FV2dnXXV6/+
u8JXGr6qzLAyjYWzNC1111O4Cle57K9vyqy22WpbN4iv+n2lbCyc1e+pp6a6
46pMUzm6SnXH6pWtKrvAzMyq2xbbbRXpq847GdS6QXzlY6wKZ2GtGkt1mUol
q9rkKqXMqtNV2Ep3ov4WzhVb4av3tqr2VdaO+x1fVfeElcba4q3qZxnx/leY
ClfNchX769jqqq+uZlcf/a5M2GtX373q8lV2R9iVYXUYa4K3up5Xl6mUOkA1
V026x6qqC8RWe2xFdlWzexWRXZ3xlWtH2Gmsbmcp2av7dTubClf1u0p5f/2V
rXCVt62OfNWZXeGrmflVpa8ijaXorG0T9T4qm6rLVWdt9dRV27tAMitsFZld
uey1u+9edeZXm4yFs/w8VW0qlaxKKa/CVbhqo62OfJV9ZhBfaftqUoaFs/Qn
+r15YirF/g9X1biquwvkntD5tqIbjOsG8dVsY+EsHU89NRWuOu8qdqzIrLBV
vK9cu0F8leurqgxL1Vh4q95SEZ5S3atSddXTvOqJq9y7wKj9dWzlM3SD+KrL
V53GqnDWNmtVPM+I932LqXBVjquu3mVFF4itKrOrTb4687kU5avoM4QbjFXl
rGneqnxmnaba7qrsHjBrx0ols6IL3GmrI19FZVcZ3aDivaJuvlLMsBSMVe0s
ZXd1PodIT6mbStlV2XnV9B0rMitsFZFdOXSDmb56aqtpvqrOsKKN1e2spz7r
/jm6PVVtquysStFVXWcCp7qKzGqWra766qqt8NUcXzlkWBnGcnWWw6h4qtJU
GVlVdQ+Y6Sq1+xYiu0Ayq122OvJVRXbF7tV1X3XuuLtkWJnOwlo6loow1Zas
yiGvmrBjdcdWuGqXrdS7wS5fKeRXjhnWRGNhrXpHRXlKOavCVXtcRRc421ZH
voqy1aZuEF/p9YSVztpqrYrnGmWqu6668/vu4Cr1uxaydqzoAnVnkq3w1ex+
MMtXrsaqctZEc1U/t05PqWVV2/Iqlx0rMitsddVWCt0g+VWtr6oyLBVjdThL
2V7dzyHSUw6mUs6qcBWuwlZ5vlLPrqb7quMMYWWGpWQsFWdFO6z75632VIep
trmq866FrB0rukCN2WIrB1+9+zeM4m57tK9UjFXtq+3Ocp2M92uaqaa6qmt3
nczKYybaqsJXHfcy4CufDEvVWVhL01JPPVVtqoysyslVXXkVrvKZqbY68pVC
dqW6246vNHbdq4yFtfo9FWGqCVlVtatUzwRm7VjRBWKrbF+9uq9fpRt09lXn
jvvkDKvKWdu9VfV8o34fFE2V0QGq5FWZPWC1q8issJWKr5z6wWnGUnOWirUq
veVmse5nEmmop5ZS81R0TjU5q1LpAXEVtsr0lVI/OMlX3TnWBGMpWSvKZd0/
m7unsvepXFzVec9C135VZA94ZKvu73Xl2WorfOXrq4nGynKWo7XcJut922qq
yr2qba6KzKy6v9PVZ4utPs0VWzntX2X76sn9V9t8pWwsnKXvqU5TKbiqsgPs
dlX1HVZ0gdgqc1x3r9R9FX2OMKsjdDJWtrOwVr+jojzlbqoOV3Xes4Cr5s92
W1V3g9t95ZhhdfaElc7CXLXPOOr3QtVUuMrfVXSB9wdbee1ePfXVu8+MTb5y
y7A6jDXZWx3PMPL34Imrrv7bYpKrlHtA9R0rbHV+ttnq01y1lZuv3v23T341
w1jd1lJ3V/czUfOUs6lwlYarsNX5wVZ5u1eTfdWx466UYeEsptJTk0yl2AHi
KlwVPRtt9WkUukH1uxmq8ivnDOupr7KMhbP8LfXUU3dMNTGrcneVwo4Vtro+
W231afBVTX7lmGF1GCvTWVjLw1JTTYWrdFxFZlUzm231aRR2r9R99e6zycFX
lcZycBbe0rJUhKcqTdWdVeEqXKU+2Op6djXxbgZ8pemrKmNhrVpHRXpK1VTq
rnpnK2VXsWOlP9tt9Wk27La7+Qpj9Ttruru6nmPk78MdV9393c/MqiI7wOl5
FTtWHoOtvjv4qtZXWRnWFmMpWEvdXt3PQ8lTVaZyz6pwFa6KGmz1/XHoBjf6
SjXDumusDc6K9lj3z6ngqWmm2uiqjrsW6AJ7Blt9f1x2rxR85dARbjWWs7Wc
J/O9VDaVQweIq3BV9WCrH5xNvjpjrCpfqWRYT42l6iys5WWpu56aYqpKV535
d6ZjD3i3C+z+Dp4y2OqHR2X3Cl/1ZViTjYW1NC31xFNPTeXoqjOfOw551d27
Ftix0h5s9fHgq/O2Ouur6I7QwVhPvisrnYW36h0V4amNporqAB1cxe6672Cr
48FXOcZSyLCccqwuZ003V+fzfPq7MM1UE1317jMbV80ebHU8GbtX+CrHV1UZ
loKxup3l5K7uZxPtqQ5TqbgqqgOcnFexu64z2Or14Kv+jlAxw1IxlqK1onzW
/TNN8pSzqXAVrnIcbPV+Ks8OVvgq4o4GZV+5GSvaWROs5TqR72HE71WlqTL2
qiI7wHeuOvPvTtUe8K6rsFXeYKtzM81XVflVdEdYkWF1GivDWVjLw1IbTOWa
VTnnVWRWPYOtzk/lbvuk/Mo1w+o2VpazsJaOoxQ8pWYqXIWrJgy2ujbT8qsI
X3V1hJuMlekszFXrqEhLdZnKIauqcpVqD4iregdbXZvq3fatvsrKsCYYq8pZ
G7xV+Rwzfg+quz+XrOqMq9TvWeCuBe/BVtcHX+l1hA7GynJWtbWc/NX9XJQ8
VWmqjKwqqgN0cBV5lf9gq3vj6KuIHfezn1tdGdZ2Y6lYa+tkvqcdnso0lWtW
hauYM4Ot7o+jr6ryq00Z1hNjVTgLa3la6qmpVHMqXHW/B+SuBZ/BVs/G0VfO
HaG6sRychbd0HdXtqTumcsiqqlz17rP5SV5FZuU12Or54CvtDMvRWNXOwls9
hlLxlJKpcBV51YTBVjGDr+ZlWN1dYbezNpir+7lG/G50uCqr/6vuABVcxY7V
zPlkK4ZhGIZhGCZu/h9J9mO1
"], "Byte", ColorSpace -> "RGB", Interleaving ->
True]
]
(* End of Notebook Content *)
(* Internal cache information *)
(*CellTagsOutline
CellTagsIndex->{
"SlideShowHeader"->{
Cell[580, 22, 136, 2, 74, "SlideShowNavigationBar",ExpressionUUID->"8bda16c8-8161-41a0-869e-f5cfbbfdf7f8",
CellTags->"SlideShowHeader"],
Cell[6735, 152, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"4a0379b0-5018-4d40-a382-1eaf4d20f80d",
CellTags->"SlideShowHeader"],
Cell[52837, 943, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"9950165c-2a91-4f6a-b8df-d4f0183ef671",
CellTags->"SlideShowHeader"],
Cell[77534, 1379, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"5403f1cd-7206-4437-ac04-dc8c94ceca25",
CellTags->"SlideShowHeader"],
Cell[116151, 2067, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"d5886e6f-1aec-43d0-bc77-c5e0a432cfd6",
CellTags->"SlideShowHeader"],
Cell[146795, 2606, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"d20a6431-3da4-4796-9240-2394732efa48",
CellTags->"SlideShowHeader"],
Cell[193032, 3404, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"c75a4f09-68d7-4fff-b1b2-b6a893272d3c",
CellTags->"SlideShowHeader"],
Cell[264931, 4630, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"645f0393-acc3-47a9-9994-f29e46e0bcd5",
CellTags->"SlideShowHeader"]}
}
*)
(*CellTagsIndex
CellTagsIndex->{
{"SlideShowHeader", 322056, 5809}
}
*)
(*NotebookFileOutline
Notebook[{
Cell[CellGroupData[{
Cell[580, 22, 136, 2, 74, "SlideShowNavigationBar",ExpressionUUID->"8bda16c8-8161-41a0-869e-f5cfbbfdf7f8",
CellTags->"SlideShowHeader"],
Cell[719, 26, 465, 9, 270, "Title",ExpressionUUID->"00e36f01-9348-4f94-aa29-323cc3d758e3"],
Cell[1187, 37, 622, 9, 45, "Subtitle",ExpressionUUID->"a60c62de-85fe-4d5b-a531-415918ca4968"],
Cell[1812, 48, 4886, 99, 492, "Text",ExpressionUUID->"9940dca6-90d5-4d58-943d-3773b318f845"]
}, Open ]],
Cell[CellGroupData[{
Cell[6735, 152, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"4a0379b0-5018-4d40-a382-1eaf4d20f80d",
CellTags->"SlideShowHeader"],
Cell[CellGroupData[{
Cell[6882, 158, 43777, 725, 131, "Section",ExpressionUUID->"6d5c40bc-43f4-4592-9d2c-fc8c046877d4"],
Cell[50662, 885, 785, 18, 74, "Text",ExpressionUUID->"e9e24cf8-09f3-4ecf-a320-391998062cba"],
Cell[CellGroupData[{
Cell[51472, 907, 216, 4, 34, "Item",ExpressionUUID->"8a0c5ff2-a12b-4f51-b5b8-97fcb2e209b3"],
Cell[51691, 913, 259, 4, 34, "Item",ExpressionUUID->"682390a8-068b-458a-9606-2d3e33c4a337"],
Cell[51953, 919, 314, 5, 34, "Item",ExpressionUUID->"2a135abf-8c46-47b3-b2e2-8ebf9be88cd7"],
Cell[52270, 926, 236, 4, 34, "Item",ExpressionUUID->"580f36ec-956b-4252-a5ee-bbc2ede148ac"],
Cell[52509, 932, 267, 4, 34, "Item",ExpressionUUID->"44add79d-81d1-4775-ab40-2df463f0ffc4"]
}, Open ]]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell[52837, 943, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"9950165c-2a91-4f6a-b8df-d4f0183ef671",
CellTags->"SlideShowHeader"],
Cell[CellGroupData[{
Cell[52984, 949, 23202, 389, 147, "Section",ExpressionUUID->"697f8473-e998-4e85-a312-973ad4e761a6"],
Cell[CellGroupData[{
Cell[76211, 1342, 229, 4, 34, "Item",ExpressionUUID->"1df1a20c-3cea-4dcf-b267-74efa440c91f"],
Cell[76443, 1348, 265, 4, 34, "Item",ExpressionUUID->"07270b16-c810-411f-8165-ddd1bc1be1a2"],
Cell[76711, 1354, 266, 4, 34, "Item",ExpressionUUID->"5f99b212-bebb-40e8-82ce-892b6df38ba3"]
}, Open ]],
Cell[76992, 1361, 493, 12, 36, "Input",ExpressionUUID->"911aba43-4d15-4f9d-a105-75ab444b8065"]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell[77534, 1379, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"5403f1cd-7206-4437-ac04-dc8c94ceca25",
CellTags->"SlideShowHeader"],
Cell[CellGroupData[{
Cell[77681, 1385, 35716, 592, 134, "Section",ExpressionUUID->"9d42ffc9-95cd-4ef9-b9d0-a9123bb5c43e"],
Cell[CellGroupData[{
Cell[113422, 1981, 205, 4, 34, "Item",ExpressionUUID->"cf4258a5-415c-43ea-b94f-da474301bf7c"],
Cell[113630, 1987, 205, 4, 34, "Item",ExpressionUUID->"e2c5b189-1e14-477f-a3ae-40b69043b44c"],
Cell[113838, 1993, 206, 4, 34, "Item",ExpressionUUID->"609e6dc2-1129-491f-883d-f1d1415e7985"],
Cell[114047, 1999, 202, 4, 34, "Item",ExpressionUUID->"3e612234-9ff1-4f12-a04b-385354eb16b1"],
Cell[114252, 2005, 282, 8, 34, "Item",ExpressionUUID->"df29bf42-69d1-4c90-b327-357a83dc8adc"],
Cell[CellGroupData[{
Cell[114559, 2017, 154, 3, 34, "Subitem",ExpressionUUID->"1d237fa8-a1ba-4f0e-a95e-ea4eb187c13b"],
Cell[114716, 2022, 175, 4, 34, "Subitem",ExpressionUUID->"f1b90eee-8e49-4b67-a3fa-8294486a355b"],
Cell[114894, 2028, 154, 3, 34, "Subitem",ExpressionUUID->"c4277496-93af-4a69-9209-96830f68f00d"]
}, Open ]],
Cell[115063, 2034, 193, 4, 34, "Item",ExpressionUUID->"d7e1c06d-5fee-4a47-9dc5-69d1898241d9"]
}, Open ]],
Cell[115271, 2041, 374, 10, 36, "Input",ExpressionUUID->"2c0181ab-0dee-421b-a990-15a6b703e226"],
Cell[115648, 2053, 454, 8, 39, "Input",ExpressionUUID->"e92be1a5-3f35-4df8-992b-da30f0a72d97"]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell[116151, 2067, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"d5886e6f-1aec-43d0-bc77-c5e0a432cfd6",
CellTags->"SlideShowHeader"],
Cell[CellGroupData[{
Cell[116298, 2073, 28662, 476, 138, "Section",ExpressionUUID->"167406a6-39ae-4757-b9c3-f8846682e0cf"],
Cell[CellGroupData[{
Cell[144985, 2553, 309, 6, 34, "Item",ExpressionUUID->"68c74b27-335f-4ba7-8a01-411c278791d3"],
Cell[145297, 2561, 186, 3, 34, "Item",ExpressionUUID->"1b425a1b-8004-4374-9974-381061d5824e"],
Cell[CellGroupData[{
Cell[145508, 2568, 210, 4, 34, "Subitem",ExpressionUUID->"abc873d8-bb53-4b2e-9259-648a0ecbfb7c"],
Cell[145721, 2574, 210, 4, 34, "Subitem",ExpressionUUID->"e39c198a-8e88-43e7-afb6-eea3b1be26e3"],
Cell[145934, 2580, 206, 4, 34, "Subitem",ExpressionUUID->"56e7e08f-d5aa-4fc2-9837-8354a50f5f9e"]
}, Open ]],
Cell[146155, 2587, 292, 5, 34, "Item",ExpressionUUID->"363a8069-ee6c-456d-9336-a5c168b2faed"],
Cell[146450, 2594, 284, 5, 34, "Item",ExpressionUUID->"c724ac4c-891f-49cc-b4c8-7a7ee140f687"]
}, Open ]]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell[146795, 2606, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"d20a6431-3da4-4796-9240-2394732efa48",
CellTags->"SlideShowHeader"],
Cell[CellGroupData[{
Cell[146942, 2612, 44179, 731, 123, "Section",ExpressionUUID->"2a049373-674e-4937-ab00-36de3e252f55"],
Cell[CellGroupData[{
Cell[191146, 3347, 267, 4, 34, "Item",ExpressionUUID->"4b881169-14e4-4e57-92a4-5c93d1d4988f"],
Cell[191416, 3353, 251, 4, 34, "Item",ExpressionUUID->"f62a28e3-8a7e-426b-ab5c-2503c900e3d6"],
Cell[CellGroupData[{
Cell[191692, 3361, 156, 3, 34, "Subitem",ExpressionUUID->"537a996f-a351-47bd-82f7-1cbdfe1d0879"],
Cell[191851, 3366, 164, 3, 34, "Subitem",ExpressionUUID->"bb0f532a-439e-4da7-b4cd-0fbbe6ec4d37"]
}, Open ]],
Cell[192030, 3372, 305, 5, 34, "Item",ExpressionUUID->"b8ebb412-9aaf-4d8a-be45-ffc0c8babd13"],
Cell[CellGroupData[{
Cell[192360, 3381, 208, 4, 34, "Subitem",ExpressionUUID->"5b6a948b-aa59-40b0-9bc9-ac3ac2195bae"],
Cell[192571, 3387, 233, 4, 34, "Subitem",ExpressionUUID->"88eaa068-3c3e-4aaa-80c0-cf6506af84a6"]
}, Open ]]
}, Open ]],
Cell[192831, 3395, 152, 3, 36, "Input",ExpressionUUID->"24deabd0-9e5f-4367-bc78-4827e8c53ec6"]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell[193032, 3404, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"c75a4f09-68d7-4fff-b1b2-b6a893272d3c",
CellTags->"SlideShowHeader"],
Cell[CellGroupData[{
Cell[193179, 3410, 64804, 1070, 159, "Section",ExpressionUUID->"286bf549-c6a4-488b-b633-8de124892c6f"],
Cell[CellGroupData[{
Cell[258008, 4484, 293, 5, 34, "Item",ExpressionUUID->"97d7eafc-c595-414a-b80f-c7c8f7c7b240"],
Cell[258304, 4491, 427, 6, 34, "Item",ExpressionUUID->"c642da4b-4446-429c-989a-d592b5f35ea4"],
Cell[258734, 4499, 154, 3, 34, "Item",ExpressionUUID->"9a311fc9-a8dd-4694-968d-a3f143d379d9"],
Cell[CellGroupData[{
Cell[258913, 4506, 406, 6, 34, "Subitem",ExpressionUUID->"abbfc901-7e73-4919-9a43-9dda974a85b3"],
Cell[259322, 4514, 476, 7, 34, "Subitem",ExpressionUUID->"d5c10663-fae8-46e1-9aba-dde45fd5dc4f"],
Cell[259801, 4523, 451, 8, 34, "Subitem",ExpressionUUID->"cdfe4ced-459d-4d71-b744-c032f2242f27"],
Cell[260255, 4533, 512, 7, 34, "Subitem",ExpressionUUID->"0e728ad5-32f3-4d33-b3df-3273bfd0ff14"]
}, Open ]],
Cell[260782, 4543, 258, 5, 34, "Item",ExpressionUUID->"bb1b0121-7837-4bec-bc11-fb2c2ae5272b"],
Cell[261043, 4550, 208, 4, 34, "Item",ExpressionUUID->"5469fc6e-a9e3-4f91-9dd6-d9dd2432c85d"],
Cell[CellGroupData[{
Cell[261276, 4558, 584, 9, 34, "Subitem",ExpressionUUID->"0c24741c-dcc5-464d-8a95-57c33c320783"],
Cell[261863, 4569, 630, 9, 34, "Subitem",ExpressionUUID->"9b62392e-cf5e-444d-bf1e-40419a8c73ab"],
Cell[262496, 4580, 577, 9, 34, "Subitem",ExpressionUUID->"d44f6bf0-a4c0-4f89-bfd7-f1dffc4d08a8"],
Cell[263076, 4591, 691, 11, 34, "Subitem",ExpressionUUID->"b2e3184b-e26c-4e04-9bd3-5d5c3cac7dbd"],
Cell[263770, 4604, 550, 8, 34, "Subitem",ExpressionUUID->"4b420ff9-33fc-40eb-bc7f-0adb805c41d2"],
Cell[264323, 4614, 535, 8, 34, "Subitem",ExpressionUUID->"44c35e4d-b612-4668-ac41-1fb89d377a5a"]
}, Open ]]
}, Open ]]
}, Open ]]
}, Open ]],
Cell[CellGroupData[{
Cell[264931, 4630, 122, 2, 50, "SlideShowNavigationBar",ExpressionUUID->"645f0393-acc3-47a9-9994-f29e46e0bcd5",
CellTags->"SlideShowHeader"],
Cell[CellGroupData[{
Cell[265078, 4636, 487, 8, 104, "Section",ExpressionUUID->"f9989c77-4308-43e8-b830-91537ff675aa"],
Cell[CellGroupData[{
Cell[265590, 4648, 379, 6, 34, "Item",ExpressionUUID->"f5b1ed4c-7d12-43cb-a31f-b7703d2febe0"],
Cell[265972, 4656, 309, 5, 34, "Item",ExpressionUUID->"27d28bdc-c422-40eb-818c-98df92917325"],
Cell[266284, 4663, 282, 5, 34, "Item",ExpressionUUID->"f4727104-6f02-46fc-9bec-46daa495bf61"]
}, Open ]]
}, Open ]]
}, Open ]]
}
]
*)