Tensorflow+Tutorial.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>Tensorflow Tutorial</title>

<script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>

<style type="text/css">
    /*!
*
* Twitter Bootstrap
*
*/
/*!
 * Bootstrap v3.3.6 (http://getbootstrap.com)
 * Copyright 2011-2015 Twitter, Inc.
 * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
 */
/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
  font-family: sans-serif;
  -ms-text-size-adjust: 100%;
  -webkit-text-size-adjust: 100%;
}
body {
  margin: 0;
}
article,
aside,
details,
figcaption,
figure,
footer,
header,
hgroup,
main,
menu,
nav,
section,
summary {
  display: block;
}
audio,
canvas,
progress,
video {
  display: inline-block;
  vertical-align: baseline;
}
audio:not([controls]) {
  display: none;
  height: 0;
}
[hidden],
template {
  display: none;
}
a {
  background-color: transparent;
}
a:active,
a:hover {
  outline: 0;
}
abbr[title] {
  border-bottom: 1px dotted;
}
b,
strong {
  font-weight: bold;
}
dfn {
  font-style: italic;
}
h1 {
  font-size: 2em;
  margin: 0.67em 0;
}
mark {
  background: #ff0;
  color: #000;
}
small {
  font-size: 80%;
}
sub,
sup {
  font-size: 75%;
  line-height: 0;
  position: relative;
  vertical-align: baseline;
}
sup {
  top: -0.5em;
}
sub {
  bottom: -0.25em;
}
img {
  border: 0;
}
svg:not(:root) {
  overflow: hidden;
}
figure {
  margin: 1em 40px;
}
hr {
  box-sizing: content-box;
  height: 0;
}
pre {
  overflow: auto;
}
code,
kbd,
pre,
samp {
  font-family: monospace, monospace;
  font-size: 1em;
}
button,
input,
optgroup,
select,
textarea {
  color: inherit;
  font: inherit;
  margin: 0;
}
button {
  overflow: visible;
}
button,
select {
  text-transform: none;
}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
  -webkit-appearance: button;
  cursor: pointer;
}
button[disabled],
html input[disabled] {
  cursor: default;
}
button::-moz-focus-inner,
input::-moz-focus-inner {
  border: 0;
  padding: 0;
}
input {
  line-height: normal;
}
input[type="checkbox"],
input[type="radio"] {
  box-sizing: border-box;
  padding: 0;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: textfield;
  box-sizing: content-box;
}
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
  -webkit-appearance: none;
}
fieldset {
  border: 1px solid #c0c0c0;
  margin: 0 2px;
  padding: 0.35em 0.625em 0.75em;
}
legend {
  border: 0;
  padding: 0;
}
textarea {
  overflow: auto;
}
optgroup {
  font-weight: bold;
}
table {
  border-collapse: collapse;
  border-spacing: 0;
}
td,
th {
  padding: 0;
}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
  *,
  *:before,
  *:after {
    background: transparent !important;
    color: #000 !important;
    box-shadow: none !important;
    text-shadow: none !important;
  }
  a,
  a:visited {
    text-decoration: underline;
  }
  a[href]:after {
    content: " (" attr(href) ")";
  }
  abbr[title]:after {
    content: " (" attr(title) ")";
  }
  a[href^="#"]:after,
  a[href^="javascript:"]:after {
    content: "";
  }
  pre,
  blockquote {
    border: 1px solid #999;
    page-break-inside: avoid;
  }
  thead {
    display: table-header-group;
  }
  tr,
  img {
    page-break-inside: avoid;
  }
  img {
    max-width: 100% !important;
  }
  p,
  h2,
  h3 {
    orphans: 3;
    widows: 3;
  }
  h2,
  h3 {
    page-break-after: avoid;
  }
  .navbar {
    display: none;
  }
  .btn > .caret,
  .dropup > .btn > .caret {
    border-top-color: #000 !important;
  }
  .label {
    border: 1px solid #000;
  }
  .table {
    border-collapse: collapse !important;
  }
  .table td,
  .table th {
    background-color: #fff !important;
  }
  .table-bordered th,
  .table-bordered td {
    border: 1px solid #ddd !important;
  }
}
@font-face {
  font-family: 'Glyphicons Halflings';
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
}
.glyphicon {
  position: relative;
  top: 1px;
  display: inline-block;
  font-family: 'Glyphicons Halflings';
  font-style: normal;
  font-weight: normal;
  line-height: 1;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
.glyphicon-asterisk:before {
  content: "\002a";
}
.glyphicon-plus:before {
  content: "\002b";
}
.glyphicon-euro:before,
.glyphicon-eur:before {
  content: "\20ac";
}
.glyphicon-minus:before {
  content: "\2212";
}
.glyphicon-cloud:before {
  content: "\2601";
}
.glyphicon-envelope:before {
  content: "\2709";
}
.glyphicon-pencil:before {
  content: "\270f";
}
.glyphicon-glass:before {
  content: "\e001";
}
.glyphicon-music:before {
  content: "\e002";
}
.glyphicon-search:before {
  content: "\e003";
}
.glyphicon-heart:before {
  content: "\e005";
}
.glyphicon-star:before {
  content: "\e006";
}
.glyphicon-star-empty:before {
  content: "\e007";
}
.glyphicon-user:before {
  content: "\e008";
}
.glyphicon-film:before {
  content: "\e009";
}
.glyphicon-th-large:before {
  content: "\e010";
}
.glyphicon-th:before {
  content: "\e011";
}
.glyphicon-th-list:before {
  content: "\e012";
}
.glyphicon-ok:before {
  content: "\e013";
}
.glyphicon-remove:before {
  content: "\e014";
}
.glyphicon-zoom-in:before {
  content: "\e015";
}
.glyphicon-zoom-out:before {
  content: "\e016";
}
.glyphicon-off:before {
  content: "\e017";
}
.glyphicon-signal:before {
  content: "\e018";
}
.glyphicon-cog:before {
  content: "\e019";
}
.glyphicon-trash:before {
  content: "\e020";
}
.glyphicon-home:before {
  content: "\e021";
}
.glyphicon-file:before {
  content: "\e022";
}
.glyphicon-time:before {
  content: "\e023";
}
.glyphicon-road:before {
  content: "\e024";
}
.glyphicon-download-alt:before {
  content: "\e025";
}
.glyphicon-download:before {
  content: "\e026";
}
.glyphicon-upload:before {
  content: "\e027";
}
.glyphicon-inbox:before {
  content: "\e028";
}
.glyphicon-play-circle:before {
  content: "\e029";
}
.glyphicon-repeat:before {
  content: "\e030";
}
.glyphicon-refresh:before {
  content: "\e031";
}
.glyphicon-list-alt:before {
  content: "\e032";
}
.glyphicon-lock:before {
  content: "\e033";
}
.glyphicon-flag:before {
  content: "\e034";
}
.glyphicon-headphones:before {
  content: "\e035";
}
.glyphicon-volume-off:before {
  content: "\e036";
}
.glyphicon-volume-down:before {
  content: "\e037";
}
.glyphicon-volume-up:before {
  content: "\e038";
}
.glyphicon-qrcode:before {
  content: "\e039";
}
.glyphicon-barcode:before {
  content: "\e040";
}
.glyphicon-tag:before {
  content: "\e041";
}
.glyphicon-tags:before {
  content: "\e042";
}
.glyphicon-book:before {
  content: "\e043";
}
.glyphicon-bookmark:before {
  content: "\e044";
}
.glyphicon-print:before {
  content: "\e045";
}
.glyphicon-camera:before {
  content: "\e046";
}
.glyphicon-font:before {
  content: "\e047";
}
.glyphicon-bold:before {
  content: "\e048";
}
.glyphicon-italic:before {
  content: "\e049";
}
.glyphicon-text-height:before {
  content: "\e050";
}
.glyphicon-text-width:before {
  content: "\e051";
}
.glyphicon-align-left:before {
  content: "\e052";
}
.glyphicon-align-center:before {
  content: "\e053";
}
.glyphicon-align-right:before {
  content: "\e054";
}
.glyphicon-align-justify:before {
  content: "\e055";
}
.glyphicon-list:before {
  content: "\e056";
}
.glyphicon-indent-left:before {
  content: "\e057";
}
.glyphicon-indent-right:before {
  content: "\e058";
}
.glyphicon-facetime-video:before {
  content: "\e059";
}
.glyphicon-picture:before {
  content: "\e060";
}
.glyphicon-map-marker:before {
  content: "\e062";
}
.glyphicon-adjust:before {
  content: "\e063";
}
.glyphicon-tint:before {
  content: "\e064";
}
.glyphicon-edit:before {
  content: "\e065";
}
.glyphicon-share:before {
  content: "\e066";
}
.glyphicon-check:before {
  content: "\e067";
}
.glyphicon-move:before {
  content: "\e068";
}
.glyphicon-step-backward:before {
  content: "\e069";
}
.glyphicon-fast-backward:before {
  content: "\e070";
}
.glyphicon-backward:before {
  content: "\e071";
}
.glyphicon-play:before {
  content: "\e072";
}
.glyphicon-pause:before {
  content: "\e073";
}
.glyphicon-stop:before {
  content: "\e074";
}
.glyphicon-forward:before {
  content: "\e075";
}
.glyphicon-fast-forward:before {
  content: "\e076";
}
.glyphicon-step-forward:before {
  content: "\e077";
}
.glyphicon-eject:before {
  content: "\e078";
}
.glyphicon-chevron-left:before {
  content: "\e079";
}
.glyphicon-chevron-right:before {
  content: "\e080";
}
.glyphicon-plus-sign:before {
  content: "\e081";
}
.glyphicon-minus-sign:before {
  content: "\e082";
}
.glyphicon-remove-sign:before {
  content: "\e083";
}
.glyphicon-ok-sign:before {
  content: "\e084";
}
.glyphicon-question-sign:before {
  content: "\e085";
}
.glyphicon-info-sign:before {
  content: "\e086";
}
.glyphicon-screenshot:before {
  content: "\e087";
}
.glyphicon-remove-circle:before {
  content: "\e088";
}
.glyphicon-ok-circle:before {
  content: "\e089";
}
.glyphicon-ban-circle:before {
  content: "\e090";
}
.glyphicon-arrow-left:before {
  content: "\e091";
}
.glyphicon-arrow-right:before {
  content: "\e092";
}
.glyphicon-arrow-up:before {
  content: "\e093";
}
.glyphicon-arrow-down:before {
  content: "\e094";
}
.glyphicon-share-alt:before {
  content: "\e095";
}
.glyphicon-resize-full:before {
  content: "\e096";
}
.glyphicon-resize-small:before {
  content: "\e097";
}
.glyphicon-exclamation-sign:before {
  content: "\e101";
}
.glyphicon-gift:before {
  content: "\e102";
}
.glyphicon-leaf:before {
  content: "\e103";
}
.glyphicon-fire:before {
  content: "\e104";
}
.glyphicon-eye-open:before {
  content: "\e105";
}
.glyphicon-eye-close:before {
  content: "\e106";
}
.glyphicon-warning-sign:before {
  content: "\e107";
}
.glyphicon-plane:before {
  content: "\e108";
}
.glyphicon-calendar:before {
  content: "\e109";
}
.glyphicon-random:before {
  content: "\e110";
}
.glyphicon-comment:before {
  content: "\e111";
}
.glyphicon-magnet:before {
  content: "\e112";
}
.glyphicon-chevron-up:before {
  content: "\e113";
}
.glyphicon-chevron-down:before {
  content: "\e114";
}
.glyphicon-retweet:before {
  content: "\e115";
}
.glyphicon-shopping-cart:before {
  content: "\e116";
}
.glyphicon-folder-close:before {
  content: "\e117";
}
.glyphicon-folder-open:before {
  content: "\e118";
}
.glyphicon-resize-vertical:before {
  content: "\e119";
}
.glyphicon-resize-horizontal:before {
  content: "\e120";
}
.glyphicon-hdd:before {
  content: "\e121";
}
.glyphicon-bullhorn:before {
  content: "\e122";
}
.glyphicon-bell:before {
  content: "\e123";
}
.glyphicon-certificate:before {
  content: "\e124";
}
.glyphicon-thumbs-up:before {
  content: "\e125";
}
.glyphicon-thumbs-down:before {
  content: "\e126";
}
.glyphicon-hand-right:before {
  content: "\e127";
}
.glyphicon-hand-left:before {
  content: "\e128";
}
.glyphicon-hand-up:before {
  content: "\e129";
}
.glyphicon-hand-down:before {
  content: "\e130";
}
.glyphicon-circle-arrow-right:before {
  content: "\e131";
}
.glyphicon-circle-arrow-left:before {
  content: "\e132";
}
.glyphicon-circle-arrow-up:before {
  content: "\e133";
}
.glyphicon-circle-arrow-down:before {
  content: "\e134";
}
.glyphicon-globe:before {
  content: "\e135";
}
.glyphicon-wrench:before {
  content: "\e136";
}
.glyphicon-tasks:before {
  content: "\e137";
}
.glyphicon-filter:before {
  content: "\e138";
}
.glyphicon-briefcase:before {
  content: "\e139";
}
.glyphicon-fullscreen:before {
  content: "\e140";
}
.glyphicon-dashboard:before {
  content: "\e141";
}
.glyphicon-paperclip:before {
  content: "\e142";
}
.glyphicon-heart-empty:before {
  content: "\e143";
}
.glyphicon-link:before {
  content: "\e144";
}
.glyphicon-phone:before {
  content: "\e145";
}
.glyphicon-pushpin:before {
  content: "\e146";
}
.glyphicon-usd:before {
  content: "\e148";
}
.glyphicon-gbp:before {
  content: "\e149";
}
.glyphicon-sort:before {
  content: "\e150";
}
.glyphicon-sort-by-alphabet:before {
  content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
  content: "\e152";
}
.glyphicon-sort-by-order:before {
  content: "\e153";
}
.glyphicon-sort-by-order-alt:before {
  content: "\e154";
}
.glyphicon-sort-by-attributes:before {
  content: "\e155";
}
.glyphicon-sort-by-attributes-alt:before {
  content: "\e156";
}
.glyphicon-unchecked:before {
  content: "\e157";
}
.glyphicon-expand:before {
  content: "\e158";
}
.glyphicon-collapse-down:before {
  content: "\e159";
}
.glyphicon-collapse-up:before {
  content: "\e160";
}
.glyphicon-log-in:before {
  content: "\e161";
}
.glyphicon-flash:before {
  content: "\e162";
}
.glyphicon-log-out:before {
  content: "\e163";
}
.glyphicon-new-window:before {
  content: "\e164";
}
.glyphicon-record:before {
  content: "\e165";
}
.glyphicon-save:before {
  content: "\e166";
}
.glyphicon-open:before {
  content: "\e167";
}
.glyphicon-saved:before {
  content: "\e168";
}
.glyphicon-import:before {
  content: "\e169";
}
.glyphicon-export:before {
  content: "\e170";
}
.glyphicon-send:before {
  content: "\e171";
}
.glyphicon-floppy-disk:before {
  content: "\e172";
}
.glyphicon-floppy-saved:before {
  content: "\e173";
}
.glyphicon-floppy-remove:before {
  content: "\e174";
}
.glyphicon-floppy-save:before {
  content: "\e175";
}
.glyphicon-floppy-open:before {
  content: "\e176";
}
.glyphicon-credit-card:before {
  content: "\e177";
}
.glyphicon-transfer:before {
  content: "\e178";
}
.glyphicon-cutlery:before {
  content: "\e179";
}
.glyphicon-header:before {
  content: "\e180";
}
.glyphicon-compressed:before {
  content: "\e181";
}
.glyphicon-earphone:before {
  content: "\e182";
}
.glyphicon-phone-alt:before {
  content: "\e183";
}
.glyphicon-tower:before {
  content: "\e184";
}
.glyphicon-stats:before {
  content: "\e185";
}
.glyphicon-sd-video:before {
  content: "\e186";
}
.glyphicon-hd-video:before {
  content: "\e187";
}
.glyphicon-subtitles:before {
  content: "\e188";
}
.glyphicon-sound-stereo:before {
  content: "\e189";
}
.glyphicon-sound-dolby:before {
  content: "\e190";
}
.glyphicon-sound-5-1:before {
  content: "\e191";
}
.glyphicon-sound-6-1:before {
  content: "\e192";
}
.glyphicon-sound-7-1:before {
  content: "\e193";
}
.glyphicon-copyright-mark:before {
  content: "\e194";
}
.glyphicon-registration-mark:before {
  content: "\e195";
}
.glyphicon-cloud-download:before {
  content: "\e197";
}
.glyphicon-cloud-upload:before {
  content: "\e198";
}
.glyphicon-tree-conifer:before {
  content: "\e199";
}
.glyphicon-tree-deciduous:before {
  content: "\e200";
}
.glyphicon-cd:before {
  content: "\e201";
}
.glyphicon-save-file:before {
  content: "\e202";
}
.glyphicon-open-file:before {
  content: "\e203";
}
.glyphicon-level-up:before {
  content: "\e204";
}
.glyphicon-copy:before {
  content: "\e205";
}
.glyphicon-paste:before {
  content: "\e206";
}
.glyphicon-alert:before {
  content: "\e209";
}
.glyphicon-equalizer:before {
  content: "\e210";
}
.glyphicon-king:before {
  content: "\e211";
}
.glyphicon-queen:before {
  content: "\e212";
}
.glyphicon-pawn:before {
  content: "\e213";
}
.glyphicon-bishop:before {
  content: "\e214";
}
.glyphicon-knight:before {
  content: "\e215";
}
.glyphicon-baby-formula:before {
  content: "\e216";
}
.glyphicon-tent:before {
  content: "\26fa";
}
.glyphicon-blackboard:before {
  content: "\e218";
}
.glyphicon-bed:before {
  content: "\e219";
}
.glyphicon-apple:before {
  content: "\f8ff";
}
.glyphicon-erase:before {
  content: "\e221";
}
.glyphicon-hourglass:before {
  content: "\231b";
}
.glyphicon-lamp:before {
  content: "\e223";
}
.glyphicon-duplicate:before {
  content: "\e224";
}
.glyphicon-piggy-bank:before {
  content: "\e225";
}
.glyphicon-scissors:before {
  content: "\e226";
}
.glyphicon-bitcoin:before {
  content: "\e227";
}
.glyphicon-btc:before {
  content: "\e227";
}
.glyphicon-xbt:before {
  content: "\e227";
}
.glyphicon-yen:before {
  content: "\00a5";
}
.glyphicon-jpy:before {
  content: "\00a5";
}
.glyphicon-ruble:before {
  content: "\20bd";
}
.glyphicon-rub:before {
  content: "\20bd";
}
.glyphicon-scale:before {
  content: "\e230";
}
.glyphicon-ice-lolly:before {
  content: "\e231";
}
.glyphicon-ice-lolly-tasted:before {
  content: "\e232";
}
.glyphicon-education:before {
  content: "\e233";
}
.glyphicon-option-horizontal:before {
  content: "\e234";
}
.glyphicon-option-vertical:before {
  content: "\e235";
}
.glyphicon-menu-hamburger:before {
  content: "\e236";
}
.glyphicon-modal-window:before {
  content: "\e237";
}
.glyphicon-oil:before {
  content: "\e238";
}
.glyphicon-grain:before {
  content: "\e239";
}
.glyphicon-sunglasses:before {
  content: "\e240";
}
.glyphicon-text-size:before {
  content: "\e241";
}
.glyphicon-text-color:before {
  content: "\e242";
}
.glyphicon-text-background:before {
  content: "\e243";
}
.glyphicon-object-align-top:before {
  content: "\e244";
}
.glyphicon-object-align-bottom:before {
  content: "\e245";
}
.glyphicon-object-align-horizontal:before {
  content: "\e246";
}
.glyphicon-object-align-left:before {
  content: "\e247";
}
.glyphicon-object-align-vertical:before {
  content: "\e248";
}
.glyphicon-object-align-right:before {
  content: "\e249";
}
.glyphicon-triangle-right:before {
  content: "\e250";
}
.glyphicon-triangle-left:before {
  content: "\e251";
}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: thin dotted;
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: thin dotted;
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: thin dotted;
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
@media (max-width: 991px) {
  #ipython_notebook {
    margin-left: 10px;
  }
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#login_widget {
  float: right;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  text-align: center;
  vertical-align: middle;
  display: inline;
  opacity: 0;
  z-index: 2;
  width: 12ex;
  margin-right: -12ex;
}
.alternate_upload .btn-upload {
  height: 22px;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: baseline;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI colors. */
.ansibold {
  font-weight: bold;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  border-left-width: 1px;
  padding-left: 5px;
  background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
}
div.cell.jupyter-soft-selected {
  border-left-color: #90CAF9;
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected {
  border-color: #ababab;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
}
@media print {
  div.cell.selected {
    border-color: transparent;
  }
}
div.cell.selected.jupyter-soft-selected {
  border-left-width: 0;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
@-moz-document url-prefix() {
  div.inner_cell {
    overflow-x: hidden;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  padding: 0.4em;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
  /* .CodeMirror-lines */
  padding: 0;
  border: 0;
  border-radius: 0;
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 20ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  display: none;
}
.command-shortcut:before {
  content: "(command)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
    </style>
<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
.highlight .mh { color: #666666 } /* Literal.Number.Hex */
.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
    </style>
<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

    </style>
<style type="text/css">
    /* Hack to suppress certificate warning display on graphlab license call*/
.output_stderr {
    display: none;
}

/* Format for custom error modal message */
.running-notebooks {
    padding-top: 2em;
}

    </style>


<style type="text/css">
/* Overrides of notebook CSS for static HTML export */
body {
  overflow: visible;
  padding: 8px;
}

div#notebook {
  overflow: visible;
  border-top: none;
}

@media print {
  div.cell {
    display: block;
    page-break-inside: avoid;
  } 
  div.output_wrapper { 
    display: block;
    page-break-inside: avoid; 
  }
  div.output { 
    display: block;
    page-break-inside: avoid; 
  }
}
</style>

<!-- Custom stylesheet, it must be in the same directory as the html file -->
<link rel="stylesheet" href="custom.css">

<!-- Loading mathjax macro -->
<!-- Load mathjax -->
    <script src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS_HTML"></script>
    <!-- MathJax configuration -->
    <script type="text/x-mathjax-config">
    MathJax.Hub.Config({
        tex2jax: {
            inlineMath: [ ['$','$'], ["\\(","\\)"] ],
            displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
            processEscapes: true,
            processEnvironments: true
        },
        // Center justify equations in code and markdown cells. Elsewhere
        // we use CSS to left justify single line equations in code cells.
        displayAlign: 'center',
        "HTML-CSS": {
            styles: {'.MathJax_Display': {"margin": 0}},
            linebreaks: { automatic: true }
        }
    });
    </script>
    <!-- End of mathjax configuration --></head>
<body>
  <div tabindex="-1" id="notebook" class="border-box-sizing">
    <div class="container" id="notebook-container">

<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="TensorFlow-Tutorial">TensorFlow Tutorial<a class="anchor-link" href="#TensorFlow-Tutorial">&#182;</a></h1><p>Welcome to this week's programming assignment. Until now, you've always used numpy to build neural networks. Now we will step you through a deep learning framework that will allow you to build neural networks more easily. Machine learning frameworks like TensorFlow, PaddlePaddle, Torch, Caffe, Keras, and many others can speed up your machine learning development significantly. All of these frameworks also have a lot of documentation, which you should feel free to read. In this assignment, you will learn to do the following in TensorFlow:</p>
<ul>
<li>Initialize variables</li>
<li>Start your own session</li>
<li>Train algorithms </li>
<li>Implement a Neural Network</li>
</ul>
<p>Programing frameworks can not only shorten your coding time, but sometimes also perform optimizations that speed up your code.</p>
<h2 id="1---Exploring-the-Tensorflow-Library">1 - Exploring the Tensorflow Library<a class="anchor-link" href="#1---Exploring-the-Tensorflow-Library">&#182;</a></h2><p>To start, you will import the library:</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[1]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">math</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">h5py</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span>
<span class="kn">from</span> <span class="nn">tensorflow.python.framework</span> <span class="k">import</span> <span class="n">ops</span>
<span class="kn">from</span> <span class="nn">tf_utils</span> <span class="k">import</span> <span class="n">load_dataset</span><span class="p">,</span> <span class="n">random_mini_batches</span><span class="p">,</span> <span class="n">convert_to_one_hot</span><span class="p">,</span> <span class="n">predict</span>

<span class="o">%</span><span class="k">matplotlib</span> inline
<span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Now that you have imported the library, we will walk you through its different applications. You will start with an example, where we compute for you the loss of one training example. 
$$loss = \mathcal{L}(\hat{y}, y) = (\hat y^{(i)} - y^{(i)})^2 \tag{1}$$</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[2]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">y_hat</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">(</span><span class="mi">36</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;y_hat&#39;</span><span class="p">)</span>            <span class="c1"># Define y_hat constant. Set to 36.</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">(</span><span class="mi">39</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;y&#39;</span><span class="p">)</span>                    <span class="c1"># Define y. Set to 39</span>

<span class="n">loss</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">((</span><span class="n">y</span> <span class="o">-</span> <span class="n">y_hat</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;loss&#39;</span><span class="p">)</span>  <span class="c1"># Create a variable for the loss</span>

<span class="n">init</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">global_variables_initializer</span><span class="p">()</span>         <span class="c1"># When init is run later (session.run(init)),</span>
                                                 <span class="c1"># the loss variable will be initialized and ready to be computed</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">session</span><span class="p">:</span>                    <span class="c1"># Create a session and print the output</span>
    <span class="n">session</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">init</span><span class="p">)</span>                            <span class="c1"># Initializes the variables</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">session</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">loss</span><span class="p">))</span>                     <span class="c1"># Prints the loss</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>9
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Writing and running programs in TensorFlow has the following steps:</p>
<ol>
<li>Create Tensors (variables) that are not yet executed/evaluated. </li>
<li>Write operations between those Tensors.</li>
<li>Initialize your Tensors. </li>
<li>Create a Session. </li>
<li>Run the Session. This will run the operations you'd written above. </li>
</ol>
<p>Therefore, when we created a variable for the loss, we simply defined the loss as a function of other quantities, but did not evaluate its value. To evaluate it, we had to run <code>init=tf.global_variables_initializer()</code>. That initialized the loss variable, and in the last line we were finally able to evaluate the value of <code>loss</code> and print its value.</p>
<p>Now let us look at an easy example. Run the cell below:</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[3]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">a</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
<span class="n">b</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
<span class="n">c</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">multiply</span><span class="p">(</span><span class="n">a</span><span class="p">,</span><span class="n">b</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>Tensor(&#34;Mul:0&#34;, shape=(), dtype=int32)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>As expected, you will not see 20! You got a tensor saying that the result is a tensor that does not have the shape attribute, and is of type "int32". All you did was put in the 'computation graph', but you have not run this computation yet. In order to actually multiply the two numbers, you will have to create a session and run it.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[4]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sess</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">c</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>20
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Great! To summarize, <strong>remember to initialize your variables, create a session and run the operations inside the session</strong>.</p>
<p>Next, you'll also have to know about placeholders. A placeholder is an object whose value you can specify only later. 
To specify values for a placeholder, you can pass in values by using a "feed dictionary" (<code>feed_dict</code> variable). Below, we created a placeholder for x. This allows us to pass in a number later when we run the session.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[5]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Change the value of x in the feed_dict</span>

<span class="n">x</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int64</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="s1">&#39;x&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">x</span><span class="p">,</span> <span class="n">feed_dict</span> <span class="o">=</span> <span class="p">{</span><span class="n">x</span><span class="p">:</span> <span class="mi">3</span><span class="p">}))</span>
<span class="n">sess</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>6
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>When you first defined <code>x</code> you did not have to specify a value for it. A placeholder is simply a variable that you will assign data to only later, when running the session. We say that you <strong>feed data</strong> to these placeholders when running the session.</p>
<p>Here's what's happening: When you specify the operations needed for a computation, you are telling TensorFlow how to construct a computation graph. The computation graph can have some placeholders whose values you will specify only later. Finally, when you run the session, you are telling TensorFlow to execute the computation graph.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="1.1---Linear-function">1.1 - Linear function<a class="anchor-link" href="#1.1---Linear-function">&#182;</a></h3><p>Lets start this programming exercise by computing the following equation: $Y = WX + b$, where $W$ and $X$ are random matrices and b is a random vector.</p>
<p><strong>Exercise</strong>: Compute $WX + b$ where $W, X$, and $b$ are drawn from a random normal distribution. W is of shape (4, 3), X is (3,1) and b is (4,1). As an example, here is how you would define a constant X that has shape (3,1):</p>
<div class="highlight"><pre><span></span><span class="n">X</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span><span class="mi">1</span><span class="p">),</span> <span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;X&quot;</span><span class="p">)</span>
</pre></div>
<p>You might find the following functions helpful:</p>
<ul>
<li>tf.matmul(..., ...) to do a matrix multiplication</li>
<li>tf.add(..., ...) to do an addition</li>
<li>np.random.randn(...) to initialize randomly</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[8]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># GRADED FUNCTION: linear_function</span>

<span class="k">def</span> <span class="nf">linear_function</span><span class="p">():</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Implements a linear function: </span>
<span class="sd">            Initializes W to be a random tensor of shape (4,3)</span>
<span class="sd">            Initializes X to be a random tensor of shape (3,1)</span>
<span class="sd">            Initializes b to be a random tensor of shape (4,1)</span>
<span class="sd">    Returns: </span>
<span class="sd">    result -- runs the session for Y = WX + b </span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
    
    <span class="c1">### START CODE HERE ### (4 lines of code)</span>
    <span class="n">X</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span><span class="mi">1</span><span class="p">),</span> <span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;X&quot;</span><span class="p">)</span>
    <span class="n">W</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">3</span><span class="p">),</span> <span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;W&quot;</span><span class="p">)</span>
    <span class="n">b</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">1</span><span class="p">),</span> <span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;b&quot;</span><span class="p">)</span>
    <span class="n">Y</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">W</span><span class="p">,</span><span class="n">X</span><span class="p">),</span><span class="n">b</span><span class="p">)</span>
    <span class="c1">### END CODE HERE ### </span>
    
    <span class="c1"># Create the session using tf.Session() and run it with sess.run(...) on the variable you want to calculate</span>
    
    <span class="c1">### START CODE HERE ###</span>
    <span class="n">sess</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span>
    <span class="n">result</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">Y</span><span class="p">)</span>
    <span class="c1">### END CODE HERE ### </span>
    
    <span class="c1"># close the session </span>
    <span class="n">sess</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>

    <span class="k">return</span> <span class="n">result</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[9]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span> <span class="s2">&quot;result = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">linear_function</span><span class="p">()))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>result = [[-2.15657382]
 [ 2.95891446]
 [-1.08926781]
 [-0.84538042]]
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong><em> Expected Output </em></strong>:</p>
<table> 
<tr> 
<td>
**result**
</td>
<td>
[[-2.15657382]
 [ 2.95891446]
 [-1.08926781]
 [-0.84538042]]
</td>
</tr> 

</table>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="1.2---Computing-the-sigmoid">1.2 - Computing the sigmoid<a class="anchor-link" href="#1.2---Computing-the-sigmoid">&#182;</a></h3><p>Great! You just implemented a linear function. Tensorflow offers a variety of commonly used neural network functions like <code>tf.sigmoid</code> and <code>tf.softmax</code>. For this exercise lets compute the sigmoid function of an input.</p>
<p>You will do this exercise using a placeholder variable <code>x</code>. When running the session, you should use the feed dictionary to pass in the input <code>z</code>. In this exercise, you will have to (i) create a placeholder <code>x</code>, (ii) define the operations needed to compute the sigmoid using <code>tf.sigmoid</code>, and then (iii) run the session.</p>
<p><strong> Exercise </strong>: Implement the sigmoid function below. You should use the following:</p>
<ul>
<li><code>tf.placeholder(tf.float32, name = "...")</code></li>
<li><code>tf.sigmoid(...)</code></li>
<li><code>sess.run(..., feed_dict = {x: z})</code></li>
</ul>
<p>Note that there are two typical ways to create and use sessions in tensorflow:</p>
<p><strong>Method 1:</strong></p>
<div class="highlight"><pre><span></span><span class="n">sess</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span>
<span class="c1"># Run the variables initialization (if needed), run the operations</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="o">...</span><span class="p">,</span> <span class="n">feed_dict</span> <span class="o">=</span> <span class="p">{</span><span class="o">...</span><span class="p">})</span>
<span class="n">sess</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> <span class="c1"># Close the session</span>
</pre></div>
<p><strong>Method 2:</strong></p>
<div class="highlight"><pre><span></span><span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span> 
    <span class="c1"># run the variables initialization (if needed), run the operations</span>
    <span class="n">result</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="o">...</span><span class="p">,</span> <span class="n">feed_dict</span> <span class="o">=</span> <span class="p">{</span><span class="o">...</span><span class="p">})</span>
    <span class="c1"># This takes care of closing the session for you :)</span>
</pre></div>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[10]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># GRADED FUNCTION: sigmoid</span>

<span class="k">def</span> <span class="nf">sigmoid</span><span class="p">(</span><span class="n">z</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Computes the sigmoid of z</span>
<span class="sd">    </span>
<span class="sd">    Arguments:</span>
<span class="sd">    z -- input value, scalar or vector</span>
<span class="sd">    </span>
<span class="sd">    Returns: </span>
<span class="sd">    results -- the sigmoid of z</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1">### START CODE HERE ### ( approx. 4 lines of code)</span>
    <span class="c1"># Create a placeholder for x. Name it &#39;x&#39;.</span>
    <span class="n">x</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;x&quot;</span><span class="p">)</span>

    <span class="c1"># compute sigmoid(x)</span>
    <span class="n">sigmoid</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">sigmoid</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>

    <span class="c1"># Create a session, and run it. Please use the method 2 explained above. </span>
    <span class="c1"># You should use a feed_dict to pass z&#39;s value to x. </span>
    <span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
        <span class="c1"># Run session and call the output &quot;result&quot;</span>
        <span class="n">result</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">sigmoid</span><span class="p">,</span> <span class="n">feed_dict</span> <span class="o">=</span> <span class="p">{</span><span class="n">x</span><span class="p">:</span> <span class="n">z</span><span class="p">})</span>
    
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="k">return</span> <span class="n">result</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[11]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;sigmoid(0) = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">sigmoid</span><span class="p">(</span><span class="mi">0</span><span class="p">)))</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;sigmoid(12) = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">sigmoid</span><span class="p">(</span><span class="mi">12</span><span class="p">)))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>sigmoid(0) = 0.5
sigmoid(12) = 0.999994
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong><em> Expected Output </em></strong>:</p>
<table> 
<tr> 
<td>
**sigmoid(0)**
</td>
<td>
0.5
</td>
</tr>
<tr> 
<td>
**sigmoid(12)**
</td>
<td>
0.999994
</td>
</tr> 

</table>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><font color='blue'>
<strong>To summarize, you how know how to</strong>:</p>
<ol>
<li>Create placeholders</li>
<li>Specify the computation graph corresponding to operations you want to compute</li>
<li>Create the session</li>
<li>Run the session, using a feed dictionary if necessary to specify placeholder variables' values. </li>
</ol>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="1.3----Computing-the-Cost">1.3 -  Computing the Cost<a class="anchor-link" href="#1.3----Computing-the-Cost">&#182;</a></h3><p>You can also use a built-in function to compute the cost of your neural network. So instead of needing to write code to compute this as a function of $a^{[2](i)}$ and $y^{(i)}$ for i=1...m: 
$$ J = - \frac{1}{m}  \sum_{i = 1}^m  \large ( \small y^{(i)} \log a^{ [2] (i)} + (1-y^{(i)})\log (1-a^{ [2] (i)} )\large )\small\tag{2}$$</p>
<p>you can do it in one line of code in tensorflow!</p>
<p><strong>Exercise</strong>: Implement the cross entropy loss. The function you will use is:</p>
<ul>
<li><code>tf.nn.sigmoid_cross_entropy_with_logits(logits = ...,  labels = ...)</code></li>
</ul>
<p>Your code should input <code>z</code>, compute the sigmoid (to get <code>a</code>) and then compute the cross entropy cost $J$. All this can be done using one call to <code>tf.nn.sigmoid_cross_entropy_with_logits</code>, which computes</p>
$$- \frac{1}{m}  \sum_{i = 1}^m  \large ( \small y^{(i)} \log \sigma(z^{[2](i)}) + (1-y^{(i)})\log (1-\sigma(z^{[2](i)})\large )\small\tag{2}$$
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[16]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># GRADED FUNCTION: cost</span>

<span class="k">def</span> <span class="nf">cost</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="n">labels</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Computes the cost using the sigmoid cross entropy</span>
<span class="sd">    </span>
<span class="sd">    Arguments:</span>
<span class="sd">    logits -- vector containing z, output of the last linear unit (before the final sigmoid activation)</span>
<span class="sd">    labels -- vector of labels y (1 or 0) </span>
<span class="sd">    </span>
<span class="sd">    Note: What we&#39;ve been calling &quot;z&quot; and &quot;y&quot; in this class are respectively called &quot;logits&quot; and &quot;labels&quot; </span>
<span class="sd">    in the TensorFlow documentation. So logits will feed into z, and labels into y. </span>
<span class="sd">    </span>
<span class="sd">    Returns:</span>
<span class="sd">    cost -- runs the session of the cost (formula (2))</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1">### START CODE HERE ### </span>
    
    <span class="c1"># Create the placeholders for &quot;logits&quot; (z) and &quot;labels&quot; (y) (approx. 2 lines)</span>
    <span class="n">z</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="s1">&#39;z&#39;</span><span class="p">)</span>
    <span class="n">y</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="s1">&#39;y&#39;</span><span class="p">)</span>
    
    <span class="c1"># Use the loss function (approx. 1 line)</span>
    <span class="n">cost</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">sigmoid_cross_entropy_with_logits</span><span class="p">(</span><span class="n">logits</span> <span class="o">=</span> <span class="n">z</span><span class="p">,</span>  <span class="n">labels</span> <span class="o">=</span> <span class="n">y</span><span class="p">)</span>
    
    <span class="c1"># Create a session (approx. 1 line). See method 1 above.</span>
    <span class="n">sess</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span>
    
    <span class="c1"># Run the session (approx. 1 line).</span>
    <span class="n">cost</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">cost</span><span class="p">,</span> <span class="n">feed_dict</span> <span class="o">=</span> <span class="p">{</span><span class="n">z</span><span class="p">:</span> <span class="n">logits</span><span class="p">,</span><span class="n">y</span><span class="p">:</span> <span class="n">labels</span><span class="p">})</span>
    
    <span class="c1"># Close the session (approx. 1 line). See method 1 above.</span>
    <span class="n">sess</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
    
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="k">return</span> <span class="n">cost</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[17]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">logits</span> <span class="o">=</span> <span class="n">sigmoid</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mf">0.2</span><span class="p">,</span><span class="mf">0.4</span><span class="p">,</span><span class="mf">0.7</span><span class="p">,</span><span class="mf">0.9</span><span class="p">]))</span>
<span class="n">cost</span> <span class="o">=</span> <span class="n">cost</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">]))</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;cost = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">cost</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>cost = [ 1.00538719  1.03664088  0.41385433  0.39956614]
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong> Expected Output</strong> :</p>
<table> 
    <tr> 
        <td>
            **cost**
        </td>
        <td>
        [ 1.00538719  1.03664088  0.41385433  0.39956614]
        </td>
    </tr>

</table>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="1.4---Using-One-Hot-encodings">1.4 - Using One Hot encodings<a class="anchor-link" href="#1.4---Using-One-Hot-encodings">&#182;</a></h3><p>Many times in deep learning you will have a y vector with numbers ranging from 0 to C-1, where C is the number of classes. If C is for example 4, then you might have the following y vector which you will need to convert as follows:</p>
<p><img src="images/onehot.png" style="width:600px;height:150px;"></p>
<p>This is called a "one hot" encoding, because in the converted representation exactly one element of each column is "hot" (meaning set to 1). To do this conversion in numpy, you might have to write a few lines of code. In tensorflow, you can use one line of code:</p>
<ul>
<li>tf.one_hot(labels, depth, axis) </li>
</ul>
<p><strong>Exercise:</strong> Implement the function below to take one vector of labels and the total number of classes $C$, and return the one hot encoding. Use <code>tf.one_hot()</code> to do this.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[22]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># GRADED FUNCTION: one_hot_matrix</span>

<span class="k">def</span> <span class="nf">one_hot_matrix</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">C</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Creates a matrix where the i-th row corresponds to the ith class number and the jth column</span>
<span class="sd">                     corresponds to the jth training example. So if example j had a label i. Then entry (i,j) </span>
<span class="sd">                     will be 1. </span>
<span class="sd">                     </span>
<span class="sd">    Arguments:</span>
<span class="sd">    labels -- vector containing the labels </span>
<span class="sd">    C -- number of classes, the depth of the one hot dimension</span>
<span class="sd">    </span>
<span class="sd">    Returns: </span>
<span class="sd">    one_hot -- one hot matrix</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1">### START CODE HERE ###</span>
    
    <span class="c1"># Create a tf.constant equal to C (depth), name it &#39;C&#39;. (approx. 1 line)</span>
    <span class="n">C</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">(</span><span class="n">C</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;C&#39;</span><span class="p">)</span>
    
    <span class="c1"># Use tf.one_hot, be careful with the axis (approx. 1 line)</span>
    <span class="n">one_hot_matrix</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">one_hot</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">axis</span> <span class="o">=</span> <span class="mi">0</span><span class="p">)</span>
    
    <span class="c1"># Create the session (approx. 1 line)</span>
    <span class="n">sess</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span>
    
    <span class="c1"># Run the session (approx. 1 line)</span>
    <span class="n">one_hot</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">one_hot_matrix</span><span class="p">)</span>
    
    <span class="c1"># Close the session (approx. 1 line). See method 1 above.</span>
    <span class="n">sess</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
    
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="k">return</span> <span class="n">one_hot</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[23]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">labels</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span>
<span class="n">one_hot</span> <span class="o">=</span> <span class="n">one_hot_matrix</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">C</span> <span class="o">=</span> <span class="mi">4</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;one_hot = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">one_hot</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>one_hot = [[ 0.  0.  0.  1.  0.  0.]
 [ 1.  0.  0.  0.  0.  1.]
 [ 0.  1.  0.  0.  1.  0.]
 [ 0.  0.  1.  0.  0.  0.]]
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Expected Output</strong>:</p>
<table> 
    <tr> 
        <td>
            **one_hot**
        </td>
        <td>
        [[ 0.  0.  0.  1.  0.  0.]
 [ 1.  0.  0.  0.  0.  1.]
 [ 0.  1.  0.  0.  1.  0.]
 [ 0.  0.  1.  0.  0.  0.]]
        </td>
    </tr>

</table>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="1.5---Initialize-with-zeros-and-ones">1.5 - Initialize with zeros and ones<a class="anchor-link" href="#1.5---Initialize-with-zeros-and-ones">&#182;</a></h3><p>Now you will learn how to initialize a vector of zeros and ones. The function you will be calling is <code>tf.ones()</code>. To initialize with zeros you could use tf.zeros() instead. These functions take in a shape and return an array of dimension shape full of zeros and ones respectively.</p>
<p><strong>Exercise:</strong> Implement the function below to take in a shape and to return an array (of the shape's dimension of ones).</p>
<ul>
<li>tf.ones(shape)</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[24]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># GRADED FUNCTION: ones</span>

<span class="k">def</span> <span class="nf">ones</span><span class="p">(</span><span class="n">shape</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Creates an array of ones of dimension shape</span>
<span class="sd">    </span>
<span class="sd">    Arguments:</span>
<span class="sd">    shape -- shape of the array you want to create</span>
<span class="sd">        </span>
<span class="sd">    Returns: </span>
<span class="sd">    ones -- array containing only ones</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1">### START CODE HERE ###</span>
    
    <span class="c1"># Create &quot;ones&quot; tensor using tf.ones(...). (approx. 1 line)</span>
    <span class="n">ones</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span>
    
    <span class="c1"># Create the session (approx. 1 line)</span>
    <span class="n">sess</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span>
    
    <span class="c1"># Run the session to compute &#39;ones&#39; (approx. 1 line)</span>
    <span class="n">ones</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">ones</span><span class="p">)</span>
    
    <span class="c1"># Close the session (approx. 1 line). See method 1 above.</span>
    <span class="n">sess</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
    
    <span class="c1">### END CODE HERE ###</span>
    <span class="k">return</span> <span class="n">ones</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[25]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;ones = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">ones</span><span class="p">([</span><span class="mi">3</span><span class="p">])))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>ones = [ 1.  1.  1.]
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Expected Output:</strong></p>
<table> 
    <tr> 
        <td>
            **ones**
        </td>
        <td>
        [ 1.  1.  1.]
        </td>
    </tr>

</table>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="2---Building-your-first-neural-network-in-tensorflow">2 - Building your first neural network in tensorflow<a class="anchor-link" href="#2---Building-your-first-neural-network-in-tensorflow">&#182;</a></h1><p>In this part of the assignment you will build a neural network using tensorflow. Remember that there are two parts to implement a tensorflow model:</p>
<ul>
<li>Create the computation graph</li>
<li>Run the graph</li>
</ul>
<p>Let's delve into the problem you'd like to solve!</p>
<h3 id="2.0---Problem-statement:-SIGNS-Dataset">2.0 - Problem statement: SIGNS Dataset<a class="anchor-link" href="#2.0---Problem-statement:-SIGNS-Dataset">&#182;</a></h3><p>One afternoon, with some friends we decided to teach our computers to decipher sign language. We spent a few hours taking pictures in front of a white wall and came up with the following dataset. It's now your job to build an algorithm that would facilitate communications from a speech-impaired person to someone who doesn't understand sign language.</p>
<ul>
<li><strong>Training set</strong>: 1080 pictures (64 by 64 pixels) of signs representing numbers from 0 to 5 (180 pictures per number).</li>
<li><strong>Test set</strong>: 120 pictures (64 by 64 pixels) of signs representing numbers from 0 to 5 (20 pictures per number).</li>
</ul>
<p>Note that this is a subset of the SIGNS dataset. The complete dataset contains many more signs.</p>
<p>Here are examples for each number, and how an explanation of how we represent the labels. These are the original pictures, before we lowered the image resolutoion to 64 by 64 pixels.
<img src="images/hands.png" style="width:800px;height:350px;"><caption><center> <u><font color='purple'> **Figure 1**</u><font color='purple'>: SIGNS dataset <br> <font color='black'> </center></p>
<p>Run the following code to load the dataset.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[26]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Loading the dataset</span>
<span class="n">X_train_orig</span><span class="p">,</span> <span class="n">Y_train_orig</span><span class="p">,</span> <span class="n">X_test_orig</span><span class="p">,</span> <span class="n">Y_test_orig</span><span class="p">,</span> <span class="n">classes</span> <span class="o">=</span> <span class="n">load_dataset</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Change the index below and run the cell to visualize some examples in the dataset.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[28]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Example of a picture</span>
<span class="n">index</span> <span class="o">=</span> <span class="mi">20</span>
<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">X_train_orig</span><span class="p">[</span><span class="n">index</span><span class="p">])</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;y = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">Y_train_orig</span><span class="p">[:,</span> <span class="n">index</span><span class="p">])))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>y = 0
</pre>
</div>
</div>

<div class="output_area"><div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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==
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>As usual you flatten the image dataset, then normalize it by dividing by 255. On top of that, you will convert each label to a one-hot vector as shown in Figure 1. Run the cell below to do so.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[29]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Flatten the training and test images</span>
<span class="n">X_train_flatten</span> <span class="o">=</span> <span class="n">X_train_orig</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">X_train_orig</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">T</span>
<span class="n">X_test_flatten</span> <span class="o">=</span> <span class="n">X_test_orig</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">X_test_orig</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">T</span>
<span class="c1"># Normalize image vectors</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">X_train_flatten</span><span class="o">/</span><span class="mf">255.</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">X_test_flatten</span><span class="o">/</span><span class="mf">255.</span>
<span class="c1"># Convert training and test labels to one hot matrices</span>
<span class="n">Y_train</span> <span class="o">=</span> <span class="n">convert_to_one_hot</span><span class="p">(</span><span class="n">Y_train_orig</span><span class="p">,</span> <span class="mi">6</span><span class="p">)</span>
<span class="n">Y_test</span> <span class="o">=</span> <span class="n">convert_to_one_hot</span><span class="p">(</span><span class="n">Y_test_orig</span><span class="p">,</span> <span class="mi">6</span><span class="p">)</span>

<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;number of training examples = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">X_train</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]))</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;number of test examples = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">X_test</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]))</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;X_train shape: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">X_train</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Y_train shape: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">Y_train</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;X_test shape: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">X_test</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Y_test shape: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">Y_test</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>number of training examples = 1080
number of test examples = 120
X_train shape: (12288, 1080)
Y_train shape: (6, 1080)
X_test shape: (12288, 120)
Y_test shape: (6, 120)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Note</strong> that 12288 comes from $64 \times 64 \times 3$. Each image is square, 64 by 64 pixels, and 3 is for the RGB colors. Please make sure all these shapes make sense to you before continuing.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Your goal</strong> is to build an algorithm capable of recognizing a sign with high accuracy. To do so, you are going to build a tensorflow model that is almost the same as one you have previously built in numpy for cat recognition (but now using a softmax output). It is a great occasion to compare your numpy implementation to the tensorflow one.</p>
<p><strong>The model</strong> is <em>LINEAR -&gt; RELU -&gt; LINEAR -&gt; RELU -&gt; LINEAR -&gt; SOFTMAX</em>. The SIGMOID output layer has been converted to a SOFTMAX. A SOFTMAX layer generalizes SIGMOID to when there are more than two classes.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="2.1---Create-placeholders">2.1 - Create placeholders<a class="anchor-link" href="#2.1---Create-placeholders">&#182;</a></h3><p>Your first task is to create placeholders for <code>X</code> and <code>Y</code>. This will allow you to later pass your training data in when you run your session.</p>
<p><strong>Exercise:</strong> Implement the function below to create the placeholders in tensorflow.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[32]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># GRADED FUNCTION: create_placeholders</span>

<span class="k">def</span> <span class="nf">create_placeholders</span><span class="p">(</span><span class="n">n_x</span><span class="p">,</span> <span class="n">n_y</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Creates the placeholders for the tensorflow session.</span>
<span class="sd">    </span>
<span class="sd">    Arguments:</span>
<span class="sd">    n_x -- scalar, size of an image vector (num_px * num_px = 64 * 64 * 3 = 12288)</span>
<span class="sd">    n_y -- scalar, number of classes (from 0 to 5, so -&gt; 6)</span>
<span class="sd">    </span>
<span class="sd">    Returns:</span>
<span class="sd">    X -- placeholder for the data input, of shape [n_x, None] and dtype &quot;float&quot;</span>
<span class="sd">    Y -- placeholder for the input labels, of shape [n_y, None] and dtype &quot;float&quot;</span>
<span class="sd">    </span>
<span class="sd">    Tips:</span>
<span class="sd">    - You will use None because it let&#39;s us be flexible on the number of examples you will for the placeholders.</span>
<span class="sd">      In fact, the number of examples during test/train is different.</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="c1">### START CODE HERE ### (approx. 2 lines)</span>
    <span class="n">X</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="n">n_x</span><span class="p">,</span> <span class="kc">None</span><span class="p">))</span>
    <span class="n">Y</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="n">n_y</span><span class="p">,</span> <span class="kc">None</span><span class="p">))</span>
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="k">return</span> <span class="n">X</span><span class="p">,</span> <span class="n">Y</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[33]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X</span><span class="p">,</span> <span class="n">Y</span> <span class="o">=</span> <span class="n">create_placeholders</span><span class="p">(</span><span class="mi">12288</span><span class="p">,</span> <span class="mi">6</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;X = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">X</span><span class="p">))</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Y = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">Y</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>X = Tensor(&#34;Placeholder:0&#34;, shape=(12288, ?), dtype=float32)
Y = Tensor(&#34;Placeholder_1:0&#34;, shape=(6, ?), dtype=float32)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Expected Output</strong>:</p>
<table> 
    <tr> 
        <td>
            **X**
        </td>
        <td>
        Tensor("Placeholder_1:0", shape=(12288, ?), dtype=float32) (not necessarily Placeholder_1)
        </td>
    </tr>
    <tr> 
        <td>
            **Y**
        </td>
        <td>
        Tensor("Placeholder_2:0", shape=(10, ?), dtype=float32) (not necessarily Placeholder_2)
        </td>
    </tr>

</table>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="2.2---Initializing-the-parameters">2.2 - Initializing the parameters<a class="anchor-link" href="#2.2---Initializing-the-parameters">&#182;</a></h3><p>Your second task is to initialize the parameters in tensorflow.</p>
<p><strong>Exercise:</strong> Implement the function below to initialize the parameters in tensorflow. You are going use Xavier Initialization for weights and Zero Initialization for biases. The shapes are given below. As an example, to help you, for W1 and b1 you could use:</p>
<div class="highlight"><pre><span></span><span class="n">W1</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">get_variable</span><span class="p">(</span><span class="s2">&quot;W1&quot;</span><span class="p">,</span> <span class="p">[</span><span class="mi">25</span><span class="p">,</span><span class="mi">12288</span><span class="p">],</span> <span class="n">initializer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">xavier_initializer</span><span class="p">(</span><span class="n">seed</span> <span class="o">=</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">b1</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">get_variable</span><span class="p">(</span><span class="s2">&quot;b1&quot;</span><span class="p">,</span> <span class="p">[</span><span class="mi">25</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">initializer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">zeros_initializer</span><span class="p">())</span>
</pre></div>
<p>Please use <code>seed = 1</code> to make sure your results match ours.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[36]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># GRADED FUNCTION: initialize_parameters</span>

<span class="k">def</span> <span class="nf">initialize_parameters</span><span class="p">():</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Initializes parameters to build a neural network with tensorflow. The shapes are:</span>
<span class="sd">                        W1 : [25, 12288]</span>
<span class="sd">                        b1 : [25, 1]</span>
<span class="sd">                        W2 : [12, 25]</span>
<span class="sd">                        b2 : [12, 1]</span>
<span class="sd">                        W3 : [6, 12]</span>
<span class="sd">                        b3 : [6, 1]</span>
<span class="sd">    </span>
<span class="sd">    Returns:</span>
<span class="sd">    parameters -- a dictionary of tensors containing W1, b1, W2, b2, W3, b3</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="n">tf</span><span class="o">.</span><span class="n">set_random_seed</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>                   <span class="c1"># so that your &quot;random&quot; numbers match ours</span>
        
    <span class="c1">### START CODE HERE ### (approx. 6 lines of code)</span>
    <span class="n">W1</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">get_variable</span><span class="p">(</span><span class="s2">&quot;W1&quot;</span><span class="p">,</span> <span class="p">[</span><span class="mi">25</span><span class="p">,</span><span class="mi">12288</span><span class="p">],</span> <span class="n">initializer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">xavier_initializer</span><span class="p">(</span><span class="n">seed</span> <span class="o">=</span> <span class="mi">1</span><span class="p">))</span>
    <span class="n">b1</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">get_variable</span><span class="p">(</span><span class="s2">&quot;b1&quot;</span><span class="p">,</span> <span class="p">[</span><span class="mi">25</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">initializer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">zeros_initializer</span><span class="p">())</span>
    <span class="n">W2</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">get_variable</span><span class="p">(</span><span class="s2">&quot;W2&quot;</span><span class="p">,</span> <span class="p">[</span><span class="mi">12</span><span class="p">,</span><span class="mi">25</span><span class="p">],</span> <span class="n">initializer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">xavier_initializer</span><span class="p">(</span><span class="n">seed</span> <span class="o">=</span> <span class="mi">1</span><span class="p">))</span>
    <span class="n">b2</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">get_variable</span><span class="p">(</span><span class="s2">&quot;b2&quot;</span><span class="p">,</span> <span class="p">[</span><span class="mi">12</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">initializer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">zeros_initializer</span><span class="p">())</span>
    <span class="n">W3</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">get_variable</span><span class="p">(</span><span class="s2">&quot;W3&quot;</span><span class="p">,</span> <span class="p">[</span><span class="mi">6</span><span class="p">,</span><span class="mi">12</span><span class="p">],</span> <span class="n">initializer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">xavier_initializer</span><span class="p">(</span><span class="n">seed</span> <span class="o">=</span> <span class="mi">1</span><span class="p">))</span>
    <span class="n">b3</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">get_variable</span><span class="p">(</span><span class="s2">&quot;b3&quot;</span><span class="p">,</span> <span class="p">[</span><span class="mi">6</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span> <span class="n">initializer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">zeros_initializer</span><span class="p">())</span>
    <span class="c1">### END CODE HERE ###</span>

    <span class="n">parameters</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;W1&quot;</span><span class="p">:</span> <span class="n">W1</span><span class="p">,</span>
                  <span class="s2">&quot;b1&quot;</span><span class="p">:</span> <span class="n">b1</span><span class="p">,</span>
                  <span class="s2">&quot;W2&quot;</span><span class="p">:</span> <span class="n">W2</span><span class="p">,</span>
                  <span class="s2">&quot;b2&quot;</span><span class="p">:</span> <span class="n">b2</span><span class="p">,</span>
                  <span class="s2">&quot;W3&quot;</span><span class="p">:</span> <span class="n">W3</span><span class="p">,</span>
                  <span class="s2">&quot;b3&quot;</span><span class="p">:</span> <span class="n">b3</span><span class="p">}</span>
    
    <span class="k">return</span> <span class="n">parameters</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[37]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tf</span><span class="o">.</span><span class="n">reset_default_graph</span><span class="p">()</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
    <span class="n">parameters</span> <span class="o">=</span> <span class="n">initialize_parameters</span><span class="p">()</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;W1 = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="s2">&quot;W1&quot;</span><span class="p">]))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;b1 = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="s2">&quot;b1&quot;</span><span class="p">]))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;W2 = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="s2">&quot;W2&quot;</span><span class="p">]))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;b2 = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="s2">&quot;b2&quot;</span><span class="p">]))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>W1 = &lt;tf.Variable &#39;W1:0&#39; shape=(25, 12288) dtype=float32_ref&gt;
b1 = &lt;tf.Variable &#39;b1:0&#39; shape=(25, 1) dtype=float32_ref&gt;
W2 = &lt;tf.Variable &#39;W2:0&#39; shape=(12, 25) dtype=float32_ref&gt;
b2 = &lt;tf.Variable &#39;b2:0&#39; shape=(12, 1) dtype=float32_ref&gt;
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Expected Output</strong>:</p>
<table> 
    <tr> 
        <td>
            **W1**
        </td>
        <td>
         < tf.Variable 'W1:0' shape=(25, 12288) dtype=float32_ref >
        </td>
    </tr>
    <tr> 
        <td>
            **b1**
        </td>
        <td>
        < tf.Variable 'b1:0' shape=(25, 1) dtype=float32_ref >
        </td>
    </tr>
    <tr> 
        <td>
            **W2**
        </td>
        <td>
        < tf.Variable 'W2:0' shape=(12, 25) dtype=float32_ref >
        </td>
    </tr>
    <tr> 
        <td>
            **b2**
        </td>
        <td>
        < tf.Variable 'b2:0' shape=(12, 1) dtype=float32_ref >
        </td>
    </tr>

</table>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>As expected, the parameters haven't been evaluated yet.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="2.3---Forward-propagation-in-tensorflow">2.3 - Forward propagation in tensorflow<a class="anchor-link" href="#2.3---Forward-propagation-in-tensorflow">&#182;</a></h3><p>You will now implement the forward propagation module in tensorflow. The function will take in a dictionary of parameters and it will complete the forward pass. The functions you will be using are:</p>
<ul>
<li><code>tf.add(...,...)</code> to do an addition</li>
<li><code>tf.matmul(...,...)</code> to do a matrix multiplication</li>
<li><code>tf.nn.relu(...)</code> to apply the ReLU activation</li>
</ul>
<p><strong>Question:</strong> Implement the forward pass of the neural network. We commented for you the numpy equivalents so that you can compare the tensorflow implementation to numpy. It is important to note that the forward propagation stops at <code>z3</code>. The reason is that in tensorflow the last linear layer output is given as input to the function computing the loss. Therefore, you don't need <code>a3</code>!</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[38]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># GRADED FUNCTION: forward_propagation</span>

<span class="k">def</span> <span class="nf">forward_propagation</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Implements the forward propagation for the model: LINEAR -&gt; RELU -&gt; LINEAR -&gt; RELU -&gt; LINEAR -&gt; SOFTMAX</span>
<span class="sd">    </span>
<span class="sd">    Arguments:</span>
<span class="sd">    X -- input dataset placeholder, of shape (input size, number of examples)</span>
<span class="sd">    parameters -- python dictionary containing your parameters &quot;W1&quot;, &quot;b1&quot;, &quot;W2&quot;, &quot;b2&quot;, &quot;W3&quot;, &quot;b3&quot;</span>
<span class="sd">                  the shapes are given in initialize_parameters</span>

<span class="sd">    Returns:</span>
<span class="sd">    Z3 -- the output of the last LINEAR unit</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># Retrieve the parameters from the dictionary &quot;parameters&quot; </span>
    <span class="n">W1</span> <span class="o">=</span> <span class="n">parameters</span><span class="p">[</span><span class="s1">&#39;W1&#39;</span><span class="p">]</span>
    <span class="n">b1</span> <span class="o">=</span> <span class="n">parameters</span><span class="p">[</span><span class="s1">&#39;b1&#39;</span><span class="p">]</span>
    <span class="n">W2</span> <span class="o">=</span> <span class="n">parameters</span><span class="p">[</span><span class="s1">&#39;W2&#39;</span><span class="p">]</span>
    <span class="n">b2</span> <span class="o">=</span> <span class="n">parameters</span><span class="p">[</span><span class="s1">&#39;b2&#39;</span><span class="p">]</span>
    <span class="n">W3</span> <span class="o">=</span> <span class="n">parameters</span><span class="p">[</span><span class="s1">&#39;W3&#39;</span><span class="p">]</span>
    <span class="n">b3</span> <span class="o">=</span> <span class="n">parameters</span><span class="p">[</span><span class="s1">&#39;b3&#39;</span><span class="p">]</span>
    
    <span class="c1">### START CODE HERE ### (approx. 5 lines)              # Numpy Equivalents:</span>
    <span class="n">Z1</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">W1</span><span class="p">,</span> <span class="n">X</span><span class="p">),</span> <span class="n">b1</span><span class="p">)</span>                                               <span class="c1"># Z1 = np.dot(W1, X) + b1</span>
    <span class="n">A1</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="n">Z1</span><span class="p">)</span>                                                             <span class="c1"># A1 = relu(Z1)</span>
    <span class="n">Z2</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">W2</span><span class="p">,</span> <span class="n">A1</span><span class="p">),</span> <span class="n">b2</span><span class="p">)</span>                                              <span class="c1"># Z2 = np.dot(W2, a1) + b2</span>
    <span class="n">A2</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="n">Z2</span><span class="p">)</span>                                                             <span class="c1"># A2 = relu(Z2)</span>
    <span class="n">Z3</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">W3</span><span class="p">,</span> <span class="n">A2</span><span class="p">),</span> <span class="n">b3</span><span class="p">)</span>                                              <span class="c1"># Z3 = np.dot(W3,Z2) + b3</span>
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="k">return</span> <span class="n">Z3</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[39]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tf</span><span class="o">.</span><span class="n">reset_default_graph</span><span class="p">()</span>

<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
    <span class="n">X</span><span class="p">,</span> <span class="n">Y</span> <span class="o">=</span> <span class="n">create_placeholders</span><span class="p">(</span><span class="mi">12288</span><span class="p">,</span> <span class="mi">6</span><span class="p">)</span>
    <span class="n">parameters</span> <span class="o">=</span> <span class="n">initialize_parameters</span><span class="p">()</span>
    <span class="n">Z3</span> <span class="o">=</span> <span class="n">forward_propagation</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">parameters</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Z3 = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">Z3</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>Z3 = Tensor(&#34;Add_2:0&#34;, shape=(6, ?), dtype=float32)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Expected Output</strong>:</p>
<table> 
    <tr> 
        <td>
            **Z3**
        </td>
        <td>
        Tensor("Add_2:0", shape=(6, ?), dtype=float32)
        </td>
    </tr>

</table>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>You may have noticed that the forward propagation doesn't output any cache. You will understand why below, when we get to brackpropagation.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="2.4-Compute-cost">2.4 Compute cost<a class="anchor-link" href="#2.4-Compute-cost">&#182;</a></h3><p>As seen before, it is very easy to compute the cost using:</p>
<div class="highlight"><pre><span></span><span class="n">tf</span><span class="o">.</span><span class="n">reduce_mean</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">softmax_cross_entropy_with_logits</span><span class="p">(</span><span class="n">logits</span> <span class="o">=</span> <span class="o">...</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="o">...</span><span class="p">))</span>
</pre></div>
<p><strong>Question</strong>: Implement the cost function below.</p>
<ul>
<li>It is important to know that the "<code>logits</code>" and "<code>labels</code>" inputs of <code>tf.nn.softmax_cross_entropy_with_logits</code> are expected to be of shape (number of examples, num_classes). We have thus transposed Z3 and Y for you.</li>
<li>Besides, <code>tf.reduce_mean</code> basically does the summation over the examples.</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[42]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># GRADED FUNCTION: compute_cost </span>

<span class="k">def</span> <span class="nf">compute_cost</span><span class="p">(</span><span class="n">Z3</span><span class="p">,</span> <span class="n">Y</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Computes the cost</span>
<span class="sd">    </span>
<span class="sd">    Arguments:</span>
<span class="sd">    Z3 -- output of forward propagation (output of the last LINEAR unit), of shape (6, number of examples)</span>
<span class="sd">    Y -- &quot;true&quot; labels vector placeholder, same shape as Z3</span>
<span class="sd">    </span>
<span class="sd">    Returns:</span>
<span class="sd">    cost - Tensor of the cost function</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># to fit the tensorflow requirement for tf.nn.softmax_cross_entropy_with_logits(...,...)</span>
    <span class="n">logits</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">Z3</span><span class="p">)</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">Y</span><span class="p">)</span>
    
    <span class="c1">### START CODE HERE ### (1 line of code)</span>
    <span class="n">cost</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">reduce_mean</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">softmax_cross_entropy_with_logits</span><span class="p">(</span><span class="n">logits</span> <span class="o">=</span> <span class="n">logits</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="p">))</span>
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="k">return</span> <span class="n">cost</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[43]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tf</span><span class="o">.</span><span class="n">reset_default_graph</span><span class="p">()</span>

<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
    <span class="n">X</span><span class="p">,</span> <span class="n">Y</span> <span class="o">=</span> <span class="n">create_placeholders</span><span class="p">(</span><span class="mi">12288</span><span class="p">,</span> <span class="mi">6</span><span class="p">)</span>
    <span class="n">parameters</span> <span class="o">=</span> <span class="n">initialize_parameters</span><span class="p">()</span>
    <span class="n">Z3</span> <span class="o">=</span> <span class="n">forward_propagation</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">parameters</span><span class="p">)</span>
    <span class="n">cost</span> <span class="o">=</span> <span class="n">compute_cost</span><span class="p">(</span><span class="n">Z3</span><span class="p">,</span> <span class="n">Y</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;cost = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">cost</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>cost = Tensor(&#34;Mean:0&#34;, shape=(), dtype=float32)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Expected Output</strong>:</p>
<table> 
    <tr> 
        <td>
            **cost**
        </td>
        <td>
        Tensor("Mean:0", shape=(), dtype=float32)
        </td>
    </tr>

</table>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="2.5---Backward-propagation-&amp;-parameter-updates">2.5 - Backward propagation &amp; parameter updates<a class="anchor-link" href="#2.5---Backward-propagation-&amp;-parameter-updates">&#182;</a></h3><p>This is where you become grateful to programming frameworks. All the backpropagation and the parameters update is taken care of in 1 line of code. It is very easy to incorporate this line in the model.</p>
<p>After you compute the cost function. You will create an "<code>optimizer</code>" object. You have to call this object along with the cost when running the tf.session. When called, it will perform an optimization on the given cost with the chosen method and learning rate.</p>
<p>For instance, for gradient descent the optimizer would be:</p>
<div class="highlight"><pre><span></span><span class="n">optimizer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">GradientDescentOptimizer</span><span class="p">(</span><span class="n">learning_rate</span> <span class="o">=</span> <span class="n">learning_rate</span><span class="p">)</span><span class="o">.</span><span class="n">minimize</span><span class="p">(</span><span class="n">cost</span><span class="p">)</span>
</pre></div>
<p>To make the optimization you would do:</p>
<div class="highlight"><pre><span></span><span class="n">_</span> <span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">([</span><span class="n">optimizer</span><span class="p">,</span> <span class="n">cost</span><span class="p">],</span> <span class="n">feed_dict</span><span class="o">=</span><span class="p">{</span><span class="n">X</span><span class="p">:</span> <span class="n">minibatch_X</span><span class="p">,</span> <span class="n">Y</span><span class="p">:</span> <span class="n">minibatch_Y</span><span class="p">})</span>
</pre></div>
<p>This computes the backpropagation by passing through the tensorflow graph in the reverse order. From cost to inputs.</p>
<p><strong>Note</strong> When coding, we often use <code>_</code> as a "throwaway" variable to store values that we won't need to use later. Here, <code>_</code> takes on the evaluated value of <code>optimizer</code>, which we don't need (and <code>c</code> takes the value of the <code>cost</code> variable).</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="2.6---Building-the-model">2.6 - Building the model<a class="anchor-link" href="#2.6---Building-the-model">&#182;</a></h3><p>Now, you will bring it all together!</p>
<p><strong>Exercise:</strong> Implement the model. You will be calling the functions you had previously implemented.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[44]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">model</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">Y_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">Y_test</span><span class="p">,</span> <span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">0.0001</span><span class="p">,</span>
          <span class="n">num_epochs</span> <span class="o">=</span> <span class="mi">1500</span><span class="p">,</span> <span class="n">minibatch_size</span> <span class="o">=</span> <span class="mi">32</span><span class="p">,</span> <span class="n">print_cost</span> <span class="o">=</span> <span class="kc">True</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Implements a three-layer tensorflow neural network: LINEAR-&gt;RELU-&gt;LINEAR-&gt;RELU-&gt;LINEAR-&gt;SOFTMAX.</span>
<span class="sd">    </span>
<span class="sd">    Arguments:</span>
<span class="sd">    X_train -- training set, of shape (input size = 12288, number of training examples = 1080)</span>
<span class="sd">    Y_train -- test set, of shape (output size = 6, number of training examples = 1080)</span>
<span class="sd">    X_test -- training set, of shape (input size = 12288, number of training examples = 120)</span>
<span class="sd">    Y_test -- test set, of shape (output size = 6, number of test examples = 120)</span>
<span class="sd">    learning_rate -- learning rate of the optimization</span>
<span class="sd">    num_epochs -- number of epochs of the optimization loop</span>
<span class="sd">    minibatch_size -- size of a minibatch</span>
<span class="sd">    print_cost -- True to print the cost every 100 epochs</span>
<span class="sd">    </span>
<span class="sd">    Returns:</span>
<span class="sd">    parameters -- parameters learnt by the model. They can then be used to predict.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="n">ops</span><span class="o">.</span><span class="n">reset_default_graph</span><span class="p">()</span>                         <span class="c1"># to be able to rerun the model without overwriting tf variables</span>
    <span class="n">tf</span><span class="o">.</span><span class="n">set_random_seed</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>                             <span class="c1"># to keep consistent results</span>
    <span class="n">seed</span> <span class="o">=</span> <span class="mi">3</span>                                          <span class="c1"># to keep consistent results</span>
    <span class="p">(</span><span class="n">n_x</span><span class="p">,</span> <span class="n">m</span><span class="p">)</span> <span class="o">=</span> <span class="n">X_train</span><span class="o">.</span><span class="n">shape</span>                          <span class="c1"># (n_x: input size, m : number of examples in the train set)</span>
    <span class="n">n_y</span> <span class="o">=</span> <span class="n">Y_train</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>                            <span class="c1"># n_y : output size</span>
    <span class="n">costs</span> <span class="o">=</span> <span class="p">[]</span>                                        <span class="c1"># To keep track of the cost</span>
    
    <span class="c1"># Create Placeholders of shape (n_x, n_y)</span>
    <span class="c1">### START CODE HERE ### (1 line)</span>
    <span class="n">X</span><span class="p">,</span> <span class="n">Y</span> <span class="o">=</span> <span class="n">create_placeholders</span><span class="p">(</span><span class="n">n_x</span><span class="p">,</span> <span class="n">n_y</span><span class="p">)</span>
    <span class="c1">### END CODE HERE ###</span>

    <span class="c1"># Initialize parameters</span>
    <span class="c1">### START CODE HERE ### (1 line)</span>
    <span class="n">parameters</span> <span class="o">=</span> <span class="n">initialize_parameters</span><span class="p">()</span>
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="c1"># Forward propagation: Build the forward propagation in the tensorflow graph</span>
    <span class="c1">### START CODE HERE ### (1 line)</span>
    <span class="n">Z3</span> <span class="o">=</span> <span class="n">forward_propagation</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">parameters</span><span class="p">)</span>
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="c1"># Cost function: Add cost function to tensorflow graph</span>
    <span class="c1">### START CODE HERE ### (1 line)</span>
    <span class="n">cost</span> <span class="o">=</span> <span class="n">compute_cost</span><span class="p">(</span><span class="n">Z3</span><span class="p">,</span> <span class="n">Y</span><span class="p">)</span>
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="c1"># Backpropagation: Define the tensorflow optimizer. Use an AdamOptimizer.</span>
    <span class="c1">### START CODE HERE ### (1 line)</span>
    <span class="n">optimizer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">AdamOptimizer</span><span class="p">(</span><span class="n">learning_rate</span> <span class="o">=</span> <span class="n">learning_rate</span><span class="p">)</span><span class="o">.</span><span class="n">minimize</span><span class="p">(</span><span class="n">cost</span><span class="p">)</span>
    <span class="c1">### END CODE HERE ###</span>
    
    <span class="c1"># Initialize all the variables</span>
    <span class="n">init</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">global_variables_initializer</span><span class="p">()</span>

    <span class="c1"># Start the session to compute the tensorflow graph</span>
    <span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
        
        <span class="c1"># Run the initialization</span>
        <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">init</span><span class="p">)</span>
        
        <span class="c1"># Do the training loop</span>
        <span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_epochs</span><span class="p">):</span>

            <span class="n">epoch_cost</span> <span class="o">=</span> <span class="mf">0.</span>                       <span class="c1"># Defines a cost related to an epoch</span>
            <span class="n">num_minibatches</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">m</span> <span class="o">/</span> <span class="n">minibatch_size</span><span class="p">)</span> <span class="c1"># number of minibatches of size minibatch_size in the train set</span>
            <span class="n">seed</span> <span class="o">=</span> <span class="n">seed</span> <span class="o">+</span> <span class="mi">1</span>
            <span class="n">minibatches</span> <span class="o">=</span> <span class="n">random_mini_batches</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">Y_train</span><span class="p">,</span> <span class="n">minibatch_size</span><span class="p">,</span> <span class="n">seed</span><span class="p">)</span>

            <span class="k">for</span> <span class="n">minibatch</span> <span class="ow">in</span> <span class="n">minibatches</span><span class="p">:</span>

                <span class="c1"># Select a minibatch</span>
                <span class="p">(</span><span class="n">minibatch_X</span><span class="p">,</span> <span class="n">minibatch_Y</span><span class="p">)</span> <span class="o">=</span> <span class="n">minibatch</span>
                
                <span class="c1"># IMPORTANT: The line that runs the graph on a minibatch.</span>
                <span class="c1"># Run the session to execute the &quot;optimizer&quot; and the &quot;cost&quot;, the feedict should contain a minibatch for (X,Y).</span>
                <span class="c1">### START CODE HERE ### (1 line)</span>
                <span class="n">_</span> <span class="p">,</span> <span class="n">minibatch_cost</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">([</span><span class="n">optimizer</span><span class="p">,</span> <span class="n">cost</span><span class="p">],</span> <span class="n">feed_dict</span><span class="o">=</span><span class="p">{</span><span class="n">X</span><span class="p">:</span> <span class="n">minibatch_X</span><span class="p">,</span> <span class="n">Y</span><span class="p">:</span> <span class="n">minibatch_Y</span><span class="p">})</span>
                <span class="c1">### END CODE HERE ###</span>
                
                <span class="n">epoch_cost</span> <span class="o">+=</span> <span class="n">minibatch_cost</span> <span class="o">/</span> <span class="n">num_minibatches</span>

            <span class="c1"># Print the cost every epoch</span>
            <span class="k">if</span> <span class="n">print_cost</span> <span class="o">==</span> <span class="kc">True</span> <span class="ow">and</span> <span class="n">epoch</span> <span class="o">%</span> <span class="mi">100</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Cost after epoch </span><span class="si">%i</span><span class="s2">: </span><span class="si">%f</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">epoch</span><span class="p">,</span> <span class="n">epoch_cost</span><span class="p">))</span>
            <span class="k">if</span> <span class="n">print_cost</span> <span class="o">==</span> <span class="kc">True</span> <span class="ow">and</span> <span class="n">epoch</span> <span class="o">%</span> <span class="mi">5</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">costs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">epoch_cost</span><span class="p">)</span>
                
        <span class="c1"># plot the cost</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">costs</span><span class="p">))</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;cost&#39;</span><span class="p">)</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;iterations (per tens)&#39;</span><span class="p">)</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Learning rate =&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">learning_rate</span><span class="p">))</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>

        <span class="c1"># lets save the parameters in a variable</span>
        <span class="n">parameters</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">parameters</span><span class="p">)</span>
        <span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Parameters have been trained!&quot;</span><span class="p">)</span>

        <span class="c1"># Calculate the correct predictions</span>
        <span class="n">correct_prediction</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">equal</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">Z3</span><span class="p">),</span> <span class="n">tf</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">Y</span><span class="p">))</span>

        <span class="c1"># Calculate accuracy on the test set</span>
        <span class="n">accuracy</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">reduce_mean</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="n">correct_prediction</span><span class="p">,</span> <span class="s2">&quot;float&quot;</span><span class="p">))</span>

        <span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Train Accuracy:&quot;</span><span class="p">,</span> <span class="n">accuracy</span><span class="o">.</span><span class="n">eval</span><span class="p">({</span><span class="n">X</span><span class="p">:</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">Y</span><span class="p">:</span> <span class="n">Y_train</span><span class="p">}))</span>
        <span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Test Accuracy:&quot;</span><span class="p">,</span> <span class="n">accuracy</span><span class="o">.</span><span class="n">eval</span><span class="p">({</span><span class="n">X</span><span class="p">:</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">Y</span><span class="p">:</span> <span class="n">Y_test</span><span class="p">}))</span>
        
        <span class="k">return</span> <span class="n">parameters</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Run the following cell to train your model! On our machine it takes about 5 minutes. Your "Cost after epoch 100" should be 1.016458. If it's not, don't waste time; interrupt the training by clicking on the square (⬛) in the upper bar of the notebook, and try to correct your code. If it is the correct cost, take a break and come back in 5 minutes!</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[45]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">parameters</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">Y_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">Y_test</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>Cost after epoch 0: 1.855702
Cost after epoch 100: 1.016458
Cost after epoch 200: 0.733102
Cost after epoch 300: 0.572940
Cost after epoch 400: 0.468774
Cost after epoch 500: 0.381021
Cost after epoch 600: 0.313822
Cost after epoch 700: 0.254158
Cost after epoch 800: 0.203829
Cost after epoch 900: 0.166421
Cost after epoch 1000: 0.141486
Cost after epoch 1100: 0.107580
Cost after epoch 1200: 0.086270
Cost after epoch 1300: 0.059371
Cost after epoch 1400: 0.052228
</pre>
</div>
</div>

<div class="output_area"><div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAYwAAAEWCAYAAAB1xKBvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>Parameters have been trained!
Train Accuracy: 0.999074
Test Accuracy: 0.716667
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Expected Output</strong>:</p>
<table> 
    <tr> 
        <td>
            **Train Accuracy**
        </td>
        <td>
        0.999074
        </td>
    </tr>
    <tr> 
        <td>
            **Test Accuracy**
        </td>
        <td>
        0.716667
        </td>
    </tr>

</table><p>Amazing, your algorithm can recognize a sign representing a figure between 0 and 5 with 71.7% accuracy.</p>
<p><strong>Insights</strong>:</p>
<ul>
<li>Your model seems big enough to fit the training set well. However, given the difference between train and test accuracy, you could try to add L2 or dropout regularization to reduce overfitting. </li>
<li>Think about the session as a block of code to train the model. Each time you run the session on a minibatch, it trains the parameters. In total you have run the session a large number of times (1500 epochs) until you obtained well trained parameters.</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="2.7---Test-with-your-own-image-(optional-/-ungraded-exercise)">2.7 - Test with your own image (optional / ungraded exercise)<a class="anchor-link" href="#2.7---Test-with-your-own-image-(optional-/-ungraded-exercise)">&#182;</a></h3><p>Congratulations on finishing this assignment. You can now take a picture of your hand and see the output of your model. To do that:</p>

<pre><code>1. Click on "File" in the upper bar of this notebook, then click "Open" to go on your Coursera Hub.
2. Add your image to this Jupyter Notebook's directory, in the "images" folder
3. Write your image's name in the following code
4. Run the code and check if the algorithm is right!</code></pre>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[46]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">scipy</span>
<span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="kn">from</span> <span class="nn">scipy</span> <span class="k">import</span> <span class="n">ndimage</span>

<span class="c1">## START CODE HERE ## (PUT YOUR IMAGE NAME) </span>
<span class="n">my_image</span> <span class="o">=</span> <span class="s2">&quot;thumbs_up.jpg&quot;</span>
<span class="c1">## END CODE HERE ##</span>

<span class="c1"># We preprocess your image to fit your algorithm.</span>
<span class="n">fname</span> <span class="o">=</span> <span class="s2">&quot;images/&quot;</span> <span class="o">+</span> <span class="n">my_image</span>
<span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ndimage</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="n">fname</span><span class="p">,</span> <span class="n">flatten</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span>
<span class="n">my_image</span> <span class="o">=</span> <span class="n">scipy</span><span class="o">.</span><span class="n">misc</span><span class="o">.</span><span class="n">imresize</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="mi">64</span><span class="p">,</span><span class="mi">64</span><span class="p">))</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">64</span><span class="o">*</span><span class="mi">64</span><span class="o">*</span><span class="mi">3</span><span class="p">))</span><span class="o">.</span><span class="n">T</span>
<span class="n">my_image_prediction</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">my_image</span><span class="p">,</span> <span class="n">parameters</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Your algorithm predicts: y = &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">my_image_prediction</span><span class="p">)))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area"><div class="prompt"></div>
<div class="output_subarea output_stream output_stdout output_text">
<pre>Your algorithm predicts: y = 3
</pre>
</div>
</div>

<div class="output_area"><div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAARMAAAD8CAYAAABUzEBbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz
AAALEgAACxIB0t1+/AAAIABJREFUeJzsvV/srd121/UZY85nrd/e+33POS0xRQvRphQTGwOJBG6M
iUEQjRE1asoVFyQ1Wr00wSuv6kW9VNFAUqFRhNZAJGghlSpVhNCWqNBWoFT7jx5a+uecd//5rfXM
OYYXY4z5PL/T0/bQd/d11+75Zufde/1+a63nmc+cY47xHd/xHeLuvB/vx/vxfnzcof9fX8D78X68
H///GO+Nyfvxfrwfb2W8Nybvx/vxfryV8d6YvB/vx/vxVsZ7Y/J+vB/vx1sZ743J+/F+vB9vZXzi
xkREfo+I/E0R+UER+YOf9Pe/H+/H+/ErM+ST5JmISAP+FvC7gB8Dvhv4fe7+/Z/YRbwf78f78Ssy
PmnP5LcDP+juP+Tud+BPAL/3E76G9+P9eD9+BUb/hL/vK4EfPf37x4Df8YW/JCJfD3w9wPPnz/6p
3/TVXwUnB8oBQZ68J14Dx3EHyR8LT956fAfg9aYv+M3j5fO7f6FP+mKf/MWurP7+pY8nl/fFfiaS
N3G+PuGLf+cXu67jfTFncvqpIwiOoyL8fAc2J/mL3pLnJ8v6rCfXlZMvouu7jxG/d9xafI84uJzu
qr7+9KyfPMP1+i80g3WP5/f+/Hs4/8zdc45+oSdTd/oLf+fTzz9/7hfewxeuvS+8Jtbz+WKXIy64
xOvifvokebJXAH70x36cn/mZn/1SLvoXHZ+0MfmShrv/YeAPA/yWf/Jr/c/+qT9Jaw1nxMRbQ9rh
VM05UVUwB20MH6iD9Ia7o24gE7eOCajDGAPpjdYaMozphogj0taimXPSWqtrgqaYDRoNV4m/m2JN
aLphZutPV8XdcRFEPa5H4tqYBk3ZtGFm7DYB2LQxccTi+13j+Zo7bgYQ9wmITVwFt4Y21rWKCd7A
zOLeJRZPb40543scRcQZw9b9Kbn4zJ8YFVSwuaPSUVXM4j3TdoS4fjQ3uztba+xu4Mc97W5pkDyu
Kedm08ZwQ2ix4Ot7zTCxmGd3pMX/EUOlU6F5vYYrqMTzl5gnpKHIupd6psNmfv/EPX7WFHDF/I7T
UWTdo0pnzknvPS8tnq82sAlNBFdHPZ5LPW+347vNDBfo2tZaNR9xHZbHVq03EcBwaYjP9XrNmUmu
kzlxd1qLOVRXpAtMo/fOnLmG3cEMVFHV0/ffUVdM4F/8l/71X+ZOfTo+6TDnx4HfePr3b8jXfpER
i8Sn4abg8ZBqs/g0mihjDKzFgxARVJVGTK4ZzJETOT02QMuNOe4Mm0yB4TCZaShsLaDddmi5eNHY
ACK4C9MNB8a8gxldiU0tx7XgysRxn8wRD1lE2G2eTjsYbsto0TQXi6ASi0ZVUYeGYKKAsnPH3NHW
AGN6nLa9d5oqjuIu3PeJaMdhLczWaoPPsLAY0nLWT5vQUURjAxvOnDPnPzdCeg2oY8Smqc/YbRI2
SkBiXuoazMh/TyYT8xEbqAuNFs8i50oh5nFOpu1MH2hjbVpJz8rdMXcwZ3ocEuZjGbLY0DviytZ1
vcfF6O0h1hbOsIkTm76lIa7Pk6ZxuqtjEsbQABOL35vz+Nx8vmqx7sQn0weShpKaizQuNDABbGAS
f3cVRBrSG116GDQUl5aHo2GwPu+21/eHQUc1DIoNbNxxJuT71Q3/Ao/nlzs+aWPy3cDXiMhXicgF
+Drgz/xSb6rTU/J0N/KEa452wZg0Ac2TV0SOjYkxxlgbFI1Tp9EQm4hutCZccgN0iQ3r7uw22W2y
bR13Ww+ntYaPsPDSG5qnh6vjXotT2KfEKbsWj9B6btIx6aLhXfhk02Nx1Zhm7CM8iTkn6rFgB74W
a5ceHq4Jc0ganDAgomEM3QXVMFagyyhCGB13Z98n4oq4HpsQX5vU8j7wiTNp/YLoDK9E0uBJx9Mo
qCpi4X2YOyLOnHt8t3t6E+ll0RDtNN1AOzZZRgQxpo91srqUZ9XifXJ4ABA/U4714jbWvBphYFrb
whDM9Mjy88bJuCthoJpujDHovYeHpvEe0DBu6XVoGm7VeP0wUhqbV3v+u4E75neYgBnTYl5EHdsN
YQsjEpaE3i6ITHxMDGhto4mjGKrxb8k5NZRL7/HMNA8g0ltD6ddLeJlT6Jtiom/JlHzCxsTdB/Dv
An8e+AHgW939+37J9814YPkZNI9N40OwEcZB+4a0itosTm8zoLO1HmFGng7rxPB4wGaA7Fy6cJ8D
iA3U24XWGmZC+ANbfHou0DknYoKY0EXT5dc4Md3ZLrK8JHdnZKgivcIkwJXWYvFw2hhzTppqbghj
27YIe2Sj5dNXVVRkhUWXa9z/dEdtwtgRh60D7jQcIdz0+J6eYUdfBtvM6MRJ2kQjtFCNjUsYBgcY
sfH6Qpfa2hQ1f67CJH7H3emn75i2Yz7ieTBRO4UugDPjO81RO3lJ7qjG36ftsWnS8xARNokNrao0
EYTGpttaS2qe77VliMRjjYnHz4Vjg1dYEM9jQ+ZpjlTXMzp7Aq01yPtyu6PW8XlDylCpIlzj8NFj
vmwSoYoMmp3mwmM2ah3NOTGUKYpbY86Yk/psM+Nux5zO9OZFPNbrNOjhbXXRLwnh+VLGJ84zcff/
wd1/s7t/tbt/4y/5+zh0jgfGCCDODZpl7J8LdE5EDRlpiS08k6kwyfAmh/SGJLZAU+43x2j0flmL
du63xGichqAtTIq7oFsPAyIR37se4dccHgtphAO/TtCmy72NUMUiPJosfAM4bXbSJQ2Mx93x/f4E
VwGgNxDjfr+vBYf2OAXT9XZY+EltRhEPb8UPj468n8IpzGUZz4rRoT5EAwPK97oJKj2MzgSpxZ9A
Z91X4T7M43kMH2EU2GGFDhPpLebXfeEduKNyYC/UddvJo4F1Hk/39GRiE5UB9ZMnu0YPo6ltQwlv
RqSBjPC6JEPc9DyW8bcdXZ5ghnve6O0SawSNQw/Sc/E8hPpaY7131JU5HL1c6Vt4mGXYxojvnkxE
nd7C81UENLCdwkd63G3gO6pxvRKh8CDm7jz/b2O88wzYAOQdI/70dmXYxBBsCi5hUPY9TikhQhn3
iUtM9LzvNBqtxUJrTfAxud/vazG0yxagpnt4AAnwdgkX2CzDJQ63P0IUPzb/HCB5InmcOpoxbrih
EQIAy43tvWNiEcLYYJqlD3CcMhCAfQFwIsKUCIPK0wpQ8PAOaj6QFp6EO2POAHLt8JjUIzTAJwpr
c+5zRKhjg04YJfOBTxDP60pAFGIzoeEt1HyUga/vCRA6AXFYAPN5TpteE6eZqMi6fxv3fCS2cJfy
aspQIWGQhs0DaOUAXMUCS1EEn7YwjifrTQIHA5bBmD4QO+ay5jg8jwLJ5ekh4J4hWeATqmF4y6MC
QJXpTtMNl8Y+bpgKXTV+xxXRPcBVEaQfc1r/98R46rvjABiBC2ka3MJybAftKIbPwAa/8P4/znjn
jYkDbsdiG2PQOrg6vStYgHzX6zXi8n3ECXUCaq/XLRZTIu73zKbERiaR/QA+a3LLVZ4EyDYTp9ht
PgGA1aG1XECJuxT4Gxt1HiFOfv/ykOQwBrp1VDtb7wy3Bc7G54VtC5xoi+yMbmCSYViGTxwZjsIu
PE9lJwDbpltmf/YFFCrCZXtgEq68inDZIt5ubWMyQRpNtwAjPT6/MljOjHurTA25cNOTqTk1G+z7
TPB45ueXpxB/38dtGR/OHkM7XPzzqFBleTs5x0dodYlDQCJDUtmo+t0FbKtiTOY+Fl4iInQNj8Z0
w8ZxzcP28L7cEXeaxpyudSvhGY2ZwHZ6MQZsuj0JYer+44WZ2chYizbDiwlvNq772q9HVi+9pJaG
RFUjy7RdsUmEkiO8HqGld3WAxWeD/nHHO29MhApxnMvlEg86M9pjBLL+sF1yA+ZpoIWkS6YtYwGk
z3Cc9vkgtzQCNnW9Pudc4cRyZ0VWhkdEGGOg2hl74DFg+JgrBFlufUugk/kEQ1neQcbky8NQRVQZ
cyIaRsAsY3Gf4U5LpictQNXalJ6YhqrmNQzcRgJxkbac6wRNr4Y4yW2S2Y/I/iwjmykeJzIVW4s0
8Zj3SB17uB1hSA4vqkZrgrjRtXHdlDbvdIkNZfs4rtOdvoWBquf0hO0h8iTFPMtrcUdoC/isTVuG
HBWmRcjiclAJzt6T4QFkypGqLdC56Yb7znZpCJXZ1wDTVRcW1tq2PAPPEKLS0xWqIRbZQSKtLDnH
9eyZtkKfJgHYe81/grSeWFBrkVKfti9qQN3bsLlS1Of1VSG1J2ArNH4xLs4/yHgneSbn4cBUaOLc
5x0XR+cRq64NVFbZY1PTwDBUO/e5oyMWT5dgPs0RG1VUuU3jsm3c9kd6a9gJjzD15dGYDVwPnkNr
jft8DA8nF/Rk0jxArxXTA854wlWIxQ/TBmDrMxRABJszAFl4YvyETG3m79Xi3TOLVAZnzMh8iQcg
XMCpmy8PguSbuMVmNozOtuZQpYEEcgAg3lCNDTlysUuGHeJ1rxYHQIU2TObWkB/6AX7uh3+QPeN+
ebjymd/8tbSv+A24wX06rTmWLjzqNOoaI6wpryQwjdMzKR4GcfDgEXY0J/hFLvl6pIBde3hNXZgj
wue1+XMN2UgeSBpcTLjbjtKYEh5pGC+l9fSY0vMRUXo/PMYwimnwalFHCi5dTsM9vVkaJoGFuPoC
foKrEgQ1Y2RYHO8XGlKGZHldgVRJAtKRTnYQR7xh8wiL3tZ4540JOOKGtgDMtCk2gzUZoKcxp9Nd
mB5uW8+H2ntntz0Wk8aJP4cAA1ps5uax8O/7TpOOpYdhAK6oCeYWm0M7ImslxILSHp9v4G4r7FCJ
hy9yEJNsFuksV4gKmzdmeR6anCuNE69OR0QinQq4j7UIIgEkmVFQRGW5sZdtS8+mFSc0F9VYnxue
smBp+AIvGIi0RahSJeZ3U8bcwwBnZiwvII1PpI1FHlDdI1OF8Y9cdv7an/02uuZ1juBPyOvBT/6f
f5X903+Lr/wdv/MAImn07ukVCK0pVuFYhXQywAvkJTaQK5BhhmxoEkiDCBcGUBGmKOJObz02NTOf
6wQLDM4dtOX76RnWRTrdxbiu6zBAGLPA4INUODIcltyrLYhKy+AX9cA9jHlrrPkHBT3AU2ARHCFD
qPLAJ2zbtkJW8cj0FLkv/pvrOyUPU9Hwuqfz1ngmvwqMSbisBSjGBF9x7gRx1GitI260nHAXJ7C2
ndY24I60C/sIRL57j43njmMsCKNidA2mQoXntXlba4zdaBJAKBp4wxixQfvWV9Yl3tfY952tX/OD
Kl0oNDEw2GVykVgMum0RL8+Bc2xw0dhQBY42hJ0KvxpNJVK1GkGgem2uI0RrCpbGVpzlEsd8ZopY
HLwx543enq8Ud5MA6sy9zta1gJ1g1zowPKhmYg0R44f/1+/g7//0T7HLoF8iFTr3gfYGsqPDefG5
z2M//VnkM7+eZIJkKjiIiOWAnzNJSnBCeo97jYzSDh7hX0cS5wHP0AcMs0mnR1iXGcCtBSXdhsZz
RdAE8EWF5pUpytDVFZULbjdcGi4jDJ5pJLj2O9K2MNxjMmbgeT6DI7J1ZbcRhroSAhqkt30G34gM
1c5hr7v8PHyj+D37uK1smnRB0aceRwLmks8x1lQYIzvN8ccd7zxmAsl+1LZQ7THfROxDnEwtKdSB
VzTM4NKU6cqcOwqMOVFXuoC14ogcSHvEk4klmKxFWABpS1dRG4v+vsCuAtTmGas4u80DUWeMke6w
IW2LFJ1vge00xZO7MbN+wmGFMsWqbarBIaDRXOlNkAnSNkQaIzd9vDVJZ+USu685rGtrGp/hMzwB
F0P0AnZkRaY70w7m7DTDRlD8JedWgJbEPunOZ//in+fxJ36Uews853GPzJn2yFyICbfbjVf3lzw8
+wybhgGpTJV64BJPMKsRIcucE8nwY/eDkFXezPTM9vgRCpsV2U1omYFCnSFpUFuEFYrEfczgnCz2
7FqNxj7eBCou48i42YwUe9Ngue6DrgHyjzFwTQB/hvdVcxkeyh709gT8pwUVwPLwWGTFzPCc/YiJ
h9csfXkbq6SAJHn6QGGlpotYZ5PIxr2lSOedNyaC0zRIZzRwUZpeMiUsuCj7nJjP4ANQoQZrIU4P
jkUdq2KBR1gSzdydTSJlIlbZAltZmrLocLieqnFyKkGRXpTqAlAliGwt/Ncn7yvwthZ1AXgmRxZp
k0jXIoabPf3+kwc1ZgByZhalBXqwWJehZC46e/wezL14OYHVtK2cVM1wIOagUrHBYJWTqx0/Y8b1
jdsd5kDc+PSbl/zsZ3+Ei2xBa79Ptn7l8T6Wu10GcdyMH/iOb8PHoJEEPGBKAs4tGL1mg2Es6r4V
iFghoxdZDZA4bZvoMqZCGIzgshwp+sB6Eu/I7MduO9KS/JchXZHUDvB3j2zdiCyhS5HxCJp6enUB
ph8AqyTGJcntKewlYaIwdmkgRYJdPdwybZ71X/MAbeuAqfu5zxF2rSjzPjMc18iU9YALmghNPFjM
b8k1eeeNSaDylXXIDIkeVHkmRElXxogqMC2Kn1Tp0oEi6FjQh73o80dWwwSMyd0ySyBb8n+euoxn
z0NVD05Knhx1UhUnBMDLwJijcokXxfC543OPmgkvvkIsukV9T/JXpYSXu6+e2aH6f4GxyQjO1OiO
rRMZbGV0NDGgWODK2G/5npmfvSdOk5wHE3pPb6E4IS1Yua01eo9T9bk2vuu//S/Z0FWA6CLcbjs+
J6/e7IwRG1z7htlga9fY6KcsjkqUSQDJ17mgXZJ/8jStOhO/iDKLoKAX/0UWAN5x25JzE4anJzNW
pEFmAoOHFOlxpJ4Di5ZwTkXvNpO5bBGMZyp58XUAP7GktxYHTtMNI9Zma5GqV42iO4e1bvCg0CNH
pW89u3nKdNVB004GL6j6YWBWSpwWa86DqmAojYMd/HHHO29MhAh0nuTVDXaLLMtMhqKJMTxOt1qQ
wwcTZ2sQZik9gx7VueUaq/ZgrU6jt8Zli0VehqO+t9KI83QyfDE03AkDUJwGEWEfI1iKdqMK1lwa
sl2CjesHyF84yUzwVQAbQa/XShlz1NU4AfjNOZcRmVmM2KXCGSJ84+BprHuywHVcYJIeG5rus9N6
0u3zXmuz73sAnnN4LlbhO/74N/M4Iozc7xkmWdzvbZ8rdEOj8rv3C7f9zt/4ru98Mt91L3PORfzD
qxwiCG21qXvO8dZ1VS/X/ZsmPUA8/2QoxwFIVsq1Sg0iXPKV7dN+gQzXFqdHZP0Jjk1wngKzk3XY
SWsREmlUyKjqqgauTV0ryJuu1Hc8s22FR60fDGLL8FJP33/OzJgF0/d8jVrPG6Vdqhpb0wN9O+Od
NyYQBWoL2JyxQbsou55y6wkqlkzBmQ/iVlW4B5cDihuSll2DT+E+MRvgyXzU40EFeBWeQbjrR+gh
mXExC4NUBLL7/Q4EaGhUeHUiN82iu8+F9gcdPYwHHPyCcz3JnAeDd8/v2K6XhdEEhyQwBveogEXl
OLGToFes4LsfpxszjXICrGXgIA1ebshWc6zhEdrWeH5/ZJOorHaBihpd4HJ5iPki8Qsa/XLh/rhz
/9zLhSmtzFJSAJxgMy/jKkdV8vJMXNnvM7yLlIqIUM+WgVncI2BWuJNr4b7vK3SqVHdt2pm7Pbxi
zeyartKB5YWkl7K4KSkj4MwIb9JjrVqZZXSyoK/o7WcjX1vU5mEsiji3DF8ejeXRaI/5mRLV7Pu4
xd8rnM5nMud8Ugj5ccevCmMiVgBlofwxKRs93EDALOJOm0HXFov6iyKfxaaKjdUQbL9jEqd7bxeq
5sMzTetiEe+fFnd4CyyCFd5XPUotrnrIZ9CucAtPI7Xo7FnxrEmWqvchtvCDxZ84GTVM2PqV1iMt
fb08OxagD/Bw4QtD8qR6K5KktACDoyAtqotVD4MRVal90dmnD8Z8XIuuZSo2OCEDEacD/Sd+HBNl
65cFPO7jhsnksj1EmJZYSL9eV7Hjw8MDD5eG9suhYXL2RH2m58C6pnUouB9G+KRxc7k8BHdmnBmm
tkIkFUnG7VhA9DJiBZ7TwmC4BZPV03OwsUKwM9Be0guR+QpjNSyA8MNbyXlOQ1AYUl2TuR/Aqx6M
6crkzUy5n3lVnnPANC6t03Fs7hl6tcTKRlAO8vok76PImG9jvPPGxJPOHofPKYsisamxKpOfFCYS
uMjBbp3DlxcCYcGHhKEYYwQ12r4A1K5NlovLiYcdla+64vT6I5pM0pGVsFZsxKyhcafnZum9c7lc
FnYzkx8Rp1ls3qVlUafjDECt4v2jSK08LQtjZVVGED+DvrgO8wTsLXC5RewvdqJj+z0L3NJNJu7Z
Uuel/khyI5gwbOevfPt/H8I8Y/D69cs8yUNaYIgzpUFrqzLbHJ69eM6+79w+utHEU8bBF7ck6n1I
Ho0GnpNhglWYkpiQcjB+7/fHCPN6pILdgr9hWfV733du9zt9i2pdm4FPhZfZlrFasgVyyAtseqVz
MI5bGrgx7yd28YGvuTXGvJ88kxGMWGYYWxJoB2bWf9X9V3hZ6X21EzmORm+NrtvC73Y39hllBLgu
5Q3PTGOFfzt3mm8UyfBtjHfemAhJxWZwaR0syD5RgLfRts6QiciGsB0AaYGf+SAK3CIJWbjSL21l
hQAuGnTtCpmqzL55pAnPNPhgV4bBqbTpRSt9uyFaGEePzXsKWcZujN1QcwbOxTeyEp2uW2RBOPFe
qBg9wdYG3iIVG+HTcfq21oKg1cIj0QSrm9s6nes6zAbDjU0IHCJJbTobLYv8mvQo24flhtfJdqav
q4HbfRnTzvXAlLwdokYjFnqdyvfbTt82RhXP5Sm95VyeFcsKXK3MU8kfdCJDYknoO8+d+Yhnmp4H
GtXZl0t4oxtbpng5wsDklHSN576JMkv2YE72ObMSOYzdyCpegE30dL2+DpvWZAGt9VSrGv2ibR12
ywvOUHbhbqmVIz1C6KLIU8zjPGSCEWhHKE97Qqlvqa+yWYduMLWgsI893nljArmxi9EnRpfAGszC
2qt3xrhHNWRuqqIbz2QArjDGPbkhxMKUZI9mRgdYtT33GTG8CVi+Vi6ha2h+zLkj4uzJ7CyDU+HJ
zCzAtIj5LXKNK13YNQrp6r2QHkmGSeXGxkYnKfGR3vWsb2miNOmICcPCvd33Q49DmjIqEyYNITwY
1R6SCsRGXYVqGipcTa9Zra0rBVmgZxHm1BUa/KVv+SNHiGehMTL2YAAPBnEstCjSZHKbYz2fpsp2
6czEu9TJdOhYgHF4hjNTo5n210MGQJ1FJf9ieyOua6SAE0sGcyT/xJg0z+eSxiEyfMGi7TMq1Xvv
UaqUXI5mfZUSbNowlVUnVBv8mPfQOalwtTKBE48w3vYwKpVSNl8hqSXIXd5NUfMXB4cAwt3zMEta
wTnzCFEPpH7OUv4a8kxwD6xEPAG54JBYE4azCEGqutJ4Y4yVmz9zQoAs1Apgy82yCOyWVO0C6g59
zZVFqsuxgxA0Bbbe18OHjKG1yunjO5rG76WQZIChrmFETourStMXnuFHqOEWQGJxU4wEd08LJpj4
gpOhhYV7e9YQjWs8QL6qji3QUU8n+/RBk0NSsOQvwtuKkGISxLHL8+TiTOPx9joKAi/hXYwxGLtx
2++IBZu5JUgNzr7fmPudb/sv/lBorpJGW2XNWfxmeHnBGSoSYWigWvI8Wh4aNVT6CofMIxTVpdAW
KXYlapgGETLVeonDq9LbYYSnj7UGmkQBXyn3DTc6jcM7amsNFv3eJagLcgqTjgyhRvbGwlgsDeAM
F0XCc6qKYjilvusQTQ/Kao2dJCQFWx5VGb3Qavnlbs6n4903JiRK7i3cfJ/LOj9sl5AhIE7zxumk
Uj0o334wSM0spBnT7fMJvV+W14L60kptHCX+IhFb997ZdFuhznIn/VAj45TlqdBjzJCYVOl0PdKS
+7gdIr/5Wdu2rYV23tyLS2IBJJaQk/nIbFQwQLcs1+8yM/3aE2fIHIpuB0clsMAEMA9XfiQ7eIwR
J3dmssIoVZgT87W5s785sj4qfRnvJkrztjyoe9aj7G8ew2u731GHS3N+06//dWwtjXgat7r3UEib
q7Bwgaqnk7mXZwTxPNem7ysLBYCG0SDpBUc4Ntf1r1DFgr0cHgvr4DAz7vMeHoyPCHVo7Cdy4fyC
sCtA/PBIJFO+zIOQWMWXrnKQ6kTo2xbXporPPcWrlK21hTGVN3U+NOo7o2I+leIkGMKRJGaJW72N
8c4bEy+8w53hsG3XJKOV+tjBNyjNkWXxRy64AuvOYQSHtizTVuYkv4yiRp/TsaEDmrzQCRTpixYn
VoZhhSUAC5knQ485D5IZeQ1LDvH0hyfvT4kEHwGM5ulncsOJcKoYkmUktUdhnCorm1ULa58DbRtw
bKRiDTuktEFkaUJagHU9Z4NWuMlzGyjp0c1gxeLK45s7+34IdE/baR6CU2WYX715ZNrg8c0dn8bY
76fQQJaXWFhBEffW/0/GpHgvnhkRJ1LAKxtS77GxvJOSjjSC8OfTFkgJLL5PZXgkw9dztqUEquvz
VyiYNTj1ev3/zKR1DfymMJL1ewmI46lSl6D0LHyMUJ4P4xn1Xm6yCgxZ/JrK5BX7OegUITdx0lF5
C+OdNybC4XF0yVqbFiFPxJzQciHD8dABtktaZOnLQCzLXdY7M0NFtR9zpgFpkcVJXsIYg33eQ8XK
QlpwnY4ZaowMU0rZyomwYRZzkuAvRX3FQR4rXRI5eScpqRbXmF67SrRhqHj94lHFXACv+WCMyMQE
eJdiwxZFfOLKvoco8hh3Il4+Ni2Aa2Mgix0aMbgmefDYsJFFAdz5m//bd9G2YHMixpSZ4Z2GtzP3
EEBOXsbYjb4pc+x85lMf8vAQ/JNuk//jf/mfcR/LQJKBTqVMK31am/FMIqv/t9YCOD6BnU84OyKU
PGTTLeQSNVT140A5wqRaK17p/lo7ZcQSW6rnHnIPqR+zvJ55ZMH2sYxdYT31PZphdfF4kJMxKI8p
jZkxwQYj/2B8AAAgAElEQVSy9XXYJdeZYusGge7wUCAOwplM7be9+d95YwKARPuDSWiWumVsmRvp
NjJd5rVhY1Pebjdswj7v4ZXMPHmLc6CKzX0BdhVztzQ4pbmp0ok2DW2BXyLC1k6hhx9U65ahjYo/
YcNKyh+W57FOMDRj/SPlWQajNku9FpBlxMM3d6rwLe7fE1NJwC/xCgh8x8WgTVQvyW8QVvsJPzaj
OsvTqtR2eXdLmUxkXe9nf+SHmeMO++TN42N4ZqqMccetsT8aeIdp7Pc7wy1JdztNGrjQcXwfvP6J
H6FvYVxq40R/IIPWV+igktXUzPjjsua5iFwiVT0dQwn+zDSLQ2P44oNo0sqHzVVXU6GRtra82tXK
grY8GfOS/zw0fp2oEo7POtbJer45hj81hsvQxD+YGSoHR+c4KM0snum92LrlrYT0xovrw1MPMjM8
Wz4/S8V/P13Lxx2/KoyJTUGnc2l9wXGbXhfAdVYZu7S+NsGBOWgodfeWGECotAU4dYQ6gaski3Xb
uFw6c+6MeV8nd0PWgr7Pk9wA26osZiZWQssTpRiPER6Vl7L4GgXK5cYW8gR1ZWuX/A5drvUiweVm
bpctWZ4Szaz88NQqFdwshYa4AoP7/RDBXqe1hXboIm/h6/sgwebTdZPiSkZkpcYYC+9Zqd/9NX3T
NKyT7drpNUcO7kZTSXxrR/adn/rbfyfmjBNJDWg+aFyWtxGb4wJ+ARlAX7hDz0rumezXiLzuYWRI
rs3WQbY0SPtxwq8wU5d3U8+wDopqPDZsx3w7AZzRqiJaefgCQBde047MWMv/jlqi8MIEnhDJqg6q
wlI4VbRnIWg9E9XwPm+325OQymZoqhgRQjU9NFDeljl5543Jwj9Uuc8RGRwfQVijcMcwGi0zOi3Z
nwdQd1Dye2ZJtOcDTiU13YIvUqLBvkd1pgB9S/6KExWhqUKu0uNP21AJSv5iUiaHZD3kJH6tLIr5
aZHZ0jgFDjX5yiRJnNxYUswzG3DpV8yAsWNEPL2XkFACpPG92TjKw0F2lwCuZ8yjRA4abVtop9qI
Aj5kufcCyfk4NFsRoUk8j/3xFkDzfR7s11zU2oW2RTXyeLwHwHu/Y2Mw72GYH55duV4ajcHf+d6/
yOb25NTM9mG42JNQK8LaIuvNhS9FD5y57r1pGPI4YDqtSeJCcxHZonVGfs8pvD0X1VVYEkpmO103
2imVv4olIWqhcuMWH2SBu6Xsr4qNkU3AAh/scmSkmmpiTDs24/tU4nn0DOe2fk2vNLzF3ntkbZxD
yzaFy0VCL5byeMoLegvjnRdHEgI+6J7MRAsI0tuBRYR+zXHC70QxXW8X9nGLcmtk8RIgPJNrU+Y0
mgz2x1AY8yKuZWZkZS1QzBK88tLH2MNb8DjhdJK6E4A6Zo5mzDrMaBxaKIc4U6QYR2Z05nB637IR
ViHtcdoanie8LmHnroKZgoC6JcWeDEk6btnmwY90cKTSL7QsdHTJDI0XwNpQ9hSYOsX3ypI3NA8y
n7ROv1XdUEhFzPu+6pcenj878A2yAVbBQSpslwiHXr98lWxv5/XP/TT3rsz7XIQzQ2DMKNxbp3aJ
LQsicdA0JiDptcbfxxghDF1en1iQIUVOHlbS9k2Q7HTYRBHpCaof5EfQxLGeav36dFQPmQYIkLn+
3QqHmjDTEMVtBNdpzJA1mO0gsIX3oHimy6Mb4OmQtWgN2nVLzCRT5r0FsTIpA8hA5PBGLr3zuD/G
9bylUOed90zIhCuE1zEVXE/Cy5mFWUCVdloPduN9HCpnFgQTkDgttlMh4G4OrWN6ELJu4wBIA+/I
1pka2YACyFQEGzP0LnpfPIU5fRmLSuU6IcbcSpJPkvDEgfNUhiHSsFF7E5S6qpg7aXpalAJMjaK+
3vuqvxCPSuMa0yukyo0tezCJU4qh5gITTAbGAbKqBimudDQOcl14WPcR0pj3+yNVBxQp0wMMHGOw
tY19vx8K8+a8evURZBOwytpdu/CX/utvoWdWqbIxbbse4uD1Pa5Zb6OET1mqcTO900Kv875P17S4
GhKGQ5NpunCq/F7NlP9BFju8phKp9urtI6cyBJGg0RM4jJVqv1he7Vwp4tV7WHPOE9tZ/Zxh4Shx
bQNOcgyRqbGD5Ddt6euIT1QuR7Uyk/sYy8taIdjHHO++MZGDEaorhGgHsSg3T/1snzM7ABrXS0+A
LUa7bMttB/B2UJePFOMhGwCp0HbCX+actN4PRm3Sve+5YSTBS8gq5tMp1XpPzky1fEzwtJpXa88+
tro2ZWWLPLkBM/vC2Ok7QseiZwYn5kR7y/RgnmCJ9NfvV5uMx3nKznhsDPUiQ0XPoCVOK4L2IO5p
8lDeLAMynuADIfocn7ttR5uI6+XCB89fLIP08PAczPjg+XPEnA8errFR7i/pz58d6XsCn3A5AM2W
NViFqViFPMB9L1ZxzwOiruvIYBXQbsKqzxppYGouyghP20OHxEdwikTWQRV9eAhOj5dQ1VFbE+eY
LR7OgVEFd+msjLbup1xyMTQzNnXQTbPkOh1FqgsfCfbeaq0x3ZeeSeBwHvjcjNYfv6YAWMeRzCxE
QRZApNh6C6GhyLzk76R4rmRntPJrKnXr7vRLqp/N/WAouq8TrqQH6lR2FDJVHB5QhEkheRAl5tqg
WkGIH6S4oF7nRp0HCaoMQkklVEx9pDqjdmbabcX6tQGCZs6Te6/mXKod5nHqVjmAu+Nd2c0Xiavu
3VUWi5RSViM0XTCPHrd1Is4IM0wi1NFk2K5ugqG3GNeWhKzHx0f6ZeN+v+OEDsq2bUzbuT3uSNu4
5Wvbdo36q/Ga7/yj//nBsbEAGot4FxWxKXPg0c+oPMICOTVxl0nQAtaBIacNLoVltbX5l9dxSjtr
2w6jld7IPm5H2r4/lSKQdlQQkz2cHV39gytbdjYq9fkecSra2yrHWPyhBIRN4vrv4xYYjZ4wwNZW
R8YtD8agCuU1atSzmY8nPXw+7njnjUn02s1uaOkWVi1D6XMujoYHAHofmZFoRYVvyfm4QIo8W4Kt
NktTM+jiw/ZVYRkPuy0dkzM/JegIvjaZp3RjGRhGvCckA8lU4liLJ1xbYcewJosPECM2tpR4sRD1
NqkL2lTTHT+d/BbvmfhJeNhSrT8LAEemnvGFHUDIHUTHvSoCLOC6r+rhmKHThiEySn1r0adXhH0+
rtRpFMQNHh8jLl+ELDeGDW73N1nANrlujWcvPuCD5y948+YVvXcexOn7Gy6VCi7+hZchPuMdvno9
a+SyV9ZjlVSU4p5nWlSiaM492dG9tGULQ7C12Rd/Q/a1ISvkieSALbDXfCwpgtA3Kc6IPeE5tRPL
tkhzdY/VAF4l+jO7+8LUIFLmT9rDmiydX6UtCYRzj54jLEsETkK+Y7rDW4JgP5YxEZH/R0T+uoj8
7yLyPfnal4vId4jI387/f9np9/8DEflBEfmbIvLPf2lfQqhc1YNLweQ557EJVLHhWZUZTZ/GvC/P
o5qem9+DRpzuLu60HoSk3ush55R4Uaj3lcZtvbgMZcRIib8O3pm2L+lG2ToqwVVZjNi+xSmEZyo3
RK1LSLpCNTNSn7NO1JmaI1kT445bxO5FThOL+bi0DgUEZ6ZrzomkJ6XTFxjp99Q6EZD+9IReWEOL
ZeKezcRaWynl7g3tkRkzbbR2VArLJqt4sUmcqtMn99tk3vYIVb3T5cr1euXNq9cAXLdLALvS8N35
9m/+T9kLKMwlUc8YOeEXnkCsZ2nFiS5ge8oXegpesZ3S2+Bjx4cvA28ZSrWqAPbJPu/4PYx1R9Y9
qSrNEsMavlio1YvH06OqTE41yxojemYPy5IHjZILcWWfY8l3Vth41nHx5JgUXlKV4oazz3ump9sS
OweYRKfAMI4x+vWyCJdvY7wNz+Sfdfff6u6/Lf/9B4G/4O5fA/yF/Dci8k8AXwd8LfB7gD8ki+Tx
iw2JjvDqbERMeiHTZTkHPiLMEK4sESQL0FKaZoVxUpTrU2tT+tNGRJZyAmOMVSy1wLQ9FkYVn1Xv
2wLVAguJhUKqnF0uRyjWFgku9Gyb9CSZabaXnCFqk42x6rqaVOOvg9+xXGSvsv3IyBRPRD3L+LeH
9ftjDKQpdw/jElyYo0AvrjP6rgw/TrPircw5Q1E/GaID5/H1DtJCl2Xu6S2Fx9f0ynDj8fEx3PT7
zn3cMHEeb2+43R959eoVn/3sZ3l8fM0wZ5hHq1dzuhjd4Dv/m2+m6tGKN1SeTtULLU9DjGbpCenx
89JvrVR5VEyH3GdlywrYbpyM6clD8YvGZzOzJCFT0BL3XJ6FJsAeBLhsXWGH9ol7KAH6zKbjWeHb
Uve3mLhPDJ77CpeJFYO6sm3XBaxXC5Mygoca20FjeMIYnm8PfIVfmTDn9wJ/LP/+x4B/5fT6n3D3
m7v/38APAr/9l/ow99TPsGD3SVMs8/FiR8gDp16vVs2mgw16VP/qAYJx8BRqQguQq9dapkoj7g2X
swDRuDbH8kQTWoCerivOb61xu90ONissBmwrcI+JZA+guo6F2qdKVrQ4ONKk8WGxqcIg6aqcrg1W
3oXv98hWbH3VyIhNrMmSsmyc+C5EErovXQ5dnxdp7ENBrnVBtvBGbsn90GS+xmY0Lhph2uvXr4le
QMJ2uQRHJedz3nYuLbNuiRF06dgwnl2Eyxz8+f/qm3EP4e3KsLQgeCxpBGYIIHnX7DTgVOM0SR3g
6eOoU3Ff9y5y9DH27HRQIZ5KeIXNyWbkgWnhffF0mkRYXZkvJfsUJ3N6EIRCkrWLHNXEpdQnLcSK
XIxZVct+MHEr87c6A6KRLseXAHYIkGcB5zKgeYh59AYSn1EwSOFC7wZm4sD/KCLfKyJfn699hbv/
RP79s8BX5N+/EvjR03t/LF/7eUNEvl5EvkdEvudnfvZnaJfYRJe+HaGO2Sp6ikUQalhkmq2pJtcj
6PRm9zi1JaQW91ssKk0Mw81AGq0fnoS5R/MvPYq9RpHCNLwWZwZt3KsLXQjtlBEqicOZRXoLdS9v
yEIyoDCTUKHXRdkv3KbwmXr/Iu56quI7CwuaM3kW4/BezEa2UsiQYOzZHDzobsKBM3iGVqFwl1yX
VtkyX4AuVqXsiTFJNIivDMi+Bzg98WTGytokF23MkcLIbcMVbm8eefPmDS9efMiLF8/48INn3B5f
Mh8fefzJv8d8rKphX608VhYnAfTJsR5AoyeNkeGcppE4ZWxcAo8rCcOmi5QYOEQePjNp6+mxRH/i
fZERqzhwukU2pap5LRqhK7Lo63FYHJhfZFlmMonm4rSUh9mS1RrXpGsduWSPoeTSxOFjEebOPYDY
/Jy575kBDK0atIcn5G/Pn/i4n/RPu/tvBf4F4BtE5J85/9Bjdf4Dmz13/8Pu/tvc/bd9+Zd9GW5x
yu8ORkxwT5dty47wkhNZcWbI1gU+UOzY3kKcxpn0y3ag98yFmlcz8ioYfLheT6CrrsxPAXchMRBy
i4W3iCv7yJNPr4u2Xyf8PbsTStYHFX4SmyK5AJlZqRqitnRiY45KjqEqpbFY1O3ScI0U8cHbjHu2
TE+SLN6VISIzHElu6z2Lx84N2FO0hxktOgq7cnf6886+74v1OvfB/R6YwJvb5Pa4c7+NYMK2Fjos
TRGFN4+P3PfXWQ9k9LaxbS3buk5ePPuAT7144KLCt3/LN3O3Yvj64YlKZJgcXYpyWptkksryWVTX
ipM08iDaoy+PZ/lA/k6Fr8HxiZIBVkhJeqk9jcYBrAY1wCH5MFDAaGT7IsXeIkmQIKw0Th0Tcg+Q
XBMPz+jh+nzhG73JyTueqSbXM8uVwOEJKHYRJNtsSItm5wrQr2yt8U4AsO7+4/n/nwT+NBG2/D0R
+YcB8v8/mb/+48BvPL39N+Rrv+QI7YixirJo4dZfpFKz52zBcYJXOlhPxWqTw5WdFjG8qK7K0fAq
TvonHgtM5ShXh8jk7DOV53NhLWkBiWIryWyI9uhjU/yEyxagmEo/ofhJsJIikR3h1zl2bk2WDotr
49JZC7K1FilzeYqplMpXXFNINZQhLA5CfH5qns5k+GoYlNqAtWmabivkaw731zf6JXrnaG9cHiJk
iQrleO++7zw+PjIJYzVsX5yOtl1wJtftQt8ar2+PXC4PC3Ae99Dw+Mkf+b94ppeVvYvQKwlwGT5G
QZ6tjFa1A1kZuVFSiFEiQTvIi+rZJydT63qqwWlfsFNm0DmyAO9EcKswtPr4JBZT+sU2w+NZIY7q
4i+t93p4R9MNNLydfd+/QFVe1iFVuF54J1kf5HUNqf8jRw1bAbBxGB2yBx93/LKNiYi8EJEP6+/A
7wb+BvBngN+fv/b7gf8u//5ngK8TkauIfBXwNcBf/dK+6yCRAUt/xFqmZiuuzNCj0mkLF/GkQ0OK
RPflbVQlbwGHAe6l+HOi794ifCptirom3DOUOtophI5GP4GWeyp1xftC0lDWayV4HGHRIeW4ZBOy
eXhvkj1VDj5BQ7AZhqi+T04LM8BHUpw6GMR7AoHRU+hQelONWLtah5Rn0lrokwb7Vda9Oxxxfc5b
fdbi19jk1auPGGPwuN95vIfn9/r1Gx5vexIAQy5y+lHhbLstDKm1xqc+/ZyHZxd+4z/2j/LN3/Qf
smWrVdIDCA6KrNAXWF5VkPR8nfwByh4p7vi9NLx64EaxNo4GV0fHQF2ZRCFkICsta3ZooawDzSsM
61TxY2W4NAqmVyvQveaTGTxBZ5Hs6n2lZ6Nx8eHJahxsIW96tAGxGeD9TK3gp4mGuM+a87cxPk5t
zlcAfzo3eQf+uLv/ORH5buBbReQPAD8M/JsA7v59IvKtwPcTNMVv8FUR9QuPg8QzIN3CaDEyUFdU
IxaFYGaGi39oYESc5ai2OHlyg5SKu2REq14tBgwRlhss+bm12Ip1GaQpybWnKXHYEy8olbGQBawN
5pVytVTa8mhubRp9huvkmBY9XILnsWPe2PDUCNnSQ6qFX6FdIypTnNZCDzRkyQu9D+arV6pRo/3B
Vhq0ZFVp3uvuRqeIbT0xFNLbG1GdTKQnL23jPnZaF+73ifi+Mhbjdgsi2gwcIQhrHVx4nLcgVXnj
/via3QdjF9qnr7x585pt27iPG/eXO9twhg0+fe3s+xv65cPAADKV2xHYQubABKSF63CfjjyxEVU8
Ga+HN9pxdnSSdPZD6vCs+jElMYy24UQt1yh5C6r8IdeRKvjOnErrEYapx8+HzSw0dCDS/vhkjhEF
mB4i0MjEzTMzeaM0d0WCpFf1ReQqnm40y/DKyjNPz0NZazdqqmKtXZL4+TbGL9szcfcfcvffkn++
1t2/MV//aXf/ne7+Ne7+z7n7z5ze843u/tXu/o+7+7d/Kd8jEgCZ0Ndmi7jxIQhd7k9i+yIDjSyM
Ik96NWdqlNGXO7qPg3/gIsnrOLQkVIRr3xaItcVBcCyYfK/IqaVC8UL8uH6A3itUiObddfKWC15p
vALdonVnLNwt092l6DamZygmK1uwqpM9vJ+QswywsiFsGk3Dio/SELpEetLds59vkK+EUKyn9ROm
k318krtyPmV/17/x+zItbLStL2W3aG4mjHmA5rjy+HgLwesROraPt9fgDWXj9viKn/6pv8+4D968
egO78OLhGaiz3++Iwx/5j/7jhV+UFzYFfI8iOC0vUZROenB2hyrxz/tZ65IdPDM2yFHCANip6K4Z
CwBeFWPprRSmtVK3Ei1N2wXMQztmpfqVBbLWxi8Mbo64rmI+R3YwRNPNAtz1VJkvYFckWo/GuhyR
ctajD5BqUv4LQ0mP2dVX2P82xrtfNZxga+8RcpRwj1a9jComDZE4ASLVJqg0xn6LLMJIQWBXhg1a
C+2MoLI3mtoS11LpEbokBnPPBTDN0JYC0W1bD0UIBqhrcEZc9gwVKmUcw9zilBMBgu8x5Aatc7GD
ql+bIE5yQURxNcSi3mYMZ+vCHmkMorAtwF+XyFNE71xFUWbQedFpKTZNGrwU4Haje8t6IsU1G5en
JyQI5pZZDEnR617OINONNx9+GCpjNJgj+ztHNmd6Y95eIq7c5532uHO5KNs4aovGvHF/vOE0nl2f
8+bNG17fXvLBl30Kt8FHr4MV++ELeDUmX/48JA3Ye6jumaFMpF0YMmGfXHRj98nuAdZe5MrwEIAm
DaH5PTJtlo5ENWgbFQpFO5LIuvRgqHhUaAc+R8yvWVbtznBWnfjcaegUSJxPMVwcsRaYiwy4O3RB
PSrH+3YBDPwS7UYyWxatTba15oN8JqhNdjOmKFsL6Ye2nWQmRWiypRcX1deWmGCjMS2u+W2Md55O
Xzn9+zwaUx165am83gg3cUavGsnGXCXUE92LMj0qkt3OIp6M+pf4LJG2NEPXe0nvIsG9znGSFB5T
YNqw/QR6HqS5mTUilRWodCMzq2+pLIEliYpV/Ts8NT4z9AqPWlPKMgBlVdIrcsRm8G/UqJ45mnyW
ao4e0ozxetNoSGbVZIoT7iB5cpXyWHpHlfqG8IJGb+jlRQLc0deo0rGx6QJoHlN49eojXr58zeNj
pIFfvXrFuE1evXzD3HdevvyI7dkDl8uF58+fc9keeP7iQ+aMTXTtnRcvXvBX/tyfywxKGAA8PC+d
ngZqZio85unuO6IHRjTnTvUH3kSRGalzSwq8ZobIPPr8NFF2PzJkTXTVw6h2hhzi3yUWqZlp64mR
mAp4D4V6S28w++GEEPglwusJajtGXz+ruXQhmdYzJTpDbjIkK5KHNXWR1KrN6X6v1hdHG41oXg7v
RDbnkxozXbRyX6sZE7BqMqZFBsU8pB1nZQv8nNv31ZAoCGuRfmwONqLrm2oAn7fbLWtHjswIFuFT
kJlyUbUAQ6uuI9x5XZqrNibl9hzNs52q0wjDaCuNeHQeDAB1M1uck+hUGDyJygjo4kIkCJq4Rhmb
belr9PUZZJFcYSPnzE/plh7XEM3IIuiuE/kA8goPerSjBYR7hC/DjH2/cRs33tx2Pv/5z3O7RQr5
5z7/ks+9/Iif++jzPN5vvL694nMffcSzF59Ct86LT33Iy5evgggmzuUSUpPPtg72yN/+3u8KPk72
THazVaUcz6VSrYErbdoyfIxSg6rLKRA/g5N1X8UnqgNj2IwMC+GRht5vZdyiitpPc+IJzsupZqdC
5OqdzHneOemgSFAZo8n9RK0wOsuDsLKD8ev7uMU1yIHPLVJerqtti1KOJsVhihRxMXLfxnjnjUm5
YI0wElGU1VZKsIhrC3mvmFVDV9VIyb7qDFexcLmLwCBU0oC18c+l78X+PGuCnNO1RcGvboGaKcEq
Ya+Cw4pZgVzmYQh7v2Tv6pOgcEkHCAdrd6RymARt3GRQjccXv8ZPaL4cmyu8F40+zBK0cpMDXwip
yaz3mIOe866qT/ocm8Ce3tjMxHyXzr/6B/6tpRESiziM9atXr3j16hX7vtOvFy4P20p59t7Zto1X
j488f/YBH375p9kZqAoi8OLFc/Y5eHj2jMvlwocpXXBx+PQHH8L+BiP1dluL0zfn2SzKCeDgJBW+
ZkaUYGh5eL4yOWLRBaEY01odCCQqqxtVGLgdvCOL/j1laBepkWxbUQe/HhhZT6xjiY1nO4161oXD
VSV24YXRs/lpv6Xe+2n9H5nDapau2DIakXEagZvkv99SlPPuGxMnAVathT9/nq7m+e/xnuSVZKc+
1eA/iOoqJVcNJmwYjcrrF5eFxSExM/Zh60SqPj31nZGOnBR9vG9hRCpVvMKBZGAWuSnc1+g5W+k5
TRwjQqBDoHpaVH9WRmm3yjZEewrxgx9TFPAKmybB6txtR7MaWV2x/R4C29qCl6IhEjUNWrsuMe0C
VoOHoQvMNXnq0Ty2K9vlIdKw5tyH8dHnX3G/37leny0uxuP9zm3fGQavXj8yDR6ePYPemaNOdXj1
6jVjTC79wph3Llfl8f4GPDIhze78qf/km7i0y6pd6j16Q7vKAoEhjN6ZB3Jp+qTBFYSHW1k75nhi
+M81OxVaus/F66i6KgjqgXsq4vlcZLpKEwMhs5i4S/Gb3IQz6zlpZUueYL9H35s9JmkV9o0xDvJb
rq2uVfiX/BdpK4vn7qhF75yDF/V29uo7b0zw4BXZlEUkqyZaKp2mV4oTUQ99kb18pEeSbEkT5riv
nLulhVYNPKJ6FSPBrB3pPvd0kdeDdmci0QRLWwKO2b5zBBCmCWR2DaCv4vUA5G2l7gLoq0K7yMYU
GckzZJMe39Fay9RknHabsLgH7r5IYofXdC6Iy/DOcqPp0cBp4nHi4lkR7GizpOAHsSs+Zx4SBzMq
uWuut/6cu0f18PBQbJ9utO3CfR8J/MIw5/G+8/LlS/r1wvXZi8gabZGqVnzJFrx8+TKo6RIbSlXZ
+jMeHiKd2c34/E/93SXwXR7kwUuqbFZccxmZkaFdaaCYBDY1JTxd6W3VLQXL1nKN2MlQk4JTofpW
rTTCoEfIU90Fm8YBh4Ra37T94K8QfB2T/fC2zRLm0+ijrR7h3OrHnLIPDro59/0x27JULc9cqeIK
e8a845K1VWVUsjvkW4pyfhUYEwSbsQgsFcdisTpj3iH7DZscQsyVsisN11WbkeniAiuLuZqslOxM
Dy4baCxYbVvQneWQhXQPgzbHffU0XkaJyX3sqYgWQJmw4dboC0TN3rYJgi4Pi6pgzUWZtSRj3LP9
ZaqZmdOI8gJgFflVejI+YCAedUXFrNwtCHjue35WZQbCYle6dLeJLYylTvQ4SRvCvO+Ucr2kyPTu
xr/87/x7TInsyOc/unF9eIFKQzRA8zHie3/25z7H9fkLHl48P/WHUdiUN/tjdBNU48MPP8Bwnr94
gfbGw8MD2oxLf8a1dR6eNf6nP/lH6ZLtPJJYFxFryihWW9h8fj6O1PimB4W9DqkyxBG69oWhVXhb
3yESDceLGDnmpLVtNYYrXM858JdIwNkKsc+0gJaHBZICWO7sPrI2Z8twpISOTokBqzA2K9Czs2Tp
3pUTNioAACAASURBVJ71XKIroqzOf9HU7e2Nd96YCFlW3YQxLCs4FcnWFFWAds6r96yRad1Xd/po
7n2ojiuy0r/TdtyilQAkCGrZWa7qUOqEtBEnjfuhdq4pC+ix+YPCfah2nVO+lVYuL6uyAVELYsxM
X06C3l26pqFmzjpdz3H8MpZ5woZw1AXkgY4kPd7SnTZULzS9Bkhph6TBOXQBFiBb+Ij7oUa2pQcC
h8d2689h27hN49nz54iAXjuiQWp7tMk+jF/3FZ+hXRr7zPSmZunBFFRDJ9ZMePPmERHh9ibBS5SH
Zy/oG7x48YJLe84F5Qe/768f68UDYD03bqvrhEPguby+8/WbEKUPqikHUM3TwRKbIsq7Ql3O5vIw
grqwH0xVG9xPnMw1r4nvned5poGJQs3sr0T1JkpwPz3WphHenDv2iQgtBciXVGbW4MScVHYxr8Xi
gO3Sw/P72LuU3FPv+HBxHvf7kkncx20thjl8gX5m0ZoCSQYkyQKV4BmgvtK4mt4JmfoLix+VtHUK
AwtYe4LPZHd7kkkbTEZWLcScRxXxzArbUTyNaau3axijqLEZWQFbiwJ06V/sNukC4nMZyci4HAu1
pwZrnchmgybR8a0A6vCvY6Hd748BRGcmC04xvx2qa+6yZAsO7yRwiGqFUe8VjGk3/rVv+Pd5ePYB
1oSpRTrcGfl77XLhYXtYad19Rljz+c+/pHoAb9slXfPJbb/z0auXbNdIz7pF7+Pr9cr1Yjy/Gj/0
l/8CTZ2einXlLRZe4mMuYuPINdB7D5kF87if8mgseCBRKHek+VvWKkWmPOQpGodOb2FdQT4cachY
/X/ENQ15PsP0TLZty8pjqOI8UhQrKsXzhko9r3DAlJfwzERFwWc76eAYXtcDqy2oZGFreNERMh+i
Eh9vvPPGRJAlmruqVyk+QJWFn7gdw5eeZgnpuBcBK+JM82h/udij+OqEtjRBYTXVKtewfvfgkcSp
D6FWf7BaA3c4g8KgKyxwjdPY3A8t0ARspz5V16rrnxxarkdvl0yXS3x+9EVpa9O4Bl6gCmohKaAe
YsSWafDyRmIeW5y8AnthUHW6neqjpleR2TEXolEA+EqF65d9eWAQ++R233l8s/Pm5SuuDw9crxfu
iZuMYdGaxOF+v/PmzZsVfjpwuW7LpX/z6k0A29q5bC3V5wPsVXO+7T/7Jh5HiEsd7VhDl6X3ngV8
gUntNnN+sh5nDjS7DAbX5CjorPYoJpEBkh4Fj1OOjOGcYZTPivegmdKN0CVBN6rndfTiUcb0rLHx
1WpkhWZETZbPankR2cj6HNNDl8fSgKCB2dByv1T6t3BEsyWSJB5A+a8Znkk8yP3496kZc9NtCeNU
TLptmTaWkjeMB9zbhWl6aG1UZSiS1GdfIGPJARQJLqjNpxMlS8nHuIdq2hcAc0VzD0JVbOgnmSc7
hydhHCrbsU7QcU8V8visAmhFInUp4os3UfNCim3HvNU1SEhe5sk2Vz2HrtPbPaQIS8e0C2xVdUsq
6ObhVWnMBUhrku0M5gxv7Hd//TdgNNoWsft9PvLhZz4dItIeVP1y2x8fHxGfh1BS0e6JzbldH2gC
n/r0M3oTHq4b2yU8m+fPngFgY/BpMb7/r303932PpuzZdD6KG7PuKUNECMNQ+EmtqSpp2DS1fKtH
UOIoBYAX4A+hNhchSedyuaxrVwXTo0VJ8Zy6bol4JhcJW03HlwjXCSOpzoA1957hT/V/LoPWMtQO
o5TKclmEOqwOjCzqk0gVz7eFvOZ4540JnEEmXfFo9ROp3HmNaUc8WicmItzHLTY5lvUMR/anQDE4
VYnme42J9ktmY/LEyB3c8gTtveOarSWwJ+5xhRmlAF/YRNXf1IYvVXdVZdzuiam0SNfiSA9MJ+QB
SfIZq9J4aeEuT+ro05v9AanHXdqsa45E1nebWXZNZL1+rmM5349lkWN8Zm6iyMvzb3/jN+EWP/vU
pz5F633ppHirfsjC9rBhKNdnD8sgt7YxCRZy18YHHz7nzesb1+uVOeJer9fI4l22xrPnV3Tr/N3v
/cu8evn5wJzmXC0izh6iqh7ZQD28uyofKIMGFl0f02gUOHteh5FKDo9tpmdTP18j1+cofC7lA6ro
7jyCL3KIN9WBZplRdAk1wZW2zhAqMJdY20/WfoVPGjKh67CjMZLkWevgbYxfBcbkqIGJjRpMRBfL
PLkvlNw9iT/ruHbmHqSwRQwjLH0g4WmIUixIpJ2aQUWYEYWDLVTEVLI1KStLck992eKFrLDKPdPA
sfElxSgKHAzgtfgbRK/j5DFUU/HInviTArvi2ZTrfS4otNPi1lRUW4Z2nW7hCS3DKJk6z/tS17Up
Qmj5IIIB69rX90vyZ1zTWERY9bnXj/APfTkffubTXC4XtktPTkRjv93RnsWJ+XmPj49cnz9j+OB+
f0QsPJOPPvocr169WlXWL54/p3dlawGo9x5ZkGbwTHf09rm432lLpf7ARnKDUjIM6XlIzK2pJGdI
1hx7NmargwBYbUGmBUBuNkDGidF61GRVGBIaxSHtWXwmJDhELrZU1/Z5PBckWL2Bf0SVaemzOJwA
dBJLSk9leepRqa40FF/Ji+khvj7mPSQcTwD1/0veu8fa9q71XZ/3MsaYc67L3vt3OefggXLggCB3
KzE2BqOptUYTra0aUAMxRFJpTSzRtP7RqH/UaDSN1lC00gI2WtTQq01LWwz0xsUDiApCAbkcDhx+
t733WmvOOcZ4L49/PM/7jrkPUKhnU84vZya//PZee13mGuMd7/s83+d7+Xhe74LNxMZsrho+YRMX
C3sW2cKkvV04qSp3x6lpkBKMVs3WdRUMzdZRccWbx2pvRaqzBD50LFsvAsotQjSbk9oUJ9wQjZD2
IhchBKfgqY15+ziyqFN4O/FVX+N7taE/RzkqpZfh0rNiY9xk45oWVw1Tqb1Na5Mn3bRQZu9Fe9Pa
sMZPGIjaGka/tRy4TQ8VtOoCwwOlMWdNdOkv/FSM1/Gv/Z5/l3AYN+c28Yjl49RsHJekXB/x6rjv
fcQH109lCGok7rUiO55OvPbae3AuMDUNzzhwNY2MQ+C7/9z/iAQzbLaNoFEH9N7afbRWTcHzvLU/
3bPFvfD5mx7M92swDBsLVgrGStb11uwsGi/EOY280DCyuFHvJb6gPo7RUh4vpj3RD7RZTCMTtoOi
TXwaY1vAmK2ZJgjeJpFKkBTM5Y2N5f0yXu+CzYQeVBXNT8ILDMGZPsJOy2rZKUWDxkveGIywjXCV
UaIS7mhy8xIj0UWc32Ir1XZvMIRcq6IQlCvSojh7P7okO82kbyiX5WN7HxL0AW3O6O3fgljrUTY7
g1IKiWxVlI6HnVNcpFUV+juNIKM5lauDm6sOqYHgp863Ad9Pr42LYk51lkHjgFC2/ryP3M2BrD2Q
6lD2Ij+lTYXaKa/VgCdcP9HNyHmoSTd+K7md1/uXzAyp+ZwGP7Lb7YgVvDMryFVB3OurK87zzG63
4/r6mt1ux26cGMeRaZq42t/wo9/3Azx/9kzd+W0zKFIZKrjYPqYf96GCBJzfwH3FgrZgr1bdtUNi
F6YNjG5xFzGaarr2a4eokt051YghSihzBtY6KtEU4YMfuvdIpXQ2ayOhqZcJNE1Y3yRbNdTuqwga
zzJt3KCwyTTUdW+iBcepoeQnTZtDBx87UxEtsWMIunEYoS1LRvwmqGo3vOWo6MTD9Dhl7alrrgpr
TTpKFnUyF1dZbAw9RX1AXVFZfWOpVgfRay5P0IKHWm3cJhvjNYpK88nKdNUeetZNJhi2IU5FZwYa
dkewoj9bR78RP0QzyDE1sMuImRGlpItOSX1ZncirqlnbQtKp1mATJM/oho4haDxEA7jN9azmzUCa
Lf0vVNu0DHNQRaySogabnoh3/M5/82sIcUAcjPsd0dTY4zjiGFiWMxVtd7IruCAcZ9XyZGCc9hDA
D5H99ZUKB+dT9wG5uTow7gam/chhDOwiPPs/vovT/WmbgAADHgk6YakOvLlvSAORjcDX8JO2IYqd
/npdtBJRg/LaN+D2wLeANDUpt6qkvPioCrq2orWyzXJb5RIttylSJJjht1WE3li8rZ2vmpYQDRQG
epIkotKQ4lQmksuqYD+GBaGtfc7Z2qiX83oXbCZKb64p07gOekK3XrG1FY7gJ5pj/NBEUiJgEZY5
554X40PocaENeGsS8oa/RAuzzkUp0bpY9F0p1lH7iHQ1KnwjtOnLE6O5sIVW3TizYLwIMPfRcBN9
aDp4ayQowhaipE5im7tak823cXTFeCm1sJZMI8Ph3Nb+2MmnzZH0Er9fLyPf2Uf7ZMhV6dc90Vqq
jbRXzc2u2AYqgISBZafM3Clq6NMQNXIh58p+v6d57s7zzPG8qtl31MU+zyu1qjv7aT5TlpUxqIH1
fr/Hx4FhGBgHx35/xeFwII4DP/zX/hfDKbCDxiY7sqmlofFq/AsEw44zNbtOu5va7l4Q0byzVER6
CmS1yqKHaPX2kherQpMy1ItRuHduUyNL2ljd4ijpQguFbd72XqvDsphMLWyVtxj1QOGA0jkoIgJV
tBKuL6cq0ZXyLnipqXHsm8Y2TVCj3Ta1Ueo620W2kynYDu29elA0QlJD3R0aCyH2tc1rtVY6Z6EJ
r6r/GNzBB9Qh0RvzVDo4WY3/oU5oKqCTWs2Mx/fRb3O7anRtZ0I+NYYuKsizjXT7XGc+rtZCWayH
EwsnCwqGas6uUHLuju3Kf0BzYOwat7S3wNbrd5Fku06uAcd6gotXklS+jGl1QXkooiZUVYR/9ff+
ftaSKejmpiHhlf00KAnMedZVs3YOu1H5OhaY1sKz8rLqBuvQ6jDqdGMcoxLYpj3OFfbTwGEMPBoC
j64m5b8QGOM22gcjnFnFJbV2nKLT623dtdbGCya5uKh6S+0mz+2+6x0PaK6PmiBt18a+l4GxLtj7
EemJfTrmpR94rU31TjEtJa2hVWADX6V5zegr+OGFiVKn1Furo34qFeLwcTyVv/T1rthMNoWnBn33
k4IN3S7WgwJ9bNZ4A0UqYiHc/d+xSYudrM6O+KaLiFPs0nZoD1LoWEcbbXpRmno/fbwjhEExmOZd
Aur05jaT67ao1JEtdPvzFn7VDZHNKqCNdjtvxDbD5kT/S2nw9FOnZexoBOgFEctvY1PvddqS7eJ6
v1Uqetrp920RFI1J6iw+1LmmJlZws4kDG6ZyePU9Ouq1ipFaNNjccm2GIWgbuazM5zMELHqk8PDw
QHWe+XS2CubE+Xgir1adeB07j+NOxZWDZ5wif+Ub/nNS0d81myGV2jJu1+CSJNcwtcEHioWUtc2l
jdP71NBt3JR2Lxsg2iYsiGYKN5DUodemtT5K69kqoe4eb+1SNY+cxmWqNlho6yfGqATNhq3Yf9na
sKYmb5jj5Zj8Us7xsmqTd8dmkhMBYTAjnLaLY2VbtQsL24PqxDaFsKXrhUGNgfSitxNevUGiLfS0
Wjj6qqI034yJer5w7gxWrZCMMVuayhaWnPRGiiqJvQdP1kCoxi8IHo0h3jw5m4P8Rn4LRr+v3frg
UhndF7cDH81h3hlPw22bcDOSuiTOiS1uHc9aiFmwDa8vzO3zg/c21rZ8HhtLtnxnrZQayWvV6xvs
AHDwL3/t15EML2oPgpbb+vCSC2OI5CUzhsiyLPghWpvhOZ0XaoV5PuGc43A44GPg7XeeMU2ahDeO
I1IzV1d7Bh8Yx5Fv/+N/RLEBSt94KUBRdmxninp1ru9Vf1VcQnLpa6uBnS0r+JLfJMZsbhtJLlpJ
ecyb10R8ntCrBv1YA3c1nBx7uFv7SKsG4zaSl6xt1JqS4mJu45A0AF+0ANdK3jb4nv/TWc9ZMaOP
8/lsr3fFZtIAV3WWt3HZMPTphVhvWkWY8wLo2NeVurlLuUZ919dmWmNRjAUSWW9A1riM0LJZpVyM
bbfEO31zmcatcKbKbDdTpxObiZL6gcjmWIZubrox6MNlNsX6cObKaFKCtgE2l3hx6v6lYGLoG6uI
LmjvXNd0OLT0bdOSreTWSURLpWu/X/v/C1OM3MbNisGoFLF2Ad4lIapJEtr3KQguFVa2iVCtlWEI
DINu9iWpyHHYTZxNi6WBaF5d1qzlqzjCGDidHjidTlxf7ZlPi2Y8p9mIbYn9IXC1m3jfTcStC47Y
J1KNR6L3pGEVgLUDOn0ya4ZxYMnGwA6+V7vAC38W3+6d/dZW7Wil1rCoTcwnWHUCvZVpI+JsRLWU
krai9rUNL8HaI8dWMbXnoimMR++0AhK0Aszq5uaxiSBoyFdN8JK2k3fFZuJ9JBrWkcsW29k8TZu5
j3eO0ZtLeM0GUulkY6PKb1yS6JRePgyDko4K1tpAytk4HJifaO1u3tG10KwLd3jDSBo4mlLSkxXr
ab2YGlj6qRMQyirWEpUuUOuM1KBTLK20LDXOWSC56EJp2EIV6cFSXVMjHie+P/ytcmmb02V+zDZm
vCij24NXTcfSJiI+2s+2zy/bqLoxgO3O6cMiniXAv/H7/yOmOCBFORpr1c0OUXaxkJiXxDSqqXIp
wpwWqsA5LTqtEliWpCLKXFjWzDjuOBwOXF/fEEJgmgalwkticIUP/ZlvJEa99g2w9sO29DWmRM20
vCgepG2RAs67YeytZ635IhVwa6tr3djGBdlIazbRCcZI9m36IqWzYgX9O06V7A3bCDGan+42OdLe
SCthJbbphKdlMBcjw2UEcVsFW6raYkhJUFUpT820AK+X8py+lO/y6/zqZbeduFvUp/Wu1lJg042m
6GwgWguGblJ/kaL0ZBFGN+hJ0PQzIgaQxhdKR9BNK+D6xtTS0ETUfMkZk9aLTiyUaNawig3fUF6M
lq273U7H3UVd3LQCrrhSKRLItWkuLkKu0EmTlukQka7DEBGiVd9tEQ4xmk1guNgEXcd5cK5ft7Yk
FIzcVLFq2iw2iVI/lUbxx+QBrR1or1IKA03E6FhC4JwqDFqVjVFD18MQlfiXQOrKspx75ZCz6nc8
qhI/HlUMeDgcqLUy3z0wzw8Mg1ZeN7sDh2FPDHA1TexGz80w8re/6eu7jWPXLzVfGxfxzqpcNu4S
bCNzZc6aH+vHxD21B7bZYriwZSCr25odCKXqNQ6A25zmW0XZMRy3KbUvsQ3l5sTeJjdinILDF6xZ
5/rPaoZKTcfmCUisjEzGMYE+fPw4X++KzQS0xWkXNJdCTRkGvegrldyo9aYEzW5jY2poeEu6U8Ob
atOL0iwBqpr0lgo96qGN7oxqX+sliKXjzYZLODcwmHWA9+pE3k65VnFoy2TkM/NybWZJgaEvIPWD
HQ2oNL6HVUMDkaYaLghYVeSwh0GEbCVwf69lay867iNaUbQzyUV1XrvEVxpgKcY10dPYNndn8RxV
KNIkCBtLt4HDbQSdaqIuiX/9D/5nrGbInNKi/7as5HVVtWzRaU0bdccYqU5IpTIvDyzLwpoK77zz
jrVtnrxkxbhSBqsOpjhRq+pPpmngaj/w17/5vwLodPMK/V7Wqu10u1BiZtBt1OqcVpDVJliXE65a
9YHuwfKXkKboAaY/uGE0CqrGEDowq9WK2BhXNuyEi83KOd3MGoCv5i0mE9H/1GOnICGS0Wpe178S
56pXQuNSs+E1L28LeFdsJl281pBo7xl2k4YuWZnnwPxMGpszdE2Ljttq53V0vkXZsA/vRAlvXpmn
TR0KKq4qXgHWptmwgQSxtS1SKd5OorARwGAbJdZaCa50LKC9jzaSbJWDmD9nKQkX3TYREmE1b9r2
vtvPl7r2z0M2MZh+Tb5gzarZoG68ofHi7XeKeDYryzaCb3qjVtaXWslF7S9bKHitud8njHOTJbOW
bBWbx0XHSVauDjfblMRasBg9qZRuGl5K4XT/wGk+k3NBnMeFHXGYaLhnjNFAbbi/P2p7WQtD0Ipv
GkeNvoiO/Tjwyi7yt771jym5y9ZWoWgKpGmmqmhYm6uOknWqIsZGbJtGstO+bySm3fFeg9oaiSz4
1qpuU6B6UQa0TaIpl733qqBmw08uy4Yq2+GlL9+nf9UU7t5p9QJm/WgpCc0YO3r93cfYbDdfFvz6
LtlMGo+ksuEKjd3YTh/ATn7pY8wG3OrD5npoNNBxhs6SrZWSHb7qaLdWFW71E31VTsdlsj2ghLb2
8bKpmANaEZRSNkal+aU0unxbYKUktYG0B0xlA5UxaN5M01R0DxITD4JKzTdRr+9VSwhaqKuBU2A3
7Dro62janG2Tau8niwKq1YBcba0ugGsrw/Uk3Fi+elJvRLD2e7RArtbaDeL4iq/7Awzjrm8cwzBo
SzSNisvkpr6NZmc46GHi4Twv3N/fk3PViY/3lLSQzwu+OPJ5oSblB1Ey+2lkcI4qiSF6Hk/wPX/6
v6P6bcrXKs7G2i0pd1xlNc5PU6kDTMNmj9lc6Bqto4eXGdaUqxEE5ZeO79vBlGoxsZ8YSNxY0lt8
RgNhL1m9+hyk/j4kW9udMtmA3mKGYc6A/gpUl8nVNDzNluAlvN4Vm0l0vlPC2wSiGdF4Q9QbJ0SM
KxKi7fStHLW4gGFs3XDou7UrvJCnA7ZInDEkvTddju8itjZa1fEsrEVPoA3c3Cjs0Yx7C5uqtPfL
3vXTpYOhTj93LcqNUQHYRh4DrTAaGCiiQGYDAmHbKNv3XMvG3qyWHgeNublFeygG5XVka5wecS9y
FIC+obSvaTwY55o7W7YW09Fyj6oBhUcGai6M09RH4UUcVLF0RLsHQ6SmldO6IFJYTQO1LMs2hj+d
e9DUsix4YBpUpzSOO/19ayXiiAgRYScrP/ht36T5xICn9mmViDANoUdiXJpxtX+vjVFt0o7GAO5g
qrM1ZqPgbZS/UetfqGyCudI6p+vZJoLOhW47unGnNjxFgfq4XVvzvqmudnyoBc+3UbD+ZxWJd91U
+mW8ftXNxDn3J5xzbzjn/u+Lj73inPurzrkft/8/ufi3/8A59xPOuR9zzv32i4//I865/8v+7Y+4
vwcIuU9AmsmPjT1bXohzrucGF4tB7L3vZXnpKmvSEjWbUjh4jxs8YbDRo7UsnQoN1k8bI7YIvuEe
3YvEmRTdsImyTW1cDAbOtgeODUCrOrGowelY2saRnc8wRPAaPg10lzddtL5vIBrI5C/GjMYlwFq0
Npq28tfbRAfo1oBObb7sZlWaBSUinR16uUnitoenZSxj77K3UC5AsBAq500ZnHFh4Ld95VdrtZVW
Gy8rjlJqIq3aCp4fjpyPM3k+cz6fSesCpTBEzWB+WM46rUurbrpB8F43m1KSbSgjjx490gOpVoJU
hloYZeFv/k/fpAHsFxMtV6WDv81uYasP2OQHwXdj6oaLvSDJaLiH/d2huJxaXth19tIJhZebi3Pa
bjVM5BKYvTyI9LmS/v++UdXQsavWqraW6hLvUQXxy8sa/rVUJt8M/LMf87E/AHyHiHw28B32d5xz
nwd8OfD59jV/1Ll2ufgG4N8CPtv++9jv+cu+Gire+BoiNj6zuIpeiqN0Z29jr7ZbD97ychpoZaSh
Fv8oDci8wBiAbVG42tmpLmpCXgjST4RW2jf3s1or4s06EW1hVBxHPyHEi47ogie4oqI5A2VFSucU
kFqglRHjfDP7kQ5Qgk5KquEsqg3Rsal6u0SLYagdL4HWi9cuSku5XkwEbDHb6sg594cDlOOi3BWb
IgidZqtAcPOT0VFu2wSjG1U5XQqPf9MHYIoMw6QHQKmspyPLsrCkmfn4QK2ZNS+UNZnGxeOHAUH9
W6dhZBo06a+3esbOneJEEZj2ByRBnEaGEBmcI+IYaubJVHnjh76PEHyvXIVipt7bxuGrXVP7GV31
7DarhPb/jQ+0bfrOha7ZaRhfFQN7xVs2tsawtKll+5yGsbQNoCUw6L3cqATtZ6gOaxvPN25KowqI
q1oBoi6DUhvM+/G/ftXNRET+OvDOx3z4XwS+xf78LcDvuPj4t4rIIiI/BfwE8I865z4FuBWR7xF9
Av/7i6/5u74cm5fEBn5u7QsiarPnbRHH0IG0GKMKu7gwTHZbxo5+H83FbZGJTcPjCGpBwICryjNJ
Renmze29ncaXD7y+tGyObCHTrfxvvBElDCnNvjo1hXZOsYEGyhWEoZX/slknAgYAx24u7VAlr69i
UZheA7gNr6hVT6wgm8esltG+V3kvXPeLdi+EoC3BxQneSvvWNA4mJqvG2PVS1WipKYwv/GJrraQs
XF/d6gNcE2lZESq73chud+D2lVfZXV1z8+Q19ldPTH8zEWPk0c0tc1oJAqfTzDAMHRsqFcYwcnd8
oFjucNxH9nFkd3PVSV5ehP3gufvwT/K//YU/ixMFT4c4dSOq0ewbnfcM4jqgf4k1Oegs676+nDnu
Y6Nml7uepr26/8gFsN3G9m3C167/5b0PF6xZPRTV26apw/vXCRfrxUMN3cdYXKVUBWL1Pv/G8kze
KyK/YH/+KPBe+/P7gQ9ffN7P2cfeb3/+2I//si/n3Nc45z7knPvQO0+f9tHnJdBacu4RAVkqzWgX
LBzJR219DHzV1Hst/3U8Zr1nUaq74gIbjVwsac+T+1g2SujajibGA+OfVFsMTWsRvPISOmCs2cdm
JWtKT9edzVLVSkFNklXx670nY+i815FupXSiV/Ca1qbtCxpm5dETKFisZ9UKSfvrouK8C5B6cN4c
99tGsRlB9aBz2VzVQPGlFvZenJpUZYqR77QUL87jh0iU0B+IZggVwkB18Lu++mtJaSGGiWEa2R8e
E/zEbjca70aV1c4XMwUKLPOZ0+nUq9IYxj4iFlED5nVNHK6uGPce0QEwfjeRz4tyc0olBgc5Qzny
anqHH/vev9KncAq4GgCaSyf0XUbGNmd6wUiNDW9zrm+oAKFqayHwwkZULywe29c5q5rahtDbG69r
qW86omsNMUPy4HFD7KzaECPE0JXR7Roi6mmj06wLBf5Len3cAKxVGi9vvqTf84+JyJeKyJe+NF6H
gAAAIABJREFU8kThmGJGSFxc+GYd0Mo9NZyx0q+V8AY8afaIeZ3bptJaBnXrNu5FF1W1ftR3cV/H
GS6rHEUMSGTzU7kcBwfaSLs5wbVsHf2+W1ZvQ/d7ReIbIBq6qjXGEapo7II5xONyvy5KrNJ2pymD
1ROhSVs31mZr45LhMS1aotlV6vfU9tJSyF4ouR15OzXtmm6+J/r9m5dqrRiAHc0h3qYdN68zxLBV
RjUT/TYpExGbiCXT+VTE2qZ1Xcmrvt85ZVItrLmyrJlaCw/PnrOcVwTHftoRY8CPO2IcmA57nThJ
oeTEwVfKR3+OqSxwEdcqIj2HRi5+P2FLCmgtaZVMLUVbcJNhVNTFvl0P8W0KdtG2JGvfkzJXa9DW
qIkG+73gRfV2bz1FIBcTuuqrZA2RH/2Fhkhip0w0Ipx0BOLvU5vzK7x+0VoX7P9v2Mc/Anzaxed9
qn3sI/bnj/34r/q6vPBNTanItkUIXIzM1KleDAvZQK228+NlS/1zW9If9n2Da5Z5RU8uu6ktW7Zp
edq8X8SUt218WBvmckm3ftHBSz+v+cFiU4/CGHz3qW3laWulNoDQ5PiWwzN2R3rFiy7Lb3zboFKf
8PTrANYrazWnfrYb70HwFm2p+EoMxia2exBxnb7tUFMq3zg8GKbSpyAGvEqzc5QuZCsl8eTxa2D6
qeAhp8UeSNerhCZoXJYzLjicVVdhiJzn++56p1O+Qs2qSF6XxPl4UhzmnFQI6AJSYdpf01nJteJk
4fv/zJ9kdAPjFDsGc2m01ZXcbVM0IR62RpuYr2+GdTtY2pprv3ufyJiTnnjXc5TavWr3E2dj5o7J
uI77XYoB2zPinDOrDHruk7iqgL1DfXxck1D8xo+G/zzwVfbnrwL+3MXHv9w5NznnPgMFWr/PWqI7
59w/ZlOcr7z4mr/rS0FB0dGoLbAhNlKO4RG22yqAto1ZQ7xgm6I3MYbtBntXNmQdtfZr/6axjW1S
46zVuSg7W2lbt+zahsM0z9PBa+TCZbUCuon0ctvMmMH3TalvVOj4ruNDbGWxLpjQlbmNWNZBWRYV
/NlG0d5bq9Za3431/c6FnpdbzQG9nYoKMOqiCzYyV6cwNfrWMXXr4bUCLL6awK1cSBNU4ZzZ4im/
9Hf+TqXGS0ZMVRxwFkWRmNPaTZnUrV4VxSGOzGnFB52WtYB1gqNWIQSzVMiZdc1KcRfh6uZaNzbZ
wtsoqlguJL7nT329tr4XYeCIIHETPraH93LM2zaO3gr2VjHTAsLbAdexIwPMG1bSxr+thWsbbt/M
2BixL4hNRS7aJd3QG+u5FvX5bVouMW2Pd/JSXdbg1zYa/lPAdwOf45z7OefcVwP/KfDbnHM/DvzT
9ndE5IeB/xn4EeAvA79Htpnh1wLfiIKyPwn8pV/rmyxSuuLXe3Xdok1eZFNytqlOyxQhN8B209m0
KAwtwbcFohWQjiiD96SL8XBLa1NSmi6Wrhh1tSftNbyjptWsHVN3JmvCvvb3xhFp/7WSWXJR3sOF
14gZX/QNpgO6dg0UBK2dtaoCNYiDeaDgVbhYaw/57vqUXvnUvpi9952CfRnCxcXm0qpDzRBqwGGj
Z2tbpuZUoQdEiWv9vtla4rl63wfwUcWWqWR8UPf6xh0avWIww6Byg/NyZr/fk0tVwuA4kHLlcDjo
fTHC3rquqEdL1T/jSCmxLAvTfkcpwhDVa7a1yEEquwAf+tN/QtfBhUmzrLkbcl2Ob6vkzbaAF6vh
BrRv10a/1xZy3rKNfplDqreVvlfd4mrf4L2POgi4ALUBxb/YKhvvt6CwXFbDyHTg0Ey3XtbrV2Ws
iMhX/Ar/9Ft/hc//Q8Af+mU+/iHgC/6e3p29BgLFSr1usWjENe9hTesLEQCIdDKbE/Xu07n95teh
HJGtumk4COgNH0PsD2Z0yhwsCGJj2SBbeduS/Kp9rbfpiZ444GqlkqkC0dl0yh6sikBJ+r6bdgPw
pRKjM/MkfRB2u5Gct4yf9qofc0qCfl8vgnMe56pNfazF6L1Re3/ygpM72HRLj0ETF724QHu/7qWP
6fV6RUQ2/Kl9r8t3rBiKZf46yFKI0TKaa8VZ7KqgMSU5Z6Q6lpSYppGUV6QI+9sbHX0Pnjkn5eTk
hK9CnEZWyyqepfLwcMf+6oCrgePxyDRE/LSj5kSMA2vJLOtqm19SEZz5Avf4k1z6+Fhqs3rUyrOl
+rV74JwSz6pk1er4TajZ9x7xJvFQcH0cR1zRqqRNiZSYaeuXrfUREbMbyGQaBmaGVYBzBiZ7331n
lJ7ncVIRk5L48P+3Ofmlr3cFA7aBhNFamYaKj8POdvqh+1tqjw0pL70nrdYaedXNdz9WwVLf8kqx
8jAE11mHraptjE4vdCeuBsK16qT3sgK5KnelhosRYsuz8X6bjNj0QE2lDd2/wFikFPuzUutLEYIT
gqsEJy8g/zgzC26jQYuxJKvk/MUNSFu2XqEMG6tSKxZ1ptN+/MIASDY6eIsGCcagbK1U7fwG+15e
3dl9DD043l3gIfjAMFkVUB1SKof9aFWmfv5ud6CUosFbw4DHcThM+Bj6tfexBcIPuGE0PEyFh7vd
jt3himUuXF/dMu524AMPD3ccz6dOMNyNe+Wi4Pm+b/l63dQNgHVSVAwpKnL0QddlWwONpe0NlK+S
OtO6VHol3Ma8zjmiHXheYBx3elAgfZ2IKDDdhIOtwm6eue1+tKplS3AcNi9Zt1XSjYSn9jdmK5H/
/pLWfsNfjfbeTr/u/1qynga+TWcabdgRmq/JxUOkE6BAWVR8BlpyVh/w1Zk7m+tTD43ivAA2L9iC
4pRej+X3bOX81tI4MXl+oAN2bUKh2bd0qn2M0aTkW//cMRgZtgXd2htnnhXtZwrqWm8gYRQdZUtU
DxQ1hGu9teBMco+NyZv2qZXd3bmusV9d7TYHiiUov6E9DH0jrwnxg4LI5rsirskfLk7VsFUz10/e
o8rhvBIHnVTEIeCDTtvm+dSTGX1uAeED07jTUfJ0bR6yjpo1pCxXtYyMMfLwcOLu2XNiCLz97Kli
JcDNzSNq1Y168pEi2hJJzYShUte1/44bAKsPZTGOTeOegAogS61KLmR8oSXSa2a2Ci3ZsbVLQUjm
dYtsaYNbpbjFWmgre9HW2PfWBAT9WKqLBW7F7hOrTn56QLXAN+BjhIMf3+sTfjNR0Kq8QOLpJ7eo
MtebxR62h0tVJqyOY7Vn9S5a9VK017BXtZMiDgM96a+dDN6qkH4CbDJ/77e4i6bK9Ra2hTOlrHjN
3GkGNOXCP9RK22qTD/XyVFzD2UPfsn+q+W4EGyF7NLVtCM5iKsCjFY+E2DGcVJXlGJzHZQttr+20
qnj9oX1U7ov0iZECkxknWtk450yi0IKftBJqni2St+mNq3ZfiuugdqsY8dKlB87pWPn+zV/g0eMb
bm4PZuLkGZxuRN459rsdwzARg1oxOtHZUsqaDIh3jHHifF54ev+gG0vQmM3TMVNT5tHjV5hzMoB8
JKXC8Xxm3B10whO0AvDeE71DSub0ix+hiUfViE2V47ksZqjtkLgZPDurTNrvJsZabhiJ2hFcTtVs
IzajozaSbptQzptVKGDWoKg2qFaqS92VTcm0OrVRMqbhVPbeLh/19rndp+YlvV6eyufX6aW8ERiG
TcaNA+/8RhN2dMKOyq0BQiemYQY+QiJ4qyDEKPnoKLOU1vtf5Bdb/m7Tb4h3eCKFQqgOFwTEEXww
Ayy9ge10d07HygH1cg3GAen6CBFqSRAC0XtwE8uysCcxUHnrx34YqnCaj7zy2qtcvfoe3kwDrz55
TH3zw/z8z/wUd7/wi7z55of59A98Fvf3z+H6hs/5x387Mu2UCet0o8KmCU3d7GKgSPMNqWongL7H
av+OgZ/egStCdduIWoyS76qWzSHo92u0+lrVkU4tJdUgKWDvw+uGHxxkKvvpQD4nHIGyOoareLHp
CcO4u5jWQPQOD+x2O4ZpIs1nDUB3nsO0w+E4Hs/sdjuKLNzcPiZL5dGTxzx//tyyaeBwOLCuuX/v
tokuy4KLE9/9l/8C/9zv/n2UVLVja36x9ti4KroZO0cuqx42hols2JMjSyH4gVIygynGtWIw6wEG
rYZsQqbSCW/rSatfB5szfnBQq06t/KBruL3/rJt7kObhKxY8hx1q2P2xQcBLigaFd8FmAtoCtF27
eV30myYbpVlLfgcXrYKQiEEXo/PRHL+bNWPDGWwaIaVT1/UkFooXpGhPr3oXM0WSCtXjDXwjelzV
Etax6WeiU7wlXIwM3Tjgi/D86UfJf+s7eT4WRu+YfMaFyHnY6ZSIQowjN+JZP/o2b/38T4IIT4eR
eVlxtfDKbeBq+hR8PnKz93g589Hv/Us4Xyk+8ixN8PQpz9cF5yPr3T1lf+DmldepJfCpH/wMvv9/
/x4+8Kmfxqd8+mfw+B/4FPaHA6clE6cRNYTWFkBQGroCr0Z1MjJZ7XhNbeehblR+o4tnB8H4Jtpy
wnB8kyHsOK1PiT6y202sqwa3J2PBns9nLeW9ShxS0arq/v6eJSXW+cTt9SNO5zuiD6zL0teKi4FT
OhMlcno4E73aOuZceXZ3r5adVbEdDGc5XF9xPiVu90Pnzjhngj/fDKPqNvkqBRcGxNosoCcHFgeB
iyykzi/xF1WM6w8+7WdJ7vwZrL3KWQFisQNyCA4R1U41138RrdJdiICBud517K0CeP2azUD8JT2n
L+fb/Dq+bJjg3IadhODIWXkgwfrKflOao5QxEKMfrUcWXNsknFCqY4geIVJ8pVAhbS5hHWtpRsqS
cXaiSXU458lUnEgf7YpVTM5iTKWqbyyK9yKhUn72Z/mp7/xfST6z242Mw549juhHxil2P9gYRiWN
VQEK4zAhDmIYyVIZJrUtlDUjBjbXlHnrjbe5ubni9rXXKGXlVSrxvY84ffjnyMvCbvTM8x2nn7/D
x8D/85Ef5coFnv70j/H2z/w4y7rivWeVwrKuTNOBOQd+x+/+WjAKueppcv/7JUmvA+TOtpX6S1dq
+7xM5Qe+7X+grou2Ly6o2ZFFYEQD2LNUhjiwPxzsexpehpAfHhj3I8fzg5L+cmF/dWCdF/M7UYnB
MI0Uizs5nmecwNXVFd577u+fa+VkBC8duWYogTzPhHGPXOBJBdHcnlw6h6Qd+R2ktU03eGgMONem
Ym19VcHb2vHRlN/SxsJqzmT1Ng5UFHlhhF1EK8rGa+qK5LBZPnRbSAfaokacqx2jK2zVysf7+oTf
TJw0bKISDKNw5vfgnUYfllrxw0gsajIjps2hRS80bgaqN6mmeynVK9aB9b7Opjy19hueEbwUhmj5
xXbDGipfAnZyqP+FgnHZmKVKTqtU3vjB7+UjP/q32aF8ClcKEoXqFuoYOZ7OOHeLmxwlCct55vb2
MSJqnpxa4HdJeBcI6AhZYmQ3HVjTCe8n3ve+9/HDP/j9vP80c/36e9hfKbL/qe97nbv7hXmeGQcl
fqWcCTWT8kKQHYiQl9UAWM8uBJ4/fwcR4Vv/i/+YcYhECv/S7/uDQCR75Yoo74T+IHqPcUq06itS
FbepAlG7d42R0PdTa2V9OBEGdWa/uX5kbYttUIO2m3NODE5H7sWC46MPrOcVUPB0v98zz7Pl6zpK
KuRcKFK5ublhTjNXV1dM08Td/T1BCjc3jyilsJxPxBiZ18QwBOac+LPf+A38rq/9OgVG0aJMcRTF
HbK1rLVUNSi36VxAWaj6u1dyBa+9RsdXitEGBIzJXDf+khSC6cvaBCYnrYydrelaC7jNohMvKvC8
mLoFr9e08VOcFByOwuav87Jen/CbiWBjR+dweO3xChRXelZw8J5QCqsTQjVD3yo4NALUO8cQB0uH
U+/NzYk9gNMUPTGgSvpEVE+SMEykIiqsE9H34cAILHYSa4nf3o+IgK985Ad/gJ//ke/FSyUwIUGY
xoiI2h36AOM4cDjst0nPmphPR5a0Mlr8ZfOxCGFQ93X7c656qguFdckIlfd/4LP5Oz/0IT73Cz6f
q5vPJPiCdyO3Vw5K5tn5Hh+cArBA8I7zwx2PnjymukjAsZTKcjqRzg/U7Ig7z7R/BRd3/LVv/gaq
wF1a+crf++/x9v3CME1QNX5THEqIwuFqJbqtLWikrFor6Rd+guvdnmfHM3EMVDy3V1cs88w6z+Sq
IOajvZocpZQIMeC9avTqouzOaZrACeNux/Pn94zjSHp4oFbFVdQ5T8O8pmnqQsFhGDRYXKCUzf8j
mAlW8J5X9ujIGqOemx8wSK+YpRa8iKITVvmmYk551Wl7515MA9CxNQzOzjw77Loy3iltQSc8Qs02
uWkTNd2SbR00glyg4rRatmlgzlk3oIbRNaW3fY7w8uj0n/CbCegOGjtdXHdpJ02dieohxONLBedt
IqHAn5Z5gcX66Og8ySrvwXww2pjYWSlYDeeIMRpGo94jRQKDQ0+UUqnBESokCwjXKiQboWjiu//k
NzCmIzUWdsPe5AAL0QdiHIhRAbd0KpSYITgYJ25vr3n06IbTvBKcY3540J66HojRnLnMDjGXghSd
VsUIvgjX19d8zud+IR/+yZ/m6tET9o9fxXt1048ItzevqCFzTtQqjH4gXB3IObPf7yilUueF02lm
Pp2pS+E6PuLu6TN2u5Hz8+c4J6S58Mf/w3+fFdgPI0Eyp+r58q/5d9i951NIadV+3DgYa0r4gOFH
wo//jW8nrYmalcka0SD6nFduHz/h2cNzbm+esK5nalSbhjWthFHH0u1hLqmy1JW0JHa7nTJeXWQY
tLxfbYqTS+X6emApFTeM+CpILaScicNEzpnJH1ju7xUHobCbdszzzNXNgZR0kTTbTUzk6byDooeT
923DsEyh4GxA4F/A40SESGSV3AmSDbxwthi9U7LiFJS+gAglJ2Ic+6aMxdhOFouBVELUzKX2Uq+U
bLGh5qeCDgg+qSqTxhdUdyvBZaMCeQ1OqmbAK6IgWvCONWMgaVO0VpyLRhOvNMpakUyzXbz8icGB
j5EsMJppjpoeVZIWHCpGE+U+xAupPuLJa+K7vukPsxsCpUXyuEyqmSE4gnPa6qxVe28R8qogb8kL
R8uHmaa9snEPO6hCWs+cToX74wNjHLi6vlXjoVQgCME7ag1IPSMh8jP/70/xaZ/5QQ43j/EhMITA
fgq4tfLk5po33p4JLuCGyNSC1b1Him46oBWAE/XnWM8PuDHgik5tSlnYjSOhQF3PrFIZh4G/+C3/
DYQKxSPOM+eFJ7dPuF8Tg1HaX70ZeOXmmrKekAi7uGPY71hy4vr2MTkXXn3yKnf392jRVykhEN3A
8XjsUaRasZ0YholZCsW4OM3jJGKKbTy7acfzuxPjGDk+uyPuJ673B7z36uSWK2ldNd0vm7PZsnKe
jwyTUQxECZFhHJCMMYu3SY6uE604XdVNxju9N6WPaLU6FoTQrDBka8U7e7uKSTuAmmx0rQp3jRwK
Wql76SH12hpeOrwFatWhQ4wKCwjBvEw80X8STXPEykl8QKpoGecFcRHyTBhGG9vaDty1JxjLUq0P
25ShaUO86NBsc22XDvAWyz8ZkO4y752yM30wV7XgySKEpnGp+jm/+AMf4u/8wHfivZKUXI0Mw+at
Mg2Bc1KtCHFgXVdq1swdN3pqFELSWfdazrpQDK3HO8bdhHOB08ORNS9cjQdd2EXIDfQLgcN+4O64
8s47z3n9/e8njLpAhxBUDOcru+nA3d0d1AzTqNkqCOPVFSklYnBqnbguKpCrVR8Cry2aVGWLppq4
utpr8JgPmoaXdIwbPLxyfct8d0d5uKcAc1p57QOfi5wWSqpcTxMp6uTkMO1IAuJ0033y5Akiwmy+
ItPVgd3VQa9bVRvG+byyLAsxeh5OhaurwwtA+rIsalp93qwlY4zEUjmfzyCFIYzUUBCrOmJQs/Ai
lb/x57+Vf+Gr/u0u1ANPXRM+BLK0NSaUvJHbpEkm2ER9Km3QlkoHw/QNRFtubf+yZQxnm/o4O6RK
rZSyalsnK2JeMdquKFhbBVWQG25TclIw37WESdcV3s55cq6fRNMcAFRhO0RPRtPJxCUkRBS5UvFS
7ZJ1R04L+GAbSNt9LeAIBa50pr+N45QerozRBiSqmhcbA4I4ITQaPLrzIzoq/qvf8ke5DerQNU0D
jkwIUTUmQU+mNVeiC8RgNHQXEVFcoS4FZKSw2vvV/NwJI9xVhzjBj4Xr2ytKypzXM7LMlmSnaH/O
mWWtfMlv/oc53z2wrGfGnTqV1TWzzkeiyzy5OvD07bcpEnRkuhtwUllPsyYYpoXj/QO5FtZ15tXX
boHCk9tHLMuCDAWh4kMzYh4oScvv5TwTR2XCvvXhn+Z4d2R3OPCbPvDp3NzuYdWT9OrmGueEISj7
M9Vim3mkGGt4HEdiSjw73muSYzMwcgokulGd1Jxz+JwRuwZUNQoKLhB8ZNhNUAs+RobdQDCXeS9O
x8kN0wmBXArDbiKfFt53MxHiyJIXrUZrpcZAqfq7Nu5OdcKlEFclBdZGiL/4uHthzXUhn2xrEVfp
PsbtKTDXtyJtrNtoLiacrBeq8qKTTvzQJQfOu06OxEHN2QSlL+ER5V2ymbRIyznpnF2FadioVqne
6rLeRrem2+nsUeV9hODIKaECN5s0lI1dq+zYqCWub0pObau2bGG6g1owiX0IA3/zm/9LroPXKgMM
G4h471hXC78uUEtlkaLTmawu6lKEWtV0uqbcF6g6wa3gtWx3Tjm+ZbbRaAh4CzSf5/kFod4wBHa7
ieX+yMPTp9zePG7UJaKel6xp4XanbNDr3V5/RvDsp4ikldcevcI4/jyTG0jrjJNbnrzyRCnZkgle
2O8P2p97XdlrzpzfecowTty9/ZR5vuOwv+bzv/iLlA8RRHGnnDg9HHWDs2RCEYfkBpBXO8XVZa06
uD5cKUXcOBXKGl0p5WyAt2N32FNSQpwjlUS1KiTPD5S6Kndm1rawlKKJirkyTnuqrCA7nj3cd7B0
f3VgXldO5zvGYWeyA/OBsVTFUivBOXxVjKRpYKqlPDY1tq4x6YpkJ1swHNQ+2tU6Gpy0BAOB6i7W
qpHbHF3fA4HQDaT0e6ZqJMKsUR9xmGhDAsAcDPnkqkzk4qJf7t6uFsTQbh8cxajgzrQMqWQ13THD
YCdeGYMixvxTG8MsW/avs3Cd9vM6J0IcwRVlvAa1W0SEMYx8x3/7hxl2EecrUoRxHCwnpbIbA+tp
2ewAXQDThtS1si5n7YvTopm208RgEoDgHFL1oUlrIXitmPDq1SJpxTn1TJmmqdOv85IRy/998823
+Iwv+Cxt31JlnCIsAzUvDNFxfbXn6TvPOewHpt0BH/W0Ph6PjEPk8fWVusBTiXEgCMRxIi8zu+sD
IQT2e8UxwLHcH8k589Ybb/JZ/+AHefLks6ilkOaF4ByvP3nCejxzPB/x0bCB0ZMTTJM+KNkJZAhD
xPuqTOOiGFkuZnKElvO7/ZXmDN/ecH86cjVd8fTZW0zDpBVqztScidZGBdQgSDJMh4kYRkIUzucz
p9MR56XHrmYRUprBRa53O+akNg/KNDVQ11edqtn41aPmVcOFkTQoy7o59jkJ1IJ6ikgl14VoTFZE
xalevK7pbkkg3XrUiU65RDJ5NXXxhQYIlAPjh2jjY4h+7BuuKijkQmH8cp7Td8Vm0sg3Fj6nrELn
euXYTmQdHweyJDVQKhV8oNTUpz/RD52hWZ0nSKU0gaCuoY2h6UVZrTnjQtW+lUooTlPgpPJt//V/
wpUU9tM16/1zrvYHkmTyUbNdTg/KHm2VxzQNpMUmRQJj8MqP2F1TJTMvukjXZHT0ITJUT8qrVSeO
4AI1VaUmzOqZ4o2LQVTlc1qE/U5P2bSuekpiYjALeZqC59HNgbIuPDzcMXgdkyZ00uWpHIbAOw+F
Gx8py8L+9VeVnxKVrSoilJJxBe6fPyXnzP3Dc/6Jf/LLlBPjI3k+U4sGkl/trlhOZ8ZxwIk+BGVN
HK5vOJ4USHVSEamUdMa7UbkvOCj6YOS0IESGIVDyqgrtWtmPEz7A7fUtTiqnk/JGaozEqNd5XVfG
nW6Cy7KQ10Suid3VTquUsrLfReackHVl8pFzKnzou76dL/gt/xSgkySd7gmhegqJINqOpFqMvr65
qamezHVwuK8vp1YMgxO48KlRnVczllL5QqkXWc7OdQDVR3WKQ0ofTbuqDoBdfNkiR9t0075Hc7h/
WZXJJ7zQD0BaC1DpCfR6+Q1Ian4ZTklCTQrfbtzgNW9Vp2tirmyDmT0r6q6eq+a4XvWmSRZTClvE
hmjyXtPXDCESzkeW+QT5zHLOpLnwcHfHvC48v3/g6bMH7p6feLifuX+YefONpxxPM+fzWTebNeHD
xFKS9t7Bc38+UZxnlkJOlYd5oQq6wEU4LydSytRUoK5dI1PSQr5fSUtmlcIxLdbQBAXfbFOexj3R
VYarPeM48p73vk5ez4gPVMkMzrEfD+z3Ezc3V7z91h0+BNZ54fxwxvnCK0+eEJ0nHxeWuwfunj3n
/v6IC/BlX/ZlRByHcWDvPfPxgXfefptX3/Ne0qyamcePXmV/OLDb64k5r2dGr5KFnFSUqHRym1IA
IoHoRnJxmlNsNPhx3JOWhbQoxuOqEMeJ1157jTAMiBdyrngcp+XEcj5yvL8npYVh0k0mLWfEvGhz
Kazr2gloBI+89fOEuoG6roo66eH7VE83eunrTJW/UT+ni+/Y1MbWLlXZRrlKxDNFtwvd0mEwrxet
UswMrOh7Ka7SDKpcAAmeYWitkOqGqmRyWWmZSLgLFftLigj9hK9MHBpG1dDnyzk9dlNrE6qJisBy
1QcnXtgQDP5g1O4KOVHci+l9elGNuOQrnhHvK6VAExLiJ+2Xq0cQfvpHfphcA3lJ1LcfVP6+3rEs
Z6ZpTykOJ5arIkKiso87XBDW82oalIHhaoQlISQQzYPJOeOlskSPlJV5LQxj1PYjDKxaf4E2AAAg
AElEQVRFH8qaEgdzHlN2pQJ302Fil3b81n/+n8EPkfv7e/a7K9776ms8ff4m0/4xa0lcX92QSbzv
ve+H4EjzwprOnOYjRTyHwzU1F54+fc6rh4lVFh4Nr0ER5rsHTscj09Ut01SYdoEv+Ic+j5oL0zBy
d/+MUgrz8YEv+uIvRpwwjCOn+zuur6+JU+DhJFyFUauGmvDDiK+Vdc2wFKqo67z3YjiNY8yOGidE
tP077CxczAcOh4ndMHFeZ/N63bMbJsQHooPXR69GSKczBeF8yhwO1+x2kfN61imUq9wcrjivC7kW
QvCsaWEFxotjXDVXkSpJqwIdEWp4uFcdzpZZ3Tx10XWmg14DTRXv0I0l67j/MvXRvk9r6UUyMarf
rcMzVL+JADH+UVaZQ3dtK6VXtnK5Kbra6Rcf7+sTfjNRarw3TYbekKa/8T5QfFIw1UVqzhCC+oh4
h3SDZ/BOH7Y2Aeger6IAb23RFd2vNVGKgVRVWZG5ZgXcRHBx4Lv/4l/AZ2E5Z/JaSMvZ2KpCZeXu
6TPibk/0SmnXHjUpLdwLMo64ksj5KftxYJDINE08v39gGiLjFPFF2ylCJdeKEJjLyrqUrpRenz9n
GBVMvt7fKlZwTjy5fkyZMy5rX53nMx/96Ed18jLt2A8Td/fPlbFZMzVXpt3Em2/8DN4PuKtrXn3y
iDB4nr75Bvm9r3A97UnrTE3qDIZ3fPSNN/De85u/6AvxqKr1dDrhQ+Ctt94ipdLV3NrSjSzrmYfT
zH6/JwTP+XxkLZUhVGuPAjWjBlFBT/79tCOEwHFeGCRQinrfLnbdg5H5lpwIJnSL1eGHgTUtVO85
nxeGYWJ/fcV+3HP75Ja7p3ccj/d47ywnR/OSSjkpKYxKqYXT/TPik9e0nQ5BzZHIOK96pJJtrTpP
MCatkqTVFye6pplxHVxucZ6+TSMrSl7kIusJjTwBTWkYwoizKiUg4D0tW7ElWDa/mMvJVwPn1czT
s5S1pyC8jNcnfpvjHDkJF1SzXiJW2bw31N/UPFGjwzsz9LHWJ9cCvnmoBqZBR4mNilxNSNg8NKUD
YUCIKO3H9Y8HSYSycHd3x5oyOQtLEh5OieN54TxnXJgoONacLGhcRWshOpaUNTO3CLkU7o8Lz48n
7h9OpJpIVO6PDxzXlSSFeRVyrWSXjWtTKTWTSiLVSk66Ud4fT7z11lssxxP379yTloQILPNMXgrz
8cQ8zzw8f87xdEcQIa+ZMQzshj3zvHB6uON8fuDJkydUV5nPJ+a18vrrr3M+PfSFen/UKqykM1/y
hZ9DlZV1WdReIATunj+HkvngBz/Ish6pJXE83pvcwbEbIw8PdzaR0VH8EHXC5WvpI30pmyF4WVOv
IHfjXgHRGki5UirUpCC0j4E1F9aSyCl1ADz6ATRdgyyZ+/t7wui4eXzDsJtYy2oA/crV1ZWqiqkM
MfKRH/mhrlQHbVeaOLDZVdSqimYRM4V2GzCakd4OIaKti1g2j/nt+sEc70VpDC0PudHfB2PLJjPy
qk7H6a5KB3hh24hablP7M2CG5WqLkD+pLAhE8IOOawtVNQtkgptMkCcdYGpEpZxzj7Dsdohex8ge
3VyKJHOu0oc8WguVSyHG5sXqKZI00a+p11BuiXNwyuo9+zA/MA6ReV7Ul5NCRen7Gk+q/JXaZvsU
Bc6cZ9hNzMcTcXCMw6AbSfXkemKMA25d8MOgp+CqfqU1Z4L3nOaZYRgNsXeMfmJOJ3bTSMqFlGZS
GchVGMeAt3FyzoVUK/NpVd1T9AYSCzVpe7i/eY1ajdRVKq+8fk1eE+95/3t0UpZUqXz//I4v+sLP
Q2qiFnVAO5/P3D97rspiEdZ1JrrIw3ri0e2rHI/PIVruLVBWHZXv9lc2JYPgPH7wyGJRr7kwTJFc
VfC4v1La/DiO3N09Y9hNSh9wiatxR6iqApYihBiIu0mZu17FMCHoxCOBpg96T02Zm5tHUDN3d3e4
MFBKYgiONWUe3vxZQoCcN1sFEVMT59I5MUtO+La2xELhqunL3Kau7uFdGMYS6hYh0j5XF7HRI1q7
D4iS+KSaYXqVbZMIirmo96vxYkRwrkkZoOLBFbx7efXEJ/5mAt3I10voaX1CwXuLSlRvQKSqZV/j
PHgbA3t/QQYSaA5UbVRbSrJNZeOcKBajfSZFb5reXI+XyvPnd4zAAiosS4lxmqilEH1EKoRxsCBy
FbyFcdCSVIS0FtwYePpwR5CCpIE8qyP87fUjkqh8PZWF0zIrIU0K86xszgTU6iirUuKfn++5Oeh2
+TAnak4cDge8RUOIjJzXlcO0o3lnLMvMuBvJc8ZHr6V4iHzKb/pMvPcc74+MLrC/vWY/HXBeuLu7
4/TwnFdeeZX99RWPn9wyhEE3gOA4P9xzPs6cz0dSXrl59JhhGLrnxmk+4sNAksqyzMSw4zifmaah
34d1Oauoz2sc6JoWQhjttNUHRs2SVd18e3urQWhLNvNp9bFtrY+Oxc9WRQRC3Bzca8rKtg2BOCgZ
sebEfnfF+XzGU1mLMA2RdZ6psuLCYKZHVb34awbvL6w4feeqZYHBqmNE7TZhqxaADQdspETvzYi6
cVSCTjFtYtkMvodhMGGgrnkd84aeDRWMHevQA1DM57hdH70GL2mUw7uhzUEvtpojmXWj/f6NEJRz
JdXUncNbIFXOGXwLkrad3Gm14o25mk0s2A2OjTzUM3GyirlAmYONvBaC4zSfCUGFX3Ec8N4z7Hf9
fenYVEveZGO51l613FxfI+O0pzjHuWR8HEhlJefK6TSzrBrpMK8Ly5LIFdacOc0rqyhbNNfCuJuo
rnJaTqxFPUnmeeb+fOL+fGJdZ44PZ87nhdNx1inWMDLurhimkWWeqalQa6GuC3VduJ4i7331Nb72
K34XH/zU17g57EnLiVcePwHvOR7vub2+AVc2hzLnOM8PzGlh2h+4vb2lVt2UU0pUHEta1RMWx5xW
E2GqK5sTOOyvub55pJKFkgg+4kSd2WJUX1dc6SW/H6Kqg6OzNDunRliyxYG4ECliFWrZQNFGiOyJ
joazpXVVl7qqU6AG1p/eeptmiNQyj0pRN7NwAWW2sfDgXa9ALgkdDcurtW6GScaGbWtRqx7p+dBt
hluNoLmR2PzFmjNWrlEpaq2dW+WdGoC3qqdNhl7W611Qmbjuol2dTjtwKtGWksD67Jw1f7hlpjQV
aGiLCfqicSjNXgAnBe8CYnhMKaIGN4atgDmeZ02ui85C0YcJL5G1JnJd8VXduyIQp8iyCEUKy7Jw
uL4iRP3ZDxa03fQicbgId/I61jutSXkEprOotbLf7zWPZ4jIqi71Tqw9i8JQhGOZ1ek8BB7KmWLh
Ut573pxnduOeN05vMcbIuH8Pz58/Z15O7McRNwyIVNbzwrjfQVbjpWpg95d87ucDcF72vHn3Njln
Hj9+RBwcD3cn9vs96+nMw90zTqeZqyePkVIVfHXCuiYEz3o+9kwgb9L4wQdyqvgolFSYre1oJ52L
gTEGigipJMaolWCcogKZaUVWb3qoyHk5URbHeBi59mpfEBwkU8sq/tAiU8beQmMVSqnOTnENsBdp
h83A//ldf4nf8q98ta6RavGucYQL7EGqCiZbZIW7qEaCV+JktrjbZiWBcT7iYDaN0utnklSCDwbA
t9ydzUC9URc2JrduTC3vqYpODdvG2qc5OX1yGUo3ZYKa3dBTyPSUs/LN6Mrq2aBu8U3M1dzeP1Zq
nbPqX6RqyLYb1NmsJdo38+DojLTmHEjs7dF+GHF7DVNPKVG9CgLXsmXVTiFyfX1tN1FPZMUbEnG0
qU9V17R1XfpGWGtllUQSYU6ZXArLmjmvSReYC6S1cC5FnfWLI4syhcdpz5rtwYiRddVEOxHHuq7/
H3lvGmvZmt53/d5prbX3Oaeq7tB9+3a3O8FNO1EMigVm/JAYCSnIRDKDQAxSRKLESJgICSQQImRQ
YviAYkQS4SEO2JFsx7EUIzvEsREg+QNxIB+IMgChnbbdfbvvUFVn2Hut9c4vH553rX2u1bKb9JV9
W15SqapOnTp1au+1nvd5nv+EcyOpFN557105CWPh9uEBrcSgqSmD0Q7vI95njB6FK5FESTvpgU9/
9Ot45XDN1TQyP6w47Xj57jssy5l5XZkOR0Ytzmnip2HJRXXIU4yevBdEaF0Wea90ldhRvbnngVK2
Z8l0VKOC1fYyiipF8Ks8yC2jKByODtMqV1cHasyk2jjNC0uMlP7g2MHt90NOFaUKCgdFOCGtSPFp
tRtltUTLGkOC80yu7J3uYOwlzlWxoy5iMHVhULfWLmFrSha6Ruv+M7ux0oX60LODezdScsZtTn/A
hsmYriTenolSLt3V/gTVbmPKFkrXuVq9qH9Qg87XQGfSLyWCvtL9WOVmaJ3VOqBVpDQN+pKLU5sg
OtDn4ybdyOMogdZPqVL6+KRUvzmE35JqAQ2VhNGPTH6UtOgtZ+x4pJaKtgpdNCUVimqsScYPo2Vu
T6EwjOJYv1kKTleTLPu0zL/OWZTS1NxoupCKLNxSigzaEEMGMrZbCngfUYjLV+1pbbInkNn56auv
9JDvhI+rzNYNyips0xgCIa6sPnN1dcVpjaw5cj55nt08QycxH2opc5gmQvL4EHl6vCb7hFLgfcC6
A+/dvSdSAu3IKIZBFLghBFTTrD4wDJYWM8Moi2OroBgxI4reM44HUqnk2oCIQ0sB1WIGpHoxEp+Z
zPWTG2q5cI/W8yInsl8x1hHCilVWRgMHy7IyjqOowo3GakBbSkqdKj9wOF7j1xlYcc4QUhHxZVQk
1ZhaJGBAyf0hYkGN7VlEpZUdydk6AqM1Vom59Lb7yDRUd/1TSu1diXQPFkwfqZXAT62IXkch+5PN
ea+UnsSwFYlH/CkQm466iwYFl6w5Y5whRv8BsUy+JjoT2ba3KuzU3WSX96suU5WKD+ytOU0S6bdt
Of3nx25f28e26IItNmBPU2vdmqNdWLcK0LXx23/HP481jtZgDYGcM74EydlVjdqXtuu6CgxMI6ZG
SB7VxV2nhzO5JmpLFBq+w5gYTYoVtNwU6zxzmhdiqoSUKbUSk7SpVRsqFlUbqURKywzDRTyWcybX
hBkHFu8JybPEwv3pxMu7W1YvERvPX77E+wV/jtRUefXV12hoHk4rPhfefe8597cnqIbSwGhLDRk/
B9566y2UsQQvXdnty+eU0vAhsK6BeV2otXK/LALV9xxgHxbYxiHjSFv0aG20UvFJJPelJmqVB945
SylZ9khroOQsCI3WHI4Th8MBqzTXzpF7Hs+yLCQfkLFVU0ompMgaAvMiZkg+igo7Nxknau8ox+Eg
3A4Dqml+4ge+X1IctaT4mSbiz0Ijlyj3h1Lo5uT77u73udtZbBk4BoW10sHJULWZRbOjlFs8Rt1C
GB8RLHOJbP672/Ow3c87jb7K4ai0sKRbFWKc1tLJDMP0gT2nXxOdSdOmc0vE/dtum/PeoiktJ4MA
NUpS1FrdyWLiSi8zqurLqVDynomjDeRacMpQkDcjpnRpBeuFgCRiKTGk/md+5+/ib/1vf424eEEE
tKO2TIhJ7ACVjBY7ca6fFFpb8WIdBow1tCrCPzEYNixBFMCizRlEJNfZi7NfsUpUxaUrjMdxJLbC
5AZyabRYGYaKj4FjuaYi9HLVQNvGukYOVxM+BBqaVDLhPNMKnOfQBVCV5y9vGZ3j6nhDS5lWA9fH
G4I/8ezZE1LvEq+HkZNx3N8vXN1cE8MsXqrei8o2S3C4c47kA8OTm72YKCNCRToS57porfUOq7VG
9AE7jTSVKTX26A7LMFjJ+y2NnANai68qiDxiCZ6nT54QkhdGaVWsJZJzAVU4Xj9hGBW6icvcNI5U
Gr5zc6zTrCmhN75SEXj1ydgwunXqR9/HtX7UKHORejRx/Gu6UGs3W+r3wdYNpLx1JttIqPfOwyiJ
GdlG6/ZoB6Ob7GzQ7F0Z/XOsklGtKalATQmRs200emXFxgC1B3d9ENev2pkopf47pdS7Sqm//ehj
f1Qp9ZZS6v/sP7710Z/9p0qpzyql/h+l1O969PF/XCn1t/qf/Sn1y5cYv9I32eoe4YiRQrIrHgGJ
v1TQt/vb6mwPUNq8NPvnx5REr9NPwVYVBrOjOK5HXyj9/tmzbjZ33SQ2tsTv/8/+GEWLoHBNoucw
g5hPxxhZV08IIka7P4sfR0qJVBulNIKXTiTF3m3EiHNS42OMtFwuJ44Whm5V8LDMxFpYvYj05sWz
BE8hkRrcz56zD9yeHjifz8zzyvOXtyw+UDXcn85kVYi1yliRpQiezys0wxoyOVcezmeW4Lmfz7x3
e8dbb/8C8+L50i9+jof33qOWQm6Njzx9ldFJHEND92KySHHve67z+czxOBFXTylFKPOl77+qnLSx
F5nWyq6zoseJhChIDQgpMWUZI6jdREh3s6BaWILH+8g8z6RYJAy9P0BGaQZ7xXqeSbEJulQLIXtR
YE8OY9TOZla9Sz1OB+FspITqI2XrhMnNZ3U7MPpN3+/By66j5dLpDPKeGmMk7xqZ5BRdb2a4FKVS
dvuIxzuOrYjsO8G20Rf6qIvwSowxuxZnZ5D3+6lwub+/2usrGXN+APgXvszH/+vW2jf1H38FQCn1
24B/A/jG/nf+W3XBnr4b+APAZ/qPL/c1v+xVK7tHxIYCAPt2GiXCMNV9NZTqBWXLiVXtUt1b23cl
m7AO6Cl1Qiwr26a99ryRngWsOvu1KnnhjHYoKt/+h/9L1DDihgntBk6n065k3dr2x74pKYklwbqu
1JaJWeIsSylk1YhZktrsYcCnCE1j3EhDCmlqUGvD+0CpmdbRKR8Sq4+sKbFGQYvm1TP7ldv7e9YQ
QGtSy2iniQExjk6V+3PYu6j78wllDfO6EEsllcjZJ37zb/tmXvv0P4Z++jFe/0f/CfLVxHJ7hzGa
WgtPpiPL4olR4N4QEiF5zvMqVgBVNCM7itLE/T/ETC2yDN1gXLEfQGQRSsbbaTpw0WeZjhYlGT+U
Yo2BmDNmHHHjwJbQmJMsrmOMhNWTa+bsT2KpoDQlCww8DFayplUjhJV1lf3KaAXGF2atRanG//Ij
3y02oe6ye2v6EkdrjHnfgypjh9of6G2xunUhUjg6kqPUTl1Q/T7bxpkmN/5eRKBnUzdBnkA4UqX7
+Ozs8LzxKer7DsjHv/5qr1+1mLTWfhZ4+RV+vW8D/kJrLbTWPgd8FvgnlVJvAk9aaz/X5Lv/88C/
9JV+k8pe+AKUbpizPfCwv1AbgWfbhaSc9/S+DRreFKjQuQBZ5tjUVcWUuncewN6dNCUxnxvprPZM
2NoUx6sn/Pv/+Xfy3nIWvYNz+xuYcyXmTPCRVoVOXxBTH+8XTvNKaYqQCiFlUSpXMM5Qi7Sua1pJ
YYXacHYEEPTHGZYYSVQeToH7eebu4YSPnpgDzUiHYN0BNxxkV1Ei59ULbb/IzmBZBUb2uVG1IVXF
w7zIKHhzxFy/wrOPvMmyntG1cDweuXv7jk/8lm/k+MlPspxmtBOeTQqRsEZu7x7IpbEsi3RTFHwM
0o2FxOxP4hnSvW9zLdhh7AHkEqFREWMgY3vQGdLWGwuVjHViHwki/RdzcMmfSVHU0jFJgHdJFWcG
jLOE1TOZAarsOLYHsdZKCZ5WJEjcGANNiv40HUkpCIaiNSOdK1kulILSR+n+3Mi4oS+amNounW7b
7j8uaQZmVxbXfRzaDsuN7bQhMtu/wZaUoOpu74gRFjgqvm8Z23oAncF0xJP3d1Jf5fXV7Ez+oFLq
9wB/A/iPWmu3wCeAn3v0OV/oH0v917/841/2Ukp9O/DtAB9/82NitYeRGVBrdBVYrLW+tLLIstXA
5qIGlwWr0uKcnrnEVyotfze3btyruruVUl1CLoJAqzWtiLpSTJQ7TTqXPsMKxd8cR/74n/lefu5n
f5af+aH/HqM0IYeOLMnIYq1YOEJHnIwlh4Rvi6hlrfiVmmmUVwx2ElOh0FLk6dXTnZsy+5WUGvVh
ljhPGiFKu67I1HrqOhdxnospkx8WWtM0U6khYbURT1stLnDr6vf4UOMMS2qMUeZwv6xk3fAPDwyj
4b1fypyWewZtqT5ilOb64PilL77H8ebAMEzkXKg1UorCDhPzKqI83Swpe9kZdXJZqglTIJWG1fIC
CMtTfm31QE7dHKk7jxkabhgpOUlLrx0+rt2EWvXANlEd5xyA3h2oToOvCuuUWEXuVgLijKfqRMQz
Gkcr654saZwh5cSVsyw9k0ebSqtKzJK4JPWJ8+fjEPJ+j9PHmNb2nJuNvKa16aBBgebI3fRLK2hN
ZCFVK8hF9n5aumohNks2sdEX+HsjwRljoObd6+QSXPfBdCf/oGXpu4GvB74J+BLwJz+Q76ZfrbXv
a619c2vtm1999RVokgdS6UZJffGFUqhWLvh7fyHlxWu7FqKUQqwKXcz+AopGQlrCZipNWcyWpta7
n13Yp7ao0cJlVLrQ8S8bdcU/9Tt/B//Jd/1pUq6cz57TOfJwfujGPBk/r+TUyKnt3dbDvDA/3LPM
npgr8xw4n0WQF0KQZVwPHYsxcw7i5TGN150J2QhLYPFZArtqoVRBYdY1sPqIj4GcKnf3Z2Y/k1eB
GtdVPu7X3E/XQsiJpmA4XlHqxl8oLMtCnhOLX4hr5MUXb2lVcbh5wrIszOtCyY119Tx/7yX3D2dy
bVTToCcrllJ2rk0tmlISJQjnx7SBYqVbyH0xWYpk/tQi7/Hmc1u6CrtVLaNOE2/dZT0TVt9jOuXh
ffLkBmcMRola93Ace9eYKX3kVDrienh5raIX0kZGDG0q1kw9JF6MjjSK/+nHf/j9SIq5BIHvXUW/
NlHq48/X/UdrwnLVOxt3G00UDUGwtmu7p3UqWLfJNdr+IFu9ObxlMQXru7+d69KJeAqzH3Qf1Nrk
H6gzaa29s/1aKfVngb/cf/sW8HWPPvWT/WNv9V//8o9/RZc2jZYhdtd4QVgkuQxtKP0h3wlCXNiG
gunLC16UQncHcNX6vKnkaykkbrH/n1Ba1KIa0z0t+szci1ipomvYYGelwFnDT33Pn+Ll3Us+9nTi
jScjRWvu7k/cPcycTi+YpmuUzxxHCc4ahgGjrZhNxwIxk63A2sBOu18Wj1G6M0oVpSTGEexgKF4e
2BYLkcZQLaEWlHXUpkgpk/MseSvKkmMBHUlFnOfQlRQz46T6rskS6oJaLdpYUg6iYUkRMw60VplX
j1EVf6u4fXGLX8/cDAPLKnsbozXr6smqMZUDZYo9qgHWdd2zcWuWQDWnDFkHXFQMQ9fhpIIe3a74
XteVq6srULJobUoOD0vPsdHyMGklxPZhHGhK/HHnuDAMA5M7UIu8rtv4pGpBK9EPGQxKF66OAzEV
cOJ6p7QUOa2tIH+DZbl/sdPtUQpVhNe0lZRNY6OUwjYj6ZBK9QziAk1QQY1EpTpliHvaZH1fEXmM
VrQmLO1aikgDOihhrRU5gboo3MtuLCbjmIhic+dXdR3Rr6efiVLqzdbal/pv/2VgQ3p+AvhhpdR3
AR9HFq3/e2utKKUelFL/NPDXgd8D/Omv9N9rVbxE9MY27C9Ea5lqjBDGOuNzi/aslT0y4PHGW9zp
+8e6US+67aSeHWarbfeJUNZ0xxth2W5q4x2QygmrGj/9fd9Lzmc+9nTg2fBRDuMR5wwxeXysvPXO
C6oa+cIX3uLufMLPXohrBwva7vO/M4bBid9rrTBMlZoUpQYO45GUE1pJp/Ds2TPW2gBLrFG4GWvA
jY7gPaGjU1prQgqUVnHGEjpc2eMRMba7dm1+GHogkTmakZgzqkSc0syLx2qDItGanKBmkOXhmiPn
8yJ7opqZQ+a1pzco3Tu9Ydgp5tSK7jaEDbEMWJNHDwdyFG5JBhxgtREPECfOY6VkGTurSCswGoVo
TloWNMP293sYB7JKvH54TaI41GXs9KeF4/EIXfOjqdQiYj1qonWrRGMPgkRNB4HeW2FdI844jtPI
eVlFdAr7vq12BMdo2Z+l3QGwx1JUwXwV9D2JIhaBhnf4eOuCewD61mVvV91UwbB3M03LwSau9ZIr
LPsboaupJrnb0qmUPtp/pU/ir3z9qsVEKfUjwLcAryulvgD8EeBblFLfhDRIvwD8uwCttb+jlPqL
wN8FMvAdbbd1599DkKED8FP9x1d0bZVYdb3EtjRVQvzYW79tDi05YuyAVpes1s2MN3X5vrhdWRIF
W/tSVSHWgUUk/VsRMihKt4GsW7TG/ucJ2zI/90Pfz5Mho6cjqiVuDjciBrOKp9dPOc1nPv76p/Eh
8olXLYerV3jvnXdZ64G//Xf+L9aHM7e1cXN1JFCZBhicpuSGX7NAxNYwzzMVcRpXVfHwcKaUwjgd
hYMzCJM2BvFaubl+AkZRoowFVsvOYAl+N2aOKVK8mB1J5ye7m9FoaivMc0aVytCtFMz2MCgJCzsM
B8w08uLd59z7iGwmFLllzvPKq688IddKWlcGKyhNKJWWulpbm65VGtDW4PoDaJ2jFchKuCV2HGU/
0ZMQlYKmNDEG7DDgjPCRSs1UI2Pn/e1d93YtKG13VM0ZxZObZ4AEthljCKuMWzc3N+QsYkltIMbC
MNhu/dhQRaH73uvH/vz38q3/+u8Tk+d+n24K81JkrybCRBEhbuiiYL/bCF3ErriPOMbIPag3prfV
qCLFbRtXHhPUNKXHnF6W0NJ954vPSkGIfc6Jl26p8rCYX0M/k9bav/llPvznfoXP/07gO7/Mx/8G
8I/8//ru+iUPNNBbRWV093DIO8YvbE+ZCTffh60ggMBvO9be2YFaa9y2e1HiBi++ou1ikoRwCTZt
g1ZalqhNoaic33mPv/tTP44mMA2G2hJXV1dCghpG8TbJhRuuOV5fMc4BOzoMGmteYw2R42//DLkE
XtyfOK+Vn/+FL/L8nRXlMq+99hrUyPXhAMmilTxkJUleTQwLWluUl0iM7D3WSREWygYAACAASURB
VJbx0GM0vY+MVtzAqgIf5XHPuVC1uPiD0NRjjJjJdh2JYplXSF2xag26GyaXmqVDaRDuQs8panz+
7eeM48hgDfMi4eNutFwdhKBXcqWZhnPj7oRfiqQMtBJRqYnKVVVaypjpQK0K031VadBUj7TIjZQD
1o60UoVUhqBhmobtESFaa4wypCKLVdt3MfQurNRMqxnnFFoPpBTAOtLqMaXHo1BxzrCuGTcIFD/7
Ex89GrRpaDRW9zDxTd3+iIC2/Z5tV/fo/ha/Yt5HW9hel81CYUtm2O5rHnXbG+0BLQvfHe3RSsbl
5tBdF5R7FvRWsEz7DabN2RaVwjHpFbnmC9RWJSFt24Lvkm/YsX15I9TOQhQ1LjsJrT4i8giNsvMA
Hu9iajf06XsXHm75mz/5IxwPBnmHFM+unxFj5Hg80oosBfXkMKaRY8IdJl7Ro3xNC8/qNZ98Q7HM
nm+wFh89n/n0x/Axcvee5+d//hd5fufxY2I6jhymCR9mpmmk+CLhXqVSyypeIKX0AK1Kqa3rfSRa
QTxnFdooDvZAzZnYW94QAnTvlrhE3GHAe48pBrLYLubYZCeBouXEXBLXxyvWuJBK5fZhRg8jufZx
IYkxkFg1jqhUGQaLUt0tvkRUVdhhIKUFpQ5UDY0kYeNaRJYbuXA0V9LVpMwye0bn2OMvOwoXfFfp
ITsWN07UWhmHgVokrDxHT86V43SgJE/qS2FjJFcmJTmw7SBclqHHZMTe3ZlBk1Plajrg8yq+Nq3S
ivCcmm5oJdR7KYBKSL71wvHYCJL00Xs70HbtV604pUUpXCsYI/euqrT6finJ7vC2LVlKRXXExmjZ
zW2BYQqD5mJzUDbm7gdwfe0UE/1+wg50KXZ/IR+/EXtVH4b984X2LJnDQkoTT4wCqC7VlmDxum/m
Wy40ZDnYoNPu++LKWv7nH/1zHEbB9EvLjONAU4oYMtMggrXSncFqLUzjFakGDodjf7A31/jGk5sb
UIqb4xWvXj3l5GfyG4rP/ObXefvlu9y+KLz9/D3e+tIXmYaRsBw5Xl9RtWQbb25hKScmBqxzDJuv
bWE3J9KqUXJhzjNuGDpDU9TVIWa0EjZpWFaKmjB7EHtF4ygds7b9tbidT2hnWXzivdkzukEWuaX2
k9XRmuTXTJMU0WfPnuBTJEVRxlpEn3KcJnIV43DYvmfhyrSaiWFl4oimkVIfGYwcIEY1cuo+H11b
c3W8JjcwBkKONNVY1gem6YglE9YzFc3kJolyRcK/Wq0cr8QcyRrL+XwHWJSptFI4nWSMLj5gzcBf
/aEf5Fv+7X+ns07bjtC0Pi5D2zOc4JLhpOjT4nbv9j1JqXXPwtk7EBCIXElR2Z6Lx1T6/TK6K6/F
PF27gUYT+v2GcpaK1qpz534dF7C/ltfWwpWa91ZPIMO08xOk+l8yQayGpgbR4zR5c4wxZHQfT7ok
u9muSb2MQjt8VxvN6G0/2dmI4rJWVON//b7/hpoTSWtqPxBqbdze3pPXjEbMeWqr1BqYhgOn8wPW
SWDVOI5y8hvDk6sbfPKyD0CRdOMV9wRjLfNh4GOvPiF9xjDPK7e3t3zpnTv+37//Fqe7lbN/ySvX
1xyur/ApSrB2SoSOcOUsEvumFGsQC8JSCnqQIKmr6YaHh7uOSFT0MFGr4uEceTplzikyOXmYRwe6
O5j5kLFWkVYhpn3h5S2vvPIKJUdybVKAteb+NHM8Tl2MWbrfSMIojTMDKawyYmpHrRGnpx1Vs3aQ
TiTEPabDpwWrrRC0akUbSw6ZYg0GWcQfBrF09GElFUHMrHXk3IVtpe8SapP0P2ewdiB2NfKhd2W0
xmANdhgxTZFaoqkmznqxYO1ARmE5k6OMRhrVjbH7jq3v9PRGMzCNiiiMcwLr+h6wFwNBp8S7ZLun
NyvSjUwua0gJ4ZIla9sLsPz5xZTLdCkCNffnw9C0kQhcpIPZ2Lhf7fWhLyYbGuO0nHAAtVUGM4gv
ai8UO1U9CwYgdnQSFC1MRs2A6GvEBk/c6rdCJP/YpTi1JqY31SpsRyO29rJmz92X3uHq6UhJ4qGq
jCYswtnQ2nD/cN7Nj84PhTD0RZcq1KpJcd3FgKfTielqkiS+JqfX8VqYrhNPWMKMc45Xrg7cHB2f
fPN1vuHr3+T5y5eU+lv5vz/7eT7/eQHXDldXoCtTMUJOUtK2l66/icpyODhCaLQSWeYXGGPwfmW0
Iyc/MwfPyMAX10wtgeMwAo3BZUalMCbKArQqvKq8OwfG6UrEi871tl0zjQeGUWTux6unGGsZBhk7
KtJ5jONISQHjRhZfuL4Gqoxk25JxHEdirkzGkWqltIKzDqMMOQaqUlilqaWSaBQvVp5qQ2OMpaTI
NHZeRo/11N0lb1tqGjdSsydGgxkMzloewnl3S9skGKo29ORYlyD8pFRJITE4Q20apxC9kBJWh6pC
YdiMTwS80ShdaNX2iIzWRXoDVSt0zeiNB8LFWW2z35Co1Ulyg0GC2PQl8mLbtaiq0UZjrRR0o7Uo
yK3YoKrGBZX8Kq8PfTGhbXDtlhnctTfqQgUWbUJfcilhMG4O4ptwShtFrpsFnyg+xS8zY8ylqu/c
ACOJaopKSp1/ggimDsbRSJxOGXXdM2tqIw9yojnt+gMaRe1aK6kWNJWQHONkBGFIhRQTh+OA9xFt
NeMw4jZxWMnEEpimCa01gyoM7pqYE68/u+LjbzwhhMQ3fPqT3N/e8eL2OXd+4ItvvcPNYeQXvvic
03ymNkONhaw1Oa9MqyT7NQUlV4ZRBG3zei+LzAZriUzTRPRxn8vnOXM9TJQaGAbpLOZUyGtFq0DZ
Fpt6RJlKaZlalYR71dqRpoQ1ZteRAOKpqpRYC6SEcY6hWlkW9vdxGqa9c1NKg2bvJGqV+NFxHNHA
EjxOG8bDQZi1JWG0xufCZJ1A0rUSU2AaHc5qFE7+X8cbsSZYV7I2Uoia+MoYZSQVoGRiTL3IFYKq
/LWf/kv8c9/2b9E5jFD7IlRD7R7FahfZyYGyAQdt4yvpJoFzCIq2C3r7GGO7m72M4uZCSlOCwAGb
PawUF9PjYCj9/rvYnraYyYrOnP5grg9/MVHS1jVtelvbUJ1ivLWAlLorifddUmu798PW9u1wLhsy
kDEbk5VHkQAYMe9CRpvd2VNVjLL85A9+DxmDboUYEkZ3AWAQMlurlZbkFCndXf28Zo4HBznR1EQM
ogU6Ho/72JOjWB20ptD9xNHGYK2MdSllDsdJDJGVwpiRwS6U0pjMDZ/42FN8bqTPvME4TuITGyVw
ahwdIWm+dPseH332KlWJw/z57p7mhFYeQ8B0hzSDwmeJiaBU1tmjjUNrI4l/1wdCSBij8Lnw2V/8
PG8/SBxnCAE9DuRWOTqLVVa4LXMQh/nSSGHpHaWVzq/DplVrSowYpUg+7pGYqSSstqQUsdYxmhFq
ZHAaWw26759ySlxdHfvCNHblLygtQVRRRcgZZwy23/5y4oPSlsRFYe6cIxdPjJnjceqG5bKeuO6B
7bEKke3gH7q1ZI/CUHIf1SoHl9YyRm4zcW1ivQlQc+2v+UDTSaQaKDaiu2LzRxE6fesgwr6boXfM
233NhuR00pqVzrwqOZC1kmhdg+y2Pqjrw19M+qWqQJOlZcRF/hG1XquerSLQrGz2u9FMayhtO+px
ib3Qgv/ILAp9wdrJ0P1mKjTMo/AumkGpxvLuF1E93HxZCoN1xLQKemoN0yAZvLlWjsaSiywSfUiM
o3jFqlY5DuKyZowmV3CdtDZYx5ok51Z3NCnnyjAMsmzVWr7mMGDtkbB6DocbUipoHdHDQFOV4+FI
9IlysIRU+LqPf5SnTyzTMOKc271oHx4eQCsmO3Ba587pmLi9fSEamhAxH/mIELyQEaSkjHderAZy
xH39pxjfeoe3nt9xc3WQHUwPtcotovQNxiph3yIQbSlFso6S8Disg+DDLrKrQ2WaJpoSv5rafU5y
TuRs99dFGS1QtdESoKWUCAe1IXQuS95GFLQgG8aiXSX3ONJhGPblLQib2YeF6XiNUoGUCjF6bm6u
+zhcKd30qBaPG69oeaXpUQ6xIjuJTS/WSkUr03d/XbZRG8bpzsamjyxKVNNcCsM2hpfOclPdgqGU
iyXktu97DC3T/7y07marhE1clMR/1J768EFdXwNOaz3rhq27sP0FU7vMe7NbTCUKXRjxgNiFVW1b
RjlJ/qvCSaitYeyWRSKVPJeyQ85673K2G7l1J/KtuEhOrY+BXMAHaUFjqqxRCFCLX/cZl6rwSyCE
IMFaaySWyuoD87yI90ZKrMGjcuV8PhNj5OHhAa1Fl1Oq9EslV/wiMnmtRZ+ite45yrJAzjny7MmR
8Tjy7PoKpxNvvPKMm8PI9TTRamJwMBrF9eAYrOJoDa88PXI1Gl5/csMbrz/FKLi5HjG6oGul5ZVp
MFhnuHlyZBwMV9cDn/rER/mHPvV1+GXd5f8hr2wiNTH/uRCupKBUQcBKJsUmMHbN+BgxPcohxyQP
I1KstdaUJF1la4VWhAOSWu10/4YzAue2UiW2tUkiou6jS66FdV44jBMlSRzpGhZZIBffw96hpozq
O7lNDZ52iFe4Jbbn1fzVH/0B9DY2bGrzanYDot1FjUuo2O6g1kPjGhd18e7Z0++frbhs9//mpKdq
e2RlKq/r5oOTtkAw5DXYqA7b/ZzqhVH71V5fA52JvPS270mgCryyTR7qkiovI4vIwTf4DJCCUaSb
aXT9REeGUm24Xt13vwnklBBuyZYOqMVr1MniN+aE7uTe0gzjMJDzQqmVmnyHaUUhrK0WSDkHqpb/
T11X6vVBboLWtUNNc393YhitaGZqxEfxaglh3S0WREqvhaXa3cHgEn2gaFxfX+8CPas0h+tpN78u
RQr0zWEipkQcrOhYamXu1PJlWVBKcz6f+Ogbr7OczmhtOc23rPNCa3dk5MFfg8dOI4fJ8OyZ4kvP
hSh3GBzj06Pc3Ipd5r+Roq21IlOokm4nKltDVcKuFc94izGbX0iPcFDy8LfamMYjFUGtnDFdBqEo
uaCU3nOqa21oJDLEWkOOCdUUL2/vGey479E2tuo4jrjBCAKGojlNqo1lPjEdriil4rY6UQsxeRyW
mgVyFTWG7kDA5V7cbEcVnQRLkW5Dawxyn5auK8uPGLPOdSJfAYq47At+1eHljvBsxUVC5OiyE7GI
rFo6+X3XaAUi/vVWDf/aXkaLrqAqWk9T23xLRNCUO9OQzoIUFuvGOdk23pv35sWcRqM7IrSR2S7/
pKM0JR6f9KKi7S4v102IS8o4luVMitKyK+UIuVCV5mEWl7LzsrB4j8+ZUio+RkozQpWfZTm2rit3
9w9gNMFn5uCJtbD4SCiZmKVjSamwBpnjlZIZPYRAKbK/sM6AkkJj+07peDXRmpDHVM+wsU7SBoP3
vPLkaXeFW+Vjy8wWRpVD4vQwc3t7y+ffeos1VZSbePMf/q0cj9ccrm/42JufYHryBGMbV4cDn/rE
m8IPGRwGI3aNIe6j6GjHDr/X3fpxM03KG0LXxCiotEKM4mymjSKXhDIWN3a5RInUmqFKdvTmuTpY
S24yjkmRUeScUK3h15lSEroqBmfIxUvY/PFqpwYowMcoQrhiKLFwc7xGmwGjDMNoCClCMyIDaBVK
42med65So1BL6l6t7OOKNp331LQsZaui5NZDy8vub7JRHeS+Lt23p1JVxapK617DUrBEMyTWFuzK
+p2HwoX8abpaniQet9uY9dVeXxPFRDfQ5cJINYND04Tp2Zpg7cgyb2cS9u6ttYZtlxZw+9iGw8vX
lGIh/hfSpuacJYzaamJLOCWt6EZHbhu5rcBoR85hBW2Y10gMbTdeEsRIWu1UhCtjjNyA85ooLbIu
iZglle3+fBY3tVzIuXLuY9RpXsV+sGS8F0vClGRUAimirTViSMynM96L6U8IgeATOVVqoXcc0jaf
z2dqyjzMZ0yRmy74hRQjJSbxaS2JeZ5pyhFSZj6duXr2OmlWfPLjn+Yjr3wKZ4/YCk+fvkKtiqvr
Eau3KI/M41D4Stu5H9pacWTvIVKbhkpvUHwpEilitgxfha6KFEWq0JRQBOSBrEQfpFjpgRCinPRV
0DijKqoVrAZrBrlXTO2ObrozY8+kEnG2a7r6fXJ1HEjBE0L3UmmKuMr3UEqPNh1GrDX8xF/8EYGE
uwbKGLcbEW1XzeV9VgWXlAQpoKKGv9zvu5NbU4AEf9WigIv9hW4GmkXCxC5+KhdelkRgCCzfIFfK
9vR/QKl+H/oxR4pFYzM6q7VCiihlyVWYj6o2tM6bsFcUk4/ChSqaTT0pyL8oVmuVDX5rlzjFnIUK
bTbVZs0oXIcpZWxZq2ZwlhYlLD139WyOCePEQGdZG1a7HgjmJEOwiVs7qmJSxFhFy0jHpRvGOVop
hBgl+a5J+JbPCU3GGUXzcHM1Mi9nRjNSdSX0myIlxzBMaOtYZr/vlewgnIiD0ZRmeHl7z2uvPuN8
8jRlKLlgnWV5uBdUqghScH86k3NlXhdalfzaj37dpzBmwmiDMoboV5F0Jrrxk8C0g1OE4Dm8/hql
1O7/0pg6z6SkBEYQhVIS0zRRu5BNtYYdLCnl3bDKupFKt+XkEoqVBdag9EWsQxFzgNJEVKyUmCJV
WeaeF482gtSY6cCaK09unkimshGhZ+oWk2PXeN3e39GUuLq11oPcrFDVpzLg10BIEa0M1Z+oWqNy
xlhHodDT1NC124mqkdyy7AL7aLqL+zpztRWRFTTEGnRDLXWD0pfbWl30O7ltOh6BExpabEb7Iaop
GDN0ASAUJ6HopZYPirP24e9MlFKkVKidyPS4ZVNaaPayrWdPMNvpx33m3Ax0abqb66p+kl8MdLYq
blQP8doQnW3R1SFl0Lz5Dd9Irpk1BlLJe2teaiP42OMvlJgFVc2yyIOdatnjK1PXl0zjNdrJyZxK
pTSBWmVpCClkUkosXuwdY0o8zIGQCud1YQ2JeRW04bzM+BhYziulSVyndDGeEFeUs0KQGw68/aXn
YkxU5MR7+623JRxrzSzLwsPDzPm88HD2lCxyAuyAMkcOB4Fe19mTUuJ8nmWJec60KDfwMBrWEDgv
M9ZKxu/jPZZodNQO/bbu9VpKopkLIpGzRF7k5Pe/W0t//xvk7KkponRjsCOpiMlTyImwrh2ala81
d9d/MRBX+NkzdINuN4248YAyssxGVWIqbGZb19dHvI/UWrrg05FSFHd5aziY7ierEi9/8bO7vadq
cgq2qqhYsXlUfaxuogyWRWy5sK/lf4lVbqcubK9R6Twp2KwFutVBJ9NZJbG2ToHqy1cBInqiAz0K
ptMpfmMl+rUOCdNjOpW0epcR5ZJMtlf1/mfbjbqhOkKiynICKJHQGmX7TS4L01zF70G+jlTvzRFL
ISHnv+tf/dcY7ISyViTwIdGUvFnViMFNqoWqe5ZuLuQsD3VtjfO64HNhGEYhlVVIJZNC7AFTjqLA
jSOn9UQulRATyxo5+8gaI3OIPHQ0x/vIvK6k0ri/O7EGzzJ7TvOZxcvntFw4nWZSKrx8+VJc02pj
Wc6c7x+w40hrmodlQQ8T9/NCKoqGJtXC+XzmyauvUWvl/v7E7FdO57M4teUse5scBb5OFYMhR4HN
xbCo7furLcvH7hTwy20YSxZ7iK2YlySLY0UPYBej8DV4SWWs/XComruH+90q02mhwecqO5eCEdGb
Umht8FFynRcfOc0PzOeVVCqLjyiryBVSFv8XCTErHMahExqFCjCOY+eTSTB5qQGrNH/9p360f++y
9N94Ig2hLYg2TB7wFP379iM7sqhEId/612mP7mOlDApHLVzQmCIusduBWrQcri130WuPbAGoqvvG
0uHnD4gB++EvJsjGeTBW8mIwKCuOXduSae9WYHcqr3tFvvze9lgB4WmUHaOXN5OdayAmM4/HpC1/
pHaHMIt/4xOgJkGDjkcqVW6oIjh+TD0Iu98kPiasHQgd29flcmJKKHmgYfd4BUA4KJOQv+w4UFrq
kQyFlBtmHJlD4v6cmEPGh8LsA3OIGKdZ1sjzF7c8v33J/WnmxYsXlFZ578Vz3EH8WFefeP7yHpRi
9WLW9PzFfc/+FWMnAGU043QNyvRo1sKSVh58t5eMmWUNZB8eFfiG7uxaodLL67vBw5u3q2QRR0pN
coJX2Uu5Dg0vy8KgTe9w+t5MaVLZQsYa57PIF0qGxQv/BS2dzzCN1JZJOQiBq7NgU0lgCiEklIX7
+3tiFs3XtkcJIWAHx3mZWXygZKEMWDMye0HYhPrf78NUmLp2SLdLQUGp92nLlBH2q3NjX/w/got7
F6w7XWEjXxq3WRiInQaq4rR7X/aN6QehyEwcpsfQbiFhWw6UrAbEae2D6k0+/MWk0+ZTLXtcQimN
1ISG3arwPXTvMLaX5rEnBAB1M9EVZGfbicClKJUsiAN1ax876NrczkTcuAK/7/f/AcaPfZxmBlLO
xFS7sE+RohhX+yidRmliNhyiZNEY0zOKq/itlibiMYGjHaf5LCpTZ8mpErOoRUMt8hCkJOiOzz0w
qpBiZQ2ZlAu1we39mVyl+BllCSVxXhZizpyXlbu7exa/kmrjtY+8yrsvngtbNkjkhR4s0Ydu3FxZ
awFrGK6vyUk8XFORjJuH8wM+RELNrCFJ3s79CWpjXQPKGM7nMyF50Y5kubFtZ8luO6dW5eHPpZBS
IMbQDZvE9V6yisWZX6kmeUn99B7cSE6bfsbii4Tcp1Yl/1dbhulIDJIEqKxkA9V+wuecJaRMWxa/
4r3wfqwWcpemCQQcIyGuQCOHxDSN5CzRqrrpvUv+C3/2e7DuclihZLxRm69IF+6Jx63qxQU5JDdm
az8QtZK/v413put95HMuQAJ0Ypu53Nvy+Rceytb5bNEddWNsfgDXh76YbIYuunMA9lxWFDXHrvot
l6wbBVrZnhTPheGnqsynffu97VJKy1K1U99+q7q70wvKI19/oy3T3+hSGr/3P/gPKW5CjTe0YSA3
8CWQWyXkhLMjxjlqbUIYMsKyzbXQrKZGgbBLacIErUqiIeB9XZOzo5gm4yQuokkwVCwZYydSEYMj
1Rq5Cps2piadyuq5Oy+8fHlLKJk1BGotoi/xmbfffpsvvP0eMTUelsCyBtYQmddA1UIo8yliGkKW
Kwlsn7eNxsdVbBCUhFkZJSHq7jBiRnFVa7kzWTtHotBIfiX3sU4ri9Ou75/EZ0b3gPKU4v56L+eF
WjevGo3tlgaNihl6MmCpzPMsnY6SoK9SGk0JkpVSYlkWYioSexECAGGJO8nNask0LhR8XDktt8Ti
UUbhjGMwR8IaOBwOGD0xDBNvf/Edch/fNPBqW8n1kvVET6RsnY0qV3dVqxlVtsziLSPqMsZvaKPu
u8AOPHaCopGCYIRAt4WYPz4oqcIg3ha42/dhlRV7yg8IzfnQFxOlFFZtat0LW69QqKpSW+pEHRFG
pVJoJXWIrO2Cvw0Ozu0ye4IInbQapFC1R6dCd9/aKvpWnLbvSZizmT/4x/8YtU5M0zNiEbQkNYTc
1pe7w+DQThaOxgkakHNmnKQtH4aRlMRbJWwPT4JS1L5faK3t4V3DNLKGDFpiPpJShFJ5cf/A3emB
0zoLdyUGlliYgydkoAmlf/aR2UceTjPT1ZHFr8yrx+dCLmJRWSsELwLFlDO5a4aW5SxEtyKL2kxj
STKm1aI4lcz9wwPruqKaYRiPKA059yyjnt7XtCLktMOVMWe0VSLR7znDkl2kqEko+Ec37p2ej4HW
0Y/WGi0XyRXu/KMYcs93LpQkS2zdkR/nnASgZcmSLnmRDJ4eHp9SodVEiQlnBsbhiMURQ2CeZ7wX
XZFfVu7uHoDCzc0NFJjcQCsZNxmg7IQ7GXckNL6pthcJuOz2NupBVeK+9pgnYo3pjv2Xxar8pYIz
nUNVumanbRlSMtZULpaSGCn8uWdba+V+Y/FMxJpRWsS0ZdJixe9CyVK2mQGnKqOetqznixAQsM6J
x+vWJipBaVrKshRs+bLI7ZR9Hu1e3ociKXWJhcTwHX/iD7NmDcM1a6goPZKidBohFXJtjFqg1VoK
h2mQ08FYJiNWA84JbKetxeiR0M2FvPf7eFcrjOOh0+sFmYrRU5pkCZd+Si2zRHSiDNqMNAbmeWX2
oQvgMi9fSAzF87sTa6qELujzJe2U/Ywi+LRT/JfljPeeNXjmB4k69d6jEKaoz4Wz96TWmM+SKOhU
oyQZvVBmlzSknuUMUjSkgGtiKD2HuBB8R+OsENyaNhhlusu97s5yse8QGm6wWOuYbq7EOtJY8aw1
jhoSRQvHQwh5nb1MYxhvUAZSXcg1kcJMyDJ6rsGLJ4iRoHatNYNzhJB2F7sY+9K+L5fFc7Xxf/zM
T0InVsqeTjpn1bq/iZLOtLLR3OkkzMKgL9yobTyRLltfDJVaE2Eh4oPSEK/ebYzZ/t72WgkBT7KG
rR0vY84HdH1NFBOlDLn/r502MlerCwlHKan4uQmtWDcn4qrWelCWoUlagmzItz9rj9pQHkFwXSOx
FY5NLv9YfQy9i6kZOxj+4//qT1CM4fjkFVKGXCsxVtZUyVVycYXXomWnAmS/EuLaGawZSpExYQv1
VgqqoRVNU46YYY0rpRkWL3aDSokBc+z2hqlUtLPM0bPEtMPFVVvmEHnn7oG1VoarA3fnGe8lzjNW
CNQOazdmv/SOT25y50ZBobxnWRaCT8zzyrJ47h5uCcnji+T9lKpBW5qSUxa7RVP0haRVmGGkVuFM
aGM6f0TMfLbfD8YSY8AZizKGWhOpJEIIqM6heXL1RIqWHViDqIx11Ryur2SZXQuojBkcOcdelGUZ
+3C6ExSnFppy1Ko7HX+gdoTK9dTE4hOpu+Yv60rKnlwFWTpMV+Kcp8RiQEaVwvLFzwLscg9FFd9c
o/cHXXZ00JTti1I57CS+RSBgsSmonQCYH+1DSu9ALodm0xeV/GVkev89gZYo5gAAIABJREFUJcZS
shbQ72f7f1XXh5+0ttGEe0u4Zd4YJeIwWZQraiu7OUwpSbwiNqTGtB6P0KnFRqGUZafJqk2uXXc0
ZysyO1SHvOZms9MTWAGndffRrPyh7/ovOL/7nD/5h/4IWjmaivjZUwdNUJ7rw5FWArlEro9i64iq
HMaJlPqN3rLwErRiXgU+rTTm052I2UI3/HED8+pRDawVpqszA6kmljVgrSP6wHGcSDGRsoQ60TQh
Fm5PD7RUyE2QscFZck6kHmmpmkYrjW+ephU5JuaHEzVKt6Ra7bueKsvXkllLIjXNeQlcjY6bqyuc
vhRs8feQ10trTU0yRuaU9hFDvErk4Ys5MwxOlpZVYPsdbesI0DQeds3R6ORn60Yhzg0DOTW8P1ML
u4nW9c2RMAeUk4PJzwvJGLQq2GmS9x3xs3HGklIhq8JoRuZ1JoXER974KPMs8PD9/S05S7B5zInc
5IHVdfPOKaiqaUrvh5HplAO5dx4zVvsStU8xW7RL6wFd27VpieSZ6C6EdD8fmhhFP+qmq7oUltaq
KOBbA/VBKXO+BorJ5gQlL0hBmRGrhI+glEJbs7dyOef3ua41RCUqb1QTT4nOgK29HdxEVYICmP0N
2N5cYwypR3vK1xXHte3vyJJNZlzTDM8++gZ/9Hv/DFpr/sqP/SV+4gd/gME2Bud465c+zytPbhin
gRblxDFGRiFUpcTE9dMnUOIeqB6LRC6UWFEMDFZMnqgIPJqTcB2qQlvdzaEjrUkqXyzCq5mmSUK7
cxZz6CRWf7U2aAofErSyI0spBlKNYjHoZPGbHh6IIe8oQ4xZFps+yuJ7GLm/W3qRdrhx2AuFTPMV
Y7XIC2rbCVsyAkQJfhccVXQ0+8PW9j0HKLSx1CIHREVJLpAylBxxk6MS8CGJl0dt5FR5ev2U3CSf
WGHQzhLiSsqKwRjWeZHkOxQxRq6urlBasfjA6CzjKPk4JRWurq44n08dWVJM08Q0aZZFdiktBSqW
ajT/4w//IP/sv/iv8OT6WryGje1LY0AhLNT+gGutqPWyK1FKiV2A0eiuXdrRIa36edYV9L2bpkpe
dG0ZlMZpAHl9lZYxWKhvGq0VeSdjfvXXh76YoEQVbNGUDNhMRMadnUdSG5i2KzI3QpDpMvQ9i6SW
HesXcxp1eSGVIteEnBlVHLY2clWfP+Uhgo2CUlvbF7OCDomjm0rypv/ub/vd/M2f/h+wgyPFwhuv
35BiYTl7np+fU1ph9ife/OgnpKW1lTUkDqPb+SZNV6wS7w+VE2HJtFZRVli8tV4o0957MS9yjrAK
92GLrwBBLVIQctzhRu+SDO89h+MonqQG1nnpnrmKmCMtZXyqxLZwujthzSTM2pIYp4nUC/Hde7fY
wYgPCx0ZcSL2kwW6PAQag3ai8G19Ue6c29txa52ocp34tpZaUaOIJHWnhKdaGKxhsIbY9xcgqYyq
akY39EW5wkSF915MpprQ/Ws/ROgjgVhoCopkrexwnDas60wOwr7OucqYs3iMkcWmUgntLC1HQlgZ
BlFn51pJPrAs7/Lqk6eyH0GEjFtMaWsQHlkxgmh6WlN9B9M75SwevltkqkSNbG6BAMKc3n7fquT7
GG3EYU0L4bMCuhaalvdeDlD3gUHDH/pi0vrc13SX17dCU5bcMrVVyI+s6BCBVCuihSgl9SIgc2VD
Ii1aRSJDe8eyJfRpZM5XrXczdGjul40+rXVvCK0uJtTIGFSz3ITvvPM5fu7HfoTf8uk3uD5OkmNr
HFpbHuYHmqqc14WhKd57fubFi1tevn0nwrKba26uj72lzxyujp0clXBGyFjxHPbOqdRKSbVHM2Ry
TJKVM460HFmCZ7QyRhwPh04Rb53ajZgWde5IrZ3e3SAXSLmypkTJhvvzPSFlbq4GftOnPs6zq4kH
f0JVzduL5/Z07v6vl7tTY7i+OmC7z4fYOipSCmjVmNwVqUSaKajuOCY8EvncoY8wS9FYY9CqkXt3
SVOcz2fGYUIheUrUCoOjtUwMgVIq02HgeDwKJFwy02CJoTFNI2H1oDY+BpJT3M24hVYvXKXkV6Hr
J2HkWqtZfOgmXVBK5Hg88PLuxDQdd9j2yhT+8vd/F9/6e78DTDdgyhmFxthHqZBsHbhwTWQa77nD
iKSv9c6kavWoAIjeTGsFVYLJlIaSBcY33ZhJCtb22skBDRWTCh9UNfnQF5PN79UqR23iT0qrGAQn
l/lZDKLbFllhTRdKaZQWMZ8sURNUvZ8KopHQ8uuNR9IuLJ4LO7ZLwnsh0dpSRbonHp8bwgPQCqfz
A3/vZ36cjzybcM/e5Opq4uF84jBdM40DH9fPLvN/kuzdGDMvXtwSfOLu4Z5aHJ/73Oc4ne6ZjtdM
04QdDIMduyOYotYo8GLf/YTkMdoxWScBVS3sJ6zq/AIJDC/gRHcyWCFtxRyREw5aVeQWuL9/oBYY
RssnPvkxflN5hcNoeP3ZKzRlyLXxSjxy/fQJ7rN/n48dP8Xfe/s5fllxT460so1DEYUhqcaoR7TV
1BqFKt5k3td97Ikx7jyS1jKpIDaFtVCUgpxpGrQWwtcwWFDCBi4aQvBcFUNMsnBsClQV7knrMbJh
iQxXB+bzA4ObaCWJUrgW1P9H3rvHXLundX2f3+k+rMPzvOe998zsmT3MMIAMUg+ttpZYayxC21gS
MDVR20ZtbZtoG2PVJq21CVXTBtNUUkpCKxRFaCxSBAQKeAAFAcuIs/fgnIfZ5/fwPOtw3/fv3D+u
31rPO0ZEOztkJ13Jzn6z3uf0Pmvd1339ruv7/XybgnQ67lmtt00QqXBWImclUjOzLPI+yC1fOKXI
oa2bBfcgNzvbO1KY+c7/9c/ztX/gD6Oy4sn1jnt3bpMrZ/Cz1XKkq61jFga1pdaAbe/vWAu9tB7S
nZyP5yd8o7zLcxXurFWupd+qtrVRGJUp+RSYrigq/f9nAIvMS6kErOpQVlq3UjO6nd2VlXYtpcYt
yeLQrFqJqtJoUvJo1TXtAhhVBFKUNcZWUhJPDEqhzx4GdZ7BVPgcWvhpw5MbFPTE31z1hp/+1r/Q
Ut7aAFFXnrv3LJlK78z5Y7vBEX1hO46kWrh394IQ5N8wmI5Hv/oFlmUmlsI8RXaHyMde/BSpBN54
9Crr9QW3tlti8mIsU4XBGnbBo3Ml5YI2cuSxWmGdpiRRngqk34FWTJOHIoUm1kSu8N53Ps87nrlF
pxJdv6bTir7fkLOk6+VacLkwTROPjgd6o+md5b0PbvHaI4MuwhPxYeb2xQqFwuRIKrGJtiydbblB
aIZeLPXDMBBjIedwc6F1jmVOrHp5u6aczsVERYVWCW0rKWZ67c4RIp3V8vtUhRSlqwspcnFxweID
BkOOUQbbsc1X6sJxXliPK66urlC60o9rjtPCuh+ZoxTooevpVgPTYSdUuDa0HcdVe8/IWl0VWU/f
SYkf/76/ym/56q/j7sUtiirUVM9ZOyEJ3MgqiCVCFR9YJaNbLrHgsqXgJAUmy6azZHnNlFIUpSFm
ut5SE5/jLha1q2qrZUCpluXz1jze9sWkKkWKMvHWtOwPVemMZL8qKxW2lpucEgUULUKzmjJFCwdW
Doqt4zBO8mFVImfQbSWq1amKy1o0V7mDG+NEbt8uhVMrCjJBL7ViqfyNb/9fMC4zaIM1hs1qaJoK
ja4RdN+0BxB9RVshrw100FnY6HbcgHes7gvCwFpykhb8y9//LNZp3rh+Qg2AUrz6xjVvPHzEJz/+
Co+Wx9i+R2fFOI5oHUSarxUrMxDCTNevCH4iFeGfLsvCvbt3+cIXnqUbYTuuzuvYeZ7ZrjcssyAT
/JRAa9Lima6PKKUY12tsN7A7HFkNHffubnnl9Yds17exupJjYn17hZ8rGNvmG5WQIkornDH4UOhH
RK2pJBO3oikNL+Cco2TRoIzrER8TTosBNKci/q2xP2ty5Igo7mQA7ZwUrqoIi6dQZd7j/VlIZ5TG
2IFxlG7DOQc1Y2oB03FcPNppVr18n/kwCxgcjbJWaIBFCmw39IwbgVJ5H1CmEj/zC/y9v/XDfNlv
+AoMEiAXfJTiXgUUlXg610lYPbJ8qFhlxMinpehoq0lRjmQWdd7M1BZCj6lyw62muYoL1SicKuRQ
znnMv2LbHKXU88C3Ac8g/f8311r/R6XUHeA7gReQ8PLfWWt90j7nTwC/D8mT/0O11h9sz/86bsLL
vx/4w/VpY8Ev8XDOkLNqaXJtb17h6WyclCX68rT9KaUQc5SBaxGeBk/FK5w2EqYNZNvPB7RjC0o2
FFoiCQotFJoTyb6imkSfplC8evNl0vEK1zs2F2v8NHM8Hrm4uGAcet54fMR5Od5Ya1iWhc1mwxIi
27XY9HPO9KZDdfLzONfEbqay7h21bojJ8wXri+ZgNbz33e/Ax8zyFR5bDTHNhCXyxqMDroNlKXTO
sH98xb37d1i8nPvHVU9RmeW44IzF2CoblYoUmhTQZUDVymrs8FF4LYfDhA+J1Z271GpIPtANRvAH
+wOD7Vk3z8phmhnHHnfUDENHypVcMkorVDVyzFSCNwyLF8xiqpyMc8Z10oUkwUOKWjhSUyEqkdEr
IwPFaZqwyoCCEjOlFsISz2HuSknucSlyNIjen4tOjJGkEl11UC3L4tFW5krzNKM1jOsVNWemYyDk
wP7qmu32sknkT4bTyGqzZpom+j633GXNidP7+KWfZfg3vprl6lo4M/PMtpfX+NQFn0SSpt21pIcW
hMWpyKRam0T/NEiVzZyq5RxpARDbILuWpmEpkJTCWE2pRcYAb9E555+lM0nAH6m1/n2l1Bb4WaXU
DwP/PvAjtdY/o5T648AfB/6YUupXAf8u8KXAO4D/Wyn1gSrwkP8Z+APATyHF5LcDP/BP++YKGQko
VXHKNaOekY6jVpTVbc9uqE9V59MwCyVdSz2FQz/1da0x5y2AURKG9PSqWB6CIigFjDaC1WutoqBO
2pymFv7Od38Hay0Zt0NvSTG2GcWO6/2ErnBMUvTE7Kd53JLwdtcHuq6jc46QlrNtXGvduoRCb5yc
m4fWRWnEhxMCzlVWgwSV59xjlObi4kIMhGSGzjHPnmmaWA2jRJ9qxRJm6nqFcz3TdMDaDkqmq5Zl
qSSXcc6KTiMlzKA5HhUYCCkz9Cu0cvj5wLpboS8t19PMxXrFm48fcftilItfJWK6YZiIo9oQUqS3
jlJlvhVCQuuCdStyCAJ2LpWuc/T9QKHZC4qEc5Ukx8xY5UI7+omh60hKkRr/RiWh0He9o+RmhMuV
ZVlkA6daLGitKNVmLVSi95Q2/XTaNW+P50TL22wu5N+mFUOyxCpbIg6grSKESn1K37QaBuY48Zf+
uz/BV3zdf8Bz73wX3djz0Q+/xBd88QdQTYdCe/8WwKYi+cttdqeUksyjpmgVo6BkXZ9DzpUWvCUN
ME4lldNsRNGe4RTs9VY9ftkDU6311Vrr329/3gMvAe8Efgfwre3DvhX4d9qffwfwl2utvtb6SeBj
wL+klHoOuKi1/mTrRr7tqc/5p/wANGdoEvp4G7piNK4Rfa3S542KDKJOkRa2HUnkzvc0qvH0/5PU
ODcptGogpNPf1SoMDtWUiAojdC+kyJ2/Dgrjg8isfWSeFh4/uqZWuLq65niY2e0OxFzZHRaeXO95
vNszLYlXXnmN6bCw2+25vtpBNUzTQvSJEEJz0C4sXrw5p7tsqpJlPPYC9hmGAeccQ+eoNXN5ecl6
u2KzvpDYy1XHvTt3GdcrtrcuuXPnFndu3Wa7XqFqYeh6ShJg0jzPWGXZjBJvYWybH2EwDkKSo8F6
vWa73WKNg2roug7XGagFazu6TvKN/RzE/doeJ9Cz3LEzSpfzcQPdUaJoXmhh47oqYisi2gqqQTu5
Fy5RhrbeezSy6p7nBbQMiRc/Q3v9fYriWs5itqxKPEJaa2LOLEm8OTnLxw/rgaEJ2TK1zezE1xJj
pCgYx5FqCyFJZCiITqnvJVIkJglSA+idZeMUP/cj3820O6By4rnnn+NH//oPQRH/juHGNXwCGoFs
LG+ynTK5hPP7QNz0+Uz6r08xS0qVMHerFcpq8bW1Dr+8ZSqTf045vVLqBeDXIJ3FM7XWV9tfvYYc
g0AKzS8+9Wmfbc+9s/35H3/+n/R9/kOl1M8opX7m8ZMnUo2rkaGqAicxWfiUJWC8MS+zTDZFPg9t
JSz/nVmZT72hTy/MKblPJMs3XIl8MgSWGzt3Lac7zY0/BGD36HVie8OGlDnuhbUapkQqmnn2QkU7
eHxIxJjZ7/dyt8uZwzKzO0wsIfKZz3yWaQ74aRFdyiRhWnPwon1omIAcThefBQqu70FrycY1PV0n
HUDf96DFdGeczCwKggfIWXw9pzf76fcxjiOxRKqueD9LOHvO5BwZh66lDMrHH+epZRq3XJxS0UZ+
ppRK20BZplnIdKfAdudM20RkShad0Olumil0XS8ajpwwtumGGu1da42fJ5kl2JbNqzW6bZmUUvgY
REZeZDjrlyAUueOB/X7PYbc/B6AHH9FVQTvyLMuCUoplFv2IX0SvMy0epQzLHLCjgLEPB/l61lpy
FRl+CpnDYWH2gXFYM/Y9ISw4YzA1YacjP/JX/gIrNwLwm3/rb5Fok2kGIyK03hg5htQiq/JGV9Om
zQnVTeqhhG4pas6Yp+qDaoyd2t6XpcjxyWr1ORyUt+Lxz1xMlFIb4K8A/1mtdff037VO462a41Br
/eZa66+vtf76O7dvN0/BUx2FVo0LIjGTouoz5wtdfuDSyGzmPKA1jSF7uiNWkAzZdmQRTYk9q2EV
5SxBVupGrXnqdELy55/5Qz/5EwQ/sxwnwgm1uJ94fH3F4XDg8ZNrplnekMd54bjMFO3wIXG12/Nk
d8R7z9VuohRYppnDfmJ/vWc6zvjGCZl8YFkCPmYhoaXK7MVavzscyVlk5sZpfBb+bSVLMDhyjDBG
WLFLiHRDz9BvkDwgEY6pUtu6WopY3ws4WRlN1w2kWPDhePaPOGPpXUf0SYKf9I3Yb5481nRsNgMp
etlWJA9V4NinVaqxGh9jO7aeTG3Q9x2uH5oEH3rbUWIil3R+LU/FcQmBclY6g9WaZZnJObH4mRQD
ru/oho5xs6bvO3JOIoxzAnTyYeLycnseKpcqx57FH4h5YbVayQ2t7/BLlARHNMoI+7ckGapba+l7
x253xbIs7HZXWGsJy0zXWYzK9Mue7/qmr+fho9f4jm/9FmpOfOhDH8Lvj5Qic6unvWPnOUr7s0Yy
e2zTmNAk9wV5zggM6Pw1Omvk86O8b2pGOC2/kjoTpZRDCslfrLX+n+3p15VSz9VaX21HmDfa8y8D
zz/16e9qz73c/vyPP/9PfZyGoJKF09yVT4nHSJFqFJDonSFmbs6d+lRcisxD8kktehMTao0g9wRk
rCkItObMzaS2ItR4mlWhalNtmhb4VSOf/OiLmCAdDknCtmJL8juBfFNKYIX1qqsmLzLQDD5QSlNl
KokNNVEzdj3E0laZiRSFOqa1oArGcZTfR4gC8WlFMoTA4AZKEXn51W6hM5ai5QIVpseh6SQyqnp0
FZBS3iem5UjVMgw8HvcoHKZr0atGt8xfAyU2B/IVl9uxXXiZUE8MXoVxHbGZHsdxJC6earUI+JTk
EJ+Ur8PYSYFpbJm+78lVjp0ahbIGHwQNmUMUZmxKjONIjpGhG5vHKbfXvGCtQ/fdOVAt+kAyMrR3
bTVujJUiH2dub25xPR0IPkmH5eS9NqzWqCoxJRqoSo5GyxzotxYCTfOUub2+ZJom5quF9z7/PI8e
vYEdLgWU3Ts0urFfMmNUvPjXv5s7Xc/f+rHv5/a9Z/j4xz/Os88+y607t2/k1khxTK2AWiMxJ7LO
zjgjHZm1N560NkIkc1o4yLVgnTp3ONJP/AoNYJVcfd8CvFRr/Yan/ur/Av494M+0/3/PU8//JaXU
NyAD2C8E/l6tNSuldkqp34gck34v8D/9sj+hXK1UI5ubVKHk1DoGQzFVtiClkKsGIlqbNuM4Da7k
n3n23mSB2MndT2G1Oa+MNe1jzqu51lJWYYc+9Xtp0vyE1Z2wW1UhewEjkaHkSC4dSkvqXi6B7qRi
LAJ8Ns6e84VNKeSaIWl6C4e84Jzh4ePdWcEo63HL2HfkIEatzkhGbkaJzdxo5jM3pBIXTzaOohXV
S4SF6wyHJ3viqmfaH7B910yFchHvjhMnZ3WuhbKIWjakdJ5JFVOFQ2Jgnj2nhMOkkuAGbKXrtLhX
jQEqq80lV28+ApNR/QqaH6YamCeP6ztqK2wAOcoqukKj3juSlzgKn+VoMs8zZIVPC6DoOpHjKwx9
36GVRllhyLq+Ow9E0YocCiF7rLVcrO4Rc6RzA8HLQFw7ybQJPqGs4RQgZrQjxYo1ijBnrNa4Ftz1
8OEVVivW6zWf/vSnuX3rLstyxC8LFxficu6t0PtKnlHVouOE/+wnefPgeec738dLL32YL/81v5Y3
Hr7J+9//fvZ7QT7cuXNHiPf1plPptSUrSWqgFIm9aHoq2Q6JD0veP+r8/oXTjfdXrjP5TcDvAX5e
KfVz7bn/Eiki36WU+n3Ap4HfCVBr/bBS6ruAF5FN0H9aT68A/CfcrIZ/gF9mkyOP2t5wpm1Nsqxn
lSLHAMaeu4wSE6pl2Fpzc6euVQZTss5RFH1yBKez2O3pdhLKeb8PhZzBmBtvhNDrG5waaTc9CVUq
47Bivn6CSpL0p2qRF9nIhbUcF0xnzt/Tt/VkzpmgdfOlRMx6BQUmP9O7jlozfde1GVA8RxxYq2Ac
ZWDatgxaa2a/yNFjhqoVXaeY9wtWS/hTmhLVSILg0HUcDwudlRJ8mI7kJGzaWhIVg27bLlH9dsR0
RHvNxBGs4XA4Ein4IiFRsWSOuz3unc+RG6+k63rS7Llz/x7X13u8n8VPRaXrBpyTQXaq4js52eb7
XlS/sUihNkY6FK01gSQmR6Ooscpsochx1WhNzAFawbFKc33Ysx6GE9WXGCObzQaAGBZyiMzzJN0O
FV21GB5LQcUEbaZTSqQBSADQTl7DeXcU5op1zH7h7p07XF094v69uzhrOe6PrNcCI0+tQ3Y645Sm
mog6vsyLP/pX+arf8wf5vh/4Qcb1ikcPH3P3zm3e894XRPIQIuthTSK2aJci4k5jSDGjnRhPAVTR
6JolWkNL5rKtNwVFV/0r582ptf44v3Qf9Ft/ic/5euDr/wnP/wzwwX+eHxBE5Qdy/i9I5qygX43g
GxVnipasdnmqq5DOpVQB4mhtoZ7s3KYVFFn9iiT+tK+X33AuTZRWmq5FqQbzaQPYWqFmnnv+A+w+
81FRX+qeojM5ZWLLHO6sY/FH2W7khLGd/H2UlPrOWELMKCNg6qUVm5wLMc+MvWOJAUGfymDROYOP
ifVqhqrZrAwhLY3qZTn4CWWqwHj0TCmFi8styQdyEm1OrgVbKv2wYpmP7Pc70Jrd4VqgS9oQs6e3
qgmkhNWSqzg8UkqkkEm5Mi+BXBuCsmbcIBqLoXNsxoFcIv1K3Lf379zm5ddexVon5PkknY14U1ro
llbYTrKE0OI/MW2db50MXWuqdH3HEjydcRSjWquvzyhPbcAmAWut3NiUoEW6F6WJMRGCxypDUbUN
lyUMaw6yMTHGYpVqxrlGT6uVXjVtSFWUlJgPR9zQN42Q4Xp/bBElCaeRec04toIdWK+2wijRWo6i
BbLf873f9Gf50t/8b1LHNf2w4hMf+zjb7Zbn3vkOBjdwXI5sVmt8Q1fQmLAy66vNKCbvzUoDSCtE
39Oui5rr09Krz/vxtocjnapYpkIbsJZmzHJandH+cJObIx4KaZ+t1WL4q6fWrpz38aJZkcyaUwdD
/dx4xnYCAl1xTqDVT/M55Lxf+Mqv+ToBFetGxddisMpZ4j99lDdljJlSG+vVWKp2DG5giYFUCyGJ
ECvkJCY0pBUNpXK9F9BRxaKUYQ5iREtZvCCPnlzz5qM91/sjh2lhPy/MXrYZwoktvPb6Q673E8dl
Fh5shsVHXnn9ZQ7Tkdl7YhJDWDWWUKpEO7SN2AkhKQZDiegIIXCYJ3b+wFw8+7DIub5hG6zTpCqz
jVRkqD0Hz2q1IhYR0DnVnWXo8jrdrPJj20acXjcpsPn8GslmSAoJpbE72iq7lsa90ZIng65tsNy8
QaUI4xaFT6JpkXwamOYZ7xdsJ7OxgBz1luBBt5mOkngMv0xM08Sz73qecezZXl6itfiuthdrUcwG
0R11XcfFapSlQY6CTrCCC9CIkrqzhk/81N/gH/zw9/KpT32G97zwPG+88QYffeklYlr4sR/5UaZp
oqQsIW7qxktGhlraf7qiGq/mxH7NOZJTc7i/hai1t30xkRVvE2id1lxV6PG1Vjl7ttWYbnOF8+dp
dWacAOdIxnSC92p7VlqeTmKnF+RknlKYs24+pfrUUaiNc0rBmo5qDLa/IGLIWopfUhXbsn5Sqcwh
MofIYZ4IuVDIhLCQaouptI5cCzEVfAj4mgWjWOXCsp0jlIqPmWP0xKZqnGbPcT4w+SAelVKJOZBK
pFCJIXO1O3BYZD3tc2JaZpQbePPJFVfThLYd+1nobMdlZjcdG5n+xugoF3LkcDgwe8/rbz5qKtcj
03JE1UK1CqXh+nrPdruVrhEFWrEkSe67uLjgcNgxDAO3b9+V7ifMNyFrJ+CUlmG5Mgbdws/nU3aO
NpwCtlzbyjjbk5qZMcaI9wtYOS75fGrzb2YJckzsIMESI8Fnjscjfkkc9pPEoljTANSenBIpZ3Ep
K0UqokmZpgNKKTabDU8eP6QWw+MnD/HeM6x65oNs466urthuLnj99Td5/eGbbNcCdkpJjsjRH9mM
lr4zaArBz3Qqc/UPf4K/++N/m2fu3uL5d7+Tj//CR3jfe1/g5c9+ivW4Qru2YazIca/R1hrhpEG3
AHMz63PWkBuXF/XWFJS3fTGBBo8uLTvHii+hlHLuUOQXdFKtyipW6o/1AAAgAElEQVTMtDsW6HMB
Oq13TzqS02rxVEBqO0tqLdm9wogN0jYXhbY3WS+AaFqa1N5qx9f8/j9I7UaK6SnGoBqvUzfhXYiJ
bBRBXFkcdkdM17P4SPBt21Pq+e5fq2rOWsUcAiHI9/bek0o+B0TF2EhqOeJDIsQoR44ig9FpSYSY
8d5znCeeXB2YY+DNJ2/yeH/N9XFijqLTqcay2x+xynKYJ7QxHBZ/nvHkXCUDeZmpVfHo0SP2x50c
zYrkAS+z6GGcUgyukyhOY7jcXoimIwfe//73N0RExjrNaiUpgTHKqlYrizE3p3DRjJzyi5BiqERB
e5y98GPbkYQTB7Xvz69vCXIc0EWjtOU4zeyur9ldP2FejgQvKQQpJY7HIzFLBvPhOAlJbgmEGKFW
Zj8zzTOH45Hr62uGzQqFYVnC+X04DB21VuajYDGn6cB2s+Hxk0dY60hRbowphcZXkd/vbrdD5YCh
0BmNUwXywnr3Kt/zv38zn/jUJ3n94Zu854XnuXv/Hj/+4z/Ofn8NcAZHi7qYc9SGtVZc10+lBhbq
U9fMWzM0edsXE6WkoxhML6Tt0o48wCly85QNe3PWfoqcdppq1+bG5GaSfZYn00hlLTT7xC4pVeGG
nlOBOpkJT12MPHcjchsv7nAwW2LRRByqF2hvKAWUEQJWlhTBnIXQflJ9FqQwZRTGCSzbWY3tHKjS
NguWJUZUp1FF45eIj4lY2kYrC7wpeOmCwhLZT4F9OHKYZhafZVaTq/hLfMHYjqrgMC/MMXG1P5CV
5ujl4vMpivy6Ko4Hz5SKAH0wDcYkhbwbHQ/u3WfJmSdXE1VXnFFn60DvOnKJDGPHZrtiGAY6a5tL
Wo6em9VAZ+XrUSXzuBZFVpBCIlMkoiN4SlQs3lOVQdVMrJGiZdhdFByXSdi6MuzCjSOmH0hKbkzr
1YqLy9tClVdtdmYHrOuxnRynOusYxzXOWEFlNrEdBZH5x8Rmc4GqmmWRzVtKgVz8+f3XWycCt25g
Xjw1V3a7HZ21Iuevit51aAXjMLBeDVgDJQVyntEkemep2XNnVfjID38Pt7dybLq+fsx7nn+Ol37+
w5SQRBWMaEhORVRrLRsxbrQ7qh2Dcs5o99aVgLd9Malt1hGLp8Qk+TnKStB3o3m7djY/3T3PR5aU
IRtUURjTo3BnxeqJ1KaUOVdrXWq7qz3dwahzRdflpruptcqGQ6nPicP4z//Yf8FeiXksFNVWspI9
rJQ5O2EBUhLm6an4WSsbiGUO0gFV+TraGOZlkeGyMVAaD7UhCWPILCFRlWFJGZ8XyLBv8vuaKq4V
tlKE7pVQ7Y65NOm4ZwkR53qWRTgpgnSQ7iplRVL5rAnJOTN0lu3Fmnv37nF5ecnV9WMeP3ki6X99
3xCSHmLGOXdO9LPW8uqrr9JvbreNTtfk5yN9P5JCJGc58qTGmi1WE1MGYwS+3G4SVsnrbrESe6lv
YmJPCk+tbetS2zE2y4WWYxLQN7WZAf1Zp9N1XTMgilamoMgxE6JEfGy3W3SzBKSUGNzA4XCgFkPy
hcN+IQbFcZkZN+vmObISE5ICyjgRMz5+zGqzxi9SJGsV+8A4OtarDmri5V/8FEPXs7Y9uhR+8af/
JixHbt26je0GNtuBT33iH/ELH/4wyoDpzOd03sa687/l6flibcfnt2qb87YvJiJ/0pD1WX2aasEU
fRb0nFSQrhnIDAZVsgQzqYKypkGm63nYKlN5oEpyn3ZWJMlt1Xyao8QoKteTEra044dM8NNZUn76
nBgzf+S/+lPcf98HiFnjqwM6otbESrswK7HqBhiCWE/yb5mXiMZCE9LJKNjQC8gsJSaNT4mEQIJO
5PdUCsu0iPEuRkrKEicaE/v9AaxI8XPNhBRZUiEVxfG4J1fLEgJ+kVVwzRWFYz6IMtfnQCg3fpTN
ZsNzzz3DdrtmvRmY55lHhwPTMdF1HRawvWXsOoppPpMo6AVywRnFymru3r1PWDxKZ2KJFFVYb0Z6
5/BhJoVFugZ1w061TlN0oejCkhYKWvKUYxYsZRDZeG6q5lwCrmXuiAxd7so+LmcGzqnQSlFvRU8r
lmU6H32O04FnnnmGW7duMR3nZkJNaCqTX1iv1/hwxDiHNqL0tWN/ViTLMS7Sd0NDJcCd+/fQqhLT
gms6puTluFRiwNXKth95+Ppn0aWy6cHvH/M3v/Nb+Ft/8Vv4zMf/Ia+//iY/8ZM/QSXzxiuv8Q9+
7kPNzyRxuikLeqHEIopjmiXF2bd0APu255nAKfC6NMK4BDMpY2XAWEoTaslHC+JRURHbusFgjSXX
CKqetSJKCatENZBdyvk8aFXN/yFryJvoAEC0FsaSc0BrYcxmVc5zFZDj09f+3t+NKZr/4b/+k8Sy
oxZFLBVdwBgrMRVoVFXnjsrqhCqSeZyLv2HYKi1znJRbyLrQ40qp1FIpKbSOLKG0DAZPW5DOGGLM
xFKZpvnc/nrvz3foiCbFBT8vGOMYhk7YIVEk8SFG2a9CQwqMdC13ZZ49u8PMp199ldeuFrZD1waB
lrHrWY8jUDBKID0xipCu70cymd5J9s+4usAafY4hSSpz4SS3xnvP1HCJucrs57TeDz4xjlbC7XMW
kDLNaNdSD3WFrEorJiI0mxbRaJAE6pva58nw1hNzaK+9WCMuL7cYrTnsdzJnaPyRi+2WsHj6XorV
OGyhJGytcqxqXY5Rhnk60LkBhQx67925IAfPhBgfq9akFHFaZhxaKUxvuHf3tjBhcyThuLq64u5t
TfGJj//kT7B63xfyVV/1VeyuJ37mZ36Gf+FXf5AwLazXGxbvQTeUjwYhW8l7XVWDMuotI6297TsT
lMCAldGCGCw3K95TjEJtEN5TRERN8XxeREtQU1WGWiQEqtK6nLbfOR19hNspndBJ+apOfgcFpUGB
T6I2uevJvOXUVtY2lNXakjX80f/2T+K7gdICnOZUOMYoKXk540siFwENl1yJJTEtniUkrvZX+GWi
VEVImdqyjE9E/tkvDU1omjdJco5zzhRtQVumJZxX5tMSiKGyzBKnobQApmI+CdsGUgqSpRMj2hpS
laCnXJGcmNbax5w4HCZef/MRn371ZXS/oRYhone9ZlwNsjKeZqzWHI/Hs6dJ9BSJ7XrN7D3Pv+cF
UvRytm8piid/zsVmy3a7bfOKwHycOB72QMVPYkBEtcD4ImK+EhO2bWFyaM+FgtVts9ZMhTWLpmee
Z2Yv4WJL8AyrkZrBasNms+Xe3TsoIKZ0ZsKuVitW/UCOSeYkDUo9zzNVGUKSztc60UmFIGv+cSUk
uPsP7mJ7R4wN35krMS7UlAk5itbpfEyp9EazHi1aJd777nfQd4b1qFmbAp/8CB/+Oz/GrbuX/Cu/
6Teyn44Yo9gddlzvrjDtTqtRgr1UoJxgCJ5Ot/y8L9WThf7t+vjgl35J/Z7/4y9KWJGuLdBIeCan
Cz9TzxueesL5YdBG2lnVCscpOe60CpOSlKGFGMmMRHQg5jzMBeGRVs64VV3Q/1hTV0E6G31CEsjw
Vzd+htOGlz76It/+jd/EfH3N6Ay5ymC1pEznbqhsUgM1iptgaqs5Jw2e1t0lx7NgSWvLOZTdGIk2
OF047XdyauOdNqSayNGTY2HVD/hczr/jvrPUKi2+sV1bocrcYT4uqKLk2GQ01WiG9YbDvHB9PBDm
xKbXrHvHu9/xDNvVwN3bW/rOMq6H8+wktegGtGb2gRAWDodJFLFVEVKRCmb0ObQqN02L7Xsh6nfy
/6urqxYXErFWnuv7roVZce4sYxLERIU2FxkopbDZbESrYkSiH0Jg7AVCHVKgIpAjZyw+Bi63F6SU
xNiIzNi8nxuqwlDJbFdrcvGshwsOxys60+GcQavC5cXmhtuaRIDXov5QqTJuZLOVg2hS0mmY23cs
ixdrQcys11tiBT9FvNIErfm1v/1ree6557h+eMWz73gnr7z2Bv04cP/+fUqu1JPNpHUjGsVXf83v
4h/8/Iufd3/ytj/mKGQdW7XUV12b+Y9KqgqnFRQ5BoGmltMxQGIgANm4GEspilSSMDmsgizAGNUK
kW7uYKOexhMI+o6W2XVSO0pA+snfEFG68WVL07hIloC0llXEdR/4gi/hv/mGP4fWluPxyGc/8Qm+
6U//WVajRqvKk+u9DPOGobFDCkoVain4KuAeq1pnVDXGCgAq5ohpqz9RxjqRU5/iKocVKcvPGkIk
m9ru4HI8u27RFjlnrNUcjrH5mG7S4K6v93R2wE+JYei4dXEXPXSsVh2TX8Ag85x9oFuNEqIeImY9
Qq0SQKY5r75TiuQMaE3XW4xqA8ya6boVOXuwzSgYI9poYir0rmsiNGFzuKHjwYMHVKOJSUK5rq+v
cX3HZlzxyiuv0A/D53SOMUYuLm41/olkWMcYWy5P4datW6g2kluNDmNWKCWcYeccJWWur5+gcbL9
SwltLcMw0HdjO3ZWxmHNHJrHpwK2cuvyElWyFEUlw2ithO0aQsQ402I57HmbRvNLxehZlpnLy1sY
k+h7Q9gf6foerTQ2Zn7qr/5l3IPn+drf9Xt4+eVP8+yz7yKS+L7v+16++t/6tyG3iI52HT1tJPx8
H2/7YiLcNI1GojAzVbYuZ3+NpOBpZSnNVayLlaCucjNcy7UAEdtUkaUI3u5k/lNtPagp7Ws33ckp
x+SEGlSS1nZaByulsLZNz5H4C9XcmXJcOmH45BnadmgYOr7oy76Uu89sePjKa1z7gHId2S+iulWG
7XbNquvlvFwKnTX4p9tSVakFnNFEMt7P9P3I9XFhu1ozzQJWLseFWsU0VxXElqSHsfiUscY1Wpth
ipHOOnz09N2a68MRgMPuwNBXLre3uLy8lN9byvhwZNUPTMvMOAwc2InfZRyZlpn9pFitOryPOGUI
JaESaGWw2hJrocSC6zpuby/YXR8IdcZpI/YCK8cd6cZ0Ay8pShTbg9OG0pSpqkItme1mjXGa/f7A
ZruFKqZKxYnpW6jFC2KiUclu3d5itaIfjHRGIYkpsJbzZqqkytXuGmc1Y7/CxwVrR6pxaFMIQSJF
hqEjlkwKkRgy/VrC03onjJecsxTXVuBijJgmolMVcskYlXGdHMuWkNBkumFF7xxKVXKphBZfGqMn
x0rnOh5sO/zuNb7jf/tGfvd/9If49m/7Vv613/xbuX//Pj/01/4a7/3CD/DCCy+ct5A3trnP//G2
LyYiSINaDYnm0zkJ0FJC9R0uG3GWtjNtzZFw2rjEhHYWRUGdLPe0DUiKkES3oo3gCEqR6FFfgihb
axYEQRKor1IC9E0p4aymVkmnk68pLuQqe5bzylcK0w0KstZMZyyf+Yc/x91Vz+a972Ld91w/2uEG
x6PrHSkLYvHq8WNqUWw3K2alGitDgs+lawgsCnrdUbVphDHN4XAgFYWOMlM4dWzGGOaQyNkzOCtJ
esairWZJma4hHUspLPORaX/AmY47d27xzIN3cffuXYiGyR+I055qhJdqtcGQsa6gagR6tutL7t65
Sz8YQg7cW9/j0ZMn9KsB7z0XlytcUiiVKaly69YthqHj9dffZBh7lG4xJFF+1+LPAROh6kjnLMGn
87HvtA2ZD0dh56YkK/QqLN0YBdVQTQM5pcq9B3dJ1WN0j1aZVYsVKWSOh5nVKMHyn/jkR3FuzXq7
oiwLMS2shi3GyuZIm/4Melq8vHe0hecfPMcy7SQl8NYls59IIUgkx3pDDlG8PKVim+HTWt1iSQLG
DYy93OiWaUeqRWDhq40IAGtmsx4xSyD4RCmZlR1I0xV/6c/9aX7dV34tIRW++P3v4xO68qGf/ile
eOHd1Cpd6mq1ecuu1bd9MQEwVhOXKNL0BtY9CYlyqiJUqqJgrBWU0Zgqx41TuhptrWyyuFprFacp
p6KjwCqJaSyx0ikn4UVaNjqSiJblzFmEHyuKb9e+d0QXsdlXpW+CuzAordrA8+bopDT87R/6Xjbj
wLuevUuaPV/8xe/n9Vde50s++D5GN/CxT/4iy7Sw2x3YXx2Z5yPLkohpPs9LhmHAaUceROBVdWLs
B5bZy0WD4A1SrvSdJszhzBAJOdHb/nPk197PWKOoS+XicsULzz2HRjH5A/cf3KHv1lS7oJJicR0l
RozRdKrj+PAaGBmNYnCDDB6XBasHtvcuWVJitbnA9RaD+JM6Z4mzqHh3+0Ln1mzWFzLI1DLgtlZL
cHkq5JgxVsLci49YozGqk40YYHNlvV6TY8KueuZHV8ANRlEGu4IHGIYBpSudXrPdjtQqPzfA7jhT
S+Lxw2uMG3n2mefw80wInhQjt2/fZg6CgLTGQMmM44YQFrRR5MVz6+4dHj15wtALZvI4L7I0cD26
MYBPKEaVC7mtoG/fvgVALIYeRLsSKtqCo0MbQYnWUqmxgHV0WnAcaIUPM51V2Gp48Ue/h+e+/F9l
d3XFF33gy1DW8X3f+/38tt/22+j6gaurq7fsOn3bF5NaK+V0MavUALmmUahkqJqqBDXLYLGgShYw
QNFkVc5gnJxkRmKQUKdqNBpZ155WqkrRRnQabTSJ3ALqbla/p9hG2ea01EAEQiPHUCuiM6Vk5lGR
tS0K4zQ5gk2Ri8FhV3cYesPm9jNkpXjX888Q4kLOkQd3t8SLFbe2K5Z7kegjaDgeFq72O+HNJhmU
LrsjSldCzOz0Aa0ywXPmWoy94XidmwNajhXGGOa0wzlLNzi2qxGtNXdv3WbznhGjwDURGNcHiEeU
6ahV1KgAMbftWsloqnSA/YoTIrPvHdv1hcywQpQAbmdQ1rB1Ky4u7uD9zHTYSYFLhcH2PPfcc3zk
Yy/iugGlCiUnUisIWYEulpADrpg2exDLf8wR1VlQhXn2XF5sZOOmBK94eXnJ5b077K4fydGxkwgT
kK9xOOyY5gM5VR48c4+w2XDc7QlzIEWBbGHkRtFbQ+0sRsmA1BqHXw5UFHfu32UJngf375CDzGZy
zmQq49C3+VaBUliW0CBaBjcO+BCppTA4R4gR6zTODcTkzxCt0Ywc9hMKkRJoFL0TgFTn5Obx6PpN
dHebT/7dH+Rr/uM/yod//ueYU+DZB/fYHx7x8JM7UAm/eN6Kx9u+mMgAtlLam7VWJS8o4tnR5YQf
kApvlCKpBuRRJ4yPEKmoIrXOSnQQJcrgTCmoMbeQaIOuN27kWkBpmnfCyIZA3ZgCc6NeGWXlKKHK
2fp+Gm2duChKSYwDaL75G/4U9zdb1uuR/e4JVoGzPVoplsNE3/dcjiuOaiH5he1my36aoShWY8/z
736WN9981FS0itl76ciMrB6n48LiJ1bjhQw2Y8CqxGo9YJwcCdebLTVGnnnHMxz9jjuXF2yGnt4Z
rJHQ8eiDsEDsmnk6QHVNMVuY/ELMgTl5phSEWuY01mpKzudZg3GaThm0VUKnq5J1YwbD1dVDxr7H
OEdq/iLbOeZlz3vf/V4ePnyD2Wf6VQdeNCBCt29QoCrRGfk82xApQSkNkB0T/dgTc+XevXtgNIer
J1xe3hYHr9Wo9UiaPT4v7PfX3Lpzm2kSOf7xMOOXCapl3KwZOsv1/njWKzlrCEEMjI/efJNxHHhw
7w7XV3s6p4mLgLEWPzH0K3KGlAqlZHFLd10jAFb6oUMHURcb2nvwZGa0QvbLuuCUIebIat3h2lFc
KUXfSbwIWlOj5/bmFgHo3MBf+cb/ng/+hn+Zd7zrA1gNd+7coxbDO9757Dkv+/N9vO2LSUVWm7W5
hFNKEv+pFSYLYLoY4ZaeIEPaSPyFygLhta7lpugbgj1P5a9mFKqzdKWJ05rk+7TROUnacykCWUIh
AdMV14hgpwEsWaEbFQ44n+dPKMjT9xw6x3zY01mRTy/7I0veYzrD6AZqTiwlUkOUbUWSod0SA+Jl
q7zr+WdFcNc2OLvDHq06+l7yWHyYydVQ4j2893S6Ywkz4+BwzjD2ju16TSwB298mzBODtuQUpPsq
QpARvsfCtHji/jFDd8nV7jHBZ6boqVbhj+GcpFdqbirek18qod0ANTPPElAVomd/KNy+uEVKkc4a
rFZsVhdM00w/btqgeqCUhXlqF6PSDUqtCSG3m4um7137XZ9QBhrVicS+1oIuCa17ao2MY4+fj1St
OB4Tp0zqcei4ffcetWZcZ7i+vm4FxzGOI8d54noWXci4HkErhsGxzAo/z9y5vIVsZQKd0dhO1uny
nnSEuGBdCwojk5bE1RJYDyPOdQSfOUXc5loYrG3rbREcOmcxGpIRSLe1liV4rh4/4u7d+3RdQ4xW
iQHxS6S3PYej5/Zm4LMf/hDhpY/wq77iX+fFF1+UiJEU2pLj83+87YuJau2hMlra1dZiVt2S4ikt
P/ik5BN+ia6y2zPKQJJCoqt0MycnsemcbIKwkr9rWxBWEdn3CTr9NGjpFMp9WqrUmhsnwzS5vqyX
5VFuMmKUoPNqzdSU0VG+bjjOaCQoKZdI9ZVl2UG1Z/bFtN9jOkfXWfIxiP6BRGekq0oGxq7jYvss
lYDJluNgqGlsJDdzVn+mYLhYSVj47duXHA4H1isLubDerMgxU7DEKHdIivyTY8zMkwcSIShKVsx+
EfNhimgld0hnnQCmxxXGGbqxa0dCI/yMGKlZBIfOGUKODF2HtRbvPYfDsWlvIjFlnOmwNrFylkdv
PhTk4WrE+yCIgDbkng5H+nE4e3BCCPRN0Ki1Yb0e22vQ4RdPQTH2HarrmedEySICzGk+K2k769DV
4GNgGNd0naMUgzOilYkxStxJSKQlUPrEM/fukmNic2vL5APGwDIdxXNUwfuZmqHvOlJJrFYDKSfK
klBaDHgSJ6Lx0yIhY0r4r5kqA9u+IxIaRxbu3r3LOepDSy53apaFojKPn7zOndv3ubx9iydXR372
h7+br/za38//89JL7I47drvP4cP/f3687YsJyGDQoVC2UpKcO0rNaOswubZMYEVKGaut5NzqSmyt
ZEFhqgjexFejqK0onRWtWj0lp1fnLRCnNXAWXYnWN9S1lNtWSSlRfzbdsvBeJYXNtO9TSkUZUTTO
04GaEst0pHQWVQurUUxxxjis6UAL7a2kwJIj67rB51nQhzU1IZnBqMq4GgWw3OTvhYgzFWMtnRP9
SPBTW1v2lLqglWK/u6LrLNEHjFYsMZBjxiqF3AIlETEsQWYGqVJrJIRZOiQn7NlUMo+fPORyXDMM
HUZXOqdYDSOr1Yqxd6w2PapqBivCL6clOSCnQlKZ3JLnrBZgs9EaLDhjGceeJ1cH3vWudxBC4uHj
N8W818yWthktU5w5wbEEdVlxSpMp9L1hniOayLgemI9NbRojtYGYlv0B2w1Y27Ec9yQdWW+3GOWI
YWYJnvt377Gb9xAqzz64x8sv/yL37t5lasmNySfm9jrK2tlzcXHB9f6K1bCmVs0cDoTQgOWp0JlO
MBtVEiZVbY5eLe83g8YYKSayrqYR8DK1sZDn6cB6tcUYK9tC7YhKJAhf8kVfzJMnT/DTkbHTbPoL
/u73fSfPfeCDXO2uGcfhl7z6/nkeb/tiUpF1Zq5ycdYm2jJIAFdpNKkSZbUmmxKDBZJO6OaOlMDm
2t54FVX0OW5RP3VmrE+rWCvkqik1SOeQW3fSzIfaiLpW5SRu1npyA4vXRlM5BaaVWiFKh3KxHoil
QDGkCM4ofCiCBFCZYD3aWsBQY6DvRnwM2KKI+YDtBP0nwdbyxnPOiLBXV2yzFSgFcQnUUrhzeYFS
0rp3nUOnghs6VquB6XgkJY8pkHMh5ITRFovjMC+gKwVDTpXZLwwry5f9i7+Of/SRj/DwjdcIx4WL
zRanFdYYnDm9ZpXj7sjqwW2clQGlXq1w/pqpdVhiHKysmqt5vd1Q2u+vCA9CgEY1YrUjG8VqWBOj
p+tHnHMcDhNKZ6zumhM8C/S6aGL1uK5j2k9cbrYsYcZfH0AlZo/wRLI4f9fbS0oN7I871sMKbU+u
4EDf99zZXjIf91yMPc71vPHGGzx4cE+6u/WIVVBNZbNZEcLMtCysxo3EwK625JTQxmCMI7RgLlnv
RhHjzQtBBQbrUEoU2TEmkgLVRIdFaXJa6IcNikTXicAxVE1fMjpLmNhmLcDxmjLOBtZjT46JT/7i
Z7i4dV/wEeFIVR35LcrPedsXExTkEtBK8ljluGGb9qS2tSbyy1cKlSWcOVWxoGdlwEocJI2Fqayh
NHOekOdl8EoWO7qumkptQ9jTejhjtSIVJcPJHKQwFRn40oqW5oZin1G4JlrDIE5cpfAVnB4IKtD3
AzlKNnCKSjZWqickydVVynE4zLJOXY3UovBeIMi73Y4cZ3q9YtEe53q0tVgUqZxUrFWMgykQYuDB
gwe8/tormFzJZJYpEqY941p8Jhrx/3gfRemLxs+eiriBx/UKtOVjL35YBpGz59atO6RFhsaWSmcG
cZWVwuX2gpoLy+zZXjiMKqhi6XvVNBU3Lm2gMVI0634khZkUI13fs12vSQWMUty5vEWpgcePdhiV
2WxWlGDE89Qcus4Yck2SD1MSq67nen8lRU5VQpCwKmUUm3FDrRIXaoeRy8uO1IBQrtMMw4r1xrIa
L7jeieGwpMitiy0qG25fbnjmzjNcP36CAkLM9LbDrMWWMA6D+HooZC8BZ6syUJQUMZUrS16wWpjC
unMsR1mbg3CAbWfx88Jm3GLdiuPxyGbd43OhLAumgbKEu6I4HmZiqViXxTYSAg7LF73v/TzcXXHY
ZaZpAbNQ/PSWXKpv/2JSQddONipoOY7keDb8WWWhEddKyijXScgToK1BFdk8VCXBRKUCIYK28BR4
+gQoMp/znOQa5zasTVmYsCmHxhTlTP2uGIyuootAhrrWGEFEamEPGCMFUaOpzmCcYZ6PUoSMJp2N
arHNGeQrZSrT/shxmc/s1RIq1iliqlTrUamAzuRQRIxWNbZxTb2XCyOnxHKcMEZhh44cPbVGoDAd
jigtrllrGotkPsWRVnKCi+1aDHep8PjJjnmeefDgGUpODG7reFgAACAASURBVHqN1rAe+/OgGWSQ
2GvH7cvL85xhXK857Has1gM+hPOdcRxXdLZDGU0KEaU0q9WasCwMXc/1/gnZK9aXHXO03Lt7l0dP
3mA5zozdiE6F1dARswxJVXL0a4tR4OdAZ8F2lq6zpK5n8Uc0jpQkIdHogeCP9FZUpv8veW8aY9ua
3nf9nndYa+2hqs7Y9/btKTaD8CBkiGWCIyOBHQehEGI+GUvkCyQG40kJdNKW2wPtOHG7baMghQBB
iRCRTERAQQgiEYWISSYiECk4VsBuN7H7drv7Dqeq9t5reIeHD8+7Vh1bEd3gK+e2ektXfbpOnapd
u/Z61zP8/7//s6b3uMwz43mhlLe3NWzoAm+++Sbvf/9r9OHAOE3cnW85Xt/QDR239/dc7ffcXS50
MRKLY5qU6mxu0nUDKS2mVfIOqRUXPd6bsHK3O1A1EWQwDEOu7LqBOdtq+LDb4X2kaDaBXNeT8tws
ARADxBA53Z+ITyJ/9/9+nevHR66ubljmxPXNnvvThfc8fWJt7TvweNcfJubqhUoml3UoqhtfxJie
FVEhdpGUFjrfdB4NfCPeGfQIj9NKdk3JKhYzqmpyNO9CW7O1akL8JnyzHtYS8XZdjyXvCNFDLaVl
tlqLVWUNoVKc66jVsmbWbZMI5OGaPJ4pamtAQYy+L6WtnOHuYlEQLpij9zKdca7Qx4GslfGcQCq7
NjBN2YxblskzGuAnK6HvTGrfmWL07u5E1w1II60PfWwSc3tlc67kkkgt4Ol8mSwsLCfKOHM3Tnz2
85/j1ddepesFVwaoyvFqYMkTezeYfd47tGaG4apFVtigNcZImmfmeaQUpet7+r5jbB6hXRcZ04Xg
/BbTWZaFq+ORucuM44XD4cCSlZv9NY9vAlKVN+9e0HUdg4M5FVznOd3dMgx7xMPueOTu/t4qNipP
nzxjmkdCvDJX9eXCNFmcat/3jNOZRzdP2O8PzMuJpaEfz5eR6+trXnvtVWtno+Pu9gVPnjxjHEeq
d1wfj0zLwtD1Fs7e91wuhprc7axN8zhqkzQYw9Vg0NRKEfvdLHmkVqXvB9uWiSOIVSvZFWqpTHkx
KFKwTKCSMjRm7v54YBoT/SA8vblGxfKZ3vPsis99/k0++Sufbb623/zjXY8gUFpMYhMnrdP7dbcu
9SEHZFkeAqxF/OY2XYPNVVtWsYu4otsOH1m3MGuwlpXcwdtQVuoDGT0ES3/TbP++FqGKIwLa2pt1
0WZ6mIdfVEqptVPwHd/1XcjhGbTohayVsIt0/Q4fAkuxRJ6UzVdyf7oYpqDCmEbuzxdSWXDeMy2Z
VCupVsa88OLulpTh/jQxlbSxcMdpYV7GzXlcmoHsfJm4u4ycziMVZ7zYXJjmxDgWsirOd9zdn/nk
pz/D3/3MZ3jy7AlIZfA9vhOcr0DhZn9FFwOH3d7+fuhIU2K+LNRsTBqA3WEwzkd0hD5Yi+aE/d4y
gB5I9IU1amK+mLM3eGk8loWr6z2iBXXCkyc3pHmyC7bvEVGePn3KsG+wopS4ub5mt9txdTjio2e/
3zNeTuSytBbLc31zxAfl2ZOnWKKAUd+0zVYePX7ctkNC5zveeuPXeHzzCOccx+PRVr9S2R8Gdrsd
wXnyklrMakKLxZ+4aFu0mipD7EAtTSEEIwmu0gTxjnEZN7mCBM+cE1NqwsgGip5bBjVOmObCPE6U
rOz35teqKOfzmfe85wkhBH7b+5+zTKd3bGbyrj9MBIu2WEnbpSRLnhN76iLSxFq+MWJXtGGLSmgf
ewgZd6RismMDNzeXsdaXQM5rm8MmtXcNH+m9GMHNsx1QzoH67kEYV8rmAQIMRbBS4hrZC+Cbv+33
QTxQvGfOhfvxzFRmllK5jCPTND/Q6tOCVs+8ZEq2n21e7KApmttBUZmnTCpWmqeUWebM7e0tL+7u
maaFcVq4P1mPnJbCi/sTS8nkeeEyL8xzYloy05w5X0bmnCgIb9yfeet85pX3vY/rmxuGPnJ9PDDs
AofeBrmHfqDrPc+fPiMOFlU5TZMJBbVaZVMtUVCCRXOmlKjJfo5usDjQ3W7fKphA33cAXC6XjUFi
Wh1HjB20jZmjMoSO97zynOvjFafTra3elwWhCQKbMxpsMJ3mxDzPHI9HHEIMjmdPHzEMgT4OTbR2
R04zyzSzO+wRtbnOssxbxVpKYcqJVGwucn193Frnu/u38QFSWsjLjPdmDbAYENOQDIeBlKftRmjq
WjP5AbblksC4zFQKd7dnhsGqObtBVk6XM4qzHOp5ZpxP3N+PDMPAdJl4+vQpOWfu7u64nO44nd9m
Pp/4nd/wj/NlA5ReWxrd8lRAQnPlVrvzrzS00FL41jdv14Vm2We7+1v0grVGIQSLpKhCLWt8hoVx
4+pWoRjtrNo6OK8iJwtMx9sQt7b84VVm77y3GchLrM2XGZwiwmsf+gDf8T3fx2kSllKZxsw4ZVJW
fDSI0zhOZDUz4pSzRX8uRp9XVS7TzOnUws6nC3NamCdzq45zYlwWTqfFKpp5YcnCNCVu705NV6Gk
DBnj045T4jInxpRZMjjfc5oSVZX3vv8DxLYu77pA13V0XcdhN7Brb+zHjx8ThsBut2O32xnztmai
D+QlEQfjt4BVKdHb3TZGs/dvg3QxvIJd6PD48eN2MxA8AVdt2F1S5rDbW+uYZ6QqSxq5ub6mD8r7
3vsKfYjEztN1Rsq/Oh55/uor5JJYlqnpaZTnz5/Txw5eivhwYoeiiDCdJvbHK/q+5623bnEKb9+9
zeHqpmUd95tytnd2c7naH8hz5rCzWIvoPTVntGQDbA+DLQpWdouDXNLmKJbgOU9nUk103jEMA0+e
Peb27p5xnEyclgqH/ZWBvbsO5wLH4zWHw85iOnJiP/TkBB/60PstPTEM7I47U/e+Q493/WEiK4ZR
iykpg7cJvQraDHtmmbGVIFgOrBdHKkIxaIPNPpqKdk0DXOE0Jv6yOIaaGi1Nmz27ND1AMseyqjRa
uz4I0NQoXOpkU1PqhgqobX4g22FjER3WsoTdju/52MeYkiOpMKbCmDJVIsXBOVmVUKoFeC2zEdnG
lBjzQq6OXJR5yVT1LHNlScqcMktpYOOqTM3HU2qlOE8RIalwGmfGaWbKlQVlUcc5Z6asjHnh1+5u
efT0Ea9+4L32s3g7VH0TE14db1DvDeW43zHPqflEBtOwJHs9pmQH3TJOVB7AP6ltYNYDpyGq6PuO
p0+fsOTE8XjVWthA13vmZSRER0oLx+OhKV4fOLzrwbTbX3F/eyLGyPX1NYe92f7LYnfv4/7AK6+8
Yq1IF9EC43TmfB5pwmZSztzfXvAS6HcDNds25vHjx9zd3RGckGZzeJ8u9/RtxZ1bP+ck4mPHPC0I
drGv4WSHYUfsI13fCHA503eDxaF6odQMGJOWUsm5sjS5/X6/Z5wm7u/vWZZs7avYAdQPO6ZxwYeu
MX2svXnr9i2y2uao94Fa4K0Xb75T1MZ3/2GiaKPSNxRiahAkVWOqejtkqjhyNYZo1UxFTCqcFqDi
FVK1YadvQ8r1jmgUMsPv2V2oYe6cszGrKD6YD8cSBStOq8VjtHCwdcXpfL9pV7boDWWrcihrw+a2
WY74jj/0kz/N8Oo/QC6R6rwJyFSIrqeocpkWllw5TTOpVMT3qATO82QHQa2cLiNzSkwlMS/GSlXn
GafEeVy4LJn780JSxyXB3XnhflnIYeA0Zy6z2tB3d+DFG/cUhOevPON42BHE8eTpoxYWJkgUHl0f
URWuj1eI9+wPA9fXe0LnDWjsnLmrxdIE13nXabw0H06xdawTbt96u/ldZGPVzMvIo+sbk5i7alod
8RyPR06nE2mZDPeomS70dqF6wdXCPvaUeSF6g0J4F9HqOeyvwDuWvNiGbinEMHB9vKIbIof9FV2I
BBepJeG18tqrz5gWaxmG/c5SFbVwf3+P+ICPcYOAJ7VW3KEMXW+QJRLOm1N8TslSFdpMSJeCj7G1
RjDNI+O8UHLzFuWMaqbbDYQ+IMGqWBcD/f5g1aoTdrseFQgxMo+2/XnrzTeh3cSmy4m333yTGHrO
dyOf+7XXGTqPpvz3vO7+/zy+4GEiIh8Qkf9ORP62iPy8iHxf+/iPiMinReRvtv/+uZf+zUdE5BdF
5O+IyO9+6eO/XUT+Vvu7Pylrzf8FHsH57eJfL2Yv1SoH1xNdhAJOEk4SHsG5ujkxTUBmh4hpU9rg
1vnGHrFfLs76c6ltIFst8c3iMDxeHzJ3tOleanUIjU2LR9rvJucFrZnOeZreCFXbAYWX7gWrVwfg
+37g3+KH//0/zeNXP0Do90xzbW2Ux/kI4qH9JKrCMmfERUoW8mKVDi6ACipCrpF5ysZ6pbKUCj6Y
IM45Qj9Q1MxyEnuqC7x9P/K5z7xBd9Wx3x9MjLY7WnsogfP9BZJyGHaMc0Jc2aqBNe6j7zrTnIRA
6IyEt8J4Ssr2e2hDv6urGzO6eWc0+mKUMpVq2AYFxA7rY9/RYZXnk+un7HY7exFL3Ybl0GYMIXB1
dYX4jtjZZqbvIzUbrS76uL0fsl42FmyuxcyS8wVxjlff937ePt/znufPrWKtllmdc6aL0bQ+peDE
hqwljZQ5M882+M66gOuotaU/Ilw9umI/9ByPR/rBlMYAj44HjvsDQxcRZ27zGDqie/CJ2WvtLS96
Saa6TUKujlTW97HQDT37w4G6JEpSrq+v+dqv/WqCg1ceP+bJs8et7Qq8UzOTL2Y1nIE/rKr/m4hc
AX9DRP7b9nc/o6qfePmTReSrgW8HvgZ4DfgrIvIPqyGd/j3gDwD/C/BfA/8s8N98wWfg2soMu9AL
JhuXypaNYnJ6T4hqgdZqXhxtiLqqYk7hmpGS6IaOtFRKxhCAojgqGfP4SMp4b6HZTqRhEFYJvpB0
RlyLyZBsa7120BmsraOqOZEdnrr6e7D5h5aK+G5LCAwSECwz+Ds//BGm+cxP/vBHTQU5TngtDRlo
WgUtDficMl3wSI2kar2/NLOYaw5pRXFhoGoxMr63VbPreo4V3njjDdIy4dXYIft+4Hi15+p6gJqZ
LjOx79uWzJQvPu4I0dS33ntiNADRmBZ20qMi9KHHVCzGeBnHkcNhT82FuYxbuZ9rRYtQmlx/3ZoF
F1jSZF6dWnHqON9PuC4iwZGzrT/RB16JqZ0N0C2q7Ppo8aKLVapOKku7G59roe87ottznu8JIRpj
pevIyeQI43zh2ZOnttrHcz7fkydDPI7jyPNXn3M6jTy6OnJ3uqfrAofDgZwTebZZ2a6PJG/Y0dgO
TecjyzQzhIh2FvFq0G7DYqaieMnEaBuglBJzqszzQugC/dCRG6T7+sZ+N8fd3n4fKtRS6fuBnBO1
yRJC3/FLv/TLvO+1V3DOeCqx93yR9/Qv+PiCh4mqfgb4TPvzvYj8AvC+/5d/8i8AP6uqM/DLIvKL
wDeIyKeAa1X9OQAR+Y+B38cXcZjYDMNWrarVwEUmKsXSZFo4NbahcM7u/WslY0rLNUwLFCEtuW1r
ADKqFgnq2obGwNWWBucQ1Bk3RWlJ80VbwHlp8OiHIO2VlrXyT1aNCeqQakNUi+/IW+lfMJqTtT2e
3u350Z/4aaoqJQif/qVfplwu/E9//ed43wffx9XxMb/yi5/kdP8md3d3pDnj88T+cMT7yO1nPmux
CkHJyRinlzTz6nte4fNvvkVOQrq/4HwlZSWGHVoMQLU77pDgXnrtgqmC1cxw/W5gyTMQyW6mqwHn
DCGwHwIxGMB7zmOLp2hrzhAZx6kNCgO5RbBWVQu4mmZCdEhTx6rTzR7vnEOKw/cdmisuOHxvraKK
MpaWokcgYT9vHztElWVcmNLEcLXH+YCvFfBIsLwhG5I3JXQ0w2HJmcdPH6EqHA5X3N2/xbAfON/V
tgzQ7ZDb7Xo+9+Yb5nAuph7ugmc37LhcTuRpxlHxwRO6SE4ju6GzSFKxSA3f2MK73c7ety29IASD
he/3PaUdHq7aDcXHyBtvfp4njx7bjaa93yU6Sjbq2m5ncOrXX3+d4bAnBMebb73F40fX5AyH4+4d
m5n8fxKtichvA/4xrLL4ncD3iMjvB/5XrHp5Gztofu6lf/ar7WOp/fk3fvzv9X3+IPAHAV57rwmD
SvPjrBGH64AzO6jJJMPOe1LVDV6kTuxOLQYNFm9vzIKAglfwwWYmqkrsTC7vcegaX9DWieJbclwI
bU1sJXitQsKGh0re/g0a8E4b/U3RaqzYpHbolWLpeaoFtxL1xaofLQuKkJtuRbTywa/4CvCOr/za
f7TNcYSv/8Z/sh1eGZCNg+qco2ThdPeCX/3FX+Kv/OW/zHL/Nr5mbu9PW+Sm956Ko98fqMtEF/d4
MQGe954l1w38U7KtQIPvLLZTDSaVS2+c3GpVWVqU4BQJ1m6ArWFzqiQpZmBcKhIGvAgpZQOCo7Za
ddEupJzZ7/e2nVksMa9Q6H3ARc/9eCaGni6YxyrUYrlC3lNz4eb6yP3dmTAMLGkyH9Bih3e/O/Li
9i1rVboOH+3fTNjWq+TM02dP8a2CS2nm5uaGkjKPnj5jOp94M830nWk7Sin4aJdSFdqNKjMny8yx
KkkQJ3Qh0ntHyQUfwGmkDw4dPNN8oum8G8U/2JA+OMY50flIdaVVH+ZFG/Z7OwyrsiyWe2T8JotY
nSYzh64YC8M69CzJcKRd6H+dN+038/iiv4qIHIG/CHy/qt5hLctXAl+HVS4/9Y48I0BV/wNV/XpV
/frHjx/ZC+oMtrv22q4pBylsaXylRUNAc10qzYJuOAIb1FrXFNugr9aKtDInJxvEUguhRTzkto6V
qtv8BexNU6sNwoIXqli7svphlAdNhalp60Zls+cfjI/CAxvWORMxibeVtqM9n8aT3eIuV81L6/lN
ydvWqe15+SDcPHnM1/2Of8LIbTWBt0jQKtVei2YfCCHguo5+Z1EUonZBzHMiFWValk2zkRV8HEgt
vCqVzJQS9+NMTpVTmsmlNPGUIS8BlrLYYVGF2n4/KVV8F3HBN1OdkrMdvofdftP+rO/13LZ5pVZi
7IjRwM2rXUBVjWkbI3e3JkQr88z+eNxmFjlnzm3rshsOLKlQcrWZzVRafAWcTidowPGcZmo25INz
sKSZw7DjsBu4vrYw9v0wbKR35xzRd00AWSxNsMV0rOHqLrqNTp/zQl6MSN81bKS0TOQYm5xAKsOu
xzubc6yRKME5xvG8HQi5HcRLLczLAgipgdU/+9nP8fTpU27fbkHn2aBS71R2zhd1mIhIxA6SP6+q
/zmAqv6aqhZVrcB/CHxD+/RPAx946Z+/v33s0+3Pv/HjX8T3102co1KbQeqh+nDKA5HKtS1Ccxe/
9DPgXNguxFLM8FcolLZWxAdEPKW1L6vYzdzJ9rVW9J5pT2jZxDZkdGJxi1XXN4Dd4YOE9vzK9r9r
Tg+q2zzFUnzEDg3vWttkkCFbgZsNfQ1wz82qvrZJ66G0vkFs45X4I3/sx/nwj/wwz588o+8MW+DF
RFp1RTzEiCotr9dCpHKx71sW5f4ycp6a98PXNuugraUXXBAu8ww4ipoNoTa6P1hQWcnCXDJFYRpL
86nM5GyHz5xmxvFCLcI0W+VmZikLBBcfmm0BQFlb/RgjvQv0IYJ6lmmmix6thmK83F8aklMssKwJ
ys7jiVQsO3gZMzXXbZjsfSTXwv3pbYbB1LypFlI2eX/sLJXRi1WOrFyVy6VtZFqsqbfge0s6sO89
50R03hYEAfb7Pd57hjigJZHLtJHzRWwz5l20+ZoXppzItbJkSyfooiE2u24gxo5+vyO6gPc2k9p1
9hz2V3vu7u549bVXwUWUNZnhnWl0vphtjgD/EfALqvrTL338vS992rcB/0f7838JfLuI9CLyFcA/
BPz1Nnu5E5Hf0b7m7wf+0hfzJLXQ3kQNsqOr+rSJ11rmbxBIq3vXuYchbKOirf9lzTYTqTbY9QKd
D1DaoZRtM7JujLbKQcG3fxd8h1O7oFbPj0VTVtv3GwIOYIvg8C04fe3PnbY5CjabKVt75o2V4r3N
bWhV0Mq3VWkbHePYivgWyaGIOov9aM9ZcSx5pjvc8N0/9CN8+Cd/ivd91dfw5PE1w2CSdtVsZj6x
9XlKBc3OKpOs3I8zKWfLWfYO7zpyVWPQYol/82wZtsuSuBvPUIVlsWTArJXanNzncWJOloF8fzeR
cmVaFsR7ipoJMiVb297d3VEyZDE2jasV8z/RZgSWCiAihK5HVRiGnlQXcrGK63QynUnOC+N42Zy1
y5w3Ipv3nvMyURQu09lWrCEwTZOlJKaZtJgeqe92xOjphoEuBLz3HK6uid6qiuvra1I1VIaTuHmL
fGu/cGJJgGWFeJsK+ObJYw77Ad9FYuzxiP1uqlUawdn7GMC393hwdqiFKLz+2c/Ye7u1XUtJBv8S
mx8ty0QQ4Xg8Ms8LmmfC3jGm6bduAIvNRv5l4G+JyN9sH/sB4F8Ska/D9kqfAr4TQFV/XkT+AvC3
sU3Qv6EP4RzfBfw5YIcNXr/wJgcaSpGHeIdkqsSiFc2FVCB0lvU6xGAelvXFF0GKVR4mf06N82p3
Eu8NbpSK4FxCaHoRpAl+ShvGCqICPNzZCoUoAW2yfSfN6btMSKDl68Rm4ipkLda+iLVNSKuYfERz
2YR0ImI6h5oRcTiVBobW5jyuFDKiEaqBnbS2A0ZqGwg/KG2jt9ekNHvAv/bd34urBmf605/4SW5v
HX0MXC5Ti9C0QXTvOtKSydkiKpdSSCmjQw94KHagiAhFF/I04oLn8eMbzinR+/Z6KNRS8Z0J7HKa
yF2gDz0ltwF0yehSyJ2j5sqLFy/ouz21LMZuwZML9MGGnvMyIc5k9aqOogvD1c5cyX7HeTGE5Pk0
48NA1cA8TfRHWwHXWi3cXQUJwuX2zJPn11xdPbdDSoQonjfeeptXnz9rlaoynk88enRtkRN1T11m
lsaOyWmmC57j9ZVFjxZl2FnCYK6V/dGo+UksyVHEwNoqAXJCxPKZo7PcnjkvbcDf2q1sbfP+eODu
dNk4tKVUnj9/Tq6Fq0c3nMcL+65nPI/EPiK9GCn/zTcILSwsp4W9H1h2UN6h7Jx3fzzoV/8j+p/9
+T+H84oSqTojdE1IBjlZ2+DFUavDBdvsrDOFFdMY24UKa6XgW3UAvknuczVnsKijaMZLoPqK0zb0
XQO21hiLl+TxXoSiaqWec1S10PS1/AVMLyE0gLA0p7JpH9St1ZRto1xRirOVd2lSf7MCFIq6l763
AaLEGcRZpdqQtK4+ZjtIex/I2iqtdoit1H2P8u9+/I+zTDOME/Nijt0lTfRxYFns7jWnC1occejZ
DR0u1zYTiAydaYGyZuq08IEPfZDgofcOzSuJvSUJ1sput8M7WOZMHz1xiCyXM8fdNZBxolwdH6N1
pu8HxNWNp2vRgELOFXGZZS6UYvzXZVmabylzuZxYcqHbDZtCWcQC2ayoFSqGoxzHkavrnTmbXUDF
0fU2uO97I9h3XUfKE4+vb5imievrR5xOJ7pdR1oKOdv8Zk4L3juobPnNFoma2A8dOc1cXx+htJD6
0tb+NVNqtu3bslBbqL06pRZrdy/TTBd7pnncBJNOnW03u4AUi7TNWS0cbR6JLvDZz3+OD77vfVSB
GD3znOmCEvyOD//Zv8ovffbFb7o8edcjCNa5g0UaVpyG1qMKeV5bGqFigd6O5qloWw0t2sT0D4+a
KjH6xjnx5HYy21xFtl9QVXMrr9R6ciEbuaThGeOWtmeMU6xVEsFVZxT7+pBlzPq9nOlNXLVoSQmC
VmufnNigOYsSxZPbTGZdHdf1ECkVWoA5OLTahe0kWByqGCiqYOjC3Gzm4kKrmGTbNGUq3/1HfxBK
JnvP9OJN/pM/+2eQkpApUb1w+/ZboIVaEwkgVXpX8CKtRYjGb5kLNcOSEwFL7EMrlwabpg1kUy6M
qblnPaSz4rzpVJxzdM7MfUqy2Ezv8D7gnQkCpnm2A9t7O0hw5GyIgNPpxPliYfdZK3VcQDK5KZ+7
fUdeih0EXcvccUoqSuccU1mIzuN9T17gzc+/xfWjK+7uz9xcH7i/P3N12HO6u2fY7ygtISDGYBnY
WOTEPBviMoRIKdaupGTtS22piqqFUhd6ZyHmWpXDfs8ZkOB58cabdP0OFyFNBrd23lqcipDnhb6P
SAxcLhcOux2pJOZp4Wq/ZxgGNJtuJ1WrjKUKNSWq9PgefitFa3/fH7XWBmENBpTO6zDNCLG1ttGl
q8ypJdxjUB9HuxM1+/96R1/do85ZlEVOVqouSyYEx1IqXVslO8WGsIJd4LXaXKINOUNre7xKWzOZ
bsU1S+Gmmm0zDXHaVqkFH9xWITkLK2zqW1v3Sm15xTQUYhO5KUrANkBrDMc6rLVkIKukjNxhLBcT
2egm7IKA6oI0haXzASmFw81j/sD3/uE2RLa0dqnK//DX/hqf/Bv/M7fnC7hCnYvJ2StMS6ELiguB
JS188lO/ygff/yq7zlbvLtj2KudECB3zPIMP1LTgguU757ky1YUh9tRgbafmgvRQiwI2R1nT+Vxo
A82UiL5jWazlCrGnGwpv357Z7XbmVlZh2HfUPLNMiZQzXR9I88S8ZI5Xe2OqqrLb7UnTzOVsqYEq
jvv7cUsBsJwdGrXfqsQ0GtoB79j1nvvziAtCmrWhDaxtTs74tAWxBEogenuN9jsz5qlWdsPA+XKh
HwZACa5DQ2rv28CwP3B/f8/18YrXP/tpnj17D10IDPs9p7s7nj17ZsmCwX7vp9M973/va7x48TaP
Hj1qdof2fv0tnJn8fX0I7WKUtsfP9iaiaSGktSil2GRbW2peQbBQ0NX+bw7hUm0NaG1RC/bG4T2b
S7M2KPS6Ei4Iqpkgbe/vLNdYq2weCws0V/xvaBuNaWIXAlWtxaomCdetqrHhcinVxC+14sTyacRV
Mx06Ndm4tAFue74AIXQvuZLD5mpev+4qDBNosxd7szufgAAAIABJREFUAzkxQ2NtgAfVBx7uSuan
bZQqlW/65m/hm77ldyEi9D7wJ37ow8TOUcSRl4nOB5Y1olWVy2y6hugdOSWimCXg/nSh7wK+KopQ
5wXvo3FjnK2vc7E2prNtOV2vpHRuw1TbMi2LrZtFISerfMZpMdzBUpmWxFJNv9INPSwjzhnWEDWQ
8zQuDMPAPCVunj0i5Zl8bmDuCrdvvEkIHcera6bpzIsXJ/rO0ffK6XJhTonjlYWOGV5CSEU57HZc
prmBv0O7XgXxLfe6rMprIXamlp6WiRgjS050LjAMe5YlI1RyGXFe8OpAIS+WM1y08sor7+X111/n
Pc+es0zTg7ZF2Cp3E8MVbm5uWohYgVKYzxe0fplUJusGZtV8WIg41j6sQeJiVUXNhS7aRem8o6Xk
4CVs8OggUGtp4tR2oEjYHMVOrXyUNtvw3iNtOFrQ1vq00GdrPliZrw7z3+CtpzdX8/qL0lZ5NIVt
TduFa8pLb4pcfZjnAJYXRMWr8VpETcDn7LvxMt5AtVDVbXjI9ZDbqh3M78L6uQjSvlJt6t6qNny1
z7djsJTUhteKE0WrMpbC93/037af2zk+/sd+lLtPf8os/P0eT+Jzb73g1VeeU5dELZXqKzUr6jxz
AY+BgbouIFIRAlQ7+DQXFl3QQ0S9oosNxlOe2fX7prNwnO4nvJcW5WHr/ylNLMkUtJd5RlBc9hT1
9EMhZ7UURELTEcHhxjiwXYiGxSzKtIzgAvOU+Pz8Jl1vEv+qyuk8Gjw7Ri7nycLfcubq6orT6cRU
FoY44HaDOXtzYr/f49rvy2H+qHWYD0IfO6qC5GyJC6LE4Oj6HWlZuCyzvU/XeNcpbUrr1157lfN5
JPYd3tusxzm3cY5fefbcmMYILz7/Nodh4HA4Ns7xO3OtvusPE9YNTptcm8iMdqe1IaJQKbUQoiNT
7cTHQr2DMy1JDJCrzRBcG1xaifoAqo4xkqpRyUyaLThKI8+vFQ4NU2CqWCO12QFT2uGhqYWje5o+
oBgfJZvOwTlraXLONoDVbJmz0KoisTuHOALmr6mA1mQKUVkPodJaG7Y3pAcbLmKoALBho9kEVoO/
BZVp5WEg2yZLIms+kB0m9po/cHG1qX9Xs9QqR/83P/JRXJvhxKL8xf/0Z/nU//ULJGdgoID5RUoj
5JWciRIJwTMuiXk2Ts2AUdGoisSOZTHLPM5wirTE52maDKvpPJfzTOxs41VKYZwyS1lMN6SFmsxF
7gTmlBExho0JlQP98Qg+MI6jBaSHSFpmI9Rp4XTOXN/sG4bR9CzTtHA4RPKc6LtICRZ8dTmPRuHH
zJalJoZdx94NhlEIPbUkiMqURmL/xAh8zlHa+9ygR+DEQFBT47ruYmScZlzwBATpB6Y8M82Zw2HH
4XDgcrpQHTy9uTYtUrbKt+ud5XI3XMTbt7fs9j2v/8pneKeWMF8Ch8nD3VxLRYKjpErsLVjcxGx2
R8qpELpIqQUw9ycKvjO/DFIIdHaY+ErJ1S4wsT40V+OkxMaZVSekUumDSay9RCgGhpZV+7DdXVpe
rY92YHnQ2qoNb34gEdNIqBru0aoEo99rSyQ0pWZmzfepbc5h1Vd8qdrQh42UA7UTlowBfaz0agBt
BEWtxVFAHcuc2yahmpdprUTUnmN1ihbbUj0cIkpVT6mLxaFK3TJeQugoydqw7OD3fvt3EJySqx2O
f+ZjP0xa7qA4lnHaSvAipvUookhRzpIMcJwKSSvZmbgul8J0vjD0kTkn8mxzIvGeuRQuZ1PpehdJ
Wi2iBAhd5PayULtkdozGYTkvE7t+x2HYI9V+N6Hv7D2VMtNkc5EYe+KQTasjEZXIOCVC8JwvE8sS
2HeGadx1PbELOO9xzjY/81S5uh6YU2Ho91TNLJPhJ70fGE8vLJFwsEFw1/dbJbmkNRlRG+O3RbOU
1ipRcVXY74etgu+Gjrfu7nh8c0Bd4Xx75nB1QxwOvH37OR4/fsxxt2PJC8FFDtdX79D49UuAZwKt
dQCqZVwRvbODpd1FH2YHbV6g4FacgIe6pdP1LCWTMLewquC8HTK1ZnzbDljpp/gKUZSkjt4ND6pX
TGOyUdxq3Ya72i4+J6FtcLJxT1vGMNA+bl4jp45aoKhsalYhbmHr0KqFBmHa2jrncK0fBxO/rWpT
rbKJsbxzrRIDqevnKl2M6Iq43F5nZVUKhyL4xmFZKxaDjWZL78OQBM5Hg/dsn2MHuc31BC/mX/pX
PvKjpHBAYoePPRnLJFqqCfymaWJJmSVnxnEmYYfUnLLhJJdEdY7LvHA+F6YESy689dYtt3cnzpeZ
qo45Z85T4fZsMKbxkiglMZ9n6lJJRVlyJY+ztcbysOJXVeZVsNgwoC/ePrGyaKuwQaWXJbMsiaow
zmnbzlgkSmjZSR5xNv9aBW6dWBtStMWqdAblCt7+Ny12iNWsxDAAhX0ciKEntq+xcnj6vt/UsylZ
y9P3kethx+WcmCdld7gC7Hk/ffS46aOUV548Y8qJw/7qHROtfUkcJtLuip4HSb2WSlErWe3v7S7t
JYCzC7PmYj262puabC+4NB+HQ0AbI0Skyei1rXIDWRdrEar139FF+/uGalyrEo9J3R2mM/Hem5CN
tLU7FpBu/fG6kkWqsUTUhq5Bgt072/dYDyXL3XFtQsM2THXVUgVLwyT46vCrTB8eGDCsB127cPDb
unrN6oWXWhx9kO0/WBIqUipBhSB5c1eva+itDZLQhGpWlVRMsewDfM8P/Rjf82Mf567Y0Dgj5hz2
DtcN1raoohLIpVKqcCmFc66kIkznibJYENj9+cTt3aXZlRw5VV7cz9yPE3PKpKqcxsqUMhlPDYGx
GBLiskyMy8JlnMhZKeoYL4XgB2KbXal4kEjog629uz1IBOfJleax8XbwVbgshdv7kVqUy3SxxUGu
XF9fM+WxDVpt2B1jb3J9rVbpIUzjaK+hN9ZLqZWcZkQ9S8nErql1naPrQ6telaVMRB+4vj6i1fRV
V1cHVJXH188J4ra849W7pk0PU5a0bR7ficeXxGHCy3ffug4mgSZbFlGopaXLW+lNLaiz/0yoBD5a
GyFdhwSjehv42TVDnbUQXoopZV330MakvMGga60PCMhaN7k+zpMbCxbPprJdiezrXdBATt12aLkQ
topmfWguGzjat0Nsq0r04eJ3zlbXhnxpw9iVQ9vWfrZab6DsquDLZnJsGDgberb/qi62XJbVsmBV
XBXzDpXm6XD1wdfxMAi3A8gSF+1nKaj5ZMSRlswPfOJn+N4f/2nmzuJDx5QpWpkxN/FSMqXCXA2P
MM1GiUvquJ9tQ1PUM+XCmCdenM5ccuW8TEyLclkWztPCvGTGOVO9YQHUeca5cDlP7A9X+BiY5sT5
cjHD4rSwjBnx3hCZy2JYhf2BUgpZq12YWsEF8jpz2jZeYjOcFuB1mWdQMfczjrq0gX7wpJpwElim
NZvILnBXhTktILZ1NLWB24bsXdcRu8Eyc4ohJLveuLxrQqBt2zx/5xd+3t6f2a4BKbZFWlvl3W6H
cw8yid/s491/mEjr1asl9al7aBfWqsS8KhXn7BdQ1CzgNpx1m4JUSzWnbS7UVB94JvIQTK45tQrC
vr3WYBxZ7wygUh5I85s+5KX2w+PNoQtth1/xYuySWquFmzexkgZMZt/iMHPTrawboV+HfnRuu9jX
75W1GorBO0NJuhaTUFc/TzavjrfRrPcNgl38hmbwEloF9NAaORfs83SFKrd5T5tv2I/mHg7R9rDD
NW8fC8FtDu01Z2j1Sznn+OiPfZzv+vGfYP/BDzGXzPH6hiqW/7KUbKbAdbailXMjt19my1/OpbJU
QWIklUoV4X6eydig+zwv7SAzrdzlPDYpPSC+OXvt5yulcH86o+I5XUZUYBkbBkHMC9QF1zCfFplS
sUPN0g8NNn5/d0ZVOM8TIZo3pyyFro+sofdlKTi1nBzxwSTuu8Pmz1rdzevNyzm7ia5ogujM5xNj
xOM3yLmqUrLNjvp9z3vf/x5++fVfxTetT/FiDnFfSTozzZfG2vlyaXPUEIjOmVitLLrNFran7xTj
pHmbpbQS3vglzmDOxVGc3SXXi85tbY1sQ8jaKg68NndwbloRO7S8Fyh5i9FYL1CpK6j6AZBkFYFd
6Gur4VaCvubtzi5Obc3dDgURj5NgA9PSVs6r90YVarYKA1jbkG1Iva6UVa1tYA31SpuhUDx25xN5
yRD4MB9Z2Srr17GV8683SxbN0LQs28/WnpJv/79gB1RBH1bvMVh1o+tFUPlX//Xv4Y/8O3+Kr/ia
r28+F6Fs+iHzFFW1geSoFSSYPsWbQnitCJaGRbgsCXEW9rWkYoP1JrkR580U6Cz61HtvVn0RtJhR
UYsNyJXS5iMTYPzWebIbxbIsiLZQ+vY+LFVJpXK6vzBPZcNPGGJg3m4Kq+huWczQKC5swOyVR7P6
lcz31Fg88jAbiZ2JCcEsFzY7a22sNzd47HZ85Qc/xGff+DzjOJtGy9nNNSfDmgbfvVMC2Hf/Nkd/
w08aukjNNuWWUsmYYW5F09XG/KgAed3UgIRKLTZYTVrovLEwFDFW24qFRClOCTics1+eF+N2xEZ1
t7RPbQT8lpfrKrUUgtAiCxyl5kZja8hHtL1BdfPy5JytclBQNXC2eoVSTGbvFFPCmhvZicM4r43e
htuUuNvqXOThVWt/3jZATVLu2set0mlfd/v/gpElpBkHbdW+tnXOgWBCKzvSFZGIuoQUobiCq/Zz
OPH4YhVJ8IbUXAe1VRSnhhIoqfC7/8Xfy7d+2z/PdH7Bn/oTP0HNE2Wu1Go5z+oDSRXvDFfpnNga
txYQSAqqRnErKTOliegiqdjGa8oLh6HHBWfD2jmRvSDiGC8ZJ2ZkdM6qS4srMdFdKQXnoeTW5oaO
ecn4zvIYU7GA+853ZvAbOs6jGfOG0jE7k8LXYNJ231nKwrIsQDABocC0zFs7U2uBWjmfz3RDZOWr
jLOxT0rKuMFRUlvvV7UbZ12oxfxhpToeX91wOp2aYbKAcwxdxzJNhGAygXfi8SVRmYi2uchL/V1K
M3PrV2s2mfoKTgI2TYj9GbQ0412pqFaW0sDCje0BrW0SJXqT06eakNAGYDGiTprh7uGublL7hzCv
gjQ1bia2eY5zzvKJq26tDk0s5l8aslo+UMveaVsWqXaH3JguRj9qFUqTm4sQXRt0OgM7r63OQxuy
6lxrm7nYHAXYDqOHR4VWHQlx/TXYa+n9hjVwbX5jFU1q0n8Fba1TkQZHanOn8mArWDdZaohog0RV
oCrd4TF/6GN/nN/+rb8HpWN/uDFfjcAwHAl9h+8HkhoNPteHMfGc2oUULCPnxfmW2hISa8MSmE5G
LTgrGcTK+8i0JKZUmHNqsgKbv4X2tbR6QrSfN4SAk0Sn2syYxcBGLZytYNumKpBU6V0kdkY10wpe
Q6uInf0+1KHp4b1wupwQhSVn9vsD0e+ojdkzzxOlZGIfcbUSnad3AedCW7sLzkW86xm6yOGw59Gj
R7x4cbutvEUsPfBynt6xAey7vjIRkW3tSrVKxYlSoM1JhFLafGA7FDzqChQI3lMxkU+trmEMbHWn
0YGPaFkQCebGdQVpK1ML5HpwdqoqwQe7T1dtkCBDAgBbZeC9b0DpbG8ct969KnFdIbcLe+3ZEZOT
ra2McxbZgdjHgjPkQm1ZQSLRBq2+lbtqDtLOBXJ1SBPQ+TaMBZqwDkIv5GRmA1XFaxv0qWuyfayF
UbUxEYYcXNfD2qI9gjgWsrVkbfsjGsHlrZ0Dq7qMKSfbpumhkipbC6TrwVtNqfnP/FPfzDf909/M
vuv4q//VX+J//x//eybAZ+iDzbV2+2vG6d7aynmhjx3qC945Qn+N3o2cXozcPH1GmO+ZJ6s0azWP
0N3lzPXxmjmbPB3sJmRtolWnznlqLe09wKbGrtp0P9i6NqWEA3JVpmlhtxuY55EQOiYtdGkmhoFp
Hjf4tYihH3e7npwNAeFdRLwZVyXb+zmVheCNPRMb29aytZM9p1Z5Ho/XpJqoLNTqCSGy5BnVzOPH
j8k5UQqkZCODYdfxZWP00za3QKyPtVPf+mTXSnzx3hAF1SGltRIJcN7MVK2Z90FIyS7a2LifimEP
S6sMaha0E3TNF06F4ptXp1SyVqPWu4Jm2gVg5PHSeCVUpYjlo+hq5FsVqavnZT0cVVjaAFZYL/x1
0OqbIM+RVa2VI+AEqmSqOtaGZl0b6zqDQXDVvEmIILqS3LNVcmI2AG18W9uMGYXfJlCG9DPukr1N
VO0QXVfxqSheI1VyEwFVU+Bi4KLa3NaarA1ZH6KYCa6qHWhOkWoHLk1HBCZpDwXGeeYbv/X38I3f
8rts9S+OX/nk/8l/8Rd+luV0AYlUrfhgOMO8KFlhiPYuAQvX2jm1LCVpmTXicdGc3yKVaTHZwfF4
JJcZ54KJI3GkNrcrpRiLRE1LU8kNuTiQq7W+u27HuIyoFrreN3B2QcQT3cOwP5e0bbxW/cfQWUUa
fceSErUqy3wyWHVOiHdE75mmNY9Zcd5vwkZoeU66xtQ6ggriLPBs2A+G5UyphcYVvmwOE3Qtw80v
Y29im0Cv+EOt5pmppaEFUiFEy60tFXzVbRUanM0BsmKREGq+l1Waj7e1bPCRkpKFkku1AWRTkJbC
1r6ImNw9oLjqyKxAaSWLtlmHDb1818DRTq2cNdG1tTsOg/K0IZwKbYUMSMWpIM5gSHiPa5uopWYC
RilbRVPrleu8tzapFooWYmPFVm0XOTyso8WEeM55onQs1VbSNmPJW+VUMSGWtq2VSrHPwZgyaN0M
ggqUJW1DWN/e7CrB8A/YTAU1oDRS0WwrdtFqVZk3jIRqxrlIwbxV7//Kf5Dv/chH7dDVyid+8KP4
+1vqYBfGNE0t09jT7Tquh55aRtICvrP30Tye6XeHZrGIhGiH0ZIz0sx6uUBeTuyGSErW7vYxMCf7
HfXRYlFTGunjYHyUbOHh1XmWubAbAtN84XDYMaepmUJLQ2UqaV7a0F2bidH+t1AoS8I7LMzdWRV9
2F8h3uh0UguCkosZArtux+XyAlULpXfBNwasUFKhZrOL9H3PPI9E328t+m/28e4/TLDrp/pKUMvv
9So2hNtUpYVSBR98G2hGitocQ9QqkqoFLQ5xATS3ViZatk2bgmdRJIF2sg0yTecxUNWoZ513pNri
MauV+2hhXMq2WtUq0CI0tQo+CIRAydX8Q7mAawrJ7Y7igIxo2oRk6kG1ZdM2b5A4xWlBvYGZvU1D
kfLy0JTGDxVwajWcKqW1He4ljcw6+1FtLBUaYuGlUsJEbvZn52qT4GcLMRNrN6PrW1tYcWp3S5EH
9XLXMoeyCiIVX2mEOGuPXFsb03QzprA1m0FcW8naxr2rbogGmarwfT/6w4RuYL59m5/62MfIpxMu
dhyvI3mcefrKe/n0r3wSojBNC+IjDmecWQz2rKoMXWA/dMxjZZ4SQx8bjc9RtA3oVRsoaWZNgsR1
TLkQHLjo0KxE31ElM10mnKvc3t7TeUeIHr8Ct1SJfUcqhh4trYLxzlk71jum6cJ+uDJTqlYu4+ml
Fb03joqaZyrnhaurqw0yvSyLrf3VIlenKbHbDdtYwOJWvlwOkybaCeJahIXNDdfYidWCHppbOIbO
2CbVLofqTQEo3vQWVZMxRryj1ofh4KaIXQFHXqjV9vrCBBiMOutakjbnsNrQrB/atLcJyqoqVcQu
OG3c1vZ9Ot/Zhe0ESsFtojS/GdJEW7OhCzF0aEk2H6l2xzbVawDMN6Mt7AvXDsGaUTWnb/QB8Q+O
4E2k5NYSiM0pvH4ONFEcBmRaH9ouYMFvc5TahG52CLh2iKxZR/Z6pGqO7NiqlHU+sr6PawsOw9tc
K1XFi6Li29apbs/LtdV/qgnnVn1Mj9ZKd7zmBz7+iYaYqEQf+JM//ZN87ldf56u+6mv41Kc+iT/C
dDkjIixtVhKaTH0Npw+hI3rb9Ulri9acnKVpkcSQdTjXkVFisFmcz0qIgfN4skM9eoZgAjn6aApq
D704ykv+Lq2JqoHgzJdUpsnC0lxgmi4bFqGUQuzY4lTHcaRku2mu5kwXBk6XixHc1CTIvhRUa2MN
R1QT/X7/5bMaXtucdT8/p8U2FU6p9UG8VpKln+VacGJzlKoFqqlMxSs05olEjyvaemWbL5gjMBgY
urUQVRyUjMQ9UhO15HY382iGpeTGxrC796pWpaETVxNibfGYSkGrR0Ub7czh4ppC94BttLxka6v8
ynFxHme3H1CbY2zeJMxG4L25VFdko2CxmfZ92dSwK6vEgI26vQE9QtKXDzfZWhZR3SzzWhT17e9L
aQeCmGa+xSoUNQt9bQfL1oJV04KsUvxV+WsCxNbSeGOuWDNllDnXEAyqlveiIjY/ck29bIMoO4ib
+AuxNvA7v+/7oVpe9I9+5MP4WnnPzWNuX7xlIKxlMZcxcNgZp7Xvd40Gb5XvMmcz8YmnVEtwDJ3R
+lKZiN0A3mZmyzIjYodALgld7IDaDZHUojucc6YdxGYbVEMx5FroQiTNib7vbT0M4CynaLVhjONi
8OqULerUKzTwVimFoetwwN3dCw5XN4zjyG6346q7YskzaTb+yzRNvFOnybt/NYzBow0AvFgvjXlz
1jtJbaDkJc9QjelRc8E72yiId80nYhsYIyuvprQWQ4BruTQOL43TWptMelPUBtR5apVtGwEvBZ2L
Wd6j85aZqwVtDFrE6GwmcntYYaeUWOW2xhhZpfBtnuGk/VttiYYGWFoVmLQMHHFly+WxA83aMMFv
35ftOa9itIehHdvrKVYVqUK1rB+HPZeaM9oI6160Cd90I62vX1fE4jSsdQobqW4NageawvfBD5QV
Eqbm1eq2Q33NObI2JwE2rN3EetnwD5IfxHKpFIrqSoi0AwtHzZ6P/tjH+aN//BO8OJ0ZdjuWJbdo
C6MwjePZ5inzDE0ouVaVq1K5C9EAdKqEODDsDqg4W0nXiluD22JHDAf7OXAtniWwzNVYtSkbdqJW
XHQtFGzgdJmsVVJPKrL5gAzIlS3Iq+85nU7cn0688dabNnjOmbRMxpzRhDrl+auvcHe6N41JeUid
nJaZJU32PN6h3fCXwGEiW3zjunotCqEP1HahindNltxtZj2LEChtAp/aG81vPbxoteEfWM8eOgvW
EpNe933PasyTqkQC1ecH6byrBNcctdX0JiE6cJYTGySYclKt2vCVZv4z1omuxsRgERPqdDtITFUp
VjmUpqItoFm3w8K1nycXO/BeVr8iJpYL3qMuU2qywK+XFKxr4xJUWtC7SejFBbJmO6SkbtVSFdu6
4F0LPCsPVUN4UPVaq2YPq7Ayq09oPayCuO0gXl/Pldu7/RztsKmUNovxiDdNilWlL4m0nK1Rq4BF
2Hi8CGGLFJGH598Ysj/0iZ/hBz/+M3RdsFbCG/xqN1yZMrbNPVYD6XpwLMvCtMykZCbSkhO5qlH0
aqYfBvquw8dAyQtJR6pvGikRLuNCKqZyrs4qOy3tPdHc0y54ptECu+Lq5Ukzobm0czbNTBcHRDxX
x5t2iAEoSzJpfdcFznf37AaTKaweoC70PDpeMV5mQugeDvjf5ONL4DCxHcI64Tbsnqemh7uaQylp
MWFaVnMIg1UeYtsVUVtJejc86B+aHDyooCk/fD1nIdvQ7rQbKb5rZXtpG4imX2lpgvY1lS6Yg7jr
9ohacHV1vuWgyEPl0QReHQb5hQY5ktrenKuateDFLtrAr68CYowGypEHo6BUOyBsjeu21eHaGtmY
tX2+84hESsvicf9Pe2cXa9tV1fHfmHOutc85ve1tLxDSAFEwJAYIIhLCA/IgUUtjgr4QnqyGiFG0
+BVTrCHwQIwYeTBEEoxGNEZCokZiwgMQEn1QsGopBay0iNGmtGopl3PPPnuvOefwYYw5127pvb0f
555zins0J3d3f5w19zxrjTU+/v//KLN0YzsGmKqsdXcc6k/wzxioLQQbNBawWkeL1tqaWqpjJMyZ
dChi60y68R1iIFZcnEpIYdHfHzGPH1HSYNihznbGbgYi1t2yWcXJeC0S7XEJvQ2fp8rdH/ggUzYF
uFtuOedqZKBt5lGrbQVBaMPTAoNLZa5LBh8IF/1CN+CiURBinEfaCtE6Poqp5x8eItF1ePwmaBSD
1paPrCZjnkuKrNeWQqpYUXi9XrO3YxFHycrqcCLFXVIaCeOCurJpgovxBmoJxKFNJMwcHK65+eZz
vhdHY88KZ0KxvLg5CS2VMQ1WT6h2l2rkKFyQp5HQahHKhuOp1S7UCZiqjb+cqDBsjts0HEpr/2qc
eSkxusROilYUdmj66GGyqAtZ+2jIEBLTWvudoaUO1gXxyCgGQko9dVCwkRVdbDp0zZAibcyFOU2x
YTj9Im/OqqBIHPodrzsp9RnM0YZ15Wrt8YA70zCnPxHpqUkVl06wSWXWXhYxkJ82HRSbBljUMCuG
O5mZxRbFDGQ/fdUnAVQxNf5WaG+Rpchgg86kdN6TBqF4PStXAbITB20IW/LBbFEwh8EEg+No1ICC
4KTEEKhFuPPd7+XMjbd0LJENLl/bBMP1itVUoArrqbpymaUxUy6gxsexVMYJqaVSixCqsl7Z8VrN
6DBP5LUx3DUHLuyvWK4nlgdrUhxY7O55tBBZuwpejAOr1YrFYkEMC6ZsYtdFAhdWa/YPlkhMns5P
rFZLDvcvWDrq4Mvd3QXnz593Z1jY29vrN856RBqwp96ZKE7sK7XPk7X6yNSnpZUpE9LCJPH8bia1
WKszGBDJ2JjOwkymVpUkMQ5+tyv2enAy4DRZrrwuGWSapwhm47/WyVnAEq09WFaWIqEQYSqZGBY0
/ZIUR8vdfag5tRWA54gkO7M4hYEoxn5OjnLNjcZcM0rBkgScgazdWdiFT+8QWEemnVTuEBuC1+cY
q49FbSYi5nQk+u+y14NPCzRE7tAdnRU8N1IKVyY+AAAQw0lEQVQo/06m/yKdCJckkDUzxNaVoac8
EUsdTfgnQrQ2ZxpaJKU+psEjpSaRGWz4uqq3/2We4WuwlwBFkWShaUxetxGvPamyd9MZ0i1n7Hul
hbW18ekDNRCxgnjJ6oQ6g9jbuk2ikQrBu2cipkZHCIZiZei1O2plsbvD8mDNOhtgcLFYMNXCN/e/
xepg6fXAzCiRFKyTtLt3E0GSFfljJO0uWK0mxnGHvb091sVEm6pDHprw9jRNfeDXTWdu5MLywMiQ
y0MnP4rN+DkCO/XOpN2FM9YsaFiOSut++ElcMoFC8q+kxZm0lc4QDkMwaHc1nopRtl0HpIHNwOsz
ANUp/WlmBjceiw+1atR8iWOPfkzR3sBp7Y6dy7rf1WPSfpHbncxHNMQdm3PibFWTRpR+TLuzeljv
0UJzIMGjkyaD0KIe6SmdtblTMrBcSCMhjTR5B0LojrrhWVoBtRXu1IY6979Nlfb91Yu082D3ftw4
mENMVuNpqU3y/Wr7WlSYiqWijXpvrVtnX4eRyR2JkaxnnAY1e1RBR6n2OofMp3jjxWhWJJhzdDgx
7/z13+TsuecgcWAcdymOqI2DKe9lpxCsJx+U7gLlU1kTh0QV7VgVS73t+w7DQBqNjJhzJTtxLw4B
jZGDwyVTrkzTquvfrCe7SU3FboJptFRyXbID4oyGEEKgrLMJORV4/PHHDZ2tFq23buJyueyi4LuL
HZbLJTu7CxuUPqaj6gyffmeCb0wKapPOppXNQZmypx1CHKxYl6uQ62QFT8/Pm+ByKQWtwdXZPDdv
rTZgZ9ixmoxaw9RSJ/qs4lhxKL3YSchMJmwaHqUUBk+vdobR57CU+WJ3fEZQAySJmlasSLT0RpUp
Z5r2iHjb1w7mUYYrtpljEgfIOUJYizkt78SY05wLnFrF5yG7Q2170e5MYXZcPWLKayQZnqLxhiTY
uhrMvjmRzc81Z9xTi9KkDVyHxef/oKYTMyaLKErA4eD40C771yYkzlouuBOLHnXlnK3+oJkqBiyr
CCEKTf/apBetc9L0XPD0qhbhp3/lNyhRupRijBadtMJl+44xjTbmsw1Iy5Xozi1Gq/SEFJlK7jKP
7ea3t9gjDkbCu3D+W0SPWg6XmalOFHz0q8wSmrlWVnnFVDI748IdrJLSgIyx11fGnTM8+vX/JqTR
UkK/gYyjQelrrYwpcOMNZyirQ84/8Q0OD5b/f2omrUFhWBFjRrYxke2u2rxwSvhQq6awXoDKtMoG
I66m7yniRbFg/xo2wJTsie3iMJ5FC4UlzZgHDZYmBZ0VsNqJPflJ2sSmWzckhqG3jmfVeOn1CKmO
AfHPV80WJotxjWx6xgYTWC3RaUjo1iIfXfCntY+bILSp1G3oqtAGc7nEgAhRgufoDuAKiiSTeBQR
6xY4wzVF6d2bRmsQH6gtwSINEyGqcztb58hC1fcSV/Yv2tMdDbZ/zRHXWhmC0GBRIo4XEh8/4mld
FWsPJ0ePjin2+kspVjSnnRtxxi+hbY8q7/qt93fezjAMpqEbI2lYkNWig1ot8h1i6uda9hTaWMjZ
ku1GcZgyFNvTC+sDDtcr9pf7DE75WF5YkauSi5FWx3FB0UDJLpK0XhvLOoQ+2tUcbSGvJ6bVmorB
588975wNXM+WCq+WS1ariSHavoCdB7u7u5w9e9aF1o/mWn1GZyIiOyLyORH5vIh8UUTe68+fE5FP
ishX/N9bNj7zLhF5UEQeEJEf3Xj+B0TkC/7a78nl9KSELl8X1TggQzTkq0nXzelOzcrk1XfVQi0m
1xdHJaXRBH3T4PUJuzC71KGIF68mdwSN9WrRR8m+Hr8b1Sj99RgWhLIhHyDSawkW7s4zdgmm3Jar
dXOkSmfzSlBqkB4xNKFsaREIOG7FrZpTanWZkGwWi7rzCF4XaFFIV4fzP31LRdrvtZZxpjhWojkO
CUrJLRKcR4N0p9UuUG/JUqxKIqlduH6aRYvyCLbOVgex1NUL5LLRKg7JLnrxlLWPcY29e9bbycH2
IqtBB1SVdS4GuxdgYY6oR4jV/l7VEcXVi52rw8Iv3P1u0mIHQqKqMYdX1bBGcbDoZ8qm3xrTaNFj
NTW2NIy93iIOWM5OGi0UpqmYKPqwQGI0MWoBfLjaer1m/5v7LBa7TD7uVEVYLQ9pzOSKabOwGEmD
taGr10cMDpFM9LvaXg9hVsjL2bAt60LvNB5VnnM5kckK+CFV/T7gVcBtIvI64C7g06r6UuDT/v+I
yMuAtwIvB24Dfl/m6t6HgJ8BXuo/tz3TwQVQh8yT5mr/Ig49JC+NtyJCqrhyvd2VbljsWhGuFem8
3boIIylE4kZYH+OCRUgMEZfBswhks5Ap0YqqFoZLv+gnsQ7OZiguJVOZUBciXkQTu04h9D8uAGkg
YeGz8TIsiolSCNVOhqqZki0iaR2bGCOLOJLiaPN3PLXxv0Ovnwwb7cnoReCKpSLBC7MxDEhQEjuG
iG0XdNy4EzJfjCZqHb1QO7eT+3f3qDH6fzO2xN5jd8nkf6dZJhPobfJJax94JiI2HkKCjz2NXUEe
DGJPsXRYqkUgwR1JnSAVc2TzeBQ6/6gWQyNXl2Mcd/f42V/+VUIaiKPVe3bjwLqC+JrjEJi0MuUV
QXYoRV1IqwHXBHTo+1VKITIwDLFH18vlytNw6zbVogRZkHNlub9ESORJqZP2aLFpII8pWetcbGRL
UDg4XLK32DEgpFRiEqKakn31elS0WbgkIMUdgqdZR2HP6EzUbN//d/AfBd4MfMSf/wjw4/74zcBH
VXWlqv8OPAi8VkRuBW5S1X9QW/2fbHzmUscHgod7K1djn6wT4i4qSupsy+qtwbnrswKgqFfPPRjK
dWKtE8W7FtY6LNZ2xLoYcXDWWQmEaOjZzTt8LxRqQWg5uZ3sVSolAGHs9ZlcvSvlkQJecLPphAmt
mYR2vViVAeIsNdmcQtdp1XUfTiZqWJTkqNIxJSvoiWnL2pgOj6ocMTwVA69JsCKmVG8pE81xefol
1ToZVhcyRKwJIzn+BUOZqsyRSEE7ItWctSmLDWGAmg0YR/VRpnOhOoaBEFznBevqNC5RFuWwmCBU
L3S21MijJnWKRSkOD6gBog3hAlAJNl4klz6m06If144RIefA7plz/NSddxKMYkwGFikx1UxGbRqB
CBIHstpQdFUDSuY6UYtQdXJR6sxUXNwaE5xSCYzj2MmgTU7R1piMPAhdC7aqrd2CUfO862ll+sYp
kRYDZ8+eZZomhmBOfloXclFD83qEah0cO78v7J+nwR+Owi7rt4hIFJF7gceAT6rqZ4Hnq+oj/pav
A8/3xy8A/nPj4//lz73AHz/1+ac73ttF5B4RuecbT3wTLUbY6p0Cid6VsfwZv0hLaYOd7QTM1eHy
JRvQSZhn04Ta27xR1NG01nKMfkc1D+/domq4hgb4KpieadZZnb6d1K1Va52E0C/eQnG0bujFy5B8
lEVtcpPBo5K5c1OLtVkbY8XeuCbUEUIwPg7BUijaKNX13KEx4QAroIYZazGmZGmMdx4AUqhQrSVt
66+9E9RSt4ZrAStKF4p9RhIqkdTGrYqwEXB4F85rVl4D2ETGlkYPaLWR4Gr6rqAXlN6a1eCgvKrm
6LEItoEYhxhc5MnQsyE6Lie4fkpw+D24w3QpBK+j1BDYvem53PaWt5iI82AaLbvjgiHMlLaWIi8W
hp9p55zMoxUJIRmDIwiHq8xhWXWU8zJnCkLG5CeWh2tUDA19sJ68K2m46To1TVhDaRMCMQ0ISs5l
1o8Nwmq1JkaTVGg3usXOHotx18CTZWJnb8FqPYuKXatdljNR1aKqrwJeiEUZr3jK68qRZV6gqh9W
1deo6mtuufksgCMD1VpyMVDEHIhgUUZIjmZN1spsit6qNvOmFT17PWXyiySYfF1uquCTz3txaL3W
0MFj0b9iVZ8T7NKPQL8YNrEWhn8o/c5rRb7iep8y1zCCKZwlSRt1DCf96aw+FsVqLe11xEByDdkq
DqozlrSlPeKRHSE96Q5kEcrcgi2tu0LwiYV2p+2w/5Y2dYcu5hQ8lG/roebO9ejf2SSajC/jUUbr
MrX2OziIr9ALzUZqjj5M3lrRQXEckfaBaLX4Xjd8jXOx2hrmtrpZG29CxGUeNqkIVgdqUdz3fO8r
uePn7rRB6lrJasJSVRVESMMCNFKKMCxG0mi1udb2p9o5VBvITdQBZsb/maYVteGaMI0TI2JGo1NE
+9u1dm+bsTwEU1ErxWJJESsoL9crj2Yqh4eHxJgo3tWb8oqDgwMO9pe9FLC3O8xkwmu0K2INq+oT
IvIZrNbxqIjcqqqPeArzmL/tYeBFGx97oT/3sD9+6vOXtC8/8JX9V//gGx+4knVeZ3su8D8nvYgN
267n0naa1nOa1gLzer7rSH5bB31d5Ad4HnCzP94F/g74MeB3gLv8+buA9/vjlwOfBxbAi4GvAtFf
+xzwOqyu+gng9ss4/j3P9J7j/NmuZ7ue74S1XI/1XE5kcivwEe/IBOBjqvo3IvL3wMdE5G3AfwBv
cef0RRH5GPAlIAPv0NbTg58H/tid0if8Z2tb29p3gD2jM1HV+4Dvf5rn/xd440U+8z7gfU/z/D3A
K779E1vb2tae7XbqEbDAh096AU+x7Xoubdv1XNxO01rgiNcjnjttbWtb29o12bMhMtna1rb2LLCt
M9na1rZ2JHZqnYmI3OZEwQdF5K5jPO7XnIx4r4jc489dManxGo7/RyLymIjcv/Hc8ZAqL3897xGR
h32P7hWR249xPS8Skc+IyJfEiKfv9OePfY8usZYT2R85aVLuSfe6L9L/jsBDwEuAEcOtvOyYjv01
4LlPee79PBlT89v++GU8GVPzEI6puYbjvwF4NXD/tRyfb8f0vOkI1/Me4Nee5r3HsZ5bgVf74xuB
f/PjHvseXWItJ7I//tkz/ngAPuu/81j25rRGJq8FHlTVr6rqGvgoRiA8KbsiUuO1HEhV/xZ4/FqO
L1dJqryC9VzMjmM9j6jqP/vjbwFfxjhex75Hl1jLxey67o+anRgp97Q6k4uRBY/DFPiUiPyTiLzd
n7tSUuNR23UjVV6D/aKI3OdpUAubj3U9IvLdGAbquhJPr2ItcEL7I8dMyt200+pMTtJer0ZqfBPw
DhF5w+aL7qlPrJ9+0sd3+xCWgr4KeAT43eNegIicAf4C+CVVPb/52nHv0dOs5cT2R4+ZlLtpp9WZ
XIwseN1NVR/2fx8D/gpLWx710A+5PFLjUduVHv+qSJWXa6r6qJ+0FfgD5tTuWNYjIgN28f6Zqv6l
P30ie/R0aznp/fE1PAE8iZTr671ue3Nanck/Ai8VkReLyIgpt338eh9URG4QkRvbY+BHgPv92Hf4
2+4A/toffxx4q4gsROTFmHrc567D0q7o+B7SnheR13kV/ic3PnPN1k5Mt5/A9uhY1uOf/0Pgy6r6
gY2Xjn2PLraWk9ofEXmeiNzsj3eBHwb+lePamyutGB/XD3A7Vh1/CLj7mI75Eqy6/Xngi+24wHMw
acqvAJ8Czm185m5f4wNcZYfiKWv4cyw0nrBc9W1Xc3zgNdhJ/BDwQRztfETr+VPgC8B9fkLeeozr
eT0Wpt8H3Os/t5/EHl1iLSeyP8ArgX/x494PvPtqz9+rWc8WTr+1rW3tSOy0pjlb29rWnmW2dSZb
29rWjsS2zmRrW9vakdjWmWxta1s7Ets6k61tbWtHYltnsrWtbe1IbOtMtra1rR2J/R/j3Tw04zaw
NwAAAABJRU5ErkJggg==
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>You indeed deserved a "thumbs-up" although as you can see the algorithm seems to classify it incorrectly. The reason is that the training set doesn't contain any "thumbs-up", so the model doesn't know how to deal with it! We call that a "mismatched data distribution" and it is one of the various of the next course on "Structuring Machine Learning Projects".</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><font color='blue'>
<strong>What you should remember</strong>:</p>
<ul>
<li>Tensorflow is a programming framework used in deep learning</li>
<li>The two main object classes in tensorflow are Tensors and Operators. </li>
<li>When you code in tensorflow you have to take the following steps:<ul>
<li>Create a graph containing Tensors (Variables, Placeholders ...) and Operations (tf.matmul, tf.add, ...)</li>
<li>Create a session</li>
<li>Initialize the session</li>
<li>Run the session to execute the graph</li>
</ul>
</li>
<li>You can execute the graph multiple times as you've seen in model()</li>
<li>The backpropagation and optimization is automatically done when running the session on the "optimizer" object.</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span> 
</pre></div>

</div>
</div>
</div>

</div>
    </div>
  </div>
</body>
</html>