report.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>vui_notebook</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
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<style type="text/css">
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/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
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aside,
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figcaption,
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menu,
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summary {
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a:active,
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dfn {
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h1 {
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small {
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sup {
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sub {
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img {
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svg:not(:root) {
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figure {
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input[type="search"]::-webkit-search-cancel-button,
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fieldset {
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  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: 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: 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: 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;
  }
}
[dir="rtl"] #ipython_notebook {
  float: right !important;
}
#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
 */
[dir="rtl"] #tabs li {
  float: right;
}
ul#tabs {
  margin-bottom: 4px;
}
[dir="rtl"] ul#tabs {
  margin-right: 0px;
}
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;
}
[dir="rtl"] .list_toolbar .tree-buttons {
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-right {
  padding-top: 1px;
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-left {
  float: right !important;
}
.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;
}
[dir="rtl"] #tree-selector a {
  float: right;
}
#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;
}
[dir="rtl"] #new-menu {
  text-align: right;
}
.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;
}
[dir="rtl"] #running .col-sm-8 {
  float: right !important;
}
.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 {
  min-width: 0;
  /* 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;
}
/* 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: 21ex;
  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;
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<h1 id="Artificial-Intelligence-Nanodegree">Artificial Intelligence Nanodegree<a class="anchor-link" href="#Artificial-Intelligence-Nanodegree">&#182;</a></h1><h2 id="Voice-User-Interfaces">Voice User Interfaces<a class="anchor-link" href="#Voice-User-Interfaces">&#182;</a></h2><h2 id="Project:-Speech-Recognition-with-Neural-Networks">Project: Speech Recognition with Neural Networks<a class="anchor-link" href="#Project:-Speech-Recognition-with-Neural-Networks">&#182;</a></h2><hr>
<p>In this notebook, some template code has already been provided for you, and you will need to implement additional functionality to successfully complete this project. You will not need to modify the included code beyond what is requested. Sections that begin with <strong>'(IMPLEMENTATION)'</strong> in the header indicate that the following blocks of code will require additional functionality which you must provide. Please be sure to read the instructions carefully!</p>
<blockquote><p><strong>Note</strong>: Once you have completed all of the code implementations, you need to finalize your work by exporting the Jupyter Notebook as an HTML document. Before exporting the notebook to html, all of the code cells need to have been run so that reviewers can see the final implementation and output. You can then export the notebook by using the menu above and navigating to  \n",
    "<strong>File -&gt; Download as -&gt; HTML (.html)</strong>. Include the finished document along with this notebook as your submission.</p>
</blockquote>
<p>In addition to implementing code, there will be questions that you must answer which relate to the project and your implementation. Each section where you will answer a question is preceded by a <strong>'Question X'</strong> header. Carefully read each question and provide thorough answers in the following text boxes that begin with <strong>'Answer:'</strong>. Your project submission will be evaluated based on your answers to each of the questions and the implementation you provide.</p>
<blockquote><p><strong>Note:</strong> Code and Markdown cells can be executed using the <strong>Shift + Enter</strong> keyboard shortcut.  Markdown cells can be edited by double-clicking the cell to enter edit mode.</p>
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<p>The rubric contains <em>optional</em> "Stand Out Suggestions" for enhancing the project beyond the minimum requirements. If you decide to pursue the "Stand Out Suggestions", you should include the code in this Jupyter notebook.</p>
<hr>
<h2 id="Introduction">Introduction<a class="anchor-link" href="#Introduction">&#182;</a></h2><p>In this notebook, you will build a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR) pipeline!  Your completed pipeline will accept raw audio as input and return a predicted transcription of the spoken language.  The full pipeline is summarized in the figure below.</p>
<p><img src="images/pipeline.png"></p>
<ul>
<li><strong>STEP 1</strong> is a pre-processing step that converts raw audio to one of two feature representations that are commonly used for ASR. </li>
<li><strong>STEP 2</strong> is an acoustic model which accepts audio features as input and returns a probability distribution over all potential transcriptions.  After learning about the basic types of neural networks that are often used for acoustic modeling, you will engage in your own investigations, to design your own acoustic model!</li>
<li><strong>STEP 3</strong> in the pipeline takes the output from the acoustic model and returns a predicted transcription.  </li>
</ul>
<p>Feel free to use the links below to navigate the notebook:</p>
<ul>
<li><a href="#thedata">The Data</a></li>
<li><a href="#step1"><strong>STEP 1</strong></a>: Acoustic Features for Speech Recognition</li>
<li><a href="#step2"><strong>STEP 2</strong></a>: Deep Neural Networks for Acoustic Modeling<ul>
<li><a href="#model0">Model 0</a>: RNN</li>
<li><a href="#model1">Model 1</a>: RNN + TimeDistributed Dense</li>
<li><a href="#model2">Model 2</a>: CNN + RNN + TimeDistributed Dense</li>
<li><a href="#model3">Model 3</a>: Deeper RNN + TimeDistributed Dense</li>
<li><a href="#model4">Model 4</a>: Bidirectional RNN + TimeDistributed Dense</li>
<li><a href="#model5">Models 5+</a></li>
<li><a href="#compare">Compare the Models</a></li>
<li><a href="#final">Final Model</a></li>
</ul>
</li>
<li><a href="#step3"><strong>STEP 3</strong></a>: Obtain Predictions</li>
</ul>
<p><a id='thedata'></a></p>
<h2 id="The-Data">The Data<a class="anchor-link" href="#The-Data">&#182;</a></h2><p>We begin by investigating the dataset that will be used to train and evaluate your pipeline.  <a href="http://www.danielpovey.com/files/2015_icassp_librispeech.pdf">LibriSpeech</a> is a large corpus of English-read speech, designed for training and evaluating models for ASR.  The dataset contains 1000 hours of speech derived from audiobooks.  We will work with a small subset in this project, since larger-scale data would take a long while to train.  However, after completing this project, if you are interested in exploring further, you are encouraged to work with more of the data that is provided <a href="http://www.openslr.org/12/">online</a>.</p>
<p>In the code cells below, you will use the <code>vis_train_features</code> module to visualize a training example.  The supplied argument <code>index=0</code> tells the module to extract the first example in the training set.  (You are welcome to change <code>index=0</code> to point to a different training example, if you like, but please <strong>DO NOT</strong> amend any other code in the cell.)  The returned variables are:</p>
<ul>
<li><code>vis_text</code> - transcribed text (label) for the training example.</li>
<li><code>vis_raw_audio</code> - raw audio waveform for the training example.</li>
<li><code>vis_mfcc_feature</code> - mel-frequency cepstral coefficients (MFCCs) for the training example.</li>
<li><code>vis_spectrogram_feature</code> - spectrogram for the training example. </li>
<li><code>vis_audio_path</code> - the file path to the training example.</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">vis_train_features</span>

<span class="c1"># extract label and audio features for a single training example</span>
<span class="n">vis_text</span><span class="p">,</span> <span class="n">vis_raw_audio</span><span class="p">,</span> <span class="n">vis_mfcc_feature</span><span class="p">,</span> <span class="n">vis_spectrogram_feature</span><span class="p">,</span> <span class="n">vis_audio_path</span> <span class="o">=</span> <span class="n">vis_train_features</span><span class="p">()</span>
</pre></div>

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<pre>There are 2023 total training examples.
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<p>The following code cell visualizes the audio waveform for your chosen example, along with the corresponding transcript.  You also have the option to play the audio in the notebook!</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">IPython.display</span> <span class="k">import</span> <span class="n">Markdown</span><span class="p">,</span> <span class="n">display</span>
<span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">vis_train_features</span><span class="p">,</span> <span class="n">plot_raw_audio</span>
<span class="kn">from</span> <span class="nn">IPython.display</span> <span class="k">import</span> <span class="n">Audio</span>
<span class="o">%</span><span class="k">matplotlib</span> inline

<span class="c1"># plot audio signal</span>
<span class="n">plot_raw_audio</span><span class="p">(</span><span class="n">vis_raw_audio</span><span class="p">)</span>
<span class="c1"># print length of audio signal</span>
<span class="n">display</span><span class="p">(</span><span class="n">Markdown</span><span class="p">(</span><span class="s1">&#39;**Shape of Audio Signal** : &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">vis_raw_audio</span><span class="o">.</span><span class="n">shape</span><span class="p">)))</span>
<span class="c1"># print transcript corresponding to audio clip</span>
<span class="n">display</span><span class="p">(</span><span class="n">Markdown</span><span class="p">(</span><span class="s1">&#39;**Transcript** : &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">vis_text</span><span class="p">)))</span>
<span class="c1"># play the audio file</span>
<span class="n">Audio</span><span class="p">(</span><span class="n">vis_audio_path</span><span class="p">)</span>
</pre></div>

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

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NcAsNPn9i7tvmBuBxAw8VBE7hKRxSKy+OBBDtKKR76BatAdnknjW8Jtj46fzcbG/YUD3iVhBjA2euLXqGeSS9L+xsvfOTeV8Lglu6J6zXAysnMjzsX2HrxY6c1pG9DjtZkxEXTn5inX5rWf0tKszO5R/WbhTnR+5Q98Mmcrrh49F5k5sdeD7tvrb3eaWCwOQbzmvXlxNdW7HUb5HOgePmV8vEw4P6/Yi5vGLMDXC3eY/tqkj5MBd6DtSMA9kYjcDKANgJGBHldKfaCUaqOUalOpUiUTm0hu8cbv5waH+VfCsNt178/DxW/8hV9W7Mm/b9uh07jmvfA74l1Ho+s1DzRq/pHvrT2F2/jJ33DvV5HlFertFd966DS+XhDZjmDBFs8BWLiSjU45kZGNvcc9n3v7l6aj5XNTHW5RaGYP5l249TAA4Nmf12DJ9qPYcvA08vJUTKUbnbDhTE0wnLnVXnuPn0VmtvUdBUdOZ2He5sP5t307lbqNnGn6+z2oDdTcYaCaF5krxcH33gWgls/tmgD2+C8kIr0BPA6gm1LK/MM+ignRBqpGhNvBeQP++7/+G02rlcb2w2cw+NNFht5j04HIBq45tfOdsno/nr28ueHnfaEjd/D3NfvzT7OnJAkaVCmJC2uX0/0ebq/20uv1P3HwZCa2vTIAh7Seq/0nMlCldFGHW1aQXd+tw6eyUG/UZJQu6uTuxxizBppuM+EszMz1B3DbJ4vQomYZfHtXRxRLTTahZQR4zkB1fDn4+B4z3fjhfKzbdxLbXhkAoGBnyikLZ+jdeywDx85koWzxVMvegwJzsod7EYCGIlJXRFIBXA9gou8CItIKwPsALldKxd+0fKSbnpDKaLxw7Ez0p85fmLTWcLA9csq6QvW8c3RWQwkXFFlxKtJr7OKd4Rfyc1hHesJj41fkXx86fgWu+t/c/DzDU5k5eOP3DcjJzcPR01m47O3Z2HE4cA+NVTVzo+Utp+g7WK79S9Odak5Qszd5etvM3Nnn5Sn8tKxgP4q31JqREptOu+XjBaa8TvcIUsr8x6Z8NncbAGD5ruOYud653eJagxVynPbOHxsDVlXxysnNs2XMiZe348bunOqJy/fYdlBBBTkWcCulcgDcD2AKgLUAxiqlVovIcyJyubbYSAAlAXwvIstEZGKQl6M4p2ejZDTgavlc9DO5RTI9+7szNhe6T+9AtaQwf2PrF6YZbo9e//09cM3nHJ05yUZ20B/N3goAGPnbOoyavhE3jVmAX1buxcrdxzH6z4LrL1ZSE8INlnPaz8s9gbGZKVvrA4x1yI2VD8yHf5ODHfRZocVzUzHix5UAPJ/RDJOqWETL90A5Frw2dUPAqipeN3w4HxcanN3TzGDZzv6Cs6xE5AhHz+kppSYDmOx331M+13vb3ihyJT0DzdzZv6nPTp0TLLj5bwyXQ21kI//CpLW4vEX1/Ocs2HoEmUEGYHq/GS7t4E5ogeKRx3+M/ZrAXUfOyE8FsMPXC3YgN1fhO7+zTAu2HkG/86vZ1o5I5OTm4V9jl6Nbo0q4prV7C40t2mbfrL2+lPJsu+Jphk4KjDNNkiMysnMN1ZL+1W+K9XgzYVmh4QsBbbOxZ82oh8MM3szJVViy/YjuaiL/m7kZYxefq8CybKd3WvnAB19u2V3VHzEZ9329FAAwZXUMfm9jrwPatfLyVP5guHBVjMLxD7YB4FMtvcTNho5fgZ+X77F8cHc0Qp19M1pVaHn+dsoYuzsM3oxgllqKDgNuMkW7F6fhmYmrdS9/wbNT0eSp3yxsUeTcesZbb4k9p3Irw02Y8o/35+Hq0fN0l0bUG0x4T+s61cN9+FQm5mw6N7tebp7CpBWemeTu/iK6WeOcEKpWdyKKpLTlhv0nsePwGTwxYRUaPv4rzmbl4urRwdMZYsHhU5l4ZuLqAtU09PhhqfvrcfcbNSvoY69OWRf0sUAdIAPfnRNgyeDyz9AZelb03pzGad/tFjbgFpHiIvKkiHyo3W4oIpda3zSKJQdOZuLTudt075ysqM98Jiu6QVgnMrIxZ9MhrNvnzsFA7/yhL8/bW4LObvYdqBTcNakg99vlxg8X4KYxC+Ju5/XZ3G3oPnIGcvNU3E+WcTIjG+nDJiF92KRCj2VEUDe8zxt/oevIGfmlLnu9PjPaJjruuV/W4NO52zB1tWfw74pdxx1ukT3+2hB8qvrBnyyM+vWDdRj8ZsNZXabh2UtPD/cnADIBdNRu7wLwgmUtopgz16d3zzu4R68DJzOQPmwSflu1N+p2DPlyaVTPv++rpbhpzAI8OUF/T72d9umsM603F3DdvhPo8p8/TJnoJDMnN6JMhC0HT+GI4fd3V/DnHRh4+buzC9wfy1OkHzuThacnrsa2w2dQf8TkkAOM1+07gU/nbA38Omf1fbZOH6wcOBm8uo8ZMcme4+6sEW9ETq7nM7rv66U4bWHZOitc8sZf+df1VoTSIzvXzEGTBb9pQ740fnbs83nbDC0f58fRrqMn4K6vlHoVQDYAKKXOwj3pkuSwZyauxo1jzpXMGrdkF46fyYZSStdOdN1eT7DyVYSTnphFKYVZGz0HDmZukM3km89shrf/2IRdR89i1qbgPTh6bdh3KqJe0HB534F8s3AnZm8812bv257KzMFvq/Zh8sroD9708g2qV+0ueGbkyZ9id3Dg037pYaHKpfV9cxae+XlNwMfu/lxf0FBvxGRTDrojFWqHxpikML1n0dwyvbtvtRyjnUKhvhu7j0V/NlEB+GbhDnzw15aoXufo6Sw85dLOIvLQE3BniUgxaNsdEakPT483UcA823u+WoIv529HvRGT82sQB+M9qHf6SHt8DOQZmk5b50kmHT7b+RHe/NECrN5zvMD7Dvp4IYZ8uQT3frXU0nrkXp/M2YrGTwYfh7DWpalJXk9PCH5AYGRAcygnDfSETlrp3ABT34lt6o+YnJ+DT4G98mvwvGZfbpzefdKKvfhkzlbd3/FApS3NpBQw/AdjBwGB5EWwE+XBpL30BNxPA/gNQC0R+QrAdABDLW0VxbS5mw/np2XsClPuzpv+EG45q20+eG6He/SMc9M4m0JnAJ2p5aaaUY5KQeHvHZGNzo/UgLc8KRyByhFaWY/c69kgvbpe0a7XzQdP5U9yYoXPtFlAF207gpvHmDOxS6zyPX2fm6fyq8zk5ilc/vbsYE9LWNPWxu48dKezcvHsz2tw+2f6JiwzUqUkM4J8f0ocYetwK6V+F5GlADrAsyt/SCkV/TloIpzrXXVzuTs32GPCqUt/3p2mGT3cRktnmWmvA/mxduxYB74zB6cyczCoU7ql7/PQN38XyjEOldPsa/G2I1Y0yVbBUqECDaBMVBnZuZhkY6qWHeZuPoxpa/ajd9Mqpr3meU8Yr7ylHOxn9nz3mSFsl6A93CJyofcCoA6AvQD2AKit3UcUVqDZHwsMknPJb90lzcD+ExkBq618PDvwoDQzuHVKdDd79Pvws+yFC8pv+Sh0r7KZU6wbtUxnLeFr3ptncUusN3XN/oieF2qacDv9veOo4cFyRkWbX+xW45eaOy4mEqEyQeZvOWxfQ8hyoVJKXtcu7wJYAOADAB9q19+yvmkUDwKFcht8cuI4u9Y5u4+dRfuXpuPq0YWDGCN9IO//WXjq+FDMiLdnbUysk14z1oU/pe6bFxyIW9bZQRvy3d1swZbIeunHzHJHEHrl/+bqHiw3YdlupA+bhEMGP/N4TZX4ddU+rNrt3vKG138w3+kmkImCBtxKqR5KqR4AtgO4UCnVRinVGkArAJvsaiDFtkDBnO8R/bbD5ybZMKM8XaTc0IPTfeQMAIEnrjEyIGa+wQAiyYSIe5tDk6Ws2ePugYmxwKzSZrFaq/vjICUNw8nILljNKC9PYeSUdbj/6+jKk1rpy/mevP3Ptfx9vWL0o9XFjEojsWrWxkOWzIlBgekZNNlYKZU/hFYptQpAS+uaRInku0Xnpiv+ROeOz+yN/4b9J5HjgklLfAMf7yQcx854DkKs3OGZkcPte+Bkp+0h3ne2hT3IZ2ysse3Wet7+B1ku+Ak5atmuY3h3xmb84uIKJ97t3FvT9U2i5aU3p9+oQR8vdDxX/p0/Erf/cPCni3RXnKHo6Qm414rIGBHpLiLdtBkn11rdMIoP4VJGfDtX9Qa9r09dH02TCsnMdu8R/mytRraVvYdmpJQstblCidc9XwXvTfx0rnV573YOEv3QBWdfAM8kVb7e92tXrPZwR8r/73V68h49DpwwFjj/veMoGoyYjHFLrMl1/nPDQUte19f0taFz9M0aK2F8Ai8Pp382Ww6FTn0j8+gJuAcDWA3gIQD/BLBGu48S2L7jGbjw+eCzz3kFTCnxyUj2LSWnN+A2u2xfLIwZtHJf7uSgSTet+v0nMnDJG39ZUhEmGqdNqokdrdy8c5NZZeXk4ZuFBSermrM5sQd4uT/c1m/nkTP4a8NBPDVhtaln/4IdlFk5c+Xtny0O+fhWk9Lhuvznj4ie538gS/ErbMCtlMpQSr2hlLpSu7yhlOI3JMF1eHl6xEf0wThZWs7tIpnUQC8ng143feLfLdqJ9ftPFggkT2fmON5zmZObh/X7TmLEjytxOjPH1B20kYOLFyatRb0Rk6GUwkWvFg4uBn28sMCA6FgQTaA3Y731vbNOuejVGbj144VYadOAwsfGh6/6E8qWg6ewZLuzJSrPRHhgvDHM4GqruanTI96FrcMtIlsRYL+olKpnSYsorpzMCLBDCxK/hMrHTVRnMj0b8a8W7AizZOTMGDRp1L7jGUhNSbJ4spzI/i7vsU1Gdi6aPT0Ft3epiycvbZr/+Mpd9lY1GDN7K8ZoZSFrlC2WP/DNDDMNBI3e2ReVAvYHSU3w/b3HwgF0nzf+iur5+09koErpoia1xnpOV6RRKvAZxR1HjM/D8P3infhu0U48f0Vz9Bs1CwCw7ZUB0TbRdk6fYXX/rzR+6EkpaQOgrXa5CJ6SgF9a2SiKH0PHLy9w+4elu3BjkFntnJq9zOkNXigZEZbjWrhVf29PqID7+FlrZt08djYL61w29bn/WvBO/fzR7K3426fm8rAfgvfGXT16rqH31Fvv2is3T5k60U9unvHxC6F20Ft8Zmw1Wht6ns6UFKWUaZUVoq1QYeWZJ6P0DK4Nt96On83GhGW7zWqSbt7VqJTC94t36jrz8Oi4FVi8/Wh+sB2rwqW8TIuwTjy5j56UksM+l91KqTcB9LShbRQHdh4puEN75PvlQZZ0jptrgStlvK42APzjff0Tknjj7UvfnoXBnyws8Nidn4feGURKtH9WivZAyvf5N/kcJIZ63SXbjU2GcsW7cwwtb3aAN11HPXF/YxfvDPqY78HAS5ONja3XWxv6zWkb0eiJX3UPdtsZQe9pLGr8pPFZDv3d99VSPPTtMhNaE9joINsy77iexduP4tFxK/D0xNB1xcNNGhVPdh619vubm6eQnevewgHxJGzA7TvjpIi0EZEhAErZ0DZyqUAzIdrtpjGeCQGOns6KapT5mawcV/dwK6XwssVlm7x//qrdJwrlpa4LUBPcDGaUIgwn0hrd78zYhLmbDhWoHnAmK9cV05ibPVmOkZQSr+E/rAz6mO/nalZ9b3/egN/37MuR01mFctuVUnhp8lpc9OoM/LaqcKk+M3rJXdTBbYrNB63NJx45JXCFKe969PZs7z8R+iyOWyaNsoPRg3ijZm08hNY6CiBQ9PSklLzuc3kZwIUA/mFlo8jd/jfDeI+r2eZsOoz9JzLQ6vnf0e3VGRG/TtOnppjYKvPZUaEi1EA3qyqYRDqdthFG0wV8/9TvFu9Erl80dfNHC/Cf39Zh1W7rU2GCVXOweucbrY9mb7W8brj3Y/JdRxc+/zvavTgd87ccxoETGXh3xibUHT45f0KrFQHy7p/8aZWl7YxFTvU9KOVJR7rtk0UAgBNnsx0frOwWdtR1PxForBWZTk/Afbt31kml1MVKqbsAODclIDnunRmRTxRg5jbUO3jt8OksV8/uFo1gPUJmWuwXxIXrXTLD3uNnXXdm4bWpG/KvJ4sU2uFnZOdh9EzzDzYD9SoOHRdd1QanHD2TjcZP/oYdh607DR7qIPD6D+aj3UvTC/1uAm12vguRGqPXm9M2hF8ohjhVIlQBmLMZrSPIAAAgAElEQVTpXK/18l3HMcrg5DyBxFrVHIpvegLucTrvI7KV7040ml4AtwV+dkv2y+9o/9L0/N5Dq9aNm/PmASA1JalQD7dVer3+Z6H7FrkgfSUaN9uQY2vk4xk9c7MlE/OMXXxuQpjsGJsi++0AAa0d28L5Ww7joN/MlUdOZ2KDX3m8d2dswqdztuKj2VsDlqHUI9oqNERmCloWUEQaA2gGoIyIXOXzUGkAsVMHieLWd4vMKZV34mxin05LEkGfNwoGfQ+PXY7/XtfSsrDYrmA2Uj/8vRvfLoq+BzRSGS6e/VSPSMq8GbXzyBnUKl9c9/I7jpxBnQolLGvPWYtTafTYcfgMVu05jl5NKiMtJTnksq//vgEP9GpY4D47SoRe/8F8FCuSjLXP982/79iZ7EID93LyFJ75eU3+7dV7jkMgmLE++EBfpVR+L73Z80QQRStUHe7zAFwKoCyAy3zuPwngTisbRe5l9fTNvhtMr2NnAm84zSojaKSiRyyZsGw3BrasEXa5SSv3FhpA9sPfuz0Bt0U74LmbDuHyFtUteW1fgb5PXrl5CgdPZqJqmaKYvLLgGRKzys5Fap8NaT2x7sYxC3BDu1o4pnPmWd+64CcyzCt3eTozByXSwk5pYYuuIz3jWW7tWAfPDWxu+Pl2DGYGCh+cKIT/zg94a3bY1z2dlYuS2mehZyZkIjsFTSlRSk1QSg0GcKlSarDP5UGllLFisxQ3zJzmN5C6wycX6plo+Rw3nJF46NtlUdfmtWr/m5OnbEkqCVVe7L+/r0eHl6dj7/GzHEDnEsd1BM8nfKqTfLNwJ35dtU/Xa/vWSJ+62rxBu82enoKM7FxXpaZ9Pm+7rt/+TL/e4iS7Im4/WTl5EVXM8bfr6Bk8/8saHE2w3u2Hxy7H4E8XOd0MCiNowC0iQ7WrN4rIW/4Xm9pHLpMTQakvo2X7Ppmz1fB7UGCfzd0W8XPv/WoJDlu048q0qQf583nBZ2X07uBX7z6By2zobQ/F7dVH7KKn5/lkhGVAj57Jxv4TGUgfNsn0+QAueGYqIphDyFLf6UiJuu2TRQUmdUp201FDBPq+OQsfzd6KVgnWuz1+6a6AlXjIXUINmvTOWrAYwJIAF0pAWREUyN90wFht17f/2IRxS3aFX5DCiiYXePJKfT2HkTh4MhPXfTDfstfXY7VWp/uOzxcjx+FoyX8QWaKy+sCj/UvTLXndrNw8vPyrsYl+rPb61PW6Sutd+b+5yM7NQ16ewkaD2+posOyfu2w7dNrpJsS9UCklP2v/fxboYl8TyU0imZEqkue4cUbKWPTujE0BJ/2ggr6cb84A3Ei5aYpwJ/3zO+tmObTa5oPuClhOZORg9iZ9E8Q0fPxXfBLF2bBIRNJ54xSnZ2Jct8/62v/s5LJeqJSSn0VkYrCLnY0k94gkpWSsg9UeEl1Wbh6GfLkUy3cec7opjrnlowW47ZOFWLPnBA6fysSmAyddMVuqL6vHRlBiuvXjhbonInr+lzXhFzLRlNXWnUEzm9PB6O6jxibxisQ7Mzblz/RJ1gg1tPo1q99cRPoCGAUgGcAYpdQrfo+nAfgcQGsAhwFcp5TaZnW7KLhPI+gF+X7JLoy8toXh553KzMkfcU7RSeQSWd5poM0YlGWVB7/5Gy1qlrG0bF2sCFVZhoxbuv0oOjWo6HQzCnno29g5mzH8h5W4oV1tx97f6DioSL0zYxMe69vYlvdKREGjGaVUfmFeEUkF0Bie6j3rlVJR771FJBnAuwAuBrALwCIRmaiU8j3Mvh3AUaVUAxG5HsB/AFwX7XtTZAa+MxvLIxyY8fKva/H3dmO9rM2fdve067EkM8f5GsEUWreRMwEAvZtUdrYhDqs7fDI2v9QfSeKZ+fD4mWwUS01GakoSFsf4hEBOuHHMAvzxcDe8NHmd002JaenDJuGlK8/HyYxsLNl+FFPXmFfpJpyHvl2GU5k5uK5NLaQkn0tMyM7NM3X8x+iZm7F0+1H0P78abulQBzl5CnM2H0K79PKOlb7MzMnFxv2n0LBKSazZcwLn1ygDEcnfPsQSCVdXWUQGAHgPwGZ4qoTVBXC3UurXqN5YpCOAZ5RSl2i3hwOAUupln2WmaMvME5EUAPsAVFIhGt2mTRu1ePHiaJoWkfRhk2x/TyIiIiICPr6tDXo2rmL7+4rIEqVUm3DL6Zna/XUAPZRS3ZVS3QD0APBGtA0EUAOAb3LvLu2+gMsopXIAHAdQwf+FROQuEVksIosPHrT/tLHVk8EQERERUXBfL3B28Hs4es4RHFBKbfK5vQWAGVP8BToX4B+56lkGSqkPAHwAeHq4o2+aMSKCTS/2wy0fLcS8LYcLPNayVllUKZ2GKdpEC70aV8axs55TUu/f0hordh1D6zrlkJmdh3u+Wop7utdHRnYuapQthroVS2DD/lNoV7c8Nuw/ib7NqmLRtiM4r2oplC2eiskr96Jn48pIThKczcrFyYwclC+RiiOns1CuRBGUSEvBH2sPYMAF1QAAa/eeQLniqTh+NhuNqpTC4u1H0LJWWZzOzMXpzBxULJWGnNw8lCpaBIBnMoLkJMHpzJyEq2sajxY/0RvFiiTjzw0Hse94Bp6zeZAUkVE3tq+NrxfsQPkSqWhdpxxKFy2C8UtZTSESTauVxpq91le7IGtd1aoGapYrhrmbD2OxA/X7L2pYEXdeVA8iQKf6FXEqIwfHz2ajVNEUHD2ThRrlimHFruNoVLkUzmbn4lRmNqqVKYbTmTkolpqMvDxAQWHe5sPo1aQKMnNyceHzv+Ozwe0wbe0BbD10CuVKpOKHpbsNtWvW0B6oVb64RX+1OfSklIwGUAfAWHiC3WsBrAcwBwCUUj9E9MZxllKSCHLzFOqPmBzRcze/1B/JSWIo9ebx/k1wZ9d6TNcxwS8PdEHzGmUK3Mf16j5/P3kxypVIxU1j5mPOpsPhnxCHJt7fGRfULBv0cX5vjdv2ygAAXHfRWPtcXxRLTQYArN93Epe8+Zet7+/9DAMx63O9oGYZ/HBPpwJ54hSemSklRQHsB9ANQHcABwGUB3AZgEujaOMiAA1FpK42KPN6AP7lBicCGKRdvwbAH6GCbbJWcoTT/q569pKInnvHRXUjej8qzD/YTjRDutXHtlcG4PkrmgMApvyzq8MtKmzji/1QrkQqAKBMsSIOt8Y5oYJtMm78PR2dbkLMm/LPrvnBNgCcV7VUyADYbH2bVbXlfZ4Y0JTBtoXCppQopQZb8cZKqRwRuR/AFHjKAn6slFotIs8BWKyUmgjgIwBfiMgmAEfgCcopxkRS2m/e8J4xNwLZjR7v3wTdzqvkdDMc9dq1LXBN65oAgFs61MEtHeoAAO7qWg8f/LXFyaYVUMRnR8duBTJDrfLF0LpO+ZDLtEsvj4Ws/hJS1TJFHX3/fueHDrg71a+AuZujPyPWsHLJqF+DggsbCYlIXQAPAEj3XV4pdXm0b66Umgxgst99T/lcz4AnhYXiROVSaTigo4xRER5lm+LOrvWcboLjvMG2vxH9m7gm4F7xTJ8CtxP1WFNPScRrWtd0fCKSWPH7v7qFXeaJS5ugZFoKTmbkYOC7c2xolcf4ezrh6tFzbXu/aDh9xqllrdBnfQZ1So864P7w1jb5Z9jIGnqimp8AbAPwNjwVS7wXSkAtwvzww9HbcZeWwoDbDSbc19mS1y1TrAg6NyhUcMgxj/Rp5Oj7ly5acIcuAceLxz89k25UYFCgW9EiySEf/8/V5+OCmmVRr1LJqLftRrWuU86S17Ur/cJO4SbEMuOM2MVN7S+nl2j0RDUZSqm3lFIzlFJ/ei+Wt4xc6d0bW0X1fD0p+N8P6ZhfKcUuF9Zm3mggkebth/NAzwa4sLY1O1xfq5+9RNdyQ7rVt7glpEeqjgPt2hXcWYnguja1nG5CWPUqFQzcujWKr0mWGlUpifduaY27uyXWmb1W3H/FBD0B9ygReVpEOorIhd6L5S0jV6pZLrqdnZ4j8SbVSkf1HkY1qVYa3c+Lrx2PGX66rzOSLMptSE4Sy17bV7jZ0WYN7YH5w3txoJBL6JnaPtre//9cfX5Uzw/mhvbOTf2tV5VSBXOR/XOT61cKv/6tMqJ/dFOKr3u+LyY9eBEA4LFLGmPd833NaFZMqFK6KD77v3ZON4PC0LOXOR/AnQBewbl0ktesbBTFr7wIzn21rxt60E+07u5aDxZ15MaMSqXSCt3XslZZ7Dl21rL3tKr33Iha5Ys7PiCKjPHvpTXinu71cV3b2rp60o1KddlBWyTr6ecHuljQkvAm3t8Zd3WN/CzTRQ0romiR5PyxP0lJgqJFkpHigm2MXRLnL41derYQVwKop5TqppTqoV16Wt0wik95YeLtokWSUMwv7/C7u60tayWChKyI4jsQZ5hf7uywfp7be45bE3ALkPAHOaEEOgDyGtr3PBtb4j4d6lXAl7e3x8YX+2Hd831Rrrj+9LOHL/bk6ieb/Hv/9aGLUDw1dL603f54uHuh+1SYUTRODVaPphTkvOE98eGtgUsgb3yxX8SvG2vsOGNI0dHz61oOgAlCZIpwPdyzH+sZcc9nND1M9So6dyrVKR/f1jb/+tU+lTy+H9IRd2vVTcoVt2aAWlKSuPYgZ8Yj3fHno90dbUPDKsHLc1UuxR75Lg0rokhyEooWScbfT/UJ/wQApdJS8lOHzBywe0uHOranwYXz0pWRpc3EYo9wtTLFgg4OFRGUiqAsbSyKZnNq9Vlk8tAToVQBsE5EpojIRO0yweqGUXwKl1Gid5vx472dCtyuUjoNl7WoHlmjAPRtHn8j2+8OUxKwfIlUTHqwC96/pXWB+9uml88Phq2qJHBN65quSCnxVaW0p1e5bsUSunKJnVKxpLurdLSuUw7/6m1v1Zc6OgZSevN7AeCtG6Ib/B2Im44fuzaqGPD+sNtfN/0ROqx5Lvyg6JOZOTa0JLZ9e1cHp5uQEPQE3E/Dk1byEoD/AlgIoIGVjSJ3ezuKnVW4Hm69Gd4pSQW/uhfULBvxDi/Zxb2t0Rjev0nYZZpVL4NLQpTRsuo0ZfHUFNNP60dr2r+7YeGIXk43A0DhwcneFB/Ak3fuZg/2aoh7e9hb9WXGw90x6vqWIZfxrW5SPNW8Xs9wk5K41ZaX+jvdhKjp+Rx7N4ntcnd6z9xGujU9r0qpuNz/uVHYT1IrAXgcwAAAnwLoBeA9a5tFbhZNT/K1QSYh8dI7qLJJtVK4uGkVjBvSEWPv7ohR17eMOCe4rovTSYoWsS+n8uPb2mCyTy8gYE2e9Td3enpTrN7Gf31ne0PLlypaBJVL25+u0TRAOkK3RgVnB61Zrhj+eLgbNr7Yz/W5mkop23OBk5IEA1vWCPr4HV3qWvK+RYskoVP9wL3JTqhRthh6N6mMqkG+x75b1ySXnWEyqr/OA51Kpdx9Rigc/0mxzNb//GqWvj6dE3SrKCKNROQpEVkL4B0AOwGINmjybdtaSDGttl9v3NOXNQu5vN4iJinJSfjw1jZok14e7eqWR/HUlIjKhV11YQ00q17G8PPscukF1XFVq+CBhJl6Nq6CptULBn9m93z8o01NdKzvyZ+9vGXkB256uCkQCmXSg+ErQ/RtVhX1KpVEkeQk11cj8P6Exw2xdrBzIO2C5KI+cWlTS97PjAlHzHRRw4oYM6ht0DKXesaqBAvWzeSN9YNtXkJ1NDSoXBKbXuyHd27QV514zZ4TRpvnKuEmL4pG//OrJlzNcieF6oZYB09v9mVKqS5akJ1rT7MoXvjXQU5KEpQMMYglkrKB517b+HN8exd7NXZfLe72dcujUwPnAkezO1OH+lRD4eA/Dz0HNb4BlJs7uEumpeDCWp68/zbp9g/E+s5ALuq93aNPewlVTcYJncNsK0YM8KSZXdQw+HL/va6FqW3y9/2Qjpj1mKfQ2cxHuuOjQYUrjMwbFji167d/XoTv7+6IlOQk3T30r15j7d/jFlUiKG96T7cGlgb0VFCoEOVqAPsAzBCRD0WkF1jqkQwK9IUJ1bMZ3UC66L6ebsxjc3q6XbPTF/ynMI/G2ze0snX96J2N1OoKJ25OKVnxdB+UMVCmz2wigi9uLzgByAtXNA+4bMWS0QXLqSlJlpcsNSpcul/pokXwywNd8N7NrYMuE+3EQuG0TS+PGmWLAfBMdNQrQI51uRKB00AaVy0d9LFgzqtayngjY1D9SiWjGl9F1gsacCulflRKXQegMYCZAP4FoIqIjBYRa5OKyPWa19BXBivQ4KlgndiDO6fr6vW8PUg+ZiRxiNtOCfvq3aQyyhZPdfQo1+w0T7NixQtqlsFlLaoHrb9rhkf6nKu08d1dHTBuSCcserx32OfVqVACLWqal6bk3xvp4njbFXnBF9Q4d2A0tO95uCnIDJDR/vQ3vNAvP3CMJc1rlAk5A6uT36/eTYKfZdSTeuUkN9THD1VOlJynZ9DkaaXUV0qpSwHUBLAMwDDLW0auNm5Ip/ALwTPlrL+0ILO86Z1e3cx9uu9EEG4LZMYMaht+IYvp7fV/PkgvYjiRfpZ2HCjd37Nh/vX29SogKUlQqVSarolWrDxbYuZrx2X9eW31lEpLwb3dGwRdXze0q2Vjo6w31qTedifPoIy+uTVWPesp9ff6tedSQR7p08jVY20A4N7uzhdvM3p2olb52DtgjGWGsl6VUkeUUu9zpkmKJu/rvh6BN0xLtx+N+DWByII338DNTfG27wxp5R2su6x333tLhzr6Xs/vdqQ790BP++m+zhG9Vii/PNAFnwwueOAzZ1j4zV80YxH8+QeMZh1wVi6Vhin/6mr4ec9cFngA4tNB7rebd/2E+wTMLA3oBsEGjBpVvoRzKUFFkpPyx/hc3bom/nq0B2Y/1qPAwW+8+evRHkEfq1nOWEBsdHNa1qKJzSgwZ+ZxpYRm1UCjSHIPfXfKTvdw+05A41tWrbtfiTg7mb1K/IPHSNe5bzx7cwdPykBdCyaraV6jDHr4nXnRE6it2HXc9LZ4mdUDWSQ5yVD5Pm8a2W2d62Ltc32x9eWCdZwHd46u9J5Z9ZK93zEzD3oSSYPKpdDIJakJtSsUL1STPhJGA1c71Q4xaZPRM4du6jSiwhhwk6WMbAD0bhSDnSKO9RzuYNMqOzmY0+z39n+1SF9/uM9EME9f1gxzh/V0dLCeFbwVdHz/VsC8naoy+OUff08nrNRqAhdLTYaIoHeTyujaqBJmDQ3eS6dXmWLmfH7e9eOm33as6VCvgimv45YqLtMf7uZ0E0Ka+Uh3U17HjQP/6RwG3GSpCgYqAVTQmToRbJMSyaZGRT10ynw9A5QnNFpRwYr0CjP47w8iSY948crmBUolFklOQnVt8Nr3DtR+DqRf8+hnH/z6zvb4dHBbNPGfGMekfWq384ydOUlLSUYpvyozYwa1xef/186U2S9LpplTnsx7BsCNv+1Y8Y825uS3uyX8S0sJ/t2q6GDKnldKsjlryki8vfa5vqa8J+nHgJsiVkFHeaZgszgO6Va4eknDyjrLNwXZqERydF8wh9vZ3YM3n85/siAgeO93MC1r6SthF47VKSWPDzCe95sXIo5qq02E5PQp8dE3t9ZV4jLUpBNli6cGHEhsVkpJCRflMN/WKb1AjfZopGqDsv99caMwS6LwwUwMevuGVlj4eOC61ZFqXqOMKRVYqsdAFZeRJtTpfqBndAMmg52NaW5woKiRLUOxVNbfthsDborYghGRb+RL+P3Y7+le35ResljVrVEltK5TDh/f1gbD+xcOPJzqrbP6DKXewZa+wqVCjL27I6b+y5lTyO19Bq7pWXXD+zUx/B5mBdx2fKNClXnz9czlzUKWqjMiOUmw7ZUBuKtr+Ilt3HJGJBqXtaju2kmkUg2MEXBKDxMmPGuls0a/P28qVrBNmtGUHDfX6CcG3BSFaPLFvD0f3rJEZmwmImlOXp47ygKWLOoJNno2rhLy9GcsG32TvqmYY5nvqeHyBifo0MusKiXenfw/exeuAPHujeZ8VsP7Gz+gsFOoWW8jVbt8cVzTuqbprxuLFBS2vTLA6WZY5vq2ntSb9AgHbHs7mQJ1qPz3H8Z73hlvuxsDbopYNDv+qy6sgc//rx1+vr8LLm5aBXdcFPzUur9gqR/RBqpWBUixzMw0m0hOL9evVHhH5obBcE8MCBxI+vYwjRvSKegsh9Ew6zPx7uQDnWUYcEE1tK5TLur3SKQeN+94lUGd0l2TuxyND24NPhulXg380gT7nx/92Aa7lQ0xGPvlq87HsqcuRr1K0aWwBdqmXXWh8YM2vduGF680f7tE4THgpohF08MtIujaqBLKFk/Fh7e2MRTsBnvbiOpw+1x/fEATvHBFcxQxaQCLEW7dQev5iKuXMf909shrLkCt8sXweIDA1g3l3vQcINauUBw3d6ijq263EWLSVvvSCzzTgFcomRawF3L8PZ0wsGXoqcLDMVoJJVYEGmhXMi0F214ZgNu71I2LA41m1cugaoCJy/Q6v0aZQrXZR13vrqnH5w33/DZDbcOaVA2e5y8iptSyLhJkMjij9HztbmhXCze1N57KR9FjwE0xJ9g+PNqygMVTU3BzhzqO7CxjuZxTOZ0HS3pDrwtqlsG1bWph1tCe6Nm4Cp69vFnB13FxDBfoczR7+m+zvil6erAf7BW/E454NatufODkrR3TQz6eFCd71okPnKt2VKV0Gh43kCLUsX6FAhOkXdmqhqG672Z79JLCU69XK+P5bTo9AUyNssVQqqi1g5i9Zxfa1zWn5CMZFyebBXKbRy85L+QMWkb5Dr4xMzYNlDunp7pEogm1Tsbf0wkA0C499Ex3wXo737+lNa71yXmdeH+XAo/f2rEO5g3vmV+95fya7p3i+a4gPd+jrm9p2ntYfUDo29tXv1JJfHhrG7x2bWSVHFx8bJSvqQWVSvo2r1bg9oj+jTHpwS5BlnYv38GYC0b0xp1d62HZUxfreq7vt3TDC/0KTNXuhPt6NChwJufn+/V9Hrd1Ttf9Hr//q2vE+73LW0R3NgkAKpcOPsiyWBFPQB/DfTsxjwE3WeK+Hg1CzqBlVKjyaV6RBCKBYsBkbpHyeVdFqGoD3l6sSCupXNKsKkZe2wLdg9SFFhFUK1MMfw3tgaVPXoy2YQJ7p7x9Qyt0aVgx4GMDW9Yw7X2KFYl+UO15VYKX4PTvpb+4aZWIBwG6+WyEl9HZ/PTo1qhSfppczXLFcFfX+mhmsMSbW7x9Q6sCJRbD9QYP7evpSW7qc+YgNSUJSS7pyBh/T0eMvOaCAgfuI6+9IP9646oFfxuXNNOfd96wSqmI93tG3ieYUOOYnhjQBIM7p6P/+dWCLkPWYsBNpjOzN88rUD1if5FszgNNtuOWHYMvo/VYzZKWkoyHejXED/d2ivq1wsVenw5uF7aigZsGtvoPPLrMYA9VoHrreiQlSaHcWKPG3RO8HF56RWvLcwYbcOqUoiEOYOZGkX9fQpvIx62TUOl1WYvqhVKL/ni4GxY/0Tvg8vd2b4A/Hu5m6kGmmVrXKY9r/Sb28T0Yur1LXbubBADo2sjYRFTB+H9W7eqWx4xHuqNciVQ8fVkzR9N6Eh3XPEXltk7phe6zYkOrq2JCBD3TgQaPOBFvh3vLt25wbrDRvy5uFBcThJgt2oFHU/7ZNeLnRttz7D9jJHCuhniFEmZOx124oaECXDdZ/lSfoJV19Kz/L29vj8f6Ni4wS+yCEb2iCuIB4L2bnS+vWa9SyZCz30ZbtcMJ3t3H1RFUBzFLHRPOCvtP+NSlQcWgE9CRvRhwU1SevDS6nrZIBJtFMZI4OVBucrgc7peuPD//eiS1UgMpF6L0FACUSEtBms6R7NMftmbSl+cGNgu/UAixkF4QqW/u7GD4OdHM9GbFqryxfW0LXrWwahZUtTFb02qlUUb7TX4yuG1Er1GnQgnc073g5DtVSheNenCcf364k+Kpxvafj/TAJ7e1dfQM573dw0/WRLHLkYBbRMqLyO8islH7v1D3pYi0FJF5IrJaRFaIyHVOtJVCS04S2zcSwXLdzEq9DpcL3q5uOVTWZgAzqze/TLHQAbcR9S3qXQpXmSF8QB2/EXfH+uFH/r9/S/R1jb1ipdxe6QA96VXLFMX84b3w5e3tHWiRPi/4pAv1OK8ybmhX8GAkmplfY7kiUSBjbm3jdBNMUbtCcVNmnYyGWfuTfs3P7SPdPMg80TjVwz0MwHSlVEMA07Xb/s4AuFUp1QxAXwBvikhk86eSpVrV9hwvPT+wGT6+zbmNr1kTgoQKuKuXKYoGlUth/D2d8Nq1LSKuaFKznN+pah074VjcT5uVlxgPzBgUZaULtd+xmbMkVi5dtNAgNMATdLtpqIR/yTjvuvDyptuYwU1/txl6N63idBPihlnpVqNvbo1trwzAghG90EPH+Ceyh7WFH4MbCKC7dv0zADMBPOa7gFJqg8/1PSJyAEAlAMfsaSLpdXHTKlgwoheqRDFJghnMCkhDBdHefq1a5YvnT8sbidE3tcaWQ6fw0LfLdD/HzFkf7eI7QUi9irGX1xnOa9e2iJsAqlb54pakCDSqUgrr9p3Mv603NcpOoarwAOcGUqcmJyErNw9XtYr8oCQWf8d6rX+hr9NNiBm9m1h/oOL0PpkKcirgrqKU2gsASqm9IhLyEExE2gFIBbA5yON3AbgLAGrXticPkQqy44c985Hu2H3sbNDHzdqNvXFdS/zj/XkBHzPrTH7xtOQCrxWsJJ5R1/mNvnecz9+od4KcWBJpb/AzUVYZSa8Qu4Og/Kf7doPSxc7tCgNNhOMtFdq7aWX876boUoNi8UyVXqHK0sWiSCZF0uOXB7oEPPND8c2yrgYRmSYiqwJcBhp8nWoAvgAwWCmVF2gZpdQHSqk2Sqk2lSrxFHa8Sq9YAp0bBK5zDJi3I2tn8PTxtlcGGM7PLeuXs+1/CjuQYH9f2/Rzz/3PNRcEXsgh8fgkwzcAAA90SURBVJavGq03rmuBz/+vHW7rHF3psd5Nq0TcUxxugK7ZUpLPfQd8J/doa2KaRrSuaX3uQDVQLXXvWYzcvOiPuNNSktDLpFxhN5XJjEdPWVQUoHmNMkhheb6EY9knrpTqrZRqHuAyAcB+LZD2BtQHAr2GiJQGMAnAE0qp+Va1leKD0eDukmbGT+kFGyxlND8318RBb98Pib5Gtl6hSoEFCvajGVwWj65sVdO0vPbza4QeDFVonIDmk8HtTHl/vZ4c0BQVtMDQ9yfqpnrAyUmC9S/0xfdDOuLRPoWnAPcOPLvKhJJxIoJH+xZ+j0jMfsy82XzJHe7v0QBf3+HeAcUUOae2eBMBDNKuDwIwwX8BEUkF8COAz5VS39vYNkoQkXRWmdDB5XmdgOdqQrNiCmqjHu5TsMbrY30b51+vX6kkLr3APSXLEl3HeoErp9hd4aRciVT8ObQHOtarUKhGsJukpSSjbXr5gD2PNct58tvNGvgayay4gRRPdSorlKzyyCXnoVOIM7kUu5wKuF8BcLGIbARwsXYbItJGRMZoy/wDQFcAt4nIMu1i/hSGFDeM7sMiCTzMilXylDLc+/vRoMjqAZvphna1Cwysu6trvQKPsz/bPuGCtmCfhROfUcm0FHxzVwfU8cs9n3BfZ8wamni9tME+uVJp+gLoecN7YkmQmR6dUDHAjL2xrF16dOlOr19rzvwMFF8cCbiVUoeVUr2UUg21/49o9y9WSt2hXf9SKVVEKdXS56K/pAMlHKOj/0uG2Ll9EEHN5PEhpsv2F8kg0zI2596GovfgpkHl+KtM4hoRdpK6qYZ3i1plo6r2E6uC/X58891DqVamGCqESO+y24xHumPR4+45AHDa1SaW1qT44Z4kOqIoGe3hfnZg86CP9bGwZvJfj/aIuH63v48Gnat7bmat4HD0tr6hCytSJLrU5PiqJBGbAv+Cgo1D+fi2NmhRqyyG9Wsc8HGnlSpaBJVKuecAwC3qV4rdakJkPiaAUdwwGsJGNrtj8N7BWuXC99QN7pyO2hU8y5lRl7qXVst1/Qt9kZJk//Gzp7f03Jofesl5mLRir+3tSEThvu/BOrI585zzgnUOBPtMezaugp6NOcGMXcwY7D3t391QqVQaOrw0HWezc5GWkoTMnAgG71DcYA83xQ07KtBVLhU8FaRy6aLo3SR0uS/ftJcWtcybODUtJdm0XnM9vD1x/rulOhVKFMrrJms8HKCaRjhdOBjLFYL9UllF012iKWvaoHJJlClWBLO0SjLebaUbJ34ie/CTp7hh9gxuL17ZHE8MaFLgvk8Hhx64OOr6ViEfj5cyeaHWdKB9VKhyghSZdnXLY/0LfbFwRK+Ajwf6rjGgcwezqpSQ+3k/ae/YCTeVwyR78ZOnuGH2Puym9nVwx0X1ClTlqBxmsGOJtBTc0C74bKcuGq8WlTeua4mGlUsiRUev+vh7OmLyQ11saFXiSUtJDvqdrMSDHNcKvq1iIB5vShX1pC4+0LOhwy0hpzHgprhxtQmTUgQz/eFuusuXvXzV+WhRswzevqFwb3eoyiix5LIW1fH7v7sFPOVaMG2mDFrXKR8yFYfM9+rVF+Dffdxb8zrRBTsbV0RnlRKKHakpSdj2ygAM7pzudFPIYQy4KW6U0zHNce8mkQ08ql+ppKHyZRPu74LLfKaxBoBh/Rrj/p4NInr/QJ4b2My017LC0L7nMdC2if8A4H+0rYW0lMLVSFrVLmdXkyiEyqUDn31ITUnCT/d1trk1ZIdULXf7shacHCxRMeCmhPL8FZ4g1e4Uyp/v74Ih3eqjaBHzSrLd2jHdtNei2OY7CUqTEDOSPtSLp7XdoGiRZIy9O3Dd/pYmDqYm90hLScaypy7G8yHK0VJ8i4/z20QGPNirIfo0tbfEViKVYqtRrhgAoAp7t22TkpyEu7vVQ7IIhnSvH3Q5OyvZUGgcN5l4yhaPrxk5yRgG3JRQlAL+fbF9ua1JAuTFyUBJvW5qVxs1yhZFj/NCl0gkcw3v1yTk49XL8ADITRhvEyUWBtxEFlr+dB/kmTjXwTd3dsANH8437wUtkJQknKTDJV67tgXmbj6EO7rUQ1UG3K6it8Zzs+rBU4SIKHYw4KaEUiVMWT+zeUtCmaVj/Qro17wqdh49Y+rrUny6pnVNXNPauuo9FLlA8fZHgwrW+V84ohdKFuVu2m5PXtoUI35cifNrJE4qIFmPv2SKW78+dBH6jZqVf/v+Hg3iIod19M2tnW4CEUXJf0vUqnZZNKhcssB94er+kzUuqFkWvzxwkdPNoDjDKiUUt/yrNbh1lse6FUs43QQislk004YTUexhDzcljD5NqzrdhEJ+vLcT6lRgwE2UaBhuEyUWBtyUEMoUK4IWLqxvy4lIiBITO7iJEgtTSoiIiGzmPbN1c4faANjjTRTvGHBTXBverzEAsFIDEblKmWJFsO2VAbiiZQ0AzOkmindMKaG4NOWfXQEAd3erj1s7piMthceWRERE5AwG3BRXvDM7nle1VP59xVKTHWwREVFwwWonpSazk4AonjDgprgy/eHuWLv3hNPNICIyxDeh5OnLmqJLg4qOtYWIzMeAm+JK3YolWNeaiGLa4M51nW4CEZmM56yIiIiIiCzEgJuIiMghtcoVBwBc1qK6wy0hIisxpYSIiMghVcsUxfoX+nKQJFGcY8BNRETkoLQUVlIiinc8pCYiIiIishADbiIiIiIiCzHgJiIiIiKyEANuIiIiIiILMeAmIiIiIrKQKKWcboOpROQggO0OvX1FAIcceu9ExvXuDK5353DdO4Pr3Rlc787hug+vjlKqUriF4i7gdpKILFZKtXG6HYmG690ZXO/O4bp3Bte7M7jencN1bx6mlBARERERWYgBNxERERGRhRhwm+sDpxuQoLjencH17hyue2dwvTuD6905XPcmYQ43EREREZGF2MNNRERERGQhBtwmEJG+IrJeRDaJyDCn2xOLRKSWiMwQkbUislpEHtLuLy8iv4vIRu3/ctr9IiJvaet8hYhc6PNag7TlN4rIIJ/7W4vISu05b4mI2P+XupOIJIvI3yLyi3a7rogs0NbhdyKSqt2fpt3epD2e7vMaw7X714vIJT738/cRhIiUFZFxIrJO++535HfeeiLyL207s0pEvhGRovzOW0NEPhaRAyKyyuc+y7/jwd4jUQRZ7yO1bc0KEflRRMr6PGbouxzJ7yXhKaV4ieICIBnAZgD1AKQCWA6gqdPtirULgGoALtSulwKwAUBTAK8CGKbdPwzAf7Tr/QH8CkAAdACwQLu/PIAt2v/ltOvltMcWAuioPedXAP2c/rvdcgHwbwBfA/hFuz0WwPXa9fcA3KNdvxfAe9r16wF8p11vqn330wDU1X4Tyfx9hF3vnwG4Q7ueCqAsv/OWr/MaALYCKKbdHgvgNn7nLVvfXQFcCGCVz32Wf8eDvUeiXIKs9z4AUrTr//FZ74a/y0Z/L7wo9nCboB2ATUqpLUqpLADfAhjocJtijlJqr1JqqXb9JIC18OwYB8ITlED7/wrt+kAAnyuP+QDKikg1AJcA+F0pdUQpdRTA7wD6ao+VVkrNU54twec+r5XQRKQmgAEAxmi3BUBPAOO0RfzXu/fzGAegl7b8QADfKqUylVJbAWyC57fB30cQIlIanp3iRwCglMpSSh0Dv/N2SAFQTERSABQHsBf8zltCKfUXgCN+d9vxHQ/2Hgkh0HpXSk1VSuVoN+cDqKldN/RdjnAfkfAYcEevBoCdPrd3afdRhLRTUK0ALABQRSm1F/AE5QAqa4sFW++h7t8V4H4C3gQwFECedrsCgGM+G2bfdZW/frXHj2vLG/08yNNrdBDAJ+JJ5xkjIiXA77yllFK7AbwGYAc8gfZxAEvA77yd7PiOB3sP8vg/eM4IAMbXeyT7iITHgDt6gY7cWPolQiJSEsB4AP9USp0ItWiA+1QE9yc0EbkUwAGl1BLfuwMsqsI8xvVuXAo8p3xHK6VaATgNz6nvYLjuTaDl8g6E59R5dQAlAPQLsCi/8/bjuraBiDwOIAfAV967AiwW6XrnZxIEA+7o7QJQy+d2TQB7HGpLTBORIvAE218ppX7Q7t6vnTaE9v8B7f5g6z3U/TUD3J/oOgO4XES2wXO6sCc8Pd5ltdPtQMF1lb9+tcfLwHPa0ujnQZ51s0sptUC7PQ6eAJzfeWv1BrBVKXVQKZUN4AcAncDvvJ3s+I4He4+Epg04vRTATVoaDmB8vR+C8d9LwmPAHb1FABpqI3ZT4RkkMNHhNsUcLcfrIwBrlVL/9XloIgDviPRBACb43H+rNqq9A4Dj2mnDKQD6iEg5rSerD4Ap2mMnRaSD9l63+rxWwlJKDVdK1VRKpcPz3f1DKXUTgBkArtEW81/v3s/jGm15pd1/vTZCvS6AhvAMZuLvIwil1D4AO0XkPO2uXgDWgN95q+0A0EFEimvrxbve+Z23jx3f8WDvkbBEpC+AxwBcrpQ64/OQoe+y9v03+nshJ0ZqxtsFnpHVG+AZzfu40+2JxQuALvCcdloBYJl26Q9P7td0ABu1/8trywuAd7V1vhJAG5/X+j94Bn1sAjDY5/42AFZpz3kH2sRPvOSvn+44V6WkHjwb3E0AvgeQpt1fVLu9SXu8ns/zH9fW7Xr4VMPg7yPkOm8JYLH2vf8JngoM/M5bv96fBbBOWzdfwFOdgd95a9b1N/DkymfD0/t5ux3f8WDvkSiXIOt9Ezz51d597Hs+yxv6Lkfye0n0C2eaJCIiIiKyEFNKiIiIiIgsxICbiIiIiMhCDLiJiIiIiCzEgJuIiIiIyEIMuImIiIiILJQSfhEiIoo1IuItiwYAVQHkwjOVPACcUUp1cqRhREQJiGUBiYjinIg8A+CUUuo1p9tCRJSImFJCRJRgROSU9n93EflTRMaKyAYReUVEbhKRhSKyUkTqa8tVEpHxIrJIu3R29i8gIootDLiJiBJbCwAPATgfwC0AGiml2gEYA+ABbZlRAN5QSrUFcLX2GBER6cQcbiKixLZIKbUXAERkM4Cp2v0rAfTQrvcG0FREvM8pLSKllFInbW0pEVGMYsBNRJTYMn2u5/nczsO5fUQSgI5KqbN2NoyIKF4wpYSIiMKZCuB+7w0RaelgW4iIYg4DbiIiCudBAG1EZIWIrAEwxOkGERHFEpYFJCIiIiKyEHu4iYiIiIgsxICbiIiIiMhCDLiJiIiIiCzEgJuIiIiIyEIMuImIiIiILMSAm4iIiIjIQgy4iYiIiIgsxICbiIiIiMhC/w9iEt+PzDqMRQAAAABJRU5ErkJggg==
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>
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<p><strong>Shape of Audio Signal</strong> : (129103,)</p>

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<p><strong>Transcript</strong> : mister quilter is the apostle of the middle classes and we are glad to welcome his gospel</p>

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<div class="prompt output_prompt">Out[2]:</div>


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+n/6v/z//j//P/y/9//3f/o//f/+f8EAAoACwAVAB4AIgAKAPX/+/8GABgAIAAlAAsAEQAYABsAFwAbABEAAgAGAAUAHQAdACcAHgAdABIAGgAmABUAIwApACkAJQA0ADYALgAwADUAKAAuABQADQAUACAADgATAB8AGgAaABoALAAnABgADwAaACQAIwAmAC4AJQApADQALwAoABsAFAAQABUAIQApACYAEQAMAPT/+v8NACUAIgAVABMABgAGAA0AFAAWAA8ACwAMABsAFgAWACsAIwASAAMAEwAZAAsACgAYABYAAAD2/wMADwD//wYAIAAbAA4A+/8DAAcA+v/z/wQADgAAAP7/DAAFAPf/AAAIAAQA+v/0//T/CAAHAAIABwAIAPz//f/2//7/AQD9//3//v/w/9z/8/8GAP3///8CAPX/8v/r//T/+//z/+3/+v/t/+X/9v/3//H/6v/r/9//5v/l/+L/5P/2/+v/8f/+/+r/4//5/wcA+//6////8f/o/+H/9f8AAOn/6P/1/+7/8v/8/+z/3f/Z/9T/0v/q//3/AgAGAP7/9P/q/9z/1f/l/+j/7v/4/wwACgAEAP//7P/f/+L/6v/1/wUA/f8DAAoA/f/w//D/+v/q/+//9P/+/wsA///z/+r/6P/l////EQAbABcADwAKAP7/+P/1//z////9/xIAHwAeAAYA/P/q/9n/1P/p////+P/3//H/9f/q/+n/7f/v/9v/5v/8/wEAAwAPABcAFwAXABUADgDx/+v/6v8GAP//+//9/wkA+f8FABgAFwANAAYAAQANABcAJQAzACQAFgADABUAIwAtACUAIAAeABUAEgA1AD0AKgAcACEAFgAcADcAUABPAC4AIwAdACYALgBFAC8ALgAvADcANAA6AC0AFQARACAAHgAtADYALAAtAB0AHgAjAB8ADwAOAAwACAAVAC4AOQAyACQAEwAPABsAGgAaACMAFgAQABUADgAKAA4ADwAJABAAGwAYAAYABwD6//H/9v8CAAsAEQAUACEAGAAAAPP/+f/4/+v/BgAUABgAGAAYAAUA9f/y/+X/5P/r/wwAEAAPAAYACwD4/+v/9v/+//H/7v8RABwAGwARABUABQD1//b/DwASAAIABQALAAQA/f8SABcACQD4//n/8v8BAA4AEAAKAAMABAADABcAIAAeABgAEQAVAP///f8BABMAFAAJABIAHAAVAP3//P/q/+v/6f/y//r/9v/y//P/9v/0/+L/4v/h/+L/6P8CAA4ABQD4/+//6P/b/9j/3v/z/wAACQAPAAMA+P/k/+n/6f/p/+j/7//6//P///8DAAIA+//9//v/AAASAB4AEQD9//v/+v///wQA/f8GAPz/+v8QAB4ABgD+/+v/5//h//X/+v/7//j/7v/1//T/8//z//T/7f8DABEADQD8//j/7P/v/wAAEwAkABcAFAAMABEABQACAAIAAAD7/wIADAAbABwAEwAZABUAAwDz//j/BAAcABYAKQAeABkAEgAXAAcA/f8BAAsAFgAdABwAEgAYABQAEQAVABIAAgD6//r/CgAPABcAEAANAAQA9//z/wwAGgATABcAEAAOABcAEgAQABYAEAAQABIAGwAVABUAEAALAPv/+f8FAAQADAD0/wUABgAKAAwAGAAVAAIA/f8TACcAGQAbABIAAAD+/xUAIQASAAQA+f/t//P/AgD+/wIAAQDw/+//+f/9/wQA+f/o/9j/3f/n//L/+//y/+P/2//j/+//9//o/+T/4//f/9j/5//3/+z/2f/l/+//8f/3//P/7f/b/9v/5//1//P/8//0//b/+v/x/+j/3v/B/7//2f/+/wYA+//v/+H/1f/X//H/BAD4/+v/7f/0/+f/9v8EAPn/5f/h/+r/8v/w/+7/7P/f/9f/4f/0//b/5v/h/+P/2v/a/+L/7v/n/+D/5f/w//P/6f/i/+D/3v/c/+7/+//z/9r/zP/J/8n/y//V/9v/3//i/+7/7f/d/9v/2P/e/+b/9f/0/+n/5f/g/+j/5P/d/9j/z//Z/+z//f/z/9//2P/W/9r/4P/y////8f/c/+H/9v/3//7/AAD6/+f/4//0/+//6v/o//H/5f/n/+j/+f/u/+f/2v/Z/+P/+f8OAA8A/v/m/+T/5//4//X//P/2/wMACQAQAAkA7//Z/9v/7/8FAA8AEQAHAAIABAAHAAgAAgDq//X/CgATABcAIgAVAAUABwAJABIAGAARAPz/9f/y//P//P8CAAMADgAZABgAFQAAAOv/5P/w//z/DwAhACsAIQAcABQADAD//wEA9P/y//X/EAApACMAIQASAAQA9v/2/wgAEQAPACMAJwAZAAcADAAEAAYADQAeACUAFQAPABAACQD+//P/AQAJABEAIQA+AC4AFAABAP3//v8AAA4ACgANAAcADQAPAAcA7v/i//D///8QABcAGAD5/+3/7v/v/+//6P/Z/+L/5v///wEADQAAAPf/4//i//X/CAAYABkADAD+//X/8P/5/wYA/v/+/wEAAAD1//H/6v/b/9r/4//1/wMADAAbAAoAAwDw//f///8JAAkADwAUAAAA/v/8////+v/3//n/BAABAAEACgAKAPn/9v/u//X/+f8KAA4AAADt/93/6v/z//X/7v/x//n/BgARAP//+//0/+7/8/8AAAMA9//x//7/BQAIAPv/9v/s/+j/9v8EAB8AGAAQAAYA+//s/+f/9f/v//D/8v/3/wAA/P/r/+f/8f/0//7/BwACAPT/7//x/wAABgD4/+n/7P/t//j/BwAUAAYA7f/e/9T/6f/5/xUAGwADAOH/2P/p/+v//P8AAAIA+v/0/wQAEgAcAA4ACQAEAP//BAAJABoAEQAKAAEABQAFAAEADQAPAAcA+v8SAB0AGwAnACkAHQAMAA4AHgAuACsAGAAMAAMABAAlAD4AMwAjABIACQAMABYAIwAiABcAEgAhABwAFQAWACQAHwAdAC4AMgAyACcAJAAdACIALwApACQAEwASABMAKAA9ADEAGAAFAAoAFgAhACsAIgAXAAcAEQApACwALAAjABUAAgAGABkAIQAhAAoA9//6/xMAHgAlACUABQDe/+3/CgAbABMADgAHAAcAAwABAAYAAQDz//3/EgAUAAkA/v8HAAUACAAPAAwAAgDy//3/EwAfABYABQD4/+r/7P8KABoACADx//P/7v/2//3/CAD8/wAABgAKAP//+P/x//T////7//n/9f/3//X////8//r/9v/3////CgASAAkA///8//3/7//n/9r/3f/i//L/AwABAPL/5f/l/+b/6//u/+3/3v/Z/+P/+/////n/6//n/+P/7v/9/wUA9v/h/9z/5f/s//X/AAD0/+z/5f/p//T/+v/u/+P/3//i//H/BgATAA0A+P/y//H//v8HABEAEwAFAP//AgAIAPT/2//c/+P/7P/3/w8ACwDu/+v/+v/6//f/9f/o/+D/5f/4/xEAEQADAPD/8P/5/wQAEQALAPz/8f/6/wEA+//+/+7/+P/6/wQACAAKAAUA8P/1//3/BwAIABUAGAATACAAIgAoABsACwAGAAUADAARACQAJQAiABwAEQAIAAQADAADAAsAGAAeAB8AGwAXAAcACQAUACEAHgAiACEAHQAeACQAKwAnABEACwAWACAALAAfABAA/P/+/wwAHwAcABUABAD+/wYACwAVAB4AGAATAAgADAAZAB8AIgAQAAoABAACABUAFQAHAAAABQD//wcADwATAA8ABwAMAAkAAAAKAAcADwAQABQAGAASABMAGgAhABwAIwApABwAGAAaABQADgASABoAFgALABAADAADAAEA/P////T/+v8LAAgAAQD2/wIABQD7/wMACQD///b/BgAOABIAEAAGAPz/9P/7/wUACgAUAAcAAwDu//n/CQAPABMAAgD9/+n/5v/2/wAA8f/w//7/8P/s/wAADAAMAAoADgABAPz///8LABIACAAEAPv//P/1/+//9v/2/wAAAgAHAAoADAAJAAkACAACAPP//f/2/+v/7v8HAAoA/P/k/9b/0v/R/+v/+v/z/+X/3//q/+3/AQD8//D/4P/Z/9//9v8SABMADgD2//b/AgAAAAQAAwD7/+//7f/+////+f/r/93/2v/b//T/BQALAPf/8v/v//H/8v/5/wYAEAAUAA0ACAAJAAMA///3//L/6f/y//v/AwD6//P/7f/j/+X/5//z//n/AAD+//f//P/8/wcADAATAAYAAAAFAAsAEQASAAkACgALAPv//v8KAAcA/f8HAAwABwAJAAwAFwAQAAsAEwAhAB0AHgAlABgACAAWACwAKgAkACIAHgAWABUAHAAaAAwACQAFAA0AGwAeACYAIgASABAAFAAXACQAJwAcABkAFwAYABQAGwAVAAQABgAMAAoACwAQAAkAEAAJAAgACAANAA4ACQAKAAUABwAVABoAGwAbABQAEQANABAAEwAWAA4ACgARABIADQD//xAACwABAAEABwD5//v/DAAOABUAEQASAA0ADwAOAAEACQAHAAkABgAHAPr/9P/6//L//v8FAPv/7P/p//X/6/8AAP//8f/u//P//f8JAAYAAwD+//v/9//7/wwACAD8//v/+//x/+r/7//3//f///8BAPz/9//2//v/+f/u/+r/9v/6//3/+//7//z/7v/l//L//P/6/wMA+v/0/+r/7//8/wEA+P/w//r/9v/v//T/9f/1/+j/7v/n//P/9v/x//L/7v/i/+H/8v/n/+n/7//y//H/7//t/+r/7v/i/+D/5P/w//j/+/8BAAgAAgD+//v//f/7//7/+P/z//P/7//y//T/+f/t//D/5v/s//P/8f/y//f//f/9/wMA/f/z//L/+//5//7/AQD0/+7/5P/n/+f/8//1//P/8f/p/+j/7P/p/+z/6//r/+3//f8AAAIAAwADAAIA+v8DAAEA/v8CAAkABAADAAUAAwD9//7//v8AAAsACwANABcAFAAPABoAHAAXABYAFgAVABwAHAAZABoAGAAOAA4ACgAIAAUAEAAcAAwADQAGAAoAAgAFAAsADAAQABEAEgAOABAABwALABwAHQAhAB8AJAAZABgAFgATAA4AEAARABIAHAANAA8AHAAXAA8ADgAbABwAIAAeAB0AGQAWABIAEQAOAAAAAAARAA0ACgASAAwABwAGABAAHQAhABsAFAAQABEABgAYAB0ABgABAPz///8EABEACwAJAAEAAQABAAkACQAEAA0AEAAOAA4AFgATAA0AAAAEABEAFAAVABIADwANAAAAAgAGAAAA+P/4//j/9v/5//f/+v/3//X/+/8CAPv/9v/6//T/8//6//7/+P/0//j/7P/r/+n/5v/s/+//6f/j/+r/6//m/+3/6v/r/+7/+f/8//P/7v/z/+7/7//0//D/8v/v//b/7v/u//f/8f/s/+//8P/z//T/8//w/+n/7P/x//f/5v/y//H/8//p/+3/7v/t/+n/9P/x//X/8P/u//L/7f/p/+f/6v/y/+f/8//z//n/9P/t/+7/8v/2//L/+v/1//f/9P/3/+3/6//m/+j/5f/i/+v/7v/w/+r/5f/s/+r/8v/x//L/8P/q//X/9P/+/wIA/f/4//r//f/2//z/+f/3//7//P8BAPf/8P/r//T/9P/7//z/AgD/////AwAFAAsACQAIAA0AFgAbABoAFgAUAA0AEQALAAgA/v/5/wQABQAKAAoABAD9//D/9P8CAAoAFQAZABAABgADABkAIQAdABIAFAAMABIAFgAhAB0AFAAEAAIACAAGAA0AEwAVAAEAAwAFAAgABwADAP////8BAAcADAASAAYA+v8LAAwADgAQABUAEAAHAAMABgAEAAoABAAEAAQA/f/4//3/BAD7//X/+//9/wMABwACAP//9v/5//3/CwAWAAwADwADAAMABgASABEAEgAJAAEA+//6/wgABgAFAP3/7f/m//z/+/8GAAIA/v/1//T/9//1//3/BgD///z//f/6//z/+P8CAP//+/8DAAkABQAMAAgABQD6//7/+f/4//b/+//+//r//P/6//n/+f/6//z/+f/3//L/+//4/wAA+P/9//v/8v/1//z/AAAEAAUAAAD3//z/+////wEA/v/y/+n/5v/h/+3/7//0//L/7f/s/+7/8f/x//H/+f/6//P/+f/4//P/9f/9//n//f/7//X/9f/9/wAAAwADAPf/8f/5/wMADAAQAAkA/f/8//P/+f///wYACAADAAIAAAD9/wUACQACAAIAAQAEAAgACAAJAAQA///4//n/9P/8//7/BQAIAAYA/P/5////+f8AAAQABQACAAgAAwAFAAgADQATABkAFwAPAA0ADQASAA0ADQANAA8ADAAKABUAFgAOABkAGgAUABUAFwAfACQAJAAnABsAGAARABgAJQAnACEAJgAgABoAGgAlACMAIwAiABgAHgAfAB0AGwAXABEACwASAB4AIwApACgAJgAoACkAKQArADUAMAAuACsALgAlACwANQAvAC4AJwAlACUAJQAkACQAJgAjACAAIgAnACcAKgAyACsAJwAhAB4AHQAfAB0AIQAfAB4AFwAWABEADQATABwAGQAZABUAFQAMAAcABwABAAMAAwAMAAsADQAGAAcADQAGAAkABwD+////AAD9/wAA+//9//f/8f/0//P/9P/5//D/8//s/+n/7//w/+j/6f/v/+v/8P/3//r/9v/y//P/7P/0//j/+P/+//n/8f/o/+3/9P/7//3/9//m/+n/6//l/+3/7f/u//D/8f/3//P/9v/z/+//7P/q/+v/9P/z//D/7v/s/+n/7P/w/+r/6P/n/+f/6//t/+7/7P/l/+b/4v/i/+H/6v/p/+n/4//o/+f/7f/t/+z/7//l/+T/5f/h/+L/5P/s/+3/6//s/+b/6f/m/+X/6P/m/+D/4//r/+b/5P/l/+v/7f/q/+3/7v/j/+j/6f/w//D/9v/z/+//8v/l/+v/5v/r//D/7f/f/9z/2P/Z/+P/5v/h/+T/5f/f/+D/5//s//P/9P/7//n/+/////3/BQAHAAQADQALABEACAAMAA4ABQAGAAAA///7//3/AwAKAAYACQARABYAFQAXABMAEgAVABYAGgAaABwAGgAcABkAFwATABQAFgAUAAgACgAFAAQAEAANABMAFgAYABcAFgAXABIAHgAnACcAIQAhAB0AHQAeABoAHAAdABwAIgAhACUAIgAnACgAJgAcABsAIwAeACEAJAAdABwAIQATABQAFQALABUAFQAUABMAEQASAA8ADgAHAAsADQAIAA0ADQAGAAAACAAPAA8AEAAKAAgA//8DAAQACQAIAAoAAgAEAP7/+//8/wUABAACAAMAAgD+/wUACAASAA4ACQAKAAoADAAIAA4AEQAJAAIABgADAAQACAAJAAUABAACAP//AgAAAPf/BAAFAAEAAAD+/wQA/f/+//z/9v/7//7/AQAHAAQABgALAAgACAAJAAQACAALAAUA/v/6//r/9//x//j//f/5/wEABgAIAAwAEAANABIABgACAAEA/v8DAAkACAAKAAAA+/8EAAAAAAADAP3//P/1//f//f/+/wIA+//4//X/7f/1/wQA/P8AAPz/+f/9//r/AwAFAP7//P/1/+z/8v/p/+7/+P/u/+//7v/y//H/9v/7//r///8AAAEAAAD8//T/9//1/+//6//s/+v/7//u/+z/8P/y//T/8v/6//r//f8GAAoABAAEAAQABQAJAA0ACwANAAkACQAKAAwADQALAAsADQAIAAsADwAPABcAEwATABYAFQAaABgAHgAdABMAHAAbABYAEwASABMAFQAcABUADwALAA8ACgAOAAoABgAPABAADgAPABEAEQAMAAoADgAVABcAGwAgACAAIQARABkAHgAeABoAFwAXABUAFQARAAoADQAIAA0AEQAYABIAEwAaABMAEgAQABYAEwAWABQAGQAVABQAEQAOAAoAAgAMAA4AEgARABQAEAANAAkAAAACAP//+//+/wQAAAD2//D/9v/v//X/9P/7//z/+v/4//X/9f/0//n/9f/w//H/9v/8//r/+/8AAP//AwABAAUABgAEAAEA+//4//X/8v/w//X/9P/u/+3/6f/o/+n/5//s/+//7v/z//L/9P/x/+7/9P/s/+X/4//i/+f/6v/s/+3/6//h/+T/4f/o/+X/5//s/+P/4f/r/+f/6f/n/+b/4//e/97/3f/n/+D/4//j/+b/4P/n/+b/5//m/+X/5//i/+b/4P/g/+z/6P/l/+j/5f/k/+j/7f/u/+z/7P/s/+3/7P/q/+v/8P/v//D/+v/4//L/5v/m/+r/6P/q/+j/7//o/+v/7//0/+//8//2//f/+f/2//j//f/8//7/AAD+//n/+f/5//f/+f/x/+//9//z//L/+P/7//j/AAD9/wIABAAJAAwACgALAAkACAAIAAcABQAIAAQAAAADAAAAAAAHAAUACAAPAA8ABAALAAsAEgAOABIAFQAUABIAFwAVABkAGwAXABEAEQAEAA8AGAAWABQADwAPAAoACAAOABEAFwAWABgAFgARAAoADwAUAA8AEwAcACIAIwAqACYAKAAoACMAHgAgAB0AGQAcACIAHAAcAB8AGwAfABsAGwAdABgAIAAcACEAIgAfACIAJwAeACAAJAAfACEAHwAeACAAFwAVABIAEQAOAAcACwAPAA8ACgAPAAIAAwAGAAYABgAHAA8ACgAMAA0ABgAMABIACAAIAAUAAQAEAAAA/v/5//v//P8AAP///f/6//n/AQD///b/9//3//n/+v/7//3/AgAAAAIA/f///wEA//8KAAEA/v/9//z/9//+//j/9//z//T/+P/5//j/9f/4//j//P/1//7/AAABAPv/+f/4//j/+//2//v/+v///wAAAwAAAPz//P/7//7//P8DAAAAAAAEAPf/+P/3/+3/8v/0//X//P/9//z////6//3//P///wQABgAEAAMAAAACAP3/+v/3//T/8//2//D/9f/p/+j/6f/n/+j/6f/m/+v/7//o/+f/5v/e/97/3v/h/+T/5//p/+j/5v/p/+n/5//m/+D/3//f/+f/5v/m/+T/4f/h/+D/5v/p/+z/5v/s/+v/6v/t/+z/6v/s/+3/7f/y//H/9f/4//X/+v/3//z/AgADAAUACgANABIAEgAMAA8ACwATABUAFAAaABEAEAAQAAwACAAPABEADgARAAwADQAOAAwADQAQABIADQAWABgAFwASABAADgAJAA8ADQANAAsADQAEAAcABQD//wcADwAVABMAGQAXABIAFgAUABYAFgAUABgAFgATABIAGQAYAA4AFgAPABIAEgAJAAsABAAGAAYAAgADAAIAAAADAAkABQAEAAUA/f8CAP7/AQADAAIACgAIAAQAAgD5//3/AAAAAP//AAD4//r////6/wMAAAD///3//P8CAP7/BgAHAAIAAgD+//z//v8AAP7/+//8//z/+f8CAAAAAAAAAAMA///5//z/+f/9//b/+P/8//z//P////r//P/5//z/AQD+//z//P/6//r//v/+//j/+P/8//3///8AAP7/AwADAAEABAAHAAoADAAOABAADAAJAAYABQACAAQAAwADAAkABwAEAAQA/P////z/AAAEAAIAAAAAAP//AAD5//3/AgABAAEABAAGAAYAAAD7//z/+f/4//b/+v/4//j/9/8AAPr/9f/z/+//9f/2//j/+f/1//D/6f/k/+L/4v/j/+7/8//2//P/8v/r/+7/7P/x//X/9P/5//T/+P/0//L/8//x/+z/7v/x//T/9f/0//n/9//1//r//P/+//7/AAAEAAQABAAFAAkABgAIAAgACAANAAcABwAHAAgACgAPABYAFwAXABAAGAAYAB0AHgAbACAAHwAeACYAJAAdACQAJQAhAB0AHQAcABsAFwAWABMAEwARABEAEAAQABAAFgAcAB0AGAAcAB0AIAAeACEAHAAdABcAFwAQAA8ADQASABwAFgAaABMAEQATABIAFgAXAB8AGgAbAB8AHwAbABwAIAAaABcAEwAUABYAEwAUABIADwARAA4ACwALAP3//v////7//P8AAAAAAAACAAYADAAJAAMAAgABAP7/9v/9////+v/7//f/9v/2//P/9//4//7///8AAP///f/9////AQD7/wAA///8////AAD8//r/9//3//n//P/7//r//v////r/9v/4//T/9P/z//D/9P/z//H/8f/t/+r/6v/p/+z/6//t/+r/7f/r/+j/6P/n/+X/6f/t/+v/6//q/+z/7f/r/+3/7P/s//P/+P/0//f/+//3//r/+f/5//b/9//3//T/7//x/+3/7P/s/+//9v/4//b/9v/1//X/8//y//j/9//v//X/8f/0//D/8P/s/+3/6f/m/+j/4v/g/97/4//g/+L/5P/j/+T/5v/n/+X/4v/l/+P/5//f/97/4f/m/+L/3f/X/9X/0f/Z/97/3//e/9r/3P/b/9j/2v/f/+X/5P/k/+f/5f/j/+b/5//q/+v/6P/s/+//8f/y//b/+v/3//7/AgAAAP7//v/+//7//P/8//v//v8CAAQACAAPAAwADAANAAsACwAKAAsACwAOAAkABAAIAAQAAgD//woACAAJAAkABwAMAAsACwAOAA8ADwATABQAFwARABEAGgAQAA4ADgAMABAADQAQABQAEgAWABkAGQAXAAwAEAAUAAoACwALAAsADwAMAAsADQAJAAsADQAMAAsAAwAFABEABgAJAAUABQAFAAIABgAEAAIAAAAAAAIAAAD7/wIABwABAP3////9//z/AQABAAUAAwAFAAcABQAEAAMABwAFAAMABAAGAAgAAwAIAAYAAwAFAAYAAwAGAAQABQAPABIAFAARABIAEgAQABIAEwAPABUAEAARABMADAAHAAgAEgAOAAwADgAMAAUAAQAAAP7/AgACAAEABAD+//3/AAAHAAAAAAD8//z//v/+/wAA/v/+//7////8////9/8BAAIABQAJAAsACAAHAAMA/f///wEAAQAAAAMA9//z//T/+//3//b/+v/6//3/+f/7//z///////////////r/AAABAAMAAwABAAEA/f8CAAEAAQD///3//P/3//j/8v/y//L/8//x//D/8//w//f/9f/5//3/AQAIAAUABgADAAsACgAGAAgAAwAFAAIAAQABAAAAAQACAAMAAQABAAAABAANAA0ADgARAA8ADgAUABQAFgAXABwAHQAcABsAEwAWABoAFgAUAA8AFAAMABQADwAMABIAEQARABAAEQAMABAAEgASAA4ADQAOAA0AEgAVABUAFgAVAB0AHAAcABoAIgAmACMAGwAhAB4AHAAaABUAGAAaABUAGwAbAB4AFwAiACgAJQAnACkALQAsACwAMgAuAC4ALAAsACoAKgAiACgAKwAjACMAIQAgACIAIwAgACAAHwAcABwAGQAeABgAGwAhABsAGgAYABYAHAAfACEAHgAeAB4AGwAWABQACwAPABIADwANAA0ACgANAA4ADQAPAAwADAAHAAQAAQD9/wAACgAHAAYAAgABAAEAAQABAP//+//7//3//f/6//b///8BAPr/9//3//j/8f/0/+//9P/y//L/8//z/+7/7f/r/+7/7v/t//H/9P/5//b/+P/0//T/9P/3//j/8//0//P/9//1//L/8f/v//D/8f/2//7//f8DAAIABAAHAAIAAgAEAAMA/v/+//n/9//y//L/7f/s/+r/7v/q/+3/6//t//P/8v/0//T/8v/1//T/9f/4//j/+f/3//P/8P/t/+7/6v/p/+D/3v/c/9X/1f/W/9L/2f/b/+D/3f/d/9n/3v/d/+D/4P/h/+X/4P/g/9v/3v/b/9v/2//g/+P/4f/e/+P/5f/k/+X/6P/r/+r/7P/t//L/7v/0//r/+P/1//n/+//7//r/+P/5//r/+//7//3//f/7/wIAAwACAAQAAgAKAAgACgANABAAEAARABYAEwAXABMADwAQABEACwAJAA0AAwAEAAEABAACAAUACQAJAAkACwAOAA0AEAAMABIAFwAXABoAHAAZABoAHAAfAB8AHwAfACUAIQAhABwAIgAlACIAIgAiAB4AHwAeAB4AHwAdAB8AIAAYABUADwASABYAEQAPAA8ACgAIAAgABQAEAAYAAwABAAIAAgACAAsAEQAOAA4ADQAOAAsADgANAAkABQACAAMAAgADAP//BwAOAAUACAAPAA8ADQALAAwADwAXABUAFgAYABUAEQAPABQADwANAAoADQALAAkACAAJAAgACAAJAAsACgAIAAwAEAASAA4ACgAIAAIABgAGAAYAAQD9//r/9f/y/+j/7f/2/+//8f/s/+3/7P/t/+v/6v/q/+//8f/0//X/9P/6//j/9v/z//X/+f/8//j/9v/2//L/8v/v/+z/5//n/+r/5f/o/+v/6f/u//D/8P/1//P/+f/7//3/+//+//v//f/7//n/9v/1//D/7//s/+r/5P/j/+P/4//i/+X/4//n/+z/7P/t/+3/9P/y//D/8f/y/+//8v/u/+3/7v/q/+v/7P/q/+f/6//t//D/8P/v//T/8//0//b//P/+//v//P8DAAYAAgAAAAMABAAFAAQACAAJAAUABgAJAAcACgANABIAEQAOABIAFgATABYAFwAbABMAGAAfACEAIAAbACAAJgAfACAAHwAYABkAFgAWABcAFAAVABMAEQAQAAoAEgAaABkAFgAWABsAHQAfACAAHQAgAB0AGwAbABsAFAAZACQAHgAeABsAGQAYABsAGgAeABwAGwAZABwAIAAbACYAJwAiACAAHwAhACMAIgAgABoAGQAVABYAFgAQAAQABgAOAAcABgAFAAAAAgAAAAIABgAHAAsADgATABIADwASABkAGQAUABUAEAAOAAoABgAGAAAA/v8AAAAA///5/wQADQAEAAMABQAHAAkACgAMAA4ACgAQABAADgAMAAcABAAMAAkABAADAP/////+//v//P//////+//6//f/9v/9//3/+P/2//X/9P/0//b/8v/0/+z/8f/x/+//5v/g/9//5P/i/+D/4P/f/+D/4f/l/+n/6v/s//T/8//2//T/+f/9//j/+v/5//n//f/8//n/+P/5//H/9P/y//L/7//t//P/8v/y//H/9f/1//v//P/7//v/9P/0//X/9f/u//D/8P/u/+r/6v/t//D/7P/q/+z/6P/u/+z/5//n/+b/7P/s/+j/4//g/+D/4P/g/97/3//g/93/4P/k/9//3P/g/+P/4//h/+L/4P/i/+P/4//g/+D/6P/q/+z/7v/q/+//9f/w//X/8//5//L/+f/6//r//f/+/wAA/f///wIABQALAA8ADgAPAA8AEAASAA4AFgASABAADgASAA8ADgALABgAFQAWABMAGAATABsAHQAfAB0AGQAbABoAGAAVABoAHAAeABgAHQAYABQAFAAMAA4AEAAVABUAFQAYABQAHAAlACUAJQAjACEAHwAdABsAHQAdABwAGgAdABkAFQAbAB0AGQAYABYAFAAXABUAGAAZABgAGgAWABQAEAAHAA4ADAAGAAYABQAGAAgADQAQABAAEAAUABMADwAQAAgACwAQAA4ACQAOAA0AEAASABQAFAASABIAEAARABMACgAOABQADgAPABEADgAMAA8AEQARABMAEwATABoAFAANABAAEQAMAAsADwAMAAoACQAGAAcABwAHAAUABgAAAPv/+//+//v//P/8//3//v////v/9//5//n/+f/6//r/9f/5//n/+f/4//j/9v/5//f/9//1//f/+P/3//f/9f/6//z/AAABAP3//P/7//3//P/+//r/9//8//r//f/9//v/+v////v/AAD6//z/AAD9/////P/8//r//v/6//X/8v/y//H/8//s/+3/6f/r/+n/6f/k/+D/4v/k/+T/4//l/+f/6//t/+r/7v/u/+3/7v/w//D/8P/w//H/8f/u/+7/7f/x/+//7v/u/+v/7v/w//H/+P/3//3/AQD///7/+f/6/wMA/v//////AQAEAAMABQADAAQAAwAEAAAA/v//////AgAAAAEAAwAEAAYACAALAAwACwAOABEADwASAAwADgAUABMAEgAPAA0ADQAUABAADwAQAA8AEwARABMADgAMABYAEAAQABIAEwAQABMAEwAaABoAHQAcABcAGgARABsAHwAaABMAGAAUABUAEAARABEACQAJAAoABwAGAAEAAAAIAAAA////////+v/5//v/+f/5//b//P/4//f/8v/1//3/AQAAAAAAAQD+//v//f/5//f/+P/8/////v/7//7/AAD+//r/+v/4//r/+v/7//v//f//////+f/9//3/AgACAP///v8CAAEABQAEAAUAAgD///7//P/+//z/9//0//r/+P/2//b/9P/w/+3/7v/u/+7/7f/r/+3/6//o/+v/7f/q/+f/5//l/+T/5v/m/+f/6P/n/+r/6P/n/+n/7//v/+//6v/y//D/7f/w/+//8v/0//L/8v/u/+3/6//u/+7/8P/u/+7/7f/t/+z/7P/s/+z/8f/v/+//6//o/+3/7P/u/+z/7P/m/+f/5v/n/+j/5v/k/+T/4f/h/+L/4f/h/9v/2f/d/97/4f/k/+X/5f/l/+j/6//t//P/9P/3//v//f/7//n/9//2//L/9P/z//H/7//0//P/8v/w//L/9v/2//T/9f/0//b/+v/5//n//P8AAAMAAAACAAQACQAKAAkABwACAAMAAQADAAQABQACAP///v/9/wAA/v8CAAwADwAOABEAEQATABQAFQAUABkAFgAVABcAGwAXABUAHAAYABcAGgAbABwAGAAaABkAEwATABQAFgAYABEAGgAiACAAIAAhACUAKwAtACoALAArACkAKwAnACcAIwAnACcAIQAfABsAGAAZABcAFAATABQAEwAVABEAEQAMABEAFgAPAAwAEwAQABEADgAPAA4AEAAUABQAFQAVABIAFgAdABQAFQAQABAADQAPAAwACAAHAAgACwAKAAcAAwAIAA0ACQAIAAcAAQABAAAABAABAAgACAAMAA0ACwADAAgADAAHAAUA/v////r/+P/5//j/9f/5//b/9P/4//L/+v/7//f/+f/2//b/8//1//T/9//7//n/9v/8//j//f/5//r/9v/3//j//P/2//r//f/9//7/+v////3//f/9//7/AQD////////7//z/+//8//z/+//9//z/9//7//P/9f/4//j/+f/0//f/8f/z//P/9P/5//X/9//x//L/7f/u//L/8P/s/+v/7//s/+7/7//t/+//8v/v//T/8P/v//X/9f/4//n//P/8//3/+//+/wEAAgABAAAA/P/8//T/9f/2//n/9f/0//X/9P/2//r/+//+/wIAAgAFAAQABAAIAAsADAAMAA4ADwAOAA4ACgANAAoACwAQAAwADQAHAAcAEgAKAAkABwAKAAkADQAKABAAEQASABIAFwAWABEAEwAdABwAFwAWABIAFAATABMAEgATAA8ADwALAAwACAARABgAEAAVABMAEwAUABgAGQAdAB8AIAAhACYAKQAmAC8ANQAtACoALAAoACoALgAuAC4ALQArACsAKQAsACYAKQArACcAJgAgAB8AHwAhAB4AHgAXABYAEgARAA8ABQAKAA4ACQAJAAoABgAHAAQABwALAA0ADQAOAAkADgAFAAoAEQALAAoACAAIAAcACAAIAAYACAAEAAMAAgAFAP7/AwAJAAYABgAFAAUABgAKAAwADAANAA0ADgASAA0ACgANAA4ABwAFAAEA/v/+//3/+/8AAP3/AAADAAAA/P/3//r/+//z//f/9//7//j/+P/4//f/9f/2//b/9//4//b/9//8//r/+//6//v/+f//////BAAFAAUABwAEAAIAAgD+/wAA/v/+//3/+v/3//f/9//3//n/+P/3//f/+f/v//n/9//4//X/9P/1//T/8v/y//P/8//x/+//6//s/+n/7//y//H/8P/w/+z/8P/x/+7/8//y//H/9//w//X/8f/v//D/6//p/+n/7v/w//L/8//0//L/8//x//H/8P/x//b/9//4//v/+//7//v/+P/1//f/9//8//z/+//+//3//f8HAAMACgAJAAIABwACAAYACAADAAYAEAAHAA0ADAAJABAACgAIAAQAAwADAAUABAAEAAQABwAMAAsAFAANABEAGgAWABQAFgARABQAEwARABQADQAKAAkACwALAAQABgANAAYABwAIAAsADAAPAA4AEwATABgAHAAeAB8AGgAbACIAFwATABUAFQARAA8ACgAEAAIABAD+/wEAAgADAAcAEAAKAAQABQD///3/AwADAAMAAgAAAP7/AQD+//j/+/8DAP7//////wEAAgACAAQABwAFAAIA/v/8//7/+f/+/wQAAAD//wAA///7//z//P/9//v/AAAAAAMABQD9/wEA/P/5//j/9//1//n/9//1//b/8v/t/+z/7P/r/+v/7f/u/+r/6//p/+3/6//t/+n/6P/k/+L/4//k/+X/4P/k/+n/8v/v//H/7//w/+7/7v/w/+//8f/x//X/8f/u//D/9P/x//H/7f/x//P/8f/v//P/8v/3//L/7f/r/+v/6f/t/+v/7P/r/+v/8P/w/+3/6v/p/+//7P/v/+v/6f/n/+n/6P/l/+f/5//k/+P/5P/m/+n/6P/q/+v/7f/o/+v/7f/q//H/7//t//D/7P/s/+z/6f/t/+z/7P/t/+n/7f/w/+//8//z//P/+P/7//3//P/8//v/AgD5/wIA+v8CAAMAAgABAAcAAgAJAAYABgD+////AQAAAAAA/P/9//z/BgAGAAkACwAMAA4ADQALAAoADAAGAAoABwAHAA0ACAAWABMAFgAXABUAFwAaABQAGwAZAB4AIwAiACUAHQAkACUAIwAjAB4AHgAeAB8AHgAfABwAHAAeAB0AGwAZABoAIwAbAB4AIAAjACYAIQAjACEAIgAgACIAIwAgABwAHwAhABkAFgAUABIAFQAVAAwAFQAMAAoADAAFAAQA/P///wUAAAABAAAABwAKABAAFgAUABIAFgAPABYAFAALABsAFwAUABAACgAPAAsADQAKAA8ACQAMAAwACgAHAAkAEwAaABgAFwAWABcAFwAcABcAIAAdACEAHwAXABUADAAQABwAFQAUABIAEwAVABMAFwAdABkAGAAVABEADwAHAA4AFgAJAA4ACQALAAkABAAJAAsADAAJAAkABQAKAAMABQAPAAsAEQALABEACQAJAAIABwACAAgACAD+/wYA8//+/wMAAgACAAMAAQD+//n/+f/+//z/AgAAAAYA///5//7///8CAAAA+//0//j/8v/y/+7/7f/u/+//8//w/+3/8P/y/+//+//5/wEA+//8//3/9//9//T/+v/x//T/8P/2//L/9v/y/+//8f/u//r/+//6//n/AQD8/wsAAAAJAAQABAALAAAAAgD8//j////7//j//P/2/wAA/f/3/wIA7/8NAPz/BAD//wUA/v8IAAUAAwANAP//EQACAA4ABgAMAAkADAD6/wUAAQAGAAoA+/8KAP3/CQAJAAIACAADAAcAJQAGACYADgAhACYAKgApAC8AHwA1ABgAKwAfABEAIQATACEAGQAWACcAEAAiACAAHAA5ABsAPgAwADEARQA1AFUAQgAuAFUAJwBGADUAJwBBACAALgAmABUAJwACACAAKQANADIAAgAlACgAFAA2ABQAJQAuAAwAMQADABcADQAGABsA+f8RAP//+f8MAN//DQDl/wIA9//q/+X/3P/O//z/yP/+/8//8//z/+r/CQDj//b/8f/a//n/5f/u/wgA4v8fAOX/HQACAA4ADgAHAAEACwDj/xUA1f8NANb/8P8JAPP/DwDm/+7/6f/4/+r/BADX/xMA0/8NAM3/8//Z//n/5f/l/+T/z//o/8j/9P/a//f/3P/s/9z/4//Y/+X/+v/V//b/uP/s/63/3f+x/7r/sP+b/7r/mv/E/5X/wv+k/8H/mv+0/5X/of+r/4f/uf93/8T/cv+v/4D/o/+Y/4r/hP9k/4D/TP+T/1P/p/9K/3//cf9v/6v/av+m/2j/sv95/5v/eP+H/5T/fP+m/3r/sP9+/7L/hv+u/5z/lf+9/4n/w/+T/9b/pP/V/8v/xf/k/7T/2f+0/9L/vv/R/8T/0v/I/83/yf/L/+3/1P8LAL7/FgC3/xYA6v/7/yUA//8vAO//GQD5/x0A/v8QAPr/AAD1//D/BADZ//D/4//7//X/vf8GAML/KQDz/ycADQAuABQARwATAEcAFAA5AD8AQQBWAEoATgBKAFAASQBvAE4AewBfAJIAdQCfAJMAoQCvAKcAugDOALwA6wC9AOwAvAD4ANkA/wDcAPkAowAMAX0A9AB4AMcAYQCcADMAXAAaAFYAMgBBACgAIgAsACoANAAlADgAGgAhAAUAGQDX/wwArf8GALj/1f+6/6L/1/+g/7b/vv9x/+7/Ov/h/1j/xf+Z/7//nv/Y/2L/DQBL/+//dv+F/6D/Yf+B/6D/P//N/xf/u/8q/43/Z/9z/4L/nv8x/8z/Gv+6/2n/fv+a/1r/lf9m/5H/e/+C/4X/qf97/9z/eP/t/6f/vf/T/5f/9/+0//v/9P/5/ykAHABgAEEAiwBSAKoARQCxAD4AqgB3AKMAwgBhAPAAMgARAWcAFQGiAOoA0QChACsBjgBsAYAAhQF8AJsBawB1AYoAJAHxAJwALAE9ADsBNQA0ATMA+wAfAK0ADABJAAUA0P8oAE3/0f/p/l//wv7g/ob+Y/5C/gX+9/2g/ZP9UP1B/Tn9w/wH/Vb82/wL/JT85/se/OP7w/vc+5D72ft4+8D7qPu++8n73fvh+xH8G/wu/HH8N/y1/E381vyq/NH8P/0A/Zf9bP22/e39Af5P/oH+mf4A/+X+f/9i/7//9v8UAJ4AkQAyAVIBtQEmAl4C7QIcA4MDtwP7Az4EkATUBEQFfgXiBfwFOwZxBoQG1gbMBvwG9gYyBz4HPwdnB0IHbAeVB3oHpgefB5IHjwdmBzwHCQcFB+UGmAaWBiYGCwa8BXYFMwWXBD0EXgPyAg8CVwGaANP/+/5c/pX98/xQ/J77NPuF+kr6sfl8+fv4lvhF+Az4w/er95/3hPea97j3tPc3+Nb3rfgO+Cn5s/hT+YD5cvnc+fP5J/p++lb6tPp++pL6+fpc+gf7cvqv+tH6fvrE+qD6wvrL+sH6xPoM+zP7GPxo/GP9CP6W/or/sv8TAUkBjgItA8sDsATmBJ8FHAa7BmIHpAc8CEoImQi2CKUI2gh2CGIIIQjaB6wHYgdIBxkHvAZ+Bh4G0wWrBUIFPwX+BOwE2wSaBJAEXQR1BJkEvATWBOIE3wQLBdoEBgXWBOUEowTCBJoEcgRBBOoDnwN2AxoDjgJXArwBcwHNAIMAEgDW/3P/C/+2/nb+2v2x/Wv9Df0i/bn8BP2J/L38Wvx//FL8Wvyn/H383PyQ/Mv8ifxe/FD8DPwn/LD7qvtk+zD7DPuY+pz6G/ob+n35S/nD+H744Pf59wr3LvdZ9iX2rPXh9Kr1e/SG9fzzn/Tg8030yPTD9LP1MvZD95j4efnZ+t377Pz8/SL/OAAGArsCXQU3BbEG6AfkCPwJrwrhC94LpwupC+MKkQooCpcJ6wmeCHoIqQdjB/YGpgaJBhsGvwXyBZMFXgbBBsAHPAhtCCEJgwkaCuoKQguZC/cL+wtJDC8MRgzcC3gLjQpXCZYIfgfoBg4GWgWCBJ4DvwL1ARIBIgBx/xH/Av5y/X78X/x7+/n6/Pk3+Yb4/PeS9+v3fvd5+LL4Nfno+GP5G/lF+OH4Ofin93z4UPco+Bz3jfdL9un1j/Zu9Mj16/NF8wn0Z/MY83LyjvIb8aTw6/Dp70jyzfQe95D5SvqF/CD9l/9MACcCKwWNBoIIsQnCCaoJiwrtCQIJ6gdWBzYGqgWrBU0EQAQcA/gAyf81/Wn9UP2e/rz+Of8rAKD/bQDVAPMAsAL4AxcFLAbiBpoHYwhxCRUJ1AjYCKUIqAhBCS0Jtwm7CcwIWAcqBqsFfgXyBaQFcAWOBQcFvARPBGMEXgT+BLQFiwVSBvQGWwdtB2wH1wY8B0kHtgfeByMI+gelBw8HQQY6BbgE4wN9A1QDoAIbAtMAXv9w/tz8nvzN+6D7FfzG+uL6m/jV98X2ovWc9b7zQPMc8t3wzvA68LbviPD87WLup+uh7PLrau1n7QHttOsh7ALqo+q86frq+uqZ64zrNOzR7afx6fPx93f3mPrH+9X9xwBFAwAHdQiqCaQJxQcACcwI9wmxCYQIpQfuBbcETQMTAnoBRwB0/1T+Lf2u/av+p/8nADAAvwBrAV4DNQVrB3AK5gucDdMNYQ50D5oQZxJAEjQSchEbEKIPCg5wDTQMygqVCZMHcQZrBfgEngSOA8ACzgHJASoC3QIABF8E2wTjBNIEqQXtBdoHCgi4CE4J+wiRCYUIiAgYCOAHoAdjBq0FmgS6AwYDzQH+//n+D/47/a77T/pu+bb3JPeK9aH0XPTh8s7zdPKj8mHzS/Kf80TxA/Gf8Tjvl/Kq77rwAvEl7bvwBewF7gTtlerX7Anp1eqf6dzrKvGM8nP3hvWy9kP3l/mt/vQAJAZ4B6IIKwkGB00Iawh+ChALyAmrCLkHVgYTBvYD3gL8ALn+IP+q/W/+av8v/9L/U/07/lz+iwCmA/4ETgeaB3sIdAkRChwNeg/pEeQSMBIWEnYRoBFcEosR5xBVD/oNPAxZChgKFQkuCGcGrgQtBFkDRgQJBPcDPQN3A7EDBgT2BOoFYwc9BzYHZgb7BrsHmQg7CUYIxwd9BhQGUwXxA08EFwLyATr/vf0P/PT57fm59qv2lvTv8wv07/C28vzvPvEI8dPvfPJc76LynO/V8Onw+u5p8iPu++/f7u/uAPJU7Mzv9uiH7NXqkOm/7WLor/CC7EDz7fOi8lv4MPQ8/M36dgBOBL4EBQmTBToJ7wYCCQYLHArJC9wILgqLBwgHygXOA00DGwEaAdf/2v8P/5/+f/3h/Mb8o/2J/24AwQKwApkDegTbBUsIkgyxD8gPcBHAD8kR7RBDE9oTQxP9EhMQDRF5DZgObQ24C/kKywfqCOUGCwhYB3oGigZpBDAG3QV5Bx0IMwi0CBwH6gcSCCkJvgn1CdsJ1wh0CPcHlgfPBu0FyQRKBCcCBAFI/zn9P/w9+sH5vfYD9Q/0xPMy9ij1U/Rx8cXwvvAJ8f/0DPQ59VLyx/EV8eLwO/Dc8YjyZ/CE8F3vCe5q8KPsIO+A6QrsyeuF78nvLe/98mvwF/Zm89H53/ll/mIBvABEBOgC/gaoCHkI+QnGB/gK8wmHCkgKWwfvB8QFygV+AxcD9wKIAXkBIv9P/3b+Iv98/nz/1/5iAK4B4gHbAmACTAWdCPoLFQwNDSsN1w03DxgQMxMAEmUSBxEuEeMPPg6aD6IMKg31CcQKcAq1CeEJVgfqBysF7waKBiQItgdgBxoHLQXmBXsGKwcQB+gGdAbZBfkFTAaEBYoFmgNbAwICywHMAJ8AywCO/Az62fiI+FD52PnB+Fr2fPdr8xvzKfMy9Qn4nfQG9TXvy/GR81z0l/Ql8B3vM+1w7p3y9u7z8xft/eqv7EDno/CI7Uzvj+tn6kztAepL8bjvZ/VG8ebvEPRU9/L7eP4ZAAb/3v/5/0QD1ghmCDwIJASYBScFJAeJCU0FhwjvAN0D0wGWAxsF2f8NAmn8+/8PAEEBlALu/kIAff4OAkMDSgXpB4sHogiJCD4KdQtFD3cNxhEVD3gPVhD7DcUSrw2CEGQNVw/BDwYOnw+DC3ILcQriCeMKVwk3CssI0gk7B70GAwbABb4FSQbXCE4G/wSlB1gERwalA8sFWgJyA+oDhAhcA1UA4QAk/rYDbf+LAT3+RP5m/mX5nf7k+079w/cH+Q73nPqY+0j91Pme8+P2X/SI+Ff2k/kw+znyoPWy7u/5NPEy9yDvmvLw8trszPN38F31Q+y17uPuo/CW8/brD/X/7iHyk/IT7yb2qPZY/GH0tfnO+mv9Ef5h/QEBRf4GAsT+jwR7Bd4FvQGn/WEEzgOaB3wAlgbhAcMCXgGIAl4F9AF/AccCTwNRB+sE+AIxBBsD8gRtCLMGTggICUAIXwqqBQYOHApUDa4LuAr+EDwKWxAUCJoP3AnMDh8KKAwaCSgNjwxjBngI/QgCCWwJQgkMCaUFBgTTCnUKGAiGBs//oAz3B50HLgdeB4//IwL1CgkJkP8jA2D/lwBHA63+MgQsBrb24P5z/yoCLQHJ9tIB2/cB/vMDv/x/AdfxOfzY9rQHqwBc/tvuXvZo/iT8ywC/96f1h/KD+gX+9AB29Ib0uPL79uD6yf8h+6LzVPHD+p/88vfp+HL4ifnP7s/8tvuU/Z30hPdJ8/z8NQO+8nL7pPym9qL4Tf4sAJD6gvMx+aX8BvwkBCjyvATK9QT6NQSl954C0Pz6+RUCev+i/bMC+/pYBED6Ef13AvQDiAR8AXED2ftUAkEGewCMC34Akwgo+xEOOwdkBHcEDfznDU3/rgwABFsJJAN2AxINAvrODwkCdQsBBFoHiAARCkwBDQUjCJQEdwX6Ai4FlQkD/8sH9vxjCOUJ//emBg0Jjv7xA/X+NAX2BIf6aQDzAJgGKAGW9+APU/B5A+EGH+/dDcPyAQmS9u0HMfmB9CsQsPDH/DIGZvnE/3z+bvzB+7D82vuoBgzxagln943+pPt59wAFe/qm94IFePve/sz4W/uFB3r0gflMAsr/a/4T+VX/GAZF8y39GAOw9mkLIPD3/kwJ/O83BVL8v/y5AqvzewfJ+UIB+gTu6ygJL/okAVn/3vphA8UEOvUO/CYDRfwNAsj6K/kCDH70OAWJ+975SAo/9LEFwvjYClb4/PyqCOL0KAf0+kQBnAf08vkLn/NCCR4EUvGXD0j5QwAhBkf4EAQrCHL0kAVFArj6xQSA/+b9CwMd/pgF8/ShCM7/Tfl9Bib8U/4OCpLzEQbVAWH6CgOK+j8G5PoQ/+oEEvv9APr/L/4NAmT+YP6YA/3+If2xARj8zQLE/l38PQRr+xEC2P8u+cwF4fz8+2cCP/09Ad3/c/6g/1T/jf9M/p7/NQOk/LP/IwGg/rD9BAMd/iz+LACtAQ79lQGH/23/IgDt/hb/IwEh/2z+AwI0/dUBqf9G/77/yv+V/4j/hAH4/Z//UgN3/UL+lgM9/cgBOADH/swDiP4RAEwApQDIAgn+Df+rBZb9Lv/DBYP8lAEgAnAA4P9RAuMA5AESABgCwQDaAW8BwABRAdIDl//NALcEmf4DAaUD3v/GANEDKP4YA0ICPv4hA20BK/9YA6D/vwDTAc7/1wAcAdcAegBfAIEB9/6EAhX/HwCwAiL+pgHvAO/+GAKX/+n/YgEVAdP+oABrANb/gABjACkAnADt/8X/zgDa/0oATQAl/+8BGf/k/6gBH/9iAMAAOf+ZAZn/4P+KAVv/9v8EATcAUgDP/4UAVAAeAIUA2/9xALYAGgDI/7kAwgCQ/10AJwDJAB0ADgCuAPT/qgDM/9v/owGU//f/5QDH/6EASAD1/6cATAAJAJ8ArP+WAOoA9f45AAYBe/9vAAsA6f+PAEwADgDx/woBEgApAK0AiwB4AJEAbgBrAKoAugBEAKQA6gA+AGYAqQBbALAAIwAzAJIAewDB/yAAvwB//wgA4f+9/1wAd//n//H/MQBr/6P/LgCK/0kAj/+k/1MA1/+J/+j/RQCM/5n/DwAr/2YAh/80/2wAgP+O/9v/Z//h/8j/2v9Y/wIA7v8m/8//0f+b/6f/AwCW/wAA/P9g/14Aev8DANr/e/9rACb//f/4/0z/bwBn/+r/+f+A/xYA0/+W/+v/+/9f/7n/FQCB/zoAbv/S/x8Amf9BAP//EABBAMP/sgDT/38ASABMAHwA7v+WACUAYQBGAO//jADU/3oACABSAF8A0f99AOf/nwArADgAWQA+AEoAMwCjAAsApQBPAGQAZAAwAIcADQA8AKIAHwBSAC8ATQACAEkAVQAiADYATwAJACYAfwD4/2EAGwDz/0QA6f9gAPP/FADt/+n/VADO/xkA//81AMb/+f8QAAEAEADo/wIA8v/z/9r/1f8OAAgA7P8HABMA1P/4/xUA2f8QAAcA7f/y//j/AgDU//T/4//N/wIA7v8NAAUAHQAbAOT/OADS//z/KAC4/+H/CwDK//D/nf8aAMf/zf/9/8b/1P/W/wcA4P/f/9X/+//v/+v/8v8OAPn/mP/n/93/3v/K/8T/AAC2/+z/v//9/+X/v/+7/8X/+/8CAJr/9f/1/6L/2/+1/w0Aw//s//T/1f8DAPn/sf8xAOP/z/8lAPL/EAAGAPD/FADm/+f/EQADAOf/CgDL/6j/6P+m/6f/vv/j/4D/5/+Q/7P/t//F/5H/9P9u/7X/5f+i/+r/g//s/6P/xv+3/+z/xf+v/6n/rv+9/8//u/+1/wAAxv/M/ysAu/8pAMf/+f/d/wIABwABABoA5/8iAMz/KQAKADUADQAsACwA8////8r/NwDU//z/NQC5/zwAo/8LAPr/l/9nAKj/JwAMAN7/JgB//00A+f/5/xgABAAMACcAGAAdAJ4Ay/9uABwAKgAhAN7/TgAJAF8AJwDC/50ACQAmAHEAFwBaAFoAYQB8AGMAbwBOAF0AWABdAGYAhABVAB4ATwAfAEkAYgBCAEgAMwASAPT/gAAdAO//TAC5/20A7f85AFkA9P+ZAD8ALACXABsAeQAJAEkAKAAQAEYA9f/U/zIA9f8LAEcAyv8yAPT/5/9uABsAWAAkAAUAMAD0/zgAQgAFAGAABAAwAGcAFwAtACQAbABMAPL/dwBcADcAJgAWAHcAFQAYAD8AUQBgABwANwBQAEQAGAAmADQAKQA+APH/AQDV/wYA2//F/ykAk//8/y4AyP9IAMP/8v/x/97/8P/t/ycA2v8IAOz/1//r/8r/KwDg/yQAyP8JAOH/3//+/8X/4f/l/7z/9v/Y/8L/wP/V/wIAkP+4/5L/yP/D/8P/kf+d/8j/lf+w/8r/tP8CAMT//v/f/97/2f/N/+3/3/8yAJ7/2v/z/07/r/+C/4b/W/+L/1r/dv9p/0z/rf9j/4n/yf+6/8D/mv/j/3r/qf+0/4H/tf+M/6v/t/92/97/yP+V/9H/Zv/J/4b/ZP+w/43/r/9u/1//vv+b/57/wP+u/87/9/+l/6H/w//y//b/1/8CADkAUwC1/97/OgDi/xIA2v/D/ysAHwBs/7T/BQCb/4X/sP+k/7v/nv9v/9r/wv+U/9f/qP+5/3v/4v8BAHH/FwAaAH3/BwD//xIAKQCw/yEASwgUCo77h/a5AcoDVf/F/jT/kQFZAnL91fvcAr8DYf5c/vv/c//AASEAOf+mAAAAov79AOUAvwAYAjD/u/2wAR0CY/9cALUAgP+q/x4AYQDzAb0Apf6v/mYA4QDLAN0AIwCR/5IAVv8OAFACJP8K/rAAu/85/2QBQQBn/9L/Rv1T/u0Ad/+C/c3/pP/PBEoHzP5R/dwAov5n/9AAbv4AAo8AZvrBAesAMv5TA3b+P/0pBF/9PAEiBB37uP4HBM76XABdBq39eP5IAhj/iP/9Atj+NP/UAY77Bv34BJD+ZwH9B3z+dgD9/7r8XgCDA43+aP+v/C0BlQFf+wUE1QCV+z0BrQFu/T4FogFT+6QDJ/3C/t0EfP2UAdIBXvlYBK8Acv1sApL+sP7lADr76QHXBIr6+gCrAgv64QNwAlv5aAfT/5j7OwHj/X8CsP46/9wApv2C/ZEC8vwGA/EBSvflBcL7vfsRB3L6dv0hBNz77P+2AZX9jATg+kT+7QaE99MCJQbG9EsDuAby8tQIhQIF8pEHSwK6940EzwDw+UgHJfw8/7EJfADNEHsAnPZOADnyggQ+AZz5YwqwAWf/SgFH/WAIEgDn/eoBv/tlAPQFDQFAB2r8jP5mBVn9+AenAlX/8vu9+3v+C/ry/zT8yPP0/3n8t/u/A0kFhvu8/HP/YANuAbgCbgH+/XgCtv8HBTL73AIY+oP5Lf2BBgECWP3bFP77QPn+CioBYAQsAD78WQY5+w385wII83H+KfiM8UYCh/jFA0gGqPpCD5YCPP81CuL9VQZCB+37sANPBML/kQlj+3L70wLS8WwCcwqk+OgMXPVZ+3AGqvAOBKwBjPniBHj4ygOJBlT9/wMk/Zv8XADa/TP/iQBZAsQA5vqOASwAMPZ3BKf3IPhKCyj9PQrBBs31IQO283H5DA6L9/QK0wEg9wsIy/jr+6cCfv9fBsf8Vf6n/u0CZgSAAHAFUwHH9zYDgfjvAJoIgfq1BpD2kQA6/aT4jADECEgF+gKjBE3/TP/y+xYHxQMzATYA7fbkAXoAAAACCq/7SwlR+Y32pQeT/wICmAAEAnsAL/vP+PMCSfwrA8YApAC6+lT95wFRAQ4F4//g+lv+efyyAvkAPf4tB3MAmfu//Xj+Lvlv/rICXv5U/6/29vvE+Rf85QIn+976hAAg/67+Yf+w/93+8P6n/fb7Mv2dAR//+Age/yL8M/+8+GD/HfuX/wP/nQEdAAz6o/s8+QUBMfu9/3YF9f9YBKsAvPwT+M8ER/6DAK7+NQED/sn/kgXB+VH8dv2J+jb+Cv9cAD0DBgKn+wf9xvpv+yL/GP3pAu/89P6y+1f7BwIvAAb+K/yv+1r4FP0o/jID3P+eAnv5W/um+q77lwHp/Qj+4Plo/pb4K/3Y9r/6wvgD/jv63v1G/UP5dPoC91X9U/e/AKH6Sv4w+pX69fkZ+4/7rftX/x/6yvx3+Jv8/PywA1P/FwAR/7X9QwA0AYYDQAUyBc8FXAWdBEcHbQbDBx8JqAdCCSIKcAk/COgG3glDCO0LvQqTCVwLfwmJCPoIlgeDCUsJagkuCocHqgcqB1AGEgeIB5gFwAZ+BmMGxgW1BPEGqwWsBagFNAOJAxwCTAJvAn4BfQL1/8b+NP+c/Kj+kv0//HD8K/yn+uv51fm0+of6F/si+jr6gPnJ+K33N/Uc+ID4j/c3+an3p/jU+PT2GfjD9Kf2ovb88sz3XPN19V70DPMd8UTvXe8I7uLvXPUu+ML9rP69APD/VP5OABcAZQbWCusPyRIZEqMSUQ1jDSwLwgmmDKUL1w2bDJMJ0gcyAvX/XPzn+/P8AvxO/l/8Wfya+lz4FfnW94j62voY/VL/qf/fAm8DxgTfBeoFXAgZCQAMPw3hD5YQvQ8uDz4NfAxzC3ILSwzrC2kMowprCKkG1wN8A5cCQgPDA4oDTwMrAjABCQAlAL7+ogBVAKYBxQKdAaoDngKKAoACiADHATwB4gF2BBsDfAX/AicB/ACn/nYADgA0AYoC3f90Ain+rf2Q/EH65frW+QT7tf0r/AD+Afq/+pX37vbN9iz3dviQ9yL5mfdP9jH1RvKQ8vXxHPEX8zTyq/Ii8eHvafAJ8eXz6PYA+hb+fP12/6j+9f7x/xcBAQaICLQMUQ6tDdQM2An1BrYHvAcoClcL8QsjC+4GbgSk/6T93/1j/REAoQCzAY4Bxf5E/WH6Afpe+jn8Jf/7AI4CWwJOAtUAmwBNAYcC7QXVBv4JPwqyCfcJ3QZeB+EGuwajCEUIJAppCC0IxAbNBIoEzAIuAzoD4QIFBEIDbAPJAikCWALgAZsB7wH6AUsCuQGNAsIBMwKnATIBfwFAAakAuAHpAPoBpADqAYsAPQFaAJoAyABbANoAkwBWAF0A1f+V/2P/2v6c/s3+//2J/l/+1fzD/Wv72fvx+ur58fri+VP6oPkm+dz4qPeZ9173BvcZ96/2Tvce9hn2mvS79Br01PRI9sX31vg++qn6IPs9+vD6b/sD/CX+9f9OAlID3wNDBFgDDwPMAp8DOwTqBFwF/wRGBOICBAKmAcwBxwHqAtACRQOyAiYCswG7APYAZgDpAFMB1gAHAnEBqQFdAQwBkgFEAZ0BvwHEAd4BugH7Af8BQgJuAlAC7AKJAr8C1AInAyMDbwMpA2cDcANtA9EDwgO+A6cDxQM6A0cD9gLTAucCagJgAvsBdwF1AQgBUwEmATgB5gDXAL8AYwCRAFAAnACEAIoAvgBWAKcAVwCSALYAeADNAK4AXABWABYA2/+0/9f/af9i/wH/e/5Y/sj9qv2M/W39Sf3y/OH8c/w8/OL7qvut+2T7UPuW+3D7jvtm+y777/qN+nz6V/pz+iL6Y/pT+rf5Mvpg+db52fnC+Zr6Z/pd+3X73Pt1/Gj8Rf1H/WX+5f42/14AQAAGAXsBoAGDApACIwN3A64DAQQ8BLoErwTpBJUElQRxBEYEfgQkBKEESwRoBF4E2wP1AycDQwNBA9wCLwPyAgED6ALLAvkCkgLHAoYCdwJrAloClgKyAuYC3QLnArsC1ALEAt4CJAP2AlQDHQP+AtwCcwKIAmECeAI4AiUC4wGoAZwBSAFHAS4BHgEZAfAAzADJALkAmQCjAFIAKAADAMP/yP+v/4z/nP96/33/Xv9Y/0n/S/9s/3P/cP9Z/0j/Sf8y/wn/BP8I/xH/If/3/tH+k/5c/vr9+v2q/Yj9Zv0f/Sz95fy8/LL8h/yB/Eb8JfwH/AP8DPwh/Cv81/sA/Oj71fsA/Mn76vvM++n7C/zj+w/8wvvr+9X72PsD/O37lvyA/Mb85vwE/YX9o/0R/mD+tP4O/3r/9f8yAI4A2wAPAXMBmAHuARoCZgLLAuYCOQMaA2IDegOAA8gDpgPLA7kDegN6A0wDHgMJA+gC3wLJApgCQgJkAjACAwIEAsUB/wG4AawBkQE/ARsB0wC2AKIAngCvALcAxQB3AGAANgBNAF0AcwCVAGsAeABFAEwAVAAuAEwAPwBEAEgAPgBEABcAJQDt/6//nv+C/47/n//C/5f/fv9k/0v/Kf/1/gz/Kv8W/yX/DP8u/xj/Bv8P/+T++P7R/u7+Iv8W/wL/4v7E/sf+x/7D/tr++f67/qb+jf5n/nX+XP5j/mT+Q/4y/g7+Dv4B/g7+G/4c/gf+F/7y/e39+v0K/jT+G/4l/g/+F/41/i/+Wv5Y/l3+i/55/r7+yf7e/h3/C/8s/zf/Pf+U/7v/3f8UAOH/HAAXADAAggB6AMUA7AD5AAoB9QAPARIBGQE1AVcBWgFjAXUBdQFkAT4BEgH1ABcBBgH3APIA3QDSAKIAlACHAH8AgQCFAF0AWQA3AD4AVgBKAFUATwA7ACQAEQASAB0ABwAMAPb/2//K/4z/pv/F/7r/wv/P/+L/2//g/+v/1//Q/7H/tv+7/57/5P/R/9T/z/+r/63/l/+X/4n/if+M/2r/f/9g/2T/Tv8q/yf/N/8l/zv/RP88/2L/VP9r/3j/R/9u/0f/RP9Q/0f/Zf9r/3T/W/9T/0j/N/9H/zX/E/8s/x//B/8d//j+Av8D//T+AP8S/yz/N/9d/2P/eP93/2f/bf9e/23/bv9v/5f/k/+b/57/f/9+/23/XP+X/4T/pf/V/8v/1v/S/8v/3P/Q/wAABQAUAC8ADwApACYA+P////H//v8pABMALgA2ACcANAASAD8AHwAfAEYANgBgAGkASgBiACIALwAkACsAfABiAFYAcgBaAGoAdAB2AH8AWwBzAHkAhgCiAHMAmACmAGUAaAB0AIoAeQCvAJUAeQCNAHAAZQBmAGgAaQB9AK8AlwCgAIcAgwB1AHwAcQB0AI8AfwB5AGAAaABLAEsAWgB3AF4AcgCPAHkAqwCuAJ4AnQCaAJgAhQCWAHEAgQCBAE0AaQBiAFAAegCOAJQAjwCJAHgAZgBvAFYAXwCCALAAkwB+AH8AWwBLAFYARABhAGgAWwB8AGwAVwBkAGIAhwB7AGgAkwBuAJkAmACdAJYAhACXAJYApgCTAGkAkQB7AH4AagBsAF0AZQBeAGUAlgBoAJsAaABcAHkATQBlAJIAlwCtAIoAggBzAFcAOwAzAC8ALQBXABwALAAGAAYAOAD5/wMA2f+3//P/yP/g/9z/8//y//T/JwAMAPf/GgBGABoAFAAbAAUA/v/l/97/2f+3/7j/sP/O/6r/rv+//+f/3v/i/9n/5P/Z/9r/3/+u//D/1f/M/9b/8P/K/+T/5//k//b/xf/N/8r/pv/B/6v/1//u/xwAKgA+ADUAPQA+ADoAJwArACQAMgAvAAgAIwDz//D/7v/E/6r/l/+m/67/mf+3/8j/rv+0/+H/yf/G/9n/zf/W/8f/u//I/97/yP+y/7D/v//F/87/9//p//7/EQDq/wAAAQAJAAgA//8JANz/2f/M/6T/yP/L/8r/6f/v//b/KwBCAGQAeQCRAKwAigCdAHgAnACNAIoAkACoAKoAsQCBAGsASwABABgAMQAzAE0AEAAmAAMA8//v/+r//v8LAA8AGwAbAAcAEwBMABAAAwAJABkA9P8BAPr/+v/y/6//z//k/+r/8/8XAG4AQABMACEA3P8QAO//FgAXAC4AOAAnAD0AKAA/APz/bQDG//j/yf+z/7L/1/9bACoAlADBASsAbAGAAOYAhP9NAPr/5/50/zr/KgAa/0AAQQDMACcAhABLAcAAYwRPBG0DnANUAtUAwfz2/dv6efrT+RL8xvx3/XAAAQLLAoIC2QQzA/0BAQGn/2b+jPzH/D/9ev+4APcBIQWSAt0F7gFvBCUA9/4O/gD9+vvY+mv9uPyv/rH/2wCWAtEBbwPsAacCOADbALD+r/4Q/lj9tf54/g4ANQCXAfQB6AHSAekA6AC4/qj+i/21/ZT97f1+//T/MQGmAU8D+wE7Ah8CQAHcAIT/OP8N/uf9XP3s/cv+Kf4vADP/KgBX/6L/0v6G/8L+Zv51/5b+QP8N/uAAu/6v//n/XwDMADP/aQFjAGYB/P9NARUAiP7B/4L/1f+p/u3/jwA7/1j/VgDj/7n/PP9VAIn+o/5j/jz/fP5n/sb/1P7P/wD+zf+h/l3/Ov6x/ywAMP/dADYAwQHK/24B9wCCAKoAnQF+/9v+GQDZ/xX/2/59AeL9UgE7/j4B5f6x/ssBcv51ABP8EgIO/VX/Q/weAGv8O/2m/MX7b/+R+hf/EgUrC6wKdBRdFKAV+g5IEE4I1gA++ef18fD960zwcPCa9X34Sv8EBH4DlAizBuwGdwMhA9H8PPls/9T2k+8d/qz1JvuU804JTvzZCG0JMwvMGh0MUho7C1kPNPpR/cL1V+zW8lHrwfh78jgBkv0ECF0J1QdoDKsDUwqp/ssDnvkY/S36+fZ++9n5if/M/G0DVgFVBZ8F6AGiBiUAOAGN/db+mfo8/Wf9uPtK/4T+fgLw/i0CDwJ8/0sBaP0vAFj7Q/+7+q79y/5u+tIBq/rKAnz5jgJ++VgAX/2h/xYEtQ11E0sQjB5uGFgXWA1LDAX/APc57y3rpOq15wXw4/Km+cn8DATgBX0G9Af2BEkCBP2d/Lf5wvRk+Vj3v/x3+8YETwndEmAQORqtGCIUow71CDgBa/T78a3nvOqp5ozrCvGA90D8oP8rByYHOgdIB64EWQFN/H/7V/ZK95L2Ivcb+136UQJGAaUH2QSUCXID7wQZAL39B/tr9xP4i/TC+Tz6qwD3Bv8MdhF0FxYZAxbOFXcMngWe+xP12uzP6nbpv+tI8IPyvPlZ/KkCBATYBt0FjwOrASH/nvvc+Ez3afXk95b6d/+3Au4HJwuXDWsLRQ1OCfkIFgMJAnj88fgi9iH3HvUf9kD5RvpA/e3+4P4K/2L+Sf3J/mT99/o7/TT70PwT+wD9qP6z/b7/QQFY/gr+3/8I/cj+zf6HAXoBkAOsBJ4BKwQl/lMAoPwr/eb8I/+Y/cr/jgAUARQAE/6f/mb+2Pxj/JD+Vf3x/cH9Uf7sAJoAGwOeBNQEhgQeA5UBSf/D+9r8gPp1/dP+kP56ALz/DAGh/84ADQC3AdwA0P8eACECsADxAEkB3f7R/1399gCc/QIBSf51/1IC8f6IAGH/9/7f/xEAvv0oAL4Amf90AA8BQwB6/XT/RP0V/97+5fzK/8gDiQFHBLIDpANdAdT/HABO/m3+Wv6C/U8CVv4aA4IEzgWpAp0B4vos+1v9Sv7C/eX+VACdAyAElgbMA2QCIf+o/778of3x/Ab/3v5w/rMAzABaA90C4gRxAkoAmAJu/IsAvvxRAngAbwRNAtgCYwPd/hEBzAELAW0DggN+AhYAtgHS/hH/CPxH/yL/Pv0hBIAA6QKaAIEFVf9sAToAMf0nAnD9swQkArEEOQO+AQAC0f9x//z7sfsp/iP+jAHnBGP9wgCE/cQCzQH+/yf+Mv9X+Wz+Rfq3ASf/o/4TBFUBiQbe//AGPwVWACYFSf0QAO/8cPi+/GL/YAG8Ap3/NP9YAOMCQQOHATQCjP3Y/QQB0v4oANP9nv3b+g/+gwKhA/EIpgLWBgT+fgLJ/C0Bbv8Z+ir+/PxO+wYAgP25BbYBIwiq/c4Fgv2lA6H/Zf/eAWr7S/6o/eAAyQJN/IUDVf6F/k4BRQUdBVcDOAMSA6sASfw2+dn+wPwnACb+vf1MBTYEhwZBARkE0/+LAQj38gFt/IsCg/9GAA0BAgDF/zkCEQBIBfT8zAGdAZ0AwQHp/uMDuQAmAcoA7P+y/y7+dgB6/bwF8gFYArr/swEI/jT/JP2xAOj+SgP4Ad8BS/0b/gsCHgDfAFsESwK2/VT7iv/eAVIElf0wBBb/dgSw/0v+IwBN/D757vx6/Rf/XAJIAKACuv1pAMz/5vxR/4YEMfwBAIb+0wOWAhUBuv9s/97+XwHCA5H+8wJWA4H/FADp/cn/jf2VAd0Auv5a/KT9i/tHAHf/WAGfA3MDzwHgAGv9TAS0/Rz+RfwR/4b+AwLmA88CzfznA/T/CwM9AQ8DZwG1/b0Ae/5r/6P9iADZ+owBRv2nA9wClgL/AawAaQL5+rv+ZvQ5/sr69AO8/fsFnPycBKH8u/9zABj+qQPl/tIDaAAyAzz+afsc/HH+Qfx6AP79LACSAgr/2gGrAYYA+f8e/Ij+kPzC/Vr7GPy0ADP/QAXqASYEagDGA/D+wAL/AgH9TvpR+lgBovyxBFsB6QTN/JP+HgBj/gQCKQEvAm8B7f5N/R39dvc1BpT8P/83AsUA8P/8AUL/ewOvACcBvfud+pz6ff1MA4cEKAIhAekAnAFX/fP/y/vZ/mH/cQVNA6gC9v0gAiL7qAKd/IcAbP4HAFcCogBVA/4CQwIBA3b9XgPB/qoA5AC0AmkA8P3r/C/7mQAj/UEHMP7sBqMAIgSY/F7+Sf9VATH7tf0++qwAWf97A6AAV/pXAZv/bQM/A70BPANKAwj98vyl/Uj/vwPT/MsB/P0ABav/ZAOS/ev/7wIu/q/99f+mALUC7P75+/T7vv0YAnABuf8CAVb/vf22ACD/4v1Y/ogCzgMjA2kDyf0s+3f88P8i/2AC//2n/JsBegZ/BsT/rAfq/coAXPzV/TMAjANzA5EA9vypAWv/ZQAvBIwDGQERAkwAov0r/On6gf0r/bf/hQFeBDcDLAMS//L/yvvd+ykBFwJq/oP9vvwiBQsDWQKP/+MCBv5E9x39qfrVAVD6bgF7/cQCxwC4AFwAVAOs/jb89vt//NH6YgD6/EAFPgQDBJD+SwRaAWUCQ/4pAFX6dPst/dD5swJX/r4FiQP7AnMFtvrW/+39Hf+1+Qf72voV/WL/GP78AJz+TP0mBAEHZgXIAjIBwv2DAj36dvsi/HP8XP9//qwCrgSqBE4EMAbT/HMAU/h7/Rv5APmp/AP8dfzN/FEDPAUfBUj+3gA9AAsCOPn5/1759vxP+5v+vgNgBOwD2AFOAbABPQDmAgn8s/7S/Cj/7vkz/Jz/mPyQAf/+VAI5/MIBwv0W/u7+sf6f/NP+iP9i+uz/aP9sBEUAaQTZAAj/eP1p/hD+xflT/pgA9vxEALAA7v6eAn0AXP8UAcP7rPpa/kQCDAP3BOYAaACE/1X9GAAPBT0CWQP6ARsCTwMo/93+ZPwd+1H/gP5vA0j/2gEfA53+cv/PAhX9WgHS/k8Auf93/aECnQAgAagAFwEM/8cEQAQBA5j9BwE2/W4ByPzI//7+fAB6AC7+oQMdAg4EDv7V/237zv8E/v78b/y0+vP/UgAjBrT/VwNRAH0BSADoALIAJgEsAhj9NP8JAYsEVgAY/zoCRAR4ALcBx/6WAC/7z/59/ND7//5U/8YBVwNHBAcFtgJTATsB2gBR/qD+WPqb/An+F/vd/WYBngRLBR0HnwYPBCj/Nfnm/CD7WfxJ/RIBMAAkA/oBOgMgBOoB+f0r/xQAAv6y/Dr7dPt//GL9iP+mAf4B5gJvBkME6gSkA4ABSP/D/Y3+yPxb/xX+SAM4ARkBngFpAEQDBgANArgBDf9D/1/7ef4x+nX88/rM/8z+/gL7AQUDHAI0BQgEFAVrA94Aaf5p/8b8Iv/KAJgCdgJBBRIGJQZ6A+UDZgHD/9r8L/1Q/tP93P8tAHYB0wTKAcoBbQCpAJX/8/2b/Zj+QQFr/+YCzgL4AosBGwCbAYAB0f4D/2P9Pf4t/Wv82PvK/dr92PpE+3D79/sb/PL5xPvc+mf7RPmc+SP6Rfu++Xf8tvzn/uv8Sv4Z/Cr9HP1i/Nf9sf5t/GT+xvzk/Jn8PPzY+/P5Q/sl+t75+vku+Wb7D/qq+038qP2M/Fn9ovow/M38E/0s/sT+tf/I/7cBPgIHA2ME9AR1BX8FJwZTBxcJMAv2DEkPmw81El4SIRPiElMT6BKrEnESQBJxET4R2BBpEcoSQRIlEk8ReBAsEPkN2g1rDOULKwzVCi8LPAocCRoI+gUvBrEDIgBo/gb87Pld+Nj2UvcB95r39Pah9zr2UvjN9lP2+vVF80Xzze9H78zuvO027uLu2vDl8OPw2vDu7rztWOuO6L/nAuUl5EjjoeO74hTkQeLa4G3gXN8N5W/m9+128uj5IgEGB34QKRZnGqkdoxz1HD8cqRocG6gYQhfEFcISBhJHD8IN1AlRBKz/nPkR9qXy6e6z7vLt7e7T8Oj0+fiS/JUA3wXECi0R4RaOGqwgHCPcJyMqciw4LgEsXStcJ10k1h9VG1sWwBCXC3gHPgRNAscBwAB/AUkByAGUAioCeQIiAAf/Pf1c++D54fep9efzD/SV89ryJfMO8y7ysvL476Pxue/17FzsFug06Hflf+Qr4h3hH9/a3TTc29ww2/zaRtma1drYftYX2LLcw+Hm8F/2/v9/CiQUeRzgHwojyCabI70geRwHG1MazRV/FKYSaA6dDacGCwSi/aD1HvCO5x7jReDZ3kXfMuH75Qjt/fCw+Kz+dQSLCGkJ3A7JEGYS8hWxGtEhACW1KdsuIDAjMcQtaSnJJNsczhSuDfsGeASRAPL/zwAUAkoE/AQ9Bs8GyAbiBgwFZwXkBawGHwjiCZELxg1wDdENLAy9CEgE8/wX9/Xxg+5a60vpIedz5fDmVubV5k3p2eSg4uXeut4Z3STaktrE1p7YOtns2nff+eFK4JzhG+Ls4yPl8eYv8EX6wv5nCMEQWhwSIzIlGyjsJn4kex7HGP0U3A/aCaoGLwISAuz+Gvy9+TXzn++A69TmoOOg4G7h5eKk5gHudfWM/YwFKwzxEj8Wlhr3HPca2RrlGe4dSyLsHzQkKSXRJcMk1iBMHroXiw+5B5kAH/74+kv5EPoB/C8DugR5DXcMFBQ1EOMVTQ6cE4oOtQ80DnINYxC3Dv8QwQ0BDTUIUQT1/Yn3Qe7L6djjLOCA3+fd0N6a3ufeguLS4Lfjud/74Ifdit2/3N/b+9uS3Cbfdt/H5ETiV+fv41PouOaE6NjpnPGo/If/tAl9D+MZWCBAI94iHSXqH38awhXcD1oMWQYqAnT+qvwW+6b5ZPeX8nzvPe5L6i7na+Zj5qDpFu1A8x/88gNzCvAQdRZGG9QdDB4dHaYa/Rl2GFQbWhtBGc4bPxpfG2cZARf3EV4MSgYHAqv+ivyy+8n7Iv87ApYJxwzaEd0UThVGF0wWyRS7ErcQ2g41DUoMaA2aDN4LRgrjCCkHOgJ0/jL4lPKP7RjoPOQ64l7hOuHf4I3ixuE+5DrlseRy5JjhjuHp4BThkd4X4QngP+Fq45jk0ePq42HineTF5b7keOeB8Qb7VQGpCBsS2xuGIlYjDCZ/JhAihhuoFmIRtQxaB7oB/P73/IT8wPni94fz9vLL8MPsPepG6j/rrezZ7+71OP71BAQLChLIGCMdvh97IH8fEh6kG5gZhxlRGUYWmhY6Fj4WgBYRE/YPsQuJB0oEGgFW/RD8vfxe/k0BOAaMCzYPehPfFQQZABrdGGIWZBQ8EgYQEg6TC7YKwggbCFgHPQYbBPQA8/3s+Tn21vHV7OzoIea75P3j2uPt4hvkz+SU5u/n2ufl5zLnVOZI5DjmyOPn37vhZ96H4OTeTNvi2ljbrd1D3fHdyuKz7pL3K/1jB4ESIB3LIg0lEiicKuolSCDRGwIWhxFqCbMDLgD4/UH7OPcz9ALyGvGS7TbquedM6Nfn1ucX6/PwHvh6/b4E2g3WFa0c+x+sIv8kQSTmIYAeJh38G3YWnhMaE5ISOxFkDs0Lvwl0BwcEJgA7/bL7if1h+lIAoQC5CJoK+A9aEbgb9Bj5G9IXaxlBF3QTIA5TChkMjAYjBBQFlwOuAqYCtv0aAXX72vgL9szvpO0k6j3o3uVy56flrubS6LvqXOy/7ffqWe3w6hDpm+cY5DHiOOC239rau9xN2lHXVtkw2VXbl94H3UDkK/Qe+esCOwp1FbkilybRKYUrxC3JKA4kTB88GocSDwqIBDIAe/3I+PnzMPDO727usOvv50blWOZU5+/nC+o68a314/v4BIUMaRYLHI8evSQRJ+0mYySUIZkgNB0hGFMVxBKtEZkNtQvxCf0HeAbDAtsAgf+b/kj/+v0wADkD5wY2CpsN3RH+FRgYUBjyGCAZAxbFEi8Poww2CiAHZASZAxUDfwKGAhUCXAEeAIr+D/yx+Zn2HvLc7tXtS+zW6mvq3ujx6cHrEu3/6+XplOvI60boc+jk44ThYeC93F/codqN2BjYAdfY2GLbO93N32Lh8eyC+tn+JAazD1objyeoJuYpfC0sLBIofiK7HrgYVg6FB2IDYP4S+zfzKPGk7l3s6Otb58fjHuTY487lCOYv6GbudPNS+hgCRwrWErMWQBz9IqglvCXoIhckCiRwHkUbwxc1FmgSbw7BDM4Jigb0A2QBVgCa/pL9MP3F/Fn/eQIjBO4GQQkBDgIRBhJQEx0U6hTTEssQ8w7ADBwKbAdtBd4E5QPWAUECXgHEARYA+/4I/ff6lPhs9MnwFfDp7AXrbepG6GronelD6bTpQegE64Do4ufp5tLlvuN14xbfO9+P3mbbX9sn2trYG9xG3VzfdOFe69n31v5HBUMOgxtlJh4oDCgwLgstUSmZIpQeHRmSEGEJvwW5AJ/8afa+82/xlu547GDpauRv4zvjneO+48Pj/ekN8AP33P1dBjEPNBZoG8Qh4iRRJoQlkybYJSYhJR7eGzMZZRUoEk4P7QsnCEcF6QJzAK79Jfw//Pj71vwR/7gBxwS+B94LQg81EYkSlBNvFD8T4RFWEA0ONAxdCvYIKQhmBv0EiwU6BB0DFwJqAKb+NfzF+aP21fNS8vLv6u1G7djr2Ovp617sUusV7K/rUOz96YvqGurs5/Hnl+Wm4x7jXeFM3q3cTtxa27jbWd7r36zk8e9f+l4AagnCEgYeJiZjKLIo9CmHKuslkSBwGt4TUQ2yCrYEu/7Q+ib44/RB8ZTtqOsH6LfkAeHv4P3hD+Pm4+Toue//94H/KQaRDcgUERxSIG0hPCJNJBEmEiMtIB0ejhz8GjEX9xLrD6QNrAmRBTMC0v5l/P/61/lM+Dz6J/yL/skA4AM9CCkLjg1DDgkPFRAREJkObgygCv0J7gi+B7gGzwVsBoUGMwXYAw8CTwES/7L83/lC9m70JvMi8VLwW/DH7yDwP/GK8YzxNfGW8ETwuO9B7tjrHupl6T7o2OfL5X/kEOPY4r/h3t+q3lXfBOHg4THmx+009un9NAbJDbwVhx5jJN4lliS4I24jjiHuG94S2A1pDBsJ7QQHAEH8+fjs+Hz2Y/Iz7cXqTunY51fmCOVx5iHpDO2m8kD4/P1yA6QJqQ9mFC8XRBmNGmAdQB4gHk0etxy8HJ4clxslGOYUZRM7EHAMXwh5BMAB5f/s/aP8V/wq/cH+lQDwAhwEPAbXCD4KhwpuCpMKRAqWCQgJoQgmCB0I1gj1CHgIxgcaB10G8QRdA+0AnP58/Ov5A/gQ9/71QPXu9Ar1FvWN9J30GvTT8wvznvKx8XDw3+/K7lPu1+2e7Dzs8urW6cnnj+Z95Hris+A23wPgZeHZ5A3rKfIt+hwCMwoLEQYYWx1NIAAgKB95Htwc8BmIFHQQAg5xDC8LvAiDBXYCYwDn/hr7I/bA8anuY+xf6pPoHegH6d3r6O+F9Gn5kP32AYoGCAq5DIcO2g8MERUTPBWtFgMY7xgeGtIbwBwHG88YcRY7EwUQ3wtiBxkDigBH/1b+Kv6J/m7/MQGQA94EwwVvBhMH6AZvBhIGKwVcBR0FlQSaBW0G0AbHB+oHsAdiBtAFkgNDAfD9H/tb+EL39fXC9J30FfYD9xX3lPi3+OT3SPck9zr24fTd80PzuPHP8KbwqPG48Abw9+8Q7//tjOyG6o3nf+Rr4CXeUt0N3gjhpuZg7Xn0WPzFA0EK2Q8cFVgY1RjuF24WTBX5E3IRDA+GDfoMTA3eDW8N1gr7B2cFMQK3/mL5pPRz8AHueOzQ60Dspu0q8NXza/fq+mP9RgBVAtsDUAQaBeUFswZMCJgKWQ1xEJATyRbnGDQanBrBGVIXoxStEXIONAsDCHgG4gWNBbMFPQZaBgMH4Ae/B70GkQTRA8kB1ABTARIBBQKmA2UE3ARdB3AHQgYsBpEEzwMWAXUADgAr/1b+ov1A/h/+jP6n/zb+oP0b/qX/0f9j/fv8W/7N/OP3kvcr+dP4xfjT+B/4PPUL9DX17/J48e/t7O1f643qPeqj6GDo9eTQ4xrjSOOd5ZTp6u8282P4+fwSAeIFmgkrDvkNfg5lDocPNxHYD+sP9A0oDl0NzQ1hDkIMVwtcCFkGWQEV/uH7Ffmm93H0R/Ti8tXz8vTN9eL2YPcP+fD5NPsL/NL8cP0I/m7/DAHWA44GpQlGDHcPcRLmFJQWRBZrFUcUbxPeEYMP9wwPCsEIPAgNCEoH5wVGBcoE/wPiApkAzP2x/GT9Svxz/Hr95v7LAL0CIgQ5AxMDKQNcA+kBswHUAH4AHQK/AtgC7QOsBSMFtgUFBOgCIgAJADD/nPzu+0v87PzR+6b8NP0J/SL9bP3V+4z6N/r7+Y74GPdk9of1tvXz9dn14/QI9OLzlfMc8m7wLO/I7XLsQuvK6ibq7up77Szw+vKM9sL5xPy+/v8AmAF/ASwBHgHJAHgBLQK8A60EGgbKBtIHiAekBowF8wPYAlwBg/88/vL8yfzK/Iv9cf4U//3/5QCmAUwCZwJtAuwBIAI1AnwC3AJfA2EEIQXrBZMGmwbXBtoGuQZXBvIFLwVLBAwE3gPiA7IDJgRlBLUEaQWZBegFmQWrBbUFhgWrBZQFxwXSBUUGUgfJBzUIWgiACFQIBAh+B1EGigXRBEsEwANeA/wCvwLdAgsD/gKuAnECCQKoAZcBQQHlAIkAtQAQAQYB/QDkAGsBtAFWAf0AhAA/ALj/Q/+o/vb9Uv3j/Gj87/tR+2z6Dfrq+Sf5nvjZ93z3QvfZ9t32Z/aa9tH2J/dG93b3eveM99D3v/eW91D3GfcS90b3bPe098b3Evhv+C35R/m3+VT60Ppu+5T7WPyq/PP8yf1+/lr/FgAcAQUCBwOVA+0DYwR8BI8EpARvBDAE+APHA8EDtAODA0YDZQNZAz4DyAKLAmcC8QG9AbUBpQGwAa4BCwJrAtQCIgN+AxYEiASmBO0ENwUIBQQFDQUrBUQFLAVlBZQF5QW/BZIFRQXLBHoELQTcA0gDyAKmAnUCaAIyAgUC9AH3Ad4BvwGYAW8BPwE4AS8BLAHCAIAAEADz/4P/If/S/qL+gf5X/mD+Nv62/Zv9h/1J/df8fvx0/Dz8K/xq/NT84fzs/CT9Gv0q/SD9KP0K/cv8kvyS/B38RPxB/Ev8DPwH/Cr8K/zv+8z70fvE+9f7sftm+zD7IPsj+/P65/r/+ir7UvuO+8777/v6+xX8Wfxd/E/8Mfwl/Pv7E/wo/Fb8avyV/KD8Lf1m/Ur9Uv2g/cH94v3//ST+p/5V/ob/eP9aAJEARQHUAQMCNwKdAsYC7gIEAzwDOAPzAi0DQQN3A3YDpQOlA4sDowOdA7UDxgN7A3sDggN8A1gDdQNmA2IDjgOBA1QDKAM/A+QCvgKjAk4CJgKYAW4BRwH8ABAB+AAUAQ4BHwExARAB+gAcAQQBzACVAKUAkwCrAHcAjwBKAGIAsQCwAGQAEQDz/yIAOQDK/2j//f7F/uL+Wv/j/r7+7v5H/4v/HACJ/87/CABCAJ7/pv+s/9b/Tv/+/wwAj/+w/3cAmwAkAA0AJADh/5X/NQD6/xH/BP8s/wgAa/+1/yQAEgCc/6//J/+e/5f/af8T/+T+Ef9v/4j/GP/G/6P/pP/2/ygAx/9y/6v/EQB+AHkA7wAbAD8AFQCrAAEBzwAUAWcAnwAgANYAOwFlAcABLAGtAfwBwgSFDewGRALKAkz+Bf9k/EsJ5//fAuEAmwGOAY/7dgRyAD8B6v8DAdcAMP1+/zwBuQPP/7QAx//g/Y/+dP+zA6gAsABX//L/Cv+E/6kB4P8a/979ev56/jr/Ov/i/0P//f3A/nP+Zv6p/5P+rv48/zP/6P3y/o//FwA2/7L+GgBY/QMAIP7wAB3+1QBK/tgABgApAAwAcADo/2b+fAB//18Buf96AA0Au/+X/zwA/f/y/08AdP9cAeL+SgGH/1IAPgGp/2sCcv56AXb/ywGm/5EAaQFw/8gA+P5HAsn+cwFy/50BHQD3/0sA7v+cAg3+bQEAAFIBDf+i/jb+pv3D/HAGEw78DlP/tARS/+P/hPoGCh8I5v4LBLQBbAbl9hcIp/8jBkD66wb7/w3/VwP9BDUGC/5pAIEAVgXgEMT//AHGAaH/IfcHAlIIsgFQ/qoCIf0OAxsGOgZf/mMD2v5LANf+RwvM/ssDqP1YAxkCVwrk/1gOZwnZDUj22A/3+6MI5/q5DzcA5vll/Yb7oPl8+nQF/AQ/AQv7Wgqv91gA+fjBCHT0QwQX/sME//mZAWQB0v+i/Rr8uP2U/gQIq//LAIf4V/4N/FoBSPZjAZb1KwaQ+UH+0Pna/FkDHPgn/un4yPu++an8Bfbo+lEA7AXCA4/5GP8o+rYDbfuhDZ4A5Reb+zgChfn/B84BgAeJAhb9cft++wr+6fj0+VH4gAut9J/64eaECND/3AbJ9RMFCfukBUX6EPnY9QYFDP+vCGX6SwBpAnECQAM79b4Aa/9fAC74BQAWBGkC2v18/4z3Bvra+RgAH/p+/6P89/5Q+2X55vlD+X79YP1Q+or9I/3w/gz/GAGX/Qv/+Pvk+RD+YAHeACgBYwRB/+n+tP/y/0b5Ovw7+WYAFQCjArn/PPwi+nr+MPdY+vn+bgDE/bIBMv3k/k4Ac/yl/iz8VgBo/2IDtgP+ARMAef6f+2/+lP9L/iwCHQGcA4v/1f0N/IX/xfwK+2n8G/9dAeIDNQJD/iz96fpb++77KwATBcYEMgWK/Rf9qv4h+/L77/tMAhEB1wdpAlT/Y/0c+I35Mfaj/KICLQDlAUD+U/+2+XH7d/gs9SH8WvrM/Kn+oQMrBGT9oPxb9/r0ZfU7/A/+XQCqApAAuP7Y+9f2kPYt9z/5WPjt/pMAxv/0/Qj90/jM9kP1Ffgn+Xr+jwAHAt0Dyf/O+9r6V/mX+T/8xP7rABEBhwK4AbH+M/8h/Pv8H/xe/wgCgwMhCBkI/QUMBjIDsQJjA+kFTgnFDKsPXQ5qDI0LuwhWCfwKXwzbDgUPxBArD/sLdguFCWQHAgdKBk8J5wluDGUKxQmSB2YG2QW6BbsHbQd7CJ0ISwdTBTgFNAQ1ArMBdAAjAVEAXf8GACQAGAC//sT9RPxi/P37Kv22+r36+/kl+wj5Lfgg+Tv4s/j69XT2DPcm9vj2t/Tz9lj0IvW68wj1EvWT8+jyV/Ay8Mju/e5L7Sfs1uto7LzpP+es5pTnPu1w72D1I/kD+xn9Ifsp/HT/0gTiCqIOaRTYET8T/xAyD04QMxGfEtwRoBHpDx4OqwsoCRIGlgRIAaf+gf1Z/BX92fxE/on+lf2u/eP6VPtm/QABRgekCnUO1hC8EGYRkxD+EdwVzBfoGT0a8xqWGVEW5BUME/4SNBGSEL4OzAwNDWUKLgrwCFkHcAaiBAcEPwQDBrYGdAYJB1kFHAM/AUgABwA3AX0C0ALjArIAlP8F/Tj9Ifxy/Nb8nfp9+/v3lPe09oP11fV49Nf1avKv8jrx8u+S7/bt3e4Q7WTvRuyZ7ADtWerw6gDnQuc15NvkJ+dr6P7xT/YY+xn+3/yy/sL7Zf1IACoHTA+MEiwWmRbDEjkPlguyCR8L6QvvDoQOogwLCtYF0gCt/Pb5Ufse+Y75Lfoa++T6Ofop+pj6WflM+iz7fv2Q/8kCGQcLCfEK9Q29D5EQfxJ+FPMXCBgUGdgZURk5GFEVPBVTE6IRRxB6DlwONAteCnoIYQb3BYwEawXYBLcFJwfvBhwHXQY4Bm8GJQQnBS4DpAMxAnsA1gDI/g3/J/3U+in7yPgF+tv3M/h7+BX3IPa887zzrPKo8frwpfHY8BTwD+487mnsO+yc69PrlusF7G/pN+lW5C/jhOHL4Kjjv+Vd7f/zzfc6/L38eP6U/bf8mAAaBT4LyBDuFCkYuBVPErEOVgpmCEkHqAg5CkEJ6AdRBY//m/oq9nD0NfND88n1u/dE+Hj4Gvhn+ET3Rvfw+Sf8Gf+JAcgEfQeUCEIKPgsvDUMQRxEPFZcVmRfKFykWyBWgE2gT9hGgEL4QqQ7NDTULLAnmBwgFDgXUA28E+wQzBb8GcQZRB04H9wbEBvsFFAYFBnMFvAXJBPsDJwI0AFL+R/ys+uD5q/lo+TX5m/j/95z2xPSG8+vxrPFO8NDwbu997w7uRO1O7KnrGetH66jqQ+rI6LfmhuRO4iPhYuKB4ynpOO9r9qD7cf8lAhICOwHWAA4EiAj2DSIUPRmxGwkZQhWyD2sK2wY6BSwHwgd4CM4HnAPU/QX3TPLK7nXtVu8W8/T1wPeu+AD5wveI9s33OPpm/QcBRQW9CMkKMQxhDW8OrQ/yEn0UYBdwGBcZLRnDFX0VABO5EYYQtg5nDxQMygpuCAEGUAXVAn4DMAPKA+MEBQXHBRoGzQZRB1cHCAiSCCwIUQd0Bs4FxgTkAsIByQBI/gv9tvn/+Kn2vPUJ9ZD0XfR28/3ysfAs7x/tGOws61rqOOvA6rbrI+r86AroXuU05IzhQeHW4BnhUOOq5V/sm/FB+Nb9iQHVBIAEfgQLBbYHQQvBEEgWqhu7HEEbyBaKEFMKlwSQAjYCHQMLBSEEYwHE+0f1je7+6Bnnr+j87Cvx4/UR+bj5Y/jH9sX2Cvh0+0sASgZrC/gO1xDCEfcRohPEEx8WDxiCGYsa+RcWFzgUUxGFDykNyw2FC3cKNAhLBUADNQCn/1L/hgAPAigDBgS+A70DtwJIAqwCFAS3BY4GmgeTB3sGEgQ1AiAApv7K/L77LPp6+Pj10/Os8drvFe+P7STumuxr7Abr/+i8517lp+SE5Mzjz+R95NPj+uJN4QPh6+Hq4wbr+fGZ+SkCSAbBC88J+QhACcoInQzKEBEYch5fIK0g1hzDFSwOnQbiAggBGwG1A1EE7QKY/yr50vKX6wbo0+d+6eHt4fLi9wH6f/pY+kj6Pfr++/z/8ARsCp4OJhN/FccXvBlhGQQcehvPHI4bGRmkGNwUbhP7EC8Q5w9mDXwM3AiDBrICrf/1/jr/xwBgAwAFjQZZBuoEAAMZAcAAlAHoAkcFBAcGCAkHrQRiAuD+UvxP+nz5bfkM+RX4sPYh9C7xne4j7EzrAOoQ6sXoSuid5ofkHuNx4dbgM+Bu33ngIuCc4ZTj0ulN7/v2Ev9rBbsK8Qp4C7QKLwpNC34PaRVtGy0g5yEdIDEaYhLvCa8D2v+B/+kBsgP0BFYDq/4L+AvwnuoZ55LniupI8A72BvpM/CD8QfsM+sf59/sjAPEFkwtAER8VxhjeGQUaKRuGGjEbqxkSGTsYzxVgFNoROhFSD68Nxwu8CEUGTwLo/1v+Kf6w/1kB2AMPBVMFTQT7AVcAxP6W/p//JwFdA30EBATRArf/ofyx+Q73Ovbr9V/27/a79rn19vP78NvuwutV6sXo1+dB6E7mLufb5FrkYeJR4Rzh5uBn4kTloeuI8MH3gP6VAzkInwcyCZgItghCCm0NVxMyF5EbwxxMHOMXqBFIC80FRAKMAMQBjgLhA/sC+f94+4P1vfDM7ADs++w68Xn18viV/Gz9W/7w/Af9Jv4KAKYDpgf2DKgRCRY7GOYa8RqVGicZoRbfFbcSxREYEOgPcQ/ZDQ0N+AnfB1QDfAAK/q78U/1Z/kkBHQPjBDkFKQTiAqEAQv+g/hH/gwAxAjkD1QP6AiQBff4q+/v4B/dU9mz2KvfD9633+/ZM9cryPfCc7eDrv+o56gnr0OrJ6sLqnekj6UPotumS7GfxC/aY/MwBUgVJB64GJgf1BcwG6QjrDAURPBTaFngWBBQhDzEKtQVaAv8AigGIAukCnAK6AHv9GPlx9dHyovGK8pf02ffY+dz7a/0e/U/9C/1V/iEAXQK8BUgJpA39D/4SQhW5FWIWdxS3E+IRPA/aDV8M8As1C6AKlQnQB2cF1gHf/qb8D/up+8D8E/+fAb0CwwNBAxQCVwD0/qb+Gv+SAM0B6gJCAxMCdgCd/ej6C/mu93/3Kvj0+EX52vgS95H0yPG87ujs4Ou463bsNu1u7UPtZuyd6nbqTer57ZLylfe0/kIDWAdVB8IGwAXiA1ME0wX5Cj8PAxOdFRwVBRJeDIUGsQEl/uT8Rf4PAMkBsQFaANL8Ifhj9Brx0vC68Qb1GfmD+yr+8P4K/yX+uv29/kYANAP9BoYM9Q8HE6sVFBYHFp4TNRJfEDAOdgxnCwQLBQqPCSgI9waLBI4B/P5x/Cb7P/of+7H8OP9NAX8CigPwAvEBjgCq/4n/GAAFAWQCVAMDAwAC3v9h/Xn6Kfjk9rH2YPcN+Nz4AviR9u7zjvDs7W7riuou6i/rruuu7GTsY+wU7U/upfIG9i78WgGQBUQI+AfbB3wGzQW8BmcJyQ2lEY4U4xUsFCoQPAqzBKEAi/2S/cj+5ADpAcsAyv5i+kP2cvKW8Cnx9fK19iD6Bf0S/yT/MP+Z/ub+fwABA3UI9gyyEdEVbBfgGPUW2RWOEzcRyw/JDa0N9wtBC6EJjAfmBYwCjgAP/jH8R/uz+nn7XfzZ/V7/mwC5AcYBpAEqAYQAbgA4AG4AIwFAAWMBfgAf/379JPvA+ZP4JPgL+BH48/e39jj1pfIq8HjtQ+s56ofph+kl6uPq3usn7XXvT/OP9jb7hv8pAzQFLQUSBr4FIQY1BzUKXg71EFgTmxNVEjoOJAkQBUUBE/+P/of/6ADZAOv/lf3q+T72r/Jn8Vbx9/IV9vL45Ps5/WT+Uf78/cP+AwEHBVAJHg+fEwwXWhjRF7gW8xPTEdcPPQ+WDhgOUA2nC7YJgwZ0A0EA5/0C/DH7E/ui+1H84/zO/W3+0P7N/jL/Af8k/wz/kv6P/gP+/P3m/Vv9Dv0L/Ab76/n5+HT4nveM98v2U/ZS9YfzDfL27mHtuOoy6broT+go6k7rDu9E8xv3XvvF/sEBwgLeAogDQgRXBW8H7wpCD6ERfhPaEyASzA66CZ4GYQMdAcIADAEjAiMB2v+a/SD6xvaP87XycfKM8zD2pvgA+1j8ZP0A/nD+FQCVA7kGzQs1EFEUqBbsFpYXlRXFFJISDhJTEcMPeA/3DNYLmAj7Bb4DDwENACf+3v1k/Un9NP3X/Fj9af28/Wb+0f4j/+L+H/6//dT8U/zX+5v77/tI+z/7svoS+sT5f/hL+DD3V/aX9S/0dPOH8c7vfu527JnrxOr/6lbs8u1g8tP1Y/qO/o4BHQRqA0QEBQTLBFEGzQg3DdMPSRIoE2USqw8PC1wHUwSrAfMA8AD1Ab8BgAA1/7H7zPgq9XTzDfPs8l714PZk+dL6mPsu/W/90gBuA/cGCwzsDowTDRSuFckVshSLFNwSWBN3EawQ1A6MDJ8KDwdBBdwChAFgALH/Qf+b/t39Gv2k/GX8hfwU/b79Sf6f/uv9QP1P/FT7fPpC+SP5xfhh+A/49/cZ+DX3JfdE9sj1OfTj8n7xq+/27WrsVes96n/qkeoE7AHud/Ge9VL49/yK/04CpwKEA3wF1QUYCEIKSQ59EHsRhhJQERUPNgtsCAwG4AOPAnkCcgJ5AcH/t/35+uX3tPUT9D30dfT49VL3HPiP+Qf6Rftv/AEAaQOcB30M3A8MFCwUmhVKFegUXxTaE2EUlBNDEyYRhA9PDBUJaAYKBNECiQFdAawAtACW/9n+I/5h/Wb9N/2a/cr92P0c/Wf8h/sy+iz5Jfj59533/fbA9n/2RfZa9Zb0GfTE8sPxFfD+7r7touvL6m7pU+l36YLqpewm8Kf0+/eP/Mz/uALIAzYEFwZjB/4IewtSDxgSrhMzFOwT6BEdDsEKRggrBhME+ANlA5IC/gCf/mD8G/nG9i31u/Tj9Oj1ifcd+Nj5d/rv+479jwCoBD4IGw3+DxsUuRQSFqYWRxbSFv8VxBZtFaQURhLSDzYNEAp7CAsGNgUHBEYDagJOAVMAR/+g/ij+Wv5u/qP+sv6Y/lf9Yvwt+8P5Hfn19zb4sPcu96T2KPav9T/0m/Nh8oLx+O8b7vDs5up46YjnsOZ65vXmwuil6sXv0fOC9xf8H/+CApIC/AMkBtQHCApuDCARLxMTFDMUshKAEOwLKQlOBwUFLgSeA4YD0QGE/wn9tPkJ93j02vPW83X0NvZc92f4c/lF+ob76PzLALQEwAgUDt8QgRVwFfwWVxeIFoMXKhZmF4wVBhWZEr0PmQ3RCWgIWQVxBC8DAAIgAbv/Vv88/pf9I/1B/Un9Gf0b/ez88/vq+uz5//gv+DH3+/Zj9qj1dfUy9b/0IPR088jyB/GZ753tBuwf6lbok+ct5gjnhuew6R3s9vDg9If46fyC/4MCAAJNBEAGwAhaC/QOlhOOFAcVVBN1Ec4NlQneB5YG+gV9BR4FFwQXAaT9yvls9lv0TfMW9Bv11faL+NX43/g++Z75oPqv/B0BqAZnCmEQlxPaFjAXCRfUF7QWTBeAFpoXtBbSFR0UCRHtDvkKjQinBQ8EzgLDAUsB0QDTAP7/Pv8A/1v+AP6j/ZH9Kf62/ZT93vwN/KD6vfii9w32y/W/9D71yvQ79MLz1fGu8FLuGe396sfpkehY55PmuOaK55npPexC8dH2wvnw/scAxgNNA3cEowcRCmgOOxHEFj4XeBYiFE0QMQ2YCJQHTwdIB1cH8wW+AzD/m/qh9iXzLfKG8lr0DfYT92D4x/fQ9tD2CfiI+Vj8wgCxBpULRw8sFNUVjhe6FmUXZxfwFtoXcxegGIwWoxVYEoEOJAvVBm0E4QGqATgBcQFPAeAA7P8b/t/8UfwD/Mb8J/6C/6UA4f/0/sb8aPrE98f18vRc9Oz0rPTx9GzzYPKF71LtC+t16azo9uZB57rl++Tv4zHkrOWN5/3rjfKV98H7IwCXAgUEZANQBqcJ/A05EdsV6hiZF7cVsRFxDnAKKgjKB7AHQQd+BfwCR/4/+W/1v/FK8O3wMfK/8wH0rPTJ9N/zx/Mt9fj3ZPoO/iMC9wWICtINkxGBFTwWuhj3F3gYTxj0F+AYoBeEGGgVtBP9Dj4LJggCBNcDgQKZA6sCwQKEAUv/y/3n+w39F/0l/0gBGgKvAn4Bof88/SH78vkB+XD4Nfjr99L2KPWh847xX+9e7fjrl+rR6WvonufQ5XLkLeIJ4u7hzePu52bsZPVk+Sr/cAIyBJUFhgQeCHwLMhEbFRsaixyxGnwXMBI9Dm0K+gjECLsJQAkxBx8D/fxl99Py8e/17jDxFPMk9XX1RvUU9TDznPOO9b/4h/y+AOUEQQicCnYO7xEwFEcYyhg/G3gZbxlPGc8XahinFroWxhIdEG0MkAghBsgDMAQkAzAD2AEIAVr/y/1v/nD+TwD7AZsDawSVA+wCqAEbAE7/xf6Q/sn9h/zd+i34Evb+88HyJvF/8EPvy+1E63rpxueI5eDj6OJE4RjhmeHS4tvm2enY8sf4wPynAZwCTQXSAhcGaApOEPoVWhkNHt4alBd7EQANBwqKCBoKjQkICp8GPAJ1+yT0GPFK7rDtqu9Y8lD07PMW89vyyfHl8fjzLvhU/JEAvgRtB0cJAwtqDFEQTRO4Fg0aSBmnGkgYxBeoFL8U6hPdEc4QqAxbDP8GMQWjAtcA///x/cr+uPzE/gH+fv89AAUAJwIdAekBHwJNA58D+gMUBBwDoAGo/gn9VPqy+Lb2VPZs9Zb02fLJ707tsen65+DlEuUC5frkx+MC4ejf5t/Z4BHk/OiO8hT6aP3xAVMCmwQzA+0FygvHEZAYlBrKHc4ZDxb6EMcLVgo0Cf0KRQk+CIsEZf+j+I7xZe9R7QLth+4M8drypPLJ8afxfPHY8Tv0xves/JwBhQa6CJ8K5QsNDK0MeQ+dFJgXIxvYGjAbIhicE3kSQA8qEPMNZA6jDCYJdQe7AjYBof0A/rr9q/3t/t7/jgGkAOYB+QGIAiUDJwTlBsQH/gjkCK8HegVCA7QByv+5/lH9Zvxl+hX4DPa881bxIO/V7QnroOrJ6NLnoead5JPj4uDb367fjONR5WHqu/AO+gT+1QCQA9EEIghsB1cOLBMdGc0bQxzLG0AW+BOxDtMMrAoPCwEKNgbgAr/9/vmr8tjv8O7q7ZTuOu8F8YzxrPFC8ejxx/LO9ZT5ov0ZAk4GyQlWCq0L2wyUDZoOrhBzFRkZXRk5GX0WPRNkD6oNKg0iDYkOJw1kC7AGtAOhAKD9Af0k/XL/Zv9KANIAQwFOAcgAIwKMAncEfwaMCBEKeApfCoYIvAZoBbQEAAQkA14CcgA7/aL50PZE9ATy6/Fo8CrwxOyG65Lp6uYQ56Pk1uX84p/jH+J34X/lmuUo6zLsBfTS+3z+GQP6AwsJrwg4C+cP7ROEGYsZaRtZGAYUhRGaDR0L/QiZCfEGVgPW/oL6M/dx8T3vqe5P7gzv1+8b8abxt/Ft8t/yBPWl+Mr8owFnBKYIzAqOCwwMdgyXDokPpxHtEkoWLhfcFZoTrQ9HDiIMNQy5C1YMkAwiCfIG0gJqATv/uv7q/oz/oQHhAIoBOAGzAUgCUgKlA68ECweuCOsJZQpmCjUKXwhVB6MGjgZaBhUFfAPnAK39APrw9iT1nvSz9KjzYPJQ8IbtPu386djqN+od6tDpbuhq5+/lRuSv5KTiPuia6C3tH/JG+GMAeP9LBGEC9Qd3CB0NiBMrFm0b3ResGCATGxG6D1YNLgxPCr8JSgYBAjP9yfkL9o7yafAL8MbwJvGt8VDx7vHn8fXycPR+92P7af9VA3QFBQi0CbwKHQyODPgO8Q8MEX8RWRIcFPQS/BCnDkINmAwwDHoM2ApQC4wINQbWAzACYQKQAakBQgB8Af4A3QDKAJwAUwJLAvYDLgV7BlMI4gg6CcQIqQhwCNMHEwigBzII2Ad7BSoD9f8r/Uf6q/hl9+32Vfe39Yf0lfEX7zPtburr7I/pG+z26mzmoukp46fnV+H44rrg+d5W6WnjIvHe7/H7OfxN/JX/Mv8pCVsHTRLeEq4YxhmtFgMY6BEAFBwQDxDCDWMMAAzHBjsDZPw6+Zb05vIn8D/w7/Cl7/fv0O1z73ruFPAM8sz0Afk4/EMB6QH7BMwF2wcSCqYKOw53Do0RHRCNENERbhGyEbEOTQ56DAQNkAyXC6ALawiiB+gEogMxAvYBxwEjAOn/av9VAK8AigAPARIB+wEvA18EEAbaB2kI6AjoCDcJiwkDCvIJlAmSCUYJgAjIBiwEJwHk/cn7L/oG+QL41/Yl9Sfywe/P7Trt5uq47Rjqyets6qLmTulH45DlMOLl43TkUd705Zbgh+u56PnvJ/em+83+6v7IBEgGcQxAEOQT/RinGd8b2hr0GEwXuBULFNwQJRA8DE8LzQZTARL8fvgc9rfy3vH27wjxne797orune6Y71vxavQH9iD7Kf1+AT8DwQRwB7MIxgxXDfIPlxCREasReREvFPYSWRRvElUR1hGSD70RcA2lDbIJ3QhrCMAFxgYsA4AD3QA/AFQA6v/pAV4BZwJpAgEEIQUCBsoHdQe9CM8JeQvQCzYMbQyvC+gLrgoVCpkI3AY2BUoDfQDQ/oT8EPpU+Av2lPPB8eTvQvC47g3uK+u96pTrFuqT6t/ojubr6AHkXuuQ5G/q/uJs5iLk5ePW6SDqVe4b8ij5Kv5M/nwCzwClB+kIxw7/ElUTjRd/FrAXzRM8FEsRTg/YDi8MOgvVCJUG4wF0/er5b/gl92n0LPUN8/bxBPL28evxmvE/9NH0Rfex+ZT8Lv4FALkB8AJPBeYHFgv5CykNtA6HDskQFRLgEu4S2BK/EqsT+BKjE2UQMBB1DBYNLwwKCjcKfwaNBgsEywOFAxYC+AKvAUsDPgMtBawEuQSNBVAFIAfdBxEJ7gh4COIIAAgqCHsHxAa/BfcEEwSJA8MB2/8C/df6Jvod+Lz3PfZp9XPzG/LU8eLwNPEC78Huz+xI7PjsHOt17DznX+o/6uPmj+yZ4knraODR6Ing5eOW6VHne/D380H4jfkE90j+lP1HBDAFaQthD+INfRR+EjsTDBAeESQP9RAcEcgPlg7SCqUI7QMrAb3/kP6++zP6BPxw+DT34PWA82zyK/Lo9CL2fvj0+PT6gPpJ/Kf+qv5AAhYEbgh3Cc0MSQ/6DqESYRBGFDUSjxX3FtUXyBglFnsWnREdEzQQvQ8GDsoM6wzpCPcJUAZHBX8DmAPhA74C/AQZA6MErwN5BF0EcwTVBUcGmweXBwAJwQeMB0cHXQZ0Bq4FcwXRA08DZQHu/47/hvwh/KX5BPgF+Gb2Q/Ub9HbzrfGo8MTwIe/P7d3s+epz7RTpT+6y6N7sc+jR6jPo6udc6dzjAOi4407jG+QM54fqR+6a8bvyhfSc9aj6BfzGAD8APwd9B00LvQ+RDu8OoA2AD1APthAnEZoPeg4vDJsL7AcYBfMC7ADC/nv+eP4a/B36x/jp9iH1evWG9b31wfZr9+X50PpM/Er96PyE/+r/QwS1BSUIwgttCl8OPQ/pDh4RjhHqFDkU7xa2FcUVnhQcEkUTBhALEHAOKQ4bDGQLLwnEBtMG2ASBBNUDjgT0A8sDKQNXAzoD/wHDAuECXgMRBNsEYQXUBJgFhgQIBFwDzAJPAgABqADh/2P/2f5e/PX4+/kO+T35fPaH9zn1cflg88r0kPOU78bznPFW86zuIvNM8FXrjPTX5zHwPOh48KrpSex/6jDqjunV5sXpRuPB6cnl4fCH7DL13fEP9b35zvaX/VD7wQBfAUgG2Qm0CeIMHQr7C10McQyhDUANgw5FDW0N8guiCtkJTQZDBooE/QSpAwgEAgPDAGcAmP08/sL8TfxN/B39TP5n/dH/pv2v/h3/JP/QATcDVQVzBqwIsAmRC8gM2Q2HDyARrRHNEncU7RLwEz0SARISEcQPKQ9EDb0MLgq0CqsI+gcoB8YGYgdmB30JDwfeB2EHfQHyBLsG8ALbCjYBVgebA1AFRv/6CEQDMwL8/a4F2v3TAjf9TQFsArv7cAGy/IP/cvdVAKH1jv+//ir09flW94n3Gvjw8rT6PfId9yrunfgU8c3v8/Ad8L7y+u6p73nt2/GO69PwxeuD8hvt9uwn7pDsg/Fp6C7yPus/8m/zIfSP99z3/viO93P9y/2//n/9oAHdBN0FfwfZB8oIKwffCG8KtQqcCMQI4whhCQcJWAZ4BJgCTwLIALIA1wDd/iX+xf21/SD/UPxJ/NH9Iv5V/kv+dgFh/xAD2QEuAm8HewFvBx8EWAr7BqEKUQthCaYN8QnLDPkNmQv/DBkN6gs3DNELCQx1CLkLnwq0B+oJZAnBBwcHaAaFAjkOLQRV/9ASfvhnCuQCbgMPB0X4QBJx+J/9/RV86bcVCu8ODuH91PU+F2npmAk5+YUCkwO08FYPD+9ABxX3Q/6ABCftkwb/9GsB3vUS9tAAJO2OAEL5+fM9+fr8he6M/FL4gPtA6vUFjvSo8ST8dfgT9O/30PqV8lr6I/lq9PD0FPzT86nyivpv8iv0pfUr81b3ZfNj+cb0l/vh+rP3b/vw/eL7ifzo/qAAnv6ZAL4DqP/2BEsCmwMZBFAEZgL5AkkE8ga3AhQETwf+AgkBhAeQArkEOgKrBt0BEQLKB+IA/gPrBEQGAQE9B3EDngK8BK8IXQJpBSsNVP2lDNEIRAD5D+z/Rg6iBVMJjAsbBTkK2gjKCEwCzA7/Ben+5RB5Ad3+BhPd/AYFtg19/IMCuQ2K90EF9wqH+wwD8Ape/Hj5hRsM5NETVwNb+kYDewn48QsMb/nc/m0KVvKV/wAMDfIIBiIIQO5CEgPxTgRg+8sBkf9d9PcIC/u7/q32pwX7/G7ysAfW/G31wPqzBxzyMvmBDH3n3QBAAjPyHv9x9/P9qvdx9AMIvvS88iQIyvAR9KIPcucb/VIDs+4U+QED7fS4+qj4Tvr/+U389voN+R39nfpA/O33fANJ9MX6tQVa9REAkv2mAjb4mgb6+vsGIf2y+yAOa/jxBikC/AX9/uQCVgsD+TEL7v8SCtT6wglVCyH2zww1BOT9gQN6DcXw/x474OMoj+I0EzQGt/JJEp3+/fpuDo/4KQtW+psHuwTD99cTPe4QGS7r7hoX8vUFzRE46IshROYQIebmTx1q780J/AWY9a0ZYt/WKnniuxHX/k8D7QDM9xsbXNjTLhjeRBUF97YLNO7uGPXsFwHHDBzrVRTc8OEM1fdNBrT4Dw4R8T8EwAac9EYAxwzc8coB5QoK7iwI8QZs680LmP/680kKQPlO/UIGdPReAR0FYfJmAYgC9fHOCKz68fNxDCvyh//tAd/3Xwky8DwGs/1C/GH4NAx27MMGFv14Adr1TBeP8Fr9WQyx83/9Vwa3ARnsEBiA7PkG6QQu+loCg/5qAV8ArQIT9WcQfPDpBO8DSP0P9k4VfObrFEz5RwE/+VEPi/BWBJILbOuLEQv4ZABwAz4APABf+3gHGPgLDWzumxJS96j91wgf/Db9yADWBBnx4xca6S8SQvpB/VoGg/9z/WkEz/13/IUIlv3p/NYIyv02/jAHHP0M/agK8vb0Bn78fgd8+SoDPP9mBEH3IwiQ/WcC/PwWB+z5CQQHASn7rQbj+YgDcvz1A/f8tQFaAJn9gwPQ/IsCMfniB1X4dAIT/8L/gART8roO6Prr+FUHLP4Q+sADWQDW+Z0D2QEL9tMJk/tX/9388wLZAbn3ewg4+4UAmv/iACP7fwiE+kn6HA3H9IIGhvvpA+f93P+O/pUFOPzm/toDW/wgA4f7OwRk/PcDb/jJDBDxYwqn/Tn+bvvfCbX17AKkAbP+O/43BXX47AaT+Q0CU//W/nIFOPc0CHz8gP/Z/gABCP/4APr93v/GBPj42gTM/xT+KAC8Aff7kANeAIb64AZX/AIBqv/5/8T/EQD2/7oBb/wNBFv/tvsjCJv7if6IBIL9VgH6+6MH3PawCY74MwQGA0f4qwha/TL+sP+yBkn0iArz/Or5SAzi9fEGkv+l/a4DQvww/xoE0f9d++YIrfWVCjb5ggFHAoD/A/x0BtH+S/yVBQf95P/B/IYIFfUnB58BCP+E+5wGb/0v/4z+CQSZ/DT9qAii9pcHVfxOAHAAlPx5CAX0owou+NcDk/99/+f84Qdc92kFzvu6Ban+CPomC3jzMQeD+7gD+/wIAYwBIv71ATD/WAGC+7AFd/saAk7/DAGgALL8RAXD++ICVP7U/9YDx/hGCNf6qAAKA9D7PACpAn371AOw/p4BGv8LADUD+/o+AnIEv/TvDG/31QOf/qL/u/8jANL/3QFa/V0CUv5VAtf7dgRf+zkEYPuyBfX4BAl39o8GvvyXAUT8iQSK/d3//AIp/EQC2gB0+jcFTfw1/vMD6P3u/uQEEf2dAj8A2fywAvP9JAAM/XEETfyg/1wBXgGB+oUEgABW+q0FCAAJ+u8Edfyn/6cBcP/Y+6kHr/kUA9EA0/zjAQYBKP1XAaUBXvnEB6b65f8zBQz6SwR4/YT/fAEn/WkA+QL0+yQCbf7B/gwHDvXTCl73mACoAAgCZ/2mA3UAjP7b/4ECP/q8AZYEHvijBUcAcP5uApAAQPvgBR0As/WLDp71ugOjBZP4hQM+BUX1lwq1/Oz7Lga/At72rwkd/rH5Ngeh/g35lQcP/7f7ogjR98YD4fy1AuD7GAVB+8kBrgND+TYHEP8d+vkGxf0W+J4OxPPCBFoB+QFK9RQST/BoBSQEVviMA50AOf42A7D+Gv9dAX0C5/c6CsL1Ewop9oEJKPjBB8b5OQbn/E4Cwfd/DUnxagwi+dUBCwXp9HkLDPW0Bb8Dhfa2ChX5wwKhACv97QNB/AcAKgMw/bb9gAi880cKs/p3Axj58QiH9iQE8gIy+gwDaQGI+yoFivmABBv9cgEH/uoB1wC3AKv9wv43AQL9VwDDA0X9NwFy/mgDifo6AbsE8/bJBxv/J/wgA30ED/X9Cy/zXApy+UYBAQRs+woBdgXP9qcJHfmaAY7+Rf/jAQX8VgVk/zr+JwJH/iX/vf87AJgCm/tiBIj/hv4YAaL+DgD8/w392gTX+X0H7filBc/7jAGaACf/xgLS+h8DXgGk+QcLY/ph/SIEBwBB+zAIw/ZiCMH6bAFhAsX7igSP+jwDWP1iAuL/zP04BN35dv5+Cq/v9Q8m9OwIw/o+AuX7Cggl97kFdfyM/08FHvsQAEIEofqWAVMFOPRfCqj69v2FAjQBbP4O/zMEJPpB/gIFavokCNP0DQ378ywGTv87/cD/UAIFAcj82QSC/4X8aQOD/Hz6vwjR+EgDtwQu/d3+WgFaANz6tQMQ/5kAVf8cAiAAbf9eAQj/jwGq/50AJf+ZAukCyPZlDorvWQyZ+DcD9P26B3H5UAFxBrn01Q0D+R3+mwNPANn69gro9bcG5/unB8D4iAkb+OwG+/mCBLT9/AWj+34Fg/0hAVr/WQHEASj9qgQn/mP8Nwbc+rsEoP7I//4EkPWPDEz82f79ATf/zPq/B+f+Lv0BB1/5OwVu/2L+1AIe/Ob8Ngnl8/sMRvrJ/YUFvPY0Cqf31gKAA/X2pQYcAGL4rwXRAib3XAOxBkL0Tgmk/dj92gCs/0f+nwGF/dQC1f1nAJgCU/t6Bw3z7Qug+f39XAaT/ib7IQEfA9n3bgmc/nX3KgtL/BP40Qvu+2z4LgmL+RsBOAdR+XIFZQBF+7r/aAmF9rYIxv37/TwGtPzP/UAErP84/IcBOwO8/EYFxftK/lP/UQCt/awACAIk/bH+NgX5/SX+ggMS/yYDa/s6BNEAJPqdBpX+CfuEBf75jf/FBQr34AN5ATn6Egc6/u/3wgsJ+DcBMQLp/OMAHv4o/20B9PuaAZYBSfpkCMj2OQcj+LQK6fSGBU4De/b5Bl/9jfvpB2j+z/dGC976lfrrBIb4EwkB92gGTP7+/IwEi/vK/cYGOvykADoDmfpyBHf8sP/VAeQASvssB7v43QHm/hn/0f8u/mkAP/7KAKABuPvbA/v8dv9+BcD36wfM/tX8cgOjA+T9rP9LAo//BQCiAUv8AgcP/U0AQQFMAqf+MwAiAJ8BD/9m/XAFV/9v/vICuPpJAgwBk/wtBLz8rwS1/kb9zQOR/jP7GQZG/VcD9wE7+lgHVvstAsz+uv/jBUT6tgQM/20Ck/0hA4z8lwM+/XgDcQBYACcCA/pOBvT4dgdB+lIEsP9m/dABRwHn/7D9WAao+80Cn/6qAOD+BwKt/z3/i/xOBST9XQBdBHf5AgVJ/bwA3QEO/l4Aof+P/sABwv5p/gQAFv4HABAAKP7DAVX/lvtzBAD90AIS+5kCwf+W+3kB5/80AVb/aQGJ/S3/sf/6ACH/pP7dAI4AZv9/AKUBK/5B/KkE7flKBAD/Rv4DAVf9wf/++8gCcv7p/NEAwv4Z+ykCrf5K/fj7xQHt+/L+VgP8+uoAo/sR/q0A5fyQ/y/9DP9p/jb9h/0LADv8APvn/sr9wvxU/2/71/4b/Yz5bAFG+rcBj/pc///9yf6A/rT9EADo/SUA8/9bArMBTwFnAD8CKAEMA4MC6gLtAoQC+QKRAjsCqwNYAaMCpAOmA/MBfAPkAjIBfgJVAT4ECQLCAkID9gJe/6wFPwAYAs8C/wIMAW0AbgQi/5kCaAGwAPUBdwEFA7j/VAOBAIMBzwF7AGgC9wHTA6oAKv+CBMz6bgV3/0gBKP36AiD8ov1OAln5yv15/5X7uf3Z/yb75v6L+V/8kPyp+Az+gfvd+mX+nfjD+ej4xfou+n36Afxt92X4+veT+I/4YPrx94j46Pf29zL7NflZ/XT5vf+1+5r+0v8N/+QCewFPBnIECgahBlgH0gcYCH0IRwlTCPcJPweyCO8GKQd6BggFOwZ6BE0DPAONAocAdgF5/0sAvP9O/2b/pv4g/9j+1f4f/zn/dQCK/7IBfgFuAWIBUgLvAkoEugSqBFUFqgVdBnEGZAiGBnwHcgfdBv8I2gaSB8wGQwb0BjYFTQbjBcYClQQKA54CBAPZAB8CQgCtAN8AFP/rAAX+Rv+Q/nz/JP4W/+P8hP7y/YoAhADV/RQBC/0CAdf/3QFoAE0B9//FAmj/2QM2AA8BEQHC/8sBTf73AOD/cvws/5z8vv3W+tT8mvtk957+Mfea+kj74/W8+s32V/nu98H1KPgP9Z72LPiG8hH3wfP18333lPeK+RP2+/kE9w35L/uI+y/+3/1lAIX/BgNQAYQClQOXBLIFIwaLB/AFrwVbBn0EnwY6BegFCAWBA+ADaAF1AlsBvAEIAbwA2f+BADb/vf+H/7n/iwETAZgBqgL9AQgDaAMMBbkF4gYvCPAGnAkHCM0JmQnGCnwJ5gr3CaUJ2QlOCCIInAZlB6cFIAZIBHEC6ABBAAQAUP84AGT90fy0/Lv6V/yF+5z7sfru+cv5BvpO++b5wPoq+o74Mful+ML5CvpE9+/4hffY+JL26/Z49PjzVvWv8HT30+xt8vTqxe2l7lX6p/ir8Ef2dutR+K326gDMAgL+ugIm/ZUGkwVXBz4KUwqfDjUNDA/WC8wMsQuICokQWw+eDh4IpgjPAg4FqAfZBN8FpAB0/qj7TfsC/HP64vqx+Yv6E/kp96D3MPbl91v6gPy8/HX8BvtI+lT8Sf7SAesBNgRFBO8C6QO/BLgGyAfZCasJ7Ao8DAILgAkkC7QJdAzkDcAMDgzLCY0HEwgfCV4KhwevBlYFCAPLAgQD4QGqAjsBOQADAFT/iP5n/Q3+qf7x/mn/vv8M/6/9WP/G/hEBYQGgAwYAigOMAPcBsgNyArkEsAPTBIkB/wLcAqD+zgNp/twBzf8J/VP8Z/y8+En76vjE9+L3d/R/9XjyW/FA8UHsA/IR7antU+yl6ODn5+nj43rlhvLdAg/o4fEy5ynwIvwm/c0I1v6dA+P9/AMHCwkJrhCND5ESKxF5EvkLjxDiEIAMMxSgEqcThwbYBGgC0wJBC+ACrQTk/XH4JPgp9GL5wfd8+BP20/Ob9Hfvn/HO8/H09PfV+c74yfg494T3UPs5ADEF/gXEBoIFrAZsB70KsRLhED0TIhHEEA8RCRC5EikRBhRcEnwOXA5DCtkIPQeECGQHggZhAy/+Df2p/N/7Jf3Y/vP7TPoO+dv3Z/k3+zP8J/7O/T3+dvwL/mkA6v9wA74DogRjBd0ClgOnAyUEHgaZBeYFugAvAM7+H/2KAcX8EPvo/MnuMviz7YLxK/IO61/sdeQg5TTgkuHO53v/P+ax5THkx+JS+1HuJgPY+Lv8eQBj99IJ0gPaD5QP3w/xFEYTzxF2EAoUCxPZGbkYyxiZDqQIKwzmBr4RZglgCAoGp/qN/ar0LPuf+mj4x/aY8drzb+5y7j7xxvFn9pT1ZvUp9PPzKPWZ91v88QA1AQEB5gF0ASMF6QVHDGwPGBAyD48OYQ7FD3cSOBMoFHYUDxOxDSUPNw3FC14O4AuDChEIBQQaATP/FAElAOr/v/4Q+3b67/gd9xv8pPnC/TX5qf1m+VD6XP8I/doC+f8gA1cCmQL9AiIC4QcUBiIJbwZfBOMEiQNOBEQFBAMDAwsAGgA0/Pn67Ppx93X6JvTx9RjvouxV8Qjmhu8K6ZXloOsO3MnnWtik5Vbsx/1Y4znoROGw8K35Pfh8ByD7TQXc/Sz9Wg/tCioYmg6XEe4WVhG9EzwO0xPxEjMX9RTAETgIXAeNBDIEkQrBAm4DL/we9YH1cfLS9wz1DPSn8ffuyO+y63fuoe+c9Mj0W/j69IP1xfX49gb94gGRBR4FoQPDBK4FjQlWCyURjBNWEugPBQ8kESgSjxP5EsISsRU9Dv4M7QoTChENjgmVCsYFvQPw/+n7sP7t/V/+mP2o+fD2bPap9O/32vfn+/D5v/nh+nn2H/30/V8BEAOXA6IF6gF7BcUEHglGCS0LKgxECnUINgcdB3QFFAh6BocHbQNY/KEBLvhI/kT47vuc9gD6T++F7N3y3umL83ntAemz7r3f7ekJ5Mvnuuor3fXtX/VD+kfqOOs07EH/8vvmBQ4J9gPmCBz94QsHEqsToxpJDsUXtRLgEvgQpw8GFlES0xOsD6sI+APkAc3+KwOUAuYAZf3x8ijxhO0q8uz0qfIL9FPwcO+n7a7tfvPi9sL53/mp/Bn7Q/sv/eMACgU1C18KTArxCkQKMgxuD8YT7BOqE9gRshEFEkIQwxLFDlASgw36DpMK+wdXBRoDkwbjApEEMf1b/Sz5Dfjt+cD4jfpi+Dz3A/cs9Q77xPQ+/ef45/6T/f39zP9f/0YC3QOyB5oHHgrEBasKMAY9C8MJnAr5DcYGYApkBFMF8ASkAfAFeQFU/3z/9/bZ/bfz1Pdv96fxM/yD6UT2nukK7XD0cOdd9uXk3e+95SPr++3E5e/ueOFz6yr0eAlH7Rj2++mj/AUDYwC5EpAEzxCRAVwDBRh3DGcecQ52EwMVpRDdD48LlQyMC6oNUQqdCLD/g/6998T0wPwA+JH/H/Ke7intJeyy82Tv6PZp9Ez0YPWF7zn5p/kl/nYA0APXBSgE6wXMBYwJQQwCD+oQcBGGD1wOwAwtDvUTeg7rEvsOQQ20C6UIxgq3BTsKTwSwBXMC+f7z/k/7nf23+k39n/xj+C35Svbt92z63/ow/BT+8fyh/PX9B/6tA7MCrgUbBIQHRwVwCc0IlAc8C1oJCg3kCpsJ8wogBcQK7ARyChIHFAScA0//If8+/RH9R/07++n7s/YC9h32bPQ99RH1+/Ni84zyevGk8+nzBvP+8D/ysPCR75Tzvu3y9GHstvLW50fwFuvjCcMAVfRf96rp9gp08mEUDAdkDnQNOfnmDCQKPA7lFTMJiRPzDboLeAfrBgUDRgrKAwIKWABL/oz9/u+g+RnyF/8S/JX1vvaP7mv1+PAx+IH9bfzc/qD5MPwk/8IARwKaB4sJIwv3C+8Ipws8BmQNWwppDzkPDgsrDpoETwfjCNwF+QlaBikFrQKWAuX9E/+lAygBfAHUAED+cv8n/ff8av1mAcMAGADMAkv/4P4HAc0AYwOIBRYEhwWFA8wCGwMABQ0F0wbSBPsGQgTnBUwC9gWzAp0E6AK7A5gD2ADBABv/WACA/jj/T/4s/1z7Wf1a+YP5TvrC+jr6PfoI99z3iveE+JD2YPiG9tz3bPTj+hzx2/kY7iT4ZO8O9TjwMu/P7pHpAevE5LPo8PS5CKTyVvhz5wL4FvYv/5oNMgz7EqwFOwAuEL4Egho/D4kUvRFsEskOMwzTA2cH5QPuBhAEwgICBhb4mfL68KfyMPze9w779Pfo8+ry4PB6+X76/QCIAq4BFQL0BDwFagdECBEL1A5fD+YQ+g29Da8K3QftCJ8Jpg2yCW4GGQR0/Y3/9PzO/rT9FP8O/eL7O/uL+139TP9O/3YA0AKpAg0DwQQDA6EHGgbnClUIWgvNCiUJHgsZBoQKKgiGCegI1AUqBw0CyQQ5AgsDpwNuAOUCeP/LASr/ogDU/8P/7AC+ASUBoAGk/ykBxP90AIUBjAC/Ak3+IP9n/Qb9y/7x/Cn+IvxO+QH6Ovhj+YH5IPiV9Mn1wvLl8tPwxfIi7FbyH+vW77rs/uij5BHkeuW75Nn6Xgki+HAAievx+4r1tgaRD4kaHxt6DY4P2Ay4CIoWihPpEuUR/hE1DkwGNgDS/Hz6F/bT9VP6ff6v8gHzqOk06XLrZ/Gz9oH69Pw8+4T71/vA/P8FqgjWCroP+xJYE0QRZRBeDbEMeQzVDaIO+g4YCV4GT/2V+Yf6efkS+9P4Bvko92L0i/RP81f2lvfa++v+mwJABYsIJQmQCisKOQ0gDrwRhxMgE4MTcA4GD6gJlAiRCB4G0gazApoC3fx9+wD5zfa0+cP3Sfsg+1n8wvsf/BX+6/xlAZkDEwbRCBgIcQjzB0MH5QYxB1II/wY+B08FkQHxAFX8yvvD+Wn37ffJ9SH2tfSc8+7y8u9K8IfvUe7m8i7xDvic8YH0QO7x8NLtTPD68eD0gO/W8N3oh+qF5Xb5jAM7BqcEf/8I/6r6m/6+B8QRkxbME3gTCg0xCowMxQvHBgAFrwj5BDoFbgGjAWr8fvM479Tt8fOA9uj8pv1i+RP5qvaV9w36HgGfB2AKWAyyDFUO9w5gDXYM5wx4C+YMYA7NDRYNEApvBEH9GPl8+HX54vu2+wj9I/o993P0yvQz9t75Mf5GAd4DHAf3CZMKsgugDEkNIQ9KEXETphRUFLUQhAvjCLMDdwSaA9YCeQLGAIf9PPp5+DL3Y/cO+SL6v/zc/rwBagJPBHMEwgQJB+4HBwsFDWQOxw5PDAoLngf0BgIFRgSRAzcBAADh/GD7z/gS96T1e/MN8wTyGPP687T0z/XD9Pn0qvIs8kT0f/Xl9jD6WvmF+jL39/ap80H0jPJM8sPzyPFX8VruROy56ZrwX/uW+/QB9wDWAF//T/72AR0F7AssDH0O3AxZC50MTA2TCU4GgQbAAPX+TP7n/goB2v8c/oj49Pb58tL0Ivd9+NL8BP+F/6b+3gA0AkgDCQWqBFkFcAblB6sJCwy8C+MKwQi/A3EBigAVAbIA/QC9/8r9jPz6+hD7l/v4+0v87/yc/Rv+yAEtA8MF6gfZCMsJvQnBClQKOQp1CpsJfwlACC0HXQZABUUD5wFSAND+JP59/a39y/1Q/sf+Ov+k/1AAQQGwAfQCMgRiBYcGWQeTB94H/gcaBxsHDgYcBVEEAQMDAvcANAC8/pL9ffwG+3b6h/ks+f/4Avi691/3Vvep9wz4GfgQ+A74QfcO96r2v/Z094b3c/eK9rn2kvW29Qn1iPRj9IvzNvLh8EzxyvMt+CX78v6eAfYCSwSQAx0EcAXNBgIHXQfjB88HBQk/CZQJ2QkFCSsH/QR7Ah4A1P6B/Sj8qvun+1T7ofsl/N/8sf1p/mz+Mf40/g3+dP5z/zQAzAH9Ar4DVAT8BF4FvgXEBQ4FNwQvAwUCQgH0ANsAJwGKARkBWQEwAT8BegFTAVYByADeAIkAqQBEAeUByAJdA40DqQO2A1wDEAOzAlEC/gHNAesB8gFnAskC7gJEA2ADtwMIBDgEhQS4BOwE9gTrBB8FKAWJBZwFcgWSBVQFQwUEBZIEJARxA6wC4AE8AckAYwBHAMj/RP/X/j7+4f16/ST96Pyj/Gr8Ovw4/Fb8YPyP/If8ePyq/JT8q/y2/Lv83vzc/NX8yvzO/KX8g/xC/CX8+fva+5P7PPsM+6r6dfpC+vD50flm+QX5oPg0+Bf4+Pcn+C34YPiW+NX4Pfma+Sb6jPoW+5X7Hvze/Fn9FP6c/ij/xv9tAEEBAgLIAmkDvQMkBGwEqQQUBS8FSwU6BScFEgUeBTcFOQVPBSwFAQXVBJcEYgQsBPADpANPAwQD2QK3Ap0CcwJFAh8C5wG4AYIBXwFBASUBAwHbALIAhwBnAGAAWQBoAJUArADYAOgABwFCAXIBwQEKAk0CkwK8AhcDTQOmA9ED9wMrBC4EdASRBLkEzgS6BKIEewRxBFgEZARgBCcE6gOEAykD4gK5Ao8CgQJoAi0C+AGUAUoBDAHcAM4AnwBzADgADwDl/8X/yf+n/5H/cv8y/yL/DP/s/u7+3P61/p7+jP51/nb+cv5e/lX+Uv44/iT+If4H/gD++/3v/ef9+f3q/fj9/v30/QT+C/4G/hj+If4m/iP+KP4t/kH+W/5j/oT+kf6T/pz+kf52/mX+Tv5E/kP+O/4t/if+Fv4A/uL91f2+/b79tP2a/aH9l/2d/a/9q/2w/bj9yP3R/ej9Bv4e/kb+VP51/on+q/7K/ur+Gf9B/3L/kP+u/9P/8f8fAEoAfwC0AOAADQEoAVsBhQG6Ad8BBAIfAkICZQKAApsCtQK1Ar4CrwKvArgCswKhApoCfwJqAlICPQIrAhEC6QHKAbUBoQGVAYABZAFCAS4BGQH+APUAxQClAIkAUQA7ACQACgDi/7f/kP9g/03/Kv8R//r+4P7M/tX+1P7b/uX+2/7e/tj+5v73/hH/KP80/z3/QP9K/13/Z/96/3L/Zv9Y/0j/RP9A/yz/J/8Q//v+9P7l/uH+1P7G/sD+r/6t/qj+qf6w/pr+mv6T/o7+l/6O/pL+j/57/oD+dP5k/lX+R/43/h7+FP4E/vr9+f3n/dv91v3B/br9vP3B/cn90v3j/fL9Bf4c/jX+XP55/p3+xP7o/hP/O/9x/6r/1v8FACYATQB6AKcA1AD8AB4BQAFeAXkBoQG+AeQBBgIgAi0CUAJqAn0CjwKQAo8ClwKcAqYCpQKXAoQCdQJlAk4CQAIrAhAC9wHXAbkBogGDAWwBWwE+ATUBHwEYAQ8B8wDrAOEA1gDYAM4AzADHALMAqwCaAJMAiwB4AHUAZABPADkAHwAXAP//8//w/+j/5v/n/9z/4v/g/93/8/8GAAwAIQAoADkAQABQAFIAUwBaAFYAVQBZAE0ASQBBADMAJAAYAAsA+P/s/9f/y//B/7T/rv+g/4z/gP92/3r/ef9v/2T/Xv9T/1D/Sv9M/0b/Pv81/zH/Lf8v/yv/If8c/wz/Cv8J/wr/DP8Q/wv/B/8H/wb/D/8X/xv/Kf8u/zf/Pv8//0n/Sf9H/0z/TP9R/1T/Wf9d/1j/W/9R/13/ZP9h/2X/Zv9n/2v/c/9y/3v/fv98/4L/hf+H/4z/mP+h/6f/qf+r/7L/sv+0/73/wf/F/8L/wP+6/7r/vP+9/8z/xf/D/8T/wv/D/9H/zf/X/9r/3v/d/+H/4v/l//T//P/7//r/+v/9//v////7/wAA+P/0/+//8f/0//X/+P/4//b/9P/3//j/+f/9/wYABgAHAAwADQAOABMAEAAdABsAHQAeAB0AFwAYABcAFQAOABEABwALAAUAAgAAAAcADQANAA4AEAATABgAFwAdACMAKAAtADEAMQAwACsAMAAzADEAMgAxACkAKAAnACYAJAAfACEAGwAWABQAEgAXABsAGQAYABMAFQAUABUAFgAUABIADwALAAsADAALABYAGQATAAgABQD+/wAABQAEAAMA+//7//3/AgAFAAMACAAJAAgACgAQAB0AIAAeABYAFAAZACEAKAAoACYAIQAfACsAKAArAC8AMAAqACUAIAAgACMAJgAjACMAHQAYAB0AHgAbABgAGAAWABMAFQAaAB0AHQAgABoAFAAPAAcADQAOAA0ABwABAAAA/P8AAAEABAAFAAEA+f/z//L/7P/5//v/+v/z/+3/6P/l/+n/7//x//H/8P/w//D/7//2//v//f8DAPv/AQAEAAkADgAMAAoADAARAA8AEAARAA8ADQAOAA4ACwAKAAoACwAQABEAEQASABIADgAQAA0ABQAMABEAEQAOAA0AAgD7//X/8//5//j/+P/4//T/7v/p/+z/8P/s/+n/7v/p/+z/7v/s//H/7v/v//P/8//3//n//P8CAPv/+f/1//f///8HAAgACQAJAAgABgAMAAkACgALABEAFgAPABMAEwAWABUAFAAXABkAIQAhACIAHAAWABgAGgAUABwAGwAhACEAHwAdABcAGAAUABMAEAAOAAQABwAKAAcAAQADAAIABAAGAAYABwAJAAwACQARAA4ABwAKABAAEQAPABcAEwAYABoAFgAXAB8AHgAjACMAHwAWABwALQAqACoAKwApAC0ALgA2ADoAQwBAAEAAPQA+ADYAPgBFADwAOAAuACsAKAApACcAKQAjABYAGQAaABkAFwAZABoAGgAXABsAFAAPAA8ADQAJAAgACgADAAoABwD8/wUADwAMABIADQALAAYACAADAAgACwAKAA8ADwAPAA4AEAAbABkAFgAXABUAEwAQAA0ADAAGAAQABQAEAAQA+v8AAAkABgAGAAcACAADAAAA//8BAAUACgAFAAEABAD+//3//P/1//T/8f/t/+//7v/q/+j/5P/j/+f/6f/r/+X/6//m/+X/5v/m/+b/6//s/+v/6v/w/+7/6//t/+j/6f/n/+z/6v/s/+3/7v/0//b/8//t/+v/5//r/+r/6//h/+j/6P/k/+X/4f/i/+b/5f/l/+f/6P/o/+n/4v/n/+T/5v/r/+r/7f/z//L/8//x/+3/7v/w/+v/7//v/+j/4//g/+f/7v/w//j/8f/w/+j/5f/p//D/+P/1//b/9f/1//j/AAD+/wIA+v/2//f/+f/4//j/+f/2/+3/6v/o/+j/8f/0//T/8P/u//P/9f/7/wEA/v/6//n/+P///wMAAwAKAA4ACAAHAP///v8AAPr/+//9//f/9//4//f/+P/3//b/BAD7//r/9//5////BAAQACAAIwAnACgAJQAlACIAIwAnACkAIQAmACQAIQArACUAKwArACwAKAAoACkAGAAzAEkAPAA/AEwASwBNAFIAUwBYAEAAPgBBADkANwAuAD8ASgAuACoALAAkACwAIgAZABEACQAAAP//AwD5/9j/8P8OAAUAEgARAA4ABwATABgAGwAfACkALAAyACIAGwAiADEAKQAbACEAKAAfACsAMgArACYALgA1AD4AOgAYADIAQQAnACYAKwAmAC0AJwAXABMAHgAbACIALAAVAO//BwApACAAOgApADAAIwAiAB4AEwAMABEA9f/1/+D/yP/j//v/3f/i/+n/6v/q/+//AAD2/wQAAAD2//v/8f/t//f/CgACAAgAGQAXACMAIQAxAC0AKwAWACMAGgAQAPL/8P/u//P/2//0/8//4P/W/9T/yf+6/7n/3P+u/8D/wf/z/+L/3v/I/7b/tv+7/7j/zP/F/8P/zf+//8P/zv+2/8j/1f/R/+b/3P/d/+X/3//H/+X/4v+7/5T/h/9m/4H/bf+D/4j/gf+Y/53/nP++/+H/AgAUACoAOABYACIAFAArADAAGQANABEA/P/2/97/1//3//X/HwAlACkASwA7AFgAlwBxAGkAWgB5AEcATQApACUA9//g/87/tf+n/5f/n//E/8X/w//T/9X/7v8CABkAJABiAHkAeQCFAJcAgQCtAL8A1QCdAGAAHAASAN//sf+h/2n/Iv/X/rT+n/6t/uP+KP/g/sf+0/+aDqAMtA7sBC8GDw2dEEQERwaB/oMA2P6A/vwBZADx+139NP11/GL6ZPt6+Lr7evsD+6H8Pfrp++f8tP2u/88APP9SBzILGQP5F9gCLxFuAu4I7AGwAOv/av3r/cT5UPy1+2X7DPzO+8z61/2N/CH+lAAJ/YUC8//V/6UCE/80AQj/bf8V/5v+9v57/kX+rv0k/i3/zfxA/yL/nv7G/mv/lf4yAZ/9lv83/rj9w/37/Dn9Ev2e/XT8cf/4/CcAh/7c///87P0S/8P9c/7F+9/9zfrx/M/9AP5F/qb+eAAT/8z/UP9x/kv94fqX/YD7Pfze+ev95fsU/pf/of3g/sD+UwFbAWf/6/6RAMkA8wCbAUv/lf/DAcP9MP/b/GD92P1j+En7sv0k/CL+ZPx3ACsADgHpAOECTAHXARUCnQBN/63/8f6T/fX8lv1i/6/9J/7oAFYCVv05AIsAF/9s/gMAr/5qACj+pwFnAVf+8wIpAZcCC/62Aez+egAx/8r/Yf15+67+w/+V/179zgCc/moBLACiAi0B4P+tAGkATQASAXgCcgF0/0r9fwP+/LAC6v4LAPH8bP+o/3MCqv54ALsBjP66AfgCBwOI/yAC5vyJAqf8BwNpAKr+mv0N/2oDfP8BAvP/9wErALIA4wGRAnYAKgNO/TEC7f1OAwcCbP3YAXP/SQKc/lUCVQHE/k8DtP9Z/7MApf/KAFf/c/8UArT+9v94AXkCOPxHAUACsv9pApT+hQEMAW7+zARcALgAugCWAQoA+gHSAYEA5f6IAhn8WgHQ/av/RgBo//MAPQBpAbP+ygMwAXj/GQG+Aab/8f9eAP0BMQE1AooAr/9vAM0BIgL0Ad/+ef2IAFMB9v+cAjP8rQDa/20AgAGQAYP/q/8lADoEuv32Ao7/qv8v/2L/6gGcAO8Agf/+AKICBgKoA57/MgRQ/rICbf6DAYH9zP37/EoBwfyw/bsCpf8B/6MB8f9KA6r/zACS/q3/kvylAn7/RQCK/eP+cP9pAwIAswLx/2gDOPx1/i//5AHMAvP9MPpq/tP/BwVABDb9Ef+6AP//mAJPAMH9xv/G/rP+6P9GA+z/ogNk/pz/xwJ4/lUBZwMJ/p79RPtb/4sAXwNA+yoDavw6/7cBvAKrA0H/KADjAor/MwJgATsA+PxX/FH89QA7/nIC2f/b/Xb7BgErAQ8GtP9i+5L7yP6KBRgEigGr/oL8sAIXBBID3ABo/TD7mP8j/Q8A/gAs+/D6L/7KAbYGKwMnAkj/Nv9lBCoGHgAN/AH/nvlw/lH9AgCR/Qn6Qf5ZA5wB/AQbAhkCtv9NA2UEvQM3/lv/bf4DADD9GQJY/C/+1/z5+0j+6vyN//r+tP07AtwCTAViBboDggUuARoISf93BLj9l/t++yn9Tv0h/j76tPtz/rUCJAFBBZwCpAIdA2cBPgNsAjEDVf9t/WL73AEV/yIAq/x4+o79+wNt/doDlwCnAG8B1AIdCG4Iuf8YAfsC+v4JAuQAWPvo+yH3kPkd/VL+jfxd/dL+gv68BdsF+gb5Be0BywIVCk4BygAjA/r7k/q++3j90P//+N77bP+0/dQALwSlBo79OQJDBD8JRv8SA5QAXgKd++0AIf7/AnT4Kv3T/pL/Y/0LA6EBI/+3/qsA7AMnBPQBUQFR/Zz+8gJEAEIBtPt1/B/9nv9u/vj/agBU/G/+qv9dBrEAJAEaAGEBFAOgAF0A/ALA/OP9vf3y/rT/hQIU/UT/hf4vADkFYwKe+2wBPAGlAfACRP9T/uT8svtvAIH8lP0p/2cAH/8LA+cDHQAIBhoCgAjBAucCIv++AVf9r/2q+9j6Qfi8/2T/vPlu/+wB2gFaA9IBVgNxA9n+0gGP//T9MQFR/Qj9oPv4AN8AzgL6/479DwCu/LABfgDm/5/78P1A/+YEVwH8AfoAkQFBAiYEm/6P/5v68/vr/vv7GP9o/d/9v/yJBSX/EgZwAToCYQE+/6ECHAN9/+z5Zf/r/mr+EgKvAH3/PQQdAVUDnQIVAa3/Jf9o+O4BAQG//E39Zf8a/dkCQAL6ALED8Pm7AkkEwfzqBFP+0/s1/t8FIAFdAQv+wf6lAQD+zQIiAI774PwAAHz+JgIq/vMATQDO/zUAZwi6/fL/9gFS/838Ev6YADICWPtk/VgBbP+eAQICQACq/boBgf65AAX/swMm/yL9Bv4EA34BswRl/2D/hPtIAskBOAKY+PL8Kv8g/m//wQTTAJ8AMPwoBdQDc/8oAYH+ovx++VoCTQCu/lP5mP+MAq0CvQP4A9oB1fx3ARACIwFO/WP9+/u4+/v7bP7v//D9V/yF/2/+CgVCAx4Dnf5eA5QA8QEmAMMBT/u7/mv9KQBU+xH9+/ol/Z/96v4g/9L+/P5UA10AvwBxAsAC9wGcAGIBxf9f/+n9b/8V/3f7jP0Q/bH8+Pwj/o39E/xZ/kQD0AFJ/cUBDwOu/yv/6QGN/s39jvu7/7//TP+6/mn+JP+5/xEClwCP/MX+Bf7l/Jz/u/uA/W/6hf6c/KMBkv83AkUAq/6yApMAIAKR/wX7H/7x/GT/S/1M+638if24/6QB8f8//4/8fP6+/VUBXP1S/7z9sf18/6IAVgGvAKD9pgAdAUT/Hf2K/Yf9sP3O/GD9KP/P/Q3+bAG6//gAiAH//1AAGf9o/iEA1v8J/t/9p/3t/g4Axf3y/97/gP9l/GIEhf8A/h0AoP+r//T90v12ACsAX/0X/eYAU/x0/1r+5P2P/n/++f/fAaX+fABlAtsCt/6ZAaP/XQHn+0P++gJH/HX7wwCrANL/9gHaAbkA+QD+/z0ES/+x/sr/nP71/yH+qv4h/iD/nv8OATQB0wA4/TsBKALT/uwBcf6PAFT+vf5gAXIDMfz9/vkCZQA2AP8AiwPvAGz9MAF+AYT9j/3nAXD+/P0dAV4BuADz/sr/FQPW//T+mv/s/8P9b/9LAD0Awf4Y/v4B6ADjAYgDdQG6/5ABGQIcAcQAPv4f/+D/PwBSABAAXACw/5IA+/6nAQYAzP4z/zgAZwHz/zkC5gCUAgICywCmA8wAQv+YAT8Azf5xAT0Adv9b/2YBPAMUAGf/JwE4/37+DgBIANX+xP+K/8UBo/+MAsoB9P99AHoB7P+6/yz/zP7w/YwAhgE6/+3+4wEUAhsA5wGSAsj9Zf4L/yf/nv1a/bb+Mf+1/lcB6wEyAAMCLANWAa8AWgDLABf/C/7I/U3+OP5y/Xv+Z/14AFf/bv82AXsAmgERATcAmv7kAGEAL/96/mT+jwAYAZf/ZQDAAJECTwC8AT4B3wBW/wMBmgBS/97+agCn/uH+pP+4AFcAGADT/8cBEQODAR8AFQGNADIA0QCGAXYAdP8mASoCFgPWAJECtgCCAC0CMQLHAF//ZP+RATYChwCtAaoCLgHMAeUCgwM7AeoAsQGFAX4AZQB2ALsA8gEvAwUDjwK8AuECCwTmA1ICvAD2AJkAIAFXAGAAjv+j/zECbQEiAeD/ff+DAIMAj/+x//X+K/1P/zEAWv+F/5j/MQAYACUBKAHW/8j+RgAj/m7+gv5l/hP9S/0s/xv/T//q/rn+eP+i/2L/4f9Y/tz+/f5i/pj+bP/2/m795P51/qn/Xv1Q/eL9t/zZ/an9vPyv/NL84PwH/af8U/0Y/c/8kv0A//j+av/2/9YAgAGkAhkCYwK5An0D+AOkA+UDZgT2BHAFlgbtBk8HaQiiCAgJiwn7CaoJEAnqCPMIigiwB/sHCgfXBjoH8QauBnMHzgdRB6kHGAfMBw0HLQb7BSIFaQQqA5MC4gDN/9f+zf3g/JL7zft0+yb7MPzp/Hr8Ff0k/VP9jf64/HT8d/wd+8r6/PoV+Yz5cfl3+PP45PkL+U/5Pfei93z45/Zb9j/17PPC87PyZ/Fu8Dzuqe1x7PPqR+vw7grxv/Uk+qIAMwiYDbAS5hYqGKkY0xb9EjoObggXART7ufWx8Q7wL+5d7nTwvfNr96z69v0bAXgDqgT+BYkGQwYaBhgGRwaTBkEHZAe1B70HqQf9BoYFGARZBJwDygKwAtACsgSSBkYILApcC5UMpQ2xDCgM9ApGCG4G4wRaAzIDcAIqA5YEdga2CKkKdAslDBEM8QoVCWgGzgN8AHn9LPvL+V/4gPeW95X3mvir+Qv6Xfr7+rX7DfsX+6T66/l8+Eb4ZfaK9fX0FfRh9ODyPfNs88PyRvFt8Ujwbe9w7s7tY+/v74zyHfee+lMAkgS6CfEODxLLEyoVCxMeEXAN5QeRA0b9K/ir9Gvwl++C79DvIfLh9FX4kvz5/kECOAXkBdQHiwhACGwI6gf5B9YHGQdRB+IGOQX3BKoDZwLoAOMAdAETAc0BhAOnBUYIcgrbDPwNLg7zDl0OrgxyCwoJsgZMBf8DLgTjA+ADxQV0B/8IzAqDC7ULaAs8Cp0IVwZxA/0AiP4//Ej7d/q4+fH5gPre+qf7U/v7+gD75fkd+cv3e/bX9Ur0xvJP8gfy+fGn8QLyavE08WTxNvHY7xHvJO6D7J/swe0l78DxlPVl+b//aAQ6CX0PlxEAFCwV3hIpEWENdgb2AZ37dvap8/nuEe7N7qbuN/Jj9Vn4QP23/4ECrAV0Bh0Ifgh0B1UI4wdyB6EH0QaiBi8GZwXYBM4DHgRPBPUDLgSWBN0FUQcvCJAJtAmaCSAK3AiACFYITAZrBboEiQSCBWAFOwbVB1UI7gkkCwgL2ArMCbAILAcVBRYDkgCx/fr7FPuz+fL4NPi890L3wvZj9s/1ZvWx9IL0HfTW9MX0ZfRx9GT02/Mi81XySPDa79ftr+yA66DpsOkM67/sKe/g82D5jv6ZBZYKPRCDFNoV/BYNFmYSAg92Ce4Baf3F9iLygO8Y7KDsNu4776Xziffp+qf/bQLQBQcJQAkJC4ELLwvqC0oLnAo3CjkJgQhfBxIFFgUTBvkEYwRWBb0F3QbjBzcIbQnMCAgJyAk+CCEIbAhlBgcGzgYdB3sHowfkCIAKNwtnDHcN8gzyCyELXglNB48FngLO/8P9/PvS+p35T/gH+L/2xfW99UT0OfNv8i3xO/HU8Zvxt/Gb8RPzOPOo8ufyHvEV8Bfuu+yF6ifpM+pl60ns9/JU+rT/TAcbDQMVrxmiGp0coBmcE1IPoQbU/mj40vDi7DXpKOg47FXt3/CF94X7wwCWBFgHjQpqCr4K2gukCkgLAQu4CX8K6wljCpsJrghwC7MK6ghZCRkILQjkBxIGYQcEBi4F6gZ0BWAHQQhNBkwH8wc2CFgJOwg9CXcKagpyDPQMbgz7DP0LXwr3CC0HnQQZARr+e/wC+p/3w/Vg9Czz1vG58YHxRvGz8TvygPJT82b04/ME883y4/Ap8G/tL+vN6hPokObu5mfk7OhW7f7ux/qE/wIHcxFoFC0baR/IGrIbrBRLCyAIlvsw9MHvl+dk58Pmm+Y/7eruHvRr+1n+5gPDBicIxwo8CrgLdwwJC3UMiwuCC8kLGwpCCyYMiwoYC4gJiwgyCZwHlQjhB/sFDwhSByAHcgmrCHoHGwj+B8YIfAgOCMYKwAqKC2MOog4pD6IQZg5MDQILUgjbBXYBUP7W+/T3xvVR9EfygvCf8JLwN/Hy8vDyjvW59mj3mffh9uL0BfVC8H7uAe2f6YbpBOiP5W7lQ+Ur6B3vKPMb/pYDzgtXFAQbAh9FIFEdlhkPEpYKWQOR+WzyTuyd6DLodulC7D3wdvNI+X3+hwHeBYEHYQgCCoMKAwwWDX0Mig1lDeMMIRBqEZoPQxDPDYwMDAxiCm4I6gVZBCgDCgNqBJwFwgVyBiIHtAi1CSELmAvdCzAMjQ1ODmIO+w5rDlYNFwx7CyYJJgaaAjj/sPos9yn01fDV7j/uPu6s7izy8/JV9ZH2BfU69pr0BvIW8QPuBe6L6+rqJetz6QXqWepy6BLoEupA9Cv5T/9tCZcOjRYZHKocFB8OGY0RuQtWALz7H/Ui7AfqmecH6frslu5r9Ev5Z/v//2oD0wX/BpgGEgkbC30LKAw3DdsOlBO1FAEVBhNNEjoUgQ8ZDCIJYATy/9T9aP6I/4f+pP+RAUwExwdHC4EJMQqEC9QK7wrKDP4LGwu2CGMJLQkuB6cEGACI+rj3UfMj8HLu6exU7AbtL+/X8YrzafOR83bzHvHu8C7wpO3h7WPtvOoM7Knpsupb6TzmreQ84Afqpvdf92kHUA3BEx0gFiBfI90jSRWUEQEF8Pgv+ynvYuoi6jfpau4n8BLz/fp1+T/7q/5t/8gCuQPIBe4Hywm0D+cS8RckHfgcFCH5GsQbKBoaEh8MSgfeAdH9Mvpi+239oP3vAFED3wRiCJUKnAoKCgwK8ArACbIKyQxmDPcKjAn2CMkGwgKY/nT5G/Vh8x/xvfB78GDyofP88hz0D/Qb9M3x//Di7qXtXu7J7NXtru/57bfucu1M64Hq1eX55M7sIPYO/vgE5AwiFy4d/h8ZIOUb6BRjDHwClfvO93fzyu9T7hbyK/XZ9QP4WfkG+9T7e/uD/Rf+2gAbBK0FhAtGFVUazxsXJCIlNiVuIBcbrhU3DsII7gKt/cT84/1q/F7/MgOZBVcFWgX5BooHjga0Bw8HVgYyCOcIiwhBCJQIsAXfAXP/Uf9L/OT5Rvi+9sP2gvVN9VT05vMj8yXwSO1+7uLudO3V7djrYO6y7/zvE/LO75Dx7/Cg7/Ht/exP7NDw1PSb+uMCLgRoC2kSsRU4FQ4Wag/SC3AGpQLT/1r60PnJ9wn1vfbc+KD22PdJ9sf3svhG+X38zf5fBeMP6RUKIfQkKSayJh8hgB28FjYOAQZWAAj8ifwc/e7/oQKuAjgFjQYgBloHIgeNBcUFmgXjBF0DVgDW/sb9j/vt+1H8Fv1w/qX/OwHwARsBgv9E/jb7jfe89BzxVfH57jHuKe4778jvDu8d723wKfFY8f/xBfNC9Kz0ePY39kn1vvar9N301vQz9qD3UvmD/Jv+rAIOBqcL1wwCDuwNkwwBCngIkgXJAfcAxv/DAJEBvgMOBmYHTApzDjEQoRJrEpoSKBLrEeISFA8XDZwJHQe8BU0ELgSlAr0DpgRvBqIHoQgICVsHtQYWBT4ETAJt/3T9LPs4+rP6vfqs+l37T/tp/Yn+0f9LAFT+RP7E/Kv8qfz1+c35Afcd9sX0V/Uu9ejyjvTU8mz1hffW94j3c/eh+J33CfuE+lD6Cfmt+YP6C/or/E78Cfuc+kH7PPtA/jH/VP8//igBuQIrBeUG5QafBYkFQwerBkAG+AVYBvAFZAgYCc4IggolCYsK9ApICrIKxAcYByYFZQVrBB4ElQJyAg0D2QGnAvoD9QVgBCoEbwM5BPIDLwOaAHIB7gGz/9f9AP/w/UP+0/3s/ZL8Mf0GAPL8HP9F/Nb7QQDl/YL+r/tL/QL9f/0D/Tj4c/zS9t75Uffe+UP6uft8+FD9l//dAEH/rfpm/b3/k/5P/Er9IQAJ+/78vP1L/Ln8nv4P/yr8XAE5+ygByfvq/k/8Z/1d/h//KQBE/TcAhP+IAk8CLAMX/4QCBANVAwr+sQJEABgALAQXAaz/4/0EAMEAZwFFBHYDggMRAmkFFf2XApb/6wCqAAoDsv8ABPsAg/2YAFgAWQL+AbkFFgGT/vwBb/0VAmv5Qvws/Ub/5gaL/7YE6v/gAmX5JAG//d/5RwQ7+OACzP6gBJH7cv+8Bjn6QABV/JQCaf1ZAtz7Qf7pAbcAhfuoACn81Piv/4r/egHsApYA8v59+iMDrv7u/hb+IwBKCVH1Cf6WAAH/m/4q/sD/kPrqA6EAGADdACEEUABy/wcCkwPb+lP9Jf0U+yX6sQCi+or6xP4PBEICTAguDlMCZffCAY0GVP49C4f5JgAB/Wb/G/7n/m7/HgFN+yQGuwEtCU34+AWs9qgApf0WA/sIBPasAfoBbQABAJr7kATP9xMCgvaY/94GrAoWDMv8MQlPA0L71/UGBgn66/e8BEX5AATMBCL72f0ZAMMCh/TFCn8FuP4hA6P3uwRB+pAB8vj2BdX72gqVBmH5uwY0+4T7YPwoAdH7wwdW64IIzv+4/1QGI/bmEcXwTgjB+yUE8/5a/FEKLvgeA5j8qPb/B+D5ZgqP+dQHAvcwBTz+KgWs+rf33g9o85kMMfVWD7vxyfyG/2T81wlL8s8AZAmmAL4HZPfaBLoCSABd+e38tA1+/YP5WPxiBHsQ9ehVBLEJKfzu/D/2txFV+pT+KgNu+RYEVwSk+Cj63AlQAlD4nPGDEI8Bk/REB0b7tAw8/n/8w/kGBrgMdOjTAiQPRvQwCbXvVRFSBPX4kf25APAFA+7tAg8OA/KH+2gPpvqD/EQGywMu+S3/sAoF/G77XALxBBcDLvgR/EQLsPwY9FcJMAMA/gr1Rw6B+8P2RAhFCIr0uwHhCZwD0PJICUr1jw3h+/r29Qmu+IoJMfgRAt8AoAWb+9r1Gg5eAX/yEgy2Bjb92wXK/Y372wGi9hb+ngMYAyL8bPyQBoMIEvMP/wYOzfwk9QYHlQap/+D3WAJ5BnkASvUbAhAH8fnhBXcAYvs+BfP7MQEr+voFNgpG7+IEEALPA8f5Bv9pA5AGtvwN+wkJsvYrDcjyTwOFCUz1SQS1AooAQgHp9r4L6/5U+P8BMQcy/E/zAwzMAfQBlf+x8gcNbAU99VD7lAv1BynzSvjYDusHzP0D438X1Az/8J/1mf92G/3wKutuC/AX7vom4+cKrhPm9/X4uvcCE2EGiOipAuEFyAMH/QbyZgkdCDEKxuyU82Qlwvoo7/L5ZAeaDzr0N+6DCdgT3vdE7GwI/g1yBbrm6f5VFcgBN/PR9TEPpwNU+In1bQctCi/+OuynBScVdPpa7h0CyREq/KL1xQMHBBYDoPq58l8PZw5i7wbseBNZC2zzEPn4ADsMmPu1/M4Aiv2YAVIFB/ODBhII6AHx9nL2JA7fBkf32u0tDC4Nev1I8IwGHgXM/vr7ZPjfEKMDlPBy97oYXwA570T6FAuzBYX5kvhqB87/9wPb/qb0Jg89CMjsA/r6D/UDVPTP9JkL+QxQ9tLvsRFvEWvmTvvrD+cH6/O88YALRQwK8vbzVhDmC3Tt3PSWFPILuOXa9aUbev9V86r5OgklES/r8fNjFxIKDfR+4qIc+Ay48ffweQMkH3P1Tt97DfUYj+8E7lcJow6cAp312/BIGSMH6e2A+voDPhQA8rbtFxHBE+7ww+W6FeYR7e/Z7kkG0RfB+N/qbATfEqT8NfKb+MwWIgqO58r1rxVZDBTnsfhrEIsNC/Oi7jMS4Ax46PEApwqeB2vytfrICaEET/z+8RYKuQvJ8sj5ChWYAYbsBwSCEOL2JPb/AYQGBv1c+W7+4wqyA+bzOwEZEYD8VvAgBIENHv9D6xwA3BWP/cbwvP3mC7EGkPlX81EKORIC8VHv3wnYFuTyrt5BFu4V0u4r7HoQABaI8g/otxAUGqDtSupHCcEUif7R5HoFwRUNAY7inwcOHIn2aOWxCnAXUPI47ogMOBOl80np8A+KE1nzh+j7ERQWf+KQ9h4Wdwkl7Ofz5xdgBDDyvPnUC2ALUfAV8Y0W1gZC6QECDg4IBFHsQf7PFXv9le0bA9oLxQIU8T7/fQz0AnrtCgLTCyv98PxJ+RoLcgEd9kEBzgN1Brv1CPuxC7cFUPUD9+ETYfq17rEK4AgM+zHz7QqjBuT6rPPfDn4GP/Sr/+sCpAaF9M4A/wuc8kj/3QdWBIDyyQK6DQHzHP2uCSX9rvtd/4oL9fuI+kX5lRKZ+hL02AiP//H+QQNd+QIHN/9O9tgD0gNcAFb8pfpFCKQCVvyi974IhwRH9wj9JwUBBIAASvQ+C2kBY/eeBlf9+wVI/rz2SAEOC5v8w/XcAsYJ2Pv38zcJUg5N7eoA2wmE/Tf84QAsAzT9oAUS/cz2tAqb/l4Dc/MICNIJ4PCj/vwGVgX79rAEvPxuAuUFhPfi/ikF4APo+qD6aAWXCFH3IfadDakB5Ptd+ikF9wgq83X+sQqy+gL73wZz/Xf3RA9u/tr0hArQ/9D5mAQH/XIETwOX9p8AZgg7/w75uP+6C8X6e/ZsBwcHh/UrAmwEE//c/HgBOwBBAMj+IQHuAUv6lARmBZj6YPjoDKb+jPbGAmcHwf4186sHKATM+6sBbv7JAJwDdPhABrgALP4VATcAw/rAByL/UvZPBrf3jAmJ/Z/4YQq//Bz/RwOf+T4FZQak9uYCev5FAKYEXvOyBDIL3fVcBebykQgMDb7u2QSxAAcI2Ppd9EMTiv5b9FIAsQSIAQj9Bv4VA3/7bgnw98r71QjRBULzEP4CCTgDWPge/OgCnQVBBKLy7v1yFUL48e7kALgWwv7+5vYDjAwaBELugfjQF4wCCen8/RISewJV+K3xuwu6C6P3W++ZCisRD/PE7AcT/Qy18dv8VwR2ACkT/+ii9nEbZv2U7f36zxScAJLr1wcGBjH5gQah+bT7AgnpC2Lq/vopGvX4FvNHCtH2QQTuBiL19/lhB2UU3uM19S8rXPEr6rIQTQK49U0N5vOg/OkH/AIy/3jtiBXJDYvb1gg2GeLw7PawDDkE1vUuB30Dq/FKA7EJHPFRAAQHlgpm9GD0mxp1+XjzDQrNBp3uEQSXB2P7UvWRD7wB+epWA7MYIfEt9r4HdhWO7NX38hc/96LvSQ8hBKnpwQ45CQTs3vzCFkn6COyeCnwQO/lM7tcOggoe7pUAmQwX/eHwRA9kBM3towTKEubyrPJeFZsEouY2DcsHNPny/RMFjAIE/l37sgWIBNX0TQfy/qn11Aug/An9AAGj/L8HkvqAAJkK+/p2+cUGLwKe+8r/xwVc+RH6+xAx8bkEGgTB9+QC2P1u/4kJrvKfAp0GoPueAFwCuQEu/sj84gbX/wj+1QQl/Jj60v09Ckj2bQKWAub71P2tBrX/yfnhA7EDTfj3AE8H2QAE+5v+ogWA+4L+lwHH/wX/WvxeBIP7wAA0/Sz9rgcg9awFKQNh+9X8YQajBUb28P4hCo/8/PrNAVsAVARI7y4L6/0j/RAGiPFtCW8Aj/eyBTX9FQJ+/4L7AwmN9WAGrvxr+NQNEPQmBBQFUvJMC5/65/kOBk35Pwyz820BJhJK6+YJ4AED+hUIfPQ/Buf8C/viB0z32f8lBO/+Pf5a/nEEqv+p+4D9Owh4//j4ggW3/c8C1/kaAzEBAvqtBYX9AfyLB57/i/xT/rUC9ASp9V4CCwIV/Uj/t/qHCQT3Hf7HByr3MAPX/98C6fqj/z4KlvheBJz8sASpAT33Xwb2AH393fkaB1EBQ/u5AF7+BAFdAd/95/8ABR/9vP4NAx8C+fsLAWYEU/u0AVUACQJ9/GX/rwPM/q/9TgJsBDn9mf8qBn/7lQLH+wsEav0K+zsKq/qD/twBsgNQ+xj/ggbW/Hf/9wP7/EsDBQEO/WwEef60/80DP/7RAJMBEv9//kUAzAHn/ykAKf4zASoDeP+a/ikHQPtXAl0Cjf1UA3H+UQLM/EMBqAW0+YkBCAWH/JgBSQCwACIAlv/XAbD8xgS6/dr+BQMVAJj/y/74/msBGf/HANsACf5ZBF/+/f8RA9f+LQBg/gMCIgF4+/gDbv/M/qQBGgJf/9T9HQTHAFb9jQJdAa396f+zASz/uf/O/9z/qgL6/mEBygGx/9z/gf+dAen+mf9mALL/ggChAEsA8v8z/zcCzv0VAIAAI/9RAKL+0AAuAA8Brv7n/q8CXP7U/mD/kQBl/0wADv4FAPcBxPxmAcEDsf7Y/lICOQFp/PEAsgAcA6kGmAxAFckN5AVM/5j9KvfA+kn9g/rO/NwACwRqAQD9L/rl/Zr/G/ywAP0AJv7l/eYBYAG+/dP9Vf8gAYoBugJ9AZsDhwAjAaoCYwE3/gj/QQFwAnj/r/9YAS0AiP2PAGP/Wv7BAd/+7P/E/rP/XP5T/7gCtv+7AqAJvwRVBuz5+vsA+Uv67gDUAPMCvgGwA6ALcATiBnz72P+lAWX/NgZn/Cn7fPnu+XUBvP/HAsUBJwHeBIgCGgmABOcCZQKC/yEAhAD7AKoBwQB1ABb+E/+d/3L+Yv48/Cz8tf22/tP+8f8VAMn9mf5G/5P+m/4V/3r+Nf3z/Qr/7f2N/90BVgDiAJwBBwTGAXEC3wHJ/ir/qP6x/nb+fv5B/YP9JP41/vf/ov4J/mQAZ/6c/xL+lf9i/ef+wf7aACsCEP9cAZ0Bhf8mAGn+Mf8C/uD+KwBAAIMBj//i/8T+dP6H/oL9/f7g/U/9Df5X/ir/Q/5e/pf+gf4P/4D+C/9m/0H/HQAp//7+4/+gASMAqP/T/27/Gf98/44BQv7Y/XH9m/65/qv+ff5d/zIAPQBhArEAif6R/5H+Bf4k/o0An//5/l4Ajv8M/tX/x/9KAIL/lf4mADT/8v+d/77/Mv9h/7H/vP/Q/wz/Xv9a/UX/n//S/oj/r/6l/Zn9vv0Y/9L9hQCb/wgAzwDb//wAJ/4L/2v+oP3M/2n+pwDO/rj/3/7G/m4B3f7W/ob+Vf2E/8T9Nf/D/nn/Y/7jAPwA3gCP/wT/hf+4/2//1v70/ob92f4D/sn/BwBI/4n/hf/MAV7/0/+o/5v/pP9y/9L/EwBX/mr/SP+3/yIAs//V/5AAHv9p/xf/j/+B/1f/+f+e/ywAKgGy/0oA6v4Q/2QAogA8AeH/EwCJALcA6AAfAcgA8AF7AcABsAGBALEApQC//ggA2P3k/7AAof/jAUX/uwD5Ap8BFgI9AEv/UQARAZABzwDvAEr/xAF/AScCHgBNAbn/agE7AyEBBwGd/0gAEQBmAG0Asf8O/9//iv93AEoAEwBH/xYBeAG9AGoBFwDl/97/nwDiAH4Btf8IARcAZgBmAfv/HgBdAJwALQCVAD0AUwAs/7T//P4aAN3/Ov9g/4r+Qf+I/6H/6P/7/mL+ff+iAKL/ewDw/ywALwAoAdgAJQBUAJ3/+v/N/3sA9f+I/+P+OgDH/zgAdgDb/2r/SgCfAE8Ar/+//0D/NwCtAJUAegByABAC3AEOAuIC8QFDAvsB6QH3AZgA3ADvAAUBlgC0AFYBhQFlAbUBQAKbAYMCoAJaARADZQLgAqQDIQI4A1MC4QL8AnADOALcAeACuAFZAVEB+gD7AD0AGAETAMH/vf6X/kT+zf3W/Xb9ZP1j/Hf8u/3J/fv9I/1P/k7+1f2h/jb9e/0//bL81f2n/Yz85Pyz/ZH+N/7v/Vv+YP9e/pr9x/2J/Un9sfzC/MD7FPuv+6b7R/sA+9z5pfoA+676FPnc92f4Q/ft9nH2CvYx9sj2d/dD+SL7sfwq/+QB/QN7BgcI5wlaCv0K+Aq9CowJlwisBqEE1gNTAvMA9v87/5n+df4F/4X+Rf/E/9QA/ADnAeACKQPJA18E0wSXBckFkAb0Bk8HwQc9CHQIoAjfCKcIjggWCK4H1gY4Br0FygS6A9UDWAPiAsUCpgKvAt4ChANcA20DxgM0BCsE5wOfAxID2gKVAigCzwEEAXQAhgC1/yH/IP4q/bD8LPxm+zD7Z/qO+iv6YvqW+g77A/vD+jf7sfsw+1H7vvrR+qf5/PiC+Jn3jfYh9VL0JvPd8RnxJPDo7ybwkvEG9KP26vkL/V8BjwWiCdAMQQ80EVESCRM6EvoPRA2TCgwI+QRmAT7+Uvut+Y/4xffb9t32T/eL+K75O/o9+2v8S/2E/jL/rf96AH8BuAGsAuUDcQRTBTgGDQdPBx0IJgiVB5EHegYyBQME4QKzAa//9v7H/lL+Wv4L/+r//QCgAicE8wU/B0UI3Ai5Ce4JVAm5CJgHzwaUBRIEaANkAosBYQEjAU4BRgG+ARICdwIPA+QCMQNXAxgDNAMdA5wCzgJcAj4CTwIBAhoC+wECAk4C6wHxAZEBWgG1AAgAX/+D/o/9nPx3+4j6oPnU+EH4m/db9+T2zPa09vD2rfb19tP2bfal9qX1jvU59JLzSPKm8AnwUO5g7R7sYuwY7RvvxvEq9H/4tfwWAmwHSwuPD9QS1RWxF54XbBa9E1gRWw4HCgwFVwCt/DL5P/a68yXyc/GA8WTyhfO89Iz2rfj8+mb8Av6O/50A4AGkAmQDYgRkBTcG4waEB7kIcwkVCk0KIQolCr8J3gimB/0FkgQAA4YBMwDV/t/9kf3C/U3++f7b/08BDwNWBIUF6Aa5B2kIegizCEkI4we+BgkGPgX5AyQDXALaARwBuwDDAPMAGAGoAVQBcAKWAp4DMwMBBNsDLQRcBOIDDAUdA4AEmgPcA4UEiwIwBAcCZwP/AQgCMAFYANb/F//X/XH9h/tW+9H5h/l6+K33kvdy9u72ivbA9tX2dvbq9r/29/YT9yP26PXZ9EH07vIX8dHv8u007cPs0+x27rnvt/IS9lX6tP9EBBsJTA3RETwVRxdHGKEXPRaXFLwRZg2DCI8Dav/Z+mb3v/O/8CzvD+8672zv5PA284n1Mfjh+in9n/+cAYsD4wQaBjIHmQdMCNQIAwloCXwJ3wlpCTEJUwnkCA0I9AYkBskEbAPdAWIAA//7/QP9SPwm/GX8mPxd/Zb+1/8jAagCLQQpBR0GNAd8B80Higc/B9AGugU3BSkENAOHAq4BfAHpANAABQHBAFYBqgHbAU0CYwLAAr4C7wIZA7wC8AIWA8ICvQLEAr4CSAJeAmUCvQFtAUEBjwDK/xH/df5w/az8E/z0+kH6jPnf+Fv4wveU9y73Jfd/9wX3YPdx92D3y/eP98T3SffO9qb2zPUO9dPzVfI58UrvKO5w7EjrHOuG6/PspO5I8aX0AvkT/qoCSQeWCwIQtBMpFoEXNxcbF2cVGBMXD2UKswbSARD+hPkE9lfz1fCM8MnvLPAv8T/z5/XV97z6Mf3K/ykCFASnBfUGIwiJCNgIBgkyCTsJGAkTCasIjQihCGEIFwiHBxsHfga/BcIEhgNbAl4BRQBf/5f+3f2w/cf9Gv6i/n3/wADIARYDZgTdBRMHpwdkCOEI/wjBCCkIpgeOBq4FwwTSA9UCFAKsAWUBTQE2AUoBpQH6AVECZAL7AhUDegOOA24DwAN7A7oDsAO2A8oDgQPrA8QDfgNCA7UCXAKzAfwA5f/v/gj+4vwE/CD7SfqS+S35DvnA+Lb42fjy+Db5fvmq+ez53vnm+df5mfmr+fL4o/gx+C/36/an9dn0xfM08oLx7u/p7tPtkuzr7IPt2e6Z8KnyFvYW+m3+GwMRB0ILYw/EEs4V0BZHFyMXFhanFCgRmg3YCbUFCALS/Yb6f/f79PTz+vKc8hvzRfTz9Sz3MPlp+2j9af/eAF8CygP6BB0GjgYVB6cHNwijCNQIzgizCOII+QhnCOcHiQcEB0MGPwVuBFMDOgJjAWIAlf/0/tP+wv5//un+VP/6/78ATAEcAtYC4wOMBOoEhwWIBa8FqQVlBekEQgQlBGIDygJZAtQBtAFTAWEBaAFxAZ4BxgFDAnUCtwL/AggDHAM7AzIDDwMAA58CVAIlAhkCqAFHAUkB2gCXAEsA5f+P/+L+o/4P/q79M/2W/E/8rvtY+wz7yfrR+oT6b/ob+g36FPqx+cb5lvlj+W/5HvlS+fj4wvjd+EL4IPiA9/v2rPZ99Tv1/vMS82Hy5fBT8L/uSO7q7k/vAvFG8jX0iPf9+lP/9wKvBtgKXQ7HEVIUcBUsFhsW5hWVFLURvA5nC+wHgwS2AGf9Vfrx9yP2kvTg88XzQvRc9U32qveI+WP7Nv3M/nUA/wF0A+kEtAV8BlEHEQjMCCIJaAnKCf4JJwrLCaAJaQnQCDQIZQd4Bn4FeASAA3MChwHrAGgACQC+/4r/uP9BALQAGQFuAVUCJAO2A3gExARLBZ8F1AXaBZ0FagX+BOEErwRXBBgE7gMBBOMDtwOmA5EDfQMlA98CoQJOArkBeQEKAZoASwDl/5v/Uf9C/xz/FP9L/yv/Rf8v/zL/A/+g/pf+F/6s/Uv9/PyJ/M37d/vq+m36IfrJ+Zj5DfnR+Lj4cPhN+DT47vfo9xX4F/hI+BP4Uvgr+Lr34Pez9rX2wvX99Er0qfIP8onwi++g7irtFO6y7tLvpvER85H2/fkN/mICsAXPCWoNoBB9E4EUvRTNFFUUFhMWEIUMjwncBXkCGf96+2/4v/WQ9E/zEPIt8pTy6PP79Pb1wvdt+WH7/PwW/sb/CwGVApsDJAQyBdYFyQZ0B2gHxAclCLQICgmWCFsIHQjGBzUHMAYhBScEJwNWAmwBbwCW/13/KP/5/uf+b/8zAO0ArgFnApsDVQRNBSEGVgbLBtEGEQeqBncGSAa0BaUFPAW1BG4EXAQsBK0DdANlAzsDAAO6AocCIgLqAYcBOgGtAD0A8P+F/3f/B/8k/3n/dv+n/47/+/8uAGsAsgChAJsAoABRAA4AeP8E/3H+Bv6e/aP8Jvxk++r6SPp4+Tv5vvi8+IP4oPiH+ML43PhE+fr4S/k1+Sr5tPhj+Kv30/YQ9tj0H/SJ8jrx4e8X71fwYPCg8T7z0/T0+Dj8fQAUBGwHfQvxDvsRXhRDFNAUxhRJFIYS8Q7iC7QIOwVsAqL+WPs++I/2qvU69GHzyPOp9N31/vYs+L35cPt9/dX+0f9UAaYCDwTXBEYFTQYpB2MIDAkoCbcJNgojCzMLpwpcCtoJbAlwCNoGTAWaA3ECcAHO/1H+cf35/BP9svwq/ZL9g/69/+kAZwJkA50E5AXpBoAH/AdlCF8IOAjvB3UH+AZfBuQF0wRRBMID+wJ7AjICpwEsAcYAsABWAPT/1f+b/5P/QP9C/2L/F//4/jf/fP+E/63/CwDu/00AgQCKAF0AbgAPAOr/gP8i/4X++P3Q/RH9mvzO+377//qn+hL6wvls+Uf5HvnP+KP4zfis+OD4wvhQ+K/4/fdc+GH3cvca9p/1qvQA88PxAfAw7nPt4e0K79XuQ/GE8o72Vvr7/t4CSgZKC9QO3BKvFC0W2xVJFrYWlRSAEYgNwAr8BqwDxACI/D35JPe09vX0+fMB9I/0bvXf9vP3qfgY+hD8Qf1B/m3/lADJAdUCFwTYBEkGmgf2COsJaQp5C2wMBA3pDFYMlQt6CngJpAexBXkDzAEmAHX+pvxg+9f6oPq3+lr77vtK/dj+kwBFAqIDgQXlBo4IJgnBCVoKOApQCuQJsgmnCF0Iygf3Bl8GtAUoBVwEdASEAwwDjwI9AqwBFQGgABkAxP9//y3/Ff/C/ob+0f7//kX/c//d//j/dwC/APkA7wAzAc8A8gCgAGsA8v+P/2v/y/6v/uP9uv3z/Pn8UPzv+5L74Pr9+ij6K/on+Wf5pvhp+Bv4WPeB94v2vfaV9az17fRg9CTz1vH+8MLubO5R7D/u4u2l7yTxdvOM98n6VABtAzwIyAsFEPMS2RQTFjMV/xWkFOIS1A55C2sIgASUAdD9xfpx90/2BvUF9A7zXfMi9PX0PPZZ9oz3q/iJ+nr7PPxi/Wv+7v/xAG0ClQM4BQ8HowjSCYYK9AvJDFwNygzoC9MKjwn2B44FVQPrAB3/Kv0y+335I/i294D3ivfB9374+/mg+/r8w/4aAEsC6wM6BWoGIQdhCKcIsgnJCc4J1QmDCecJ/gjVCAgIlQfcBucF9AScA58CqQE9AIr/dv7E/Tv95fyz/LL86fxb/QD+c/4L/7T/hADyAHsBoQH3AcwB5AFxARkBqgBPAEQAsf/E/8r++P6k/if+Tf53/eP9JP0Y/cH8Ffwl/E77rPuU+xT79Pou+iD6t/kc+QP52ffv9772Ufap9crzTvN08fnwQe8/7Yfsauy/7nLvS/GE80730/trAGwEFQi1C7IP/hKEFOYUQhRXFMUTohE2DsUKaQgoBqADlAC8/Xj7YPqD+T/4Hfdd9gb3SfdO9571W/QG9pf3I/oJ+vr7PfyW/h0B+wL1BEUGQQm9CtIMKA1mDl0Osg7HDWMMsgqwCDAGxgPrABz/tvzg+uP4W/eu9sr2WPdY99P3jPgy+j/7D/3d/bv/ZAEbA50EvwXwB10JVwucDF0NQQ4cDgcPVQ6cDZIMngqBCfMGwQUpA2oBg//O/aH8mvtP+w37N/sA/P38Ef4h/ysAlgGSAq8DOgSoBLwEzgSUBIkEoQNSA2AC9wE8AYgAd/8H/wX+sv1u/Nj73Pok+uT5+viw+Pn3B/jY9yT4fvct+PT3dvjW+Cz4RPnn92L4efdx9s31ufII84vvO+4B7Tzsvu5M70HzzvTc+goAogXjCQ8O+RHKFBMXGRZsFXESmRDBDCsJMgRyAIL9IPus+An3/PVe9Uj1FPaN9Qn3Tfaj90z3efjE+BH5t/qa+8z9Wv8PArgEkQdmCkoM6A65D7wQQxBQD9gMkApgCfUDGQLw/EP8MPdY+PD0pPWv9TH3i/e++UL7o/zW/Qv/Lf9mAKQAJQGwAIgB8QE0AwoEoATcBRMH9QeQCPIIaAj5BxQHQgXRA8cB/P/d/Rz9Cfxm+3H7B/xC/cH+uAAkAjgEjgUYB/cHkQhwCAUIxgf3BugFCgUCBJ0D8QJbAh4CEwKwAX8B/AGhATcB+AB5AHoAy/+R/6H+Tv+B/kn/a//v/30ARgEKAsYC9AI8A+sCFAS8AigDiQHpAVkA5QCK/0H/d/73/SP+RP2g/cD7/PxM+3T8pvq5+9z56/pL+pP7cPpo+/36tvxE/Br8gPxh+iv8SPh9+e32zvR582/xhfJi8fnxbfMR9ob6S/7DAUYGewrLDcYQKRFVEqQQtw85DcsJrAfmAhkBpf0z/Mf6PPkH+RD42Pjn+F34rPgH+KP4kPix+Ez5A/qR+2r9U/9sAp4EeAfuCfMLuw0cDj0OAA2aC6UJPQaPAwEAQf3u+hv4WveZ9eD19PWv9j/4Mvn1+i38nv0P/wQAzwCnAQ8CUgOrA6UEQgXWBRgHJAfkB7EHOwfMBjoF6APOAcv/jf1H+975Q/gk98H2t/ZM91n4v/l6+zL9H/+fAEAChgNZBH0F3AVTBmoGhQZbBkcGLwYABqYFBwWdBMkDDQOoAV8AKP/9/aD8mvvR+k76Svo/+gD7v/vZ/Cz+i/+lABcC4AKnA2EEgwR/BD4EzwO3A9wCjgLtAaEBfAEcAe8A8gCLAIwAYQDd/0f/Tf/X/ZL+BP2B/TP9kv1f/Qr+Ev/c/qIAUgDuATQC7QL6AZkDswG2AikBXAE2ACIBhf9IAHUAsgDTAKoBVAH/AcABsAFiAQEB9f9mAHj/ev/h/k//AP+H/5b/BQAYAAz/+/85/5T/OP4A/kD8H/3J+tX7k/k8+jr4G/mQ97/3ovel9Tj21PTB9RT2BvfO9576R/0nAXsDNQg2CukNcg/HEAcRXhD1DZgMjQgLBzgCSwBg/Lb6OflC96n2LvYM9nP2ffaP92z36vhn+Yf6h/x+/fj/tQEmBPUGIQlwC+IMGA61DkYOqA2oC4MJwAbFAwUBQf6U+835tvdu9+r2RvfN95D4G/ow++/8z/1C/1cAfAGIAmMDkwREBQQGGgeWB/EHRwjMB5cHxQaOBd4DKAIuACH+gPyM+lP5Uvgd+Pn3W/hW+Vv6wvsq/ZH+FwAvAWwCFQMDBLAE+ASFBbgFvwUBBr8F1AUhBbIEwwO+AqwBOQDX/if93/tu+n35+vhz+JX4BPm/+f/6Svyy/R7/fgCcAaQCYgPvAxwEMwT5A9MDgQMJA4YCIwJ3Ae0AKQCP/9H+4v0V/S/8gvvj+qb6WPqL+sz6fvtw/H39n/7b//EAHAIAA8oDNwSNBIYEbwRABJADUAOPAg8CagHDAFAApv9V/5f+Df67/f788/yl/Jz8o/z6/GT9K/7l/vv/vgDtAaMCfwMjBHQE3QTiBFgEfARbAyYDUgKaAdsALQBh/6b+Gv/s/T7+HP69/UX+8v72/WP/oP+V/7UArAC7AOYBiwG0ATcCeQHXAW0BHgEHAaMATQC2/97/jf+b/wP/W/+W/rP/AP/i/p/+8f58/hb/P/69/lf+/P5f/mn/oP8V/zIAN/+c//b/Tv7W/Vr9d/vt+mb4qfjB9qH2XvSm9Xf0gvX+9E729fcO+rr7dv4vAQkERwdqCGIL+wt3DWUMEwxjCt0IJgaSA7oA8P5b/Gb60Pim9yX3WPZk9uj1K/cZ99f3DvkJ+tz7WP0h/0MB4gOPBW4H/wixChgLjAv8CtEJzgiZBpkEKAIPAJf96/tV+kH5sPha+BL4yfh4+V/6bPuE/Mz9QP+WANYBBQOQBKYFZQZCB60HEwi9BykHSAY7BdEDDQJgAKf+Cv2D+0j6mvkQ+fP4HPmp+bn6jvum/NH9+f5yAIMBdwJ4A0oECgW8BT4GfgaLBmMG5wV6BaAEhwMyAsoAZP///YX8Sfsn+qv5AvkJ+T354/mG+pn70vwR/lj/cgCHAaUCXgMiBJcEEgXUBO4E9gSLBFcEswMzA/UCpgI/Aa4B6P8tAPX+s/4C/iv+Lv1V/c/9zv3j/mH/cgBiAd4DIgSfBYIHKgfXCF0Iqwe+BzUG/QNFA2gBZP+a/ub8ePyH/MT7RPx+/Bb9kv0g/kf+af5R/7z+8P7P/q7//f5ZACT/cwBGALQAfwC3AFQAzf+j/av9P/uV/Fb7FvQu+fbxwPkw9GP3CfU89IX1Z/J5+IH4i/SW8vr25flPBWj/UwfSBqsP9hEMETEZLxEuE2cGvgwKByYHfvml9pX38vYI9z3z6vNP9vP2uPXm+qr5M/6/9wz78f08AqUDnQDcBWoJug12DpQOExACEU0OnAzCCfIHlQKE/ef5GvmT+O/zDvPk8tL13PcS91f5FftG/YH+3v8/AmgDWARtBIcGFAmuCoMJegmnCZ0K9QmTBnUEBgLd/0T8gvr69/720vTa80L1u/ag+IL4o/qz/EMAhwGxAnkDXwWXBZcGDweDB/MH2gYMBy8HZwc3BpwEIwMLAisB0v4I/e/6Kvrf+JT4Xvgk+Wf5Z/pD+6T9XP+RAEUBIwKcA50EawTIBIUEkwRHBbwDIgU+BBAEaAP1AsEDJQKdAnX/3wAu/+D+7/1F/bb8wvwA/Vn80P3//Wn+Pv+NAIkBmQO3A30EcgYVCEAHFQmgB6MHaAfdBJ8DoQJpAND9KP0K+2f7ivoh+rP5VfzM+8j8Nv72/U3/OgDR/pAAMQDb//v/yv9n//j//v/x/mn/Bf/d/mv+ff5u/SH9rvz++pX6s/ol+BP5nPZt99f20PYI9yj3Bfh99z/3J/kW90L4UfZx9cr1UfSl9NL1GflV+sn+IgH4BlwKTA4QD9YRsxDnD88NJgo8BygDcf/o+/b5tfiG9zX3ZPbW92L4xvhy+Y35CPqq+hX7ZPwP/iEAzgGiBKwHRgowDfwNMA+3D4gO0gx8CiEHQwRuAI39uPoN+a/3k/Yg9yf3pPja+eD6WvzC/Sj/QABuAfwCDwSsBXAGCwg6CesJZgpgCiEKRAmLB9cFdgNqAbT+k/zI+iv5afhq9+T3Kfg++UD6yPtu/b/+XADAAWAD7wSvBZwHqQh2CvwKMQw1DNIM8gtfCwIKfAhhBkMEygLOANwAEP60/xj+rP8IAKb/wgFdAFsCuQBqAuEAewE2AXAAvwFmATsCIALOAtkCLQM/A/EBbwLqAPv/Tf9F/mj94Px5/Mz7svzt+6D8Dvzc/Gn8Gf0W/UP8R/1y/Aj9fP0G/a39dvuU/sr6Tf+f+zX8J/zg+SD8pfd4+4v1kflK9Bb2mPWS9PPzfPLD8yDxK/Sh8kr3s/k/+5IAXgOFCUoLmQ/dD8cRShGXDwAOHAssCA4ECgGz/XX8bfql9w74CfYH94b2iPYG99T2Gvg3+C/6Tfvn/eT//wH+BOMHTQqnC3MNow2sDaIMiQo9CaQFIwP4/1z9Rvsz+WX4xPb09r32q/cS+G35G/oL/Ar9hf5+ALUBsAPNBM0G5Qc1CRwKNgpgCucJNAkNCMQGxwTQA2oCWAEgAL//GP+J/yT/vv9rAJkB/QFRA+EEyQVOB8MHuwh2Cc0JZQlbCXIIdweKBggFkgNaAhgBtv/h/kX+nP25/TL9L/21/bb91P2//R3+uP2H/vL9Pv7G/kP+xv7A/v7+G/8X/8P+2v6c/ln++f3m/VT9JPyv/Cj69fpH+cb4uvhz+M34V/mA+tv6rvxn/X79zv5v/XP+wPtJ/OH49vj59gLzf/R68MPxDvAL8Y30X/eD+T/+kQFsB+EJIQ3HDwAQQBH5DrIN+QyMCKEH1QIZASkAHv3v/GL6MPqu+ab4qviA96X3UffE9oz3evgv+t/7Af01APwCuwWlCEQKjwwpDYgNFQ3dC44K4Qc8BTkCGwAM/v77VvoT+ez4V/iX+NL4PfkO+iv6S/sA/C79cP4e/xsBiwJ9BMMGRgj8CioLiw0XDd0NvwyXCwoKmgd6BQMDSAHo/pD9VvzB+877pfuE/In82v0B/jf/lP8jALkAsABSAXkBVALoAioD0QMCBJ4EcwRjBMsDSQMdAucA9f+w/uP9t/wx/IH7i/uq+7L7V/yp/Fv9h/0q/ln+xv6Q/nH+av4o/gn+9P3r/ev97f0w/uX9N/6T/aT9Bv2y/Cb8D/wJ+9P7l/qD+xL7qvsC/Pb7hfy5+yX8IPvr+nP6Wfmd+Pj38/Yt97z3jPiE+Sz7t/xC/xYBcgMuBR0HdAdMCG4IrQdpB8sFdQThAskBrgA5AIz/Af8g/xf/Af8j/yv/2/6F/jv+0v0b/pL9qv3j/TH+B/+2//4A3AELA64DUATbBC0FJQXOBCwEbwPJAt0BSgF9AO//Pv87/8z+2P4o/zD/lf+2/0QA2ACWARkC0QKEA94DcgTOBBIFJQUHBZsEjgQpBMIDhQMcA74CfgKHAjwCVAIPAhUCRwLoARsC6gHoAboBgQGCAVABcgEXAVQB5wBkAf8AXAFgAVIBiwGiAZQB4AGPAb4BZgFJATwBywDcACwANQCT/7v/Hv8F/7f+bf5G/qv99f1c/br9P/1x/Xj9bf1w/Zr9pv3a/fX92P1C/lb+cP5i/jz+Qv4F/v/9Zv2H/Sr99PzU/JT8ePyx/Bv8dfzT+y38Dfwz/Av8+/sV/BD8I/y3/Cb9pP0Y/nP+SP/N/18A3gARASYBJgHxAMwAUABBALX/wP+N/5b/AgDz/2kAbQDpAAIBaQFfAXsBewF5AUEBUwFFAVwBLwESASEBPAFTAVEBQAFPAVUBXQFuAUwBeAFwAZQBnQGBAcABpQGiAY0BjwFiAXABXwFYAUwBNQEQAWkBQwFpAV8BiAFwAXsBiwGCAdABQgF7AUIBOwEuAe4AFgH6AAABuADaAMsA5gDaAMwAqgB9AMUAagCiAGMAVwBGADAAFgD//x8AEQBUAD8AsQBbAL8AWgCQACYAVAD8/w8AFACg/33/Mf8r/97+0v56/qj+aP5d/n/+Rv6A/h7+p/41/nP+Qv6Q/ib+qf5q/tz+WP6p/nr+hv6d/mT+mP43/mz+7f0g/s79Fv6v/cj9m/2s/br95P3M/bb9tP24/d79N/76/U3+EP5k/kD+af4w/nX+Uv52/nT+gf6g/qL+9v7q/hL/Iv9C/0X/hP+0/7X///8HAFwAcgCTAK8AvADWAAsBJQERARwBLAEVAWcBVwE7AX4BLAGSAVEBggFOAXUBfQFVAVcBRQFbAW0BZgF+AXsBdwGNAbIBxQHiAYwB0AG6AfYB2AFlAboBWAH5AUkBwQFQAcIBMwGyAWcBgQFrASUBhwEMAUgBRQEKAQkBzwAQASwBrADyALgA3wCqAMAArQCfAFoAgABUAE4ALwBbAP3/RgD1/1oAyf9GALz/7f/H/yEA4f8TALf/wv9h/8D/of+Y/yL/Mv8G/5z/7f6l/+D+Lf+z/lz/qv4w//T+BP/h/t7+5f7G/v3+wv6z/q/+w/4i/8r+rP53/tT+g/75/oD+vf5M/nX+sv6A/g//df4F/17+pv79/gn/+/7e/rj+t/4m/77+bv9e/67+U/+6/q7/tv6d/wj/dP/c/mH/LP8E/5b/Yf+E/2L/Tv+f/0b/5P+Y/+j/tv/A/xUAuv/y/1UAJgBvAHUAdwB3AG8AkQDeALIA0QDYABoB6QD7AAsBygCHAYoAvAH8AGIBowCvAV4BjwEcAf0ATwHLAdUBUQF/AcIA0wEPARYCIQF9AeIAKAGfAcYAIgHVAH4B0AAbAeEAsAD4AAcBkwD/ALgAsQD/AKsAuwAJAeP/6AB3ABEBcQBUAGAASQAZAfz/EQD//1kA0v+TAHcAt//A/5v/MQBOAPb/gv97/7z/BADw/wUA5f8A/8X/j/9TAIz/Qv+a/47/z/+7/57/W//Z/x7/WP+5/43/QP+I/1j/Nv9x/9D/pf+Q/8j/B/+N/xUAOf97ANv+1v+h/lUAd//NAGT/3//1/rr/AQCk/yEAvP9//2H/w/8DAPb/SAA4/9L/cv+aALf/VgBO/zQA4f+H/zcAxf+UABYAr/9SAMr/vQDA/34A+P+dAJP/tQDP/40AawD9/xYAHgA8AAIA2ADY/64AHADK/9wAfP+zAEEAxgDg/8QA7/9gAWX/XwHF/8gA2AAPAIsA3v+DAKYAgQA8ALMA7/+0ADkAqwDq/98A0P8gAEIA8QAd/24BnP/CAMj/JQDP/2EAzwAHABsArP/A//P/qQA9APv/yv/N/mgAPQBO/8wATP+U/xn/2v/b/6UAxP4dAFT+JgB3/ywAlv8l/0v/hv8g/wYAZf9v/w7/nf9O/47/JACN/7j/x/40AAP/rP/q/6v/ov5QANX+wv+6/5z/Iv+x/xv//f+G/8b/vP9T/5T/tv/d/8X/Sf8EAL7/nf/U//3//P90/00Av/+D/xkAvP98ACn/3P/J/yMA0f/r/3n/kf8kALv/nv+UAH7/cgBW/8AAH/9zAJz/HQDI/xkAfgCc/h4AEwD4/x0AK/+7AGr/oP+EAKH/JwCZ/wEA/v9fAMv/EQCEAC3/5gC8/38Ayv+z/8EAh//WALP/zf+1ABcA1P96ANP/WADx/zcA8P+ZAFcAPAAsACQA1v9DAJsAFwAEAZD/rABG//gAKgD9/+IA0v+VALX/AwClAFwAYAASAPv/7f/N/7YA3wC5/xIAxP+HAOH/KwDR/ysCAP7VAN8Asf8B/zcBvv+l/9YAgwAI//f/1v/gAAv/WwHI/qEAhP45AKn/PwHz/xn/4/+c/mAAev8YAFkBv//A/0H+dwAn/x8APgDwAGD/aP4gALz/RwDl/4sAGv8y/wUA+//uAP3+8P6gANL/y//D/1oAd//3/qX/MQH7//v+AAAvAHP/f/78AF0AqP8Z/qr/gwG6/s8A8/6PAK7/Q/9QAZn+F//K/7wBEP+zANb+rwDf/pv/PQA7AEQBq/5Z/3MA8v/t/s3/3f8QAFgAXP8vAJAAGP8pALj/PQCr/7MA+P/R/xkAx/5lAIAASwDc/yAAg//N/3T/zQCY/6cALQBtAGz/TP///zQB2f/kAA0A///m//MA/f6cABwBx/9O/8cAxwCoAJD/oABuAGwATv/oAGwASAD2/uAAAwFA//YAo/9EADL/HQGKADYAawB9/+v/XwBVAHcA8////+r/nwAEAEwATQCq/8j/dQB7//YAtP8BAJ7/EwCQAM//CAAfAF8Anv+c//n/aAAVAJf/IQBJADYAEf9KAMYAV/9FABEAlwCH/x4ATwAAAEMAEAA5APP//P/W/7D/kwCt/6IA1//q/8L/jABnAPH/DADF/6QAYP+2AAEA9gAfAMj/VgDo/0kATQABAKT/UgCIAKr/QgBFANoAkv6gAE0AjwCG/7D/iABXAJUA0f+HAFMAV/9/AD8AdQBOALv/sQDK/z4A8QCFAFj/5/8NAcz/0/++AKkAzv8kAA8AhwDw/9f/LgB8AG4A+P9IAHAAQgCh/1AAhwCOAHb/NwB9AFQA2/9SAEcAXgC+/z8Awf+ZAOj/dgAYABIAw/86ADQAIQAKABkAIgDS/7UAxv/u/xAACQB0AA//mADT/8z/Vf9jANIADP/L/y4AZwBI/1D/wwAHAOf+DQCQAIj/vP9GALz/5f/L/7f////Z/zL/gABo/7r/5ADd/vT/9v/G//z+0QD9/7j+XgDU/xAAX/+8/4AAV/+p/6X/fAE1/4P+IwGo/+3/9v9n/zUASAA2/0H/bAHM/8H+mAC7/3j/zP/s/7P/ZQBUADD/YQAAALb/sv/M/2cAKwDw/pQAOQB4/+7+9AG3/hkAXAB5/0oA5//r/3kAc/+N/xUA6gBF/wAATgDK/zwAT/9AAGIAs//A/4cAjQCO/uIAUv8kAV4Ay/64AOr/cgCW/6YBb/73APb/1v4sAXEAUwCw/0X/gAHjAM/+8gCyAbH+HAEtASMAgwBXAFf/mgL0/4AANgFZ/+AA3QER/x0Cl/9XANkAuwDE/6kB8P/v/cADOP/RANQAff66AWEBIgA9AYAB/f2/AfcDEf2BA9D/Ef/DAa7/7QAcAR7+BAGzAt/9EwCWArr+xP84AYX+awGI/joAQAEYAGEAmv9LAQoBRACu/kgBlgBm/7cAr/97AC0BbP/3ADUBbv6q/4sAjQE5/0oA9f4yAQYBuf+VAXwBJv0UAQwCQ//x/yn/NwCnAWb/a/9NALj/DwDQ/1kA7P9D/X0Anf/t/McD6f3J/sMBLf0/AvYAyf3fABgCyfrsApUBI/3PAaL9MgAEA9n7Rv/OAoD7p/8MAnf+LQAo/wP9HQDSAI/7YAA0/m3/+QGN/KoAJv8j/p//TQFF/aP/LQDd/eMAp//P/tH+eACJ/80Bgv9c/+f+rv4y/yv/AgCVAcH/lf/6/yb/DgCG/s3+zP0K/mb/Cf8S/qn/c//9/i//aP1P/VT/0fym/cD+mPwv/1n+V//L/hf/Qf/S/2gBqf/h/vn/tP8s/1//wP7aAPv/awCj/yX/cv8I/58BSv0bAdT/Zf6dAhwA1/46AKL9yACQ/wL+LQGJAFACCwLnAPcCRwFwAMYDogAmASYBNQAxAej/hwB4AUz/SQBV/s39owEz/Kf/wf8LAGQCEv4SAPb/Xf+dAH3+8f0TAE7+AwBoAvD9o/9J/EECj/8J/0P//v/aAEb/igJeAdL+EgAmAYYAX/7p/xEAKv/+/LkAogDU/kf/x/6pAa3+agAJALwABwAn/+b/qwCOAYD+1gEoAS8B4f6XAHYCnv80AMIAVAKMAHD/vwD5Ac4AzQB2AMoAXAEM/8sC6wBdACgAswDdASv/tv9QAbkADADz/i4BIAAVANP/tQDx/3r+DgC+AbAAI/+a/wcCZACt/kMBCgDC/+n/z/+eAQAA/ADd/zABMAHb/xYBVQLP/2cAawBmAVEB1f9ZAcsBfABwAOgAcADH/+b+OP+GABL/bf8s//D+Gv/9/p3/1f9y/6H/p/6g//z/Qf/F/2AAXQDG/8X/tv/S/o8Azv/b/f79TAAxANn+Zv/R/pT+Ff0J/lf/Df7I/df9c/6z/ZP9Yv3L/ZD+8v3g/Vv+Rf7G/nP++f2U/eT9QP6f/Qz9cP6i/rn9l/3D/Tj+T/3Q/VP9aP3c/GH9Jv7Y/RD9T/0H/iP+Qv10/YD+9/0Y/vH9Zf6O/hv+1v1E/xz/nv9L/3n/Wv8//5f/xf+0/+r+VP8U/yD/VP9H/4j/4f47/5b/jP+t/5f/EQDg/7v/KAA8ADcAtQAdASQBnQFgAewBTgGeARMCWQLCAlkCEgMcA3QD6gNsBEMEngNABKEEbgTPBHYEuAQ9BUUEhwU5BckFaQWiBB4FgwVABcEENARlBKkEZASqBAkEgQTqA+kCygJNAlwCIwPOAsAA/ADGAKMCFwIwAMf/ov+R/1H/Zf2U/WX9LvyK/UD8v/xY+3j7w/xL/OH8FfsQ/Ib9Vf33+5z9qP18/ff8vfwC/kH9Vf2m/jj9QP3Z++z8zf0v/cf7TvyR/qv9Ofw8+7b86v1G/Fv7Hfs5/Hz8hPyD+3j7gfyX/PT85vuO+zD7+/qE+ur5oPnm+Jj5mPnG+Kr4vPiU+Cf4xfdL+C35Tvpp+xL8YP1k/tX/EwHYAXgCFwMeBNEEzwW4BkMHwAewB60HOQcmB8QGEAaUBXsEHwSvAxsDrgIEArsBUgHKAJQADgDj/9r/EgBUALIAVwHxAdwCRARPBRgG8AZ3BzUIDgmyCRwKtAo9C8oLLAw+DE4M9QtxCyQLZQrxCRgJMgiAB6wGVgaqBW4FuwRiBLkD/gLLAoECfgK0AXABOwEuAXIBDwHhAM8AawCx/6n/q/9D/wP/zP6G/ub9X/2d/B78aPvR+p76G/qW+jj6KfrW+dP5ivm/+Xn5Wvnz+C/5N/mA+Zj5j/nf+Zn5zvkw+vP5wPll+Tj5efmr+XP5fflC+YH5XPmq+an5VfmJ+X/5WPlH+af5BPpP+m/6MvoW+l76Lvo++mz6Yvpp+r36U/vg+3/8Tv3g/Tz+ov4L/1b/tf8ZAGYAAwFUAeoBLwLaAmkDzwP9AxEEQgRDBFMETwR5BIQEewSfBNwE7AQIBRwFKwVfBVEFOgU+BVQFTwVtBYYFVAU/BWIFgwV/BXEFggVzBWUFngWhBdMF4wX6BRIGUQajBqcGCgd5B8QHAwhICJEIrQjMCPMI+ggRCQYJ8ggCCe0IlQi1CHEINwj+B5EHYwf/BpkGRAbdBX4FKAXVBHUEJwSSA10DHgOiAiwC2wGNAVMB/ACzAIIAMADa/3P/PP/O/lv+N/7r/Zf9H/2c/FL8//vE+337J/vZ+sL6l/p++jf6CPpR+iH69/nt+db52vnG+dL51vna+cP5v/nX+dP53PnD+eL54vnQ+eb51vnS+aj5fPmH+WH5X/lw+Xj5Y/lm+XL5a/l6+V/5PPkn+Tv5RPlv+cj5Gfp3+q76HfuE+9L7PPyt/Er9tf0i/qj+Pv/L/2MA8wB3AQsCeQIBA5ID/gM+BJUE4wQCBTgFTgVxBaEFqgW4BZwFgAVlBUIFGgXtBKMEiQSTBGQEPwQHBAgE+wPzA/8D5APzA94D7QPuAwEE6gM7BGQEfgSGBL4E/wQjBUQFXwWWBaUFpgWuBbsFuQW9BeAF7AXoBc4FzwXQBawFogVuBTYFDAXFBJkEWQQIBKEDWwMtA7gCcAL5AYIBMQHcAIMAJQC4/2D/Bv+w/mr+Cv7S/aD9Pf3v/KD8WfwQ/N/7l/tp+yP79vrD+ov6WPpE+jX6Efrr+db5sfmh+Yv5jvlx+Yr5fPmA+Yb5hvmM+Yj5p/mz+bv5pfml+aj5l/mX+Yr5a/mH+Wz5WPlP+TT5FvkT+Rb5EfkL+Q/5D/kd+Tb5YPmS+dP5Hfpz+sT6HvuM+xL8p/wn/bf9Of7N/kX/3f9XAOAAaQHuAXsC1wJiA7QDFQSJBNkENgV+BZwF1AUQBigGPAZGBlEGVQY3BhYG4QXXBdIFnAVzBUgFDQXvBLIErARtBFgERgQTBCsEEgQIBC0ERgRcBHwEngTMBOAEHgU8BWYFjQWqBdAF5wXvBQQGCAYpBicGIwYjBjsGOQYzBjIGBQYQBg0G9gXdBacFYQVEBQcF0QRoBCEE1AN0AyQD7wJ9AhsCrwFdAeEAowAQALf/Y//x/pD+L/7Z/W/9Kf0I/c/8k/xi/PH7qftB+/H6qPpp+gn6vPmQ+WT5Nfkn+Qz5JvlJ+Z75rvml+WD5Yfn9+P34ifgc+OT3jfdb9z33//a59lj2OfYC9pv1v/Ud9Qn12vRz9Dj0J/T28+7zA/Qd9Dr0hPQg9Tn1HPaD9gn34Pew+GP5Pfrt+qz7XvxT/Qz+yf6z/0gAJwHUAZYCGAO3AyEEYgS5BPEE+AQVBRcF9wToBMgEnAR4BEgEEQTbA8sDlQN6A1ADVANCA1UDWAOKA68DBAQ7BJwEAgWMBRUGsAZIB7gHPAimCCUJlAnzCUIKhwrRCg4LFQsvCw0L+QrkCrwKhwo4CugJuglxCS8J6Qh0CDkI4gejB2IHDwfSBpQGZwZGBvsF3wWaBW0FMAXaBKMEMQTRA2QD5AJuAsUBOgGhAOP/Lv9p/pD9zPzd+yf7VPqJ+cX49/c595L2vfVG9b30JvTR83DzXfMe8w/z+/Lg8vvyHvMd84vzqfOf8+3zJvRN9J/0pPT19O30RvUy9UX1aPVd9Un1d/UK9VH19/Q39SD1vPT59Mn03vR+9Yf1Sfbq9lP3jfjm+H369foj/Fb9WP6R/64AagGzAnMDagQ2BckFpAbVBk0HnAevB+YHxAeSB1UHDgeeBkQG3QV7BQEFpwRKBOYDtQM8AycD5wLyArcC0AK7Au4C5gI1A1UD0wNGBKIEOgW8BU4GyQZfB+AHXwjJCDAJdAnpCQ8KJAo/CjcKHwr6Cd4JhQk4CfwIlwgoCOQHXQcOB64GcAYrBvQFugV+BVEFOAUIBdsE5AS0BI4EVgQrBM4DogMoA7sCOwKiAekAQwCN/7j+9P05/W/8l/vm+vj5XPmM+PX3MffX9jL23PV09TP14fSc9G70WvRi9Ej0p/Rv9OD01vQp9Uj1oPXe9Qj2Xvbc9sv2mfd098D36/fc9xH4/vf79xb44fcp+OX33ffg97v3CPhU+OH4O/kC+mf6bfvJ++v8bv2A/lr/SQAnASwCxQLRA3wESwXoBVgG1wYOB0oHVgdZBxkH7gaNBmYG0QW6BRkF/gSKBDsEyQOZAyYDAgOqApECVAJAAhgC/wEPAgUCBwJCAmACvAIOA3oD9gNqBNgEVAXKBUUGyAYkB7oH6wddCIUI2QjOCO8I1gjICLAIfwg8CAsIxAeMBzsHCge+BnQGWAYqBvEFzAWoBXwFcQViBT8FJAUUBdcEqwRrBBIEqgNPA+cCWALXAVIBrAALAGv/pf7y/UH9hPze+yP7i/q3+Sn5qvgT+J73PPex9j/2CfaQ9aj1aPV/9Uz1hPV/9aP11/UE9jD2Y/bd9hH3Nvfl93f3TvgV+Gb4VPhK+E74OvhN+KX4H/iA+Cf4Q/iY+M34VPmx+Zf6IvsK/L/8jf0T/lD/3P8IAV8BTAKuAl0DRQSPBDoFqAXKBT4GUwZTBm0GAAZDBqkFjgU+BbkEbQRQBMwD4wNjA0cD0gKsAoECDwIEAuUBkwGWAXIBTQFBAScBPAFOAYIB0AEIAm0C4QI/A8UDJQSpBNYEagXBBQkGdQayBvcGSgdMB18HSAc/By8HCwcBB84GkQafBloGSQYRBuUFyQXOBcIFswV1BXMFSgVGBTcF8wTBBIIEQwT5A4kDGQOXAvwBgAHbADgAYf+z/hL+X/2h/Ov7EfuP+gX6fvnJ+IH42Pcg9/72dva59aT1RfX89ED19/TL9Kf0rPTe9Iv0SvUN9Tz1ufU59tj1NPeY9pf3iPdG+P/3MvhM+Db4JvjK+FD4ffjA+E34SvkH+Yz6Jvqn++/77PyN/YL+Ef8NAOMADAK8AnIDUgS1BNwFUgYHB0kHiAelB7EHuAdmBxEHxQaoBvgF3AUhBeIEZAR0BCQE3AOVAyUD5wKfAl4C/QHoAaMBmgGWAYkBXQFVAY4BgQGiAbUBGwJYAqwCQAOiA/EDfgT3BGoF8QU+BpEGBgdiB6IH4wcHCBUI5AcRCOAHqwekB5MHWQdfBzgH4wbaBr0GjQZOBlwGAwbOBdQFuAWLBZwFLwUHBcYEhgTuA6cDNAOZAg8CdgHlAB4Abv+H/sP96Pw9/E37rvoD+mn50PhV+I/3Efd49kj2jfWB9Rf1JvXb9N30d/TJ9Er0+fTx9GH1qPW09Rj2R/a29s/2/fZj96/3evco+CL33/ct9673effP9zn3uPdw97f4vvjT+az6GvtE/BT93v3Q/sv/qgAMAlICqwPZAx0FiAVmBuUGwQe1ByIIEQjwB94HhQdUBwIHdwYiBnkFMAWZBE0E4AOAA9sCuwInAt0BdwExARgB4ADNAKYApAB0AIEAiQCxAK4A8gA4AbUBEgLMAgMDqQM+BLkEGAW0BQ8GWgavBt0G+AY8B30HUgdpB3cHNwcmB0IHHwcPByMHFwfuBucGwQaLBrQGfgZjBlAGTAYhBhgGIAbOBW8FcAX/BKUEOwSnAyQDfwLtASYBTACD/5b+nf0F/fz7NPte+sv58fhE+JL3q/Zt9pL1NfVr9KD0kvNf9D/zBPQU88Xzf/Ou8/zz0PMQ9GX0fvS79Ez1tPS59Yb06PXv9Iv1QvWB9WL18vVE9bn2X/Zf99j3KfnF+bD61vuw/Ob9H/9+AGsBDgN5AyMF3wVlB5oHQQlDCYEKVAolC6UKKAt/CpQK6wniCfMIlgjfB0kHmAZaBpQFGwWFBB8EiwPaArICJwINAm4BkQHaAOUAqgDXAJsA6ACXAPwA7QCbAcsBbQLoAmsDEwSJBOEEOQXWBe8FfgavBg8HCgdyB6MH8wcECCgICQg8CBQIUQgdCEcIMwj2B+UH6geGB8MHwgfeB7UHQQpzCNQHLQrLB6gIRQeXCRIGwQZsBMQDmgE0AaX/l/64/Hj7yfm/+GL31Pbv9eT0jvMH84fyRPIC8rrxm/HG8CPxZ/BU8KjvY+8g8EzwuPC48L7wMvHd8GTxHfEB8BHw4u7P7pPuLe7A7iHuS++x7tDv4PC28Sj0WvXu9335FvzO/kgBJgVzBkcJNgq/C/IMOQ6gD10Pmg/6DwsPfA6LDFgMRgrHCNsGcwQ4A3gBuQD9/yP/0P6f/c/9Y/28/TD+uP7G/3UAJAK/AloE5wReBukG/gY3Bx8H0geEB0cIjAlbCkkKYQljCNYHswaHBjMGdwX+BIEEQAT/BK8EHQXkBAEFtwTSBDcG4gbHCGEKEQuuC0ALSgzyDJsN1Q1/DTQN2wyXDGgMaQxbCyIK7whcBygGbQSWA24C0QBT/6j8Uvug+YD4oveb9XH0A/O08ozyKfKm8tTyXvMk80/zk/JX8zXzffPF86PyCPNW8g7zHvO/8vTyD/Iu8t/wDvIW8F3woe7z7VnuE+xg7drqMuxa7KjscvBg77Hy5vPC9o/6cvtpACoD/wb+CRwLmA2RDv0P3hClEVQRdBAxEG0P0g1PC2oJlAeeBOsCAgCU/7f9R/3O/H/7z/u8+l78dP23/aD/+wBUAyMFtQbuCA8KJgv7C54MsQwLDWAN9w3yDaAO/Q3eDFMLBglKCCoHTwYuBkEFAgUKBCwDIQMWA3ED3gPOA4sEtgUyBzoJ+glrCmsKaQqkC6YLWww2DK8LxQtACgkK4QhlCNMHwga/BQ0FWQQqBN8CKAF4/9P9Sf1Y/Mb6nvlw9wT2lvNb8pfxo/Bj8f/v+PAH8fXxhPKc8nzxU/HQ7yXy3vH+8xL0l/It8k/wovCI8D7wgu/l7S7uyu3T7vbsHuwL6aHnludm6JLsA+6u8KHwLfPn9Vb3/Pyu/6ME+gb9B/kLxw2NENMR9hDGEJsO1w2GDr8NZAwPCk0H7QRhAa//kP6Y/Yb88/qk+vj6dfvi/ND9Xv7T/hwARAPMBUgINguNDGIOzw7LD+0QQRGxEUQROBHmEZ8RghA+Dw4M3gqnCF8HmgagBboFAgULBBoEHwPuA8IDtwNGBAgFwAa/CAYKAAuUCu8K/wpBC1QMggyhDCMMDgtuClsJXwh9B2sFcgT+AkYCfwLsAZUBw/8e/u/8Mvti+2r62fke+T/39fZY9TL0nvPn8I7xWvEC8jX0Z/NM9JnzSvPg887yWfNS8jryRfM68n70mfEz8y/wqO8h7h7vQuyQ7Qrp8Oq+6GrsCu7I7+zvSvAt8hH28/dP/3cBxgVSBpoH8AqdDA4PqhDUDx8Pdw5NDsoO+Aw1Cy8IRgRlAdP/sv6z/aT8E/vU+Y74HPlK+gD7J/yR/Mf+AAGRAyEHwAhBCwUMfw2eD94QeRJHEykTYhN+EgMUuRMsEvUPbAyQC8sJ+AiuCFAHeQbxBIoDqgPuAqIDTQNsAzcDTQS2BfQHfwj7CIUIQwi0CGoJMwpoCiUKrAmMCKwHiQaPBRcFSAM8ArIBQgHwAFMABP/a/ZD7KPsZ+uH6cfoT+kb5uvjB98b2I/WT9K7xv/Hm8PjxOfHR8efwQ/Kg8YXy4fC08FjwFfCp8S3wcPLw7/HxsfBP73Hvtuzq7d/rluy+65bsnvA48f3yMfSS9PH33PhJ/gcARAPzBKIG7AjCCvIKIgycC6gLuAmDCdwJJQi1B/4EwgK7AAn+bP2a+0D70vk9+Hz5Ufmt+g77+fsq/Qf+UQBrAu0ElgfoCOkKXAzXDf0O4w/VELIQzBBIEeIRShPqEeQQ+g3cDEQLqQrxCdcI8gdtBjMGEQbtBnsF5QT7BAEEpgSzBYgHPQedCDUHwwYDB2MIQwgtCDgI8wU5Bv8FbwYfBpYESwOdAT0BJQGRAEf/Sf92/W796fxG/C/8t/rg+/j5qfqy+En6UfhQ91T27vKt9PPxmvSI88T0ke9+9jTzFu+69lfvR/ec6iT21+wj9B7yd/Qf8cHvaPLM7uzx4fBV8RDwJfKA9Kj1cvic+j/7i/zr/TYBqAHyBCcE+QY7BU8JGQjWCZwHygfxBXcF0wRWBIsCAAJUAFEAcf20/n38Xfzk+ir7b/qo+uv70fzu/Tv+CQASALMBPwM8BAkF2wXxBnEHBgjXCV0JiAq6CYEK0QkVCkIKOQpQCZoIDQiWBzsHDAe6BqYF4AS6BMwEGQWyBEoEwQNqA50DwwODBIUEDwVXBOgE/QMhBPoDjwM3A7oDFgM7AokCrwG4At8BIAHX/tv+5P99/g4Aaf4b//H87f2G/b77wv7T+6P/hvuV/Sn7yPsF/X/7PP7t+aX7vfm7+1/6+vqR+kz5n/kO+E75Svgv+V34i/id9zD3xfcE+Nv4FviW+Jv33PeY+CH4cvhr+NX3YfjP9yn5Lvdk+Rj5IPvk+of8XPxX/Mf8gP2l/lr+OP8X/17/lQDHADQCAQKpAosC0wKGA48DMgQ5BLoEqQT+BPUEVwWfBegFiAVvBXQFLwWkBesFkwWCBQ4GWAbQBksH4gbaBVYFlQUZBl8FlAWdBIYElgRIBSMFTQVTBYAFcgXEBC8F7gQTBSAFCwW4BIgEkAQRBTsFUwVfBcwEiwSoBI4E7ARxBDsExwPLA2cDZgMSA+8CIwIUAn8CbgNPBKgELAN1AZUAJAI4A1cCVgDK/gf+3v9NAasB3f92/hz/z//cAK4Aa//8/Q3+HP+R/zD/N/7l/bH9Bf9Y/wH/1f2B/Y79r/6b/tL9ivwq/B/96/11/mD9NfxB/N78Hf6f/VH8bPpt+vr7lP1n/c37sPms+Vb7rv32/Uj8x/l1+S/7Bf5E/tD8RPrW+ab7dv50//L9xvts+5788P7u/wL/Ff2y/OL9JgA/AV8BzQBBAPgATwKgA04EVANBAxMEZgxWFk0RNAwVBA4LogeMAGABvAnZDWMMcgP8/xD+mAYZCUACmfxP+3wAuQEJA1EDoQMEBFYCP/+Y/04CEwXbAycDxAEgA3gD5gSgA7wClAJ6Bc4DPAOp/yv/6/7T/uL9XvuK/Jj/cwEy/936evmK+yv92fri+Aj53fwb/LX6+via+oH5xPt1+vn6jfoK+2L6Fffu9mr4WfwE/ND4k/aR92j6+frY+af5Sfpr+oD3XfX99DL3DPeO9ej0BvV29hz28fY3+NH7eP6r/vP9mf5eAJ0CPQNkA8cCdQMqBCQEHwV3BtAHpwc0BlAFNAO5AqEAogCJAA0BUgC2/vn9nv2b/sH/UP/J/rL8n/y+/CL+df+I/10A3wD2AWEChwMABSEG8gUMBu8FngYhBkEGZQajB2IIAAnQCLII5ghMCYEIdgdoBk8GrQUBBc8DEgNlA+UDOwQRBFQEjwTrAy8DhAKhArQClQJ/Au4B+wFVAeMAVgAmATECFgI+AfT/GADp/vf91P6pAfEDlv9s/un8qf86/2r/Gv3D/Y/+kv/D+5z6xvpK/Pz8s/r6+Of4VPl0+SD4gfji9pj4qPaV9rrzBvTE9IDzyvPi8a3xNPEN8Yryt/Ei8+7wxPHX8Qnxu/SW9Vr6pfp4/vcAVgK4BpwHqwnLCMUJUQkSB1YITgdYB3EFvwX7BO0CpwKiADb/i/x4+3j5dfcD9+j1fvY599T4APqf+gT9K/9DAR4DwQS0BdIFeQZmB/IH5Ai+CS4K9QlMClgKVAoVCvsJ6gjKBzAHpgW6BCsEGARlA3UDxwMhAz8DwAOABIkEpQRhBAYEUQRvBBMFFAWgBXMFeAV2BS8FbgXTBAUENANSAsUB6QDiADsATQCs/17/xP6s/nj/F/9o/53/PP8R/6T+dP9Y/6z+I//x/Zz+F/73/Zv9kf29/V38L/zw+rL5M/h191L1C/R289LxE/GG7zH00/BT72zu0PGl9e/vTu8X7vzy6fKJ8171wPYg/FAAhgaWCKIMMBFYER8TZg93EUcM8QzMCIkHsQSOAM7/lv8UAMf9w/r9+Tb4BvhX9eL0tPL187zz0PVB+Pb6pP5YAgIHBQqDC24NIQ6/D5QO4w3OC8oKPwmsCFEHfgYrBpYFWgVhBDIE+APcAvECnwHnAf0AtwEdA+4DiwWkBQMHegjqCVELqwq5CnMJ+giyBxIH7gURBdoDbAMxAzAC3AF/AQwBHgGwAIYA0f+T/+P/2/9tAFYAhQDjAZsBJQGAASUDHAKrAcYBywD6APT/GACL/i3+3/2L/Df8Wvp4+kX4VPcS9iH0qvSe8e7zXPHt8qjyJPKC8x7yofTx8G/z+vD37+fvE+/08Jnyffey+ND/DQJECVML6Q9/E7MSuRT7D9wQBgz0CXMGlQInAYP9Of1W+tP6ufjV+H/3xPY19g30PPUM88f0LfW69i/6ZvwvAW4DyQfvChcOChBCEDsQ/A6ADmALngkzBp8DEAJi/0r/8PzF/Dn8ivyl/hH++v7M/+EAmgLhA4IFzgaQByQJ8wkYC98LyAoADIIK4gmZCDIH6QaRBFMEFQOXASAB5v/5/4X/2/+e/6//LADf/6QA8wDPAT0B6gFeAm8CSAMxAzUDxQJZAzkCrQIyAp8CaQGdAEwAVP5B/+D+XP5g/Qj8Ffzc+VD58/dD9oL0pfN38a3ytfDF8pDy3PJ39GnyvfX28vzzm/Lc8dPxre0J7hzuSvEp9p35Ov6iApYILg5OFNEW9RePFCwV3BKPD0cL5ASOAvH9mft6+Sj4n/dj9g73Rvd79i728fXm9Z/1rfVJ9h34oPoC/cEA8QTvCKoM3Q/JEecSohOHE2gR+w2qCgkHegTKADn+cvtM+Yz41ffx+Nv4EfqV+239/P+SAQkEnwaJCOUKLQyrDb0OjA/PD60PEw4sDSgLgQrTB94FuAPaAToAmv5P/Sn8Jfwr/LP89fxW/g//1wCpAc4CmQMPBBwF1AS1BfsEPQXyBIIEcgRoA40DWgPiAp4CyQGPAVYAsP/e/n394/wb+z373/lx+f73MPex9iT2MvbB9EL1z/Sb9XP1ovVv9UD0JvUw9YT1nPQf8jLyavEH8TPvzO0y7DTtR/H79Tb5iPsLAkEGmQ30EJETfRSqEkcTlxGQDlAKRwQlA5n+lPxs+WT4lvfB9sz19PVv9kz1PvWm9ED1UvX59dH4hvm3/CX/KgOuB00KsQ0MD1IRgBJ/EgARAQ7RCt0HEQW3AWn+x/ow+XT3rPb/9p/2n/fc+A37Hv5pAEQDmAVLCHUK2QuPDbYO1Q6PDtENDg1DDNsKtwjnBu8E0gLSAI//Nf4//N77S/tU+5b7e/ua/LX9af9JANoB6QKpA44ENQV2BXMFWAXKBNEEfgTSA20DGQOmAt0B0QF8AbUAeQBa/7j+xf1H/aD8vPvK+kD6nPkm+VX4QfgO+L73bvfw97v3J/jr9yb5bPjb91D4Cfd59ST1IfSQ8X3xc+4t7pDrfelv6Dbr/vDU8hf20vweAmoItA3sE2sWqBXGFMcWshUeEWkLjwhhBswAJf7Q+7j5A/h19e31bfU39AbzkfKe85LyqvKf9Of2AvnQ+7D/qQQdCawMlhDGEgsVSxZKFsYUFRFJDkEKlgbxAoT+S/tB+EX2dPUc9cD0IvVq9gj5kPsl/scAdwPvBmkJuQtGDn8PGxC4EKMQSxCNDiANDwvhCC0GZwMgAQH/Zf2Z+376UPpN+oT6U/uK/I39aP/EAEcCagMnBB0F0wUzBv4FpAWnBaEFEgUPBXMEIARUAyUDrQLoAWwBLwC+/z3/H/4q/bX8Gfwf+5/6hfqT+Wj5C/mK+PX3k/dl94T37vds9/z3Z/ga+C/4MPin97P2o/bT9OXz9PGH8L/vZe3260zp2OYN5njqvfD+73L1E/sYAn4HVw3AFAUVERUZFOsYKBQbEV4KngnTBVEA/f6Q+yb8oPd19jf3ivXW9D3yv/OV8tTx5PF79On2z/fJ+xr/7gQ4CPoMJhD+EbgUnRTAFQ0TMhDSDH0JjQaCApL/hfxA+jL4tfed9z/3OfeU+Kz7Hvxg/iQBoAOEBngHeQofDGkNOQ4mDxEP6w2bDMYLtAojCL0FtwK4Af3/Hv5s/Vr83/wz/Jj9af4G/x0AsQAyAsMCcgOjA3EEaQR8BE4EqwT+BPAETQUhBTAFLQXyBB8F5gNAA0ECeQHJAEj/lf5R/TX94vvi+xv7yfpH+ub54vmc+T/5zfh3+Bf42Pcq+E/4UfgC+e33Jvl3+O/4efeE91/1avTE8gDx4e8q7ZzrKulm55vm4+pN8ALwffVJ+moApwZwDEwTmBR6E0YUoxeiFNQR5AxXDG8IfQX+Aq0BrAE+/ln8J/zF+cL3+vWq9QT0VPEr8bTzEPZk92b6Ev6hA9MGVwvzDUkQohHCEYoRTBAZDsoLtAk0B+kE1gL0AaQAIf9R/gv9r/yO/Kn9dP17/KT+jf+zAb8CewRuBlAIigiTCmgLHgsACsYJWAkXB/kFLgTmAqoBz//W/4QAh/8kAAkADgHkAJsB+AHiATgBCQEIAdwAqgB+ABQB5ADKAasC6ANRBCsFDgVjBb0EugRjBKoDhgKfAd4AUACK//v+dP6b/Wv9zfya/ML7XPuA+pj5x/hF+Pn3nfcE98j2bPfI9iL4iPfC9/P2QffU9Tr1WPRn8vbxW/G97jnu9+w56wzrIOsE8inzvvQH+zj/LQQgBlALYA84D50Mdw+3DrkNFgucCiULAQfgBpIFewYCBU8BWgCv/vb7uPlP+Ob2i/V29Kr1XfcP+fz7PP64AOwCQAW9B4MIcwmKCU4J3AgPCRYJAAlTCHMICwiXB4AHIQatBfgD+AHhAFf/u/9MAGgAPgDLAvkDgQX0BvgHOwkzCM8H4garB7AFsgQJBFkE+wIcA68DYwQ9BEADdASJBFUEVQORA9gD0AESAlwChwJXAugBMANHA24DOANpBOADgQPcAnYDywJjAlwCPwK0Av0BOQKdAlkC+wFWAfoAMAB1/4n+CP6w/bv8iPxc/ND7JvxR+0n7FfsK+vz58fj5+Db4vfcE+Hf3Cvei94b2H/et9r32+fbM9Jv1PfT787fxlvLw8XXx/++t9Av1+/V5+c76///L/RoBtQT2BNACsgWNBbsGxwRmBqIJCgfnB7MI4glECRgHugfDBrwDFAImATIBvf6T/Zn+n/6a/ZD+af/s/y7/iP7T/87+S/5c/rr+Av9p/iAANQEkAiEDwgPDBPkEwgT8BLIEJgTKAx4DmgMKBJoEjwQiBnAGXQbPBkEGdQYUBWcDEgPVAcgA8v/z/0MAhv8bAJQASAEoAdsAZAECARIACQCR/0kAKP+N/6cAcQBYATYBqQJ9AscBOgK+AX0B2wAkANcAyv/q/0QAXgDfAIAA1wAwATIAMACg/xj/jf6n/bj9Pf0E/fL8Cf2b/dz8Xf0M/QH9zPwR/ET8x/vX+4370/v++9H7UP8A+G0BA/vx/Bj8tvtC/fb5M/vD+tX7y/nu+Vv7oPox+uT47fo++O74oPcc+G/4dfYv+Rr4rPn1+QD7B/0N/Jz9df5w/6P+JQB0ADUBkwG7AXUERANcBekEZAZlBjEFRQfaBMoFxwNgBI8D9ALXAtcC+gIIAu0CDgL6AlgBjQFJAR4AawA0/wsATf+I/+n/DACoAKoAIgF4AU4BAwF6ARQB6wBaAdAADwJtAbcC5QJfA0UE2QOrBHoEuwRsBIMEJgR3BBAEXAQjBH8ENwQfBPEDzwMwA+UCgAL5AWUBKAERAcQAyQDDAP4AzgDaAPEA3wDAAF0ATwBhAPX/EAAqAFUAegCZAOwACQH/ANQA4wCNAGAA0f/O/33/Tf8h/xn/U/8h/z7/Kf9M/xr/5v7h/o3+f/79/RT+B/7Q/d794/3h/dX94/31/eb9v/2c/ZL9UP1b/R39T/1U/VP9ff2e/az9yv20/dv9w/3Y/cj9tP38/cD9//0w/jD+n/6F/s7+1/7K/tz+x/7K/qP+qP6D/o/+ev6J/nP+rf7D/pD+Bf/5/gL/af83/4D/mf+d/+H//f88AFEAgACyANcA2AAlASIBWgFFAVgBYwFsAWsBZAF2AXMBZQFaAVgBbAFSAUoBWQFLATgBVgFZAUQBUgFJAWMBMgE1ATIBLQH9AOUA4wDnALQAwwDDAKMArQCKAJQAggBtAD8AWgBLACoAJgBJADIARQBRAFEAeABVAGMAWABAAFUAHwAWADEA6v/o/8L/tv+c/2//eP86/yr/Fv/e/vP+2P65/uT+2/4S/xH/Lv9c/0X/av9x/0//ff9s/1L/ff9w/2r/dv+J/4D/Y/9e/2D/M/8y//H+Ev/b/rX+wv67/qz+ov6k/rf+sf6T/pL+ov6x/pT+uP7Y/t3+5v4I/x7/Tv8//2D/hf+a/3j/rv/B/7n/3P/k/woAEQAhADIAbwBkAH0AlADPALQAwADOANYAwQDXAMQAzADTAKQA1QCrAMgAlQCaAMcAhgCfAJ0AkgCIAI0AiwCGAKwAqwCUAMsA3wDMAOAADAHwAAgB8AALAfYA+ADmAOcA8AD4AAsBCwEbARkBDAEnAQgBDgHmANkAxQCbAIYAjQBHAGgAKwA1ACMAFAAjADkAEQA2AA8ABAD1/+r/1f+v/6P/hv92/5D/g/99/5//v/+c/4//n/+W/4j/dv9t/2z/af9e/5b/i/+R/5n/p//H/8f/xP/g/9P/3P/P/9r/7//D/+H/7v/S/9z/xP/f/77/sv+j/4L/e/9v/03/W/9y/1r/g/9h/4z/gv+D/6H/nf+n/4T/gP+d/3b/fP+T/4v/ff+Z/3T/f/92/1r/Tv9i/1//K/9b/z3/T/9N/2D/Zf9W/4T/bf+G/5//l//B/7r/rP/m/9z/3P/l/+z/9P/1//3/DgD6/ysADQD3//3/9v/5//L/8v/4/+f/0f/2//L/7f8TABoAPgBBADYAmwBmAKMAnQC/AJ8AigBtAGsAVgBFAGQAMQBEACgA+v8HAGAAJgA+ACEAJgAjADgAUgBeAF4ATwBVAE0AWwAeAF0AcwAqACcANQAjACgADAAYAA0AHQAWABwATwAoADIAZwCRAHcAjQC2AMAAjgCGAHEAXABRAFkASABRACkAJwBRAHMAeQBzAIQAcwBuAF0AbACGAJAAmwCtALEApABjAMwAtwCaAJ8AjgCRAH8AhAB6AFIAVABDAEkAZQBEACkAJABdAFoAMwAeACkAMAA6AFkAYABhAHEAWwBNADIAEgAvAEEAGADx/9r/zv/R/+T/5//0/wIABQA2AEQAXwBIAH0AjwB6AIAAXwBpAE0AXgBHADMAIAAeAPL/8P/R/7D/yv/7/9r/z//l/+T/3/8DAAgAFAAqACMARwAUAB8A7//z/9H/of+u/73/wf/O/9n/3P/3/wAAHAAWABkAEADL/wQA/P8BABQAAgANAAUA3//f/7v/yv+w/6T/m/+M/6b/tP/R/9f/xv/Q/+j/9P8tACkAEQAMAOn/0P/z//L/1v/F/7D/sf+R/9X/w//A/8b/zv/Q/8H/3//c/+P/6f/m/8T/zv+2/9z/7P/N/+f/5/+9/83/0v/s/+f/AQD2/7b/7//3/+//JwASACAAEAAWADkALQA6AEYAJgAfABsA/P/b/9H/0v/E/97/6v/f//j/2v8AAPv/DgALACgAJADt/yAALgAeAAYACgDq/+7/1f/D/8D/pP+6/8T/0P/h/8P/x//9//P/+f8DAPn/GwAuAAMAFAAOAAkACAAKAAQAzv/6/xYA9P/6//X/CwACAA0ADQAhADgAVgBmAH4AhQBeAF8AfgBiAD8AIAAcACAA+P8lADAAawBZAIcApACLAFsAYgBFABUA2P/6/77/vv+k/9H/6//i/xsAIQA0ADMA/v8cAPj/2f/h/67/4/+2/+j/8P/7/xQA7v8LAAwAzP+f/6f/mP+W/7P/r//a/8b/AgDe//L/4//y/9T/0//A/6//uv+//8P/1//f/9j/zv/w//L/yv+//7b/sP/c/7b/of+8/9D/AwD2/0YADQA/ACsAKQAYABcA8P/7/8r/1f+v/7f/w//K/5T/lv9//4j/nP/u/9P/4v+6/8X/3//b/8P/3//f/7z/2//E/93/t/+Z/5X/vf/P/8L/1v/T/8r/r//D/6P/sv+D/7X/uP+O/53/jP+D/4z/d/+c/67/sv+w/5v/5P/K/7L/t/9M/yH/b/8j/w3/S/8O/4D/jwBACFwGIQX2BVYAEf2H+t/3pflB9o/6A/x/ACIFrQKgBwgG0gRAAcb9S/4E+rr5j/tV+lP/3P7jAsoFTQUWBhkDgAOgAD38gfuc+fT57fls+ar9Xv5TBuEL/ApIDAoLfwVMAmv/WPsZ+NP0M/b2+UoBDAPLBJoK1QoCCAkFvwI8/wP6qvmd+DH7Ifte/aMBegfoB+MGAQeQBoYD9/+b/O77V/vv+RL+4wLfBlYJ0QpuCgEJ+QNE/yj6rPZw9NzyR/fv+cX/ogKjBiAJ5gh1B6IG5AAUAAv65vhC9+j19PrV+3gAHAY/Dt4M5hA7D6gHwQMa//D3JPcf8Fb0cvJr+1wA4gA7CeIGBwqJBxwE3wGj/J35cPqp9hX6J/kL/0sCowRfCHcHPgc7BlkC/v8c/cv7svgD+XH9UQMZBaUKMg0CCvIMjQZmBlj+FPq99mLxQ/aU9lr5wf+yACMHTQjtCP8I2ggSBwoESQIx/+z63f4WAdgD0gRRBlkEiwZdBeUENAJk/Bf7NPZh+uD3oPir/Wj9agKJArYC3QHMAIEAJP5S/er6aPpn+e/9pAEmAQUFpwgDCFgHHwdhBfAA/gDf/Kf56fkW+Rz7wfqxAaIA4QIqAnsD7wBJALH7jvoQ9335lve69gn8wvwkAQQC6gMABcQCNgEu/2H8LvmO96D1Wvit+Rn+KgBKAVwEowO7ABABzfxs+CP2vvU79Rz10/cS+t77PABHA83/aAOPAef+av1t+mv54/hu+u37Svsa/l8B7P/WBZMC1QI7AVEAEQEo/cz4QPrk9bj5pfsX+2H+NvntAjADtwN8AgAADP/r/ej96f1I+xL8vf1e/ssBjADxA3kBcAOfAkv+qP5i/En9A/1K+oP/mfo6/3gAkQMtAGX+rwPX/xf/pgJX+6H+e/itA+b9//4DA/j+qwLcA+EDnACMAgsCvADK+owCf/jx/+v8DgCH/B/9qAM1AUkFigTiAoz+hQQ1/i8DvvzbAfX4Lfxp/6X8AACbBB0BkARIA4wEdQBlAAIE4wEL/4cDDPdm/VX/lQNyA93/agP4/agACQIYBUQCEgGnAV4AQfy9ANT/gQYw/X8DlvnD+1j+KwEgCKEBHwWl/XcCTQGrBo798QJI+z0DoPfmANP5iwMC/5sJcPyABl3+9wcHBnUBtgaw/LEDpfm5A4z5wgVhADkFffhXBfH9uQDoBCsCNP39/IUCnP7L/x4FJAYC/m8G7P6vApf9nwStAdv9kP34/9QA8fu/AosBPQN4BGwEOQRA++EFOv1DAsj5oQOj9UMCufqGBTX47AK3AdYDbAJqAswCpQIrBu//AAPw+b8CVvspAzf8SQD6+1UGmf+bBZ753wJB/Y3+0gSi/SQB7fjaAUD/DQPnAzECHvxq/1D/swPu/lYD0v3qAAn7gAfd+TYG7fwSBoX8cwLY/jkBfAAUAuj+8fxrAC79SABXALAD1fxi/q4Amv5DA7P8rQkX+cALlfp/BPf3eQW+AIoC1/yP/sX8J/1kA6AAtwR7/uMAdAB8/Z0Asf41ANMDqPzWAPT6SQIWAXsC9wFEAZwAMgQVAawEj/1u/Vr/YAHQAK/7pAC89xkDxP/DDEb5SQ3g+dQJLfqjBij8+P/2/oD6qPyx+wEA0f96B2MJMAPeAc7/swZ2ARH/CP2F+uH8Z/nY/1v3AwVT/IsKhgJIDfz+SAfeAhEIqfr0ASD3Tvtf+ZD8Gfzr/xwC9Qa6BC4H1wI9A2ABKQNfALD9DvnO+wr/rPoGAAP+1QmwAEgFzf6oAgX/dQMB/vX/g/pr+b377f9NACcFd/0vBLABiAQV/FMEuQH9/zz6Pfum+Wj9WQC0/zMEjgG9/joBwwSx/xQAif0jAzD93Pyp+BcBoACuA74BpQbs/TkCVP9gBL7+xgHU+m0BSPsJ/vb5aAAPAu8AqAPb/cICKP0zAc765f19/Pz96/w6/pv8YvvAAsEFEAc2AVUF2/xhAPb7agIC/ZH87/qQ/cb6CfnQANkB7QEV/QUEAAD+//n+OQD2/gf8Av9uARMBdf6nAL0CbACFAeEApP92/sn+Nf4r+2v80f1v/737Xv9//2UAgP4WAkcAUPxx/fL9tAAx/en+CP5D/5H86AIOAmQAv/7MAe/+W/rF/On89/9i/F38df2k/Rb/QQCOA8X/lwEW/yP91/09AF//H/on/Qz7Uf7j/NcDeQKpACL+YwCJAUEAUQFK/zz+R/rw+lv78P5BAyIDHwBa/Nn9YQGcAkoEYAIl/2b69/tXALz/JwBZ/xsCt/tL/Wj+6gMfAgYC9ADR/Pv9x/4yAXIACwIY/SH+7f+qBrv+vgGpAkwD7v13AXgCKQB3/3L/a/2M/y0AmP6A/sABav9w+0wA3wR5Ak4AugDuAIr/IgPLA18BYAFx/+3+9P/FAZkAF/9PAB//Cv43ANABTgNXAMT/y/8OAIwBPQT3Aq3/bv1aABcAQAICAyYB9f/n/vr/af1d/xgChv9b/gv+hv9Q/a3+LgNM/mv/if/A/5f+x//bAO38oQBFAVP+2v5l/wb/2v3u/+//hPxL/uX93f2A/ob/4/9G/mUAtAAv//v/1wDh/4v98f1l/vv9P/+y/2z+5/3t/ZP9qP3P/4j/8P3c/Yv+E/8e/rz+UgBk/q77lPxq/of+Af7m/l/92P3F/rb+//7o/sP9H/yK/G/8Dvxb/KT8mfv9+sj7WvzH/X/+SP48/p39wP6eAJsAogGSAAYBqgEgBEwF6QbGCMoI1whdCr0KcAucCtEJSQgAB/cFHgY8BvYEDAUfBYwF6QUrB68H7gefB48HXweABywInQcBB80GWQXABDgEVAShA9cBNwGp/nP+mv1H/UX9fvye/Pb6G/zg/On8Jv1q/On85vum+wH8tfug+yn7z/wo/Rb96P0U/ev8EPtu+436Nvmb96D1HfSc8+3zqfPL8tXymfFG8UDyzPKQ8l7xEfB87gHuBu1t637r8O7V9Kr4swD9BwsOFxLTF2Ab3RvQGvITJRBGCi4EwgA3/J/5/PTG87X1uPeO+tn7P/7b/oEA8wGgA/8FiwQpBIgFJAeDCPUJoQvjCqQJ1giACPUHdQVVAk//nv3K+0z7wv0B/3UAAANHBqsLiA/jEsIWQBmIGe4YCxnHFg0UkxGkDBIKoAetA1ACAQKPAVoA1gHSAqUDwgWfBwwJTQpvCngKCwplCrcItgaVBeYBvf9W/Yz8Q/tT+V75Rfkk+gr6KfvT/PX77P2W/Pr9AftB+1j4MPYW9gXzPfJP7/bvQO5x7Crueezc7Sjs4+ww7Izq/+p/5mLoQuvz68TvBveg++gAzQiuD3gVxBr0G+gXARfmEgcJ9QWx/bb4xvBP8TDv0e8U87vynPix+Nv8Kv0BASQDDAHgAyMEJgYZBnUIgwmYCq0KJwoYCuMH4QTqAIn+7/oY9yb2vvQz9QX2e/gN+2L+LQG/A1wGDQmHCkILRA41D6YQXxG0EqEUyxObE8QREBKkDZYJiwe7A0UBZf3s/dP99/1CACQBrgZ+COAJ3gpZDMYLuwl3CdwIiAYEBDwEwwOKA58CDgMYAtUAkP7U/HH8+fkt+Dz3RvZb9a/0mPV19Vr2ufWV9oH3a/Q99HnzrPFZ8j7w9e+p7C7rKeqx52zoGucc5H7kOuQV4dfnPuzK7Or2O/2QBM8LRRNlGeYZxRoGGGkRhA3CBd77Yfgg8UDsueyv66PuxPGJ88X4m/vB/hcBuQGuBqkFmQVfCkcKQQqiDdMLWwv2CPwGwQOG/+H8LfnP9Sb1JfZG97P53/wcAD8DAgViCBYJLgnlCI8Higa4BpoKXglsC8APkBB+ElMSChRNEWEMYQuBC1oEpgiXB6EE+QcFCL8JkgeDCQsKwQNhB1QIxQWsBxwLOAn3CQ0LcwsECjsIJAnhBcMDjwTQAcgA+f/d/W/8x/s6+jD6Mvqd+R/5vfm7+IT3uvar9mv09vJt8r3uiu+a8d/v5++V8p7vw+sJ7qXpiuXJ5rPihOH84GTm/ux37QX4ggFiBD0OyhPQFYEZXxWREkQPzQaFAon8+/Qz8jTuJu3d7Gbup/Lx8rH1Cvyn/VMBVwXiBhkKHgo5DI0N5AtHC6UJwAWcAv//1vwY+S/3TPYU9Xr1tfgO+zj+BgEPBAIHQQiZCR0KKAlVCF8GWAQQAyUCcAEXBCoGDwZfCxMNrw7rEHIPkA8wDakI4gYlB80LAQeQDGwNNAnVDvIKIwdwB1ECOgAoAOMCIAfKCDoNVBCoDl4PZAxuCvwG3AIaAv7+i/6WAH3/rQDK/3/+Wv0C/CT76fqX+eH3LPk5+Br29PeT9L7y8fGb7k7u6uvh6XLr0Ogh6eTtFuoR68HtX+6X6Y/pLOqU4ovrvuxM67b52gBtB5EW+xe5HschrhXVFQYNs/4q+33vOulH6jHnD+sz8PLyCvk/+3z9XQHnApsEOgWZCPUKJwzlD0AQMQ8yDuUIawWz/035+Pbc8sDwMfSv9WP5uf/LA6UHLgrNC34MKwwtCm8InwadA4cCxgEXAH//gP+y/kwEvAaeBvUP2w9xEsQYxBTAFQYTNAreCcQB1QGICkIBsAadDjIG8QxYDYwJYQn1BKAELgREBSQMPQ1ZDf8Pww5CDM0KagnSBXoCBQKVAEMBXATDA0YEtQKXAAz/UP0w+436KPi79Zf13/Qd9LLzrPLV8tPwG+2o7uPwT+uI8HXv7enA7+bsdusI7WDmX+mU4vHg9u9A7J7wjgFFBAEOxhh7GZsfgRmjFDkQowIw/Z34Ku2g647qQunO7Entn/Mw9y/3WPxJALkCEgeRCmkOQg94EBQS4Q94DNgIYgO9/Gn39fRs8nnwUfIO9S33UvsEAMYDKAZiCIcJQApUCfwJHgl6B9QFqgNOAGf+bfxL+ib4FPif+YL6MgdlItoLIiGoMfQIAx+5Fhz2VgZt85Tv1Pfx8Y4QMgaWCPwffAz8C8MPIwYdBLQB1gZxBVgIyRFDDZ0N3AsABqYE+/2d/xQBL/3WBVQF3wZcDEEEwQNY/8z2BfdC8yb09vJL86L36fNk9/f5KPS576ztl+xK6grozO937EzmqfOw65DlsPRU45LlZOXk3C/pQOs/7z8DOgiAD8oeQxxMHfAcXRHKCJ4AZPSg8Yzr/Ocv7TPrD+3b8ovyZvdA+hH7wwBDBGUIcg0SEzsUIBVpFO0PZQqGBJH9jPZB8jjuPe7j7z7ypPg4+7P/lwRRBokIJQriCZQLjgtgCskL4gnHBp4E5f8L/ND4HPao9nP56//3BfMNmRbuGdcdrR9XFscRCwzz/VH8fPlC90f9GP94BeAKZgm2EMoOAQqRDHcHegW9B5EIsgqrCwMM+ApkB0QG4QO0AV8AJwGyAjYDWQg/C7kKOQwDCjAE8gCW/Zr4g/d/9rf0N/UH9lD3r/eu+P/16vO58aPtcuvg61fsq+3K79rrWvGV7w/qse+f5mXme+Mb3TbiBObb7/ADLw2yF+MluiF1IawfIhHkCBP9Ie+Q7J7m8OWy6zfrI+6c8STxi/Wq99f61QDmBDsLBRJcFxwZXhk0FhQO3ASY/aL1/+6S7HPqeuxx7x30Nfsv/hECsAWFBQoHfwo9C60NxQ4GDjkOSgppBuQBU/uK9Yrxme8084T7VwJiDL8WmRw4H7gd9Bg3EOoH1wHz+uz37/q4/B//JQUSCesIBwmYCqIH+QVUBjIGZAcyCe0M/AtPChILjwUmAYMAXv6Q/toAGgKLBrQHAgqvDO0IoAeUBNf/X/8//uX+Rf1n+4j6Ofbx9PzzWPB28czvRO6f8EjuE/Gm8s7yk/W58FfvEe9n6MjuoOop5fzpIOJ54lftEO+j/AoMYQu4Fr0cJhhyHcMWvg0iCd75LfVF8mnqj+5j7GzqL+6W76nynPeR/PEACQUBCmgPmxOLFlYWsBNmDj4HJAJF+0X2CPQ/76fv2/Hl8mr4LvzT/noCegQQB38KRwyBDgkQgg2tDIwKXwXfAcP9V/jJ9cD3k/xbAVcJbBN9FtEWPxjqE9AMTgrGBID+Jf7+AJcB4AIrCjMLgwhACikIxgVDBRMF6QVQBDMIigrjCLkKpApeBtQD9gMZA7QCVwQ6CG8HEAk6DAUJ4wZOBlsCq/6m/eH+avyH+0D+E/v69zr5MfVU8b3z0vNC8i/zKvRL8ufuD/AU8t3qjO797nbkSvDh7OTm6e8m5Gbh/O1L6Zn3FQ76C/4XkiRsG2AeuR2FDS4IoPvi7q3uXufQ6arwIOoV7wTzae+u9rf8y/0YBZsK5gx3FNMXAhdOFjQPuQaAABX4cvOn8t7uD/BD88HyMvmx/ev92gKdBEUEkggsCxoNDxD/DXsMNAqCA9j/3vvG9gX5bf3m/UIJkRFRDmcVexMICk4MwgUoAT0E2AETB7UISAnJDZEIHQaoBJH/CP6iALkBrgSzCTsL8wszDTcKVQh8BiIDtQNKBCcEGAdjBmMGrgbwAe8BLQB5/vb/agCDATcCwQFG/776kfjR+I70MvV79GXx3PHg85TywvFI9r7w6emX7srp4Oft8EnqW+su7vPo3emX5WbwAPRc8BIJpwppDWUhBhuMHLob2A/8CWb8kPe/9Rrqn+2A8AzsuvCC8/rz9PZS+mP+3QG0B2APGRKMFMYWhBPZDskIAgNv/Kb2QPX/8XXyNvab9gb5qfzi/bP/pQE3BBkH8AgjDGQN/gxUDIUJXgV4Abf+A//WAZgDFgvODWIK6A+WCT4GdAi9AU0DyQQOBtoKNAumDmoP1QibB5AGvv/SANkCU//QAtEGPQePCDsKnQoUB/0FPQcYCDYHmAmpCtoFkgZmBdwAQgLx/4r/7P6g/ckBdf8rANUBKv5M/A36LvdW9gr0svNv8qLwZ/W58Y3uD/Ns6lTrxfDj6NPsIPGY6gDvb+116c/n8enM8Nbvrf/eC8cHdRlxGJIWvxm3D9ANVAHk+YX6wu5B8M3zEO4/75rw9/Cn8kX2Uvyp/80DZwpmDWYPNhEVEWoMIwfWA3/+Ovp8+ZD3kfb494z2Xfi0+W/6AP3a/YwAcwPIBSkJvQq8CgcKLgeaBGUFmwf8BTwKJgw/BBoIxQNP/+YCEf4BAQkEewa1DfMNiBAkEgIL0giTBhUANwAm//f7hwATAgQDGwafBpUHoQYTCGgJhwpqDcIMIAv4CfwG4AOPAND+bv0+/OH8X/z2/QX/rP1V/wD/R/xM+yT4GfWO9av4CvYL98T0euys7k3pN+177KzqYfGX7vrt8e4R7D/lf+IL3N/kgOo0738N+wnAE2gnNxW8G0QaNwoKC9L7U/tL+qvvb/iy9PPsW/Eu7Wnrau9R9ef7dAGuC4AP5hOZFYgTwRFGC84FUQKw/KL7c/wV+VX73vnO9435RPjy+TL8/f58AjgGqQpEDEkN4QxECh4J7QlBCYAKTQ2DCBEHSgWG/mcBrv9VAVAIGAp2EQcTvREVE60LFAZ2Akf+9P0AANAC+wNwB/0G8AUyBlYFigdmBz0JwQyHDbgPjw+OC2MIKQMxAVL/Sf6YAaIAXgDzAIb+7v0y/cX72vqv+F77lvkb+qT3kfRP9e/x/fCi9JvvX/Vb8wjpJ/EJ7Ejo7O5u6EzpT+i13w7nCuu26ev9LQnXBFEZfRuJELwbJxRzCq8IoP0+/NL1R/AQ96jwJe1Y8/PuPe5B9W/5H/1kBWEL4w04ErgRERGADmwIIAY7Asz88v2q+ij4E/vt9zv4cfpX+I/7NP46AE0FiAd/CoYMqw1mEwkTJhS5FEAKmAgqAab8Xv5C+84CfgSdBrwQzA6lD0YQFQ1FCT4GRQZoAkkDWQYxBoMGvwZoBokCoQKCBL8D3wYeCkYMvwwSDW0MQgjkBhwFxAHYAJgApv41/er81voa+sX4ivcI90n3Wvea9+H5ufaF+vP1rfHF9l3wXfL78SHsQO4m6JLov+OR6Bnlm+Jm4fbbaeyv7pv41xjTDVUbHyNnDcUcVw+lBxEIX/VE/Aj2o+5P+wHxwO/87w3sv/Bl8w399wDZBREPChCrEwcU2g6qDuID4QP0ARj+qQIW/nv7//ud9wv5Bfku+fT7w/ysAAcF8QpwFiUXLRwPHzMSAxXnDmMFSQvQAtYETQSiANEIbwPIBS0IBQRVBuUIkgqyChQOdg6vCXgJAQeKAyACyAEnAzEDzgYvCoEI+gq9CvsEZgZvBC4EDQdHBAgDjf49+bn4UPSG86/2l/Rq9hv4/fgC+wr8UPem8Qzw2+6k8Tr3ZPOb+EXzUe0Q8PvoLurp6aHhhd/K3azlZfFwAOoNKQ4sF8kOCQ9jE9kJIA9RBsj85gAT+Xf8zfsH8lTy7+kw6prvCPOM+6L/oQTnBp4KOw2rCz4MyAbZA0AExwHYBOUE6f89/iD62vZM+In3g/i9+rj/bgeUDCEXfxrNF2gW3BBvDN4LLQnQByYEnQMJBQ8CAwZTCNoE4gVkCH0Ilg2tD3oPhQt2Bu0Dfv7Y/TT/KP9C/38BcgMWBH4FKwaMBL4DkwSOA7MDuABcAEr8AfdS+AL0ffH79MPxiPNB9bLwIfKR8ebxc+028pH19PW6/OP0N/Np8s3wGfCT5Hnpa+Nn5FjoBudZ8cb5EAg5CVAEqBj+BU0THQyIBjkOawMd/7v+efcb+lP66+rE95rrbPdR8pv9PvuZBI8BcQRbB1EFYwlqBDMG6AEWCO0AtARlAdsAQv7m/SADKgk2EXgViRSEFUwQ0A5jCsQHuQatA9MCFwVsBMUG5gZzAkUFpgQZBy8Maw4PECwScQ+PDykMqQmnBoUCEwEbA0gDIgRXA6gAnf6p/HH9OP0d/sz+4v1J/Nj7xPvY+wn8+fvh+GL57faY80T3UvXq9pzzs+pk7tzuBe5c9AvybPWf8d7uuPIu53DrOO7i5c3vzfVB89D3Hv8gAyQDSAn+DjELOwywDYAIgQVZCVYFRfy//Vn8nviQ96H5EPqS95n6X/ul+qr+igMPA2IDHgenBw4FcQVaBlAEqgc0DYwTFRJRFDAVZQwJD8QKvwjaBscG6gaCA1QH9gZIBgcEzQP3AZ8DHQfYCHEMBQzdDSwL/wlGCYcIlwhUCOcIWQjxCJYHygUbAtv/TP35++77hfur+zP7n/kI+QL4AfjV9zH3Cfke+fz3Lfbn9RDzb/Jr8+X0uPDy9EX6D/tI/JnyoPPP8Yft2/RY7PLrC+5m8Fbuwu4A9e3xSfL38gf0MfcD/9oDtAjTDMIJJw69BgoE+wX//3L+rf6kAIT+GgAZ/hb7tfq999b5ePlj+zUAigTkCaoVCxptGOwbdhQoEzkTpBAHD+0NiguPBtQGrANgBGUCSgIrAo8CWAe3CNULUQtNDDoLvAgsCTsIPwc8BtYGGwTcA08DYAG9ADX/sgCnAIsBPQPZAd4Br/74/F/6aPq/+NL2Vvee9zX4ZPph98byIvTl8S3xpPT89Mz2y/iA96f5V/fN9mD34vTg9srz7fqD8WfxI/Q47drvWe6f71fvxPTl8wr2wPuv/osBMwR6B0QJGQ1UClAKoQlWBrgDRALHAIf/vQGcAAAAtgISBPQEBQeGCVYMMg1lEcIPphDOEO0Mcg1ICtcKxQqCCcUJnwmRCQ8J0wg3B5gITwhyCtUKaAwnDSELEAoFB18GBwTCA6ECIgDUAIX/QQCy/5//9P+G/4AA2QArARgCEwB6/8X9MP1b/Kz7VPwx+gH80Pmk+mb6mPY89xPzEfVD95727PYy9LD2CPal9b70QfNp9pP2lvhK9Ov57/TF9mf2dPWZ92v1gfhM82D4ivco+0b7IPrg/VH66QCj/g0EYwQuBboFXQPxBh4EZAd/BekFUwaiBCQIXwUxBn0FrwirChwJpQvGCdoKPQqRCS8KwwhgC3UIFgr3CH0I0AnHByoIBgWNBt0FTQY1BlkFCwYxA0EDdAFkAX0AggAfAHb/zf9r/hYAi/2w/iP95P25/x3+U//U/f79hPy7+376J/uR+vb5Gvr5+nL3wPr2+NH5Wfis+Wb5Mvt0+3L40vsO9az9W/UG+0f5jPgT/BT2N/yQ99T57/Oh+SX0CPjm+UP2RfoZ9jH8PfYY/U35nPen/Db62v7G/QkBVwCpAtkDhgSBA90CHgRwAtQDlAKZAfECpwI/AE0CQALfBAoEMwfJB3wFxQj5BiYHjAdPBk0HeAd3CSkHKAiABToHSAXpA0kHawL/BCIFhwWKBVkDgAJuAhgBUgJCAHkBbf9yAa0AbQEX/3n9uv5//oj91f1/AIkALwPWABwCX//A/ogA0P6N/kT/HPzs/k3+sfsW+lj7afhG/Xn+RPzW+vf6c/sa/8T7+f9n+ln+WftW+5n+cPzJ/6X4qwA//RH77v0m+ecAL/UJ/kP5yv1/+pX8m/5g++P9Fvo9/bH/WvtK/1b89v7s+YUAv/+1/xAAD/7HAbz/gQKkAS4DLgMT/uoAtP//AoL/7f4RAk//DgN1AR8ChARUAJEA4gFmApQDvwGCAaAEnwKCAH4AmAOsAccBagA1BUYCbwViAowDwQV0+skCsf0HBGn90gBdAez+iAGn+rsBLP6y+/oCL//qAt0ATgGeAq/5owjA+A7/nQE1/xP/+QK5A1j58ALs+Sr82f7X/zb7wAICAdX5t/9k/gT/ovklAUP9CgIoAXn8/wCl/1L7wfxXAyz+uPvxA+37qgCA/2L+EwK+/fAAif6zA1z8hPybAXL7pAC+/f//B/hvA637Bv+QAv/8gAAS+1oEnvr5/b0APv48/73+egNcAaD8VP3DAQ79T/7I/QECNwQ39xUDsABD/4L6NQJF/33/CQFq/gP+agUf/hX+Jwqt/eIAOPvjCTT65v4nBKz/ogDp+qQDqABH/ZP7mQGpArn8cAJW/j8DlP4aAnn9LARkAQH8qwTiA3b+F/p+CHr8owG4/U0GuQIY9vsG1/5tAlb8ggYXBvj6MwYI/iEEtv4p/RUASQGFAYQBqf7QBCQDx/gbAwIH6P4uAPT+pQaG/bj80wW1/+gASwEG/wj+kgRk+vIF8AGoB1r1PQUICX3vahDM/a37rAYi/AkBLQVB/cf/Gv9NA23/Jf3IBn/+QQNHAL3/jAXK/dwABAdG+xUFzP8OBSX9rgF9Asf80gKZAKP6ygWV/y0EJ/qZCWACxvrABS76dwk38v0Kx/bWC1n1OQdo/ckBtgl+72oQ/fkFAqAAuwIG/SQBzgFeAAr6Kwyr/Ov6Fgro+gsAjQFrB0n17QZhAmn4Vwjg+xIEH/m8BYb9z/u8A6cDWPj3CV4Bkv0RA9f/twaq8zIQ+/R/BggDyPqIA6L9sglf9M4HCQUD+eoBLwqj85UFlP9k/p4AOQFZABT+2AJNBAL2oAnFAer3EAky+kgD4gH691kGPAH8/a8BWPwpCAP6EACg/u0GC/2//PQB4AJb/2MAQf04AX0IB/AxCwIEbfpr/M8IKf6+/5H9TQf//DcCW/vNBzj2tQqP9usBEQF1A/r4MARLAPwBgvfWBlwAL/41AcX9kQNAAiT4BQdb/c8CDP2Y+yIJtPl3/KYFVAK8/MAB9wAm/r4AWP7ZAVD++gRt95UHxADj9v0LNPMHE0XvUwZjBZb38wSW/CACjgKC+h0KHfpNBEIC4fxG/NgEWQiA7bEJwwO0+lwADv0rCw/0cv9uCbb8K/qcBgoAQgMw+OILcPe4/2sJBvd9A4sB3AKb+jb9nguK+2XzIA1ABdzy+wIJB20DWe61Ca8M4ewpB1AB8/9hBPHzMBB68YkHOwF99/cI5gND+Nn9bAoE/tf7uPgUC1YER/A8AgIPnPbJ+2YDeQJD/EsCcPaaEwzuKQP0CMjuXhSa6wEP2/v2/kMCw/oICWP4AQTA+a0Gj/1x+jwBAwuv8C8Dyge3++L99fnWFZ7pNQbWBVT4xQOf+IUMz/CqBhMGivaC/noQoOtZCm79ggW894X93xDA7FoIa/7W/A4KS+2NEdr6/vONF4fiiRhV8YsCzAfu7xMSP/N0AzsD/PqzBpDzrQjEBIXvfwwUAP/9LgCx95cQkfDKAT4EhvsIBhXzQxHl8nYBlAg67/QNrPv9+LMHNPsGBUz8avwZCr34xvujCrPvWBLN79QHIAJL9JIRIe4iB6QHnu/IBgwHcfP3BiP+4QBvBf/sEBU3+fT38QNVCHb1Tvw/DazymAX6ALL8TgKn/TIIs/QgBS0DUwDl+WYAOwsd9vr5rQv8+kL8AwN9/gIBpfiFDJXxEAs6+oIBiwHZ+0kAbAI2/8P7PQfx+rcDnvi0C/H0Dgfs+8MAZwPx9+4IV/iJAhACQfkMDWvzNwXLBOj2tQdu/Vj7PQZy/en97QRf/LQAvgGb/wL/UAPI+WkF6wC8+tMDmAFO/ccC3vlyCCT+SPifDNDzkAZPAGj7qAER/tsLT/BMBQ8LD/mP9egO3foIAf742gP0DOns/gWCB7v3w/76CLf3awPyBpb4zv+PBMMA//nz/uQL7PUqAGP7UBLO8uD87QpV+yYASfu3Bdr/8PkXBbX7age6+i7+YAJV/yoAjP3EAEcE3PiVBv39KQG/+n8HBvlRAGEGEvcoBc8C8PbZCQD3Zgbe/Vj6Hgh4+PMGJ/eyCDf3GAg4/X/7ZAVQ/k0Bb/h6DJv2j/yNDGv8nvJKCSUI5vMiAooGjvvUALcCmPmLBG3/Gv0c/FoLPfYNAIkHZfov/gQFIf53+hgEG/xHBJn5qgd0+VYDMQL++c8FCf4Z+QMMIvjO/wkEvPpcBzD2uQeR+fYB2v+H/7P6FAoy+un79Aj59w4FDPp9AvgBsf+g9KEOwfVYCDr0XQdV/vwAlPqrAigGQfWVByX9twD8Aqf4MwbN+wcE2vp4/00F1PiyALoBOf4JB8XzPQhVARz7D//q/iUHVvev/lQI5/agB6X6hf2LCdb1ZwPD/MULpvPHAW0JRfrN/O4Dc/2oAYL6dgIs//f9AgTp/Df8VA2j7oQOm/VPA24GqPHyDbL2dggQ+GYAFgiZ9jAFovxKBt7+lPPHFNfwEgRTATH/EQJc+M4Iv/wIAL8A0P8xAcgBVPgNCa/7zP1sBEr7AAin9yoG+f23AX4Ck/bsB34Bi/ob/3QD6gI/+34BFAN3/cEDbvpDAxoDsfpfA+X7CAeT/R/7Vgpo+J0IufeXAHMNNOxzDOD8rgT09XANbPNyCKcAwfOXDgn4dwKE/TEBggcR9S8GLP/WAM756gay+7UAAgNM+s0JL/hTBOwBRPlQCYL48f5sB0v3owRUASb/EP70/SIJrvbHAWL9EwhE94QCSADhAdADVfL+DFH81/2oAgH7KQcN/RIC+fmqBnkA4/kSA4j/swEF+8UCBAGrAnH6RAE/ASMDkPr//VQCsAWZ+nH8/ghV/JL+kv/TASv/h/+o/cAFYvuhBOb5+f7LB7n4yvtUBVAAuf4M/6kA3gi08x8KO/U4Cnb/z/IbDt/77f5r/ToEMwIZ9fIPUfEsCqn40AUm/pj1ERPq72IBUQNpBIv1NwNeCHfwJAihBSb2Ev1VCvj6mfvwBDL8qASv97kIVPto++YJxvXDBwj4Bgeq9wQCtgP89rYHNPfmCL/4ogQm/IUBHAQr9rgJCPtF/mIBEQOg908CIwf68u8FWv0qB1rzBwOeCLb0qgXt/HQC2flgAtsDU/ZCAH0J5Prw9GgPZ/gTAgH93v0WDrPseA999H8FmQC9+QoExv9d/e8CxAED+V4F2f5qA2f5/P+rDTXuZw59+Mr+Xwvz7+ULm/j/Bfb+BvoVCi/4WQkX+RwCRQSt/F4CKP1vBED8uwRk+53/tQny9wMB4gCeAW8EDvNaDAT8SADo/1cCn/0WALwE6fVrByIBdvf1COH4Pwlh+MsAKAbJ+icHnfWCCl4AsfhRCSz6IQaE+l0E8f5C/GwL2fIaClr5xgU6/8D60gk18ucMyftv/N4GGPslCLD3Uweb/gL/dAmU8E0Q5vb0AikD+fZvDljzZQfgADX6Zw2e63AT1/b0/c8I0/WgDDHzXglO/or6+wm09aIHKf6S/dYGD/lbA/gDM/jTCsH07Am4/gj2OxFz8JoHVf3FAMICVvV/ELzy2AKCBKL53Afo9RwJ7PwW/VAKGvN3CG0Bs/arCWP2VQZ7+h0BtQUI8pMPQPcLArwB5/iEDrruuQbXBz/vrQ4M9/8D5wDd9/0NffAICe7+d/lRCY7y1Q029jEBXweL8G8Lyvnw/ssEbvJ9Dp35s/u7CVTxzhIB8Q8BJg087YMRGfSXBKIDPPPwEJfwXQd7BWPxdg44+aL/PAVF9zIJyfp2AAUD9fvhA978lADJAxf2qwyr+cX+NgYY+jcHBvqYAeEA3P46BD/14AyW+Yr+bgWf+AwJ1vPRCKH7fwGcAfz3HAz1+Jj+IwN8/kABY/o7CX36df10CG75XgNY/JYGbfsO/oEHNfnsBNj9uv5mAz0AMf4M//ADFQEW/C8BgQbd9gAGDgFKAPb/tP7UCH33pQSuASf9jgNQ/kQDR/4cAigCZP0bAtYAp/+Y/pQC+wH+/JACHALGAMX+AQOA/3kAKgAZAaYA3gLj//D+ZwZ4/hYAmgDf/qgED/xwA6r+AQTi/+/8TQRCADn+JQGr/gcClADY/08AFgDYAFUAtfvqA6T9Nv45Acf+bgN9+7gC5v/o/v8CvfyOA/772gLPANX8ywLR/OcCbf7j/SwC1f0U/w//HQCs/jsAsf6L/nT+cv+//Yv77f3M+/n97PiY/X38JvmA/Ej5Rfxm+f/4A/tn+sL7lfyf/ff9FwAF/x4AzgFY/4UCo/8kAyME+QFJBo4DMgY0BIEERwRxA0oDdQGTA5YBtwLkAUQBJQIuAPcAEv/b/3X/sf33ALP/oP++ACIBTgAEALIBJAAOAJoBMgAzAmUBFwIrA2MCYgNXAkIDJQO8Ak0DQwPVBLwEoQOlBQgFqAMYBfsD5gPkA0EDTQNeA1ADrQGGAlUCBQElAa8AnADa/zoAWwCs/6wARwB3/5AAs/96/w7/SACVAN/+nP9yAL//xv6Z/53/+v5q/gv/yf98/nf+gP90/l3+KP52/aP9Jf1V/en7r/v4+x76Tftz+fD5kfeN9tH3E/V09KfyxfKA8fT2vvbt9wT6FPmR/3P5NABK/gb9egFC/nAIQgP7BxQIuAakC3MFJAqBBb8FmwV0BOUHLwX9BFcEnwOOAu8BgP/H/sj9Of2g/Tv+qP5z/HX+5vzi/eD93/sX/WD8Vv4x/tEAHADhAPoBBgGTA6gBHQLoAakCngPzA6gFXAQiBUAFtQSVBFUDpgIWAq4BnQE3Aj8BVgENAbIAjgBV/3v/5P1Q/qT+Xv58/93+vP9g/1H/QACR/5T/Vv8IAGoAoQDFASsBDwJYAi0CtwJoAi8CNgK5AsACiQMiA/MDmgMgA28GfwM9A3QGSgHPBq8CtgO/BvAAWwaJAiIFRwPeAVIEKQCuA///+AFmAd//AgLc/6gBEgDU/wcA6//j/2z/MwB5AB8AiAARATMAUAAaAPX/DgBdAFkAlgD3AJ0A5QDGAO//GQA3/2T/Ev/g/k7/4v3w/v/9kP1R/qP8a/07/AL8wPyr+3X95vxS/XD+Lfwc/8H75fys/VD6Yf5s+1b9Ov1e++b8rPkY+/r3O/cP99LzCvXa8vX1mPT184P3IvUc+1D5bvkP/jP7Rv9T/zMB6gNqAmsFUQZpCAUIxgZcCXIGiAeAB14FTAfHAzAEEgXcAvcBfgBBAC7+g/7f/Rv8dP1q+677F/1g+wT85Pt1++n8A/2D/UH+Nf+i/0IAPAJVAWwCxAJ7AiMElAM/BJIEkQTWBBAFWAXDBFwEPAM3AzwCkgEhAWMAOAB8/yUAJf+n/mb+0P3W/aL97v1b/UP9Cv75/XD+Ov/x/if/w/8bAB8B2wBPAxsC3AMFBqcDbAgEBLMHswcvBQ0K/QXKCMcGrgdQB6YF1QZeA4EFWQICA+ACiwCoAQYAjwA9/8v/YP5a/t3+k/35/kj+u/7b/kn/wv8FAGcAqP9/AF4A8ADKAOoAUAFzAPsBLAGqAYwBMQAcAfT/3ACT/0H/XQC9/XT/A/4K/qH9Efsb/sP7d/sr/ej6s/5y+sD9fPxt+uX9E/jf/Uf4V/rI+ub3hPrn9fr3fPPf86LzNPQ09ar0qPh1+Mz9GfzY/dMAgf0NAq7/XwSQBAsEeQiMB3ULIQgxCTcJTAX1BgAFLAQnBWECcwPQAuEBjwAN/k7++vr4+6n6KPq5+7T5f/w4/Lb8zvwa/Cr9NPwo/lL+I/9XAQABYQMqBBwEOAQ8BK0DBwRUBM4D2AQ5BAsFrATvBKkDnwI6AkgA0ABR/+3+GP9V/u/+If6H/kn95PyY/BT8W/w5/OL8tvxU/jb+Mv/o/3f/egBwACED6wDWBecCUAXkCM0CFgwEBL4Jsgd8BqkKygR3ClsEmwjLBdsEqwZmARcFugAyAm0BZP+lALT9/v8z/Yn+CP3+/EX9Z/z7/bH8jP6w/NL+qP0K/+L9pf7U/h/+LADq/VkAAf+v//X/l//m//n/oP8P/1//sv4D/wn9kP2Q/AP9G/2F+2L9Hvzw+7f8ffop/Zz56PqW+zb5Of329w38fflI+FP5OvX/9+7yvvMJ89H0nvaB9Gn8kvyo+1b+PgFLAHAAjgGpA+sFPgTbCF4KrgrrCQAKAAydBpgIyQVJBd8GRgL4BUkDxQIeAWf/8v68+1j8OPmc+sL6GPqR+5D8CPz3+/X8jvvx/PH8sP07/9cAywHkAtkE7gMRBacEOQS3BEEEQASaBdsFdAWHBkUG5ASFBK0D2AGSAdIADgCeAOT/zv/0//L+Vf4H/qn9Dfwi/Hr84PtO/VP9Df7v/jr/hf/4/4YBQQUwAJcEHgajBEMKwwJTDVEH3AZYC0QH/AseBNYJhgZnBmEH8QKZB2QBFQMhA00AFAJT/uL/cv4Y/0H+Sf2u/l38OP5Y/FX+AP0C/er9ov3+/jT99v5l/pD+OP6D/1H+Vv6b/mH+V/95/vn+Jv5i/4H97/4E/ib+0f3j/RP+8/0H/RP9dPwE/F/8iPrA/Nv5UfsS+mr6Fvqk+OH5bfdK+Yj21Pcy9jf2NPT489byXvH58aLyiPui9kz3QAEG/A8B9v13AoAE0/ygB5IEwwqRCAsHzxD+BlgMsgnJBv8IZwI7B1kEuAVeBGgAXAQj/yP/xf0X+gL8ePh2+av6qPld+kz5BvyA+nb6sfvv+RD85/yy/YUAcQCPAXACewNLBDADPQRkA8UDmAW8BOUGogYiBesGbQU2BNwDiQJtAbMAMgFNAHQAPACb/un/7/7y/Xb9s/56+7H9rf5z/Q0B8P04AZMALwFgAfwBQAdp/+EJ0AQoBu0KRgJ2DRUEOQkBBzoHHQk6BAYLUwMsCK8EnANYBdsARgP+AAIBFgH3/2gAvv6G/4v9k/3N/YP8Xv1N/Jj9h/0T/Ub9Uv6+/Or9g/1z/Bj/NP22/h//Xf8d/8n+Bv8Y/wr/b/4w/6D/GP9i/0wCpP1+AL/+9P2t/pH7uf3a+n39HPkv/eH64/l8++f2Cvqi9hX3IvZo9c70RfTp81jzt/Hx9nz7LvE5/nn7cvyA/9D66AhY+9wD/AVFBM0NJwDEEGQJywjRDugFBQ+KBM4I1QjoBMMJWwE4Bo0DPwAKA2P99f7y/OX6rPwN+/n7y/na+pX8y/i1/Af6zvqv/Gr60P5l/Xv/Zf+UAIICJAH0AoUCDAOnAxsEKwU6Bl8FRgbEBuAFwwWWBOEEAQOHAyIDlAE8A8UBTwFoAkEBSP/OAOP9cv8s/5v+VAFa/6EBPQAQAwAC5wBKBJEAGQQJA34DnAVwA10GzARIBkQFHAWrBSAEwgWUBPYEwASdBEIEAATRA/YCUAI0AWIBHQELAGn/t/8F/0/+SP75/a79/vy0/Jj82/wY/Ib8BPwr/Hz8pvtz/Av8bv1G/aP9rP2J/XX/JP13/xT+KP6j/bX+ZP8p/xr/Yv03AM/7+P63/CL70f1a+Dj9+/m/+wn7N/jl+6T2vvrp9eL30fZE8wH4pfNF9lT0NPkr+kz1HP8++pP+S/xL/mMDwvwTBFQCmQbzBrkEKQwPB5MJggk0CJAKAgbiCGcHRQfaB48E2wbvA9UCAwMNAMsAnv46/mz+lv3W/X38L/1w/NT7YfyF+1L8Pfxp/Kb9LP4w/xz/bwD2AIsAXAGuAd4BgwIAAxgE6QS4BHAFuwVXBe0E1gTPBNgD4gQjBGkEbQb5A78EEAVkA4cEDwFBA5sBRwE7AiYBJAShAJsCWgKfAQgCqQBcAgQBBQIXAsMCcQMYAtIDLgPZAk4DhQIlA6gCFQMmAz8DdgNuAhUDLwJRAr0BBwH1AOMAEgDM/14A5/50/0b+jf50/rr8fP2q/FD8kvsc/L/72fpb+9v6C/zj+tT7Af1b+7X8ovyC/Bz95vvn/s37YP7//Sv9qf+L+xb/sPxV/AH+4frT/YX6b/yl+8T5r/xT+Tr57/lY9/35MfZm+Pj3BvbZ+Cf1dvi49nT4j/j/+Z76g/tq/Nv8CP/q/UgBfv91AvECDQIzBhEDCAdLBTYGpAfDBBkIYASIBlAFKgS/BYgCnwTyAZECAALl/0kBwP6m/0z+Jf4W/oD9hf14/Wv94fw0/Tr9WP0x/Sb+2v3c/hv/Wf+kAGwARwE5ASACOgKSAlkDNQPmA/oD/wR5BEEGYgaLBHEH8QScBmgFBgWxBtgDgAbtA2kGeARiA5oFYwJwBCcCogJiAnEBAQJCAZgCpwBSAZ8BnABUAWEA+wD0ANYAFAFIAdIBFQHyAcwBFAIVAj4CKwL0ASgC7QGfAZgBkQG2ADsBOQBMAMr/uv/F/3/+RP9n/vb+Jf3J/XP+ufw5/UP9BP0x/Lj85PyL/Z383/1y/bL96fwN/Q3+5vsV/b/8kvw0/Vb98/0t/Sn9y/yS+9H74vpj/Hj51fsu+077ofs3+mj85vjS+hT54Phr+cz5pPqJ+vv9nvvT/rf91v5g/739kgEf/g0DBwH/ApEFiAKnBwwEswZlBYMELgZhA+AGzgO6BV8F7QOqBdkCVgTJAbUB/ADi/3YAD/9IAHj/pf9w/7P/Gv+o/sP+/f2V/nH+G/9Z/8//kwDHAGMBZgGTAZ8B5AHMAXECmgJxA7EDAQSHBTQF6QR1BekErwQsBCwEQgR6AxsECgTHBOEDOQPFA2YCJQJXAR0B5QBNAPYAIQEBARoBGgELAYsA1gBaACcANgCX/8gAawGpAfP/UgIeAq0AMQHF/kICbwB5/2v/pwKZAIj+JQHAAc8ASvz8/5X/jvzJ/if+k/7f/tz9Nf/E/Yz9W/1Z+279w/vy+5X+2/yC/wL91PwV/078QPtl/Lf9Uvxa/Kz+wf5R/gT8jP/y/NX70/0v/BH7O/4w/BD8B/02/Zr9w/sI/cP9pPoj++f7H/yu+vn8aPwb/Aj94PsV/dP80/xo/GD8E/57/tn+uv5UAL8Alv//AIQBTQEmAfwBewMfA+wCiQNVAzUDXQNkAwkDlgIUAkECjgLtAcsBMgHnAT8B1gANAZQAUQCJ/ykAXgCM/xYAhQD5AI0A9QC3ATQAfwBrASwBkQAGAXsCVgFvAvwCHAM+A58DXQNVA1UDDAMwA0sCqwN3AzYEBQTvA58DCANuAssBZAKyAgsB1AEaA8sCWgKbABcC5AHA/28A7QBCALAAwAGkApoAjgC0AX3+EgHT/9L/5QOmABL+pQNQAY//SgEf/owCw//b/W0DWQFq/RkBGgAh/1P/D/56AdAAUf2O/vkARgK794EASAIm/J3+7v9I/t78qv9b/jEAiPqhASr8h/7M/0j8Tv4q/JkAZ/ux/ewB1/54+AECs/5V/On/3/cBAk79MPuOAkb9Pv1T/VX+4P59+vT/rvvO/GIAL/v0/t//D/zt+nz/VP/p+n77uAA9/u37L/8CAA7+MvzhAUn9Sf5zAor9tP0DAR8D0P3S/6oC3/4FAGMBIwKOAIn/bgEdAhH/LwHqASACdP/qAVEC8/8EAogAdQE5AiP+tQSkAIj+hATB/2ECWACRAVMDg/1pA3IB2gCxAxb9qwXoABP/HAQX/ykESP51AbwCswHCAKUA6QGQAmr/8QJmAMn+9wWb/or7vghFAY78VP9kBcMF6/d1/2cJHf0lAFX8vAmn+5X8Kgcd/W0BHQJA/4T/VAFBB+j3T/xbCAoCpvgv/loLa/3e93MD2wZs/Yn6of3jCj77NvlGBxb8lQJF/5/8EgDHAg4AbPgpA4AGOPbZAdL+AQP/+ur/JQO6+u8BRANj+GL/IAey+9f6Mf/oBNsBHfS+AGUJK/wd+CUArwer+Qf8EP2pA8sD5feJ+rUEtgX79275uQK0B+n6uvGmCE0JtvYk9foHEQlu98r49gQIBQX7q/teAX0DbAEi+nj/9QUmAQ34ygFUBv787P3AAeAEiPpkAy4FkvmHAYIErf5ZAaD92wRTAu/8WwB5AmID9P/c+5MCnwn/+Q37FQfcBWD7qfrBCBcDXgCf9b4GVgmy+hX4XwA+FGv3xfCpDLoLWfhT8ocMigo78mD7ZwvvBSv3BPolCWQGjfcH9SEMhgij8vn+qQZaBCr6Ev/X/UQI+/sn+QoBfwoP+Lr6PwbfBxj2Rfx/BKoHa/KC/TgFywLbAWvtjQz8CR32DfXOBsMK0Pba9BMCrhc86Uf61RJt/cXv3ATXBWr+rfh2/awMUPps+W0D3fwqCeH2+PcNCyQAmvlWANwBZAFW/O37AggL+Un8Wgjh+kn+bwEQ/U0FbfwY/G3+qQn69wD7LgiU/YL7GQDEBXv6A/+cBmT66/vRDJL1dv0LArMGyvzx84gL/gZ6+Kz1JQlyDRns4wFxCKMFFfeK+swJgwOL9ZgC/APm/7L/JfxKAbsK7fdT/BEEYAgz9kz6HQsRArX3bAMfAMgEgvlVBRj9afzlC633df/B/u8MzvMU+44Q8Pzi8d8HHgkR/lLuKQ2hB8P2OvkiBqgRnOo1+ewcNPCB9dETqflE+E4JMv72ARb+JPt9Con+uvftARUKvvR5AxgJtu48DF8IkeybDFv9+vsRDJXuAwabDbP1JfM8F4758PVFCmP8pf83BJX29wPZCsz07/yXDkD4CgCJBFvvLBLfA5LluxX/AwruGBKq86ICYwtX8UH+ew6Z99z9FAUi/lMBMf6hAXv+TQeq810FaAep9UUGHwKz8RgUMvbP+6gInvnvCQDy3gIxEAfv1fowEWT+IPSIAbkNrP8N54kS7Att7NT90gizBgz35vsWB5QHXfO/+/gN5P7i8cAFPw4m7PkGtwo18vYGXf52/TIDsQCN+csE4ALz+gH+2wyX8oT/8w0I83MBmARw/RcC4fHVEgMAPuu9DxoHm/UN9lYO3QaZ7l/9FREn/mHxQwa6CrDxowYd/SMDgfp5Bkf+VfzxAcwD0f6g+aUEN/pkDP7z6vtBDpL6pvxR+NoYbulqAbkLpvbdBQ34ogrb9w0DXAJQ9NkQ//aj+kcMt/2T9dsMS/pu/a8FD/l4A3MBsPzf/lwFm/4G/CUDjQEb/e3/JwJ3AqH0/Q+P9t4BFgA6AuT+bv1BA5z9RgHDAnT3rwd5AHj6dQZz/IEBkP53Bin1EAhj/7z/GvumBAoHVPJ5A7gLIvVQAHwCoAIt/VgAyPz4B7/2OAcZ/6X66gjn+fkAyQHF/0H/Xf63AMYEofiqBE8CT/f8DCP5KPWVFwfyM/ZhFIrz1gS492MIHAjv6DkP6Aho640Jlgdz7KgX/eyFCdQAAfg2D4zssAj5EODgoxB7BaLyiAao/wj+4QXS+HADxALU9zMOFu+LBmMHbfYMBb/32RGO8Kz9NhP/7+/8Ug/P9WD8YAl9/If9JAWP/Ob/RgG7Anr5RgCzCtr0aQEKB4X4vP9uCLH3jwIlApT9rwXG80oOE/j7/ZYK4vNHBFwJIe38DzT6lPq6DlDxPgDMEnzoJAcZBq37IfowCv/+IvV3DxL34ABhAZcCEvzK+d0Pw/SB+0sJjwHt8F0Ouv8r89AOnvP3CCX9Zvs8BCUArQLp9GkL7/1098YGDgbF7a0O+gE08rMMZ/cfBcH/f/kCCgj2RAkj+s76WQwn94X6eBEl88T6pRN36wUFvAq/8+4CxQBFBHb58P/7BRv7QwFf/fICfv1bATL51w3w8E8GCQZY9SsE5ACwAjz3KgMUBTP8sv39AzcA+PnnCqbw9wkZBjzuRAuyAUv8mv6F/44IQvdQBRr7ZQF6BsT2dfwCEo/vOwOrCHb0egps+tEAv/xjBuz85vyMAkMDFQLn9VkHlASl/DrzvBC0/Gv5PAMcBDb9e/vfB6T+2vq4A8EAIv6uAdj8mQZA+XEEvwIm9wAKIwB98j0MzQCf9vEFbQOl/Hn+bAAkBPIE+e3SDWD/NP6z/b0AuwN+AEr2OxCZ9BYFwf20AH3/RgEg/QoG6Pqr/w4GMvoaBH4CfPhWAv4E8vyqAHD9bwJeAyr8PQIT/27+KgV9+rX8zg0z863+Qw9g84YBeQQ1/lgAvP8N/asECQVr8KcMhP27//b+w/0DBScA2vfCBpj/a/9bAW75sglY/f35wAY0+uQIzfdMAFUKR/SSBtz+MP35B6LzWAgoAzj4d/+nCO/7hgGn9nULVQPl8kYHCv8YBEz6Kv5wBbYCOvp8/PwKXPoNApD3WAlJ/kL+Wv1wCaP3cwO8AMn43wqz+i75WQok/qD5MgQbAYUG2/EIAtcSL+npBs4F2/mmA3UDNPYMBaIGo/J6C+TzxggUCM3pMxEN/y7yHg91+on7uwfc+BAIyP6x8kMNKAbo66kOL/oeAhb/wP7+/gMHMPTqCvL7evRMFPzyzwJL/SkFFwFD+br+EQ9+7DMKtAWj7WkUufba+o4J6PZqCBf76f+T/l4HCPemBpn2dA3X+X/7QwB9DwHqUwtABRbwCBGr9jT+iQhA85MP1fbk+t8LnvsT/cgCf/8wApL+8f4mAG8Dl/r5AiQHR+wJFGb5jf0xAfz8xgsV+SXyrBln9m/2lwULA3wEXvZ0AK0DggW39pwCHv+iAXkJeO2rBj0M0O55D9XxEAWFC9XyIgKxArUBcQFb9JUJJQBZAezzzwyoAIT7g/wrBGgIU/B/BlUFcvPXEdLtUxCw9PIChwq28Sb9cAwE/yL41v6cCNgDweyrFLL1Pf7kCYb0WgG2Bjr/bP6QAdD1vhRl9/v1CARaCZz7fvl3AV8Kb/eZAKH7zQOdC0jwGf0LDQ/+qPxz+tUInvqvCKb2dvv+CWgBL/tv9VoPdgIK+vb6e/xOGGbvDvQsEnb9swCL998CgwYsAEj8J/TCDcAHEPNg/IcCjg9X+GT01gB0Funz5vBSCfYM7/Za/S74oRG1APjyOv7FAyANpfT09noHrgp1+jj0yAUgCvL8z/Yn/F4LkgNl85r9aAfVDDfuSPsuDvABlfyv8LwH/g4A9uL2wf3CFgX2nPQxAjAPgvm59gD9Jw4F/b/9zvDsE8IDifCq/30DYwg3/QjqDhYiAWT7Cvcn/lcbpOyb9eEJEgEyC+PsEvZ5JEbtvPbuBPcHRgFU70kHtgg29JYMr/SO+hAO8f+y9mf56QrTDJ7qdfeMHtjx3fxu+pgBdha354cEJf/WAmAMHu8m+eQV4vjU/1fvKQtrFNbl2AHrAiIL+AOL4wgS+wDm/3/+tPMKDZoInfGB/xgEGgWG/mr3Af9lCcr/ef8n9U4IXQg29x4DcvVvDOkBp/GtCdr9/wTf/Ir99gOu+5sDTQVc8MYLUfz/Bq/5tPdMDZ74dweY97gAbga1/hYEvvFaCLAIo/zY8uAFqglv+sgBGPbUCicEmPXd/9cFoP2fBb73Z/1pESPzAQKm/xL+vAtP83wC6AAtDNTsBwo6Aun8zAB9/dX+qAxh8nUAhAXDBg3u3QQHDeT5NfuT+nsQC/ro9TYFQACuBjv3aQOx/isFrQE49PEF4QSw/z766/7tA9ICfP/K9sEIaQND8kIHvwT3+BMENf4CAb0CDfu+AQsCFPr7B0v/CfSNEQ73agFR/lb6NBAI9NX69Aqo+TkCvP2A/k0F4PzC+zkHMfo4BSD5XQAlDGD4R/3VBDr9sgMg+WoBhAOT/p0CY/qEA14An/5NACH56QgW+bEDy/sRBFwB1fUeB5MB2f94+k/+swbQ/VwC4fU3Cor9SfnmBFr8cQxT8YALM/p+/nUGvfZPAqL+mANMAKH4dAsy984FE/pk+18HwwD4+u8BpPsIBcz/nADq+vP/wAmB99D5FAX6Akn9J//CAW8BDf9L/X8A//35AiIA9/wSAS8C5v3D/0ECsgAG/XT/Af9M/wgD/v1f+yELt/e4B374JvwLD3fupwyD+P0BcgL/+FgF5/uTCAj7Vf8PAob6QwZY+ZYFSfuYBPj+jf+nAaD+/gPd9m4GZgF99l4Izvp6Bpb87v+YAyH+AgLz+JcBuQLw/+cAN/tIAz8EeP7a/OsC0gKv+XL/+gES/6EB8P73Alr/8wIx/LP/hP9SADP+Rv4kBhb+af8BAmn9xgSM+7oA3v7//y4EqfeGBqf+t/+vAqH8GgQ6/87/jP43/mIBGwIo/5r+7wL7AJUAEf4J/kMEYP2t/jz/tQG5A6L5FAR8AHcAoP/G/QECZv2AAsD8K//nBHb+ngDk/6kEe/26/DgB0P/g/gIAXwH5ALABqf5/ALoBUP6I/9r+9/3/Ar3+2P97AksA/QC+/uD/vP8m/zABIP7bAKABrP9iAOoApf8OAZb+8f4CAZP/rgAv/1sBeQCR/7gATv+xAeb9FwCzAHf+8gD5/7D/cgGX/1UAsP0XAmX/af4TAJoAMgDCAMf9ewHvAJr+UADo/6j/3QGk/VIA0gBaAFMA8/5qAFsB1f6CAIz9uwPC/XYAxv/qAAEB6/8I/0f/pAJa/cIAtv5HAnAARv3VATD/VQFZ/1f/RP9kAeH/Xf7QAJv/LQE0/gz/tgBxAFj/jv6+AIP/3v84/msAFgBX/wgArP4fAnv+/f8EAFf/hgDH/1z/2v9EAUT//f9MAEsBnf6ZANj+vwADAOT/FQAxANsAn/8PAYX+bAEuAP3+vv8kACsBP//x/xQBwv8kAM7/fACh/3sAAgDi/l4B5v+CACMAp/9qAZH/Zf+aAI0AN/95AD8AxP/KAJf/AACyAMn/CAD2/1AA2v9sAJP/PgC5AJ//dQB2/5kABwBp/wUBFgBh/9EAw/8JAH4Ayv90APj/LgBMAH3/EQDJAIP/BgDTAOP/MQBqAMn/MgBPAAYA9v/x/+MA0f/y/24ADwCTANT/6P8IAH0AoP8OAFcA1//NAHb/vf/RAL7/nP9cAMr/RQDb/9T/PgBQAAEA4f/g//v/UQDe/8X/UAAqAAkA0/8JAIMAuv+x/yIATwCW/1MA0P8CAJ8AKf8xADcA1/8hAGf/cQBAANf//v8ZAE0A1//e////OAAuANP/1f9vAGsAt/8zADsABwA6AJP//v+uAIr/4P+cALz/+P97AHj/VAAgAIT/SQDR/wkAUAC+/y0ANwC9/wYABwCq/04Aqv/o/3gAu//X/1MA1/8TAJb/LgDY/8r/JwDF/wkAHwDp/9X/FQA1AJ7//P/X//T/IQCW/wYAWgCh/+z/5v+0/zoAlv+v/z8Ajf8yAPL/Wf98ANz/Tv82AMn/AACb/+j/EQDF//3/zP/m/+H/pf8OAKr/zP9AAI7/6//1/9D//P/C//3/3v/K//7/2/+0/zUA1P/J//X/2P9CAJ7//v/g/yMA6P+0/xEAQQDa/9b/PgC3/3kAj//4/0QAxv8HAPT/CAAlAAoA0/8UABIAJADa//j/LQA9AKX/TQAEACEAIQDK/z4AAAAhANf/IAA4AMj/OgDK/y0AFwC+/zMA4f8qAOv/EQAdABAADwAUAPX/UwDt/wsAFQAZADkA0P8iACwAFQDY/zMA/v8JABEA4v8sAAIAEAD9/wgAGQAAAAsA5/8eAEkAr/9DACEAEwARABAAGwBBANH/DwA0AO7/KADT/zQADAAhAOz/FAAnABAACwDg/ycARADY/87/bgD//9D/QQAFABwAIwDK/0gAGADv/xMAJQAeAAsAVwDB/1oAJQD9/wsALQApACEA2P9mACkA4f9SAAEACgBYAMf/QAAcAAEASADz/zkALQAQADIACgAyACMA7/8XAE0A5/8AADkAEQAVAPf/HwAWAPD//P8jANv/GgD8/87/JQDk//3/9P/t/wsACwDU/wEANQCo/zoA8//K/zUA2P8AAM7/NwDV/+j/GgDp/xkAx/8OAAMA2P8DAP3/3v8iAND/CgD4/+b/LQDj/83/XwDP/9n/KADm/x0A1v/d/zsAxv8PAL//BwAZAJr/OQDZ/+///v/y//r/4v8VAOb/8P/y/xMA1//o/x4A0P/6////7f/s/+L/BgDa/wQAxv8fAOj/3f/+/+b/FgDm/9f/IADq/+n/EQD3/w4A+/8FAPz/AAAIABIAz/8dAA8A4v/+/wQA9/8PAOz/CQAbAOL/MgD+//z/DQAZAOv/HAAfANj/NQD4/wQAGgDq/ykA/v/z/y4A9P8bAA0ACAAOABYACgAEAB4AEQAPAA4ABgBEAAAAJQAZAPr/MgANAA8ALwAVABsAFAAOAB4ADwAQAAoAFQAWACoA8/8yAB4ABgAfACQACwAyAPr/RAAYACUAEwBGABQAFgAyAB0APAAQACMAPQD8/zIAKAD+/0MAAQAfAAgAHgAlAPf/BgAxAA8A8/8qAPX/NAD4/wEALwADABEAFQD8/y4A9P8IABgABQAUAPP/BQAfAAMABgAEACAAAwADABkAAAAWAAoAEAAaABoAIwAgAAUAMgAXABcAGAAHACIAHgDc/y0A/f8TABMA/P8XAAoACgAIAAAAHwAJAAcABgAdABwA+v/5/ycAGADp/xoA+f8EAA8A5f8PAO3//f/x/+L/9v/1/+X/6P8DAPj/4//x/+3/BQDb//L/9v/1//X/4f8IAPL/2v8DAOn/4f/n//P/yv/3/9P/5//j/+n/4P/l/+P/6v/f/+7/1f8DANH/3f/u/9v/5v/U/+3/5v/o/9X/9P/W/+//1v/+/9b/5v/d/93/0P/h/9X/6f/D/+r/6f/X/9D/5//V/+v/zP/0/+P/9v/g/+b/+//e//X/+f/U//n/7f/U/xUA3f8CAPb/7P8IAAYA6v8EAPr/AgD2//z/AgABAAQA+/8AAA0A8/8HAP3/8v8TAO7//v8JAPf/CADn//z/DAD7/+n/AwATAOv/9v8LAAUA9//0/wYA+v/6/wAA9f/m/xMA9P/t/+v/CwDz/wAApP+PAGz/EwDw/yIA2f/O/xwABADo/+P/JwDk/+//9/8OAAoA3/8QAB4A7//9/w8ADgAEAP//FAAMAAoA9v8zAAEAEAAOAB4AEgAHABoALQD3/yoAEwATAA4A+/8bAAEAGwDi/zMAAAAAAAQABAD6//z/BQABABsACAAFACAA9f8+AN//JgAKAA8AIAAUAPv/LgALAA0ABAAOAAwABAD2/xYA//8EAN//CgAEAPj/6/8KAAkADQD2//7/DQABAA4A8/8eAAoACgD4/wYABQD4/+b/CgDl//v/4f/q/+j/AgDi//b/8////+X/+P/k/wQA6f/8/wIADADy/wIA9f/w//r/3f/z//D/4P/r/+D/5v/w/97/8f/b//H/4f/r//z////w/wwACAACAAAA+f8DAAsA+P8XAOT/GwDh/wMA1//9/9v/+//h/wIA6f/9/9v/5v/6/+P/7//q/+T/+//w//H/4v/z/87/5P/U/+j/zP/d/9b/2v/P/9D/2P/T/9r/0v/x/9v/+//Z/wIA7v/o/+3/5P/w/+P/9//V//D/3f/k/8j/4//T/9//1f/Z/+L/9P/e/wYA0P8SANP/EQDU/ykA0f8iAOf/GADt/wEA8f/9/wEA/P/y/wcA4//9//H/4P/x//P/7v8EAPv/AAACAPP/AwAEAPL/EgD7/xUABwANAAUADQAHAAwADQAIAA4ADAARAAsAGgD8/yQAAwAgABsAJwAQAD8AFQAzABcAJQAUAEUACgA5AAYAPAACADkAGQAkAB8AFAAMACwAEAAZABgANQADACEACAAlAB0AEQAhABoAEQAVAP3/GgD6//P/8f8LAPn/9f/y//r/9//Y/wYA9f/8//j/6v/2/+7/1P8HAPX/CwD1//r/8//1//P/8P/2//L/8v/7/93/+f/X/wYA5/8iAOj/KgD4/xAABQAJAPL/GQDl/yYA5P8JANX/HADy/y0A7f8vAP//FQD4/xgABgAmAAoANgAXACQABwAfAA0AMwDx/0QA3v81AN3/JQDW/w4Az/8gAOX/BQDa/y4A8/8lAPj/HQD8/yAAAQAqABUAIAAFAA8A7f8oAO//HQD7/xsA5v8FAOr/7v/g//D/8P/9//L//P/s//f/1/8UAPj/AwD9//z/8v/g/9z/6//Z/+P/yf/Z/7//z//k/8z/9f/V/+T/z//o/7r/2v+t/8L/wf/S/7v/3v+q/9X/pv/E/6f/5P+//+v/xv///+H/9v/M//f/9v8gAPT/NAAMADIABwAJABcAFwAWABgABQAkAPT/MwAMAC0A/v8SAPb/VgBFAEgAQABCADUAZQA1AIEAUwB0AEgAYgAyAEMALgBMADkAFgAhACoAJQBWAEYAWgBbAC4AKgAkACIAAwBqAE4AgwAvAAQAAwDs/ygADwBHADoAeABHAF0AMwA6AE0AgwCAAJUAggCHAHkAdQB/AHwASgBFADoAVgAbAB0ANgByACwASAAVAG4ARwBfAHUAhwCmAIsAmQCcAJkApgB3APkAtwD0ALgAygCYAHgAVwBOAG0ARQBUAEcAKwA1AAsAZAAoAGsAQwBdAGcAbABvAH4AcQCCAIMAfgBXAFkAVwCBAG4AdwBrAIsAZgB3AGUAYwBCAHAAUABRAEMALABNAHMAOwBnADUARQAkAF4AOQBzAEMAXgA6AD8AEgAFABwAKAAcAPb/CwAFAOT/1P+0/8v/3P/Z//v/2P/p/7j/5P+0/8j/nP/C/5H/5f+M/+n/d//h/6z/7P+0/+T/zv/Y//D/zP8NAOP/5f/N/7T/u//V/8P/7P+g/8n/Wv9w/0X/gf9s/4r/Qf9T/37/rP/S/9r/o/9u/5j/egBRBfkHsgnlBssCwQCE/y8BswFUBHECqQOBAJf/5v1L/YX9Uv03/sT/zAK8BNIE2gP2AEIAzv/DAUEDCwSFBDoD4AKpAMP/0/6c/Tj95vyI/nsA9QEfAa/+5/vW+Xf7A/0QANEB6wCFANP80Px4+zH+A/1q/mz8Yv1n/t7/AwDd/p37CPvt+QL95f2XAO//nf8v/lT8p/1g/ZkA5/9wAXL/Yf9H/wYAxf9m/h/9p/yY/cL+S/4j/wL9ev7K/Jj/0P16AGz+MwCE/scAff+qAfX/tQDf/tn/qv3B/uf9VP64/un9Jv1w/M37L/w//O77kfyu/gH/MQDj/pH+SP8z/5gA5ADvAKoBAgFjAvIAwgHC/yYBxP9NAMr/wgBnAeoAl/90/+7+j/+A/6r/NP/j/kT/nv+NAC3/BAA6/8f/8/5BAHcA9gFwAQcCkAGYArsBFQOoApgDzgLUBJMEKgZYBd0FBwU6BScEoAVDBR0G+wRqBSoEtQSUA7ED9QLCAjwCoAITA/4C8gKXAmICbQIrAsoC5gKTAnACjwEDAmcB+AFZAeAA6/8W/4r+3P1f/cH9Ev5Z///9dv1p+137ZfuX+2j8Kvwt/fj7qfxs/Nj8GP0y/Bf9gfxQ/VH82/u3/Ef7Mf0T+mj7//mo+4/7jfuU++37yfz5/D79x/1N/c3+If5u/+L+2v53/0X/if8w/3j/HAALAKcAxv8YAQAA+gDm/2kAm//B//z/OwCQ/3n/fv41/+P+fP8m/6r/j//d/z0ApwDgAOEALgEaAVIBjgHIAaYCWwK3AlsCuAJWAnAC7QFKAngBygFGAdEBfgH/AAcA1f8t/57/TP/k/yIArACCADoB+AC9AdEB6AI0A8UDHwSTBGEFSwU4BasEHwQ/BBgENwQcBJYDYwOuAoYCngGJAUABGAEYAR4BVAFhARMBrgDg/wYAef9cAFIA2f9o/0b/Tf8d/2z+Rv2d/I388/zR/dH9Vf3s/Kn8tfwo/Kr8UvwB/Sf9FP1F/Un8B/v6+Yv6EPse/G/86vt9/M/7Ff3//GD+WPw0/hn9hP5G/dT8RP3r/Hn+Mv0V/zz+Pf+L/v7/wv9wAGwAqgDsALwAfP8OAKb/6ABoAIkB0wB9Aa0A1gGhAWECFAFLAYcABgEVAYMBEAFTAVYAAwFVAfYBwAG/AZUB3AHrAd4CrgLgAtYBOAHaAJMBNgKBA2YDQwNtAn8CGwMEA1oDYQKMAUgB6AETAy0DGgO1ASMB/gAnApkCqgMrA/gCKgN+A+ID1QN5A7gCBQKdAlUCkQNKA+ACVQJyAZcBPwE4ATIBsABjAEsArQD+AFIA8f8C//v+9v79/uP+R/5r/ar8bPyW/FP89PvD+1P7GPtm+pb6w/o3+3P8Nf0w/3P9wfst+nb56fnq+8L75Pob+7z5s/qb/Lv8UPsn+pD5Pvoe/NT9a/y5/Pn5//k9+q77vPvh+6r8I/yH/Uf/3v5v/3v+1f3m/cH+Sv9N/33/j/5M/lL/av8MAMb/Vf9J/8H/YAApAWkBAAFQALcApwCyAYcCugK/An0CywJUAysE9QNeA7sCxQIjA+AEywTvBIgEXgREBNgFQwUiBRUFwwSvBBwFYQXmBHkEEASHA1EEMgQQBDUESgTVAwwEowTYA8oDWgPiAkcDdwN8AxADNANTAiACJALxAbABkQH7AGUAmwBdAJz/nP+A/jf+4P3T/aT9Vf36/Iz8hfx7/Pf72vvm+pH6APs9/Kz8HP1V/Hj6zvmr+Wf66fpL++P5Gfn7+Xz6S/sG/WX7Yfrm+Rz6n/kY/Oz6efqn+qn51vlR+xn8qPs3/Ev8i/zG/WP/Y/4E/2H+9v27/kcAZgDuAAsBNgEjAZcCawPPAqID0wK8AoIDzAPGAyQE5AOtA/kD3wTdBKsFpwXQBeIFpgaTBqwGjwZRBgUGuQbxBksHygcrBzsHPQeYB/kHwAjaBzcHYgb5BR4GqwanBgAGqQUVBYEFQQY/BqoFBgX6A9ADBARrBK4D+gK7ATcBKAGwATkBCAE6AKL/kP/a/7z/sP+2/u/9Pf04/cP8zPxm/IL7PvtY+5L7evu7+qP5s/i8+DP5bPlA+eT4pfdD+C35efrQ+gD7t/hC+CP4oflY+tv6Qfn/97r3ePic+pT6wvre+Ob4G/kN+7j7MPyc+mr6gfqG/NL9Bv/W/av9Yv3d/kYAYwG/ABIAXv8JADABlAKKAjoCXwGyAccCLQTCBLAEMASVA2UEXAUYBkAGzwVuBb8FbAZmB00HVwd7BvYGnQcvCBQIAwj4Bi8HFQdRByoHBQdwBpUGmgZHBqAFkwX4BEkFngVBBboENwSrA54DJQSRAyEDNgKqAXQBjwF8Ad4AJQBp/zL/hf9G/9v+8/2f/T79XP1y/eL8Vvyn+7X7t/vC+zP7Uvr8+Qb6/fkH+ln5Ffmc+Lr5zfku+qX5dflX+dj5v/p2+uf5ofkD+d35LvrG+uz5WPkR+cv44Pn4+fn5Xvml+cr5m/qT+7D7jfsa/Pn7Af2n/XL+p/4a/7f/DQC8AC0BFwG0AegBPQK+AiMDbAONAwMEMQQ2BF0EaASWBAkFKQVXBW0FtgWsBeEFKwY7BmcGbwa2BrwG4wbuBgcHxgbDBqUG4gb+BgQH1wa2BnIGRwZBBjQGBQa9BYcFWwVuBWgFOwXoBE4ExgOMA1cDAgOQAvYBBwGFACwAuf9I/6f+w/08/fL8fvwc/NH7afs0+yz78frk+s76ZvpB+hn6DvrC+en5Uvn3+Jf4bvgf+Br42Pdr9zj3H/cT9/X2EPeD9lj23PUJ9sj1C/bi9ZT2avYv97z3Wvj9+Bf62/qi+1L85vw0/Wn+DP+Z/2sAzgAHAWQBHQI8AowCsgKdArEC2ALJAs4CqgKeAmQCpgKVAqMCkAJQAh8CMQIUAg0CBQLrAaUBAgKuAqUDXATFBBEFXAXSBbMGLAclBx0H3QbOBigHUQfYBmwG9gVxBaQFDwbnBawFhAXwBPwEKAUhBbAEdwQNBAAEcwSlBEoEQATuA8AD3wMGBK0DRwO0Ah4CygGNAd4ATADJ/0v/3f6Y/if+o/00/d78c/we/KL7L/vn+mX6Cfqs+U355PjD+Hn4RPjw94X3DPfZ9o/2PPbu9Z31LfUQ9ez0EvUZ9Tz1WvUa9ov2Mvf997P4NPm4+nr7SfwD/XH92/2k/qP/PADHAHUBrQE1AuoC5gIgAzADQgNpA9ID4QPdA+0DrQOQA8sDvQOaA6gDpAOAA+ID+gPlAwkE+QPeAzIECgW2BTcGyQb4BicHmgf8BxYIDgj7B7wH0gf/B7UHUQewBj0GugXyBRAGygWlBUwFDwUUBRAFxgRuBFEE8gMuBNQEzgSgBGUEFwTtA2IETwStA0UDsAIjAgACvQH8AD0Aqv/c/lD+HP52/Tz9t/0T//b/6v4I++n2T/Rq82D0bvfL+S36KfkJ+Pv2HfcW+OH49Pfl9f3yzPDV7yvxtvPd9VX2lvYl9sn1IvbU9835BvuQ+4T7+Pr3+iX8Rf5RAI0BdgJHAtkB5wHjAsUDZAQ9BH4DPgJtAbkBrQJmA+ID7wO1AywD5gLpArkCrwKzAqEChAKJArECCgOyA3sEgQU/BpIG7gYCBzYHcgf4B80HVwf9BpUGdwbVBvMGuQYgBtQFLgURBeAEgAQ1BNsDrwOaA7gDlwNkA5sDiwOJA7kDmANXAzwDTwNFA3MDlQNAA98CdgLzAXkBLAHEAAEATv++/jf+6f1F/Xz8qfvz+mT6Ffoc+vf5b/n2+HD4xPeV90z3QPfc9pn2avbz9dz1ovVO9Rf1sPSW9GH0mfSt9GT1Efba9m335fdu+FX5jvrm+1T9af4+/+T/nAARAZIBEAJ/AgkDeQObA6gDfANbA0ADTgM1A/0CqAJWAkMCkgLBAukC4gKpAoACvAIpA6IDGwSpBP0EwAVzBhgHsAf5BxgIQghTCH4ITwhQCPYH5wevB1kHzgZqBucFxQW9BZYFDwWaBDAE+gP/AwUE9QPUA74DjgOLA6EDpAOfA5QDUwM+A0gDVAMvAxADuQI3AokBuwDj/zH/qP4t/tr9aP2Y/Pf7iPtT+wf7v/pu+rP5YPnu+Kz4cfgF+G/38/a19k32//Uu9uH1Gva29Yz1GfWr9HT0K/Rx9AL1g/Vr9h734/cG+Rv6ivt//NX9av58/x8ALQHkATwCkAKuAswCQwMrA3EDTANPA/sCngJTAt4BeAFAAQwBDwH/ABwBKAGYAfgBPgKuAuwCbgPKA3kEfAUgBucGVQefBwwIHwioCJYIlwhCCMUHhAcNB5MGIwa2BWwF7gSzBEkE5gPWA6sDggMxA+MCngKmArkCtALRAu8C3ALBAuIC2gK7AioDeAPzAvEBiQFEAQsBwwAzAED/ZP7n/Uv9n/xM/BL84PvB+1L7H/qN+cn5+fnM+Un5S/hB96v3Gvjp98L3Rvem9mr2s/YA9un19vWe9Wb1Z/UB9Sj1CPb39lH3OPgk+Rv6yPs0/QH+Hf9IAAMB+AG2AiADowMfBGMElgTdBAQF3gQKBXoECgSbAwoDrwJBArgBTAEPASwB+AAjAUkBdgHWASICoAI/AykE8wTTBXgG+AaHBzMIvwgACTMJEgnQCMEIewhJCMIHPwfGBi0GzQVFBQwF0gQ+BPEDVwM3A/AClAKeAmICQAJEAmECaQJ0AqkCuQKwAr0CmgKUAosCVwLhAXsB2QAmALH/HP9n/rD9KP2i/Cj8CPyL+yP7xPp6+ij68fkC+uH5jflo+Qf5Efnc+Kz4uvim+LT4U/gD+Kr3l/eC9w33wfbJ9q72J/c790T4GPkq+hv7Dvxh/Y7+l/+HAFQBjgLGAlsDxQNNBJgEoQToBCsFIQUDBX0ESQS2A0gDxQJDAtsBPwHZAHAAUwBXAEsARgBlAM4AgAECAmoC5QKtA0kErAQyBaMF/QU6BmYGhwbSBsMGtQZ5BlkGJAa9BasFUAXeBGUE2AOIAyoD6AKXAkUCMALlAcwBlQFiARsBCgH7AM0AugCQAGcAhgCIAJcAWAA2ABEAz/9O/+H+Rv7W/S/9y/xw/Dr8Efy++0v7Zvsj+3r7+PpD+w376fqU+kn6Kfra+ab5ePly+Xv5q/mP+Z35jvmK+UH5M/nR+Kj4Q/hS+Ef42fjr+KD5afpx+yj8S/0//lr/DQDdAEEByAExAtAC7AI+A1MDpQNoA5ADegOzA4YDVQM2A+QCYQINApUBYwHYAKkAmABeAG0AogDIAPoATwHDAQoCYALrAjQDsgMpBGYEjgTRBPkE+wTlBNwE8wTSBMkEzQTuBOEEvwSzBMUEiARpBCUE7gOJAx4DzQJ4AmACNgLzAbQBTwEkAS4BTAFlAV8BRQESAbAAsQApANT/Pv/W/nH+M/71/cX9kP2e/WH9OP01/fj83/zM/K/8lfyA/Jv8evyE/BX8SvwP/C/8DPzj+3z7Zvv8+vL6kfqF+jD6CPrJ+cP54Pnu+Q76kvrM+jr7kPuM/CT9zP2F/vP+pf8hAJEAKwF9ARcCZgLRAt0CHAN8A30DmwOqA7YDvAOTA4cDkgNzA1UDDAMNAw4D+QLjAqsCsgK4ApMCigKIAqMCiwLTAsgC6wLlAgUDNwMCA+8C2gIEAwEDPAMhA0YDOgNZA1EDRgNUAw8DCgPHAogCdgJEAhoCvwGYASEB7gCYAFYA5f/J/6v/Vv8A//3+nf5S/g7+IP6w/bX9Rv0j/b/8ufxA/Bv89vv9+w38JvwR/Ob79/sb/Ov7Svwu/DH8K/wk/Bb8+Pv6+9L7kfuP+3j7R/s/+0L7Evst++f6Hvtm+4v7Ffxj/OP8VP0P/sv+Ov/6/1QA9QAqAYUB0wEXAmMCegLMAu0C6gIPAx0DOAM9AzMDTwNkA0EDRgMFAxAD3wLQAqsCdAKDAkUCggJqAlgCUQJ1AoMCcwKcAocCogKyAr0CzQK5AtwC0ALIAuYC2wL6AvAC3ALJAp0CjwKWAnICnAJdAnECGQLWAZABhgEGAeoAlwCEAB4ACQCJ/2f/LP/k/pv+Rf4v/qv9n/1z/SH93fyw/Jr8Svw7/B38Hvz8+/z7+fvj+z/8Vvx4/Iv8aPxx/EP8X/xG/HD8Vfw3/BD8CPwr/O379fsW/Hr8vPw4/cH9R/7w/nz/HgBzAC0BegEMAkoCogLHAuYCSwNtA50DkAPZA+oD5gMlBOoD/AO9A7gDoQNvA0UDCAP6AgYD+wIAA9wCxwLuAswCxALZAv8CNAMVAzcDNQMeAw0DRAP0AhMDtgKbAsICgALJAmkCeAJQAiwC8QHWAYYBnQF4AXUBeQFVAZAAgQBRADIA0v9+/2b/CP+s/mz+GP5Y/hH+I/7I/Qz+if0t/YT8X/wO/PD7Bvy4+6D7Yvt/+677bPu1+2j7mfue+5n7q/t++7f7YftV+xz7NPvx+kX7jPvz+0X8Jfyp/MD8ov0G/rb+Tf/9/5wAHwGwAewBNQJUArEC3wLXAvcCvgLzAuUCEQMkA2kDrAPuAzIEJwRZBEgEawQJBMMDmgNTA2QDLQNFAxQD6AK8AukCWwPtAgMDvQIgAwsD1gKxAtQCgwIUAgwCJAI4AlcCMwK5ARYCbgEpARYB/ADgAC0AogA1ABAAw/9Z//n+ef4z/mL99vxz/DT8EPzl+wf8yfvH+4n7R/sY++z67fov+7j6Svso+8L7gvvE+3z7EPtQ+0b7dftK+4H7B/sa+936PvtF+037D/xR/BL9rv1a/gT/nP8wAHgA+ACWAf4BPQLTAhgDJQODA7UDHwQfBE0EbwR+BHUEgARqBG4ETQQtBCYE+QMBBM4DrgMLBLADsANiA3UDggOaA+ED4QMrBAEELATiAwQE4APcAxQE9wN+BEgEJAQcBI0DQgOCAkcCCQJ+Al8CVQLWAcEB+QBDAMP/Vf8d/0X+Jv7a/eL93v2o/SH9Q/we/EX7Cft9+nv6zPls+e/4m/gV+f/40/mZ+sX69fq/+gX7G/rQ+Xr52fhc+Ob4k/jj+F35Fvrd+o77bfzx/Hv95/2S/k3/xP9xALsAWQFnAWYCoAIkA70D1AMwBHMElASEBGUELQQfBNMDtQOoA58DcQNiA0sDQANIA08DdQN6A40DWgNjA8ADDAT0A1sEdATzBAQFagWCBYUFnAUxBf8EowSKBHkEUQQHBJYDfwMIAxIDiwIMAn4B8QCKAPv/Xf/f/j7+t/2K/aP8FvyR+wj7Z/pX+b344/ej96j2afYl9sf1M/Yf9u726PZB9zH3Gfdf9wT3HffE9mT2D/a19en1MfZ19/b3qPkO+2n8x/06/5AAhAGdAtcChQOKA/ADOgTRBCoF3wWSBoMGMgcjB4gHGQfPBjgGQwWwBKgDewMCAwoD8AJ7AwgELQS7BPMEZAVgBYMFqAXqBQoGKQaSBpsGBgcNB7UHKghvCHgIDAjGB0YH6wZZBt4FTwWfBAcEegMCA1MCJQJbAaoA0//X/gf+Hv2D/E/7gvrL+eL4Cvi09hX21fSc9BD0kvP6827z//OM8xz0OPRv9NH0p/RJ9er0TfXL9AD10vQr9vf2Avjv+g38vP6v/6ACZwMpBXMGcAa4B5YGzgdUBxoIiQgDCYYJdgntCW0JWgl2CPwHfQZ/BVwErgNIAxoDeQMUA1QE1APtBEwFrwVnBr8FxwY2BgMHjAZfBxoINwh4CWcJIwo+CroKgQq7CUkJUwhAB1wG8QXCBAQEIQPIAn8BAQE1ABr/H/57/G37f/l9+Pr29PWS9JbzsPKA8Sbxh/Bu8MvvA/DH7x7wwe9s8MnwYPDF8fXwz/Ez8eLxz/Eb80X1sfXt+d/6/f2M/6EBoAOqBMkGswY3COgHwwjOCf4J5QpLCzkLsgpXCmoJkAhZB8cGLwV5BFMDtQIPA3ACewOhAmYDHANPA+0DfwO8BC0EqQXsBaAG1Ac8CKMJrwmBCmQKcQqJChQKFArZCUQJwQjhB0QHlAYsBVAE5wIcAnIAW/8w/kj8oft2+ZL42vZA9fPzv/Hm8CPvIO487Z3tte1O7THu7u2/7lDuMe/l7rLvxO/67z/w2fAz8lf0vvZX+eb89/2QAOEBfAPeBFoG2Qc/CEMKUAr9CwYNBQ64DiUOdw3cC6EKAQk7CEMHYgaSBRsFTwStBCIEywOtAw8DnAKtAWwCvALBAy4FWwasB1QIxglFCtQKjQtqC7ILnwsPDBEMHAx1DKsLzwpRCfQHWAbhBM0DbgIgAeH/mP5C/cH7Svpc+Br24vOG8Wrvd+3T7MLrAOze6znsv+xW7EvtT+zu7KTsUu177Ujucu/n78jyZ/XS90n7Zf5JAFICBgR6BR8H4wiaClQMpw1xDpUP/w/eD+8Pvw54DRkMxgqPCaoISwgrB18GqgVpBCcDkQKeAYIBGQGkASwCqQL2A4AFLQaJBtIH4wcWCM4Imgl2CjILPQx5DNwMsQz3C9kKzglKCHYGFAVZBFMDEAIlAYT/c/0v+8v4wvYC9Azyl++e7RnskOrv6bTpBeoK6YPpyOiN6Ibop+iv6QTqTuua6yztzO758QP0Vfho+2z+OgB8AsYEkAYnCbwKjA1rDpwPYhDgEHQRNRHkEK8Png7fDIkLqwoGCgoJdggUB/UEbQS0An8CbgEwAjoCSgLfAqkD6wTeBEoGgwbgBjEHmQfSCMoJ7QqHC7ULjwvgCqEJtAjSB/YGegVrBFAD0gFIAMP+DP3L+m/4R/bE8zPxT+/T7Ifrz+l06UDo9+do6LnmOuc95rzmlubm5lvojOhd66rtpu908+T2aPqe/B//ngI0BD0HaQkJDWoPnRDGEh8TyhOrE1ITDBMvEh4R1A9aDisOkwzhC14Kcgh1B5QEjgTfApIDxgNvAz8E4gMmBLYDIQQIBXEFIgb9BqQH3wgNCQoKAAruCXYJGgjfByMHlwbvBSsFHAQnAnsAnv7N/EX7dvlh9xD1SPLZ79/s7Oto6hTq0Ol76DjpseZM5+XlqOZa5s3mAenF6sjtCvCI9Pn2v/pY/F3/rgEmBAMHBQrDDW4P5xF4EqUTbBNGE04T1hKJEvURKBEBEOwOEw4HDAIK8QiKBpcFygNZBMsDrQPPA9sCMQMSAo8CUAJkAyIEvQREBaoFEwbYBcwFBgYABj8FngUeBfkEGARtA0ACxQDU/5H9aPy5+oT5Avfh9Kzyv+/y7Rzs8ut662zqbeqB6YTnv+ei5Urm7eZD6XLrIu028SnzKPYY+A37S/5MAIYDbwa8CXMMDQ4REN4QOBFbEc8QoBFvEU0RzRBPEE8PkQ1kCxgKPAgQB6sFNAX2BPMD5gMuA+MCLgLEAakBwwHbAl8DFgSVBMwE7gRrBLEECAW0BD0FNAXJBFAENQMeA4ABDwElAGb+Yv2D+3L6wfaw9ijzXPHx7+Xti+507E3t1+o1673oBOlb58no7ur066burO+e80z09PeK+Tv9/f/5AQIFAAdhCpoLEw5oD+sQmhClEJcQEhGQEGQQ7Q8xDx8OlAubCuEI+gd4BqAFcQU8BJsDrQMKA1EDsgLeAsYCQAMcBBIEbQUEBfMFXQV2BTAGhwWbBjMGgAadBeoEhAQHA5sCYAFgALD+f/14+/j5Cfic9ZnzDfKR8J/vI/B/7ujuhOwt67TpnOii6vLrXe9W8OnybPMk9TD3Qvqb/Z8BZgTHBUAIiAmYCx8Nxw/tEK0RGRGwEHcQ4w/qD0UPdQ9VDVQLsAmTBzAH1AWABS0F9AN/A1kCnAKRAroC+QIoA8cDfAMWBNwEXQWvBTMGGQb6BdEF9AW/BTMFAQUcBKoD/gGFAc7/f/7t/JL7jvl291r2efO68sjxo/Hl7yvwYu7e7JzrhuqB6vbqRO3s7mnwL/Gr8ubzH/as+bL8EAClAkoEjQUlB3IJogtYDWoPJhDiDx0P6g50DkYOpw1wDQAM3AmUCLIGEQYLBfsEpwMRAyoDnwHcAecBiQIlAlYCVQM8A9kDRAQiBRkFPAXsBZYF3wX3BcUFlgW2BBQEqgKZAfcAn/8y/pH85/rw+P32vPRY86zxX/Hw8AzwHO977oDsHuu76lnqBuxf7RXw/fAa8oDyuPMS9iv51P1GANYDIwUBBt4GoggjC9wMEQ/VD/MPPQ8EDuENjg1BDY8MWAvRCbEHZAbsBJMExwPQAxsDKwKpAeQAeQHNAfQCVgPxA/gDHQRJBOME0AX8BcIGfAZeBpIFBQXQBE0EuQPNAqcB3f9c/n/8WfrX+Jr2ePW98zvyC/Py8Enx6O/u7mvsJOxI617rZuxw7uPw9/DU8tfyM/QN9nj5mf3tAEMEwwVcBmgH6winCtMMgw95ECUQnA+GDpINhwy9DEEMDAt+CQUIRAbOBAAESAM4Ai8CkgJAAQkCSQKSAvoCAQSZBJIEfQWqBZ4G0QahBwEIwAfPB5MHsQYdBicGTAVTBIYDPQLb/4z+2vyh+mv40vY29dXyz/Ht8UvwLvCN7y/u7eyV63Hr1OpW7NLtYfDg8Q/z3vSG9LH2F/n+/GUAZATQBqUHqAhFCWQKoQs/DoMPLxDaDxoPRA19C4AKxAn6CCcIoAesBVsEAwO/AdcANgH0AUUB7QH5ATUC8AExA3oE6gTjBYAGNwdTB2oI8AgXCTcJtAiXB+MGdga2BZQE8wN0Avb/Uf4N/Ib6Ffj39ZL0CPKK8BTwJ/CG7vzuIe7G7MHrI+s262vr2OxM7tjw+PEr9Kn02PUr+Ov64v0zAiAGvAe1CFcJHwpTCuML3g2AD8MPwg93DiQMIgpzCBUHsgaQBmkFTwTHAhcBSv9y/m/+HQDXANsBagP2AjQDlwPHBKwFhAfhCJcJNgpaCjQKqQnECYwJEAkuCHsHggbhBJsDBQIBADb+ofwi+yv5APd39Cjywe8/7g3vN+7M7krvMu4Q7Trsh+uv65vs3O1O8KLyn/Q/9jn3bPg7+jr9UQAwBSAIigqVC+wLqwuzC/MM9w3MD+EPqQ/PDSMLfQhYBj4F2gSRBMID0AJ6AWL/7f2m/cj9I/82ANwChQQ1BM0FZQapBnAH8gk+C8YMHg5dDgcOGQ3cDHYLzwqvCiUKqwhiB3QGeQPfAMf/wf2E+3z6Uvnf9nf09vF877vsVeuF7Bjt5+0173bvNe0o7QnsR+vX7NnudfEZ9Af3xPf0+HH52fvw/twCRAf7CngN5QxkDQ0MNgxODcQOKRC3EK0Pzgz7CYUGUAT6AnMCnQLHAiQBUf/z/SD8x/uY/Fj+eQC4AkwETwbwB6sHgwlFClQL2gxTDrsPaRDCEJQPfQ6gDJcLjgpACVcJEgjrBfoDIAIw//n85/tv+tX4//da9mD03fGh7xDteurx6ZHpwuvZ61Tuku7E7Z3sRuvJ6kvqPe0370fz1fVR+Kv4HPrQ+xz/AwNUBtILYAxMDaUMogxjC7kM3A1cDrMOqAwxCqAG/APXAacABABiADH/uv0U/Q386/op/E796P4HAb8CvwRSBlMIfQqJDIENmQ8AEOUPthCtEG8QFBDKD/UNDAxBCjUIlgaKBBwEegJdAOH+9Pzx+pj5aPkU+Dn3svV+9FLyMfAQ75Dt+OsH69Dqy+rc61rsP+5/7iTuae0W7ATrDeuR7Bbv7PJb9iz5QfzZ/vkAWgJ1Bc8HTQkuC/QMhg6NDjsPtg7CDcwLigldB3AFeQQvA38CDAJwANX9y/vW+oH6VPuP/dMA+AIhBAoFyQWVBuQHlgpFDqARMxNuFC0UXRKmEPkO7w6gDscOjQ70DL4KXgdIBEMBz/8F/13+Uv44/iP9q/sz+gb55/fd9n32OPa19Zv0zvPr8fTvEu4k7C7sleys7eHuP/B472vugOz/6THpE+nf60fvSPSs+Df+FgI8A+wFLAbYBjMIaApSDkMRJhRsFcMUbBEqDSEJJwU/BBMEVQQ6BXEEigHf/dn5zfZr9Wf2I/pS/hYCyQSNBvQFkgX1BScHHwvODhcT8haiF+UW6RPzEEMOCwzeC2IMVw1ADLgKpgdrA73/4/zn+3T8fP0b//r/Rf/S/WP7GvmA9y/30fYF+F/43/eh9sHz9/D77dzqjem66uDq6+vB7oHtZOxd6ybnIOcO5Wnn1usj8CL2q/1sAmoEGAkdCMwIQQovCwoPGRPkFacYohhqFUsRZQvpBUUDjQG5AN0CIQLM//v8bfeQ8rXvau5A8WD1NPpLACUD0gSxBawFKAVhCHELaQ/FFNEX5xkLGW4W8BMQEJoMVwyZC+YKKwsbCvsGjQPx/3f8jvqv+XD7JP1F/tz/tP/p/Yz86PpW+WP5CPrj+tj7pfuX+n34BfXO8Vnvn+yd61/sSexI7Ujute347Dnryekv6ODn4Oiw7OvwtPUU/kEDiQbZCxoMbAzYDBwNSw+nEfMUZBfcGI0WZBPHDbgGpwJo/nX8Vv17/fH8YPtM+ITziO/w7JXsQu9E8xP56/2uAXYFoQXvBvYIHwp2DWwRLxX7FzMZahknGCoVLxJqEEINSAuMCtII6gZaBfoCYAAt/m78qvtQ++P7o/2N/oL/yACsACkA1P9E/9P+qf71/u3///8VAIn/LP7z+v/3KfXQ8RDwAu9W74rvzO/M7/rupuz66irpm+cS6NnpGe258ZH2Kv3kAIMEbghcCDoK0QqnDIIOPxHZE6IVHhYDFI4Rqwz8ByIEXQC+/tH93vzW+z36RPdF83rwuO3L7Cfu1vDL9PH4y/yW/30B4APkBQoIYAyjD6QTfhZPGGkZCxgUF1sVlRNkERoQJw6dC54JyQZRBNoB3/89/uj8Rvzq+9/7Afz3/JP96f0h/5j//v9nAPwAOQFFAeIBGgITAjECqgGLAC3/8/xS+p/3+vRr8hPxlu9w7+Xu1u7L7arsbev+6K/oVudf6OzpFexj8CPzB/jx++r+9AI/BZ0HOwkqC7sM1A32D8gQsBErEQUQEA6RCgIIqgTzAT8AZv4L/Tf7Yfml9vLzNvIe8Djw9fC28uX1APgP+0T9YP8aAfEDggcJCsMO5REjFBgW2xUBFsMU2xNTE0sSfBHODxUOugorCBYF0gFRALH+Xv3M/Db8tPs3+wT7aPvq+4z8Ev5//2cAAAJUA/IDKwWRBYMFEgUEBB8DOwE9ANT+zv0Z/JD6JPlF9p70zPKQ8fjvEPCO773uVu7F7ontzO1T7qbufO4L8M3wJPIc9Wn3tfso/XYAJAMEBXoJ0gtZD2gONA/GC1MKwAkwCSALYQx2DFcMAwmSBj0Djf/v/d37hvot+cv4hPg2+Dr5rPnl+Sz6Tfno+cn5ZvsX/t0AigTuB6oK1AuODUQNCg1mDYANAg52DmMPrQ+mDs0N+wv8CBAGGASvAef/oQDo/7n/uf+v/iv+/Pzz/VX+Bf/RADsCZwN/BMMF0QV0BawEfQNlAcoAOP9N/97+I/8C/yP+Gf22+8D58vft9s310vUV9gX3PPcR+Jb3r/cE96721vWC9pP1hPba9ez1evWz9K30U/Xe9aD3H/ov+8v9Wv55/1z/lgCiADgCzANKBUQHhQhZCa4JSQmkCPUH6AZlBoAFmQR4A18CtgCE/3b+VP3C/PT7H/uF+uT5ifnn+Yf6Tfsm/K/9hf5L/x8BFwJqA2wFBwd3CNEJzwo1C3wLaQtNC9EKiQqMCW8IJwfaBVYE/gKAAisB2wCNAGoARQCUAMMAzQD6APMAaQDr/8z/5v77/hn/ZP9M/xsAy/8uANT/w/9C/yn/c/6A/kr+CP65/Xj9UP1o/In8wPvg+z37Gvu8+lb6Dfre+Yv5g/lB+fb4wPhM+N/3XffI9mz26PUr9e30NvVG9Tz2mvhb+Uf7Qvwi/XH93f3s/n3/YgBsAnYDtAQjBrMGGgc4B6cHawdLB0sH7AYRBqYFAgUkBHoD0gIZAiABcQCy/+/+eP52/ir+lf7G/rT+yP6w/pf+q/4q/8f/rgCcAX0CNQO4AwMEZQSsBL8E+wT3BBAFFQVPBboFqwUaBjQG2QWkBTAFyAQdBB0EGATmA7IDqwNFAwQD1gK2Al4CAgLZARQBqQA7AAYA7f8CADYANQAmACYAKgDX/97/sv+X/2L/Xv9e/0//R/9z/2b/MP/f/p3+IP61/Wb94Py+/Gz89/vP+xb7dPq0+f74YPjR95v3YPdC92X3lffk95P4Hvnx+VX69/po+9T7avwt/fj93v6T/5QAWgEoAssCTgOKA5wDtwO7A+YD3wNPBKkEDAU2BUMFCgWBBNwDAgOCAhkC2wHHAe4BywGHAV0BRwGnACEA2/9K/yH/DP9s/77/XADUABsBXAFiAVoBmAHiAT4CkgI9A8MDCgRpBFQEXwREBAQEyQOnA1wDSgMkAykD2QLMAqICZwI5AhYCvwF2AS8B1ACmAFMAVQALABgALgATAOr/yP96/0H/0/6q/n3+Uv50/mb+i/5v/if+A/67/U79/Py8/LL8vvzl/PX86/zd/KP8Zvwf/Kz7evtY+1r7GPvl+rn6lvol+u/5tPl7+ZH5xfn/+VP6r/oF+z77ifvV+yP8uPxO/Rb+2v6U/y4A3ABpAf0BdgLXAhoDhAP1AycEYgSVBLEEqQSbBIkEawQ8BOIDqgNsAwIDnAJxAmACDgLSAawBcAFZAS4BFQH1AK8AugAXAawA3ADPACMBTAFuAdgB3AF1AlkCvQK/AggDAANfA0sDhAOmA7QDqQOxA48DNgMoA/MC4AKMAmkCEQK+AZgBLwHoAKcA9v/x/8j/nf98/0T/Dv/X/q3+dP44/hj+Fv4t/iX+DP4R/lT+jf6+/vn+EP8l/yj/cP9o/4L/kf+I/4D/Y/9I/9v+qf5W/g/+uf1m/RL9wvxo/Bj8yfta+xn7zPqi+lH6BvrJ+c357fkh+o/6wPo8+7T7I/zT/BT9sv1I/tT+dv8WAKMAWgH/AXYC3AJBA58DqQO1A8YD/wMCBMgDsgO6AywD+QLLAnUCHAK0AYABSAHoAMUAoQCzAKEAiQCMAGcAcQCJAMUAowCVAI8AtwCyALoA0QABAR4BLwFqAYUBjwFoAasBxAGnAXYBgQF2AWkBUAEvAToBHwEmAfQAuACRAEAAPgBCAPn/3v+f/23/Sv80/0L/EP8P/yH///73/uL+uf74/v/+4/7e/u7+//4W/wn/C//f/u7+3f7J/rz+q/67/uX+4v6//qf+nf5s/jX+B/7W/ar9f/1b/Sj98PzD/GP8C/zq+7r7rfua+4z7hvuS+5P7pPu6+9X7E/xE/J/83Pxn/dv9D/6E/sj+I/9n/3v/wf8eAHAAygA1AZYByAHlARECNQJgAmwCtQLWAtsC9AINAyADKgM9AzADOAMJA9oCCAMiAwMD9AIHA+sC1wLMArUCoQKOApACfgKOAlcCMAJMAlMCRQJUAocCYAIbAggCIgIYAiUCDgILAucB0QHVAeoBJQLlAcABuQGuAZEBgQGAAU4BQAFCARQB3gBjABMACgAEAOf/t/+u/5r/pP9j/0P/Cf8R/+f+E//4/sr+rP7y/u/+nP6R/o3+g/6C/nj+ef6j/of+e/5f/mj+PP4n/hf+JP7s/b/9nf2a/WP9Qv0y/QD96/zi/PH89vza/Pj89/w3/Sj9U/16/X79vv3f/Q7+MP57/sD+5v4L/z//b//F/w8AbwCcAN0AGQFsAaMBngHaARMCLgI+AkwCbgJyAoQC1AKsAssCoQKvAo8ChgJwAkICVQIoAjUCDgLyAeIB0QESAr4BmgFmATEBNgEmAVYBMwFhAXkBXAF6AV8BUwFhAacBqwH7AekB9AEeAiUC+QFgASABJAGbAXABKAGqAeoBQQIrAYwBcwH8AEQBmQUAD58LHQ4DDXUKhAKs+A/4FPN/8MXtzvV4/P77LwG7B/0FRv96+kv6UPh99O3zGPta/1n+DQFVBlAGFwH7/jL+ZPxh9pL3fPoL/9L8Gf5IAZkAO/5Q+oz8MfkS+Mv1j/np+mr7V/w6ALoB/P0N/VwAcwNlAV4EPweOCLYFmgPPA/kAgPpY+Fj69/kl97X7wv8NASAAvwA2AX7/v/uA+o39D/0y/H4AvgQ/BgoHMAmyCfoIIAaFBNIEfAM4AicDIgWNBGUEXASBBIAD+gEoAHoAKABO/30A3wHGAtgCIQP7A40DhAM9A/ADXARiA6YEsgQPBv8EGgVzBXQEMANrApICYQESAMsAmAGnANcAXACrAHQAD/6K/lH9gfyU+zX7j/2t/Nr8wfzD/TP9/vt5+jL8pfrl+iz54/ts+uz7yPrOABf9J/+p/N/92/vV+er4oPmv9vD1FPUz+Kj1jPYE9nH3hPK08r3wVPI38YbvlfGo8pLxGvKU9fj56/oW/igANgSgA2wECAbCCacJtQhbCq0LmgvjCtML8wy/CtYHJQVDBLgB6v74/UH+9vtQ+hj6Yvr8+nP69/pD+8P6rvoC/ED/yQBnAy0FSQfJCOMJ8Qt1DWkONA7RDXgNKw0fDFIMpgsUCssILQfeBT4FtAMmA3ACRgLwAJsBGwGtAYgBsAHrAXsC+QF/AjsDRAMVA+ACMQNmA40CAgO6AnQCnABgAFP/of/P/WD97Pw2+1X5SPl997D1+fSZ8x/yfPK48dbxwPHj8b/w2/OX833yS/Tf81rxePEU8WLyjfHc8Q3y4fGS8ePvUvCC8V/vP/Cs8Tv1ePhV/O8AKwRhBuwIXQk3DKMMaAwDDBwMSAttC5kLZQzdCxMLGghcBosDLAFy/rX8xPm194H23/Z599v4vPm8+wz8Pf19/pf/ewAtArkDvAUTB4QJYQtYDiEQ/RAnEycUdBOqEwUT+xGGEGYPMw6HDIYLgwlOCMAItAc2B/wGkQZVBZ4EAwXsA8EEswQABaEFJgY4BsoGTAhvCN4IOAiPB1UG8QVrBesESARRAyADJQPQAsoCKAPeAhgC0QHhAEYAHf/U/qb9wfzc+1365PgI91v11/Pq8t/yz/Hy8G3wl/CK8HrxnvEg8RPwAu/e7cztae1N7U3souxk7PDrue4z8bnzf/hw/U4BXwX8CQEN5Q7/EKkR4RHjEaYQKQ+rD3YOqAwPDNEKBQhXBeQCjf9b/Jv50/bJ9Av0g/II8iLz+vR29hP5d/si/UT/YQFbAzAFDAdmCM8J6QttDR4OWA9ZEPoQxxHpEjMSMRHjDzIOWgzpChQJAAdNBQQEtQKvAtQCxAI0A+UDmgPbAygEjwTTBIEF5QU2BvkGTgesBz8ITAimB4kHIgcNBgoF+wPdAtIBvAEeAZ4ByQGSAR0BaQFCAeMArwD8/yb+9/x4+2T6wvku+Sr4ifZE9kH1BvUd9Vv1TPTk80nz3vJt8nHyKPH377bu+u3n7ErtG+zj6i3qLuq36rztfPDy80b4Av2eAZoGBwtVDn8QTBKnEl0S1BFUELsONQ0TC0MJIgg+Bj0EHwIuAOf8WvrR94D14/K78TPwpe9F8BXyK/Qj9yr6/vwHAFQDTwadCBoKKAvhC9kMHg2WDcwNOg2QDJcM1wxADcAMvAvFCtoIQwciBg0FRQPBAaQAYwCNAHQBgAL/AtUDlQSwBU4GWAdyBzQHwwbKBrQGrAbgBmYGxgWSBacFRgUnBbQEwwMJA14ClQHKAIUAmP+j/g7/wv5c/s3+Ff/d/rD+P/9r/rb9pf0G/Z/7q/rh+Tn47ff/95z3q/ZT9kT1mvTu9FH0TfM98ivxlPBZ8Mnvx+7M7GrsBOxW7CXrR+xS7evvZPVO+4/+ygIzB9MLxw+JE2sUKBPnEUgR3A9WDnALKgcwBC8DswFvAM/+Pvt/+BP3I/dZ9WPzyPHV7j3v5PHD9CDzm/PJ/an9AAAmBGsLugiCCwQMNxCBDYgNNwuVC+QJ3wl8B78GtwRTBlADWQSIAqsChQD8AEsBkQCFAHkAdQBMAdoB/wIMA9wDqASLBRwGiAbpBv8GywYVB9oGmgakBZUFZwQFBF4DVgMCAtwByAB5AHn/2/9e//L+7v6o/wP/af+PALcACwACATsBfgFWAdkBWQBD/9n+d//O/ZT9tPsV+tr4h/l5+OH36/Tb99/x+fY19rbza/gf77P4SfBa+F7ygfQB8anx5vCx8frvDO9I72Ts9PBk8lT2CPnR/KABQQU/CoIPxQ+4EkESBxPzEHURCg0AC1QGFQXiATAAUv/9++/6cPlU+Oj3NfcC9zz1R/UE9db1+PXW+FH56/tB/ugAkQTZBj4KWAsfDXoO1A42D6cOzAzvCuYICAdyBZED3AHh/7z+a/6o/oL/PQDPAIkBmQJlBHIF3AbGBkoHBQcDCOwHHAipB30HWweBB+UHwge7ByEHjQYiBrAFAgWwA5wCkAE3AWAA7gDv/yb8FftIDdAAefi6+ckRlQMX90X+jxCz/3/7pP0uCe/9lgC7/dEEKf/lAD/8a/5H/cwAFvqY+Er3e/uU8kD1/vJw+GfxH/bx8Tj4y/XR92f1Lfqh+Oz4bfdU9wH0LPbu8U7xuO8F8uTrzO3I79D0Ofbj+47+jgQtCUsMog4cFCITnhHHEUUS2gylCUkIdgR9ANEAEf+I+zX6Hfp9+Kb3bfew9+D1BPag9aT1GvVw9s73bfqS+7v+xACiA4QGEQoMDLgNBA+pD6UOSQ6FDOcJRAdLBbIC0wBT/mD8CPup+8H8Yf3g/vD/zwHOAncEEgZVB+IG7AaGB5IHigZaBpMGUQZCBiMHAAfxBlcGWAaDBWkFowQVA6gBAgEuAP7+yP7G/q/+ZP+3/0kAxwCcAVwB9gHFAngCEgEoAfQAzgCmAIEAsf8Q/6v/6/94//f+Iv7h/BP8NvvJ+eH31fWk9OzzpPRp9Drz6PNl9L/0KvXt9j/2N/bk9rn2LPUR9un0EvPw8VnyZvCG7mDuQe4b7zfz9/av+Vb+sgMvBxsMrBCRE7ITyRRbFGAS6w+MDBEIxwRDAj//9/us+Wz3G/ae9c71c/Vj9c/0mvSU9Tf2t/bg95T5q/sS/lcBLASJBxILTw7NEOUSmBOHE8oS8hBODrALQQiTBOIAH/4G++74u/ea94v4kvq1+1f+KAFxAzQGsAjuCmEL+wtvDBIMoAz3C3gLtQpECtsJ3Qh/CDkH4QXmBG0DfwLyAHD/Jf58/ab9Sv3p/ZP+PP9/ANMB8gL4A3kE4gSrBLYEWATWAy4D2wLPAZQBEgGYAEYAwf9t/1L+vf1X/Cj6D/nA9jb1q/Mz8sfxgvDl8N/wwfBp8gjy7PJq8xT0CfS88wjzHfJg8N/vTe6x7U3speqs6qTs3e4Z9c34eP6DA5MIXQ7lETEWNReNFs0VAhIeEJYLwQYRAy//2fz8+Yn49fbQ9Bz1C/XX9AH1DfR+84vykfOr9C32l/gq+0n+SgK7BuoK4w5PErUUKRZxFkcVGROlEBcNSQmHBXIBhf1y+kj4gvbo9Tj2a/ep+ZL7//0MAPYC0AUsCJMK/AvmDIQN/A2HD3IPMA94Dk8NVAxVCrEIwwYTBDwCw/9T/jv9mfsH+9H6v/un/G39Of/k/+AAhgJlAwsFlwWGBccFZQaEBikGXQYTB+UFHQWwBHQDuALIAHj/ZP6s/Pb6AvkS+E33X/Vh9KzzhPKD8hPxD/Hz8azxgvFA8vvyB/Qk86PzNfOW8t3xNvB076zv+uy26nrq9urz7f3x/vcz/hMD8QgzDXcSuRYLGFsYVhfwEz8QAwweCHkEswEQ/+389Po4+pP4tvf39oL2kvU79Dnyk/GP8XXyrPRN+AD8F//4AfgI2w7xE8QWYBnLGZIWBRQAEWoOgwnoBE8Chv/U/cH6Ofsp+iP6Xvn1+E769fqO+/z9FABkBMsHUwubDxoTuBWPFvsXVBcdFr8REQ5+CdcFigJ3/5r9JfzB+3P6SPwo/b/8B/3Z/k/+TP89/z4BGAE7AqUDJwUuB60I0wjxCXkKDApUCEAIjwUxBN0CWAF3/9n/T/6H/Vb9Fv1m/En7FvpM+O71D/TV8j3yj/Ba8SrwdvMS9HXzS/Si9KnzwfF68ifw9+9Y7YfqSuk/6lXou+WX5nvmg+2H9ef9GwbFDSITmBeqGGka9hu+FWoP2QodBosEW/98/UX8hPub9531cPTY8Fbsm+mh6dDqSuzL7m7zivp1AmwJthCkFRYYGhZdFjgVHhRrEHoNSAquB8gFmwPUAiv/A/wn+Ob0LfIq7+TtOO2x7vzxr/bb+04BrgcpDyMVBRm0Hvkg+CLEH4ofZRwsGEoT+QunBnUCqvzK90j3mfU1823zCPXa9YT4rvqT/NsAegLBBaMITAx+D50OfRBtEQYQRA5kDSEKagg+BlIDogHyASUAHgAOAOj/MgDN/xH/kf5W/hr+0v3k/Vj9KP15/O363Pqs+FD4hvd+9bP28fXX9fX1S/fp+Hb1SvWY8/Ptle127PLn3OzN5OnqgeQy5cnl89/h3hbpJPZyAIoIFhO2Hp4cfSAIIQAbphoeDQoKUQfoAx8Dzf5K/OT5jvMV7lnoe+Pr4mTfw+JM7Lfyrvt/AwkKmRLkFfIZShmlGKYXJhO8E6gT3hKBEDwNZQfrAgX86PUk7/Xq4+ir5lPp2e268874Hv1fA6QGhAk6DMAObQ9TE6YZcRyKHechzSBgHawbiBKDC9MDVf1k9fHy4vMt8xTzGfdE+E35CvvT+g38I/8+AbUEMwuwEJUSjBY0FkMU9BIhDfMJWwZpBBYCLwKVAmABvAE9AMv9/v3E/MX7e/tI/ar+swDDA78E9APKBdYCKv/m/8j8M/kB/M74B/kz+rv6KPeY9/30O/Ab8S3vNO6H6wXx6e677sjuJPG87s3r1Opy7VvevO0v4HbaBuNz5dTxtf9NDUkOAB2bGEkaFxfQFUQPKgxtCBYHAgpNBiYDNv5Z+N/vjunG5bTfn+LV5LToQvTk++MCzAaTCv8Mpw4qEjwTixbpF/4XbhnwF64UEg/aBwn9I/dy8P7rieq26zDtWe//8wP2KvlV+6P8u/8NAsgHog3tED0XchkUGisaQBl5FVESgA1GC2AIfAkxBgICIwDf+9D4Jffx9Qr1Fvdw+Ff7BgAUA1kGywb2CpoL0g36DLgQSg9uDc0RJAuhDIQM8QUoBVcEbACcAOAAlf5Q/7L/Ov/M/3wBkQGIAk8DQgShBJYGMgX+BfYEKwPtAT//zfw8+5f32/d79mn0EvZC9FT0WPXo8PP0FfEh8mXxsfMd7/XxaPAK75zsRe7Y56Xsn++H4J3nH+Kv3/jYd+NV8VgCbA9mEhIclBzpGVAWpRGZDzEQmgcjCn0NzAlxBfv6/vGK6+zisN973/Xj3ep48Fn6dwLGCJQKGgiBCyAPrhF3FxAdAh5KIBcbcRV8EBEGRf5g82vuIu097WvunvDa8sjzY/Mz9RH3Evkr/tICzwhjEPgVChptGpwYahUsD6gKnAbHAtcB8P6YAwcGNwBVBo8Br/vt/mv59vfp/loBJwJ4CEMKRgwBCRMLhAYIB1sH5QeYBicKswtrCecI4AXnBs7/JAIoAaAAqASFB+cEbgguCKQEXwTqAV8BfQCjApkDaAWFBuQFdgNwAQ3/j/wT+/j7C/yq/aj88fsc+eb2xPOQ8y/1pPQp9h/7sPRe+rT0Ku9S76DoKOo652rzwu4/7ED5muyO4tXzmNdD4BvrmNRi3iLh7Ow3BpcNQRUSGVoT0hUYDmAThBKwFDwUTAscE2gS3QL5AF3wx+Ne6bTheubj76PuvvRX92349gPgAboDrAaJCgYS9xnXIGwhsh5BG1gPxAnGBd79VvwN94r14fgw9AL1TfPn7CXuge3H8Jn33P/gBVIK6w6bE/sUFBX6EuIRLA83DqkOTwsOCgMLDwBWA4QGV/k6BNr/tfjoAbP8kfz4BDEEHwF4Bl0GlgStCakIfAjKDXoIUAyvDRIJxw/+C3UIUAnjCVECzghFB1MCtAgDB3QE4gdKBIYDeALyADICMgEcApEEGwPhA/MDcAMEAMoBBgCK/CsBPf51/DAAcfrI+lL4+vNL+Kb2O/Sk/xnx5fmr+v7sa/HA7eLonu0A8EfuZe5M+DzmZO0O71fmVPJs6b7mI+JX5+7bCOTf+xcJGw2bGccR6BEZFNUL/gvaDiYP6BH+Cf8O9Q65ATP5/u6u54Lkxerg6SXvv/fr+T/4o/u7/4X/VwD3AmMKYhNBGRYgPBwBF6gTZAhXAsL/1ACi/Nn6rfqm+FT1rfMz7w3sDO1v8AP1dPtXAyAKsgkmDh4NuwzEDY4NJg7TDloOIw9pCt8F2gIf+ooAj/8T/VAHvf47BSkDQfy//9YAIP8WAAQGtQX/B/MNPgcxB6oLHAQ6B+oG/QhQDDILrgtkCw4HpgcRBRcCggbvB5QF6gczCCYEgQT5AVP99ABLAZcBxAJXBXgE+QK0ATb9zP4k/WP+eACi/pIBmf/g/Gf7h/g89ML0UfKI89n5Zff4+5v0r/Wp8L/t5u805eDrN+qs7hvyI/VH907sKfSa5cLnMul757npa+tn6MnsgvsEAM0OrAwQDAoQHQqOC5MPWBElExgVQA3YDFEIjQHt+SvyQu+g7H7vH/KZ8oP2IvYw9Pz3OfcP/mUBbQS+DOYRWxZeGsMXJxTVEKkJ9gdUBWQGrgTbAPL9l/cb9QDy5O7p78nvp/MK9z36HQDfAlYEiQf+BlQKgQ3DDqYRGRI+ETcPmgtiB98FYgP5AEEIWQSXBe4IJQHzAAoAmfrG+1r/3/+cAFMGegdnBAAKVgckBEUJZQguCnwMwRBrDdIOKg2CCEEGDwdiBLQFQgYEB7cEQgOJAs/9XP6T/3r9+gDfAVYDSwJEBLID0/9+ArQALv4NBGX/mwAmAdP7k/oB+I30I/XS9CD1RPcW+SX3x/tw9ePxafJJ6w/pDOwk7afrn/lS8nL03PRU7ATtmuZa6B3xBeeW7+fset+d6xHzsPEHDfsM9Qm2EiAMjAqNDWYOrQ/eELwObQ2lCNUEn/5o9lLxRu3Y7l/sn+5R9VDysPX2+XT0NfyL/uL/6QgwDnQTsxhtF5MVNhKbDJAJXwe3BQAFgAP2/tv5JPm28nrww/Dc7XLxTfQ897v9KgHAAzcGPQbqCB4L6Q2/EdsSzBJUETYO4QkaBeUAhf3JCGoS0v1JF6YCQvePCZ3xxvTsBq3+p/wDCR8JjQEoCqQJMP1ZCX8MIwbMDjAWbBUCDSwSHQtBAjcKvAc9AIYK7wssBMMDfAgM/QD9YwPn+fAA/wg9AmwEngafA7IAOAPJAJMAvQQQAucADAIT/yj9R/rH96H2Pfcd+V33vPo6+zj28PWG9ZDwjvCY6Q/sq+i27q/xauoK+VboJfbB6kfyhe685ob43Nkl7KvtS9Wz94b4W/R7G5wLHgr3GWMDaQoSDl0KuRb4EU8VRg5kCIAF6/cv99Pvy+wV9L/ve/Gh/PTwuvgt+GbwJP0b/uMAexHED7MZ7BpsFYEV1w7/DHQInQu1CJ4HSQeH/zH5lPn+7z7uQPLp7dz1QvgB+XUAyv93AnYEeQVKCrwNfhKmFLkWrxZ/EskOwQmUBMQCaP1MB98Z6AMFEqsPJ/HRB/n5eu1WBsIHhP2bB1EODADcBkIL7/zxA1gQUwi3DEYVnRQIEMoLYQ6xAo0EHQ3wAQYGjg5tBoL/6gZB/rv4dgLc/ub+Vwp1BfEBEwVxAkX+wgH3/mT/LANqAD0Bfv+O/Lz4w/TS8tnxJPQU9Lv21fX09Tjy1O5X7SPq9eqp5n7rD+sL6j32oOdD9cPuJOsW7hr0IeoC8z3vI+gx5pblFt326FH3cvxwCCMP7AkOCsEGvAOEB8gLCREmE3QS/RB+CsIDT/kh9+jw9PC69aTzZvil+Z31W/WJ8xnzj/aP+7UC2gwCEeIVMxZCEtcQKQzPCdYJBAxKDLcJHAiZAor75PgD8gvxDPJT8sv1lvpu/Kf/XAEx/40BcwJ/BbgKrg4FFOEWuBShEeAOOwi9BIIDaQAXAywZTQwNDOQY1vf4AwQDN/B7AiYMEgMTBjQSAAbxBIYN2wGqAGkRVQvhCscWTRUhEWYPkQ+nBFgD+QubBFMGDRG5DCwD+giXBBb5xQKDA1L8PgvyCBQDOwSuBaT9Y/5jAcP+ZgEPBpH/yf/+/sv3D/g89TH0c/ds9qT37vec+Wz5uPSC8Xztkefi6fvsPObx8cDxX/Ab9jz3IOtH8EvvOOT+6Ifwt+R07fbvrtrP8fTzzfP9CosHSQzuEZIHEwnyC80MuhEUEM0PlQ19CCMC+/p3+y71DvHm9E7r5vK+9MHumPa29cvz+PuY+TIBtQqtDC0TnhbvFFYVAhMbDhoMfQ17CpAFEAi3ADf8Efvx8TfxtfFy757yWfNU+Gb7PvySAfABQwWECMkJgAxrEIURFxLnEAkOjQoRB+MEQQP2BMkKKggkCVQIcgBKAHb9n/mj/JcBvgB1AhEHUAOEA1kG/QLaBvMJbQooDO4MRBDeDY0MJww7CK8G9gbIBuEDoQfABs8ASALMAJb7uv42/7T9DwOUA78CWAIuBM4ArwHVAckAgAPUAigCuwFq/1f8A/v09vr26Pek9jP2U/eZ9tv4hvZz9Uz0AfNx747wXOx77t/0ae5u8nn0BfJl9FPxk/Lu6rzxaOpz6MfryuZZ6pHoOfqp/KQJfg3kDAALaQqIBqIJpw65Ek0WRQ96EbgI4wCs/TL2D/W98vjy0/Eu8iH1VvU88pf1TPR69xf8UQNUCDAQEhRJFfITrhH6D0gLqAxRC2YLiAobBtMClvwK+E30tfBN8Vvyk/Mn9ij5lPod/qT9WgBaAp0F2wlcDAYR+BGyEmEQIQ0xCXIGywWRBMcICw20CJkLtAQkANH9+/o8+dn8QgA5AEACUgTPAeIBfwMSAB0GiQc1CsEL4w3EDc4LTQyWCaAHBgjjBeUGkQdtBt8FaAISAbP92P3Y/Nb+VgBfAooDrAOsA+8BvAKPAVsBGwNJA2oDlAL/AcP+mP34+gH4i/cE9cL1A/Yi93f4lPqG9vj0XfGb7H/tq+xa7VLyg/Hp98X0v+x4+HPqkuwv9wnnIO/z9Tzmf+kh7J3iTPQz/8EFZAxBEXkLgwbaCPwFEwuBFEMPZBILECAH0AUB/qj0yfc57wnuhvJL8LTzlPfq8gLzLvTI85X2kf/iBI8LIhQdE5QTjBNSDUoM8gp9CGkLzgiVBTsEhvxb+Fj0ve8w73vw1PGB86b3efrQ+v/9w/4oAO0DsgYCC4oP/RGZE04QCg5gDPcJdQj4DYML5gzpDEwFLwIt/WP5fPe0+pf6nvqiAP37kf7y/if9YAGAA/wGpgk5DyAO3xAODk4M2Au5CU8JtglICfwIBgoHBPsCwQDJ+6X7Mv32+x8A8QIPAoICywTNAeMAXgPOAQsESgVYBYAEagUIAmb/zPwx+fP33fYU+Y/5ifrt/T75jPXy9ZbsLfEb7aHxkvRj+ff4i/Q89lP4iucI9mDt4u0q+9X09O3Q+Zfpi+UY8N7tH/8IDaEJNxKdDtcI2gfLBmwIUQ+DEbgPwQ9PD2kHZAH1/tHwB/Wg8VPuvPaE9/n32flh9ATzBPeW9dL8zgTIC94QbBbfEfsRUxBwC1wJqwwgCUUMVgsSBYMDTv0+9u/zkvDy8BPzrPVp94H7Xfzs+/r8mfzz/yID8Ad+C0gQ9hD0EdIQsA68EOUPORENEYgNaA3JBBsChP6E+hv7ZvlW+Jj3nvgv9lL3s/lM+6H95gJTBT8HNAykDF0MBA3zDTQL8QyFC34LKAsXCRkIuAI6Apn+hPtm/PH7ofw2/Q/+CP5I/Vr+Kv8s/5QB3gIvArEECwRbAz8C9AD2/V39kfvp+2j6bfvE+s/6W/ka9EP0J/K57E3y8fDt8RP3vu899BjyzPWJ7hr23PFq9/r0LPQ09lbyPPRw6n3uK/CF+aUDVAXdC0sLYAZvA9AD5AJEC6kNAw2pD4oMGwoDA33+QvoL91D3zvRg+KD5O/lx+Iz0JfMY9NrzCfii/kUFPQplDhgNHA0pC0MJjgjHCVQMZQ0ZDR8Klwc+Avn8PPn49FD1ivUJ90f3IPma+LD3bfer96z6//zUAfkFhwpVD1YRiRTtFM8WoxTGFSATGhHPDhoKmwfWA7UAK/yp+b71kfJs84/zePN6+Fn5yvuCAL4BEQS2B48KNAsoDsoPKQ8yENARqAyYDhYLfAbaBmcCyQB//8r9K/zg+337pvmm+8r6O/1X/mH+EwBAAPj/RQBpAOr/0QAXATwBSv+eAOD7mv7d/JL6nfmU9PzyH/P873zyjPI87yzwF/G27PD1H/He77j1RfCV8znyyvFS8aTs9fBw79j4MAg8BZgLhAykAh0IMgXKBHoOlw3ZEI0OQwvTCHEDLv7Z+Uj4VviY92b4M/jK9ZD2hfE173/y0PIa9yv9YQGFCHsKdgyPCqEKsAoiC3oNIw8WEGsQ4AuUCMcE9/4+/Mv5tvbl93T3vPZI9hH1KfTd8hf0zPUs+nj/0wROC80PQxVyFAMXthaDFVwXjRSQExUT4Q5GC88HJQJb/Bj5k/OE8oPyh/JB823zSfbz9WT4oPu3/lgBuQbxCfsKKxAbECwP8xBGD3wNow1dDPoJUAjyBU8B6f4m/WH6c/ny+Tf4pfhL+QH5XvmR+cT6u/nS+q/8uf3N/U4ATP/d/Xb/Xv7H+oX8LvzR+g75r/sm+i3y9fk38MPrO/NO8Y3tEPRF9sbos/Cf8w/kmfKM7tjkM+/q+Nr/xwloC68KFwUsCFIGmgiWEtwTaRUCFX4NkhAGCP//uv/O+ID5m/tf+hj3e/d39HLt4+3n7gvwyvQf+pr8nAMZBxQIuQnGCGoKKw2zDZgSwRQtFbwQkA6ICKcEvQPb/0v9v/0P+9/4Lvi69BvzkfI58Cbz2fim/mYGbQloDIwQ0RH0EgAVOBb7FkwXYxeEFdMUzRBcCwkFYgFP/rf82fnJ+Dj3OvY79mL1L/UI+Br5tvswAEUCmwbTCEMJbgnvC8ULdgyvDtYMuA1YDYQJeQlkB5ADPQMGAfD+f/80/r/7qPuN+DP3v/dR9sL2E/gH9w733fej97L4Xvl6+XL3ofiJ+Mr50v8C/ej/Hfm9+A73Pfel9pn2tPZM8i706fND7jPveu+j5YLrHOmR5+X2DP5B+X0Bhf8P/qsCtgagBUkQ8RM/EQgUTBTbDbUO5gleA5MGyAXxAEUBmvyb9g31dfEE7szvV/K48J7zAPfV9rH7cPya/Pv/yASPBpYLtQ4cD/QPPA/iDCcNWQ1MC3cKmwnhBLUE8wAe/OX7kPuL/CD9Gv8q/6gDHgOWAyYFAwd7CFkKugv5DCMPAg2aDeUMZgrlCtIIMwa3Bn0FTAPVAdoAfv0+/r/9ufyG/uT+gP4V/7v+wP7V/wQCMgF+A5IEBAVOBXsF9QQSBPgE7wQ2Bd8FUAUiBEID5AAe/qj9mPyY+y/74fim9wj2jfR18nbxOvHP8Bb02/Ec8iryG/J182PycvBm9Hf17fR49jr0//Wx9RX21vJ29EH0GPLU8O/wcfIf/OD/C/wm/0/9I//XAGgCQwRsCQ8MjAt0DEcMBwoMCRMHDgUBBygJVwZwBaoBGf5z/Ar6Rfhb+Iz5bPmC+X363Pn9+Tz71PmT+1j/vgHFBPUGDQfXBw8ITQiSCC4KyAvPCzoMXAsBCtcLwgvFCuwKeQkfCYIJKAp2Cb0INgdCBlgGPwffBUYG0gVPBPkEBgQNBDwEmwNWA4QDpwMUAyQDKwKDAfIBrQJHAsADywLiAmYDjwLuAlYDFAPmAnEDFQMmAwYDSgKIAV8CXgLwAfwBggA6AKv/Jv5b/Xn8Ivvv+pb5a/kh+Hf3MfU/9mf1v/R09K/z//DM8jfwvfHf8WXxH/AA8l7xKvKg8pTx2/Dv8Dbwe/HX8bPyFPJx9uz7cv1f/qz9VP5lANgCDAPfBl4IeQm3CZcKGQpGCN8H/gaNBjcIHweEBxAGygI2AAj/Cv7e/Mz7EPyI+/n7bftH+vv52/ja+Fn6P/yU/Rb/3P8EAfMAwgGyAn4DigX9BSgIygosDXgP8w1QDZcM1wyQDpIPkA4ED9MO9Q2GDYQLaglJB84GdgUOBUYFdgPZAaQAuf4p/if+6v2Z/cH9Jf7D/vv+KP9p/vD+NP9ZACwBDAL8AnkCTwJ+ArgCkwL3AmICcQL/AvwCRAJdARsAb/6w/V79MPxS+936p/l4+Sv5evfB9o/2hfYL9rD2E/aW9ZH1wfMB9Bf00fT29O30n/SP9OX0JvTb9G/z0/NY8870r/YF+a/69vkU+xH7UfzG/aD+//92AZkD7ASgBtoGQAb1BSAGfwYkB3oIbQheCPIHBAcxBrMFWAQ1A7YCeAJNAnYC9gGfANr/0P6E/sn+/f5O/6T/RwB4AEUBewHpAXkCdQPlBN0FRAezB2gIpAiQCM0I9AhWCWQJvwnSCdAJmQnlCAIIJAdyBucF1AUSBWsEuAOvAgcCYwHnAM4ADQFTAaIB9AH2AeYB0AFvARcBCAE7AV8BTwEiAfAA1ACUADIAmf9m/1L/Rv94/yb/1v5e/gD+rv1U/Vn9NP0i/Rv94Pyt/G782Ptj+wr7v/pg+g/6wPlY+fP4bPjc93j3Cfd39i320PWF9V/1JfVT9VX1j/Xv9UX2oPZ/9tf2IveD9+z3Nvix+ED5/fnV+nL74vtT/NX8cf0V/tb+k/9XAPAAWAHIAUACrQIhA5YD7wN2BOQEOQWIBYoFtgWhBcIF3QXiBQsG3gXHBbwFwwXcBcUFmwW0BbUFqAWZBWUFUwU7BRsFKgX9BBkFDgU1BXIFNgUlBf8E2gTVBMMEzQSnBJkEhARuBGIENQTlA7cDpwNSAxUDwwJvAjUC8gGvAWoBKwH9ANAAtABqADsAJwAdAPj/w/+a/3D/TP84/xb/4/6z/m7+KP7Y/ZH9UP0x/fD8pfxO/Pr7jvsd+6T6YPoN+tP5pflQ+QP50Pid+Ev4E/ix92z3XPdC9yz3Uvdj92r3hveQ9833I/hr+Mv4Pfm9+S36yPps+9f7b/wC/Zz9Xf4i/9D/hgAbAZ8BHAKuAjUDrQMfBG0EuwQFBU8FiwWLBagFpQWiBagFkwWFBZcFkwVoBVkFRAVDBTMFDAUCBf8E/gTlBNYEvgSjBJkEkQSXBHgEXQR7BJEEqgS/BMEEtAS0BMUE1QTgBOAE0QTWBOoEyQStBIEEUAQyBBoEBATmA8MDjAM6A/wCxAKGAlYCKALgAacBfAFIARMBxgBnAAUAxv+A/zr//f6o/lb+Gv7l/aL9Uf0V/eL8rvyK/Fb8F/zY+477OPv6+rH6b/o2+vb5oflG+fL4pvhS+Bv40PeW91/3LPf79t32yfa89sj26fYD9zz3iPfO9yf4k/gR+Y75F/qV+in7zvtt/Br9vP1k/vD+ef8UALEAPAG/ATcCoQINA2wDywMeBHYEuAT9BD8FZwWJBaMFqgW/BdAF8gX9BQEG/wXmBeMFygW5BacFmgV+BW0FXAVSBToFHQX9BN8E0ATABLcEpgSUBIYEfgR4BGUETgQxBBcEBQT2A+ADyAOnA4UDVQMmA/ICvwKgAnkCTQIkAvoBxwGSAV0BLQEEAd8AvgCTAGMANAACANr/rf92/0H/Bv/W/qf+cf5A/gn+zv2U/Vn9H/3m/K38dPww/PD7uft3+0L7BPvL+pL6Vfog+uf5tfmI+VT5LvkS+Qf5+fj0+PP49vgE+ST5T/mC+cD5A/pM+pz69vpW+7/7JfyL/Pn8b/3q/Wf+4f5b/9H/PwCvACIBgQHrAUECmALxAjUDfQO2A+0DGwRGBGsEhQShBLEEvATGBNAEzQTPBMwEvQS1BKcEnwSTBIcEdwRhBFUEPwQ0BCUEFQQIBAYE/gPtA+gD2gPXA9ADywPBA7IDnQOKA3IDXANMAzMDIAMOA+sCzgKzApMCcAJNAioCBALkAbwBlAFrAUABDwHmAMAAkQBhACkA+P/C/5H/Zv8x///+xP6Q/mT+Mf77/dL9ov1q/T79D/3f/LL8hfxY/Cz8/vvY+677hvtd+zj7E/v1+tH6qfqK+mb6Sfoz+iH6EfoG+gH69Pn3+fP5+PkH+iL6Ovpd+oz6uvr0+jH7cfuy+/z7SPyW/Ob8NP2J/eL9O/6S/uz+Rf+Z//D/QwCTANwAHQFiAZ8B2wETAkMCcwKdArsC2ALzAgkDHgMwAzcDPwNSA1UDXQNlA2IDWgNaA1sDVANOA0cDPQM2AyUDFgMAA/AC4gLPAsMCsAKbAosCgQJvAlwCUwJDAjUCKgIfAhUCBAL3Ae0B4QHbAc8BygHLAbcBrgGeAZABegFkAUkBMwEVAf4A3gDGAJ8AdwBYAD0AGwD4/97/wP+j/4r/av9I/yr/C//r/tX+vf6j/pD+e/5g/kb+Lv4U/v795/3R/br9pv2U/X/9bv1a/Uz9P/08/TX9M/04/T/9Q/1J/U39Uv1W/Wb9d/2D/Y79nP2r/cj94P36/RX+K/5G/mP+fP6f/sb+4/4M/zT/Wf9//6z/2f8CACUATAB0AJYAvADiAAcBKQFHAWUBfgGYAasBwQHZAeQB8QH6Af4BBQIKAg8CFQIdAiACHgIkAiMCJgIsAjYCMAI2AjcCNgIzAisCJgIfAhkCEwIXAhgCGAIJAgcC/QHvAeYB2gHOAcQBtwGsAZwBkAGAAXEBXgFLATMBJwEaAQMB9QDiAM4AuwCdAIMAaABSADsAKgARAO//2v/B/6v/kf93/1//Sf80/yH/D/8E//P+6f7d/tL+wP6x/qz+ov6Z/pb+kP6I/nv+a/5k/mD+Wf5V/lH+SP5B/jz+O/5A/kL+Qv5D/kT+Sv5S/l7+aP5x/n7+k/6h/q/+uv7L/uD+8P7//hn/Jv8w/0L/U/9m/4X/kP+c/6n/sP+s/77/0f/W/+H/6//5/wQADwAMABMAGgAjADEAPgA6ADwAQgBNAFQAVABfAFYAWQBfAGUAZgBrAHMAcQB4AIEAgQCbAK8ArgC0ALYAvAC7AL4AvQC8AL0AvgC2ALkAtQCyAL8A2ADLANoA3ADfAOIA4wDfAN4A1gDZAM8AygC+AJYAmwChAIIAcgBlAFQAQAAuABkAEQABAPn/6f/o/+X/0P/a/+n/2P/V/9z/4P/R/8X/wv+y/67/pv+d/5r/kv+C/5D/hv96/4X/bf9n/2f/ev96/3P/ef9m/4H/e/+I/5L/pv+5/7f/tP/P/9f/1v/n/+j/1P/U/8n/x//K/9b/1//h/+f/2v/g/+P/zf/c/+b/+/8OAAgAIQAkACoALAAeACkAMwASAA4AAQD4/+f/1v/Q/8L/w//B/8j/0v/G/7//7f8SAAwAFAAFAB4AFgAcAB0AFgAUABgAEwARAAkABwAJABIACQDz//D/5P/n/+7/EQASAA8AFgAdAC8AMAAuADgAQAAgABoACgAUABIAHAD//+//5f/M/8v/wv+z/4X/uv/a/7T/qv+7/7D/t/+7/6f/sf/B/7f/yf+w/6v/mv+U/7v/n/+i/5v/nf+w/5X/nP+h/7T/qv/I/9P/u/+8/8z/8f/P/9H/zv/R/8D/xv/d/9X/1v/X/9//yP/l/9X/4f/3//b/7//r/+7/9//s/+P/3f/Y/9L/0f/d/8r/zv/l//L/8v/u//D/6P8BAAEAEAAGAPv/+//i/+//3v/W/+//3//l/+T/3f/Y/87/5v8FAAYAGgAgAA0AJAAeABcANgAmABYAIQAjAAcAJAAyABsAFgAbABwALAAnACgAGAAkAGUAOgA0AEsAXgBcAFIAbwBYAG8AjQBlAHoAZAA5AGQAgQBkAEAAEQAwAA0A/f8bAA4ADgDY/8//6v/j/wMAMgBIABcAHQA9AFEAXwCBAGEAbABnAJIAhwBnAF0ALQArAEIAQgA5ACAAFQAFAPr/BwAuAEMASwBaAEcASAAiAFAAjABqAGgASQBVAEgAOABOAD8AIgAfABYA+v8TAPz/GABHACsAKwAyACEAIwBCAD8AOABdAGcAWQBIADIACQAwAFcAQQAuACUAIAAXAB8AMQAxADAAFwAHAAUADQDo/w8APAAkACIAFQAaABoAOAAiAEEASgBJAEgAHQAOAM7//f8oABYAGgALABkADQAUADMANABPAFcAVwBlAF0AMwAxADwAFQAHAA0ABwAIAPL/6v/Y/9//6f/c/+z/3P+p/83/DADX/9X/DgAZAA8AHAANAAkAAwDz/+z/0v/k/7T/tP/P/6j/rP+t/83/uP/I/7z/vP/L/77/zf/I/9H/uv/T/9L/9f/b//b/6P/o/9r/1v++/9r/2//V/9v/z/+7/9n/wv/C/7T/u/+4/9v/1v/i/9//4v/U/+D/0/+2/7D/u//h/9v/7v/b/7P/pP+H/33/jv+x/7z/tv/L/77/xv/W//X/IQABABUAAgD9/+r/+P/N/9r/6//2/+7/9v/1/xgAIQAIAAkAKQAqADAAIAA/AA4ATQA+ACwAVQA9ABoAHABeADwALAAmABoAJgAzADgAUwBvAGUAPAA8ABYA9P8mAHEASAA5AP//BwDZ//b/AAD8/wEA8P/K/+L//P/d/wcAGgAvAC0AaQB/AGkAfgB5ANgAfABeAGwAdgAwAJMAKQBUAGoAxQBoAAAAwQCA/88ApACgAEMAtwCKACsAZf+qAHgAGACz/2sAkQAcAOYIjRAYAu0Bi/rr9jr3ywYfCUMEW/9V/WP5e/qDATsHjwOxAAQAuP0r+5/+EwJOAiUAbACt/nD97P+xAysEUgF8AF7+Xfyk/cz/aQGbAFb/Ff+w/6n/7QA1Auz+K//f/xEC4gMvDQUM4gae+933kPTH/v4E5gnkAzn+pPaX+LP7Wf1BAGwAvP/IDcAKJQd+BuX7fPaE+dEFOAFBBTEKaQbK/b0IBf89/If+3gg4A1kGRgmVAZb7BP32AE78Jfzx/8QDIgIqC0YIkgK7+lb79frA/XMGewdaBYwDBwXu/2n/gPwV/Mn6nAKJBUoFLQRxAPH8avsg+af8g/wlASQGKwh6A5T/2vvS/JT+9QM5AD8AAv9RAhwBBv/k/F/73vm7/UL87/4G/iUDDwAZ/rj7A/n9+an6NgNPBKv9bP7p/nkABwKT/Xj+5PfK/BQCYQOsA8MCtvrI/b/7v/0B+zb7Df9t/kz9qv/0/H/8ifzY+wr6yPga/ev9z/+F/0v5Xf2f//37bgEI/wv6Tvhl/c39TP5hAFP8cvnZ/R7/KvzH+pP9mveW+rr99v35Aaf66fs0+136NvlQ+vb7I/9YAbL8Ov8n/5X9Xvrd+on3xvqt/DAEzgD1AM372vtz+t76Mv4i/msAQgIZ/usBL/37+Qn4Mfzq+aH+gABuA7sBlQLY/NH6AfvU+Bf9NvyOAjoCjwXiA0z8Ov7g+qz6S/vC/UQCWgJrBdAByP/0/Iv8kvmx/GIDcQMzAXAC5AFHAB3/dP+Y/yD8yv/C/nAAcAQMAfb9OwB8/aH+BP9N//L68/wnAQsBCANVBHIBrPzH+zz8O/+OAi0Bhf/w/oAAgP/1Afz/sP8OABP/nP+vAXYCLgP//xb/OP4xAOj9yABjAOn/2AB0AP3/kv6b/2b+Vv43AM3+oQA7AdcAmv+6AY/+lv65/zT+7wChAeABgAAHAowApf07/9f8C/4S/gUB7QAKA+sDOwGXAI3/5v71/jD/qAAyADoCFgMuAVUDcgTz/nL/YgBn/nD+rQB5ANkAxgKVArkBVQO5AUoB3/5P/3H/aP+2AIn/fwHLAg4CwQHEAgkBsv+Y/8j+N/+eADYBvgFnA94BsAHt/7QAHP8d/3b+3f7WABgCtgBhAjoBlwAxAFwAFwBbADQAewCTAJEB7QGFAokA0gF8AoUBWwIJAAAAM/68/zUAiwEKAncCHwK8AXQB6QAaAJD/VwDi/1YAEgELAasBDANHA2gCzgIGAFT/Ff6D/LD+Uv8aAc4C+QMjBLsCmgD//1H/Jf7g/RwAwwAMAq8D7gNwArACxwBo/8j+l/7s/bj+6/93ARUE+ALiAzYCjgJkAVsAQv/PAKwA+AGnArICDAKSAnwCxAKkAqQCXwHWAD8AmAAsABIBowFtAgcDEQIpA7MB0gHt/2UAm/67/q4A/P+4AboBFwLIAn4CXALZAEUAlADG/9gAWwLLAT4DzAJtAkECJAECAJP/WAAbALMATQA0AecC9gHgAXgBVgEJAWcBmQBpAe8BJAExAWwBCAEfAcYALgEBAtEBAwEaAX0ARgFLAGkAYQD4AFoAdgAIALT/xv9p/x//iP/1ANb/EwH4AacBFgF2Ae//lgA8AM//uf+0ADIBYwGqAbEBcgHuAP7/mv8lAML/pv8wADAA2QDfAfwAxQHPAbQBdQBFACj/7v5g/sH+Lf+i/6wAKQG2AXIBQAGTAGj/1/59/t394v0+/zIATgFHAh4D2gIxAvEBvAC2AA0ARQB//xwAhQAPAVUBqQHtAVIBMQHLAEMACwARAJn/Nv9V/1H/3/8zAOYAKgFjAYYBzABBAJH/QwBt//b/bgBrAccB5gHvAmYCfwIOAoIBnADV/+r/x/6K/6//sADHAB8BbwFQAf0A0QDiAMAAyP/i/8L/7/74/kv/Jf87AHYAvADEAKUBGgFiAbUAaQDR/67/S/9S/47/yv9SAL0A+QCGAUYBTQHcAAgBSQBMADYA1P+V/wr/Mv8Q/5X/pv8qAHAAUwAtAJj/kP/2/m//Jv+0/7P//f8OABgASgBKAFMATQCu/0IAJ/+9/0b/9P9cANwAxgDCAFQAOgD8/lr/BP+l/xQATgAwAVgBaQFCAQIBDgFkADkAOv89/4r+8/5f/7L/ogDQAKkBEAG9ATUBOgFZAK0A2v9L/5X/qP7G/wQAzAA0AcUBTwDIAZsBhQC5AicBsAGFAfz/OwCq/yj/HgAAAPD/mADT/xIASgCU/7AAgwCeAOQATwD9/x8Ah//k/y4A2/+lAPX/VQD6/5H/mP+t/17/5P9B/3b/KP8U//L+Af/F/un+gv7c/sb+0/7O/tz+f/5Z/uH9jv2e/RP9Vv3L/dn9Qf73/Wf+V/4m/kn+V/6y/tT+t/7b/qL+gf5I/gX+bf2Q/Xv9dP21/f39LP43/kL+Vv4L/hr+5f3W/Rv+6v1r/n/+J/8o/8z/Uf+Q/2f/Iv/N/sb+jP5f/of+dv7E/vv+Rv+O/3r/vf+r/6L/sP+S/17/W/89/zP/Tv9a/3f/mf+5/wQApgBOABoBsQDyAKwAxgBoAHkAIQD5/5X/nP9+/2L/uP8kACsAyQC9AC4BgAGMAbQBlwF0ATYBBgHJALkAyQDKAKAA4ADfANgABQGiAR4B4gHFAYEBhAHYAIMA2v9+/0j/3f7j/rf+dP7J/tv+Iv+T/0H/0/8AAML/9P+4/1n//P7p/nn+Sf5X/m/+Wv6g/nv+eP6m/k3+L/4J/vL9vv3w/cL9x/0H/iD+/v1B/qL+ov7f/gb/4f4U/xL/pP62/pf+p/69/tz+2v70/jD/5v73/hD/9v4t/1f/2v/C/5cAUwC/AHkAywBVALQAbwAGAccANwEjAY0BbwFrAWMBeQEjARkB8gCyAKIAnABzAGIAhwB0AH0AigClALIA6wADARUBWAGuAe0BOgJaAtUC6AIgAwcDYwM7A1IDBgPuArYC4wLOAtMCxgIIAwADGAMFAwUD4ALlAsMCuQKhAp4CSwIuAvcB4AGUATUB6gD/AIMAQwAyANP/fv9Z/wH/S/4b/qP9T/3V/O78S/ya/Ff8a/x6/Cb9JP3V/az9PP4g/n/+/v3m/Y39df1m/En8vvtp+zT7Efu1+tv6aPsz+7T72vtz/IT8n/yg/Mn8n/yI/O/7x/tK+0P7CPuw+u36KfsI+zv7bPvE+0z8L/zD/Or8b/04/TL9FP1J/R/9l/1G/ev9H/5d/t/+gv9xAGkBaQJhA0UEVwVLBvQG2weNCEIJqAnWCe8JDgrfCZMJKQkgCaAIJAjLBx4HzAZtBuUFfAUUBbkEWATeA24D8gKxAlQCFwL3AdEBjgGWATIBQgEvARcBxADPAHQAJQCA/2v/E/8l/7/+l/6G/nv+Iv4X/ub9l/2e/W/9Gf24/Ln8K/wQ/Lz7g/vz+vT6Sfo5+uj5yfl1+YT5k/l9+dv5kfnk+U/6WPoB+nn6PfpI+vz55vkS+Qn5Ufiw9xP3tfYR9kj2jPaj9k33QvhL+br6LvzV/WL/PQG1AjUEnwXRBkkHQgiICM4IHAkaCdwIsQgvCNUHLAffBlMG4wVuBfQEbgQoBHcD1wJHAp8BYwEbAcIArwC2AB0BTgHtAaoCTgMdBOkEAwb2BsMHiwgZCWwJ2An6CewJxAmqCVYJ3gh1CAIIiwdYB7EGWQb6BXYF5ARHBMgDNAODAtQBvwDw/w7/AP5N/aX8CPyB+w77lvpP+jj6EfoP+gP69/nq+Qn68vnZ+f756PkV+sz5ufle+Rj5B/m4+Gf4IPie92D34PaA9jr2zvWc9RX1k/QU9IjzNfP88pXyR/KM8snygfNZ9JD1zvZp+DD6zvvT/Yr/XwHXApoE7QVWB0QI9giQCd0J9AnrCcgJpwk2CaAI7QcsB5oG4QVBBaEE6QM8A38CuQH9ABkAcf/s/iz+tf1S/UP9L/0s/ZT9Ov4Q/x4ALgFHArsD7AStBvsHPwkjCv8KlgvWC/0L7wt0CxMLjQr+CVUJdAjCB00HGgfYBpEGeAbmBVoFzgTvA0EDhQKhAcQA/f9k/7f+Yf5X/kP+RP7d/bT9h/0f/dH8mfwF/Mz7f/sz++b6ePql+nH6S/pZ+iX6H/rS+Y/5Q/n2+LD4Svji94r3uvZh9rL1W/V99An0FPOh8rnxdfHn8KHw0vA28cnxkvL982j1Sff2+Bj7CP0e/w0B7gK+BIIG3QcsCQ0K3QqQC8gL7QvSC6QLMQubCgMKZwm+CEsIcwfRBvkFCwU1BC4DTgJhAakAEABX/6X+RP7W/br9q/3t/Sr+f/4y/xoAJwFYAnADxwQgBkAHWAhNCT4K2ApBC3MLnQtQCwcLUArOCScJjAgiCLQHeQc3ByEH7gbcBtoGwQZrBvwFgwXwBF8ElgPqAl8C5gFkAb4AVAD1/7z/oP9g/xf/vP5F/tL9K/2L/AP8W/vy+lv64fle+eX4ZPgB+KH3a/fx9rX2QPbr9Wb11vR09OnzP/OP8vbxZfGh8AXwau/V7nLuI+4M7hDuUe4e77Pv8PBK8tLzxvWH97P55/v//f7/0AGGAzoFXwa1B1kIOQnmCfgJKArtCdMJegkOCZMIGQiMB+8GIAaOBcEE1wMgA1sCjAHfAD0Avf8v/77+XP4B/r/9f/1l/Wf9kP3k/Yf+NP8ZACUBTQKuA+sENQZ8B4YIZwnqCXoKoQqWCkkK8AmLCfYIhAhGCBwI7gf/B+MHAQjoB+EHuwdrBxoHlQYpBq0FJQWbBEQEtwNyA7YCegLXAYYBHwHeAKYATwD7/87/bP/w/mX+2/1z/cX8V/yp+xP7m/rx+Yz5+Pih+An4tfdJ98H2ZPbm9Yz1KPWQ9PXzd/Ov8ibybvHP8BTwWu/H7iTune1E7fDsAu3s7Mntj+6Z7ybx2vIY9TD3fPng+1H+twDVAsEEoAYcCHsJpQpnCywMlAzkDPgM5wzPDHAMAwx/C+0KLQppCY4IrQe0BqoF0wS1A+oCKwJpAccAEwC9/13/7P62/pz+uv72/lP/AQC4ALwB0QL0A0YFfQbLB/0I/QnYClcLwgvdC5kLZgvMCmQK2QliCScJ+wjuCPEIAQlRCTQJHgnyCLcIgQj+B6kHPwe+BlMGwQVKBecEYwQdBO0DcwN1AyIDEAOrAmICGgKmAU4BxgBjANf/P/96/s79SP2L/L37EftQ+tz5JPmd+Pn3Zffw9ln2zfUQ9Wj0/fND87Py8/Fh8dPwK/CG7+DuTO7O7STto+wf7LjrcOtx68jr/esK7QXufu8i8UTzpPUs+Ir6T/3+/14CqASuBpUI+AkiC+ELdgzUDOAM2gxtDPoLsAsiC2EK0AkPCU8IVQeQBrEFpQSGA4kCjgGuAPD/WP/D/kD+8v22/X79TP23/Q/+jf4Y/ygAOQFFAokDtgT6Be4GEwjZCIIJEgqFCtkKEAsACygLFAsAC+8Kzwq3CqIKjQqLClsKKQrFCWkJGQmJCBwIeAcdB5QGZwb5BcYFYQVDBR0F8ATnBJ4EYgQlBMEDRAO/Aj0C8QFlATwBvQBYAP//rv9F/+b+Rv4Z/nH9YP14/I/7DvvE+a75y/cP+Cb2OvYU9Zv0B/QM89XyL/La8TzxC/F48EHw+e9c73Lvyu6q7h3uIu5L7YHtsexp7ZHtx+1Y7/XvZPK/85b2EvnP+2n+UwGKA0kGpwefCfkKuwvYDNYMQw1FDfIMBQ1uDAoMmQsDC2sKkAm0CO8HtQaEBR0EnwIsAaf/G/4G/bz77/pV+uX5F/qK+jr7H/xq/e/+cQCrAUkDmwQIBj0HPgiHCUsKZwv3C74MoA31DeQOPA/GDyYQLhAhEK8P+w4yDgENnAsuCscInQcxBi8FVgSxA2ADzgLzAgYDLgNHA1kDkgOPA2oDDAPEAksC6gGKAQoB0QAeAPz/hP+e/5X/iP/O/3L/df8X/4H+6/3j/Pn72/os+Tv4eves9s71yfRJ9J/z3fIn8vbwivCr7+zuzu4B7pfuYO0u7n/tBu7N7WDt4O2T7VXtaO1o7eHsYe3S7CDtMu7U7cjv1/Dc8ib1efcU+jj9vf+PAvIETgcUCYUKCgx3DOYMQw1yDMUMnAsIC3kKTgllCNIHZQZoBRQEsAK2Acb/Vf7O/HL7MPrk+Hj47/fz94T4IvmQ+iP8mf2h/5cBOgNDBWsG4AckCc8JxQpRC9ULrwyCDb0Ogw+vEPMRHxP7E0AUORTlE7sSUhFxDzsNGgvHCHsGqwT5AhwCXwF1AUcBAwKKAmUDzQN9BGMEewT1A38DOAOzAjkC4QEQAn8CyQKOAxYEnwT3BNQEfQSFA1kCYwElALj+ev16/J/7nfpF+mn5G/nS+CD4EvgI95b1YPRk8zPxXfGC7+juYe8N7szuZu9l70XwFPBg8ELxq/GY8ZDxpvFm8JbwsO8277ju2+597S/wme+c8iz1KveJ+hn+AgGIBWgHQQrUC5YNjw1jDt8Nqw3SDFEMywukC90LagoDC1YJ5Ai8B4cFkQOHAYr+kvxD+hr4Zfcr9lb2GfdW+Lj6j/wg/yIBXAOWBb8GOAj+CIAJTwpXCnoL7gutDL8N/A5mDwYRSxHzEroSqBJqEkoRVxCTDrUMNQvyCJUHBwbYBFQEGAOyAi8CGAKwAhICIQI0AvMBhgJ0AvYCgQOKA8IEFQU8Bv4GIwcOCMYHvgeKB5kGPQaHBFIDIwOIAWwBFwCA/y//Jv7a/e78Wfwj+8n5yfi89172pPW384ryxvF78V/w1PCw71zwaPBJ8ODvVfAR78Hvve5E7nbu1O5i7Wrve+7W7/3wL/BM8avxE/CL8ebutu5K7eHs2O407+nyyfX4+Mv9vQD2BZkJEwvqDfUMvA2LDZELpAv8CeQIBQkbCEkIpQhcBwgH5AQ5AyMB3f2C+z345vXE9AD00vQH9tT3Wvt8/UEBggRGBjMJmwm0Cr8LTAtMDH0MogzCDb0OSBD5ECURgxHyD98OGQ2gCtEJQAckBMAD3QOKA70FhAOeBXMGbwdHCMwFHAgPBpsGsQV/BrQGUwY4CLsI8wpoCngMPAzSC54KYAqUCRAHnwWlAzgEQgKWAtsCaQL0AgsCSAJ2AQQBwP/Z/sr9uf2b/Sb+Yf7+/gIAPgFeAbQBNwEGAPv9K/xL+pz3JfaD8wv05/I88v7yL/Pm8X7zae+08g7wtO5Q7knwlusc8kztIvEX8anxhfR+8VH2cPGf89PyXO8H8IPu+ekA7xju9fFh+BX4NADgAucHDwwrDM4OFQ57C/sMlAkiCoIJmAf6CGMIuAc4Ce0GMwQAApX+9/tB96P1wfIa8Z7zuPK99wX7Hf0XAuEDegY5ClIJxwpJCmUK+AopC7wMRw2bDUQPBw6pDucMjwrtB0oDWADt/ND58Pi6+W/70vve/ysDkQaYCfIKiQtWDBoMgQuiC9QKyAsHDIoMUg2wDewONQ1HC30JlwZxBHgANv7k+3T7Kftf+8z8Wv7u//4ALQGkAmoCcQJEAQIBQwEEAgEDPQNcBWIGQAftB60HBgflBVcDLQGy/nb9MPzw+Uf6v/ik+Qf6l/cP+F73c/Ws9DfyVfIy8HDw8e/37g/zDfEl9iD10PZM+IH5YPeZ9nP5UPE3+Jjw/vI+8qvxdvLR7svxku0X7bbsOOwz8Lf0GPaE+wECgARtDbwOlxHREgYTTxO6DtMQBg3TC8sKQAiHCPQHfwRUAhIAPfuf+r71sfIQ8ZbwdfFD8kn3hfq9/VcDBgV1CZ8Mvg2JDkwOFg4JD9YOQA79DuMNOg6DCwYLDAjnA0sB3fqu+Mb0h/KU8Y/wfvJX9ez43Pz1AU4G6wowDycSsBOUFqkWRhaHFpgVvRTjEsAPOg2KCnkG0AJJ//P6NvhL9Z/zufPX9Ln0bveN+X38TQAFA08EJgdECSgK6QtdDIENyw31DmINrA7HDE8LZQiaBmcD6AAS/7L7xvqK+Uf5d/i1+ZH58PkZ+5T6Uvzn+4D82PsM/PL8evwz/Nz8l/vk+1b7k/gZ/F32JPgm9UH0MvYb8bD2tu7x8971fu1A9UbuD/K28ubuXO9p8drtDe3s68Dp0+qM8KP67vbdAZEHJA/KFJQVzhjTGgcVYxJdEHoMbglnBdMCfgCy/6X/V/u59/v2z/Kh8Vrtdeu66y/tr+4Z9Nb5pACgBGsK9A8qEyoWjRSwE8wTPA+9Ds0LcAnVB2oFvwMCAZL/2vwP+Ij0PfId7zbuieyP7UrwfvNb+Ib9ugI1BykLxA4jD5oQGBALDnQNOA37C4IOOQ4LDpIO4w7cDe4K2Af/AkH+Kfpc9WzzevIh8pz0Ovdi+4z/xQMgBqMISAqNC3IKIQpkCn8KUgnKC4gL4QusDNMKZApGCEAEDwGD/nD6bvh294H11/XG9/j4R/sH/vf+qP/nAQ4CJgL4AQ8CpAEYAf4ABQLqAOQA/f/s/aP+I/s5+Un4wvXf8snzJPKk8RXzWfCy8qHxHfF48+3yp/Re8hL20PRL87n22vRJ9jDxw/Y37hnwW+nQ7Wf9+ve1/PoEkg1NFJ4VHxnsHGYaxBFPEXUMBgljAPz7EPvZ+Ej7sfY99kb2MfZp9vz0kvAT8nzxkO849Zj3Ev72ARcFIQ9NE9wXmhbnFSkWoRJ8DUAJPQVYAN784PnV+7b66PgR+E34JvpA9jH1BvZ39G/0pfTO+Uj9af9/BGQKlA8cEvAS5BO8EZQOBQwTCFUCBf+e+gT5B/k3ABj9vPylAwAC7giOBLMFwwPeBSf/fv5LBPT+Kf95AnYDcwV5CPcG2geSCjoGLwc2Bc8CVQCpAMEAaABhANEBFQJ0AZ4FbQWaAnQDkwHOAPcA8f27/gf+Pv4A/bIATwI7AfkBIgIAA2wCyQCT/r3+mv6M/DL8avyX/Db6C/1H+4j8sPyp+tT7UPo8+935l/fy+Drzcvis9OP0dfRm9BH2lPZj9Hv3Ufaw8c73r+/b9KPtmuh36YDmWOOI8AP0xvQ4/+4EqRT+FgQYPiHeH7ocMhdUFOIPSwXC/C3+u/eP9SbypPDC9TLxRvSJ9OfyFvID8EXz1/QQ9bz4+PtPAeYI/w2WFPIXGRkHHT8bqBhSE1MNrQjwANf6+/Yj88jw9+1N76TxN/GJ8270Cfhg+tn62fsb/5b/zALiBZkKzAzWDc0ROxN6E4kSMhBBDfMHCASt/836UPZG8qrwbO9v7XT+6fh//ggBSQrKEiUNAQywGC4QCAxeCSkNMwhgAUcBUARhAlgDGwPMAeYIkgNWC04CtAiVAkUFMgB/BLAATQKh/0kBfAQiBr4CpQQgBTwE7AO1AQMA8/5z/hf9lPxj/hMBbP7FAX0CHQbeAy4CNgNkAtMBz/0g/Tj9evrN+bP5UPrM+jv5+fpa+v76gvow+lL5w/bN9kH1dfOq83LxxPP89Mf2d/W49uz5mfbW+MX04fIb76rpWef+7MjyYeyc9Ij7BwdzDM8QLhjSG0EeXxhnG0wVLA4oAykA5PuV9M7vD+t07zDta+/U8kL1KfZk95f7r/03/+T9IwA7ASADGwZgCM8MjAyjEEwTLxSZEhcQ+w1qCt4EQ/7i+gv0ie8X7VDsB+2y7A3vSu8++9EAKPfSEnb9vxF9CRsSAw9dDO0NSQsdBwIPTAJECJoBN/9EBXX5zQH284n7OfOx9iz0CPJ7+M/9q/yaBPMJzQ28Fd4SUBrzFcEcZg+cDyIPNQWTAsT9IP2m98j6QPiP+8L9L/8CAh0E0AcmBFIIXAXsB4oCvwWlAhoBBAPQANcCBAJrAjgCoAIJAlQBvP84AWD9I/17/Un7Kv2k+vr9xP3g/Q7/Ff47ATz+1/7l/jT88/kH/Kj2Tft69oj4v/ml9177TfgF/On6Mfjs+e34lvgg9or0+/Yy9vP1p/R19uz1GfZs9Uf1kPQs8UHvye3R8V71BvbZ96z+bgQzDIEO6BOaFlMZ6Ba+FasUFw5kCC8BSv9E+g/1cvAN8GHwTvBC8nX04fce9yL74v2KAQwCxgLaBGMHWQkGCzENtgxeDxsPyhDiDiENbwvOB0cEVgAh/J34cfTf8dzw7fCV8TPyefR0+Ib86v8qBBQH7wnxC9sNUA8xDlQNYgzdCccJowYkBdMCNgBT/wX9Vvzc+kH5cPga+KP5wf+G/tQAMAQBCL4NMA2eEOoPJxGbD0cLcg6eBwoFbgGQAfP/wf0f/Xz9Bv/F/9gBYQHXBQYC/gOPBJEFCgSWAXgDov/rAeoAaQDl/0MB1f/bAFoC3f/sAHMAEQAK/3L/xP5I/dT8qP1U/U3+3f1h/En+Tf0N/cv8y/x9+975Gft2+QH5T/jx9w/4Lvga9tL1FvVY9JLz5PNN9drz8PUI9db4E/lY+X35vvm6+Cr1X/TZ78/tIuta8anwXfNH9iL9JQaFCTMQ1hE2GRIWphSfFIUQNQqcAqP/bfuw91DyAvNw8grzpfP89PT5cfga+gX7c/7Z/n7++/9MAcsDogSwCDMKlgxcDTEPshDhDu8NUQsYCDQErv/0+6z4/vOr8SrxafH+8bHyH/Zn+RL90ADvAzwHtghuCtYLxQzWC4gKrQnMCPQGigW7BPkC1QHk/53+/f07/I76RvlU+NP3tPdf+NX5wv5eB0QKrw4vEssWohn1GD0XMhLxEAsIEgPY/2f8RvfN9Fj4Gvgt+0z9XQDIA48HQgeQCKUK7AbrBF4EhAQdAcgBBwBM/3UBvAIqA0UDfAS1AdECJAJi/9D98f1M+zn6M/t/+7b7Rv1M/rT+dAEiAN3/m/84/0P8yPun+nT4ffdF9gX2tPXT9dH0sPSj9aH1rvV09ST2NPRM9lT0FfRS9IHzo/Jx70LwY+2l8t70WfWU+cL92gKpB1oLrw/lEDISJhEfEJUOZApgBJwB1v75+tT2J/Wr9IzyfPQ/8wj2Svdm9jP4q/kr/C39mf4ZAK4BIwQmBz0Jhwt9DJMNWw8dDqINrwuACPEFywF2/nP7XPcj9U7zTPIx8xjz2PSS95b51/xPAAADWAUMB5IImwmSCuQK1wktCa8Ihge1BpsEcQOOAkkADAD9/i//rf58/5f/UwCkAL0BnQHbAogDHwSEBXgEEAW2BaQF0wVHBUwGmwWDBlAH4wc7CO8IRwclCLwHEgaIBLEDxQGy/0sA/f0n/v/9PP5u/t//tgBmAFYCIQIRAlgCuQJEAb0AqgBG/3r///6Y/ij+mf7b/Vz9Zf5Q/cf8tPzh+1D7nPoR+qL4OvgN97T1JvZ99FP0qvPt81bzV/T09Gv0KPbk9V/3Ffg8+LL3svaP9ljzcPLF8cH1bPbh9qf7M/65BeUHvAytDmsRhBDcDoEP1gvuCIoBJAFJ/dj6rfhL9473Fvhj+V348fwV+1b8V/tl/SH+Af5IAI7/sgEOBO8GXgnNC68MqQ43D8IOpg10CzsJ9gQ/ARf/IvuN+Jv2z/Tq9Q/2Nfcs+S378/zh/rYBpQPgBLsFrgalB7QIIAnqCSILDwxwDSEPHxAHEIEPAA7tC1sJzgWVAn/+p/oX+B72vfWo9Uj3D/m3+9gAVATRB3AMKA4nDyQRhxBjD4ANWQyrB6oHDAYhAj4D/wCuAIn/RQEm/4X+6f8q/Qz9xP0//Yz7sP5M/aD9/v+FADkAGwGAAmP/oQDg/5z9fP0F/TH73/qY/F/6ifpV+4v5SfkQ+CT23fOl9DPy2e9H8XLwt/FJ8mHzkvSM+FX47fhR+Zr4RffT9N3xRu/Z8H3zy/KC9Yb7EQCaBQYKQw/tEfoTMBExD64PiAgZBVn/uPt0+W737fUv9iH3PvnR+XL61v0H/MX9cPsb+9f86PvZ/Ef+fAAOBBQHaQpcDkwP9xFIESsQMQ8RC2AHgwPU/X/7YfhD9nv1ePXU9mD3qPlh+zv93v6b/70A4AJMBGkGywgaC0kOrxBXExMUFxVWFKkRXBBPC48HpALL/d35pvYK9Y3zPfXd9pb5if25AA0EFweRCaoJRwvCCjUKogncCE4IlQdICN4GFAhqBzMHNAY0BWAE8QH3ANf+GP7v/IP8CP1//CD+Pf6l/0AAAAAjAEL/8f4C/fX8Qfu++tX6evqJ+wT8U/1N/e79f/yr+0X6Nfe99RLzwvJA8CjxMfA58kz0ifOb91T2EfgG99P1rPK68Yvvt+u08PDxLfP9+Zn/hAP8CqMPIROKFb4URBKMEZ4Mfwd2BY8BI/yY+7P7h/r7+sD64vt0+0b6g/kh+cT3g/Vh9q33PPiV+ykANwSPB/sLMQ/bEVcSvRFTEO0NrwkoBrED/P9c/ar8r/t5+8L7gvwa/R/9qP12/mf/0P9dAW8DCAUvByEKbQxfDsUPuxBWEMoOHw0rCkQHYQN1AOz9Cvx1+1P6//zG/LH+6gAGAkgDyQPEBI0DMwRHAzwDWQMlA9QDpwR2BQ8GxAZwB7gGLQaYBb8DpAIDAS4AU/4B/rP9G/0x/rj9Xv53/tj94v0g/Zf8LPu8+mX6gfmU+af5nPnV+Z75JPou+Vr3lPeo9W71mfTe8mfzV/I/80PzBvXt9Iv0Mfdx8x316fPf8pvyCPDS737vAO7o8jrzXPdc+Zb9HwIiAtsGhAh+CPkI5gYyCJcFXgT2BEYEKARsAiYEuQRmAmoDuwF+AW8B8wCZ/dv+sf5K/CH+dv46AMQAUgDjAqEDpgOQAy8FAwUFAmIDmwPSAsgCYQJ7BZcDuQMxBYgGqQZQBqMI7Qh0CLUIsQi/CVoI9wdhCEEI8wbXBQAGoQXKA7UDrQMaA04C5AFuAsoB0wEtAhcCEQN5AkIDZwPBAzEEkgMjBAYEOQPgA/kCGgPdAlUCZgK9AdsBCAEiAV0BRQDYAPgAOwCiADgAgQA2AAcAuf8j/5v/e/65/nf+Hv4U/qD92P2O/Wf9dP0U/TT90fzU/L/8ffyI/Nn7K/zT+9f7IPzA+wn89Puh+377OPv9+ob63/nl+WL5PPn9+Lv4HPmy+M/4fvht+IL4uPgv+S35FPpR+ur6//tA/Ej9Wv02/nb+wv52/zr/2P8NABMApACnAHEBiAEIAqoCwgJTAxUDqgPMA4ID9wO3A9wDrAOJA5QDHAMrA/MClQJ7Au4BBALSAZABewFcAWoBZAFmAcgB/AF5AigDfwMDBIYE6gR2BZIFkAXEBb8F0gWCBX8FXAX8BAkFAwXRBLQEfgSHBDkEGASuA2cDeQMBA/4CFAPiAowCmwKHAkECSgIqAhYC4QGbAZQBeAFnAVABSwFeAWoBTwGYAeUB3wH2ASEC0AG6AZwBYQEWAdQAVABQAN7/nv82/zr/EP/I/oj+IP7+/ar9nv1x/Ur9Nf0u/Qj9F/1l/Tr9ff1e/QX96vzt/Ir8oPwl/Nb7WfuO+0f7V/vG+sn72fow+9/6UQD1Amv0dgCZ9OgFdfIjBev0OQPv89L8MvyF/sz8e/lg/SD6s/zp+U389fvh9+X5NPrM+/H6LP0IALz91QBG/JsBvQD2/gMDPADEA/T89AIQAD8FaAJgAssFUQE1A9sB+QO0Aw8B2QE5AD8Dsv8cA6AC+wI+AisC9QOZAuQDRALKA6cCSQKcAyUDkQRiAkEEJwM/BJQDGQOhBHMCoAPYAQAEMgIgA4UC/AJxAvsBRAIUArEBdAERAZ8BgwB8AVkB7AHQAXUBGgLSAXECEwEuArcABgFCADcAkAAfAFMAIAC6AAkAXQD2/z8AXf94/9v+NP+U/uL+e/4F/8/+Uv+q/jz/Df+5/uH98P4h//79FP4O/7f+0/0k/nX++f3v/Xj9r/0F/V39qvxh/TL9Wv25/Ej9Df1R/cT8kf0w/Qf9IP2C/Sj9Vf3W/fz9Kf76/QT+G/4n/v/9//0C/vv9uv3o/bj9DP6e/cH9jv3A/Y/9wv3A/SL+0P0y/i7+b/5X/s3+3f7f/gH/O/85/1X/Z/9v/3f/hP97/4r/iP+T/2L/aP9g/1r/Vf9s/1f/pv9r/7b/k//2/9z/bQAwAFoAWAC5AKsAAQEtAVUBIQFVAS4BZwFBAT4B7QDgALkAUgBvADwANQAgAMj/BgAQAC4ACwAYACcASQBFAE8AbgBfAGMAhwBAAGAACQA+ACkAKwA8ADgAPwAmADUARgBEAA0AKQB3ADIAUABhADQANwANABAA/v/Q/w0A7v8WAAEAEQAEAHYADgAsAEIAPQB3AHIAlwCPALgAvAAHAQIBCgEqAUsBXwEtAf4A+QAEAekApgCpAJoAhwB3AG0AegByAEYAggB8AH4AYQCUAJEAgACZAGQAmgCUAD4AhwBhAFIA6v8lADMA2P/I/xIA5f/0/8n/8//c/yUAEQBnAFsAYQCCAIcABgHEAAUBvgDTAMsAqQC9AH4AtgAqAHAA+v8qAMr/EAAEAOH/7v/x/xUA4v/w/xQARQA0AFcAZABoAJAAQADMAI8ACgA6ADoA9v+y/xEAOACw/6D/yP8jAN7/4/+H//3/0/+Z/8v/l//b/2L/KwCa/9b/y//Y/+P/W//T/4P/0/9h/1L/rv9W/4T/Vv/r/xYADwBWACYApgAfABQA3v/g/+7/Sv/n/xIApgDr/wcAOQA3ACgAUv9XAOT/ff/q/n//5v9N/5b/IgB0APT/3P94AGsAd//r/z4A7f8dAH//jQEXAHEAHgAFAEYAd/8sAFEALACAAMX/9gCc/50Ak/9hACAApv8uALP/y/9r/17/kf8S//3+zf63/1H/DP9V/63+XwD//o8AhP5x/07+Vv51/vj9G//P/Rz/lP6j/+D+2/5VABUA7AAzAhoN7AqsBkEHagPGAgv1O/mS+Mb2nPU1+JcAzQF8BJwHhAWOBcQBRwTWAk4ADfw/+338jPqk/Nr/lQU0BbsERgdGBgMEl//LAIH//vwS/cP/EQTgAXUD5wPoA1kAm/7CAAgA+/+N/K3/0f/+/mr/4wDJAkMBrwHfAkACKQG9AAMBKABK/oL/cv9L/7r/RP7P//39rQYgBt8C6QnCB40MLQSWCVEJxQPHAW//cQTm/RP+z//IAZ//qP2zAVEA7f5O/Rv+R/0s+yr8M/5H/+z+uwC2AdUB4gBtAr0CAAC7/4P/ov/7/nP/tgDcAKj/nP9TADAApv5d/t7+ifw4/DH90v7XAA/+VQG5/hEBdgAWAVMEnAABAo4Bdf8BAAD9xf9W/K/7WPzJ/rP/5v2V/24AB/9V/ND8Av5a/SH8lvzy/IP9dv1Z/sL/q/6L/8v+sP6c/pz9Sv5L++77+/u7/O38+P1FAKL+pf7f/Yj9Xfw0+vj7aPvA+gD7XvxQ/cT7B/1g/aX8bPxt/Kz95P3L/ZD9Ef28/b/8s/5e/WT+uP0l/m39gvyF/IT9Ff1M/Zn99v3n/rv9dv1l/Lr9bP3V/Tj9yf9l/3T/IP3y/ej+wP3N/Xn+4ACG//b/TP/TAK7+b//h/eX9iP0q/hv+t/xn/vf+DP58/Xn+bQBxADT/4f+C/2f/pv43/3/+0f8AASoBQwDCAV0C/P9Y/8P+Nv+D/2//3v97/7z/pf8F/4H/tP5MAPj/i//k/70ArAHnAQsCIwBUAR0A8P9m/z4BHwL8/nAAhACdAOr/kwCMADgBFgG1/yP/R//0AEv/HP4L/7IAnAMTAbkAJQHoAIIA3f2KAOMAfgJHAbT/TwFNAu4Bav95AMUBygJgAZEAOQGJAqgCtf73/70BfwJrALX/QQJ+AuUA6v+kABwBrv8AAXUBugEFAnoCmAF7AoAD6QF8AbQCAgT8AoMDpgJHAgQDYAGhAIsBxAKQAuoBNQLJAVgDqAJ9AAsCnQNzAkcCGgVfBCcDTAOKAxwCBAMsBHMCUQKtAr0C1AMWBHUDnQL6AmUCKgP0A4YD2wFqA0UDCgIXAr4BPQJuAugCvwDiAEED1wN5AV0AVwJcAnEB4AFNAysEmgJgAssBPAGKAHL+k/7S/lD/aAAj/wv/DQHHAbQAeP97/+D+XP6K/zf/vv1f/n3+P/zE+27+sv98/U/+hABe/yT/E/6S/tb9EP/S/5//KQCr/9v/cf4B/Yj8lPzU+yz8xP1j/jn9Zf3Y/ID8zPxI/cT7AvuU/eX8V/wL+6H8mvsb/Hr8EPzD+6P8pv5v/of90Pwa/Df9uPwb/E38F/xh/Lf8Rv1p/Ff8s/yH/P37xfxG/ND8wfwZ/Uj9qP6m/2n/hQCDAboBDwJCAxADxgJ1AzgElgTHBY0GpAaLB4oIAQgDCJQH4Ac5B4UGPAYZBpYG1wYaB6wHPQe0B/oGKgbwBVQGcQZ5BSoFvgXQBdsF+gV+BrwGRQaZBY0E1AO7A3wDPQNpA/QC3QEnAaMBKgFMAXYAxv8V/hL+Nv6d/RP97fyM/IX8Bvyx+/n74vsj/B384fzw/AD9Cf28/IL8OPxb+6r63Pk8+jb6CfqF+Xn5GfrZ+XX5nvhR+D/4EPg1+FD4ovhy+G34pvfL9kX2TfaQ9n72oPa89qb2bfbS9Zf0GPS/87b0vPYn+YX7SP6hAAUCPwO6BIIF9wWyBmgG/wURBicG+AXzBQ0GfAWhBGEEmgNeAx8DdgLzAQkBWQDF/4P/pP+t/5EALQGXAR4CbQL9AkcD7wMoBDwEWgRBBP4DTAR7BOwEUQXnBTIGfAYrBwYIawg6CZQJsQm3CdsJEArvCQMKtwklCcII9gd3Bx0H2QZyBvQFzQWABWEFdQVUBV8FOAUZBdQEdgRCBJ8DggNCA8wCYgLlAWUB4ABoAGYAKwAzACMAev/g/g7+pf3k/Kn8TfwD/MH7WPvM+rH6FvpY+gD6JPrr+av5qPlS+QH5uPj+9+L3GPf+9ub2BPfn9sT2+vbG9qD2rfae9pH2vPb69vz2CfcW9zL3ZPee9+/3Y/j++Lr5Wvo5+/L7oPw4/cj9WP7M/mL/wf8fAIkArwAFAScBcAGdAcQBFQI2An4CqQKmAtMC3QLyAgADBwMjAzUDXQNwA2oDhgN+A5ADsQPRA+YD2wPgA8sDuwOgA3cDXwNRA0ADMwMMA/kC6QLpAvACAwMmA0wDiQPtAzsEpAQKBWIFuAUMBlcGmQbIBggHPgdsB5YHrQe/B78HtAe8B9EH1QfWB7oHlgdwB0QHKAfwBscGcwYsBucFlwVLBQcFvgRuBBIEzQNwAy4D/gLCAo0CMgLbAYgBRAEJAa8AbgAIALL/Y/8S/8b+Vv7n/YL9Iv3H/Fz8A/yg+zL7zPpj+hL6vPlw+RL5w/h6+CL44PeQ90b3/Pa39on2WPY79hb26/Xd9b31wPW99dL19PUh9nH2wPY096v3OPjb+Gv5DPrF+pD7Wvwm/fr9of5R//T/oQBGAdoBcQLtAmsD0wM0BIoE1QQIBTcFPwVDBSgFJQUXBfMEvwSHBEQEGQTUA5cDUgMCA8ACbgI1AvgBugGYAWcBTwEuAQ8BDAH0APsA8wAFASgBSgGGAbkBAAJDApcC9wIwA3gDrgPtAyMEVgSGBKoExQTpBAsFLQVOBVUFbQV1BWQFWAU9BScF/gTYBKYEdwRKBBsE2QOtA2MDHwPkAq8CaAIXAsoBfgEpAeAAkgBOAAkAvv93/y3/2v53/hr+xf1S/eT8ffwW/KH7MvvD+lH68fmG+RH5l/gg+Kb3O/fX9lb25/V09QT1tfRl9Cn08PO585Lza/Nv83rzmvPK8xH0Z/TV9GP1//Ws9mn3Jvjm+K/5fPpd+y/8Ef3s/dL+uP+NAGIBKALgApMDLgS8BEAFrQULBk8GgwaqBrsGxgbJBqcGjwZhBicG6gWmBWIFIQXQBIYEMwTsA5wDVwMfA/cCxAKNAmQCOAIOAukB4QHMAcQBzAHGAdQBzQHcAQQCPQJ3Aq4C9gI8A3sDuQPrAyQEYgSNBMAE8wQmBVEFiQW4BdMF5QXzBfQF8gXkBdAFuAWZBXcFTwUqBQAF2wS9BJ4EawQxBO4DsgN0AzMD/AK5AnUCPwIDAsgBewEoAdYAcQAAAI3/D/+B/uX9SP2k/BL8dfvb+k36u/ks+an4Mvi49yj3k/b/9W717/SJ9DL03vOZ81fzK/MQ8wnzAfMg8zbzV/N+883zI/Sb9Bf1vvVw9jf3+/fN+Kv5h/pX+038J/0C/tL+sP+JAFgBIALXAoMDEASbBAwFdAXBBfkFGAY0BjAGLQYmBg8G+AXLBaMFcwUyBe8EqQRYBAMEtANyAygD3gKaAloCHQL3AcIBmgFzAVUBMgEaAQAB6ADKAMoA2gD1AB4BSgGJAb0B7wEpAmACkgK3AtYC8QISAy8DYgOWA7sD4gMABCUENwRRBFsEawRvBHAEewR+BHkEdQSDBJMEnQSsBLcEsgSiBIkEfQRtBFYEJwTxA7QDYAMLA70CYwL5AXcB8wBXAL7/F/9n/rf9BP1N/Jn77fo9+pj5Cfl1+Mf3KfeR9gf2mPU79cr0ffQm9N3zsvOA82rzVvNm83LzhPOS86rz0PP/8zn0kvT09If1Dvaa9jb34feA+FL59fms+lb7CPzk/Lr9nv6B/1cA9ACrAWwCZgMfBMsEEwVaBY4F/QWdBtoG5AazBoAGgwa2BvgG/gbBBlYG9wXPBcgFrQWUBUkF5gSJBEkEPQQrBBME3QOMA0cDIgP6AuwCwwKRAmECSgJaAncCmgK+AtsC9AIEAyQDQwNjA4MDoAPDA88D/ANFBHQEqgTXBPEEEQUcBT4FQQVJBVYFRQU/BT4FOgU9BS8FOAUnBSAFGwUMBfoE2AS3BIgEWAQVBNgDrQNSA/kCtAJhAv4BjAEOAYkA5f9R/7P+A/5I/X783fsw+3z63PlF+bz4Lvi090b30vZk9u31efUn9eH0nPSP9If0gvRQ9Fr0PfRJ9Gf0nfTB9N709fQR9UH1dPXc9Rv2v/b69oz39Pem+DX52vmO+jz75fuP/DX91P2M/i//CACvAGgB6wGbAiMDmQMLBGsEvgTuBC8FXwWBBZUFpQW7BdAF4AXXBcoFpAWVBVkFPwUABeEEtASEBFgEIwT8A+UDxAOgA4EDXQM7AwQD4AK8Ar4C4QIcA1YDfwOhA7kDywMVBCcEQAREBEIEPgRFBHMElASpBNgExwS9BMEEugTUBOEE4ATQBMoExQSuBLMEzwTcBAcFDwUOBSAFEAUPBRQFDgXyBKYEgwRCBBIE1gOlA0UD6gJ+AhcCsgFFAZUA5P9p/3P+9v0w/aX82ftk+6H6S/r5+Xz5S/m4+HP42feo92n3avcL9yH3+/bD9o326/YE91T2x/Zc9mn2I/aO9nL2yPbD9tr2Dfdw97b32/c4+If47vgP+QD6S/rD+lv7ZPzw/Jv9l/5M/7j/YQAwAZwBMAKoAkwDrwMXBF0EyQQmBVYFngW/BekFzAXqBfcF2QW6BaAFegVGBSwFFgX9BMMEtQSTBHEEXAQ2BCYE5APOA6ADkgNfAzwDEQMTAw0DRAOfA8UD4wMNBEUESgR8BJsEuQTTBNoE4gQDBf0E9wQEBUQFIAXhBPAE0wStBKoEjgSLBG0EfQSABKoEtASdBKUEuQSYBJcEmgSFBD0EBgT8A+MDuQN7A0ED+QKjAkQC5QGOAQQBXQCx/yH/hP71/WD9vPw5/Of7V/vM+jr6y/la+fX4kvhP+B/4jfcn9/z24Pad9mL2P/YV9vL1wPW99er16/XG9bz1w/Xf9fH1H/Yx9lL2n/bZ9i73XPeY96j39Pcf+GT40Pg8+Zr5I/qT+iX7vvt0/EL9zf1j/s7+Tv/e/2MA/gBsAewBcgL3AnMD3AMTBHUEpQS8BM4E2ASlBG8EhAR6BG0EYwQzBAMECAT4A+oD5gPHA6sDmgOSA2wDZQNvA2QDkAOtA/UDNQRVBJQExQT1BAwFEgUYBQwFCgUQBTMFKwUWBREFMQVDBTgFOwU4BRUF+wT1BOoE5ATUBPIE+ATqBOME6ATeBLwErgSUBGsELQQ0BCIEEwThA7kDqQOaAz0D+gLRAncC+wGZARgBkAAyAKj/Cf/F/j7+k/1b/QX9fPwn/NH7RPvb+of6FPrN+af5R/nb+KL4O/gK+Pn37/fD9633kfds94H3f/d894P3ffdv93b3jvex99H3KvhU+JL42PgM+S75fPm0+QT6P/pI+p76r/rh+mz7Qvyn/Cf9pP0p/sX+hf/n/0YAlgDcAEMB1AESAnkC2AJLA5MDJARQBGcEpwT4BOkEGQX+BAAF1AQpBTYFUAU/BTgFRgWLBZAFoAWmBagFrAXGBe0FAAbfBd0FBQY4Bj4GZQZoBk4GXwZcBk8GNAYyBv0F9wXuBecFzgXUBboFnwWQBZcFewVfBSsFEgXvBNkEuAS7BKgEcwRoBDkECgTlA7sDgwNRAwkDwAJqAjAC2wGdAVcB9wCZAEUA1/9m/wP/ov5I/vT9j/0m/df8kvw7/Nb7dfsn+/P60fqX+lL61Pli+Tb5FPnq+MH4hPgy+DX4Gfjl96H3bfci9xb3APfa9sv2qvaR9o72vPbA9gn3PPda94j35ffk9yj4eviJ+Oj4Tvlm+Zv5IvpZ+s76NPt8+5X7Nvzh/Hb9Wf7K/kf/4P9jAAgBawEBAl4C6AKSA+oDVwSpBDAFygUQBmkGlwarBt8GQAeZB+UH5wcNCCQIYAiqCLsIHwkiCVMJbwmXCYYJgAmuCakJuwmiCZQJewlbCUEJFgn0CJEIOQgQCMIHXgfoBsYGcwYcBtMFWgUNBZgEawQpBAAEkQMPA6ECQQLLAVcB/QCHAB4Aw/9g/xj/6P6g/iX+w/1z/Qf91vx5/DT8/fvo+6/7e/t0+yT7+frd+tX6p/qI+pr6j/pV+kX6SfqK+rP6MPsB+9X6yfpd+l/6hPod+uT5xPmS+Wv5Tfkw+ZD42vjM+GP4sfiT+Kv4+fhm+QP5Pvlm+U351/lU+l36OvoB+3v6TPtF+977R/sh/Bf8/PtT/CH8PPxa/Or80vw7/Yv9s/3r/ZD+4P5r/73/AwCMAD0BAwJnAhADtwMABLwEZwX9BagG9QZ9B8UHWAjXCBkJagnNCQgKagqLCrYKqQruCuoK2wqzCqcKZwroCeAJbwkwCawIVQgQCN0HLQeqBn0GSQarBR0F2AR9BPMDkwMiA7YCEQKZAfsAfgAhAHr/Jf/u/kH+uP1T/cv8X/wW/LD7T/s8++T63vqg+lH6FPpJ+lb6Pvow+hT67fnc+cX5pPnJ+fn5K/pI+rn6vPrP+iT7JvsE+wD79foB+y37HfsK+zH77vrl+j/7Efvo+h/7MvtU+677jPt2+3n7kvtD+xv7I/u9+oH67fr0+hv7pPuR+4X7Kft3++T6KPt5+/b6Rfts+6n7Kfxm/Kz8jvz6/Kz9Cf5y/rv+Uf5e/+D+P/8r/2j/qv/9//EBEwH8AVIC0wJDA/kDTQSTBAQFSwWNBVkG3QYNB2YHVAd3ByMIvAieCRYKZwpoCjgKoQqPCqcKcgoRCuIJkgmkCbEJpwmnCU4J8AhUCOEHwAfbB20HwwZBBtwFZwU8BTMF/wRUBJcDHgPIAosCFQKGAWsBvwBVAOv/rv93/wz/fP74/Xv9Jf0i/RP97vx0/EH8q/t9+2j7efuT+3D7QPv1+tz6ovql+uX62vq++s369/rm+kP7cPtp+zT70/p8+rr64/rl+vL6xPpv+nf6xPoX+yn7JvsK+8z6NPtt+9/7J/zH+337I/uM+m36a/oD+9P6NPvB+gD6z/ko+tb6Q/tf+5X6Y/pM+q/7N/x+/FT7ufqL+xz8Ov2n/Rv9L/3m/H79//2D/gf/+P4b/5P+K/6W/gH/Yf/o/6b/HgDy/5AA+ACdAfwB+gFHAtkCQQPIAx4EFwRQBGME5gQdBWUFNQV6BQ8GewbcBvMG6QarBgEHjAdaCJ8IJAjAB18HSgdfB+YH0weUB6YGDQbgBRMGRAYGBnMFBwVwBKAElgRJBCQEhAMXA7ICdQKCAkcCyAEyAbMAegAmAAgA8/9k/8D+fv5k/qz+S/7S/SH94Pyd/Lr87/z6/IX8GPzV++H7RfyD/Hb8RvwF/L/7x/sC/DT8XPxf/Dn89fvo+0T8jPzK/Ov8xfza/Ob8h/x//IT8zvzg/MH8efwo/G78MP0a/QP9Zvxl/Aj9kf24/Rz9W/xe/Fr8tfx+/DT8kfzf/E79DP3E/DP8Qvw7/XP+5f5t/uz8RPw+/Df9QP4B/p/9F/yZ+wf8uPw9/uf+Df9i/oT99/1//sz/KwGpAKz/Kv72/W3/twDMAboCeASfBYsFuAWKBrcIvAp9C/cJzAfaBqIGAAjxB+QGvwXyBA4FhwU3BrsGoQZOBxMHbwalBpsGRgdKB1gGrwUfBY0FlQXwBTMGmAVmBVoFBgUiBb4EgwRmBBwEsQP4AooCgAJPAgcChQESAesAcwDu/3v/Gf/Z/tT+3P7L/mL+//0A/jj+iv6R/ov+pf50/lX+8/0j/oz+mP6f/kr+Wf6R/tX+0/66/vf+AP/b/sn+pP6N/lH+m/1t/X39mf10/YD9hf1Z/V79VP0//U79Uf1M/UP9Bf2p/Gr8cfyj/Kv8yPyH/IH8jfxV/Cv8D/xb/H78n/xa/DP86vsP/Pr7XvzS/Cf9nPzg+0/7W/tQ/AL9GP2K/NX74vt7/Cf9lP10/fr9Kf6x/XX9T/0g/s3+o/5o/uL9Tf6t/rX+zP4N/53/DABq/+n+j/4s/6X/qP9b/+r+u/4O/6j/sgC6AMQABwFYAc0BgwGYAQICSgIiAvABkAF2AewATAE0AgMDEgM6AlUBYgEOAvUCFATBA1YDnwI9AncC5AKxA18EFQSZA7kCuAI9A5YDXwRZBBwECATAA90D3AP0AwsEBQRiBCAEpwNjA5oCrgLFAjEDmQNeA9UCJgIxAuQCLAOBAzwDhgIsAp0BlwGpAaoBfgEYAeIAoACaAPYA8ADRAMMAsACwAM8AsABlAOj/vv/D/7z/iv8n/9v+3P5u/iX+Iv54/pz+W/70/Yb9cf0N/kr+Kv79/Y/9uP32/VD+Cf7p/eP9F/5A/l7+xP1o/WH9rP3G/ab9+P2Z/Wv9aP3H/SP+Rf5Q/vf90P3a/YT9pP2b/Q39v/29/Yz9zPz6/KH9oP3E/Wr9aP3d/Qn+ZP1o/VL9sf26/an9qf1x/Wf9A/3g/DP9t/27/cf9O/3a/BH9M/0L/l7+Xv7o/Xn9+/15/s3+9f6J/lH/8f/D/2z/0v7k/8MAlgGKAYoAZQBFAK8AdwG0ASMC6AF2ARIBqwBiAWcC+wJFA04CDwLPAawCuQMVBHcE6QNpA+8C4QLFA5wE0gQ6BNwCzwIEA+QDpwRQBO4DSQMoA2EDdwOwA2cDQgOXAwAD3QI7AjMC5wJnA3oDkQK2ATEBIAG9ATECnQEnAQkA1//l/1MAWAAiANr/Q/8v/2//lP9n/5b/mv/8/7n/Mv+F/p/+Uv+G/4X/Cf9C/vP9L/5//u3+6P4D/yP+4v3y/TT+cP7H/XL9Q/2G/Yf9Yv3O/NT8Sv2I/rv+KP6g/Yf9Gv6G/o/+Cf41/S/9pPzf/BD9uvyX/B38W/zx/Hz9YP2B/Aj8ofxs/ST+X/2G/Bj8YPxI/aD9vv1r/Zr9Bv7l/Wr++P4Y/wv/h/5e/jD+gf7H/of+Df6t/fn95P4f//H+AP9B/4T/Wv+I/6n/0v8kAI4AygCPAH4AlwA/AagBMwIUAgwCgAGFAQECQQI1ArECrgIRAuEBXwIrA3QDzgPWAh8D+ALIAwQEDwTUA30DyQNwBBwEDATAA80D9QPDA00EvQMDBGsDlwLnAhEDRQOnAycDfAPrAi8DRgMlAxcElQMBA5wCIgI1AgoCdQKZAgsC+AEbAfMAcQF8AX4BLQEHAasAUACaAEUAWgAUAOz/0//w/7T/vf9b/x7/XP+i/7//Jv8I/xX/if6m/pP+bv6l/g7+DP6V/Sf+J/7h/fn9af1n/b79r/2j/TD96vz3/CX9R/0V/Yr81/ti/Lj8tvz9+7L7AfwC/AL8yftH+1D72PuE/A79uvzY+977M/wq/Zv9p/3b/M77DfwK/Qn+8v3+/KL8Bf2r/QD+k/1I/VT9Uv0g/qD9+P3O/Zj9hf3g/c7+I/89/3n+vv5Z/4X/sP8MAMv/7/9i/yoAl/9RAPP/UgA4AYIA1wD4ABcBUwEnAQsCqQI3AugBvQB/ApkCVQMvAzgCkgLVAmEEbQTbA7sDjgM0BAwFdARFBQAEPgRcAzIETAVfBccF7QTMBAoFHwXLBV8FZQXGBZUEmgQiBI8EvwTSBO8EkQSLBEsE/wOiBJcEbQTUBM0DZwPRAlsCLwKUArcCfQL2AV0BEQFvAQACiQGKAc8AuwCjAL8AUwDq/47/Zv+s/y0ANf/g/tz+3/6R/9n+Xv5U/nH+Nv7U/ej9+P3m/S3+fP3P/bX9Hv0c/Sb9Jv0M/c788fzW/FH9Tv3A/Dn9sfx8/K/8L/2E/f78mvvs+x/8lPxA/H38Pvz/+y38Gfxx/PP9E/4o/XD8Gf3V/Tj+dP2t/L/8uv0v/SH9WP1n/X79fP3I/bf96f26/fP9wP6+/jT+R/64/S/+8v77/tP+q/1v/X39/f0N/+n+iv4h/j3+VP8VANr/CACR/+cA5QBJAmYB7AGQAeMBIgLVArkCXAP4AlADVgMjBOgExwTkBSIFSQV2BdMFsAX/BTEFaga+BZ8GaAUsBrIGoAbDBnEGPwYxB5IGbAdWBqYGXwbdBeoGZAWnBQ0FHAUQBX4ENQStA4wDdAO8AlYDugJYAqgBFwFbAYUBUgHAAOz/8v/w/+L/tf8P/wj/Z/7Y/vr+If9J/lb93/3//TL+2P2Z/Bv8nPu2++X76PvJ+1D6//nq+df6DPwy+xj62vk3+mb7EvyQ+8366PoZ+3376vsm/PP7OfzO+0f70/te++H6+PoH+8r7Pvvc+lb6Xfrh+tj7rPtb+hL6X/tc+9j6k/r9+hj8ofzn+9j7Cfxa/Ir8q/yB/eX8avy8+yv8nPyZ/PT75fti+777bPsj/IX8Ev3b/df9T/4v/27/qgByAcMBBwKyAlkEcAUOBzQGGAeCB8gIDAonCrkKiQp6CjYLAAsIDfgLCAz9CtUK4wsmC78L9QrhCnsLqwqzCmgKDQs0C/oKCAs7CmcK1QnOCYkJwAlBCYEIygeRB4YGswbtBTgFywSuA9sCegIsAnIB6wA7AJ7/b//a/iv+Tf1d/Sf9NP1k/Ob7dfwz/Hn8Mvwn/CT82vrb+vr6O/vd+pP5dvk8+H34Evjy98/4wfdy9+L2b/bn9mP3R/fm9v32ofYV9133RvY09vz2wPcD96r2VPUj9on3Xvc+9uz1t/V390f3BPdy9nP2Ivio9134IPeo9+f4uffc+Ob4efnn+Hv3ffey9yr6+fnk9/n3GfgJ/dv8LP1u+xb8BwDpACYETwKUAzsE2ATcB38HBwpbCfAJ0wmRCmsN6QyJDa8MIA7IDlUQ9A9ADs8Oow59EN0Q9A9zDykOhQ5pC/8R8hBFD/cNNgoEDnoO/w8zDTMM3QvaC64MSgw3C0EKCgiwB/AH/QdlB2oFQgPUAU4CvgLgASIAXf4W/jT+Tf7R/Zn8PPxA+2P7w/qr+vv5HPkf+S/4Ufje91/4hPiN94v3OfZ89jv2Uvba9gD2qfX29LT0bPT59CD1svME9MHzb/P08vPxtfJg8m3zoPIw88zyJfIG88DxavMg8dnzbvMD9j/0I/QR9LHzhvTv8wr2i/d++JX9ZPlD+7X4zPz//j4BFAS4AggEHgTEA84FQQTwBicGCAfUBvAGWAY4BZgEnATIBEoGCQZEBc0D7gKRAwsEcwRRBJAEYgR7BUcGDwgbCWkKuwwhDdUPoxDMErETQRUhFmAV9RbtFWkWABYEFeMTMxLtERkQFhA5D/AOfQ0yDSAMDgvDCqQKSQrqCQcKGgl2COYHwAaXBqsFdgX1BHcEowOaAt0B0gBeAP//df9H/yr+dv0i/En7rPra+fr4d/jI94z2ZPWc9IHzBvT88gjyrPEv8eDxwvDT8DvuyO/O783vCvDs7iTvc+/e77/uyu4V7Z/uXe6W70jvVu797cXs6u8P7pXv8+5t7ZLwCfGK9SD0/vYX92n2Afwa/DAAJACqAYcDQgS8BsMGFAjLB28HlQiOCLEIFwhxBukFTwXMBAAF3gPDAmkBWwEZASwBwADa/xUALwDKAEAB4gGoAcUB7wIHA1AEYgS3BngIsgj1Ck4MDgyiDeYO+Q9fEAMSABKgEYkSCxE8EegQuxCgD8UOUg8LDSkNYgz4CyULCQtUC6MJwAqrCUUJ6AlACQIJQQj3CKkH+wfoB7IGbAZABTUFEwTHAxoDTgE2ATAAE/95/T79qvt0+vH5cvg897z2R/YG9Tb1r/Mg87ryGfJG86Dx2PLp8ODw6fDU79HwuO/d79rub+7u7ybtSu+L7ZntOu4a7UTu0O2I7mftkuw47vrt3vC+8YHx8vR08x74+vik+hj8Y/zpAJQB5gTMBQMG1gfVBmAJ1wm/CXAKkgowCmoK4wnmCOwH+AZPBi8FNAVOBGQDrAJSAZMBXQAzAeEAUABLAT4BMwIGAgcDtAKaAoYEbQT7BUMGeAhoCn0LYwyvCy0Niw18DwMR3BDoEEkQDhGJEE4Qsg4UDRYN0Qw4DXgM1AsWCn8JPAlSCXoJTgiBCDQIugh4CAoIfAezBtwGmAZABwIHewa+BZsEoASqA9MCkgG2AN7/FP/3/n79IPxg+kT5N/ge+K73W/aV9B/0cfMn8rfx9PDW7/DvlO8o7/Tt6e027DXtdO2X7Pbt4+wC7U7sgOzm7Lvszevf7Svr5O0i7KbtGOzl7KTun+7L8iXyrPRV9Qn4Cfm8+s/8s/woAEAAowTpBAUGnQbEBWsICgekCYoICQlfCSQIPgo7B2AHBga9BEYFGwTEBPcC5QLbAXkB8ACDAIgAyf86ATIBlQHaARgCTwLiAaEDKAOMBCgFDgddC8cJcwsTDIoLJQ3aDBAQig6VEOkPUA+lEUwO2w5aDPAMPQxjC94MDQvXCjoJ4gmmCOUH6QdxBnkHrgfIB20HMAfZBSQFJwbQBT0G/gXwBcgFfwVhBTkEkQNeAlIB0gAcAHL/Mf22/Mf7nvl/+dn3J/bV9D70s/Oj8gTzyvE+8M/vMe9H72Lt3O5S7WjtgfAE7d7v+ewI7nvuyu1i8MftKe9V78TuVPAJ7zvvhPB17+Dy+PKa8/f1kfSv+Lv4J/qA/Bn7Kf+5/ykBpQSaAjcGgAOEBp4HmQYOCVcHgQimCPUHDQkwB6wGYQZCBUUG8wRcBBsEywEpA0wBPwF/Aaf/XwFZAP0AFQLsALoCjgHRAqsDSgNNBTQF6QiqCQQJxgyFCXEM+wuqDRYPCQ3ED2ENOhCrDlUO0Q1jC9IMbQpTDPIK1QmuCE8I2QjSBnwHwwSoBL8EOgT+BA8E1QMpAngDugPvA1EEhQOSA/oCxAMqA7ICLwG8/4H/KP5N/vH8qvsz+rj38PeJ+E33kvXl8nb1qfPV8ur0ffFB8b3tGPPp8HLxMu9o77Hue++P8Tfxye/h8PDv2u4G9LLwjfFJ7QXzBO9d7wfxw+9y8crvbfPi8iT1D/bx9Tn5F/kV/P36rv6k/6kA2gGIAg4F1QOkBXoGkwbUBz8GdQjXBzcI6gfaBs0HRwUsBooFrASFBPYC7wKCAmQCewEdAWgB2ADYAC8BnQEGAdgBDgIjAzgDzANmBXQG7QcdCGgKSwoGC7ELcgyyDdAM5w36DZ8OHw9dDR0OkwxHDCoLVguAC/4IbgmNCM8HzAbvBWIF8QPaA8cEegSmBNkCBAOLA4ADvwG4AqEEDwGhAeYCJANEAVECU/6NAsf+bQDg/NL/1fsp/uX5C/4I+Mj61PZL+En4qPi39Sj1yvZm95TyPPZJ9sjxkPQD9Hz0XfRP9FLzI/Jl9Sjy6/Iz9cbw4fRM8fHy2vMI8QjzRvEF9V/zpPS19yb1Nvog94b7+Pqr+wz+Kv3NAiMB0gKbBP4D7QVbBQMHIwcsBmMHdwejCAUIWQceB5EGNgUzBs8EyQS/A6MCNwQpAhgDrQEPAbgBXAC2AWgBPwIsAgwCxAOeA8MEFAZYBpoGJAgpCIQJ/wlgCTYLpgofC3wL7wvZCmEK5AqrCaUK3gmGCCcI3AdCBzcH8ga2BigFBgU1BTwF3QMyBGcC4QNSAxoDKQC2BKsBmgAFAlgD0P7zAlz8JAgF+eUGmfw3/40Bvfzi/cP9M/64+HT+jfl0/3X3V/y7+ub20Pdi/ury5fhD+VHyAPpJ9xb29fSZ9iT06/U79Rr2DPIp9tbyafTZ9MT2wvDN8wX0efPu8qrzTvX98F73KfQM96f1Z/kM9kz5Hvvy+pz83PuT/mL/cv+fAbgCogEmApwDKATWA30FtQTmBNsFoQRBBnIEwgT4AwMEYgOLBIQCJAPDAoUCrwIxAvYCBwJ2AQIDdQJcA9gCZwTSA3IDPQboBKcF6gZGBrAGiggZCa0FNQunBqYJzQgPCrkHhwjwCEMImwmgBoAHYgZmB7IIYgQwBkwHMAbBBOb+sg30AcL//wKgDQr4hAF9CaEBN/l/CroAu/2mBtz5pAsD858P8vX6BZ/9xvtfCjTxMwYl/Y8A7PGzCCL35wA38WsJ//SR+CEBb/OfAJ73/fXt+vT+qfJZ+Ez/EvGZ9sP/SvLM+Mj2NPnc8yf6e/Wh+9nwLfvA9rj2Rfnd9BT7pPOU/PL14fwX+XX4Rv2g+r374f03/Ff9bv6m/o0ATwB7ANz/fQN0AHABdgVBAaIBqQT/AlkDWwTSA0MEwQJAA+wD+wQ7AX8DQAR6AgED2wHrBj8DwwCYBPsDngJvBk3/JAnLAhAGkP7ADbgC8QC7B2QHRwEXB6EDnAZWCAQAdQc2BxUBBwnj/RYJewQwBOT9SQ01ACr+3QgaAp8DKPlCF+ntOgg/C/32jwDZAycGivhk+l8TCfcr9dwI6Qrh73X+5BF8760B7/98CObrBgrKBrbv6gO+AKP9I/TzBtv7CPyy9U8I/PaE+iv9mv2B/VrtcwyX82T4pPyY+2/8p/AVBCT6dPOX/an6sfzr7nkD3fqX8EICePe5+0zzHQP79pP0WwJI9wf4KfsO//H1NP+D+vj//Pcs/l//Pfs6/vn/yv6A/ZYBaACC/vcBQAKV//MBKwIyA9QBhAIqAuEDrgQTAsUB/QbdAhwDlwIpBt8FHANOBWYBmQfQB1b6/wn2DH35qAMZE4T5+gQkDoQAa/+SCvcJRfzmA/UKRgfM94MQQgbz+GoKGQVOBVT/XAToCdgBg/fHE2L8NwIx/c8LvgRZ7gobxfDfDaPy9Q5BApPwDxRK9l0CMAP/+jsEp//kAf34mAcb/4n32wRPAOD84/juCi32XwC1AUv7EvwNBj72TQIn+wYDYfvL+DsJSvE5Bz77iPUHBUb+C/FdCSb4jf77/A76RQN08+UCFPzr+jL9bPp+AOn5q/yPALL5av2z/Y37Lv4l/Zv+Hf7n9rwCA/0N+5wAFP70AET1OAZD/y75SQDyAhf9a/oXBnH+D/wwBp770/6SBM//M/01AtAF3PyRAT8Bcgin9q0JjwI++Q0GJQayAZT5fQ5/AiX5HAdCCh76QQJwCG8EZvdNCXMIFfuMB3QCKgmL97IJ5QEZA9/7Hgk1/N4FnfsvCE4Aff7nBu0EIO4JE//7vvkTBNAD3AaO6XEXifUeB8Xv9xRl8bwEEvv+AX4EPvXnAIMD5wEv88AFXQQT9Mv7kAjD/EP2/gQpAYj4PP10ARX9QABt+LcB8ALj80oECv1ZATv1rQmp9uz+pf3IAeb7mPs1Ae378gAG9ikF7gPb8o8BKQNmAOXwygj2AqLzmAMoART+V/y3Av35iwcb+P37+gZ7/v35sP3ABr7/k/TcCb7+efozBmX6Pf9ZB0b5GQFqAMMFevkCAzoCaQBk+08EDP72AnUGuu6iGYfywf8iCYv+jvufCyn7z/8aBwn+OAKC+pkVReuHDHMFEPkUBC4JlPhtBQgExP8B/58CdQqM8rAOpP4B/IwKU/g8DK/zOhLD8vgGVgM9Acn5SwqZAT/2QA3o9vYPr/BvCM8DVP0zAd/2KxCX+Br4ZQyW/OQB//W5DLf5pgBV/zEIt/UXA1z/UgSl8jkLzfs/+9QEVf1wAZX8JgOB/TgBGfwdA4r/v/2H+OUKjfoc+LEOqe7ADwL1VP8rCEX46v9lBf/yahJy71ID4Adx9BAJzPfOB3z7bQP/9bsLXfieAGr8JQqh+UD4jBFi8rACEPy3DDLtpwrlAUn1dgt893sIEfH+Fh3oIwklBcH1WAOoAcIEevOGDfj2hAVT/DAFVPixCSf5pf44CtXwXhNq7doQDfaiB8P4BASgCFPqwBhC7+MPpu2GFmrvCwoR/X4CwP5p+iAT7OZTFlH4/ANb+44FmAKO9mUHDwI2/DoBQwESB6r9n/UXDvb7eP5X+BINvgPT7D4VmPQhBr33tgxH99H7XAp19zIEMf6uAYoDefud/dcEiP43+rkBsQVo90gFzwQK7wwSgvfs+roG6fzUAPv9Yf5jBVj9FwARAAsAGwD896QKRfY4Cmr5Df8/B/P0Egvw80AFsAUC+wf2PhHU9KwEze5QJQLb/A1bBMT7O/5y9zAYi+pFBVP/Rwo48HUGpwPC/7v99/3LBWT4pQhH8+YKbf8Y/Zb++AFLAvECQvJXC7IHkO/IAY0IqfseAaP7ogss+LAFTvg7CjX8MfnOCR35jwQK/vgFEfZbFfjmOA/k+sUFD/QrCJQGofPQCVMAsvtWBLsDtu/ZFPXxggYk+QoOofaGAEAEXP7T/n4FsPItER38C/P5D2b0WgV0/mkAPAee9RoPlvJIAkYEqPyE+psHp/d4E9fuEwHSEezq9wxg7vQPqPud9BsKPP33CvXuQAiZCp/2ffkOB7z4YgSV++r7RQ/+8VARD+oAFHz9GO6JCUEEtvPRAHgKPvg+AkYFgfxW/r4Cgv3y+XADB/ulBtP9UfhTEIzzOAiK9u0IVvm/AvP2pgL8Bjj1IAeN/hcEhP5e93gJcf9p+Sf8SQad+eYDs/6w/CIKSQDZ8q8JyP1TArnv/hAU8+8KRvn9/O4L5vS+CCrxsRHd9EMCV/itC4/5HwAm+WcR7+7gBiQEcvbcDT/qFBRl80ADNwE0AJL9QALm/6/54ghz/GH7uQJQCMHvZw2L+m/8pgr078oQnvC/Ceb+LvtBBNz9qf0yBDX7NgIvA8L60wZq+CEE/P5S/J4DM/y8Aq78RgLe/zUApP8DAOX+RQBx/RECqv1UAW4BU/yUAZIAuP+Q//r/Nv9xAEn8pwMA/o8AtwJv/UUBnv5UAob8BQTX/ZIBaf96/gMDyv0WAen+rQF1/7//jAGHAIoA6/7F/wQCg/6C/kkB8P98/74A0wCFAVL+3wJS/mr/NQJo/WkBUwD3/qMAsgBsAEgA0QDzAGAAm//JAXf/Ff8NAiP/BQCgANAA4v+HAJ8AxADO/4EAIgHS/6gADwC0AEH/2QHt/i4ATwJL/msBzQDg/94A3f/UAO7/y/+9AB8AIADVAKMAQgC+ADsAMQCEAMX/wAApAGAAcgBNAFoAZgB4AHT/jgF+/yX/6AFk/y8AngBVACMAzP8nAZL/r/8UASD/YwBAAOr/IABKAPn/MgDF/40AyP+E/9IALv8jACUAZ/+8AEP/lQCa/7v/XwB+/zcAnv9wANb/sP9gAOb/kv9eALr/8f8kAJn/QQDv//v/4f8jABAAnP9UAAoAVP/JAEH/cgAfADf/agEJ/28ArwD//kQBUf/s/8AAXP/y/4cA1P+y/3kAMgDC/xcAYwCg/6cAdP90ACIAm/9kAMH/aQDE/+b/rQCw/wEAbgD///T/JABRANX//f+UAGX/iAACABYA5f+zALv/v//8AEP/TAAkAA8ABAAWABkAYgC1/ykAiACX/1wAIwDu/xIAOgCs/3IAxP/2/4kAhP86AD4Asv/e/4cAy//F/7cAav9RADUAs/8bAG4AZP9IAC0Atf8YABMAMgC6/wkAUAC//+v/PADe/9b/RgDS/x4A4v9SAHD/agAHAFz/1ACD/+L/cwCn/x4AEgDM/10Anv8SAIcAXv9RAC0AyP8tABwA1f9KAOL//P8MACoAxP8YAE4Ae/+vAIn/RQB3AEf/2wCm//j/dwCV/14ANgCU/4IAGwCy/4gA1P8ZAC8A4P9KANP/HwA/ALf/PwDz/xgA6//v/ykA2v/8/9n/bgCk/yUABAA/ANX/GgA1AOb/PADZ/zgA5/86AMn/EgBVAJf/CwBSAJj/CAAJANz/LgB+/3MA8v+F/2sAz/8HALr/VADR/+L////6/yMAi/87AAUAuP/a/zQAvf/U/8//AAAYAEH/dgDI/93/0P/4/wMAqP/j/ysAm/8BAOn/qP9MAHD/GwDZ/9L/1//6/9f/uf8zAIT/8P8iAHT/AgD7/8D/vv8VAM//3v/l/+f/7f/C//3/9f+7/wkA1P/B/wMA8f+u/wgAEwCB/yMA6v/A/+P/9v/N/9j/5f/m/+n/0f/y/xQAl//z//f/tP/o/xAAq/8hAMT/+v/h/93/5v/8/8j/8f8QALn/+f8CANv/3v8IAOn/4/8EAN3/CAAOAM//OwDK/zMAFADB/3AA5//9/0YACQDg/1gA3P8gAPj/DgA1ALT/dADP/yQAMQDW/1wA/v/u/0gABQD0/zEA6v9RANT/OgAeAPP/GgAeABwA2v9KAOX/IAAeAAEA+/8eAAsA+v8/ALD/dAC+/0cABwDs/3oA0f8EAHkAzv8lAC4ADABdANL/UwACACYA9P8qAFcA0P8rAEoA8v8YAFEA4/9IABQAIgBJABwARQAqADEAPwA7ADsAMwBBADUAJABOACcALgBbAPX/WgAtACcAOQAgAEMAGgAYAGoA/P8FAHIA3v8xAEoA9/88ABIAJAAZADwA+/8lAEYAzP9GADkAtv+XAMH/EgCJAIL/nwCY/5AAkv+AAMP/VgDu/wMASwC0/3QAwv80AOj/WwCd/1UAKwDE/y4AHQDw//j/IgDh/0IArf90AMX/PADF/0IA8v/T/2MAm/9AAP//3//7/yQAx/8GACEAz/8HAAgA1v/z/wEAvv8mALn/v/9QAIj/8P8VAJ7/8f/n/77/AQDI/8b/DACS/yoAh/8QAIf/DgCg/7r/OgB7//7/rv/y/5D/+f/F/8f/9v/J/9j/AADJ/8f/6v/F/8j/zv/S/+j/tv/p/+f/pv8CAM3/4P/u/+7/x//q//v/xv/i/+X/0v/0/9b/6/8RANL////s/+n/6//v//b/1f8cAPD/1/8BAOb/4P/f/+n/CQDP/+n/IwCv/yIA4f/V/zoAyP8HABsA4f8TAAQACAAXAAQA4v8vAM7/0//+//3/wP8dAMf/5//3/7D/GAC2/wcA7P/c//X/9P+n/9//8v/l/7P/0P8FAJv/wP/U/5b/tv+h/8L/s/+3/8X/n//E/8D/vf/T/7v/4/+5/8v/5P+e/+T/xv+i/+v/rP/V/xsApv8GAOL/7P/2/9P/9P8MAND/GwAoAI//LgAOANb/aAAXAFkAWQBXAF8AlwBAAHoAvACJADQAfwBoAEcAbADl/5UASwAmAKMAGABKADkAJwCDAD4ARAByAFQAcAAbAFsAKQAwAEMA/v8vACYADgAVANH/FAALAOr/PQDi/w8AHQD9/yMA6f/e//v/AwDh//b///8sAMr/DgBJAOf/VgBFABoAXgAfAEUAJwAVAD4AEAAtAAkAEQBLAO3/DwAfACkAGwDX/w8AGADd/9T/ov/Y/5z/ov/S/23/if91/2j/tv8m/4b/Sf84/1j//f54/2f/AP84/zb/RP9T/xn/a/8r/1L/XP9P/6H/N/+O/1T/S/84/y//Rv9S/2b/V/+Q/5r/iv8//5T/NP9h/3z/ef+G/4P/Rv98///+Gv80/+r+Hv8y/zj/M/8c/x//6/7//hz/M/8i/2r/M/9S/yL/G/8w/1z/mf9F/4v/h/+m/67/oP+R/+n/fv+8/yr/cv/k/9P/Uv+i//L/hP9l/6H/h//m/w8A3P/b/xUAPgAiAMf/ZgByAD0AVwAcAGEAggBOAD4AQQBYAF4ACwAnAOH/EQAVAAsAaQBuAKcAXgB6AFoAIwAYADoAKwBVAKkAPADIAHEAhQA4AEcAYQBJAIMAdwB+AIcASQB2AF0AVgBUAEIAzAC1AJoA3AClAKoAcABLAIYAVwBRAI4AggBdAF0ASgBYAEwAfwBmAIIAlwBxAHEAbQCAAGYAZQChAL8AfQC/APMA4wCqAKMAqgB/AHgAgQCwAJMAwACuAOUAmwCjALwA0ADRAKEAyACdALYApACgAKMAWQBzAEQAUwBRABsAOQB/AB4AXQBIACcAVgAzAFgAbABnAFIAQwA/AHUABABCAEgAMwAPABgAbQApAGUAZQBlAH4AewCdAHUAMAAvAPj/OwARABcAAwAMACQABwD6//f/awBWAPb/tv+0/8D/RP8CAM//HgDR/5f/w/+T/2r/a/88/3v/d/9C/3b/+/5L/yT/6f62/tX+I/8i/27/kf+Y/7f/j/94/7P/ff8u/0j/WP/I/8r/e/+t/8r/FQAgABgAXACx/3H/pv/V/7b/2P8JAA8AsgBNA50POhHpDJQFVv1R+nDvWPL39z/+GAPlAz4LKAUd+/72rvPF+GH0Yvj5/yAAGgX7EVMR/BMGBlAGMffQ8CIAG/3ADyYDSg/TCgD+Ivv+7D/4evcd/e8GtQqjEN8C+P2j+jb2evZn9T7/YAZOB40HyAbmAsX9Ifcm+A/8yf77AQYDawdZBcH/efq/9/T6zfq9/osD7AWfBtwC4QFD/Tj8bPrU+sf+vANNDecPywYy/uL0n/TE9Q8ENQ9KHiYgKBr2FWoQuQurA2X8EgIqCyIKxRECDNgMbvhz9Enxrvdd/M77vwG5/Xf9//f19Tv1lPT78tD1k/4cB58KtQwbByED4Pqc/QUAXQixCf0LWAmOBccFpwGO/279wfpM/Dn86gGnAm0AgfrK8yrxHvDD9Xz5PfxD/LT7f/km+nr53vkR+RT43fpg/T4CTQMDA0sCVv0h/xj+yAPsBD0EtQQ1AV8DaP/6APT/MQDp/tT9fv6kADL/Vf+7+kH6nPkj+9r73fxI/UP9Qv1n+s/83P7g/S/+mf2M/wEANQB1AbYAlQD4/iv/Uv8xAdABgQCh/1j+m/1L/tz9xv+Y/hIAnf/jAOoBgABJAID9q/9x/icCXQJtBDcDZgEvADX+Mf09/1D+Pv70/Sj+BQCS/ub/wv4Q/mT7avpp+UH78Pro/Uj+twIhAZ8BpQAD+434SPUU97T5MP3SABEFVAKWAI786Ppk93H02vUJ96f7bPwz/tYAXfu5+yL15fV39FX3pPi7+XH5if3u+tn7Vfs8+vz5ivtX+p79nf4aAOH+4fvr/q797/3X/sz9xv+E/oH9EP7M/Lr8Zvsk+wf8O/0x/bn+Jv2O+2r7xvse/Qb+u//xAfsBJAOHBNQDyAXcAp8CAAPpA0cFywbNB0kIOwdZBywHwgVgB4YGbgZ+BREFXwYfBYAFrASaA0oDgQMSA3cD+ANuA2gDBwOOA/EDbAT0BHMEEAXUBZsFiAcrBikH9wTIBe0EWgWYBJkFSwSKAxMEhAT9A8wB+QBxAAgAff7G/Wb99fzh+/H7zPtW+qH6+Pqw+nj6cvqR/GH89Psd+fL50Pp++ZX5K/l2/Ff7x/19/QD+If1T/F/8mPu3/Dz+tf7Q/a/9D/55/lP+6PwD/JP8v/xf+3P6Qfl1+sL5zvjB99X3JPfm9Q325/dT+Gz7/Pxw/gwCCQOOBPgESgaHBaUFrwjOCW4KBQxeDHsMEAusCqkIGAhJBcwDrgIkAlYBRQEdAVH+W/68/ZL8vvox+g36pvoF/d78j/8ZART/NgJFAZ8C2QGaBKMDWQfhB6QH4glLCmIJfgjDCnMI2AdoCN8GVgb6BnsGBAaFBFcDKgI4AQEAgwA5AOr/YQAlAaUAqQEWAtIBnAKaA38DNAPhBLwESgRwBMQEcwOdAyAC1AGZANv/h/+y/uf91P0i/Qf9c/xv+9j8Bv14/yL+cf/n//b/o/4u/sf+Fv29/NX7zP0V/VT+A/5P/XP9nvx4+xT61vhV+GX4lvhe+Sn4qvir9s33aPV/9AX00vLu8gb0+PTq83r0JvIH84Xwve9q7LvtuPRP+EH6j/93A4QJdQ28DPAOQBDZDSEN8gvyC3UMCgt+CxMKTAphCA0FFAHD/a35W/YI8njxJfJW8xH1Bvai9wH8rPyG/lb/bwBXAjUE7AV3CeILQg3KDoIPghDFD+QNmgyFCX4HKQaMAzYD7gHQAZcBSQFvAZwBigFpAWIAmQAeAXEBVgOVBHkG7wdrCA0KiwkpCdwIYwcuB4QG8wXgBXQF1gR1BZgDLQPAAaQAfwDq/n/+TP5G/gP+PP55/xQAgwCHAAABUgGXAQQCtwFeAjMCCgKFAncBhgHZAFj/Ev7j/H77u/ka+ef2rPWA93r0o/TU9WzzQ/Vo9KT0s/Yl9Uj3cPTb9Ez2XfNJ9I3yfvCm8LHum+0D79fy3/TQ+Ej97gK6CbcNEhENE84UYROkEfIQ4Q4jDLEKHwdnBuwEoAEhAOv7TvnB9Xbygu8A7Vrtgu3H7sHyU/ds/IEAvgTIB6ELNQ3sDiEQnxAJECoQSxD8D2YPpw1XC+YIpAU7Alj+Kfs39xz1+PLT8tHz4PWV+RL81wDDBKoIvwuTDb4OIw9DD24PyA/iDyAP+g3CDJ4L0wlKB/EDogHu/cn7T/r2+Jz4s/jH+sv7X/5GANACYQTNBHwFsQXeBaoEyAR4BGME9QRoBboFDQY0BSYEeQJPAZ//Ev4n/Ef6kPnW+dD4SPm4+Jv4Qfgh+Nv3BPdQ99f1XfV79rP1rPco+lr4E/v+/GP7J/zX+zT4X/mq9B3z+/E67r3tsemu6Ezn4eNW5W3q++/o8lX74AD2CdMQsBQmGXkaYRmGGJAUuxJFD4oJkALJ/6/+YPrZ9hv0d/H98OnrU+zG7ArsQu2J7u/zjfp8Aa0G3gwdEx4Xxho1G5saWRnYFPIQDQyGCZ4FzwC2/Nv5jPhn9WHzcfFC8IDuCu6E7zLzu/bt+kIBLgloEdYWQRwZH/EgjyAtHbUZzRR1DmUI4gLy/qr7BvlU9vj0avXs9Tz1F/ed99j4ifom/RkA3QPhBxcJlQ3RDk0QEhBdDrkMXAngBskCawKEAIH+MP8q/W/+VP4W/Hn9wfti+4L6Bvld+e74i/hP+Rj5Qvui+zH8WP3G/nX98v2g/cb76fv7+qv5z/pi+eH55vjC+QT4YPau+PDySfQP8bfx6u9B62PuPOqt6EDoKOJ67e7zPfR5/wIEUQ1sGWYYPyCRIogcWRqsE0kPLQtEAa/6ZvXY8qHxxO+r7XjuzOy67vnrd+/U8Tbw1vP/9zH+hwcQC8MS0hhRHK0foh+7HZwaIBL3CqQDXv3w93zwju2260rrGe3m7cHxYfNW9X/3rfvv/gkCvwXTC4cS2xcLHlEh5iPDI9UgghxoFv0OAwWP/OD2j/Go7erreuvp7jzxNPWC+Tv9LAHxAyIFVgdwCQsKtAlBDQEMBA6GD8AMwg4qC5gHpAS8ABH+c/nG9q31M/UO94T4Ovtq/XcAAAL4AgEFnAMlAxoBcP+r/vX84vzg+o37qfzU+jP9qPo/+nv4NPZY9eLyWPPQ8u7xIfMH9Hj2XfYl9xj3kvkw9mryB/Ur7z/tiuvx5QPlsuYq7DH1ePdHAcwKrRQvGKAeZiIFH1cYshRuDWQJuf/P+XL03/CV72Hxie/e78TxevAp8nP0Cfal9+73z/xAA00IVg9UFcQafhxtH+8fixx9F0oQ8wYG/473M/IL7dnojeh36nTshvAv9ZT5n/sa/zkDTgY5CD8KBg0cErcVhRnLHj4fQyBBHxQaVBYPDyMFePy39Knu/uls6KPozOtc8Fj1Nf3MATYHEwqqCwwO8Q68DbANEg63DLcM7AwQCwYMAQnkBJoDM/+P/GP5nfbB9XP1A/cb+dn7sP8zAsIEowYJCR8JZwaWBTMC3/8e/r37K/vs+qP6Ovvy+478sPux+5r4d/b19PjxS/GC8XTv4vBF8bnwkfS28z/zyfVo8tbyzfMJ7oTxqupB6H7niuAv64rzlfRP/vQH0BAyHWIckiSDJLQbDxVuDxcIdP9c9UjvRuo7663rvOz67ujwqfOG9Y72/ft0/aH71f8eBPIJZQ/NEy8ZXBwLHKodgxqLFU4N3gPt+e/yhe1y6KHkV+V85zntOvJU+FkA4QPABiYKuwwnDqcMNwxeDdoPDxHaE5AVJheRGFIUNhLsDX0GAv7O9lfxAu526uvqru1k8hj3RvxzA58IIQz2DUIPNxBqDh4P0QrkCdAK4wZ0CC4GZgXvBKEAJwCK/vP8YPut+MP6DfqU/Of90/+fA8wEdAevCOkHBgnDBrgDtgJB/578sfoP+a747/jf+WH65fpe+2H6/Pml+BP3sfX+8oDxSfP/8Q/0pPDG8+30xPNA8y72D/MF8gvwE+uD6pjoVt/54z/wzfY7+6MIEhHZHbAjACQoKhcktxaVEfoEvv5i9yDr6udC5znnmey77Vbyp/aF90j5Yfx8AbUBTwKtBVQKCRMyF7saAiDlH/ocxxu5E78NnAO19S3uQ+g05SPkq+M26NrvRvZ2/I4FwwuhDdgOqRB2EIAQ1A2ODDkMCwsWDcANqA0EELUN5gqKCSgIJgO//jb7Tvea94r3Vvdq+4z9g/9gAy0FBgnRCb4I2gnEClUK8wobDPkJsgsWC98H4wnrBvACVAI5/nL9+PzO+9v7i/xv/r3/ggITBKYFzAbtBCUGaQVYA3sDGgB3/nr+XPxe+wj7K/qj+U/5UPn0+KD5Fflt+Hn5m/hq+IL4f/by9fH0UPO28l3yU/HV8LXwAu6c7/Pu+uwr8Ffr7+1U6bzll+Z84dvsN/ym9vUJ7xKBFlEoBCJ6JuEmVBMIEFkEBvgT9mfp1eM65R7lAOtP78XyNPkm+m/+3v/5BNsG5gWWCFIMphAzGA0Z8xtIHmwXNRYfD7oF5P498hbp9eQZ4njkC+Yh66zyqft7Ak8JeBE4Ev8RYBLYDg4PQQwTCfAILwYZB1wIrgYWCR4HUAXVAgcBAwBQ/ez9Wv29/awB/gHGBRgIsAc3CW4HrQZMBkwDJgOYAgIDGwSCBxAJBwrYDLMK3QrcCX8GTgTnAbj/X/6S/kX//P9SAmQD0QQHBokGYgZjBMADgwIfAOoAuf9i/2MAj/9Y//7+4f7o/Bj7APrS+Ib3pfiE96P4v/qK+fv65Ps6+gr3//ZU88vxCPB97PvumezU7+juwPIC9uLyEvdr8h7yE/F651PpsOFM3tXgge6V+Gn/QA6cFrof6CihJN0lGh69DCsHMveG8dbud+YF50/pGe3/9MT5cv0c/4L/Df1o/o3/7gAuAxAFJwlbEcQXPhoSHqEbphWKEEoFQv0n9uHqZ+UK4ojjhurF70D2eACgBaIKGQ60EJUPhAy5CV4FDwYQBQgGwgdGBvUJfAiUCyMQpQUlCsADEv7pAYL8kf/6/x4AKgJAA8IJWgi1CUkI7QLyBB8AtwPYA0MDqAm1BP0JyQ2aCwAOeAnTBgcDfALaAkT+XACd/mn/mAHnAkgGdgQuBaQDkAGNA1kAmQB9AEH+8v60/Wr/3P8K/7L+PfsA+5P6Sfmo+dj4VPma9+j38vjU9//4+vUd+d7+XPmu+3n79/Su+lvyufL68anwZ+037hrxC/AN8lfxv+988FvsZO1x6a7nMOmQ5v/rxfeE/cUGhg+YEo8aZBvKGtsWqhA0CKD//Pb09KDykvBV8P3wsPTV98j63P2j/fT/Nv9M/nUD0gM2CJkJlAvJD5YQ5RLIEc8NTgpZBP/+ivoT+DH1SfOn8+/15/lw/58BrwWUBrwGHQgcBtEGVgVfA9QCegJ+BGIFzwYSB1AHSQdOD2kUvw3WFecQvQyXEWIHQAXQA5n96fhb+Uz7f/5/BQoEnQg2DH0M9A+tDXgNSw6LCcYFVgkLBycI0AjzA/YEqQX/A0MCdQSlAYQBxQIkAGkFzQUXBFQEsAKkAmQCzADP/Yj+O/tb+rb6jfpB/Af8yfob+0v83PuW/KL7HvvG+/X5nPma+Zz5DPc29Xrz/fE/84PyGvOw8w3ztfMP9FH0i/WP9MHzOfLY8/vx9PJL8onwQfE37YHuU+s+7LPoa+cO6HTsQPRn/IkDzQxZD4UVTxYpFJsT7gweBiIAOvmS90H2ePS59SL2D/j1+BH8IP3H/9kBmQDsAscEqQVxCRsKvgq7C+MJtAhICJMFEwREAaT9pv0S/eH9Zf6g/8j/ywGEAjUCNQVlBMEDeQMPAs8CVwR8BTwICgvYCx4QZhFQE5ET3xGFDkkMFggDBcADwQF8ABICtwN/CZYNJA0aEDIOKQ87DkkL6gc8BvUC/wBaAmoC9QT1B74H8wjjCoIKPQpgCTYHbgZ2BBgC/ABxAHP/If/s/fv8R/30+3L8RP0i/Z/+1P8N/3MAHQGF/zT/p/1l/KP7rPox+uH5svmP98H2BfZ+9Wj3GPd09/L2wvcV+FX3Y/h89xb3lvU69kT0d/Qg8zT05fQa9MD00/T29dX1yPWI9YP0v/aR8wzzG/EK8K/wBfH17w/wk/GH8Vnya/Pb9jL7oAD2AkIDbwabCkQKVQhVCH0EmwJ/AQ7/Uv6M/07+i/1B/uz+Bv4q//39cP7dATMCxQNXBKMFjAfmB1AIowgFCAkHDQZgBOEECgVXBOYCwwMzA2YDWwSBA6EEfwlWDKkOZxB0E24T4xbeFQUSqxTWC24KMggsBnsG8AeKBigGqgr6CHML6QpLCzULNAxsC+YKKAx6CQcKYAefBwkG3QNkAh0APwFXAFcCDAJXA0YEggInAzoBaADW/k39bfzB+wv8DPsx+6P7pvsO+y76W/qP+Q/7u/v++0D85fuh+0b7Ivuc+bj5wPbf9SL2MfRV9T30EfUS9AH1VPYK97r3jvWo9dr1D/cq9oD24PbH9hr46vZ+9+r2wPap9B70PfRP9Pv0l/MQ82DzLfVo9E713PQA90D3+/eS95L4TPlX+JL5Ifio+UH7pfoQ+ub5HPu7+8L7aPoG+gP7g/up/OT9u/7CAJgA1QDbAHQBXgJhAiUCeAJMBMwEDQWzBTEGQgctB6kHzwd8CKEIHAjUCNMIpQnKCcYJWghhCZsKlgj0CJAIlwnECEUIqQfzB5sI5QY9BzQHfQcBB6kGiwcsCAEI4AYEBkIFjgSYA6MD4gMxAh0DdAPfAuwBiwIjAZgBLALT/ywAuf+p/0oApv/b/gYATv5t/h8AIP4vAGP+B/8aART+s//Y/NT8Nv3f/Ab+I/wx/4L9VP/Z/Cz/Pv7g/Vf+5P2u/bj8FP6o/o3/FQFD/pD+Iv/jAJb+zP8S/5H9MQDS/0D/h/03/4b7hP1s/0X9ZgCR/BMAT/7g/w/+Ov1uApz73/3U/Fn/tf9n/yj++QLRAcMB4fx9+7H9xPo8/b/9rf1j/pUCNQEk/aMCh/9xAMv/8/zuAgn9vgJ+/Uv/nwGC/TP/Ev0p+0//y/vm/fgADQXh/wEGHgZyBR8CzgbwAQQAegJC/14EN/5z/7//pf31/jwBQQNB/VACegNmBZ0EsAMxAEgCvgEOBej8lQDVAkL9DACGANAA4wL/A8YAJQCUAnYAKf8B/vr+RAAHAtUDWAKnAiMCLQMl/oIBYf47BcL9gwEsANb+hwOi/Af/TgEMARoAYgTv/QICLv1lAAL/e/2zA3f52gGLAyH6XQKkAdcDav3lAe4CpP3T/gb9NAhl9CQBGQDO/VIBq/1zBzT/VP4oAGL+Vghv9tb/bv0J/5EEFAKy/0EB8QHvAaP5pAd2+t33RwFdA8H/ZvYNB+n+kwMT+DgGHQDlARf3MQDaAw8AKfv3AdT5oQDR+YP7MAY1+EcGKfpLB5f+6P7TBbsBUgUMACgBHfxdBav9c/8bAE//OAWV+uH+zwCi8YENb/TrAtQEZ/8+BqL9aArA/cr4k/pVBHH3bQSn/igAAA+T7vgIlvrv/xUCxPYMBmAJkQQG/MoC+AGTCIDvCwNt+1H7Hf2S/BUIKvqJBcz4AwbI99ABcwxc9OUMBv6MB3kDLvyU/87yxQhxAnv5mghkA2z1Owzc9EgCavpbAmz9ZvsrC1D8YAFd/6QFmQFy9lD9Gg019639hQPXA88MMeyRD7j65QO1/eMBkgeA/nQDr/n7BSz7yPvG9NoJb/3N/Nz9rAe2AP/1egNMCZv7hPhUCcYEX/p6Az8CmAhF9LD9iwoxAQb7Dv1ABvD6ZwJe+a0EhARZ+YQEpv5dBaD7Cva9Dqz5Ufuz/hMGYAXQ7dcLt/wU/k8DcPY9ECr07wjE94UJGv/T+msFhfzeCerx0gcB9xwLu/FBBdID5/TiDjf17gOy/2j9zgEI+gcHcPwu+xQQ6OwyDZT/2PmYAwP4MQse9RcDTAZl+zIBF/7n+nYQLPC+A5n80gjm+6L/6gL6AQoBjf5N+4z6nQJ5Acb+7fDQHoXpjAqg97QBbAEn99cPOu1tEKP3Xf3sA7AD6QA7+agAFApX+cEBPvgcDRH7fPmWBA0Fdvpv+0wC3AcA8AEOJfvL+twNOfJOBLsEg/szAJ3/+f+oBaD2qBBY8fgAYhGj6AAOi/YKEtbuEv+XC2YCK/b5ADoLz/UUASgIaPto+TENBPpk+5oFvgiD8AAHrwaP9G4E6P2U/TkGz/zP+GwPCPdFB2XvCBep9db3DRJz8kD+Ggvg9cX/1weH/R0BlfJoE871G/7gBXn+2AN8+cUFt/meB1P6+v91BOzzRBW4+1n4rRTuAqPwaAJFCYDxjvutCZb6fgAaBqn5lQuX9ZAGTe24Eh/1Wf3uBbH9Zv6rCKbydwb5CVHwhApJAi3/T/ni/mkS9uvG/+QGbgPx82MLyPiNAMID4AAI/lj5vA2i92z3egTSC5X0GfieBhoJVPz07LEaBPUa/ZEGTvn1AYUFbfx4+f4BrwjJ9xEAggJ//+P8GQgz+WT8QwlKAgX1SfyCEdrxAgWn+nEAMQ4K7/kH6/8sBbHyXQhI+5cGgQMd6HgU8wAC/ibsIhX1CGXkYg3q+gIPXu0SBdz+HQia9FYBKQd894QMru7HC9L9EPcLCTf5lwSFARX1PQkDB1Xym/9TDBj2SAM4/oP67w3Q/Dn1vgQWBH383/6L84AdF+z/9pAWM/Yt/Lz9nglV9YD+dAiT+Xf9vQmq/UTu9hlY9BD7fgW5+DcNp/RV/TIHZQGL9uQG3QAo/FoBPfz3BRL33wFsBV/77vjQBwQBRPiYBTT+NwOy9K8OLPqX/NT/Vgbf+Ij4+A8d9dL9Bgb2/LsBSv58/dEGyfYzByj7vv8iBrD4T/y3/l0PhPDW+TQS1PoC920I+gHs+W4Hg/yiAv73WwSmA/T7SvCaFSYAce53CogCHf1SAUn+2ARu9XYIfwDE9y4EGwIrBVz3hPmJE9jz3v5nCGz3AAhC+x3/EwLT+5EHE/hE/4sKxfe/CyzwvAWoC3vyFgTt/gb7ARBs8wP8yQ0U98YK2Phf+NAUefak/iwDCfuTCBH8LP1nBgr9vgLP/2b+6f2QCfb5OQFeAJz98AVkAC37PP2FBu8BCf54+SEHUwPR+sz/5wCJAGYGYffg/K8KEPtMAIwCRvlxBqoARP5m/An/9AhU+qL93QUp/eICZ/80+vwFXv1c/vMEyfrbAxj60QdMAZ3xwwzn/Rr6bAmT9YoAzgoR923+rALBAxz+qfm9Bl37bwE3BGL2XQVVBDL63/mYDWT6XvtsBuD+7v1w/mH/aQCIBHb9IfnAA4cFiP2Z+ZADKwN3+/UAJwC9/hcC4gCc+ngELQDu/FsDwvunAJ8Cif7s+sUJmPj9AZwFl/bsCtL9ePcrCJkDTPpo/g/8mAyv/RX2xgYYALAD5vlK+AwRdPg//tgEK/yVAZwD8/ojAbIDNfsXAUABJQNn/F39lwZm/lEBuP/C/0AA/wHq/13+0AN2/5n6YwQA/pn9qP+wA2MADf2S/WgEpP28AWv+gP6tBw73hAKbB7DzgwYCBCb2Dwuh+xL5iAqu+UUDXgDY+lgHf/vmAgD/zP3jBWD6H/9bBn/81wGjAKH7zQV6/6L9tfraB5H/Hv13BJL8AQCxB3j3bwNrAIwAewJZ9zsHeQFz+cEIzvgWBe3/5fnmBzQAmPsSBjT6YANABSL4SgKt/hcD4gJy+ZcEHACG/HkInfx8+iYHrf3X/9j/LP/LBJH7iADS/wIAUgOQ/7X/Gf1/AcQAuv/0Afr+i/69AZj/6v8hAH0B0P37ARoBcf0cAy3+qgA6AFf+uwFU/kIAqAEf/GYDeP+qAMv+FgAUAP39uwTV/TH/+v8cAV79xgF5AcP9Q/8nAHr/bgEw/zr/Tf8k/xACB/5bAQgBrvtAA7/9fQD7A7H5swF0/58AIgHy/GYBjP1AAoX/N/71Ai3/Gv1NAxv81AAFAef9WwF7/ewA7v8u/8v/Av9hAen/zwCI/SkCOADT/S0CN/zFASoAM/47Agz9DAFqAC/94QFT/iL/wgJZ/cP/5/86/yMAS/5SAZP/hf9//zH/sv8Y/93/SP8V/xcB5/7f/gEAIv85ABL/4f9E/xUA8f5UAAb/CAAs/w7/MgAP/3X//gBa/rH/6QBH/lkAtf9S/1gAT/8p/1AABgA9/wMAEAB6/5QAJP8QAbj/yf/BAK7/aQDDAHj/qgD4/9YARAC//wkBXwADAFIAYACbABwAjAA6ACkAxwD//0kAsgC7/8wADgASAKIACgBaABAAXwC/AHP/1QBQAMj/IAG2/2sAggAgAGoA8P+VAFAA5/9/AD4A3//HAAYA4v+fAOn/cAAsAHcAuf/MAN7/RQAFAE0AGwAyABoAIwAsAEAA8//o/5MA6P8TACwAKgAXAEcAEQAWACkAYgApAAgAAgC1AKX/VABSAO//eAAUAP//OAAkAFwAAwARAD4AJgAMAHkAxv9sAFwAl/+GABIAMgBSAJ//ygCk/wwApQB//3gAJQD4/zsAEwA+AJ//nQDb/9D/5QA0/3wAgwB3/7kA8f8HAFIADQAfAD8AsP+JANn/4/94AL//NgA0ALz/RwAcAOP/JgA5AO7/KwA/AN3/MgA5APv/GgAMAGMAsf84AEQAnP9NAPf/4f8LAJT/YwDM/77/XwCX/woAHQDK/9//SwC1//b/FgDM/xcA3//u/9z/EQDu/7v/FwDX/77/KwCz/+H/JACn//n/9f/E//7/y/8cAKf/BAD1/9P/CQDV/+L/FADM/+7/9f+///v/8P/P/9L/GgDV/9L/EwD0/9L/FQD4/8X/TwDJ//H/LwDg/wAABwAOANX/JgDY/x0Ayf8FAPD/y/83ALj/CwD5/93/IgDm//T/SgDG/zoAEADY/0kAsP80AAQAuv9DALn/CQAmAKz/MQD4/+j/JQDb/x0A/f/3/xwAxP9NAND/EAAyANn/OgABAO3/MgDx/wgANAC6/0MABQDQ/2QAxf/l/3EAo/8sABgA6f8sAAIA/v8mAPz/KwD5/xkAIwDw/0gA5P8sACcA4/8lABwA9v8aAP//AAAZAPL/KwDo/xMAJgDn/zgA5/8NAB4A6f8gAB8A8P8tAPD/GwAQAOj/MQDg/wkAMADE/yUAAwDl/ywA5f8bABAA6P8dAPL/EAD2////DAD7/w4ABgD4/x8A8v8RAAAA9v8uANX/CgAqAL3/DwAtANv/BAAjAOD/BgAEAP3/AQDz/xAA7//8/wgAAQD7/xAAAwAXAOj/GAAKAN7/GwDi/+z/BgDI/xAA8//O/x4A2P/z/xcAyv8CAP//4v/5//n/3v/0//f/xf8JAMv/5v8GAMX/FgDS/8v/CADK/+b/3P/X/+//yf/g/93/6//T/+z/9f/K/wcA3v/f/+z/2v/w/9j/9//a/+H/AADB//H/9/+5/wQA1f/J//f/xv/u/+D/wP8CANX/yP/0/9n/yP/n/+f/1P/e/+T/2f/m/8z/7f/i/83/9f/j/9v/7P/n/wAA1P/j/wQAwf/2//v/t/8TANb/4f8CAM3/FADO//L/DQDF/xIA6//q/xMA4v8EAP3/7P8ZAPP/+f8VAOf/AgACAO7/EADt/wYA7//3/wsA7v8IAPT/AAAMAO//+f8AAAQA9v/r/w0A8//3/wwA5f8LAAYA7P8MAPP/EAD5//L/EQAFAPv/FgAHABAAEgD//xMACwAMAAYAIQAEAAEALgD//x4AIQAbACAAGQAcACoAFQAnAC4ADAA9AAAAGgAeAAIAJQAPAPr/KgAPAAkAKQABACsADwAWAB4AFAAOABkAKwAPACIAKQASAC0AFgAmACAAFAA7AAgAHAAuAPX/LgAwAPz/QAAcAA4AMgAgAB8AMAAgACYAGwApACMAEwAyACQAKQAlABIAOwAYABUAOgASACgAGAAgADAAGQAkAB0ANAAXAB8ALAAGACcAGAAMAA4AEwARAAYADgAJABQA8P8QABEA9/8EAA8AAQD3/wwAEwD0/xkADgD3/wAAAAAEAAMA//8MAAIA9/8KAPj/EQDx/w8AAwD1/xkA+v/y/xYAAwD6/w4A9P/6////8v8FAOj/9/8BAOH/+f8AAOr/7P8FAOv/7v/4/+v/8P/r/+r/8v/s//n//f/4/+//7P8CAPH/7v8GAOL/5//0/9f/8P/X/+//5v/S/+r/5v/U/+H/9v/i/+n/7//w/+r/6f/1//H/6P/8/wUAy/8NAPT/2v8OAOH/BQDj/+z//v/d/+7/+v/k/+n/CADs/wEA9P/+/wMA9f8LAAoA/P8GABUA/P/z/xgA+//u/wcA9v/l/wEA6/8DAOr/7f8NANb/DgAFAOX//P8BAPT/AwAGAP3/CQD7/xMABgD2/xoA//8PAAQADAAQAAIADAACAA8A8v8SAA4A7P8hAPv//v8ZAPz/FgAJAAwAHAD9/xsAHQDu/xQAGgAKAAIACAANAAIA/v8MAAoA8/8UAPz/5/8ZAOH/8P8PAOv//v/0////BQD3/wcA/f/3/wcACwD9/yYAAwARABUADAASAP///P8JAAIA8/8cAP7/CAAWABIAHgAWACoAMAAmAC0APQAbADAANgATAB0ALQAYABwAJwAaAB0AAABEACIABQBLACwAIgBfACkAVgA+AD8AVgAnAEQAMQAiADgAKAAhAB8ADwAXAP3/AAAOAO3//P/9/wUACADl/wYAGQACAPv/DQAKAPj/GwAFAPf/BgAJAPX/FQABAAQA6v8EAAkA0//v/+7/1v/Z/9f/2P/Y/8n/4v/P/6r/3/+u/8D/6f+3/+n/uP/f//H/tf8DAM//2f/l/9r/4P/I/9z/0/+7/8P/uv+y/73/rP+5/6b/tv/b/57/2f/K/8T/uP/T/83/rv/F/9z/xv/Q/9D/u//R/9D/uv/O/7n/v//C/83/7P/T/9n/6//i/w0A3//o/wcA2//y/+f/5f/m/8X/AQDj/9r/6//6/+D/9//+/+X/9P/6//T//P/x////8v8UAAUA+P8bABgA+//x//X/4//m/93//P/c/93/7//R/+f/+P/6//n/6v8zAOX/DwDq//b/7f/u//P/2//l/9n/CADx/+3/5P8JAPn/EwA5APr/MwAxACUASAAfAEEALgA2AEIAKAA2ABUANgA8AD0AHAATADEAJAAgADQAAgAdACIAIQASAA0AFAAHACAAKQATABsAHgAbAA8ADQDz/w4ADgAQAPP/DAD2/xEAGwAdACgAJwAoAHAAKwBOADAAGgByAFIAIgAxAEMALABPADAAMABEADQAOgA9AC8AMQBCAFMAZQBJAEcAYwBXAGYARABMAF0AVABkAGEAWgBYADcAcQBAADsANQA3ADsATQBIADUATQBAACIANgAdAAwAIQAwADIAEgAWADAABQAVAPn/3////+j/9P/c/+X/2/+4//T/4f/N/9T/3P/O/+X/1P/T/9P/w//D/8j/mv/A/7b/s/++/6T/s/+e/6j/mv+J/4H/i/+M/5X/df+A/5X/df+k/6H/gf+X/5j/hP+X/5b/gf+M/33/lf+I/5r/eP+N/5//lP+f/4r/ov+l/5r/nP+T/5j/kv+R/4L/if9//4f/o/+H/6L/nf+D/5v/pf+c/5L/gP+Y/6P/mv+0/5D/lv/h/6f/w//E/4//3v+7/63/w/+X/7T/y/+6/9H/vP/U/8r/0//S/7X/r//E/7T/sP+3/7T/tf+4/7n/y//B/8T/0f/g/8L/yP/C/7z/w/+9/8H/uP/D/97/z//E/9D/2//1/+X/8f/c//P/BQD+/wMAEQAXACwAOAAbAEsAKAAtAFAAKgArAEcANgBIAE4ATQBZAGMAdgBpAGoAogBRAI4AowBqAH0AfQB0AGgATgBIAEwAQQAlAB8AIAA0ABEAHAA3ADsAMgA/AEYAWQBRAFIAQQBWAC4AagBWAAoAQAAvAGwAOwBjAA8AZAA7AB0AJAAbAIAAngBQAI4ASACWBF4CGwA1A9gAuwR8A5UAkQQgApoE9AO0A5EDFwJ0AmMBmQF8AKIAoP8wANb/vv+Q/8L+SP9r/7P+Xf+N/rn+v/9+/+3/lgCPAOgAdwEtAe8BNQEGAVEA5P8/AK//1f+o/iP/Pf/C//f/c/8FAH7/3f+m/9z+KP84/ir+5v10/RX+2v2x/fT9tP5T/x3/j/8jABYF+v8QA/cAwAQuAVICGAAA/+n/4/zH/bP7Gf2q+w38T/x0+8/8sPyf/Hn9k/0b/tf9/P64/uz/Yv/G//D/4/+SAVYA4ACvADIBxgDxAIwAJAAMANj/Yf/u/hT/4v5c/uL+4v2//hb/0v4C/2n/kv+o//j/4/+YAIMAtwCcAJsAvADNAHUBPwH7AccBUAGTAS0ERgFkA58BQQKCAaMBwgBZAHgB7v86AVIAuACoAKoAFgHn/9UAYgDAALAAQADGANEBCQIOAdkBxwFUAn8C7gEZAUIBowJwAagAegC1ALIAqgB7/6j/MQBS/6X+Lf4U/tb9c/3+++j7Jf0E/WH8Z/x2/Qr+zP7I/tz+5P9AABkAFwB9AKQAPwD4/9/+i/8Z/2f+nf2c/en9gP1i/QL9jf3E/fX95v1T/oX+fv5e/kv+Xv6o/bz9ovzR/OX8ofvV+7j6iPp9+hP5Pvj79sn25PUJ9Xn1rPYN+LH5ufyk/z0ELAfdCgsOKhBuEtkSlRJoEQsPWQwRCSEFKgJI/nb73/gD9932XvZc9hT3xPiP+nX8F/6Q/zkBzwIPBAYFvQUIBsMGewd8B/EHOAhICCcIJQjeB0wHpgZTBS0E2wI2AQ//T/3x+4H6c/mg+GP44viX+fj6q/zq/i4BBwSTBloJUwtVDfQOVA/DDxYPCw5cDCUKwgedBVcDOgHe/rP9cPyE+6D7KPuh+yf81fyf/az+pP/RAPsBsgJnA1YE9gRJBegF5QUDBs4FjgX9BKAErAOCAs8B2QDa/wr/Q/5j/d/8Yfz7+/378vuq+/L7MfyL/Az9U/2q/QL+oP6z/qP+nv5M/jn+uf0R/Yv86/uR+6T6Tfr2+Xf5rvlo+SP53fgK+Q35yvjF+In3MPdF9sj11POM8jnxu+8Q76TsD+yR7jfyBfO89QX72wFkCN8MPBEDFhsathupG3oawxczE6AOBQhfAv/83PaK8eLtF+x669TqCuvH7W7xWvXy90X7Jv99AnQFtgaPCC0KvgozC94L+wsoDAkMkQucC6gLHgsdCYsH/gUfBKsBGP6g+jf48fVd84vxqvDe8KvxmfMp9sb5e/3/APcEDgl/DN0ObRACERoRNBAuDjQLbQiYBX8Cgv+I/Ij6Ivk3+HX3XffH96H4sfn5+lr8D/7s/wYBFAOHBGkGzQciCWUKEgtGDBEMOwzxC8YK2Ak/CH8GdwQDA28A2P5r/TX8m/v6+gj77fpa/BD9Kv5i/7MAsgHxAuoDKgQNBQcFZAX5BPgEUATOA4QDjAJAApUB6gAYABQAnv/m/t/+Mf5c/ob+RP7W/Sz+Ov5a/pX+fP61/gj/Sf8s/2X/r/9O//7/z//f/xAAAwDQ/6//xv87/+P+YP7o/fv8bfwq++v6Tfqm+XX5Cvkr+lb6Ufs9/F39Uv5a/yAA4v8NAHf/l/0s/CP6evfX9C/yD+8C7Q3r7ejj6XHuZ+418YL2J/2NBEkJzA2qEiAYoxqqGlkapRioFCgRqQvvBfUAlPr/9QfyTO8P7kns6+t/7TDwKfOt9ET3Gvsq/18B3gIDBUIHngjJCT0LtQs6DH0MzAwPDckMzgtECtcIKwcfBQ0Clf5Z+774uva4807xc/Db8Gnxo/Is9T34BPy5/9wDswcYC2YNZA8eESMROBCbDnAM7QlNBxoErACW/XH7xPkt+Pb2R/Zg9lP3kvcA+Hz5RPoh+3/83f2i/3kACAK1A4UJsw0dDKcPXBE1FtAWIBT/EMgPfg+pCEAFW/9b+6/4d/Wj8mHxxvJx8XT04PfP+f79v//fAuUFPgqHCScJhQrgCQMLnwcPBvgDHwSjAXv/1f///Jb9afw0/P37uPvO+5z6ZPxo+0f8TPxm+zz97f2//tz9Cv/G/48AagFcAE8BXgGAAWEA0wD9/xP/iv6A/Wv9pPwK/Oz6Pvsq+/v6V/vi+qz7fPsv/Pj7a/zj/D/8GfyF+7n7+vpo+Tj4VfYW9krz7PHt77PtWexQ6ybvu/Bk8Rz0o/r4AQYH2AolD/MV3BmnG+MaGRp9GCUUkxAFCuQDIP5392zz4+5U7H/pbeiB6XTrIu9p8YD0lfgz/lgChAQEB/EJkQxADYINqw1+DTQNbQxYC2AKFwkrB+QFwgSJAncAS/6f+/H5b/gK9nbzsPKn8tfyavOP9GH28flS/SwAugNNByoK0Az/DuIP7A9cDwIOIgyYCWwGlAKa/6X8Kfr696D1UvQ09MH0NPWh9Uj31fjx+nD8E/6D/8YA5gG8AvUD+wMzBK4EnQWYBhMGtQbmBjgLxAwCC7ALwgutDpIM3glmBYoFnAP3/dH76fdw9r/0iPT586v05vdW96P8Pf9VAdsE5AV0COcI6QskCVEIFggdBekFHAIdAGP9XP72+5H6Zvss+a36rvpu+2z7Qvyu/D/8zf65/e793v58/jL/0P9GAIn/igDhANgAzQFnAP7/FwA1AP79n/2g/Er7RPt5+nX5ZvmX+TP53vmr+lD63Pre++z7z/xX/fP8wfzg/Pb8MvyG+4/5h/jf93X1lvN88frvFe0f7J3twu+S8KvwcPXA/OMCPwYdCoUQ3RZuGsYaJhvhGkIZWxbXEewL/wQgAEf7vfUw8SPtouvq6ifrbewl7xHyufRY+Ub+vwFjBCoHIgqTDMgNww3FDeYNCg5xDbIMKAvPCbIJEwkIB+4EeQMZAuv/2f01+zH5WfdZ9TL0zvPG87zzjfXP9zv6Tf06ALMDGAeLCigN4w7uD18QvBDeD6UN4wqFCMwFywJv/6X8Ofqd+Fj3pfZI9mz2Fvdr+Af6XPvK/En+iv/WAPIB+wI/A+ADWwTwBIIFkQVLBloGYQcaCEkLNgx6C9kMOg2zD8cN0gv2CMkHywYKAWD/A/rw+FX2oPU99BDzEvV99Af6H/o1/aD/vgLuBUQGxgkuCOkJGgmFCF4IRQVjBDQB3QGb/oL9nPyh+l77D/oh+6j5WPoP+g/7Xfwn++v7IPx6/W79Ev5B/m3+2P97/0cA1P/V/1X/Mv8Q/1n9Mv3h+5L7k/r++Zn5DfkF+Xr48fg4+U/5kflO+gz7kfsM/Az8QPzU+4H7u/qV+eH3t/Wi9NPyb/A57uPsDu928I/wGfLm9b78JgGPBQMJEA41FKsWSxgBGMoXYRZtFLEQ5gr4BbkARf1Y+PvzNvD37mruiu2l7jvwbPIH9Yj44fum/pQBsgMcBuoH4gjkCRsKYQqwCcEKrQr8CQgJuwhFCVMINQdJBTQEJQMrAfL+gPx6+p74YPe79Zf0SPQF9fj1dPdq+bn77f6XAWsEJgeiCYILcQymDboNhg1PDLYKIQnuBgIFZgJSAGT+qPyN+3b6s/lT+WD57/lp+ij75Puc/KX9cP6f/6sA0wGmAhAEmgXZCAsLVwzyDTEPnBKPEmwSRBDpDkkODgoRCPoBs/+4+yz5ePfB81v0pPHp9db1Hvgo+pD8PgHhAWEGSAYYCUIJewmHCjUIQggyBbQF5wJvAYsAQf6A/sv7Ef1/+y78dPv4+rb8l/s4/Qj8ff1W/bT9sv7a/Vz/a/7n/5n/GADp/87/gwCT/+H/r/7H/v39bv2r/LH7cfs++mj6vvmi+WH5W/nF+c75ifqF+k37wfuB/A79pP0P/u39rf4m/oP+nv2O/fn7PPs1+rT4ifc19dHzLfLK8F3vQu2S7DHr1OwO7xbwP/KT9Ab79P8nBakIjAxKEkoW+xg4GfIYYRivFssUKhD/CnEFJwGJ/d744PMX8B7vj+1a7VTtEu+P8Gzz/vbW+WL9of8eAw0GEgjVCegKbgxMDH0MBg2yDDQMjAoGCmUJRAjGBpsEZgO+AR0AeP5i/GT69fgw+G/3Yfb19VL2VffS+Or5vvvz/TgAqAK3BN4GYQjDCRsLfwuiC88KDwoDCWoHsAWhAxACOwCL/mH9TfyX+xD75Pon+6v7WPyE/V7+vP8ZAdoDMAcDCGYKDAv4DjQQ8xCgEAQPsBCJDdgNBgnmBmAE8gAuAan7s/xS9wj6zfjB+FD6mvj5/bv7BQHC/+ICswOUAykHZQSaBzAEVAaoBH4DEAQuASgDDP/NABX/Qv+I/yD9iP8a/YL/nP1v/kH+If0k/wf9Ev/S/CL+2/3P/Xj+vPyp/sb8K/6z/A/9Bv0Q/Nb8bvu8/J37OPwJ/M77tvze+y/9afz6/NT8HP3J/Rn9iv38/Jb9mf34/CL9Tfy2/Jj7dfuD+rv5MfnA91H3YvWm9AjzXvI68eXvTe/r7kvxu/G88xj14viu/aQBIwauCLYNTRHuFMoW2hZDF+wVGhUwElMOZgm/BDwBxfxd+P/zf/GW74LuC+6B7qHvRfFO9O72HfrH/Mj/5gLeBAgHiwhMCtYKtwpDCwkLTAsXCigJewhuB+sGagVKBKMCXAF0AAT/if2t+5v60vkM+Rv4sPef9yL45fjF+RH7VvxK/igAQgLWA2cF0gZjCBIJqwmUCVsJBAlZCJoIiAbBBqsELQVeBHYDnAOeAW0DDQF5ApsAUgDRALH+4gDD/R8Aif09/3//5v5fAVf/bQO2AaAEagSKBTEHvQWgCPEFzgeBBS0FlQTOAU8Cjf6Q/3D8V/yd+yb6wfu1+Tv8BPsq/Y79Rf5vAK//RQJdASMDrwLMAjQD8gHVAuMAcwH1/7v/Hv/s/Tz+rvyr/U/8nPwm/Pv7ivyJ+5v8qvuj/P77R/yg/Cr8FP0p/DX9ePwm/c/8sfxc/Y/8hf1//HP9A/2K/bj9R/0Y/jP9d/6k/eb9iP3//Cz92/vz+5f63/nw+Ev3BPcK9bL0KvOF8g/yQPGi8rby1PSa9UX4dPvN/uQCdQWNCTgMLBBXEhwU1xSeFMgU8xKuEQsOIAt5Bw4E/gC8/E36//av9RD0Y/OM83jzOvVc9tn4jfr3/HD/dAHCAyIFOAcnCDsJpgkSCnAKOwo7CnoJUwluCB8IjAejBsEFjQQMBMUCyAFfACD/L/7n/Cn8IPuf+v/5BPpr+sr6mPs8/Jz9Ev+FADoCggMdBWgGsAdcCb4J3wqWCjULRAvGCsIKDQn7CFoHmwahBYQDUQORAPsA8/7N/r79svzY/Tr8ff7s/DT/3P4+AKUBuQFoBBcDHwYGBbIGZwYoBvMG8AQZBkMDHgTQAQYBCgAI/k7+0/vH/Lv6U/u6+tj66fsf+9v8QPw2/ib+Fv/H/5r/BQEXAG0BeQDKAFUA+f9BAPD+cP8G/mX+nf1e/Sn9X/yY/KP7IPw/+zn71/qd+qj6M/pr+hD6dPpR+qr6DPt7+yv8Yfwv/Un9N/5f/vH+5v6q/rT+Kv5d/hH9zfyZ+077uvpJ+gn68fld+nz6TPt+++37APwY/Ov7ZvvI+m755PiW9233lvZP9j/2CPej+Oz5aPzl/S8BSQOPBpcI1woZDAQNEg5iDTQNCQu/CT8HGAWBAuX/0v1F+zf6yfhV+Af4Q/hJ+TP6tfvh/Mb+PAB2AdcCpAOkBNcEMAUHBeUEpQQZBPQDLgMQA3ICjAJYAlACSAInAncCJgJvAgQC/AF4AVEB3wBwAB8Afv96/yX/LP8R/1T/eP/B/0kAqwBOAbkBNQKeAtcCEgP2AvUCmwIwAtIBZAFJAeQAowC+AOMAfwKaAjoEDASSBWwGkAdTCEUHyQduBuAGSwUaBP4CjQCMAIf+T/8F/Uv9+PxC/eb+zv1hACD/0wETAd0C3AJQAngDmQFcA9UAuwEEAAcAc/8y/k3/aP3v/in9cf7d/Tr+u/4k/ln/Af5p/5f+N//o/mD+/P4b/hb/+f3C/hj+Of6J/hD+sP6l/VD+gv0V/qL9Wf1j/aH8P/2Z/Bv9ffy9/LP8u/xB/QX9lP13/ff9Df5f/pj+hf7X/ov+2v6q/rD+ev5I/g3+2P36/cX9ov2E/WP9nP2a/aD9W/0//Qv96PzE/AT8tPvU+p/66fmj+eH4mPiR+N74jfkr+gj7Q/z7/db/qgEeA6cEKQZ2B30I8ggYCYQIFghJB1YG5AQLA8IBOABB/9v9TP1f/DT8EPyJ/Pn8c/0t/vH+5v+DAE8B4wF0Ar0C5gIYAyIDBQPbAqwCdgIvAhgC6gHKAYwBcwF8AYABZgFHATQBFwHtAOAAsAB3ADMAEQAEAO3/vP+t/7r/4P8OADsAcACaAAcBbAH/ATMCigK1Ai4DcAOaA58DYwN0AxYDGgOJAlICugFoATQB4gCsAF4AdgB3AIYAqwDGAEUBWwHZAewBVAJdAqQC0gLMAs4CfQKJAkgCEAK0AWQBNAHYAKUATAArAOz/zP/S/6T/sP+T/8X/xv/q//H/BAAsADgAWgBWAG0AUABeAFEAPAAqAPv/7P+7/6j/jv97/4D/ZP+L/3T/kv98/5L/hP9x/2//S/80/9D+s/5w/k7+Iv7z/er9t/3Z/cv9I/40/mf+j/6Z/vH+Gf+Y/4H/uP+W/8P/8P///x0ArP+4/17/m/9N/y7/xf5k/ij+/f3h/Yr9OP0W/fD8KP39/Fr9LP2q/aH9Lv47/of+t/7e/hv/G/8s/wn/9/7Z/o3+Zf4Q/u39if13/Vb9Zv1y/Yf9+f0u/rv+GP/J/zMAqwAnAX8B6gHkAS4CDwIbAtEBugGLAT4BFgG8ALoAbABaADgATgBJAEcAcgB0AJoAkAC3AMgA1gDLALgAvgCfALUAnADGAJMAmwCeANcA1ADkANwA5gD2AA8BCwETAfEA8wDrAAYB5wDuAL8A0wC5ANAAtQDCALQAuQDDAMgA1wDaAPIACgETAR4BGgExAR4BNwEXAR4B8wDqAM8AxQCmAIsAeABpAFgAZABVAFkAPwBIADEAUQBUAFgAPQAyADQAPAB0AHsAXwBBAE8AbABvAG0ANgAiAAsACwD9/83/m/9p/2r/Zv9r/1H/Tf9D/1H/Xf9x/4T/gf97/3f/hf96/3f/df9l/1b/Qv9L/1f/ZP9M/z//NP9C/z//Sv8y/yf/8/7//gb/Bv/2/u/+6f7m/vn+Gf84/0X/Qv9X/1f/fP+G/7H/n/+T/2//ff+N/7L/sv+R/23/av93/5X/kf+Q/1b/T/9Q/4n/hf+B/2j/Wv9m/37/ov+T/43/ef+J/5z/tf/C/8T/q/+s/7n/0P/V/+j/2P/d/+D/+P8EACEAIAAnABwAIAAoADsANgA7ACEAGwAoAEAAWgBiAGQAWgB4AHkAoACbAKMAjgCdAJUAowCdAKgAowCiAJ0AqwCmAKYAnQCqAK0AqACrAKwAsACvAKcArwCsALgArAC2AJsAnACAAJIAjgB1AEoAMwAjACUAHwAfABAABQD+/w8AHAAwACwANQAuACoAIwApACgAFADw/8T/s/+p/7H/p/+Z/3z/af+C/6n/v/+z/7D/n/+g/6b/uv+1/6b/hv+A/2//e/98/4v/jP98/4H/i/+f/7L/t/+s/6D/kv+m/7r/uP+t/6L/of+q/8b/5P/n/9P/w//K/8v/yP+9/4//cf9g/1r/V/9g/1//R/9P/2n/m/+o/7b/s/+//9b/+f/+/wcA+f/w/+H/3v/U/9r/0f/B/7r/pv+x/9L/AgAMABUAEAATACUAQQBeAFkAKAAcACcAPwA1ADkAGQAZAAoAFwA2AE8ASgBQAFcAVgB+AJkApgClAI4AkACDAI8AigCBAFQAOAASABsAOQBBAB8AFAAgAC0AVABpAHwAdwBwAGkAcwBiAGEAcQBgADQAIwAmADMAOwApAB0AHwAkADEARgBIAEwASABeAGUAYQBmAGkAVgBPAGEAWABeAE8ARgA+AEYASwBNAEIASABIAFMAZwB4AG4AYQBbAFUAVQBlAGQAXgA1AAcAHQBJAE4ASQAmAAEA///6/xwAWABYAOv/qv/T/zAASAA2AP//3P+f/8b/EAAvAAEAh/9e/7X/BQAmABEA3v+z/6//7/8lABEA2f+F/3b/m//B/9L/q/+b/4j/hP+0/+r/CwDh/7P/u//p/xgAGwABAOX/xP/E/9D/4P/G/6X/lf+Y/7f/zv/k/9f/xf+//9r/7f/3//H/6//t/+H/6f8GABYA7//H/+L/AQD7/+j/5f/z/9z/xv/X/+T/wP+b/6f/2f/n/9f/6v8SABcA//8MABwADADl/+r/9//o/8n/z//X/9v/yv/k////+v/u//j/FAANAAEAAgAQAAAA1P/U//n/AADo/+7/CQALAPv/FQA5AEQANAAqACUAKAAnABkAHgAaAO7/2//x/w8AHwARAAwAIQA0ADkASQA8ACEA+v8PACkALAANAPj/8v8NAA0AGgD1/9n/3f/1/wsAAQDq/+r/6v/z/xEAKQAXAPn/AwAxAD0ALwAmADoAEwD8/wYAJwALAOr/4P8GAAQA8P/8/yoAFwDu/wAAPQBEACAAFwA7ACgA9P8JADcAHgDc/9D/+/8LAP//DgAvAB4AAQAKAFwAWgAMAP3/OQBAABoAGgBGAEcAFAAHACkAJADo/+f/JAA4APj/4P8KAD0AMAANAP3/IAApABkAJQBRAFUAGAAAADMAVQAqAO//9/8dAAIA0P/U/ycAUQD7/8r/FABEABIA7f8aADQA6v+///z/OQAOAL3/xP/t//r/1f/O/97/2P+q/63/9/8KAMD/k/+//+T/0/+8/9b/3//Q/8j/2v/w//f/1f+7/9D/4v/a/7v/rv+v/9D/6v/6/9T/xf/O/+//CQAmAAwA1f/B/+r/BgAaAPH/yv+z/9v/+f8SAPb/0f+7/+P/BwAHAPn/7v/S/+r/JwBYADEA/f8VADkAKwAtADUAIwDo/9T/8/8FAOX/tP/B/9P/yP/Q//7/BgDi/8f/7P8tAEMABQDg/+j/4//m////BwDK/5n/kP/E/wIAFQD6/9D/3P8KAC8APgA0AAUA2P/P/wYAKQAQAMf/p//V/xwAKAAnABkA9v/l/xUAVgBRACMA7/8MAFAAZgA8ABoACwDr/+H/8/8EAPP/uf+T/+v/QQAGALX/yv////X/9P8OAB4A8P+q/8v/RwBxAP7/yP8MAC8A//8PAE8AGAC//8z/JAAlAAUA7f/z/+r/5P8BAEYARgD0/+T/PwBhAC0AMwBdAD0A6P/8/0wAYgAsAA0ADgAmAAwA+v8hAFYAHADI//P/cABiACQANwBfACcACgBFAIwAYgDz/8X/DgBOAA8AyP/m//X/uv+9/zgAPQC+/6D/DwBJABwA9/8aAEIAMQAaAFkAfgAhAM3/DQBIAAwAsP/h/yUA8v+5//z/VgBEAPD/AAA9AD0AAQATAFAAFACR/53/EwAXALP/lv/N/+L/xv/q/0YAMgC1/5X/9P8xAPf/t//F/83/n/+P/wIANwDe/5n/0/8PACAABQAEAP7/1P+p//X/RQAVAKv/vf/8//H/3v8FABoA2f+x/+D/KAAfAP7/AQAPAP//8P8dAEIAHADV/+X/HgALANX/3v8AAOX/s//W/xwABQC3/9T/MQAoAOT/3//4/+T/yP/R/+b/zv+o/5b/1P8PAAYA5f/r//P/9f8hADAACgDU/8n/3//4//X/7f/Z/67/uf8EADYACADi/+r/FwApACYAKQAcAOn/vP/q/z0AJgDU/8f/7v/t/+v/GwAhAOf/wv/e/xcALwAPAPP/8P/0//L/FAAqAA0A0//W/yEASQAZAPr/DQABAPn/GQA/ABcAxv/L/yQARAAXAPv/9f/s//r/KABXAEQA+v/a/x4AQQAaAOv/8v/w/+T/4f8XADkACQDj/yQAYABIADcAOgBCADAAMQAyADQAFwACABYAOgAvABMAGgA0AD4AOgBPADoAGAAYACwAKgApABoACgAHABQAHwBCAEgAGAAOADMAOQAcAAoAGQAPAPP/5v/+/wcA9f/v/xAAEwACAAUAKwApAAUAEwAiAAkABAATABQA+P/g/+v/HwAvAAAAAQBBAEAAGAA1AF8ALQD2/w0AOQAYAPL/AAAMAOz/2//f////9P/N/9n/HAASAPH/GgBTACoA/f8gAEoAIwABAAgACQDj/7D/uv/k/8//oP+q/9f/1f+8/9//CAD9/9r/6//8//H/5//y/9z/xP+z/7r/1//i/7//r//I/9n/4/8BAAQA3f/h/wsALwAmABMADwAfABEA//8YACkAAwDH/9D/+f/2/8X/w//p/+f/t//E/wEAFgDi/9X/+P/+/+b/+f8sABIA6/8AACMAKQAhAAUAEwAWAP//9P8VABYA7v/U/+v/AQDv/+f/8//2/+r/7//8/w0ADgAHAP7/EgAcACcAJgAgABYAFQAdABUAEQANAPr/7P/3//T/9P/l/9j/6P////P/5/8CAA4ABwAIABwAEgADAPj/DAAWAA4A9f8FAAgA//8EABwAJwDy/+3/BwAXAAgABQD7//7/5P/g/xoAPQADANX/BAAfABIADwAkABgAAgDy/wgAHgAVAAAA+//r////CgAPABIAAQD9/w8AAgDd//7/HQD9/+D/CQAaABgAFwAqAEEAQAAVABIAQgA8ABQA/f8GAPv/6//0/xAABgDl/+b/AQAYABgAFgAQAAYABAAGABsAKgAXAAkAEwAjABgAHAAmABoA8v/r//b/AwD5/+j/6f/t//j/+/8UACsAIgALABoANAAzACEAFAAEAPT/9f/3//b/9v/6/+3/9/8LABAAEgAbABwAHAAcABcAJAAnAB4AGAAUABIAFAAbABAAAAD+/wAA9f////z/9v/o/+b/6//+/woAAgD7/wsAEgAEAAcACQAGAPb/6P/o/+//5//b/9n/1//S/8r/yP/Q/9P/0P/H/9P/3//l/9//3v/o/+f/6f/v//H/+//2/9v/4v/0//L/3P/e/9//4v/Z/9L/3f/f/9P/0v/j/+n/3P/W/+L/6P/c/93/6f/r/+b/7//t/+3/7v/w//b/+P/4//X/9P/8//r/+P////7/8//4/wIA/v/1//X/8P/k/9//2v/a/9D/zP/R/9r/4P/f/+z/7//0//r/CQABAPv/AgADAAcABgD7//n/+P/4//T/8f/w/+P/3v/u/+v/5P/q/+j/6P/w//X//P/+//3/AwATAB0AFwAXABoAGgAOAAYA///9////AAD8//n///8AAAUABwAJAAQABQAAAAMABgAHAA4ACAAGAAoADwALAA4AEgAMAAwADwAXABkAFgASAAkAEQAWAA4ABQAIAAQAAgAIABMAEAANABgAIAAhAB4AFwAbACMAIQAbABkAIAAZAB0AHwAaABYAGgAgACMAIQAbACEAIwAXACEAIwAWABgAIAAiACUAIwAeACUAJwAeABcAHAAeABMADwASABQAEgANABIAEQASABIAEAAMAAsAEAAZABwAFAAYAB8AHwAdABkAFQAMAAoABQAGAAIA+P/v//f/AgD7////AgAKABAADAAOAA8ACwAOABAAEgAPAAIABQAHAAMA+//7//b/8P/x/+//6v/n/+D/3v/f/97/3f/h/+T/5P/r/+7/7f/u/+v/7v/u/+T/5P/m/+b/4v/m/+7/7//w//P/9v/3/////v8AAAIAAAD9//z/8v/u/+7/9P/t/+b/5P/o/+//7v/0//X/7v/2/wAAAgACAAYAAwAKAAkACgAAAPz/9v/0//H/7f/q/+f/5f/m/+r/7f/o/+r/8v/x//T/8f/3//z//P/9//v//v/+//z/+//8/wAAAwAEAAYA/////wUAAgAAAPz/9v/5//j/+/8AAAUABwACAAkABAAJAA4ADwALAAgACAAHAAYABQAFAAMAAQADAAYADgAIAP////////7//P8DAAYAAQACAP3/BQAEAPX/AQAGAPr//v////v/+//5//3//P8DAAQABgAEAAgACQANAA8ADgAOAA0ABwAHAAQABQAOAA4AEQAZABoAHwAdACQALQAqACYAKwAuACQAJQAkACIAIwAiAB8AGwAWABAAFQAbAA8AEAAQAA0ADwASABYAFQATAA4AEgATABEADgAPABcAEAAQAA0ACwAIAAMA//8BAAQABAAFAAcACgAIAAoADwAJAAsACQAMAAoACgAIAAgABwAIAAoACgAPAAoADwASABEAEwAOAAsADQANAAsADQAIAA8ACgAFAAkACwANAAwADAAUABUAFwAXABYAFAAKAAgABQAEAP3//P/4//3////6//r//f/5//P/8P/0//T/9f/5//b/9//1//b//v/7/wAAAAD+/wEAAgADAP7/+f/4//b/8v/u/+v/6f/s//P/+f/2//j/+P/4//j/9//0//f/9P/x//L/8v/w/+3/8P/w//L/7P/y//L/8f/x/+//7P/u//D/9v/8//v/+/8AAP///v/+/wIAAgAFAAQABgADAAMAAAAEAAcACAALAA8ADwAKAAUADQADAAQABAAFAAgACAAFAAgACQD//wgAEQAIAAgAAwACAAIABQAEAAQAAgAAAAQAAQD///3/BwAKAAYAAwABAP//+P/5//r/9//5//v//v/+//7///8EAAoABgAEAAIA/v////v//v8AAAEABgAPABEAEgARAA4ADwAPAA0AEAANAAwADwALABAADwALAAwACgALAAcACAAQAA4AEwAZABwAHAAYABcAGwAbAB0AIAAeACQAHgAjACUAJQAhACQAJAAfACEAHQAdABwAHAAZABkAEwANAA4AFQAPAA4AEAAPABMAFAATAA8ACQALAAYABQAEAP3/AwAHAAUABQAIAAoACgAMAAwADAANAAgACQAGAAIAAAADAA8ACgAKAAgACQAJAAgACgALAA4ACgAQABAACwAEAAkACAAIAAQADAAGAAgACwAHAAMABAACAAIA/v////z/+f8AAPn/+f/1//b/9P/2//f/8//0//f/8//z//L/7v/z/+v/5v/k/+X/4v/i/+j/6v/r/+7/7f/z//P/9f/0//b/9//z//D/8P/x/+7/6//r/+n/6f/q/+7/8P/5//f/+f/8//z//v/8//3//P/4//H/9P/0/+z/6//p/+X/5f/s//X/9v/w//T/9v/2//f/+P/5//v/9//0//X/9v/z//X/9v/z//X/8v/0/+3/7v/y//X/8P/v//L/8v/4//X/+f/7//j/+P/6/wEA/v8BAP//AQD+/wAA/v8BAAAA+v/9/wAA/v/9/wAAAAACAAMAAgADAAAABgAIAAkACgAEAAcACAAJAAgACwAKAAcACwAHAA4ADgALAAoACQAEAPv/+/8DAPj/+f/4//b///8CAAMACAAJAAgABgAIAAgABgALAAYACAAFAAkABgAGAAUABQAHAAYACgAHAAgACgAIABAAFwAWABYAFQATABcAGgAfAB4AHQAdAB8AGwAbABYAGgAfAB4AGgAaABwAGAAXABYAFAAWABkAGQAaABsAFwAbACEAHwAgACAAIwAdAB0AGgAUABQAEwAUABIAEwARABAAGgAWABcAGAAYABkAGwAUABkAGQAUABQAEAAUAA0ADgASAAgABgACAAUAAgADAAIA//8CAP7/AgAEAAoABwAPABMAEwANAAwACAAEAAoABQABAPn/9f/y/+3/6//p/+r/9f/s//D/8P/x//T/8f/2/+z/8v/x/+//9v/x/+7/8P/3//n/+f/y//H/7f/x/+3/7//r/+n/5f/o/+j/6P/v//L/8//y//X//P/5//7/+/////z///8DAAAA///6//f/9P/v/+7/6v/p/+v/7f/v//H/7//y//P/9P/3//f/+/////7/+//7//r//v/7//7//P/+//n/+P/2//X/8//x//j//f/3//b/9P/2//f/+P/5//f//f8BAPr//v8BAAAABgAAAAMAAQAHAAYA/v/+//v//f/2//X/9P/v//H/8P/7//r//P/9/wAA//8CAP//AwABAAQAAwACAAcAAgAHAAsACgAKAA0ADQAGAAQA/f///wAAAgAEAAEABQACAAUAEQAOABMAEwAWABQAEgAXABcAEwATABYAFwAYABYAGAAiAB0AGwAfAB4AHAAcABwAHQAZABkAGwAdABsAGwAfACYAIgAhACUAJAAnACkAKAAkACIAHwAZABYAGQAPABYAFwAQAA8ADgAKAA8ACwAMAAoACwANABEAEQARAA8AEAAUAAwABwAHAAcABQAFAAUABQADAAYABwADAAoAAQAGAAwACAAHAAYABQAHAAYABQAIAAcADwAQAA8AEgANABUAGAARAA4ABgAEAAQAAQAAAAQAAQAEAAUACQAIAAMABwAPAAUAAgAEAP7/+//8//7///8BAPz/AAD7//n/8//3//v/7v/t/+z/7f/o/+n/5//q/+r/7P/p/+z/6//n/+v/7f/t/+v/7v/u/+7/8v/3//r/+v/1//f/8v/y//P/7//2//H/8v/x//H/8f/v//P/7f/w//L/7//w/+3/6f/s/+3/8v/s//D/6//t/+z/7P/w//L/+P/1//T/8P/s/+j/6v/j/+L/4f/j/+X/5f/r/+v/7v/t/+7/6//t/+7/6//x/+//8v/y//b/9f/1//b/+f/7//j/9//6//j/8v/x//H/8f/x//P/9v/z//b/+f/8//v/+P/6//z//v/5//n/+v/5//j/+f/4//3//f/9//7////9//3/AAD///3///8CAAEABAACAAEAAgD8//3/+v/3//v/AAACAAUAAQALAAwAEAANAAoACgAMAAoACwAMAAoACAAIAAkACQAGAAUAEAAJAAgABgAFAAQABQAFAAcACQAKAA0AEQAPAAwAFQAvADMAJgAlAA4AEgD6/xEAAQASAAYADQAKABAAFwAZABIAFgAQAA8AEQALAA4ACwALABAADAAOAAgAEgAKABMAGgAVABMAEgAVABAADgALAAkADgAMABQAEAANAAkADAARAAwABwAAAAAAAwAGAAYADgAPABAAEgAQAA0ACAAMAA4ABwABAP3/+P/5//X/+v/3//b/8v/0//L/8v/q//D/8//w//L/8P/v/+//7//z//b/9f/3//f/+P/1//L/8P/v/+v/7f/s/+7/7P/s/+n/6P/n/+X/6v/m/+n/4f/o/+P/6//u//X/8v/z//P/9f/4/////P8AAPz/AgD0//f/9v/0//f/+f/5//b/9v/1//P/8f/0//T/+P/7//f//f/8//r//v8BAAIABgAEAAQA//8AAP3//P/8//j/9//3//r/+v/4//X/9f/1//X/8//x/+3/7P/s//H/8f/v//j/+P/1//j/+P/3//z/+P8AAP////8AAPv/+f/6//j/+P/7//j/+P/2//j/+//5//b/+P/2//P/9f/2//f/+v////z/+v/3//r/+v/5//n//f/7//f//v///wIAAwABAAIABAAHAAgACQAKAA8AEQATABMAEwAQAAwADAAKAAgACAAQAAsACAAIAAgACwATAA8AEgAVABQAFAAUABUAEgAYAB4AGQAYABUAEwASABMAEwARABAAEQAQABMADQAJAAcACgAHAAYACgALAA0ADAAPAA0ADwAQAA8ADgALAAcADgAYABEADgAOAA4ADQAKAAsADAAMAAkADAAMAA4ACAAQABUAEAAPABAAEQAQABAADwAQABEADQALAA4ACwAFAAYACQAFAAUABgAPAAoACgAEAAcAAgAGAAAA+f/6//H/+P////v//P/8//v/9//5//j/9v/5//P//P/s//X/5P/1/+f/7//l//H/5f/r/+b/6//l/+T/6f/h/+H/4P/Z/9v/3v/c/97/3f/Z/+H/5v/i/+H/4P/k/+f/7f/o/+j/5//z/+z/7P/p/+b/7f/v/+7/8P/u/+z/8f/v/+7/7P/v/+3/7f/l/+P/4//m/+b/6P/m/+f/5P/r/+r/7v/s/+v/7v/u//X/8P/3//j/9P/6//n/+P/5//v//P/9//r/+P/8//b/9P/x//T/7//0//r/9//9//v//f8AAPz/+v/7//7//P/7//3//P8BAP7/AQD6//3/+f/7//v//v///wcABAABAAEA/v8CAAMAAAD///n/+v/3//j/+f/5//P/9P/7//D/9P/0//n//P8CAAMABgAHAAoACQALAAYACAAKAA0ADQAMAAcADgAMAA4ADQAPAA4AEQAPAA4AFAAOABAAGAATABEAFAATABoAFQAbABsAHQAhAB0AIQAfABsAHAAgAB4AGwAlACEAJQAjACMAIgAaABoAFgAVABYAEgAaAB4AHQAXABkAGQAZABkAGwAZABsAGgAaACMAIgAcACQAJQAdACEAHAAeABkAFQAbABMAHAASABIADwARABQADgAeABcAFAAZABgAHAAXABsAHAAXABUAEwAYABUADQAUABcAFAASAAgABAAEAAMABgD//wMAAgABAAkABQAAAAYACgAFAAQAAQD8////+//5//n/+P/z//f/9v/3//D/9P////b/+f/2/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" 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<h2 id="STEP-1:-Acoustic-Features-for-Speech-Recognition">STEP 1: Acoustic Features for Speech Recognition<a class="anchor-link" href="#STEP-1:-Acoustic-Features-for-Speech-Recognition">&#182;</a></h2><p>For this project, you won't use the raw audio waveform as input to your model.  Instead, we provide code that first performs a pre-processing step to convert the raw audio to a feature representation that has historically proven successful for ASR models.  Your acoustic model will accept the feature representation as input.</p>
<p>In this project, you will explore two possible feature representations.  <em>After completing the project</em>, if you'd like to read more about deep learning architectures that can accept raw audio input, you are encouraged to explore this <a href="https://pdfs.semanticscholar.org/a566/cd4a8623d661a4931814d9dffc72ecbf63c4.pdf">research paper</a>.</p>
<h3 id="Spectrograms">Spectrograms<a class="anchor-link" href="#Spectrograms">&#182;</a></h3><p>The first option for an audio feature representation is the <a href="https://www.youtube.com/watch?v=_FatxGN3vAM">spectrogram</a>.  In order to complete this project, you will <strong>not</strong> need to dig deeply into the details of how a spectrogram is calculated; but, if you are curious, the code for calculating the spectrogram was borrowed from <a href="https://github.com/baidu-research/ba-dls-deepspeech">this repository</a>.  The implementation appears in the <code>utils.py</code> file in your repository.</p>
<p>The code that we give you returns the spectrogram as a 2D tensor, where the first (<em>vertical</em>) dimension indexes time, and the second (<em>horizontal</em>) dimension indexes frequency.  To speed the convergence of your algorithm, we have also normalized the spectrogram.  (You can see this quickly in the visualization below by noting that the mean value hovers around zero, and most entries in the tensor assume values close to zero.)</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">plot_spectrogram_feature</span>

<span class="c1"># plot normalized spectrogram</span>
<span class="n">plot_spectrogram_feature</span><span class="p">(</span><span class="n">vis_spectrogram_feature</span><span class="p">)</span>
<span class="c1"># print shape of spectrogram</span>
<span class="n">display</span><span class="p">(</span><span class="n">Markdown</span><span class="p">(</span><span class="s1">&#39;**Shape of Spectrogram** : &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">vis_spectrogram_feature</span><span class="o">.</span><span class="n">shape</span><span class="p">)))</span>
</pre></div>

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


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<img 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>
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<p><strong>Shape of Spectrogram</strong> : (584, 161)</p>

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<h3 id="Mel-Frequency-Cepstral-Coefficients-(MFCCs)">Mel-Frequency Cepstral Coefficients (MFCCs)<a class="anchor-link" href="#Mel-Frequency-Cepstral-Coefficients-(MFCCs)">&#182;</a></h3><p>The second option for an audio feature representation is <a href="https://en.wikipedia.org/wiki/Mel-frequency_cepstrum">MFCCs</a>.  You do <strong>not</strong> need to dig deeply into the details of how MFCCs are calculated, but if you would like more information, you are welcome to peruse the <a href="https://github.com/jameslyons/python_speech_features">documentation</a> of the <code>python_speech_features</code> Python package.  Just as with the spectrogram features, the MFCCs are normalized in the supplied code.</p>
<p>The main idea behind MFCC features is the same as spectrogram features: at each time window, the MFCC feature yields a feature vector that characterizes the sound within the window.  Note that the MFCC feature is much lower-dimensional than the spectrogram feature, which could help an acoustic model to avoid overfitting to the training dataset.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">plot_mfcc_feature</span>

<span class="c1"># plot normalized MFCC</span>
<span class="n">plot_mfcc_feature</span><span class="p">(</span><span class="n">vis_mfcc_feature</span><span class="p">)</span>
<span class="c1"># print shape of MFCC</span>
<span class="n">display</span><span class="p">(</span><span class="n">Markdown</span><span class="p">(</span><span class="s1">&#39;**Shape of MFCC** : &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">vis_mfcc_feature</span><span class="o">.</span><span class="n">shape</span><span class="p">)))</span>
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<p><strong>Shape of MFCC</strong> : (584, 13)</p>

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<p>When you construct your pipeline, you will be able to choose to use either spectrogram or MFCC features.  If you would like to see different implementations that make use of MFCCs and/or spectrograms, please check out the links below:</p>
<ul>
<li>This <a href="https://github.com/baidu-research/ba-dls-deepspeech">repository</a> uses spectrograms.</li>
<li>This <a href="https://github.com/mozilla/DeepSpeech">repository</a> uses MFCCs.</li>
<li>This <a href="https://github.com/buriburisuri/speech-to-text-wavenet">repository</a> also uses MFCCs.</li>
<li>This <a href="https://github.com/pannous/tensorflow-speech-recognition/blob/master/speech_data.py">repository</a> experiments with raw audio, spectrograms, and MFCCs as features.</li>
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<p><a id='step2'></a></p>
<h2 id="STEP-2:-Deep-Neural-Networks-for-Acoustic-Modeling">STEP 2: Deep Neural Networks for Acoustic Modeling<a class="anchor-link" href="#STEP-2:-Deep-Neural-Networks-for-Acoustic-Modeling">&#182;</a></h2><p>In this section, you will experiment with various neural network architectures for acoustic modeling.</p>
<p>You will begin by training five relatively simple architectures.  <strong>Model 0</strong> is provided for you.  You will write code to implement <strong>Models 1</strong>, <strong>2</strong>, <strong>3</strong>, and <strong>4</strong>.  If you would like to experiment further, you are welcome to create and train more models under the <strong>Models 5+</strong> heading.</p>
<p>All models will be specified in the <code>sample_models.py</code> file.  After importing the <code>sample_models</code> module, you will train your architectures in the notebook.</p>
<p>After experimenting with the five simple architectures, you will have the opportunity to compare their performance.  Based on your findings, you will construct a deeper architecture that is designed to outperform all of the shallow models.</p>
<p>For your convenience, we have designed the notebook so that each model can be specified and trained on separate occasions.  That is, say you decide to take a break from the notebook after training <strong>Model 1</strong>.  Then, you need not re-execute all prior code cells in the notebook before training <strong>Model 2</strong>.  You need only re-execute the code cell below, that is marked with <strong><code>RUN THIS CODE CELL IF YOU ARE RESUMING THE NOTEBOOK AFTER A BREAK</code></strong>, before transitioning to the code cells corresponding to <strong>Model 2</strong>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#####################################################################</span>
<span class="c1"># RUN THIS CODE CELL IF YOU ARE RESUMING THE NOTEBOOK AFTER A BREAK #</span>
<span class="c1">#####################################################################</span>

<span class="c1"># allocate 50% of GPU memory (if you like, feel free to change this)</span>
<span class="kn">from</span> <span class="nn">keras.backend.tensorflow_backend</span> <span class="k">import</span> <span class="n">set_session</span>
<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span> 
<span class="n">config</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">ConfigProto</span><span class="p">()</span>
<span class="n">config</span><span class="o">.</span><span class="n">gpu_options</span><span class="o">.</span><span class="n">per_process_gpu_memory_fraction</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="n">set_session</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">(</span><span class="n">config</span><span class="o">=</span><span class="n">config</span><span class="p">))</span>

<span class="c1"># watch for any changes in the sample_models module, and reload it automatically</span>
<span class="o">%</span><span class="k">load_ext</span> autoreload
<span class="o">%</span><span class="k">autoreload</span> 2
<span class="c1"># import NN architectures for speech recognition</span>
<span class="kn">from</span> <span class="nn">sample_models</span> <span class="k">import</span> <span class="o">*</span>
<span class="c1"># import function for training acoustic model</span>
<span class="kn">from</span> <span class="nn">train_utils</span> <span class="k">import</span> <span class="n">train_model</span>
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<pre>C:\Anaconda3\lib\site-packages\h5py\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
Using TensorFlow backend.
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<p><a id='model0'></a></p>
<h3 id="Model-0:-RNN">Model 0: RNN<a class="anchor-link" href="#Model-0:-RNN">&#182;</a></h3><p>Given their effectiveness in modeling sequential data, the first acoustic model you will use is an RNN.  As shown in the figure below, the RNN we supply to you will take the time sequence of audio features as input.</p>
<p><img src="images/simple_rnn.png" width="50%"></p>
<p>At each time step, the speaker pronounces one of 28 possible characters, including each of the 26 letters in the English alphabet, along with a space character (" "), and an apostrophe (').</p>
<p>The output of the RNN at each time step is a vector of probabilities with 29 entries, where the $i$-th entry encodes the probability that the $i$-th character is spoken in the time sequence.  (The extra 29th character is an empty "character" used to pad training examples within batches containing uneven lengths.)  If you would like to peek under the hood at how characters are mapped to indices in the probability vector, look at the <code>char_map.py</code> file in the repository.  The figure below shows an equivalent, rolled depiction of the RNN that shows the output layer in greater detail.</p>
<p><img src="images/simple_rnn_unrolled.png" width="60%"></p>
<p>The model has already been specified for you in Keras.  To import it, you need only run the code cell below.</p>

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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
rnn (GRU)                    (None, None, 29)          16617     
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 16,617
Trainable params: 16,617
Non-trainable params: 0
_________________________________________________________________
None
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<p>As explored in the lesson, you will train the acoustic model with the <a href="http://www.cs.toronto.edu/~graves/icml_2006.pdf">CTC loss</a> criterion.  Custom loss functions take a bit of hacking in Keras, and so we have implemented the CTC loss function for you, so that you can focus on trying out as many deep learning architectures as possible :).  If you'd like to peek at the implementation details, look at the <code>add_ctc_loss</code> function within the <code>train_utils.py</code> file in the repository.</p>
<p>To train your architecture, you will use the <code>train_model</code> function within the <code>train_utils</code> module; it has already been imported in one of the above code cells.  The <code>train_model</code> function takes three <strong>required</strong> arguments:</p>
<ul>
<li><code>input_to_softmax</code> - a Keras model instance.</li>
<li><code>pickle_path</code> - the name of the pickle file where the loss history will be saved.</li>
<li><code>save_model_path</code> - the name of the HDF5 file where the model will be saved.</li>
</ul>
<p>If we have already supplied values for <code>input_to_softmax</code>, <code>pickle_path</code>, and <code>save_model_path</code>, please <strong>DO NOT</strong> modify these values.</p>
<p>There are several <strong>optional</strong> arguments that allow you to have more control over the training process.  You are welcome to, but not required to, supply your own values for these arguments.</p>
<ul>
<li><code>minibatch_size</code> - the size of the minibatches that are generated while training the model (default: <code>20</code>).</li>
<li><code>spectrogram</code> - Boolean value dictating whether spectrogram (<code>True</code>) or MFCC (<code>False</code>) features are used for training (default: <code>True</code>).</li>
<li><code>mfcc_dim</code> - the size of the feature dimension to use when generating MFCC features (default: <code>13</code>).</li>
<li><code>optimizer</code> - the Keras optimizer used to train the model (default: <code>SGD(lr=0.02, decay=1e-6, momentum=0.9, nesterov=True, clipnorm=5)</code>).  </li>
<li><code>epochs</code> - the number of epochs to use to train the model (default: <code>20</code>).  If you choose to modify this parameter, make sure that it is <em>at least</em> 20.</li>
<li><code>verbose</code> - controls the verbosity of the training output in the <code>model.fit_generator</code> method (default: <code>1</code>).</li>
<li><code>sort_by_duration</code> - Boolean value dictating whether the training and validation sets are sorted by (increasing) duration before the start of the first epoch (default: <code>False</code>).</li>
</ul>
<p>The <code>train_model</code> function defaults to using spectrogram features; if you choose to use these features, note that the acoustic model in <code>simple_rnn_model</code> should have <code>input_dim=161</code>.  Otherwise, if you choose to use MFCC features, the acoustic model should have <code>input_dim=13</code>.</p>
<p>We have chosen to use <code>GRU</code> units in the supplied RNN.  If you would like to experiment with <code>LSTM</code> or <code>SimpleRNN</code> cells, feel free to do so here.  If you change the <code>GRU</code> units to <code>SimpleRNN</code> cells in <code>simple_rnn_model</code>, you may notice that the loss quickly becomes undefined (<code>nan</code>) - you are strongly encouraged to check this for yourself!  This is due to the <a href="http://www.wildml.com/2015/10/recurrent-neural-networks-tutorial-part-3-backpropagation-through-time-and-vanishing-gradients/">exploding gradients problem</a>.  We have already implemented <a href="https://arxiv.org/pdf/1211.5063.pdf">gradient clipping</a> in your optimizer to help you avoid this issue.</p>
<p><strong>IMPORTANT NOTE:</strong> If you notice that your gradient has exploded in any of the models below, feel free to explore more with gradient clipping (the <code>clipnorm</code> argument in your optimizer) or swap out any <code>SimpleRNN</code> cells for <code>LSTM</code> or <code>GRU</code> cells.  You can also try restarting the kernel to restart the training process.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_0</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_0.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_0.h5&#39;</span><span class="p">,</span>
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
101/101 [==============================] - 138s 1s/step - loss: 881.7945 - val_loss: 764.8204
Epoch 2/20
101/101 [==============================] - 138s 1s/step - loss: 784.7477 - val_loss: 759.3296
Epoch 3/20
101/101 [==============================] - 139s 1s/step - loss: 779.6679 - val_loss: 757.5473
Epoch 4/20
101/101 [==============================] - 140s 1s/step - loss: 779.6899 - val_loss: 757.6076
Epoch 5/20
101/101 [==============================] - 142s 1s/step - loss: 779.5561 - val_loss: 757.2116
Epoch 6/20
101/101 [==============================] - 136s 1s/step - loss: 779.3052 - val_loss: 757.6368
Epoch 7/20
101/101 [==============================] - 138s 1s/step - loss: 779.2572 - val_loss: 756.9291
Epoch 8/20
101/101 [==============================] - 134s 1s/step - loss: 779.2802 - val_loss: 757.2749
Epoch 9/20
101/101 [==============================] - 135s 1s/step - loss: 778.8091 - val_loss: 757.7857
Epoch 10/20
101/101 [==============================] - 134s 1s/step - loss: 779.0159 - val_loss: 757.4328
Epoch 11/20
101/101 [==============================] - 138s 1s/step - loss: 779.3366 - val_loss: 757.3067
Epoch 12/20
101/101 [==============================] - 137s 1s/step - loss: 778.9145 - val_loss: 757.3958
Epoch 13/20
101/101 [==============================] - 136s 1s/step - loss: 779.2400 - val_loss: 758.3892
Epoch 14/20
101/101 [==============================] - 138s 1s/step - loss: 779.2769 - val_loss: 757.7726
Epoch 15/20
101/101 [==============================] - 138s 1s/step - loss: 779.1268 - val_loss: 757.7480
Epoch 16/20
101/101 [==============================] - 133s 1s/step - loss: 778.7611 - val_loss: 758.2979
Epoch 17/20
101/101 [==============================] - 133s 1s/step - loss: 778.7364 - val_loss: 756.6821
Epoch 18/20
101/101 [==============================] - 139s 1s/step - loss: 779.0858 - val_loss: 757.0015
Epoch 19/20
101/101 [==============================] - 141s 1s/step - loss: 779.0283 - val_loss: 757.0965
Epoch 20/20
101/101 [==============================] - 138s 1s/step - loss: 779.4709 - val_loss: 757.5939
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<p><a id='model1'></a></p>
<h3 id="(IMPLEMENTATION)-Model-1:-RNN-+-TimeDistributed-Dense">(IMPLEMENTATION) Model 1: RNN + TimeDistributed Dense<a class="anchor-link" href="#(IMPLEMENTATION)-Model-1:-RNN-+-TimeDistributed-Dense">&#182;</a></h3><p>Read about the <a href="https://keras.io/layers/wrappers/">TimeDistributed</a> wrapper and the <a href="https://keras.io/layers/normalization/">BatchNormalization</a> layer in the Keras documentation.  For your next architecture, you will add <a href="https://arxiv.org/pdf/1510.01378.pdf">batch normalization</a> to the recurrent layer to reduce training times.  The <code>TimeDistributed</code> layer will be used to find more complex patterns in the dataset.  The unrolled snapshot of the architecture is depicted below.</p>
<p><img src="images/rnn_model.png" width="60%"></p>
<p>The next figure shows an equivalent, rolled depiction of the RNN that shows the (<code>TimeDistrbuted</code>) dense and output layers in greater detail.</p>
<p><img src="images/rnn_model_unrolled.png" width="60%"></p>
<p>Use your research to complete the <code>rnn_model</code> function within the <code>sample_models.py</code> file.  The function should specify an architecture that satisfies the following requirements:</p>
<ul>
<li>The first layer of the neural network should be an RNN (<code>SimpleRNN</code>, <code>LSTM</code>, or <code>GRU</code>) that takes the time sequence of audio features as input.  We have added <code>GRU</code> units for you, but feel free to change <code>GRU</code> to <code>SimpleRNN</code> or <code>LSTM</code>, if you like!</li>
<li>Whereas the architecture in <code>simple_rnn_model</code> treated the RNN output as the final layer of the model, you will use the output of your RNN as a hidden layer.  Use <code>TimeDistributed</code> to apply a <code>Dense</code> layer to each of the time steps in the RNN output.  Ensure that each <code>Dense</code> layer has <code>output_dim</code> units.</li>
</ul>
<p>Use the code cell below to load your model into the <code>model_1</code> variable.  Use a value for <code>input_dim</code> that matches your chosen audio features, and feel free to change the values for <code>units</code> and <code>activation</code> to tweak the behavior of your recurrent layer.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_1</span> <span class="o">=</span> <span class="n">rnn_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                    <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">)</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
rnn (CuDNNGRU)               (None, None, 200)         217800    
_________________________________________________________________
batch_normalization_2 (Batch (None, None, 200)         800       
_________________________________________________________________
time_distributed_2 (TimeDist (None, None, 29)          5829      
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 224,429
Trainable params: 224,029
Non-trainable params: 400
_________________________________________________________________
None
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_1.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_1.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_1</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_1.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_1.h5&#39;</span><span class="p">,</span>
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
101/101 [==============================] - 40s 391ms/step - loss: 363.7264 - val_loss: 268.6951
Epoch 2/20
101/101 [==============================] - 36s 358ms/step - loss: 252.5056 - val_loss: 218.8018
Epoch 3/20
101/101 [==============================] - 37s 362ms/step - loss: 221.5043 - val_loss: 216.7974
Epoch 4/20
101/101 [==============================] - 36s 359ms/step - loss: 203.1994 - val_loss: 193.5304
Epoch 5/20
101/101 [==============================] - 37s 363ms/step - loss: 189.4311 - val_loss: 182.9306
Epoch 6/20
101/101 [==============================] - 37s 368ms/step - loss: 178.7338 - val_loss: 176.9979
Epoch 7/20
101/101 [==============================] - 37s 363ms/step - loss: 169.3131 - val_loss: 170.8548
Epoch 8/20
101/101 [==============================] - 36s 356ms/step - loss: 161.8442 - val_loss: 160.8516
Epoch 9/20
101/101 [==============================] - 37s 368ms/step - loss: 156.0493 - val_loss: 156.2942
Epoch 10/20
101/101 [==============================] - 37s 364ms/step - loss: 150.6076 - val_loss: 154.6475
Epoch 11/20
101/101 [==============================] - 37s 364ms/step - loss: 145.9454 - val_loss: 151.1147
Epoch 12/20
101/101 [==============================] - 36s 356ms/step - loss: 141.6726 - val_loss: 149.6704
Epoch 13/20
101/101 [==============================] - 37s 369ms/step - loss: 137.7126 - val_loss: 146.5323
Epoch 14/20
101/101 [==============================] - 36s 361ms/step - loss: 134.2540 - val_loss: 147.4087
Epoch 15/20
101/101 [==============================] - 38s 374ms/step - loss: 131.2588 - val_loss: 146.3616
Epoch 16/20
101/101 [==============================] - 37s 364ms/step - loss: 128.4217 - val_loss: 143.9746
Epoch 17/20
101/101 [==============================] - 36s 356ms/step - loss: 125.5123 - val_loss: 145.1795
Epoch 18/20
101/101 [==============================] - 36s 357ms/step - loss: 122.6887 - val_loss: 143.2153
Epoch 19/20
101/101 [==============================] - 36s 359ms/step - loss: 120.2055 - val_loss: 142.1612
Epoch 20/20
101/101 [==============================] - 37s 371ms/step - loss: 118.1425 - val_loss: 145.0223
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<p><a id='model2'></a></p>
<h3 id="(IMPLEMENTATION)-Model-2:-CNN-+-RNN-+-TimeDistributed-Dense">(IMPLEMENTATION) Model 2: CNN + RNN + TimeDistributed Dense<a class="anchor-link" href="#(IMPLEMENTATION)-Model-2:-CNN-+-RNN-+-TimeDistributed-Dense">&#182;</a></h3><p>The architecture in <code>cnn_rnn_model</code> adds an additional level of complexity, by introducing a <a href="https://keras.io/layers/convolutional/#conv1d">1D convolution layer</a>.</p>
<p><img src="images/cnn_rnn_model.png" width="100%"></p>
<p>This layer incorporates many arguments that can be (optionally) tuned when calling the <code>cnn_rnn_model</code> module.  We provide sample starting parameters, which you might find useful if you choose to use spectrogram audio features.</p>
<p>If you instead want to use MFCC features, these arguments will have to be tuned.  Note that the current architecture only supports values of <code>'same'</code> or <code>'valid'</code> for the <code>conv_border_mode</code> argument.</p>
<p>When tuning the parameters, be careful not to choose settings that make the convolutional layer overly small.  If the temporal length of the CNN layer is shorter than the length of the transcribed text label, your code will throw an error.</p>
<p>Before running the code cell below, you must modify the <code>cnn_rnn_model</code> function in <code>sample_models.py</code>.  Please add batch normalization to the recurrent layer, and provide the same <code>TimeDistributed</code> layer as before.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_2</span> <span class="o">=</span> <span class="n">cnn_rnn_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                        <span class="n">filters</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                        <span class="n">kernel_size</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> 
                        <span class="n">conv_stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
                        <span class="n">conv_border_mode</span><span class="o">=</span><span class="s1">&#39;valid&#39;</span><span class="p">,</span>
                        <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">)</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
conv1d (Conv1D)              (None, None, 200)         354400    
_________________________________________________________________
bn_conv_1d (BatchNormalizati (None, None, 200)         800       
_________________________________________________________________
rnn (CuDNNGRU)               (None, None, 200)         241200    
_________________________________________________________________
batch_normalization_3 (Batch (None, None, 200)         800       
_________________________________________________________________
time_distributed_3 (TimeDist (None, None, 29)          5829      
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 603,029
Trainable params: 602,229
Non-trainable params: 800
_________________________________________________________________
None
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_2.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_2.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_2</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_2.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_2.h5&#39;</span><span class="p">,</span> 
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
101/101 [==============================] - 31s 303ms/step - loss: 261.4280 - val_loss: 232.5022
Epoch 2/20
101/101 [==============================] - 27s 267ms/step - loss: 205.4853 - val_loss: 178.6748
Epoch 3/20
101/101 [==============================] - 29s 285ms/step - loss: 169.7363 - val_loss: 163.5155
Epoch 4/20
101/101 [==============================] - 30s 298ms/step - loss: 152.9896 - val_loss: 151.5381
Epoch 5/20
101/101 [==============================] - 31s 304ms/step - loss: 141.7773 - val_loss: 146.3623
Epoch 6/20
101/101 [==============================] - 28s 275ms/step - loss: 133.9184 - val_loss: 142.2189
Epoch 7/20
101/101 [==============================] - 28s 273ms/step - loss: 126.9339 - val_loss: 142.9084
Epoch 8/20
101/101 [==============================] - 29s 285ms/step - loss: 121.1896 - val_loss: 137.6124
Epoch 9/20
101/101 [==============================] - 28s 275ms/step - loss: 115.9265 - val_loss: 137.8424
Epoch 10/20
101/101 [==============================] - 27s 265ms/step - loss: 110.9594 - val_loss: 137.6336
Epoch 11/20
101/101 [==============================] - 27s 272ms/step - loss: 106.2251 - val_loss: 140.3188
Epoch 12/20
101/101 [==============================] - 29s 284ms/step - loss: 102.0149 - val_loss: 138.4180
Epoch 13/20
101/101 [==============================] - 28s 279ms/step - loss: 97.4520 - val_loss: 140.0433
Epoch 14/20
101/101 [==============================] - 27s 272ms/step - loss: 93.3885 - val_loss: 143.2403
Epoch 15/20
101/101 [==============================] - 28s 276ms/step - loss: 88.9219 - val_loss: 145.9923
Epoch 16/20
101/101 [==============================] - 28s 273ms/step - loss: 84.9552 - val_loss: 146.0248
Epoch 17/20
101/101 [==============================] - 28s 275ms/step - loss: 80.9123 - val_loss: 150.6582
Epoch 18/20
101/101 [==============================] - 29s 285ms/step - loss: 76.7405 - val_loss: 153.2414
Epoch 19/20
101/101 [==============================] - 30s 301ms/step - loss: 73.0058 - val_loss: 156.1222
Epoch 20/20
101/101 [==============================] - 29s 286ms/step - loss: 68.9633 - val_loss: 161.8327
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<p><a id='model3'></a></p>
<h3 id="(IMPLEMENTATION)-Model-3:-Deeper-RNN-+-TimeDistributed-Dense">(IMPLEMENTATION) Model 3: Deeper RNN + TimeDistributed Dense<a class="anchor-link" href="#(IMPLEMENTATION)-Model-3:-Deeper-RNN-+-TimeDistributed-Dense">&#182;</a></h3><p>Review the code in <code>rnn_model</code>, which makes use of a single recurrent layer.  Now, specify an architecture in <code>deep_rnn_model</code> that utilizes a variable number <code>recur_layers</code> of recurrent layers.  The figure below shows the architecture that should be returned if <code>recur_layers=2</code>.  In the figure, the output sequence of the first recurrent layer is used as input for the next recurrent layer.</p>
<p><img src="images/deep_rnn_model.png" width="80%"></p>
<p>Feel free to change the supplied values of <code>units</code> to whatever you think performs best.  You can change the value of <code>recur_layers</code>, as long as your final value is greater than 1. (As a quick check that you have implemented the additional functionality in <code>deep_rnn_model</code> correctly, make sure that the architecture that you specify here is identical to <code>rnn_model</code> if <code>recur_layers=1</code>.)</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_3</span> <span class="o">=</span> <span class="n">deep_rnn_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                         <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                         <span class="n">recur_layers</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> 
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
cu_dnngru_2 (CuDNNGRU)       (None, None, 200)         217800    
_________________________________________________________________
batch_normalization_5 (Batch (None, None, 200)         800       
_________________________________________________________________
cu_dnngru_3 (CuDNNGRU)       (None, None, 200)         241200    
_________________________________________________________________
batch_normalization_6 (Batch (None, None, 200)         800       
_________________________________________________________________
time_distributed_4 (TimeDist (None, None, 29)          5829      
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 466,429
Trainable params: 465,629
Non-trainable params: 800
_________________________________________________________________
None
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_3.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_3.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_3</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_3.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_3.h5&#39;</span><span class="p">,</span> 
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
101/101 [==============================] - 52s 512ms/step - loss: 288.1279 - val_loss: 239.7029
Epoch 2/20
101/101 [==============================] - 50s 492ms/step - loss: 234.9142 - val_loss: 223.7755
Epoch 3/20
101/101 [==============================] - 49s 487ms/step - loss: 222.4836 - val_loss: 210.2581
Epoch 4/20
101/101 [==============================] - 49s 489ms/step - loss: 199.7976 - val_loss: 187.0597
Epoch 5/20
101/101 [==============================] - 50s 493ms/step - loss: 176.0846 - val_loss: 170.3109
Epoch 6/20
101/101 [==============================] - 50s 494ms/step - loss: 162.5345 - val_loss: 158.1474
Epoch 7/20
101/101 [==============================] - 50s 490ms/step - loss: 153.3677 - val_loss: 154.9440
Epoch 8/20
101/101 [==============================] - 50s 493ms/step - loss: 145.5320 - val_loss: 149.5163
Epoch 9/20
101/101 [==============================] - 49s 488ms/step - loss: 138.9650 - val_loss: 142.2867
Epoch 10/20
101/101 [==============================] - 50s 494ms/step - loss: 132.7807 - val_loss: 139.8802
Epoch 11/20
101/101 [==============================] - 50s 493ms/step - loss: 128.0623 - val_loss: 138.7998
Epoch 12/20
101/101 [==============================] - 50s 498ms/step - loss: 123.4784 - val_loss: 135.1469
Epoch 13/20
101/101 [==============================] - 50s 497ms/step - loss: 119.4480 - val_loss: 134.3682
Epoch 14/20
101/101 [==============================] - 49s 487ms/step - loss: 116.4221 - val_loss: 133.3589
Epoch 15/20
101/101 [==============================] - 50s 495ms/step - loss: 113.0396 - val_loss: 133.0994
Epoch 16/20
101/101 [==============================] - 50s 497ms/step - loss: 109.8646 - val_loss: 132.3901
Epoch 17/20
101/101 [==============================] - 50s 493ms/step - loss: 107.1566 - val_loss: 131.4241
Epoch 18/20
101/101 [==============================] - 50s 491ms/step - loss: 104.3642 - val_loss: 129.9949
Epoch 19/20
101/101 [==============================] - 50s 495ms/step - loss: 101.1868 - val_loss: 129.7708
Epoch 20/20
101/101 [==============================] - 50s 493ms/step - loss: 98.6302 - val_loss: 131.2318
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<p><a id='model4'></a></p>
<h3 id="(IMPLEMENTATION)-Model-4:-Bidirectional-RNN-+-TimeDistributed-Dense">(IMPLEMENTATION) Model 4: Bidirectional RNN + TimeDistributed Dense<a class="anchor-link" href="#(IMPLEMENTATION)-Model-4:-Bidirectional-RNN-+-TimeDistributed-Dense">&#182;</a></h3><p>Read about the <a href="https://keras.io/layers/wrappers/">Bidirectional</a> wrapper in the Keras documentation.  For your next architecture, you will specify an architecture that uses a single bidirectional RNN layer, before a (<code>TimeDistributed</code>) dense layer.  The added value of a bidirectional RNN is described well in <a href="http://www.cs.toronto.edu/~hinton/absps/DRNN_speech.pdf">this paper</a>.</p>
<blockquote><p>One shortcoming of conventional RNNs is that they are only able to make use of previous context. In speech recognition, where whole utterances are transcribed at once, there is no reason not to exploit future context as well.  Bidirectional RNNs (BRNNs) do this by processing the data in both directions with two separate hidden layers which are then fed forwards to the same output layer.</p>
</blockquote>
<p><img src="images/bidirectional_rnn_model.png" width="80%"></p>
<p>Before running the code cell below, you must complete the <code>bidirectional_rnn_model</code> function in <code>sample_models.py</code>.  Feel free to use <code>SimpleRNN</code>, <code>LSTM</code>, or <code>GRU</code> units.  When specifying the <code>Bidirectional</code> wrapper, use <code>merge_mode='concat'</code>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_4</span> <span class="o">=</span> <span class="n">bidirectional_rnn_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                                  <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">)</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
bidirectional_1 (Bidirection (None, None, 400)         435600    
_________________________________________________________________
time_distributed_5 (TimeDist (None, None, 29)          11629     
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 447,229
Trainable params: 447,229
Non-trainable params: 0
_________________________________________________________________
None
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_4.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_4.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_4</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_4.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_4.h5&#39;</span><span class="p">,</span> 
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
101/101 [==============================] - 50s 498ms/step - loss: 355.3885 - val_loss: 243.0136
Epoch 2/20
101/101 [==============================] - 48s 470ms/step - loss: 235.1148 - val_loss: 207.8779
Epoch 3/20
101/101 [==============================] - 48s 474ms/step - loss: 207.7804 - val_loss: 193.4948
Epoch 4/20
101/101 [==============================] - 48s 480ms/step - loss: 194.4914 - val_loss: 185.6990
Epoch 5/20
101/101 [==============================] - 48s 477ms/step - loss: 183.7918 - val_loss: 177.1169
Epoch 6/20
101/101 [==============================] - 48s 475ms/step - loss: 174.8826 - val_loss: 173.7912
Epoch 7/20
101/101 [==============================] - 48s 477ms/step - loss: 166.9946 - val_loss: 167.0437
Epoch 8/20
101/101 [==============================] - 48s 477ms/step - loss: 159.5132 - val_loss: 160.9170
Epoch 9/20
101/101 [==============================] - 48s 478ms/step - loss: 153.2113 - val_loss: 157.2033
Epoch 10/20
101/101 [==============================] - 48s 477ms/step - loss: 147.8417 - val_loss: 151.7689
Epoch 11/20
101/101 [==============================] - 49s 481ms/step - loss: 142.6592 - val_loss: 149.8205
Epoch 12/20
101/101 [==============================] - 48s 475ms/step - loss: 137.8695 - val_loss: 146.8804
Epoch 13/20
101/101 [==============================] - 48s 479ms/step - loss: 133.5774 - val_loss: 146.3755
Epoch 14/20
101/101 [==============================] - 48s 478ms/step - loss: 129.3877 - val_loss: 144.2891
Epoch 15/20
101/101 [==============================] - 49s 482ms/step - loss: 125.5449 - val_loss: 142.9851
Epoch 16/20
101/101 [==============================] - 48s 477ms/step - loss: 121.8065 - val_loss: 141.1066
Epoch 17/20
101/101 [==============================] - 48s 477ms/step - loss: 118.3250 - val_loss: 142.4753
Epoch 18/20
101/101 [==============================] - 48s 477ms/step - loss: 114.8136 - val_loss: 138.6616
Epoch 19/20
101/101 [==============================] - 48s 480ms/step - loss: 111.8465 - val_loss: 139.7590
Epoch 20/20
101/101 [==============================] - 49s 482ms/step - loss: 108.5352 - val_loss: 140.9357
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<p><a id='model5'></a></p>
<h3 id="(OPTIONAL-IMPLEMENTATION)-Models-5+">(OPTIONAL IMPLEMENTATION) Models 5+<a class="anchor-link" href="#(OPTIONAL-IMPLEMENTATION)-Models-5+">&#182;</a></h3><p>If you would like to try out more architectures than the ones above, please use the code cell below.  Please continue to follow the same convention for saving the models; for the $i$-th sample model, please save the loss at <strong><code>model_i.pickle</code></strong> and saving the trained model at <strong><code>model_i.h5</code></strong>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">## (Optional) TODO: Try out some more models!</span>
<span class="c1">### Feel free to use as many code cells as needed.</span>
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<p><a id='compare'></a></p>
<h3 id="Compare-the-Models">Compare the Models<a class="anchor-link" href="#Compare-the-Models">&#182;</a></h3><p>Execute the code cell below to evaluate the performance of the drafted deep learning models.  The training and validation loss are plotted for each model.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">glob</span> <span class="k">import</span> <span class="n">glob</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">_pickle</span> <span class="k">as</span> <span class="nn">pickle</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="o">%</span><span class="k">matplotlib</span> inline
<span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="n">style</span><span class="o">=</span><span class="s1">&#39;white&#39;</span><span class="p">)</span>

<span class="c1"># obtain the paths for the saved model history</span>
<span class="n">all_pickles</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">glob</span><span class="p">(</span><span class="s2">&quot;results/*.pickle&quot;</span><span class="p">))</span>
<span class="c1"># extract the name of each model</span>
<span class="n">model_names</span> <span class="o">=</span> <span class="p">[</span><span class="n">item</span><span class="p">[</span><span class="mi">8</span><span class="p">:</span><span class="o">-</span><span class="mi">7</span><span class="p">]</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">all_pickles</span><span class="p">]</span>
<span class="c1"># extract the loss history for each model</span>
<span class="n">valid_loss</span> <span class="o">=</span> <span class="p">[</span><span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span> <span class="nb">open</span><span class="p">(</span> <span class="n">i</span><span class="p">,</span> <span class="s2">&quot;rb&quot;</span> <span class="p">)</span> <span class="p">)[</span><span class="s1">&#39;val_loss&#39;</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">all_pickles</span><span class="p">]</span>
<span class="n">train_loss</span> <span class="o">=</span> <span class="p">[</span><span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span> <span class="nb">open</span><span class="p">(</span> <span class="n">i</span><span class="p">,</span> <span class="s2">&quot;rb&quot;</span> <span class="p">)</span> <span class="p">)[</span><span class="s1">&#39;loss&#39;</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">all_pickles</span><span class="p">]</span>
<span class="c1"># save the number of epochs used to train each model</span>
<span class="n">num_epochs</span> <span class="o">=</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">valid_loss</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">valid_loss</span><span class="p">))]</span>

<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span><span class="mi">5</span><span class="p">))</span>

<span class="c1"># plot the training loss vs. epoch for each model</span>
<span class="n">ax1</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">121</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">all_pickles</span><span class="p">)):</span>
    <span class="n">ax1</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">linspace</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_epochs</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">num_epochs</span><span class="p">[</span><span class="n">i</span><span class="p">]),</span> 
            <span class="n">train_loss</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="n">model_names</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="c1"># clean up the plot</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>  
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="nb">max</span><span class="p">(</span><span class="n">num_epochs</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;Epoch&#39;</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;Training Loss&#39;</span><span class="p">)</span>

<span class="c1"># plot the validation loss vs. epoch for each model</span>
<span class="n">ax2</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">122</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">all_pickles</span><span class="p">)):</span>
    <span class="n">ax2</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">linspace</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_epochs</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">num_epochs</span><span class="p">[</span><span class="n">i</span><span class="p">]),</span> 
            <span class="n">valid_loss</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="n">model_names</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="c1"># clean up the plot</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>  
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="nb">max</span><span class="p">(</span><span class="n">num_epochs</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;Epoch&#39;</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;Validation Loss&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

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<p><strong>Question 1:</strong> Use the plot above to analyze the performance of each of the attempted architectures.  Which performs best?  Provide an explanation regarding why you think some models perform better than others.</p>
<p><strong>Answer:</strong>
The model 3 has the best performance. Although model 2 has the lowest training loss, and the validation loss decreases fastest, it starts to overfit after 10 epochs. Model 3 has the second lowest training loss and lowest validation loss, so it is the best model. The reason why model 3 is the best may be it is the deepest rnn model among all models, so it has the best performance. The model which has second best performance is model 4. It is good because it has bidirectional RNN layer that has information from both side of the sequence, but since it only has one layer and not deep enough, so it can not outperform model 3. Model 1 is a simple RNN plus time distributed dense layer, which is less complicated than any of the above models, so it is worse than all of the above models. The worst model is model 0, a naive RNN directly connected to the input and output. It does not have a time distributed dense layer to map hidden state space into output space, which leads to a low dimensionality in the hidden state space and not able to learn enough information from the data.<br>
The CNN architecture is the fastest because CNN can be highly parallelized on GPU. The second fastest is the simple RNN with time distributed dense layer because it is the simplest RNN structure among the models. Deep RNN and bidirectional RNN takes almost same amount of time. The slowest model is the naive RNN model because the RNN cell has to use softmax activation function, which is not available in CuDNNGRU, so it can not be speed up bu CuDNN.</p>

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<p><a id='final'></a></p>
<h3 id="(IMPLEMENTATION)-Final-Model">(IMPLEMENTATION) Final Model<a class="anchor-link" href="#(IMPLEMENTATION)-Final-Model">&#182;</a></h3><p>Now that you've tried out many sample models, use what you've learned to draft your own architecture!  While your final acoustic model should not be identical to any of the architectures explored above, you are welcome to merely combine the explored layers above into a deeper architecture.  It is <strong>NOT</strong> necessary to include new layer types that were not explored in the notebook.</p>
<p>However, if you would like some ideas for even more layer types, check out these ideas for some additional, optional extensions to your model:</p>
<ul>
<li>If you notice your model is overfitting to the training dataset, consider adding <strong>dropout</strong>!  To add dropout to <a href="https://faroit.github.io/keras-docs/1.0.2/layers/recurrent/">recurrent layers</a>, pay special attention to the <code>dropout_W</code> and <code>dropout_U</code> arguments.  This <a href="http://arxiv.org/abs/1512.05287">paper</a> may also provide some interesting theoretical background.</li>
<li>If you choose to include a convolutional layer in your model, you may get better results by working with <strong>dilated convolutions</strong>.  If you choose to use dilated convolutions, make sure that you are able to accurately calculate the length of the acoustic model's output in the <code>model.output_length</code> lambda function.  You can read more about dilated convolutions in Google's <a href="https://arxiv.org/abs/1609.03499">WaveNet paper</a>.  For an example of a speech-to-text system that makes use of dilated convolutions, check out this GitHub <a href="https://github.com/buriburisuri/speech-to-text-wavenet">repository</a>.  You can work with dilated convolutions <a href="https://keras.io/layers/convolutional/">in Keras</a> by paying special attention to the <code>padding</code> argument when you specify a convolutional layer.</li>
<li>If your model makes use of convolutional layers, why not also experiment with adding <strong>max pooling</strong>?  Check out <a href="https://arxiv.org/pdf/1701.02720.pdf">this paper</a> for example architecture that makes use of max pooling in an acoustic model.</li>
<li>So far, you have experimented with a single bidirectional RNN layer.  Consider stacking the bidirectional layers, to produce a <a href="https://www.cs.toronto.edu/~graves/asru_2013.pdf">deep bidirectional RNN</a>!</li>
</ul>
<p>All models that you specify in this repository should have <code>output_length</code> defined as an attribute.  This attribute is a lambda function that maps the (temporal) length of the input acoustic features to the (temporal) length of the output softmax layer.  This function is used in the computation of CTC loss; to see this, look at the <code>add_ctc_loss</code> function in <code>train_utils.py</code>.  To see where the <code>output_length</code> attribute is defined for the models in the code, take a look at the <code>sample_models.py</code> file.  You will notice this line of code within most models:</p>

<pre><code>model.output_length = lambda x: x</code></pre>
<p>The acoustic model that incorporates a convolutional layer (<code>cnn_rnn_model</code>) has a line that is a bit different:</p>

<pre><code>model.output_length = lambda x: cnn_output_length(
        x, kernel_size, conv_border_mode, conv_stride)</code></pre>
<p>In the case of models that use purely recurrent layers, the lambda function is the identity function, as the recurrent layers do not modify the (temporal) length of their input tensors.  However, convolutional layers are more complicated and require a specialized function (<code>cnn_output_length</code> in <code>sample_models.py</code>) to determine the temporal length of their output.</p>
<p>You will have to add the <code>output_length</code> attribute to your final model before running the code cell below.  Feel free to use the <code>cnn_output_length</code> function, if it suits your model.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># specify the model</span>
<span class="n">model_end</span> <span class="o">=</span> <span class="n">final_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                        <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                        <span class="n">filters</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                        <span class="n">kernel_size</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> 
                        <span class="n">conv_stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
                        <span class="n">conv_border_mode</span><span class="o">=</span><span class="s1">&#39;valid&#39;</span><span class="p">,</span>
                        <span class="n">recur_layers</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
conv1d (Conv1D)              (None, None, 200)         354400    
_________________________________________________________________
bn_conv_1d (BatchNormalizati (None, None, 200)         800       
_________________________________________________________________
max_pooling1d_1 (MaxPooling1 (None, None, 200)         0         
_________________________________________________________________
dropout_1 (Dropout)          (None, None, 200)         0         
_________________________________________________________________
bidirectional_1 (Bidirection (None, None, 400)         482400    
_________________________________________________________________
batch_normalization_1 (Batch (None, None, 400)         1600      
_________________________________________________________________
dropout_2 (Dropout)          (None, None, 400)         0         
_________________________________________________________________
bidirectional_2 (Bidirection (None, None, 400)         722400    
_________________________________________________________________
batch_normalization_2 (Batch (None, None, 400)         1600      
_________________________________________________________________
dropout_3 (Dropout)          (None, None, 400)         0         
_________________________________________________________________
time_distributed_1 (TimeDist (None, None, 29)          11629     
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 1,574,829
Trainable params: 1,572,829
Non-trainable params: 2,000
_________________________________________________________________
None
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_end.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_end.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_end</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_end.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_end.h5&#39;</span><span class="p">,</span> 
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/30
101/101 [==============================] - 36s 354ms/step - loss: 237.7655 - val_loss: 211.6516
Epoch 2/30
101/101 [==============================] - 31s 309ms/step - loss: 205.4389 - val_loss: 186.5985
Epoch 3/30
101/101 [==============================] - 30s 299ms/step - loss: 190.9897 - val_loss: 176.5298
Epoch 4/30
101/101 [==============================] - 31s 308ms/step - loss: 181.7656 - val_loss: 167.7820
Epoch 5/30
101/101 [==============================] - 30s 295ms/step - loss: 174.3039 - val_loss: 162.7246
Epoch 6/30
101/101 [==============================] - 30s 299ms/step - loss: 168.6530 - val_loss: 157.2020
Epoch 7/30
101/101 [==============================] - 30s 296ms/step - loss: 162.6592 - val_loss: 154.0213
Epoch 8/30
101/101 [==============================] - 30s 296ms/step - loss: 158.0283 - val_loss: 150.6817
Epoch 9/30
101/101 [==============================] - 30s 298ms/step - loss: 153.5708 - val_loss: 148.7958
Epoch 10/30
101/101 [==============================] - 30s 300ms/step - loss: 149.3002 - val_loss: 146.5247
Epoch 11/30
101/101 [==============================] - 30s 294ms/step - loss: 145.4402 - val_loss: 144.1132
Epoch 12/30
101/101 [==============================] - 30s 294ms/step - loss: 141.8986 - val_loss: 141.7772
Epoch 13/30
101/101 [==============================] - 30s 295ms/step - loss: 138.2324 - val_loss: 140.4358
Epoch 14/30
101/101 [==============================] - 30s 296ms/step - loss: 135.0641 - val_loss: 138.3214
Epoch 15/30
101/101 [==============================] - 32s 315ms/step - loss: 131.9117 - val_loss: 137.3962
Epoch 16/30
101/101 [==============================] - 30s 297ms/step - loss: 128.9103 - val_loss: 136.6382
Epoch 17/30
101/101 [==============================] - 30s 295ms/step - loss: 126.2045 - val_loss: 135.4890
Epoch 18/30
101/101 [==============================] - 30s 293ms/step - loss: 123.4839 - val_loss: 135.2201
Epoch 19/30
101/101 [==============================] - 30s 294ms/step - loss: 120.7580 - val_loss: 133.9804
Epoch 20/30
101/101 [==============================] - 30s 294ms/step - loss: 118.0934 - val_loss: 134.4486
Epoch 21/30
101/101 [==============================] - 30s 296ms/step - loss: 115.9492 - val_loss: 133.7673
Epoch 22/30
101/101 [==============================] - 30s 300ms/step - loss: 113.4156 - val_loss: 134.3959
Epoch 23/30
101/101 [==============================] - 30s 295ms/step - loss: 110.9657 - val_loss: 133.9262
Epoch 24/30
101/101 [==============================] - 30s 295ms/step - loss: 108.8729 - val_loss: 132.7703
Epoch 25/30
101/101 [==============================] - 30s 294ms/step - loss: 106.4956 - val_loss: 133.2062
Epoch 26/30
101/101 [==============================] - 30s 301ms/step - loss: 104.4349 - val_loss: 132.5333
Epoch 27/30
101/101 [==============================] - 30s 299ms/step - loss: 102.8143 - val_loss: 134.0303
Epoch 28/30
101/101 [==============================] - 30s 297ms/step - loss: 100.6798 - val_loss: 133.0659
Epoch 29/30
101/101 [==============================] - 30s 295ms/step - loss: 98.8451 - val_loss: 133.6845
Epoch 30/30
101/101 [==============================] - 30s 297ms/step - loss: 97.1967 - val_loss: 132.6040
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<p><strong>Question 2:</strong> Describe your final model architecture and your reasoning at each step.</p>
<p><strong>Answer:</strong>
In the final model, I want to integrate all the advantages of the previous models and overcome the disadvantages. After feature preprocessing, I want to use a convolution layer to learn the feature representation in the spectrogram since one layer of CNN works well in the previous model. In order to avoid covariate shift, I add batch normalization layer after the convolution layer and all the layers afterwards. In order not to overfitting, I add maxpooling layer and dropout layer after the convolution layer. Dropout rate of 0.2 is generally used, so I decide to accept this rate. In order to make the network deeper and have bidirectional information, after CNN architecture I add several layers of bidirectional GRU. In the previous example 2 layers of RNN layers have done an excellent job, so I decide to set the number of layer as 2. I also add dropout layer with dropout rate as 0.2 after each GRU in order to prevent overfitting. Finally, the output sequences are inputted into a time-distributed dense layer with softmax function in order to get the output.</p>

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<p><a id='step3'></a></p>
<h2 id="STEP-3:-Obtain-Predictions">STEP 3: Obtain Predictions<a class="anchor-link" href="#STEP-3:-Obtain-Predictions">&#182;</a></h2><p>We have written a function for you to decode the predictions of your acoustic model.  To use the function, please execute the code cell below.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">AudioGenerator</span>
<span class="kn">from</span> <span class="nn">keras</span> <span class="k">import</span> <span class="n">backend</span> <span class="k">as</span> <span class="n">K</span>
<span class="kn">from</span> <span class="nn">utils</span> <span class="k">import</span> <span class="n">int_sequence_to_text</span>
<span class="kn">from</span> <span class="nn">IPython.display</span> <span class="k">import</span> <span class="n">Audio</span>

<span class="k">def</span> <span class="nf">get_predictions</span><span class="p">(</span><span class="n">index</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">input_to_softmax</span><span class="p">,</span> <span class="n">model_path</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot; Print a model&#39;s decoded predictions</span>
<span class="sd">    Params:</span>
<span class="sd">        index (int): The example you would like to visualize</span>
<span class="sd">        partition (str): One of &#39;train&#39; or &#39;validation&#39;</span>
<span class="sd">        input_to_softmax (Model): The acoustic model</span>
<span class="sd">        model_path (str): Path to saved acoustic model&#39;s weights</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># load the train and test data</span>
    <span class="n">data_gen</span> <span class="o">=</span> <span class="n">AudioGenerator</span><span class="p">()</span>
    <span class="n">data_gen</span><span class="o">.</span><span class="n">load_train_data</span><span class="p">()</span>
    <span class="n">data_gen</span><span class="o">.</span><span class="n">load_validation_data</span><span class="p">()</span>
    
    <span class="c1"># obtain the true transcription and the audio features </span>
    <span class="k">if</span> <span class="n">partition</span> <span class="o">==</span> <span class="s1">&#39;validation&#39;</span><span class="p">:</span>
        <span class="n">transcr</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">valid_texts</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>
        <span class="n">audio_path</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">valid_audio_paths</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>
        <span class="n">data_point</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">normalize</span><span class="p">(</span><span class="n">data_gen</span><span class="o">.</span><span class="n">featurize</span><span class="p">(</span><span class="n">audio_path</span><span class="p">))</span>
    <span class="k">elif</span> <span class="n">partition</span> <span class="o">==</span> <span class="s1">&#39;train&#39;</span><span class="p">:</span>
        <span class="n">transcr</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">train_texts</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>
        <span class="n">audio_path</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">train_audio_paths</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>
        <span class="n">data_point</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">normalize</span><span class="p">(</span><span class="n">data_gen</span><span class="o">.</span><span class="n">featurize</span><span class="p">(</span><span class="n">audio_path</span><span class="p">))</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Invalid partition!  Must be &quot;train&quot; or &quot;validation&quot;&#39;</span><span class="p">)</span>
        
    <span class="c1"># obtain and decode the acoustic model&#39;s predictions</span>
    <span class="n">input_to_softmax</span><span class="o">.</span><span class="n">load_weights</span><span class="p">(</span><span class="n">model_path</span><span class="p">)</span>
    <span class="n">prediction</span> <span class="o">=</span> <span class="n">input_to_softmax</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">data_point</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="n">output_length</span> <span class="o">=</span> <span class="p">[</span><span class="n">input_to_softmax</span><span class="o">.</span><span class="n">output_length</span><span class="p">(</span><span class="n">data_point</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="n">pred_ints</span> <span class="o">=</span> <span class="p">(</span><span class="n">K</span><span class="o">.</span><span class="n">eval</span><span class="p">(</span><span class="n">K</span><span class="o">.</span><span class="n">ctc_decode</span><span class="p">(</span>
                <span class="n">prediction</span><span class="p">,</span> <span class="n">output_length</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="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">flatten</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
    
    <span class="c1"># play the audio file, and display the true and predicted transcriptions</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;-&#39;</span><span class="o">*</span><span class="mi">80</span><span class="p">)</span>
    <span class="n">Audio</span><span class="p">(</span><span class="n">audio_path</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;True transcription:</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="n">transcr</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;-&#39;</span><span class="o">*</span><span class="mi">80</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Predicted transcription:</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">int_sequence_to_text</span><span class="p">(</span><span class="n">pred_ints</span><span class="p">)))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;-&#39;</span><span class="o">*</span><span class="mi">80</span><span class="p">)</span>
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<p>Use the code cell below to obtain the transcription predicted by your final model for the first example in the training dataset.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">get_predictions</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> 
                <span class="n">partition</span><span class="o">=</span><span class="s1">&#39;train&#39;</span><span class="p">,</span>
                <span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_end</span><span class="p">,</span> 
                <span class="n">model_path</span><span class="o">=</span><span class="s1">&#39;results/model_end.h5&#39;</span><span class="p">)</span>
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<pre>--------------------------------------------------------------------------------
True transcription:

mister quilter is the apostle of the middle classes and we are glad to welcome his gospel
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Predicted transcription:

mis tr culter is the apost o ol fhf itle class and wer glad tololtom his gospl
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<p>Use the next code cell to visualize the model's prediction for the first example in the validation dataset.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">get_predictions</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> 
                <span class="n">partition</span><span class="o">=</span><span class="s1">&#39;validation&#39;</span><span class="p">,</span>
                <span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_end</span><span class="p">,</span> 
                <span class="n">model_path</span><span class="o">=</span><span class="s1">&#39;results/model_end.h5&#39;</span><span class="p">)</span>
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<pre>--------------------------------------------------------------------------------
True transcription:

stuff it into you his belly counselled him
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Predicted transcription:

stefot into ou his bely cauptilthim
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<p>One standard way to improve the results of the decoder is to incorporate a language model.  We won't pursue this in the notebook, but you are welcome to do so as an <em>optional extension</em>.</p>
<p>If you are interested in creating models that provide improved transcriptions, you are encouraged to download <a href="http://www.openslr.org/12/">more data</a> and train bigger, deeper models.  But beware - the model will likely take a long while to train.  For instance, training this <a href="https://arxiv.org/pdf/1512.02595v1.pdf">state-of-the-art</a> model would take 3-6 weeks on a single GPU!</p>

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