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+# Introduction to NASA Earthdata Cloud and ICESat-2
+
+### Learning Outcomes
+
+The purpose of this overview is to introduce the data search and access options provided within the Earthdata Cloud, along with an introduction to NASA's ICESat-2 Mission. 
+
+### Prerequisites
+
+None
+
+### Credits
+
+This guide was adapted from the following tutorials:
+* [Data Discovery and Access: Overview](https://icesat-2-2023.hackweek.io/tutorials/data-access-and-format/overview.html) by Andy Barrett, NSIDC DAAC
+* [Using icepyx to access ICESat-2 data](https://nasa-openscapes.github.io/2023-ssc/tutorials/data-access/icepyx.html) by Rachel Wegener, University of Maryland
+* [Data Strategies for Future Us](https://nsidc.github.io/data_strategies_for_future_us/data_strategies_slides#/workflow-solutions-3) by Andy Barrett, NSIDC DAAC
+* [Accessing and working with ICESat-2 data in the cloud](https://nasa-openscapes.github.io/2023-ssc/tutorials/data-access/) by Rachel Wegener, University of Maryland; Luis Lopez, NSIDC DAAC; and Amy Steiker, NSIDC DAAC.
+
+## 1. Modes of Data Access
+
+In the past, most of our scientific data analysis workflows have started with searching for data and then downloading that data to a local machine; whether that is the hard drive of your laptop or workstation, or some shared storage device hosted by your institution or research group. This can be a time consuming process if the volume of data is large, even with fast internet. It also requires that you have sufficient disk-space and update your copy every time an updated version of the data is released. If you want to work with data from different geoscience domains, you may have to download data from several data centers. 
+
+<figure>
+<center>
+    <img src='images/shiklomanov-cloud-paradigm.png' alt='Earthdata Cloud Transition. Credit: Alexey Shiklomanov, NASA ESDIS'/>
+</center>
+</figure>
+
+Figure credit: Alexey Shiklomanov, NASA ESDIS Project Scientist, from [The future of NASA Earth Science in the commercial cloud:
+Challenges and opportunities](https://docs.google.com/presentation/d/12mh_8WU9lsrPviBO_MBv2blbjRufXoQmqCB4XGyxQ90/edit?pli=1)
+
+However, a change is a-foot. New modes of data access are becoming available. Driven by the growth in the volume of data from future satellite missions, the archiving and distribution of NASA data is in a [state of transition](https://www.earthdata.nasa.gov/eosdis/cloud-evolution). Over the next few years, all NASA data will be migrated to the NASA Earthdata Cloud, a cloud-hosted data store that will have all NASA datasets in one place. This not only offers new modes of accessing NASA data but also offers new ways of working with this data. As with Google Docs or Sheets, data in these "files" is not just stored in the cloud but compute resources offered by cloud providers allow you to process and analyze the data in the cloud. When you edit your Google Doc or Sheet, you are working in the cloud, not on your computer. All you need is a web browser; you can work with these files on your laptop, tablet or even your phone. If you choose to share these documents with others, they can actively collaborate with you on the same document also in the cloud. For large geoscience datasets, this means you can _skip the download_ and take your _analysis to the data_.  
+
+## 2. NASA Earthdata Cloud
+
+NASA's cloud-hosted storage is known as the Earthdata Cloud; all NASA datasets are being migrated to be available in the cloud. During this transition period, data will still remain freely available for download directly from the DAACs (Distributed Active Archive Centers), which have archived and distributed NASA data for over 20 years.
+
+<figure>
+<center>
+    <img src='images/NSIDC-DAAC.png' alt='NSIDC DAAC Intro'/>
+</center>
+</figure>
+
+The NSIDC DAAC now offers all [ICESat-2](https://nsidc.org/data/icesat-2) and [ICESat/GLAS](https://nsidc.org/data/icesat) data products via Earthdata Cloud. A listing of all NSIDC DAAC cloud-hosted data can be found [here](https://nsidc.org/data/earthdata-cloud/data). More details on ICESat-2 below.
+
+### Earthdata Cloud Computing Basics
+
+"The Cloud" is a somewhat nebulous term (pun intended). In general, the cloud is a network of remote servers that run software and services that are accessed over the internet.  There is a growing number of commercial cloud providers (Google Cloud Services, Amazon Web Services, Microsoft Azure). NASA has contracted with Amazon Web Services (AWS) to host data using the AWS Simple Storage Service (S3). AWS offers a large number of services in addition to S3 storage. A key service is Amazon Elastic Compute Cloud (Amazon EC2). This is the service that is _under-the-hood_ of the CryoCloud JupyterHub you are using during today's workshop.  When you start a JupyterHub, an EC2 _instance_ is started.  You can think of an EC2 _instance_ as a remote computer.
+
+AWS has the concept of a region, which is a cluster of data centers. These data centers house the servers that run S3 and EC2 instances. NASA Earthdata Cloud is hosted in the `us-west-2` region. This is important because if your EC2 instance is in the same region as the Earthdata Cloud S3 storage, you can access data in S3 directly in a way that is analogous to accessing a file on your laptop's or workstation's hard drive. This is one of the key advantages of working in the cloud; you can do analysis where the data is stored without having to download or move the data to another machine.  
+
+### Cost Considerations
+
+The notion of _analysis in place_, or the concept of bringing your compute, or processing, to the data, provides several advantages over the more traditional download method: You no longer need to move data from its archived location, and you only pay for the compute needed to do your analysis. A few key points about cost:
+
+* Cost to access: As long as you are performing your processing in the same location (region) as where the data are located in Earthdata Cloud, then the cost to access the data is completely free. CryoCloud is running in the same `us-west-2` region as where the NASA Earthdata Cloud data are stored.
+* Cost to compute: Just like your laptop costs money up front that provides you with certain CPU and memory, the compute resources needed to run your analyses do cost money. This can be thought of as the difference between an upfront cost like purchasing a laptop to process data locally versus something you can pay for as you go. There is a cost associated with the EC2 instance mentioned above, paid for by CryoCloud.
+* Cost to store: With _analysis in place_, the data are being streamed directly from its native location in the cloud, so storage is not needed. However you may wish to store analysis outputs or other data using your own S3 bucket, which does incur a cost. 
+
+### "When To Cloud"
+
+Migrating to a cloud-based data analysis workflow can often have a steep learning curve and feel overwhelming. There are times when the cloud is effective and times when the download model may still be more appropriate. Here are a few key questions to ask yourself: 
+
+* What is the data volume?
+* How long will it take to download?
+* Can you store all that data (cost and space)?
+* Do you have the computing power for processing?
+* Does your team need a common computing environment?
+* Do you need to share data at each step or just an end product?
+
+
+## 3. Introduction to ICESat-2
+
+![IS2](https://icesat-2.gsfc.nasa.gov/sites/default/files/MissionLogo_0.png)
+
+ICESat-2 carries a satellite lidar instrument, ATLAS. Lidar is an active remote sensing technique in which pulses of light are emitted and the return time is used to measure distance, in this case the height of something on the earth's surface. The available ICESat-2 data products range from sea ice freeboard to land elevation to cloud backscatter characteristics. A list of available products can be found [here](https://icesat-2.gsfc.nasa.gov/science/data-products). 
+
+![IS2-Product-Tree](https://nsidc.org/sites/default/files/styles/article_image/public/images/Other/icesat2_graphic_2023_update_final.png.webp)
+
+More key features of ICESat-2:
+
+* Height determined using round-trip travel time of laser light (photon counting lidar)
+* 10,000 laser pulses released per second, split into 3 weak/strong beam pairs at a wavelength of 532 nanometers (bright green on the visible spectrum).
+* Measurements taken every 70 cm along the satellite’s ground track, roughly 11 m wide footprint.
+* The number of photons that return to the telescope depends on surface reflectivity and cloud cover (which obscures ATLAS’s view of Earth). As such, the spatial resolution of signal photons varies.
+
+### Data Collection
+
+ICESat-2 measures data along 3 strong/weak beam pairs, resulting in 3 strong beams and 3 weak beams. The strong and weak beams are calibrated such that the weak beams have more sensitivity to viewing very bright surfaces (Ex. ice), while the strong beams are able to view surfaces with lower reflectances (Ex. water). The beams are designated in each data product as `gt1l`, `gt1r`, `gt2l`, `gt2r`, `gt3l`, and `gt3r`, where `gt` stands for "ground track", the number refers to the photon emitter, and the `l` and `r` indicate "left" or "right" beam of the pair. Which of these designations is strong or weak depends on the orientation of the satellite (forwards, `sc_orient==1`; backwards, `sc_orient==0`). A helpful table of which beams are strong/weak can be found on p131 of the [ATL03 Algorithm Theoretical Basis Document](https://icesat-2.gsfc.nasa.gov/sites/default/files/page_files/ICESat2_ATL03_ATBD_r006.pdf). The ATLAS spot number (values 1-6) is based on the ground track designation (`gt1l` etc.) and spacecraft orientation and, once determined, can be used to consistently identify strong (Spots 1, 3, and 5) and weak (Spots 2, 4, and 6) beams.
+
+![Tracks](https://ars.els-cdn.com/content/image/1-s2.0-S0034425718305066-gr1.jpg)
+
+Photo: Neuenschwander et. al. 2019, Remote Sens. Env. [DOI](https://doi.org/10.1016/j.rse.2018.11.005)
+
+### Counting Photons
+
+The ICESat-2 lidar collects at the single photon level, different from most commercial lidar systems. A lot of additional photons get returned as solar background noise, and removing these unwanted photons is a key part of the algorithms that produce the higher level data products.
+
+<img src="images/ATL08_signalphotons.jpg" width=450/>
+
+> _Fig. 2. Results from signal finding methods for simulated ATLAS data. Black points show raw point cloud data as ingested from ATL03 product. Blue points overlaid in each plot show which photons each method identified as signal. Top panel reflects the signal photons as identified on the ATL03 data product (medium and high confidence signal photons). Bottom panel reflects the signal photons identified from the ATL08 DRAGANN method._ (Neuenschwander & Pitts, 2019)
+
+Photo: Neuenschwander et. al. 2019, Remote Sens. Env. [DOI](https://doi.org/10.1016/j.rse.2018.11.005)
+
+To aggregate all these photons into more manegable chunks, many of the Level-3B products such as [ATL08](https://nsidc.org/data/atl08) consolidate the photons into variable segment lengths.
+
+
+## 4. Navigating ICESat-2 Tool & Access options
+
+There are many options across NASA Earthdata when it comes to search, access, visualization, and customization tools. The [Tools & Services Roadmap](https://nasa-openscapes.github.io/earthdata-cloud-cookbook/cheatsheets.html#tools-services-roadmap) cheatsheet as part of the NASA Openscapes Cookbook presents a high level view of some of these pathways. 
+
+We will be highlighting a few tool and access options specifically for ICESat-2 today. This table provides an overview of the capabilities supported by `icepyx`, `earthaccess`, and SlideRule Earth. These open-source tools have been co-evolving through ongoing collaboration across our cryospheric open source software community. 
+
+```{table} Data Access Method and Tools
+:name: data-access-overview-table
+
+|                                             | `icepyx` | `earthaccess` | NASA Earthdata Search | SlideRule Earth |
+|---------------------------------------------|----------|---------------|-----------------------|-----------------|
+| Filter spatially using:                     |          |               |                       |                 |
+| - Interactive map widget                    |          | soon!         | x                     | x               |
+| - Bounding Box                              | x        | x             | x                     | x               |
+| - Polygon                                   | x        | x             | x                     | x               |
+| - GeoJSON or Shapefile                      | x        | soon!         | x                     | x               |
+| Filter by time and date                     | x        | x             | x                     | x               |
+| Preview data                                | x        | x             | x                     |                 |
+| Download data from DAAC                     | x        | x             | x                     |                 |
+| Access cloud-hosted data                    | x        | x             | x                     | x               |
+| Subset (spatially, temporally, by variable) | x        |               | x                     | x               |
+| Plot data with built-in methods             | x        |               |                       | x               |
+```
\ No newline at end of file
diff --git a/_sources/tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.md b/_sources/tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.md
new file mode 100644
index 0000000..f828516
--- /dev/null
+++ b/_sources/tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.md
@@ -0,0 +1,60 @@
+# Using NASA Earthdata Search to Discover Cloud-Hosted Data
+
+## Learning Objective
+
+In this tutorial you will learn how to:
+
+- Discover cloud-hosted datasets using NASA Earthdata Search.  
+- Get AWS S3 credentials so you can access this data.
+- Get the S3 links to data granules.
+
+## Prerequisites
+
+- An Earthdata Login account. See the NASA Openscapes Cookbook "[Authentication](https://nasa-openscapes.github.io/earthdata-cloud-cookbook/appendix/authentication.html)" guide for more information. 
+
+## Overview
+
+NASA Earthdata Search is a web-based tool to discover, filter, visualize and access all of NASA's Earth science data, both in Earthdata Cloud and archived at the NASA DAACs. It is a useful first step in data discovery, especially if you are not sure what data is available for your research problem.
+
+This tutorial is based on the NSIDC [NASA Earthdata Cloud Access Guide](https://nsidc.org/data/user-resources/help-center/nasa-earthdata-cloud-data-access-guide) and the "[How do I find data using Earthdata Search?](https://nasa-openscapes.github.io/earthdata-cloud-cookbook/how-tos/find-data/earthdata_search.html)" guide in the NASA Earthdata Cookbook. 
+
+
+## Searching for data and S3 links using Earthdata Search
+
+### Search for Data
+
+Step 1. Go to https://search.earthdata.nasa.gov and log in using your Earthdata Login credentials by clicking on the Earthdata Login button in the top-right corner.
+
+Step 2. Check the **Available in Earthdata Cloud** box in the **Filter Collections** side-bar on the left of the page (Box 1 on the screenshot below).  The Matching Collections will appear in the results box.  All datasets in Earthdata Cloud have a badge showing a cloud symbol and "Earthdata Cloud" next to them.  To narrow the search, we will filter by datasets supported by NSIDC by typing "NSIDC" in the search box (Box 2 on the screen shot below).  If you want, you could narrow the search further using spatial and temporal filters or any of the other filters in the filter collections box.
+
+<figure>
+<center>
+    <img src='images/Screenshot_EDSC_Searching_Cloud_Datasets.png' alt='Screenshot of Search for Cloud Datasets in Earthdata Search'/>
+</center>
+</figure>
+
+Step 3. You can now select the dataset you want by clicking on that dataset.  The Search Results box now contains granules that match your search.  The location of these granules is shown on the map.  The search can be refined using spatial and temporal filters or you can select individual granules using the "+" symbol on each granule search result.  Once you have the data you want, click the **Download All** (Box 1 in the screenshot below). In the sidebar that appears, select **Direct Download** (Box 2 in the screenshot below). Then select **Download Data**.
+
+<figure>
+    <center>
+        <img src='images/Screenshot_EDSC_getting_s3_links_workflow.png' alt='Screenshot of getting S3 links'/>
+    </center>
+</figure>
+
+### Getting S3 links and AWS S3 Credentials
+
+Step 4.  A Download Status window will appear (this may take a short amount of time) similar to the one shown below.  You will see a tab for **AWS S3 Access** (Box 1 in the screenshot below). Select this tab. A list of S3 links (urls) starting with `s3://` will be in the box below.  You can save them to a text file or copy them to your clipboard using the **Save** and **Copy** buttons (Box 2 in the screenshot below). Or you can copy each link separately by hovering over a link and clicking the clipboard icon (Box 3).
+
+Step 5.  To access data in Earthdata Cloud, you need AWS S3 credentials; “accessKeyId”, “secretAccessKey”, and “sessionToken”.  These are temporary credentials that last for one hour.  To get them click on the **Get AWS S3 Credentials** (Box 4 in the screenshot below).   This will open a new page that contains the three credentials.  
+
+<figure>
+    <center>
+        <img src='images/Screenshot_EDSC_S3_links_credentials.png' alt='Screenshot of S3 links and credentials'/>
+    </center>
+</figure>
+    
+### Using links and credentials from the command line
+
+In the next `earthaccess` tutorial, we will work programmatically in the cloud to access datasets of interest. There are several ways to do this. One way to connect this web-based search part of the workflow to our next steps working in the cloud is to simply copy/paste the s3:// links provided in Step 3 above into a JupyterHub notebook or script in our cloud workspace, and continue the data analysis from there.
+
+One could also copy/paste the s3:// links and save them in a text file, then open and read the text file in the notebook or script in the CryoCloud.
\ No newline at end of file
diff --git a/_sources/tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.ipynb b/_sources/tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.ipynb
new file mode 100644
index 0000000..68b9ea6
--- /dev/null
+++ b/_sources/tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.ipynb
@@ -0,0 +1,1923 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7fd4844a-aee8-4a9c-b22a-02688a8067f9",
+   "metadata": {
+    "tags": [],
+    "user_expressions": []
+   },
+   "source": [
+    "# NASA Earthdata Cloud and data access using earthaccess and icepyx\n",
+    "# Part 1: Introduction to the `earthaccess` python library\n",
+    "\n",
+    "## Tutorial Overview\n",
+    "\n",
+    "This tutorial is designed for the \"[Cloud Computing and Open-Source Scientific Software for Cryosphere Communities](https://agu.confex.com/agu/fm23/meetingapp.cgi/Session/193477)\" Learning Workshop at the 2023 AGU Fall Meeting.\n",
+    "\n",
+    "This notebook demonstrates how to search for, access, and work with a cloud-hosted NASA dataset using the `earthaccess` package. Data in the \"NASA Earthdata Cloud\" are stored in Amazon Web Services (AWS) Simple Storage Service (S3) Buckets. **Direct Access** is an efficient way to work with data stored in an S3 Bucket using an Amazon Compute Cloud (EC2) instance. Cloud-hosted granules can be opened and loaded into memory without the need to download them first. This allows you take advantage of the scalability and power of cloud computing. \n",
+    "\n",
+    "We use `earthaccess`, a package developed by Luis Lopez (NSIDC developer) to allow easy search of the NASA Common Metadata Repository (CMR) and download of NASA data collections. It can be used for programmatic search and access for both _DAAC-hosted_ and _cloud-hosted_ data. It manages authenticating using Earthdata Login credentials which are then used to obtain the S3 tokens that are needed for S3 direct access. `earthaccess` can be used to find and access both DAAC-hosted and cloud-hosted data in just **three** lines of code. See [https://github.com/nsidc/earthaccess](https://github.com/nsidc/earthaccess).\n",
+    "\n",
+    "As an example data collection, we use ICESat-2 Land Ice Height (ATL06) granules over the Juneau Icefield, AK, for March and April 2020. ICESat-2 data granules, including ATL06, are stored in HDF5 format. We demonstrate how to open an HDF5 granule and access data variables using `xarray`. Land Ice Heights are then plotted using `hvplot`. \n",
+    "\n",
+    "<figure>\n",
+    "<center>\n",
+    "    <img src='images/atl06_example_plot.png' alt='Example plot using data downloaded in tutorial'/>\n",
+    "    <figcaption> ATL06 Land Ice Heights for the margin of the Juneau Ice Field </figcaption>\n",
+    "</center>\n",
+    "</figure>\n",
+    "\n",
+    "### Learning Objectives\n",
+    "\n",
+    "In this tutorial you will learn:  \n",
+    "1. how to use `earthaccess` to search for (ICESat-2) data using spatial and temporal filters and explore the search results;  \n",
+    "2. how to open data granules using direct access to the appropriate S3 bucket;  \n",
+    "3. how to load an HDF5 group into an `xarray.Dataset`;  \n",
+    "4. how visualize the land ice heights using `hvplot`.  \n",
+    "\n",
+    "## Prerequisites\n",
+    "\n",
+    "The workflow described in this tutorial forms the initial steps of an _Analysis in Place_ workflow that would be run on a AWS cloud compute resource.  You will need:\n",
+    "\n",
+    "1. a JupyterHub, such as CryoHub, or AWS EC2 instance in the us-west-2 region.\n",
+    "3. a NASA Earthdata Login.  If you need to register for an Earthdata Login see the [Getting an Earthdata Login](https://icesat-2-2023.hackweek.io/preliminary/checklist/earthdata.html#getting-an-earthdata-login) section of the ICESat-2 Hackweek 2023 Jupyter Book.\n",
+    "4. A `.netrc` file, that contains your Earthdata Login credentials, in your home directory. See [Configure Programmatic Access to NASA Servers](https://icesat-2-2023.hackweek.io/preliminary/checklist/earthdata.html#configure-programmatic-access-to-nasa-servers) to create a `.netrc` file.\n",
+    "\n",
+    "## Credits\n",
+    "\n",
+    "This notebook is based on an [NSIDC Data Tutorial](https://github.com/nsidc/NSIDC-Data-Tutorials) originally created by Luis Lopez, NSIDC, and Mikala Beig, NSIDC, modified by Andy Barrett, NSIDC, Jennifer Roebuck, NSIDC, Amy Steiker, NSIDC, and Jessica Scheick, Univ. of New Hampshire."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "afb08333-e7f5-4c78-98c4-949313b6d481",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "## Computing Environment\n",
+    "\n",
+    "The tutorial uses `python` and requires the following packages:\n",
+    "- `earthaccess`, which enables Earthdata Login authentication and retrieves AWS credentials; enables collection and granule searches; and S3 access;\n",
+    "- `xarray`, used to load N-dimensional data with labeled axes;\n",
+    "- `hvplot`, used to visualize land ice height data.\n",
+    "\n",
+    "We are going to import the whole `earthaccess` package.\n",
+    "\n",
+    "We will also import the whole `xarray` package but use a standard short name `xr`, using the `import <package> as <short_name>` syntax.  We could use anything for a short name but `xr` is an accepted standard that most `xarray` users are familiar with.\n",
+    "\n",
+    "[`xarray`](https://docs.xarray.dev/en/stable/) is a powerful library for working with multi-dimensional data using labeled indices (analogous to Pandas for tabular data). It is leverages numpy, pandas, matplotlib and dask to build Dataset and DataArray objects with built-in methods to subset, analyze, interpolate, and plot multi-dimensional data. It makes working with multi-dimensional data cubes efficient and fun. A few great tutorials for learning Xarray are [here](https://nasa-openscapes.github.io/2021-Cloud-Hackathon/tutorials/03_Xarray.html) and [here](https://tutorial.xarray.dev/intro.html).\n",
+    "\n",
+    "We only need the `xarray` module from `hvplot` so we import that using the `import <package>.<module>` syntax."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
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+       "    for (const name in js_exports) {\n",
+       "      var url = js_exports[name];\n",
+       "      if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
+       "\tif (!window.requirejs) {\n",
+       "\t  on_load();\n",
+       "\t}\n",
+       "\tcontinue;\n",
+       "      }\n",
+       "      var element = document.createElement('script');\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.type = \"module\";\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      element.textContent = `\n",
+       "      import ${name} from \"${url}\"\n",
+       "      window.${name} = ${name}\n",
+       "      window._bokeh_on_load()\n",
+       "      `\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    if (!js_urls.length && !js_modules.length) {\n",
+       "      on_load()\n",
+       "    }\n",
+       "  };\n",
+       "\n",
+       "  function inject_raw_css(css) {\n",
+       "    const element = document.createElement(\"style\");\n",
+       "    element.appendChild(document.createTextNode(css));\n",
+       "    document.body.appendChild(element);\n",
+       "  }\n",
+       "\n",
+       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.2.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n",
+       "  var js_modules = [];\n",
+       "  var js_exports = {};\n",
+       "  var css_urls = [];\n",
+       "  var inline_js = [    function(Bokeh) {\n",
+       "      Bokeh.set_log_level(\"info\");\n",
+       "    },\n",
+       "function(Bokeh) {} // ensure no trailing comma for IE\n",
+       "  ];\n",
+       "\n",
+       "  function run_inline_js() {\n",
+       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
+       "      for (var i = 0; i < inline_js.length; i++) {\n",
+       "        inline_js[i].call(root, root.Bokeh);\n",
+       "      }\n",
+       "      // Cache old bokeh versions\n",
+       "      if (Bokeh != undefined && !reloading) {\n",
+       "\tvar NewBokeh = root.Bokeh;\n",
+       "\tif (Bokeh.versions === undefined) {\n",
+       "\t  Bokeh.versions = new Map();\n",
+       "\t}\n",
+       "\tif (NewBokeh.version !== Bokeh.version) {\n",
+       "\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
+       "\t}\n",
+       "\troot.Bokeh = Bokeh;\n",
+       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
+       "      setTimeout(run_inline_js, 100);\n",
+       "    } else if (!root._bokeh_failed_load) {\n",
+       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
+       "      root._bokeh_failed_load = true;\n",
+       "    }\n",
+       "    root._bokeh_is_initializing = false\n",
+       "  }\n",
+       "\n",
+       "  function load_or_wait() {\n",
+       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
+       "    // versions of Bokeh and its dependencies at the same time.\n",
+       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
+       "    // to determine whether there is an ongoing attempt to initialize\n",
+       "    // bokeh, however for backward compatibility we also try to ensure\n",
+       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
+       "    // before older versions are fully initialized.\n",
+       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
+       "      root._bokeh_is_initializing = false;\n",
+       "      root._bokeh_onload_callbacks = undefined;\n",
+       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
+       "      load_or_wait();\n",
+       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
+       "      setTimeout(load_or_wait, 100);\n",
+       "    } else {\n",
+       "      Bokeh = root.Bokeh;\n",
+       "      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
+       "      root._bokeh_is_initializing = true\n",
+       "      root._bokeh_onload_callbacks = []\n",
+       "      if (!reloading && (!bokeh_loaded || is_dev)) {\n",
+       "\troot.Bokeh = undefined;\n",
+       "      }\n",
+       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
+       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
+       "\trun_inline_js();\n",
+       "      });\n",
+       "    }\n",
+       "  }\n",
+       "  // Give older versions of the autoload script a head-start to ensure\n",
+       "  // they initialize before we start loading newer version.\n",
+       "  setTimeout(load_or_wait, 100)\n",
+       "}(window));"
+      ],
+      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n  var py_version = '3.2.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n  var reloading = false;\n  var Bokeh = root.Bokeh;\n  var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      run_callbacks();\n      return null;\n    }\n    if (!reloading) {\n      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n      })\n      require([\"jspanel-modal\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-tooltip\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-hint\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-layout\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-dock\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 9;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    var existing_stylesheets = []\n    var links = document.getElementsByTagName('link')\n    for (var i = 0; i < links.length; i++) {\n      var link = links[i]\n      if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n      }\n    }\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.2.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      Bokeh = root.Bokeh;\n      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "\n",
+       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
+       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
+       "}\n",
+       "\n",
+       "\n",
+       "    function JupyterCommManager() {\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        comm_manager.register_target(comm_id, function(comm) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        });\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        });\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
+       "          var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "          function processIteratorResult(result) {\n",
+       "            var message = result.value;\n",
+       "            console.log(message)\n",
+       "            var content = {data: message.data, comm_id};\n",
+       "            var buffers = []\n",
+       "            for (var buffer of message.buffers || []) {\n",
+       "              buffers.push(new DataView(buffer))\n",
+       "            }\n",
+       "            var metadata = message.metadata || {};\n",
+       "            var msg = {content, buffers, metadata}\n",
+       "            msg_handler(msg);\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "          return messages.next().then(processIteratorResult);\n",
+       "        })\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (comm_id in window.PyViz.comms) {\n",
+       "        return window.PyViz.comms[comm_id];\n",
+       "      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
+       "        if (msg_handler) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        }\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
+       "        comm.open();\n",
+       "        if (msg_handler) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        }\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
+       "        comm_promise.then((comm) => {\n",
+       "          window.PyViz.comms[comm_id] = comm;\n",
+       "          if (msg_handler) {\n",
+       "            var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "            function processIteratorResult(result) {\n",
+       "              var message = result.value;\n",
+       "              var content = {data: message.data};\n",
+       "              var metadata = message.metadata || {comm_id};\n",
+       "              var msg = {content, metadata}\n",
+       "              msg_handler(msg);\n",
+       "              return messages.next().then(processIteratorResult);\n",
+       "            }\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "        }) \n",
+       "        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
+       "          return comm_promise.then((comm) => {\n",
+       "            comm.send(data, metadata, buffers, disposeOnDone);\n",
+       "          });\n",
+       "        };\n",
+       "        var comm = {\n",
+       "          send: sendClosure\n",
+       "        };\n",
+       "      }\n",
+       "      window.PyViz.comms[comm_id] = comm;\n",
+       "      return comm;\n",
+       "    }\n",
+       "    window.PyViz.comm_manager = new JupyterCommManager();\n",
+       "    \n",
+       "\n",
+       "\n",
+       "var JS_MIME_TYPE = 'application/javascript';\n",
+       "var HTML_MIME_TYPE = 'text/html';\n",
+       "var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
+       "var CLASS_NAME = 'output';\n",
+       "\n",
+       "/**\n",
+       " * Render data to the DOM node\n",
+       " */\n",
+       "function render(props, node) {\n",
+       "  var div = document.createElement(\"div\");\n",
+       "  var script = document.createElement(\"script\");\n",
+       "  node.appendChild(div);\n",
+       "  node.appendChild(script);\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when a new output is added\n",
+       " */\n",
+       "function handle_add_output(event, handle) {\n",
+       "  var output_area = handle.output_area;\n",
+       "  var output = handle.output;\n",
+       "  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
+       "    return\n",
+       "  }\n",
+       "  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
+       "  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
+       "  if (id !== undefined) {\n",
+       "    var nchildren = toinsert.length;\n",
+       "    var html_node = toinsert[nchildren-1].children[0];\n",
+       "    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var scripts = [];\n",
+       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
+       "    for (var i in nodelist) {\n",
+       "      if (nodelist.hasOwnProperty(i)) {\n",
+       "        scripts.push(nodelist[i])\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    scripts.forEach( function (oldScript) {\n",
+       "      var newScript = document.createElement(\"script\");\n",
+       "      var attrs = [];\n",
+       "      var nodemap = oldScript.attributes;\n",
+       "      for (var j in nodemap) {\n",
+       "        if (nodemap.hasOwnProperty(j)) {\n",
+       "          attrs.push(nodemap[j])\n",
+       "        }\n",
+       "      }\n",
+       "      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
+       "      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
+       "      oldScript.parentNode.replaceChild(newScript, oldScript);\n",
+       "    });\n",
+       "    if (JS_MIME_TYPE in output.data) {\n",
+       "      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
+       "    }\n",
+       "    output_area._hv_plot_id = id;\n",
+       "    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
+       "      window.PyViz.plot_index[id] = Bokeh.index[id];\n",
+       "    } else {\n",
+       "      window.PyViz.plot_index[id] = null;\n",
+       "    }\n",
+       "  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
+       "    var bk_div = document.createElement(\"div\");\n",
+       "    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var script_attrs = bk_div.children[0].attributes;\n",
+       "    for (var i = 0; i < script_attrs.length; i++) {\n",
+       "      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
+       "    }\n",
+       "    // store reference to server id on output_area\n",
+       "    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when an output is cleared or removed\n",
+       " */\n",
+       "function handle_clear_output(event, handle) {\n",
+       "  var id = handle.cell.output_area._hv_plot_id;\n",
+       "  var server_id = handle.cell.output_area._bokeh_server_id;\n",
+       "  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
+       "  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
+       "  if (server_id !== null) {\n",
+       "    comm.send({event_type: 'server_delete', 'id': server_id});\n",
+       "    return;\n",
+       "  } else if (comm !== null) {\n",
+       "    comm.send({event_type: 'delete', 'id': id});\n",
+       "  }\n",
+       "  delete PyViz.plot_index[id];\n",
+       "  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
+       "    var doc = window.Bokeh.index[id].model.document\n",
+       "    doc.clear();\n",
+       "    const i = window.Bokeh.documents.indexOf(doc);\n",
+       "    if (i > -1) {\n",
+       "      window.Bokeh.documents.splice(i, 1);\n",
+       "    }\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle kernel restart event\n",
+       " */\n",
+       "function handle_kernel_cleanup(event, handle) {\n",
+       "  delete PyViz.comms[\"hv-extension-comm\"];\n",
+       "  window.PyViz.plot_index = {}\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle update_display_data messages\n",
+       " */\n",
+       "function handle_update_output(event, handle) {\n",
+       "  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
+       "  handle_add_output(event, handle)\n",
+       "}\n",
+       "\n",
+       "function register_renderer(events, OutputArea) {\n",
+       "  function append_mime(data, metadata, element) {\n",
+       "    // create a DOM node to render to\n",
+       "    var toinsert = this.create_output_subarea(\n",
+       "    metadata,\n",
+       "    CLASS_NAME,\n",
+       "    EXEC_MIME_TYPE\n",
+       "    );\n",
+       "    this.keyboard_manager.register_events(toinsert);\n",
+       "    // Render to node\n",
+       "    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
+       "    render(props, toinsert[0]);\n",
+       "    element.append(toinsert);\n",
+       "    return toinsert\n",
+       "  }\n",
+       "\n",
+       "  events.on('output_added.OutputArea', handle_add_output);\n",
+       "  events.on('output_updated.OutputArea', handle_update_output);\n",
+       "  events.on('clear_output.CodeCell', handle_clear_output);\n",
+       "  events.on('delete.Cell', handle_clear_output);\n",
+       "  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
+       "\n",
+       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
+       "    safe: true,\n",
+       "    index: 0\n",
+       "  });\n",
+       "}\n",
+       "\n",
+       "if (window.Jupyter !== undefined) {\n",
+       "  try {\n",
+       "    var events = require('base/js/events');\n",
+       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
+       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
+       "      register_renderer(events, OutputArea);\n",
+       "    }\n",
+       "  } catch(err) {\n",
+       "  }\n",
+       "}\n"
+      ],
+      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        comm.open();\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        }) \n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "  ),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# For searching and accessing NASA data\n",
+    "import earthaccess\n",
+    "\n",
+    "# For reading data, analysis and plotting\n",
+    "import xarray as xr\n",
+    "import hvplot.xarray\n",
+    "\n",
+    "import pprint  # For nice printing of python objects"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cf13e8ff-a256-4108-bc6c-5e20fc8f321c",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "## Authenticate\n",
+    "\n",
+    "The first step is to get the correct authentication to access _cloud-hosted_ ICESat-2 data.  This is all done through Earthdata Login.  The `login` method also gets the correct AWS credentials.\n",
+    "\n",
+    "Login requires your Earthdata Login username and password. The `login` method will automatically search for these credentials as environment variables or in a `.netrc` file, and if those aren't available it will prompt you to enter your username and password. We use the prompt strategy here. A `.netrc` file is a text file located in our home directory that contains login information for remote machines.  If you don't have a `.netrc` file, `login` will create one for you if you use `persist=True`.\n",
+    "\n",
+    "```\n",
+    "earthaccess.login(strategy='interactive', persist=True)\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "dd332b9e-0aca-4c47-9d4e-8d92a48b2e42",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Enter your Earthdata Login username:  amy.steiker\n",
+      "Enter your Earthdata password:  ········\n"
+     ]
+    }
+   ],
+   "source": [
+    "auth = earthaccess.login()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fcd4d20c-71bb-4a49-85c1-d43e7e9eeb3e",
+   "metadata": {
+    "tags": [],
+    "user_expressions": []
+   },
+   "source": [
+    "## Search for ICESat-2 Collections\n",
+    "\n",
+    "`earthaccess` leverages the Common Metadata Repository (CMR) API to search for collections and granules.  [Earthdata Search](https://search.earthdata.nasa.gov/search) also uses the CMR API.\n",
+    "\n",
+    "We can use the `search_datasets` method to search for ICESat-2 collections by setting `keyword=\"ICESat-2\"`.  The argument passed to `keyword` can be any string and can include wildcard characters `?` or `*`.\n",
+    "\n",
+    "```{note}\n",
+    "To see a full list of search parameters you can type `earthaccess.search_datasets?`.  Using `?` after a python object displays the `docstring` for that object.\n",
+    "```\n",
+    "\n",
+    "A count of the number of data collections (Datasets) found is given."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "4b6131f7-0f3c-4227-9301-618f364dcec6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Datasets found: 89\n"
+     ]
+    }
+   ],
+   "source": [
+    "query = earthaccess.search_datasets(\n",
+    "            keyword=\"ICESat-2\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bfd55ecf-6245-4caa-bd7e-903374086827",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "In this case, there are 89 datasets that have the keyword ICESat-2.  \n",
+    "\n",
+    "`search_datasets` returns a python list of `DataCollection` objects.  We can view metadata for each collection in long form by passing a `DataCollection` object to print or as a summary using the `summary` method for the `DataCollection` object.  Here, I use the `pprint` function to _Pretty Print_ each object."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f54b13d9",
+   "metadata": {
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{   'concept-id': 'C2559919423-NSIDC_ECS',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': [   'https://n5eil01u.ecs.nsidc.org/ATLAS/ATL03.006/',\n",
+      "                    'https://search.earthdata.nasa.gov/search?q=ATL03+V006',\n",
+      "                    'http://openaltimetry.org/',\n",
+      "                    'https://nsidc.org/data/data-access-tool/ATL03/versions/6/'],\n",
+      "    'short-name': 'ATL03',\n",
+      "    'version': '006'}\n",
+      "\n",
+      "{   'cloud-info': {   'Region': 'us-west-2',\n",
+      "                      'S3BucketAndObjectPrefixNames': [   'nsidc-cumulus-prod-protected/ATLAS/ATL03/006',\n",
+      "                                                          'nsidc-cumulus-prod-public/ATLAS/ATL03/006'],\n",
+      "                      'S3CredentialsAPIDocumentationURL': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME',\n",
+      "                      'S3CredentialsAPIEndpoint': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentials'},\n",
+      "    'concept-id': 'C2596864127-NSIDC_CPRD',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': ['https://search.earthdata.nasa.gov/search?q=ATL03+V006'],\n",
+      "    'short-name': 'ATL03',\n",
+      "    'version': '006'}\n",
+      "\n",
+      "{   'concept-id': 'C2120512202-NSIDC_ECS',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': [   'https://n5eil01u.ecs.nsidc.org/ATLAS/ATL03.005/',\n",
+      "                    'https://search.earthdata.nasa.gov/search?q=ATL03+V005',\n",
+      "                    'http://openaltimetry.org/',\n",
+      "                    'https://nsidc.org/data/data-access-tool/ATL03/versions/5/'],\n",
+      "    'short-name': 'ATL03',\n",
+      "    'version': '005'}\n",
+      "\n",
+      "{   'cloud-info': {   'Region': 'us-west-2',\n",
+      "                      'S3BucketAndObjectPrefixNames': [   'nsidc-cumulus-prod-protected/ATLAS/ATL03/005',\n",
+      "                                                          'nsidc-cumulus-prod-public/ATLAS/ATL03/005'],\n",
+      "                      'S3CredentialsAPIDocumentationURL': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME',\n",
+      "                      'S3CredentialsAPIEndpoint': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentials'},\n",
+      "    'concept-id': 'C2153572325-NSIDC_CPRD',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': ['https://search.earthdata.nasa.gov/search?q=ATL03+V005'],\n",
+      "    'short-name': 'ATL03',\n",
+      "    'version': '005'}\n",
+      "\n",
+      "{   'concept-id': 'C2564427300-NSIDC_ECS',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': [   'https://n5eil01u.ecs.nsidc.org/ATLAS/ATL06.006/',\n",
+      "                    'https://search.earthdata.nasa.gov/search?q=ATL06+V006',\n",
+      "                    'https://openaltimetry.org/',\n",
+      "                    'https://nsidc.org/data/data-access-tool/ATL06/versions/6/'],\n",
+      "    'short-name': 'ATL06',\n",
+      "    'version': '006'}\n",
+      "\n",
+      "{   'cloud-info': {   'Region': 'us-west-2',\n",
+      "                      'S3BucketAndObjectPrefixNames': [   'nsidc-cumulus-prod-protected/ATLAS/ATL06/006',\n",
+      "                                                          'nsidc-cumulus-prod-public/ATLAS/ATL06/006'],\n",
+      "                      'S3CredentialsAPIDocumentationURL': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME',\n",
+      "                      'S3CredentialsAPIEndpoint': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentials'},\n",
+      "    'concept-id': 'C2670138092-NSIDC_CPRD',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': ['https://search.earthdata.nasa.gov/search?q=ATL06+V006'],\n",
+      "    'short-name': 'ATL06',\n",
+      "    'version': '006'}\n",
+      "\n",
+      "{   'concept-id': 'C2144439155-NSIDC_ECS',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': [   'https://n5eil01u.ecs.nsidc.org/ATLAS/ATL06.005/',\n",
+      "                    'https://search.earthdata.nasa.gov/search?q=ATL06+V005',\n",
+      "                    'https://openaltimetry.org/',\n",
+      "                    'https://nsidc.org/data/data-access-tool/ATL06/versions/5/'],\n",
+      "    'short-name': 'ATL06',\n",
+      "    'version': '005'}\n",
+      "\n",
+      "{   'cloud-info': {   'Region': 'us-west-2',\n",
+      "                      'S3BucketAndObjectPrefixNames': [   'nsidc-cumulus-prod-protected/ATLAS/ATL06/005',\n",
+      "                                                          'nsidc-cumulus-prod-public/ATLAS/ATL06/005'],\n",
+      "                      'S3CredentialsAPIDocumentationURL': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME',\n",
+      "                      'S3CredentialsAPIEndpoint': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentials'},\n",
+      "    'concept-id': 'C2153572614-NSIDC_CPRD',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': ['https://search.earthdata.nasa.gov/search?q=ATL06+V005'],\n",
+      "    'short-name': 'ATL06',\n",
+      "    'version': '005'}\n",
+      "\n",
+      "{   'concept-id': 'C2565090645-NSIDC_ECS',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': [   'https://n5eil01u.ecs.nsidc.org/ATLAS/ATL08.006/',\n",
+      "                    'https://search.earthdata.nasa.gov/search?q=ATL08+V006',\n",
+      "                    'https://openaltimetry.org/',\n",
+      "                    'https://nsidc.org/data/data-access-tool/ATL08/versions/6/'],\n",
+      "    'short-name': 'ATL08',\n",
+      "    'version': '006'}\n",
+      "\n",
+      "{   'cloud-info': {   'Region': 'us-west-2',\n",
+      "                      'S3BucketAndObjectPrefixNames': [   'nsidc-cumulus-prod-protected/ATLAS/ATL08/006',\n",
+      "                                                          'nsidc-cumulus-prod-public/ATLAS/ATL08/006'],\n",
+      "                      'S3CredentialsAPIDocumentationURL': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME',\n",
+      "                      'S3CredentialsAPIEndpoint': 'https://data.nsidc.earthdatacloud.nasa.gov/s3credentials'},\n",
+      "    'concept-id': 'C2613553260-NSIDC_CPRD',\n",
+      "    'file-type': \"[{'FormatType': 'Native', 'Format': 'HDF5', \"\n",
+      "                 \"'FormatDescription': 'HTTPS'}]\",\n",
+      "    'get-data': ['https://search.earthdata.nasa.gov/search?q=ATL08+V006'],\n",
+      "    'short-name': 'ATL08',\n",
+      "    'version': '006'}\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for collection in query[:10]:\n",
+    "    pprint.pprint(collection.summary(), sort_dicts=True, indent=4)\n",
+    "    print('')  # Add a space between collections for readability"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b7e7fbf6-44f3-46df-99c6-5a138c2e7b11",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "For each collection, `summary` returns a subset of fields from the collection metadata and Unified Metadata Model (UMM) entry.\n",
+    "\n",
+    "- `concept-id` is an unique identifier for the collection that is composed of a alphanumeric code and the provider-id for the DAAC.\n",
+    "- `short-name` is the name of the dataset that appears on the dataset set landing page. For ICESat-2, `ShortNames` are generally how different products are referred to.\n",
+    "- `version` is the version of each collection.\n",
+    "- `file-type` gives information about the file format of the collection files.\n",
+    "- `get-data` is a collection of URLs that can be used to access data, dataset landing pages, and tools.  \n",
+    "\n",
+    "For _cloud-hosted_ data, there is additional information about the location of the S3 bucket that holds the data and where to get credentials to access the S3 buckets.  In general, you don't need to worry about this information because `earthaccess` handles S3 credentials for you.  Nevertheless it may be useful for troubleshooting. \n",
+    "\n",
+    "```{note}\n",
+    "In Python, all data are represented by _objects_.  These _objects_ contain both data and methods (think functions) that operate on the data.  `earthaccess` includes  `DataCollection` and `DataGranule` objects that contain data about collections and granules returned by `search_datasets` and `search_data` respectively.  If you are familiar with Python, you will see that the data in each `DataCollection` object is organized as a hierarchy of python dictionaries, lists and strings.  So if you know the dictionary key for the metadata entry you want you can get that metadata using standard dictionary methods.  For example, to get the dataset short name from the example below, you could just use `collection['meta']['concept-id']`.  However, in this example the `concept-id' method for the DataCollection object returns the same information.  Take a look at https://github.com/nsidc/earthaccess/blob/main/earthaccess/results.py#L80 to see how this is done.\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "82f2d885-ea84-44fe-b2d8-cf139562fc70",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "For the ICESat-2 search results the concept-id is `NSIDC_ECS` or `NSIDC_CPRD`. `NSIDC_ECS` is for collections archived at the NSIDC DAAC and `NSIDC_CPRD` is for the _cloud-hosted_ collections. \n",
+    "\n",
+    "For ICESat-2 `short-name` refers to the following products.  \n",
+    "\n",
+    "| ShortName | Product Description |\n",
+    "|:-----------:|:---------------------|\n",
+    "| ATL03 | ATLAS/ICESat-2 L2A Global Geolocated Photon Data |\n",
+    "| ATL06 | ATLAS/ICESat-2 L3A Land Ice Height |\n",
+    "| ATL07 | ATLAS/ICESat-2 L3A Sea Ice Height |\n",
+    "| ATL08 | ATLAS/ICESat-2 L3A Land and Vegetation Height |\n",
+    "| ATL09 | ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics |\n",
+    "| ATL10 | ATLAS/ICESat-2 L3A Sea Ice Freeboard |\n",
+    "| ATL11 | ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series |\n",
+    "| ATL12 | ATLAS/ICESat-2 L3A Ocean Surface Height |\n",
+    "| ATL13 | ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5329bbf6-4530-4dfd-88dd-153a1fb5d862",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "### Search for cloud-hosted data\n",
+    "\n",
+    "If you only want to search for data in the cloud, you can set `cloud_hosted=True`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "322d78c3",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Datasets found: 40\n"
+     ]
+    }
+   ],
+   "source": [
+    "Query = earthaccess.search_datasets(\n",
+    "    keyword = 'ICESat-2',\n",
+    "    cloud_hosted = True,\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "904e589e-4524-4aaa-9c91-8f464c0ccb96",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "## Search a data set using spatial and temporal filters \n",
+    "\n",
+    "Once, you have identified the dataset you want to work with, you can use the `search_data` method to search a data set with spatial and temporal filters. As an example, we'll search for ATL06 granules over the Juneau Icefield, AK, for March and April 2020.\n",
+    "\n",
+    "Either `concept-id` or `short-name` can be used to search for granules from a particular dataset.  If you use `short-name` you also need to set `version`.  If you use `concept-id`, this is all that is required because `concept-id` is unique. \n",
+    "\n",
+    "The temporal range is identified with standard date strings. Latitude-longitude corners of a bounding box are specified as lower left, upper right.  Polygons and points, as well as shapefiles can also be specified.\n",
+    "\n",
+    "This will display the number of granules that match our search. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "5fba5c34",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Granules found: 4\n"
+     ]
+    }
+   ],
+   "source": [
+    "results = earthaccess.search_data(\n",
+    "    short_name = 'ATL06',\n",
+    "    version = '006',\n",
+    "    cloud_hosted = True,\n",
+    "    bounding_box = (-134.7,58.9,-133.9,59.2),\n",
+    "    temporal = ('2020-03-01','2020-04-30'),\n",
+    "    count = 100\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "89147064-a839-4900-beea-9cc5c228ce04",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "We'll get metadata for these 4 granules and display it.  The rendered metadata shows a download link, granule size and two images of the data.\n",
+    "\n",
+    "The download link is `https` and can be used download the granule to your local machine.  This is similar to downloading _DAAC-hosted_ data but in this case the data are coming from the Earthdata Cloud.  For NASA data in the Earthdata Cloud, there is no charge to the user for egress from AWS Cloud servers.  This is not the case for other data in the cloud."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "a04370d3",
+   "metadata": {
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "</style><style>/*\n",
+       " CSS to override bootstrap or define custom styles\n",
+       "*/\n",
+       "\n",
+       ".bootstrap .p {\n",
+       " font-size: 18px;\n",
+       "}\n",
+       "\n",
+       ".bootstrap .pull-right {\n",
+       "    @extend .float-right;\n",
+       "}\n",
+       ".bootstrap .pull-left {\n",
+       "    @extend .float-left;\n",
+       "}\n",
+       "</style>\n",
+       "            </div>\n",
+       "    <div class=\"bootstrap\">\n",
+       "      <div class=\"container-fluid border\">\n",
+       "        <div class=\"row border\">\n",
+       "          <div class=\"col-6\">\n",
+       "            <p><b>Data</b>: <a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01.h5\" target=\"_blank\" class=\"btn btn-secondary btn-sm\">ATL06_20200310121504_11420606_006_01.h5</a><p/>\n",
+       "            <p><b>Size</b>: 3.03 MB</p>\n",
+       "            <p><b>Cloud Hosted</b>: <span>True</span></p>\n",
+       "          </div>\n",
+       "          <div class=\"col-2 offset-sm-3 pull-right\">\n",
+       "            <a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01_BRW.default.default1.jpg\"><img style=\"max-height: 120px;\" src=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01_BRW.default.default1.jpg\" alt=\"Data Preview\"/></a><a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01_BRW.default.default2.jpg\"><img style=\"max-height: 120px;\" src=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01_BRW.default.default2.jpg\" alt=\"Data Preview\"/></a>\n",
+       "          </div>\n",
+       "        </div>\n",
+       "      </div>\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "Collection: {'EntryTitle': 'ATLAS/ICESat-2 L3A Land Ice Height V006'}\n",
+       "Spatial coverage: {'HorizontalSpatialDomain': {'Geometry': {'GPolygons': [{'Boundary': {'Points': [{'Longitude': -134.3399, 'Latitude': 59.03152}, {'Longitude': -134.44371, 'Latitude': 59.03709}, {'Longitude': -134.75456, 'Latitude': 57.4161}, {'Longitude': -134.6551, 'Latitude': 57.41076}, {'Longitude': -134.3399, 'Latitude': 59.03152}]}}]}}}\n",
+       "Temporal coverage: {'RangeDateTime': {'BeginningDateTime': '2020-03-10T12:15:10.646Z', 'EndingDateTime': '2020-03-10T12:15:58.724Z'}}\n",
+       "Size(MB): 3.034775733947754\n",
+       "Data: ['https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01.h5']"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div id=\"6f73314c-2fa7-4595-b6f8-fb40d55bbd96\" style=\"height: 0px; display: none\">\n",
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.alert-info{background-image:-webkit-linear-gradient(top, #d9edf7 0, #b9def0 100%);background-image:-o-linear-gradient(top, #d9edf7 0, #b9def0 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #d9edf7), to(#b9def0));background-image:linear-gradient(to bottom, #d9edf7 0, #b9def0 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9edf7', endColorstr='#ffb9def0', GradientType=0);border-color:#9acfea}.bootstrap .alert-warning{background-image:-webkit-linear-gradient(top, #fcf8e3 0, #f8efc0 100%);background-image:-o-linear-gradient(top, #fcf8e3 0, #f8efc0 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #fcf8e3), to(#f8efc0));background-image:linear-gradient(to bottom, #fcf8e3 0, #f8efc0 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#fffcf8e3', endColorstr='#fff8efc0', GradientType=0);border-color:#f5e79e}.bootstrap .alert-danger{background-image:-webkit-linear-gradient(top, #f2dede 0, #e7c3c3 100%);background-image:-o-linear-gradient(top, #f2dede 0, #e7c3c3 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #f2dede), to(#e7c3c3));background-image:linear-gradient(to bottom, #f2dede 0, #e7c3c3 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff2dede', endColorstr='#ffe7c3c3', GradientType=0);border-color:#dca7a7}.bootstrap .progress{background-image:-webkit-linear-gradient(top, #ebebeb 0, #f5f5f5 100%);background-image:-o-linear-gradient(top, #ebebeb 0, #f5f5f5 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #ebebeb), to(#f5f5f5));background-image:linear-gradient(to bottom, #ebebeb 0, #f5f5f5 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffebebeb', endColorstr='#fff5f5f5', GradientType=0)}.bootstrap .progress-bar{background-image:-webkit-linear-gradient(top, #337ab7 0, #286090 100%);background-image:-o-linear-gradient(top, #337ab7 0, #286090 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #337ab7), to(#286090));background-image:linear-gradient(to bottom, #337ab7 0, #286090 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff337ab7', endColorstr='#ff286090', GradientType=0)}.bootstrap .progress-bar-success{background-image:-webkit-linear-gradient(top, #5cb85c 0, #449d44 100%);background-image:-o-linear-gradient(top, #5cb85c 0, #449d44 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #5cb85c), to(#449d44));background-image:linear-gradient(to bottom, #5cb85c 0, #449d44 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5cb85c', endColorstr='#ff449d44', GradientType=0)}.bootstrap .progress-bar-info{background-image:-webkit-linear-gradient(top, #5bc0de 0, #31b0d5 100%);background-image:-o-linear-gradient(top, #5bc0de 0, #31b0d5 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #5bc0de), to(#31b0d5));background-image:linear-gradient(to bottom, #5bc0de 0, #31b0d5 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5bc0de', endColorstr='#ff31b0d5', GradientType=0)}.bootstrap .progress-bar-warning{background-image:-webkit-linear-gradient(top, #f0ad4e 0, #ec971f 100%);background-image:-o-linear-gradient(top, #f0ad4e 0, #ec971f 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #f0ad4e), to(#ec971f));background-image:linear-gradient(to bottom, #f0ad4e 0, #ec971f 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff0ad4e', endColorstr='#ffec971f', GradientType=0)}.bootstrap .progress-bar-danger{background-image:-webkit-linear-gradient(top, #d9534f 0, #c9302c 100%);background-image:-o-linear-gradient(top, #d9534f 0, #c9302c 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #d9534f), to(#c9302c));background-image:linear-gradient(to bottom, #d9534f 0, #c9302c 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9534f', endColorstr='#ffc9302c', GradientType=0)}.bootstrap .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)}.bootstrap .list-group{border-radius:4px;-webkit-box-shadow:0 1px 2px rgba(0, 0, 0, 0.075);box-shadow:0 1px 2px rgba(0, 0, 0, 0.075)}.bootstrap .list-group-item.active,.bootstrap .list-group-item.active:hover,.bootstrap .list-group-item.active:focus{text-shadow:0 -1px 0 #286090;background-image:-webkit-linear-gradient(top, #337ab7 0, #2b669a 100%);background-image:-o-linear-gradient(top, #337ab7 0, #2b669a 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #337ab7), to(#2b669a));background-image:linear-gradient(to bottom, #337ab7 0, #2b669a 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff337ab7', endColorstr='#ff2b669a', GradientType=0);border-color:#2b669a}.bootstrap .list-group-item.active .badge,.bootstrap .list-group-item.active:hover .badge,.bootstrap .list-group-item.active:focus .badge{text-shadow:none}.bootstrap .panel{-webkit-box-shadow:0 1px 2px rgba(0, 0, 0, 0.05);box-shadow:0 1px 2px rgba(0, 0, 0, 0.05)}.bootstrap .panel-default > .panel-heading{background-image:-webkit-linear-gradient(top, #f5f5f5 0, #e8e8e8 100%);background-image:-o-linear-gradient(top, #f5f5f5 0, #e8e8e8 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #f5f5f5), to(#e8e8e8));background-image:linear-gradient(to bottom, #f5f5f5 0, #e8e8e8 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff5f5f5', endColorstr='#ffe8e8e8', GradientType=0)}.bootstrap .panel-primary > .panel-heading{background-image:-webkit-linear-gradient(top, #337ab7 0, #2e6da4 100%);background-image:-o-linear-gradient(top, #337ab7 0, #2e6da4 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #337ab7), to(#2e6da4));background-image:linear-gradient(to bottom, #337ab7 0, #2e6da4 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100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9edf7', endColorstr='#ffc4e3f3', GradientType=0)}.bootstrap .panel-warning > .panel-heading{background-image:-webkit-linear-gradient(top, #fcf8e3 0, #faf2cc 100%);background-image:-o-linear-gradient(top, #fcf8e3 0, #faf2cc 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #fcf8e3), to(#faf2cc));background-image:linear-gradient(to bottom, #fcf8e3 0, #faf2cc 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#fffcf8e3', endColorstr='#fffaf2cc', GradientType=0)}.bootstrap .panel-danger > .panel-heading{background-image:-webkit-linear-gradient(top, #f2dede 0, #ebcccc 100%);background-image:-o-linear-gradient(top, #f2dede 0, #ebcccc 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #f2dede), to(#ebcccc));background-image:linear-gradient(to bottom, #f2dede 0, #ebcccc 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff2dede', endColorstr='#ffebcccc', GradientType=0)}.bootstrap .well{background-image:-webkit-linear-gradient(top, #e8e8e8 0, #f5f5f5 100%);background-image:-o-linear-gradient(top, #e8e8e8 0, #f5f5f5 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #e8e8e8), to(#f5f5f5));background-image:linear-gradient(to bottom, #e8e8e8 0, #f5f5f5 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffe8e8e8', endColorstr='#fff5f5f5', GradientType=0);border-color:#dcdcdc;-webkit-box-shadow:inset 0 1px 3px rgba(0, 0, 0, 0.05), 0 1px 0 rgba(255, 255, 255, 0.1);box-shadow:inset 0 1px 3px rgba(0, 0, 0, 0.05), 0 1px 0 rgba(255, 255, 255, 0.1)}\n",
+       "</style><style>/*\n",
+       " CSS to override bootstrap or define custom styles\n",
+       "*/\n",
+       "\n",
+       ".bootstrap .p {\n",
+       " font-size: 18px;\n",
+       "}\n",
+       "\n",
+       ".bootstrap .pull-right {\n",
+       "    @extend .float-right;\n",
+       "}\n",
+       ".bootstrap .pull-left {\n",
+       "    @extend .float-left;\n",
+       "}\n",
+       "</style>\n",
+       "            </div>\n",
+       "    <div class=\"bootstrap\">\n",
+       "      <div class=\"container-fluid border\">\n",
+       "        <div class=\"row border\">\n",
+       "          <div class=\"col-6\">\n",
+       "            <p><b>Data</b>: <a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01.h5\" target=\"_blank\" class=\"btn btn-secondary btn-sm\">ATL06_20200312233336_11800602_006_01.h5</a><p/>\n",
+       "            <p><b>Size</b>: 29.99 MB</p>\n",
+       "            <p><b>Cloud Hosted</b>: <span>True</span></p>\n",
+       "          </div>\n",
+       "          <div class=\"col-2 offset-sm-3 pull-right\">\n",
+       "            <a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01_BRW.default.default1.jpg\"><img style=\"max-height: 120px;\" src=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01_BRW.default.default1.jpg\" alt=\"Data Preview\"/></a><a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01_BRW.default.default2.jpg\"><img style=\"max-height: 120px;\" src=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01_BRW.default.default2.jpg\" alt=\"Data Preview\"/></a>\n",
+       "          </div>\n",
+       "        </div>\n",
+       "      </div>\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "Collection: {'EntryTitle': 'ATLAS/ICESat-2 L3A Land Ice Height V006'}\n",
+       "Spatial coverage: {'HorizontalSpatialDomain': {'Geometry': {'GPolygons': [{'Boundary': {'Points': [{'Longitude': -134.41459, 'Latitude': 59.54887}, {'Longitude': -134.63538, 'Latitude': 59.53739}, {'Longitude': -134.59212, 'Latitude': 59.32438}, {'Longitude': -134.2125, 'Latitude': 57.38652}, {'Longitude': -133.7114, 'Latitude': 54.60434}, {'Longitude': -133.55731, 'Latitude': 53.68969}, {'Longitude': -133.36771, 'Latitude': 53.70055}, {'Longitude': -133.5178, 'Latitude': 54.61543}, {'Longitude': -134.00456, 'Latitude': 57.3981}, {'Longitude': -134.37249, 'Latitude': 59.33607}, {'Longitude': -134.41459, 'Latitude': 59.54887}]}}]}}}\n",
+       "Temporal coverage: {'RangeDateTime': {'BeginningDateTime': '2020-03-12T23:40:36.093Z', 'EndingDateTime': '2020-03-12T23:42:07.293Z'}}\n",
+       "Size(MB): 29.99279499053955\n",
+       "Data: ['https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01.h5']"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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+       "</style><style>/*\n",
+       " CSS to override bootstrap or define custom styles\n",
+       "*/\n",
+       "\n",
+       ".bootstrap .p {\n",
+       " font-size: 18px;\n",
+       "}\n",
+       "\n",
+       ".bootstrap .pull-right {\n",
+       "    @extend .float-right;\n",
+       "}\n",
+       ".bootstrap .pull-left {\n",
+       "    @extend .float-left;\n",
+       "}\n",
+       "</style>\n",
+       "            </div>\n",
+       "    <div class=\"bootstrap\">\n",
+       "      <div class=\"container-fluid border\">\n",
+       "        <div class=\"row border\">\n",
+       "          <div class=\"col-6\">\n",
+       "            <p><b>Data</b>: <a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02.h5\" target=\"_blank\" class=\"btn btn-secondary btn-sm\">ATL06_20200410220936_02350702_006_02.h5</a><p/>\n",
+       "            <p><b>Size</b>: 32.95 MB</p>\n",
+       "            <p><b>Cloud Hosted</b>: <span>True</span></p>\n",
+       "          </div>\n",
+       "          <div class=\"col-2 offset-sm-3 pull-right\">\n",
+       "            <a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02_BRW.default.default1.jpg\"><img style=\"max-height: 120px;\" src=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02_BRW.default.default1.jpg\" alt=\"Data Preview\"/></a><a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02_BRW.default.default2.jpg\"><img style=\"max-height: 120px;\" src=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02_BRW.default.default2.jpg\" alt=\"Data Preview\"/></a>\n",
+       "          </div>\n",
+       "        </div>\n",
+       "      </div>\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "Collection: {'EntryTitle': 'ATLAS/ICESat-2 L3A Land Ice Height V006'}\n",
+       "Spatial coverage: {'HorizontalSpatialDomain': {'Geometry': {'GPolygons': [{'Boundary': {'Points': [{'Longitude': -134.28339, 'Latitude': 59.54228}, {'Longitude': -134.50433, 'Latitude': 59.53072}, {'Longitude': -134.46626, 'Latitude': 59.34436}, {'Longitude': -133.988, 'Latitude': 56.87365}, {'Longitude': -133.46142, 'Latitude': 53.88745}, {'Longitude': -133.34478, 'Latitude': 53.18986}, {'Longitude': -133.15724, 'Latitude': 53.20085}, {'Longitude': -133.27098, 'Latitude': 53.8986}, {'Longitude': -133.78272, 'Latitude': 56.88519}, {'Longitude': -134.24631, 'Latitude': 59.35609}, {'Longitude': -134.28339, 'Latitude': 59.54228}]}}]}}}\n",
+       "Temporal coverage: {'RangeDateTime': {'BeginningDateTime': '2020-04-10T22:16:27.813Z', 'EndingDateTime': '2020-04-10T22:18:06.791Z'}}\n",
+       "Size(MB): 32.94972229003906\n",
+       "Data: ['https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02.h5']"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div id=\"e6f50b4a-ed75-4088-a9c5-58535d1c7a47\" style=\"height: 0px; display: none\">\n",
+       "            <style>.bootstrap{font-family:sans-serif;line-height:1;-ms-text-size-adjust:100%;-webkit-text-size-adjust:100%}.bootstrap{margin:0;font-size:10px;}.bootstrap article,.bootstrap aside,.bootstrap footer,.bootstrap header,.bootstrap nav,.bootstrap section{display:block}.bootstrap h1{font-size:2em;margin:0.67em 0}.bootstrap figcaption,.bootstrap figure,.bootstrap main{display:block}.bootstrap figure{margin:1em 40px}.bootstrap hr{-webkit-box-sizing:content-box;box-sizing:content-box;height:0;overflow:visible}.bootstrap pre{font-family:monospace,monospace;font-size:1em}.bootstrap a{background-color:transparent;-webkit-text-decoration-skip:objects}.bootstrap a:active,.bootstrap a:hover{outline-width:0}.bootstrap abbr[title]{border-bottom:none;text-decoration:underline;text-decoration:underline dotted}.bootstrap b,.bootstrap strong{font-weight:inherit}.bootstrap b,.bootstrap strong{font-weight:bolder}.bootstrap code,.bootstrap kbd,.bootstrap 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.badge{text-shadow:none}.bootstrap .panel{-webkit-box-shadow:0 1px 2px rgba(0, 0, 0, 0.05);box-shadow:0 1px 2px rgba(0, 0, 0, 0.05)}.bootstrap .panel-default > .panel-heading{background-image:-webkit-linear-gradient(top, #f5f5f5 0, #e8e8e8 100%);background-image:-o-linear-gradient(top, #f5f5f5 0, #e8e8e8 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #f5f5f5), to(#e8e8e8));background-image:linear-gradient(to bottom, #f5f5f5 0, #e8e8e8 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff5f5f5', endColorstr='#ffe8e8e8', GradientType=0)}.bootstrap .panel-primary > .panel-heading{background-image:-webkit-linear-gradient(top, #337ab7 0, #2e6da4 100%);background-image:-o-linear-gradient(top, #337ab7 0, #2e6da4 100%);background-image:-webkit-gradient(linear, left top, left bottom, color-stop(0, #337ab7), to(#2e6da4));background-image:linear-gradient(to bottom, #337ab7 0, #2e6da4 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+       "</style><style>/*\n",
+       " CSS to override bootstrap or define custom styles\n",
+       "*/\n",
+       "\n",
+       ".bootstrap .p {\n",
+       " font-size: 18px;\n",
+       "}\n",
+       "\n",
+       ".bootstrap .pull-right {\n",
+       "    @extend .float-right;\n",
+       "}\n",
+       ".bootstrap .pull-left {\n",
+       "    @extend .float-left;\n",
+       "}\n",
+       "</style>\n",
+       "            </div>\n",
+       "    <div class=\"bootstrap\">\n",
+       "      <div class=\"container-fluid border\">\n",
+       "        <div class=\"row border\">\n",
+       "          <div class=\"col-6\">\n",
+       "            <p><b>Data</b>: <a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02.h5\" target=\"_blank\" class=\"btn btn-secondary btn-sm\">ATL06_20200412104246_02580706_006_02.h5</a><p/>\n",
+       "            <p><b>Size</b>: 20.34 MB</p>\n",
+       "            <p><b>Cloud Hosted</b>: <span>True</span></p>\n",
+       "          </div>\n",
+       "          <div class=\"col-2 offset-sm-3 pull-right\">\n",
+       "            <a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02_BRW.default.default1.jpg\"><img style=\"max-height: 120px;\" src=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02_BRW.default.default1.jpg\" alt=\"Data Preview\"/></a><a href=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02_BRW.default.default2.jpg\"><img style=\"max-height: 120px;\" src=\"https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02_BRW.default.default2.jpg\" alt=\"Data Preview\"/></a>\n",
+       "          </div>\n",
+       "        </div>\n",
+       "      </div>\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "Collection: {'EntryTitle': 'ATLAS/ICESat-2 L3A Land Ice Height V006'}\n",
+       "Spatial coverage: {'HorizontalSpatialDomain': {'Geometry': {'GPolygons': [{'Boundary': {'Points': [{'Longitude': -134.62761, 'Latitude': 59.53143}, {'Longitude': -134.84844, 'Latitude': 59.54238}, {'Longitude': -134.8761, 'Latitude': 59.3961}, {'Longitude': -135.19822, 'Latitude': 57.71464}, {'Longitude': -135.43039, 'Latitude': 56.42147}, {'Longitude': -135.46534, 'Latitude': 56.22639}, {'Longitude': -135.26355, 'Latitude': 56.21509}, {'Longitude': -135.22779, 'Latitude': 56.41013}, {'Longitude': -134.98845, 'Latitude': 57.70329}, {'Longitude': -134.65611, 'Latitude': 59.38441}, {'Longitude': -134.62761, 'Latitude': 59.53143}]}}]}}}\n",
+       "Temporal coverage: {'RangeDateTime': {'BeginningDateTime': '2020-04-12T10:42:46.111Z', 'EndingDateTime': '2020-04-12T10:43:37.436Z'}}\n",
+       "Size(MB): 20.340317726135254\n",
+       "Data: ['https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02.h5']"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[None, None, None, None]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "[display(r) for r in results]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "944dc900-02c7-43fa-bef8-12d91b566195",
+   "metadata": {
+    "tags": [],
+    "user_expressions": []
+   },
+   "source": [
+    "## Use Direct-Access to open, load and display data stored on S3\n",
+    "\n",
+    "Direct-access to data from an S3 bucket is a two step process.  First, the files are opened using the `open` method.  This first step creates a Python file-like object that is used to load the data in the second step.  \n",
+    "\n",
+    "Authentication is required for this step.  The `auth` object created at the start of the notebook is used to provide Earthdata Login authentication and AWS credentials \"_behind-the-scenes_\". These credentials expire after one hour so the `auth` object must be executed within that time window prior to these next steps. \n",
+    "\n",
+    "```{note}\n",
+    "The `open` step to create a file-like object is required because AWS S3, and other cloud storage systems, use  object storage but most HDF5 libraries work with POSIX-compliant file systems.  POSIX stands for Portable Operating System Interface for Unix and is a set of guidelines that include how to interact with files and file systems.  Linux, Unix, MacOS (which is Unix-like), and Windows are POSIX-compliant. Critically, POSIX-compliant systems allows blocks of bytes or individual bytes to be read from a file. With object storage the whole file has to be read. To get around this limitation, an intermediary is used, in this case `s3fs`.  This intermediary creates a local POSIX-compliant virtual file system.  S3 objects are loaded into this virtual file system so they can be accessed using POSIX-style file functions.\n",
+    "```\n",
+    "\n",
+    "In this example, data are loaded into an `xarray.Dataset`.  Data could be read into `numpy` arrays or a `pandas.Dataframe`.  However, each granule would have to be read using a package that reads HDF5 granules such as `h5py`.  `xarray` does this all _under-the-hood_ in a single line but only for a single group in the HDF5 granule, in this case land ice heights for the gt1l beam*.\n",
+    "\n",
+    "*ICESat-2 measures photon returns from 3 beam pairs numbered 1, 2 and 3 that each consist of a left and a right beam"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "11205bbb",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 2 µs, sys: 0 ns, total: 2 µs\n",
+      "Wall time: 6.2 µs\n",
+      "Opening 4 granules, approx size: 0.08 GB\n",
+      "using provider: NSIDC_CPRD\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3c8c4ebd847d4d708af8dc46d11750d8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "QUEUEING TASKS | : 0it [00:00, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "835ab9a1db8c47e894d90db6c247eb36",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "PROCESSING TASKS | :   0%|          | 0/4 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "71b19709cfc14756bc2be85c201b874f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "COLLECTING RESULTS | :   0%|          | 0/4 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%time\n",
+    "files = earthaccess.open(results)\n",
+    "ds = xr.open_dataset(files[1], group='/gt1l/land_ice_segments')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "75881751",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
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+       "\n",
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+       "\n",
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+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
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+       ".xr-index-name div,\n",
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+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
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+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
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+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
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+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
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+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
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+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
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+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:                (delta_time: 24471)\n",
+       "Coordinates:\n",
+       "  * delta_time             (delta_time) datetime64[ns] 2020-03-12T23:40:48.24...\n",
+       "    latitude               (delta_time) float64 ...\n",
+       "    longitude              (delta_time) float64 ...\n",
+       "Data variables:\n",
+       "    atl06_quality_summary  (delta_time) int8 ...\n",
+       "    h_li                   (delta_time) float32 ...\n",
+       "    h_li_sigma             (delta_time) float32 ...\n",
+       "    segment_id             (delta_time) float64 ...\n",
+       "    sigma_geo_h            (delta_time) float32 ...\n",
+       "Attributes:\n",
+       "    Description:  The land_ice_height group contains the primary set of deriv...\n",
+       "    data_rate:    Data within this group are sparse.  Data values are provide...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6334c5b9-3fde-4db6-bead-f8973ff0811a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6334c5b9-3fde-4db6-bead-f8973ff0811a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>delta_time</span>: 24471</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-eb5402d7-c7d4-4d0e-9bb0-bd7710f46308' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eb5402d7-c7d4-4d0e-9bb0-bd7710f46308' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>delta_time</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-03-12T23:40:48.240324376 .....</div><input id='attrs-0d81d9fc-12e2-43ed-9f76-123301b9462e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d81d9fc-12e2-43ed-9f76-123301b9462e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2bb2663-ebcd-4a21-b5eb-952c7d3bd154' class='xr-var-data-in' type='checkbox'><label for='data-a2bb2663-ebcd-4a21-b5eb-952c7d3bd154' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Number of GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds relative to the GPS epoch can be computed.</dd><dt><span>long_name :</span></dt><dd>Elapsed GPS seconds</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-03-12T23:40:48.240324376&#x27;, &#x27;2020-03-12T23:40:48.243204864&#x27;,\n",
+       "       &#x27;2020-03-12T23:40:48.248890800&#x27;, ..., &#x27;2020-03-12T23:42:06.944719032&#x27;,\n",
+       "       &#x27;2020-03-12T23:42:06.947529672&#x27;, &#x27;2020-03-12T23:42:06.950340312&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-47202956-385b-4a79-9cb4-9b3cc2decb96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47202956-385b-4a79-9cb4-9b3cc2decb96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1c33f5b-feaa-4f59-8171-6ad218828e98' class='xr-var-data-in' type='checkbox'><label for='data-b1c33f5b-feaa-4f59-8171-6ad218828e98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Latitude of segment center, WGS84, North=+,</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>source :</span></dt><dd>section 3.10</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-42f5b4aa-f0bf-4b51-9cf8-ec93820f4c8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42f5b4aa-f0bf-4b51-9cf8-ec93820f4c8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7889b745-a812-4f52-9568-1cfff0fd6f74' class='xr-var-data-in' type='checkbox'><label for='data-7889b745-a812-4f52-9568-1cfff0fd6f74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Longitude of segment center, , WGS84, East=+</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>source :</span></dt><dd>section 3.10</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-92445bd3-7193-4da5-a939-fa9bc3d0d248' class='xr-section-summary-in' type='checkbox'  checked><label for='section-92445bd3-7193-4da5-a939-fa9bc3d0d248' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>atl06_quality_summary</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d68c8585-43a0-4a5c-9f4c-a9c2b5f1d084' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d68c8585-43a0-4a5c-9f4c-a9c2b5f1d084' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ef6af10-a70b-4628-a501-a53f087d156d' class='xr-var-data-in' type='checkbox'><label for='data-3ef6af10-a70b-4628-a501-a53f087d156d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>qualityInformation</dd><dt><span>description :</span></dt><dd>The ATL06_quality_summary parameter indicates the best-quality subset of all ATL06 data. A zero in this parameter implies that no data-quality tests have found a problem with the segment, a one implies that some potential problem has been found. Users who select only segments with zero values for this flag can be relatively certain of obtaining high-quality data, but will likely miss a significant fraction of usable data, particularly in cloudy, rough, or low-surface-reflectance conditions.</dd><dt><span>flag_meanings :</span></dt><dd>best_quality potential_problem</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>long_name :</span></dt><dd>ATL06_Quality_Summary</dd><dt><span>source :</span></dt><dd>section 4.3</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>1</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=int8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_li</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9afaeaa2-4bba-4afd-9000-c243b15b2090' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9afaeaa2-4bba-4afd-9000-c243b15b2090' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69c90a13-5d06-4c33-b019-96979184f9e7' class='xr-var-data-in' type='checkbox'><label for='data-69c90a13-5d06-4c33-b019-96979184f9e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Standard land-ice segment height determined by land ice algorithm, corrected for first-photon bias, representing the median- based height of the selected PEs</dd><dt><span>long_name :</span></dt><dd>Land Ice height</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_li_sigma</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-17493af2-723b-42f0-8597-bf1e60515e40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17493af2-723b-42f0-8597-bf1e60515e40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a7d97da-2111-4c29-9b26-bcca1bfeff47' class='xr-var-data-in' type='checkbox'><label for='data-0a7d97da-2111-4c29-9b26-bcca1bfeff47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>qualityInformation</dd><dt><span>description :</span></dt><dd>Propagated error due to sampling error and FPB correction from the land ice algorithm</dd><dt><span>long_name :</span></dt><dd>Expected RMS segment misfit</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>segment_id</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-be1133f5-a7d6-41e7-823d-b23bab900217' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be1133f5-a7d6-41e7-823d-b23bab900217' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa0ae650-56de-4068-97fb-6a755702f05f' class='xr-var-data-in' type='checkbox'><label for='data-fa0ae650-56de-4068-97fb-6a755702f05f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Segment number, counting from the equator. Equal to the segment_id for the second of the two 20m ATL03 segments included in the 40m ATL06 segment</dd><dt><span>long_name :</span></dt><dd>Reference Point, m</dd><dt><span>source :</span></dt><dd>section 3.1.2.1</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma_geo_h</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8fbdf6ed-9905-4c18-afa7-60ddb0595a89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fbdf6ed-9905-4c18-afa7-60ddb0595a89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecaabd76-10d8-4cac-ba57-08a8e700a9ff' class='xr-var-data-in' type='checkbox'><label for='data-ecaabd76-10d8-4cac-ba57-08a8e700a9ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>qualityInformation</dd><dt><span>description :</span></dt><dd>Total vertical geolocation error due to PPD and POD, including the effects of horizontal geolocation error on the segment vertical error.</dd><dt><span>long_name :</span></dt><dd>Vertical Geolocation Error</dd><dt><span>source :</span></dt><dd>ATBD Section 3.10</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2d739679-1b1d-4713-bf3e-43c723e75a4a' class='xr-section-summary-in' type='checkbox'  ><label for='section-2d739679-1b1d-4713-bf3e-43c723e75a4a' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>delta_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d1db6856-cd89-4a5b-82e5-d608a07359c7' class='xr-index-data-in' type='checkbox'/><label for='index-d1db6856-cd89-4a5b-82e5-d608a07359c7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-03-12 23:40:48.240324376&#x27;,\n",
+       "               &#x27;2020-03-12 23:40:48.243204864&#x27;,\n",
+       "               &#x27;2020-03-12 23:40:48.248890800&#x27;,\n",
+       "               &#x27;2020-03-12 23:40:48.251708224&#x27;,\n",
+       "               &#x27;2020-03-12 23:40:48.254545184&#x27;,\n",
+       "               &#x27;2020-03-12 23:40:48.259401024&#x27;,\n",
+       "               &#x27;2020-03-12 23:40:48.697626680&#x27;,\n",
+       "               &#x27;2020-03-12 23:40:48.707952856&#x27;,\n",
+       "               &#x27;2020-03-12 23:40:48.710775896&#x27;,\n",
+       "               &#x27;2020-03-12 23:40:48.713604360&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2020-03-12 23:42:06.925044328&#x27;,\n",
+       "               &#x27;2020-03-12 23:42:06.927867648&#x27;,\n",
+       "               &#x27;2020-03-12 23:42:06.930687608&#x27;,\n",
+       "               &#x27;2020-03-12 23:42:06.933504432&#x27;,\n",
+       "               &#x27;2020-03-12 23:42:06.936302200&#x27;,\n",
+       "               &#x27;2020-03-12 23:42:06.939099968&#x27;,\n",
+       "               &#x27;2020-03-12 23:42:06.941909704&#x27;,\n",
+       "               &#x27;2020-03-12 23:42:06.944719032&#x27;,\n",
+       "               &#x27;2020-03-12 23:42:06.947529672&#x27;,\n",
+       "               &#x27;2020-03-12 23:42:06.950340312&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;delta_time&#x27;, length=24471, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-92b7f673-adf0-4318-af8a-68528a442b82' class='xr-section-summary-in' type='checkbox'  checked><label for='section-92b7f673-adf0-4318-af8a-68528a442b82' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Description :</span></dt><dd>The land_ice_height group contains the primary set of derived ATL06 products. This includes geolocation, height, and standard error and quality measures for each segment. This group is sparse, meaning that parameters are provided only for pairs of segments for which at least one beam has a valid surface-height measurement.</dd><dt><span>data_rate :</span></dt><dd>Data within this group are sparse.  Data values are provided only for those ICESat-2 20m segments where at least one beam has a valid land ice height measurement.</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:                (delta_time: 24471)\n",
+       "Coordinates:\n",
+       "  * delta_time             (delta_time) datetime64[ns] 2020-03-12T23:40:48.24...\n",
+       "    latitude               (delta_time) float64 ...\n",
+       "    longitude              (delta_time) float64 ...\n",
+       "Data variables:\n",
+       "    atl06_quality_summary  (delta_time) int8 ...\n",
+       "    h_li                   (delta_time) float32 ...\n",
+       "    h_li_sigma             (delta_time) float32 ...\n",
+       "    segment_id             (delta_time) float64 ...\n",
+       "    sigma_geo_h            (delta_time) float32 ...\n",
+       "Attributes:\n",
+       "    Description:  The land_ice_height group contains the primary set of deriv...\n",
+       "    data_rate:    Data within this group are sparse.  Data values are provide..."
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0a261535-692b-4e3a-af1f-e7316b7f9084",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "`hvplot` is an interactive plotting tool that is useful for exploring data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "be7386c3",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {},
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='p1002'>\n",
+       "  <div id=\"f18ad8ea-95ea-4ab6-98e8-a37bd6fcafa9\" data-root-id=\"p1002\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
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UeBbZgwMMLf2AFtmDAgG/KoQW2YMCg9k3iBbZgwIP6cCIGtmDAjD2CYga2YMBSlbmiBrZgwHE0NuMGtmDAWCzjIwe2YMBpHCZlB7ZgwMnJIqcHtmDAVE+T6Qe2YMCrWeArCLZgwKIB0W0ItmDApOxGrwi2YMDqlETwCLZgwOMBbDAJtmDARaMhbwm2YMCKhAatCbZgwAXgvOoJtmDAb3gKIwq2YMD8Kj1gCrZgwMs9Y6UKtmDAkmnV5Aq2YMAmIpElC7ZgwJ4JaGcLtmDAoTqgqQu2YMBAo+XrC7ZgwDbQGi4MtmDAZmMkcAy2YMDfbcSxDLZgwH8ia/IMtmDAwLdFMg22YMCJEDp/DrZgwPcAObENtmDAb+nnCg+2YMAvvbJwDrZgwFAWij4QtmDAGTq7hRC2YMAyw3nMELZgwC2TJA8RtmDAH4Q4EhC2YMAT1TNbELZgwP/cf+QQtmDAw3hNMxK2YMCVU22wEbZgwIXtY7YStmDAInOU+BK2YMBb1M87E7ZgwI+r2n8TtmDAy8GovhO2YMCKQ2YFFLZgwP49dUwUtmDAOFA0kBS2YMChTE/vE7ZgwF0udTIUtmDAmP+PVxW2YMAON9aYFbZgwII7i1gVtmDAydLT3BW2YMDsAVomFrZgwBa/uxgWtmDAdNwxVxa2YMBNVEiVFrZgwKnMOtMWtmDA2cxBERe2YMARaWtPF7ZgwKjK+I0XtmDAAkyQzRe2YMB74IcNGLZgwAG7GE4YtmDAz4QHjxi2YMAERnLQGLZgwJpjShIZtmDAUj8+VBm2YMCYIUOWGbZgwE5viNgZtmDAsi0/Gxq2YMCP2VZeGrZgwCDlwaEatmDAT7pg5Rq2YMBh42opG7ZgwHSaFG4btmDAaJHQshu2YMDZ6h73G7ZgwBtl5DoctmDAbpoCfhy2YMCRPW/AHLZgwEKQyQEdtmDAXxlWQR22YMAQFgaBHbZgwITMu78dtmDAEXRI/h22YMBhods8HrZgwJGbtXsetmDAC1IEux62YMCZuFj7HrZgwCNghzwftmDAA2pufh+2YMCPZ/fAH7ZgwPYeLQQgtmDA2LcUSCC2YMDCQGCMILZgwG69BtEgtmDAlSTaFSG2YMA1EsRaIbZgwPYoq58htmDArlJy5CG2YMCWsRQpIrZgwOY3fm0itmDA4P9ssSK2YMD7nPH0IrZgwBsCEjgjtmDAo8DdeiO2YMD9cCa9I7ZgwODHEv8jtmDAbCybQCS2YMBRY/+BJLZgwKULUMMktmDABWYtBCW2YMAsVrhEJbZgwCpyA4UltmDAMt0ixSW2YMDRewMFJrZgwG4hg0QmtmDAr2ungya2YMB/ry7DJrZgwP5eUgMntmDA4OhhRCe2YMC0SYqGJ7ZgwN2Jo8kntmDAm1BcDii2YMB8e8tUKLZgwPadn+EqtmDA/RN14yi2YMCZeLkqKbZgwBTDpHEptmDANJ/Utym2YMBdMNz8KbZgwMI2/T8qtmDA4bxygiq2YMBr7QvEKrZgwI8acwUrtmDAkU+3Riu2YMCBigGIK7ZgwHUqxMkrtmDArEdBDCy2YMABgzJPLLZgwHFLPZIstmDA5yQ61Sy2YMA/ZAEYLbZgwBQSrFottmDAe5LOnC22YMDm7kfeLbZgwDESbh8utmDA6zy+YC62YMDInmSiLrZgwHsuueQutmDAhrqjJy+2YMDp7F5rL7ZgwK80dbAvtmDAcOJi9i+2YMD7jtI8MLZgwDt9coMwtmDA9Z0LyjC2YMCJjmwQMbZgwEVzdFYxtmDAYVvHmzG2YMCu9obgMbZgwDy1nSQytmDAf1hgaDK2YMD3ur+rMrZgwOs25u4ytmDAiZ/lMTO2YMAYmtF0M7ZgwBFNsLcztmDAfmq++jO2YMA15Ak+NLZgwEtHjYE0tmDACQh8xTS2YMDhSaEJNbZgwJPIXk41tmDAtl2akzW2YMA94ebYNbZgwLQAIR42tmDAj+stYza2YMCJIfynNrZgwBBoiOw2tmDAAE5xMDe2YMAbPoJzN7ZgwO8GmLY3tmDAMZjt+Te2YMAJZLs9OLZgwAO26YE4tmDA8DOkxji2YMBnQrsMObZgwOfp4VM5tmDAVjIxmzm2YMC460jiObZgwAe65Cg6tmDAFDfHbjq2YMAw8tezOrZgwMcFaPc6tmDAB/tHOTu2YMDx4WR6O7ZgwIu3Jrs7tmDALdjm+zu2YMCLZfg8PLZgwDyGqH48tmDABL5RwTy2YMBaB28FPbZgwEaPeEo9tmDARsNFkD22YMArK77WPbZgwIuz2B0+tmDAx7BfZT62YMATjButPrZgwEaWy/Q+tmDA+t9pPD+2YMB9iAiEP7ZgwOIioss/tmDAKy+zEkC2YMA+sazHQrZgwJcwKKFAtmDAe7v650C2YMDfW3guQbZgwPSifHRBtmDAsBi/uUG2YMBkIWz+QbZgwIn+ZEJCtmDA2laHhUK2YMDq3g3IQrZgwNdsSgpDtmDAlRPCKUa2YMBvsbN/VrZgwOQW78tUtmDAVTXWElW2YMD5OrxZVbZgwMQYaaBVtmDAfr5v5lW2YMANsRYsVrZgwFfqkHFWtmDAWAL1tla2YMDyzED8VrZgwEKPgUFXtmDABSrLhle2YMDYzj3MV7ZgwJoEvhFYtmDAXKY1V1i2YMDQUBOcWLZgwFlIteBYtmDAHLrwJFm2YMB7UY5oWbZgwIhpqqtZtmDAUBpB7lm2YMAq6H0wWrZgwFJni3JatmDAczKLtFq2YMB/U5T2WrZgwIxe1jhbtmDAXAFFe1u2YMCblh6+W7ZgwJDNaAFctmDATlluRVy2YMBrgu+JXLZgwObdjJ5etmDAUAKrVF62YMC8FhFIYLZgwNEFnXBftmDAzOMStl+2YMC5m9b6X7ZgwF/lsj5gtmDAe9sihGC2YMDSJ3OsYLZgwLyNdwdhtmDAYAqGXmG2YMBqNnmVYbZgwLvONcVhtmDA74VlMmO2YMCBoYd3Y7ZgwP6DZUditmDAhvLjdWK2YMDPoD+4YrZgwESjMvpitmDAquGrO2O2YMDYeSJ9Y7ZgwPAmNr9jtmDAa8wIAmS2YMAKaJZFZLZgwCAI84lktmDACYfIz2S2YMDUVBsXZbZgwFut5l5ltmDAC4xQp2W2YMCCHovvZbZgwBSRETdmtmDAmGV52We2YMAiBzHEZrZgwB0lgAhntmDAWBCmS2e2YMBojbWNZ7ZgwGzt6KlqtmDAA8aM7Gq2YMAv78Uua7ZgwNRSeBZqtmDAB9waWmq2YMC1aHKearZgwEg7tONqtmDAoeOcKWu2YMArfvJva7ZgwG2LnrZrtmDAjuhO/Wu2YMAmJepDbLZgwLpCfYpstmDAyk+t0Gy2YMD9djUWbbZgwOKTtFpttmDAOko9nm22YMC7fs/gbbZgwP0xPSJutmDA7e47Ym62YMC/sS2hbrZgwNtFmd9utmDA66YMHm+2YMBCCrhcb7ZgwC0l85tvtmDAWRrs22+2YMApeggdcLZgwMnXfV9wtmDAZZjionC2YMAEsvPmcLZgwBmMoytxtmDAvgHscHG2YMAJvWy2cbZgwOInC/xxtmDAoYagQXK2YMBar/eGcrZgwGLY8stytmDAeFBaEHO2YMDVOkhUc7ZgwA21fJdztmDA8HIE2nO2YMBd8MkXdLZgwOl8/lh0tmDAez0QnnS2YMC/jF3fdLZgwAlK6yB1tmDA7frHYnW2YMAgOmSldbZgwB5urOh1tmDAhnphLHa2YMCWm0hwdrZgwNZnRLR2tmDAnEY1+Ha2YMBe/gI8d7ZgwPJUhn93tmDAJVhgwne2YMBLHuEEeLZgwNjAJUd4tmDAB+5HiXi2YMCGWEHLeLZgwJYKMw15tmDADTYoT3m2YMBUFSORebZgwGxBN9N5tmDAXqx1FXq2YMD6pdtXerZgwJDAfJp6tmDA9qZa3Xq2YMCRkG4ge7ZgwFWVpWN7tmDA2hQNp3u2YMDOdHjqe7ZgwDdpzS18tmDA1PTncHy2YMB+XcSzfLZgwGnTUfZ8tmDASoJxOH22YMBA2Dh6fbZgwMDBwrt9tmDAkaEd/X22YMC3S0c+frZgwP0mWX9+tmDAEGtrwH62YMBxEnoBf7ZgwEiJmUJ/tmDAJewEhH+2YMDoP8XFf7ZgwMGi4AeAtmDAiZuGSoC2YMB4WHaNgLZgwMgNi92AtmDAx3vHY4K2YMDIqgumgrZgwBDyb+WCtmDAoyqTJIO2YMB1adJig7ZgwOPCwKCDtmDA+TXS3YO2YMCzYUkchLZgwElH4aeEtmDAWAhkwoS2YMAkNRkChbZgwCymc0CFtmDAXxjafoW2YMDjd3+9hbZgwIrNW/yFtmDAVT7eO4a2YMDfmfN7hrZgwALGpryGtmDA91Pd+Ya2YMBk5ck6h7ZgwF+pe4KHtmDAxGpjxYe2YMBs1bgIiLZgwPstakyItmDA1QpyRYm2YMBJEA6EibZgwK5R98KJtmDA2Ps5Aoq2YMD5MyVDirZgwFhRMYWKtmDAO3wOjoq2YMBx90VoirZgwK4tEayKtmDAfLZXJIu2YMD2WdBti7ZgwHebFHCLtmDAxMr8sIu2YMCozxzyi7ZgwPLp0TKMtmDAlwJQc4y2YMDdtnGzjLZgwIEPNPOMtmDALi3XMo22YMAg6TNyjbZgwHeGHbGNtmDATx8V8I22YMBR1GQvjrZgwDewPW+OtmDAUd35r462YMC19SrxjrZgwHYgoTOPtmDAJrE0d4+2YMAv/ri7j7ZgwHrwtwCQtmDAiobWRZC2YMAX3PGKkLZgwCn62c+QtmDAcoVZFJG2YMCzesxXkbZgwH2ylpqRtmDAdpLU3JG2YMAuvYcekrZgwKRHzV+StmDA+AeloJK2YMD6QhzhkrZgwCF0TyWTtmDAL/u4wJO2YMBb0IWik7ZgwCDsvuKTtmDAtRXcIpS2YMALdONilLZgwGaP5qKUtmDAKhax4pS2YMDWLlgilbZgwOx4YWKVtmDA5kVoY5a2YMAwVkAslrZgwECx5fqWtmDA3VdMapa2YMDnLMN6l7ZgwC8OICOXtmDAylQ89pe2YMAR4GcTnbZgwOiZHKOetmDADesc3562YMAra6Man7ZgwB43hlWftmDAPOQmkJ+2YMBrFjbhrLZgwBtzjH2ttmDA6/ABdK22YMAmu3/srbZgwMisIimutmDA9vyUV662YMDQ5tNCuLZgwNPt93+4tmDA7HVqhLm2YMDFRO76uLZgwFSa2wW6tmDAmeANSrq2YMA3Zx2QurZgwDtBRda6tmDAQLjsG7u2YMALmXpgu7ZgwC4tHaO7tmDAQvk/5Lu2YMBuknsivLZgwDu4EV28tmDA7bP4lby2YMBwDh/OvLZgwCyM8AW9tmDAvBYdPr22YMAOv7Z2vbZgwFFyarG9tmDAs+su7r22YMAY+bMsvrZgwBVFw2u+tmDA/fjoq762YMDHmsHsvrZgwKFKxle+tmDAc+L2lr62YMBI6hrCv7ZgwCSjhhW/tmDAeJvuF8G2YMDPNbNYwbZgwOCQAhfCtmDARyGzAcG2YMCzlnRAwrZgwEGRS2bCtmDAfu9tpMK2YMA4SvXiwrZgwJzj/CHDtmDAjmNFYcO2YMAYtju0wrZgwGIxet3DtmDAWfixGsS2YMA4G2Zzw7ZgwPN1lLHDtmDA/1eczMS2YMDn/DMSxbZgwLdSJjnFtmDA5tQrcsW2YMA+VbqzxbZgwGTeyu/FtmDA1CHiLMa2YMC2Bk5qxrZgwLG1vqnGtmDA9UYC8Ma2YMDxZ6Uyx7ZgwHFYRHXHtmDAVMKpt8e2YMA1DS75x7ZgwGqShznItmDAOBx/eMi2YMCl1G/sx7ZgwDicQfTItmDA9he4Zci2YMD2/89tybZgwDJbGKrJtmDA2rBr5sm2YMCKiLsiyrZgwDui5V7KtmDASq5Y38m2YMBfwPkeyrZgwFMAhxPLtmDAA8zTT8u2YMCBJxqMy7ZgwElsdPnLtmDA+Dh4WMy2YMBp5KyczLZgwCmU69zMtmDAzK+QGM22YMBM8fVSzbZgwAlbZ5jNtmDA7GVW2s22YMBiQ00VzrZgwLGXw1PNtmDALUnimc62YMCO+ibWzrZgwIouvATPtmDA/MIgWM62YMAayBiZzrZgwMGc3tnOtmDAb1ZjGs+2YMB1M+/5z7ZgwN2cgznQtmDAKaVeeNC2YMAQboS20LZgwJ1NzPPQtmDAWBOUMNG2YMBAWfZs0bZgwFt5LqnRtmDAxdlN5dG2YMAIlj0h0rZgwGVpp13StmDA4IWOmtK2YMB6sJnX0rZgwDkBoBTTtmDA85F7UdO2YMAgIWCO07ZgwKrUDMvTtmDASko1B9S2YMDte+JC1LZgwMzVhH7UtmDAsx3AutS2YMD7CoX31LZgwCvt/TTVtmDATxyKc9W2YMBRiQWz1bZgwN/h0PPVtmDAqH6ENda2YMA3TXV31rZgwETpXrnWtmDAEkD6+ta2YMCdKOk717ZgwFaf6HvXtmDAcmnUute2YMA+fdT417ZgwLeFqjXYtmDALVa2cdi2YMAawg2t2LZgwIumAujYtmDAv6CdItm2YMBh4LVc2bZgwB5R5pbZtmDA61qx0dm2YMCjnXwN2rZgwElUWEratmDAXVeFiNq2YMAbOjvI2rZgwHr0FwnbtmDAZJjQS9u2YMDu2QKP27ZgwE1JltLbtmDAwBQhFty2YMBDvjRZ3LZgwES/p5vctmDAc2+r3Ny2YMCLwVkc3bZgwOT1DlvdtmDApaTSmN22YMBpZ/7V3bZgwMupaxLetmDA/1VwTt62YMD3BV+K3rZgwGVgP8betmDAS44HAt+2YMDM8+A937ZgwN8E2nnftmDAngIFtt+2YMA0EWjy37ZgwNX3FS/gtmDAmpcSbOC2YMBfwpap4LZgwPlGuefgtmDAylQ8JuG2YMBcP69l4bZgwJ7Rs6XhtmDAxpMj5uG2YMAejkon4rZgwOIz1WjitmDA7pScquK2YMB2+nXs4rZgwLp9Ti7jtmDAT27xb+O2YMB1+Wyx47ZgwNikH9zjtmDAc+tDM+S2YMCl5Spz5LZgwB0UYbLktmDAEvzE8OS2YMAL42cu5bZgwB87H2vltmDAQ6oAp+W2YMAHA1bi5bZgwGdboB3mtmDAlBYoWea2YMAt1SmV5rZgwGe539HmtmDAqgpRD+e2YMAMxEJO57ZgwCQRMY7ntmDA0YOtzue2YMDF8pwP6LZgwI7O6FDotmDAmgZqkui2YMB249rT6LZgwLIM4RTptmDAZu2rVem2YMCnvIuW6bZgwJwse9fptmDATQOCGOq2YMBu95RZ6rZgwLfrxprqtmDAdF+h3Oq2YMCVSIYe67ZgwPEV21/rtmDAYKBcoOu2YMABNfnf67ZgwFqITB7stmDA1iqZW+y2YMARGUiX7LZgwGs2i9HstmDAdHHHC+22YMCVCgV87bZgwGlZ1YTttmDASl6xxO22YMASAzUF7rZgwLBkOEbutmDAdQFXh+62YMDQAm199rZgwI5Ujb32tmDAc/Jg/fa2YMDL1+XM97ZgwP2kjg/4tmDAx6DhUfi2YMDjDVeS+LZgwOwM1U74tmDAR3cGkvi2YMDFHh/S+LZgwNo0dBH5tmDAyfNzT/m2YMA1vSmN+bZgwD7327L5tmDAuKHqB/q2YMB/eB5F+rZgwBAtzmj6tmDAzcSHwPq2YMBJKsr++rZgwJvpMD37tmDA48fGe/u2YMCMsYa6+7ZgwFwRcfn7tmDAs9FqOPy2YMBrqfh1/LZgwHc8zrP8tmDAmDNS9fy2YMAZqeJIDbdgwN158ZYNt2DAxxis1Q23YMCEnsMTDrdgwAWxw1AOt2DAFBgPjQ63YMAXIxjJDrdgwA0+CwUPt2DA2A4yQQ+3YMCG/ol9D7dgwMvAgLoPt2DAswZg+A+3YMCJ3hU3ELdgwGMLeXYQt2DAapupthC3YMAowV33ELdgwMZlrjgRt2DANe90ehG3YMC3JJS8EbdgwG5Bzv4Rt2DAsWMDQRK3YMAvixCDErdgwDeFz8QSt2DAwan8BRO3YMCUFTMHFLdgwDbI8UQUt2DA3+UmwhO3YMAoAH6/FLdgwE7Fv/sUt2DARQ9hNxW3YMChlFdyFbdgwFHZM60Vt2DALb1Y6BW3YMBLu+cjFrdgwMp/R2AWt2DABgZQnRa3YMCv4mTeFrdgwFGNWoMWt2DAUU6TLhe3YMDInQeIF7dgwGbGOgAYt2DAHsHkBhi3YMCfqzycGLdgwPxxTH0Yt2DAi7fPGxm3YMC0/dboGLdgwKRRp0Uot2DAqfsphSi3YMBdlgOUKbdgwEm8B9Apt2DA7vxSDCq3YMB77AVIKrdgwM2HooMqt2DAgvMJvyq3YMDngYD6KrdgwNR/DzYrt2DA5Rf4cSu3YMBByhKuK7dgwCJid+ort2DA4KpSJyy3YMCdH+FkLLdgwO94SKMst2DA/slz4iy3YMCP5mYiLbdgwPTzMGMtt2DA6SwRpS23YMD61njnLbdgwIGY5mYtt2DAcH0Cpy23YMB8NcMNL7dgwMJpASQut2DAWw+nWC+3YMCarBhtY7dgwN2SOxlkt2DAkDIyWWS3YMC6DZmZZLdgwEF7W9pkt2DA+nN+G2W3YMDiAKdcZbdgwOOunJ1lt2DAeD023mW3YMAru2geZrdgwL7oAV5mt2DAtdugnGa3YMAE8o7aZrdgwEMEoRdnt2DA3kiDVGe3YMCaUG6RZ7dgwPrQfs5nt2DApA7nC2i3YMAooNxJaLdgwHlu+4hot2DArXPayGi3YMCvedsIabdgwLhJAO1ot2DAKzQ6LGm3YMD9xb5wabdgwO0K0QZqt2DAlnOCRGq3YMBOzlOBardgwK+LQb5qt2DAR51u+2q3YMA7clo5a7dgwJxQOidrt2DAANIst2u3YMDWqWj4a7dgwBYJsPFst2DAs/i0wGy3YMCnxs8DbbdgwIaLBAZtt2DAVEnbSG23YMDsT2jIbbdgwHFd6AZut2DAGIe2EW63YMAL+SFUbrdgwK8TE5Zut2DAl8yU/G63YMDgYgo4b7dgwG5MPXNvt2DABSAurm+3YMBDKY3pb7dgwIUxbyVwt2DAa+sgYnC3YMCSIsyfcLdgwDjLZ95wt2DAhne2HnG3YMCaAudfcbdgwACiC6Jxt2DA8Y+J5HG3YMBh1PsmcrdgwHnGJGlyt2DAt8nDqnK3YMBPX2brcrdgwCdVrypzt2DA20EXaXO3YMCUubGmc7dgwGkTr+Nzt2DAvpssIHS3YMBvbShcdLdgwI4+9Jd0t2DAcZD403S3YMDmWu0PdbdgwHOWCkx1t2DADI9ziHW3YMAOmVHFdbdgwIFaaE52t2DAQQ/ylHa3YMDknwV+drdgwFczmrx2t2DAAR3l+3a3YMBOVso7d7dgwBblwHx3t2DAHUQkvne3YMD9gsdleLdgwHmmRKJ4t2DA0zd83ni3YMCYKsgaebdgwFCzNcJ8t2DAilvrBX23YMACtClJfbdgwPkY3ZN9t2DA6wnkzX23YMBpBacPfrdgwK2hfFF+t2DAEJ6ok363YMD+IP1007dgwOPJybHTt2DAWJN0GNO3YMDq4OdZ07dgwOKTap3Tt2DA4DYY4tO3YMCC0DUm1LdgwJHYlmLit2DAzpCBpeK3YMDS3DLk4rdgwIhA1SHjt2DAlu1ua+O3YMCwlGvg4rdgwO8VFfTjt2DAdrJjN+S3YMCCPzx75LdgwDDSr13jt2DAvD3En+O3YMCD5Qji47dgwFR/diTkt2DA8zIzZ+S3YMAICECq5LdgwEESve3kt2DAxVbCMeW3YMD3sUB25bdgwGwDP7vlt2DAHIftAOa3YMDMhS1H5rdgwB8hiI3mt2DAUriv0+a3YMBGM40Z57dgwOW/1F7nt2DAwRuio+e3YMCWcH7n57dgwN93jITpt2DASykMbOi3YMBqhJSt6LdgwMZq9+7ot2DAkigKMOm3YMDfDidx6bdgwMvwfLLpt2DAn8Zy9Om3YMCB86U26rdgwOrp4Hjqt2DAPkIhu+q3YMDDY0396rdgwJ7uaj/rt2DAULZIgeu3YMB4F/fC67dgwD+migTst2DAjsTfRey3YMAgaBGG7LdgwIOwIzHut2DA7m1/cu63YMDN5JGz7rdgwF41uRzut2DACts/PO+3YMDxMRsm7rdgwMnB42zut2DAdRZ7s+63YMAaWp357rdgwPrR9D7vt2DAujSFg++3YMANre/G77dgwPlQtQnwt2DAOFg/S/C3YMATSNWL8LdgwCSVV8vwt2DArWo5CvG3YMD3Bw1I8bdgwJG6NoXxt2DA2n35wvG3YMDec+YB8rdgwG0uFELyt2DAQs3ig/K3YMAgtS7H8rdgwOPSqw3zt2DAQ3xiVvO3YMCEv9mf87dgwAlEZOnzt2DABatwMvS3YMDxQpx69LdgwJ5kx8H0t2DA1CMuBvW3YMByYhpI9bdgwHxMjoj1t2DAYcRUyPW3YMC9CcEH9rdgwNETOEf2t2DAGAvahva3YMDeXdjH9rdgwI+khwr3t2DAO47HTfe3YMCQDkOR97dgwEccx9T3t2DAwiA3GPi3YMCuX6Nb+LdgwD7oPZ74t2DAPcWk3/i3YMCT4vQg+bdgwILmfGL5t2DAxt1HpPm3YMA8DDnn+bdgwAGegir6t2DAxoBb2fu3YMCqhPK0+rdgwJz9n/v6t2DAWk+uQvu3YMDzgtSJ+7dgwCHhzND7t2DAx6BBF/y3YMDAUfRc/LdgwDKT2qH8t2DA6xiu5fy3YMC9b74o/bdgwBQrsWr9t2DAIKAHrP23YMBmm6zs/bdgwK2zySz+t2DAeLAwbP63YMAzlm6r/rdgwGrdqer+t2DAktFRKv+3YMC7nldq/7dgwEf8Gqv/t2DA/GCR7P+3YMAoxBAvALhgwOMYk3IAuGDA2Tc+tgC4YMDwz976ALhgwInJ4T8BuGDAme8xhQG4YMAcMbDKAbhgwNI9LxACuGDAhzGWVQK4YMD8dNeaArhgwPEixt8CuGDAkIF3JAO4YMCcC9NoA7hgwF79yawDuGDAs0Jc8AO4YMCDAVwzBLhgwGEwJ3YEuGDA0wjnuAS4YMDtLnf7BLhgwGN75T0FuGDAOfE2gAW4YMDVR6nCBbhgwMqKWwUGuGDA/TYDSAa4YMA59oqKBrhgwDmr5MwGuGDA+n8nDwe4YMDycFRRB7hgwLjFbpMHuGDA/NUV1Qe4YMBRw8EWCLhgwHILi1gIuGDARV9vmgi4YMDz0ZHcCLhgwALb9x4JuGDALi1/YQm4YMDaCzSkCbhgwJ32dOcJuGDA5YNAKwq4YMD5o4FvCrhgwMMijrQKuGDAKV7e+Qq4YMAlEeo/C7hgwJF5xoYLuGDAEZWFzQu4YMDDHqwTDLhgwJSLHFkMuGDAxZptnQy4YMAxBLTgDLhgwHI9LyINuGDAOGeTYQ24YMAy7BagDbhgwLE0GN4NuGDA8r4iHA64YMB4j0s7D7hgwFPFXpkOuGDAe9mM2Q64YMBYwqQbD7hgwDkD5V4PuGDASPvVog+4YMD8HkLnD7hgwPTxDywQuGDAAQcEcRC4YMBmqZm1ELhgwAXYh/kQuGDA+Y0TPRG4YMBLtdmAEbhgwNWw68QRuGDAhrZkCRK4YMDBEhlOErhgwIIhepMSuGDAtCjn2RK4YMCkDcogE7hgwLcuQ2cTuGDAGbw+rRO4YMBALfHxE7hgwMoogjUUuGDA0168dxS4YMBX45e3FLhgwBC/EPYUuGDAhBLtMxW4YMA/HKFxFbhgwGQpia8VuGDAUdn+7RW4YMBBM04tFrhgwMDGJm4WuGDAhHGQsBa4YMC6ranzFrhgwNuRfzcXuGDAawfNexe4YMCdYEbAF7hgwBwmvQQYuGDAPinlSBi4YMBFVYWMGLhgwADsu88YuGDAjh1xEhm4YMADMpZUGbhgwMbBN5YZuGDAD/Ff1xm4YMDMHNYXGrhgwBWOpFcauGDAO1pxlxq4YMD4OIHXGrhgwL3GDBgbuGDAg1c4WRu4YMBrWe2aG7hgwC8N890buGDAIp5RIhy4YMCOK+JmHLhgwMh7k6scuGDADW0P8By4YMDp+yM0HbhgwM0B0ncduGDAG59Tuh24YMApDWv7HbhgwOhrETweuGDAKl7hfB64YMAKWCC+HrhgwN9p7/8euGDAHeBmQh+4YMAVUF2GH7hgwP3ZEMwfuGDA6F8aEiC4YMBR47zUILhgwJsfa50guGDAOrpq4SC4YMDm4lokIbhgwNSfOGUhuGDADU23oyG4YMBQXq7gIbhgwP+h+RwiuGDAVpkdWSK4YMC1OXKVIrhgwG+cNNIiuGDA3YxHECO4YMAWhf9PI7hgwGyo9pAjuGDApTQw0yO4YMBQ8S0WJLhgwIvb9FkkuGDAveZJniS4YMBjhOPiJLhgwOlpcycluGDA7TfoayW4YMA5sC2wJbhgwPJWNfQluGDAvy/4Nya4YMDcSEB7JrhgwB4AA74muGDAX5UyACe4YMBSdv5BJ7hgwG2peoMnuGDAnNm/xCe4YMAZmNoFKLhgwHoF0kYouGDAD0KIBCm4YMDJiqw/KbhgwObE8gkpuGDAL/sRSym4YMAeHQ6MKbhgwOSI/8wpuGDAuU2LDSq4YMBAo6WjKrhgwL6x+Y0quGDAEQnVzSq4YMDCs8oNK7hgwBEeBU4ruGDAlnJ3jiu4YMCq1H/PK7hgwMYGuBAsuGDAnIh3Uiy4YMDoSvCULLhgwFOvxNcsuGDA/QnHGi24YMAIWPNdLbhgwE14JKEtuGDABUsl5C24YMBMYc4mLrhgwOBxEGkuuGDATmXxqi64YMDYOm/sLrhgwFzhgC0vuGDAef8Zbi+4YMBUJk+uL7hgwO+DzmowuGDADlCqLTC4YMDmWAxtMLhgwDtqVKwwuGDAYNeW6zC4YMAOj0aqMbhgwMQxnGoxuGDAyR2oqjG4YMDxD51xMrhgwNSRPSsyuGDAT7bUiTO4YMDS5BTLM7hgwNvsXgw0uGDAxtZcdDO4YMCqow2VNLhgwKWsZts0uGDAaG0oIjW4YMCPcgCCN7hgwAL+NcM3uGDAT7gRBDi4YMDll8dEOLhgwFzQYIY4uGDA7rwAxzi4YMDs/osJObhgwK64OEg6uGDAdz6Xizq4YMAFV3fOOrhgwPGMgxA7uGDA0N2aUTu4YMAyZo50O7hgwEsh69I7uGDAy5HjEzy4YMBXjhpUPLhgwLM1bng8uGDApjRuuzy4YMCWHEr/PLhgwEE5AEQ9uGDA6Eoepz24YMBZ2izuPbhgwKj9O3s9uGDAnDxlvj24YMBajzAAPrhgwLd490A+uGDA9VdDfz64YMDpAJG7PrhgwIu9FPc+uGDACNk4iUG4YMB+hX7xQLhgwGo9LzZBuGDAe8DO00G4YMCTnoK/QbhgwHy8egRCuGDAWQSfKkO4YMDNs+GLQrhgwJBGvrZDuGDAIOcGEkO4YMBmZENUQ7hgwFNGO5ZDuGDArYXq10O4YMBh8IsZRLhgwDI4wVpEuGDAfamOm0S4YMB3QdfbRLhgwJa/wBtFuGDA4A8wW0W4YMBB0h2aRbhgwMRPkdhFuGDAfvjfFka4YMBOpjlVRrhgwJV95ZNGuGDAccP30ka4YMC7SrASR7hgwNEkFFNHuGDAlXdIlEe4YMB2TmXWR7hgwIjGHRlIuGDAWLt8XEi4YMBhR4agSLhgwDaV6eRIuGDAgKGlKUm4YMCySK5uSbhgwLZWybNJuGDAEDmf+Em4YMAXRhQ9SrhgwF/yFoFKuGDA63l5xEq4YMCntEYHS7hgwB75KUlLuGDA1I9tiku4YMAm5PvKS7hgwNt02RFNuGDALBgzVE24YMATI8SQTbhgwFHD2WpNuGDAJq0prE24YMB+/QbsTbhgwGmGSitOuGDA9glPa064YMCooXerTrhgwKfz80lPuGDAqtbp3k+4YMCS3lm3T7hgwDeP9PlPuGDAcCXmPVC4YMAMQ3yBULhgwGGkiMRQuGDAie1pCFG4YMD0CwHCUbhgwKb4ZQJSuGDAU5KNNFK4YMAG5gtwUrhgwP842KdRuGDA+cXX6FG4YMCpihIqUrhgwGca2mtSuGDAjL1ErlK4YMC5pwfxUrhgwAC6ADRTuGDASSQpd1O4YMDNpmG6U7hgwH6Opf1TuGDAgqzRQFS4YMCIFNqDVLhgwPmo1sZUuGDAfkvJCVW4YMA2Z65MVbhgwLlWoY9VuGDABNyS0lW4YMCvtJcVVrhgwPEbxVhWuGDA44/vm1a4YMAoo/3eVrhgwJ/S0SFXuGDAQxaDZFe4YMATfR2nV7hgwGUVeOlXuGDA0PZ6K1i4YMAdLl9tWLhgwObYX69YuGDAUf2H8Vi4YMDtkCA0WbhgwKu47nZZuGDAJLhQulm4YMCsHGL+WbhgwMfav0JauGDA8if6hlq4YMBjyfTKWrhgwBi1Ww5buGDAwPdWUVu4YMAK4WmTW7hgwL84mNRbuGDASNQeFVy4YMC2lmBVXLhgwBJ7opVcuGDA4rsU1ly4YMBAjNwWXbhgwAZjPlhduGDAIGtcml24YMBOqVrdXbhgwMKfuSBeuGDAvWaTZF64YMAcp7ioXrhgwPkbMe1euGDAmsG/MV+4YMD9eiN2X7hgwFeoaLpfuGDAcTvW/l+4YMCC1zxDYLhgwA0mjodguGDAKDbIy2C4YMCwcfsPYbhgwN6FTFRhuGDA3NpumGG4YMCcaCfcYbhgwG/bWR9iuGDA0rPuYWK4YMANX+ujYrhgwN2QL+ViuGDA1RqsJWO4YMA8X2VlY7hgwIn4maRjuGDAkzC+42O4YMDmTbEiZLhgwNGfyGFkuGDAKycsoWS4YMDPuuLgZLhgwJ70KiFluGDAeXdDYmW4YMCD7zCkZbhgwEkyWOdluGDA6gWRK2a4YMBw1qFwZrhgwH1S87ZmuGDAQN2Y/ma4YMDj3TFGZ7hgwLKvmo1nuGDAls9l1Ge4YMCAUCIaaLhgwB5z5F5ouGDAh9qloWi4YMA1DWjiaLhgwPRmBSJpuGDAJLEEYWm4YMAQMrCfabhgwHB9ct5puGDATatEHWq4YMCVxBtdarhgwJhvaJ5quGDAVuI34Gq4YMCZJlsia7hgwBXnFfdruGDAdBGap2u4YMBfbWrqa7hgwOByzyxsuGDA0gN6bmy4YMAbdjOwbLhgwK/bQ/JsuGDAhToWNW24YMAVR+P6bbhgwAK8YTluuGDAJHCdAW64YMB3LQhIbrhgwB2lKY9uuGDAzrRQ1m64YMA0Mj0db7hgwGrFTWNvuGDA0S7CqG+4YMBMXC7tb7hgwGWuzC9wuGDAREA0cXC4YMCkwNGxcLhgwFOQlfFwuGDAUIzWMHG4YMCtfcxvcbhgwKn5r65xuGDAzhjZ7XG4YMCm9DwtcrhgwHb/F21yuGDADxyGrXK4YMAcfojucrhgwBG4MjBzuGDAUvF1cnO4YMANnXi1c7hgwPWXN/lzuGDA22cFPXS4YMChuAqBdLhgwD6YCcV0uGDA+xblCHW4YMCIGBJddbhgwF9wXY91uGDAcqSx0XW4YMDWWcQTdrhgwEfhmlV2uGDANJpNl3a4YMCKB/bYdrhgwJZBjxp3uGDAG7xHT3e4YMBo7ryed7hgwO67kMZ3uGDAs2WwA3i4YMBkplhkeLhgwDswjqV4uGDA4iFq5ni4YMBkkJQmebhgwKrSB2Z5uGDAZgSYpXm4YMAHooLlebhgwL/j4CV6uGDAsGzXZnq4YMCucJCoerhgwMsnTut6uGDAMkB2L3u4YMDqKQp0e7hgwCvs77h7uGDAdOvT/Xu4YMDKKpRCfLhgwAXv1YZ8uGDA0uJxyny4YMD5wggNfbhgwI866059uGDABIxZkH24YMAaDmrRfbhgwGgeNxJ+uGDAlYTCUn64YMCxdVeTfrhgwJKPMtR+uGDAPUkJFX+4YMCicctVf7hgwPeNbJZ/uGDAP0Ph1n+4YMDdYGIXgLhgwKkjnFeAuGDADBCNl4C4YMD0AXrXgLhgwJ9GqBeBuGDALXM2WIG4YMAzLCmZgbhgwBH/iNqBuGDAnpF6HIK4YMCIZxZfgrhgwI9/N6KCuGDAmKl65YK4YMDuSNAog7hgwGcz22uDuGDAWNWiroO4YMAn5uDwg7hgwPU4dTKEuGDA32Rjc4S4YMCngrOzhLhgwL/XpPOEuGDAn+AZM4W4YMDZuytyhbhgwLrQ9LCFuGDAZlJ974W4YMDcNtkthrhgwFG7NGyGuGDAC/2mqoa4YMAwgzzphrhgwFKd/SeHuGDAKXv8Zoe4YMAZgXKmh7hgwLltPeaHuGDAo2w1Joi4YMAvgklmiLhgwL22XaaIuGDAmQZt5oi4YMCWzmEmibhgwFctDGaJuGDAgFqLpYm4YMAzfx/libhgwF473ySKuGDAYOzsZIq4YMCXA2OlirhgwHfX/eWKuGDA9px+J4u4YMAU6Hdpi7hgwEMheauLuGDAeRco7Yu4YMCQLXAujLhgwOxsMm+MuGDABBBQr4y4YMBMTWrujLhgwHPAVCyNuGDAEEXPaY24YMDHXu6mjbhgwDdBDOSNuGDAXvpPIY64YMCZ96tejrhgwOKbm5yOuGDABbw/2464YMCK6mgaj7hgwMFO4lmPuGDAW2rWmY+4YMDkTRPaj7hgwDVgihqQuGDAbN6sW5C4YMAJFP6bkLhgwAMQrNyQuGDAw2I1HZG4YMBiR4JdkbhgwNZ7gJ2RuGDApqox3ZG4YMCG02EckrhgwAmm5lqSuGDA924RmZK4YMDxrSrXkrhgwBCqTxWTuGDAPACIU5O4YMCSpNmRk7hgwIXHq9CTuGDAgugyEJS4YMCH5LlPlLhgwPRwB4+UuGDABhzdzZS4YMDzJSMMlbhgwACgsUmVuGDAWUpOhpW4YMB/NbXBlbhgwIBuV/yVuGDAK9h0N5a4YMBaWmBzlrhgwC7XQLCWuGDAlV+q7pa4YMDJYJAul7hgwKWKfXGXuGDASCPJtZe4YMAPNKH6l7hgwB9zeD+YuGDARJbFg5i4YMAn5E/HmLhgwEvu6wmZuGDA6tx1SZm4YMBBBXSHmbhgwG9VbsSZuGDAWiqLAJq4YMAsoiQ8mrhgwLJdi3eauGDAFA/5spq4YMDaSwrvmrhgwPUasSubuGDAHDrAaJu4YMAq92Gmm7hgwM2WguSbuGDAj38AI5y4YMAjYtZhnLhgwA3AFaGcuGDA1cOV4Jy4YMBKjycgnbhgwP+Otl+duGDApLwJn524YMCHuyfenbhgwITfDx2euGDA4+4yW564YMB5F/uYnrhgwLNBudaeuGDAFke4FJ+4YMCuhBZTn7hgwISR9ZGfuGDAzP5J0Z+4YMD1LIwRoLhgwGE2yFKguGDAHew/lKC4YMAcjpHVoLhgwOgGqxahuGDAoYxoV6G4YMDss3qXobhgwFoZYtahuGDABo9eFKK4YMBbJYRRorhgwKXJE46iuGDAzYVyyqK4YMA6QLsGo7hgwH/m9UKjuGDApF95f6O4YMDNBVi8o7hgwEi4qvmjuGDAF+paN6S4YMCwmZt1pLhgwOshPrSkuGDASic186S4YMCv6ZUypbhgwNMiZnKluGDAaaxSsqW4YMB09PvxpbhgwDUFUzGmuGDAW2dKcKa4YMDwSMSuprhgwHgDi+ymuGDAN7qEKae4YMChntNlp7hgwJO/+6GnuGDA9yUj3qe4YMB8x3oaqLhgwJ8uC1eouGDAWjgMlKi4YMBlG+XRqLhgwFYfXBCpuGDAG7EdT6m4YMDWnBeOqbhgwHpPM82puGDASI1jDKq4YMBP2W5LqrhgwFCDNIqquGDAk/C1yKq4YMB9shUHq7hgwEcYQUWruGDANfI3g6u4YMCIKArBq7hgwGxtvP6ruGDAQTJbPKy4YMC9IwF6rLhgwBUrtLesuGDA/gGG9ay4YMC+GYszrbhgwDVj0HGtuGDAWmxisK24YMCKy0TvrbhgwCxRcC6uuGDAxqecba64YMA3e8KsrrhgwCqBxeuuuGDAPC2KKq+4YMCrkvlor7hgwB0R+KavuGDA05Zv5K+4YMD/BqghsLhgwHRdv16wuGDAVdzIm7C4YMC8Q8rYsLhgwHxW1RWxuGDAbPYdU7G4YMB7Hp6QsbhgwCxfXM6xuGDA6WxVDLK4YMBKGpZKsrhgwFZlHomyuGDAQ9bbx7K4YMC6ydkGs7hgwFQc9EWzuGDAAKwshbO4YMDfLo/Es7hgwL+c7wO0uGDAcSlPQ7S4YMAyX6SCtLhgwEUE5MG0uGDA/ewKAbW4YMAh3fk/tbhgwG+/m361uGDAwqXmvLW4YMAvBNT6tbhgwPfIYTi2uGDAK71mdba4YMDGvP6xtrhgwP1fbO62uGDAP227Kre4YMCfjgpnt7hgwN3KjaO3uGDADV0+4Le4YMDbOlkduLhgwEM/4lq4uGDAevvemLi4YMBo4z/XuLhgwC35Oxa5uGDAzHm2Vbm4YMCiHZOVubhgwIdJydW5uGDAI1SKFrq4YMCpenVXurhgwGheIJi6uGDA9gtX2Lq4YMDG6uwXu7hgwGH3u1a7uGDAhr64lLu4YMAgDKXRu7hgwPkwpg28uGDA1PQSSby4YMBI9QKEvLhgwIn4vr68uGDA6bh/+by4YMBI33E0vbhgwMtO80y8uGDA431Uq724YMBvxbnnvbhgwJC+4SS+uGDADjEVY764YMDCbQ+ivrhgwAJcyOG+uGDAc7GkIr+4YMDJCk1kv7hgwDynUaa/uGDAm7Y46L+4YMBXydkpwLhgwAAd8mrAuGDAO51Bq8C4YMAStnbqwLhgwNICfCjBuGDABh3KZcG4YMBdVX6iwbhgwPebvd7BuGDAbFXIGsK4YMANk7pWwrhgwJzW5ZLCuGDAoSRSz8K4YMCmdvYLw7hgwC0i2EjDuGDA+jDuhcO4YMAaK1DDw7hgwBIj7QDEuGDAOO7BPsS4YMDZdNV8xLhgwDBfNrvEuGDADiPO+cS4YMBlOZw4xbhgwED5nnfFuGDAs1HWtsW4YMB6eUb2xbhgwKmcsDXGuGDAJPozdca4YMBnwLe0xrhgwERJHvTGuGDAMShnM8e4YMDlppVyx7hgwKFHrLHHuGDAtUKm8Me4YMAHe0YvyLhgwNxJf23IuGDACBUsq8i4YMCH8JDoyLhgwH0LjyXJuGDA5L3iYcm4YMBqdYidybhgwIubpabIuGDARvBW4si4YMCOgDJRyrhgwKQ0XI7KuGDAjBAEzMq4YMCqVtAKy7hgwFZ9iUvLuGDAyNRJV8q4YMCObifOy7hgwElj8Q7MuGDA5XA7T8y4YMDSHayOzLhgwNfW88zMuGDA5/+yCM24YMDcLGpDzbhgwNXm0X3NuGDAJGs0uM24YMBXKtPyzbhgwMiSGC7OuGDAnrhkas64YMAR+iKozrhgwBM7c+fOuGDAdh1TJ8+4YMCm8bVnz7hgwAoaUajPuGDAwgnp6M+4YMAmFz0p0LhgwMgr5GjQuGDAOtO/p9C4YMCEHSHm0LhgwMC99SPRuGDAoiBUYdG4YMCqrk2e0bhgwEpNCdvRuGDALjmhF9K4YMAZRq4t0bhgwCBiJgnZuGDAk1M10tm4YMA0iAQS2rhgwOppPVLauGDAKmDrktq4YMDDH97T2rhgwEux2xTbuGDAjQhKQ9q4YMBoV6aV27hgwCoCFtXbuGDAqYHUE9y4YMANh5FR3LhgwNLiAY7cuGDAz6/Tydy4YMCq4DIF3bhgwPkMa0DduGDAgZWoe924YMDpDwu33bhgwE4j5vLduGDAFGJ4L964YMBX8ats3rhgwARQFKreuGDA3d+T5964YMDJ0zUl37hgwLD7EnveuGDAlMUBoN+4YMD+dffc37hgwMfHuxnguGDAdeWQVuC4YMB7MYuT4LhgwNVS2dDguGDAGPt4DuG4YMBwpZhM4bhgwJulNIvhuGDAES1cyuG4YMDHBRIK4rhgwPIfL0riuGDApY+2iuK4YMBjTWTL4rhgwONfVkTiuGDAEi+4TuO4YMBmCK2O47hgwNuYa87juGDAcUme2Py4YMCNMVWX/LhgwKAVQN38uGDAjuTOdvy4YMDxCN5m/bhgwO9Bsvf8uGDAVyYBOf24YMDyFqh7/bhgwIFMjb79uGDA4++yAf64YMCT7Y7t/rhgwDDgqof+uGDASiUoyv64YMAkhEAM/7hgwNzEME3/uGDA4dybjf+4YMAhS27N/7hgwByxngwAuWDAxZBySwC5YMClWe6JALlgwCaIJMgAuWDAJihJBgG5YMDmTIdEAblgwJysBYMBuWDA3RLYwQG5YMBMuBQBArlgwMfu7UACuWDA7GIWgQK5YMAj1gTCArlgwHmp91IEuWDAhX03lwS5YMBVU2+IA7lgwLuOyMsDuWDA9OmiDwS5YMD97sZTBLlgwAq1qJgEuWDAhsyy3QS5YMA6SDUiBblgwLvtrGUFuWDA8r0PqAW5YMCCsmbpBblgwBbEZSkGuWDAcARbZwa5YMBsdvyjBrlgwOq3PeAGuWDATkvmGwe5YMAod5JYB7lgwIFs95UHuWDATISA1Ae5YMCqISMVCLlgwCyqfFcIuWDAVT6Smgi5YMDm811qCrlgwANBxlUJuWDAhJI09Aq5YMCItOU4C7lgwHHXsnoLuWDA1M2Auwu5YMDlBNP9C7lgwFfT0ckLuWDAPgdm/Aq5YMC70Bo+C7lgwPiRi38LuWDAZqi8wAu5YMDYH9sBDLlgwNSN2UIMuWDAqkqagwy5YMC8yCXEDLlgwJ3gjgQNuWDAw/LpRA25YMCS/B2FDblgwEJhOsUNuWDA76pqBQ65YMAi5N5FDrlgwDb6poYOuWDAkVK2xw65YMD3/B0JD7lgwF5tBksPuWDA9/R9jQ+5YMAHRTfQD7lgwLiPExMQuWDAeaP8VRC5YMDOcteYELlgwMLtq9sQuWDAFOExHhG5YMDL0F9gEblgwBnIaaIRuWDA9/aF5BG5YMD87LkmErlgwN3/G2kSuWDAho2gqxK5YMAxipHuErlgwEUTMDITuWDA5ckQdhO5YMBdA965E7lgwHQ+l/0TuWDAwc0lQRS5YMB0rJaEFLlgwC/vk8cUuWDAJ0m2CRW5YMACP6pLFblgwAc0y40VuWDADd5R0BW5YMCo4E4TFrlgwP0Y9FYWuWDAWMXGmha5YMDdIFjgFrlgwCJGsyYXuWDAXEDmAR65YMDjKiiiHblgwIwasOMduWDAoQiGyx65YMBuubpkHrlgwCpqQqkeuWDA6WPH7h65YMCWSjprJ7lgwOjkNJAmuWDAA0sr1ia5YMAlXI4cJ7lgwI2WRWMnuWDAZVMBqie5YMA+npbwJ7lgwFaZ0zYouWDAONCZfCi5YMCk5cHBKLlgwMAwQwYpuWDAtLoKSim5YMAZZr+MKblgwONxrc4puWDAiQ4wECq5YMBL+FBRKrlgwB4AU5IquWDAl+BQ0yq5YMCgSncUK7lgwGyODVYruWDAxXwZmCu5YMAi0EHaK7lgwDF8dhwsuWDAZwSyXiy5YMDGa++gLLlgwC9qLeMsuWDAqAUPJS25YMD2SspmLblgwJ0pxqgtuWDAl6kz6y25YMA//PYtLrlgwOcDJXEuuWDAjebetC65YMC8K2/5LrlgwFX1vT4vuWDArJdNhC+5YMCuo+vJL7lgwH/PbQ8wuWDA0FW/VDC5YMA8qbKZMLlgwBMl/N0wuWDAVwqiITG5YMD1H89kMblgwB/QrKcxuWDAiv0j6jG5YMBnUF0sMrlgwIeVaW4yuWDAVFB4sDK5YMAXtb3yMrlgwDSiAzUzuWDAzqVIdzO5YMDG7Ha5M7lgwMH7lvszuWDAuJjGPTS5YMBQZuh/NLlgwF+b+ME0uWDAlfBDBDW5YMAH9tpGNblgwODi4Yk1uWDA6SxezTW5YMCvSWYRNrlgwBOg+FU2uWDAy1pBmza5YMC6P9HgNrlgwB80WSY3uWDAwDGkaze5YMDSfpiwN7lgwD1aFPU3uWDAjUnmODi5YMAadLF7OLlgwNsU5L04uWDA9wrA/zi5YMD0qXBBOblgwIacEIM5uWDAzCmzxDm5YMDTAK0GOrlgwPO2Rkk6uWDAByRxUju5YMBW+LTOOrlgwGKLExE7uWDACLtTUzu5YMAVUGaVO7lgwNa5Fdc7uWDA3GW2Fzy5YMAWSfJXPLlgwMflWmE9uWDA1bQE2jy5YMCx/gcbPblgwKZC7Vw9uWDAiKt/nz25YMAVGO/iPblgwFYA5CY+uWDA9c12az65YMACr8qvPrlgwBv+4PM+uWDAM+u1ikC5YMDIs9q1P7lgwOY52RJBuWDAOgN1VUG5YMDjlByWQblgwJuef65EuWDAw//4rES5YMAbjqy8RLlgwHeJE/FEuWDAu9XxL0W5YMA2CR95RblgwNpGSnFFuWDApgEDhUa5YMChLGz4RblgwJ6h5TxGuWDAxWKTf0a5YMCyp9HCRrlgwDdntwVHuWDAYAVFSEe5YMAEf4GKR7lgwKfUgcxHuWDAt/wvDki5YMCy3ZlPSLlgwNBMuJBIuWDAc5ef0Ui5YMDMgXUSSblgwI0EFFNJuWDAyYKXk0m5YMDpkyPUSblgwBQspRRKuWDAQwNRVUq5YMCUJBqWSrlgwKTk49ZKuWDAmQb3F0u5YMCFLllZS7lgwN8jMZtLuWDArRxy3Uu5YMCSqxQgTLlgwMrRAWNMuWDAyIHTpky5YMAHqbHqTLlgwIUHVC5NuWDAWHXycU25YMB8yxq1TblgwKB5tvdNuWDAjtSuOU65YMCH+at6TrlgwBieGrtOuWDAY+hK4E+5YMA3vnwmWLlgwC92fulYuWDALK7YJVm5YMDHebmtWblgwCkHO6BduWDArwZB4F25YMAmVc0fXrlgwE1xTmBeuWDARmmlo165YMBgFfnoXrlgwMJwzi5fuWDADtVAvl+5YMCnmLYBYLlgwMGh2kVguWDAzMAkh2C5YMDlFVdPYblgwGE6dn9huWDApNzPwmG5YMC/XvYFYrlgwKRtHkxiuWDASJq8kmK5YMCqw0bYYrlgwPcKNhpjuWDAlGZQlGW5YMDAYeDbZblgwHK3aBpmuWDA+ZEMq2e5YMBTRubwZ7lgwFQkBOJmuWDADqF+fWi5YMBvHSR4bblgwM+MaLptuWDAWxJE6my5YMB4aDMtbblgwM7nOG9tuWDAX8w9sG25YMBogQPwbblgwEfaNy9uuWDARhA0bm65YMBWp0CtbrlgwMTjrOxuuWDAwSfNLG+5YMCC88ltb7lgwDYA4K9vuWDAuj4C82+5YMB5aGA3cLlgwLLQnLhxuWDA0mXIwnC5YMCX9t0JcblgwHpwt1FxuWDAPPulmnG5YMATsIXjcblgwF0IxytyuWDACgx+c3K5YMAIP6S5crlgwMihv/5yuWDA/73zQXO5YMDwMBODc7lgwL5p0sJzuWDA2sEKAnS5YMBSvwNBdLlgwMH9AYB0uWDAaRVZv3S5YMAcdLD/dLlgwIWFZ0F1uWDA6qNEhHW5YMDl/SjIdblgwKVgeQx2uWDAiElvUXa5YMBawsuWdrlgwLVIXNx2uWDAIuHnIXe5YMB/BEhnd7lgwC6IfKx3uWDAEgRF8Xe5YMBbi8Y1eLlgwFMz4Hl4uWDAk+6KvXi5YMAn3JwAeblgwOKBD0N5uWDA3wN8hXm5YMAo/7/HeblgwB/i5wl6uWDAfSoNTHq5YMANQF2OerlgwO6sEtF6uWDA+oAdFHu5YMAUaQ1Xe7lgwMxXxJl7uWDAMJge3Hu5YMAlRiQefLlgwM7z6V98uWDAn2z1oHy5YMAbt0/hfLlgwHutwCF9uWDAGBesYn25YMAfoS2kfblgwKYagOZ9uWDAXTjZKX65YMA1mUhufrlgwG2tR7R+uWDAvCXP+n65YMDxMNlBf7lgwDiQEol/uWDALs800H+5YMAPJvoWgLlgwAYTJl2AuWDAPm+VooC5YMAoTU7ngLlgwK9VCCuBuWDAj0zgbYG5YMCUVduvgblgwFI/HPGBuWDAIkZOMYK5YMDn++dwgrlgwMPxJLCCuWDAGNP6voS5YMC7LU0BhblgwIOHiESFuWDAdj8Rh4W5YMAzNuXJhblgwOjy5QyGuWDAwIwgJY25YMBpeNNmjblgwMwyPqmNuWDADoFg6425YMAvkBUxjrlgwKanh+aNuWDAjNj0I465YMDqxKdpjrlgwHo3XKmOuWDA+HMR1I65YMDWkRHaj7lgwGfIJHSVuWDAAbtpuJW5YMA0zsz3lblgwCNO4TyWuWDAB3Uigpa5YMC/TtXGlrlgwFtlfAWXuWDAcg8nzJi5YMCs6fSNl7lgwPYeg5mXuWDANZ7l25e5YMBXJTAemLlgwM4eZGCYuWDAr3B2opi5YMBYuWvkmLlgwLyCVyaZuWDAxJ9YaJm5YMDG2w7xmrlgwDMwFOyZuWDAEAFae5u5YMBNt1lwmrlgwIW8xrKauWDAec/L9Zq5YMCX9jc5m7lgwJXiMX2buWDAyv2RwZu5YMBXeXAGnLlgwILnSUycuWDAtP13kpy5YMCXSnzYnLlgwHRIMR6duWDA4uF7uJ65YMA8Xs6nnblgwPdSU+uduWDAqM1PLZ65YMDrRXFunrlgwJ3oOq+euWDAPkHq7565YMB50scwn7lgwCOl2nGfuWDAWfJ5s5+5YMCuAXv2n7lgwDTMNjqguWDAjRs5fqC5YMAvz0LCoLlgwDSMIQahuWDAqYjCSaG5YMBQFwKNoblgwFEqQs+huWDAME2yEKK5YMCNJDlSorlgwO32B5SiuWDAWz5w1qK5YMDFaYwZo7lgwLlUlF2juWDAO6N6oqO5YMAk0STko7lgwJZCaiukuWDAZ9pmdqS5YMCh5QO9pLlgwCnOJAOluWDAg//SSKW5YMDC0lCNpblgwGPVe9CluWDACAkFE6a5YMCZVLdUprlgwLu3ypWmuWDACRaE1qa5YMB7zvIWp7lgwMRGMFenuWDAsEpGl6e5YMACusTXp7lgwP0YwxiouWDAWymdWqi5YMBTXV+dqLlgwJqxz+CouWDA9Wt1Jam5YMBYNGRrqblgwIb2xLGpuWDAmRZg+Km5YMASg9Y+qrlgwOFB8YSquWDALMiByqq5YMDQAywPq7lgwHyO5FKruWDAFnzFlau5YMDgz9morblgwK7kFe+tuWDA8oY7Wqy5YMABLCWbrLlgwPUdoNusuWDA5S4XHK25YMAVQtxcrblgwBEBIp6tuWDAIpEI4K25YMBnDsgirrlgwLaiR2auuWDAw3bDqq65YMBmaZXwrrlgwHxXLTevuWDAP57+fa+5YMBrxsTEr7lgwE0WWQuwuWDAS5pyUbC5YMASBSCXsLlgwFDrPduwuWDAcgiZHrG5YMCCKLBhsblgwPqXsaSxuWDAem2457G5YMCax+IqsrlgwOLOiG6yuWDA9NsAs7K5YMBUwQz4srlgwMYBhT2zuWDAkY4lg7O5YMD45c/Is7lgwFLYYg60uWDAzSnEU7S5YMC4lfqVtLlgwBEInNm0uWDAcOlzIbW5YMCN02dltblgwKBlKqm1uWDAfFXC7LW5YMB7Iz8wtrlgwER5q3O2uWDA+AIFt7a5YMBhb136trlgwNlO1z23uWDAc+hPgbe5YMD/V/3Et7lgwCFZyQi4uWDAwjzETLi5YMBBQvuQuLlgwJxnStW4uWDAXk7CGbm5YMDpAFZeublgwKh3BqO5uWDAXs3L57m5YMDe2ZwsurlgwJ3lYnG6uWDAuK0ntrq5YMAdwgb7urlgwBvU+T+7uWDAy4oJhbu5YMD1BjbKu7lgwMxfgA+8uWDAYYXiVLy5YMCxIUGavLlgwOoKj9+8uWDAqlzEJL25YMDu+8VpvblgwFvhia69uWDA+iYj8725YMAMDpY3vrlgwFnRtXu+uWDA28OHv765YMB24hYDv7lgwE3qgEa/uWDA2Wziib+5YMAx1AzNv7lgwGsQBxDAuWDA5cAcU8C5YMCh+JyWwLlgwHCEtNrAuWDABdhhH8G5YMAZaL5kwblgwEuJE6vBuWDAJg1S8sG5YMCqoD86wrlgwOAUVYLCuWDAQj5mysK5YMAmNi4Sw7lgwLMrrFnDuWDAEVJ/oMO5YMAvcVDmw7lgwC/IgCvEuWDAYhpefca5YMC3xT+0xLlgwA3sJvjEuWDAabzhO8W5YMDVAq5/xblgwOCnyMPFuWDAoS0lCMa5YMBS5ptMxrlgwLucMpHGuWDAsOXj1ca5YMDRYMMax7lgwG3brF/HuWDAlMJ5pMe5YMCUlVHpx7lgwE+AUC7IuWDAsSCDc8i5YMBm2Rq5yLlgwMRB1P7IuWDAoaa2RMm5YMApCwiLyblgwPM1jNHJuWDAwcznF8q5YMDWnBJeyrlgwOM926PKuWDAKi4z6cq5YMDT7Rouy7lgwBSvOnLLuWDApoPAtcu5YMCSQMP4y7lgwLsEZDvMuWDAe0QZfsy5YMAna5T4zLlgwM8IxlPNuWDAslDlm825YMA8bLnFzblgwO7Tu9zPuWDA3DHgDc65YMD4mMdl0LlgwOpumZjOuWDAooLZ3s65YMDk6Ecmz7lgwHoP+HPRuWDAB6zBt8+5YMCpjsYA0LlgwB5UlUnQuWDAxhiQgtK5YMCwVvfZ0LlgwEYf2SDRuWDA4pOJZtG5YMBaOHGr0blgwBwF9O/RuWDAKFgcNNK5YMCtdCF40rlgwAUmFbzSuWDACcdXANO5YMD1bidF07lgwHLjKIrTuWDAZoY8z9O5YMBFCmgU1LlgwDbFo1nUuWDAdkjOntS5YMCSmMLj1LlgwJSphijVuWDAcUw5bdW5YMDcnfex1blgwNeT//bVuWDAvQMSPNa5YMBre4uB1rlgwI37TsfWuWDAPmdjDde5YMBbydlT17lgwMCjyZrXuWDAtYYX4te5YMDDvbYp2LlgwI+7i3HYuWDAXoWYudi5YMBaWPMB2blgwKUXUErZuWDA1uVMktm5YMAMOrbZ2blgwAjfmyDauWDA9d2JZtq5YMBFrjoA27lgwA4raE7buWDAw2xwf9u5YMBqxk/n27lgwP5nDSrcuWDA4KkaP9y5YMD9Lhzy3LlgwMTl2g3duWDAZo/9E9+5YMDgadBc3blgwC8csaTduWDAONprX9+5YMAS5Ish3rlgwENcqWfeuWDAg9hwrd65YMDdneTy3rlgwFoBaTjfuWDAakghft+5YMAj7QrE37lgwLv8NArguWDA6UGGUOC5YMDc8mSX4LlgwB8+w97guWDARXEUJuG5YMA+/Rlt4blgwMaRI67huWDAFmQC9eG5YMCuNw4/4rlgwCkAbYPiuWDAUG/fxuK5YMAnPdYJ47lgwM/wfUzjuWDAiQcUj+O5YMBc6brR47lgwHfNmhTkuWDA9vQGWOS5YMCaevqb5LlgwPaecuDkuWDACMdFJeW5YMD2O3xq5blgwLDC9K/luWDALXaq9eW5YMBYE4s75rlgwEi2jYHmuWDAWHd7x+a5YMBIVTYN57lgwOcXvlLnuWDAssDtl+e5YMC3iszc57lgwMLaQiHouWDA2ykIZei5YMCLGpCo6LlgwLgcGuzouWDA0rm8L+m5YMAWPIdz6blgwFKfgbfpuWDAJg3Q++m5YMC42ydB6rlgwP5IvIbquWDAneZQzOq5YMCEmL0R67lgwH5L8FbruWDA8ArYm+u5YMAL8kHg67lgwPShOL7tuWDANpDNxey5YMCz6Rzt7LlgwHvsaTDtuWDAHphqpe25YMARyCAD7rlgwP3dEnDuuWDAsHcDRO65YMCrCgfE77lgwMmKP2PxuWDAlcA1pPG5YMAMLqDk8blgwNMTriPyuWDAhjOhKvK5YMDDMcxn8rlgwM4oKaHyuWDANUaH5PK5YMBL3XrO87lgwDjxNAzzuWDA/07bUfO5YMAb8/CX87lgwBrU39v0uWDAwNoQofS5YMDIsEl4/rlgwH3Jprr+uWDA6SHp/f65YMBxojtA/7lgwBbZhoL/uWDAlpPy3QO6YMDQ/+YdBLpgwOm5r1wEumDAfKInmgS6YMC0fkEKBbpgwKatiEsFumDAWhReRge6YMCCj96BB7pgwGXOcsEHumDA/dFV/we6YMDnV0jcB7pgwBXmVR8IumDAE5sZYgi6YMDlUImkCLpgwEQlx7wIumDA2K6ZAQm6YMBsybFCCbpgwBsfMasJumDA73KL6gm6YMC5rB0qCrpgwLY/hmkKumDAvFekhAq6YMAVVhPqCrpgwGKZPysLumDAH6tibQu6YMChjyJ/C7pgwJdAiL0LumDAJzla/Au6YMBZvaI7DLpgwJXtYsAMumDAw3FfAw26YMDD2ipFDbpgwA68CYUNumDAbJA8xA26YMD61DcDDrpgwGFiHEIOumDARqJHgQ66YMBbqK7ADrpgwLqG+AAPumDAm2qeQg+6YMDIed2ED7pgwGFKgccPumDAA6lUChC6YMCtLkJNELpgwJrd/0cQumDAFay+0hC6YMAMHqwUEbpgwMM/JVYRumDA7wKelxG6YMAqcCmJEbpgwPDtFRsSumDAbqouXRK6YMAJi82fErpgwFgyJeMSumDAGq/jJhO6YMAwDE9qE7pgwBas9KwTumDAB4Pf7hO6YMAAmvwvFLpgwEUo3W8UumDA/UbfrRS6YMABJqHqFLpgwCUDGycVumDA4Cm7YxW6YMCGeOqgFbpgwCjMwt4VumDA5sLAHRa6YMBSr4xeFrpgwKeZ0zcWumDAPxj04xa6YMAq3W0nF7pgwIZcHmsXumDAmzigrhe6YMB6E9XxF7pgwBFaHjQYumDAEHJbdRi6YMAF+fO1GLpgwHt4CfYYumDAFMmeNRm6YMC2OQF1GbpgwFcYMbQZumDALdM+8xm6YMAIRlkyGrpgwGPGqnEaumDA3VdBsRq6YMD+S0LxGrpgwDIEuzEbumDACp0p9hq6YMD5atw4G7pgwLKJHPYbumDACS8ZOBy6YMBRfbp5HLpgwI24p7ocumDAcM7a+hy6YMCMqTy+HLpgwBs/DXgdumDAzepotB26YMCmFFfwHbpgwLR0ZyweumDAI9PyaB66YMBcylymHrpgwBSct+QeumDAk5IdHh+6YMD7WDZZH7pgwHNr1iUfumDA1O9s7h+6YMDIzeYyILpgwNHBHXcgumDAY4udJyC6YMBwsP79ILpgwAzV/z8humDA6xDfgCG6YMB17B3BIbpgwPWsVF0humDA0/XYQCK6YMC1CoyAIrpgwEcFeMAiumDAHYItASO6YMD1hCSeIrpgwMhCtd8iumDAjQZBISO6YMAUJcoDJLpgwHn+KUQkumDAka4WhCS6YMDU6DfDJLpgwJbhHAIlumDAZVslQSW6YMAZlp+AJbpgwKzRLcAlumDA6upWACa6YMBPJOtAJrpgwD9yPIMmumDAymHvxSa6YMAJkZAIJ7pgwKRdw0onumDAwUp8jCe6YMBfGCnNJ7pgwEPDOw0oumDAkJkNSyi6YMDU4+yHKLpgwEUMVsQoumDAZgV9ACm6YMDk68k8KbpgwJvqbnkpumDAW/nItim6YMAeAin1KbpgwFpExjQqumDAwOJIdSq6YMBfcYa2KrpgwBFVbvgqumDAZcrXOiu6YMBGI599K7pgwJr+F/wqumDAcJJnAyy6YMBOh4BGLLpgwNZLh4gsumDAp+f6ySy6YMB0CXAKLbpgwARmHUotumDAtSd0iC26YMCWn23FLbpgwCFQNgIuumDAE5YTPy66YMC8eTJ8LrpgwL7HzLkuumDA9y0Q+C66YMCHBs83L7pgwK6xUXkvumDAa9CQuy+6YMACdUT+L7pgwH8ZGEEwumDAwIDegzC6YMCi14XGMLpgwNxSNQgxumDAyN7tSDG6YMDMFAqJMbpgwHQ3i8gxumDAe06eBzK6YMBHn0hGMrpgwGSHtYQyumDA7nUiwzK6YMDXnrQBM7pgwMrLTUAzumDA9KnEfjO6YMDaRiS9M7pgwJpLY/szumDANJujOTS6YMD1/ad3NLpgwLZJO7U0umDA1ebu8jS6YMCEMC8xNbpgwOR07W81umDA+848rzW6YMCF1F7vNbpgwLEbdjA2umDAKNmXcja6YMDBlpq1NrpgwJyHnPg2umDAfCpMOze6YMA0Z/yPNrpgwO4aw743umDAiWkX/ze6YMCbTrs9OLpgwIxvN3s4umDASU8AuDi6YMAS5470OLpgwBIxATE5umDAVW6ebTm6YMBfSLSqObpgwPREoug5umDAE1N+Jzq6YMDkHttmOrpgwKLfAKc6umDADm6e5zq6YMC6BJEoO7pgwOIjzmk7umDAVKg6qzu6YMDe+qzsO7pgwPSzty08umDAL5rhbjy6YMDOU9+vPLpgwLX2KvA8umDA01EgMD26YMBuoFJvPbpgwJMG7a09umDA3tFX7D26YMAvnqsqPrpgwMZHBmk+umDA0POepz66YMCIOGnmPrpgwJpqACY/umDAWNobZj+6YMBJBW6mP7pgwGqi0uY/umDABxUJJ0C6YMApOWxnQLpgwGcskadAumDAoNIS50C6YMBzM9glQbpgwBOglmRBumDAOMFIo0G6YMCOaRziQbpgwIeeAyFCumDA1EhQRUG6YMCA5y6gQrpgwIIFgeBCumDAgcfzIEO6YMAleSRhQ7pgwP8i3aBDumDAj4PK30O6YMA4RxIeRLpgwEq6K1tEumDAtCm6lkS6YMBPBL7RRLpgwJAkdAxFumDAXsIlR0W6YMBljOqBRbpgwA3+ir1FumDA1i+d+UW6YMD18NFBRbpgwMSTqoBFumDAjMqTtUa6YMDYi4f1RrpgwKeJMDZHumDANoced0e6YMCp2Fa4R7pgwKXkg/lHumDAH3GuOki6YMBlHS9+R7pgwGC7JL1IumDA6a6Q/ki6YMBC+mc5SLpgwHSvQHZIumDAYsKiwkm6YMB7cAwESrpgwGsuB0VKumDAe0FehUq6YMAAD7qjSbpgwHeBrARLumDAj92kQku6YMBNzTKAS7pgwNkw9bxLumDAf0+h+Uu6YMBtOk02TLpgwJv8f3NMumDApcstsUy6YMDMTorvTLpgwIg3Cy9NumDAYKSsb026YMD/QsCwTbpgwOg6ufFNumDA605MM066YMDDZUd0TrpgwG6v+bROumDAiWLy9E66YMB1sfozT7pgwM+MoXJPumDAP9HgsE+6YMDfadnuT7pgwFgQXixQumDAlziEaVC6YMBvrxqnULpgwPwww+RQumDASaSFIlG6YMC+Z19gUbpgwFUSXJ5RumDAJOaU3FG6YMAWegsbUrpgwG268GBRumDA/AyRmFK6YMA9SKjXUrpgwPyjFRtSumDA6fFJVlO6YMCHobuVU7pgwDacfdVTumDAOh4qFVS6YMAuri5cU7pgwECYxpRUumDAAM8I1FS6YMBz33gTVbpgwEYwslJVumDA9E6+kVW6YMDmtbPQVbpgwKVefQ9WumDAX1kMTla6YMAuYlyMVrpgwElAb8pWumDATT1JCFe6YMC8DPBFV7pgwOB1ZYNXumDA95+twFe6YMDC8c39V7pgwLtGVjtYumDA5zPMeFi6YMBKrrC2WLpgwHrUu/RYumDAeLwpM1m6YMDLf1NyWbpgwCjDtrFZumDAZPI78Vm6YMBzUbIwWrpgwJtHD3BaumDAKKo7r1q6YMCsshjuWrpgwLUETG1aumDAmyLCalu6YMBk88ioW7pgwHxWsyxbumDAWNzSI1y6YMBPNjZhXLpgwODVmJ5cumDA0iv321y6YMCqwoEZXbpgwJKzYFddumDAY5uY7Vy6YMBnjaHUXbpgwAJ0ExReumDAbjksVF66YMAIVhqVXrpgwMWql9ZeumDAGemjGF+6YMAnH8+qXrpgwLB2aJtfumDAK1HvKV+6YMDY1eQdYLpgwDQN111gumDAGVz+nGC6YMCaiqfbYLpgwOOG7hlhumDArqO8V2G6YMCop1CVYbpgwJPixtJhumDAv99BEGK6YMA4TcpNYrpgwDPKpotiumDA2i/pyWK6YMBlbJ0IY7pgwIU/HbtiumDAbe/1h2O6YMAFQrDIY7pgwCZXIgpkumDA8oHES2S6YMC6gl6NZLpgwHDnoc5kumDAQ9wqe2S6YMBF0plPZbpgwLHfJI9lumDAKyb1zGW6YMCpWW8KZrpgwGPNvUdmumDA7uYphWa6YMD6q+zCZrpgwNhVCgFnumDAHvbYP2e6YMCIA+d/Z7pgwMy4bcBnumDATJcWAWi6YMD90YZBaLpgwAp6jYFoumDAKR0bwWi6YMDw+Mb/aLpgwDd4ST1pumDAzhoeemm6YMDs0922abpgwNT9svNpumDAghzjMGq6YMDezBwSarpgwGWJ1KxqumDAqKGP7Gq6YMA6pR8ta7pgwOQHC25rumDAHDpZr2u6YMANouDwa7pgwFyBbTJsumDAmArLc2y6YMCdsMm0bLpgwIvQU/VsumDAXCV/NW26YMBfBG91bbpgwNLpAbVtumDAZf489G26YMALJhszbrpgwJ5y23FuumDAAMxYsG66YMAPXZzubrpgwJFXtixvumDAgrvEam+6YMDiG9Kob7pgwEtJ/+ZvumDAt3QxJXC6YMCF9GtjcLpgwCgOJ6JwumDAPqpE4XC6YMDKvf8gcbpgwAeWdWFxumDA5AODonG6YMDshkPkcbpgwKAlsyZyumDAbyNlaXK6YMAFxiiscrpgwFdawu5yumDAfOD3MHO6YMBlaJtyc7pgwG6wrrNzumDAi2jn83O6YMCaZlMzdLpgwC5PG3J0umDAlDSWlXS6YMBIhd3tdLpgwOTP4ip1umDAE1ybZ3W6YMByywikdbpgwCIaaeB1umDAgBGvHXa6YMB3xblbdrpgwGU4x5p2umDAh1yP2na6YMBq5z4cd7pgwKZ1Q193umDA/6IZo3e6YMBrCiLnd7pgwEPD+yp4umDAkdCBbni6YMARR1GxeLpgwGodGvN4umDAsgX6Mnm6YMDFJy9yebpgwDeDs7B5umDA1l727nm6YMB9dxEterpgwN8AN2t6umDAzqO1qXq6YMC9lAHperpgwLIauSh7umDACOPRaHu6YMA+Vy+pe7pgwN+M4+l7umDAA/61Kny6YMAhqrZrfLpgwAwOoKx8umDAVm/17Xy6YMC4r+YufbpgwCn30m99umDAVnPasH26YMDtxjzxfbpgwPINpjF+umDAlqy2cX66YMCGlE/XfrpgwKbhrPF+umDAnVLWMX+6YMCEuTpyf7pgwHicArN/umDAehbk83+6YMBIUs01gLpgwMOIEXiAumDA71nW3YC6YMC4UaP8gLpgwKHJ5z6BumDAkujwgIG6YMCcT7/CgbpgwLhhyQOCumDANAxgRIK6YMBN0cSEgrpgwI6WQcWCumDAFCLQBYO6YMDjUYlGg7pgwE+OjYeDumDAm7EpyYO6YMDrWEsLhLpgwASXXE2EumDAyXtUj4S6YMALrOnQhLpgwOrIDRKFumDAlgKGdoW6YMAVN0a8hbpgwB/v8dGFumDAe8b9EIa6YMDDcSJQhrpgwDHOgo+GumDAg/I+z4a6YMDMdqoPh7pgwHX9+VCHumDAjSRVk4e6YMDoQjXWh7pgwFDdNRmIumDA/D09XIi6YMD2BvqeiLpgwEFUWOGIumDAh1X9Iom6YMAgQTuHibpgwKyP9aOJumDAjWsA5Im6YMAQvtUjirpgwAykq2OKumDAgxSYo4q6YMD3ZyIPi7pgwA0JfCSLumDAE11/ZYu6YMBKH8Smi7pgwIjSM+iLumDA7AC8KYy6YMC1MHtrjLpgwNsqQK2MumDAfHP87oy6YMBJHhlRjbpgwLIasHKNumDAGAF8tI26YMBY6NwVjrpgwNtTfziOumDA2guaeo66YMCNOdO8jrpgwFye/P6OumDA1Z4NQY+6YMAcZBiDj7pgwCuM/8SPumDAkPzBBpC6YMDyl15IkLpgwIkkqImQumDAnDrlypC6YMDX490LkbpgwBahC02RumDAJdJYjpG6YMDQyvjmkbpgwMS1nhGSumDADnLSU5K6YMBioESWkrpgwPANqtiSumDAMAwvG5O6YMDupZpdk7pgwLKl25+TumDA57Di4ZO6YMDm2ncjlLpgwJxKsWSUumDA8K3bpZS6YMB9SiTnlLpgwNqDhiiVumDA4SktapW6YMB39UeslbpgwNo9r+6VumDAINa5MZa6YMDAC7R0lrpgwJMYX7eWumDAGnW3+Za6YMAaR60+l7pgwCl4BH2XumDA8usrvZe6YMBL3EP8l7pgwHIyMDuYumDAXobicZi6YMC2fgS6mLpgwNOtHPqYumDA7MMVO5m6YMCK+W19mbpgwHPmfcCZumDAajNuBJq6YMAF4oBImrpgwOahRIyaumDAZJubz5q6YMA2uHoSm7pgwJofH1SbumDA9T9KlJu6YMAivPDTm7pgwLkVXBOcumDABc/YUpy6YMC3gKKSnLpgwORYrdKcumDAknNj7Zy6YMBPJbBVnbpgwKwzwpidumDAG9+w2526YMCYBIQenrpgwAvoH2GeumDAzIR6o566YMBlsznlnrpgwNfq1SWfumDA0QfyZZ+6YMDcneOln7pgwJ5o6OWfumDAyOXy6p+6YMDliUEroLpgwOzxvGugumDAl1pjrKC6YMDG19UqobpgwCMr6S2humDA88kar6G6YMAX3v7wobpgwPmmwzKiumDAhqcYdKK6YMCtxUK0orpgwAV5PPSiumDA/wdqNKO6YMB7Q910o7pgwNpNzrWjumDAxLte96O6YMCeoMg5pLpgwOPsMH2kumDAHFiewaS6YMAPgwIGpbpgwI1kBUqlumDA3aCUjaW6YMC/UC5lpbpgwJY2RamlumDAPpN27qW6YMAkuQWQprpgwMMdCc6mumDAd+O+C6e6YMCFmHxJp7pgwKnzhYenumDAf6dExqe6YMB9AigGqLpgwJrUZEeoumDAXIoLiai6YMBu4/fKqLpgwOqiTraoumDAdcb0Tqm6YMA1TseQqbpgwM1UndGpumDA59e/Eaq6YMCO2xpSqrpgwNa8YD2qumDAF5zCfqq6YMCl/k8Uq7pgwCfu4lWrumDAZ4ukmKu6YMDxDGXcq7pgwFgzsrarumDAs/z1Y6y6YMAazlOnrLpgwGuQ3OmsumDAR3S+K626YMBe8DlsrbpgwEVgQqutumDA+Wmh6a26YMAETGUnrrpgwNUNGvCtumDA4V1roq66YMAbUgbgrrpgwGK5Ph6vumDAUqWVXK+6YMCptvibr7pgwDLPBtyvumDAM48vHbC6YMCVsChfsLpgwB+XBaKwumDA803t5bC6YMC0Z7EqsbpgwE+cDHCxumDAzMIHtbG6YMANkK35sbpgwCGpuz2yumDAR4figLK6YMCQN8zCsrpgwAgNo3iyumDAsxsaQrO6YMB/YAD9srpgwPC9iz6zumDAmTd+f7O6YMD+3FI8tLpgwCyoQXu0umDAYLswvLS6YMDMUxn9tLpgwBAE6T21umDAWW5WfrW6YMBXYSi+tbpgwGTGXP21umDAl1FNO7a6YMAc58N3trpgwBTyVCq2umDA7zaKaba6YMD0h+KptrpgwN6zyma3umDA5EY2pLe6YMAgGS/jt7pgwH4Z3CO4umDAzIRfZri6YMDzR8SpuLpgwAYE/u24umDAozeXMrm6YMCg20p3ubpgwOQ9zru5umDALc3R/7m6YMByLBBDurpgwFlGiIW6umDA1IX6xrq6YMCAfXUHu7pgwDQX6Ea7umDAd5pGhbu6YMC+8wPDu7pgwKDZiv+7umDA//GiO7y6YMDbTJF3vLpgwOCVrrO8umDA8clD8Ly6YMAXPU4tvbpgwGZBQ2u9umDAomELqr26YMCgpdvpvbpgwC3WUtK9umDAtgIPEr66YMCWkhuuvrpgwDEc6/C+umDAfZmRNL+6YMDJzKp4v7pgwN/1iby/umDA4bK7/7+6YMDJ0vFBwLpgwLlpS4PAumDA6r9Ow8C6YMAR82ABwbpgwDnmNT7BumDAY1K9ecG6YMCrQ/W0wbpgwGMlOfDBumDAb8L/K8K6YMAFz3NowrpgwPnFM6bCumDAeI3c5cK6YMCLwoYmw7pgwP13GWjDumDAwidOqsO6YMAj8hHtw7pgwOvS1uzDumDASpU0c8S6YMDMiia2xLpgwF0K3vjEumDAE90oO8W6YMCSGb58xbpgwAIQ2L3FumDArzln/sW6YMCyZVs+xrpgwPpRzTTGumDAkzgmu8a6YMAqaMi0xrpgwMxwojfHumDA6Wtkdse6YMBFNpm1x7pgwHuyXfXHumDAx6NmNsi6YMBmXiZ4yLpgwJUn/bnIumDANlK++8i6YMC7JCg9ybpgwCXVN37JumDARhdYkcm6YMDbY1r9ybpgwF9cYDvKumDASsNHecq6YMAJr023yrpgwDo5TPXKumDAILskNMu6YMDtHoRzy7pgwHF5B7TLumDAK5+69cu6YMA71LY3zLpgwANmBXrMumDAQb9WvMy6YMCevX3+zLpgwC3xYUDNumDAYrGWgc26YMBYuuvBzbpgwMk3UwLOumDAROOEQs66YMBIaKyCzrpgwO06AcPOumDA9SOAA8+6YMBcOgJEz7pgwBGKj4XPumDAxSJ0x8+6YMC5Yb3wz7pgwGLOiC/QumDATwQIb9C6YMDfTIDJ0LpgwAPv4wjRumDAJDGLR9G6YMBtMdGF0bpgwKulw8PRumDAfVCGAdK6YMAtUSY/0rpgwPnpAn3SumDA9LziutK6YMB3+e/40rpgwK2OpDfTumDAlgdRd9O6YMDsLBTS07pgwKIwXxPUumDAYDgiPNS6YMBSAjKA1LpgwM3YjdjUumDAIylaGtW6YMANXSlR1bpgwNFp2JXVumDABmhq2dW6YMASlrMb1rpgwOdJzGDWumDACr7Smda6YMCs8EXW1rpgwOUzyBHXumDAAii4TNe6YMB87aqH17pgwAtGqOPXumDAjSWOJNi6YMBgxwk82LpgwNIPlXrYumDAcarrudi6YMAkNtP52LpgwN/LgDrZumDA/0nEe9m6YMB4XnW92bpgwCx1UP/ZumDA8z5VQdq6YMDBMmW52rpgwGKFbfzaumDASHtECdu6YMDI6lxM27pgwMqono/bumDA3REz09u6YMAn9eUW3LpgwNGIJ1rcumDAk1jKnNy6YMBvE67e3LpgwKxcxR/dumDABB/wX926YMCr1Lye3bpgwBRfmdzdumDAlepXGt66YMDADmBY3rpgwOoZ6ZbeumDAf1kn1t66YMCRWnkW37pgwGrGuKHfumDA5K6zm9+6YMA8OrXf37pgwKIxECTgumDAhuDRteC6YMDBXGH54LpgwDRJnvDgumDAuqBeM+G6YMBfwCp14bpgwLqgkLbhumDA0xLB9+G6YMDlbOc44rpgwBStFnriumDAT+p1u+K6YMCPU1D94rpgwGm4mj/jumDAsZ0vguO6YMAvkvzE47pgwPuj3wfkumDAUqLWSuS6YMBEvd6N5LpgwAVLXCblumDA4u2RE+W6YMBfvM5V5bpgwF9HmpflumDA/1q42OW6YMAGxxwZ5rpgwP136FjmumDAWS2Bl+a6YMDmQ/DV5rpgwFGr1xPnumDAFHb0Uee6YMBIU3yQ57pgwARgUM/numDAVJoSEOi6YMDbXF5R6LpgwNNKL5ToumDApRMN2Oi6YMDnZV8c6bpgwAldGmHpumDAzAj0pem6YMBjE7Hq6bpgwNjdGi/qumDAlVDKcuq6YMDXzLi16rpgwPkJBfjqumDADHWNOeu6YMBbGjN667pgwFewPrrrumDATrzp+eu6YMBzdrM47LpgwBxnW3fsumDAuu7Rtey6YMDZez9r7bpgwGAWlDPtumDAx14Kc+26YMAcfkGz7bpgwOjkCXHuumDA9hYFs+66YMCUpu147rpgwNVyubvuumDAHYis/u66YMDEXr1B77pgwDCtq4TvumDAE8BPx++6YMDOTpoJ8LpgwKftzUvwumDAa1jxjfC6YMCrPR/Q8LpgwB+HVxLxumDAxOvJVPG6YMDB0zMq8rpgwIh3TmzyumDAQNDKHPK6YMDlW85f8rpgwFlNz6LyumDAsILm5fK6YMBTC9Yo87pgwCWTEWzzumDAqe9Gr/O6YMAAcAny87pgwL5FXzT0umDAt0/zdfS6YMCqB/q29LpgwLA0Kff0umDA92R4NvW6YMAfOLd09bpgwP+58jv2umDA900R8fW6YMAtRQYw9rpgwNVbcW/2umDAusokT/e6YMAdq3Dx9rpgwKQiWzT3umDAheVQePe6YMDwVAS997pgwCb3aAL4umDAHy1lR/i6YMBx2umM+LpgwMVKK9L4umDAXUPeFvm6YMCt1Rxb+bpgwBx/up75umDAmi7I4fm6YMCCEBQk+rpgwH1TzWX6umDAXrcFOvu6YMCXG0J++7pgwMal7ib7umDAPphpZvu6YMCqRqOl+7pgwG6/6uT7umDA9kf/I/y6YMA6/Xtj/LpgwAVuDGL9umDAeaNQ4/y6YMCBgEck/bpgwHmbJGb9umDAHkq4qP26YMBfFXPs/bpgwH6Lp/X+umDAcnPwNv+6YMB16oa9/rpgwE4JMAT/umDACYZs/f+6YMCyezmQ/7pgwLPsUNX/umDAFCJIGQC7YMC411RbALtgwCMVnpwAu2DAFp/N3AC7YMCu78scAbtgwMpQjS4Cu2DALLLsnQG7YMAsoRDfAbtgwHJNQ/ICu2DAfYICZgK7YMAKvwWqArtgwMtwqO0Cu2DAUGXdMAO7YMDTsSlzA7tgwHSgWIQEu2DA4pO8zgS7YMBRUagZBbtgwGc2fnAEu2DAXXU/rwS7YMBktbDuBLtgwPRf+D4Gu2DAXhukfQW7YMBSgbq2BbtgwA+J3P0Fu2DAdSC6RQa7YMAFdBWOBrtgwOWeXtYGu2DAaj9AHge7YMAj/pFlB7tgwJXPxaoHu2DACU0I0Ai7YMAS78UwCLtgwLNF/3EIu2DAayBSsgi7YMBbWS7iCbtgwIKInjAJu2DAQ0t4cAm7YMCspOGvCbtgwGj2oO4Ju2DA5NnNLQq7YMD8EyhtCrtgwAuepqwKu2DAVLuE7Aq7YMAjrENHDLtgwPOa9GwLu2DA6rKCrQu7YMApFdnuC7tgwNavOjEMu2DABGNldAy7YMB9pB24DLtgwMhF1fwMu2DA001gQg27YMAocgKJDbtgwF+B8AoPu2DAEV4mUA+7YMCdkPyUD7tgwKopUJ8Ou2DAuTmx4w67YMDtVyYnD7tgwH67kmkPu2DAIedIqw+7YMBiMIMpEbtgwCvMAC0Qu2DA9x45bRC7YMBQTkytELtgwMsLUe0Qu2DAGvx7LRG7YMAnYg1uEbtgwM5k9BATu2DA3jAJWBO7YMBgrTufE7tgwJdbfuYTu2DATzObuRK7YMAw+kP+ErtgwHTsUEMTu2DA6S2fiBO7YMCbLv3NE7tgwCOqQhMUu2DAxB5TWBS7YMCP2/CcFLtgwJy5IOEUu2DAMkx3nRa7YMByOHdoFbtgwDokh6sVu2DAmHw47hW7YMB8PJswFrtgwMDRznIWu2DAwjDFtBa7YMBk0XT2FrtgwI9LETgXu2DAYdKceRe7YMBUDTG7F7tgwPYdCv0Xu2DALO6WPhi7YMCRgmMzGrtgwGzBK3Uau2DAJmVwBRm7YMAQuTlIGbtgwGHyuTwbu2DAxZFMgRu7YMB+5EvHG7tgwAu1Z1cau2DA8g77mxq7YMAKmuXgGrtgwDAT9iUbu2DAGvH4Kx27YMAC+niwG7tgwMSw7PUbu2DA8geFAB67YMAM18pGHrtgwLiG8MUcu2DADHXBCh27YMCwo1ZPHbtgwNPXm5Mdu2DAK/Qs1x27YMA66AcaHrtgwD7wGl0eu2DAaeA4oB67YMD+K125ILtgwAMmfycfu2DAHHS+ax+7YMDkuwSxH7tgwN6BRvcfu2DAgQSVPSC7YMDgYtBeIrtgwKEJR8ggu2DAtrLl7CK7YMCB0xhPIbtgwLuCI5Ahu2DAcFN/ziG7YMBXaDUMIrtgwCMUQUoiu2DAd7t+iSK7YMCDz2/KIrtgwDwV3Awju2DA5q06UiO7YMAD4fmaI7tgwO+E7uUju2DA8N6eMSS7YMASQad9JLtgwNUG8dEmu2DACbcYFye7YMAys6hdJbtgwCWzcqQlu2DAK/hB6SW7YMCtH18sJrtgwDSof24mu2DAT+5arya7YMCfvYLvJrtgwAujUy8nu2DAJ7xxbye7YMD178WvJ7tgwJ4kR/Anu2DAYw8NMSi7YMCd+4xyKLtgwAOTYbQou2DAqPbc9ii7YMAe5es5KbtgwFCXf30pu2DA3GA0wim7YMCZ9zsIKrtgwOa8nKksu2DAzaX0lSq7YMAdoD41LbtgwG7DAigru2DAoDBYciu7YMDar4W8K7tgwL9Cjj8uu2DAzY4MTyy7YMDzuZeWLLtgwN7JDd0su2DAmKlzIS27YMCeLRNkLbtgwJwA56Utu2DATUEr5y27YMCU/UIoLrtgwOdbiGkuu2DA/TUoqy67YMBmLOHtLrtgwLRO/zEvu2DAEXYMdy+7YMCuUJi8L7tgwPp29QIwu2DAqJezSTC7YMDBUAGRMLtgwNKGNtgwu2DAwHlwHzG7YMAQprhmMbtgwE5e9K0xu2DA9n0Z9TG7YMBGSAw8MrtgwFMtpoIyu2DATKojyTK7YMBHaUUPM7tgwLp3FVUzu2DAoaKrmjO7YMA4xgPgM7tgwPCVICU0u2DAL/P7aTS7YMB5P6euNLtgwO5gSvM0u2DAYyfSNzW7YMBUGiV8NbtgwBdmYsA1u2DAFXeEBDa7YMDYsp1INrtgwEjUQOY4u2DAAoax0Da7YMDSSPcUN7tgwBXWiVk3u2DADg4FBjq7YMBTDc/kN7tgwMp4his4u2DAKZNY4Tq7YMAdWA0qO7tgwK8gf3I7u2DA/mCXuju7YMCV2yqZObtgwPOxTeI5u2DAK8zkKjq7YMCZ8kZyOrtgwNtBGLk6u2DAUx9c/jq7YMCEJTBDO7tgwOtBv4c7u2DAO49ezDu7YMDaEBIRPLtgwPtaLVY8u2DAAOU4nDy7YMBfR87iPLtgwLK3fSk9u2DAiOYkcD27YMCgYuoVQLtgwLdm0fw9u2DA7GOcQj67YMDQc9GHPrtgwCUJMMw+u2DAkctkED+7YMAG3olUP7tgwN7knZg/u2DAfRCM3T+7YMDhhcwhQLtgwLAYi2ZAu2DAHKdKrEC7YMBIjoHyQLtgwCs9nDlBu2DA2iKNgUG7YMD561zKQbtgwHZE2BNCu2DAwkdXXkK7YMAVPNCpQrtgwAR4MvVCu2DAdQMwQEO7YMChDaeKQ7tgwAbkCxJGu2DARgjzVEa7YMAd+bOXRrtgwLo/p6hEu2DA4tva7ES7YMAX4tVjR7tgwMoDpHNFu2DAONnwtkW7YMDdIFD6RbtgwJ6FlT5Gu2DACaUwhEa7YMCnKUfKRrtgwDVrMxBHu2DAd1sYVke7YMA1E72bR7tgwJqRFOFHu2DAmta3JUi7YMC3kf6ySrtgwET6j/NKu2DAeobA8Ei7YMBHmh11S7tgwLjx33xJu2DA43v1xEm7YMA7KPYOSrtgwBtlM1xKu2DAylS3yky7YMDX0WL4SrtgwHK1mEVLu2DAeunckUu7YMBgpRncS7tgwBPo2CNMu2DAY+FhaEy7YMBsOFeqTLtgwCfLBOtMu2DAm1IdK027YMBB0g9rTbtgwGlAq8BPu2DA4G1AAU67YMAPGDQwTrtgwE146HROu2DAK4Bqu067YMC6jMICT7tgwCATL2BRu2DAfXF3p1G7YMBd2bzdT7tgwHeAhidQu2DAuZiHf1K7YMDuLeu6ULtgwKHOLARRu2DANUX0TFG7YMC/5w6VUbtgwL76qNxRu2DAivNHI1K7YMBJXgppUrtgwAkyQa5Su2DAevVX81K7YMAxbD44U7tgwFwIFX1Tu2DAT5XawVO7YMDZpV8HVLtgwBOzSk1Uu2DAGeA4k1S7YMBPGzXZVLtgwCE8UwJXu2DAZuE3ZFW7YMA4NpWpVbtgwF9ZQu5Vu2DAn2dXMla7YMAs8q12VrtgwAWNUrtWu2DA0WxyAFe7YMDAEGhGV7tgwJqhFo1Xu2DAM7fp1Fe7YMA4RdgdWLtgwPsyYGdYu2DAN7wosVi7YMDxa+rNWrtgwGwpbURZu2DAL5qRjVm7YMDCSJvVWbtgwBBY6Bxau2DAVNSAY1q7YMDsvUSpWrtgwArzfu5au2DAChM7M1u7YMAzG513W7tgwDhxpbtbu2DAlbLC/1u7YMCjteZDXLtgwAexzIdcu2DA9D8zy1y7YMBBqqYOXbtgwFK7QlJdu2DAUceclV27YMBr7jWPX7tgwNLtTxxeu2DAzzN2YF67YMA8NjKlXrtgwPmfWOteu2DAWodSMl+7YMCdOEh6X7tgwNPH2sNfu2DA509YDmC7YMBq0ef/YbtgwMx3LaNgu2DAM3Dm7GC7YMCCLzbEYrtgwKeYfn1hu2DAFL6/w2G7YMBbg3QIYrtgwCyhd0xiu2DA2jnLj2K7YMBPmNjSYrtgwH3ZxBVju2DAiDnoWGO7YMCd1hkSZbtgwKPtiOBju2DAaabgJGS7YMDillhpZLtgwH66pa5ku2DAGjrVa2a7YMAy8mw5ZbtgwB9jSn9lu2DAgYAfxWW7YMCinvcKZrtgwGKkrFBmu2DAP+smlma7YMCQBGbbZrtgwAU+MIlou2DAzfnTZGe7YMCb2NmoZ7tgwF6T+exnu2DA6o5kMWi7YMCzOh92aLtgwOnnZLtou2DAveIOAWm7YMCWDbpHabtgwPG+UY9pu2DA/lwB12m7YMCA3XAeartgwC/ZbGVqu2DAHMCzq2q7YMAeqkzxartgwFvRrTVru2DAweyHeGu7YMDHOci6a7tgwC6lyPxru2DAlseyPmy7YMD8EAnTbbtgwDEbMMNsu2DAhfIyBm27YMDhKGZKbbtgwIGABI9tu2DAtYrK3227YMBQFZ9ub7tgwLdirWBuu2DAkNFSp267YMB0DBHubrtgwG2ZnzRvu2DAwspJe2+7YMD4qA/Cb7tgwJHx3Ahwu2DAw5qST3C7YMD8Z0/GcbtgwMU9uNxwu2DAoedHI3G7YMAYzZFpcbtgwAv/v9Ryu2DAdTcfGHO7YMAKKFs4crtgwCf+1ntyu2DA8XZ3vnK7YMDL3ggAc7tgwFbgCUFzu2DAjKPhgXO7YMAlec/Cc7tgwGt7KgR0u2DAXAE1RnS7YMDrK9KIdLtgwO56z8x0u2DAmoanEXW7YMAJQG98drtgwDA28p11u2DABIUO5XW7YMC03McsdrtgwBfUB3V2u2DAOYxsvXa7YMBOtbkkeLtgwIGYbk53u2DAvnR2lne7YMCgMM7dd7tgwK5xYSR4u2DAguxJd3m7YMC8UzS2ebtgwLvmnPJ4u2DA3XWbNXm7YMDvxsxwertgwNfllbl5u2DAS7y9+nm7YMAR9uM7ertgwHbw33x6u2DA87zgvXq7YMBnYQT/ertgwEMtakB7u2DAlq5Dgnu7YMAVr6HEe7tgwL/Uagd8u2DAkdvPSny7YMBeKM2OfLtgwNwzXdN8u2DAM4G2GH27YMBNve5efbtgwGmZ5ah+u2DApKqx7H27YMC10Gkwf7tgwCpTsnN/u2DAyf9wxX67YMDEGmMNf7tgwIMEplR/u2DA46wvm3+7YMABTFi+gLtgwDt9Rv+Au2DAuo90aIC7YMATNbyqgLtgwB+9XOyAu2DAUYdNBYK7YMBugtNHgrtgwC7jYIuCu2DA7tWV8IG7YMAh/ggygrtgwEFN/XOCu2DA1yt4toK7YMB/kX75grtgwE6BsyKEu2DAoEOYgYO7YMC5a4zGg7tgwNgWWAyEu2DAOYJWUoS7YMAH7WiYhLtgwH8QPKOFu2DAgrncI4W7YMB1/jBphbtgwI0nvq2Fu2DA/qQi8YW7YMBQCQ00hrtgwMXPpjOHu2DAr9gPuYa7YMBNbp77hrtgwFlH/D2Hu2DAQDKxgIe7YMC+0Z3Eh7tgwBZQfgiIu2DA9lYETIi7YMCoYRaPiLtgwIJij9GIu2DAWDmCE4m7YMBkK1tkibtgwHJU3GuKu2DAUXDR0om7YMBLye8RirtgwN/sz1GKu2DAbVFrkoq7YMBTtSG2i7tgwHyXbfmLu2DAFDoWPYy7YMAP/J2AjLtgwFaT4cOMu2DA+iunBo27YMB+/zV+jLtgwF3q8caMu2DA2ku0vo27YMCXyrf/jbtgwLXG3TiOu2DAGWHwbY67YMDNuOOnjrtgwA4z04yPu2DA/GUMLI+7YMAPMKNuj7tgwBgbgFiQu2DAnE0r84+7YMBZ0C01kLtgwA4EtnaQu2DAJuzhaZG7YMAKrxitkbtgwJR3TPCRu2DAmb5sfpG7YMBsiMe/kbtgwDGVKwKSu2DAlp3P9pK7YMAoD3hCk7tgwAcqt9qSu2DAFX9GzJO7YMByoFYQlLtgwHIlWpCTu2DA7/x31JO7YMA9HE0ZlLtgwAx0rV6Uu2DAklgDpZS7YMCr52+QlbtgwIe9Sy6Vu2DAh7QWe5W7YMCLkFvBlbtgwHHwHQaWu2DAIHY9Spa7YMClmAWMlrtgwOVzi8yWu2DApRGDC5e7YMC7gadJl7tgwITiCoiXu2DAIErGxpe7YMBQajq6mLtgwHwui0aYu2DAFWEiiZi7YMBixLfMmLtgwET8LRGZu2DAYlkbVpm7YMBDrH6bmbtgwOVXJeGZu2DALvlmu5q7YMAY805rmrtgwD190K+au2DA8cnq9Jq7YMALFkI5m7tgwG/YuH2bu2DAV4irwpu7YMCHnIQHnLtgwA9/W02cu2DAbX0ssZ27YMASLgnznbtgwCx3jWilu2DAyCwuqKW7YMAmneZipbtgwMYNHqSlu2DAO0FF1qW7YMA25Hq6pbtgwNZEif6lu2DARLq+Qqa7YMC3PNuFprtgwF3i0Smnu2DAmMXBEqe7YMBiCPywp7tgwApMcIynu2DARTM5zKe7YMDt6S4MqLtgwJ7Awkyou2DAdwXejai7YMCowfbPqLtgwIfSqBOpu2DAxJ9DWam7YMCzWaifqbtgwM/oU+apu2DALVvhLKq7YMBuT+9yqrtgwBdA5u+qu2DAkTpK/Kq7YMBAMvU9q7tgwMsltH6ru2DAcMfovqu7YMCDb8b+q7tgwLxxoD6su2DA45eYfqy7YMA1TDa/rLtgwADJrgCtu2DAUky4Wq27YMBG45jDrbtgwDMEqMitu2DAbk5oC667YMChOiNOrrtgwEVtgZCuu2DA51sF0q67YMCbLU4Tr7tgwORCuFSvu2DASoKrlq+7YMBxw1zZr7tgwCHUsxywu2DAI4rbYLC7YMCqX5KmsLtgwPLTJO2wu2DA83PeM7G7YMBydGx6sbtgwJKSkMCxu2DA/T4SBrK7YMBdCk5KsrtgwBfqP42yu2DACIz7zrK7YMDShqwPs7tgwHZqBk+zu2DAyzOujbO7YMDaVKvLs7tgwISWQB20u2DA9JocXrS7YMAME1iDtLtgwJE818C0u2DA+6hkJbW7YMBp4RFptbtgwIelHa21u2DAI+hC8bW7YMCyrEoHtrtgwOPr4k22u2DArUgQlba7YMAmhGnctrtgwF05oCO3u2DANLp2are7YMBEMpawt7tgwM+tA/W3u2DAteeNN7i7YMBKdHh5uLtgwKAhibq4u2DAQURw+7i7YMBcujQ8ubtgwOE8/3y5u2DAN7+pvrm7YMAeyc4AurtgwHXPFWK6u2DAG2pNgLq7YMBrXgngurtgwO79NAu7u2DA0UPRXru7YMBbQ5WOu7tgwHmJlM+7u2DAM/EWELy7YMANKERQvLtgwDI9r5C8u2DA4bYy0Ly7YMDP6JIQvbtgwAn0sW29u2DAQ4vBkL27YMBrSOLRvbtgwLEOURO+u2DAbuWMVb67YMDYOKu9vrtgwAJ849u+u2DAvb84IL+7YMDiyh1lv7tgwHXlk6q/u2DA6GEp8L+7YMA536A1wLtgwPvm/HrAu2DAL/H4v8C7YMACClsEwbtgwC4gXU3Bu2DAJx45kMG7YMDiKB3NwbtgwFebcg7Cu2DAZWocT8K7YMC5K4aSwrtgwMwsZs7Cu2DAoQdhDcO7YMDxoxFMw7tgwG9QWYrDu2DA9+U3yMO7YMC4Z+oFxLtgwJKT0lTEu2DAF2pNgcS7YMDILjC/xLtgwKD8AiHFu2DAyl3JOsW7YMDCyFx6xbtgwB218bvFu2DAskmyMca7YMAyF5ZCxrtgwLr+FInGu2DAKY530ca7YMBK+Voax7tgwGiVdGPHu2DA3W5ErMe7YMBNCW70x7tgwAM43jLIu2DAOR2SgMi7YMC1MMHDyLtgwBAAlgXJu2DArsFxMsm7YMAny0N0ybtgwN5c47rJu2DAVAzb/cm7YMBP/W9CyrtgwOYHVYHKu2DA0svjyMq7YMDP/eMMy7tgwC9HSj3Lu2DAqCTue8u7YMBmW8u6y7tgwHHeafnLu2DAZUZgN8y7YMBA4zN2zLtgwH13m7bMu2DAXWQZ+My7YMD8+ec6zbtgwM74On/Nu2DAlNcgxc27YMAQbzkNzrtgwCye8lXOu2DAcPObns67YMD4aj3mzrtgwLegfizPu2DAgRAScc+7YMCnoxaxz7tgwIDbrfLPu2DAXyUTMNC7YMA59d1r0LtgwCQJAKfQu2DA2a9v4dC7YMA2f/ob0btgwEn3NlfRu2DAfMmCk9G7YMCpCP7Q0btgwMxbjw/Su2DAZNeBT9K7YMA2eKWQ0rtgwFvCOdPSu2DAGKvzFtO7YMA0ZtNb07tgwBA84djTu2DA22+nG9S7YMABWmcu1LtgwH1mwnTUu2DAIZLKutS7YMDT00kg1btgwHsi0F/Vu2DA8eqAh9W7YMAq/h7K1btgwC1AsR7Wu2DAhatXTta7YMAcB02g1rtgwGV4vdDWu2DASXaFJde7YMAD1nxU17tgwKl+aZXXu2DA6pM91te7YMBHBKEW2LtgwKHZDVbYu2DAb0cgldi7YMCPZOXS2LtgwMjIT0jZu2DAhTtuUNm7YMDRLDSL2btgwBJoUcrZu2DA8E+mCtq7YMB671NM2rtgwI+6sdvau2DAQ+4NHtu7YMCx4F1g27tgwJisAWXbu2DAs57Tqtu7YMDRGxrx27tgwHXGdjbcu2DA56Ffety7YMAo1Dm83LtgwF769Pzcu2DARF1JPd27YMDBk+V83btgwPrTN7zdu2DA+dd0+927YMBwfPY63rtgwGna0Xreu2DA0uRdu967YMDLGOr73rtgwO9Asjzfu2DATFS4fd+7YMAzy/a+37tgwEFhPwDgu2DAbemJQeC7YMAlK33L4LtgwE01HA7hu2DAUlbKBuG7YMCzniNJ4btgwKhf2Yvhu2DA4qXazuG7YMCpDCcS4rtgwDeCv1Xiu2DAHiSSmeK7YMBAxDci47tgwNHsNGTju2DA7n6AZeO7YMBO+LTn47tgwCNXqu3ju2DA+QVQMeS7YMBueH105LtgwAHt57bku2DAqvm0MOW7YMDI3w455btgwI0kl3jlu2DA/iUkt+W7YMAgFH715btgwAWohCDnu2DApw7aNOm7YMDZM23P6LtgwIMBjRXpu2DAyleCCOm7YMAmPoVJ6btgwElzznnqu2DAtgwuu+q7YMCR/M3z67tgwF8Epjfsu2DA1iGGKuy7YMCb0H9t7LtgwJmw26/su2DAnFws8Oy7YMCZEq0v7btgwN5NAbztu2DA9kCb++27YMByD8U77rtgwHnVTSvuu2DARZqqau67YMCga9yq7rtgwAwQ8uvuu2DAAt3CLe+7YMBslxFw77tgwLBEQhLwu2DAz6FS9u+7YMBQJxE68LtgwJVxMH7wu2DAG+YMwvC7YMAgcB8G8btgwLlQa0rxu2DAOK3VjvG7YMATnEPT8btgwLwl1xfyu2DAAcknXPK7YMDWv4ig8rtgwO/abuTyu2DATyE5KPO7YMDgh6hr87tgwMkPZ+bzu2DAqofHJ/S7YMCEv5Zo9LtgwBmlIqn0u2DA+riLtPS7YMDCEP0p9btgwAMecGr1u2DAWJYnq/W7YMC+6aG09btgwGUNWfT1u2DAOUvaM/a7YMAlNJpz9rtgwCm9PbT2u2DAu7duN/e7YMDmEJJ797tgwPaIqsD3u2DA0uquBvi7YMCx5cMI+LtgwOzOzlD4u2DA94uumPi7YMACz+Df+LtgwBwVQSb5u2DAfA5ga/m7YMBeN1Ou+btgwDMUWO/5u2DAbUYQLvq7YMC5nzRs+rtgwAZvDar6u2DA0LTx5/q7YMBxBhg6+7tgwDLDDGb7u2DAE8JMp/u7YMChbTjq+7tgwFteEy78u2DANHJacvy7YMD1oQu3/LtgwIis3fv8u2DA8YSGQP27YMAqhXiE/btgwMiPtsf9u2DA8Y3wF/67YMAzTUVN/rtgwMZHb4/+u2DA0zZm0f67YMCeyjAT/7tgwBpN7VT/u2DA/8iPlv+7YMCPulnY/7tgwIyLBxoAvGDAfLq5WwC8YMCW4HOdALxgwNxgNN8AvGDAJK//IAG8YMAPqNZiAbxgwOlHuaQBvGDAcRus5gG8YMBMw68oArxgwB7jyGoCvGDAnFTorAK8YMDudzDvArxgwCiqoDEDvGDA1EkIdAO8YMCsTzONA7xgwPILe/gDvGDAPk55OgS8YMBSuFB8BLxgwIt63L0EvGDADpgk/wS8YMA/MXJABbxgwHxHO4IFvGDAXPV/xAW8YMDbWWUHBrxgwPH80UoGvGDAE/M4jwa8YMBQdazUBrxgwMY0dRoHvGDA6VRcYAe8YMBC6BemB7xgwMejYOsHvGDANm4NMAi8YMBrrNZzCLxgwCrHfbYIvGDAJ8UQ+Ai8YMBCs984CbxgwJpluXgJvGDAHrG/twm8YMDnslb2CbxgwE4fOTQKvGDAPT23cQq8YMBlfB+vCrxgwFcl5OwKvGDAP5YHKwu8YMDaCEJqC7xgwEy9NaoLvGDA+oZC6wu8YMALpr8tDLxgwKrAbXEMvGDAK27HtQy8YMDDFaD6DLxgwIKPI0ANvGDAsOH6hA28YMCywxTKDbxgwJi2uw4OvGDACNjRUg68YMCC6peWDrxgwPHxxtkOvGDAc/p/HA+8YMA3yrFeD7xgwNwRWaAPvGDAQTaJ4Q+8YMDQPkciELxgwGe5tmIQvGDAXyjIohC8YMCPVY7iELxgwJ/SKSIRvGDAm3asYRG8YMChwQ0LEbxgwBPZruARvGDAw0dFIBK8YMBice5fErxgwK/Vtp8SvGDAlt6u3xK8YMCwoNsfE7xgwNHzKWATvGDAc/upoBO8YMDHFaPhE7xgwOMyNyMUvGDAspdzxhO8YMAie4OoFLxgwMDqJewUvGDA4IqRMBW8YMC2MtB1FbxgwKS/WbsVvGDAiQHxABa8YMBd2lhGFrxgwN7QVYsWvGDAvMK9zxa8YMCUYFMTF7xgwKy8NFYXvGDAkRPzlxe8YMDGN5fYF7xgwMuhTxgYvGDAKPHOVhi8YMCysoeUGLxgwKQYJdEYvGDA0MO7DBm8YMD0zBdIGbxgwPRA14MZvGDAEe6gwBm8YMCqKFD+GbxgwPqJZz0avGDAzgFdfhq8YMCr5k/BGrxgwKOWsQUbvGDAj1nBShu8YMBQbQ2QG7xgwK9dRtUbvGDA2jc6Ghy8YMCFzhdeHLxgwM31uqAcvGDAdGw/4hy8YMCqcxQjHbxgwD4QZWMdvGDAHYptox28YMBoWx7jHbxgwMf25CIevGDAnDIwYx68YMDMhqOjHrxgwEH77+MevGDAkuAPJB+8YMDFVe1jH7xgwJqKl6MfvGDA3NDp4h+8YMDJ04UhILxgwJ9W218gvGDACLk/niC8YMC/h/fcILxgwEEkARwhvGDAaU1/WyG8YMBRqJ2bIbxgwG73qdwhvGDATYpvHiK8YMA3sq5gIrxgwKWGSqMivGDAhaAT5iK8YMDMIuIoI7xgwPfNjGsjvGDAMj3rrSO8YMDApsbvI7xgwKFibDEkvGDAsObMciS8YMB8kOyzJLxgwKpzwfQkvGDArPjA4iO8YMDkdgd2JbxgwEl9frYlvGDAxOyi9iW8YMBzTmM2JrxgwCm8lHUmvGDAgdBmtCa8YMCMS8fyJrxgwH5YkDAnvGDAYiXQbSe8YMDzShqrJ7xgwH/WpOgnvGDA1iKeJii8YMCjhztlKLxgwNByoKQovGDACx/F5Ci8YMAZWxMmKbxgwFhLA2gpvGDAqcCnqim8YMAEv7PtKbxgwJ6QCTEqvGDANvp+dCq8YMA50uq3KrxgwFT6F/sqvGDAfgLIPSu8YMCFCeR/K7xgwB2FSMErvGDA54nGASy8YMBKxIhBLLxgwBLqOYAsvGDAFVL2vSy8YMCJTDH5LLxgwHArRzUtvGDAQhQNcy28YMB+WYmuLbxgwPI73OktvGDAxBkcJS68YMAHcFxgLrxgwBwaA5wuvGDAV5BK2C68YMCLBUcVL7xgwP4dOFMvvGDAT8XwkS+8YMC2Q9rRL7xgwO4fSBMwvGDAPPtRVTC8YMBSkZGXMLxgwKXhstkwvGDA3w40mi+8YMA3KaRcMbxgwJ6P+pwxvGDAPljz2zG8YMB9WfEZMrxgwGjPVFcyvGDA0LFVlDK8YMBssRvRMrxgwCnn2w0zvGDApnW5SjO8YMDl6yCIM7xgwD3ZIsYzvGDAQSVwBDS8YMD4cgtDNLxgwMymAoI0vGDAw1NBwTS8YMAMeMkANbxgwNCwiUA1vGDAQ81TgDW8YMBZyxrANbxgwNbD0v81vGDAkTxoPza8YMBNOuJ+NrxgwDVOSr42vGDArqtB/Ta8YMA63S08N7xgwBlOJ3s3vGDAKW4kuze8YMCgF7X6N7xgwEd5iDk4vGDAbCEsdTi8YMDh+61JN7xgwPejBAE5vGDAhpYyxTe8YMBuytICOLxgwEbLhUA4vGDA4T4hfTi8YMBAMZW8OLxgwPuZuv44vGDAMaf9yTq8YMBjZlYIO7xgwMm36kY7vGDA4BPshTu8YMDnlFrEO7xgwNy2/g88vGDALoyrTDy8YMC9p0+CPLxgwLz7X8M8vGDAXMW0BD28YMB2PJtFPbxgwA7tsoQ9vGDA7UXfxD28YMAkiT0FPrxgwNh5rUQ+vGDACNbCgj68YMCylgvCPrxgwLEYtQI/vGDAEnOiQz+8YMCvJ3OEP7xgwDZXN8Y/vGDAeH+7CEC8YMCh8f5KQLxgwGxp7oxAvGDAhlp6zkC8YMDjoyoPQbxgwFaTCk9BvGDAqb22jUG8YMA/EezKQbxgwDTVkQdCvGDAmm9qQ0K8YMC8xuV+QrxgwLQsl7pCvGDAU7Pu9kK8YMD2Sd8zQ7xgwMxhcHFDvGDAiFhgR0K8YMA4wxuHQrxgwPZLnCxEvGDA25ARakS8YMAaDUhJQ7xgwLv/NYtDvGDAd+cszEO8YMDNPHAMRLxgwC3Uo0xEvGDAkZ7F2UW8YMBeW2vNRLxgwJ8bRGVGvGDAkYfLm0a8YMCtOBrYRrxgwMxazRNHvGDAe7JAT0e8YMDrsR2KR7xgwENKTMVHvGDAGlZ+AEi8YMDgY3M6SLxgwAcPPHVIvGDAwBsMsUi8YMC9t5zpSLxgwFt3USZJvGDAhYoXY0m8YMDPQPafSbxgwGVYfdtJvGDAdtcLGUq8YMDF4iVXSrxgwMhXmpVKvGDAVS2NIkq8YMDXmBUjS7xgwCvhwGVLvGDA22cfqEu8YMCxaDtHTLxgwLXs1J5NvGDAhvNz2028YMC7N4gYTrxgwIQMvlROvGDApUiykE68YMCNcKrMTrxgwFyVNQhPvGDAVAj6SU68YMA93liFT7xgwBmP/sJPvGDADa61AFC8YMAENSlCULxgwMPsVYJQvGDAdS0Pw1C8YMD6z0cEUbxgwCTRtkRRvGDAjPGEiVG8YMBA8ivUUbxgwJiM4jdRvGDAPe8Od1G8YMB4N6W2UbxgwPWMC/dRvGDAdiNEFFO8YMD3GrlTU7xgwHN02pJTvGDAyorG0VO8YMB7MM4PVLxgwNkMg01UvGDADSCZilS8YMDoSY/GVLxgwAf4RgJVvGDAIKo+PlW8YMDnIt96VbxgwEAGj7hVvGDAnKXH9VW8YMBG4OYyVrxgwNf/5nBWvGDAGF0Vr1a8YMDN7g/vVrxgwBgEeS5XvGDA1WTFbFe8YMBxRpmnV7xgwPLMBe9XvGDADhOYole8YMDthyxtWLxgwJVzJiNYvGDAIOXq81i8YMD70AE0WbxgwJ0rrXBZvGDAhQNOsFm8YMD2ViHuWbxgwMtvHipavGDAYlohalq8YMAp3pKoWrxgwOqQP+ZavGDAmCRhI1u8YMCPmg9gW7xgwDCUB5xbvGDAGEETZ1u8YMDtsL4QXLxgwG/UcUpcvGDAG7rGh1y8YMA8cNnEXLxgwBgTSQNdvGDAxAc/Ql28YMDrpPyDXbxgwAYOkcVdvGDAUZqpBl68YMD09ntHXrxgwItuU4hevGDAdFUoyF68YMCi2tQHX7xgwKG+ZUZfvGDADhfMg1+8YMBBA2zCX7xgwD+z2wFgvGDAzgaOP2C8YMAjw9WAYLxgwF4fxsJgvGDAXZDVAmG8YMDUtwJGYbxgwOjwuYdhvGDAchd3yWG8YMAA5UwLYrxgwJabFkxivGDAXmq5imK8YMCCupLHYrxgwOOh9QNjvGDAzIniP2O8YMAGCc57Y7xgwMuTE7hjvGDA0YEZ9WO8YMCeTggzZLxgwH3/PHJkvGDAjYyAsmS8YMC4CkbzZLxgwCmIbTRlvGDAkpHKdWW8YMDqL9+3ZbxgwFqmYvllvGDA7wIwO2a8YMCG7NF6ZrxgwBv7RLtmvGDABQ3U+2a8YMDz7KM9Z7xgwOp2231nvGDAAGMRv2e8YMARshMAaLxgwM+UIj5ovGDACDwZgGi8YMAGTUvAaLxgwDovEwBpvGDAEi5DQGm8YMDYmlyHabxgwPsS7clpvGDAVXXP/mm8YMCQKFBSarxgwK7ZRJVqvGDA106r3Gq8YMDwu8r9arxgwAUaGzxrvGDAjh95fmu8YMBoZNHBa7xgwCBYiARsvGDAY9LbR2y8YMCKZPWGbLxgwOX1MdNsvGDArJKZXm28YMD8qOpcbbxgwHsKT6BtvGDAk5q34228YMAdmeszbrxgwG/956ZuvGDA0JqEwm68YMB0W5HrbrxgwFaZaC1vvGDAjq8acW+8YMBkniy1b7xgwAV4r/hvvGDArc8LO3C8YMAYgb18cLxgwMeqFr5wvGDA1OTo/3C8YMC511VCcbxgwDYKDYNxvGDAUkv9wnG8YMDnIbYCcrxgwPRr9EFyvGDAJnSYgXK8YMCSyL++crxgwNi4gftyvGDAFK32OXO8YMC3L4Z5c7xgwI7D27lzvGDAPqT4+nO8YMAxJV49dLxgwCGjLLF1vGDAsSlb9nW8YMCFL1k9drxgwOd3uoR2vGDANXJByXa8YMBN7nMOd7xgwIjHjFB3vGDABZLEk3e8YMCEKu7ldrxgwJJ17xp4vGDA6r/YXXi8YMARQcevebxgwC7BYfZ5vGDAN+n1PHq8YMBYpriCerxgwNU4f8p6vGDAM0iOEnu8YMDqRaBae7xgwKZxWaN7vGDAF7ds6Hu8YMDJO+4ufLxgwO6L9XZ8vGDA7VuG93y8YMBy3mo4fbxgwPSGh3p9vGDAdRH2vH28YMBbpr78fbxgwGEaUyV+vGDApMVHaH68YMA9TGPIfbxgwPZHs+5+vGDAz9lfMn+8YMAc6Gx2f7xgwHWrMr1/vGDA9M26AYC8YMBFuXdGf7xgwETnfIh/vGDAH/B2y3+8YMDywr8OgLxgwAZYtlKAvGDAd/z+loC8YMBiw/LagLxgwO6w7yGBvGDA85qPZoG8YMAF2p6ogbxgwGZIgOqBvGDARvxQLIK8YMBzaltxgrxgwA+w3bSCvGDAO3oC94K8YMCBFKdAg7xgwAxVKY2DvGDAn5J7yYO8YMBayF0NhLxgwAWM0UyEvGDASd5mxYW8YMAIJyANhrxgwHwwBVSGvGDAR6qsZYW8YMDBGDWqhbxgwF/GO+6FvGDAnhstMoa8YMD5FBl2hrxgwLwjrbqGvGDAqy3W/oa8YMABnW5Ch7xgwDXofoaHvGDA+QkIy4e8YMBV+hUPiLxgwB7ry1KIvGDALnbrloi8YMDuaoraiLxgwEoI8xuJvGDAYHvjXom8YMB99VeGi7xgwPkgKcuLvGDA5RWAD4y8YMByoVZUjLxgwGsLZZiMvGDAmYHV3oy8YMCpaHIjjbxgwO1eDGeNvGDAb9fVPo68YMAPlEqGjrxgwKXJ+BSPvGDA+8cx7I+8YMBu0zkzkLxgwIz9BnmQvGDAbqB6vZC8YMDFAnEAkbxgwFUJUUORvGDA60/xh5G8YMAwA73NkbxgwFibyRSSvGDAyCgpXpK8YMAhUcemkrxgwAyRU+6SvGDAwLCrM5O8YMD/yEd6k7xgwDW/ZNWUvGDAn6u9F5W8YMCzcPCalbxgwJxHTuCVvGDAyCQOJ5a8YMBWmflslrxgwJkgAbOWvGDAOR+i9pa8YMB618o9l7xgwGPSBIGXvGDAsahpxZe8YMB5hIsJmLxgwDER3U6YvGDAa1vNJJm8YMBSwplhm7xgwFiHAKibvGDAgb3fAJu8YMCjPLaNnbxgwIHvTdCdvGDA4btST568YMAcP0eSnrxgwBJSMNeevGDAcIwrHZ+8YMAcdr/zn7xgwD2yqzygvGDAobMhhaC8YMCpfnjLoLxgwATdeGeivGDAvA4Zfqa8YMAqQ8TFprxgwKId2UynvGDA4oPZjqe8YMDebtoOqLxgwCJHVC2qvGDAe/JXc6q8YMC61ZS7qrxgwK/s5f2qvGDAzjFNhKu8YMDVLhfKq7xgwOUxdw2svGDAvSmqNaq8YMByS3GSrLxgwEmPutWsvGDAtz9VFq28YMBnBN4wq7xgwENWzHSrvGDAaU+XvKu8YMBMqyz/q7xgwGA6CVKsvGDAGK7HnK68YMCHkqvhrrxgwF5aJB+vvGDA8Zlnlq28YMBxAv3nrbxgwPNP4yiuvGDAskUCd668YMDM2+/DrrxgwKoCSgWvvGDAi1MX0rC8YMDqNsWVr7xgwLh3dlmxvGDANVVWIbC8YMB3CyxlsLxgwACMWKqwvGDAtGxm7rC8YMAeu8AzsbxgwESEQXixvGDA6DxeqbG8YMAIChDzsbxgwOLaQUeyvGDAbsPdibK8YMCuQN/EsrxgwL5UAxOzvGDAuwRAVrO8YMA3qSCas7xgwAB1L96zvGDA0DH6IrS8YMDmY9VntLxgwMo8EAq2vGDAwV9t8LS8YMB4Uzs8tbxgwKe3+oG1vGDAY3opyrW8YMASuXURtrxgwLEvvVa2vGDARaL87Le8YMDGNkzrtrxgwKWOMHq4vGDATOvFaLe8YMAnZ9Out7xgwCapLvW3vGDAG116O7i8YMDszxeCuLxgwBjGEMm4vGDA5orpD7m8YMDNghZ2urxgwPkr6py5vGDAhF3g4rm8YMDQAGEourxgwLXuXG26vGDAjWDcsbq8YMATwtn1urxgwBCP9UG8vGDAyOJZfLu8YMDfFRy/u7xgwBvkvQG8vGDAlsILRLy8YMBY4CaGvLxgwPzYl8i8vGDA7tCsC728YMARe4VPvbxgwBUxN5S9vGDAJ/OL2b28YMC8bocgvrxgwJ+7Zmi+vGDAsO71sL68YMC0+q75vrxgwE3pbkK/vGDAxBacir+8YMDTon7Sv7xgwLDrkxnAvGDAV9kiPsG8YMD5AU6kwLxgwMH2+ujAvGDA8Kk5LcG8YMDI8kJxwbxgwFFTIbXBvGDAA71S+cG8YMB60hg+wrxgwLkIyoLCvGDAhGU4x8K8YMCxMTkLw7xgwH5dyU7DvGDAKZMMksO8YMBS8IXUw7xgwIj51hXEvGDAOIT4VsS8YMCF8pGYxLxgwNLi0NrEvGDATfUKHsW8YMC107YvxrxgwC539KfFvGDABwDv78W8YMC7mdA4xrxgwIaxyD7HvGDAxnF6y8a8YMCy6AQUx7xgwAB/+EfIvGDAtz/v8Me8YMAV8TUsyLxgwOWZt2/IvGDA9BVGssi8YMDjpXKUybxgwJCkvTbJvGDAoEmHeMm8YMAv1NdayrxgwBtzYv7JvGDAdlSR3sq8YMB3NlUgy7xgwE2N/WHLvGDAPUhqDMu8YMAY7MJQy7xgwOa0MZXLvGDAUwaP2su8YMAISJOpzLxgwLGwd+rMvGDAVRJ5qsy8YMCmyaHvzLxgwOtKtjTNvGDAecuXec28YMA4vTu+zbxgwMri1ALOvGDAl+tkR868YMB4sAWMzrxgwIwlutDOvGDA/vRWFc+8YMCQOSBaz7xgwI3XIp/PvGDAfbExSdC8YMBCpJCN0LxgwBxcqG3QvGDAzxPuEtG8YMDAqCZS0bxgwP4lzTnRvGDAAWEMfdG8YMAYXwLA0bxgwCZW4QLSvGDArRGuRdK8YMAVoYiI0rxgwJ4SdcvSvGDASiyQDtO8YMAKHLCj07xgwPYafZXTvGDAy6Hc2NO8YMBQSfIb1LxgwIDb8MXUvGDA9IqYodS8YMB6w7nj1LxgwC42BiXVvGDAFsYGZtW8YMC0HqgG1rxgwPtPfkjWvGDAwD5Fh9a8YMD9UUjH1rxgwED1UzXXvGDA1IQClte8YMABHcHf17xgwGZNvyLYvGDAr9NxH9i8YMDyGSRX2LxgwCKzNVXYvGDACpHi39i8YMCoYqMg2bxgwLB5lmHZvGDAxOtkYNm8YMBJX6A+2rxgwE56qzLavGDA8NyDeNq8YMBm19TK2rxgwECSwT3bvGDALfckO9u8YMBArDdW27xgwAiwHFvcvGDAkolTutu8YMCqbg3527xgwJQvFzbcvGDANX2Eedy8YMCz93G83LxgwON6tf/cvGDAfyHdQt28YMD+WaiB3rxgwDasyvLdvGDAA5yXO968YMDGGSh83rxgwHQa8b7evGDAcSWyBd+8YMD0pM4T4LxgwGEdgFPgvGDAm78tleC8YMCaB+DW4LxgwJTGLRjhvGDAeCv3WOG8YMBhR0ub4bxgwAi3jt3hvGDAfzdWI+K8YMB5VVBo4rxgwDlJGq/ivGDA9GqW9eK8YMDDdIk747xgwOi0voHjvGDArT9ATum8YMAIaGKS6bxgwHSYrtXpvGDAc3ipGeq8YMAWqvih6rxgwM9TPefqvGDARZtVAO28YMCuK25B7bxgwHze2oTtvGDAbhMPyO28YMC8zTMK7rxgwMgtaE7uvGDAnqMCk+68YMBFzJbY7rxgwOlwOBXxvGDAFPeCW/G8YMCKUnug8bxgwIvRB+XxvGDAuISFKPK8YMDeVUNq8rxgwIvOqqvyvGDAhz737fK8YMAkaOwv87xgwEgOIHLzvGDAjt91hPK8YMBmp9aZ8rxgwBzq1NzyvGDAvKklLPO8YMAOBJtc87xgwATEn5vzvGDAsSRL2/O8YMBmMlsc9LxgwGoq1V30vGDAn3m8ofS8YMCJHZ/m9LxgwJT5RSv1vGDAdSx7W/a8YMDrq/6f9rxgwFcFUvj1vGDAnu4cO/a8YMBQKtt89rxgwNPPB772vGDAVcoA//a8YMAfXvI/97xgwEiENIH3vGDAF+vXwve8YMCTViIF+LxgwI5OYkj4vGDAAk0aivm8YMCXfqXQ+LxgwNmXcxX5vGDAp43RWvm8YMDmyhGg+bxgwPIWqOX5vGDA5tAcK/q8YMARa2tw+rxgwKvsZ7X6vGDAmZy/9/q8YMAgGypC/LxgwG8pQ4j8vGDAXvLisvu8YMAy9HgA/LxgwPvMOEn8vGDA1w7Jivy8YMCdcfzL/LxgwOd+CA39vGDAKJ77Tf28YMBvnPiO/bxgwNoJH9D9vGDA5/OKEf68YMCXYiBT/rxgwMV6EJX+vGDAnYQ/1/68YMC/NP0Z/7xgwCM83Vz/vGDAdh09oP+8YMCD1fvj/7xgwAXMGSgAvWDApEyVbAC9YMCIgGKxAL1gwKybefYAvWDAeivQOwG9YMB82V2BAb1gwHo7FMcBvWDACEDKDAK9YMCow2hSAr1gwG7C9ZcCvWDAgdVR3QK9YMBQL3giA71gwBO/YWcDvWDAMiriqwO9YMBbIdHvA71gwFF+nTMEvWDAgE/FdgS9YMC++n+5BL1gwKhG4PsEvWDA3pOiPQW9YMBQEWZ/Bb1gwDBju8AFvWDAi78mAga9YMCLJrVDBr1gwPK6a4UGvWDAKRr2Sgi9YMAVIhEKB71gwCWIEU0HvWDAVUyGkAe9YMCPRtJZCb1gwD3HERgIvWDA4CAgXAi9YMD+DXegCL1gwO2nw+QIvWDAKpriKAm9YMDH9iSbC71gwKlKUbEJvWDARFd8IAq9YMCEZldyDL1gwGCdBZ0KvWDAH7/G3Qq9YMAQOi4JC71gwIlrv3QLvWDAJaMN6A29YMB7+rUvDr1gwMO8RXYOvWDA/KKKug69YMBxwkOtDL1gwOt8heMMvWDAp61lJQ29YMCqffLAD71gwNKVEawNvWDA3Hy49A29YMBhVwM5Dr1gwFzLHHcOvWDA1uMPvQ69YMD+XAQED71gwKkKmwkRvWDAzx3DUxG9YMDiRKidEb1gwBbY+OURvWDAnLKwaBC9YMCaj+NyEr1gwEVLWrgSvWDAWV2b/RK9YMATdGMaEr1gwPrx610SvWDAOMWgohK9YMA4IrfnEr1gwCRiiFoUvWDAIaPXoRS9YMDqmq/pFL1gwMp5GNcVvWDAWZ44Hha9YMCK6M9lFr1gwEPSla0WvWDALX4X9Ra9YMDQragJFb1gwG9UaekWvWDAz4N/MRe9YMBXn/14F71gwOJEZ78XvWDA8I1zDRa9YMAhZKtIGL1gwJ6qupgWvWDABS8M2Ba9YMDLnW8+F71gwFaim3QXvWDAoiU9vRe9YMD+CR7kGb1gwHGgX0sYvWDAbLCIkRi9YMAYWmiuGr1gwFczsvkavWDAwG4f+Bm9YMCFdoyPG71gwAoO1XoavWDANSKPHBy9YMCtMwQHG71gwPt1Ak4bvWDAY6gpkRu9YMAb+27FG71gwM9luBccvWDA+2pWWhy9YMBQYsGdHL1gwBZZt+EcvWDA8a9ulx69YMAF0YHfHr1gwFwjDCgfvWDADTALcR+9YMBpLbe6H71gwBGsmecdvWDAkzlVMB69YMDpM3R5Hr1gwKci0cIevWDAhtZyCx+9YMAEtblTH71gwEIvibUhvWDAKXY04h+9YMBGxbsnIL1gwKChYWwgvWDAEyRLsCC9YMDoXZjzIL1gwIh3ZzYhvWDAcNL8eCG9YMAy/XW7Ib1gwEKH7x8kvWDAIluyQCK9YMACqyqEIr1gwKjLV8givWDARcAzDSO9YMDbr8pSI71gwBHFiZkjvWDAD9034SO9YMCDs6ApJL1gwLLZZXIkvWDArN5GuyS9YMDSlwgEJb1gwG91hUwlvWDAZg5RlCW9YMCBKIXbJb1gwHlS6CEmvWDAAOPoZya9YMAwPk+tJr1gwEiSRvImvWDAsyDlNie9YMDGGUR7J71gwOMya78nvWDAmBWVAyi9YMCWHeVHKL1gwK84jIwovWDAvnN50Si9YMCDf9wWKb1gwHNxrFwpvWDAhQo8oym9YMAgjVbqKb1gwL7+uTEqvWDAhrdPeSq9YMAvBBLBKr1gwFrU1QgrvWDA4B+BUCu9YMCmrh6YK71gwAI3PBUuvWDAasVUXC69YMDwUWltLL1gwKh59rMsvWDAqyZh+iy9YMDAdYRALb1gwHEjSIYtvWDAXq7eyy29YMARrJQRLr1gwARzo1cuvWDAWAUIni69YMC1wf/kLr1gwPtL/2wxvWDA6kWqszG9YMBNO4f6Mb1gwPVPBQcwvWDAWRUoUDC9YMDBP+CYML1gwE5xLuEwvWDAiO7pKDG9YMAoCoVvMb1gwFF8GrUxvWDA1IIw+jG9YMCGduGHNL1gwLKOS4MyvWDAb6myxzK9YMBiQUwMM71gwJ1TIVEzvWDACw2eljO9YMBsI3fcM71gwDLu7SI0vWDA7hMQajS9YMBRQJyxNL1gwM8Nx/k0vWDA9DGFQjW9YMDJLqOLNb1gwAVuGtU1vWDAWct9Hja9YMC1m35nNr1gwNHDSLA2vWDA/8KW+Da9YMBlbVpAN71gwM53UIc3vWDAhM+gzTe9YMAHcN0SOL1gwNDIg1c4vWDATTlYmzi9YMBn9uDeOL1gwDqFTiE5vWDAh64ZYzm9YMD6vNXlO71gwKSyOOc5vWDAIT/vKTq9YMBOJ35tOr1gwEyvuAs9vWDAYGbKVD29YMB4Ghw/O71gwOexoYc7vWDA/9rf0Du9YMBu5PMaPL1gwE8ikGU8vWDA4q9ZsDy9YMB8Hy37PL1gwOq84EU9vWDAQEErzT+9YMAeadHZPb1gwNblyyI+vWDAQ59Qaz69YMAJNgSzPr1gwDph+/k+vWDAnJEYQD+9YMD933OFP71gwJizw8o/vWDAzielD0C9YMDyL3ZUQL1gwFMuQJlAvWDATElW3kC9YMBlgeAjQb1gwGZk5mlBvWDA4EJ7sEG9YMABp4r3Qb1gwJ4P+T5CvWDASdV2s0S9YMBXS+XOQr1gwJRIiBdDvWDASsAyYEO9YMBb9RipQ71gwBfbQ/JDvWDAdtOMO0S9YMBRW/CERL1gwPB5Q85EvWDAl9LDF0W9YMADVQNrR71gwGTARapFvWDAUfp98kW9YMBfV745Rr1gwC1aMoBGvWDAim+DxUa9YMCEmccJR71gwEZOh0xHvWDAmav0jke9YMAHLVXRR71gwKhgAhRIvWDAO9MyV0i9YMCNMCObSL1gwHtQgOBIvWDA1yJrJ0m9YMDnVqBzS71gwHDxd7dJvWDAtudlAEq9YMBzDKpJSr1gwFzt/ZJKvWDALdEY3Eq9YMDm/7MkS71gwHBq02xLvWDAs8cJtUu9YMDKyN/8S71gwP2kakJOvWDA3JzUi0y9YMCvHBrTTL1gwNJGnhpNvWDAyy6/YU29YMDH8i+oTb1gwE8Kq+5NvWDAq4VaNE69YMAP1oN5Tr1gwIYpCL5OvWDAvn2lAU+9YMCx4vtET71gwIzxW4BRvWDAfpgYxFG9YMABsEURUL1gwM6SwFZQvWDA3ExgnVC9YMAyN/nSUr1gwD0zGS9RvWDAvEGZeFG9YMA9FdPBUb1gwEcdBwtSvWDAR4fBUlK9YMACJcxrVL1gwINUdd9SvWDAWvfkI1O9YMAyHuFnU71gwN99GX1VvWDA9uUPwVW9YMBDLyk3VL1gwJOBJX5UvWDAZ/CCxlS9YMD7DpoQVb1gwEMVThJXvWDAdq2LVVe9YMCddTDxVb1gwDIByDtWvWDAPB2+hVa9YMCsI0DOVr1gwBi9vBVXvWDAmTJAXFe9YMDowfahV71gwDW92+ZXvWDAxvNnK1i9YMCmmGNvWL1gwPE7orJYvWDAitPv9Vi9YMBjVWc5Wb1gwK/XOH1ZvWDAjbADbVu9YMAx1mkGWr1gwENixEtavWDAK4Ndklq9YMBUh5jZWr1gwAlQdSFbvWDAnLuzaVu9YMDzlDSyW71gwLEwyvpbvWDAQzdSQ1y9YMCgZWeLXL1gwKieS9NcvWDAikjpGl29YMBBeTliXb1gwFSCHqldvWDA3fjaUl+9YMAc6zQ2Xr1gwNsYa3xevWDAx16Wwl69YMDEOHYIX71gwDdM301fvWDA87jukl+9YMBsQJ/XX71gwMotJxxgvWDAuDT2X2C9YMCyFWmjYL1gwMTm4+ZgvWDA4BarKmG9YMC/zO1uYb1gwN3w4rNhvWDAdK2K+WG9YMDhlVBAYr1gwFSB0odivWDArTxY0GK9YMCiWCwZY71gwLq6I2JjvWDAZRApq2O9YMDTWfjzY71gwJ3jQDxkvWDA1LPlg2S9YMAC/+bKZL1gwHxlOhFlvWDAN7cJV2W9YMALTVScZb1gwH35JuFlvWDA0v+GJWa9YMBO9M51Z71gwEBdGrlnvWDAJidd/Ge9YMA1QDo1Z71gwGlHPXlnvWDATX+IvWe9YMBYMCMCaL1gwHfdaEdpvWDAk11vjGi9YMAo32HSaL1gwKJhwhhpvWDAOkNdX2m9YMCshEemab1gwCvXje1pvWDALosJNWq9YMB6fJt8ar1gwKM2OMRqvWDAGPTBC2u9YMAwbWokbL1gwGzrlGdsvWDAp0Rk4Wu9YMBqNQMobL1gwOMmXW5svWDAhI1vtGy9YMDv5Dr6bL1gwEfqqD9tvWDA/iRgMm69YMAUHC/Kbb1gwP+ANQ9uvWDAODtHVG69YMDsXD+Zbr1gwO+lJd5uvWDAtmH0Im+9YMA4crhnb71gwM6JeKxvvWDAiVEp8W+9YMBpx9Y1cL1gwBvzgHpwvWDAYRFNv3C9YMDkL0gEcb1gwID9cUlxvWDAhzi1jnG9YMBFklPUcb1gwOQNJBpyvWDAykkAYHK9YMDEfbilcr1gwInKNutyvWDABFdWMHO9YMBNES11c71gwErFgblzvWDAGMki/XO9YMDcxohAdL1gwI4Kt4N0vWDA35jPxnS9YMA8h98Jdb1gwCD0C011vWDAmik4kHW9YMC4QvPTdb1gwLLP6hd2vWDAKks8XHa9YMBo1fWgdr1gwB0LFuZ2vWDALvqMK3e9YMBwtVtxd71gwJ6Lu7d3vWDAbpEv/ne9YMAO4YNEeL1gwPBvYop4vWDAWbkO0Hi9YMB2TxUVeb1gwK4BW1l5vWDApm+znHm9YMAB7mzfeb1gwDhg5SF6vWDA+yJUZHq9YMAPv/Kmer1gwDU53ul6vWDAqzwhLXu9YMBbd5Nxe71gwOzqc7Z7vWDAmi6S+3u9YMDt2s9AfL1gwCV6C4Z8vWDAiMwpy3y9YMDhnvUPfb1gwMRGHlR9vWDApIbWl329YMCFmUvbfb1gwH2LiB5+vWDA086gYX69YMBeAKekfr1gwGvrred+vWDAMPrkKn+9YMAZ/Fluf71gwH/90rF/vWDAg9hK9X+9YMDlCqM4gL1gwH2n9HuAvWDAiU4/v4C9YMBhwz0Cgb1gwCoY6ESBvWDABIPIh4G9YMBcFN3Kgb1gwAZWvJqBvWDAHPCwUoK9YMARaCiXgr1gwCezZdyCvWDAwf5CIoO9YMDaEC9og71gwMDus62DvWDABHCj8oO9YMAycqY2hL1gwN5113mEvWDAPmZqu4S9YMCpIun7hL1gwBqrTTuFvWDADv8geoW9YMCnVey4hb1gwKVyffeFvWDAHHhWNoa9YMB8us91hr1gwHeqL7aGvWDANnhR94a9YMADMTk5h71gwAwD4XuHvWDAqyWDv4e9YMAQOzUEiL1gwIQryUiIvWDA1ZW0joi9YMCQ9sXUiL1gwOXz8xqJvWDA50HlYIm9YMDta2Gmib1gwKNnTOuJvWDAHBhKL4q9YMCKaX5yir1gwDtwx7SKvWDAFs8c9oq9YMDUNsc2i71gwHe2v3aLvWDAOQswtou9YMD3UDn1i71gwDj7tDOMvWDAhE8icoy9YMAwlQGxjL1gwF07SPCMvWDAZqdEMI29YMAp1xVxjb1gwPlZ1bKNvWDAJ0fn9Y29YMA/nS46jr1gwNorhX6OvWDAmHk6w469YMCrGOsHj71gwHEUFUyPvWDA3WXSj4+9YMBOYKKvjr1gwDa4yhWQvWDAOhaaV5C9YMAo0AGZkL1gwA27s9mQvWDA2AHiGpG9YMA7GIVbkb1gwE/GXZyRvWDA+q1O3ZG9YMCCISUekr1gwCxu1V6SvWDAZX5dn5K9YMA3ZZOvkb1gwIS80B+TvWDAuACpX5O9YMCgWSqfk71gwOLFgKWSvWDAL7M14pK9YMDU8jpblL1gwK2hO52UvWDAfzUW3pS9YMBFgtwelb1gwCorDGCVvWDAjrh2oZW9YMDwuPzilb1gwB+3gySWvWDA6ij9ZZa9YMCr9F+nlr1gwGSzieiWvWDAN5JCKZe9YMD01N9pl71gwOmZZKqXvWDAgpv86pe9YMDQBJgrmL1gwIs3L2yYvWDAvGkJrZi9YMDmlC7umL1gwN5iTC+ZvWDAZj82cJm9YMBkXOWwmb1gwKDGSfGZvWDAeXZhMZq9YMB8f99wmr1gwNmBza+avWDAYIR07pq9YMBW9wktm71gwGECrWubvWDA+7N2qpu9YMDlFG7pm71gwAIs3yicvWDAa6bUaJy9YMCCtiGpnL1gwOWVh+mcvWDAvJH/KZ29YMBWSGdqnb1gwMYGqKqdvWDAfrOj6p29YMB9I/C2nL1gwIR4ammevWDASD2hqJ69YMC9EGHnnr1gwD+O5yWfvWDAUP9LZJ+9YMCy27Exnr1gwOxgnOCfvWDASGm2HqC9YMChmRFdoL1gwFah9pugvWDAvTxK26C9YMBerzsbob1gwKM0xluhvWDAixQanaG9YMDwyDrfob1gwCQefSGivWDAEPzRY6K9YMCGq/qlor1gwOsm3eeivWDApttQKaO9YMD92RRqo71gwA6/C6qjvWDAA4a96aO9YMBF/k4ppL1gwNAubGikvWDAZNusp6S9YMDybNvmpL1gwMq3vyalvWDAdwpaZqW9YMCO2jOmpb1gwMQp0eWlvWDAjuE9Jaa9YMC9l7rppL1gwMfTDqKmvWDAVv4M06a9YMAZsx0gp71gwAoe5l2nvWDACXLsm6e9YMCk4D9qpr1gwN1oPheovWDAWyCs7Ka9YMA3C1ssp71gwBCyTMeovWDAatW/Cam9YMBrrqdQqb1gwDBTro6pvWDAgHoUzqm9YMAE8LwNqr1gwLigl02qvWDALiOnMKm9YMBc7BR0qb1gwMOXX7upvWDAInYx/qm9YMBCyQWOq71gwGFTb86rvWDA6cjzxKq9YMD47+pPrL1gwG3TkpCsvWDA0de40Ky9YMBizU4Qrb1gwGZMpk+tvWDAUmlFPKy9YMAI4PXLrb1gwEyzn7usvWDA2jz7RK69YMBJJ12Brr1gwMg0Cr6uvWDAsQAQ+669YMAfVGv0rb1gwECBtXevvWDAC9aQt6+9YMBr81n4r71gwDiRpzmwvWDAGK03e7C9YMDAd+W8sL1gwEUUk/6wvWDAWlr0P7G9YMB8BcOAsb1gwEPTLcGxvWDAESoKAbK9YMCWwq1Asr1gwGpT9H+yvWDAO6X3vrK9YMCd5Mr9sr1gwGdXijyzvWDAokQ5e7O9YMABJniHsr1gwNtuNfizvWDAhGSPNrS9YMClhAN1tL1gwGs9brO0vWDAfTbq8bS9YMAOUYEwtb1gwBsPIW+1vWDAdMPGrbW9YMBJ32/stb1gwGABKiu2vWDAqAoFara9YMBd0rWotr1gwKaLYOe2vWDAMX1nJre9YMC6KO5lt71gwOP0Baa3vWDAvD+h5re9YMAzkYQnuL1gwMXMlmm4vWDApqFyrLi9YMB3u/fuuL1gwAv3BDG5vWDAS6hCdbi9YMBHpUG3uL1gwKJVG+u5vWDATHDwvrq9YMC/qjvKur1gwArkJaa6vWDAbpgq7bm9YMAq4MFIu71gwEkacV+7vWDACJwBlbu9YMBnKvzgur1gwGMy4B+7vWDAVuEdUry9YMCruiyTvL1gwFvqvNS8vWDAGx5zF729YMCwThtZvb1gwMWZhbq8vWDAKvf5A729YMBm5XtNvb1gwACfjpa9vWDAons6mr69YMCZRJfZvr1gwJeYvhi/vWDAf2VTq769YMAkkIuXv71gwNvb09a/vWDAlsT4FcC9YMBRq+VVwL1gwOmVTOW/vWDAuh5Y1cC9YMAs248Vwb1gwHkfwVTBvWDArwqFlMG9YMAZlerTwb1gwEDoAV3BvWDA/V+ZWcK9YMBZoZSmwr1gwJZ0h9HCvWDAqUGAEMO9YMAYrBChwr1gwDnpUuTCvWDAPrHjzMO9YMBKeCEMxL1gwIxN2kvEvWDA3O0ojMS9YMBVgTbNxL1gwLbdsw7FvWDAYE6stcS9YMBLbgeRxb1gwKV6DjvFvWDAbS9cFca9YMCl2adWxr1gwNPxTZfGvWDA1qWA18a9YMBKFpYXx71gwNGUm1fHvWDA7A24l8e9YMA3H9fXx71gwPZxGhjIvWDAVYQiWci9YMByVF+ayL1gwIZMrNvIvWDAHZooHMm9YMCYdiBcyb1gwOi73ZvJvWDAMgYP28m9YMA0wgAZyr1gwKAOEFbKvWDAD9W0k8q9YMBSsrHQyr1gwGrzXw7LvWDA7VvNTMu9YMCHVkiMy71gwJlfcs3LvWDA1Js0D8y9YMALr7tRzL1gwMG48ZTMvWDAe10VfMy9YMDHKT++zL1gwIaSV1/NvWDAN9ppos29YMANbHjkzb1gwLn45CbOvWDAcCM0Zs69YMA8WIuozr1gwOb745nOvWDAOxeXKM+9YMBBDmhoz71gwIFzYqjPvWDAGIKh5c+9YMDnB/gi0L1gwEUJEWTQvWDAXSeNo9C9YMBLD0Ov0L1gwAtbWybRvWDA7aGcaNG9YMBpjGir0b1gwNIF7U3SvWDAPOBdmtK9YMA0EA7X0r1gwNgowvPSvWDAU4rGx9O9YMCkYpoG1L1gwFkgZ7HTvWDAVDEKLtS9YMBXUWXD1L1gwKt9ppHUvWDATGtdjdS9YMDY8e3v1L1gwAeP+THVvWDALu33c9W9YMBhnhWb1b1gwPzLzvrVvWDAH+WNPda9YMCsCvGA1r1gwFsrPMTWvWDA6U03B9e9YMBEp+tJ171gwKfgJ4zXvWDAmfHnzde9YMBH2hEP2L1gwMzwz0/YvWDAUPTij9i9YMB52oPP2L1gwCIi3g7ZvWDAvXMQTtm9YMAmOkWN2b1gwB/fj8zZvWDAzxwTDNq9YMBYlvVL2r1gwBm2x5PavWDAqNcZzdq9YMCpkEIO271gwG0A7k/bvWDAvgD/kdu9YMAD+lHU271gwLJkQRfcvWDAn5JyWty9YMDTWBSm3L1gwDYa7eDcvWDAjCKXKN29YMDlhZ5m3b1gwNvzBKndvWDAWlz76t29YMBSBmUs3r1gwLY9wG3evWDAwPyDu969YMB/pd/u3r1gwKw4iy/fvWDAMbMtcN+9YMCvWbKw371gwIavcfHfvWDAJ3tpMuC9YMDwDrZz4L1gwLN8U7XgvWDA/PF3DOG9YMAGF0RR4b1gwP0kc5jhvWDAJqw33+G9YMC9Por74b1gwK0evk3ivWDAVi4QieK9YMDs8fPK4r1gwFdGvaXjvWDAj2c06OO9YMCyXhUh5L1gwMYl0NLjvWDA9BdmFOS9YMDsZFpW5L1gwKWRtMbkvWDAbfFDcOW9YMCr9BAv5b1gwErIy4zlvWDA2QbTwuW9YMCViNTw5b1gwFh3cCPmvWDAiyZdZua9YMAs/TzT5r1gwLeYUevmvWDAojs3Lee9YMA4NyVv571gwJHLLbHnvWDAdpxk8+e9YMBTW9A16L1gwAbSfHjovWDAbGd5u+i9YMBHCwr/6L1gwADR2ULpvWDAkqu6hum9YMDxFFbK6b1gwA7E7xDqvWDADn4HXuq9YMDLvAKa6r1gwIxWq9jqvWDAQWHBGuu9YMBb07Jc671gwPZ/raHrvWDAoZhI5Ou9YMA7+oUl7L1gwB+AfmbsvWDAztHSp+y9YMA6wDTo7L1gwFSnWyjtvWDAB7u1ae29YMAuhX+r7b1gwEIyi+3tvWDAlW2cL+69YMC4BXBy7r1gwNnoi7buvWDAuB56++69YMC7US0+771gwIavkIrvvWDAWK7Jwe+9YMC82QwE8L1gwJ54Q0bwvWDAzy/oiPC9YMC6bIPL8L1gwAwADQ7xvWDANRCRUPG9YMDqXxiT8b1gwF08rNXxvWDA2c1nGPK9YMDxG1Fb8r1gwOLwRJ7yvWDACbVB4fK9YMDB7Twk871gwL/kOGfzvWDAoaUvqvO9YMCYsvTs871gwHavjC/0vWDAUhEfcvS9YMA4+8C09L1gwAOScPf0vWDA5s8xOvW9YMAsKfp89b1gwHoxEcD1vWDAzJJsA/a9YMD05cBG9r1gwK6bq4n2vWDAEBs8zPa9YMBmZ1IO971gwEXhDVD3vWDANEgFkfe9YMBt2ePQ971gwJeuwBD4vWDAPiETUfi9YMCfuiCS+L1gwFNTLNT4vWDAjLkgF/m9YMDJTdFb+b1gwGpZjKL5vWDAunEn6vm9YMDWXsgx+r1gwIkUAHn6vWDAdZB9v/q9YMA9v8oE+71gwJX8gkj7vWDAE+W6ifu9YMB2j4nJ+71gwGEOYgj8vWDA0+W6Rvy9YMDoqOKE/L1gwDZ1JsP8vWDAHL0JAv29YMC1JvhB/b1gwDhk1YL9vWDA/0yKxP29YMB2B88G/r1gwORwxkn+vWDA9ptAjf69YMAY6S7R/r1gwAE/fRX/vWDAhID3Wf+9YMD2tI2e/71gwKDjY+P/vWDAqeCoKAC+YMAwUiReAL5gwH8lLrEAvmDAsxF89QC+YMAI5YA5Ab5gwEcTinwBvmDAYvBcwAG+YMC0JqoBAr5gwMPE9UQCvmDACJiAiAK+YMAkw/fMAr5gwCzLIBEDvmDAAWccWgO+YMAPCG3UA75gwMDaAtsDvmDAM+O0HQS+YMCy/jtgBL5gwBU+QKAEvmDAT1Fz3wS+YMCWYTweBb5gwNMwpF0FvmDAJs5knQW+YMDoncbeBb5gwCWZ/CAGvmDAH2LxZAa+YMBL+uGrBr5gwNvAKvMGvmDABTxvOge+YMAO/HuCB75gwBddJ8oHvmDAooO1EQi+YMD8rY1YCL5gwG2eIKAIvmDAbKty4gi+YMAXd+kmCb5gwH5wdZkJvmDA9+g0qgm+YMB9NCLtCb5gwEvnBy0KvmDA1DV8bAq+YMBGZ5urCr5gwCVsl+kKvmDAhvT1aQu+YMDtgvapC75gwM1xA60LvmDAMSfDMQy+YMAGOFl2DL5gwDJFHXkMvmDA/NDMywy+YMBm87QFDb5gwKempn0NvmDAscAswA2+YMD7DYQBDr5gwP6luEIOvmDAgvoUdw6+YMCTqgy/Dr5gwPt2SwgPvmDAs2v0SA++YMAWnVaID75gwNAmwMcPvmDASJwq6w++YMA31BdIEL5gwK25z3MQvmDA7wo2uBC+YMATDkf8EL5gwBGlAFMRvmDALDGMmBG+YMCgZ6XeEb5gwMQ8cAUSvmDALXEHRxK+YMDgoHeIEr5gwJwImcoSvmDALI/jCxO+YMB5hCJOE75gwJt4EZETvmDAfSt81BO+YMDJWq0vFL5gwKra6lwUvmDABSIgoRS+YMAJEXHkFL5gwC/hHCkVvmDAk+L5eRW+YMAPrnGrFb5gwKlIIO4VvmDAutysRBa+YMBPGYFwFr5gwAKLorEWvmDAWPV/8xa+YMCabpM1F75gwGcWF3gXvmDA793Puhe+YMANCNn9F75gwKLJL0EYvmDALKmwhBi+YMD1qU3IGL5gwHJVNgwZvmDAhrpNWBm+YMAiJJucGb5gwO3dsdcZvmDAwbnEGhq+YMAmVE5dGr5gwO5r26YavmDAENAn5hq+YMBD/BUhG75gwDnjWGEbvmDAE+K9ohu+YMBNAg3iG75gwC/KuiQcvmDACEbsZhy+YMD0ZZmlHL5gwHXE5e4cvmDAVLqVMx2+YMCZ0+h4Hb5gwNarMrEdvmDAHgDZAx6+YMCAVtU0Hr5gwF5IF3UevmDA8fCw0h6+YMDlZDcVH75gwEWrVjQfvmDAccspdB++YMArwkS0H75gwJRlWRwgvmDAaoOtXCC+YMB+YWOcIL5gwNvnFtwgvmDAqSMQHCG+YMDjPHBAIb5gwLlnNpwhvmDAmlno3CG+YMCMm54eIr5gwPCbP2EivmDAAgpqpCK+YMDjRjPoIr5gwJervRgjvmDABSU9cSO+YMC8akC2I75gwBL4E9cjvmDAtsoxFCS+YMCfFwCGJL5gwMTxDsskvmDAu1nsDyW+YMDhdHpUJb5gwOHbr5glvmDA4oZ73CW+YMDA/sEfJr5gwOGCmGImvmDAR5EYpSa+YMCRzUznJr5gwEnlUCknvmDAiBMLaye+YMC5872sJ75gwBZnhO4nvmDAYrAHMCi+YMBt+xFyKL5gwOJ3uLMovmDAT81F9Si+YMAoGss2Kb5gwLjzP3gpvmDAahONuSm+YMAibZ76Kb5gwHBUDzwqvmDApdEMfiq+YMDTc3vAKr5gwE+MpwMrvmDAV4BoRyu+YMBV+hiMK75gwLdN2NErvmDA02WjFyy+YMCQCDJdLL5gwF+8PKIsvmDATtud5iy+YMB8aVUqLb5gwPqZQWwtvmDAA6gSrS2+YMAygh/tLb5gwAkCsywuvmDAHnMRbC6+YMD2jXarLr5gwJm5EOsuvmDAJcQ4Ky++YMAi3RNsL75gwD9VqK0vvmDAPxbN7y++YMCqZ68yML5gwFHOHnYwvmDALmsPujC+YMBucX3+ML5gwDmFiUMxvmDAWl1ziDG+YMBHavDMMb5gwCSb0xAyvmDAEk7KUzK+YMAnlxOWMr5gwJVIxNYyvmDAVuogFjO+YMD6uKlUM75gwGFLHZMzvmDA13HV0TO+YMAiYf4QNL5gwGINAFE0vmDA2G5KkjS+YMDinhXVNL5gwDsT/xg1vmDADrQ2XTW+YMBsaGGhNb5gwOqyPOU1vmDACAyqKDa+YMAoEyFrNr5gwB5S16s2vmDAcf6k6za+YMDfHRcrN75gwDBWbWo3vmDAoVbwqTe+YMB6H8HpN75gwFsDFSo4vmDAX1OVbDi+YMC7l7qyOL5gwDMPw/Q4vmDAGeuHODm+YMC/AMx9Ob5gwJJ6XMI5vmDAi9u+Bjq+YMACHxFHOr5gwCL+t4k6vmDAG8Km/Dm+YMBn8hAPO75gwH6I/E47vmDAcJcSvjq+YMAbxH/PO75gwF1RBhI8vmDAhZ/uVDy+YMAcwrWXPL5gwI8CK9o8vmDALe9FHD2+YMBNfuNdPb5gwLjw+p49vmDAMRw/3z2+YMB2b9wePr5gwCY7KV4+vmDAukRInT6+YMAc4WncPr5gwFOZwhs/vmDAa7Itgz6+YMBTx3abP75gwCMdItw/vmDAhslvHUC+YMCb9hRfQL5gwGbOKcw/vmDAmk0840C+YMD0NHAmQb5gwCObamhBvmDAgYL8yUC+YMDV9GcIQb5gwDhtxkZBvmDAHaIxhUG+YMC+nDX4Qr5gwPRPwvJCvmDAi/LPQkK+YMCyMH+rQ75gwJkJa+NDvmDA1SPA+UO+YMADJCdEQ75gwPw5faJEvmDA6SkD8US+YMAr6KpcRb5gwJeRaq1FvmDA2ea/yUS+YMBHWUIsRr5gwBK1sWtGvmDA3l98t0a+YMDfZXS4S75gwCSrT5dMvmDAc9pq30y+YMByrOzyTL5gwHy9xCBNvmDA3aTcZE2+YMDcCUiWTb5gwJYx9u5MvmDAIpFvLU6+YMDLHKWWTr5gwNa9ZeROvmDA33GTKE++YMDLTDyATr5gwBdIMrJPvmDA4zBP80++YMD+2ZdKT75gwLdOwHFQvmDAhuXhr1C+YMD8fCHuUL5gwOrxeTFRvmDAsx7HlFC+YMDiEoSrUb5gwJUHAe1RvmDASZm8L1K+YMBcVvueUb5gwERqr7VSvmDAPnom91K+YMDeYCI4U75gwCFiB3lTvmDA67e3uFO+YMAKyer1U75gwIEFazNUvmDAdl+8clS+YMBp9ruxVL5gwIWU6vFUvmDAGDZfMlW+YMA3xTR1Vb5gwL35sbhVvmDAmkeb/FW+YMAALWdAVr5gwGYs2INWvmDAEtLjxla+YMBGydEIV75gwDHcOklXvmDApTx5iFe+YMA2XAfHV75gwMw2GgVYvmDAD6LlQli+YMAvcZeAWL5gwGzuOL5YvmDAkZAJ/Fi+YMAw2+w5Wb5gwKmvQHJZvmDAb0pwsVm+YMAKN/bxWb5gwK4jtjBavmDAfhzWfVq+YMBS6bGzWr5gwE3lVPZavmDA9nDcN1u+YMD/j1F5W75gwC+687pbvmDAY6p+/Fu+YMBoTRQ+XL5gwGYH1H9cvmDAl0xlwVy+YMDZuLgCXb5gwIQ4DURdvmDAsy9zhV2+YMDja9bGXb5gwNStXghevmDAMxnlSV6+YMCqBFCLXr5gwGdos8xevmDA6NPvDV++YMC/At9OX75gwB7ofVBfvmDAMx+e0V++YMCzqu4RYL5gwIvMulJgvmDA1B0OkmC+YMD3fq3RYL5gwEOHwhFhvmDACHvuUWG+YMBF2oaSYb5gwILHp9NhvmDADjAgFWK+YMCt5tdWYr5gwKNIg5hivmDAfZcC2mK+YMDMzdobY75gwNHphF9jvmDA43YQnmO+YMCY2/LiY75gwNBW2yRkvmDASeUiZ2S+YMD/CyqlZL5gwM280O1kvmDAG9UZMWW+YMA1Hit5Zb5gwOYriLxlvmDAmhHE/2W+YMD1vF5CZr5gwLtzboVmvmDAEfBfyGa+YMCeua8KZ75gwBGIJExnvmDATS38ime+YMBxIa7MZ75gwEm+UQ1ovmDAsKGLTGi+YMAUSM6LaL5gwBD9e8tovmDAJUzxC2m+YMCBqs5Nab5gwISS9Y9pvmDAXWzh0Wm+YMBXNyQUar5gwPu4e1ZqvmDAj/+1mGq+YMCUU2Paar5gwOHc7BprvmDA7OS5ymu+YMBNFD+ba75gwFzNKdxrvmDAFS0VHWy+YMCZY+tdbL5gwP9ZZp5svmDA8g7W32y+YMDBeroebb5gwBptlF1tvmDAuDbunW2+YMBKTnPebb5gwGZUJh9uvmDA3tNEYG6+YMAezRqibr5gwI1zfuRuvmDA0PQCJ2++YMDHFXJpb75gwOpgqKtvvmDApxyJ7W++YMCU7PsucL5gwA1hUm9wvmDAQM0gr3C+YMBLGQjvcL5gwOS9qi9xvmDAAGnpcHG+YMCsDpuycb5gwH8DK/VxvmDAV7v6OHK+YMC8Tml9cr5gwB5uwsFyvmDA1lQBBnO+YMDu3pRJc75gwIEiTIxzvmDAL/BSznO+YMD0zvUNdL5gwKcKVEx0vmDArmKyinS+YMC8cbjJdL5gwP1b1Ah1vmDAn5EESHW+YMDUsiSIdb5gwHi/KOF2vmDAVbSXCHa+YMB1C3ZKdr5gwCQm7Y12vmDA0UDs0Ha+YMBJJNMRd75gwL6PpVJ3vmDAhTIylHe+YMAn71zveL5gwN+M5TJ5vmDAnN5iVXi+YMBMwuaWeL5gwFpgD9l4vmDA1+KtG3m+YMDgoUFfeb5gwD9hyKR5vmDAWOrD6nm+YMCH360ver5gwOqLlHR6vmDASTxVuXq+YMCONX79er5gwF4b4UB7vmDAyK+vgnu+YMALq3HDe75gwDASXgR8vmDASPFPRXy+YMAuXgqHfL5gwH7v8Mh8vmDA79YADH2+YMAAwPpPfb5gwHZCbpR9vmDAR0+Q2X2+YMC4pdoefr5gwN/hjWR+vmDAXutoqn6+YMDpEm7wfr5gwK8TaDV/vmDAE5BjfX++YMCL7tvCf75gwBrdlgiAvmDAdrioToC+YMDQNMWUgL5gwKUXCtuAvmDA6eyVIYG+YMBpySpogb5gwPRtW66BvmDAPNOf84G+YMC4C0g8gr5gwPNj6n+CvmDAbihdx4K+YMCD/lMMg75gwBPGxVGDvmDAHZthlYO+YMCHthXag75gwCp7RyCEvmDAbg59ZYS+YMDIIuyphL5gwI9bse+EvmDA4zV8NYW+YMAvEhV7hb5gwMtdXMGFvmDAlsjdBoa+YMDcNwVNhr5gwLoKwJOGvmDAw9cK2oa+YMA3s9nhiL5gwAbYDyyJvmDA3cSTr4e+YMDetzD1h75gwEwjQQaKvmDAaMqoTIq+YMBCfIqSir5gwBp+59eKvmDAc3ItHYu+YMBMJEVii75gwDVqKtiJvmDA5ugZHIq+YMAAzN5eir5gwMCYrqGKvmDAJFt05Yq+YMCZ7dApi75gwEeE7W2LvmDALW8dsou+YMB1cJL2i75gwM87ADuMvmDASpebf4y+YMCrs4bEjL5gwGZZ9wiNvmDA2iCRTY2+YMCtF2CTjb5gwOu2KNeNvmDA1cTxGI6+YMCz7glcjr5gwJ8ulp6OvmDAALw14Y6+YMBLz8kjj75gwPIY9WaPvmDA+Hp1qo++YMD4NOHuj75gwDtQOjSQvmDAJ/nbepC+YMAtlNHBkL5gwC7XTwmRvmDAqNFzUZG+YMAW8+mZkb5gwOeCCuKRvmDAU7TkKZK+YMByFN1xkr5gwHKK17mSvmDAZVtbAZO+YMDpCVhIk75gwEGURo+TvmDARj4J0pO+YMDgk/4Jlr5gwPa1sFaUvmDApklynJS+YMC0A03mlL5gwK6u4SWVvmDANOw6Z5W+YMC4vuWplb5gwKkiAwSYvmDAXbPvS5i+YMDvhOlhlr5gwC/d/5yWvmDA9Tw26Za+YMBwM65rmb5gwBjutX2XvmDAVvx3wpe+YMBWq/wHmL5gwOiQK02YvmDAux8xlZi+YMCP5L3cmL5gwLZ1FySZvmDAIhMHtJm+YMAVe4v8mb5gwGa1N0SavmDAuRbIi5q+YMAuXKfSmr5gwD4o8RibvmDAX8p4Xpu+YMA+2uffnb5gwHSyROWbvmDAW2RSJ5y+YMClu1BpnL5gwBMBequcvmDAiFBl7py+YMBlxtwxnb5gwGKwh3advmDAV4OeHKC+YMDvHBNmoL5gwL1Z402evmDAPJuSl56+YMDbvtnhnr5gwOGsZSyfvmDAoBvdhKK+YMBhozPCn75gwAl4ywqgvmDAHvhcVKC+YMDizmZOpb5gwM02XciivmDAep30o6W+YMBvnI3apb5gwMpp65WjvmDAlYwJzqO+YMC3/yADp75gwBnX+UunvmDA3cc8FKm+YMBvXZFIqr5gwMUgofOqvmDASXEQQKu+YMACngKnrL5gwN+DvOGsvmDAa5j7Qqq+YMDryUOJqr5gwCON8cCtvmDARSNnDK6+YMCQUnysq75gwFErdRysvmDAphraY6y+YMDL5HxyrL5gwB8Qi2+vvmDATgjr+6y+YMBaw1VIrb5gwDqRE5GtvmDACw45zq2+YMAzE7Aarr5gwHhACTaxvmDA9ZRbdLG+YMCL0e1Zr75gwHmuTKCvvmDAVYig6q++YMCRT7Mjsr5gwIsiAWuyvmDAIRCwsbK+YMAMWvL3sr5gwG8Lvz6zvmDAVslo+bC+YMDmI17Ms75gwKZ7CRO0vmDAwTPAWbS+YMBxzCIesr5gwPDYZuW0vmDA9n0JK7W+YMC78RPlsr5gwCCRLTuzvmDAleOQgrO+YMC+sv3Is75gwNJpSg+0vmDAMEu6VbS+YMAgsHSctL5gwBRwpeO0vmDAE8x7K7W+YMDnwe5ztb5gwI2Mvr21vmDA23vfB7a+YMARViFStr5gwCDaS5y2vmDA23Mx5ra+YMD997gvt75gwHYudHi3vmDAs+xQwLe+YMBAtI0HuL5gwGR4SU64vmDAuhyslLi+YMADXdHauL5gwBZ43CC5vmDAjRriZrm+YMAItQatub5gwCj8a/O5vmDApVI6Orq+YMBMZ4WBur5gwLgHUMm6vmDA0JGQEbu+YMD1QnRau75gwGZnG6S7vmDA7qcG7ru+YMDVKOA3vL5gwK7LeYG8vmDAYJ+Xyry+YMD6xTUTvb5gwLPoD1u9vmDAQ62qob2+YMCqSY/nvb5gwOyuHC2+vmDAjP5zcr6+YMDpfsq3vr5gwHb6P/2+vmDAGVMHQ7++YMBSknyJv75gwLI5b1DCvmDAImuNl8K+YMDWZHDiwr5gwCnSnCvDvmDAwH5OdsO+YMCdQgPCw75gwLD20g3EvmDAjPjyWcS+YMAuxdASwr5gwMoPDlbCvmDA1q55ncK+YMCz1rLvwr5gwCoNvDfDvmDAhUPqDca+YMCSnXvEw75gwHM7d5XGvmDAI4E12Ma+YMDq6KB9xL5gwIbWSsbEvmDA0YUQFMW+YMB0ddIqyL5gwHOyum7IvmDAKY/1tMi+YMC5K0f8yL5gwAn/jETJvmDAYxy9jMm+YMDmr73Vyb5gwLANXyLKvmDAD8zWbMq+YMBfJqfdyr5gwCA3IPzIvmDApugrM8u+YMCWNhl8y75gwGFqOtfMvmDA1AlGmNC+YMAMQkrl1L5gwG2/B7fWvmDAAV+oG9i+YMCP/Rhi2L5gwEST66fYvmDAKNBZEtm+YMDw6bIz2b5gwC3DsHnZvmDAII1uKdi+YMBnPCBr2L5gwBWXapTYvmDAJgy199i+YMC2mC042b5gwEcYUnrZvmDA02+k3Nm+YMDMgyCW275gwDjed9jbvmDAUeH0Gty+YMAkJ7iF2r5gwJePZcnavmDAjo7sGdu+YMAHG4Ng275gwP0tZm3dvmDARaeL9Nu+YMBzsuX23b5gwB8NuTvevmDAtkdCwty+YMAKrgIe3b5gwFp3nGfdvmDAnLr+r92+YMCGU8CR375gwPd91z7evmDA3oSVG+C+YMBNoTzE3r5gwLeLSxLfvmDA/Z8dWN++YMCQUQie375gwEzhw+PfvmDARx5VKeC+YMAEJc5u4L5gwKUvDbTgvmDAO3tc+eC+YMBvoPw+4b5gwHGlPYThvmDAs7HByeG+YMBY6qAP4r5gwKE/G1bivmDAksYqneK+YMCIasjk4r5gwKX/Ky3jvmDAMpl0duO+YMBTEyTA475gwIiR9wnkvmDAqmqwU+S+YMDBKBOd5L5gwLM+K+bkvmDAj159LuW+YMCXXAh25b5gwJMBx7zlvmDAYUgCA+a+YMBwlNBI5r5gwM64VY7mvmDAr2Wc0+a+YMCkmt8Y575gwJeIS17nvmDAb3jbo+e+YMDEa5Xp575gwIbFgS/ovmDA1smkdei+YMBEahO86L5gwIsHvgLpvmDAAUinSem+YMBXzsuQ6b5gwAalQtjpvmDAqiAGIOq+YMCL4hFo6r5gwC8IWLDqvmDAVzXU+Oq+YMCMd4BB675gwG3VRYrrvmDAr2H20uu+YMAB6ngb7L5gwJ1Qs2PsvmDAGEeTq+y+YMD3LP7y7L5gwJ2R8jntvmDAoL9fgO2+YMBpOU3G7b5gwNDNtwvuvmDAYnKpUO6+YMD2qkaV7r5gwKj+i9nuvmDALiV/He++YMD9VTFh775gwNvp9aTvvmDAntXp6O++YMAdSTgt8L5gwNRw53HwvmDAt24St/C+YMDUKO788L5gwE8NaEPxvmDA3AtRivG+YMBkPI7R8b5gwGzu/xjyvmDA+t+RYPK+YMDkMRyo8r5gwBAvlO/yvmDAca3nNvO+YMDwOed9875gwI07dsTzvmDA4e2TCvS+YMBwvzNQ9L5gwJawbZX0vmDAPZr82fS+YMCJXdsd9b5gwEY+mGH1vmDAGI14pfW+YMAaArTp9b5gwAztVC72vmDAwOJ1c/a+YMAfkIm59r5gwF1BxgD3vmDAm616SPe+YMCXHS6Q975gwDj7m9f3vmDAuUyaHvi+YMCG/ixl+L5gwI2Ri6r4vmDAqQCJ7vi+YMAR3cgx+b5gwGpEA3X5vmDApGiGuPm+YMDss4T8+b5gwGhyF0H6vmDAgWDJhvq+YMCCv0bO+r5gwCQ+fRb7vmDAkjq3Xvu+YMBkA4em+75gwO+3tu37vmDAx8AfNPy+YMDq+TR5/L5gwA9cRbz8vmDAQOT6/fy+YMAJ7tFI/b5gwNvA3X/9vmDAE4OuwP2+YMC43pUB/r5gwNfT81b+vmDADUkf0/6+YMCt6s34/r5gwDO6/Tz/vmDAEEsvVf++YMD2siia/75gwCHQhikAv2DAsaAaXgC/YMC7ZSFrAL9gwEaokSYBv2DAt4E1OgG/YMCg8TaAAb9gwBuFrOUBv2DAHzkmCgK/YMA1wJBPAr9gwKc9DMQCv2DAsPodjgK/YMALA0AiA79gwGBNsWYDv2DA3Gg72QO/YMApVsnRA79gwCiOh28Ev2DAY1ecrwS/YMAGwwXwBL9gwK/w9jAFv2DAFI5ZsgW/YMAjLZjcBb9gwGxApD4Gv2DAEU53hQa/YMBE0ScTB79gwK7Ff0gHv2DATRmK7wa/YMCrxUxOB79gwP7cOeQHv2DADqOSJwi/YMCSwe+qCL9gwLpWT2IIv2DAMUmhoAi/YMA2n/6ZCb9gwNE3rSEJv2DAPwJf7gm/YMCkaN8uCr9gwLw7hbIKv2DAX0dq6wq/YMD2UBAuC79gwAWxs64Kv2DAUXkz7wq/YMCFXoQvC79gwLh1ha4Lv2DAeYeS7Qu/YMDz+vssDL9gwMUFqmsMv2DA6o3hqgy/YMAMSL3qDL9gwHqnEysNv2DA8WIYbA2/YMC0HCyqDb9gwDb4QPYNv2DAkm7QNA6/YMA21L+/Dr9gwGgwnAUPv2DA+nJZSw+/YMAodk9OEL9gwFauHrwQv2DAD2ak6hC/YMB3JOArEb9gwK+5UI0Rv2DA2UyE3BC/YMDaxJfNEb9gwCHJ5lsRv2DACZ4xmxG/YMCa/KiCEr9gwNYwGxoSv2DAv3ELBRO/YMA+JMBFE79gwNsGYYYTv2DAby2XxxO/YMCVTS0JFL9gwJb2RUsUv2DAMO6OjRS/YMDpy0PRFL9gwL/XOhUVv2DAnl9QWRW/YMC1AgCdFb9gwBiGF+AVv2DA0KRkIha/YMCYu+pjFr9gwIw1zaMWv2DA8z8j4ha/YMDoJYkgF79gwDehhl8Xv2DAndt7nxe/YMD+hbLgF79gwGiJsJEXv2DAHP+XaBi/YMAZ4SmwGL9gwGnOpvgYv2DALt0VQRm/YMCORMWIGb9gwLiiQM8Zv2DAnoAeFBq/YMCvxIxWGr9gwPIRe5Uav2DALn+50hq/YMC10xAPG79gwEdx9Uobv2DAwGvZhhu/YMAf3DLDG79gwGQfzQAcv2DAh18+QBy/YMD5WveAHL9gwDnIPMIcv2DAwPD8Ax2/YMDlCv1FHb9gwOdcL4gdv2DA8Un0yR2/YMCFMuwKHr9gwF3qrUsev2DAxVWNjB6/YMBY8q7NHr9gwIJeKw8fv2DAtYv+UB+/YMD9EHKTH79gwGEX2dYfv2DAWASWGiC/YMAMj0JeIL9gwKa4q6Egv2DAwc6f5CC/YMAAfv4mIb9gwM2lomghv2DADF0SqSG/YMBhrc7oIb9gwFvx8Cciv2DA9VWxZiK/YMB6ZTOlIr9gwFWeqeMiv2DAjZs8IiO/YMCtYPpgI79gwOrAK6Ajv2DAGXMC4CO/YMDLdJ4gJL9gwMapEmIkv2DAc1ZbpCS/YMBV42jnJL9gwNWwqCslv2DAtsiccCW/YMBo1pu1Jb9gwG37Sfolv2DAyhl7Pia/YMA5QtuBJr9gwGOVbsQmv2DA5tg2BSe/YMBkHIVEJ79gwNMlOYMnv2DA9DZdwSe/YMD4HEn/J79gwLKgLT0ov2DARCgyeyi/YMBOaA26KL9gwHKpq/kov2DAs/qPOSm/YMD0hNh6Kb9gwBFMxrspv2DAMiQK/im/YMDLZpY+Kr9gwFtF734qv2DAtisBwCq/YMBc3bn/Kr9gwOFMT0Arv2DAJJfAgSu/YMAQfHnBK79gwMKMkQIsv2DAo8/6RCy/YMBYbaKHLL9gwG0uxcosv2DAnm3pDi2/YMD3iuxSLb9gwNaEH5ctv2DAQMA/2y2/YMDvV5sfLr9gwEEN8WMuv2DAWxQyqC6/YMCW1kjsLr9gwF8/CDAvv2DAXndvcy+/YMDNKfu1L79gwKGU7Pcvv2DATRj5ODC/YMCAaXh6ML9gwI9Mg/Ywv2DAXb6F/DC/YMA1JIs9Mb9gwCtpGn8xv2DAvSakwTG/YMA7xHEFMr9gwHeNfEkyv2DATyKQjTK/YMBDZ1rRMr9gwJH9ehQzv2DAynN2VzO/YMD2lxqaM79gwOF2Adwzv2DAKLzFHDS/YMBmB7ZdNL9gwFZVrBc1v2DAssue3jS/YMDW0kggNb9gwIOMR2I1v2DAahBhpjW/YMAjSGfrNb9gwKu9IjE2v2DAgUfCdTa/YMDeuva5Nr9gwOrENv42v2DAdTzRQTe/YMDnJ76EN79gwIKR9cY3v2DAQdzrBzi/YMAdIedIOL9gwOoWLok4v2DA8Fo4yTi/YMAHIhMJOb9gwBptp0g5v2DADQ3Fhzm/YMDhPE7HOb9gwIcZSQY6v2DAbpkKRjq/YMBcufSGOr9gwLnCcsg6v2DAwPd7DDu/YMDFm0JPO79gwBwkYpE7v2DAcQY41ju/YMC2KH8aPL9gwGhYPV88v2DAlANPpTy/YMCaXIvsPL9gwJPFMzA9v2DA4WEFdj2/YMCD4CS7Pb9gwApSef49v2DAxvDtQD6/YMD5yDeDPr9gwOIK4MQ+v2DAOcWzBT+/YMBp/75FP79gwOazdIU/v2DAEcKIxD+/YMD0SrADQL9gwGzc10NAv2DALO7ChkC/YMDxxTjUQL9gwIiTlA5Bv2DA1+7OT0G/YMA0DHyRQb9gwKI32tNBv2DAdpt0F0K/YMCpM9pdQr9gwLy01KJCv2DAdS5C7kK/YMAqxqg1Q79gwOcg/ntDv2DAjXYsxUO/YMBIkBoLRL9gwJo5qFFEv2DA95Tvm0S/YMDS2WHfRL9gwFaZwSVFv2DA777sakW/YMA8i4yvRb9gwPsp/PRFv2DAVgxdN0a/YMBcfqN7Rr9gwDlonr1Gv2DAUNmyAEe/YMCuFaxDR79gwBnguYZHv2DAxNplyke/YMCZq0IOSL9gwNMxv1JIv2DATLkJmEi/YMB3fZXdSL9gwB8piSNJv2DA7KaaaUm/YMCHA5avSb9gwDi+yPVJv2DADW9aPEq/YMC+lgaDSr9gwFrZs8lKv2DAUWNaEEu/YMD538JWS79gwOOqqpxLv2DA0kGv4Uu/YMA0oJAlTL9gwKajkGhMv2DAn864qky/YMDXhTzsTL9gwPoWZS1Nv2DAVtT2bU2/YMA8ykCuTb9gwP//QO9Nv2DAln7HME6/YMDXL4NyTr9gwHzvB7VOv2DAwBF0+E6/YMAZYVI8T79gwLpzhoFPv2DAQCAfyE+/YMARQZsPUL9gwIe25ldQv2DA/WPQoFC/YMBQEG7qUL9gwPGqVDRRv2DAFF4SflG/YMDTrUvGUb9gwNuGVA5Sv2DA3Gg2VlK/YMBwmQGbUr9gwFd7gOFSv2DAwCYCJ1O/YMDf0oBrU79gwELTqa9Tv2DAwTlM81O/YMAGR382VL9gwCPqa3lUv2DAWXfRvFS/YMAfKDsAVb9gwK8jI0RVv2DA3HCviFW/YMA0UfrOVb9gwKXE9xNWv2DAQRTIWVa/YMCXcfOfVr9gwMK/o+VWv2DAfsuyK1e/YMCI6yRyV79gwFkBUbhXv2DAStZ6/le/YMCHLtVEWL9gwK8RXotYv2DAzn820li/YMDR8aAZWb9gwCRQhmJZv2DA5ow2qlm/YMASiXrwWb9gwBWSeTZav2DATWdjfVq/YMC/1bPDWr9gwJbiwQlbv2DASXBoUFu/YMA2GCaXW79gwKf7e91bv2DAKdJcI1y/YMD09CppXL9gwF7BA69cv2DAkeLk9Fy/YMAnVLs6Xb9gwF2IVoBdv2DAnnJ/xV2/YMDI1VEKXr9gwDP2/1Bev2DAaUuvll6/YMC2cRvfXr9gwAxvPiVfv2DACMnOaV+/YMC/XHmxX79gwDMWIPlfv2DAGpyqQGC/YMCGVCCIYL9gwBvz2s9gv2DAElcGFmG/YMBqNsxbYb9gwD7osKFhv2DAD6za52G/YMBfpCAuYr9gwOdbeXRiv2DAcAPhumK/YMANdu4AY79gwBPSyUZjv2DAMzWFjGO/YMCfk+nRY79gwGwXVBdkv2DARMNjXWS/YMAyGrWjZL9gwA1w2ulkv2DAmz5GMGW/YMBAOit3Zb9gwGOKNr5lv2DA0NldBWa/YMDz0p1MZr9gwLE7305ov2DAr20slmi/YMA6TOL6ab9gwFaThEFqv2DABH28h2q/YMCDs3/Nar9gwA0lpmppv2DAuH7VVGu/YMDVZIWYa79gwI953N5rv2DAKD/AIWy/YMCFwuxjbL9gwHZxzyBrv2DANh2yYWu/YMAE4TSma79gwP4EYOprv2DAXcO9Lmy/YMBQRjBzbL9gwOoN4LZsv2DAzmDd+2y/YMDFCKhAbb9gwGkNSoZtv2DAmOpTzW2/YMBY0pETbr9gwJuiQlpuv2DAB5SHoG6/YMDh6XHlbr9gwIGKzypvv2DACm2Qb2+/YMBuOXq1b79gwK0L/Ppvv2DAIXKEoXG/YMAyvT+KcL9gwJ/hhNRwv2DA1M0VHXG/YMCUvY9pcb9gwHhJqLVxv2DA1kJvAXK/YMBz3plMcr9gwJjVr5Zyv2DAl9rb3nK/YMAXLeokc79gwAzIIWlzv2DAZjwmrHO/YMCVAmHuc79gwEsH6S90v2DAh/i9cXS/YMAmgd2zdL9gwIPLy/Z0v2DAhBA5OnW/YMANbBp/db9gwJ71o8R1v2DAWI+UC3a/YMBOhVFTdr9gwEDD8px2v2DAxFMb53a/YMATa+Exd79gwAb1Y313v2DAt/jJyHe/YMB6bPQTeL9gwP7VkF54v2DARDJ/qHi/YMDRTlfxeL9gwHCX6Dh5v2DAIPidf3m/YMAARofFeb9gwMCzxgp6v2DAwB13T3q/YMCUrv2Ser9gwMNZQdh6v2DAQa36HHu/YMCl/cVje79gwGs5q6h7v2DAQdl063u/YMDDt+AvfL9gwE2bXHl8v2DAIxgZv3y/YMA0P9oEfb9gwMy/tEp9v2DAuO/kkH2/YMCeqdDXfb9gwO9jVB9+v2DAEE4hZ36/YMC4zUKvfr9gwCi1qvd+v2DA19g6QH+/YMDZxZeIf79gwNyVydB/v2DA1fy1GIC/YMCUFVJggL9gwFnRdKeAv2DAbPpE7oC/YMC7G2Q0gb9gwP1XsHmBv2DAkqwdvoG/YMDThrsBgr9gwOf5RUSCv2DA9Cv6hYK/YMCWwofGgr9gwDkDswWDv2DA5K0ERoO/YMCurx4ShL9gwM/tNMqDv2DAEXwgDoS/YMBO5IJThL9gwG75Lp2Ev2DAeynh54S/YMBfaJoxhb9gwN830nyFv2DA2MMmyIW/YMDnuhcVhr9gwFoNyaGGv2DAKkN5p4a/YMCWm+fthr9gwGesITWHv2DAF2K1e4e/YMCn3bXBh79gwLYaxgaIv2DAKC83S4i/YMBqpWqQiL9gwMWdANWIv2DAtpc9GYm/YMDATD1dib9gwKnn9KCJv2DA6h1i5Im/YMAWLY0nir9gwHLAomqKv2DAs4LHrYq/YMD+kOXwir9gwJ58aTSLv2DAc6r1dou/YMAJBke4i79gwOReYfqLv2DAy7XNO4y/YMCbyMl9jL9gwBZRtMGMv2DAZFVrBo2/YMAUeQ5Mjb9gwAHyp5CNv2DAQtXO1o2/YMCEotIejr9gwIRLxWaOv2DADKZ8rI6/YMDVgJ69jr9gwK5/FD6Pv2DAbhp2go+/YMCQqd3Ij79gwCUgIA6Qv2DALozIUZC/YMACezSYkL9gwNs84tuQv2DANQDzHJG/YMCQOctdkb9gwC5PqJ+Rv2DAnp9/4JG/YMAI8+0hkr9gwM3YDGWSv2DAOi9MqJK/YMA4Rsfrkr9gwCbsky6Tv2DAV5bVcJO/YMCrhhyyk79gwCTO//KTv2DAtvTJNZS/YMCrIb95lL9gwFpkj7eUv2DAm63w+pS/YMC8Wl8/lb9gwOlOp4WVv2DA9RSK0JW/YMDpq/salr9gwP2ITWKWv2DA4LwOq5a/YMB2OJXzlr9gwFB5FD6Xv2DAO8mJhZe/YMBAhOLJl79gwBqN+w2Yv2DAl1UBUZi/YMDu4P2TmL9gwLnfataYv2DAjlMJGJm/YMD+g7lZmb9gwOIstJuZv2DAe26t3Zm/YMD6+Ggfmr9gwKBcZ2Cav2DAWAyjoZq/YMATRrbjmr9gwN4royWbv2DAKIe0Zpu/YMAjPDenm79gwLmy8uebv2DALwAOKZy/YMDLBLlqnL9gwArObK2cv2DA7eXU8Jy/YMAYOW41nb9gwNRQJXudv2DAXbydwZ2/YMCmzgEInr9gwGRUNk6ev2DAr1GClJ6/YMAHrivanr9gwOTlqB6fv2DA2ynWYZ+/YMAugHmkn79gwEUKcOafv2DAMCu4J6C/YMAkyBhpoL9gwEMUvKmgv2DAg4Iw6qC/YMAFtu0qob9gwGFrP2uhv2DAXldDq6G/YMD4Ufnqob9gwC9mTCqiv2DAlRFVaaK/YMDb79unor9gwL1x2eWiv2DAPIFTJKO/YMBr2bBjo79gwKcOMaWjv2DAu7t95qO/YMABz5IopL9gwFWOL22kv2DASQsCtKS/YMCdrRH8pL9gwIaG4UOlv2DAhx9ei6W/YMBCY5fRpb9gwNzWthamv2DA9a1vqqS/YMAg/rycpr9gwNkiT9mmv2DAwt1DF6e/YMADIlFTp79gwKbElY+nv2DAhYdCzKe/YMDhh4UJqL9gwBt8dEeov2DA7aAahqi/YMAwixHGqL9gwFYTPQipv2DA6cbBSqm/YMAKZ3GNqb9gwBnMQ9Cpv2DAwn4xE6q/YMDc23tWqr9gwL/XGpqqv2DAt7Ig3qq/YMBnQgohq79gwGxdOWWrv2DAZ/vjq6u/YMAkhAXvq79gwFIMBTKsv2DATPG4dKy/YMB5LWm2rL9gwFzmafmsv2DAEsjmOa2/YMDgv4R6rb9gwD1PiLqtv2DAtwO2+q2/YMDBCH86rr9gwLr+U3euv2DAzpjss66/YMCcz57yrr9gwK6MkTOvv2DAGr1OdK+/YMBssBm0r79gwG6POPKvv2DAhR6KLq6/YMD6L7pxsL9gwM3bkbOwv2DAkny/9bC/YMAdB9Q6sb9gwKLcsXqxv2DAQoKFu7G/YMDjPm39sb9gwIdrWT+yv2DAb2IogrK/YMDtL8PEsr9gwGvGHQazv2DAi8NuR7O/YMA1siSIs79gwPXQn8izv2DA0PK/CLS/YMDAYmxItL9gwP2tvYe0v2DA4fLDxrS/YMC54nQFtb9gwCza60O1v2DAD6khgrW/YMCQwGTAtb9gwILN9P61v2DASL9wPba/YMBWNyV8tr9gwKtOP7u2v2DAEvNg+ra/YMDlYEI5t79gwGyudni3v2DAwdM9tbe/YMCRF7zyt79gwL9UAjC4v2DAsehkbLi/YMCR/QmpuL9gwNoqF+a4v2DACBnHI7m/YMB17LBiub9gwNW3U6K5v2DADc7n4rm/YMD2GTwlur9gwMo62me6v2DA1G91qrq/YMDpcTLtur9gwKq/wS+7v2DABiiucbu/YMAe2/yxu79gwAs7Ie67v2DAsFsUK7y/YMBU6uhmvL9gwF9zcKK8v2DAjqGUV7q/YMD/HTUYvb9gwOBafFO9v2DAPc/okL2/YMBqbEHQvb9gwLVPGw++v2DAX+zSTb6/YMB3L2WMvr9gwFNl98q+v2DARJ0BC7+/YMBEDNLAvL9gwEXDk4e/v2DABBDHxb+/YMBvSU4EwL9gwDmbVUPAv2DAH/3zgsC/YMBm9fbCwL9gwCpzCQbBv2DAYIl9ScG/YMBZgCKMwb9gwIkyUs7Bv2DA6XMQD8K/YMC01c9Owr9gwE1VeY3Cv2DAxfcUycK/YMBbdssCw79gwCC8RjvDv2DAJ86fc8O/YMBO0r6sw79gwKtdnObDv2DANDxAIcS/YMBl7iZexL9gwNfrFp3Ev2DAHDYF3cS/YMDPdk0dxb9gwGXSiV3Fv2DA1i6/ncW/YMCftErdxb9gwEGOORvGv2DA5Kk+Vsa/YMCp0t2Rxr9gwO/oZ9PGv2DA/b4wEce/YMBGRNtOx79gwOcwWYzHv2DA937Kyse/YMBl4RIKyL9gwCi7AknIv2DAehTkh8i/YMBo/u3GyL9gwARCfgbJv2DABKEyRcm/YMDnSR+Eyb9gwI2BdMLJv2DAnET1/8m/YMB4ULo9yr9gwHz1dXvKv2DAI20Etcq/YMCX9Trxyr9gwNQoaCzLv2DAm7fSZcu/YMDfonqgy79gwNjkVt3Lv2DA657ZGcy/YMBqdnRUzL9gwFbQ0JPMv2DAvmOI0sy/YMAeoCoSzb9gwFNvxOnKv2DA+c8tjc2/YMDBKGnOzb9gwK+/nA7Ov2DAYpUxTs6/YMDE5+GMzr9gwAIg4crOv2DAKqOIB8+/YMCDmddDz79gwIi61X7Pv2DA/YvTuc+/YMAcVZrzz79gwBbkcivQv2DAHZsuZdC/YMB9Cb+e0L9gwB7bhtjQv2DAbaXfEtG/YMBDRf1N0b9gwNTT34nRv2DAQphyxtG/YMC1nxkF0r9gwGBavkTSv2DAZlnDhNK/YMAINeXE0r9gwLhq3wTTv2DApqr3Q9O/YMDdexOD079gwPl3N8HTv2DAfHW+/dO/YMCcuW841L9gwAAoZHbUv2DAJB/Hs9K/YMA2JZ/v1L9gwJeM8CzVv2DAO8Boa9W/YMCAdkaq1b9gwKORGurVv2DA7nHyKda/YMB/Xt9p1r9gwH1U86vWv2DA0PeT69a/YMAV+YYr179gwHMvMGnXv2DAwUe+pde/YMDFL1Pi179gwODU5x7Yv2DAGSXaW9i/YMDw0NiY2L9gwCR3A9bYv2DAWlY4E9m/YMAUZGZQ2b9gwCxUn43Zv2DARE/Hytm/YMBUx+IH2r9gwMalgEXav2DAE24Eg9q/YMACAnvA2r9gwFEQSf7av2DA74Z7utm/YMCtZDF5279gwMEa4Lfbv2DANDUq+Nu/YMAFOHE33L9gwF6gtnbcv2DA9kZrtty/YMCf1zT33L9gwGEROTXdv2DAnAuXc92/YMBjGcCx3b9gwDq2ue/dv2DAipz9v9y/YMCjFwBr3r9gwKO6gqnev2DAleY7496/YMBysvAe379gwG0sF1vfv2DAVXOXl9+/YMBSBznU379gwBlschHgv2DAl2+AT+C/YMA0m7aN4L9gwOhRmM/gv2DAVupWDuG/YMDvXalk4b9gwFxjdI/hv2DAOCmFzuG/YMAenqkO4r9gwOTUAU/iv2DAVIjXjuK/YMCZ64rO4r9gwGKIKg7jv2DAiQDPTeO/YMCe94CN479gwC8oe8zjv2DAA2F5CuS/YMAf+75I5L9gwBDYnIXkv2DAltP7weS/YMDUcXz95L9gwOJ2vTjlv2DAxGP5cuW/YMCtmOWt5b9gwCfGv+jlv2DA+k7qI+a/YMC7iYFf5r9gwEQBJJvmv2DAabnV1ua/YMAZ/DIT579gwEMZ5VDnv2DAOX5NkOe/YMBWo4HQ579gwG5AfRHov2DAzkEiVei/YMC2VbCa6L9gwKjSHeDov2DAmlbFJem/YMD/5vZq6b9gwMNF/K7pv2DAlmQ28um/YMBU9zAz6r9gwLj1uHHqv2DAtmAIr+q/YMA9yRzr6r9gwJJ4cybrv2DAlJJVYOu/YMDOk3+Z679gwI+hW9frv2DARIxQE+y/YMBlGWVP7L9gwNMRdIzsv2DArK50yey/YMCBDYcH7b9gwOtIHEbtv2DA/XVHhe2/YMCtYUfF7b9gwG3+Rwbuv2DAPfkvSO6/YMBvmsyK7r9gwF+e383uv2DAmpWDEe+/YMDgQuBV779gwKGaSJvvv2DA1Abk3++/YMDvioYk8L9gwGrhM2nwv2DA5zQrrfC/YMByBp7v8L9gwEsdjDDxv2DA7wMUcPG/YMAycG6u8b9gwF/eI+zxv2DAOtYvKfK/YMBVtt1l8r9gwOOZSqLyv2DA86HQ3vK/YMA1fbgb879gwFJ/Llnzv2DA5PJVl/O/YMAtNm3W879gwEjKXhb0v2DAweqWV/S/YMAGK/Ca9L9gwPvaSOD0v2DAO4bPJvW/YMCoanZt9r9gwIeKY7D1v2DAw2if9fW/YMAoVpA69r9gwPVGbn/2v2DAaEn7w/a/YMAefsIH979gwBaGzUv3v2DA9YZUj/e/YMBFHm7S979gwMEkOhX4v2DA0HbCV/i/YMDtvgSb+L9gwDhpZN/4v2DAevDTJvq/YMB7Teln+b9gwOq1Bqv5v2DAgjET7fm/YMDGPVws+r9gwEYcnmr6v2DAPynwrPq/YMB+BHbr+r9gwCXGHSr7v2DAzD9gafu/YMBiaq2o+79gwOMpjOj7v2DAU0dfKfy/YMCQjHtr/L9gwMnbYq/8v2DANLoCa/6/YMAnxiI2/b9gwLn1lnr9v2DA6KBpvv2/YMDqr5cB/r9gwKuocEj+v2DAfqrZjv6/YMB0PCXV/r9gwFgQxRv/v2DAden+7gDAYMBLGIKj/79gwN1zAOv/v2DAeeTKLwDAYMD9n85zAMBgwJ0nOrcAwGDAsqwK+gDAYMBzEfw7AcBgwFw+5H0BwGDA2hdDwAHAYMBjtSYCAsBgwMoQMUQCwGDAY7FNhgLAYMCNoK3IAsBgwE3qYQsDwGDAany7TgPAYMDMYouSA8BgwNVo3tYDwGDA4jGrGwTAYMCIDvZgBMBgwMHDv6YEwGDAuRKL7QTAYMBHS0s1BcBgwBqKdn0FwGDA0hkqxgXAYMBCYi0PBsBgwJWIPFgGwGDAlesToQbAYMCskZHpBsBgwDjGkTEHwGDAQBcdeQfAYMBC/4W/B8BgwAnVMQUIwGDARzDySQjAYMBR3TqOCMBgwCrRGtIIwGDA/RJrFQnAYMBQ4ldYCcBgwLU4M5sJwGDAB6xP3gnAYMBRhq0hCsBgwEP6D2YKwGDAg+1vqgrAYMD4KzbvCsBgwF903jQLwGDA9WXmegvAYMAEkYvBC8BgwER44ggMwGDApHMcUQzAYMCXkLC2DsBgwNAsn+QMwGDA0lqhLg3AYMB8yHl5DcBgwLn0xMQNwGDAHR9aDw7AYMBwhiZZDsBgwJJQsKEOwGDA5Dei6A7AYMBF5TouD8BgwJSqunEPwGDAns/Hsg/AYMB3YCbzD8BgwL00sTMQwGDA3tV1dBDAYMBlR5u1EMBgwFP6T/cQwGDAwgVDOxHAYMBd3lWEEcBgwEwfjMsRwGDA2bF1FBLAYMCe+7lFEsBgwFLaEt0UwGDA022D7BLAYMDGU5E1E8BgwC9QrX4TwGDAxVyjxRPAYMDsXWEOFMBgwI/xdFYUwGDAnEeBnhTAYMD38DjlFMBgwCAg5iwVwGDAENVNeBXAYMCnGtfAFcBgwAh1ewkWwGDAZXUzUhbAYMCSrLGaFsBgwOMj0uIWwGDAm8uKKhfAYMAVv9FxF8BgwJffpbgXwGDAklix/hfAYMAUBUtEGMBgwE/pWYkYwGDAgzkezhjAYMA9D00SGcBgwFnL6lUZwGDA0oaPmRnAYMCu8JzdGcBgwAvCYSIawGDAQxXeZxrAYMBFi1CuGsBgwJnT/PUawGDAHz0gPxvAYMCNnWKJG8BgwBrlGNQbwGDA4jr+HhzAYMDDb8NpHMBgwPvIuf0ewGDAjJTo/RzAYMAGb4hGHcBgwAZLKY4dwGDA+sgy1R3AYMCKbL8bHsBgwOMs8WEewGDAhZ36px7AYMAkHBHuHsBgwDbdTDQfwGDAkUnNeh/AYMAWkrDBH8BgwCEbDAkgwGDA72jnUCDAYMCJkkaZIMBgwEas/eEgwGDAr6aQKyHAYMBKvMJ1IcBgwHltyb8hwGDAl302JiTAYMBvfCtmJcBgwOWKx/UkwGDANdLFniXAYMAxiNDGJcBgwDE9SQ0mwGDAqrchRiTAYMDbRsONJMBgwEXgGtYkwGDA5mDcHyXAYMC8xoluJ8BgwGZ057clwGDAjiNA+SfAYMCsggZFKMBgwIippJkmwGDA/ykE1SjAYMD+Sr4dKcBgwPQmhmYpwGDA8ZILvSfAYMAMubz/J8BgwJIMNkUowGDAkUlNiijAYMBQQeXOKMBgwAE+RRMpwGDAFACtUSvAYMDEP1GeKcBgwK+IfOQpwGDAhQvhKirAYMDffXlxKsBgwFaob7gqwGDAVD1W/yrAYMAlnQFGK8BgwAmuL40rwGDAih2t1CvAYMCrQmMdLMBgwGz9AWcswGDAhIrpsCzAYMBLR1/7LMBgwGoes0gtwGDAWTBdli3AYMDqxt/jLcBgwFer+DAuwGDAO5dkfS7AYMB8nw3ILsBgwIeRkxAvwGDAdVeZVi/AYMASCgWbL8BgwCYi/d4vwGDAqjfuIjDAYMDBWwtnMMBgwMoPqqwwwGDAXgwF8jDAYMAzDJQ5McBgwAsPgYExwGDAlncEhTPAYMAkmMTJM8BgwEKH5F4ywGDANXMTqTLAYMAM6kTxMsBgwBtLZzgzwGDALhNYfjPAYMAvyJ7EM8BgwGy3+wo0wGDA5EAwUzTAYMA0CH+ZNMBgwEEguuA0wGDAhtoBKjXAYMAX3VR0NcBgwGwpmL81wGDA8lJZCjbAYMBf/K9UNsBgwK5IPqA2wGDAcnMc6zbAYMCYXnUzN8BgwP/C/ns3wGDAX5ePxDfAYMCSKzILOMBgwK0h3lE4wGDAUpksmDjAYMD910TeOMBgwNpO3iE5wGDAwkWVZTnAYMATZSKqOcBgwOQqbfE5wGDA496dOTrAYMCxn5SAOsBgwBiiKMk6wGDAtetjEjvAYMA0w7BbO8BgwFWl8aU7wGDAqKrY8TvAYMDFCS8+PMBgwJgUW4o8wGDAwNO61zzAYMDM5X4iPcBgwLgyUG09wGDAHHkDtT3AYMDIWH37PcBgwBi6KUI+wGDAaNt+hz7AYMCkKubLPsBgwOGyWQ8/wGDAji+0UT/AYMD/1SuVP8BgwM5ilNg/wGDAsUllHUDAYMD42qRiQMBgwAsIiqlAwGDAO7K88EDAYMCF3ic4QcBgwH5NUX9BwGDAtpG1yEHAYMD/usMSQsBgwJlA2FxCwGDA0EfOpkLAYMBFS53wQsBgwJiIAjpDwGDAj9Qqg0PAYMD6V5TOQ8BgwBmNXxhEwGDA5NuyX0TAYMAG7FWmRMBgwOcxsexEwGDAUIEwMkXAYMA9UPN2RcBgwH4rsrtFwGDAO7yQ/0XAYMCvlkpCRsBgwK1+f4VGwGDA4bhHyUbAYMC1d80MR8BgwDRfK1BHwGDA285hk0fAYMAdnJbWR8BgwOB3NhpIwGDAy3y9XkjAYMDCq9OjSMBgwIIS++hIwGDAEdgiL0nAYMBx+aN1ScBgwMFviLxJwGDA2Zx1A0rAYMCWmvhKSsBgwMaQ3ZJKwGDAEXu42UrAYMB1kM0gS8BgwEQlBmhLwGDA+1Ewr0vAYMAluFb2S8BgwJTIjT1MwGDAkzm2hEzAYMCu5VHMTMBgwPPudRNNwGDAkzX9WU3AYMAvncOgTcBgwBYdMedNwGDAI49CLU7AYMC1OD5zTsBgwLmqbbhOwGDAniYgsk/AYMDZvIn1T8BgwDLgQIpPwGDAbdfczk/AYMB2uPTDUMBgwDODIAlRwGDAmOXpTVHAYMBZHsEhVcBgwAiQc9JWwGDADc2AGFfAYMAyjeVbV8BgwH01qOdXwGDAYEYkbVjAYMBK7l2xWMBgwAgrAPNYwGDAQhtHuFjAYMAcTRikWcBgwJs1puZZwGDA2xxGxVnAYMBAOEQKWsBgwNKBM1FdwGDA1Esb+F3AYMDFzsk7XsBgwGgpSLNewGDAKzUhxF7AYMBlWfYHX8BgwFZuxkpfwGDAYDwGjV/AYMASVVnPX8BgwNyt6BFgwGDAPlsyVGDAYMBTvuyVYMBgwIYB7tdgwGDAL0ubGmHAYMAscFFeYcBgwIn8BaNhwGDADP/V6GHAYMBn82IwYsBgwNNNbXliwGDAsJIpw2LAYMC9vEMNY8BgwLyKKldjwGDAGOVOoGPAYMCih1DoY8BgwBBm8S5kwGDAoFTOc2TAYMDWflC3ZMBgwHw5rvlkwGDAPQ36OmXAYMDR32x7ZcBgwOoDUrtlwGDAG3S++mXAYMC3VNc5ZsBgwKkXdXlmwGDAjS7JuWbAYMByJyT7ZsBgwDZghT1nwGDAH+cZgWfAYMBylJLGZ8BgwGAbdQ5owGDACKxGV2jAYMB5x4OgaMBgwCeQ8ulowGDA000aM2nAYMAgarZ7acBgwEFwOcNpwGDA7IBZCWrAYMBMqllOasBgwEm4apJqwGDAjAd41WrAYMDxvkEYa8BgwISXxFprwGDAFXlNnWvAYMDLlT/ga8BgwKlIrSJswGDAOdywZGzAYMCtyJembMBgwIHc/edswGDAzeILKW3AYMCXRJFpbcBgwNjBIaltwGDAp8SQ6G3AYMB6/nQobsBgwAc6EmluwGDAdTKpqm7AYMC7g4LtbsBgwKTQ4DFvwGDA8TI5eG/AYMBntT/Ab8BgwLh73whwwGDA8jWVUXDAYMB3n/OZcMBgwMZAiuFwwGDAy8IPKHHAYMDkc7tsccBgwKUk2K9xwGDAH10C8nHAYMDRZjwzcsBgwE9m6HNywGDAI84mtHLAYMDwV1H0csBgwIahLDVzwGDAqomUdnPAYMA/D+63c8BgwBClE/lzwGDABgP4OXTAYMBXfpx6dMBgwP5mJbt0wGDASIYU+3TAYMADiyQ6dcBgwAhsfnl1wGDA5eeSNHXAYMBDcw51dcBgwOb2HDp2wGDA8tMbdXbAYMCM1va4dsBgwIprFf52wGDAG8OSQ3fAYMA7JbCId8BgwD919sx3wGDADMbOEHjAYMBzhZdTeMBgwCgSh5R4wGDA7kJY03jAYMAO6RURecBgwKiOY055wGDATbIJi3nAYMBJPE7JecBgwNo1tgd6wGDAU7mFR3rAYMAfCeeIesBgwInTcst6wGDA+WT+DnvAYMATdcNTe8BgwAalaZp7wGDADQWy4HvAYMC0m4gmfMBgwCRXamx8wGDA5MsCsnzAYMDf6xX3fMBgwHEWiTt9wGDAOhpVf33AYMBW2Y3CfcBgwJVb8wN+wGDAxrd8k4PAYMBE1dWahMBgwEdz492EwGDA5UuLY4XAYMAI1vynhcBgwGf+1nOGwGDA6dlHxofAYMCaiYoGiMBgwF3xOkiIwGDAndH8iYjAYMA8jLvNiMBgwBSu+RCJwGDAi1v1VYnAYMDlmOqbicBgwLui3dmLwGDAUJGtHYzAYMCFvAhjjMBgwBdlzKeMwGDApHTJ6ozAYMDTLIktjcBgwBAoZ3CNwGDAmZsgUZ3AYMCbIo6YncBgwCvBA96dwGDAFo6CiJ3AYMDdFAhtnsBgwNg8QLOewGDAhm7o+J7AYMDgHL0/n8BgwAv1nYefwGDA2XCa0J/AYMBiWYgVoMBgwP6JT12gwGDA5Ns8paDAYMDCsQ7uoMBgwKSvcz6jwGDAoBlEhaPAYMDk/PHLo8BgwNFARRGkwGDATGJ0UqTAYMDkW0KTpMBgwDQSR9WkwGDAt3uMM6zAYMC5TCI0rsBgwLqbXn6uwGDArJqJxq7AYMCgfj0Or8BgwEzRD1ivwGDAWGXpoq/AYMA95vfnrcBgwJPRtC2uwGDA9eMXc67AYMDCPJy3rsBgwFOZDf2uwGDAWqy3Q6/AYMAKE8iJr8BgwECSD9CvwGDA+tQzFrDAYMDDit5csMBgwC8TnaOwwGDAn46NNLPAYMAz51eBs8BgwGd0MH2xwGDAyvRTxbHAYMAfG3MOssBgwI7XHViywGDA6NlXobLAYMCIuKPpssBgwMA/rzGzwGDAyjGWebPAYMBiopPAs8BgwCYptgS0wGDActpHSLTAYMBZaX+LtMBgwHcea860wGDAXKwUEbXAYMAE2exTtcBgwPlAO5e1wGDAPYXj27XAYMCS7oIhtsBgwEPaH2i2wGDA/941r7bAYMCo0T72tsBgwJWUYDy3wGDAqqsIhbfAYMA+yQfOt8BgwL02psu6wGDAC52hFbvAYMA6hAtfu8BgwL2r8qe7wGDAFDAG8bvAYMDTFBmAucBgwMWvzse5wGDApdpNDrrAYMBnC9OYusBgwOfK/N66wGDAEXixI7vAYMDgAqxou8BgwCPQn4K+wGDAko5Gzb7AYMBbtkAuvMBgwMqENWS/wGDAs3mer7/AYMBLm2H6v8BgwH3phETAwGDA9nPUjcDAYMArfmXWwMBgwL3+cR7BwGDAbMC9ZsHAYMAFrw+uwcBgwDjIU/XBwGDACdlnPcLAYMDem1prv8BgwOKAobW/wGDAsRFzAsDAYMD6k0ZPwMBgwC5/mJvAwGDA5fCm5sDAYMD46JsxwcBgwHNtrXfBwGDASRPgusHAYMAeRBb8wcBgwIE/zDzCwGDAU/znfMLAYMCGefy8wsBgwJozpP3CwGDA5DKXQMPAYMARVh+Gw8BgwAqRgMbDwGDApY8gEcTAYMC2mMFaxMBgwFy8lKXEwGDAdosO7cTAYMBb5+g4xcBgwFQ044LFwGDADnTPy8XAYMBwZm0UxsBgwGPsDF3GwGDAenLupcbAYMD6F2LvxsBgwO7Hd4PHwGDARhNBB8zAYMCPWxRTzMBgwOt5bJ7MwGDAJ4kk6szAYMBTHkk2zcBgwL8OOILNwGDANwVPzc3AYMAD0DUVzsBgwFch9VXKwGDAyLfWmsrAYMBmxvnfysBgwHKv7SXLwGDAeZATbcvAYMCuJBK2y8BgwORAwwDMwGDAmAtQa9DAYMA72YKXzMBgwCY3cOTMwGDAU/ppMc3AYMDyIoh+zcBgwBrmp+bRwGDA00OhMdLAYMDe3a590sBgwEksZ8nSwGDALeoJFdPAYMBniU9h08BgwFC2+azTwGDAXKLP+NPAYMCyoHVD1MBgwIY0aozUwGDAMx8nYt3AYMADZ6SJ3cBgwGgrls/dwGDAapKLP+HAYMC075YK3sBgwD1QJlnewGDADHDYpt7AYMCn2jEQ8cBgwL/WoVbxwGDAQ7/SnPHAYMDTdQPi8cBgwA4v9SvywGDAlLRcefLAYMBFAOzB8sBgwOXQ+2zywGDAMKNoPPXAYMApLKuA9cBgwC1Uo8T1wGDA3nxSCPbAYMDRCVze88BgwB+jjyf0wGDAg/iXXv3AYMB8+cCn/cBgwLVE4e79wGDAiAS9Nf7AYMBo8Eh8/sBgwCfl+cP+wGDAyHuhDP/AYMDyUtJS/8BgwEC49Zf/wGDAvu312//AYMAk2mIfAMFgwBQWAmIAwWDAAAUKBwPBYMBx4hpNA8FgwBcu45IDwWDA+rwQ2APBYMDBZiy1AsFgwLVZrF8EwWDAGPcHLgPBYMDK645zA8FgwL5+r7gDwWDAl9oR/gPBYMD89+eeBcFgwIt7TooEwWDASxWD0QTBYMDIy3sZBcFgwN2WkWIFwWDAzrPUrAXBYMA+n/r3BcFgwNs9hUMGwWDAhjRIjwbBYMA4GtraBsFgwJ4VIyYHwWDAJ9bIcAfBYMBP15W6B8FgwHwy6AMIwWDAzkPlTAjBYMB41aCVCMFgwIANZd4IwWDAMhwfJwnBYMDVB/ZvCcFgwLTfJrkJwWDADkRuAgrBYMC4r4xLCsFgwL6GtZQKwWDATVan3QrBYMCBKlcoC8FgwGJxfm8LwWDAtMd0twvBYMDDnqz+C8FgwGhxp0QMwWDA42+ciQzBYMDpRJLPDMFgwJXEGBUNwWDAq9QAWA3BYMChMtqeDcFgwLeFiuUNwWDA1TZULA7BYMCgZ1JzDsFgwJ3qi7oOwWDAh5wMAg/BYMCyWNRJD8FgwHeYO5IPwWDAiufy2g/BYMCh0tkjEMFgwPBTWGwQwWDAd43RtBDBYMADaof9EMFgwKMjOEYRwWDAukBbjhHBYMBsqBDWEcFgwMfBGB0SwWDAcc6uYxLBYMDE9COqEsFgwCSIIfASwWDAY83PWxPBYMD1QODZE8FgwAaY1hoUwWDA1Z7hVhTBYMCx5BhNFMFgwJWApZIUwWDArRZp1xTBYMAFil8cFcFgwAGNT2AVwWDAZ7FRoxXBYMC8e3/mFcFgwDeHMYQWwWDA/NcnABfBYMBIwNhCF8FgwFyuWXcXwWDAeOf2qRfBYMC+kkz+F8FgwFvImE0YwWDAcUFmmBjBYMBpJjfbGMFgwIvDn4AYwWDA1teUwBjBYMD1zIcBGcFgwM/TdkMZwWDAuWV3hRnBYMBXlriiGsFgwBP2wuIawWDAXVJEIxvBYMADG6mDGsFgwH5qzakbwWDAGUVP6hvBYMD7B5m4H8FgwB9UKvYfwWDAKCSzMyDBYMDcOMRyIMFgwMppFrEgwWDANfcy7yDBYMAJtwUfIsFgwMhMLGsiwWDAksGtqSLBYMDn5tvnIsFgwDf6vEokwWDA207OjSTBYMDElorRJMFgwPZZZBYlwWDAJSjoWyXBYMBOl+qhJcFgwMdcUpskwWDAdyOHLybBYMAwQhp2JsFgwGIqQbwmwWDAJHLHASfBYMCy0yVHJ8FgwIv2a4wnwWDA/o03QibBYMBDZax+JsFgwJzla7kmwWDAtG+t9CbBYMBFpBTSKMFgwMbbpRIpwWDA6Wr7UinBYMBOIjuTKcFgwFYn7NMpwWDAeFU6FSrBYMAEz8VWKsFgwEG+sZkqwWDATH4M3SrBYMB3DJUgK8FgwGe1XaUpwWDAjCEd5SnBYMDfAYklKsFgwHFOG2YqwWDACwvlpSrBYMDU5delK8FgwMX/3xotwWDA+NEAICzBYMA9e3haLMFgwN3LIpcswWDAt4knPS7BYMD5qp8LLcFgwOq/87wxwWDAHVc2+jHBYMAYSvw3MsFgwJxWeXYywWDAsD+ztTLBYMAxBAn1MsFgwPfETzQzwWDAsw98czPBYMBnPnOyM8FgwAotGfEzwWDAW9THrjbBYMC+3x30NsFgwBDH/TY3wWDAQgSBdzfBYMApbne2N8FgwMoSVPM3wWDA1Deu9DfBYMDmHPQyOMFgwKWg+BI7wWDAP6j2VjvBYMC8TQCcO8FgwCiF/+A7wWDABN1zJjzBYMBphdlrPMFgwLPo4LA8wWDALBgI9TzBYMActq43PcFgwPFgbSw7wWDAb0geazvBYMCIMYSoO8FgwBt21+o7wWDAgvgwLDzBYMDLPh1rPMFgwNkuY6U8wWDAsdzyID3BYMA3HQ9ePcFgwJRRldQ/wWDAWn38EUDBYMCTdi5QQMFgwK/C9I5AwWDAnLUPzkDBYMAkOTvRPsFgwG5EPxI/wWDABX6iTz/BYMAPqOmLP8FgwDuey8Y/wWDAjy6OzkbBYMCKV9sLR8FgwHxja0dHwWDAQ5F8r0rBYMDlAb/ySsFgwKbNRvlHwWDA2VHjNEjBYMCoZLBwSMFgwEVY3PtLwWDA6aUG7UjBYMDOtB4uScFgwKoXYLdMwWDAWpe7tEnBYMAOQJuoTMFgwC0oSuNMwWDAKrHlIk3BYMAhd+9jTcFgwFVhSaJNwWDAASpf4E3BYMD7wkIeTsFgwIoVqVtOwWDAGA8DmU7BYMCXw9fVTsFgwHpnmhJPwWDAPdI3T0/BYMDeNrSLT8FgwHL3ZchPwWDABMRuBVDBYMCflM5CUMFgwAtbN4FQwWDAEaDkvlDBYMAJHRP+UMFgwHsOrz9RwWDAgrrsf1HBYMC/m2O/UcFgwJXz3v9RwWDAQbnLP1LBYMAvBkR/UsFgwALsPb5SwWDA+rtu/FLBYMDSoe05U8FgwAOstHZTwWDAjRbnslPBYMDuTtvtU8FgwM2WEihUwWDA7WXjYVTBYMA7bLyaVMFgwGLzwtNUwWDAChr0DFXBYMCjUkRGVcFgwPZ8/H9VwWDAOGxlulXBYMA+y+b1VcFgwILebzJWwWDAGd8ZcFbBYMBnmY6uVsFgwMZRwO1WwWDAY6ibLVfBYMCNkeptV8FgwFEFm65XwWDAR89v71fBYMATXi8wWMFgwBoDtnBYwWDAOBO3sFjBYMBhiH3wWMFgwHg0SS9ZwWDAyHxYbVnBYMD8NvGqWcFgwLOZ7ehZwWDATSB4I1rBYMCeXKGlWMFgwKq5MplawWDApHfA0lrBYMBzrbUOW8FgwN/PBklbwWDApFOyglvBYMBTLf++W8FgwKwZ8vlbwWDAhBhNOFzBYMDUCQh0XMFgwC9UWbFcwWDAmPo48FzBYMBx5CswXcFgwOggfHBdwWDAZ5kysV3BYMBj7fPxXcFgwKFVeDNewWDAxOLsdV7BYMAKYyS2XsFgwKA8OvVewWDAXLY4NV/BYMDnNch0X8FgwN5XFrRfwWDADzny8l/BYMD29BUxYMFgwGpRyW5gwWDA+A5qrGDBYMBP0WzpYMFgwI/zxiVhwWDA+MO3YWHBYMCl5TKdYcFgwPVvUthhwWDAYRC8EmLBYMAyi6tMYsFgwB9s9YZiwWDAxcD0wWLBYMBQc/v9YsFgwPFOODtjwWDASwqQeWPBYMBuz3m5Y8FgwI/p5v1jwWDAdgvgQ2TBYMBa/E2HZMFgwBV+JChkwWDA00pPDWXBYMA1ZL9QZcFgwAJispFlwWDAuayy0mXBYMASfQUSZsFgwBqzGlBmwWDA8rTPjmbBYMCwMXBLZsFgwDfPCQtnwWDA0gQjSWfBYMDXi6WHZ8FgwJ3yXWNnwWDAJB3SBWjBYMCYVlFDaMFgwKmV0oFowWDA135FwGjBYMB+1bD+aMFgwGhznjxpwWDAItrVemnBYMBV84O5acFgwNM5yPhpwWDAlebPOGrBYMAyHu95asFgwKzkRLxqwWDAPnPjAGvBYMDvnrdFa8FgwDbmZoprwWDArSmDzmvBYMAsd0oSbMFgwJioD1VswWDAs6nolmzBYMBxYBbWbMFgwOmWsBNtwWDA3+uPUG3BYMA+5D6NbcFgwOip18ltwWDAhmTKBm7BYMDsvl9EbsFgwPxw3NtuwWDAatcOxG7BYMBLDBhrb8FgwJkVhEpvwWDAp6ROjG/BYMCCLdLKb8FgwP5YYRBwwWDAVmzKS3DBYMCIqNKOcMFgwLM5/85wwWDA2UpcD3HBYMA2rXlQccFgwLw2YpJxwWDAvKzn1HHBYMAf0bkXcsFgwPPyH11ywWDAtlR/oHLBYMBc42zjcsFgwLsF5idzwWDA2ElobHPBYMCS8cewc8FgwJVT5vRzwWDAHqmnOHTBYMCgKsN7dMFgwDv1cr50wWDAJNKV73XBYMAKKPtBdcFgwN27p4R1wWDAsp3nxXXBYMDzwCYGdsFgwEu9HUZ2wWDA9U0dhnbBYMDV4tbFdsFgwOVmsgV3wWDAaTLHRXfBYMDRinaFd8FgwGi0u8V3wWDAvSVCBnjBYMBHXy5IeMFgwE0soop4wWDAKMVNznjBYMC1DuUSecFgwC29OFh5wWDAwKBZnnnBYMARbvDkecFgwGvunyt6wWDAzd8+cnrBYMBR8d24esFgwPBORP96wWDAXmEVRXvBYMD+WDSJe8FgwEih6cx7wWDA0ZV8EHzBYMAjohr5fcFgwGEAHpd8wWDAZOtd2nzBYMBW7xoefcFgwC4aBGN9wWDAk80qqH3BYMAwykLtfcFgwJUKajJ+wWDAurqhd37BYMDOfL+8fsFgwI4F/f9+wWDA9AyKRH/BYMB4jzqJf8FgwJPPbMx/wWDAwE6wD4DBYMCD8BRUgMFgwLz5X5mAwWDAgxLm34DBYMBWeQIogcFgwLU0ZHGBwWDAHe1Cu4HBYMDDcBAFgsFgwNHyQ06CwWDAxPsll4LBYMDzc6LegsFgwM2EZiWDwWDA6/FAa4PBYMC67DOwg8FgwEm6H/SDwWDAG5J/NoTBYMCujuR3hMFgwLJIpbiEwWDANhah+ITBYMCWmsM3hcFgwPFcJXaFwWDArrlwtoXBYMBSeXL3hcFgwNWPwjqGwWDAt9Oxf4bBYMA6WxjHhsFgwOQzsxCHwWDAIBhxW4fBYMBVC+Omh8FgwOU7bfKHwWDA34epPYjBYMCZi4WIiMFgwLSasNGIwWDAQebwGInBYMC3hyJficFgwMwX36SJwWDAcjbH6YnBYMBh3ZMuisFgwCDbk3OKwWDAuKTpuIrBYMDREm7/isFgwE3lMkaLwWDADR4NjYvBYMCq/wDUi8FgwCZSvhqMwWDAXu4+YYzBYMCQHwenjMFgwDWVF+yMwWDAMIPdMI3BYMD0z6x1jcFgwIIi7LqNwWDAqZupAI7BYMBbFClHjsFgwJEhlI6OwWDAxGFx147BYMD7SBghj8FgwPd7SmuPwWDAlIKStY/BYMBjlLv/j8FgwNLDyEmQwWDAANqqk5DBYMAdsejbkMFgwJ0O7iSRwWDAuAY4yJPBYMCxd60NlMFgwJXUEgGSwWDAhj14SZLBYMD2fY2SksFgwEOpztuSwWDAE9S1JpPBYMD6L3Nwk8FgwInLWrmTwWDAO/cwApTBYMDk5BFMlMFgwKXDiJGUwWDACoA21pTBYMB05wMdlcFgwKC25WKVwWDA1kIIp5XBYMBI3kzrlcFgwJ4ILDKWwWDA+8g2eZbBYMCdXlTBlsFgwE/+m2qZwWDA3V9eUZfBYMD8GVqfl8FgwNqwoOmXwWDAHme2NJjBYMCbVpV/mMFgwLPi78mYwWDAvkmCE5nBYMDvb8RcmcFgwICE0qWZwWDA2VDQ7pnBYMDp6jx4nMFgwBFTLYOawWDAtr3fz5rBYMARYyoYm8FgwGeSeWKbwWDAkjNMrZvBYMCJa+H3m8FgwDFzKUKcwWDAKaIXi5zBYMCVECnTnMFgwAdUeh2dwWDAUTASZp3BYMBPohuvncFgwLAOy/adwWDAMJsjPJ7BYMDG346DnsFgwA42pcyewWDA9DIUFp/BYMAVnolfn8FgwMfFUKmfwWDAR4u185/BYMBW3849oMFgwL7zzoigwWDAvQkF1KDBYMCB/3ofocFgwD2ULGuhwWDA2mait6HBYMACM1QDosFgwJ44+U6iwWDAWgxQmqLBYMCc64rlosFgwJymqTCjwWDA4TAFe6PBYMDYYP3Eo8FgwMskHQ6kwWDAhQ6CVqTBYMDy136dpMFgwLpZm+OkwWDAEqThJqXBYMA2NZlrpcFgwBOkBK+lwWDA6Pd086XBYMCRsZQ4psFgwO31iX6mwWDAAKQtxabBYMBhpMcMp8FgwDRuG1WnwWDATzQznqfBYMD5mNfop8FgwHxeZTSowWDAjq/PgKjBYMCMBUfSqMFgwDwDbR+pwWDAQsuzaKnBYMBWHo20qcFgwEw+4P6pwWDA/LZKwKvBYMDbjcyhqsFgwPxFHu+qwWDAf381OKvBYMCXdYJ+q8FgwCxy1sWrwWDAnZKpDKzBYMCA1MtRrMFgwLdgZZaswWDAJTPO26zBYMAIq00hrcFgwDk592atwWDAErD+rK3BYMAxkKDzrcFgwPep1jquwWDAjmfrgq7BYMDZ1w/MrsFgwPsoehavwWDARQ0MYq/BYMD1ZZqtr8FgwHfXfPivwWDAGls1Q7DBYMC3VKGNsMFgwPS5fNewwWDAYPcTILHBYMCLNltnscFgwKaz2K2xwWDACNgx9LHBYMDfSow6ssFgwLSrI4GywWDAxKGEyLLBYMBxuoIQs8FgwFJiz1mzwWDAx9lbobPBYMAsEhTqs8FgwONctPG0wWDAEakCNLXBYMDk8fa5tMFgwHKwEgC1wWDArYPlRbXBYMBZVruLtcFgwHDvjtG1wWDAGZh0F7bBYMDakMpctsFgwI7DWaW2wWDAcSiX8LbBYMDoT9g2t8FgwFLyiYC3wWDA8iBhzLfBYMBPLIEWuMFgwCs/QmG4wWDAY8HRqbjBYMB2cSfxuMFgwEp9qza5wWDAiLqOf7nBYMCT06vEucFgwJNCaQi6wWDAq3FbT7rBYMAOZaWWusFgwM4uwti6wWDA4zmLGrvBYMAdoGRiu8FgwLH1Kae7wWDAxlHM7LvBYMC9dCAzvMFgwPMsgHm8wWDA3JIawLzBYMD8I3YFvcFgwHUTFEq9wWDAn4s4kL3BYMDsWtzWvcFgwP2rLB6+wWDA3GcyZb7BYMC/10esvsFgwESLAvS+wWDALlb7Or/BYMDTNvyBv8FgwEGy7si/wWDAX7OxD8DBYMDo9WhWwMFgwBei0JzAwWDAm/Xf4sDBYMCSarcowcFgwP5I1m7BwWDAEVpCtcHBYMC6cCL+wcFgwMt9cEbCwWDAsDJ4jsLBYMCTeB7VwsFgwCUrJB3DwWDAzhMJZcPBYMBz9yitw8FgwFcf1fPDwWDAxbI2OsTBYMBfycSBxMFgwAByGsjEwWDAip1wC8XBYMCXuKROxcFgwHt+iZXFwWDAImub2sXBYMATMnkdxsFgwBXnCGHGwWDATPz9pMbBYMAJVfXpxsFgwDWD5izHwWDA+p2rb8fBYMAbg3yzx8FgwGtgNvbHwWDA3mYiOMjBYMAiLQx9yMFgwO8u38PIwWDAakGnCsnBYMAhAvdPycFgwHQhGJbJwWDAg98e28nBYMAVlocdysFgwA2Ba2HKwWDAv+LupMrBYMAJgYfnysFgwLZd2SnLwWDALjfFa8vBYMBIwTqty8FgwDhKZu/LwWDAuauyMszBYMA5fv12zMFgwHNScLvMwWDASW8ZAM3BYMDPfLREzcFgwOkN+onNwWDAtHGRzs3BYMCvSjITzsFgwKuUy1nOwWDA13vRos7BYMCU3BLozsFgwB5kwizPwWDAtEAvcc/BYMA/U9O0z8FgwEmxWPfPwWDAEiJ8ONDBYMAioZx40MFgwH1VI7jQwWDAiohA99DBYMD0Ahw20cFgwBEvS3XRwWDASUcxtdHBYMDi9tX20cFgwJamSjnSwWDA1lX2e9LBYMD5+G++0sFgwCZ4wADTwWDAFoXEQtPBYMBIdZOE08FgwPx6OMXTwWDAJLvZBdTBYMCFypZE1MFgwPT2xobUwWDAgqfdyNTBYMAVq/YL1cFgwNQrJlDVwWDArqEdltXBYMC57tfd1cFgwL6KWCbWwWDAo2J7btbBYMAt2iK21sFgwL4MN/3WwWDAo+scQ9fBYMBCpViH18FgwBOGq8jXwWDAdu6WCNjBYMB5W7pI2MFgwH/ZIIrYwWDAMBCsxdjBYMBq/60F2cFgwHwTbkPZwWDABHPOgdnBYMDV0tG/2cFgwOr3jfzZwWDAGJ8QO9rBYMATCtl62sFgwDtvXbvawWDAy0ay/NrBYMCEnU0+28FgwF1xwYDbwWDAFgnbw9vBYMAsVCMH3MFgwF+px0vcwWDAoMcakNzBYMDkAxTV3MFgwDTRjR3dwWDAOHKmYd3BYMALZMym3cFgwJpaIOvdwWDA5sWdLd7BYMDkDOtv3sFgwMMvBLHewWDACqj78N7BYMANZgMv38FgwKDO7G7fwWDAPbRcrt/BYMDlXzrt38FgwHQwKyzgwWDAb769aeDBYMC7rlSo4MFgwLSS+d/gwWDAJpc7L+HBYMBlaRRv4cFgwAxuvrHhwWDAD7ub9eHBYMA6kag54sFgwMCTNX3iwWDASMcCwOLBYMA+NbwC48FgwBceOEXjwWDAIWw6h+PBYMABY6PI48FgwP9QZgnkwWDA1ShpSeTBYMCUGzeJ5MFgwJFiSsjkwWDAeqq3B+XBYMAEuklH5cFgwJxKAYflwWDA+OYtx+XBYMBDbZEI5sFgwB0cy0rmwWDAw8L5jObBYMC5QQLP5sFgwB6nohDnwWDAzsh8UefBYMA5SpKR58FgwLLWF9DnwWDAMApCDejBYMAjUUVK6MFgwMokZ4fowWDAzAGuxejBYMDqaNoE6cFgwBdzLkXpwWDAHvvphunBYMBP9cfK6cFgwJoeoQ/qwWDACuQMVerBYMCobTOa6sFgwJVNi97qwWDAkfQLIuvBYMCVufZk68FgwBG+gKbrwWDAlTLf5uvBYMCqolIm7MFgwKDcwmTswWDAuE6WoezBYMCT5Kfd7MFgwET9FBntwWDA2t9sVO3BYMBqmJCP7cFgwGcH38rtwWDA81i0Bu7BYMDpcJtD7sFgwPL/kIHuwWDAHu1Zwe7BYMB39lkC78FgwNr/XETvwWDAJRfDhu/BYMCuitnI78FgwG43xwrwwWDArWMuTPDBYMC1awGN8MFgwBsKNczwwWDAf1WWCvHBYMC6iipI8cFgwOq1jYXxwWDA8SV1w/HBYMBDq7YB8sFgwJ4TCUHywWDA0PGhgfLBYMCruBTD8sFgwPuPHAXzwWDAqkS4RvPBYMD6FhuI88FgwJk81cjzwWDANF3QCPTBYMAdgGhI9MFgwEtXQYf0wWDA/S2wxfTBYMAwP5oD9cFgwJufM0H1wWDA5e6WfvXBYMB7NCC89cFgwOZnN/r1wWDA5I+ROPbBYMCEDv129sFgwC+Vg7X2wWDAxsAp9PbBYMAZpiwz98FgwLXWNnL3wWDAPOe7sPfBYMCrX57v98FgwJakSi/4wWDADhNJb/jBYMAKPP6v+MFgwJ5Vd/H4wWDASrrYM/nBYMCULnZ3+cFgwPPLarz5wWDAdzRXAfrBYMD5Y31F+sFgwG+JtYj6wWDAlO6ryvrBYMDAB54L+8FgwCpbM0r7wWDAzypshvvBYMDnv9XA+8FgwDdIe/v7wWDAMudHNvzBYMCMiC5x/MFgwIxFUKz8wWDA9dbM6PzBYMB69d0m/cFgwJbE5GX9wWDAj6G3pf3BYMCoj1Dm/cFgwF4qgCf+wWDAYVcfaf7BYMA3A82q/sFgwKtEYOz+wWDAWVnrLf/BYMDzknFv/8FgwD7j1LD/wWDAvBcU8v/BYMB++iAzAMJgwO7i6XMAwmDArvV1tADCYMCT9dH0AMJgwH8YOTUBwmDAL+jGdQHCYMBLxV22AcJgwMvg9/YBwmDAUX3XNwLCYMD1ljF5AsJgwGyyf7oCwmDAWKZ3+wLCYMD5Nug7A8JgwGIvu3sDwmDAPfEEuwPCYMBHUFz5A8JgwCHDZzYEwmDAnRD8cgTCYMDYBKSvBMJgwKAppewEwmDAXwNAKgXCYMADgWtoBcJgwEqJfacFwmDA/6to6AXCYMA6vTkqBsJgwLQkR2wGwmDAF2Y8rgbCYMAGkbjvBsJgwA7brDAHwmDAZrHAcAfCYMCz5CevB8JgwE66RewHwmDAJDv2KAjCYMDjXWRlCMJgwIjWy6EIwmDAuu523gjCYMAZgo8bCcJgwKWzqFkJwmDAB+ismAnCYMC8oTHYCcJgwIMTSBgKwmDAYz3OWArCYMAr6seZCsJgwPAxA9sKwmDABuhyHAvCYMAQCvpdC8JgwF2FZp8LwmDA8ISk4AvCYMBm9qUhDMJgwGOtYGIMwmDAkaH8ogzCYMAzvvXiDMJgwDv5ayINwmDAVwpDYg3CYMBhbuaiDcJgwALyWOMNwmDA9GauJA7CYMD/M8lmDsJgwC/1aqkOwmDAy+SQ7Q7CYMBqie4xD8JgwDxZinUPwmDARV4buA/CYMAyn4X5D8JgwCkrsDkQwmDAf4fSdxDCYMC9SwKzEMJgwKKYre0QwmDAOENiKBHCYMBNEMJjEcJgwJH1E6ARwmDA2WuN3RHCYMCwcKEdEsJgwML3w2ASwmDAGyxBpRLCYMDc/nnqEsJgwDV08S8TwmDAxW82dRPCYMCaaAK6E8JgwFCul/0TwmDABY2kPhTCYMDhdgF/FMJgwAb79r4UwmDAN+LQ/hTCYMANQvk+FcJgwAaHuH8VwmDA6eJHwRXCYMAGDWUEFsJgwCf4VkgWwmDAEJ2UjBbCYMDjpu3QFsJgwMKGWxUXwmDAT40MWRfCYMB1XFKcF8JgwAWEht4XwmDADar3HxjCYMBPpNRgGMJgwAM1T6EYwmDA0Zxj4RjCYMBrBSshGcJgwAVpa2EZwmDAkDCJohnCYMDWLd/jGcJgwDEpKSUawmDAwjG0ZhrCYMBWgpuoGsJgwOJq1uoawmDA+YM2LRvCYMDbsbdvG8JgwN2WlLIbwmDAfwLE9RvCYMCfcHM5HMJgwJe3tX0cwmDA28dlwhzCYMA4e4wHHcJgwEVJMU0dwmDAFB8/kx3CYMB4Cx/ZHcJgwID+oh4ewmDAdE+UYx7CYMDDe+SnHsJgwF7FjesewmDAxt4QLh/CYMDxDotvH8JgwFrokbAfwmDAYfU38R/CYMAWaYExIMJgwN6bOnIgwmDAuyRusyDCYMCL5FX1IMJgwKvriTchwmDAnCjIeiHCYMBXIoy9IcJgwHYydAEiwmDAD9CIRiLCYMD47Z2MIsJgwNl0a9MiwmDAtEQXGyPCYMBNhABjI8JgwNPLlaojwmDA4mLW8SPCYMAe2WQ4JMJgwGpaFX4kwmDAxTeZwiTCYMCukYwFJcJgwOJvmEclwmDAQfwUiSXCYMDLZDfKJcJgwMiOPwsmwmDA/W5BTCbCYMC1pQKOJsJgwPAbEtAmwmDAacbVEifCYMCmuBRWJ8JgwC18OpgnwmDApZAD3CfCYMDP+rAiKMJgwNomnGcowmDAKpKurCjCYMAQSu7xKMJgwJ1ZgzcpwmDAKGWtfSnCYMA+I13EKcJgwDe+lgsqwmDA+kDmUirCYMDqTtqaKsJgwMKedeMqwmDAwXqlKyvCYMCNVA9zK8JgwOAyoLorwmDAdleYASzCYMB32zZHLMJgwGARkowswmDAys8u0SzCYMDjWHoVLcJgwJahn1ktwmDAJXaQnS3CYMCzr1HhLcJgwJ3XpiUuwmDAXr/+aS7CYMCCSZevLsJgwMLVXvMuwmDAX/uGOi/CYMDPK0yCL8JgwMz4nscvwmDASdTFDTDCYMDqeglWMMJgwOZ0Dp8wwmDAgKa56DDCYMDK2hwyMcJgwPKj/3oxwmDAkMiAwzHCYMC3I4cLMsJgwMcvC1QywmDAXg5MnDLCYMANLprkMsJgwB+RgCwzwmDAoy4KdDPCYMA7snq7M8JgwMtoswM0wmDAq+hsTDTCYMAsb1L8N8JgwKdus940wmDAcweXJjXCYMCUTx1vNcJgwM1dWbY1wmDANQTq/TXCYMDikXJENsJgwF3kBYo2wmDAnKYYSjrCYMBjWQyWOsJgwHWgu1c3wmDAwTTxnjfCYMAJOajmN8JgwAovji84wmDAweCoeTjCYMDnmUvEOMJgwLdBLg85wmDAaiwdWjnCYMALFOSkOcJgwKqBZe85wmDA4NI5OTrCYMBsc1qCOsJgwIY9+co6wmDAY8ZhEzvCYMB23bdbO8JgwLXtFqQ7wmDAhrGt7DvCYMAwtY01PMJgwEY65H48wmDA/y23yDzCYMCPqPISPcJgwLNHp109wmDAH8O1qD3CYMAXVhv0PcJgwEVF3z8+wmDAGQ0RjD7CYMCGGU/YPsJgwKQtUiQ/wmDAJvLmbz/CYMDwnNu6P8JgwMlUWgVAwmDASi8OT0DCYMA4y3+XQMJgwPpCbt9AwmDAnyFkJ0HCYMB6AZhvQcJgwBfsXbhBwmDA+sygAULCYMCcpvBLQsJgwLDulJdCwmDAoY1P5ELCYMCTpFwxQ8JgwGHthH5DwmDA9wCDy0PCYMDo6TMYRMJgwL2PVmREwmDAchAor0TCYMCdTBn5RMJgwPUSqkJFwmDAFsfsi0XCYMBFXR7VRcJgwLMNYx5GwmDAObjaZ0bCYMAY2xyyRsJgwN9F+/xGwmDAWzIrSEfCYMD3Y46TR8JgwDfBIt9HwmDAE2TWKkjCYMCH17h2SMJgwEmVTMJIwmDALXKXDUnCYMCZ3VpZScJgwGMUmKVJwmDAPbuF8knCYMDPGBZASsJgwOUQQY5KwmDAFWmN3UrCYMAZANotS8JgwG5cKH5LwmDA8n0MzkvCYMBtwCkdTMJgwCr0gGtMwmDA74CzuEzCYMBGFOIDTcJgwK49mE1NwmDAPDsplk3CYMDquiveTcJgwMWvyCVOwmDAHZRjbU7CYMBZcie1TsJgwCB4z/1OwmDANmJfR0/CYMC6RM2RT8JgwMZsDN1PwmDAPLQoKVDCYMCa2/B1UMJgwOmXecNQwmDAc6CWEVHCYMBdeBhgUcJgwCdBFq9RwmDAoD90/lHCYMBfEy9OUsJgwE8NKZ5SwmDAjTc37lLCYMAEelY+U8JgwAXmg45TwmDAmkty3lPCYMAGNe0tVMJgwOPShXxUwmDAAr+HylTCYMDAhJ8XVcJgwHl4zWNVwmDAdS72rlXCYMDOqkj5VcJgwHWhCENWwmDAKvl+jFbCYMB1QLTVVsJgwMeA7h5XwmDA5YRYaFfCYMARxiGyV8JgwIGcePxXwmDAblVnR1jCYMB0FfOSWMJgwIB9JN9YwmDA9ccdLFnCYMCkI7l5WcJgwF+M+MdZwmDATTPPFlrCYMBFph9mWsJgwH68y7VawmDA/2vHBVvCYMAsPN5VW8JgwJAU9aVbwmDANQAg9lvCYMBktihGXMJgwPgxlZVcwmDAgb5c5FzCYMAWF0QyXcJgwFM/Kn9dwmDAJjhcy13CYMD6rykWXsJgwASY7F9ewmDAdOZSqV7CYMCoMrPyXsJgwEk8PDxfwmDANNtahl/CYMDG7QbRX8JgwGRc3RxgwmDA3GvYaWDCYMA+P5m3YMJgwALCywVhwmDAOlpJVGHCYMABo/iiYcJgwBYiqPFhwmDAGkESQGLCYMCtYhuOYsJgwE5Ux9tiwmDA1OYmKWPCYMAVNih2Y8JgwH0Y1MJjwmDACeA8D2TCYMDmEldbZMJgwIVSIqdkwmDAWjPu8mTCYMB6PtU+ZcJgwJWS/oplwmDA9cd412XCYMC/N0QkZsJgwBu5nXFmwmDAECeAv2bCYMAOPbcNZ8JgwLnF5FtnwmDAi7jzqWfCYMCDAuX3Z8JgwL83kEVowmDAnMO2kmjCYMAp6W7faMJgwA/ckCtpwmDAjctMd2nCYMDROIrCacJgwKFAcQ1qwmDA3nYeWGrCYMDQiICiasJgwGSgfuxqwmDA6IacNmvCYMBG6SCBa8JgwMNjqsxrwmDADn64GGzCYMAnepdlbMJgwIPum7NswmDAZ2QKA23CYMDNvEdTbcJgwPEMk6NtwmDA2ECc823CYMBIzupCbsJgwG2PcZFuwmDAUezD3m7CYMDr1yEqb8JgwKZ6BXRvwmDAAd9IvW/CYMCarT0GcMJgwB4QNE9wwmDAnHxsmHDCYMBqfUbicMJgwC0+ZC1xwmDA1diteXHCYMDn6UrGccJgwLgSJhNywmDAW7QOYHLCYMCx3+KscsJgwEXAnflywmDAEcRXRXPCYMBqCmOQc8JgwJrhcttzwmDA9de5JnTCYMAvTFBydMJgwOv1Yr50wmDAwEPwCnXCYMD98npYdcJgwBgU6qZ1wmDA5Id19XXCYMA9AtFDdsJgwAdWJZB2wmDA/l3Z3HbCYMDFNoArd8JgwMh033Z3wmDAtUwAwXfCYMALwjoKeMJgwA46qVJ4wmDA5pWBmnjCYMALH/bheMJgwCm1Ryl5wmDAuK12cHnCYMA1Kbe3ecJgwFCCkv95wmDAPmhjSHrCYMBbEEiSesJgwEcqZN16wmDAvXvjKXvCYMCwoch3e8JgwL8absd7wmDAwODXF3zCYMD67NJkfMJgwDhoP7h8wmDAcq4iC33CYMD23rJafcJgwKeuD6l9wmDAkcoR9n3CYMAeGlxBfsJgwOB2TYt+wmDAZ24Z1H7CYMB/Yusbf8JgwPgMx2J/wmDAO0g4qX/CYMAoiAHvf8JgwFxWfzSAwmDAd0WieoDCYMDgQiTBgMJgwNMSygiBwmDAuYo9UYHCYMCbAK6agcJgwJXIueWBwmDAtEUDMoLCYMBa65F+gsJgwGVMasuCwmDAWOmvGIPCYMBAjxpmg8JgwE7L77ODwmDAkyoYAITCYMCf5a9LhMJgwM7oqJWEwmDAg/YX34TCYMDfIRMnhcJgwAnbsnGFwmDAcnuZt4XCYMDPwMz8hcJgwJ43n0OGwmDAli8Wi4bCYMDSgLbShsJgwIVWnhqHwmDAxiblYofCYMDCO4Crh8JgwFsq/vSHwmDA3pUGP4jCYMDinTuJiMJgwIhOhNOIwmDAlxW7HYnCYMBAmLlnicJgwCszdrGJwmDAgpik+onCYMBCSkpDisJgwH6loouKwmDAm5LQ04rCYMDnEtwbi8JgwNAm5GOLwmDAJr0HrIvCYMAnzTb0i8JgwAvQgTyMwmDA/7EjhYzCYMDMZiPOjMJgwAqQgxeNwmDAXH47YY3CYMAhHyKrjcJgwF8Bo/WNwmDAW0S7QI7CYMDuimaLjsJgwKzFhdWOwmDABAMvHY/CYMDEocRjj8JgwHyurK2PwmDAWGzt8o/CYMCLgGU2kMJgwOrJNHmQwmDAd6j2u5DCYMBRrhH/kMJgwJPxu0KRwmDA22J5h5HCYMCvefHNkcJgwMNMHRaSwmDAOFyYX5LCYMBk+7mpksJgwLZbMfSSwmDA7mu/PpPCYMCinEmJk8JgwGKv/9KTwmDAK9G+G5TCYMAWI+djlMJgwIpQsauUwmDAMWxV85TCYMCo2OQ6lcJgwJiFZoKVwmDAruQuypXCYMDkHE8SlsJgwFVafVqWwmDAQj+kopbCYMDkdZbqlsJgwHhLIzKXwmDAulLweJfCYMC4mE2/l8JgwKAyzQSYwmDAKeS8SZjCYMBjcjmOmMJgwK9uktKYwmDA89G1FpnCYMD/MeVamcJgwB47KJ+ZwmDAYajKCJrCYMDPWHIomsJgwD850m2awmDA77/js5rCYMDViZr6msJgwNJzBkKbwmDA97ooipvCYMC1Dj7Tm8JgwKjN/hycwmDAvsPvZpzCYMD3B9+wnMJgwNbZcPqcwmDATBvCQ53CYMBMYU6MncJgwHH/BdSdwmDAaomdGp7CYMC1cKpgnsJgwI5aFKaewmDACRxJ657CYMAwsxMwn8JgwC3ApXSfwmDA59U7uZ/CYMD9OPT9n8JgwNHMsEKgwmDADDBrh6DCYMBtUT3MoMJgwOJVFBGhwmDA2xMaVqHCYMA2ayKbocJgwBAmL+ChwmDApgx3JaLCYMD5/wprosJgwEmq17CiwmDAzVbz9qLCYMBxYEM9o8JgwIHcDy6jwmDAPiB4y6PCYMBhDU0SpMJgwBEtOFmkwmDAr/Lan6TCYMDjnh7mpMJgwI7V4iulwmDAiYcHcaXCYMB+0U21pcJgwDcQO/mlwmDAbmDcPKbCYMCzClaApsJgwJGMwsOmwmDABIRDB6fCYMBc8ANLp8JgwH8nOY+nwmDAc2Ks06fCYMBuP10YqMJgwJrYUV2owmDA2KJ3oqjCYMDO0c3nqMJgwBfgNC2pwmDAV3udcqnCYMAU0g+4qcJgwLHzf/2pwmDAG7XkQqrCYMBYXDuIqsJgwIyAXc2qwmDAEYJeEqvCYMA0lEBXq8JgwNr/8JurwmDAaB014KvCYMDIdwYkrMJgwAZoXWeswmDANxFGqqzCYMBiDrDsrMJgwHU+fi6twmDAgiX0b63CYMA8h02xrcJgwGtmrPKtwmDA4nQ4NK7CYMC1kAl2rsJgwJyjR7iuwmDAtlwp+67CYMAHiYc+r8JgwPyUfoKvwmDA3mwtx6/CYMCGNE4MsMJgwOQI+VGwwmDAqg8RmLDCYMAhCKbesMJgwOj+eyWxwmDAQB1GbLHCYMAaEeqyscJgwGeZKfmxwmDAlIgBP7LCYMB15wimscJgwGiQ4siywmDAGkWVDLPCYMDAEcRPs8JgwIamnZKzwmDAzYEH1bPCYMCiMDAXtMJgwIZNQFm0wmDAjQxYm7TCYMA+TIHdtMJgwCLkuB+1wmDAxeMKYrXCYMDtuHCktcJgwPfDnPO0wmDA6reqKbbCYMCpJXxstsJgwCxgdK+2wmDAHgeC8rbCYMAPGqQ1t8JgwKSa3ni3wmDAUecbvLfCYMC6UGb/t8JgwE6qp0K4wmDA+QrghbjCYMD22D/Pt8JgwMCapQy5wmDAhOftT7nCYMCAJIOTucJgwJ6jLte5wmDAMwYFG7rCYMBfNxVfusJgwK3eGqO6wmDAls4C57rCYMBSsr8qu8JgwMf/N267wmDAA19wsbvCYMAXgD70u8JgwHrziDa8wmDAxjGHeLzCYMDdkL+su8JgwBoMz/u8wmDA7b46Pb3CYMDHzJF+vcJgwCs79b+9wmDAfBt2Ab7CYMB7/hJDvsJgwAFCx4S+wmDAfs2Jxr7CYMCoX2cIv8JgwHimWkq/wmDAOmBujL/CYMCacZnOv8JgwK/aGgm/wmDA0QI/U8DCYMDWY82VwMJgwLB0gtjAwmDATrVhG8HCYMAqFmVewcJgwGJrYaHBwmDA5m185MHCYMB7pc0nwsJgwGgoX2vCwmDA+Swfr8LCYMBuCALzwsJgwLMREzfDwmDAHrR5e8PCYMAHiRfAw8JgwC5vLQTEwmDAueuFR8TCYMASkfKJxMJgwAljb8vEwmDA8m/kC8XCYMBXnr1KxcJgwIi5H4jFwmDAtCCNxcXCYMC5D30DxsJgwNpbR0LGwmDAYkOrlcXCYMDF98vDxsJgwF3ndwfHwmDAXmamTcfCYMBPZp6Ux8JgwH9T+tvHwmDArJYuI8jCYMAK1LxpyMJgwPNSlq/IwmDA5Q5c88jCYMD2+rs1ycJgwOFIiXbJwmDAYnXHtsnCYMBLlGT2ycJgwGqewjXKwmDA4977dMrCYMCoUAK1ysJgwCrgu/XKwmDAQP7aNsvCYMBtwBR4y8JgwKqHX7nLwmDAtp6x+svCYMDLPyM8zMJgwEs+Kn3MwmDAsRqLvczCYMDawy7+zMJgwMY5iz/NwmDAN324gc3CYMBoUefEzcJgwLch+gjOwmDArNpdTs7CYMD6GcqVzsJgwAf5oN3OwmDAW0opJc/CYMBqbthrz8JgwDQWSLHPwmDAs0h99c/CYMBxdZ830MJgwNixuHbQwmDA3zHws9DCYMCxqHrw0MJgwNncVizRwmDAH2kWaNHCYMAu5gSk0cJgwNFvyuDRwmDA5YYoH9LCYMAon49e0sJgwJbI3J7SwmDA+4wK4NLCYMBV0r0h08JgwCChDWTTwmDAhr7MptPCYMCQO6Hp08JgwAnBkizUwmDAvBSjb9TCYMCILsay1MJgwBCh6/XUwmDACi8MOdXCYMC+NSt81cJgwF1wR7/VwmDAUe7WAdbCYMAcFaxE1sJgwPaXkIfWwmDAs/p6ytbCYMCPensN18JgwDBTjVDXwmDA08rgk9fCYMDJSU3X18JgwM8zlRrYwmDAiAugXdjCYMDOFEeg2MJgwIuIkOLYwmDAV+l2JNnCYMCVPrRl2cJgwBlP7VLZwmDAt8a/5tnCYMDTxfcm2sJgwNyyQ2fawmDAy0myp9rCYMCSak/o2sJgwIlAaSnbwmDAmmoKa9vCYMAkOwqt28JgwJHfV+/bwmDAfHbmMdzCYMDWW6t03MJgwDVLp7fcwmDAE6Wu3NzCYMCxp7Y93cJgwIbc3YDdwmDAB2QRxN3CYMD5Nm4H3sJgwEI52krewmDAU7Z8gd7CYMA6PojI3sJgwBJ1fxXfwmDAiNARWd/CYMDVxXCc38JgwERgp9/fwmDA6CmPIuDCYMA4/jtl4MJgwGzddqfgwmDAzY5l6eDCYMAYWRgr4cJgwL6ijmzhwmDAmxym5+HCYMAmZVDv4cJgwPcCvDDiwmDA8+U9cuLCYMCIXduz4sJgwK+vuvXiwmDAGmHuN+PCYMB9CY1648JgwH5mlL3jwmDA+uzMSeTCYMC0wtGO5MJgwOZrVInkwmDA9EUDzuTCYMB/maMS5cJgwC/2I1flwmDAmxwzm+XCYMB6TNRE5sJgwJyPIyLmwmDARH2DZObCYMBgtzmm5sJgwMKRr+fmwmDABPwfKefCYMAWlrVq58JgwKE0cqznwmDAfSOJ7ufCYMCpIXkx6MJgwJa/5HTowmDAy52EuOjCYMBLnkz86MJgwEXXGkDpwmDALZrig+nCYMDTcX3H6cJgwDxezgrqwmDA+0TLTerCYMCj4M2Q6sJgwLL86pvrwmDA/LAoF+vCYMBFsbla68JgwMjwgZ7rwmDAwVXz4uvCYMAfiMkn7MJgwFQ73GzswmDAEh0zsuzCYMAM3KX37MJgwC3QKz3twmDAFq+tgu3CYMA8bRPI7cJgwDiPRw3uwmDAPgrUS+7CYMBFSN2Q7sJgwKhA1tvuwmDA8wg/IO/CYMBjU29k78JgwJg3iKjvwmDAAS9/7O/CYMAybEgw8MJgwM1EwnPwwmDAg70Mt/DCYMC7nC768MJgwH+zMT3xwmDA/Yr6f/HCYMD0dIrC8cJgwJ+TYQXywmDAfjyVSPLCYMDIUGGM8sJgwAWvy9DywmDAWWPhFfPCYMBTvetb88JgwP2H76LzwmDAJHuP6vPCYMCT7LMy9MJgwOQaX3r0wmDAtrO1wfTCYMDoXvsI9cJgwEUylE/1wmDA3f0glfXCYMCDD5va9cJgwAY8wB72wmDAkBjPYvbCYMDAi9Sm9sJgwNSwHkb4wmDARg7kLvfCYMB95bZx98JgwNF9ja/3wmDAR0rQ/PfCYMDvFfZA+MJgwJsVwoX4wmDA+PydyvjCYMAvaoYP+cJgwKDJUlT5wmDAkHlWJfvCYMDYUm/e+cJgwIL87yP6wmDAN7nhafrCYMA6WDGw+sJgwLFb6Pb6wmDAu2E/PvvCYMBrp9CF+8JgwGM9qc37wmDA+fidFfzCYMBUfE5d/MJgwEgVejn+wmDA+5T36/zCYMDgcM8y/cJgwDMeKnn9wmDAtaDsZP/CYMCeX90D/sJgwCPPzEj+wmDA47D1jP7CYMD0kaDQ/sJgwE1wwhP/wmDAE6BvVv/CYMDhg3SZ/8JgwHCfON3/wmDAkTuBIQDDYMAtADlnAMNgwIMCuK0Aw2DAaizy9QDDYMA5uLM/AcNgwBWhAooBw2DApKSn1AHDYMBmIj0fAsNgwK4ah2kCw2DAen5gswLDYMDJ7Bn8AsNgwNZpeEMDw2DAwVs4igPDYMDlwyLMA8NgwIDqOQsEw2DAs0TpWgTDYMAXtsmfBMNgwILNruQEw2DAHvu4KQXDYMC9yOpuBcNgwC4uNbQFw2DA1J3R+QXDYMCyEJs0CMNgwD0ieYUGw2DAnSDMywbDYMD/enMSB8NgwHOmaVkHw2DAMhSXoAfDYMDj5RLkB8NgwBabTCkIw2DA8VCVdwjDYMAVWJq/CMNgwH9frAcJw2DAGAbcTwnDYMB5Mw6OC8NgwJRXyOAJw2DAs7WOKQrDYMDPp2JyCsNgwIATZ7sKw2DAfFOtBAvDYMBCk+9NC8NgwI6LCJcLw2DAKkXe3wvDYMAj1lEoDMNgwAlUd3AMw2DALTMXuAzDYMC6+On+DMNgwJDXSEUNw2DALwNcgw/DYMCStcjLD8NgwGy1lRkOw2DAoKH9YA7DYMClFg2pDsNgwCK0O/IOw2DAzSUKPA/DYMAbAsmFD8NgwCeuQ88Pw2DAo0U6GBDDYMBfj7xgEMNgwL5sUqgQw2DAEEur7hDDYMAYvOYzEcNgwLQpPHkRw2DAJEsNvxHDYMD0N8UFEsNgwK6S+UwSw2DATQSPlRLDYMAl07rgEsNgwEU9My0Tw2DA7y0NehPDYMBy/uTGE8NgwHoML+kVw2DA+0exXhTDYMCAj06pFMNgwBVo1/EUw2DA3nZxOBXDYMBOQhp+FcNgwNmEEsMVw2DA9z6qBxbDYMAuUi5MFsNgwC5JApEWw2DAt85c1hbDYMAFu84cF8NgwO7N7WMXw2DAwcvsqxfDYMCZRoj0F8NgwPJP7D0Yw2DAehXLhxjDYMDq6mvSGMNgwKbIcB0Zw2DAgM2uaBnDYMCf3emzGcNgwG4s8/4Zw2DAzBvHSRrDYMCcnk2UGsNgwGC2Gd4aw2DABdQ1JxvDYMCN0t1vG8NgwM0Eergbw2DAQGYGARzDYMBpgo9JHMNgwDkuSpIcw2DAClyP2xzDYMA+W2UlHcNgwPffkG8dw2DAnpp0uR3DYMAa9B0DHsNgwHQ9lEwew2DA46q4lR7DYMAsZELeHsNgwH874CUfw2DAxMovbR/DYMDJQni0H8NgwBuDGfwfw2DAmELNQyDDYMAH1oGLIMNgwEapKdQgw2DAG2KykCLDYMCq7K7VIsNgwHbH4hsjw2DATleY8iHDYMBEVfilI8NgwPXzGI4iw2DAuwu31iLDYMBSTHceI8NgwKw1lWUjw2DARfhVBCXDYMCUHovyI8NgwGKBsjgkw2DAj7FH0iXDYMBRdf3EJMNgwP5Kdwslw2DACI1BUiXDYMCx6FqZJcNgwKmV2eAlw2DALiS3KCbDYMBac/NwJsNgwF2Zorkmw2DAhKebAifDYMB7HPJLJ8NgwJb+7LQow2DAjM7A3yfDYMCSDscpKMNgwI3wMnQow2DAKRatvijDYMDq0X0JKcNgwLJUSVQpw2DAf/jIninDYMDOHPLoKcNgwB5ykDIqw2DA3t+JeyrDYMBxtSLEKsNgwLo4oQsrw2DAjzdiUivDYMAivK+YK8NgwFLFc94rw2DA9d3GJCzDYMDpG89qLMNgwL9N+bAsw2DArDSH9yzDYMB79dA+LcNgwK0+XYYtw2DAxfg9zi3DYMABT2EWLsNgwABwy14uw2DAE4Zjpy7DYMBFFBbwLsNgwMBVyTgvw2DA0rihgS/DYMA0v53KL8NgwO16tRMww2DAL+/hXDDDYMD1JRKmMMNgwDusXu8ww2DAb1qzODHDYMA/OdeBMcNgwPx/98oxw2DAasTGEzLDYMD4UUdcMsNgwIx4d6Qyw2DAYHw67DLDYMC/HsQzM8NgwCb8qcEzw2DAuihnwTPDYMAMDGkHNMNgwGBP+kw0w2DAWHs6kjTDYMAN5wvXNMNgwAJwCRs1w2DA7/cGXzXDYMBgKnijNcNgwE8ayug1w2DA5a04UDbDYMA89Ax2NsNgwDumNL42w2DA7qh9CDfDYMCJN45TN8NgwHqiy543w2DANmOw6TfDYMDWS/MzOMNgwBWnbX04w2DA+iZAozjDYMAU1BsMOcNgwJ3qySk5w2DA3fXLlDnDYMBxpHLYOcNgwAkB+xs6w2DAWK2tXzrDYMCmK+OjOsNgwLhw8Og6w2DArPnhLjvDYMCPba11O8NgwD/9J7k7w2DA+JW9/zvDYMAhmYhNPMNgwCozJ5Y8w2DAwxdz3zzDYMBW880oPcNgwI/kxnE9w2DA+GKbuT3DYMCN4toAPsNgwEn37UY+w2DAtPsJjD7DYMAYJDvPPsNgwO8i1BA/w2DAIflUUj/DYMBRACGUP8NgwD/asNY/w2DAGxdZGkDDYMBBSTZfQMNgwO8vMKZAw2DAcoqx70DDYMD1TOY5QcNgwF2ZQYRBw2DAYt1kzkHDYMCOEuMXQsNgwCEWU2BCw2DAfqURp0LDYMDF2qDrQsNgwMZ17y5Dw2DAkTSccUPDYMAPQdqzQ8NgwNS7B/ZDw2DASF8cM0TDYMDR1FRzRMNgwEDJUL9Ew2DAoJ3qA0XDYMCL/txIRcNgwIHBDY5Fw2DAxoNb00XDYMBzw7QYRsNgwA9w3V1Gw2DARlF3okbDYMAZM/LmRsNgwJB4aStHw2DAc5Tgb0fDYMDRpWC0R8NgwCzhDPlHw2DANLqpPUjDYMBkD46CSMNgwLEymsdIw2DAUwiQDEnDYMDrvV5RScNgwMHG5pVJw2DASRMm2knDYMA0qRoeSsNgwMGdgmFKw2DAppSopErDYMAw9YLnSsNgwG75MMBJw2DA+RDXbEvDYMBLu3avS8NgwJUGH/JLw2DA3nSmwkrDYMAcRO4ES8NgwOAV8LpMw2DA6UJu/kzDYMAXslRCTcNgwLlYo4ZNw2DAEBVWy03DYMAR+JEQTsNgwJcbKFZOw2DAHHaem07DYMCK6rLgTsNgwAulDXdNw2DAxGN3aU/DYMBfpNOsT8NgwJfVOe9Pw2DAkDg0LVDDYMBwJ7ZrUMNgwL3+0LJQw2DAf5oi9FDDYMDgkOM1UcNgwO2cN7NPw2DAtaNC7U/DYMCU5sn/UcNgwGepSkRSw2DAGKRuiFLDYMBkCU7MUsNgwPE3gA9Tw2DAuUFAY1HDYMBQx8eSU8NgwE4kMedRw2DAItSaEVTDYMAhsMJQVMNgwAlPoZBUw2DAOeIo0VTDYMAmQFUSVcNgwONpclVVw2DAUbdOmlXDYMCQ1U7vU8NgwOmteiVWw2DAQZUXa1bDYMD3502wVsNgwEZzBvVWw2DATQHzN1fDYMC3n8x5V8NgwBHMhbpXw2DAJKns+lfDYMA7UTY7WMNgwFC+lXtYw2DArAkVvFjDYMA8F4L9WMNgwB7R2D9Zw2DAbAqRglnDYMBKSD3FWcNgwJcBmwdaw2DAvJRzSVrDYMBLqv6KWsNgwGYvjctaw2DAC7TDClvDYMCPQGtJW8NgwK/L3odbw2DAC4l3xlvDYMBHFWcFXMNgwCat50Rcw2DAvukJhVzDYMCcioCLWsNgwFjXughdw2DAHRduS13DYMATg4SOXcNgwO5eo9Fdw2DAmWHPFF7DYMDfJ85XXsNgwMAPaJpew2DAk3CO3F7DYMCKFSYeX8NgwHSeMV9fw2DAV4Svn1/DYMAVstXfX8NgwM5O7h5gw2DACQCdXWDDYMA52+GbYMNgwI8jDtpgw2DA9HleGGHDYMBD+zDuXsNgwJ43HSlfw2DA6Oc51WHDYMC4jasVYsNgwHwQxlZiw2DARsoPmGLDYMD6EV3ZYsNgwDNIkRpjw2DAoDmaW2PDYMA2/DicY8NgwJicM9xjw2DAnqZiG2TDYMC5t5RaZMNgwP2N6plkw2DAu4So2WTDYMBx1N0ZZcNgwIlfplplw2DAhGZcnGXDYMBxh87eZcNgwO0n3SFmw2DA/6BTZWbDYMCVg6moZsNgwNqi0Otmw2DAVaO+LmfDYMDAuwlxZ8NgwF+H5rJnw2DA4ojn82fDYMAsXlQ0aMNgwHo30HNow2DAgwuPsmjDYMClt8DwaMNgwC56Gy5pw2DAXmS4amnDYMALCUSnacNgwDIkE+Rpw2DA+VhHIWrDYMAh/EBfasNgwDrU2Z1qw2DATG+O3WrDYMDofQAfa8NgwAuBAWFrw2DAYpJPo2vDYMB67bDla8NgwDIJ5Sdsw2DAOxndaWzDYMCAofuqbMNgwHplAutsw2DAKz9ZKm3DYMCCXHxpbcNgwCHdl6htw2DAmc7H523DYMBh5wInbsNgwAg4zmZuw2DAlvjLp27DYMB4X9robsNgwJPkoClvw2DAEyTSaW/DYMANmzipb8NgwNRu7udvw2DA9mOEJXDDYMAEUVlhcMNgwBvSTZxww2DA381P13DDYMAHL6wSccNgwGGY0U5xw2DAJWnPi3HDYMCJ/DDKccNgwEtsFgtyw2DAYAUoTXLDYMAf/82PcsNgwJr9otJyw2DAAXdCFXPDYMCVbE5Xc8NgwLwsZJhzw2DAAZ822HPDYMAEHF4WdMNgwDbW3lN0w2DAQMWzkHTDYMARFDLNdMNgwDDVfwl1w2DAEwnkRXXDYMCupqGCdcNgwFSn7b91w2DAztKs/XXDYMDm+wk8dsNgwF5M9Xp2w2DAZ/duunbDYMDOflb6dsNgwOyC6Tp3w2DAV5fke3fDYMD8Yfa8d8NgwElcLP53w2DA2QM4P3jDYMBFN/x/eMNgwMOOUMB4w2DAVjk6AHnDYMBRVWE/ecNgwIREAn55w2DA9gswvHnDYMAiAOX5ecNgwHQsPDd6w2DAX7UvdHrDYMAzIfywesNgwLYus+16w2DAb0c9KnvDYMAZzLRme8NgwJLIJaN7w2DAD0Go33vDYMAdFU8cfMNgwPlA/Vh8w2DAz4PFlXzDYMD2cuXSfMNgwKSwfRB9w2DACSKtTn3DYMBtf2+NfcNgwGbgrcx9w2DAFvXEDH7DYMCRIatNfsNgwIZe545+w2DA5sj8z37DYMCGsrQQf8NgwInJ4VB/w2DAaoGFkH/DYMAscSjPf8NgwIWkIAyAw2DAVWKpSIDDYMAZnRGFgMNgwKnsHL+Aw2DAdgfI+oDDYMA/vR88gcNgwDQomXqBw2DApht7uoHDYMAy5zz7gcNgwNcqOjyCw2DAfUAvfYLDYMBNLMe9gsNgwMYf/v2Cw2DAJIZCPYPDYMBIlWp7g8NgwCS5eLiDw2DASB8w9YPDYMBoUcQxhMNgwA6zYG6Ew2DAetBOq4TDYMDLQePohMNgwGsT+yaFw2DAMWArZoXDYMA+nMSlhcNgwCwPpeWFw2DA9C22JYbDYMB7DutlhsNgwMA2CKaGw2DAKcbz5YbDYMA4zYUlh8NgwECw9GSHw2DA57c+pIfDYMAToWTjh8NgwBR0ayKIw2DA7EhZYYjDYMAlSCWgiMNgwDJ13t6Iw2DAdWefHYnDYMC7dW1cicNgwEZPVpuJw2DASP9Z2onDYMD5F2oZisNgwFs1xViKw2DAse5smIrDYMDsSADYisNgwHq8XBeLw2DAgsFrVovDYMDaYj2Vi8NgwDmM0tOLw2DAh7elEYzDYMBWXtxOjMNgwOOeLIyMw2DAQl3fyYzDYMCCzDAIjcNgwL0bOUeNw2DAoPcBh43DYMBzXAXIjcNgwN5RtgqOw2DAwwK7TY7DYMBns7uQjsNgwM3iV9OOw2DAUcNOFY/DYMAls5xWj8NgwAlOqpKPw2DA3DeUz4/DYMAvjD0RkMNgwGwuyk2Qw2DAPPI+ipDDYMCHDNnGkMNgwKd38AORw2DAg60PQpHDYMDc3naBkcNgwCSDxcGRw2DAuMJfApLDYMAVQRhDksNgwBemuYOSw2DABUkoxJLDYMBIEPADk8NgwJLs4UKTw2DAwHQ7gZPDYMBqdZO/k8NgwJ0yE/6Tw2DAyKzpPJTDYMBanjl8lMNgwJS4TLyUw2DA3g8+/ZTDYMCERQ0/lcNgwJIDIIGVw2DAm3hHw5XDYMBWPFMFlsNgwKyxMEeWw2DA0O2YiJbDYMBPuhvJlsNgwATeDgmXw2DAy6izSJfDYMBpxRuIl8NgwKLFb8eXw2DAx5XHBpjDYMCl70BGmMNgwFcjC4aYw2DAydQ9xpjDYMCUBJkGmcNgwEXmF0eZw2DAbl2th5nDYMCs2mPImcNgwHPIIwmaw2DAAqnMSZrDYMDh0m6KmsNgwJX1JMuaw2DAiXXzC5vDYMBvDOVMm8NgwGc+/I2bw2DAF2I8z5vDYMB5Y7wQnMNgwH/UXlKcw2DA6ngTlJzDYMBONdbVnMNgwM4Elhedw2DAP2xEWZ3DYMCG/MiancNgwDK3R9ydw2DArpGmHZ7DYMDKn8NensNgwNeYfp+ew2DAdPrY357DYMDR59Qfn8NgwEA/pV+fw2DA7jXunp/DYMB507Tdn8NgwDMUpxygw2DAGhEaXKDDYMDbnnicoMNgwGkYnN2gw2DAliLUH6HDYMCvlm9jocNgwPfGi6ihw2DAVB6H7qHDYMDPOeM0osNgwKNlSXuiw2DAHcZswaLDYMA6jDoHo8NgwKCvJUyjw2DALauLj6PDYMB0wlTSo8NgwNkc4Yykw2DAuv8GVqTDYMAxRjOXpMNgwCyWLNikw2DAeUIcGaXDYMDRYEZapcNgwGq3npulw2DAKzQS3aXDYMBiPsUepsNgwIYoq2Cmw2DAXJ/LoqbDYMDRCzXlpsNgwBiT+yenw2DAQv/naqfDYMCFt+utp8NgwGgN/fCnw2DAK0kFNKjDYMDUfAh3qMNgwIJC87mow2DANVmV/KjDYMCWuB4/qcNgwKYkwIGpw2DABGyFxKnDYMBOz4YHqsNgwOm20Uqqw2DA37R1jqrDYMCSVnPSqsNgwHvT8xarw2DAIT2cW6vDYMC5klOgq8NgwLA0EuWrw2DA7aPEKazDYMBx0ElurMNgwMuTkLKsw2DAEXOS9qzDYMAwOV46rcNgwMsP+H2tw2DATEJlwa3DYMCgArUErsNgwGqF6Eeuw2DAg+cVi67DYMDgI0vOrsNgwEuFohGvw2DA3v4wVa/DYMCM7/yYr8NgwJ5vIt2vw2DAsL6cIbDDYMD66XZmsMNgwJa26Kuww2DAneU18bDDYMC/4243scNgwP166H2xw2DAL5jCxLHDYMDO7eELssNgwO3zR1Oyw2DAucQYm7LDYMDwYL/issNgwLvz0ymzw2DAZFi/cLPDYMCZPM+2s8NgwPZoQfyzw2DA8o5YPbTDYMCS7Nx/tMNgwFpT78a0w2DAKEiFCbXDYMBqFQNMtcNgwB4pp461w2DAjZuV0bXDYMCtpxMVtsNgwKE9Y1m2w2DAqQpfnrbDYMC1lgfktsNgwN/yYiq3w2DA7umCcbfDYMBCDhu5t8NgwMiRRQG4w2DAwIIASrjDYMCu4+KSuMNgwAjN6tu4w2DA8hfzJLnDYMBPG8BtucNgwP8aYLa5w2DAfqqY/rnDYMALfVJGusNgwCF4ho26w2DA2fZM1LrDYMD9zYkau8NgwJDAcmC7w2DAfvb/pbvDYMA77D7ru8NgwMd5VDC8w2DAuNpPdbzDYMAemVG6vMNgwF47Zf+8w2DARLqnRL3DYMCiEDSKvcNgwK4ZINC9w2DArYBjFr7DYMBTQBxdvsNgwDyjpaS+w2DA3F3r7L7DYMCmMAk2v8NgwINkBoC/w2DA1B3Kyr/DYMCPoHoWwMNgwJKC62LAw2DASqVdq8DDYMDz4Bb8wMNgwCHjT0jBw2DAr0IRlMHDYMBLUBDfwcNgwLh/CynCw2DA2i0FcsLDYMBB+A66wsNgwHx1bgHDw2DA7y8vSMPDYMBGaGuOw8NgwO+CVNTDw2DAm1f5GcTDYMBtEaBfxMNgwP3xVaXEw2DAXxUc68TDYMD8iyExxcNgwEYZZHfFw2DAhjAUvsXDYMBUPRoFxsNgwLaVakzGw2DANktslMbDYMCoSB/dxsNgwCotwCbHw2DA6bwMccfDYMDqAxa8x8NgwJJm/AfIw2DAXzcdVcjDYMBo+CmiyMNgwPOQ0e7Iw2DA82l5OsnDYMDoHkWFycNgwB0RAc/Jw2DAL7LjFsrDYMB2npdcysNgwMzVpKHKw2DAlKmZ5srDYMB1b+ory8NgwLSv8XHLw2DAISTvuMvDYMDPyocBzMNgwJLX3UzMw2DAZhF3mczDYMAbjenmzMNgwEUi9TTNw2DAH7hfg83DYMA449HRzcNgwMLgxh/Ow2DAV7YLbc7DYMAGpXi5zsNgwDRTXgXPw2DA/oecUM/DYMCLETibz8NgwG9YSuXPw2DA0ArnLtDDYMB2HiZ40MNgwDG8IcHQw2DAxof1CdHDYMANdrRS0cNgwKfKfZvRw2DA1KZl5NHDYMA9TH8t0sNgwLRA7XbSw2DAfTKvwNLDYMBucLsK08NgwEJHJ1XTw2DAQqb+n9PDYMBNqRXr08NgwPKGcTbUw2DAYzEZgtTDYMBDffDN1MNgwFiD7RnVw2DAhPb4ZdXDYMDAXASy1cNgwEQ9B/7Vw2DAdWDzSdbDYMC6HsuV1sNgwPHacOHWw2DAPwDjLNfDYMBUFSl418NgwHjSQcPXw2DAAnY0DtjDYMD34PpY2MNgwN2/lqPYw2DAq0QO7tjDYMD+5IQ42cNgwLBeFIPZw2DA+G/IzdnDYMAd4poY2sNgwNYx5Crdw2DAWYjhrtrDYMDs+qX62sNgwLIHZ0bbw2DAoplDktvDYMAKySDe28NgwJCP9Cncw2DAJeCuddzDYMDO1E7B3MNgwEx01Qzdw2DAEiYNWN3DYMDqlemi3cNgwMYIXe3dw2DAe3J8N97DYMAzJVmB3sNgwMJpscrew2DAg1BeE9/DYMBjcxFc38NgwMWjM6Xfw2DA9UXb7t/DYMB5/S054MNgwNtxMoTgw2DAFR6W0ODDYMAS8Rge4cNgwMJNTGzhw2DAyFdjuuHDYMDxnfkH4sNgwPbA01Tiw2DA14fzoOLDYMC+f+jr4sNgwPmkJTTjw2DAJB7Ge+PDYMDsmj7D48NgwDYWEAvkw2DAs+SOU+TDYMDR/eWc5MNgwEfkbufkw2DA5vUrNeXDYMB/v9SD5cNgwEFYy9Llw2DAleeYIebDYMCcmsdv5sNgwJrMAL3mw2DA72TJCOfDYMAazINS58NgwHuBaZrnw2DAKcbu4efDYMDZfG8p6MNgwGb5a3How2DArbvvuejDYMAbp6UD6cNgwN8IkU/pw2DANgLbnOnDYMCk78jq6cNgwNphBDnqw2DAY+A+h+rDYMBT6QbV6sNgwL3iPCLrw2DAqLR5buvDYMCq61e568NgwIY8dgPsw2DARJtZTOzDYMA/3lyU7MNgwOBTqdvsw2DAc6h0Iu3DYMBB811o7cNgwMnJyq3tw2DAz6vh8+3DYMBWyUI77sNgwIcPCITuw2DAQWKWzu7DYMDKWOAa78NgwPWRWmnvw2DAE9kAu+/DYMA7sS4N8MNgwKw7Zl/ww2DAJYrWsPDDYMDSR3YB8cNgwH/qZFDxw2DA/Z6NnPHDYMA5/fnl8cNgwL+pZC3yw2DAikHkc/LDYMAEx8m58sNgwCG4iP/yw2DAYuJ9RfPDYMDaPoSM88NgwOOzItXzw2DAjVduHvTDYMCVLaVo9MNgwHB1LLP0w2DAZk40/vTDYMCyintJ9cNgwPwYspT1w2DARKu23/XDYMD/MYUq9sNgwBVKD3X2w2DA59xXv/bDYMDk31wJ98NgwEL1HFP3w2DAUT14nPfDYMBDG2/l98NgwHq3Ny74w2DAh4EZd/jDYMD+Yj7A+MNgwFn9rAn5w2DAFWdzU/nDYMCZv7md+cNgwDRUzOj5w2DA2nQ4NPrDYMDCoLN/+sNgwJSwHMv6w2DAO60pFvvDYMDqFulg+8NgwC/lKqv7w2DA7Fpz9PvDYMBn4zU9/MNgwBdomIX8w2DANtiwzfzDYMCtAacV/cNgwEirll39w2DAXxikpf3DYMANORHu/cNgwPDxzjb+w2DAE1LHf/7DYMBAC9/I/sNgwAeMMhL/w2DAxiesW//DYMAMxDyl/8NgwC7qz+7/w2DA1uJZOADEYMAd+BCCAMRgwO3L78sAxGDAUAnyFQHEYMC+ohFgAcRgwO3anacBxGDAth/S7wHEYMBUDEg/AsRgwOPin4kCxGDA+ae20wLEYMAR1WIdA8RgwNXIhmYDxGDA/UdOrwPEYMCEU1H3A8RgwESFtz4ExGDAS222hQTEYMBMRVTMBMRgwLgPwBIFxGDACtsPWQXEYMCulGefBcRgwB15teUFxGDAXfkVLAbEYMCu9+5yBsRgwHI1XboGxGDAEzRlAgfEYMDY0HNLB8RgwOwA/5QHxGDA1Xuq3wfEYMAsrjgrCMRgwHstDHcIxGDAFgeiwgjEYMC3QKkNCcRgwASJ+FcJxGDAp0NmoQnEYMC0RTnpCcRgwIvJTi8KxGDAt8F/dArEYMBkal+5CsRgwDtnRf4KxGDArd96QwvEYMAXqwuJC8RgwIehrM8LxGDA9PUZGAzEYMCNnS9hDMRgwMIBYKoMxGDAM4Wb8wzEYMDyzYo8DcRgwJ65IoUNxGDASYT4zA3EYMCYCxITDsRgwFeajFgOxGDApw2snQ7EYMA+RLDiDsRgwAbVxycPxGDA9X0MbQ/EYMDy8d+yD8RgwKiZhfkPxGDAWCPaQBDEYMCXGG6IEMRgwCrfKtAQxGDA123oFxHEYMBLLJVfEcRgwA9B/KYRxGDAYJ/z7RHEYMDe7300EsRgwPjTq3oSxGDAqi+dwBLEYMCf0EIGE8RgwP9XtksTxGDA5f4BkRPEYMDQQEPWE8RgwG8PhhsUxGDAwnW1YBTEYMB48NulFMRgwGuo/+oUxGDALK8uMBXEYMDuhXp1FcRgwFZbtboVxGDAbYj0/xXEYMDMSpJFFsRgwDSGnIsWxGDAHyw80hbEYMDHSUoZF8RgwB0nxmAXxGDAyAkbqRfEYMBtdBTyF8RgwEyl+ToYxGDAOkuWgxjEYMAgrYvLGMRgwKLz5BIZxGDAhOZUWRnEYMCBSKueGcRgwJBId+IZxGDAHL+9JRrEYMAjiJFoGsRgwPZqeasaxGDAtnxt7hrEYMDNNLsxG8RgwP7aq3UbxGDA62fHuhvEYMDotmIAHMRgwGtOXEYcxGDABemVjBzEYMAL9f7SHMRgwMVKihkdxGDACtPQXx3EYMAeHralHcRgwDRPj+sdxGDAD/iBMR7EYMBXhKF3HsRgwHi+8r0exGDAlNNkBB/EYMCfcDZLH8RgwJN6oZIfxGDA9UcC2h/EYMCwOx8hIMRgwJLj02cgxGDApmztrSDEYMCOoGLzIMRgwFp0BzghxGDAW4ZleyHEYMD+6zW+IcRgwEWNrgAixGDAd5UYQyLEYMDkjaSFIsRgwFPZacgixGDAq3+5CyPEYMDDo+BPI8RgwIklq5QjxGDADOzq2SPEYMA2gYcfJMRgwMWLaGUkxGDAtxqGqyTEYMBobbDxJMRgwLl8tDclxGDAJCmefSXEYMAEOHfDJcRgwDGbOQkmxGDAvILcTibEYMAioFyUJsRgwJGmu9kmxGDAa2P8HifEYMBBnCBkJ8RgwOz9E6knxGDA/1/n7SfEYMBA2o4vKMRgwEajOnMoxGDAX0V+uyjEYMCFdrP/KMRgwPfXxEMpxGDAZqfVhynEYMBZmejLKcRgwKODBRAqxGDAPuM2VCrEYMBEun6YKsRgwPc1Bt0qxGDARzvHISvEYMCU9m5mK8RgwP565aorxGDA37gi7yvEYMDEjxQzLMRgwKbh13YsxGDAG+sHuizEYMDMGqn8LMRgwLplaj8txGDAuodygi3EYMAqJwTGLcRgwKkXFAouxGDADMPPTi7EYMAtKJWULsRgwKMFZ9suxGDA+eaZIi/EYMAKbOZpL8RgwJ7PELEvxGDADVn19y/EYMDXvnM+MMRgwEDrLYQwxGDAUOCnyDDEYMBMzaoMMcRgwNuEWVAxxGDA1tTLkzHEYMDcVDHXMcRgwOl0mBoyxGDAs3JYXjLEYMAiN36iMsRgwACh5+YyxGDAVU+KKzPEYMDZBFdwM8RgwHwPOLUzxGDAyqEg+jPEYMCnKgM/NMRgwPb6zYM0xGDAiOdqyDTEYMDs2NYMNcRgwGeDBVE1xGDAQMgmlTXEYMCJGnLYNcRgwPwFshs2xGDAd/2WXjbEYMAF9zOhNsRgwPg5n+M2xGDAXrbiJTfEYMAjrRBoN8RgwIrePKo3xGDAyahw7DfEYMBiNKguOMRgwEbt/XA4xGDA4t+RszjEYMBcL3f2OMRgwGJ0ozk5xGDAY1gQfTnEYMBvR9jAOcRgwJ6jKwU6xGDADArQSTrEYMBGLEuOOsRgwEvba9I6xGDAR002FjvEYMBSECYiO8RgwMVCZ5w7xGDAEUMR3jvEYMDTMAgfPMRgwFLwVGA8xGDA+fZGojzEYMDIlxPlPMRgwCExCSk9xGDAY10Lbj3EYMDRQle1PcRgwCZHUv49xGDAB/+QRz7EYMAUgaqQPsRgwOv7G9k+xGDA70yGID/EYMBgPLlmP8RgwMuQ6ao/xGDAOC537D/EYMBpJg0tQMRgwEgk32xAxGDAQuVHrEDEYMD6+q3rQMRgwIQlZitBxGDA0n4ebEHEYMBzivCtQcRgwMQ/lPBBxGDAuokcNELEYMDvdW94QsRgwG7AXb1CxGDA4YfWAkPEYMDOJNdIQ8RgwOjARY9DxGDA6V2q1UPEYMAK3MIbRMRgwP6hY2FExGDA9nBjpkTEYMAhv8/qRMRgwEuHGS5FxGDAmagocEXEYMB+RLixRcRgwIqfMPNFxGDA24HTNEbEYMABvcp2RsRgwPjIGrlGxGDAyYB+/EbEYMCUmUtBR8RgwGfiNIRHxGDA3JaJxkfEYMBA8DoRSMRgwHczHFZIxGDAV9eJmkjEYMC3Og3eSMRgwIBcGiBJxGDAKxSOYUnEYMCiBxSjScRgwENU7uRJxGDA1IpXJ0rEYMCfHo9qSsRgwMCf+q5KxGDAF0MZ9UrEYMBTb0g8S8RgwJ5K2YNLxGDA8Ldly0vEYMA/6aoSTMRgwNxfc1lMxGDALsJZn0zEYMD7GpzjTMRgwCngvCZNxGDAZJlPaU3EYMDCVIKrTcRgwB6ih+1NxGDAlJqLL07EYMAjq+BxTsRgwIoW57ROxGDAS0em+E7EYMB1Yn48T8RgwLJlXYBPxGDA0JkkxE/EYMBBZc0HUMRgwFQxQ0tQxGDAw4gSjlDEYMDG2WvQUMRgwHWY6BJRxGDAOQHTVVHEYMCUCDKZUcRgwCdTQd1RxGDAafsUIlLEYMBb7hBoUsRgwByXGa9SxGDAMkfG9lLEYMCBAcw+U8RgwDKxGIdTxGDA0DRxz1PEYMB3H6kXVMRgwOsXg19UxGDA593UplTEYMAw7qXtVMRgwAic4TNVxGDA2uKYeVXEYMB/rJe+VcRgwJymJwNWxGDAkIULR1bEYMDZ/1yKVsRgwIz4bs1WxGDAXe9mEFfEYMAc5mVTV8RgwK4QoJZXxGDAoeUB2lfEYMBlzQ4eWMRgwH0evGJYxGDA8ODRp1jEYMDFNiDtWMRgwAwmoDJZxGDA43E5eFnEYMAlz+29WcRgwPGEZgNaxGDA7PGPSFrEYMDmnMONWsRgwC9MY9NaxGDA2e9QGVvEYMDKX89fW8RgwG08saZbxGDAGIJt7lvEYMDEuQY3XMRgwLCBkn5cxGDAXS+1xlzEYMADoqoQXcRgwLi16FddxGDAHmcdnl3EYMDCnvfiXcRgwJTEHCZexGDAIsYEaF7EYMCMw2epXsRgwHQXi+pexGDA5/HDK1/EYMCLWUptX8RgwIprna9fxGDAGszp8l/EYMBpZHs3YMRgwA2rsnxgxGDA2FDWwmDEYMDutpEJYcRgwFvi7FBhxGDA/VS2mGHEYMC7zvLeYcRgwCrvuSZixGDAYyo/cWLEYMBHuna5YsRgwBeYggFjxGDAGnxRSWPEYMAYCteQY8RgwI8W7NdjxGDAzYuqHmTEYMAqdgNlZMRgwFbN+KpkxGDAoXqc8GTEYMAQofM1ZcRgwBwuBntlxGDASjX1v2XEYMA+7b4EZsRgwOWZkUlmxGDA4GeNjmbEYMD4H8DTZsRgwDIlQxlnxGDA4jcFX2fEYMDe2FulZ8RgwC8wWOxnxGDA9QSKM2jEYMD99Qt7aMRgwPVMxsJoxGDAdhi/CmnEYMB4OeBSacRgwHJd95ppxGDAXMjy4mnEYMC8TAErasRgwLBzJnNqxGDAoqJiu2rEYMBBBawDa8RgwNQC8UtrxGDAXb5klGvEYMC3cgPda8RgwDO3XyVsxGDAJPFjbWzEYMB6fNi0bMRgwB91tPtsxGDAC4L6QW3EYMAjvYmEbcRgwGBbBcptxGDA6GJyEG7EYMC8WKpUbsRgwNH8DJluxGDAA6/T3W7EYMDuCCgjb8RgwA1RUWlvxGDAScRbsG/EYMA6uGT4b8RgwMwaYEFwxGDAv3w9i3DEYMCrFf7VcMRgwHDFYCFxxGDApdxubXHEYMBiUze6ccRgwHEZJwdyxGDAQu/HU3LEYMBBIeCfcsRgwMF4MOtyxGDAyMxFNXPEYMCoyMd+c8RgwL+i7cVzxGDAPk5JDHTEYMCF7H1RdMRgwCgl6Jd0xGDA9pW43XTEYMDLVtkjdcRgwA+XlGp1xGDA3xqosnXEYMAWAx38dcRgwM4ZT0Z2xGDA6Z0xkXbEYMC7gk/cdsRgwHNFqSd3xGDAJ3JYc3fEYMBcKSa/d8RgwAe10wp4xGDADV09VnjEYMA5gL+heMRgwLmQze94xGDA9TlMPHnEYMAYMp+GecRgwCLjVdB5xGDAHrr+GXrEYMCFilFjesRgwGzzMK16xGDAYpMF93rEYMDsqNZAe8RgwOkIsYp7xGDAiLSc1HvEYMD938QffMRgwJt9zml8xGDAeYA7s3zEYMD1tGv8fMRgwMcZz0V9xGDAzfvvi33EYMBOm5rUfcRgwEYOLBt+xGDALlPvYX7EYMAEkmSpfsRgwJGBffF+xGDAtx3BOn/EYMAsEuaEf8RgwMp5YtF/xGDAtAP1H4DEYMDi0T1vgMRgwBSxUr+AxGDAqyCsD4HEYMAR5wBggcRgwJb7Qq+BxGDADxye/YHEYMCqPilKgsRgwHt1i5WCxGDAwQxJ34LEYMDxyRoog8RgwPZ3jnCDxGDAiX36uIPEYMC323AChMRgwCuKgk2ExGDASHtgmITEYMDH6jjkhMRgwJ5PbDCFxGDAVTaJfIXEYMC0m2/IhcRgwFIDdBSGxGDAwPQtYIbEYMCG88OqhsRgwL5LtvWGxGDAfiQNP4fEYMC8d3SHh8RgwHBbldSHxGDA5jXGHojEYMDq25loiMRgwAdOMbOIxGDA4RMU/ojEYMAgnndIicRgwPISC5OJxGDAHZhS5YnEYMA3MLkyisRgwIsHDIGKxGDANV2z0YrEYMAKnW0gi8RgwPo45m+LxGDAe6JgwIvEYMD+AZ8QjMRgwBtQ+F+MxGDAD1hsrozEYMCBCJL8jMRgwKztQUqNxGDAGAedl43EYMDoPQfijcRgwDb+1C2OxGDAHvzgd47EYMA69i2/jsRgwMrIegePxGDA2esjUI/EYMCZuUaYj8RgwFkfQOGPxGDA65ccKpDEYMDXujF0kMRgwLddkb+QxGDAMcdhDJHEYMDNellakcRgwCdq96iRxGDAtgDr95HEYMBZM6FHksRgwFtk+peSxGDAQRYv6JLEYMDgyZc3k8RgwBBaANSWxGDAexixHZfEYMDzCNgklMRgwLHClXKUxGDAzUb7vZTEYMDzCO0IlcRgwBHUtlKVxGDA2v6Qm5XEYMAn0PfjlcRgwD1PZCuWxGDAeeRZcpbEYMDOgtu5lsRgwGAlqgGXxGDAadPzSpfEYMCqVc2Tl8RgwCcSWd6XxGDAEiHXKJjEYMBQAFZ1mMRgwK3Ok8KYxGDAe7iKD5nEYMAgrZFcmcRgwDgcLaqZxGDA4vh4+ZnEYMBaauVJmsRgwAzT+JmaxGDAahi+6JrEYMBlwm03m8RgwL+PFYabxGDAYTZc1JvEYMC8w7oinMRgwPzqnXKcxGDA22dhvpzEYMDCnxAKncRgwOE9bFWdxGDA140onp3EYMAvIDrpncRgwMhuAzSexGDASEZWfp7EYMDu/cPHnsRgwEXDpxGfxGDAbgG9W5/EYMA8zgCmn8RgwMGsd/CfxGDA1fiAO6DEYMDx6f6HoMRgwHsH8dWgxGDAFo1ZI6HEYMAZAXVzocRgwPcoBMOhxGDAsYHaEqLEYMBQnT1josRgwMs+JbKixGDAWYPrAKPEYMAMPI5Po8RgwOv1UJyjxGDAZnaK5qPEYMAkLGIxpMRgwJ8vwXikxGDAuxr8wKTEYMC09LUFpcRgwAlMekilxGDAPpZikKXEYMAvXsvXpcRgwNjRQB+mxGDAdlU2Z6bEYMBFJMSvpsRgwN3LuPmmxGDAH0c2RafEYMD5uM2Qp8RgwLmYld2nxGDA3D7PK6jEYMCDACN7qMRgwKyQBMuoxGDAg14lGqnEYMBCoUhpqcRgwDbwUbipxGDAyEI6CKrEYMBTlnVVqsRgwPx105+qxGDAJZkN66rEYMCn/kc3q8RgwDXdY4KrxGDAcb7kzavEYMBKl9UZrMRgwB9I6GWsxGDADZBqsqzEYMD/LhIArcRgwITHe0ytxGDAVeJpma3EYMBLe/vkrcRgwMa6rC+uxGDAp4MUe67EYMCqa0LGrsRgwKiR7Q+vxGDAh/wHWa/EYMC8+WCjr8RgwEjA+u+vxGDAH7hsOrDEYMCBbaiEsMRgwGwHu9CwxGDAII1yHbHEYMCrswFpscRgwGdFSrGxxGDAmaXW+7HEYMDmTW5FssRgwB88to+yxGDACOOP2bLEYMDx++ges8RgwF9xZGezxGDAPF+TsLPEYMAPzJf6s8RgwOPV0UW0xGDA5Wzck7TEYMCDMyHitMRgwFbxVjC1xGDAqGYKfrXEYMA1QCbNtcRgwKmIRhq2xGDAFtsMZbbEYMB8PB6ttsRgwLOhcfW2xGDA3f2iPLfEYMDfUXuDt8RgwD/b58m3xGDAxX05ELjEYMBPWKtWuMRgwKEm5524xGDA79nZ5bjEYMBZ/F4uucRgwDufvXW5xGDAsfTDvrnEYMCj0zsLusRgwFAI31W6xGDA//+9oLrEYMAfPtHrusRgwO7LLje7xGDAfBzIgrvEYMDaxYfOu8RgwOaaVhq8xGDA2JITZrzEYMD8FuOxvMRgwPEJp/28xGDAK7bgSL3EYMAEEIOTvcRgwDIVXN29xGDAbHtaJr7EYMBmoXhuvsRgwP2xjrW+xGDAcMGZ+77EYMDZnhpBv8RgwH2PT4a/xGDAiUR7y7/EYMDeXtAQwMRgwBYeflbAxGDAI1bMnMDEYMD8QNPjwMRgwN8FoCvBxGDAvWohdMHEYMC8oVu9wcRgwBr+NgfCxGDAfxS2UcLEYMBsgLWcwsRgwEVZJOjCxGDA9kS5M8PEYMB04y9/w8RgwIQeWsrDxGDAI6v5FMTEYMBMQ/NexMRgwHkHE6jExGDAgFc78MTEYMDps3Y3xcRgwMqK3H3FxGDA4tt5w8XEYMAGD18IxsRgwJwirkzGxGDA+4OGkMbEYMAWdhXUxsRgwGSrfRfHxGDA4lzwWsfEYMBPpZuex8RgwKMA7OLHxGDA64kPKMjEYMCqyz9uyMRgwB9S+bPIxGDAudeL+sjEYMB8X9NBycRgwOl7W4rJxGDAqVak08nEYMA+X5kdysRgwIkjemjKxGDA9J3btMrEYMA6/L4By8RgwOcTT07LxGDA+Tb9mcvEYMBGPWjky8RgwO/7gS3MxGDA26n0dMzEYMAivQq6zMRgwBajNf3MxGDABZSmP83EYMDWB5OBzcRgwDMAcsPNxGDAWgzHBc7EYMBe8fNIzsRgwNaql43OxGDAjevr087EYMDqrHUbz8RgwA9K/mPPxGDA/4DBrM/EYMBTNYP1z8RgwIu/CD7QxGDAYlxLhtDEYMCyjgXO0MRgwAhiKxXRxGDAq7C8W9HEYMBPBPuh0cRgwIPCFOjRxGDALWYbLtLEYMAkQ/dy0sRgwEeUOrfSxGDARFy2/NLEYMDN3eBB08RgwHE4RIfTxGDAMRe1zNPEYMAijtES1MRgwGzgZ1nUxGDAgx/bn9TEYMAX1Mfm1MRgwAjZgC3VxGDAGCZfc9XEYMBFDNa41cRgwNXsz/3VxGDA/sJ+QdbEYMDHwH2D1sRgwEOAdMTWxGDAiFhYBdfEYMC2iZBF18RgwPGNToXXxGDASLrcxdfEYMCW4+gF2MRgwECR7EfYxGDAbCFTitjEYMCymsTN2MRgwOl9/RHZxGDAcl6JVtnEYMDxOlub2cRgwHfKIOHZxGDAh4/NJtrEYMBC8GZs2sRgwG/ljrHaxGDApN8s9trEYMBtP58528RgwMr+S33bxGDAGRuUwNvEYMBfkqwC3MRgwJwbdUTcxGDAVIWrhdzEYMCsNgLH3MRgwDtVoQjdxGDAAjiQSt3EYMB/UcOM3cRgwBHkJtDdxGDAWeWuE97EYMD8+Y5W3sRgwMftUJrexGDAybuC3d7EYMAqmiQg38RgwO2pLmLfxGDAVmV+o9/EYMCI3FXk38RgwMgN2iXgxGDAjEPtZuDEYMByFTep4MRgwI1t+uzgxGDAFiutMeHEYMDXnsJ24cRgwMuzeb7hxGDAZEZwCeLEYMAHR0RR4sRgwCwtBpjixGDAoL1c3eLEYMBG4Ych48RgwHNi9GHjxGDAnkfkn+PEYMAzMt/c48RgwO/MWxnkxGDAyqftVeTEYMDYzPqS5MRgwCTOn9DkxGDAYuzZEOXEYMDBUntT5cRgwEVbpJblxGDAaVMF2uXEYMA6TzEd5sRgwLg6CWDmxGDA+CEWoubEYMAugwLi5sRgwLgWWSDnxGDArJElXufEYMBY4Xec58RgwAiLz9vnxGDA/U1VHOjEYMBjNnhe6MRgwIovF6PoxGDAqQvT6ujEYMCgiLYz6cRgwFNqmHzpxGDAc2PRxOnEYMAle7kL6sRgwN7PDlHqxGDAYHzXk+rEYMDI+5vS6sRgwLmprQ/rxGDARM6nS+vEYMBB7waH68RgwCdvYsLrxGDAok0M/uvEYMCLrQs77MRgwCeY+XnsxGDAgWt6uuzEYMCKrsT77MRgwMGeUj7txGDAqB2oge3EYMA8RZnF7cRgwCro9AnuxGDAG2BcTu7EYMA/OsmS7sRgwMdJLtfuxGDAY6duG+/EYMDfUXBf78RgwLIuDqPvxGDA0X5M5u/EYMBzCfoo8MRgwNGfEWvwxGDAO6/JrPDEYMATnNrt8MRgwJiiWi7xxGDAU8xcbvHEYMAP8uWt8cRgwMyxHO3xxGDAJpb2K/LEYMAX+WJq8sRgwIktaqjyxGDA654t5vLEYMDl7Kcj88RgwI9fAGHzxGDAMtUNnvPEYMDiFAjb88RgwJS9dRj0xGDAHOtrVvTEYMAXViuV9MRgwCXRvdT0xGDATAItFfXEYMApXdhW9cRgwNEelZn1xGDA1xu/3PXEYMBQ+Cgg9sRgwDL5gWP2xGDAplmRpvbEYMDUNC/p9sRgwOrG9ir3xGDAJmHPa/fEYMCUn+Cr98RgwI/nZOv3xGDA4txPKvjEYMCAB8Zo+MRgwISU5Kb4xGDAhEPI5PjEYMBaF50i+cRgwJTza2D5xGDAGWJKnvnEYMDok03c+cRgwLx2jhr6xGDAts4WWfrEYMCk3vCX+sRgwGkAJdf6xGDA4FjHFvvEYMCfX9VW+8RgwFy2Xpf7xGDAlGBI2PvEYMD93YsZ/MRgwEslNFv8xGDAhkJWnfzEYMDo4pPf/MRgwF7MyiH9xGDAMzfoY/3EYMDhpcql/cRgwMYLduf9xGDAc8mrKP7EYMBQ4TNp/sRgwIsHeKn+xGDAwImh6f7EYMD8n8cp/8RgwGwSAmr/xGDA2IRNqv/EYMAS9OXq/8RgwNYq5ysAxWDAKf8KbQDFYMA11PmtAMVgwB/Ih+4AxWDAqOOWLgHFYMCq+xRuAcVgwGed9KwBxWDA+p3j6gHFYMB6HDooAsVgwP3wIGUCxWDALprXoQLFYMB7FGneAsVgwBphGxsDxWDA0lMJWAPFYMC3LSuVA8VgwK5DntIDxWDAGZdkEQTFYMD1bilRBMVgwMMkN5IExWDA2tF01ATFYMBPMgUVBcVgwLWd7lgFxWDAE361owXFYMBb2hbqBcVgwF07zS8GxWDANAiYdAbFYMBGzOS3BsVgwKVdw/kGxWDA6leeOAfFYMBtI051B8VgwPpZ+LAHxWDAONaZ6wfFYMAlL+AlCMVgwKckMWAIxWDAJgY+mwjFYMBGOdPWCMVgwGvsHhQJxWDAs9N4UgnFYMA8MD6SCcVgwOU8ONMJxWDA8TFyEgrFYMCz7V9UCsVgwGviQZ0KxWDAYIWs4grFYMATJjMoC8VgwI6SaW0LxWDAYIL6sQvFYMAptZL1C8VgwNqH8zcMxWDA61areAzFYMC1sDK3DMVgwIYbkPQMxWDA1Zk3MQ3FYMBM7kxtDcVgwJsGOqkNxWDATng55Q3FYMDFGdohDsVgwFFDe18OxWDAiIm3nQ7FYMCmBHbcDsVgwP8GixsPxWDAZZQBWw/FYMATT+OaD8VgwCDHxNoPxWDAA0+VGhDFYMDj7ahaEMVgwFLNJZsQxWDAer8c3BDFYMB4fYkdEcVgwKNbaF8RxWDAwmjeoRHFYMDCk/PkEcVgwA1zWSgSxWDAYiOwaxLFYMDK2syuEsVgwEzzd/ESxWDAfOqVMxPFYMC8Mtt0E8VgwCgYGrUTxWDAj6ac9BPFYMAEvGMzFMVgwIYZmHEUxWDAAu9TrxTFYMCX/rrsFMVgwPgF+SkVxWDALFFBZxXFYMAXpKSkFcVgwEvZN+IVxWDAZOwEIBbFYMA+GjJeFsVgwJn0zpwWxWDAiL3V2xbFYMDIrV8bF8VgwMVIO1sXxWDA5zX1mxfFYMDzxuLaF8VgwOXm7BsYxWDAFn/AYRjFYMDLS8akGMVgwILEpegYxWDAFpvfLBnFYMCtUypxGcVgwG8kM7UZxWDAGeLx+BnFYMBxVgs8GsVgwMD7jH4axWDAyVYkwBrFYMBg+r8AG8VgwLNIrUAbxWDA2b8UgBvFYMDWMBW/G8VgwAAQ0v0bxWDAI4pqPBzFYMAUChh7HMVgwI079LkcxWDA3c4d+RzFYMDnOow4HcVgwJ6oingdxWDAPDv4uB3FYMBNFuz5HcVgwLSWcDsexWDAYKOjfR7FYMD+ZTfAHsVgwFyoNwMfxWDA+SB3Rh/FYMBZheeJH8VgwPFXgM0fxWDA2df7ECDFYMDbBUpUIMVgwLJ1kZcgxWDArhLz2iDFYMBqfX0eIcVgwPUGKGIhxWDAjGuApSHFYMAysznpIcVgwMgdcC0ixWDAzNZqcSLFYMAO3tm0IsVgwIqbiPcixWDArMB/OSPFYMDo/oh6I8VgwFXKpLojxWDA3ef5+CPFYMCuprU2JMVgwL+ljXQkxWDA3BDjsiTFYMB0cRjyJMVgwPahITIlxWDATRK8cyXFYMAQmoC3JcVgwANFpvwlxWDAKm8XQibFYMDT/JKHJsVgwHHoyMwmxWDAc4+DESfFYMCAs05VJ8VgwFSzmpYnxWDAw2vr1ifFYMApcw8XKMVgwJbMYVcoxWDAC1QSmCjFYMDMxjHZKMVgwKJn2CcpxWDAm2EbYCnFYMBfC/mlKcVgwLPZAewpxWDAfbL+MSrFYMAdm5d3KsVgwHCWGL4qxWDAQsUSBCvFYMBtwoRGK8VgwPmIMocrxWDA+8JsxyvFYMA34Q4HLMVgwLoG+EUsxWDAhg7RhCzFYMDEhAbELMVgwDm+iQMtxWDAvxTxQy3FYMD+Dw6GLcVgwA+DNsktxWDA2Lo4Di7FYMD9DKxULsVgwA0Ti5wuxWDAGVio5i7FYMDqC9syL8VgwLWzUX8vxWDARV6Hyi/FYMD57gQVMMVgwNWopF0wxWDAjHfWpjDFYMBB+QPuMMVgwKYdnzExxWDAbEcOcjHFYMB9jlGxMcVgwLiSt+8xxWDAtLkLLjLFYMDeEvdsMsVgwDSkXK0yxWDAsxJ47zLFYMAHJF8yM8VgwBzG13UzxWDAMlgHujPFYMBkApX+M8VgwOs6nkI0xWDAJgCHhjTFYMAMtg/JNMVgwGDdfQw1xWDA1vqtUDXFYMBB5paVNcVgwJ2yYts1xWDAi57gITbFYMCGciNqNsVgwLXQZ7Q2xWDAHtAB/zbFYMAA929JN8VgwPu1pZY3xWDAgQe53zfFYMDpaDUnOMVgwDua1Ww4xWDAZtJMqzjFYMAQO8XtOMVgwBC8bC05xWDAGzjGbDnFYMADdJCsOcVgwHMucik7xWDA+dKJNDrFYMCnw3V2OsVgwJblab06xWDAHDqlBDvFYMDk7ktNO8VgwN2tuZU7xWDAwYx13jvFYMB+Wr4nPMVgwCQ9uXA8xWDALgQ8uTzFYMBZ9v4APcVgwClg+Ec9xWDAhobDkT3FYMAQ7MnYPcVgwOynKCA+xWDAUwUCZz7FYMDCA+6uPsVgwLiNsPU+xWDAN2JRPD/FYMCZAeuCP8VgwKZYrck/xWDAhIeIEEDFYMCsHlpXQMVgwNkaj55AxWDAts0g5kDFYMAXwJssQcVgwDER53FBxWDArg/+tUHFYMCAlXP5QcVgwDH8FztCxWDALMT9ekLFYMBsLiS7QsVgwBdQb/xCxWDAihAVP0PFYMALVtCDQ8VgwH+mjcpDxWDAT0gjFUTFYMCnb/NjRMVgwEV08LNExWDAg/3wA0XFYMAr61JTRcVgwJVetaFFxWDAODAD70XFYMCLIJ05RsVgwEn3MYFGxWDAXPZ8x0bFYMBQf3UMR8VgwBd38lBHxWDA9No3lUfFYMA1yiXZR8VgwB9BTR5IxWDAfFpTZEjFYMBKm8GqSMVgwNVvjfFIxWDA0j1nOEnFYMDHT3R/ScVgwPox1sZJxWDA2DGCDkrFYMAmjLJVSsVgwGooGZxKxWDAHOrN4krFYMAM2rYpS8VgwHrNJHFLxWDAblcJuUvFYMBWxt4BTMVgwOlKdEtMxWDATUTOlEzFYMB0SYfeTMVgwGL5EChNxWDA4BpycU3FYMA/3VO7TcVgwEyKvwROxWDAVhCSTk7FYMD90lGYTsVgwJz7bOFOxWDAcqohKk/FYMCWLttyT8VgwF/tQ7xPxWDAMQSUBFDFYMC5ewRMUMVgwN0Qa5NQxWDAZLqu2lDFYMB6Is8iUcVgwOz6OGtRxWDA94Hds1HFYMCADAj9UcVgwBBjN0dSxWDAD1X1kVLFYMC/po7cUsVgwErd5SZTxWDAOEz1cFPFYMByicG6U8VgwC/82ANUxWDAUIViS1TFYMDXnweSVMVgwHTyJ9lUxWDAwdS2IFXFYMA4u7JoVcVgwACUV7FVxWDA9VTp+VXFYMD4g5dDVsVgwAv2rI5WxWDAb+CL2lbFYMByUE8mV8VgwLqQz3FXxWDAkh35vFfFYMBXbZ4HWMVgwEJ9IlFYxWDAtR4umVjFYMBTLITgWMVgwAst6CZZxWDApW/Pa1nFYMBwXAawWcVgwOxOQPRZxWDAHlFkOFrFYMC57F58WsVgwEHHFsFaxWDA/m6GBlvFYMB1OMpMW8VgwDfKR5RbxWDAvUnb3FvFYMDQgZQmXMVgwB/kSXJcxWDAC/3xv1zFYMCRhCwOXcVgwAI1z1tdxWDAludoqV3FYMBtpWH2XcVgwFIbT0JexWDAw1BtjF7FYMANyezVXsVgwOW0dB9fxWDAnULHaF/FYMDOIuuxX8VgwFmeIvtfxWDAaN15RWDFYMBFsnuQYMVgwG6YRdxgxWDAvnFVKGHFYMDD881zYcVgwKYE7L1hxWDAcLgmB2LFYMBMUjVPYsVgwFt2n5VixWDArTq722LFYMA3ad4gY8VgwBWuaGZjxWDA1WgxrGPFYMAAFYnzY8VgwLgZjzxkxWDAp2I/h2TFYMAw07HTZMVgwFaQ/SBlxWDAONb8bmXFYMBKgz29ZcVgwDXASQtmxWDAR0qhWGbFYMAzjNukZsVgwBQX5u9mxWDAXL4uOmfFYMDhWSaDZ8VgwEhtF8tnxWDABICSEmjFYMByHgVZaMVgwO6avZ5oxWDAVzNi5GjFYMARhwUqacVgwPsHpG9pxWDAr7NYtWnFYMBcBaH6acVgwNRzAUBqxWDA4mCHhmrFYMCrCtzNasVgwF4ewBVrxWDASBY6XmvFYMC8w+Ona8VgwDNA1/FrxWDAwgNYPGzFYMD7CI6HbMVgwJSBwtJsxWDAY+6QHW3FYMBc02FobcVgwNbQD7NtxWDAC+LP/G3FYMDa171GbsVgwH/R+JBuxWDALYkw227FYMDNRQMjb8VgwBKA6mtvxWDAF/u2tm/FYMA6jtn+b8VgwFMOZEdwxWDAOgFvkHDFYMAvgo7XcMVgwDybcR9xxWDAcKP2aXHFYMBJ5HyzccVgwOtPqvxxxWDAdUTKRXLFYMDcXSyPcsVgwA/6MtlyxWDAIluJI3PFYMBDsOxtc8VgwLeDrLdzxWDA5gpV/3PFYMAdFblJdMVgwKAuCZN0xWDAVXZ72HTFYMCIgiYfdcVgwP28vGV1xWDAD0Ujq3XFYMDYip/wdcVgwB1yzjV2xWDAkJF5e3bFYMAhDATCdsVgwIAmwQl3xWDAuZs7UXfFYMASeEyYd8VgwOyb3N53xWDAp2jLJHjFYMBIVDxqeMVgwLO8Dq54xWDALBuw8XjFYMDh/+I2ecVgwOvC53p5xWDA9cimvnnFYMAVTG0DesVgwNC6xUl6xWDArVYgkXrFYMDUU5TZesVgwK5xwSJ7xWDARc3GbHvFYMCcFw+3e8VgwCCdUQF8xWDAOvbjS3zFYMD+KYuWfMVgwMYY/OB8xWDAAN23Kn3FYMCnsMl0fcVgwLI0j759xWDAV17oBn7FYMD/X5lNfsVgwCsrt5J+xWDAYVoH137FYMCc29Eaf8VgwB9PCF9/xWDAVsrCon/FYMBi9/rlf8VgwFAwKCmAxWDAaSg6bYDFYMDAL5OxgMVgwBVM//WAxWDANFJhO4HFYMCeaeOAgcVgwPo5TsaBxWDAqSp0C4LFYMC7EvRQgsVgwEa1V5aCxWDAu+Ak3ILFYMBFaYsig8VgwFGFIWmDxWDAijUisIPFYMAYySP3g8VgwKL5vz6ExWDAsK78hoTFYMAnOnzPhMVgwGOXbhiFxWDAm51EYIXFYMDQPwKohcVgwHvLVfCFxWDAkoZBOIbFYMBmsN1/hsVgwDcDNMaGxWDA9gmgDIfFYMAvoFBSh8VgwEUmUZeHxWDAYStE3IfFYMAo0dsgiMVgwKsrNWWIxWDA37s4qYjFYMAQKAHtiMVgwIYIyzCJxWDABJi1dInFYMDRy824icVgwMPtOP2JxWDAuSH2QYrFYMAFXTmHisVgwKrvA82KxWDAY1VFE4vFYMAmHSJai8VgwKs9Z6GLxWDA7NE56YvFYMBmVXUxjMVgwLkvtnmMxWDA7ruqwYzFYMD8GxoJjcVgwMhOFFCNxWDAdamRlo3FYMC+foHcjcVgwKPrwiGOxWDAI5rwZY7FYMCdPjGpjsVgwH+lWeuOxWDAsjDILI/FYMD3ishtj8VgwAoxWq6PxWDA9sZu7o/FYMBZ4DgukMVgwJVdZG6QxWDAYLGJr5DFYMBHv5DxkMVgwJg8jDSRxWDAGyVjeZHFYMASM2TAkcVgwILcMQmSxWDAr4+yUpLFYMB5xXycksVgwD0Q8OWSxWDA9t7dLpPFYMBe5Cx3k8VgwCZ6v72TxWDAI8uIApTFYMB4dlhGlMVgwBHTcomUxWDAC8MfzJTFYMC6TFQPlcVgwGatO1KVxWDA+9mUlJXFYMDykzbXlcVgwGXqDxuWxWDAQaymXpbFYMD1R8ChlsVgwHPx6eOWxWDA4eXKJZfFYMD/Sdtnl8VgwPxIZKmXxWDAGVBT6pfFYMBjkZ8smMVgwBov+W+YxWDAYz6FsJjFYMDQir/ymMVgwPcUADaZxWDAyvLifZnFYMBU/ZjCmcVgwFiStQiaxWDAJoU+T5rFYMAcLfGVmsVgwLrcZ9yaxWDAD9ohI5vFYMBiMOVpm8VgwK8Q36+bxWDAw4Lz+pvFYMCKsBxBnMVgwF/XPYWcxWDA8i+9y5zFYMBHA7ASncVgwI5eD1SdxWDAP+3MlJ3FYMC3pSPXncVgwJFdjBqexWDArKdpXJ7FYMD4U8ednsVgwCP0FuCexWDA83wVIp/FYMDLBqVln8VgwG2F36ifxWDALcFN7Z/FYMBXpoIzoMVgwDkBSXigxWDAiufdvaDFYMDNXUEEocVgwBzpr0qhxWDArMKJkKHFYMCVh0DVocVgwOsuUxqixWDAX+4gX6LFYMB6ArSjosVgwL1ljueixWDA+1rsKqPFYMADIbdto8VgwLWYSLCjxWDAR/Rs8qPFYMD3XWw0pMVgwNekUHakxWDAIIpDuKTFYMAtRUz6pMVgwLg+qjylxWDAcvynfqXFYMAFm0fBpcVgwGcITASmxWDAFTjdR6bFYMD2+KOLpsVgwLiQZs+mxWDAr0FIE6fFYMB846ExpsVgwM0VjZ2nxWDACKxz46fFYMDo+1wpqMVgwHfi0j2nxWDAqYVagafFYMDZBff8qMVgwPetdUKpxWDACpfMhqnFYMCfeL7LqcVgwBmJnt6oxWDAx9ukJ6nFYMDV+6twqcVgwC9FpNuqxWDAJn9D/6nFYMBPr9VEqsVgwK7AU6GrxWDAhtw1y6rFYMBkttYKq8VgwP2FqUmrxWDAFwd4h6vFYMA9q1L0rMVgwI2QpgesxWDAMqdsSKzFYMAPDLWKrMVgwAtdmM6sxWDAsclpE63FYMCNe8VYrcVgwB+z8p2txWDAMlKwBa/FYMDDTRRHr8VgwKYMAoevxWDAxaE8x6/FYMDFnHIIsMVgwFzsNkqwxWDAp9azjLDFYMDn//Kur8VgwC6aYBSxxWDA8D6tWbHFYMC79SmfscVgwCnBzuSxxWDAi4f1KbLFYMDETHRussVgwLh4DbGyxWDAe+UV87LFYMDX62Y0s8VgwMEf1HSzxWDABkjzs7PFYMBiyZTxs8VgwElLZy60xWDA820EarTFYMDIeTKltMVgwNPK9uG0xWDAfyDRHrXFYMCosStbtcVgwIEtLpi1xWDAnWQB1rXFYMDcVrUVtsVgwHYNb1e2xWDACu2VmrbFYMDfVG7ftsVgwOxlUia3xWDAlwyXbrfFYMAX5H63t8VgwA38TQG4xWDARQmuSbjFYMBRyIaQuMVgwEQ6Cde4xWDAJHvaG7nFYMAHUhdcucVgwGFEVZu5xWDAx+Jh2bnFYMBOMOQWusVgwFJ/GlS6xWDAw2yPkbrFYMCv6QbQusVgwDxEFQ+7xWDAok/RTrvFYMDTnM2Qu8VgwEkO4dK7xWDAwdjRFbzFYMDo4yxZvMVgwHW8m528xWDAiQZc4rzFYMBFAC0mvcVgwHPzsGm9xWDAvYG0rb3FYMCvTJ/xvcVgwM2fLjW+xWDA8NHZd77FYMB8MLm5vsVgwGXup/u+xWDABBZHOL/FYMDGLSR6v8VgwOBoILq/xWDA1D1j+b/FYMCyVWs6wMVgwCYl433AxWDAtO/qwsDFYMCxmwYIwcVgwBvi8EzBxWDAqOB6kcHFYMCmHvrVwcVgwLpKkRrCxWDA3i2xYMLFYMA/2jijwsVgwAg+hubCxWDAPPa2KMPFYMAuE05rw8VgwKMPTq7DxWDAWXkm8sPFYMC5Mak3xMVgwNkmOH3ExWDAu/r5wsTFYMBCkykIxcVgwJhg1EzFxWDAaAVQkMXFYMDGUujTxcVgwD+07hXGxWDAbV+XUsbFYMCoOO2OxsVgwJZSCs/GxWDAiAnmD8fFYMAb/ZtQx8VgwOuvMpbHxWDAZ3vT1cfFYMBXhuMZyMVgwPIGdF3IxWDAv8mDosjFYMBSZoPnyMVgwBP+qCzJxWDAem9zb8nFYMBs1/yvycVgwFMPxfHJxWDAkmdKNcrFYMAPd0h5ysVgwOvuUxXKxWDA1e6pAcvFYMAW8fBJy8VgwPh8N4zLxWDASK/pz8vFYMAtd2EUzMVgwCcHRFrMxWDABuQlnczFYMB/T2TgzMVgwIINBSPNxWDAR8Chac3FYMCuwtmszcVgwMKb3O3NxWDA78jFL87FYMBqdN5yzsVgwBgEibXOxWDA7kyz987FYMBKZi47z8VgwIflSX/PxWDAmShaws/FYMDgQce7z8VgwJqTLAXQxWDAqfx3jtDFYMAI3PDR0MVgwC4CvxTRxWDA5OnMV9HFYMDpBgqb0cVgwAr9MN/RxWDADGptI9LFYMDPmrxn0sVgwKj9mqzSxWDA1SDT8dLFYMAhlbU308VgwGOASn7TxWDAh/1lxdPFYMDXV84M1MVgwLiYzVPUxWDAdum8mtTFYMAwe5zg1MVgwGtA9yXVxWDABD6Ja9XFYMBiWp2w1cVgwOvie/XVxWDAoMkPOtbFYMB2eEh+1sVgwCnXdcLWxWDAFfvpBtfFYMB9F1tL18VgwFRFcI/XxWDAzR3f0tfFYMCx8t0V2MVgwObGeVjYxWDAHskRmtjFYMAEeLXa2MVgwPT3IRvZxWDAJyoTXNnFYMACg3md2cVgwDUOcN/ZxWDAXmLAItrFYMAvDYnM2sVgwBHmhqnaxWDANj4E8drFYMBXnTk328VgwOkEhX3bxWDA8aduw9vFYMA/MYsG3MVgwHFnb8LcxWDAXy6sjtzFYMAenVXV3MVgwHKUEBndxWDAi/Y1Xd3FYMDqOt+g3cVgwIAvTeTdxWDAuV3yJ97FYMDv2eQA38VgwLVXIErfxWDArDUzlN/FYMDXs8zb38VgwNhAC27fxWDAkDRurt/FYMCD8xrv38VgwG359jDgxWDAkbVjceDFYMCFK+Ox4MVgwPBcf/DgxWDAs9ycM+HFYMC1vtx14cVgwM4Y5rjhxWDAgFYZ/uHFYMCKkDNE4sVgwEyCBYnixWDAX6w90eLFYMCYEGAU48VgwGqF+FfjxWDAx24znePFYMBC81Pg48VgwGnMcSLkxWDA7DsJZOTFYMCO3zOl5MVgwN2UOebkxWDAiv+MJ+XFYMAoIOJo5cVgwFxCN6rlxWDA4JOx7eXFYMCkNJ8x5sVgwMTKCnbmxWDAbrM/uubFYMBOAGL+5sVgwAxy+ULnxWDAiYwAh+fFYMAo/lLK58VgwJsvrQ3oxWDAdizZUejFYMB4UaeW6MVgwMz8RdzoxWDADwvAIunFYMDhrmVq6cVgwDoDnbTpxWDAMgNu/+nFYMD/4FJK6sVgwNdV/JTqxWDA0EAL3+rFYMDy3nko68VgwIm8C3HrxWDAA4Ibt+vFYMDy6Ov668VgwNQERj7sxWDADSh5gezFYMDeH4bE7MVgwOcRuQftxWDAaGHxS+3FYMC17aOR7cVgwNCXzNjtxWDAvyAOH+7FYMC+vApn7sVgwKtQiqzuxWDAFH0R9O7FYMDeKws/78VgwMweh4bvxWDAr0gDzO/FYMDgRPwR8MVgwM0GRVrwxWDAYMTMo/DFYMBGPO3u8MVgwOUFPjnxxWDAviBjg/HFYMAbvQDP8cVgwKkOnhryxWDAC7KTZfLFYMBq1eCy8sVgwGtp5//yxWDA4Z7kSfPFYMBJ1GaS88VgwBb3btjzxWDAUgZeH/TFYMAg+Q9n9MVgwGDWoaz0xWDADRH88PTFYMD0Da819cVgwGt9N3z1xWDA2G9Qw/XFYMB7atZa+cVgwFfPzU72xWDAprx6mvbFYMA8hcHg9sVgwFqt8yv3xWDARL2zePfFYMBX3HvG98VgwKfiyRT4xWDA+d1rYvjFYMCA3oSv+MVgwOrRJP/4xWDAmzvTS/nFYMBE1+mW+cVgwHVuJeD5xWDAkPFCKPrFYMD23lJv+sVgwLwcubX6xWDANEAu/PrFYMBqRm1C+8VgwDz7zIj7xWDAS9Zi0PvFYMCJmSYY/MVgwGcn0V/8xWDAEH8lp/zFYMCwhx7t/MVgwDV/Azb9xWDAcjiZgP3FYMDVzXbL/cVgwD2QmBb+xWDARAP0Yf7FYMCx7LOt/sVgwOjAr/r+xWDAOucOR//FYMDScT+S/8VgwDRgn9//xWDAok4WLgDGYMCRiX57AMZgwJisJcgAxmDAmDGbFAHGYMBrQf9eAcZgwNp+tqkBxmDAnCL99wHGYMATtwJDAsZgwIIJA40CxmDAuSh01QLGYMDrBvkeA8ZgwPbZTmkDxmDAE87RsQPGYMBeD0P6A8ZgwLnEP0MExmDA4GvEiwTGYMA2SM7UBMZgwLJ8SB8FxmDA8OT6agXGYMCGMGS3BcZgwNvMFQUGxmDA5FweUwbGYMCv2kujBsZgwJPTz/YGxmDAx1scRgfGYMBybLWWB8ZgwDB16+kHxmDA+4VH2QzGYMCfjx0qDcZgwPep/XoNxmDAjRYuzA3GYMBMnb97CcZgwNkV5MoJxmDA7DJjGQrGYMAA3/5mCsZgwNzAF7UKxmDAgj0oAgvGYMDhYYpOC8ZgwJnVS5oLxmDAlVKd5QvGYMBjIg0xDMZgwIxnEXsMxmDAhPvDxAzGYMCTibYODcZgwFy+cFkNxmDAjMYqpQ3GYMARSsbxDcZgwL48gz8OxmDA2vgZjw7GYMDKzhjgDsZgwNqVhDEPxmDAwuFlgw/GYMBYJljVD8ZgwDqUuyYQxmDAMF2bdxDGYMBOkj3HEMZgwIFpThURxmDAVkG6YhHGYMAe6DWwEcZgwKz53eYWxmDAGMJySxLGYMDiTEaZEsZgwJTCbOcSxmDARqwWNhPGYMDylRWFE8ZgwC2n/9MTxmDAWALcIhTGYMB9kKpxFMZgwL5MVMAUxmDABlGoDhXGYMCk2gZdFcZgwAmYCqsVxmDAEJuF+BXGYMB+DCVFFsZgwPEd45AWxmDAaSpE3BbGYMCVeHEnF8ZgwFhdtXIXxmDAmYeivhfGYMDu228LGMZgwPH9BVkYxmDA9XtWpxjGYMDILFD2GMZgwKjZjkYZxmDAhZljmBnGYMCUjKrqGcZgwCuAEj0axmDA0+vKjxrGYMBQa9DhGsZgwIzJdDMbxmDAcMcKhBvGYMCgUuLSG8ZgwEyJiCAcxmDAsmFvbRzGYMDbUtq5HMZgwHCOggYdxmDAkGFkUx3GYMCj6JygHcZgwNRFR+8dxmDA5WiDPx7GYMBrHgaQHsZgwIPsf+AexmDARO8YMR/GYMAADvqBH8ZgwH490tIfxmDAVYYrIyDGYMDIlhlzIMZgwIoIMcMgxmDADslNEyHGYMDhDUxjIcZgwGUGFbMhxmDASGWQAiLGYMAEkT9SIsZgwLoMbKIixmDA00X58iLGYMAjPQ9DI8ZgwIfaMpIjxmDAU4Z+4SPGYMCvt20wJMZgwAVtl34kxmDA5+/eyyTGYMDEKBQZJcZgwDDtQmYlxmDAhCZJsyXGYMBDVnwAJsZgwALf6UYmxmDAcRcAnSbGYMBfNarsJsZgwNuHOD4nxmDAZ62xkCfGYMC++vHiJ8ZgwAYhFTUoxmDAZpn7hijGYMA6ejHZKMZgwPXtvSspxmDAo/A6finGYMArtaPQKcZgwNSNISIqxmDAq00/cyrGYMAcMyjEKsZgwGUioRQrxmDAfbcPZCvGYMD1d/myK8ZgwHCyxwEsxmDAvzp9UCzGYMDb+GOfLMZgwIyyZ+4sxmDAvyfFPS3GYMAjyvONLcZgwLHtft4txmDAY0uDLy7GYMDVaBWBLsZgwPmUidIuxmDAHSPGIi/GYMBbQ7txL8ZgwPNSzb8vxmDAn+HuDTDGYMBhoo9eMMZgwLgUH64wxmDAW4ut/jDGYMBitMpPMcZgwAQecqMxxmDAj6gw+DHGYMB6pW9OMsZgwLFlBKQyxmDA60Rz+TLGYMCe3ghOM8ZgwDn4P6EzxmDAd3QE9TPGYMC4bXRFNMZgwLgAAZc0xmDAf7Qi4jTGYMBjqlkvNcZgwLNaIXw1xmDAOqBmyTXGYMAd0MYXNsZgwA0tloI5xmDAgyok0DnGYMBMORMNN8ZgwCLS7Fw3xmDAObfdrTfGYMCPnrP9N8ZgwIZDE0w4xmDAlxVDmTjGYMCc/sblOMZgwHrGbjI5xmDAlBwufznGYMAPflXMOcZgwEqj8Bk6xmDAV8fjZzrGYMAxYmu3OsZgwJYWywg7xmDAMLTtWjvGYMBBQ4atO8ZgwLNA7v87xmDAhLxGUjzGYMC7P6ekPMZgwNtvzvU8xmDAtRbvRD3GYMCa5oCSPcZgwDLm+zJAxmDAFJ/NLz7GYMDUFh3BQMZgwMkDo8k+xmDAnWjEFD/GYMB7zTlgP8ZgwHGVyqs/xmDA+hIH9j/GYMCWR9hBQMZgwKaMto5AxmDA6esE3EDGYMBIdykqQcZgwDvpenlBxmDAAzi+yUHGYMDsB1gbQsZgwENQWWxCxmDAmHuUvULGYMCy4v8NQ8ZgwPSdyzJFxmDAAJNteUXGYMCeY9b1Q8ZgwLYsk0FExmDAmXnEjUTGYMDl1NjaRMZgwKFP+yhFxmDA0PQreUXGYMD8fq/KRcZgwMQxnBxGxmDApCbUbkbGYMCY0YrARsZgwMSPJhFHxmDAlfBFYEfGYMDlQLitR8ZgwKaQ0vdHxmDAT7LEP0jGYMCQqkeHSMZgwHnRFc9IxmDAwnEZF0nGYMDWcpFfScZgwIm0KalJxmDAiCSX9UnGYMAf0exDSsZgwBCs2pJKxmDASdML4krGYMBmbuwwS8ZgwMJXCX9LxmDAgtuSzEvGYMAl6vXwTMZgwGYnnzhNxmDA/W3ufk3GYMCHd2bFTcZgwGX9GQtOxmDAJrTsT07GYMDCupfWTcZgwGNM9iJOxmDAe0JmGE/GYMAGGiG9TsZgwJfDowlPxmDA2xiVVU/GYMAynzyhT8ZgwEgrw+xPxmDALtqgm1DGYMCBqxV/UMZgwFHEjsZQxmDA/hvKDVHGYMBqxINVUcZgwPCdop1RxmDA1owo5lHGYMA48/8vUsZgwCv41npSxmDAvTTpxVLGYMCD3CESU8ZgwFq4611TxmDAeJ1tqFPGYMAcLxkOVMZgwE3Y/lFUxmDAI7ABlVTGYMD18a3WVMZgwBzZ0BdVxmDAYENQX1XGYMDhmeSmVcZgwGWA7+1VxmDArSL/M1bGYMBGZip6VsZgwH2nMsBWxmDAHhx6BlfGYMDa9W9NV8ZgwJ/gPpRXxmDA3D/e21fGYMDrjFkkWMZgwJbbGWtYxmDA0GKfU1jGYMCOPtH7WMZgwA6YdERZxmDAhukcjFnGYMDJFb1OWcZgwM6XqY9ZxmDA6278XVrGYMD08syhWsZgwIIRn+VaxmDAtnPVKVvGYMBb3r1uW8ZgwK29YrRbxmDA8kEH+1vGYMCwaUNDXMZgwC3Mv41cxmDA1KUI2VzGYMCAnqZKXMZgwBSrnWpdxmDA3SVytF3GYMD8IrH9XcZgwKqOmUVexmDAD4UTjF7GYMAL8hvSXsZgwDYNiRdfxmDApQbmXF/GYMArLQWiX8ZgwGwFPOZfxmDAAu5PKmDGYMBnt4NuYMZgwN9MDbNgxmDADg0B+GDGYMBqtSM9YcZgwO0itIJhxmDAnfz8yGHGYMDq8MEPYsZgwFhkKVdixmDAV2Uun2LGYMAkaL3nYsZgwCLiuTBjxmDAYYg6emPGYMDVdzbDY8ZgwLPRtA5kxmDAYp+XCGPGYMCznTRJY8ZgwEe/5OdkxmDAk1T3LmXGYMA8OssMZMZgwBOA6b1lxmDAa3biBGbGYMAsKbJKZsZgwFFnRI9mxmDAeCH8YGXGYMCKrF0aZ8ZgwFUD51xnxmDAH796n2fGYMBJXEjjZ8ZgwEqaFrRmxmDA1q/tZ2jGYMBg9nE6Z8ZgwLi9sn1nxmDAn3kOwWfGYMDxxgh5acZgwPzx8cBpxmDAX8gzCmrGYMD6XAhUasZgwNG5NJ1qxmDA1yiY5mrGYMCq8Fgva8ZgwEH+3XZrxmDAyP0QvWvGYMANlxQCbMZgwNFHjUZsxmDAqyfHimzGYMAikpPNbMZgwNUl0A9txmDAXuytUW3GYMAZJ+yTbcZgwMPNZtZtxmDAu8YLGW7GYMDIWxhcbsZgwJCZXp9uxmDAluaT4m7GYMC8Hs4lb8ZgwNAUxmhvxmDAO+M1q2/GYMCAHbLtb8ZgwBm6azBwxmDAQn9Kc3DGYMAeLra2cMZgwGhM0fpwxmDAbWawP3HGYMAxUAiGccZgwK2Cs8xxxmDAYxogE3LGYMC7v0ZZcsZgwCOheZ5yxmDAbizJ4nLGYMDHFHImc8ZgwLhfy2hzxmDARIH2qXPGYMC3pVzqc8ZgwDqfFyp0xmDAy1OXaXTGYMCPAfuodMZgwHJSbuh0xmDAny+AKHXGYMBHxGBpdcZgwEkObqp1xmDAJfhb63XGYMCgdHIsdsZgwImW/G12xmDA55evrnbGYMDlJFHvdsZgwMlZdzB3xmDAZZOUcXfGYMD06pqyd8ZgwEtvEPN3xmDAOXH3MnjGYMBoh6lyeMZgwHtpwLF4xmDAVudJ8HjGYMBbLiEvecZgwJIbuG55xmDADiFqr3nGYMCctyDxecZgwJsskzN6xmDAH+Ghd3rGYMBAK6i9esZgwAMPTwR7xmDAK/MwS3vGYMAakOWRe8ZgwAnNA9h7xmDAW7FlHXzGYMAltgBhfMZgwNZTIKN8xmDASmB25HzGYMCrOtUkfcZgwDXPiGR9xmDAGtPZon3GYMDLpE3hfcZgwJ+SlB9+xmDAbzS7XX7GYMCz27+bfsZgwOH4/Nl+xmDAtSMPGX/GYMBbGKBYf8ZgwIeEo5h/xmDAu2fC2X/GYMCB88QbgMZgwOZKaF6AxmDAsFlWoYDGYMDVxkPkgMZgwOHYAieBxmDAYobcaYHGYMDhAIKsgcZgwJsy0e6BxmDAZBStMILGYMAEnPxxgsZgwFb697KCxmDAmqPs84LGYMCCFs80g8ZgwMKvhHWDxmDAkpMmtoPGYMDTS3/2g8ZgwGLs5jaExmDAfdmcd4TGYMBWmXG4hMZgwNcCO/mExmDA6IeyOoXGYMDXdep8hcZgwCCZJsCFxmDAoWtQVYTGYMCAmWKYhMZgwCRkyoiGxmDAtDmGwYbGYMC5kjgDh8ZgwGxHAESHxmDAiKEDhYfGYMDqh/jFh8ZgwHH1ogWIxmDADv3IRYjGYMDPY0yGiMZgwA1h8MeIxmDA5zXJCYnGYMBGjMNKicZgwIPM2YuJxmDA95xszYnGYMDO2uIOisZgwJArPVCKxmDAy7bakIrGYMDy2lXSisZgwCKkKxOLxmDA4Hq3U4vGYMBoJE2Ui8ZgwIqE4dSLxmDAW5FaFYzGYMBzNtNVjMZgwNCSLJaMxmDACJlV1ozGYMBhim0WjcZgwDqDwlaNxmDANgebl43GYMDcfffYjcZgwHuLwhqOxmDATVSJXI7GYMAyZYGejsZgwIRfaOGOxmDANEHgJI/GYMDu3mpoj8ZgwEg156uPxmDA28dk74/GYMABPp0ykMZgwBvckXWQxmDA9TAUuJDGYMC2suH5kMZgwB7J5zqRxmDAT2hfe5HGYMApT1i7kcZgwKb9WfqRxmDA8HAbOJLGYMCmnpx1ksZgwAesibOSxmDAqEnr8ZLGYMBYIAQxk8ZgwDVGQXGTxmDAbtsks5PGYMBzMDD3k8ZgwARXZzyUxmDATu8cgZTGYMBZl9rElMZgwPO63AeVxmDAvDiQS5XGYMANluWOlcZgwETnM86VxmDAj8NKDJbGYMDMLHJLlsZgwMrMr4qWxmDAqSFkypbGYMCPjNIKl8ZgwCjUZUyXxmDABavqj5fGYMC/AqDUl8ZgwDWashmYxmDA0D3kXpjGYMDRZrKjmMZgwByVbOiYxmDAh81fLJnGYMCBmL9umcZgwFcGZK+ZxmDAXfCU75nGYMA/Lr8vmsZgwHd5em+axmDATWkvr5rGYMDD3BHvmsZgwNbbmy+bxmDACoPXcJvGYMDBx1eym8ZgwNNHB/SbxmDAIonRNZzGYMBbxbN3nMZgwCO8yrmcxmDAAfOB+5zGYMDUB8w8ncZgwI75iH6dxmDAal02wZ3GYMA/LG0EnsZgwIhgiEiexmDA7Z8bjZ7GYMAl1pjSnsZgwKODoxmfxmDAC/FHYJ/GYMA2Xmqon8ZgwOOUGO6fxmDAi2r+M6DGYMDuzoR4oMZgwNEURLugxmDA37+H/KDGYMBEwkg9ocZgwBlvZn2hxmDAyMYuvaHGYMALFKv8ocZgwCi1OTyixmDAjLQUfKLGYMAK45S7osZgwNnP1PuixmDAzGwjPaPGYMCE2Zp/o8ZgwEVntMKjxmDAr284B6TGYMC5jNtNpMZgwO+7kJWkxmDAtEIb3qTGYMAuHsQmpcZgwM8oQm+lxmDAZcA5t6XGYMDQQUb+pcZgwDNsG0SmxmDAuo7th6bGYMB9PJjKpsZgwAtTkQynxmDAOhg4TqfGYMAApeSPp8ZgwC7A2NGnxmDA9MSXFKjGYMDKn8tYqMZgwIT8752oxmDA0CJm46jGYMAzryIpqcZgwGsKKW+pxmDAcGo3tKnGYMC9mLX5qcZgwJVuwj6qxmDA82+4gqrGYMCNTK3GqsZgwIQsKAqrxmDAwKORTavGYMBWmVGRq8ZgwHr8kNWrxmDA6UQHG6zGYMCNvkxhrMZgwKLUI6isxmDADAYx76zGYMDPxj02rcZgwK03N32txmDAPnsExK3GYMDMpHIKrsZgwHGzdFCuxmDAj94Hlq7GYMAeJxLbrsZgwPkNoh+vxmDAJu/XY6/GYMA6L9Gnr8ZgwBGRduuvxmDATs7RLrDGYMAJVDJysMZgwF2IorWwxmDAc4Mn+bDGYMArXvY8scZgwPIyb4GxxmDAGESPxrHGYMB5UVkMssZgwEHqYVKyxmDAUwqXmLLGYMAGGQ3fssZgwFJMkyWzxmDA8mEkbLPGYMCYnUays8ZgwJK46vezxmDADFugPbTGYMDLMqODtMZgwMvmIsq0xmDAWo4DEbXGYMD22kpYtcZgwPosKqC1xmDAtgL56LXGYMCrBuIxtsZgwHMusHq2xmDAee8Ow7bGYMB328sKt8ZgwBkatVG3xmDA9jWSl7fGYMB0A0Tct8ZgwJPEJci5xmDApcuVZLjGYMADCgOpuMZgwOjwmO24xmDAUb+CMrnGYMA1Wf13ucZgwBJ2sr65xmDAl9R1BrrGYMBHH+JOusZgwA2Hm5e6xmDA2W+U4LrGYMDbGb0pu8ZgwHndvnK7xmDA3pN1u7vGYMCwhwoEvMZgwPKa/ky8xmDAbZrLlLzGYMAeu6HcvMZgwO951CS9xmDA3QJobL3GYMA1pGmzvcZgwPTfZfq9xmDA+yKhQb7GYMDv6x+JvsZgwCzobdG+xmDAHNBiGr/GYMDOt8Rjv8ZgwH4/va2/xmDAWoj397/GYMC2wmFCwMZgwFlmT4zAxmDA2+U51cDGYMC9lzwdwcZgwPh7WGTBxmDAdPNCqsHGYMA60BHvwcZgwJ5XyzPCxmDA5euVeMLGYMAZ7oy9wsZgwM9gWQPDxmDAJUWkSsPGYMA3b/STw8ZgwDt+GN/DxmDA7u/iKsTGYMCnjfV2xMZgwD7Z98LExmDAmkKZDsXGYMA39NNZxcZgwIVFdKPFxmDAqXqT68XGYMCDoVgzxsZgwFS9GXvGxmDA5gvOw8bGYMD10VZZycZgwIeItFbHxmDAIDG7o8fGYMCR08Lwx8ZgwLu0Iz3IxmDAvoSKicjGYMD5fBjVyMZgwFFRQiDJxmDAvd8sa8nGYMD9Y3W0ycZgwL5eNfvJxmDADBClQcrGYMCn0dqHysZgwBCkO87KxmDAxYpZFcvGYMC/gE1dy8ZgwIl1eabLxmDAZvzW8cvGYMB1jHY+zMZgwHLEkI3MxmDAJNYY28zGYMA0dQYpzcZgwFPM5XPNxmDALfbHv83GYMDvC7MKzsZgwJZW01TOxmDANt8ins7GYMAcjvjnzsZgwCIrRjDPxmDA4PYGeM/GYMDY9X+/z8ZgwC8MHgfQxmDAXx53T9DGYMDeiWqX0MZgwEI8DeDQxmDAhKahKdHGYMBVdVtz0cZgwLQfnL7RxmDA/cciC9LGYMABDXdY0sZgwNApwaXSxmDAqk/t8tLGYMC8LTk/08ZgwJ1gOYvTxmDAbpWi19PGYMBOcvMh1MZgwAflI2vUxmDAy7ketNTGYMCnPIT81MZgwJhuWUXVxmDAWcnYjtXGYMBwXwbZ1cZgwB9hrCLWxmDAYa5BbdbGYMBD4oa51sZgwASTngXXxmDAm4ouUdfGYMAnPHWc18ZgwNWAyefXxmDAFEUsMtjGYMCs5XV72MZgwKNQXcTYxmDAAN7OC9nGYMD9kY9U2cZgwCBR+p3ZxmDAI3Z359nGYMCUpcAx2sZgwB6zuHzaxmDApNANydrGYMB+DaEV28ZgwELvK2LbxmDASRxkrtvGYMA0FUL628ZgwNQ2KEXcxmDAbkxqj9zGYMDu0ZrZ3MZgwAX0KyTdxmDAITMVb93GYMCVhZC63cZgwESdOwbexmDAtkOJUt7GYMCN9Dqf3sZgwFcHUu3exmDA736FOd/GYMBbPVyE38ZgwGOqz87fxmDASO+RGODGYMBEHKBg4MZgwEhW+abgxmDAb/pZuuLGYMAjUK4w4cZgwJE2SHbhxmDAJNfivOHGYMCTvpIE4sZgwAurQk7ixmDASV2BmuLGYMDUVXbo4sZgwNdFOTfjxmDA9ilxhuPGYMDraLfV48ZgwK2V0STkxmDAnEURc+TGYMD1g9K/5MZgwEhzygvlxmDAjtE9V+XGYMDFRGKi5cZgwPFgSu3lxmDAuiEaOObGYMBBgvuC5sZgwOKnY87mxmDAhHANGufGYMCt/gpm58ZgwInyk7LnxmDAGCst/+fGYMCZ7DRL6MZgwOudQJfoxmDAz9bJ4+jGYMDynzYv6cZgwFvbO3rpxmDASxzmxOnGYMAIV70O6sZgwB5S4FfqxmDAbQRCoOrGYMAFyh/n6sZgwCnGVS3rxmDAOvvgc+vGYMA7tvu668ZgwEJuBAPsxmDAWTYRTOzGYMBa+G2W7MZgwNK4TfbtxmDAhKk3PO7GYMBH8FiA7cZgwFQCE9DtxmDAVwiZH+7GYMCRAGFu7sZgwKNCMbzuxmDAnHnGB+/GYMBjlBNS78ZgwA17XpvvxmDAhcOG4+/GYMAypVcq8MZgwAWY/nDwxmDA4A3Xt/DGYMBezef+8MZgwITHGEbxxmDAev6CjfHGYMBFH3/V8cZgwENBMB7yxmDAN7CFZ/LGYMBXPpmx8sZgwJPIa/zyxmDA+rfzR/PGYMD71fOT88ZgwGg3TODzxmDA2ZjrLPTGYMBCm3l69MZgwE5Lzsf0xmDAShK9Y/XGYMBGii9f9cZgwD8m2ev1xmDAb1ZgMPbGYMDbf0xy9sZgwCJcmbX2xmDAoW/S0/bGYMCf6+wc98ZgwEUp+mX3xmDALgu9rvfGYMAIIOz298ZgwIDXnD74xmDAIB/nhfjGYMBeYt7M+MZgwDCOthP5xmDAvfPpYvnGYMBJhYOm+cZgwG6KL+r5xmDAvoUOLfrGYMAPem90+sZgwBmHNrz6xmDABDPVBfvGYMDB+rpQ+8ZgwLCY7J37xmDA9mCi6vvGYMDq6I43/MZgwMuapYL8xmDAJZkZzvzGYMDj428Z/cZgwCesxWT9xmDAMrbVrv3GYMC5DHH3/cZgwGzgtD/+xmDAWgM6h/7GYMBcy8HO/sZgwOxo9hb/xmDActs8X//GYMACqyCo/8ZgwB846O//xmDAwoisNwDHYMAP0dN+AMdgwL1z1MUAx2DAFStJDQHHYMBcFrtRAcdgwIL4oZMBx2DAToYE1wHHYMAPMzwbAsdgwGRHoWACx2DAycLApgLHYMBsA2XtAsdgwPo4dzYDx2DAjonMgQPHYMC+prnMA8dgwDJi2xcEx2DA3/TgYgTHYMDrdGitBMdgwPjU/vYEx2DA69LfPgXHYMCLIZuEBcdgwBFEsMkFx2DAKpVxDgbHYMA/hS5TBsdgwApbFZgGx2DAAFdF3QbHYMCoR4MjB8dgwOKpGWsHx2DAUaIlswfHYMDnbmX7B8dgwKUToUMIx2DAIRmciwjHYMDDEk7TCMdgwGBqpBoJx2DAzCzLYAnHYMBhu7alCcdgwBHklOoJx2DAt+LdLgrHYMC1uiZyCsdgwJWQWLUKx2DAQtxE+grHYMAHTgA+C8dgwEMf7oELx2DAHGU1xgvHYMAOuucKDMdgwGWB7U8Mx2DAhT5olQzHYMB1znzbDMdgwKf3RiINx2DAmK1uaQ3HYMBjea2wDcdgwIPo2/cNx2DAz7fpPg7HYMAGqLuFDsdgwDdeBswOx2DALvufEQ/HYMBxZMVWD8dgwDjnjpsPx2DABjoM4A/HYMDFAVokEMdgwGop32gQx2DA8htzrRDHYMDRCvbxEMdgwNqfmTYRx2DAWr6UehHHYMCOW76+EcdgwDKutwISx2DANNuhRhLHYMDv2TqKEsdgwIm2kswSx2DAPalVDhPHYMB9LhNQE8dgwBNpcpITx2DADvHt1RPHYMBt31kaFMdgwNyc/18Ux2DANn1ipxTHYMB0phzwFMdgwKotMDkVx2DAKdVDgxXHYMAquwLKFcdgwDE0FxEWx2DA6i0TVxbHYMB0Z7OaFsdgwH6ZWtwWx2DA+UAmHRfHYMBHTVddF8dgwAfvZ50Xx2DAFseZ3RfHYMDhAm8eGMdgwCI2WWAYx2DAunOeoxjHYMDL85fnGMdgwDoebisZx2DAcyW7bxnHYMC3nDK0GcdgwIL3x/gZx2DAO4YZPRrHYMCQFc6AGsdgwNi9W8Qax2DAURyaBxvHYMAxtVNKG8dgwORi44wbx2DAptBWzxvHYMCJUYERHMdgwJSsOlMcx2DAPnfplBzHYMCiru7WHMdgwL16CBgdx2DArlpFWR3HYMDrm2WZHcdgwPdjGtkdx2DAKLpJGh7HYMCkkoNbHsdgwATiI50ex2DAB0Op3h7HYMAEDhYgH8dgwHQYEmIfx2DApfjwox/HYMAZLkrlH8dgwA7+qicgx2DAJFE+aiDHYMDzQjWpIMdgwFcqQOsgx2DAgwjwKyHHYMCHr9psIcdgwBUQT60hx2DA+lmP7SHHYMAq5dwtIsdgwFGI3W4ix2DA14yOsCLHYMBBooDyIsdgwDbrKDUjx2DAQd01diPHYMDRtu+3I8dgwNXiyfMjx2DASogYOyTHYMCJRu18JMdgwE5xJr4kx2DAiC2m/yTHYMA2NwRAJcdgwHliFX8lx2DADZBzviXHYMB3uH/9JcdgwAW8tjsmx2DAem+UeSbHYMDRq1C5JsdgwJBFovkmx2DAoY9mOCfHYMBYm2t3J8dgwJrR0rcnx2DALPj49yfHYMDNNL04KMdgwK3++Xkox2DAZkC3uyjHYMDywtj9KMdgwIiK5D8px2DACtacgSnHYMC8o9TCKcdgwM1yVgMqx2DA1B9YQyrHYMBQDBGCKsdgwJWYHcAqx2DA0Knc/SrHYMCYKxY7K8dgwD7Wy3grx2DABjCttivHYMAbmcX0K8dgwPXQjDMsx2DAPRFCcyzHYMC9uHizLMdgwD2iDvQsx2DAbbAWNS3HYMC3VWx2LcdgwKZ14rctx2DA5dlc+S3HYMCHVsA6LsdgwPDg9Hsux2DAbrYhvS7HYMARlf39LsdgwM2AYT8vx2DAAjWwgC/HYMBYB5nBL8dgwE82bwEwx2DAhXh2QDDHYMDXy1aAMMdgwEPpicAwx2DAigbaADHHYMCMQOZAMcdgwOHEd4Exx2DA8fznwjHHYMAq1yMEMsdgwNqmIEUyx2DAd3v0hTLHYMCQkivGMsdgwFjTxgUzx2DAVLNyRDPHYMD+xnOCM8dgwM/of78zx2DAwOSs/DPHYMBoUk05NMdgwEgDvnU0x2DAp/G9sjTHYMCZIOfwNMdgwJ7T5DA1x2DALYWtcTXHYMBq7q+yNcdgwPxKuPM1x2DAa3mMNDbHYMDum1l0NsdgwIT/d7Q2x2DALpi69DbHYMBerKgyN8dgwAV6NXA3x2DA08ExrzfHYMC7zULtN8dgwGnqyyk4x2DAxEs9aDjHYMDUIGWnOMdgwDG/UeY4x2DA3oqDJjnHYMCNpMRmOcdgwM/O+aY5x2DAs9yF5znHYMDBqC4oOsdgwNNRfmg6x2DAobrTqDrHYMDRSRvpOsdgwNzuUyk7x2DA0sm5aTvHYMCkGFyqO8dgwGikBOs7x2DAuK3BKzzHYMCqo7VsPMdgwMD3l608x2DA7ORb7jzHYMDsIhcvPcdgwO2m5W89x2DACQ2UsD3HYMDJUfPwPcdgwPg9LTE+x2DA4AKPcT7HYMCxcOuxPsdgwG8dRfI+x2DADhsLMz/HYMBWEfRzP8dgwM5GHbU/x2DAANlC9j/HYMDSdD83QMdgwEq05ndAx2DAK8bLt0DHYMATp473QMdgwG309DdBx2DABgBsd0HHYMBYTy+2QcdgwMVWhvRBx2DAN4NnMkLHYMApPD9wQsdgwPYP561Cx2DA2UBu60LHYMDzfzIpQ8dgwLImMGdDx2DA6F0xpUPHYMBSvuPjQ8dgwLCWViNEx2DA7YF6Y0THYMBYiWekRMdgwLSaxeZEx2DADcIEKkXHYMBCvDVuRcdgwMk4d7FFx2DA4Iuv9EXHYMAp2GM3RsdgwESmXHlGx2DAK+tnukbHYMBdpFv6RsdgwDPBpzlHx2DAacDpd0fHYMCTb+G2R8dgwErEqvRHx2DAiknIMUjHYMAtUg5uSMdgwN4T2alIx2DAOoJ35kjHYMD3auojScdgwE87bWJJx2DA/KL/oUnHYMBS+sTiScdgwPW17iRKx2DA4REJaUrHYMCvqJCuSsdgwH8SofRKx2DAjrOrOkvHYMBk1WKAS8dgwMU3cMVLx2DAGtlvCUzHYMDsUZtLTMdgwBwcEY1Mx2DA5SOezEzHYMBXzTcMTcdgwOiIb0tNx2DAs3piik3HYMAah1nJTcdgwJ8Q3whOx2DAttb/SE7HYMBRlU6JTsdgwIT3tslOx2DA0G9jCk/HYMDOxEZLT8dgwPsXT4xPx2DAKv7izE/HYMBcoysNUMdgwHF9001Qx2DADyQTj1DHYMCYvPbQUMdgwMWxhRNRx2DA8yOoVlHHYMBtMdyaUcdgwGSX+N9Rx2DAYZdEJVLHYMAvJH9qUsdgwK+YYq9Sx2DA4DF/81LHYMDnZ043U8dgwG4kanpTx2DAZgX7u1PHYMCE3PP8U8dgwAlxij1Ux2DAESkDflTHYMDwoY++VMdgwFXfkv9Ux2DA+YRReVTHYMC0NxbBVMdgwGrl98RVx2DADfSUUVXHYMAYWRabVcdgwE8ZZY9Wx2DA1HS/0VbHYMCwNLl8VsdgwIGDzlZXx2DARsKNmVfHYMCp91/cV8dgwOhEzB5Yx2DAAL6YYljHYMBUobCmWMdgwAFh6+hYx2DAva3NKlnHYMCU4J8bWcdgwOva7q5Zx2DAHPCF8VnHYMDWmrw0WsdgwPt29Hdax2DA5MoEhlrHYMCdrHUAW8dgwB122kVbx2DApcCPi1vHYMCNAvytW8dgwMQgy/dbx2DAYXRZQVzHYMAth5eKXMdgwNz+j9Ncx2DARXFmHF3HYMAFBvRkXcdgwPobOa1dx2DAWAtn9V3HYMBoTFo9XsdgwPn3CoVex2DANLLFzF7HYMDOPpn+XsdgwCDqHUVfx2DAL9Fii1/HYMBvSF7RX8dgwOSmfxdgx2DAjDqiXGDHYMBz9H+hYMdgwMEGOuVgx2DANJ12KWHHYMDw46FtYcdgwNQz6AZix2DANLHx9WHHYMAVqfc6YsdgwPk3AOVix2DAZmrHKmPHYMBI3W1rY8dgwAerKVRjx2DAsfFXmGPHYMBYqtrbY8dgwEQQbRpkx2DAMQb2YWTHYMDriLSjZMdgwBMRmOVkx2DALQMzJ2XHYMAL3SFoZcdgwEz53qhlx2DAxR7G6WXHYMC5GVcrZsdgwH9h321mx2DA3GVnsWbHYMDnmoP1ZsdgwJw92zlnx2DAIZCOfmfHYMDiLBPEZ8dgwEdIZApox2DARN2jUGjHYMAM5gWWaMdgwDMSPNpox2DAjNUGHmnHYMD2K2RhacdgwN9dxaRpx2DABvMS6GnHYMC3lGAqasdgwHzYR2xqx2DAP7NYrmrHYMAmvtfwasdgwP9qvTNrx2DAmQHydmvHYMCh4EC7a8dgwD8GvQBsx2DAxoboRmzHYMDvRUKNbMdgwD9Rt9Nsx2DAuQTuGW3HYMBI0xZfbcdgwE9QTKNtx2DAIkPD523HYMBt0NIsbsdgwD0imHFux2DASZsEtm7HYMApGPP6bsdgwIIrWUBvx2DA135MiG/HYMAXqm7Rb8dgwL9JuBpwx2DAKPUFZHDHYMCksGKtcMdgwB31lvZwx2DADbdBP3HHYMAlmTmHccdgwFpiQc5xx2DAMO1iFHLHYMCLkyhacsdgwI6Ns59yx2DAV1Yf5XLHYMAPq6kqc8dgwFBM/3Bzx2DAHfFsuHPHYMDq4CsAdMdgwPtS4Ed0x2DA3/jcj3THYMBX7qXXdMdgwCx4FR91x2DAcxHXZXXHYMBh3rirdcdgwCaMz/B1x2DAo2n2NXbHYMC08bl7dsdgwGucYcJ2x2DAF3EWCnfHYMBoI8xSd8dgwFSh85x3x2DA1h2w6HfHYMCRpu80eMdgwMy4k4F4x2DA2N0lznjHYMAFBHkaecdgwKRnMWZ5x2DAH52msHnHYMDl52v5ecdgwF5r/0B6x2DASRoPiHrHYMDGcs3PesdgwN3s8xZ7x2DAsr4MXHvHYMDfE72he8dgwCFAB+d7x2DAH4jVLHzHYMBrVWdzfMdgwDTMvbp8x2DAdwDcAn3HYMCB665LfcdgwGD9kpV9x2DAGiar4H3HYMAVtIQsfsdgwCKRsyWBx2DArDhOv37HYMAgbWoJf8dgwN2Z1lJ/x2DA2xsMm3/HYMDPrcjhf8dgwJkxPCiAx2DAJKfSboDHYMD1cYi1gMdgwNLDXvyAx2DAlE1aQ4HHYMBt5lCLgcdgwKZ5y9SBx2DARanoHoLHYMCpKURpgsdgwK37ebOCx2DAOSpM/YLHYMB2vIRGg8dgwLLJS46Dx2DAsye01IPHYMCshhwbhMdgwOJzxGGEx2DAxGmtqITHYMDCA1rwhMdgwCJxTziFx2DA7PeYgIXHYMBrRr7JhcdgwN+CrBOGx2DAp6ISXobHYMAD4oOohsdgwIVav/KGx2DAGw2VPYfHYMAB5qSIh8dgwN7S+NOHx2DAu3mNYYvHYMCTNOtpiMdgwNzIkLSIx2DAw0ar/ojHYMBMaP9HicdgwHtQcJCJx2DAZPXy14nHYMDTzCMfisdgwNOOw2WKx2DAWiwzrIrHYMAAa7byisdgwKVpsTmLx2DApd0rgYvHYMA9jpTJi8dgwLGISBOMx2DArdChXYzHYMA8sC6ojMdgwKNxJvOMx2DApzzePo3HYMCs8ueKjcdgwDtKvNaNx2DAdiVzIo7HYMCc01pujsdgwKELpLqOx2DAsLVsB4/HYMCBu5xUj8dgwHF336GPx2DA7tlD74/HYMAqfrU9kMdgwLav1IyQx2DAMq0O25DHYMA8zBQpkcdgwHMeBHeRx2DATqEsxZHHYMBOXCsSksdgwFvQMl6Sx2DA8IbCRJbHYMC/ATWTlsdgwIVnV0STx2DAbt1yj5PHYMAU0RHak8dgwMBneyaUx2DA+Rx2c5THYMC/j87AlMdgwEZabA6Vx2DABu8KCpnHYMCEne+qlcdgwAS1TfuVx2DAF99mSJbHYMBjIBWWlsdgwMzRB+SWx2DAyt1nMpfHYMBzOouBl8dgwJ1YhdCXx2DAiSfWH5jHYMAVv9ZvmMdgwPPZWcCYx2DAJFAUEZnHYMDCZdVhmcdgwHGWVbOZx2DAPpVRAprHYMB/sWBRmsdgwNuJXkKex2DA3g377prHYMAsrhM9m8dgwJ+pSYqbx2DADXF81pvHYMA+ORginMdgwJK+ngagx2DADP5vVKDHYMAAPrEFncdgwGvlwFCdx2DAidNvnJ3HYMAnvPPoncdgwDUzQzaex2DA96QbhJ7HYMC9CUV5osdgwJ4yuSKfx2DAkaJycp/HYMA1Rzlio8dgwGiZ2BKgx2DAEP1AY6DHYMCmkcSyoMdgwCJ8KwGhx2DAotZeTqHHYMAIdriaocdgwMDIzeahx2DAPW8/MqLHYMCD889/osdgwBuGgsmix2DA+26dFaPHYMD8OwZko8dgwPvgm7Ojx2DApqbaAqTHYMAKq7pRpMdgwIWn4Z+kx2DASZAv7aTHYMAvkk45pcdgwHqXRYOlx2DA5ggSy6XHYMAczS4SpsdgwDLVQFmmx2DANMn0oKbHYMDaOIfppsdgwOGqJjOnx2DAA6L0f6fHYMBqGxzPp8dgwGs2tB+ox2DA7uX1cKjHYMCYd3fCqMdgwOCgYROpx2DA00o2ZKnHYMCKzGS0qcdgwGUmoQKqx2DA1i1XUKrHYMB0EtKdqsdgwIFKSOuqx2DAc2XSOKvHYMD6HPyFq8dgwITYI9Orx2DAxgIwIazHYMDyWmpvrMdgwEzLgrysx2DATDQLCa3HYMAGn/tWrcdgwHp2xaWtx2DArEqL863HYMDGUXo/rsdgwM7knouux2DAKlde2K7HYMC+b10nr8dgwMlomVKyx2DAf7NywK/HYMDopCwQsMdgwB7YYWGwx2DApGAPsrDHYMBkFsoBscdgwIN8nlOxx2DAGRqSpbHHYMBLB3n3scdgwGn/JUmyx2DAss6qmbLHYMA3L8TqssdgwPcV4Dmzx2DAAlNHiLPHYMBVSgLWs8dgwDWh5CK0x2DAduR5b7THYMCBlj9Ht8dgwJPHJQa1x2DAJOGCUbXHYMCTdXWctcdgwCsdVOe1x2DAYsAhOLbHYMDNKo6GtsdgwAaKfNa2x2DAM8B4gbnHYMBmCtDKucdgwGK+eNK3x2DAUv1FJbjHYMAhP2d3uMdgwJuv1si4x2DAFKdwGLnHYMCLGQhmucdgwB6cs7K5x2DAgekY/7nHYMCJaLFLusdgwEncbZi6x2DANUSA5brHYMCINHAzu8dgwKl/cIK7x2DAMcOx0bvHYMAcOvMgvMdgwOfGG3C8x2DAGtLpvrzHYMAU3kENvcdgwEYjsVq9x2DAtVQ6p73HYMANuiLzvcdgwNfTjD6+x2DAO0dRhr7HYMAjHfXPvsdgwA6DABq/x2DAi2GzL8HHYMAha6NzwcdgwEw7MbbBx2DA4EYF98HHYMDHNh6IwMdgwJrjh9HAx2DAXwfsG8HHYMCNpIlmwcdgwHMWW7HBx2DA82nB/MHHYMCuOQhJwsdgwCvVVJbCx2DAVZIo5MLHYMA/rAwyw8dgwGWIeYDDx2DAVykDz8PHYMAekvYcxMdgwCNyZGrEx2DAmrVit8THYMC3zp8DxcdgwFBsNE/Fx2DA9b+RmcXHYMC/6a/ixcdgwC4U0CrGx2DAoyGDcsbHYMCUUMq6xsdgwE39kgPHx2DA/qT0TMfHYMC6dU+Xx8dgwFEj1OPHx2DA1qLSMcjHYMDgN6aAyMdgwNqEEdDIx2DAGPQJH8nHYMCz0C9tycdgwO3jIbvJx2DAhLmWB8rHYMCa9KJSysdgwGlkEJzKx2DA185Q5crHYMAftnsuy8dgwB785HfLx2DAEz+pwMvHYMBD1NMJzMdgwBQQmlPMx2DAsPt5Tc3HYMCe8AjnzMdgwHH44y7Nx2DAcUKtes3HYMARumfEzcdgwANInw7Ox2DAYl3MWM7HYMAFrGKjzsdgwFeAA+7Ox2DAwZZ+OM/HYMBOMDKDz8dgwDYV7M3Px2DAb6mZGNDHYMDNeXhj0MdgwP3bo67Qx2DADMix+dDHYMALKy5E0cdgwBPISY7Rx2DA4DyZ19HHYMC+9fog0sdgwP00gWvSx2DArkURttLHYMD+XFIA08dgwIc5vkrTx2DAIQN8lNPHYMD3tTrd08dgwAsUpCXUx2DArfVAbdTHYMChlxu01MdgwPA1qPrUx2DAT4QpQtXHYMDTBGCI1cdgwJiiXM7Vx2DAKT2OFdbHYMBhZvJc1sdgwDfdTKTWx2DAii/D69bHYMACU1Az18dgwLwtCXvXx2DAKNVlw9fHYMAWXQAN2MdgwFCc41nYx2DAR9Bwo9jHYMCRhe262MdgwKVEWS/Zx2DAqgDpa9nHYMDb8Re62cdgwAFTKwPax2DACnUsS9rHYMDCzO2S2sdgwLd6F9vax2DA5S5MI9vHYMDgPH5r28dgwNYP3bPbx2DApJx1/NvHYMDj385E3MdgwKahB43cx2DAOwZ/1dzHYMA8ka4d3cdgwGZ8YWXdx2DA1bBQrN3HYMD4HBzy3cdgwIM6Kzbex2DAv9lVed7HYMDEqs283sdgwI4vjQDfx2DAGuqZRN/HYMAWqeyJ38dgwKnLAtDfx2DA8Ob6F+DHYMAVNPVg4MdgwP83Yargx2DAt24s9ODHYMAuTXs+4cdgwBkJKonhx2DAyE6+0+HHYMCcTZ4d4sdgwJsX0Wbix2DAOTTtr+LHYMA3F5f44sdgwELv2kDjx2DAHXQei+PHYMDXO6rR48dgwPsjGRjkx2DA1GzvXeTHYMBjCSWk5MdgwPxuyezkx2DAZ3QnM+XHYMCbDLB45cdgwIVsq8Llx2DA+zx8TeXHYMCLpdCX5cdgwMi/jJ3mx2DAdKSd5ebHYMAnYjwt58dgwISqL7zmx2DAijm4BefHYMAMIo5P58dgwDwCHpbnx2DABl723OfHYMAAwBjc6MdgwGLQTiLpx2DA1DBzaOnHYMAE+Gmu6cdgwI0xgfTpx2DA2OX1OurHYMB9NHKB6sdgwDlGncfqx2DAWvuiDevHYMCtyIxT68dgwBDOPZnrx2DA1k+z3uvHYMCOLfYj7MdgwE/jPGnsx2DALLmQruzHYMDSVfTz7MdgwA5aYTntx2DAkC0If+3HYMCMcfbE7cdgwMYBtAvux2DAsz+TUu7HYMA/IB2Z7sdgwPZQb9/ux2DANS33JO/HYMC/Auxp78dgwEplcK3vx2DAP3tU7+/HYMAPPnMw8MdgwNOw4XHwx2DAZ+MUtPDHYMAzevb28MdgwBbYcDrxx2DAsjDCfvHHYMDEaP/E8cdgwARwTwzyx2DAlO8nVPLHYMCgtEGc8sdgwC4MC+Tyx2DAgT1YK/PHYMB0AQJy88dgwLurlrbzx2DAUyhG+vPHYMAIB+s89MdgwFcBBH/0x2DAaIHrwPTHYMApKQcC9cdgwM2EmkL1x2DABxi1g/XHYMDyxkDF9cdgwHB83wb2x2DAigTSSPbHYMApTm6L9sdgwKaAbs72x2DAHJOzEffHYMC+WE9V98dgwBJpOJn3x2DAypdw3ffHYMCTU0Yi+MdgwCGx2Wf4x2DAKjHWrfjHYMDMc4bz+MdgwFpOBDn5x2DAm6yUfvnHYMCTOz/E+cdgwHDqrAn6x2DAEnJPT/rHYMBX52CV+sdgwFSXmdr6x2DAzIZyH/vHYMBB+yxk+8dgwDdr+qj7x2DAhGpP7fvHYMC378kw/MdgwBX1xnP8x2DAfzaPtvzHYMAZWL34/MdgwMgwZTr9x2DADEcDfP3HYMBK0di9/cdgwIYUJgD+x2DAm1UZQ/7HYMA1oqKG/sdgwNMdLsz+x2DADfOiEf/HYMBkkE9Y/8dgwCNwIqD/x2DAJ3cu5//HYMDgGMktAMhgwGk7NnQAyGDAGL1VuQDIYMCFTWr9AMhgwKToCEEByGDARD0/hAHIYMDqH0PHAchgwNz2IQoCyGDAz2/9TALIYMARlcqQAshgwBZIQdUCyGDALk0xGgPIYMC3xwpfA8hgwJWK5qMDyGDAKdzj6APIYMDZqs0tBMhgwMezfHIEyGDAq6K/tgTIYMDJdaP6BMhgwAYSUz4FyGDAlV7IgQXIYMCFyhnFBchgwEEaZQgGyGDACYYuSwbIYMAGaV6NBshgwLvYD9EGyGDA5qR8FAfIYMAr+Z5XB8hgwOsE+ZoHyGDAO7l33wfIYMDVsW8kCMhgwAxcyGgIyGDAuM3ErQjIYMBXZM7yCMhgwCGRmTgJyGDA5r1ZfgnIYMADWePBCchgwMeMaAYKyGDAX2dFSgrIYMDL4qKNCshgwIUmhNAKyGDAm+41EwvIYMCZi9JVC8hgwL08m5gLyGDAPoGl2wvIYMDmrukeDMhgwAgOm2IMyGDAE9VapgzIYMAlhzXqDMhgwCj3rC4NyGDAVDUCcw3IYMB3Mt2zDchgwAHXQvkNyGDAQL1XQQ7IYMCzeIuGDshgwJGHE8wOyGDAWmnjEQ/IYMDzendYD8hgwOmAHZ8PyGDAWPeP5g/IYMCVPYguEMhgwJHVn3YQyGDAzKHLvRDIYMAOETEEEchgwIGmUkoRyGDAOI+hkBHIYMDfXxlSEshgwHBSdhwSyGDAifso6BLIYMBAtWGlEshgwCi5BYATyGDASaBAKhPIYMC1je9tE8hgwI106LETyGDAXXDz9RPIYMAkLf05FMhgwK8ztn4UyGDA0mVMxBTIYMBFoJEKFchgwEab/1AVyGDApWUhmBXIYMA7YTngFchgwKkowigWyGDA0UZPcRbIYMDPrhC6FshgwBxWHQIXyGDAeVOMSRfIYMB3F/aPF8hgwA5Pu9QXyGDAI6tPGBjIYMDgfiJbGMhgwGrTt50YyGDAVstt4BjIYMBknmEjGchgwPctQGcZyGDAa9/1qhnIYMDsaCDwGchgwBXaqjUayGDAlowWfBrIYMCTcqDCGshgwE9XWQgbyGDA1CbxTRvIYMAwIcyUG8hgwOlMudsbyGDAESC3IhzIYMAwUbtpHMhgwKCfxrAcyGDAZZGk9xzIYMAi2NE+HchgwE9k+YUdyGDAlx81zR3IYMDXjVoUHshgwJwaZFseyGDAeYdVoh7IYMC1nibpHshgwFm23y8fyGDACIhcdh/IYMBdlJu8H8hgwBOW/wIgyGDAcuChSSDIYMAt1ZeQIMhgwA725tcgyGDAjfubHyHIYMAsvwZoIchgwDSQNbEhyGDAjNmR+iHIYMAwAfhDIshgwEb+Q40iyGDA+EVj1iLIYMBOfTofI8hgwKp4emcjyGDAsrPhriPIYMCpWRH2I8hgwDy0ST0kyGDAgxawhCTIYMBmEGPMJMhgwPvrXxQlyGDA6fEHXSXIYMCnZJ+mJchgwAVAd/AlyGDAslg3OibIYMD1R7iDJshgwFQU0cwmyGDAlfJIFSfIYMCpVwhdJ8hgwDJDsKMnyGDALWDN6SfIYMC5UVwvKMhgwDRBq3QoyGDANKbcuSjIYMCoUzf/KMhgwE2BJkMpyGDA5sT1hynIYMAOzdTQKchgwF+NFRgqyGDAuARQYCrIYMDxYompKshgwA/b0/MqyGDA99tOPyvIYMA1+DCMK8hgwHpo69kryGDA7CiIJyzIYMAZHaV0LMhgwFyzZsAsyGDA5LrBCi3IYMC4tCdVLchgwJsE050tyGDAyqLB4y3IYMDwLEwpLshgwJyDvm4uyGDAvSyGtC7IYMArVtn6LshgwOHcFUIvyGDArPeciy/IYMCxARnXL8hgwIeEDCMwyGDAywtLbzDIYMDV06S7MMhgwDQpywcxyGDAVDe+UzHIYMDDGzWeMchgwEakxucxyGDAMw3dMDLIYMCOCnd4MshgwE0MQbUyyGDAnrHcCjPIYMCLF3xTM8hgwJ5xmZwzyGDA/eMX5jPIYMDJCsAvNMhgwAbDdnk0yGDAxleQwzTIYMDaayAONchgwNN08Fg1yGDA1gDYozXIYMC+x8DuNchgwJNclzk2yGDAIeU/hDbIYMAP+LTONshgwGxO5Rg3yGDA4nTSYjfIYMAYSUWsN8hgwEEoqfU3yGDAyd6xPjjIYMAGdZuHOMhgwDcAftA4yGDAIgxrGTnIYMDnQG5iOchgwG1yras5yGDAGzo29TnIYMCJugk/OshgwHJSGIk6yGDAGqd00zrIYMCL1gseO8hgwIao82g7yGDAPKPzszvIYMA4YPT+O8hgwL9PN0o8yGDAr/7GlTzIYMBarbLhPMhgwJ505C09yGDAyao4ej3IYMCt9vHGPchgwGTTQBQ+yGDA2mCHYT7IYMAuaj2uPshgwK52L/o+yGDAnrIwRT/IYMDiWUiPP8hgwAz0P9g/yGDAXwBCH0DIYMDbhXxlQMhgwNJ/wKtAyGDAzOiB8kDIYMDC+Rs6QchgwKNfv4JByGDAA8kIzUHIYMB3NaEZQshgwFbhCWhCyGDAFdMct0LIYMBiCc4GQ8hgwAf7kFZDyGDAUe8spkPIYMANGT31Q8hgwFsO8EJEyGDAnTqJj0TIYMDlrKXbRMhgwBg2jidFyGDAMRBBc0XIYMAi9/y+RchgwKZ0xQpGyGDAqrVeV0bIYMCdkW6kRshgwB6sjvFGyGDAE9qePkfIYMAY/YGLR8hgwLouINhHyGDAaL+DJEjIYMCmpjhwSMhgwLTuXLtIyGDAuI5KBknIYMDW0x9RSchgwI0K8JtJyGDAk37b5knIYMDcmwwySshgwKDBkn1KyGDAn8WTyUrIYMAkaAkWS8hgwBis02JLyGDAvCg3sEvIYMDdVfH9S8hgwF+/GkxMyGDAC6OnmkzIYMAfgJfpTMhgwCi6ozhNyGDAzoqqh03IYMCug4PWTchgwCQKJyVOyGDA0u97c07IYMA98FTBTshgwP7ocQ5PyGDApwFeW0/IYMBLnASoT8hgwBSXtvRPyGDAmBl3QVDIYMBkAFGOUMhgwKJVkttQyGDA7fFMKVHIYMC/YSp3UchgwKhx88RRyGDA0JmFElLIYMD3lstfUshgwEE32KxSyGDAru1K+VLIYMDPmQFFU8hgwMhZbJBTyGDAfV/o21PIYMA5Cp0nVMhgwJJYv3NUyGDAb00+wFTIYMCGKYENVchgwDEr2FtVyGDAq9fNqlXIYMAC7A36VchgwO1NY0lWyGDAZKSymFbIYMDxLtnnVshgwGrThDZXyGDAGSedhFfIYMCFQpQ3W8hgwCKpPB9YyGDAsUkLbFjIYMDwDYK4WMhgwD74qwRZyGDAC37XUFnIYMAEddmcWchgwGEWJNhZyGDAnbY4JVrIYMBOyO2AWshgwAKRLs1ayGDApQqPGVvIYMCcovBlW8hgwEdt0rJbyGDAR9EddV/IYMD/kQ5NXMhgwEOmBppcyGDAsoIK51zIYMD0XQE0XchgwOAE64BdyGDAvpiNzV3IYMDbwNwZXshgwIasgGZeyGDAcBWYs17IYMAB1UgBX8hgwAqKmE9fyGDAHedvnl/IYMCMnpTuX8hgwF7wvj9gyGDA5ugWkWDIYMBuykjiYMhgwFshNTNhyGDAIXJlg2HIYMDN30PTYchgwEMyjiFiyGDAP7qXbmLIYMBJSR+7YshgwBBebAdjyGDA9R+5U2PIYMBjs0WgY8hgwNC6Je1jyGDAHKvjOmTIYMAouL2JZMhgwOpLCNlkyGDA71wNKWXIYMC1URd5ZchgwLpNQsllyGDAIxNuGWbIYMCuI1ZpZshgwBHZ0bhmyGDAgY4OCGfIYMB+5vxWZ8hgwG8GxaVnyGDAH21U9GfIYMAf1cJCaMhgwIo1E5FoyGDAemdN32jIYMAyRIAtachgwM5wsHtpyGDABm/lyWnIYMCdWSYYashgwG5ud2ZqyGDAeC/htGrIYMDrqH4Da8hgwOXJIFJryGDADYygoGvIYMCaavHua8hgwDN5/DxsyGDAb/PTimzIYMBIll3YbMhgwPlZQyVtyGDA80L9cW3IYMBxWb6+bchgwO7PsAtuyGDAaRnxWG7IYMA/U36mbshgwGfVgvRuyGDAAXY+Q2/IYMCWh4uSb8hgwDlr6+FvyGDAiFBMMXDIYMCLhpCAcMhgwGoIgc9wyGDAR/kJHnHIYMBO4r9rcchgwK4q57hxyGDA/Dh6BXLIYMAYl8BRcshgwFwhpZ1yyGDArpFL6XLIYMAHSsg0c8hgwE2PW4BzyGDAmiUHzHPIYMBrKqAXdMhgwLYDKmN0yGDAfXijrnTIYMBzFxr6dMhgwE55o0V1yGDAsXz6kHXIYMAkDTrcdchgwK0N6Cd2yGDAwewkdHbIYMA2Xx3BdshgwESsyA53yGDA5fdcXXfIYMBW6vCsd8hgwJHKmP13yGDARU2OTnjIYMDdDYOfeMhgwHeWR/B4yGDABYE1QXnIYMBT7yWQechgwCPJ4PN5yGDAmUsOLnrIYMC1aj0VfMhgwBy3Nll8yGDAmHMUEnvIYMB4KAxde8hgwOGQ96d7yGDAbJzd8nvIYMAJLe49fMhgwDqJRIl8yGDAi/sb1XzIYMDp+mohfchgwAd0NW59yGDAuuuGu33IYMAedsIJfshgwGmv3lh+yGDAJeg0qH7IYMCSsXL3fshgwAOuXEZ/yGDA2YG/lH/IYMDCI5Lif8hgwAFyWS+AyGDACwXaeoDIYMAaDX3FgMhgwNSmtg+ByGDAWUImWoHIYMBZg+qkgchgwCJ12O+ByGDAJ6V8O4LIYMCGBzKIgshgwFjXmdWCyGDA/g8bI4PIYMCZi4Jwg8hgwM2Ri72DyGDAbYAzCoTIYMDNBi5WhMhgwKQe4qCEyGDANPnQ6oTIYMDHiJg0hchgwDQlf36FyGDATBbTyIXIYMCEK5sThshgwOyYGF+GyGDAvT/sq4bIYMDH2Dj6hshgwMHENEiHyGDAG611lYfIYMB8/Cbih8hgwOyi4y2IyGDAd09weYjIYMCpacXDiMhgwNz+ZA2JyGDAOmGjVonIYMCiTZ+fichgwCums+iJyGDAbwsTMorIYMAlyt17ishgwO7MqcaKyGDA5y2yEovIYMBO6s9ei8hgwFPF5qqLyGDAJYTn9ovIYMD2oiVCjMhgwJ0o1YyMyGDAkhtK1ozIYMCJjrcejchgwE/7fWaNyGDAfgAnro3IYMAvvL31jchgwIJZbj2OyGDAs0dihY7IYMCW5xnOjshgwO5AAhiPyGDA9XUQY4/IYMCpND2uj8hgwC4+b/mPyGDACi9ORJDIYMCxN4WPkMhgwADCmtuQyGDAbnm9J5HIYMDNDHZzkchgwKmrEb+RyGDAdIavCpLIYMAtQG9WkshgwD6GGKGSyGDAO21c65LIYMCHIDY1k8hgwEaGZn6TyGDA0OMjx5PIYMAzLJoPlMhgwIvrxFeUyGDAtaePn5TIYMAwmHrnlMhgwCvZzi6VyGDAuCRRdpXIYMDaGp29lchgwAKAqQSWyGDA7bxwS5bIYMDCSA6SlshgwKEcQNiWyGDA8uciHpfIYMAfAf1jl8hgwJwQP6qXyGDA3VMv8ZfIYMD7NFo6mMhgwDNJuYOYyGDA79HJzZjIYMCn6XwYmchgwGKsH2SZyGDAvp9DsJnIYMBy2L35mchgwANFRUWayGDAp1GDkprIYMA+g5LcmshgwBdyAiWbyGDANWTtbJvIYMC8M7izm8hgwCjosfmbyGDAJ0d/PpzIYMDhwYyCnMhgwNTwx8WcyGDAPBYwCJ3IYMBATKlLnchgwB4sMY6dyGDAbfVfypvIYMCkhxQVnshgwN96+1qeyGDAlBWkop7IYMCmqBnqnshgwK5+szOfyGDAiIM6fZ/IYMC42HrGn8hgwKetDRCgyGDAqxx/WaDIYMB5ifKhoMhgwNeNkOigyGDAWtOYLaHIYMBMvLRxochgwLCCmrShyGDADp2586HIYMA832U0oshgwHqF3XWiyGDA2kppt6LIYMDtwr35oshgwCSqODyjyGDAXwtLf6PIYMDnGKjCo8hgwAPo+QakyGDANMRiS6TIYMDxt7KOpMhgwOfOh9GkyGDAmchVEqXIYMCznnRSpchgwBnETJSlyGDA1Ka31qXIYMAZuHAZpshgwKJUpVmmyGDAXbnamKbIYMDJrsTbpshgwHpQWh6nyGDA1zZVYafIYMBtA72kp8hgwPcvyOinyGDA9CSRLajIYMCBIuJyqMhgwNbUsLeoyGDAf17e+qjIYMC5zQhAqchgwH+T9oSpyGDAT+AyyanIYMD5BMkMqshgwCeqcU+qyGDAeiYzkarIYMBgME3SqshgwMahkxKryGDAgrdgUqvIYMCmybKRq8hgwHTTrNCryGDAjaxRD6zIYMCDSedNrMhgwO2c7YysyGDAP1qgzKzIYMDNhQsNrchgwHDUbk6tyGDAfuCjkK3IYMBe7aHUrchgwMsTbxmuyGDATRfFXq7IYMAIWWekrshgwLDQAuquyGDAaA59L6/IYMD4F450r8hgwMaOz7ivyGDAHfhU/K/IYMBMwi4/sMhgwByrdYGwyGDATys2w7DIYMCd9JIEschgwCa6bEWxyGDAsOv5hbHIYMC+qjHGschgwCnugwayyGDABlgMR7LIYMC86PeHsshgwERRIMmyyGDAHFfCCrPIYMDvDQdNs8hgwKQfQZCzyGDA530807PIYMBZK8YVtMhgwJrFjle0yGDAt0ozSbHIYMC8cWPYtMhgwLYF8xa1yGDA+KYAU7XIYMDis0tGsshgwDLBS8y1yGDAzR03CbbIYMAqUQBHtshgwIoWc0ezyGDATUurxrbIYMCUMU8Jt8hgwEDrhg+0yGDAgeU2xLfIYMCRhEHVt8hgwGd/Nxm4yGDAgRWZXLjIYMDzaMqeuMhgwMLBI9+4yGDA6IC9HrnIYMDBanZduchgwFlKp5u5yGDAQUF+2bnIYMDAXyUXushgwEtT6FS6yGDAqzUSk7rIYMAq8pDRushgwPNEZRC7yGDArA+0T7vIYMBA24GPu8hgwCo3qs+7yGDAxEdTELzIYMAgbnxRvMhgwL1U75K8yGDADa0w1LzIYMDQdF8WvchgwDyOH1i9yGDAu2flmb3IYMD9b13bvchgwO8HoRy+yGDA7HNsXb7IYMAkBxaevshgwJMqSd6+yGDABUQlHr/IYMDMz65dv8hgwGCx1py/yGDAj+yv27/IYMAQIEgawMhgwNCtwljAyGDA7VYul8DIYMB8nJzVwMhgwOa0JRTByGDAyNfGUsHIYMBNvbORwchgwKrvytDByGDA098vEMLIYMCpd6VPwshgwGYwMI/CyGDAlMh6z8LIYMCBvKD8wshgwLpyF1bAyGDAqXFEjcPIYMBk0TTNw8hgwHFZTwrEyGDA6CA7SsTIYMAW98KMxMhgwCTC18fEyGDAsZ28EMXIYMCVjPVSxchgwHGr9JTFyGDAgFtU1sXIYMC1MKIww8hgwJQ37VbGyGDAlL1MlsbIYMCnTa/4w8hgwGZQrxDHyGDAdQC2TMfIYMCFrnWIx8hgwJ8XOMTHyGDAbiNDAMjIYMB9+ag8yMhgwI+b+nnIyGDAub9auMjIYMCKJHP3yMhgwD8pNjfJyGDAwAKNd8nIYMDLBXO4ychgwCDVk/nJyGDAhKlqO8rIYMDLQ0WEyshgwNg2ktDKyGDAmMuJFcvIYMCebVFEy8hgwNgwUYXLyGDAyoElxsvIYMDbqk0GzMhgwPKCRrfJyGDAosfzhMzIYMDcsqjDzMhgwNAa4QLNyGDAl75vQs3IYMBRneiBzchgwJGTVsDNyGDAfolaAM7IYMBZ001AzshgwFo/BoDOyGDAfRTkw87IYMBQ2k8Dz8hgwLkdEf7MyGDAXJ6Og8/IYMC/KS3Bz8hgwE9cIv/PyGDAQXKwYNDIYMBF8+ae0MhgwKQmoMLQyGDArq4n7dDIYMAZRBBI0chgwOq+T4rRyGDAnvk3ws/IYMBy9lsT0shgwHjvtlfSyGDARWX2nNLIYMBgUBTf0shgwJ/npyHTyGDA1ZSnZNPIYMBOaDOm08hgwNizJuXTyGDAbV+9IdTIYMC4V1tg1MhgwJ2/UZ/UyGDANter3tTIYMDK05Qd1chgwPSZt5zTyGDATNunotXIYMA00uht1MhgwF0waLXUyGDAF5Dc/NTIYMApC1VE1chgwOlcp4zVyGDAIVhx1dXIYMAdQygf1shgwPeww2jWyGDAHnfSTNjIYMAWe7iO2MhgwDGA0M7YyGDAKXT0jNfIYMCx40TU18hgwAZUeBrYyGDAJ8D/XtjIYMCBdgSj2MhgwOwhf+XYyGDA3pyhJtnIYMC7vonW2shgwOLDAh3byGDA4lO27NnIYMCzpNWp28hgwHib+u7byGDAwCqLM9zIYMADbCd13MhgwOt7HFjbyGDAzK4DpNvIYMAoYxjv28hgwCEswTncyGDAnJh8g9zIYMD56Inp3chgwO01Cw7dyGDA51vZaN7IYMAdwjuq3shgwCflzOveyGDA4vb0Ld/IYMDNHrRw38hgwEg1PbTfyGDAzWFm+N/IYMAjnc474MhgwLmKfn/gyGDAp1HmwuDIYMDMG3IF4chgwJqJu0XhyGDAc0YAhuHIYMD9QInG4chgwC4fKzXhyGDAmlT2duHIYMDu/SOB4shgwGLiRMHiyGDAjPBj/OLIYMCPXkk848hgwNQXDX3jyGDAKuXRuuPIYMBF1Hf548hgwO81ZDvkyGDAMawJfOTIYMDUI0q85MhgwJALn/zkyGDAP3UDPeXIYMB06Lh95chgwKOLZ7vlyGDAcwZt+eXIYMCL1hI65shgwMeRSXvmyGDApxq8vObIYMD+L/f+5shgwI1QYELnyGDAzJqWhufIYMA9GCDL58hgwHT85A/oyGDA7O6SVOjIYMAY0diY6MhgwBA0t9zoyGDAeGfmH+nIYMDYh/9h6chgwPjVtqTpyGDAEsCM4+nIYMBJqyYk6shgwJMSRWPqyGDAvVnCoerIYMBgVt7g6shgwEnAmR/ryGDA7DASX+vIYMAF88+c68hgwDXvKOHryGDAj51vH+zIYMB0BlVj7MhgwLQ/k6/syGDAa2h9+uzIYMDDTX5D7chgwGSA0IvtyGDA+V8+1O3IYMBafjob7shgwLd1J2TuyGDAwjwVrO7IYMCLyUvy7shgwDCevDbvyGDAW55ue+/IYMA7pGS/78hgwKnqAAPwyGDAsmtjRvDIYMAW09SJ8MhgwMCQzCzxyGDAQoNKEfHIYMD8xgVV8chgwAAXYJjxyGDAuvF/3PHIYMC9qQ0h8shgwBwD9mTyyGDAgCftqPLIYMCbWvLs8shgwP5lXDHzyGDA3+3AdfPIYMAAkYG688hgwPqHn//zyGDAYgN6PvTIYMAKwPiF9MhgwJySVMr0yGDAnYrtDvXIYMBTYcRT9chgwPsC+5j1yGDANH6s3vXIYMAEmq0k9shgwPAOVmv2yGDA6YpUsvbIYMBGhXj59shgwC7Lu0D3yGDA76j7h/fIYMBWviDP98hgwI3AFRb4yGDAFSO5XPjIYMAdhQOj+MhgwDYsFun4yGDA+EErLfnIYMC+ewdy+chgwApmAbr5yGDAo6NY//nIYMAB3ZJE+shgwBV6xYn6yGDANywVz/rIYMCD/YIU+8hgwG8MJVr7yGDApWcBoPvIYMBJzCXm+8hgwBtIpyz8yGDAgbiec/zIYMBFo666/MhgwCbawQH9yGDAp2HHSP3IYMCRwLiP/chgwJQ1odb9yGDAESohHf7IYMDwL0pj/shgwMeqehEAyWDAaF9w8P7IYMAO7q83/8hgwGKapn//yGDAvHgEyP/IYMACN54RAMlgwJ2U81sAyWDAoyGxpgDJYMDu2HbxAMlgwD98HzwByWDA9itkhgHJYMCHkBPQAclgwPjbAhkCyWDAXkUfYQLJYMBwN2WoAslgwCxa5O4CyWDAyGXjNAPJYMAHIEt6A8lgwF21ir8DyWDAmIldBATJYMA3fgJJBMlgwIy98o0EyWDAW0ub0wTJYMA3rDYaBclgwBi+l2EFyWDA1CEmqgXJYMBH+eDzBclgwIPmij8GyWDAkMrWiwbJYMCIKojYBslgwLFcWiUHyWDAknH7cQfJYMAkKi2+B8lgwOffegkIyWDAZnGXUwjJYMDXmsOcCMlgwKFL5OQIyWDAYxQRLAnJYMDPYVFyCclgwDxF77cJyWDAQQz1/AnJYMAsnGVBCslgwJgasoUKyWDAgww+ygrJYMAGlTwPC8lgwKkM+VQLyWDA9pF8mwvJYMDUEQPjC8lgwGbWBywMyWDAd/0RdgzJYMBvnfrADMlgwDELgAwNyWDA/HhrWA3JYMAmU7akDclgwIZJFvENyWDACzYrPQ7JYMAGu/yIDslgwA8JmdQOyWDAWBbxHw/JYMDvkAFrD8lgwKc+tLUPyWDAQe8UABDJYMA+LFdKEMlgwJnkYZQQyWDALQbr3RDJYMDQCuEmEclgwMxqVm8RyWDA491HtxHJYMA4Qwf8EclgwHbjI0MSyWDAZMP1ixLJYMAjU4vSEslgwABPyRkTyWDAwnTRYRPJYMDWtPGqE8lgwGMEBvUTyWDAG4EyQRTJYMCpJ82OFMlgwLrNut0UyWDAPj2eLBXJYMDBaSt7FclgwDF+TskVyWDA2Q2rFhbJYMAchZtiFslgwOwUJq0WyWDApRzT9hbJYMCO1NQ/F8lgwA4LiYgXyWDABm7i0BfJYMCTyC4ZGMlgwCiP42EYyWDA76hDqxjJYMBIZ9D0GMlgwC+pcT4ZyWDA1tUmiBnJYMBkaOfRGclgwPDOvBsayWDA2EZLZRrJYMByY3KuGslgwFHluvcayWDA/YxSQRvJYMA86XOLG8lgwOy9G9YbyWDAENlxIRzJYMBb3a1tHMlgwMCzDLscyWDADzbdCB3JYMAJKp9WHclgwHI2CaQdyWDAQx/r8B3JYMCq+Q49HslgwOKyD4geyWDAJJim0R7JYMC7BmIaH8lgwBes5mIfyWDA25eQqx/JYMBGxYD0H8lgwFNObz4gyWDAv/xeiSDJYMBwiPnVIMlgwAOHiSMhyWDA1XZicSHJYMDoRD2/IclgwDCw8AwiyWDA++NsWiLJYMCEw1mnIslgwBe8SfMiyWDA7/k0PiPJYMAJeLqII8lgwIF9+9IjyWDA1o0RHSTJYMCQdDVnJMlgwNiokLEkyWDA4v1i/CTJYMDQHJhHJclgwB6TKZMlyWDATJ4M3yXJYMC/+iErJslgwGrLYXcmyWDAiiK1wybJYMBWziEQJ8lgwJ1iylwnyWDAsD1RqSfJYMBo6XT1J8lgwILAD0EoyWDA6AQIjCjJYMCCRG3WKMlgwGv8+R8pyWDA0KS7aCnJYMAOYW6xKclgwPkJOfopyWDAqRA3QyrJYMBQ15CMKslgwEhQRtYqyWDA0/zKICvJYMAI5ztsK8lgwAcR/rcryWDAbcZ1BCzJYMAf9TxQLMlgwLOsV5EuyWDAKOBm6CzJYMBXPbozLclgwCBiqn4tyWDAYHDeyS3JYMDuWT4VLslgwIei/WAuyWDA/9JNrS7JYMDJHwj6LslgwDiLXEgvyWDAMLj/ly/JYMA4CxXoL8lgwKvcTjYwyWDAbDDZhDDJYMDMS2bRMMlgwBZeAR4xyWDAqmaiaDHJYMBsrRSxMclgwPrsh/gxyWDAs7d/PzLJYMCTzWSGMslgwJyRn80yyWDAqwJpFTPJYMCyh3deM8lgwO67JakzyWDAs3z/9DPJYMBQoHdBNMlgwCFkfo40yWDAiRrC2zTJYMB19zUpNclgwFylaXY1yWDAjiwWwzXJYMAkXGYPNslgwPGOkVs2yWDAB4CRpzbJYMBbnmfzNslgwKCGKz83yWDA7AkFizfJYMCAbBLXN8lgwGVlNSM4yWDAtZVJbzjJYMD2a0K7OMlgwI5qBQc5yWDAUZSPUjnJYMCa4sadOclgwEALuOg5yWDALW5iMzrJYMA5ptV9OslgwGldDsg6yWDAF/oYEjvJYMCNGwBcO8lgwKN116U7yWDAgUyd7zvJYMAE+GQ5PMlgwBtvfIM8yWDAdbruzTzJYMBdju0YPclgwMAblmQ9yWDAgovJsD3JYMD4Y5P9PclgwOcHAks+yWDAm0nnmD7JYMAlCjTnPslgwKaHzDU/yWDAAr1rhD/JYMCTItHSP8lgwMdYxyBAyWDAqw4bb0DJYMDqnZq8QMlgwPdKOAlByWDAyK/oVEHJYMDdd1GfQclgwBMjquhByWDAb5NoMELJYMAFF2t2QslgwBx09rtCyWDADJOBAUPJYMCwoXVHQ8lgwAgpFI5DyWDARKSH1UPJYMDhRzAfRMlgwJuyP2pEyWDAnB6ntkTJYMA+hr8DRclgwMLdWVFFyWDA2ggxn0XJYMAGgv7sRclgwDHZXjpGyWDANrjPhkbJYMDMX8HSRslgwAkdTB5HyWDAVL9PaUfJYMAYCQK0R8lgwKArUP5HyWDA0K5+SEjJYMD2EaGSSMlgwPxqldxIyWDA9otbJknJYMDi2eRvSclgwL1pO7lJyWDAPupNAkrJYMDkGH5LSslgwKrILJRKyWDA32bT3ErJYMDtoJclS8lgwCPWgm5LyWDAKwuxt0vJYMCuEyQBTMlgwKc8/UpMyWDAo3ZklUzJYMDHkRjgTMlgwMqT3CpNyWDAB32MdU3JYMAqlhDATclgwFZ7UApOyWDAV5QrVE7JYMDZ8mydTslgwCZUFuZOyWDAccu3Lk/JYMANNGl3T8lgwJ3AVMBPyWDAJKRyCVDJYMAeC+tSUMlgwOMVFJ1QyWDAoCXP51DJYMAgXlkyUclgwOCaUnxRyWDAalmUxVHJYMBhKAIOUslgwA8Cf1VSyWDAvk98m1LJYMBIshLgUslgwClbGSRTyWDAJQDUZ1PJYMDMio+rU8lgwLh7sO9TyWDA5lk8NFTJYMABRrF5VMlgwKrxXsBUyWDAYBDBB1XJYMD6TdJPVclgwHCweJhVyWDAV7aX4VXJYMCwjCYrVslgwOhc2XRWyWDAoGaTvlbJYMC+kVwIV8lgwKvBJFJXyWDAvjbZm1fJYMCTzWXlV8lgwDR3uC5YyWDAqkLEd1jJYMDAinDAWMlgwMgsyQhZyWDAdsTAUFnJYMCeQ12YWclgwKogmN9ZyWDAXFBlJlrJYMDxTvRsWslgwIolZbNayWDAO/9f+VrJYMC/IMA+W8lgwDcuhYNbyWDA7muXx1vJYMCBlE4LXMlgwD6TKU5cyWDAQVwDkFzJYMDjzvnRXMlgwL+XhBRdyWDANvUlWF3JYMCvaiCdXclgwNpHMONdyWDAOyoZK17JYMBnbs91XslgwF0ZqMFeyWDAzwy0DV/JYMCMsGlZX8lgwKw5QaRfyWDANKgd7l/JYMDlUyM2YMlgwA3qG3tgyWDAjzwyvmDJYMAfn0cAYclgwMO1t0FhyWDAhkflgmHJYMDp0w/EYclgwAkbtgViyWDAIPEvSWLJYMDF7YSNYslgwOEeQ9JiyWDA1ic2F2PJYMCeezZcY8lgwNLmJ6FjyWDAKd/l5WPJYMAO2bgpZMlgwBvx9WxkyWDAq7BjsGTJYMC99Cz0ZMlgwN/BmThlyWDAF5mlfWXJYMAKxUTEZclgwBV/4GpkyWDA2RD6rGTJYMBz03edZslgwCDfiOZmyWDADSRDL2fJYMDS0oV3Z8lgwHNY975nyWDAx0xfBWjJYMCfr7NKaMlgwHkcQY9oyWDAYH4t02jJYMCp+pQWaclgwAOGm1lpyWDAuU9dnGnJYMBDehXfaclgwK4m5yFqyWDA/s/fZGrJYMAbZweoaslgwAVpY+tqyWDACSMHL2vJYMDdOftya8lgwHDUXLdryWDAHm4u/GvJYMD4/ixBbMlgwBfxMYZsyWDA7ngky2zJYMA9Ee4PbclgwBPOfFRtyWDA9sitmG3JYMDi02/cbclgwOmzOiBuyWDA9JIxZG7JYMAXoGKobslgwDKP1+xuyWDAdBaGMW/JYMDZ8u92b8lgwLRsVL1vyWDA7jXJA3DJYMCYNeBJcMlgwKV/YY9wyWDAmcUf1HDJYMDlFgMYcclgwMeGkFpxyWDAfVtam3HJYMBJj0LbcclgwKTH4BpyyWDARm18WnLJYMA0o5yacslgwI8Ed9tyyWDAhDaEHXPJYMCh7A9hc8lgwOf9q6VzyWDAvk8m63PJYMA9QCAxdMlgwEtjZXd0yWDATg+zvXTJYMDRQdYDdclgwOmTqEl1yWDAEkftjnXJYMBMZ3jTdclgwDKLIRd2yWDAU/riWXbJYMBP082bdslgwBG0tNx2yWDA1DpVHHfJYMDMLRBbd8lgwOxS1Zl3yWDAN8fv2HfJYMD0hZsYeMlgwL6iVFl4yWDA8KDWmnjJYMD8sY7eeMlgwLB2qyN5yWDAOnEEz3fJYMC8EPuteclgwONP3/J5yWDAbpDTNnrJYMCJH5N5eslgwEHwTrp6yWDAv6gA+XrJYMAL5n43e8lgwILnPXZ7yWDAyBOktXvJYMCg4Av2e8lgwMiKuTd8yWDAwZW2e3zJYMCYpVzCfMlgwM5Lrwl9yWDACI40UX3JYMAl3mmYfclgwN8M5959yWDAkvRUJH7JYMCJActnfslgwN0KnKh+yWDAh0R86H7JYMCg4twnf8lgwMf1B2d/yWDA59Jdpn/JYMB64g3mf8lgwJF/9iaAyWDA1U9iaYDJYMAnBoKsgMlgwPQZ+u+AyWDAfpqVM4HJYMC65Ct3gclgwH4hw7qByWDAp/uq/YHJYMBbWpM/gslgwHz9f4GCyWDAOibLw4LJYMAEu7MGg8lgwKDPRUqDyWDA/HHTjoPJYMDIN9/Ug8lgwDtHKxyEyWDAxk1GZITJYMAxwmushMlgwNc6gfSEyWDAqvNKOYXJYMAk/XJ9hclgwOoLd8CFyWDAJRTjAIbJYMAycuQ/hslgwGLYyH2GyWDAn7TuuobJYMD4ugz4hslgwP15azWHyWDAnmKGcofJYMBZLSqxh8lgwBcAs/KHyWDA8xnhM4jJYMDBVx92iMlgwMAGfLmIyWDAqNvY/YjJYMDDZjdDiclgwClLZomJyWDAYUlX0InJYMCXTtAXislgwLKfmV+KyWDA2NKOp4rJYMAHy3zvislgwLjuNDeLyWDARMyQfovJYMCUNnHFi8lgwBtTlguMyWDAGd/mUIzJYMD022CVjMlgwOxUztiMyWDAXwS9G43JYMBHxd5cjclgwA+oyZ2NyWDAg2l73o3JYMA7yccejslgwBzAIl+OyWDAStKSn47JYMAf3BbgjslgwGO9aCGPyWDARuoMY4/JYMAsGVGlj8lgwMeIkOiPyWDASMXcLJDJYMDwNPhxkMlgwJG1EriQyWDAHP8m/5DJYMDUhS1HkclgwElnfo+RyWDA3j2c15HJYMClRmUfkslgwK3vR2aSyWDALLqVrJLJYMBINj3xkslgwGcUYTSTyWDAF08MeZPJYMBMqU+7k8lgwM2OR/yTyWDAkqEiO5TJYMCk7Jt8lMlgwNS4776UyWDAAplzApXJYMC90JdGlclgwEA33oqVyWDAJx0Oz5XJYMDNIqcTlslgwJtuZliWyWDAFpQWnZbJYMAYsnnhlslgwEWW2iWXyWDAg0duapfJYMCPRVOvl8lgwBTRl/SXyWDA+DBCOpjJYMD/J6+AmMlgwJzwWMeYyWDAjTMRD5nJYMDEv9NWmclgwPH8pZ6ZyWDAeSMD55nJYMBB53svmslgwGpTW3iayWDAa3NpwZrJYMAr0+wJm8lgwH84KFKbyWDAoR/omZvJYMAL64Hgm8lgwE1jTyacyWDA3Umaa5zJYMDz/u+unMlgwNSARPGcyWDAP96IM53JYMCJqph1nclgwLGIUridyWDAaxSq+53JYMCAgug/nslgwM9DOIaeyWDAUVh0zZ7JYMAOS2IVn8lgwC0q0l2fyWDA5Mdgpp/JYMDLlQ7vn8lgwLFQNzegyWDACg0VfqDJYMAhty/EoMlgwJ3magqhyWDAxFDKUKHJYMBF2WKXoclgwJwCd96hyWDAnCflJaLJYMCfq8VuoslgwAXgjbiiyWDA9SVgAqPJYMCAC/xLo8lgwK/BF5WjyWDApb6f3aPJYMBF0mklpMlgwBAQ9mukyWDATFU6saTJYMA0VRn2pMlgwPRy3jqlyWDA5tXBf6XJYMB6mAXFpclgwNUbzgqmyWDAt3ynUabJYMBFI7SZpslgwAzNnuKmyWDAiIxHLKfJYMA+OoV2p8lgwPAuRMGnyWDAooBiDKjJYMBOoaRXqMlgwKM1w6KoyWDA213P7ajJYMCcLd84qclgwNUTsYOpyWDAuVg5zqnJYMBA1WYYqslgwOoAOWKqyWDATOB5q6rJYMAmU1D0qslgwDQ+tzyryWDA+hu2hKvJYMC5htnMq8lgwCR+IBSsyWDA189nW6zJYMDbfZSirMlgwCior+msyWDArCvUMK3JYMCudyl4rclgwNgQvL+tyWDAdJ2VB67JYMDySuNPrslgwGmovZiuyWDAEqpQ4q7JYMB26oosr8lgwNkzR3avyWDAVlj6wK/JYMBmPCEMsMlgwEGIhFewyWDAit8co7DJYMCq0PLusMlgwNWi8zqxyWDAK10Hh7HJYMAnkx3TsclgwEEuTh+yyWDARylza7LJYMBs8X+3sslgwCYhXgOzyWDAp0oQT7PJYMAnhIqas8lgwICCauWzyWDAzWTIL7TJYMBxhZR5tMlgwKlKBcO0yWDADTIkDLXJYMDZ0bRUtclgwF4ii5y1yWDAsAHL47XJYMBpYq8qtslgwEK3T3G2yWDAGuUdt7bJYMAvVan8tslgwPEZEEO3yWDATtW8irfJYMBNCgfUt8lgwJspB2e7yWDA7UiYa7jJYMAA8i+7uMlgwMwvNg25yWDA2F3ZX7nJYMBUvISyuclgwMUHmQS6yWDAM8RCVbrJYMD/zWKkuslgwCOMmvC6yWDAl62bObvJYMBKuhaBu8lgwFKJRMe7yWDAvujiDLzJYMC7qlhSvMlgwL54FZi8yWDAo74B37zJYMBTgIAnvclgwJ6UFXG9yWDA+Aifu73JYMA6BhAHvslgwCygblO+yWDALNjioL7JYMCqqObuvslgwFizhT2/yWDAH22HjL/JYMB2ItXbv8lgwE0dPCvAyWDAvSatesDJYMBHohp3xMlgwIvuWBnByWDAm+D8Z8HJYMDWJyq2wclgwMLm4wPCyWDAqjYLUcLJYMAsNeidwslgwNZhKenCyWDAtHKvM8PJYMBU1IWAw8lgwG0D/8vDyWDADL132MfJYMCwX+tgxMlgwG5/9KrEyWDA9+Te9MTJYMCNe3U1xclgwBxS837FyWDAh5xn0cXJYMCRkX8bxslgwP4onWbGyWDA+BezssbJYMC+UwoAx8lgwP5Thk7HyWDAsjyPn8fJYMAf3i/yx8lgwFvbkkbIyWDALqvImcjJYMAYsiTsyMlgwOpgjD/JyWDAZ86CkcnJYMBrUuDkyclgwKmp6TTKyWDAAEaYgsrJYMAdSjXRyslgwNuXMx3LyWDAMcdIa8vJYMBsc8i2y8lgwAvlugfMyWDALwBAVszJYMCIEdqkzMlgwFBgzvPMyWDAHXiNQc3JYMBnrhORzclgwDxgQ+DNyWDA13SFLc7JYMClaK+O0slgwOfQbsXOyWDA9viJEM/JYMA2rptcz8lgwMB14qjPyWDAZHxB9c/JYMBJkaJB0MlgwCQsaI7QyWDApi/W29DJYMA27AUp0clgwFPv4XXRyWDAt/a/xNHJYMBI9AMT0slgwNpvVGTSyWDApm5WtNLJYMDdP3QE08lgwIr3DFfTyWDAdlWuqNPJYMCxlNb408lgwNj7iknUyWDAvrz+mNTJYMBu4Pof2clgwCkiwy3VyWDAfvfWedXJYMBAUtvF1clgwEDwDxLWyWDAycyqXtbJYMCzQzGs1slgwE49IvvWyWDAchTJStfJYMBLWhSb18lgwMPAzevXyWDAm+HEPNjJYMDuM+2N2MlgwPXG8t7YyWDAB8GaL9nJYMBYd5HL3clgwG10uBveyWDASbKHINrJYMA+tplw2slgwBaHicDayWDAbyZsENvJYMDl1z5g28lgwDvcBLDbyWDA5YfG/9vJYMAXhHVP3MlgwBW8J5/cyWDAvpjM7tzJYMAhSm4+3clgwKdmhordyWDAYYqi2t3JYMBif6Mt3slgwBxiwHzeyWDAmY55y97JYMCulOMZ38lgwHkj2mffyWDAFDr9tN/JYMClnsAB4MlgwCZebEvgyWDAFp97meDJYMDh0SDr4MlgwA35izrhyWDAF9dHi+HJYMAJXnHd4clgwG3IFjHiyWDALjtNheLJYMDg59nZ4slgwHOHZS7jyWDAEEetguPJYMBgZXfW48lgwLhPKSnkyWDAqh3ZeuTJYMC0QX3L5MlgwJpHbRvlyWDADEloauXJYMDOBL+45clgwF8gbwbmyWDAf8OyU+bJYMA2Ysmg5slgwENamu3myWDAfUpROufJYMBU6xSH58lgwH1XB9TnyWDA4ENUIejJYMBBUeFu6MlgwPJawbzoyWDAhQFrC+nJYMDvRP1a6clgwBuptavpyWDAyL1N/enJYMAScvpP6slgwCaw3aPqyWDA6J0P+erJYMDtoY5O68lgwFYO7qPryWDAdhS5+OvJYMB8T65M7MlgwADX0Z/syWDAzLIa8ezJYMD1b9BA7clgwHXcM4/tyWDA9xne3O3JYMAdAxoq7slgwKMvG3fuyWDASpkuxO7JYMDdG7gR78lgwAplBmDvyWDA2Rn3ru/JYMAg6mj+78lgwC7eUU7wyWDAnxepnvDJYMAuM0zv8MlgwLMgQEDxyWDAsXRokfHJYMA7fK/i8clgwFeu/jPyyWDAUy1KhfLJYMCaj4DW8slgwHs3rifzyWDANieYePPJYMDMlx3J88lgwCWTkRn0yWDAVeEsavTJYMASdfu69MlgwCJ+zm34yWDAlzHsXfXJYMAw5f2v9clgwCTF6gL2yWDAE0BDVvbJYMBhHWip9slgwD4OB/z2yWDA7wjvTffJYMDhVQSf98lgwM+Wle73yWDAL2SXPfjJYMDGONKK+MlgwEaPldf4yWDAhBg8JPnJYMAZiANx+clgwP3pLL75yWDAkhQxDPrJYMDH4whb+slgwP+pZav6yWDAWQRI/PrJYMA6AqlN+8lgwE0WW5/7yWDAtfox8fvJYMBx2xND/MlgwKmKkJT8yWDACVh75fzJYMA0X1k2/clgwIUEP4f9yWDAtxQx2P3JYMCUeTop/slgwHh2U3r+yWDArpvXy/7JYMBNWdYd/8lgwHOEnW//yWDAYDYBwf/JYMCc780RAMpgwOl4E2IAymDAOgOQsQDKYMBeWgIAAcpgwIb3aU0BymDAchdQmgHKYMCCPijnAcpgwHXUMDQCymDA7PiggQLKYMDypW3PAspgwKKZZR4DymDAmuaxbgPKYMCtIXu/A8pgwMSHgxAEymDAsKOnYQTKYMBFRKayBMpgwPdfZgMFymDAGLKDUwXKYMB3ArSiBcpgwAiTVPEFymDANdSZPwbKYMByxZaNBspgwLbIf9sGymDAPM1NKQfKYMCDZSZ3B8pgwGJTK8UHymDAHPpgEwjKYMBQQJxhCMpgwORk868IymDAPYuj/gjKYMCjfy5NCcpgwCiEv5sJymDAs7eY6gnKYMCXNEg5CspgwKnMjYcKymDA1TxC1QrKYMDySWoiC8pgwEN6AG8LymDAmIr1ugvKYMBoK5IFDMpgwLRIqk8MymDAwOkymgzKYMDZmYXlDMpgwDn16TENymDAoWWOfw3KYMC8o5LODcpgwO5y8x8OymDAPH8fcw7KYMA6Ro7GDspgwCnT1RkPymDAhUJObA/KYMDpFsi9D8pgwIwTEw4QymDALqNbWxDKYMDc7numEMpgwNvTOfAQymDAgd3sOBHKYMCjadGAEcpgwNZhTcgRymDAb2OYDxLKYMCZr3tXEspgwHlYGKASymDANBIy6RLKYMDUPN0yE8pgwFmJGH0TymDA+bf1xxPKYMCrN2YTFMpgwPdsRl8UymDAZdiRqxTKYMD+BmL4FMpgwBZTtkUVymDAtOSHkxXKYMBU97DhFcpgwEtxODAWymDAzeEIfxbKYMCxoRLOFspgwMsBFx0XymDAZ93saxfKYMCGP3W6F8pgwAT4jggYymDAN9okVhjKYMCwAyKjGMpgwO78ie8YymDAi3xTNhnKYMBnd0N+GcpgwAVijs4ZymDAshx9GhrKYMDFsehjGspgwMdJyqwaymDAWmwv9RrKYMDcJow9G8pgwDolUIYbymDAHGuYzxvKYMBrnq8ZHMpgwNh0dmQcymDAyi1psBzKYMA42dL9HMpgwAI6+0sdymDA/YSEmh3KYMBzrR/pHcpgwPP6jDceymDAqq2qhR7KYMDlB/3SHspgwNpJKx8fymDAz8xoah/KYMC0FR61H8pgwPD1YP8fymDAqxllSSDKYMDeK/KTIMpgwCd18/cfymDA2QGgKiHKYMCJaz92IcpgwEO39r4hymDA+PPrCCLKYMAlU7hQIspgwNWgFpkiymDAJ4n33yLKYMBlzk0eIspgwJkYLmEiymDAHXCBsCPKYMD6dS32I8pgwD5iFz4kymDA4TC7hSTKYMDKjZnNJMpgwIZr5xglymDACzLBaiXKYMAtNNW5JcpgwH4oFQgmymDAd7nFdSbKYMDxJ5y1JspgwE06xPEmymDACYGVOCfKYMADsHaDJ8pgwESNwscnymDAQhgcDijKYMDDx2ZTKMpgwAmWKZ0oymDAvWdk4CjKYMBDd58jKcpgwKmIhGgpymDAIt4VrinKYMBFoY3zKcpgwHwBQDwqymDATgyqgSrKYMB9jnXIKspgwNQnlA4rymDADeVlVCvKYMCxZPSaK8pgwCXKhOMrymDA5+DgKSzKYMCWEFdxLMpgwMEbQb0symDAAfwfBy3KYMAfSaSEK8pgwNVIXJotymDAZq8e5S3KYMB+WIwvLspgwDI9unguymDAyu0+wS7KYMC/4lgIL8pgwFZPbU0vymDAu0jWkC/KYMC4XSvTL8pgwCWjBBYwymDA7R/bWDDKYMAw9YqcMMpgwJsIQd4uymDAjBhDJjHKYMB04m1tMcpgwFoyWLQxymDA0bU7+jHKYMAJsTNCMspgwAkhBIgyymDAiZIzzTLKYMB9Pn8SM8pgwO3MZVczymDAql6wmzPKYMC07LHfM8pgwEDSxSM0ymDAuni5ZzTKYMCG8OqqNMpgwGtUwO40ymDATLObMzXKYMB4ELt4NcpgwFZt1701ymDA4Y1YAzbKYMDLTh1KNspgwLn44JE2ymDAn0772jbKYMCWhW8kN8pgwL78KW03ymDAq3tKtTfKYMAVfqL8N8pgwI+3JUM4ymDAqYBciDjKYMDkjnXLOMpgwOAL8Qw5ymDASYeNTTnKYMAccy+NOcpgwPk5Osw5ymDAI+A9CzrKYMBQ/WJKOspgwHLWjIk6ymDAU6p7yTrKYMBUKVgKO8pgwAnPy0s7ymDAXjTIjTvKYMBbMpLQO8pgwAeKRhQ8ymDAhpjXWDzKYMB+6PSdPMpgwMiguOM8ymDAoJRPKj3KYMC7dxZxPcpgwDUL57c9ymDAVZ+N/j3KYMA3fDhFPspgwEfUnos+ymDAaGtp0T7KYMA3aosWP8pgwH4Bulo/ymDAd1fbnT/KYMA0O+bfP8pgwBSqWyBAymDAgNxcX0DKYMAAjfudQMpgwM7qS9xAymDAlAN6GkHKYMA3OMNYQcpgwCdxFZdBymDAkZzX1UHKYMBrUrYVQspgwEsuN1ZCymDAbamvl0LKYMB7PJTZQspgwJwB9htDymDANqbaXkPKYMCPTOOhQ8pgwJj56+RDymDAtTg0KETKYMCTqJJrRMpgwBDZx65EymDAZ8vS8UTKYMDwRwU1RcpgwNa323lFymDAk2LMvUXKYMDcNM4ARspgwBlBr0NGymDAYi1chkbKYMBXtmrIRspgwOHg2wlHymDA/tR1SkfKYMAY06qKR8pgwPqSp8pHymDAmEBGCkjKYMAUOT5JSMpgwDvvcYdIymDAc5E0xkjKYMAl8KwEScpgwNcQ3UJJymDAvOsZgUnKYMDATwXAScpgwDWAtv9JymDAnfynQUrKYMCI5nCDSspgwM8X88RKymDA8xc7CkvKYMBIJVpQS8pgwFxUwpdLymDA5bSo3kvKYMDJvr0kTMpgwP6ZnWpMymDAFcB8r0zKYMAJ/4TyTMpgwASkNzRNymDAbJjQdE3KYMB6tvy0TcpgwOGnyvRNymDANGZnM07KYMCa9LxyTspgwG7ATLJOymDAgpnP8U7KYMAaDM4xT8pgwPm0p3JPymDAzwH9tE/KYMAKZuX3T8pgwNsU0jpQymDAKqSSflDKYMCdcvjBUMpgwIj1lQVRymDAAHg+SVHKYMAe0RePUcpgwFGzWtNRymDAnOb/F1LKYMBmzFddUspgwIO6uaFSymDAgzdN5VLKYMAxQXUoU8pgwNcWiGpTymDAqSrWnlPKYMA8iYqbUspgwAuPgixUymDAJOb0a1TKYMCMEJ6qVMpgwC80z+dUymDAX8G/JVXKYMAaAnBkVcpgwFDybaBVymDAeaaH4FXKYMD35d4gVspgwC+jcmJWymDAce0SpVbKYMAmYMHnVspgwIZzTytXymDAafI6b1fKYMBkCGSzV8pgwANouvdXymDAPvomPFjKYMB82fiAWMpgwN2uTsVYymDA30EiCVnKYMAINjZNWcpgwJHIEpFZymDAqxua1FnKYMAKj98XWspgwOKWIVtaymDAC6JAnlrKYMD7XDHhWspgwDC19SNbymDAQ2W0ZlvKYMCbksqpW8pgwN3UC+1bymDABocCMFzKYMCTsplyXMpgwKA91rRcymDAkKzU9lzKYMBlpXI4XcpgwA3GVXldymDA5cwCul3KYMAcPkX7XcpgwEvzlz1eymDA/noWgV7KYMCt4t/FXspgwCCm5wtfymDA0W1tVF/KYMDpppqeX8pgwPYIIOlfymDAKp6XM2DKYMCA4Zd9YMpgwNOTjcZgymDAHQt+DmHKYMAvyudTYcpgwNiAbpdhymDAOd2v2WHKYMAWekUbYspgwMJzVlxiymDAUUFPnWLKYMCfHQreYspgwEXuzh9jymDAkwJ5YmPKYMAbO+GlY8pgwBDi6uljymDAf8QfLWTKYMA+64BwZMpgwBkoW7VkymDAwjZV+mTKYMC2wXM/ZcpgwFayvoRlymDAob8IymXKYMBOfy0PZspgwBosYlRmymDAeknjmWbKYMAQavLeZspgwLA+jyNnymDAaP13aGfKYMCZ1tytZ8pgwHBs1/NnymDAG2V3OmjKYMDmbpKBaMpgwLDoysloymDAGctNE2nKYMAT0QFdacpgwBmBBaZpymDAlekx7mnKYMDnAGI1aspgwKau8XpqymDAsBwSvmrKYMD+LEL/aspgwEey3z5rymDA79yCfmvKYMDffVq+a8pgwHa5Sf9rymDA33+CQWzKYMAh1lmFbMpgwEXh1cxsymDAzYZ6FW3KYMBRurRfbcpgwD48TaptymDAnnkq9W3KYMBkCwdAbspgwKTNL4puymDAhRDx0m7KYMAQjZsab8pgwKKE+GFvymDAXLslqW/KYMDu+S7wb8pgwP34MzdwymDAFYGLfnDKYMDRSK7GcMpgwADDQw9xymDA2re1V3HKYMBnXN6fccpgwA3mWudxymDAIk16LnLKYMAzwfZ0cspgwBYMA7pyymDAzWBO/nLKYMDZ9VNCc8pgwGJ+74VzymDAtTFvyXPKYMAfryYNdMpgwGW4PVF0ymDAoP7nlXTKYMCiFEjbdMpgwEINXiF1ymDA6RUGaHXKYMBHtFyvdcpgwJCoYvd1ymDAlhSnP3bKYMBTx2mIdspgwCZzDdJ2ymDALfuBG3fKYMDBhX5ld8pgwO8Yvq93ymDAbTPe+XfKYMA/ufVDeMpgwC839Y14ymDA/cHl13jKYMA6qEYhecpgwNkWBGp5ymDAMSXZsXnKYMBEZ8j4ecpgwN0H7z56ymDALy4ohHrKYMB/yT7IespgwBx3+Qt7ymDAdH6UT3vKYMCC22KTe8pgwK80tNd7ymDAD9XMHHzKYMDlmLJifMpgwDFst6l8ymDAfEws8nzKYMDUNaU7fcpgwEnVu4Z9ymDARbT80n3KYMAIlyUgfspgwPY3dm5+ymDAWoQSvX7KYMCHKaUMf8pgwNqeEF1/ymDAFahlq3/KYMD0BT/4f8pgwBKCokOAymDAfnYRjYDKYMCmAKTTgMpgwMCOqRiBymDAUrC1XIHKYMDC+EOggcpgwJOU0OOBymDAtpGzJ4LKYMD06JxsgspgwJH1LbOCymDA9J4b+4LKYMDIXjpEg8pgwOxyfI6DymDARDGc2YPKYMA/PcslhMpgwOANj3KEymDA76iZv4TKYMA8Pe0MhcpgwP9EblqFymDAFDL+p4XKYMA8eov1hcpgwEos+kKGymDAQ3gnkIbKYMDipNvchspgwOLY9yiHymDAXlIKdYfKYMBkEmrAh8pgwEtgf2SJymDAfzFMY4jKYMCpC2akiMpgwF/x/P2IymDAMQsaSYnKYMBXborfispgwIJZDMqJymDA8BMjKorKYMCvYZqiispgwOcyaxKMymDA3n/WEYvKYMCt7Egzi8pgwFaNGnmLymDA67TtwIvKYMBfbbQsjMpgwDoGclSMymDAh6A7nYzKYMDIWp/pjMpgwJG+ZziNymDAriPEh43KYMB5+HzWjcpgwPe3fCSOymDAFVmwcI7KYMANFHC/jspgwCDxTA2PymDA0RhIV4/KYMAcqMGfj8pgwHngueePymDA3uAMrZHKYMAIh196kMpgwCdQTMSQymDAYCfSD5HKYMC2x9FfkcpgwMsL66uRymDA8sOta5PKYMBKjEdEkspgwJFvLP+TymDARqUx25LKYMBPvqwkk8pgwL5uo2uTymDA2Mn1sZPKYMC/vZD4k8pgwHfs6j+UymDA3cJxiJTKYMAqgwfRlMpgwOBHXRuVymDA6jrOZ5XKYMCHLVm1lcpgwBl4lgOWymDAq/RWUpbKYMDhSSOhlspgwMybnO+WymDAq09PPZfKYMBvXdWJl8pgwDZrStWXymDAqrsaIJjKYMDZCVlqmMpgwMNIyiKaymDA+m68bZrKYMC55im6mspgwAA03pOZymDA91bz3ZnKYMDxDiwomspgwB8ZwnKaymDAshvFvZrKYMAoF8oIm8pgwGyz/lObymDAcW3goJvKYMDAqNrum8pgwKopzjycymDAlFvLipzKYMDSXrvYnMpgwIInvSadymDAndOIdJ3KYMBJg2XBncpgwKswtA2eymDAKQMLWp7KYMBVsEqmnspgwG+XefKeymDAKnSKPp/KYMA3ecyKn8pgwBBx09efymDABqb+JKDKYMDOZjlyoMpgwI3tpL6gymDAThr/V6LKYMAMShVXocpgwMS42qGhymDAb5FOOKPKYMAmEuyCo8pgwP/Wtc2jymDAnuPiF6TKYMCgMGJhpMpgwLeQraqkymDA5vI286TKYMD3q3U7pcpgwC8uo4OlymDAsbzNy6XKYMAVt30UpspgwPvr0V2mymDA29Pjp6bKYMDFL+3ypspgwH161T6nymDA1gAMTqbKYMCcLkeXpspgwMLy3SSoymDAH5dvcajKYMA9bIG9qMpgwHDqfr2nymDA1QadCKjKYMAg8YGfqcpgwKAKGOqpymDAH/iYM6rKYMA9c4B8qspgwP4THsWqymDAr3KkDKvKYMAGbrMoqspgwOOSAJqrymDAAeWM4KvKYMBHcCwnrMpgwM3oF26symDATSxUtazKYMCWunD9rMpgwK0vj0atymDA4Qkhh6zKYMBgt4vPrMpgwDfj7RatymDASq13Xq3KYMB4RbCmrcpgwHlvme+tymDAv+/GOa7KYMCcIJ+FrspgwFe6QNKuymDAOoIsH6/KYMAKyKFrr8pgwC+AuLevymDARPk1A7DKYMDTqz8oscpgwL2VtW+xymDAD9FC2rDKYMCbyHwescpgwFgHOWOxymDAspWNqLHKYMB/BEruscpgwPnyNzSyymDAbQDTe7LKYMD3QePEsspgwNXrYQ6zymDAPOA5WLPKYMALcFqis8pgwAO/w+yzymDAILBBN7TKYMDPeBqBtMpgwIuuhcq0ymDAYbMtFLXKYMBg5VpetcpgwLAXW6m1ymDA2+Mr9bXKYMDfSMdBtspgwOA3+I+2ymDA680u37bKYMCQizwut8pgwHcPzXy3ymDAfSaZyrfKYMAsJuEWuMpgwP36GWG4ymDApt0eqbjKYMBptB7vuMpgwCahUzS5ymDAV8YLebnKYMCB8Jy9ucpgwMiHiAK6ymDAbOQmSLrKYMDSwW2PuspgwJTyjNi6ymDA5jjjIrvKYMCj2Bluu8pgwKpEA7q7ymDAX+BiBrzKYMBZQBRTvMpgwKy81J+8ymDATO1s7LzKYMB0af84vcpgwLOjPoW9ymDAx6Tj0L3KYMDbqBccvspgwEuF2Wa+ymDA108ssb7KYMAoe/r6vspgwFsGeUS/ymDAgsQjjr/KYMAkRPbXv8pgwFk1KyHAymDAEmgvacDKYMAxhKOwwMpgwKlFdPjAymDAqzx6QMHKYMD/Fo6IwcpgwLE9PdDBymDAFwd1F8LKYMCgKiVewspgwKn3EaTCymDAJ1eX6cLKYMAD1YEww8pgwGpzZ3jDymDAisXHwMPKYMBJn7gJxMpgwD+lJFPEymDA/lp2ncTKYMBUYfjoxMpgwO6gyTXFymDAAw8jg8XKYMCnbVDQxcpgwJmcMBzGymDANI6KZ8bKYMBkKTSyxspgwMXctfvGymDAo2L/Q8fKYMCWfDCLx8pgwCI47dHHymDA4lUPGMjKYMDv4vRdyMpgwKM+YqPIymDAATXB6MjKYMCRUF+4yMpgwAJALrrJymDAbv2MAMrKYMB7IQ9HyspgwCysDI7KymDAML+B1crKYMBhv8wcy8pgwAV/MmTLymDAPs6SrMvKYMDiEy71y8pgwMb9tj3MymDAW0MyhczKYMC41c/NzMpgwJRfmhbNymDAe9SsXs3KYMBPOv2hzcpgwPkleuvNymDAg8z4Ms7KYMDufkJ7zspgwFvGm8POymDAamXMC8/KYMDRx6lTz8pgwMprFpvPymDAqAMG4s/KYMBogXgo0MpgwCdch27QymDA8+Xxs9DKYMD4udH40MpgwO8a0D3RymDA/Z9Jg9HKYMD5kGfJ0cpgwMxeDMjQymDAh5k+DNHKYMA1OfVP0cpgwNZlR1rSymDA7qs5nNLKYMDYIAHf0spgwB8HdLLUymDAf1jc+9TKYMALIOpE1cpgwM5S49XVymDAPBatHdbKYMBxbtd41cpgwNyiLoTXymDAt6VDytfKYMDE3DgQ2MpgwD0DFVXYymDAzOH/mNjKYMBV6NHc2MpgwB2hvCDZymDAJ1LnZNnKYMCiXfOo2cpgwFzLSu3ZymDA2aCUMtrKYMBRtp932spgwPnXUrzYymDAojzrANvKYMBbF65G28pgwJ4rrIzbymDAGW2X0tvKYMBqAGoY3MpgwNLJYyXaymDAn+ASotzKYMBm4nDm3MpgwBKi3CrdymDA4gXSbt3KYMCZkV6y3cpgwFaWY/bdymDA0XOvO97KYMBDlfaB3spgwINlDcreymDAzXi4Et/KYMCoHPpa38pgwK5sejrdymDAappDe93KYMDCrt+83cpgwLcYEHjgymDA2/P1vODKYMDMq7MB4cpgwNKydEbhymDA69f2iuHKYMBL0ynP4cpgwHtYURPiymDAFTo5V+LKYMCb/dSa4spgwJcNxt7iymDAnyFDI+PKYMAHDGFo48pgwEQ6USThymDAOYUB9ePKYMDDVFJo4spgwNeCR6riymDAkJj47OLKYMCjEox448pgwJiOd7zjymDAYh4MAeTKYMBOerRF5MpgwIBv05LlymDAf95e0+XKYMBeXM0T5spgwAgiLlTmymDAR7G7cunKYMDO4oy46cpgwGlVOP7pymDAaUA3wunKYMAk2T0F7cpgwPM3b0vtymDAq5cQkO3KYMA1ZNvS7cpgwAnnFRPuymDAXHGbUu7KYMCJr8GR7spgwPOnqtDuymDAftWMD+/KYMCDR5hO78pgwAWZ0o3vymDAT8dpze/KYMAAX4QN8MpgwJPzbk7wymDAUUEAkPDKYMC8JlnS8MpgwDTlEBXxymDAUkzYV/HKYMDVXfya8cpgwHtzjN7xymDAaow8IvLKYMD/x+pl8spgwAEp/6nyymDA+Wc6x+/KYMAUYCcw88pgwGzZCHPzymDAWiK5tfPKYMBxBhT488pgwMwGFDr0ymDAcfw+e/TKYMDJSEm89MpgwH7uEf30ymDAaeHVPfXKYMATGNl+9cpgwCFjxJXyymDAnkpqavTKYMDsm5yx9MpgwE/hqPf0ymDABS+xPPXKYMA7pui5+MpgwAKY7P74ymDAicg2RPnKYMC2qX2J+cpgwL/Jp875ymDAxrhTE/rKYMCa4DxX+spgwHdrUY73ymDAgWdU0PfKYMBWjZIS+MpgwAgGU1v7ymDA11ROl/jKYMBm5WDZ+MpgwDJ/UBv5ymDAnSLvUfzKYMD5KoWe+cpgwB0Nv+D5ymDAafjCI/rKYMB29X1n+spgwG7Vlav6ymDAbWox8PrKYMB67nA1+8pgwEfZJHv7ymDAuREkwfvKYMCEn+0G/MpgwEINERz/ymDAfCZoX//KYMChOTGi/8pgwKP5x+P/ymDAb3n1IwDLYMBUcQWl/cpgwFHYpaQAy2DAcKNy5gDLYMABJqMoActgwFfk+bn+ymDAKSlf//7KYMCNpYxE/8pgwGxXuIn/ymDAaHQ9z//KYMD42d+3AstgwOLCgfkCy2DANooAOwPLYMCfwtF7A8tgwHMwA7sDy2DA5eEf+QPLYMDJNnY3BMtgwAkReHYEy2DAbA4/tgTLYMCIMMH2BMtgwD+xhDgFy2DAz1IffAXLYMCYD83BBctgwFgBKAgGy2DAq0gJTgbLYMCEUCuTBstgwOJQR9cGy2DAHRZ7GgfLYMAy9h1cB8tgwKaHQZwHy2DAK7qf2wfLYMCI7GUaCMtgwLYIflgIy2DAOaBOlgjLYMD/mDjUCMtgwFyYlBIJy2DAGpBgUQnLYMBM7gtRCctgwGCEZ5kJy2DAYsUF0AvLYMCeHBQqCstgwFeqwHEKy2DAfxXa+wrLYMC8hwhGDstgwB+P/TINy2DAqyWKeg3LYMCSmFfCDctgwPkvKgsOy2DA9bh9VQ7LYMDH0h2FD8tgwJKjKc8Py2DA9r2fGBDLYMBeywBhEMtgwJEXL6gQy2DABGZPfRHLYMDO57PFEctgwAtfmQ4Sy2DAexkvWBLLYMACw9miEstgwGZflYgTy2DAJIWi1RPLYMCQTHIiFMtgwO+nym4Uy2DAtrFsuRTLYMC3It6YFctgwPJWR+EVy2DAe6urKBbLYMBjCYI+F8tgwJiz6bQWy2DAY89aihfLYMDLBWSVGMtgwDKqXtQYy2DAnCTGYxjLYMCHetROGctgwBbujIsZy2DAhRl5yBnLYMC9Ap0FGstgwIUO0kIay2DAe2/FgBrLYMB12WW/GstgwAfR9P4ay2DAFPtfPxvLYMBbudSAG8tgwG6aiMMby2DANqmCBxzLYMDB6K1MHMtgwHIf6ZIcy2DAwPsN2hzLYMAEJVsiHctgwDji0msdy2DAC9z9tB3LYMCs9Ef9HctgwAJHXkQey2DAWiEKih7LYMDk1Q7OHstgwEpVqw8fy2DA0cSYTh/LYMDWlYKMH8tgwCpD8skfy2DAJ9NtByDLYMDhy25FIMtgwHuPS4Qgy2DA5RHoxCDLYMBkjL0HIctgwDiSFkwhy2DAWY++kSHLYMByo3fYIctgwLrUJyAiy2DAWoCGaCLLYMC4skWxIstgwHB7Cvoiy2DA2QnaQiPLYMCYv5qLI8tgwHyaNdQjy2DA0J2OHCTLYMDGKJlkJMtgwLQKP6wky2DA0aNm8yTLYMDyOSk6JctgwBhXm4Aly2DAn93BxiXLYMAi76wMJstgwHsnXVImy2DABCnvlybLYMChfoHdJstgwHHQ+CIny2DAKIU7aCfLYMA8BjutJ8tgwDmn/fEny2DAdbqHNijLYMC1sc96KMtgwBNTxL4oy2DARG6RAinLYMCVOXRGKctgwO1MkIopy2DACj7/zinLYMDwoNgTKstgwA/IMVkqy2DAsLonnyrLYMDvRrXlKstgwKYowywry2DAki9KdCvLYMDcrza8K8tgwPvodQQsy2DAeeftTCzLYMByBZ6VLMtgwDZSZd4sy2DABSAHJy3LYMDHtmetMMtgwNbZ0Fsvy2DARg7QoC/LYMCKS+DlL8tgwEGsFyswy2DAOxylcDDLYMBjKzjUMstgwMGT90Mxy2DACvufizHLYMClMdPTMctgwMhjlhwyy2DAQ0v8ZTLLYMBURvuvMstgwAloWfoyy2DAV9zHRDPLYMDweTSPM8tgwDp4etkzy2DAtJ6DIzTLYMBX8yNtNMtgwJ2qEwY3y2DAz316RzXLYMAfxJiPNctgwIrEjtc1y2DA3QBrHzbLYMD32idnNstgwN810iU5y2DAoSOjPjfLYMCi/oOHN8tgwEXe3dA3y2DAld6wGjjLYMA2z2RlOMtgwNUcL7E4y2DAmlFS/TjLYMC8LUhJOctgwGpM0ZQ5y2DARuK93znLYMD69hUqOstgwH6gQXM6y2DA0/qqujrLYMBCB18BO8tgwIiMPEg7y2DAA5ShjzvLYMCun+PXO8tgwFZ0ISE8y2DAjJDqazzLYMDaeB25PMtgwDIR7Ac9y2DA86/7Vj3LYMBrxM2lPctgwCuT8PM9y2DAMQYgQT7LYMARjbaMPstgwMJI6tU+y2DACuokHT/LYMDqXbhjP8tgwCSvBao/y2DA9TeA8D/LYMC1y483QMtgwE+omX9Ay2DAEYxeyUDLYMCsjdwUQctgwOMlkWFBy2DAfA9Cr0HLYMA5y7T9QctgwNrfxkxCy2DArN8nnELLYMCyNq3rQstgwAdiFTtDy2DAEAApikPLYMAPFrrYQ8tgwIiRqSZEy2DAdKjmc0TLYMC1XXXARMtgwF3l6QtFy2DAXuw5VkXLYMBpejegRctgwCI5MOpFy2DA5eRfNEbLYMDrne1+RstgwKmB4MlGy2DA6SgMFkfLYMDmCoRjR8tgwBnSM7FHy2DA/w6k/kfLYMBSeJBLSMtgwOijzJdIy2DADixd40jLYMAF81QtSctgwLYCcHVJy2DABc4lvUnLYMAP8CgFSstgwAQF6E1Ky2DAedXJl0rLYMDE8+XiSstgwBoDMjBLy2DAp/QKgEvLYMC0PUTRS8tgwBMdACNMy2DADjzGdEzLYMCy5gXGTMtgwAsAfRZNy2DA4rdoZU3LYMDzKVWyTctgwKIftf1Ny2DAyKUPSE7LYMAmT6SRTstgwNdUudpOy2DAa7eOI0/LYMB8WX9sT8tgwLEwF7ZPy2DAsLE1AFDLYMAvT65KUMtgwJmek5VQy2DADNnm4FDLYMArGcYsUctgwBA//nhRy2DANylxxVHLYMDIxEYSUstgwM0BpV9Sy2DAWCCbrVLLYMBach38UstgwMKqH0tTy2DASm+vmlPLYMCdQszqU8tgwOj7ODtUy2DAhiili1TLYMB2A+DbVMtgwNd5vitVy2DAIDERe1XLYMDZyLrJVctgwB5btxdWy2DAC7X/ZFbLYMA29kuxVstgwLh7uPxWy2DA8J5JR1fLYMDYdjGRV8tgwF/phtpXy2DANGAAI1jLYMDVOe5qWMtgwBK3V7NYy2DALX+q/FjLYMCbJSRHWctgwFNeCpNZy2DArDhp4FnLYMB/UEAwWstgwARHUYJay2DAXtRD1VrLYMAyGY8oW8tgwFVjyHtby2DAG++RzlvLYMBxWp0gXMtgwHTJ+nBcy2DAyw9Fv1zLYMD3SqkMXctgwMl5flldy2DAYBMUpl3LYMCq56HyXctgwAarRD9ey2DAVOHAjF7LYMAlSZ/bXstgwGTRoipfy2DAjOx+eV/LYMDb8u/HX8tgwNRGyBVgy2DALzgEY2DLYMCZWU+vYMtgwP86XPpgy2DAnEtXRWHLYMA/MXKQYctgwOC/69thy2DAqTgZKGLLYMDpIox1YstgwN0hZMViy2DA3CFfHWfLYMBTfvRtZ8tgwHyA2L1ny2DAI5nDDGjLYMDAEbZCactgwEtQVY5py2DAXN5Bo2bLYMDshq7wZstgwLL8iT5ny2DAKcBbjWfLYMBCiOxea8tgwLb+Enxoy2DAtm01/GvLYMDrJT9LbMtgwAlzNGxpy2DAaUyRumnLYMBetc+DbctgwLLHxaRqy2DA3ZLC82rLYMB69bRCa8tgwOV/t5Jry2DA4S3342vLYMDQJhw2bMtgwMuXjohsy2DA1efk2mzLYMBHBt8sbctgwJpkR35ty2DAsyH5zm3LYMB1drIebstgwO+0Qm1uy2DAlsBuum7LYMCSpZ8Fb8tgwGlucVJvy2DAtyNAnm/LYMBg7EHpb8tgwKt9tjJwy2DA/daHe3DLYMCN8fnFcMtgwIt4xRFxy2DAKrLdXnHLYMAqR2GtcctgwIDKIv1xy2DAzT4DT3LLYMAvLjGjcstgwDufp/dyy2DA7bn8S3PLYMCqllqfc8tgwMIkpvFzy2DA5cS1QnTLYMC3gC+RdMtgwIQn9tx0y2DA1J2jJ3XLYMDVA0xydctgwJMFkb11y2DAIZC2CXbLYMBkgvhWdstgwIv2waZ2y2DAHxub+XbLYMBqLFbPectgwFaNpxl6y2DAH6sgZHrLYMAZT/6uestgwP/O//p6y2DAB2bDSHvLYMCH6yyggMtgwIixvGl+y2DAC6RDuX7LYMBf68QIf8tgwI0nM1h/y2DAz77xCoLLYMA7QeKegstgwHEm6BaEy2DAlCPqq4TLYMDsd5i6gstgwMk5ZweDy2DA2Ph3VIPLYMD0t82hg8tgwBF1GSSGy2DAPNeevIbLYMB2H9TahMtgwNoTHSqFy2DA127VeIXLYMA2e+7YistgwP4TjDuJy2DATc58h4nLYMAcYMrSictgwKTIcx2Ky2DAlcJOZ4rLYMACGErMjMtgwFTtD0KLy2DA7gCRi4vLYMCA0+PVi8tgwIQFBCGMy2DAfU1VWY3LYMC/SGSpjctgwEYczvmNy2DAiKiaSo7LYMB1yz1HkMtgwKTz6Y+Py2DAWfVZ4I/LYMDl+A0wkMtgwO9+B3+Qy2DAr5wWzZDLYMARRXPMkstgwHPC5bCRy2DAG8FH+5HLYMB92XxFkstgwBj8c4+Sy2DACvNY2ZLLYMBX8Gojk8tgwBVjv22Ty2DAG1bluJPLYMC5dJkElMtgwOp5AVGUy2DAiKr4nZTLYMAzOZbrlMtgwF4e4DmVy2DA/BEi5pbLYMC0X8ImlstgwMPc73WWy2DAd03uxJbLYMD1xPITl8tgwCgzm+iYy2DAc1vgSpjLYMC4No2XmMtgwBUIBeSYy2DA9xNtMJnLYMCr/brPmstgwCsr52Kay2DA1IirrZrLYMALWpz3mstgwBiRleGby2DANgN1uJzLYMCR4HZsnMtgwHZRcrecy2DAq16tAp3LYMAZsVxNnctgwITZvpedy2DAvjaFlJ7LYMDSDXd2nstgwBCabcKey2DAdAzcDp/LYMDTyKFbn8tgwPvWcKmfy2DACheM+J/LYMCwa3hHoMtgwGfsA5Sgy2DA5nAO4KDLYMDtNTIroctgwDRigHWhy2DAmcTEvaHLYMCKWvgDostgwLugWkmiy2DALEh7jqLLYMAa8dvTostgwElk3Bmjy2DAmvfKYKPLYMD8ksepo8tgwKYFX/Wjy2DAD2XAQaTLYMARTkGOpMtgwIlsS9qky2DADIzNJaXLYMDsgpVwpctgwLY2dbqly2DA7sjG/qXLYMBOonJDpstgwCmXQYimy2DA0ruMzabLYMDlN8ETp8tgwLj6D1uny2DAEpenpKfLYMABGRHxp8tgwLHjOT+oy2DAdu+2jajLYMB6v2fcqMtgwFX65Cqpy2DAWfqPeKnLYMAwsJnEqctgwMEGFQ6qy2DA38G8VarLYMAKmDScqstgwGBvweGqy2DAIdmuJqvLYMA4HFxrq8tgwMr3TbCry2DAFqER9qvLYMARlZo8rMtgwB2HqoOsy2DAYC5Iy6zLYMCqgXkTrctgwCZ0QVyty2DAreCKpa3LYMBb/hnvrctgwMUC+Diuy2DAxXJPg67LYMDLDRXOrstgwKPKPBmvy2DAoFOtZK/LYMBG21iwr8tgwPcraPyvy2DAlgIY7a/LYMBiY97fsMtgwEPjRiqxy2DADJjoc7HLYMBuO4u8sctgwOgNBQSyy2DAgOYzxrHLYMCZ0/LUsstgwLoNBxqzy2DA8pE4X7PLYMCK7ruks8tgwFa33eqzy2DAZRbCMbTLYMCtuIB5tMtgwOv6pcG0y2DAJBSzCrXLYMBt40JUtctgwGjSUJ61y2DAnkXP6LXLYMBZLZ0ztstgwIrab362y2DA8t48ybbLYMBAgJMTt8tgwFN+g123y2DAv+vYprfLYMACQnrvt8tgwCggVze4y2DAS+08frjLYMDXutDEuMtgwLOxUQq5y2DABYdnT7nLYMC5MgOUuctgwGfmNti5y2DAA9sMHLrLYMBDKetfustgwMHOwaO6y2DAoNI+6LrLYMBDsCwtu8tgwFNQs3K7y2DATkYMubvLYMCW8SgAvMtgwBwkDlq7y2DA5hSokLzLYMBspL3ZvMtgwIOsASO9y2DATspzbL3LYMBVnO21vctgwMDEO/+9y2DAyUxESL7LYMCZuPSQvstgwGHwNdm+y2DAxqoDIb/LYMASfDpov8tgwLJWzq6/y2DAaDHb9L/LYMDtGVg6wMtgwKbeOn/Ay2DAzI+Dw8DLYMBdNkIHwctgwClZlUrBy2DAWbmUjcHLYMDDOSLQwctgwOHwjxLCy2DAeDhJVcLLYMB0BoaYwstgwLezd9zCy2DA7FktIcPLYMAbqtJmw8tgwF5vta3Dy2DAUeK/9cPLYMDywkw+xMtgwGNaDofEy2DAyV7Zz8TLYMAG1nwYxctgwG7jxWDFy2DAgB9JqMXLYMA6Kf7uxctgwFCZITXGy2DAf57EesbLYMBxCAHAxstgwH9l7gTHy2DAjQCQScfLYMCVRiyOx8tgwISk29LHy2DAkHVzF8jLYMCXpPNbyMtgwLAla6DIy2DAq5np5MjLYMAZDHwpyctgwFa6AG7Jy2DAdgB3ssnLYMDWqjb3yctgwO9LYTzKy2DA1jINgsrLYMA7VETIystgwNNjBw/Ly2DAc997VsvLYMAp0Z6ey8tgwIVjDefLy2DAu0CJL8zLYMCiFtp3zMtgwPM21r/My2DA/lBlB83LYMDExj1OzctgwNzSNpTNy2DAlg2p2c3LYMAHv70ezstgwLcHi2POy2DAITgoqM7LYMCZsp/szstgwAvZMzHPy2DAH3wRds/LYMCm8/m6z8tgwG6p0P/Py2DAo+GNRNDLYMCRsieJ0MtgwJSboM3Qy2DAM1/iEdHLYMBA+OBV0ctgwI4FwpnRy2DARnSg3dHLYMBiVpAh0stgwKuap2XSy2DAnOMBqtLLYMC5TKju0stgwDT9mjPTy2DA8fb9eNPLYMCuYvu+08tgwFhyjAXUy2DAOiO9TNTLYMAZwnSU1MtgwApXxtzUy2DAlSrQJdXLYMCZhzlv1ctgwIirk7jVy2DAYs+yAdbLYMCEL01K1stgwPfGVJLWy2DAanyZ2dbLYMCjy6kf18tgwIPryWTXy2DAuAJSqdfLYMBDtort18tgwGAkfjHYy2DAJjdaddjLYMAdG0252MtgwCjnwf3Yy2DA5uPBQtnLYMButc+H2ctgwAQ+3czZy2DAa/HeEdrLYMDyD9VW2stgwG+hvpvay2DAtKgy4NrLYMDhCkok28tgwM6Py2jby2DAqX7ordvLYMAxc9jz28tgwL9CuDrcy2DA3DZ0gtzLYMCfFqzL3MtgwIBKUBbdy2DA9R15Yd3LYMBOXcis3ctgwO8Y6vfdy2DAImONQt7LYMA41n+M3stgwCZCO9Xey2DAUUOHHN/LYMDCk9di38tgwIAfY6jfy2DAB/pM7d/LYMA+2r0x4MtgwNkz4HXgy2DATb0DuuDLYMAkdmf+4MtgwOLd8ELhy2DA2tCvh+HLYMBNebrM4ctgwA/TGhLiy2DA8/XoV+LLYMDOfgqe4stgwClrY+Tiy2DALZY6K+PLYMANU71y48tgwAGi07rjy2DA+bCMA+TLYMDe3bdM5MtgwEfviJbky2DATwAe4eTLYMBGs7gr5ctgwByv13Xly2DAPqwSv+XLYMD7tzsH5stgwLZnRE7my2DAvvClk+bLYMAtkxTX5stgwKYCORnny2DA/8rOWufLYMD020Oc58tgwDas/t3ny2DApFtGIOjLYMDZXIhj6MtgwIFiaajoy2DAyad47ujLYMBEMuM16ctgwK+C3X3py2DASKW/xunLYMCFfDkQ6stgwLslFlrqy2DAUzw4pOrLYMDPx23u6stgwOMObzjry2DAgu0xguvLYMA8qXzL68tgwKMkWBTsy2DAmv6vXOzLYMAf1Aik7MtgwCnxrursy2DA9lZWMe3LYMDH1R147ctgwExdYb/ty2DAGVcaB+7LYMArVG1P7stgwPI5BZnuy2DAxt3u4+7LYMCy7LAu78tgwE+dO3nvy2DAjHjbwu/LYMC+C60L8MtgwIZfjFPwy2DA8RCAmfDLYMA2nlzd8MtgwGjsESHxy2DAuD7uZPHLYMB6uvKp8ctgwFxwH/Dxy2DACP3CN/LLYMAT1tKB8stgwOPYxc7yy2DAnsjcHPPLYMDvCcfZ9stgwOlE1YD1y2DALeJNyPXLYMAhwUsP9stgwD7VvVX2y2DAHKknnPbLYMCKg8vi9stgwDj7hyn3y2DAd0dDcPfLYMAYT3CA+ctgwFDF8cz5y2DAxOu1GvrLYMB3Qvtp+stgwHWsXZP9y2DA9NMo4v3LYMCE9A4x/stgwAcgIYD+y2DAt/jqwP/LYMAiGlwN/stgwJ3QWVj+y2DAjb9dov7LYMC/dujr/stgwFgB6DT/y2DAtamGff/LYMAgq/3F/8tgwNulVw4AzGDAccs0VwDMYMBAVmmgAMxgwK5S1OkAzGDA2scxNAHMYMBHz5B/AcxgwMoUmMoBzGDAjgXIGAbMYMDo6kdnBsxgwIuL2rUGzGDAJXGdtATMYMC3R9j/BMxgwCDzI58HzGDAFnpSlgXMYMAenp83CMxgwDPEJoMIzGDAUtFldwbMYMDyEZDDBsxgwC4IiQ4HzGDAMEUiWQfMYMD0jUCjB8xgwND9L+0HzGDAwnwWNwjMYMBy/BiBCMxgwJHyPssIzGDAbqeWFQnMYMBhJVZgCcxgwNqUg6sJzGDAjzsr9wnMYMBLjORCCsxgwGbRB48KzGDA3Dhp2wrMYMAwxgQoC8xgwBzIynQLzGDABk+owQvMYMDmHsoODMxgwIYS7VsMzGDAFRNgqQzMYMDXk+j2DMxgwDXmhUQNzGDA+Zc3kg3MYMAuLP7fDcxgwNFysS0OzGDAxpBTew7MYMB2srDIDsxgwIxU0RUPzGDA31WtYg/MYMCPhESvD8xgwFnTpfsPzGDAdF59EBPMYMDPqyPfEMxgwGLbrSoRzGDAlQY1dhHMYMCH4rDBEcxgwEQ1BQ0SzGDA8yAxMxXMYMA3Q1DxEsxgwDAHjT4TzGDAVnFkjBPMYMAhcfraE8xgwLd3USoUzGDA7f3cURfMYMBMTdsaFcxgwBxfdWoVzGDAHU6FuRXMYMBxcM0HFsxgwAwQ6VQWzGDAnnCGdBnMYMBl8mA3F8xgwJWn9IEXzGDAvhJazBfMYMCT2boWGMxgwC/NXGEYzGDAWuxDrBjMYMCK0G/3GMxgwFxNt0IZzGDAk0xAjhnMYMCuJfXZGcxgwORo4yUazGDAAyvpcRrMYMBLmQe+GsxgwBMHQQobzGDAO9hmVhvMYMAP3VCjG8xgwGS5afAbzGDA867KPRzMYMC2f42LHMxgwN0H88IfzGDA269cdh3MYMD5z7rEHcxgwK945RIezGDAcKrqYB7MYMAsGGHgIcxgwNaiB5YfzGDABzsD4x/MYMCgiQowIMxgwJKuF30gzGDAMnZFyiDMYMB3H17xI8xgwK2bcbIhzGDAnPLc/yHMYMDsFgdNIsxgwFy4FpoizGDArIzl5iLMYMD1TE0zI8xgwI/PpX8jzGDAkFjoyyPMYMA8xFYYJMxgwG3A4mQkzGDAyt2isSTMYMAOa7f+JMxgwD2kSkwlzGDAlZAsmiXMYMDi0VjoJcxgwN8zuzYmzGDA6v8shSbMYMAdjaDTJsxgwCCQAyInzGDADkpMcCfMYMBSoGK+J8xgwHEoKAwozGDAxdiXWSjMYMASwq+mKMxgwOzDffMozGDAuVnvPynMYMB14+GLKcxgwFc7ndcpzGDA2up4IyrMYMCf/JFvKsxgwNDhH7wqzGDAzi8XCSvMYMDoErJWK8xgwEXeLKUrzGDAQoZS9CvMYMDvnrZDLMxgwI8UIZMszGDAT4dl4izMYMCtTGUxLcxgwMhz+X8tzGDAzP7JzS3MYMBk6q2zMMxgwJS2CrQuzGDAhXxfAC/MYMAK+KlML8xgwOMpApkvzGDAtem+5S/MYMCVx7nXMsxgwGVPU80wzGDAfrl7GjHMYMDe8plnMcxgwDVdwrQxzGDAlel+ATLMYMA62Dz1NMxgwKLOdUI1zGDAJS0NkDXMYMCJTL7dNcxgwA/aQBc3zGDAHH6VITXMYMDPqK1yNcxgwAxXLcM1zGDA/VaAEjbMYMBksGkpOcxgwEbaTnQ5zGDAEoqsvznMYMDKP4/YN8xgwMR47CM4zGDA5WQNcDjMYMDMP7tYOcxgwN9Sw6c5zGDAhrUn9znMYMAar/BGOsxgwEWaLJc6zGDALsNtiDvMYMBR5ZfXO8xgwFq3GSY8zGDAl8fgczzMYMAGDI7APMxgwLy19aA9zGDAigb26z3MYMBlkIw3PsxgwD3E1oM+zGDAzg1k0T7MYMBSLcC/QcxgwH3LhQlCzGDAsDCEU0LMYMAT5LedQsxgwKCha+hCzGDARYUwykPMYMD7sJUvQsxgwHq6W3lCzGDArfoRw0LMYMBLnQsNQ8xgwOwbutVFzGDAfAWsOkTMYMB87+qHRMxgwMYszNVEzGDAKgdRJEXMYMBOvDXaR8xgwEmqAmNGzGDAh+2hskbMYMDQi9IBR8xgwB7kXlBHzGDAeVtQnkfMYMA7i9/YScxgwDnyMyFKzGDATyZ5aUrMYMB/yEYWScxgwCzCsF9JzGDAkI/RqEnMYMCzJHjVS8xgwKt2ooNKzGDAP7UzzUrMYMAcF0gXS8xgwP/zCmJLzGDAzLijrUvMYMBAP8aVTMxgwF//leRMzGDAWf+dM03MYMBEGt+CTcxgwBnmQ9JNzGDAYy5OwE7MYMDGJxUPT8xgwM+xg11PzGDAe6iBq0/MYMBIl+T4T8xgwM54h91QzGDAox1TKVHMYMDY0R91UcxgwOW/+sBRzGDApKIQDVLMYMAuKOr0UsxgwE68/kFTzGDA4d7tjlPMYMBFmuDbU8xgwB6vTP1VzGDAlsFWV1XMYMAvKcyOVsxgwItrgddWzGDATokz9lfMYMAzB693V8xgwJSY2MVXzGDACvDNy1jMYMBnS77uWcxgwPyNcjRazGDAumewelrMYMC4Y37QW8xgwNEp1I5bzGDAwjDQ2VvMYMBrLEQlXMxgwD7KkLNdzGDA0h9o913MYMAb2nf0XcxgwNC+R0JezGDAHLWuj17MYMDDX2XcXsxgwAGto5RfzGDAynfsvV/MYMC1YjEIYMxgwLS/N1JgzGDAubcCnGDMYMDKr8/lYMxgwBBfFWlhzGDA+luUw2HMYMAP+W0NYsxgwDxVOVdizGDANjbyoGLMYMDY5Y/qYsxgwEXyzj9jzGDAOII0x2PMYMBbm/AQZMxgwG7py1pkzGDAEJ7jpGTMYMC6EiXvZMxgwLrGRM9lzGDAXrf+GmbMYMC/SAxnZsxgwO5+drNmzGDAIXhZAGfMYMA8QuDoZ8xgwNGgJzVozGDAqWW+gGjMYMCC8mDLaMxgwKKk1RRpzGDA/xcvEmnMYMCuxrUvasxgwGjuA3ZqzGDAj8mvvGrMYMC30BYEa8xgwL5nGNFqzGDAU48wK2zMYMBf2112bMxgwEgkx8FszGDA/Vg7DW3MYMCSonJYbcxgwDM2/LRszGDAhti3OG7MYMDxofuCbsxgwGps98xuzGDAv+ucFm/MYMByViBgb8xgwLy13B5yzGDAiHtqHHTMYMAWYg5mdMxgwMNFqa90zGDAatIp+XTMYMApqUZCdcxgwEQC1Bp2zGDA8+aWYnbMYMAdaj2qdsxgwMjFx/F2zGDAVqpko3XMYMBwC1wQeMxgwOkl9ld4zGDADXuDn3jMYMA1bwXneMxgwMeaFgR6zGDALScbS3rMYMAWHxKSesxgwMaM+9h6zGDAleb/83vMYMDW4ro6fMxgwGLEhIF8zGDAWQxcyHzMYMA3NUoPfcxgwBiwrEd7zGDAlTt4K37MYMAwRityfsxgwFAKpbh+zGDADWjiDn3MYMAN4gVQfcxgwNGFIFuAzGDAJ5AQoIDMYMBdX5blfsxgwK/pECl/zGDA++Pwa3/MYMCWTBSxf8xgwPqZ+KuAzGDAcTai6oDMYMCqPAIqgcxgwE43Z2qBzGDA6hXSrILMYMAlgJ3sgsxgwGlmIS6DzGDAW5SHcYPMYMCIyos+hMxgwLZGmn6EzGDA9FH//IfMYMA4xaFAiMxgwOM8H4CIzGDAIYHcvojMYMAKLo7nhcxgwPMlCnmJzGDAL8SxtonMYMC02OfzicxgwL6cwTKKzGDAAoGQcYrMYMAkUgexisxgwFhDIfGKzGDA43F3MYvMYMDXo+Nxi8xgwEtiNbSLzGDAVmhX9ovMYMDJ4+04jMxgwGbzCXyMzGDAlE9tv4zMYMDSiPICjcxgwDKqkkaNzGDAOMojio3MYMD/FXrNjcxgwOOIlhCOzGDAHqiXU47MYMCSyG+WjsxgwIIgGNmOzGDA7th1G4/MYMChpHRdj8xgwEDwRJ+PzGDAvWq94I/MYMCmQ7shkMxgwLjynGKQzGDAL3+2o5DMYMCHqC7lkMxgwIZmJyeRzGDAU+yHaZHMYMACYLWskcxgwD3+8PCRzGDA6m+NNZLMYMAY0gJ6ksxgwA4XH76SzGDAmvWVAZPMYMDDAFFEk8xgwMyk9IWTzGDAjxzJxZPMYMAwELMElMxgwEjdOkOUzGDA5CS3gZTMYMA0a17AlMxgwNWOUf+UzGDATocHP5XMYMC6fCSAlcxgwKtlLsKVzGDAKzp+Q5TMYMBeOoH8l8xgwFOuZTqYzGDA5lUqeZjMYMCWNCW5mMxgwADJHvuYzGDA9fpM45XMYMD6aWj2l8xgwFsbdZmbzGDAXbol2ZvMYMD568QYnMxgwP3iZliczGDA9oKQmJzMYMBcurK+mcxgwKWodludzGDASQQKnJ3MYMCOC1DcncxgwKNhUhyezGDAnlb6n5vMYMArvGQWn8xgwEPrc1WfzGDAoh4RlZ/MYMBhjkzVn8xgwOrfBeGgzGDALrB1JKHMYMDdqYpnocxgwFp6HKqhzGDAxZsJ2J7MYMBoI2Rgn8xgwLD+YaqizGDA2y0v6aLMYMDfa/wno8xgwKKr4GajzGDAnxN4r6DMYMB0nOwzocxgwGSX+makzGDAC+Cip6TMYMBVjT7opMxgwD2kviilzGDArr4KaaXMYMDr7iJlo8xgwLnGb2amzGDA9Ae1pKbMYMDdCaXipsxgwA++JyCnzGDAk/EoXafMYMBERAKap8xgwDy9IdenzGDAKtu6FKjMYMCPtPNSqMxgwPIt5pGozGDAlnHY0ajMYMAXeOYSqcxgwOf591SpzGDApreLl6nMYMCIzXTaqcxgwCsadx2qzGDABddpYKrMYMBC5B6jqsxgwDmDS+WqzGDA0kbtJqvMYMA91wtoq8xgwKS9rqirzGDA8p/Z6KvMYMCEv6IorMxgwJ4/ImiszGDAxolQp6zMYMBa+k7mrMxgwCCdgiWtzGDAR+YdZa3MYMB730SlrcxgwKBpF+atzGDAe/OiJ67MYMAMpyZqrsxgwNEbsa2uzGDA/kXF8a7MYMCxDy42r8xgwPZiw3qvzGDAhgdYv6/MYMBxCsEDsMxgwPXatEewzGDANa8Gi7DMYMDOMOvNsMxgwPJRcBCxzGDAWsWPUrHMYMAq31iUscxgwOgrydWxzGDAc9MUF7LMYMCLXGRYssxgwEJycJmyzGDA6uws2rLMYMASyZoas8xgwAipylqzzGDAhLDWmrPMYMBkypbas8xgwOOd9xm0zGDAl5SjWbTMYMB/Po6ZtMxgwOHfjtq0zGDAUmJHHLXMYMBkOORetcxgwOcRuKK1zGDA0hXj57XMYMDUbQgutsxgwEdvenS2zGDAgQhDu7bMYMCmfPQBt8xgwJ0KYUi3zGDAKLc2jrfMYMDxliDTt8xgwDgAe1W3zGDARgEhnbjMYMDjm/reuMxgwEk8JiC5zGDA4CbIYLnMYMAb9wOhucxgwKHPzly5zGDAgIAzYLrMYMCK0dyfusxgwOPXvd+6zGDARmHkH7vMYMBxR0lgu8xgwNTID6G7zGDAcbr14rvMYMCW63UlvMxgwMGkFmm8zGDA/CGirbzMYMD25CvzvMxgwHQ24Tm9zGDAfHR8gb3MYMB5pDjJvcxgwFqy0BC+zGDA8hbTV77MYMDH9ieevsxgwH5qgeO+zGDABsV9J7/MYMBjSUhqv8xgwCGVv6u/zGDAshPz7L/MYMA89HktwMxgwED/ym3AzGDA8XYbrsDMYMBAHInuwMxgwM6iOC/BzGDA3/zPcMHMYMA5xN6ywcxgwFywOPbBzGDArIJ6OsLMYMD0Xqh/wsxgwN6mNMbCzGDA+CVCDsPMYMCJZptWw8xgwA4o8p7DzGDA5dWs5sPMYMAJBdUtxMxgwHoENXTEzGDAj1YGucTMYMBFS8r7xMxgwOj2ND7FzGDATcOhgMXMYMBlW+7DxcxgwJ1kDgjGzGDAPAEuTcbMYMAHzEGUxsxgwBJD/t3GzGDAzpmiKMfMYMBch4Vzx8xgwOAY4r3HzGDAFXSFB8jMYMAKfENQyMxgwBd4JpfIzGDA0GdI28jMYMDMyh8eycxgwLSma2DJzGDAWf2kosnMYMAW8SzlycxgwMjHQyjKzGDAyruqbMrMYMC6BRuzysxgwMSRrfrKzGDANbdJQ8vMYMASLESMy8xgwFsHitXLzGDANMPzHszMYMDX2R5ozMxgwKFwirDMzGDAH5OG+MzMYMCjgl9AzcxgwMgDP4jNzGDAtUU50M3MYMCq2lsYzsxgwMQxzWDOzGDAv5fJqc7MYMA0sivzzsxgwA/OvzzPzGDApJ5Xhs/MYMDW6OXPz8xgwLNSVhnQzGDAVeqQYtDMYMCX0nKr0MxgwMDBEPTQzGDAyF1CPNHMYMBBYleE0cxgwMUVJczRzGDAoUbKE9LMYMBg/lBb0sxgwOPds6LSzGDAMjkD6tLMYMBKfYgx08xgwAIoMHnTzGDAqyY6wdPMYMAHn5UJ1MxgwHnSSFLUzGDA/TeJm9TMYMBrdVbl1MxgwK7RSC/VzGDAcGU/edXMYMBZhRfD1cxgwOSowAzWzGDAgIUpVtbMYMCkbhCf1sxgwJEWZufWzGDAJPOLL9fMYMDalKh318xgwEwR37/XzGDAwvs6CNjMYMBOb9ZQ2MxgwApK7ZnYzGDAHqCi49jMYMAg17It2cxgwA8N53fZzGDADWNRwtnMYMCwHc8M2sxgwD38YVfazGDA9kfeodrMYMCj/Cns2sxgwO87hDbbzGDAhLgAgdvMYMCcS7TL28xgwEMuphbczGDAAMHeYdzMYMBiJW6t3MxgwMClWPnczGDAAySCRd3MYMB6pf/N4cxgwA+8sPHfzGDAW6LAO+DMYMANkTWF4MxgwP1u7s3gzGDAnzSXFeHMYMD0WNZc4cxgwJTXKKThzGDAdcXM6+HMYMCSKgs04sxgwBsI93zizGDA/YjpxuLMYMD2uF0S48xgwNQc3l7jzGDA7Kr2q+PMYMC4+nH548xgwEhDIUfkzGDAP3HalOTMYMDKyV3i5MxgwPOGRi/lzGDA1Zybe+XMYMC+AMfH5cxgwDPo2BPmzGDAIcLrX+bMYMD5PAqs5sxgwOl2RPjmzGDAb9P2ROfMYMAsaAmS58xgwJxFD9/nzGDAOvHqK+jMYMAMRYZ46MxgwNWe18TozGDAdyzLEOnMYMCfVCFc6cxgwGBF3abpzGDAz4iE8enMYMDlKUA86sxgwAMFN4fqzGDAOFeB0urMYMADSDAe68xgwIa8mWrrzGDAp17at+vMYMAe3nAF7MxgwESZO1PszGDA+WoboezMYMABTfLu7MxgwAyRrDztzGDAgCUJiu3MYMBeAvfW7cxgwD9DoSPuzGDAOewxcO7MYMB2ZqO87sxgwNxpEAnvzGDA8WKLVe/MYMArXRii78xgwPPLve7vzGDAdhGqO/DMYMA4IryI8MxgwAV4S9bwzGDAt3sZJPHMYMDr5hxy8cxgwD3Rj8DxzGDAlFyND/LMYMAST3xe8sxgwHAfTq3yzGDAirlq+/LMYMBnAQ5J88xgwKrTIpbzzGDA28VF4vPMYMCTJEAt9MxgwAJ6xXf0zGDAkTRSDfXMYMCzCt9Y9cxgwIb6JKX1zGDAiUWK8vXMYMDX34NB9sxgwLlDZpH2zGDAGzPY4fbMYMAJT1gy98xgwCWkuYL3zGDA6y/G0vfMYMA+kyUi+MxgwINranD4zGDA5CgwN/vMYMBjpqmC+8xgwIUi61b5zGDAMILkovnMYMCuka/u+cxgwMhueDr6zGDAwZxxhvrMYMApkaXS+sxgwLufRh/7zGDA5hAibPvMYMANYHu5+8xgwM0+Rgf8zGDAXZh9VfzMYMChjiWk/MxgwJEwJvP8zGDAb4mlQv3MYMDyJVeS/cxgwKziRuL9zGDAb49DMv7MYMChxTqC/sxgwBeBNNL+zGDApvEBIv/MYMAHm15x/8xgwJtAJ8D/zGDAKNNADgDNYMBE5bBbAM1gwJ1FdKgAzWDAiGp09ADNYMBDh6s/Ac1gwCBbVooBzWDAvUau1AHNYMDJed8eAs1gwAjOFGkCzWDAfhZvswLNYMDXIAj+As1gwIMsB0kDzWDAN52MlAPNYMC0XKngA81gwGmYeS0EzWDAU5ruegTNYMCt6A7JBM1gwIPv8RcFzWDA0NmXZwXNYMC22Zi3Bc1gwAl0uwcGzWDAhELMVwbNYMBh2KqnBs1gwPE9OvcGzWDAyMghRgfNYMD9GUqUB81gwKV78uEHzWDAJQ1DLwjNYMDLrl18CM1gwLL1T8kIzWDAULolFgnNYMC7aCRjCc1gwHp0fLAJzWDADaro/QnNYMBD5NaPEM1gwNPOrt4OzWDAzq3nLw/NYMBburCAD81gwCSCztAPzWDArrYMIBDNYMDFH11uEM1gwAVMy7sQzWDAH3SlCBHNYMA+GMVUEc1gwMbrbaARzWDAWbCq6xHNYMCmbX02Es1gwDn2FoESzWDAGhATzBLNYMDC4l8XE81gwASYZGMTzWDAQb0bsBPNYMDI/pL9E81gwJYqXkwUzWDAo54wnBTNYMDLXj3sFM1gwBWtPzwVzWDAcW3hixXNYMC5EQXbFc1gwHZQgykWzWDArXekdhbNYMA5JWzCFs1gwFee1A0XzWDA/nsxWRfNYMDPhtikF81gwL3/5/AXzWDAvQuMPRjNYMDuhFeLGM1gwP6CbtoYzWDAI+eMtxzNYMDsnPOdG81gwA4m0OkbzWDAUf9rNRzNYMCAH9KAHM1gwDB+IcwczWDASa10Fx3NYMBFZABjHc1gwMEDtK4dzWDAYe75+h3NYMCLhJtHHs1gwPOBt5QezWDAaXde4h7NYMBps5kwH81gwKYOOX8fzWDAbYwKzh/NYMDndwcdIM1gwIbO/GsgzWDAIPbTuiDNYMDyenMJIc1gwAOdvVchzWDAAEO4pSHNYMBPBxLzIc1gwL4ZEEAizWDAQKiLjCLNYMB2J53YIs1gwEttMyQjzWDAk3c2byPNYMA1yfm5I81gwPbwvAQkzWDAfu6fTyTNYMCk8L6aJM1gwAo7JeYkzWDA3gIHMiXNYMCam6p+Jc1gwM3AysslzWDAPwn8GCbNYMCvnRNmJs1gwMvl7rImzWDA/2N1/ybNYMAdaoFLJ81gwNEKv5YnzWDAONNT4SfNYMAYa8krKM1gwGQ2SHYozWDAd7kLwSjNYMAL8RwMKc1gwFoXqVcpzWDAD60BpCnNYMBeVRTxKc1gwEapiD4qzWDAgWkdjCrNYMBz9sLZKs1gwLr/TicrzWDAvcaedCvNYMBgTYbBK81gwFam9Q0szWDAIw/VWSzNYMC0m2KlLM1gwJp6UvAszWDAOCXjOi3NYMA1LiCFLc1gwIyj8c4tzWDAza1kGC7NYMATpu5hLs1gwO5Nl6suzWDAyMPA9S7NYMBt8ldAL81gwHNua4svzWDA98ZS1y/NYMCRrAkkMM1gwJaVI3EwzWDAJgVfvjDNYMCJZokLMc1gwHSfhVgxzWDAnL06pTHNYMArP0XxMc1gwLVofzwyzWDAqXI8hzLNYMChOb3RMs1gwPVo4RszzWDA/7noZTPNYMDIMtGvM81gwMVJ4PkzzWDAHQ5PRDTNYMBzRcGONM1gwPLLHtk0zWDAtrIxIzXNYMD22RJtNc1gwF9axrY1zWDASQkIADbNYMApxapINs1gwP1SKJE2zWDAIGGWhDbNYMCaZjkjN81gwA16EG03zWDAomGOtzfNYMAfMvACOM1gwIgvjk84zWDAOJ/KnDjNYMBB3xHqOM1gwAchFzc5zWDA55+WgznNYMCxWWvPOc1gwPfaLho6zWDAqCSZYzrNYMCD6umrOs1gwDUtWvM6zWDAeU6JOjvNYMBAHGuBO81gwBUPRMg7zWDAp19RDzzNYMAYFNdWPM1gwFuM2p48zWDAqHOC5zzNYMCFW5AwPc1gwOSLRHo9zWDAgj5sxD3NYMC4VAIPPs1gwNV4Plo+zWDAY1HhpT7NYMC0RF3xPs1gwDpHrTw/zWDAiO5vhz/NYMBt/6rRP81gwBlhSxtAzWDAsTjOY0DNYMB6O0erQM1gwAsd4bpBzWDA9jsAPkPNYMBTlf+IQ81gwIAJidNDzWDABCtnHUTNYMCPp0BmRM1gwMYe9a1EzWDAloaP9ETNYMDfT7s6Rc1gwDm1839FzWDAeHfRxEXNYMAM5HUJRs1gwJNt101GzWDAn7gIkkbNYMD7JNfWRs1gwL+PExxHzWDAhgbDYkfNYMBVBV+qR81gwLge+/JHzWDASqkiPUjNYMBt9QOJSM1gwJCzdNVIzWDAkbL5IUnNYMD/ZL9tSc1gwJ5tz7hJzWDAvGjRAkrNYMD5SBdLSs1gwFHCJJFKzWDAaAqx1UrNYMD5y6UZS81gwNAU+FxLzWDAUFpFoEvNYMA6eLDjS81gwOu20SdMzWDAk4s8bUzNYMAFgVyzTM1gwKckF/pMzWDACkAGQU3NYMBVXCaITc1gwGboZc9NzWDAMeN8Fk7NYMCZXQVdTs1gwP6srFBNzWDA2otKME/NYMBbrBJ3T81gwHnLHb5PzWDAlfuDBVDNYMAEI3JNUM1gwN79u5VQzWDA8Pcj3lDNYMDtw4QmUc1gwMqGum5RzWDAu4eutlHNYMAqJD3+Uc1gwONBTUVSzWDALkvii1LNYMDvSaDRUs1gwM5SAxdTzWDAzSGsW1PNYMBRF82fU81gwLOkc+NTzWDAtQqTJlTNYMBTY1dpVM1gwAtxBaxUzWDAPx+87lTNYMC0JsExVc1gwIaUHXVVzWDAzQ7vuFXNYMCcWVH9Vc1gwGuUOUJWzWDAIOr8h1bNYMCtBvHNVs1gwI7glBRXzWDAMAWRW1fNYMDaENKiV81gwGeTaupXzWDAMKVOMljNYMBnwdV5WM1gwIfRLMFYzWDArqCvB1nNYMC7hotNWc1gwH4mvJJZzWDAYMzY1lnNYMCWStwZWs1gwBjRaFxazWDAMF/YnlrNYMAqtWrhWs1gwMQBSSRbzWDAq4WWZ1vNYMChg8yrW81gwPHEJ/FbzWDAjZtBN1zNYMC6Mq19XM1gwPfQoMRczWDAK5HAC13NYMBflxJTXc1gwKr9M5pdzWDAoSzi4F3NYMBUwIUnXs1gwLQvMG5ezWDAop0YtV7NYMDUKSf8Xs1gwMukUENfzWDA857Til/NYMBjNMnSX81gwB5suhpgzWDAhXE7YmDNYMDc+jepYM1gwL3gdO9gzWDAyfUtNWHNYMDxumB5Yc1gwLZMYbxhzWDAk8mF/mHNYMDlSSFAYs1gwLrViIFizWDATuLlwmLNYMAGqmkEY81gwJcXXEZjzWDAoFU1iWPNYMA4R7rMY81gwPoVYxBkzWDAQdvaE2PNYMDVOoVeY81gwL8tdt5kzWDArjRlJGXNYMAjNJppZc1gwH/hna5lzWDA70mC0GTNYMDGFDM6Zs1gwCSVuIBmzWDANtzmx2bNYMDaYZIPZ81gwJBVXVhnzWDAzzK/hWbNYMBiBljrZ81gwC49hhRnzWDA2R80XWfNYMAxtxmmZ81gwAf9M+9nzWDA/T9wOGjNYMAuEt+BaM1gwOi1estozWDAcyXdFGnNYMD0Lokxas1gwHTUZHFqzWDA11tTsWrNYMBPKe7zas1gwLQ2tjhrzWDAgZeRz2rNYMA+ufXEa81gwM5CCAxszWDAcuQNU2zNYMDq2/KZbM1gwGSddd9szWDAzKVZI23NYMAZ+Lhmbc1gwBbE36ltzWDAoK8U7W3NYMBelowwbs1gwMN6WnRuzWDAIDkEuW7NYMDiaBz/bs1gwBRl30VvzWDA+ZPrjG/NYMBoVfXTb81gwKaXwxpwzWDATzMtYXDNYMDJEq+mcM1gwACILOtwzWDACjTtLnHNYMDvTTZycc1gwLLnMrVxzWDA6osF+HHNYMDYZNA6cs1gwNUr0X1yzWDAGks3wXLNYMAPr9sEc81gwKg4n0hzzWDA1wmFjHPNYMCPkJ7Qc81gwFOs8BR0zWDA8spZWXTNYMDsQrmddM1gwAYQVeJ0zWDA4+Z2J3XNYMBFhyhtdc1gwFNPdLN1zWDAug5q+nXNYMA+lBxCds1gwLuFsYp2zWDADjXT03bNYMD6FRAdd81gwA5oLGZ3zWDAOTkGr3fNYMD5U3b3d81gwNCQQz94zWDAcgcuhnjNYMBvA1nMeM1gwH5P6hF5zWDAQDQMV3nNYMCAvdubec1gwFZTdeB5zWDAufb9JHrNYMAb9Ylpes1gwJJ9P656zWDAB1tQ83rNYMB8W904e81gwEHf9357zWDA0gGsxXvNYMCf6fgMfM1gwKy1J1V8zWDAltgennzNYMASXUHnfM1gwOOYVjB9zWDAH7gveX3NYMA96afBfc1gwI++sAl+zWDApbvCUH7NYMBuc9OWfs1gwP8DpNx+zWDAF8trIn/NYMCYFltof81gwIZrna5/zWDA26dE9X/NYMCsueE8gM1gwN2Ih4WAzWDADBWXzoDNYMBvHtIXgc1gwAL4N2GBzWDAEA7oqoHNYMCYU1L0gc1gwDSy8zyCzWDAEj+ehILNYMBDawfMgs1gwMBkYBODzWDAfBTXWoPNYMBUU4mig81gwGjtZuqDzWDAC/3aMoTNYMADCSF8hM1gwC6sucWEzWDAWbJcD4XNYMBHCMBYhc1gwGyktqGFzWDAG37i6oXNYMDDfXs0hs1gwBCjUE2IzWDApkShxYbNYMCVzM4Oh81gwGTM0liHzWDAzseipIfNYMDvKwfth81gwHJ4azeIzWDAYqAcg4jNYMCFMKjOiM1gwJz6XRmJzWDAtduAY4nNYMDMFJesic1gwC43S/WJzWDAVIjSPYrNYMCTMSOFis1gwI0vscuKzWDAyO2hEYvNYMC3pWFXi81gwDxhZZ6LzWDAoC+iLI7NYMBM5ogsjM1gwMfdunWMzWDArFtewIzNYMBUXhEMjc1gwAkYUFiNzWDAe9UlFZDNYMAOD8hnkM1gwHU0u7qQzWDAuhlSDZHNYMCG387Xjs1gwH1PxSKPzWDA71aubY/NYMC+NoS1j81gwNTjUv6PzWDAWIBfQ5DNYMAL7t+NkM1gwBj0vdeQzWDAsz3AIZHNYMDxMfdrkc1gwH3GQbaRzWDAZEiIAJLNYMBNbc9Kks1gwNCwGpWSzWDAipB035LNYMBEGvkpk81gwIFEtnSTzWDA902wv5PNYMDB5fYKlM1gwME5kFaUzWDAzQhzopTNYMDnDKPulM1gwN4XHzuVzWDAJvDXh5XNYMCS4cnUlc1gwLQw5SGWzWDAumcMb5bNYMAzakm8ls1gwCjYmwmXzWDAmD7UVpfNYMB4JM2jl81gwPhJf/CXzWDAjurfPJjNYMDu1uqImM1gwIn0j9SYzWDAD/fPH5nNYMDyidFqmc1gwIRKsrWZzWDAMg2YAJrNYMBJc6JLms1gwJmw55aazWDAPDZ/4prNYMBR2HYum81gwNvc6XqbzWDARe3ax5vNYMBqCmEVnM1gwO6mcWOczWDAqP78sZzNYMBWyBoBnc1gwP3B2FCdzWDAXUXdoJ3NYMBg6d/wnc1gwDJarUCezWDAU1wmkJ7NYMB3ODLfns1gwK6ami2fzWDAHZQFe5/NYMDzK8bHn81gwOHSXRSgzWDAXqQBYaDNYMBaaqitoM1gwIQkavqgzWDA+2fER6HNYMAw+5KVoc1gwIENL+ShzWDA1KkmM6LNYMAgJuuBos1gwAo0vtCizWDAZ5RYAafNYMBlundTp81gwKbbzkeozWDA5jSvmKjNYMC6WkfpqM1gwOCSKjqpzWDAnoIQi6nNYMBMTGjcqc1gwBu2Yy6qzWDAXTrlf6rNYMDYFlfRqs1gwJzT+yKrzWDA9StCdavNYMAV0hDJq81gwDdu+R2szWDA4nfNYqjNYMAz/pzCrM1gwArCGBOtzWDANs+7Y63NYMBLbw+zrc1gwFCHl+SpzWDATlX1L6rNYMCaBZB7qs1gwJLCcceqzWDAoWH9E6vNYMAGrp9hq81gwFoG56+rzWDAkubo/qvNYMCbqPJOrM1gwFu7uZ+szWDAxFPB8KzNYMCyfmBBrc1gwFAmo5KtzWDAI02z463NYMAXxC40rs1gwIANqIOuzWDAOu3O0a7NYMCWIEIfr81gwOMox2uvzWDAPAocuK/NYMAv+Q81tM1gwNR2GlOwzWDAnxUBnrDNYMB/gnzrsM1gwAzgXzmxzWDA+3h9h7HNYMBk/v3Vsc1gwNLrwSSyzWDA/Nvmc7LNYMCVG0zDss1gwFx9/hKzzWDAi479YrPNYMCEmU+zs81gwENyDE+4zWDAUdXWVLTNYMDIuimmtM1gwN8G9ve0zWDAqv04SrXNYMDMwJmctc1gwArE4O61zWDACnneQLbNYMBomm2Sts1gwN2MmeO2zWDAchHoM7fNYMAzQESDt81gwKxTkNK3zWDAOEz1IbjNYMB5lxdxuM1gwGGhTcC4zWDAFCr8D7nNYMCtCGdguc1gwKp+ArK5zWDAx+/vA7rNYMCFLSRWus1gwFQ0hKi6zWDAJAA6+7rNYMAidV5Ou81gwNIBlKG7zWDA7/uU9LvNYMAvjt5HvM1gwPZ3dZu8zWDAGFXo7rzNYMCARgVCvc1gwD/6VJW9zWDAtX3cN8LNYMB545k9vs1gwNJuNJC+zWDAN6EhMsPNYMCzB8c2v81gwHXaN4q/zWDAAOz93b/NYMCsTRUywM1gwJWDsGvFzWDAtgpgvcXNYMBqMqDawc1gwBmmFC/CzWDAXQSQg8LNYMCOM7Gox81gwLf2dvzHzWDAR8sBT8jNYMAc6f9vxM1gwJOzK8LEzWDA2OlBFMXNYMCFtCfcyc1gwGE8GBXGzWDAi8nvacbNYMCNHeO+xs1gwBUyDBTHzWDA+zWID8zNYMBhCexmyM1gwMUduLnIzWDAQa5vBM3NYMBJV/JVzc1gwEaS1ZjOzWDAdnh9BcvNYMCzU+tYy81gwOPCCojPzWDAnUA9/cvNYMBrjTFOzM1gwAtD98PQzWDA0FytEtHNYMDgu4lh0c1gwMp9oLDRzWDAoXn3/9HNYMCwHUzm0s1gwDt91zLTzWDAMC6lf9PNYMAfvdfM081gwAx0XBrUzWDAlTbMZ9TNYMC7QbD+0M1gwI6Pr07RzWDARg1DTtXNYMC1xSqa1c1gwOtQWOXVzWDAsePHltLNYMB9b7Dq0s1gwNGOND/TzWDAJyh1k9PNYMBY2RDn081gwJ8K5jjUzWDA2XXEidTNYMCldQ3a1M1gwBIPJCnVzWDAVQbzdtXNYMDPz0rE1c1gwCfQaRDWzWDAdKrvytnNYMAkCc2n1s1gwKPm/vPWzWDAHGBYQdfNYMB2zPSP181gwL7XHd/XzWDAyBIUMNjNYMArUzjF281gwBch1w7czWDA7NJCW9zNYMDwEE2q3M1gwETbdvrczWDAvBUiS93NYMA+uL6b3c1gwOvxQrfazWDAy9r3CdvNYMCjd41c281gwPyCP6/bzWDAMs1HAtzNYMCBAyZV3M1gwGs1NqfczWDAchlt+NzNYMA5ePJI3c1gwDC8u5jdzWDAZv+E593NYMACpgY13s1gwHl5HILezWDATlxMz97NYMAj5dsc381gwOrd0mrfzWDABPxVud/NYMAYrxwJ4M1gwP8of1rgzWDACBEzreDNYMAaFIgA4c1gwP+WIVThzWDAFwvqp+HNYMCs+sT74c1gwCN0Wk/izWDAn006ouLNYMAGGpb04s1gwJ+grkbjzWDAf6u3mOPNYMBc23zq481gwOTh2DvkzWDAMpkZjeTNYMAcSm/e5M1gwEXOvy/lzWDAr1XxgOXNYMCqVunR5c1gwOtJZiLmzWDAXXGYcubNYMCy/ZXC5s1gwPi1e+7pzWDAab6a/ufNYMDXB2xO6M1gwO9F5Z7ozWDA2/TV7+jNYMCMU2rq681gwCclOTrqzWDAmbNkjOrNYMD10/nd6s1gwNWG1i7rzWDA1pjX6+3NYMDNMp5n7M1gwO5Bg7XszWDAKjXRA+3NYMApToRS7c1gwJ99r+rvzWDAZvRkmO7NYMDALqjq7s1gwHVf0DzvzWDAPbayju/NYMBEzebf781gwAx0HeHxzWDAO5iMzvDNYMBWOUEd8c1gwLu9pGvxzWDAQ82+ufHNYMBknPIH8s1gwJPMOtfzzWDAHahC8vLNYMAX3dM/881gwJz5Mo3zzWDADW592vPNYMBWBnEn9M1gwNGXz9j1zWDAiYeIDPXNYMB7qalZ9c1gwNykTqf1zWDAn+Rx9fXNYMAZmGxE9s1gwIS7Y5T2zWDA/XzW5PbNYMA8Pco1981gwKOp14X3zWDAFmXW1ffNYMAsUi8l+M1gwPbFlHP4zWDAvuwbwfjNYMArB6kN+c1gwH8sdFn5zWDAdkzqpPnNYMCueCbw+c1gwMfsNzv6zWDAOcw4hvrNYMDcclrR+s1gwJqD2xz7zWDAxl4zafvNYMDExOi1+81gwLvxEgP8zWDA5w0hUfzNYMB2kfSf/M1gwHjIsu/8zWDAV84EQP3NYMB3+ICQ/c1gwBPPGOH9zWDAWNChMf7NYMByxN2B/s1gwI+qg9H+zWDARnknIP/NYMDacPVt/81gwI1UYrv/zWDALGJrCADOYMDIgiFVAM5gwFznkKEAzmDASOvs7QDOYMCKy606Ac5gwFuxtIcBzmDA5xNr1AHOYMCq+NkgAs5gwNt1v2wCzmDAGGEpuALOYMCtayADA85gwLRbGk0DzmDAbukMlgPOYMBrEUnfA85gwMcRzigEzmDAwoJFcwTOYMBhtKq+BM5gwMEM8QoFzmDAkIj3WAXOYMAUTdOoBc5gwLZ2FvkFzmDAfjlESQbOYMAiX/aYBs5gwLgGwOcGzmDAqDh8NQfOYMBxw1CBB85gwO/h0soHzmDAMxsLEwjOYMCsemxaCM5gwLoMS6EIzmDAVgHs5wjOYMDq54kuCc5gwKnouXUJzmDANHbDvQnOYMADW38GCs5gwAjPyU8KzmDAziSWmQrOYMCZtN3jCs5gwNFFki4LzmDAzG2WeQvOYMC23s/EC85gwJrHLhAMzmDANjKOWwzOYMCRGN+mDM5gwLyREfIMzmDAZOwaPQ3OYMDFEuGHDc5gwBjXO9INzmDAnSZQHA7OYMDDjD9mDs5gwHSwEbAOzmDAZcPW+Q7OYMCbPo5DD85gwEI4ZY0PzmDAi96M1w/OYMDulsIhEM5gwFgpxGsQzmDA7Dd5tRDOYMCUKtj+EM5gwECf5kcRzmDAA7V6kBHOYMDBR1XYEc5gwOJSth8SzmDA6sdFZxLOYMDXMyyvEs5gwHt2k/cSzmDAqYd+QBPOYMCwXC2KE85gwIkUONUTzmDAddgjIRTOYMDkNgBtFM5gwAOZf7gUzmDAXGpBAxXOYMC82B9NFc5gwN1v+pUVzmDAx+Do3BXOYMCLmgAiFs5gwBoDoWYWzmDAD2YyqxbOYMCBGgTwFs5gwMJSazUXzmDAwg+NexfOYMCVUlHDF85gwI132AwYzmDAOhbdVhjOYMDGGf+gGM5gwOgW6OoYzmDAXQVJNBnOYMCAGv18Gc5gwNHSRcQZzmDACK8VChrOYMDDzQ1PGs5gwOBgb5MazmDAEixw1xrOYMCKYkobG85gwBdJI18bzmDA52hRoxvOYMD29C3oG85gwE95my0czmDAbDOmcxzOYMBWrk66HM5gwEK9kQEdzmDA/Nd1SR3OYMA6v/GRHc5gwE8LBdsdzmDARWphJB7OYMCzOOxtHs5gwJ1ygLcezmDAC5ntAB/OYMDmrBVKH85gwEVrypIfzmDAPjXk2h/OYMAx02oiIM5gwM39XWkgzmDARpW3ryDOYMBE9471IM5gwPimyzohzmDAjl+PfyHOYMBEofjDIc5gwFEOAwgizmDAf/qvSyLOYMDBUBGPIs5gwDRyNtIizmDA6HtUFSPOYMC+9WxYI85gwJ+9bZsjzmDA56SX3iPOYMDqqE4iJM5gwE1VrWYkzmDA6dLhqyTOYMDvrPvxJM5gwDh3LjklzmDANsTAgSXOYMDDi0LLJc5gwI7CBhUmzmDAjuS9XibOYMBvmyGoJs5gwNFLBvEmzmDAwycIOSfOYMD7RMN/J85gwI9NX8UnzmDAsXgCCijOYMB+BdFNKM5gwI+CvpAozmDA2oQM0yjOYMBdqNMUKc5gwBzzNVYpzmDAXbpwlynOYMByHcnYKc5gwK6UcRoqzmDAW9GWXCrOYMA6iWKfKs5gwCD13uIqzmDA6OBMJyvOYMBMCKlsK85gwB6EnrIrzmDABMoE+SvOYMCNztM/LM5gwClW34YszmDAHprzzSzOYMAc77EULc5gwIJ171otzmDAXIiioC3OYMCTyeHlLc5gwOnVvyouzmDAk+s6by7OYMAYBUSzLs5gwPO16PYuzmDAeUUwOi/OYMBeeQd9L85gwDRXcr8vzmDADPeWATDOYMA/IYdDMM5gwNoWaYUwzmDAl9AaxzDOYMCCuIcIMc5gwMeFPkoxzmDAkNpVjDHOYMAMrAHPMc5gwGZgXBIyzmDAUR5cVjLOYMDsDFibMs5gwI9ZS+EyzmDAuiG/JzPOYMAePlhuM85gwAVh3bQzzmDAUSga+zPOYMBtweBANM5gwIpk2YU0zmDASrXMyTTOYMB0PQ0NNc5gwGc83E81zmDA+c5SkjXOYMDT8p3UNc5gwBcb3BY2zmDAcR09WTbOYMAn8eKbNs5gwDkQ0942zmDAqp4MIjfOYMAn6pllN85gwJ2zdqk3zmDAZAih7TfOYMANcRsyOM5gwKT963Y4zmDA9I/juzjOYMBfc8oAOc5gwKvuhkU5zmDAFQL/iTnOYMAn4S/OOc5gwNcv9hE6zmDAKyQsVTrOYMChwASYOs5gwBmp09o6zmDARJC1HTvOYMAoQMVgO85gwDLSF6Q7zmDAq5jM5zvOYMAIfQssPM5gwBzj2HA8zmDADlgNtjzOYMDlBJD7PM5gwKSXS0E9zmDAgcYqhz3OYMAylgfNPc5gwGH+vRI+zmDAOtA3WD7OYMCeAnGdPs5gwFyiUOI+zmDApXLNJj/OYMCp5t5qP85gwKg0g64/zmDAuyrI8T/OYMDjebg0QM5gwNE/NXdAzmDAboNFuUDOYMCJ2vf6QM5gwHSwaTxBzmDAjTHHfUHOYMCFtdu+Qc5gwNLrtP9BzmDAFUoEQULOYMDyJAqDQs5gwB8978VCzmDAnnXMCUPOYMCAhLJOQ85gwFe995RDzmDA2/Ca3EPOYMAi3N4kRM5gwM7faG1EzmDA+I7ytUTOYMDXxDr+RM5gwK14/kVFzmDAhFTijEXOYMDVjJTSRc5gwImfYhdGzmDAgctFW0bOYMB8hlKeRs5gwAYWouBGzmDAu8NXIkfOYMCSn5FjR85gwAyujqRHzmDAnlx95UfOYMAmPXQgR85gwM1QxmdIzmDAZhx5qUjOYMBCFjf5R85gwIWDnS5JzmDAK4lxcknOYMDYHx23Sc5gwBIWXRRJzmDAhUApQ0rOYMA8loKKSs5gwEmlS9JKzmDAM+K1GkvOYMAasdxjS85gwItLBK1LzmDA+8QL9kvOYMCx3Cw+TM5gwGoMc4VMzmDABPmny0zOYMA3unoQTc5gwNgUbFNNzmDAC7J7lU3OYMBvOhXXTc5gwIGk2BhOzmDANaIuW07OYMCYel2eTs5gwOpVmOJOzmDAP9mVKE/OYMAu5kvkTs5gwImAfrdPzmDAOhUYgU/OYMCi9BfPT85gwDB9MpRQzmDAyvSC3VDOYMBgYWAmUc5gwAQUIW9RzmDANyHet1HOYMCKAn0AUs5gwOZZJEhSzmDAS/guj1LOYMAM1OPWUs5gwHMRnh5TzmDAm1gHZlPOYMBhZMddU85gwAt7//RTzmDAQJsHPFTOYMBsYwqCVM5gwEjErcdUzmDAw92bDVXOYMASo4FSVc5gwMCeg5dVzmDAlJ563FXOYMD/8k4hVs5gwKpw2WVWzmDAcqWShFbOYMBnINI1V85gwEDv+HpXzmDA+DeywFfOYMDsj2EKWM5gwHmcIFFYzmDAZYUPhVnOYMBipFf1Wc5gwMdoV0VazmDAkIMtcVrOYMDdwSlNW85gwPkApI9bzmDAR0Qh0VvOYMA6TtcRXM5gwJlGGVNczmDAa88wlFzOYMAtSDnXXM5gwHl5YRhdzmDATMolXF3OYMCDM9qhXc5gwD8wb0hezmDA8IzEKl7OYMCDVghwXs5gwDHYqbZezmDAsy6F/V7OYMCBMQtFX85gwEyJHo1fzmDA+hms1V/OYMAZZ54eYM5gwBx58WdgzmDADw7QsWDOYMC6ukv8YM5gwAvnD0dhzmDAEyq5kWHOYMCJuw3cYc5gwE2X8iVizmDAMntLb2LOYMDf5OS3Ys5gwNspd/9izmDAKepLRmPOYMCE7tmMY85gwAeFTtNjzmDA7nTHGWTOYMDUuW1gZM5gwMZGfKdkzmDAzqBb72TOYMAoJeQ3Zc5gwBAIsIBlzmDAG+WgyWXOYMDCjagSZs5gwKjvq1tmzmDApfKOpGbOYMCjA//sZs5gwDy/HDVnzmDAISdCfWfOYMDzJYDFZ85gwIK+5g1ozmDAhmuNVmjOYMDKGIifaM5gwLD6/uhozmDAbPHwMmnOYMC960F9ac5gwBHA4cdpzmDA3wrBEmrOYMCJ8M5das5gwI/I+6hqzmDADWQ09GrOYMAE/mU/a85gwAo5bIprzmDAnhss1WvOYMBJPJwfbM5gwLn8s2lszmDAhM1os2zOYMCBK6n8bM5gwC6We0VtzmDAfqMIjm3OYMBQ5mXWbc5gwHhKqR5uzmDALQbxZm7OYMCcQF2vbs5gwH/X9PduzmDAa7q9QG/OYMD72PyJb85gwPrgxNNvzmDAYZcpHnDOYMBD/TNpcM5gwLMn0LRwzmDAtyArAXHOYMAr9TtOcc5gwP8CqptxzmDAjAcq6XHOYMDJhI82cs5gwHRdqINyzmDAnxtf0HLOYMAc7Wccc85gwKQlimdzzmDAHMYGsnPOYMChYOr7c85gwBSqlEV0zmDAiaKbjnTOYMC9rF/XdM5gwEOUKiB1zmDA7t9WaXXOYMAYp15Pd85gwDbWr0R2zmDABzjFjXbOYMCFwUHXds5gwGUB44F5zmDA4pU+R3jOYMDaFIGSeM5gwGKoOnN6zmDAF0bjLHnOYMBDA/Sne85gwOVWufJ7zmDA9WmHwHrOYMCKfZ4Pe85gwOj+9V17zmDA6d21q33OYMDSGjWGfM5gwK3igM18zmDAqiD1E33OYMDsEItZfc5gwLux09J/zmDAdjH8IoDOYMCKHUJxgM5gwChW7L2AzmDA9hs1CYHOYMAXkTSKf85gwGQ+MdZ/zmDAPgmtIoDOYMD2Eu9vgM5gwKm7t72AzmDAadnqC4HOYMBfCkpagc5gwHVFlaiBzmDAJgGX9oHOYMDBqT9Egs5gwF6qcZGCzmDA0BMb3oLOYMCw6zIqg85gwPgZtXWDzmDAcfiIwIPOYMAzL7gKhM5gwORRhVSEzmDAe0YgnoTOYMDeqarnhM5gwLfWSjGFzmDAzFkee4XOYMA2e1XFhc5gwL4/ExCGzmDAyoNKW4bOYMDSTvqmhs5gwLGnKPOGzmDAH2ffP4fOYMBxEReNh85gwMJpvdqHzmDASk62KIjOYMC3fgR3iM5gwHGAo8WIzmDA7Dl9FInOYMCCOX1jic5gwIccjrKJzmDArXSyAYrOYMDDLN9Qis5gwAJZ05+KzmDAqe9Z7orOYMDUt108i85gwGaXxomLzmDAwnSj1ovOYMDjhskijM5gwH69MW6MzmDACCYEuYzOYMDtCGYDjc5gwDyRdU2NzmDAPWVal43OYMBBYj/hjc5gwJJjRiuOzmDAkRh+dY7OYMCVtR3Ajs5gwFO6XAuPzmDAbT9XV4/OYMAQwx+kj85gwC03ufGPzmDA9b8xQJDOYMDTuJqPkM5gwC0gtd+QzmDA0lEQMJHOYMCcwGyAkc5gwDQildCRzmDAm9hRIJLOYMDscXJvks5gwHkrrb2SzmDAIKcJC5POYMAWql1Xk85gwGnkS6OTzmDA5nll7pPOYMDe7AY5lM5gwGLnMoOUzmDAzO4HzZTOYMCUq1YJl85gwDYihaqVzmDABSoK9ZXOYMDRlgFAls5gwLPgi4uWzmDA7KDQ15bOYMBe+qYkl85gwEvjn3KXzmDASzPBwJfOYMAln70PmM5gwJCUG1+YzmDACRbGrpjOYMBqb+P+mM5gwFxqSe+ZzmDAtSf9PZrOYMC48vCLms5gwMhJI9mazmDA7QF6UZ3OYMDrBEUCnM5gwOU7dUyczmDARPU5l5zOYMDOMK7inM5gwFbikR6ezmDAobeIbp7OYMCa9CS+ns5gwNXcLQ2fzmDA6WREW5/OYMByERI9oM5gwK0DfoegzmDAkmb70aDOYMDoja8coc5gwJz05GehzmDApjznz6POYMB8Lxqcos5gwCxkF+qizmDA9Ak8OKPOYMBt6myGo85gwH9yjtSjzmDA8+ODIqTOYMDfIDRwpM5gwNC4ib2kzmDAv42FCqXOYMBc7yRXpc5gwKb1Y6OlzmDAG6MY76XOYMDKJIU6ps5gwMcw9IWmzmDAQ6V50abOYMDOkEodp85gwMLXcmmnzmDA1mIWtqfOYMCA/VwDqM5gwN9JseOpzmDATr4m7qjOYMC1mPY8qc5gwKpI24upzmDAkou52qnOYMCFsXUpqs5gwPcgKBSrzmDAd9ewYavOYMC34tquq85gwIxVqfurzmDAJab8R6zOYMANKOyTrM5gwGScj9+szmDAfpwmK63OYMCBBrZ2rc5gwHhdUsKtzmDAaWkKDq7OYMD+6AVars5gwM4rXaauzmDAHWLP8q7OYMAZejw/r85gwDM5iIuvzmDAqDq/16/OYMCIGdojsM5gwGAhpG+wzmDAkkALu7DOYMDirHAGsc5gwPga2FGxzmDAfI2TnbHOYMCpgJHpsc5gwI+y5DWyzmDAE3qwgrLOYMCibgfQss5gwPD7ux2zzmDAe5WKa7POYMA4NHK5s85gwJTeRge0zmDAkOLwVLTOYMAqpkyitM5gwPAhTO+0zmDA76bNO7XOYMB+giiItc5gwG1m1tO1zmDAFr03H7bOYMCTJTZqts5gwN6p37S2zmDA50A//7bOYMC3/qzet85gwPo6Qyi4zmDA5GiZ3bfOYMA1b8snuM5gwLw9NXK4zmDAaxnWvLjOYMCCtasHuc5gwGEsQRS6zmDAy9Vw67nOYMAZBLM4us5gwFmLjIa6zmDANtQK1brOYMC9m1wku85gwJSSzPu7zmDA0IW1ErzOYMAcHh9hvM5gwF3tsa68zmDAcbs9+7zOYMAx4mZGvc5gwIe3/N6/zmDAzFtkG8DOYMBMulZmwM5gwFBDULLAzmDAHDtn/8DOYMDcxulNwc5gwA/Q5p3BzmDAWiEW7sHOYMASmyA+ws5gwB1gaY3CzmDAr3Lm28LOYMDuxUMpw85gwHszsXTDzmDAafIOvsPOYMCkPFgGxM5gwE/IdE7EzmDAFVlVlsTOYMD++2fexM5gwBeDyybFzmDAwXNhcMXOYMA+C6C7xc5gwJDxTgfGzmDAJ/kUU8bOYMDsZ7Sexs5gwAcCFerGzmDAiyspNcfOYMCDTyl/x85gwE+/ycfHzmDA+LlCEMjOYMD7jdBYyM5gwOZPP6LIzmDAfpBf7MjOYMAf4Fs3yc5gwLpV8YPJzmDAz3xw0snOYMBrN78hys5gwBVNRXHKzmDA+bOCwMrOYMBze00Py85gwCaDW13LzmDAWzANqsvOYMDR5MX0y85gwOfmPT7MzmDA7MW6jsvOYMCOsVjPzM5gwGzjVhfNzmDAZM8rX83OYMBeMVenzc5gwOZvU/DNzmDAaY9LOM/OYMA+7c/I0M5gwKymGxLRzmDAaPIWXNHOYMAMGwmn0c5gwJE3fvPRzmDAiJTuQNLOYMC0NmqO0s5gwDaxtNvSzmDA8jlGKNPOYMCOnBp0085gwCGAz77TzmDAfIelB9TOYMDktNlO1M5gwFFCQ5XUzmDAn/WM29TOYMA8W8Qh1c5gwMAVNWjVzmDA9rcJr9XOYMCVfjD31c5gwHlnnEDWzmDAq+tFitbOYMCmJuvT1s5gwCnUNR3XzmDAGFMUZtfOYMA7DWau185gwPEeg/XXzmDAc9M0O9jOYMCNe6iA2M5gwLqeJsbYzmDAExIaDNnOYMBt3qhS2c5gwHGG6ZnZzmDA0dtu4tnOYMBIGGMs2s5gwFhXD3fazmDAdGARwtrOYMBCiVMN285gwO+egVjbzmDA8DJro9vOYMBdNKzt285gwKHLIDfczmDAFL21f9zOYMCgZ3TH3M5gwJBlSg7dzmDAp3FNVN3OYMA9nHmZ3c5gwNuQ8d3dzmDAgl+2Id7OYMDTNwpl3s5gwGnqL6jezmDA29BS697OYMAOYaAu385gwMdqPXLfzmDA4cphtt/OYMBEQxz7385gwDGEnEDgzmDAOCOWhuDOYMAthPHN4M5gwLbl2hXhzmDANtqDXuHOYMDP3/Gn4c5gwJnvFPLhzmDAnOkx0uLOYMAjVKkc485gwA62uGbjzmDACMcmsOPOYMDtR834485gwGX0tJzjzmDAAtTRoubOYMBxzFHk5s5gwLPL6SXnzmDAcRK8Z+fOYMDqh6Wp585gwMwF7uvnzmDApupEL+jOYMB1ZWVz6M5gwGYI5bjozmDAHsN2/+jOYMA7tB1H6c5gwFfnSJDpzmDAKLCp2unOYMAgUD4l6s5gwAoFsW/qzmDA1kt1uerOYMCfWEkC685gwIfwBUrrzmDAceHfj+vOYMBicdPT685gwPw0XBbszmDAX0gTWOzOYMDJq5qY7M5gwAshr9jszmDAY11zGO3OYMDzLD9Y7c5gwO/HWpjtzmDAoYHm2O3OYMABUtMZ7s5gwBSWwlvuzmDAAFRfnu7OYMDEpNHh7s5gwE+8MSbvzmDAl/+Ia+/OYMAScIix785gwLS8JvjvzmDArCgmP/DOYMDpr2GG8M5gwBNfps3wzmDApgrXFPHOYMAbwM1b8c5gwH+ITKLxzmDAaK496PHOYMBR0X4t8s5gwBnZ6XHyzmDAkA+WtfLOYMDEOW748s5gwEbzUjrzzmDAq2WWe/POYMDEHpG8885gwEr/Lv3zzmDAZN3TPfTOYMAkrJ9+9M5gwEbutb/0zmDAXaFBAfXOYMA/alSo8s5gwJqad8n1zmDAg7N9DfbOYMASFBhS9s5gwHSgU5f2zmDA7DZF3fbOYMBttcqB9M5gwEfpg7D3zmDALXfA9vfOYMCkIr08+M5gwOa7N4L4zmDAU1XbxvjOYMAzysF39s5gwCYvJZL5zmDABC+f1fnOYMArTQYZ+s5gwNJYf1z6zmDA6OCLoPrOYMB+Tvjk+s5gwKernij7zmDAcLzca/vOYMAy/RKu+85gwLVsa+/7zmDAKHW6L/zOYMBfz1Vu/M5gwLsOjav8zmDAT6EaJPzOYMCOWoEB/85gwJWhZUn/zmDAwZbSkP/OYMD67IvX/85gwM7cgRwAz2DAvWF1XwDPYMAwu1ChAM9gwHJet+IAz2DAspeCIwHPYMA3YylkAc9gwMTxxaQBz2DAmdD85QHPYMAgfhkoAs9gwKs2eOsBz2DAmUJ2cwTPYMCsT5WzBM9gwCeS6vMEz2DA4D+aNAXPYMDID951Bc9gwCwv1rcFz2DAlZF3+gXPYMA7BWs9Bs9gwKkVIIEGz2DA4MMnxQbPYMCQo5gJB89gwIkmS04Hz2DA6r0dkwfPYMCGIh7YB89gwDmI5BcGz2DASeGAYgjPYMBEE7qnCM9gwE4f2+wIz2DA4iLmMQnPYMD+fel2Cc9gwDrEaRkIz2DAxBI7QwrPYMA/5hGGCs9gwIpHP8gKz2DAH0GkCQvPYMDhKERKC89gwHl/FiMKz2DAOuvlCQzPYMBhWulJDM9gwBe1XIoMz2DAebVhywzPYMAhpBcNDc9gwHCrck8Nz2DACn4lkw3PYMDjjGzXDc9gwKFM1BwOz2DAFur1Yg7PYMC0rOapDs9gwCjGpfEOz2DAFWz1OQ/PYMBKqQ6CD89gwK3BtckPz2DAcEJfEBDPYMCqWAZWEM9gwFvuYJoQz2DA0swn3RDPYMD9jkweEc9gwOwObV4Rz2DAqgrcORLPYMDvqeVVE89gwCI535gTz2DAXONl3RPPYMDPsZUjFM9gwOuKD2wUz2DAg+/RthTPYMBo+UUCFc9gwM4Kyk0Vz2DA82zLmBXPYMD84dHiFc9gwAC8zCsWz2DA+iJcchbPYMDoKSO2Fs9gwM7pqfgWz2DAHJ63OhfPYMCxmnh8F89gwLcQa74Xz2DAiXOuABjPYMCx2WlEGM9gwAEpPIoYz2DAyD6r0BjPYMD1Dy8XGc9gwJv5YV0Zz2DAQ8cVoxnPYMDCEkroGc9gwAQDHCwaz2DAocvJbRrPYMBDiwKvGs9gwDskjvAaz2DA6gLaMhvPYMD4r0d2G89gwL1LAbsbz2DAmYDAARzPYMBh+CtLHM9gwJZPHZYcz2DAdMzD4RzPYMA5jpotHc9gwJqkMHkdz2DA+yMjxB3PYMActdUNHs9gwFYqwlUez2DAXukGnB7PYMBF8PngHs9gwJqlzCQfz2DATFmfZx/PYMAZx7CpH89gwECVOesfz2DAOXpvLCDPYMAUvKRtIM9gwLEVLK8gz2DA9m8+8SDPYMBtBRQ0Ic9gwGfkynchz2DACC+NvCHPYMD7nrACIs9gwEmX/Ekiz2DARwIHkiLPYMD5I6TaIs9gwLmYpCMjz2DA+5TebCPPYMBWDR+2I89gwI0K+f4jz2DAHdVnRyTPYMAcMcyPJM9gwKfBLtgkz2DAQLKaICXPYMDNWxhpJc9gwFlpnLElz2DAARab+iXPYMCt2RBEJs9gwJBcSY0mz2DAXl4o1ibPYMB7bZMeJ89gwNa3d2Ynz2DAC9DyrSfPYMATGFT0J89gwPcgmTkoz2DAxU0FfyjPYMDenejEKM9gwOXGogspz2DACnM9UynPYMAI/OibKc9gwN0YhuYpz2DAf2hDMyrPYMCClXyAKs9gwIeokM0qz2DAvAX/GSvPYMBOomVlK89gwLYZ1q8rz2DA667s9yvPYMAxqkQ9LM9gwFjZu4Esz2DA/7otxizPYMCWjCILLc9gwAxbHFEtz2DAi+gjmC3PYMAWoaPhLc9gwLjYRy4uz2DARqdCfC7PYMD1Hp3KLs9gwDj3whgvz2DAhsM8Zi/PYMDeec2yL89gwDmKV/0vz2DADGQqRTDPYMBjS36LMM9gwNWYS9Ewz2DAfNoOFzHPYMCGdzpdMc9gwM1dGaQxz2DAOShq7DHPYMBqIes2Ms9gwPqACIMyz2DAM7hI0DLPYMC9UlMeM89gwFJK4mwzz2DArs66uzPPYMBfnXsKNM9gwKjWxVg0z2DA9weDpjTPYMAGNcbzNM9gwBU7g0A1z2DAifaxjDXPYMBj1VfYNc9gwMs1eyM2z2DAOI/8bTbPYMD0iAu4Ns9gwI/E/AE3z2DA9tH3SzfPYMDHyRuWN89gwLgKgOA3z2DAoxg/KzjPYMAZNs52OM9gwNRrD8M4z2DAM15pDznPYMDLjbVbOc9gwF+b16c5z2DAhBi88znPYMD+W1g/Os9gwPJxMIo6z2DA6VNF1DrPYMCY6ZQeO89gwBpCbGk7z2DADdr9tDvPYMCLD3oBPM9gwOK39U48z2DAKjj6nTzPYMDGdb3uPM9gwFJ7H0A9z2DAlJnEkT3PYMBtwF3jPc9gwN04nTQ+z2DAy6FahT7PYMBOEdPUPs9gwPzR0SI/z2DA5OIDcD/PYMB/yK28P89gwATe9QhAz2DAOOoNVUDPYMDYcPugQM9gwIDcZ+1Az2DA1yWuOkHPYMCzQfuHQc9gwOOuGtVBz2DAU4r0IULPYMAZ2YFuQs9gwFK36rpCz2DAt7aEBkPPYMAlzuxQQ89gwIKrd5tDz2DArgz55kPPYMAvgdozRM9gwOUHRYJEz2DAxNgt0kTPYMAsQ5ckRc9gwCurC3pFz2DAUILI0EXPYMAFHlwnRs9gwPY3CH1Gz2DAciwx0UbPYMB8nYYjR89gwH39CnNHz2DA4LdjvkfPYMB5JyMHSM9gwNqB1E5Iz2DA1/M0lkjPYMB06vPdSM9gwCdzmyZJz2DA+H4gcUnPYMA2g6W+Sc9gwJ+ZuQ5Kz2DABQwoYErPYMDqAbWySs9gwOKCFAZLz2DALBrmWUvPYMBqSsKtS89gwOvB0ABMz2DAj8g/U0zPYMAmIFmlTM9gwH+zHPdMz2DAnPmPSE3PYMBXlraZTc9gwBk/mepNz2DArLxZO07PYMB69ACMTs9gwJDpftxOz2DAI2vfLE/PYMAEXyZ9T89gwN+7UM1Pz2DAiaddHVDPYMDmF35tUM9gwAF5rb1Qz2DAr2CoDVHPYMA8cFxdUc9gwMWOz6xRz2DAs+H8+1HPYMAPC/9KUs9gwITigplSz2DAWviQ51LPYMAMl/Q1U89gwIOb64RTz2DAjiil1FPPYMA7f0QlVM9gwCMSynZUz2DAv8G/yVTPYMA7JSceVc9gwBtOFnNVz2DALWwtyFXPYMDy1RwdVs9gwJ4WpnFWz2DAN1KSxVbPYMBa/WQYV89gwIPkvmlXz2DAEo1TulfPYMCgkk0KWM9gwFSM3llYz2DA3dUrqVjPYMDB/mT4WM9gwN450kdZz2DAL3Gal1nPYMCUdrXnWc9gwHxHJThaz2DA2Z/wiFrPYMA7HBHaWs9gwERFfytbz2DAdRZXfVvPYMDVJKfPW89gwNF7KCJcz2DAFNmodFzPYMBbeg3HXM9gwOt1Sxldz2DAZl99a13PYMDK6D+9Xc9gwIXQNA5ez2DAzyMoX17PYMCjKa2wXs9gwHlR+gJfz2DA/Q0tVl/PYMDCYkmqX89gwICmxP9fz2DAv/dBV2DPYMACNqivYM9gwKoQxAdhz2DA6M4DX2HPYMAuDRq1Yc9gwOSIuwliz2DAr3Y7XGLPYMDASaOrYs9gwEx62fhiz2DA4jhgRWPPYMDxbtmRY89gwA731N5jz2DAE2W5LGTPYMAa9RJ8ZM9gwOa2WM5kz2DAOQm/ImXPYMBu2Bx4Zc9gwMpRCM5lz2DAcI4fJGbPYMAiohV6Zs9gwCwBb89mz2DACDdYI2fPYMDHect1Z89gwFd/ycdnz2DAYxCEGWjPYMAhWjFraM9gwM3W9Lxoz2DAv67pDmnPYMBsd8Jhac9gwJkmd7Vpz2DA95U/CWrPYMChgetcas9gwHrfULBqz2DAanRJA2vPYMCNWbpVa89gwGDMU6drz2DADfwH+GvPYMDV7z5IbM9gwBBGHJhsz2DAovjU52zPYMAc2pM3bc9gwNBYkodtz2DAjJjY123PYMCBp34obs9gwPsZ7Hluz2DAITxMzG7PYMBNGJgfb89gwDoj+nNvz2DAGFBKyW/PYMBbu+YfcM9gwLL2tHdwz2DA+tbuz3DPYMAW+Rcocc9gwCuk2H9xz2DAExbY1nHPYMCKafQscs9gwJb8e4Fyz2DA+3bp03LPYMB8AzAlc89gwLSGsHVzz2DATOClxXPPYMD82EEVdM9gwIyrnGR0z2DABzxotHTPYMD4GDIFdc9gwFzTNVZ1z2DAj0zZpnXPYMDLRgT3dc9gwNfBjkZ2z2DAORarlXbPYMCxPLfjds9gwF6NBzB3z2DA8Y0afHfPYMDEexnJd89gwNAfiBd4z2DAGfDdZ3jPYMDqojO6eM9gwHbdHw95z2DAtXfdZ3nPYMAYe+XCec9gwC7XkB56z2DAcAIlenrPYMAHCejUes9gwGwCRi57z2DAtZN+hXvPYMD/TRvZe89gwIUfvil8z2DAytGueHzPYMBMB1DGfM9gwF0YFBN9z2DA2jRqX33PYMB+kN6rfc9gwE9RX/l9z2DAUzzzR37PYMD0LCeXfs9gwCCA+OZ+z2DAIQhkN3/PYMDH3ViIf89gwLrFxtl/z2DAl35zK4DPYMCmI0x9gM9gwHHyhc+Az2DA/z0cIoHPYMAZZAB1gc9gwAtyLciBz2DAmbKSG4LPYMCGrzdvgs9gwE88E8OCz2DAEmLtFoPPYMBFca9qg89gwIaGTL6Dz2DAd+GuEYTPYMCAzMtkhM9gwH3ulbeEz2DAn5IHCoXPYMDObh1chc9gwNTE5K2Fz2DAUiVIgYjPYMAnE7bOiM9gwJEcWhuJz2DAehxlZ4nPYMAUi9+zic9gwCVVw/+Jz2DA5zNs5ofPYMDyH8+Vis9gwBN74eCKz2DAMDAy3ojPYMB8alwyic9gwNW8W4eJz2DA9q71C4zPYMB0OHBXjM9gwE52IqOMz2DAySTN7ozPYMAi0HE6jc9gwOkpRIaNz2DATN+zao7PYMDoW421js9gwCVM8P+Oz2DA3UjHSY/PYMDU796Sj89gwJ98j26Qz2DAmtzG/o7PYMBwazdRj89gwLkJDqOPz2DAdlvj84/PYMA7lBlDkM9gwLEkVzmSz2DAi735hJLPYMAqvf8rkc9gwLkzTnmRz2DAfMGYxpHPYMCkMzUUks9gwJlC3WKSz2DAc8pPMJTPYMBxvFF0lM9gwD+t+E2Tz2DAY7BInpPPYMDU8SLvk89gwDzYPkCUz2DArfmbkZTPYMCHf/TilM9gwF8h8DOVz2DAQqVghJXPYMApsyHUlc9gwJdHDyOWz2DAvHQNcZbPYMAo4Ny9ls9gwEaYngmXz2DATRTjVJfPYMCJE86fl89gwIA4oeqXz2DAqtCJNZjPYMAn5LqAmM9gwDDCa8yYz2DAWr++GJnPYMABDMVlmc9gwJwNj7OZz2DAQ/MnAprPYMC09IJRms9gwHjxg6Gaz2DAbKpR8prPYMAbNtdDm89gwPQphJWbz2DAkiQW55vPYMD1Glk4nM9gwOYkG4mcz2DAhYxA2ZzPYMDE+mYonc9gwGd6VHadz2DAIwymw53PYMB4334Qns9gwIELEl2ez2DAQ5qDqZ7PYMDj5ur1ns9gwGa1o0Kfz2DAPlrUj5/PYMCCYTTdn89gwP60oCqgz2DAUSsKeKDPYMCu517FoM9gwJT5mhKhz2DARNSiX6HPYMDlf2ysoc9gwMl2D/mhz2DAuOyVRaLPYMC1jhSSos9gwKKroN6iz2DAaW5YK6PPYMCcax94o89gwPGX2MSjz2DAqPnyEaTPYMDAJahfpM9gwNWIDK6kz2DArOAy/aTPYMDuVutMpc9gwE+lcJ2lz2DA6NEl76XPYMCM9TdBps9gwDGCspKmz2DALgM846bPYMCzh0Eyp89gwFrVvX+nz2DAKpk/y6fPYMDQtP4TqM9gwDkBkVqoz2DADV4WoKjPYMDco/vkqM9gwEbSvimpz2DAbnTTbqnPYMBKUau0qc9gwC8AFfypz2DAoH3qRKrPYMDULfeOqs9gwDL2Gdqqz2DA565EJqvPYMA8xFtzq89gwJbwNcGrz2DAMd6dD6zPYMB3yGherM9gwGcNdK2sz2DAL9SV/KzPYMCEYZxLrc9gwNr8W5qtz2DA99K16K3PYMBr4YM2rs9gwIxTrYOuz2DAzFos0K7PYMAYK0Icr89gwLBwlGevz2DAgilrsq/PYMAGZq/8r89gwMKUl0awz2DAe6VBkLDPYMAKDETZsM9gwGh6FCKxz2DALLxOarHPYMDqJUCysc9gwDv6Cfqxz2DA6qptQbLPYMAbyGyIss9gwN+78s+yz2DAwIOoF7PPYMCYWJJgs89gwGFAR6qzz2DAH7TX9LPPYMA9C9VAtM9gwFpUN460z2DA5VxU3LTPYMDtJaUqtc9gwHn/vni1z2DAXtJbxrXPYMBLoCsTts9gwEFdwF62z2DAmxaqqLbPYMAqKEzxts9gwJQX6zi3z2DAShWqf7fPYMCpTKnFt89gwKN1Gwu4z2DAqfhCULjPYMBz2mGVuM9gwLkvh9q4z2DA0grEH7nPYMA9fzdluc9gwEp1+6q5z2DAJDMe8bnPYMDLC7c3us9gwJZXyn66z2DARHRlxrrPYMCoW4cOu89gwEasLle7z2DAtZVPoLvPYMBhCuDpu89gwADGxzO8z2DAl2H2fbzPYMBWpFHIvM9gwFpDyRK9z2DAeB5HXb3PYMATU62nvc9gwGG+2/G9z2DAG7nMO77PYMDPxpmFvs9gwK7ZDc++z2DAah7dF7/PYMAic/Nfv89gwIJrP6e/z2DAUHvU7b/PYMDULr0zwM9gwDOEfHjAz2DAnJ17vMDPYMDM1aQAwc9gwJluYUXBz2DA9wrkisHPYMDMKH/Rwc9gwPbxRhnCz2DAOA/1YsLPYMDHrIuuws9gwELAxfrCz2DAJdA+R8PPYMD3lJqTw89gwADlet/Dz2DAnYu0KsTPYMBi4F10xM9gwOf0ULzEz2DADTd3A8XPYMCfvxFKxc9gwPcdUZDFz2DAnhtm1sXPYMDB9WUcxs9gwGuP9WLGz2DAudJPqsbPYMCJHK7xxs9gwMJl3zjHz2DAN4PHf8fPYMAZAEDGx89gwBJ+UQzIz2DA3QCgUcjPYMCs3uOVyM9gwJ1L7tnIz2DAxr4EHsnPYMB0iFxiyc9gwFTQKKfJz2DA5Lh+7MnPYMCKicIyys9gwKzZI3rKz2DAs9A+wsrPYMBBQNYKy89gwK0zvlPLz2DAne3TnMvPYMDfe/Ply89gwGh93C7Mz2DAE0pQd8zPYMDsWm6/zM9gwLH1QAfNz2DAWBu8Ts3PYMCb1OiVzc9gwBJtv9zNz2DAc01XI87PYMDGbcppzs9gwDY6AbDOz2DA81fu9c7PYMALpJY7z89gwKCh/IDPz2DArHY5xs/PYMAuMEEL0M9gwFRy+E/Qz2DAuditlNDPYMBn6KnZ0M9gwCXKCh/Rz2DAU1H1ZNHPYMBLNFyr0c9gwNpAc/LRz2DAamlvOtLPYMADtwyD0s9gwPbz38vSz2DAcUu7FNPPYMCjL3Fd089gwDyZ5KXTz2DASLHg7dPPYMAMphI11M9gwGr3lHvUz2DAOKywwdTPYMBVeHYH1c9gwNfAB03Vz2DApOR1ktXPYMCDn9zX1c9gwLaAcR3Wz2DA31s7Y9bPYMD+KA6p1s9gwDTy4+7Wz2DA0xS6NNfPYMBmPIl6189gwPKWTsDXz2DA8AAGBtjPYMDzhq5L2M9gwP+HTpHYz2DAkkfo1tjPYMB80YMc2c9gwDagK2LZz2DAnvHxp9nPYMAKSKrt2c9gwBrSUzPaz2DAAkNXedrPYMAYVNe/2s9gwJAP1gbbz2DA6EBbTtvPYMA271OW289gwGDfCt/bz2DAumOTKNzPYMCWUAxy3M9gwKbIGrvcz2DAtFd+A93PYMCDJwlL3c9gwJ56jZHdz2DAoCWv1t3PYMCmmzYa3s9gwDQ40lzez2DAUg/ent7PYMBk6qrg3s9gwGoXiSLfz2DAGgnAZN/PYMArcqan389gwAzTduvfz2DAoXFUMODPYMAjnTl24M9gwCINLr3gz2DAvrguBeHPYMDRRyVO4c9gwHBzEJjhz2DAPNDt4uHPYMC7y0Uu4s9gwHH1rXniz2DA8WvoxOLPYMDvrrUP489gwLBQ7lnjz2DA61gzo+PPYMC+bjHr489gwEUOJjLkz2DA22FKeOTPYMDwfsy95M9gwKG0xgLlz2DAyLRQR+XPYMByz7yL5c9gwDuLYtDlz2DAHwImFebPYMCwRM5Z5s9gwKgYXp7mz2DAAT3m4ubPYMBscoon589gwFM3LGznz2DAfMVrsOfPYMCGLMP0589gwItj/Dnoz2DAG/NYgOjPYMCj3g7I6M9gwIfgEBHpz2DA4yyEW+nPYMDuWUWo6c9gwNpUk/bpz2DAAOgPRerPYMAqEC2T6s9gwG9GZuDqz2DAXrloLOvPYMB/C8h2689gwP0vc77rz2DA/t7CA+zPYMAHALJH7M9gwE9N4Irsz2DAgXKkzezPYMDoKm0Q7c9gwBgVjlPtz2DAdXjXl+3PYMDmLZLd7c9gwIkjIiTuz2DAsphka+7PYMADt0ez7s9gwHhoqfvuz2DAT5F0RO/PYMDk1k6N789gwPFDENbvz2DAMLgLH/DPYMAjS1Vo8M9gwLGA4bHwz2DADRqy+/DPYMBofMVF8c9gwOCYIJDxz2DAmHbP2vHPYMD2IaEl8s9gwICBiHDyz2DAabxTu/LPYMCkg+AF889gwNlobVDzz2DAJpifmvPPYMDWjpjk889gwL+JOC70z2DACcO5dvXPYMBAiFPA9M9gwPij1Aj1z2DAFlcnUfXPYMAoDzSZ9c9gwGGW7OD1z2DAV/0IKfbPYMDzsiNx9s9gwFJ6Sw34z2DA6I99A/fPYMABdP1N989gwKx5ZZn3z2DAtGlV5vfPYMANT8Mz+M9gwDAtXoH4z2DA6+fdzvjPYMA1iP4b+c9gwKDdmWj5z2DAia5RtPnPYMBprXj++c9gwMxliUf6z2DA1qVUkPrPYMAZGADZ+s9gwE8/tCH7z2DAFsafavvPYMD1Rc+z+89gwPCEyaP9z2DAuuEs8v3PYMAqtw9A/s9gwJG6Zo3+z2DA7RYq2v7PYMAo8KAm/89gwGrS4XH/z2DAt8GWvP/PYMA+HJAHANBgwENWjn7+z2DA7FwSwP7PYMC3zgwE/89gwKC6iEn/z2DAf4HGkP/PYMDJn2Lb/89gwIQV7ygA0GDADY/odwDQYMCRxY/HANBgwA0UjBcB0GDAtXtHZwHQYMDCEmm2AdBgwBMF+gMC0GDA6lV2TwLQYMBJSP6ZAtBgwDCCy+MC0GDAU1P8LAPQYMDjscB1A9BgwK/bV74D0GDA9sswBwTQYMA2wYlQBNBgwH+CLZoE0GDADbgl5ATQYMCSXX4uBdBgwK4gRnkF0GDADFB5xAXQYMCVrBgQBtBgwJt0JlwG0GDAbwyTqAbQYMDeMlL1BtBgwOaTaEIH0GDA+zi/jwfQYMDJ+lLdB9BgwEyKAysI0GDAegy8eAjQYMBGK57GCNBgwCRfvBQJ0GDAx+kOYwnQYMC3DZSxCdBgwPlZOQAK0GDAIE0cTwrQYMD4DmqeCtBgwL9KoO0K0GDA8QN7PAvQYMA1RcuKC9BgwFhjgdgL0GDAHkCeJQzQYMCkMs9xDNBgwOAn3bwM0GDA3XlPBw3QYMBEvaVRDdBgwE8vHZwN0GDAytDi5g3QYMCftSkyDtBgwMMJO34O0GDA4kO3yw7QYMCmT/wZD9BgwDVhrGgP0GDA2uZ7tw/QYMDRkE8GENBgwO2iEVUQ0GDAQF5soxDQYMAUtujwENBgwOHLzz0R0GDAg3jhihHQYMB791HYEdBgwGLRQiYS0GDAvpvGdBLQYMAjkwPEEtBgwNdzrxQT0GDAv9U9ZhPQYMBGAOG3E9BgwDsCSwkU0GDAWUb4TRfQYMDZCIeqFNBgwKaxpvkU0GDAqyd1RxXQYMAPX9OTFdBgwO7DYN8V0GDA+2VtKhbQYMCe2xd1FtBgwMJYwb8W0GDAOQWoChfQYMCIpPZVF9BgwAbxvqEX0GDAaa6YGhvQYMDTmOJqG9BgwOKHmIwY0GDAbr963RjQYMAaF7BdHNBgwNZOra8c0GDAq0g9VB3QYMDYSjqmHdBgwLks7vcd0GDA8ot3SR7QYMCVxKOAG9BgwEBZmNMb0GDA9MvXix/QYMADE5bcH9BgwJfLkC0g0GDA/9YwaR3QYMDV7z/RINBgwHC5MyQh0GDAHCzhICLQYMAmWKd1ItBgwGClycoi0GDA6uBOICPQYMD2voBvJNBgwCcILsEk0GDAljdLDSXQYMCZqsJZJdBgwNoGVKYl0GDAaelpXiPQYMBKABywI9BgwJ6yAwIk0GDAQzMPVCTQYMAHihCmJNBgwMBoifck0GDAsYJISCXQYMDOvw2YJdBgwOuw1uYl0GDAwBOLNCbQYMBgIV+BJtBgwAvKvs0m0GDAQm6CFyfQYMCNELxaKtBgwEOKnagq0GDAol7d9ifQYMC0cZw+KNBgwJvafYoo0GDApj671yjQYMARGfMmKdBgwAnb0ncp0GDA99yOySnQYMA+JtIbKtBgwOGjUm4q0GDA+5nYwCrQYMDHIikTK9BgwMNGtmQr0GDAZdhqtSvQYMBqqOkFLNBgwD5eSlYs0GDAhxiYpizQYMCih9n2LNBgwKf3Bkct0GDAiEayly3QYMAYXgLpLdBgwFlBUTou0GDAZJZkiy7QYMDsCy7cLtBgwA88mSwv0GDAZPGYfC/QYMBXMePLL9BgwKi6bhow0GDAjyzlaDDQYMA7kHG3MNBgwDjzQgYx0GDAECaAVTHQYMAw3UClMdBgwHbNz/Ux0GDAXaNTRzLQYMDsZEKZMtBgwDSsausy0GDAvc2lPTPQYMAbGb2PM9BgwB923eEz0GDABB+zMzTQYMABox6FNNBgwMVemNY00GDAkYIrKDXQYMBcAt15NdBgwG8Kxss10GDAgQTYHTbQYMB2FkZwNtBgwCaHJcM20GDAn9cSFjfQYMDJn8loN9BgwEq1ILs30GDA4QoCDTjQYMBaTlBeONBgwJDB46440GDA/4uX/jjQYMBXzLJNOdBgwCk6RJw50GDAtuyu6jnQYMCLvQE5OtBgwGJ2WIc60GDAb4/j1TrQYMCgncckO9BgwLpaCHQ70GDAHBqpwzvQYMAzHqsTPNBgwKMUDmQ80GDATp7EtDzQYMBsJ8oFPdBgwAwEI1c90GDAjCaqqD3QYMC1RDX6PdBgwNhloUs+0GDAD4vbnD7QYMAqZtPtPtBgwBNEbj4/0GDAR6+Fjj/QYMDi5C/eP9BgwL15eC1A0GDAeweJfEDQYMDTkVfLQNBgwKQ5/RlB0GDAf6+RaEHQYMBeWUe3QdBgwDQmGgZC0GDA1YD9VELQYMAWzuejQtBgwDpI+vJC0GDARicyQkPQYMDry4mRQ9BgwBZo3uBD0GDAIUbuFEbQYMCnQAFiRtBgwDj4sq1G0GDAjNyN+UbQYMDUwvpER9BgwM1jxI9H0GDAAz0xuUjQYMB4jA96R9BgwFdG081H0GDAbLIEmUnQYMBXlD96StBgwOm1ScVK0GDAKggND0vQYMDlTED0SdBgwM4QtT9K0GDARnWaikrQYMAaZMnVStBgwLj7oyFL0GDAH98mbkvQYMBIUQ+7S9BgwPUvQwhM0GDAKXWbVUzQYMCNVG+iTNBgwDtMaO5M0GDAO6CDOk3QYMCuvyKHTdBgwMx4jdRN0GDAWFrlIk7QYMCJcy5yTtBgwBGFD8NO0GDAvOyVFU/QYMAv1vRoT9BgwBsTnbxP0GDAd0HHD1DQYMBteINiUNBgwPnafbRQ0GDAumEMBVHQYMAnNdRTUdBgwNeLRKFR0GDA6SDQ7VHQYMDEtpM5UtBgwLk/1YRS0GDAa7jQz1LQYMDTuMsaU9BgwEd75WVT0GDADQlZsVPQYMCYNF/9U9BgwGBUGUpU0GDAwgeUl1TQYMAPKO3lVNBgwNQEUTVV0GDAMw3thVXQYMAvA13XVdBgwJ33vShW0GDACnOleVbQYMB4O8vJVtBgwB32CxlX0GDAB2EQZ1fQYMANhBuzV9BgwCoZl/1X0GDAesOdR1jQYMDTAI2RWNBgwCfoydtY0GDA9J2JJlnQYMBuUipyWdBgwCDwgb9Z0GDAuCtQDlrQYMAmW5ldWtBgwBQNG61a0GDAJySR/FrQYMBlBb1LW9BgwFvsXZpb0GDAJ3j+51vQYMBUr180XNBgwMF2QoBc0GDArvbKy1zQYMBFGyAXXdBgwG60cGJd0GDA3fLmrV3QYMDGmLz5XdBgwFUhGkZe0GDALJjikl7QYMB8CRrgXtBgwHSGwS1f0GDAohTDe1/QYMDe9QLKX9BgwHEjphhg0GDANUupZ2DQYMAeR3C2YNBgwHJEyARh0GDAwr2DUmHQYMDFVYGfYdBgwN1+xuth0GDAUJHTNmLQYMBZ83yAYtBgwPNDocli0GDA09SjEmPQYMCDGshbY9BgwMekRKVj0GDAyTE272PQYMDLCC46ZNBgwFaVkoZk0GDA4weM02TQYMC3MKogZdBgwK9vtW1l0GDAoOF0umXQYMDdWNcGZtBgwFT5UlJm0GDA+1SlnGbQYMAyQ1fmZtBgwC1B1i9n0GDAGgVVeWfQYMAoXwjDZ9BgwLhECQ1o0GDA6QqpV2jQYMAqmDWjaNBgwDqfYe9o0GDAl3oxPGnQYMCDdkKJadBgwHObjdZp0GDAO2TeI2rQYMASIhlxatBgwLu9Or5q0GDAsYOK22nQYMAE+qSha9BgwHTIyutr0GDAMdwdNWzQYMArZZB9bNBgwI2UYZht0GDApP5W323QYMCe6egmbtBgwDipT29u0GDAnR4YuW7QYMCxU/QDb9BgwEHNbU9v0GDA5gs/m2/QYMAWmjnnb9BgwECKLDNw0GDAEbLefnDQYMC3E/XJcNBgwCXKTBRx0GDAqy4uXnHQYMBOV4incdBgwD7AcvBx0GDA+jb2OHLQYMCaihaBctBgwLqH/chy0GDAbJPHEHPQYMA1NktYc9BgwE46nJ9z0GDAGvW/5nPQYMCYPcMtdNBgwB39ynR00GDAGuClu3TQYMAUTVgCddBgwEjEX0l10GDAws/skHXQYMBnvw3ZddBgwPIY1yF20GDAlvdAa3bQYMCX6aK1dtBgwMryGwF30GDAEQnGTHfQYMAbjDOYd9BgwE3rI+N30GDA4DJkLXjQYMDxdsx2eNBgwHuK5b540GDAKwQDBXnQYMC9lGRKedBgwGXreY950GDA9uuU1HnQYMBzUfEZetBgwCbTlF960GDAvD5kpnrQYMBbJvbuetBgwGLwBDh70GDAz+vbgHvQYMBL6CXJe9BgwA6JpRB80GDAk/ldV3zQYMCYimycfNBgwHYANd980GDAe/fQIH3QYMALTKVifdBgwNxVRaV90GDAc2ki6X3QYMAjoEsuftBgwFDpwHV+0GDAtiWhwH7QYMAfM2MNf9BgwEn8gFp/0GDAqA1Kp3/QYMCivS/zf9BgwIFl2z2A0GDAy2VbhoDQYMC6MAXTfdBgwMMFLg6B0GDAlImsT4HQYMA1ZbGQgdBgwIDAS9GB0GDAuPR/EYLQYMCTUyBSgtBgwO5aUpWC0GDAXVVT2oLQYMBzSlYgg9BgwOMd5GaD0GDA4HGzrYPQYMBu6oz0g9BgwPM5LTuE0GDAh/EUgYTQYMA4TB3GhNBgwDoTwQqF0GDAaXkOT4XQYMDYgSKThdBgwIHBGteF0GDA5YYMG4bQYMAIdBxfhtBgwApGcaOG0GDAXwsK6IbQYMA4zPQsh9BgwKliOXKH0GDAjNTWt4fQYMCvtrz9h9BgwOB9CkSI0GDAMZGuiojQYMAHTm/RiNBgwN/yJxiJ0GDAnsfDXonQYMBysSulidBgwJRNUeuJ0GDAnef7MIrQYMA3pAh2itBgwIK90LqK0GDAhSd3/4rQYMCF3Q5Ei9BgwPXnooiL0GDAPcoszYvQYMCzJAISjNBgwIzHP1eM0GDAHplmnIzQYMCXrDThjNBgwBxFlSWN0GDAL6ZjaY3QYMC/p62sjdBgwDhjGu+N0GDAKshlMI7QYMBIKDZxjtBgwI/fzDiN0GDAx7+jx5DQYMCKqXALkdBgwNZ54E6R0GDAZZiYkZHQYMAm1yLTkdBgwF2p/ROS0GDAYLOpVJLQYMDAI1qVktBgwCVYR9aS0GDAwSujF5PQYMAEHZ9Zk9BgwAyVjpyT0GDAZJhB4JPQYMCiq34klNBgwJ25I2mU0GDA3F0FrpTQYMDBEw3zlNBgwE/MEjiV0GDAiJfUfJXQYMBswkzBldBgwG8ntgWW0GDACW8OSpbQYMD4mVqOltBgwAHBnNKW0GDARSTfFpfQYMDovTJbl9BgwMbHkp+X0GDAA2Lo45fQYMAZ/yoomNBgwDEvTWyY0GDA2xJBsJjQYMDxYPfzmNBgwIamgzeZ0GDAJ4beepnQYMDTWNK9mdBgwN+QUgCa0GDAWedeQprQYMBPwvCDmtBgwBDEKMWa0GDAsvPDBZvQYMBBB9dFm9BgwLHO74Wb0GDAs0pNxpvQYMBEShgHnNBgwK1UfEic0GDANeN9ipzQYMBVFn/NnNBgwDZEmhGd0GDAKYA2Vp3QYMCgnRKbndBgwGhC/t+d0GDA0PnIJJ7QYMAn91JpntBgwN4bSK2e0GDAKk9p8J7QYMBECgMzn9BgwApTNXWf0GDAV+oJt5/QYMAN0ZP4n9BgwJxI2jmg0GDAd1QSe6DQYMDZZ028oNBgwGiki/2g0GDAXQDCPqHQYMBM2imAodBgwEuercGh0GDAwg1lA6LQYMCiAUFFotBgwBcRQYei0GDA951/yaLQYMBlryUMo9BgwJ9ZBE+j0GDAiyFEkqPQYMAHANTVo9BgwCYjxRmk0GDAvgQpXqTQYMBWD7eipNBgwF+pKOek0GDApipNK6XQYMA5XRNvpdBgwPsPV7Kl0GDAPIH89KXQYMD829A2ptBgwCt6A3im0GDA4VLruKbQYMDESLL5ptBgwFsIfDqn0GDA6Ltre6fQYMDOdbK8p9BgwB7Gc/6n0GDAnL3DQKjQYMDtzpiDqNBgwIYW5cao0GDAnIKyCqnQYMAZSt5OqdBgwLp0ZpOp0GDAP4dD2KnQYMDAVUQdqtBgwFHcFmKq0GDADAujpqrQYMDB1ffqqtBgwFSHzy6r0GDAqcQpcqvQYMBfW/i0q9BgwHRvSPer0GDAJ/1COazQYMCS51ycqtBgwOXtteeq0GDAI9wEM6vQYMCuMGJ9q9BgwPywsMar0GDAMO4Zwq3QYMDUySIDrtBgwDKSDESu0GDA9dsfha7QYMAGi2PGrtBgwIE25Aev0GDARhC1Sa/QYMAsQ72Lr9BgwKMTIs6v0GDA2KnvELDQYMC0HQBUsNBgwJ2DIpew0GDA76332LDQYMBGwDYdsdBgwO+tNGGx0GDAsr5kpbHQYMACtczpsdBgwJa5+S2y0GDArrVScbLQYMAhBIa0stBgwO4Vefey0GDAyTigOrPQYMBvmFJ+s9BgwLGzGsKz0GDArI+uBbTQYMCxOBpJtNBgwIW0koy00GDA84vMz7TQYMDDKVMStdBgwGoRoVS10GDAUwpNl7XQYMCjY43atdBgwHAYhB620GDAfLoMY7bQYMDZIIiottBgwDQ+jO+20GDASC8kN7fQYMDk8HF+t9BgwLyBNMW30GDAGfT8CrjQYMDo1udPuNBgwHEBU5O40GDAB4pj1LjQYMCygygUudBgwNte+FO50GDAf5ZqlLnQYMDliN/VudBgwKZwqhi60GDAp1ZbXbrQYMD4tielutBgwLWXG++60GDAQycAOrvQYMDcTTaFu9BgwIQhRNC70GDAX+KtGrzQYMD9SRhkvNBgwFb3bKu80GDAC5rM8LzQYMDBVxE1vdBgwLnOfni90GDAPLliu73QYMBLHgT+vdBgwEePtUC+0GDAq5DPg77QYMDkx6THvtBgwDt7Owy/0GDAWyuhUb/QYMA4Me2Xv9BgwFJkHN+/0GDAQhcQJ8DQYMCkXgZwwNBgwAbt6bnA0GDAg5XsA8HQYMDUar9NwdBgwJYPHJfB0GDAuDvQ38HQYMBRb9snwtBgwE2teW7C0GDA4WKSs8LQYMD/FyX4wtBgwDk1pDzD0GDA0MVcgcPQYMCk+oHGw9BgwMoQKwzE0GDAos01U8TQYMAQxAOcxNBgwD3dXOXE0GDAYqS7LsXQYMCbTN53xdBgwNgUf8DF0GDAwPmjCMbQYMBcY3RPxtBgwEekZpTG0GDA1ri82MbQYMDe2S8dx9BgwFGnIGLH0GDA2DbYp8fQYMBBHIDux9BgwKph3jbI0GDAkliGgcjQYMAj6GTNyNBgwBuazBnJ0GDAMQxdZsnQYMD8SbOyydBgwAoCq/7J0GDAyZh9ScrQYMCoFp+SytBgwB5CsNrK0GDAOl5jIsvQYMBOJPRpy9BgwIWnn7HL0GDAiJyA+cvQYMDkPwtCzNBgwD7D2YvM0GDAvdaB1szQYMCIljghzdBgwO0RwmvN0GDAjo3rtc3QYMCFhpn/zdBgwCk8fEjO0GDAHHkNkM7QYMC4AanWztBgwOQgLB3P0GDAm1DSY8/QYMB+Auiqz9BgwHZln/LP0GDAPjIuO9DQYMCXwlmF0NBgwL5N1NDQ0GDAjFH7HNHQYMCBbaVp0dBgwLYumbbR0GDAOy+2A9LQYMBteNdQ0tBgwD72i53S0GDAr8Co6dLQYMBQeHc109BgwAKeCoHT0GDAuPpXzNPQYMDFl2wX1NBgwDGJWGLU0GDAO8ItrdTQYMBOhPH31NBgwKSQ1ELV0GDAOE3ljdXQYMCHX/DY1dBgwLQLKiTW0GDAf/Ovb9bQYMD0zLC71tBgwJCVOAjX0GDA6aK9VNfQYMBAchOh19BgwBleNO3X0GDAjdEMOdjQYMDnNp6E2NBgwPhOps/Y0GDAq9QUGtnQYMBolHBk2dBgwK7bB6/Z0GDA/b/4+dnQYMCNO2JF2tBgwLE7eJHa0GDAYkkL3trQYMCpQaMr29BgwBHVw3nb0GDAsnRByNvQYMAGz9cW3NBgwDCWeGXc0GDAY/kCtNzQYMCDOZMC3dBgwKuD61Dd0GDADO7+nt3QYMDBWiRT4NBgwD+uSjre0GDA7majh97QYMApdcPU3tBgwNgqTiHf0GDA78H2bN/QYMCPZpu439BgwEABnYvi0GDAleJ43OLQYMDwOvqd4NBgwOqKwOvg0GDASRSiOOHQYMDicuCG4dBgwHdHK9bh0GDA9/HpJeLQYMCMpn914tBgwBve4MTi0GDAhb7xE+PQYMBUYMEI5tBgwELsVK/j0GDAp6R3++PQYMB+7RtH5NBgwKLz1pLk0GDAohfy3uTQYMCeEIgr5dBgwHyA0njl0GDAhJQkx+XQYMD85CEW5tBgwOzpk2Xm0GDAgs0ZtebQYMB2towE59BgwCOo2lPn0GDAXKT2oufQYMBK3jzx59BgwFKixz7o0GDANbYPjOjQYMAWvm/Z6NBgwC5pzSbp0GDA8s+IdOnQYMCVievC6dBgwAufKBLq0GDARMeTYurQYMBwmXqz6tBgwAIKAAXr0GDA3sDBVuvQYMAiQXCo69BgwA1MFvrr0GDAay0+S+zQYMDll9Kb7NBgwHa48Ovs0GDAqHR8O+3QYMAt/m2K7dBgwJRVGdnt0GDAkaefJ+7QYMCUjFNR8dBgwBfJ5qzv0GDA4Goi+e/QYMA743RG8NBgwL72febw0GDAclAKNPHQYMDHFp5n9NBgwDNot7T00GDAQFKYHPLQYMAkkZZr8tBgwEkHsLvy0GDAqKT97PXQYMB1fTxf89BgwPGwULHz0GDAky8lA/TQYMBAzrxU9NBgwMO9naX00GDAwop69fTQYMAjDZpF9dBgwKGHD5T10GDAeu0bwPjQYMCZsX0w9tBgwGT+Hn/20GDAtq95zvbQYMDT+OYe99BgwO/FsXD30GDA7gVAw/fQYMD0evcV+NBgwATdxWj40GDACTlRu/jQYMC+SPEM+dBgwH3Cul350GDAXanlefzQYMDDUxT5+dBgwMcJ6EX60GDANMIak/rQYMB2W3mi/dBgwCMpsUb+0GDAmvwnnf7QYMB/t/7v/tBgwFrtqkL/0GDAQyuEyvzQYMBGgPka/dBgwG8UP2v90GDAr6lYuv3QYMAVPrYI/tBgwKufkFf+0GDAXVtcdQHRYMBQWn/CAdFgwBjLaUf/0GDA97+pl//QYMDx97/n/9BgwO+oUTgA0WDAyYeNRQPRYMBVprzbANFgwFHQly0B0WDAU44gfwHRYMDvkMzPAdFgwBg0NskE0WDAoaKwcQLRYMCfmIPCAtFgwOWbBbsF0WDAL/lDCwbRYMD4T+yzA9FgwJK4GAQE0WDALCXC9gbRYMC4QHNEB9FgwP3L5pEH0WDAU2D13gfRYMCCiuQrCNFgwCDeL+UF0WDAEyuiNQbRYMCBRkiGBtFgwDhmR10J0WDAzkGTqQnRYMAv09d3B9FgwGQ2ksgH0WDA8W+1GAjRYMDpaUxoCNFgwNDVhrcI0WDAj8vJBQnRYMDLujFTCdFgwGmCnAwM0WDA4yaJWAzRYMBQboc6CtFgwOQab4gK0WDA5qHn1grRYMBM7DomC9FgwIf1zXYL0WDAUU3xIQ7RYMD8qm1vDtFgwGswM2wM0WDA4BUzvgzRYMAHIxQQDdFgwLzxtWEN0WDAkuvCsg3RYMBca5qbENFgwCrl6KIO0WDADFVx8g7RYMCWrLNBD9FgwO3U7JAP0WDAUUc34A/RYMBeq4etEtFgwNLTAtAQ0WDAddMkIBHRYMB3pGdwEdFgwHc+78AR0WDAPSakERLRYMB9VaNtFNFgwCwLLroU0WDA4aduBRPRYMBomy9XE9FgwG5DHakT0WDA5Egy+xPRYMBDt3JNFNFgwK4E2Z8U0WDAaJWX8RjRYMC93geBF9FgwJTlUdEX0WDAUKnhIRjRYMBG1z1yGNFgwFBAcsIY0WDALdZkEhnRYMADvelhGdFgwEouGVYb0WDAfgcdohvRYMCmnxbuG9FgwCkIvjkc0WDAgBNrhRzRYMD8mGrRHNFgwHJJnx0d0WDAdSn82hvRYMA9Zy4qHNFgwCER2Xkc0WDAILDZyRzRYMA9GZwZHdFgwKE4HT0f0WDA0sRzih/RYMAetjJZHtFgwGdFJqoe0WDAuJCxbSDRYMDy5ONNH9FgwA5kQf8g0WDAiBOrRyHRYMAiio2QIdFgwFQujdoh0WDAsY9YJSLRYMBw8IdwItFgwBHO0bwi0WDA7jwnCSPRYMBp4plUI9FgwMdi154j0WDAMvZZ0SLRYMCHpLAyJNFgwEPHnn0k0WDANqSrySTRYMCkRHMWJdFgwMgVpwIm0WDAfM9KUibRYMBztByfJtFgwEAlq+om0WDAJ1kLNSfRYMBFnQd/J9FgwJB5icgn0WDAujKSESjRYMCtMnFZKNFgwO60eTIp0WDAnBZNeinRYMDjPEbCKdFgwBW1Ewoq0WDAotW6USrRYMAUNo2ZKtFgwDZIV94q0WDA2OsDICvRYMBQOc1oK9FgwJwrUrEr0WDAJQpA+ivRYMDcmzFCLNFgwBNeoYks0WDAufzWRyzRYMBpDcAWLdFgwFGGCtos0WDAmBW8Jy3RYMApA1F1LdFgwGqFpMIt0WDAzJCEDy7RYMB2/k9cLtFgwBfpiaku0WDAoV+F9i7RYMAngLxCL9FgwCHyX+cv0WDAeqITLzDRYMBysrAcMNFgwNmdY2Yw0WDAYuqisjDRYMDYH5b/MNFgwLCuVE0x0WDApFK+mzHRYMAXRJ3qMdFgwCX6tTky0WDAFj7viDLRYMBnlCvYMtFgwBsiSycz0WDALncRdjPRYMBBxx7EM9FgwOLkQhE00WDARwmDXTTRYMAcLv2oNNFgwIkILvM00WDAIZQePDXRYMAVMX6ENdFgwFW2sMw10WDAo+D8FDbRYMAuO51dNtFgwJtgoqY20WDAIsiH8DbRYMCW34c7N9FgwBq4UYc30WDAG6fb0zfRYMAiDf0gONFgwC7xlG440WDAMVp+vDjRYMCOoKEKOdFgwG6B7Fg50WDA/AcWpznRYMCokv30OdFgwJGPlEI60WDAuTyzjzrRYMBMdkjcOtFgwB6nLSg70WDA+wg9czvRYMDTCLa9O9FgwPsG0gc80WDArTOzUTzRYMDvFWubPNFgwGiPHOU80WDAFSX6Lj3RYMBn6Fx5PdFgwMLS9MM90WDArbdeDj7RYMChWIpYPtFgwGBGY6I+0WDAevbg6z7RYMBNJu00P9FgwGrBIH0/0WDA0NvpxD/RYMB9tTUNQNFgwJgVQlZA0WDAW78poEDRYMCUV+TqQNFgwLi0qjZB0WDAd9Y4hEHRYMAloSTTQdFgwKZ9VyJC0WDAJcJwcULRYMAczBHAQtFgwKl60w1D0WDA1tsXWkPRYMDCt26kQ9FgwAqxq+xD0WDApGbqM0TRYMBpl3t6RNFgwAEcs8BE0WDAv/PRBkXRYMDL2B1NRdFgwC2OJJRF0WDAyAsy3EXRYMBmmuQkRtFgwEMs1W5G0WDAlc3NuUbRYMBDN7IFR9FgwNSyYVJH0WDAHpLGn0fRYMCxKrjtR9FgwChr4ztI0WDAxkdDikjRYMCnm8/YSNFgwM23XidJ0WDAiDmUdUnRYMCoySnDSdFgwLOuAxBK0WDA13kmXErRYMAAAYCnStFgwJrZB/JK0WDA0nXpO0vRYMANqRaFS9FgwHmNi81L0WDAxjVHFUzRYMBHC4ZcTNFgwI2qaaNM0WDAo3sr6kzRYMC5e9gwTdFgwBdYkHdN0WDADUeHvk3RYMBw/b8FTtFgwCisI01O0WDAd24flU7RYMAJfLPdTtFgwFcw7yZP0WDAbY+xcE/RYMBZbt66T9FgwEqbHQVQ0WDAj7+NT1DRYMCh0n6aUNFgwLcR3+VQ0WDAqOJ+MVHRYMDx8iZ9UdFgwMQPB8lR0WDASURaFVLRYMB5OIphUtFgwJXy+qxS0WDALnpf91LRYMBNgmVAU9FgwODYHYhT0WDAgK9bzlPRYMCieLkSVNFgwPfPkFVU0WDAez3rl1TRYMCOqUDaVNFgwAhZ+xxV0WDAbCB8YFXRYMD3EkGlVdFgwIa2sOtV0WDAmsHfM1bRYMCJVgl9VtFgwLd/9sZW0WDAGMBYEVfRYMBafyJcV9FgwAzI/aZX0WDAAglf8VfRYMA5Qz87WNFgwN09GYVY0WDAXFSizljRYMDgackXWdFgwBUIn2BZ0WDAmZFzqVnRYMD0jULyWdFgwFu79zpa0WDAcyKHg1rRYMDGpRXMWtFgwDCpihRb0WDA4oqQXFvRYMDJ422kW9FgwO7UV+xb0WDAAoRGNFzRYMD+BAt8XNFgwKJTjcNc0WDAaQbpCl3RYMBONEdSXdFgwCxOiJld0WDAo95s4F3RYMBBaz0nXtFgwPCZSW5e0WDAbdeYtV7RYMDZGzr9XtFgwEK1UkVf0WDAenTLjV/RYMCMq+PWX9FgwDDLrSBg0WDAOgWOamDRYMB9pXS0YNFgwGZ+y/5g0WDAUypbSWHRYMAMA6KWYdFgwPxPNeFh0WDASLSsKGLRYMDMeaVwYtFgwEc7Krhi0WDAWued/2LRYMB2H9lGY9FgwN2F0I1j0WDAqMj71GPRYMDkWEgcZNFgwDCYlWNk0WDAXhb9qmTRYMD3kqDyZNFgwNMEdjpl0WDAdu5PgmXRYMDDFw/KZdFgwPTK/BFm0WDALAzuWWbRYMAHWcChZtFgwOpBcOlm0WDAi07jMGfRYMBl4yx4Z9FgwJ2JLL9n0WDAjLWrBWjRYMArQdRLaNFgwCz1CJJo0WDAgCta2GjRYMCT6fceadFgwHJw6WVp0WDAkb82rWnRYMA57uf0adFgwFVezTxq0WDAjXSbhGrRYMDhFjLMatFgwBdHlRNr0WDAtkfiWmvRYMBIMemha9FgwG3yVehr0WDABEwuLmzRYMB8haZzbNFgwMwi5bhs0WDAFNMH/mzRYMBNjSlDbdFgwFnobYht0WDATJXqzW3RYMCtRLUTbtFgwHWk01lu0WDA0TRCoG7RYMB+MxTnbtFgwJgKRi5v0WDAyCztdW/RYMA0jUO+b9FgwKh+Owdw0WDAD/NTUHDRYMAzdV+ZcNFgwPdjKeJw0WDA+SWYKnHRYMDBV4hycdFgwIX9eLlx0WDAUYY+/3HRYMDZFYBEctFgwJTIhYly0WDAg1uIznLRYMA135oTc9FgwH6Jolhz0WDADlv/nXPRYMDh8gbkc9FgwFQGpSp00WDAVtiUcXTRYMDnk4G4dNFgwI9RTv900WDA39UYRnXRYMCJv3OMddFgwIJ9LNJ10WDABsq+F3bRYMAaM31ddtFgwIQ5sKN20WDAhshd6nbRYMCd35Exd9FgwIB4j3l30WDAGVBtwnfRYMDj2NoLeNFgwO4jn1V40WDAj4mGn3jRYMAAEmjpeNFgwKbHJDN50WDADBqnfHnRYMC/IdjFedFgwLSSSg560WDAX56VVXrRYMDEE7WbetFgwGvC8+B60WDAfJWlJXvRYMAr9Gxpe9FgwFO1Vax70WDAIN3R7nvRYMA68s8xfNFgwMZvmnV80WDAyiWXunzRYMA8UL0AfdFgwP/3X0h90WDACQ0fkn3RYMAgiXLdfdFgwDqNTyl+0WDApVoodX7RYMC3Do3AftFgwMpMWQt/0WDArfwNVX/RYMD71Rmdf9FgwNMMZuN/0WDAkzu4KIDRYMCebzNtgNFgwNFnZbGA0WDAEemg9YDRYMDMtLY5gdFgwKuf0n2B0WDAhCvPwoHRYMA7CkEIgtFgwKStnk6C0WDARErulYLRYMDB4V/egtFgwPnqLyeD0WDA9OOhcIPRYMCD5Ri7g9FgwLl+9QWE0WDAWT/bUITRYMDTK4abhNFgwD+InuWE0WDA05r1LoXRYMDnJ3h3hdFgwDTBfb6F0WDAizZ2BIbRYMDVehJKhtFgwJcT/o+G0WDATLDK1obRYMBL73Eeh9FgwPey1GeH0WDAvvE3s4fRYMCPDj7/h9FgwL6+bEuI0WDA1wCQl4jRYMCXmV/jiNFgwFuq2S6J0WDAmosqeYnRYMCFdU7BidFgwIGdsgiK0WDADugJUIrRYMCzlXOXitFgwHb3Xd+K0WDAuK7uJ4vRYMB0nuFxi9FgwHGTr72L0WDARTdsCozRYMB9FoBXjNFgwAEqoaSM0WDA3Yh68YzRYMC/h+w9jdFgwPF6eImN0WDAnbF2043RYMBWVJgcjtFgwFGPeWWO0WDA0KJ+ro7RYMDkOvn3jtFgwCEaDUKP0WDArFf3jI/RYMCiCC3Zj9FgwKpEeSaQ0WDA6+iHdJDRYMCDsSbDkNFgwF/pMhKR0WDADORuYZHRYMCfjJawkdFgwI9ljv+R0WDALyA1TpLRYMC0ZUicktFgwEUjn+mS0WDAzO0yNpPRYMBJAfiBk9FgwI2Y+cyT0WDAZQbeFpTRYMA1nC5glNFgwARef6mU0WDAp5oU85TRYMAWlCU9ldFgwFXy5oeV0WDAgBCS05XRYMADsZYgltFgwJyT926W0WDA2n02vpbRYMAu3wAOl9FgwKs2Jl6X0WDAIeFurpfRYMDOIIn+l9FgwMYSAE6Y0WDATGftnJjRYMAnaWjrmNFgwGO5TTmZ0WDAnxqAhpnRYMBlLzXTmdFgwAjMVx+a0WDAA3loa5rRYMDi+hO3mtFgwLaBDAKb0WDANTT3TJvRYMCzHvWXm9FgwGzSFOOb0WDAT6xzLpzRYMA8okJ6nNFgwOOhk8ac0WDAjyOhE53RYMAyH6hhndFgwHHkUrCd0WDA3uOV/53RYMDugaJPntFgwI2KeKCe0WDAbmrb8Z7RYMD/KrNDn9FgwAoulZWf0WDAsQBY55/RYMCIevA4oNFgwN/MPoqg0WDAVtsU26DRYMAhOSArodFgwCK3lHqh0WDAiwF+yaHRYMDKIN0XotFgwDDh6WWi0WDANkObs6LRYMBUwQABo9FgwLPCUE6j0WDAjySJm6PRYMASa8joo9FgwDtCXjak0WDA3yAPhKTRYMCs/ebRpNFgwIvTESCl0WDAlWE1bqXRYMCYCTO8pdFgwAc8Ywqm0WDAdM5HWabRYMDErQypptFgwOVn7vmm0WDA5odJS6fRYMCpt+Ocp9FgwG29Fe+n0WDA84nQQajRYMA6FdCUqNFgwLAjyOeo0WDAVHcEO6nRYMDRUtOOqdFgwDL0xOKp0WDAoVXONqrRYMCGRkqKqtFgwBCPCd2q0WDAHS3WLqvRYMASbrJ/q9FgwE/Zo8+r0WDA+EkvHqzRYMDOJH9rrNFgwHIghbis0WDAVNwlBq3RYMC5kpZUrdFgwADNiqOt0WDAokhd863RYMBqMXlDrtFgwHe805Wu0WDAqYDh6K7RYMA2OE88r9FgwFYUkI6v0WDAni7k3rPRYMBp5Z0ytNFgwCMZ3Iyw0WDAscGq4LDRYMBFQT40sdFgwBcVfYex0WDAMFuM2rHRYMAbsGYtstFgwMnaL3K20WDAUMgS0rLRYMCQXLIjs9FgwIWiK3az0WDA3cvTzbfRYMBOUCkatNFgwATbqmu00WDAx6vxvLTRYMDJ1M8NtdFgwPQpjWG10WDAwE3Os7XRYMCAIXYjutFgwAUh4Vi20WDAAwLHqbbRYMC53kP8ttFgwGCc/U630WDAOKbnobfRYMBJmNX0t9FgwMiw4ke40WDAO1eOrrzRYMBgNCzwuNFgwDzorFa90WDArKjPrL3RYMCRwNgDvtFgwE8NOFu+0WDAkveKsr7RYMBwF38Jv9FgwDxe6F+/0WDA4Whrtb/RYMCmR+EJwNFgwAR2fUq80WDAp6kUnrzRYMCnrSLxvNFgwEy16lTB0WDABIWrpsHRYMBwYJbpvdFgwIjKQz2+0WDA/KBqkb7RYMByHszlvtFgwDYsOUbD0WDAlVSOmsPRYMD/zRbvw9FgwJwpyTfA0WDA5vr4isDRYMD6uCnbwNFgwK3MgSvB0WDALh4ifMHRYMBI3IfpxdFgwBPNMB/C0WDAA7+kcsLRYMCyU+XHwtFgwMXfATvH0WDAVWuWjsfRYMAHWNzhx9FgwFfeEivE0WDADawShsTRYMC7TnvfxNFgwILP2zjF0WDAI+lpksXRYMA6K07rxdFgwFptgELG0WDAi7nFmMbRYMDBICTuxtFgwBaIuULH0WDAexH9lcfRYMAyrJnox9FgwCOLrTrI0WDADTX4i8jRYMAZOJLcyNFgwFvkrizJ0WDAjqu/fMnRYMDOdpXMydFgwEhafhvK0WDAzbrYacrRYMD6q+y4ytFgwNuknwjL0WDA1PH9WMvRYMDHU2iqy9FgwDWx3vzL0WDAeryyUMzRYMCOkrOlzNFgwFggyvrM0WDAyD9tUM3RYMC+S3ylzdFgwELeNPrN0WDAgAxvTs7RYMAMlqChztFgwEBjlfPO0WDAPeNBRc/RYMBUvKaWz9FgwEpk4efP0WDAhVo7OdDRYMAzH8mK0NFgwDBV/NzQ0WDAPutJMNHRYMBGo2CE0dFgwOWu+tjR0WDAJeOdLdLRYMCmevaB0tFgwGh/2tXS0WDAFZH3KNPRYMC/5G9709FgwLeB4c3T0WDAc9FvINTRYMCodSVz1NFgwEfqLMbU0WDAXu2eGdXRYMAAVZpt1dFgwCRYPcLV0WDAzD9SF9bRYMCj7ats1tFgwBIxL8LW0WDAzBmoF9fRYMD95dts19FgwOe8wMHX0WDAJQ2LFtjRYMBeqhRr2NFgwInV3r7Y0WDAtIffEdnRYMA/2v9j2dFgwIzEb7XZ0WDAxtg7BtrRYMCRuFhW2tFgwNihIKba0WDAj7Lb9drRYMCyK41F29FgwDyU1JXb0WDAyLjm5tvRYMADwZk43NFgwAGtQ4vc0WDAQPAS39zRYMCBEGUz3dFgwLA+I4jd0WDAHOFE3d3RYMAqw3wy3tFgwFg3zofe0WDA+cbX3N7RYMAHSV8x39FgwFmFmITf0WDAxl+zrOLRYMBIlQ364tFgwKFIMEfj0WDAo7Nxk+PRYMB3vxzf49FgwIlnZXvh0WDAzh0+z+HRYMBOHb4i4tFgwOvKYHXi0WDAAbsIyOLRYMCOjIUa49FgwFCxsWzj0WDAc3WAvuPRYMAjEGUQ5NFgwFxWw2Lk0WDAquovteTRYMAW3Kmp59FgwNflMffn0WDACwiaQejRYMARYe8I5tFgwIvaltLo0WDAKIWMGunRYMD/ygYO59FgwEmugWPn0WDAmxoQuOfRYMAoCzEL6NFgwOcaw1zo0WDAuP/N2+rRYMDY2fj86NFgwP2tY0zp0WDAhMiim+nRYMDLqPPq6dFgwBTyvWDs0WDAGnoPi+rRYMCeLq747NFgwJJo6y3r0WDAzdX8f+vRYMDY0BnS69FgwHROayTs0WDA+x7xduzRYMCbrX3J7NFgwCNgxxvt0WDAruGkV+/RYMCy+m3B7dFgwCEFGRTu0WDAog54PfDRYMBZ5/yJ8NFgwKdWhtbw0WDAsri6IvHRYMArrmFu8dFgwD4OSbnx0WDAzHasA/LRYMBLV5lN8tFgwOZALfPw0WDAtHGdHvPRYMC91mPn8dFgwKBzpjjy0WDA64Gwh/LRYMCs4S7Y8tFgwK6VESnz0WDAwSR8ePPRYMB7dSXI89FgwJj6PxX00WDAfc5GYvTRYMCLUcKv9NFgwPTjOP300WDAz7kqS/XRYMAbzPCX9dFgwAJ23eX10WDA5S80NPbRYMB06LWC9tFgwOJKRtH20WDA6T3BH/fRYMAh9lFu99FgwOhIgbz30WDAXKoqCvjRYMCXAfNX+NFgwNGIOKb40WDAJ7gP9fjRYMC1G5NE+dFgwC45vZT50WDABdQH5vnRYMADUZw4+tFgwLlnMIv60WDAAhh53frRYMDiG4Ev+9FgwDW8ToD70WDA5Iv4z/vRYMCwpuAd/NFgwH4OAWr80WDAVXdxtfzRYMCBgI8A/dFgwFk4gUv90WDAy1TJlv3RYMCFb8Pi/dFgwHAR0C/+0WDAMxeJfv7RYMBV/jHO/tFgwGU3Zx7/0WDAmcv/bv/RYMAaDMO//9FgwAgHvRAA0mDAsKrhYQDSYMC8O/iyANJgwPh++AMB0mDAVtbUVAHSYMBdjH6lAdJgwGBNHPYB0mDAxcaQRgLSYMDmTwaXAtJgwMByk+cC0mDA9lPeNwPSYMBcJLqHA9JgwFJjyNYD0mDAyEv8JATSYMAR8GByBNJgwAbLxb4E0mDAmU4bCgXSYMDKVcxUBdJgwIIrhJ8F0mDAK7Be6gXSYMAiJG01BtJgwCzr64AG0mDAmV/0zAbSYMDZDcAZB9JgwC4KP2cH0mDAOiJqtQfSYMBobxIECNJgwP/Y+FII0mDATEDsoQjSYMCNcUvxCNJgwJy6DkEJ0mDAGWfZkAnSYMABel7gCdJgwIOwji8K0mDAm4RsfgrSYMCjG9/MCtJgwCM93xoL0mDAPm9NaAvSYMAYRwK1C9JgwN9NgAEM0mDAX8urTQzSYMDfjQKZDNJgwM7kDeQM0mDAahEBLw3SYMCD0vN5DdJgwOyw9cQN0mDARL16EA7SYMBie09cDtJgwIxQKagO0mDAGySb9A7SYMBqhstBD9JgwM/TKpAP0mDApXgy3w/SYMDKL0ouENJgwFsICn4Q0mDAgaqezRDSYMDkuqQcEdJgwFfINWsR0mDAn6YUuRHSYMBQl6gFEtJgwH1I4FAS0mDAiXenmxLSYMCJylHmEtJgwDIBHTAT0mDAeh3DeRPSYMBmvFfDE9JgwHrZhwwU0mDANSWQVRTSYMATlcWeFNJgwPKVyOcU0mDACs9dMBXSYMCpsAh5FdJgwLL4vMEV0mDAiRS0ChbSYMDNpf5TFtJgwA/tip0W0mDARBiM5xbSYMDtMboxF9JgwEA+cXwX0mDAKKg3xxfSYMBmLakRGNJgwFACxAoX0mDARn8LqBjSYMDUKcvzGNJgwOdOkz8Z0mDAJ4t4ixnSYMC9NZDXGdJgwH2NeyMa0mDAc21GbxrSYMAX0Im6GtJgwNV9cgUb0mDAHWfTTxvSYMCOx9yZG9JgwAMFAuMb0mDAmVs0KxzSYMCItItyHNJgwDqQfrkc0mDAYyCmAB3SYMAMROhHHdJgwE4r744d0mDAqm1Z1h3SYMD6U1AeHtJgwBYGV2Ye0mDAjfd0rh7SYMASff32HtJgwIxo9T8f0mDAXXYaiR/SYMB549XRH9JgwKCcKBog0mDA3uhoYiDSYMB3cmSqINJgwCJxlPIg0mDA4uboOiHSYMCYY9qCIdJgwCOFnsoh0mDA3cTFEiLSYMDhpXpbItJgwEsJa6Qi0mDAwjIq7SLSYMA8lwI2I9JgwCkK734j0mDAFXL9xyPSYMBaCv8QJNJgwJbSA1ok0mDAJqgfoyTSYMAlxljsJNJgwDmPkTUl0mDAeMrEfiXSYMC+5NLHJdJgwJkExhAm0mDAV1+qWSbSYMAVPSmiJtJgwHnKSuom0mDA/eb0MSfSYMD/FeJ4J9JgwF+fz68l0mDAIRI19yXSYMDQGIFKKNJgwAFGSI8o0mDAtnSf1CjSYMB3EmcaKdJgwPqG0mAp0mDA6LG8pynSYMCa3vfvKdJgwCPUyjkq0mDArz0zhCrSYMD/nn/OKtJgwBD2VBgr0mDAsNBHYSvSYMCdI2OpK9JgwIVUGPAr0mDAUsJcNCzSYMA3+2d3LNJgwJQ4Eros0mDA0jPK/CzSYMCGlN8/LdJgwPvaj4Mt0mDAACZxyC3SYMBm2jUPLtJgwKXUX1cu0mDAvB8UoC7SYMAeliXpLtJgwAy3FTIv0mDAGLG0ei/SYMBzxbzCL9JgwGmcAgkw0mDAByu8TjDSYMCf8lOVMNJgwHa8stsw0mDA8YqiITHSYMCrDdhnMdJgwLDYOa4x0mDAT/i69THSYMDsNBg+MtJgwOxiLIYy0mDAK84nzjLSYMDdVigWM9JgwB6rzF0z0mDAaJ8JpTPSYMCrp0/rM9JgwDaLMjA00mDAyfGydDTSYMAf3gm5NNJgwAJYrv000mDACqubQTXSYMBE+dOFNdJgwNXNNco10mDAc6/cDjbSYMBKSjhUNtJgwKLhWZk20mDADCmC3zbSYMC2QxgmN9JgwNVBbW030mDAtbQatTfSYMAa98X9N9JgwCN/qkY40mDA07RmjzjSYMBrKrvXONJgwHI1hR850mDAKNvFZjnSYMB2aumsOdJgwNQ7xPE50mDAmIBSNjrSYMB4GOh6OtJgwIllmb860mDAeuWUBDvSYMBOVSRKO9JgwKSQxZA70mDARcvP2DvSYMA9j1ghPNJgwJ55p2k80mDAFL1esTzSYMCVlGP4PNJgwCs11j490mDAGil9gz3SYMDySiPGPdJgwJfVKQg+0mDA7ok/Sj7SYMAHoB6NPtJgwJ+7VNE+0mDAJZLXFj/SYMAl9qNeP9JgwP2Xiak/0mDA/xIF9j/SYMBpibNCQNJgwNOP4o5A0mDAaovn2UDSYMAk2cEjQdJgwFd+X2tB0mDAEU2Br0HSYMCOiTLxQdJgwEu/sTFC0mDAsFblcULSYMDUo06yQtJgwLbvEfNC0mDACAexNEPSYMAw4FJ5Q9JgwD52sb9D0mDA0r71BkTSYMA7oUFORNJgwCZ2a5VE0mDAg+BE3ETSYMCkW3EiRdJgwNBsRGdF0mDA7/XTqkXSYMB8kAHuRdJgwJh48TBG0mDATBvHc0bSYMByfPW2RtJgwM90m/pG0mDAV9QbP0fSYMAPAX2ER9JgwCJa7MhH0mDA6+M1EEjSYMCXotVaSNJgwECUkaNI0mDAWs9i7EjSYMDxNWE1SdJgwL3rmn5J0mDAs6fwx0nSYMBTBTARStJgwI1IFlpK0mDAcR1yokrSYMDd10XqStJgwDOUgTFL0mDA1RQSeEvSYMBeFfm9S9JgwK97kANM0mDAy+HOSEzSYMA8Tb+NTNJgwO3kLdJM0mDAOZpSFk3SYMAez4xaTdJgwHG2/J5N0mDA33uP403SYMBzVK8oTtJgwMA2Qm5O0mDAKhIetE7SYMBw3x0TTtJgwI6qSV5O0mDAlmbMqU7SYMD74W3RT9JgwKgF7BlQ0mDAe8nSYlDSYMDMQBesUNJgwKGjifVQ0mDAYmf5P1HSYMBa8GCKUdJgwMgj6NRR0mDAS1O5H1LSYMCM+UmqUdJgwH33XPdR0mDAMbR6RFLSYMB8yLaSUtJgwPE5LuNS0mDAUexJKVTSYMCCFVFxVNJgwFPSa7lU0mDAR2u6AVXSYMBplhVKVdJgwPG8RJFV0mDAURZraVXSYMAlWE+6VdJgwAztXApW0mDAaVEXtVbSYMBTk+D+VtJgwHGKLe9W0mDAaYINOVfSYMCeceGCV9JgwOA3KM1X0mDA0+MKGFjSYMBCx0tkWNJgwMVXJbJY0mDAyVw4AVnSYMBuCHahWdJgwE8PyqFZ0mDAnKJ88lnSYMCVIYxDWtJgwGLA0ZNa0mDA\"},\"shape\":[24471],\"dtype\":\"float64\",\"order\":\"little\"}],[\"h_li\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"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+       "  var render_items = [{\"docid\":\"77daec3e-dafa-47a9-97b5-6ebc5610277c\",\"roots\":{\"p1002\":\"f18ad8ea-95ea-4ab6-98e8-a37bd6fcafa9\"},\"root_ids\":[\"p1002\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  const is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1\n",
+       "  function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version && !is_dev) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ],
+      "text/plain": [
+       ":Scatter   [longitude]   (h_li)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "p1002"
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds['h_li'].hvplot(kind='scatter', s=2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e9b656e1-9a42-4656-bd59-79256053f1c8",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "## Additional resources\n",
+    "\n",
+    "For general information about NSIDC DAAC data in the Earthdata Cloud: \n",
+    "\n",
+    "[FAQs About NSIDC DAAC's Earthdata Cloud Migration](https://nsidc.org/data/user-resources/help-center/faqs-about-nsidc-daacs-earthdata-cloud-migration)\n",
+    "\n",
+    "[NASA Earthdata Cloud Data Access Guide](https://nsidc.org/data/user-resources/help-center/nasa-earthdata-cloud-data-access-guide)\n",
+    "\n",
+    "Additional tutorials and How Tos:\n",
+    "\n",
+    "[NASA Earthdata Cloud Cookbook](https://nasa-openscapes.github.io/earthdata-cloud-cookbook/)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
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+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/_sources/tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.ipynb b/_sources/tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.ipynb
new file mode 100644
index 0000000..6f46d2c
--- /dev/null
+++ b/_sources/tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.ipynb
@@ -0,0 +1,3477 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7fd4844a-aee8-4a9c-b22a-02688a8067f9",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "# NASA Earthdata Cloud and data access using earthaccess and icepyx\n",
+    "# Part 2: Using the `icepyx` python library to access ICESat-2 data\n",
+    "\n",
+    "## Tutorial Overview\n",
+    "\n",
+    "This tutorial is designed for the \"[Cloud Computing and Open-Source Scientific Software for Cryosphere Communities](https://agu.confex.com/agu/fm23/meetingapp.cgi/Session/193477)\" Learning Workshop at the 2023 AGU Fall Meeting.\n",
+    "\n",
+    "This notebook demonstrates how to search for, access, and analyse and plot a cloud-hosted ICESat-2 dataset using the [`icepyx`](https://icepyx.readthedocs.io/en/latest/example_notebooks/IS2_data_access.html) package.\n",
+    "\n",
+    "<figure>\n",
+    "<center>\n",
+    "    <img src=\"https://icepyx.readthedocs.io/en/latest/_static/icepyx_v2_oval_orig_nobackgr.png\" alt='icepyx logo of the word icepyx in raised letters on an iceberg with an ice ax'/>\n",
+    "</center>\n",
+    "</figure>\n",
+    "\n",
+    "icepyx is a community and software library for searching, downloading, and reading ICESat-2 data. While opening data should be straightforward, there are some oddities in navigating the highly nested organization and hundreds of variables of the ICESat-2 data. icepyx provides tools to help with those oddities.\n",
+    "\n",
+    "`icepyx` was started and initially developed by Jessica Scheick to provide easy programmatic access to ICESat-2 data (before `earthaccess` existed!) and facilitate collaborative development around ICESat-2 data products, including training, skill building, and support around practicing open science and contributing to open-source software. Thanks to contributions from countless community members, `icepyx` can (for ICESat-2 data): \n",
+    "- search for available data granules (data files)\n",
+    "- order and download data or access it directly in the cloud\n",
+    "- order a subset of data: clipped in space, time, containing fewer variables, or a few other options provided by NSIDC\n",
+    "- search through the available ICESat-2 data variables\n",
+    "- read ICESat-2 data into xarray DataArrays, including merging data from multiple files\n",
+    "\n",
+    "Under the hood, `icepyx` relies on `earthaccess` to help handle authentication, especially for obtaining S3 tokens to access ICESat-2 data in the cloud. All this happens without the user needing to take any action other than supplying their Earthdata Login credentials using one of the methods described in the `earthaccess` tutorial.\n",
+    "\n",
+    "In this tutorial we will look at the `ATL08` Land and Vegetation Height product.\n",
+    "\n",
+    "\n",
+    "### Learning Objectives\n",
+    "\n",
+    "In this tutorial you will learn:  \n",
+    "1. how to use `icepyx` to search for ICESat-2 data using spatial and temporal filters;  \n",
+    "2. how to open and combine data multiple HDF5 groups into an `xarray.Dataset` using `icepyx.Read`;  \n",
+    "3. how to begin your analysis, including selecting strong/weak beams and plotting.  \n",
+    "\n",
+    "## Prerequisites\n",
+    "\n",
+    "The workflow described in this tutorial forms the initial steps of an _Analysis in Place_ workflow that would be run on a AWS cloud compute resource.  You will need:\n",
+    "\n",
+    "1. a JupyterHub, such as CryoHub, or AWS EC2 instance in the us-west-2 region.\n",
+    "3. a NASA Earthdata Login.  If you need to register for an Earthdata Login see the [Getting an Earthdata Login](https://icesat-2-2023.hackweek.io/preliminary/checklist/earthdata.html#getting-an-earthdata-login) section of the ICESat-2 Hackweek 2023 Jupyter Book.\n",
+    "4. A `.netrc` file, that contains your Earthdata Login credentials, in your home directory. See [Configure Programmatic Access to NASA Servers](https://icesat-2-2023.hackweek.io/preliminary/checklist/earthdata.html#configure-programmatic-access-to-nasa-servers) to create a `.netrc` file.\n",
+    "\n",
+    "## Credits\n",
+    "\n",
+    "This notebook is based on an [icepyx Tutorial](https://nasa-openscapes.github.io/2023-ssc/tutorials/data-access/icepyx.html) originally created by Rachel Wegener, Univ. Maryland and updated by Amy Steiker, NSIDC, and Jessica Scheick, Univ. of New Hampshire."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "226c1ce2-0351-4a06-88ee-7d31aa5b9d86",
+   "metadata": {
+    "tags": [],
+    "user_expressions": []
+   },
+   "source": [
+    "## Using `icepyx` to search and access ICESat-2 data\n",
+    "\n",
+    "We won't dive into using icepyx to search for and download data in this tutorial, since we already discussed how to do that with `earthaccess`. The code to search and download is still provided below for the curious reader. The [icepyx documentation](https://icepyx.readthedocs.io/en/latest/example_notebooks/IS2_data_access.html) shows more detail about different search parameters and how to inspect the results of a query."
+   ]
+  },
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+   "id": "8b144e54-6e70-499d-8cd0-2d3dffe238db",
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+       "      var url = css_urls[i];\n",
+       "      if (existing_stylesheets.indexOf(url) !== -1) {\n",
+       "\ton_load()\n",
+       "\tcontinue;\n",
+       "      }\n",
+       "      const element = document.createElement(\"link\");\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.rel = \"stylesheet\";\n",
+       "      element.type = \"text/css\";\n",
+       "      element.href = url;\n",
+       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
+       "      document.body.appendChild(element);\n",
+       "    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n",
+       "      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n",
+       "      for (var i = 0; i < urls.length; i++) {\n",
+       "        skip.push(urls[i])\n",
+       "      }\n",
+       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
+       "      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
+       "      for (var i = 0; i < urls.length; i++) {\n",
+       "        skip.push(urls[i])\n",
+       "      }\n",
+       "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
+       "      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
+       "      for (var i = 0; i < urls.length; i++) {\n",
+       "        skip.push(urls[i])\n",
+       "      }\n",
+       "    }    var existing_scripts = []\n",
+       "    var scripts = document.getElementsByTagName('script')\n",
+       "    for (var i = 0; i < scripts.length; i++) {\n",
+       "      var script = scripts[i]\n",
+       "      if (script.src != null) {\n",
+       "\texisting_scripts.push(script.src)\n",
+       "      }\n",
+       "    }\n",
+       "    for (var i = 0; i < js_urls.length; i++) {\n",
+       "      var url = js_urls[i];\n",
+       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
+       "\tif (!window.requirejs) {\n",
+       "\t  on_load();\n",
+       "\t}\n",
+       "\tcontinue;\n",
+       "      }\n",
+       "      var element = document.createElement('script');\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.src = url;\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    for (var i = 0; i < js_modules.length; i++) {\n",
+       "      var url = js_modules[i];\n",
+       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
+       "\tif (!window.requirejs) {\n",
+       "\t  on_load();\n",
+       "\t}\n",
+       "\tcontinue;\n",
+       "      }\n",
+       "      var element = document.createElement('script');\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.src = url;\n",
+       "      element.type = \"module\";\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    for (const name in js_exports) {\n",
+       "      var url = js_exports[name];\n",
+       "      if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
+       "\tif (!window.requirejs) {\n",
+       "\t  on_load();\n",
+       "\t}\n",
+       "\tcontinue;\n",
+       "      }\n",
+       "      var element = document.createElement('script');\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.type = \"module\";\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      element.textContent = `\n",
+       "      import ${name} from \"${url}\"\n",
+       "      window.${name} = ${name}\n",
+       "      window._bokeh_on_load()\n",
+       "      `\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    if (!js_urls.length && !js_modules.length) {\n",
+       "      on_load()\n",
+       "    }\n",
+       "  };\n",
+       "\n",
+       "  function inject_raw_css(css) {\n",
+       "    const element = document.createElement(\"style\");\n",
+       "    element.appendChild(document.createTextNode(css));\n",
+       "    document.body.appendChild(element);\n",
+       "  }\n",
+       "\n",
+       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.2.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n",
+       "  var js_modules = [];\n",
+       "  var js_exports = {};\n",
+       "  var css_urls = [];\n",
+       "  var inline_js = [    function(Bokeh) {\n",
+       "      Bokeh.set_log_level(\"info\");\n",
+       "    },\n",
+       "function(Bokeh) {} // ensure no trailing comma for IE\n",
+       "  ];\n",
+       "\n",
+       "  function run_inline_js() {\n",
+       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
+       "      for (var i = 0; i < inline_js.length; i++) {\n",
+       "        inline_js[i].call(root, root.Bokeh);\n",
+       "      }\n",
+       "      // Cache old bokeh versions\n",
+       "      if (Bokeh != undefined && !reloading) {\n",
+       "\tvar NewBokeh = root.Bokeh;\n",
+       "\tif (Bokeh.versions === undefined) {\n",
+       "\t  Bokeh.versions = new Map();\n",
+       "\t}\n",
+       "\tif (NewBokeh.version !== Bokeh.version) {\n",
+       "\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
+       "\t}\n",
+       "\troot.Bokeh = Bokeh;\n",
+       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
+       "      setTimeout(run_inline_js, 100);\n",
+       "    } else if (!root._bokeh_failed_load) {\n",
+       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
+       "      root._bokeh_failed_load = true;\n",
+       "    }\n",
+       "    root._bokeh_is_initializing = false\n",
+       "  }\n",
+       "\n",
+       "  function load_or_wait() {\n",
+       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
+       "    // versions of Bokeh and its dependencies at the same time.\n",
+       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
+       "    // to determine whether there is an ongoing attempt to initialize\n",
+       "    // bokeh, however for backward compatibility we also try to ensure\n",
+       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
+       "    // before older versions are fully initialized.\n",
+       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
+       "      root._bokeh_is_initializing = false;\n",
+       "      root._bokeh_onload_callbacks = undefined;\n",
+       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
+       "      load_or_wait();\n",
+       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
+       "      setTimeout(load_or_wait, 100);\n",
+       "    } else {\n",
+       "      Bokeh = root.Bokeh;\n",
+       "      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
+       "      root._bokeh_is_initializing = true\n",
+       "      root._bokeh_onload_callbacks = []\n",
+       "      if (!reloading && (!bokeh_loaded || is_dev)) {\n",
+       "\troot.Bokeh = undefined;\n",
+       "      }\n",
+       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
+       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
+       "\trun_inline_js();\n",
+       "      });\n",
+       "    }\n",
+       "  }\n",
+       "  // Give older versions of the autoload script a head-start to ensure\n",
+       "  // they initialize before we start loading newer version.\n",
+       "  setTimeout(load_or_wait, 100)\n",
+       "}(window));"
+      ],
+      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n  var py_version = '3.2.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n  var reloading = false;\n  var Bokeh = root.Bokeh;\n  var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      run_callbacks();\n      return null;\n    }\n    if (!reloading) {\n      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n      })\n      require([\"jspanel-modal\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-tooltip\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-hint\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-layout\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-dock\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 9;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    var existing_stylesheets = []\n    var links = document.getElementsByTagName('link')\n    for (var i = 0; i < links.length; i++) {\n      var link = links[i]\n      if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n      }\n    }\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.2.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      Bokeh = root.Bokeh;\n      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "\n",
+       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
+       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
+       "}\n",
+       "\n",
+       "\n",
+       "    function JupyterCommManager() {\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        comm_manager.register_target(comm_id, function(comm) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        });\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        });\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
+       "          var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "          function processIteratorResult(result) {\n",
+       "            var message = result.value;\n",
+       "            console.log(message)\n",
+       "            var content = {data: message.data, comm_id};\n",
+       "            var buffers = []\n",
+       "            for (var buffer of message.buffers || []) {\n",
+       "              buffers.push(new DataView(buffer))\n",
+       "            }\n",
+       "            var metadata = message.metadata || {};\n",
+       "            var msg = {content, buffers, metadata}\n",
+       "            msg_handler(msg);\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "          return messages.next().then(processIteratorResult);\n",
+       "        })\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (comm_id in window.PyViz.comms) {\n",
+       "        return window.PyViz.comms[comm_id];\n",
+       "      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
+       "        if (msg_handler) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        }\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
+       "        comm.open();\n",
+       "        if (msg_handler) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        }\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
+       "        comm_promise.then((comm) => {\n",
+       "          window.PyViz.comms[comm_id] = comm;\n",
+       "          if (msg_handler) {\n",
+       "            var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "            function processIteratorResult(result) {\n",
+       "              var message = result.value;\n",
+       "              var content = {data: message.data};\n",
+       "              var metadata = message.metadata || {comm_id};\n",
+       "              var msg = {content, metadata}\n",
+       "              msg_handler(msg);\n",
+       "              return messages.next().then(processIteratorResult);\n",
+       "            }\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "        }) \n",
+       "        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
+       "          return comm_promise.then((comm) => {\n",
+       "            comm.send(data, metadata, buffers, disposeOnDone);\n",
+       "          });\n",
+       "        };\n",
+       "        var comm = {\n",
+       "          send: sendClosure\n",
+       "        };\n",
+       "      }\n",
+       "      window.PyViz.comms[comm_id] = comm;\n",
+       "      return comm;\n",
+       "    }\n",
+       "    window.PyViz.comm_manager = new JupyterCommManager();\n",
+       "    \n",
+       "\n",
+       "\n",
+       "var JS_MIME_TYPE = 'application/javascript';\n",
+       "var HTML_MIME_TYPE = 'text/html';\n",
+       "var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
+       "var CLASS_NAME = 'output';\n",
+       "\n",
+       "/**\n",
+       " * Render data to the DOM node\n",
+       " */\n",
+       "function render(props, node) {\n",
+       "  var div = document.createElement(\"div\");\n",
+       "  var script = document.createElement(\"script\");\n",
+       "  node.appendChild(div);\n",
+       "  node.appendChild(script);\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when a new output is added\n",
+       " */\n",
+       "function handle_add_output(event, handle) {\n",
+       "  var output_area = handle.output_area;\n",
+       "  var output = handle.output;\n",
+       "  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
+       "    return\n",
+       "  }\n",
+       "  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
+       "  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
+       "  if (id !== undefined) {\n",
+       "    var nchildren = toinsert.length;\n",
+       "    var html_node = toinsert[nchildren-1].children[0];\n",
+       "    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var scripts = [];\n",
+       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
+       "    for (var i in nodelist) {\n",
+       "      if (nodelist.hasOwnProperty(i)) {\n",
+       "        scripts.push(nodelist[i])\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    scripts.forEach( function (oldScript) {\n",
+       "      var newScript = document.createElement(\"script\");\n",
+       "      var attrs = [];\n",
+       "      var nodemap = oldScript.attributes;\n",
+       "      for (var j in nodemap) {\n",
+       "        if (nodemap.hasOwnProperty(j)) {\n",
+       "          attrs.push(nodemap[j])\n",
+       "        }\n",
+       "      }\n",
+       "      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
+       "      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
+       "      oldScript.parentNode.replaceChild(newScript, oldScript);\n",
+       "    });\n",
+       "    if (JS_MIME_TYPE in output.data) {\n",
+       "      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
+       "    }\n",
+       "    output_area._hv_plot_id = id;\n",
+       "    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
+       "      window.PyViz.plot_index[id] = Bokeh.index[id];\n",
+       "    } else {\n",
+       "      window.PyViz.plot_index[id] = null;\n",
+       "    }\n",
+       "  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
+       "    var bk_div = document.createElement(\"div\");\n",
+       "    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var script_attrs = bk_div.children[0].attributes;\n",
+       "    for (var i = 0; i < script_attrs.length; i++) {\n",
+       "      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
+       "    }\n",
+       "    // store reference to server id on output_area\n",
+       "    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when an output is cleared or removed\n",
+       " */\n",
+       "function handle_clear_output(event, handle) {\n",
+       "  var id = handle.cell.output_area._hv_plot_id;\n",
+       "  var server_id = handle.cell.output_area._bokeh_server_id;\n",
+       "  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
+       "  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
+       "  if (server_id !== null) {\n",
+       "    comm.send({event_type: 'server_delete', 'id': server_id});\n",
+       "    return;\n",
+       "  } else if (comm !== null) {\n",
+       "    comm.send({event_type: 'delete', 'id': id});\n",
+       "  }\n",
+       "  delete PyViz.plot_index[id];\n",
+       "  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
+       "    var doc = window.Bokeh.index[id].model.document\n",
+       "    doc.clear();\n",
+       "    const i = window.Bokeh.documents.indexOf(doc);\n",
+       "    if (i > -1) {\n",
+       "      window.Bokeh.documents.splice(i, 1);\n",
+       "    }\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle kernel restart event\n",
+       " */\n",
+       "function handle_kernel_cleanup(event, handle) {\n",
+       "  delete PyViz.comms[\"hv-extension-comm\"];\n",
+       "  window.PyViz.plot_index = {}\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle update_display_data messages\n",
+       " */\n",
+       "function handle_update_output(event, handle) {\n",
+       "  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
+       "  handle_add_output(event, handle)\n",
+       "}\n",
+       "\n",
+       "function register_renderer(events, OutputArea) {\n",
+       "  function append_mime(data, metadata, element) {\n",
+       "    // create a DOM node to render to\n",
+       "    var toinsert = this.create_output_subarea(\n",
+       "    metadata,\n",
+       "    CLASS_NAME,\n",
+       "    EXEC_MIME_TYPE\n",
+       "    );\n",
+       "    this.keyboard_manager.register_events(toinsert);\n",
+       "    // Render to node\n",
+       "    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
+       "    render(props, toinsert[0]);\n",
+       "    element.append(toinsert);\n",
+       "    return toinsert\n",
+       "  }\n",
+       "\n",
+       "  events.on('output_added.OutputArea', handle_add_output);\n",
+       "  events.on('output_updated.OutputArea', handle_update_output);\n",
+       "  events.on('clear_output.CodeCell', handle_clear_output);\n",
+       "  events.on('delete.Cell', handle_clear_output);\n",
+       "  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
+       "\n",
+       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
+       "    safe: true,\n",
+       "    index: 0\n",
+       "  });\n",
+       "}\n",
+       "\n",
+       "if (window.Jupyter !== undefined) {\n",
+       "  try {\n",
+       "    var events = require('base/js/events');\n",
+       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
+       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
+       "      register_renderer(events, OutputArea);\n",
+       "    }\n",
+       "  } catch(err) {\n",
+       "  }\n",
+       "}\n"
+      ],
+      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        comm.open();\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        }) \n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "  ),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<div class=\"logo-block\">\n",
+       "<img src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAEAAAABACAYAAACqaXHeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\n",
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+       "     style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
+       "\n",
+       "\n",
+       "  <img src='data:image/png;base64,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'\n",
+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
+       "  \n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "</div>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import icepyx as ipx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "068bdc10-a87a-46c8-b854-3454307c87ec",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import math\n",
+    "import warnings\n",
+    "\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from shapely.geometry import shape, GeometryCollection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "9de015ca-967e-4075-92e5-315688838331",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "22884c88-8938-45de-8441-6cdeb0c66161",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/svg+xml": [
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+      ],
+      "text/plain": [
+       "<GEOMETRYCOLLECTION Z (POLYGON Z ((-103.495 20.715 0, -103.49 20.714 0, -103...>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Open a geojson of our area of interest\n",
+    "with open(\"./bosque_primavera.json\") as f:\n",
+    "    features = json.load(f)[\"features\"]\n",
+    "\n",
+    "bosque = GeometryCollection([shape(feature[\"geometry\"]).buffer(0) for feature in features])\n",
+    "bosque"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "85424146-5854-46b0-a591-6940f95c06ce",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Use our search parameters to setup a search Query\n",
+    "short_name = 'ATL08'\n",
+    "spatial_extent = list(bosque.bounds)\n",
+    "date_range = ['2019-05-04','2019-05-04']\n",
+    "region = ipx.Query(short_name, spatial_extent, date_range)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "e47243c3-ad90-40fe-b963-61b699260098",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[['ATL08_20190504124152_05540301_006_02.h5']]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Display if any data files, or granules, matched our search\n",
+    "region.avail_granules(ids=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "606ed988-4b27-467b-98ec-09dcce55db3e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[['ATL08_20190504124152_05540301_006_02.h5'],\n",
+       " ['s3://nsidc-cumulus-prod-protected/ATLAS/ATL08/006/2019/05/04/ATL08_20190504124152_05540301_006_02.h5']]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# We can also get the S3 urls\n",
+    "region.avail_granules(ids=True, cloud=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "56235e33-17a0-4010-91fe-9d30f9ecded4",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Enter your Earthdata Login username:  amy.steiker\n",
+      "Enter your Earthdata password:  ········\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total number of data order requests is  1  for  1  granules.\n",
+      "Data request  1  of  1  is submitting to NSIDC\n",
+      "order ID:  5000004735271\n",
+      "Initial status of your order request at NSIDC is:  processing\n",
+      "Your order status is still  processing  at NSIDC. Please continue waiting... this may take a few moments.\n",
+      "Your order is: complete\n",
+      "Beginning download of zipped output...\n",
+      "Data request 5000004735271 of  1  order(s) is downloaded.\n",
+      "Download complete\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Download the granules to a into a folder called 'bosque_primavera_ATL08'\n",
+    "region.download_granules('./bosque_primavera_ATL08')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "598ce7b4-3deb-4e30-ad7a-123a2e59865d",
+   "metadata": {
+    "tags": [],
+    "user_expressions": []
+   },
+   "source": [
+    "<div class=\"alert alert-block alert-info\">\n",
+    "<b>Tip:</b> If you don't want to type your Earthdata Login information every time they are\n",
+    "    required you can setup more automatic methods of authentication. Two common methods\n",
+    "    are 1) Add your earthdata password and username to as environment variables\n",
+    "    as EARTHDATA_USERNAME and EARTHDATA_PASSWORD. 2) setup a .netrc file in your home directory. See <a href=\"https://nasa-openscapes.github.io/2021-Cloud-Hackathon/tutorials/04_NASA_Earthdata_Authentication.html\"> the Openscapes tutorial</a> </div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eb212ef0-8817-4040-85ed-eda09e871a89",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "## Reading a file with icepyx\n",
+    "\n",
+    "To read a file with icepyx there are several steps:\n",
+    "1. Create a `Read` object. This sets up an initial connection to your file(s) and validates the metadata.\n",
+    "2. Tell the `Read` object what variables you would like to read\n",
+    "3. Load your data!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d65b6b5-6796-4c9c-9c70-9ce30d4cb0b6",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "### Create a `Read` object\n",
+    "\n",
+    "Here we are creating a read object to set up an initial connection to your file(s). The pattern outlines the file naming convention. For example, `{revision:2}` describes the last two values in the filename which denote the product revision number. Details on the filenaming convention are found [here](https://nsidc.org/sites/default/files/documents/user-guide/atl08-v006-userguide.pdf). "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "bd2f1313-0756-414e-85f7-816a82a7d209",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "You have 1 files matching the filename pattern to be read in.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pattern = \"processed_ATL{product:2}_{datetime:%Y%m%d%H%M%S}_{rgt:4}{cycle:2}{orbitsegment:2}_{version:3}_{revision:2}.h5\"\n",
+    "reader = ipx.Read('./bosque_primavera_ATL08', \"ATL08\", pattern)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "19d027f3-25d6-4667-9ebb-8bbf1844fdfb",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<icepyx.core.read.Read at 0x7f2b12bb0c10>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "reader"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8ec85d0c-65fc-4896-9c4b-0d63af233ea4",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "### Select your variables\n",
+    "\n",
+    "To view the variables contained in your dataset you can call `.vars` on your data reader."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "6d1c5e47-d748-410f-adf7-3e887c682d68",
+   "metadata": {
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['ancillary_data/atlas_sdp_gps_epoch',\n",
+       " 'ancillary_data/control',\n",
+       " 'ancillary_data/data_end_utc',\n",
+       " 'ancillary_data/data_start_utc',\n",
+       " 'ancillary_data/end_cycle',\n",
+       " 'ancillary_data/end_delta_time',\n",
+       " 'ancillary_data/end_geoseg',\n",
+       " 'ancillary_data/end_gpssow',\n",
+       " 'ancillary_data/end_gpsweek',\n",
+       " 'ancillary_data/end_orbit',\n",
+       " 'ancillary_data/end_region',\n",
+       " 'ancillary_data/end_rgt',\n",
+       " 'ancillary_data/granule_end_utc',\n",
+       " 'ancillary_data/granule_start_utc',\n",
+       " 'ancillary_data/land/atl08_region',\n",
+       " 'ancillary_data/land/bin_size_h',\n",
+       " 'ancillary_data/land/bin_size_n',\n",
+       " 'ancillary_data/land/bright_thresh',\n",
+       " 'ancillary_data/land/ca_class',\n",
+       " 'ancillary_data/land/can_noise_thresh',\n",
+       " 'ancillary_data/land/can_stat_thresh',\n",
+       " 'ancillary_data/land/canopy20m_thresh',\n",
+       " 'ancillary_data/land/canopy_flag_switch',\n",
+       " 'ancillary_data/land/canopy_seg',\n",
+       " 'ancillary_data/land/class_thresh',\n",
+       " 'ancillary_data/land/cloud_filter_switch',\n",
+       " 'ancillary_data/land/del_amp',\n",
+       " 'ancillary_data/land/del_mu',\n",
+       " 'ancillary_data/land/del_sigma',\n",
+       " 'ancillary_data/land/dem_filter_switch',\n",
+       " 'ancillary_data/land/dem_removal_percent_limit',\n",
+       " 'ancillary_data/land/dragann_switch',\n",
+       " 'ancillary_data/land/dseg',\n",
+       " 'ancillary_data/land/dseg_buf',\n",
+       " 'ancillary_data/land/fnlgnd_filter_switch',\n",
+       " 'ancillary_data/land/gnd_stat_thresh',\n",
+       " 'ancillary_data/land/gthresh_factor',\n",
+       " 'ancillary_data/land/h_canopy_perc',\n",
+       " 'ancillary_data/land/iter_gnd',\n",
+       " 'ancillary_data/land/iter_max',\n",
+       " 'ancillary_data/land/lseg',\n",
+       " 'ancillary_data/land/lseg_buf',\n",
+       " 'ancillary_data/land/lw_filt_bnd',\n",
+       " 'ancillary_data/land/lw_gnd_bnd',\n",
+       " 'ancillary_data/land/lw_toc_bnd',\n",
+       " 'ancillary_data/land/lw_toc_cut',\n",
+       " 'ancillary_data/land/max_atl03files',\n",
+       " 'ancillary_data/land/max_atl09files',\n",
+       " 'ancillary_data/land/max_peaks',\n",
+       " 'ancillary_data/land/max_try',\n",
+       " 'ancillary_data/land/min_nphs',\n",
+       " 'ancillary_data/land/n_dec_mode',\n",
+       " 'ancillary_data/land/night_thresh',\n",
+       " 'ancillary_data/land/noise_class',\n",
+       " 'ancillary_data/land/outlier_filter_switch',\n",
+       " 'ancillary_data/land/p_static',\n",
+       " 'ancillary_data/land/ph_removal_percent_limit',\n",
+       " 'ancillary_data/land/proc_geoseg',\n",
+       " 'ancillary_data/land/psf',\n",
+       " 'ancillary_data/land/ref_dem_limit',\n",
+       " 'ancillary_data/land/ref_finalground_limit',\n",
+       " 'ancillary_data/land/relief_hbot',\n",
+       " 'ancillary_data/land/relief_htop',\n",
+       " 'ancillary_data/land/shp_param',\n",
+       " 'ancillary_data/land/sig_rsq_search',\n",
+       " 'ancillary_data/land/sseg',\n",
+       " 'ancillary_data/land/stat20m_thresh',\n",
+       " 'ancillary_data/land/stat_thresh',\n",
+       " 'ancillary_data/land/tc_thresh',\n",
+       " 'ancillary_data/land/te_class',\n",
+       " 'ancillary_data/land/terrain20m_thresh',\n",
+       " 'ancillary_data/land/toc_class',\n",
+       " 'ancillary_data/land/up_filt_bnd',\n",
+       " 'ancillary_data/land/up_gnd_bnd',\n",
+       " 'ancillary_data/land/up_toc_bnd',\n",
+       " 'ancillary_data/land/up_toc_cut',\n",
+       " 'ancillary_data/land/yapc_switch',\n",
+       " 'ancillary_data/qa_at_interval',\n",
+       " 'ancillary_data/release',\n",
+       " 'ancillary_data/start_cycle',\n",
+       " 'ancillary_data/start_delta_time',\n",
+       " 'ancillary_data/start_geoseg',\n",
+       " 'ancillary_data/start_gpssow',\n",
+       " 'ancillary_data/start_gpsweek',\n",
+       " 'ancillary_data/start_orbit',\n",
+       " 'ancillary_data/start_region',\n",
+       " 'ancillary_data/start_rgt',\n",
+       " 'ancillary_data/version',\n",
+       " 'ds_geosegments',\n",
+       " 'ds_metrics',\n",
+       " 'ds_surf_type',\n",
+       " 'gt3l/land_segments/asr',\n",
+       " 'gt3l/land_segments/atlas_pa',\n",
+       " 'gt3l/land_segments/beam_azimuth',\n",
+       " 'gt3l/land_segments/beam_coelev',\n",
+       " 'gt3l/land_segments/brightness_flag',\n",
+       " 'gt3l/land_segments/canopy/can_noise',\n",
+       " 'gt3l/land_segments/canopy/canopy_h_metrics',\n",
+       " 'gt3l/land_segments/canopy/canopy_h_metrics_abs',\n",
+       " 'gt3l/land_segments/canopy/canopy_openness',\n",
+       " 'gt3l/land_segments/canopy/canopy_rh_conf',\n",
+       " 'gt3l/land_segments/canopy/centroid_height',\n",
+       " 'gt3l/land_segments/canopy/h_canopy',\n",
+       " 'gt3l/land_segments/canopy/h_canopy_20m',\n",
+       " 'gt3l/land_segments/canopy/h_canopy_abs',\n",
+       " 'gt3l/land_segments/canopy/h_canopy_quad',\n",
+       " 'gt3l/land_segments/canopy/h_canopy_uncertainty',\n",
+       " 'gt3l/land_segments/canopy/h_dif_canopy',\n",
+       " 'gt3l/land_segments/canopy/h_max_canopy',\n",
+       " 'gt3l/land_segments/canopy/h_max_canopy_abs',\n",
+       " 'gt3l/land_segments/canopy/h_mean_canopy',\n",
+       " 'gt3l/land_segments/canopy/h_mean_canopy_abs',\n",
+       " 'gt3l/land_segments/canopy/h_median_canopy',\n",
+       " 'gt3l/land_segments/canopy/h_median_canopy_abs',\n",
+       " 'gt3l/land_segments/canopy/h_min_canopy',\n",
+       " 'gt3l/land_segments/canopy/h_min_canopy_abs',\n",
+       " 'gt3l/land_segments/canopy/n_ca_photons',\n",
+       " 'gt3l/land_segments/canopy/n_toc_photons',\n",
+       " 'gt3l/land_segments/canopy/photon_rate_can',\n",
+       " 'gt3l/land_segments/canopy/photon_rate_can_nr',\n",
+       " 'gt3l/land_segments/canopy/segment_cover',\n",
+       " 'gt3l/land_segments/canopy/subset_can_flag',\n",
+       " 'gt3l/land_segments/canopy/toc_roughness',\n",
+       " 'gt3l/land_segments/cloud_flag_atm',\n",
+       " 'gt3l/land_segments/cloud_fold_flag',\n",
+       " 'gt3l/land_segments/delta_time',\n",
+       " 'gt3l/land_segments/delta_time_beg',\n",
+       " 'gt3l/land_segments/delta_time_end',\n",
+       " 'gt3l/land_segments/dem_flag',\n",
+       " 'gt3l/land_segments/dem_h',\n",
+       " 'gt3l/land_segments/dem_removal_flag',\n",
+       " 'gt3l/land_segments/h_dif_ref',\n",
+       " 'gt3l/land_segments/last_seg_extend',\n",
+       " 'gt3l/land_segments/latitude',\n",
+       " 'gt3l/land_segments/latitude_20m',\n",
+       " 'gt3l/land_segments/layer_flag',\n",
+       " 'gt3l/land_segments/longitude',\n",
+       " 'gt3l/land_segments/longitude_20m',\n",
+       " 'gt3l/land_segments/msw_flag',\n",
+       " 'gt3l/land_segments/n_seg_ph',\n",
+       " 'gt3l/land_segments/night_flag',\n",
+       " 'gt3l/land_segments/ph_ndx_beg',\n",
+       " 'gt3l/land_segments/ph_removal_flag',\n",
+       " 'gt3l/land_segments/psf_flag',\n",
+       " 'gt3l/land_segments/rgt',\n",
+       " 'gt3l/land_segments/sat_flag',\n",
+       " 'gt3l/land_segments/segment_id_beg',\n",
+       " 'gt3l/land_segments/segment_id_end',\n",
+       " 'gt3l/land_segments/segment_landcover',\n",
+       " 'gt3l/land_segments/segment_snowcover',\n",
+       " 'gt3l/land_segments/segment_watermask',\n",
+       " 'gt3l/land_segments/sigma_across',\n",
+       " 'gt3l/land_segments/sigma_along',\n",
+       " 'gt3l/land_segments/sigma_atlas_land',\n",
+       " 'gt3l/land_segments/sigma_h',\n",
+       " 'gt3l/land_segments/sigma_topo',\n",
+       " 'gt3l/land_segments/snr',\n",
+       " 'gt3l/land_segments/solar_azimuth',\n",
+       " 'gt3l/land_segments/solar_elevation',\n",
+       " 'gt3l/land_segments/surf_type',\n",
+       " 'gt3l/land_segments/terrain/h_te_best_fit',\n",
+       " 'gt3l/land_segments/terrain/h_te_best_fit_20m',\n",
+       " 'gt3l/land_segments/terrain/h_te_interp',\n",
+       " 'gt3l/land_segments/terrain/h_te_max',\n",
+       " 'gt3l/land_segments/terrain/h_te_mean',\n",
+       " 'gt3l/land_segments/terrain/h_te_median',\n",
+       " 'gt3l/land_segments/terrain/h_te_min',\n",
+       " 'gt3l/land_segments/terrain/h_te_mode',\n",
+       " 'gt3l/land_segments/terrain/h_te_rh25',\n",
+       " 'gt3l/land_segments/terrain/h_te_skew',\n",
+       " 'gt3l/land_segments/terrain/h_te_std',\n",
+       " 'gt3l/land_segments/terrain/h_te_uncertainty',\n",
+       " 'gt3l/land_segments/terrain/n_te_photons',\n",
+       " 'gt3l/land_segments/terrain/photon_rate_te',\n",
+       " 'gt3l/land_segments/terrain/subset_te_flag',\n",
+       " 'gt3l/land_segments/terrain/terrain_slope',\n",
+       " 'gt3l/land_segments/terrain_flg',\n",
+       " 'gt3l/land_segments/urban_flag',\n",
+       " 'gt3l/signal_photons/classed_pc_flag',\n",
+       " 'gt3l/signal_photons/classed_pc_indx',\n",
+       " 'gt3l/signal_photons/d_flag',\n",
+       " 'gt3l/signal_photons/delta_time',\n",
+       " 'gt3l/signal_photons/ph_h',\n",
+       " 'gt3l/signal_photons/ph_segment_id',\n",
+       " 'gt3r/land_segments/asr',\n",
+       " 'gt3r/land_segments/atlas_pa',\n",
+       " 'gt3r/land_segments/beam_azimuth',\n",
+       " 'gt3r/land_segments/beam_coelev',\n",
+       " 'gt3r/land_segments/brightness_flag',\n",
+       " 'gt3r/land_segments/canopy/can_noise',\n",
+       " 'gt3r/land_segments/canopy/canopy_h_metrics',\n",
+       " 'gt3r/land_segments/canopy/canopy_h_metrics_abs',\n",
+       " 'gt3r/land_segments/canopy/canopy_openness',\n",
+       " 'gt3r/land_segments/canopy/canopy_rh_conf',\n",
+       " 'gt3r/land_segments/canopy/centroid_height',\n",
+       " 'gt3r/land_segments/canopy/h_canopy',\n",
+       " 'gt3r/land_segments/canopy/h_canopy_20m',\n",
+       " 'gt3r/land_segments/canopy/h_canopy_abs',\n",
+       " 'gt3r/land_segments/canopy/h_canopy_quad',\n",
+       " 'gt3r/land_segments/canopy/h_canopy_uncertainty',\n",
+       " 'gt3r/land_segments/canopy/h_dif_canopy',\n",
+       " 'gt3r/land_segments/canopy/h_max_canopy',\n",
+       " 'gt3r/land_segments/canopy/h_max_canopy_abs',\n",
+       " 'gt3r/land_segments/canopy/h_mean_canopy',\n",
+       " 'gt3r/land_segments/canopy/h_mean_canopy_abs',\n",
+       " 'gt3r/land_segments/canopy/h_median_canopy',\n",
+       " 'gt3r/land_segments/canopy/h_median_canopy_abs',\n",
+       " 'gt3r/land_segments/canopy/h_min_canopy',\n",
+       " 'gt3r/land_segments/canopy/h_min_canopy_abs',\n",
+       " 'gt3r/land_segments/canopy/n_ca_photons',\n",
+       " 'gt3r/land_segments/canopy/n_toc_photons',\n",
+       " 'gt3r/land_segments/canopy/photon_rate_can',\n",
+       " 'gt3r/land_segments/canopy/photon_rate_can_nr',\n",
+       " 'gt3r/land_segments/canopy/segment_cover',\n",
+       " 'gt3r/land_segments/canopy/subset_can_flag',\n",
+       " 'gt3r/land_segments/canopy/toc_roughness',\n",
+       " 'gt3r/land_segments/cloud_flag_atm',\n",
+       " 'gt3r/land_segments/cloud_fold_flag',\n",
+       " 'gt3r/land_segments/delta_time',\n",
+       " 'gt3r/land_segments/delta_time_beg',\n",
+       " 'gt3r/land_segments/delta_time_end',\n",
+       " 'gt3r/land_segments/dem_flag',\n",
+       " 'gt3r/land_segments/dem_h',\n",
+       " 'gt3r/land_segments/dem_removal_flag',\n",
+       " 'gt3r/land_segments/h_dif_ref',\n",
+       " 'gt3r/land_segments/last_seg_extend',\n",
+       " 'gt3r/land_segments/latitude',\n",
+       " 'gt3r/land_segments/latitude_20m',\n",
+       " 'gt3r/land_segments/layer_flag',\n",
+       " 'gt3r/land_segments/longitude',\n",
+       " 'gt3r/land_segments/longitude_20m',\n",
+       " 'gt3r/land_segments/msw_flag',\n",
+       " 'gt3r/land_segments/n_seg_ph',\n",
+       " 'gt3r/land_segments/night_flag',\n",
+       " 'gt3r/land_segments/ph_ndx_beg',\n",
+       " 'gt3r/land_segments/ph_removal_flag',\n",
+       " 'gt3r/land_segments/psf_flag',\n",
+       " 'gt3r/land_segments/rgt',\n",
+       " 'gt3r/land_segments/sat_flag',\n",
+       " 'gt3r/land_segments/segment_id_beg',\n",
+       " 'gt3r/land_segments/segment_id_end',\n",
+       " 'gt3r/land_segments/segment_landcover',\n",
+       " 'gt3r/land_segments/segment_snowcover',\n",
+       " 'gt3r/land_segments/segment_watermask',\n",
+       " 'gt3r/land_segments/sigma_across',\n",
+       " 'gt3r/land_segments/sigma_along',\n",
+       " 'gt3r/land_segments/sigma_atlas_land',\n",
+       " 'gt3r/land_segments/sigma_h',\n",
+       " 'gt3r/land_segments/sigma_topo',\n",
+       " 'gt3r/land_segments/snr',\n",
+       " 'gt3r/land_segments/solar_azimuth',\n",
+       " 'gt3r/land_segments/solar_elevation',\n",
+       " 'gt3r/land_segments/surf_type',\n",
+       " 'gt3r/land_segments/terrain/h_te_best_fit',\n",
+       " 'gt3r/land_segments/terrain/h_te_best_fit_20m',\n",
+       " 'gt3r/land_segments/terrain/h_te_interp',\n",
+       " 'gt3r/land_segments/terrain/h_te_max',\n",
+       " 'gt3r/land_segments/terrain/h_te_mean',\n",
+       " 'gt3r/land_segments/terrain/h_te_median',\n",
+       " 'gt3r/land_segments/terrain/h_te_min',\n",
+       " 'gt3r/land_segments/terrain/h_te_mode',\n",
+       " 'gt3r/land_segments/terrain/h_te_rh25',\n",
+       " 'gt3r/land_segments/terrain/h_te_skew',\n",
+       " 'gt3r/land_segments/terrain/h_te_std',\n",
+       " 'gt3r/land_segments/terrain/h_te_uncertainty',\n",
+       " 'gt3r/land_segments/terrain/n_te_photons',\n",
+       " 'gt3r/land_segments/terrain/photon_rate_te',\n",
+       " 'gt3r/land_segments/terrain/subset_te_flag',\n",
+       " 'gt3r/land_segments/terrain/terrain_slope',\n",
+       " 'gt3r/land_segments/terrain_flg',\n",
+       " 'gt3r/land_segments/urban_flag',\n",
+       " 'gt3r/signal_photons/classed_pc_flag',\n",
+       " 'gt3r/signal_photons/classed_pc_indx',\n",
+       " 'gt3r/signal_photons/d_flag',\n",
+       " 'gt3r/signal_photons/delta_time',\n",
+       " 'gt3r/signal_photons/ph_h',\n",
+       " 'gt3r/signal_photons/ph_segment_id',\n",
+       " 'orbit_info/bounding_polygon_lat1',\n",
+       " 'orbit_info/bounding_polygon_lon1',\n",
+       " 'orbit_info/crossing_time',\n",
+       " 'orbit_info/cycle_number',\n",
+       " 'orbit_info/lan',\n",
+       " 'orbit_info/orbit_number',\n",
+       " 'orbit_info/rgt',\n",
+       " 'orbit_info/sc_orient',\n",
+       " 'orbit_info/sc_orient_time',\n",
+       " 'quality_assessment/qa_granule_fail_reason',\n",
+       " 'quality_assessment/qa_granule_pass_fail']"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "reader.vars.avail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2bab202e-bbaa-40f1-a9b3-bd368de60bde",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "Thats **a lot** of variables!\n",
+    "\n",
+    "One key feature of icepyx is the ability to browse the variables available in the dataset. There are typically hundreds of variables in a single dataset, so that is a lot to sort through! Let's take a moment to get oriented to the organization of ATL08 variables, by first a few important pieces of the algorithm.\n",
+    "\n",
+    "To create higher level variables like canopy or terrain height, the ATL08 algorithms goes through a series of steps:\n",
+    "1. Identify signal photons from noise photons\n",
+    "2. Classify each of the signal photons as either terrain, canopy, or canopy top\n",
+    "3. Remove elevation, so the heights are with respect to the ground\n",
+    "3. Group the signal photons into 100m segments. If there are a sufficient number of photons in that group, calculate statistics for terrain and canopy (ex. mean height, max height, standard deviation, etc.)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8a78a4f8-ab6d-4317-8b9a-920c674daa03",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "<img src=\"https://nasa-openscapes.github.io/2023-ssc/tutorials/data-access/.images/ATL08_photon_classification_example.jpg\" width=450/>\n",
+    "\n",
+    "> _Fig. 4. An example of the classified photons produced from the ATL08 algorithm. Ground photons (red dots) are labeled as all photons falling within a point spread function distance of the estimated ground surface. The top of canopy photons (green dots) are photons that fall within a buffer distance from the upper canopy surface, and the photons that lie between the top of canopy surface and ground surface are labeled as canopy photons (blue dots)._ (Neuenschwander & Pitts, 2019)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2cd5e74-bb18-4c36-94d3-52a4b86e2c0e",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "Providing all the potentially useful information from all these processing steps results in a data file that looks like:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "37d18566-7eb3-47d7-acf9-04fde4911e54",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "<img src=\"https://nasa-openscapes.github.io/2023-ssc/tutorials/data-access/.images/ATL08_structure.png\" width=650/>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d2259a0-be76-4922-a700-16c21f618585",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "Another way to visualize these structure is to download one file and open it using https://myhdf5.hdfgroup.org/. \n",
+    "\n",
+    "Further information about each one of the variables is available in the [Algorithm Theoretical Basis Document (ATBD)](https://icesat-2.gsfc.nasa.gov/sites/default/files/page_files/ICESat2_ATL08_ATBD_r006.pdf) for ATL08."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "79bb7f14-b778-4b73-a56c-0393b3d7d8e0",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "There is lots to explore in these variables, but we will move forward using a common ATL08 variable: `h_canopy`, or the \"98% height of all the individual relative canopy heights (height above terrain)\" (ATBD definition)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "c9510cdf-f838-422c-a887-f58caf1e0fd2",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "reader.vars.append(var_list=['h_canopy', 'latitude', 'longitude'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b373e46a-cf1e-4ab6-88a6-9b4f14d3b5d9",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "Note that adding variables is a required step before you can load the data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4de08fc7-7f7e-4dea-a748-b5c6c885b88f",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "### Load the data!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "b65c7e21-f39e-4b93-b59f-17290262e22c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
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+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
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+       "\n",
+       ".xr-text-repr-fallback {\n",
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+       "  display: none;\n",
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+       "\n",
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+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
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+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
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+       "  display: contents;\n",
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+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
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+       "\n",
+       ".xr-section-item input + label {\n",
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+       "\n",
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+       "  padding-left: 0.5em;\n",
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+       "\n",
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+       "  color: var(--xr-font-color2);\n",
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+       "\n",
+       ".xr-section-summary-in + label:before {\n",
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+       "\n",
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+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
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+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
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+       "\n",
+       ".xr-var-dtype {\n",
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+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
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+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
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+       ".xr-attrs dt:hover {\n",
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+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
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+       "\n",
+       "dl.xr-attrs {\n",
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+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
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+       "  padding-right: 10px;\n",
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+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:              (gran_idx: 1, photon_idx: 211, spot: 2)\n",
+       "Coordinates:\n",
+       "  * gran_idx             (gran_idx) float64 5.54e+04\n",
+       "  * photon_idx           (photon_idx) int64 0 1 2 3 4 5 ... 206 207 208 209 210\n",
+       "  * spot                 (spot) uint8 1 2\n",
+       "    source_file          (gran_idx) &lt;U74 &#x27;./bosque_primavera_ATL08/processed_...\n",
+       "    delta_time           (photon_idx) datetime64[ns] 2019-05-04T12:47:13.5766...\n",
+       "Data variables:\n",
+       "    sc_orient            (gran_idx) int8 0\n",
+       "    cycle_number         (gran_idx) int8 3\n",
+       "    rgt                  (gran_idx, spot, photon_idx) float32 554.0 ... 554.0\n",
+       "    atlas_sdp_gps_epoch  (gran_idx) datetime64[ns] 2018-01-01T00:00:18\n",
+       "    data_start_utc       (gran_idx) datetime64[ns] 2019-05-04T12:46:31.876322\n",
+       "    data_end_utc         (gran_idx) datetime64[ns] 2019-05-04T12:48:54.200826\n",
+       "    latitude             (spot, gran_idx, photon_idx) float32 20.59 ... 20.73\n",
+       "    longitude            (spot, gran_idx, photon_idx) float32 -103.7 ... -103.7\n",
+       "    gt                   (gran_idx, spot) object &#x27;gt3l&#x27; &#x27;gt3r&#x27;\n",
+       "    h_canopy             (photon_idx) float32 12.12 4.747 11.83 ... nan nan nan\n",
+       "Attributes:\n",
+       "    data_product:  ATL08\n",
+       "    Description:   Contains data categorized as land at 100 meter intervals.\n",
+       "    data_rate:     Data are stored as aggregates of 100 meters.</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d1b6461a-0c9a-4ce8-8ad7-2e280618b6ea' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d1b6461a-0c9a-4ce8-8ad7-2e280618b6ea' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>gran_idx</span>: 1</li><li><span class='xr-has-index'>photon_idx</span>: 211</li><li><span class='xr-has-index'>spot</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-cbe50fe0-c127-4af1-a2e8-5a072e8a56c0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cbe50fe0-c127-4af1-a2e8-5a072e8a56c0' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>gran_idx</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.54e+04</div><input id='attrs-3a7e4163-637c-4efc-aeb5-9f86c1813126' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3a7e4163-637c-4efc-aeb5-9f86c1813126' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07596e09-7912-47f5-bd10-ad11aefbc1ef' class='xr-var-data-in' type='checkbox'><label for='data-07596e09-7912-47f5-bd10-ad11aefbc1ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([55402.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>photon_idx</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 206 207 208 209 210</div><input id='attrs-3e0759ae-cd38-4ec9-bd91-831903435d4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e0759ae-cd38-4ec9-bd91-831903435d4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8a8cbbf-cc4b-49dd-b4f6-f7f4bd619fd9' class='xr-var-data-in' type='checkbox'><label for='data-e8a8cbbf-cc4b-49dd-b4f6-f7f4bd619fd9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 208, 209, 210])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spot</span></div><div class='xr-var-dims'>(spot)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>1 2</div><input id='attrs-e6335c68-10e3-43a9-a171-cc87ad2f1585' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6335c68-10e3-43a9-a171-cc87ad2f1585' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a11bcf5a-ac22-4363-b535-80bea3c55c60' class='xr-var-data-in' type='checkbox'><label for='data-a11bcf5a-ac22-4363-b535-80bea3c55c60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_file</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>&lt;U74</div><div class='xr-var-preview xr-preview'>&#x27;./bosque_primavera_ATL08/proces...</div><input id='attrs-f91428ac-b128-424e-9c9a-0ed21ba014be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f91428ac-b128-424e-9c9a-0ed21ba014be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6999471-7560-433c-a6fe-94a280aee714' class='xr-var-data-in' type='checkbox'><label for='data-a6999471-7560-433c-a6fe-94a280aee714' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;./bosque_primavera_ATL08/processed_ATL08_20190504124152_05540301_006_02.h5&#x27;],\n",
+       "      dtype=&#x27;&lt;U74&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta_time</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:47:13.576668792 .....</div><input id='attrs-a96644f6-ae49-461d-9409-88da3ec843e5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a96644f6-ae49-461d-9409-88da3ec843e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec5cdcdf-c644-4c62-8da5-2cfd78c2e743' class='xr-var-data-in' type='checkbox'><label for='data-ec5cdcdf-c644-4c62-8da5-2cfd78c2e743' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:47:13.576668792&#x27;, &#x27;2019-05-04T12:47:13.590795176&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:13.604878696&#x27;, &#x27;2019-05-04T12:47:13.618858776&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:13.647116752&#x27;, &#x27;2019-05-04T12:47:13.731658440&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:13.788115696&#x27;, &#x27;2019-05-04T12:47:13.802188288&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.013615136&#x27;, &#x27;2019-05-04T12:47:14.027716720&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.041828320&#x27;, &#x27;2019-05-04T12:47:14.069985944&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.084116656&#x27;, &#x27;2019-05-04T12:47:14.098204416&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.112308544&#x27;, &#x27;2019-05-04T12:47:14.126439192&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.140474800&#x27;, &#x27;2019-05-04T12:47:14.154503088&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.168615944&#x27;, &#x27;2019-05-04T12:47:14.182727944&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.196803520&#x27;, &#x27;2019-05-04T12:47:14.225002096&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.239145008&#x27;, &#x27;2019-05-04T12:47:14.253240544&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.267282136&#x27;, &#x27;2019-05-04T12:47:14.281345400&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.295463616&#x27;, &#x27;2019-05-04T12:47:14.309582960&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.323643288&#x27;, &#x27;2019-05-04T12:47:14.337699200&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.351769576&#x27;, &#x27;2019-05-04T12:47:14.363045864&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.379987728&#x27;, &#x27;2019-05-04T12:47:14.394098040&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.408184296&#x27;, &#x27;2019-05-04T12:47:14.422336984&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.436399800&#x27;, &#x27;2019-05-04T12:47:14.450439312&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.464605056&#x27;, &#x27;2019-05-04T12:47:14.478736368&#x27;,\n",
+       "...\n",
+       "       &#x27;2019-05-04T12:47:15.425911016&#x27;, &#x27;2019-05-04T12:47:15.439995088&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.454061472&#x27;, &#x27;2019-05-04T12:47:15.468143592&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.482238848&#x27;, &#x27;2019-05-04T12:47:15.496324880&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.510409496&#x27;, &#x27;2019-05-04T12:47:15.524510280&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.538615648&#x27;, &#x27;2019-05-04T12:47:15.566816696&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.580919696&#x27;, &#x27;2019-05-04T12:47:15.594985688&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.609048944&#x27;, &#x27;2019-05-04T12:47:15.623173096&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.637281512&#x27;, &#x27;2019-05-04T12:47:15.651381832&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.665494736&#x27;, &#x27;2019-05-04T12:47:15.679564576&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.693640304&#x27;, &#x27;2019-05-04T12:47:15.707745176&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.721833264&#x27;, &#x27;2019-05-04T12:47:15.735931400&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.750026272&#x27;, &#x27;2019-05-04T12:47:15.764102288&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.778227184&#x27;, &#x27;2019-05-04T12:47:15.806428968&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.820523432&#x27;, &#x27;2019-05-04T12:47:15.834607024&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.848673504&#x27;, &#x27;2019-05-04T12:47:15.862757488&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.876856944&#x27;, &#x27;2019-05-04T12:47:15.890974768&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.905085432&#x27;, &#x27;2019-05-04T12:47:15.919119064&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.933193432&#x27;, &#x27;2019-05-04T12:47:15.947348696&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.961461904&#x27;, &#x27;2019-05-04T12:47:15.975561616&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.989663088&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f424906-f54c-4fde-9495-7014639dc333' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0f424906-f54c-4fde-9495-7014639dc333' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sc_orient</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-df1f4257-676f-4c33-91c3-260e35e3d730' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-df1f4257-676f-4c33-91c3-260e35e3d730' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c188cce-6a32-403e-b610-b94e3fcff4c9' class='xr-var-data-in' type='checkbox'><label for='data-1c188cce-6a32-403e-b610-b94e3fcff4c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cycle_number</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>3</div><input id='attrs-7cdc0af6-d6fd-4597-850e-6634582eea76' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7cdc0af6-d6fd-4597-850e-6634582eea76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a29506e1-b2c3-4dbb-ba27-6e1d62abf776' class='xr-var-data-in' type='checkbox'><label for='data-a29506e1-b2c3-4dbb-ba27-6e1d62abf776' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rgt</span></div><div class='xr-var-dims'>(gran_idx, spot, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>554.0 554.0 554.0 ... 554.0 554.0</div><input id='attrs-73eae40f-eafe-407f-840d-d2893f346e54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73eae40f-eafe-407f-840d-d2893f346e54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd0f701e-9510-458f-a826-5f58a5a3ade6' class='xr-var-data-in' type='checkbox'><label for='data-dd0f701e-9510-458f-a826-5f58a5a3ade6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>The reference ground track (RGT) is the track on the earth at which a specified unit vector within the observatory is pointed. Under nominal operating conditions, there will be no data collected along the RGT, as the RGT is spanned by GT3 and GT4.  During slews or off-pointing, it is possible that ground tracks may intersect the RGT. The ICESat-2 mission has 1387 RGTs.</dd><dt><span>long_name :</span></dt><dd>reference ground track</dd><dt><span>source :</span></dt><dd>Operations</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>1387</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "...\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554.]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>atlas_sdp_gps_epoch</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01T00:00:18</div><input id='attrs-11ea1c90-bd5d-4c0e-ac89-1876ba894ddf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-11ea1c90-bd5d-4c0e-ac89-1876ba894ddf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac201fb3-6366-4644-9a60-cbe1dad33039' class='xr-var-data-in' type='checkbox'><label for='data-ac201fb3-6366-4644-9a60-cbe1dad33039' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:18.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_start_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:46:31.876322</div><input id='attrs-db1a681d-8007-4ea6-8df8-6e5a86ee15a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db1a681d-8007-4ea6-8df8-6e5a86ee15a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8d4be77-b088-47b1-b459-c40e794b2727' class='xr-var-data-in' type='checkbox'><label for='data-b8d4be77-b088-47b1-b459-c40e794b2727' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:46:31.876322000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_end_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:48:54.200826</div><input id='attrs-e19e5be0-5689-488d-a195-d8471d49992c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e19e5be0-5689-488d-a195-d8471d49992c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04d60e55-ae5a-4c7f-8af0-55b9f9259d97' class='xr-var-data-in' type='checkbox'><label for='data-04d60e55-ae5a-4c7f-8af0-55b9f9259d97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:48:54.200826000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.59 20.59 20.59 ... 20.72 20.73</div><input id='attrs-749c1d12-74cc-4c89-9f24-ab553af3c414' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-749c1d12-74cc-4c89-9f24-ab553af3c414' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbf7465f-2b1e-4ac7-b9fc-305ff55386f4' class='xr-var-data-in' type='checkbox'><label for='data-bbf7465f-2b1e-4ac7-b9fc-305ff55386f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Latitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([[[20.592943, 20.593845, 20.594746, 20.595648, 20.59745 ,\n",
+       "         20.60286 , 20.606464, 20.607367, 20.620888, 20.621788,\n",
+       "         20.62269 , 20.624493, 20.625395, 20.626297, 20.627197,\n",
+       "         20.6281  , 20.629   , 20.629902, 20.630804, 20.631704,\n",
+       "         20.632607, 20.634409, 20.635311, 20.636211, 20.637114,\n",
+       "         20.638014, 20.638916, 20.639816, 20.640718, 20.64162 ,\n",
+       "         20.642523, 20.643244, 20.644325, 20.645226, 20.646128,\n",
+       "         20.64703 , 20.64793 , 20.648832, 20.649734, 20.650635,\n",
+       "         20.651537, 20.652437, 20.65334 , 20.65424 , 20.655142,\n",
+       "         20.656044, 20.656944, 20.657846, 20.658749, 20.659649,\n",
+       "         20.660551, 20.661451, 20.662354, 20.663254, 20.664156,\n",
+       "         20.665058, 20.665958, 20.66686 , 20.667763, 20.668663,\n",
+       "         20.669565, 20.670467, 20.671368, 20.67227 , 20.67317 ,\n",
+       "         20.674072, 20.674973, 20.675875, 20.676777, 20.677677,\n",
+       "         20.67858 , 20.679482, 20.680382, 20.681284, 20.682184,\n",
+       "         20.683086, 20.683989, 20.684889, 20.685791, 20.686691,\n",
+       "         20.687593, 20.688496, 20.689217, 20.690298, 20.691198,\n",
+       "         20.6921  , 20.693003, 20.693903, 20.694805, 20.695707,\n",
+       "         20.696608, 20.69751 , 20.69841 , 20.699312, 20.700212,\n",
+       "         20.701115, 20.702017, 20.702917, 20.70382 , 20.704721,\n",
+       "...\n",
+       "               nan,       nan,       nan,       nan,       nan,\n",
+       "         20.625654, 20.626554, 20.627457, 20.628359, 20.635569,\n",
+       "         20.63647 , 20.637373, 20.638273, 20.639175, 20.640078,\n",
+       "         20.640978, 20.644585, 20.646387, 20.647287, 20.64819 ,\n",
+       "         20.649992, 20.650894, 20.651796, 20.652697, 20.653599,\n",
+       "         20.655401, 20.656303, 20.657204, 20.658106, 20.659006,\n",
+       "         20.659908, 20.662613, 20.663513, 20.664415, 20.666218,\n",
+       "         20.66712 , 20.66802 , 20.668922, 20.669825, 20.670725,\n",
+       "         20.671627, 20.672527, 20.67343 , 20.674332, 20.675232,\n",
+       "         20.676134, 20.677036, 20.677937, 20.678839, 20.679739,\n",
+       "         20.680641, 20.681543, 20.682444, 20.68605 , 20.68695 ,\n",
+       "         20.687853, 20.688753, 20.689655, 20.690557, 20.691458,\n",
+       "         20.69236 , 20.693262, 20.694162, 20.695065, 20.695965,\n",
+       "         20.696867, 20.69867 , 20.699572, 20.700472, 20.701374,\n",
+       "         20.702274, 20.703176, 20.704079, 20.704979, 20.705881,\n",
+       "         20.706781, 20.707684, 20.708586, 20.709486, 20.710388,\n",
+       "         20.711288, 20.71219 , 20.713993, 20.714895, 20.715796,\n",
+       "         20.716698, 20.7176  , 20.7185  , 20.719402, 20.720304,\n",
+       "         20.721205, 20.722107, 20.723007, 20.72391 , 20.724812,\n",
+       "         20.725712]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-103.7 -103.7 ... -103.7 -103.7</div><input id='attrs-4ce0e933-3786-46d6-b3ec-f839a00f95f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ce0e933-3786-46d6-b3ec-f839a00f95f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b675e97-21da-4234-91b1-9a6baab74fd8' class='xr-var-data-in' type='checkbox'><label for='data-3b675e97-21da-4234-91b1-9a6baab74fd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Longitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([[[-103.67242 , -103.672516, -103.67261 , -103.6727  ,\n",
+       "         -103.6729  , -103.67346 , -103.673836, -103.673935,\n",
+       "         -103.67535 , -103.675446, -103.67554 , -103.67573 ,\n",
+       "         -103.67583 , -103.67592 , -103.67601 , -103.67611 ,\n",
+       "         -103.6762  , -103.6763  , -103.67639 , -103.67649 ,\n",
+       "         -103.67658 , -103.676765, -103.676865, -103.676956,\n",
+       "         -103.67705 , -103.67715 , -103.677246, -103.677345,\n",
+       "         -103.67743 , -103.67753 , -103.67762 , -103.6777  ,\n",
+       "         -103.67781 , -103.67791 , -103.678   , -103.678085,\n",
+       "         -103.678185, -103.67828 , -103.678375, -103.678474,\n",
+       "         -103.678566, -103.67866 , -103.67876 , -103.678856,\n",
+       "         -103.67895 , -103.67904 , -103.67913 , -103.67922 ,\n",
+       "         -103.67932 , -103.67941 , -103.679504, -103.6796  ,\n",
+       "         -103.6797  , -103.6798  , -103.67989 , -103.679985,\n",
+       "         -103.68008 , -103.680176, -103.68027 , -103.68037 ,\n",
+       "         -103.68046 , -103.68055 , -103.68064 , -103.68073 ,\n",
+       "         -103.68083 , -103.68093 , -103.68103 , -103.68112 ,\n",
+       "         -103.68121 , -103.681305, -103.6814  , -103.68149 ,\n",
+       "         -103.68159 , -103.68169 , -103.681786, -103.68188 ,\n",
+       "         -103.68197 , -103.68207 , -103.68216 , -103.68226 ,\n",
+       "...\n",
+       "         -103.67717 , -103.67727 , -103.67736 , -103.67754 ,\n",
+       "         -103.67764 , -103.677734, -103.67783 , -103.677925,\n",
+       "         -103.678116, -103.67821 , -103.67831 , -103.6784  ,\n",
+       "         -103.6785  , -103.67859 , -103.67887 , -103.67897 ,\n",
+       "         -103.67906 , -103.67925 , -103.679344, -103.67944 ,\n",
+       "         -103.679535, -103.67963 , -103.67972 , -103.67982 ,\n",
+       "         -103.67991 , -103.68001 , -103.6801  , -103.68019 ,\n",
+       "         -103.68029 , -103.68038 , -103.68047 , -103.68057 ,\n",
+       "         -103.68067 , -103.68076 , -103.680855, -103.680954,\n",
+       "         -103.68133 , -103.68143 , -103.68152 , -103.68161 ,\n",
+       "         -103.68171 , -103.6818  , -103.68189 , -103.681984,\n",
+       "         -103.68208 , -103.68218 , -103.682274, -103.682365,\n",
+       "         -103.682465, -103.682655, -103.682755, -103.682846,\n",
+       "         -103.68294 , -103.68304 , -103.68313 , -103.68322 ,\n",
+       "         -103.68332 , -103.68341 , -103.68351 , -103.6836  ,\n",
+       "         -103.68369 , -103.68379 , -103.68388 , -103.68398 ,\n",
+       "         -103.684074, -103.684265, -103.68436 , -103.684456,\n",
+       "         -103.68455 , -103.68465 , -103.68474 , -103.68483 ,\n",
+       "         -103.68493 , -103.68502 , -103.68511 , -103.68521 ,\n",
+       "         -103.6853  , -103.6854  , -103.68549 ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gt</span></div><div class='xr-var-dims'>(gran_idx, spot)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;gt3l&#x27; &#x27;gt3r&#x27;</div><input id='attrs-1a0f3f75-3070-4a81-abe6-ac7e60356c6d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a0f3f75-3070-4a81-abe6-ac7e60356c6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-488e4c41-132f-425f-9287-4f5b884faca9' class='xr-var-data-in' type='checkbox'><label for='data-488e4c41-132f-425f-9287-4f5b884faca9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;gt3l&#x27;, &#x27;gt3r&#x27;]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_canopy</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.12 4.747 11.83 ... nan nan nan</div><input id='attrs-1b2b4e27-855f-447c-80ad-df560a16cb3d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b2b4e27-855f-447c-80ad-df560a16cb3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c4c8918-4b68-4909-8b00-9021b0ca7ef8' class='xr-var-data-in' type='checkbox'><label for='data-7c4c8918-4b68-4909-8b00-9021b0ca7ef8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>98% height of all the individual canopy relative heights for the segment above the estimated terrain surface. Relative canopy heights have been computed by differencing the canopy photon height from the estimated terrain surface.</dd><dt><span>long_name :</span></dt><dd>height canopy</dd><dt><span>source :</span></dt><dd>Land ATBD section 4.12</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([12.117554 ,  4.7471924, 11.826294 , 12.599121 ,        nan,\n",
+       "       18.487427 ,        nan, 24.531128 , 23.573975 ,  6.973877 ,\n",
+       "       15.614014 , 18.686768 , 10.208862 , 19.486816 , 19.792969 ,\n",
+       "       24.182617 , 26.141113 ,        nan, 27.215698 , 27.964355 ,\n",
+       "       28.768066 , 23.500977 , 20.939087 , 12.468384 , 12.3302   ,\n",
+       "       12.56543  , 18.28833  ,        nan,  3.2608643, 15.973389 ,\n",
+       "       20.57251  , 16.383667 , 19.53479  , 19.167236 ,  8.956299 ,\n",
+       "       10.339844 ,  6.9119873,        nan,  6.6381836, 13.006592 ,\n",
+       "       10.125366 ,  7.1741943,  6.220581 , 13.171265 , 13.741211 ,\n",
+       "       14.266846 , 13.998291 ,  6.2819824, 10.767212 ,        nan,\n",
+       "       11.753906 , 19.83789  ,  8.949463 ,  6.9605713, 17.22107  ,\n",
+       "       20.040527 ,  8.8289795, 10.093262 ,  6.963379 , 10.654053 ,\n",
+       "       13.63623  ,  8.8897705,        nan,  8.487671 ,  4.117676 ,\n",
+       "        2.7399902,  5.741211 ,  9.786987 ,  5.447876 ,  6.3466797,\n",
+       "        2.6264648,        nan,        nan, 14.463623 , 19.986572 ,\n",
+       "       26.920166 , 23.636475 , 20.366577 , 23.44165  , 18.091675 ,\n",
+       "       12.490723 , 21.749268 , 10.508667 , 18.734863 , 16.601318 ,\n",
+       "        7.385254 ,        nan,        nan,  9.800293 ,  5.3067627,\n",
+       "       12.211426 , 15.874878 ,  8.875732 , 15.800903 , 12.877563 ,\n",
+       "              nan,        nan,  2.3807373,  6.1132812,        nan,\n",
+       "...\n",
+       "              nan,  5.647461 ,  8.42688  ,        nan,        nan,\n",
+       "       28.482422 , 41.51538  , 36.190186 , 44.303833 , 54.733765 ,\n",
+       "       48.05542  , 30.716309 ,        nan, 23.340576 , 38.804565 ,\n",
+       "       44.656982 , 30.472778 , 22.952637 , 12.519897 , 16.93335  ,\n",
+       "       30.526001 , 30.635742 , 20.736328 , 29.40503  , 11.497925 ,\n",
+       "       20.793457 , 15.886963 , 18.502075 , 12.783813 ,        nan,\n",
+       "              nan, 16.045044 , 12.643677 , 13.928345 , 10.867432 ,\n",
+       "        9.350586 ,  8.6102295, 20.031738 , 20.65039  ,  9.560913 ,\n",
+       "       14.163574 , 16.621704 ,        nan,        nan,        nan,\n",
+       "       10.887817 , 12.17334  , 11.110474 , 11.06665  , 10.12915  ,\n",
+       "       11.172485 , 10.751099 ,  3.20813  , 16.136719 , 16.071533 ,\n",
+       "       16.224487 , 18.876953 , 30.146606 , 22.111328 ,        nan,\n",
+       "              nan,        nan,        nan, 12.220581 , 14.92688  ,\n",
+       "              nan, 13.107788 ,  7.1689453,  7.2957764,        nan,\n",
+       "              nan,        nan,        nan,        nan,  9.05249  ,\n",
+       "              nan,        nan,        nan,        nan,        nan,\n",
+       "              nan,        nan,        nan,        nan,        nan,\n",
+       "              nan,        nan,        nan,        nan,        nan,\n",
+       "              nan,        nan,        nan,        nan,        nan,\n",
+       "              nan], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6cbc8ff6-5bdd-49d4-85ae-d5f0dc48b489' class='xr-section-summary-in' type='checkbox'  ><label for='section-6cbc8ff6-5bdd-49d4-85ae-d5f0dc48b489' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>gran_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-82639a85-888d-486f-8bf4-3b1e369f87b1' class='xr-index-data-in' type='checkbox'/><label for='index-82639a85-888d-486f-8bf4-3b1e369f87b1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([55402.0], dtype=&#x27;float64&#x27;, name=&#x27;gran_idx&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>photon_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ac7399d5-6c6c-4883-90a7-d33ada26fa51' class='xr-index-data-in' type='checkbox'/><label for='index-ac7399d5-6c6c-4883-90a7-d33ada26fa51' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
+       "            ...\n",
+       "            201, 202, 203, 204, 205, 206, 207, 208, 209, 210],\n",
+       "           dtype=&#x27;int64&#x27;, name=&#x27;photon_idx&#x27;, length=211))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spot</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9eae8a06-3857-491f-ab5a-1f630c35a7e8' class='xr-index-data-in' type='checkbox'/><label for='index-9eae8a06-3857-491f-ab5a-1f630c35a7e8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(UInt64Index([1, 2], dtype=&#x27;uint64&#x27;, name=&#x27;spot&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ea84d7ee-5f69-4484-8557-551c5e239939' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ea84d7ee-5f69-4484-8557-551c5e239939' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_product :</span></dt><dd>ATL08</dd><dt><span>Description :</span></dt><dd>Contains data categorized as land at 100 meter intervals.</dd><dt><span>data_rate :</span></dt><dd>Data are stored as aggregates of 100 meters.</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:              (gran_idx: 1, photon_idx: 211, spot: 2)\n",
+       "Coordinates:\n",
+       "  * gran_idx             (gran_idx) float64 5.54e+04\n",
+       "  * photon_idx           (photon_idx) int64 0 1 2 3 4 5 ... 206 207 208 209 210\n",
+       "  * spot                 (spot) uint8 1 2\n",
+       "    source_file          (gran_idx) <U74 './bosque_primavera_ATL08/processed_...\n",
+       "    delta_time           (photon_idx) datetime64[ns] 2019-05-04T12:47:13.5766...\n",
+       "Data variables:\n",
+       "    sc_orient            (gran_idx) int8 0\n",
+       "    cycle_number         (gran_idx) int8 3\n",
+       "    rgt                  (gran_idx, spot, photon_idx) float32 554.0 ... 554.0\n",
+       "    atlas_sdp_gps_epoch  (gran_idx) datetime64[ns] 2018-01-01T00:00:18\n",
+       "    data_start_utc       (gran_idx) datetime64[ns] 2019-05-04T12:46:31.876322\n",
+       "    data_end_utc         (gran_idx) datetime64[ns] 2019-05-04T12:48:54.200826\n",
+       "    latitude             (spot, gran_idx, photon_idx) float32 20.59 ... 20.73\n",
+       "    longitude            (spot, gran_idx, photon_idx) float32 -103.7 ... -103.7\n",
+       "    gt                   (gran_idx, spot) object 'gt3l' 'gt3r'\n",
+       "    h_canopy             (photon_idx) float32 12.12 4.747 11.83 ... nan nan nan\n",
+       "Attributes:\n",
+       "    data_product:  ATL08\n",
+       "    Description:   Contains data categorized as land at 100 meter intervals.\n",
+       "    data_rate:     Data are stored as aggregates of 100 meters."
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# turn off warnings for load to not show an xarray warning that was resolved in the coming release of icepyx v1.0.0\n",
+    "with warnings.catch_warnings(record=True):    \n",
+    "    ds = reader.load()\n",
+    "\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "24b5d69b-ab57-4094-bbcd-efa3dd9a1de7",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "Here we have an xarray Dataset, a common Python data structure for analysis. To visualize the data we can plot it using:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "d36197d5-1f11-44ab-8a4e-de611742e1bf",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7f2b0ac81390>"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds.plot.scatter(x=\"longitude\", y=\"latitude\", hue=\"h_canopy\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "953375b5-ca84-4093-b33f-9e6829408ab3",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "Notice also that the data is shown for just our area of interest! That is because of icepyx's subsetting feature. You can find more details on this feature in the icepyx example gallery [here](https://icepyx.readthedocs.io/en/latest/example_notebooks/IS2_data_access2-subsetting.html). "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c5aa30c2-69a6-4d1c-8bdd-2d095d7d1163",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "## When to Cloud\n",
+    "\n",
+    "The astute user has by now noticed that in this tutorial we downloaded a granule to read in rather than directly reading it from an S3 bucket. Recall from the previous tutorial that reading a single group was a time intensive step and did not include multiple groups. Due to the way ICESat-2 data is stored on disk (because of the file format - it doesn't matter if it's a local disk or cloud disk), accessing the data within the file is really slow via the virtual file system. Several efforts are under way to help address this issue, and icepyx will implement them as soon as they are available. Current efforts include:\n",
+    "- storing ICESat-2 data in a cloud-optimized format\n",
+    "- reading data using the [h5coro](https://github.com/ICESat2-SlideRule/h5coro) library\n",
+    "\n",
+    "Please let Amy, Jessica, or one of the workshop leads know if you're interested in joining any of these conversations (or telling us what issues you've encountered). We'd love to have your input and use case!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9d8c219e-39c8-4b79-b795-1ff417538dc6",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "## Some example plots\n",
+    "\n",
+    "To close, here are a few more examples of reading and visualizing ATL08 data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ef1d3998-8d29-4f6c-bec5-5a8a267d0e38",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "### Example 1: View the photon classifications"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "17a3c448-7872-4998-a6f9-9e80224ac500",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "You have 1 files matching the filename pattern to be read in.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Set up the data reader\n",
+    "pattern = \"processed_ATL{product:2}_{datetime:%Y%m%d%H%M%S}_{rgt:4}{cycle:2}{orbitsegment:2}_{version:3}_{revision:2}.h5\"\n",
+    "reader = ipx.Read('./bosque_primavera_ATL08', \"ATL08\", pattern)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "ecfa5b27-9d18-45c0-a220-16d359b43ef1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Add the photon height and classification variables\n",
+    "reader.vars.append(var_list=['ph_h', 'classed_pc_flag', 'latitude', 'longitude'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "47fc67bb-5eba-4481-8dae-bc7248d09c91",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:              (gran_idx: 1, photon_idx: 25234, spot: 2)\n",
+       "Coordinates:\n",
+       "  * gran_idx             (gran_idx) float64 5.54e+04\n",
+       "  * photon_idx           (photon_idx) int64 0 1 2 3 ... 25230 25231 25232 25233\n",
+       "  * spot                 (spot) uint8 1 2\n",
+       "    source_file          (gran_idx) &lt;U74 &#x27;./bosque_primavera_ATL08/processed_...\n",
+       "    delta_time           (photon_idx) datetime64[ns] 2019-05-04T12:47:13.5766...\n",
+       "Data variables:\n",
+       "    sc_orient            (gran_idx) int8 0\n",
+       "    cycle_number         (gran_idx) int8 3\n",
+       "    rgt                  (gran_idx, spot, photon_idx) float32 554.0 ... nan\n",
+       "    atlas_sdp_gps_epoch  (gran_idx) datetime64[ns] 2018-01-01T00:00:18\n",
+       "    data_start_utc       (gran_idx) datetime64[ns] 2019-05-04T12:46:31.876322\n",
+       "    data_end_utc         (gran_idx) datetime64[ns] 2019-05-04T12:48:54.200826\n",
+       "    latitude             (spot, gran_idx, photon_idx) float32 20.59 ... nan\n",
+       "    longitude            (spot, gran_idx, photon_idx) float32 -103.7 ... nan\n",
+       "    gt                   (gran_idx, spot) &lt;U4 &#x27;gt3l&#x27; &#x27;gt3r&#x27;\n",
+       "    ph_h                 (spot, gran_idx, photon_idx) float32 nan ... 0.05542\n",
+       "    classed_pc_flag      (spot, gran_idx, photon_idx) float32 nan nan ... 1.0\n",
+       "Attributes:\n",
+       "    data_product:  ATL08</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3c158e7f-8099-4e8d-8713-dd8ce8eb6e38' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3c158e7f-8099-4e8d-8713-dd8ce8eb6e38' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>gran_idx</span>: 1</li><li><span class='xr-has-index'>photon_idx</span>: 25234</li><li><span class='xr-has-index'>spot</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e2201564-de81-483e-8f77-a40f90ff5386' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e2201564-de81-483e-8f77-a40f90ff5386' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>gran_idx</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.54e+04</div><input id='attrs-5786abc6-c256-45b8-beaf-f599263e56e2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5786abc6-c256-45b8-beaf-f599263e56e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4e36c04-bc35-4e34-9859-33b5e97e32aa' class='xr-var-data-in' type='checkbox'><label for='data-a4e36c04-bc35-4e34-9859-33b5e97e32aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([55402.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>photon_idx</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 25230 25231 25232 25233</div><input id='attrs-56d7551a-390c-425c-bd11-b3faad06a517' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56d7551a-390c-425c-bd11-b3faad06a517' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d047584-c11e-45d2-95ab-2bf980d38143' class='xr-var-data-in' type='checkbox'><label for='data-5d047584-c11e-45d2-95ab-2bf980d38143' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([    0,     1,     2, ..., 25231, 25232, 25233])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spot</span></div><div class='xr-var-dims'>(spot)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>1 2</div><input id='attrs-b5d2455f-30a1-42a2-9614-13df0cb6b110' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b5d2455f-30a1-42a2-9614-13df0cb6b110' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a74837e-c225-44f5-a78b-8376511c8597' class='xr-var-data-in' type='checkbox'><label for='data-3a74837e-c225-44f5-a78b-8376511c8597' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_file</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>&lt;U74</div><div class='xr-var-preview xr-preview'>&#x27;./bosque_primavera_ATL08/proces...</div><input id='attrs-5f2eedc1-4d07-463d-8d4a-1d43f671ecaf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f2eedc1-4d07-463d-8d4a-1d43f671ecaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d64f1d8-1e04-4459-b223-97110f841975' class='xr-var-data-in' type='checkbox'><label for='data-1d64f1d8-1e04-4459-b223-97110f841975' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;./bosque_primavera_ATL08/processed_ATL08_20190504124152_05540301_006_02.h5&#x27;],\n",
+       "      dtype=&#x27;&lt;U74&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta_time</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:47:13.576668792 .....</div><input id='attrs-c57f6d87-fac8-456a-8167-b46fc764cbe1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c57f6d87-fac8-456a-8167-b46fc764cbe1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b43c71bd-2186-4aa0-91aa-c7471aba6609' class='xr-var-data-in' type='checkbox'><label for='data-b43c71bd-2186-4aa0-91aa-c7471aba6609' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:47:13.576668792&#x27;, &#x27;2019-05-04T12:47:13.590795176&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:13.604878696&#x27;, ...,\n",
+       "       &#x27;2019-05-04T12:47:15.995923304&#x27;, &#x27;2019-05-04T12:47:15.996123296&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.996323304&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7083f307-17c6-4a5f-b0d7-e70680c30754' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7083f307-17c6-4a5f-b0d7-e70680c30754' class='xr-section-summary' >Data variables: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sc_orient</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-cf57ccd9-68f4-42f2-a8a5-27b28791aab0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf57ccd9-68f4-42f2-a8a5-27b28791aab0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb03ca80-89ba-47b7-9b05-68af71ad640e' class='xr-var-data-in' type='checkbox'><label for='data-eb03ca80-89ba-47b7-9b05-68af71ad640e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cycle_number</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>3</div><input id='attrs-2885be38-0c22-465c-8d0b-64d3a2e79c4b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2885be38-0c22-465c-8d0b-64d3a2e79c4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-235f47e7-4c49-472e-9af2-31f472de8e09' class='xr-var-data-in' type='checkbox'><label for='data-235f47e7-4c49-472e-9af2-31f472de8e09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rgt</span></div><div class='xr-var-dims'>(gran_idx, spot, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>554.0 554.0 554.0 ... nan nan nan</div><input id='attrs-4f14ba52-7351-4b74-b844-54ae9bbb6166' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f14ba52-7351-4b74-b844-54ae9bbb6166' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70c9fed7-e2f6-4ab2-8329-104d0beca9c0' class='xr-var-data-in' type='checkbox'><label for='data-70c9fed7-e2f6-4ab2-8329-104d0beca9c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>The reference ground track (RGT) is the track on the earth at which a specified unit vector within the observatory is pointed. Under nominal operating conditions, there will be no data collected along the RGT, as the RGT is spanned by GT3 and GT4.  During slews or off-pointing, it is possible that ground tracks may intersect the RGT. The ICESat-2 mission has 1387 RGTs.</dd><dt><span>long_name :</span></dt><dd>reference ground track</dd><dt><span>source :</span></dt><dd>Operations</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>1387</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[554., 554., 554., ...,  nan,  nan,  nan],\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>atlas_sdp_gps_epoch</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01T00:00:18</div><input id='attrs-40112329-ed61-4513-9ad2-850d1278675c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-40112329-ed61-4513-9ad2-850d1278675c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f20dbbf9-f887-4704-b8f6-4a3c6a1fd111' class='xr-var-data-in' type='checkbox'><label for='data-f20dbbf9-f887-4704-b8f6-4a3c6a1fd111' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:18.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_start_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:46:31.876322</div><input id='attrs-17ddd9c1-44bb-4f87-a0a6-a188a234c5e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-17ddd9c1-44bb-4f87-a0a6-a188a234c5e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89e9f2e1-0ccb-4e68-97ba-c3d6b8c502f9' class='xr-var-data-in' type='checkbox'><label for='data-89e9f2e1-0ccb-4e68-97ba-c3d6b8c502f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:46:31.876322000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_end_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:48:54.200826</div><input id='attrs-24e8d2b4-c949-4e2e-a2bc-a74430259b5e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24e8d2b4-c949-4e2e-a2bc-a74430259b5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92b3e576-033b-4829-bbcb-f5e1c66f9173' class='xr-var-data-in' type='checkbox'><label for='data-92b3e576-033b-4829-bbcb-f5e1c66f9173' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:48:54.200826000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.59 20.59 20.59 ... nan nan nan</div><input id='attrs-602f4d3f-0574-441c-8c75-8d24508fb896' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-602f4d3f-0574-441c-8c75-8d24508fb896' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1954e42c-3e3a-4642-8d6d-14dce801128f' class='xr-var-data-in' type='checkbox'><label for='data-1954e42c-3e3a-4642-8d6d-14dce801128f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Latitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([[[20.592943, 20.593845, 20.594746, ...,       nan,       nan,\n",
+       "               nan]],\n",
+       "\n",
+       "       [[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-103.7 -103.7 -103.7 ... nan nan</div><input id='attrs-26a00f50-65ed-41e5-b740-a899a1986712' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26a00f50-65ed-41e5-b740-a899a1986712' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-629b504b-5ba0-469c-9d79-aec5e477ba4e' class='xr-var-data-in' type='checkbox'><label for='data-629b504b-5ba0-469c-9d79-aec5e477ba4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Longitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([[[-103.67242 , -103.672516, -103.67261 , ...,         nan,\n",
+       "                 nan,         nan]],\n",
+       "\n",
+       "       [[        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gt</span></div><div class='xr-var-dims'>(gran_idx, spot)</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;gt3l&#x27; &#x27;gt3r&#x27;</div><input id='attrs-9bf38c40-a7f7-461c-bd16-5958c9edfbd8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9bf38c40-a7f7-461c-bd16-5958c9edfbd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c6e8a18-343a-4ea9-9d7c-2f58f9f8a3f1' class='xr-var-data-in' type='checkbox'><label for='data-4c6e8a18-343a-4ea9-9d7c-2f58f9f8a3f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;gt3l&#x27;, &#x27;gt3r&#x27;]], dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ph_h</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan ... 0.05103 0.05542</div><input id='attrs-cb9dd55e-bf6e-40d0-8f48-6d6212fbcf1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb9dd55e-bf6e-40d0-8f48-6d6212fbcf1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d61fafc6-abae-439d-9078-566b7e6fec7c' class='xr-var-data-in' type='checkbox'><label for='data-d61fafc6-abae-439d-9078-566b7e6fec7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Height of photons above interpolated land surface</dd><dt><span>long_name :</span></dt><dd>relative photon height</dd><dt><span>source :</span></dt><dd>land/veg ATBD, 15May2020, Section 2.3.4</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([[[       nan,        nan,        nan, ...,        nan,\n",
+       "                nan,        nan]],\n",
+       "\n",
+       "       [[       nan,        nan,        nan, ..., 0.15209961,\n",
+       "         0.05102539, 0.05541992]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>classed_pc_flag</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 1.0 1.0 1.0 1.0</div><input id='attrs-21223354-0689-4d53-b6d7-2c037286f09b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21223354-0689-4d53-b6d7-2c037286f09b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-722e17bd-f360-4968-9d5e-74f3b42d314c' class='xr-var-data-in' type='checkbox'><label for='data-722e17bd-f360-4968-9d5e-74f3b42d314c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Land Vegetation ATBD classification flag for each photon as either noise, ground, canopy, and top of canopy. 0 = noise,  1 = ground, 2 = canopy, or 3 = top of canopy.</dd><dt><span>flag_meanings :</span></dt><dd>noise ground canopy top_of_canopy</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3]</dd><dt><span>long_name :</span></dt><dd>photon land atbd classification</dd><dt><span>source :</span></dt><dd>Land ATBD section 4.10</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan]],\n",
+       "\n",
+       "       [[nan, nan, nan, ...,  1.,  1.,  1.]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cad7f491-88d6-44bc-8aa5-3922b91d6e12' class='xr-section-summary-in' type='checkbox'  ><label for='section-cad7f491-88d6-44bc-8aa5-3922b91d6e12' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>gran_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-67c16473-3569-4a5f-a6fc-7fbb20622316' class='xr-index-data-in' type='checkbox'/><label for='index-67c16473-3569-4a5f-a6fc-7fbb20622316' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([55402.0], dtype=&#x27;float64&#x27;, name=&#x27;gran_idx&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>photon_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a9b09626-5141-4860-8f33-ddd218d3f29c' class='xr-index-data-in' type='checkbox'/><label for='index-a9b09626-5141-4860-8f33-ddd218d3f29c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([    0,     1,     2,     3,     4,     5,     6,     7,     8,\n",
+       "                9,\n",
+       "            ...\n",
+       "            25224, 25225, 25226, 25227, 25228, 25229, 25230, 25231, 25232,\n",
+       "            25233],\n",
+       "           dtype=&#x27;int64&#x27;, name=&#x27;photon_idx&#x27;, length=25234))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spot</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f9297b74-c26d-45ef-959c-83095a2a2485' class='xr-index-data-in' type='checkbox'/><label for='index-f9297b74-c26d-45ef-959c-83095a2a2485' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(UInt64Index([1, 2], dtype=&#x27;uint64&#x27;, name=&#x27;spot&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-02a31ccc-07fc-433a-8f0f-b9c25b94dc32' class='xr-section-summary-in' type='checkbox'  checked><label for='section-02a31ccc-07fc-433a-8f0f-b9c25b94dc32' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_product :</span></dt><dd>ATL08</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:              (gran_idx: 1, photon_idx: 25234, spot: 2)\n",
+       "Coordinates:\n",
+       "  * gran_idx             (gran_idx) float64 5.54e+04\n",
+       "  * photon_idx           (photon_idx) int64 0 1 2 3 ... 25230 25231 25232 25233\n",
+       "  * spot                 (spot) uint8 1 2\n",
+       "    source_file          (gran_idx) <U74 './bosque_primavera_ATL08/processed_...\n",
+       "    delta_time           (photon_idx) datetime64[ns] 2019-05-04T12:47:13.5766...\n",
+       "Data variables:\n",
+       "    sc_orient            (gran_idx) int8 0\n",
+       "    cycle_number         (gran_idx) int8 3\n",
+       "    rgt                  (gran_idx, spot, photon_idx) float32 554.0 ... nan\n",
+       "    atlas_sdp_gps_epoch  (gran_idx) datetime64[ns] 2018-01-01T00:00:18\n",
+       "    data_start_utc       (gran_idx) datetime64[ns] 2019-05-04T12:46:31.876322\n",
+       "    data_end_utc         (gran_idx) datetime64[ns] 2019-05-04T12:48:54.200826\n",
+       "    latitude             (spot, gran_idx, photon_idx) float32 20.59 ... nan\n",
+       "    longitude            (spot, gran_idx, photon_idx) float32 -103.7 ... nan\n",
+       "    gt                   (gran_idx, spot) <U4 'gt3l' 'gt3r'\n",
+       "    ph_h                 (spot, gran_idx, photon_idx) float32 nan ... 0.05542\n",
+       "    classed_pc_flag      (spot, gran_idx, photon_idx) float32 nan nan ... 1.0\n",
+       "Attributes:\n",
+       "    data_product:  ATL08"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# turn off warnings for load to not show an xarray warning that was resolved in the coming release of icepyx v1.0.0\n",
+    "with warnings.catch_warnings(record=True):\n",
+    "    # load the dataset\n",
+    "    ds_photons = reader.load()\n",
+    "    \n",
+    "ds_photons"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "2c7006bf-dbf9-4070-8c91-673c97af8910",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Select just one beam\n",
+    "gt1l = ds_photons.sel(spot=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "2e6412ed-242f-4b63-bcc7-19c6dec899e4",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7f2b0a8ff040>"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# A less complex plot\n",
+    "fig, ax = plt.subplots()\n",
+    "fig.set_size_inches(15, 4)\n",
+    "    \n",
+    "gt1l.plot.scatter(ax=ax, x='delta_time', y='ph_h', hue='classed_pc_flag')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "c0571f04-2c2c-44a0-a041-a4a178b4008d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Height above the ground (m)')"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1700x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# A plot with more customization\n",
+    "fig, ax = plt.subplots()\n",
+    "fig.set_size_inches(17, 6)\n",
+    "fig.suptitle('Classification of input photons', size=16)\n",
+    "\n",
+    "labels={0: 'noise', 1: 'ground', 2: 'canopy', 3: 'top of canopy'}\n",
+    "colors={0: 'grey', 1: 'orange', 2: 'brown', 3: 'purple'}\n",
+    "\n",
+    "for g in np.unique(gt1l.classed_pc_flag[0]):\n",
+    "    if not math.isnan(g):\n",
+    "        ds_group = gt1l.where(gt1l.classed_pc_flag == g, drop=True)\n",
+    "        ax.scatter(x=ds_group.delta_time, y=ds_group.ph_h, c=colors[g], \n",
+    "                   label=labels[g], s=8)\n",
+    "ax.legend()\n",
+    "\n",
+    "ax.set_ylabel('Height above the ground (m)', size=12)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c0f2ce93-ac2d-4cb2-9b30-16707ce1ef25",
+   "metadata": {
+    "user_expressions": []
+   },
+   "source": [
+    "### Plot the canopy compared to the ground height"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "2fa8d69a-3f70-4e50-9fdf-979aaaff3db3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Remove our previous variables\n",
+    "reader.vars.remove(all=True)\n",
+    "# Add the next set of variables to the list\n",
+    "reader.vars.append(var_list=['h_te_best_fit', 'latitude', 'longitude'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "25272b20-5b03-4213-af06-1d73799fab70",
+   "metadata": {},
+   "outputs": [
+    {
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+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:              (gran_idx: 1, photon_idx: 211, spot: 2)\n",
+       "Coordinates:\n",
+       "  * gran_idx             (gran_idx) float64 5.54e+04\n",
+       "  * photon_idx           (photon_idx) int64 0 1 2 3 4 5 ... 206 207 208 209 210\n",
+       "  * spot                 (spot) uint8 1 2\n",
+       "    source_file          (gran_idx) &lt;U74 &#x27;./bosque_primavera_ATL08/processed_...\n",
+       "    delta_time           (photon_idx) datetime64[ns] 2019-05-04T12:47:13.5766...\n",
+       "Data variables:\n",
+       "    sc_orient            (gran_idx) int8 0\n",
+       "    cycle_number         (gran_idx) int8 3\n",
+       "    rgt                  (gran_idx, spot, photon_idx) float32 554.0 ... 554.0\n",
+       "    atlas_sdp_gps_epoch  (gran_idx) datetime64[ns] 2018-01-01T00:00:18\n",
+       "    data_start_utc       (gran_idx) datetime64[ns] 2019-05-04T12:46:31.876322\n",
+       "    data_end_utc         (gran_idx) datetime64[ns] 2019-05-04T12:48:54.200826\n",
+       "    latitude             (spot, gran_idx, photon_idx) float32 20.59 ... 20.73\n",
+       "    longitude            (spot, gran_idx, photon_idx) float32 -103.7 ... -103.7\n",
+       "    gt                   (gran_idx, spot) object &#x27;gt3l&#x27; &#x27;gt3r&#x27;\n",
+       "    h_te_best_fit        (photon_idx) float32 1.342e+03 1.34e+03 ... 1.381e+03\n",
+       "Attributes:\n",
+       "    data_product:  ATL08\n",
+       "    Description:   Contains data categorized as land at 100 meter intervals.\n",
+       "    data_rate:     Data are stored as aggregates of 100 meters.</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-34f600c0-2bd6-48ae-95b9-045f8f2183bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-34f600c0-2bd6-48ae-95b9-045f8f2183bc' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>gran_idx</span>: 1</li><li><span class='xr-has-index'>photon_idx</span>: 211</li><li><span class='xr-has-index'>spot</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-68081ec5-fdf4-4e5d-b634-03f22343cd77' class='xr-section-summary-in' type='checkbox'  checked><label for='section-68081ec5-fdf4-4e5d-b634-03f22343cd77' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>gran_idx</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.54e+04</div><input id='attrs-2160c78c-f3ae-4b78-9343-1620ddf6b18e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2160c78c-f3ae-4b78-9343-1620ddf6b18e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6de02ff6-132a-402f-beeb-74758395ff4e' class='xr-var-data-in' type='checkbox'><label for='data-6de02ff6-132a-402f-beeb-74758395ff4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([55402.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>photon_idx</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 206 207 208 209 210</div><input id='attrs-0b1564db-cb00-4daa-b070-cc8e295fefcf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0b1564db-cb00-4daa-b070-cc8e295fefcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1441108b-89d6-4723-a1f3-6bdebd20b363' class='xr-var-data-in' type='checkbox'><label for='data-1441108b-89d6-4723-a1f3-6bdebd20b363' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 208, 209, 210])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spot</span></div><div class='xr-var-dims'>(spot)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>1 2</div><input id='attrs-4bdd2b31-04e0-420e-87e8-b65fed7e12d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4bdd2b31-04e0-420e-87e8-b65fed7e12d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4fef6dc-9c54-4acf-bbfd-20a960a4a897' class='xr-var-data-in' type='checkbox'><label for='data-d4fef6dc-9c54-4acf-bbfd-20a960a4a897' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_file</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>&lt;U74</div><div class='xr-var-preview xr-preview'>&#x27;./bosque_primavera_ATL08/proces...</div><input id='attrs-86d84dc5-0861-4bb1-a4e5-9abd20379778' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86d84dc5-0861-4bb1-a4e5-9abd20379778' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba28c75b-3a90-46e2-801e-f5c4c7eaf955' class='xr-var-data-in' type='checkbox'><label for='data-ba28c75b-3a90-46e2-801e-f5c4c7eaf955' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;./bosque_primavera_ATL08/processed_ATL08_20190504124152_05540301_006_02.h5&#x27;],\n",
+       "      dtype=&#x27;&lt;U74&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta_time</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:47:13.576668792 .....</div><input id='attrs-2e11c09c-558d-47cc-80b1-b4aac51a68f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2e11c09c-558d-47cc-80b1-b4aac51a68f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d334403-37fc-4ee2-98f9-3ad2aedd694c' class='xr-var-data-in' type='checkbox'><label for='data-6d334403-37fc-4ee2-98f9-3ad2aedd694c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:47:13.576668792&#x27;, &#x27;2019-05-04T12:47:13.590795176&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:13.604878696&#x27;, &#x27;2019-05-04T12:47:13.618858776&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:13.647116752&#x27;, &#x27;2019-05-04T12:47:13.731658440&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:13.788115696&#x27;, &#x27;2019-05-04T12:47:13.802188288&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.013615136&#x27;, &#x27;2019-05-04T12:47:14.027716720&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.041828320&#x27;, &#x27;2019-05-04T12:47:14.069985944&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.084116656&#x27;, &#x27;2019-05-04T12:47:14.098204416&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.112308544&#x27;, &#x27;2019-05-04T12:47:14.126439192&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.140474800&#x27;, &#x27;2019-05-04T12:47:14.154503088&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.168615944&#x27;, &#x27;2019-05-04T12:47:14.182727944&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.196803520&#x27;, &#x27;2019-05-04T12:47:14.225002096&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.239145008&#x27;, &#x27;2019-05-04T12:47:14.253240544&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.267282136&#x27;, &#x27;2019-05-04T12:47:14.281345400&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.295463616&#x27;, &#x27;2019-05-04T12:47:14.309582960&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.323643288&#x27;, &#x27;2019-05-04T12:47:14.337699200&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.351769576&#x27;, &#x27;2019-05-04T12:47:14.363045864&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.379987728&#x27;, &#x27;2019-05-04T12:47:14.394098040&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.408184296&#x27;, &#x27;2019-05-04T12:47:14.422336984&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.436399800&#x27;, &#x27;2019-05-04T12:47:14.450439312&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:14.464605056&#x27;, &#x27;2019-05-04T12:47:14.478736368&#x27;,\n",
+       "...\n",
+       "       &#x27;2019-05-04T12:47:15.425911016&#x27;, &#x27;2019-05-04T12:47:15.439995088&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.454061472&#x27;, &#x27;2019-05-04T12:47:15.468143592&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.482238848&#x27;, &#x27;2019-05-04T12:47:15.496324880&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.510409496&#x27;, &#x27;2019-05-04T12:47:15.524510280&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.538615648&#x27;, &#x27;2019-05-04T12:47:15.566816696&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.580919696&#x27;, &#x27;2019-05-04T12:47:15.594985688&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.609048944&#x27;, &#x27;2019-05-04T12:47:15.623173096&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.637281512&#x27;, &#x27;2019-05-04T12:47:15.651381832&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.665494736&#x27;, &#x27;2019-05-04T12:47:15.679564576&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.693640304&#x27;, &#x27;2019-05-04T12:47:15.707745176&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.721833264&#x27;, &#x27;2019-05-04T12:47:15.735931400&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.750026272&#x27;, &#x27;2019-05-04T12:47:15.764102288&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.778227184&#x27;, &#x27;2019-05-04T12:47:15.806428968&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.820523432&#x27;, &#x27;2019-05-04T12:47:15.834607024&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.848673504&#x27;, &#x27;2019-05-04T12:47:15.862757488&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.876856944&#x27;, &#x27;2019-05-04T12:47:15.890974768&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.905085432&#x27;, &#x27;2019-05-04T12:47:15.919119064&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.933193432&#x27;, &#x27;2019-05-04T12:47:15.947348696&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.961461904&#x27;, &#x27;2019-05-04T12:47:15.975561616&#x27;,\n",
+       "       &#x27;2019-05-04T12:47:15.989663088&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1967c4a6-d790-4eb6-aa94-4eeea370737a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1967c4a6-d790-4eb6-aa94-4eeea370737a' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sc_orient</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-8590e8a7-8bbc-4a1a-b731-b66c2cd5b088' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8590e8a7-8bbc-4a1a-b731-b66c2cd5b088' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-541979da-afec-472f-8690-3542325135fc' class='xr-var-data-in' type='checkbox'><label for='data-541979da-afec-472f-8690-3542325135fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cycle_number</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>3</div><input id='attrs-1d12e4f1-4f42-4d33-8665-309055d677f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d12e4f1-4f42-4d33-8665-309055d677f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8575c75d-1cf2-4981-962f-acc188ddf809' class='xr-var-data-in' type='checkbox'><label for='data-8575c75d-1cf2-4981-962f-acc188ddf809' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rgt</span></div><div class='xr-var-dims'>(gran_idx, spot, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>554.0 554.0 554.0 ... 554.0 554.0</div><input id='attrs-6ccbf657-316f-4195-9fb6-b48652f09f55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ccbf657-316f-4195-9fb6-b48652f09f55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b042f91c-fedf-43af-8d34-d8772c6f44f1' class='xr-var-data-in' type='checkbox'><label for='data-b042f91c-fedf-43af-8d34-d8772c6f44f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>The reference ground track (RGT) is the track on the earth at which a specified unit vector within the observatory is pointed. Under nominal operating conditions, there will be no data collected along the RGT, as the RGT is spanned by GT3 and GT4.  During slews or off-pointing, it is possible that ground tracks may intersect the RGT. The ICESat-2 mission has 1387 RGTs.</dd><dt><span>long_name :</span></dt><dd>reference ground track</dd><dt><span>source :</span></dt><dd>Operations</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>1387</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "...\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,\n",
+       "         554.]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>atlas_sdp_gps_epoch</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01T00:00:18</div><input id='attrs-5329027b-61e0-47c6-889f-189a6ba3ad2a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5329027b-61e0-47c6-889f-189a6ba3ad2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0562a92d-0f6c-4774-a1ab-94feb69e72e2' class='xr-var-data-in' type='checkbox'><label for='data-0562a92d-0f6c-4774-a1ab-94feb69e72e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:18.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_start_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:46:31.876322</div><input id='attrs-ec325ce0-cd2d-4256-911e-7200271b7e55' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec325ce0-cd2d-4256-911e-7200271b7e55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59f19872-2952-4f88-9261-2d2aa4490b02' class='xr-var-data-in' type='checkbox'><label for='data-59f19872-2952-4f88-9261-2d2aa4490b02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:46:31.876322000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_end_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:48:54.200826</div><input id='attrs-ce3d3ec9-abf8-40f5-8e66-a08602eda0ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ce3d3ec9-abf8-40f5-8e66-a08602eda0ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f245eeb2-9b3e-4315-92b8-0917e3cba2d1' class='xr-var-data-in' type='checkbox'><label for='data-f245eeb2-9b3e-4315-92b8-0917e3cba2d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:48:54.200826000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.59 20.59 20.59 ... 20.72 20.73</div><input id='attrs-7e11affa-64cd-425e-9046-a82ed18a3400' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e11affa-64cd-425e-9046-a82ed18a3400' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f4c32b3-9b07-4998-a4d7-7de0dcd3959c' class='xr-var-data-in' type='checkbox'><label for='data-7f4c32b3-9b07-4998-a4d7-7de0dcd3959c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Latitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([[[20.592943, 20.593845, 20.594746, 20.595648, 20.59745 ,\n",
+       "         20.60286 , 20.606464, 20.607367, 20.620888, 20.621788,\n",
+       "         20.62269 , 20.624493, 20.625395, 20.626297, 20.627197,\n",
+       "         20.6281  , 20.629   , 20.629902, 20.630804, 20.631704,\n",
+       "         20.632607, 20.634409, 20.635311, 20.636211, 20.637114,\n",
+       "         20.638014, 20.638916, 20.639816, 20.640718, 20.64162 ,\n",
+       "         20.642523, 20.643244, 20.644325, 20.645226, 20.646128,\n",
+       "         20.64703 , 20.64793 , 20.648832, 20.649734, 20.650635,\n",
+       "         20.651537, 20.652437, 20.65334 , 20.65424 , 20.655142,\n",
+       "         20.656044, 20.656944, 20.657846, 20.658749, 20.659649,\n",
+       "         20.660551, 20.661451, 20.662354, 20.663254, 20.664156,\n",
+       "         20.665058, 20.665958, 20.66686 , 20.667763, 20.668663,\n",
+       "         20.669565, 20.670467, 20.671368, 20.67227 , 20.67317 ,\n",
+       "         20.674072, 20.674973, 20.675875, 20.676777, 20.677677,\n",
+       "         20.67858 , 20.679482, 20.680382, 20.681284, 20.682184,\n",
+       "         20.683086, 20.683989, 20.684889, 20.685791, 20.686691,\n",
+       "         20.687593, 20.688496, 20.689217, 20.690298, 20.691198,\n",
+       "         20.6921  , 20.693003, 20.693903, 20.694805, 20.695707,\n",
+       "         20.696608, 20.69751 , 20.69841 , 20.699312, 20.700212,\n",
+       "         20.701115, 20.702017, 20.702917, 20.70382 , 20.704721,\n",
+       "...\n",
+       "               nan,       nan,       nan,       nan,       nan,\n",
+       "         20.625654, 20.626554, 20.627457, 20.628359, 20.635569,\n",
+       "         20.63647 , 20.637373, 20.638273, 20.639175, 20.640078,\n",
+       "         20.640978, 20.644585, 20.646387, 20.647287, 20.64819 ,\n",
+       "         20.649992, 20.650894, 20.651796, 20.652697, 20.653599,\n",
+       "         20.655401, 20.656303, 20.657204, 20.658106, 20.659006,\n",
+       "         20.659908, 20.662613, 20.663513, 20.664415, 20.666218,\n",
+       "         20.66712 , 20.66802 , 20.668922, 20.669825, 20.670725,\n",
+       "         20.671627, 20.672527, 20.67343 , 20.674332, 20.675232,\n",
+       "         20.676134, 20.677036, 20.677937, 20.678839, 20.679739,\n",
+       "         20.680641, 20.681543, 20.682444, 20.68605 , 20.68695 ,\n",
+       "         20.687853, 20.688753, 20.689655, 20.690557, 20.691458,\n",
+       "         20.69236 , 20.693262, 20.694162, 20.695065, 20.695965,\n",
+       "         20.696867, 20.69867 , 20.699572, 20.700472, 20.701374,\n",
+       "         20.702274, 20.703176, 20.704079, 20.704979, 20.705881,\n",
+       "         20.706781, 20.707684, 20.708586, 20.709486, 20.710388,\n",
+       "         20.711288, 20.71219 , 20.713993, 20.714895, 20.715796,\n",
+       "         20.716698, 20.7176  , 20.7185  , 20.719402, 20.720304,\n",
+       "         20.721205, 20.722107, 20.723007, 20.72391 , 20.724812,\n",
+       "         20.725712]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-103.7 -103.7 ... -103.7 -103.7</div><input id='attrs-5c142732-f740-48e4-9166-788d60e711bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c142732-f740-48e4-9166-788d60e711bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-778cd090-34f7-4499-b988-936f2d51ab32' class='xr-var-data-in' type='checkbox'><label for='data-778cd090-34f7-4499-b988-936f2d51ab32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Longitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([[[-103.67242 , -103.672516, -103.67261 , -103.6727  ,\n",
+       "         -103.6729  , -103.67346 , -103.673836, -103.673935,\n",
+       "         -103.67535 , -103.675446, -103.67554 , -103.67573 ,\n",
+       "         -103.67583 , -103.67592 , -103.67601 , -103.67611 ,\n",
+       "         -103.6762  , -103.6763  , -103.67639 , -103.67649 ,\n",
+       "         -103.67658 , -103.676765, -103.676865, -103.676956,\n",
+       "         -103.67705 , -103.67715 , -103.677246, -103.677345,\n",
+       "         -103.67743 , -103.67753 , -103.67762 , -103.6777  ,\n",
+       "         -103.67781 , -103.67791 , -103.678   , -103.678085,\n",
+       "         -103.678185, -103.67828 , -103.678375, -103.678474,\n",
+       "         -103.678566, -103.67866 , -103.67876 , -103.678856,\n",
+       "         -103.67895 , -103.67904 , -103.67913 , -103.67922 ,\n",
+       "         -103.67932 , -103.67941 , -103.679504, -103.6796  ,\n",
+       "         -103.6797  , -103.6798  , -103.67989 , -103.679985,\n",
+       "         -103.68008 , -103.680176, -103.68027 , -103.68037 ,\n",
+       "         -103.68046 , -103.68055 , -103.68064 , -103.68073 ,\n",
+       "         -103.68083 , -103.68093 , -103.68103 , -103.68112 ,\n",
+       "         -103.68121 , -103.681305, -103.6814  , -103.68149 ,\n",
+       "         -103.68159 , -103.68169 , -103.681786, -103.68188 ,\n",
+       "         -103.68197 , -103.68207 , -103.68216 , -103.68226 ,\n",
+       "...\n",
+       "         -103.67717 , -103.67727 , -103.67736 , -103.67754 ,\n",
+       "         -103.67764 , -103.677734, -103.67783 , -103.677925,\n",
+       "         -103.678116, -103.67821 , -103.67831 , -103.6784  ,\n",
+       "         -103.6785  , -103.67859 , -103.67887 , -103.67897 ,\n",
+       "         -103.67906 , -103.67925 , -103.679344, -103.67944 ,\n",
+       "         -103.679535, -103.67963 , -103.67972 , -103.67982 ,\n",
+       "         -103.67991 , -103.68001 , -103.6801  , -103.68019 ,\n",
+       "         -103.68029 , -103.68038 , -103.68047 , -103.68057 ,\n",
+       "         -103.68067 , -103.68076 , -103.680855, -103.680954,\n",
+       "         -103.68133 , -103.68143 , -103.68152 , -103.68161 ,\n",
+       "         -103.68171 , -103.6818  , -103.68189 , -103.681984,\n",
+       "         -103.68208 , -103.68218 , -103.682274, -103.682365,\n",
+       "         -103.682465, -103.682655, -103.682755, -103.682846,\n",
+       "         -103.68294 , -103.68304 , -103.68313 , -103.68322 ,\n",
+       "         -103.68332 , -103.68341 , -103.68351 , -103.6836  ,\n",
+       "         -103.68369 , -103.68379 , -103.68388 , -103.68398 ,\n",
+       "         -103.684074, -103.684265, -103.68436 , -103.684456,\n",
+       "         -103.68455 , -103.68465 , -103.68474 , -103.68483 ,\n",
+       "         -103.68493 , -103.68502 , -103.68511 , -103.68521 ,\n",
+       "         -103.6853  , -103.6854  , -103.68549 ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gt</span></div><div class='xr-var-dims'>(gran_idx, spot)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;gt3l&#x27; &#x27;gt3r&#x27;</div><input id='attrs-6898a21c-181a-477d-bab9-4ad99aae9cd8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6898a21c-181a-477d-bab9-4ad99aae9cd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ffa3bac-f38f-46c6-90e5-322eaf53475d' class='xr-var-data-in' type='checkbox'><label for='data-1ffa3bac-f38f-46c6-90e5-322eaf53475d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;gt3l&#x27;, &#x27;gt3r&#x27;]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_te_best_fit</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.342e+03 1.34e+03 ... 1.381e+03</div><input id='attrs-89bea8f5-3760-4679-b733-6df0119a0a45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89bea8f5-3760-4679-b733-6df0119a0a45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0600ef65-37f9-4be0-82ac-a3e0daaa7108' class='xr-var-data-in' type='checkbox'><label for='data-0600ef65-37f9-4be0-82ac-a3e0daaa7108' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>The best fit terrain elevation at the the mid-point location of each 100m segment. The mid-segment terrain elevation is determined by selecting the best of three fits- linear, 3rd order and 4th order polynomials - to the terrain photons and interpolating the elevation at the mid-point location of the 100 m segment. For the linear fit, a slope correction and weighting is applied to each ground photon based on the distance to the slope height at the center of the segment.</dd><dt><span>long_name :</span></dt><dd>segment terrain height best fit</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.1.15</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([1341.6261, 1339.7549, 1342.2279, 1352.5458, 1352.1498, 1369.6022,\n",
+       "       1341.8672, 1342.6127, 1379.6085, 1387.4363, 1378.2903, 1398.2286,\n",
+       "       1408.835 , 1412.2861, 1408.1262, 1402.0425, 1390.7015, 1377.3165,\n",
+       "       1374.2667, 1362.9102, 1351.8086, 1356.7529, 1372.503 , 1374.2352,\n",
+       "       1371.826 , 1372.7759, 1369.5962, 1379.0153, 1380.004 , 1369.1742,\n",
+       "       1331.0907, 1332.0349, 1337.1906, 1364.3312, 1369.7789, 1368.005 ,\n",
+       "       1380.9327, 1378.1477, 1378.0027, 1365.716 , 1341.7355, 1362.7502,\n",
+       "       1369.3937, 1365.5645, 1371.5692, 1360.3632, 1371.7815, 1378.1556,\n",
+       "       1374.7207, 1375.1332, 1374.8978, 1343.2148, 1374.0865, 1377.0504,\n",
+       "       1375.9967, 1348.3921, 1370.8029, 1371.5946, 1368.5741, 1366.4877,\n",
+       "       1349.1473, 1349.8328, 1351.8678, 1337.4954, 1348.1287, 1350.1534,\n",
+       "       1347.2864, 1344.1531, 1349.8016, 1356.35  , 1361.5197, 1362.969 ,\n",
+       "       1362.5942, 1352.9877, 1348.731 , 1345.9487, 1331.6982, 1345.9829,\n",
+       "       1347.6493, 1351.7913, 1358.8625, 1344.7389, 1355.0139, 1331.1632,\n",
+       "       1323.9978, 1325.0448, 1326.3163, 1326.6976, 1328.0988, 1332.0776,\n",
+       "       1341.5808, 1348.429 , 1365.6849, 1371.8914, 1377.0238, 1378.2782,\n",
+       "       1381.2715, 1382.6595, 1387.2151, 1388.956 , 1393.6167, 1394.5526,\n",
+       "       1394.6461, 1394.7386, 1394.2676, 1392.7904, 1391.0226, 1390.6882,\n",
+       "       1392.7502, 1390.3289, 1389.7281, 1389.8076, 1390.4437, 1391.2537,\n",
+       "       1391.2205, 1390.5575, 1385.5656, 1383.5444, 1381.2579, 1380.6188,\n",
+       "       1360.0029, 1368.5271, 1380.5599, 1378.5365, 1348.2975, 1361.3527,\n",
+       "       1368.1271, 1377.8864, 1378.9846, 1367.561 , 1357.905 , 1363.3611,\n",
+       "       1368.037 , 1369.7767, 1380.6696, 1352.8546, 1345.157 , 1343.4655,\n",
+       "       1357.3806, 1373.508 , 1369.7052, 1364.288 , 1370.0299, 1379.9648,\n",
+       "       1376.0862, 1377.4329, 1369.4843, 1376.7523, 1374.9471, 1374.8214,\n",
+       "       1372.7871, 1373.7095, 1364.68  , 1345.6294, 1347.3657, 1340.5127,\n",
+       "       1341.6628, 1349.958 , 1350.7115, 1348.8658, 1346.0786, 1351.665 ,\n",
+       "       1359.094 , 1366.7888, 1364.4694, 1363.6366, 1350.4138, 1367.0265,\n",
+       "       1359.8527, 1358.6835, 1358.3513, 1354.3091, 1348.4569, 1326.3341,\n",
+       "       1325.2039, 1325.5641, 1326.9438, 1326.9764, 1328.5076, 1335.6763,\n",
+       "       1338.7979, 1358.19  , 1373.2162, 1379.8351, 1379.533 , 1379.962 ,\n",
+       "       1383.1627, 1386.4252, 1390.6842, 1394.9309, 1394.6163, 1397.2983,\n",
+       "       1395.9186, 1394.3945, 1390.8865, 1391.3041, 1394.9935, 1390.8632,\n",
+       "       1390.6216, 1390.5719, 1390.7397, 1390.6544, 1389.8055, 1389.2607,\n",
+       "       1388.0011, 1382.5074, 1381.5883, 1380.8461, 1380.4548, 1380.2258,\n",
+       "       1380.7296], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d30c7fe-a6b7-4db8-ad95-422fcf46772b' class='xr-section-summary-in' type='checkbox'  ><label for='section-7d30c7fe-a6b7-4db8-ad95-422fcf46772b' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>gran_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1b069a76-18ca-4ab3-9430-05038d33a4c3' class='xr-index-data-in' type='checkbox'/><label for='index-1b069a76-18ca-4ab3-9430-05038d33a4c3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([55402.0], dtype=&#x27;float64&#x27;, name=&#x27;gran_idx&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>photon_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2788349a-332d-4e6a-954a-d98c8e3e74d3' class='xr-index-data-in' type='checkbox'/><label for='index-2788349a-332d-4e6a-954a-d98c8e3e74d3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
+       "            ...\n",
+       "            201, 202, 203, 204, 205, 206, 207, 208, 209, 210],\n",
+       "           dtype=&#x27;int64&#x27;, name=&#x27;photon_idx&#x27;, length=211))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spot</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-17556f4d-8a07-4b23-8123-1094637f0852' class='xr-index-data-in' type='checkbox'/><label for='index-17556f4d-8a07-4b23-8123-1094637f0852' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(UInt64Index([1, 2], dtype=&#x27;uint64&#x27;, name=&#x27;spot&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-30b24902-22ec-4e62-b6a1-e5558dca5607' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30b24902-22ec-4e62-b6a1-e5558dca5607' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_product :</span></dt><dd>ATL08</dd><dt><span>Description :</span></dt><dd>Contains data categorized as land at 100 meter intervals.</dd><dt><span>data_rate :</span></dt><dd>Data are stored as aggregates of 100 meters.</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:              (gran_idx: 1, photon_idx: 211, spot: 2)\n",
+       "Coordinates:\n",
+       "  * gran_idx             (gran_idx) float64 5.54e+04\n",
+       "  * photon_idx           (photon_idx) int64 0 1 2 3 4 5 ... 206 207 208 209 210\n",
+       "  * spot                 (spot) uint8 1 2\n",
+       "    source_file          (gran_idx) <U74 './bosque_primavera_ATL08/processed_...\n",
+       "    delta_time           (photon_idx) datetime64[ns] 2019-05-04T12:47:13.5766...\n",
+       "Data variables:\n",
+       "    sc_orient            (gran_idx) int8 0\n",
+       "    cycle_number         (gran_idx) int8 3\n",
+       "    rgt                  (gran_idx, spot, photon_idx) float32 554.0 ... 554.0\n",
+       "    atlas_sdp_gps_epoch  (gran_idx) datetime64[ns] 2018-01-01T00:00:18\n",
+       "    data_start_utc       (gran_idx) datetime64[ns] 2019-05-04T12:46:31.876322\n",
+       "    data_end_utc         (gran_idx) datetime64[ns] 2019-05-04T12:48:54.200826\n",
+       "    latitude             (spot, gran_idx, photon_idx) float32 20.59 ... 20.73\n",
+       "    longitude            (spot, gran_idx, photon_idx) float32 -103.7 ... -103.7\n",
+       "    gt                   (gran_idx, spot) object 'gt3l' 'gt3r'\n",
+       "    h_te_best_fit        (photon_idx) float32 1.342e+03 1.34e+03 ... 1.381e+03\n",
+       "Attributes:\n",
+       "    data_product:  ATL08\n",
+       "    Description:   Contains data categorized as land at 100 meter intervals.\n",
+       "    data_rate:     Data are stored as aggregates of 100 meters."
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# turn off warnings for load to not show an xarray warning that was resolved in the coming release of icepyx v1.0.0\n",
+    "with warnings.catch_warnings(record=True):\n",
+    "    # load the data\n",
+    "    ds_te = reader.load()\n",
+    "    \n",
+    "ds_te"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "1058b07e-af9b-4fe1-a230-f68e510f7afe",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7f2b087aada0>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "fig.set_size_inches(12, 3)\n",
+    "\n",
+    "# plot the canopy height above ground level\n",
+    "(ds.h_canopy + ds_te.h_te_best_fit).plot.scatter(ax=ax, x=\"delta_time\", y=\"h_canopy\") # orange\n",
+    "\n",
+    "# plot the terrain values\n",
+    "ds_te.plot.scatter(ax=ax, x=\"delta_time\", y=\"h_te_best_fit\") # blue"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a664ff4d-9154-41da-9706-64c01c6ce392",
+   "metadata": {
+    "tags": [],
+    "user_expressions": []
+   },
+   "source": [
+    "## Summary \n",
+    "\n",
+    "In this notebook we explored the opening and rendering ATL08 data with icepyx. We saw that icepyx will subset our downloaded data to our area of interest and also allows us to download only the variables we need. The ATL08 data has a folder-like structure with many variables to choose from. We focused on `h_canopy` and showed additional examples using the raw photons and `h_te_best_fit` for the ground height.\n",
+    "\n",
+    "More information about ATL08 or icepyx can be found in:\n",
+    "- The [icepyx documentation](https://icepyx.readthedocs.io/en/latest/)\n",
+    "- The [Algorithm Theoretical Basis Document (ATBD)](https://icesat-2.gsfc.nasa.gov/sites/default/files/page_files/ICESat2_ATL08_ATBD_r006.pdf)\n",
+    "- Neuenschwander et. al. 2019, Remote Sens. Env. [DOI](https://doi.org/10.1016/j.rse.2018.11.005)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "85f192b9-3b4b-4711-847c-6c9d553a828c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/content/Code_of_Conduct.html b/content/Code_of_Conduct.html
index 129ed74..b49bf6c 100644
--- a/content/Code_of_Conduct.html
+++ b/content/Code_of_Conduct.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/content/Getting_Started.html b/content/Getting_Started.html
index 0d9a56b..5678ab8 100644
--- a/content/Getting_Started.html
+++ b/content/Getting_Started.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/content/about.html b/content/about.html
index 15b504e..46d91e0 100644
--- a/content/about.html
+++ b/content/about.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/content/citing_cryocloud.html b/content/citing_cryocloud.html
index 8946e6e..08cad1c 100644
--- a/content/citing_cryocloud.html
+++ b/content/citing_cryocloud.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/content/hub_best_practices.html b/content/hub_best_practices.html
index ac8231d..0d02f63 100644
--- a/content/hub_best_practices.html
+++ b/content/hub_best_practices.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/content/mission.html b/content/mission.html
index 76dd96b..772d4d7 100644
--- a/content/mission.html
+++ b/content/mission.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/contributing/index.html b/contributing/index.html
index b41e995..5810c9e 100644
--- a/contributing/index.html
+++ b/contributing/index.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="current reference internal" href="#">
    Contributing
   </a>
-  <input checked="" class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input checked="" class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/contributing/workflow.html b/contributing/workflow.html
index afc5a0e..749b5bf 100644
--- a/contributing/workflow.html
+++ b/contributing/workflow.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="index.html">
    Contributing
   </a>
-  <input checked="" class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input checked="" class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/external/Earthdata_Cloud__Single_File_Direct_S3_Access_COG_Example.html b/external/Earthdata_Cloud__Single_File_Direct_S3_Access_COG_Example.html
index af39b70..d72916e 100644
--- a/external/Earthdata_Cloud__Single_File_Direct_S3_Access_COG_Example.html
+++ b/external/Earthdata_Cloud__Single_File_Direct_S3_Access_COG_Example.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/external/Earthdata_Cloud__Single_File__Direct_S3_Access_NetCDF4_Example.html b/external/Earthdata_Cloud__Single_File__Direct_S3_Access_NetCDF4_Example.html
index 78c05b1..c11b72e 100644
--- a/external/Earthdata_Cloud__Single_File__Direct_S3_Access_NetCDF4_Example.html
+++ b/external/Earthdata_Cloud__Single_File__Direct_S3_Access_NetCDF4_Example.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/external/Earthdata_Cloud__Single_File__HTTPS_Access_COG_Example.html b/external/Earthdata_Cloud__Single_File__HTTPS_Access_COG_Example.html
index e9083df..a1f6e9d 100644
--- a/external/Earthdata_Cloud__Single_File__HTTPS_Access_COG_Example.html
+++ b/external/Earthdata_Cloud__Single_File__HTTPS_Access_COG_Example.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/external/ICESAT2_ATL10-h5coro_large_scale_time_series.html b/external/ICESAT2_ATL10-h5coro_large_scale_time_series.html
index 0847da0..0c32363 100644
--- a/external/ICESAT2_ATL10-h5coro_large_scale_time_series.html
+++ b/external/ICESAT2_ATL10-h5coro_large_scale_time_series.html
@@ -332,10 +332,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -360,8 +387,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/external/ICESat2_Earthaccess.html b/external/ICESat2_Earthaccess.html
index 1d71075..ff1acc3 100644
--- a/external/ICESat2_Earthaccess.html
+++ b/external/ICESat2_Earthaccess.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/external/Multi-File_Direct_S3_Access_COG_Example.html b/external/Multi-File_Direct_S3_Access_COG_Example.html
index 4de1e51..82f8cc4 100644
--- a/external/Multi-File_Direct_S3_Access_COG_Example.html
+++ b/external/Multi-File_Direct_S3_Access_COG_Example.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/external/Multi-File_Direct_S3_Access_NetCDF_Example.html b/external/Multi-File_Direct_S3_Access_NetCDF_Example.html
index 42ee8cb..d34e748 100644
--- a/external/Multi-File_Direct_S3_Access_NetCDF_Example.html
+++ b/external/Multi-File_Direct_S3_Access_NetCDF_Example.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/genindex.html b/genindex.html
index 6a82e7f..e00e33d 100644
--- a/genindex.html
+++ b/genindex.html
@@ -327,10 +327,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -355,8 +382,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/background/earthdata.html b/how_tos/background/earthdata.html
index 2606dfd..a70f144 100644
--- a/how_tos/background/earthdata.html
+++ b/how_tos/background/earthdata.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/background/earthengine.html b/how_tos/background/earthengine.html
index 40c6a4d..0f37ad2 100644
--- a/how_tos/background/earthengine.html
+++ b/how_tos/background/earthengine.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/background/git.html b/how_tos/background/git.html
index a735810..744b1d8 100644
--- a/how_tos/background/git.html
+++ b/how_tos/background/git.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/background/github.html b/how_tos/background/github.html
index 44d3438..5821555 100644
--- a/how_tos/background/github.html
+++ b/how_tos/background/github.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/background/index.html b/how_tos/background/index.html
index 63f33d0..ccc05aa 100644
--- a/how_tos/background/index.html
+++ b/how_tos/background/index.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/background/jupyterhub.html b/how_tos/background/jupyterhub.html
index a03ffb1..115482f 100644
--- a/how_tos/background/jupyterhub.html
+++ b/how_tos/background/jupyterhub.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
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   </label>
diff --git a/how_tos/background/python.html b/how_tos/background/python.html
index c565cc1..a9d8765 100644
--- a/how_tos/background/python.html
+++ b/how_tos/background/python.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
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   </label>
diff --git a/how_tos/background/swc.html b/how_tos/background/swc.html
index f2a9489..1e92883 100644
--- a/how_tos/background/swc.html
+++ b/how_tos/background/swc.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/data_access/Cloud_Sentinel2_access.html b/how_tos/data_access/Cloud_Sentinel2_access.html
index 310f3bc..3431599 100644
--- a/how_tos/data_access/Cloud_Sentinel2_access.html
+++ b/how_tos/data_access/Cloud_Sentinel2_access.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/data_access/CryoCloudScratchBucket.html b/how_tos/data_access/CryoCloudScratchBucket.html
index 70489c7..9787046 100644
--- a/how_tos/data_access/CryoCloudScratchBucket.html
+++ b/how_tos/data_access/CryoCloudScratchBucket.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/data_access/Instructions_for_configuring_AWS_S3_bucket.html b/how_tos/data_access/Instructions_for_configuring_AWS_S3_bucket.html
index f7a43cc..4a0b415 100644
--- a/how_tos/data_access/Instructions_for_configuring_AWS_S3_bucket.html
+++ b/how_tos/data_access/Instructions_for_configuring_AWS_S3_bucket.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
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   </label>
diff --git a/how_tos/data_access/index.html b/how_tos/data_access/index.html
index bbf7ae8..e5e7d93 100644
--- a/how_tos/data_access/index.html
+++ b/how_tos/data_access/index.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/index.html b/how_tos/index.html
index 73f1251..932c58c 100644
--- a/how_tos/index.html
+++ b/how_tos/index.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/how_tos/nbdime/nbdime-hub.html b/how_tos/nbdime/nbdime-hub.html
index 4eea087..60bd747 100644
--- a/how_tos/nbdime/nbdime-hub.html
+++ b/how_tos/nbdime/nbdime-hub.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/intro.html b/intro.html
index 75412bd..9a4e88a 100644
--- a/intro.html
+++ b/intro.html
@@ -329,10 +329,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -357,8 +384,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/objects.inv b/objects.inv
index 416b127..8439fe8 100644
Binary files a/objects.inv and b/objects.inv differ
diff --git a/recorded/index.html b/recorded/index.html
index 988f224..aa67e4b 100644
--- a/recorded/index.html
+++ b/recorded/index.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/reference/IS2-resources.html b/reference/IS2-resources.html
index d368a7c..ad62e94 100644
--- a/reference/IS2-resources.html
+++ b/reference/IS2-resources.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/reference/glossary.html b/reference/glossary.html
index 0afb68c..84dd7b5 100644
--- a/reference/glossary.html
+++ b/reference/glossary.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/reference/open_science.html b/reference/open_science.html
index 7fce1ef..0e20772 100644
--- a/reference/open_science.html
+++ b/reference/open_science.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/reference/open_source_software.html b/reference/open_source_software.html
index 724c040..aeebf96 100644
--- a/reference/open_source_software.html
+++ b/reference/open_source_software.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../tutorials/GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/reference/questions.html b/reference/questions.html
index 64e927f..0694dad 100644
--- a/reference/questions.html
+++ b/reference/questions.html
@@ -329,10 +329,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../tutorials/ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../tutorials/NASA-Earthdata-Cloud-Access/4.icepyx.html">
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diff --git a/search.html b/search.html
index ea8c2c9..8a080a8 100644
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+     <li class="toctree-l3">
+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
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+      <a class="reference internal" href="tutorials/NASA-Earthdata-Cloud-Access/3.earthaccess.html">
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index ffabcf2..c2f2b73 100644
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Code of Conduct","Getting started","About","Citing CryoCloud","CryoCloud Best Practices","Mission","Contributing","Workflow for contributing to our JupyterBook (or any GitHub project)","COG Direct S3","NetCDF/HDF5 Direct S3","COG HTTPS","ICESat-2 ATL10-h5coro large-scale time series","Earthaccess","Multi-COG Direct S3","Multi-NetCDF/HDF5 Direct S3","Earthdata Login","Google Earth Engine Sign-Up","Git","GitHub","Background Work","JupyterHub","Python Installation and Environments","Software Carpentry Training","Sentinel 2 cloud access","Using CryoCloud S3 Scratch Bucket","Instructions for setting up an AWS S3 bucket for your project","Data access","How To\u2026","nbdime - version control for Jupyter notebooks","Welcome to CryoCloud!","Cloud Training","ICESat-2 Resources","Glossaries","Open Science","Open-source Software","How to Get Help","Analysis-ready, cloud-optimized data: writing zarr directories","Determining ice sheet change using Greenland Ice Mapping Project (GrIMP) 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Code of Conduct","Getting started","About","Citing CryoCloud","CryoCloud Best Practices","Mission","Contributing","Workflow for contributing to our JupyterBook (or any GitHub project)","COG Direct S3","NetCDF/HDF5 Direct S3","COG HTTPS","ICESat-2 ATL10-h5coro large-scale time series","Earthaccess","Multi-COG Direct S3","Multi-NetCDF/HDF5 Direct S3","Earthdata Login","Google Earth Engine Sign-Up","Git","GitHub","Background Work","JupyterHub","Python Installation and Environments","Software Carpentry Training","Sentinel 2 cloud access","Using CryoCloud S3 Scratch Bucket","Instructions for setting up an AWS S3 bucket for your project","Data access","How To\u2026","nbdime - version control for Jupyter notebooks","Welcome to CryoCloud!","Cloud Training","ICESat-2 Resources","Glossaries","Open Science","Open-source Software","How to Get Help","Analysis-ready, cloud-optimized data: writing zarr directories","Determining ice sheet change using Greenland Ice Mapping Project (GrIMP) tools","Using ICESat-2 ATL15 (Gridded Arctic Land Ice Height) to investigate ice-surface height anomalies","ICESat-2 and Landsat cloud access and data integration","Introduction to NASA Earthdata Cloud and ICESat-2","Using NASA Earthdata Search to Discover Cloud-Hosted Data","NASA Earthdata Cloud and data access using earthaccess and icepyx","NASA Earthdata Cloud and data access using earthaccess and icepyx","CryoCloud Tutorials: 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\ No newline at end of file
diff --git a/tutorials/ARCOdata_writingZarrs.html b/tutorials/ARCOdata_writingZarrs.html
index a91d906..7f71251 100644
--- a/tutorials/ARCOdata_writingZarrs.html
+++ b/tutorials/ARCOdata_writingZarrs.html
@@ -53,7 +53,7 @@
     <script async="async" src="../_static/sphinx-thebe.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
-    <link rel="next" title="Determining ice sheet change using Greenland Ice Mapping Project (GrIMP) tools" href="GrIMP/GrIMP_tutorial_AGU23.html" />
+    <link rel="next" title="Introduction to NASA Earthdata Cloud and ICESat-2" href="NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html" />
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@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2 current active">
+   <li class="toctree-l2 current active has-children">
     <a class="current reference internal" href="#">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input checked="" class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
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@@ -8874,6 +8901,8 @@ <h2>Take home messages<a class="headerlink" href="#take-home-messages" title="Pe
 <li><p>your workflow will need to result in uniform chink sizes within each dimension.</p></li>
 </ul>
 </section>
+<div class="toctree-wrapper compound">
+</div>
 </section>
 
     <script type="text/x-thebe-config">
@@ -8910,10 +8939,10 @@ <h2>Take home messages<a class="headerlink" href="#take-home-messages" title="Pe
             <p class="prev-next-title">ICESat-2 ATL10-h5coro large-scale time series</p>
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-    <a class='right-next' id="next-link" href="GrIMP/GrIMP_tutorial_AGU23.html" title="next page">
+    <a class='right-next' id="next-link" href="NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html" title="next page">
     <div class="prev-next-info">
         <p class="prev-next-subtitle">next</p>
-        <p class="prev-next-title">Determining ice sheet change using Greenland Ice Mapping Project (GrIMP) tools</p>
+        <p class="prev-next-title">Introduction to NASA Earthdata Cloud and ICESat-2</p>
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diff --git a/tutorials/GrIMP/GrIMP_tutorial_AGU23.html b/tutorials/GrIMP/GrIMP_tutorial_AGU23.html
index 0ffbb7d..77db974 100644
--- a/tutorials/GrIMP/GrIMP_tutorial_AGU23.html
+++ b/tutorials/GrIMP/GrIMP_tutorial_AGU23.html
@@ -54,7 +54,7 @@
     <link rel="index" title="Index" href="../../genindex.html" />
     <link rel="search" title="Search" href="../../search.html" />
     <link rel="next" title="CryoCloud Tutorials: SlideRule" href="../SlideRule_applications/SlideRule_applications.html" />
-    <link rel="prev" title="Analysis-ready, cloud-optimized data: writing zarr directories" href="../ARCOdata_writingZarrs.html" />
+    <link rel="prev" title="NASA Earthdata Cloud and data access using earthaccess and icepyx" href="../NASA-Earthdata-Cloud-Access/4.icepyx.html" />
     <meta name="viewport" content="width=device-width, initial-scale=1" />
     <meta name="docsearch:language" content="None">
     
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2 current active">
     <a class="current reference internal" href="#">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
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   </label>
@@ -5763,11 +5790,11 @@ <h2>Point Plots<a class="headerlink" href="#point-plots" title="Permalink to thi
                 
     <!-- Previous / next buttons -->
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-    <a class='left-prev' id="prev-link" href="../ARCOdata_writingZarrs.html" title="previous page">
+    <a class='left-prev' id="prev-link" href="../NASA-Earthdata-Cloud-Access/4.icepyx.html" title="previous page">
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             <p class="prev-next-subtitle">previous</p>
-            <p class="prev-next-title">Analysis-ready, cloud-optimized data: writing zarr directories</p>
+            <p class="prev-next-title">NASA Earthdata Cloud and data access using earthaccess and icepyx</p>
         </div>
     </a>
     <a class='right-next' id="next-link" href="../SlideRule_applications/SlideRule_applications.html" title="next page">
diff --git a/tutorials/IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.html b/tutorials/IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.html
index 1440886..b4746a0 100644
--- a/tutorials/IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.html
+++ b/tutorials/IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.html
@@ -332,10 +332,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../GrIMP/GrIMP_tutorial_AGU23.html">
@@ -360,8 +387,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
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   </label>
diff --git a/tutorials/IS2_cloud_Landsat_integration.html b/tutorials/IS2_cloud_Landsat_integration.html
index 8585645..cc9c69a 100644
--- a/tutorials/IS2_cloud_Landsat_integration.html
+++ b/tutorials/IS2_cloud_Landsat_integration.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html b/tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html
new file mode 100644
index 0000000..caae1f8
--- /dev/null
+++ b/tutorials/NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html
@@ -0,0 +1,1032 @@
+
+<!DOCTYPE html>
+
+<html>
+  <head>
+    <meta charset="utf-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+
+    <title>Introduction to NASA Earthdata Cloud and ICESat-2 &#8212; CryoCloud</title>
+    
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+            <li class="toctree-l1">
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+                    Welcome to CryoCloud!
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+            </li>
+        </ul>
+        <p aria-level="2" class="caption" role="heading">
+ <span class="caption-text">
+  Details
+ </span>
+</p>
+<ul class="nav bd-sidenav">
+ <li class="toctree-l1">
+  <a class="reference internal" href="../../content/about.html">
+   About
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+ </li>
+ <li class="toctree-l1">
+  <a class="reference internal" href="../../content/mission.html">
+   Mission
+  </a>
+ </li>
+ <li class="toctree-l1">
+  <a class="reference internal" href="../../content/Getting_Started.html">
+   Getting started
+  </a>
+ </li>
+ <li class="toctree-l1">
+  <a class="reference internal" href="../../content/hub_best_practices.html">
+   CryoCloud Best Practices
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+ <li class="toctree-l1">
+  <a class="reference internal" href="../../content/Code_of_Conduct.html">
+   CryoCloud Code of Conduct
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+ </li>
+ <li class="toctree-l1">
+  <a class="reference internal" href="../../content/citing_cryocloud.html">
+   Citing CryoCloud
+  </a>
+ </li>
+</ul>
+<p aria-level="2" class="caption" role="heading">
+ <span class="caption-text">
+  Cloud Training
+ </span>
+</p>
+<ul class="nav bd-sidenav">
+ <li class="toctree-l1">
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+   Cloud Training
+  </a>
+ </li>
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+<p aria-level="2" class="caption" role="heading">
+ <span class="caption-text">
+  How Tos
+ </span>
+</p>
+<ul class="nav bd-sidenav">
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+  <ul>
+   <li class="toctree-l2 has-children">
+    <a class="reference internal" href="../../how_tos/background/index.html">
+     Background Work
+    </a>
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+    <label for="toctree-checkbox-2">
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+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/background/github.html">
+       GitHub
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/background/jupyterhub.html">
+       JupyterHub
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+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/background/git.html">
+       Git
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/background/earthdata.html">
+       Earthdata Login
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/background/earthengine.html">
+       Google Earth Engine Sign-Up
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/background/swc.html">
+       Software Carpentry Training
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/background/python.html">
+       Python Installation and Environments
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/nbdime/nbdime-hub.html">
+       nbdime - version control for Jupyter notebooks
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toctree-l2 has-children">
+    <a class="reference internal" href="../../how_tos/data_access/index.html">
+     Data access
+    </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-3" name="toctree-checkbox-3" type="checkbox"/>
+    <label for="toctree-checkbox-3">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/data_access/Cloud_Sentinel2_access.html">
+       Sentinel 2 cloud access
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/data_access/Instructions_for_configuring_AWS_S3_bucket.html">
+       Instructions for setting up an AWS S3 bucket for your project
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/data_access/CryoCloudScratchBucket.html">
+       Using CryoCloud S3 Scratch Bucket
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/ICESat2_Earthaccess.html">
+       Earthaccess
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Earthdata_Cloud__Single_File__HTTPS_Access_COG_Example.html">
+       COG HTTPS
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Earthdata_Cloud__Single_File_Direct_S3_Access_COG_Example.html">
+       COG Direct S3
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Multi-File_Direct_S3_Access_COG_Example.html">
+       Multi-COG Direct S3
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Earthdata_Cloud__Single_File__Direct_S3_Access_NetCDF4_Example.html">
+       NetCDF/HDF5 Direct S3
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Multi-File_Direct_S3_Access_NetCDF_Example.html">
+       Multi-NetCDF/HDF5 Direct S3
+      </a>
+     </li>
+    </ul>
+   </li>
+  </ul>
+ </li>
+</ul>
+<p aria-level="2" class="caption" role="heading">
+ <span class="caption-text">
+  Tutorials
+ </span>
+</p>
+<ul class="current nav bd-sidenav">
+ <li class="toctree-l1 current active has-children">
+  <a class="reference internal" href="../index.html">
+   Tutorials
+  </a>
+  <input checked="" class="toctree-checkbox" id="toctree-checkbox-4" name="toctree-checkbox-4" type="checkbox"/>
+  <label for="toctree-checkbox-4">
+   <i class="fas fa-chevron-down">
+   </i>
+  </label>
+  <ul class="current">
+   <li class="toctree-l2">
+    <a class="reference internal" href="../IS2_cloud_Landsat_integration.html">
+     ICESat-2 and Landsat cloud access and data integration
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.html">
+     Using ICESat-2 ATL15 (Gridded Arctic Land Ice Height) to investigate ice-surface height anomalies
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../../external/ICESAT2_ATL10-h5coro_large_scale_time_series.html">
+     ICESat-2 ATL10-h5coro large-scale time series
+    </a>
+   </li>
+   <li class="toctree-l2 current active has-children">
+    <a class="reference internal" href="../ARCOdata_writingZarrs.html">
+     Analysis-ready, cloud-optimized data: writing zarr directories
+    </a>
+    <input checked="" class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul class="current">
+     <li class="toctree-l3 current active">
+      <a class="current reference internal" href="#">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../GrIMP/GrIMP_tutorial_AGU23.html">
+     Determining ice sheet change using Greenland Ice Mapping Project (GrIMP) tools
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../SlideRule_applications/SlideRule_applications.html">
+     CryoCloud Tutorials: SlideRule
+    </a>
+   </li>
+  </ul>
+ </li>
+</ul>
+<p aria-level="2" class="caption" role="heading">
+ <span class="caption-text">
+  Contributing
+ </span>
+</p>
+<ul class="nav bd-sidenav">
+ <li class="toctree-l1 has-children">
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+   <li class="toctree-l2">
+    <a class="reference internal" href="../../contributing/workflow.html">
+     Workflow for contributing to our JupyterBook (or any GitHub project)
+    </a>
+   </li>
+  </ul>
+ </li>
+</ul>
+<p aria-level="2" class="caption" role="heading">
+ <span class="caption-text">
+  Reference
+ </span>
+</p>
+<ul class="nav bd-sidenav">
+ <li class="toctree-l1">
+  <a class="reference internal" href="../../reference/glossary.html">
+   Glossaries
+  </a>
+ </li>
+ <li class="toctree-l1">
+  <a class="reference internal" href="../../reference/IS2-resources.html">
+   ICESat-2 Resources
+  </a>
+ </li>
+ <li class="toctree-l1">
+  <a class="reference internal" href="../../reference/open_science.html">
+   Open Science
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+   Open-source Software
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+        <i class="fas fa-list"></i> Contents
+    </div>
+    <nav id="bd-toc-nav" aria-label="Page">
+        <ul class="visible nav section-nav flex-column">
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#learning-outcomes">
+   Learning Outcomes
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#prerequisites">
+   Prerequisites
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#credits">
+   Credits
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#modes-of-data-access">
+   1. Modes of Data Access
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#nasa-earthdata-cloud">
+   2. NASA Earthdata Cloud
+  </a>
+  <ul class="nav section-nav flex-column">
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#earthdata-cloud-computing-basics">
+     Earthdata Cloud Computing Basics
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#cost-considerations">
+     Cost Considerations
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#when-to-cloud">
+     “When To Cloud”
+    </a>
+   </li>
+  </ul>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#introduction-to-icesat-2">
+   3. Introduction to ICESat-2
+  </a>
+  <ul class="nav section-nav flex-column">
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#data-collection">
+     Data Collection
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#counting-photons">
+     Counting Photons
+    </a>
+   </li>
+  </ul>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#navigating-icesat-2-tool-access-options">
+   4. Navigating ICESat-2 Tool &amp; Access options
+  </a>
+ </li>
+</ul>
+
+    </nav>
+</div>
+    </div>
+    <div class="article row">
+        <div class="col pl-md-3 pl-lg-5 content-container">
+            <!-- Table of contents that is only displayed when printing the page -->
+            <div id="jb-print-docs-body" class="onlyprint">
+                <h1>Introduction to NASA Earthdata Cloud and ICESat-2</h1>
+                <!-- Table of contents -->
+                <div id="print-main-content">
+                    <div id="jb-print-toc">
+                        
+                        <div>
+                            <h2> Contents </h2>
+                        </div>
+                        <nav aria-label="Page">
+                            <ul class="visible nav section-nav flex-column">
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#learning-outcomes">
+   Learning Outcomes
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#prerequisites">
+   Prerequisites
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#credits">
+   Credits
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#modes-of-data-access">
+   1. Modes of Data Access
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#nasa-earthdata-cloud">
+   2. NASA Earthdata Cloud
+  </a>
+  <ul class="nav section-nav flex-column">
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#earthdata-cloud-computing-basics">
+     Earthdata Cloud Computing Basics
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#cost-considerations">
+     Cost Considerations
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#when-to-cloud">
+     “When To Cloud”
+    </a>
+   </li>
+  </ul>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#introduction-to-icesat-2">
+   3. Introduction to ICESat-2
+  </a>
+  <ul class="nav section-nav flex-column">
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#data-collection">
+     Data Collection
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#counting-photons">
+     Counting Photons
+    </a>
+   </li>
+  </ul>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#navigating-icesat-2-tool-access-options">
+   4. Navigating ICESat-2 Tool &amp; Access options
+  </a>
+ </li>
+</ul>
+
+                        </nav>
+                    </div>
+                </div>
+            </div>
+            <main id="main-content" role="main">
+                
+              <div>
+                
+  <section class="tex2jax_ignore mathjax_ignore" id="introduction-to-nasa-earthdata-cloud-and-icesat-2">
+<h1>Introduction to NASA Earthdata Cloud and ICESat-2<a class="headerlink" href="#introduction-to-nasa-earthdata-cloud-and-icesat-2" title="Permalink to this headline">#</a></h1>
+<section id="learning-outcomes">
+<h2>Learning Outcomes<a class="headerlink" href="#learning-outcomes" title="Permalink to this headline">#</a></h2>
+<p>The purpose of this overview is to introduce the data search and access options provided within the Earthdata Cloud, along with an introduction to NASA’s ICESat-2 Mission.</p>
+</section>
+<section id="prerequisites">
+<h2>Prerequisites<a class="headerlink" href="#prerequisites" title="Permalink to this headline">#</a></h2>
+<p>None</p>
+</section>
+<section id="credits">
+<h2>Credits<a class="headerlink" href="#credits" title="Permalink to this headline">#</a></h2>
+<p>This guide was adapted from the following tutorials:</p>
+<ul class="simple">
+<li><p><a class="reference external" href="https://icesat-2-2023.hackweek.io/tutorials/data-access-and-format/overview.html">Data Discovery and Access: Overview</a> by Andy Barrett, NSIDC DAAC</p></li>
+<li><p><a class="reference external" href="https://nasa-openscapes.github.io/2023-ssc/tutorials/data-access/icepyx.html">Using icepyx to access ICESat-2 data</a> by Rachel Wegener, University of Maryland</p></li>
+<li><p><a class="reference external" href="https://nsidc.github.io/data_strategies_for_future_us/data_strategies_slides#/workflow-solutions-3">Data Strategies for Future Us</a> by Andy Barrett, NSIDC DAAC</p></li>
+<li><p><a class="reference external" href="https://nasa-openscapes.github.io/2023-ssc/tutorials/data-access/">Accessing and working with ICESat-2 data in the cloud</a> by Rachel Wegener, University of Maryland; Luis Lopez, NSIDC DAAC; and Amy Steiker, NSIDC DAAC.</p></li>
+</ul>
+</section>
+<section id="modes-of-data-access">
+<h2>1. Modes of Data Access<a class="headerlink" href="#modes-of-data-access" title="Permalink to this headline">#</a></h2>
+<p>In the past, most of our scientific data analysis workflows have started with searching for data and then downloading that data to a local machine; whether that is the hard drive of your laptop or workstation, or some shared storage device hosted by your institution or research group. This can be a time consuming process if the volume of data is large, even with fast internet. It also requires that you have sufficient disk-space and update your copy every time an updated version of the data is released. If you want to work with data from different geoscience domains, you may have to download data from several data centers.</p>
+<figure>
+<center>
+    <img src='images/shiklomanov-cloud-paradigm.png' alt='Earthdata Cloud Transition. Credit: Alexey Shiklomanov, NASA ESDIS'/>
+</center>
+</figure>
+<p>Figure credit: Alexey Shiklomanov, NASA ESDIS Project Scientist, from <a class="reference external" href="https://docs.google.com/presentation/d/12mh_8WU9lsrPviBO_MBv2blbjRufXoQmqCB4XGyxQ90/edit?pli=1">The future of NASA Earth Science in the commercial cloud:
+Challenges and opportunities</a></p>
+<p>However, a change is a-foot. New modes of data access are becoming available. Driven by the growth in the volume of data from future satellite missions, the archiving and distribution of NASA data is in a <a class="reference external" href="https://www.earthdata.nasa.gov/eosdis/cloud-evolution">state of transition</a>. Over the next few years, all NASA data will be migrated to the NASA Earthdata Cloud, a cloud-hosted data store that will have all NASA datasets in one place. This not only offers new modes of accessing NASA data but also offers new ways of working with this data. As with Google Docs or Sheets, data in these “files” is not just stored in the cloud but compute resources offered by cloud providers allow you to process and analyze the data in the cloud. When you edit your Google Doc or Sheet, you are working in the cloud, not on your computer. All you need is a web browser; you can work with these files on your laptop, tablet or even your phone. If you choose to share these documents with others, they can actively collaborate with you on the same document also in the cloud. For large geoscience datasets, this means you can <em>skip the download</em> and take your <em>analysis to the data</em>.</p>
+</section>
+<section id="nasa-earthdata-cloud">
+<h2>2. NASA Earthdata Cloud<a class="headerlink" href="#nasa-earthdata-cloud" title="Permalink to this headline">#</a></h2>
+<p>NASA’s cloud-hosted storage is known as the Earthdata Cloud; all NASA datasets are being migrated to be available in the cloud. During this transition period, data will still remain freely available for download directly from the DAACs (Distributed Active Archive Centers), which have archived and distributed NASA data for over 20 years.</p>
+<figure>
+<center>
+    <img src='images/NSIDC-DAAC.png' alt='NSIDC DAAC Intro'/>
+</center>
+</figure>
+<p>The NSIDC DAAC now offers all <a class="reference external" href="https://nsidc.org/data/icesat-2">ICESat-2</a> and <a class="reference external" href="https://nsidc.org/data/icesat">ICESat/GLAS</a> data products via Earthdata Cloud. A listing of all NSIDC DAAC cloud-hosted data can be found <a class="reference external" href="https://nsidc.org/data/earthdata-cloud/data">here</a>. More details on ICESat-2 below.</p>
+<section id="earthdata-cloud-computing-basics">
+<h3>Earthdata Cloud Computing Basics<a class="headerlink" href="#earthdata-cloud-computing-basics" title="Permalink to this headline">#</a></h3>
+<p>“The Cloud” is a somewhat nebulous term (pun intended). In general, the cloud is a network of remote servers that run software and services that are accessed over the internet.  There is a growing number of commercial cloud providers (Google Cloud Services, Amazon Web Services, Microsoft Azure). NASA has contracted with Amazon Web Services (AWS) to host data using the AWS Simple Storage Service (S3). AWS offers a large number of services in addition to S3 storage. A key service is Amazon Elastic Compute Cloud (Amazon EC2). This is the service that is <em>under-the-hood</em> of the CryoCloud JupyterHub you are using during today’s workshop.  When you start a JupyterHub, an EC2 <em>instance</em> is started.  You can think of an EC2 <em>instance</em> as a remote computer.</p>
+<p>AWS has the concept of a region, which is a cluster of data centers. These data centers house the servers that run S3 and EC2 instances. NASA Earthdata Cloud is hosted in the <code class="docutils literal notranslate"><span class="pre">us-west-2</span></code> region. This is important because if your EC2 instance is in the same region as the Earthdata Cloud S3 storage, you can access data in S3 directly in a way that is analogous to accessing a file on your laptop’s or workstation’s hard drive. This is one of the key advantages of working in the cloud; you can do analysis where the data is stored without having to download or move the data to another machine.</p>
+</section>
+<section id="cost-considerations">
+<h3>Cost Considerations<a class="headerlink" href="#cost-considerations" title="Permalink to this headline">#</a></h3>
+<p>The notion of <em>analysis in place</em>, or the concept of bringing your compute, or processing, to the data, provides several advantages over the more traditional download method: You no longer need to move data from its archived location, and you only pay for the compute needed to do your analysis. A few key points about cost:</p>
+<ul class="simple">
+<li><p>Cost to access: As long as you are performing your processing in the same location (region) as where the data are located in Earthdata Cloud, then the cost to access the data is completely free. CryoCloud is running in the same <code class="docutils literal notranslate"><span class="pre">us-west-2</span></code> region as where the NASA Earthdata Cloud data are stored.</p></li>
+<li><p>Cost to compute: Just like your laptop costs money up front that provides you with certain CPU and memory, the compute resources needed to run your analyses do cost money. This can be thought of as the difference between an upfront cost like purchasing a laptop to process data locally versus something you can pay for as you go. There is a cost associated with the EC2 instance mentioned above, paid for by CryoCloud.</p></li>
+<li><p>Cost to store: With <em>analysis in place</em>, the data are being streamed directly from its native location in the cloud, so storage is not needed. However you may wish to store analysis outputs or other data using your own S3 bucket, which does incur a cost.</p></li>
+</ul>
+</section>
+<section id="when-to-cloud">
+<h3>“When To Cloud”<a class="headerlink" href="#when-to-cloud" title="Permalink to this headline">#</a></h3>
+<p>Migrating to a cloud-based data analysis workflow can often have a steep learning curve and feel overwhelming. There are times when the cloud is effective and times when the download model may still be more appropriate. Here are a few key questions to ask yourself:</p>
+<ul class="simple">
+<li><p>What is the data volume?</p></li>
+<li><p>How long will it take to download?</p></li>
+<li><p>Can you store all that data (cost and space)?</p></li>
+<li><p>Do you have the computing power for processing?</p></li>
+<li><p>Does your team need a common computing environment?</p></li>
+<li><p>Do you need to share data at each step or just an end product?</p></li>
+</ul>
+</section>
+</section>
+<section id="introduction-to-icesat-2">
+<h2>3. Introduction to ICESat-2<a class="headerlink" href="#introduction-to-icesat-2" title="Permalink to this headline">#</a></h2>
+<p><img alt="IS2" src="https://icesat-2.gsfc.nasa.gov/sites/default/files/MissionLogo_0.png" /></p>
+<p>ICESat-2 carries a satellite lidar instrument, ATLAS. Lidar is an active remote sensing technique in which pulses of light are emitted and the return time is used to measure distance, in this case the height of something on the earth’s surface. The available ICESat-2 data products range from sea ice freeboard to land elevation to cloud backscatter characteristics. A list of available products can be found <a class="reference external" href="https://icesat-2.gsfc.nasa.gov/science/data-products">here</a>.</p>
+<p><img alt="IS2-Product-Tree" src="https://nsidc.org/sites/default/files/styles/article_image/public/images/Other/icesat2_graphic_2023_update_final.png.webp" /></p>
+<p>More key features of ICESat-2:</p>
+<ul class="simple">
+<li><p>Height determined using round-trip travel time of laser light (photon counting lidar)</p></li>
+<li><p>10,000 laser pulses released per second, split into 3 weak/strong beam pairs at a wavelength of 532 nanometers (bright green on the visible spectrum).</p></li>
+<li><p>Measurements taken every 70 cm along the satellite’s ground track, roughly 11 m wide footprint.</p></li>
+<li><p>The number of photons that return to the telescope depends on surface reflectivity and cloud cover (which obscures ATLAS’s view of Earth). As such, the spatial resolution of signal photons varies.</p></li>
+</ul>
+<section id="data-collection">
+<h3>Data Collection<a class="headerlink" href="#data-collection" title="Permalink to this headline">#</a></h3>
+<p>ICESat-2 measures data along 3 strong/weak beam pairs, resulting in 3 strong beams and 3 weak beams. The strong and weak beams are calibrated such that the weak beams have more sensitivity to viewing very bright surfaces (Ex. ice), while the strong beams are able to view surfaces with lower reflectances (Ex. water). The beams are designated in each data product as <code class="docutils literal notranslate"><span class="pre">gt1l</span></code>, <code class="docutils literal notranslate"><span class="pre">gt1r</span></code>, <code class="docutils literal notranslate"><span class="pre">gt2l</span></code>, <code class="docutils literal notranslate"><span class="pre">gt2r</span></code>, <code class="docutils literal notranslate"><span class="pre">gt3l</span></code>, and <code class="docutils literal notranslate"><span class="pre">gt3r</span></code>, where <code class="docutils literal notranslate"><span class="pre">gt</span></code> stands for “ground track”, the number refers to the photon emitter, and the <code class="docutils literal notranslate"><span class="pre">l</span></code> and <code class="docutils literal notranslate"><span class="pre">r</span></code> indicate “left” or “right” beam of the pair. Which of these designations is strong or weak depends on the orientation of the satellite (forwards, <code class="docutils literal notranslate"><span class="pre">sc_orient==1</span></code>; backwards, <code class="docutils literal notranslate"><span class="pre">sc_orient==0</span></code>). A helpful table of which beams are strong/weak can be found on p131 of the <a class="reference external" href="https://icesat-2.gsfc.nasa.gov/sites/default/files/page_files/ICESat2_ATL03_ATBD_r006.pdf">ATL03 Algorithm Theoretical Basis Document</a>. The ATLAS spot number (values 1-6) is based on the ground track designation (<code class="docutils literal notranslate"><span class="pre">gt1l</span></code> etc.) and spacecraft orientation and, once determined, can be used to consistently identify strong (Spots 1, 3, and 5) and weak (Spots 2, 4, and 6) beams.</p>
+<p><img alt="Tracks" src="https://ars.els-cdn.com/content/image/1-s2.0-S0034425718305066-gr1.jpg" /></p>
+<p>Photo: Neuenschwander et. al. 2019, Remote Sens. Env. <a class="reference external" href="https://doi.org/10.1016/j.rse.2018.11.005">DOI</a></p>
+</section>
+<section id="counting-photons">
+<h3>Counting Photons<a class="headerlink" href="#counting-photons" title="Permalink to this headline">#</a></h3>
+<p>The ICESat-2 lidar collects at the single photon level, different from most commercial lidar systems. A lot of additional photons get returned as solar background noise, and removing these unwanted photons is a key part of the algorithms that produce the higher level data products.</p>
+<blockquote>
+<div><p><em>Fig. 2. Results from signal finding methods for simulated ATLAS data. Black points show raw point cloud data as ingested from ATL03 product. Blue points overlaid in each plot show which photons each method identified as signal. Top panel reflects the signal photons as identified on the ATL03 data product (medium and high confidence signal photons). Bottom panel reflects the signal photons identified from the ATL08 DRAGANN method.</em> (Neuenschwander &amp; Pitts, 2019)</p>
+</div></blockquote>
+<p>Photo: Neuenschwander et. al. 2019, Remote Sens. Env. <a class="reference external" href="https://doi.org/10.1016/j.rse.2018.11.005">DOI</a></p>
+<p>To aggregate all these photons into more manegable chunks, many of the Level-3B products such as <a class="reference external" href="https://nsidc.org/data/atl08">ATL08</a> consolidate the photons into variable segment lengths.</p>
+</section>
+</section>
+<section id="navigating-icesat-2-tool-access-options">
+<h2>4. Navigating ICESat-2 Tool &amp; Access options<a class="headerlink" href="#navigating-icesat-2-tool-access-options" title="Permalink to this headline">#</a></h2>
+<p>There are many options across NASA Earthdata when it comes to search, access, visualization, and customization tools. The <a class="reference external" href="https://nasa-openscapes.github.io/earthdata-cloud-cookbook/cheatsheets.html#tools-services-roadmap">Tools &amp; Services Roadmap</a> cheatsheet as part of the NASA Openscapes Cookbook presents a high level view of some of these pathways.</p>
+<p>We will be highlighting a few tool and access options specifically for ICESat-2 today. This table provides an overview of the capabilities supported by <code class="docutils literal notranslate"><span class="pre">icepyx</span></code>, <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code>, and SlideRule Earth. These open-source tools have been co-evolving through ongoing collaboration across our cryospheric open source software community.</p>
+<table class="colwidths-auto table" id="data-access-overview-table">
+<caption><span class="caption-number">Table 1 </span><span class="caption-text">Data Access Method and Tools</span><a class="headerlink" href="#data-access-overview-table" title="Permalink to this table">#</a></caption>
+<thead>
+<tr class="row-odd"><th class="head"><p></p></th>
+<th class="head"><p><code class="docutils literal notranslate"><span class="pre">icepyx</span></code></p></th>
+<th class="head"><p><code class="docutils literal notranslate"><span class="pre">earthaccess</span></code></p></th>
+<th class="head"><p>NASA Earthdata Search</p></th>
+<th class="head"><p>SlideRule Earth</p></th>
+</tr>
+</thead>
+<tbody>
+<tr class="row-even"><td><p>Filter spatially using:</p></td>
+<td><p></p></td>
+<td><p></p></td>
+<td><p></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p>- Interactive map widget</p></td>
+<td><p></p></td>
+<td><p>soon!</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+</tr>
+<tr class="row-even"><td><p>- Bounding Box</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+</tr>
+<tr class="row-odd"><td><p>- Polygon</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+</tr>
+<tr class="row-even"><td><p>- GeoJSON or Shapefile</p></td>
+<td><p>x</p></td>
+<td><p>soon!</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+</tr>
+<tr class="row-odd"><td><p>Filter by time and date</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+</tr>
+<tr class="row-even"><td><p>Preview data</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p>Download data from DAAC</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p>Access cloud-hosted data</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+</tr>
+<tr class="row-odd"><td><p>Subset (spatially, temporally, by variable)</p></td>
+<td><p>x</p></td>
+<td><p></p></td>
+<td><p>x</p></td>
+<td><p>x</p></td>
+</tr>
+<tr class="row-even"><td><p>Plot data with built-in methods</p></td>
+<td><p>x</p></td>
+<td><p></p></td>
+<td><p></p></td>
+<td><p>x</p></td>
+</tr>
+</tbody>
+</table>
+</section>
+</section>
+
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new file mode 100644
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+  <ul>
+   <li class="toctree-l2 has-children">
+    <a class="reference internal" href="../../how_tos/background/index.html">
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+    <ul>
+     <li class="toctree-l3">
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+     <li class="toctree-l3">
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+       Git
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+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/background/earthdata.html">
+       Earthdata Login
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/background/earthengine.html">
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+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/data_access/Instructions_for_configuring_AWS_S3_bucket.html">
+       Instructions for setting up an AWS S3 bucket for your project
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/data_access/CryoCloudScratchBucket.html">
+       Using CryoCloud S3 Scratch Bucket
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/ICESat2_Earthaccess.html">
+       Earthaccess
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+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Earthdata_Cloud__Single_File__HTTPS_Access_COG_Example.html">
+       COG HTTPS
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Earthdata_Cloud__Single_File_Direct_S3_Access_COG_Example.html">
+       COG Direct S3
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+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Multi-File_Direct_S3_Access_COG_Example.html">
+       Multi-COG Direct S3
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+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Earthdata_Cloud__Single_File__Direct_S3_Access_NetCDF4_Example.html">
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+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Multi-File_Direct_S3_Access_NetCDF_Example.html">
+       Multi-NetCDF/HDF5 Direct S3
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+     </li>
+    </ul>
+   </li>
+  </ul>
+ </li>
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+<p aria-level="2" class="caption" role="heading">
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+<ul class="current nav bd-sidenav">
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+   <li class="toctree-l2">
+    <a class="reference internal" href="../IS2_cloud_Landsat_integration.html">
+     ICESat-2 and Landsat cloud access and data integration
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.html">
+     Using ICESat-2 ATL15 (Gridded Arctic Land Ice Height) to investigate ice-surface height anomalies
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../../external/ICESAT2_ATL10-h5coro_large_scale_time_series.html">
+     ICESat-2 ATL10-h5coro large-scale time series
+    </a>
+   </li>
+   <li class="toctree-l2 current active has-children">
+    <a class="reference internal" href="../ARCOdata_writingZarrs.html">
+     Analysis-ready, cloud-optimized data: writing zarr directories
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+    <input checked="" class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
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+    <ul class="current">
+     <li class="toctree-l3">
+      <a class="reference internal" href="1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3 current active">
+      <a class="current reference internal" href="#">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../GrIMP/GrIMP_tutorial_AGU23.html">
+     Determining ice sheet change using Greenland Ice Mapping Project (GrIMP) tools
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+   <li class="toctree-l2">
+    <a class="reference internal" href="../SlideRule_applications/SlideRule_applications.html">
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+        <i class="fas fa-list"></i> Contents
+    </div>
+    <nav id="bd-toc-nav" aria-label="Page">
+        <ul class="visible nav section-nav flex-column">
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#learning-objective">
+   Learning Objective
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#prerequisites">
+   Prerequisites
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#overview">
+   Overview
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#searching-for-data-and-s3-links-using-earthdata-search">
+   Searching for data and S3 links using Earthdata Search
+  </a>
+  <ul class="nav section-nav flex-column">
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#search-for-data">
+     Search for Data
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#getting-s3-links-and-aws-s3-credentials">
+     Getting S3 links and AWS S3 Credentials
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#using-links-and-credentials-from-the-command-line">
+     Using links and credentials from the command line
+    </a>
+   </li>
+  </ul>
+ </li>
+</ul>
+
+    </nav>
+</div>
+    </div>
+    <div class="article row">
+        <div class="col pl-md-3 pl-lg-5 content-container">
+            <!-- Table of contents that is only displayed when printing the page -->
+            <div id="jb-print-docs-body" class="onlyprint">
+                <h1>Using NASA Earthdata Search to Discover Cloud-Hosted Data</h1>
+                <!-- Table of contents -->
+                <div id="print-main-content">
+                    <div id="jb-print-toc">
+                        
+                        <div>
+                            <h2> Contents </h2>
+                        </div>
+                        <nav aria-label="Page">
+                            <ul class="visible nav section-nav flex-column">
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#learning-objective">
+   Learning Objective
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#prerequisites">
+   Prerequisites
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#overview">
+   Overview
+  </a>
+ </li>
+ <li class="toc-h2 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#searching-for-data-and-s3-links-using-earthdata-search">
+   Searching for data and S3 links using Earthdata Search
+  </a>
+  <ul class="nav section-nav flex-column">
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#search-for-data">
+     Search for Data
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#getting-s3-links-and-aws-s3-credentials">
+     Getting S3 links and AWS S3 Credentials
+    </a>
+   </li>
+   <li class="toc-h3 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#using-links-and-credentials-from-the-command-line">
+     Using links and credentials from the command line
+    </a>
+   </li>
+  </ul>
+ </li>
+</ul>
+
+                        </nav>
+                    </div>
+                </div>
+            </div>
+            <main id="main-content" role="main">
+                
+              <div>
+                
+  <section class="tex2jax_ignore mathjax_ignore" id="using-nasa-earthdata-search-to-discover-cloud-hosted-data">
+<h1>Using NASA Earthdata Search to Discover Cloud-Hosted Data<a class="headerlink" href="#using-nasa-earthdata-search-to-discover-cloud-hosted-data" title="Permalink to this headline">#</a></h1>
+<section id="learning-objective">
+<h2>Learning Objective<a class="headerlink" href="#learning-objective" title="Permalink to this headline">#</a></h2>
+<p>In this tutorial you will learn how to:</p>
+<ul class="simple">
+<li><p>Discover cloud-hosted datasets using NASA Earthdata Search.</p></li>
+<li><p>Get AWS S3 credentials so you can access this data.</p></li>
+<li><p>Get the S3 links to data granules.</p></li>
+</ul>
+</section>
+<section id="prerequisites">
+<h2>Prerequisites<a class="headerlink" href="#prerequisites" title="Permalink to this headline">#</a></h2>
+<ul class="simple">
+<li><p>An Earthdata Login account. See the NASA Openscapes Cookbook “<a class="reference external" href="https://nasa-openscapes.github.io/earthdata-cloud-cookbook/appendix/authentication.html">Authentication</a>” guide for more information.</p></li>
+</ul>
+</section>
+<section id="overview">
+<h2>Overview<a class="headerlink" href="#overview" title="Permalink to this headline">#</a></h2>
+<p>NASA Earthdata Search is a web-based tool to discover, filter, visualize and access all of NASA’s Earth science data, both in Earthdata Cloud and archived at the NASA DAACs. It is a useful first step in data discovery, especially if you are not sure what data is available for your research problem.</p>
+<p>This tutorial is based on the NSIDC <a class="reference external" href="https://nsidc.org/data/user-resources/help-center/nasa-earthdata-cloud-data-access-guide">NASA Earthdata Cloud Access Guide</a> and the “<a class="reference external" href="https://nasa-openscapes.github.io/earthdata-cloud-cookbook/how-tos/find-data/earthdata_search.html">How do I find data using Earthdata Search?</a>” guide in the NASA Earthdata Cookbook.</p>
+</section>
+<section id="searching-for-data-and-s3-links-using-earthdata-search">
+<h2>Searching for data and S3 links using Earthdata Search<a class="headerlink" href="#searching-for-data-and-s3-links-using-earthdata-search" title="Permalink to this headline">#</a></h2>
+<section id="search-for-data">
+<h3>Search for Data<a class="headerlink" href="#search-for-data" title="Permalink to this headline">#</a></h3>
+<p>Step 1. Go to <a class="reference external" href="https://search.earthdata.nasa.gov">https://search.earthdata.nasa.gov</a> and log in using your Earthdata Login credentials by clicking on the Earthdata Login button in the top-right corner.</p>
+<p>Step 2. Check the <strong>Available in Earthdata Cloud</strong> box in the <strong>Filter Collections</strong> side-bar on the left of the page (Box 1 on the screenshot below).  The Matching Collections will appear in the results box.  All datasets in Earthdata Cloud have a badge showing a cloud symbol and “Earthdata Cloud” next to them.  To narrow the search, we will filter by datasets supported by NSIDC by typing “NSIDC” in the search box (Box 2 on the screen shot below).  If you want, you could narrow the search further using spatial and temporal filters or any of the other filters in the filter collections box.</p>
+<figure>
+<center>
+    <img src='images/Screenshot_EDSC_Searching_Cloud_Datasets.png' alt='Screenshot of Search for Cloud Datasets in Earthdata Search'/>
+</center>
+</figure>
+<p>Step 3. You can now select the dataset you want by clicking on that dataset.  The Search Results box now contains granules that match your search.  The location of these granules is shown on the map.  The search can be refined using spatial and temporal filters or you can select individual granules using the “+” symbol on each granule search result.  Once you have the data you want, click the <strong>Download All</strong> (Box 1 in the screenshot below). In the sidebar that appears, select <strong>Direct Download</strong> (Box 2 in the screenshot below). Then select <strong>Download Data</strong>.</p>
+<figure>
+    <center>
+        <img src='images/Screenshot_EDSC_getting_s3_links_workflow.png' alt='Screenshot of getting S3 links'/>
+    </center>
+</figure>
+</section>
+<section id="getting-s3-links-and-aws-s3-credentials">
+<h3>Getting S3 links and AWS S3 Credentials<a class="headerlink" href="#getting-s3-links-and-aws-s3-credentials" title="Permalink to this headline">#</a></h3>
+<p>Step 4.  A Download Status window will appear (this may take a short amount of time) similar to the one shown below.  You will see a tab for <strong>AWS S3 Access</strong> (Box 1 in the screenshot below). Select this tab. A list of S3 links (urls) starting with <code class="docutils literal notranslate"><span class="pre">s3://</span></code> will be in the box below.  You can save them to a text file or copy them to your clipboard using the <strong>Save</strong> and <strong>Copy</strong> buttons (Box 2 in the screenshot below). Or you can copy each link separately by hovering over a link and clicking the clipboard icon (Box 3).</p>
+<p>Step 5.  To access data in Earthdata Cloud, you need AWS S3 credentials; “accessKeyId”, “secretAccessKey”, and “sessionToken”.  These are temporary credentials that last for one hour.  To get them click on the <strong>Get AWS S3 Credentials</strong> (Box 4 in the screenshot below).   This will open a new page that contains the three credentials.</p>
+<figure>
+    <center>
+        <img src='images/Screenshot_EDSC_S3_links_credentials.png' alt='Screenshot of S3 links and credentials'/>
+    </center>
+</figure>
+</section>
+<section id="using-links-and-credentials-from-the-command-line">
+<h3>Using links and credentials from the command line<a class="headerlink" href="#using-links-and-credentials-from-the-command-line" title="Permalink to this headline">#</a></h3>
+<p>In the next <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> tutorial, we will work programmatically in the cloud to access datasets of interest. There are several ways to do this. One way to connect this web-based search part of the workflow to our next steps working in the cloud is to simply copy/paste the s3:// links provided in Step 3 above into a JupyterHub notebook or script in our cloud workspace, and continue the data analysis from there.</p>
+<p>One could also copy/paste the s3:// links and save them in a text file, then open and read the text file in the notebook or script in the CryoCloud.</p>
+</section>
+</section>
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+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/data_access/Cloud_Sentinel2_access.html">
+       Sentinel 2 cloud access
+      </a>
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+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/data_access/Instructions_for_configuring_AWS_S3_bucket.html">
+       Instructions for setting up an AWS S3 bucket for your project
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../how_tos/data_access/CryoCloudScratchBucket.html">
+       Using CryoCloud S3 Scratch Bucket
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/ICESat2_Earthaccess.html">
+       Earthaccess
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Earthdata_Cloud__Single_File__HTTPS_Access_COG_Example.html">
+       COG HTTPS
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Earthdata_Cloud__Single_File_Direct_S3_Access_COG_Example.html">
+       COG Direct S3
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Multi-File_Direct_S3_Access_COG_Example.html">
+       Multi-COG Direct S3
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Earthdata_Cloud__Single_File__Direct_S3_Access_NetCDF4_Example.html">
+       NetCDF/HDF5 Direct S3
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../../external/Multi-File_Direct_S3_Access_NetCDF_Example.html">
+       Multi-NetCDF/HDF5 Direct S3
+      </a>
+     </li>
+    </ul>
+   </li>
+  </ul>
+ </li>
+</ul>
+<p aria-level="2" class="caption" role="heading">
+ <span class="caption-text">
+  Tutorials
+ </span>
+</p>
+<ul class="current nav bd-sidenav">
+ <li class="toctree-l1 current active has-children">
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+  <ul class="current">
+   <li class="toctree-l2">
+    <a class="reference internal" href="../IS2_cloud_Landsat_integration.html">
+     ICESat-2 and Landsat cloud access and data integration
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.html">
+     Using ICESat-2 ATL15 (Gridded Arctic Land Ice Height) to investigate ice-surface height anomalies
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../../external/ICESAT2_ATL10-h5coro_large_scale_time_series.html">
+     ICESat-2 ATL10-h5coro large-scale time series
+    </a>
+   </li>
+   <li class="toctree-l2 current active has-children">
+    <a class="reference internal" href="../ARCOdata_writingZarrs.html">
+     Analysis-ready, cloud-optimized data: writing zarr directories
+    </a>
+    <input checked="" class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
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+    </label>
+    <ul class="current">
+     <li class="toctree-l3">
+      <a class="reference internal" href="1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3 current active">
+      <a class="current reference internal" href="#">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../GrIMP/GrIMP_tutorial_AGU23.html">
+     Determining ice sheet change using Greenland Ice Mapping Project (GrIMP) tools
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../SlideRule_applications/SlideRule_applications.html">
+     CryoCloud Tutorials: SlideRule
+    </a>
+   </li>
+  </ul>
+ </li>
+</ul>
+<p aria-level="2" class="caption" role="heading">
+ <span class="caption-text">
+  Contributing
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+<p aria-level="2" class="caption" role="heading">
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+  Reference
+ </span>
+</p>
+<ul class="nav bd-sidenav">
+ <li class="toctree-l1">
+  <a class="reference internal" href="../../reference/glossary.html">
+   Glossaries
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+  <a class="reference internal" href="../../reference/IS2-resources.html">
+   ICESat-2 Resources
+  </a>
+ </li>
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+  <a class="reference internal" href="../../reference/open_science.html">
+   Open Science
+  </a>
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+        <i class="fas fa-list"></i> Contents
+    </div>
+    <nav id="bd-toc-nav" aria-label="Page">
+        <ul class="visible nav section-nav flex-column">
+ <li class="toc-h1 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#">
+   NASA Earthdata Cloud and data access using earthaccess and icepyx
+  </a>
+ </li>
+ <li class="toc-h1 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#part-1-introduction-to-the-earthaccess-python-library">
+   Part 1: Introduction to the
+   <code class="docutils literal notranslate">
+    <span class="pre">
+     earthaccess
+    </span>
+   </code>
+   python library
+  </a>
+  <ul class="visible nav section-nav flex-column">
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#tutorial-overview">
+     Tutorial Overview
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#learning-objectives">
+       Learning Objectives
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#prerequisites">
+     Prerequisites
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#credits">
+     Credits
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#computing-environment">
+     Computing Environment
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#authenticate">
+     Authenticate
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#search-for-icesat-2-collections">
+     Search for ICESat-2 Collections
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#search-for-cloud-hosted-data">
+       Search for cloud-hosted data
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#search-a-data-set-using-spatial-and-temporal-filters">
+     Search a data set using spatial and temporal filters
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#use-direct-access-to-open-load-and-display-data-stored-on-s3">
+     Use Direct-Access to open, load and display data stored on S3
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#additional-resources">
+     Additional resources
+    </a>
+   </li>
+  </ul>
+ </li>
+</ul>
+
+    </nav>
+</div>
+    </div>
+    <div class="article row">
+        <div class="col pl-md-3 pl-lg-5 content-container">
+            <!-- Table of contents that is only displayed when printing the page -->
+            <div id="jb-print-docs-body" class="onlyprint">
+                <h1>NASA Earthdata Cloud and data access using earthaccess and icepyx</h1>
+                <!-- Table of contents -->
+                <div id="print-main-content">
+                    <div id="jb-print-toc">
+                        
+                        <div>
+                            <h2> Contents </h2>
+                        </div>
+                        <nav aria-label="Page">
+                            <ul class="visible nav section-nav flex-column">
+ <li class="toc-h1 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#">
+   NASA Earthdata Cloud and data access using earthaccess and icepyx
+  </a>
+ </li>
+ <li class="toc-h1 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#part-1-introduction-to-the-earthaccess-python-library">
+   Part 1: Introduction to the
+   <code class="docutils literal notranslate">
+    <span class="pre">
+     earthaccess
+    </span>
+   </code>
+   python library
+  </a>
+  <ul class="visible nav section-nav flex-column">
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#tutorial-overview">
+     Tutorial Overview
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#learning-objectives">
+       Learning Objectives
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#prerequisites">
+     Prerequisites
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#credits">
+     Credits
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#computing-environment">
+     Computing Environment
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#authenticate">
+     Authenticate
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#search-for-icesat-2-collections">
+     Search for ICESat-2 Collections
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#search-for-cloud-hosted-data">
+       Search for cloud-hosted data
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#search-a-data-set-using-spatial-and-temporal-filters">
+     Search a data set using spatial and temporal filters
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#use-direct-access-to-open-load-and-display-data-stored-on-s3">
+     Use Direct-Access to open, load and display data stored on S3
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#additional-resources">
+     Additional resources
+    </a>
+   </li>
+  </ul>
+ </li>
+</ul>
+
+                        </nav>
+                    </div>
+                </div>
+            </div>
+            <main id="main-content" role="main">
+                
+              <div>
+                
+  <section class="tex2jax_ignore mathjax_ignore" id="nasa-earthdata-cloud-and-data-access-using-earthaccess-and-icepyx">
+<h1>NASA Earthdata Cloud and data access using earthaccess and icepyx<a class="headerlink" href="#nasa-earthdata-cloud-and-data-access-using-earthaccess-and-icepyx" title="Permalink to this headline">#</a></h1>
+</section>
+<section class="tex2jax_ignore mathjax_ignore" id="part-1-introduction-to-the-earthaccess-python-library">
+<h1>Part 1: Introduction to the <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> python library<a class="headerlink" href="#part-1-introduction-to-the-earthaccess-python-library" title="Permalink to this headline">#</a></h1>
+<section id="tutorial-overview">
+<h2>Tutorial Overview<a class="headerlink" href="#tutorial-overview" title="Permalink to this headline">#</a></h2>
+<p>This tutorial is designed for the “<a class="reference external" href="https://agu.confex.com/agu/fm23/meetingapp.cgi/Session/193477">Cloud Computing and Open-Source Scientific Software for Cryosphere Communities</a>” Learning Workshop at the 2023 AGU Fall Meeting.</p>
+<p>This notebook demonstrates how to search for, access, and work with a cloud-hosted NASA dataset using the <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> package. Data in the “NASA Earthdata Cloud” are stored in Amazon Web Services (AWS) Simple Storage Service (S3) Buckets. <strong>Direct Access</strong> is an efficient way to work with data stored in an S3 Bucket using an Amazon Compute Cloud (EC2) instance. Cloud-hosted granules can be opened and loaded into memory without the need to download them first. This allows you take advantage of the scalability and power of cloud computing.</p>
+<p>We use <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code>, a package developed by Luis Lopez (NSIDC developer) to allow easy search of the NASA Common Metadata Repository (CMR) and download of NASA data collections. It can be used for programmatic search and access for both <em>DAAC-hosted</em> and <em>cloud-hosted</em> data. It manages authenticating using Earthdata Login credentials which are then used to obtain the S3 tokens that are needed for S3 direct access. <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> can be used to find and access both DAAC-hosted and cloud-hosted data in just <strong>three</strong> lines of code. See <a class="reference external" href="https://github.com/nsidc/earthaccess">https://github.com/nsidc/earthaccess</a>.</p>
+<p>As an example data collection, we use ICESat-2 Land Ice Height (ATL06) granules over the Juneau Icefield, AK, for March and April 2020. ICESat-2 data granules, including ATL06, are stored in HDF5 format. We demonstrate how to open an HDF5 granule and access data variables using <code class="docutils literal notranslate"><span class="pre">xarray</span></code>. Land Ice Heights are then plotted using <code class="docutils literal notranslate"><span class="pre">hvplot</span></code>.</p>
+<figure>
+<center>
+    <img src='images/atl06_example_plot.png' alt='Example plot using data downloaded in tutorial'/>
+    <figcaption> ATL06 Land Ice Heights for the margin of the Juneau Ice Field </figcaption>
+</center>
+</figure>
+<section id="learning-objectives">
+<h3>Learning Objectives<a class="headerlink" href="#learning-objectives" title="Permalink to this headline">#</a></h3>
+<p>In this tutorial you will learn:</p>
+<ol class="simple">
+<li><p>how to use <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> to search for (ICESat-2) data using spatial and temporal filters and explore the search results;</p></li>
+<li><p>how to open data granules using direct access to the appropriate S3 bucket;</p></li>
+<li><p>how to load an HDF5 group into an <code class="docutils literal notranslate"><span class="pre">xarray.Dataset</span></code>;</p></li>
+<li><p>how visualize the land ice heights using <code class="docutils literal notranslate"><span class="pre">hvplot</span></code>.</p></li>
+</ol>
+</section>
+</section>
+<section id="prerequisites">
+<h2>Prerequisites<a class="headerlink" href="#prerequisites" title="Permalink to this headline">#</a></h2>
+<p>The workflow described in this tutorial forms the initial steps of an <em>Analysis in Place</em> workflow that would be run on a AWS cloud compute resource.  You will need:</p>
+<ol class="simple">
+<li><p>a JupyterHub, such as CryoHub, or AWS EC2 instance in the us-west-2 region.</p></li>
+<li><p>a NASA Earthdata Login.  If you need to register for an Earthdata Login see the <a class="reference external" href="https://icesat-2-2023.hackweek.io/preliminary/checklist/earthdata.html#getting-an-earthdata-login">Getting an Earthdata Login</a> section of the ICESat-2 Hackweek 2023 Jupyter Book.</p></li>
+<li><p>A <code class="docutils literal notranslate"><span class="pre">.netrc</span></code> file, that contains your Earthdata Login credentials, in your home directory. See <a class="reference external" href="https://icesat-2-2023.hackweek.io/preliminary/checklist/earthdata.html#configure-programmatic-access-to-nasa-servers">Configure Programmatic Access to NASA Servers</a> to create a <code class="docutils literal notranslate"><span class="pre">.netrc</span></code> file.</p></li>
+</ol>
+</section>
+<section id="credits">
+<h2>Credits<a class="headerlink" href="#credits" title="Permalink to this headline">#</a></h2>
+<p>This notebook is based on an <a class="reference external" href="https://github.com/nsidc/NSIDC-Data-Tutorials">NSIDC Data Tutorial</a> originally created by Luis Lopez, NSIDC, and Mikala Beig, NSIDC, modified by Andy Barrett, NSIDC, Jennifer Roebuck, NSIDC, Amy Steiker, NSIDC, and Jessica Scheick, Univ. of New Hampshire.</p>
+</section>
+<section id="computing-environment">
+<h2>Computing Environment<a class="headerlink" href="#computing-environment" title="Permalink to this headline">#</a></h2>
+<p>The tutorial uses <code class="docutils literal notranslate"><span class="pre">python</span></code> and requires the following packages:</p>
+<ul class="simple">
+<li><p><code class="docutils literal notranslate"><span class="pre">earthaccess</span></code>, which enables Earthdata Login authentication and retrieves AWS credentials; enables collection and granule searches; and S3 access;</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">xarray</span></code>, used to load N-dimensional data with labeled axes;</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">hvplot</span></code>, used to visualize land ice height data.</p></li>
+</ul>
+<p>We are going to import the whole <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> package.</p>
+<p>We will also import the whole <code class="docutils literal notranslate"><span class="pre">xarray</span></code> package but use a standard short name <code class="docutils literal notranslate"><span class="pre">xr</span></code>, using the <code class="docutils literal notranslate"><span class="pre">import</span> <span class="pre">&lt;package&gt;</span> <span class="pre">as</span> <span class="pre">&lt;short_name&gt;</span></code> syntax.  We could use anything for a short name but <code class="docutils literal notranslate"><span class="pre">xr</span></code> is an accepted standard that most <code class="docutils literal notranslate"><span class="pre">xarray</span></code> users are familiar with.</p>
+<p><a class="reference external" href="https://docs.xarray.dev/en/stable/"><code class="docutils literal notranslate"><span class="pre">xarray</span></code></a> is a powerful library for working with multi-dimensional data using labeled indices (analogous to Pandas for tabular data). It is leverages numpy, pandas, matplotlib and dask to build Dataset and DataArray objects with built-in methods to subset, analyze, interpolate, and plot multi-dimensional data. It makes working with multi-dimensional data cubes efficient and fun. A few great tutorials for learning Xarray are <a class="reference external" href="https://nasa-openscapes.github.io/2021-Cloud-Hackathon/tutorials/03_Xarray.html">here</a> and <a class="reference external" href="https://tutorial.xarray.dev/intro.html">here</a>.</p>
+<p>We only need the <code class="docutils literal notranslate"><span class="pre">xarray</span></code> module from <code class="docutils literal notranslate"><span class="pre">hvplot</span></code> so we import that using the <code class="docutils literal notranslate"><span class="pre">import</span> <span class="pre">&lt;package&gt;.&lt;module&gt;</span></code> syntax.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># For searching and accessing NASA data</span>
+<span class="kn">import</span> <span class="nn">earthaccess</span>
+
+<span class="c1"># For reading data, analysis and plotting</span>
+<span class="kn">import</span> <span class="nn">xarray</span> <span class="k">as</span> <span class="nn">xr</span>
+<span class="kn">import</span> <span class="nn">hvplot.xarray</span>
+
+<span class="kn">import</span> <span class="nn">pprint</span>  <span class="c1"># For nice printing of python objects</span>
+</pre></div>
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+        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;
+        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);
+        if (msg_handler) {
+          comm.on_msg(msg_handler);
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+      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {
+        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);
+        comm.open();
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+        var comm_promise = google.colab.kernel.comms.open(comm_id)
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+          window.PyViz.comms[comm_id] = comm;
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+              var content = {data: message.data};
+              var metadata = message.metadata || {comm_id};
+              var msg = {content, metadata}
+              msg_handler(msg);
+              return messages.next().then(processIteratorResult);
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+            return messages.next().then(processIteratorResult);
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+        }) 
+        var sendClosure = (data, metadata, buffers, disposeOnDone) => {
+          return comm_promise.then((comm) => {
+            comm.send(data, metadata, buffers, disposeOnDone);
+          });
+        };
+        var comm = {
+          send: sendClosure
+        };
+      }
+      window.PyViz.comms[comm_id] = comm;
+      return comm;
+    }
+    window.PyViz.comm_manager = new JupyterCommManager();
+    
+
+
+var JS_MIME_TYPE = 'application/javascript';
+var HTML_MIME_TYPE = 'text/html';
+var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';
+var CLASS_NAME = 'output';
+
+/**
+ * Render data to the DOM node
+ */
+function render(props, node) {
+  var div = document.createElement("div");
+  var script = document.createElement("script");
+  node.appendChild(div);
+  node.appendChild(script);
+}
+
+/**
+ * Handle when a new output is added
+ */
+function handle_add_output(event, handle) {
+  var output_area = handle.output_area;
+  var output = handle.output;
+  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {
+    return
+  }
+  var id = output.metadata[EXEC_MIME_TYPE]["id"];
+  var toinsert = output_area.element.find("." + CLASS_NAME.split(' ')[0]);
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+      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];
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+    // store reference to server id on output_area
+    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE]["server_id"];
+  }
+}
+
+/**
+ * Handle when an output is cleared or removed
+ */
+function handle_clear_output(event, handle) {
+  var id = handle.cell.output_area._hv_plot_id;
+  var server_id = handle.cell.output_area._bokeh_server_id;
+  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }
+  var comm = window.PyViz.comm_manager.get_client_comm("hv-extension-comm", "hv-extension-comm", function () {});
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+  delete PyViz.plot_index[id];
+  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {
+    var doc = window.Bokeh.index[id].model.document
+    doc.clear();
+    const i = window.Bokeh.documents.indexOf(doc);
+    if (i > -1) {
+      window.Bokeh.documents.splice(i, 1);
+    }
+  }
+}
+
+/**
+ * Handle kernel restart event
+ */
+function handle_kernel_cleanup(event, handle) {
+  delete PyViz.comms["hv-extension-comm"];
+  window.PyViz.plot_index = {}
+}
+
+/**
+ * Handle update_display_data messages
+ */
+function handle_update_output(event, handle) {
+  handle_clear_output(event, {cell: {output_area: handle.output_area}})
+  handle_add_output(event, handle)
+}
+
+function register_renderer(events, OutputArea) {
+  function append_mime(data, metadata, element) {
+    // create a DOM node to render to
+    var toinsert = this.create_output_subarea(
+    metadata,
+    CLASS_NAME,
+    EXEC_MIME_TYPE
+    );
+    this.keyboard_manager.register_events(toinsert);
+    // Render to node
+    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};
+    render(props, toinsert[0]);
+    element.append(toinsert);
+    return toinsert
+  }
+
+  events.on('output_added.OutputArea', handle_add_output);
+  events.on('output_updated.OutputArea', handle_update_output);
+  events.on('clear_output.CodeCell', handle_clear_output);
+  events.on('delete.Cell', handle_clear_output);
+  events.on('kernel_ready.Kernel', handle_kernel_cleanup);
+
+  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {
+    safe: true,
+    index: 0
+  });
+}
+
+if (window.Jupyter !== undefined) {
+  try {
+    var events = require('base/js/events');
+    var OutputArea = require('notebook/js/outputarea').OutputArea;
+    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {
+      register_renderer(events, OutputArea);
+    }
+  } catch(err) {
+  }
+}
+</script><div class="output text_html"><style>*[data-root-id],
+*[data-root-id] > * {
+  box-sizing: border-box;
+  font-family: var(--jp-ui-font-family);
+  font-size: var(--jp-ui-font-size1);
+  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));
+}
+
+/* Override VSCode background color */
+.cell-output-ipywidget-background:has(
+    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]
+  ),
+.cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {
+  background-color: transparent !important;
+}
+</style></div></div>
+</div>
+</section>
+<section id="authenticate">
+<h2>Authenticate<a class="headerlink" href="#authenticate" title="Permalink to this headline">#</a></h2>
+<p>The first step is to get the correct authentication to access <em>cloud-hosted</em> ICESat-2 data.  This is all done through Earthdata Login.  The <code class="docutils literal notranslate"><span class="pre">login</span></code> method also gets the correct AWS credentials.</p>
+<p>Login requires your Earthdata Login username and password. The <code class="docutils literal notranslate"><span class="pre">login</span></code> method will automatically search for these credentials as environment variables or in a <code class="docutils literal notranslate"><span class="pre">.netrc</span></code> file, and if those aren’t available it will prompt you to enter your username and password. We use the prompt strategy here. A <code class="docutils literal notranslate"><span class="pre">.netrc</span></code> file is a text file located in our home directory that contains login information for remote machines.  If you don’t have a <code class="docutils literal notranslate"><span class="pre">.netrc</span></code> file, <code class="docutils literal notranslate"><span class="pre">login</span></code> will create one for you if you use <code class="docutils literal notranslate"><span class="pre">persist=True</span></code>.</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">earthaccess</span><span class="o">.</span><span class="n">login</span><span class="p">(</span><span class="n">strategy</span><span class="o">=</span><span class="s1">&#39;interactive&#39;</span><span class="p">,</span> <span class="n">persist</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+</pre></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">auth</span> <span class="o">=</span> <span class="n">earthaccess</span><span class="o">.</span><span class="n">login</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Enter your Earthdata Login username:  amy.steiker
+Enter your Earthdata password:  ········
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="search-for-icesat-2-collections">
+<h2>Search for ICESat-2 Collections<a class="headerlink" href="#search-for-icesat-2-collections" title="Permalink to this headline">#</a></h2>
+<p><code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> leverages the Common Metadata Repository (CMR) API to search for collections and granules.  <a class="reference external" href="https://search.earthdata.nasa.gov/search">Earthdata Search</a> also uses the CMR API.</p>
+<p>We can use the <code class="docutils literal notranslate"><span class="pre">search_datasets</span></code> method to search for ICESat-2 collections by setting <code class="docutils literal notranslate"><span class="pre">keyword=&quot;ICESat-2&quot;</span></code>.  The argument passed to <code class="docutils literal notranslate"><span class="pre">keyword</span></code> can be any string and can include wildcard characters <code class="docutils literal notranslate"><span class="pre">?</span></code> or <code class="docutils literal notranslate"><span class="pre">*</span></code>.</p>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>To see a full list of search parameters you can type <code class="docutils literal notranslate"><span class="pre">earthaccess.search_datasets?</span></code>.  Using <code class="docutils literal notranslate"><span class="pre">?</span></code> after a python object displays the <code class="docutils literal notranslate"><span class="pre">docstring</span></code> for that object.</p>
+</div>
+<p>A count of the number of data collections (Datasets) found is given.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">query</span> <span class="o">=</span> <span class="n">earthaccess</span><span class="o">.</span><span class="n">search_datasets</span><span class="p">(</span>
+            <span class="n">keyword</span><span class="o">=</span><span class="s2">&quot;ICESat-2&quot;</span><span class="p">,</span>
+<span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Datasets found: 89
+</pre></div>
+</div>
+</div>
+</div>
+<p>In this case, there are 89 datasets that have the keyword ICESat-2.</p>
+<p><code class="docutils literal notranslate"><span class="pre">search_datasets</span></code> returns a python list of <code class="docutils literal notranslate"><span class="pre">DataCollection</span></code> objects.  We can view metadata for each collection in long form by passing a <code class="docutils literal notranslate"><span class="pre">DataCollection</span></code> object to print or as a summary using the <code class="docutils literal notranslate"><span class="pre">summary</span></code> method for the <code class="docutils literal notranslate"><span class="pre">DataCollection</span></code> object.  Here, I use the <code class="docutils literal notranslate"><span class="pre">pprint</span></code> function to <em>Pretty Print</em> each object.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">for</span> <span class="n">collection</span> <span class="ow">in</span> <span class="n">query</span><span class="p">[:</span><span class="mi">10</span><span class="p">]:</span>
+    <span class="n">pprint</span><span class="o">.</span><span class="n">pprint</span><span class="p">(</span><span class="n">collection</span><span class="o">.</span><span class="n">summary</span><span class="p">(),</span> <span class="n">sort_dicts</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">indent</span><span class="o">=</span><span class="mi">4</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>  <span class="c1"># Add a space between collections for readability</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>{   &#39;concept-id&#39;: &#39;C2559919423-NSIDC_ECS&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [   &#39;https://n5eil01u.ecs.nsidc.org/ATLAS/ATL03.006/&#39;,
+                    &#39;https://search.earthdata.nasa.gov/search?q=ATL03+V006&#39;,
+                    &#39;http://openaltimetry.org/&#39;,
+                    &#39;https://nsidc.org/data/data-access-tool/ATL03/versions/6/&#39;],
+    &#39;short-name&#39;: &#39;ATL03&#39;,
+    &#39;version&#39;: &#39;006&#39;}
+
+{   &#39;cloud-info&#39;: {   &#39;Region&#39;: &#39;us-west-2&#39;,
+                      &#39;S3BucketAndObjectPrefixNames&#39;: [   &#39;nsidc-cumulus-prod-protected/ATLAS/ATL03/006&#39;,
+                                                          &#39;nsidc-cumulus-prod-public/ATLAS/ATL03/006&#39;],
+                      &#39;S3CredentialsAPIDocumentationURL&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME&#39;,
+                      &#39;S3CredentialsAPIEndpoint&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentials&#39;},
+    &#39;concept-id&#39;: &#39;C2596864127-NSIDC_CPRD&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [&#39;https://search.earthdata.nasa.gov/search?q=ATL03+V006&#39;],
+    &#39;short-name&#39;: &#39;ATL03&#39;,
+    &#39;version&#39;: &#39;006&#39;}
+
+{   &#39;concept-id&#39;: &#39;C2120512202-NSIDC_ECS&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [   &#39;https://n5eil01u.ecs.nsidc.org/ATLAS/ATL03.005/&#39;,
+                    &#39;https://search.earthdata.nasa.gov/search?q=ATL03+V005&#39;,
+                    &#39;http://openaltimetry.org/&#39;,
+                    &#39;https://nsidc.org/data/data-access-tool/ATL03/versions/5/&#39;],
+    &#39;short-name&#39;: &#39;ATL03&#39;,
+    &#39;version&#39;: &#39;005&#39;}
+
+{   &#39;cloud-info&#39;: {   &#39;Region&#39;: &#39;us-west-2&#39;,
+                      &#39;S3BucketAndObjectPrefixNames&#39;: [   &#39;nsidc-cumulus-prod-protected/ATLAS/ATL03/005&#39;,
+                                                          &#39;nsidc-cumulus-prod-public/ATLAS/ATL03/005&#39;],
+                      &#39;S3CredentialsAPIDocumentationURL&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME&#39;,
+                      &#39;S3CredentialsAPIEndpoint&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentials&#39;},
+    &#39;concept-id&#39;: &#39;C2153572325-NSIDC_CPRD&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [&#39;https://search.earthdata.nasa.gov/search?q=ATL03+V005&#39;],
+    &#39;short-name&#39;: &#39;ATL03&#39;,
+    &#39;version&#39;: &#39;005&#39;}
+
+{   &#39;concept-id&#39;: &#39;C2564427300-NSIDC_ECS&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [   &#39;https://n5eil01u.ecs.nsidc.org/ATLAS/ATL06.006/&#39;,
+                    &#39;https://search.earthdata.nasa.gov/search?q=ATL06+V006&#39;,
+                    &#39;https://openaltimetry.org/&#39;,
+                    &#39;https://nsidc.org/data/data-access-tool/ATL06/versions/6/&#39;],
+    &#39;short-name&#39;: &#39;ATL06&#39;,
+    &#39;version&#39;: &#39;006&#39;}
+
+{   &#39;cloud-info&#39;: {   &#39;Region&#39;: &#39;us-west-2&#39;,
+                      &#39;S3BucketAndObjectPrefixNames&#39;: [   &#39;nsidc-cumulus-prod-protected/ATLAS/ATL06/006&#39;,
+                                                          &#39;nsidc-cumulus-prod-public/ATLAS/ATL06/006&#39;],
+                      &#39;S3CredentialsAPIDocumentationURL&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME&#39;,
+                      &#39;S3CredentialsAPIEndpoint&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentials&#39;},
+    &#39;concept-id&#39;: &#39;C2670138092-NSIDC_CPRD&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [&#39;https://search.earthdata.nasa.gov/search?q=ATL06+V006&#39;],
+    &#39;short-name&#39;: &#39;ATL06&#39;,
+    &#39;version&#39;: &#39;006&#39;}
+
+{   &#39;concept-id&#39;: &#39;C2144439155-NSIDC_ECS&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [   &#39;https://n5eil01u.ecs.nsidc.org/ATLAS/ATL06.005/&#39;,
+                    &#39;https://search.earthdata.nasa.gov/search?q=ATL06+V005&#39;,
+                    &#39;https://openaltimetry.org/&#39;,
+                    &#39;https://nsidc.org/data/data-access-tool/ATL06/versions/5/&#39;],
+    &#39;short-name&#39;: &#39;ATL06&#39;,
+    &#39;version&#39;: &#39;005&#39;}
+
+{   &#39;cloud-info&#39;: {   &#39;Region&#39;: &#39;us-west-2&#39;,
+                      &#39;S3BucketAndObjectPrefixNames&#39;: [   &#39;nsidc-cumulus-prod-protected/ATLAS/ATL06/005&#39;,
+                                                          &#39;nsidc-cumulus-prod-public/ATLAS/ATL06/005&#39;],
+                      &#39;S3CredentialsAPIDocumentationURL&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME&#39;,
+                      &#39;S3CredentialsAPIEndpoint&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentials&#39;},
+    &#39;concept-id&#39;: &#39;C2153572614-NSIDC_CPRD&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [&#39;https://search.earthdata.nasa.gov/search?q=ATL06+V005&#39;],
+    &#39;short-name&#39;: &#39;ATL06&#39;,
+    &#39;version&#39;: &#39;005&#39;}
+
+{   &#39;concept-id&#39;: &#39;C2565090645-NSIDC_ECS&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [   &#39;https://n5eil01u.ecs.nsidc.org/ATLAS/ATL08.006/&#39;,
+                    &#39;https://search.earthdata.nasa.gov/search?q=ATL08+V006&#39;,
+                    &#39;https://openaltimetry.org/&#39;,
+                    &#39;https://nsidc.org/data/data-access-tool/ATL08/versions/6/&#39;],
+    &#39;short-name&#39;: &#39;ATL08&#39;,
+    &#39;version&#39;: &#39;006&#39;}
+
+{   &#39;cloud-info&#39;: {   &#39;Region&#39;: &#39;us-west-2&#39;,
+                      &#39;S3BucketAndObjectPrefixNames&#39;: [   &#39;nsidc-cumulus-prod-protected/ATLAS/ATL08/006&#39;,
+                                                          &#39;nsidc-cumulus-prod-public/ATLAS/ATL08/006&#39;],
+                      &#39;S3CredentialsAPIDocumentationURL&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME&#39;,
+                      &#39;S3CredentialsAPIEndpoint&#39;: &#39;https://data.nsidc.earthdatacloud.nasa.gov/s3credentials&#39;},
+    &#39;concept-id&#39;: &#39;C2613553260-NSIDC_CPRD&#39;,
+    &#39;file-type&#39;: &quot;[{&#39;FormatType&#39;: &#39;Native&#39;, &#39;Format&#39;: &#39;HDF5&#39;, &quot;
+                 &quot;&#39;FormatDescription&#39;: &#39;HTTPS&#39;}]&quot;,
+    &#39;get-data&#39;: [&#39;https://search.earthdata.nasa.gov/search?q=ATL08+V006&#39;],
+    &#39;short-name&#39;: &#39;ATL08&#39;,
+    &#39;version&#39;: &#39;006&#39;}
+</pre></div>
+</div>
+</div>
+</div>
+<p>For each collection, <code class="docutils literal notranslate"><span class="pre">summary</span></code> returns a subset of fields from the collection metadata and Unified Metadata Model (UMM) entry.</p>
+<ul class="simple">
+<li><p><code class="docutils literal notranslate"><span class="pre">concept-id</span></code> is an unique identifier for the collection that is composed of a alphanumeric code and the provider-id for the DAAC.</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">short-name</span></code> is the name of the dataset that appears on the dataset set landing page. For ICESat-2, <code class="docutils literal notranslate"><span class="pre">ShortNames</span></code> are generally how different products are referred to.</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">version</span></code> is the version of each collection.</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">file-type</span></code> gives information about the file format of the collection files.</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">get-data</span></code> is a collection of URLs that can be used to access data, dataset landing pages, and tools.</p></li>
+</ul>
+<p>For <em>cloud-hosted</em> data, there is additional information about the location of the S3 bucket that holds the data and where to get credentials to access the S3 buckets.  In general, you don’t need to worry about this information because <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> handles S3 credentials for you.  Nevertheless it may be useful for troubleshooting.</p>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>In Python, all data are represented by <em>objects</em>.  These <em>objects</em> contain both data and methods (think functions) that operate on the data.  <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> includes  <code class="docutils literal notranslate"><span class="pre">DataCollection</span></code> and <code class="docutils literal notranslate"><span class="pre">DataGranule</span></code> objects that contain data about collections and granules returned by <code class="docutils literal notranslate"><span class="pre">search_datasets</span></code> and <code class="docutils literal notranslate"><span class="pre">search_data</span></code> respectively.  If you are familiar with Python, you will see that the data in each <code class="docutils literal notranslate"><span class="pre">DataCollection</span></code> object is organized as a hierarchy of python dictionaries, lists and strings.  So if you know the dictionary key for the metadata entry you want you can get that metadata using standard dictionary methods.  For example, to get the dataset short name from the example below, you could just use <code class="docutils literal notranslate"><span class="pre">collection['meta']['concept-id']</span></code>.  However, in this example the `concept-id’ method for the DataCollection object returns the same information.  Take a look at <a class="reference external" href="https://github.com/nsidc/earthaccess/blob/main/earthaccess/results.py#L80">https://github.com/nsidc/earthaccess/blob/main/earthaccess/results.py#L80</a> to see how this is done.</p>
+</div>
+<p>For the ICESat-2 search results the concept-id is <code class="docutils literal notranslate"><span class="pre">NSIDC_ECS</span></code> or <code class="docutils literal notranslate"><span class="pre">NSIDC_CPRD</span></code>. <code class="docutils literal notranslate"><span class="pre">NSIDC_ECS</span></code> is for collections archived at the NSIDC DAAC and <code class="docutils literal notranslate"><span class="pre">NSIDC_CPRD</span></code> is for the <em>cloud-hosted</em> collections.</p>
+<p>For ICESat-2 <code class="docutils literal notranslate"><span class="pre">short-name</span></code> refers to the following products.</p>
+<table class="colwidths-auto table">
+<thead>
+<tr class="row-odd"><th class="text-align:center head"><p>ShortName</p></th>
+<th class="text-align:left head"><p>Product Description</p></th>
+</tr>
+</thead>
+<tbody>
+<tr class="row-even"><td class="text-align:center"><p>ATL03</p></td>
+<td class="text-align:left"><p>ATLAS/ICESat-2 L2A Global Geolocated Photon Data</p></td>
+</tr>
+<tr class="row-odd"><td class="text-align:center"><p>ATL06</p></td>
+<td class="text-align:left"><p>ATLAS/ICESat-2 L3A Land Ice Height</p></td>
+</tr>
+<tr class="row-even"><td class="text-align:center"><p>ATL07</p></td>
+<td class="text-align:left"><p>ATLAS/ICESat-2 L3A Sea Ice Height</p></td>
+</tr>
+<tr class="row-odd"><td class="text-align:center"><p>ATL08</p></td>
+<td class="text-align:left"><p>ATLAS/ICESat-2 L3A Land and Vegetation Height</p></td>
+</tr>
+<tr class="row-even"><td class="text-align:center"><p>ATL09</p></td>
+<td class="text-align:left"><p>ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics</p></td>
+</tr>
+<tr class="row-odd"><td class="text-align:center"><p>ATL10</p></td>
+<td class="text-align:left"><p>ATLAS/ICESat-2 L3A Sea Ice Freeboard</p></td>
+</tr>
+<tr class="row-even"><td class="text-align:center"><p>ATL11</p></td>
+<td class="text-align:left"><p>ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series</p></td>
+</tr>
+<tr class="row-odd"><td class="text-align:center"><p>ATL12</p></td>
+<td class="text-align:left"><p>ATLAS/ICESat-2 L3A Ocean Surface Height</p></td>
+</tr>
+<tr class="row-even"><td class="text-align:center"><p>ATL13</p></td>
+<td class="text-align:left"><p>ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data</p></td>
+</tr>
+</tbody>
+</table>
+<section id="search-for-cloud-hosted-data">
+<h3>Search for cloud-hosted data<a class="headerlink" href="#search-for-cloud-hosted-data" title="Permalink to this headline">#</a></h3>
+<p>If you only want to search for data in the cloud, you can set <code class="docutils literal notranslate"><span class="pre">cloud_hosted=True</span></code>.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">Query</span> <span class="o">=</span> <span class="n">earthaccess</span><span class="o">.</span><span class="n">search_datasets</span><span class="p">(</span>
+    <span class="n">keyword</span> <span class="o">=</span> <span class="s1">&#39;ICESat-2&#39;</span><span class="p">,</span>
+    <span class="n">cloud_hosted</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
+<span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Datasets found: 40
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+</section>
+<section id="search-a-data-set-using-spatial-and-temporal-filters">
+<h2>Search a data set using spatial and temporal filters<a class="headerlink" href="#search-a-data-set-using-spatial-and-temporal-filters" title="Permalink to this headline">#</a></h2>
+<p>Once, you have identified the dataset you want to work with, you can use the <code class="docutils literal notranslate"><span class="pre">search_data</span></code> method to search a data set with spatial and temporal filters. As an example, we’ll search for ATL06 granules over the Juneau Icefield, AK, for March and April 2020.</p>
+<p>Either <code class="docutils literal notranslate"><span class="pre">concept-id</span></code> or <code class="docutils literal notranslate"><span class="pre">short-name</span></code> can be used to search for granules from a particular dataset.  If you use <code class="docutils literal notranslate"><span class="pre">short-name</span></code> you also need to set <code class="docutils literal notranslate"><span class="pre">version</span></code>.  If you use <code class="docutils literal notranslate"><span class="pre">concept-id</span></code>, this is all that is required because <code class="docutils literal notranslate"><span class="pre">concept-id</span></code> is unique.</p>
+<p>The temporal range is identified with standard date strings. Latitude-longitude corners of a bounding box are specified as lower left, upper right.  Polygons and points, as well as shapefiles can also be specified.</p>
+<p>This will display the number of granules that match our search.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">results</span> <span class="o">=</span> <span class="n">earthaccess</span><span class="o">.</span><span class="n">search_data</span><span class="p">(</span>
+    <span class="n">short_name</span> <span class="o">=</span> <span class="s1">&#39;ATL06&#39;</span><span class="p">,</span>
+    <span class="n">version</span> <span class="o">=</span> <span class="s1">&#39;006&#39;</span><span class="p">,</span>
+    <span class="n">cloud_hosted</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
+    <span class="n">bounding_box</span> <span class="o">=</span> <span class="p">(</span><span class="o">-</span><span class="mf">134.7</span><span class="p">,</span><span class="mf">58.9</span><span class="p">,</span><span class="o">-</span><span class="mf">133.9</span><span class="p">,</span><span class="mf">59.2</span><span class="p">),</span>
+    <span class="n">temporal</span> <span class="o">=</span> <span class="p">(</span><span class="s1">&#39;2020-03-01&#39;</span><span class="p">,</span><span class="s1">&#39;2020-04-30&#39;</span><span class="p">),</span>
+    <span class="n">count</span> <span class="o">=</span> <span class="mi">100</span>
+<span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Granules found: 4
+</pre></div>
+</div>
+</div>
+</div>
+<p>We’ll get metadata for these 4 granules and display it.  The rendered metadata shows a download link, granule size and two images of the data.</p>
+<p>The download link is <code class="docutils literal notranslate"><span class="pre">https</span></code> and can be used download the granule to your local machine.  This is similar to downloading <em>DAAC-hosted</em> data but in this case the data are coming from the Earthdata Cloud.  For NASA data in the Earthdata Cloud, there is no charge to the user for egress from AWS Cloud servers.  This is not the case for other data in the cloud.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="p">[</span><span class="n">display</span><span class="p">(</span><span class="n">r</span><span class="p">)</span> <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="n">results</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html">
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+</style><style>/*
+ CSS to override bootstrap or define custom styles
+*/
+
+.bootstrap .p {
+ font-size: 18px;
+}
+
+.bootstrap .pull-right {
+    @extend .float-right;
+}
+.bootstrap .pull-left {
+    @extend .float-left;
+}
+</style>
+            </div>
+    <div class="bootstrap">
+      <div class="container-fluid border">
+        <div class="row border">
+          <div class="col-6">
+            <p><b>Data</b>: <a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01.h5" target="_blank" class="btn btn-secondary btn-sm">ATL06_20200310121504_11420606_006_01.h5</a><p/>
+            <p><b>Size</b>: 3.03 MB</p>
+            <p><b>Cloud Hosted</b>: <span>True</span></p>
+          </div>
+          <div class="col-2 offset-sm-3 pull-right">
+            <a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01_BRW.default.default1.jpg"><img style="max-height: 120px;" src="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01_BRW.default.default1.jpg" alt="Data Preview"/></a><a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01_BRW.default.default2.jpg"><img style="max-height: 120px;" src="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/10/ATL06_20200310121504_11420606_006_01_BRW.default.default2.jpg" alt="Data Preview"/></a>
+          </div>
+        </div>
+      </div>
+    </div>
+</div><div class="output text_html">
+    <div id="6f73314c-2fa7-4595-b6f8-fb40d55bbd96" style="height: 0px; display: none">
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+</style><style>/*
+ CSS to override bootstrap or define custom styles
+*/
+
+.bootstrap .p {
+ font-size: 18px;
+}
+
+.bootstrap .pull-right {
+    @extend .float-right;
+}
+.bootstrap .pull-left {
+    @extend .float-left;
+}
+</style>
+            </div>
+    <div class="bootstrap">
+      <div class="container-fluid border">
+        <div class="row border">
+          <div class="col-6">
+            <p><b>Data</b>: <a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01.h5" target="_blank" class="btn btn-secondary btn-sm">ATL06_20200312233336_11800602_006_01.h5</a><p/>
+            <p><b>Size</b>: 29.99 MB</p>
+            <p><b>Cloud Hosted</b>: <span>True</span></p>
+          </div>
+          <div class="col-2 offset-sm-3 pull-right">
+            <a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01_BRW.default.default1.jpg"><img style="max-height: 120px;" src="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01_BRW.default.default1.jpg" alt="Data Preview"/></a><a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01_BRW.default.default2.jpg"><img style="max-height: 120px;" src="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/03/12/ATL06_20200312233336_11800602_006_01_BRW.default.default2.jpg" alt="Data Preview"/></a>
+          </div>
+        </div>
+      </div>
+    </div>
+</div><div class="output text_html">
+    <div id="46c007cf-f31a-4b65-890e-3faaedcf2871" style="height: 0px; display: none">
+            <style>.bootstrap{font-family:sans-serif;line-height:1;-ms-text-size-adjust:100%;-webkit-text-size-adjust:100%}.bootstrap{margin:0;font-size:10px;}.bootstrap article,.bootstrap aside,.bootstrap footer,.bootstrap header,.bootstrap nav,.bootstrap section{display:block}.bootstrap h1{font-size:2em;margin:0.67em 0}.bootstrap figcaption,.bootstrap figure,.bootstrap main{display:block}.bootstrap figure{margin:1em 40px}.bootstrap hr{-webkit-box-sizing:content-box;box-sizing:content-box;height:0;overflow:visible}.bootstrap pre{font-family:monospace,monospace;font-size:1em}.bootstrap a{background-color:transparent;-webkit-text-decoration-skip:objects}.bootstrap a:active,.bootstrap a:hover{outline-width:0}.bootstrap abbr[title]{border-bottom:none;text-decoration:underline;text-decoration:underline dotted}.bootstrap b,.bootstrap strong{font-weight:inherit}.bootstrap b,.bootstrap strong{font-weight:bolder}.bootstrap code,.bootstrap kbd,.bootstrap 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+</style><style>/*
+ CSS to override bootstrap or define custom styles
+*/
+
+.bootstrap .p {
+ font-size: 18px;
+}
+
+.bootstrap .pull-right {
+    @extend .float-right;
+}
+.bootstrap .pull-left {
+    @extend .float-left;
+}
+</style>
+            </div>
+    <div class="bootstrap">
+      <div class="container-fluid border">
+        <div class="row border">
+          <div class="col-6">
+            <p><b>Data</b>: <a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02.h5" target="_blank" class="btn btn-secondary btn-sm">ATL06_20200410220936_02350702_006_02.h5</a><p/>
+            <p><b>Size</b>: 32.95 MB</p>
+            <p><b>Cloud Hosted</b>: <span>True</span></p>
+          </div>
+          <div class="col-2 offset-sm-3 pull-right">
+            <a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02_BRW.default.default1.jpg"><img style="max-height: 120px;" src="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02_BRW.default.default1.jpg" alt="Data Preview"/></a><a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02_BRW.default.default2.jpg"><img style="max-height: 120px;" src="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/10/ATL06_20200410220936_02350702_006_02_BRW.default.default2.jpg" alt="Data Preview"/></a>
+          </div>
+        </div>
+      </div>
+    </div>
+</div><div class="output text_html">
+    <div id="e6f50b4a-ed75-4088-a9c5-58535d1c7a47" style="height: 0px; display: none">
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+</style><style>/*
+ CSS to override bootstrap or define custom styles
+*/
+
+.bootstrap .p {
+ font-size: 18px;
+}
+
+.bootstrap .pull-right {
+    @extend .float-right;
+}
+.bootstrap .pull-left {
+    @extend .float-left;
+}
+</style>
+            </div>
+    <div class="bootstrap">
+      <div class="container-fluid border">
+        <div class="row border">
+          <div class="col-6">
+            <p><b>Data</b>: <a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-protected/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02.h5" target="_blank" class="btn btn-secondary btn-sm">ATL06_20200412104246_02580706_006_02.h5</a><p/>
+            <p><b>Size</b>: 20.34 MB</p>
+            <p><b>Cloud Hosted</b>: <span>True</span></p>
+          </div>
+          <div class="col-2 offset-sm-3 pull-right">
+            <a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02_BRW.default.default1.jpg"><img style="max-height: 120px;" src="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02_BRW.default.default1.jpg" alt="Data Preview"/></a><a href="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02_BRW.default.default2.jpg"><img style="max-height: 120px;" src="https://data.nsidc.earthdatacloud.nasa.gov/nsidc-cumulus-prod-public/ATLAS/ATL06/006/2020/04/12/ATL06_20200412104246_02580706_006_02_BRW.default.default2.jpg" alt="Data Preview"/></a>
+          </div>
+        </div>
+      </div>
+    </div>
+</div><div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[None, None, None, None]
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="use-direct-access-to-open-load-and-display-data-stored-on-s3">
+<h2>Use Direct-Access to open, load and display data stored on S3<a class="headerlink" href="#use-direct-access-to-open-load-and-display-data-stored-on-s3" title="Permalink to this headline">#</a></h2>
+<p>Direct-access to data from an S3 bucket is a two step process.  First, the files are opened using the <code class="docutils literal notranslate"><span class="pre">open</span></code> method.  This first step creates a Python file-like object that is used to load the data in the second step.</p>
+<p>Authentication is required for this step.  The <code class="docutils literal notranslate"><span class="pre">auth</span></code> object created at the start of the notebook is used to provide Earthdata Login authentication and AWS credentials “<em>behind-the-scenes</em>”. These credentials expire after one hour so the <code class="docutils literal notranslate"><span class="pre">auth</span></code> object must be executed within that time window prior to these next steps.</p>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>The <code class="docutils literal notranslate"><span class="pre">open</span></code> step to create a file-like object is required because AWS S3, and other cloud storage systems, use  object storage but most HDF5 libraries work with POSIX-compliant file systems.  POSIX stands for Portable Operating System Interface for Unix and is a set of guidelines that include how to interact with files and file systems.  Linux, Unix, MacOS (which is Unix-like), and Windows are POSIX-compliant. Critically, POSIX-compliant systems allows blocks of bytes or individual bytes to be read from a file. With object storage the whole file has to be read. To get around this limitation, an intermediary is used, in this case <code class="docutils literal notranslate"><span class="pre">s3fs</span></code>.  This intermediary creates a local POSIX-compliant virtual file system.  S3 objects are loaded into this virtual file system so they can be accessed using POSIX-style file functions.</p>
+</div>
+<p>In this example, data are loaded into an <code class="docutils literal notranslate"><span class="pre">xarray.Dataset</span></code>.  Data could be read into <code class="docutils literal notranslate"><span class="pre">numpy</span></code> arrays or a <code class="docutils literal notranslate"><span class="pre">pandas.Dataframe</span></code>.  However, each granule would have to be read using a package that reads HDF5 granules such as <code class="docutils literal notranslate"><span class="pre">h5py</span></code>.  <code class="docutils literal notranslate"><span class="pre">xarray</span></code> does this all <em>under-the-hood</em> in a single line but only for a single group in the HDF5 granule, in this case land ice heights for the gt1l beam*.</p>
+<p>*ICESat-2 measures photon returns from 3 beam pairs numbered 1, 2 and 3 that each consist of a left and a right beam</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%</span><span class="k">time</span>
+<span class="n">files</span> <span class="o">=</span> <span class="n">earthaccess</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">results</span><span class="p">)</span>
+<span class="n">ds</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">open_dataset</span><span class="p">(</span><span class="n">files</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">group</span><span class="o">=</span><span class="s1">&#39;/gt1l/land_ice_segments&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 2 µs, sys: 0 ns, total: 2 µs
+Wall time: 6.2 µs
+Opening 4 granules, approx size: 0.08 GB
+using provider: NSIDC_CPRD
+</pre></div>
+</div>
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+.xr-var-name:hover,
+.xr-var-dims:hover,
+.xr-var-dtype:hover,
+.xr-attrs dt:hover {
+  overflow: visible;
+  width: auto;
+  z-index: 1;
+}
+
+.xr-var-attrs,
+.xr-var-data,
+.xr-index-data {
+  display: none;
+  background-color: var(--xr-background-color) !important;
+  padding-bottom: 5px !important;
+}
+
+.xr-var-attrs-in:checked ~ .xr-var-attrs,
+.xr-var-data-in:checked ~ .xr-var-data,
+.xr-index-data-in:checked ~ .xr-index-data {
+  display: block;
+}
+
+.xr-var-data > table {
+  float: right;
+}
+
+.xr-var-name span,
+.xr-var-data,
+.xr-index-name div,
+.xr-index-data,
+.xr-attrs {
+  padding-left: 25px !important;
+}
+
+.xr-attrs,
+.xr-var-attrs,
+.xr-var-data,
+.xr-index-data {
+  grid-column: 1 / -1;
+}
+
+dl.xr-attrs {
+  padding: 0;
+  margin: 0;
+  display: grid;
+  grid-template-columns: 125px auto;
+}
+
+.xr-attrs dt,
+.xr-attrs dd {
+  padding: 0;
+  margin: 0;
+  float: left;
+  padding-right: 10px;
+  width: auto;
+}
+
+.xr-attrs dt {
+  font-weight: normal;
+  grid-column: 1;
+}
+
+.xr-attrs dt:hover span {
+  display: inline-block;
+  background: var(--xr-background-color);
+  padding-right: 10px;
+}
+
+.xr-attrs dd {
+  grid-column: 2;
+  white-space: pre-wrap;
+  word-break: break-all;
+}
+
+.xr-icon-database,
+.xr-icon-file-text2,
+.xr-no-icon {
+  display: inline-block;
+  vertical-align: middle;
+  width: 1em;
+  height: 1.5em !important;
+  stroke-width: 0;
+  stroke: currentColor;
+  fill: currentColor;
+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;
+Dimensions:                (delta_time: 24471)
+Coordinates:
+  * delta_time             (delta_time) datetime64[ns] 2020-03-12T23:40:48.24...
+    latitude               (delta_time) float64 ...
+    longitude              (delta_time) float64 ...
+Data variables:
+    atl06_quality_summary  (delta_time) int8 ...
+    h_li                   (delta_time) float32 ...
+    h_li_sigma             (delta_time) float32 ...
+    segment_id             (delta_time) float64 ...
+    sigma_geo_h            (delta_time) float32 ...
+Attributes:
+    Description:  The land_ice_height group contains the primary set of deriv...
+    data_rate:    Data within this group are sparse.  Data values are provide...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6334c5b9-3fde-4db6-bead-f8973ff0811a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6334c5b9-3fde-4db6-bead-f8973ff0811a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>delta_time</span>: 24471</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-eb5402d7-c7d4-4d0e-9bb0-bd7710f46308' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eb5402d7-c7d4-4d0e-9bb0-bd7710f46308' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>delta_time</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-03-12T23:40:48.240324376 .....</div><input id='attrs-0d81d9fc-12e2-43ed-9f76-123301b9462e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d81d9fc-12e2-43ed-9f76-123301b9462e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2bb2663-ebcd-4a21-b5eb-952c7d3bd154' class='xr-var-data-in' type='checkbox'><label for='data-a2bb2663-ebcd-4a21-b5eb-952c7d3bd154' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Number of GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds relative to the GPS epoch can be computed.</dd><dt><span>long_name :</span></dt><dd>Elapsed GPS seconds</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-03-12T23:40:48.240324376&#x27;, &#x27;2020-03-12T23:40:48.243204864&#x27;,
+       &#x27;2020-03-12T23:40:48.248890800&#x27;, ..., &#x27;2020-03-12T23:42:06.944719032&#x27;,
+       &#x27;2020-03-12T23:42:06.947529672&#x27;, &#x27;2020-03-12T23:42:06.950340312&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-47202956-385b-4a79-9cb4-9b3cc2decb96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47202956-385b-4a79-9cb4-9b3cc2decb96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1c33f5b-feaa-4f59-8171-6ad218828e98' class='xr-var-data-in' type='checkbox'><label for='data-b1c33f5b-feaa-4f59-8171-6ad218828e98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Latitude of segment center, WGS84, North=+,</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>source :</span></dt><dd>section 3.10</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-42f5b4aa-f0bf-4b51-9cf8-ec93820f4c8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42f5b4aa-f0bf-4b51-9cf8-ec93820f4c8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7889b745-a812-4f52-9568-1cfff0fd6f74' class='xr-var-data-in' type='checkbox'><label for='data-7889b745-a812-4f52-9568-1cfff0fd6f74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Longitude of segment center, , WGS84, East=+</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>source :</span></dt><dd>section 3.10</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-92445bd3-7193-4da5-a939-fa9bc3d0d248' class='xr-section-summary-in' type='checkbox'  checked><label for='section-92445bd3-7193-4da5-a939-fa9bc3d0d248' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>atl06_quality_summary</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d68c8585-43a0-4a5c-9f4c-a9c2b5f1d084' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d68c8585-43a0-4a5c-9f4c-a9c2b5f1d084' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ef6af10-a70b-4628-a501-a53f087d156d' class='xr-var-data-in' type='checkbox'><label for='data-3ef6af10-a70b-4628-a501-a53f087d156d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>qualityInformation</dd><dt><span>description :</span></dt><dd>The ATL06_quality_summary parameter indicates the best-quality subset of all ATL06 data. A zero in this parameter implies that no data-quality tests have found a problem with the segment, a one implies that some potential problem has been found. Users who select only segments with zero values for this flag can be relatively certain of obtaining high-quality data, but will likely miss a significant fraction of usable data, particularly in cloudy, rough, or low-surface-reflectance conditions.</dd><dt><span>flag_meanings :</span></dt><dd>best_quality potential_problem</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>long_name :</span></dt><dd>ATL06_Quality_Summary</dd><dt><span>source :</span></dt><dd>section 4.3</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>1</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=int8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_li</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9afaeaa2-4bba-4afd-9000-c243b15b2090' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9afaeaa2-4bba-4afd-9000-c243b15b2090' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69c90a13-5d06-4c33-b019-96979184f9e7' class='xr-var-data-in' type='checkbox'><label for='data-69c90a13-5d06-4c33-b019-96979184f9e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Standard land-ice segment height determined by land ice algorithm, corrected for first-photon bias, representing the median- based height of the selected PEs</dd><dt><span>long_name :</span></dt><dd>Land Ice height</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_li_sigma</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-17493af2-723b-42f0-8597-bf1e60515e40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17493af2-723b-42f0-8597-bf1e60515e40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a7d97da-2111-4c29-9b26-bcca1bfeff47' class='xr-var-data-in' type='checkbox'><label for='data-0a7d97da-2111-4c29-9b26-bcca1bfeff47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>qualityInformation</dd><dt><span>description :</span></dt><dd>Propagated error due to sampling error and FPB correction from the land ice algorithm</dd><dt><span>long_name :</span></dt><dd>Expected RMS segment misfit</dd><dt><span>source :</span></dt><dd>section 4.4</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>segment_id</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-be1133f5-a7d6-41e7-823d-b23bab900217' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be1133f5-a7d6-41e7-823d-b23bab900217' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa0ae650-56de-4068-97fb-6a755702f05f' class='xr-var-data-in' type='checkbox'><label for='data-fa0ae650-56de-4068-97fb-6a755702f05f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Segment number, counting from the equator. Equal to the segment_id for the second of the two 20m ATL03 segments included in the 40m ATL06 segment</dd><dt><span>long_name :</span></dt><dd>Reference Point, m</dd><dt><span>source :</span></dt><dd>section 3.1.2.1</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma_geo_h</span></div><div class='xr-var-dims'>(delta_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8fbdf6ed-9905-4c18-afa7-60ddb0595a89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fbdf6ed-9905-4c18-afa7-60ddb0595a89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecaabd76-10d8-4cac-ba57-08a8e700a9ff' class='xr-var-data-in' type='checkbox'><label for='data-ecaabd76-10d8-4cac-ba57-08a8e700a9ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>qualityInformation</dd><dt><span>description :</span></dt><dd>Total vertical geolocation error due to PPD and POD, including the effects of horizontal geolocation error on the segment vertical error.</dd><dt><span>long_name :</span></dt><dd>Vertical Geolocation Error</dd><dt><span>source :</span></dt><dd>ATBD Section 3.10</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>[24471 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2d739679-1b1d-4713-bf3e-43c723e75a4a' class='xr-section-summary-in' type='checkbox'  ><label for='section-2d739679-1b1d-4713-bf3e-43c723e75a4a' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>delta_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d1db6856-cd89-4a5b-82e5-d608a07359c7' class='xr-index-data-in' type='checkbox'/><label for='index-d1db6856-cd89-4a5b-82e5-d608a07359c7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-03-12 23:40:48.240324376&#x27;,
+               &#x27;2020-03-12 23:40:48.243204864&#x27;,
+               &#x27;2020-03-12 23:40:48.248890800&#x27;,
+               &#x27;2020-03-12 23:40:48.251708224&#x27;,
+               &#x27;2020-03-12 23:40:48.254545184&#x27;,
+               &#x27;2020-03-12 23:40:48.259401024&#x27;,
+               &#x27;2020-03-12 23:40:48.697626680&#x27;,
+               &#x27;2020-03-12 23:40:48.707952856&#x27;,
+               &#x27;2020-03-12 23:40:48.710775896&#x27;,
+               &#x27;2020-03-12 23:40:48.713604360&#x27;,
+               ...
+               &#x27;2020-03-12 23:42:06.925044328&#x27;,
+               &#x27;2020-03-12 23:42:06.927867648&#x27;,
+               &#x27;2020-03-12 23:42:06.930687608&#x27;,
+               &#x27;2020-03-12 23:42:06.933504432&#x27;,
+               &#x27;2020-03-12 23:42:06.936302200&#x27;,
+               &#x27;2020-03-12 23:42:06.939099968&#x27;,
+               &#x27;2020-03-12 23:42:06.941909704&#x27;,
+               &#x27;2020-03-12 23:42:06.944719032&#x27;,
+               &#x27;2020-03-12 23:42:06.947529672&#x27;,
+               &#x27;2020-03-12 23:42:06.950340312&#x27;],
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;delta_time&#x27;, length=24471, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-92b7f673-adf0-4318-af8a-68528a442b82' class='xr-section-summary-in' type='checkbox'  checked><label for='section-92b7f673-adf0-4318-af8a-68528a442b82' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Description :</span></dt><dd>The land_ice_height group contains the primary set of derived ATL06 products. This includes geolocation, height, and standard error and quality measures for each segment. This group is sparse, meaning that parameters are provided only for pairs of segments for which at least one beam has a valid surface-height measurement.</dd><dt><span>data_rate :</span></dt><dd>Data within this group are sparse.  Data values are provided only for those ICESat-2 20m segments where at least one beam has a valid land ice height measurement.</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<p><code class="docutils literal notranslate"><span class="pre">hvplot</span></code> is an interactive plotting tool that is useful for exploring data.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;h_li&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">hvplot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;scatter&#39;</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><div id='p1002'>
+  <div id="f18ad8ea-95ea-4ab6-98e8-a37bd6fcafa9" data-root-id="p1002" style="display: contents;"></div>
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+</div>
+</section>
+<section id="additional-resources">
+<h2>Additional resources<a class="headerlink" href="#additional-resources" title="Permalink to this headline">#</a></h2>
+<p>For general information about NSIDC DAAC data in the Earthdata Cloud:</p>
+<p><a class="reference external" href="https://nsidc.org/data/user-resources/help-center/faqs-about-nsidc-daacs-earthdata-cloud-migration">FAQs About NSIDC DAAC’s Earthdata Cloud Migration</a></p>
+<p><a class="reference external" href="https://nsidc.org/data/user-resources/help-center/nasa-earthdata-cloud-data-access-guide">NASA Earthdata Cloud Data Access Guide</a></p>
+<p>Additional tutorials and How Tos:</p>
+<p><a class="reference external" href="https://nasa-openscapes.github.io/earthdata-cloud-cookbook/">NASA Earthdata Cloud Cookbook</a></p>
+</section>
+</section>
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+<ul class="current nav bd-sidenav">
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+    <a class="reference internal" href="../IS2_cloud_Landsat_integration.html">
+     ICESat-2 and Landsat cloud access and data integration
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../IS2_ATL15_surface_height_anomalies/IS2_ATL15_surface_height_anomalies.html">
+     Using ICESat-2 ATL15 (Gridded Arctic Land Ice Height) to investigate ice-surface height anomalies
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../../external/ICESAT2_ATL10-h5coro_large_scale_time_series.html">
+     ICESat-2 ATL10-h5coro large-scale time series
+    </a>
+   </li>
+   <li class="toctree-l2 current active has-children">
+    <a class="reference internal" href="../ARCOdata_writingZarrs.html">
+     Analysis-ready, cloud-optimized data: writing zarr directories
+    </a>
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+     <li class="toctree-l3">
+      <a class="reference internal" href="1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3 current active">
+      <a class="current reference internal" href="#">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../GrIMP/GrIMP_tutorial_AGU23.html">
+     Determining ice sheet change using Greenland Ice Mapping Project (GrIMP) tools
+    </a>
+   </li>
+   <li class="toctree-l2">
+    <a class="reference internal" href="../SlideRule_applications/SlideRule_applications.html">
+     CryoCloud Tutorials: SlideRule
+    </a>
+   </li>
+  </ul>
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+ </span>
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+        <i class="fas fa-list"></i> Contents
+    </div>
+    <nav id="bd-toc-nav" aria-label="Page">
+        <ul class="visible nav section-nav flex-column">
+ <li class="toc-h1 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#">
+   NASA Earthdata Cloud and data access using earthaccess and icepyx
+  </a>
+ </li>
+ <li class="toc-h1 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#part-2-using-the-icepyx-python-library-to-access-icesat-2-data">
+   Part 2: Using the
+   <code class="docutils literal notranslate">
+    <span class="pre">
+     icepyx
+    </span>
+   </code>
+   python library to access ICESat-2 data
+  </a>
+  <ul class="visible nav section-nav flex-column">
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#tutorial-overview">
+     Tutorial Overview
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#learning-objectives">
+       Learning Objectives
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#prerequisites">
+     Prerequisites
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#credits">
+     Credits
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#using-icepyx-to-search-and-access-icesat-2-data">
+     Using
+     <code class="docutils literal notranslate">
+      <span class="pre">
+       icepyx
+      </span>
+     </code>
+     to search and access ICESat-2 data
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#reading-a-file-with-icepyx">
+     Reading a file with icepyx
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#create-a-read-object">
+       Create a
+       <code class="docutils literal notranslate">
+        <span class="pre">
+         Read
+        </span>
+       </code>
+       object
+      </a>
+     </li>
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#select-your-variables">
+       Select your variables
+      </a>
+     </li>
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#load-the-data">
+       Load the data!
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#when-to-cloud">
+     When to Cloud
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#some-example-plots">
+     Some example plots
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#example-1-view-the-photon-classifications">
+       Example 1: View the photon classifications
+      </a>
+     </li>
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#plot-the-canopy-compared-to-the-ground-height">
+       Plot the canopy compared to the ground height
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#summary">
+     Summary
+    </a>
+   </li>
+  </ul>
+ </li>
+</ul>
+
+    </nav>
+</div>
+    </div>
+    <div class="article row">
+        <div class="col pl-md-3 pl-lg-5 content-container">
+            <!-- Table of contents that is only displayed when printing the page -->
+            <div id="jb-print-docs-body" class="onlyprint">
+                <h1>NASA Earthdata Cloud and data access using earthaccess and icepyx</h1>
+                <!-- Table of contents -->
+                <div id="print-main-content">
+                    <div id="jb-print-toc">
+                        
+                        <div>
+                            <h2> Contents </h2>
+                        </div>
+                        <nav aria-label="Page">
+                            <ul class="visible nav section-nav flex-column">
+ <li class="toc-h1 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#">
+   NASA Earthdata Cloud and data access using earthaccess and icepyx
+  </a>
+ </li>
+ <li class="toc-h1 nav-item toc-entry">
+  <a class="reference internal nav-link" href="#part-2-using-the-icepyx-python-library-to-access-icesat-2-data">
+   Part 2: Using the
+   <code class="docutils literal notranslate">
+    <span class="pre">
+     icepyx
+    </span>
+   </code>
+   python library to access ICESat-2 data
+  </a>
+  <ul class="visible nav section-nav flex-column">
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#tutorial-overview">
+     Tutorial Overview
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#learning-objectives">
+       Learning Objectives
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#prerequisites">
+     Prerequisites
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#credits">
+     Credits
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#using-icepyx-to-search-and-access-icesat-2-data">
+     Using
+     <code class="docutils literal notranslate">
+      <span class="pre">
+       icepyx
+      </span>
+     </code>
+     to search and access ICESat-2 data
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#reading-a-file-with-icepyx">
+     Reading a file with icepyx
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#create-a-read-object">
+       Create a
+       <code class="docutils literal notranslate">
+        <span class="pre">
+         Read
+        </span>
+       </code>
+       object
+      </a>
+     </li>
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#select-your-variables">
+       Select your variables
+      </a>
+     </li>
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#load-the-data">
+       Load the data!
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#when-to-cloud">
+     When to Cloud
+    </a>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#some-example-plots">
+     Some example plots
+    </a>
+    <ul class="nav section-nav flex-column">
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#example-1-view-the-photon-classifications">
+       Example 1: View the photon classifications
+      </a>
+     </li>
+     <li class="toc-h3 nav-item toc-entry">
+      <a class="reference internal nav-link" href="#plot-the-canopy-compared-to-the-ground-height">
+       Plot the canopy compared to the ground height
+      </a>
+     </li>
+    </ul>
+   </li>
+   <li class="toc-h2 nav-item toc-entry">
+    <a class="reference internal nav-link" href="#summary">
+     Summary
+    </a>
+   </li>
+  </ul>
+ </li>
+</ul>
+
+                        </nav>
+                    </div>
+                </div>
+            </div>
+            <main id="main-content" role="main">
+                
+              <div>
+                
+  <section class="tex2jax_ignore mathjax_ignore" id="nasa-earthdata-cloud-and-data-access-using-earthaccess-and-icepyx">
+<h1>NASA Earthdata Cloud and data access using earthaccess and icepyx<a class="headerlink" href="#nasa-earthdata-cloud-and-data-access-using-earthaccess-and-icepyx" title="Permalink to this headline">#</a></h1>
+</section>
+<section class="tex2jax_ignore mathjax_ignore" id="part-2-using-the-icepyx-python-library-to-access-icesat-2-data">
+<h1>Part 2: Using the <code class="docutils literal notranslate"><span class="pre">icepyx</span></code> python library to access ICESat-2 data<a class="headerlink" href="#part-2-using-the-icepyx-python-library-to-access-icesat-2-data" title="Permalink to this headline">#</a></h1>
+<section id="tutorial-overview">
+<h2>Tutorial Overview<a class="headerlink" href="#tutorial-overview" title="Permalink to this headline">#</a></h2>
+<p>This tutorial is designed for the “<a class="reference external" href="https://agu.confex.com/agu/fm23/meetingapp.cgi/Session/193477">Cloud Computing and Open-Source Scientific Software for Cryosphere Communities</a>” Learning Workshop at the 2023 AGU Fall Meeting.</p>
+<p>This notebook demonstrates how to search for, access, and analyse and plot a cloud-hosted ICESat-2 dataset using the <a class="reference external" href="https://icepyx.readthedocs.io/en/latest/example_notebooks/IS2_data_access.html"><code class="docutils literal notranslate"><span class="pre">icepyx</span></code></a> package.</p>
+<figure>
+<center>
+    <img src="https://icepyx.readthedocs.io/en/latest/_static/icepyx_v2_oval_orig_nobackgr.png" alt='icepyx logo of the word icepyx in raised letters on an iceberg with an ice ax'/>
+</center>
+</figure>
+<p>icepyx is a community and software library for searching, downloading, and reading ICESat-2 data. While opening data should be straightforward, there are some oddities in navigating the highly nested organization and hundreds of variables of the ICESat-2 data. icepyx provides tools to help with those oddities.</p>
+<p><code class="docutils literal notranslate"><span class="pre">icepyx</span></code> was started and initially developed by Jessica Scheick to provide easy programmatic access to ICESat-2 data (before <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> existed!) and facilitate collaborative development around ICESat-2 data products, including training, skill building, and support around practicing open science and contributing to open-source software. Thanks to contributions from countless community members, <code class="docutils literal notranslate"><span class="pre">icepyx</span></code> can (for ICESat-2 data):</p>
+<ul class="simple">
+<li><p>search for available data granules (data files)</p></li>
+<li><p>order and download data or access it directly in the cloud</p></li>
+<li><p>order a subset of data: clipped in space, time, containing fewer variables, or a few other options provided by NSIDC</p></li>
+<li><p>search through the available ICESat-2 data variables</p></li>
+<li><p>read ICESat-2 data into xarray DataArrays, including merging data from multiple files</p></li>
+</ul>
+<p>Under the hood, <code class="docutils literal notranslate"><span class="pre">icepyx</span></code> relies on <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> to help handle authentication, especially for obtaining S3 tokens to access ICESat-2 data in the cloud. All this happens without the user needing to take any action other than supplying their Earthdata Login credentials using one of the methods described in the <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code> tutorial.</p>
+<p>In this tutorial we will look at the <code class="docutils literal notranslate"><span class="pre">ATL08</span></code> Land and Vegetation Height product.</p>
+<section id="learning-objectives">
+<h3>Learning Objectives<a class="headerlink" href="#learning-objectives" title="Permalink to this headline">#</a></h3>
+<p>In this tutorial you will learn:</p>
+<ol class="simple">
+<li><p>how to use <code class="docutils literal notranslate"><span class="pre">icepyx</span></code> to search for ICESat-2 data using spatial and temporal filters;</p></li>
+<li><p>how to open and combine data multiple HDF5 groups into an <code class="docutils literal notranslate"><span class="pre">xarray.Dataset</span></code> using <code class="docutils literal notranslate"><span class="pre">icepyx.Read</span></code>;</p></li>
+<li><p>how to begin your analysis, including selecting strong/weak beams and plotting.</p></li>
+</ol>
+</section>
+</section>
+<section id="prerequisites">
+<h2>Prerequisites<a class="headerlink" href="#prerequisites" title="Permalink to this headline">#</a></h2>
+<p>The workflow described in this tutorial forms the initial steps of an <em>Analysis in Place</em> workflow that would be run on a AWS cloud compute resource.  You will need:</p>
+<ol class="simple">
+<li><p>a JupyterHub, such as CryoHub, or AWS EC2 instance in the us-west-2 region.</p></li>
+<li><p>a NASA Earthdata Login.  If you need to register for an Earthdata Login see the <a class="reference external" href="https://icesat-2-2023.hackweek.io/preliminary/checklist/earthdata.html#getting-an-earthdata-login">Getting an Earthdata Login</a> section of the ICESat-2 Hackweek 2023 Jupyter Book.</p></li>
+<li><p>A <code class="docutils literal notranslate"><span class="pre">.netrc</span></code> file, that contains your Earthdata Login credentials, in your home directory. See <a class="reference external" href="https://icesat-2-2023.hackweek.io/preliminary/checklist/earthdata.html#configure-programmatic-access-to-nasa-servers">Configure Programmatic Access to NASA Servers</a> to create a <code class="docutils literal notranslate"><span class="pre">.netrc</span></code> file.</p></li>
+</ol>
+</section>
+<section id="credits">
+<h2>Credits<a class="headerlink" href="#credits" title="Permalink to this headline">#</a></h2>
+<p>This notebook is based on an <a class="reference external" href="https://nasa-openscapes.github.io/2023-ssc/tutorials/data-access/icepyx.html">icepyx Tutorial</a> originally created by Rachel Wegener, Univ. Maryland and updated by Amy Steiker, NSIDC, and Jessica Scheick, Univ. of New Hampshire.</p>
+</section>
+<section id="using-icepyx-to-search-and-access-icesat-2-data">
+<h2>Using <code class="docutils literal notranslate"><span class="pre">icepyx</span></code> to search and access ICESat-2 data<a class="headerlink" href="#using-icepyx-to-search-and-access-icesat-2-data" title="Permalink to this headline">#</a></h2>
+<p>We won’t dive into using icepyx to search for and download data in this tutorial, since we already discussed how to do that with <code class="docutils literal notranslate"><span class="pre">earthaccess</span></code>. The code to search and download is still provided below for the curious reader. The <a class="reference external" href="https://icepyx.readthedocs.io/en/latest/example_notebooks/IS2_data_access.html">icepyx documentation</a> shows more detail about different search parameters and how to inspect the results of a query.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">icepyx</span> <span class="k">as</span> <span class="nn">ipx</span>
+</pre></div>
+</div>
+</div>
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+  var comm = window.PyViz.comm_manager.get_client_comm("hv-extension-comm", "hv-extension-comm", function () {});
+  if (server_id !== null) {
+    comm.send({event_type: 'server_delete', 'id': server_id});
+    return;
+  } else if (comm !== null) {
+    comm.send({event_type: 'delete', 'id': id});
+  }
+  delete PyViz.plot_index[id];
+  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {
+    var doc = window.Bokeh.index[id].model.document
+    doc.clear();
+    const i = window.Bokeh.documents.indexOf(doc);
+    if (i > -1) {
+      window.Bokeh.documents.splice(i, 1);
+    }
+  }
+}
+
+/**
+ * Handle kernel restart event
+ */
+function handle_kernel_cleanup(event, handle) {
+  delete PyViz.comms["hv-extension-comm"];
+  window.PyViz.plot_index = {}
+}
+
+/**
+ * Handle update_display_data messages
+ */
+function handle_update_output(event, handle) {
+  handle_clear_output(event, {cell: {output_area: handle.output_area}})
+  handle_add_output(event, handle)
+}
+
+function register_renderer(events, OutputArea) {
+  function append_mime(data, metadata, element) {
+    // create a DOM node to render to
+    var toinsert = this.create_output_subarea(
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+    CLASS_NAME,
+    EXEC_MIME_TYPE
+    );
+    this.keyboard_manager.register_events(toinsert);
+    // Render to node
+    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};
+    render(props, toinsert[0]);
+    element.append(toinsert);
+    return toinsert
+  }
+
+  events.on('output_added.OutputArea', handle_add_output);
+  events.on('output_updated.OutputArea', handle_update_output);
+  events.on('clear_output.CodeCell', handle_clear_output);
+  events.on('delete.Cell', handle_clear_output);
+  events.on('kernel_ready.Kernel', handle_kernel_cleanup);
+
+  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {
+    safe: true,
+    index: 0
+  });
+}
+
+if (window.Jupyter !== undefined) {
+  try {
+    var events = require('base/js/events');
+    var OutputArea = require('notebook/js/outputarea').OutputArea;
+    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {
+      register_renderer(events, OutputArea);
+    }
+  } catch(err) {
+  }
+}
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+  font-family: var(--jp-ui-font-family);
+  font-size: var(--jp-ui-font-size1);
+  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));
+}
+
+/* Override VSCode background color */
+.cell-output-ipywidget-background:has(
+    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]
+  ),
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+}
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+       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>
+
+
+
+
+
+</div>
+</div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">json</span>
+<span class="kn">import</span> <span class="nn">math</span>
+<span class="kn">import</span> <span class="nn">warnings</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">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+<span class="kn">from</span> <span class="nn">shapely.geometry</span> <span class="kn">import</span> <span class="n">shape</span><span class="p">,</span> <span class="n">GeometryCollection</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%</span><span class="k">matplotlib</span> inline
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Open a geojson of our area of interest</span>
+<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;./bosque_primavera.json&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
+    <span class="n">features</span> <span class="o">=</span> <span class="n">json</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)[</span><span class="s2">&quot;features&quot;</span><span class="p">]</span>
+
+<span class="n">bosque</span> <span class="o">=</span> <span class="n">GeometryCollection</span><span class="p">([</span><span class="n">shape</span><span class="p">(</span><span class="n">feature</span><span class="p">[</span><span class="s2">&quot;geometry&quot;</span><span class="p">])</span><span class="o">.</span><span class="n">buffer</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">feature</span> <span class="ow">in</span> <span class="n">features</span><span class="p">])</span>
+<span class="n">bosque</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="../../_images/4.icepyx_5_0.svg" src="../../_images/4.icepyx_5_0.svg" /></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Use our search parameters to setup a search Query</span>
+<span class="n">short_name</span> <span class="o">=</span> <span class="s1">&#39;ATL08&#39;</span>
+<span class="n">spatial_extent</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">bosque</span><span class="o">.</span><span class="n">bounds</span><span class="p">)</span>
+<span class="n">date_range</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;2019-05-04&#39;</span><span class="p">,</span><span class="s1">&#39;2019-05-04&#39;</span><span class="p">]</span>
+<span class="n">region</span> <span class="o">=</span> <span class="n">ipx</span><span class="o">.</span><span class="n">Query</span><span class="p">(</span><span class="n">short_name</span><span class="p">,</span> <span class="n">spatial_extent</span><span class="p">,</span> <span class="n">date_range</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Display if any data files, or granules, matched our search</span>
+<span class="n">region</span><span class="o">.</span><span class="n">avail_granules</span><span class="p">(</span><span class="n">ids</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[&#39;ATL08_20190504124152_05540301_006_02.h5&#39;]]
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># We can also get the S3 urls</span>
+<span class="n">region</span><span class="o">.</span><span class="n">avail_granules</span><span class="p">(</span><span class="n">ids</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">cloud</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[&#39;ATL08_20190504124152_05540301_006_02.h5&#39;],
+ [&#39;s3://nsidc-cumulus-prod-protected/ATLAS/ATL08/006/2019/05/04/ATL08_20190504124152_05540301_006_02.h5&#39;]]
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Download the granules to a into a folder called &#39;bosque_primavera_ATL08&#39;</span>
+<span class="n">region</span><span class="o">.</span><span class="n">download_granules</span><span class="p">(</span><span class="s1">&#39;./bosque_primavera_ATL08&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Enter your Earthdata Login username:  amy.steiker
+Enter your Earthdata password:  ········
+</pre></div>
+</div>
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Total number of data order requests is  1  for  1  granules.
+Data request  1  of  1  is submitting to NSIDC
+order ID:  5000004735271
+Initial status of your order request at NSIDC is:  processing
+Your order status is still  processing  at NSIDC. Please continue waiting... this may take a few moments.
+Your order is: complete
+Beginning download of zipped output...
+Data request 5000004735271 of  1  order(s) is downloaded.
+Download complete
+</pre></div>
+</div>
+</div>
+</div>
+<div class="alert alert-block alert-info">
+<b>Tip:</b> If you don't want to type your Earthdata Login information every time they are
+    required you can setup more automatic methods of authentication. Two common methods
+    are 1) Add your earthdata password and username to as environment variables
+    as EARTHDATA_USERNAME and EARTHDATA_PASSWORD. 2) setup a .netrc file in your home directory. See <a href="https://nasa-openscapes.github.io/2021-Cloud-Hackathon/tutorials/04_NASA_Earthdata_Authentication.html"> the Openscapes tutorial</a> </div></section>
+<section id="reading-a-file-with-icepyx">
+<h2>Reading a file with icepyx<a class="headerlink" href="#reading-a-file-with-icepyx" title="Permalink to this headline">#</a></h2>
+<p>To read a file with icepyx there are several steps:</p>
+<ol class="simple">
+<li><p>Create a <code class="docutils literal notranslate"><span class="pre">Read</span></code> object. This sets up an initial connection to your file(s) and validates the metadata.</p></li>
+<li><p>Tell the <code class="docutils literal notranslate"><span class="pre">Read</span></code> object what variables you would like to read</p></li>
+<li><p>Load your data!</p></li>
+</ol>
+<section id="create-a-read-object">
+<h3>Create a <code class="docutils literal notranslate"><span class="pre">Read</span></code> object<a class="headerlink" href="#create-a-read-object" title="Permalink to this headline">#</a></h3>
+<p>Here we are creating a read object to set up an initial connection to your file(s). The pattern outlines the file naming convention. For example, <code class="docutils literal notranslate"><span class="pre">{revision:2}</span></code> describes the last two values in the filename which denote the product revision number. Details on the filenaming convention are found <a class="reference external" href="https://nsidc.org/sites/default/files/documents/user-guide/atl08-v006-userguide.pdf">here</a>.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">pattern</span> <span class="o">=</span> <span class="s2">&quot;processed_ATL</span><span class="si">{product:2}</span><span class="s2">_{datetime:%Y%m</span><span class="si">%d</span><span class="s2">%H%M%S}_</span><span class="si">{rgt:4}{cycle:2}{orbitsegment:2}</span><span class="s2">_</span><span class="si">{version:3}</span><span class="s2">_</span><span class="si">{revision:2}</span><span class="s2">.h5&quot;</span>
+<span class="n">reader</span> <span class="o">=</span> <span class="n">ipx</span><span class="o">.</span><span class="n">Read</span><span class="p">(</span><span class="s1">&#39;./bosque_primavera_ATL08&#39;</span><span class="p">,</span> <span class="s2">&quot;ATL08&quot;</span><span class="p">,</span> <span class="n">pattern</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>You have 1 files matching the filename pattern to be read in.
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">reader</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;icepyx.core.read.Read at 0x7f2b12bb0c10&gt;
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="select-your-variables">
+<h3>Select your variables<a class="headerlink" href="#select-your-variables" title="Permalink to this headline">#</a></h3>
+<p>To view the variables contained in your dataset you can call <code class="docutils literal notranslate"><span class="pre">.vars</span></code> on your data reader.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">reader</span><span class="o">.</span><span class="n">vars</span><span class="o">.</span><span class="n">avail</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&#39;ancillary_data/atlas_sdp_gps_epoch&#39;,
+ &#39;ancillary_data/control&#39;,
+ &#39;ancillary_data/data_end_utc&#39;,
+ &#39;ancillary_data/data_start_utc&#39;,
+ &#39;ancillary_data/end_cycle&#39;,
+ &#39;ancillary_data/end_delta_time&#39;,
+ &#39;ancillary_data/end_geoseg&#39;,
+ &#39;ancillary_data/end_gpssow&#39;,
+ &#39;ancillary_data/end_gpsweek&#39;,
+ &#39;ancillary_data/end_orbit&#39;,
+ &#39;ancillary_data/end_region&#39;,
+ &#39;ancillary_data/end_rgt&#39;,
+ &#39;ancillary_data/granule_end_utc&#39;,
+ &#39;ancillary_data/granule_start_utc&#39;,
+ &#39;ancillary_data/land/atl08_region&#39;,
+ &#39;ancillary_data/land/bin_size_h&#39;,
+ &#39;ancillary_data/land/bin_size_n&#39;,
+ &#39;ancillary_data/land/bright_thresh&#39;,
+ &#39;ancillary_data/land/ca_class&#39;,
+ &#39;ancillary_data/land/can_noise_thresh&#39;,
+ &#39;ancillary_data/land/can_stat_thresh&#39;,
+ &#39;ancillary_data/land/canopy20m_thresh&#39;,
+ &#39;ancillary_data/land/canopy_flag_switch&#39;,
+ &#39;ancillary_data/land/canopy_seg&#39;,
+ &#39;ancillary_data/land/class_thresh&#39;,
+ &#39;ancillary_data/land/cloud_filter_switch&#39;,
+ &#39;ancillary_data/land/del_amp&#39;,
+ &#39;ancillary_data/land/del_mu&#39;,
+ &#39;ancillary_data/land/del_sigma&#39;,
+ &#39;ancillary_data/land/dem_filter_switch&#39;,
+ &#39;ancillary_data/land/dem_removal_percent_limit&#39;,
+ &#39;ancillary_data/land/dragann_switch&#39;,
+ &#39;ancillary_data/land/dseg&#39;,
+ &#39;ancillary_data/land/dseg_buf&#39;,
+ &#39;ancillary_data/land/fnlgnd_filter_switch&#39;,
+ &#39;ancillary_data/land/gnd_stat_thresh&#39;,
+ &#39;ancillary_data/land/gthresh_factor&#39;,
+ &#39;ancillary_data/land/h_canopy_perc&#39;,
+ &#39;ancillary_data/land/iter_gnd&#39;,
+ &#39;ancillary_data/land/iter_max&#39;,
+ &#39;ancillary_data/land/lseg&#39;,
+ &#39;ancillary_data/land/lseg_buf&#39;,
+ &#39;ancillary_data/land/lw_filt_bnd&#39;,
+ &#39;ancillary_data/land/lw_gnd_bnd&#39;,
+ &#39;ancillary_data/land/lw_toc_bnd&#39;,
+ &#39;ancillary_data/land/lw_toc_cut&#39;,
+ &#39;ancillary_data/land/max_atl03files&#39;,
+ &#39;ancillary_data/land/max_atl09files&#39;,
+ &#39;ancillary_data/land/max_peaks&#39;,
+ &#39;ancillary_data/land/max_try&#39;,
+ &#39;ancillary_data/land/min_nphs&#39;,
+ &#39;ancillary_data/land/n_dec_mode&#39;,
+ &#39;ancillary_data/land/night_thresh&#39;,
+ &#39;ancillary_data/land/noise_class&#39;,
+ &#39;ancillary_data/land/outlier_filter_switch&#39;,
+ &#39;ancillary_data/land/p_static&#39;,
+ &#39;ancillary_data/land/ph_removal_percent_limit&#39;,
+ &#39;ancillary_data/land/proc_geoseg&#39;,
+ &#39;ancillary_data/land/psf&#39;,
+ &#39;ancillary_data/land/ref_dem_limit&#39;,
+ &#39;ancillary_data/land/ref_finalground_limit&#39;,
+ &#39;ancillary_data/land/relief_hbot&#39;,
+ &#39;ancillary_data/land/relief_htop&#39;,
+ &#39;ancillary_data/land/shp_param&#39;,
+ &#39;ancillary_data/land/sig_rsq_search&#39;,
+ &#39;ancillary_data/land/sseg&#39;,
+ &#39;ancillary_data/land/stat20m_thresh&#39;,
+ &#39;ancillary_data/land/stat_thresh&#39;,
+ &#39;ancillary_data/land/tc_thresh&#39;,
+ &#39;ancillary_data/land/te_class&#39;,
+ &#39;ancillary_data/land/terrain20m_thresh&#39;,
+ &#39;ancillary_data/land/toc_class&#39;,
+ &#39;ancillary_data/land/up_filt_bnd&#39;,
+ &#39;ancillary_data/land/up_gnd_bnd&#39;,
+ &#39;ancillary_data/land/up_toc_bnd&#39;,
+ &#39;ancillary_data/land/up_toc_cut&#39;,
+ &#39;ancillary_data/land/yapc_switch&#39;,
+ &#39;ancillary_data/qa_at_interval&#39;,
+ &#39;ancillary_data/release&#39;,
+ &#39;ancillary_data/start_cycle&#39;,
+ &#39;ancillary_data/start_delta_time&#39;,
+ &#39;ancillary_data/start_geoseg&#39;,
+ &#39;ancillary_data/start_gpssow&#39;,
+ &#39;ancillary_data/start_gpsweek&#39;,
+ &#39;ancillary_data/start_orbit&#39;,
+ &#39;ancillary_data/start_region&#39;,
+ &#39;ancillary_data/start_rgt&#39;,
+ &#39;ancillary_data/version&#39;,
+ &#39;ds_geosegments&#39;,
+ &#39;ds_metrics&#39;,
+ &#39;ds_surf_type&#39;,
+ &#39;gt3l/land_segments/asr&#39;,
+ &#39;gt3l/land_segments/atlas_pa&#39;,
+ &#39;gt3l/land_segments/beam_azimuth&#39;,
+ &#39;gt3l/land_segments/beam_coelev&#39;,
+ &#39;gt3l/land_segments/brightness_flag&#39;,
+ &#39;gt3l/land_segments/canopy/can_noise&#39;,
+ &#39;gt3l/land_segments/canopy/canopy_h_metrics&#39;,
+ &#39;gt3l/land_segments/canopy/canopy_h_metrics_abs&#39;,
+ &#39;gt3l/land_segments/canopy/canopy_openness&#39;,
+ &#39;gt3l/land_segments/canopy/canopy_rh_conf&#39;,
+ &#39;gt3l/land_segments/canopy/centroid_height&#39;,
+ &#39;gt3l/land_segments/canopy/h_canopy&#39;,
+ &#39;gt3l/land_segments/canopy/h_canopy_20m&#39;,
+ &#39;gt3l/land_segments/canopy/h_canopy_abs&#39;,
+ &#39;gt3l/land_segments/canopy/h_canopy_quad&#39;,
+ &#39;gt3l/land_segments/canopy/h_canopy_uncertainty&#39;,
+ &#39;gt3l/land_segments/canopy/h_dif_canopy&#39;,
+ &#39;gt3l/land_segments/canopy/h_max_canopy&#39;,
+ &#39;gt3l/land_segments/canopy/h_max_canopy_abs&#39;,
+ &#39;gt3l/land_segments/canopy/h_mean_canopy&#39;,
+ &#39;gt3l/land_segments/canopy/h_mean_canopy_abs&#39;,
+ &#39;gt3l/land_segments/canopy/h_median_canopy&#39;,
+ &#39;gt3l/land_segments/canopy/h_median_canopy_abs&#39;,
+ &#39;gt3l/land_segments/canopy/h_min_canopy&#39;,
+ &#39;gt3l/land_segments/canopy/h_min_canopy_abs&#39;,
+ &#39;gt3l/land_segments/canopy/n_ca_photons&#39;,
+ &#39;gt3l/land_segments/canopy/n_toc_photons&#39;,
+ &#39;gt3l/land_segments/canopy/photon_rate_can&#39;,
+ &#39;gt3l/land_segments/canopy/photon_rate_can_nr&#39;,
+ &#39;gt3l/land_segments/canopy/segment_cover&#39;,
+ &#39;gt3l/land_segments/canopy/subset_can_flag&#39;,
+ &#39;gt3l/land_segments/canopy/toc_roughness&#39;,
+ &#39;gt3l/land_segments/cloud_flag_atm&#39;,
+ &#39;gt3l/land_segments/cloud_fold_flag&#39;,
+ &#39;gt3l/land_segments/delta_time&#39;,
+ &#39;gt3l/land_segments/delta_time_beg&#39;,
+ &#39;gt3l/land_segments/delta_time_end&#39;,
+ &#39;gt3l/land_segments/dem_flag&#39;,
+ &#39;gt3l/land_segments/dem_h&#39;,
+ &#39;gt3l/land_segments/dem_removal_flag&#39;,
+ &#39;gt3l/land_segments/h_dif_ref&#39;,
+ &#39;gt3l/land_segments/last_seg_extend&#39;,
+ &#39;gt3l/land_segments/latitude&#39;,
+ &#39;gt3l/land_segments/latitude_20m&#39;,
+ &#39;gt3l/land_segments/layer_flag&#39;,
+ &#39;gt3l/land_segments/longitude&#39;,
+ &#39;gt3l/land_segments/longitude_20m&#39;,
+ &#39;gt3l/land_segments/msw_flag&#39;,
+ &#39;gt3l/land_segments/n_seg_ph&#39;,
+ &#39;gt3l/land_segments/night_flag&#39;,
+ &#39;gt3l/land_segments/ph_ndx_beg&#39;,
+ &#39;gt3l/land_segments/ph_removal_flag&#39;,
+ &#39;gt3l/land_segments/psf_flag&#39;,
+ &#39;gt3l/land_segments/rgt&#39;,
+ &#39;gt3l/land_segments/sat_flag&#39;,
+ &#39;gt3l/land_segments/segment_id_beg&#39;,
+ &#39;gt3l/land_segments/segment_id_end&#39;,
+ &#39;gt3l/land_segments/segment_landcover&#39;,
+ &#39;gt3l/land_segments/segment_snowcover&#39;,
+ &#39;gt3l/land_segments/segment_watermask&#39;,
+ &#39;gt3l/land_segments/sigma_across&#39;,
+ &#39;gt3l/land_segments/sigma_along&#39;,
+ &#39;gt3l/land_segments/sigma_atlas_land&#39;,
+ &#39;gt3l/land_segments/sigma_h&#39;,
+ &#39;gt3l/land_segments/sigma_topo&#39;,
+ &#39;gt3l/land_segments/snr&#39;,
+ &#39;gt3l/land_segments/solar_azimuth&#39;,
+ &#39;gt3l/land_segments/solar_elevation&#39;,
+ &#39;gt3l/land_segments/surf_type&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_best_fit&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_best_fit_20m&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_interp&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_max&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_mean&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_median&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_min&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_mode&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_rh25&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_skew&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_std&#39;,
+ &#39;gt3l/land_segments/terrain/h_te_uncertainty&#39;,
+ &#39;gt3l/land_segments/terrain/n_te_photons&#39;,
+ &#39;gt3l/land_segments/terrain/photon_rate_te&#39;,
+ &#39;gt3l/land_segments/terrain/subset_te_flag&#39;,
+ &#39;gt3l/land_segments/terrain/terrain_slope&#39;,
+ &#39;gt3l/land_segments/terrain_flg&#39;,
+ &#39;gt3l/land_segments/urban_flag&#39;,
+ &#39;gt3l/signal_photons/classed_pc_flag&#39;,
+ &#39;gt3l/signal_photons/classed_pc_indx&#39;,
+ &#39;gt3l/signal_photons/d_flag&#39;,
+ &#39;gt3l/signal_photons/delta_time&#39;,
+ &#39;gt3l/signal_photons/ph_h&#39;,
+ &#39;gt3l/signal_photons/ph_segment_id&#39;,
+ &#39;gt3r/land_segments/asr&#39;,
+ &#39;gt3r/land_segments/atlas_pa&#39;,
+ &#39;gt3r/land_segments/beam_azimuth&#39;,
+ &#39;gt3r/land_segments/beam_coelev&#39;,
+ &#39;gt3r/land_segments/brightness_flag&#39;,
+ &#39;gt3r/land_segments/canopy/can_noise&#39;,
+ &#39;gt3r/land_segments/canopy/canopy_h_metrics&#39;,
+ &#39;gt3r/land_segments/canopy/canopy_h_metrics_abs&#39;,
+ &#39;gt3r/land_segments/canopy/canopy_openness&#39;,
+ &#39;gt3r/land_segments/canopy/canopy_rh_conf&#39;,
+ &#39;gt3r/land_segments/canopy/centroid_height&#39;,
+ &#39;gt3r/land_segments/canopy/h_canopy&#39;,
+ &#39;gt3r/land_segments/canopy/h_canopy_20m&#39;,
+ &#39;gt3r/land_segments/canopy/h_canopy_abs&#39;,
+ &#39;gt3r/land_segments/canopy/h_canopy_quad&#39;,
+ &#39;gt3r/land_segments/canopy/h_canopy_uncertainty&#39;,
+ &#39;gt3r/land_segments/canopy/h_dif_canopy&#39;,
+ &#39;gt3r/land_segments/canopy/h_max_canopy&#39;,
+ &#39;gt3r/land_segments/canopy/h_max_canopy_abs&#39;,
+ &#39;gt3r/land_segments/canopy/h_mean_canopy&#39;,
+ &#39;gt3r/land_segments/canopy/h_mean_canopy_abs&#39;,
+ &#39;gt3r/land_segments/canopy/h_median_canopy&#39;,
+ &#39;gt3r/land_segments/canopy/h_median_canopy_abs&#39;,
+ &#39;gt3r/land_segments/canopy/h_min_canopy&#39;,
+ &#39;gt3r/land_segments/canopy/h_min_canopy_abs&#39;,
+ &#39;gt3r/land_segments/canopy/n_ca_photons&#39;,
+ &#39;gt3r/land_segments/canopy/n_toc_photons&#39;,
+ &#39;gt3r/land_segments/canopy/photon_rate_can&#39;,
+ &#39;gt3r/land_segments/canopy/photon_rate_can_nr&#39;,
+ &#39;gt3r/land_segments/canopy/segment_cover&#39;,
+ &#39;gt3r/land_segments/canopy/subset_can_flag&#39;,
+ &#39;gt3r/land_segments/canopy/toc_roughness&#39;,
+ &#39;gt3r/land_segments/cloud_flag_atm&#39;,
+ &#39;gt3r/land_segments/cloud_fold_flag&#39;,
+ &#39;gt3r/land_segments/delta_time&#39;,
+ &#39;gt3r/land_segments/delta_time_beg&#39;,
+ &#39;gt3r/land_segments/delta_time_end&#39;,
+ &#39;gt3r/land_segments/dem_flag&#39;,
+ &#39;gt3r/land_segments/dem_h&#39;,
+ &#39;gt3r/land_segments/dem_removal_flag&#39;,
+ &#39;gt3r/land_segments/h_dif_ref&#39;,
+ &#39;gt3r/land_segments/last_seg_extend&#39;,
+ &#39;gt3r/land_segments/latitude&#39;,
+ &#39;gt3r/land_segments/latitude_20m&#39;,
+ &#39;gt3r/land_segments/layer_flag&#39;,
+ &#39;gt3r/land_segments/longitude&#39;,
+ &#39;gt3r/land_segments/longitude_20m&#39;,
+ &#39;gt3r/land_segments/msw_flag&#39;,
+ &#39;gt3r/land_segments/n_seg_ph&#39;,
+ &#39;gt3r/land_segments/night_flag&#39;,
+ &#39;gt3r/land_segments/ph_ndx_beg&#39;,
+ &#39;gt3r/land_segments/ph_removal_flag&#39;,
+ &#39;gt3r/land_segments/psf_flag&#39;,
+ &#39;gt3r/land_segments/rgt&#39;,
+ &#39;gt3r/land_segments/sat_flag&#39;,
+ &#39;gt3r/land_segments/segment_id_beg&#39;,
+ &#39;gt3r/land_segments/segment_id_end&#39;,
+ &#39;gt3r/land_segments/segment_landcover&#39;,
+ &#39;gt3r/land_segments/segment_snowcover&#39;,
+ &#39;gt3r/land_segments/segment_watermask&#39;,
+ &#39;gt3r/land_segments/sigma_across&#39;,
+ &#39;gt3r/land_segments/sigma_along&#39;,
+ &#39;gt3r/land_segments/sigma_atlas_land&#39;,
+ &#39;gt3r/land_segments/sigma_h&#39;,
+ &#39;gt3r/land_segments/sigma_topo&#39;,
+ &#39;gt3r/land_segments/snr&#39;,
+ &#39;gt3r/land_segments/solar_azimuth&#39;,
+ &#39;gt3r/land_segments/solar_elevation&#39;,
+ &#39;gt3r/land_segments/surf_type&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_best_fit&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_best_fit_20m&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_interp&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_max&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_mean&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_median&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_min&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_mode&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_rh25&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_skew&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_std&#39;,
+ &#39;gt3r/land_segments/terrain/h_te_uncertainty&#39;,
+ &#39;gt3r/land_segments/terrain/n_te_photons&#39;,
+ &#39;gt3r/land_segments/terrain/photon_rate_te&#39;,
+ &#39;gt3r/land_segments/terrain/subset_te_flag&#39;,
+ &#39;gt3r/land_segments/terrain/terrain_slope&#39;,
+ &#39;gt3r/land_segments/terrain_flg&#39;,
+ &#39;gt3r/land_segments/urban_flag&#39;,
+ &#39;gt3r/signal_photons/classed_pc_flag&#39;,
+ &#39;gt3r/signal_photons/classed_pc_indx&#39;,
+ &#39;gt3r/signal_photons/d_flag&#39;,
+ &#39;gt3r/signal_photons/delta_time&#39;,
+ &#39;gt3r/signal_photons/ph_h&#39;,
+ &#39;gt3r/signal_photons/ph_segment_id&#39;,
+ &#39;orbit_info/bounding_polygon_lat1&#39;,
+ &#39;orbit_info/bounding_polygon_lon1&#39;,
+ &#39;orbit_info/crossing_time&#39;,
+ &#39;orbit_info/cycle_number&#39;,
+ &#39;orbit_info/lan&#39;,
+ &#39;orbit_info/orbit_number&#39;,
+ &#39;orbit_info/rgt&#39;,
+ &#39;orbit_info/sc_orient&#39;,
+ &#39;orbit_info/sc_orient_time&#39;,
+ &#39;quality_assessment/qa_granule_fail_reason&#39;,
+ &#39;quality_assessment/qa_granule_pass_fail&#39;]
+</pre></div>
+</div>
+</div>
+</div>
+<p>Thats <strong>a lot</strong> of variables!</p>
+<p>One key feature of icepyx is the ability to browse the variables available in the dataset. There are typically hundreds of variables in a single dataset, so that is a lot to sort through! Let’s take a moment to get oriented to the organization of ATL08 variables, by first a few important pieces of the algorithm.</p>
+<p>To create higher level variables like canopy or terrain height, the ATL08 algorithms goes through a series of steps:</p>
+<ol class="simple">
+<li><p>Identify signal photons from noise photons</p></li>
+<li><p>Classify each of the signal photons as either terrain, canopy, or canopy top</p></li>
+<li><p>Remove elevation, so the heights are with respect to the ground</p></li>
+<li><p>Group the signal photons into 100m segments. If there are a sufficient number of photons in that group, calculate statistics for terrain and canopy (ex. mean height, max height, standard deviation, etc.)</p></li>
+</ol>
+<blockquote>
+<div><p><em>Fig. 4. An example of the classified photons produced from the ATL08 algorithm. Ground photons (red dots) are labeled as all photons falling within a point spread function distance of the estimated ground surface. The top of canopy photons (green dots) are photons that fall within a buffer distance from the upper canopy surface, and the photons that lie between the top of canopy surface and ground surface are labeled as canopy photons (blue dots).</em> (Neuenschwander &amp; Pitts, 2019)</p>
+</div></blockquote>
+<p>Providing all the potentially useful information from all these processing steps results in a data file that looks like:</p>
+<p>Another way to visualize these structure is to download one file and open it using <a class="reference external" href="https://myhdf5.hdfgroup.org/">https://myhdf5.hdfgroup.org/</a>.</p>
+<p>Further information about each one of the variables is available in the <a class="reference external" href="https://icesat-2.gsfc.nasa.gov/sites/default/files/page_files/ICESat2_ATL08_ATBD_r006.pdf">Algorithm Theoretical Basis Document (ATBD)</a> for ATL08.</p>
+<p>There is lots to explore in these variables, but we will move forward using a common ATL08 variable: <code class="docutils literal notranslate"><span class="pre">h_canopy</span></code>, or the “98% height of all the individual relative canopy heights (height above terrain)” (ATBD definition).</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">reader</span><span class="o">.</span><span class="n">vars</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">var_list</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;h_canopy&#39;</span><span class="p">,</span> <span class="s1">&#39;latitude&#39;</span><span class="p">,</span> <span class="s1">&#39;longitude&#39;</span><span class="p">])</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Note that adding variables is a required step before you can load the data.</p>
+</section>
+<section id="load-the-data">
+<h3>Load the data!<a class="headerlink" href="#load-the-data" title="Permalink to this headline">#</a></h3>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># turn off warnings for load to not show an xarray warning that was resolved in the coming release of icepyx v1.0.0</span>
+<span class="k">with</span> <span class="n">warnings</span><span class="o">.</span><span class="n">catch_warnings</span><span class="p">(</span><span class="n">record</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>    
+    <span class="n">ds</span> <span class="o">=</span> <span class="n">reader</span><span class="o">.</span><span class="n">load</span><span class="p">()</span>
+
+<span class="n">ds</span>
+</pre></div>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;
+Dimensions:              (gran_idx: 1, photon_idx: 211, spot: 2)
+Coordinates:
+  * gran_idx             (gran_idx) float64 5.54e+04
+  * photon_idx           (photon_idx) int64 0 1 2 3 4 5 ... 206 207 208 209 210
+  * spot                 (spot) uint8 1 2
+    source_file          (gran_idx) &lt;U74 &#x27;./bosque_primavera_ATL08/processed_...
+    delta_time           (photon_idx) datetime64[ns] 2019-05-04T12:47:13.5766...
+Data variables:
+    sc_orient            (gran_idx) int8 0
+    cycle_number         (gran_idx) int8 3
+    rgt                  (gran_idx, spot, photon_idx) float32 554.0 ... 554.0
+    atlas_sdp_gps_epoch  (gran_idx) datetime64[ns] 2018-01-01T00:00:18
+    data_start_utc       (gran_idx) datetime64[ns] 2019-05-04T12:46:31.876322
+    data_end_utc         (gran_idx) datetime64[ns] 2019-05-04T12:48:54.200826
+    latitude             (spot, gran_idx, photon_idx) float32 20.59 ... 20.73
+    longitude            (spot, gran_idx, photon_idx) float32 -103.7 ... -103.7
+    gt                   (gran_idx, spot) object &#x27;gt3l&#x27; &#x27;gt3r&#x27;
+    h_canopy             (photon_idx) float32 12.12 4.747 11.83 ... nan nan nan
+Attributes:
+    data_product:  ATL08
+    Description:   Contains data categorized as land at 100 meter intervals.
+    data_rate:     Data are stored as aggregates of 100 meters.</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d1b6461a-0c9a-4ce8-8ad7-2e280618b6ea' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d1b6461a-0c9a-4ce8-8ad7-2e280618b6ea' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>gran_idx</span>: 1</li><li><span class='xr-has-index'>photon_idx</span>: 211</li><li><span class='xr-has-index'>spot</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-cbe50fe0-c127-4af1-a2e8-5a072e8a56c0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cbe50fe0-c127-4af1-a2e8-5a072e8a56c0' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>gran_idx</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.54e+04</div><input id='attrs-3a7e4163-637c-4efc-aeb5-9f86c1813126' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3a7e4163-637c-4efc-aeb5-9f86c1813126' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07596e09-7912-47f5-bd10-ad11aefbc1ef' class='xr-var-data-in' type='checkbox'><label for='data-07596e09-7912-47f5-bd10-ad11aefbc1ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([55402.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>photon_idx</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 206 207 208 209 210</div><input id='attrs-3e0759ae-cd38-4ec9-bd91-831903435d4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e0759ae-cd38-4ec9-bd91-831903435d4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8a8cbbf-cc4b-49dd-b4f6-f7f4bd619fd9' class='xr-var-data-in' type='checkbox'><label for='data-e8a8cbbf-cc4b-49dd-b4f6-f7f4bd619fd9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 208, 209, 210])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spot</span></div><div class='xr-var-dims'>(spot)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>1 2</div><input id='attrs-e6335c68-10e3-43a9-a171-cc87ad2f1585' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6335c68-10e3-43a9-a171-cc87ad2f1585' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a11bcf5a-ac22-4363-b535-80bea3c55c60' class='xr-var-data-in' type='checkbox'><label for='data-a11bcf5a-ac22-4363-b535-80bea3c55c60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_file</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>&lt;U74</div><div class='xr-var-preview xr-preview'>&#x27;./bosque_primavera_ATL08/proces...</div><input id='attrs-f91428ac-b128-424e-9c9a-0ed21ba014be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f91428ac-b128-424e-9c9a-0ed21ba014be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6999471-7560-433c-a6fe-94a280aee714' class='xr-var-data-in' type='checkbox'><label for='data-a6999471-7560-433c-a6fe-94a280aee714' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;./bosque_primavera_ATL08/processed_ATL08_20190504124152_05540301_006_02.h5&#x27;],
+      dtype=&#x27;&lt;U74&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta_time</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:47:13.576668792 .....</div><input id='attrs-a96644f6-ae49-461d-9409-88da3ec843e5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a96644f6-ae49-461d-9409-88da3ec843e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec5cdcdf-c644-4c62-8da5-2cfd78c2e743' class='xr-var-data-in' type='checkbox'><label for='data-ec5cdcdf-c644-4c62-8da5-2cfd78c2e743' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:47:13.576668792&#x27;, &#x27;2019-05-04T12:47:13.590795176&#x27;,
+       &#x27;2019-05-04T12:47:13.604878696&#x27;, &#x27;2019-05-04T12:47:13.618858776&#x27;,
+       &#x27;2019-05-04T12:47:13.647116752&#x27;, &#x27;2019-05-04T12:47:13.731658440&#x27;,
+       &#x27;2019-05-04T12:47:13.788115696&#x27;, &#x27;2019-05-04T12:47:13.802188288&#x27;,
+       &#x27;2019-05-04T12:47:14.013615136&#x27;, &#x27;2019-05-04T12:47:14.027716720&#x27;,
+       &#x27;2019-05-04T12:47:14.041828320&#x27;, &#x27;2019-05-04T12:47:14.069985944&#x27;,
+       &#x27;2019-05-04T12:47:14.084116656&#x27;, &#x27;2019-05-04T12:47:14.098204416&#x27;,
+       &#x27;2019-05-04T12:47:14.112308544&#x27;, &#x27;2019-05-04T12:47:14.126439192&#x27;,
+       &#x27;2019-05-04T12:47:14.140474800&#x27;, &#x27;2019-05-04T12:47:14.154503088&#x27;,
+       &#x27;2019-05-04T12:47:14.168615944&#x27;, &#x27;2019-05-04T12:47:14.182727944&#x27;,
+       &#x27;2019-05-04T12:47:14.196803520&#x27;, &#x27;2019-05-04T12:47:14.225002096&#x27;,
+       &#x27;2019-05-04T12:47:14.239145008&#x27;, &#x27;2019-05-04T12:47:14.253240544&#x27;,
+       &#x27;2019-05-04T12:47:14.267282136&#x27;, &#x27;2019-05-04T12:47:14.281345400&#x27;,
+       &#x27;2019-05-04T12:47:14.295463616&#x27;, &#x27;2019-05-04T12:47:14.309582960&#x27;,
+       &#x27;2019-05-04T12:47:14.323643288&#x27;, &#x27;2019-05-04T12:47:14.337699200&#x27;,
+       &#x27;2019-05-04T12:47:14.351769576&#x27;, &#x27;2019-05-04T12:47:14.363045864&#x27;,
+       &#x27;2019-05-04T12:47:14.379987728&#x27;, &#x27;2019-05-04T12:47:14.394098040&#x27;,
+       &#x27;2019-05-04T12:47:14.408184296&#x27;, &#x27;2019-05-04T12:47:14.422336984&#x27;,
+       &#x27;2019-05-04T12:47:14.436399800&#x27;, &#x27;2019-05-04T12:47:14.450439312&#x27;,
+       &#x27;2019-05-04T12:47:14.464605056&#x27;, &#x27;2019-05-04T12:47:14.478736368&#x27;,
+...
+       &#x27;2019-05-04T12:47:15.425911016&#x27;, &#x27;2019-05-04T12:47:15.439995088&#x27;,
+       &#x27;2019-05-04T12:47:15.454061472&#x27;, &#x27;2019-05-04T12:47:15.468143592&#x27;,
+       &#x27;2019-05-04T12:47:15.482238848&#x27;, &#x27;2019-05-04T12:47:15.496324880&#x27;,
+       &#x27;2019-05-04T12:47:15.510409496&#x27;, &#x27;2019-05-04T12:47:15.524510280&#x27;,
+       &#x27;2019-05-04T12:47:15.538615648&#x27;, &#x27;2019-05-04T12:47:15.566816696&#x27;,
+       &#x27;2019-05-04T12:47:15.580919696&#x27;, &#x27;2019-05-04T12:47:15.594985688&#x27;,
+       &#x27;2019-05-04T12:47:15.609048944&#x27;, &#x27;2019-05-04T12:47:15.623173096&#x27;,
+       &#x27;2019-05-04T12:47:15.637281512&#x27;, &#x27;2019-05-04T12:47:15.651381832&#x27;,
+       &#x27;2019-05-04T12:47:15.665494736&#x27;, &#x27;2019-05-04T12:47:15.679564576&#x27;,
+       &#x27;2019-05-04T12:47:15.693640304&#x27;, &#x27;2019-05-04T12:47:15.707745176&#x27;,
+       &#x27;2019-05-04T12:47:15.721833264&#x27;, &#x27;2019-05-04T12:47:15.735931400&#x27;,
+       &#x27;2019-05-04T12:47:15.750026272&#x27;, &#x27;2019-05-04T12:47:15.764102288&#x27;,
+       &#x27;2019-05-04T12:47:15.778227184&#x27;, &#x27;2019-05-04T12:47:15.806428968&#x27;,
+       &#x27;2019-05-04T12:47:15.820523432&#x27;, &#x27;2019-05-04T12:47:15.834607024&#x27;,
+       &#x27;2019-05-04T12:47:15.848673504&#x27;, &#x27;2019-05-04T12:47:15.862757488&#x27;,
+       &#x27;2019-05-04T12:47:15.876856944&#x27;, &#x27;2019-05-04T12:47:15.890974768&#x27;,
+       &#x27;2019-05-04T12:47:15.905085432&#x27;, &#x27;2019-05-04T12:47:15.919119064&#x27;,
+       &#x27;2019-05-04T12:47:15.933193432&#x27;, &#x27;2019-05-04T12:47:15.947348696&#x27;,
+       &#x27;2019-05-04T12:47:15.961461904&#x27;, &#x27;2019-05-04T12:47:15.975561616&#x27;,
+       &#x27;2019-05-04T12:47:15.989663088&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f424906-f54c-4fde-9495-7014639dc333' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0f424906-f54c-4fde-9495-7014639dc333' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sc_orient</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-df1f4257-676f-4c33-91c3-260e35e3d730' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-df1f4257-676f-4c33-91c3-260e35e3d730' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c188cce-6a32-403e-b610-b94e3fcff4c9' class='xr-var-data-in' type='checkbox'><label for='data-1c188cce-6a32-403e-b610-b94e3fcff4c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cycle_number</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>3</div><input id='attrs-7cdc0af6-d6fd-4597-850e-6634582eea76' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7cdc0af6-d6fd-4597-850e-6634582eea76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a29506e1-b2c3-4dbb-ba27-6e1d62abf776' class='xr-var-data-in' type='checkbox'><label for='data-a29506e1-b2c3-4dbb-ba27-6e1d62abf776' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rgt</span></div><div class='xr-var-dims'>(gran_idx, spot, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>554.0 554.0 554.0 ... 554.0 554.0</div><input id='attrs-73eae40f-eafe-407f-840d-d2893f346e54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73eae40f-eafe-407f-840d-d2893f346e54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd0f701e-9510-458f-a826-5f58a5a3ade6' class='xr-var-data-in' type='checkbox'><label for='data-dd0f701e-9510-458f-a826-5f58a5a3ade6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>The reference ground track (RGT) is the track on the earth at which a specified unit vector within the observatory is pointed. Under nominal operating conditions, there will be no data collected along the RGT, as the RGT is spanned by GT3 and GT4.  During slews or off-pointing, it is possible that ground tracks may intersect the RGT. The ICESat-2 mission has 1387 RGTs.</dd><dt><span>long_name :</span></dt><dd>reference ground track</dd><dt><span>source :</span></dt><dd>Operations</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>1387</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+...
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554.]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>atlas_sdp_gps_epoch</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01T00:00:18</div><input id='attrs-11ea1c90-bd5d-4c0e-ac89-1876ba894ddf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-11ea1c90-bd5d-4c0e-ac89-1876ba894ddf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac201fb3-6366-4644-9a60-cbe1dad33039' class='xr-var-data-in' type='checkbox'><label for='data-ac201fb3-6366-4644-9a60-cbe1dad33039' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:18.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_start_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:46:31.876322</div><input id='attrs-db1a681d-8007-4ea6-8df8-6e5a86ee15a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db1a681d-8007-4ea6-8df8-6e5a86ee15a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8d4be77-b088-47b1-b459-c40e794b2727' class='xr-var-data-in' type='checkbox'><label for='data-b8d4be77-b088-47b1-b459-c40e794b2727' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:46:31.876322000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_end_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:48:54.200826</div><input id='attrs-e19e5be0-5689-488d-a195-d8471d49992c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e19e5be0-5689-488d-a195-d8471d49992c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04d60e55-ae5a-4c7f-8af0-55b9f9259d97' class='xr-var-data-in' type='checkbox'><label for='data-04d60e55-ae5a-4c7f-8af0-55b9f9259d97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:48:54.200826000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.59 20.59 20.59 ... 20.72 20.73</div><input id='attrs-749c1d12-74cc-4c89-9f24-ab553af3c414' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-749c1d12-74cc-4c89-9f24-ab553af3c414' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbf7465f-2b1e-4ac7-b9fc-305ff55386f4' class='xr-var-data-in' type='checkbox'><label for='data-bbf7465f-2b1e-4ac7-b9fc-305ff55386f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Latitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([[[20.592943, 20.593845, 20.594746, 20.595648, 20.59745 ,
+         20.60286 , 20.606464, 20.607367, 20.620888, 20.621788,
+         20.62269 , 20.624493, 20.625395, 20.626297, 20.627197,
+         20.6281  , 20.629   , 20.629902, 20.630804, 20.631704,
+         20.632607, 20.634409, 20.635311, 20.636211, 20.637114,
+         20.638014, 20.638916, 20.639816, 20.640718, 20.64162 ,
+         20.642523, 20.643244, 20.644325, 20.645226, 20.646128,
+         20.64703 , 20.64793 , 20.648832, 20.649734, 20.650635,
+         20.651537, 20.652437, 20.65334 , 20.65424 , 20.655142,
+         20.656044, 20.656944, 20.657846, 20.658749, 20.659649,
+         20.660551, 20.661451, 20.662354, 20.663254, 20.664156,
+         20.665058, 20.665958, 20.66686 , 20.667763, 20.668663,
+         20.669565, 20.670467, 20.671368, 20.67227 , 20.67317 ,
+         20.674072, 20.674973, 20.675875, 20.676777, 20.677677,
+         20.67858 , 20.679482, 20.680382, 20.681284, 20.682184,
+         20.683086, 20.683989, 20.684889, 20.685791, 20.686691,
+         20.687593, 20.688496, 20.689217, 20.690298, 20.691198,
+         20.6921  , 20.693003, 20.693903, 20.694805, 20.695707,
+         20.696608, 20.69751 , 20.69841 , 20.699312, 20.700212,
+         20.701115, 20.702017, 20.702917, 20.70382 , 20.704721,
+...
+               nan,       nan,       nan,       nan,       nan,
+         20.625654, 20.626554, 20.627457, 20.628359, 20.635569,
+         20.63647 , 20.637373, 20.638273, 20.639175, 20.640078,
+         20.640978, 20.644585, 20.646387, 20.647287, 20.64819 ,
+         20.649992, 20.650894, 20.651796, 20.652697, 20.653599,
+         20.655401, 20.656303, 20.657204, 20.658106, 20.659006,
+         20.659908, 20.662613, 20.663513, 20.664415, 20.666218,
+         20.66712 , 20.66802 , 20.668922, 20.669825, 20.670725,
+         20.671627, 20.672527, 20.67343 , 20.674332, 20.675232,
+         20.676134, 20.677036, 20.677937, 20.678839, 20.679739,
+         20.680641, 20.681543, 20.682444, 20.68605 , 20.68695 ,
+         20.687853, 20.688753, 20.689655, 20.690557, 20.691458,
+         20.69236 , 20.693262, 20.694162, 20.695065, 20.695965,
+         20.696867, 20.69867 , 20.699572, 20.700472, 20.701374,
+         20.702274, 20.703176, 20.704079, 20.704979, 20.705881,
+         20.706781, 20.707684, 20.708586, 20.709486, 20.710388,
+         20.711288, 20.71219 , 20.713993, 20.714895, 20.715796,
+         20.716698, 20.7176  , 20.7185  , 20.719402, 20.720304,
+         20.721205, 20.722107, 20.723007, 20.72391 , 20.724812,
+         20.725712]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-103.7 -103.7 ... -103.7 -103.7</div><input id='attrs-4ce0e933-3786-46d6-b3ec-f839a00f95f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ce0e933-3786-46d6-b3ec-f839a00f95f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b675e97-21da-4234-91b1-9a6baab74fd8' class='xr-var-data-in' type='checkbox'><label for='data-3b675e97-21da-4234-91b1-9a6baab74fd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Longitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([[[-103.67242 , -103.672516, -103.67261 , -103.6727  ,
+         -103.6729  , -103.67346 , -103.673836, -103.673935,
+         -103.67535 , -103.675446, -103.67554 , -103.67573 ,
+         -103.67583 , -103.67592 , -103.67601 , -103.67611 ,
+         -103.6762  , -103.6763  , -103.67639 , -103.67649 ,
+         -103.67658 , -103.676765, -103.676865, -103.676956,
+         -103.67705 , -103.67715 , -103.677246, -103.677345,
+         -103.67743 , -103.67753 , -103.67762 , -103.6777  ,
+         -103.67781 , -103.67791 , -103.678   , -103.678085,
+         -103.678185, -103.67828 , -103.678375, -103.678474,
+         -103.678566, -103.67866 , -103.67876 , -103.678856,
+         -103.67895 , -103.67904 , -103.67913 , -103.67922 ,
+         -103.67932 , -103.67941 , -103.679504, -103.6796  ,
+         -103.6797  , -103.6798  , -103.67989 , -103.679985,
+         -103.68008 , -103.680176, -103.68027 , -103.68037 ,
+         -103.68046 , -103.68055 , -103.68064 , -103.68073 ,
+         -103.68083 , -103.68093 , -103.68103 , -103.68112 ,
+         -103.68121 , -103.681305, -103.6814  , -103.68149 ,
+         -103.68159 , -103.68169 , -103.681786, -103.68188 ,
+         -103.68197 , -103.68207 , -103.68216 , -103.68226 ,
+...
+         -103.67717 , -103.67727 , -103.67736 , -103.67754 ,
+         -103.67764 , -103.677734, -103.67783 , -103.677925,
+         -103.678116, -103.67821 , -103.67831 , -103.6784  ,
+         -103.6785  , -103.67859 , -103.67887 , -103.67897 ,
+         -103.67906 , -103.67925 , -103.679344, -103.67944 ,
+         -103.679535, -103.67963 , -103.67972 , -103.67982 ,
+         -103.67991 , -103.68001 , -103.6801  , -103.68019 ,
+         -103.68029 , -103.68038 , -103.68047 , -103.68057 ,
+         -103.68067 , -103.68076 , -103.680855, -103.680954,
+         -103.68133 , -103.68143 , -103.68152 , -103.68161 ,
+         -103.68171 , -103.6818  , -103.68189 , -103.681984,
+         -103.68208 , -103.68218 , -103.682274, -103.682365,
+         -103.682465, -103.682655, -103.682755, -103.682846,
+         -103.68294 , -103.68304 , -103.68313 , -103.68322 ,
+         -103.68332 , -103.68341 , -103.68351 , -103.6836  ,
+         -103.68369 , -103.68379 , -103.68388 , -103.68398 ,
+         -103.684074, -103.684265, -103.68436 , -103.684456,
+         -103.68455 , -103.68465 , -103.68474 , -103.68483 ,
+         -103.68493 , -103.68502 , -103.68511 , -103.68521 ,
+         -103.6853  , -103.6854  , -103.68549 ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gt</span></div><div class='xr-var-dims'>(gran_idx, spot)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;gt3l&#x27; &#x27;gt3r&#x27;</div><input id='attrs-1a0f3f75-3070-4a81-abe6-ac7e60356c6d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a0f3f75-3070-4a81-abe6-ac7e60356c6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-488e4c41-132f-425f-9287-4f5b884faca9' class='xr-var-data-in' type='checkbox'><label for='data-488e4c41-132f-425f-9287-4f5b884faca9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;gt3l&#x27;, &#x27;gt3r&#x27;]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_canopy</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.12 4.747 11.83 ... nan nan nan</div><input id='attrs-1b2b4e27-855f-447c-80ad-df560a16cb3d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b2b4e27-855f-447c-80ad-df560a16cb3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c4c8918-4b68-4909-8b00-9021b0ca7ef8' class='xr-var-data-in' type='checkbox'><label for='data-7c4c8918-4b68-4909-8b00-9021b0ca7ef8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>98% height of all the individual canopy relative heights for the segment above the estimated terrain surface. Relative canopy heights have been computed by differencing the canopy photon height from the estimated terrain surface.</dd><dt><span>long_name :</span></dt><dd>height canopy</dd><dt><span>source :</span></dt><dd>Land ATBD section 4.12</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([12.117554 ,  4.7471924, 11.826294 , 12.599121 ,        nan,
+       18.487427 ,        nan, 24.531128 , 23.573975 ,  6.973877 ,
+       15.614014 , 18.686768 , 10.208862 , 19.486816 , 19.792969 ,
+       24.182617 , 26.141113 ,        nan, 27.215698 , 27.964355 ,
+       28.768066 , 23.500977 , 20.939087 , 12.468384 , 12.3302   ,
+       12.56543  , 18.28833  ,        nan,  3.2608643, 15.973389 ,
+       20.57251  , 16.383667 , 19.53479  , 19.167236 ,  8.956299 ,
+       10.339844 ,  6.9119873,        nan,  6.6381836, 13.006592 ,
+       10.125366 ,  7.1741943,  6.220581 , 13.171265 , 13.741211 ,
+       14.266846 , 13.998291 ,  6.2819824, 10.767212 ,        nan,
+       11.753906 , 19.83789  ,  8.949463 ,  6.9605713, 17.22107  ,
+       20.040527 ,  8.8289795, 10.093262 ,  6.963379 , 10.654053 ,
+       13.63623  ,  8.8897705,        nan,  8.487671 ,  4.117676 ,
+        2.7399902,  5.741211 ,  9.786987 ,  5.447876 ,  6.3466797,
+        2.6264648,        nan,        nan, 14.463623 , 19.986572 ,
+       26.920166 , 23.636475 , 20.366577 , 23.44165  , 18.091675 ,
+       12.490723 , 21.749268 , 10.508667 , 18.734863 , 16.601318 ,
+        7.385254 ,        nan,        nan,  9.800293 ,  5.3067627,
+       12.211426 , 15.874878 ,  8.875732 , 15.800903 , 12.877563 ,
+              nan,        nan,  2.3807373,  6.1132812,        nan,
+...
+              nan,  5.647461 ,  8.42688  ,        nan,        nan,
+       28.482422 , 41.51538  , 36.190186 , 44.303833 , 54.733765 ,
+       48.05542  , 30.716309 ,        nan, 23.340576 , 38.804565 ,
+       44.656982 , 30.472778 , 22.952637 , 12.519897 , 16.93335  ,
+       30.526001 , 30.635742 , 20.736328 , 29.40503  , 11.497925 ,
+       20.793457 , 15.886963 , 18.502075 , 12.783813 ,        nan,
+              nan, 16.045044 , 12.643677 , 13.928345 , 10.867432 ,
+        9.350586 ,  8.6102295, 20.031738 , 20.65039  ,  9.560913 ,
+       14.163574 , 16.621704 ,        nan,        nan,        nan,
+       10.887817 , 12.17334  , 11.110474 , 11.06665  , 10.12915  ,
+       11.172485 , 10.751099 ,  3.20813  , 16.136719 , 16.071533 ,
+       16.224487 , 18.876953 , 30.146606 , 22.111328 ,        nan,
+              nan,        nan,        nan, 12.220581 , 14.92688  ,
+              nan, 13.107788 ,  7.1689453,  7.2957764,        nan,
+              nan,        nan,        nan,        nan,  9.05249  ,
+              nan,        nan,        nan,        nan,        nan,
+              nan,        nan,        nan,        nan,        nan,
+              nan,        nan,        nan,        nan,        nan,
+              nan,        nan,        nan,        nan,        nan,
+              nan], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6cbc8ff6-5bdd-49d4-85ae-d5f0dc48b489' class='xr-section-summary-in' type='checkbox'  ><label for='section-6cbc8ff6-5bdd-49d4-85ae-d5f0dc48b489' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>gran_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-82639a85-888d-486f-8bf4-3b1e369f87b1' class='xr-index-data-in' type='checkbox'/><label for='index-82639a85-888d-486f-8bf4-3b1e369f87b1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([55402.0], dtype=&#x27;float64&#x27;, name=&#x27;gran_idx&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>photon_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ac7399d5-6c6c-4883-90a7-d33ada26fa51' class='xr-index-data-in' type='checkbox'/><label for='index-ac7399d5-6c6c-4883-90a7-d33ada26fa51' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
+            ...
+            201, 202, 203, 204, 205, 206, 207, 208, 209, 210],
+           dtype=&#x27;int64&#x27;, name=&#x27;photon_idx&#x27;, length=211))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spot</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9eae8a06-3857-491f-ab5a-1f630c35a7e8' class='xr-index-data-in' type='checkbox'/><label for='index-9eae8a06-3857-491f-ab5a-1f630c35a7e8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(UInt64Index([1, 2], dtype=&#x27;uint64&#x27;, name=&#x27;spot&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ea84d7ee-5f69-4484-8557-551c5e239939' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ea84d7ee-5f69-4484-8557-551c5e239939' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_product :</span></dt><dd>ATL08</dd><dt><span>Description :</span></dt><dd>Contains data categorized as land at 100 meter intervals.</dd><dt><span>data_rate :</span></dt><dd>Data are stored as aggregates of 100 meters.</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<p>Here we have an xarray Dataset, a common Python data structure for analysis. To visualize the data we can plot it using:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s2">&quot;longitude&quot;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">&quot;latitude&quot;</span><span class="p">,</span> <span class="n">hue</span><span class="o">=</span><span class="s2">&quot;h_canopy&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f2b0ac81390&gt;
+</pre></div>
+</div>
+<img alt="../../_images/4.icepyx_28_1.png" src="../../_images/4.icepyx_28_1.png" />
+</div>
+</div>
+<p>Notice also that the data is shown for just our area of interest! That is because of icepyx’s subsetting feature. You can find more details on this feature in the icepyx example gallery <a class="reference external" href="https://icepyx.readthedocs.io/en/latest/example_notebooks/IS2_data_access2-subsetting.html">here</a>.</p>
+</section>
+</section>
+<section id="when-to-cloud">
+<h2>When to Cloud<a class="headerlink" href="#when-to-cloud" title="Permalink to this headline">#</a></h2>
+<p>The astute user has by now noticed that in this tutorial we downloaded a granule to read in rather than directly reading it from an S3 bucket. Recall from the previous tutorial that reading a single group was a time intensive step and did not include multiple groups. Due to the way ICESat-2 data is stored on disk (because of the file format - it doesn’t matter if it’s a local disk or cloud disk), accessing the data within the file is really slow via the virtual file system. Several efforts are under way to help address this issue, and icepyx will implement them as soon as they are available. Current efforts include:</p>
+<ul class="simple">
+<li><p>storing ICESat-2 data in a cloud-optimized format</p></li>
+<li><p>reading data using the <a class="reference external" href="https://github.com/ICESat2-SlideRule/h5coro">h5coro</a> library</p></li>
+</ul>
+<p>Please let Amy, Jessica, or one of the workshop leads know if you’re interested in joining any of these conversations (or telling us what issues you’ve encountered). We’d love to have your input and use case!</p>
+</section>
+<section id="some-example-plots">
+<h2>Some example plots<a class="headerlink" href="#some-example-plots" title="Permalink to this headline">#</a></h2>
+<p>To close, here are a few more examples of reading and visualizing ATL08 data.</p>
+<section id="example-1-view-the-photon-classifications">
+<h3>Example 1: View the photon classifications<a class="headerlink" href="#example-1-view-the-photon-classifications" title="Permalink to this headline">#</a></h3>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Set up the data reader</span>
+<span class="n">pattern</span> <span class="o">=</span> <span class="s2">&quot;processed_ATL</span><span class="si">{product:2}</span><span class="s2">_{datetime:%Y%m</span><span class="si">%d</span><span class="s2">%H%M%S}_</span><span class="si">{rgt:4}{cycle:2}{orbitsegment:2}</span><span class="s2">_</span><span class="si">{version:3}</span><span class="s2">_</span><span class="si">{revision:2}</span><span class="s2">.h5&quot;</span>
+<span class="n">reader</span> <span class="o">=</span> <span class="n">ipx</span><span class="o">.</span><span class="n">Read</span><span class="p">(</span><span class="s1">&#39;./bosque_primavera_ATL08&#39;</span><span class="p">,</span> <span class="s2">&quot;ATL08&quot;</span><span class="p">,</span> <span class="n">pattern</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>You have 1 files matching the filename pattern to be read in.
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Add the photon height and classification variables</span>
+<span class="n">reader</span><span class="o">.</span><span class="n">vars</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">var_list</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;ph_h&#39;</span><span class="p">,</span> <span class="s1">&#39;classed_pc_flag&#39;</span><span class="p">,</span> <span class="s1">&#39;latitude&#39;</span><span class="p">,</span> <span class="s1">&#39;longitude&#39;</span><span class="p">])</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># turn off warnings for load to not show an xarray warning that was resolved in the coming release of icepyx v1.0.0</span>
+<span class="k">with</span> <span class="n">warnings</span><span class="o">.</span><span class="n">catch_warnings</span><span class="p">(</span><span class="n">record</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
+    <span class="c1"># load the dataset</span>
+    <span class="n">ds_photons</span> <span class="o">=</span> <span class="n">reader</span><span class="o">.</span><span class="n">load</span><span class="p">()</span>
+    
+<span class="n">ds_photons</span>
+</pre></div>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;
+Dimensions:              (gran_idx: 1, photon_idx: 25234, spot: 2)
+Coordinates:
+  * gran_idx             (gran_idx) float64 5.54e+04
+  * photon_idx           (photon_idx) int64 0 1 2 3 ... 25230 25231 25232 25233
+  * spot                 (spot) uint8 1 2
+    source_file          (gran_idx) &lt;U74 &#x27;./bosque_primavera_ATL08/processed_...
+    delta_time           (photon_idx) datetime64[ns] 2019-05-04T12:47:13.5766...
+Data variables:
+    sc_orient            (gran_idx) int8 0
+    cycle_number         (gran_idx) int8 3
+    rgt                  (gran_idx, spot, photon_idx) float32 554.0 ... nan
+    atlas_sdp_gps_epoch  (gran_idx) datetime64[ns] 2018-01-01T00:00:18
+    data_start_utc       (gran_idx) datetime64[ns] 2019-05-04T12:46:31.876322
+    data_end_utc         (gran_idx) datetime64[ns] 2019-05-04T12:48:54.200826
+    latitude             (spot, gran_idx, photon_idx) float32 20.59 ... nan
+    longitude            (spot, gran_idx, photon_idx) float32 -103.7 ... nan
+    gt                   (gran_idx, spot) &lt;U4 &#x27;gt3l&#x27; &#x27;gt3r&#x27;
+    ph_h                 (spot, gran_idx, photon_idx) float32 nan ... 0.05542
+    classed_pc_flag      (spot, gran_idx, photon_idx) float32 nan nan ... 1.0
+Attributes:
+    data_product:  ATL08</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3c158e7f-8099-4e8d-8713-dd8ce8eb6e38' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3c158e7f-8099-4e8d-8713-dd8ce8eb6e38' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>gran_idx</span>: 1</li><li><span class='xr-has-index'>photon_idx</span>: 25234</li><li><span class='xr-has-index'>spot</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e2201564-de81-483e-8f77-a40f90ff5386' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e2201564-de81-483e-8f77-a40f90ff5386' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>gran_idx</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.54e+04</div><input id='attrs-5786abc6-c256-45b8-beaf-f599263e56e2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5786abc6-c256-45b8-beaf-f599263e56e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4e36c04-bc35-4e34-9859-33b5e97e32aa' class='xr-var-data-in' type='checkbox'><label for='data-a4e36c04-bc35-4e34-9859-33b5e97e32aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([55402.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>photon_idx</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 25230 25231 25232 25233</div><input id='attrs-56d7551a-390c-425c-bd11-b3faad06a517' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56d7551a-390c-425c-bd11-b3faad06a517' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d047584-c11e-45d2-95ab-2bf980d38143' class='xr-var-data-in' type='checkbox'><label for='data-5d047584-c11e-45d2-95ab-2bf980d38143' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([    0,     1,     2, ..., 25231, 25232, 25233])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spot</span></div><div class='xr-var-dims'>(spot)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>1 2</div><input id='attrs-b5d2455f-30a1-42a2-9614-13df0cb6b110' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b5d2455f-30a1-42a2-9614-13df0cb6b110' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a74837e-c225-44f5-a78b-8376511c8597' class='xr-var-data-in' type='checkbox'><label for='data-3a74837e-c225-44f5-a78b-8376511c8597' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_file</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>&lt;U74</div><div class='xr-var-preview xr-preview'>&#x27;./bosque_primavera_ATL08/proces...</div><input id='attrs-5f2eedc1-4d07-463d-8d4a-1d43f671ecaf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f2eedc1-4d07-463d-8d4a-1d43f671ecaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d64f1d8-1e04-4459-b223-97110f841975' class='xr-var-data-in' type='checkbox'><label for='data-1d64f1d8-1e04-4459-b223-97110f841975' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;./bosque_primavera_ATL08/processed_ATL08_20190504124152_05540301_006_02.h5&#x27;],
+      dtype=&#x27;&lt;U74&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta_time</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:47:13.576668792 .....</div><input id='attrs-c57f6d87-fac8-456a-8167-b46fc764cbe1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c57f6d87-fac8-456a-8167-b46fc764cbe1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b43c71bd-2186-4aa0-91aa-c7471aba6609' class='xr-var-data-in' type='checkbox'><label for='data-b43c71bd-2186-4aa0-91aa-c7471aba6609' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:47:13.576668792&#x27;, &#x27;2019-05-04T12:47:13.590795176&#x27;,
+       &#x27;2019-05-04T12:47:13.604878696&#x27;, ...,
+       &#x27;2019-05-04T12:47:15.995923304&#x27;, &#x27;2019-05-04T12:47:15.996123296&#x27;,
+       &#x27;2019-05-04T12:47:15.996323304&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7083f307-17c6-4a5f-b0d7-e70680c30754' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7083f307-17c6-4a5f-b0d7-e70680c30754' class='xr-section-summary' >Data variables: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sc_orient</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-cf57ccd9-68f4-42f2-a8a5-27b28791aab0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf57ccd9-68f4-42f2-a8a5-27b28791aab0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb03ca80-89ba-47b7-9b05-68af71ad640e' class='xr-var-data-in' type='checkbox'><label for='data-eb03ca80-89ba-47b7-9b05-68af71ad640e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cycle_number</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>3</div><input id='attrs-2885be38-0c22-465c-8d0b-64d3a2e79c4b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2885be38-0c22-465c-8d0b-64d3a2e79c4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-235f47e7-4c49-472e-9af2-31f472de8e09' class='xr-var-data-in' type='checkbox'><label for='data-235f47e7-4c49-472e-9af2-31f472de8e09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rgt</span></div><div class='xr-var-dims'>(gran_idx, spot, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>554.0 554.0 554.0 ... nan nan nan</div><input id='attrs-4f14ba52-7351-4b74-b844-54ae9bbb6166' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f14ba52-7351-4b74-b844-54ae9bbb6166' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70c9fed7-e2f6-4ab2-8329-104d0beca9c0' class='xr-var-data-in' type='checkbox'><label for='data-70c9fed7-e2f6-4ab2-8329-104d0beca9c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>The reference ground track (RGT) is the track on the earth at which a specified unit vector within the observatory is pointed. Under nominal operating conditions, there will be no data collected along the RGT, as the RGT is spanned by GT3 and GT4.  During slews or off-pointing, it is possible that ground tracks may intersect the RGT. The ICESat-2 mission has 1387 RGTs.</dd><dt><span>long_name :</span></dt><dd>reference ground track</dd><dt><span>source :</span></dt><dd>Operations</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>1387</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[554., 554., 554., ...,  nan,  nan,  nan],
+        [ nan,  nan,  nan, ...,  nan,  nan,  nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>atlas_sdp_gps_epoch</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01T00:00:18</div><input id='attrs-40112329-ed61-4513-9ad2-850d1278675c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-40112329-ed61-4513-9ad2-850d1278675c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f20dbbf9-f887-4704-b8f6-4a3c6a1fd111' class='xr-var-data-in' type='checkbox'><label for='data-f20dbbf9-f887-4704-b8f6-4a3c6a1fd111' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:18.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_start_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:46:31.876322</div><input id='attrs-17ddd9c1-44bb-4f87-a0a6-a188a234c5e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-17ddd9c1-44bb-4f87-a0a6-a188a234c5e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89e9f2e1-0ccb-4e68-97ba-c3d6b8c502f9' class='xr-var-data-in' type='checkbox'><label for='data-89e9f2e1-0ccb-4e68-97ba-c3d6b8c502f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:46:31.876322000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_end_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:48:54.200826</div><input id='attrs-24e8d2b4-c949-4e2e-a2bc-a74430259b5e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24e8d2b4-c949-4e2e-a2bc-a74430259b5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92b3e576-033b-4829-bbcb-f5e1c66f9173' class='xr-var-data-in' type='checkbox'><label for='data-92b3e576-033b-4829-bbcb-f5e1c66f9173' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:48:54.200826000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.59 20.59 20.59 ... nan nan nan</div><input id='attrs-602f4d3f-0574-441c-8c75-8d24508fb896' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-602f4d3f-0574-441c-8c75-8d24508fb896' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1954e42c-3e3a-4642-8d6d-14dce801128f' class='xr-var-data-in' type='checkbox'><label for='data-1954e42c-3e3a-4642-8d6d-14dce801128f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Latitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([[[20.592943, 20.593845, 20.594746, ...,       nan,       nan,
+               nan]],
+
+       [[      nan,       nan,       nan, ...,       nan,       nan,
+               nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-103.7 -103.7 -103.7 ... nan nan</div><input id='attrs-26a00f50-65ed-41e5-b740-a899a1986712' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26a00f50-65ed-41e5-b740-a899a1986712' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-629b504b-5ba0-469c-9d79-aec5e477ba4e' class='xr-var-data-in' type='checkbox'><label for='data-629b504b-5ba0-469c-9d79-aec5e477ba4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Longitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([[[-103.67242 , -103.672516, -103.67261 , ...,         nan,
+                 nan,         nan]],
+
+       [[        nan,         nan,         nan, ...,         nan,
+                 nan,         nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gt</span></div><div class='xr-var-dims'>(gran_idx, spot)</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;gt3l&#x27; &#x27;gt3r&#x27;</div><input id='attrs-9bf38c40-a7f7-461c-bd16-5958c9edfbd8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9bf38c40-a7f7-461c-bd16-5958c9edfbd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c6e8a18-343a-4ea9-9d7c-2f58f9f8a3f1' class='xr-var-data-in' type='checkbox'><label for='data-4c6e8a18-343a-4ea9-9d7c-2f58f9f8a3f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;gt3l&#x27;, &#x27;gt3r&#x27;]], dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ph_h</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan ... 0.05103 0.05542</div><input id='attrs-cb9dd55e-bf6e-40d0-8f48-6d6212fbcf1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb9dd55e-bf6e-40d0-8f48-6d6212fbcf1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d61fafc6-abae-439d-9078-566b7e6fec7c' class='xr-var-data-in' type='checkbox'><label for='data-d61fafc6-abae-439d-9078-566b7e6fec7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>physicalMeasurement</dd><dt><span>description :</span></dt><dd>Height of photons above interpolated land surface</dd><dt><span>long_name :</span></dt><dd>relative photon height</dd><dt><span>source :</span></dt><dd>land/veg ATBD, 15May2020, Section 2.3.4</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([[[       nan,        nan,        nan, ...,        nan,
+                nan,        nan]],
+
+       [[       nan,        nan,        nan, ..., 0.15209961,
+         0.05102539, 0.05541992]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>classed_pc_flag</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 1.0 1.0 1.0 1.0</div><input id='attrs-21223354-0689-4d53-b6d7-2c037286f09b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21223354-0689-4d53-b6d7-2c037286f09b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-722e17bd-f360-4968-9d5e-74f3b42d314c' class='xr-var-data-in' type='checkbox'><label for='data-722e17bd-f360-4968-9d5e-74f3b42d314c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Land Vegetation ATBD classification flag for each photon as either noise, ground, canopy, and top of canopy. 0 = noise,  1 = ground, 2 = canopy, or 3 = top of canopy.</dd><dt><span>flag_meanings :</span></dt><dd>noise ground canopy top_of_canopy</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3]</dd><dt><span>long_name :</span></dt><dd>photon land atbd classification</dd><dt><span>source :</span></dt><dd>Land ATBD section 4.10</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan]],
+
+       [[nan, nan, nan, ...,  1.,  1.,  1.]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cad7f491-88d6-44bc-8aa5-3922b91d6e12' class='xr-section-summary-in' type='checkbox'  ><label for='section-cad7f491-88d6-44bc-8aa5-3922b91d6e12' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>gran_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-67c16473-3569-4a5f-a6fc-7fbb20622316' class='xr-index-data-in' type='checkbox'/><label for='index-67c16473-3569-4a5f-a6fc-7fbb20622316' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([55402.0], dtype=&#x27;float64&#x27;, name=&#x27;gran_idx&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>photon_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a9b09626-5141-4860-8f33-ddd218d3f29c' class='xr-index-data-in' type='checkbox'/><label for='index-a9b09626-5141-4860-8f33-ddd218d3f29c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([    0,     1,     2,     3,     4,     5,     6,     7,     8,
+                9,
+            ...
+            25224, 25225, 25226, 25227, 25228, 25229, 25230, 25231, 25232,
+            25233],
+           dtype=&#x27;int64&#x27;, name=&#x27;photon_idx&#x27;, length=25234))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spot</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f9297b74-c26d-45ef-959c-83095a2a2485' class='xr-index-data-in' type='checkbox'/><label for='index-f9297b74-c26d-45ef-959c-83095a2a2485' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(UInt64Index([1, 2], dtype=&#x27;uint64&#x27;, name=&#x27;spot&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-02a31ccc-07fc-433a-8f0f-b9c25b94dc32' class='xr-section-summary-in' type='checkbox'  checked><label for='section-02a31ccc-07fc-433a-8f0f-b9c25b94dc32' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_product :</span></dt><dd>ATL08</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Select just one beam</span>
+<span class="n">gt1l</span> <span class="o">=</span> <span class="n">ds_photons</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">spot</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># A less complex plot</span>
+<span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">set_size_inches</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
+    
+<span class="n">gt1l</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s1">&#39;delta_time&#39;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s1">&#39;ph_h&#39;</span><span class="p">,</span> <span class="n">hue</span><span class="o">=</span><span class="s1">&#39;classed_pc_flag&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f2b0a8ff040&gt;
+</pre></div>
+</div>
+<img alt="../../_images/4.icepyx_37_1.png" src="../../_images/4.icepyx_37_1.png" />
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># A plot with more customization</span>
+<span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">set_size_inches</span><span class="p">(</span><span class="mi">17</span><span class="p">,</span> <span class="mi">6</span><span class="p">)</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s1">&#39;Classification of input photons&#39;</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">16</span><span class="p">)</span>
+
+<span class="n">labels</span><span class="o">=</span><span class="p">{</span><span class="mi">0</span><span class="p">:</span> <span class="s1">&#39;noise&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">:</span> <span class="s1">&#39;ground&#39;</span><span class="p">,</span> <span class="mi">2</span><span class="p">:</span> <span class="s1">&#39;canopy&#39;</span><span class="p">,</span> <span class="mi">3</span><span class="p">:</span> <span class="s1">&#39;top of canopy&#39;</span><span class="p">}</span>
+<span class="n">colors</span><span class="o">=</span><span class="p">{</span><span class="mi">0</span><span class="p">:</span> <span class="s1">&#39;grey&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">:</span> <span class="s1">&#39;orange&#39;</span><span class="p">,</span> <span class="mi">2</span><span class="p">:</span> <span class="s1">&#39;brown&#39;</span><span class="p">,</span> <span class="mi">3</span><span class="p">:</span> <span class="s1">&#39;purple&#39;</span><span class="p">}</span>
+
+<span class="k">for</span> <span class="n">g</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">gt1l</span><span class="o">.</span><span class="n">classed_pc_flag</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
+    <span class="k">if</span> <span class="ow">not</span> <span class="n">math</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">g</span><span class="p">):</span>
+        <span class="n">ds_group</span> <span class="o">=</span> <span class="n">gt1l</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">gt1l</span><span class="o">.</span><span class="n">classed_pc_flag</span> <span class="o">==</span> <span class="n">g</span><span class="p">,</span> <span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+        <span class="n">ax</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">ds_group</span><span class="o">.</span><span class="n">delta_time</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">ds_group</span><span class="o">.</span><span class="n">ph_h</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="n">colors</span><span class="p">[</span><span class="n">g</span><span class="p">],</span> 
+                   <span class="n">label</span><span class="o">=</span><span class="n">labels</span><span class="p">[</span><span class="n">g</span><span class="p">],</span> <span class="n">s</span><span class="o">=</span><span class="mi">8</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+
+<span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Height above the ground (m)&#39;</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Text(0, 0.5, &#39;Height above the ground (m)&#39;)
+</pre></div>
+</div>
+<img alt="../../_images/4.icepyx_38_1.png" src="../../_images/4.icepyx_38_1.png" />
+</div>
+</div>
+</section>
+<section id="plot-the-canopy-compared-to-the-ground-height">
+<h3>Plot the canopy compared to the ground height<a class="headerlink" href="#plot-the-canopy-compared-to-the-ground-height" title="Permalink to this headline">#</a></h3>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Remove our previous variables</span>
+<span class="n">reader</span><span class="o">.</span><span class="n">vars</span><span class="o">.</span><span class="n">remove</span><span class="p">(</span><span class="nb">all</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="c1"># Add the next set of variables to the list</span>
+<span class="n">reader</span><span class="o">.</span><span class="n">vars</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">var_list</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;h_te_best_fit&#39;</span><span class="p">,</span> <span class="s1">&#39;latitude&#39;</span><span class="p">,</span> <span class="s1">&#39;longitude&#39;</span><span class="p">])</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># turn off warnings for load to not show an xarray warning that was resolved in the coming release of icepyx v1.0.0</span>
+<span class="k">with</span> <span class="n">warnings</span><span class="o">.</span><span class="n">catch_warnings</span><span class="p">(</span><span class="n">record</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
+    <span class="c1"># load the data</span>
+    <span class="n">ds_te</span> <span class="o">=</span> <span class="n">reader</span><span class="o">.</span><span class="n">load</span><span class="p">()</span>
+    
+<span class="n">ds_te</span>
+</pre></div>
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+}
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+}
+
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+  text-align: right;
+  color: var(--xr-font-color2);
+}
+
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+  grid-column: 4;
+}
+
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+  grid-column: 2 / 5;
+  color: var(--xr-font-color2);
+}
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+.xr-var-dims,
+.xr-var-dtype,
+.xr-preview,
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+  overflow: hidden;
+  text-overflow: ellipsis;
+  padding-right: 10px;
+}
+
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+.xr-var-dtype:hover,
+.xr-attrs dt:hover {
+  overflow: visible;
+  width: auto;
+  z-index: 1;
+}
+
+.xr-var-attrs,
+.xr-var-data,
+.xr-index-data {
+  display: none;
+  background-color: var(--xr-background-color) !important;
+  padding-bottom: 5px !important;
+}
+
+.xr-var-attrs-in:checked ~ .xr-var-attrs,
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+.xr-index-data-in:checked ~ .xr-index-data {
+  display: block;
+}
+
+.xr-var-data > table {
+  float: right;
+}
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+.xr-var-name span,
+.xr-var-data,
+.xr-index-name div,
+.xr-index-data,
+.xr-attrs {
+  padding-left: 25px !important;
+}
+
+.xr-attrs,
+.xr-var-attrs,
+.xr-var-data,
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+}
+
+dl.xr-attrs {
+  padding: 0;
+  margin: 0;
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+}
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+}
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+}
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+}
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+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;
+Dimensions:              (gran_idx: 1, photon_idx: 211, spot: 2)
+Coordinates:
+  * gran_idx             (gran_idx) float64 5.54e+04
+  * photon_idx           (photon_idx) int64 0 1 2 3 4 5 ... 206 207 208 209 210
+  * spot                 (spot) uint8 1 2
+    source_file          (gran_idx) &lt;U74 &#x27;./bosque_primavera_ATL08/processed_...
+    delta_time           (photon_idx) datetime64[ns] 2019-05-04T12:47:13.5766...
+Data variables:
+    sc_orient            (gran_idx) int8 0
+    cycle_number         (gran_idx) int8 3
+    rgt                  (gran_idx, spot, photon_idx) float32 554.0 ... 554.0
+    atlas_sdp_gps_epoch  (gran_idx) datetime64[ns] 2018-01-01T00:00:18
+    data_start_utc       (gran_idx) datetime64[ns] 2019-05-04T12:46:31.876322
+    data_end_utc         (gran_idx) datetime64[ns] 2019-05-04T12:48:54.200826
+    latitude             (spot, gran_idx, photon_idx) float32 20.59 ... 20.73
+    longitude            (spot, gran_idx, photon_idx) float32 -103.7 ... -103.7
+    gt                   (gran_idx, spot) object &#x27;gt3l&#x27; &#x27;gt3r&#x27;
+    h_te_best_fit        (photon_idx) float32 1.342e+03 1.34e+03 ... 1.381e+03
+Attributes:
+    data_product:  ATL08
+    Description:   Contains data categorized as land at 100 meter intervals.
+    data_rate:     Data are stored as aggregates of 100 meters.</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-34f600c0-2bd6-48ae-95b9-045f8f2183bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-34f600c0-2bd6-48ae-95b9-045f8f2183bc' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>gran_idx</span>: 1</li><li><span class='xr-has-index'>photon_idx</span>: 211</li><li><span class='xr-has-index'>spot</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-68081ec5-fdf4-4e5d-b634-03f22343cd77' class='xr-section-summary-in' type='checkbox'  checked><label for='section-68081ec5-fdf4-4e5d-b634-03f22343cd77' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>gran_idx</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.54e+04</div><input id='attrs-2160c78c-f3ae-4b78-9343-1620ddf6b18e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2160c78c-f3ae-4b78-9343-1620ddf6b18e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6de02ff6-132a-402f-beeb-74758395ff4e' class='xr-var-data-in' type='checkbox'><label for='data-6de02ff6-132a-402f-beeb-74758395ff4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([55402.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>photon_idx</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 206 207 208 209 210</div><input id='attrs-0b1564db-cb00-4daa-b070-cc8e295fefcf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0b1564db-cb00-4daa-b070-cc8e295fefcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1441108b-89d6-4723-a1f3-6bdebd20b363' class='xr-var-data-in' type='checkbox'><label for='data-1441108b-89d6-4723-a1f3-6bdebd20b363' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 208, 209, 210])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>spot</span></div><div class='xr-var-dims'>(spot)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>1 2</div><input id='attrs-4bdd2b31-04e0-420e-87e8-b65fed7e12d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4bdd2b31-04e0-420e-87e8-b65fed7e12d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4fef6dc-9c54-4acf-bbfd-20a960a4a897' class='xr-var-data-in' type='checkbox'><label for='data-d4fef6dc-9c54-4acf-bbfd-20a960a4a897' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_file</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>&lt;U74</div><div class='xr-var-preview xr-preview'>&#x27;./bosque_primavera_ATL08/proces...</div><input id='attrs-86d84dc5-0861-4bb1-a4e5-9abd20379778' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86d84dc5-0861-4bb1-a4e5-9abd20379778' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba28c75b-3a90-46e2-801e-f5c4c7eaf955' class='xr-var-data-in' type='checkbox'><label for='data-ba28c75b-3a90-46e2-801e-f5c4c7eaf955' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;./bosque_primavera_ATL08/processed_ATL08_20190504124152_05540301_006_02.h5&#x27;],
+      dtype=&#x27;&lt;U74&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta_time</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:47:13.576668792 .....</div><input id='attrs-2e11c09c-558d-47cc-80b1-b4aac51a68f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2e11c09c-558d-47cc-80b1-b4aac51a68f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d334403-37fc-4ee2-98f9-3ad2aedd694c' class='xr-var-data-in' type='checkbox'><label for='data-6d334403-37fc-4ee2-98f9-3ad2aedd694c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:47:13.576668792&#x27;, &#x27;2019-05-04T12:47:13.590795176&#x27;,
+       &#x27;2019-05-04T12:47:13.604878696&#x27;, &#x27;2019-05-04T12:47:13.618858776&#x27;,
+       &#x27;2019-05-04T12:47:13.647116752&#x27;, &#x27;2019-05-04T12:47:13.731658440&#x27;,
+       &#x27;2019-05-04T12:47:13.788115696&#x27;, &#x27;2019-05-04T12:47:13.802188288&#x27;,
+       &#x27;2019-05-04T12:47:14.013615136&#x27;, &#x27;2019-05-04T12:47:14.027716720&#x27;,
+       &#x27;2019-05-04T12:47:14.041828320&#x27;, &#x27;2019-05-04T12:47:14.069985944&#x27;,
+       &#x27;2019-05-04T12:47:14.084116656&#x27;, &#x27;2019-05-04T12:47:14.098204416&#x27;,
+       &#x27;2019-05-04T12:47:14.112308544&#x27;, &#x27;2019-05-04T12:47:14.126439192&#x27;,
+       &#x27;2019-05-04T12:47:14.140474800&#x27;, &#x27;2019-05-04T12:47:14.154503088&#x27;,
+       &#x27;2019-05-04T12:47:14.168615944&#x27;, &#x27;2019-05-04T12:47:14.182727944&#x27;,
+       &#x27;2019-05-04T12:47:14.196803520&#x27;, &#x27;2019-05-04T12:47:14.225002096&#x27;,
+       &#x27;2019-05-04T12:47:14.239145008&#x27;, &#x27;2019-05-04T12:47:14.253240544&#x27;,
+       &#x27;2019-05-04T12:47:14.267282136&#x27;, &#x27;2019-05-04T12:47:14.281345400&#x27;,
+       &#x27;2019-05-04T12:47:14.295463616&#x27;, &#x27;2019-05-04T12:47:14.309582960&#x27;,
+       &#x27;2019-05-04T12:47:14.323643288&#x27;, &#x27;2019-05-04T12:47:14.337699200&#x27;,
+       &#x27;2019-05-04T12:47:14.351769576&#x27;, &#x27;2019-05-04T12:47:14.363045864&#x27;,
+       &#x27;2019-05-04T12:47:14.379987728&#x27;, &#x27;2019-05-04T12:47:14.394098040&#x27;,
+       &#x27;2019-05-04T12:47:14.408184296&#x27;, &#x27;2019-05-04T12:47:14.422336984&#x27;,
+       &#x27;2019-05-04T12:47:14.436399800&#x27;, &#x27;2019-05-04T12:47:14.450439312&#x27;,
+       &#x27;2019-05-04T12:47:14.464605056&#x27;, &#x27;2019-05-04T12:47:14.478736368&#x27;,
+...
+       &#x27;2019-05-04T12:47:15.425911016&#x27;, &#x27;2019-05-04T12:47:15.439995088&#x27;,
+       &#x27;2019-05-04T12:47:15.454061472&#x27;, &#x27;2019-05-04T12:47:15.468143592&#x27;,
+       &#x27;2019-05-04T12:47:15.482238848&#x27;, &#x27;2019-05-04T12:47:15.496324880&#x27;,
+       &#x27;2019-05-04T12:47:15.510409496&#x27;, &#x27;2019-05-04T12:47:15.524510280&#x27;,
+       &#x27;2019-05-04T12:47:15.538615648&#x27;, &#x27;2019-05-04T12:47:15.566816696&#x27;,
+       &#x27;2019-05-04T12:47:15.580919696&#x27;, &#x27;2019-05-04T12:47:15.594985688&#x27;,
+       &#x27;2019-05-04T12:47:15.609048944&#x27;, &#x27;2019-05-04T12:47:15.623173096&#x27;,
+       &#x27;2019-05-04T12:47:15.637281512&#x27;, &#x27;2019-05-04T12:47:15.651381832&#x27;,
+       &#x27;2019-05-04T12:47:15.665494736&#x27;, &#x27;2019-05-04T12:47:15.679564576&#x27;,
+       &#x27;2019-05-04T12:47:15.693640304&#x27;, &#x27;2019-05-04T12:47:15.707745176&#x27;,
+       &#x27;2019-05-04T12:47:15.721833264&#x27;, &#x27;2019-05-04T12:47:15.735931400&#x27;,
+       &#x27;2019-05-04T12:47:15.750026272&#x27;, &#x27;2019-05-04T12:47:15.764102288&#x27;,
+       &#x27;2019-05-04T12:47:15.778227184&#x27;, &#x27;2019-05-04T12:47:15.806428968&#x27;,
+       &#x27;2019-05-04T12:47:15.820523432&#x27;, &#x27;2019-05-04T12:47:15.834607024&#x27;,
+       &#x27;2019-05-04T12:47:15.848673504&#x27;, &#x27;2019-05-04T12:47:15.862757488&#x27;,
+       &#x27;2019-05-04T12:47:15.876856944&#x27;, &#x27;2019-05-04T12:47:15.890974768&#x27;,
+       &#x27;2019-05-04T12:47:15.905085432&#x27;, &#x27;2019-05-04T12:47:15.919119064&#x27;,
+       &#x27;2019-05-04T12:47:15.933193432&#x27;, &#x27;2019-05-04T12:47:15.947348696&#x27;,
+       &#x27;2019-05-04T12:47:15.961461904&#x27;, &#x27;2019-05-04T12:47:15.975561616&#x27;,
+       &#x27;2019-05-04T12:47:15.989663088&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1967c4a6-d790-4eb6-aa94-4eeea370737a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1967c4a6-d790-4eb6-aa94-4eeea370737a' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sc_orient</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-8590e8a7-8bbc-4a1a-b731-b66c2cd5b088' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8590e8a7-8bbc-4a1a-b731-b66c2cd5b088' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-541979da-afec-472f-8690-3542325135fc' class='xr-var-data-in' type='checkbox'><label for='data-541979da-afec-472f-8690-3542325135fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cycle_number</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>3</div><input id='attrs-1d12e4f1-4f42-4d33-8665-309055d677f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d12e4f1-4f42-4d33-8665-309055d677f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8575c75d-1cf2-4981-962f-acc188ddf809' class='xr-var-data-in' type='checkbox'><label for='data-8575c75d-1cf2-4981-962f-acc188ddf809' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rgt</span></div><div class='xr-var-dims'>(gran_idx, spot, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>554.0 554.0 554.0 ... 554.0 554.0</div><input id='attrs-6ccbf657-316f-4195-9fb6-b48652f09f55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ccbf657-316f-4195-9fb6-b48652f09f55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b042f91c-fedf-43af-8d34-d8772c6f44f1' class='xr-var-data-in' type='checkbox'><label for='data-b042f91c-fedf-43af-8d34-d8772c6f44f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>The reference ground track (RGT) is the track on the earth at which a specified unit vector within the observatory is pointed. Under nominal operating conditions, there will be no data collected along the RGT, as the RGT is spanned by GT3 and GT4.  During slews or off-pointing, it is possible that ground tracks may intersect the RGT. The ICESat-2 mission has 1387 RGTs.</dd><dt><span>long_name :</span></dt><dd>reference ground track</dd><dt><span>source :</span></dt><dd>Operations</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>1387</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([[[554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+...
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+          nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,  nan,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554., 554., 554., 554., 554., 554., 554., 554., 554., 554.,
+         554.]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>atlas_sdp_gps_epoch</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-01-01T00:00:18</div><input id='attrs-5329027b-61e0-47c6-889f-189a6ba3ad2a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5329027b-61e0-47c6-889f-189a6ba3ad2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0562a92d-0f6c-4774-a1ab-94feb69e72e2' class='xr-var-data-in' type='checkbox'><label for='data-0562a92d-0f6c-4774-a1ab-94feb69e72e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-01-01T00:00:18.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_start_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:46:31.876322</div><input id='attrs-ec325ce0-cd2d-4256-911e-7200271b7e55' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec325ce0-cd2d-4256-911e-7200271b7e55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59f19872-2952-4f88-9261-2d2aa4490b02' class='xr-var-data-in' type='checkbox'><label for='data-59f19872-2952-4f88-9261-2d2aa4490b02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:46:31.876322000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_end_utc</span></div><div class='xr-var-dims'>(gran_idx)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-05-04T12:48:54.200826</div><input id='attrs-ce3d3ec9-abf8-40f5-8e66-a08602eda0ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ce3d3ec9-abf8-40f5-8e66-a08602eda0ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f245eeb2-9b3e-4315-92b8-0917e3cba2d1' class='xr-var-data-in' type='checkbox'><label for='data-f245eeb2-9b3e-4315-92b8-0917e3cba2d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-05-04T12:48:54.200826000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.59 20.59 20.59 ... 20.72 20.73</div><input id='attrs-7e11affa-64cd-425e-9046-a82ed18a3400' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e11affa-64cd-425e-9046-a82ed18a3400' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f4c32b3-9b07-4998-a4d7-7de0dcd3959c' class='xr-var-data-in' type='checkbox'><label for='data-7f4c32b3-9b07-4998-a4d7-7de0dcd3959c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Latitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([[[20.592943, 20.593845, 20.594746, 20.595648, 20.59745 ,
+         20.60286 , 20.606464, 20.607367, 20.620888, 20.621788,
+         20.62269 , 20.624493, 20.625395, 20.626297, 20.627197,
+         20.6281  , 20.629   , 20.629902, 20.630804, 20.631704,
+         20.632607, 20.634409, 20.635311, 20.636211, 20.637114,
+         20.638014, 20.638916, 20.639816, 20.640718, 20.64162 ,
+         20.642523, 20.643244, 20.644325, 20.645226, 20.646128,
+         20.64703 , 20.64793 , 20.648832, 20.649734, 20.650635,
+         20.651537, 20.652437, 20.65334 , 20.65424 , 20.655142,
+         20.656044, 20.656944, 20.657846, 20.658749, 20.659649,
+         20.660551, 20.661451, 20.662354, 20.663254, 20.664156,
+         20.665058, 20.665958, 20.66686 , 20.667763, 20.668663,
+         20.669565, 20.670467, 20.671368, 20.67227 , 20.67317 ,
+         20.674072, 20.674973, 20.675875, 20.676777, 20.677677,
+         20.67858 , 20.679482, 20.680382, 20.681284, 20.682184,
+         20.683086, 20.683989, 20.684889, 20.685791, 20.686691,
+         20.687593, 20.688496, 20.689217, 20.690298, 20.691198,
+         20.6921  , 20.693003, 20.693903, 20.694805, 20.695707,
+         20.696608, 20.69751 , 20.69841 , 20.699312, 20.700212,
+         20.701115, 20.702017, 20.702917, 20.70382 , 20.704721,
+...
+               nan,       nan,       nan,       nan,       nan,
+         20.625654, 20.626554, 20.627457, 20.628359, 20.635569,
+         20.63647 , 20.637373, 20.638273, 20.639175, 20.640078,
+         20.640978, 20.644585, 20.646387, 20.647287, 20.64819 ,
+         20.649992, 20.650894, 20.651796, 20.652697, 20.653599,
+         20.655401, 20.656303, 20.657204, 20.658106, 20.659006,
+         20.659908, 20.662613, 20.663513, 20.664415, 20.666218,
+         20.66712 , 20.66802 , 20.668922, 20.669825, 20.670725,
+         20.671627, 20.672527, 20.67343 , 20.674332, 20.675232,
+         20.676134, 20.677036, 20.677937, 20.678839, 20.679739,
+         20.680641, 20.681543, 20.682444, 20.68605 , 20.68695 ,
+         20.687853, 20.688753, 20.689655, 20.690557, 20.691458,
+         20.69236 , 20.693262, 20.694162, 20.695065, 20.695965,
+         20.696867, 20.69867 , 20.699572, 20.700472, 20.701374,
+         20.702274, 20.703176, 20.704079, 20.704979, 20.705881,
+         20.706781, 20.707684, 20.708586, 20.709486, 20.710388,
+         20.711288, 20.71219 , 20.713993, 20.714895, 20.715796,
+         20.716698, 20.7176  , 20.7185  , 20.719402, 20.720304,
+         20.721205, 20.722107, 20.723007, 20.72391 , 20.724812,
+         20.725712]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(spot, gran_idx, photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-103.7 -103.7 ... -103.7 -103.7</div><input id='attrs-5c142732-f740-48e4-9166-788d60e711bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c142732-f740-48e4-9166-788d60e711bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-778cd090-34f7-4499-b988-936f2d51ab32' class='xr-var-data-in' type='checkbox'><label for='data-778cd090-34f7-4499-b988-936f2d51ab32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Longitude of the center-most signal photon within each segment.</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.4</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>array([[[-103.67242 , -103.672516, -103.67261 , -103.6727  ,
+         -103.6729  , -103.67346 , -103.673836, -103.673935,
+         -103.67535 , -103.675446, -103.67554 , -103.67573 ,
+         -103.67583 , -103.67592 , -103.67601 , -103.67611 ,
+         -103.6762  , -103.6763  , -103.67639 , -103.67649 ,
+         -103.67658 , -103.676765, -103.676865, -103.676956,
+         -103.67705 , -103.67715 , -103.677246, -103.677345,
+         -103.67743 , -103.67753 , -103.67762 , -103.6777  ,
+         -103.67781 , -103.67791 , -103.678   , -103.678085,
+         -103.678185, -103.67828 , -103.678375, -103.678474,
+         -103.678566, -103.67866 , -103.67876 , -103.678856,
+         -103.67895 , -103.67904 , -103.67913 , -103.67922 ,
+         -103.67932 , -103.67941 , -103.679504, -103.6796  ,
+         -103.6797  , -103.6798  , -103.67989 , -103.679985,
+         -103.68008 , -103.680176, -103.68027 , -103.68037 ,
+         -103.68046 , -103.68055 , -103.68064 , -103.68073 ,
+         -103.68083 , -103.68093 , -103.68103 , -103.68112 ,
+         -103.68121 , -103.681305, -103.6814  , -103.68149 ,
+         -103.68159 , -103.68169 , -103.681786, -103.68188 ,
+         -103.68197 , -103.68207 , -103.68216 , -103.68226 ,
+...
+         -103.67717 , -103.67727 , -103.67736 , -103.67754 ,
+         -103.67764 , -103.677734, -103.67783 , -103.677925,
+         -103.678116, -103.67821 , -103.67831 , -103.6784  ,
+         -103.6785  , -103.67859 , -103.67887 , -103.67897 ,
+         -103.67906 , -103.67925 , -103.679344, -103.67944 ,
+         -103.679535, -103.67963 , -103.67972 , -103.67982 ,
+         -103.67991 , -103.68001 , -103.6801  , -103.68019 ,
+         -103.68029 , -103.68038 , -103.68047 , -103.68057 ,
+         -103.68067 , -103.68076 , -103.680855, -103.680954,
+         -103.68133 , -103.68143 , -103.68152 , -103.68161 ,
+         -103.68171 , -103.6818  , -103.68189 , -103.681984,
+         -103.68208 , -103.68218 , -103.682274, -103.682365,
+         -103.682465, -103.682655, -103.682755, -103.682846,
+         -103.68294 , -103.68304 , -103.68313 , -103.68322 ,
+         -103.68332 , -103.68341 , -103.68351 , -103.6836  ,
+         -103.68369 , -103.68379 , -103.68388 , -103.68398 ,
+         -103.684074, -103.684265, -103.68436 , -103.684456,
+         -103.68455 , -103.68465 , -103.68474 , -103.68483 ,
+         -103.68493 , -103.68502 , -103.68511 , -103.68521 ,
+         -103.6853  , -103.6854  , -103.68549 ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gt</span></div><div class='xr-var-dims'>(gran_idx, spot)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;gt3l&#x27; &#x27;gt3r&#x27;</div><input id='attrs-6898a21c-181a-477d-bab9-4ad99aae9cd8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6898a21c-181a-477d-bab9-4ad99aae9cd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ffa3bac-f38f-46c6-90e5-322eaf53475d' class='xr-var-data-in' type='checkbox'><label for='data-1ffa3bac-f38f-46c6-90e5-322eaf53475d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;gt3l&#x27;, &#x27;gt3r&#x27;]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h_te_best_fit</span></div><div class='xr-var-dims'>(photon_idx)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.342e+03 1.34e+03 ... 1.381e+03</div><input id='attrs-89bea8f5-3760-4679-b733-6df0119a0a45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89bea8f5-3760-4679-b733-6df0119a0a45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0600ef65-37f9-4be0-82ac-a3e0daaa7108' class='xr-var-data-in' type='checkbox'><label for='data-0600ef65-37f9-4be0-82ac-a3e0daaa7108' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>The best fit terrain elevation at the the mid-point location of each 100m segment. The mid-segment terrain elevation is determined by selecting the best of three fits- linear, 3rd order and 4th order polynomials - to the terrain photons and interpolating the elevation at the mid-point location of the 100 m segment. For the linear fit, a slope correction and weighting is applied to each ground photon based on the distance to the slope height at the center of the segment.</dd><dt><span>long_name :</span></dt><dd>segment terrain height best fit</dd><dt><span>source :</span></dt><dd>Land ATBD section 2.1.15</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([1341.6261, 1339.7549, 1342.2279, 1352.5458, 1352.1498, 1369.6022,
+       1341.8672, 1342.6127, 1379.6085, 1387.4363, 1378.2903, 1398.2286,
+       1408.835 , 1412.2861, 1408.1262, 1402.0425, 1390.7015, 1377.3165,
+       1374.2667, 1362.9102, 1351.8086, 1356.7529, 1372.503 , 1374.2352,
+       1371.826 , 1372.7759, 1369.5962, 1379.0153, 1380.004 , 1369.1742,
+       1331.0907, 1332.0349, 1337.1906, 1364.3312, 1369.7789, 1368.005 ,
+       1380.9327, 1378.1477, 1378.0027, 1365.716 , 1341.7355, 1362.7502,
+       1369.3937, 1365.5645, 1371.5692, 1360.3632, 1371.7815, 1378.1556,
+       1374.7207, 1375.1332, 1374.8978, 1343.2148, 1374.0865, 1377.0504,
+       1375.9967, 1348.3921, 1370.8029, 1371.5946, 1368.5741, 1366.4877,
+       1349.1473, 1349.8328, 1351.8678, 1337.4954, 1348.1287, 1350.1534,
+       1347.2864, 1344.1531, 1349.8016, 1356.35  , 1361.5197, 1362.969 ,
+       1362.5942, 1352.9877, 1348.731 , 1345.9487, 1331.6982, 1345.9829,
+       1347.6493, 1351.7913, 1358.8625, 1344.7389, 1355.0139, 1331.1632,
+       1323.9978, 1325.0448, 1326.3163, 1326.6976, 1328.0988, 1332.0776,
+       1341.5808, 1348.429 , 1365.6849, 1371.8914, 1377.0238, 1378.2782,
+       1381.2715, 1382.6595, 1387.2151, 1388.956 , 1393.6167, 1394.5526,
+       1394.6461, 1394.7386, 1394.2676, 1392.7904, 1391.0226, 1390.6882,
+       1392.7502, 1390.3289, 1389.7281, 1389.8076, 1390.4437, 1391.2537,
+       1391.2205, 1390.5575, 1385.5656, 1383.5444, 1381.2579, 1380.6188,
+       1360.0029, 1368.5271, 1380.5599, 1378.5365, 1348.2975, 1361.3527,
+       1368.1271, 1377.8864, 1378.9846, 1367.561 , 1357.905 , 1363.3611,
+       1368.037 , 1369.7767, 1380.6696, 1352.8546, 1345.157 , 1343.4655,
+       1357.3806, 1373.508 , 1369.7052, 1364.288 , 1370.0299, 1379.9648,
+       1376.0862, 1377.4329, 1369.4843, 1376.7523, 1374.9471, 1374.8214,
+       1372.7871, 1373.7095, 1364.68  , 1345.6294, 1347.3657, 1340.5127,
+       1341.6628, 1349.958 , 1350.7115, 1348.8658, 1346.0786, 1351.665 ,
+       1359.094 , 1366.7888, 1364.4694, 1363.6366, 1350.4138, 1367.0265,
+       1359.8527, 1358.6835, 1358.3513, 1354.3091, 1348.4569, 1326.3341,
+       1325.2039, 1325.5641, 1326.9438, 1326.9764, 1328.5076, 1335.6763,
+       1338.7979, 1358.19  , 1373.2162, 1379.8351, 1379.533 , 1379.962 ,
+       1383.1627, 1386.4252, 1390.6842, 1394.9309, 1394.6163, 1397.2983,
+       1395.9186, 1394.3945, 1390.8865, 1391.3041, 1394.9935, 1390.8632,
+       1390.6216, 1390.5719, 1390.7397, 1390.6544, 1389.8055, 1389.2607,
+       1388.0011, 1382.5074, 1381.5883, 1380.8461, 1380.4548, 1380.2258,
+       1380.7296], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d30c7fe-a6b7-4db8-ad95-422fcf46772b' class='xr-section-summary-in' type='checkbox'  ><label for='section-7d30c7fe-a6b7-4db8-ad95-422fcf46772b' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>gran_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1b069a76-18ca-4ab3-9430-05038d33a4c3' class='xr-index-data-in' type='checkbox'/><label for='index-1b069a76-18ca-4ab3-9430-05038d33a4c3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([55402.0], dtype=&#x27;float64&#x27;, name=&#x27;gran_idx&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>photon_idx</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2788349a-332d-4e6a-954a-d98c8e3e74d3' class='xr-index-data-in' type='checkbox'/><label for='index-2788349a-332d-4e6a-954a-d98c8e3e74d3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
+            ...
+            201, 202, 203, 204, 205, 206, 207, 208, 209, 210],
+           dtype=&#x27;int64&#x27;, name=&#x27;photon_idx&#x27;, length=211))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>spot</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-17556f4d-8a07-4b23-8123-1094637f0852' class='xr-index-data-in' type='checkbox'/><label for='index-17556f4d-8a07-4b23-8123-1094637f0852' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(UInt64Index([1, 2], dtype=&#x27;uint64&#x27;, name=&#x27;spot&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-30b24902-22ec-4e62-b6a1-e5558dca5607' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30b24902-22ec-4e62-b6a1-e5558dca5607' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_product :</span></dt><dd>ATL08</dd><dt><span>Description :</span></dt><dd>Contains data categorized as land at 100 meter intervals.</dd><dt><span>data_rate :</span></dt><dd>Data are stored as aggregates of 100 meters.</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">set_size_inches</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
+
+<span class="c1"># plot the canopy height above ground level</span>
+<span class="p">(</span><span class="n">ds</span><span class="o">.</span><span class="n">h_canopy</span> <span class="o">+</span> <span class="n">ds_te</span><span class="o">.</span><span class="n">h_te_best_fit</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s2">&quot;delta_time&quot;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">&quot;h_canopy&quot;</span><span class="p">)</span> <span class="c1"># orange</span>
+
+<span class="c1"># plot the terrain values</span>
+<span class="n">ds_te</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s2">&quot;delta_time&quot;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">&quot;h_te_best_fit&quot;</span><span class="p">)</span> <span class="c1"># blue</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f2b087aada0&gt;
+</pre></div>
+</div>
+<img alt="../../_images/4.icepyx_42_1.png" src="../../_images/4.icepyx_42_1.png" />
+</div>
+</div>
+</section>
+</section>
+<section id="summary">
+<h2>Summary<a class="headerlink" href="#summary" title="Permalink to this headline">#</a></h2>
+<p>In this notebook we explored the opening and rendering ATL08 data with icepyx. We saw that icepyx will subset our downloaded data to our area of interest and also allows us to download only the variables we need. The ATL08 data has a folder-like structure with many variables to choose from. We focused on <code class="docutils literal notranslate"><span class="pre">h_canopy</span></code> and showed additional examples using the raw photons and <code class="docutils literal notranslate"><span class="pre">h_te_best_fit</span></code> for the ground height.</p>
+<p>More information about ATL08 or icepyx can be found in:</p>
+<ul class="simple">
+<li><p>The <a class="reference external" href="https://icepyx.readthedocs.io/en/latest/">icepyx documentation</a></p></li>
+<li><p>The <a class="reference external" href="https://icesat-2.gsfc.nasa.gov/sites/default/files/page_files/ICESat2_ATL08_ATBD_r006.pdf">Algorithm Theoretical Basis Document (ATBD)</a></p></li>
+<li><p>Neuenschwander et. al. 2019, Remote Sens. Env. <a class="reference external" href="https://doi.org/10.1016/j.rse.2018.11.005">DOI</a></p></li>
+</ul>
+</section>
+</section>
+
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diff --git a/tutorials/SlideRule_applications/SlideRule_applications.html b/tutorials/SlideRule_applications/SlideRule_applications.html
index 881be71..e42a35f 100644
--- a/tutorials/SlideRule_applications/SlideRule_applications.html
+++ b/tutorials/SlideRule_applications/SlideRule_applications.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="../ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="../NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="../GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
    </i>
   </label>
diff --git a/tutorials/index.html b/tutorials/index.html
index d917920..e4b3a20 100644
--- a/tutorials/index.html
+++ b/tutorials/index.html
@@ -330,10 +330,37 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
      ICESat-2 ATL10-h5coro large-scale time series
     </a>
    </li>
-   <li class="toctree-l2">
+   <li class="toctree-l2 has-children">
     <a class="reference internal" href="ARCOdata_writingZarrs.html">
      Analysis-ready, cloud-optimized data: writing zarr directories
     </a>
+    <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
+    <label for="toctree-checkbox-5">
+     <i class="fas fa-chevron-down">
+     </i>
+    </label>
+    <ul>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/1.Intro-Earthdata-Cloud.html">
+       Introduction to NASA Earthdata Cloud and ICESat-2
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/2.earthdata_search.html">
+       Using NASA Earthdata Search to Discover Cloud-Hosted Data
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/3.earthaccess.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+     <li class="toctree-l3">
+      <a class="reference internal" href="NASA-Earthdata-Cloud-Access/4.icepyx.html">
+       NASA Earthdata Cloud and data access using earthaccess and icepyx
+      </a>
+     </li>
+    </ul>
    </li>
    <li class="toctree-l2">
     <a class="reference internal" href="GrIMP/GrIMP_tutorial_AGU23.html">
@@ -358,8 +385,8 @@ <h1 class="site-logo" id="site-title">CryoCloud</h1>
   <a class="reference internal" href="../contributing/index.html">
    Contributing
   </a>
-  <input class="toctree-checkbox" id="toctree-checkbox-5" name="toctree-checkbox-5" type="checkbox"/>
-  <label for="toctree-checkbox-5">
+  <input class="toctree-checkbox" id="toctree-checkbox-6" name="toctree-checkbox-6" type="checkbox"/>
+  <label for="toctree-checkbox-6">
    <i class="fas fa-chevron-down">
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   </label>