{ "cells": [ { "cell_type": "markdown", "id": "d1b6a33e-1aa1-42b0-9d91-6e7bba3f228f", "metadata": {}, "source": [ "# The Basics\n", "\n", "This tutorial will introduce the basic functionality and usage of MDAnalysis. It will focus on analyzing a Lithium-ion battery electrolyte composed of 49 Li+, 49 PF6-, 363 Butyro Nitride, and 237 Ethylene Carbonate. This tutorial will assume a basic familiarity with the [MDAnalysis](https://www.mdanalysis.org/) core data structures." ] }, { "cell_type": "markdown", "id": "2067c1b3-85d1-4951-9b14-a5daea1642f9", "metadata": {}, "source": [ "## Creating a Solute\n", "\n", "\n", "First, we import solvation_analysis and MDA and instantiate a universe object. " ] }, { "cell_type": "code", "execution_count": null, "id": "b6226e61-99a2-4061-8a8d-93d1c1b87308", "metadata": {}, "outputs": [], "source": [ "# imports\n", "import MDAnalysis as mda\n", "import solvation_analysis\n", "\n", "\n", "# we can use a test trajectory supplied with the package\n", "from solvation_analysis.tests import datafiles\n", "\n", "# instantiate Universe\n", "u = mda.Universe(datafiles.bn_fec_data, datafiles.bn_fec_dcd_wrap)" ] }, { "cell_type": "markdown", "id": "7dc41644-0b2f-4d81-a9e2-32b182f280b5", "metadata": {}, "source": [ "Second, we need to select the solute and solvents AtomGroups that compose the solution. Here, I am selecting the relevant AtomGroups using Atom types, in general, you can select the AtomGroups any way you like. Generally, solvation_analysis will work best when 1) the solvents are disjoint sets and 2) the set of solute and solvents includes all atoms." ] }, { "cell_type": "code", "execution_count": 2, "id": "026c729e-eeb6-4f90-8785-fb38a79810d4", "metadata": {}, "outputs": [], "source": [ "# define solute AtomGroup\n", "li_atoms = u.atoms.select_atoms(\"type 22\")\n", "\n", "# define solvent AtomGroups\n", "PF6 = u.atoms.select_atoms(\"byres type 21\")\n", "BN = u.atoms.select_atoms(\"byres type 5\")\n", "FEC = u.atoms.select_atoms(\"byres type 19\")" ] }, { "cell_type": "markdown", "id": "71854641-81a4-4d3e-bd6e-aa55e47198a4", "metadata": {}, "source": [ "Finally, we can instantiate the Solute from the solute and solvents! The solvents are supplied with a dict of `{str: AtomGroups}`. The strings should be the names of the solvents or some other convenient identifier because Solute will use this to identify the solvent in all future analysis." ] }, { "cell_type": "code", "execution_count": 3, "id": "03ec0dce-8887-471b-8aa3-d3635a5336ed", "metadata": {}, "outputs": [], "source": [ "# instantiate solute\n", "from solvation_analysis import Solute\n", "\n", "solute = Solute.from_atoms(li_atoms, {'PF6': PF6, 'BN': BN, 'FEC': FEC}, solute_name=\"Li\")" ] }, { "cell_type": "markdown", "id": "b318d459-615e-4920-9875-8ce38a80526d", "metadata": { "tags": [] }, "source": [ "We can see that solution now contains our atoms of interest as attributes:" ] }, { "cell_type": "code", "execution_count": 4, "id": "e515cc9f-435a-4318-9092-69b9d90fd601", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ", , , ..., , , ]>\n", ", , , ..., , , ]>\n" ] } ], "source": [ "print(solute.solute_atoms)\n", "print(solute.solvents['BN'])" ] }, { "cell_type": "markdown", "id": "0f2ca114-4e12-49bd-885f-1c11357c3e59", "metadata": {}, "source": [ "## Running and Validating a Solute\n", "\n", "Now that we have a solution, we can run the analysis by calling `analysis.run()`. When `run` is called, a few things happen:\n", "\n", "\n", "First, Solute calculates the RDF between the solute and each solvent and\n", "uses it to identify the cutoff radius of the first solvation shell.\n", "\n", "Second, Solute uses the cutoff radii to find all atoms in the first solvation shell. This is repeated for each solute at every frame in the analysis and the data is compiled into a pandas DataFrame, hereafter called `solvation_data`.\n", "\n", "Finally, Solute instantiates the analysis objects from the `solvation_data` (by default Speciation, Coordination, and Pairing), providing a convenient interface for further analysis. These will be discussed later in the tutorial.\n", "\n", "Now let's do it!" ] }, { "cell_type": "code", "execution_count": 5, "id": "928e706d-7206-404f-b1ba-41a3897fd194", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# run analysis\n", "solute.run()" ] }, { "cell_type": "markdown", "id": "174a1618-02ec-4fa7-a162-c20f47eb87b8", "metadata": {}, "source": [ "\n", "It's important to check that Solute did a good job identifying the solvation cutoff radii. Let's inspect the cutoff radii that were calculated by Solute." ] }, { "cell_type": "code", "execution_count": 8, "id": "1da344ad-5c88-44da-b0c2-bd6e3ac6fc0c", "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plotly.com" }, "data": [ { "mode": "lines", "name": "RDF", "type": "scatter", "x": [ 0.05, 0.15000000000000002, 0.25, 0.35000000000000003, 0.45, 0.55, 0.6500000000000001, 0.75, 0.8500000000000001, 0.95, 1.05, 1.1500000000000001, 1.25, 1.35, 1.4500000000000002, 1.55, 1.6500000000000001, 1.75, 1.85, 1.9500000000000002, 2.05, 2.1500000000000004, 2.25, 2.3500000000000005, 2.45, 2.55, 2.6500000000000004, 2.75, 2.8500000000000005, 2.95, 3.05, 3.1500000000000004, 3.25, 3.3500000000000005, 3.45, 3.55, 3.6500000000000004, 3.75, 3.8500000000000005, 3.95, 4.050000000000001, 4.15, 4.25, 4.35, 4.45, 4.550000000000001, 4.65, 4.75, 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tS0/FbYtZ+/UotaXlwsV/UaWBp9ityJJHHyqLAvly4tLlK3iuTV/1tUAEyrv9J2Dx6i1xtVziT75R6/dUzY9f136mRFFyAsWbqRCMQPFmi0j2xButG+H+kkWQP09OVZD3w1Ez4BUoXpn1YbdXbjua2B+BsuqrEeo4Xm9LXANFvn7p36v49ItvsWT1FlU819tG9ntDHY18p5aUQAkF60gKFDnqWLb7xM9uirZfllwvCZAACZAACZAACZAACZBAdBOgQAlAoHgfGclMkHoosu1FCtB663B466TsXDEJqVPdqivh3XLSrNFj6NX5pWQFitS3qNqwk5Iwclxsi04D0aFVI7R/uYEa2lvQU07qkZoY3ubd/pOUQPHWXYn/uCeugeKtvzJ9dI+4E2PkeqfThYfqt0fO7Jmx5IshqotwChSp4yL1XEQyiWzytm+WbsB7Q6bECRQ5LaddtxHo/Gpjtc0kfvNFoHww8nPMWbjmtoybpARK/L4lk+i7VZvVSUFSuPbL8b39FiihYB1JgSLZRk+16KGKFK+aMxyZM6VPcnipP+Mt8Bvdv1q5ehIgARIgARIgARIgARIgAbMRoEDxU6AsWb1VHacrmSbeNnP+Kgwc84U6nUROKZFim1J0M3HBTblGrvUWiE0uA0X69UoE2cIjp8/Ez+jwvuB3aNlQHbXrbd7MlfgCRY7jHTB6htomI9tl7iRQ1m/+Ge17jETiYqkr1u/Am30+TnDiTDgFimTfyFqmjHgXD5UvpaYsL+Zyao3w82ageGvDSA0Uqc2S6j9ZJV9v2Oq9BMcYJ1UD5ZPPF+Ljqd9g2Puvo17NSmociUm/EdPUccHeU3ikWKwUWC1aKH8cPpFnkk0khWpTOrkpqQyUULCOpECRsUReicSSor8Dur2a4KhqqVcj27+WrduGycPeMdvvSa6HBEiABEiABEiABEiABEiABBA1AkVOI/G+jMePe77cOdQ2EV9P4ZHtOXI8bsN6j6jjbOVl/bPZS9WRu0tnDkGObJnVaTSPNuqkhhHJUbRQPmzZuVcdLSsv+/On9lef0t9JoHizVaSPxIVWvd+TbICGdasgT67s2P7TXmzY+osaM75A2fnLAbzUcYA6LrhV03q4cTMWpe8thIcrlL5tzW63G806fKiyap6qUxnVHiqr5I3UX5HmPaZZ/hxOgSJZIZIdIvLoqdqVYbEAUhNFthBJ8woU+bO3aK0c5yxHDh85dkq9yEtL6RhjORGpZZfBKqui9Qv1cO3aDZVZ4t2i4xUoXmElTB68/16kSZUK67f8rCSPZAVJdtCdWlICJRSsQylQpKaM95jr+P3K6UHeU3ck86ZJ276KjzxPTzz2EOTnRwr9ytHREh/ZyjZnYh/+aiUBEiABEiABEiABEiABEiAB0xEwvUDxHhebXOS8J8v4KlAku0ROI5HMA2+TYrJyXLFICW+Tl8luH06Ie+mXr4sI+bDbq0qySPMKFDnxRk6+Sdy8RwWP7t8Rtao+mODbMgepN+Jt8kL7bP3qGPfZN2jZpC7eaf983PdE8Mj1IkOk9e3aEs/Vr56kNLp46YrKwJCTdLxNRMawPu1RpkThuK8lJ1Ak20WyXhLXFUm8titXr+N/T7RTWTGJi8hKtkmfoZ9hwbIf4m6TrTIl7imoJNTHAzujRuVy6nsyX8mOiV+PRorKigiJX8h3y4+/4ZW3P1Jbp2QLlbfJ9is5EcfbJIbFChf4bwuR58QZOQFn8NhZaptW/CYMe3R6McE2raSeMxEoFR8ogWmjuif4drCsk3um5ete6ZP4OOzE93izfZLrSwrGSuFYb7t67YaqBSOZQPF/BkRC1X70QTR7ppaSKGwkQAIkQAIkQAIkQAIkQAIkYDYCphco4QiYZA9Ilon8I1kO2bNmhtVqSXIo+dT+9NkLyJ83JzJlSBfS6Uhh06PHTyFtmtS4u0CeZOcgg8qcRaBkSJ8WWTNnTHEeckrO38dPqbX5ctJMih0GcMGpMxcUu+zZMiFPzltFXpPqSq49f/EyCt2VJ0Whkfh+ue+fU+dUNkVytT3kHhFe/5w6q26XrJ+0aVIFsKrbb9ED60AWIgLon9PnkD5dGuTJlY21TwKByHtIgARIgARIgARIgARIgAQMQ4ACxTCh4kRJgARIgARIgARIgARIgARIgARIgAS0IkCBohV5jksCJEACJEACJEACJEACJEACJEACJGAYAhQohgkVJ0oCJEACJEACJEACJEACJEACJEACJKAVAQoUrchzXBIgARIgARIgARIgARIgARIgARIgAcMQoEAxTKg4URIgARIgARIgARIgARIgARIgARIgAa0IUKBoRZ7jkgAJkAAJkAAJkAAJkAAJkAAJkAAJGIYABYphQsWJkgAJkAAJkAAJkAAJkAAJkAAJkAAJaEWAAkUr8hyXBEiABEiABEiABEiABEiABEiABEjAMAQoUAwTKk6UBEiABEiABEiABEiABEiABEiABEhAKwIUKFqR57gkQAIkQAIkQAIkQAIkQAIkQAIkQAKGIUCBYphQcaIkQAIkQAIkQAIkQAIkQAIkQAIkQAJaEaBA0Yo8xyUBEiABEiABEiABEiABEiABEiABEjAMAQoUw4SKEyUBEiABEiABEiABEiABEiABEiABEtCKAAWKVuQ5LgmQAAmQAAmQAAmQAAmQAAmQAAmQgGEIUKAYJlScKAmQAAmQAAmQAAmQAAmQAAmQAAmQgFYEKFC0Is9xSYAESIAESIAESIAESIAESIAESIAEDEOAAsUwoeJESYAESIAESIAESIAESIAESIAESIAEtCJAgaIVeY5LAiRAAiRAAiRAAiRAAiRAAiRAAiRgGAIUKIYJFSdKAiRAAiRAAiRAAiRAAiRAAiRAAiSgFQEKFK3Ic1wSIAESIAESIAESIAESIAESIAESIAHDEKBAMUyoOFESIAESIAESIAESIAESIAESIAESIAGtCFCgaEWe45IACZAACZAACZAACZAACZAACZAACRiGAAWKYULFiZIACZAACZAACZAACZAACZAACZAACWhFgAJFK/IclwRIgARIgARIgARIgARIgARIgARIwDAEKFAMEypOlARIgARIgARIgARIgARIgARIgARIQCsCFChakee4JEACJEACJEACJEACJEACJEACJEAChiFAgWKYUHGiJEACJEACJEACJEACJEACJEACJEACWhGgQNGKPMclARIgARIgARIgARIgARIgARIgARIwDAEKFMOEihMlARIgARIgARIgARIgARIgARIgARLQigAFilbkOS4JkAAJkAAJkAAJkAAJkAAJkAAJkIBhCFCgGCZUnCgJkAAJkAAJkAAJkAAJkAAJkAAJkIBWBChQtCLPcUmABEiABEiABEiABEiABEiABEiABAxDgALFMKHiREmABEiABEiABEiABEiABEiABEiABLQiQIGiFXmOSwIkQAIkQAIkQAIkQAIkQAIkQAIkYBgCFCiGCRUnSgIkQAIkQAIkQAIkQAIkQAIkQAIkoBUBChStyHNcEiABEiABEiABEiABEiABEiABEiABwxCgQDFMqDhREiABEiABEiABEiABEiABEiABEiABrQhQoGhFnuOSAAmQAAmQAAmQAAmQAAmQAAmQAAkYhgAFimFCxYmSAAmQAAmQAAmQAAmQAAmQAAmQAAloRYACRSvyHJcESIAESIAESIAESIAESIAESIAESMAwBChQDBMqTpQESIAESIAESIAESIAESIAESIAESEArAhQoWpHnuCRAAiRAAiRAAiRAAiRAAiRAAiRAAoYhQIFimFBxoiRAAiRAAiRAAiRAAiRAAiRAAiRAAloRoEDRijzHJQESIAESIAESIAESIAESIAESIAESMAwBChTDhIoTJQESIAESIAESIAESIAESIAESIAES0IoABYpW5DkuCZAACZAACZAACZAACZAACZAACZCAYQhQoBgmVJwoCZAACZAACZAACZAACZAACZAACZCAVgQoULQiz3FJgARIgARIgARIgARIgARIgARIgAQMQ4ACxTCh4kRJgARIgARIgARIgARIgARIgARIgAS0IkCBohV5jmsIAjcdLly/4USm9DGGmC8nGVoCF6/EIl1qG2Ls1tB2zN7uTKBTJ2Ds2FvXjB4NyNci2JwuNy5diUXWjKkiOCqH0guBy9ccSGWzIHUqm16mxHlEkMCZizeQI3PqCI7IofRC4OoNJ+B2I10au16mxHlEkMDZSzeQLWNqWCwRHJRDGY4ABYrhQsYJR5IABUokaetvLAoUjWJCgaIReA7rJUCBEt3PAgVK9MafAiV6Yy8rp0CJ7vj7unoKFF9J8bqoJECBEpVhj1s0BYpG8adA0Qg8h6VA4TMgBChQovc5oECJ3thToER37P1ZPQWKP7R4bdQRoECJupAnWDAFikbxp0DRCDyHpUDhM0CBEt3PAAVKdMefGSjRHX9fV0+B4ispXheVBChQojLszEDROux3ECg3b8biwqUryJY1I+w23+pTHDpyAqfOXkClciV9XpkvNVBiHU44nU6kSa3vOikHDh3F5X+vonyZe+F0unDjZizSpWV9hzs9DNzC4/OPiikvZAaKKcPq06IoUHzCZNqLKFBMG9qQLowCJaQ42ZnZCFCgmC2i/q2HGSj+8QrZ1UkIlJ9rPYnpXy3H8nXb4oYRIfDRe22RN3f2Ow79+dzlWLfpJ0wd2c3nKSYWKEdPnMaIiV/ho97t4sTNx1O/weoffsQ3Uz/0uV9fL6z53Js4efq8ujxd2jSoUvE+9OzUHLlyZPG1i7jrxk9fiN//OIwx/Tth8449eLXrUGxc+DGyZM7gd1/RcgMFSrREOul1UqBEb/wpUKI39rJyCpTojr+vq6dA8ZUUr4tKAhQoURn2uEVToGgU/0QC5drwkXh05e+o+Ug5dGjZENmyZMLBw8eVUHm12RModW+hsAuUvQcO49nX+uCnlZMRE+M5neHUmQu4/O8VFC2UP+SgRKC0ePZx1K5WAafOnMcHI6Yjd86smDDkbb/Hii9Q/r1yDYePnkTxe+7yOYPH7wFNcAMFigmCGMQSKFCCgGfwWylQDB7AIKdPgRIkwCi5nQIlSgLNZQZGgAIlMG5muYsCRaNIJhIoh/oPRv1VezFrfG+ULVU0yUldvHwFH437EivW70DGDGnxbP3qaNO8vpIE8TNQ3uo7Hg9XKIXn6leP66djr9GoX/thVCpXCq/3GIk/Dh1T3yt+z93o3aU5ihe9S8kTkSgli90Nm9WKnp2bQ7JSfty9H++/2UJdL1JnwKgZ2LprL4renQ9vtH4GdapVUN8b/PEs2O02HPzrOHb8vA81Kj+Ajq88g7vy5UpyPSJQurz2LJ6uU0V9f9Y3q/HJ9AXYsMBzvHO3AROxafuvOHfhshqrQ6tGeLx6RfW9q9eu46Nxs7F49RakSR2jMlhEmEgGisyx58BJiqXL7UbzDh+qrJq7C+RW946ftgAZM6TDS8/WwfUbNzF8whwsW7sN12/EomzpoujVqTkKF8yr0YMRuWEpUCLHWo8jUaDoMSqRmVOoBcrlf4GMTPaLTPBCMAoFSgggRkEXFChREGQuMXACFCiBszPDnRQoGkUxkUBxjxqFuluOInWqGLR6vh7KlCiCQgXzJMigeLf/BPz+xxG81bYJzl24hEFjZykB8eIztRIIlClfLsFXi9Zi2ayPYLFYsGffX2jSti/WfT0KqVLF4JulG1D+vmKw2e2YNHMxjh4/iXmT+qmvvzdkCiYPe0eJkHuL3oWFy36I2xokdUXqvfguSt9bCC83qYttu/Zi3LQF6l6RLq93H6nESZfXGuOewgUwYsJXqFS+pJpvUi2+QHG73ej24URYrBYM6dVWXT5z/krVT/YsmbBu808Y+elcbFo0DpkzpUe/EdOxfvNP6NCyEe4pnB8TPl+EmBibEije9f68egpcThfK1XkNX0/+ACXuKaj67TloErJlzYSu7Zpi8qzFmP7VMnw8sAtsNivWbtyFh8q0MU/pAAAgAElEQVSXQsUHSmj0YERuWAqUyLHW40gUKHqMSmTmFCqBcvYcMHmGAydPu9HjzRjkvPNO08gsjqOkSIACJUVEvAAABQofAxK4AwEKlOh+PChQNIp/EjVQDj/TFBNnLMLC5RvVpCSr4o3WjZQgkcKyFeu1w9Der+OJxyqp70vGx9adv6n6JPEzUGTbTY1nu+CLj3uh3H3FMHDMTJw5dwEj+nZQ9127fhO79x7En4ePY9evf2Lxqo3Ys26ayj5JvIUnfr8bt/+KNu8Mw6qvRiBvrmyqr6df7omqle7HO+2fVwKlfJlieO3F+up7Xy/+Hl98vSLZ+ikiUHLnzIaC+XNh/8G/1T2j+3dEwfyeTBEpBrvv4BEljWRNY6fOx5yJfVC8yF14oPar6P9uazzzxKPq2vhbePwRKFLj5duVmzDmw064t0gBJZyipVGgREukk14nBUr0xj8UAmXFWhfmf+eEw+HhmCkj8E7HGOT1/Ppm0zEBowmUA3+6sfp7F9q19K2ovo7RG2pqFCiGChcnG2kCFCiRJq6v8ShQNIpHCqfw/HnkBFZ9/yM++XwhPh3aFflyZ0f9Fj2w5IshcVtRvlu5WWVibF86IYFAkRV16j0G2TJnQo9OL+KRBh0x6oM3VJFW2brT6s3BagtLhbIl8O/VG1i+dotPAmX+ku9VFoh3i42M02fYZ+r0G5EziQWKFMMdMXEuln85NEnIIlAeKF0M95cqgnGfLVBbjPq89bK69srV62jXbYSSJ1IXJm+u7Jg08zt8Ob43smbJiLrN3sW3nw9Ckf+22gQqUE6cOodegyapLUkirF5oWBPtWjSIihN8KFA0+tnXybAUKDoJhAbTCEagnDwNTPnCgT//cquZP17TiiNH3di7340M6YGub9hRIF/0iGgNwhf0kEYSKIcOuzHsYwdu3ARq17CiaUNKlKAfAB87oEDxERQvi04CFCjRGXfvqilQNIp/IoFyffgIxHTurLaRxG9VG3ZEs2dqoVnDWqj8dAeMG9gF1Ss/oC6R7Ikla7YoqZL4FJ4NW3crAfFht1dU5sbK2cNV30PGfakyTaYMfxewWLBp5z606zpYCRSRFY1ffR87V0xSW4mkxe937aZdeKPn6LhtNPL95m8MQMliBdGr80sBCRRvDRTZ+vNy50HqFB7JuFm9YaeSQJu+HYfMGdOruZSu3lIJlJL3FsIDtV5RW40erlBafS85geJ2Q107+5P3UaZkEXVt/C08XtYnTp7Ftp9+x4ejZqBHx2ZxmS0aPR0RGZYCJSKYdTuI2QRKbCxw/B+3+ufESTeOHvf8ucjdVrR5mS9d8R/EQAXKdytcWLDYqbrKlQNo3dyOewp7ZMmYTx3YvceNdGmBrh3tKJifEkWvP/xGEShHjrkxdIwD167fItmiqQ2PVk749yS9cjb6vChQjB5Bzj+sBChQwopX951ToOgjRJIBMXT8bHRs/Yx60Xc4nFj5/Xa1/eazkd3xv3IllKzIkD4N+rzVEucvXsabfcahTrWKeLtdk9sEisPpRI3GXVQBVpEU3m014z77Bms3/YRPBr+JGzcdGDPlm7gtPLK1p0LdNuoo5PtLFoXUJZn33bq4GigyZp3n31FZGq++WB87fvodHd8bg/GD3kS1h8sGJVAkCvO+W68yWiYMeQsxdjteefsjzJ/SH3lyZlPFYgeMnqEEyv2liiq5Ilt8unV4ARcvXVGZOPnyZL+tBooU2H2p40A8eP+9aP3CE9j1ywG8N2QyGtR9RNVAkTorUr9F+pSsl0at38M7rz+PejU926TM3ChQzBzdlNdmZIFy+O/bRcmZs8mvuX1rO8qXja4X+kuXgR0/uVCwgCVOcngJ+StQJMNk6kynklLSJOuk4RM2xHg8e1wbN8WBXbvdSJsWeLu9HYUKRhfzlH/q9HGFEQSKyM8hox24chW4r6QFhe6yQASetLc72FHyXj5b4X6aKFDCTZj9G5oABYqhwxf05ClQgkYYkg7ktJtBY2cqWeFtsqUkfjbEoSMn0Ln3WHXKjDTJRBncs43ajjNj3gpVAFXkh7dJVoYIkzVzR6rjgaXJlhU5kUeyUKQ99GBpbPlxj8pAkSZZLbJtSJpkePzx17EE/a7f/DO6fvCJOgVHWrsWTyvpI0228IioeLXZk+q/l6/bjhETv7rjFp74p/DIPVLXRdayYOqHqkDtyu93qL5qVimHNRt3xWWS7Pr1ANq8M1zNQzhJIdmc2TMrgfLb/r/wXJu+kCKyIlDW/LBTiRmRSXISj2TXPPK/+5V4mjp7CYZP+EqNIf3IiUL93mkVFccfU6CE5EfXsJ2EUqCcOg3kyhk+FPsPurFpqwv7/nDh9B1EiSTO5cltQZ5cFpUhIddu/dGF9OmAD3vFRMVJMTt3u/HDFqfKBvE2Wf8DZazqn9IlLHC4nIDbjXRpPMfV36lJnZMlKz0vrhLjV5vbUaRQ8i+vE6c5sX2XC6lTA2+9bkfR/zJUUhqH348cAb0LFNkmNnhULOR0pxLFLOjc1q5k3bQvnfhhiwtp0wC93o5BnqQP+IscSJOPRIFi8gBzecERoEAJjp/R76ZA0VcEJXPk/IXLsFqtyJ41U5KTk4KqqVPHxG1tCWQFx/85g4wZM8DhsiJrxlQJupBMlJuxscn2L5kf/5w+h2xZMiFtmoT3BjKXO91z5txFtfUoa+aMt10W63Di1JnzKkMl8danxBcL17PnLsWJpPjf934ve7ZMUSFOvGunQAn106q//iRjIGsWixIIiVuoBMqcb5xYuc6FrJmBcmWtKFfGGpJPh0+dATZtc2LzNhfOnk84eylYmjePR5TkzW1BvjwW5M5lQXaPJ07QBo9y4I9DbpS734IOr6QsDPQXxZRnJJ/Wb9jiwpbtLvXS6W0iL65elS1NCfsoVQIoW9qC/5W3JyuVhNnUmQ6IHJOWXNZJUrOb8oUTm7e7kCoV0KWdHfcWZbZAylGM3BV6FiiSSTZoVCwuXgKKFbHgzdft6jnytuHjHKreTo7sQO+uMUn+boscSXOPRIFi7vhydUESoEAJEqDBb6dAMXgAg5i+0+XGpSuxtwmUILrkrQYiQIFioGAFONUPhjpw4aIbrV+0qzT4+C1YgSJbRMZPdeCPP29lOnj7lzoY5e+3onxZK+4v7fvL8/UbnowRkSbyAu9taVIDlR60olIFK+7Kb1GfQPvaJAulz6BY3IwF2r5sQ8Xy5qifcO0asHWnS30i/9eRW6xyZAMeeciGRx6yIktmDyWRILt+ceGnX1yQE03ityJ3W1D2PivK3mdRxV+lWOc33zmxar3vWSdJxWL6bCc2bHZBsoI6tbWrTAI2fRDQq0A5fwEYPDoWcjy2PJeyVUcymeI3ee4/HBGLk6egtqZ172JOKaqHJ4UCRQ9R4Bx0S4ACRbehicjEKFAiglmXg1Cg6DIsEZsUBUrEUGsykLxYS8q7t9WoakWTBrfqVgQjUESaiDwRiSLFQtu/aofLBWzf6cLO3S5IjRJvkxegB+6z4sGyViVx4n+a7L3ml9/c2LTNpbZ+xG+SJVG5kg0PBlm/ZO0GF2bOc6raHAN6xagjd0PZ5NPyzEknDIZyGNXXb/vc2LjVpURT/FaxnBVVH7aiVPE7iwp5Ad32kwM//+rC7/stuHnzVi8iXy5fAW7c8HzNn6yTpBY6c64Ta39wwW4HOrWxpzi3kMNih0kS0KNAkZ+hIWNiley7+y4Lunawq5/XpJpI0Q+Hxar6KA9XtOKV5iwSHY5HnQIlHFTZp2kIUKCYJpQBLYQCJSBspriJAsUUYQx4ERQoAaPT/Y3yAtyjf6wSHBXKWbHjPzEhdUFee9mOwgUtCFSgyHYd2bYjrfL/rGj94u0vL7Ll5sefXNj5c8JMErlHMh1EpuTKYVGyZcsOl5qnt8mnyg9VtEKEQFJbjwKF7039FynTsU3oPrWe9bUTa753KXnxZB0bREKEuv17BRAJtGGLE+fibWfKmxuoVsWm4iBZP762+EVkRcjs3uNSGSryyb80X2qd+DqWd4uXXC/chT+btgT0JlBk29lHY2LVVjPJgnqnoz3Fn33JUJPtedIaPWnDk3XMkVmm7ZORcHQKFD1Fg3PRHQEKFN2FJKITokCJKG5dDUaBoqtwRHwyFCgRRx6xAb/+1omlq1wofLcFvd6yqxeTSZ87IKepSHu6ng2VH45FjsyJ8uPvMEORMp/NcmDHT54+mj1rQ82qKb+0XLjoOQ1GXtD3Hbh9u4/0lTO7yBibEify53A02R7w3sBYlV0hn1jLJ9fBtjkLnFi5NmEmiPRbv44NuUNQ4FK2KaxY68T6TbfGkGKalcpb1VGudyrmeqe1JXcKjxwbe+iwG5UrWm87YScYVvMWObFstWcNUodG6tGwaUdATwJFskiGjnWoE55ECHbrHIMM6X1jI1lYkz73yNzXW9uDzlTzbdTouYoCJXpizZUGQIACJQBoJrqFAsVEwfRzKRQofgIz2eUUKCYL6H/LOXMO6N4vVv2XyBORKN62YLEz7ijQu/K78XqrVD6dnvPPKWDcZM8nxLJVRY4FDuR0FXlZkqwUESqyzefBB6xKZEjWSSSabBOS43ilhoqcyhPMtpu5C51Yvsalthm0bmbHn4ddKhNFaohIkwwa+VRcPlH3t8mpQ8vXOPHzr7eEkwiZOtVteKiC9ba6EP727+8xxv72n9T1i5a5sGip52W3XUubyoxi04aAXgSK1DwSeSK/C+T57tbJ/+11C5c48e1ylxJ+3Trx6OxQPlEUKKGkyb5MR4ACxXQh9WtBFCh+4TLVxRQopgqn34uhQPEbmSFuGD/FATnKNrnaAH/+5VbZKFJHQF46mjayoXqV5F9mf/zZjSkzHKoI6z1FPCfZZMxgCBRJTnL0RAek5orUY5ETYgJp3qN9pbht1zduvbRJfRERH1KAVV4OpZW/36K29khdh5SafKIumRp/H7slTsqUsqBmVRvk36FqWggUmbusTbJRpDVrbFPbnuQZZIssAT0IFBGNsq1Ofh9J1ln3LoELzQmfeTLjZMtfn3djkC2J07giS9gco1GgmCOOXEWYCFCghAmsQbqlQDFIoMIwTQqUMEA1UJcUKAYKlo9TlcyFj8Y41Evp4PeTfyGRwqHT59zE1h2el3J5OW/VzH5bcdXZ82+dxlK7ulXJFqM3qbfy3oBYXL0GtGxmwyOV/MuE8GZSCGOp1SCnhSRuIk9WrRMZ4owTKSJsnq5ru23bjWwpWrfRhVXr5Qh7T09SdFXkwmOP2pAnBFuBEs9PK4Ei8xC5JM+VNNmqUau6DY9VtSZbMNToz5se56+1QImNBUZ+4oD8vpKjx2XbTjDSQ/qTTJY/D7tVxlePN+1IHe/oYz3GwAhzokAxQpQ4R80IUKBohl4XA1Og6CIMmkyCAkUT7LoZlAJFN6EI2UT6DvHUEnimvg1P1L6zGJAisv8cT4WpMz2n6cinty2b2VGujEX99ydTHerIW3mZb9XMpo4RNkuTrBpZn5wQJFt5sv533G9K61uy0gXJPpGjed9sb0exInfOChGRItt6JCtFti9Jk3vqP25D3twWrFzvxPebXHGn3mTNAtSqZlP1Tfw5qjmleetJoMhcJAPo22VO9cIrTV52qz9iRZ0atqC2VfnLQavrpaaNFFGWrWtaZOBoLVBGTXDg171uFeseXWKQIwR1j6TQcv9hniOQRQh3bhtYdplWz4Qex6VA0WNUOCfdEKBA0U0oNJkIBYom2HUxKAWKLsKg2SQoUDRDH5aBN2x2YfpsJ7JnA4b0SXlfhPcUHnmxnz7bgZ0/e15m7y9twV9H3EqiyIkyb7xmD6iOR1gWGcJOP53uxLadLnW07lvtU37Z8m4/EaEkW39KFPN9S41sV1j3gwtLVzkhL3qJm9STqV3NGrG6IFpmoMRfuxyHvXytE7t239qyJPKoXi1b0MWEr10HTp9xo2AB3+MUwscrya5+P+DGjDkOnDx969siUe69x4J7i1pxb9Gkj/kO9by0EihygtfiFZ6fATlKXDJPcucM3eqkRtOA4bEq68ssGXOho+N/T5oLlA1bf0HJYgWRI5uPitv/NfIOEgiYAAVKwOhMcSMFikZh7NQJGDv21uCjRwPytQg2CpQIwtbhUBQoOgxKgFOSbSDdP4iFHAfa/hW7qruRUkt8jPHm7S7MmueEvHhKky0nbV62+3U8bkpj6un7soWn98BYXLwEvPy8px5Hci3+0c0iT4RNIE3qyMhxxLK1R2IlWT11alh9qo8SyHjJ3aMXgeKd36nTUCJl/cZbpw1VLG/FE7WsuCt/yqzlpCepG3P4qBuH/3bh76NuSDFlaZLVI8c8P1wxPNuhfImLPGNfLXBCatxIk3o4FguUqEzcChW0oPg98o8VxYpawpKJFGmBInJXCgifv+hZrcRUfrfIqTuhbnIs94jxnuONJ49OWSSHenwz9ae5QOnYazTWbNyFhnUfwQuNHsN9xQubiS/XYnACFCgGD2CQ06dACRJgoLdToARKjveFiAAFSohA6qAb74kw8gn2u51SzqaQKScWKPI1qcExeYZDfRLe4Anj1ztJKTSylUSKysoWkv49k67DsPp7F7782lOzo2MbO8qWTvmFPqVxpWaDZP5k0ehzVb0JFC8vkUqrv3eqbB1vpo5sx5CMFHkmpYls+fu4R5TI6S3yT1JZPUnFoHBBiyquXKmCVW1Zi0ST5+eb7zy1cKTOR/Pn7CrLS5rUIpI6IPv+cOH3/W4cSkKoFMxvQfFikqViVdvrQtGSEygiemw2T22aUDQp7PrNYgfkOG5puXIAjZ60QeRYOJuIuCWrnD5l4oVzHkbvW3OBcv7iZSxcthGfz1uOk6fP4/5SRfFS4zqo/eiDiInx7X90Rg8C569fAhQo+o1NJGZGgRIJykmMQYGiEXgOG/eycs2BVDYLUqcy/4uymaMup+n0+MBzbHHfbr5vt0lKoJiZU3Jrk21P8gm5bMmRE3Xit7U/uDBzrkee+JrZYwSGehUoidmvWONUp0VJk2NuL1xA3DHR8a8VGSJbdSSzQ7Ib5J98eTyyQQTF1h0ubNvlgpyS5G0iZiQzRY6bDkc7dNitttRJTSJp9WpZVRHhO9U8Ecly4KAbv+13Yd9+N47EO41J+pBaPfVq21CzanBzTixQJFtn6UonpDaLNMmCkSyrsqWtCY5B95WT1DeZ/60zbv4iChvUu3OWl699+3qdxFqOGGcLnIDmAsU7dYfTiY3bfsWXC1ZBtvVky5IRLz5TG42ffBQ5s2cJfIW8kwSCIECBEgQ8E9xKgaJREClQNALPYb0EtMxAkU+M+wyOVS85RQpZULSQFVIHIlKfCpvpKRg3xaFqSMhRxM2b+C7DKFA8T4G8tL4/KBbnzgMvPmdDjUc8L6dS3PXzOR550ralLWwv2lo8i0YQKF4uUptHtjx5C85KFocIkrvvsuLuAh5Z4usJLj/vcWPbjy7s2u1Sx3JLk+wjyUiRzJSUigL7EivJLJKjmkXKSZPMmZeaBrZdRbaZSd2UfQdc+OOQJ9tGmtQPqfeYDdUesaqCxv42r0D55xSwZKUTsn0vuSa/k8uUsqrCrPeVvHPmjmxJmrvIiX0HPPOUe5+obcPjNYMTPv6uj9eHhoBuBIp3Ob/t/wsDx8zErl8PxK3wqTqV0azhYyo7hY0EIkmAAiWStPU3FgWKRjGhQNEIPIf1EtBSoMz62qlOJ0ncpGipfPrpFSoiV9iSJyAvKkM/dqg6CYPej/Er9Z4C5RbXfX+41TGo8jL6Qc8Y/H7AhWmzPPLkleY29XJtpmYkgeLlLpkcWbOERrKKPBGJsmWHS50I5G3y+0eETPZsFuTOaUHePBZ1WpKcFuNL27jVBdlOJ4I4YwbguQY2leUSqvbnX24sWuZUJ9hIk602cnJRzUetSJPa91F2/34T3/9gxU+/3Fq71ON5srYV+fJaIHVEft3rUuMc/ydhnRY5tluEimSoFP7vCG8p3jr/Wwd2/defZNnUrWlF3cds6qQrNmMS0IVAuX7jJlau34Evvl6JX/cdQrq0adDiuTqoW+N/2LZrL6Z8uUTRXTN3pDEpc9aGJUCBYtjQhWTiFCghweh/JxQo/jPjHSEloJVAkb+Qvz/IU+Sv7mNWnDztVsUUpf5GUk3+wi7ZKfcU8XziHIojL0MKMoDOfv7Vje27XOq4Wm9thwC6gffY4uefsaFWNf9e1ChQEhKXOidSr0LqNJw64/leSsVlA4mZHu4xokAJFzfJGPnxJxe27nTFZU4kHkvkhMiUPLk8QuXWnz1XHj/hxudfOSGnCkmrVsWKxk/ZwlaAWX5fikjZvccznmxVeexRK2pXt90xi2/vfk82z57fE5569EQtW7K/V+VY4N2/iUxxYe8+d1zmjowrGSYimrzZQfI1+T30ZB2bEkhsxiaguUCZvXANhk/4ClevXVcZJs0b10atqg8idby8K9nes+PnfXiofClj0+bsDUeAAsVwIQvphClQQorT984oUHxnxSvDQkArgTLyE4f6C7x8qi+f7nubFJA8eMiNg3+5IJ+0yl/Kpdhm4ibFTZ963D9ZEBaAfnYqR5du2OxJl5dijd4mn/w2bWRTafn+NKlXMGOOU9WGGNDL/zx+CpSEtCUroe+QWFWkVJpsh5JtUWZsFChJR1VOifnjT5cqenripBunzrhx7IRbFXtNrskxvN5jiSV7pUVTW0B1QwJ5zo4cdWPhUidEyEqT10rJRnm8ZkKBId+X44O9okPKb1Z/xJMh4mt2jXd+yWWnVKlkVXVOfN1OFch6eU9kCWguUN7qOx7p06XB8w1qonTxQpFdPUcjgRQIUKBE9yNCgaJR/ClQNALPYb0EtBAo3lNP5C/6suUkpb+8ywuCSBXP8aRudVSptFCdhhLup0FevCTTROohSA0Db5NtSlL0UupsSJMtOA2ftKlPkX1pUreje79YtVXgzdftKF3C/61OFCi3kxZxN3CkA4Fk9PgSN71cQ4HiXyREeEqm3D/xpIr8t1e2SYZKo/q+//z6N3rKV8vvRclIkVpI0uwiSKpY1VYk2VbkLWQrGSO1qtnwQDkHCuRKpY5SDqadPQ/88psUYLYiT65geuK9eiSguUD5Yt5K5M+XAzUql0vA5/DRk5g8azF6dmqOtGlS6ZEd5xQFBChQoiDId1giBYpG8adA0Qg8h/US0EKg9BoQqz7dlaMsn6zjmyyIH7FV612YPd+p9vv3ficG8umvHtuBP93qxWXbTlfcp9dSr+Dh/1lRtZKnzoA0YfHFXAcktV6ar59ge48tluNQO7UJ7DRHCpSknxzZHiGCy8yNAiV00ZVCrCJAU5LBoRsx+Z5ElHy3woUduxLWl5K5yVHQsmVQ5HVyxxhHYo4cwzgENBcoHXuNRqnihfB6iwYJqJ0+ewHVG3fBN1M/xL1FChiHKGdqKgIUKKYKp9+LoUDxG1lobqBACQ1H9hIwgUgLFK/8kBTvge/FqE9JA2kTpzlVVod84tm7a4xuihReugxs2ubCD1uckJcqafIJrxRbrPqQDWXLWGBLxhlt3+nC7G+ccVt7qj5sVQUo0yVxDKd86t17oGdvU/+eMcgVoESiQAnk6TPHPRQo5ohjcquQ3z+Lljpx5KhLbeeRQra2eAd0UaCYO/6hWp0uBYrUPFmyegt6DJyE9fNHI0e2zKFaL/shAb8IUKD4hct0F1OgaBRSChSNwHNYL4FIChQp1Nitb6w6MrZdKzsqPBD4J/wOBzBwhANHjrnV0Zqd2wZoYkLwKLhcgByNKtJEtifJf0uTzJhHHvK8uPj6yfSNG8CCJZ5CptKPZKxIIcpHHrImSLUf+6lDjVm7hhVNG/p+bHHi5VKghOABMGgXFCgGDVyIpk2BEiKQJu9GM4FStWFHnLtw+Y54H69eESP6djB5CLg8PROgQNFzdMI/NwqU8DNOcgQKFI3Ac1gtBMqseU6s2eBSJ8682yl44SE1CfoM9tQAafiEDfUjXFRWPuH1FoSVzBNpqVMBFctZlfC4p0jggkhOKZo+26lqv0grXNCCl1+woUA+C/YfdOOjMQ4lVwb3ifHr6FIKFP7sewlQoET3s0CBEt3x93X1mgmUb5ZuwLXrNzF7wWrkyZUN1ePVQImJsaF8mXtR9O58vq6D15FAWAhQoIQFq2E6pUAxTKhCPlGny41LV2KRNSNrcIUcrgE6jFQGyomTt7ac9O1mVyIgFE3qjAwZ7TkOuUs7u9oqE84mGSJS00Rqm8QvCFusiEVJE5EnqUL4oyTbgaTWiZxOJE0KzO494FZHpobieF1moITzadF33xQo+o5PuGdHgRJuwuboXzOB4sX3y++HkCFdGhQumNccRLkKUxGgQDFVOP1eDAWK38hMcwMFimlCGdBCIiVQvMcWV6tsxUtNA99yktQi125wYeY8T1HZ998JvB7InQCKqJHTcnb85Io7Vlm25cixnbJNJ1eOgPD7dNPVa8C8Rc6403rkpoL5LXj/3eCzeChQfAqBKS+iQDFlWH1eFAWKz6ii+kJNBIrUOLl5MxZp06SGJdhzoqI6fFx8uAlQoISbsL77p0DRd3zCOTsKlHDS1X/fkRAov+51Y9QEhyr0Ovj9GGTMEHoun81yqqyQvLmB96SobAiyQGSLkPT5w1Zn3FGlMnOp3VKlkk3VXolkk3ovM+Y4ceiwG9062yFZL8E2CpRgCRr3fgoU48YuFDOnQAkFRfP3oYlAWbfpJ3ToOQpLvhiC0ZPnYfm67cmS3vTtOGTOmF7zSLjdbjhdLtjjl2rWfFacQLgJUKCEm7C++6dA0Xd8wjk7CpRw0tV/35EQKN5ji6XYqRQ9DVcbMNyBQ0fcKHe/BR1eCTw7Q2qbLFjswI6fPPVHpMmRw5I981AFK9KnC9cKfOt3z+9ulC4RvDyR0ShQfGNuxqsoUMwYVd/XRIHiO6tovlITgfLnkRP4buUmtCZUUtQAACAASURBVHj2cezacwBHj59ONgZNnq6B1HIwt8bt2xWbMHLSXKyZO1LjmXD4SBKgQIkkbf2NRYGiv5hEakYUKJEirc9xwi1QvMcWyxYXOW43nJ/NxC8q2+hJG56s45+sOXseWLjEic3bXXC7oY4PrlTBikcqWXH3XaERFnp7CihQ9BaRyM2HAiVyrPU4EgWKHqOivzlpIlD0hyH5GR05dhKvdR2GoydOI3fOrBQoRgpeCOZKgRICiAbuggLFwMELcuoUKEECNPjt4RQocmxxjw9iITU8OrWx4/7S4ZcQsr1l8CgHnC7grfZ2lCqe8phyis+iZU6s3+iC0wlVBLZWNSvqPmZTEsXMjQLFzNG989ooUKI39rJyCpTojr+vq9dcoPz820Gs/H4HXn3hSWTJnAEr1u/AjHkrkCF9WvTo2AwF8+f2dS1huU7qtZw5dxFrftiFybO+o0AJC2X9dkqBot/YRGJmFCiRoKzPMShQ9BmXSM0qnAJl1tdOrPnepSSGyIxINTm5ZupMJ9KmAXpLUdlkCrxeuw4sW+3EynUu3LwJ2G1A9UesqP+4TR0RHA2NAiUaopz0GilQojf2FCjRHXt/Vq+5QOn6wSc4efo8ZoztidNnL6B64y64t0gBXLx8Rf17wpC3/VlP2K5dumYrhn4y+zaB4nTe2gsctsHZsWYEYp0u3LjpRIa0yW0jY/w1C04EBpaXqDSpbIixpfxpbQSmwyEiSEB+tf97NRaZ0ye/hZQ//REMSISHunLDiVRWC2Ji/NvuktI0T58B3h/kVJd90MOGnGE8pSapucyc68KGzW7kzgn0etuW4Gjhm7HA2g1uLF/tUtkxVivwcEULnqprRZbMKa0s9N/X8rfu+X9jkTWD9tvHQ0+VPaZE4NpNF2SvWtrUoT0VK6Vx+f3EBLT5DXD+35vIkiEVtBk9ck+BjX+vDQq25gLl6Zd7onH9anj5uccx97t16DtsGtbOG4UrV6+hfose2LHsU6RNE4Ky8UFhApITKOcu3wiyZ96uZwKy31v+kb9IJt3M/itWz9EJ/9xcLjesEmKeFhZ+2Hobwe2GS/3sJ/8zzp9+vQUtdPORn335G7Q1xD/7k6cD+w5YUPVhN55+MnTz9bUn2Yoz7lML/j4G3FfKjZebQW3P2fqjBavWunH5skX9unugDFC3NpAtq3aaULuRAfW7/w4/+77y5nXGIyCHRkjjKaFax06b3wAul/zelwdA6/WHd/xsGVOHdwCT964LgfJCo8fwQsPH0HPQJOw9cBjfTP0QV6/dQMV6bTF7Qh+UKVFY8zAkJ1A0nxgnEFYC3MITVry675xbeHQforBNkFt4woZWNx3/8psb3y53Imtm4PXWCbfShGMLz2/73Bgx3qG2wQzsHaNZHZFLl4H+Q2Nx/iJQ6UErDh5y4cw5T1jKl7Wg4RM25Mtj8reHFJ5CbuHRzY9pxCfCLTwRR66rAVkDRVfh0O1kNBco7w2Zgp2/7EfLpvXQb/g0tGvxNDq2fgZSG6VZ+/5YOXsY8uWJcI5rEuGiQNHtMxzWiVGghBWv7junQNF9iMI2QQqUsKHVTcdDRjtw4E/Pp5wvPmtDjaq3Ug3DIVB6D4zFiZPAS01sqFYltFuD/IV6+G83+g9zxN12X0kL5IQes56q4y8fChR/iZnnegoU88QykJVQoARCLfru0Vyg/H38FF7uPEjVQZFTbiT7JHPG9Ojy/sfYvfcgVs0ZoWkapaTyORxOLFu7TR1jvHzWUFisFtjDeeZg9D2Hul0xBYpuQxORiVGgRASzLgehQNFlWEI2KTlhpkvP2AT99XnXjrvyezIvQi1Q1m5wYeY8Jwrks6Bvt8gVjr0TMDmW+PtNLjR+yoZ7ikR3xkliThQoIftRM1xHFCiGC1lIJ0yBElKcpu1Mc4EiZG/ejMWJU+dwV75ccbJk928HkTlTBtxdQNtTeP44dAwNWvVK8AA8VacyBvdsY9qHggu7RYACJbqfBgoUjeLfqRMwduytwUePBuRrEWwUKBGErcFQGza7MH22ExUesKgPRbbvdCFXTqDvuzGqsGooBYqcatOtr+fY4nc72XFvUcoKDULu15AUKH7hMtXFFCimCqffi6FA8RtZVN6gC4Ei5KVg17XrtxdkTZ8uTVQGhovWBwEKFH3EQatZUKBoRJ4CRSPw0TPs6IkOSA2UNi/bUPY+K/p9FItTpz01QV5rYQupQJk934lV610of78F7V/RR/ZJ9EQ6sJVSoATGzQx3UaCYIYqBr4ECJXB20XSn5gLl1JkLmDhjEVas345zFy7fxn7Tt+PUlh42EtCCAAWKFtT1MyYFikaxoEDRCHx0DCuf1bzxrmf7ztghMUibBjhyzI0PPvLUBGn9og1lyriQymZB6lTBHWW65nsXZn3tObZ4cJ8Y5MgWHYyNvkoKFKNHMPD5U6AEzs4Md1KgmCGK4V+D5gJl4JgvMHP+KnRo1Qj58+SA3Z7wLyt1Hq2AmBh+YhP+R4EjJEWAAiW6nwsKFI3iT4GiEfjoGHbbThc+ne6EFE7t0u7W3y9Wf+/Cl187kSoG6NrZivy5EZRA8coTORZYTvmRDBQ2YxCgQDFGnMIxSwqUcFA1Tp8UKMaJlZYz1VygVG3YEc89VR2dXmmsJQeOTQJJEqBAie4HgwJFo/hToGgEPjqGnTDNiR27XHipqQ3VKic8Dce7tSdPLqB7FysypA8sA2X5GhfmLnTCagXataI8MdqTRYFitIiFbr4UKKFjacSeKFCMGLXIz1lzgdKu23BVPLZX55civ3qOSAIpEKBAie5HhAJFo/hToGgE3vzDOpxAx26xiI0FRg2MQYZEO4Sl0GufQbE4fxF45CELWr7gfwbsomUuLFrqkSdvvGrH/aWZeWK0J4sCxWgRC918KVBCx9KIPVGgGDFqkZ+z5gJl4/Zf1ZHFS2cOQY5smSNPgCOSwB0IUKBE9+NBgaJR/ClQNAJv/mF373FjzKcO3FPYgu5dkpYjhw67MXCkA243VNFXf7beSNaJZJ/YrEAHyhPDPlAUKIYNXdATp0AJGqGhO6BAMXT4IjZ5zQVK1w8+wdI1W5NdMIvIRuxZ4EBJEKBAie7HggJFo/hToGgE3vzDTvvSiR+2uNCkoQ11aiTcvhN/9V8vdmDpCjdSpwb6dfet+Gt8edK5nR2lijPzxKhPFAWKUSMX/LwpUIJnaOQeKFCMHL3IzV1zgbJ6w078ffxUsit+odFjSC0V3dhIQAMCFCgaQNfRkBQoGgWDAkUj8OYeVjJKuvSMxZWrwJA+Mch+hxNxLl114OOJbvz5F3BXfgve62pXWSXJtVnznFizwQWpg9+pLeWJ0Z8kChSjRzDw+VOgBM7ODHdSoJghiuFfg+YCJfxL5AgkEDgBCpTA2ZnhTgoUjaJIgaIReHMPu+8PN4aOdaBAPgv6drtzbZPL1xy4ftWCAcNd+PcKULuGFU0bJl1QdvpsJzZs9siTN1+3o3gxZp4Y/UmiQDF6BAOfPwVK4OzMcCcFihmiGP416EKgnL94GWs37sKxf86gZpXyKF28EBav3oLsWTPhofKlwk+BI5BAMgQoUKL70aBA0Sj+FCgagTf3sLPnO7FqvQtP17Ph6bp3SCcBIAIllc2CP/+yYvg4hwLTua0dZUrdkiOS0fL5HI88iYkBurSlPDHLE0SBYpZI+r8OChT/mZnpDgoUM0UzfGvRXKCcOHUOT7/cE1evXVerHNyzDZ6qUxnDJ3yFBcs2YO3Xo2C3BXaMYPiwsedoIUCBEi2RTnqdFCgaxZ8CRSPw5h727d6xuHgJKvtEslDu1LwCJXUqG+YtcmLZahfSpgU+7BmDzJmgCsxOnenE5u0eefJ2B7sqTMtmDgIUKOaIYyCroEAJhJp57qFAMU8sw7kSzQXK+GkLsGbjLozu3xH9hk/DU7UrK4GyZ99faNK2L5bN+kgdc8xGAloQoEDRgrp+xqRA0U8sIj0Tp8uNS1dikTVjqkgPzfHCQODw3270H+ZA9qzAkL4p11WLL1BkOgOGO3DoiBv3FLGge2c7Jk53YvtOypMwhEoXXVKg6CIMmkyCAkUT7LoZlAJFN6HQ9UQ0Fyg1n3sTr71YHy80fAxt3hkWJ1AuXrqCyk93wOwJfVCmRGFdQ+TkzEuAAsW8sfVlZRQovlAy5zUUKOaK64IlTny33IXHa1rxXIOUs1oTC5Sz54D3B8Xixk0gZ3bg9FkgVSrgrfbMPDHXk+JZDQWKGaPq25ooUHzjZNarKFDMGtnQrktzgfJC+/4of18xvNP++QQCZftPv6Nll8FYP380cmTLHNpVszcS8JEABYqPoEx6GQWKSQPrw7IoUHyAZKBL+gx24NgJN7p38U14JBYostSdu90YP8VTD0WON367vR1FCnHbjoEeA5+nSoHiMyrTXUiBYrqQ+rUgChS/cEXtxZoLlMmzFmPijG/xYbdXMGfhGrV9555C+dFtwERkzpQBX47vHbXB4cK1J0CBon0MtJwBBYqW9LUdmwJFW/6hHF2yR7r1i0X6dMCogTGw+OA8khIoMqcZXzmxdYcLb79hR+GCPnQUyoWwr4gRoECJGGrdDUSBoruQRHRCFCgRxW3YwTQXKA6nE90HfIqla7YmgFggb06MH9QFRQvlNyxcTtz4BChQjB/DYFZAgRIMPWPfS4Fi7PjFn70UgJVCsNWqWPFSk5S378i9yQmU2FjgxEk3ChagPDHPE3L7SihQzBzdO6+NAiV6Yy8rp0CJ7vj7unrNBYp3or/uO4TfDxzBv1euoWCB3Hj4wdJIm4bF+3wNJK8LDwEKlPBwNUqvFChGiVTo50mBEnqmWvU4cIQDfx52o0s7O+4r6Zv4SE6gaLUGjhtZAhQokeWtp9EoUPQUjcjPhQIl8syNOKJuBMrVazdgt1mRKlXK1fGNCJpzNiYBChRjxi1Us6ZACRVJ4/VDgWK8mCU1Yzm2WI4vTpMaGDM4Blarb+uiQPGNk1mvokAxa2RTXhcFSsqMzHwFBYqZoxu6tWkqUK5dv4lPpi/Aph17sPfAYbWqSuVKona1CupUHjYS0JoABYrWEdB2fAoUbflrOToFipb0Qzf22g0uzJznRKUHrXithW/bd2R0CpTQxcCIPVGgGDFqoZkzBUpoOBq1FwoUo0YusvPWTKBc/vcqOr43BnLazsMVSuO+4oUh9VB+3nMQO3/Zj+cb1ETPTs1hs/n4cVFkuXG0KCFAgRIlgU5mmRQo0Rt/ChRzxH74OAf27nfj9dZ2PFjWt+07FCjmiH0wq6BACYaese+lQDF2/IKdPQVKsASj437NBMoHIz9Xp+6MH/Qmqj1cNgHtLxesxoejZqBv15Z4rn716IgEV6lLAhQougxLxCZFgRIx1LobiAJFdyHxe0LXrgOduseqbTtjh8TAnx3CzEDxG7epbqBAMVU4/VoMBYpfuEx3MQWK6UIalgVpIlBu3oxFuTqvoUOrRmj/coMkF9ap9xicPHUecyb2CcvC2SkJ+EKAAsUXSua9hgLFvLFNaWUUKCkR0v/3N293YcoXTpS9z4KOr9n9mjAFil+4THcxBYrpQurzgihQfEZlygspUEwZ1pAvShOBcuLUOdRq8hbmTeqHksXuTnJRi1dvwbv9J2DPumkhXzQ7JAFfCVCg+ErKnNdRoJgzrr6sigLFF0r6vmbcFAd27XajVTMbqlTybzswBYq+Yxvu2VGghJuwfvunQNFvbCIxMwqUSFA2/hiaCJTf9v+F59r0xfr5o5EjW+YkKW7Z+Rteeesj7Fj2KY8zNv5zZtgVUKAYNnQhmTgFSkgw+t9Jp07A2LG37hs9GpCvRbBRoEQQdhiGuhkLdO4RC4fDc/pO2jT+DUKB4h8vs11NgWK2iPq+HgoU31mZ8UoKFDNGNfRr0kSg7PzlAF7qOABbF3+CDOnTJrmqn387iGbt+2PTt+OQOWP60K+cPZKADwQoUHyAZOJLKFA0Ci4FikbgzTOsZJ5IBkqJYhZ0fcO/7TtCgQLFPM9CICuhQAmEmjnuoUAxRxwDXQUFSqDkous+TQVK7pxZk6UdG+vAuQuXKVCi63nU3WopUHQXkohOiAIlorhvDUaBohF48wwrtU+kBkqzxjbUfNS/7TsUKOZ5DgJdCQVKoOSMfx8FivFjGMwKKFCCoRc992oiUI4cO4nP5izzifK77V/gFh6fSPGicBCgQAkHVeP0SYGiUawoUDQCb45hXS7P6TvXbwDD+8cgcyb/18UMFP+ZmekOChQzRdO/tVCg+MfLbFdToJgtouFZjyYCJTxLYa8kEHoCFCihZ2qkHilQNIoWBYpG4M0x7N79bgwf50Chgha897b/23eEAgWKOZ6FQFdBgRIoOePfR4Fi/BgGswIKlGDoRc+9FCjRE2uuNAACFCgBQDPRLRQoGgWTAkUj8OYYduY8J9ZucOGZ+jY8Udv/7TsUKOZ4DoJZBQVKMPSMfS8FirHjF+zsKVCCJRgd91OgREecucoACVCgBAjOJLdRoGgUSAoUjcCbY9i3e8fi4iXgw14xyJMrsDUxAyUwbma5iwLFLJH0fx0UKP4zM9MdFChmimb41kKBEj627NkEBChQTBDEIJZAgRIEvGBupUAJhl5U3/vnYTcGjnAgb26gf8+YgFlQoASMzhQ3UqCYIowBLYICJSBsprmJAsU0oQzrQihQwoqXnRudAAWK0SMY3PwpUILjF/DdFCgBo4v2G+ctcmLZapfauiNbeAJtFCiBkjPHfRQo5ohjIKugQAmEmnnuoUAxTyzDuRIKlHDSZd+GJ0CBYvgQBrUACpSg8AV+MwVK4Oyi/M5ufWNx9jxU8VgpIhtoo0AJlJw57qNAMUccA1kFBUog1MxzDwWKeWIZzpVoLlCmzVmGQnflwSOVysBuC/zTonBCYt/RS4ACJXpjLyunQNEo/hQoGoE39rDH/3Hj/UEOdWyxHF8cTKNACYae8e+lQDF+DANdAQVKoOTMcR8FijniGO5VaC5Q+o2Yjq8WrUXunFnxcpO6aPj4I8icKX24183+ScAnAhQoPmEy7UUUKBqFlgJFI/DGHva7FS4sWOxEzUetaNY4uA9kKFCM/SwEO3sKlGAJGvd+ChTjxi4UM6dACQVF8/ehuUARxL/s/ROzF67BgmU/KOJNnq6B5xvURPGid5k/AlyhrglQoOg6PGGfHAVK2BHrdgCny41LV2KRNWMq3c7RzBPrO8SB8xfcyJAeSJ/eov6dId6/0yf4b8/3Rn7iwNHjbrzzhh3FiwW+fUe4UqCY+elKeW0UKCkzMusVFChmjaxv66JA8Y1TtF+lC4HiDcK5C5excNkPmPH1Cpw8fR4VHyiBlxrXQbXKZbm9J9qfVI3WT4GiEXidDEuBopNAaDANChQNoP835Oz5Tqxa7wpoAunTAaMHBbd9hwIlIPSmuokCxVTh9GsxFCh+4TLdxRQopgtpWBakK4Fy8dIVLFqxEZ/NWaoESrq0aXD12nVky5IR7Vo0wIvP1AoLBHZKAskRoECJ7meDAiV640+Bok3sf9vnxojxjoAHr1LJilbNgtu+Q4ESMH7T3EiBYppQ+r0QChS/kZnqBgoUU4UzbIvRhUD5dd8hzFm4FvOXfK8WWrNKOTRrVAuVypfCvoNHMGPeCmzZ+RvWzB0ZNhDsmASSIkCBEt3PBQVK9MafAiXysf/3CvDegFjIv1s0teHRytbIT+K/EbmFRzP0uhiYAkUXYdBkEhQommDXzaAUKLoJha4norlA8RaRlWwTyTB57qnqyJ8nx23QLl6+gswZWVxW10+TCSdHgWLCoPqxJAoUP2CZ7FIKlMgHdPg4B/bud6NsaQs6trFHfgLxRqRA0RS/5oNToGgeAs0mQIGiGXpdDEyBoosw6H4SmguUTz5fiAJ5cqJ2tQpIk5rF+nT/xETZBClQoizgiZZLgRK98adAiWzspeaJ1D6RYrED3ouB1DLRslGgaElf+7EpULSPgVYzoEDRirw+xqVA0Ucc9D4LzQVK32HTUKxIfrz4TO0ErPYd/Buvdx+Bryd/gKyZM+qdI+dnUgIUKCYNrI/LokDxEZQJL6NAiVxQj51w44OhDjidwJuv21G6RHAn6IRi5hQooaBo3D4oUIwbu2BnToESLEFj30+BYuz4RWr2mguUjr1Go1TxQni9RYMEaz599gKqN+6CeZP6oWSxuyPFg+OQQAICFCjR/UCEUqCMm+zAgw9Y8VAF7eo6RHc0/Vs9BYp/vAK9OjYW6DskFidPA489asULjYMvABvoXOLfR4ESCorG7YMCxbixC3bmFCjBEjT2/RQoxo5fpGavmUDZe+AwYmMd+Gj8bBQumBfP1a8Wt2aH04mla7Zi1jersWPZp0ibhlt7IvVAcJyEBChQovuJCJVA+fFnNz6Z6jlZpMIDFrR43o50aaObrd5XT4ESmQh98ZUT6za6kDc30L9n8McPh2rWFCihImnMfihQjBm3UMyaAiUUFI3bBwWKcWMXyZlrJlCqNuyIcxcuJ7tWObr4lWZPomWTupHkwbFIIAEBCpTofiBCIVBu3gR6fRiL8xdvscySGXj1JTtKFNN+q0J0Rzj51VOghP/J2L3HjTGfesTiB93tyJdXPz8PFCjhj7+eR6BA0XN0wjs3CpTw8tV77xQoeo+QPuanmUA5+NcxxDqcGDD6C9xTOD+aPl0jjkhMjB2F78oLq1U/f5nSR7g4i0gToECJNHF9jRcKgTJvkRPLVruQP68Fb7xmx8RpDvx1xK0WWruGFU0b6mPLgr7Iaz8bCpTwxuDiJaD3wFhcvQY0aWhDnRr62tpGgRLe+Ou9dwoUvUcofPOjQAkfWyP0TIFihChpP0fNBIp36Vev3YDNZkXqVPpJ3dU+LJyBXghQoOglEtrMI1iB8s8pz0ui2w2897YdhQpa4HIBi1e48O1yp/qzbF1o/0qM+jebfghQoIQvFvLzMHSsA/sPunFvUQve6WiHRWefl1CghC/+RuiZAsUIUQrPHClQwsPVKL1SoBglUtrOUxOBcvb8Jfz+xxGUL3MvTp89j8v/XkuWQol7CirBwkYCWhCgQNGCun7GDFagDBrlwMFDbjxSyYqWzRJmmhw64lbZKGfOAnYb0Ki+51N4vb1IahKNTp2AsWNvDT16NCBfi2CjQAkf7OVrXJi70KnqAEndk8yZwjdWoD1ToARKzhz3UaCYI46BrIICJRBq5rmHAsU8sQznSjQRKOs2/YQOPUdhyRdDMOyT2VizcVeya9z07Thkzpg+nAzYNwkkS4ACJbofjmAEypYdLkye4UTatMCg3jHIkMSvsRs3gC+/duKHrS4Fungxi6qNkjVzdHNXsoQCJSIPwZWrQPp0ERlKDXLkmBsffOSpe9LhFTvK3a+z1JP/UFCgRO6Z0ONIFCh6jEpk5kSBEhnOeh2FAkWvkdHXvDQRKFI8Vk7h8WSgXMC/8je4ZFrxosxA0dcjE12zoUCJrngnXm2gAuX6DaB7v1j8ewV4qYkN1arcOYvu51/dmPyFA9euAWlSA61ftKN8WX2+WEbkiaBAiQjmk6eAgSNj8chDVjz7tC3s2U83bgJ9BsXizDmgSiUrWiXKyorIon0chALFR1AmvYwCxaSB9WFZFCg+QDLxJRQoJg5uCJemiUAJ4fzZFQmElQAFSljx6r7zQAXKrHlOrNngQuGCFvR62+7TOqWo5uQZDuzd7ykwW7GcFS2a2lQGS9Q1CpSwh/zceY88ufDf6VClilvweit7WJ+36bOd2LDZhRzZgH49YpA6VdiXGfAAFCgBozPFjRQopghjQIugQAkIm2luokAxTSjDuhBNBIps2Tl6/JRPC2vaoCYLzPpEiheFgwAFSjioGqfPQATKkaNufDDUs0Xh/XfsKFjAv0ySVetdmD3fqe7PmgVo39qOwnf714dxCCczUwqUsIbw0mVg8KhYnDoDVcRVMqWO/+NGrhxAp7YxyJMr9MPv3O3G+Cmen4ueb9lRROfPNAVK6J8BI/VIgWKkaIV2rhQooeVptN4oUIwWMW3mq4lAeavveCxft82nFbMGik+YeFGYCFCghAmsQboNRKAMGO6AFIitWdWKZs8GdkTx8RNufPq5E0ePu1HyXgve7uBbFotBsKY8TQqUlBkFeIXsmP1ojAPHTrhxTxEL3mpvV6dBSfbTT7+41Raydq3suK9k6KTd+QvA+4Nj1Ra1Bk/Y8NTj+i8MT4ES4ANmktsoUEwSyACWQYESADQT3UKBYqJghnEpmgiUMK7H565v3ozF+Yv/IleOLLDw2AufuUXbhRQo0RbxhOv1V6Cs3+TCjDlOZMoIDOgVE9R2CKkX0eGdWDWhUQOTLkJr2uhQoIQltPJMDfvYgUOH3bj7Ls/xwSJMvG3hEie+Xe4paNz4KRvq1QpedGzb6cKCJU6cOg0ULWxBjy7GkIEUKGF5BA3TKQWKYUIV8olSoIQcqaE6pEAxVLg0m2zUCRS3241PPl+EcZ99o6Bny5IRHw/sgrKliiYZhNUbdqJT7zG3fW/nikncWqTZYxu5gSlQIsdajyP5I1BkG0SP/p5P2V9pbsPDFYN/+Rz5iQN7fnerWiiPVg6+Pz0yTnJOFCghD1VsLCDP0/6DbrVFp8ebMUmeviNZKJ9+7sDNm0ClB61o+YINMTH+T2fnz24lTmRrkLSMGYBeb8UgR3b/+9LiDgoULajrZ0wKFP3EItIzoUCJNHF9jUeBoq946HU2mgiUg4eP49sVm/Byk8ex69c/7lgPJdQ1UHb9egDN3xiAGWN7okyJIhgzZT4Wr96MVXNGwGq9PWV51YYf0WPgJMyb1C9BDAvmz8XMFb0+1SGcFwVKCGEasCt/BMrUmU5s2uYK6afsUnBTCm9KgU/ZahE1jQIlpKGWLTofT3Zg9x63KuDa6+0YJTSSa7KFbPREB86eBwrmt6BTWzuy+Hi0tgiYhUud+PvYLXFS9zEbalS1IlUAIiakTDLcqwAAIABJREFUIPzojALFD1gmvJQCxYRB9XFJFCg+gjLpZRQoJg1siJeliUBZv/lntO8xEku+GILRk7++Yz2UUNdAGT7hK+z94zAmD3tHoTx15gJqPNtFCZKSxe6+Da8IlH7Dp2HDgrEhRs/ujECAAsUIUQrfHH0VKH8ccmPwKE+BzA+625Evb2jqR0i9is49PNt4Rg9KOmMgfKvXsGcKFMhR2PIUpY63xSbQiEz63ImtP7qUBOnRJQbZs6Xckzx7n0x14PcDbiVb3njVruRgcu2X3zwZJ4f/viVO6j9uw6MPWwPKYEl5huG9ggIlvHz13jsFit4jFL75UaCEj60ReqZAMUKUtJ+jJgLF6XT9v70zgbOx+v/45y4zDMbYRbLv2SOEbJWULEVCtpCx70uW7Hv2yE5EQtn3bJGlUj+UslMiW3aDmXvv/3/OdMfMGObeO3c5z/N8zuvVqzLnOef7fX+fwX3PWfDgYSRCkgf7fRVHz6GfIW1YKvTv0jSG/vNVWmD6qG6oXL54ggKly8CpqFOjApIlC0bp4gVQo0oZWC2eHQ4Z+JIzAncIUKC4Q0t/fV0RKOKn+wNHReLSZaBGNTMa1PHu7w0Tpkfh6DEHmr9nQaXyBtnGQ4EiV4CcPO2QW7derWJxeQVI/O/CRcts2PW9XW7X6dc9CJkzuv59Kt7tZatsEDdDiT/ymja0oGLZuO+geDeFODl9NlqciPN/5IqTitoUJ046FCiuvyd67EmBosequpYTBYprnPTaiwJFr5X1bl4BESgJpXDizHmcv3gFdpsD2bNlQt6cz/pErnzY6xMUyJMdPcLfjQmjTM1wDO7ZAm9WL/dYaEf+OCNXyISFpsSFS9ewbM0ONK5XPUbAXL/90LsV4WhKERBn5jgcSHB7l1KBMhifELDZHRA7+5520PTuvSas2QCEhjrwUXd4/aftP/xkwvJVQIF8DrRu7pM0lRs0Ra9uSDZzekxc98ZOwIPwDn6N0wGHvJ3GksDWTl8HsmuPCes2xZ2leFGgaiUHns3q+uzrNwM7d5vkQbHt2ziQ5RnXn43d8+AvJiz9OvpXKpRzoG4t4PRZEzZudeDsuehVKalSOfBKFRPKvuCAVUNbdZ5ExG53QJwvz0PmPXtntP6U+L0/EN/7Wuemh/jt4i99/7+a1MwLJvRQTrdzMMr3ftrQYLfZ8IFHBAIuUO7cjUB4nwkQZ5PEbiWL5MPIj1oj+7OZvVovsQJFHBzbr/P7MeM+bQVK/Mm/2fAdBo6dh0Pb5spVKFG26BsL2PRJINLmwIOHNqQKMdD5E/ospUdZ3YmIQvJgC6yWhLcu3LwFfDzSBnG7SdsWFpQs5tE0T31IHE7bc6BN9pk4wpKkm328H51+RxTy5E5EJFKn9K8NOH4SmDA9ut4Vyppw/YYDR4894pw3F+SKFCFUntY2bXNg1Xo7goOB7u0tyJk9abU69xcwfa4N4p2P3cSKkxrVzXi5vMnr8jBpESft6bsPbAgymxAcZJBVX0nDpbunb9yJRJpU/v3e1x1EjSZ0/6Ed4idnyZN5dzWpRnEYLmzxvR+WMkgKdD03q4V/tiWlvgEXKCMmL8KSldvkihAhTZIFB+GH//2Bhcs3I1WKEHwzb5hXt8uIM1COnfoTs8b1lNwSOwMlPtzdB44gvM94HNw8C8mT0d4l5eXTwrPcwqOFKvkuxsS28MxcYMOPv9hRKL8JPTr4TrI5t/F80MSCl17kH3q+q/ijkcVPoW7djYQ/f0pz/SYwZEwkhDQTtziJ25xEE9vDtu+2QRwq/DD6SBxkTA+8UsWCSuXMUpLEbjv22LF4ebSE6dnRioL5vPM3wVu3gU9nR+H0uehzUd58zYJXKuvzfeQWHn98l6k7B7fwqFsbX0fGLTy+Jqz2+NzCo3Z9VIku4AKlUt1OeKFYAUwa2jEOk3Vb96HPiJlYOW848ufO5jVej27h6Y+ihXJj8pwV2LBtf8wtPAuWbYK4uljc0iOakDsF8jyHwvlz4ubtO+g1dAaCrBbMm9jHazFxIHUJUKCoWxt/RPY0gfL7cQfGT4s+OHbkwCBkyuC7iJy38RR73oTOH/pO1PguA+2NHAiBMnJilDxLJFtWE/p3tz62okMcLLtnvx3f7rLh6rVopilCgCoVzaj+sgVhqYH9P9kxZ1G0PBHvinhnvN3EgbTiimM9NwoUPVc38dwoUBJnpNceFCh6raxreVGguMbJ6L0CLlBa9xwnzzvp27FxnFrcuHkHFep0xJfTB6JY4Txeq5M40+LT+SsxY+Ga//7ymRyzxvWQq19EGzd9KZat3YkfN86Q/z9h5jLM/XJDzPwilnEDw5Etixsn8Xkteg7kbwIUKP4mrtZ8TxMo/YZF4vJV4K0aZtR5w7dLfcWKhK79opceTB0ThJDkanHSYzT+FiiLV9iwY7ddbtEa1DtIXjf8tHboV4cUKULkOVvJYib8cjj6/9s2t6BMKX1LDl++dxQovqSr/tgUKOrXyFcRUqD4iqw2xqVA0UadAh1lwAXK5p0/YsCYufh22Xh5UKuzHTx8HM06j8QPG2YgZQrvf1q4/+Ah/r1+C89kSp/oAaGi75VrNxCaMgXShKUKdM04vx8JUKD4EbaCUz1JoKzfYsfK9Tb5IXdYvyC/nP0gVruID8tiW4fY3sHmWwL+FCixV410a2fF8wVdXzVy8RKwbZcNew7YERW9IAotGllQsRzfkaS8IRQoSaGn/WcpULRfQ08zoEDxlJw+nqNA0UcdfZ1FQARK98HT5c02rrR966YjdaoUrnRlHxLwOgEKFK8j1dSATxIoXT6KxN17QJe2VhQt7PqH3aQkv2uvHYu+sqFEURM6tuY2nqSwdOVZfwmU8xccGDEhCpGRQN03LKhVwzPxEXE/enuP1SJu6/FsDFe4GKUPBYpRKp1wnhQoxq0/BYpxay8yp0Axdv1dzT4gAkWcMfLXhcsuxdioXnV5sCwbCQSCAAVKIKirM2dCAuXoMQfEoa6ZMgIjB/jv9yYpbD6KhMUCTB4VJK+mZfMdAX8IlIgIYNCYSPx7HfIg4u7trbo/+d93FfPuyBQo3uWptdEoULRWMe/FS4HiPZZaHIkCRYtV83/MAREo/k+TM5KAZwQoUDzjppenEhIoi5bZsOt7O958zYx6b/r27JP4HMd9GoVjJxxo3dSCcqW5ysCX75mvBYrDIa4rjt6WJW7U+bhXEK+o9mVB3RybAsVNYDrrToGis4K6kQ4FihuwdNiVAkWHRfVBSsoIlDt3IxAhrhiI1zKkC4NJ75dx+6CwHNI7BChQvMNRq6PEFyjiQ684zFWsBvm4txXZn/XP9h0nP+f1tCWLmtCB23h8+lr5WqCs3WTH6o02iAWWA3sFIUtmn6bDwd0kQIHiJjCddadA0VlB3UiHAsUNWDrsSoGiw6L6IKWAC5RLV66j84Ap+PXYmQTT27t2WpzDZX3AgEOSwBMJUKAY++WIL1COn3Jg7JQopEsLjB3sv+07zirE3sYjbuPh7kbfvZ++FCjObWAi+vYfWFGquH9FnO+o6WdkChT91NKTTChQPKGmj2coUPRRR0+zoEDxlJyxngu4QBky4XN8+91PaNOkFsZM+xLD+7RC2rBQeX3wM5nSYdqobggSp+KxkUAACFCgBAC6QlPGFyhLvrZh+3d2vF7djPq1A/P70ripUTh20oEPm1vwIq+p9dnb4iuBcu06MHh0JMShr9VfNqPRO4F5j3wGTicDU6DopJAepkGB4iE4HTxGgaKDIiYhBQqUJMAz0KMBFyj1PhiAWq++hKbvvIqSr7XBms9HIk+OrNi17xDafzTRZ9cYG6jGTDUJBChQkgBPB4/GFyjdB0Ti1m2gfw8rcmUPzKqBHbvtWLzCJlctiNULbL4h4AuBIq4ZHvZJFP6+6EDuHCb07WqFmUfZ+KaASRyVAiWJADX+OAWKxguYhPApUJIATwePUqDooIh+SCHgAqVGo15o1fhNvPtWFZSpGY6xA9ui6kslcf7iFYivLZk+EMUL5/EDCk5BAo8ToEAx9lsRW6CcPuvAyIlRSB0KTBju/+07zkrcvAX0GBiJoKDo23h0uY2nc2dg6tRHL9/kyYD4NT82XwiU2QttOHDQjtBUwJC+QfJdYlOTAAWKmnXxV1QUKP4ird48FCjq1cSfEVGg+JO2ducKuEBp1H4YSj6fF707NEL3wdNw4+YdjB/cHmu37JVberYvn4jMGdNqlzAj1zQBChRNly/JwccWKMtW2bBlhx2vVjGjYb3AbrsQ57CI81jCW1hQuqQOlzDoUKCIm5vEDU7iTPSPulqRO2dgVjAl+ZvCIANQoBik0E9IkwLFuPWnQDFu7UXmFCjGrr+r2QdcoEyZ+zWOnfoL00Z2xaGjp9C4/bCY2GtUKYMJgzu4mgv7kYDXCVCgeB2ppgaMLVD6DI6EOL9CbLvImyuwH37FOSziPBYhT4RE0V3TmUA595cDIydEwWaHPPNEnH3CpjYBChS16+Pr6ChQfE1Y3fEpUNStjT8io0DxB2XtzxFwgRIf4Ykz57H/4FEUyJMdZUoU4BXG2n/HNJ0BBYqmy5fk4J0C5cJFkzy7Qmy5GD8sSK4iCGTT/TYeHQkUeeX1qEiImpUqZkL7Vjy3JpDfO67OTYHiKil99qNA0WddXcmKAsUVSvrtQ4Gi39p6MzOlBMrNW3dhd9jlLTxsJKACAQoUFaoQuBicAmXtJgc2bLWjWiUzGtdXY8XHmMlROHHaoc9rcHUiUBwOQNyaJLZbPZvFhP7drQgODtz7zJldJ0CB4jorPfakQNFjVV3LiQLFNU567UWBotfKejevgAsUm82OGQtXY8Gyzbgn7nUEkCIkOZrWfxWtG9dCipBk3s2Yo5GAGwQoUNyApcOuToEyYLhNbt/p1cmKAnkDvPzkP87bvrPjy69tKFPKjLbN1ZA6XnsFdCJQVqyxYdM2O0KSA4P7BiE9j/Py2ivi64EoUHxNWO3xKVDUro8vo6NA8SVd9cemQFG/RipEGHCB8uWqbRg+aREqlS2K0sULIllwEPb+9Bu+238IPANFhVfE2DFQoBi7/kKgXL9mxvDxdqRMAUwaGfjtO86KxN7GM3VMEKx6cig6ECiHf3NgyqwoWa7u7a0oXEAN8Wbs72jXs6dAcZ2VHntSoOixqq7lRIHiGie99qJA0WtlvZtXwAVKtQbdkC5NaiyfNTjOeSfzlm7A+BnLsPnLcciWJaN3s+ZoJOAiAQoUF0HptJsQKNt3mLB+qwOVXzKjaUO1LMXoSVE4ecaBDq2tKFlURx/QNS5QLl8FhoyJxIOHwFuvm1GnplrvjU6/Xb2aFgWKV3FqbjAKFM2VzGsBU6B4DaUmB6JA0WTZ/B50wAVKw7ZDUL708+japn6c5C9fvYGq9bti0dT+KFU0n9/BcEISEAQoUIz9HgiB8skUEy7+41ByFcG3u+xY+o0NZV8wo00zHX1I17BAefgQGDouEv9cBgrlN8n3JtCHDhv7u9iz7ClQPOOml6coUPRSSffzoEBxn5menqBA0VM1fZdLwAXKnCXr8c2G77Dm85GwWh59ADh55m/Uadkfu76ZjAzpwnxHgCOTwFMIUKAY+/U4eS4Koyc45PadiSOCYFbs9lnnNp5kyYDJo3S0jUfDAmX63Cj8fNiBdGmBIX2CEBJi7O8hrWZPgaLVynknbgoU73DU4igUKFqsmvdipkDxHks9jxQQgTJ78Toc+eO05PrwYSR2HziCUkXzI22aVDGs//r7Mo6fPo8fN87kQbJ6fgMVz40CRfEC+Ti8FesisWkrULGsGS0aq7nCY9SkKJw640CnNlYUL6KTbTwaFShbd9jx1SqbPI9mQE8rsmXVST18/H2m4vAUKCpWxX8xUaD4j7VqM1GgqFYR/8ZDgeJf3lqdLSAC5bOFq3H4aLRASayNH9RO3srDRgKBIECBEgjq6sz58ehIXLgIdGlrRdHCan4Y3rrTjq9W2lC+jBmt3ldT8rhdUQ0KlNNnHRAyS1xdLLZTiW1VbNolQIGi3dp5I3IKFG9Q1OYYFCjarJu3oqZA8RZJfY8TEIGib6TMTk8EKFD0VE33crn2L9BnSCRU3x6j22087pXL671tdgdu3Y1E2tDgRMe+dRsYNDoSt+8AVSuZ0aS+TkRWopnrtwMFin5r60pmFCiuUNJnHwoUfdbV1awoUFwlZex+ygiUc+cv4cSZ84iIeIBsWTOiaKHccc5EMXaZmH2gCFCgBIp84OfdtM2OFWtsKFvahDZNrYEP6CkRjJwQhdPnHEqvlFEaYALBuSpQ7HZA3IYk+OfOYULfrlblzsrRGnsV4qVAUaEKgYuBAiVw7AM9MwVKoCsQ2PkpUALLXyuzB1ygREZGYdAn87F68/dxmOXIlhmThnZC/tzZtMKSceqQAAWKDovqYkojxkfhzJ8OhLc0o3QJtVcUbNlhx7JVNlQoa0ZLRc9qcRG7Mt1cFShLvrZh+3d2hKYChvQNQupQZVJgIEkgQIGSBHg6eJQCRQdF9DAFChQPwenkMQoUnRTSx2kEXKBM/3w1ps1fiY4f1EO5UoURljoVfj58HPOWbpCpx7+dx8c8ODwJxCFAgWLMF8K5LcYaJG7fsSAkmdrnWcTexjN1tHq3BWnxLXJFoPx8yIHp86LkNcUfdbUid041z8nRIv9Ax0yBEugKBHZ+CpTA8g/k7BQogaQf+LkpUAJfAy1EEHCBUrt5PxTMmx1jB4bH4bX7wGGE95mANQtGIE/OZ7XAkjHqkAAFig6L6kJKzoNZSxQD2ja3IMiqtkARKY2YEIUz5xzoGm5FkUL8IO9CmZ/aJTGBcvESMGxcJB5GAg3rWfBqFfXfkaQyMdLzFChGqvbjuVKgGLf+FCjGrb3InALF2PV3NfuAC5QajXqh9msvoUPLenFiPnXuAoRcWTS1n7zimI0EAkGAAiUQ1AM/5+jJUTh52oHmjYFyL2hDoGzebsfy1TZULGdGi0ZqbzkKfIUTj+BpAuXBA2DwmEhcuQaUKmZC+1Zqn5GTeLbsEZ8ABYqx3wkKFOPWnwLFuLWnQDF27d3JPuACpe/IWdi2+2csnfExcmfPApPJhOs3b2PUlMVYv20/ftgwAylT8Bpjd4rKvt4jQIHiPZZaGSlm+44VGDEQSJ1KGwLl2nWgz+BIpAgBpowO0gpuZeN8mkCZOjsKh351IEtmYGDPIAQnflGPsnkysIQJUKAY+82gQDFu/SlQjFt7ChRj196d7AMuUC5euobaLfrjXsR9pEsTigzpwnD89HmZw8BuzfBenWru5MO+JOBVAhQoXsWpicF27LFj8XIbSpcwodG7DqRIpg2BIuA6t/GIa3TFdbpsnhOIL1DELTv7f7Rj/0923IsAkicDPu4dhEwZPJ+DT6pLgAJF3dr4IzIKFH9QVnMOChQ16+KvqLiFx1+ktT1PwAWKwHfz9l0sW7MDv5/4ExH3H0DcwPPWqy/h+QI5tU2X0WueAAWK5kvodgKffBqFP0445Nkn+QvYNCVQDhy0Y/ZCm8y5RjUzGtThVh63X4D/HhAC5fzFKPz6mwV79tvkdh1ny/GcCfVrW1AoP8+a8ZSv6s9RoKheId/GR4HiW74qj06BonJ1fB8bBYrvGethhoALlEUrtuDqvzfR7cMGeuDJHHRGgAJFZwVNJJ2794AuH0XCYgGmjglCxMNITQkUkd6h3xz4bF4UoqKAooVNaNfSyi0mbrzGDx4CP/1ix94fbDh28tGDadMA5cuYUeFFCzJncmNAdtUkAQoUTZbNa0FToHgNpeYGokDRXMm8GjAFildx6nawgAuU3sNm4MatO5g1rqduITMx7RKgQNFu7TyJ/Lu9diz8yobiRUzo1MaKm3e1J1BE3uf+cmDyzCjcug1kzWJC93ZWpAnzhIgxnnE4gKPHHNj7gx2/HLbLm3VEE2eblC5hxksvmlEgr0leV8xmDAIUKMao85OypEAxbv0pUIxbe5E5BYqx6+9q9gEXKEtXb8f4Gcuwb900WMWPfdlIQCECFCgKFcMPoUyaEYVff3eg1fsWudpAqwJFoLp+E5g8IwrnLziQKiXQrZ0VYusJW1wCazfbsW2XDXfuPvr15wua8OILZuTPG4WM6XhCrBHfGQoUI1b9Uc4UKMatPwWKcWtPgWLs2ruTfcAFiriu+L3woWj5Xk1UfanEY7Hnz/0cLBYehuhOUdnXewQoULzHUvWRIiKATn2jlx5MHR2EkBBoWqCIPMR1uzM/j8Lh3xwIDgJaN7PKa3eVb507A1OnPgpz8mRA/JqXmzgsWBwaLFr2Z00oW9qMcqXNCEsNPO0WHi+HweEUJECBomBR/BgSBYofYSs2FQWKYgXxczhcgeJn4BqdLuACpVP/ydj+/S9PxLd37TSEhabUKF6GrXUCFChar6Dr8YvtG/MW2+S5IV3aWuWDWl6BEjvzr1basHVntCio+4YFtWooLqX9IFCWfmPDt7vscptO13Ar8ueJK5YoUFz/3tFjTwoUPVbV9ZwoUFxnpbeeFCh6q6h7+VCguMfLqL0DLlDOnb+EW7djrZ2OV4lC+XNwa49R304F8qZAUaAIfgphyqzolRotGllQsVy0YNCLQBG5iPNdFi2zQZz3Ia5obtPcCmUX9/lYoMTIkyCgZycrcud4fFUOBYqfvvEUnYYCRdHC+CksChQ/gVZwGgoUBYvix5AoUPwIW8NTBVygiBt4xBadtGGhGsbI0PVKgAJFr5WNm9f9B9G379jtwKSRQUiZIvrrehIoIh9xPfPUWVEQN83kyWVC5w+tMbkqVWkfCpRVG2xYt9kOqxXo0cGKfLkT3tJEgaLUG+H3YChQ/I5cqQkpUJQqh1+DoUDxK27lJqNAUa4kSgYUMIHy59+XEN5nAsQKFNHKliyE0f3bIlOGNEqCYlDGJECBYoy6Hzhox+yFNhTKb5Ifqp1NbwJF5HXhogMTZ0Th+g0gfVqga7sgZMns/TrfvAXcvO3AzZvAzVsOeSNQ5kwmuVUmNFUi8/lIoGzYasc362xyclFnUe8nNQoU778TWhqRAkVL1fJ+rBQo3meqlREpULRSKd/ESYHiG656GzVgAqV+m0FSnrRrXhuRkTbMWbIepYsXwGeju+mNMfPRMAEKFA0Xz43Qp8+Lws+HHGj6rgWVKzw6H0SPAkVgETfOiGuOz5xzIFkyoFlDC9Kkdu9w2bv3osWI+OeGkCXyvx/9+2n4M6QH8uU2y1UweXOZkC1rvLl9IFC27rDjq1XR8kSceVKk0NPzpUBx4xtIh10pUHRYVDdSokBxA5bOulKg6KygbqZDgeImMIN2D4hAuXjpGl5p2AMzxnRHpbLFJPotu35Ct0GfYtc3k5EhXZhBy8G0VSNAgaJaRbwfz8OHQOePIhEVFb19R1z562x6FSjO/GZ9bsMPP0cfLuvtJrZBhYWZkOq/7VBifLsD+Ou8Q24hit2SJwPy5REyxYy8uU0oMKWLV2/hEYfFinNPRBMHBIuDghNrFCiJEdL31ylQ9F3fxLKjQEmMkH6/ToGi39q6khkFiiuU2CcgAuXI76fxXruhcWTJteu38HK9zlgyfSCKF87DypCAEgQoUJQog0+DECtPxAqUAnlN6NXp0fYdManeBYrIcfVGG46dcLjNOHlyICy1CWlSR4uSmP9ObUK6tE8f7uIl4PRZO8795cCpsw7579it0a5uqH5o2qNfSsI1xju/t+OLZdHypGNrK0oUTVyeiL4UKG6/Erp6gAJFV+V0OxkKFLeR6eYBChTdlNKjRChQPMJmuIcCIlB+PnICTTuNwIH1nyFVyhAJ/eHDSJR8rQ3mTuiNcqUKG64QTFhNAhQoatbFW1GJLSdDxkbK8zka17egWqW41/saQaB4i2VSxzlx2oFTZ4RQsaP4rK6o+MMjgbKp9kQk69UZ5V4wIyT6jwyX2p79diz4MlqetG9lRalirskTChSX8Oq6EwWKrsubaHIUKIki0m0HChTdltalxChQXMJk+E4BFSiZM8b9MeWlK9eRLk0ogoIe/RR49fwRCI29BtzwJSMAfxKgQPEnbf/PNXx8FM7+6ZBncPTrZkVwcNwYKFD8XxM5Y7wzUL58eQK2legov1S+jBkVy5pRIN/TZci+H+2Y+0W0PAlvaZVXN7vTuALFHVr660uBor+aupMRBYo7tPTVlwJFX/V0NxsKFHeJGbN/QASKuIFn/lebXCLeu30jhCSP96nGpSfZiQSSToACJekMVR1h3mIb9v5gl9f4DuodlOC2EwqUAFUvnkD5d/AkrCvYEeK2pAcPomPKlBGoVM6CCmXNSB0aN86f/ufAzAVR8hfbtnBfnojnKFACVHtFpqVAUaQQAQqDAiVA4BWYlgJFgSIEMAQKlADC19DUAREoGuLDUA1OgAJFny+A81BRkwno3dmKfLkTXp1AgRKg+j/hFh5x4K849Pa7fXacPvvo3BRxrkml8hYUf96E/x1xYNrcKDgcQOumFpQrHXdblqsZUaC4Skqf/ShQ9FlXV7OiQHGVlP76UaDor6buZESB4g4t4/alQDFu7Zm5CwQoUFyApLEuvx93YPy06NUJ4vrel1968gdsChR1i3vhHwd2fW+Xq4gi7kfHKc5HiYiI/u8WjSyoWM4zeSKep0BRt/b+iIwCxR+U1Z2DAkXd2vg6MgoUXxNWe3wKFLXro0p0FCiqVIJxKEmAAkXJsngc1NV/gaFjI3EvAqha0YwmDSxPHYsCxWPUfn1QrErZtdcec5tQ03ctqFzBc3lCgeLX8ik5GQWKkmXxW1AUKH5DrdxEFCjKlcSvAVGg+BW3ZiejQNFs6Ri4PwhQoPiDsn/meBgJjJwQhfMXHAleWZxQFBQo/qmNt2a5cg2yviVdvKr4afNyBYq3qqLNcShQtFk3b0VNgeItktobhwJFezXzZsQUKN6kqd+xKFD0W1tm5gUCFChegKjIENPmROGXIw6kTQNnUup1AAAgAElEQVQM7hMkD49NrFGgJEZIv1+nQNFvbV3JjALFFUr67UOBot/aJpYZBUpihPT9dQoUfdfXW9lRoHiLJMfRJQEKFH2Udd1mO1ZtsCEoCBjQw4pns7h2pS0Fij7q70kWFCieUNPPMxQo+qmlJ5lQoHhCTR/PUKDoo46eZkGB4ik5Yz1HgWKsejNbNwlQoLgJTMHuR446MHlm9KGxHVpZUbKYa/JE9KdAUbCgfgqJAsVPoBWdhgJF0cL4KSwKFD+BVnAaChQFi+LHkChQ/Ahbw1NRoGi4eAzd9wQoUHzP2Jcz/HMZGDYuEg8eAnVqWvDW6+4dLEqB4svqqD02BYra9fF1dBQovias9vgUKGrXx5fRUaD4kq76Y1OgqF8jFSKkQFGhCoxBWQIUKMqWJtHAxHW2Q8ZF4uo1yENFO7S2JvpM/A4UKG4j080DFCi6KaVHiVCgeIRNNw9RoOimlG4nQoHiNjJdPUCBoqty+iwZChSfoeXAeiBAgaLNKjocwITpUfj9uANZs5jkuSfBQe7nQoHiPjO9PEGBopdKepYHBYpn3PTyFAWKXirpfh4UKO4z09MTFCh6qqbvcqFAcZHt7Tv3EGWzIW1YqItPsJseCFCgaLOKy1fbsHm7Xd60M6h3ENKl9SwPChTPuOnhKQoUPVTR8xwoUDxnp4cnKVD0UEXPcqBA8YybXp6iQNFLJX2bBwVKInzvRdxHn+Ezsf37X2TPYoXzYOrwzsiQLsy3leHoShCgQFGiDG4F8ePPdsz83AaLGejZyYp8uV0/NDb+RBQobqHXVWcKFF2V0+1kKFDcRqarByhQdFVOt5KhQHELl+46U6DorqQ+SYgCJRGsc5asx/K1O7Foan+EJA9Gu74TkSt7Fgzr/YFPCsJB1SJAgaJWPRKK5s5d4PhJB06esePceQdOn3UgMhJo0ciCiuXcOzSWAkX9evsrQgoUf5FWcx4KFDXr4q+oKFD8RVq9eShQ1KuJPyOiQPEnbe3ORYGSSO3qtxmEGlXKoE2TWrLn5p0/oPvg6fh1x3yYTJ7/ZFu7r4yxIqdAUa/el64AJ07bcfKUQ/5b/H/8VrWiGU0aWJIcPFegJBmhZwN07gxMnfro2cmTAfFrfmwUKH6EreBUFCgKFsWPIVGg+BG2YlNRoChWED+HQ4HiZ+AanY4CJZHClakZjuF9WkmJItrR42fR4MPB2Lt2GsJCU2q07AzbVQIUKK6S8k0/ux3487wQJdGy5ORpB27dfnyuLJmBvLnNyJPLhLy5zHgmk3fioUDxDke3R6FAcRsZH/AuAQoU7/LU2mgUKFqrmPfipUDxHkstjkSBosWq+T9mCpSnMHc4HChStSWmj+qGyuWLy56nzv6N2i3649uvxiNL5vRo3SXS/1XjjCRgYAJBQcBz2RzI8ZwDOXOY5L+TJzcwEB2mnrJPd4TMnB6T2d3R4xER3kGHmTIlEiABEiABEiABEvAvgQxhyfw7oc5mo0BJpKBiBcqIvq3xWuXSsmf8FSgUKDr7jmA6yhFIE+ZA9uxAzuxAjueALM84YE7a0SbK5ciA4hKgQOEbQQIkQAIkQAIkQAK+IUCBkjSuFCiJ8BNnoLxe9UW0bvym7MkzUJL2wmntaW7h0VrFvBsvt/B4l6fLo3ELj8uo2NE3BLiFxzdctTIqt/BopVLej5NbeLzPVEsjcguPlqoVuFgpUBJhP3vxOqxYt0vewpMiJBnC+0zgLTyBe1/9PjMFit+RKzUhBUqAykGBEiDwnNZJgALF2O8CBYpx60+BYtzai8wpUIxdf1ezp0BJhNTde/fRc+hn+G7/IdmzSIFcmDqiCzJlSOMqY/bTMAEKFA0XzwuhU6B4AaInQ1CgeEKNz3iRAAWKF2FqcCgKFA0WzUshU6B4CaRGh6FA0Wjh/Bw2BYqLwG/evovIyChkSBfm4hPspgcCFCh6qKLnOVCgeM4uSU9SoCQJHx9OOgEKlKQz1PIIFCharl7SYqdASRo/rT9NgaL1CvonfgoU/3DmLBolQIGi0cJ5KWwKFC+BdHcYChR3ibG/lwlQoHgZqMaGo0DRWMG8GC4FihdhanAoChQNFi0AIVOgBAA6p9QOAQoU7dTKF5FSoPiCqgtjUqC4AIldfEmAAsWXdNUfmwJF/Rr5KkIKFF+R1ca4FCjaqFOgo6RACXQFOL/SBChQlC6Pz4OjQPE54oQnoEAJEHhO6yRAgWLsd4ECxbj1p0Axbu1F5hQoxq6/q9lToLhKiv0MSYACxZBlj0maAiVA9adACRB4TkuBwndAEKBAMe57QIFi3NpToBi79u5kT4HiDi32JQESIAESIAESIAESIAESIAESIAESMCQBChRDlp1JkwAJkAAJkAAJkAAJkAAJkAAJkAAJuEOAAsUdWuxLAiRAAiRAAiRAAiRAAiRAAiRAAiRgSAIUKIYsO5N2h0CUzQarxeLOI+yrAwIR9x/i+o1beCZTepjNJh1kxBRcJeBwOHD95h3cuRuBzBnTIllwkKuPsh8JkAAJkIDGCURGRuHytRvImC4Mwfz9X+PVZPgk4H0CFCjeZ8oRdUTgz78vo2aT3ti69BNkfSaDjjJjKk8j0Kn/ZGz//hfZJV2aUNR9vRJ6hL9LaAYgcPjoKXToNwn/3rgts00Rkhz9OjdBvZqVDJA9U3QSePgwEq16jEPE/QdYMXsIwRiEQO3m/XDq3IU42XZoURftW9Q1CAFjp3nmz4v4eNx8/HzkuAQxsFszvFenmrGhGCD7lRt3Y8CYuY9lWqPKi5gwuL0BCDBFdwlQoLhLjP0NQ6BR+2EQH6ZEo0AxTNllop/OW4nXqpRB9mczYf/Bo/ID9dLPPkbRQrmNBcKA2R46egonTp9HtYqlEJoqBWYsXI0ZC9fg5y2zuRLFIO+DWIEk/jK9atMeFMqXgwLFIHUXaQqB8uYr5fF61Rdjsg4LTYk0YakMRMGYqV66ch3VGnRDzWpl0bhedRTKlxP3HzxA2rBQYwIxUNZitem167fiZNx35CwUKZAT/bs0NRAJpuoqAQoUV0mxn+EIXL56A/9cvgYhUihQDFf+OAmLv1SJn0J9+P5bxgZhwOyXrd2JqXO/xvYVkxBk5VY+I7wCsxevw4Zt+1Hr1ZewcfsBChQjFP2/HIVAadHwdbz9xssGypqpCgJjp32JtVv3YsfXk7ht2+CvhPjhqfi7/8bFY+UP0thIID4BChS+EyTwFALOn0hQoBj3NTl3/hLeeL8Ppo/qhsrlixsXhMEyP3j4ONZs+R67DxxGj/CGeLN6OYMRMGa6W3b9hGETP8fy2UPw3b5DEAKNW3iM8y4IgZIyZQjy5MiKrJnTo9ar5ZH92czGAWDgTEXtQ5InQ5bM6XHx0jW5+iy8eW08kzGdgakYM/UWXUfL3wPEFi42EkiIAAUK3wsSoEDhO/AEAnfv3cf7HYcjVcoUWDCpLywWM1kZhMC6rfuwftt+/PrHaYQ3q40mb79qkMyNm+aRP87gg25jMG9iHxQtmAvL1uygQDHY6zBt/kqYLWY4HMD2PT9DCPSv5wyhRDHAe/B8lRYoW7KQPO8qONiK2YvX417EfayePwJBQVYDEGCKgsDuA0cQ3mc8ti+fKA+RZyMBChS+AyTgJgGuQHETmI66i1t4ugycgn8u/4uFU/pxD7yOautOKmIlSrPOI7FpyVg8l5VLed1hp7W+wyYuxL6Dv6FK+RIy9KMnzuG3Y2fRoFZltGteR56Jw2YcAuImlhqNe6HpO6+h5Xs1jZO4QTMVAmXKsM6oXqmUJCAOlK3V7CN8M3cYCuR5zqBUjJW2zWZH/TYfo1LZYujelhcHGKv67mXLFSju8WJvgxGgQDFYwf9L99ade+g8YAoiIh5g5tgelCfGfA1k1lf/vYnKb3fBF5/2R8ki+QxMQv+pi+1av584F5OoOFBY7IVvWv81vP/Oq/JGJjZjEWjYdggqv1QC7ZvXMVbiBsy2fptBcqumU5adOvs3arfoj6UzBskVaWz6JyBWnfYeNgN7Vk/l4cH6L3eSMqRASRI+PqxnApFRNnmI7OuNe2PDF2PkNcY8RFLPFY/O7V7EA7wXPgRRNhsmDumIVClD5K+bzWZkycS90Hp/A8R1huLWjReKF4DZZMLE2SuwdstebF8+gSsQ9F78ePlxC4+xCv7n35fk9fXiBp70acOweccP6DNiplyB+EKx/MaCYcBs5y3dgPlLN0phIv7cnzhzObbtOYgtS8cjJHmwAYkYK2Vxdf3rTXqjfq0qFKbGKr1H2VKgeISNDxmBQJma4XL/q7OlSxOK3aumGiF1Q+foXHUUHwLrb4zXQhwaOmT8gphkxR7okX3boNwLhY0BgFnGEKBAMdbLIASKODxS/BngbH06NEKzBjWMBcKg2YoP0P1Gz5E3b4kmfu+fNKQjihXOY1Aixkp76ertGD9jGX9YYqyye5wtBYrH6PggCZAACZCAHgmI1UfX/r0FBxzIlD4tzGaTHtNkTiRAAvEIOBwO/HvjtvzhibiNxWrh1eVGe0nEFt67dyPwTKZ0MJn4e7/R6s98ScAVAhQorlBiHxIgARIgARIgARIgARIgARIgARIgAUMToEAxdPmZPAmQAAmQAAmQAAmQAAmQAAmQAAmQgCsEKFBcocQ+JEACJEACJEACJEACJEACJEACJEAChiZAgWLo8jN5EiABEiABEiABEiABEiABEiABEiABVwhQoLhCiX1IgARIgARIgARIgARIgARIgARIgAQMTYACxdDlZ/IkQAIkQAIkQAIkQAIkQAIkQAIkQAKuEKBAcYUS+5AACZAACZAACZAACZAACZAACZAACRiaAAWKocvP5EmABEiABEiABEiABEiABEiABEiABFwhQIHiCiX2IQESIAESIAESIAESIAESIAESIAESMDQBChRDl5/JkwAJkAAJkAAJkAAJkAAJkAAJkAAJuEKAAsUVSuxDAiRAAiRAAiRAAiRAAiRAAiRAAiRgaAIUKIYuP5MnARIgARIgARIIBIFr128hfdrUgZiac5IACZAACZAACXhIgALFQ3B8jARIgARIgARIgATcJXD89HkM+mQ+Dh89hUL5cmBwzxYoUiCXu8OwPwmQAAmQAAmQQAAIUKAEADqnJAESIAESIAESMCaB7oOnITRVCvQIb4jPPl+Ns3/9g89GdzMmDGZNAiRAAiRAAhojQIGisYIxXBIgARIgARIgAe0SqNGoF8Kb1Ua9mpWwZddP6D96Dn7cOEO7CTFyEiABEiABEjAQAQoUAxWbqZIACZAACahN4Pade/jxf3/EBJksWTByZMuMbFkyJjnwGQvX4NLV6xjUvbkca/POH5E6VQqUL/28S2MvW7MDe348ginDOj+xv9iWcvXfm/LrQUFWpEoZgtw5siIsNGWcZ+5FPMDmnT+gSMFcyJcrm0vza63TkT/OYOSUL9C4bnW89dpLMeHP/XIDRC3qvl4Bm3b8gLffeBndPmwQ8/XZi9dh175D+GRQOzyTMZ3W0ma8JEACJEACJKBrAhQoui4vkyMBEiABEtASgd9PnEP9NoMeC7nWq+UxvE9rBFktHqcjVjqcO38JX3zaX45RrUE3eQbHtJFdXRpzytyvsWrTHmxfPvGJ/TsPnIJtu39+7OtCIAzo0lQKFdEuXrqGVxr2QO8OjdC8QY1E52/aaaQUScP7tEq0rwodomw2vBc+FFkypcOkoZ1gsZjjhNWo/TB5BooQY5uWjIXJZIr5upBLzTqPlF+bNLSjCukwBhIgARIgARIggf8IUKDwVSABEiABEiABRQg4BcqscT1RoUwR3LkbgYUrtmDa/JUY+VEb1KlRweNI4wuUW3fuwWI2I2WK5C6N6apAuXLtJr6cPhAPH0bi8rUb2LLrR4yfsQxlShTEjDHdkTxZMOx2B27dvouQkGRIFhyU6PzvdxwhBcqIvq0T7atCh8XfbMXIKYuxY8UkZMqQJk5I/964jUp1O8l8hNASAuW5rJni9Dl6/CwafDgY00d1Q+XyxVVIiTGQAAmQAAmQAAkAoEDha0ACJEACJEACihCIL1BEWJFRNpR4pRU+eO8N9Ah/V0a64KtNWLZ2B4SsEK3483nQ6YO3UbxwnphMvt19UIoXcetLnhxZ8eBhJDKmTxOzAmXIhM+RNXN6tGlSSz7TffB0/HbsDM5fvIJ0aUJR4cWi6NamATJnTCu/7q5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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# iterate through solvents\n", "for solvent in solute.solvents.keys():\n", " # plot the RDF!\n", " fig = solute.plot_solvation_radius('Li', solvent)\n", " fig.show()" ] }, { "cell_type": "markdown", "id": "89c15995-e399-4726-8446-34c81ef9cbbf", "metadata": {}, "source": [ "These look pretty good!\n", "\n", "However, one could argue that our solvation cutoff for PF6 actually misses the first cutoff. This shouldn't make a huge difference, but it's not too hard to change either, so let's fix it.\n", "\n", "The trough of the first peak looks to be about 2.6 A. We can simply use the radii keyword of `from_atoms` to specify the radii." ] }, { "cell_type": "code", "execution_count": 9, "id": "e7a6367c65eaded3", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# assign a new PF6 radius\n", "solute = Solute.from_atoms(\n", " li_atoms,\n", " {'PF6': PF6, 'BN': BN, 'FEC': FEC},\n", " solute_name=\"Li\",\n", " radii={\"PF6\": 2.6},\n", " kernel_kwargs={\"default\": 3.0}\n", ")\n", "\n", "solute.run()" ] }, { "cell_type": "code", "execution_count": 10, "id": "6172b9fc-8c94-4bfe-8b08-b534e30f5e31", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'PF6': 2.6, 'BN': 2.6500000000000004, 'FEC': 2.75}\n" ] } ], "source": [ "# inspect the radii\n", "print(solute.radii)\n", "\n", "# check that our new radius looks good\n", "solute.plot_solvation_radius('Li', 'PF6')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "d638417f-01be-4c54-a066-675568ff9143", "metadata": {}, "source": [ "There! Now we have solvation radii for all our species!\n", "\n", "Occasionally, Solute will fail to identify the first peak, in that case you can add a solvation cutoff as shown above." ] }, { "cell_type": "markdown", "id": "883d8a3a-afcc-4091-b68d-b855928ae1b4", "metadata": {}, "source": [ "## Basic Analysis with Coordination and Pairing\n", "\n", "Solute instantiates Coordination, Pairing, and Speciation objects as attributes so that we can easily access detailed analysis through the Solute class. As an example, lets get the coordination numbers of our solvents. Here, the coordination number can be interpreted as the mean number of solvent coordinated with each solute. So in the case below, there are on average 0.253 FEC coordinated with each Li ion." ] }, { "cell_type": "code", "execution_count": 11, "id": "f274646c-1d88-4bb5-85d2-c219e74cd5dd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'BN': 4.351020408163265,\n", " 'FEC': 0.3346938775510204,\n", " 'PF6': 0.12040816326530612}" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspect the coordination numbers\n", "solute.coordination.coordination_numbers" ] }, { "cell_type": "markdown", "id": "d7133a84-e3f9-4e38-b21a-9185df413825", "metadata": {}, "source": [ "We use the same interface to view the percentage of solutes paired with each solvent. The pairing is defined as the percentage of solutes that are coordinated with *ANY* solvent. So in the example below, 100% of Li ions are coordinated with BN and 21% of Li ions are coordinated with FEC." ] }, { "cell_type": "code", "execution_count": 12, "id": "2c8cfe82-a0e3-4f11-85c7-d4f4f0ad6b54", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'BN': 1.0, 'FEC': 0.2653061224489796, 'PF6': 0.12040816326530612}" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspect the pairing percentages\n", "solute.pairing.solvent_pairing" ] }, { "cell_type": "markdown", "id": "d50bca64-7240-4357-bf86-88f107e86c7f", "metadata": {}, "source": [ "If we want to view this information across timesteps, we can instead look at the by-frame data. This can show us the coordination numbers or pairing fraction at each frame instead of averaged over the whole trajectory." ] }, { "cell_type": "code", "execution_count": 13, "id": "ad3867bc-067f-4e33-b468-92a8ea93384f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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frame0123456789
solvent
BN0.4346940.4367350.4285710.4326530.4326530.4367350.4346940.4448980.4346940.434694
FEC0.0244900.0265310.0306120.0367350.0306120.0489800.0306120.0367350.0387760.030612
PF60.0163270.0122450.0142860.0122450.0122450.0061220.0102040.0142860.0122450.010204
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" ], "text/plain": [ "frame 0 1 2 3 4 5 6 \\\n", "solvent \n", "BN 0.434694 0.436735 0.428571 0.432653 0.432653 0.436735 0.434694 \n", "FEC 0.024490 0.026531 0.030612 0.036735 0.030612 0.048980 0.030612 \n", "PF6 0.016327 0.012245 0.014286 0.012245 0.012245 0.006122 0.010204 \n", "\n", "frame 7 8 9 \n", "solvent \n", "BN 0.444898 0.434694 0.434694 \n", "FEC 0.036735 0.038776 0.030612 \n", "PF6 0.014286 0.012245 0.010204 " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspect coordination numbers by frame\n", "solute.coordination.coordination_numbers_by_frame" ] }, { "cell_type": "markdown", "id": "4cd4ae64-2ca6-4a8d-81c4-702830aee5ba", "metadata": {}, "source": [ "This systems was already equilibrated, so unsurpringly, there isn't much change." ] }, { "cell_type": "markdown", "id": "e79ec4a7-4899-40aa-b873-2e4f4ab175a3", "metadata": {}, "source": [ "## Exploratory Analysis with Speciation" ] }, { "cell_type": "markdown", "id": "a9c56e02-b75b-4e2e-a2d2-756616c7709a", "metadata": {}, "source": [ "Speciation aims to enable a more interactive style of analysis. It helps identify the most common solvation shells, find specific examples of them, and select those examples for further analysis or visualization. It also collects summary statistics in the `speciation_fraction` attribute, which shows the fraction of solutes that are solvated by a shell with the given composition." ] }, { "cell_type": "code", "execution_count": 14, "id": "15fe843d-03df-4b59-ab20-1d81abf97875", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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BNFECPF6fraction
05000.359184
14000.257143
24100.138776
34010.085714
45100.048980
54200.030612
63200.024490
73010.022449
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" ], "text/plain": [ " BN FEC PF6 fraction\n", "0 5 0 0 0.359184\n", "1 4 0 0 0.257143\n", "2 4 1 0 0.138776\n", "3 4 0 1 0.085714\n", "4 5 1 0 0.048980\n", "5 4 2 0 0.030612\n", "6 3 2 0 0.024490\n", "7 3 0 1 0.022449" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "solute.speciation.speciation_fraction.head(8)" ] }, { "cell_type": "markdown", "id": "d453c6ec-6b2e-41c9-a4d8-06f485792412", "metadata": {}, "source": [ "We can also use Speciation to determine the fraction of shells with some composition, such as having 4 BN." ] }, { "cell_type": "code", "execution_count": 15, "id": "98db8743-b0b5-4f63-9d8e-bf74583b1b21", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.516326530612245" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# calculate # of shells with 4 BN and any number of FEC or PF6\n", "solute.speciation.calculate_shell_fraction({'BN': 4})" ] }, { "cell_type": "code", "execution_count": 16, "id": "06ccfc96-181f-4d50-bb44-c50bf6923fed", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.08979591836734693" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# make it more specific by specifying 1 PF6\n", "solute.speciation.calculate_shell_fraction({'BN': 4, 'PF6': 1})" ] }, { "cell_type": "markdown", "id": "7fd3f634-6b65-4981-99b3-35da775b9d20", "metadata": {}, "source": [ "Perhaps we are interested in shells with 4 BN, 0 FEC, and 1 PF6. We can find these with `speciation.find_shells`. This will find every solvation shell with that composition in every frame of the trajectory. Let's see it in action" ] }, { "cell_type": "code", "execution_count": 17, "id": "d943842a-b58d-4cbd-9649-1e60295cf2f9", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
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solventBNFECPF6
framesolute_ix
0655401
667401
670401
683401
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693401
1667401
668401
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" ], "text/plain": [ "solvent BN FEC PF6\n", "frame solute_ix \n", "0 655 4 0 1\n", " 667 4 0 1\n", " 670 4 0 1\n", " 683 4 0 1\n", " 690 4 0 1\n", " 693 4 0 1\n", "1 667 4 0 1\n", " 668 4 0 1\n", " 670 4 0 1\n", " 671 4 0 1\n", " 683 4 0 1\n", " 693 4 0 1" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# find all shells matching the given dictionary\n", "solute.speciation.get_shells({'BN': 4, 'FEC': 0, 'PF6': 1}).head(12)" ] }, { "cell_type": "markdown", "id": "70900475-f8de-4c70-8811-f58af9ecbbb4", "metadata": {}, "source": [ "Awesome! Let's see what we have here by inspecting the data associated with the cluster. I like prime numbers, so lets go with solute 683 in frame 7. To do this, we will use the `get_shell` method in the solution class. Setting `as_df=True` will make the function return a DataFrame instead of an AtomGroup." ] }, { "cell_type": "code", "execution_count": 18, "id": "554278b5-8664-41c1-8594-3702c600d48f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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distancesolutesolventsolvent_ix
solute_atom_ixsolvent_atom_ix
700537002.047750LiBN308
5682.129007LiBN47
4122.147081LiBN34
8922.294223LiBN74
67552.435834LiPF6603
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" ], "text/plain": [ " distance solute solvent solvent_ix\n", "solute_atom_ix solvent_atom_ix \n", "7005 3700 2.047750 Li BN 308\n", " 568 2.129007 Li BN 47\n", " 412 2.147081 Li BN 34\n", " 892 2.294223 Li BN 74\n", " 6755 2.435834 Li PF6 603" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# get the shell DataFrame\n", "solute.get_shell(683, 7, as_df=True)" ] }, { "cell_type": "markdown", "id": "40e03fdb-3e12-4c46-9c86-047aa180de33", "metadata": {}, "source": [ "We can see that this matches the desired shell composition and shows us the indexes of the involved Atoms and Residues. Additionally, it shows us the distane of the closest atom of each solvent. If we want to return the AtomGroup instead of the DataFrame that's easy as well." ] }, { "cell_type": "code", "execution_count": 19, "id": "31f2f907-dbdb-412e-922b-d4f1ea7912ac", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# get the shell AtomGroup\n", "solute.get_shell(683, 7)" ] }, { "cell_type": "markdown", "id": "4d61a55e-fe5f-4972-afd5-e0d63158bfef", "metadata": {}, "source": [ "## The Core Solvation Data Structure\n", "\n", "All of the analyses in `solvation_analysis` are built on top of the solvation data, which is collected in a pandas DataFrame so that it can be parsed with vectorized numpy and pandas operations. Unless you want to design your own analyses, you probably won't have a need to interact with this much, but it still might be useful to take a look at." ] }, { "cell_type": "code", "execution_count": 20, "id": "cf10b57b-079d-4068-a2a2-c1712423a905", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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distancesolutesolventsolvent_ix
framesolute_ixsolute_atom_ixsolvent_atom_ix
0649673341682.103129LiBN347
23082.127130LiBN192
61102.176079LiFEC538
13122.316887LiBN109
26082.376575LiBN217
........................
969771176522.018652LiBN54
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14682.148709LiBN122
33282.184715LiBN277
18042.371709LiBN150
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2355 rows × 4 columns

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" ], "text/plain": [ " distance solute solvent \\\n", "frame solute_ix solute_atom_ix solvent_atom_ix \n", "0 649 6733 4168 2.103129 Li BN \n", " 2308 2.127130 Li BN \n", " 6110 2.176079 Li FEC \n", " 1312 2.316887 Li BN \n", " 2608 2.376575 Li BN \n", "... ... ... ... \n", "9 697 7117 652 2.018652 Li BN \n", " 4000 2.092055 Li BN \n", " 1468 2.148709 Li BN \n", " 3328 2.184715 Li BN \n", " 1804 2.371709 Li BN \n", "\n", " solvent_ix \n", "frame solute_ix solute_atom_ix solvent_atom_ix \n", "0 649 6733 4168 347 \n", " 2308 192 \n", " 6110 538 \n", " 1312 109 \n", " 2608 217 \n", "... ... \n", "9 697 7117 652 54 \n", " 4000 333 \n", " 1468 122 \n", " 3328 277 \n", " 1804 150 \n", "\n", "[2355 rows x 4 columns]" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# the core data structure\n", "solute.solvation_data" ] }, { "cell_type": "markdown", "id": "a068ec81-e207-4f62-b003-4f7a68bb5239", "metadata": {}, "source": [ "As you can see, the solvation data is indexed by the frame, solute_ix, solute_atom_ix, and solvent_atom_ix, which provide a unique identifier for each atom involved in solvation. Critically, the solvation data only includes atoms within the first solvation radius. By looking at the res_id's we can determine the molecules involved in solvation. From only solvation_data, we can derive almost every interesting property of the solvation structure." ] } ], "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": "3.11.9" } }, "nbformat": 4, "nbformat_minor": 5 }