Aragon_Conviction_Voting/models/v3/Aragon_Conviction_Voting_Mo...

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"# Aragon Conviction Voting Model - Version 3\n",
"\n",
"New to this version 3 model are the following elements:\n",
"\n",
"* Adding the realism that not all participant tokens are being allocated to proposals at each timestep.\n",
"* Refactored parameters and system initialization to make more readable and consistent.\n",
"* Changed file structure and file names to align with emerging cadCAD standards.\n",
"* Making the distinction between effective and total supply.\n",
"* Refining alpha calculations to more accurately reflect the 1Hive implementation. Discussion of alpha and its relation to alpha in the contract and how it relates to the timescales\n",
"* Updated differential specification and write-up to respect new state variables\n",
"* Moved all unit denominations to Honey, the 1Hive governance token.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# An Introduction to Conviction Voting\n",
"\n",
"Conviction Voting is an approach to organizing a communities preferences into discrete decisions in the management of that communities resources. Strictly speaking conviction voting is less like voting and more like signal processing. Framing the approach and the initial algorithm design was done by Michael Zargham and published in a short research proposal [Social Sensor Fusion](https://github.com/BlockScience/conviction/blob/master/social-sensorfusion.pdf). This work is based on a dynamic resource allocation algorithm presented in Dr. Zargham's PhD Thesis.\n",
"\n",
"The work proceeded in collaboration with the Commons Stack, including expanding on the python implementation to makeup part of the Commons Simulator game. An implemention of Conviction Voting as a smart contract within the Aragon Framework was developed by 1Hive.org and is currently being used for community decision making for allocations of their community currency, Honey.\n",
"\n",
"\n",
"## The Word Problem\n",
"\n",
"Suppose a group of people want to coordinate to make a collective decision. Social dynamics such as discussions, signaling, and even changing ones mind based on feedback from others input play an important role in these processes. While the actual decision making process involves a lot of informal processes, in order to be fair the ultimate decision making process still requires a set of formal rules that the community collecively agrees to, which serves to functionally channel a plurality of preferences into a discrete outcomes. In our case we are interested in a procedure which supports asynchronous interactions, an provides visibility into likely outcomes prior to their resolution to serve as a driver of good faith, debate and healthy forms of coalition building. Furthermore, participations should be able to show support for multiple initiatives, and to vary the level of support shown. Participants have a quantity of signaling power which may be fixed or variable, homogenous or heterogenous. For the purpose of this document, we'll focus on the case where the discrete decisions to be made are decisions to allocate funds from a shared funding pool towards projects of interest to the community.\n",
"\n",
"## Converting to a Math Problem\n",
"\n",
"Let's start taking these words and constructing a mathematical representation that supports a design that meets the description above. To start we need to define participants.\n",
"\n",
"### Participants\n",
"Let $\\mathcal{A}$ be the set of participants. Consider a participant $a\\in \\mathcal{A}$. Any participant $a$ has some capacity to participate in the voting process through their token holdings $h[a]$. In a homogenous fixed token quantity system (like you might see in a democratic allocation of equal tokens per each participant), $h[a] = h$ for all $a\\in \\mathcal{A}$ where $h$ is a constant. The access control process managing how one becomes a participant determines the total supply of \"votes\" $S = \\sum_{a\\in \\mathcal{A}} = n\\cdot h$ where the number of participants is $n = |\\mathcal{A}|$. In a smart contract setting, the set $\\mathcal{A}$ is a set of addresses, and $h[a]$ is a quantity of tokens held by each address $a\\in \\mathcal{A}$. \n",
"\n",
"### Proposals & Shared Resources\n",
"Next, we introduce the idea of proposals. Consider a proposal $i\\in \\mathcal{C}$. Any proposal $i$ is associated with a request for resources $r[i]$. Those requested resources would be allocated from a constrained pool of communal resources currently totaling $R$. The pool of resources may become depleted because when a proposal $i$ passes the reserve is decremented by $R^+= R-r[i]$. Therefore it makes sense for us to consider what fraction of the shared resources are being request $\\mu_i = \\frac{r[i]}{R}$, which means that thre resource depletion from passing proposals can be bounded by requiring $\\mu_i < \\mu$ where $\\mu$ is a constant representing the maximum fraction of the shared resources which can be dispersed by any one proposal. In order for the system to be sustainable a source of new resources is required. In the case where $R$ is funding, new funding can come from revenues, donations, or in some DAO use cases minting tokens.\n",
"\n",
"### Participants Preferences for Proposals\n",
"\n",
"Most of the interesting information in this system is distributed amongst the participants and it manifests as preferences over the proposals. This can be visualized as a matrix $W\\in \\mathbb{R}^{n \\times m}$, with participants holding randomized affinities from -1 to +1 over all proposals.\n",
"![](https://i.imgur.com/Rk2BYKd.png)\n",
"\n",
"These private hidden signals drive discussions and voting actions. Each participant individually decides how to allocate their votes across the available proposals. Participant $a$ supports proposal $i$ by setting $x[a,i]>0$ but they are limited by their total token holdings $\\sum_{k\\in \\mathcal{C}} x[a,k] \\le h[a]$. Assuming each participant chooses a subset of the proposals to support, a support graph is formed.\n",
"![](https://i.imgur.com/KRh8tKn.png)\n",
"\n",
"## Aggregating Information\n",
"\n",
"In order to break out of the synchronous ad hoc voting model, a dynamical systems model of this system is introduced, which is explored further below.\n",
"\n",
"### Participants Allocate Voting Power\n",
"![](https://i.imgur.com/DZRDwk6.png)\n",
"\n",
"In the above diagram, we examine the participant view. Participant $a$ with holdings $h$ at time $t$ supports proposals $i$ and $j$ with $x$ conviction. The sum of all conviction asserted by participant $a$ is between 0 and the total holdings of participant $a$.\n",
"\n",
"### System Accounts Proposal Conviction\n",
"![](https://i.imgur.com/euAei5R.png)\n",
"\n",
"In the above diagram, we examine the proposal view. Proposal $j$ with total conviction $y$ at time $t$ is supported by participants $a$, $b$ and $c$ with $x$ conviction. The total conviction $y$ at time $t+1$ is equal to the total conviction at time $t$ decremented by an exponential decay $\\\\alpha$ plus the sum of all conviction from $k$ agents in time step $t$.\n",
"\n",
"### Understanding Alpha\n",
"Below are some graphs used to demonstrate, play with, and understand the shapes and choices for the $\\\\alpha$ parameter, which regulates the half life decay rate of the agent preference conviction growth and decay.\n",
"\n",
"* https://www.desmos.com/calculator/x9uc6w72lm\n",
"* https://www.desmos.com/calculator/0lmtia9jql\n",
"\n",
"\n",
"## Converting Signals to Discrete Decisions\n",
"\n",
"Conviction can be considered like a fluctuating kinetic energy, with the Trigger function acting as a required activation energy for proposals to pass. This is the mechanism by which a continuous community preference turns into a discrete action event: passing a proposal.\n",
"\n",
"### The Trigger Function\n",
"\n",
"https://www.desmos.com/calculator/yxklrjs5m3\n",
"\n",
"Below we show a sweep of the trigger function threshold, considering the share of funds requested (on the x-axis) with the alpha parameter and effective supply (y-axis):"
]
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"application/javascript": [
"IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
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"<IPython.core.display.Javascript object>"
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"source": [
"%%javascript\n",
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" return false;\n",
"}"
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{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import warnings\n",
"warnings.filterwarnings(\"ignore\")\n",
"\n",
"from cadCAD.configuration.utils import config_sim\n",
"from model.parts.utils import *\n",
"from model.parts.sys_params import * \n",
"\n",
"sim_config = config_sim({\n",
" 'N': 1,\n",
" 'T': range(100), #day \n",
" 'M': params,\n",
"})"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"for reference: max conviction = 5.25318713934522in log10 units\n"
]
}
],
"source": [
"supply = initial_values['supply']\n",
"alpha = sim_config[0]['M']['alpha']\n",
"\n",
"mcv = supply/(1-alpha)\n",
"print('for reference: max conviction = '+str(np.log10(mcv))+'in log10 units')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"supply_sweep = trigger_sweep('effective_supply',trigger_threshold, sim_config[0]['M'], supply)\n",
"alpha_sweep = trigger_sweep('alpha',trigger_threshold, sim_config[0]['M'], supply)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": false,
"tags": []
},
"outputs": [
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qqfxb6LYQERGljkEQIiK79kVW+2MZWXr6Hw+sKvEyAJ9CVjvkLAB/3nQDiWg8Efk2slovzx+sz0FERETN43QYIiIiIiIiIkoCC6MSERERERERURIYBCEiIiIiIiKiJLAmSE5kNwV+K3QzKrAhdANm4DEm56XN1rcLCd0A+6xsaiHbEeq1m959mtwdmnhvdb+fut5DXdtb1c9b1fNZep5ZP9NZtrlpX3ua993EY8rcv9R9i5W3kbnJ0+7nNkx+rjnMfh8Zc/scRrdz3POOuk1GPF+Z+w+7b5HrijxX/+Vxj++/bdT1O9+nl1+3/r6D/0pekmHurvyOPWD7w3p9//aGXL4rv2//7Xeu/1fvAjp3AdsAdJD9+wvgZlW9JyL1EBFdrfH5fwF8XVWPqPElGsEgyHa/hay+YAy2hG7ADDaHbsAUlkI3oCDrfbsxdAPWsxSbUQCbQjcCwELg1w+1GTfd9032cxN9umuNz71c43PX0TdV90WV73+xoueZtU2z9vssfTxt26dtc9m2lm1fmc90U/E6gXPLrUL3W1jsTrzP0qbJzzU/V+B5MP55FsfcvoDRzz/ucUtoj3i+TqnnGvb6w+477PUGX2ux0H12PPfgc8733bf/tv7nGPX4tcf2X7f2uczn73H75U5+39U8KLIKbH+JtbP4O/L/r13uAFjJL3fyf9fuc2v+7y07Lm+7BbjiNuBGAFcg+/fNwNWI2CrqrZL/ZmCPGp++MVbGFg1gwXYbbg/dgIixb0tj3ej1hh/XEYVT55AXhTHrz9UdlbSinKZ+Yuvc3lfCRP5bK5MHk7q9+QZaEod2ZdHMnXX6ovPtugYAQw+0UDIYBNnJ8GiuP1tDN2BG3k7Wi42G0CTbQjdgOEuBkJXQDTAg1NdD030fW7ApxElpFerY3qruCwaBqhVbf8ZyaFuzDkYHWaY54e84Optv1RA0qeM5iarEIMg6sfxaeA+EeOMlEGI9wGQ0EGKJhUBI6BN065uxNzH0Z2wnrqFUdQjEzyN6vdVigYFOmxkc/coEVGrLtiAi1gQZro3qJsaGtBV+64PcDvs1LAa14KM+iMe+DUxhqz6IBR2kl7a6gmZrg6TYx0RrUvmpugP11syhqLSwOLIOSQyvN5MFMACLLMMhhrPYujETZCQnO/xEnjNCYhiepPKYDTKRhWyQ0Pj1UK0m+pNTYnbglJj6xVwXhIZqBRiI4rQPIp8YBBmLgZDwvB1RcFpMNQwGQizVBrEi9LSYEFgbxC4GAqoRy6HPLKxvSxEWR22C5ekl42qSWMdAEHnEIMhEPBqgshgIiZalQAizQbgJV43ZIFQl64GElDg4lC2yQgwN56kI69TqXAqdksQgSCEOfj0mYjZIs7wEQiwzmA1ijYVASIqZCswGsauuE29OiQnD488/1YbL5BJRVVgYNSkslEqDrPfrNgAbQzdiZyySaov1TdibJvqThSDti6U+vJdtzUs7B/RWlzC3PHnQp9Oex8Jit4EWEdEG+D3baxIzQQqLIRsEYEZIk7xkg3jrVwM4LWZnKWYqMBskPR6yQazxnJ0ybdv5k+rWuLocluuJVK1b8/SaEAVsiQYxCFIKAyHheTu6YCBkdpwWQxNY3nypeZ5PvGeV8ntPDT9rIqKpMQhSGgMhVJaXQIhlBgMhzAbZWYqZCrFmg7BAKgF2DncY5KxGmc8z4hVimjSqYGlKWSXjdBdqyjhhEVUqgEGQqVg5MkgVj4jqwX6lGYUMhHDzpX4pF0ilnXnpXy/trFEVK8RwqsVwgwGZugIx46bSdB0vA0zxYWHUqcVQNYyFUpvTAlz8MFvuVxZJHWsFwKbQjUhQ0/3eARpZDZEFUv1aha2RUGvtKWPatlv+KU1cG0tYrDhDt4VFLHGAdGqt5TksrfZCNyMaG8CvnyKYCTKTGL7wPE+L8Tb0y2kxs+O0mLFSnxbj7SuByDorhznct83qrRYb4Om0q8kCSG2Z3GkzNtruB2qr43W4l+rFIAjBdyCEqsejTaJSLASf6uD9q4BTYih2LI6apBYDHEQzYxBkZlaGSWblNRDi7SjdSzaI5X5lNshYFk7ImQ1Sr5iK0PLkvx7WTo5Dt4fbWYbFUckLr1PoyA0GQSoRSyDEK29nPV4CIURUmIXgUx28fb0O8pQNQjZNuw1Ns40wWJO0TsDCoXVml7BYLVnEwqiVYaHUsLxVIfNQKNVyn7JI6lgWiqQ2VcBzGMubblVC9m/VWCA1Y7UfrBzepLBfU3AdzGMB3aG31VFUlWq0DOCW0I1o3hzsn2FYwEyQSsWQEeJ1WgzVw/JwJ6fFkDGxZoOQT6GnoFAyihZHLYLL5E5ncAlcIhqPQZDKMRASjuUT9mE4mkA1snBCztog9Wqqf733JafE2BA6KBPrVJPQ/erQtCuuTCO24ET/+2myH4mqxiBILRgICcfbUamHQIjlPmU2yFgWAiGpYZ9PJ9YT1LKs9kMMhzWzaDLQYHUbqACXyfWJq9FQjBgEoQhZPmn3ynKfGgyE0A7MBqkXs0FonNiyBLxthxbbyxVialE2UMAsihK4UgzVgIVRa2OlktgsWCi1GR6KpFIpLJKaNvb5dOosDLqKeg6kPf3UWFDX50BERACyDAf+LE3GTJBaxZA/6nVajDecFjMbg9kglqbFhMZskHqF7F+qntXpEDEc0ljtWyKCMkBKDWIQpHYxHDV4DYR4O/thIGQ2BgMhVrBOBVXB8u5fRGxTQ1IVaju0vP0YaFuVK8RQHFhLhCxjEKQRDISE4/2onVxjNsgOqWWDMPA0HY8j9dZ/ZgycICdtmu3D435QodDL5HZgq/BqVfVDyqxU0y25qg0DHuQNgyCNiSEQQvVjNshsmA0ykoWTck7bqA8LpMYl5pNgBmXCC1gctaoVYkKxUtCUQQei2bAwKpXgtVCqt8p1HgqleuvTgCwVSU1ZiE2WBVKn47FAaipiqPle5/ZFjen25jE/15368W0sYdHgwFMH81jA9O+rXxuLWBwT8bLaBzSbOfj/mm4CM0EaFUM2CKfFkHUGs0GsTIthNkjcmA0SjvU+iS37gnVBiIhoBgyCNI6BkHCsH6X28xCZt9yfBgMhVlgIhITC2iDkCafEUBnsU7PK1OIgomYwCBIEAyFUBAMhUbGSDWIBs0HqE0vf1hkA4MnibGI4hGlaIsVRuUIMEXnBIEgwPIoIgyft6WA2yEgpZycwG6Qa/Cpdz3qfMPizg8MAQ+WMH4ZWsUJM00IXK00q44S1nWhGLIwalPcKYyyUWj8WSY0Ki6Tu0AFSOl6jKbCAJftgHP70NGdFgE3VpTN22vNYWKym+KdnLEw6owUwuDvEBvg8O2saM0FoRl6nxVgfsuvn4QfSan8yG2SkGLMTioo9G4QFUifjgXN4Xj8Dr+1OUMv8IJItoTNZ6rCxL2OEMVPqxyBIcMbzEQvxGgihNBgLhLA2yA6x1K8gWmM9MFTVCXwMhy5Na2LbSCxA0+3N1/bcHdT33EQxE5F9ReSivr+tIvLqIfc7NL/9UhE5q+/6q0Tkkvy28+tqJ6fDmOB9WoxXnnJpOS0mKlamxawA2BS6EYGE2Fyb7O9YphvVOR1kFT7mlXNKTD089KuHNiaI01hqtgAOkjimqpcD2B8ARGQDgOsBnNJ/HxHZDcBHAByhqteIyJ4DT3OYqt5cZzuZCWKG92EVr9kg1oft+nn4wbXan8ayQWgHHuj4ZnWXD4l90hz2Nc2gbX5wyaduyAi8h8B2Wg4H8HNVvXrg+ucB+LKqXgMAqnpT0w1jJogp3jNCvBZK9cRDRohV2wBsDN2IHZgNEl7syUuxZIOQTVUcsnjJxhnktd2Dajjs7K0uYW7Zw6CNL8w+oaIaKIy6x8A0lRNU9YQR930OgM8Puf4hADaKyLeRHYl9UFU/k9+mAL4hIgrgo2OeeyYMglDFPAZCYj8Tahr7k0pK6WQ9xqBT3bs8p8RU2wde3jPZUvEKMUW0VpawtCm9E/8O5rGAOFfP6WIe85G+t4TcrKoHTrqTiMwDeDqAY4fcvAuAA5BliiwC+J6InKOqPwVwiKpen0+ROVNELlPVsytsPwBOhzHI+7QYrzzl1KZ3QFAdY9NirBRJ5UoxRNXiduXDHQ2/Houjbtdps/DorJpczaX/tToVjFoUXrlnUvCXAV3LngLgQlW9ccht1wH4uqqu5rU/zgawHwCo6vX5vzchqyVyUB2NYxDEJO+BENYHqZ/1QIinviQA4QMhKdUGiXG53Lo1fbJKzZn1pD32nxtu+66MCkxUETigXGzZlPF6LoZPhQGAUwEcIiK7iMgSgIMB/ERElkVkMwCIyDKAJwP4UR2NYxDELAZCyDurR6bMBqEBVjdVTzz3oZOR80pxqVyKxKRlcgtnHESqPRCUsRaM6S7Yag9VIw9gPAnAl/uuO1pEjgYAVf0JgDMAXAzg+wA+rqo/AnAvAP8uIj/Mrz9dVc+oo42sCWIaC6U2z1M9CxZJnR6LpA4Vul4Fa4PUI6V+taTqnxMul2pLLLVVvB9q1ijm2hxVYcFWewTAYp1n+HdOvouqrgK4x8B1xw9cfj+A9w9cdyXyaTF1YyYI0TqehjSt//B46ktKGjfV2dXdh5wWQHXgdlW53ioHaIriMr1EYTAIYp73XFNOiyGrZ5ecFjMUa4M0h7VB7OCUmOlVcZiSUl0Qz8VRVyykLFZr2iBELMGLce+jW2EKYePTkmLI0qJaMQjiAgMhzfN0RGU9G4SIKFFV/5QwayFNCX/urZU4gg1NsVbzg8gqBkHcYCCkeQyEVMdqXzIbZKhUs0GsbqaecEoMpSTFDKIKcZlcqgRrJdEUGARxxXsgxCOeFRFRjTglxg6e0KaLwTUioqRwdRhqkMfVYjyxvlqM1ZV3uFLMUKmuFGN1M/Wk7j70tkqK5VViqlrhpIoVRmZti6d911pbuUIMVaCFRSxNOWDbWp7D0mpv8h0XwID+BBs2AJvrrIlyW43P3SBmgrjjPRuE02LqxWkx0zE2LYbSwmwQO5gNQlSJJleI6fbGT6tpvChnTWIpxkpkAYMgLjEQ0jyrJ+8UJdYGybA2CBFRpuyUHa4QE0yrgrSaDuKol1JFXxDVgUEQt7wHQqg+zAaZjrFsECuBEGpG6IBT1VggdWeWV4mxtFSuR8weilqVwQgPK7cwaEGpYBCEAmE2SNrYl26EPjlnNkj1OCVmPJ7UhjNr38+y33oLrEWCK8QQUQgsjOqa90pWHgulWqtmNor1IqlWsUgqBRS6GG3VvHxdEoXA/aOw1soSljbVl+XaxhIWzWfRDjdLMdKoLIMB7JzMARtZGHUiZoK45/2Lz2NGiBfWf9CtDrUbmxZjAbNB4hNDNkjqI/epv3+qlvfDyQCqKlTKgqf1Wxz4l4hBkCjwl6tZMZ8ZkTmsDULUvDpGFC3/dLAuyGyaGoG2UhyViMg5BkHIAI/ZIJaPZvsxG2Q6zAZZh9kgzYhtuVyruzjZxbog9hVcIabJZXKpOA8FWonqxiBINLwPv3gMhHjBQIh7zAYhGo4nrUQEoNsbX2C1lfCUk3Ysk0DqrHNByWFh1Kh4L5TqDauaxc1YkVQLQhfu7ABJDGCF7mfKrKL6g+6qfzbuALBrRc9Vx/ul8XgYQTQai51OR1Dd70LEmAmyXS90AyriOSPEYzaIlywGZoO4x2yQcGLePGOYEsNsEFs8H4ZQEFwml4iaxiBIlDwfgXgMhHhhPRBiEWuDrJNqbZCmhe5nopA81gWxWhy1DMOHj62VdKezlFVXzY9WX7Z5Xa+hzEajhjAIspOYh/s88RYI4XZTDav9aCgQwmyQcKxunlWIIRukLh5WiWEmDI3D6QSFjFumtoPymSotR9PT61iit5vE3FXyjEGQdbweqQ0yHM6Pkpftxno2iJd+TByzFMgaBgKqwRNmKoorxEyFK7MQ2cDCqEPFUqnKc6HUrQC2hG5EpFpAwlXSp2OoSKoiK3qVslAFUpv+aWCBVPLK8+FH02I55KTKdTCPBXR3uq6NJSw2OKDVxQLmvcxDXUY6U2bH2QAWuS6AmSAjxTIi7TkjhNNi0sR+nMjCtBhmg8SFU2JG45SYMELWBSEqqI6pJERUPwZBiCrl5ajL+rQYiwzVBqFwoz1N7+IMNqbROAQAACAASURBVBUXYyAgBE6JsV8clYbq9rjKTAgMBJFHDIKM5eWEdhJmg5A3sex7NWI2CFWNacRUJc+HHtZFuEJME8vktgyfrDOQMAGnd1DFGASZKJaTMc9HI94CIV62GevZIBb7kdkgpvCk3R+Lu3URHqbEEI3CDJWoeVqJhsgKBkEKieVIxXMgxBsv24z1QAiNxWyQMDglxq6Up8TE+N5TOXn3csgQWGuF2RJEEwmy4vF1/UWCQZDC+AsVlrdsEKqGxf2O2SCmMBukWiyQSkA8wYdZtjXWBZmMy+RGiZkllAIGQZLjORvEWyDEy5E+s0HKMxQIYTZIGMwGSQ+nxJTn+ZCDkjOuLkcHLLpalS77kgxgEKSUWI5WPB+VMBBSD8uBEC99SMEwG4T6xTgtpKiU33tq+FkTEU2NQZDSeEJGRACzQQakmKkQazYIp8QQYGdah5V2eFemHz2PlRnCaSXj1bZaz671PC3FZZfQDfDpdgCbQzdiRm3A7ZfzVgBbQjeiBC/bSwswu0Sblz6kYDqIqmAXGbUKLtXojZefDy/tNK7bm8f8XDd0M8bqYAELDacwtrGIxcDRrRaWsGQ68zgSc+DvVAHMBEma51A/p8Wkx2IfMhtkJ8wGiYf3KUaepgrEug2t8XyoweKojeq0668VUUf2wbhaIlZ1aho1YPYLecEgyNRiOWrxfHRC1WOEnhzzfuJeREyBplh+Rq3xFAAi/wquEFOV1JbJnbYga11Bjjp0F+pt6yLnPdAQDILMhEdwYTEbpB6WAyEW+5DZIDuJ6SSdfKsrGJDSKL+V92qlHdY4CnhxmdzqeMw8IbKGQZCZWTwpK8tzNggDIUQUGAukTo9fiRn2Q73Yv0S++ElkIaeYIEQ5z4VSqXosklrONgAbQzciowCazU5ebwXApkCvzQKpRFmGgKUVEniIUUzdP29lCvvyM2tcG0tYNJ2NSy6wMGohzASpRCxDDF4zQpgNkh72IRkT6ybpvc4Kp8TQrFgclRJQ5xQbFkslixgEqUysR8BeMBBSPY5GlMPaIDsJWRvE+4l7ETHVXvHwddgEq/1g5WTeSjsoauOCAdMWKaVAmBVKYzAIUimrRzBleM0GoXpYDoRY3N8MBUKoeRY3SSIiR6pYJrfbSy9YwWwLonIYBKlcDEfBXgMhzAYh2o7ZIPGLqUBqnRytoFEpa+879KFFrD+5Fj7nhpfJpXAYbKFYMAhCkfEWCPGA2SDlMBuEqDSLu/IkdUzPsNoPqU9FsRBoiEBVy+S2VmZ7nlaDhd9jDhp0ON/EpjlkhbHr+osEgyC1sHoUU0boIZtUxLCtkFnMBmked2mi+ngLxkzT3rq/Q8q0iYeCtfEUQOiGbmtEJ94pEJF9ReSivr+tIvLqgfv8FxH5noh0ROQvBm67SkQuyR97fl3t5BK5tbG4jGdZXtdH2wpgS+hGlOBhW+GSueUYWjKX4tbUcsTelx62tmRsU1J930QN4/K2RBlVvRzA/gAgIhsAXA/glIG73QrglQD+cMTTHKaqN9fWSDATpGYxDAl6HQbgtJjq8cfdpdSzQUKI4as/BI/95i0zIbTQhxQetzEiIr8OB/BzVb26/0pVvUlVz0PAOeQMghCZwCOz2VjsP9YGMcF7Uc8iWCA1Lha/zgAGfCxjzRKKQGuZp6VO7CEi5/f9vXTMfZ8D4PMln18BfENELpjw3DPhdJjaWUzVL4vTYprhYVvhtBiXFEDo4v1NTdsgGoVTQ+KwCmA5wOty+xlvRYBNFlIPyYouFjDP6Hnz5lD3d+TNqnrgpDuJyDyApwM4tuTzH6Kq14vIngDOFJHLVPXsaRo6DkNujbA6rFNG6BzWaXFaDIXEbBATWCDVD4/9Zj1DglkCYVksjmpcpz0/83N0e9M/R9vYYE8Hs/cHALRLDGiWXdXGWp+RCU8BcKGq3ljmQap6ff7vTchqiRxUQ9sYBGlO4r9oVJCH7cRybRAP/RcIB+jixikxcYn5q8zrmEpMAq4QU9UyuaFUFZCYFYMO5MBzUXIqjIgsi8jmtf8DeDKAH9XQNp9BEBE5QkQuF5ErROQNY+73RyKiIjIxZYeK8Hrk4i0bxMPRr+VAiDXMBtmOy+VSaMyKmI31rJciuF9GobUSZxCgyuCGp2V4KS55AONJAL7cd93RInJ0/v97i8h1AF4D4M0icp2IbAFwLwD/LiI/BPB9AKer6hl1tNFdTZB8qZ0PI+vY6wCcJyKnqeqPB+63GcCrAJzbfCtHiaFmAeuDkHUx7Gc1sVAbhOoTS90Vj7twqDoVRcVWz8J6f5N5LSxhKfEBnQ4WsMD0PqqBqq4CuMfAdcf3/f8GAHsNeehWAPvV27qMx0yQgwBcoapXqmoXwBcAPGPI/d4F4K9hbtyHQxBUhIftJO2Dh3KYDbIds0H84zEzpcrYEeVOLLeNiJozB2Chxr9IeAyC3BfAtX2Xr8uv205EHgXgfqp6epMNSwenxZB1MZ55VoS1QciDOndhLyeLMX+NeT2MmBaLoyatbJFRIqqfxyDIWCIyB+A4AK8tcN+Xrq1xDNxWf+O2i+GXzesRjKdAiIfthNkgxTEbZLuQ2SCxY4HUcGKol1FEDO/Tw8+rRytpz7dksVIiPzwGQa4HcL++y3vl163ZDOB3AHxbRK4C8BgApw0rjqqqJ6jqgdlax3erscnD8BeYiuB2Mj323UgpZ4NwSgylyksGDDXDeDCrimVyU5NUxkkM9a8oKI9BkPMAPFhE9haReQDPAXDa2o2qepuq7qGqD1TVBwI4B8DTVfX8MM0dx/uRMbNBCLCdDWJtH2M2yHbMBqFJOCXG3leYJcZP4qPCZXJrwdVbZsTiyDQDd6vDqOqdInIMgK8D2ADgE6p6qYi8E8D5qnra+GeganG1mPp5WCqhBTAN1JeUV4rpoPniXk3uxk2tEhOiHykeXg8fYltpJ2Ld3jzm57qhm+FGG0tYND2wNYW+fTWZo9Q5MEBUgLsgCACo6tcAfG3gureOuO+hTbRpeh5OcCfxeiRDabC2j20DsDF0I2yIZUlXojXWl26t6gTe+vu0qIk+SyxA01pZwtKmek7aowwIENF2HqfDRIj5rmF4mhbjYRvhwYI7rA0Sr1imG3n46qsb+6AeHvrVQxsT1AHrldRJGWClBjAIYob3XzrWB6mf920kJGt9x9og28Vysl6Etc2wCp6DSV7qgtBorAtCM2ilM0GiUUELtHKKJhXEIAhVyGsghKrDbBB3Us4GIaoDT8yL83rYEEsArY5tNfFlcuvC7BOiarmsCRIva7ULUsEiqWmw1nesDRIcC6T6YG3X9Y51QWgaLP9G5AMLoxbCTBBzvOdLex3WoeowG6Q4I9NiQmeDpDQlJkacElM/74cGVrFfTeu008x+aEc8TYdTkMgKBkGoBh4DIawNUi2rgRAPfUeN8nwCXwQDTGFwSgwNM812UfZny0lgr7fKk+FZNRks6falTVZR86NbdHrPsIyGhRH/JyqBQRCTeKIWBgMhFAKzQQCkdbLO3bc89lm8Zh03YcCJDBkVmAhaLLRP20g7iEJjEMQs70d8HrNBqFrMBiEnYs8GaYLnPnQycl7pV1dV75kBCAqstTI+G6LbS3NKzZqO8VQJTo+hUFgY1TTv1eA8VtFikVQKwUiRVAUQsrB/LIU8i2CB1PixcGjcqiowGxq305HaWMKi2QEdGzpYwILrKHiE5hDHd1PNmAlCtI6naTHWWT14YDYIUeXqPg7mbkt14HZVPS6TW5j1TA2iWDEIYp73X2dOi6mX9+0jJGt9Z6Q2SGihaoNwICttXqbExCqluiCe2joowkO61KdjjAvCVFnHpPGaKMxuogkYBHHB2slaWR5/NT1lg1jfPqxmg9BQoQukpqTJXTelwrMxY12QNEW6QoxnnaKrmxCRSQyCEI3kKRBindVAiLUAErNBgmI2yOw4JWZnDBAQjVRkmdxOm8GGMqysQtMoZn3QFFgY1Q3vRTA9Fkn1xPv2QaawQGpzWCDVjlgKXVJzuM0QkTVzYGCoAGaCuOJtCGwQp8WkjdkgxTAbJChmg1BKOG0iY+1ngIiIasUgCFE0eBRHFQpdG4Q1LPzilJidVT0lxuL7r+I9sjhqONbaQy61Zygy210ouEoOMxyoIgyCuGPx6KcMZoPUy/r2wWwQonVYINUOZkYQVaPBZXJbK+NPvru9OOqKsBgrUXUYBHHJ+wkbAyFE4xmZEpNqNginxBCRNVZWiPF4COfQLFkVlnTHLMFLFBKDIG55D4RQfaxvG8wGIVonts2PU2LqZXGp3FSx/2jAqACGh5VbYgm+JE0ALNT4FwkGQSgQj0MJzAahJjEbBACzQerAKTHNS6Hmgve6IKkH1mgoBgWI4sQgiGvef7E9BkK8sL5tMBuEiIziyD5RY3qrk4MMnXa9tTBajgMdDNLkuFQ1lcQgiHs8aWsWs0GoScwGSUpsX+ecEkM0mrXsIGvtIarQltANIHMYBKHAPGaDeAmEWD9DYDYIFcQpMdXjlJjmWV4ql9kvRKVVtVpLJ6ZCC8YxGEJrdgndAKrC7QA2h24EmWR922gBTOWcYBuAjaEbkWWDNLfiYbqs77KpuANMr57GKoDlGZ+jDTioH7mzpraXst8PobfjFQE2MZWQqFEbMPv3cAKYCRINz6PXzAYhazzvT5FiNkj1muhTTomhprE4av08HrYlbDDTpO0uykhUPQZByAj+otbH+lGd1WkxlhipDUJERGRQa2V8Vmm3V29xVWoAsxuoQgyCRMX6yW5smA0SN+5P64TOak6ljgU3PRvqqJPBuiDUj8VIiUZjqRSqEYMg2/VCN6Aino+ePWaDeAmEWN8umA0yGbNBguGUmNlwSkxaeGJPRETGsTAqGeOxIhrFi1Uq12GBVCKq26yHAlUUaC3LanHUMkL0G4De6hLmlscPhnTa81hY7DbUIt9aWMRSDQOLXSxgPo9q1/UareU5LK3GMjAdyByATaEbYR8zQXYSy2g0h8WaxWyQasSy/9WJ2SDJFEi1vrumIrUpMRRff3Ka08zaU6xiN81jQuESvZQiBkHWieVEzPOvuMdpMV543i5CYZ+tE7o2CFUrhikxVA2eMFOiWg0FLVqJZDun8j7JLwZByChvgRAv2SDWxRKErBOzQVggldZhX9nCuiDxK3qYtsL5k9Malk3SAVe5IaoCgyBDxXIixqPCZnkJhHC7KI99tk6K2SDMZiBqjrexkGkxYESGucro4BK6VAILo47UAhzN5xvNc2FHFklNUyz7Xp22AdgYuhFhrYCFv6rURH924HPJwzoKXlZdgNLzT31dYi6OSmZ0MI8FsGArGTIHn7+1DWMmCFGlmA0SL/YZgQVSLWNfVYN1QexvS9bbF0hrZfwASrfHqSR1YGFVGiQiu4nIySJymYj8RER+d8h9DhWRi0TkUhE5q+/6q0Tkkvy28+tqIzNBxoplRNrzEBGzQdIUy75XJwPZIFwul4hGCbTcKs3I8DK5MetgAQuccznarmCA1pcPAjhDVf9YROYxcFAvIrsB+AiAI1T1GhHZc+Dxh6nqzXU2kJkgE8Xyhex52MDbxGBmg8SLfWZKKgVSm8JVYkbzsFQu0Sg8eYyap+V4KX4icjcAjwPwjwCgql1V/c3A3Z4H4Muqek1+n5uabSWDIAXFEgih5ngJhFjG/W4yAyvFsEBq/Rh7Ky7lvorxvXsbA5kWA2KFdNqczkLkwN4AfgXgkyLyAxH5uIgM5pc9BMDuIvJtEblARF7Qd5sC+EZ+/UvraiSnwySF02JokPVtwuK0GOt9lhgWSK0W+5OAeAp8ckpOvYoemq0IsCnFiDlRAHOo+3tvj4FaHSeo6gl9l3cB8CgAr1DVc0XkgwDeAOAtA/c5AMDhyL5Fvici56jqTwEcoqrX51NkzhSRy1T17KrfBDNBCotlVNrzUJG3ISEv2SCetwkyIcVjW2aDTM/rlBhKy7T7HKeekHN1T69pmRvcopJuVtUD+/5OGLj9OgDXqeq5+eWTkQVFBu/zdVVdzWt/nA1gPwBQ1evzf28CcAqAg+p4EwyClBJLIITIE4v7naUzUgNTYogsqWv3ZF2Q8mJ/fyFZ+hmKxLiTc9bdICpGVW8AcK2I7JtfdTiAHw/c7VQAh4jILiKyBOBgAD8RkWUR2QwA+RSaJwP4UR3t5HSYJHlO5/c2LWYrgC2hG1GA522CTAi5UgyncFSL/elXjF/l3n72Y8BpRJVoYwmLJgdybOhiHvPoVv/Ey2BGVnivAHBSvjLMlQBeJCJHA4CqHq+qPxGRMwBcDKAH4OOq+iMR2QfAKSICZHGKz6nqGXU0kEGQ0izWKJhGjEdKVnkJhFhmcb+ztA8ZWC43RR0ACw2+nqVNblZN9x2VF0tdEMok8nm2VpawtMl24KGFRSw1PMWbS/BSk1T1IgAHDlx9/MB93g/g/QPXXYl8WkzdGASZisUTspRwWKgeMZ1hUXKYvUD96vo6q+NEkqPu9fLSv17aSTTGuOyXEMGfJNVfGDUKrAmSNM8TSr19iXopkmqZxZEdS/uQgdogLJAaj5XQDaBoeK4LwuKojeqt1j/A2O1Vv8xuB/6W7m0bGkxkoVQKgUGQqVk8IZuGpZM4Co/bA5FpMe2isQaQQotpGyH7Gh6T6rT9BRxCaBkKchBZxCDITGIJhHjFbJD0WNznLJ1xJJ4NwuwFakJKo/xW3qu3n3tabyVU5Wzfhq1K4zHzJKTNnBpCQzAIQrB1EkfhcXsgKiXWjAbvQSVPX2Wep4xQOJ62cSIiQxgEmZnFkelpeP0l9TY85CUbxPL2YHGfs9RfzAaJnqXNbVaxBpBCs7aNhA7yhH59K8pk9rDPKCBl9sb05pAV8K7rLxIMglTC4klZShgIISIioho0GVBi4CFpnYDrhod8baIQGASpTAyBEGtDRxSW5e3B4v5mqb8MZIOEFCIbpOmMhqY2N++ZNXX1k5VaGU2w8l69jXdY6TcqZdxKJcPqc9BkXQZYyCAGQSgS3o6OmA1CkUtxuVyaDqfEZJgFQERUHU6poTEYBKmUxdHpsiyNZlN4lrcHi/ub5f6i2vFknizh1xE1pcJxqN7q7NkWrZX0MjaYpUJUzi6hGxCfFuD+i+h2AJtDN2IKbcDVuuhbAWwJ3QiK1jYAG8M2QQGEWhVxBcCmQK/dlKa+qr33ZV39dAeiKhJXu1WEHZkN/fp18XrIRi51sYB5Rvxtm0Oc33UVYyYIRcbbtBgPLA8nMhuEKAo8pibL+LVejZVqouKd9vxMj+/2Znt8GTFnaLRcDTwS7YxBkFpYPDEri7/4zWBtEKqTgQKpqS2Xy5N5moXVuiBWinx6G+eYpt/q3ga4TC6VxGAHxYhBkNowEBKOt6MkD4EQy9uCxX3Ncn9RVLhKDI3DryKiRnRQLruEgYUSOLWDasAgCBFR1AxkgxAVUWcWDZfKtYGZBUREZAALo9aKRVLDYZHU6lneFmLY1yKWWoHUDoCFhl+T4hFrAU8L2LdEFDsBj0EKYCZI7Sym6qfC27QYioulPHRmg0SNU2KoCcx6scvSzw3RlLoLPHOn5jAIQgXw17UZrA0yGwYcTQtZIDUEFkidjscpMdbF9r5DjW/E1o9Vq/Bz6a0ys7Of1xVmWPeELGMQpBExnJx5/fVnNgiF5HW/iQwzGKhOzJCgcSyuEJOA1sr0gYOW06DDJJ0ScyTKBl7KPDeRBQyCNCaGQAjVj9kgs+F+NhqnxESNU2LiEvNJcMzvzYuQy+SuhCoQVQ0rWRllV6Mhop0xCEIlWD75HYfZIBSS1/2mBiGnxIQ4eeeUGHu4O84mhqwXBmGi0GnHGQSoMqOC01GIRuPqMI2KYQULyyuEjONptRiuFDObGPazumwDsDF0I4jG87i6zh0Adg3diDEsf2UTBdDtzWN+rhu6GUG1sYhFDhTGZw5QroI1ETNBGsd0fSqC02Liwr7aLrUCqU3ilBhKBYujEhHRDBgEoSl4PQpgtDsdDDaOlnBtEE6JIU9inrYR83sLxeuhWQKs1BEhoh0YBAmCJ2hUBLNB4sK+2o7ZIPWJZTPjUrl2xVAXpGlcIYaIyBQGQWhKXo8imQ2SDgYbR2M2SKNizAbhlJj1rAcHvP5s14EBhnokfojFFVsa5K1uFJnDwqjBxFC80WulNRZJrZbX7SAE9hURERlgvJhvb3UJc8txD2a0sIilCiNHbSxhkQNAyettAFrLdeY59Gp87uYwEyQoflER1Yv7mFmcElOfWEb8OSWGGQvjsDhqc6reDlek4iekJG0qcB+ukkIjMAhCM/J6NOApZ5O1QagOnBLTKE6JSYP1KTGWMMBDNWuteM+4blYn8jkmzMOlfgyCBBfDSDVPgMkya/sY95ftmA1C5BODPeU10WeJ/bx02vXV4Gi5n7JOROMwCGKCtZO0VDAbpFqJHX1Fgdkg0Ypld4wxgyakWLaLKnjIRPHQxgRxydt61VvPgmIhIhtE5LJpH8/CqFQRFnwky6wVIub+kqQO4qtov4Ji87It8rIbroLz2kfxVOeczOn25jE/1w3djOgELdC6jOSD5yqC7kKdBxs2BpFV9S4RuVxE7q+q15R9PIMgZlg7SUuFpyMorhRDddgGYGO4l1cArJFHMTG+6oYpDPDEx9NhFRF5tzuAS0Xk++jLnVPVp096IIMgpngPhHg9Afb0i+0hEGKVtf3L6/4SEc9ZDEVwE6M6pRzsiWXfSvkzdIbL3xIN9ZZpH8hJV1QxTjgmbgNUUkoFUmNM0627vgqXyq1Wiu+ZZhegPklv1dLARXNiXqWl5WbQkTxQ1bMAXAVgY/7/8wBcWOSxDIKYwyhvGDbmtxXjoUiqVdb2LytnIwkXSCXygAUy69F0v3JVnR1WOA9yVh3UtzrOON0KgjSFV9+Z9FKcTpc0EXkJgJMBfDS/6r4AvlLksZwOY5K1tP2yYskTpelxGyAnQkyJabJAKnfFMDjNoDmeZrROo2zdFO7zJnmfztLCIpasDBgug4HhMXqYq3mJZyPbQeblAA4CcC4AqOrPRGTPIg9kJgjRdqZ26gmYDRIPZoMASGtKTIw8T4mh6VWR2cCTGYpIqOyMoqxNteka7y8yr6Oq25d4EpFdUPCIkkEQs/xGizNWTuwoHKvbgPd9iypX9wk82Wb1q6pOKb5nilKnPf4kurXiObN6dqzBQZE7S0TeCGBRRJ4E4EsAvlrkgQyCUI08HmUxG4QomJSyQZrMbPD4VUzrMWPCFu5XRAyyUGhvAPArAJcAeBmArwF4c5EHsiaIad5rgxBZnZxsbd+y0k/bAGwM3Qii4ZqspVIF1gXxoWzNjdjUsZ1GUqelhSUs1Zw9aqrWBpEzqtoD8LH8rxQGQcyzdrJWlpWTuzI8/XpvBbAldCOI/AtRIDU2nvvQ408V7eDpZ9tzcCz1gFGE2ljE4oggjOtirrsi2ey5HuaSqbUiIpdgfR7xbQDOB/BuVb1l1GM5HYZoKEblq2M1Z9jaD7uVfmKB1MZwSgyFVNU2weKo9nB/L6zbm+5kse16gLJ5VSyrS36IyG4icrKIXCYiPxGR3x24/b+IyPdEpCMifzFw21UicomIXCQi5094qX8BcDqAI/O/ryILgNwA4FPjHshMEBeYDULjMBuEiMikqkf9ORKfpoQ/997qEuaWrQ1a2OU6e4Ni8kEAZ6jqH4vIPNafyN4K4JUA/nDE4w9T1ZsLvM4TVfVRfZcvEZELVfVRIvIn4x7ITBA3+IXWPGaDVMfqsJS1/cpKPyWaDcJVYmbHpXIpJVa+sr1akdAtoBgwycQUEbkbgMcB+EcAUNWuqv6m/z6qepOqnofZDzg3iMhBfa/9aAAb8ot3jnsggyDUEB4p1IsrxRC5xCkxdrB/iIiIJtlDRM7v+3vpwO17I1ux5ZMi8gMR+biIlMllUwDfEJELhjz3oBcD+EcR+U8RuQpZ4OUl+eu9b9wDOR3GFU6LaZ6namvWWf38re1XVvspEZ6LexKVVdXXjYVin7P8XCc83YSI4tLDHFr1HtferKoHjrl9FwCPAvAKVT1XRD6IbCnbtxR8/kNU9XoR2RPAmSJymaqePeyOeTbJI/LsE6jqbX03/9O4F3EZBBGRI5DNNdoA4OOq+lcDtx8N4OUA7kJ2SPtSVf1x4w0lahRrg1CVAi+XqwCYKe1T3YGk1JfKjfWEPdb3NYyFoFE/a+0hlzpYwMKU6Y2FlyNeBgsp23cdgOtU9dz88snIgiCFqOr1+b83icgpAA4CMDQIIiKvGbgMZKvDXKCqF417HXfTYURkA4APA3gKgIcBeK6IPGzgbp9T1Ueo6v4A/gbAcQ03s0bWahiU5THfmLVBqmP18/e+X5FrnBJjB/uHqBoNHjp12uNXeGmtWMr2nB5XpCEPVPUGANeKyL75VYcDKJSMICLLIrJ57f8AngzgR2MeciCAowHcN/97GYAjAHxMRP5y3Gt5zAQ5CMAVqnolAIjIFwA8A32dq6r9BRKWEd2ii9bS98kOZoPEwcqUmESzQTglhoisKZspU9fPSEoZOwHNklVhSQuLWOJgYopeAeCkfGWYKwG8KJ+pAVU9XkTujWwp2y0AeiLyamTJDXsAOCXP6NgFWWLDGWNeZy8Aj1LVFQAQkbchWzL3cQAuQJYMMZTHIMh9AVzbd/k6AAcP3klEXg7gNQDmATyhmaZRMVZO8MrwVBvEeiDE6ufP4CJRZRhIolRY/UmjYDqYxwK6667n8rWUinwqymDdkOP7br8BWQBj0FYA+5V4qT2xcz7tNgD3UtW2iIyNInoMghSiqh8G8GEReR6ANwM4avA+ecXZvOrsHk02rwLeT9g8HjV4CoSQfx73EZpak3UuYti0WBekutF4S8VRQ2YZMMOBhihcqyISsWSgpKwHQSud85WTAJwrIqfml58G4HP5VJqxU3Dc1QQBcD2A+/Vd3iu/bpQvAPjDYTeo6gmqemBWJKgiUQAAIABJREFU4dbyyPko6XwpU1nWl8zlxHs/Zl3CfUahJjOuBHpdCo9fT34x696flfAVsLu98TVFLOvAb9srxQBmklT1XcgSGn6T/x2tqu9U1VVVPXLcYz0GQc4D8GAR2TufZ/QcAKf130FEHtx38Q8A/KzB9lFhHo80eYQVN2uBRY/7CFGOgSSi0e4I3QA/equeM5+JqGoisiX/9+7Iao58Nv+7Mr9uInfTYVT1ThE5BsDXkS2R+wlVvVRE3gngfFU9DcAxIvJEZEOYv8aQqTDx8D4thurD2iBUlcAFUlPBKTHleJsSQ2QZl8ktjTU+/NgC4MbQjaAqfQ7AU5EVP+3PGZb88j6TnsBdEAQAVPVrAL42cN1b+/7/qsYbRVPyeCTO2iBxY2DRHK4SQzFIoS4IEZXGFVSaw6+5OKjqUyVbQubxqnrNNM/hMghCg3jSRqMwG8Q/K33EbJBGMLvBBiu7nTfei6NOq6ntxcoyuUVxzIiocYo5dBM4kFBVFZHTATximsd7rAlCQ3lOx/NY94AR+7h53p8ixQKp1Wviq7fu/uMiBjRolp/n1cpaETf2kyuDK4V0EjhBpmRcKCKPnuaBDIKQER4DIV5wpRj/2EdERESjdNrjV0lprTBj2j3WrKH1DgbwPRH5uYhcLCKXiMjFRR7I6TBR4bSYZjHPM27cn9bjlJhGcEqMDXVMJWBdEOrHYqREI+kyIMw6ovF+f9oHMhOEDOFod32sZ4PQZNw/OCWmBjFMiSFbuPQrERE1492qenX/H4B3F3kgM0G2uyt0AyrC0etmMRukGlaHILk/rcdsEDKGmTPx8VgcNQahMlNWBNgUKspNFJce5tbVgYnYw/sviMgGAAcUeSAzQXYSy0ir56KOHj8DL0VSmQ1CEUjlOJkFP4mmF6I4alOHL4lOD+itckCiqHbJwZt2wRPm/hPrulYf6S4wok2TicixInI7gEeKyNb873YANwE4tchzMAhCREZ4DIA1jX0UDKd0zMZr/9Wxy1U9XSTRk2IqiD8bhXR7owurtqbICO1gfKHW2JUNxBCVoarvU9XNAN6vqlvyv82qeg9VPbbIczAIsk4svxbMBmkWs0Hi5Xlfqsu20A2gKnn8yh3EzJlqxLAtEBnG4ABRdYoGPIZhEISM4pFYmvi5T8Y+4pQYIuNYHDV+RTOQvIwRGdQZMuWEQRSiarAw6lBWizSWxaKOzfJSJHUrgC2hG+EM96X1EiyQugJgU+hGECUileKoXCaXDGtjCYteMmJ3BacHIiuMymDZZMwEGSmW0VYnX1xDxfIZUDn83CdjH1HFuFTuaKwL4hMzEKgBPNkkCktE9hORY/K//Yo+jkEQokp5OepibZDyPAcUIxRqSkzTJ/KcElMc+6oajLHaXyGGhuq00y5GGkpCy7GSMSLyKgAnAdgz/ztRRF5R5LEMgowVy6+Z55O3WD4DKoefuw8skEpE1Lg6M38irufSWrGbtcFAAtFU/gzAwar6VlV9K4DHAHhJkQcyCDIRT8aoLGaDxMtSQJHfTckUSG0Kp8RQlSI+mXbHw8/FioRugVtJLMebQn0gmoYAuKvv8l35dROxMGoyPBd2jKVQLZXDz90HFkitXQcYskgANamOr6OqC2LGWEg0xvdEU+utLmFu2dJgBJE9Chm6slCkPgngXBE5Jb/8hwA+UeSBzAQpxEMIvQj+cDSH2SDUhFi+m4gqwrog5BGzZoiISlPV4wC8CMCt+d+LVPUDRR7LIAg5wZO9NFn83BlMNIVTYqrFKTEE2PzqnYaX8QivitYm4edARDUQkc+q6oWq+qH87wci8tkij2UQpLBYjgg8n8B5+wy8/OozG4RmlWCBVK4SQxQ3rhBDiap7KgWLwFKFHt5/QUQ2ADigyAMZBCmFv2xEzbO431kKJlrsH6KA6goY1bGrxT4NIvb3R1Hp9kYXGG25ratHFB8ROVZEbgfwSBHZmv/dDuAmAKcWeQ4WRk0Si6Q2pw24iHhvBbAldCOIpqMoWAucCvH2NUs7xFhINMb3VIU6+6Xqor2J6mAeC+iGbkZ6FlDvMtLG9TAXfbaNqr4PwPtE5H2qeuw0z8FMkNI46kpEALNBBnFKTO1imhLDuiD2Wfhaoerw8yRjmF1Ds5o2AAIwCJIwSydwZXn7JWdtkNl5+8ypcSyQSk3gV5E/Xn6CqRKd9ugpLVa0A5z8W8gM6KazbCs5wCDIVGI5CvIcCCGywNI+ZOF7KcFsELLJU9ZM7HUzPL+/JlPqPfdTVVbqn9fYWmH2AVBf8dO6i6oSVYVBkKlZOOFImbf+9zIUxWwQolJinRLDpXL9SnguvBn8uUpKiMyOmHRhP3uH7BKRDSJyHxG5/9pfkcexMGryPBdJJSLqwwKpRETNarhwbW91CXPLlrIw69XBAhamiH63sYRFU9mq4WxcBnBb6FY0RyHJTD0SkVcAeBuAGwH08qsVwCMnPZZBkJmwhH5Y3vqfK8XMzuJnbimQaKF/tgHYGLgNRDWysJs1xcp75Qoxw3nqFy+HQA4wwEG03asA7Kuqt5R9IKfDzCyGnEfPX6Te+t/LtBgiKizWaR3evl4HsS4IEZFLrWWeolIh12LKPB9mghDREMwGKYfZIDsLmA2SwpSYDhBNpusKgE2hGxEhaxkCdwDYNeDrMwuhvNCfGRHRZFcC+LaInI6+oQ9VPW7SAxlmq4T34TKA2SBNYjYIERGRCzGtEOPtcCkxFpaxJXLmGgBnAphHNgK49jcRM0Goj6XRbKJxLGQ7DOL+k7RYMxos7mpl1JU1471fqH7cRlzq9uYxP9cN3YzGtbGIxZoG6VpYxBIHABvTw1wyATVVfQcAiMim/HLhCcrMBKkMw+theet/Dz8GlpfLpfEs7A/bwr20hnvpxniqdzFJrDVVyrJaF8TC1wnApX8puBYHOnyxNCWQaiEivyMiPwBwKYBLReQCEXl4kccyCFIpK0cKs/A8LYbSEsP+RkRERNutzF7UqdOer6AhROTACQBeo6oPUNUHAHgtgI8VeSCDIBQRbyfFzAaJj6Ugorf9IQLMaCBLrGVOhM508fCTOw0Ln7OFNiSug2YCP6lMsyA3llX1W2sXVPXbKJgDFDQIIiIPFpGTReTHInLl2l/INs0uhhMPSydyROQXp8TUqqkpMd5/1urqJ+/9QpSo1kpz01qaCk6E0I1mmTJy7EoReYuIPDD/ezOyFWMmCl0Y9ZMA3gbgAwAOA/AiMDuFZuKtEpmHdfu4XG45LJBKVFqshWXLsrosqcWv2iZZW3LYq4oOeXqrS5hb5oAd0TA9zKGdznHonwJ4B4Av55e/k183UeggyKKqflNERFWvBvB2EbkAwFsDt2tGMRwt8ESOyD8L30XbAGwM89IKYPbp5eXwZJ6oPt6CEdN8BdcdCCvTJqtBOWpUG0tYZJY4lSAiVyH7trkLwJ2qeuCQ+xwK4O+QHSTerKqPL/rYNar6awCvnKaNoYMgHRGZA/AzETkGwPWI5vDRwsnHrLwGQrz1PbNBZmPx8/a675A7dS0BO8jibkaTeQsaEDlVNlDAwEIJC4hrRbR0HKaqNw+7QUR2A/ARAEeo6jUismfRx+aP/ztVfbWIfBVDJkCr6tMnNS50EORVyM4UXgngXQCeAOCooC0iIooKz17JiTqzaOoKFnH3KoeZBUREBDwPwJdV9RoAUNWbSj7+s/m//2faBgStv6Gq56nqiqpep6ovUtVnqeo5IdtUrRiqpnmNUnvrew9l6y2vFOPt805NYgVSuUoMzSL0Kiox8/BTS0TknwL4hohcICIvHXL7QwDsLiLfzu/zghKPhapekP93f1U9q/8PwP5FGhg0E0REHgLgdQAe0N8WVX1CsEYREVWCU2KoIZwSQ03g528Xpz1RBFpYwpLbwVc7ephDp96Dgj1E5Py+yyeo6gkD9zlEVa/Pp7mcKSKXqerZfbfvAuAAAIcjqwnwPRE5R1V/WuCx/Y4C8MGB61445Lp1Qk+H+RKA4wF8DFnxkwjFcNTg9WTOW9+zNshsvH3eTWLfEDUWLKJ6hTrhZ6BhPPYPDWDdk2jdPK5YKQCo6vX5vzeJyCkADgLQH8i4DsAtqroKYFVEzgawH4CfFngsROS5yKbU7C0ip/XdtBnArUXeROggyJ2q+g+B29AAnoCEw76nkLwGEOvAVWKoAI/9Zv1nhienYVlcIca6FQE2hZjLmOn25jE/1w32+oM6WMBCw5VBQ7wmxUFElgHMqert+f+fDOCdA3c7FcDfi8guAOYBHAzgAwUfCwDfBfBLAHsA+Nu+628HcHGRdgYJgojI3fP/flVE/hzAKeir+6uqhSI41CSezDWD2SBUF+tnajQTZjmQF6mf4FuQwM9Bpz2PhcXqAxmep2y0sIilmgrj1Pnc5M69AJwiIkAWa/icqp4hIkcDgKoer6o/EZEzkAUsegA+rqo/EpF9hj128AVU9WoAV4vIkQB+oap3AICILALYC8BVkxoZKhPkAuw8Nve6vtsUwD6Nt6h2MfzieA2ExND3VAw/a9sCZoNQNbiLNYOBgvp4GGuwpOptkf1fCU41IatU9UpkU1sGrz9+4PL7Aby/yGPH+CcAv9d3+S5k5TYePemBQYIgqrp3iNcl8sHDEQKzQYrzGjyMDKfE+OFxqdxUMAhGRvRWlzC3HF8QoMqMCgZK0qQQtM2fR1RmF1XdnvKlql0RmS/ywKBL5IrIriLyGhH5soj8PxF5tYhEPPYRwzKeXr9MY+h7Koaf9WjsG6JaWN+1VkM3gMiW1goHJ2peQYSoCb8SkaevXRCRZwC4ucgDQxdG/QyyQ4f/m19+HoDPAvgfwVpEZIKHbBAqjtkgO3BKTG24VC6lgivEEBERcDSAk0Tk75Hl+14L4AVFHhg6CPI7qvqwvsvfEpEfB2tNI2I4evR6QhdD31tieUoMP+vREu4bTokhT2KuCxLzewuFARqzOpjHAuysNkMUC1X9OYDHiMim/PJK0ceGDoJcKCKPUdVzAEBEDgZwfuA2NSDhkxAqgdkgcfEaPCQKgHVBKCZcJpeIqDIi8ieqeqKIvGbgegCAqh436TlCB0EOAPBdEbkmv3x/AJeLyCUAVFUfGa5pNJ7XEzoGoKplORuE7OKUmNpwSkw4qfRJDO+TYwz1SDwbhYVIyYIe5lKo97L2TTP1r1HoIMgRgV8/oBiOIogs4z42WsJ9wykxlKrET1BpgPWfgRUBNmnoVriS1LSbZWRBf0qSqn40/+9HVPVX0zxHkNVhROTuInJ3ZF/B6/5U9WpVvTpE26gMr9Fu62X8+1WzTFq9toZugCNe95k6bAvdACL77gjdAMO44k1zuB3Wou0yo5rIlP8QkW+IyJ+JyO5lHhgqE+QC7Dwetxbqlfz/+4RoVPOsh+GJvOM+RgmKpeYF64KQRcyomR2nI1EVFpD9TlCyVPUhInIQgOcAeFO+wMoXVPXESY8NEgRR1b3X/p9nhDwYyZZ/8n6Sxtog9fNwtMDaIMVZ2Wc87QMV45SYaiS8CY3EPimOhT+pZp32PBYWp5se0u3NY34ukakluTYWsegiA7kEBrujp6rfB/B9EXkvgOMAfBqAzSDIGhF5MYBXAdgLwEUAHgPguwAOD9kuKsvKSR3RMDwrsYsFUokaVVUWA79Wy2uizxLLUumtLmFumdNMqRjrw4lV6WEOrUTerYhsAfBMZJkgDwJwCoCDijw2SE2QPq8C8GgAV6vqYQD+K4DbwjYpBE81KmLiqd89ROZZG8QfT/tAxWKvtxdLwTimOlNdPPysshaHSS0O/NWqu8D0DSrshwD2B/BOVX2Iqr5eVS8o8sDQq8Pcoap3iAhEZEFVLxORfQO3iabCbBCyzNqwJfeXJHFKjC1e6oJw2ghRLVorS1jaxEySqnWwgIVoIvFk3D6qOtWwVuggyHUishuArwA4U0R+DSDRVWE8H0l65qnfWRuEYsQpMRQZTz8r3iU2/YOIJlgGV45Ky4NF5C8APBB9cQ1VfcKkBwYNgqjqM/P/vl1EvgXgbgDOCNgkmglHt4mKs7K/JHzGFqJAKlEsqvjq8JrlEkvwpY6v/1j6xhhmVxAN9SUAxwP4OIC7yjwwdCbIdqp6Vug2hJfwyUhQnvrdQzaIVZ4+Z4pWk1NivEz3mCTGaUQh8SSVpuE1YEWUmB7m0DYxyNaIO1X1H6Z5YOjCqLSO90KFnFtJLJDqT+jvnW2BX59mEnrzmYWXgVUWyKQUraSZqhfzyh7dKCLzZMhXReTPReS3ROTua39FHsggCBEAX0fxHkraW2Xtc2bQMLjYV4khotGa/jlt4ifISz0EHsrMrMnR/v7XqiJIU/Q5dFLWGrMEU3cUgNcB+C6AC/K/84s80Mx0GOrnPW3fSq0DCocFUolG4pSY+Hn/Gfck9uk9nIYShQ7msYBu6GbEgcVPKaeqe0/7WGaCEG1nLUtgHA6hxMNKNkjo7Z9TYlyre/NZqfn5aTpVfO6c6kMRsV6LwdpUm5bx/iLbRGSjiLxSRE7O/44RkUJLDjITxCzvw0jMBiGr2SDe9y2qHFeJSVuK2TKxZ09QMnqrS5hbHj2Y0GnPY2Ex3QyMNpawaGawhZqgEHQwH7oZTfkHABsBfCS//Pz8uhdPeiCDIEQ78XSCzJViKDbbkP2WJYBTYqgsTouwhYEkInSxgHk3FaYpQo9W1f36Lv+biPywyAM5Hca00Onps2LkmayuFGNt37Kyr1jrFyLHuDuRB3Vsp5HUa+j2khlNJ/LqLhF50NoFEdkHwF1FHshMEKJ1mA1ClBxOiZld3V+dTWbPUDr4M0oBcbpKTZbBekNpeB2Ab4nIlciO4h4A4EVFHsggiHmeTsiHYW0QssravmVlXwndLwlNiSE7OGVoelV8Zcw61cfT1JTQX7GziHBKVmtlCUub0g1CdLCAhRHTWcbdVlYLi1hiUX+qmKp+U0QeDGDf/KrLVbXQRssgiAuefzEBOyd3ZXjqc+vDWFYLpBIFxrogVFaVJ6GeAgepK/u587OtXQtLWGIGBxnUw5z5VYqqIiIvB3CSql6cX95dRP5MVT8y4aGsCUJERAQgmxJDs+FSuTtjXRCi0YokBqxwnmIZCa0KsgMDfil7iar+Zu2Cqv4awEuKPJBBEDe8H0l5jJZ76nPrKYYskFqMlf0kdL9sC/z6REQFRFIAlIjIqQ0isj1SKiIbgGKRQAZBiIiIQmkys4GrGI7H/iEiIvLkDABfFJHDReRwAJ/Pr5uIQRBXQo/OzsrKKHcZ3vvcEmaDFONxP4kIp8RQSqrKZLDwNTrLe7GeTElERMO8HsC/Afhf+d83AfxlkQeyMCpRNKwXSCVfQhcH5ioxbnGp3J1V3R8RrtABIN73NUzor9dB1tpDLs2yAkwX85hHd/IddwWXvp1AIegkUgldVXsAjs//SmEmiDsWhltm4XGU23ufW8JsEKJ1OCWGiGLTYL2U3ur4lTA67QSLhRLRWAyCEEWFOb1xsBIsTDQ4xCkx6WKQiKwqO/pdVxCCo/DBeBzdT2WpVvKHQRCXvJ+YWDnBK8N7nxN5xFViiMg4rhBDA0ad+JdZvrbF6c1EI4nIZ/N/XzXtczAI4hZPymkU69kgnBJDtE6TU2KaUPfuFFt/lVXlaDxP4oko12bwhXw4QETuA+BPRWR3Ebl7/1+RJ2BhVAqkBbhLkWPlMGqSlX0k0e1eAcjEe/nUARxmVfuWwm5UxXuctTjqKoDlKR/L2uI0RLc3j/m5AgU7iYzoYS6FTKLjka0Esw+AC7DzEZvm14/FTBDXOHJNozAbZDrcp+zhlBhqGOuCEDWnyOHKSr0R6daKhQGH6bDmRo6B/aSo6odU9aEAPqGq+6jq3n1/EwMgADNBKCgrI91lpDCcR3Z43Edoat6Wfp2EX5dEo3H/ICKaiar+LxHZD8Bj86vOVtWLizyWmSDuceSaRmE2CFUl0e+ZmFeJiSHbIfW6IERVSvRrfhYtDlK4schh/yiJyCsBnAT8f/buPE6Wsrz7//fLcuacOUcERYyKETFoXEjQ4JIfUVGj4gYmGsUlijExj8aYxF80+mhMNCaPhiSaqM/L8MQ1aiQxkvAghqiAO8giIOAGuLCoyKIwZ4Y5cOZ6/qgaaPr09HRP13LfVZ/369Wvme6u7rpr7aqrrvsq7Vc+Pmz79yf5LKsEWpbjlW4u33Qbyzc9N0vas+1GALOpetcya/2MQbPU0gAwkyXNa0uWd07MT25nHFjXb0t6eERslyTbb5X0ZUnvWO+DZIJ0AuF7rCX1bBCsjwMjoHFdyJRpQ18PR5q6w860dwXizj8Aus2Sdg4836kJy9qTCYIEkA3SXzdI2qvtRozA8t1V2/OkJ9kg1AVB33GHmPRNuozIMAIat6Ld+lQw932SzrR9Qvn86ZLeM8kHyQTpjL5efgH6gGyQ1lAXJG3UBQEgaWV7b076pjZ8QtyD26eiZba/a/trts+zffaI93/e9pdtL9v+42k+Oygi/k7SiyRdVz5eFBFvn6SNZIIgEWSD1Cf1S1upZoNgV7ms80CiUq4LAnTY8tImzW3Z0XYzMIutootXXh4TEdes8d51kl6hInNj2s/eTkScK+ncaRtHJkinkA0CVIftKT03t92AZpDdkIYuZMpMg5OL5vEzA6xpcSunqV0VEVdHxFlq8cAuy7XL9hG2v2n7EtuvGfH+K21fbPsC25+xfa822tmOnH9Rc0z5z2V+p14gldvlri/H7aMj6BIzm1x2k6gGyxsAumxf22cPPF4yYpiQ9N+2z1nj/XFm+ezEsusOY3t3Se+S9HhJV0g6y/aJEXHxwGBflXRoRCzafqmkv5b07PHfvHP82wB6iO4fu2KeIDFdKyaLPLv5dKEIaFu799R77UISt/LNxYqsZW2qcxTXRMSh6wzzKxFxpe39JH3K9jci4nMTfv/En7V9V0n3KJ9eGRE/mnAcWWaCPEzSJRFxWUTskPRRSUcNDhARp0XE6lZ6hqT9J/vqrlyNzvkyTI4711zmd+rZIMAk6BIDYB2zdO1J/ady2tvkdsXCRHe9hFT3CbCk+oqrLmZXHxCjRMSV5d+rJZ2g4vy9ss/aPsT2GZJOV5Hs8NeSPmv7DNsPmWQ8OQZB7iHp8oHnV+i2CNAoL5b0yVpbBKACXQlC1inHIGFHdLlLTBNyiRUPq6O7UNXzoq8nxZgMtV4msriw9sn3jpXpgwo53aJ0WXNtNwEdYnur7Tus/i/pCZIurPiz75f0BxFx/4j41fLx85L+UMVtc9eVXXeYadh+vqRDJT16jfdfIqnsa7RP+WpX7lSRc8p6jneKyQU5p9PLeVuqC/OkU5YljoEhqRtdOoCELWuT5tT9u9Qsa05zvasujdJdJZ1gWypiDR+JiP+y/T8kKSLebftnJJ2t4qR7xfYfSnqApH1HfXbEOLZGxJnDL0bEGWXwZF05BkGulHTPgef7l6/dju1flfQ6SY+OiJFbYUQcJ+m4Yvh7cp0PM+CksBpdCULWiSBh0SVmz7YbgZRQFyQt/CR236R1Wwisbdiitmh+qH8WwQWkLiIuk/SLI15/98D/P9TochU3jPrsCJ+0/QlJH9RtPUTuKekFkkYFTXaRYxDkLEkH2b63iuDH0ZKeOziA7QdL+kdJR5T9iabUlROxnI9CONFDSnLellCZkNRkt3RO7IHu4+cFQIVCu2XVHWsjIuIVtp+koi7orYVRJb0rIk6e5DuyC4JExC22Xy7pFEm7S3pvRFxk+02Szo6IEyUdq+LQ8d/KdJrvR8SRrTUaPZHLkUzqXWK6EoTsulzWd0ykiS4xua4ydcybXOdFk3K8Qwx6Z1Hzmu9wva6sMk+2ihpJPRIRn9QMdT+zC4JIUhnhOXnotTcM/P+rs4+lKydiOR9pkQ0CjMa2QZcYYAABg1210Q2Drh+tWtk+r922djcgAWB9to+LiJesN1yWQRAgXbkEnVLPBklRLssWtaJLTLqYV9XgRD79n0iCXhuyvLRJc1u6X5S0aTs0p025ZIugE2zfaa23JD15ku8gCDIW2SDt44p3P3Vl2+u6nPctAIBdsFtvxZLmtaXD3WqAiv1Y0vd0+8tSq5ep9pvkCwiCrIuTMUwrlyOI1C91pSilZUuAkC4xFaMuCKrEsk5HDtk9HJJsWC8CKHMSySaTWdFuWuz+8eFlkh4XEd8ffsP25SOG38VulTcJibqx7QbMoOM7dqzhhrYbAIzW9A3VFxoeH3ZVx8F3zj/LTaHIIQYtNNkXEUDC3i5pnzXe++tJvoAgyEQ4GcO0cjm6XVp/ECQshQBhLus6eqHPASMCBvliNwoAE4uId0XE+Wu8945JvoPuML2Sc24qqf9IRc7bURfRJaZSTXSJQfpy6D4xia5MR6omLdDKcgBQA9u/PuLln0r6WkRcPe6zBEEmRm0QTIuT5dmx3eWBdR1TYHVBDjZao4ITfmRuSVu0hUxh5OHFkn5Z0mnl88MlnSPp3rbfFBH/vNYHCYL0Ts5Hn2SD1INqZNNLaTtiu2gFt8rtnzqyZFLaldSh69OHTllcmNf8ttHdTHesbNKm3bi9bhW4pW69VrSbdqxsarsZTdlD0v0j4keSZPuukj4o6eGSPidpzSAINUGm0pXaIHQ+bQ7zenZd2e5Qn5vbbgBSQl0Q9AHLGgDuuRoAKV1dvnad1jk4JAiCzKRQCLKLSHvErAj4dQYX6JASTvabx+68EktkaY61WFcWMt3R+uR02yfZfqHtF0o6sXxtq6SfjPsgQZCpdeWqNL9wzWFezy7F7S6l5UpwsBXcKnfjUtp8MNr2thuASrE8AXTP70l6n6RDyscHJP1eRGyPiMeM+yBBkA1J8YSsTzjhqwfZIMgZXWLQALJk8pPLyT+BwUqsbE8/+2JZzddrSCErpbbMD/RWRISkL0g6VdJnJH2ufG1dFEbtNSqWAbNJaRtKoUBqSvMDvZZTIdmubzY5Tx91w5vF/G7MorbOiqCyAAAgAElEQVRovoaLX3V9Lya3snM3LS60fTzYDNvPknSspNNVlKt/h+1XRcTH1vssQZAN49ad7UrhhG8auRwFpnwEwjaHBDV9l5im1HEnlGG57BZzc5OkzW03oue4TW6ylpc2aW5LtXd5WdS85slS3jDmH2bwOkkPjYirJcn2XSR9WtK6QRC6w/Qe+ZcAuqIHXWK6VBcEQP6aLly70MWoc/Xa6HIDtGC31QBI6VpNGN8gCDITaoO0K7eoMQGn2aW4zaW0XFPYJlKaHwBmkko9De4Qk79U1qXMUEejAmTGddl/2T7F9jG2j5H0CUknT/JBusNA5CTj9lLuEgMkiC4xaaqrLkgd84WfYWwEXZ96aVlzmqNKM6CIeJXtZ0g6rHzpuIg4YZLPEgSZGXUK2kVtEAA9k1PRz/WwS0QTqNEBZGXH3Jw2LRPo2YhYsZaX+tMdKiL+XdK/T/s5usOgRAo7BqVc2ZsuMeP1vUtMD+qCAOtJrftISrvIPpumSwrLDECibN9o+4YRjxttT3SiQCZIJcgGaRfZIAAAoAZN9hDl8KDXljSvLS1dyKCLDXISETPvKckEwQDC/hhENsh02H56LdpuQE1yPyau6246uc8X1I9CoFlaXMjpoloelrK6UIm+IAhSmRRPyvokhS4A0+CEGXVKYXugS0ytunSrXHaHhVTnQyon86l18UHv7FjpT52FTqBoMMagO0ylutAthlxMAAAAtKCC7kcr2+e129YULgYALVjZTSvbyb5ZD5kg6BB+8KpHl5jppHQpl+2hcV3tEoM8pZY50fbuMZWMli5KbV3rIbqcANMhCFK5FE/MptX2kUpfMJ/RdXSJqVVTXWJyr39BXRB0GQEINIhgC7qCIAg6hqvf1SMbBEDNiAkjZSn/DOakqmycBc/08eWl5mp7dDlosNjYbZOA6hEEqUUXTsw4Im0G87l7UlqmBAUbR5cYzCKl3ccgupI0J9V1AL21rLm2mwBUjsKo6KBFqcORdyAvbRZbvlnSni2NG0DlblJed3zYLmlr240YMk2bqJU/sUXNa36KCw/L2qQ57aixRd0RWyUTiJ3cimbOluoDMkFqQzYIJpXDfE45FzjFbS2HZYpOoC7IZLp0S+FpUC8CAIBdEAQBgE6jSwwykWPsMPfgUNNyXMYAgM4hCFKrFK9QTyvXI5bcTvxymM9kg2CjenaXGOqCYBY5/BzkipR6AIAIggBATTiTQUPoEoMmEEBIF92e0AE71NxdewAKo9buBkl7td2IGeVaGYsCqdVbkrglWobYFgBgJvz8AVNZ1pzmiJ43b0VpJ28ngkwQIBlkDsyGLjFpo0sMJlDnalJXxkzqx/hdyxLo2vR0RZXLhRO421lsIfq2RMQPHUcQpBFdODnL9QQ9t9og6JZctxsAQCU20o2In46ZrWzfePbj4kI3MyeXaswI3aG52r4bqANBECApORz5pHyJpgsBx7oQEOw06oJ0Sw4/BRvV5WnLRZv1XTKvLbNjJY26FcsEHYCZEARpTBdOznI9cuHkD23KdbupQ8/mBV1i0DWZn8BK6sY0NKlnu+22VZmtsUyhUWBNFEYFkpNDIVoqxCE3N0vas+1GYBJ17gIXJG2r6bsBNGfB0raNR5qXlzZpbsuOChuUn0Vt0XzS2b3YkBUR7J0AmSCNIhukPWSD9EcXtrO6sB10WlNdYrCr1LsJUUwUANAg27vb/qrtk9Z4/1m2L7Z9ke2PDLy+0/Z55ePEutpHJgiQJLJBuiWH5dkU5kX2liW6o6NVN0na3MJ4+dkDgEn9gaSvS9pr+A3bB0l6raTDIuJ62/sNvL0UEYfU3TgyQRrXhavUZIMgdV3YzurS5+2AW+UiI7n+1E6iy9PWFrJ9klXnXVmAFNneX9JTJP3TGoP8jqR3RcT1khQRVzfVtlUEQVrBCRoAAGuq8ySZbkNoGrfJBdAvb5f0ahUVSka5r6T72v6i7TNsHzHw3mbbZ5evP72uBtIdBhuUa0r7opRNRD6HeUxu8ORyWJ5NYV7UhsKf7elLN6Htkra23YgZdWEaUtRWNyUAt1lR3Zlh+9o+e+D5cRFx3OoT20+VdHVEnGP78DW+Yw9JB0k6XNL+kj5n++CI+Imke0XElbYPlHSq7a9FxKVVTwRBkNbcoBFdpABUhm1sbTkFA6vWwl1iQpKbHWXt+nLC3yWcoGIQgaDKLWpe873uctqgreIOKO25JiIOHfP+YZKOtP1kFb86e9n+UEQ8f2CYKySdGRE3S/qO7W+pCIqcFRFXSlJEXGb7dEkPllR5EITuMJgBuZr1y2Eec3u1yeWwPAEAaFkPDi2WtanS76P2CFIQEa+NiP0j4gBJR0s6dSgAIkn/oSILRLb3VdE95jLb+9ieG3j9MEkX19FOgiCtojZIO4jS9wfbWLoICGEdrCLMg3EoBNqcqtdDruCjCmQyZcX2m2wfWT49RdK1ti+WdJqkV0XEtZLuL+ls2+eXr78lImoJgtAdBjOib3/9mMeoA11iOou6IOtjHrUv1582SmFlY2X7vHbbyoWvXtsq6bq2G9FfEXG6pNPL/98w8HpIemX5GBz+S5IObqJtBEFaR92CdvT5BLAOHBVOLtcjf8yEuiD90Jd5Qj0JdNziwrzmt/UrgLKsOc1pue1m1GYvSY3fh7UNKyKLcAJ0h0EF2NKQMrrEpIt9B9AoupC0p4kuIH1bvgtdiywDaApBkCRwktaOnCL8OZws9qCKWefktA1gKgttNwBIXA51KXL46QcqtkimNhpAEAQV4ZcamBzbS/tubn6U0fwos1fnppJLoIjdBZCUHSvV3tUFQPMIgiSDbJB25HQlnCPhjWP7Shfrdda6230cOehb9w9UanmJYEYdFtusEbe5vVEjLxRGBVAhCqTmhyLBQKX6Uhy1CtSJblcdBW5vEieiNVjUFs3T7RiT2Kk8uvu1jEyQpOR+tTrXK7pkg/RDatsXy7J9LXSJaVIu3T2Qpz4fZHMuCgBZIwgCoGIcHWJaPQoIdbEuSN1dYqgLUi26kGAjerSbBtB9BEGSk9rV6mnxKwnkJ6dsKKCH+GlFH/X0mspSh7uotlovBBhAEASQlNdJIEfDG5dakJFl2b6Od4lBOygYm4emu/Q0Mb5cMn363J2qIssNFh8aHFcVQZodE7Z9ces6p6rUX8IGURg1STdI2qvtRsyASmegQCqm1aP9RkhyQ+NakLStoXEBbeh6Ic4e7Rq7bEnz2pLVBbeEbVY+wb42hJg/EyATBLhVTj9OZBB0RyrLMqf1H8nJuS4INq6Kq/ksW3TIYuJdWVLrakP3GLSFIEiyUkvbnxZHNUi1M2/u2xaqR5eYXqM4KtBZK9vTOulv2rI2td0EIEkEQYDbyelqOIEmABPo40l+F7HLT0uqcf6+WWiqbyFGIZMDuSIIkrTcr1hzxIZUpbZtpbKttB0ETGU+NKCLt8rF7VEcFTmgQOmaFhf6nUUCdBmFUYFdLEqJ9ZnMFwVSgd5YVr2V+ikQiTpsl7S17UZ0TNeL1VZoWZs0px1tNwNdslO9uqa0UWSCJC+1K9bTYiusF/MXqAZ1QXqNLkN5y6nGSc6ZFxxydM647ixLOV/E4ta5WAdBEAA1S7XjdGoBxlSOLukS05gmu8Rwko9hVQUOuENMenIKCrVseWljhUN3rFBwdBqp3ZUGIAiShdRO1qaV49FN2yeC08hx/gIApsbuvp9Y7gBQKYIgAABIoktMBeouBprbySDFUYG1TZJFlGoyaaLIuAAmQ2HUbNwgaa+2GzGDHCvaUSC1OqkWSE1tu0plO2l73U9lPgDAGKn+tAF9sk1519qp2oqYHxMgEwTohNwujwKQRF2QlDB/AADoBYIgWaE2SPNyqg2SulRzWnPfrgAAM+GqKQD0CkEQoDNyDDJhV6ksx7YDgG3NB+qCzIw6GPWqctPo0h1iuCPKxhEEQgV2cF9aZIQgSHa4at28tk8GAXRak11iuiCVOOGkCAphGEGHRq1sp75b6hYnrUO2td52oD8ojIqGUfCwXqnP31SryKVWIBWoyYKKInIYjfkDVOMmSZsbGteCpW3djyYvaovmk+1ajGSsKN0e6AkhEyRLZIMA3ZbKpe62s6DoEgMAkqbfHdbVPSiVn6eO68qtbpfpIoNEEQRBC3L8BW37ZLBLCE8DnUcXEPQFP2kYslbXjq4ENoAuIAiSLbJBsJYcg0wpSG2bYjn2SvczuavV982jq8VRAbSKzA30BUEQtCTHI1iyQdBHfV3vO9wlZqHtBvQQmTGTafMOMQRxMMLiAtkbQBdRGDVrFHPEWiiQujFsU+lJfV1G51AcFWjOdrV+x4/lpU2a27Kj3UZs0LLmNEeUtViHmA2FFRHUnQCZIGgR2SDAeDluIwCAdXGSMjnqrgCoGEGQ7KVWxwBA9xD8a0TX6oLUfVWOGCFQHYIy6LA7tJxthPQQBEHLOIqtT+rzNtVLOwQW08OtcitHXZDmVR0USn0XD3TcjpVNlXzPsqr5HqyPzrVYRRCkEzhpaxZXxdEkznSAxvUtSMQdYmbTVEyfnwMAqASFUZEACh/WJ/V5m2qBVOxqURJV8msXktx2I4AWpf6zlZObJG3u8fiBPlpRdYHtDiMTBNgQskG6jeyq9NAlpnJNZDtQrR9N4za59SMjBUDmCIJ0BidtQHdxxAmMxKYBQJIWxqfQrWzvbybjcM2RJbI6AYIgSEWOR7K5ZIOkPm9TLZCKXeWyzgOJojgqAGzMXNsNQJcQBOkUskGA6rA9pacnZ3xdu1VuriiOirrR/QZY0445oh6oD4VRkRCqodUn9XlLgdT1pb4Mu+xmSXu23Yh6LEjaVvM4lsUVvD7ZLmlr240AgJ5aUW+uGc2CTJBbrbTdgIpw9bpZdA8AgFZxsNc9LNN2tJWZQkYMgIYRBEFiOPJBSggq7orAH4DEtdG1p6nyVn09TKJ82MTqKny6PJDSR3FVrMf27ra/avukEe89yva5tm+x/cyh93baPq98nFhX+7IMgtg+wvY3bV9i+zUj3l9zxo7XlT0sJ27NyuWkMPUjp65sf3VKfRk2oSe3yqUuSHdx2+C0kZWAIYsL3T7hX0yoO/KOoTvZIGt/IOnra7z3fUnHSPrIiPeWIuKQ8nFkXY3LLghie3dJ75L0JEkPkPQc2w8YGmzcjEXyONFDSggqouOaKACa64l/DsVR+cnEOBS8ncjyUrUn34trZEr0JYMipcAKmmd7f0lPkfRPo96PiO9GxAVqsR5FjoVRHybpkoi4TJJsf1TSUZIuXh0gIr5bvreBGduVAo03SNqr7Ub0yKKUxQ8bxTVRhVzWd/QGu7Zq3CRpc9uNAABs2E7VndG2r+2zB54fFxHHDQ3zdkmv1sZ+mTeX33+LpLdExH9ssJ1j5RgEuYekyweeXyHp4S21BUCluhKErBNne8wDIHHcIab7Jt0NE1jbsCXNa8tQl+tFbdE83YfRrmsi4tC13rT9VElXR8Q5tg/fwPffKyKutH2gpFNtfy0iLt1oY9eSXXeYKtl+ie2zi2jTYMisKzuXnNP4ye9FSnLellAd6oIAqBg1SJCwJS5MYXqHSTrS9nclfVTSY21/aNIPR8SV5d/LJJ0u6cE1tDHLIMiVku458Hz/8rWpRcRxEXFoEc3ikgVmRYHUanQlCNl1uazvmAh1QZrFvFhf6j9VgKQdKxTyTMbc+oOgfhHx2ojYPyIOkHS0pFMj4vmTfNb2Prbnyv/3VRFQuXj8pzYmxyDIWZIOsn1v25tUzNwabp/TlROxnK9gcwQEjMa2wTxAYyiOmqcu3yYXADJj+022jyz/f6jtKyT9hqR/tH1ROdj9JZ1t+3xJp6moCVJLECS7miARcYvtl0s6RdLukt4bERfZfpOksyPiRNsPlXSCpH0kPc32GyPigS02G72RS8FIaipMj2LDkIouMXs2N7qQ5OZGlzV2a9WghgM1TXK1YGkb/QibRp2SxISSuStURJyuokuLIuINA6+fpaI3x/DwX5J0cBNtyy4IIkkRcbKkk4deW3fGTq8rRRpzPnnjqLafurLtdV0uQT8A6JA6D406HABa2T6v3bam2ZVzWZs0px1tNwPojRy7wwCJS/MHFl1D/jsqRl0QVImCn+lI5KrwWKwvGCM6GphDewiCrKsr6V3UBsEw5uv0ct6Ouoh1GA2pI0BEQAhABZapCApMjSAIgER1JQDZdX3MfOJWucnqc1ysi9PexWnCxnFYAKAiBEEm0pW9Llexm5PLiSFHmHlj+QFA9ugKAgCNyrIwKvqIAqn9lGKB1JwLDXcR+4ZKLUja1nYj0Lqu3CGmK9ORqkl3vywHoDk7xTWyCZAJMrGuZIOgOblkgwCzYl3HFKiFgRxsNDuDw0Vkjhoj6AOCIL2Tc5cYwpr1YL7mjeXXDuqC9A7FUadHNw9kZHlp05rvLS5wO/iqLCaX4Ys+IggyFcL7QPNS3O5yDiYCHUdcEH3Aeg4AG0YQpJdyPoHL7Vc/l24Cuc1XYBDrb6XqyHhAM7q4KXRxmgAAraIw6tRSLNQIoHkpFUhNoTjooqS+pQvfLGnPthuRp2WJbudAg6YpTrpd0tYa29ITi5rXfDYXw5q3Q3PaVEefwK3qd1e8UPe7WlaATJDeIhukOfwAzi7FLjFAw6gLgibd1HYDgA1YcNstWNdSCxcMlrV2vROgjwiCbAgnZOii3IJLwCDWXzSArkL5ySWY0+cr1+iFNoI/wFoIgvRaztkguSEbpJtS2oZSCAKwniMRKWwOk+p62nLOJ/c5tz1HDczvle3Vn4jvWMkvy6KugMQO+jkiEwRBNoxskHbldISbk5TnK9scUtTwrXKb0kTGQ9dP/tuS8m68L/i5AibGLXPRBgqj9l5KxR0BAGOFpPS7vAPoi6brcnN/goksaV5byM7sp52i6+YEyASZCaH+duV2uYsfo9mluM3RJeb22lzPU5h+oENSqafBpp2/VNalzFBHowLc6QgjEASB0jqJQ/s42gTQAXXtyrjChlTwc91LdB8BZkcQZGYpXpnuk9yOAMgGAbqn4bogTd0ql5P95lAfBQCAxhAEAZCZFAOPKWVTpRAYpEsMJsTJfz+0fZcVumJMr+1lhl5bpBsQakZh1Ep0oUoTBVIxqOlKZwCAyrALr852NVdToO5x3SRpc43fj5ksa5PmtKPtZiB3K+J60ATIBEEH5Lal0yUG6J6O3ioXwMakmLQIrIE6I+gbgiCV6cKvXUop/WhfysGlFLe3lLaflJddE3ow/dQFmQzFUWeXSleSHmzWaN/y0qa2m9A5y5pruwnALgiCoCNyOzoiGwRdxzqOCVEXpMB8AJK2uECdiqxwa1yMQRAEQ1K6mg0AAIDeqKIg64Ir+BIAXUZh1Ep1oUBqzqgEV72U52mK2xsFhvvtZkl7tt0IoJDy7rsNFAWtD+ta65Y1pznSySAVhVFZFdZFJghGIBukGXQXQJ1S6CLGrXJrRV2QyfRgVcgCt1ytB+s3GkR9D3QFQZDKpViwEZhFykdYbG8AWpJ7cAhoWiJFdle2N1fbY1HdrSOy1OFpQ/cRBEHHpHzCPgrZIN1DJhUwNVJ3C6nOh0ROXltDFktauP4BYEYEQWrRhb0zJ3JA/lIICvYt0Hdz2w0AuiuFXdo0NnI4WHfAZZqAFsEfSFpKrv4aMDsKo6KDqNBVvZTnaYoFUpGGlNfbioSkJm6EsCBpWwPjAYAM7VjZpE277Zh4+CXNa0vvLhJszOLW3TS/faXtZuRjRXTXnACZILUhGwST4kewe9h2gKTklkFQlb5ONwAAYxAEQUdx5AcU2BaaR5eYDUm1HsY4XG2bTtvdK/pe2wQAIIkgSM3IBsGkcsgGSflkugvbWpdxq1xgYjkGgwAAyAhBEACoBQFENCQaGg9ZD/1GFgWAGnX5dsJID0GQ2nXhCnWuJ3NcAa4e8zRPLDcAmEnbXXnGYRcPYFDU+OgIgiBAMnLoEpOyLgQcu6xv6zd1QZLT1xPFrk1316anK6pcLikHnDCxRe7ch4QRBGkEJ2ft4WgJbco1i6pr2A9kI8d6GHQTwjgbOQQkCNCq5aVNbTfhdpZa6CayrLnGxwk0iSAIJsTJXDNyuFrOCWWeWG6d1qEUVXQcJ/howoLbbkFyllVfcIesD+SGIEhjyAYB6sd2lrYcgnwYi6yHZuSYEYN8TFPktuqgVeYFdhcX0ijeSdABmA1BEEwh12wQroCjTbluN13Txn6AuiDomMxPYCV1YxrQ2WseVWZrtNGNBikIFccfdT26gSBIozq6x0bFcrhaTmApTyw3ZKDOLAg2AQCSVrYTICBIgjrY3mz7K7bPt32R7TeuMdyzbF9cDvORgdd32j6vfJxYVzv3qOuL0VU3SNqr7UZswI2S7tB2I9CIJYk0UfRRSKIbfDsWJG1ruxFj8BMIAGjGsqTHRsSC7T0lfcH2JyPijNUBbB8k6bWSDouI623vN/D5pYg4pO5GkgkCALWjS8xtcsh0wljUBUHb2srooagrAIwVhdUjhT3Lx3D59t+R9K6IuL78zNUNNlESQZAWdKFLTK4ndDnlQedwopjT/AQk6oIgKxRHxTT4SQbQjH1tnz3weMnwALZ3t32epKslfSoizhwa5L6S7mv7i7bPsH3EwHuby+89w/bT65oIusMA6CC6xKyNvHgALdsuaWvbjWgQP0m9tqh5zWdxcQvdsFM1R0WviYhDxw0QETslHWJ7b0kn2H5QRFw4MMgekg6SdLik/SV9zvbBEfETSfeKiCttHyjpVNtfi4hLq54IMkFa0YVsENQvhx9MLj1NLtcMqjrksG5najjhNFcUR00Xd1dpBl1vAGSuDGqcJumIobeukHRiRNwcEd+R9C0VQRFFxJXl38sknS7pwXW0jSAINijXEzqOfvuDYCNGYR9QCeqC7Ip5kg8COfXo+e51x0p1t7cFcmX7LmUGiGxvkfR4Sd8YGuw/VGSByPa+KrrHXGZ7H9tzA68fJuniOtpJEKQ1nKABaEvPj1QbR10QJIDNHoNSDwSRCTO1Zc213YTmbG67ARjjbpJOs32BpLNU1AQ5yfabbB9ZDnOKpGttX6wiU+RVEXGtpPtLOtv2+eXrb4mIWoIg1ATBDLhdbv0WpeTv457T/GxbrtsMACSGn57m9K2GS0OWNK8tdA9Fx0TEBRrRhSUi3jDwf0h6ZfkYHOZLkg6uu40SQZCWUSkLqBfbWLpyCPBlKiS57UZUYFmq7cJmLifQdc4DoC03iSv5mN1WkTE00oqovbY+usNgRrnWBskJOzLUoc+58X2ediARuZ685NruPlroQjQYMyGDCWsgCNI6aoO0g5OgajE/J0fgsJ86WBeEQqC76ss8Sb2eBDCj5aX+FTldJHMWPUIQBEDHEWhMF1lOAHqiiZ+ivl2P4OcdU6AiGwYRBEEFcr2yndPRAieLqENO2wCAmbHJ3yaHbBa63qCHdqh/WThoHoVRk0DxRnRBLpUGU8BdYtrXxvp6s6Q9mxkVxVHXl8sui+KoQFIWF+Y1v42LU0jVioh4r49MEFQk12yQnPCDu3HkzAK16EsNDKSJ43zMYGU7dyirww6itsgAQZBkcJLWDo6gqsX8xLQI7qFjCAwBQDu4GwwmRBAEFSIbBJhcKtsLgSsALcm15kWu7R5WR10UflJqsSSyVoAqEQRJCtkg7cjpF5ur5hvH9oVhbWz7Dd4qN5obVa2W225Ax1S12udQWBQAgBEojAqgYrlUG0Q6FiWucuVrQdK2thuxQeyugMlsF10NgCzsVDrZxukiEyQ5uV+tZqMD8pNTNhTQQ2TDoI+60u1oSssdvkUs3XqQCoIggKS8TgLpErNxqQUZCRq2L6dtH0Clmu7S08RPUC67NLpTzWxRWxob19LAuJYruPvLpG3fMbfOuMhOwgYRBElSaidq0+LEDrkchQFtoC5I53GHmOZ0/eemp9kQXbNIBkR1CHygAgRBgFvldCRFNgiq1vb6zzqNMegO0l2c5KNDdqx0tysL0CUURkVNbpC0V9uNAEZYkhpMIV0f2wo6gOKoealqmm+StLmC7wHqsmBpGylxq5a1SXPa0XYzbrVDc9pElLtiK8q/V0H9yARJFisvctd2ZgEwKdZVZIDzhLSQwZIGDpfHohApMBpBEOB2cjoZovsAuqZP6zR1QQAAeSPIglwRBEla7uFtCqQiValtW6lsKzkFAYHEURwVOeAuLWtaXqK+B9BVBEGAXXAiWB3mJdAbdZ/00x0EdSAIUD1++idGJgXQDgqjJi+1Io7TouhjvRYlfkCBCvSxOiZuxeLPW07LL+fDuu3i9qQds6R5bVmjK+qy5jSXa/R5q3ocOF8Rkcj1kQkCoGap7ojpEjNa28uLuiC1oC4IhlW1qVeRSUGRUbRkZTsXkpqwrLm2mwDcDkGQLKR2sjatVE7uptH2ieA0+nTSCAA91tsrmz03bZAop0OYTC0uEDwBckYQBAAAoA4URwVmQ5bQVMi4ACZDEARYE5dSqpPqvEwtyyqVrKm2l1db2U1tT3cHUBwVfcIJ+mwoSosqEPfBBlAYNRs5V9KSKJBaNwqkAnm6WdKebTcCUl7FNQEAGGlFdJVfH5kgAAD0AcVRAQAACILkJbXU/Wmlkuo/DdLjq5PqvExtu8pxO+mSVNdToAas7gW6ZQBArxAEATqD1DdUqe2zI9bnbFEXpF4pTn8Kt8lte5eVM4JAqMBi1t320TcEQbKT2lXrPuDICkCdbm67AagTd4jBMA7lmrXgtluAdUwcQKEIKipCYVQ0jAKp9Uq9QGqqlQdzLzwMTCgkcT6wtlR3UUBumtyWevITvqR5bSFLEuvaKS7gro9MkCxxCQHotlTqgvT1R7Sv0w0gWdN2F6prN8ZtgRuxrE1tN6ESdJFBqgiCoAWpnOBNg5MioHlc8QKQOIICGLJjZXQAYzHpTF2gXwiCAJ2T+oljqgElMqzQpo7VBaE4appLjOsAACAASURBVL2qnP5Ud8kAGkfmBvqCIEi2cj9hIxsEGC/HbQRZiLYb0EN9KI6a+x1Gcm8/arG81I1uKQBuj8KoAIAx2q4U2Vax37anG+ih7ZK2zvB5NlsAvbdTXEhbH5kgWcs9GwT1oUvMxrBNAb2X6u4J6KJJMnBqrruysj3fWh10Xylta7sByA1BELQoxyglR8doUo7bCFDqQxcQYKOIuQNAawiCZI9fUQB1I/jXjI4VR61b34ujAlWiJgqAHiEIgpZxpbs+dInZGAKL6WlrXU51Ha0AxVGbV3VmDEEgoFWLC9V0o1ni1rm127OsNUTnIayiMCowNSqvoUk3SNqr7UYA6DJ+1vIwa+FYAD2wIi7orS/LTBDbR9j+pu1LbL9mxPtzto8v3z/T9gHNt7JJrOhYS+rZIACQoA4nAdWqii4VNRfBrEWqbWY9BtAw25ttf8X2+bYvsv3GEcM8yva5tm+x/cyh93baPq98nFhXO7MLgtjeXdK7JD1J0gMkPcf2A4YGe7Gk6yPi5yS9TdJbm20lppNjlxiOLKqR6nwksLirVJdV13SsLgjFUdG0WXZV1MWYzKRBH342gD5alvTYiPhFSYdIOsL2I4aG+b6kYyR9ZMTnlyLikPJxZF2NzC4IIulhki6JiMsiYoekj0o6amiYoyR9oPz/Y5IeZ9sNtrEFnLQB6DLqglSuC3VBqIsBAGMN1xxZ1qaWWoI+iMLqJZA9y0cMDfPdiLhARd+dVuQYBLmHpMsHnl9RvjZymIi4RdJPJd25kdZhg3LMBslF6l1iOnySWRm2DwAA1rTetcCFjl8LBRJie3fb50m6WtKnIuLMKT6+2fbZts+w/fSamtjvwqi2XyLpJeXTBen132yzPZjKvpKuabsRmAnLMH8sw7ztq2hg+dUd56zr+/NYs9kG88cyTMC4y9Hj4ivleyzDvNyr7QbU66pTpNfvW+MINts+e+D5cRFx3OAAEbFT0iG295Z0gu0HRcSFE37/vSLiStsHSjrV9tci4tKK2n6rHIMgV0q658Dz/cvXRg1zhe09JN1R0rXDX1QusOOGX0f6bJ8dEYe23Q5sHMswfyzDvLH88scyzB/LMH8sQ6QkIo5ouw2rIuIntk+TdISkiYIgEXFl+fcy26dLerCkyoMgOXaHOUvSQbbvbXuTpKMlDVeOPVHSC8v/nynp1IjoQu9nAAAAAACSY/suZQaIbG+R9HhJ35jws/vYniv/31fSYZIurqOd2QVByhofL5d0iqSvS/rXiLjI9ptsr1aQfY+kO9u+RNIrJe1yG10AAAAAAFCZu0k6zfYFKpIXPhURJw2eq9t+qO0rJP2GpH+0fVH52ftLOtv2+ZJOk/SWiKglCGISJJAj2y8Z7n+GvLAM88cyzBvLL38sw/yxDPPHMgTyQxAEAAAAAAD0QnbdYQAAAAAAADaCIAiSYPsI29+0fYntXWq42J6zfXz5/pm2Dyhff7ztc2x/rfz72IHPnF5+53nlY7/mpqhfZlh+B9heGlhG7x74zC+Vy/US2/9g281NUf/MsAyfN7D8zrO9YvuQ8j22wQZNsAwfZftc27fYfubQey+0/e3y8cKB19kOG7TRZWj7ENtftn2R7QtsP3vgvffb/s7AdnhIU9PTNzNugzsHltGJA6/fu9znXlLugzc1MS19NcM2+Jih38KbbD+9fI9tEEhNRPDg0epD0u4qbn10oKRNks6X9IChYV4m6d3l/0dLOr78/8GS7l7+/yBJVw585nRJh7Y9fV1/zLj8DpB04Rrf+xVJj5BkSZ+U9KS2p7Wrj1mW4dAwB0u6dOA522Bay/AASb8g6YOSnjnw+p0kXVb+3af8f5/yPbbDPJbhfSUdVP5/d0k/kLR3+fz9g8PySG/5le8trPG9/yrp6PL/d0t6advT2tXHrMtwYJg7SbpO0nz5nG2QB4/EHmSCIAUPk3RJRFwWETskfVTSUUPDHCXpA+X/H5P0ONuOiK9GxFXl6xdJ2uLy1kpozIaX31pfaPtukvaKiDMiIlQcbDy9+qajVNUyfE75WTRv3WUYEd+NiAskrQx99okqqrdfFxHXS/qUpCPYDhu34WUYEd+KiG+X/18l6WpJd2mm2SjNsg2OVO5jH6tinysV+2C2wfpUtQyfKemTEbFYX1MBzIIgCFJwD0mXDzy/onxt5DBR3Cb5p5LuPDTMMySdGxHLA6+9r0w9/FPSuGsz6/K7t+2v2v6s7UcODH/FOt+J6lS1DT5b0r8MvcY22IxJluG0n2U7bNYsy/BWth+m4ir2pQMv/2XZTeZtXCiozazLb7Pts22fsdqNQsU+9iflPncj34npVLINqsiWHP4tZBsEEkIQBJ1g+4GS3irpdwdefl5EHCzpkeXjN9toG8b6gaSfjYgHS3qlpI/Y3qvlNmEDbD9c0mJEXDjwMtsg0KAye+efJb0oIlavVL9W0s9LeqiKNP0/aal5GO9eEXGopOdKervt+7TdIEyv3AYPlnTKwMtsg0BiCIIgBVdKuufA8/3L10YOY3sPSXeUdG35fH9JJ0h6QUTceuUrIq4s/94o6SMq0hxRvQ0vv4hYjohrJSkizlFx5fK+5fD7r/OdqM5M22BplytfbIONmmQZTvtZtsNmzbIMVQaQPyHpdRFxxurrEfGDKCxLep/YDusy0/Ib2F9epqKe0oNV7GP3Lve5U38npjbTMiw9S9IJEXHz6gtsg0B6CIIgBWdJOqisgL5JxcnUiUPDnChp9Y4Fz5R0akSE7b1VHPS9JiK+uDqw7T1s71v+v6ekp0q6UKjDLMvvLrZ3lyTbB0o6SNJlEfEDSTfYfkTZheIFkv6ziYnpqQ0vQ0myvZuKA79b64GwDTZukmW4llMkPcH2Prb3kfQESaewHTZuw8uwHP4ESR+MiI8NvXe38q9V1JNgO6zHLMtvn9UuEuV+8zBJF5f72NNU7HOlYh/MNlifWfajq56joQsCbINAgtquzMqDR0RI0pMlfUtFJsDrytfeJOnI8v/Nkv5N0iUq7lZwYPn66yVtl3TewGM/SVslnSPpAhUFU/9e0u5tT2dXHzMsv2eUy+c8SedKetrAdx6q4kDhUknvlOS2p7PLj40uw/K9wyWdMfR9bIPpLcOHqujjvl3FFeaLBj77W+WyvURFV4rV19kOM1iGkp4v6eah38JDyvdOlfS1cjl+SNK2tqezq48Zlt//Vy6j88u/Lx74zgPLfe4l5T54ru3p7PJjxv3oASoyR3Yb+k62QR48Ens4IgQAAAAAANB1dIcBAAAAAAC9QBAEAAAAAAD0AkEQAAAAAADQCwRBAAAAAABALxAEAQAAAAAAvUAQBADQS7ZfZ/si2xfYPs/2w8vXv2t73xbbdWzZrmOHXj/G9o/Ltp5n+4MVjW/i6bX9ftvfKcd/vu3HVdGGjbK9t+2XbeBzf277j+toEwAASNsebTcAAICm2f5lSU+V9JCIWC6DAJsq+N49IuKWGb/mJZLuFBE7R7x3fES8fMbvn9WrIuJjth8j6ThJB7XYlr0lvUzS/26xDQAAICNkggAA+uhukq6JiGVJiohrIuKqgfd/3/a5tr9m++clyfbDbH/Z9ldtf8n2/crXj7F9ou1TJX3G9lbb77X9lXLYo4ZH7sKxti8sx/Hs8vUTJW2TdM7qa+PYPtz2SQPP32n7mPL/79p+44jpuLPt/y6zTf5JksvXt9r+RJnhceEE4/+ypHuUn929nJ6zysya3x2Yznfa/qbtT9s+2fYzB9q3b/n/obZPH2jHLvPP9gPL184rx3GQpLdIuk/52rHlcK8aaMcbB+bN62x/y/YXJN1vvXkLAAC6iUwQAEAf/bekN9j+lqRPq8iw+OzA+9dExEPKrhZ/LOm3JX1D0iMj4hbbvyrpryQ9oxz+IZJ+ISKus/1Xkk6NiN+yvbekr9j+dERsH/j+X5d0iKRflLSvpLNsfy4ijrS9EBGHrNHuZ9v+lfL/v5f0nXWmc9R0/JmkL0TEm2w/RdKLy2GPkHRVRDxFkmzfcZ3vPkLSf5T/v1jSTyPiobbnJH3R9n9LerCKgMMDJN1V0sWS3rvO975OI+afpP8h6e8j4sO2N0naXdJrJD1odX7ZfoKKzJSHqQjunGj7UZK2SzpaxTzfQ9K5ks5Zpx0AAKCDCIIAAHonIhZs/5KkR0p6jKTjbb8mIt5fDvLx8u85KgIWknRHSR8oMxBC0p4DX/mpiLiu/P8Jko4cqDmxWdLPSvr6wPC/Iulfyi4vP7L9WUkPlXTiOk2/XXcY24evM/yo6XjU6v8R8Qnb15evf03S39p+q6STIuLza3znsWWgZ39Jv1y+9gRJv7Ca5aFiXh1Ujmt1Oq8qs2XWs9b8+7Kk19neX9LHI+Lbtkd99gmSvlo+31a24w6SToiIRenWjBsAANBDBEEAAL1UnpifLul021+T9EJJ7y/fXi7/7tRtv5V/Iem0iPg12weUn101mOVhSc+IiG/W0e4ht+j2XVs3D70/ajpGiohv2X6IpCdLerPtz0TEm0YMuloT5PdVZHX8kopp/v2IOGVwQNtPnrDtg+1ea/593faZkp4i6eSyy81lQ8NY0v+KiH8cascfjmkHAADoEWqCAAB6x/b9yoyOVYdI+t46H7ujpCvL/48ZM9wpKmqKrNbaePCIYT6vomvL7rbvoiJj4iuTtH3I9yQ9wPZc2XVkkru1fE7Sc8u2PUnSPuX/d5e0GBEfknSsii4+47xT0m62n6himl9qe8/yu+5re2s5rtXpvJuKrJtV31URQJFu61YkrTH/bB8o6bKI+AdJ/ynpFyTdqCLLY/Czv2V7W/mZe9jer2zH021vsX0HSU9bfzYBAIAuIhMEANBH2yS9owwc3CLpEhV3ZRnnr1V0h3m9pE+MGe4vJL1d0gW2d1NRt+OpQ8OcoKIryfkquta8OiJ+OO1ERMTltv9V0oXleL66zkck6Y2S/sX2RZK+JOn75esHq+jqsiLpZkkvXWfcYfvNkl4t6fGSDpB0bhm8+LGkp6uYzseqqAXyfRVdWgbb8R7bf6HbZ9WsNf+eJek3bd8s6YeS/qqswfJF2xdK+mREvMr2/SV9uYyhLEh6fkSca/t4FfP7aklnTTCfAABABzki2m4DAADoAdvvV1Fv5GNttwUAAPQT3WEAAAAAAEAvkAkCAAAAAAB6gUwQAAAAAADQCwRBAAAAAABALxAEAQAAAAAAvUAQBAAAAAAA9AJBEAAAAAAA0AsEQQAAAAAAQC8QBAEAAAAAAL1AEAQAAAAAAPQCQRAAAAAAANALBEEAAAAAAEAvEAQBAAAAAAC9QBAEAAAAAAD0AkEQAAAAAADQCwRBAAAAAABALxAEAQAAAAAAvUAQBAAAAAAA9AJBEAAAAAAA0AsEQQAAAAAAQC8QBAEAAAAAAL1AEAQAAAAAAPQCQRAAAAAAANALBEEAAAAAAEAvEAQBAAAAAAC9QBAEAAAAAAD0AkEQAAAAAADQCwRBAAAAAABALxAEAQAAAAAAvUAQBAAAAAAA9AJBEAAAAAAA0AsEQQAAAAAAQC8QBAEAAAAAAL1AEAQAAAAAAPQCQRAAAAAAANALBEEAAAAAAEAvEAQBAAAAAAC9QBAEAAAAAAD0AkEQAAAAAADQCwRBAAAAAABALxAEAQAAAAAAvUAQBAAAAAAA9AJBEAAAAAAA0AsEQQAAAAAAQC8QBAEAAAAAAL1AEAQAAAAAAPQCQRAAAAAAANALBEEAAAAAAEAvEAQBAAAAAAC9QBAEAAAAAAD0AkEQAAAAAADQCwRBAAAAAABALxAEAQAAAAAAvUAQBAAyZ/uRtr/ZdjtSYfuTtl/Ydju6zvbptn+77XakwvYxtr9Q9bAAAKBaBEEAIEG2FwYeK7aXBp4/b3DYiPh8RNyvrbYOKk/udg61/501ju/PbX9o8LWIeFJEfKCGcb3fdtg+auj1t5WvH1P1OCds14ttf8P2jbZ/ZPtk23dooy1Ii+3HlevGou3TbN9rzLCH2P687Z/avsL2nw6897yhbXqxXOd/qXz/z23fPDTMgU1MIwAA0yIIAgAJiohtqw9J35f0tIHXPrw6nO092mrjmHF/ebD9EfHyRhtWr29JesHqk3IePEvSpW00xvajJf2VpOdExB0k3V/S8W20BWmxva+kj0v6U0l3knS2xq8bH5H0uXLYR0t6me0jJSkiPjy0T3qZpMsknTvw+eOHtvvLqp8qAABmRxAEADJi+/DyKu2f2P6hpPetvjYwzENsf7XMDPg328fbfvPA+6+2/QPbV9n+7fKK7s+V783Z/hvb3y+zCt5te8ta456i3buk/w+N9/2232X7E2W7z7R9n4FhH2j7U7avK9v1P20fIel/Snp2eeX5/HLYW7tp2N7N9uttf8/21bY/aPuO5XsHlG14YTm919h+3TqT8n8l/YrtfcrnR0i6QNIPB9p6H9un2r62/M4P29574P3v2n6t7YttX2/7fbY3TzovhzxURdDpq5IUEddFxAci4sbheVE+v91yKKf/FbYvK9t6rO3dBob9ou13ltkB37D9uOEG2N5ULpeDB17br8wWuMuI4X/O9mfL77zG9vHl62+0/Y7y/z1tb7d9bPl8i+2bbN+pfP4I21+y/RPb59s+fOD772j7PeU6fqXtN9vefZJpsv0a2yetNbPL9y8t19GLbf/amGHXnLcDw/xNuQ58x/aTBl5/ke2vl+O5zPbvrjWeMX5d0kUR8W8RcZOkP5f0i7Z/fo3hD5D04YjYGRGXSvqCpAeuMewLJX0wImID7QIAoFUEQQAgPz+j4mrtvSS9ZPAN25sknSDp/eUw/yLp1wbeP0LSKyX9qqSfk3T40He/RdJ9JR1Svn8PSW+YZNwVOFrSGyXtI+kSSX9ZtvkOkj4t6b8k3b1s12ci4r9UZEGsXoH+xRHfeUz5eIykAyVtkzTcPedXJN1P0uMkvcH2/ce08SZJ/1m2VSqyQj44NIwl/a+yrfeXdE8VJ6CDnifpiZLuo2J+v37MOMc5U9ITywDCYbbnNvAdvybpUEkPkXSUpN8aeO/hKrJc9pX0Z5I+vhqIWBUROyR9VNLzB15+jopl9OMR4/sLSf+tYjnvL+kd5euf1W3r40NVBJYeVT7/ZUnfjIjrbN9D0ickvVnFuvjHkv59IODyfkm3qFhPHizpCZIGa5esOU0R8ZaIeOqINq+6VNIjJd1Rxbr6Idt3GzP8evP2m2U7/lrSe2y7fO9qSU+VtJekF0l6m+2HSJLtny2DP2s9nlt+xwMlnb86sojYXrZ/rcDG2yW9oAxA3U/FPP/08EAuutQ8Sruu908rg2EX2X7pmHkCAECrCIIAQH5WJP1ZRCxHxNLQe4+QtIekf4iImyPi45K+MvD+syS9LyIuiohFDZyclydgL5H0R2VGwY0qggxHD3x+3LhvbcPQSdkjJpyuEyLiKxFxi6QPqwjESMXJ4A8j4m8j4qaIuDEizpzwO58n6e8i4rKIWJD0WklH+/Zded4YEUsRcb6Kk8ZRwZRBH1Rxsri3im4D/zH4ZkRcEhGfKufRjyX9XTncoHdGxOURcZ2KYM9zJpye24mIz6u44v8QFYGBa23/3Wrmw4TeWi7v76s4ER5sy9WS3l6uS8erOGl/yojv+ICk5wycxP+mpH9eY3w3qwii3b1cnquZKV+WdJDtO6s4yX6PpHvY3qZi/n22HO75kk6OiJMjYiUiPqWiq8eTbd9V0pMl/WFEbI+IqyW9Tbdfhyedpl2UWRVXleM9XtK3JT1szEfGzdvvRcT/iYidKubf3STdtRzPJyLi0ih8VkXQ6JHle9+PiL3HPD5Sfv82ST8das9PJa1VL+YkSc+UtCTpG5LeExFnjRjuBZI+HxHfGXjtX1UE/O4i6XdUBBM3tE4DAFA3giAAkJ8fl+nto9xd0pVDaeqXD71/+Rrv3UXSvKRzVgMYKrIvBrs0jBv3qjOGTsrOWGf4VT8c+H9RxUmcVGRSbLTmxt0lfW/g+fdUBInuOsF4RypP2u8i6XWSThoOBtm+q+2Pll0xbpD0IRVX+wcNzvfvle3cRXlVfbXQ5CPXaM8nI+JpKrIijlKR+TLNXVvGtWV4XRrZ1jIotSjp8LK7xc9JOnGN8b1aRbbMV8rp+63yO5ZUBDMerSII8llJX5J0mG4fBLmXpN8YDLSpyOa5W/nenpJ+MPDeP0rab9ppGsX2C2yfN/DdD9Kuy3bQuHl763pXBiSlct2z/STbZ5SZFT9REdgZN55RFlRkkgzaS9KNwwOWmTD/JelNkjar2OaeaPtlI773BSqCNreKiIvL4NDOiPiSpL9XEVABACA5BEEAID/j+uH/QMXVcw+8ds+h9/df471rVFwFfuBAAOOOZSHEScY9znYVARZJku2fmeKzl6voyjLKeu25SsWJ8aqfVdFV4kdTjH+UD0n6/7VrlwCpyJ4JSQdHxF4qMhc8NMzgfP/Zsp27iIgHDhSa/Py4BpXZCZ+RdKqKk3NpaL6r6M40bFxbhtelNduq4sT4+SqyQD62VrAsIn4YEb8TEXeX9LuS/rfL2jAqAh2PVdGN5azy+RNVZFt8rhzmckn/PBRo2xoRbynfW5a078B7e0XEYBeQaabpVmU3kP8j6eWS7hwRe0u6ULsu20ETLeeh8cxJ+ndJfyPpruV4Tl4dT9kdZmHMY/XuURdpIKvJ9lYV3a8uGjHaAyXtjIgPRsQtEXGFii5OTx5q22EqAjkfW2cyQuPnCwAArSEIAgDd8mVJOyW93PYeLm7nOpiu/6+SXmT7/rbnVdw5QlJxEq3iJO9ttveTJNv3sP3ECtp1vqQHurgN52btWiNjnJMk3c32H7oo3HoH2w8v3/uRpAOGC04O+BdJf2T73mW3itUaIrdscDpW/YOkx+u2E/NBd1BxFf6nZf2KV40Y5vds719egX+dNnhHF9tH2T7a9j4uPExF1sRq9s15kn7d9nwZaHjxiK95Vfn5e0r6g6G27CfpFWWdiN9Q0eXh5DWa8yEVNTCer9HBodU2/4bt1UDc9SpOmFfK559VkWlwcRS1Rk5XkdXynbitvsiHVNSfeKLt3W1vdlG0d/+I+IGKriN/a3svF4Vx7+PiLjrrTpOLW72evkbTt5Zt/XE57It0W7BpLePm7Vo2SZorx3OLi4KpT1h9s+wOs23MY/XuUSdIepDtZ5Tb3BskXRAR3xgxzm8Vk+TnlvPsZyQ9W0XR30EvlPTvZVe5W5Xr4eA6+AoVtXMAAEgOQRAA6JDyxPHXVZzs/kTFCelJKq6OKyI+qeIE/jQVxUdXT5aXy79/svp62ZXj0yqKhs7arm+pSLX/tIo6Cl8Y/4nbffZGFQGHp6noQvBtFYVOJenfyr/X2j53xMffq6I2xeckfUdFYdPf38AkDLfpuoj4zFC3ilVvVFGj46cq6nR8fMQwH1Fxsn6Ziq4+bx4xzCSuV1GD4duSVrveHDtwIvw2STtUBIs+oKLWyrD/lHSOioDJJ1TU4lh1pqSDVGQJ/aWkZ0bEtaMaEhGXq7hlakgal7XyUEln2l5Q0WXmD+K226l+SdIW3RZculjFMrs12FSO5ygVdwb6sYrsj1fptmOaF6gIJFysYv58TEVXmUmm6Z6SvrjG9F0s6W9VBBp/JOngtYYdMG7ejlSu769QEbC8XtJztXbXonHf82NJz1AxjderKMR6a20UF3d+enc57A0q9ht/VA57noosl8G7Sm1WUVPodl1hSker2G/cqCIA9taIGDUcAACt8+jjNwBAV9g+U9K7I2KXW9q6uBPKhZLmKsiOwARsf1fSb0fELnfeaKEtIemgiLhkxHvHqGjnr0zxfe+VdFVEbPRuN7Vab5psnyfpcWsFeqYc15rzFgAAtIdMEADoGNuPtv0zZXeYF0r6BRVFD1ff/7WyW8k+kt4q6f8SAMGsbB+gIptg3WyHVEXEIVUEQAAAQLoIggBA99xPRQ2On6go3vnMslbCqt9VcZvQS1XUD3lp4y1Ep9j+CxUZRccO3ToVAAAgKXSHAQAAAAAAvUAmCAAAAAAA6AWCIAAAAAAAoBf2aLsBqdhj371jzwPu3nYzkrCbVtpuQvKYRwWrf93purzsu7Q8c11OubQ75Xam0ra2t6c25kOT46x7XHV9f9XrRZXtnPW7Zp22jY5/2s9N285Jv3/i4VbWH7/X+6qdY94b9/Vrfe+o1zf62jTPR/0/7rXV6Y6h9wb+jxVpZUVaCenm8iO3qLhX/Iqkq6RrIuIuI6akE+5rx/Yav/8q6ZSIOKLGUTSCIEhpzwPurnuf/eG2m5GEeS223YTkbWEe3WpOO9puQuO6vI1s6tDyzHU55bJ/mddS200YaU7LbTfhVltankdtbAObGpr/da9/dc27OvaxVbW1iu+ZZfo2Ov5p95nTHrdM8/3zO9dfL+eW1x//3HpnsQtj3hu3Ca71vaNev2nCYYefD49/3PA3jXh91PvD7y0PvTYw3M3bpaVl6cabpB9JukHF3yslLUl6vfQ9ddh2SS+r8ftfL+1b49c3hu4w2MWi5ttuQvKWmEe3WtamtpuACu1geQLIwKK21Pz99fzOs49tH8ctE9rcdgPWsbXtBiBnBEEwEoGQ9REI6S+2jzzkupzYt8xmWXNtN+FWSzWfqAMAgOkRBMGacj2BaBInK4U+XlXp8vbBlUpMou4r8ZhdG/upHQkFoQAAGIWaIBhrUfPZ9qtvypLms+nDX6dlbeplfRCkLdd9GPuV2SxrLqnaIEAOct1f5mZ5btNEdUE2bE7j64KkbqvWrl2Cde0mcYliAmSCYF1dvuINzKLL2wbZIJgE2SDro0tMfagLUujKb1Gq00HW75RIBkMGCIJgIqn+MKWCH8gC3WK6pSuBkFyXEfsVVIEuMWhSG78bXdxXLlP0E6gVQRCgIl38Ed6IPgZCgD5LNRskpQKpAFCpbW03AMgbQRBMLNerqU0iEFLoWyCky9sGMLF9LAAAIABJREFU2SDA7OgSA6Slb8cptSJrBRmiMCqmQtEsAGhOLgVSF7VF81pquxm7oEBqoY3f7h2a06YG5n3d615d826HNmlTgsXEOc6bzeLuWzS/M7194a3WKjpaZzHSJgqdbpZ0U83jyMTukvZquxEZIBMEU+OK6nhkgxT6dpWly9sF2SDA7MgGQZ3YvwHA5AiCYEP4sR2PQEiBQEh3dCUQkiP2JwByMsvvRZd/RwGkgyAINowfqvE4cQHSw36rPhRITVuX1/1U1z00h2MuANMgCAKgVmSDdAfZIO3hAL8b+tYlpiu3yu3yfh2TYR+cp8E9LnUyMIggCGbCgcF4/GgWCIQgJSyf+qR6RZ5sEKSo6sByVfs29pH1W57r13ERkBruDlMKue0mZItK4uPlcneHui1rk+YSrISP6aR6R4Np5bjfYl+CWeW43gMAJre7pDu03YgMkAkygFTvjeOqwXhkhPQP2wT6KtVskFTQJaYeda937NO7p29ZqgBuQxBkCIGQjeMAYTwCIf074OjqNtGV/WSOy4f9yMbRJQZoDneImd3y1hk+zO4OGIsgyAhdOcBvAz9cWE/fAiFdxX4S45ANMl6b2SD8TqeFfWn3LP4/9u4/3raqrBf/59kb9zp7nx8CIlwDvGIR+RMEUq5XTcMf6KsbftW+aRZoKJGodO2W0re0b97S6qblt4SOQELXzEILvILKlxSvKdjBEFQsDlgKoQgov/Zh7TznuX+sudhrr71+zF9jjucZ4/N+vdbrnD3X2nPNPecYY875zGeMsZhQ+7cl9gYQhcEgyBQ8KdXHC6zp+BQ3P6wPtnk8PmxH6mM2SBypdInxIOfBUbNrG7dF+t4mGSpERnBg1BlSGQCQbOHghvkNkprqYIRsI2mWVSxjBXtibwZRa1Jty4mi2QLgwRKf2wrggcDbkogFILdwYC3MBJmDGSH1eHyC0KXsnlZMwG4xZIXH9optiH/sEkPkC9tdonQwCFICAyH18CJrNp5M8wqEpFof2D6SN+wSE0dXXWI8SrUdTfXvIiL/GAQpiQ15Pane+BHVkWp9SKF99HhsPARSOUYDdY1lLg1dtckxH8b0e5G+O/aYHrG/nwgMglSSwoV+DB5vLrri4SYmtJyyQYjIBivZIOwS44+H/Zbz4KhERGVwYNSKOBBgPRxMbDoOlJrXQKmp1oUU2kaPx8ZD+8EBUomIHODgo0lYALA99kY4wEyQGpgRUg+fKEzHjJC8sC7YxWOTD2aDdF/eOVXudLy2bAevpxxjN5lkiMhZIvJlEfmKiPzShPdfKSLXi8gNIvI5ETm6621kEKQmnqyI2sVuMf6xXYzDw0W/x5tSIqK6Vhczb/NCxTsZKDFPRJ4I4LUAngrgaAA/ISI/NPaxrwP4MVV9EoC3A9jZ7VYyCNIIL/ir41PW6TzcyISWUyAk1bqQQruY6rEhonZ4aCOsbGMK54SY+l5u+r1sJ3XhcQCuUdVVVf0+gKsAvGT0A6r6OVX9bvHj1QAO63gbGQRpio17dVZOzBYxEJJXIISoLR7aDovZIOwSk26XGGpHzGs2i9eLHtpaosi+DOCZIvIIEVkB8CIAh8/4/GkALu9ky0ZwYNQWpDAgYNc8DkDYFQ8DHVI7Uq0HKbSJqR4bolx4HJA3hbaTOrYNwP1T3usB6He4LSFsAfBg7I3wZRHAjrBfcZCI7Br5eaeqPtSdRVVvFJHfBfBJDIbavQ7A3kkrEpHnYBAEeUbA7Z2IQRCKhjcZ0+UeCOFsMUTVeWg3LN6Y9tFDz/2dAhHVldM1B1EL7lTV42d9QFXPB3A+AIjI7wC4dfwzIvJkAOcBeKGq3hViQ2dhd5iWsFtMPRZTHckGdovxLYU2ke0TdYldYnxh+2AXu6wQxSUiBxf/PhqD8UD+Yuz9RwP4CICfU9V/7n4LGQRpVQoX/THwQmIynsTzkWodYJvYPbYbROssjkPTJSvnFp4Lpuv3uG9q8R9HTd2HReSrAD4K4ExV/Z6InCEiZxTvvxXAIwC8V0SuG+te0wl2h2kZ+3PWwy4Bk3lIbw8ppxRV1gGbeFzaxy4x0+3BMpaN7RsitoPU2FYMRoegLKjqMycsO3fk/68B8JpON2oMgyABMBBCbWIgJJ9ASIrYHnYv9zaD6un6RncNPSwZCDxZwzZzIwZgDLA+OCkDLBssAJnnwJXD7jCBMPWvOitpmxblnuKey/ggrAM28bi0z2I3BSvT5ZIfbBtoltVFe+0cEQ0wCBIQAyHV8YKCcpdiHUihLfR2XHIPnHoWc4DUFFkMuHXJW9vlQRLt69bIv08UGYMggaVw8d81nrAnS+Kk20Au2SCpYltI4yzenOaeDcJZYihXlq8x+gw4ELWOQZAO8OK/OgZCJmMgJI+6xPJvk7fjknt7QdSFEO2CxevGpn9n138T2z8imoUDo3aEA11Vx8GwJst90MNcBkpNsfyzHaRxFmeKsYCzxLSL5YyoJCuDjFrZDocWAeyIvREOMBOkQxYj+9Z5e/LaFT7hIIrDW5vEtqI6dolhlxiyxVu7S0T2MQjSMQZCquPJj8axW4xfbANpnMWxQSzgAKnUlhTPJSnp9xqeF7fNeI8xRgBgDaBNGASJgDcB1Ibcn/AyEOKX9zbQ2zHJva2oI/dskBSFDLblMi4IEVEqGASJhCe3arzddHQl95ubXAIhRERdYpcYmsTb4KgWrC4yo4vIIg6MGhEHCawmxYEi25D7QKk5SLHse2//vB0T6+0EB66cjAOkEnWnysDr1ttUyteCANtDxpUfDLjuDjETJLIco+JNMCNkspwzQnLJBkmx7Htv/1I8JrSOXWIoJTm2VzlfGxHRbAyCGOD9RqBrOZ7IabZcAiFETVi/IeAAqZPFGiA1xXMtxwXxK8XySETxBAuCiMjhIvIpEfmqiHxFRM4qlh8oIleIyE3FvwcUy0VE3iMiu0XkehE5dmRdpxafv0lETh1ZfpyI3FD8zntERGZ9h2U80VXDk+Fm1m9wqLkUy733ti/FY0LrmA3SHY4LQuTc1rGfy1bpLW1vCNF8ITNBvg/gl1X18QBOAHCmiDwewFsAXKmqRwK4svgZAF4I4MjidTqAc4BBQAPA2wA8DcBTAbxtJKhxDoDXjvzeScXyad9hmvebga7x5mOznAMhuWSDsNxTE9bbCGaD2ML2hsaxTMTRHw8wEFEjwYIgqnq7qn6x+P99AG4EcCiAkwFcWHzsQgAvLv5/MoCLdOBqAPuLyKMAvADAFap6t6p+F8AVAE4q3tuhqlerqgK4aGxdk77DPAZCquHJeDPrNzkh5RIISY33do/tUNosZIPE6hKTIgba4vLe3lNLGNShyDqZHUZEHgPgKQCuAXCIqt5evPUtAIcU/z8UwDdHfu3WYtms5bdOWI4Z3zG+XadjkHWC/R79qIp/VTjeZ03omrdZGrqQ86jlVUZ39yrFMs92rzvW2wfOFJOvNfSwhH7szagtRNvcZtuY4rmDGtgK4IGSn92CZGYFSd3CArDM2WHmCj4wqohsA/BhAL+kqveOvldkcGjI75/1Haq6U1WPV9XjFx9pa9gQRsqJaBZmH9jC40GpYtkmz6pmx1bJKG0z87bf43U/UZeCBkFE5GEYBEA+oKofKRZ/u+jKguLfO4rltwE4fOTXDyuWzVp+2ITls77DFQZCyuNF2mbsFpO+1Mo927zuWG8frHVZYJcYovi8nvNWFzuou9vCf0UK2IrSUMjZYQTA+QBuVNV3jbx1KYDhDC+nArhkZPkpxSwxJwC4p+jS8gkAzxeRA4oBUZ8P4BPFe/eKyAnFd50ytq5J3+EObwrK83pyDMn6jU5IuQRCyA5vbVDO7QPZ1cUsMd6myrUmh78xa2XH6+C4HuRYyEyQ/wzg5wD8uIhcV7xeBOCdAJ4nIjcBeG7xMwBcBuAWALsBvA/A6wBAVe8G8HYA/1C8fqtYhuIz5xW/czOAy4vl077DJQZCyuOJebOcb3RyCISkVua9t3epHY+YmA2yWaxsEJbruNpsFy0cS+/tvDvxmy4ic4INjKqqnwUgU94+ccLnFcCZU9Z1AYALJizfBeCJE5bfNek7POOggeVx4K/NrA+ESM2kVubZ3nWHbQMREVE6ZAF4WMgsnXsCrrtDwQdGpfYwcl6ehScd1uSaEZJDNgjZwvanPcwGyZP3LjFENEGZG3N2saGOMAjiDAMh5fFGhIZyCISkVt7Z1nUn1wCpV+wSYx/3lS1s44hoHIMgDvHmoDxeiGyU84UAAyH+eG7rUjsWRBSXtfYwVhvXxfdavV7oM0uCqDUMgjhl7WRoGW9GNso5EEJEk1luF6x1W7DQJSaH6XLZJSYcC9dFqVzHWm47s8DAENUUbGBUCo+DB1JduQ6G2McSeonXGQ6Sakdqx4KIZZqontXFZazs3TPzM/3eEnp9n+c7MmQBDA6VwEwQ51KJpIdm4amHNbk+vbCa5tomlnc7PB0Ly22CtSf2FrJByDZPdZ8oRdu3xN4CsoxBkAQwEFIOL0hoKIdASErYxhFtlsMAqV10ifGEbSERUTsYBEkET4zlMBCykeUnv9RMamXdcxvn6VhYbhOYDUIhWCtXXWmjXfLUtmVhW43fSbTbxDKbZ5qDQZCEeL5J6BJP2htZvukJKYdsEJZ1orTlMECqZ2yDw6izX3O91klKogEbioNBkMQwEFIOL0w2yvXiIIdASEo8t2+e2hzL7UGuT+2tYZcYaoPlNp3XB4ZUHNvjYbkHSxYw2GehXolgECRBlk8qlni6KemC5RufkFK/0GE5JwqHXWLS4Cm4xms8qqWNpqrMDXDuAQhyg0EQyhpvEDfKNRCSupTKuecbAE/HwXJb4OmGtQvsEkMUl+X2MjsTgjA7ut8KcoBBkER5vlHomqcbEwoj9WyQ1Hhu39jepCfXbBB2iSnHcp3n4Kj+9LvKtGjre/xWXUocgyAJ83yj0DWexNfl+kQj9UAIyzhVZbktYDbIRswGIbJvdXF+Pe330r4WCSqh8SoovP1ibwCFtYYlLGEt9ma4sIoVrGA19maYsAcrWM5wX/SxhF7C9SWlMu65bUvpONBAHz300I+9GdTAKpaxgj2xN6MUz+3fuLp/S512NNdrm+RsBfBA7I0wbAEcm6UEZoJkgBkhVIflp8BEANu2LlhuB5gNEh+7xBARkUcMgmSCNwvlsMvARpZvgEJhtxjqAo8DtY1dYuyyXN85Lsh0qV8PtIIZB+QUgyAZYSCknFRP5nUxEJKelMo427XwLLcBlrJBch0gNSWWyhMREYXDIEhmeMNQTko3iVQPAyF+eG3XUjoGZEOMbBB2iYnDa7tHgW2LvQEtYpYJBcSBUTOU0oBaIXHwwnUcTIwoDC/tjOU2wNKAlhwglabxUtdj6HJw1FAst5FmcYDTMDgwainMBMkUnyCUwye16yynxIfCbBA/2KYRxZNSW5Jjl5iUjh/VwBtmyhCDIBlbwxJvHErgxcE6BkLSw/Idn5djYLn+W7pxjT02SOoDpLJLjE1sx8pZXUy7fta2JfYGUJtE5L+KyFdE5Msi8kERmXiEReSlIqIicnzX28ggCDEQUoKXk3sXYl9AxJB6ICQVbMvCy7H+E1nFNi9N/d7s49qvm7lhIX7IrJPkicihAN4I4HhVfSKARQAvn/C57QDOAnBNt1s4wCAIAeCJtAwGQtbxRigtKZVtr21ZSseA8swGSakMh8osSmkf5YIPQYhq2Q/AsojsB2AFwL9N+MzbAfwugAe73LAhBkHoIV5vHrrEC5h8pX4hxLJNZVkNglrqEkNhsUsMEdEUgkHWT6gXcJCI7Bp5nT769ap6G4D/AeAbAG4HcI+qfnLDJoocC+BwVf1Yy399aQyC0AYMhMzHm8UBqzdCIaUeCEmF13aMbQsRxRK7/anbbsfebqIM3amqx4+8do6+KSIHADgZwBEAfgDAVhH52ZH3FwC8C8Avd7nR4xgEoU283kB0iSfdAQZC0pJSufbajnk5BlbrvqVsEHaJoS5YautyP/5W28VWcQBTmu+5AL6uqt9R1X8H8BEATx95fzuAJwL4tIj8C4ATAFza9eCoDILQRJZOqmRbFif9MQyEEBHFFbpLDMcFSVeO1y21WB/ElL3irPoGgBNEZEVEBMCJAG4cvqmq96jqQar6GFV9DICrAfykqu7qciMZBKGpGAiZjRcy63hBkZZUyrbXNszL/rda75kNso7ZIERE1CVVvQbAxQC+COAGDOINO0Xkt0TkJ6Nu3Ij9Ym8A2baGJSxhLfZmmLWKFaxgNfZmmLAHK1jOaF/0sYQe64Z5bMOIiMrhNU03VheXsbJ3T7gv2Abg/nCrD24rgAdibwQ1oapvA/C2scVvnfLZZwffoAkYBKG5eBMxGy8a8pVyIITlOi4v+99q8HMVy1hBwJuMCvrooYd+7M1I0hp6WAq4b0OVo7brdyrXaVb/jpTP9UEwiBHXIux3ZTKA3WGoFK9p5V1h+u+A1fT4kDg+iH1e269U9j/FxS4x1KUYxz7F8tbv+TxvEXnBIAiV5vVGoispnoTryDEQQpQzq3WeY4MQUar6fNJP1AiDIFQJAyGzMRAyYPWmKBRmg9jnte1KZf9TXDGyQbridZYYq3Jpc0Jdp7i9/mkSVLEQkLGwDeQKgyBUmdebia7kcgExj9sLgZoYCLGPbVc4Vut7bjewlqTSboTS9v5h+0alxEhKYyIcGcSBUakWq4NXWeFlUMPQrA6aGAoHT6MQ2J6kgQOkUi6atFm8viRqaAHMjCmBmSBUG586zManYANWnxBTNamUZ6/tlof9b7WuMxtkgF1i6mMZss9DG0lEdjAIQo14vaHoCk/K+WG3GPvYboVjNRBiRW4DpKbSZoTC/eNH2+f21UUG1rqwY+T/26NtBVnEIEhhH3dFbbyhmI0XOfndGDEQQiFw39fHJ/kDKWeDUHvXY2xriCh1vPMfwUa/PgZCZmPZYiCEbGGbFU5udb0qZoOEEbpLDKWHbRVRvhgEGcOb1fp4UzEby1Z+FxypBkJSKcse26xU9n0MzAahJlh+qmnSVnlsm0Po9xrsh23tbQc5swBgS8BXIhgEmYAXmfXxxEXz5BYISRXbSZqF9Xy2mNkg7BJjC9vS9CTV/nGWEUoUgyBT8KRUHwMh07FcDSR1gTBHqtkgqfDYXrEdqY9P8+Ngl5ju5DwuiMdtbqIfK0CRUDYA5YtBkBlWsZJdg9oWjzcWXWGZGmAgxL9UyrLH9srDvs+pjnvDbJB6GETLW6rn8qjKBnIYeKGWMQhSgoeLTYs83lh0hWUqP6lePLEskzdWbmRzGyCVpmM7SkTULQZBSuIJqh4GQqZjmcrvSTEDIXZ5bKs87Pfc6jhNxy4x+fEwOGrMNmp1MVJANnYV4TgjYS1gsI9DvRIRLAgiIheIyB0i8uWRZR8SkeuK17+IyHXF8seIyJ6R984d+Z3jROQGEdktIu8RESmWHygiV4jITcW/BxTLpfjcbhG5XkSObetv8nDBaZHHm4uusEzxJonsYFuVD2aDsEtMXVbKziw5jwtCDSR0g0s0T8hMkPcDOGl0gar+tKoeo6rHAPgwgI+MvH3z8D1VPWNk+TkAXgvgyOI1XOdbAFypqkcCuLL4GQBeOPLZ04vfbw1PCPXw5mI6lqm8AiHMBqE2edjvOdVvms1DeSXfWMaIqIxgQRBV/QyAuye9V2Rz/N8APjhrHSLyKAA7VPVqVVUAFwF4cfH2yQAuLP5/4djyi3TgagD7F+tpDRvYehgImY5lKq8bJQZC7PLYTnnY7xbrt5Un+swGaZ/HLjEe6jGVZ7HN61SdrJIyg58yW4VaEmtMkGcC+Laq3jSy7AgR+UcRuUpEnlksOxTArSOfubVYBgCHqOrtxf+/BeCQkd/55pTf2UBETheRXSKya993JsZrpuLJqh6PNxhdYZnK66Ih1UBICthOEdEsVgJos1hpx3ht00y/Z+M4EqVmv0jf+wpszAK5HcCjVfUuETkOwN+KyBPKrkxVVUS06kao6k4AOwFg6fgnVf79YcO+gtWqv5q1NSxhCWuxN8OkVaxkX572YAXLme8Dz1iG4/Cw3y3W7VUsYwV7Ym8G+uihh36U796DZSx3uA88lFVaF/N4Wbxe7GMJPWPbZMJWAA/E3ggCsD4wKs3UeSaIiOwH4CUAPjRcpqp9Vb2r+P+1AG4G8MMAbgNw2MivH1YsA4BvD7u5FP/eUSy/DcDhU34nCEa5q7PyhMIilqd8pJoNkkIZZhtF5Bu7xFBZnrNQ+7Nudrd1thnh8GaeAonRHea5AL6mqg91cxGRR4rIYvH/x2IwqOktRXeXe0XkhGIckVMAXFL82qUATi3+f+rY8lOKWWJOAHDPSLeZYHjiqo43GdPlXp48X5BUxUAItcXDPrdYt610bYg5NghVZ6XcEBFRdSGnyP0ggM8DOEpEbhWR04q3Xo7NA6I+C8D1xZS5FwM4Q1WHg3S8DsB5AHZjkCFyebH8nQCeJyI3YRBYeWex/DIAtxSff1/x+53wcAFqDQMh0+VenizeLIWSaiDEO4/tU+7tBtXT9QCpLKfd8NiGtcFT+VpdZDCNKIZgY4Ko6iumLH/VhGUfxmDK3Emf3wXgiROW3wXgxAnLFcCZFTe3NezrWp3FPp9W5F6eLI4hEEqK/YxTKL9sn9pnsV5bGRuE2rWGHpYijbWSkqZteQrnAmqoB7RaFTkGCTUUa3aYpHmKQFuR69OKMnIvTzllhKQo9/IbA/e5XzlNl8tyOhn3y0a8PjTA+rgc1revawsYTDcc6pUIBkEC4UmsOp7opsu9POUSCEm1W4z38su2qX0W6zTHeEhTyAFSWWZoFovtHBENMAgS0CpW3F/8d20NS7zhmCL3spTLxUSqgRDvvLVLubcXnnGAVGqTt7YrlirXGEmcp5s2MwllBFCeGATpAC9Gq+NJe7LcyxIDIX7lXnZjsL7PLdbn3J/ss0uMDSnul67/ppT2Yb+X3jUBUWwMgnQkpca4KwyETMaylAcGQuxhm9Q+i4EQC5gN0i52iWnOe/tNJVkZX8PKdlCyGATpEE8g1fGmY7KcyxJvmigmb21Szm1FXbnc1E7DbBCyxlu7S0T2BZsilybjNGHVcYrKyXIuSxan2AyB0+ZSDnKpz1X10UOP07tSC3gdZdvq4jJW9taforu/FehNmy52G4D7a686GduBfM4yC2AmTQnMBImATz2q41OAyXIuS7lkhLBbjD3e2iPv+zsGZoOk9/d76xLDektEFA6DIJFw5pjqvN14UHgMhPjlvf3z1h5Z39+51OWqchkbxHr5pIGmx8n6cQ4xQwzbNiKbGASJzPoJwRpvNx5dyL0M5XKBkWIghMiy3LNBiLzL/fqIiKZjEMQANtLVMBCyWe5lKJdASGq8l1tvbZH1/c16PFmsbBB2ianGepcYb+3VOO/bT0S2cGBUIzhYYDUc5Guz3MtQDoMrcqBUe7y1Rd73d9dWsYwV1B+wkMpj2SSart9bQq9v/FyzFcADM34u+3vUDAdGLYWZIIZYf0pnDZ8KbMYylL4Uu8Ww3NIQs0FsSTEbhJpJfVwQIsoDgyDG8ORQDQMhm+VchnK5gUoxEOKZt3bIehthrR5bGBuEA6S2h11iiApVqkLbmQXMVKDIGAQxiDPHVMOT+mY5lx9rN1ChpBYI8V5m2Q5RqpgNQp5VPbfEuoZYXWQ9I+oSgyCGeb8p6BJvQDbLufwwEOKT9zLrqR2yvq+t1WFmgxDFZ62NtTRNbp+ZFaXsiL0BZAaDIMZZv1C1xNrJ0YKcy4+1mygqJ+cy2zXua7KIXWLsY9vhzLaKny8bUNlSdUOoEwsYdHUK9UoEgyAO8GRTHgMhm+VcfnIIhKSWDeId26D2WKu/Fm5uOV1unlIbFyTn6xKi1InIUSJy3cjrXhH5pQmfe3bx/ldE5Kqut5NT5DrBqePKG57gPU1bGVrO5YdT5/rjvbx6mjbX+76mNHVRLtfQwxL6Qb+DiCg3qvpPAI4BABFZBHAbgL8Z/YyI7A/gvQBOUtVviMjBXW8nM0EcYeS8GgtPOyzJufxYe6IcQmoZITmXV1pnre4yG4TKsFBOiMwp03Sxi01qTgRws6r+69jynwHwEVX9BgCo6h1dbxiDIM5w5phqGAjZKOeyY+1mKgQGQuzw1PZY38851F2ieazV01jbU6dt9TJDzDz9np/zCiXtIBHZNfI6fcZnXw7ggxOW/zCAA0Tk0yJyrYicEmZTp2N3GKeYwlyep9T0LuRcdnLoGkN2eGp7cm4XqlrFMlawJ+o29NFDL0JXjj1YxnJHfzu7xIRjoW1Kpc1JrTuqOz0gwyo82wLKD25bz52qevy8D4nIEoCfBHD2hLf3A3AcBpkiywA+LyJXq+o/t7qlMzATxDFrTwUs8/RUtgssO+liNgilyOqTWaJp2CWGRpVpw1YXWWYoKS8E8EVV/faE924F8AlVfUBV7wTwGQBHd7lxDII4xxuE8hgI2SjXspPDzRQDIXZ4anc87+euWbjBjTU2SJdYJomoruX0m0jrXoHJXWEA4BIAzxCR/URkBcDTANzY2ZaBQZAk8CKhPE83JF3ItewwEOKP57Lqqd2xvJ+t1VsLgZAYUhsgdc1RMMnaVLmW24sc9et0gfBT/Ct5WNjuIDSHiGwF8DwAHxlZdoaInAEAqnojgI8DuB7AFwCcp6pf7nIbOSZIIoYnohT6V4ZmoS+sJan0y60qh/FB2FeZKG2xxgahciyMH5OiOtdxuV7rJGULgAdjbwSVoaoPAHjE2LJzx37+fQC/3+V2jWImSGIYlS/H05PZLuRabqw9WQ4hpYwQz+XUU5tjeT9bq7PMBgnPcnmkZiwfW2ttTdaqZnXkngUyHBg11CsRDIIkyPJJxRJPNyVdyLXc8ELHF8/llG0OhZDD2CCh5dolhtrh4mHDthbWUeYGOPZN8pbI309uMAiSKJ4ky+EwAGHhAAAgAElEQVRNyUa5lpvUAyEuLtAqyLWcdsnyPrZWX5kNEp7l8jiP5fLBcUH86fc6Op+3FcyIHRQBDNdAiolBkITxxFQOAyEb5VpurN1YtS21QIhXntoby21B6vWViNLDdiswAwEX8oNBkMStYsX0hawVa1hydXMSWq5lJvULlJQCIZ7LKNua9MR+2s8uMc2xS0wcdf+WOu2oh/22usi8hbkY7KAWMAiSCQ8NvwW8OVmXa5lhIMSPXMtolyzv49TrqgfsElNO7CAZUTAcg8OeBQyOS6hXIhgEyYjnC4guMRCyjmWGrPNaRj21M173cddi3+gyG6Q5T9kgbeG4INMx0EqULgZBMpPqiaptnm5QQsuxzKR+4ZNSNohnbGeaS72uetBlNggRZYTdXiggBkEylONNbR28QVmXY5lJ/eYqpUCI5/LppZ2xvI8t1VVmg4RluRzO03bZ8Lwv2mKp/bRyTu17Chx42lZKDoMgmeKAqeVYOsHGlmN5sXRzFYKVi7Y25Fg+u8Z9TNOklA3CLjHd67JtYTs2gYUiz4AIdWy/2BtAca1iBStYjb0Zpq1hCUtYi70ZJuRYXvZgBcsJ/819LKGXSPn2Wj7ZxjRnqZ6uYhkr2BPt+/vooYd+tO8PzWs9Tx2PSzmW2ipK1AIYVCqBmSDEqHgJsZ+SWJJjeWFGCIXmpY3Jsf4TtYVdYqiMedPk9ns1zxfb6v1aqyxknRCBQRAq8EQ6n5eblC7kWF4YCPEhx7JJA5bqaI5jg6Q0XW6OXWJoMkvtChG1h0EQeghvHuZjIGRdjuWFF0M+eC2bXtoXr/uXiKaL3f7UbVdibzcR+cQgCG3AAVPnW8MST7qFHMtKyoGQVLJBAL9l00vbYnX/WqqfzAahLliqi5a2JYaUzqFTcawJSgSDIDRR7ieyMrzcrISWY1mxdKPVtiwu4ihpKddPWue1S0zs4Bjled1Si/WAh/XtI9M4OwxNxZG+5+OsDgM5lpWUR3hPZcYYr+XSS7vidf92KceZYvZgGcsR/2YioqxxdphSmAlCMzFaPh8zQgZyLCspP3FOJSPEa7n00q5Y3b+W6iaf/IfDbJDh+trZD7HbnVzak9DtUz/2DXDT79/SylYQzcQgCM3FcULmi33hYEWO5cTSzVbbGAiJi+0KtYFjg1CXYrS3KbaV86bJJaJmGASh0rzeSHQlxZNwHSwnZBHLZThW962lACWzQYioTf0erzmJmggWBBGRC0TkDhH58siy3xSR20TkuuL1opH3zhaR3SLyTyLygpHlJxXLdovIW0aWHyEi1xTLPyQiS8XyXvHz7uL9x4T6G3Nk9WLXCgZCBnIrJ5ZuttqWSjaIV17aFKt1PuW6WUWMbJCusEtMu7y0OU2FKjfmz5nbpixvUszndV/pontO7C5A5E7ITJD3AzhpwvJ3q+oxxesyABCRxwN4OYAnFL/zXhFZFJFFAH8C4IUAHg/gFcVnAeB3i3X9EIDvAjitWH4agO8Wy99dfI5aZPVi14pcLiDmya2cpHyzZf6iriSvZZJtShqs3vSGwi4x3fLavo1L5e8gikYwCGqFeiUiWBBEVT8D4O6SHz8ZwF+qal9Vvw5gN4CnFq/dqnqLqq4B+EsAJ4uIAPhxABcXv38hgBePrOvC4v8XAzix+Dy1iCep2dawxBsX5FdOGAixL7cy2SWr+zblelkFs0GoKzweRGRdjDFBXi8i1xfdZQ4olh0K4Jsjn7m1WDZt+SMAfE9Vvz+2fMO6ivfvKT6/iYicLiK7RGTXvu+UjdfQEAdMnY+BkPwuhlK+4WIgJB62JWlgNohPuXWJ8Sh0G+lthhga2D7SVYd7nEZ1HQQ5B8APAjgGwO0A/qDj799AVXeq6vGqejwOOijmprjm8YaiS7x5ya+MpHxxk0ogxCMPbYnVup5ynawi5WwQSmeqXCKi0DoNgqjqt1V1r6ruA/A+DLq7AMBtAA4f+ehhxbJpy+8CsL+I7De2fMO6ivcfXnx+rtU1RuTrsnrhawUvKPIrIynfdKUQCMmtPHaJ+3a23J7+d5UN4nWAVIqHbRVRvjoNgojIo0Z+/L8ADGeOuRTAy4uZXY4AcCSALwD4BwBHFjPBLGEweOqlqqoAPgXgZcXvnwrgkpF1nVr8/2UA/q74fCmra8sMhtTEk8lsDITkV0ZSDoSkwGN5ZDtSH+vjALNBbEk1KNakffXYNo9q60HB6mL9stFva7YUzrrizyIGswCFeiUi5BS5HwTweQBHicitInIagN8TkRtE5HoAzwHwXwFAVb8C4K8AfBXAxwGcWWSMfB/A6wF8AsCNAP6q+CwAvBnAm0RkNwZjfpxfLD8fwCOK5W8C8NC0ulUwEFIPxwmZjTcw/i9uqkr1xiuFbBDAZ3n00I5Y3a9W6mOqN77TpJIN4kHOXWI8bnMT/V6kv5eBEUrAfvM/Uo+qvmLC4vMnLBt+/rcB/PaE5ZcBuGzC8luw3p1mdPmDAH6q0sZOsbq2jJWlPW2sKjurWMEKVmNvhklrWMIS1mJvRlS5lY89WMFygn9vH0voJVCWPZZHD+2Ix/2aiz566KEfezPcWUMPS9xv2Ur1XB7VVgAPtPg5opJizA7jCrvH1McnMtPl9rRiktzKh5Un0G1LJSOE8mGlLjIbhIZyKwtERLExCFISAyH15HajW8UalrIPhuTWfcrKzVfbUgiEeCyHHtoPj/u1SzFvflMdG4Rlzs4+8DAuSMx9Fe2aIPa4Dmk2PeRMsO4wKRoGQthFpprhCYZp0ZN5SGsPLae0+VTTaVPoGuOxHHpoPyzu11TrIYWXU5cYD+0LtagHZFK0k6YLLQ6MmzBmgtTArJB6rDyZsMjDE93QciofzAixK6dymDsr9TCnbBAOkDodu8S0g9dTjvHGnTrEIEhNDITU4/HCpCs8cedVPqzcgJF/HtqOnOo2pW+N+fyl5Vr3LUyTG1WogMaWQOul7DAI0gAHTa0n1xNiGR5uZkLLqXykGAhhNkgcHtoOi/vVSh1kNgi1LYWpctlmOBIqOMHsEAqEQZAWMBBSXW4DYlbh4WYmtJzKRooXVAyExMG2g2idxzrMLjFxeCwrQ/3e9Haf40IQTceBUVuyurbMAVNrsDhgngUcjIxlwzsOlEqTWNynVgZJXcUyVhDnOqKPHnodjoi4B8tYjvS3tiWnAVK94TUU5WzfgqDfe1jAb0ijbjETpEXsHlOP5wh8SJxCN5+ykWI2CMCMkBg8tBkW92mqdTB3Fstal6z8/Va2w6Js2p62s1KY5ZIFEVkUka+FWDeDIAEwEFIdT5DTebipCSmXspHqhVAKgRBvcm8zPOPYIGSxSwzHBcmc9YADxylOlqruBfBPIvLottfNIEggzAqpjuOETJf7TU0u5YKBEJs8lj/rbYbFfZpq/ctdyLLGWWLyVLat8H7um8l6YIRScgCAr4jIlSJy6fDVdKUcEyQwjhVSncU+4xbk3sc1l3JhZXyCtnkfIySX8tcl7tPJODYItYn1rJzs9tM2APfH3giiUn4jxEoZBOkAAyHVZXcyKomBkDzKRaqBEO+8lb/c24s6rNS9mIEQqibEAKkWj3/T9qTr9jOl9m91cRkrezsqDz2A4/36tg8LWF0M2Ruh23qlqleJyH8EcKSq/v8isgJgsel62R2mI+weU53FdGkLrKe5h5ZLuUgxNT+F1GBv5c96e2Fxf6ZY96roemyQLlgsZ1Qej1+GtsTeALJCRF4L4GIAf1osOhTA3zZdL4MgHWMgpBqOEzKZ9Rub0HIpEynejKUQCKF25VKfq7I4QGYIHCA1PNYx25qe6/u96efVPsfuAADsiL0BmRGR/UXkYhH5mojcKCL/aez9h4vIR0XkSyLyFRF59YzVnQngPwO4FwBU9SYABzfdRgZBImBWSHU8gW+W+xS6uZQJBkLs8Vb2cm4n6kqx3lXBbJBqQgyQmksQjIiS9EcAPq6qPwLgaAA3jr1/JoCvqurRAJ4N4A9EZNrFSl9VH+qDIyL7AdCmG8ggSEQMhFTj7cajKznf4ORSJlK8IWMgpFvW2wlv+7MrudwIMxvEh6btiPV6XmX7OEMM0WQi8nAAzwJwPgCo6pqqfm/sYwpgu4gIBsP03g3g+1NWeZWI/BqAZRF5HoC/BvDRptvJgVEj46Cp1QxPUJ4GJ+xCSgOAVeVtsMq6rAzY2CbOGNMt6+2Etf2ZYp2rouuZYroQsoyFGCC1TdbqVxest3lEIezDQuCHZ/ccJCK7RhbsVNWdIz8fAeA7AP5MRI4GcC2As1T1gZHP/DGASwH8G4DtAH5aVfdN+cK3ADgNwA0AfgHAZQDOa/pXMBPEAHaPqc7604QYrD/pDSmX8sCMEHtyKXu5slDnmA2Sr1yOfRlsax0YH8y07HgkHLfEmztV9fiR186x9/cDcCyAc1T1KQAewCCQMeoFAK4D8AMAjgHwxyIycegWVd2nqu9T1Z9S1ZcV/2d3mJQwEFINT4ibMRCSPgs3ZW3zHgjxxHobkUs99iLFsUGomdS7xFgVdspTolbdCuBWVb2m+PliDIIio14N4CM6sBvA1wH8yKSVicgNInL92Ot/i8i7ReQRdTeSQRBjmBVSDU+mm1m/yQkpl9mEUgyEeOatzFlvI6ztTwv1LZeMgC6yQXIeINVa3aLItlX4bNvZGoyvJktVvwXgmyJyVLHoRABfHfvYN4rlEJFDABwF4JYpq7wcwMcAvLJ4fRTALgDfAvD+utvJMUGM4lgh5XGckM2GNzm59oXNoe9zauMVcHyQbrGvfDUW6tsqlrGC7q8LUhwbhPJRta2r0paXbRfKnN8stDE52B57A/LxBgAfKGZ8uQXAq0XkDABQ1XMBvB3A+0XkBgAC4M2qeueUdT1XVUczSW4QkS+q6rEi8rN1N5BBEMMYCKnG201IF3K+0cmhPKR20cRACA1xX+ZrD5axHDjYw/LVTKxrCx636fq9JfT6fs+flBZVvQ7A8WOLzx15/98APL/k6hZF5Kmq+gUAEJEfBbBYvDdtRpm5GAQxbtg1hsGQcniC3IyBkLTLAwMhtngqc9bbBmv70kJdYzaIfSFmiWnzuFuoVxa2ISf9rUDvgfmfe0gPKFWEt2Iw5CWZopDUxlp7DYALRGQbBlkj9wJ4jYhsBfCOuitlEMQJZoWUx+4xm1m/2Qkph4stCzdnbWIgpDs5tw1kVxfZIEREZJ+q/gOAJ4nIw4uf7xl5+6/qrpdBEEeYFVKNpxuRLuR8s5NDWWAghOqy3DZYq7sW6hmzQdoRsmyFyAah+iy3cVkpkznC7BIaIyJvGvsZAO4BcG3R7aYWzg7jEGePKY8joW+0hiXzM0OEkkNZsDCLRZs8p3PmUN66Ym1fplbPrOpiphhPrM0SE+taoov2wFqbM8RpcilTxwM4A8ChxesXAJwE4H0i8qt1V8ogiFMMhJRn9WQWEwMh6UrtBo2BkG7k2iZ4FWvK3H5i81p6qqOpSWXflz3nljmXpXb+7kTbU/eSRYcBOFZVf1lVfxnAcQAOBvAsAK+qu1J2h3GM3WPK4zghm+WaHmotvT4ECyn7bfLcNcZTebPcJljbjxbqWKxuMVQOu8QQxfWwrcCeDKvgPiykFlA7GBuH6v13AIeo6h4RqX2EmQmSAGaFlJfKk4e25Pr0N4dykNgJkBkhHbHcJljbj6nVsbK6zAbpokuMtXI1C7vE0Cz9Xo3jsa397TCBGSIp+QCAa0TkbSLyNgB/D+Avitlhvlp3pQyCJGJ1bZnBkJI8XfB0IdeLmBzKQa43aUS5iNUthspZS6z7kBV1zt+5XuskYevYv5QVVX07gNMBfK94naGqv6WqD6jqK+uul0GQxDAQUs4qVrK4CS4r14uDHMpASoEQZoN0w3J7YG0/plS/qmA2CLXB8n63vG119NsIIHgJQmyJvQHUBhHZUfx7IIBbAPx58bqlWNYIgyAJYlZIeamd5JrIdeaYHMpASjdqDIR0w3Jb4Gk/doHZIHlhlxh7UjrHNhY7ADEhULOj+62gdvxF8e+1AHaNvIY/N8KBURO2urbMQVNLsDbgXmyWB0cMJYeBcy0M5NgWDpTaDcttgaX9mFLdqqKPHnodDfy5B8tYdjoILAdIpaE2zl2ri8tY2dtBXegBrRTbrQAeaGE91r7LsH1YSOJhgar+hIgIgB9T1W+0vX5mgiSOWSHlsHvMRrk+2Um9DKT0tIoZIWRJ7LrFbJDmPNXLlI533f2e6rggsdsSF2Jnm1BnVFUBfCzEuhkEyQQDIeV4uggKzcPFQgipl4GULrAYCAnPcjvgZR92JcaNcWpjg4TCAVIpWV7GCSHPvigiP9r2ShkEyQgDIeXwwnqd5RugkFIvAwyEUBWW2wFLdTWlepUrS+WpKxwXZLocywORQU8D8HkRuVlErheRG0Tk+qYr5ZggmRkGQjhWyGw5jBFR1vDixurYAKFYGnMghJTGMfA6RoinMmZ5fBBLYterVSxjpeOxMzg2SBwxjjVNF7vuD/V7S+j1nbTV88Yd2QLgwY62hSx7QYiVMhMkU8wKKYdPAdal+qRnltSPf0pPrr1mhKRexrrAfRhfl91iQgtVntglZrouxwWhCbbF3gBqk0IemvExxCuC/66q/zr6AvDfm66UQZCMcdDUcniSXcdASHoYCInPSxmzXP8t7cPYdSqlQTMn8Tw2iFU5dYmJvZ1ez1PBcWwRmu4Joz+IyCKA45qudG4QRETeICIHNP0isouBkPksXWDHFvsCIobUj3/sm7Y2eb3A9FLGcqz/VE5K2SChtJ0NknrAy4IYbfO8c/LqYr3j3rcQaLCwDeSCiJwtIvcBeLKI3Fu87gNwB4BLmq6/TCbIIQD+QUT+SkROKubrpcQwK2Q+TqO7LmJKXDSpH/uUAiFeeSljVuu+pf0Xuz6lfnMcOhvEUlnKBfc5EY1S1Xeo6nYAv6+qO4rXdlV9hKqe3XT9c4MgqvrrAI4EcD6AVwG4SUR+R0R+sOmXkz0MhMzHE/U6qzdDoaR+7GPfuLXFazYINWepjsauT6lPmUvt8tolhnW+Y8zkoI61EfCYpNTsMKqqIvItAN8C8H0ABwC4WESuUNVfDbFhFA9nkJnP06wOoeU2a0TqMwdZGeG+Kc4YE1Zu9Z7sCT1TTKi6uIYellqcTYezxFTH9qukebO3xLYVwAOxN8KefVgwFRy0qsyYIGeJyLUAfg/A3wN4kqr+IgYDkrw08PZRRMwKmY3dY9bllhEC2Hr61LZUnmZ5zQjxUras1ntL+y92XWI2CBER0WZlxgQ5EMBLVPUFqvrXqvrvAKCq+wD8RNCto+g4Vsh8li64Y7J6QxRSysc+9s1bWxgICctqvbe0/1KpSxZ5HRvE6gCpsetN7O+fpu3tCn1e6vcit8tbGv4+u9zQGBE5WkReX7yObmOdU4MgInKgiBwI4I8A3Df8eWQ5VPXGGb9/gYjcISJfHln2+yLyNRG5XkT+RkT2L5Y/RkT2iMh1xevckd85TkRuEJHdIvKe4cCsxXZcISI3Ff8eUCyX4nO7i+85tulOImaFzMOskAEOmJqWVG7eGAgJy2qd97L/QmM2CHUp93FB2pLK+ZeoKRE5C8AHABxcvP6niLyh6XpnZYJcC2BX8bp27LWrxLrfD+CksWVXAHiiqj4ZwD8DGB3o5GZVPaZ4nTGy/BwAr8VgcNYjR9b5FgBXquqRAK4sfgaAF4589vTi96kFDITMl+KJuA6rN0WhpHzcU7kQYyCEYkqlHlnkNRvEqlz+Xu/XKXWnyQ3CQuYG464pOw3A01T1rar6VgAnYBAbaGTqwKiqekSTFavqZ0TkMWPLPjny49UAXjZrHSLyKAA7VPXq4ueLALwYwOUATgbw7OKjFwL4NIA3F8svUlUFcLWI7C8ij1LV25v8PTTAQVPn8zKwYWi5DTyW8nHnYKlxeShbVuu7pX0Xsx7FGDyzjx56pkdVjIsDpKbJ+vmyvxXoTRpMdBuA+wN9KQcw7VSCA6MKgL0jP+8tljVSZkwQiMhLRORdIvIHIvLipl9a+HkMghlDR4jIP4rIVSLyzGLZoQBuHfnMrcUyADhkJLDxLQCHjPzON6f8DrWEWSGzsXvMgPcnLVWlfMxTeZLtNSPEA6v1PeV6WUWMbjFdCZ0NQtU0aQtYX4lozJ8BuEZEflNEfhODRIoLmq60zOww7wVwBoAbAHwZwBki8idNvlRE/h8Mptr9QLHodgCPVtWnAHgTgL8QkR1l11dkfWiN7ThdRHaJyK59d95V9dezx0FT5+PJPL9xQlI+5gyExOOlXOVU1+tIpQ6VlcrYIF4GSG2Ll/ZmVOht9jY4Kg0sj1Sx7fE2gxpQ1XcBeDWAu4vXq1X13U3XO7U7zIgfB/C4ItAAEbkQwFfqfqGIvAqDWWVOHK5TVfsoZqJW1WtF5GYAPwzgNgCHjfz6YcUyAPj2sJtL0W3mjmL5bQAOn/I7G6jqTgA7AWDhKU/RtQd7WNrC1M2qVteW2T1mBkvp2DFZTZcPYXixlOJxt57qW5bHrjFsS+qztO9y6xbTlT1YxnKif1tZKR9fIsqTiPy5qv4cgC9OWFZbme4wuwE8euTnw4tllYnISQB+FcBPqurqyPJHishi8f/HYjCo6S1Fd5d7ReSEYlaYUwBcUvzapQBOLf5/6tjyU4pZYk4AcE+V8UDWHrQZlbeOWSGzsXvMQG5PiVM95qk8zfb4JM5DmbJazz3suxQxGyRPHrrEWG2rhpqca6NPk0vUnieM/lDEDI5rutIyQZDtAG4UkU+LyKcBfBXADhG5VEQunfZLIvJBAJ8HcJSI3CoipwH442J9V4xNhfssANeLyHUALgZwhqreXbz3OgDnYRB4uRnr44i8E8DzROQmAM8tfgaAywDcUnz+fcXvV7L2YI/BkJoYCJmNF1H2LzraluoxZyAkHg9lymo9t7LvYtaflKfM9Tg2SNtdYto6vlbqShVWtrmr+t3JDDGTiqeF2WBoKoU81BU9xKsrInK2iNwH4Mkicm/xug+D3h+XzPn1ucp0h3lrnRWr6ismLD5/ymc/DODDU97bBeCJE5bfBeDECcsVwJmVNnaKYSCEXWSq4Qwys1lKy44lp64xQLrHnF1j4vFQpnKr556w20Q9HuodhcPjH0APKDVJEmeYyY6qvgPAO0TkHap6dtvrn5sJoqpXAfgnAA8HsAPAP6nqVcNX2xtkEbNC6mFWyHTsHsMBU1PBjBCaxWIdt1IXU6k7ZTEbZDqrA6Q2ZbH+E5EvIQIgQLnZYV4D4AsAXgLgZQCuFpGfD7ExlrGLTD0cK2Q2KxfjMeV0kZTq8c7tZs6KVMtTF6zsu9y6xaTAStmZJYUuMTmMCxIr+N6P3Z0l9vcTodyYIL8C4Cmq+ipVPRWDgUjeHHaz7GIgpB4GQqbzcEEVGgMh/qUQCPGYDeKhPOVUv2k2ZoNQaB7aRLO2xd4Aou6UCYLcBeC+kZ/vK5Zli1kh9TArZDp2j8nrRinVY81ASBweypPF+m1lvzEbxJ8QZSfVLjG5aqteuz2vbqnxO2UyRJhFkiURWRSRHxCRRw9fTddZZmDU3QCuEZFLACiAkzGYyeVNAKCq72q6EV5x4NR6VteWOWjqFLkPujW8UcphMMXhRXRqxzuFwVI5UGoYFgdKtbLfYtabrgdJ7aOHXqmREJvZg2UsZzz4a1vHtWkdaVLvrdTPURa3aZp+bwm9fkdtbqiBS7cAeDDAehO2DwtmgvxtEJE3AHgbgG8D2FcsVgBPbrLeMkGQm4vX0HBKmu1Nvjglaw/2GAipiDPITJfqzXEVFm+WQvF0QVUWAyFxpFiWusD9RlasoYelDgJEtJHna47VxWWs7OW1NCXtLABHFTPDtmZuEERV/982vzBVzAqph1kh0+V+Ye75oqSqFI81AyFxWC9LOdXrqpgN0r6Q2SDW6xqQ71TIHo7NkMfzjAnMEMnJNwHc0/ZK5wZBRORTGKScbKCqP972xqSAwZDqmBUynacTeQi5dY9J7VgzEBKH9bJkMRBiZZ+lUGeoGYvZIDG7xJABPaBxkQzVXYZycAuAT4vIxzBSEpsOyVGmO8x/G/n/FgAvBfD9Jl+aA3aRqY5ZIZOxe0w+F1BWbsTaNBzUzfONncdAiHUW63SK9a8KZoNUl3uZ6YLnfcygZkcYYEndN4rXUvFqRZnuMNeOLfp7EflCWxuQMmaFVMeskOk8Xwi0weJNUwipHmfvF4PeAiEeylEudboqdouhNuXaJaaqKu2Rh/Z1nv5WoNckcMDAg1mDgVHTmflrODSHiGwrfr6/jfXOnSJXRA4ceR0kIi8A8PA2vjwXnFK3Ok6lO1lKoz3XYXGazRBSnTLZ7VR/BW/T56ZYhkKzss+81xVr9gS8Ichlutymf2fX528rdbkNnbYH27r7qpk4Fa5rIrK/iFwsIl8TkRtF5D+NvS8i8h4R2S0i14vIsTPW9UQR+UcAXwHwFRG5VkSe0HQby3SHuRaDMUEEg24wXwdwWtMvzhG7yFTDrJDJcu8ew3FCfGNGSLeslyGL2SDW91lozAYha3Kvk9TcMoB7Y29EXv4IwMdV9WUisgRsiuS9EMCRxetpAM4p/p1kJ4A3qeqnAEBEng3gfQCe3mQD52aCqOoRqvrY4t8jVfX5qvrZJl+aM2aFVLe6tszMkAlSespRR05ZIanx/pSbGSHtsliXLewz7/XEmpyzQVJKjU9R03PK6uL049vv2WtfKW0i8nAAzwJwPgCo6pqqfm/sYycDuEgHrgawv4g8asoqtw4DIMX6Po0WcoWmBkFE5EdF5D+M/HyKiFxSpK4c2PSLc8dgSHUMhGyWareJsizePIWQ4jH2foPHQEi7cqnLVcWqJ13fNPcNdv+gzbx1iamqyvaV3Rfez3VEExwkIrtGXqePvX8EgO8A+DMR+UcROU9ExoMWh2Iw9e3QrcWySW4Rkd8QkccUr1/HYMaYRmZlgvwpMMEmOIoAACAASURBVMhRFZFnAXgngIswmKd3Z9MvpgEGQqphVshk1m9wQrJ+UdWWFI+x94tDBkLaZa0uW99foaWYPcBsEL/q7N/c6zDlaR8WsIZesBeAO1X1+JHXeFxgPwDHAjhHVZ+CwRC6b2nwJ/08gEcC+EjxemSxrJFZQZBFVb27+P9PA9ipqh9W1d8A8ENNv5jWMSukOgZCNsv5ZL+GJXM3UCGkeIwZCOlWimUoJAv7y3sdKYvZIETTuWgHxp/1byn5e6z6qbkVwK2qek3x88UYBEVG3Qbg8JGfDyuWbaKq31XVN6rqscXrLFX9btONnBkEEZHhwKknAvi7kffKDKhKFTEYUg2zQjZj9xhfN6R1pHiMXVzczeAtEGKZxTpsob7l0i2mCyGzQXKQepcYmqLt2xPO/pIsVf0WgG+KyFHFohMBfHXsY5cCOKWYJeYEAPeo6u2jHxCRPyz+/aiIXDr+arqds4IZHwRwlYjcCWAPgP9dbMgPYdAlhgIZBkI4k0w5q2vLnEFmTM4jqVucbSKE1I4xZ43pjvWyk0sd9qLL2WK8zxQTom6toYellvZJ1zP/WFD1mMRqf2KcQ/pbgd4DnX5ldPFD2tl4A4APFDPD3ALg1SJyBgCo6rkALgPwIgC7AawCePWEdfx58e//CLGBU4MgqvrbInIlgEcB+KSqavHWAgZ/GAXGKXXL43S6m+U8lW4u0+hav5mtioGQ7lgvO9YCIRb2l/f6UVYXgZA9WMZyZsGANsWqDxbq4aiy29NF3V1dXMbKXpZpskFVrwNw/Njic0feVwBnzlnHtcV/j1HVPxp9T0TOAnBVk22c2a2lmLJmfNk/N/lCqoZZIdUwK2QzaxcNXbJ2IxVCasfX+40eAyHtsVZ/LeyvWPUjxwyCupgNMp+1up26fm8JvX6F/b0NwP0lPrcVgyEvyZR9WDDRjbNFpwL4o7Flr5qwrBKO7eEEgyHlMStks9yzQlK/2LJwc9YmBkK6Y73sWKu/1vdXKpgNQpSgMkETBlaoICKvAPAzAI4YGwNkO4C7J/9WeQyCOMMuMuUxK2SzXC/grd1IhZDasWUgpDuplZ3UMRvEvhzqlKcuMV7GBZnH+3mRqKLPAbgdwEEA/mBk+X0Arm+68lmzwzxERP6jiDy3+P+yiGxv+sVUH2eRKY8zyGyWWIpcaTlMo5vazDGcNaY7lsuNtXprYV/lMFtMF1PmepopZq3F/WFh1h9r9bouC+1B1jjLTLJU9V9V9dMAXgngGlW9SlWvAnAjBlPqNjI3CCIir8Vgft8/LRYdBuBvm34xNcdgSHkMhmyU2s1yFalceM2S0rHdgxXXwRAGQtphrd5a3ldkA8sIjSpzHvN0vnCBAZJU/BWAfSM/7wXw101XWqY7zJkAngrgGgBQ1ZtE5OCmX0ztYReZ8thFZqMcUnYnsZrq2qbUjq3nNGB2jWmHtXobe1/l0C2GY4NsZG2A1Nh1gDaqM0NMstPkbgHwYOyNiEMhrrLcSthPVR86+avqWjH1biNlusP0R79YRPYDoDM+TxEwK6Q8ZoVslGtWSC7dY1LCjJBuWC43qdfZqjzXibK66BYTiuW6ZEHd+lxnv1b9HbY1hmwp/i2b2cEMkNR8R0R+cviDiJwM4M6mKy0TBLlKRH4NwLKIPA+D9JOPNv1iCoPBkPIYCNko14u11C90Ujuunm/6PAVCqBwL9StGnbAwpkSbPD01bXNsEGqHhXZgnn6vhfNPmaIXOwAR+/sphDMA/JqIfENEvgngzQB+oelKywRB3gLgOwBuKL7wMgC/3vSLKSwGQ8phVshGOWeFpCy148pASHiWy4u1+mp5X4WU2iCpoVguH20cQ8t/nzVtnLs6O/9ta2k9W+Z/pDVTmontXW4DtU5Vb1bVEwA8HsDjVPXpqrq76XrLjAnyYgAXqer7mn4ZdY/jhZTDsUI2yrGf7/DGytKYA21L6bhyjJDwLJcXjg+ykef6YEWuY4PEVrcudzFVbgxezg9RbQWQ4jgmtIGI/Kyq/k8RedPYcgCAqr6ryfrLBEH+C4B3i8hnAHwIwMdV9ftNvpS6NcwIYTBktmFGCIMhAx4uFkKwdnPVtpSOq+cbPy8XupbLS+p1taoY9SG1QVJDsVyPujyG3rCNKYEBCXP2YcF19tyIYeem7SFWPjcIoqqvFpGHAXghgFcA+BMRuUJVXxNigygcBkPKYTBk3TDN1erFWyipX/hYviCvioGQ8CyXF0t11fJ+Cimlm2hP2SCW5Fr2iSgcVf3T4r/vVdXvtL3+MmOCQFX/HcDlAP4SwLUYdJEhpzheSDkcK2Rdjn1+U589JqVjyjFCwrNcXizV09j7yXNdKMPz0822y0ZKA6R2OUtMKFa2ZXXR0bXrvEFMOcgpDfy9iHxSRE4TkQPaWuncIIiIvFBE3g/gJgAvBXAegP/Q1gZQPAyEzMeBU9elNrhmWZZusNqW0jH1fPPHQEhaYu+n1GeLCR0I8TRTTFtyGiA19nZaPFf1LQQbeEtCU6jqD2MwKcsTAFwrIv9LRH626XrLZIKcAuBvARylqq9S1cs4Jkg6mBVSDgMh62JfQMSQciAESOeYWry4LIuBkGZSr6MepDZtbgjMBvEnRtsy73xQ91zXyjS5TVkIuJA7qvoFVX0TgKcCuBvAhU3XOTcIoqqvUNW/VVUOJJEwBkPmY1bIupQyCMpK/SYrleO5BytugyEMhDRjqY7G3kde60BZzAZpX+wglqX6S0R2iMgOETlVRC4H8DkAt2MQDGlk6sCoIvJZVX2GiNwHQEffAqCquqPpl5M9HDx1Pg6cui63wdBSn0Y3pePpdcBUDpbaDAdKXZf6bDE0YGm63BhlPnY9G2VpW4LpAUaKG02xDwvRg5ot+xIGvVJ+S1U/39ZKpwZBVPUZxb9BpqUh29Ye7DEQMsfq2jIDIchzBhlLN1ptS+kijoGQsKyWFUv10+o+SkHoKXNDzRTDMhEfj0FJ2wDcH3sjZtgC4MHYG0EdeKyq6vyPVVNmYNQ/L7OM0sMuMvOxi8y62OnfXUs5dTel7k5euwWwa0wzKdfPKlIfJDW03LrFxD52Vutt29sVul5GnyGm6bgfHDeENjpSRHYWM8T83fDVdKVTM0FGPGH0BxHZD8BxTb+Y/GAXmfmYFTKQW1YIu8f4wIyQPFnJCIldj1LuFhM6GySUtssEu8Skca4axfaf6CF/DeBcDGao3dvWSqdmgojI2cV4IE8WkXuL130Avg3gkrY2gPxgZshszApZZ/XpcChWn161IZVjyYyQcFIpIyHF3kdey38ZHCS1XbGzQboSqk52VdfbrtONpsm1kLlhYRsolO+r6jnFDDHXDl9NVzprTJB3AHiHiLxDVc9u+kWUDo4XMhsHTh1I8cnMLClnhaRyLJkREo7VMmIlGwSwu49C4SCps6WcDdKEpTqbon5vCb1+x/uXY3d0ah8WUgt8f1REXgfgbzAyLK+q3t1kpXPHBAHwBRF5+PAHEdlfRF7c5EvJP2aFzMeskLTGligr1ayQVI6l1wsDZoTUZ6lOxtxHKY8PwmwQW2KU89DfaakdofIexgyRFJwK4FcwmB732uK1q+lKywRB3qaq9wx/UNXvAXhb0y+2RveV2RU0jsGQ2dhFZsDqzVEoKV8spXAsGQgJx2r5SLlOVuG17Keq7fqy1lIwKJcuMTGxLnZvR+wNoFpU9YgJr8c2XW+ZO/9JnykzoKo7e+5fwZ772SjVwWDIbAyGpJNJUNYalpK98UrhOO7BisuLUAZC6rNSH63un1CYDZKnJuW8q7pqvS42ae+jzxBD1BIReZiIvFFELi5erxeRhzVdb5kgyC4ReZeI/GDxehcGaSjJYjCkPgZDZss9EALYv+hom5Ubr7alchwZCAnDavmwUh/ZLSaM0IGQEJgN0h4r7Y7XwVEn2jZhmb9qRr6dg8HMtO8tXscVyxopk9HxBgC/AeBDABTAFQDObPrFHgwDIcvb8hnIrC0cPHU6Dpya51S6KQ70lspAjx4HTOVgqf7F3D8ey7wFe7CMZQ72mq1Uz+VRbQXwQInPcXDV0vZhwUxAsCU/qqpHj/z8dyLypaYrnZsJoqoPqOpbAPyYqv6oqv6aqpYprhCRC0TkDhH58siyA0XkChG5qfj3gGK5iMh7RGS3iFwvIseO/M6pxedvEpFTR5YfJyI3FL/zHhGRWd9RFzND6mFWyGzMCrHz1KYLqXaPSaWbEzNCwrBYNlKsh3V0XeaZDTKd1WyQptglZrZY551+L3IbyMFKqZq9IvKDwx9E5LEA9jZd6dwgiIg8XUS+CuDG4uejReS9Jdf/fgAnjS17C4ArVfVIAFcWPwPACwEcWbxOR5HmIiIHYjAQ69MAPBXA20aCGucAeO3I75005zsaYTCkHgZDpuNYIencRJeV6g1YCseQgZAwLJYNK/XQ4r4JyWMXi3E5jQ3i8XjlVqfa1Gdwgmz6FQCfEpFPi8hVAP4OwC83XWmZMUHeDeAFAO4CAFX9EoBnlVm5qn4GwPgcvicDuLD4/4UAXjyy/CIduBrA/iLyqOK7r1DVu1X1uxh0xzmpeG+Hql6tqgrgorF1TfqOVjAYUg+DIdMxGJLXhYuVG7C2pXAMGQgJw2LZsFIPc3wSHRqzQSi27I9nnYBKmWrLQE12VPVKDJId3ojBMB1Hqeqnmq631LywqvrNsUVNUlAOUdXbi/9/C8Ahxf8PBTD6PbcWy2Ytv3XC8lnf0SoGQ+phMGQ6BkLyyQpJuXuMdx5vDBkIqcdKHcwpEJJCtxgP2SBWBkj10CWmiq63yc0MMaGCEwx6ZE9EzgSwrKrXq+r1AFZE5HVN11smCPJNEXk6AC2mqPlvKLrGNFVkcGgb66rzHSJyuojsEpFduOs7tb+DwZB6GAiZjFkhNm+WQrF4kddUCsEsj1PoMhBSj5U6aHHfhOKxm8W4EIGQnMqAJZ73u7fzFIWnkIcetIV4RfBaVf3eQ3/foGfIa5uutEwQ5AwMZoM5FMBtAI5Bs9lhvl10ZUHx7x3F8tsAHD7yucOKZbOWHzZh+azv2EBVd6rq8ap6PB7xyAZ/0gCDIdUxK2S63IMhKdxIl8WsELu8XWAyEFJPivWvCm/lvCyP3WLalMIAqR6+r4lU694mW1peHzNEcrI4nPwEAERkEWh+0p4aBBGR3y3++xxVfaWqHqKqB6vqz6rqXQ2+81IAwxleTgVwycjyU4pZYk4AcE/RpeUTAJ4vIgcUA6I+H8AnivfuFZETih1zyti6Jn1HJxgMqY7BkOlyDoQAvi5mmkrxRiyF4+ftIpWBkHos1D92i/Ell2yQmMfKQr2sy+KxrGVb7A2YgwGR1H0cwIdE5EQRORHAB4tljczKBHlREVw4u+7KReSDAD4P4CgRuVVETgPwTgDPE5GbADy3+BkALgNwC4DdAN4H4HUAoKp3A3g7gH8oXr9VLEPxmfOK37kZwOXF8mnf0SkGQ6pjMGQyZoXklRWSmhSOHwMh7fNeJkJhIKRdzAbJ++8vq0q9S+E83XiaXBYr6s6bMZgR5heL15UAfrXpSveb8d7HAXwXwDYRuReAYDC2hmAw1MaOeStX1VdMeevECZ9VTOlmo6oXALhgwvJdAJ44Yfldk74jlmEgZHnbauQt8WMYCFna0o+8JbYMAyErS3sib0kcw4uUFaRdl4YXWEtYi7wl7VrFiutjtwcrWHa0/X0soWe8DFkrE2tYMlHvrO0X7/rooYcw1xN7sIxltHtOtnj8V7GMlQZ/Z9d/k8V9WFeXbXl/K9B7oJOvmm0rAAvbQdGp6j4A5xav1swKgvy6qv6KiFyiqie3+aW5YjCkOgZDJltdW842EAKkdXEzi5UbsjZ5P3YMhLTPWpmwUu9i7Zeuy3jTm2uabw09LAUKAnXBSp0MpWmdm/X7q4vLWNnL+rUDyKaV2YcFZlqWMKs7zOeLf+/tYkNywm4y1bGLzGbsIuO/i0UZKaTdjvN+3LzNHMOuMdWlWO+qYLeYajg2SNnft/c3hZbj30zkwawgyJKI/AyAp4vIS8ZfXW1gyhgMqYbjhUzGYEj6dSjF2WNSCGJ5C4R4CIZYYqHO5TQ+CIWV49ggVetPbuOCEFkmIn9e/HtWiPXPCoKcAeCZAPYH8F/GXj8RYmNyxWBINQyGTJZ7IMT7DXUZKV50eT9u3m4ULQdCLJYFC3XO4n4Jgdkgm+Vy7MuwUBdjstx2P2R8lpays7Zwdhea7DgR+QEAP1/MEnvg6KvpyqeOCaKqnwXwWRHZparnN/0imo9jhlTD8UI248CptsYWCCHFQVO9HzeOE9Iei2XBwngEHB+kPd4GSbXG2wCp1JJtAO5vcX0c+JTmOxeDmWAeC+BaDCZnGdJieW1TM0FE5FcBQFXPF5GfGnvvd5p8Kc3GzJBqmBmyWc5dZJgV4pP3Y8aMkPZYLAsW6lus/eKtbKemzePuvUtMnXpooUtMmXXGqGeNp8l1aHvsDeiAQh7qAhvi1dnfofoeVX0cgAtU9bGqesTIq1EABJjdHeblI/8/e+y9k5p+Mc3HYEg1DIZslmsgBLB5I9W21MYK8R7A8nazyEBINSnVtaq6LNvsFmNfF8eIqplVR1cXqx2vftnuKbzkpilE5F9E5AYRuU5Edk14/5Uicn3xmc+JyNHT1qWqvygiR4vI64vXk9vYxllBEJny/0k/U0AMhlTDYMhGzApJv+6kdnPm+Zhx5pj2eC4HoeSyT7wHQtqWWjZILuWYKHPPUdVjVPX4Ce99HcCPqeqTALwdwM5pKxGRNwL4AICDi9cHROQNTTduVhBEp/x/0s/UAQZDqmEgZKPcgyGpYyDEFgZC2mGtHFioZ+wWYx+zQcKx1iWmS5bb6lK2lPgML92zoKqfU9XvFj9eDeCwGR9/DYCnqepbVfWtAE4A8Nqm2zArCHK0iNwrIvcBeHLx/+HPT2r6xVQfgyHlMStks1yDITlkhbB7jC2ebhotX1xbKwMW6lgOgRBmg2zEbBCbvI8L4l6ZwArFoAA+KSLXisjpcz57GoDLZ7wvAPaO/LwXLfRKmTU7zGLTlVNYnE2mPM4ks9nq2nKWs8gML0RSHp3ewmwWbfI8m4CnmWM4a0x5FuqYtX0SQhezxYQSYqaYHI45UWu2IMsZaPZhIXRA7aCxcT52qup4d5ZnqOptInIwgCtE5Guq+pnxFYnIczAIgjxjxvf9GYBrRORvip9fDKDxzLWzMkHICWaGlMfMkI1yzQoB0nkKNU2KWSFeeXq6x4yQ8izUrxj7xFN5LiPXQVLbyAZJuUuMR3XqposZYoYDtVbJ+ig7uCvVcaeqHj/y2jSeh6reVvx7B4C/AfDU8c8UA5yeB+BkVb1r2pep6rsAvBrA3cXr1ar6h03/CAZBEjIMhjAgMh+DIRvlGgzx3t2iDAs3am3xfLw83TgyEFJeSvWrCnaLicdaHWjC8t9iedvqqDpDzETbSnwmdvChZ2AbMiciW0Vk+/D/AJ4P4Mtjn3k0gI8A+DlV/ed561TVLxZT5r5HVf+xje1kECRRDIaUw2DIRjkGQoD0LnbGMSvEBk8zxzAQUl7susXxQWxjNkj62hwXZJ6u2ubS0+TO02VAYsp3LfMyv2uHAPisiHwJwBcAfExVPy4iZ4jIGcVn3grgEQDeO20a3dCmjglCaeC4IeVwzJB1w0BIbuOFcKwQXzz3jfcyTgjHCCkvdt2ytj886qOHHnxcA6R0vOv+LXXqnIf95uX8ENVWZDnWhxeqeguAoycsP3fk/6/BYNaXaJgJkglmhpTDzJB1OXeRSVnsp9Zt8nysPGWEWM0KsXb8Y9et1McH8dwthtkgPllrY0ziJTMFJiKHiMixxeuQttbLTJDMMDOkHGaGrMsxMyT1rJDhzVoKWSGej5WnJ35Ws0KsPdnNMSOky3LsebaYtlkr+7mLXfeHPJ1X5mZ0MOOjln1YSCKAJyLHADgXwMMB3FYsPkxEvgfgdar6xSbrZyZIppgZUg6zQtblmhWSwolkmthPrtvk9Th5yQgB7I4T4vXYh5J6RkhozAbpXt0y63GWmNjfP4mJGWI4mClt9n4AZ6nq41T1ucXrRwD8EgbT5jbCIEjmGAyZj11k1rGLTHpSGjTV63HigKnNWTr2qdSnqroqw567XrQdCLFU7j0fl1ksBhXrtsOtzBDTVJVpbil3W1X1mvGFqno1WgibMQhCABgMKYPBkHU5BkOYFeKD5+PEQEgzlo577PpkaV+EEPqG29OUuW3JKRuEiFy4XEQ+JiI/LSJPL14/LSIfA/DxpitnEIQ2YDBkPgZD1uUaDEkVs0LiYyCkGUvHPXZdsvgEu01eAyHMBokv1D6LXefbNnGa3G2db8Z07EKTNFV9I4A/BvAcAGcXr+cA+BNVfX3T9XNgVJqIA6jOx8FT162uLXPg1IRYGeCtKa8DB3oZ2I6Dpc4Xuy6lPlAqtWsNPSw5mSbYs9D10n0d7AEshvUpJJmAnKpeDuDyEOtmJgjNNMwMYXbIdMwMGcg1K8TSU7g2pZIV4vUYeRknhBkh88WuRylnhDAbZMBSeW9yTKx2iUm5DgXBDA0KTER2Nl0HgyBUGoMhszEYMpBrMCRVsW/g2uL1GHm4EGYgZL7Y9cjSvmib10CIVbHHBumK9y4xbbe7jWaImVdkugiKMPCSHBE5cMrrEQBe1HT97A5DlbGrzGzsJjMwDITk0k0m5S4yw4s6711kLHWTqMJDavPwgtxa9xhLxzx215iueSi3Me3BMpbR3vnRUllfxTJWav5tlv6OFK0uLmNlbx7XZeTedwD8KwAZWabFzwc3XTkzQag2ZobMxsyQgdwyQ1J+4hr7aXYbPHeP8cBiVoil4x2zDqWc0u81G6TtbjFt8ZgN4q1LjKV2KWkjGSI2axvNcAuAZ6vqESOvx6rqEQC+3XTlzAQZ2ivA/T1gW95P7+tgZshszAwZyGnwVGaF2OfxaaOXJ+sWB0y1dLxjZoSkPFBqk+yDMvrooWd8tEZL5dwD7i9K0T4spBJk+0MABwD4xoT3fq/pypkJMu7+3vqLKmFmyGzMDMkzKySRE9EmzAqJgwOm1mfpWOeWEULTWR0ktWk2SIoDpJbV1nbMa+tntbNtnSfMT5NLyVLVP1HVL0157/9run5mgswyDIQwO6QSZobMxsyQPMcLSfFpE7NC4vGQFWI1IwSwkaWVU0YIs0EoBR7PFeZtBfBAi5+j5IjISyYsvgfADap6R931MhOkDGaG1MLpdWdjZkhemSEesw7KsvL0rQmPx4YZIfVZOd45ZYRwfJDpmA0y6Xe7Ki/x2oJY3726GPm6a0vcryd3TgNwHoBXFq/3AXgzgL8XkZ+ru1IGQapgV5naGAyZjsEQBkNSsIYl98EQj8eGgZD6rBxrBkLaFzoQEoLVQVK98X4eiqnRNLlt4DS3NNl+AB6nqi9V1ZcCeDwGs8Q8DYNgSO2VUh3sKlMLu8pMx24y+Q2emmJabQrTgHo7NsMbS8vdYyx2jQHsHOsU6k1ZHrpyzeOhW0xbZXsNPSw1+FtTmy637Da1Vafd1JcesKGYhOq+sgXAgwHWm5B9upDag8XDVXV0Npg7imV3i8i/110pM0GaYnZILcwMmS73zBBmhfiXSlaIN9azQvpYMpkV4vFYtynVv5/ZIFSW5zrQxeCoUTE7hIBPi8j/EpFTReRUAJcWy7YC+F7dlTII0iYGQypjMGQ6BkMYDPEuhUCIt+Pi4aKXgZDJ2C2mfSEDISHGBmmbhXINdB+Q8nTusXKMgms7mPF/2nvzcNuustzz/dLsfc7ZJ3CiCTwxAQNWwELAAKG5hVo0RQiIBIs8ELzSSYkl4HMtSgQuliKoJZeywcIrlasIlA1wES4pGmPoxUtCGkIauMAhoCREuiSQ02Qfcs5Xf8y59p57rdnPMcf4xhjv73nWc/ZZe665Zr/X/K33+wblSE68GMBfAji7fLwVwItV9aCqPnbsTClB5oAyZDCUIc1QhuQlQ1KDqRD/UISMw8J+pghxT2wixGIaZGqD1ClYOC/HEvvfvgXmh8llo9WkUVUF8EkAHwHwYQCfKJ+bBCXInLBUZjAcUaYZypA8ZEiM6YM+xP5hMLb9chh7zMsQipB6KEKISxGSwkgxYxh6Hg3ZTimcJ8FHiCGkJyLyDACfBnABgGcAuFxELpg6XzZG9QUbqQ6GTVTryb2Bai7NUxcfsqw1hZvC4kNpzA0gLTbqa8N6Uz2LDVMt7OOQjVJ9r7+PY3RKc84uYmiSGjsWzslc2Fxfw/qmgWvycqPViZy0C/heJg1Vjx07LrUvTV8F4OGq+k0AEJFTAXwIwLumzJRJEN8wHTIYJkPqyTkZkksqBLDxzbRrUkiFxIT1b9uZCKknp0SID3Iui7GSBsmRPufx1P2TfHNUkjvHLQRIyXfgwGFQgoSEMmQQlCH1UIakL0NiK8XoQ+y9QmLbJ9bLYyyOHGNh/+YiQiwfm6lg4XhmSQwhZAR/LyKXiMjzROR5AN4P4ANTZ0oJYgGmQwbBviH1UIZQhsRIzCIEiO+DsPWbTYqQVWI/R/ri49jMOQ3iilBpEAvnYkisX7sBYOXQ6DuCC0d6IS2o6ssAXATgweXjIlV9+dT5UoJYgzJkEJQhq1CG2PvQ6JrUPgwyFeIX6x+mKUJWCXV+pNAAcpmcRYiFY9l3GiQWQuybIc1Ra0eImQJHdCEDUNW/U9WXlo/3uJgnG6NahY1UB8Emqqvk3EB1IUJSbqCaauNUNk31AxumDsPCvg11frBRKlnmCNaxFqAZ7Jhjceh5M+Q9+k7r49x1ec3s3Rx1L4ADTt7SG3cLvQAe0GPHJfEFsYjcAaBuKFxBMXLupN3JJIh1WCozCCZDVmEyJO1vnWJLIXSRQiokFmLoE2IJC/s2l0RIzDAN0mcZ0v67bA3L13lCmlDVk1T1bjWPk6YKEIASJC4oQ3rDviGr5C5DUsfCokL14wAAIABJREFUB1uXxC5CYtoflj8gU4SskoMIYVnMKtb6g8TUG2TOBqk+sXyt7kWfkhr2ByGeoASJEaZDBkEZspNcZQhTIfHBVIg/LH+4tjZyjIX9ShHihthEiCssHMOppEH6bksfQ+VmCaUJGQklSOxQhvSGMmQnlCHpQhlih5j2Bctj+mNhv1KEuCGmm3FrZTGh0iCknjHXyCHNUaNiAxQkpBU2Rk2FqghhM9VW2ER1J7k2UGXz1PiIuXGqhcaafbHcNJUNU3eSQ7NUy8djF5tYx3qABqKxMLZBrbUGqTHg4jza3ADWDzpaoCFsADhY+beLdSDr0+6o8AvyHnhPgojI/UXkmsrjeyLyqyLyahG5ufL8kyuveaWI7BeRL4jIEyvPn1c+t19EXlF5/j4icnn5/DtExM7XRz5gOqQX7BuyEyZD0iX0N9YuiT0VEgtMhPQn9H5lImQ6MZXFMA1ij5TOhQWb6yOvK8uHg880RkP640QmQkgN3iWIqn5BVc9W1bMBPAzAIQCL8X7/aPE7Vf0AAIjIAwBcCODHAJwH4D+KyPEicjyAPwXwJAAPAPCscloAeF05r/8OwG0AXuBr/UzB3iG9oQzZhjIkTSzE910SswiJZT9YLo+hCNlJDiJkbnItiwnN2O3uo0Gqa9gXxBG7Qi8ASYHQPUEeD+DLqvrPLdOcD+Dtqrqpql8BsB/AI8rHflW9UVWPAHg7gPNFRAA8DsC7yte/FcDTZluDWKAM6QVlyDaUIWkS0014F0yF+MGyCLEkQ0Lv01jPhb7E3B8k9SapqaZBQp/TUbA39AIQMo7QEuRCAH9b+f9LRORaEXmziJxcPnc6gK9VprmpfK7p+R8EcLuq3rX0/Aoi8kIRuVJErsRt35q+NjHAdEgvKEO2WciQ3IQIZUg8xHrzF9M+sCpCAFupkND7M8S5kGIpwBxYLosJjc80yFxYWRZL18NOuhIdeX3sJJ4JJkHKPh1PBfCfy6f+DMCPADgbwC0A/mDuZVDVi1T1HFU9ByefOvfb2YMypBP2DdkJZUh6WPngNhWmQubH8g2opQ/+ofcnRcg0ciyLySkNEvrvhIuSmLHnQNPrvI4Q09Sfg307iGdCjg7zJABXq+o3AGDxLwCIyH8C8L7yvzcDuFfldWeUz6Hh+e8A2CciJ5RpkOr0pA6OLNMLjiqzTY4jyqQ8mkxKo8gsPmDGNopMLPtg8SHa4mgdlkaOCT2yRIhRY1IaMWbsqCVdWB4tJvQx63OkGEvzJ8Q5CuDO0Athn5DlMM9CpRRGRE6r/O5nAVxf/nwxgAtFZF1E7gPgLACfBnAFgLPKkWDWUJTWXKyqCuCjAC4oX/9cAO+ddU1SgumQTpgM2SbXZEiqxFSe0UXob/vGEsv2t5oKYSJkGyZCphFLfxBLZTG5p0FCn/OuqRshZtNSYsPSspDoCCJBRGQDwBMAvLvy9H8QketE5FoAjwXwvwGAqt4A4J0APgfg7wG8WFWPlimPlwC4BMDnAbyznBYAXg7gpSKyH0WPkL/wsFppwd4hnbBUZpvcZEgOJTIpfJiLtUQmlu1vWYRYkSGh92PqImRuYiqNcUHofWd1e7veLnOfl8Gvf1M/DlJuEA8EKYdR1YMo5ET1uWe3TP+7AH635vkPAPhAzfM3ohg9hriA5TKdsFSmILcymZRLZIB0YsAhSgNcEMP2Z3lMN6FLnVIujZm7LGYuXJfFHMZu7J6hfGcMR7CONc8lPzFcK4fStU6xHvuEWCH06DAkNpgOaYXJkAImQ9IhllRCF0yFzIvlVIgVQu7HlBMhLIspsNQkddr7+/lbmmtJzCzNUbuGyfWR7OgaaYaQJUI2RiUxw3RIK1URknM6hMmQdAj9bbYrYm6can3bW02FWEmEAGH3IxMh48mxUeoUUkyDuJ5/rAnF6NgF4GDx490AI3mpmTkK4EDohbAPkyALFp102U13OEyHtMJ0yHYyJJd0CJMh9mEqZD4spkLYJ6SAiZDxWO1XUcVSGiSGJqkx/h0gJBZE5HgR+YyIvK9lmqeLiIrIOT6XDaAEqYcyZBxsptoKZUgBZUgaxHAz3kXMJTLWsShCADvlMRQh82D1uGuDZTF17z1uHaxcG10tR9d82o53V9c68yPEEMv8OxSDl9QiIieV01zubYkqUIK0cScoRMZCGdIIR5UpoAyJn1iSCV3EKENi2PaHscfkTSlFCEXIWGLpD2KFGNIgQ7B+zY2Svr08KF6iQkTOAPDTAP68ZbLXAngdAt1pU4L0hUJkHEyHtEIZQhmSAjHckPchNhECxPGhnCKkGYqQ+GBZjB98pUFCXvdDvfcszVGHQKERO6eIyJWVxwtrpvljAL8O4FjdDETkoQDuparvn3NB22Bj1DFURQi7EfeHzVQbYSPVvJqoptpANYXmqTE2To1hu1scznEhQkI3TWWzVPfE2Cg11WFzQzRJnZO+x6+r4zyGptgAihFiqs0414HBu30DW01MJ02TO8cwd2PUb6tqYw8PEXkKgG+q6lUi8pia3x8H4A8BPG+2JewBkyBTYUJkHEyHNJJ7OoTJkPhJIRkSa4mMZVge00zIcybVREiMjVItlsXEmAYZSmzX+io++oIExd4pQbp5NICnishXAbwdwONE5K8qvz8JwAMBfKyc5lEALvbdHJUSxCUUIsNhuUwjlCH5jCiTsgyJndg+HMcgoChCmslJhPjA4rHWhUsRYqUsxndvEOvXwCoxnHt1zVEH47oEpprEZ3mNKVT1lap6hqqeCeBCAB9R1Z+v/P67qnqKqp5ZTnMZgKeq6pU+l5MSZC4oRIZDIVILG6nmkw5JUYbEcFPeBVMh7rF4c0oR4vc4Z6NUP7gSIaGwmAbpe+xavg5PPS84QgwZioi8RkSeGno5FlCC+IBCZDiUIbVQhlCGxApliH+sb3OL5TGbWDMhQ3JpmEoRUk+KZTFMg4zH57p4a47aBSVLEqjqx1T1KeXPv6mqF9dM8xjfKRCAEsQ/lCHDYDqkltzTIZQh8WL9xrwPMYkQwP7NgDURAthIhVCEuCVnEcI0iG2mnm/J9wVxwO70PzJucww7v4B3/UgESpBQJHgwzQ6FSC2UIekfD5Qh9mAqxC1WUyGhoQhxC0XINEKmQcZs3zmHy02hJIaQnKEEsQCFyHAoQ1agDElfiFCG2CNGGWIZipBVchk5xvqxSQpiK4tJhSjOj71L/++7q3d1T0KIayhBrEEhMgymQ1ZgqQxlSIykIENiwfq2tihCrMiQEKQmQpgGiZeU0yAh/oYMORecjBBTJVDPj7jPAOISShDLUIgMg0JkBcqQtI+FVGVIrDAV4g6Wx9RDEeIGipBpMA1iD5d9Qfo2R+UIMSRmTgi9AKQnVRHC2Fg3CxGydzPschihKkJ27z0UcEn8sxAha7vSPRYWImTP2uHAS+KGxQfsPYjzWF3cMK7hSOAl6cb6tj6MPdhtaNk2sYb1wPv1EPYE2V9HsObtmPaxjnMeW4ewG3uQxvW4iVDH4ZhtO3RZfR7rQwi1zZ2xAeCgg2lIO8cAHAi9EPZhEiRGmBDpD9MhK+SaDsmhb0hqyRDrZRtdMBXiBmupEAvlMUyEuCGmRIi1NMhUUkmDxF4SEz1taRQmVUgLlCCxQyHSHwqRHeTcO4QyJC5iliExlchY386WRAgQvjyGIsQN1o6rNqyJkFDHoI/eIDEy5liO6fgfJDXS/YhHHEEJkhIUIv2hDNkBZUiaUIbYgTLEDRZTISEJta8oQvphvT9IaCynQeZokBoSF9eqXs1Rl0eIccGQw2QDq7KEiRBSAyVIqlCI9IPpkB3kmg7JRYakIkQs36R3EZsMsQpFyE4oQqYTkwhxhYU0yFgRYnm7NuGiJMbXud63OWonc3y0apIa7JlIBsDGqDnApqr9qIoQNlTdEiE5NVKtipBUG6mm1ETVelPPNqw23lvG8ja21DR1IUJCNk0N0TSRzVL74bpR6ibWsQ43f6MOYzd2T1y2WBp2ptIg1RKbG8A6G5na4ijYGLUHTILkBhMi/WBCZAumQ9KEyZDwMBUyHZbH7ISJkOnEkghhWYytNIiVa2RUfUG6ylRYxkJmhBIkZyhE+kEhsgVlSHpQhoQnFhlieftShGwTSoT4OoatHoN9sCpCLJTF+GLocro+rkOWxIS+NgFgKQsxAyUIKaAQ6QdlCIA80yGpD7GbmgyJEcqQaVhKhYQeRjf1hqlzr5uV46gPqYgQpkHioFdzVEIigBKErEIh0g3TIVvkJkOAtNMhqcgQqzfqfYhBhAB2P/BbuoEN/c0rRch4YimLcYkLERIDoa9dsRy7zpqjDqVvGQzTI2QCbIxK2mFT1W7YUBUAdoiQXJqpLkRIik1UU2mgarmxZxuLG0nrTfmsbt/FTYCFxqmbWGPD1JmYe91ybJQ6lSn75AjWsTZiPVxvz2VCNEjtek/TzWj3go05Q6LgF9k9YBKE9OdOMCXSBRMiAPIrl0m5VIbJkLDEVCJjESupEAvlMb5hIqQd9gepZ2xZzFDmOm6sXgsXNF2Hphznm13JDR+7lE1UyUAoQRYcDb0AEUIh0g6FCID8ymUoQ2xDGTIfVrettV4hoQixfyhC2klZhPhm7jKjEA1SiQMqcuQkJtpJBUqQKgcqDzIMCpF2KEOyTYekxkKGxC5ErN6wd2FdhAB2t60lERJahviEIqQdyz1CpsA0yHSmnDvR9wUhZGYoQZo4AEqRsVCINMN0CIC80iEslbGN1Rv2NmJIhQA2v+lkKqSAImQcMYgQpkHmw9p1N9Q11ukIMX3LWNL7CEUCQwnSFwqRcVCINEMhwnRIIlCGhCEGGWJ1u1KEhBEhPo7XWEWIS6yIkBiGzA15fQomMWboCzII9u8gBuDoMGOoipC9wZYiPjjSTDMcYSar0WVSHVUmhRFlrI520kYMI8lY3K5WRpBZ3JCEGEEmxH7xMdJGjKPGWB0x5jB2Y/eE5QoxWsyc9D1+XR2DIUamGcPmBrB+sPLEmBFidmH1S9MNAAdb/k9WOQp+ad8DJkGmwrKZcTAh0gwTItmkQ1ItlWEyJAyxJEOsYeWb/dxSIXMTYyLEaqPU2MgpDdL2eivXtllgmoRMhBLENRQiw6EQaSZzIZJTuUzKMiRmIRKrDLGMxW1qpVcIRYhb5j7WYhAhLoixLMYC1q5zY6lrjjq4L8icu5FChIyAEmROmBIZzp2gFGmCQiQrGZKqEIkVizfubcSSCrG2Ta2IkFAyJEURAsy7XtZFSAr9Qca933xpEN/X1jneL3hfkC4oNsjMUIL4hEJkOBQi9WQsRJgOiRvKEL/EIkMskXsqxPcxThFSj0UREoqY0yB9YEnM/JxIqUKWYGPUUCyLEDZY7YaNVetZiJAMG6rm0kw1xUaqsTdRtdjosw3rzVMtbs85ml8OJXTTVF/7w1fzxznXyXqzVBeNUmNrkjp0+w1ZPt8NUmNgpTkqCcMx8Av3HjAJYgWmRIbBhMgqGadDgDzKZVIslWEyxC/WkyHWtidTIX4TIbE3TM0hERJbWUwq+CyJqaOuL0gnbV/wbjT8TIgnKEEswl4iw6AQWSVjIZJLuUyqMiRWIWLt5r2LGGSIJShC/EERYp+pImQsY8piLPQG6TNPSyUxfacf3BzVAHcLvQDEDJQgMUAp0h82Vl2FQiRpIcJ0iC0oQ9xhbVtaSIWEapqaYp+QmESItTTIVKw3SSUz0efQY7k78QQlSIxQiPSHQmQnFCJZCJFUoAzxh1URAtjbllZkSAgoQvqTuggJVRbjo0mq1TSI5et0MNqkSTofh8gMsDFq7LDBan/YWHUnVRGSWVPVhQhJtZlqVYSk0Ew15iaqFht+NhFD81RL2zF049RQTVNTa5gaU7PU1BqljsVHk9QYGXMsb2ItSOPlQWwAOIhCavTZ7YseI7k2aWVj1F4wCZIaTIn0g2UzO8k0IcJ0SFzE3DfEWpqhDZbI9CfXVIjP/eDjeGQiZDxTEiGWzuVl5kiDuGDse7noC9KnOermcpNTn1/ObqD+S05+8UlqoARJGfYS6Q+FyDYUIqEXZRZS6x0Suwyx/OF/AWVIfyyIkFAyxBcUIduk1OPCZ1nMnE1SXc3P0nWtD0Gao3I0GeIASpCcoBTpB4XINpkLkVShDLGBtRv5JihD+pFzKsQXFCHbuBIhodMggO3+IH2xco20cj3sRZfMoOwgMxJMgojIV0XkOhG5RkSuLJ/7ARG5VES+VP57cvm8iMifiMh+EblWRB5amc9zy+m/JCLPrTz/sHL++8vXiv+1NA6FSDcUIttkKESYDokHlsrMj3UZYoVcRYjP8pg5oQgZR6hhc4eSQhrEdUmM12tG06FG4UE8EzoJ8lhVPVtVzyn//woAH1bVswB8uPw/ADwJwFnl44UA/gwopAmA3wLwSACPAPBbC3FSTvOLldedN//qRAxTIt2wj8g2FCLJkYoMAeJNh1CGTMPS9gudCkm9PMaHCJlrXShC6rFcFtMXi9fFKYztC+INipN6jgE4POMjEUJLkGXOB/DW8ue3Anha5fm3acFlAPaJyGkAngjgUlW9VVVvA3ApgPPK391NVS9TVQXwtsq8SB8oRbqhECmgEEmKFNMhsWHpZr4NypBuLMgQ37Bhajcpi5ApWDlvlwmRBrE8/y5WmqMOhY1MiQdCShAF8A8icpWIvLB87p6qekv5878CuGf58+kAvlZ57U3lc23P31Tz/A5E5IUicqWIXInbvzV1fdKGQqQdpkQKqkIkEymSgxCJnVhLZSzdzLdBGdJNaBHiW4awPKabVEVIiLKYFNMgMZXEdDZH9TFCDFMhZCAhJchPqOpDUZS6vFhEfqr6yzLBoXMugKpepKrnqOo52HfqnG+VFkyJdEMhUpCpEEkNpkPCYulmvg3LMsQCTIXMB0WIW0KKEKtNUmNLg5CSihzZHf9HGOKQYBJEVW8u//0mgPeg6OnxjbKUBeW/3ywnvxnAvSovP6N8ru35M2qeb+YYeGM/FkqRdihECjISIjmkQ2IXIpQh82FRhljadiFlSKhUiA8oQmwNnRtChAx/n7jTIHO9topVUUfIVIJIEBHZEJGTFj8DOBfA9QAuBrAY4eW5AN5b/nwxgOeUo8Q8CsB3y7KZSwCcKyInlw1RzwVwSfm774nIo8pRYZ5TmVc/eGM/Hm63Zlg2U0AhkgQpyZCYhMjiht7KTX0TlCHt5JQK8bXd5z7mchIhoRuljiG2NMhUXJfE9MVpc9S+ZSwsd+nPMQAHZ3wkwgmB3veeAN5Tjlp7AoC/UdW/F5ErALxTRF4A4J8BPKOc/gMAngxgP4BDAJ4PAKp6q4i8FsAV5XSvUdVby59fBOAtAHYD+GD5GM/yDb2P+rYU4HZrpypCcm0EVRUhezfDLYcHqiJk995DAZfELVURsrYr3n24ECF71uJpf774UL4Hdo+nxQf1NRwJvCTbWNlui5uR3QGWYyFC1j3ul0PY42WbH8HabMfbXOtwGHucHQeHsBt7HAzjsIl1rCPMNX3sdj6CdawNWGZX22p1ObqPQV/nQ182sebserC5Aaw33TCvA7W7aAPdN9lNryVmEJFdAD6BYm+dAOBdqvpbNdM9A8CrUbS/+Kyq/pzP5QwiQVT1RgA/XvP8dwA8vuZ5BfDihnm9GcCba56/EsADJy9sE3UpB97gd0Mp0sxyMiRHKUIhEj0LIUIZ4hcrN/VtUIY04/IGeCgub3z6QBHSTIoi5DB2Y/fI5fB1rAzZVr7FRdf7tR3nPpd1c30N65sznG99xAixxiaAx6nqARE5EcAnReSD5QivAAAROQvAKwE8WlVvE5F7+F5Ia0Pkxg1LaIbDbdZM7mUzLJmJmhR6h8RcKmMZq2UyocmpV4jP8pi5mGsdUiyN8d0fZO6ymL70Of4sXHu6cHJMuv7Ss1oek+OXhobRgsVd3YnlY3mwk18E8Keqelv5mm/CM5Qgc8Ib/OFwm9WTey8RCpGoSUmIxAJlyHCsbLPQMsQn7BNSD0XIdIaKkCHbyfd1wucx1vca4LQvSB0UG1EjIseLyDUoBjm5VFUvX5rkfgDuJyL/JCKXich5vpcxVE+QPGEpyHCq24zba5uce4ksi5CEy2ZSLJmJvVymKkJiKJepfngOXfLRhLUymdxLZHz3CvG1vWMrj2FpzDbWemcA/ZfJR28QKyUxpsmprOYY5v7C9BQRubLy/4tU9aLqBKp6FMDZIrIPRR/QB6rq9ZVJTgBwFoDHoBjF9RMi8iBVvX3WJV9aABIKSpFhcHvVk3svkUz6iCyESGoyBIhfiMQgQwA7N/dNUIasErpxamq9QihCwouQsYzZvlaapLogBpmx3BektTlqlZwERRp8W1XP6TOhqt4uIh8FcB6KkWAX3ATgclX9PoCviMgXUUiRK2pmMwssh7HEcikIy0Ha4baqh2UzSZfNsFzGHiyVcQvLZFYJVSITolfI3LA0JizW+4PMURbjozfImON6yLHl/PoT6M/9Sbl9URgAETm1TIBARHYDeAKA/7Y02X9BkQKBiJyCojzmRo+LSQliHt7o94fbapWce4lQiERJCjIkFiFi4ea+DcqQVULKEF/42M5zHls5iJDY+oPkztBjcra+IH0S3BvdkxDznAbgoyJyLYpkx6Wq+j4ReY2IPLWc5hIA3xGRzwH4KICXlaPEeoPlMLHBkpD+cFutkmsvkQz6iKTWPyT2cpmYSmUslH20wTKZVUL0CwnRKyTW8pg5jhFrpTEx9QeZsyzGZ2+QGEpivNNWSrMBBKjcyh5VvRbAQ2qe/83KzwrgpeUjCJQgscMb/f5wW+0k514iifcRoRCxQ0yNVK03UbUoQ0KLEMB/vxCfMsSHcIqpTwhFSIE1EWKFMcdyqAbMg1iIjr69QxafZ3PtM3IUwB2hF8I+LIdJDfYV6Q+3005yLZ1JvGwmtZKZmPuHsFTGDZbKZCxsp1xKZOYkpvKY1EpjxhL6vKviszfI2PV2URLT59jbXN/5us05yluaDrkN1JfTsMSG1EAJkgO82e8Ht9NOKESSI1UhEhsx9Q6xcJPfBGXITlJvnOqrV8gczCFCXO3v0CLEZ3+QOZukWsH3NXFwX5Ah5JRQJt6hBMkRpkX6wW20TY4pkaoQSVCKpCREmA6Zn8UNaOgb/TooQ7ZhKmQ6sYgQwJ34ilWE+Bgtpi8xp0G8XjOqpejVXcG0BvEMJQgp4A1/N9xG2+QmRAAKkUiIVYgwHTIdypBtQsgQ36mQOZnrWJrjuKAImVeEzDFkbiyMLYnxBsUJmQAlCKmHN/zdcBsV5J4SSYyqEIldisQuRKwT+ka/CcqQbVKWISyP2YYiZN7jwHVZjIs0yNT5z8lyX5DBUG4QD3B0GNKPupv83EdXWYajzxTkNupM4sPvpjLSTIwjzMQysozVUWUsjSYTeljdUEPq+hpBJsbRY6yOHBN61JixI8YMZehoMX3xNWrU2Pdpet2U4+fQ8bux52jzPtvcANbnHqllF/L5Iq6LY8h3ZJwBMAmy4Bjy+ibbBUxCtMPtU5BbUiSTlEjMxJwOsZ4QCZ18qGORDAn97SgQdvswFTKeOctjXJJzIsRSWUy/9573vLBwvTNBZRefyIQJqUAJUsfyTVsON24uYMPVdrhtCnI6rxJurpqCEGG5zHxYlCGAnVKZHGWID2Isj3F9LFgSIb6xUhbjajnmapA6hNn7gvT980uBQRxDCdIXipFx8Ma/GW6b/M4pChGzxChEYkiHWB1VhjLEvwxJKRUyBymKkBj6g4QcLSbUNcjHKDGtfUGaysX7iA7KEOIISpApUIwMh2mRZrht8jqfEk2JUIiEwboMAWymQyhD0pYhcxFDeQxFSH9ClsV0v9/4NIjPa9uh42faLk195eL580yMwsaorqm7cUu9MeRU2HS1mdybrebUZLUqQhJprppCU9XYGqrG0Ew1dJPQOqw0UQ25bXw3T/XROHXu7TlH01SXjTUXImTqfp3aLDW1Rql9t0effTlX490uhhxndefq0OvFrM1RN8BGoFUWfS5JK5QgPqAYGU7uN/9N5L5dcpEiCY44QyHiH+tCxOKoMrnLEFc3zX1ZJEJ8yJA5RQjg9phxvf9dCK7YRIivUVpc0CVCutal7fdDJUuIkaRqcS02djmeH4kelsOEgqU0w2CpSD25b5Nczp/EymaqJTOxls3EVjJjvVzGWqmMlRFlQm2XFEtkYuwVYq08JrbSGAtlMZaua3OzXBLT2hekShx/RkliUIJYgmJkGLkLgDpy3ia5nDsJ9hKhEPGH9WaqFhupUob4lSFzM+e2pAjphiKk6X3bj505RooZ8hrn52agJPNu+3+miScoQaxDMdIfpkVWyXmb5HLeUIiYgkLEHZQhq+QgQ2JvnDrHcWJRhEyRIdZFiFXGrsfQ47HvMTL0WNrk6C/EEOwJEiPsMdIfNl1dJde+Ijn0E0msl0jsfURi6iFiuX+Itd4hFvqG5NAzxEe/kDm3o+uGly6X1VXfhyl9Qqb0CJmbnJqkxtQ7pZam3iGLz3g59gE5BuCO0AthHyZBUoGJkf7knI6oI9dtkcP5klBKJPY+IjEmRCxiKR1ioW8IkyFuyDEV4mofhkiExFoW44K29XA5XG7dsdHnPBzdF6SNhdDoSonsKqdZno7pElIDkyAp03Rjl+I34FPJNR1RR67pmdSTIkyJmCGWhAjTIf0JnQ7JJRnCVEiB62F0Q44cMzYR4mPEmCGJEFfvH2rI3LHMOppMU8qDQ+ISBzAJkiNMjXTDtMhOctwWqZ8jCTVYZUJkfiz3D7GYDglFyGSID5gK2cblvmYipJm+iRArTVLHpEF8XjN29AWpfsFm+08gSRAmQUgB+4x0k2tCoo4ckzM5JUUiToksi5CYUiJMiEzDUjqkerMR4lvdEMmQlPqF5JgKYSJkOlPW3yJ1x8TciaxBrANG28qQCKAEIc2wnKYbipGCHLdDylIkodL2u4umAAAgAElEQVSZWMtmYhMilmQIEK48pI6QpTIhxBBlSDeWRQgwbd+lKEJcN0p1URbTNo+23zXNd8oxtCxLDh2/G3uObm+DzfU1rG8OON7HlLuwRGabY+C26AElyIJjoRcgIpgaaSdHIVBHbmkRShHzUIjMB9Mh3eTWNyS1fiFziBDA3fFgafSYWETIEEL0ByEO2MB2WoSihFSgBKnS1Osg9Zs3F1CMtEMxkt82yEWKJCBEgHikCIXIeKykQ3IrlfElQ5gKKbBSHhODCJmrUaqrspi50iBDmL0kZi/69ZrbhTT7s5FgUIL0gXJkHCynaSc3KVBHTmmRVKUIUyLBoBAZB9MhBZQh44glFUIR0o+Q/UFCjRYzR0nMyryWSmKqbG4A63WJjD49PpjmII6gBJkC5cg4mBppJncxktP6p3oeJCBFYkyJUIiMw4oQoQxxz5wyJIZUiKtlnLq/FqOmjJEhFkWItbIYH2mQPnQJs8F9QRZwmFwyE5Qgc0A5MhymRprJSQzUkdP6p5gWSUyKUIi4wbIQsSBDAP9ChDJkOHNsM6ZCdhKzCPFVFuNynnXbIcgoMUMkR59pN5BPOc0x5LOuE6AE8QnlyHBS/bZ8KjmJgTpyKaOhFDFHbCmRqhABbEoRa0Ik93SI7/X3KUNiK5GxmAqhCClwKUJSSYMQEhPHhV4AguKGru5B6rmz4ZE7OR9Duax7isf8gfWdj8g4fGDP1iMGjty5vvWwyKEju3dIkdAcwp6tRyiOYG3r4Ruf634Ye7aEyFxsYm0rGeKaObaV6/3uYvmm7qNFecxQNrGOTQy/bh0e+H5DttGRnsvTZ5273rfrOBizb4ccW332+/I0h45vXu/Njcp/PH6RdeJG9zQkD5gEsQyTI8NgSc0qOSdGclj31JMiTInMiuWyGWvpEMBWuUzKpTI+kiE5l8i4SAa46BPis2GqlWapUxmbDhq6Pn2nH5qu6tUXpE9zVEIcQAkSI23fcqd2k+cCltTsJAc50ETqZTSpHesJlc5QiIzHmhCxUC4TqncIZUh/5pIhrkQIELY8xroI6UssZTFNzNFvxDmLnh91w+TWSZNq2oPNU0kDlCCpwfRIP5ga2UmuYiSH9U4pLRKxFIkpJWK5jwiFyCoh0iE+1zsFGZJ6KiSWkWOGiBCr/UFCpkH67OvladqGyh1N24gxQL0oyUmGHAVwR+iFsA8lSC5QjvSDcmSbXI+Z1MUIpYgJYpUiFCLNhBYiqadDqv0G5hIic8mQ1FMhocpjUhUhU/CdBpnScHhzA1hfyIm9WP38xWFwyYxQguQOS2v6QTmyTeqSoI6U1zmlEppEpAiFyHCWm6mGliKh+4eETIekUCoTiwxJLRWSiwiZ+p7W0yBt9OoL0hdKEjIBShDSTK5JgCGkdAM5hZQlQRMp9xdJJS0SqRSJJSXCspkey5FhOiSlUpmYZIilVAhFSPuyzF0WM2bIXJdpkMklMWOao1KIkIFQgiw4iu2bmpRuZuaA6ZF2mBopyE2ipSyCUpF9lCKzEkNKhEIkzXRIzDIkxVTIlP0xtk+IJRHSb37zNkq1OsKNd6pyZBcoSsgWlCB18CZ/PLnd+A6BcqQgZVmwTMrrmkJaZFmKAFGIkRhKZyhEOpYjoBAJmQ6hDFnFaolMjKkQKyLEV38Q12UxdfObuyRmR1+QNpj0II6hBBkKBck4uN2aoRzJS56lKkaYFglCDCkRq2UzFCL+hYivdaUMcVsiE5sIATBIhoQUIVPfb2xZjGu6SmJ60ac5at0wuWSVu0IvgH0oQVzCG/1x5HQDPATKkXSFwTKprmeKaRFKkclYTIlQiPgvl/GRDsldhlhJhUwtj/HRJySUCJm7LGboPOdKgzjvC1KVI2N6iJDsOc73G4rIvUTkoyLyORG5QUT+Xfn8q0XkZhG5pnw8ufKaV4rIfhH5gog8sfL8eeVz+0XkFZXn7yMil5fPv0NE1hCaAx0Psgq3Vz13NjxyIZdjIsV1TOG4PbC+82Gcwwf27HhY48id6zseFjh0ZPfWI+hyYM/WwydHsLb18IGPdTyMPVuPOdjE2pYQcYXL7eJqf05dnrHb/xB2b/UKGcIiFdKXwwPeo++2ONJjGcas2873aN63Pq8frs8Bp2yEXgBijRBJkLsA/O+qerWInATgKhG5tPzdH6nq/1WdWEQeAOBCAD8G4IcAfEhE7lf++k8BPAHATQCuEJGLVfVzAF5XzuvtIvImAC8A8Gezr9kUmCIZBrfXKm03lDF+Az+UVNMUVVJMTcVeRsOkiFOspUSsDL0bashdn+UyKZTKzJUMsVQiE1sqJJVEyBxlMXOnQdp+P6oviAsoQ0iJdwmiqrcAuKX8+Q4R+TyA01tecj6At6vqJoCviMh+AI8of7dfVW8EABF5O4Dzy/k9DsDPldO8FcCrYV2CtNH1DXDMN0BzkOKN4lRyLa3J5VhITQDFXEYTWbNVy1LEYi+R0GUzuZTLxF4q41qGWC2RCdErhCLEzjV6KL1KYur6grTR1jB1A3EmTokXgvYEEZEzATwEwOUAHg3gJSLyHABXokiL3IZCkFxWedlN2JYmX1t6/pEAfhDA7ap6V830acJURD+4nVahHNlJSsdBSmKEaRFvUIr0J1chklo6hDJk/LK5SIVQhCzPa7wICZEGWcZJg9RlFqJj8W9Tc9TllMfByvN2/+zOgAL4fuiFMI/3niALRGQvgL8D8Kuq+j0USY0fAXA2iqTIH3hYhheKyJUiciUOfGvutwsDe5H0g9toJ7n2HUl9/6e0fjEfnxH1FbHcU8RSL5HQfURy6B8y9/rN2TfEdc8Qa/1CpizL2G0+pk/IJtYH9QkJ1SNkCmP25dT9N5bN9e1l3awrUwl/aScjaOr/uTTN3UXk/xORz5bTPN/3cgZJgojIiSgEyF+r6rsBQFW/Ufn9fwLwvvK/NwO4V+XlZ5TPoeH57wDYJyInlGmQ6vQ7UNWLAFwEAPLD5+jE1YoTpiO64TbaJse+I6mnRpgYCU9EJTRWkyKWUiKh+4gs39D4Son4SojEnA6xngxhKqRuudwnQrrnM09ZzNDXjU2DtC7D0FFi2mgrhSEhqe3/WfbtXPBiAJ9T1Z8RkVMBfEFE/lpV/QxPhjCjwwiAvwDweVX9w8rzp1Um+1kA15c/XwzgQhFZF5H7ADgLwKcBXAHgrHIkmDUUzVMvVlUF8FEAF5Svfy6A9865TsnCFEk33D7b5JYeSXm/p7RusR6TkaRFrCZFLI06k2NKJLV0iGusJkNcpULGLsuUVMhQQiZCXIwY0/Y+Y0aLcZkGWT62B+/TMV/ENG3S6hchbIrqBVW9RVWvLn++A0Bd/08FcFLpBfYCuBWFPPFGiCTIowE8G8B1InJN+dy/B/AsETkbxUb5KoBfAgBVvUFE3gngcyg2zotV9SgAiMhLAFwC4HgAb1bVG8r5vRzA20XkdwB8BoV0aUeRb3+EsbBhaztMkBTklh5JOTmSSmokxsRIJGmRGJIiTImU7+0hIZJKOqR6E+cyHWI1GeKqX4jPVMhCGgxJhQxNhADolQrps+4h+4MMYY40SJXqKDGtMPVhiVNE5MrK/y8qqytWWOr/WeWNKIIOXwdwEoBnquox94vajBTBCSL3Pkfxa1d2T1iH9Q/PVonx5skXuW+bnM6pVPd1CusV23FoUIosY0WKVAndYHVBqOF3Af8jzfgYYQaYd73maKTqcmhdwN36T91fU5ZjzHYeWh4zpGEq0E+EFMvRvexdIqSYT/v7tb1P075rek3d83XzqJtueV9Vj+fl31VLYqoSZGuo3OqXLotNdLDy752Vnw9WpjtY+f3i5++gyBmUP8uXcJWqnrOyAokg8hAFPj7jO9y91/Yr+39+HMDvLtpfVH53AYpgxEtR9AS9FMCPl31CvRB0dJhk6BOvju3DtA+YJGkm9xRJTumRVJMjKaRGYkuMRJAWsZgUsdJPJORoM6knRGJJh1TLCFwIESvJkCnL4SMVsiiNcd0nxFciZAxDRotxkQYZvB+7hsqtjhDDlIg56vp/LvF8AL9ftrHYLyJfAfCjKFpeeIESxBcUJcOhJKmHgqSe1M6fFOVICusUuxihFOnEghQJWTaTohDxVS5jtVTGpQwJUSIzdvsOlQdzNEz1IUJ8lMX0YVl0LA+X20TvkpgprIOixBNN/T+X+BcAjwfwjyJyTwD3B3Cjp0UEQAliC4qSYVCSrJLzNsklPZKCSFgm9tRITGLEeFqkrrlqaDFiTYpQiExjznXKQYbEmApJRYSMfY8mERIyDdI0SszmRqUkZg6s/m1Oi6b+n/cGAFV9E4DXAniLiFwHQAC8XFW/7XMhKUFig6KkPzkLgSZyTZHkIEhSkyOxrw/FiDOspUVCS5FQKRHfQ+/6FCJzyRDAfalM7jJkjGiaszzGpwiZo1HqEJHhM1Wyg3UU/T7qyl6Wn1seAYbpD++o6idRiI22ab4O4Fw/S1QPJUiKUJT0g5JkJ7luj9QFSWriK2Y5QjHiBEqRnViQIrELkZjSIS77hliRIbGnQvqOHBNahAyh73yWpxtSEtOUBtmiqS9IUw+QhSzpO32yHAXgrb9otFCC5ApFSTddUgCI48bLFandTPchV0ES4/6MdV1i6nFjtL+ItRIaS1KEQmQ4c62L5XRIaBliPRXisjzGhwhpnu88ZTFDaJJXo/qCVJujEjIQShDSDEVJN7mmJ5bJcTukLEhSEl6x9huJITXCtEgvQkqRECkRn2UzsQsRyhA37z9WhoQqj+mznlNEyNxlMV2vHdsgdWv6MX1BmtIeG+AoMqQWSpAFR8Fv/sfQ18Ba+/DuCx5TBblJkhwFSUz7MNZ1oBgZjaW0SM5ShEJkJ67TIa5KZVysaygZYiEV4qpPiAURMncapLMkZkFTqQshI6EEGUqfm1rA/odp3zBV0gxFSV6SJFVBkkJ6JEY5EkM5TSRihFJkfiniKyXiS4hYLpexkg7xLUN8pEJ89gmZS4QMoc98XKRBaktilvuCLNIc1VQHEx5kBJQgc9FXlgC2P2D7hKmSZnKSBHXksv5d50Csx36McqFKjMtvPTViUIxYSYtYkSKppETmFCIxlMukIkPmLpEZkgqZozzGtwiZWhYz90gxzofK3UBGSRIFRvSMyQ1KEAswXTIMypJVck+TUJLEebzHnh6Jbfmtp0YiECM5SZEUUyJVIQK4lSLWy2Vcl8r4liE+S2RClMdYFyF9ymKGpEGaSmJGNUgdwvIQuiRbKEFigumSYbAEZyc5i5IcJAkFiS1iSo9YliN1YgQIJkcspEWWpQjgR4yElCKxpURiESK5yBALqZDYRMiY5es7zWAWJTF1fUGWR4hZvjweLKdhuQxZghIkVShM+sFUyU5yFSWpS5LUymxiFiSxyxErx4qh1IhFMZKaFPGdEslFiLhIh0xdP+syxGUqpE+fkK71OlLe5TfJEFcixFVZzJg0yNa0TSUxbSPBUHaQnlCCEAqTPgwZh9zKTcJc5Fi+lbocSkmSxCpIYlnu2FIjmYoRSpFpxChEYk+HWJUhQ1MhFspjhsib7fn1EyEuymK66F0Sw+aoZAKUIAuOIa5v6EJBYdIN0yUFqYuDZVJOk6QiSWIRDcvE8LfJqhwxVE4TUoyEKKEJJUXmFCKAOyniepktpkNikCGuS2SslMc0iZCh5Sp9RchYeu+D5VFi+lKVI+vIRJQcBXBH6IUwDyVIH8acdJY+nIZi6HbLbZtRluQlSlJe1xT6kcQoSGJY5pjkSOZiJBUpEmNKxPUyWxEiU0TP2O08VIbMVSLjsjzGlwiZMmLMkDRI03C5vUpiFn1BqnJjuS8IIT2gBJkLCoDhMGVST+6lODmV36QoSlJIkcQgG5axnh6xKEeMpEZCiRHfaZFlKQLMI0bmlCIxpERcC5FY0iFzyhDfqRALIqTP67tESBN1aRDno8SwXIYsQQliBaZNhkHJVE/OwiQXWZKaKIl9FKfYyqCsC51Y5AjFyCz4SIv4kiKpChEL6ZAUZUhXKqRPw9Q5RYiLspixaZBW2uTGBlb/pnCIXFJCCRIzFCf9oTRZJddynBxkSW6ixPIxal06VLG8rNZKrgykRqyIEUqReuZIiaQqRFKQIS5LZMamQiyIkLFpkDoWaZCtkpi2oXKBVcFRbZrKchmyBCVIbowRJ0D4D8C+oTTZZugfDss3pENIXZakJEpilSQxpUhiFCQZypEQYsRnWsRHCU0sUsTlcoYWImPlzpjkzVwyxHUqZIoIAeqH0J1LhPR53YKmNEjXcLm1sMSlgaMAvhd6IcxDCbKAo8O0w9RJO9w+2+RWkpOyLElFlMRachOLJLEqSChHANSLEWBeORJSjMQoRSylRFwKEcvpEAsyJER5zBwipEuMtP2+qSxmZbrlBqnLNDVH3YWdiZAwo6YTg1CC9GFsegKw8yE1BEydtMO0SV7CJNXGv6lIoBjTJDFIEouCxFJpjTE5koIYmTstMocUsZoSmSpEQqZDYpAhPlIhTSKkbtlcipC2spimYXF7NUitK4lhIoSMgBJkbihQhkN5Uk/uaZOcynJSEQtVYl+nGNMk1iUJBUkzgeSI79RIKDGSsxTJRYgMTdoMfQ+fMmRKKmRon5Apo8Z0iZAqXU1SBzdI7WKRCGm4tJL8oASxzBSBAoT/gOsbypNVchYnOUiTFNMlMZfgxCZKLEsSi8tmQZBkIEd8iJE50yLWpYiL5Tu8NI+hUsSFELGSDhkiQ3yUyDSJEKB/n5Cm9e/T9LRNhPTpJ9KWBqktiammQOquwwfBpAiphRIkZShR+sG0zk5yFSepS5OUhEnMqZKYRIlFEbHA2rKF7j9iSI74EiOAWzkylxhZlg7AdDEylxQJkRIZK0R8pkNcyRAfJTJjy2P69gmZOvpLU1nMoDRI1ygxhPSAEmTBMaDxmrT6dzEPKFG6YfqkIMftkLI0SUWYxLoesQxfbTm1Y6XUJnSvmSY5AswmSFJKjfgSI1akiOuUSAxCxHWpjC8Z0pYKGVMe41KEjC2LaXtupTfIMk1pj+rwuNkkQo4BuCP0QpiHEqQPrkrScpMpUyUKYOvGxCUUTAU5pU7GjFEf+ia3D6k0+I0xXRJDqsSiKLGUIglZYuM5PeJLjsydGplDjLhOi1iRIlPKZnwJkbnSIT5liKvymCENU6eIkKblqhsydzkNslUSs0iDAP3kRlWGEAJKEL9QpgyHsqCenEt4ckqdpJg2iTWdsSC25Y8hVWJJSgB2lieUIPGcHgkpR3IRIxalyFghAvSXInMKEUsyxEcqZE4R0lUW08rQkpiNAdOSpKEEiRGHzZKTFyou0iiAjZsZV+QqlnIQR6mlTWJPmcQkTCzLEmtpEgvLE6rMxqMgaZIjgDtBMmdqxIcYcSVFgHFiZMry+E6JjBUifWVI13z7CKC+MsRliUxbKmQOEdI0v7aymEUapLVBKlAvOA5ie2QYQipQgiw4hu0TJCdL6FKoAOlKFZb2bJOjREk5fTI2HmpRnsRcXhWLMLEqS6yVM4VOk4RIkRgQJNbliGsxYi0tEkKKzC1EQqRDDlU+TNcJkan9QvqmQuqkzFQR0meo3d5pkD4lMcujx1CGkBJKkDrmOkFykCtMqTTDVEpBThIl5XVNRZ7EmDaJQZgMOT58HhMWUhxA2OUIkSLxJEjmTo/MIUfqxAgwXo64EiMu0iKupMgYIQL0kyJzCJGh6ZCxpTJj+4VMTYXUvX6sCOkqi+mVBulTEpNNU1Sg+GbffSPq1KAE8QnlyjBcp1SANMSKK5kC2LihG0pOqZwUS3hilyexpU1ikDzW0iVWUiWhRIlvSdImSABnkmTO9IgvOWJNjPiSIr5SIqGEyNRSmSn9QoakQrrKY1yLkF5U0yBVFvdGy5sk1XsmMhhKkBSY02ymdrGgWNlJrkIlh1ROaimUmOVJTOLEsjSxli6xIEtCiBLfoxLNnCKZMz3iWo64TI3UiRFgmByZmhbxKUWGpkRCC5EpMgRYFSJNMmRIKqRPecxyL5UpImRQGgTYec9y59LzHBmGLEEJsuAYpp0gFj5oz8Hc0bEUJAvFSoFLoQLYuwmvI2WZkopEifW6HksfGqvSxJIwCS1LLIoSV9t85hTJXIKkSY4A4wTJ3HLElxgZ+95zS5EhsmaoEBmbDhnbN2SMDJlaHjNGhGyvR70IWaGpJGYdO3s+UoaQEkoQV/g8qVISLpQs9cwhVoC45EpOUiVFmZJC2VKMAsW6PLGYirEyFHXIXi++RY2vNMmMkqRNkADjJYnL9IgrOTI1NeJbjCxLEaBbjIyVIlOFiItymTGlMkNkyJRUSFVwVOfbJUK6ymJ2pEGA7mvYoilqSvdQZBKUIDFC4dIfH02QYhItc8kVwL5gcS1VgPA36cukVt4Us0iZep22OrrKMlaaiC4z53JZkCahhIlPWeJDlASSJGMEicv0SJMcAYYJkimpEZdiZI60SN9+In2XpU8/lanlMm3pkDllSFsqpK1PSF8R0lUWs0XdKXIQmTVFBYCjAO4IvRDmoQRZMNfxctIM8/RJiNhYbOLF14XVumyZU7AANiVLymIllSROrCkbF9deS30x6gjdK6OOEI1G63DaU2PAtK7W35csmbupbpckAUaJEtcpEh+CpK8cmZIaqRMjQP+haYe83xApspwSAZrFyBgpMkaIjE2HNPUNmSJDulIhbX1CuobP7RIhANrTIBvYLpPJToaQNihB5ia0iItRwlC81OPzwm1RuOQiWeYQKwtiGqWkC+u9L9qw2BejiTmvjRb7zliRJ6HSJr57vPgSNHOmSmYQJS4lSZsgAfpLkqnpEd9yZKgYGVpC07d8po8U6UqJdM2jTYgMTYccrky/uyXhUSz3emuJTFsqpEuE9GmUCmBnGqTuGnEQhSFZ9AOx+PmWBIESZMExdN9kxnjihJYwC6zLmJCNkiwKGN+m3MK5NbdkWRBStqQkWGJO4cQkVCyLFEsSJXQiJtToST6lydzCZM5muo5FSZckAfqLEheSZIogaZIjwLBRWRYMFSNt7zNEjMwlRYamRMYIkSHpkFWx0a9Epi4VUp1XXxGyY32W0yB1n12r6Y9dYBKEbEEJMgTLJ46Fm8g2rMgYwJ6QCd2p2oKECXFuhTpnfMkWwK9wmVOwAHZ7T/TBYtlHE1bKQZoIVSZSh+/SkTmWwbc88dXfZW45M0cZTh9RAvSWJa5EyVRJMocg6duMtIqr1EhfMdK3hKZLikxJiUwRIlNlyJhUSHWaqghZPLdYn+WyGKyjuTfI4lxdyBDr90vEG5QgC/oOkWvhhrEOy4IGsHXRsSRkgPBSJrSEAcKcVyHPGV/ng0/hAswrXeaWLAsslVj0xUqioQ2fo4r0xXcKoglf6QiX7+1TnvgQJ3NJkznSJQ5liQtRMkWStAkSoFmSjEmPNMkRoDtt0TV/l2LEpRRpEiLLy1cnROrSIXWlMlNkSFcqpKlZarFMq2UxW+9ePZ93YbsvSDZD5B6D/w+A8UEJMpSYT56QAse6pKniW9hYkzJVfAkaa+fV3OdK6PNhrmM8xN9c1+LFl2wBbCQJ+uBiOS3KFdfXHZ/piCbmvvmf+p6+Rk2au7fLHGLGdR+YvrIEaBUmfUQJ0CxLuiQJ0CxKxkiSNkEC9OvJsWPZOiRF03zrxAiwKke6xEhXSqVNioxJiYwVIsvy5UjlNWvYrJUhfVIh1fVqEiE4HlujxWDHO2Pn6DAcIpdUoARZcAxhbkZ9pgCs3WiOwcfFK/QN6hjmuqm1LGgWzHEOWTxXXB77Vo5xF8dtyC87pgoYn8IFGC8MLKdwLAmgua4bg0oqHL7vnEJg7PvNLVHmLE1yLU5cShMHwmSKLBkrSrokCbAqSoZKkr6CpG86pY8cmSJG2vqkNEmRppTIUCHSJx1SlSFjUiFdImSFakPUTdj5/EOCQwmyIFRj1BhuMqfi8ibV4s3pFFzd2MZ+UZ9ybsV2Do09H6wf+2OOZWvH7dDj0ELadIiI8S1dFvi+me5Ln+XysUyuEwJDaL0xnuH92tbVh8BxtS3rttscpUkupYyrEqYhwgRYkSZ9ZQmwU5j0ESXAqiwZKkqGSBKXgqRLjtSJEWBbjowRI02vqZMih5b+2OzB4RUhMiQd0kVVeHQtZ1WEFG9RkwapjhJDCChBhmHtA3to+l5IYrtJdUWfm13rN7Yu6HNznNK51XVexHw+tB3TMR3LTcek5eOw6biyIGKq1N1vhJIvVVzfYI4l9HK4ujHuy8oN9IzvVV23uQXOHDLFdWmSK4EyVZ4MlSbAljgZIkyAQpr0lSXAtjDpI0qAQpZ0SRJgZ7Kh9f0bRER1Pk1yBMDWsLF1rLfMu2n56panrxQZQlWINKVD6l5TTYU0UidCqr1Aho1WTRKGEmTB9xHXh3gLVLcXa+xWqd5Q5WyeFzf9oRvA+mJxXqR4TiyO6diP5zsQ3/EYy3Fltfv+YYQdnnrBAfgfTjrk+4deX+u43j53ws01Ivh+GyFOMNwJHz6wp/dQwoPo9h9kTpZFSLUMxvKXHc44CuB7oRfCPMlKEBE5D8AbUJwKf66qv9/5ottmWphkt3IF199ux3aD0sWcEdxYcPGHx+LNVRNTzwnL54DvYTXnYMzxaOH4G3JchTqG5hgRwwV99/nc+7nPnVrIkZZc3/z6er+293HxHk3H9VyjDLns4TNmXnXrO7U/zdjSuN6j8SzJkx7Le7iaVOkYUaeaTGmTJ9U0SuvoOIsERI9RcNoauraNbtM2mk1Tk9a6/iN1ZUDLJT/LvU+WG65W+4pU+4nsrm2Wur6VElkkROp6gyyWZ2UbVEXIAQD3APBN2Pg7njgici8AbwNwTwAK4CJVfcPSNILiPv3JAA4BeJ6qXu11OVXV5/t5QUSOB/BFAE8AcBOAKwA8S1U/1/yahylwmacljJ0TQy+AfXIQX32wfCM/B5Zu8l2TwgeHWI/HWI4rqysXbnEAAA/LSURBVMeIpf0ecl+G2D++0jdzpxbmmr/r+bo6vlws15R5jFmPMe835DVDlqnH8MR9EihtAgVolidA81DBQL00aXpN3VC/y8P61r12+T2qv6/Oc0/FCq9XalUWYmTxusWQu3tWnj+y9fMeHNr6/24cwjqOYDcO4eRD38X6N1AkQr4JyP+Iq1T1nJWVSASR0xV40Yzv8But209ETgNwmqpeLSInAbgKwNOq9+Ei8mQAv4JCgjwSwBtU9ZEzLvQKqd6qPQLAflW9EQBE5O0AzgfQKEGAIwC+6mHRmrCQ042Ju4VegHbuCvGmBo+hudJVtWQg50Jesb8103x93qB+Z4Z5xiIoFsx5I+ziGJnjeJi63y3sYxf7bcz+8S2Qxm7rbw+Ydsy27Lvt5vgz7FKU9J1X2/acOo8p51Pbeze939DXDJIdTfNdSqTUTHd4eZqa911RHEty5bs4eevnZalyO/Zt/dwkU5YlyuI1VWGxYz4tYmMx3bI0WQiT27Fva/rFtGs4snV5Xvxu8frbsA97cBi3Y9+WHNmNw7gdJ2MPDuF27MMaNremWe4Zsvh5E2vAHmDPvQ/jbrceGVtpRQagqrcAuKX8+Q4R+TyA07HzPvx8AG/TIo1xmYjsE5HTytd6IVUJcjqAr1X+fxMKy9TCHQA+Xv5s6Wuj2BjWxCo/eGyZF1iz4Gi/B5FrbTj4xO9VlDUR4zFpUHquYFRMWvnkE/LPQQix4yuJMud2nWu7ud42rrbB1PWdsl5jL3FDpdFc0/fZdn3mtWOamjv48n0O1/1u7+J39c9/t2Feq/NZlSjL0mVZtCwLlrakyLIAAbblSfV1a5Xndm+lPw7vkCRFGqSQI4tkyCn4NvYdfzt2n3oI+069HTVrTmZCRM4E8BAAly/9qu5e/XSU8sQHVj4KBEFEXgjgheV/DwC/+IWQy0MGcQqGffdD7MF9GD/ch3GT5/6zIhPdCMA892FacB/GT3b7cFmsLP/fuGb44dALMC9fvwT4jVNmfINdInJl5f8XqepFyxOJyF4AfwfgV1XVXKfWVCXIzQDuVfn/GeVzOyh32MpOI/YRkStTrufLAe7D+OE+jBvuv/jhPowf7sP44T4kllDV80Ivg4iciEKA/LWqvrtmkl736nNynM8388gVAM4SkfuIyBqACwFcHHiZCCGEEEIIIYSQJClHfvkLAJ9X1T9smOxiAM+RgkcB+K7PfiBAokkQVb1LRF4C4BIUgyS9WVVvCLxYhBBCCCGEEEJIqjwawLMBXCci15TP/XsA9wYAVX0TgA+gGBlmP4ohcp/veyGTlCAAoKofQLGBSZqwjCl+uA/jh/swbrj/4of7MH64D+OH+5CQElX9JADpmEYBvNjPEtUjxTIQQgghhBBCCCGEpE2qPUEIIYQQQgghhBBCdkAJQkwgIueJyBdEZL+IvKLm9+si8o7y95eX405DRJ4gIleJyHXlv4+rvOZj5TyvKR/38LdGeTFh/50pIocr++hNldc8rNyv+0XkT8pGS2QmJuzDf1vZf9eIyDERObv8Hc9Bj/TYhz8lIleLyF0icsHS754rIl8qH8+tPM/z0CNj96GInC0inxKRG0TkWhF5ZuV3bxGRr1TOw7N9rU9uTDwHj1b20cWV5+9TXnP3l9fgNR/rkisTzsHHLv0tvFNEnlb+jucgIdZQVT74CPpA0bz2ywDuC2ANwGcBPGBpmhcBeFP584UA3lH+/BAAP1T+/EAAN1de8zEA54Rev9QfE/ffmQCub5jvpwE8CkVd4QcBPCn0uqb6mLIPl6Z5EIAvV/7Pc9DWPjwTwIMBvA3ABZXnfwDAjeW/J5c/n1z+judhHPvwfgDOKn/+IQC3ANhX/v8t1Wn5sLf/yt8daJjvOwFcWP78JgC/HHpdU31M3YeVaX4AwK0A9pT/5znIBx/GHkyCEAs8AsB+Vb1RVY8AeDuA85emOR/AW8uf3wXg8SIiqvoZVf16+fwNAHaLyLqXpSYLRu+/phmKyGkA7qaql6mqoviw8TT3i05KXO3DZ5WvJf7p3Ieq+lVVvRbAsaXXPhHApap6q6reBuBSAOfxPPTO6H2oql9U1S+VP38dwDcBnOpnsUnJlHOwlvIa+zgU11yguAbzHJwPV/vwAgAfVNVD8y0qIWQKlCDEAqcD+Frl/zeVz9VOo6p3AfgugB9cmubpAK5W1c3Kc39ZRg//D8a4Z2Pq/ruPiHxGRD4uIj9Zmf6mjnkSd7g6B58J4G+XnuM56Ic++3Doa3ke+mXKPtxCRB6B4lvsL1ee/t2yTOaP+EXBbEzdf7tE5EoRuWxRRoHiGnt7ec0dM08yDCfnIIq05PLfQp6DhBiCEoQkgYj8GIDXAfilytP/VlUfBOAny8ezQywbaeUWAPdW1YcAeCmAvxGRuwVeJjICEXkkgEOqen3laZ6DhHikTO/8vwCer6qLb6pfCeBHATwcRUz/5YEWj7Tzw6p6DoCfA/DHIvIjoReIDKc8Bx8E4JLK0zwHCTEGJQixwM0A7lX5/xnlc7XTiMgJAO4O4Dvl/88A8B4Az1HVrW++VPXm8t87APwNipgjcc/o/aeqm6r6HQBQ1atQfHN5v3L6MzrmSdwx6RwsWfnmi+egV/rsw6Gv5Xnolyn7EKVAfj+AV6nqZYvnVfUWLdgE8JfgeTgXk/Zf5Xp5I4p+Sg9BcY3dV15zB8+TDGbSPix5BoD3qOr3F0/wHCTEHpQgxAJXADir7IC+huJm6uKlaS4GsBix4AIAH1FVFZF9KD70vUJV/2kxsYicICKnlD+fCOApAK4HmYMp++9UETkeAETkvgDOAnCjqt4C4Hsi8qiyhOI5AN7rY2UyZfQ+BAAROQ7FB7+tfiA8B73TZx82cQmAc0XkZBE5GcC5AC7heeid0fuwnP49AN6mqu9a+t1p5b+Cop8Ez8N5mLL/Tl6USJTXzUcD+Fx5jf0oimsuUFyDeQ7Ox5Tr6IJnYekLAZ6DhBgkdGdWPvhQVQB4MoAvokgCvKp87jUAnlr+vAvAfwawH8VoBfctn/8NAAcBXFN53APABoCrAFyLomHqGwAcH3o9U31M2H9PL/fPNQCuBvAzlXmeg+KDwpcBvBGAhF7PlB9j92H5u8cAuGxpfjwH7e3Dh6OocT+I4hvmGyqv/YVy3+5HUUqxeJ7nYQT7EMDPA/j+0t/Cs8vffQTAdeV+/CsAe0OvZ6qPCfvvfyj30WfLf19Qmed9y2vu/vIavB56PVN+TLyOnokiOXLc0jx5DvLBh7GHqCoIIYQQQgghhBBCUoflMIQQQgghhBBCCMkCShBCCCGEEEIIIYRkASUIIYQQQgghhBBCsoAShBBCCCGEEEIIIVlACUIIIYQQQgghhJAsoAQhhBCSJSLyKhG5QUSuFZFrROSR5fNfFZFTAi7X68vlev3S888TkW+Vy3qNiLzN0fv1Xl8ReYuIfKV8/8+KyONdLMNYRGSfiLxoxOteLSK/NscyEUIIIcQ2J4ReAEIIIcQ3IvJvADwFwENVdbOUAGsO5nuCqt41cTYvBPADqnq05nfvUNWXTJz/VF6mqu8SkccCuAjAWQGXZR+AFwH4jwGXgRBCCCERwSQIIYSQHDkNwLdVdRMAVPXbqvr1yu9/RUSuFpHrRORHAUBEHiEinxKRz4jIfxWR+5fPP09ELhaRjwD4sIhsiMibReTT5bTnL7+5FLxeRK4v3+OZ5fMXA9gL4KrFc22IyGNE5H2V/79RRJ5X/vxVEfntmvX4QRH5hzJt8ucApHx+Q0TeXyY8ru/x/p8CcHr52uPL9bmiTNb8UmU93ygiXxCRD4nIB0TkgsrynVL+fI6IfKyyHCvbT0R+rHzumvI9zgLw+wB+pHzu9eV0L6ssx29Xts2rROSLIvJJAPfv2raEEEIISRMmQQghhOTIPwD4TRH5IoAPoUhYfLzy+2+r6kPLUotfA/C/APhvAH5SVe8Skf8JwO8BeHo5/UMBPFhVbxWR3wPwEVX9BRHZB+DTIvIhVT1Ymf//DOBsAD8O4BQAV4jIJ1T1qSJyQFXPbljuZ4rIT5Q/vwHAVzrWs249fgvAJ1X1NSLy0wBeUE57HoCvq+pPA4CI3L1j3ucB+C/lzy8A8F1VfbiIrAP4JxH5BwAPQSEcHgDgngA+B+DNHfN9FWq2H4D/FcAbVPWvRWQNwPEAXgHggYvtJSLnokimPAKF3LlYRH4KwEEAF6LY5icAuBrAVR3LQQghhJAEoQQhhBCSHap6QEQeBuAnATwWwDtE5BWq+pZykneX/16FQlgAwN0BvLVMICiAEyuzvFRVby1/PhfAUys9J3YBuDeAz1em/wkAf1uWvHxDRD4O4OEALu5Y9B3lMCLymI7p69bjpxY/q+r7ReS28vnrAPyBiLwOwPtU9R8b5vn6UvScAeDflM+dC+DBi5QHim11Vvlei/X8epmW6aJp+30KwKtE5AwA71bVL4lI3WvPBfCZ8v97y+U4CcB7VPUQsJW4IYQQQkiGUIIQQgjJkvLG/GMAPiYi1wF4LoC3lL/eLP89iu2/la8F8FFV/VkRObN87YJqykMAPF1VvzDHci9xF3aWtu5a+n3detSiql8UkYcCeDKA3xGRD6vqa2omXfQE+RUUqY6HoVjnX1HVS6oTisiTey57dbmbtt/nReRyAD8N4ANlyc2NS9MIgP9TVf+fpeX41ZblIIQQQkhGsCcIIYSQ7BCR+5eJjgVnA/jnjpfdHcDN5c/Pa5nuEhQ9RRa9Nh5SM80/oihtOV5ETkWRmPh0n2Vf4p8BPEBE1svSkT6jtXwCwM+Vy/YkACeXP/8QgEOq+lcAXo+ixKeNNwI4TkSeiGKdf1lETizndT8R2Sjfa7Gep6FI3Sz4KgqBAmyXFQEN209E7gvgRlX9EwDvBfBgAHegSHlUX/sLIrK3fM3pInKPcjmeJiK7ReQkAD/TvZkIIYQQkiJMghBCCMmRvQD+71Ic3AVgP4pRWdr4DyjKYX4DwPtbpnstgD8GcK2IHIeib8dTlqZ5D4pSks+iKK35dVX916EroapfE5F3Ari+fJ/PdLwEAH4bwN+KyA0A/iuAfymffxCKUpdjAL4P4Jc73ltF5HcA/DqAJwA4E8DVpbz4FoCnoVjPx6HoBfIvKEpaqsvxFyLyWuxM1TRtv2cAeLaIfB/AvwL4vbIHyz+JyPUAPqiqLxOR/x7Ap0qHcgDAz6vq1SLyDhTb+5sAruixnQghhBCSIKKqoZeBEEIIIRkgIm9B0W/kXaGXhRBCCCF5wnIYQgghhBBCCCGEZAGTIIQQQgghhBBCCMkCJkEIIYQQQgghhBCSBZQghBBCCCGEEEIIyQJKEEIIIYQQQgghhGQBJQghhBBCCCGEEEKygBKEEEIIIYQQQgghWUAJQgghhBBCCCGEkCz4/wFGKrOEN1VcggAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 1440x1440 with 4 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"trigger_grid(supply_sweep, alpha_sweep)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These plots demonstrate the increasing conviction required to pass a proposal when either % of funds requested, effective supply, or alpha parameter is high. Blue areas represent lower required conviction, and red areas represent impossibly high conviction. This ensures that the reserve pool of funds are not depleted by a small number of large proposals.\n",
"\n",
"\n",
"### Resolving Passed Proposals\n",
"\n",
"![](images/stockflow_cv_trigger.png)\n",
"\n",
"This diagram shows the trigger function logic, which depends on token supply $S$, total resources available $R$ and total conviction $y$ at time $t$, as well as the proposal's requested resources $r$, the maximum share of funds a proposal can take ($\\\\beta$) and a tuning parameter for the trigger function ($\\\\rho$). Essentially, this function controls the maximum amount of funds that can be requested by a proposal ($\\\\beta$), using an equation resembling electron repulsion to ensure conviction increases massively beyond that point.\n",
"\n",
"## Social Systems Modeling\n",
"\n",
"In the conviction voting model, multiple graph structures are used to represent participants and proposals to represent a subjective, exploratory modeling of the social system interacting.\n",
"\n",
"### Sentiment\n",
"\n",
"Global Sentiment denotes the outside world appreciating the output of the community.\n",
"Local Sentiment denotes the agents within the system feeling good about the community.\n",
"Sentiment increases when proposals pass and work is completed in the community, and decreases when proposals fail and community progress stalls.\n",
"\n",
"### Relationships between Participants\n",
"\n",
"Edges from participant to participant denote influence (to represent subjective social influence) and are assigned randomly as mixing processes.\n",
"\n",
"### Relationships between Proposals\n",
"\n",
"Edges from proposal to proposal represent conflict, either positive or negative.\n",
"Some proposals are synergistic (passing one makes the other more desirable).\n",
"Some proposals are (partially) substitutable (passing one makes the other less desirable).\n",
"\n",
"\n",
"### Notion of Honey supply\n",
"#### Total supply = $S$\n",
"#### Effective supply = $E$\n",
"#### Funding Pool = $F$\n",
"#### Other supply = $L$, effectively slack. Funds could be in cold storage, in liquidity pools or otherwise in any address not actively participating in conviction voting.\n",
"$$S = F + E + L$$ \n",
"\n",
"System has the right to do direct mints:\n",
"$$F^+ = F + minted$$\n",
"$$S^+ = S + minted$$\n",
"\n",
"\n",
"Arrival of new funds which come from outside:\n",
"$$L+ = L - donated$$\n",
"$$F+ = F + donated$$\n",
"The above assumes the donated tokens were not in use for voting\n",
"$$L+ = L + tokens$$ that haven't been used in voting recently\n",
"$$E+ = E - tokens$$ that haven't been used in voting recently\n",
"$$L+ = L - tokens$$ that come into use\n",
"$$E+ = E - tokens$$ that come into use\n",
"\n",
"Tokens in $L$ or $E$ are defined at the level of the account holding them.\n",
"\n",
"Total supply $S$ can be made a param and the state supply should be only $E$, effective supply."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## cadCAD Overview\n",
"\n",
"In the cadCAD simulation [methodology](https://community.cadcad.org/t/differential-specification-syntax-key/31), we operate on four layers: **Policies, Mechanisms, States**, and **Metrics**. Information flows do not have explicit feedback loop unless noted. **Policies** determine the inputs into the system dynamics, and can come from user input, observations from the exogenous environment, or algorithms. **Mechanisms** are functions that take the policy decisions and update the States to reflect the policy level changes. **States** are variables that represent the system quantities at the given point in time, and **Metrics** are computed from state variables to assess the health of the system. Metrics can often be thought of as KPIs, or Key Performance Indicators. \n",
"\n",
"At a more granular level, to setup a model, there are system conventions and configurations that must be [followed.](https://community.cadcad.org/t/introduction-to-simulation-configurations/34)\n",
"\n",
"The way to think of cadCAD modeling is analogous to machine learning pipelines which normally consist of multiple steps when training and running a deployed model. There is preprocessing, which includes segregating features between continuous and categorical, transforming or imputing data, and then instantiating, training, and running a machine learning model with specified hyperparameters. cadCAD modeling can be thought of in the same way as states, roughly translating into features, are fed into pipelines that have built-in logic to direct traffic between different mechanisms, such as scaling and imputation. Accuracy scores, ROC, etc. are analogous to the metrics that can be configured on a cadCAD model, specifying how well a given model is doing in meeting its objectives. The parameter sweeping capability of cadCAD can be thought of as a grid search, or way to find the optimal hyperparameters for a system by running through alternative scenarios. A/B style testing that cadCAD enables is used in the same way machine learning models are A/B tested, except out of the box, in providing a side by side comparison of muliple different models to compare and contrast performance. Utilizing the field of Systems Identification, dynamical systems models can be used to \"online learn\" by providing a feedback loop to generative system mechanisms. \n",
"\n",
"\n",
"## Differential Specification \n",
"![](images/Aragon_v3.png)\n",
"\n",
"## File structure\n",
"* ```Aragon_Conviction_Voting_Model.ipynb```\n",
"* model\n",
"\n",
"In the model folder there exist 4 files and folder, the [```config.py```](model/config.py), [```partial_state_update_block.py```](model/partial_state_update_block.py), [```run.py```](model/run.py), and [```state_variables.py```](model/state_variables.py). The [```config.py```](model/config.py) contains the simulation configurations, aggregating the partial states, and the state variables. The [```partial_state_update_block.py```](model/partial_state_update_block.py) contains the partial state update blocks and how they update the state variables. [```state_variables.py```](model/state_variables.py) defines the state variables and [```run.py```](model/run.py) actually runs the simulation.\n",
"\n",
"The mechanisms of the model live within the parts subfolder as:\n",
"* [```system.py```](model/parts/system.py)\n",
"* [```participants.py```](model/parts/participants.py)\n",
"* [```proposals.py```](model/parts/proposals.py)\n",
"\n",
"The initial parameters and hyperparameters of the system are defined in [```sys_params.py```](model/sys_params.py) and helper functions, plots, trigger function, etc are in the [```utils.py```](model/utils.py)\n",
"\n",
"## Schema of the states \n",
"The model consists of a temporal in memory graph database called *network* containing nodes of type **Participant** and type **Proposal**. Participants will have *holdings* and *sentiment* and Proposals will have *funds_required, status*(candidate or active), *conviction* Tthe model as three kinds of edges:\n",
"* (Participant, participant), we labeled this edge type \"influencer\" and it contains information about how the preferences and sentiment of one participant influence another \n",
"* (Proposal, Proposal), we labeled this edge type \"conflict\" and it contains information about how synergistic or anti-synergistic two proposals are; basically people are likely to support multiple things that have synergy (meaning once one is passed there is more utility from the other) but they are not likely to pass things that have antisynergy (meaning once one is passed there is less utility from the other).\n",
"* The edges between Participant and Proposal, which are described below.\n",
" \n",
"\n",
"Edges in the network go from nodes of type Participant to nodes of type Proposal with the edges having the key *type*, of which all will be set to *support*. Edges from participant $i$ to proposal $j$ will have the following additional characteristics:\n",
"* Each pairing (i,j) will have *affinity*, which determines how much $i$ likes or dislikes proposal $j$.\n",
"* Each participant $i$, assigns its $tokens$ over the edges (i,j) for all $j$ such that the summation of all $j$ such that ```Sum_j = network.edges[(i,j)]['tokens'] = network.nodes[i]['holdings']```. This value of tokens for participants on proposals must be less than or equal to the total number of tokens held by the participant.\n",
"* Each pairing (i,j) will have *conviction* local to that edge whose update at each timestep is computed using the value of *tokens* at that edge.\n",
"* Each proposal *j* will have a *conviction* which is equal to the sum of the conviction on its inbound edges: ```network.nodes[j]['conviction'] = Sum_i network.edges[(i,j)]['conviction']```. \n",
"\n",
"\n",
"The other state variables in the model are *funds*, *sentiment*, *effective_supply*, and *total_supply*.\n",
"\n",
"The system consists of 100 time steps without a parameter sweep or monte carlo.\n",
"\n",
" \n",
"## Partial State Update Blocks \n",
"\n",
"Each partial state update block is kind of a like a phase in a phased based board game. Everyone decides what to do and it reconciles all decisions. One timestep is a full turn, with each block being a phase of a timestep or turn. We will walk through the individaul Partial State update blocks one by one below."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```\n",
"{\n",
"# system.py: \n",
"'policies': { \n",
" 'random': driving_process\n",
"},\n",
"'variables': {\n",
" 'network': update_network,\n",
" 'effective_supply':increment_supply,\n",
"}\n",
"```\n",
"\n",
"To simulate the arrival of participants and proposal into the system, we have a driving process to represent the arrival of individual agents. We use a random uniform distribution generator, over [0, 1), to calculate the number of new participants. We then use an exponential distribution to calculate the particpant's tokens by using a loc of 0.0 and a scale of expected holdings, which is calculated by .1*supply/number of existing participants. We calculate the number of new proposals by \n",
"```\n",
"proposal_rate = 1/median_affinity * (1+total_funds_requested/funds)\n",
"rv2 = np.random.rand()\n",
"new_proposal = bool(rv2<1/proposal_rate)\n",
"```\n",
"The network state variable is updated to include the new participants and proposals, while the *effective_supply state variable is updated for the additiona of new particpant's funds. \n",
"```\n",
" {\n",
" 'policies': { \n",
" 'random': minting_rule\n",
" },\n",
" 'variables': {\n",
" 'total_supply': mint_to_supply,\n",
" 'funds':mint_to_funds,\n",
"\n",
" }\n",
"},\n",
"```\n",
"A behavior called *minting_rule* is included to record the general expansion of system supply every day. The *total_supply* and *funds* state variables are incrased with these minted values.\n",
"[To see the partial state update's code, click here](model/parts/system.py)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```\n",
"{\n",
" # participants.py \n",
" 'policies': {\n",
" 'completion': check_progress \n",
" },\n",
" 'variables': { \n",
" 'sentiment': update_sentiment_on_completion, #not completing projects decays sentiment, completing bumps it\n",
" 'network': complete_proposal\n",
" }\n",
"},\n",
"```\n",
"\n",
"In the next phase of the turn, [to see the logic code, click here](model/parts/participants.py), the *check_progress* behavior checks for the completion of previously funded proposals. The code calculates the completion and failure rates as follows:\n",
"\n",
"```\n",
"likelihood = 1.0/(base_completion_rate+np.log(grant_size))\n",
"\n",
"failure_rate = 1.0/(base_failure_rate+np.log(grant_size))\n",
"if np.random.rand() < likelihood:\n",
" completed.append(j)\n",
"elif np.random.rand() < failure_rate:\n",
" failed.append(j)\n",
"```\n",
"With the base_completion_rate being 100 and the base_failure_rate as 200. \n",
"\n",
"The mechanism then updates the respective *network* nodes and updates the sentiment variable on proposal completion. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```\n",
" # proposals.py\n",
" 'policies': {\n",
" 'release': trigger_function \n",
" },\n",
" 'variables': { \n",
" 'funds': decrement_funds, \n",
" 'sentiment': update_sentiment_on_release, #releasing funds can bump sentiment\n",
" 'network': update_proposals \n",
" }\n",
"},\n",
" ```\n",
" \n",
"The [trigger release function](model/parts/proposals.py) checks to see if each proposal passes or not. If a proposal passes, funds are decremented by the amount of the proposal, while the proposal's status is changed in the network object."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```\n",
"{ \n",
" # participants.py\n",
" 'policies': { \n",
" 'participants_act': participants_decisions\n",
" },\n",
" 'variables': {\n",
" 'network': update_tokens \n",
" }\n",
"}\n",
"```\n",
"\n",
"The Participants decide based on their affinity if which proposals they would like to support,[to see the logic code, click here](model/parts/participants.py). Proposals that participants have high affinity for receive more support and pledged tokens than proposals with lower affinity and sentiment. We then update everyone's holdings and their conviction for each proposal.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Model next steps\n",
"\n",
"The the model described above is the third iteration model that covers the core mechanisms of the Aragon Conviction Voting model. Below are next additional dynamics we can attend to enrich the model, and provide workstreams for subsequent iterations of this lab notebook.\n",
"\n",
"* Add a uniswap instance\n",
" * A next step to model the 1Hive ecosystem would be to model the Uniswap interface. With this interface, agents would be able to add or remove liquidity, buy or redeem Honey for more voting power, and ultimately enter or leave the system. \n",
"* Mixing of token holdings among participants\n",
" * Introducing heterogeneous token holdings would be another next step in creating a model more representative of the live system.\n",
"* Proposals which are good or no good together\n",
" * Introducing conflict \n",
"* Affects of outcomes on sentiment"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Simulation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Configuration\n",
"Let's factor out into its own notebook where we review the config object and its partial state update blocks."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Params (config.py) : {'beta': 0.2, 'rho': 0.0025, 'alpha': 0.875, 'gamma': 0.001, 'sensitivity': 0.75, 'tmin': 1, 'min_supp': 1, 'base_completion_rate': 45, 'base_failure_rate': 180, 'base_engagement_rate': 0.3, 'lowest_affinity_to_support': 0.3}\n"
]
}
],
"source": [
"from model import config"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# pull out configurations to illustrate\n",
"sim_config,state_variables,seeds,partial_state_update_blocks = config.get_configs()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'N': 1,\n",
" 'T': range(0, 100),\n",
" 'M': {'beta': 0.2,\n",
" 'rho': 0.0025,\n",
" 'alpha': 0.875,\n",
" 'gamma': 0.001,\n",
" 'sensitivity': 0.75,\n",
" 'tmin': 1,\n",
" 'min_supp': 1,\n",
" 'base_completion_rate': 45,\n",
" 'base_failure_rate': 180,\n",
" 'base_engagement_rate': 0.3,\n",
" 'lowest_affinity_to_support': 0.3},\n",
" 'subset_id': 0,\n",
" 'subset_window': deque([0, None]),\n",
" 'simulation_id': 0,\n",
" 'run_id': 0}]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sim_config"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'policies': {'random': <function model.parts.system.driving_process(params, step, sL, s)>},\n",
" 'variables': {'network': <function model.parts.system.update_network(params, step, sL, s, _input)>,\n",
" 'effective_supply': <function model.parts.system.increment_supply(params, step, sL, s, _input)>}},\n",
" {'policies': {'random': <function model.parts.system.minting_rule(params, step, sL, s)>},\n",
" 'variables': {'total_supply': <function model.parts.system.mint_to_supply(params, step, sL, s, _input)>,\n",
" 'funds': <function model.parts.system.mint_to_funds(params, step, sL, s, _input)>}},\n",
" {'policies': {'completion': <function model.parts.participants.check_progress(params, step, sL, s)>},\n",
" 'variables': {'sentiment': <function model.parts.participants.update_sentiment_on_completion(params, step, sL, s, _input)>,\n",
" 'network': <function model.parts.participants.complete_proposal(params, step, sL, s, _input)>}},\n",
" {'policies': {'release': <function model.parts.proposals.trigger_function(params, step, sL, s)>},\n",
" 'variables': {'funds': <function model.parts.proposals.decrement_funds(params, step, sL, s, _input)>,\n",
" 'sentiment': <function model.parts.proposals.update_sentiment_on_release(params, step, sL, s, _input)>,\n",
" 'network': <function model.parts.proposals.update_proposals(params, step, sL, s, _input)>}},\n",
" {'policies': {'participants_act': <function model.parts.participants.participants_decisions(params, step, sL, s)>},\n",
" 'variables': {'network': <function model.parts.participants.update_tokens(params, step, sL, s, _input)>}}]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"partial_state_update_blocks"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Parameters\n",
"\n",
"Initial values are the starting values for the simulation."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'initial_sentiment': 0.6,\n",
" 'n': 30,\n",
" 'm': 7,\n",
" 'initial_funds': 4867.21,\n",
" 'supply': 22392.22}"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"initial_values"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$n$ is initial participants, whereas $m$ is initial proposals.\n",
"\n",
"Sim_config holds the global hyperparameters for the simulations"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'beta': 0.2,\n",
" 'rho': 0.0025,\n",
" 'alpha': 0.875,\n",
" 'gamma': 0.001,\n",
" 'sensitivity': 0.75,\n",
" 'tmin': 1,\n",
" 'min_supp': 1,\n",
" 'base_completion_rate': 45,\n",
" 'base_failure_rate': 180,\n",
" 'base_engagement_rate': 0.3,\n",
" 'lowest_affinity_to_support': 0.3}"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sim_config[0]['M']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Hyperparameter explanations:\n",
"* $\\beta$ = .2 Upper bound on share of funds dispersed in the example Trigger Function\n",
"* $\\rho$ = 0.002 Scale Parameter for the example Trigger Function\n",
"* $\\alpha$ : 0.875 The decay rate for previously accumulated conviction\n",
"* $\\gamma$: 0.001 The expansion of supply per per day\n",
"* sensitivity of participant decisions to changes in affinity \n",
"* tmin = 1 unit days; minimum periods passed before a proposal can pass\n",
"* min_supp = 50 number of tokens that must be stake for a proposal to be a candidate\n",
"* base_completion_rate': 45, \n",
"* base_failure_rate': [180],\n",
"* base_engagement_rate' :[0.3],\n",
"* lowest_affinity_to_support': [0.3],"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Initialization\n",
"Now we will initialize our model's state variables. "
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"# initialize \n",
"network = initialize_network(initial_values['n'],initial_values['m'],\n",
" initial_values['initial_funds'],\n",
" initial_values['supply'],sim_config[0]['M'])\n",
"initial_funds = initial_values['initial_funds']\n",
"\n",
"genesis_states = { \n",
" 'network': network,\n",
" 'funds':initial_values['initial_funds'],\n",
" 'sentiment': initial_values['initial_sentiment'],\n",
" 'effective_supply': initial_values['supply']-initial_values['initial_funds'],\n",
" 'total_supply': initial_values['supply']\n",
"\n",
"}\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Exploring the State Data Structure\n",
"\n",
"A graph is a type of temporal data structure that evolves over time. A graph $\\mathcal{G}(\\mathcal{V},\\mathcal{E})$ consists of vertices or nodes, $\\mathcal{V} = \\{1...\\mathcal{V}\\}$ and is connected by edges $\\mathcal{E} \\subseteq \\mathcal{V} \\times \\mathcal{V}$.\n",
"\n",
"See *Schema of the states* above for more details\n",
"\n",
"\n",
"Let's explore!"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"# To explore our model prior to the simulation, we extract key components from our networkX object into lists.\n",
"proposals = get_nodes_by_type(network, 'proposal')\n",
"participants = get_nodes_by_type(network, 'participant')\n",
"supporters = get_edges_by_type(network, 'support')\n",
"influencers = get_edges_by_type(network, 'influence')\n",
"competitors = get_edges_by_type(network, 'conflict')"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'type': 'participant',\n",
" 'holdings': 1304.342249620273,\n",
" 'sentiment': 0.9095416561915247}"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#sample a participant\n",
"network.nodes[participants[0]]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'Count of Participants')"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Let's look at the distribution of participant holdings at the start of the sim\n",
"plt.hist([ network.nodes[i]['holdings'] for i in participants])\n",
"plt.title('Histogram of Participants Token Holdings')\n",
"plt.xlabel('Amount of Honey')\n",
"plt.ylabel('Count of Participants')\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Participants Social Network')"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"nx.draw_spring(network, nodelist = participants, edgelist=influencers)\n",
"plt.title('Participants Social Network')"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'type': 'proposal',\n",
" 'conviction': 0,\n",
" 'status': 'candidate',\n",
" 'age': 0,\n",
" 'funds_requested': 2122.1789148984158,\n",
" 'trigger': inf}"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#lets look at proposals\n",
"network.nodes[proposals[0]]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Proposals initially start without any conviction, and with the status of a candidate. If the proposal's amount of conviction is greater than it's trigger, then the proposal moves to active and it's funds requested are granted. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"All initial proposal start with 0 conviction and state 'candidate'we can simply examine the amounts of funds requested"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"funds_array = np.array([ network.nodes[i]['funds_requested'] for i in proposals])\n",
"conviction_required = np.array([trigger_threshold(r, initial_funds, supply, alpha,sim_config[0]['M']) for r in funds_array])"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'Amount of Honey requested(as a Fraction of Funds available)')"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.bar( proposals, funds_array/initial_funds)\n",
"plt.title('Bar chart of Proposals Funds Requested')\n",
"plt.xlabel('Proposal identifier')\n",
"plt.ylabel('Amount of Honey requested(as a Fraction of Funds available)')"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'Amount of Conviction')"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.bar( proposals, conviction_required)\n",
"plt.title('Bar chart of Proposals Conviction Required')\n",
"plt.xlabel('Proposal identifier')\n",
"plt.ylabel('Amount of Conviction')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Conviction is a concept that arises in the edges between participants and proposals in the initial conditions there are no votes yet so we can look at that later however, the voting choices are driven by underlying affinities which we can see now."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 55.73999999999998, 'Participant_id')"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1440x360 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"m = len(proposals)\n",
"n = len(participants)\n",
"\n",
"affinities = np.empty((n,m))\n",
"for i_ind in range(n):\n",
" for j_ind in range(m):\n",
" i = participants[i_ind]\n",
" j = proposals[j_ind]\n",
" affinities[i_ind][j_ind] = network.edges[(i,j)]['affinity']\n",
"\n",
"dims = (20, 5)\n",
"fig, ax = plt.subplots(figsize=dims)\n",
"\n",
"sns.heatmap(affinities.T,\n",
" xticklabels=participants,\n",
" yticklabels=proposals,\n",
" square=True,\n",
" cbar=True,\n",
" cmap = plt.cm.RdYlGn,\n",
" ax=ax)\n",
"\n",
"plt.title('Affinities between participants and proposals')\n",
"plt.ylabel('Proposal_id')\n",
"plt.xlabel('Participant_id')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Run simulation\n",
"\n",
"Now we will create the final system configuration, append the genesis states we created, and run our simulation."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"from cadCAD.configuration import Experiment\n",
"\n",
"# Create configuration\n",
"exp = Experiment()\n",
"\n",
"exp.append_configs(\n",
" sim_configs=sim_config,\n",
" initial_state=genesis_states,\n",
" seeds=seeds,\n",
" partial_state_update_blocks=partial_state_update_blocks\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" ___________ ____\n",
" ________ __ ___/ / ____/ | / __ \\\n",
" / ___/ __` / __ / / / /| | / / / /\n",
"/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /\n",
"\\___/\\__,_/\\__,_/\\____/_/ |_/_____/\n",
"by cadCAD\n",
"\n",
"Execution Mode: local_proc\n",
"Configuration Count: 2\n",
"Dimensions of the first simulation: (Timesteps, Params, Runs, Vars) = (100, 11, 1, 5)\n",
"Execution Method: local_simulations\n",
"SimIDs : [0, 1]\n",
"SubsetIDs: [0, 0]\n",
"Ns : [0, 0]\n",
"ExpIDs : [0, 0]\n",
"Total execution time: 253.60s\n"
]
}
],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"from model.parts.utils import *\n",
"from model import run\n",
"from cadCAD import configs\n",
"pd.options.display.float_format = '{:.2f}'.format\n",
"\n",
"%matplotlib inline\n",
"\n",
"rdf = run.run(configs)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"After the simulation has run successfully, we perform some postprocessing to extract node and edge values from the network object and add as columns to the pandas dataframe. For the rdf, we take only the values at the last substep of each timestep in the simulation."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"df= run.postprocessing(rdf,0)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
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"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>network</th>\n",
" <th>funds</th>\n",
" <th>sentiment</th>\n",
" <th>effective_supply</th>\n",
" <th>total_supply</th>\n",
" <th>simulation</th>\n",
" <th>subset</th>\n",
" <th>run</th>\n",
" <th>substep</th>\n",
" <th>timestep</th>\n",
" <th>...</th>\n",
" <th>funds_requested</th>\n",
" <th>share_of_funds_requested</th>\n",
" <th>share_of_funds_requested_all</th>\n",
" <th>triggers</th>\n",
" <th>conviction_share_of_trigger</th>\n",
" <th>age</th>\n",
" <th>age_all</th>\n",
" <th>conviction_all</th>\n",
" <th>triggers_all</th>\n",
" <th>conviction_share_of_trigger_all</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
" <td>4889.60</td>\n",
" <td>0.60</td>\n",
" <td>14020.01</td>\n",
" <td>22414.61</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>[1323.341149127691, 2079.632146915326, 1125.26...</td>\n",
" <td>[0.002499835738457735]</td>\n",
" <td>[0.27064392758061434, 0.42531724531884846, 0.2...</td>\n",
" <td>[7189.420999356341]</td>\n",
" <td>[0.011546133692685135]</td>\n",
" <td>[1]</td>\n",
" <td>[1, 1, 1, 1, 1, 1, 1, 1, 1]</td>\n",
" <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 83.01...</td>\n",
" <td>[inf, inf, inf, inf, inf, inf, inf, 11467.5110...</td>\n",
" <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.011...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
" <td>4912.02</td>\n",
" <td>0.60</td>\n",
" <td>14020.01</td>\n",
" <td>22437.03</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
" <td>...</td>\n",
" <td>[1323.341149127691, 2079.632146915326, 1125.26...</td>\n",
" <td>[0.002488428438644818, 0.044972996729207036]</td>\n",
" <td>[0.26940891986512255, 0.4233764292650907, 0.22...</td>\n",
" <td>[7188.58371621743, 11698.210005037909]</td>\n",
" <td>[0.03424941411142155, 0.007216295459532184]</td>\n",
" <td>[2, 1]</td>\n",
" <td>[2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1]</td>\n",
" <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 246.2...</td>\n",
" <td>[nan, nan, nan, nan, nan, nan, nan, nan, 7188....</td>\n",
" <td>[nan, nan, nan, nan, nan, nan, nan, nan, 0.034...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
" <td>4934.45</td>\n",
" <td>0.60</td>\n",
" <td>14020.01</td>\n",
" <td>22459.46</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>[1323.341149127691, 2079.632146915326, 1125.26...</td>\n",
" <td>[0.0024771135216868838, 0.04476850391943287, 0...</td>\n",
" <td>[0.26818391395028074, 0.42145133105262617, 0.2...</td>\n",
" <td>[7187.753385508128, 11667.116998689173, 7353.6...</td>\n",
" <td>[0.25121382811760656, 0.01445417243194367, 0.0...</td>\n",
" <td>[3, 2, 1]</td>\n",
" <td>[3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 1]</td>\n",
" <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1805....</td>\n",
" <td>[nan, nan, nan, nan, nan, nan, nan, nan, 7187....</td>\n",
" <td>[nan, nan, nan, nan, nan, nan, nan, nan, 0.251...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
" <td>4956.91</td>\n",
" <td>0.60</td>\n",
" <td>14105.76</td>\n",
" <td>22481.92</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>...</td>\n",
" <td>[1323.341149127691, 2079.632146915326, 1125.26...</td>\n",
" <td>[0.002465889875439541, 0.044565660631624114, 0...</td>\n",
" <td>[0.2669687894301271, 0.41954176146334665, 0.22...</td>\n",
" <td>[7186.929921405335, 11636.398103183781, 7352.0...</td>\n",
" <td>[0.4718002394320366, 0.036870444922324656, 0.5...</td>\n",
" <td>[4, 3, 2, 1]</td>\n",
" <td>[4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 2, 1]</td>\n",
" <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3390....</td>\n",
" <td>[nan, nan, nan, nan, nan, nan, nan, nan, 7186....</td>\n",
" <td>[nan, nan, nan, nan, nan, nan, nan, nan, 0.471...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
" <td>4979.40</td>\n",
" <td>0.60</td>\n",
" <td>14198.92</td>\n",
" <td>22504.41</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>...</td>\n",
" <td>[1323.341149127691, 2079.632146915326, 1125.26...</td>\n",
" <td>[0.0024547564055378895, 0.044364447087486845, ...</td>\n",
" <td>[0.26576342782359114, 0.41764753430411256, 0.2...</td>\n",
" <td>[7230.064355326959, 11677.03065066607, 7395.40...</td>\n",
" <td>[0.7248171201716649, 0.10100657554367327, 1.02...</td>\n",
" <td>[5, 4, 3, 2]</td>\n",
" <td>[5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 3, 2, 1]</td>\n",
" <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5240....</td>\n",
" <td>[nan, nan, nan, nan, nan, nan, nan, nan, 7230....</td>\n",
" <td>[nan, nan, nan, nan, nan, nan, nan, nan, 0.724...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 33 columns</p>\n",
"</div>"
],
"text/plain": [
" network funds sentiment \\\n",
"5 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4889.60 0.60 \n",
"10 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4912.02 0.60 \n",
"15 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4934.45 0.60 \n",
"20 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4956.91 0.60 \n",
"25 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4979.40 0.60 \n",
"\n",
" effective_supply total_supply simulation subset run substep \\\n",
"5 14020.01 22414.61 0 0 1 5 \n",
"10 14020.01 22437.03 0 0 1 5 \n",
"15 14020.01 22459.46 0 0 1 5 \n",
"20 14105.76 22481.92 0 0 1 5 \n",
"25 14198.92 22504.41 0 0 1 5 \n",
"\n",
" timestep ... funds_requested \\\n",
"5 1 ... [1323.341149127691, 2079.632146915326, 1125.26... \n",
"10 2 ... [1323.341149127691, 2079.632146915326, 1125.26... \n",
"15 3 ... [1323.341149127691, 2079.632146915326, 1125.26... \n",
"20 4 ... [1323.341149127691, 2079.632146915326, 1125.26... \n",
"25 5 ... [1323.341149127691, 2079.632146915326, 1125.26... \n",
"\n",
" share_of_funds_requested \\\n",
"5 [0.002499835738457735] \n",
"10 [0.002488428438644818, 0.044972996729207036] \n",
"15 [0.0024771135216868838, 0.04476850391943287, 0... \n",
"20 [0.002465889875439541, 0.044565660631624114, 0... \n",
"25 [0.0024547564055378895, 0.044364447087486845, ... \n",
"\n",
" share_of_funds_requested_all \\\n",
"5 [0.27064392758061434, 0.42531724531884846, 0.2... \n",
"10 [0.26940891986512255, 0.4233764292650907, 0.22... \n",
"15 [0.26818391395028074, 0.42145133105262617, 0.2... \n",
"20 [0.2669687894301271, 0.41954176146334665, 0.22... \n",
"25 [0.26576342782359114, 0.41764753430411256, 0.2... \n",
"\n",
" triggers \\\n",
"5 [7189.420999356341] \n",
"10 [7188.58371621743, 11698.210005037909] \n",
"15 [7187.753385508128, 11667.116998689173, 7353.6... \n",
"20 [7186.929921405335, 11636.398103183781, 7352.0... \n",
"25 [7230.064355326959, 11677.03065066607, 7395.40... \n",
"\n",
" conviction_share_of_trigger age \\\n",
"5 [0.011546133692685135] [1] \n",
"10 [0.03424941411142155, 0.007216295459532184] [2, 1] \n",
"15 [0.25121382811760656, 0.01445417243194367, 0.0... [3, 2, 1] \n",
"20 [0.4718002394320366, 0.036870444922324656, 0.5... [4, 3, 2, 1] \n",
"25 [0.7248171201716649, 0.10100657554367327, 1.02... [5, 4, 3, 2] \n",
"\n",
" age_all \\\n",
"5 [1, 1, 1, 1, 1, 1, 1, 1, 1] \n",
"10 [2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1] \n",
"15 [3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 1] \n",
"20 [4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 2, 1] \n",
"25 [5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 3, 2, 1] \n",
"\n",
" conviction_all \\\n",
"5 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 83.01... \n",
"10 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 246.2... \n",
"15 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1805.... \n",
"20 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3390.... \n",
"25 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5240.... \n",
"\n",
" triggers_all \\\n",
"5 [inf, inf, inf, inf, inf, inf, inf, 11467.5110... \n",
"10 [nan, nan, nan, nan, nan, nan, nan, nan, 7188.... \n",
"15 [nan, nan, nan, nan, nan, nan, nan, nan, 7187.... \n",
"20 [nan, nan, nan, nan, nan, nan, nan, nan, 7186.... \n",
"25 [nan, nan, nan, nan, nan, nan, nan, nan, 7230.... \n",
"\n",
" conviction_share_of_trigger_all \n",
"5 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.011... \n",
"10 [nan, nan, nan, nan, nan, nan, nan, nan, 0.034... \n",
"15 [nan, nan, nan, nan, nan, nan, nan, nan, 0.251... \n",
"20 [nan, nan, nan, nan, nan, nan, nan, nan, 0.471... \n",
"25 [nan, nan, nan, nan, nan, nan, nan, nan, 0.724... \n",
"\n",
"[5 rows x 33 columns]"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f2f1fd59150>"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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Cz8tFT2q1xYLxfWKRJXV0wt/DAHjqpXYmNURZNn9qxfdVKx76riO9zGpqpCkRD7QdtUI8NrpaoBbnKpyc5eJDhJ7JGjJZO+yu8PcwAJ56qYMLFs+oygnkRYK1EKFrdD5MfMQM3kzWkDXhX3XeL0SExpg/y9B5d0k23B3p2eUzB7sH2XWkryr+OTgzEqEGPPT2Pk5RQc/hCbcnJjlRUUEvGL8Wivbukmy4Owp/D6vMul3tQHX8c6gND/3IsSE6+5IsOUlz0D28C61nhSVzgh7+KNEvGuP+rCvqzdi1YVA0/D2sMs++3MXkxhhLq7TifbQGarls298NwNlVGDOoFxpGRugWiYpfJOIRX9IWvYuqDXdH4e9hlWnd383SuVOIRKoTiXkeepDVFlv3OYK+dF51LmL1gFdjxzsuNomKXzTGor4MinpljNVyUYoikzXsOHCsqsLm3dpnAvTQt+7rZtHMiUzRDJccnrWSVA+9ZJxBUf889LgFd0fh72EV2d3ey0AqU1XroRbK527b16N2ywjiuQjdERP10Isn4ZeHnhsUDf93r4LuI637ewA4q4oRejTgQdGjfUn2dQ2ooI9gOMvFs1zsue33C9+yXCwavwh/D6tI6/4eGmKRqmZ7DM9IDEbQcwOi81TQ84nnsly8QVH10IvF9zx0C7778PewirTu7+aMOU1VPXGiAXvo2/Y5dyVnz9cB0XxG5qHb5OP6hW+DoiroSrEYY9i2r6eqdgvkzUgMyHLZtr+blukTmDaxIZD91yrHs1zUQy+cRDziSy0XtVyUotnXNUD3QIqlVbYegvbQt+3rVrtlDEbO4FUPvXj8itC9i6oN3334e1glghgQhWDz0LsHUrzc0c+yFhX0kXji4UWHNvm4ftHo28Qie7778PewSrTu6yYicOac6gp6NMBaLtsDuojVA8MRujv1XwdFiyYRj/qyYpFaLkrRtO7v4dRZk5nQUNkVikYSZB76tn065f94HK84lw2i4hfexCJjyju3bZoDoGeXT7Tur/6AKOQV5wrActm2v5u5UxM0T26s+r5rnXhE89DLpTEWIWvKD1Zs+u7D38Mq0N47xMGewUAi1SCLc23d181ZOiA6Jl7t7VHlcy2oye0X3nq85U4usslyKWgJOuXEeAOiQRSnEhGiEfHVQ99xoIfr/uP34/6QBlNZVp8zz7f9homc5ZL28tDVQy+W4YWiszSV8Tk2DYqqoPtAqztb8qy5wUSrjqD7F6E/s6eTrv4U11+8KPejGotYVLjugoW+7TdMeFZYKjcoao+o+EVjzF0ouszZojZVulRB94E/HOpl7tQEUycGU20wHhFfPfTd7X1MbIhy+1VLEVGLoBREhHhURg+KWiAqftEYdxeKLtNyGUrroKhSBEGvp+l3hL67vY9FMyepmJdJLBLJVVtMWSQqfpGL0MtMXfQW57bhfFZB94E9HX0sClDQY9GIrzNFd7f3sXiWrg9aLk6EPpzlIjI8iK2Mjxehlzu5KJnOWnMhVUEvk67+JF39KRbPDDpC92dQNJnOsrezXxd89oF4NJJXnMsQtyRK9IuEbx561ooMF1BBL5vd7X0AgUbo8Yj4NvV/79F+soZALaSwkC/o3m2/Ujh+eeipTNaKAVFQQS+bPR2OoC9unhhYG6JR8c1y2X0k+AtUWIhFJW9NUXtu+/0iP22xHIbSKuhKgexu7ycisGBGcIIei0R8GxT17jjUcimfhmjkVWuK2iIqfuFNLPIjbfFE6bdhwo5eVpA97X3MmzYhNyIfBNGIjxF6Rx/TJ8a1vrkPxPLSFpNpo4JeJJ4Il225aISuFMqejmBTFsGZxOIJR7nsPhJsxk6YiEcjr7JcbBmY8wu/JhYlM1lrSi4UdIaJyOUi8oKI7BSRW8Z4faGIPCEiz4nIFhG50v+m1h7GmFzOdpDE/PTQA86pDxPxUZaLHaLiFwkvbdGHQVFbBqTH7aWIRIG7gCuApcB1IrJ0xGafAh40xpwLXAv8m98NrUU6+5IcG0wHHtFGffLQ+5NpDvYMqn/uE/FRg6J2iIpf+Bahq+XyKi4AdhpjdhljksADwNUjtjGAV5lqKrDfvybWLl6Gy6KZwQ2IgmO5+BGh72nvB2Bx8+SyP0sZOw9dKZx4VBApP0JPWmR3FdLL+cDevMdt7nP5fAZ4j4i0AWuBj4z1QSJyg4hsEJENR44cKaG5tcVuVwCDj9D98dCHc+qDvUCFhVg0kivOlUrbc9vvFyJCIhb1Z2KRJd+9X728DrjPGNMCXAl8X0RGfbYx5m5jzEpjzMpZs2b5tOvg2NPe56QsTg9WAOM+eei723sBAh8TCAsNUcnVcElZNDDnJ43xiA9ZLvbcHRXSy33AgrzHLe5z+XwAeBDAGLMOSADNfjSwltnd0UfL9ImB38755aHvau9jzpQEkxq1CKcfOPMDNA+9HJxl6PzIcrHjuy+kl88Ap4nIYhFpwBn0XDNim1eANwGIyJk4gl7/nso47GmvjRQ//zx0zXDxk3gskivOlcwYa277/SQRL99ySVpkd43bS2NMGrgReAzYgZPN0ioid4rIanezjwMfFJHNwP3A9abclV1rHGOMI4ABD4iCf+Vzd9fIBSosxCOvroduS5ToJ40xHyyXTJYGS+yugu6tjTFrcQY785+7Le/v7cBr/W1abXOkd4i+ZKYmBNBJjysviunqT3K0P6Upiz6ixbnKp9GHQdGkRXaXHb2sAHtqJMMFHA+9XMvFy3BRy8U/Yvn10C2qye0niXik7HroNmUY2dHLCrDHE8AayAiJ+WC55HLqVdB9Q/PQy6cxFmWw7BWLjDV2l6YzuGzY08lLR3oL3v7X2w8Tiwgt0ydUsFWF4Udxrv1dgwDMnxZ8f8JCQ+zVlosKevE0xiJ0DSRLfr8xxirLRQUd56C/7zvPcGwoXdT7zmmZSqwGThQ/inMd6B5g2sQ4ExqCqxoZNmJ5C48k0/bMVvSTRDxa1pqinuVlS/lcFXSgZyDNsaE0H33TaVz7mgXjv8FlxqTaKDHrR3GuA12DzJ2q0bmfxKPO/ABjjBbnKpHGWITBMjx0L9Cx5btXQQcO9AwAcPrsycyrQ8vBjwUuDnQPMndqwqcWKTAsIkPpLOmseuil0BiPlBWhJ9OeoNvx3dvRy3E40O34x/UqaH546Ad7BplTp/2vVTwRGUhmXvVYKZxy0xa9CN0Wu8uOXo7DQVfQZ0+pT0FzslxKP+kHUxk6+5LMU0H3FW98pd+dGGNL6pyflFvLJZnRCN06DnYPIgInNdWnoOUvRlwK3gVtjnrovtLgWi797mC7LT6un3gReqkTzz3LxZaLqR29HIeD3YM0T26s29syrzhXqSd9vVtOtYoXofd5lkudnl9B4q1alCwxi8vLcqnX33ax2NHLcTjQU98DgrGIE/mVaqMfdAeF6/k7qEW82/z+ZPpVj5XC8VYtKnVyUUotF/s41D1Yt/45OIOiQMk+ujepSAdF/SWes1zUQy8VL3+81On/Q2lNW7SOA90DrDplRtDNKBkvQk9nDKWUMj/YPcjUCXEmNujp4CfxEYOitkSJfuIJ+rv+Y33B318sInxm9Vmcf/J067JcrP8F9w2l6RlM13V06nm1peaiaw56ZcgJug6KlszFS5p52/K5RaUuPr7jEP/z4pFXC7olF1PrBf1gT/0PCHoReqm56Ae6B+q6/7VKzLNcdFC0ZOZPm8A33nVeUe95zT8/ziF3oF8nFlnGoTrPQYfyPfSD3YOaslgBGkYMitoSJQbNnCkJDh1zfte2WS529PIEDKfs1a+glROhD6YydOikoorgHRcvQrdFVIJm9pTG3NyKpJu2qBG6JXiWy5w6jtBzHnoJk4sO9WiGS6XwLJZ+nfpfVWZPSeTOa51YZBlhKBuby3IpIUIPwx1KrRKPuBOLdFC0qsyZkuBof4qhdEYtF9s42D1U19E5DHvomRI8dO/WdO60+v4OapG4uzCx1nKpLt542OGeIevK51p/hh3sGah7u6GcCH1/tzNLtN4varVILDIybdH6n1tVmO3+ng/2DA5nuWiEbgcHQ5CDHc2bWFQsB7sHmZKIMamUGUnKCRnOctG0xWriBSeHegZzNWBsuTuyo5fHIZnO0t6bZM6U+vaP42VMLDrQPViXi3rUAznLJTcoasdtf9DMntIIOMFKKq1ZLtZwKASTiqA8D/1Ad/1bTrVKznLRPPSqMnVCnMZYxI3QM0QjkvuNhB2rzzAvZXF2nQtarEzLpd4vaLXKKMtFBb0qiAhzpiY41DNEKmOsupDa09MxCEsd8GiJE4uG0hnae5OaslghRk39t0hYgmZ2UyI3KGqT1WX1GXaoOxyTaryJRakiBf1Q9xBQ//2vVTwB1zz06jN7aiI3KGpLDjpYLugHugeZ1BClqc4zPGIleugHunVhi0riCXg6a4hHBREV9GoxZ0qjI+jprFoutnCwZ4DZUxN1/0MrNW1xuNKkWi6VQERyF1u1W6rL7CkJBlNZOnqHrEoXLainInK5iLwgIjtF5JYxXv+KiGxy/70oIl3+N9V/wjIg6Hm1xXroB0NiOdUy3rFRQa8u3mzRvUcHrPrux+2piESBu4ArgKXAdSKyNH8bY8xNxpgVxpgVwNeBhyvRWD/IZg3pTJZ0JuuUja3zHHQYtlyK9dA7+pI0xiJMquM6NrWOJyY2iUot4AUpezv7rbJcCjGPLwB2GmN2AYjIA8DVwPbjbH8dcLs/zfOXgWSG1/3LE7T3DuWemxeCGiZevnOxHnpHb5KZkxrq3nKqZTwhb9AB0aoyu8n5XQ+ls1ZZLoUI+nxgb97jNmDVWBuKyMnAYuC/jvP6DcANAAsXLiyqoX6wv3uA9t4h3rp8LmfMbiISEf7svJaqt8NvSvXQO/qGmDm5sRJNUly8gVGbRKUWOGnK8Hlt08XU7/SOa4GHjDFjLtFtjLkbuBtg5cqVpa2XVgadfUkArlm5gD8+fVa1d18xSvXQO/uSzJjUUIkmKS5quQRDIh5l+sQ4R/tTmrY4gn3AgrzHLe5zY3EtcH+5jaoUHb2OoIdNxKIlVlv0LBelcqigB4c3MGrTd19IT58BThORxSLSgCPaa0ZuJCJnANOBdf420T+8CH3m5HCJmLeQQjpTnIeuEXrl8SwXm277awUV9DEwxqSBG4HHgB3Ag8aYVhG5U0RW5216LfCAMabqVkqhHO13BH36xHCJWDRafITen0wzkMqoh15hvAFrm277awWvjK5N331BHroxZi2wdsRzt414/Bn/mlUZOnqTTGqIkoiHK02vlEWiPftJLZfK4g2G2hQl1gpeGV2b0hbt6SnQ2TfEjJDZLVCah+7ZT2q5VJa4zhQNDK+Kqk01dKw6yzr6ksyYFD6LIZbz0EsQ9BBe4GoJHRQNDhstF3t6iiNiYbQYohFBpLiJRR2uoDeH8AJXS3gppQ0xe6LEWkEHRUPO0RBndcQiUpTl0uHOltUIvbI0aIQeGJ6gq4ceQowxruUSTgGLRqSoQdHOviQNWsel4mhxruCYOamB5skNOWG3gfouBF4E/ckMQ+lsaAU9FokUF6H3aR2XaqAeenBEIsJvPn6pVUGLNYIe9qyOWFSKmljU2ZcM3QSrWqRBi3MFytQJ8aCbUFWsCRu8QcAwDopCaR56GDN+ag21XJRqYs1ZdtQV9OkhFfRiPfSOkGb81Bo5y8Wi1DklOKw5y8IfoRfnoWsdl+qgHrpSTaw5yzr73DS9kIpYMR76QDJDfzKjHnoV0OJcSjWxRtA7+pI0RCNMbgznOHC0CA+9w724hfVupZaIaYSuVBFrzrLOXsdiCGuaXqwID30440cHRSuNWi5KNbHmLOvsS4Z2QBQgWoSH3hHyFM5aIlecSwdFlSpgzVnW2R/urI6iInS3dG6zeugVxxNy9dCVamCPoIc8qyMWFVIFDop2hHyAuJZQy0WpJtacZZ6HHlaKidDDPkBcS8R1YpFSRaw4y4bSGY4NpUNtuRST5RL2AeJaQiN0pZpYcZYd7UsB4Z0lCs7EomKyXMJ8t1JLeMsDNuqgqFIFrDjLOkM+SxSKm1jUroW5qkaDrimqVBErzrKwV1qE4opzdfYNhfriVkt4ywPatK6lEhxWCHpuZmSIo9JiinM5HtN8KfoAABBASURBVLpOKqoGuUFRtVyUKmDFWeZF6NMnhlfQCy3ONZjK0Kd1XKrGspapXLKkmVNnTQ66KYoFWJG31tmXRASmhVjQC43Qw151staYO3UCP/jrVUE3Q7EEayL06RMbiEbC62MWOrHImyUa5vEERbEVawQ97AJW6MQiG8YTFMVWrBD0DgsEvdDiXFppUVHCizUe+pKQD0qNjNC7B1Js398zartNe7sAjdAVJYwUJOgicjnwNSAK3GOM+cIY27wT+AxggM3GmHf52M6y6OxLMmNxuAVspId+x5pWHn5u35jbNiViNGkdF0UJHeP+qkUkCtwFXAa0Ac+IyBpjzPa8bU4DbgVea4w5KiInVarBxZLJGo6GvHQujI7QD/YMcsacJm6/6qxR286bltA6LooSQgoJ0y4AdhpjdgGIyAPA1cD2vG0+CNxljDkKYIw57HdDPdp7hzjcM1Tw9scGUxgT/qyOkR56z2CKedMmcNGpMwNslaIo1aQQQZ8P7M173AaMTKw9HUBEnsSxZT5jjPmlLy0cwU82tvH5//d80e+bOzVRgdbUDiMj9J6BNEtmqa2iKDbh1y8+BpwGXAq0AL8VkWXGmK78jUTkBuAGgIULF5a0o8uWzubkmZOKek9jPMIlS5pL2l+94E0sMsYgIvQMppgyIR50sxRFqSKFCPo+YEHe4xb3uXzagPXGmBSwW0RexBH4Z/I3MsbcDdwNsHLlysIKj4zglFmTOSXkGSul4NUMSWcNsQj0DKSYklBBVxSbKCQP/RngNBFZLCINwLXAmhHb/AwnOkdEmnEsmF0+tlMZh6hb1S+TNfQlM2QNTJmgloui2MS4gm6MSQM3Ao8BO4AHjTGtInKniKx2N3sM6BCR7cATwCeMMR2VarQyGm8hhXTW0DPgLOihEbqi2EVBIZwxZi2wdsRzt+X9bYCPuf+UAPDq1GQyhp5BV9DVQ1cUq7Bi6r8NeB56KpulZyANaISuKLahgh4S8j30nOWiHrqiWIUKekjI99CPDamHrig2ooIeEl7lobuWS1NCI3RFsQkV9JAQy+WhZ3OWS5NG6IpiFSroIcFbXT6ddbJcJsSjNOjCxIpiFfqLDwme5ZJ2LRcdEFUU+1BBDwneoGjGjdB1QFRR7EMFPSRE8z10LcylKFaigh4S4vke+kCaKZrhoijWoYIeEl7loWuErihWooIeEry0RW+mqHroimIfKughwYvQU9ksPYOa5aIoNqKCHhI8D/3YYJpM1miErigWooIeErwIvbPXWUBbZ4kqin2ooIcEz0Pv7NdKi4piKyroIcGL0Lv6k4BWWlQUG1FBDwneTNHOPlfQNW1RUaxDBT0kxKLOocwJuk4sUhTrUEEPCRqhK4qigh4SPA/9qOuh6+IWimIfKughwYvQj/alSMQjNMaiAbdIUZRqo4IeEjwPPZnJaoaLoliKCnpI8CJ0UP9cUWxFBT0kRPMFXf1zRbESFfSQEJVhQddp/4piJyroISESEbwgXS0XRbETFfQQ4Q2MquWiKHaiv/wQEYsISTRCV6pLKpWira2NwcHBoJsSKhKJBC0tLcTjhf+eCxJ0Ebkc+BoQBe4xxnxhxOvXA18E9rlPfcMYc0/BrVB8wRsY1bRFpZq0tbXR1NTEokWLkLyxHKV0jDF0dHTQ1tbG4sWLC37fuJaLiESBu4ArgKXAdSKydIxNf2SMWeH+UzEPAC91UUvnKtVkcHCQmTNnqpj7iIgwc+bMou96CvHQLwB2GmN2GWOSwAPA1SW0Uakwwx66RuhKdVEx959SvtNCBH0+sDfvcZv73Ej+TES2iMhDIrLgOA28QUQ2iMiGI0eOFN1Y5cQMR+gq6IpiI35luTwCLDLGLAd+DXx3rI2MMXcbY1YaY1bOmjXLp10rHsMeulouilIsmzZtYu3atbnHa9as4Qtf+MIJ3lE+//3f/81TTz3l2+cVIuj7gPyIu4XhwU8AjDEdxpgh9+E9wPn+NE8pBo3QFaV0Rgr66tWrueWWWyq6T78FvZBQ7hngNBFZjCPk1wLvyt9AROYaYw64D1cDO3xroVIwmuWiBM0dj7SyfX+Pr5+5dN4Ubr/qrBNu09fXxzvf+U7a2trIZDJ8+tOfZsmSJXzsYx+jt7eX5uZm7rvvPubOncull17KqlWreOKJJ+jq6uLee+9l1apV3HbbbQwMDPC///u/3HrrrQwMDLBhwwa+8Y1vcP311zNhwgSee+45Dh8+zLe//W2+973vsW7dOlatWsV9990HwK9+9Stuv/12hoaGOPXUU/nOd77D5MmTWbRoEe9973t55JFHSKVS/PjHPyaRSPCtb32LaDTKD37wA77+9a/zute9rqzvatwI3RiTBm4EHsMR6geNMa0icqeIrHY3+6iItIrIZuCjwPVltUopibg7KKq10BXb+OUvf8m8efPYvHkz27Zt4/LLL+cjH/kIDz30EBs3buT9738/n/zkJ3Pbp9Npnn76ab761a9yxx130NDQwJ133sk111zDpk2buOaaa0bt4+jRo6xbt46vfOUrrF69mptuuonW1la2bt3Kpk2baG9v53Of+xyPP/44zz77LCtXruTLX/5y7v3Nzc08++yz/M3f/A1f+tKXWLRoER/+8Ie56aab2LRpU9liDgXmoRtj1gJrRzx3W97ftwK3lt0apSyiEaEhFiER11roSjCMF0lXimXLlvHxj3+cm2++mbe97W1Mnz6dbdu2cdlllwGQyWSYO3dubvt3vOMdAJx//vns2bOnoH1cddVViAjLli1j9uzZLFu2DICzzjqLPXv20NbWxvbt23nta18LQDKZ5KKLLhpznw8//HDZfR4LDeVCRCwiarcoVnL66afz7LPPsnbtWj71qU/xxje+kbPOOot169aNuX1jYyMA0WiUdDpd0D6890Qikdzf3uN0Ok00GuWyyy7j/vvv922fxaK1XEJENCI6qUixkv379zNx4kTe85738IlPfIL169dz5MiRnKCnUilaW1tP+BlNTU0cO3as5DZceOGFPPnkk+zcuRNwfP0XX3yxovsciQp6iIhFI1o6V7GSrVu3csEFF7BixQruuOMO7rzzTh566CFuvvlmzjnnHFasWDFuNskb3vAGtm/fzooVK/jRj35UdBtmzZrFfffdx3XXXcfy5cu56KKLeP7550/4nquuuoqf/vSnrFixgt/97ndF73MkYowp+0NKYeXKlWbDhg2B7Dus/Kr1IFkDl589J+imKBaxY8cOzjzzzKCbEUrG+m5FZKMxZuVY2+v9eYh4y1kq5IpiM2q5KIqihAQVdEVRyiYo6zbMlPKdqqArilIWiUSCjo4OFXUf8eqhJxKJot6nHrqiKGXR0tJCW1sbWkHVX7wVi4pBBV1RlLKIx+NFraqjVA61XBRFUUKCCrqiKEpIUEFXFEUJCYHNFBWRI8DLRbylGWivUHNqGRv7bWOfwc5+29hnKK/fJxtjxlzyLTBBLxYR2XC86a5hxsZ+29hnsLPfNvYZKtdvtVwURVFCggq6oihKSKgnQb876AYEhI39trHPYGe/bewzVKjfdeOhK4qiKCemniJ0RVEU5QSooCuKooSEuhB0EblcRF4QkZ0ickvQ7akEIrJARJ4Qke0i0ioif+8+P0NEfi0if3D/nx50W/1GRKIi8pyIPOo+Xiwi693j/SMRaQi6jX4jItNE5CEReV5EdojIRZYc65vc83ubiNwvIomwHW8R+baIHBaRbXnPjXlsxeFf3b5vEZHzytl3zQu6iESBu4ArgKXAdSKyNNhWVYQ08HFjzFLgQuDv3H7eAvzGGHMa8Bv3cdj4e2BH3uP/C3zFGLMEOAp8IJBWVZavAb80xpwBnIPT/1AfaxGZD3wUWGmMORuIAtcSvuN9H3D5iOeOd2yvAE5z/90AfLOcHde8oAMXADuNMbuMMUngAeDqgNvkO8aYA8aYZ92/j+H8wOfj9PW77mbfBd4eTAsrg4i0AG8F7nEfC/BG4CF3kzD2eSrwx8C9AMaYpDGmi5Afa5cYMEFEYsBE4AAhO97GmN8CnSOePt6xvRr4nnH4PTBNROaWuu96EPT5wN68x23uc6FFRBYB5wLrgdnGmAPuSweB2QE1q1J8FfgnIOs+ngl0GWPS7uMwHu/FwBHgO67VdI+ITCLkx9oYsw/4EvAKjpB3AxsJ//GG4x9bX/WtHgTdKkRkMvAT4B+MMT35rxknxzQ0eaYi8jbgsDFmY9BtqTIx4Dzgm8aYc4E+RtgrYTvWAK5vfDXOBW0eMInR1kToqeSxrQdB3wcsyHvc4j4XOkQkjiPmPzTGPOw+fci7BXP/PxxU+yrAa4HVIrIHx0p7I463PM29JYdwHu82oM0Ys959/BCOwIf5WAO8GdhtjDlijEkBD+OcA2E/3nD8Y+urvtWDoD8DnOaOhDfgDKKsCbhNvuN6x/cCO4wxX857aQ3wXvfv9wI/r3bbKoUx5lZjTIsxZhHOcf0vY8y7gSeAP3c3C1WfAYwxB4G9IvJH7lNvArYT4mPt8gpwoYhMdM93r9+hPt4uxzu2a4C/crNdLgS686yZ4jHG1Pw/4ErgReAl4JNBt6dCfbwE5zZsC7DJ/Xcljqf8G+APwOPAjKDbWqH+Xwo86v59CvA0sBP4MdAYdPsq0N8VwAb3eP8MmG7DsQbuAJ4HtgHfBxrDdryB+3HGCFI4d2MfON6xBQQni+8lYCtOBlDJ+9ap/4qiKCGhHiwXRVEUpQBU0BVFUUKCCrqiKEpIUEFXFEUJCSroiqIoIUEFXalr3KqFf+v+PU9EHhrvPWXsa4WIXFmpz1eUclFBV+qdacDfAhhj9htj/nyc7cthBc7cAEWpSTQPXalrRMSrvvkCzqSNM40xZ4vI9TgV7SbhlCb9EtAA/CUwBFxpjOkUkVNxJnbMAvqBDxpjnheRvwBuBzI4RaTejDPxZQLO1OzPA48CXwfOBuLAZ4wxP3f3/afAVJxCSz8wxtxR4a9CUYiNv4mi1DS3AGcbY1a4VSofzXvtbJyqlQkcMb7ZGHOuiHwF+CucSo93Ax82xvxBRFYB/4ZTU+Y24E+MMftEZJoxJikit+HM5LsRQET+D065gveLyDTgaRF53N33Be7++4FnROQXxpgNlfwiFEUFXQkzTxintvwxEekGHnGf3wosdytbXgz82CktAjhT0QGeBO4TkQdxikiNxVtwiov9o/s4ASx0//61MaYDQEQexintoIKuVBQVdCXMDOX9nc17nMU59yM4tbhXjHyjMebDbsT+VmCjiJw/xucL8GfGmBde9aTzvpFepnqbSsXRQVGl3jkGNJXyRuPUm9/t+uXe+o7nuH+faoxZb4y5DWcxigVj7Osx4CNu5UBE5Ny81y5z15GcgOPlP1lKGxWlGFTQlbrGtTWedBfk/WIJH/Fu4AMishloZXh5wy+KyFb3c58CNuOUeV0qIptE5BrgsziDoVtEpNV97PE0Tm37LcBP1D9XqoFmuSiKz7hZLrnBU0WpFhqhK4qihASN0BVFUUKCRuiKoighQQVdURQlJKigK4qihAQVdEVRlJCggq4oihIS/j/+7FCj+i1B0AAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df.plot('timestep','sentiment')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The above plot demonstrates system sentiment changing over time as proposals pass or fail."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f2f1f7d1ad0>"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df.plot('timestep',['funds', 'candidate_funds'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Funds represent the total available funds, whereas candidate funds represent total funds requested by candidate proposals."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 612x792 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"affinities_plot(df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The above matrix represents participant affinities towards proposals, ranging from -1 to +1."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7f2ed03469d0>"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df.plot(x='timestep',y=['candidate_count','active_count','completed_count', 'killed_count', 'failed_count'],\n",
" kind='area')\n",
"plt.title('Proposal Status')\n",
"plt.ylabel('count of proposals')\n",
"plt.legend(ncol = 3,loc='upper center', bbox_to_anchor=(0.5, -0.15))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The above graph shows the number of various types of proposals at a range of timesteps. Ecosystems with more completed proposals will have higher overall agent sentiment than systems with more failed and killed proposals."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7f2ed1146fd0>"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df.plot(x='timestep',y=['candidate_funds','active_funds','completed_funds', 'killed_funds', 'failed_funds'], kind='area')\n",
"plt.title('Proposal Status weighted by funds requested')\n",
"plt.ylabel('Funds worth of proposals')\n",
"plt.legend(ncol = 3,loc='upper center', bbox_to_anchor=(0.5, -0.15))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The above graph shows the amount of funds requested by various types of proposals at a range of timesteps."
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"nets = df.network.values"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"K = 0\n",
"N = 1\n",
"\n",
"snap_plot(nets[K:N], size_scale = 1/300,savefigs=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On the left side are participants, with the right side of the graph being the proposals. With this graph, we can see the links between the participants and the proposals that they support. The percentage on the right hand are the the amount of the required amount to pass that has been fulfilled.\n",
"\n",
"You can move the K and N to different points within the 100 timesteps, 0 indexed, to see how the model evolves overtime. \n",
"\n",
"As you can see with the plot above at the start of the simulation, no proposals have been formally supported yet. Below we can see a many interactions between agents and proposals."
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"snap_plot(nets[80:81], size_scale = 1/300,savefigs=True)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f2ed2ad22d0>"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df.plot('timestep',['effective_supply'])"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f2f1fce18d0>"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df.plot('timestep',['participant_count'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As expected *effective_supply* is increasing with the arrival of new participants."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Conclusion\n",
"\n",
"We have created a conviction voting model that closely adheres to the 1Hive implementation. This notebook describes the use case, how the model works, and provides descriptions of how it fits together."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}