1790 lines
743 KiB
Plaintext
1790 lines
743 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Aragon Conviction Voting Model - Version 3\n",
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"\n",
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"New to this version 3 model are the following elements:\n",
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"\n",
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"* Adding the realism that not all participant tokens are being allocated to proposals at each timestep.\n",
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"* Refactored parameters and system initialization to make more readable and consistent.\n",
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"* Changed file structure and file names to align with emerging cadCAD standards.\n",
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"* Making the distinction between effective and total supply.\n",
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"* 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",
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"* Updated differential specification and write-up to respect new state variables\n",
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"* Moved all unit denominations to Honey, the 1Hive governance token.\n",
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"* Added system health metrics\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# An Introduction to Conviction Voting\n",
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"\n",
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"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",
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"\n",
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"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",
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"\n",
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"\n",
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"## The Word Problem\n",
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"\n",
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"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",
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"\n",
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"## Converting to a Math Problem\n",
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"\n",
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"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",
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"\n",
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"### Participants\n",
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"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",
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"\n",
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"### Proposals & Shared Resources\n",
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"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",
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"\n",
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"### Participants Preferences for Proposals\n",
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"\n",
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"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",
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"\n",
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"\n",
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"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",
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"\n",
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"\n",
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"## Aggregating Information\n",
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"\n",
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"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",
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"\n",
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"### Participants Allocate Voting Power\n",
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"\n",
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"\n",
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"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",
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"\n",
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"### System Accounts Proposal Conviction\n",
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"\n",
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"\n",
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"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",
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"\n",
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"### Understanding Alpha\n",
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"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. Alpha from solidity code is defined as: \n",
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"```uint256 _decay = 9999599; // 3 days halftime. halftime_alpha = (1/2)**(1/t)```\n",
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"Half life associated with solidity code alpha (in number of blocks on xDai). \n",
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"\n",
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"The half-life of this system is defined by $T$ such that $y_T = y_0/2$ which satisfies the equation\n",
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"\n",
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"$\\frac{1}{2} = \\alpha^T$\n",
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"\n",
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"thus the Half life in epochs for a given $\\alpha$ is\n",
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"\n",
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"$T = \\log_\\alpha \\frac{1}{2} = -\\log_\\alpha 2$\n",
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"\n",
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"and conversely the $\\alpha$ which achieves a desired half-life $T$ is\n",
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"\n",
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"$\\alpha = 2^{-1/T} = \\frac{1}{\\sqrt[T]{2}}$\n",
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"\n",
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"Further note that the relationship between $T$ and $\\alpha$ is sensative to timescaling. Suppose we wanted a half-life of 3 days but our discrete time scale simulation has 1 day timesteps, then we must use $T = 3$ in the above equation to equal:\n",
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"\n",
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"$\\alpha = 2^{-1/3}$\n",
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"\n",
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"\n",
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"See the [Deriving_Alpha](Deriving_Alpha.ipynb) notebook for more details around alpha and how it is derived.\n",
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"\n",
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"\n",
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"## Converting Signals to Discrete Decisions\n",
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"\n",
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"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. See [Trigger Function Explanation](Trigger_Function_Explanation.ipynb) for more details around the trigger function and how it works."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Resolving Passed Proposals\n",
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"\n",
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"\n",
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"\n",
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"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",
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"\n",
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"## Social Systems Modeling\n",
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"\n",
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"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",
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"\n",
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"### Sentiment\n",
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"\n",
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"Global Sentiment denotes the outside world appreciating the output of the community.\n",
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"Local Sentiment denotes the agents within the system feeling good about the community.\n",
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"Sentiment increases when proposals pass and work is completed in the community, and decreases when proposals fail and community progress stalls.\n",
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"\n",
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"### Relationships between Participants\n",
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"\n",
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"Edges from participant to participant denote influence (to represent subjective social influence) and are assigned randomly as mixing processes.\n",
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"\n",
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"### Relationships between Proposals\n",
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"\n",
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"Edges from proposal to proposal represent conflict, either positive or negative.\n",
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"Some proposals are synergistic (passing one makes the other more desirable).\n",
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"Some proposals are (partially) substitutable (passing one makes the other less desirable).\n",
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"\n",
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"\n",
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"### Notion of Honey supply\n",
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"#### Total supply = $S$\n",
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"#### Effective supply = $E$, honey committed towards votes (whether for proposals or abstain)\n",
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"#### Funding Pool = $F$, community funding pool where proposals are funded from\n",
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"#### 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",
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"$$S = F + E + L$$ \n",
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"\n",
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"System has the right to do direct mints:\n",
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"$$F^+ = F + minted tokens$$\n",
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"$$S^+ = S + minted tokens$$\n",
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"\n",
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"The system may also see the arrival of new funds which come from outside supply and are donated to the funding pool:\n",
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"$$L^+ = L - donated tokens$$\n",
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"$$F^+ = F + donated tokens$$\n",
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"\n",
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"When tokens are added to a liquidity pool or cold wallet and removed from staking on proposals:\n",
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"$$L^+ = L + tokens$$ \n",
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"$$E^+ = E - tokens$$ \n",
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"\n",
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"When tokens are removed from a liquidity pool or cold wallet and staked towards proposals:\n",
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"$$L^+ = L - tokens$$ \n",
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"$$E^+ = E + tokens$$\n",
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"\n",
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"Tokens in $L$ or $E$ are defined at the level of the account holding them.\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## cadCAD Overview\n",
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"\n",
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"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, essentially views on a complex data structure. Metrics can often be thought of as KPIs, or Key Performance Indicators. \n",
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"\n",
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"\n",
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"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",
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"\n",
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||
"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",
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"\n",
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"cadCAD models are micro founded with metrics being at the macro or the institutional level. If you are interested in insitutional dynamics, see Dr. Zargham's recent paper: [Voshmgir, Shermin and Zargham, Michael (2019) Foundations of Cryptoeconomic Systems. Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Research, 1. Research Institute for Cryptoeconomics, Vienna.](https://epub.wu.ac.at/7309/)\n",
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"\n",
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"\n",
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"## Differential Specification \n",
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"\n",
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"\n",
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"## File structure\n",
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"* ```Aragon_Conviction_Voting_Model.ipynb```\n",
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"* model\n",
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"\n",
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"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",
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"\n",
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"The mechanisms of the model live within the parts subfolder as:\n",
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"* [```system.py```](model/parts/system.py)\n",
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"* [```participants.py```](model/parts/participants.py)\n",
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"* [```proposals.py```](model/parts/proposals.py)\n",
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"\n",
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"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",
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"\n",
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"### Note:\n",
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"When running this notebook simulation, be sure to run from \"Kernal\" -> \"Restart & Run All\"\n",
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"\n",
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"## Schema of the states \n",
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"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), and *conviction* The model as three kinds of edges:\n",
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"* (Participant, participant), we labeled this edge type \"influencer\" and it contains information about how the preferences and sentiment of one participant influence another.\n",
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"* (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",
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"* The edges between Participant and Proposal, which are described below.\n",
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" \n",
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"\n",
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"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",
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"* Each pairing (i,j) will have *affinity*, which determines how much $i$ likes or dislikes proposal $j$.\n",
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"* 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",
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"* 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",
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"* 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",
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"\n",
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"\n",
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"The other state variables in the model are *funds*, *sentiment*, *effective_supply*, *total_supply*, and the metrics variables of: *fractionOfSupplyForVoting*, *fractionOfSupplyInPool*, *fractionOfProposalStages*, *fractionOfFundStages*.\n",
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"\n",
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"The system consists of 100 time steps without a parameter sweep or monte carlo.\n",
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"\n",
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" \n",
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"## Partial State Update Blocks \n",
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"\n",
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"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."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
|
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"```\n",
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"{\n",
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"# system.py: \n",
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"'policies': { \n",
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" 'random': driving_process\n",
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"},\n",
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"'variables': {\n",
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" 'network': update_network,\n",
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" 'effective_supply':increment_supply,\n",
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"}\n",
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"```\n",
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"\n",
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"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",
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"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 addition 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",
|
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"},\n",
|
||
"```\n",
|
||
"A behavior called *minting_rule* is included to record the general expansion of system supply every timestep. 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",
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||
"\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",
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||
"\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",
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||
"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": [
|
||
"```\n",
|
||
" {\n",
|
||
" # metrics.py\n",
|
||
" 'policies': {\n",
|
||
" 'calculations': kpi_calculations\n",
|
||
" },\n",
|
||
" 'variables':{\n",
|
||
" 'fractionOfSupplyForVoting': kpi_fractionOfSupplyForVoting,\n",
|
||
" 'fractionOfSupplyInPool': kpi_fractionOfSupplyInPool,\n",
|
||
" 'fractionOfProposalStages':kpi_proposal_stages,\n",
|
||
" 'fractionOfFundStages': kpi_fractionOfFundStages\n",
|
||
" }\n",
|
||
" }\n",
|
||
"```\n",
|
||
"\n",
|
||
"In the Metrics section we create KPI's to calculate the system's health. To see the logic, [click here](model/parts/metrics.py)."
|
||
]
|
||
},
|
||
{
|
||
"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. We will initialize the network x object and pull out the simulation configuration, state_variables, and partial state update blocks from the [config.py](model/config.py)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Params (config.py) : {'beta': 0.2, 'rho': 0.0025, 'alpha': 0.7937005259840998, '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"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
|
||
" import pandas.util.testing as tm\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from model import config\n",
|
||
"from model.parts.sys_params import initial_values\n",
|
||
"from model.parts.utils import *"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from copy import deepcopy\n",
|
||
"from cadCAD import configs\n",
|
||
"\n",
|
||
"# Initialize network x\n",
|
||
"for c in configs:\n",
|
||
" c.initial_state = deepcopy(c.initial_state)\n",
|
||
" c.initial_state['network'] = initialize_network(initial_values['n'],initial_values['m'],\n",
|
||
" initial_values['funds'],\n",
|
||
" initial_values['supply'],c.sim_config['M'])\n",
|
||
" \n",
|
||
"# pull out configurations to illustrate\n",
|
||
"sim_config,state_variables,partial_state_update_blocks = config.get_configs()\n",
|
||
"state_variables['network'] = c.initial_state['network']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"\n",
|
||
"# pull out configurations to illustrate\n",
|
||
"sim_config,state_variables,partial_state_update_blocks = config.get_configs()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"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)>}},\n",
|
||
" {'policies': {'calculations': <function model.parts.metrics.kpi_calculations(params, step, sL, s)>},\n",
|
||
" 'variables': {'fractionOfSupplyForVoting': <function model.parts.metrics.kpi_fractionOfSupplyForVoting(params, step, sL, s, _input)>,\n",
|
||
" 'fractionOfSupplyInPool': <function model.parts.metrics.kpi_fractionOfSupplyInPool(params, step, sL, s, _input)>,\n",
|
||
" 'fractionOfProposalStages': <function model.parts.metrics.kpi_proposal_stages(params, step, sL, s, _input)>,\n",
|
||
" 'fractionOfFundStages': <function model.parts.metrics.kpi_fractionOfFundStages(params, step, sL, s, _input)>}}]"
|
||
]
|
||
},
|
||
"execution_count": 4,
|
||
"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": 5,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'sentiment': 0.6, 'n': 30, 'm': 7, 'funds': 4867.21, 'supply': 22392.22}"
|
||
]
|
||
},
|
||
"execution_count": 5,
|
||
"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": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'beta': 0.2,\n",
|
||
" 'rho': 0.0025,\n",
|
||
" 'alpha': 0.7937005259840998,\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": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"sim_config[0]['M']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Initial state variable values"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'network': <networkx.classes.digraph.DiGraph at 0x7feceda18090>,\n",
|
||
" 'funds': 4867.21,\n",
|
||
" 'sentiment': 0.6,\n",
|
||
" 'effective_supply': 14020.008000000002,\n",
|
||
" 'total_supply': 22392.22,\n",
|
||
" 'fractionOfSupplyForVoting': 0,\n",
|
||
" 'fractionOfSupplyInPool': 0,\n",
|
||
" 'fractionOfProposalStages': 0,\n",
|
||
" 'fractionOfFundStages': 0}"
|
||
]
|
||
},
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"state_variables"
|
||
]
|
||
},
|
||
{
|
||
"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",
|
||
"* $\\alpha$ : 0.79370 timescale set in days with 3 day halflife\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, expected number of days to complete a proposals.\n",
|
||
"* base_failure_rate: 180, expected number of days until a proposal will fail\n",
|
||
"* base_engagement_rate: 0.3, probability of being active on a certain day \n",
|
||
"* lowest_affinity_to_support: 0.3, lowest affinity to required to support a proposal\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": 8,
|
||
"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(state_variables['network'], 'proposal')\n",
|
||
"participants = get_nodes_by_type(state_variables['network'], 'participant')\n",
|
||
"supporters = get_edges_by_type(state_variables['network'], 'support')\n",
|
||
"influencers = get_edges_by_type(state_variables['network'], 'influence')\n",
|
||
"competitors = get_edges_by_type(state_variables['network'], 'conflict')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'type': 'participant',\n",
|
||
" 'holdings': 1448.6338105270497,\n",
|
||
" 'sentiment': 0.378853737393662}"
|
||
]
|
||
},
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"#sample a participant\n",
|
||
"state_variables['network'].nodes[participants[0]]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0, 0.5, 'Count of Participants')"
|
||
]
|
||
},
|
||
"execution_count": 10,
|
||
"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([ state_variables['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": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:563: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" if not cb.iterable(width):\n",
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:660: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" if cb.iterable(node_size): # many node sizes\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0.5, 1.0, 'Participants Social Network')"
|
||
]
|
||
},
|
||
"execution_count": 11,
|
||
"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(state_variables['network'], nodelist = participants, edgelist=influencers)\n",
|
||
"plt.title('Participants Social Network')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'type': 'proposal',\n",
|
||
" 'conviction': 0,\n",
|
||
" 'status': 'candidate',\n",
|
||
" 'age': 0,\n",
|
||
" 'funds_requested': 648.6100683917992,\n",
|
||
" 'trigger': 59323.37588931}"
|
||
]
|
||
},
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"#lets look at proposals\n",
|
||
"state_variables['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": 13,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"funds_array = np.array([state_variables['network'].nodes[i]['funds_requested'] for i in proposals])\n",
|
||
"conviction_required = np.array([trigger_threshold(r, initial_values['funds'], initial_values['supply'], sim_config[0]['M']['alpha'],sim_config[0]['M']) for r in funds_array])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0, 0.5, 'Amount of Honey requested(as a Fraction of Funds available)')"
|
||
]
|
||
},
|
||
"execution_count": 14,
|
||
"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_values['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": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0, 0.5, 'Amount of Conviction')"
|
||
]
|
||
},
|
||
"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": [
|
||
"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": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0.5, 55.73999999999998, 'Participant_id')"
|
||
]
|
||
},
|
||
"execution_count": 16,
|
||
"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] = state_variables['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": 17,
|
||
"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: 1\n",
|
||
"Dimensions of the first simulation: (Timesteps, Params, Runs, Vars) = (100, 11, 1, 9)\n",
|
||
"Execution Method: local_simulations\n",
|
||
"SimIDs : [0]\n",
|
||
"SubsetIDs: [0]\n",
|
||
"Ns : [0]\n",
|
||
"ExpIDs : [0]\n",
|
||
"Execution Mode: single_threaded\n",
|
||
"Total execution time: 40.74s\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"import pandas as pd\n",
|
||
"from model import run\n",
|
||
"pd.options.display.float_format = '{:.2f}'.format\n",
|
||
"\n",
|
||
"%matplotlib inline\n",
|
||
"\n",
|
||
"rdf = run.run()\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": 18,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"df= run.postprocessing(rdf,0)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\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>fractionOfSupplyForVoting</th>\n",
|
||
" <th>fractionOfSupplyInPool</th>\n",
|
||
" <th>fractionOfProposalStages</th>\n",
|
||
" <th>fractionOfFundStages</th>\n",
|
||
" <th>simulation</th>\n",
|
||
" <th>...</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",
|
||
" <th>percentageOfActiveProposals</th>\n",
|
||
" <th>percentageOfCompletedProposals</th>\n",
|
||
" <th>percentageOfKilledProposals</th>\n",
|
||
" <th>percentageOfActiveFundsRequested</th>\n",
|
||
" <th>percentageOfCompletedFundsRequested</th>\n",
|
||
" <th>percentageOfKilledFundsRequested</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>6</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>14285.81</td>\n",
|
||
" <td>22414.61</td>\n",
|
||
" <td>0.64</td>\n",
|
||
" <td>4.58</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[1, 1, 1, 1, 1, 1, 1, 1]</td>\n",
|
||
" <td>[701.3809628873984, 0.0, 386.6042834645637, 40...</td>\n",
|
||
" <td>[38144.58457408024, inf, inf, inf, inf, inf, i...</td>\n",
|
||
" <td>[0.01838743220614326, 0.0, 0.0, 0.0, 0.0, 0.0,...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.25</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.29</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>12</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>14285.81</td>\n",
|
||
" <td>22437.03</td>\n",
|
||
" <td>0.64</td>\n",
|
||
" <td>4.57</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[2, 2, 2, 2, 2, 2, 2, 2, 1]</td>\n",
|
||
" <td>[1590.9088026195595, 0.0, 1125.1058257914385, ...</td>\n",
|
||
" <td>[38166.56160770424, nan, inf, inf, inf, inf, n...</td>\n",
|
||
" <td>[0.041683314807651445, nan, 0.0, 0.0, 0.0, 0.0...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.22</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.29</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>18</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>14285.81</td>\n",
|
||
" <td>22459.46</td>\n",
|
||
" <td>0.64</td>\n",
|
||
" <td>4.55</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[3, 3, 3, 3, 3, 3, 3, 3, 2, 1]</td>\n",
|
||
" <td>[2114.0202578166263, 0.0, 1782.5616959761367, ...</td>\n",
|
||
" <td>[37489.64025928574, nan, inf, inf, inf, inf, n...</td>\n",
|
||
" <td>[0.05638945167773405, nan, 0.0, 0.0, 0.0, 0.0,...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.20</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.29</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>24</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>14285.81</td>\n",
|
||
" <td>22481.92</td>\n",
|
||
" <td>0.64</td>\n",
|
||
" <td>4.54</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 1]</td>\n",
|
||
" <td>[2407.2973464628867, 0.0, 2304.3847659530657, ...</td>\n",
|
||
" <td>[36835.83680877524, nan, inf, inf, inf, inf, n...</td>\n",
|
||
" <td>[0.06535204721857729, nan, 0.0, 0.0, 0.0, 0.0,...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.18</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.29</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>30</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>14285.81</td>\n",
|
||
" <td>22504.41</td>\n",
|
||
" <td>0.63</td>\n",
|
||
" <td>4.52</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[5, 5, 5, 5, 5, 5, 5, 5, 4, 3, 2]</td>\n",
|
||
" <td>[3230.1837803203393, 0.0, 3614.0041181658235, ...</td>\n",
|
||
" <td>[36204.05929547125, nan, inf, inf, inf, inf, n...</td>\n",
|
||
" <td>[0.08922159125743123, nan, 0.0, 0.0, 0.0, 0.0,...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.18</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.29</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>5 rows × 43 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" network funds sentiment \\\n",
|
||
"6 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4889.60 0.60 \n",
|
||
"12 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4912.02 0.60 \n",
|
||
"18 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4934.45 0.60 \n",
|
||
"24 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4956.91 0.60 \n",
|
||
"30 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4979.40 0.60 \n",
|
||
"\n",
|
||
" effective_supply total_supply fractionOfSupplyForVoting \\\n",
|
||
"6 14285.81 22414.61 0.64 \n",
|
||
"12 14285.81 22437.03 0.64 \n",
|
||
"18 14285.81 22459.46 0.64 \n",
|
||
"24 14285.81 22481.92 0.64 \n",
|
||
"30 14285.81 22504.41 0.63 \n",
|
||
"\n",
|
||
" fractionOfSupplyInPool fractionOfProposalStages \\\n",
|
||
"6 4.58 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"12 4.57 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"18 4.55 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"24 4.54 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"30 4.52 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"\n",
|
||
" fractionOfFundStages simulation ... \\\n",
|
||
"6 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"12 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"18 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"24 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"30 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"\n",
|
||
" age_all \\\n",
|
||
"6 [1, 1, 1, 1, 1, 1, 1, 1] \n",
|
||
"12 [2, 2, 2, 2, 2, 2, 2, 2, 1] \n",
|
||
"18 [3, 3, 3, 3, 3, 3, 3, 3, 2, 1] \n",
|
||
"24 [4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 1] \n",
|
||
"30 [5, 5, 5, 5, 5, 5, 5, 5, 4, 3, 2] \n",
|
||
"\n",
|
||
" conviction_all \\\n",
|
||
"6 [701.3809628873984, 0.0, 386.6042834645637, 40... \n",
|
||
"12 [1590.9088026195595, 0.0, 1125.1058257914385, ... \n",
|
||
"18 [2114.0202578166263, 0.0, 1782.5616959761367, ... \n",
|
||
"24 [2407.2973464628867, 0.0, 2304.3847659530657, ... \n",
|
||
"30 [3230.1837803203393, 0.0, 3614.0041181658235, ... \n",
|
||
"\n",
|
||
" triggers_all \\\n",
|
||
"6 [38144.58457408024, inf, inf, inf, inf, inf, i... \n",
|
||
"12 [38166.56160770424, nan, inf, inf, inf, inf, n... \n",
|
||
"18 [37489.64025928574, nan, inf, inf, inf, inf, n... \n",
|
||
"24 [36835.83680877524, nan, inf, inf, inf, inf, n... \n",
|
||
"30 [36204.05929547125, nan, inf, inf, inf, inf, n... \n",
|
||
"\n",
|
||
" conviction_share_of_trigger_all \\\n",
|
||
"6 [0.01838743220614326, 0.0, 0.0, 0.0, 0.0, 0.0,... \n",
|
||
"12 [0.041683314807651445, nan, 0.0, 0.0, 0.0, 0.0... \n",
|
||
"18 [0.05638945167773405, nan, 0.0, 0.0, 0.0, 0.0,... \n",
|
||
"24 [0.06535204721857729, nan, 0.0, 0.0, 0.0, 0.0,... \n",
|
||
"30 [0.08922159125743123, nan, 0.0, 0.0, 0.0, 0.0,... \n",
|
||
"\n",
|
||
" percentageOfActiveProposals percentageOfCompletedProposals \\\n",
|
||
"6 0.00 0.00 \n",
|
||
"12 0.00 0.00 \n",
|
||
"18 0.00 0.00 \n",
|
||
"24 0.00 0.00 \n",
|
||
"30 0.00 0.00 \n",
|
||
"\n",
|
||
" percentageOfKilledProposals percentageOfActiveFundsRequested \\\n",
|
||
"6 0.25 0.00 \n",
|
||
"12 0.22 0.00 \n",
|
||
"18 0.20 0.00 \n",
|
||
"24 0.18 0.00 \n",
|
||
"30 0.18 0.00 \n",
|
||
"\n",
|
||
" percentageOfCompletedFundsRequested percentageOfKilledFundsRequested \n",
|
||
"6 0.00 0.29 \n",
|
||
"12 0.00 0.29 \n",
|
||
"18 0.00 0.29 \n",
|
||
"24 0.00 0.29 \n",
|
||
"30 0.00 0.29 \n",
|
||
"\n",
|
||
"[5 rows x 43 columns]"
|
||
]
|
||
},
|
||
"execution_count": 19,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.head(5)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7feccc6b0550>"
|
||
]
|
||
},
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
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|
||
{
|
||
"data": {
|
||
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KdeHMTl55fOPzk1R1StWh1/KOPgqsEpGVOEJ+JfA/Ks55EXgdcJuInAx0AtH2VMZh54FhBoZznLZkdtihGMaYeLPIc8UiHbHRgvXV+7bzz7/cUfV3U4kY82Z0+BZHvSMIPG751XZuvmd76VgEHvvERcydnmrocbOFIkUl5LLFAqoayHCwCQVdVfMicg1wNxAHblXVLSJyE7BRVdcDHwX+RUSuxVkgvVpVo7vsPQFP7nIyGFsQNaKMt4FCrqBUS7b3Hc5w7MxO7lh33qj7ZnYlmdXV2AbR5XE0ark8s+cwxy+Yztff/Ts8uL2PP//BZnoPHmlY0L3disIYnetdt6iQLyrJeAQEHUBVN+AsdpbfdkPZz1uB8/0NLTw29w6Qisc48dgZYYdiGGOScAUily9ClWR74EiOudNTrJg/velxNGq59Owb5NTFs1gxfzpDWcfj33VwmNOXNvYtOePtVhRShl6+DV2ywd2hasE6RauwedcALz/WFkSNaFOyXMbIjvuHc8ye5k8WPlEcjWTo6VyBnQeOcMIxTgK1ZHYXALv6hxuOzdt+LryyRee6QfnoJuhVeHrPIVbb/BYj4niWy1g14AMBCnojdejP7x+iqJQEfVZXkumpuC+C7lkuYXroQGC16CboFRwcynLwSI7jj2nu11TDaJRkwrFcxurS7D+SY1ZXYx50LTTa+v/c3kFgRNBFhMWzu9jtZ4Ye1nAu97pB1aKboFewY/8QAMfNN//ciDbjWS6qysBw1reFz/HjkIZa/3v2DhITWFnm9S+Z0+VThu4Jelh16M51g6pFN0GvYMc+J1s4boFl6Ea0ScTGtlyGcwVyBQ3EcknEYuTdevh62L53kOVzpx0luk6Gnm44tuGQBd2zXMxDD4nn9w+RiAnL5toeoka0SbmWS7Vu0f4jOQBmB5Che5Uc9daiP7f3cMlu8Vgyu4sDQ1mOuBUv9ZIJe1E0aR56qOzYN8TyudMCKTEyjEYYz3LxBD0oy8WJY/IZer5Q5Pn9QxxfRdCBhrP04ZDLFr0qF7NcQmLH/kGzW4yWYFxBH84CMCugKhdw6+EnyYsHjpArKKuOOXoI3pI5/pQuelUuYS2KpqzKJTwKReWFviMct8AWRI3okyzrFK3k0LBnuTS/yqV8BMFkqaxw8VhcytAbFXQ3QzcPfeqxu3+YbL7IcU3urDMMP0iNkxmXPPQAMvTUOB8sE9HjCvrxFd+KF3Z3EI8Juw42JuhRWRQ1yyUEtpcqXCxDN6JPqfW/quUSnId+1AiCSbJ97yCLZnXS3Xl0nIl4jGNndvqQoYc8y8X9ILE69BDYsc+pQV9pGbrRAiTH6RQdGM6RjAvTAlgMnGgEwXg8t3dwlN3isWR2F70+WC6dyVggkw6r4X17MQ89BJ7fP0R3Z4L5M5rvOxpGo3hiUa2px+sSDULIxvtgGY9iUdm+b5Djx/hGvHi2Hxl6ITT/HMrLFi1DDxynwmVGaJ/mhjEZkomxLRenS9SfDSwmIjXBCIKx2HMozZFsgVULx8jQ53Tx0kCaQp0NSwDD2fA2twDz0ENlx74hjje7xWgRJqpDnz0tmG+a9Vouz/32MAAnjJmhd5EvKnsP11+Lns4XQxX0EcslGEEP5iO8BTiSzbNnIG3+udEyJEut/6Mz2IHhHMfO7AwkjvFGEFTSN5jhsd8cBOCebc6mZuN56ODMRV80q6uu2MLcfg6cQWOpRCywskUTdJfnvaFcVuFitAjjWS79R3K8fGH3qNubwXgjCCr5mw3P8O+P95aOF8/qHHMrvPK56GvrjM1bFA0Tbxu6IDBBd/EqXKxL1GgVkqVF0epVLkF0iZbHUUvZYt9QhhMXzuDz71wDwKJZY3+L8KNbNOxFUXDa/yNluYjIxcCXcPYU/Zqqfqbi/i8Ar3UPpwHHqGpL7bBsJYtGq5GIOZlxpeWSKxQZzOQD6RKFsg+WGjpFB9N55s/o4NQa9uudlkowZ1qyoUqX4VxhVI170HQkYoHVoU8o6CISB24GLgJ6gUdFZL27jygAqnpt2fkfBM5sQqxNZcf+QZbM7grVbzOMySAiVTdoLrX9B5yhV/PyKxnM5Fk2vfZJpotndzXULZrOFSOQoTe2o9NkqCVDPwfoUdUdACJyB3A5sHWM868CPulPeP7z/P4hDgxlRt3+9J5DZrcYLYezQfPRYhFklyiUTVuswVYYyuaZ0VG707tkdhe/6TtSd2zD2UKpFjwsUolYaYxvs6nllV0C7Cw77gXOrXaiiLwMWAn8V+Oh+c/BoSyv//wvx6xrffWqBQFHZBiNUW2D5gFP0IP20GvIQgfTeaZ31J4xL57dxYPb+1DVuvpDMvkIeOjJiHnok+BK4C5VrfpxJCLrgHUAy5cv9/nSE/PigSMUispHLjqRNcuOtvhF4KzlcwKPyTAaIRmPkatIUAYC3NzCiwFqE/ShTIEZHbXHtXROF4OZPIfS+bq+cYTdWATQEY9WlcsuYFnZ8VL3tmpcCXxgrAdS1VuAWwDWrl1bf/tXnewZcLy4C086pqZFGcOIOqmqlos7Cz0gQU/V6KFn80WyhSIzJpGhz3dLGvsGM5N+PsWiks5HwENPxhjKNLbzUq3UYi49CqwSkZUiksIR7fWVJ4nIScAc4CF/Q/QPb/eT8UqlDKOVSCZGWy4jo3MDqnIptf6Pn6F7ojZ9Eh56aZ54HYuKfUNZCkVlQXf1OvegcOrQI9L6r6p54BrgbuBp4E5V3SIiN4nIZWWnXgncoaqBZ961smdgmI5EjLnTbfiW0R44HnqF5eJ66DM7g2kzqdVyGXQFfTKLoqkGNoh4aSAaCVzk6tBVdQOwoeK2GyqOP+VfWM1h90CaRbM6bfiW0TYkYjIqe+0/kqO7M0EioH1xx6qHr6QeQS+VRNYhiJ7FWu/YAL9IBdgpOqWGc+3pr38mhGFEkVQVy2VgOBeYfw5OPXwyLhNm6PVYLo1k6HvcDP3Y0DP04Ga5TC1BH0izaLb550b7kIzHRo2tHRjOBdZUVB7HRHXohxsQ9EwdHvqegTTJuDAvZIs1Uh56u5AvFPntoTSLLUM32ohkvJrlkg2s7X8kjhj5CeaWexl69yS8/fH2TZ2IlwaGOXZWJ7FYuBZrRzJuW9D5zd7DGYqKZehGW1Gtsag/YMvFi2OiSpSgq1x2D6RZNDP8BC4VYB36lBF0b4HEMnSjnajaKXokuEmLI3GMroevZDDjiNqMVHBVLmH75+B8KBV14rJOP5gygl6qQbcM3WgjHCEdsTpU1fHQQ8jQJyxbTHsZeu2NPvUKuqryUkTWzILcV3TKCHpUSpgMw0+c1v8RoRjKFsgXNYRFUZlwg4uhbJ7OZGxS5ZT1bkDdN5QlWyiyKKBdm8ajI+F8gJmg+8ju/jTTU/HAmi0MIwgqx+f2Hwm27d+jpgw9M7lJi1B/hv5SqWQx/ASuVKkTgI8+ZQR9z8Awi2Z3WVOR0VY45YIjmXFp0mLAVS7V6uErcSYtTlLQ69xkeU9EukShbGHXMnT/2ON2iRpGO5GoaOgpTVoM2HJJxGqwXOrJ0CcxybGcksUaBQ/dLBf/2d2fLm06axjtQmW5YNCbW4wVRzUGM5PP0GMxpwt1stntnoE0iZgwf3q4g7lgJEMPohZ9Sgh6Jl9g/2DGFkSNtiOVOLpTtD+kDL0Wy2WyuxWVHjs++db5lwbSLJwZflMRmIfuO78dcLaci8LXL8Pwk8oZKp6HHkanaC0eel2CXseenLv7h1kckf/fzUP3md3WVGS0KV7LfdFtu+8fzpJKxOgMeB/NZFxGzZSpZDBTmLTl4jx2HRn6oXQkKlzAaf2HYDz0KVHDF6UFEsPwk9Is8mKRjljc6RLtSgZezVVr6/9kdivySE1yWqGqsmcgzRtPicb/796H64duf6LUZHTdm07mHWcv9f1aU0LQvS5Ry9CNdiMZd4Q7V1A6ErB/MBvKdMGJLJd8ochwrr4MPZWITWra4oGhLNl8kWMj0FQEcMKCGXzgtceX1jcAls1pjhZNCUHfMzDM7GlJulLh7i1oGH7jZejenJD9g5nSPpzBxnH0CIJKhrLuHJc6F0UnM23Rq0GPioeeiMf42BtPCuRaU8JD39OftgoXoy2pbI13BD16GfpQHbsVeXRMclE0Sl2iQVOToIvIxSKyTUR6ROS6Mc55p4hsFZEtIvJv/obZGLsH0iy2piKjDRlpvFFUlf2DmVA2Ra5V0Ou1XCbjoY/MbZp6/89P+OqKSBy4GbgI6AUeFZH1qrq17JxVwPXA+ap6UESOaVbA9bBnYJizXzY77DAMw3eSCddDzxcZyhZI54qhWC5OHfrYlou3W9GMOmYppRKxSTXllJqKQngdwqaWV/ccoEdVdwCIyB3A5cDWsnP+GLhZVQ8CqOpevwP1GBjOlQYQ1UI2X6T/SM4sF6MtScRGWuP3HXb6LcIQMqf1vzmWSyoe47A7ercWvKaieASaioKmlld3CbCz7LgXOLfinBMBROQBIA58SlV/6kuEFdzxyIv87f97ZtK/t3zutCZEYxjhUu6he23/80OyXLx6+GrdmSXLZRKbW5Q/9mQsl93u1nNTEb+qXBLAKuACYClwn4icpqr95SeJyDpgHcDy5cvrutBrTzpm0h5hRyLO61dHygUyDF9IuZZLvqDsdzP0BSFZLjBSD1+Jl2HX3Sk6CUF/aSDNqUtmTfo67UAtr+4uYFnZ8VL3tnJ6gYdVNQc8LyLP4gj8o+UnqeotwC0Aa9euHb+tbAxOXNjNiQu76/lVw2g7kmXTCPcPupZLdxhVLiMfLNU0e6hBD73WKhevqeii1QsnfZ12oJYql0eBVSKyUkRSwJXA+opzfoiTnSMi83EsmB0+xmkYRhXKLZd9g1lEYO60cMoWYewxt14d+mS2n/PomESGPjCcI5MvsjAiTUVBM6Ggq2oeuAa4G3gauFNVt4jITSJymXva3UCfiGwF7gE+pqp9zQraMAyH8k7RfYczzJ2WmtQWb36RmGCruMFMnmRcSrPBJ0OqhrECHvsHnYKJqVjhAjV66Kq6AdhQcdsNZT8r8BH3n2EYAVHKjPPF0GrQAVJlHyzVqHfSIkzOQz8w5Aj63BDGH0SBKdEpahjtSqn1v1gMre2/PI6xWvSH6tjcwmNygu6sI8wLoVs2CpigG0YLM+Kha2ht/+VxjOWh17NBdPljl48IHg/PcpkXgZ2KwsAE3TBaGK/1P5t3GotCz9DHslwazNBhbH++HM9ymTM92B2booIJumG0MF7rf/+RLOlcMTwP3RtBMFaVSwMZemqCBddyDgxl6e5I1LX42g6YoBtGC+O1/nsTBsPK0MtHEFSjEctlMlu49Q1lp6x/DibohtHSeNmrNwM8jLZ/GD3Gt5KhTKGuGnQos1xqEfTBzJStcAETdMNoaTzLxds3N6xF0RHLZWwPfUZHfb72ZAT9wFCWuVN0QRRM0A2jpfEy4939jqCHMcelPI58lQxdVRnK1refKEAq7vxeLR5631A4W/BFBRN0w2hhEu5kw72HM07bf0hiNl7Z4pFsAdX6NrdwHtt5jhNl6KrKQfPQDcNoVUSEZFxQJbS2fygT3SqWy2ADuxXBiOWSmUDQDw3nyRfVPHTDMFoXLzsOc37JeJ2inqB31zFpEcpG805gueyf4l2iYIJuGC1PSdBDGJtbGUM10W1kcwuovWxxZI6LLYoahtGieGIa1oJoeQy5Ku35DVsu3qLoBILeV2r7twzdMIwWxZt0GKblkhrPckn7Y7lMVOXiZehmuRiG0bIkSpZLeIKeiI/d+j+U9WdRdOIM3fHQbVHUMIyWJRmBDH08D30wU/9uRc5j11a22DeUZcYUnuMCJuiG0fKUPPQQM/RxyxYb2CAaysoWa7BcprLdAibohtHyeIIXVts/jNTDj1XlEhPoStaXOXe4i6JjbZ7h4bT9m6AbhtHCRKHKxYujWuu/NwtdROp63FoXRad62z/UKOgicrGIbBORHhG5rsr9V4vIPhHZ5P77X/6HahhGNRIxCbXtvzyOasO5GpmFDpNbFA37NQibCV9lEYkDNwMXAb3AoyKyXlW3Vpz6XVW9pgkxGoYxDqlELNS2//I4jmTzHHGrWjwGhnMNCXo8JsRjMq6gqyoHj2SZF/K3lMvh5HsAABE7SURBVLCp5VU+B+hR1R0AInIHcDlQKeiGYYRAVzLOMTM7ww6DzmScOzf2cufG3lH3nf2yOQ09dioeG9dyOZTOkyvolLdcahH0JcDOsuNe4Nwq571dRF4NPAtcq6o7K08QkXXAOoDly5dPPlrDMEbxZxefRDpXCDsM/v7tp7N510DV+847bl5Dj51KxMbN0Efa/k3Q/eBHwO2qmhGR/w18E7iw8iRVvQW4BWDt2rUTb+FtGMaEnHDMjLBDAOCVJ8znlSfMb8pjJ+OxcactWlORQy2m2y5gWdnxUve2Eqrap6oZ9/BrwNn+hGcYhuEM6Bpv2mKfm6GH2VwVBWoR9EeBVSKyUkRSwJXA+vITRGRR2eFlwNP+hWgYxlTHLJfamNByUdW8iFwD3A3EgVtVdYuI3ARsVNX1wIdE5DIgDxwArm5izIZhTDFScRP0WqjJQ1fVDcCGittuKPv5euB6f0MzDMNwSCXGr3LpG8wyPRWns85u1HbBOkUNw4g8E1kufUOZKV+DDibohmG0ALVYLlPdbgETdMMwWoBkIjbutMW+QZvjAibohmG0AJah14YJumEYkWe8OnRVNQ/dxQTdMIzIM96i6OGMzXHxMEE3DCPyjGe5HHRr0OeYoJugG4YRfcarQz807Izrnd2VDDKkSGKCbhhG5BnPcjmUzgEw0wTdBN0wjOiTHMdyOTTsCHp3p1/DY1sXE3TDMCKPZ7mojp66bRn6CCbohmFEng53X9Fqe5Z6HvpMy9BN0A3DiD4pd7/Uagujh9I5YgLTUyboJuiGYUSelJuhV/PRDw3n6O5MEotJ0GFFDhN0wzAiz7iCns4zs8uyczBBNwyjBShZLmNk6DM7bUEUTNANw2gBkl6GXiiMuu9Q2gTdwwTdMIzI42XomaoZulkuHjUJuohcLCLbRKRHRK4b57y3i4iKyFr/QjQMY6ozbtmiZeglJhR0EYkDNwNvAlYDV4nI6irndQMfBh72O0jDMKY24y2KHk7nranIpZYM/RygR1V3qGoWuAO4vMp5fwX8HZD2MT7DMIwxBT1fKDKYyVuG7lKLoC8BdpYd97q3lRCRs4BlqvqT8R5IRNaJyEYR2bhv375JB2sYxtRkpLHo6EXRwYzbJWoeOuDDoqiIxIDPAx+d6FxVvUVV16rq2gULFjR6acMwpghjZehe23+3ZehAbYK+C1hWdrzUvc2jGzgVuFdEXgDOA9bbwqhhGH6RHKPKpTSYy+a4ALUJ+qPAKhFZKSIp4EpgvXenqg6o6nxVXaGqK4D/Bi5T1Y1NidgwjClHx5gZuk1aLGdCQVfVPHANcDfwNHCnqm4RkZtE5LJmB2gYhpEao2xxJEM3QQeo6XuKqm4ANlTcdsMY517QeFiGYRgjjLT+H70oWhqda4uigHWKGobRApQWRQtjeOhmuQAm6IZhtABjV7nkEIEZNgsdMEE3DKMFSMQEkSqCns7T3ZGwWeguJuiGYUQeESEVj5GptFyGc2a3lGGCbhhGS5CKx6pk6DaYqxwTdMMwWoJUIkZuVIZuo3PLMUE3DKMlSCUsQ58IE3TDMFqCaoJuo3OPxgTdMIyWIBWPja5Dt/1Ej8IE3TCMlqAyQy8UlcOZPN02mKuECbphGC1BKhE7atriYNpr+7cM3cME3TCMliBZUbZoo3NHY4JuGEZL0FFRtjhgo3NHYYJuGEZLULkoaqNzR2OCbhhGS1C5KGqjc0djgm4YRkswStAtQx9FpD7acrkcvb29pNPpsENpKzo7O1m6dCnJpP3hG61L5SwX235uNJES9N7eXrq7u1mxYgUiNg7TD1SVvr4+ent7WblyZdjhGEbdpBKVHnoeEejuiJSMhUpNlouIXCwi20SkR0Suq3L/+0Rks4hsEpH7RWR1PcGk02nmzZtnYu4jIsK8efPsW4/R8iTjR9ehHxrOMcNmoR/FhIIuInHgZuBNwGrgqiqC/W+qepqqrgH+Hvh8vQGZmPuPvaZGO1BZtng4nTf/vIJaMvRzgB5V3aGqWeAO4PLyE1T1UNnhdODorbkNwzAapNqiqPnnR1OLoC8BdpYd97q3HYWIfEBEtuNk6B+q9kAisk5ENorIxn379tUTb0uwadMmNmzYUDpev349n/nMZ5p6zXvvvZcHH3ywqdcwjDBJxWMUFfJulu4M5jL/vBzfyhZV9WZVPR74OPCJMc65RVXXquraBQsW+HXpyFEp6JdddhnXXTdq6cFXTNCNdqe0UbQn6DY6dxS1fLztApaVHS91bxuLO4CvNBIUwI0/2sLW3YcmPnESrF48k09eesq45wwNDfHOd76T3t5eCoUCf/mXf8kJJ5zARz7yEQYHB5k/fz633XYbixYt4oILLuDcc8/lnnvuob+/n69//euce+653HDDDQwPD3P//fdz/fXXMzw8zMaNG/nHf/xHrr76arq6unjiiSfYu3cvt956K9/61rd46KGHOPfcc7ntttsA+NnPfsYnP/lJMpkMxx9/PN/4xjeYMWMGK1as4N3vfjc/+tGPyOVyfO9736Ozs5OvfvWrxONxvvOd7/DlL3+ZV73qVb6+doYRNiVBzxeZlnIy9O5F3SFHFS1qydAfBVaJyEoRSQFXAuvLTxCRVWWHbwae8y/EYPnpT3/K4sWL+fWvf81TTz3FxRdfzAc/+EHuuusuHnvsMd7znvfwF3/xF6Xz8/k8jzzyCF/84he58cYbSaVS3HTTTVxxxRVs2rSJK664YtQ1Dh48yEMPPcQXvvAFLrvsMq699lq2bNnC5s2b2bRpE/v37+fTn/40P//5z3n88cdZu3Ytn//8yDrz/Pnzefzxx3n/+9/P5z73OVasWMH73vc+rr32WjZt2mRibrQl5YIOtltRNSbM0FU1LyLXAHcDceBWVd0iIjcBG1V1PXCNiLweyAEHgXc3GthEmXSzOO200/joRz/Kxz/+cd7ylrcwZ84cnnrqKS666CIACoUCixYtKp3/tre9DYCzzz6bF154oaZrXHrppYgIp512GgsXLuS0004D4JRTTuGFF16gt7eXrVu3cv755wOQzWZ5xSteUfWa3//+9xt+zobRCiTjjqBn8kWKRWUwY5ZLJTWtKKjqBmBDxW03lP38YZ/jCo0TTzyRxx9/nA0bNvCJT3yCCy+8kFNOOYWHHnqo6vkdHR0AxONx8vl8TdfwficWi5V+9o7z+TzxeJyLLrqI22+/3bdrGkar0+Fm6LlCkcOZPKo2OrcSm+VSwe7du5k2bRrvete7+NjHPsbDDz/Mvn37SoKey+XYsmXLuI/R3d3N4cOH647hvPPO44EHHqCnpwdwfP1nn322qdc0jKiTio8silrbf3VM0CvYvHkz55xzDmvWrOHGG2/kpptu4q677uLjH/84Z5xxBmvWrJmwmuS1r30tW7duZc2aNXz3u9+ddAwLFizgtttu46qrruL000/nFa94Bc8888y4v3PppZfygx/8gDVr1vCrX/1q0tc0jKjjeeh//K2NvOvrDwOWoVciquH0AK1du1Y3btx41G1PP/00J598cijxtDv22hqtzsGhLJ/+ydMM5xybsTMZ5xNvXs3c6amQIwsWEXlMVddWu88+3gzDaAnmTE/xf995RthhRBqzXAzDMNqEyAl6WBZQO2OvqWFMDSIl6J2dnfT19ZkA+Yg3D72zszPsUAzDaDKR8tCXLl1Kb28v7Ty4Kwy8HYsMw2hvIiXoyWTSdtUxDMOok0hZLoZhGEb9mKAbhmG0CSbohmEYbUJonaIisg/4zSR+ZT6wv0nhRJmp+Lyn4nOGqfm8p+Jzhsae98tUteoOQaEJ+mQRkY1jtbu2M1PxeU/F5wxT83lPxecMzXveZrkYhmG0CSbohmEYbUIrCfotYQcQElPxeU/F5wxT83lPxecMTXreLeOhG4ZhGOPTShm6YRiGMQ4m6IZhGG1CSwi6iFwsIttEpEdErgs7nmYgIstE5B4R2SoiW0Tkw+7tc0XkP0XkOfe/c8KO1W9EJC4iT4jIj93jlSLysPt+f1dE2m5LGhGZLSJ3icgzIvK0iLxiirzX17p/30+JyO0i0tlu77eI3Coie0XkqbLbqr634vAP7nN/UkTOauTakRd0EYkDNwNvAlYDV4nI6nCjagp54KOquho4D/iA+zyvA36hqquAX7jH7caHgafLjv8O+IKqngAcBN4bSlTN5UvAT1X1JOAMnOff1u+1iCwBPgSsVdVTgThwJe33ft8GXFxx21jv7ZuAVe6/dcBXGrlw5AUdOAfoUdUdqpoF7gAuDzkm31HVPar6uPvzYZz/wZfgPNdvuqd9E/i9cCJsDiKyFHgz8DX3WIALgbvcU9rxOc8CXg18HUBVs6raT5u/1y4JoEtEEsA0YA9t9n6r6n3AgYqbx3pvLwe+pQ7/DcwWkUX1XrsVBH0JsLPsuNe9rW0RkRXAmcDDwEJV3ePe9RKwMKSwmsUXgT8Diu7xPKBfVfPucTu+3yuBfcA3XKvpayIynTZ/r1V1F/A54EUcIR8AHqP9328Y+731Vd9aQdCnFCIyA/h34P+o6qHy+9SpMW2bOlMReQuwV1UfCzuWgEkAZwFfUdUzgSEq7JV2e68BXN/4cpwPtMXAdEZbE21PM9/bVhD0XcCysuOl7m1th4gkccT8X1X1++7Nv/W+grn/3RtWfE3gfOAyEXkBx0q7EMdbnu1+JYf2fL97gV5Vfdg9vgtH4Nv5vQZ4PfC8qu5T1RzwfZy/gXZ/v2Hs99ZXfWsFQX8UWOWuhKdwFlHWhxyT77je8deBp1X182V3rQfe7f78buA/go6tWajq9aq6VFVX4Lyv/6WqfwDcA7zDPa2tnjOAqr4E7BSRl7s3vQ7YShu/1y4vAueJyDT379173m39fruM9d6uB/7IrXY5Dxgos2Ymj6pG/h9wCfAssB34i7DjadJz/F2cr2FPApvcf5fgeMq/AJ4Dfg7MDTvWJj3/C4Afuz8fBzwC9ADfAzrCjq8Jz3cNsNF9v38IzJkK7zVwI/AM8BTwbaCj3d5v4HacNYIczrex94713gKCU8W3HdiMUwFU97Wt9d8wDKNNaAXLxTAMw6gBE3TDMIw2wQTdMAyjTTBBNwzDaBNM0A3DMNoEE3SjpXGnFv6J+/NiEblrot9p4FprROSSZj2+YTSKCbrR6swG/gRAVXer6jsmOL8R1uD0BhhGJLE6dKOlERFv+uY2nKaNk1X1VBG5Gmei3XSc0aSfA1LAHwIZ4BJVPSAix+M0diwAjgB/rKrPiMjvA58ECjhDpF6P0/jShdOa/bfAj4EvA6cCSeBTqvof7rXfCszCGbT0HVW9sckvhWGQmPgUw4g01wGnquoad0rlj8vuOxVnamUnjhh/XFXPFJEvAH+EM+nxFuB9qvqciJwL/BPOTJkbgDeq6i4Rma2qWRG5AaeT7xoAEfkbnHEF7xGR2cAjIvJz99rnuNc/AjwqIj9R1Y3NfCEMwwTdaGfuUWe2/GERGQB+5N6+GTjdnWz5SuB7zmgRwGlFB3gAuE1E7sQZIlWNN+AMF/tT97gTWO7+/J+q2gcgIt/HGe1ggm40FRN0o53JlP1cLDsu4vztx3Bmca+p/EVVfZ+bsb8ZeExEzq7y+AK8XVW3HXWj83uVXqZ5m0bTsUVRo9U5DHTX84vqzJt/3vXLvf0dz3B/Pl5VH1bVG3A2o1hW5Vp3Ax90JwciImeW3XeRu49kF46X/0A9MRrGZDBBN1oa19Z4wN2Q97N1PMQfAO8VkV8DWxjZ3vCzIrLZfdwHgV/jjHldLSKbROQK4K9wFkOfFJEt7rHHIziz7Z8E/t38cyMIrMrFMHzGrXIpLZ4aRlBYhm4YhtEmWIZuGIbRJliGbhiG0SaYoBuGYbQJJuiGYRhtggm6YRhGm2CCbhiG0Sb8f3X3uQDDhXWYAAAAAElFTkSuQmCC\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": 21,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7feccc63d190>"
|
||
]
|
||
},
|
||
"execution_count": 21,
|
||
"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": [
|
||
"In the above graph, funds represent the total available funds, whereas candidate funds represent total funds requested by candidate proposals."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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WJSKFRGQCsAgYoqpj/h+1W2xd/b63p91zHMdxnJ2BxGxdqroJaBKPFn9LRBqp6vfbWLvF1mUNOnMcx3F2bLzHNYfE07pUdRmRnevopNviOI7jOGklqbSuKsCGeNKUbB/2f5Joi+M4jpNe/Bp2Dkn5sJsBn5Fj6xqlqm1E5CugMdEPiTVAf1U1E7s29D0j+ALWn3u62Y6Sc+yYv6IPvxvUDmhe06wdVcr2g0rj8EysLcd8bda2q13G1Dtf/FlQu+Xug83aV6vXMnVKh7276/qHfesAP/b/2dTbnx+OOx3StYVZ22TUDFO/rkL4Q9+jSWOz9q6x35j6qvWbjHXvZtZO/m2xqXerFfZpby5T2azd+MgTpn5pw7D/vOettl+5bE17H/y59xFBrVS7gWbtRf9qYuqf/Rz2+xfdbxezttBH9lTGhYoWCmpZhewOyfW9bjF1nfRFUCv2rD0/wrrz2pn6pm/D8yN8cng1s3aXkmVNff/f7AOm7H3Tdj2iFrumZb4fpNbdPyKVvxKS6hIfD+yqqiWAMkDJOF7zFqBo3K53AHt2EsdxHMcpIKTN1jU4exkRGUs0n7jjOI5TQPEu8RxSaeuKJ1M5G/gwqfY5juM4TppITbymiDTKkB8HRqjq57nVZvqw+46w53l2HMdxdlwkS/L9llZSZ+sSkVuBKsBVRk0fVW2mqs26taybPw11HMdxnARJla1LRLoBRwHtVHVzEm1zHMdx0kOaz3jzm6RmOqsGPC8imfGag0RkIzATGBXPbvOmqt5hrejhA8LWlI5rZ5uNmFJoialP+nJpUPvpCjtecFAedrmaJdcGteePtq1XjR8M280AugzvFtTu72jHJt5zbzjiEuD6PU8NakX3sy9PLH18iqlvWL0hqE1cPM+sLXefPbPtfdeF368swtGEAO//ZO8n844Ir3v9c3a7Cp9nW5haDH47qP37attutuQ3ex/s3bVGUKvW1rZH/VbBjnjdTPi5K40Ndp4BcOti2/43+YgKQa1W6d3tdh18oKn3Xx6OYe38nR0fu3nIm6a+ccqvQW3wlYeZtUuq2D2JQ4uH99HZS8JRvgANK4XtlAC3LrVtpuYXtPO3klSXeHa8pvLHeM3niUaPZwFTgQcTaZ3jOI7jpIy0xWteqaorAETkQaAHcG9CbXQcx3ESxrvEc0ibDzv7YC1ACTD61RzHcRynAJFYWld8/Xo8UBd4LNuHLSLPAscCk4Crk2qf4ziOkzx+hp1D6nzYqnoeUB34EeicW22mD3v0m5Pyrc2O4ziOkxSp82HHj20CBgAdAzVbfNgHn7JP/jTUcRzHyXd84pQcEjlgi0gVESkf/5/tw/5JROrGjwlwIjA5ifY5juM4TtpIjQ8beB/4XETKElm9vgUuyWtFLTsPD2oX3LvSrB0+/BdTn/jBOUHt+LK2f3bGGttL+vh33wW1J4ZMN2ur7mZ7YOutLh7UTrvKbnfFleGoSIBZrcPDCvYY2susffCp9aY+6MDaQe2u0TPM2mev2NfUh7UIx3OePvJ9s7ZoEft3rey2X1DTDXbk6KTfFpn68nUbg9q+R1Qxay8/3fbuTihfJKh9d91os7bk/uF5BAAmnfhjUKvx4XVm7QOzlpl6r6lzg1rhc22f9W0zh5t6t4ZNg9qZ0+338qzThpr6pGFtgtq47+abtdcfGI61BWh2QThSt+qAE81a7fCUqd/xjh0b6uQfqfFhq+pmVT1UVfcFhgInZY8adxzHcQomIpLvt7SSKh+2qo4WkWZAeCojx3EcxymApMqHHXeR9wK6AB2SaJvjOI6THtI8CCy/SVsedg/gXVU1L+hk2rreWm5f73Icx3GcnYHEJk6JrVtN4tHib4lIS6AT0HobavsAfQDG1avvs6E5juPspPgZdg5p8mG3IZr1bKqIzABKiogd/+Q4juM4BYQ0+bDHq2pVVa2jqnWA1apq+1Icx3Ecp4CQVJd4beAzEckisnWNivOwnwNaAcuBEiLSRFUnWCtq3j7sSdYO55uNGNR0sKnXn/JbUGs39wWz9vYWe9rrrhDe9BM+WWjWTnzB9hyzcnlQurNFQ7N08lI7d9ryWusvdm7u9T3GmfoJ3cOe5N8aVDdrFw0M+34BNiz8MKjtfoDtax8+zfamL9ocziKufJidz9x1gSnzzxnhMRr197fbPaP9KaZe5JmXg1pWd9uvP+0EO7O91sTwHAfLS5cya1+ZYO//vS+6MKh9vGsPs/a4Cnb36oX3rQ5q38y1XaaV321p6o9srhjUxjULz50AsFsP+7vqh5/Dcxy0XlrUrC17aCVTn9XjIVOv0G/7jg/2LvEckuoSHw/sqqolgDJE3d/Z3wDXqmoTVS2U18HacRzHcQoKqbJ1JdEWx3EcJ734GXYOabN1AdwtIt+JSG8RKZZU+xzHcRwnTaQtXrMnUB84EKgIXJ9bbaYPm0n2XMyO4zjOjoundeWQJlvX0ao6XyPWAc8CzQM1W+I12WeX/Gyu4ziO4yRCmmxdk0WkWvyYACcD3yfRPsdxHMdJG6mJ14xtXUNFpAqR1WsC0D2vFZXetXRQq9z7QbN22LPTTH3jBWEL1GNdbVvL3uvKmHqvqTOCWqM3Opm1+5esbOprStQKavU32b/Rav83HNMHwE1HBqXPS/1ulp59yz6mvvTgcEzlqMr2mMSDS9q2mCtLhGMqD61iD5W4rOtxpt7+tUFBbfHqDWbtg5dNMvVlH4W3t1QJ24QAKj3wuKlPHLk4qBUpYX811O58tqmfs+qroFZj/BCzdsHJrU197QN9g9rGr+woyVHLV5l6/eXh/eTsU8aatV+PsHv7Nk2cEdSeW2XHZz7SaW9T3/XJBkFNKuTaUbmF5bceauqb+jxt6tubNHdR5zepideMH28HvAsUBZoCtpHacRzHcQoIqYrXBBoAtYD6qrpZRPwCteM4TgHGz7BzSJsP+xKgi6pujpfzIeCO4ziOQ/p82HsCnWPL1gciUi+p9jmO4zjJ47auHNLmwy4GrFXVZsDTQL/cajN92BvGz82/RjuO4zhOQqTKhw3MAd6MpbeAXIcNZ/qwizStkT8NdRzHcZwESZUPG3ibKBcbotSuKUm0z3Ecx0kHIpLvt7SSNh/2SOBlEbmSaFBat7xWNPTlOUFt5TA7XjDreduHXeTo/YNa+9e+NGuHPWP/1lh/wwFB7cBZa83an+rafueiWWFP8uYvPzBri7Xdy9Q3f/BGUDu8tt3bUbpoIVMv/vzQoHbzaWGfKUCLlkeb+rxh7wS1TqXD7zOAFNrV1JtUDc8F0KNxHbt2vb1N1rwbjg1de98FZu3SJz8y9fnPhD3Lc+q8ZNaeHI0LDdJs17C3/ez6rc3aW7/51NQPPjO8j36/ZKVZ+/B4O7pz6GlhT3LJlQeatV20gqkvPnBdULt+gx3dmbUhvI8BVLwo7Lk/s9tks/bFo84y9S417TkOXjNV5+8kqQN2tg87Ow87+1urKdHBfFN8s49MjuM4zk5NmgeB5TdJXcPO9mE3BpoAR8d52E8AZ8aD0V4Bbk6ofY7jOI6TKhI5YMcBH7n5sBUoGz9eDpiXQPMcx3GclJBWW5eIHC0iP4nIVBG5IRd9NxEZJiLfxJHRx/6v2yJtPuxuwGARmQOcDdwbqN1i63pr+bL8a7TjOI5T4InHXz0GHAPsA5whIluHJdxMND5rf+B0wJ7cfxtImw/7SuBYVa1JFK+Za3pHpq2rQ7ny+ddox3Ecx4min6eq6nRVXQ8MAE7aapm/vcc4qUFnW1DVZSIyjOiXSuP4TBtgIPBhci1zHMdxkialg85qALMz7s8BDtpqmduAj0XkcqAU0P5/fdI0+bB/BMqJSLZnI/sxx3Ecx8k3Mi+7xreL/sJqzgCei3uMjwVeFJH/6Zib1Bl2beCzuPECjIp92A8D38bG9eXA4XmtqPGl4czqqSXLmbWjB7Q19X2q1Qlqk8bbXtGPX25n6rvPXh3UsvqF/cgAv5exLwN8+GQ4L7ikHbtLy3uamnrWHuEAtcJ97ZzjFQ9eb+pF+74S1Cp/9ItZe+kjD5j6a32uDYt5eIq/W21nVr/8Xtjn+kILO0v7918+N/XDmlcKar12u82s3TzhclOv8054Pyv66L5m7Uk/jTH1f+zeOqjphG/M2hvenGXqJW7oEtTGL/rCrB1/1ta9ln+kWKFSQW30gnFmbanb7W3C4xcGpR+W2Pv3yjLh/QBg6uClQa3Tffb3xYyVP5j6q3X2MPXtTVYCp5Wq2gfoYywylyhZMpua8WOZXEA0gyeqOkpEigOVicZt/SWSuoY9HthVVUsAZYCSItICuJCoW7wE0cZqmVD7HMdxHCfEOKCeiOwuIkWJBpW9u9Uys4B2ACLSACgO/Pq/PGmabF2bgPWqmj1F2BCgYxLtcxzHcdJBIZF8v+WFqm4EegAfEV26fVVVfxCRO0QkewrBq4ELReRboD/QNY6W/sskNugsHhY/HqhLNDx+LFBYRJqp6lfAqfyxy8FxHMdxUoGqDgYGb/XYLRn/TwLCc93+BVJj6wIaEnUr9BaRscBKorPuP5E5IKDvKPvaj+M4juPsDKTJ1nW0qt5PPNBMRI4Ecp3lP3NAwPreHf+nLgbHcRwnvRRKp60rEdJk65osIrvEjxUDrgeeTKJ9juM4jpM20hav2UtEjo8fe0JVbX8TcHq9cOxcz4OeNWvvu6mRqZe/5M6gdsxVe5q1ZYuWMPV6FdYHtQ8Ghi0aAKuPsSMZj5sYto9QurJZ+32rXGeD3SY2Dr3K1Cs9aP/++qhv+PLGzFZVzdqSB1U39fIPhmcFLF3F9rrNLF3G1DfdFbZPrbz2MbN27VI7SvWMBuH9bIWdJMm0jvb2ntUk/Nk5rI1t5ZGa9Ux97SNhi96st382a2+6rbmpn7gobJ8aPntVUAPo+eMnpv5M0/B73f0x2462sb0dTftLm/Bnq877Z5u1e5Szv6v2ealFUJvXw7YO/vZi2KoJQPlkZ5PclkFgBYWkRol/F8+vuj9RzGb2J/RxYAVR3OYh8XB5x3EcxynwJDboLOYK/jib2X+A3qpaF1hKZDx3HMdxCiiFsvL/llaSTOuqCRwH9I3vC9AWeD1e5Hng5GRa5ziO4zjpIsnfEg8B1wHZ80JWApbFhnSIJlOvkUTDHMdxHCdtJDVK/HhgkaqO/4v1W3zYv3w4Je8Cx3EcZ4ckjTOdJUVSZ9iHAieKyAyiHNG2wH+B8iKSPXI9t8nUgT/mYe9+tD0y03Ecx3F2BpIaJd5TVWuqah2i2c2GquqZwDCiKUkBzgXeSaJ9juM4TjrwM+wcEp/pbCuuBwaIyF3AN8AzeRVccXHYk9nh1gZm7bLptt/5lAW3BbXJm+eYtUcWrmPqZYuGI+0OfOoQs3bMYbVN/c7R3wa1V96zowtrjQ97zwF+rP+voFb8vpfM2nX33Wrqq5f0Cmpv97KnoD2zu+1n3tzj2KAmde1I0WF1rjb1g8YvCGrrVqwza3+bYu+DV+0fzr/RR5abtZuX28+9uUv7oDa+0BKzdviq7039jArhL715z51u1n785khT778wPJdApbb2sJcnV9g+7Qtenx3UumD79TevDM+tADDj1ROC2jmvjjZrB3XcYOqtvgu3e7fOu5u1jzZ63tQXTbvB1Hc1VefvJNEDdjxxSm9yur6PBSoCewIHq6r9jeM4juPs1PjUpDkk7Tjb2of9BdAemJlMcxzHcRwnnaTGhw2gqt+o6oyk2uQ4juM4aSVNPuxtJtPW9d7vy/7+ljmO4zipoJDk/y2t7JA+7Exb1wmlkp2Y3nEcx3Hyg6QGnWX7sI8FigNlReQlVT0rofY4juM4KcQHneWQJh+2H6wdx3EcJ0AabF1PA2Xj+18BjeN2zRKR/qpqJnYd/kjYs3xJLTud85aJC029Sr+Xg9riKYvN2t9LljV1rg3n1xY69Vyz9L1R/U29417hTN/Ox9cya98vYrf79xEdgtobm2wf6tdLRpn640eFPbQj9wlnNwOsGPObqVMpnPm7QmwP98ovwx5ugNO++zWodTl5rFl78rW2R1af6hvUClWzt0mRM22/88QDrw9qC2apWdv9/n1MfV6XU4PaQzNsn3WJCnaWfI1VYS/1qr72VbZN6zeZ+oYu4bP0ahkAACAASURBVLkbapQqYtbWLF3R1O8aGc4Bn7OX/bnMqmTPzfD1lWGPeLkLXzNry9+0n6mvLWznwW9v0jyRSX6TBlvXuPgGcAtQlKhd7wBfJdQux3Ecx0kVabN1DdYYYCzRfOKO4ziOU+BJsks829b1p/4WESkCnE10Bu44juMUUHzQWQ5ptXU9DoxQ1c8D9Vt82H0+/mm7tdNxHMdx0kLqbF0icitQBbg4VKyqfYA+AJvfPM8eHeM4juPssKR5IpP8JlW2LhHpBhwFnKGq/+8Z0BzHcRxnZyVt8ZpPEgV/jJJoKP+bqnqHVdBv77AF5JB2n5pPtmnqPaZe+r7Hg9riVfame+OKeqZ+5vTfg9rwTZ+YtffsdbCpf7ombB8ZMToc6wlQ+PBwTB9Au2JhG1L3720L07kNbBvSM6+H27augT3+8PeHgh0yEQvnBqWyYscmfrXQjmS8oXl4mxy68HCz9p1VP5r6tcPD78dPJYubtSOWjjP1w/qeFNQW1rB/yw879V1T55Swxa9a02Fm6fRr9zB1KV4oqNXbrZxZO/pte/+efGS4bRM/bmPW7n3SQFMf9kmPoFby4dfN2guy1pj6I3s1Dmob29lxvGu+tu2tRe99ztS5JRwB+3fg17BzSNTWlRGvmc3zwCqidk0FHkyiXY7jOI6TNtLgw848xbhSVRur6n7ALCD8k9RxHMdxChCJdYln+LDvBq4CUNUVsSZACcAHlDmO4xRgfKazHFIXrykizwILgPrAIwm0y3Ecx3FSR+p82Kp6HlCdqKu8c6B+iw97xGuTtm9jHcdxnMQoJJLvt7SS1Bl2tg97BjAAaCsiL2WLqropfjzX4YeZedgtO9khBI7jOI6zM5DINWxV7Qn0BBCR1sA1wNkiUldVp8bXsE8EJifRPsdxHCcdFEp6aHSKSJMPW4DnRaRs/P+3wCV5FR2xW6OgVuvNUmbtymL2njD0slZBrcK3tnfx5s/nm/o5X88Laq3a2j7UzvXtKMmLV4b9zv824gMBRh5wv6l/9V7roLZvZTt+sFElO8ZvU4dwZOnjVe15dHqsM2WosW9QqvrEo2bp8Q0q57HyMBdOHGOve3c7znTKieFozy+b3mfWNutcx9Sr1QzHzw7sGN5eAPPfCsesAtRdGv58XNAzHKMK8Fq38Gca4JjS4X149jrbM087289cpU54H73ouXDUKcDSfi1N/cdV4fOP1RfbEa4zzg9H/QL83nB6UJv7Zfi7BmCvZ08zdXatZutOvpEaH7aqblbVQ1V1X2AocFL2qHHHcRzHKegkfYad7cPecpohIs2ACom1yHEcx0kNaR4Elt+kKg87PuPuRWT3chzHcRwnJm0+7B7Au6pqXgDOtHW98uzI7dlGx3EcJ0EKZUm+39JKIl3imT7seJQ4IlId6AS0zqs+M15z5srHfTY0x3EcZ6cnNXnYwA/AOmBqnNRVUkSmqmrdhNroOI7jJIxfw84hTXnYFVS1qqrWiR9f7Qdrx3Ecx4lIdJR4PMjsaeJR4iLyHNAKWA6UEJEmqjrBWsfMlWGP4Y817F9mjU+719SfuDTsBz2pru2fnbF3C1NfMPi1oFZ7lJ3Z271xRVNfcvcX4XXf3dysPfSxw0y95VPht2PzdaeYtdX6vGDqx+wd9jv3q2HnSo8/8FZT3+PQXYPavOPz8L2v3WTqn80Je47LF7V/E7e662tT33BAOMe7QZsqZm3xI+1M9sGXDQlq/fcPby+AW1+ZZupryhULar/3vNCs3TzuS1OXFmETye93vGLWlryktamf9n7/oDa9k+1XPm/Mx6a+z6Hh7c2Sf5m1ZarbWfKDrwjP+HjIvZ3M2rL321ncK45pZupUtWXn7yMNtq5xZNi6gGtV1d6DHMdxnAKBz3SWQ6psXY7jOI7j5E7abF0Ad4vIdyLSW0TC/WqO4zjOTo+ndeWQtnjNnkQ52AcCFYHrA/VbfNjvvmRfA3Qcx3GcnYHU2LpE5CVVPSvW14nIs0QpXn8i04c9Yt7N7sN2HMfZSUnzRCb5TZpsXWeJSDWAOF7zZOD7JNrnOI7jOGkj6VHiW/OyiFQhitecAHTPq+Dw2RuD2tT6tt+g8pF1TL122fDm6dBrlFm7+S676VUfOzuolRv4oVl75SdzTH3A5+H4zWPrHGHWdp4ctpsBVNwjbCnThUvM2gua2lahuw/qHBbziE385s22pl72/M+CWvnrjzRr7+v+qqnv/kk4kvTnFv80axessy1jj5wdtmbder4dyVit75umPnBox6DWqeUbZu1u3eqY+u3HhvU9at1m1rbpWsvUS+61e1CTknlEvI791tTfe+anoLbh+DPN2subhNsFsO+j4X249P39zNoh97c39VPHhe1/g/bvbdYOrmCfwf7neHs6jBtM1fk7SU28Zkw74F2gKNAUOD+JdjmO4zjpwAed5ZD0GfbW8ZpdgVpAfVXdLCK7JNUwx3Ecx0kTiR2wM3zYdwNXxQ9fAnRR1c0AqroooeY5juM4KcAnTskhbT7sPYHOsWXrAxGx51Z0HMdxnAJC2nzYxYC1qtqMaI7xXEdiZPqw+7xtTjXuOI7j7MD4NewcUuXDBuYA2UNb3wKeza0404etY25wH7bjOI6z05MqHzbwNtAmXqwVMCWJ9jmO4zhO2hDVZE9QRaQ1cI2qHi8i5YGXgd2AVUB3VTWNk8u6tQ6+gEXf2mPW6r1zqd24ueHozkeKLjVL9yhX0tSbXjkyqPXt2cSs/XTmSlMfWioc/Tn34bFmbc3/nGDqGLMOzb1+kF1axP59WKN6WJ89M+y3B2jcxjYUTPluRVC768IGZu0Dm0uZOqvXBqW7K9ufrwsaHmjqHd79JKjdesk3Zu2gt+xI0solwtu7U7cRZu0ebWua+tdvhecKOOzDLmbtFxXt97rhTWFP/QfXhyNxAU546EdTL901HD87oevbZu2+Pzxi6q/+HK6vX7GaWVukzUumXu+0vz7cZ+GVx5h67c3hOFMAyp2xXfuQLx3WLd8PUo+36ZvKfvG0+bDfA2oAm4DawO1JtMtxHMdx0kaqfNiquuWUQETeAN5JqF2O4zhOCshK8SCw/CaVedgiUhZoS3RN23Ecx3EKPGnzYWdzMvCpquZ64THT1vXc5PB1ZsdxHGfHppDk/y2tpM2Hnc0ZQP9Qvar2UdVmqtqsa/3q26WNjuM4jpMmkjrDzvZhzwAGAG1jHzYiUhloDryfUNscx3EcJ3WkzYcNcCowSFXDXhnHcRynQJAl+X9LK4mOEo9tXU8TjxIXkXZAL2CRiIwEuqrqVGsdlUttCGorj7bzaYdttq9/nzdhclCb2e1ys3b+KXZKbL8bw17rW/rZmb1P9zjA1Jkb3uNqPtLJri1dzpTf+D28Tbq3s/Ouf+3UztS1yp5Bbd7pd5u1JcoVM/UK5+4f1NZtWmPWLnzYzj6vet/JQe36QV+ZtT92DWdpAzxXNKy1vcf2j89rY+c3fzBjcFAb9nKboAZQ99WZpt7/hcOCWtu+H5u1Dfa3L3N9e/8FQe2wznb281EX1Df1z77+JajtfexuZu27pXqYelkjqntlGfso0fOB8P4LMLJq+LMn++xj1s6o/6CpfzvSzl0/sdwZpu78faTB1jWOnHjNJ4DmqvqjiFwK3EwUuek4juMUQNI8CCy/SZutS8k5eJcDfAi44ziO45DsGXa2ratMxmPdgMEisgZYARycRMMcx3GcdJCV5ovK+UzabF1XAseqak2ipK5cL65k+rA3f79gO7fWcRzHcZInTbau94HGqjomXmYg0CK34kwfdlajqvnSYMdxHMdJktTYuoCTgHIisle82BFE84w7juM4BRSf6SyHpEeJb0FVN4rIhcAbIrIZWAqcn1fdgCcXB7VbhzY0az/7fLqp/7JrxaA2f03Y/gHwrx52zF+fheHEuIt72/aQiz4ZYurdjjo9qA2t9U+ztuH0nqY+dnrYHt+zTS2zdmYFw6MEzN/n+qB2yM//NWtnjfzA1DfPWRLU7v08HAUJUPrNe0w969KbgtqmDk3N2r062JayShrWpw2Zb9YOuaW7qR/XKRybuHrXymbtZxfZ+3evB74Oar8dU9esnfqbvU3eWz4hqB1eKxwtCzBio/2Vt+micPRnvx/eNWtvKm/KTBi6MKjVee5ss/Y/h/0pcuEPyISwjfT9lRPN2oOn3WzqlYva0Z9O/pEGH3ZvYG780HJgA1AUmAnMSqhpjuM4TgrwMWc5JJqHTU68JiKSBTwPnK6qjYgO2Ocm2DbHcRzHSQ1p8mFXAtar6pT4/hCgYxJtcxzHcdKBX8POIU3xmouBwiLSLL5/KmBfFHUcx3GcAkJqfNiqqkQjxnuLyFhgJbApUL/Fhz1k07J8abPjOI7jJElSg86yfdjHAsWBsiLyUpzYdTiAiBwJ7JVbsar2AfoAvF5s7/Bwa8dxHGeHJktS3Eedz6TGh62qZ4nILgAiUgy4HngyifY5juM4TtqQqCc6wQaItAauUdXjRaQXcDzRD4knVPWhvOqnHbZv8AU0aW/HPa7o3NrUZ/V4Pajt9sY1Zu2aPGIqz/owvO633v/JrH2//1JT79g97JssXq64WTvrmotNvfSsKUFt2KH9zNply02Zpi1KBLUvhtre3A43297easU3BrWlJx5i1vaRsH8W4MIZuV65iciyfxNLi3AMJcCaO18IanNHzg1qAHUHX2vqdd4M+4pfvXeSWTtsYGtTv7zxMUGtzD/vNWsPaGHHWH514qlBbWMp2wx96MBnTH39pvD34dd7h+NfAShpf7bWfxj2j+fFN2fuZ+oDp4T3hScH/2zWPnSWHdN6UdUDTV0qn79dT4HvHHtxvh+k/tX8qVSe1ifmw46nJc2+Tp39bfpvoAlQBzhORJ5XVfvo5DiO4zgFgKR92G1UtYmqZo8MvwH4VFXrAZ/G9x3HcZwCSpbk/y2tJH3A3pqTiCZPIf57coJtcRzHcZzUkOQBW4GPRWS8iFwUP7arqmZPkLwAyPUidKata8CC3/KjrY7jOI6TKEnOJX6Yqs6NR4YPEZHJmaKqqojkOtgg09ZlDTpzHMdxdmwKua1rC4mdYavq3PjvIuAtoDmwUESqAcR/FyXVPsdxHMdJE0nNdFZKRMpk/w8cCXwPvEtO4Me5wDtJtM9xHMdJBz7oLIekusR3BSaLSLaBdYmqfhifVT8iIv8GxgJhM2fMgSfUDGoL8zCEnT/HzrRu2jvszz3f8McClLjGHi/3YKuwt/Hqy8aYtYcMOt7UlwwKe2h/6W+/5gaV7Nf1Xu8fg9oJ3WqYtasuPNbUs+4Ne9NfG2n7sL+4yPaplvsw7G0fU8Us5cJdw75fgNtWDQxqt9dtbtb+drk9N1DFHmGfdt2e4dxzgIdmjzb1Ga3D+2DZuSvs2katTL3Epx8GtRE3H2HWHvyxnVN//NCwf/zFo+3Pxi+Lfjf1tntVCmpXrfnVrL37DTtX/Y2uewS1acvD8wQAHLZhnalfeu2XQa3T2/b+u2unN039qKtWmvrHp5xv6s7fRyIHbFWdLiLzgGaqujhDGg00BZ4imkzFR5Q5juMUYNKcnpXfJDno7E+oanY2dtJNcRzHcZxUkTZbl+M4juM4uZAqW5eqjtiWwvgAfxFAyQ4NKXaQx2Y7juPsjOQxHX+BIm22rm2t7aOqzVS1mR+sHcdxnIJAImfYsZUrS1VXZti67kiiLY7jOE568YlTckjS1vVWPLisMPBKbOvqADwCVAHeF5EJqnqUtaIlxx4U1Lr/atssnmzV0dQ33/JIUKte2e6c+PXjsM0CoOmi8AD455fak7dducm23Nx4S+egts8N9ls+e65tqdG64R6Nz/fdxaz9hrWmPvf+bkGtcoOwTQhgUYXdTb1LwyVBrUirAWZt1UvHm/qnT4fjC1ceakcbVi5t23n+ZRglbl+/2qzt+nDYggcgD4ftVeWqjzVrl7W/x9TrGNG2v7z4nVmbdd4Bpr5vybDF6ael9mu+s13YBgpQrmihoDZynm2tKt42bNsCqFKiVFA74mb7auCud9p2tSGvhfWj7/rYrP1i7gZT73XzV6bOKbbs/H0k0iWuqtOBcvHzbwA6xFILYBXwE/AlED7yOI7jODs9PnFKDklfzt86XnMI0EhV9wOmAD2Ta5rjOI7jpIekD9h/QFU/VtXsPsLRgN1/5TiO4zgFhCRtXdk+bAWeihO4MjkfCM/56DiO4+z0+ExnOSR5hn2Yqh5ANF/4ZSLSMlsQkZuAjcDLuRVm5mH3ed0eEOQ4juM4OwOJnWFn+rBFJNuHPUJEugLHA+1UNc88bJ14m+dhO47j7KSkeRBYfpOqeE0RORq4DjhRVW3PiuM4juMUINLmw54KFCOaqhRgtKp2t1a017jvg9roYQvMRhQpOdxu5Qn7BqVlz39mlhY680hTX1yibFDrf10vs/bu12yvdOs5YZ/2+x3sxNI6Lw419e97hmNDD+8Vjj0EmPzVMlO/54amQe3RSy80a+vfcZ+pX3rUnkGt6XcPmLWLTBWuaPJ2ULv/51Vm7eqZtqd+WNVyYTHL/vhWrWh3Pn3d4qagtvTE6mbt6mW2d3fveuGYyhLL7RC+4fXLmPqJhw8JajM+am/W1itfwdT3KBd+3ec8aQ+p+ahR2HsOsPzHsI+7152297zTsyNNvf3J4e+q9c3D+z7A5r3t+RGKdGpr6tsbnzglh7T5sPsD2SnWi/DZzxzHcRwHSN7WtbUPu5eq7qeqTYBBwC0Jts1xHMdxUkPa8rAz+wdLEVm/HMdxnAKKDzrLIXV52CJyt4jMBs4kcIadaeta/pl9PddxHMdxdgZS58NW1ZtUtRaRB7tHboWZ8ZrlWtkT7juO4zg7LoUk/29pJc152C8DdpyW4ziO4xQQ0ubDrpex2EnA5CTa5ziO46SDLJF8v6WVJH3Yk0VkU3x/SezDfkNE9gYqAtWAsLkw5qoDqwS10ks3m7U91oQzkgGeeDXs8X6//9KgBrC24iemPv/6o4NarZr2DvPGZXub+otnhL3U1b6cZdZOnfi7qRc/55WgduBZdc3a3ZbYc+EUfiecZfzI3tPM2s9fm2vqbYqFd/WLG9mZ1XtMXWzq97QIZxFv+OBJs3bmh7+Y+nGLw/voG9fYXugHzmlo6j8/vjCoLa9n+7Anf2bPM3Bvg2eD2oODWpu1pxz7pqk3/O7OoDbo+7BHG+Cs0+x139f7sKC29D/XmLXfLLanST6s3P5B7ec2N5u1Lf/RyNQXfD81qPW/084I3zDKDrQ+9Dk7T7tYz0tNfWclnujrv0AhoK+q3htYriPwOnCgquYRLm6TpA97HlBLVUuoas348Y5E17QnArMAe+YTx3Ecx8lnRKQQ8BjR8Wof4AwR2SeX5coAVwBj/o7nTdqHnRu9iaYndUuX4zhOASelg86aA1NVdbqqrgcGEF3G3Zo7gf8A9nRy20iqbF0ichIwV1W/TbBdjuM4TgEm0zoc3y7aapEawOyM+3PixzLXcQBRL/L7f1e7kpw45TBVnSsiuxDNHT4ZuJFoAJpJvPEuAuhyS0sOO/VPPRGO4zjOTkASg8AyEyH/CiKSBTwIdP272gTpsnW1AnYHvhWRGUBN4GsRqZpL7RYfth+sHcdxnHxmLlAr437N+LFsygCNgOHx8exg4F0Racb/QCJn2LGVK0tVV2bYuu5Q1V0ylpkBNFNVe4iu4ziOs9OSUpvVOKCeiOxOdKA+HeiSLarqcqBy9n0RGQ5c87+OEk9VvOZfWdHExWFry4yXbTvDgI11TP3Bi5sEtf1m2tu9zq72pj10RNgCctXY08zaaTPtwfNdDykf1N5/2Y42XD3tPFNv9MBH4dpT7Nqs4XaWS5mq4VjFeReFbUIAR15kW8qmfR2O9qxUdHezdvqV/Uy96ODdglqp27uatbU3PGPqo98O2/CaX1PNrO2TNcPUTxp1elD77gw7SrL8C2HLI0DzbmFb2PiL7GjaOqfY7+VJw94Laq/PX2/WPv9yHlGRi8L15fOIvV3fpaWpl+8XtvjNHnmXWTv2PTu6ljLhz86vP91glj404UtTr31pa1O3wzt3TlR1o4j0AD4isnX1U9UfROQO4CtVzeMN+2skcsBW1ekiUg5YSU685t0ichtwIfArsIxoJN7gJNroOI7jOCFUdTBbHZ9UNdezElVt/Xc8Z9JpXW1y6fLurar3J9Iax3EcJ1WktEs8EdLow3Ycx3EcZytS5cOO6SEi34lIPxGpkFTjHMdxnOTJkqx8v6WVtMVrPkE0hqEJMB94ILfCTFP7pEGeD+I4juPs/KTJh91cVReq6iZV3Qw8zZ8jN7Nrt/iw9zm+fv412nEcx3ESIm3xmpk+lQ6A7R1xHMdxdmo8XjOHVPmwReRFEWlCdH17BnBxXivq90E4GvHmz682a5dMn2Pq/ffrH9RqbnjYrK38cl9THz1nRVBrUXGNWbv3w/bvmF1uDMf4PXTESrP24woHmvr3N5QMahv62p7iT3q2MfXWk5YHtX7H217pucPs+XWKlQ7rz/wS9pYDdG9WztQ7jRwV1G6/fZxZW/MY+3V9MqBVUJvbyPaHbxhje453GRqeC2CPf4XnIAD49+F7mPqq6eGsg3cfmmfWNrjV/tw+uSYcSTqz3YNm7T9mhuN4Abq0s1+XRZGXbH/5xM/CUamNdnnRrC2UZR9EvhgU/i77tuvnZm2/2+y43u7/GmvqfPpPW3f+NpKM1ywXP3+2DxugKLAJ2AzsB3yQRPscx3GcdOBn2Dmkyoetqp2z/xeRB4DwKZfjOI7jFCCSPmDnikR95acBecwj6DiO4+zMpPmMN79Jow8b4HBgoarmeoE609a16dv5272hjuM4jpM0afNhZ3MGEBzxlWnrKtTYDkBwHMdxnJ2BxLrEM33YIvIWked6hIgUBk4BmibVNsdxHCcdZPkM2ltIlQ87ltsDk1XV9lw5juM4TgEiSR/2ZBHZFN9fEvuwmwAvAmtF5CvgUlU1TYBTv/89qF01YqTZiH6f2H7QPeafEdSWbLRzpZtXL2vqs1aEfao6Y6FZW7nnEaZ+WPViQa3be2PM2isqDTD1iy4PezoL3WPnAb8z7VdTP2hQ2F8bficiBvedbeodXj04qF3wyNdm7ZAbbf/414uWBrXqrWqZtb+Nt9/rdUeGL/l0v3cvs3b161NMfdV1l4bFkuFMdYD6Lzxh6g+1CfuZu95Ux6z9YI9LTP2gZ48Oamvz2N6DLzvA1Pe7aURQe7bMZrN27T72c39z41FBrdW3M8zaJz6w9+/SVcMDs6Y1Cn8fABxVv7Kprzyzhalvb3zQWQ5J+rDnAbVUtYSq1oyl+4BzVLUWcEt833Ecx3EKPGmzdSmQfWpajuig7jiO4xRQ/Aw7hyQP2Nm2LgWeUtU+wD+Bj0TkfqKz/2T7YhzHcRwnJaTN1nUJcGXcJX4lkOvk1Jk+7Jdn2ddFHcdxHGdnIG22rnOBK+JFXgNyTdCIz8b7AMw5tplu/9Y6juM4SZAlbuvKJm22rnlAdjxRWyAcxeU4juM4BYi0xWuuAv4bT56yFth6ytI/sXzOqqD23JGdzNpZt1xr6jVurxrUxlS9zazt8287nrDwwWFLzvzb7LjHavc3MPUKnQcGtQ17VTRrHx5g24x2e651UGuworhZe2j1Tab+690nB7UJuz5i1p405yZTb1IkHGf69MBpZu07K+0MmmtrGO/11c3M2oM/+NjUn6wdtnWdeakdm7jnVfZzbx49PKh9e/kQs3Zu55qmXqn9u+F1f/0Ps7Z65bC1CuCHHh8GtYb35xHhuqttPRzz+RtBbeMXdozkayt/MPVjKu4b1MbPn2jWlnrgBlP//dr/BLXlH9pfo6uG2rGgDT6aZOp0seX/FR90lkPa4jVXAuvjxxfhZ9iO4ziOAyRv6/pDvCbRNetrVPUzETkfuBb4VzJNcxzHcZLGz7BzSNvV/L2A7P6wIUDHBNviOI7jOKkhbfGaPwAnxf93Auy5/hzHcRyngJA2H/b5wKUiMh4oQ3Q9+09k+rBf+21Z/rXYcRzHyVeyRPL9llYSO2Bn+rCBt4DmqjpZVY9U1aZEedi5Dt/NzMPuVNEOKXAcx3GcnYFEBp3F3ussVV2Z4cO+Q0R2iSdSyQJuBp5Mon2O4zhOOvCJU3JImw/7ChG5LF7mTeDZvFZUeXTYn7h+UzjCEuCuu8ORiwBXNH0oqFWqZHebnFrDjrR7e/e9g1qF/b8xa0cf+byp73dy+NJ/ya55TM/+pO0Bf29a2M98xbpw1ClA0WPNpFQ2L6gX1LJ+OM6sbTxokKk/dtN3Qe3nj9qatde+P8PU2388KqjVvPNIs/bbQ5ua+u2zpge1C2uUNmt/vn+cqVdpWClcO9WeQLBLyzqmXu6f4QjMyje9adZO+GCOqfd96rCg9uE0ex6BmRvs74Tmr4TnArh88niz9uIeti/+lsfDz51XHO+Hs+3P5VGnGbGhd7xm1vaZHf5MA6zsZ/vPvY8z/0jSh92KyGddCDhLRA4hmulsA1AXeF1VfdpRx3GcAkwWku+3tJKkD/u/wIeqeqqIFAVKAsuAU4CnEmyX4ziO46SOpK5hlwNaAl0BVHU90YjwZbGeRLMcx3EcJ7UkdTV/d+BX4FkR+UZE+saDz7aJTFvXi/2Gb7dGOo7jOMnitq4ckjpgFwYOAJ5Q1f2B3wF7dvsMMm1dZ5/fevu00HEcx3FSRFLXsOcAc1R1THz/df4fB2zHcRynYOC2rhySGiW+AJgtItnepnZAHhlujuM4jlNwSXKU+I3AKBEpSWTl6igibwPHEVm9RorIF6razlqJGL++Sr76ttmAoavDWdoAU2/fP6hVLV3UrH17z7CnGOD2n8Kezes32W62xj/3MvVVXe4JalPPCGdlA6zr3sjUq80ITwU7/9MFZu0u00439Trfzw5qRferb9ZOHPWlqZ97W8OgNq2q7cfv2nCzqf/jM3RXowAAIABJREFUwBpBrSJLzdq3v/jF1N8/JewR//1Fex9reFM42xlgzpwNQa31Cjtf/MRetre3ePNjgtqdZ+1p1t66yfbzv3JE+LNz9QGFzNrFZ6809bJjpga1ARvWmLVXfGHnTj84b3VQW/famKAG8M1FX5j6nIlhr3TFAbZ/fJ/mFU194Sr7/cCecuJ/Js3XlPObJA/Y3YDrVLVvhq0L4FRV3Sgi4UR2x3EcxylgJNIlnmHregYiW5eqLlPVj1V1Y7zYaKBmEu1zHMdxnLSR1Bl2pq2rMTAeuEJVM/tezgfs/lvHcRxnp8a7xHNIpa1LRG4CNgIv51ac6cN+4Zlh+dFex3Ecx0mU1Nm6RKQrcDzQLjSXuKr2AfoALFrzgs837jiOs5Pitq4cUmXrEpGjgeuAE1U1PKTScRzHcQoYSY4Svxx4OR4hPh04DxhHZBIYEs8nPlpVu1srUQ1bbnTtxqAGMH2tbQGZ2z9sDa/zaEezdlmvIaZeqHvYplTsoLBNCGBF9wdMvUaN8Ovq/47dIdHkRzvacMaUcERgzUdPNWs3lLIjBKVaeHba28bYtpdNHeyYyg9P+ySofXnHD2btmjX2NttrSNh6dcxFI8za/hc3MPWasxcHtekX2kM8Nl7T3NRntG0cFjeE7XsAddWOqfz1kReD2gObbXvU8oeuM/XFk24LanWeP9esLXT1Y6Y+574Lgtq7K8K2Q4Dd+o409S+6hC2TLdruZdbOPL22qb/6ddi69WDvG83aBya/buonjPzU1Aed1NXU/1f8GnYOSfY1zIhvRYG9gfpAf9hiXF0E3JFEwxzHcRwnbSR5wM6O16wPNAZ+BHqp6n6q2gQYBNySYPscx3EcJzWkLV4zk1KADyhzHMcpwGThXeLZpM6HLSJ3A+cAy4E2CbXPcRzHcVJF6nzYqnqTqtYi8mD3yK3Y87Adx3EKBp6HnUNSB+zcfNgHbLXMy0CuQ7E9D9txHMcpaCTSJa6qC0Rktojsrao/kePDrqeqP8eLnQRMTqJ9juM4TjrwiVNykMBkYtv/iUWaAH2JbF3ZPuy+RBavzcBMoLuqzrXW8/PyB4MvoO7icHwgwMk/2P7bN1aEt02RL34OagCTRtk+1iIlwr+V9riphVk76jLb29vhqnDs4rh3bS9pw0MrmfovU8Ie2hnjfzNrjzy/jqkvKl8uqP12bjiuEaDc/XaUZK+jqwe1Bz+dada+3/UgU69aKrzNZq1caNZu3N/2wLb79Iyg9lFZe26h0QuWm3qnCz8Laj/8aH8vHNIu7JkHuOry/YLaqvWbzNqnn/7R1Gv07RrUpNLuZu2Lvww2dYszxtjbc83oeaZeqEw4krfEDV3M2mqv2Pt3izrlg9objcMxwQDl+r1v6icfUsvUXziy33btQ568tFe+H6TqV7g2lf3iafNhTwQqEB2waxHZvRzHcRynwJPkTGfZPuxTM/KwjwJ6q+r9CbbLcRzHSQlpHgSW36TKhy3+xjiO4zhOriTVJZ7pw/5GRPqKSPZFsR4i8p2I9BORCrkVZ9q6Bjw3Kt8a7TiO4+QvIln5fksrafNhPwHsCTQB5gO5plxk2rpO73pIPjXZcRzHcZIjVXnYqrplSK2IPE00n7jjOI5TQMlKdGx0ukhbHna1jMU6AN/ne+Mcx3EcJ4UkOUr8RmCUiJQENhDNanafiLQDKhKFgYRDdWPavxrOoJ3RrKFZO3DCUlN/tfNuQW3RIPu3TuWBZ5v6p4e/ENTW3PDXfdYAc4uWDGrLqoQ1gJX/ONPU19z/WlBrXiGcTQ5QaMFKU1/4eTj7ufakPmbtO1fbl0YurdosqE1fHs7KBli1wc5+1mOfDmqHnFjXrH1/lO0v7z4znE9+9flfmrXv3mf7+Rs8flxQ67NphVm7btewpxigd82wI7Nhb9t7PqXPkaY+v9WjQW3pUtuyW85+K1n+VfugtqRTWAMo890rpl7iutOCmn49zqx97T8/mXrV6oWC2tIG083aJf1uNvUffgtnbTv5S5IH7G7AdaraN8PWtQGoBhynqutEZJcE2+c4juMkTJoHgeU3abN1XQLcq6rr4scXJdE+x3Ecx0kbabN17QUcLiJjROQzETkwofY5juM4KSBLsvL9llbSZusqTHT9+mDgWuBVyWU2lUwf9qoRv+Rjsx3HcRwnGdIWrzkHeFMjxhLNKV556+JMH3bplvZk/47jOM6Oi5CV77e0kipbF/A20AZARPYiCgYJDx12HMdxnAJCkqPELwdejkeIZ8dr/g70E5HviWxd52oe+Z//vSIckTmh9iSzAU2+uNHUz771yaC2OQ8Lk9Y72NTb/VgjXPv552Ztv3PCVjaA8VPCkYwHnXS4WXvoJ0NM/eGrwlahxVd/ZNZmFQlbTwDKnhu2QK0cO9+sLbGyjKnfumBYULvr4e/M2nYda5v6xY8eGtQG/GjHrI76xY6aXHtEeF+YVcUs5fFW4f0AQJeFk2vrzLItY2dVtIP0FmSFv1pWLVpl1h7yxART3+3S8H7yckfbynncqAWmXqpfeOqHPRvaY2AX1y5u6kMkHLW64PSPzdozrt/TXnfX8Ofy/GH29+AVJf5h6h1nXmnqTv6R5AF7RnxrRE685j/j/zcSXct+kGiaUsdxHKcAkuZBYPlNquI1VbVztigiDwB2YrzjOI7jFBBS5cPO0AU4DWibRPscx3GcdJDmQWD5Tdp82NkcDixU1Z+TaZ7jOI7jpIu0+bCzOQPoHyrO9GF/vNEe1OM4juPsuPjEKTmkzYeNiBQGTgEGhoozfdhHFi6/3RvrOI7jOEmTNh82QHtgsqqGY4ocx3Ecp4Ahedict98TizQB+hJNjjIdOE9Vl4rIc8BoVQ2boDPQn+4OvoCKb9p+5mWz7O50ve/qoPZz+9vM2o+ebmnqR10YjtAc90Jrs7Zi8VKm3rpmq6A2dPZws7ZtLfu5uTv8thTr2sYsvXnuZFMvUyT8+/HDX+y4x086nmfqle7uFdSWHR2O3gSQJrZ3nXWrg1KVp581S5/KI37z5InhSNKlR9txj69PtWNaG1YKG7lfmTzPrB0wNuzhBvhH63A07cX32j7rqs9cZuofrQx7pauWsnvcRsydbep1ypYIaifWOsqsfWXau6Z+cLW9g1qLFz41ay9rXtXUL/lveJt88C/bGXvwucNN/bTLG5n6N2cN/NP00X8n81f3y/eDVLWS52/X1/RXSbKzfkZ8K0rsw44P4vWB7vE16ubJNc9xHMdx0kOqfNjAq8DtqvqBiBwL3Ae0TrCNjuM4ToJkua1rC6nyYYuIAmXjxcoBdr+c4ziO4xQQ0ubD/ifQS0RmA/cDPXMrzrR19Rk4Lv9a7TiO4+QrIln5fksrafNhXwJcqaq1gCuBZ3IrzrR1XdT5wPxqs+M4juMkRtp82OcCb8aPvQb4oDPHcRzHIaFr2Kq6QERmi8jeqvoTOT7sPYBWwHCiecR9alLHcZwCTJpnHstvkvRhHw68QzQ6fAPQEagGPAYUAtYCJ6mqaSZ9/f/YO+/oqKqvDT+b3kFEmoAUQZqAgtgFRSygoqgUsffef3b97GLvDQW72EVUEBFBFGwogvQiXQQpAkKo2d8fdxKGmLNDgGQuyX7WmpVk3tl3zrScufeed78l9wo+gPanVDHHsPbFs0y9xuejgtq6nPKZz7d92JQqEZQafP1jUAOY0dDOZ273Vzjz9+uV9uv972h7nd+Qm/YOai2q1DZrm98+wNQ/ui6cIb5H58FmbdNzmpj6972aBrXW935v1g57zfYcl5vaNagdMdn2j99UdoOpP1g/7KGdX97+R5a20c6d3uvmD4La4uX2tle/dJqp7zEt/B4c0vF9s/aKR8LvMYBpx4YzgRZd8bpZO+aRcHY5QL8JS4LamyPDedYAA86zM6sbV64R1OpXCHu0AX74y16rc3TFFmFx4/qwBlwxwX7/z16x1tQ/6/JGnnqWl6x9M98nqSqlTo+lDzuVtq7zgRtU9eUkW9dQoLOqfiMi5wIdAbv7g+M4jlNgEYqmegixISXHGpJsXX0hsnWp6j9AIzZP0EOJ9rodx3Ecp9CTqj3sZFtXS+AX4CpgItAFGACcCtjHWB3HcZwCjZ/D3kzcbF3nApeKyC9AeSDbky/JPuyhmzxe03Ecxyn4xMrWpapTVPUoVW1NlIc9M7viZB92x6Ier+k4juMUfHI8JC4iq4DgKj1VrRDSjJpsbV0iUlVVF0vUauY2YKsSuxzHcZyCiXgv8UxynLBVtTyAiNwDLATeAAToRWTD2lauAN5KrBD/AzgHOFNEMrL1PgLsbEKg69DOQe3fA2wLx67jfjH1iUeGrULNDtvfrK358ZemPjst/CasXL24Wbt20GRTH3lDz6Cmv9r2kNJ/2lagjnXCz2n9h+2Xa+RtHU390LvDz9msny43a7+p97SpH1ElHJtYokiaWfumLdPpg2lBreKKFWbtynM7mfr8c14OarUHhSNDAY779FVT//PRC4NapbeHmrUt3vjK1F87LmxTWvnjUWbt0/vbn520aauD2jm9Gpq1A2rbkaTrNw0JaosetWNBK788y9Tr/Hl7UKs4/w+zduIK2x54xbCwZXLS2ReYtftWtf/f/K/1Pqbu5B+5WXR2gqq2TPr7eREZB9yR2zsVkb2AVxN/phM1STkLeB04DqgLtAYqActzu33HcRynYOCLzjaTm2ditYj0EpGiIlJERHoRLRbLNao6VVVbqWorool5DfAx0cKzYaraEBiW+NtxHMdxCj25mbBPA7oBixKXUxPXbS8dgJmqOofI0vVa4vrXgBN3wPYdx3GcnRRP69rMVh8SV9XZRBPqjqYH0YpwgGqqmtHz8y+gWh7cn+M4juPsdGzNKvEbVPUhEXmabFaLq+qV23rniQVnJ5BN7rWqqohkuzpdRC4ELgR4/roOXHiC0UfXcRzHcQoAW7OHnbEkeUwe3P+xwK+qmtFVf5GI1FDVhSJSA1icXZGq9gH6AKSPvDY16SWO4zhOnlPEbV2ZbI2t69PEz9es24nI06p6RS7vvyebD4cDDCRaLd478fOTXG7PcRzHcQokOyxeU0R+VdV9c3H7ssBcoL6qrkhctyvwHlAHmAN0U9Vl1nZWrv8w+AAqFLO7oP3V7VZTr1ktnLD2ztVtzNpTZqWbevXJc4PaSXvbp+5PbbibqS+r/1FQm/fj4WbtPlUrm/rYxeGX4+ym7czatac+Zuolyob9oEufP8msHb8k/HwCnP/2lKC24tywlx+g78qwzxrgjIHhSNJSc8Mxk1vDd4PCrXfTvrOfk06Pf2fqG9dtDGqV6tifnR5tdzf1Z/dpH9SuHveNWfv4ajudSfaoGdYa2J7hjR+8Z+rrx/8d1MZfG45/Bdh/ddjrD6BTwz7tqpPnmbWDX8i26WMm+017Pqj9sep3s3bGP3Z87O7H2ftNzcZPydMoyjUbP833o6hlih3v8ZoZJHzY7wLzgG9EpD6Rn3sBUB1oAPTMabJ2HMdxnMJCSibsRDvSVgAiUpRoov6YKBO7K/BiKsblOI7jxAtvnLKZHTlhb+shhGQfdrQhieXRCMdxHMdJGTvyq8uT21iX7MPeKpLjNV952e557DiO4zgFga3xYX+KndZ1QuLnq7m9c8uHbZFs67IWnTmO4zg7N57WtZmtOST+SB7ef1YftuM4juM42bA1Pmzbg7F9ZPVhO47jOE4mvuhsM1vtwxaRhsADQFOgVMb1qlo/13ca2breT2xrElGc5h1Ae6AzUBRYD4xS1Q7WtlZfeWTwAZS9/xJzHGtLlzL1kpPC2dG6wD4oMPNAO5d3zYF9gtpvHx5h1p6Rg8e7Y9qqoDZ0V9vDfbnaedgnnPxtUDtqgO1nntSsqqnvfVs40/fTG+1s83onfG7qLz9zaFC75h67iV/1TvZb/Ng64ffRF4vDXmeAm5tXMPVNxsfz8Nrlzdo2V9s+7F+fDD8nOXHN13NMfdWaDUHtj7nrzNomDcuY+vefzQ9qNZ4/06y9ZfZ4U7//oHCW/Lr7njBrS11ztqlTslxQSrvHXgJU6s7rTH3ysp+CWtUrBpq1g29vZeq95tsTZpEjn87TVcIb0ofk+2nP4kWOjuXK59ysEn8F+D/gceBw4By2cdFawtbVAv5j65oEnKKqG0XkwW3ZtuM4jlNw8HPYm8nNM1FaVYcR7ZXPUdU7ifaGt5dMW5eqfqmqGbskPwC1dsD2HcdxHGenJzd72OskCgqdLiKXE+0Vh4/xbD0hW9e5RN3QHMdxHKfQk5s97KuIOpFdCbQGziAK6Nhmkmxd72e5/lZgI/BWoC7Th91vgt0H13Ecx9l5KSJF8v2yNYjIMSIyVURmiMhN2eglReTdhP6jiNTd3udiq/ewVTVjBda/InIeUE5VV27n/f/H1iUiZwPHAR00sCIu2YdtLTpzHMdxnB1NYu3Vs0BHYD7ws4gMVNVJSTc7D1iuqnuKSA/gQaD79tzvVu9hi8jbIlIhkbI1AZgkIv/bnjsni61LRI4BbgBOUNU127ltx3EcZydHpEi+X7aCtsAMVf1DVdcD7wBdstymC5ARS/0B0EG2s+92bs5hN1XVlSLSCxgM3AT8Ajy8LXecmPg7AhclXf0MUBIYmnhcP6jqxdZ2ls8Ixw8uIxyVB9DuVbut6ZBTwlaiBsvtgwuHvmHb1xdOCsfhzSpjPmSKnrWLqX/yxvKglr7yGbP2mc9yWDbwZjie87TVdrha/9X2GsIqjaoEtc6bbEvYJwOONXUr+LPCZ7eYtecMH2Tqv/0etvhVWGp/7xzXz44+rHNi2B5YYr8SZu3tN9l2nZE/LQxr9eqate1/Db/HABaMDkeOPvT8YWbt19eNNvV1xY1/qPPCli+A+9baVs5bRofbQlz7u/3/ZNf7nzb11TdcFNTmDrTjMytOsJtB7l0j/Jx8PcL+XN7WPvw+AGj6yCRTbz3VlAsquxOlTWYwH9g/dJuE82kFsCuwZFvvNDfnsIuLSHHgRGCgqm7AaFlqkfBhj2JzvOZKEblaVfdU1drAG0BL4LZt2b7jOI5TMBBNwSVpnVTicmGqnwfI3R72i8BsYBwwUkT2ALbpHLYRr4mI1AaOAuZuy7Ydx3EcZ3tIXicVYAFQO+nvWonrsrvNfBEpBlQElm7PuLZ6D1tVn1LV3VW1k0bMIWqgsr1kjdd8nOg8ti8mcxzHceLIz0BDEamXcDv1ALK2lBvIZifVKcDXoYXUW8tW72GLSEWiTmcZJ6C+Ae4GVmzPAEjyYYtIF2CBqo7zTGzHcRwHtVsx5wk5TD+Jc9KXA0OIWmn3U9WJInI3MEZVBwJ9gTdEZAawjGiu2y5yc0i8H9Hq8G6Jv88galfadVvvPDleU0TKALcQHQ7Pqe5C4EKA3s3q0KuO3R/bcRzHcXYkqjoIGJTlujuSfl8LnLoj7zM3E3YDVT056e+7ROS37bz/TB+2iOwN1AMy9q5rAb+KSFtV/Su5KPn8wvxObfzQueM4TkElFXvYMSU3E3aaiByiqt8BiMjBQNp23n+mD1tVfwcyvTsiMhtoo6rbvATecRzHcQoKuYnXbEVkAq9IdIR/GXCWqtp5deHtlSVaCV5fVf9zHnyrJ+xNQ4MPIP1bO3LxkL/siMyvfgt7vEt3b2PWTjjjfVMf/lZ4vd5lU2zv7pxnx5p6g2bheMKNhzYyazcutOM1S5x9QlAbvW9vs3bvY2qY+glHhvVnjmhh1lbs9Z6pN2haNqgNenOxWXvkQtu7fv3o8H3fO9LedqlrzzX1ifvfGNSWD+kW1AAO3ljZ1GdVDK853dA+3CcAYNZse6/n/N5Ng9r0P8PRmwClLupk6kXufj2oDX7X9ocfM+tOU5/TNRwS+P0Ie/+k+6/2Kcq0178Paj9du59Z++e/4f9FAD2pGb7fV+yY1WW3nWTqPy2yfdhdGzyRtwuONuZ/vCbFdvJ4TVX9DWgpIhUSf29zW9KED/tdNvuw6xPlYVcCLgD+Bv4h6iZjd61wHMdxnEJAblaJ70q0SvwQQEXkO+BuVc21r8zwYZ8DPK6qj+R2m47jOI5TkMlNp7N3iPZ8TybylP3Njom/zOrDdhzHcZwITc//S0zJzYRdQ1XvUdVZicu9QLUdMIasediXi8h4EeknItk2zU5uG9fnJfs8teM4juMUBHIzYX8pIj1EpEji0o3INL7NZJOH/TzQgOhw+ULg0ezqVLWPqrZR1TYXXtB5e4bgOI7jxJn09Py/xJTcTNgXAG8D6xOXd4CLRGSViGzrArQt8rBVdZGqblLVdOAlokVnjuM4jlPoyc0q8fJ5cP9Z87BrqGpG1ttJRJ3VHMdxnMJKjM8p5zdb7cMGEJET2NxLfISqfrZNdxrZut4HmgKTgLpEtq7WRIvQKhPtxb+hqpeZ27rkgOADqFzf9qEuOecUU5/b/amgVrFeJbP2pwF2xuxR8x4Kauueey2oAfzYM+xxBTioejj9+fAPXjFrm1YJe7gBJi0Je8SHTl9t1hapWNLUix/aJKjd+K/9fD7UJmt2/Jak3f1sUFt44zFmbVGxv9eOrfZkUFv7W0ezdtyS9aZ+f/FwRrguz6GNfyn7+f6sdlirW8Fu91vrOtttueSJ8OtR9Xr730b1yvb/pOPb1QtqR9e137/XD7Bzp998cHZQK5LD8cijnrEPCOrqsP98whN208gcXkoO7hl+Trq2CXu0Ad4aaj8n036zD6DW/uLXvPUsr/00/33YpY7fuX3YItIb2A94K3HVVSJysKrayerZkLB1tUhsN9nWNQ6oAXRW1XUiUjW8FcdxHMcpPOSmNWknoFXi/DIi8howFsj1hJ2FTFuXiDwM9FbVdQCqareJchzHcQo2fkg8k9wsOoOoE1kGFXfQGJJtXY2AQ0XkRxH5RkTsfn2O4ziOU0jIzR72/cBYERlO1Ev8MOCm7bnz5HjNpPFUBg4gOvz+nojUzxr6nRyvyWH1oKkfOXccxymQ+B52Jls1YYtIESCdzRMpwI1ZYy+3gS1sXcB84KPEBP2TiKQDVYi6qmWSHK9pLTpzHMdxnILCVk3YqpouIjeo6nvAwB14/1vYuoABwOHAcBFpBJQAPF7TcRynsBLjRib5TW7iNXsTTZ7vApn+HVVdtk13nE28ZuIQeT+iTmfrgetV9WtrO2s2hpf8H//JO+YYlqVtNPXfRoXbm9doaUdFLjihg6kP2TA3qFUtU8GsbVipmamfOPCDoPbG69PN2ruusmMsB04Jf39a0KqhWbvxV7tdfIlzewa1b/ey1zY+8qxtqfm4WNjuI7Wrm7W61I42lLLhbU+sb7+WzSu1NvUlZ94Z1L67x37MJ1Y/zNTr938zqI0evMCsHfmAvbxk/+phi97JA78xa9M22v+gv/smvBb1ratty2PN/c1/J7z5/gFB7cxuP5i1+yy6ytR3Lxv+fBQZZMfxrvhoqqmffeIeQe2iM380azstCdtXAZq99bKpTzzr/by1QP37Yf4fRS138s5t6wK6AwpcmuX6+rm9UyNe80BgL2Aj0bnsx0ikejmO4zhOYSY3E3ZTosn6EKKJ+1vghW2501C8pqo+kXEbEXkUyKEzhOM4jlOg8UVnmeRmwn4NWAlkHD85LXFdt+0cw3/iNUVEEts9Yju37TiO4zgFgtxM2M1VNfkE0XARmbQDxpA1XhPgUGCRqtonXB3HcZyCje9hZ5Kbxim/ikjmigwR2R8Ysz13nk28ZgZZV49nrcvMw+730hfbMwTHcRzH2SnIzR52a2C0iGQsb64DTBWR3wFVVXt5cfZk9WEjIsWAron7y5ZkH7a1StxxHMfZyfE97ExyM2HbkUbbRnZ70kcCU1R1fh7cn+M4juPslOQmD9s20eaShA+7I3BRFim7c9pBaj/+fFB7t0dLs/aAB38y9bKXdwpqh02cYtamPZpDf5krw2611nfY8YNfDwj7ZwHG37BnUPvkXtv3+8Ju9nN2UI3xQa3zFLvx3f/uHWfqDT6eFtQOGX2xWdvs9g9Nfde9yga1MfePMmsfvzfszQV42oii7DvRji68pIX9ETygRdjH/WU5Oz72jvGDTX1Q1/DjKjLkI7P2+Nf/MPWS+68Laq8es49ZO37JPFOvULx0UFuxzt4bO/NMO2ry4pnhthK9mxU1a4/+0PZ4H1t/bFC7tr39uay1m/1af7xiVVCr97Ddt+G9vWz/+G/Tw/GxTv6S2/CPHULChz2KzT7slSJytYi0AhoDFyfOUdudIRzHcZwCjeqmfL/EldwcEt9hhHzYwEvAXao6WEQ6AQ8B7VMxRsdxHMeJEymZsLOQnIetQMYxwIrAn6kbluM4jpNyvJd4JnGYsJPPWV8NDBGRR4gO1x+UXUFyvGaZrs0odUCd/Bin4ziO46SMlJzDziAbH/YlwDWqWhu4BuibXZ2q9lHVNqraxidrx3GcAoym5/8lpqR0wua/PuyzgIzlqe8DvujMcRzHcUj9hJ3Vh/0n0C7x+xGAtyZ1HMdxHHKRh71D7zSydb1PlAA2CahLFK+5HHgWKAqsBbqo6khrW+XvPDL4AFZeeaY5jver3WfqBy2/LqjVYlezdn63B0y9cpOwr3L9/ReYtc1fe9vUi0o4ynVWvd3N2her2RnhC1eHLQ81yto+1fOG/23qI05sENTO+szOA/781Dam3uiu4UGt7CXtghqAzrHXPu4+O+w/79E87NEGuOutGaY+6Lqwh7b5rrXM2iZD7Fb/xb4N+97T78uaorslt039ztQ3GEcV9961uFlbp8MwU297bvh9Unc3+z14azv7/b9hU/j/YcvddjFr1+9te9ffee/goNZ81xJm7Yr19mHaexZuCGob54c92gDFO9hNKk+cab9HPznh9TzNjtYl/fJ9kpIq58YyDzsle9iqOlVVW6hqMWAfYA2RretyoLOqlgauI2qs4jiO4ziFnlQfEoct4zUbARl71EOBk1M2KsdxHCf1+KKzTOIwYSdfdmpkAAAgAElEQVTbuiYCXRK/nwrUTsmIHMdxHCdmxM3WdS5wqYj8ApQH1gfqMuM1N/yyIH8G6ziO4+Q/voedSar3sLewdanqFFU9SlVbE+11Z5uckOzDLt7aXkTiOI7jOAWBVE/YW9i6RKRq4mcR4DbghRSNy3Ecx3FiRcpakwbiNXuKyGWJ3z8CXslpOyXKhu0QUqr89gyRnxaFbTG7DZhr1tZvHI4ABGjYomJQe36pHUNZuphtXalTsWRQe6e2fbjn4o01TP2P698PanvuHY6wBLCNQrCpafi+fx9lW8LalgxHFwKM/GNFUCtX344U3dTkQFP/c2I4njOtiR2bOPWi/5l6jyeuDmq6ZrlZu/Bd22aU/tqVQW3ZFfZ35XufvNDUGw0Ix8v2fHiCWdtq5DmmvujGj4Pa+5ccadbWKGvHVK5avyaozf83HL0JcPywU0397zLh+uPqHWrWrjnxYVPveEGToHbv4/bz3aakPQ28eW53U89zvJd4Jqncw74Q+AsYJSL9RaQUMJDIi10EqAfYhk3HcRzHKSSkKg97d+BKoI2qNidqlNIDeBB4XFX3JJq4z0vF+BzHcZyY4IvOMknlHnYxoLSIFAPKAAuJ2pF+kNBfA05M0dgcx3EcJ1ak5By2qi5IRGjOBdKAL4FfgH9UNaM35nzAl4A7juMUZmK8x5vfpOqQ+C5EDVLqATWBssAxuajP9GGv/cFe/OU4juM4BYFUHRI/Epilqn+r6gaiFeEHA5USh8gBagHZdkXxPGzHcRynsJGqCXsucICIlBERIeonPgkYDpySuM1ZwCcpGp/jOI4TB3zRWSapOof9o4h8APwKbATGAn2Az4F3ROTexHV9c9rW3HnZdi8FYGGv3mbtkb2qmnqlRWFXWZlFS83albvafs+xd/4e1A76YZ5Zu66JHav4xeHVgtpJj/1g1l64i+0fX/Vo56C2acEis3bszd+bepGH2we1ooceYtZ+kWY/Zw0mh33cq/u/a9YW62Zn0FyzPNwed/T7U8za+5bayYE64cegVrL/t2bt+ndvN/XVRcP/mMrvV92sHbZ6sqmPn5UW1I671/amf7pHU1Mfcs+coPbj1HDUKcBhR4b7CAC0XnZRUDvgxs/N2h9+tn3xN/2vcVA7+vYnzdpfnrMjYO/tMDio7Tr2fLO2yKDxpl5uyUJTx27d4OxAUtY4BfgHyAhXLgYI0AmoDDQADlDVdSkam+M4jhMHvHFKJnHzYY8iOr8d/grtOI7jOIWQVO5hZ/iwNxD5sP9U1bEA0Wltx3Ecp9AT43PK+U1K9rBVdQGQ4cNeCKxQ1S+3tj7Z1tVvgsdrOo7jOAWf2PiwReT0ra1PtnWd29x7qziO4zgFnzj5sA9K0Vgcx3GcuOK2rkzi5MO2fSKO4ziOU4gRVdsHmmd3LDIEaA8o0XnslsDXiZ/FiHqM91dVO7Er7ZPgAyh5+6N26WGN7DHWDhsMR3Sy/Zwf9rfzbZ85MJxr8tnCr83aTnPt12zeXeH6uo1KmbU3ndHC1GuUDWdxj10c9sQD9C1fxdT1j7Df86JqdtLqbqXtjPC7fgz75ovWsnPTix4T9p4DpI81/OU5ZJfnaFlZFs7x1rQNZmnRLqeY+tILHgxqu5zXxqw95C/bc9+/c/j9X/35oWbttz3DfmWADmsrhMWKu5q1Vd8K53QDjDqnfVBrON3Ow/60ylpT39g07OMe9JndZ+DZ9vZrWeLvsLHm4kljzNrrc+iP0OmicNY2wPRzP8jTVcI666F8n6Sk3g2xXPmcSltXI6CSqpYCfga6AncAJRLj+gSw32mO4ziOU0iIm60rc6W4iPxE1E/ccRzHKaykp+YocByJpa1LRIoDZwBfpGJ8juM4jhM34mrreg4YqarZNktO9mH36Tsk7wfsOI7jOCkmVYfEM21dACKSYet6U0T+D9gNCHbhV9U+RGEh5qIzx3EcZyfHe4lnkqoJO9PWRbQavAMwRkTOB44GOqjG2AznOI7jOPlM3OI1VxMFf3yf6Cf+karebW2rxK2PBLV1t9qOsPV97bjt+Q+Fow0P/yNsiQG46zM7svG9ctcGtVatbCvQ2fcdYOpp17YKapvW5eBW+Mc+S7KidfugdvnCEWatFLetWXJk2Nry0kK7BW3RPnZn26ZX7BvUznzyF7N2yfFHm3q3v8MWpxEjZpm1Q26wYxMf/TscWPd/7RqYtfvPm2DqZ51SL1xbJhyPCdC391hTn3xg7aBW5Gs726fFGDsic/SP4RjLVavsA27TTrRjQ0s9Ojwsnn2YWbv7MR+Zeofb6ga15Xva1qmhC0aYer+J4ffg3Xf8ZNY2uO9wU//yge9MnXNtebvxPexMUtU4BbKJ11TVYqraABgJ7JnTZO04juM4hYW4xWsiIm2AXVIxLsdxHCdmpGv+X2JKKvewM3zYxUj4sEWkKPAwcEMKx+U4juM4sSNuPuzLgYGqGu5R6TiO4ziFkDj5sM8ETgWe3or6TB92+nh7gYrjOI6zE5Oenv+XmBKneM27gD2BGSIyGygjIjOyK07Owy7Swl716TiO4zgFgTj5sB9T1cy9axH5V1X3TNH4HMdxnDgQ4z3e/CZuPuxcs+6STkHtf5NGmbXXXmbHJs557OGgVvezj83aIV3PMPWNa7oHtXJXPmDWXlLcPjDy4rdhT6ZcdrxZu+r/bP942T+MiMF99zBrlz0xwtT/fe60oDa9sh3dWbVJVVPvtVfXoPbdqWGvM0Dtu+23ZqmK4cjStL3s/JriRXc39SkN/glqze4aadYefoR99GnEyeE+BWd+9ZZZ2/hj23zb/JEBQa3/sNVm7anjw68VwOmTpwS1iiXtf2nXLbHv++kODYPaEbu3NWtLFH/F1Js2qBzUqg34xqwd9tJ0U+86Nbyyefxku49AnbftXgFjf7BjQ8NufmdHEysfdoL7RGQaME9Erkzd8BzHcZyU47auTFKyh53kw26qqmki8h6RD1uA2kBjVU0XEXu3yXEcx3EKCbHKwwbuBU7L6COuqotTOD7HcRzHiQ1x82E3ALonLFuDRSTbE0pbxGu+Y/fJdRzHcXZi3NaVSZx82KcDJYG1qtoGeAnol119sq3rwh72QhDHcRzHKQjELQ97PpEnG+BjwF526TiO4xRsYrwILL+Jkw97DLASOByYBbQDpqVofI7jOI4TK0Q1Nd9eRGQI0B5QovPYLYEvgGZACaIEr+9U9QhzQ6veDz6A52d/bZaeM/BPUz+kbthf26lBRbP24gd+M/VqpzcNakUa2X7maiN+NfUiRcNnOhYZublbQ519awa1GVLSrC1+1pmmXuLG+4Pa60/a6w8PWXGdqfeZMCaondUk/FoALGvzgqlX/TXsPqz60Odmbal7rjf15q89F9QmdD7WrJ3R+VFT3+OMZkFt0dn2x+6kT4zcaODrU7sFteL3ZHumK5MFX9l52fVHPxnUZLztTR9ccY2pV2z3aVDb738tzFopZefYf3jYrkGt4z32/4vh/xfOcwfY5+zw63HTza3NWuPfBQBXXPyDqR88Z4rYW9g+9Odb8n2Skv3uz9PHtK2k0tbVCKiUZOvqqqoHJd3mQ+CTVIzPcRzHceJGrOI1MwQRqQAcAYTbJTmO4zhOISJVrUkXiEiGrSsN+DJh68rgRGCYqq5Mxfgcx3GcmBBjm1V+EzdbVwY9gf5G/WYf9itf5e1gHcdxHCcGxM3W9aaIVAHaAieFilW1DxlhIcaiM8dxHGfnJhULo2O54ozUncPOtHWJiBDZuiYntFOAz1TVjohxHMdxnEJEHOM1ewC9t3pjxUoEpYYdbFvXtMlnm3qr32YEtfa1qpi169+0LUxFlofjIn8va8c9jvlsvqlXPTQc6biBMmbtgKuamPrl74dj/soss61XT00ZaOob0jYEtSNODkcTAvSbYlvdPp2xIqhNW25bat5+8EBTn905bPsqcmx9s3bjy3Z0Z73dwtbCso+9Ydb+nLbJ1Iv3OCao1ZppW6vGjVlg6nXnvxzUll7Wxaz96d7HTb3v9+EI2I5d7ZjKo/58xtTvfjf8PjmQXczay9OWmvoTX4Y/H6Ur2edpN1Zobuo8WSEovfi0/ZzUrRd+jwE0fq+dqR9sqjsAP4edSdziNTsAFYDeIvKdiOyZstE5juM4ToxI1aKzjHjNNqranKhJSg/geaCXqrYC3gZuS8X4HMdxHCduxC1eU4n2sAEqkuTNdhzHcQohfkg8k1j5sEXkfGCQiKQR9RU/IBXjcxzHcZy4ETcf9jVAJ1WtRZTU9VigfrMPu++Q/Bq24ziOk9+ka/5fYkqcfNgHAy1V9cfEbd4lCgP5D1v4sNM+ie+z6ziO4zg7iDj5sCcBFUWkUeI2HdnszXYcx3EKI+np+X+JKXHzYc8HPhSRdGA5cG5O20ofFW5NuuS7jmZt/ZOC3U8BeLJ1taBWcr7tlf7uSLtXzh4Vwn7nljfbXtFDLrC90iPbtw9qZe951axdeIftZ15+ejiSsXvRjWbtxTX2s/Xbwo+ryL1vm7XptVqZ+iPfhGMTx57Q1aydsmmuqfdcE45sPKx22B8LsHaTfYDojYPD7+HKX9h+5Zz+70jFGkFt9X32Z2N1g3DMKkCVpcvD4pzZZu21Tzc29QXzwp+9ogvtKNSGrzxr6pfua/RXmG88JuCwLt+a+pTFZwe1+2bZfQbW71rb1Mve91pQW/TC5Wbt7xvsx3X8xyNM/c79TdnZgcTKhw2sADYQ2bzmEO2JO47jOE6hJ04+7NOA14AeievmAGelYnyO4zhOTPBD4pnEKQ97NbBeVacl9KHAyakanOM4juPEiZRM2Kq6AMjwYS8kOhT+HlBMRNokbnYKkO2Jmy1sXZ9PyI8hO47jOKnAbV2ZxMaHDfQiak/6uIj8BKxi8znuLVDVPqraRlXbXNg5h6b4juM4jlMAiJMP+yBVfRM4NHHdUUCj8CYcx3GcAk+MzynnN3HyYU8WkaoAIlISuBGwPRqO4ziOU0hIpQ97HpHXWoHfgQuBb0WkZeK6aUQ+bZPLi6YFtSe++Mes/btiSVOvX690UFs3/2+z9rRpdsbs7X/PCmoLHjnfrE1X+xvnfML6pnuvMGunH3Wvqa9qFz4FcU96OM8aYE6xsF8ZoO4uYR/2aV1s77lOmmTqf5/aIagN3+v/zNqD5tt+56du7hvUiuTwlbh2o/B7DIDPwj7soiWKmqXNB11o6rs+8XRQ63jU7mZt/2YtTH3yZWEf92PH25/LhT1PMvVpHR8Mag1OPd2u7XqiqRcxeiBcdZadC71HHbv3wmEvjAhqyy+w19dOXjHe1L8dGM7irobd12Ht43ea+uddU7k22UkmVeewmwO1gF2AckSLzmoTxWmWVdVSwGDg5lSMz3Ecx4kJbuvKJFVfnZoAP6rqGlXdCHwDdFXVLxN/A/xANKk7juM4TqEnVRP2BOBQEdlVRMoAnfivhetcor1sx3Ecp7Ditq5MUuXDngw8CHxJlMj1G0kWLhG5lajH+FvZ1Sf7sCd9NiUfRuw4juM4qSVlqwlUta+qtlbVw4gWn00DEJGzgeOAXqqa7VedZB920+PsoADHcRxnJ8bPYWeSKh82IlJVVReLSB2gK5HN6xjgBqCdqtpLih3HcRynEJGyCZsoRnNXonSuy1T1HxF5BigJDI3s2fygqhdbG3ns20VBrdgh9cwB1Jo839T/veS8oFZ2k31wYv7Ghabe6P6w7aXPHj+btXcsWG/qakQ2ytf2KYTrHjnI1NsunhnULh34h1l739F1TL111XDM31lNq5q1UrqhqevYsUGtUZvyZm2Jv+eY+qpV4ef7f0/a9qe7LrTtOg1ahS1nG8fbdrONb2d7RimTipXDlrL+LdsENYAaHw01de0Yju6cM9j+bAw7c6qpV/nyjKCWtulfs7bYo3ZsqD50XVCr9NTLZm33voeY+sYRYSsnJcqYtU2W21a4urc0DWqLzjjVrP1+D9vquctvZ5t67XKm7OxAUmmw+wBIJ/rSsHfiuv5Eh8cBFgN3p2BcjuM4TlzwQ+KZpNKHfQHQFmgJHCciewIPq2oLVW0FfAbckYrxOY7jOM62IiKVRWSoiExP/NzFuG0FEZmfOMJsEjcf9sqk25Ql6njmOI7jFFZ2TlvXTcAwVW0IDEv8HeIeYOTWbDR2PmwRuS/RtrQXvoftOI7j7Hx0AV5L/P4akG1PXBFpDVQjsjjnSOx82Kp6q6rWJvJgX55dfbIPu+8Ye0GQ4ziOsxOTgnPYyXNM4mI35v8v1VQ1Y3XlX0ST8haISBHgUeD6rd1oylaJq2pfoC+AiNwPZF2y/RYwCPjPMllV7QP0AVh79/F+2NxxHMfZYSTPMSFE5CugejbSrVm2pSKS3Tx1KTBIVecnXFE5EjcfdkNVnZ64SRfA25g5juM4sUNVjwxpIrJIRGqo6kIRqUHkesrKgUSnhi8lCsEqISL/qmrwfHfcfNh9RWQvIrvXHMD0YAMc0ShsApw+zvYFD/s47PsFKMcDQW1TRzvusVbnU0x9efmKQe3flu3N2lnX3W/qE38L+7Q3vX2oWVukzXGmrn+MC2rdru1q1r5TzH45F888Iah1HDLPrF1/fntTL1Ej7Lnf/WM7UnStbDT1k87/z9GuTPofYsdUXni/3R9oyeWXBrVSt/Y2a8ffcrypT+472tQt/jrLjrGs8Fh456TsktVm7cb1lew7t9oQ/D3RLN20Z3CxLgBj294e1JbefYBZK+uLm/rcfWoGtZpvf2DXFrXjevt22iuo/dX2LrO2/YmVTX3GKbZ3neHWeqrtx+orEWMGAmcBvRM/P8l6A1XtlfF7osNnG2uyhpj5sFX1ZFVtTnSS/jhgXeqG5ziO4zjbRG+go4hMB45M/I2ItBERuwOPQUr2sLP4sNcDX4jIZ6o6Q0RqA0cBc1MxNsdxHCdGxDg9K4SqLgU6ZHP9GOD8bK5/FXg1p+3Gyoed0B4n6ie+871KjuM4jpNHxMqHLSJdgAWqGj5Rypa2rkXDZuTHeB3HcZxUsEnz/xJTUnJIXFUni0iGD3s1kQ+7JHAL0eHwnOozl9wf9E7P+D67juM4jrODiFMe9kSgHjBORGYDtYBfRSQ7n5vjOI7jFCpi5cNW1SeT9NlEy9yXpGqMjuM4TmrRnXDRWV6RSh/29yKSYVLtq6r/AIjIFcBlQE2iLmdmWOvoE7oFtVJ3PmEOYK/9Kph6hZphfeT+YU8lQMebwh5ugKVrwp7NXb74yqxt1KW2qc9vF9Zu2MXuqNNr3xtNff9jdwtqrz5u5y/vu+w/iyO3oNun4Rzww35fatYOKnW1qXd9pW1Qm32h7YFt8PkNpv71+9n1RIhoU9VunTvwDDt3+pmpnwW1NZ32MWsXFLODikteeUFQ+32fa8zaXjfYOd8rzg97wHW63R+h5ahfTH3uvBVB7dv+9vPd4lDb4z1ztxJB7ZsD7c/84avsTOtBK8NZ3VPuGmDW3vCU3T+he/GSQa3oN+eZtaUeHWzqRYulmbqTf6TS1pUGVGazrWtPogCQLkBLVV0nIlVTMT7HcRwnJsR4EVh+k6o97ExbF4CIZNi62gC9VXUdgKqGd10cx3EcpxARK1sX0Chx/Y8i8o2I7Jei8TmO4zhxYFN6/l9iStziNYsRHSY/APgf8J5kE2OS7MPu02+rYkQdx3EcZ6cmbvGajYGPVFWBn0QkHagC/J2ldnP02ZqP/QSH4ziOU+CJla2LKAzkcGC4iDQCSgBu63IcxymkuK1rM3GL1+wH9BORCUSrx89K7G0HmdX5zqB28OXNzQHsVeovU/+nTniRevF7h5m1xUrZT23a42cFtSq39TVr1z56p6kzLGwRuemFX83SmoZtC+CjK8P2qPvb/mnWfjv4d1Mf1zr8ei0dMsSsPeHOxqb+3hk/BbXTVtlxpQOr32LqB/x9a1Arde1zZu37q22LXs+Hw89Z9TZ2VGTnDatMve+68HvhmacOMWt/K2ZbIm+cPSGo3XJgR7N22AuPm/qbN4UtZdPvnW3Wvj8g/P4FmFIsbI8q89+zc1uyZq0pTzgv/Lnce7QdgVlj+nBT1wPfCWrNjrPjMzecmkNs6KnlTd3JP2IVrwm8ATQHNhKdy34sNUNzHMdxYoH3Es8kbvGa3ZNu8ygQ7pDgOI7jOIWIOMZrklgZ3g3on6LxOY7jOHEgXfP/ElPi5sPO4FBgkapOT8noHMdxHCdmxM2HnUFPjL3rZB92/z/tHtOO4ziOUxCImw8bESlGdHi8tVGb6cOedXjL+B6/cBzHcbYLjfEisPwmbj5sgCOBKao6P1VjcxzHcZy4ITnYnPPujkW+BTJ82Neq6rDE9a8CP6jqC1uznTmrngs+gKVrl5m1rabbi9D/uC4cO/fJs7ZP9eopa0y95pJ/gtqYQfZ3lSZtbf/tb0MXBbXb7rDjHN85srupT1g5Lqg1+9f+/rf2lRGm/vOFrYLaKxMXmrV33D/G1Ou+f1VQK3J7H7M2J099sZJhPaemDwNetnsBHLDw3qD20+63mbWdelUxdSs+9seLba/0jd+G3wcAV+8b9pd/PCP8/gTo1biOqbd7KuxJ/qTPArO2w+cnm/o/LVoGteq3PmvWvnz+3qbebWC4T0HJS083awcs/s7Upy0PR2B+OnOlWTtouP0erFjEjtdMf/b7HAzq28f6p07J90mqxJUf5Olj2lZi5cMWkVZE7UkvTpyjtrscOI7jOE4hIVY+bOAh4C5VHSwinRJ/t0/FGB3HcZwY4OewM4lbHrYCGcfpKgJ2r0vHcRzHKSTEzYd9NfCwiMwDHgFuzq442db19iv2uR3HcRzHKQikZA9bVSeLSIYPezWbfdiXANeo6oci0o3I9nVkNvWZti5r0ZnjOI6zc+NpXZtJ2aIzVe2rqq1V9TBgOTANOAv4KHGT94nOcTuO4zhOoSdlE7aIVE38zPBhv010zrpd4iZHAN6a1HEcpzDjaV2ZpDIP+3sR2T3xe99EHnZv4DMRKQqsBbrktJFbRv0c1N48oINZu7ClnV979U1hf+IN1W2Pa5Hi9lP7U91w1nbty/cyaw8a8Iqp73nDpUHt7QnhXGiAas8/b+q/nHtcUCv94Ftm7bpV60z9hWXhNrPVyxY1a2v1aGLqS8uVCGob9qtv1i7ufoSp11ga9rmueTzs5Qco/ba97cn73R7UOg62PcWvV7D7DCxK2xTUGpYP+5EBzmw6z9SXpP0b1F78YoZZ+1jFmqa+tHQ4n/mrn8LvT4AJx31k6qXKfhLU1o1+wqxlvd17Ib15+L2gy+aYtaMXrjb1y+4If64vbbKrWXtrjwamnn7Aiabu5B8p2cNO2LrSiDKvywF7iciewOVAZ1UtDVwH2N0bHMdxnIKN72FnErd4zUbAyMRthgL2LoTjOI7jFBLiZuuayObD4KeyZeSm4ziO4xRa4haveS5wqYj8ApQn6oL2H5J92DMGTc2nUTuO4zj5jaZrvl/iSqxsXao6RVWPUtXWRHnYMwO1fVS1jaq22bOTvUDLcRzHcQoCsYrXTLquCHAbsFWJXY7jOE4BZVN6qkcQG1Jp6/pQRDLiNS9L2LquEpHLEvpHgO1fAt7+ZHJQGz47HGEJ8Mglk0z9jr96BbUzB483a8ctDltmAIpcenRQm7fGtp9/QXFTX1e6TFDbbcivZu13l9s2oxu/+z6oHbx/LbN2Uw6Hmq5+M/xapt12hVn7RuWvTX3cz98EtUd//sOsXTJ8rqlz5/FBqUQz2/636SjbMtN0r3pB7eN0u9X+YdVsa9bDv4QtkTMODseRAvTqELYlAqy+J2xHe6pXtme6MlnxePi1Aih3aPh9NmCm/Zk/4dNOpt7jpbFBbdON95i1a6/rYerfnDciqK0YVdqsbd/Zfk5+NhIwDyq3yqy9oLlt65q9fpap1y1pys4OJE8nbBHpBxwHLFbV5onrKgPvAtWB2UA3VV0uIo2BHsAewK2q+khejs1xHMeJP3E+p5zf5PU57FeBY7JcdxMwTFUbAsMSfwMsA64kCv1wHMdxHCeJPJ2wVXUk0UScTBfgtcTvrwEnJm67WFV/JjpE7jiO4zhOEqk4h11NVRcmfv8LqJaCMTiO4zg7AzHuPJbfpMzWBaCqCuT61Uj2YTNpcR6MzHEcx3HiRSom7EUiUgMg8TPXM26yD5um9mpVx3EcZycmXfP/ElNSMWEPJMq9JvEzHI/jOI7jOA4AEh2VzqONi/QH2gNVgEXA/wEDgPeAOsAcIlvXMhGpDowBKgDpwL9AU1UNZxcC6PDgA6jymL3gfPns5aaevjFs2K/WzD71fuY+tn7PD0uCWuXltpf06dMam/q5DcO+4PRvBpm1S/qMMfUqpzcLav9+nm1jukwaNgvHIgIsnhw+2FKhZgWzdvnedtv5TQvDcY/FDgs/JoD+ze3Y0Dc+ahvU7jvE7sT362LbS31+45OC2vw02x87ZbmtN7n0q6D2y1OHmrXD59ne3qv32SeoSdeXzNpa/2f3AvizVfg53T3N3geZX3qjqU+u+3hQe7bf/mZt9y4/mnrP8T2D2qzL7NjPPS4LP58A6f+Eo2urr7T/ha7+247u/PbjRaa+3/QpYt5gO1lz07H5vstbpvfgPH1M20peLzpLA4oCU7P4sDNmwuRz2B2IVpQvB1YBl+Q4WTuO4zhOISFOPuxZQDtV3Ru4B+iTx2NzHMdxnJ2GPN3DVtWRIlI3y9VdiA6TQ+TDHgHcqKqjk27zA2D3uXQcx3EKPjFeBJbfpGLR2db4sM8DBoc2kGzr6tPns7wYo+M4juPEilSGf6CqKiJbfH0SkcOJJuxDjLo+ZBwyNxadOY7jODs5ntaVSax82CLSAngZ6KKqS1MwNsdxHMeJJbHxYSdysT8CzlDVaSkYl+M4jhMzNF3z/RJX8tqHPROoS/TFYAGRD3sE8BNQnsi+1UZVZ4nI50AnYG2ifJmq7p7TfWx87fTgAxhwcFU5dF0AACAASURBVGWz9pSqB5v6pb8MDWrPtjzMrK3x9oem3v++qUFt8Af2tq993M7iPuqEOkHtneNam7Xjd+tn6iWmHRvUjnxonFlbsYgR2gtsPLRRUCvS6Siz9trxdl7waed9G9T2G3ufWbv+pbdNvezcsE/1u4Fhvz1A50vtLOKlM8IHmnZrvJtZO+132ys9+oOFQa3T30+YtetftKPqi3c5KKg9sXSKWXu12o9Ll68Iamu/sL/r/9J/tqkf9EjYa73k+MPN2qJF7DOMyw69P6jVv8r+XD7QKJxxD3DbbuH30bsb7Dz3MvuG/88BzPzOftzXtHohTz3Lq6/pmO8zaNnHh8bSh53Xe9jnAPsBE1W1lqr2BS4CHlbVEsDDwMWJ2z4MfK6qpROXHCdrx3EcxyksxMbWlZfjcBzHcXZSPK0rk7jZug4UkXEiMlhE7H6RjuM4jlOIiFO85q/AHqraEniaqOd4tiT7sF8aMT0fRuo4juOkAl90tpnY2LpUdaWq/pv4fRBQXESqZLeB5HjNC9o3zK9xO47jOE7KiJOtq7qISOL3tomxuRfbcRynEKObNN8vcSVPF50lx2uKyHwiW1dv4D0ROY9EvGbi5qcAl4jIRqKUrx66FZ6zF/YJRzZ+MdGOzzy5kh0r92yLYLM10irsYtY+cZVtXdlglN/w3ESzdkXfHqZ+2bywZazFXQPN2o3rnjL16QdfG9QqDL3D3vZgO9qzzYa1Qe3nT74wa5/4YYap3zDuhqA2sOotZu3xo+zne0OjM8Nas3fM2ocOst9HPRpdHBZve86sLdlxD1P/69qmQW3UnteYtQcN7G7qcyqF/7VcXTZs+QKo+Y4dNVmvcumg9vOGcIwqwLz9K5n6tAfCEZkN/rS3XeKC00z9jZfCds2PptnBhIP2yZqhtCUnDv44qI2cGI6tBRhQ0XYwVS6Z0jOnThJ5/Uokx2tm2LqUbOI1VfUZ4LLE3+WBB/J4bI7jOI6z0xCbeE0RqQQ8B5ygqs2AU/N4bI7jOE7M8UVnm8nTCVtVRwLLslzdhch/TeLniYnfTwM+UtW5iVr7OI7jOI7jFCJSkdYV8mE3IloZPoLokPiTqvp6CsbnOI7jxIT0GC8Cy2/i5MMuBrQGOgNHA7eLSLbNpZN92KM+mJQ/g3Ucx3GcFJKKPexFIlJDVRdmidecDyxV1dXAahEZCbQE/tPNPzkP+5nxl/jXL8dxnAJKnM8p5zex8WEnfh4iIsVEpAywPzA5BeNzHMdxnNgRGx+2qk4WkS+A8US2r5dVdUJO93Fu005BrceDvc1aPeFse+OfhGMV686x18QtfCMc0wcw4d6fglraUjuGskE5u836rIrhuMf/dbdrJ+57lanv2bNxULvh92Fm7QM5nIu6uFU4DvXfJ+zvbqsr2/7aMsVrBLUeV9Y0a2c3siMwH/j5s6D20lz7fdImBw9s9xeeDGpSprhZm74s7GsHOLtJ2D/+0uf2a3XA+Fmm/tKacHTnyXuG418BJp3X09SrXB9+Tn68PRz/ClDphfDnDqDq9e2CWtuZs83a6/8cburXvvhbUNvUsYlZK4vnmfqKdRuD2pkH1TZrD9mjqqmPXLXJ1J38I68PiSf7sJsDiEhlsvFhi8j/gF7A+sS4HhWR11U16ypzx3Ecp5Cg6ek536iQEBsftqo+rKqtVLUVcDPwjU/WjuM4jhMR1zzsnkD/PBya4ziOsxMQ597e+U3c8rBJLDg7BvgwtIFkW1e/l+we047jOI5TEEiFrSsTVVURyfr16XhglHU4PNnWtWbjp/71y3Ecp4Ditq7NxCYPO4ke+OFwx3Ecx9mCOPmwEZGKQLvk6xzHcRzHAdmKyOlt37jITKAu0ReDBUQ+7BHAT0T9wlcBbVR1VmKyHpG4/Z/AI6r6Sk73sXL9h8EHUG7E12btpllLTd3yse5eYoNZO3+1/V1o0/LwtufcfqRZ22RtWVN/eGHYvn75+3PM2krr7czf6eNWBbU6r4R9vQAXz7DbyD72aXhsZR+40qxNH2FnbVebHPaxzl1i20ZK321nQ39T54qg9uPA9mbtg1/PNfVW9cN52YMXrDNr3zzS9te2u/DboLbn3vZ7rGKtiqY+fkTYf16ja7YdhzOpvcn2j/95Wfi9UP72+8zal86w/c5VD/0qqNWbfolZu8tVwWU3AJzTtV5Qu/822x/edISd2T5m//uDWotzw70TADatsN9HP79he+7bLZhiNxPYTv7ucVC+HxPf7Z3RefqYtpW83sM+B9gPmJiUh30R8LCqlgAeBi5O3PYy4EtV3YVoFfmjIlIij8fnOI7jODsFcbJ1KVBeRAQoRxTLGW7f4ziO4xR4fNHZZuIUr/kM0fntP4kOl3dXVW9x4ziO4zjEK17zaOA3oCbQCnhGRCpkV5fsw37l5aH5M1jHcRwn30lP13y/xJU4xWueA/ROTOIzRGQW0JhogdoWJPuwrUVnjuM4jlNQiJOtay7QAUBEqgF7AX/k++gcx3EcJ4bEJl4TuAd4VUR+BwS4UVWX5HQfCw+4LajN++REs7bjx7+YevcTwnaIv2vuYdaO7PSuqR/29RlBrWbZ+mZttTdeN/UrDgzHRRbdrbRZ+/TRdU29zrpdg9qH62ebtftXtxf9l2gUjtdck8M7tcEf4ThHgNHnHhHUShex4wf/2fiPqW/44aSg1r6E/XyvOcw+QFS+eNhdMvYG+/177jn3mPrimmOD2ugvlpu1K1bYeo/n9g1q77461axd+Oblpr44LWzR+3WQ/T4Y2m0vUz/2uOpBLa1YObN2xoMdTf1mY0lO3fZ/mrUjmoVtWwDtXjosqEmb8GsBwJzZpnxf2/BnHqLGGXmJ9xLfTGziNRO3XZ34O43ofLbjOI7jOMQoXhO4BfhNVVsAZwLhlHrHcRynUKDpmu+XuJKnE7aqjiTyUyfThch/TeJnxnHrpsDXibopQN3EuWzHcRzHKfTEKV5zHNAVQETaAnsAtfJ/eI7jOI4TP+Lkw+4NVBKR34ArgLHApuzqkn3Y7y6xFwQ5juM4Oy9+SHwzsfFhq+pKIi82ifakswjYupJ92FP3bRLfZ9dxHMdxdhCpmLAzfNi9SfJhi0glYI2qrgfOB0YmJnHHcRynkOK2rs3EyYfdBHhNRBSYCJy3Nfdx6tV7B7VzltpeUX3idlN/aspnQU3qNTVrx3za3tRrnfdOUHv83gPM2r+uvNrUi6SH/Z5/PWQ/5jdrlzL19r1HBLU37tzPrB05MRy5CHDmjdcFtSlLfzRr3zjejk1sdtfHQW3iqKzrIrekdaewrx1g5GWHB7UaZezaFu3fMvWnXm8d1A4e1cPe9sfvm/riw8Lxm0/d18asrVPe9uZ+f9cXQa3W8/a41+9Sw9QXLAv7z0+42I6SHNco7FcGaH1w+D36YZtHzNr+Lx5q6o8f3C2o6UX22ckyn79t6jX++CuorRpt94QY8obtXb81p0SHrjnozg4jFT7sU4HqQAOgp6ouA1DV70XkFaKJuhnQFhiSx+NzHMdxYowaOyCFjVT4sCcQfScbmXyliDQFehBN1scAz4lI0Twen+M4juPsFOS7D1tVJ6tqdr0JuwDvqOo6VZ0FzCDay3Ycx3GcQk9KbV1Z2B1IbhI8P3Hdf0i2dS0b7vkgjuM4BRXdpPl+iStxmrC3GlXto6ptVLVN5cPtoAzHcRzHKQikwtYVYgGQHJtUK3Gd4ziOU0iJcyOT/CZOe9gDgR4iUlJE6gENgZ9SPCbHcRzHiQV57cOeCdQFiiT5sBsDVyfue4iIjFHVo4n6ipcnsoKtAE5T1WxbkybTdvfyQe2KFiebtdMPtP3M54/qHdRq9etn1i4Ya3sbFz4Q9lq/OXKuPa7mtid5l+7vBbU1S9eatSOb2T7W4/8vvHB/2ZoNZu2qv1aZ+oqz7gpq6x8+0qw97INppr7u+u5BbezNdnvbf3J4LWVN2LsuZSqatUdfXMfUlzWtFNSaVg73IAB4+uaw1x+g8fSbglrdu181a5di53ynX2hkQxezc9F/XDTK1O8YFV63MrdK+PkC+LrOnaY+c9KNYbGV7fWf2tb2va9df2JQm9XL9lnvP9UOL1xxSzgvO+0q+//gD/2fM/V139n1eU2672FnkteHxM8B/gVeT/JhNwFeBl4ErlfVMYnbriWK1WwONFfVwXk8NsdxHMfZaYiNrUtVV6vqd0QTt+M4juM4ScRp0ZnjOI7jbEGcbVb5TZwWnW01yT7sKZ9NSfVwHMdxHCfP2Sn3sJPjNc8fdp5//XIcxymguK1rMzvlHrbjOI7jFDZSEa+5DHga2A34XER+S9i6EJHZQAWghIicCBylqpOs+2hRJWwRWXtl2JYF0Oki26bx7vJxQe25a81hceBxdvzg2vvCEYF1HtzfrG383Pemvmq3MkFt3MtHmLVNqrc09UfP6B/Ujr3MjhzdcGNPU9dfxwe1ehXqmrXnN7OtcP2q7xXUfp8ajt4EKNfW7qZXp3x426Uvv8esvbqnbc16eGzYClfutafM2v0e39fUv7vuhaD23KX7mLV/7WF/dooXCX8uqzwSjq0F2P0a28KXtnFGUCtywilmbcWK9mdnVtcnglqncxuZte8sOsvUSwz5NKjtebn9fOvfM039hq7h96DOs/tPLR3e2dQP2NV+rfMaP4e9mVTFa64AagKdM2xdItIW+CdxEeDOnCZrx3EcxyksxCZeM3F9G1Vtlah5UUR2ynPsjuM4jrOjydMJUVVHikjdLNdNBhCRrLddk/RnKcCPgziO4xRyfNHZZmK16ExE9heRicDvwMWqujHVY3Icx3GcOBCrCVtVf1TVZsB+wM0ikm2T5mQf9ugP/DS34zhOQUXTNd8vcSVWE3YGicPm/xL1Fc9Oz8zDPugUe2Wy4ziO4+QnIlJZRIaKyPTEz10Ct3tIRCaKyGQReUqynivOQmwmbBGpl7HITET2IEr1mp3SQTmO4zgpRTdpvl92ADcBw1S1ITAs8fcWiMhBwMFAC6Kd0/2AdtZG4+TDPgS4SUQ2AOnApaq6JKf7uLJ+2Fe8rt4is3b58jRT/3zWvKB223A7cu74P8O1AC+/MT2ondc068L6LTlish2bOLNS+Evas40/N2tnL7E9xzM/Oi6sLQpHbwIMT//T1D8qF/6gFP3Zjlycscx+LYsumBjU9tqlqll7woAfTL1iyTFBbdNz95m1Zwx509SLjwq/T/TpcBwpwC/NrjL11uMfDWoz14bvF6DuD//J79mC9R06BbUSbWqatf+0DfvDAYZ13D2o/fmO/ZzIqF6m/tzUsJ//y7vDrzPA+RXCMasAQ+rVC2q/XjHCrP2wSThGGOAlI5L3rpvt/gc3vmbHa07+abSppz97uqkXUroQzX0ArwEjgKzZrUq0wLoEkZW5OGBOWnm9h53sw66lqn2JviSsSAyuc0bTFOBbIGO2KMJ/7WCO4ziOszNQTVUXJn7/C6iW9Qaq+j0wHFiYuAzJcFGFyGuf86vAM8DrSddl+LBfzOb2MxM+bMdxHMchPQWLwETkQuDCpKv6JDIskm/zFVA9m/Jbk/9QVRWR/zwIEdkTaALUSlw1VEQOVdVvQ+OKjQ/bcRzHceJAcsCUcZtgD10RWSQiNVR1oYjUABZnc7OTgB9U9d9EzWDgQKKjzdkSm0VnCeqJyFgR+UZEDg3dKNnW1eeVr/JzfI7jOE4+kp6e/5cdwEAgo7n8WcAn2dxmLtBORIqJSHGiBWcpPSSeGxYCdVR1qYi0BgaISDNVXZn1hlt8+1n1fnxNc47jOE5hpDfwnoicB8wBugGISBuipmDnAx8ARxA1ClPgC1UNJ8QQowlbVdcB6xK//yIiM4FGgL0003Ecxymw7KA93nxFVZcCHbK5fgxwfuL3TcBFudlubA6Ji8huIlI08Xt9oCHwR2pH5TiO4zjxQFTz7ohyYi+5LtEXgwVEPuzGwNVEe/fLgDGqerSInAw8CNRI3H4R0FhV11r3sfG104MP4IMDK5nj675rG1OfUWxZUCt/3ntmbcUmdh62xZKfF5p6nXrhrGGAubPWB7VBj9hZ292fME+hsGRi2Br/6fOHmLW3fTDN1IuXLh7U/rn+SrP2gwrXmnq38ysHtVVP/KenwRYUue8lW7/9sqC2bJ39Wlb/126XL6UqBrX3Fn1n1qY3/tLUu9zUIKgtHZvdGpnNXJxDlvxTh+8X1J7+7Xez9rGGdjb0jX/8FtQerFzHrJ11kf257XlJuHPiix1bmLXNBtiP67w6pYNa1z3DrzPAMXvYGeG/Lv4pqFUpbXu4a5ULZ2kDjF5o+7CPrP1Anq4g/r1543w/7bn3hCmxXBWd13vY5xB1b5mY5MPuR9TV5Rvg6CQf9ifAGuAgVS0NtAY25PH4HMdxnBizky46yxPiZOs6ChivquMSt1ual2NzHMdxnJ2J2Cw6I1pgpiIyhKht6Tuq+lCKx+Q4juOkkBiHZ+U7sVl0RvTl4RCgV+LnSSLyn1V2sKUP+6URds9jx3EcxykIxGkPez4wMiPwQ0QGAfsSJZ1sQbIP21p05jiO4+zcxPmccn4Tpz3sIcDeIlImEbPZDpiU4jE5juM4TiyITbymqi4XkceAn4m6vgxSVTsLEnigSdmgdt7udo5Ik/c/M/WpP84Pao/cYm978nJ7gftbQ2cGtQ9fyPZMwObaegNNvd3LzYPapCbheEyA4h3XmPqV3cLxm10rhG0rAFNv6mHqaw5/IqitL9PPrP3nV/s5++WUr4Naxw/tuNJp5e2DOD+2uyGorVxqvw/GLbK3ffS0rIl8m7noA/t00KInW5p6kTLhj//Bde2oyFkVbdvin0XC9Rc039OsXV8xHEMJcE/VsP7wb9l1gEzST7JtX393Oy+o6YywdQqg6qpVpv7lVWOD2j5jHzZrN737rqmXvCs8tvJjw+9PgKM/6m/qY361Y3HTepuyswPJ60PiyfGazQFE5FSieM2aRPGaYxLX9wKuZ7OV63oReVtVw6ZLx3Ecp0Djh8Q3k9eHxF/lv7nWGfGaI5OvVNW3VLVVIl7zDGCWT9aO4ziOExEnH3YyPQH7OKXjOI5T4PE97M3EaZV4Mt2BLqkehOM4juPEhTitEgdARPYH1qjqhP9v78zDrCquBP47CLIKAqKiBFFEUVyxQZPoAK4YFTGiMWYRTWKMJlHMRMmYSZzMJKMxJq7RoBFjJFFDNCoxCi7EuMOwIyA2IMjuhqItspz541TT1+erem2/7n6v6fP7vvu9++rcU7du3bq1n6rENVvtsKc+kF772nEcx2m6+NKkNZRdgQ2cBSSnLarqGFWtUNWKitPSmxA4juM4zrZAWXWJi0gLbKPvo0odFsdxHMcpJ8rGDjuo/BuwTFVrvQ/2j3sdFpXpP6cmdV+ZsjwpP+2k+LZzjy1Zn9SdsCK+xSXAV/6wKip779ubk7ojR+2clH+4X9xWetPNY5O62iVtS/1WVby/aOjdryZ12658Pil/eEH8ufuM+m5S9xtz/5WUb74ivt3j7cfH7dYB9u/UPylvu/bnUVm/A3dJ6nZrl94qdegOcf2WbdKf79Jx6XWHet8wLCpbvDq+jSrAqgHpOPtg8K+jsn1Hpbe1bdFnXVK+/o4XorLuF6d73FbtVmDb2w3x71q6p+3H7736rqT8kMfi6xC8Len1D175z7QN+Jmj49uCLvkoncYK0alHeuvPhqacu6gbm4buEs/aYVdvr9kSs8NuhdlhnwAgIq2w7Tjbi8g8EflRA4fNcRzHcZoMZWOHDZwBtFbVA7G9sL+daxLmOI7jNC980lkN5WSHrVjruiXQFvgIeLchw+c4juM4TYVymiU+HngfWAksBX6lqm/luzBr1jXmrtyGuuM4jrOt4C3sGspplvhAYDO2xnhn4F8i8ni+CWjZ7TV1zRjfXtNxHMfZ5imnFvbZwKOqulFV1wDPAunppI7jOI7TTCinAnspcDSAiLQHjgDmlzREjuM4TknxLvEaRLXhepRFpBLohVUMlmN22H2BS7Du+LeAqap6goh0BqYB3YP6WFX9TqF7vD/quOgDtPvusUndz09JbwZ240/j+9d23HG7pO7eE0Yl5avax+tK3emc1N0yK26HCrB54NFRWcu5aVvopb3SNt6/mDItKjtpz45J3d2HPpKUVy6Kp8XJE9Nr6dxyX3QlWwBatW0VlXXZq0tSd+2CtUn5pgtyDSFq0DffSerOvTAdJ/1uPSkqa9H/yKRuix/+Mim/9Ky4LfXgkwrMDZmV3lf9JI3bj+/zVNqm+Pqj0/thf6FnPL4v/ld6z6DObdJtlJ47xL/r0ZOWJXVHHJS2ub9+0BlR2cb/iO8FD9Bm4K5J+U4L4+s6bPpwU1L3zZ3T6f/tkfE0CLBz268nd3Iqlqe69230Yc8hK+c36DPVlYZuYZ8LDADmZuyw7wAOAP4JnJBZNOVsYLKqtgF6AgPDymeO4zhOM0VVG/0oVxq0QFTVp7FWdNZtnqouyHP5/sCT4Zo1wDv4GLbjOI7jAOU1hj0TGCYiLUVkT2zxlM+UOEyO4zhOCfEx7BrKqcC+A3gdmApcBzyHmXl9gqwd9h2zX2/EIDqO4zhOaSgbO2xV3QRsnaklIs8Br0Su3WqHnZp05jiO4zjbCmVTYItIO2zW+vsichywSVXT2w05juM42zTl3EXd2JTT9po7A4+JyBbMBOxrtblHr56to7LXfvdUUnfclJVJ+Z7/F982ceXX0iYzy8+5NSnvMf6KqGzn2+5I6r5w7nFpv2+6LSpb9+0vJXUPvS5979fXxLfAbHvhMUndB5elO0P67B23pOh9wTNJ3WvmXJ2Ut3sjvpXqjWtmJ3W/N2xQ+t5r83YEAXDrwrRJ2KQd4+ZmAJUH7h6V7dYqPaK1/JpvJeUbT70xKlsyP26CBHD6vWmTyLWXxM2+fnP06qTuiZt3Ssq1Rfy5TzkjbY7Wb8nlSfmmL94UlV3y2fTWnD13SGenLWfG0/D2695O6r7xwHtJ+d0Px9PZ0LvT6XfyIen4HvJ+2iyM9I68Tj3S0C3s7PaaBwCIyDXAeqzgrsRMv1DVJSJyJ/ANbLJZX+C1Bg6f4ziOU8Z4C7uGUmyvOQk4QFUPwsaofwQgIvsDZwH9gs5vRSS9OonjOI7jNBNKYYc9MUwwA3gB6BHOTwXuUdUNqroYeBXbEMRxHMdpprhZVw2lNus6D/hHON8dyK7993pwcxzHcZxmT8kKbBG5AtgEjKuD7lY77A+fX1r/gXMcx3GcMqMkZl0iMhI4GThGaxZuXc7HVzbrEdw+QdYOu9tvTnY7bMdxnG2Ucu6ibmwavYUtIkOBy4BhqvpBRvQQcJaItA5Lk/YB0tv6OI7jOE4zoRR22D8CWgOTRATgBVW9QFXnish9wMtYV/lFqho3+g2s7rNbVLapVXprw73eS8u3rI/bNnb/42VJ3Xcuidu4Aiwc8uOobNULNyR1l7+/MClv2bNTVPZIm/h9ASbtk95Vru1DcfP4qUPHJnUrnxmSlHc7bXJUdvjP0vvA3PnKY0l5h4TN8m7t07bQr57x+6R8dEV8W9Et/3tJUnePLfcm5beti9ss771kXVK36pePJ+W73nB6VNbn1xOTunOffSspv+ekv0ZlB+2U3iKg7VXpLUfHX7gmKvvv6w9N6i763f1J+dp/XBuV3bxgfFL3q90GJOXSOf7c629Ip++Ol6bXGdj4yLCorLJf96gM4Oj2/ZLyvnfH13UAmD/yvKS8WLyFXUMp7LD7AqdgrftKYHRwPw74IvAB8BGwoYHD5jiO4zhNhrKxwwbeAE5R1QOBc4A/NnDYHMdxnDLHzbpqKBs7bFWdrqorgvtcoK2IxNcddRzHcZxmRDnZYWc5HZimqnm7xbNmXWMendegAXQcx3GccqBku3XF7LBFpB9wNXB8TDdr1rVlwvlu1uU4jrONssVz+K2Ukx02ItIDeAD4uqpWliJsjuM4jlOONHqBnbHDHpS1wxaRHYG/A6NV9dnGDpfjOI5TfpTzJLDGRjIN3Pr3XKQS6IWNlS/H7LB/BXTAusM3APer6nkicgtwPmbSBbAKOFxV40aXwDef+Eb0AW7ruXcyfGe+siApP+3k56Oys56N2z0CjNqYtvG+8ohjo7JO26f3p/3w8muS8qqV66Oy9b89O6m7/9VpW9N2XdtFZS1bp+t/S9anbby/2i9uP37fSeckdfXR+5Lyj46L78/c+tX03s4XrViclF83O/6uZ944J6l72LVHJuWbKuP7JG+3S/uk7hkd0/G9b5f4nM4Zq6uSuucesGNSvmjdxqjs8FMmJ3WPHp72+8ghe0VlP6jYJal72jXxbxrg3tvj8b1pTvybBeg++Imk/MzL4vnRxDGvJnUPvubfkvL2z8T3ZP/g3OOSuue8lu7MfPWtdFp47qw/pxNakYxvvW+jd4qP2LCgQZ+prjR0C/tcbO/ruzJ22MuAJ1V1k4hkVwP4AfC94N4dmEnODHPHcRyneeEt7BrKyazrg4x7G8CnGjiO4zhOoKzMukTkcBGZC8wGLsgU4I7jOI7TrCmr7TVV9UVV7QcMAH4kIm0iulvtsOdPmN84AXYcx3EaHV/prIaSFNgZs66vaJ5Zb6o6Dxv7PiCfvqqOUdUKVa3oe3LfBg2r4ziO45QD5WTWtSewLEw62wPoCyxp7PA5juM45UM5t3gbm7LZXhM4EhgtIhuBLcCFqvpGQ4bPcRzHcZoMqrpNHcD5dZUXo+t+u9/ut/vtfvvRkEfJA1DvDwRT6yovRtf9dr/db/fb/fajIY9Sm3U5juM4jlMLvMB2HMdxnCbAtlhgjylCXoyu++1+u9/ut/vtNBgNuvmH4ziO4zj1w7bYwnYcx3GcbQ4vsB3HcRynCdDoK53VNyLSFzgV2D04LQceUlvetFi/BwKqqlNEZH9gKDBfVR/Jc+1dqvr1Yu9ZizBtD5wFrFDVx0XkbOBzwDxgjKrGNyJ2Fbb9JQAAD2NJREFUHMdxmixNegxbRC4HvgzcA7wenHtgBdo9qnpVAf2+WEH/oqquz7gPBQ4HTsQqNZPC/6eA44BuwMKsV8AQ4EkAVR2Wc58jgYHAHFWdKCKHA/NU9V0RaQuMBvoDLwO/AM4BHlDVZXnCPC6EqR3wDtABuB84Bnuf54jIXsAXgc8Am4FXgD+p6rup+HDKHxHZWVXX1FG3q6q+Wd9hqg+KCVsxceI4TYpSG4IXc2AFUas87tsDCwvojgMWAH/D1iw/NSObhm3xuR1WML4LdAyytkAVcDe27Oqg8LsynA8CXsr49S1gBrYs67NY4TwXaBnkY4DrsKVZf4oVvuuAFcC/gAuBbhn/ZoXflsBqYLvwX4BZwPeBicCPgeeAm4GfY5WBwaV+Z3new85F6HZthPB1Aq4C5mN7u7+J9WZcBexYQHci8L/AH4Gzc2S/BXYFbgnvqCtwZUh39wHdgS45R9eQVjsDI3LC+Pvw/v8E7BLCt1OQVwCLgFeB10IanRbSSO884a7AKqd3Y5W+SSFNTgEOxSqJPwvpeB2wFtvbfmTQvx/4KtAhEi+psH0hFd8F4qRLgTjdC9vH4IdAG2Ak8BDwy/BMB2XC2CrEz0NYJXrXItLBP4ChqfeVke2CVd77Z90j/nZJyIblccuXV+4U0b+wFt9G34b+/vzIifNSB6CowNvHs0ce9z2ABQV0P6rOUIBewFTg4vB/OjA9c+30HN0ZwKiQkR0S3Bbluz5kct3CefuQeczLyKfl8Xs6Nr/g+PBhrwUexVreL2MVks7Ae9UfbciA5gX/qwvxdsDkcN4z+OsF0KcogIDHgMuBXTP+7RrcJlKTueYeh2EVu6uA4VjG/1egdfV7D+/0e1glblbw8zPB7UFsTf3FOcfG8LshE57bgf/B0v0orBI6OyN/ChgQzvfB0vpi4FfAUuCloLdbuOYlrHfpy8Cy6neD9eI8H8I2EuvNuhT4T6AP8AescFsOjMfS133AacD2mfCkwrauQHyn4mRRgThdDlyLpdUngJuAo4BrsDQ9LXPPa4E7sbT1m6Bb13SwMsfvfO/rECzNzQMeD8f84NYf+HyQzcV6+yYBleH9jMZ61KqP04FVmf9DsB7IN0JYe2Xzn/AOs8cPwrWXApcm8oOlpS4DmtvR1LvEh2If3UIs4YIVTHsD38VqznlVgX6qunXSnYh0wDKZl4GjgQ3AEFX9QERaqOqWcF0n4ClV7S8iPbCPeTVWo+0ZrpmJtbpbAI+pakXmPtOxguYRVR0rImOBm1V1qojsg7X8t1PV/hmdVtRkoKcAa7DW/7XY+P0i4IgQ/hFAhapuEJHOwKTq+4vIHCzjeRL4g6quCu67YpWBY7CPPxZnzwDXY5nIeVhGeXa417QQrr9jFZOzw7P8CSuwjg1hfy3H3x5YZrKbqrYO4bkdy3BuwzKcQVhBfGCQPwVcpja3YJ9wj65YgXhm0P0zcK+qrhCRl7Deix2xNDFKVceLyDFYxrkGeADLJM8M4b8HqwCcrKpd80aIyAIsrf0zxE8ug3LS2BVYC3IYluGKqh4aZEur00/4PwMrRI4Dfqiqs4P7YlXdU0SmVacREZmhqofk6LYGDlTb/e4FVT0iI58NbMzoH4WlrS9ihULvTFrODdd0oIWqHpxxm6KqA0SkBfb9VKnqoSLSEUufX8b2uJ8Q3sv1ibBtqE4HkfgeE4uT6vAl4rRKVduK7Tq0Euiuqhr+zwQ2Z3RnYBWJjUFepaptEuFKpYMjsEp66n0BfFtVX8zx+wjgd1h+9A2scvkwMFxVnxGR/lgF7BEsHVfffwSWHyhwINb7MVdERmCV7q+p6gvhfe4d9Odm9C/Bev5OxCpwn3hs4BxV7ZgvTpwGotQ1hmIPrFA8AqtVnh7Oq1uYq7Ga6x45Ry/sAzgkx6+WwF3YuG/ryP12wjKbrNtJwC8y/5dghWh1rb97cO+AtaA7YbX3SuBFrOBbhH3wB5PTos+5VztgN2paQztiH+fA8P9irGVxG1ZDPze4dwOeJtHzgA0RbMYK9KfyHFtyrr8C6+bvitXUsz0LS3OunYHV3B/Nxh+wOPxmWyAz8ujOo2YY4YUc+ewc/aOwVtSqEO6liXBNB2bmuE3JpK33sW7U3G7Ly7ECfg7QJxKfG7HCLes2EssYX8veF/if3GcKvz2AvwC/BnYg9ORglZzq1tAiwnyUIJuFtSgnYpXPK7FCchDwX+S0JjN622ETK9dgvTtnhHAOD/JBWOHwHHBkcBuGVUqzaSif312BC0LaSoVtRSq+U3ESZKk4rcqc35EjmxnisbqFOi9H/l4R6WBZLd5XdAgPq+Bnv63csM3Hegy+k/td5cZJ+N8vvKfh2HfbM8Tn1UC7cM2izHOfj1Xoc483YmH2o2GOkgegQR/OulWPjMgeINO9lSP7fAOFpx2wZ+Z/R6yAPiwnI9inyPv0wwrxT4wxhYzSCyCtdQG0MGRk84G3sW7eecGtS4jnfSPxdT9wbB73ocHfn5FnnBdr8YzPcRuG9WysCv9/mnNUD7vsCtwVzgcD92KVktlYK+p8bHz2nkT6ORgbCvgHti/99dgEx7mYRcLBWKvrbazXZd+g1w2bQ/F0LdJoLGzdUvGdipPglorTxRFZ7/AcY4E7wu9YwjcS4vSfIQzzQpg+TToYnvOufpL7voAbsN6pL4U4/lw4/zvWi5j9tobn+D8Hq1xejFVQB/LxSsxUcvI67DucAbyXcTsVq4CPoOa7fBL4XOS5FheTT/nx6Y+SB8CPRn7hNl5cnSHmZjydC2Q85VoAtaS4AuggPl4A7RP0qgugvliXfofc5w6/fbHhhE/IE7ITC+nmyrEJjwfUwu+C4apFuPcroLtfgTgZSM3Y9P5YZewLkfdzFFZROx4bn+0U3NuFNDUBS5+dgrxjRv5LrKJZLf8+8JnIfVoDXyekYWzY5ibgIqwS0xprOcbkvbEJazdgQ2EXVIclXL8X8O8hff06j7xaPyY/EbgV6/J+OJx/IfO9tMvzTL2x4aHq/7tj8wayBfaxwMF5dDsBV+S4tcfG9J8O/7vku68fpTma9Bi2U7+IyLmqOrYu8rroBpO23qo6p779rsdwj8Mmrc3DhlcuVtUHg2waNrRxUUS+DPggoTsWm2vREH6ndAvdexk2FDA/4feFCfmDxE0iH8MsMgaG678Zwvk3rMDeG9hdbXx7TAjHX7HKw8HAvljhE5MfE9wqsfHyv6jq2sy7jJlEghXKMfl+2IS4p7F5CNPDNaeFuDgIOLmuclWdjOMUotQ1Bj/K56DArM+UvBjdMve7kDXB7IS8qgjdpu53zCRyFmkrig8zsnwWFMVYWMwJ18VMIlMmk1WkrS8KWWfU1nqjuss915wtZd3RMyEraHJWQJ60DEnp+lH/R5Nf6cz5dIjIrJgI2KWAvEdEXhvdpup3Sw2L6qjqEhEZDIwXkT2CvEVCThG6TdnvTaq6GfhARCo1LNijqlUisgVoESwYWmBzFdYG+fsiUpXp9ZgpIhVaY0GxEVhYQL6dmkXHRGBijoVFX7GVAttjhWYnrIBrjbWuNyfkghXkm8P/DiHMS8M9tEj5fdh48RD9uPXGyCDTIB+sn7TumIZ1Y+eT3SciKcuPQ8JM85j8qOD/X4HzROR0gmUINsHXaUxKXWPwo3EP0jPnVxSQby5Ct6n6Xcia4MmEXIvQbcp+v0jNbOMWmWs6YZn/EuJWFLNIW1AUY2FxWbj2NWys+wnMmmI2Nm9iVEL+CGnri0LWGcVab6TkHxXQTVl+VBWQJy1DSp2fNbej5AHwo5FfeHrm/J8KyCuL0G2qfietCbDZtjH58CJ0m7LftTaJzJFvtaIgYkGRubZOFhYkTCILyUlYXxQrp7D1Rkr+ZgHdQiZndbYMScW1H/V/+KQzx3GcEhOGCEZjplU7B+fV2Ap51XsixOS3AN9J6B6DmVUuyHPf4VjvSEx+PzZW/XiO+1DgRlXtU5fndeqGF9iO4zhlTGNbb9SX30794wW24zhOGZO7xOqnkRejW6zfTv3js8Qdx3FKTFO1sIjoOQ2Et7Adx3FKjIisBk7AVtv7mAhbOne7hLwSm3xXF92i/FbV3Qo8mlOPeAvbcRyn9EzAFqOZkSsQkcnULGaTT76kCN1i/XYaEW9hO47jOE4ToEXhSxzHcRzHKTVeYDuO4zhOE8ALbMdxHMdpAniB7Th1RESGi8j+mf8/E5FjE9dXiMgNDRCOkSKSnK0rIrdnw5qje1N9h8lxnPrHZ4k7Th0QkZbYmtsTgJcBVPUnKR1VnYptRVnfjMTWg16RuPc3G+C+juM0It7CdpotItJLROaLyDgRmSci40WknYj8RESmiMgcERkjIhKunywi14nIVGxjhWHANSIyQ0R6i8idIjIiXDtARJ4TkZki8pKI7CAig0VkQpBfKSJ/FJHnRWShiHwruHcQkSdEZJqIzBaRUzNhnScit4nIXBGZKCJtw/0qgHEhHG0jzzpZRCrC+bki8oqIvIRt1uE4ThPAC2ynubMvtrnBfsC7wIXATao6QFUPANoCJ2eu315VK1T159jmCj9U1UNUtbL6grCn8r3Axap6MHAsZuuay0HA0cBngZ+Ebu0PgdNUtT8wBLi2usIA9AFuVtV+wDvA6ao6Hmu1fyWEI999tiIi3YH/wgrqI4FPdJM7jlOeeIHtNHeWqeqz4fxurBAbIiIvishsrEDtl7n+3lr4uS+wUlWnAKjqu6q6Kc91D6pqlaq+ge09PBBbQeoXYTnIx4HdqVkCcnFmAYv/w/br/rQcDkxW1bWq+lEtn8dxnDLAx7Cd5k7uykEK/BaoUNVlInIl0CYjf7+B7/0VoBtwmKpuDCtNVd9/Q+bazVjr33GcZoK3sJ3mTk8R+Ww4Pxt4Jpy/ISIdgBEJ3feAHfK4LwC6i8gAgDB+na9yfKqItBGRrsBgYArQCVgTCushwB61eIZYOPLxIjBIRLqKSCvgjFrqOY5TYryF7TR3FgAXicgd2GzvW4DO2KzrVVghGuMe4DYR+T6Zgl1VPxKRLwE3hklgVdg4di6zsK7wnYD/VtUVIjIOeDh0x08F5tfiGe4EbhWRKuCzqXFsVV0Zeg2ex8bBP7FGtOM45YmvJe40W0SkFzAhTC5r7HtfCaxX1V819r0dx2maeJe44ziO4zQBvIXtONsQIvIAsGeO8+Wq+lgpwuM4Tv3hBbbjOI7jNAG8S9xxHMdxmgBeYDuO4zhOE8ALbMdxHMdpAniB7TiO4zhNAC+wHcdxHKcJ8P+JxcS+kMx9gwAAAABJRU5ErkJggg==\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": 23,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.legend.Legend at 0x7feccc36a3d0>"
|
||
]
|
||
},
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
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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": 24,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.legend.Legend at 0x7feccc2914d0>"
|
||
]
|
||
},
|
||
"execution_count": 24,
|
||
"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": 25,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"nets = df.network.values"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:563: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" if not cb.iterable(width):\n",
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:569: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" and cb.iterable(edge_color) \\\n",
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:579: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" for c in edge_color]):\n",
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:660: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" if cb.iterable(node_size): # many node sizes\n",
|
||
"/home/aclarkdata/repos/Aragon_Conviction_Voting/models/v3/model/parts/utils.py:356: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
|
||
" plt.tight_layout()\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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emxT7DukdmYL43Oc+h2OOOQaHH3443va2t+Goo45KTCg/44wz8IMf/ADnnnsunn/+edx2222YP38+jjvuONTW1uL000/Hq6++Oqlz/vjHP8acOXNQW1uLu+66q2yeYlVVFT71qU+hvb0dzc3N+Pa3v41f/epXOOCAAwAAN954I7785S+jvr4ed9xxB6644grMnj0bXV1dWLhwIY477rjE4woh8L3vfQ8zZ87E+eefj2w2i4cffhg/+9nP0NnZifb2dnzmM58xUbJ33nknhoeH0d7ejquuugof/OAHJ7zGk08+GfPnz8dpp52G66+/Hv/wD/9gfjvxxBPhOA6OOuqoSUmrcSxcuBCf+tSncPzxx6OtrQ0vvfQSTjzxxHH3OfXUU3HooYeavkxCe3s7Ghoa0NnZicsuuwx33XUXDj74YADAd77zHXz+859HTU0Nbr311l2yQohIm5qacNRRRyEMQ/z7v/87Ojs70djYiP/5n/8pO/jH9wWAn/70p1izZg06Ozvxvve9D1/84hdx+umnT7o95dDU1IQHH3wQX//619HU1ITbb78dDz74YKS/Lr/8clx11VVob2/H2NgYvvWtbwEAFixYgJ/85Cf4xCc+gebmZvzmN7/Bb37zG+RyORQKBdxwww1obm5Ge3s7+vr68NWvfhUAcMcdd+C+++5DTU0Nrr766shkKY7Jvjcp9h2EnKw+kiLFNMepp56KSy+9FB/+8If3dVMAqBSJD3zgA1i3bt2+bspbFqeccgo+8IEPvGXuWYq3HjITb5IiRYpnn30Wzz//PO6///593ZQUKVLsRaRyaIoUE+DKK6/E6aefjm9+85uRCMcUKVJMfaRyaIoUKVKkmLZILcEUKVKkSDFtsUs+QapPmCJFihQpUkwlrFmzJrGowS6R4Jw5c7BkyZK91qgUKVKkSJHizcAxxxyT+H0qh6ZIkSJFimmLlARTpEiRIsW0RUqCKVKkSJFi2iIlwRQpUqRIMW2RkmCKFClSpJi2SEkwRYoUKVJMW6QkmCJFihQppi1SEkyRIkWKFNMWKQmmSJEiRYppi5QEU6RIkSLFtEVKgilSpEiRYtoiJcEUKVKkSDFtkZJgihQpUqSYtkhJMEWKFClSTFukJJgiRYoUKaYtUhJMkSJFihTTFikJpkiRIkWKaYuUBFOkSJEixbRFSoIpUqRIkWLaIiXBFClSpEgxbZGSYIoUKVKkmLZISTBFihQpUkxbTG0SXL8e+OtfgCAApFT/pUiRIkWKFJNEZl83YI/wt+eAZcuAw98W/V4IAEL9O5nP5l/Yf1OkSJEixX6PqU2C55wHvPtMwBuNfi8lIzfXEpuUAEIgJKsx/i8wMWFi4t9TpEiRIsWUwNQmQQDI5oBMFvAKgF+w38tQ/RcGACQgHMDNAE4GcF31dxycEBM/h2q7OInSZyDZwpyUNYqURFOkSJHiTcbUJ0FAkUeuQpFhYcSSFQBDTkSIYQAUA0WCjquJUZOiIaXdaANZkuWIlEg0LPc7u5ZUyk2RIkWKNwX7BwkSHBeoqAb8IuCNKSlUBooc4oEzZAkGntoWUFYiEaMhxUliT4nIECJQ3hrdQyk30sZUyk2RIkWK/YsEATWYZ/OKyIqjALQM6hf1BhLG1CPrkCRSCPUdWZP0PZHjG0kUe2KFApOTcsNxiDbShlTKTZEixfTA/keCBMcF8jO0VVgAMnlFMF4BcBwAEghDwM0qqy8IgNBXhJnNq/3DUH3njWmydPV/4/gV9xX2uZRL506l3BQpUkwdTGkSlMuWAi+/AFxwIYSjCYkGV/ocsQqhiDEMVBCNkUSL6nO2Qv/tqe2djNo3n1fHDDVR+kWg6LNgG02MXHKcSthrUi4j08lIudwKnTR5ltk2RYoUKXYDU5oEseQZ4PnngbPPgpRSDZDCiRlDeuCksbawU5Of/jLwzGbwC2pgdjJAJqe+J58hEZ6bVVYlDeCBr0lzTB1jT/yKUxVvqpSbQLSRNpSxNlMpN0WKFAmY0iQorvggcNnlkAObIXdsA7yiihKta1Yk5jgQbhZwHU1IWvakVIpMVo2hZOEJoQhMhoDvIzKQSqksQONbNK2wg7+EOk7g22AbIey5zWfB9o0NxHFLdjrgjZRy5WSlXNbnu+MTTZEixZTElCZBAICbgWjqgqhtAbxRSL8IuW0zMNAH6XsQDe0QDa1AvlKRoqOtOSkVaWbzQL5KHctYfa6WRjXxQQJuThGr0LKoX1RkJ0SCj1AHn1DgjdS+RamDcmgQZTE6JYO5AZMAgWRZML7ddCLZvSnllo3QTaXcFCn2V0x9EiTopHlRHIVo7QZaZ0HKABjsh9zwOuS2jUAmB9E5D6JekaKAVKTnFdT+bhbIV+tgmFEYP6EQivTGhhXZZXJArlKdNwxYmoWwkqmbEE0qpd7e16QYwESvkl+RfJvGSmGDsvk+NlBHtiOrB9GBOiXZZOwNK3RXpNz4/Yu0IZVyU6R4s7H/kCCgBoR8lSKZ4iiEkwUa2iDqW4B5R0CODEFu34zw1WeAwX6gqQOi4wCI+lYIr6DIENBklFWfiyOWDDN5RV7FMQBS/Z3JAm4lICu0jKqDaiA1GWZteoUgktTdTqRIRFrOr+i8AQNdSrJ7jpK27yL2ppQb759Uyk2RYlLYv0iQ4GZU0rxXUBZcJg/IAKKyGqKqDuicDxn4kANbgL61CJc9BdS3wJn3diWPZl0I8hVKqSy2wk41aGTyQK4KRiodHdPBMjlFXLkKABWM2EbVMdyMIkyKIgVipJhng562Fv2i3pflKu6tfMU9HcAnQkqyE+MNkXJZP+1VKbcM0aZIMcWxf5IgoF5QXkpNOEBuBhB6gB9AZPMQLTOBpnbIBYuA4QHIzT1q144DEA5uhchXAY0dEK5ro0Ap4IWkz6y2ACkFI5OzhOho32IY6n0LQDjKJNNMdCARAhB6P4pOpVzFMACKRXUunqvoZN6ag1FKstHPbwTJ7u2AoklLuax/Uik3xRTH1CbB5cuBNSuBU09jFlLsxRJC+e8CT0mbmZyVTP0i4GQghANU10FU1wGZLOTYGERtI+AVED71AFBVA9E6C6JlFkRlrZI8/THt1wsVUVGRbirZ5mZt0r3jAE5e/U2E6BdUewwhZpMHBccBnJz9W0odgRpoUtUEP1Fx8P0NKckikVAmS7J7xQpFGfKMSblJRMvbP1HgUCrlpngDMbVJcP06YMVK4F3vZF+O94JIRT4++yr0o5t4BQhXAG4FkKuAc/TpkDsHgbWvIXz1WaBiBkRTJ0RzJ1DdACEDfdoY8QQey0HUFp7x7wntK8woqdUrKEtSOEz2ZAOduTQauBwg4wLIqWsKQxuxWgxg/IolxcFTTBopyUY/lyPZvS3lRq5jb0u5SdeYYrpjapPgaacDi09VUZvggwUbBEypM/0fhA1uyeSUdSalqhrj68oxlEIR+BAIIKobgIXHQWZywMAWyK3rEC5/BvCLEM0zIToOAGbUQghhy7DRTNikSWiyDWBJiV5MxwWk3ifwVFuSXlh+XWbwi/1NHzkJR5A0qMV/i/2929tR+ye5nfknwZrf35CSbPSzcNTvk7Fk32gpdyJZd7y2pZhymNokCCi5sKpWyZuFnaW/U55e4MO8BLSMEhFOttJGf5LvTghFkELonEAPwhsDahshmjqBQ46D3DkI2deLcNWLwOBWYNYhcDrnqlSMXBXg5u3LEobaCtXEJGHXOnRY4AsV8iYfZOApK9JEmk5C6oyQJWwEKv0nQ5gE/oilyIlVjnPMOAGzpavC8bbjRB07vhmEE84dwb4k4L0wSUg8/xuAaU2yTunv/N/I41XOGt2NFVvo+KmUO6Uw9UmQ4GaAylrrk4MDMzhLGX3wzAPpKEIojgBFWAkxm4eRTqXUEaMVNjAm8JQvsWIGxJzDgLlvg/QKkFvXQa5+GdL34Mw6BMjlFYFVN6japjlNtoGvjw1T2QahjMmZFPySVW0JfEvOGZZ6kYT4S8bTMqg/yK8YeG/t4uBJZMn+KU+su0HANEhPtF38eLty7hKUIWpgHGLdG0Q9zrl3aZLglHy1V/BWIVkz6RTJ10/nNv8QkbKxJ0nK3ZUgov3YCn300Udx/fXXY+XKlWhubsYNN9yAj3zkIwCAF154AZdeeik2b96Mz372s/jf//t/AwA8z8NJJ52EX/7yl+ju7t7jNggpS970sjjmmGOwZMmSPT7pG44wVMnuQaDIIijaB0dKNdADavAXeuZIqRBOBoDUVhrUSyClJSw3qyJMvQLMC5HV+YKaOGQYAgObIYf6IapqAMeF3LEdoqoWaOqEyGTt+f2isg4dVyXsC9een/9nLDeSTXW1Gjdrz70n/hkqHUeraZRddDjFHmGyxLpXCHg3ifoNt9J3kajNP3txkhB3H0BPlCckWfbd7pBs/DuBhC5NuIfx474VpNyRHapNFdWTU6hi8DwPzc3NuP322/GRj3wES5YsweLFi/HEE0/giCOOwFlnnYVPfOITOPzww3H44Ydj6dKlaG9vx2233QYhBD796U/v0vnK8df+YwlyOI5eRslTZEgWHl9TMNQzNSejHsQwUM8YEUCuSpMjz9sr6NUnhA1qIenSG9O5gDlVmq2xA6KxA5AScmQIIpMDwgDypT8hDHwWbTqDWZkFdT5Ks6A0CUNS7D9Ie26/qK4hnpw/WQhhrcUs7Ew2iNVBnY7Fwfc2xrXGphjGtdL3BgGz7d4QK32i+f8uWMoiRnZ0zvGC9CDYdgltEuyaBADJGDNC1gltTDxfQpupjRHS1AsMOPy7GJECMPdjbIf6bRfJcNu2bRgaGsLll18OIQQWLVqEQw45BMuWLcMRRxyB1atX49RTT0U+n8eBBx6I3t5eFAoF/OpXv8ITTzwx6fNMhP2TBAkZnYtnSqPlYdIYIHVVGF0s28nYpZT8opJIAbuiBPkHTb4fRZWS9CEUsRZHtdVoE+jFjDpLZAcvgvB9yC1rET7xa6ByhiLD1llAXTOEDNXxR3dEk/BLJM3QEqKvS7DxAt/U7ngu4mQgBEy+ImClHMpX3BeLDqd48zB5cSiG8ayxyAl2oS27047dbP9kpff4dkn78XchkXBjJuCETY5NlhLv0a5cN7dod2G3SBOkCgYEIGUIjA7h2eczeOr5anzykxPv39bWhksuuQR33303rrnmGjzzzDPo6enBSSedBAA47LDD8PDDD+PII4/EmjVrMG/ePPzTP/0T/u3f/g3ZbHb3Gp2AqU2Czz8PvPIy8L/+V5Qg4hCOIiVaPcLNqty7gKwqvciur5PRhaNIQGppsKgtL5olCUetTEFERA+0lPYzJyQiFeGoUm5ZF6J9LmT7HGB0J+Sm1QhfeAzwPYjmTojmmarcG61yDzm+JOnq6FJAETEV7C7y9A8WkbpHZCW1JCugJhABIAusr9mscbdMnN0dgCd7+Df4+Lva/l1uzhvd/jcLu6JUvMHH363Dv4HHH/cZHU/S3BUrd++CyHDjhhCrVk1+v0suuQQf/vCH8UnNmt/97neNn++OO+7ARz/6UWzatAnf+MY38MQTT6CmpgZz587F+eefj4GBAXz84x/HhRdeuEdtn9okuK0f2LBRWyhswOfLFvEZlJNRBEGpEI4LwGF+N01WxroDDKkJHbVJFhGkJcs4ARJhmSizECZFgo7puBCQQFU1xNy3AfPfDjk2ArllHcK1y4GlTwL1rRAtMyGauyCEo3yRlEsYJzNzjcwik9JWnJEhk5V037i76+tL2L4kJYT1J00aJh0ZN4UHMHWCN3Tzqd8/bzDi8ue4ltze+n0cSXdcUiojuU4abNx5E8hPnaL0HFJKSN/Deedkcf7FkzvW8uXL8f73vx//+Z//iTPOOAMrVqzAOeecg87OTpx99tmYPXs2fvvb3wIARkZGcPzxx+Phhx/GJz7xCVx88cU4++yzcdhhh+G0005DY2Pjbl/T1CbB089QuYJjI1GSoQEfLJHd0YTlZtUz4xcVOeQqAbcKJkePimjnKtR+gactRD2o5yp1cExo1w4M9NqDDidUqSrTkKQYavINmF9Ssgc3CCCyOYjuBSraNPAh+9cDfb0IX/87UFkN0TZHyaZZCQGhJNpylWaSQAW+6Xp8XekGiK1ksRekTe5XDIPpEZcAACAASURBVH2g6Kl+T/2KUx9TnWTigTKT/t2JbBZpj+BERO1hf8cDbnjbefBNSbSq/l+8j/j+3Fe6l1FCer4PWdipxsm6FgghFAGODMKZUQ9U1U362C+//DIOOuggvPvd7wYALFiwAGeffTb++7//G2effXZk21tvvRVXX3012tra8NJLL+HLX/4y6urqMHPmTKxcuRLHHnvsbl/j1CZBQD18lTOsPy5eAQbQg7EEBFvXj/x4VFc0k1eWUX6G9rNRkEoeqKhR33ljbHsWvMKjK7lFNDZsfY2uLq4t8zYqNPQ0+VC0qG/yAwWglnxq6oQ8RABD/SpJ/++PKtl01iGq9mk2p4JuyHc4bl85Ot0jbwnK97QlHaq2+x6MJLwn0aERv2K54uCpXzER+5pE9jXJOLu7P1dGmBrCryEx0b7cb/z7hH4oCRaJfY63TSQcO5EYhZpEE/mRZ6Fc2ghvzx5agyWkVxxTFbO8IkRFFVDTCKe6Xm0rJWQQQO4chFPbqGoz7wKOPPJIrFixAo8++igWL16MVatW4cEHHyyJ+ly2bBkef/xxEwwzd+5cPProo6irq8OKFSswa9as3b5eAPthikTgAYVRRMKdCZT7xgd5wCaQ8+2ouozUll0mp1ejkCpohrbnwSv8xfM9S6QAAIelUvDtiihZuFeGinDDkAWnaGJ1XMjRnZD9GyC3rgfGdkLMPUxForouBFmqu0ImZAVTgj6vrsMXBua5hHx5qN2FDG1KBlnQb0Zx8GlLMnvp95Jt9gLKpiKMQ2D8czkCi7SXPa/Gbz3Bb9Qm3k4pLSnx/L/J5AJGL5pxX5i8r/qDtYETN782lF7zJGGJTwJjI5BD21Q1rIoqZe1lygSh5KpsACEcoKpml8/9i1/8Arfeeit6enpQV1eHyy67DF/96lfhsCjTxYsX42tf+xre8Y53AFD5g5dccgn6+voi+YMToRx/7X8kCFhy8Qo2YCbwoiRIA2wYKqITOjgGIrqCPMmeBCEAkVGzVV8fU4bqOXVzerkkZpEF2oKM+yxpWSUik3jOIOX++QVNwlr65FGhYQDpjUFu7wP6N0JCwumcB8yoU9dRVadWwNjVvjPVanwl8VKdU0hLWIGWmt0EYtxdkon4FCWMtW4Cepxxjp+SzJuG3SGsyRAYANsfCaSUZHGVIzA6RqTN45BW5HPI2sSev5LPgLLaEL0mc61h9LhmP1ZggL8bERKNncccOzZZ5/vyPhyHDA3pSQmMDkNu36ze9XwVRH2LIr/x4OSAfIXt8zDcrTzBNxvTK09QCOsvIwLKVqoHKCjah4cS4l2q2hKwvDihiCibBxz9UAS+2j/wrAxPBbThqPOM6cR8SpFwXcCdEU0tICnS0/5BSn/IsMo0flE9XJkskM3alSeIDHUOochXQVTVAx3zIQNPJemvWwnk8hDNnZBFbY3WNCrZdFdIxHEB6JQNjNm+NdsL5hNlEaJJ90N9iP2tv4uTAE/NAOxgEnr2d/Lzgi86vJ+QzN7E7sh9k5EMAZQSVjkCi92jcQlsguuIE5UJPhuH3Ph5EwlNty9uAfKqL+Z8sXOZ48Sjr+lfGWubfv+NeyFOpogem18/73szoWeTCrrOGAFGSW+HUpG8IkSuAqKhFaJrvonuHB8OUDGjlPCmAAGOh/2TBAmOo5dNolXbdRK8lMznp019X1eAyeYAOLagtu8BkFYKdLPKhyf1kkjkFJchTDKrlIo4KMiGR6saC5PIkxNJwsNsEvw1vDG2pqHejsYQCBVRWt8KAJAjQ5CFnWpdxLGdCAdWA1JCNLSrJP14UqwhoQQSoZeIqsoIYcu6OWShAXFLNSI9O0zi3B0SKvEr6v5/IxYd3hfYHblvMpIhgHGtpcjfjLAmtMB29xo5UTFSmchCi7cpQiRshZY4EUXkS0aetAwa/74ssZH1RkNmjNhCVrA7Ep0O1S4zNgibxiTZNnwCZ5Li6V4Ke85I38f6RT8DZo4qQ2BkGHLbesjRnRC5PER9K0TXgXDGSylLQn7G+GloUxhT+6p+9EPgv38L/OD/Wh8WPewG0jwnZoV4AGbQp4LWtK0Xt2j0zhHi4nDsjJG2JUslDAHQAz/ehUi7HiAAYylKGR3YyX9mpMlQkXaGFepmEJU1dnJZGFG+9mwWGOhD0LNMvRSNHSpJ380oMpswCEb7RSNWs4xWqympU0ol2fRkBEiWUScCD7bZ14sO747cNxGB8eucyF8VIaxyFtgeElY5jOcL4wQzGaus5HPMKiuxrFgb4ueTUr3j8e8ixMbJLX4uwNYdDe1/YQhINuGlXGFzvAzUyxXfL4huT21wBSNfnadM949k0/gYFoFgfQBAOJB0ztFhyP5NkENbIbIVQH0LRPtcOLmK3bvXmbwtFLKfYmqT4OgoMKIlxoBr5fxBda2lQhab76mHL5PXg6RU35Hf0NHWTaijGOnhpAfCWEQ6/F8KNfDSQx0GKtAtX2WlApMiwV4mwBIoWYPkL8xVaiINWDsQ9WUCujRccVwyBKCswbyygmV+BpyGdiDwITetgXztWYi6VrU6Rn2LKvYdsd5iFpYQVsKVFGnq6Wo5Mlrgm28L2AGKrssbg6mNaqztXUifmOyiw+Y69GBE25aT+yYiMP6sTeiv4lGPbzJhjYfJ+skmZZXFPgs2mZqs7JlEbCH7HCfXRGITLGiL3WuaHBsrTFqlwpClYGMFGz9I1oyQK4052vKjd8YQnj4X9HkQ2mND9w90PIIMAbimqbY/dLv5+071ianNYzsht22G7N8AZLIQdS0QTe0QMw+cpMRZBo6OlN+PyY8w9QNjpFQDaVw2NCBpAexh1QnuRHrZSl11RbIVHkJbMFuGimgouMXN6RUiGMGx9IYI3Kzy83HdnIJgAo+1TyjyIGvPNF/YF5GKZ9P5SKIJQ3ucyc7caBDwi5C+p+TSDSuBjauBxja1TmJTJ0S+kuU+OpZIDDHG/AFkIQaeaperJdPxyrfRwBKwKFEjo/KBJbbPhASmv09EwuA5aclwHxDWeJiMlBj5PNnAjyRyS7DKJmobECWxJEuNtynuPkiSPrmkzokpTnT0vTmuU0p05h3k+4b2syFHZgESSO2hbfkzCzosOyY/humHwJ5DvdD2ndbnMqRXGIUc6IPc3Kt+rm+BqGsBapsgTHDfHmI/lT7338AYIewSRcUxloxOkNEHLpSAE5hnXkmkw1APoV7Pj6S2wAe8YTWI5yrUNn5BEdioDrDJ5k3hbJMzaJLSPba4raOsNbKQcpWArNDWkCZYr6B+z1dr669giYdeUJPOoQfkuL+Ainy7ZE2WGayYhSZyIZCrgFtVAznv7ZCjO4ANKxGu/JtK0m+dBdHSrYJrSObxdNRqfIAgayeTs2RdHLX3QTh2hgskkBnsj2a2TgXDEZulO7HZ9XgExs4XIVxfBTnta79iCYHHIgvH+wxMQGJJEqPD9tuNtpYjtIgMmkRsjMScTLQ9QpS2J35skjs5WZnjM3KjSRefQBli01Hf0rfHjjxP+p1zhd3P+Lp9u71xHWg1iY4VBAB89jvFAgh7DUR4dH9MO2DeaQkJFMYgB7dAbloNFMcgGtqUtXfocUruNK4YNtnfXWQrbGT8NMLUJ0GCEEC+EgjzehklH6b+p3k26CGT9uFxXLUd+ZUAAH50m9AHxjz94mZVcA2lEPhFNcg7magMmNPJ8TxFwgS1CJtK4WZUxJWUiry8glmv0ES0+hRxmlfEBsReaKc0sCbwgFHd5kwlkNF+xHJyH6AIMZRq+ad5b4ecdyQwPKAWDqbapo0dSjZtaFV+RCP3xP2lbBDOZGCc/cbKY4FGfHY9rrUoGXEFTL527X2ciMDIsuZpLOP6FXcxiX9XZcVxJcZJBn6M12+7gslYahMRW0QGLUNskfPpY8YLTRDR8ckT/y+TiU6AIu0PUWLRxWVLx1XvMtUNNq6MUEUh8wmekfVziuxCanMASPYMUjsp0pzO7TCClQKmOAVvv4Sy9jwPcqgfcnMPMLQVqG+DqG+Fc+BREJU6Dy8eg0CT/N3FRBPm/Rz7DwkSaBmlQFsg5GOjSiiAfuBhpT0uqZHMmM3BVHLhlkNQjFqbpoA2kgnRpEiEKiiHZsqUa0dtpMCYfLWNTKXC3eQH9EbV4r9m0Vs2+3NdG53Gc4mkBLwRIKbSlkSG0svoCgB5tUnoA9X1EDUNwIJjIMdG1eoXG1cBy58BGtujS0KZc9KsWQ8qAUu2dzO23WEI+DtZf9FvCTD+HgdqvSe6jyGLFuUEtgvRqHG/opG39f3hIe1x+SzJKhtXSkyyymKEtjcxGUuNT/gi5EXWihPtx8n4a6lPeM5nXKKUsvR8/FwRawkoITnfj5IdVyUcOg6RD6L7hr4qG8glSsexz6AQpc8xEHUFOC47JgWysQAzySbXQlrSczJA6EOGalyRw9sh+3qBreuBmiaIhlY43QuAGceqiSa/P9y1Y8az3X04hE552MVc4v0M+x8JEtyMWt+KkuZpkKXQ+ni6gpsFHDX4IyjqKMaY1ZZh+YRksRm/oK4fSp+LPoBRGKLh4dD0chHI2kOClGuOTRBRuYWiICH03YxbB8L2AX9bTECOYNIRs6SEJkPjJy1CuC7EzAOBOYeq2qZb16napq8tYbLpLB1tqicB5nySDSjM70eE4hX0BMJlkaYxP2AcvM1Jay/6HhDq6NVI1KuAVQQmY5VxH44e7LiVwAdbs98biMlYauWIzVxPArFNtu2R85PVlUB09CzG5fJ4dGX82PRsxEkuSbY0FiE9K9K6DcJAWXUkoUZ82lkgw31wmuhoTU+uMJCKQsoLBbdFgsYc21bfj/4mHdMeKSXk8ADklvXA5jVAxQyIhjY4rbOAA45Q1VnMs8buL+zlmX6i+7U7VuA0lT6TsP+SIKBusEmaL6hyapmcMv0pkIUeZpIjZWgHBXoAywbdIGp1mSeUZp9k9SXN2PTgT+ehtpqV5f2o9SpcFrzjqb+lbtsEkaGmXmhS9RpokpOOHuA1OZuEdD1o5Crtucd2QjiOIrz2AyClVEn6fb0IX3xcyaYt3arYd1OnfbFL1kRklhxZc/TZG7OzZiOZ0j4TyIrxwA/ogYKvAWkGaG41JvgXE++5Pge11xvVfbYHxcEjxFXGUksitoh0yv1Uu0hsSdc3HtEBUTLjltd41mJEAt0F2VKwyRnfX0uIdmIpovtmM/qdAjuPVnTM9q61ArlfnwLYIuqCrp5kCI+tSBNZlUb9LiGAkR2QW9dD9vWoQvlNHSpfr/sg9W5QehdZzSX9xhSfuNm3q/w3zaXPJExpEix8+l+AX/0nBv6/n6OyuRkVNTOQraiAMLMjLlFp+PEEdnqpKKcno585/UJyssrmoZzY8WRwV81wAwrg0N/lq+3DRsEygfY3mNQJTTpS6gAS3TY3YxcBJsvTD6Jt5yTtFWx903IWFJdmvYKWdYXtJ7JwzBJLjh1kaIDigSPeGFCU6kWub1M5hwe/A3LnoCLENS8DLzyuZFNNiiJfhQhR8Zmu4wIyNgs2gUUcwraBV42ZbOBHXEalajwlKSFlBvK4X9H4K+OLDiccJ5HYdB/ELc8S62kvSKdxK46THREdPe9xci0XIVm2fxlRTVa2TJI/ibSkJRd7Dxw76aD9jTUZ2MpLcesuyywuM/EqxAjPjZYqDHxAFqNSu6PjDgIfEALScVT9zW0blcS5c0j5zxva4Rx2EpCvVOMTETMtc0a+VJqERngvNoZxKXSyLCic6Ko2KQymNAmirh5eZSVe/+tz2L5pE/p71mNg/UZkKvKorK/DjOYm1La2oq6rA42zutE0ZxYaujrhukLLnUIFr5AlSEspSdhV2Sm/j6IcHVdJCVktncqQJbFLS2oUmJLJqe2JRLN57SdjgztZgyRPUFFtIRAJ8+fSR5IEQvu5euWKcg+849ggIop2hT4PrZtIAQJkwRlCDu1gRPtEFhB2lJXYPhfomAtZLEBu2whsXadk04oqiKYuiOZOoLYZwgx8erBP8pPxWTet5UhWXUiDYCwSbzxMJKMGniJ4CZiIYTPT55OGcSw1wB7PnhhR6zO3d4iNkNSWEl+cjJKbCebIANlJWsJAKbHtimzJj218h6FVPugZ4xKmcHS6EZtURCR2D/AolYfdX9oHwpJZkoUXsQK1vz5MWP6L2uZ7mvRcwCuqXL0ta4GBPmBGHURjB5wD3q586gjtNRhFIoRJ15LaZxjpk6T+j7/7nCnHQSp9joupnycIqBQDLUkFnoft6zeiv2cd+nvWor93PfrXrlefe9ZiaFMfatvb0DJ/Lk666hIc8Z7TsKV3A0aGR9DQPVOTpGPz+KhOp3D0i1a0s9kM+43PXmkgpZJrAGBSJGJSWRiqWa6nV5IQjiZNEW0DrQwROe4ELwERbyYX/T5CpJL5z/zYLJNemqRzxAZvLkVyMFlVQgBDWyG3rFWz5CTZdCLQYE5WtZTMquZyWtyqm8BySSI2HuFX0gfMOuODe4n/LfZcUMAN9TVfx3G8AB7exqQ8OCMBU3sSiG6iaM2Sfo7LoSHz5SJKcvF0gCRfXyQwhfctYvJnzOKMWJZB1CKMyPautQaT/M+8v0lKJlUn8EutQGo3FcXQ+8sggBzoA7aug+zfqKKqGzsgGttVvh4F25GiwldI4RNJOgfl4FKMAo8dKHkfJ/HeEyi1y/hLpzf2/1UkyJIr6mCUyENCL6VEUCxi+8Y+9PduQH/vOuzY2o+5Rx+OzkMOxMPf/H/x2Le/j5rWFjTNmYWOhQtw+HtOwwGLjoSby8LzQ1Q2NMF1hPUD0WyVksLjA26iHw42GpQP0lSGzBT2zuoEet+uLkEWGVmtGe0vkQmD1ESIyIfa6qTjGDlU+00o4d1IQ1TMOiEZniI1aVkm7l9lM3U5ppeE2rIOGOovH206HviEQ0rdr469lkheJScl/T8jx7Lf434tLq/GpdT4wDmejMoR8Sv6dlWOSKJ1jJyBmIWVRHS7MNuP+9binyNyqBP9XM5ajPh5Y88klzA54SVOFhh50TPD02Ai/cQsPLon8YkQkQmfiAiwCQg7Vpz0AGBwG2T/elWZpTACNHZY314ur1dcoUAYWJmTJjd0bke7W+j85t3Vk7kw1N87lhDHfZ8TCFE4evHvqS307W3s/yRIoAAXr6AeOOPvc2AGlIg0EdiHToaQEhjsH8TmlavRv6YX/Wt60L+mFxUzqnDwycfjoHcdj1ce/TNWPPEs5p94LA4/81RsW78JmcpK1Lc1w81klEUTJ8QwVGtvEcHRb8ZfQVFrDhBqQo8TubrA5OsumYUTIQWA9JP3MUEBfGDSg4HHpFWKqg08KxuZqjusfBxJRkTuQFQqpQo8gJ3N64FOFkfVki79G9XsmqJNW2eZFaxLgmDicqSp8JHQb45rvzekIuy17+4aiZFBW/sESUYlKTVOoNTueMI3m6wZkjZty4xfdadc2yDLk1ySbBn5PJ71HLMOSyRMhz3TCRODOFmShUfvZ9zCi1iEMSsvyfLnlje3xMzxiHyCEstcOg6wc0hN0Po3qAlabRNEYydEQxswoxaCCJosS7IYaSJGVp0hPv03XR9NCLk1SMehiRUnQfMvvQdlrMFU+iyL6UOCBBnqYBKPVYCJy2cBTNSlkS0oBB524GEvYlAsYmx7P7JZF97YGHpfWIaquhrUt7fi/lvvQM+Sv+HY91+Aw88+Aw1dHeh7vQc7BwbhZjNonNmFhpkdypKcFPSDbqQbPcA7GfvZzanNvKKVPsvN0JNSJQB7fHByYN+FgSbDPGyIeAizCLAp5xbYIgI0GJC/jnyHXGKmHCi6F3qAk74PDPapiLptGxOS9LPMMkiSIPWEx5RvC6yl7sZC0MPYoArYgXsyll1JoIm0AzrlbfL7adrtsACkMn447m+ODOSsOLhpAyc5ZoXR/TWkEpMaJwxwkSUTlkiQVOKxE66D97Ox7jhZutH9d4Xw6PnhkxGJaJF2YwnSpC0wpAcnoyZh/RsV6W3bqNbWa+pUwV61jWoSpoNfjEvDPDMSKoKVtcOck/8NuwKLsfQQtfpIojW+wjgJkmUYI0Eno/z8qfRZFtOPBAlhoIJgZKgjJ4X2J9HMj83i6AGntQFN7h91EbOyjIwW7T4Zhti+cTO2rOrBji39qKiegebZM9EwsxOv/ekpLPnlA9i0chXefd1Hccjid2Lja6+jsbsL1Y31KBZ95Osb4WazTN6h6hWwgwUN8ACM1OJmrZSSq7SDQxyRACAms/CZJh/4uaXDt+XE57gwCwrzAYz8jBSKTuSUFLWb5FMTStaUI0PKj7hVy6Z1LUqKauqCqKoe3+JQN8VKyrQKB+WNxgeNiLTGrJNyAR3lAk24v5CsurhkN1kZ1Uin3NqMPXskNfLI3vFky6Tjc5LbFQkz6TiTte5K9puA8Oh5D2LWd8S/6sJMGjnpsahOGQbA9k3a2tsIBD5EUwfQ2AnR2KbW3jSR3DSZgzpvyVjhRY9P104Eb6xGZqEmWYA04aV9wwTy48Fx6sarqM9U+pwQ04sE44EfRHJU6YV0+4gUNQEEe2lN7h+bDRMx0UNqokLpRVcDsfQKkEGAkcEd2L5hI2pbmjCyfRB/vfeX6Fx4IN525ml47S9PY+kf/oTiWAFNc2ahac5sHHjiIjR3tUM4jhb4aGAGIgW06WWZjCwS+LYGKA0uEf8JI0WqpEFRrSWTgcROs+cn0jQBHHqAo2LBFGRUjryp572CIsPNverfihkQzV1qAJtRDxEJjGGSHCd18iGShEtpFnSfeNAJWPuBGPmVGaQng0QZNUa28XNFAlHIUoc9hvFzlclXTJQwSY53SvtrvOtJsqL5cbj/LuKLLUd4JE3H/OQR3yk7j7GGmUVME4wwRnpuRgVlDW61EufOQbX2Jll7ldUQpHIA1p3BFQ4ewGS+Y3JoqAvik8IR+LYvjcXo2rGDyjVGgmJ2wQJMpc9dwv5Jgv/1n8BTTwJfuBlmQABgHpKkwA8TnOHYQdeQJNXazIFKG5mXio5HDx5gX2Y+K40jaVUHGoj5OaWSNgM4GB3YjlzWQXFkFCuefBYvPfwYtqxcDW9kBO/5l4+j/aB5+MsPf476rg7MPupwtM2bgxkNdQAEhOvYnpiMg5yu3S/YfolEo7H+5KA20wycfCymHwRMcju1hUtxZjBkBYlJqibf4QQvtwxDk6Rvo01nqmLf9W3avcbku7LXRBMIInzy504gg3JpL2K9JMipEd9lYMknLlvy55Rb5pMp7m0GbCKCuH+U7kOZCUK5Y0auMYwO6HELr8TvJ1FKeEi2gs01+NF3io4diewE246TniJHKVxgZNBaets3K19eU6eS1WubVTH4iD9bVyni5yYrEAJmTUzu8ybfPfm6qYYvETMFzAj2mY7FJ+NUiaocCXLyS6XP3cL+SYJ//Svw9yXAFZeX2UBEX3Luf6GKLJmstdjoBfSL6oHl6RGmNqWWBV1muSTNckuWVXK0tRMrGG1IiC/VlLU5S76ubKFXqQh8Hzv7t6KqMoctPevwtwcfQd+K1zG4cROqaqrReciBOOLcM9F58IEQrnpJCjt3YtPKXsxorEfjzA64mVg9wqToR7J8+fU6WaiiAHxyoF9Ox1X9SLPgMGA+QB3YYUpUMQLgkZlxq9LNqkmEG7MOS/xwynKTw4OQW9epmf6ObUo2be5Sy0JV0Npoku3PpDrTBmYB8wCnySBk957WiUuUfbm1NI7FFScgLqNyazDiiwzt/aTrAqLkG/crGosr5v+LWHdcco5Zd/yexAkPiOZZxgmPvy+J7WOTiLKkp0iJ/Hro36B8ycKxpNfQpgLWSnzW2ahlFwYsEhqM+FxGdGyZMMexbSfLmxMhtZsfj/v0jfzpRiehiTIoUulzD7B/kiAh8FXk5XiXEiEeAIgNUGZwogFJMKtGy5uutgC9sZgFl2VBILHZWbkUiXIzYa9gq9pAWKIlGZJmxBI2QIUGaSkRFAvYvmET+nvXYWx4BJ2HHIjmWTMBISDDEBuWvYqlf/gTtqzpReCHaJjZhaa5s7XsOguN3TPhZlwbVEQDBU0aHMemboANHhR0BNgIUkfXXPQ9HSHK+tHIizFSLGfBlNzPMn44nTogvSJk/3qgr1elYMRrm8ZD8iO+LLpXNPsWutpOlg3gYWnbjUTNrV5G8CZoJeYnG88nmGhxjmPhlXsO+fF4wFDcHRD3rZX1U8ZVEE148Wvi1Yt4xCbtV06+NaSXFBSkSS/wge2bVXWW/g3A2E6VZkPEVzFDRXES8Rlrkk3UuCXHSStCfMwKpP1NMQnHkppJk4gRIbecTWCMSCA/aa+dJmS74t5IMS72bxIk0MoRSdFTPDAjLtEBdmCiYtQmMTmInYRZl3wwo1m0GYhiFl8YqrbxAdbsxwdQYSWScYlAxKQVhy3emzBL12stSv13GIQQALZt3Iz1L7+ClU8+i5d//yi2rHgdNW2tJk/yqPe+B/OOPQqFkVH4UqC2tRUuQjsguFQAQCBajk2DD1xGBmbLz5g2Ml9cRMKm+5UkyTp24BynpFeybKqT9Ju79JJQrK/iVkei31g/T3wdwomiLaONipIuLwfGnz/qwySfXcTXF5PlTYCTluK4pcatO/IrE0lz/xyRYaS9ROJ0b2P+0IgqIq3VVhIMlClNHzE5k2xblnIjIYGhbSx1YatKXSC/Xk2T8gkTyVPAWCSNgSo1CZhVXszEwLeTPCIpPvEDrBWYYeQoQ5gVZwLP3p+A3QciVS6FkuKgOgDGqqflnYic04T3vYLpQYKAffGKY+pv8u3Riw9EJSUugXFfGFk7ZqCWNjKMH4+synJgUY7mxUokN0dJjSaohx9Tt4f8ChQYQKThZnX7fPXClPOnhYEm4jjBWilQQmBsZAzbN2zGhuWvYeOyVzG4YSM6D56Po84/E5tfW4U/3/MzjAwO4cjz34ODTz4B9R1tGB4YAtwsaltblCVZIgeXdIztl/6t4QAAIABJREFUV8eNkmk5IjGBPNyq1pMSPnEoCSJh91oIJZv29ShCHOoH6lvMQCryFQmWJZMWqWSWWb+R+2pi/rFEHxk9aywwxUTPsmvhSfIlAThO6aDICY5Li5EuZ/7FckW+jZRPki57Tsy+WWNxl5y/JEinjD+TR7vyZzo2qZAjOyC3adLbtgnIVerI4E6goV1NYIx/nUVt0iQ0Ygk6llRJoeDER/5AqqlrvotbgYHdj8YXkkfpOaVrJR+i8Qlm7ERDQBNhkh9QptLnXsb0IUECzfq8MfWQZXL64S3C5BBJwFZEoXw2KJkjYANtXN6iGRu9vGXBZ3mT2EY40Vy2eK4bbU+Odl4YmIid/Hm5yqgUxfuF8gVpAOFBLJEKFyEichWA0PMQegV4hQJ6nn8JK/7yV4wODaHjoHk46F3Hw81k8MJDj2D1s39HbkYVjjz/TBx00nHwxorwJVDT2gpXSNt3gl0LBSVNJPvQNfhFmGAaY8Gwwd0kcCf45gBAOGpJqO2bga26Gkg52TQJNMBStRp6Rri/0txjaT/zwJkJozBjfkEjPcasLiPbMsKJV5+JH4OeHa5WxANeHPaexC067m+MWHnM17irpOcVgG2brLUXeIrwGjsV+eWr7LsXT2HgE0VDfPSbnjTGic/VEiW3HHlQHGDfR24FCqHLFwKmpij5BaHbQGNMGNjzJEmhRhLVZDhFpc9isYhrrrkGy5Ytw7e//W0cffTR+7pJEUw/EiTEB/1MHuCJ20RwZEnwsPgJ/VJcepR2IJay9EE2L65vz0vkRQNIOV9P3A9lrBImoSXdxvFeJrIKAdUvvs+OlTR4J1w7nZOIC0DgeygODSCbcTG6Yxirn3sRrzz2ZzTN7MQxF5yF9Utfxf/8x48xMrgDHQsX4MAT34GZhx2Cxu4O5CryMCkgTsYm1JcLGiGrwyw5ldBeESMc2jchQEfVNmXlsfyilk1nl5dNIwTlR+8Dt0IR214IlOQ3JlmOnLC47y0xZQeW/OI+vfFI0JwvtBMJTmj0vJgAHSr8zkjY+BIzNpDJLETNSS9qFcowAAa2WGtveMCmLjR1AtUN6nkwUilLYeD+PZI5iYiMjy+0gW7G4stYiz707cSTW9GkAhmZVEuzxgp01XXSe5PJRomQ+pv2oeeBAmPikigRsHFpTD3cd999uPrqqzEyMoLDDjsML7300r5uUgTl+Gv/srVpRhyJHtSfabZVGC7dxySexwatMEYylO5A+5nBJLCDEMEbU//RihOUkkFRn0am0fuRczw3Q43lZtFeEfVT0mw6fg1JREhtMEEqsMQZH8RVB8CQiIkOJck1YwmV/Fg0uPk6mMfNws3mUdncBkiJmpo6HN7aisP/4WQ9YGVR29WNgxe/E2PDO7FqyYtY89zfseyPf0L/ml6MDQ2hff5cHHHemThk8UmorK1FGPgY7OvH8PYBVNXVobGrA26GBRGYe0ZL3uiIVVP03LcDmcusgvhAI0OIMASaK1Qh5PlHqsVP+9cjXPUC8MJjOklfDc4iX6H242RBdVyNBc9ktJJqNdI+O2RhJE0+aBLkZtTyP0lSKD0D5JcOAruEUDyhnqw0eiaT5Fpqe7y6EO2bnxGTNhkJeaNAUbLzZeyKJo4DKSWwc9BaegObgSqVuuDMP1pJ02RZBZ6q08lTGPIzbP/4ni6EoZ9PWo9T6n2LY5b4MnkA2hL0xqysm83D1Bymc5BCQtHjVBuUavVmczrYK4wGjRHB07PGLT6zALewCojxAUNd1xSXPru6ugAAFRUV6O7u3setmTymtiX4+/8GXvg78PH/J/o9SZaRteZY0AlJJZmczeEzUgmTPOIOciIfU3Ek5nszEY56e0ovUDvZKiXxGT9tH2h5jwZx84Kx2pvkkPf0EkimbBlZNnIcv6PpIDYg6lk7Ld2Uq1S/+zw6lElJ5KznqQMmHYL5yYgUeDAADcw0QNDAYPo5VNGt6zegf3UPhvq2oKalGe0L5qO2tRmh76Pn+Rfx0u8fxdae9XBzOVNMwES3zuzSq4AUFBlQEr6J8Iv7jshHBGZxxXx2EJC+p2ubrldh+BVV0ZwzCvIoWQGBSXckz0VSG7hlmBTwwiTvpHqc1O64hZdk/fI0ibjfMl7smgeumIlP7PhERjQB5NIma5ckC21khypNNjwAUVWjVg5p7IDIVcQmhrEUBpfdH74EmZlYOJb4eCAL+f7i35M0ySOWnQxMqpLjKB81HRNQz5GU0eP4HgAiQmYFhqH63smwgBjYfucS6BSVPsvh4YcfxooVK3DFFVegpqZmXzcngv1TDn3lFWDlq8BpiyfeloerQ/9HAS48H5Bm6kHRav4Z9rLF62/y2WNSoEEQqNlxSZQpGCHGBqPI9prM+UCVJNeaklmxwZSi1Iqj0e3tjogktZvvBLOIA0ZWDswiopCw5dL0+XjwCg1OZkKiB81EH51gPiLXbs+tDa8I6atyb2EYIih66FvVgzXPvYhXHv0TVj/zPIY2bjLRrTOPOAxvP+cMzD36CARBCD8IMaOpGa7r2sCPyH0R9txxOZHBRJtu7oXc0qtk06YuiOYuJeVRgBN/1ui6I5fsWAubR8rGYSw0rQKUS22gZzGemhA/FhFNyXHYxMiNkSi3/iNyKFk21sqUQLQ6y9hOoHWWkpar6wHHUYnq9MwTAcaiQQFEJxBC2HfR+OU9s7af/Q32e0BPxrJQliDLAXaztj+MBJphlp3uT2PRa0s/1D5gmqTSpJlPIEy1GKHuGz1zRH5TXPqcitg/SZBQkn5QBjywJT7bLvElJQxgJvDChZFW4gnLXHLjslVSG+MSpTpxaVuSroHIhawoI9WwUm0cNIv1EpaaMv49yT5DLYQKNkiVBAHFyJj7L0usUWEHPJ57B9gBTgI21WOcYBGyPH1PN0ETsxAI4WDnwBA2r1yNvtdWon9NL7b1rkVdWwsOOfWd6Fx4EP52/+/w2p//aizJ1gPnY+bhh6CpuxMVVZXqtElLRJWBHB6IRpua2qadekkoRuT8+h19zWQh0MBMYftJATFxH2ckuplZr9wqBaylYgJfMihJRk8MwGEwBJmN3B8ZhsDwNsidgyr9JFcBzKi1lm++Sq8VySxjssK4vzTJB2kmmbGkdgro4opMkpID2O3JJSG0PMmtPgGt9nB/oGfVBJoA0xjAJ9CU6kKkSH1FUnig7xtNNimCO8Wbiv2bBAkh+aeKsYGdBt8yFgmXKwDAzcNEYJp8QZKKggQrhoEG8wgxCDPulV2gNWJ1sJk/Pw6FWtOsPJLyQYQaANlKLZsmQIbKVxL6iNQupL6iRHx+nWRlArA+1Ek/NjD9TXl15DeLpwgg1m9UgaYsGYZ2MJsoMEaTS+B5KAwOIJfLYLh/O1b+dQmW/uFP2LpqDfrX9GJo4ybMPe4YHHnee3DQO9+BtgPnYXTHMAqjBWQqq2wKSJkC0dL3IbdvArasU7VNk6JN49Ik5feVS53JUMDJBIQckRR123j/8/4w0aNkgdK+vh3IeU4iJ1oJlbM3uhNycIsi/yBQxN/YqRLWKSCE2sMJlQifyCYkCy0W4MR99GT1CSeqzPA6sHRMeq5JfqftKUiOiI4IjMiNiIm7H0gVEtpKTZJAM1n9rnIJlL2P5CfM5pVvcj+RPqcapgcJEsJQV3XxrTVD/iw+04wnDPPq+cD4A4YJjY9bR7sDRgAkCfHoP3pReTqEIXTmk+HHctzyaRIACwbQFqtJcHcQ9WWWaS+3pCnAwHGjAzHJVNTHFEEZ398cE8kTDLK+nZjVI9lAqW6gJVSyqMLQDuw8gtFhA6UMQctCBUGgfZJr0L+6B9t71yGTddHY3YmZb1uI2pYmvP70c9iw7DUMbt6KyoZ65ZPUVXcau2eqVUAAjFvbtKFNESK38CKRwAmWGN3XiM8xRqg8RYEnowP23sT9h+a2Cts3MXlfegW96sJGyMEtKl+vuQuithHIVWiDnLWN8nUjUaEZdY+4rGvOTcSo/WNU8J6nKpF6IAQQ6uOTfz4SCepZmRmaKIMiswQdO3lyGRnybShtgge7yEA9J9R3kYjQuBXoW9+j66qJaSp97lNMLxIkhIGOsvRtuD29XBIsgotZVjxPjiQXAImzdJMiAWbh6e2pcHUkgo5ym1g0KlldpkgvJ2GRTAoATH4d+LkT4GZVWyIDpiaREguEXSsNZvx3irITsAMBTS6oveMFzVByMUlPQkQj+mgwD6gPyj2aglmVMf8nkDwYmgLfvh2EiRSpncYiZf7eWD5f4BUxsm0bpFdEZXUVRod2oPeFpVj+2F/w4m8fwbY1vcYn2TRnFppmd6Np1kw0zepCS0cj6rM+MNCnapvWt0G0dkO0zYGorC69TDOhYM9sRFKO9Ukk3SJOqjQZ0Mczkm8m2v/6Hkiy0otjkMMDwNBWSCcDUVkL0dgG1DQiUnrO9xDNr41Zc6TAhOyZM5WEqP9jebflCC4+aaT7B/08uXz7IGYJ6iXETDCMl1wekEg7YJMk6kMKkqEoUJO6lFXbU0BOKn2+pTA9SZAQIcNsdEBMmm1z0KDjuHo9wtiAHbdKgKh1k2OrThDioejcT5jJw+QsUVFtHgXHcxwpqIZIKeJzGvei7CDpOIAUdhacq7TnSAoOAHRfUA6fwwg+NnOn2b0JsAit38b4CGOWNEVP8sEz1JIUyVSRS3FgeYuunyxNsi5J9maRmabQQYJ8KqXaL5O3/qAk8FxFTTASAjsHBrHl9TXYuGw5+nvXob93vfq3Zy2GNm5GTVsrOhfMw2HvOBTzDupCa1MlAjcP2diJygMWwmlqh+DHjliL5H8GI3jyq4VRNSP+bJs+ZdIqWXpJqQs1TYqk61pUHc5IPqJj+4AUCv5M0OSS5+9Fnj8eDBZYqZMsWHqm+CRMuDbCOgzUQtJUaQX6PtP7yttDVh99B/28B4HexrVJ9CTRUiEGU2TDty4GIknAfk/PvZE+c6n0+RbD/k+CkdzAMPqZUgfiwSCmqgWsbEZRZiZs3o/KnsLRs814egQLHiFyiwyw5Msg4uKSoLQvdciIhso2GYsLLHAi1INAaAduE3Dh2H8nY1UlWRXcP0mVYwT1iR6wSH4z1h+TwWghYyPfxk+hSYq2oTZk8uVDximSzxtjFjIj0yR5u1zgk2mHllkRuxfGqmcTICIOnucXCSKRlhxCyawtG2ATeJ6SW9f06v96sG1ND/L+CDpaZ2D+wbNQVVOFntWbsWWwiEKuFg2zZ6Np7hw0zZ1t5VZjIepAEMolpevlKTCcJFgaiKR8xtFhyKF+oDCqluipaYSob4PIV0b7Pp4Kw/3dOjDJnou+Y2RE/j86TlL5Oy6pc4uNnitekIAseZJPwyCq5BDxmshmAVPo3ciijAwdJ0Z+IYsK1cRJ/VlChBmVOJ9Kn29Z7J8k+H+/B/zlL8B3/g/7UtiX0SRTs880KBfHYEoU8STmuD+Lr21H4f8y9nLxJWniGC9FgslsEZ+jX9QrSSQRFLtOnoPnOOrliy87RJChGuSSImjN7FlA+QQ16ZlQdAlbEGBXAmJgr0G42j+rfY5cfuSWDG2ftA6juRY9eEfIkJFW5PS6f0kBoPtIgzAPx49UdZnEtVLAEPeh8TbGrX2TAuAqkuRqhB7QgyDEYM8aFNeuRG6kH1Wuj82bh/DqS6vx/OPPYd0rK5XcOrtbS61d6FgwH7PefhgauruQrchDlKm2Y1Zd6N8AuW2DegdaZqlcvZoGIJNVqQvmvgj7bJgI1kxJdKhSLchHzi1W2k/fYwk7IXJ10rlRErTfLqRnQN8PI3fq/TJZJU1CS5tx5cFYytJOPniOL5EtbZPJWzKkv2kMoKIKxret5U6aYBAR0rFS6fMtjf2TBJcuBV76G3DeuWU2EPYfc5UJ/i/AEiRfsZusIO4/ImKg5ZFo5mqCEjJ2oIsn0hfHmE9DMhKjAbfMrTArn0s7YDqOtXBpsPO9aAGAJJicQdYumhiUS3EwwSe6T3jUqulLAVMAnMisJPiFX5ML4+Pi5BOHcNXgQvlV8TD+yLZ0HUINlBSIQVZT5B7pCUgknyxnpTjyTcatlQnTV/iEi/VB0ooU9EyNkycovYJaCqqvR0Wb5qowmpmBrUMeNqzbaqXWNWvRv6YXoefh2Pe/D0eedya6DjsY/T3rsGNtL8Kt69CQC9Ew7wBk2mbZJP+kpY6MZC0RCdAiZSWSPsSkZl5ViO6nV7THoufdpASx94zuGQ+M4Qs982Py/iOyp1qyhnBJ/WH9DGhJnZG78Xczq44mth6LGjUWZDYa8DWZdy7FWwL7JwkSpIytw8eh5U7wh575xEz4tw/jZ4lEKjI/yLiRoGXOY2bT1NYkH6Swvjfjc2QDMbc84zJlUsSoDLVVWMY6pQABrxh18lNby/lJI+kfTIak33K66n0kVF+TPpfDTEg6s57MNdMAOQHZGOtZT1rIhwpYnyqvF8mXvuHRiWaAN//T/cjzPQVKJjS03qL9kkmPEokSPB07LoUTsfBAFciSIB4pHGDHNsit6yG3rEXSklD+0HZsX/oC+pe9hO09vch3dKNp4dvQvnABev72Mp775QNY9ezfkK+p0YE7s9A0qwtN3V1o6u5AY3cX3IrKBGuvDKkZOZQTJCwB8eAWI+0XLRlxiTkerWpWrBA2WpMsPB5ZC3YuOgdFbJKPLoxZjKR8mDy/BIWE0iCgA2NIinWzOseQTdBSvOWxf5MggfKAvDE2ODJphwYl7icBrHXBESn260SPEfraf+fHzrOXkLRmHI/qo0GSiKNcFKlwNDGxl9T4TplPqdy+ZkZNwRDM38Gtsbj/k+drqZNGrQuTlhGzNug+CIFIFR26r2UjdDEO4bDrjlirjPAiA7e0gySgy67lk308JXmKMZD8aYKaqP/D6L8UYJW4JJe2+g0ZW0tTjgxBbloNufF1YHjQ9ldzJ0TrbCVzUtSpnuiEuibt2I6d2Lzidax88hmsX/pqSeCOiW7Vka1N3Z1omt2Nxtmz4FZURQmSJjxeMXp/TY5tTDmgnDuuYPB1+czqCzHfOj0XAnaSQe6KwAeCQpn3QbCgFmYtcsk7ouhkYVYfof3puqRU92m8SWaKtySmBwkSaNAkv1qG1QGkSE8uy5BEZgIq2KwzIoFxC5GDtiH5VeiagMw/QORJDnwu8/DKGGTBxOVJirYj+WlPYSROkuu0fyNXaa0q37P+tFDaQYb6lMu+fAISh5l0UJ8HyddAfiIKSopDSnV8HiUaiQxk10T9PVkfJlk0ZnIUl2cFs9JCG+AhYJ+duPUJRK2MkpSEgAV0uNHnkD8rLAhFUn4cXXNxDCqlQQIjg5ADfUD/RhXN2TpLWYm1zWqF9ZBNeiiMPwwtybpZBH6A7b1r0b9qFfpX96B/7bqI5GrL0unUj+4uNM2eqQJ3DjhAkWSOksw9m7BOzzcRWNyKI3mRRxsDOsFcB6n4BasscL+euT+6/8LQpiqQjF5iCZKPk1mCSQFmYWAnc0aRYVZ7pMhFircyphcJEkw0YUE9pBSyzC0gPohzqyeOiBQJWMkrZL8TUTFfBOULJrZNyzQ8146nYpjw8tDmOjnaCixSMQAKkeeRf0lW0S6AAmS47EozYSA2YMDmVJG06pHvs+TA0b6JSKFM1uXJ90kwhFtgh4xPWPg5NdiST5HasFRsmZLxTXCMLPXjxY8tBFMK4lGY0gZnkDUc97W6GSW1lQlokmEIjO6A3DmorqSiCiiMQPq+WluvukEV72ZR0TJQuYhy63rIbRuVbNrYoWqbNnVAmDq5bBIWX7OSAlB4u8IAwdiIIsmeXvSv3cgIstdU3KlpbVbEOHuWjmpVka1Ns7rR2NEC12ETqUxWdYcpPkEStSjtdx5Y5Ot3mCYc9K5HfIbCWoauvu9+wU6WknJyhQBERj/jiLbDRNuSXE1+XlgC5qkfKd5SmJ4kCNgBzadcIdgBPP6SmeAYJjdGos+EzePjeVKcEM0sN+5jcHT5Kzd59ihD9WJTMi8AkxcltE8k9GCDSRBtP680E5dSAXX9iUW0Y8RE0i75S8j6jVfT2R3wazeSZMgmEzESi6ejxNMSIjKsljopNYEXSCYVgIfMm+AYPSmiYAfu0xPUZnbfqBpR/P7yVAtOpCUQ0fPwQCJHRZvKIFSl17ZtVDl7UqpAlqZOiIZ2iGwOJastRHLu+PcZyLGdkFvW2tqm9a0QzfpYtCRUpH2wFj9XR6D7lQJ5EiKqgyDA9s396F+7Af09a5U1uXoN+tf0KLl1Ux9q2lrsyh//P3vvFmvZVaaLfWPOdd33vWvvql1VdrlsMOA27TbO6XCkvIDdQVGjRP2AIp0H1GrhIyEufZDIg6VIoCAUJaKthItEgyHWURKOEiEdv7TUB4UWp6FpSEMDBkMHY3ypi6vKteuy72utOefIw38Z/xhrrLV3YbeS2q4hVe2915qXMccc4798//f/426BWu8iT/Lesyjl+Yb74Z7ilY29c7OWhRXb1Kzs+J2l1XdU4RW0vgTGFVg1XSM2r9LOv1xKjqwRVdgZktyd9v9JO5pKcGsLuHoVOHs29uTGtsJBDP1JnFDiCQKtSMKsLcckFS3SpF+BUlhwRTFGaSIgRvtJzNHApzZpXZmZTaBspy2F/7R48ABh77ZMX6Q/NmaqLE7+ThToWBzHBa9MIahEWZWcZ9U0gK8Cg1QFThmUno3D0UXzzzqpKTHGGBNCuACC8hNFpTHKwqRWZJQuEPo7abssO5ZSds0WALfXU8OkRXNOctBEafF1fG2Mn5SJy2PvLAlojHVq47oMC5ZJigSvD1GIuHoB/tolrm16D9zxuyk5Xjycsa3AokFKDDG5ZzusMzE8FFKn/tSjEa6fO4+NF14g5XjuYlCYL71MMcnjq5T+ce89pCzvuRvH7jqJY2dOYeXsWZT9WU494nSlwigoG8eTOLN6gj4QWlyRN+qiEIW8J58oPkOqUwa5UX7KZkVQwBbuniQv7rR/1nY0leD7/xj46/8AXHgJWFjgD2WBsmcg+wlGCxcI2wHBWLZFkIt1BS0DZRPCnYuhON3BoIjhmpynNxyQctPcuQyEGjWjLIUlFy24AsrMEwWW7pOYa9ab0ULAlVnwUyBhIChBVaTcpKya3QUhrbEqFPgoLaFN19OculwKRs4gMO8z/iU5d9J33FKIK6XvK2RpmYxpfNeFW1jDKk3NcLybejUEBntoLr8MXPwNwZp2f0IZD8titUbSxOexnlzmb7PruvceuHkl1DYdDbkI9klg7S64Tj/2MCVOPJY6w+9HDNDUU7PzXIxBgUIl/sklzmoP8iRfPoeN375I/145R7CrEHdESUrN1jOnSUmevQcr995LBc5Hg2BwjBHfzPoT9qgYelrS0IUxK8xzqgcviI8xslPmttzTGrgydw6SF3faG96OphL8q78C/vY7wKf+2ykTiIWA5DU587kI5luF+JwDvAOceDAuhkfTOCEQvISUbBHFAkUhmOtYQWjvb5W6jeWo94VAzsl6Muz5jiStJIWACkAS5+3zyM4Ocl/pYwojKXGggBJBtPYjwvXGKPFT4irixUVjYcgMCk9ZgZt4rDDvbAxWnqBsJzWJ6dlUAVXmowDPFSX8YAfY3aJ7dftUuKDgmHFRwrUnlGgT7z27E4OMl4k5KwGmGp8XBzyj39uGv3aJINjNa1Tke/UuUoztLhl7EuMUw0m8HBH8tnaspB5VFcaT6DNogo4jzylXsjHHhuZoQJ7klWukFF8UJXkBG+cucEySlaR4kGdO4diZu3HsLfdyTHIVZacXDMYoxQgIBJ3SeNwuKD1VqAmKY9e3xIOjZ/LJuXGsVQlWtvDCHaX4hrajqQSlec8xPxNPS1ukkHKKykG2iYm2alGZwQtXhYxhigGJIAUmCZpwzEHDztdR5Sp94EWrQtzHz5NrNiVEoGK7iEVwt7jeocBGAmXZLWYEIlPv2EB7unuHKDoDSU17RutVFq3AEJ3myUZbZh2kxPjzomWEqoXrhCjBY9PqkJFjNw8GYkUXXX5ccfkU4q2GoaxWp0dbDXnxuq0ycCCKvofS9DVn0ZamqxNP0Sh4V8RQP/cpQP5JGUCNW4Xj/GAffuMCsHGRYNPeDHmqK6eABSmebZ9Rxpg9XlVkCIQkgSB1bhXx56LoxetN57VCkOxxSswcjte+R+1KXL94meDWl17GxvlXuZBAiEkurB8n71Gh1lM4dt9ZrN5/P5ZOraMsBdaX8EqyXqxXHoVhTHqPKNCUM6CEJH7tlhSWyifd8/FOXPGNaEdbCUrTGNwgQH3R5LQLi60xZfYhjiVqc/kJmCWJGEEghI60b+kuBnahSD6aJgabhQBZOD4IC7VYYRZjxso+VDMKJDIMPCBpGa4ECgC1sZoVMpJ4IoIHYJtdyAIh5uI3tj85WFehSCGA5LxChARt9SzqkJcox2qyvg/eStTnMq4ZavtgS6+5gq7Kislv36DyZHBws4twK+tAtw8nscMIevexwJ36ikQAG2Vsdy+xisnGoMTA0zqjrFThgtfofVCYNmWn1aYhvXEZ/jJvHFwNiW26dhdw7DRcixV6tIdh2nfTZyk3Z9MhZJsiKaUmxRwkvimfaaHtMqypLFRemBi113Slem8H1y9dJeX4wgvEbD33Ksckid26sH4i5EmePYNjZ+/B8fvvw+rZM1hYO0bRFeUeNEG2jIVADLwujGuN15v3rkiSgVJtuESV4p244utpbw4laJsoQ1sGKSqfZQSgTtQUksksMGutyd/OTmAjBIoyhg9ts3BnWtGi7AQYMyqS3DKWc8VxDwvnuODVpEzM4W4SF8k0C2tFSgLBmMhCbLfaJkCRU71Ge3oRlK7EalJiDMBeUhO8KElVSMvXpdfWfvH3rQ69RyPgvPfA7ialIIwGcDPzwMw8MNgnxd2docPFS7Njafc3FAVlPWtRTiPjeQOJYZLAbdSp2Bia5BWr0JY56xHlwEmqgK2rKn0u2/D/CfogAAAgAElEQVTDPfirF0kh3rwKLB8npbiyDje3xErLjaMzqpQRDMKxMU/ehcxtmefi+YkhKDt9SBUarRJjDEW539hQFGGN8JjUVYXrFy+RUmSyTih2nlGS996DUw+8Hcffei+WT5/EzNICCnkWi9qk5en8BAVovV/53Brudt1YOF43A7jjLU5qbz4lKM3CL1L9w3votj9ZlmAaQwHUU5Nq80A8ma1Fn/USJYZTYqLlWNcmIVhuLzGHDOxZsIfo2cNoJQn6ubHg5OqIOWe9Octqi8gVBjIea44Ef7trPLUqGV/EW9E4F1I6JIk72gFgGvlDbjsBnjx0k/dsvH0d5/Hn9AD8zk3gGm0ui7qCWz5BqQsrHDez+YetNkGbYhzlthSSGK71gvSGPlRisUpKvkvJFYAxmurAihXylsQJ0zkfMVIRvKdsBRvuNytQPxrAX78MbLxKY9Kfo812V04CswtwqtgRG3uO54zs06cGKxt68MBoBN2xROFj9lpzYYeUOV20+HnrwA6VedZm2D9CUJKf8pwGBq2rmpXkecqVfIlzJjNKcu0t9+KuP3gQJ9/xNhw7cxfm146hN9sn0lPEJTDPMqbwRDk248+o7wLhegKf3okrjrU3pxK0wegxKjli60krgLjgOUhAvjECBAgLTPL+JsESAhGN9mLlFQlvWWQy4WFgEquEECz0tHSULT9VHpAmAYQcLIHmLBwmCjBtKRnHCgrbT5vXJ+OappekNR5zLFOx6K3BMRqMl0+z56aVadLEdFcCzhgrFvaVHe+NZ6UszrqGVlVJxiQWMS4eDrpKfI4KvQT6stewuW/KDGYv3RZPKCT1wiaJ8/y1cLCMn8RAlQnswnsU4SnHCYRod2K3e0rKsxQhh9NXI0rS3zBJ+mwgYPk4xUEnNse7jLgwL6R2qDCyGxO3rkchF7DVgRBntE9RrBQZo9SFOWrngSXDqG7y5l+qKH10DVKSl4nR+vJ541HGSvLE2+/H2X/xME6/8x1Yu+9eLJ08jpnFBbQ6LebxpcoxQUzsM1lDVo6R8+7kK2o7mkrQcyynVQYlplh9ytAqgkUnG8AK+yxlcMmCb+oYSnNFgHis8BZlMq1ihFi7lUmRiKw4IJrgKbFClF/kFZpnlAUplTAyEN742A041aMct/yVhAAD1TryViQnUI2MBmMb6srxdv/Ephk3ROQ4eJC3zEpZymWNjaOP474WCpZxi65pb1ME70xik6KgXQEv2+ZUI0obeOWfgLmlkLqwuArX+HGjJhoz40nbcbTwmM4PowgPExOc2ibNncRIiXY4MfdP81ItUxcIClQhSW9i2y7MQ1OVx29fp9qmVy8AW9eJbXr8DLFNS67PmYUrjWJK81VTEpEocsBA4zwvZPNdgU2FrayXSBUbryH7t4WVbUxW+ijdApLr2msEL66uKly/cIk3Wz5vFCV5lZuXLuPE29+K+/7lH+LuP3gn1t/+FqzcdQpzx5bR7feBwjEpKVGEY7IkbYI6CCLVwlTy2RFsR1MJPv2/AD/6B+Bz/0PmS3656hG5+CvvjbAysEQWu/dB2aVBecv4SuGMCOsHYovO9omtSVtbUgULC6lqaCzbBCLJQUPSyjYrQwSBoMQUmH43oRqOeBzC4BOvONoI1YVduNN413Av6duUhSkEkbFYI3/X7cdQnQgWKTeX2x0AiBe6ogHjaQbee/jdLWBviz5aOEb3ZwXg2r28MpYiCGOKX57LxUpP47OCKjSx550yQIV4o7FLxOOoEGYRDAtRWjI+dkwtZBbFtUXA5wRrrk04P+qjeef8XH40gt84B1w5T15ifxZu7Qzc6t3A7DyceKcS79b32A4w+2ifxq3Dxt1oEAw+OFbkMLFtQ4iT/qZ9tnG0CO0w39lHcvyM3jx/ToFGY5rcR1t6rkc94pgk50VKYXOBX+E97v1PH8E9/8nDOPnA27B29gwWTqyhNz/L06JAepepTWO/JqXpiLajqQQvXwZe+i3w+793iINTqMOFz7XuJmLPRZsIXpnkxspXS1RXCCYLfemHHHLYoZ+mSH7Xlix+j/Ac4jFLH5Wt5gDJHRSrcpJSz90vTaeQupwHxvb4vg5h7DWnKkeMsbCaLXbQgq8qYPsaH1fCb27AFW1gdgHodA0UhfjZ1Jjg921jb2pls/AVhaTl3gwk7xOPx8YEbbwZoOsI4SNKaSiNgdYYaNPEcQsuRm4hSDGm6hQ+NXEkC5tadEOqAEVGRxlyG2VMrJGU8+DY8MDN18Zrmx47dQBsahVwY5SmSSUpigDZSg1eIF7v6frz9ue4YoqN2JwiNX2zxkQKqYYXe8D1zDVhz/eohyNcv3CRlOK5C/TzlfO4du486uEIM4sLuPvh38ddD/0e1t/2VizfdRLd2Rn4piEFeRglKYatpolNOEOISK/Dm/zpT3+KD33oQ/jVr36FBx54AF//+tfx8MMPAwC+8Y1v4JOf/CS63S6efvppvPe97wUAvPDCC/jgBz+I7373uygnbSKeaUdTCdomu75LbCcnUCPsnz/LEU7kWAttRmkDTRCAOdZZLtdNPMfIExP2GOh33VQUptKKEai2fqEkjZfdWNBaxp0IS8mrmtYiQoZhnlmatlx/LBaoF5ELIFrAojDHCAHcRJFEx7wxSp9kTXIt37DHQM8Wemo9Aj9+XtoMqzBSStbzSD0jiTtK77IEIOtJFUERWQgSCDE8hQwz76RshRiZpBdIDmFWofPz27gsjDIGK2yHQIDSbnN4QQupD0LBahl3q8DLDtDpwu9swV/6LZVz27oGLK/Drd0Ft3QCrmMrCpnn1OvUGWVYIp6LMO/SKKB0zCOPUD6T95H53MPMFQcqnpFcO7pvRtlm+2Dk07Tr2PP4Rz0a4fr5V0Ms8pXzuH7xVdTDCq1OB3PHlnHPv/gD3PXOB7B4ch3tboeXgkC7aZybn9HuC+kcts6/jPmVJTQAit787+RBDodD3H///fjEJz6Bj3zkI/jKV76CJ598Es8//zyKosB9992HH/7wh/jxj3+MJ554Ar/4xS8AAO9///vxqU99Cu9+97tv6X5HXwlKs4nUosRkoVuIMhejkZ+1xEhysSbTrBAEgiKSJrU8J1krNu1gEvFGPJooN7BIhB8MnDaBFSZehe68kHiuNgYoijONSep3wJjALdtU/SRSmHXsHbgiCFDxRkred7BOoM0oEd8dYmcKeree47Z++wbQVHAzC8DeNvxwj35fWINDE6fK2BJnllmnbMpDpIVEzNokvmeJC7bQdmogTYMhIxg8ZyQkRsc/S+N72Li0hVNzykVhWz8ZOpb312rDj4YUQ7x6nmubzsIdOw23coJqm7baiIxPmbda7zcDXY95Kmbcx4bNx99N8xjtZ6lyPUhpiXL1PlGuPBapHRldE1PmyvR5UI9GuH7hVY1F3rh0GdX+EK50WFg7juP334uTb38r5tdW4cqC44/28o6jFzWcUXyuOwe0Wrh+HdjYAN7ylsywJ+1b3/oW/uzP/gznz5/X+5w5cwZf/epX8a53vQt/8id/gr//+7/H/v4+VlZWsLu7i29+85v41re+ha9+9avTL55pk/TXNLrW7dmkFFW7F6xX5xjKKow300CTdgEmB1SZySVKpgzwiljQacwQBUIpNU/3GWxLxxh2SjxLYcBJZkNVAdU+E01Mcrc03XzVG7iqYIq5QFiZ2edcIJvYRGQ4I5ysV5wqUR6D0ghAq4TrEbAnicxGIevWRRUbJ8l+g7o3oAvxO+mrjQV2Z+h+Em8UgeMcwWv1CNjagt++DnhPsb25JaBswbVXwtM0I1LEXe6XkmPYSPI1MBJPqzQ1Li001YznGvpJXh1oTNoct5L7WfhUCVjJjhkWCs0Rl3R3hSYwOu2GtDZFQlM3Mkoq2vjXh3hkFGc0BpsqIAuH+mDIpGQgKa5g2aS2QLd5XudASfjr98A3DXCd2KbNP/0Ds03XqWrNsZNw0i9Zsw0zscfilmnzmV8Pazi46Efmj/BM8p1VeNHh8p29N7+DnC6LAIUifJlCrVNa2W5j9ewZrJ49k/1elORvvv9/4+alyxjs7qEz08fSyRM4dvZuLKytod3tEKwqLGrv4Qfb+OHflfij98+jroE//VPgL/9yalfw3HPP4aGHHooU7UMPPYTnnnsO73vf+7CxsYHz58/jJz/5CR588EFsbW3hs5/9LL797W9Pv/AttqOnBKVZoW+r9GshbM5PSzdotdumKPORPYLhLsagIjdhCL1RDpLUXjcBktJjjCUdWfoI3xVFuI9uC8PWYj0CKkPOGe7Ss3V6sRKJxoXJHrInoRVy9jibeyZK3WW20hGoSogz9RBRoXC6YKYvxoN2rIC8B1AA+9tkdNiKMUUJdGfhR/vAaEDe3nAfbnEVfrAH1+7Ard9L1qrSwlvhHgLfjfaAnFOZmt9NA/h9+tx6GK6g8a3KoCys4aDMO1YE1ZC3sUpvZ3LmItYownXkfBlDh0RRJh50bbxueX7nANfh+WLmu3rBnuaN9fJb5j2LQvbCujTs2tEAkaHYmQn9Hg1ozouCbXgdSv/aPfquHpGnb2HNuqLRPLZOGwPXFfz2Nfjrl9FcfAH4px8Ci2vENj1xD1xvNoZ1XRmv5UltGhCW87jHlGZOoZoPrHeY7YeZc3p+gjhMAaOCws98eXiQT9s0JUniZoSrL5/T7y2Q+I1v1NjZod+ffvpgJbi9vY3FxcXos8XFRWxtbaEoCnz5y1/GBz7wAXS7XTz11FP49Kc/jY9//ON49tln8ZnPfAadTgdPPvkk3vnOd97yc9p2dJWgKDCNv/mwmIFg5aexkaYKWw1JvlWnT+eIhazxEW5KO7eeHs9coYzbGEkOIvEeWmzaQktNzR6GFYSWjSoLyFjcviIlUpRAux+8XRvXq0WZ+qD82j3ojuOyRVBRBC9aUktEKaZlnFqziOuHmmcsHD9bERSu9boVFvLh84rGy7e6tJHsxkUq7nzjNWDlBIqz7yRCS3cWRX8+IcYUQUg7hLhaqxNyRrVvJmXAEp9EiI326R+MoQJ+XwKdCvQrhKLREICJD0ZNYHlAcz3TOaWHFkEByxzOIhb2mjy2oz32jOxhNs2mIeQhvZ8o17H+8LyWuHBKihJDMW05GNs3ZlwR+o0kxq7F2QHXn4PrzwGn3gJfDeGvXQY2LqL5zU9CbdNjp4D5ZThZ96J0x+J6yP891tLjD/j+UE0Un0deseVOmeDR3rInm+/N5HuY73yDEh6rp9cBAE3TYPvqNVy/8CpOvuOt+C/+8x6+9r+SKPjDPzz4vnNzc9jc3Iw+29zcxPz8PADgsccew2OPPQYA+NnPfoYf/ehH+NznPoezZ8/ie9/7Hs6dO4fHH38cP/jBD271kaN2eyvB0QjY3ASWlwxUYzwaUSoi/DT3iGN+UqWixTtot9qAbwMtHzyHIe89JwK/1QbAG3eKVe3BQfvKMClZUckasbu9W4vbst0kDuGMQLN5VKo4CnM+e065GEFTGzjWNheUvDQRSiJMNZbTaHFiPVevL2OdEd5jfREY1z63tWBjw4BsAP57tA8UBZEl1u7CWPB+NAliNReTfMBs32zMD0ERxL2BKj/7TM3QKDp+HuuZ5ZSV3NO+g0kxQfEEbZx37F344E2KB2hJUnacPbNUozilJa5IjK02HhUbXJrPKJctQ5qM9FMq1QhMa9MdhHUIkJHgHBdsx3hxdjG6BLmA530g6VquMwN3+n7gzAP0EW8J1fw/DJuu3UUe5MpJOGKMICqIoGiPeb8Hxvdy3zX5z6NmIFFgsudmj7ctJaIdkjiWVW5ivPBG0n40CIiQJUZxqMiVzDJud4k93aYwwqVf/waLJ9cxv7qM+dk2XL+PP/4ve/je94CXXwb++I8P7B4efPBBPPnkk/DeKyT67LPP4qMf/Wjy+B4f+9jH8MUvfhFXr15FXde45557sL6+jmefffbgGx3Qbm8l+IX/Gfje3wH/+7/Nfy+WZYbAGY6pgGFqDdtJyMLaKtf4YCisZSfvxOTnBL4QGE2rwFRAbYSTFvh2AWZqalKq6n0aGHWs2kyu+SAM5T4y8cUzdJ4FhYHeBIrVcbCQTREUtnjhYgwo27QdFiAQdutoGoI4qyH8a+eJGDHcox3QV9bhlk/QIsmy4pLPJpVesxsOR2XdxKM1QlvGVDzlshPgb4X5jEJVL7bJDLsLrDrw+61M7p9cpyiB9owRzvwebEpDem27uatPFE7ZArqzQemod7cfPEpb8FzmmMKpBjaXfjYDfh72TMXTskqu3YdCn6rEGNKOtu7isVHl5wJiUlfQRStQrRxvFfZoHxjxSPZm4M68AzjzDtoSauMimt/+DPjZdwg2ZS/R9WYCbAqE8ZPx1PsAamxKjN2D1oXn79OwhZfPfJgTERPUm/G293Hmd3M9O078mU/RE5FLNXnufsjQ+2AXfjgI/XcFXNEC2pTq40Sp9ed4V5BbY3eeuGud1iz6cLOLQKsPdDp45BHgkUcOd433vOc9KMsSX/jCF/DhD38YTz31FADg0UcfjY772te+hkceeQQPP/wwqqrC3t4efvnLX+KVV17Bfffdd0v9zrXbWwl+6F8D7C5PbM5MYBufcuafBK1lKyUhq9gYjVWMsiNBlG9lri8stczO3mNpEnJtXwMoAiRp4VklTjB5QhLXRwP2RFwQ5mUJFCY9Q+7fNLQ4ohQSCz+KMBAPrUk8KuN1ALEwks9FqelwNGGsNB5ElrgvHO2p5/aoEPWll0hYnThDFvzsIhEfbKtHfI4L942Uo4u9H/udkJQk1lm0KK4HEIzcmBQBy2aVuJXOg5JIOpZta71YjSsXZKg0NSu9jLdslbooPFfE8LU3c0r6JnmPFoZN8w9Fyae7rms+oEl3URKLGU/vx+HKqXAoP0OTwK9yHb2EzBuMrx0b+5R5VI8A2RhbDDwx/oTYpfemteJmFokY9ZZ3wVcj2hLqyjk0L/0C6M3Crd0Nt3qaNjKWcQAAXwTvUJVc6uEZxaXpDG7CdzDXM16cRX34Hl5i/CIjKgq9+BFVdfKDXWB/l4o6SBy/w8qs3WNvrUN/LxwD2qfhWu2D0d7fpbkSbn4Vrub3WnaATueWL9PpdPDMM8/g8ccfxxNPPIEHHngAzzzzDDrmWlevXsXnP/95fP/73wcAtFotfOlLX8Kjjz6KXq+Hp59++vU/zpFJkWjEQueFZBO5U4GdelhWwGsMbgKskXo/uViMHCfVLnIEFSAIG5tKYPsYla2q4+8BQLZmkc9kx4ppM9/mGBZlECw2H9A+g31WIVLIWE6j9suxJo3ED3aA4YCE19420JsNQrjVhoMPBgBAsdg0cVqEqlSzse8qTd5vtaHb8Miza0wzUer2OUVp2FaabZ3Ek4i29WHPU9mZdVC4ziFKlHeO3p3DlLlm+pODzV9HDChLzJJ+RXHbXOK7aUWJUEKvIVgNCKQsKQhvDRbZYNk3wcAQ1q/Eje2c0lKEps9RaADj4zOhv957YOsa7YCxcZFg09VTcKt3EWyq70OerQS9JxePlX0H3vyzBBh+bx58TWYgE/y4Bwz2aT3s7QC6Llo05ztdqlTU6Sq5z7GSQ7tLaSIp6hS/4Pz7er0tJaqNGAUQY/L/5+3op0gUBZXY8j2FBuARKNyNIY5YxWeVnsBgZYloexkgWOjOKLRoIWQ8wigOxedb5atpEjZG4QOBZhJRQoUYC1ZhIjI8NFUZMsNSd2kHDFkkZYfy9BAiRj0EvEl9SONUDZMx2Cr3DSj2M9yj79pdLnkFqskJIN4P0cfxtMEO3avdD4pJ0xkEti1JWEg1FFskoBox8cMHwyeFsGRM7bY1FsaVpozXpFlCkoyVfufj7+hmfGv2/EVJTosJSnctLR4uJuVInpw8Y11xnJuRA2FC5+6jyeU8pmAjodOPIcrR3rhnGik5E4+UewkqYpENaWPEGA+kO1dEsU2EdVOUgGuHMVL42wUFFu3gUVFptsVVuKXjwP2PEGx69TyaV/4JeO7vGH4/Cbd6Eq7Tj42Agg0XLrDgAZpboyEw2ocf7NN8HezBD/dpzg/ZWJN53+nDddhz63RR9OeAtS4pt1YbWhNUf8rrTuWLMeCsD5PGON+I5oq8MQrwThy3fzs6SlCac4GRKezAasDJ3DPQuozp7vAepFBqxPCGkA58Q7G6wgUywCSPSyamCI/Kpkgg9rr0+Gmep3gUJTQPUa1RBMElXtWQIcNOL8Bhtm8KofF1pBKIbG1jlY1zofpNbQSpwIBaVackouruFvzWdbiZObp/XdM+exzzcar0mgDjeWMUpAK6roB6a/L79jUwSBiJdcYgSZWVhcTlPYniV4ZuYzw4MZymeGGWYaqfFVyTtUzGVbxTyUlkL8CmnnCcNDxKE4wmGRtLwmqqoEMKVgJaNkygbr4XGlI6UmJO2bxGwA734tQOy0pON03WMU4MBYX9RXFn9vsTRZ5DQez8tQUY0md3hYnd1ZzrOcB4c2psuU6XyDV3vwO+ruGvXYR/7Rz8iz+nubtwjOJlM4twPTII/OYGeZE3N2hddPoES3Z6dM7iKopWV+FJQjhgDG0XvwudUkksf5JssbG7CMRzyd+vs+mG1rcWK7wd29FTgrYVZUiyrkZhQUcxJUlpYE/GIcRNbDxFF5/1CNgaVxaqgf/kPgUvBvXwbF4ZwnVcaVIteGXYwLcoujHmIgwEhHBd741ysAtKFqLAPWItN6F/MibiVYyGyAkUcmgChR0A7aDe7UGUjDMhQjpuFFvzMPCXKKAxIXsL8E5OqEorOwzd+AAvi5erO13UgDekiVYHKGcMaYLHNqrpad6XzB9LJoryEjOKEqC+jLzZhNlnjDEWnqI8Wm1S7J49Nwv7S3wuTZGI4qZIGLMGncgRu9K/lZRTBw+kKLlyUIGwZRcAJ3FugZFdKHwtil7+lrWWS+6XVpThK88KXT1+k7LkAK/J/wzxjobw+ztksDkH1+3DzS7AzS0CTQ3fmwO2bwC7m7RPom/gF1ep2PfqKRTLJ+jxs/m+NgTgQh8LeeeCYIicMLJCWN4yllkyWPoujNHyRrR2f7w4xBFvR1MJWgKKhfnsAhfWXqsbxxvEQ6mrsIBFKXb6wZOsBkGANoBCk+KNWWUoSibn8Ulema+Bqg6LwTkj+31YUFnGKcavO+0770lw6jqS+xkFJNa4eG4suP0oPLcf7FKS8vZNOu7YOlGqI/KPEbhFgWhz03oUyqNZqKxsE2RrvW0LE4twSEkxAEKumShZBCu8HgJ7kifKxoswViPWa3herQrjEsEgELb11CJok+/R6lFfKqlryx6RTdeR99PUBKlFzXrx5t2n/VXDohj/PoLJMvNP+81KwvN9rUBMdwcp2IOMNl/m++7vhPuIcdgkSlUMCdskxuqKEMtVg7CJDULvqUSeGLjChvQNXFmSF9Oboc83r1HpvME+lWGbX4brz1M+obJpiWxU9BeS2D7g97YoR/Xyi8Bvfgy/dBzu+N3A6l1c7FsMFvaSfU1K2cqBwgGeYXrwWHin8GpgnBr0R5W8UbCQ92jee5YkdgtNSGKTuAtHvN3eSnA0Am5cB5aXGQpqAvQiHkFRUg1OmWRAUHZNDexvGeGRekwG+pmaY5aQKCamRwDiIcmvZMEiJHjrghd4riQrWsgB4h1KEnCLK4HACAgR0Fp4GdC9A3NNFIoD9UEEZjXkX32AQIf7kDicm12kUxaP0XVEiGkNU4fIsKiG456JHVcRmAIX2kUp8G6rzQSMJnghItwjL7mhcSs7gUUoifyNsG4RXz8nRMY8KuOVCjHEAbqHZWPOn5ibyF6jwtzOCN7MsZOapJ3YeGnD/StaQG8ujKFnI0DIDEAcQxwzAjx7sPuhDzbemoNDc3CxTcUReBMwIQpGDXg9ekVcuAxcXQFDZkfubMLv3qT3XxRwPab3zy7SjvZtqg5FeWclvd/ZJbi5Y3BK9HHxu47ivgYBMDV63cw8XP9tBJuORvDXXwWuXkDzPCfpr52BO3EG6M4QFUahfTY2Nf4fSGJkOPNatrLHzsFJAIhVina+3qoCfBNBntPaba0E/b/734Bnfw78d58CXJJA3dQgQQjWUUb5SNDZFaEWpixUhSQLHp1kclqBYWMddraKcLT7c6niFWHZxOdLsn3ZCjVKZeGK5ynxN0lnEKan9Fs2Ds1BGe1e2JF7tG8WYx3LLBHGoxH87k2CfGYXiZ7d6QGrq3AK/zVhIct4pBVD1PvOvEAhZIjRoHE7FtjVkO6Zbkmk9254rLv0kiuBWtl7rSXuK97XAbCqn/hH/nM1gMSiL0PfrCdkWaW643kC++Zigjavz46nloKrTUUU2z+GPPd3ePwRFJySaXj80oox4UYYV2hNPCyiLFSBe2ghdc9KlKFyL/cc7Ya1t78DbG3A7+/C72wSBLlzg+7d7QEziwRR9ufhZuaBxWMBguRdDZzENEUxNzVVixHllhqpFqZUY6CMvSxdm8l5cHDtNhVsWLub2aYb8K9dQPPsf2S26d1wJ+8F5haDPBKkx/mwHlxJ15d5rCxgGXKRK/I7JvyeztMD5rhA/LlC42/SdnunSIxG8JcuwPdbZIEJi8lN2h7H/DwMKUU8RHuOklJMEN8G7u091dKaMtmscmxGgbAiLVUUtilxoIDuepHmtU26ZzVkaLGEbyr4nU1ip3V7wPYmLcHeLFnY6fPaDTgj2Bfs7SWCW8ZEk9JlDBMP+tDNem23Cv9YISFeUxkEleTgqbFTQQtRqxczTKrowCh6o3BzMbQcNGi/l5igb0JSvo09KXkoY3zd0jDIdRzPISjMqH1vdcIeilXFBo7xIp0LnpudA00Dv78Nv3UN2Nmi+q4LK3BrdxOTcvMaoTgzc5S3Jx4+G4zOojhFAUVINJbLc2fs/YuXx+fZ3S6s0RqRS3LvQQwpWdeZuarxvODVU5L+BSLObF0Hlk/AnXoL3OIa7I4LkUdtlWAkR5zpvyXxND8AACAASURBVFl7WfbyIeZB0WLi223t97yudjRTJNptuLvPMtmwpo06r7xCOmN5Ha43CxcJPCM4RaDoQnNmwTWhMHGdTn6x5DgWAISFpo1/rwbGUi84xcKFBWR/OkeeWqujibKQILoewxNf4w+AJuzLs4wGpITkWhll6KshcO1V2tC0KKkAsW/g6wZudhlubQFOK6o0ploKK8+aC2VHhoAhZWTtKrbUvYuN3LF2GAWXjrdpNr6VMxqklqowP1PIsmmAZj8cb6uuSNPC7KY4uiooT88mHqp8psXFWfHkYoK+ydfejGJpCWQZwWcWHvPjqMLI7EwiXjQ9dPDAAcB7+q0aUnGCAXtqwz0qtVWUcDMLcIsrwO42/I0r8LtbRIrqzQDzK1Tnc2YhdNU5OBQEH84tUT9LzuMsjWGgSEmdh5Jl3Gy9XosSCOO4mhC+sMrNxtKsoeEbhCpQ4PeVnGe9fTigcAE2vettobbppZfR/PIHZEyefivc8gnK9dN1bAzslAiVGlnyXu3PHKPatjuQ54Ht9laCprmipM04l9fh93eI7vzqb+Fn5mnrlZkFmnjiaVlCABAW3Zj1bqC8lEiTa6pkgUCy4evWVmnYBTCBNBMuyoqjiJmHqk1cfH0g5GCVLfiiTUnC116Fv3GFBNvScbil41RZo9uH681RHpXstQcES1QUctSlJv49uxCNRyTs18akHNgKM5LAL4tfiptbpaYVb8z1IyMHhgxSBPq/wGNNndRSFeGXWtL8txJVXHj3Dqb8l2fiSCd48nJ+XQca/1gTAWdJKTYmyIZYOpaTEAtNyE/up2QsGhdfc3pLI0ZgRe94b5uo/1vXVBi7To+II7NL5K3157jrDZwklLfawNJxFIuroe9lO9T6HOyFdw0wOcQ8Sy5mKl6gxHJtvEygZGWPTsmjdSWHOni8G+NBKunEokEAVXWR33luSO6iMmDNfaQpOzV859pdIs8cvxveN8DmNfiNVyknsRrCnXorVUbqzbII8tS/sdi0S34iNnai44xibHcPRoTuNAC4zeHQA5p6hxsXSYCunKRk2FYneHoRw048Q1vurEkWkBzLKQYKmWagwagz3pTZAqIVJQQYiSPa+KPQ7G1+WXqPJMDv5bNJzcLF1hvVhdUEJSJwrHyvdRcTpdExdSYt8Uit88RrdCVZ23b8xdt0zqQKJE1p99zvKJE6sYoF2tRcRhc85Wg8DiJ8TGuO7RBj1ERVYJyJaTJJxElfzXsrpbapIQNJJZWxIgYBOkQ9hG/EgzLwWGH6Aw+/v0e7tg/26G+wzG+1qHzYzHwwGvhdu1Y7wKG2mDyAKH1omidix4n7ooQeNVJMCoPESiNPKDEANC/Q5up6aIELHf/EexKDJ4rTC6yaeloWjhQIMlGeFp68BWhaapsqbLp+L4oT93CpQGtgC/pTQ0l6ESSetDuQ59R2NOHQA5orSmDpBNziGvzuJvz1S/C//hF8bwZu8TiwcAyu2w0LTyqpS7xHKk/Y/fOkGkY1Is/LFVRgQyCmlAlmmG/xgtFOQok5dQYKo4OMkGWL0XoAZUE1EnduApsb8DevAk0DN78Ct7hK8JSzQsU0C8Oo4nfGA5zQnxS2lMRquzO7EI+0CDMTeXwFHrT4+VR4lVwthtmDUT4WP7dl8mlVE0OMAaCM4YOEk3rR9rkac18DYQIYgySFUZuNcXqCj3U8WmE+2FZXQLPD5CZKM/HDXVaCPBdbbWJKjvYoFaU7Q3VXNzfIo1hcJVhy+wbES3XdWRKu/VlKD5g0BpFA99AY4Wg/GIDCVB4zFtKxMWM4dm3w3JJ0l8Icn4xhquisUagEI6O8LCws5d+cnMeGgkK/8u5cMGQlXCKKMTWQ9XoNYvTDrM9cnFLvxZ/05+HuimFTf/7X8NcuAUtr5CUurABli2qbyrNrS4wDCX1MQ6jutInt6HmCskAlP1By3jhtwAOkKK69GrzD5XUqk2QXkjJAbRA+UUbAIa1g2/ga0cJuTHJ+ESBD8Rps8j5bp340oGT4poJ/9UX4V39LgXjZU60/D7tjsz6T3YFe7m0ZnOlu39rtIrBPdZz4p8ZzElJPxAqdNM1EgN7KeBYBWvOHUHLRqZIyYGOXLjyX7gloBFyH8+Vss2OZPo9WOylCH9nT8eJJWA8DMEYTt7oG9ndJEdp6lr0ZiruJ99chjzkwIs3cbPdCaauG440RecuH8bAw8rSYa/SoZRgrmTc27UHyDqU6zKFbokSVEY3YmEzDCmKIqmHHzyhjrp5gGZRjzpOV69r3l3r3GpfPhQIO7xXa5n0D3CTZ5DcuAmUb7u63wS2dMGXVzD06hyDB3WnaJumv21sJ7uwAF84DZ+8JisObxRHRjkVoA7LI/WCXvKYttqQXVqmmpV1cKUYfsUMzkAkQIFWpW6rwpg3+m592EQncZVMdmhpetuBpamLXbVwgIsvqabjl40RwaU8mw0RNN76tuI+lEVRGKOeKPwPQTXRzVXKiTXVNE2jSxtvUIxJPFOH93FKTEw3UlfUAHdPDTQFiqQI0JqT5miLk212OCRovWSC8skV0eRHQ9YjuL4pwbwd+5yb8zk2KFa2eoim4eZUKKLc7Cg+6/gzQmyeYMvTSDs7v0Mz4aMtdywWIX9JNJG2jGsV1QgUOnRj3tJfld2LXgdSfLVphzOphQDkm9pGbxA4tGmEhYa0EJZfy+TmhbFJjHI0pRguhwqwF+07M7ykDXb8/4JmSFsGmgz2402+judPpU2qIxNTvKMFDtaMJh/6f/wfwjz8G/sf/Pv5c85kEmkH8EwCKgmCJ/gL8ibPA9nX465eAq+fgl07ALa0TVKoCWhawj1loWgIJLGfYAvayaWgnnO9KACWQFmbQ67Ki49JsXr6rRsDeFlXEaHeJXbeyjkKZiJImUZF30uJSbZMYYbpbvOxmzrVDZXNh3aOMqe9lCyjM5qfKDB3Fyn9aSyuYCGTVarHXWwFO4kwMtYnCkmcb7iX3EkVloCi9B0PZQGxsRIzdSS0YPrp/23AfGHLl/+2bDEsOyLvao8LJ6M3CHb8bbpl23vZb1+ndzcxTLPr43fz4ZDi4mfkgbCfGBDm5X2BXKRIg3lE9QkyiyQlbn/ksaYIM2BJ4kgMoexpqjmIzDocWYjSZsIGNuaeCOi23p5cy0LesH4G7LbvV5vGp0oH5W7xtJJ5jovA0dp3EljXmaY5RGZKOq0EzprGjJ4PR2eb6czFsev0K/Eu/gL+5QYxuTtBH2ab4rYQh7rRbare3J9g0wPYW0GkbZt6kZqBMJQ2kkxrELL35GrB5FejOwi2uAbMLh5i+1trODakQaEw/rFJ2jmocbt8gpl49QrG4BnT78NWI0j2kBmnqQY5ZntwHYerZqiBCsPFNgFmBkMhtE4dlQR9W0SnTEiCYyC58H8gQImwFqhahKa3VybNwLblItyyaUmM0l9PICf1eak02XApuwNVR2l24uWV6Dzev0iV7swQv9+fycRce/8lzxJlUHEDTM3JeiaQN1KMQM9PCCdOgXwMhivcq5bBcEYok2OUuxpOvcWtwpdwy7RtCtSAlCVXjSEIUH/WJgWTjsBOe1cYYCwkj8DlKwhJDi8dGSUjpmEtfhBhl15ZFkdJmIfkJKAKAMTLNrTbLK+B3TIS/q/DXL8PfuAI3twR38j4qalGURPwr2/m5+iZuR9MTLApgYZF+t0JeikBLVfmoagjMpBRI0qt34jp9uLW74VdOAdsbVCLpysvwyyfgVk7DdfuxVasLxMeT3Xp3WmPUsvcKeDiy9Ac78AOqruG6M3BLa0RRL1pwvuH9w/z0smfxB/zck8p2cVNyAYJ31jQA6iCkBBIVurhAh2kcxCZW237Jcze8rVHaH9+A6iVyH4qS+jUYcU6fgYWdI8/Qpm0I09B7+GaEiNRTlqw0h+RxuhLY36acN9/ArZyE522e3NwSxVerChgOKT1gYQWAg2sZ6E4Ym5MSlUXxRnEniVEn3kZKpLAwqx0fIWBprNJA1rZsmm4O24SfTUProDahAo3l1ogJStq5oFDFOxWPUMMAvL6axNCZNOc0z86sC4FFXcFOrlWWLii4oojXkR13KYFnm1bd4T5FYZIyzCmJWaaeIDBuWAp5xsN4kJmhS8/NKtDDQttirEujsSbC3xptCeUckf42XoV/8RcUOzx5H6U+FQXtS3hHIU5tt7cStE1gO4GV6pHG0KJqH2L1SvymMJRsY426sgQWj8MtrMEPduBvbsD/5sfw/VkKVM+vwAlkosn2OV9A9jzzlKTOlHe/s0PMr5kF8j66MwSn2TQDS6DQ4sbTiCPpgjnMuPF/nn/q380Udmh6gUR4C/QbEYDAwiz1CMRjaIKHKG24C8DBl21SvnvblLhdMWzsPMVxXYHmwvPAtUvEhFw9RazYwpHi7fSoRJf3QH8Bbn6VHrWuyLuWvqAL17EedhGEp7zrkmtyai1WqwCFDFNT/8S4ynkCwiQujHKTcmpSUNx6GFH6QxtKEpkG7fpmPPk+StK2Al5Yqwy9ihfvEXLyJF4NgTqlS06JZ1FZNjF8fB3pyagv2TnG80YVXHKyhTdbbeqTKF/LvI24AXw/nyhNjX2zcSAxTg9Tc7Yen5tpn2zJPCUoTWqTPFwH2PrB6XiMscvpOgSb3m/Yppfgf/1j+KaCO36GEvSLAmj3yaB+kxbKntRubzj0MK1puA4lW6daa5DjULCCmodCUiO0VicJDF9XwI3XyDsc7QMLa3CLq0RXt2w1kyLhqxH89nXK0drbBtodSs+YmQfKcjqEptcyihZg74B3N5B4iUBBagwkex6ql8FCU1MSDDwbeRkOkRXriiR3L/F8LRMwPc8qFYk9wROsI+da6NUlz26b0uRNP3V8QFayjJHCsQkEqHmD/NVEjzk5V7wijZG58LUTpuAEy98KMVvlxMYEW70QxwSSmKDcg+fuRKjOzmdDYrGkJx2LMlzv8GIgzG/APAfPQZ37LMyzJcdYedld6atR7GlGxoWdi8ZLzXfOjIsz3qr1BFnppVBtlIrj42tKCEUhafEMPfJEGfkb5rMJHqCd5x7QeZQS++w6AmLDKHMPZZtuvAo/2qfybWt30fmdHhHpcmvsiLajCYce1HTiiJCvjbdSMMXYsCkt8UUo8JKL5Eq4oqCdqRdXiVl64zL8K7+E783CLVDskJxKA0t5stR0Y1nniOpsF5zkYAnkJl6p5C02DeDLWIDDhTgPQN91Z2MhaptzptxXFeJNUrGlSQWhi2EjXwevwlrP4smUnIJStil1Q4gU9SAct7cJv30d/sZrVCi5ruFOnIFbv5f2eNu+rvd1Lfbo+/NkwYoFn1uwdiwtMaYt3j+ChxDBZzmhFbkq8X3SJHsrmL3ME6P0pRVF8JBsPNS2ugLqbYY3W0AjO7OXmjcYX5eNEOtpWnIGkEmR2IsV6qQYo3gkvqafZSsukOA9OSzIPGvKds4177loQeLF2nWh92mZ+C+/P2usClxqizjoI3lElVwUxrQ7lzhDlDHyQgg0At02TZjHFuaPHwyx4hMkwIW/4wcOPAFvzjnQIOH7RPD4+D2cKxg2XaOz9rbhL70Iv7dNMun4GTWYXXcmNprfRO1oKUFVYCYGI7GtdjcmR9QjihUN98fp1upFmEVv998D4IoC7thpNCungJtX4F97Bf5VrrXoSjjO2cPCKilP9WBM4F0D8S7EmujiQdmVraBYhSxBBwXF6VghDnYOLu0mcTVJONdC0I4FjmyyK4xNAEULvuxyTG8IOCPEBFIWWHF/h7a9GVEuoptfBtol/O42eb6rp6lcFL8XJ2kT1QBulmtNlsxujWCbLo3ZaEBegxAyIqFrFrCvgaqBwotlG3C9YABEJIkJXpWNAcFAVWPBoBSmMwxEiTvnBL5636bVI5gdeDHGgsx5fmMeCTcpnZdrYykADIeqV8hxYUmRaISsw7HYFBosS6qVqtVxfFhnunGxFfbi7ds1J+NixjUX87Njk0ttkXeZI11prLEEpESgMLyldrAYfWndYGWdJxArgHgHEX63kxRa5EkjjMkkAppOUxkrDw1bjMGkkxWosk2BUNt0+wattdXTIb+zP08pGG8ShXh7K8HdXYIYZ2eNMDSLy26pY3epjiBLiccwvKhFh4twLTmHm9/dgr95hTcPBbEJz/weKcCdG5R3KIfrT7nWBOUki0UEjQiPdFIrs5QnvOSkAUHB728hW0JJvBC5dlHAF60gCHwN7Nwkav9gl0gjABUSmJknooj3tCt3UZI1WY3g93eo4HZ/Dlg4jqKUMRXLu6YtcQBognUhil9iVi7E3eoRjVta+FcgWVeGfe6Utu9D/Ehyz5oaYzGgXNOalj4YTSJgnePdSUw+lqZrYFyZAEGAqqfsxmWT9WZsTLDk3K8ctGzjk6L46tSz1YOnP3PcGWTZ1b7JbPIr95G1xMK/aYB6D8DeuIIAEKA9FuLqHUuRglFCjIGB9VlBV8PxNWHXsG9iPaBKy/aZnzX1Bm3MT+cUMEaqkX07vQ9zWYyHNNaajpnGf/kwe1ykCKW/tusJtBopQiQKdLoyBADX6sS1TW9uwL92nsg0S8fh+3M0h2cWGDbNKEQJXdzm7fZWghtXgN1toH+3+VA8rvDnWMtZzXJwJj7k4UjQiCfUeIIPZheJjcWwiZuZB2bmiFm6cw3+ykvAhV/DLxwjPL7TpwumE8dac9ltdlwI0ttj5Tk1LlOHNdJUwICgI19XpLD3dwl2FEUrFU9KzsfrzaJYXKWE3NGQCiW3uQp9u0trrh6F6joAeXPdPi3uVjeurJIyReWevs4z6/RzH2JEWpAZnOPHOY2WXl/zZ9KnSQncLYlpCpwlkLPpzBhZw5HCa/vgdQuEJvNEBWby7oTZGb1KQ6Ky+9YVbaDXNx5km7wvLUJtzq1HQD1JyPnA5nQl0OVr1hXX/szE53IeiM2zlHizbQLJ5xRwjtQhfZOmXtwUYk82lzDxwsZQm7SPiGFfJ0YSYhKQ5DgKCiLQe5T/l3p5qafo4++lD2nuXoQ6GA9wGgwql7Rwu8bFk89vyQBCHja98gqENe3nlmjd9jhNyDlgMIDfeo2io6t33dL9bPvpT3+KD33oQ/jVr36FBx54AF//+tfx8MMPAwC+8Y1v4JOf/CS63S6efvppvPe97wUAvPDCC/jgBz+I7373uygnhX9u5flve2KM7LJuPb2oOTMnLfwl3mD6E5RDtks0ehSOAsuDPbiZJbilVWIgTuyQXeie9lW7cRm4eZVKXklVGkvjFtJC6qHKYmF4xitjzwcBoXGuhpQdPx7liHWJbTqJDcYC3elJiBfnxJYRam9IO9iCzZ6jQiW8w7iIso+PT6vcRNR7AHb/ulvqirzTJL4qxdHFWBHlm43HlUDpzGa3IkBzVkPBlWX4nmnuoSs4JljQGmkqxLBddGPoeMl4lh2gw9540xgG8IR1BpAh1OZnbZpgVKasYIWoDTFG2c8ZJSKGa5Zxaz3T9Lv0+Q7ZcmQcIIxbrtxcSgBLCXcarzQKLwuBWsPBPps5NBt3fePXpa+GFMMfDWl/0YVlYLAPX1e8VZaH39tGsXbmlr3C4XCI+++/H5/4xCfwkY98BF/5ylfw5JNP4vnnn0dRFLjvvvvwwx/+ED/+8Y/xxBNP4Be/+AUA4P3vfz8+9alP4d3vfvct3e/oEmMKjlt0+mExyaKzZIQx6jQLS+cIDhhxPpnkLpUlyZ2igDtxFoUoKYFmdJK7yS+/BFx7BW5+Bf50Ddy4QiWQXjtH3uHCMbh2l6esIyE22qOY2v4OVSgZ7gGDfS5OXRKRZOUkbX+zfZP60iEChGt3ueB3l9hfLbMrhVSTEQs3JcEAZmG58WNcYbY3mgDpChN3lBGUrgzVXxSqTGM6qSV9GHjH80CLZ8zesN7Phb4Jbd/G2eT6diNdiCA+bDMwqHSzYDKHpuTsjZ+TI9H4Okndm0YySb3WpPkmwLb2+hObzGXxqIfA3oQUBhXMlsjSANU+/YsON/CiKIDKMLblc/XyxNMST8+clzYt7dcAETtX0ALul62JWzBaEe2Gwoor8g5llwsmJTkm4kSVokp+702QKzIWHnkFmI5lxDI2ys/5+HPLds5Bzm+4UQqCTVdP09V9Q1tCDXYpr7YoiOQ3M4/m8ksoTpzFX/8HhxdfBP7VvwKWlqZf+zvf+Q6qqsInPvEJOOfw53/+5/iLv/gL/M3f/A3e9a534fTp0zh58iT+6I/+CL/97W8BAN/85jdx+vTpW1aA09rtrwRtE8u33Q1BeU2NkG1hKG6mVUIAEur7O/R5qws3M0NJpgACgUWEWSbhe4Jn6T14Y9IdUlqDXV0U/tolKuItyqk/T0pxdpEIInOLQFWReC0YauxyzUDv+fgVM+/9+B58tkkOl/WclWmKBHbixSakFRFGEdHCBaq5JRXlKqEAJChGRhCJtVx26PhqGAuMdidQ6KXVFVc9YYEkHnREUTdQ1YgFk/RTNjWuU8HuQ8pJZOEbgdM2UOpgL5CuIoJN0soW4NrEUKxT2I8FreQWChlDquVordhMErcQO7zn+Z1RlFbBlm1kUxVsbFEE/Zj3YxRS+myCUhzkdXlPAt25AHcD4+fZKRt5SonBYq+fkl4UFfDJOpXn8Jn3DyiBKfooGft0T8EU9s32NelbzsDUQ83xzo6RPT49r4g/v5VUl1tszhXEjgeIYSoOBByKhRX8u7+8jMf/m3U0DfCVrwA//en06z333HN46KGHYAuDP/TQQ3juuefwvve9DxsbGzh//jx+8pOf4MEHH8TW1hY++9nP4tvf/vYb+lxHSwnaJgK+RQrRVwNgf49iYq+dh7/0Iu2jJrsuLJ+k6iwiDPa3oLEfYfu12hQflD3tZBEMduH3tmMPqCgpMbXTJ6W8eAyuWVFB45yja+1tUYm20YDiNwurQQGr4uV/g92Yog2wVWsWsBJwJo0Le87tHid8mz5LLU+9d2XGkr0qrXwignMa6SRZ8FKsW86tmAkpgkviL+I55BR5Mcub2jIxRix+ILBZnXkGXwPVJO/HKDmpiWmVuFjoUu5NlEJvNt6XUAhYthh4lrloby2wJMOYBW+NJErfsbcytMzQJjxn1hAzStk3VHFHWLt1FTYIBugYm/Cul+FrOBdivAJtWjg0F6uDDxCqrBMp1ZbCobYurPd52FT32CxjaFVjYQV0Z3qpRmS/s0Qri3KUSUxQ7tUAkRIbi5cmHnBujsrY2p8+810ULx87CNF7yhpZfsKfbvIxb2Dz+7vwezs0D8oSvmzj7589iV3muT333MHX2N7exuLiYvTZ4uIitra2UBQFvvzlL+MDH/gAut0unnrqKXz605/Gxz/+cTz77LP4zGc+g06ngyeffBLvfOc7X9ezHFkl6L2n3dSlCvvN16jKy8m3wK3fC3f6rXCy00PZpqkmtP8Bw5ASKyq5Hh9vW6Ne3WhEkMDMPAWV65pTGFhQdmcoBWCMzMKK0DdAbwZYOs41S6/AP/8jyjtcXAuxQ7uodPdpw0orWHn5hjxaSVnILdIUMrZ5VgIZC+tNhGldYby8llFuznFag9llwZIWJCF5InRXxEIeIIWvuZym3qgQaywxQwWywEdisSdCgGHiKM9LafxJ3yxEJUUG2kwhr4bQjU4tBKvnZe7bYo9QWZ+JgmxGwP4oA3MZDyYlmEhsDYDms9lnHu3Rv6ix4aDv1wdPXg/hd5E9H7GXKXlwAt1NhFBtFwSNOKCQucDIkyr/Kfw64busxzfBQ8wZLGNxN6sMeYxS0kt0uBhZdk6k6zExuFLFmUYCDhWz/+dtHqDSjjxnhFbyr/90D//2G33s7QH/5t8cfJ25uTlsbm5Gn21ubmJ+fh4A8Nhjj+Gxxx4DAPzsZz/Dj370I3zuc5/D2bNn8b3vfQ/nzp3D448/jh/84Aev63mOlBKUrUdw7SL8xqsklFdOUnHZ+/4ArqngB/vwVy8AowF8q0PQ48w8/I3X4G9cIQZlp0sMyE6P95Lrht/bXbiZRUoJSEtbMRkliidI0/ghgLFtJEA1QxfX4JsauH4Z/tpF4MorMbNUQ2UGtvINNCFYFpEwQ4FAQ9cKOSIEWRBG3gB7eqiCpVt2jLBvEmvdCOhK9inkmKFd62UJeBYWY2XTDPFDhIZuJFpPoOjzdeyYqpIQUkuiRIBY8MozKXyWtOgz/n0sWT4DQ+Y+O9TOFZPOt0LSKD9yPccNC6vcpjVlPrpg/MjnkYBNFK80m0KAJnydpizYfqVeVWlgXd9gbD9KSdQvGe2QdBA7Du0OgDIYWZacInB+k8xZvWfq9d+CYhHDZ2LI1sCfcn37XXLomCdn44F6z0leoZzK52Y9y9fXvN7fdif++/f/5QouXwa2t4HV1YOv+eCDD+LJJ5+EZ2QMAJ599ll89KMfHbvPxz72MXzxi1/E1atXUdc17rnnHqyvr+PZZ599PY8F4DZXgvV3/gbur/49/H/9fkr6rEcEKbU6lLNWjYDXXiF2ZqcH3+5RYepOD+jPhd8dJXEXq6cQ0aWdi2WAWLARC4yHUISppjpUwDChj2t8KwNZ8HnOe9oB/PT98MN9+M2r8K/8Cr43wztaLNKEsQtn2uLNenGThCR7BfKs9TAOcQBBeEYLDkHo1YNwzlhCsYsJEk0D+AqxQpr8KOPdtV6MPBPfXPdzlLF2gbhjq694INT85D4hFd7Sf0kZSOM+SadFAMvOETV7VdmHk/P5ZyuJaQvEZ9+XzREbg8U8tH6pKxhi5cICQkaR6+XiefJn2eYCEyZNYjQM838Su9S5UJjClkKzObw2ZtdYrz31UmUOTlL0DYUlck3W6vgX47E+GbexJv0VIpyJ3Soaw/2IEuDtfERmrI2CjHJIp4QxsmksbAQKAvIGK79I8QmZqa44b5ZKPvqmYTSMYM1ej/4dpr3nPe9BWZb4whe+gA9/+MN46qmnAACPPvpodNzXvvY1PPLII3j4Rxnt9QAAIABJREFU4YdRVRX29vbwy1/+Eq+88gruu+++1/2ct7USdF/4n+D++v+C/+P/DJhfphSENu8/1mbvrdUhSFFp8QV07zP+jOajCHXj8VjhJMe4guNjCYSknTKfyYKR5No03gG+tO7KLWXRCMZ0vTm4+WPw6xWweZX2O3ztFfiFNbiF1bC7BN04fgZRaC2OzzS5+phWyRvPUhZXyiAt26HaTPqs0kQwRXEYPl9JNonA0/62yJGrK2g1HAsnS56hxD2l6HbEamWlJUZImrCe9fo4Licx4KITIEvvx5PlG1ZqYykJJkViqucngt4SUTwiRqswFRVVgBHeRsCqoSFj6mOvp66DUePFu7Dni2EiwrSJFfCk/kd4nWnNFO9d4Wr7UaJMxcCz5c7SZ7QKwXFZOfUkjYHa6tBhEfxs5siBCsOMU8ootuvWxoHhg8KUikPOJ32XZ2EPWpVnvgtjClCVn/QRGH+WW7UozdHSR8kjRkFOw9yKiY1DnQtRgLfaOp0OnnnmGTz++ON44okn8MADD+CZZ55Bp9PRY65evYrPf/7z+P73vw8AaLVa+NKXvoRHH30UvV4PTz/99O90b9tu7zzBwQC4fh3+2DL81jWqPbm7xYnh25xW0A4luGwZLBGokhAu+U2tTtigsjtD1WB6M3Q/WVidLjGlbqVJ8H9kPMm0KcwFqEACjPdVkHd48wrFOPvzcCunaL9DIaxIxZFc2SOJq1X83JpCkoGiJgnHqL8MP9ocqqnPBqgidAjxSIA9FD43ty2TfQbdwYGb7CdX16xrDcQ21fsyrShBcKzN8TMCU+quAqxg9+P3I8+Vay0+V5TtmIFwiCYeeoq/yTs4lFCPTqTjs/lwieeZ64u8z6gwt4tz/xohquQEsgtrzrJ+0/vIu9XCAj4x9l5vs0YuV4QRw0MMFSlgkaZvHHhpAzlHMVefGG8+HJNbs5HStwoQmX7cmvKLFJ9UQvKe3kt3jtOujkYJtaOZJ9jtAuvrJPdWTgLL61FqhHcg8spgD35vC9jdhN/bpCozRQtYXAP6s0C7x7XyWKA3LKxGQ6oJOpId3ZfhFo8B119Fc+0SKV0us+ZMZRXN2Wu1AyOyZI8TdhLbyZqSE4ylL0zXooDr9ODmluGP30N5h1deon4un4A7dpoq2UxqzoU+SYHwamAEYREnXzcVdbEo2EsxBYV1cSa0cbtI7eK1ScauBdrjLmE5KuRUE2tWFI/1wKRqjH1XvkaIJwLBYk+EgUCNSt7xdO4oLaNlWZZ8ral1OAFobmFGAN1KTHBSs95zqwVIEn3q5cj9tbh0GY6zMeHIs7DPK/dINjZuGnp+UeA5D857GkchZDmGZVMBLs+SyymMnjlHbsmgFLkCAELWEpZqtKlvmRgNMnfMMelmzVHsmtdKIfNI7ivxaOPt2Wo/mkLF3q43Rrn1kicqnCkKMCXWTGle++ZJ6cl66vaB2SVWfO0p/Tha7fZWgmlzLuTDtXuU7lCOqLTZ/JLWIfTwJGR3bsDvblLR5/0d+sx7qpc3s8A/1+n33izF4ryHn1kgsopYp8N9+P1tYDggD2HnJprRIMRg5KdzxutkRTm7SEWme7NE824aaN3PNuXJOd8w8zQE/h0cpVMsn4Qf7dMu07/5R/gZ9g4XjuW9VYFlRSiqVZ96eUxu0YT2aXR/R3R8WzLN3k/uKblvqA1vxRA50vscVADaW4UrMK6JF4UO0mcHKiNr5d+KRe3jn3Y3e9mNYbiP/PUSj0w2Qa0N9GvhbbDxMOYFuSAIdR0Y6FoMH2EGR0qkCHFD8bY0HSJnsKVwaALzpTBqBGdmvL1phA/J77Xkq7Tv0fsWBeMnv+tIIbpg5MFDtwQDfz4G4UtrYkKZfU82lqj3tHFRIY5xX1NPXt5hODn01V7PjsEUzzTy9ioutO+bkHs8sxBKJ75JFJ9tR0sJ2mYVYqtLQqUaAn6f5l2rDRw7BXf8bPTi/WhAHuPOTWB3E831S1RCrRqSIuzP08/eDG2u2puF69O/2BKXe5Mn4wVuEOU4GmhKht+6Bly7TDDr7CLQLckDvfIKsH095FSJl9mfJ+JPdwauQ1abW1qDX1gFdm/CX3mZapYur1MeZKePKEkegBYwFktWrXOz1VTRAjrMsAOMEksWuvdUCHuI8HkUtPcZISIDfouwYHxysK5VEEp8lSFwrS3IfZUNYlNPyPZFBJoKF8dxQV4u6kEnwkfzBQ8q2p0KTf4hKQ9FAbgOot3opTJJ1AoWXKAYmsQwfZPfqih6XuOtT831zLwz56AkobFyaBx+kPmmCjujROV5LdQp1xevZmpsEvn5I0pSim9Xg8x7MuM/LQVIlJOk5Ag0GxlKxgjQx7NGAszzy3tC7BmKseT9wYooNQIyBp8eIfnFo30oUWp2iZCvsh0jLW/SdnSVoCbXskDS/frKYK0OB4AbBtIMQN5dp0fw5tKaekreN8D+NiWI7m2juX4F2P0NTbBuH5hdhltZ53JCJAyd2cHBWShSPpvU72oIt0bbm3iBS5og2PyIvYTdTfjRkJRpXZHH2+mRVzmzQEn8v/4H+FYnbInDG7I6VawdVbLObCA8kR1qt53Sp/BBYAgJSFehCLwyCHgPaHwshalkk1XZS082svU+wHGR98DWu9xLFLP0fYTQ3wi6Ms2DoS0WcgLjybHtThwXaXfpOFEydqf3sT3mAN2iyiEotlwqhPcUy8412Ug39UYib8cq1ynNshlttRpLlhEBaSvoCFEigkMT70S8NYHUx5p5BonNp9+nsJ5u85TxIm3ie9SnSQrUIA+iyGTPQiDkcnomrUSkF9PHsVQQo+zGxj/xmvVjcw+Fj8UjTKVDzjMsont5uWY1pHlU1xzbmwV6c5QX3e68qaDOw7SjowRTmM976O7w0Y4DI8TC0EErnwgZpNUzDEiQDIcHOn1iSGmCtiOba7hPkOruFvy1V6m47OwicOwkrYn9HaCp4DozlP4gu8FTx8cXvWm6AW/B8bqZeYJCbT5X4ml5gT2qIXx/gYhCe5v02fwysLAKeCrujRuvwW/fALau0ThIXLPVJoLQ4hrc4ioZAqMhLUUT+0TZgkthGmGHyvMBiCq3iCdRtoCyR4dIgee6Ji+uZ6qnyDndmTg2Jda6Js7X4W8xHkShqxwSBe6M92GgLVHQVpmI0aFsQxHc/A4kniiVhVIC0YGe4WFbgjKIotEC4DyXcuQomf+yTZd4gA0/RypjBQ4dY58CpEjsgKXdzBgCuSIArY7Z5Hk/uYdpk8ZuTIkmXpcrgbYUKajN+xZjQYgvyftRQk5KjDEKOsdKjhSg8RIPbIni9B5UNs28FGe+4z56awQOdknxlSWFJmaX4cS4t9V57rSxdnsrwZ//HPj5T4E/+a/y39cV4MSCBv2UyWW9A+vNZK3HxIITCjt4l/h+m+KHKychAsV7cBHsvZCPONiDv/A8mptXydvszwHdWbheH+gvEg1ZUhDUs+IFKIn5aX6b1MWEVy/DlVyCq2xHCsrv71AS/sXn4fvzcIvHgWOnUHgPL4JbymPVFXw1BIZD+GuXAFdQ7KA/C3/zaoBqm4Y93I56uq7Fm+J2Zqi+aXeGFzYLpaIgj3tsk2BT5go+zlMDoKScqHK/ZXMaDyMX0ytKNnAMFNb4UAEmHBhfT36OeS2JoNLKMQxTitebrTcrTfrJP/m9oRqaHLgEWssqVTGMEAhHmm5TAmBlGSXFwyiejKcB5BVa4aCiw46/lClU2HhIeaNqpAERDPlGEIbEy9Yttcw9fB3KzkmzKIYkpCvUadCCHDHGFXROVCwC9CwRomENB9smeIS51jQgspzpAxCAztE+cRhGA95AoAcsr3OosTi42P2dpu32VoI/+D7w3e9OVoJAsNycETaW2l8geAbKOGwCjCrWVsGxxdbhhswBvFOz9MMD/RHh8Rxb87ubwOYGmhuXaHPgpibYoj9LynFmnmDN3hxBq0UHSv+vhXRj4JN2l2HP/MR3vVm4U/fDr98H3HyNqutcfhF+cQ1ubolih+029btp4LzxrAzU6FZOAivr9FhaU3KkcKCXuNtoAH/lFfhqRIXBl08AezfhL76AZnODhGWnD8wv0/e9WS6TVgKjKigdFlpBTIsAZ2WnhAtrkWeEd1MDQ5vDZoSR5uLVgK2AYo9RVuvIfJ4TZk2s3MeOsbBlYlzJs6nynyY4GbaU41K4d1L9Uo1FmdhglOqAQJSwcKjE+FJo0N5PN0me0G41raEweYBjXp8fNwgck1xKRk8iYpYYkUVyDWsos6yQ9KACDNuz52zvE5GCEpjXHjfm4R52DGgeeoDHljftLkpaN/15YP4YdHXkis7faQe22ztPEAgLX6oZKAPLCkqEz1ThJZi4YPuHGQ4rRNLr2b+dI09DUwGS2IFej+BBz0Fsv7cN7G2Rktzd5F0m5tgTWyDPsd0Hen24sgsVBkLEmVjY14wZb6zr93eImLN5la69fIJqlnpvmHIyftLtzBiVnZCPKfewUK8YFvUQOuWamnZkGA2pwPmIC3o3FXzRhut04eZXKMbpAOxuUz7ocA8YDugRTWEEN7tA8Q/ZN687Q56preRRVcBoN/+excN3hYlXuvFUDe8DOUbnQzGuSOx1RVmlJJA3rAUjRftUtgKsJ96obAEkz5H2w8KWyhpFjEIcxpMZ654bH3PxVgSmHYszTrqHNV4KmnsmRDHx3DRnL2Jsynpt8udG8fLUyHKMLiAzprc+Vnq0eLOND7HboiCkR8aylRgrd9rEdjTzBAFVIJBd28cIMYau7hEm/tjWMQiCQyq3KIbuw7m6G3kFuAZabFqZeT6zEGwTb1TgWP6sqSnu2JujCgxK3XbwVQXs3ITfuQHsbaHZ2iD8f39XSTBudpHSIrozgBPiS6KUbEyISSiuvwDXm4VfOQlsX4N/7Rxw8TfwS8fhlk7QrvHSbZtvFY2Nz5e3CgMbxqMoWSl5oCk1tiVgj15b8wopXcRzYW83u0AKWp6pGpLhsLsFf5m9zoUVuJV1+Msvwl94gY5pt9m7adHY9Gfhlk4QqakaBliNrX2ClZg2L7mUosikoLbAVZa0IakGaYynqgwa8ToVoPXiVKEayFG8J5nHALRKkrx/+25EwEe5gvxcdS6+5xClFJh3G8Gh1ciUWTMojGUij0HMNt4IznVs01rTHU/M+DUN0Ng0GvmuCDmv4u1JSTyfU5TGiM31dcxbZHki1WC0wo2gTKkcECMyryAjxScx21aHrlVy2MWiA5LLd8fre93t9leCaSsKoGDShsb4uCKFVWwpjVrp/g1XL+HFqx5fQtJQIVDFn4tSE7q4tdJS70j/Np6RjW3wInEAeX1SuUYWTuMJ3tvjPMeLL6DZ3wZ8A7d2N8GWdQ0/3CM105sl1iuAsBO5dL0gaGX+WKhZ+uKzVLN0YZXyGYVkFFG7rWUtyjBTq1TH0IekbSEgiJCxY9zuRd6XEy9XWIpNTdZ3QbRvt7gWBBXfxx07Tcq9aQhKGtGehZ6NAX/9Mt17/hhcfxb+4m/gL79E4yKbHs8tATPzCon5vS1gsEvjqWkrXGlIkveBMNc0BSWFWGVcrIfkOCbYglLb5VpSuEA9EX5WMe5sCTaZR1MyC8yLj5W4toKfi1NkKt5pQ43HJpwvkPSBcKiZ6/JcstehlilM+jGNVCREJFmH3o5nhnnqCnquwsgAm1YSoRyy7uU7+dwYYGMMTvt97tnTT4xXORpSGECMFxQ8tPYeLlxHkAjd7uqOMvxd29FTgraJ9a6EAU7Utt/ZhGKxbIsmwFaaQJwJhst1rGcCGAWY4POqNEwfrWJU2rXALWZBSuKuWJPewxWecxXnkkt6EvrbN+Cbhog5/Tn4zatorl0CRgMi5fRm4XpzlHPY7hKbDI5ih90Z+JVTwM51KtN29Rz84gm45RN0vUgBcr8aT2OZ21g3V95JPRqPqFxZlIKRvE99BUYIjSUWy3dcnb4s6Rn7jtisIjgV8qX+utNvBU6/1bBrudDB5galyHRmQpyW0xn89nX4zQ3gxlVgfgnFmXcA3qO5ehGuGvFWXZSe4xaOMcO1DsxNz0aOGFCCJLiC0A2t3yhjYPPCfFC6U1sKyZm/x3LMzDiKMaOwnFk76Zwfu5+8iyn3z6ExE/sv17N9t4acMcSAoPBgIE951tqOmVNUhCdxIKNF6S4FxRkV7TFsXABxcXUfn8dzUj+ta6DhVB9J8ej0DIktUXxiqORySyve19KmtNxJf7ildvvHBHPNeoDCkhOPr3A8CYVanmGP2QK48tPCI01FOYbWGo+C7GlLhHVqVY4dbu5rrfu0KgpgLHKJ3zTBq7Llj3wDX5napfu78Ddfo3jg7iY9U3+eyCldEfaL9JlzFDu8cZlih71ZuIU1qlk6LebhHLScmQiwkmt0OoeQ22WhIo6vCLwksK7U60wFoY6vDwo59TgOagJpOyQKpwzj2+kFOFQ2i0UQSl76IXOvKIHRPinIwb7ON+8KFKungbJE8/IviT28dJyq/8xzjmldwW9dp+ctCtpkeXYxpPq0uXat94jKvWm/WVG2u+Qp2BjYSFIkTPytlHgXH3OQYppkrNk5B5hUGasMgYnzJX8z41Wn8dTU+Dns9VqBIewzuZ3KBJVaok2yrq0H7jFu4GV6JdB9U7PxTc+UVVdpXFZ/F6/bKkS7FnhdyZq5owyjNkl/HR0lqNVARtDkeJcoJ6swIkjPQ3OJFLozHk5k/SVtzCMyytLCHekw2wkNMPtUYnjsocgCTfsu11XmnA/CpuyMe6Bpk9hgNVJF70f7wO4W/HCfFOTeFrB7k5Rmb448R65So7U9R8MAG/ZmudakeFkI/ZTnkTxN24R4cYAwyTc73ogNGlsGynqWVcWQ3QQPRrc/OoAYM9w3lHwDSWYFvUvQhtBP733YoqgaEbu2P0tMXU/emN/bIq++rlAcP0PkoAvP83O24VZPw63dRSQjOKDbS7xpxwKX30WWscjHiTfE146Khtsi53qKEdKTmsbP7HEuGBZcejBbAzV/weAdGfh7LAYHhxCbm3BNNTglLlrH683eT4huMj42/GGad8bQtqiDplXlHollRlrYQWSYzEX73BPHiL9Lt8N6k7ejSYz5278FvvcfgU/8+fh3QnXXZiaMF/gtUV6tNiKhHVXpcCb3RhLpb8HSYoFGSeEJ9Cf9jeIp3KeiiEkOskBkRwqprSlK9DAV36V6jirPhiDChdVQ5YbhID8aUCGAwS79vH6JduqQSjn1iDYB7vSoIPnyOop2xxgOXq+VrSDSmMU9UTgbAkquWXKGxh2nEXXMGMu71ThRTYrSNilBVrYYSkv6EfU59VD5szTvjJWNcwVtxNyf4+o47B3Idk1lSQbG4vEwfp1TcMdO0THs3futGxQzLkv4Ky/D7+/SRs3LJ4g8NdxFc+1VKge4v0esWVHuLa5VOzMH151N5hCTlpTwZccNEwzDMghrNQDFMDLIwHAPgN25PjE8JazQ7tJ1FBo2MCR8fl7JPcZIMOz5RmXmJiTLi5GquZCihGK0QbsicVNXBIKQcwirMVFcNk4u3mhWQRqjMoonW2g8fXaEnOcUFbrTonZ7K8F//BHwd3+fV4IApluT/L2dXCrLjOdmrX/JhROr0W6S6/inPUcWUZVLkZD7873LMtS7FK9IYxN1AmHxtYWN5wCtpDLyGMvx0tt5TY1QWKbVDfewJASOVziJOdqEfXAt1AGVkPO7W8D+FvzlF4HLL6GuR+ShcI1T1+3zzzmGQ8UzTCqdiJKXnQjEio3egWUUsoWs1jK/N5cKPmkFeR+FUbZRTqgZW7W4zTUmJrynXn4RCEQeE8gdZn4J7Lq/HXudhSWNyDsviB3rG54zJdDleBKXfXMn30KHiyfnAV+UcOv3kTcoHuZwjwya4T6wtwNsXUdTDWi+9md515Q1+KYi73OH0nWcVhXqhDq6khPL780BzAw9YKxsCgY/ov7im3xCvXp+YOOwjbhyjrlG9Du/8zHiFl/Tkt0sTB9B7LRevSig4T7Nx5LnazkTK77IsDOKmEsr0sfGQ89pQS8GYhOOG0OXpniGvgkGR5rKdKcdETg0hUJ1krnwvZ00UZ4feCI2wStJvS65RuODZWivk/YlA5GMN5eZt5n+6b3NAtB+m4UZWelyLTMOuo1O2oecUp7U5SJOH0khYADN3jZw5WWKHXLcxA/3qBiAA0Or8xRPnFkEZpeIFDAaBEUxdT/BxsSa+HtN6Obzi4IER6rE5Bl0nHxGaE55/laXfgqF3eblaT9cErcy106JDbfUuG/ipYgizxpHgi405K0r5LgXx7ZyuXvWACgKeBQ874V9Cdo1ZUfg8iFVFhoNKZY8vwy3tEZKdvMq/PZNoK6IldzpE8t4diGwQoX6X5SsoO14yibTDE+LMXDQONrnGntGh7D/5DT6bGpIFfCFC9B1XWl5QZlTkeIDwrMo1OkA2YJJ48mGgBNVRxKDrog/iww0uWvGQz+ovQm9w6MJh0qTMkH/L3vvGmvbVaWJfXOttR/ndc99X78AQ1VLcZlYhi6FlpJIvFR/0mq3FNSKSuJPoCME2EKNIqEkEhLiTwkcxKNEaEORX/yISOQoUVQtNYgSiEIRTxeGoigosI3B9r3Xvveec/bZe6+1Zn6M8Y055txrn3OMSTf31p3S9TneZ+215pprrvH4xjfGIMRH0gsFRFYMOCQKOWtVykn0Z3QkFEdQqUZAE/LvM/k4TST/vWmAepKK82Yvo/dCkRRa7N153dzKOpArsFtM5/XXOLJmpVN6tEIz+vgA1ML1DYWnDAB9hyr2wIV7EM+RWXpFvJRLrwV2ziK0S+npOLuB/sXnhJTTKSln85TUKt0+rda1QnYk/Hjl56Eg8175fFS42Nq4NRqE76rkTQOakuAUqO9DCABxohVxHBQN5AaSHxTmNFw6xpzWCaxSmDkYLkYMFja3EfM9OT8iZYGVVaLb89yXjTCnA++NHnjspZrRZBM4e8nNV69dVYiVdIYI022EC3rOwwNJ49m/hvjS84gxImzuSDGE0Rjx6m+kY8vhgSjTMxclNWeyKTC8KnApEL+dlE8zEQif0F/mIYX8d3pjQ2QiD8PqvUTLE9W0HzLKxxu5t8e15P7ysmOIh8C18u+Y5y8AxeMP2bzy/R/xWxlX3jsse0f+Ixu3hhL0I4SU8I5p8hK7pT50brQgLxK7K3D4GBbrVFoPswGvwtf55N9JWCnzd7zCiIBh/VSABkmWBIG4SpMPhXDPfiL9zjyivk0waBZ891BNASmySzirVdC4MOhGrzNA+gl1A5y6gHDqAuL8APHaZeCpJxGnWyLcTl9EpfcQu1YE3WwPuHEV/QtPAe1cGKgXXy0l5mY35NTTbWC6Cet4kTFC3TNY6Y8W0l4o4TUjTuh5vNcNKNuzcqzHWV46zUPIZbI3UMChNDSCu25UOG0jN0LYdovthlAqzpDm5FMYjh3Bzct/5vYbU0SGRtZnr5yTxjRtSfV+NneEcQzAiqcTsu87MYIu3Zue0eG+VEzav6bVgHZFwV6/gvjcL4GD6wLXnr8bcWNHFOuNK0A9QnVaqh6hWyLOZwIfTzfFkFGDMiAglUXUCUd3J4wVArKHGK/10KUxZJVE5UlxfIeyohvpOnmuJd9n9w4OKbTy3B6mHfTqTzh8sfR/ZN4hcCsqQT8s9kQBEVI1CzYYjT0sx8d7gWRzhSrV4/PHsTlplqANpPha5xrC6oZasdgcHOlfLpJvghOIVJAG7QJ57CnmlSZKhmjlPGXGBWNMHibjKYSfogr37IVDmnsJwbF82cDLE6bbogyXh8C15yXV4oWnpWbpqfNSNHxrVwSdf3xdB8z3U1eOeoR49VnEn35H5rmxnfIdJ5tagHwsczRizEkgolKRD1jXKyQOtxZcA2P61rkB0XUp0dw8NbcnWA/28EZKa/C0fYMBq9V5ZuSfwiDyBQe6Vu8BGPSGV+6Hp/T7gfMvDD7AGY/tig1gc7O9sRrrC3ZMDYw0r3L7TDJoNY4Zzk6As3fatWOogK5HOHc3wvm7pDjEbA947ilgPBZUoRkhvvg84tVnETZ2EC68CjFGxCvPIvYdqnN3AdMtxOuXgcN9hDN3AOOptCxrRkoWi6IArR5pv/oOUA545W/bz3l+LraYjg/puJXHEvU8zkgBkCm+oxiwJx2ldziaFAr81hy3RkzQD4NDl8laZ14OoUyvqPwIQaGrJll13LyWsuCYnaViMA8LaYOSoj24zE5o1XWC1ShoLOePFqVTjFYrUY8PlXYlPwE7lOtET8O8p1FKuTCB5iqglJ7S0P1Y8rtbO3+ses9xMUN86Xng2mXx7E6dl+LizSitdT0W5qRn0LYag4qQforXX0hQ2+yGeBcbO+IxnjqLsHXaDJ9ABeMLK5N1uMLePOlrMQBdvhJBdJLrZIaP92aK/cjP6MmvU3IlTEwUoB4nIhMLB0SnwIdiUSRbVVVCYLoWRjCJQAZVe2PDcmCxOqej1qP8nLAm38ciDtqHGlgupJB9VUu5wPlMDK2NbWD/GvobL6LSakHxhWekx+ele4GDG+gvPwN0neyn8SQVrh9NdI/lJess1pmFHtxPG+59KcMUtt7+b6p4X05c++WOlytXfo/HrZ0n6BVfu3SWGIV2SWSh1Ya0gdYKiSp/SUMtsT7SwLM8wWPm6JmZcvIB7zC7eErY9/luZAzG3gX5O5dOcURNwTJH0Dcl9cJCyQoG95onSgUHN2d/72u2k3m2MVWUqWpEBGD/JUm9mM8k7/DMnUKeGLJCyRCll03DJUbEvpVzLGbS/PjgusCoVYVw8dWiaPevIc4PEcZjiS2xUofPE7NXggo9amf5UfKqloduz+j3s+9yaTRebYzGPuWQrRXipWCDE3jFXvEl/04Mh76CYXueDMVynu4dW/F63Pytpq++Ry37gPo9SMhUm+qu1D0FjGhCg2Zd7l4Gmbv9GswHPXLY2XpvR/J2AAAgAElEQVT1yvpO9th8lozJ5VxSitz/o++FjUkDbLIhqMVE2x8149Q+zch8cZVkYwY5VpWeGRhHGQ2/g1HrfVC2LLRV1nT7t1aQ3//+9/Gud70LP/7xj3HffffhC1/4Ah588EEAwJe+9CV88IMfxGQywRe/+EW85S1vAQD87Gc/wzvf+U58/etfR02+xQnGrUmM+Xf/DvirrwL/0/+Qfx6BFYKCf0jB/QwqRGq3mQh3+m7Vg8xIpBfOrLNijr1TfuugDgoFJSNk2H90HmFWaZ/f7yGCgCxQrWZCWNXgsKVUubE0DSq2Pt1LRjYZ8JSrRgpRrxQb8Pfbu6a3/vMOCJx7gnBCgBQA39hGbJeI168i/vJvEDdPIZy9S5Sih3sXh/rcnNLRa4UQJCdusimEC72nSCE7PxBrfes0cHAN/VM/kmbC023JxdtUcs6WQGiBAtMrQLmQE7Rcy9a8XBGSEdZ5YekKPHPdqipf3zKx2d+vh+DKMdRX0KDKkdLhK41jdolklHl+RXyrPJ8Vn2deHQCQiVvAocaOLudUTO/IRsMh3dtiTToDoPfQA727Z3ftGCp57ouZrPlkQ/6unnTwMcEhrzGbkRoxtMvqBmF7F9h2EH5pEIeAyFxOetLtMrFpZ3tAu0BPximbN3dLUZibkp6EySbCZJqQjKZJDGHbg8CR1Zt+F8OHGMZToFV4fXZDSgm+zLFYLPDQQw/hAx/4AN773vfic5/7HB566CH89Kc/RVVV+NCHPoTvfve7+M53voOHH34YP/zhDwEAjzzyCD7xiU+8LAV41Li5leAv/wH42c+POcgLaiouwgoB9jIDOWSRxfli8kDKcxuMA7f/TroR3XH2wpdxp6H74dejE1zFNdflWK3Mz3l29HQz0oNek0pzSY/YK4SYvMUSiss8XTJtFZ5jHFK93DAaI5y9hHj6gniHz/0CeOYniKxKM5q46TtvugryLP06WGd1JWqMpqIg6YnvnEW9cxas2BIPrgGzPfTPPwXMfigGw3QLOH8PqrN3mLeJqikcVC916Rk2ihao1dxHFSBkL3JN4RRQL3mCZOpZdZ04YIy4MmdDHiWLkscWiA0QNa7dHw4rniGPjvt/siE/6f0O7Ql643VBquh7WEH1skCExU1DUvgZtOuPZUzSzbGMjfpVsC4varhOt2BszgAYkWVlDVaXJt1ryTb23m2f1sATVgCEWufgeotaFxRvPLvfI2Fu8g6WC8RuKXma/H8qUo98jaYIG5vCqB1PpdzeSJP2S2TIGa8v34eLiPMDpFqnUVjeL1MRfu1rX0PbtvjABz6AEAIeeeQRfPzjH8dXv/pVvOENb8Ddd9+NO++8E29/+9vx85+LnP/yl7+Mu+++G29605te9qzXjZtbCf5375F/Boe6tAi+PB4WpZLLrGpnPXlvz3/XC/2Va0WsKj89Z93krWWGRgmfUdn6/C92kCccZsr6KJq9Hxp8z/KW/HydIrRzBxVSdYKbLLWkSy/7So6ag7j8mmSx2uL4Yh1CVUk6xc5ZiR1eu4L49N8mZunWrniHJmy5FkiGi48Jr6xRUs4hBGA8QRhfBE5ftL/HvlPG6g1pDByA6tR5YLyB/sqvEPevpyIAUyXnsOJQXK6h4fvBdSkU0GB7oWKsjcny704xLoaMKm+8DcFofF86Uczl36qCneyfLWar+8uQA0LCqvSY0xuBpGSq3MjjT38+b3eQXTo/0C7rU41hyXsXmC9qub1BPGQgGRmcI/MpGStkqox5+VWK1VuBBsZIFW2xsAXv1c/bK7ziRvwKh7BS//M4RRWJFi11/ywXEgq4cSV5on0vdn8I8v5UDTCZIk63JfWkcdyJ4Zllf4p8fwBERISDa/h/f7iLv/s74F/9K2A8PnrOTz75JB544AGnTIEHHngATz75JP7kT/4EV65cwTPPPIPvfe97uP/++3Hjxg189KMfxVe+8pVjVuPljZtbCXKspEXEZA12Gsci8YRWsvXVq/RvTHVwSi6LaQArAjU4RVkmTXtosxxGlInppTKyzoCAix3QDiToe3aY9uUz4o9VHnEWYBk7repkvWbWs4sDRletRE6SzuXXZbyxmsto9+XuMb+xdE0vIAyWDQhbZxF2L8lLfu0FxCvPApefQTx9SbxDWrgZfby4BgctYyP+9Gk9srlFScHYPJVo/fr9GCqE8VSg0tme5Ldd/pVUXmkaIeVsn5Gi2NNNAJXAWRTWTAFYFxOkl+RzVcuka4M765Qi0XWwhPaVc4bhz72H3jRpPY4zrMxmWnfege+sew+y94lelDvRiocWRJATScBS9ut4QzwgBCGiAEVlGCr2iMFyekROOMpwQOyR9VYs9kuusH2OL69d/Brc/5zEjs0nu3LuQINy0si+i0jrcNSZyJJvF8DBTIhnXavvbBTF34yMLRqYb114lgHAT/4u4M1vlsf4138N/PmfH33tvb097O7mjPDd3V3cuHEDVVXhs5/9LN7xjndgMpngsccew4c//GE8/PDDeOKJJ/CRj3wE4/EYjz76KF7/+tefYM3Wj1tDCZYjBO2Dxm7eFPwLIJJQUSuF3OXyecHYd85aC847dNZz9qK4jb4CbRYvts2zcsK7T/MmvZ5CgErZ0jf0+4wj0rI+Ls/HGwvNRNdkDvP8mrHAZiB5gz3sAlj1Pmck0iiIa/rIUaipwCBE6Q0NIysgWd4AMN7MlGoINXDmDoQzdyDuX0O88ivEX/wQcWNbKO1bpxBIuAmMyxWQ1/Iwj8/Z/ENixRpc6Lxj140hAECzK+ceTSWGWNUS+5kfSIPf+QHiC08jtgtJATl9Ef1Lz0vsZLIpFXOmW9qDUC9XN0AzTYUVAE1rOEzzJOMRWN1/ZbI1kKdIsKdilhvH0eel6DjqRp4DkIgeNBZ9uywSi1bgUIeYZAzNWuOfI8c+VWhvgBgTq0ae2+GenK8eaSGKGmim4oF3bR53p6fDeLhHfoj20CAhwYzQddR9b1AsjQP3/+YNwhkpVX4dkx0aUw1r5MBRnw3yFuOa34849ZoRqhoY1zlce8x3PJcyOuW//+ISwCksFsDVq8dfe3t7G9evX88+u379OnZ2xPB829vehre97W0AgB/84Af49re/jY997GO499578Y1vfANPP/003v3ud+Nb3/rW8Rc7YtyaSpCDMYnWdVggNEmlmAlFwCBRNnEtA/++MkWWLF9YZ5YqgFWLl8Py/UKCEPse6Bh7ieka7NBAaLZVAsySBIXmaO/TrqkKc6nKbyS1JRNrlJ0RFIJtxrnHVFruZMnamndOEBT37SFKFvFmrdTFYW5QDJJAOmA+k8teeg3iubuBvSuIl58Bfj2XvMPd8+4lVgHkE+u98vVwsJ8XPeMAIAbtCl+ltaX1TE+j7+Sakw1h/1UX7bnFEIDlUjzDs3cCey+if/6XwP5Lcg56jufuEnp+CMBoA6Hv1ngsSDGeqGsa/Zo74WtKvwKGkvcqTbXwBLDsebXALBdSqTSdpuxQOXPfDsW0Q5WOlZPI/sNAvFqNwshrzR2szNw1OEG9rlB67NfkUCIpZl6P+42F05m75/cFYVpCuJkCDLm37ZENM8b4neA83pjZWnpCpHzA4vOXPQr05nc0QgjolwuEukGc7SHUDcJ0E2980yY+/3nghz8EPvjB489z//3349FHH81g1SeeeALve9/7suNijHj/+9+PT3/607h8+TK6rsNrXvMa3HHHHXjiiSde8f3cekqQ1l27kBeTyox/Wx6mmFZg7l1IgiQqmysQWio3kArWWqHGMn1hnQKyYPc8F/YMrLPihMUgydaLefyE50JUtuYYQJUE82KW6Oc+VSLG1I0aSEp6OXdzr5Py9RAsx0m6aHAO5boRevVMx76s3hKS80gDZR1rr2vl8jvnJBF/cYh47XnEXz4pMY4zd0ieYFlwYKiGqsHaSELex7VityZZ3n2fMCyvE+R5ywpFRSYAnDqH+tQ5+bTVyiiHN6QIwOIQYeccwhnxHOONFxHGk9TKarot0xwsm+a8cl7TxoACRMhJMllT2GMGn0dFCV5ce4UxGtO7YQajN1Ag8apeYbh2KcXZYxSIc7oj8T3LjaWCqVMKBSsiZWzuUaq20zNfkYaOY8NamyLKAkL37n3MDN3S6C3+3xtw/nPLufVcA7hHFdKPbIsOKbHglKdTqNnxv1vl568dGkmtqraUDKPF8f/0T09+lje/+c2o6xqf+tSn8J73vAePPfYYAOCtb31rdtznP/95vPGNb8SDDz6Itm0xm83wox/9CE899RRe97rXveK7uTWUoCmYRYoxyR9WFQiQfjerTpUO26dYLMLH+ZpETz7pnABYTt9QikSWthGS8jJrUYfBoSwO7mDU5cJdj9fUY0svN5ufizMBySI1YTgQw7M8LTc/Y9queVFtTgMpF6uTUllaCJR177KbQxiNEc7fg3j+VcDei4hXfwX85ueIu+cldkhDiLETWvsRIgR9WbMVhXLctGPaQ/yeQbwVUPmq/Qo1d60Iku1dodpzVCPEqkI4NxLv8GAP8cqz6J/7pcCp4ynCpXvlb20r5xtvSGy0fAbVKOV10QDyhk52Dz7mrN4ha6YCroSbq6vq2Zrs5kDYHID1IGT+X3R7uqokhaFvpenw4kCOnW4JjLtzTlNU9DwkGmVEtw5YrtlTK+xod+1MkVa50mZZwbKRL+WDsaCR7tOv3TrUx3/WO0VdvutGWlpzGlN+BbQ6+P79rkYlqVGsnAUg9L1UOALESPkt6o6Ox2M8/vjjePe7340PfehDuO+++/D4449j7Bg1ly9fxic/+Ul885vfBAA0TYPPfOYzeOtb34rpdIovfvGLr/jubu5k+e99F/jJj4F/8c+PPs6TQ0rvxSx+wDZTBi25vw2f/Ji/r/mOt+K8hbnuvN7bjMWxRyqik8ylUGq8fyvf5v7mlXE55zp/UVaWjzCsfcefw1vF7pyVkh6AFDdinl2EI3KE4jzRmKW4cUW8qHN3Sc9EIAm3rP3O0D1p65mMjUoBq+SiukmswujnMrTcLq7sPbG60fqUPibYKXLRplkttPnx4Z7lQ8arv0Z84SmJMW7sSG7lzjkjjISqGVh7vd+sA8eavTxErLHiAt5rOn7/2RG+0IDtvyCwGMMCfu97iNzPhwgDvbq+S58ZWax1xC/n8QFpHwBOiQ2swcoo30+vAAs29nHDEuJpRAXk77R7X0r5taJ0fxt5NDAfoj7HoVtHhV5+z8atmSy/mAOzI6rk2/CwDbAi+AOcpxI0VtWsboCMVahEFbPKwuqmZyyPUNhJhsGW3nPk+Qes0AwiRbJeeR+s58m5M/fIM2aBJCgIFwEuDrh2smkOrFRTOxq5lZpzXqWnqHsBhAiERtIxtB8hixbbGG/IZyRpMGZaj2EwOKIJuTDeQLhwj8QO96+Konj27zXv8Ly09wGQlQ4jjGYEIMJ57rarKtVV9CXXzEvpk7LzXpHBg+5cPlH9cC8J8BXGqk5hsilxRD7nrgUuvArhwqukxdH1K8D1y+if+4UUk77rDxEREa89DwRt0Lt5Sph+AQMoyYDwLBUg4dBQYzX9ppLnG/RcfScMRK7n/EA+H02BzV2ZByF/EmhsWzE1SOF+L/C9l5ZBl7r/+nU5skH3pDsPGbb0bmOfPEEgXSNjWhfv+jq2aGZArDEUynOtwKTu83XfGzKOTzq450gSPKliu4kU4FHj5vYE/aBi8ixKK0XEmA89Pf5bB9Hl1mkeyPbeYu552BhqCMvhLbwsPaKgp2cWa3AKo7D6uHGjMvyoeI+r9dfr8d0ieS+jca4ATNE7ph3jK4BTuGuGt47ZOSB2iVlYs/xc5WBrrG/tEqN4Ruys4I0CXg8oFK7P+6wRZ3sClV57QXL7WLO0cvsje+bufEPVVmw48klW/JzP+BXCVSViYZd1rMYB5mdcanGA0RiYzwRWvX5ZamHe8TqEi69WAs1cCwpsJ2h1PE0KYnkoBhS93hXBnRi5sR4riWlf/rVLrXwilXfMEz/yPo9AXrIcXjjjVI1Ynw4VoEQY7wnS8IB7nkc9n1IG9O4c3hM+Zt7292O85jKtCTHfj0ChAI+CYYfOr+/iy1V6N/m4NT1BPxh78SQYKkQGzEucv27Esq6cwvDeHmMZRgcvlKPBQcVc+haYe9LBkADjy+iuydQFKmx6p77DgwkbEkuUsVkpnf0kXmffaXmmNtHF+1Y+W5I4o1Z4PUrr1RUKp6rV6ndCKXarJecAJKKNEwBdBwQnREzRdhJvYB5c1WgjU+eVljlgJDRwZEn7qtS7Q4QQEc7dhXjmDqkjeu156Whx6rwwS5sRMku+fK4rwyMKmoPa98iYK1bAXZ+rNYgduAZTBxhHpmdu+WfFd6xrg+4nT2wZTRE2TiVvZLyJemNbWKt9J/d//bIkSm+dlrSOH/+1vBNn70J14Z5kaIymCPTSAQeHiocWo3pwMSYPbDRR6r3CnEMGY5kmZHAyZA8247SnfWzc2Ly690g2AZCYqkODhBj1zJk25L0+T2ChQh7y/DyMXoV0/7xORkh6GUZQFq8/xjNfUYAD3zHGexHeuD0A3EpKsBzEtQEXw1lAhJNTeF2XAtU+94pCvh5JaxdLYXDJpUAuuFfgmuj2pN+k+v8UHEA6B+EinoNwjSWo0itUQePnxT53VjKs2OxW+LlzqQDLRCbyzWTXsUN92gjXkPdD5ZoJDF0AerYk9VgeYsy9pt6t4YnINM5DtzULKUZXCgVlFIZQSbWXc3cjzvcRr/4G8ekfI042XVWakM7ZaLwTSPFAFhbgOgx5SIBLDdH5emOMc6u0tBbXlukp1rsQztDo89+NjFOwjpkiUXrsTOnYPi3tinTtwx2vRbx0rxQg37+G+PwvJe64ewHxNz9Hf+VZ8Z4vvgph5xxitwT6KKxNzrdrgfEWUFcIRCZ8nDlyPdlsOiTYPXLu9Mp7YDmTf0PP3ZQn81mjM87GyWCkMWywpu5FrtsQ5G/eWO/2qIN+S/izj/l3y5SpTDEdA4/aYe5vzjbI5APc+2LvWpUMr+oYROj2uIWVIOMMrcYZmhEw2YIJDlqUPm7Al2M0dd5Yn+pNlhAEewyyqoJPmRicT5kiUfzdLNIC9oidMAFXYDUKwZCsVqaBLPRlhxMofmRJ/mrFGn0ceRyP4yQlvXjOzGOO6V5a7yGXMPU6iKxO3mrsYRDqEDRpVHannDnqRry1GBUGlu+Hqka4+GrE8/cANy6nfoenLyGcv1uq/vvhY5NWbABJ+DAWCqQ18Hl4WYPdOq3R4V6uxMs1tWed0gqGhWjhyQ7FnIx80Se2bIwI6ETxTbckeZ/FGCYbCHf9AeLBDeDqr9Ff/pV4iqMp+md+IrL33J0IZy6J0upqYblaDLtOW8GYm+W8VQFWIT1juwcHeVKRZeUN9RjfCHtluH3pYUwrRh3ya2R6i8YhEaESDi2PdWu9Vs+9DO8QMTem/T0zLEIy0G2l97LGraUELReMZcGq9KLEXr0sOAilhiyBs+JjmwspObH8GPKEjhv0eAaZeW4jE4INgMGkVFCZUPXw0THKI0YMJJTlcwjpV3vRKLgIRfqXaqXQsY6qls7oZWV3eybtqmCiAPGCwuerld0bgGSUkDjEXDGmohAaBlY9wa7FiuSl1d4txfPbvYBw9i7E+QzxpecQ//47eUcLhARVloqKnmzVqCeCBFuvyDud19A5ho71isuTo4h2cJ9xEFrnXvXdRSpC3G1SHH49aJgsZ4hsBjw/kLSO6RZw1x8guNqa1R++UdoIvfQ84jN/J3Vft3bRP/23wOIQ4dJrpFjA4lD3yUS+74qcW3yesfHYDhuVVSUoY+yBri+2N5WoeoJcN3qBZsjyHVLIsmwEHLzciIVB6JAH/5n3XrPneZRH+HKH+y5ZyR7KvT1+q3FrKMHYS74cSR4+puZhGPNI1AKmsiFmzkPIorS2Q7p5mfNklOah8/Lnms2ekW30JBVfSCrD0kQOmpxPGLeHvbVH0rCDY6fGFKszOLR2sQxVVJmn0Q0rvIxNiHTPy0OgdXEZD88hKmlHyzNlqRYBttbWTHdr1aKlwG7nyYPq25QrRi/aszWtILpLkPZK1HuWgfcxR6gCwplLiLsXgP0XEZ/7h+GOFivrgAL+5DxG+boOKcZKYcJKySfLQ5hSz9aT1+pTDBchFUfgHBYHWopNUwWqRtdd42X0HDyUG3tEjzgw9jresOcRvCLguzaeCsmGPedij+oP3gB0SymA/ptfIJy5CCxb9D/9NlDVWj4uFQLAZEMMEXtn1YiL9FoJHauSq+oEqTLue6wn6JRqUKOPSs/eXxcWyb5Ho5WhD3Nt82dTErTSA0vn+62UoQst9G16rrfHKxo3txL8888A//f/Bfzv/1v+eUbIsP/kf4+AKEIg8/g8tFU5Kyu6v3sPpszdK+NhrOV5kmTSFcjUzYsloDwJhS8xQl4Obh07dVzn19G2LDbXRotuUxFbq6M6leqiIvWK3BiQ6xSyCoy+VwGsXjALfPedWPWEo7slMO9S2gWv6yvRlB5UGfcyiAupkMI6lqavGpIZKBCm5I7k3UVNQYjP/EQ7WlyQZPcS7hwa3qAgvOvrb/KZ8Tkydpr1ZqQx0SSlblVU4AS328fLGTCY5aKCNFZSmzMEaZLadzKPdiHG08YpUUyLmZzTmiy3q3s9BFjLKAABUSq9nL0E4A671+qP/nPxHPdeAg73pVP74R5weCDFnzdPSU3WzV35ubGNUDeyXky5ITlmGVfnUFVAoEEQk5Iv0yn4VXrwJitoCKphxHh/dAhRSejxYyUmzvP+loN726db0OhcHmrXjGPKJd4ea8fNrQQ3t4CtrYE/+M2wziNzyot4Pz0Hy/GiUPTnVHikZW+4AbixFGh+eCVq+XQk5zgFbEyuKgkdZ63bizoaJyiwbsSiPglcS0XnUxcY47I5NCnG1S2Btk9/o3fFuKhPch5qqmvpCvTSKZgW6e9e0FBoHVX1prwfzo3eRFt41NUIGDV5HM4YuFSEzrCgwlGDImzuIpy+JMxKdrR44SnE0xcRds6KoCYtn8/Xz83m2imMF9JcYpR0gkGhWXzWOy/a57KW1zFBTu9YFTCA6O/dUooqTZPRbuckgXkmKDsprJQYc4p3XZxSvdWgYYow3VIPU/ZEbFupVXpwHfHgOvDC0+hnN2RdmrHkR25sy8/NXSmaPt7QufE94nsywOQluYXoRyC0rO95FdJ72HcAincSjNeXMcOQx+T9/RNdWFmLgeHjx+wkMoi6+J9Ri6wfus4xt5Xhyxm3Tp5gLF5qwk2ETGh9B8CanFph7UIwemuL3sORsCNHcEhHPOYzB8sQvqNFZ9BOlyewm5ANqQII5+X/vo4GTShweZjiomXnhbX36rxas0hj+mmGQZd/xx+7ds3cXNcey0UsBP8QgUROtPr/ZTyVn/ni5b7sXoypjUzJiFUmbDy8oQnqV4GpMCmxcxaBvRhJhOFeWzvPY4ZPvOczqioAzF1UgWllzbDyvCLzAfsO2NMy/xu7kloTopQpy5K7104mrR2VIweLHADihfa9i1sunWAfuAaVAA0rLcEWAWA+U+V4DdhXJTm7LnPY2BaFOt0SiHXzFDDelIa2fO8yQ3Ngj7CQu+3/4A4b2EtHPr91fyvu2yu90rP0SpDK2dAO9y4M7anbynBw3Pp5gsz38d5X76zDbp6/gKFahSppTXbOosziSkxM7rTrgUstyEgqxylAIEuP4Chb/RgD1Qn8rBgAC2hTgPdAO0t/s/UoYTVdm6xbdkSykmsMdiZYmR89EP9iV2mdyvhn16mnGfPz+jQJzgMqCMYbSQFR+bQJcrNuFIwL03vzRAVa7UOkExIsOB8zINyaH+7BmLaFpR/GmwgXthDP3SM1S198Dnj+qdXYIT1nzmOl8AHvRWO4hHAt5YXGkfNysmeoa+fqeUYW/aZHRwZy3QC7F/UOg3hEVQXEkBsV9IKZYsTPjFQzYCwxHurz17hnfBpOCCnO7dONQISkFQ5TCAo3R2BjC2FjCzh3tyjHqpLvHh4gzvaA2XWplHNwXe7D4o2b0vh48xQw2YL1oOR6DcXhvaGF8r3muunPFfZt+trKOSkL6ibtBf4N/P/gvhshfAF/wiEF6P7OfN/byvBE49ZRgkPDBHFML7dnoy3n+oIW3kKthYd9MWnm4WVMOueVELqkhzVE6uiUJToEoRKWLBvTUkkwwZoKg82BLaYXc2VrRbSPW6TyZUe6R8tPdF6QT4T3yo/Flv3LbC2YPMEmqEBXgcu18PGmAM01K7Zn5v3pmvdt6p7uiTE+z9OIMSEp4pK4UnoCPl/RnsUQ0zbqKSpgVxLu4+E+4rXLiE//RPodnr4EbGu/w0jDaigmqOX6gGR4dY0IeuvXWEkRd0vuzhVSNFKJg2Or2vrF5bvSGSGdCt+6kWvYM1aPk6XcLDbtUmkyjyrkwt0La/OwNNbGgt5Bja5ukR+fJcHr3jR0pkPodc9s7kjz43jJrhljL8rxcA+Y7UuO49N/K+/fRJXixpZCq6dSKTrKihLuDIT9neLMdKKTFf69sOpBMT1vK9RPboG7R0BliltWWz8kb9D+fpQyZCWgsfXDvD1Wx62rBOkxtMuUyGuxg1arlUA3L18y3ZSDOUyQTeTbCZ1kUxkEWaRIlPArk9NZJYTflV/yOfjPDEIpjvMjS+h3BJQMVnTWsAlYwsongOysGMEauAdKhEF0MPRIXk6EvAanKTIKHz3HnEZIYdjITeqy9MV90XgoSTHB3WtMFUjWwbejSfJcLEWidxV3kqIP0y2EyVaqWXrlGeA3i9w79EQgQK7JFJ51cKHckO6RypR3rGvpu9cuREFSWUy3hbUZQm6AhcYUSbpnVVqsdsO1WqxJVI+drDmNxdglpTaeJg9veQhrEm0FDBwKEp0hJB/o42wc81M/7yMQeqDnno9JoXIP6LMLVaXKcTu9G6FCjPBuJbgAACAASURBVFFqrM72gNkNxBefQ/zVT2Xtx1OBVjdOCTln65QoTP/u2BI474zvr0eZKB98fiNCeheZegGsvu9rxUpMfywV5NoRk2dYGqq3B4BbTQlagjzLpCmxg/3gzEMLiTlmm7NKG5SCu2y5Qi/SLEHnqQ3FEQfjHgVMaExPJAvarHhvETthSYZclh/EF0QtzLICiV+jrPyUo4E3jCEh5QOaoG+SYOtVAAbkFr/BQ24tbA0cpMaxUkmlSoeb4TA0BowDi/l56NS7wYn0YXmjHvamVV1S8UfTVY+UhhAbG/sGrVRAdSPKbnMH4dyrEA+uicB9+m+l3+HuBSF2rMBs5X0N3T2NuU48xPlMINTRVMqbUVGzxx5TLmyvlvN1wj1j2FYAmrQfGHLwxmRJXCrTQ/gZ17NWQ6hrU94tUZa6hqRD8LkMWaJABrlnhmQB8XsFqUonIALjifRp3D1n3maMlazl7Dri/jXgxd+g//XfA4f7iSW7sZ3ijtNNbc/lFEqJAnnym/dqTWnGwgjnexOwoggz9rNTtlmM8JjB1lK3lWE2bg0lyLSCznkJ/HxQEQES/wIQqSSi27QD34n9arUUn8xrMcECMqNiKZPIV86vgqEjzb38W9EJm/Plubte40c1MNpKcc6Vew9JqNOrqtUz8P3XMnZol3uyRsChxeuu5TsF+GFwscKOjG3KxWCW/okGvTgvPErPsDiW3cyXzlu156d7oe9EKNEQ6FthJlqHDM2pM6+3uI7pZnq76ZjQjBEu3Yt48V5g74pUpXn+l+Id7l4QAetJTb4oQFUh1iNROEwlqGvx9DTuY82DyQK1FImSXeu8ZE8OAmAeO+PeQQ2Hqgb6Sbrv4J57mR/H98HHrXnuvkMGKWf9/pBSPQhjd52ciwxST3rrO8f+HUBHgttT/j6tM4WbY9choBUveucswqlzZpzGvgfmAqnGhZBz+ivPOlLOKYFit04jbO1KkfCqkn57pvyKEAfzDDOF6eeII0bM5Y3d9wkVoV/328oQwM2uBP/t/wL8+38P/K9fcB/G4d8zBiIgOXYlHKheIckJlhRfbBISDdZZq6HSaidrUiT48vkKGf4Frkea4F6549o0P0/SYL5f1UhZuOOULWGxvs29Pr6sng3rBX0IQMN7cpY3U0X6AeWdvpwMjDIWZ/DOmu+Opim4z++TZehjflbPNQKVzxFrHVmkeI4+JcO88h5oT+DdZLdXJcEbkYQcIEK3mci8+hYhtlKz89R5xHYpVVae/lvEzZ28Kk1VKczZAoezpIRHU2DjFFDV0oLoqBzNqoK0p6qTZ0imNJ9ZxgZWFIHr1bVAtzdwwzHtmWaaGKkkPbFSTbtMaxmYjM53MiSUIiOYdfleihDFn611lacQAbBiAsxt9YxLT5Iq31nGZzk/I/2IAg4haCL/pj0XYayqtz3bk7jjwXX0V54RUk7XaqzxtCjVzR1gIqhMsHeY4QgUCu0YhRSjk0dOIZ5UAfphynCspSL/cSrDm1sJvvpe4HWvHfhDSEIpw+71p3kdfvMhHbeuI3W50Xj+DBLUTTnfT8fYV2P+PYuXKSxiTM8uUdlJJGHDVfMS5ql1Ei3yOfvRFekUgLyYi1kuLFcEe0yQTVmhJMY88bqMifC+sjZObj2G6qausOo077BbDr+YVQVUk8RYXB5qjpTz7BAEBo30ZCfJa7V8x0Va9+z2BxRJOTzrcaWouVNGZq13wLLoeameUqjr1NFi7yri87+QqjTbZ0RR0gubSPWcYAZDL6hfMwLCODeSOL9Q5Y1Rm5FLq/EeF3sxerZqyAlRVC72mYNj28M8fh6R9n66YVgZNB9XjV16PmZoFIKYTF8jazVuPw104jCSGj3zwvPiu8FzWix3iB3qkAIgoSsxigFSNwJpb2wDZy7BoNWuA+b7iLN9YHYD/VX1HBeHwljdOQvsnBVFOZaWYYHenIdv1w4HhVIpnjzTbXUQcfhHqgxvnTxBIPdILAk4ppfXqmw4piXjEv7B+zQJX+WjdkLAV1SxYLfzomwUUE1JRPDxwJdrzZWeqodHXtZL4YwGxOQJsHZopQKB7aXKNkAhuBxHJA81q9KBZMGTqMFkfcboqCDtmVT5c3H5eSlZnPdd/u4NlGI9PJvXC/QhJejb+WSQFuFKtxYUmL3CeJaiogKXeZSEvHog0ihTJRrnM2DvRfnH2OH2rsCdWW7mwPBkK+AIz9zfX5W8TLJzl4cpZjcap2dvcGjt9opPqahzEhYRilrLvhmL9QTQnS8xN/QOWe1M7rmY3kkiKxncCF3wUmkmglFuNHOO6dmkeH9ffNd/Ry+Weekyl9hHYKHpHId7Rs7B4b4YOqcvIGyfEaWqMGXgdXwIZIXA9TKg0JOMeqTkpjUhlZt03Pp5goC+0FV6MYAk4Iwd5wWye2FLOIUvr0+U7lotCzUUiwgp57BkXnJ0S7EGM2GrsKzv9+XLPdFKZ9cDg5FifszLXadM8SG96D5GdFJ2aIzKIiyYhN5CJSTVzvUeqsTYtXqm7nkcqjdRubmsXjiTi6ZcQkBqMqvD5+B5UgyZo+ZxOHJFqLSFUrP6LNvlqidCgUeCBPva2XOTvRGZ8kLEYLkApltSJmz7LML5e7BSlebMJYSd8wi1piZUjewz9GnPGuy77nmFtEZA8lzL2BwVXPl5eZ+hSuX5rADFIsXBqzoxRO3cOucYUp4ui3vXI/k8tgPPmx6P/m4pQB661v1svRsBg3cJj2ZpP15ZqUKPjKlSYRaoEtMbsv1QKj3noRkkC4QqAI3GEN11hbE6V+9xTwhUsxvAbA/Y3AF2L6DaPi2KcjQ2nRf+/1KE3RKYLW9ZZViOW0sJloM05HYhQofVP4AU0yvjXlUNQL0fn5w+FLNbp+zKOaykSATHbEPynI6LO1n1DzjFd4QCLOENvuhWQKBzejymQLmfTx9dsjYE/uoLa96EisbUvBdu69AjdZIv5kLhHHus5OedxJvh/NfFFQkxLw48VwVZux4jCdVAoBEVk4DO0j3WDd0LTDPQRP5YNaIgWOVkcQiwssnWGYkTVd6jgHh+p84jbJ5CnN2QvMNf/I3ULCWzFIzlVkBUSJxrXtaPNU9umQwCn9rBBtJcS65FdGtLBjWPMcJUIYDLmGr+oOT4KrjiC7oJPYu0GqVrjKZIBpS3eqLMxzfStr3n0n2YikKCmeU66jP1MV3/u7+OrQuv45SdkVr4/ToZZdl9cy19DDcgVDWw0Uh6xumLdlzk+h6KcgSV4/xAoNRT54WMM91MsgFBodXfwaAyXMc0v0XGrakEudlJsWdsxBLeuwSHNXVSltZJAat50ewz6JuoEg4yj4yfrSMr6MtFBZi9fPpCArBqIZmXER1D1AfV9bz1COYVrGN9eYgujkQYdyoUAwp2aJ0IA+hTsnYI6h03VtbKRt9rJZ2CMch1WdfKKGO7xfxvPkWh7Cru4UbG+jJijIM5fWzHrPWuWD9dZ3Yd9/NZRz4oY74qKAV9c/uJ0PvuRSBUCP55c42GvGkAYTxFuPgqxAuvAvZe0n6Hv0TcvYSwex4hqlfDfolU3otZelaMYda6Z33Mmu2owjgZbUAyfgjfL0s4lMMZQ80ksUuXc7nFeqL7i8XX3VLy2dvzISzu9tBgU10dfQssCqILlahPP4J/x+g5ARlcbnCzGmMefvbP36c5sSBHhFuT4r31582QEffTDz0+hCDKRxsbpz/rs5jtiVKkcuw7YLwhuahbp1K1JZ3XEab60aNvtWpSrexXpwy7dpgAeBONm3v25cisXbXICJkEt1kBVYQAUCVlSCHQ90qucHBI7IDFQMDfW5Ce/sxRa3zrKNYmLV6SA/yLwn8Z1NIBUb3W0TR9txmJh3EUfBGjCrO5wr0jpZrHJDR4jbZQZozTASoUHct1heQyEGchm7SEEF2SsxGEhqriNyMAIyDqPbcLyZEbIsZA41NjxhaBxOotvAkqjTI26ufZuKobXG/rLi/KIsYOOLgh3t7shgihjR1gugOEgOD3FIJTwkdY7jTWQhAyxu45hJ0ziPN9aVGUeYe7CKE452ABcuflmNLv5Dn4+zelXHh6Hg5luIBklcVBgpbpgfas6KNEHCpEsl2jkpysEALSnmdBBUKtbCuV5QPqnvWdQxgj9DHUwZjqgJLk/1eFErXjY/HIYvqXKb0I7/Flxi73dra07rz+/BkjNAhKMBJDN+CcWzMgLpcSb9y/Blz5tZbOA8JogrgtfR4xGtm5LO54khG71Ph5splYu6EGNrZPepZsfP/738e73vUu/PjHP8Z9992HL3zhC3jwwQcBAF/60pfwwQ9+EJPJBF/84hfxlre8BQDws5/9DO985zvx9a9/HfVxbPgTjJtfCfLlK8uRldYkRwBM6HoyRkYuUQVTO/afh0islQvp2NBrOStzPNDehC8Iy4VlsKF+l81QKQR8E1vfhLRvgeUyr8sIJBbfEKmEys97nH5h7B4brLJDeydQ3Vp45cdWTJkgIty2TMfSe2P6Aj9nHLZs5OuHN3T43Pz68Xd6zqVHTQ/SYq9I8LB59Ty2AsaT1eeoHmhsJqIoKBi6pcxv8xRw+g5ZZRounYN9S0IJwkAdW2cYMTeP91c1CFtnELbOInb3Atcvu5ql5xHOXEKYbCCRjmJS2lWlBQMcLG3PpyuWynlOEciK0HN+LUud+We0Jsk9KuGMYzD1pEACymOsqhFhXqZXKNLT9S5UgXxuKxCnvzesKsns/8ufA8fz3F6p0jPP4ojeEy21nlOog8MbfIWHGiHdP7bPIGyfzr+lcfa4d1VijSzMP94QpupkM4Pjj1SOsZe0EFXOgSUo1/XYXDMWiwUeeughfOADH8B73/tefO5zn8NDDz2En/70p6iqCh/60Ifw3e9+F9/5znfw8MMP44c//CEA4JFHHsEnPvGJ34kCBG52JfgXnwf+6q+Az37m6OOCEywW4AaSJaweHOFCT//3ZANTYI44Ybl1zuKjFR0O0//7F8VDcxw+f2txmOZT1SlnkC8qreaq0Sa1AUYAYDmvzLMbIBkMjajnZzzFlC49l6jnL8kyAVYaq1tIj7chJiCJMO0CgOYpEl7xjFLCaFUBd5as1NJD8cQYKjf+vda1qqpkwCy0CbOxfvU7rIrSd7rWnSnniJgYfSRzjDeEkFVNkuDQJHf5HhmWbTJqqFAIExvU7fJTe6c0vLBzjZFDXQNn7xIyzXyG+OKvEX/5ZJ53SCaleVSH6V2wd6JOe5nhAt8OjM+lWzgWqn8MMcGhTGMgy5R7yNpV6ZdoMHVL+VvdwIgxPtWEJCOL2UPzFBk77MT757ot52nvm97JXCus98Ddd8zDCgP/H9Jes/MHDGoOb6TxPKXy8/8fy3lRUZcnd177ijItjqzq1Kcxm1ovaMr1y4iLg8QBmG4JKWdd/V69njz6iLA8lOfRnFylfO1rX0PbtvjABz6AEAIeeeQRfPzjH8dXv/pVvOENb8Ddd9+NO++8E29/+9vx85//HADw5S9/GXfffTfe9KY3nfg6x42bWwne/58Cs4PVzy3WVrnfC8uL1nHsYflSXjFlMT+yy6hAFU6gB4GQ4i7RvWBDG9PiX45hGioVdq27hgpiIBEtzGtSoYXoiD0DL/ZaEocXYE65Ws6ivuSZp3qE8kFU1uzQtdxxZZWVo5LQ4zF/50HR/X4UiWZt4nfI2b7GEOVpI+JQCbfJpggKaEI1sLrH+h7o5wA887JySsQZU1Qa6+DLDFbWZ2U9AnugD5J3eP4exLN3AdevpLzDU+e1Zuk4v08vlCu+I+o99n0eN/SC2dATB5HTQFwc6Hk0vmdQM2CFA0JQz9QpK39cVYvhwBh3pZ4yPeN6BIw2YAUAjOy2MDKSIQA0fI4aK0oHq+9S+XssDw75cStKt3iHTqyUB65ZKmkgf55D97NmhFDJPp5uZfqbNVax/5Lsf1TAdANhspmz7wGEEBBjRDfbx7/5H3fxxBPAn/85cP/9R1/7ySefxAMPPJDeHwAPPPAAnnzySfzJn/wJrly5gmeeeQbf+973cP/99+PGjRv46Ec/iq985Ssnvr+TjJtbCb7pTfKPw3t11sFAFZ3l84Sk2FbYk2RFuqoS9LbMml2mRHYfr6PnRa9iqMB2qykSZfsbQL9H2js3c5/mVKZVkGZuStWdy49mqkn4SErNUh/gLEm3HjQQCO81oxSL6eZ6mZDP21oFadC+VF5lQeSMYees/pX7qPT6dfKA6KmYp6iwGJPgCSsyDYLXtzxRl/+JmD4HgL4X65hr0mp+X11ZXDBQ4TLNpqxcYtV9YtojQFJaHobLujBwhNy7WgdvW6rHMhkuMcoKb+8ibJ9GXBwiXr+M+IzWLD19Edg5g+AVKmOl9gyK+ViMunZEEK4PDRtnGMUIs4ismIO+l23BJvXPHhVSo9sO1mGCXUh4j/SceQ++sIU3TAEldJUe3bpxhPIY/NPJlc3vZsTsx3ol/cpHCEFQmsnGinMblwugGZnyilFIPP/PX9b4i78A9veBf/2vgW9+8+hr7O3tYXd3N/tsd3cXN27cQFVV+OxnP4t3vOMdmEwmeOyxx/DhD38YDz/8MJ544gl85CMfwXg8xqOPPorXv/71r+heb24lWA7z+CrAw8W+DqMJJoXlzAtQBUqmnNGuKSRctZMQkmIYElDlYBV3w/PVkwtQFppTvulm0rwAnU8FiyXG3skSFeZUoLFXiG44lmX3xRghBbWtEZJCD7WL/SDBs4SNTWi689ktOMJLVq7KezYF1ESlNJoMxAYdg5OC0Fcn4X10SyDqvZIlS+XUMlfUnbfvESm026XAnctDKU+2eUogxRK+9nNYzHIvkAn2XBsPoXuP2z/rUVGqD4ARibqlKDrC03ze0RNEkNa61v1bNwibpxBOX8zzDp/7BeLpS1KztBk5JcfnFbDSTNjq8y6TJ+vDAiTKMLYJpNSgoOvNY/QxW787I8Z06rk1MEJb1QCjTTlmMVOvUFMmFocJgqURRIiVkGjdpL07WA3lKMUCrBgEr/T4Ep1Zd/zv8QijMWLfy0z7HlGrNr36VTsSEt8E/sk/Of4829vbuH79evbZ9evXsbOzAwB429vehre97W0AgB/84Af49re/jY997GO499578Y1vfANPP/003v3ud+Nb3/rWK7qfW0sJloOW6lJhksmmfG55chrbspw9JYMsPSvSeSdDxA9eh8rMfu8GrPyAVGleFUjtoVt9QUsCC5AICEZWUKFCIgnraR7XSNOIRBqvpAAxzzYkD611L2xQj4xzYuxxKBXEJ/2bt6yK0PoRRqx4t9Uo5batG/RSWfjAPHE9hz0TZbeWQqbS2Fhdi2LQZqyY3RAm58YOsHNObrls0uznQDjSQ6n+2ssueU61h7bbxCrNijAs3drRc4ryPKoGiCzU4IwUdo7we4eFFegB6bMIUQg7YbqVmKX/8IT0Ozxzh9S4ZIySlYFI+OGesJikMwY5X+7/xSFW0jyih375n5D6efo9ba2bHETqUYWI3PCJfZ4i4Y0wg4x1GFTrwiPmJQLFL+ke8w/yw6L7f4+sDB1PA8luhD88kuOMyrUjDMzXHb8OFfpdDu3KEyYb0ugYNR78Z9v4+teBn/0M+Jf/8vhT3H///Xj00UfNkwSAJ554Au973/uy42KMeP/7349Pf/rTuHz5Mrquw2te8xrccccdeOKJJ17xrdyaStCC+G3yBmhJEmIy4dInBeCp3YTSvBBtnRDyG80LoVK4k+K9jslkLMBFIobwnAa1BWGCkmziX0ySLapGGV4DMKxfl/mB84R6YdPZPapwqN262Dx7FxdzMCzXoKqLLvB98h4YV6RSqZ3SJqRJJUnBS+XOXMSuU8KQzwnzgkwFiO/jlpX0ahDrRua0/6Iov3YuxZE3TwFn7hKSSWbYqAdsnt4aAUUEwnK/+FwVriyLhpd98k4SE+R1/PwMYVg34mDFlzDZQri4hXj+HmD/Rel3+OufIe6elwTs0Ti/jm2PATi0Wyry6YS/RwD4HAEYUzggV/atEpSIrhjMqh4yUYqu1a4WIyX4LFMOcKul9BppHiykJd1by3lS2D4HcognUMbVvPI/krxCxVQoWFP6QyNkW5enzhGeNdfw4xhSzG8/9H0yNvWanMNJaoD9T/+p/DvJePOb34y6rvGpT30K73nPe/DYY48BAN761rdmx33+85/HG9/4Rjz44INo2xaz2Qw/+tGP8NRTT+F1r3vdK73JW0gJUugxXkfvjsFzD994+Md62Dnr3isFe/CF4KeQ4/eiHs+NOARHmgfR5f88S2+0kZQQq5XQoh9tJiXTqgAMtXiTsRdL18eR+K/ttIqHf0nKF1s/o0UPOPiNwqJPcbfyJY0x5ex5mIwKzZS95uNVVYLNvOIPet6iFdHwM/dzoGBepedHIPcoRhPXaV2f60oj5Ziff4gcVPaPs3kUCMCgsIUzmJwCt33mjDPfusp7Fr6Wqze8su/o/i0bATdjjftsIpy+hHhwA/HaC4hP/Vi8w7N3ALsXxTukgbJcpBQcIF2Tx0TkSATfx6V2KhhP5RiDVqGfbySDg/mDtZa3W6inyJSl5QLAPK1F61GTmCfW+2ce4Yyi4HKHyRXgc9Lfq+KZHrcnSkW6AnvTUCoMt5B+TR9TORb7bci4Xes1lh7pEYOoRFZjeZ3i1rG5m57rsbHW4TEej/H444/j3e9+Nz70oQ/hvvvuw+OPP47xeGzHXL58GZ/85CfxTQ0wNk2Dz3zmM3jrW9+K6XSKL37xi7/Vtf24uQtodx1wcABMaOGtuRWz4ikonOXOjWmd1TWuQQFXCnoqLiusTWi0ZGIWm3YoaTYC1pHadyPIlAjfEiB/uZCunS4yYKGeZJSQSjl396Jl5BUnsIfO6QlHQHrBsvtRT5T/Bp8hBVVMRoO9sKvEmBhqEYyzG5q0ru2HNndF+Fs5vGUyPsoYl807aAx0lISDLzXWt+6+ohBpzNNp0nn8nrElCuLVrCum4A2HVskvWdcKIhg+3UIRDN8DsfTc2mV+ry7/NMZeYodXnxUFdPqSMEubUe5Zc/6+egz3bnR7wz//o4bFFZ2hyfWz564QMCFxBMcM1RhgM04cAMY0CbnWTk4w7hjhIO9iH8biWflwRHC/Z/fBR+zPxf93qEt5vvTQ07Mv37vyuPJdHySWFWv8cpXdLTRuzQLa7/pvgcf/T+AXP5XKIOvGinAtlEl+sL40+UcrXsCg4NQ3wNiF6xQSvUh+D7lwD2NniVLg9QmKNWFcWptrRj0Vb9FSHhSeNEZnTNRz9ZCy/nzGDvXsPiTr3HscFnNk8QK3kH2fw0tlvpm/D9a+LGNyJsxbu07kubW/G+b7qTbn2bvF46HSWMzy+x8S1IRumzU9IbluFKrtooCOg67dwh3bJGjP4FqND873k5A2cgwVIHMFdT91upd5vBWLVsVTq6JkusLKUC/D71VXLi8A0jX9rj9EXMyKqjTKLDXPL6b75noETY0gDFzVgmAQavbeHtejbxOsS0JUVPgbUHbzJMWCWRYNffLoWABj4TzBLD6IPJbpEQnufZbb4/EoPL3MYNO97JWa5SYW//h9pt8YksKwxICHWD6ztRAonEHNuTgEho2v13mSt8dNrgT/63cAp3fzOplZIjtjf1WyWLkRyXSrCzJGJmSLuBXhzXaZFKUJhD55JvwZio3XLlNcMlOYcJ5ngAgRvmzd6uY2+BTuZeDLQ5ilGmjsW3TXIGmI3+uWwMx5uFnvNhdLoYXtPQzGbMpqISVkyEo0XoD6WJdvojs09IWPVHjLQ7n2aCLxvVPnAJyDVdg3gogKBCM20aNbJmFd6z7g85/vp3UgvGj3usSqkeM81lJo9l0yfEoIjeSedV0b0s3D4LKInFDjk8PN0CiEMJDHWjm65EXbdZoRwnQbYfdS8g7Z0eLsnQhn75ScMd4bmaBklTaTZJgsZ8BSlXaogVHliDcheYFArsQ4qAy9susXyYulQVE3QDURD79TkhghU8a6WRTekuw7OWdJwBlUaoTrnaLyxrQR44pwgN/L5slHp0SjzCGLJcb1tq1/57mvrZrPbWX3csfNDYcOjcxS65zFVjAFCZ0w5mVB/rJEGWEmpxQBGLHG54mt23xkwflre6WQQR7832KuPtfKcs8cTFQ3yWMYubzGodH3IphYbJv3jkqdiiGoxRkVnHPJfi0JLbReyaIkG5d/43MxGAfD3qU+17g4FFLLUiuejDe0ur2kDYRS6JgRgRzeJlHH7qlycs3du4/5Hjc8XFWuewlhG4ztFCVC8uqYrM74NA0w/0yZI8g96RUYW4B5A8gbK5YTqJ8b+UGPz0qsuc8BxMN9xBd/DVx7Qfodnr6oNUv5PNetlVMcxoylwdclJWXvm0K2bMvE6j0hyGdAql5UK2vZiGOOmDM4FTU6rIlzm+bULRL07Y0Zr7CyUIozPmyd9bjsO6VCVCUXy2MK5ISfm6Krjpc3t8fguDXh0KFhllCVhIAF4luFmxRuMeKJ/y4FdIQkhhPS080/mkBqL7p4HDdx16VNbQnpcfX8FMhlugTnypyp7PxOidPirBpReOyyfZL0CJ8bCGhdSgpvyLpVDj70381iWs7zbEape4AJ22UeM6sbUVidyzlsRuJ9GfGmS4zKdoFYKiNAGLCTTSBop3WzzHWOK8QYnedKLVkvjBSW8rHJoVw+XxDAGK+qsH3dz2zN9di2dVB0GY87osA6val2nid+M65V13k+H73b+UFSLD6GmMH3bn3jEsAynZtr1neQijfyXoW6RrjwasTzrwL2riJe/TXw3D8gnr4D4cwdCNNtGPTIHpi+STK9Tr6LzYYAFFbnVZnOhER9GgXJN9bRRBWDGa6NvNuM9bE6TUsCmR7bqwKkIQEgq2tKY5jPtKohecdUXDReaDwWSo4GkcWxewBq1GTHEbmBU9pVuuZtZfcfZNx6SpDDGG3zZFEyJ65bJJizTU7vOwAAIABJREFUGcMIKn2nQpSwE4VgTBsyRk24jvnLsI4IQEW1jvhgHii9UKiX6nrB8e8+bSJGuQ8roB2Sp1Vai1752bUpDN198jPfWd7YoTEpNU8mQcyT7MtB+LkvYb6Q37Ouc/TeGCGjEGz9As/phURZ7d8KnKuXVJJEfL7iShFx50Uc1dGC68Rz+BZUHib2MPloklI+aFQw4Z8Ki3E1QrJWAQXJ6+D6WNEE/XtJ6GAMzt+fJyd579dX4qndPTOeyhixGl9hNAbOvwrh/KvEO7z6LOLPvy81S8/cqXmHrsMJk9c9IaTcN7w/KjWuGfceFWqtUCaVI6sctQv5vKqB0Bf7XfcuwyO2r8YuPlg7eDkgKwVo3h8N2BqAKkdTcn06r3n8VIZVMpysN2NdKLzbyu4/xrj1lCBJHgy01w0QKyekaK2rMEStVqLGMnr1JjqWXqK13AFWncN5Qz6mYfl3GO7pF52wyZraqqCxDhIhxR2jQrPjTRhsSM+gqiWlwiz33lnga6CgofXK/t95CuYJULDqC23kAUcMyBiuzpOy89WabI+0nirEI+9/eQgcHsj3mpGwOTdPCRHDvte79VsmONg60Kvi4fOkxc+4lRE5quRJ0RCJCs8CyXtdYeD6dSO8F9IzjF0yLEhe8QKOhkr2fcYE1xgTpYfhWYCZx+72K5W+LwZOmNP+XnivfHcY3yOsSo/VlPMSONQ4GyqhbZy9E3H3gniHz/8C+NXfSd7h7kWEsRKzuP+N1DNKRh4RCd/7k14gPcPANXIpEbFLcUSiLLxG42KC9NgtpOEMWg7r9KHPknFDIMXHaZx4wzhUQGjEs7M4sDMqqDR9PPq2wvu9GbeOEjTmmUvopgXrvR0qnbqGNc7sF0DnvT++jI3b5A62oEAlOSITlHody0+EUwqcmhNqpdKZlz0LgVQpxAk5gzN5v84DGBplKkdwlmjU89SNKNWAgh06TqQQxvbMcynKmxnc5QWKCgWtxBNpKLQL6b8335OE2/FESpQN5VhyUAlHnc9ykTxKT7DxRIdQJ4GeJfOroUHCjFU/6ZOR0s5gcSaOIQXINfXxVCoVI1zoelQBUmnECU17Hurpey8TyOPPRDl8TdmslFlcVZpUiITPee8elrd7C0k5lYn+NHZqGh30RhshymycQrj4WsT5gXiHT/0o72hBBIDvKvMfq9optFl+zahwclUpUzQkL9mU5lJJXoqWkGjEYfu2SlAr1BP0XrCHjHvnFbKXYT0qvL8OiK4CkKEwt0kqN8u4+ZWgJ3lkwymEWCgO+R99kaMoQMvXc3lVZE5GAPBeT3kpp1gyptjQwd5TgnoqjC81Yn1WtQpK5F6MD/rHHkApmIvBNj8rRA2FbYwVSMXRQTotqFCua1WQSyAuckEaVIgb09bBdkABV9aIIYiCP9C6nEyS3jmTCjrXtSMlDK2zN0Aci9WUX0ieT3D3GTug6+U5e2PBYC1nQNHDWrl2SfgIGIzdDBFkGNcjnGyO2xExwRoAtHILn5PPhaVin2yl61EBMrWiZcNhb+Dx2iG9D30PREKFtbTDCe6eLC+SKTpVHhc3FugcgHhuoW4kdrjS0eKc5B2ON5wH3Ka1aHQdOjWkiI4gpsR7Ku6qGmDUxhQ64PfaZeEJEuXpc6O5d0qSSFAVkqfN+rdmrIyF6Xo7bndTj5tbCf4fXwb+5m+A//7fHHGQs2zNMtbPO8JXIcE+AAxusjihQm6Ng3AWrqdfgCNKuEodBbvRii3LRWCeAIen0ZfsNlL4Dfb0sbmYjuk1BjWerlcmfOHbRaoH2mqB71Al5ds65W4lrpZAnKf5WbpGSAQIvW7slkWndSatX5TTxqgxt6KiDGFg827Uk1y5DSd4SPTIvC6us1/PQlgFAEZPj+k5+vhrSVDwxCcqKH+8h5ItIVuVFtNxvDe3UO+f3p59X71RzxD0MGipADxqYTVLkQwpxsvWQaFc/4VWZPGxVMLDPsaXwXrOuLAYdhAo+8wlhHN3ar/D5xCf+Qni5qncO6QR0iF5UVXlEAk+01qeGb268YY8P5YdZJ5tv8xhU+8J1o0qfmgIpEuKMfo9BH2fmmTUNo0q1XA0A/v2uGnGza0E/7N/Bpy/kCjSVrGiEN4WzHaB93aR4L8MImuT1U7iDL0LCuiszFdw3tEai3C5yMs5ee9lHXXePFAdVmKNx1UA+qRwW4VmJwolrhvdUsqb0SiwruUqLJj6ATgjgLHOwpOSiRt5JCLI+sxuaPfqZarNuXtJijhTefO5sE1OGSfjPa+MkHsCGVwdkudC8gvhXDNyYrrmEDGGsRvfJWNlCg5ebJyA9fmUgIsDNcnrMfq/N4BcrG2lf6KD2Va8Td3zWTF4N7cynunJOMt5ERflvVWOeFKk9tD7DQ4OpYLlvTajtLcZg9T4YhhvIFy6F/HCPcC1y4jP/zL3DokwxE5CFVWdSGVlrmo9kvsu8wo7ZbmydyHfae8J+ng/jQhfAIC9C/sOqKfpmTSjJDf4rHy93Nvjphw3txK85x75NzSy/B5CinMnwFWAMBHXVxGptTo/Pa7lInkiodKE7tGAkFHKNa9X9gH0cYNQCDYgQYsZY65WUgHS+XxOmC+g3UzkePMQ3WCTVINr3TqU64ZeBaRCdYTSsmR4EcaRMNXCCUurzRn07FEsdU+w4HqR9l7CjZ48UXo0/Ecol94XkJQ2eyPye8u5U8BN7i0TYs7OPU8enI/VASoA6eUVbEB2VFhJMUhrJsci7VGLCboWVZ6NSwJXrZ5QxiSsYUUQPCt2Mcu9WHu+LmZo94o0P7JXa6baBGccMj5J2NrFEVlcfjnL15QGnVPwIVTA7nmEM5fEO3yp8A53zgpK0Or5Wl037hF2eSGTlZ4hkMqodUd5guO0l5hSZPHJJiXXNxNYIW9WB2JN017JV4f7x6cm3R6/1+PmVoJHDebkhWqgo4SziAl1Ej6jYFgCSUHEpPwYQ+o6ILp2Qr0TLj6uRAbn2tqQzovgS05mI+BiMSH1aqMHtzxUi1fhxHbu5jHgba4uEgwatjn1q98x6LNSjw+ypvMDUaz1SGJT022pNBIjrGqHZ9ICSREBCUqm1xuqnKCyMl31QOjpemJMrzR3Xo9ly+jZVnVetqx8DjYnwol12gtdi6w7fLZ+VVJKPHcT0t9CQNbg2dJwYOtp8bVyXr73IxWi74RSwu3lszMl7NaPCr0pId4+eW6xA+oIK8sWmiT8PanGE5+MjFOlfc3cvbHrbkLjRYkmYTxFuHgv4vm7gWtF7PD0RfUOgSylYaT1QZdzNa7qtAZLV12mdt3p2c2FpJxmJOchiauZpO8T/iVDlu9braXa+k6+3y1ve4W3wLh1lSAFJOELVqqfF50WogqpAGfthzyATiu0rMXoIUxTOIC8/AOkFFN66kUQRqLgarRWZkdh1ydIlgJ+OcvjRACygsj+/iOGR3CC3mDiKlc8jq4fm7EIxtkecHBdG85qbc7Tl6TvHuAEExOIaRCEBEVDPU0TlDqP0TEQpF/Dbpm8c+/lGJQbck+LgrsljOjWyH/Xx7i8MqkqUQT03JnUbwqdnlxdQOsuF5GxKIuZUrF1eUww89yiU249Ms8qa1KMdP3Gp2S4+zFyS6uMWMYGHQOa1VnsuBmwKDYR52dwaBSlPmTA9J3CobM0R/MQkd1DCDVw+iLCubukZunV32hHix3paLG5K3B6VzDArUiAxsJZtIH7sBkD04mQb+b7SibakPubz1QZjhKqMJrC8osbJSaxZRPDA83YKV/1+G97hTftuPWUoFd+Fsx3gkgOUhjLQV0knPgO8GVCtrc4PdvPeyAm/HtRuJyThzB9TMdb6p7oYEoKiSzj85PIbltp3FuMZiqpB5x3CRH3S2DpvEedbwwVrH7mwXWZz8Yp4MwdwHRLVAljb4QaeX9WhqtOAt86pHeOPETCAWN4jgHL71oKB3P8inik/SCE6Gjt9PCz+qmqWLIC5ox1quFQj8S7Xluxw+c7upgc0ylseuqlM15sSk2VqEHS62KCajx4ODaLC7pnSsWlzU6zeqfe4GF5Pa73Sv9ChUSp+LnPPPu3hEO5Bu0aD5HrTISACpcK23uH3QIh1KIMz1wCblxGfP4pKZR++qJUpZlswpoHAynuamkfIdUv7RaSe9ooWtFrTNwrw8VhYqay9+BIY4GxF8XGOG4z1lizPgd6mWSN3vYKb7px6yhBxn2M6BGRWcpG/IB4f7GX2I1Zp30inrBaiwmtAfgTcMqsUELr2IzyR1jKhSYbW7pDo8W8eT8eRlu5pt4HnHI1dmcvUNB4ikyAEyL2L6d5VnNE76VGyHym2+L1hUojfFGIL4Cz6mOCm2pnmXsikf3dQXyxTwqsCkBwCnqQJIJ03SyuWsCPtk7l0jtPHOqFkUxCj5XK0JLq9T9DMVaDsnWelUKHNIK4J7PGt8HNn96hn7sqkOz86nH6mqoGwbpn6pmOLKW3YiCFZFwQYfBkor6Tr5BdynmN3DPNyg26/U9lbajIgIfoCTOWcI9VgyD2wiw9d0+ed/gPT6S8w52zCIyjR027mWym2DrRlekWrFtH3egx6gnW9aoyrCqgZahhnBNyWoXdayWjMSfRcivb217hTTZubiUYo9C5+zZXOkMxMG89VyG9dH0PZDUlY6pe4dmQRoBQyCkiBd4rVpPohq1wztWgoZg+47yGKO9ewNQTIMQkrOglMpZWK3U7VKnD/FGj7xAZ11vM5N9yDmztAtMdYDTW2J6PKel/fKI386pCpcQIF4cy2JWJ7Q5e83lq4G1670hHrYxDS2J35BUKWV9FP0v8dh4MY64U1GzZM5hDScLIUoQriSt8ZkOet1e+IQjJxe6R3qebex+F6GLrVCjaqgKqcYoNM5+ubxPBKzOI+uJcFTBST84QAKZ/6HFZ7NWRa4hyDCk6rjdj0wZrw3mIjP8NKU3kx3LusVslQjF+tzhEaEYId7wO8Y7XSUeLF56WqjTsaNFsyLGHe4nYBqTqN+YJthLWCLULkagyHG8k5ixZrta6qQG6edpnDLMYHDpOMUIa0+1tr/BmGDe1Eoxf+LfAt78NPPoxfpJ+qMIKdREf8TESNiplN3d7qbtkrfpqIiFo3tJhEtbMZyLVvGSMAsMpEgASU08ZoF7Qlk2COxcH4fyrRuBOQlvjzXQfgwsWEdsFcHBNhEXXasxE0xgABC9Eq5CEcMZ29QZCD3RDxJuQfhoL1sVQLP2C6xGTsjGqfbGWdZVDmx7epXIY6mxhVPvCKOGz9oSSlRgcrzVwj6Z03bM/idXvFSKVTcSqEidE7+fjCTg8xkg9dTK+MgapG1RMvodf5o25a2SKrk9GXlkw3Jfrmx/k6084umE+bT/MMo29vltzMciYkzvZSn+b78v+3D6DcPpS8g5/+p3cOyQsDKg3prDofF+eE0sN+tqjjLeHOsUFGQsEYBWVjCRDRc0YoRpkUfdKrcSZ0Nz2Cn/Px02tBPFf/Qvgj/4IONxHnM9ks81niPMDeRkPtTDxZAuYbEgsYSzpDWGyIbUpN3aE2EHFx2K6tBwDFCo5cBCZwiRNkYu1IpQLD5UCZKhoroMlE0vUeZMs+FwFINBqb0UhcywPgc4rMfkZFwspTdYtYRVBts+aURDgBSoFLhWdQq6WPkK4tksEnaEegz7Zm/GUtBDOi9HrWaL9gBExNDLPSq8T4OJm/nk4yLIcnhjk4W9TyKNhpZKlazjDyGKZLp5cKhmD1KlwalhcNNO1we2VSVKSa9fDEV983cosHumg3vJvxgAeQDKAoz07KjuWNeN8rIiEg1e9oXm4lzxL9vZkA+mFoiZEA0aTpJxm1xHqkeQdXnotcP1y7h2euQOhGYkB2h/mnqCPG1KpxYjUoknLyVEZ0lgkmlOPZF7shGH3WMtn1SitPxEkllm87RX+3o2bWgmGO+8E7rxTfh/4e+SmPdwHDm8g7l+XF2t+gP7qb5Tiry1nxlNgsokw2QImU2A0QWBpr8lUFKUvim3KbukEIr2QAj5aaW6LJJDaNhFGAHlBxpvyPZ8g3IwldkGYhQQIJhjTUu97xKjKySueZmQQTzByhYupeUjO4jasHeo6gDNdox4BU1cggBa+jy3RC7NmtSo4uoV6PjoH3+R4XR6lTxPo1JP03n0ZB848Wl17nw5gPSadJ8s1IVR6lEIu0zV4XsKvPrd0JW4cnOeosGUJiZbw6XKGtXmLnmxj14PuKW+EKTQ9Hg/fn1dOizkQD3J0wittyyOM7nnE3NDj9wivMneRkOd4QxXNkEIcp2T3Vr04hJT/OZ5aIn6IPbB1GmH3AuLiULzDv/9u8g63zyCwW0ddp7g7iVj1OEGcsUv31pYkGU2NiF4B6l5i/VLjEvSqDDWHt29l3W57hb9346ZWgseNAMhLNRoBzRlp8cLgtdL4I/uPzfaB+Z40bl3OgRtX0c9nGjNTy1GbuIbx1CnNTWC6CTRT5xRGFTYbuaDx+YkmrJUdxzzAGOV6jLfxpEz+NcWmAohpDBRSXrEGCPQz2RIlTi/PILYOWDKdQa/FY6jAYkzVRVirMlQJysvIFHUSMr58mJWLU6t+ur0q8L3nQBJSGR/0TzZrMOogwnWQpGdR0lOn10O2LRXJsvDqhtIfsnV0vwPOC2dqi+4J39zZYnOFAWK3GJJHxmdLI6NtgVjkLVLBhUq8sbCRDATev1XSWQD9LN1XBr92aT+yfBnTMmJICnil7JpnqOr7Yp0sRsmTomdFpcZjRtP1CrGZpL8xxscwhcGlC+BwH6GqEC6+Zr13WDcJBm6c8lto7mClsb22dSQZlzzfKbpDEhIVI6vQUL7QG2QIwJvpt73C36tx6ypBi7XEZL154RYC0EeE2MpLeOosgHOptJcjhEQK86VQyuP8UJTj3kvor/xKAusLpYZPppJCMNkSRTmeIowmIpjoXRIKjD1SE9iYICarhEEvCGJR9voyqScaGX9YKBQcoyigjR2xjH3rIjnx6jpRMbfzpBisSojzLBinZFFxUwwuBcDirYzv0NIeJcuX5yljcLwO1wJI5/QVSLzSYXUeL8wrd5+m9AiXMj41BuoNJ/yL9aBn3zGVoYRzda4GVY6AhrCqUzzrhodSy1qpXP8QkVWe4b4IlcLwbNMVU0yOrN5YeIuZcqVxA1hh8eye6vUVkYb6J7LeKdfVlF2XvD/uAR5Xj4A4zY8hrH6cQhxNgTENWYVM60aNq4nFJkPXShuuU+fFO3zx17l3uLUrxxhpZiPNpa7l3e07TZ4fJWUZglyL1YLY9inGFAf03iDzfukNMiXktlf4ezNuPSXIjc1iwcz983R+i32IIkwxo5D+NpoaMSAA8t2pxEQCCSKO4BKpTBaiEOPiUJTjwXX0y0NRkqzZOd4AxhPxIkeSxxeYfD7dRmBPNGNBiqCKtBrnMyG3LGbagmgKnDovlflP+kIRpmK5M/sOobrgvAIkj4Vr1Duvlkno65iTZXkxBIFCe8CEBT0ZkjtOQjIpcx67pYOkeTsq9D0kbUSPNvfmVsgnla7FKDdILLeRZKFF7i0Szg0DCjFGNz1eBzqXDih7VjIueRT5xjsTlhS/TAaLXY4edC25o36OZYx1Nk8GiJFtKhhj1XvWHp738cS6ATAtvMRZUtCs4DR2CnE5B/qDEyrEDVWIy0SKsrDF1K4XEKX578V7gRtXVr1DBHmnqsqRZBwUylQXroWlTKgy7PvkDXI9WaGqp5wYQjXiba/w92DcOkqw7+QFI5RD+AhABkUASViHIHGdPiSPjPGjFfjRDVr/VFBVjUDB2YyA7bPihRWxkbicy0usqQlxoTlk+9dSjLKAXjGeSrpCVYlnMhpLjGPrtCg+37nhJMrPl5viMIufsU7Auh4wHWSIQVmuJ4W6fKifO8VHOIwMU6twUkB3Jx2cF709QrImTBwEuEKMcbFEKrpqjeJaGTWyhHnvPfYKMfvydeU68br07EYNVuBLID/nEPkmQxRi2o/GiG0AUMl6wlY37C1aE95JruRoLAUk5WVznyQYv1RkXoFmkKj3EqPzJJX8kl13lq7pYdFSIY43Zc0y6F2rNunnYTEDNrYR7n094nKx6h1unkLoHHrBLhYkbgHqAVfJw4t9QY7ROKBngLNAAcMLbPTM8AOq217hf8RxcyvBvgeuXwPGxN051sWS9HMy85g0T2Yb2XBGxOiwUrcTUBbmMt+sVrJpQBm1S2BxIKqYL/rGDgKcQNN/MQJxdh146Xl5yWd7UmSYntt8BjzzU+nPN9mUuORU2K+YbAnrdbolnxMONSizZPShgMr0vgmTlXE2Hzsj89XndnniCVmhFOI+TYVdvftWqtVUy+R5rXSG8I+vT7lyZT9BT4zpu3QeGiL++l5h9H2CZ+36Pt54hEfq2cBWBaZkXw4ZYMHNx91reSzTVEINVHp+Ix91A8cqi/S4dA0Pn5JJ6uOjK3HQUim6HELvvfMn77Osd8pk/3qkBdZdkXpf9JuQKd+3svOFQa9UmIVCnGzJXtD3Dp7trfHDEDuEc3cjXng1cOOqeIeLmXqHlyRHlsnzhDzp3YUqGVXNgDcYIcY1YVAfx4+dQqMRVg2JRLtbwCuMMaLrOjTNzaNabp6ZDo2/+LzkCf7PHyv+ELAiUClMCFXQy/O5dZartEiberot52OSLYXPkPAHnKVLJdC6aVXIoCUVVJHxyhtXgINrCO1Srnv6tcBkCxXnVddAM0YMSsXWAtaWHvLS8+jJePWs1/FUoFL/uynKca7ohgSyZ3VaIXKXO2m5Z12yjpk3eZSXmikR/bds0+98loNGTcjX8SjlOTTWsXV7p2wsXSXka+I9YX9tCsijYoMr19ECA1TCmedIkhIVIaHRwth6uekabEMFZyQN5S2WTNSMHORjp3yf4BSd8+6Ak8UTPTuVNX6pEOnR2d9JrKGXuUYhjlUh8jv2+QToOoR2Id7ha/4IcblEfOk3iH//veQdNmOEVsMpI6ZJLGC5wawfa96gixMaNOrTJQiNFu8XPfqb2Ct8/vnn8cd//Md49tln8bnPfQ7vete7/mNP6UTj5laC/82fAv/Ff5ksP8vx6tPvPUkNhSCll2CCW625SoPsjVptBrFCNuRoI1WTMOvYxe+GLPSBFIkYe+27d11qc0IV8u4l8RJpGbZzgV5ZjDv2CD2L/Y6AZlfiicX9ZTHK5QKxVeE220P/0gsuj7JSj3Jj1aMcSZmzQBisGaVEY57bN42tGjnXcYqoJLgMMSzTwcl7DEjP1XIa9TCVHzJOqAj9fMqUkhVkoTyfV87es/M/B4bdS5T59lF+Z7qGT7Exr9F5pkPe6bp0jXXkmyHFaFCojpN6i03tCip4RbfIvT+mRpwknkjyiynYhRig/hzsGk8P0ivMqVOIXvFNtgD0qcYpi9NX4rUFRISzdyGevwfYeyn3Dk9fQuB7TuOP3iDzjJluEYeUIZJ8IVJBw8egUe6nmzNW+Jd/+Ze4cuUKuq7Dn/3Zn91Wgv9BxvY28J/cd/xxsRdoo1smkgFfktLSL6vzcxAK7JZivfucQJ8kzhFqUShuAw92Wp9si+IbTxCqWhTqfJ8nkWt0C5lTcEKWgntNAe1QN+JNnjpvZ1pZFuZR0qM8VMV49dfiUS4OVUAFuZcR00M2gOkmwsa2XGO6jTAa+xOnGMmQovMwpq88Y5CkKtyj4pzHeZGe3GJVWCiMIgD33ZJ9SQLI6BjPsoRV+4XAu957898lbJpdS2N3Q0QaM+q8lzZPQjPLqSy+/0oV40m9RabFUNH9f+1d24slx33+qrvPfWZ2Z2e1u9YlsgghxBgsyL4kIC0ywnoxGEIUG4xBJM4iogfJGCH7zQ9+CnmQMVjCBIPQP2BbIi/CxjJGCskSLPzkyJZWSqJdS17trHZ3zrW78lD1q/pVdfe5zGVnzpzfB0Jnz+mpvlXVV9/vVuSjpvO5nTKsr40sBERA8/gTHcny9ApYv11mSU+zAJmcEWLT/8YJMWuZ5zoZm35DJloNk1PY7kH9yV8Y3+H2h9C/Z+owzYy1JlCDlvSoL6QN30cdGTJ/uTON2khdCrri7wrKqNpGeylU4UMPPYRGo4FWq4WvfvWrh305c2O5SXAWKMeN9g9r9ezK0qYzJCmAlDm1aTWsTXADJWS7MHU+yVCn1WXSJP/e2JLXZGjbK4xJpXfSBLe4P1B+5U3J5aklXdgVMZ8IA7MZUyOAn1jmGDBKWV9JsuYjVCPfnybz5tikR+ixjXK9dQPFtSuR6bUmj7LTM+oya5nLdMqZ5eqlNbU86y/eT/7xO6fIT0qhGE+A0kJBedMg7TM4ywdYdQ2Ux5cUQJECKvc+Ik25Y+zaALh9LmMTbsknSN/FZMZNqtZvzTeFjn16+0WMu1GLfG9MZzVhqROc7BotQLUx1Z9IwTFOSZJKtNfW7JhnXvIzMl9hTIi0kzx3g9hEeJUkUKfOmf0Ob9+I1OEZQ5iAsdbQ/bmtxSa+f1CATJA7OCeokMQRV4UPPPAA3n//fVy/fh3333//YV/O3DieJOgCQYbeL8VrgSKxk4byA4Q6KtUcdASRhZMjBVJQNRVKw7CrOw22qnXRgCnQNhNP7fRKg5xU0XjiiTdNTRu0K3s+AdwuFDC/NRcgEbpXdx8Kxmdq/RIF3KSiaGNSO/Eo+lumtDQR9XgADAfQo75PD/n4qplwXHoIq8zT7hoVWRXMM+v6efmxODCFR18mDavomFKqUpH5GNDD0r2ViEoDTkXyFBYeVOP8oDXBPUFax4ipV3Y+TmSV5Fi1AIiui/y0/Pg44GevxJg1sJBa5H5CCo6KS72RWnRm0Sn+xJYlPSJN7ivMmsZ87xSfTXtIG8ZsT+cfUsBNw5h39cQn1NtrUfnEWD/u/XPofGLV4a+NOty6B2gmUAUjwHziF5MFBcjYe06VJ0PnD+SkSKZ2ZhbXxVKowo2NDWxsbBz2ZSyE40WCZPYYD2D8LpYwVB52MlopuR7GAAAZoklEQVRduwnMTiZOmTS8zb7IfZg091exNjT97bBvNp7NMrP3XmfDJMjTxBtHaDpCLnzUnWkcfqVoV8UgVcHIStmVL49qnQZaOcfpAs6PBXY9Y0DzwCJLKBXBJ+5TZ82snmnCcrsLZCbHsdCWKCmYZwe48ZEP5uE+ynbXBPC0OkCzA9VsuXB8RWkni5ov+f1WkQjgTZCueg2ZWGOfMhFI5CObeW5LOpXnZYRO56WFECfHujxER2hZ1C6ZbYnUYpNq3OYeiJFHiALzqUUq/edIMQ/NotQmBcdM8yc6XyGZVnNGvpEfMU6joKLiRIhJatXowHyXGQuLgobaPAu9dTewc8PsdzjqQ2/dA7WxZRaK1C9d7iDMfanUk2GimH/Qvj+t/bPwL9Z/HC+HKlwmHA8S5OTnOg8LUKmyPJBJigYeRzExBACEE5H1d+iiMH492oZoPGQ7rZ/zO60TXKg2nZvUCMxASNmu6oAPCc9t6kBqBw75HoiQiFg1u+/A14YyeQfPoELt8Hqd84ATuAuSYQEOdqJ2rbXawNpJ/2/m99J5blb6feujtIUHsPMJitHQ1X01RNmxlXm6PlVkUUVJ53d+PTLT2uflVFPDE4XLpWQqcjKHipxVTSYg5tj0ycyfzvfJIkqnpXUQUXL/nmuX3bPLbWT3HajRPRBjSf3NUIvcLOoI1JIij7AmFRj4E3N/TqpkVDDyJxO2q7k7CRPt+fcjm0Cf2epNVLw7yfxWY501qHv+zKjDGx9Bv/MWdHfDqEM0oTTs+LXWosQqWxclCtunyExqfYHljur/X+RLoQqXBctNglevAm//FvjLB2ccyAiCT0Q0kdEu15yEaCfzzJRq0koZlbf9B9MBVWJIb/NTZjIOQtt1SGQElXqCCELcLYnnA59blDWM/5CuRSXlLZ94sAlN3lNJj53PPRdrVlTa/BdM5PSs2DPjfh0y+QaTV5UJcB7zZWoUXqNtI0zPGgUdtRUG8+yYHUNmKUob/RooyqwFlSZ+0uZBKmTGqiWsGSoyeC8T/xmctGrMrVXvzPkFF0jr4Cbh2N/p/qszqbL2qsy9TjlaUtwNMfLJe5ZapEAWwB83GQGjSXhco2ve2zR/okI5gMaRHJmQJ6w/M1M/U4Ou/1t3iUpSow5PfQq4/Qn0h+8ZdXjXfVBrmybam4JgKEBIR4THDUBxH+C5hnSQqMJ9wXKT4HPPAj/+KfB/lxFWxGfmI74yV7YD0WaXfFcI6uhsD0GNhiG+nauG+LKG2XD27J+aABBORjSoaNJwl5JYf10jnORIQdAWSS4fqgsXzUq1BlMbWMDLQ7nUAU5sOjwvJfhXTa5xOgn45M2+r0ovoefL8+JoEeCiQhnJ7Tb6sgJKKVuHtRkqSnZfusjNLgiDWz7qdbRjKvNQxOuwv7+K0lycJ6wq7CaidZqKnBYcFL+DuIpNEFkajZU0QVCKrUS2LLcxDsLh2yK5v59XMXKz6Ay1GJCibZeqLTn1ScdU+BMpNYLInsyWpWLf45C0KUiMCJHatxGhSilg7QRUdx06H0N/cs2ow7UTNrK04RfMuoBzu8TvtYoMyx1KVOE+QGkdv4F6nD9/HpcuXTrI61kMV64A77wD/PVfhRN21WeaFKbcrqYORE70ycgO6NSoiIbdFYKTHa1auQ8RsCTU9mYgAMF+bOSr4OkVUeHukMATuDw5Wjnzsly0usyaXi3uBjxcnW+J5My1diFB9z+NKJ3iqJjM6yIiF7lO7uuiZ1JSLRUmQkxRlPS5VlFSlR72eRGinHU/XEVWpZUsoiLrzsPTOioUefDMZiX+x2PB+TBZO1X+0sD8TG1UECMPSCMVSMfHvkVeLjHYYzIL3Q28f/M2yLRK5yC/IC2Sqb4wFWmgdug+AbhKRlR+sZiY4bHzCfT2h2YBduZ+qO6GrRiVIdgWzAXM2Puj/uxU45TpOklFFU5BHX8ttxJk+wnWhl1yf2GS+tWbDRDR1OEogjFJjRpr9wD0bLO28/Hd4R3s6jBnpg0iN4o2dZNDfG00AcFPQhlTb5oN/MnIDmg7KGkQ8pX3bgiF+11yRnqumgdFzrJgDa5AOOG48/OFByNKHjHLg00CM11ElECoDhwx8KhHO5HVmWOr3tosRYkpRHnjIxQf7jNR3ikVST6xWe27wBzyZUXvmlfJqQrEmTe3MWMLtnkUI5kugelqMWsZSwORYhSo5fqLC36z7g+nIqMKNuSHTywhUXR4SoRYhGqSFrUaJkZgbdOow4lVh394F3pjC+rkORN9yhXhomZRglOFLW+2FczEcpPgLPDtlCi3aNQ3aQx57qu1NNsmkvPkWWPfpwkAYAMw8wO4yL09HvArNwDOX1CVcB/DqSjFVqKTMImf0iOylK08SfHtgvhosqPoOlqFkjmZ7iUfAXq35ktVvyiJrwVgRMlIn/5d2bwlaa4oXXu0GNmDyqTTHCWinCeidS++yKntM3KcN60jiU2i/P1SG5H6o7/lE/g8xNhoAaoTLuhi3yIRGwWhxKXeaJsmOh+VVSRCJaJzlXAs+Wn4xSMpRFrwKTt+AXctqtWF2mpBb54Fdm5C/+FdYDKCPnM/VLsHNdfAAaYqwvHQ1NhtiSqcB8eTBGlj1GICJA1oKn+WTwzpDW7ZSic9YG3LjDfyd9BqsNmFS2ols9Fo5M2QDnbVS52NIuzIt1AKgCFito5yBeODc8qGTKu0is1h0iP4/eWmMgnl+MUBLPwzJ73StaN6dT8rknGviCdEvtmsi0RkPqbgXhbxY1aYXmtV5+7u9UgQ5YGryGT/0jp48jzASJsRXaDymZ+RyHFexQh2bLzTSJoCmQ2kcaTISr3x/S+L3G5LBU90AFuUsvMRCdN4AjwhJql7ZirNgPVTUL0T0OMh9M1r0Fd+D33yLNSJu4AkmUKHXAXWyEYtqnBeHC8S1NoGt4ygaUU22jElyoZ9l5yNtVNQrjo/mSEoeMMmrA9tHhH3uSnlE+gnthoMmT21toEtlEvHOh2ZW4i0HJQ3CSVsxUh+Q6pmwnfxrvJ70mq/oAlpiooCGElGfjlSUrkuk6n7uwXfBw+oCPxPbHJsNFG7/1583dMm+9K5I9Oru54KMi35MGvMs7sgzEMnyoNUkc4ft8e0Dh7UEft7a3MbbdAYBbxNI0YyfwL+HmO16ILk7MJ2QilJ1i1AKQwUHU3RsUliF7K2TnGVIkxSf43Uj2zfU60OVOte6JNWHV59x1zjXfeZmr78uZZf4PTONx6aftXqiiqswfEgQa0N8VHH19oovvHQTDztniE+HlxC5c6IK5zJ0056VMTWlVGyK73J0Of8OVNLRHzczxCbVt3OE2wgUGQqOd5p94okmuzjlXccfclXhW7wM+f+tMAhIoui5hhqv1J12t+IRCl4x9VWJR/j7iJCd4Xg2mYM/lIQFSNNMs0u4scMvsdc93poRHmQKpJSgirby70fbVpaR2KL2XOrBpFdXW6jW1TOIEbnX9T+WrhazIj4aDzb6+R/y60sCbtfIlq6D8CPU2XNqC5f0ChWlSTAximo9U3o4Q70zevAld+ZEm3rpwCV2n4xQwWW3mEhqnAKlpsE+33oK/8DnD1j/j0e2IoPmQl779ryPcHAsp2OtgbiHcOlLdjaog1biqzIfcoCYCfzpu/cVcElhDQDsk7ZLEph664Sva1tqOwKUue+3ig3F9IkYxpik0AFwcZw5LWLZx2oBTIdF3CkZ05g26ZJi67RHj/NbFv32V33AWKR51LyY3LSLDxpcjU+iyir7rnyMu8AUcbpIQelItOGIbdSW2xxV5vWkXgScuZRbvasiBKmBRi9O2565cTYiNI08mGoFrllyEV5kyIFfFEL7eccsO/SzLznUnR3aHVSzQ7UXV3ozXPAzjb0B++Yezl9j6maNC8BcogqrMRSk6D+t58Cv/1v4J8uAtB2lwNbRYImE6fsYBXj2K/Qsrb5bTyE34zVVo0oLCEWfT8oKK+QfHUUUUZhzQp+wFTl6LkVKYssSxvms86B4ZitiPmAz2DMMKQAbXBMmvnk7v0mCkfseUh89EyT1Joxk9nnPzAFeggE6tqdcxK5w37MPRPlPOkhpTzKfVaRWQPBO3SmUSK7caQeI3KkgBXnIshrchtZAr0jvQpirIrWdmqRKUIaLy7Qh8iUSNESoLt/GwxHRSv4+7T9WCUKWN+CWt+CHt6G/uQacHsbOHU30DsBqMSkWswLUYUlLDUJqr/5OxOs0iRHu/ad363YyfSZh6oLsFGYLKqTojNHUSAKtTUZ+oTbYKJNbDuJWRE6h/jYr44rUySs+TCOvgT8qpavNpPMEPd+kl4wwdQEqSSp2buQJ8Uvgr0q0GUm0CPoxzwcoqy510VVJG0qHJhHmYUiZ+qRW39ofPFgGac2KZCHfNTWveGU6SQkRnJ/AKEiJIVLz5rnTaZZeO6A5Avz7xkDRDU7UKd70JufAm5vQ3/wOxPZvnkOyBqLDS9RhQ5LTYJQCmi1+BflfqQLu5fgxHQYlfgi0mkGoOEn/jQDEqvMJjYMnMCd8QBc4jut6CigppiYwJLqRJ/w+yIHUHi/JOhnNsG52oV2kGirCBUbNAHJ1EzgcwWppPV72x0WVolAj5Afc3GinLMoeh1RNtvl+1tURZIKpHE2T1oH+fpVAjMWq0yqFP3Jzal1xMjGmQaCKFFOgFQPmN4hN4u6Z8CeBVPFKkmA9U2oDasOtz80z3rznClir+ZMtBBVCGDZSXAabLAMxkNbh7PlA11ohZhTubIMQGp+o4R4Zf0DtIJTMCbQ3Aa7AKzTFAhX+tb0kdUksTvTC6vKQgODDxo61ilcmrT5926khAOoFmyyS1JAsetzfrwc0PGEvo/q6E7hOBPoEfBjuv0oGycPgCg7Zg/KgChZEe5FVWQjrnhkF4J1aR3BwpMUobUcceKjd6ABVyDAmVLJZ6lRIkBzI2VV6N4vqtfRdG/2GRh1eI95zrc+NpGlrR5w8i4gSefr+qQKm112bauD40mCvI5gmvkC1M6MxFZe+QRQdsVH+T2ZVYPcR0BQKgxA4WRG9QrjsmV8EPA6hbTC5A73eREHEnCTJgCfY8UnM4SrT35tAJvU+THs3/4hIAiAoedSp0znOcZ9d0RwnAj0EP2YStlJv7sB9E6Yf5dOt49EmbG9QedWkXahmyh2f8wHT0qNzKp0j85vbsdd4J+0NxcHtbmdSPiCg5GzG5fReK1eYoD8kUol3nc46kN/fMXMMyfPmdrFs9ShLoDhrbCe8orgeJGgi+K0HbLIAb6lEoeC6bDaEpkmP6D2gTNKeVNlynZs5ztEOMXXDTsO3wi0VK6pXU5/mAYe/cYd8LRypdDseYJU9oJAddL/I2XKP9ep19IxjGD3SqZHQb0uO4G63+6MH1PR53bPbE1U4cfcN6Jsdkyi+jwqkgjSmSIRjj9OqKUgOEbA8bikxSsRI//ePaOKZ00BOPR33NTNxpBRh/dCFwVw+zr09hWozgb02iamJ+HDxj2MjJpcEVV4PEhQa1sRZhx+5xC9dm3Nl9RJqRoFEZNLbIdPk9Asl48UHPkYqc3JxBOf1rO3GKq6j2lBKmTG3UuQyl7grn+XE/w0zCTTmHCnqdeoneCaj7h6XUYCdabTg/NjOqJstk0CeYUfUwP7Q5RZ0/jdAkUYqcgkDQkSYD5ITqaZUZiOq+h3ujerGnl/ndmndPRZRd9R8xXqEAA2z4DKDlafSRtVmNIcd7xV4XKT4I0bwNX/Be67t/p36mTc10a+wHHfElQPvh6o3Uoptf5AAMHO0mnDE5/WVuUNvV+BlF6rO530uHnUBalwk8kRDVI5SCziD1sEq6Rel4lAqZ/X3esu/JiOKLMG0NiEWt8Kz6dsMsFkYrfTIqK8XU+UrQ5Uu+eJkgoOZCkUVDXxpZT6oDzBcR8mqexAYdKzZO9P2+ca9DUiZ/Z5ChG6PyPfIanDwQ7U2iZ0u1dPhvkI6I+PvSpcbhL89X8B71+uJ0Fn8shZH2GrrSI3u0fQgKYBUxRAbqvCOFOjPX4wBihBnHwAQYK68uel81FSOdUIpU5LzvOElOgBmjJXFUujXivI9U6q12UgUDc+4ntFmShr/JiKfksSoLsB1TtZTZR5bkonjvrQI0aUVQUHiCjbXaC9bhRl0wTVKY2yiiT1B5T7CX939MoquY0p5TmJ0Bweq8OrUGkDeuOUew5hFyBV2DDbNB3D+Wm5SfDCI9Xf66gj6MKbOLOGIZ3C7qIAhOkNgFWOUfkjIj0kzpQQnK+w+4gFAQMciv3Pmkco8bYSfELig0KFx/A293LMPOeaecyKQdQrO0Yt5ucO7vUACTTYw5ITTI3SLCxR6sIUqcjWoLrr9URpN2nWljBx/Wq9ouydMCkM7R5Uo+VSOhwx8+cKAEr7V+bmH3jicwtxxd75bCJ0zTc7UFsdrw7HY6j1U9C2UlDQq/OxUYXNni3ecXxwvO6GwDsSRYomiZH1+dh0VtqDLp8AemL9gh0fgJLbiNLU1rwk4psapJL63Q8WDVKJiRtsAPBOHRy3wDE0URKKXbYTHxNAiHtfsDTqNWonuOa9kqkK33+tyfQACFSxgBhN5+b9vzAKL0msmbQNtXaCqTlGlEUODC1RjoaGHD+5hmLUd5s4QyVAZ91Ez/Y2jK+y2fHF+hWgHMHFz6DAXojQXK5Vh4BRh9vbUO0OdHvNPXt35tFtYEIuH/ttUexuAXREcDxJEPA5f1QAu8hNh3PboBRme5i0AVMxfgwoSnNoAknHmzGoyC+vRLHfQSqlQX4AE+B+Q4h78WMOm7hXRr1WkCk/hre9HwRKO8mz96cAn0/YXfeKj/kxPVEOgbElypvXoUcfQA8HrmIPWh2zCUB3HaqzZkyTDZte5USkQnlRshhUswPVZOoQCqp7ApqbSouJ2Yu12YUe7Zjvml2bWrZ8OH4kqLUJ8x2PbFUG7fcCo85BgTC8BmdqO1CRA3nffA7Khq1QkMq8EOIuHyPE7dtL9qkzHKp6rVGm8fU58cXJexqBJvaTMhtmZy0AG7b18Dp1ob1FazSAHg2AW9fN52Hfu3XaXWdyVa2urV8ckvO8b0QliSFdWHU4GEB116CpPaVMPIW9WjXaAbITc7bucfHiRbz++ut4++238aMf/QhPPPGE++1nP/sZvv71r6Pf7+P555/HV77yFQDA9vY2Pv/5z+P111/H+vr6wueMcbxIkEydAADtK7vEUHbl5ur+UURm4ksvzZPSIFg+CHGXjzlOxB2oxVnt8PuJrn2aeo3JNFDB0f3HZKrZddElBJcSPz9lmsga5r/uuiHO6N60LgwZjvqGHG9+7EnT5k2rJIVudY3Ztd3zBfDdRVQTZaAOd26YyPmGL1eplILWGqp/y/g8F8DnPvc5fPnLX8Zzzz1X+u2ZZ57BK6+8gjzP8cgjj+Dxxx9Hmqb49re/jW9961v7QoDAcSHBPDcvn4phl8B6m4voTLzSE7ITHGUIcZePOUrEraaoxIom/TkVguAXDn6tCoDmTMnVpvKmUKr12t2ovBKtrTAY9YH+TegbA2BkduPQClAUAdoxRQVKe0EqBXRPAEpBD4dQzSaoApBSCrqYQE0mCwXOPPXUUwCAdrtd+u327dv47Gc/CwBoNpu4du0aLl++jHfffRcvvPDC3OeYheUmwTfeAP7z34F//Ifyb64sUjpd2blUBoFAcMdRa1Y9JMxL3nXHBofVEfAcbccoEWFVGzOaUIopyjmIcjSAntiykWnD7NbT6NjI1tQpQNc2gL99vMCb/wG89hrwmc/Md111OHPmDN566y0AQJIk2NzcxJe+9CW89NJLe2s4wnKT4L/+EPjxT4C/f4IlczK7PlV7qBOIAoFAcORRY94lVBLsbqDnJ8rRAMVo4L9TKQqt8JNXT0Ip4Fe/2jsJvvjii3j66afR7/fx8ssv44UXXsCjjz6KwWCAxx57DKPRCN/5zndw4cKFPZ1nuUnwxR8C//wvwPqpw74SgUAgWAkoABh9CLTb0JMx1PA2sLaGrLOBV18FLl0Cvva1vZ/nwQcfxC9+8QsAwJUrV/DNb34Tb775Ji5cuIDnn38ed999Nx5++GG89957qCrMPi+WmwSbTeD06cO+CoFAIFgt9E4Cw5tIWj1g47Szvj32mPlvv/GNb3wD3/3ud9HpdPCb3/wG58+fR7PZxHg8xkcffYQzZ87suu3lJkGBQCAQ3HGoZhNobu25ndFohKIooLXGeDzGYDBAs9lEwpLvX3vtNQwGA3zxi18EADzwwAP4+c9/jvvuuw/D4RBbW3u7juVN8xcIBALBUuMLX/gCOp0O3njjDVy8eBGdTge//OUv3e/D4RDPPvssvve977nvvv/97+PJJ5/Eo48+ih/84AdI91jcW2k9v1f1/PnzuHTp0p5OKBAIBALBnUYdf4kSFAgEAsHKQkhQIBAIBCsLIUGBQCAQrCyEBAUCgUCwshASFAgEAsHKQkhQIBAIBCsLIUGBQCAQrCyEBAUCgUCwshASFAgEAsHKQkhQIBAIBCsLIUGBQCAQrCyEBAUCgUCwshASFAgEAsHKQkhQIBAIBCsLIUGBQCAQrCyEBAUCgUCwshASFAgEAsHKQkhQIBAIBCsLIUGBQCAQrCyU1lrPe/Dp06fx6U9/+gAvRyAQCASC/cfly5fxxz/+sfT9QiQoEAgEAsFxgphDBQKBQLCyEBIUCAQCwcpCSFAgEAgEKwshQYFAIBCsLIQEBQKBQLCyEBIUCAQCwcpCSFAgEAgEKwshQYFAIBCsLIQEBQKBQLCy+H94KvEGm1imAQAAAABJRU5ErkJggg==\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": 27,
|
||
"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": 28,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7feccbd27d10>"
|
||
]
|
||
},
|
||
"execution_count": 28,
|
||
"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',['total_supply','funds'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7feccbc7c290>"
|
||
]
|
||
},
|
||
"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('timestep',['effective_supply'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"As expected *effective_supply* is increasing with the arrival of new participants."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7feccbc38ed0>"
|
||
]
|
||
},
|
||
"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('timestep',['participant_count'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Review system health metrics\n",
|
||
"\n",
|
||
"Below we will analysis system health metrics, such as fraction of supply used for voting, which is effective supply over total supply and percentage of proposals and requested funds in different stages. "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7feccbbaae10>"
|
||
]
|
||
},
|
||
"execution_count": 31,
|
||
"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',['fractionOfSupplyForVoting'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7feccc328390>"
|
||
]
|
||
},
|
||
"execution_count": 32,
|
||
"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',['fractionOfSupplyInPool'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7feccbadfa50>"
|
||
]
|
||
},
|
||
"execution_count": 33,
|
||
"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',['percentageOfActiveProposals','percentageOfCompletedProposals','percentageOfKilledProposals'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7feccbb6dc90>"
|
||
]
|
||
},
|
||
"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',['percentageOfActiveFundsRequested','percentageOfCompletedFundsRequested','percentageOfKilledFundsRequested'])"
|
||
]
|
||
},
|
||
{
|
||
"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
|
||
}
|