1801 lines
728 KiB
Plaintext
1801 lines
728 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",
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"```\n",
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"proposal_rate = 1/median_affinity * (1+total_funds_requested/funds)\n",
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"rv2 = np.random.rand()\n",
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||
"new_proposal = bool(rv2<1/proposal_rate)\n",
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||
"```\n",
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"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",
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"```\n",
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" {\n",
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" 'policies': { \n",
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||
" 'random': minting_rule\n",
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||
" },\n",
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||
" 'variables': {\n",
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||
" 'total_supply': mint_to_supply,\n",
|
||
" 'funds':mint_to_funds,\n",
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"\n",
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||
" }\n",
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"},\n",
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"```\n",
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"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)"
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||
]
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||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"```\n",
|
||
"{\n",
|
||
" # participants.py \n",
|
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" 'policies': {\n",
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||
" 'completion': check_progress \n",
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||
" },\n",
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||
" 'variables': { \n",
|
||
" 'sentiment': update_sentiment_on_completion, #not completing projects decays sentiment, completing bumps it\n",
|
||
" 'network': complete_proposal\n",
|
||
" }\n",
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||
"},\n",
|
||
"```\n",
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"\n",
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||
"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",
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||
"```\n",
|
||
"likelihood = 1.0/(base_completion_rate+np.log(grant_size))\n",
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||
"\n",
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||
"failure_rate = 1.0/(base_failure_rate+np.log(grant_size))\n",
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||
"if np.random.rand() < likelihood:\n",
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||
" completed.append(j)\n",
|
||
"elif np.random.rand() < failure_rate:\n",
|
||
" failed.append(j)\n",
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||
"```\n",
|
||
"With the base_completion_rate being 100 and the base_failure_rate as 200. \n",
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||
"\n",
|
||
"The mechanism then updates the respective *network* nodes and updates the sentiment variable on proposal completion. "
|
||
]
|
||
},
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||
{
|
||
"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": "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"
|
||
]
|
||
},
|
||
{
|
||
"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"
|
||
]
|
||
}
|
||
],
|
||
"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['initial_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": [
|
||
{
|
||
"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": 3,
|
||
"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": 4,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'initial_sentiment': 0.6,\n",
|
||
" 'n': 30,\n",
|
||
" 'm': 7,\n",
|
||
" 'initial_funds': 4867.21,\n",
|
||
" 'supply': 22392.22}"
|
||
]
|
||
},
|
||
"execution_count": 4,
|
||
"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": 5,
|
||
"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": 5,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"sim_config[0]['M']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Initial state variable values"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'network': <networkx.classes.digraph.DiGraph at 0x7f51e80d8c50>,\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": 6,
|
||
"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": 7,
|
||
"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": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'type': 'participant',\n",
|
||
" 'holdings': 833.2406503557274,\n",
|
||
" 'sentiment': 0.4709502362775757}"
|
||
]
|
||
},
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"#sample a participant\n",
|
||
"state_variables['network'].nodes[participants[0]]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0, 0.5, 'Count of Participants')"
|
||
]
|
||
},
|
||
"execution_count": 9,
|
||
"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": 10,
|
||
"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": 10,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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miNfQQFpaGjIzM/H777+jQ4cOZdPRd8W8ecCMGaX/ERAQAIwbV3Z2fSSIEZ9AIChTFAoFwsLC8oicXC5XCly3bt0wZ84cODo6Ql1dPVd5Ozs7NGrUCEuXLoXzm6Mzc/Mcl/xS7OO7YmGB29HReP17X1NTE/U+Rvd+4ehTKsSITyAQlJisrCzcvn1bKW5XrlzB9evXYWxsrBzBvb5sbW0hkUhK12ApT26RHzuGpuPG4fz588jKyoKmpiaGDBmC4cOHw8HBoXS2vUvatgX27Cl9Pd7ewO7dpa/nI0OM+AQCgUqkpKTgxo0buHLlilLo7ty5Azs7O6W4tW3bFnXq1IGpqel/Y0S9ejkHThfTm1GurQ31BQugXr8+du/eDWdnZ0RGRmLXrl04deoU6tevjyZNmmDUqFH46quvSi/Q/zXC0adUCOETCAR5ePHiRZ6pyvDwcFSvXl0pcn5+fqhVqxb09PTerXGvD5pWMTpDhpoaRmRk4PSyZZhsYIAuXbrg2LFjWLduHVq3bo3WrVtj6tSpWL9+Pfr37w8jIyOMGjUKXbt2haam5rvpU3GpVUs4+pQCMdUpEHzGkMTTp0/ziFx8fDxq166dy+mkevXq0NLSet8m/49Ll3Jc8vftyzmR5Q3XfuroICM9HdktW+Jpnz6o1a8fsrKyoK+vD4lEgrVr16Jr1655qlQoFNi7dy8WLVqE0NBQDB06FIMGDYLxexwZpaamYvfu3VAoFJBIJJBIJIi7fRv+c+dCkpFR8oo/1ePbVEAIn0BQVnzgBwQrFAo8ePAgj8hJJJJcAlenTh04ODhATe0j2eYbGwsEB2PTpElwLl8ezm5ugLMz5kRFITw1FcuXL0e5cuWUG+ENDAxw7NgxfPHFF4VWe/XqVSxevBh79uzBN998gxEjRqBy5crvoke5ePjwIRwcHKCnpweFQoH0/x/lvWrRAnqHD4sDu0sCBQJB6bhwgezYkdTRyblyHkU5l1Sac69jx5x874iMjAxeuXKFa9eu5dChQ9m4cWPq6+vT3t6eHTt2ZGBgIHfv3s2nT59SoVC8M7v+K86dO0cANDQ0ZHZ2NkkyOjqaRkZGfP78OVu2bEk1NTVqaWnR19e3WHU/e/aMkydPpkwmY/v27XnixIl3+p7J5XK6uLgQAAFQS0uL27Zty/k+6erm/r6peunqkhcvvrM+fGgI4RMISsPy5TkPEYmk8AeNRJKTb/nyMjfh1atXPHPmDH/66Sf279+fLi4ulEqldHJyYq9evbhgwQIePXqUL168KPO2PxSaN29OANTU1OT69euV94cMGcLJkyfzt99+Y/369RkaGkonJycuXry42G2kpKRwxYoVrFKlCl1dXblhwwZmZGSUZTdyIZfLuXXrVjo7O9PJyYlaWlqUSqX09/f/X6bX37/iit5/8D38mBDCJxCUlPfw0ImNjeWhQ4c4d+5c9ujRg1WqVKFUKmXdunU5cOBALl++nOfPn2dKSkoZdvTD5tatW5RKpcoRkbm5uVKQQkNDaWpqyqSkJGX+x48f08bGhn/99VeJ2pPL5dyzZw+bN29Oa2trfv/992X6oyI7O5ubNm2ik5MT69evz3379lGhULBFixZ0dnbOK7bLl1Mhlb7XH18fG0L4BIKS8B9PMykUCoaHh3Pnzp2cMWMG27ZtS1tbWxoYGLBJkyYcOXIk169fzxs3bjAzM/MddfrDZPz48VRTU6NEIqGamhoB8OTJk8r0bt26ceHChbnKXL58mWZmZjx37lyp2r527Rr79u1LIyMjDhkyhPfu3StxXVlZWdywYQOrVq3KRo0a8eDBg7mmVBMTE3MJOJkjwkFBQfwC4EF9/Zxpdak0/+n2Tp0+6+nNNxHOLQJBSSjDSOByuVzpdPLmHjlNTc08TicVK1b8eJxO3hEZGRl48eIFmjRpgnr16uHXX3+Fjo6OMv3y5cvo0KEDwsLCcnml7tu3D35+fjh9+jQcHR1LZUNUVBSWL1+OVatWoX79+hg9ejQ8PDxU2g+YnZ2N33//HUFBQbCyssKMGTPQrFmzIss+fvwY3bp1w+XLl6FQKKChoYGsyMgcB6ubN3OiUBgb52xZ6Nv3g3Cw+mB438orEHx0REfndWIp5pWlqcnx/fqxYcOG1NPTY6VKldi5c2fOnj2be/fuZWRk5Pvu5UeHk5MTu3fvnm9a8+bNc639vWbVqlWsXLkyY2Njy8SG1NRUrlq1itWqVaOLiwvXr19f4DpgZmYm16xZw0qVKrFp06Y8ceKEyu0cPXqU2tralEgkuZxeBKohhE8gKC5z55Za+NLV1XnS25vHjx9nfHz8++7RJ4GLiws7dOiQb9rBgwdZo0YNyuXyPGkTJ05ko0aNmJqaWma2yOVy7tu3jy1atKCVlRVnz56tFNeMjAyuWrWK9vb29PT05KlTp4pdf2hoKG1sbJSiB4BqamplZv+njpgzEQiKSxkcEKwtl6OJsTE8PDxgZGRURoYhZy/hvHmAj0/OeY4+PjmvY2PLro0PFE1NTWRmZuab1qJFC2hqamL//v150oKCgmBnZ4c+ffpAoVCUiS1qampo3bo1Dh06hIMHD+Lhw4dwdHSEm5sb7O3tsWPHDmzcuBGHDx+Gm5tbset3cHDAli1boKurq7ynUCjKzP5PHSF8AkFx+RAjgV+8mLPuaGeXE65m48acQ4w3bgRmzgQqVMhJv3ix7Nr8wNDU1ERGASeZSCQSjB8/HnPnzs2Tpqamhl9//RUxMTEYP358mdvl6OgIFxcX6OrqIjo6Gunp6VBTU0NaWpoySkRxIYkJEyagZ8+ecHd3x5IlSzBo0KAytvzTRQifQFBcPrQDglesyIlYsHNnzkj07dFoWlrOvZ07c/KtWFE27X5gaGlpFTjiA4CuXbsiIiIC586dy5Omra2NHTt2YO/evVi2bFmZ2JOamorFixfDwcEBR48exe7du3H//n08e/YMHTt2xPDhw+Hi4oLg4OACBbsgtm/fjlevXuH8+fOYOHEihg8fjlWrVgnHJ1V533OtAsFHx9y5VJRyjU8hlZLz5lGhUDAlJYXPnj1jVlZW8W0RG5iVtGzZkg0aNCg0z08//VTgOiBJPnz4kFZWVty5c2eJ7UhOTub8+fNpaWnJTp068erVq/nmUygUPHDgAFu1akVLS0sGBgYyJiamyPrT09Pp4ODAoKAgOjs7fxIn77xrhPAJBMUgOzubW376iWmlED0CTAVooaZGdXV1amhoUCKRcHlxxUgcWZULb29vurq6FponOTmZZmZmvHPnToF5Ll68SDMzM/7777/Faj8pKYk//PADzc3N2bVrV16/fl3lsrdu3eKAAQNoZGTEgQMHMiQkpMC8CxcuZJs2bdi0aVNu2LChWDYKchDCJxCogEKh4P79+1mrVi02bNiQsW5ulBd1UkYhJ2hctrfP5YquoaHBp0+fFs+ojh2LPq2jEBvYqdN/82a9Jzp37kxnZ+ci882cOZN+fn6F5vn7779pZWXFsLCwIutLTExkUFAQzczM2LNnT966dUtlm98mOjqaAQEBtLCwoJeXFw8dOpRrRBcXF0eZTMatW7eyfPnyn/3hBSVFCJ9AUASXLl1is2bNWLVqVW7fvp0KhYIbhg9nSglFJ0tbm7x4kcOHD1cetSWRSKirq8sBAwaotr2hDPYSUkeHVGFq7WPhm2++YbVq1YrMFxsbS2NjYz579qzQfMuWLWPVqlULPI4sPj6eAQEBlMlk9PHxKXQUWVzS0tK4bt061qxZkzVr1uTatWuZlpbG4cOH09/fn926deOiRYvKrL3PDSF8AkEBhIWFsUePHrSysuLKlSuZlZVFuVzOMWPG0MnJiS+Dgoo91Zito8PxBgacP38+s7Oz6eXlRSDniK2ZM2fSzMyMEomEDRs25NmzZws2rgz2EvL/1xk/Ffr160dHR0eV8g4bNozjx48vMt/YsWP51VdfMS0tTXnvxYsXnD59Ok1NTenr68v79++X2OaiUCgUPHz4MFu3bk1TU1Pq6urywIEDec4fFRQPIXwCwVvExMRw+PDhNDU1ZWBgIJOTk0nmnLTh4+PDxo0b/28UoGJ0hmyAmVpa5PLlDA8PZ506ddi7d2++ePGCK1asyDWddejQIdapU4cSiYRWVlZcsGBB3o3XvXqVTvReX717v6u39T9nyJAhtLOzUynvo0ePaGJiwoSEhELzyeVydu3ald27d2d0dDQnT55MExMT+vn5MTQ0tAysVp1mzZrxyy+/pJaWFmvXrs2bN2++0/Y/JYTvq+DD4z1twk5JSUFQUBCqV68OhUKB27dvY9q0adDT00NycjLatWuHxMREHDp0CCYmJpDL5eh99iz6VaqUc/amjg4gleauVCoFdHSQ4umJ1lIpQlu0QIUKFXDmzBlkZGSgdevWaNeuXa5zGVu0aIErV64gMjISTZs2xZQpU6Crq4uePXvi+fPnOZnKaC9hzP37uHXrFl68eAGSZVLn+0JHRwfZ2dkq5bW3t4eXlxdWrVpVaD41NTUsXLgQZ86cgZ2dHeLi4nDp0iWsWbMGDg4OZWG2Spw8eRIPHz7Etm3bIJVK0apVK7Ro0QKtWrXCgQMHPvrP7p3zvpVXIFDyngK6ZmVl8ZdffqG1tTW7devGBw8e5EqPjY3ll19+yf79+yu3HERHR7NRo0YE8L91pZgYct483qlXj8f09XNGU/PmKdfRfvzxRzZs2FAZKFWhUHD27Nm0tbXlhUL6JJfLuXjxYtrY2FAikbB27dp81rRpmYz4Dlpasnr16jQyMqK2tjbt7OzYoEEDdurUid999x1nz57NdevWcf/+/bx27Rqjo6PzPfbrQ2DSpEm0tLRUOf/Vq1dpbW3N9PT0fNOfP3/OMWPG0NjYmP369WOlSpWK73lbBsjlcrq6uvKPP/7gjBkzOGDAAJI52xqCg4NZq1YtOjk58ZdffinTY9c+ZYTwCT4M3kNAV4VCwR07drBatWr08PDIV3weP37MqlWrctKkScrpyNOnT9PY2Jjq6uoEwIYNG+YqU7VqVQLg3r17c92Xy+Vs2rQp58yZk+v+jh07KJPJVHJNP3/+PBs1asRxyNkSUZZrfKmpqXz48CHPnDnDP//8k0uXLuXEiRPp6+vLli1bsmbNmjQ1NaWmpiZtbW1Zr149tm/fnoMHD2ZAQABXr17NPXv28PLly4yKilIK/LvitaNJcWjVqhXXrFmT615kZCRHjhxJY2NjDh06lBERESRzzse0tLTk7t27y8xmVVi/fj0bNGig3Ipx9+7dXOkKhYJHjx5lmzZtaG5uzunTp/P58+fv1MaPDSF8gvfPe9iE/c8//7Bx48asWbMm9+7dm+8m4Bs3btDW1pZLlizJdb99+/bU0tIikLMV4c1N0yEhIdTW1iYAWltb5zmZPzw8nDKZjNeuXcvTVsWKFTl+/HiVBCPh/n1mqqu/F6/O9PR0Pn78mOfOneP27du5bNkyTpkyhf3792fr1q1Zu3ZtmpubU1NTk1ZWVnR1daW3tzcHDhzI6dOnc+XKldy1axcvXLjAiIiIMnPJnzdvHo2NjYtV5ujRo6xatSrlcjkjIiI4bNgwGhsbc+TIkfl6fZ4/f54ymYyXLl0qE5uLIiUlhba2tjx79iyXLVvG9u3bF5r/zp07HDx4MI2MjNivXz/euHHjndj5sSGE71MlOjrH869XL9LbO+ffuXM/PPf1d7wJ+86dO+zQoQPLly/P4ODgAkXm1KlTNDc35+bNm/OkKRQKzpw5k1paWtTU1GT9+vWVaf3791eOBHV1dfn999/nKR8cHExnZ+c8U2yxsbH08PDg119/XaTTxZMnT3jW0pLZJRW9d7CPLzMzkxEREbxw4QJ37drFFStWcPr06Rw4cCDbtGlDV1dXWllZUUNDg+bm5qxduzZbt27N/v37c8qUKfz555+5fft2njt3jo8fPy5wSvI1P/30Ew0MDIplo0KhoLOzM728vGhsbMwxY8YwKiqq0DI7duygtbU1Hz16VKy2SkJgYCC7devGrKwsVqpUif/8849K5eLi4hgUFERra2t6enpy7969H+wU9ftACN+nxntaJysx72gTdmRkJAcNGkSZTMZ58+YVuhayc+dOmpmZ8dChQ/mmKxQK1qqneqQAACAASURBVK9fn5s3b+a+ffu4detW5X1dXV3q6OgQyAkTU6tWrXzLd+jQgRMmTMiTlpmZSX9/f1arVi1fN/ns7Gz+9NNPlMlkXD1oEBUl/NGQrqHBxtrarF27Nrt27copU6bw77//Vum9LGuys7MZGRnJy5cvc8+ePfzll18YEBDAwYMHs127dqxXrx5tbW2pqalJU1NT1qxZky1btqSvry8nTpzIpUuX8s8//+SECROoq6ur8jrXo0ePOGjQIOrr69Pa2rpY04NLlixh9erV+fLly5J2u0giIyNpYmLChw8fcsuWLWzUqFGx68jIyOBvv/1GFxcXVqtWjStXrmRKSsp/YO3HhRC+T4n3sE5WKt7BJuzExEROnTqVJiYmHDt2bIGbkV+zevVqWlpa8mIhI8mDBw+yevXq+Y4Wb9++zZCQEEokkkIfMNHR0bS0tOTp06fzTV+5ciXNzc1zie+NGzfYoEEDNm7cmMHBwezYsSPTf/yxRNPEUTNmUE1NTTldK5FI6ObmVuh7876Ry+WMjo7mtWvXuG/fPq5du5azZ8+mv78/O3bsSEdHRwI5AVmNjIxYvXp1Nm/enD4+Phw3bhwXL17MP/74g5s2bWKXLl1oYmLCyZMn8/nz53RwcCjwsyiIUaNG0cPDo8iRaEnx8/PjuHHjqFAo+MUXX5Tq/FCFQsHjx4+zbdu2NDMz45QpUz7rYMdC+D4VPsbDist4E3ZWVhb//vtvdunShU+fPuXSpUtpYWHBPn368PHjx4Wa8trDsmLFioVuSFYoFGzUqBE3btxYaH1GRkZFiuzOnTtZqVIlvnr1Kt/0kydP0tLSkvPnz+ekSZNYrlw51q5dm7q6ulRTU6OamlqOuC5fToWubpHTnq/3Esp//pkkOXXq1Fyj05MnTxZq74fOjh07qK2tTYVCwbi4ON68eZMHDx5kcHAw58yZw969e9POzo4aGhpKL9Zy5cqxSpUqrFy5Mq2trTl69GguWLCAGzdu5LFjx3j37l0mJibmuwYsl8vZqVMnfvPNN2V+UPT169dpbm7O+Ph4Hjt2TLkOWRbcu3eP/v7+NDY2Zp8+fQo8RLtIPpbllHwQwvcp8LEeVlxGm7CTOnRQjurKlStHNTU1VqhQgV5eXnmcSPJDLpdz6NChrF27dpG/go8cOcKqVasW6YBSsWJFlTY49+vXj99++22B6Zs3b6aWlhYrVKhAfX195QgNAH18fJT5zvz4I48aGeVEjZBKcwuetjbl2to8a2XF+urqlEql7NevH58+fUpzc3NqaWnR09OTMpmMK1as+GjXgg4ePEhNTc089+/cuUMfHx/KZDIGBAQoj4RTKBSMj49nSEgI9+7dS0NDQ44ePZojR45k9+7d2aRJEzo6OlJPT4+6urp0cHCgm5sbu3XrxhEjRnDu3Llcs2YNq1evzkGDBvHly5dlIoAKhYKenp5ctmwZSdLLy4urV68udb1v8+LFC86ZM4c2NjZs2rQpd+/erdpn/7Etp+SDEL5PgY/1sGJv7zIRvr3/70zy5tWwYUMOGjSIkydP5uLFi7lhwwYeOHCAly5d4uPHj5XTkOnp6ezWrRvd3d2LdChRKBR0c3NTaduBq6trodOlr0lMTKSdnR337duX6/7Lly/p5+dHW1tbbt68mR07dqSTk5NyelJPT4/nzp1T5m/VqhXXr1+v3EvI3r1Jb29eqFaNx77+WvkrPCsri7NmzaK5uTklEgmrVKlCZ2dnZmVl8datW6xfvz7d3d3/02O4/itOnz5NdXV15euQkBD27NmTZmZmnD17dpGf7+zZs+nr65tvWlJSEu/evcvjx49z06ZNXLBgAceMGcNvvvmGjRs3pqamJnV0dKijo0N7e3s2atSInTt35tChQ/n999/z119/5YEDB3j9+nXGxsYWKpB79+5l1apVmZmZyevXr9PKyirXkWllTUZGBn///Xe6urqySpUqXL58ufK0ojx8bMspBSCE72PnYz6suIxGfM9btqS1tbUy2oGamhq3bNnC5cuXMzAwkMOGDWPPnj3p6elJFxcX2traUltbm1KplNra2jQyMqKnpyd79erFESNGcPbs2Vy5ciW3bdvGkydPMiQkhDExMTxy5AgdHR1VipvXvHnzAp1j3ub48eO0trZmXFwcFQoFt2zZQisrK3733XdMTEwkmePoYGFhQalUqtwm8PrheffuXZqbm+e71vTnn3/S29s733aPHDnCL774ghKJhJaWlpw7dy4zMzO5ePFimpqact68eSWLEfieuHLlCtXU1Hjjxg127dqV5ubmnDNnjspnWr548YLGxsbKfXvF4f79+7SwsOD27dv54MEDnjp1ilu2bOHixYs5fvx49u7dm56ennRycqKxsTG1tLRYvnx51q9fnx06dOCQIUM4a9Ysrlq1iuXLl+eSJUv4/Plz+vj45OsZ/F+gUCh48uRJdujQgTKZjJMmTcodMeRjXE4pAAlJvtOjYgRly7x5wIwZeaNuFwepFAgIAMaNKzu7VKEMbM9QV8ccHR2YfP896tatCz8/P7x48QIxMTGFlnv+/Dm8vLxQo0YNDBs2DPHx8YiNjUVcXJzy3zf/jo2NxcuXL6GnpwdbW1vIZDKYmZlBJpPl+vv1vzNmzECPHj3Qu3fvXMeRFcTo0aPx4MEDAMCjR4/wyy+/oFGjRgCA8PBwtGjRAr169YKTkxP8/PwwaNAgLFiwAAAwbNgwGBkZYdasWXnqjYqKQo0aNRAXF1dgdO6YmBiMHTsWf/75JxQKBdq3b49Ro0Zh2rRpSExMxNq1a1GrVq0i+/C+2bVrFzp06AALCwuMGTMGQ4YMgb6+frHqGD16NCQSCRYuXFjs9s+ePYsOHTrg4MGDqFOnTqF509PTERUVleuKjIzE8ePHcf/+fVhbW+PZs2eIj4+HpaUlbG1tYWVlBSsrK1hbW+f529zcHBoaGsW2+U1IIjw8HPb29ggNDcWSJUuwceNGtGnTBlNatkS1wYOB1NTiV6yrC5w8CdStWyr7yhIhfB87Pj7Axo2lr6d3b+C330pfT3GIiQHs7EolfFnq6ki/fx/lKlUCAMjlcjx79gwVKlQosExYWBhatWqF3r17Y/r06SoJ06lTp9CvXz+cOXMG8fHxhQpkXFwc7t+/j4yMDKipqRUqkDKZDCYmJti/fz8WL16Mjh07YtOmTdDS0gIA3L17Fy1btsSYMWMwYsQIAMC1a9fQoUMH+Pj4YMyYMXBwcMDNmzdhY2OTr+2Ojo7YtWsXatSoUWgfFQoFfv75Z8ybNw/Pnj1DzZo10bRpU2zatAlDhgzBlClToK2tXeR79a65fPkyAgMD8e+//yI6OhopKSnQ1dUtUV0RERGoXbs2wsLCYGxsXOzyf/31F0aMGIGzZ88W+h3Mj6SkJFSpUgUHDhyAi4sLxowZg+zsbIwZMyaXOL4tllFRUXjx4gVMTU3zFcU3/7a0tISmpma+7Z89exZfffUV+vfvj0WLFsHAwADx8fFYvXo1nGfMQKv0dJTocGeJJOcs27/+Kknp/wQhfB87bdsCe/aUuporNjZY+fXX0NPTK/LS1dXN87qg0USRdOoE7twJSQm+hgqJBPs0NTGvfn1UrFgRtra2sLOzg5+fH9TV1fMtc/XqVXh7e2PatGkYPHiwym15enrim2++Qf/+/VXKP2HCBBgbG2P48OGFCmRYWBguXLgAuVwODQ0NJCUlwdDQEObm5pBKpbh37x6+/PJLNGzYMJdoqqmpYfr06UhJSUG1atWwffv2Am3p27cvGjZsiG+//Vbl/l68eBGjR4/G2bNnYWBgADMzM2hoaGDdunVo0KCByvX8l1y4cAGBgYG4evUqJkyYgG7dusHKygqlfaT5+vqiatWqmDx5conKL1q0COvWrcOZM2dgZGSkcrlJkyYhOjoa69atQ0JCAipVqoRr166pJKDZ2dmIjo4uUiBjYmJgZGSUryg+fPgQK1asAEno6upi9erV6NSpEySxsWCFCpBkZJTo/QCQc4D7kyeAmVnJ6yhDhPB97JTRiC+scWMc9vFBSkoKUlNTkZKSUuj1Zp60tDTo6OgUKZD5XbJHj/D1/PnQLcHXMFNTEx4AzmVlKe8ZGRkhOjpaOWJ6k2PHjqFHjx5YsWIFOnfurHI7//zzD3x8fHD//v0Cfy2/zQ8//ID4+HjMnTs33/S0tDTMmjULa9asQVBQEPz8/KCmpoaZM2cqR5fDhw/HoEGD4OjomK9oxsTE4MmTJwAACwsLWFhY5Du6vHnzJkJDQ7Fo0SKYmZnB1NQ03/cnP5KSkjBx4kRs2LABqamp0NTURI8ePfDzzz9DT09PtTfwTWJigOBg4MaNnAgThoZArVpAv34qPxTPnTuHwMBA3Lp1CxMnToSfnx90dHSQlZUFLS0tyOXykv8QA3Dr1i14enri8ePH0NHRKXZ5khgxYgRCQkKwf//+3O91Af1/0rw56rRsiZs3b8La2ho//PADbt++jd/KeBZGLpcjNjY2X4E8ffo0QkJCcv1w6NOnD9bXqPHxLqcUgBC+j50PYI1PoVAgLS2tSIF8+4qLi8Pu3bsxTFMTk1+8gI5CoXKbaRIJRpF4O6hM48aN0aZNmzwCe+nSJSxduhSLFi2Ch4eHUphVGa22bNkSXbt2xcCBA1W2b9WqVbh8+TJ++eWXPGnHjx/Ht99+CxcXFyxZsgRWVlbKtKysLNSoUQNRUVHYsWMHPD09C2xj3759mDZtGnr16oU5c+YgKCgI9vb2eUaXDx8+xMmTJ+Ho6IjY2Fi8ePEC+vr6hU6/vn3P0NAQGzZswIwZM/D48WNoaGhg/PjxCAoKUu0NuXgRmDMH2L8/5/Wb31epNMcVonVrYNIkoF69fKs4c+YMAgICcP/+fUyePBl9+/bNM/UqkUiQmpoK6dvhoYqJt7c32rZtW6xR8pvI5XJ07twZhoaGCA4OhuTSpUL7n5mRgbAqVVD9t9+QUasWKlasiAMHDrzTtVVHR0eEhYVBXV0dFStWhL+/P/r27QvjYcM+3uWUAhDC97FTButkCi0tnNm0CfEaGkhMTERiYiI8PDzg7OxchobmJiYmBs2bN0f79u0xa9YsSFauBMaOBdLSch6CBUCJBAptbTz090fD9evx4sULZZqamhr09PRQoUIF1K9fHySRkpKC27dv4/79+6hcuTJIqjRafX2lpaXh33//Re/evWFgYKDyNPChQ4ewd+9e/PXGusbLly8xbtw4HD58GD///DPatm2bp39btmzBd999h+zsbFy6dAmOjo4FvhdeXl7o2bMnfH19cezYMfTs2RPTp0+Hv79/rnVLkjA3N8eVK1dQvnx5KBQKJCQkFDj9+vrvN1+npaUpRVFPTw/37t1DQkIC1NTUUL9+fQwaNAi2tra5xFMpSitWqPTZQiLJEcEFC4AhQ5S3T5w4gcDAQDx+/BiTJ09Gnz59ChyxSiQSxMTEwKyUU2qnTp2Cn58f7t69W+C0eVGkpqaiadOmmCqToe2JEyp9tyVSKf7p2BGzX7zA/tci+Y6oXLkyQkNDla81NTUxYMAALI+IKJPlFHh7A7t3l76eMkAI36dAp07Azp2FP1QKQiLBbg0NtMvKgo6ODtTV1ZGRkYGlS5diyBsPn7IkKioKzZs3R/fu3XM7l1y6hOQpU6B15AiyFQrkck94PSr4+uucUUHduvj5558xbtw4pKWlAQB2794Nd3d3BAYGIjg4GDNmzMDz58+xdetWHDx4EBUrVsxjS0Gj1dfiOHXqVNSqVQv16tUr1mg2ISEBaWlpUFdXh66uLtTV1ZGUlARjY2M4ODjkK6L37t3DmTNn4O/vj/DwcFy6dAnz5s3LN++zZ8/g5eWF8PBw5XRcWFgY2rdvj8aNG+Onn37KJQ4dO3ZE9+7d0aNHjxJ9ZhkZGXmE8tGjR1iyZAmio6MB5Ewzy2QyJCcnIy4uDlKpFMO1tDAlPh7SYozmoasLLliAY1WqIDAwEM+ePcPUqVPRq1evIqeaJRIJHj16BHt7+xL18zUk0ahRI4wZMwZdunQpcT1J8+ZBY+LEYk3lp0kkCB8+HNV+/LHE7RZEamoqHj16hLCwMOV169YthIaGIjIyMs/66Jdffol/K1cWIz7BB8jFi4CHR4ldjZ9u3IjqvXsjOTkZAKChoYGLFy/CxcWlbO0E8OzZMzRr1gx9+vTBlClTlPdjY2Mxa9YsbNq0CZMHDkTW6tX4tlEjGJGAsTHg7Az07ZtrHSgpKQkWFhaQSCSoW7cutLW18ddff8HAwADXr1+Hl5cXkpKSsG3bNrRu3brYtl64cAFdunTBgwcPiu3NePHiRQwePFg5ggsPD0dgYCAqV66cr1Du2bMHZ8+eRdeuXaGlpYXk5GTs27cPxsbGsLKyyiO28fHxyM7OVk7XvhZEHR0dhIeHgyTc3NxgYmICPT09hISEICUlBd26dVPZcUnVdcCTJ0+iR48eSE1NRVJSEipUqIDx48fDp2pVlGvbFmolmI1IBeAllUKzYUM0aNAAFhYW+U7Dvr0Gp6amhps3bxbpwaoKO3bswJw5c/Dvv/+q5Pmbh1L8v6SuLiQl2AJAEjExMXj48CHCwsKU/4aGhiI0NBTx8fEwNjaGlpYWsrKykJCQgHLlyqFatWrQ1dXFoUOHAADq6upYuXIlBgwY8EEsp5Q1Qvg+FV5PJxXjP1m6mhrUFi+G1vDhOHv2LDw9PZGZmYnatWsjIiIC9erVw/Dhw9GiRYtSOQu8JiIiAs2aNcPAgQMxfvx4AEBKSgoWL16MH3/8Ed988w2mTZumnE6Ljo5GuXLlCq1z/vz5qFmzJlq2bIlhw4bhn3/+wfbt2zF27Fi8evUK3bt3x4wZM+Dt7Y05c+bA1NRUZXu9vb3x9ddfw9/fv9h9vXfvHho3bgwAGDVqFMaNG5evkJDE5MmTsWvXLhw+fDjXloQnT56gbt26OHz4MGrXrq28n5SUBHt7e1y/fh0mJiZ5RPTVq1dYvXo1jh07hqFDh8LExAR3797Ftm3b0KtXL5VHrQBU9uzV0tLCuXPncPnyZchkMjx9+hTbFAq0I0vkAq8A8KxePezu27fQ/ZWampq5xPDAgQPo2bMnnJ2d8xVKY2Njlb/LCoUC1atXx8qVK9G0adPid6KUMzEFbQHIzMxEeHi4UtTeFLiHDx9CS0sLFhYW0NPTA0kkJycjKioKWlpaqFWrFmrWrImaNWuiRo0aqFGjhtLz9Pnz57CysoKtrS2OHz/+v2n2mBjIbW2h/oYTWbERXp2C/4wVK8CxY6FITUVhqxL8/7WUdU5O2FiuHHbt2oVy5cphw4YN6Nu3r3ID7ebNm7F06VKkp6dj2LBh6NOnT5FCVBCPHz9Gs2bNMGzYMIwaNQrZ2dlYt24dAgIC4ObmhqCgIDg4OAAA4uLiUKVKFbx8+bJYbZBEYGAg5syZg6ZNm2LXrl3Q0tJCQkICpk+fji1btiAoKAj9+/cv8uF36dIldOjQAWFhYcUe7V2/fh39+vXDzZs3ERISgipVquSbTy6XY+jQobh06RL2798PmUyWJ89vv/2GBQsW4OLFi0o7li5dirNnz+KPP/4o1I4//vgDw4YNw8qVK9GuXTuYmJggIiJCZRf7zMxMlQTyzevRo0c4cuQIrDU0cCk2FsX3iXyjfXV1zOjbF5TJ8vUQ1tXVhUQiQWZmJjIyMpCSkoL+/fvDz88PJiYm+a5fvp5uVsWhx8zMDLt378aePXsKXG/buXMn1q9fjwULFii/vwDKbO199/LluBMbm0vcoqKiYGtriwoVKsDIyAjq6upIT09HbGwswsPDkZ6ejho1aigF7rXImZubF9nmqVOn0KBBA+Vnef78ecyePRtr4+PRKiMDamUs4u8LIXyfACSxcuVKLFu2DEt694bmggVwT0lBemZmLk9JSqXITE9HXP36sPnpJ8jr1MHgwYNx8+ZN7N+/H8bGxoiOjoaFhUWuuk+fPo2lS5fi+PHj6NOnD4YOHZr7P3kRPHz4EM2aNcOYMWMwdOhQ7Ny5E5MmTYK1tTXmzp2Lem958V29ehV9+/bF9evXi/U+REZGwsvLC9bW1rhy5Qo2b96M5s2b56r39eht+fLlhZ6u0b59e3h6emLYsGEqt5+WlobAwECsXbsWQUFBGDx4MLKysvIV2aysLPTp0wfPnz/Hrl27YGBgkG+dJNG5c2dUrlwZc+fOhUKhQNWqVREcHKwcURbG5cuX0bFjR/Tv3x+nTp3CuHHjSjTtWxwyMzNxqm1bND50CKXxrczW1MT51q1xpmFDlUQ3JSUFUVFRUFNTUzo6vX1JpVJoaGhAXV0dEokEJKFQKJCVlYWsrCykp6crRf7Vq1dITExEZmYmzMzMlCekmJubw8zMDGZmZjh37hz27t0LLS0tdOrUCQEBAXBwcID6woWlnh5Mk0iwtUYNXPP0hFQqhVwuR0JCAiIiIhASEoK4uDg4OTnlETkbG5uSTc0CCA0NhZOTE7Kzs3Ot9/05fjy6LFv2yZzcIs7q/Mi5e/cuGzZsSIlEQgMDA7q5ueUERo2JYYC+PhPatSO9vZnRvTt/srPjzjVr6OzsrDyFXaFQcNSoUaxduzajo6MLbSs8PJwTJkygTCZj27Ztefjw4SJPo79//z7Lly/PFStW8MyZM2zUqBGdnZ25b9++Asvu3LmzwPMlC+LevXu0t7fnnDlzqFAoeOLECZqbm+cc3PwGcrmca9asobm5OYcNG5bvwcVXrlyhtbV1sQ4GPnLkCB0cHNitWzdlBG8DAwNlJIA3SUlJ4ddff822bduqFDQ1JiZGGbtv7969dHV1LVYUgKioKDZs2JDVqlXj2LFjVS5XKsroHFb27l2sZnV0dPjnn38yIyODL1++ZEREBO/evcvLly/z1KlT3L9/P7dt28bffvuNK1as4IIFCxgQEMDx48fzu+++Y9++fdm1a1d+/fXXdHd3Z926dSmTySiVSmloaEgtLS0CoKampvLcVLx1QLqamhq3aGmVSf93lCtHHR0dOjs7s2fPnpw9ezZ37tzJ0NDQIiOElITs7GxlH19f1tbWOd+3T+isTiF8HzEBAQGUSqXKw5mdnJxoY2PDzMxMnjhxggC4a9cuklS+btCgAb/44gtu2bJFWY9CoeD06dNZtWpVlQ7oTUlJ4erVq1mzZk1Wr16dK1asyPc097t379LW1paBgYFs3749y5cvz+Dg4CL/wy5dupT+/v4qvw///vsvLS0tuXbt2lz3b9++TXt7e86aNSuPUMTFxXHgwIG0srLihg0bcqV36NCBixcvVqntuLg49u3bl+XLl+fu3btzpdnZ2fHhw4e57iUkJNDNzY29evViZmamyn18HbvP09OTwcHBKpd7TXp6Olu2bEk9PT0+evSo2OULYt26dTQzM2O3bt24fv16PnnyJCehjCJvsJg/gHR1dfP82CktCQkJNDExUcZ0lMvlfPXqFaOiotimTRsCoIaGBtXV1Wltbc06derwQBkJX5K7e7G+J6VBLpczICBA+TwBcgIUnz179n+ZRHQGwftmzJgxykCiAJQP+bS0NFpaWhIAe/bsSZJcvnw51dXVqampyUaNGrFatWp5BGj+/Pm0t7dXKY4c+b+ozh07dqSpqSnHjBmjfNCHhITQ0tKS7u7ulMlknDdvnsojqLFjx/KHH35QKe+BAwcok8n4999/55seGRlJV1dXDhgwIN8HyPnz51mnTh26u7vz1q1bvHbtGi0tLYsciSkUCm7atImWlpYcPnx4vhEAXFxcePnyZeXrmJgYurq60t/fv0Qx7zp16kSpVFriEDWJiYnU0tKihYVFmQWd3b17N6VSqXIUBIAODg7vbcSnr6/PlStXlknfyJyQPffu3WOXLl3o4eHB0aNHs3379qxZsyZ1dXWpra1NdXV11qpVi2PGjOG6det48uRJpnTs+F76X1Lu3LnDihUrUiKRsFy5cnR3dycAfvHFF3kzX7yYE8osn9iPynh8nTq9vzifKiCE7yOnU6dONDAwoJqaGrW1tfn8+XOOGzdOOV0hlUqZkpJCX19fpUDq6OjQ3Nw837hyK1eupI2NDUNCQoplx6NHjzh27FiamprSzc2NOjo61NXV5dixY4uMRP423bt3LzLCOUn+/vvvNDc355kzZwrN9+rVK7Zu3ZpeXl75ClR2djaXLVtGmUzGypUrFxkG5vHjx2zdujWdnZ15/vz5AvM1bdqUR44cIUlGRESwWrVqnDx5comDlQ4aNIgGBgbcu3dvicqTOXECFy1aRHNzc65atarY5bOysnjlyhUuX76cvr6+dHBwyDXFZ2RkxBMnTuRE4i5luCy5jk5ObMFiYGhoqPJo/TUvX77kxYsXuWXLFn7//fccMGAAmzZtygoVKlBLS4uVKlWim5sbtbW1OWPGDG7bto1Xr15lYmIiU1NTmZ6ezufPn/Po0aNcsmQJBw4cyGUVKjC1tKInlRa7/8UlMzOTY8eOVf4o9vLy4suXL5mdnc0ePXrwwYMHBRd+K/Yje/fOeS0isAv+S/755x9aW1szJiaG3t7ebNWqFe/fv68MVgqA2tra3LBhA2vWrEn1/w/YamxszK5duxYYW27Dhg20tLTMNVpRhYyMDI4YMYISiYS6urqsUqUKV61apQz6qioNGzbk6dOnC82zaNEili9fnrdu3VKpzqysLA4YMIB16tQpMMr68ePHqaOjQ2tra27dujWPQGVnZ3PRokU0NTVlUFBQkVNQnTp14p9//sn79+/T3t6e8+fPV8nW/EhMTKSxsTG3bt2qjN1XEl5HDr9//z6rVavG7777rtB+REREcNu2bRw7dizd3Nyop6dHJycn9u/fn6tWreL169dpbm5ObW1tNmrU6H8/csogTmQqwHr29ioF/n2NiYlJnh8u2dnZfPz4MY8ePcrVq1dz4sSJ7NatG7/44gsaGRmxXLlydHFxYefOPf2ViQAAIABJREFUnTlu3DiuXLmShw4dYlhYWK73pn///pw4cSJPnz7NFStWcOjQofTw8KBMJqOJiQmbNGlCf39/Ll++nGd37qRcW7t0wvcfx8m8ePEira2tqaamRl1dXa5bt65MIsh/DAjh+0jJyMhgjRo1uGXLFmZnZ7NixYo8f/48X7x4wTlz5tDR0ZFSqZRVqlThvHnzOGrUKAYEBLBevXrcuXMnSdLDwyPPuthrtm/fTjMzsyJHU2TO2sDmzZtpY2NDLS0tLly4kAqFgkeOHGG7du0ok8k4fvx45RpJUdjY2DA8PDzfNIVCwfHjx7NatWoF5ikIhULBoKAg2tnZ5Tui7datG+fNm8eTJ0+yZs2abNGiBe/du0eSvHr1KuvWrcumTZuqHJ3cz8+P06ZNo7W1NVevXl0sW99myZIl7NatG0ly1KhR7Nq1a4keUm8Gpk1ISODXX3/Npk2bMjY2likpKTx16hTnzZvHzp0708bGhjKZjN7e3pw9ezYPHz6crzPQsGHDOGLEiLw/ojp2LHotqJA1oqQWLejl5UV1dXXq6+vT39+/wKCyycnJvHHjBg0NDdmiRQv6+/vTy8uLlStXpra2Nm1sbNikSRP269ePs2bN4qZNm3j+/PkCo6EnJyfzwoULXLduHUePHs1WrVopo9bXrVuXfn5+XLx4MQ8fPszIyMhcdSgUCm7evJn7dHQoL6noSSQ504X/Aampqfz222+poaFBXV1d1qpVS+XljU8FIXwfKUFBQWzTpg0VCgV3797NevXq5Up3d3enm5tbnnKLFi3iwIEDSZKnT5+mvb09MzIy8m3j9frZ4cOHC7Tj6NGj/OKLL1itWjUaGxsrRfVNwsLCOHr0aJqYmLBTp048ceJEgQ/tzMxMampq5jsSzczMpK+vL+vXr1/iEQ+ZM6I1Nzfn8ePHlfdCQkJobm7OV69eKdtauHAhTU1N2bBhQ8pkMq5du7ZYYtOzZ0/q6enleNmWArlczsqVKyt/hKSlpdHJyYmbNm0qdl2RkZE0NjZmVlYW79y5w3Xr1tHFxYVaWlqUSqX88ssvOXz4cG7cuJFhYWGlGwFcuFB8L8DXl66uco0oIyODEydOpJGRESUSCatUqcKBAwfSx8eHjRo1ooWFBXV0dFi9enVqa2vT1dWVS5Ys4Z49e3j79u1C10TT09N5/fp1bty4kZMmTWLbtm1ZsWJFSqVSuri48P/YO++oKM+tb8/QO8IUGHoXFCkqCHYBUZBiwYa9xK7Ye0GjsZeIRo0m0cSu0WgUNbbYQ+yaRKOxxGgi1iiCtJnr+4PDcxxngAHxnJzv5VqLxZpn5mlT7n3fu/x2165dmTNnDnv27OHu3bskJCSwbNmyEo93/fp1IiMjCQgI4PKaNZVy/5XJ0aNHkclkGBgYYG5uzuTJk/9jyTP/JKoM3/8gN27cQCKRCCuo6OhojUy26tWrk5ycrHVfIT35X/uuWLGixHMdP34cmUymYdAuX75My5Yt8fDwYMaMGchkMo2sxrfJysrik08+wdfXl4CAANasWaORRHL37l2cnJw09s3OzqZVq1bExsZqzSAtL4cPH0YmkwnGo3PnzsyePVvtNQcPHsTV1RUXFxecnZ1LTKDRxoEDBzAzMxNWae9Cenq6RgnDuXPnkMlk3L9/X6djPHnyhPT0dKZOnYqpqSlWVla4ubnRqVMnFi9ezLRp05BIJFonLhWhsLCQ9evXs7xWrXIP/gVGRhzp0IERI0aQkJAgJJLIZDJ8fHywtrYWXPYpKSncu3dPSBZydnZmyJAhGtdTbOi3bdtGamoqSUlJ+Pr6YmJiQo0aNejQoQPTp0/n66+/5tdff9U68YKi8IK7u7vG89nZ2UyaNAmJRMLixYv5+eefGTBgANkLF/4jSgBevHhBcnIyhoaGWFtb4+joqJM35/9Xqgzf/xgqlYpmzZqxaNEioGiGKZfLNWa1UqmUadOmaT2Gt7c3Fy5cAIpKAZycnEqdFZ89exY7Ozs2btzI3bt36d69O3Z2dixdulQwIPv27dP5HpRKJQcOHCAuLg6ZTMb48eOFNPjjx49Tv359tdc/efKEsLAwunfvXqmz0ytXruDs7MzIkSORyWSCG+3Jkyf06NEDFxcX9uzZAxQZQR8fH+Lj4zVKFN5m27ZtyGQyRo4cSf/+/d/5Olu2bMkXX3yhsX3GjBlER0drrMry8/M5d+4cy5Yto2vXrnh7e2NlZUVERAQTJ04kIiKCeVqSJjIyMnB0dGTmzJkVXundv3+fKVOmYGtri1gsRiqVwiefUGhiQmEZA36hSES2SMRgfX1atGjBvHnz+Prrr7l06RIvXrxQO88ff/xBUlISRkZGmJiY0K1bNx49eoS7uzudOnVi9+7dfPTRR3Tp0oXAwEBMTU3x9PQkMTGRSZMmsXHjRq5cuUJubm6577Fhw4Zs2rRJeLx7927c3NyIjo5mwIABuLi4CHH2hw8f8nz2bLJFIlT/pRKAXbt2Ua1aNYyMjJBIJHTp0kWry/r/ElWG73+MtWvXUqdOHWHGOXToUCZOnKjxOhMTEzZv3qz1GCNGjGDGjBnC47i4OD7++ONSz3vy5EksLCwwMzNj8uTJvHjxQnCblOYKLYubN2+SkpKCjY0NSUlJTJ48mY4dOwrP37t3Dz8/P8aMGfNeAu/379+nWrVqhIaGkp+fz/r167GzsyMlJUVwexaTm5vLrFmzkEgkfPjhh1oHzc8++wyFQsHFixfZuHHjO6/4fv31V60TGyhaxYSEhDBz5ky2bt3KyJEjadCgAebm5vj7+9O3b19Wr17N1atX1UpX1qxZQ5cuXbSe78GDB4SGhtKxY8dyJyU9ePAAPT09taLusLAw2rdvTzNLS3bq6fFaJCLnLQOQIxZTYGCAsnVrOHuWY8eO4e3tTfv27UsUVVCpVDx48IB9+/YRGxurVtZjZGREy5YtGT16NGvXruXcuXPlvpfS2L17N8HBwdy+fZuEhAS8vb3Zt2+fkF1dfB1NmjQBipJilnbv/h8vAcjMzCQ+Ph4TExNkMhm2trY6ZUv/X6DK8P0P8ejRI+RyuZBt+fLlS2xsbP5dNPwGYrGY69evaz3O4cOHCQ0NFR5fuHABhUKhdXDIyclh7ty5SKVSOnbsiJOTE4sWLeLgwYPIZDK1ONm78PLlS9LS0pBKpcjlcj7//HPOnz+Ps7MzCxcurJRzaOPXX39FIpEQFhaGTCbD39+fjIyMUve5c+cOiYmJeHt7c+DAAWH7woULcXV1FRJi9u3bR/Pmzd/p+oYOHcqkSZOEx1lZWXz//ffMmTOH1q1bI5PJEIvFREZG8tFHH3H48GGN1dHbXL9+HVdX1xKff/36Nd26dSM4OFjrdysrK4vLly+zY8cOFixYwMCBA2nRogVeXl5qA7+hoSF9+/YlLS0NKysrbt++jSozUyMF/lSbNvR/K5EjJyeHsWPHIpfL+eSTTzh69CjLli1jwIABNGzYEBsbG+RyOREREQwdOpRVq1axbNkywQDK5XJmzpxZosvyXXj9+jVyuRxLS0u1CdDx48cxMDBAJBJhYWHBtm3buHjxInZ2dv9eYf2rBOCAvT33goLeSwmASqXiyy+/xPJfqi/u7u40bNhQ5+Sy/wtUGb7/Ibp27cqoUaOEx8uXL6ddu3Yar3vy5AkikajEIum8vDyqVavGw4cPhW1t27ZVS7cvLCzkiy++wNnZmdatW3Pt2jWgSLbM0dERMzOzSiuCfpMBAwYwcOBAwsLCEIvFJCQk6BzHqghdu3alZcuW2NraUqdOHerUqaP2vpTGnj17cHd3JykpiWHDhlG9enU1Q/HDDz9Qt27dCl/b8+fPsbKyYsGCBfTr14/AwEDMzMwICwtj+PDhbNq0iTt37vDxxx8THh6u8yCvUqmQSqVajVrx8w8ePGDQoEFYW1vTq1cvunTpQnh4OHK5HFNTU2rUqEF8fDwpKSksXbqUPXv2cO3aNWbNmoWLiwumpqaYmJiQn5/P2LFjGT58eInX8+eff1KtWjUePXrE6dOnWb16NSkpKURGRmJra4uenh42NjZ06dKFpUuXcuTIkRJXgkFBQcTGxtKzZ09BUqx169aVNugfPnxYiFG/6ZLPz8+nc+fOBAUFYWpqKtTPRkZGsnz5crVjnDt3DicnpxKTyt6F33//naZNm2JhYYGjoyO2trbMnDnzvcib/S9TZfj+R/juu+9wc3MTEjtUKhV+fn5aV1wHDx7EwMCg1OMlJSWpxY2uXr2KXC7nxYsX7N27l1q1alG/fn2NAPiePXuQSCR4enoyevToSnc/tmrVikmTJiGVSlm9ejVDhw7FxsaGjh07curUqUo93zfffIO+vj6NGjXi5s2bqFQqUlNTcXd3Fwx9Wbx69YqQkBD09fWZOnWqWgzy119/LVIx0ZHHjx+zZ88eJk+eTFRUFKamppibm5OcnMzSpUvJyMjQ6l5VKpXCik9XEhISWLhwIXv37mXp0qUMHz6c+Ph4atasiampKTKZjLCwMJo2bYqZmRm9e/fm+PHjPHjwoMQJ1YYNG3B2duaPP/7g1KlTzJ07l6ysLCQSiVpcNCcnh/Pnz7Nu3TrGjBlDbGwsxsbGGBsbU7duXXr27MmCBQvYv38/f/zxB7m5uXz44YdIpVI++eSTUlVv6tatS0xMjPC+rFy5EhcXF8RiMTVq1GDnzp06v0dv8ueff5KcnIyLiws7d+4kNzcXR0dHzp07R15eHm3atCEmJoacnBwOHDjAggUL2LNnD35+fhoTko4dO7JgwYIKXUdJKJVK0tLSMDc3x9TUlODgYLy8vMr0Xvxfpcrw/Q+QnZ2Nh4cH6enpwrZDhw7h7++v1RAsXrwYKyurUo+5du1ajdVidHQ07u7u+Pr6snPnTo1jf/PNN8jlcjIyMnj69CkhISEMGDCgQvJbJeHk5IStra2aIsqLFy9YsmQJnp6e1KlTh3Xr1lUoKaGY7OxsxowZg4mJCYmJiRr3+fnnnyOXy8ssos/Pz6dr1640bNiQ8+fP06JFC2rWrFmkXEKRa9rW1lbrvnl5eWRkZLB06VKSk5Px9PTE2tqaqKgoJk+ezK5du3B3dy/zGoq5d+8eMpmMixcvAkUToydPnvDjjz+yadMmZs6cSe/evWnSpAnOzs7o6+tjZWVFdHQ0AwcOZP78+ezYsYNLly5p1Mpdu3YNb29v7bV6/+LIkSPIZDKuXLmido8TJkygXr16TJ48mdatW+Pt7a0mujxr1ix27drFpEmT6NWrV6n3+PPPPxMWFkajRo0Ed/Lb1K9fn8jISI3tFy9epEmTJoK6zOjRo3WSfisoKGDp0qVIpVLGjRunllG8YMECkpKSiI2NpU2bNmrfyfz8fHx9fYXkqGJu3bqFra1tme7o8nDt2jXq1q1LtWrVcHNzw9nZmd69e2vEqKv4N1WG73+A8ePH06lTJ7VtiYmJJWoSFmeWlUZmZibW1tbk5eVx8+ZNOnTogFwux8LCQmuN3Pbt27Gzs+PcuXPCthcvXtC4cWO6du36zrEUlUrF7NmzEYvFnDlzRutrlEole/bsITo6Gjs7O6ZMmcKDBw/KdZ7vvvsODw8P4uPjsbGx4dmzZ1pfd+DAAWQyWYk1eK9fvyYhIYGYmBghNqpSqdi+fTvOzs507dqVe/fuoa+vT2FhIXfu3GHz5s0MHz6csLAwoXC4X79+fP755/z8889qE4j09HSCg4NLXeEWFBRw+/ZtDh06xKpVq2jVqhVWVlYEBQVhbW2NlZUVwcHBJCUlMXbsWFatWsWhQ4e4ffs2p06dIiAgQOf37dmzZ0RHRxMVFaUhQXfx4kVsbGyYMWMGH374IR07dqRmzZoYGxtjaGhIkyZNmDp1Klu3buWXX37Rmpl79+5dpFJpmd+jwsJClixZgkQiYe7cuRqvb9q0qdb61WKysrIYOnQolpaW6OvrEx0dXaI8X7GOa9OmTbW+5q+//sLQ0JD4+HiNe1q+fDlRUVEan9+QIUMYP358qfeoK/n5+Xz44YdYWFhgbm5OREQEcrmcbdu2Vcrx/3+myvD9w7l8+TIymUwt7nTnzh1sbW1LnNG1bNlSp9hSnTp1SExMFLIUX716Rffu3TXKIDZv3oy9vb2wmniT7OxsWrZsqTHjLQ9KpZKUlBT8/PwwNTXVyZ35yy+/MGjQIGxsbEhOTi5VMxOK3IjdunXD1dWV9PR0+vbty+TJk0vd5+LFizg5ObFgwQK1a3r58iXNmjWjY8eOWuM0f/75Jx07dsTMzAw9PT2kUin29va0bt2aOXPmcPTo0TJn4zExMXzxxRe8fPmSS5cusWPHDubPn8+AAQOIjo7G09MTIyMjnJ2dadKkiaBIEhISQrdu3Xjy5Emp72N+fj4WFhZa2yaVtk/fvn1RKBSMGjWK7t27U6tWLcRiMTKZjLi4OMaPH89XX33FxYsX2bx5M2FhYTofv27duoK2aVncunWLyMhI6tSpw6VLl4Tt0dHROp9z48aN+Pj4IBaL8fDwELpePH36lH79+mFvb6/RuaOYFy9e0KBBAwICAhg4cKDac3///TdyuVztuqDoO1itWrUSJfPKw9mzZ/Hz80Mmk+Hl5UVwcDDNmjXTqbtKFVWG7x9NYWEhoaGhGnJX48aNY8SIESXuFxAQQOvWrUt8/tWrV8yYMUNQp3j0RkbZb7/9hkQiEWb169evR6FQqLmw3iY3N5d27doRHR1d7rTxvLw8OnfuTKNGjTh16hS+vr7l2v/58+csWrQId3d3QkNDWb9+vZoxUqlUfPXVV9jZ2TFixAiysrKEiYMu4tn37t3D39+foUOHUlhYyJMnTwgJCeGDDz6gsLCQwsJCrl69ypo1a+jbty+1atXC3Nyc+vXr06NHDwwNDfHy8lJv7fIGSqWSBw8ecPz4cdauXcuUKVOIi4vDwMBA6ANXs2ZN4uPjGT58OEuXLmXv3r1cv35dq6vu0aNHKBQKnVykzZo1U3Ofv/mePXz4kEOHDrFkyRL69u1LeHg4VlZWKBQKIQ44YMAAQcBAGw0aNCiXas3s2bM1jEhpqFQqPvvsM2QyGZMnTyY3N5e4uDjtHQVK4caNG8TGxqKvry8o2HzwwQclTgqK3fyDBg3iwYMH2NjYqP2Gxo4dS58+fTT2mz59utbt5SE7O5vRo0djaWmJpaUlbdu2RSaTMW/evEoNOfz/TpXh+weTlpZGo0aN1L7QOTk5yGSyUlXTFQoFI0eO1Nien5/PypUrUSgUQpGvp6enxoy2b9++TJgwgbVr1+Lg4KBTp4aCggK6d+9Oo0aNdI5fvHz5kubNm5OYmEhOTg7p6ekVTv8vLCxk9+7dREVFYW9vT2pqKhkZGURHRxMYGMiPP/4ovLZfv35MmDBB52M/f/6cZs2aCdqPbdu2ZcKECURERGBlZYWXlxddu3Zl2bJlnD17Vs3wBgQEMH36dORyOdHR0Xz00UekpKQQFxdHjRo1MDU1RS6XEx4eTpcuXZg6dSpRUVF069ZNQwNSV3bt2oWHh0eJupbFTJ06leHDhwuiy4MHDxbaSL0tunz8+HG1icKxY8cwMjIiPDxc64D7ww8/4OrqWi4X+I0bN7C3ty/3AP7gwQMSExPx8/OjadOm1KpVq1z7Q5FnpX79+jg4OGBtbY2enh4NGjTQSA7JzMwUWhAVfzb9+vVjypQpANy+fRtbW1uNVV12djZyuZxffvml3NdWzJEjR3B1dcXBwYHq1avTqlUrfH19BTGKKnSnyvD9Q7l37x5SqVQju/Dzzz8nNja21H3Nzc359NNPhccqlYodO3bg4+NDREQEZ/9VJKtSqXB0dNSo97t79y7m5ubY2dkxc+ZMnTsgKJVKBg4cSN26dcvU0szMzKRu3br07dtXGBxXrVr1zjNigEuXLgnlEMHBwWqrrd9//x1bW1seP35c5nFyc3M5c+YMS5YsITY2FrFYjFgspmnTpkydOpX09HTBpfj48WMyMjLYuHEjH374Ib169aJx48YYGRlhYGCAu7s7Li4umJiYkJSUxPbt27l8+bKGy7O4C8O7uqx69+5Nv379hMdZWVlkZGQIosvR0dFIJBL09fUJCwujb9++gujyX3/9VarBVSqVJCcn06JFC2rXrk1ycrKG9FzHjh0FdaHyUKtWLZ0Tet5EpVKxdetWTExMsLGx0VnW7uXLl4Jyz8qVK4W0/7179xIQEIBYLMbR0ZHFixfzxx9/4Ofnx5QpU9Tenxs3biCVSsnKyqJjx45Mnz5d4zyffPIJCQkJ5b4vKJp49e3bFxsbG6ytrenZsyeurq4MHDiwUgvz/y9RZfj+oSQmJpKamqq2TaVSERwcrNU99SZ6enpCzOvkyZPUr1+fgIAA9u3bpzGg9e/fX6NAfNmyZYIUlL6+frkKyIu7J9SsWbPEWMbt27fx9vZm8uTJatczadIkrYNGeTh//jy1a9cmMjKS8+fPM3/+fFxdXQkLC2Pjxo3069ePcePGab3uW7dusWHDBoYNG0ZoaCiupqYsdnDgmIsL+wwMyPDxYX1gIL4SCX379qVdu3YEBQVhZWWFtbU1tWvXpn379owbN45PP/2Uw4cPEx0drebuu3jxIuHh4YSGhqolChWzdOlS2rdvX+H7z83N5dKlS6xevRpra2tCQ0MF0eXg4GC6devG3Llz2bNnDz/99BNmZmbljs2OGzeO8PBwcnJyyM7OplOnTtStW1eot7x7926FMxdTU1NLrfkri+TkZCwtLXF3dy9VUajYUDo6OtKzZ88S6wIfPHhAx44dMTQ0RCwWExgYqLXOs127dqSkpODk5KRhdAsLC/Hw8KiQQd+5cyf29va4ubnh5+dH3759sbe3L5dubBWaVBm+fyA7duzA19dXY0A6deoUXl5epbqCXr9+jUgk4ty5cyQkJODi4sK6detKLGDdvXs3zZo1Ex4vWrQIfX19jI2NEYlEGBgYaNV1LA2VSsXMmTPx8vLSKBy+dOkSjo6OpKWlaezXrVs3rZqUuvDq1StGjx6NXC5n7dq1aga1sLCQnTt3Eh4ejlgsZvz48dy8eZODBw8yc+ZMQTNUoVAQERHB1JgYLri5kaevz+u35LVe6+mRKxazS1+f1f37c/bs2VJjhb169WLNmjVq25RKJZ999hl2dnYMHjxYiCUVd2HQZYB8U3R52rRptGvXTkN0uXfv3tjY2JCRkVHi51+7dm1OnTqly1sMFE2KfHx81FbMxRm5jo6O/PDDD4waNUqrq10Xrl69iouLS4XrNQcOHCgkMLm4uNC7d2+NWN2NGzeIjo7G39+f48ePl3nM3377DRcXF+Lj41EoFIIn4U3DmpGRgZGRkcZnDbB161bCw8PLdU8PHz4kKSkJOzs7bGxsGDRoEKGhobRo0YK//vpL5+NUoZ0qw/cP4++//8bR0VHrD7Jz585ldpfes2ePIA48f/78MmuVsrOzsbS0VEsSGTVqFKampohEIsRiMXPmzKnQvSxZsgQXFxeh5ur7779HJpOxZcsWra9v0qSJzll9b3LgwAHc3d3p0qWL1pl7YWEhly9fpmnTpri5uWFhYYFIJMLMzAw3Nze8vb2xsbHBzMyMGQoFr/X1y+yjphSLyRaJuPCGO1EbI0eOLLEB7dOnT+nfvz/29vasW7dOawmDUqnk1q1bguhycnIyAQEBmJiY4OXlJYgub9q0iatXr2pkmY4cObLU3n0pKSk6f747d+5EoVBw69Ytrc/v3r0biUSCubl5hZVSVCoVPj4+ajHZ8jBixAgcHR2BIrfxoEGDcHBwYOfOneTk5DBlyhQkEgkLFizQSfD82rVrODk5qZUOnTx5knr16gnZrNOnT2fDhg1YWFhodElRqVSEhIToXDivUqlYu3YtEokEb29v/Pz8mDp1KlKplI8//rgqgaWSqDJ8/zAGDRok9Mt7k2JZp5Iyzf7++28mTpyImZkZBgYGJdanaSM2Npbk5GS8vLwEGavTp08jkUgQiUSMHTu2YjdDkWizg4MDixYtQiaTlWrYPDw8dG7yCkUZjF27dsXNzU3oDpGTk8OxY8eYOHEiUVFRODo6oq+vLwgnm5ubExAQQLt27YiKikIikVCrVi1WrVpFQVpauVvIZItEHC7FNTljxgytIuJv8uOPP1KnTh2sra3p3r07CxYsoFevXoSEhGBubo6zszMxMTGMGTOm3KLLZfXue7MxbWmcPn0aqVQqxIdLYty4cZibmzN69OgKy2SNHz9eqztaFyZMmIC9vb3atmPHjuHg4IC5uTlxcXE6x08vX76MQqEQyhze5unTp/Tp00eYJPr5+VG9enW1ScbRo0fx8fHRyWDduXOH5s2b4+rqikQiYfjw4bRr1w5/f/9Ss6qrKD9Vhu8fxOnTp1EoFFqNVmpqKgMGDNDYnpuby5IlS5DL5fTo0YMPPvgAhUJRrvPGx8djZWWloYn57NkzatSoURRzycyEuXOhS5ciceEuXYoe6yCu26dPH/T09DRmw2+iVCoxMjLSSJJ4G5VKRWZmJlOnTsXKyoqwsDBBcaZ4ACqunSsuO/jqq6/o0qVLiX3atm/fTr/gYLIr2C08RyxmYefOWge3tLQ0jRT9x48fc/ToUdLS0ujfvz8NGzbE0tJSEHYODg5m6dKlnDp1qlLax5TWu6+4MW1pA/Ovv/6KnZ0de/fuLfU8BQUFuLm5ceDAASIiImjZsmW56gSLOXv2LF5eXhVyd06fPr2oFdK/+P3332nTpg0eHh60b98euVxeYm3e29dgZ2dXonfiTebMmUNAQACurq6IRCKcnJzYvn07UDSpfDPRTBvFRfk2Njb4+/vj6+vLJ598grOzMykpKTopzFRRPqoM3z+EvLw8/P39tf7Q8vLyUCgUXL16VdimVCrZuHEj7u7uxMTEcPnyZQDatGmjczq3SqVi2rRpeHl5YWtrq32G/uOP0KZNUdsUExPt7VTatCl6nZbjp6b1FUxIAAAgAElEQVSm4uHhwcqVK5HJZIKc19v8+eefyGQyoKjs4rfffuO7775jxYoVjBkzhrZt2xIQEICpqSl6enqC5JahoSGurq4kJCSwaNEirl27pjGoFQ/upRYOt2lTdr+0Ev5UYjHfSyQkJSWpDVIvXrxg2rRphISEMGzYMCIiIrCzs6NatWo0aNCA/v37k5aWxtGjR+nbty8TJ04kMzOTnj174ujoyJYtWypNm7Sk3n0Anp6eJWbuPnz4EA8PD41aUm1s27aNBg0aAEWf4dChQ6levXqJ8mIloVKpcHV1rdAqZ968edjY2JCfn8/cuXOxtbUlNTVV+FzOnTtHYGAgMTEx/P7771qPcerUKa3Nl7Xx6NEjJBKJkBk9a9YsqlWrhp6entDGq7QYcLEMm6+vL1KplNGjRzNq1CgcHBzK1eOyivJRZfj+IcyaNYvY2FitA9OmTZto2rSp8PjQoUPUqVOHkJAQjhw5ovbakJAQWrRoUeb5VCoVEydOxN/fn4cPH1KrVi3NIutPPily/VWggWZhYSEDBw4kKChICMYfOnRIaFr74sULLly4wPbt25k7dy5t2rQRsvGMjIxwdXWlYcOGtGzZksjISIKCgjAxMUFPT4+AgADmzZvHyZMny1whQlHcZ9iwYSW/IDMT1dtGvZx/SiMjWtSujaOjI5GRkTg7O2Nubo63tzeOjo6C6PL9+/c1PmNtJQwnTpygVq1aREVFldheqjwUFBQQGhrKJ1qanPbs2ZMVK1ZobM/KyqJOnTpMnTpVp3OEh4fz9ddfq2379NNPkclk7N+/v1zXO2LEiBIbKZdGWloaZmZm1KhRgxYtWmitd83Pz2fmzJlaRa+LNUd1vd7BgwczdOhQtWO7uLhw7Ngx/Pz8MDY2Rl9fn8jISLXJRV5eHtOnT8fW1pbatWvj6+vLli1bqF27NvHx8WoF8VVUPlWG7z9FKa7CGzduIJFINBICfv75Z06cOEH9+vWFTtQtWrTA09OzxNWAq6trmV2/VSoVY8aMISAgQPiBTZgwQT0WVWz0ymMA/mX8Xr9+Tdu2balfvz579+7l888/Z9KkSXTu3JkaNWogFosxNjamVq1aJCYmMnLkSHr16kVgYCCpqal0794dX19fLCwsaNKkCd27d8fNzY1GjRrx22+/lettf/jwITY2NqVqeirnzCFPX/+dDF+OWMz6wEAaN26Mg4MDR48eRalUcvr0abXeh9ooqYShoKCARYsWIZFImDhx4jvXbF2/fh2pVKoRR9XWmLagoIDY2Fh69eql06rz9OnTuLu7a/UanDhxAoVCwcKFC3VewZ48eRJ/f3+dXlvMw4cPhczd7du3l3muX375hfDwcEH0et++feXqMXnt2jWkUqlGzWpx3WexFuyWLVuoXr06YrEYd3d3Jk2ahL+/P7Vr10YmkzF69GiWLVuGVCplxYoV76XhchXqVBm+900ZrkKViQnHpVI2vFW7lJWVhUKhwNLSEoVCQXJyMnZ2dqSlpZXax8va2rrUujuVSsXw4cMJDg5W+8GeOnWKwMDAf19zeY3eG+n+DYyN0dPTw97engYNGtCtWzdSU1P58ssvOXXqFN999x1SqZShQ4cyZswYGjdujLGxMba2tvTq1YuVK1dy6dIl/v77b0aOHImdnR1ffvllhQaE0aNHM3jw4BKfLygo4JSHxzsZPeGvWzegSKBYoVCQkZEhdDYoCaVSiY+PT6klDA8ePKBTp064urryzTffvNPAmJaWptG77+3GtCqVir59+9KiRQudMh8B2rdvz8cff1zi87///jtBQUH06NFDp5iVUqlEoVDo5CYtLCxk+fLlSKVS4uLiMDEx0emai/ddsmQJlpaWmJub61TeUExcXJzW9kKvXr3C1NSUHj16qG2/cuUKHh4eQhza2tqarVu30rp1a4KCgt5J1aWK8lFl+N4nOroKC0UiVG+5Crt164axsTFisRgDAwOmTJmiU0GwgYGBWlfwN1GpVAwZMoSQkBCNBJrCwkIkEklRVmebNmW7N0u5lx8cHdWuNTs7mxMnTjB//nySkpJwcnKiWrVqmJiYEBcXx3fffceAAQPUBpH9+/fj5uZG165dK+z2yczMLFUFJTc3l7Zt23JaKq0cw/dGduSuXbuQSqWsW7dOLdnibfbt20dQUJBOxuzQoUP4+vrSqlWrEksKykKpVBIVFaXWu0+lUiGTyYSM3hkzZlC7du0yJc+KuXPnDhKJpMzXv3r1iqSkJMLCwnQSah40aFCZPQaLM2IbNmzI1atX+eabbzA2NtbpuovZvHkzUqmU0NBQDdHrkji2bRuzbW0p7NxZw4Pz/PlzTExMSE5OFl5/6NAh3N3dady4sdDrsDihycHB4b00da6iZKoM3/viHVyF27ZtE9LvRSIRJiYmZUqAQdGgJhKJtBoKpVJJ//79CQsLU8sUzM/P5+bNmxw4cIDQ0FCSGjcmT0/vneNdm/+VzVi7dm3MzMwICQlh6NChrF+/nt9++01QSnF3dxdifFu3biUzM5Pk5GTc3d3LHRd6m3HjxpUoevzq1SuaN29O27ZtiwavSjB8uR06qJ0jIyMDOzs79PT0SjRsMTExfP755zrfU15eHrNnz0YikTB9+vQKZfy93bsPipKiNm7cyBdffIGbm1u5iqRHjBjBmDFjdHqtSqVixowZODk5lVkacfjw4RIFp589e8bAgQOxs7NTEyz47rvvMDQ01Pna165dK4iwaxO91uDHH1EmJpIrFlNgaKjhwcHEhF9r1mRss2bY2Nhw7do1evfujaOjI02aNMHLy4vDhw8zYsQInJycmDNnDkFBQYjFYhwcHFi4cGFVrd5/gCrD9z54B1chZmaEGRggFovR19dHLBYjEonYsGFDmae9ceMGYrFYY/uzZ89ITEykevXqpKam0q9fPyIjI9USSSIiIoiIiGCeVKr5gy7nX45YzFcBASxatIjTp0+XOjjfv38fX19f7O3tmTx5MnK5nNGjR+ustVgSjx8/xtbWVmvm3rNnzwgPD6dXr15FLr+5c1G+Y3JLrr4+k01M6Nevn1r27a1btxCLxaSkpGgMaDdu3EAmk+mUoPM2xWn6Xl5eFcr+++qrr/D39xc+m4ULFxIXF4dcLte5+zwU1Y/a2NgIq0Vd2bFjB1KptMT6QihyQ0ulUu7cuSNsU6lUrFu3Dnt7ewYOHKjhuThx4gT6+vo6XcOKFStwcnLSuN8HDx7QunVr/Pz81BO+/jWZVergwVGamLC0Rg0sLCyIiYlBoVAwfPhwzp49K9SRvjmZLXZnF3ei79SpU5VCy3ukyvC9D97BVYhYTFaLFty5cwdnZ2eOHz9epsK9Uqnk3r17TJs2DQMDAyZOnEinTp0ICQnB1tYWAwMDoXh31KhRLF++nP3793Pjxg21eOHz58/ZZGBQKauf4niXLmRkZCAWi5FIJFr1KyvCxIkT1USai/nrr78ICAhgxIgRKJVKMjMzmTZwIK/f9X5NTHh49SrTp08XpM927dpFYWEhCoWCOnXq0KlTJ7VVxLBhw8rVJUIb6enpeHp60q5du3IZH5VKRbt27YSV2rp169DX1+fkyZPlOv+CBQvo3LlzufYp5sqVK7i7uzN+/PgSi9379OkjxKyvXr1Ko0aNqFOnTonKLufPn0dPT6/Mcy9evBg3N7cSk6WKtTzt7e1JSUkhd8mS8osbiMUM0tPD3d2dY8eOkZaWhlQq5bPPPivRA6BUKlm4cKEgjRYUFPTOno8qNKkyfJVNZqZmEksFBtH0deuoV6+ecNjs7Gx++ukndu3axeLFixkyZAixsbFUr14dY2NjFAoFzs7OGBsbM336dL766iuOHz9OmzZtaNasmc4rqFO2tpVj+HRQA8nPz2fOnDlIJBL09PQICwujT58+FVb8KObp06fY2tqqrRSgKBbl5eXFjBkzePjwIaNHj8bGxoYhQ4aQ07LlO01WaNtWOE9eXh4bNmwQBKLt7e05dOgQ7dq1o3Hjxjx79oyXL19WaKWkjdevX5Oamip0JS8t+elNinv3bdmyBYVCgYmJSbkKzgsKCnB2di7TZVkajx8/pkmTJsTFxWmNYaenp1OvXj3GjBmDVCpl+fLlpX4/rl+/rtXr8SazZs3Cy8urxDq+N3ny5AnTYmPfSdxgWc+exMbGEhISUi5lotOnTwtZqhKJhClTpuj82VZROlWGr7KZO/edDV+BoSEf2drSsGFDGjZsiEKhwNjYmOrVqxMTE8OQIUNYvHgxu3bt4qeffhLS3Lt27YqPjw9QZFQ6dOhA8+bNy5UG/1NwcKUYvkcxMaVmBJ49e5bAwECio6M5fPgw7u7uZGVlERERQceOHXXOJtTG5MmTNdob/fLLLzg7OzNr1izGjBmDjY0NgwcP/nfiyzu6pylh8P/hhx+QyWRYWFgwYMAAevTogZ+fH6mpqSQlJVX4HrXx22+/ERMTg5+fn84p+Rs2bMDQ0JC5c+cSERFRZuePN9m8eTONGjWq4NX+m/z8fAYOHIifn59a3Z1KpWLz5s2IxWLatWuntSvC2/zxxx+IRNqHNZVKxaRJk6hRo0b5uqC3aVOme7OkP6VYzNciEePHj6/wd/r58+d88MEHghxhXFxcuct6qlCnyvBVNl26VIrh2GBgwMqVKzl69Cj37t3TaRXUuHFjGjduTF5eHm3btiUmJqbcyQ+Zo0aR847XnqevzwJ7eywtLWnevDkffvghx44d4/Xr12RlZTFixAjs7OwE6ajDhw/TpEkToGj1Eh8fT3x8fIUSN549e4atra1a1uPZs2eRyWTExMRoGrw3UC5bVpRdW16jp6Uo/E0SEhL47LPPmDp1KnZ2dvj4+KCnp8eqVavKfX9lUdx70cXFheTk5FIH+NevX9OgQQP8/f354IMPmDp1qs6u1/KKL+vCihUrkMvlHDp0SDDiNWrUICoqiuXLl+t0jOfPn2s1fCqVipEjRxIYGFi+LOFK8ODkisVsLKXUQ1eUSiVr1qzB3d0dsVhM9erVdZJUq0KTKsNX2cTFVYrhu1ZK7VdJ+Pj4kJycTEJCAvHx8eXuswagevhQoxVPuf9MTODRI54+fcquXbsYNWoUISEhmJiYCIXrW7duFdLfv/jiC7p27SpcQ35+Ph07diQyMlKjUWtZTJs2jZ49ewqPd+7ciZmZGebm5iUavJcvXzJ79mwMDAz4unnzCqvVlET37t2FzM3c3FxGjx6NkZERenp6fPDBB5Wix/k2r169Yvz48UilUpYsWaIRJ1YqlbRr146OHTvy/Plz3Nzc+PDDD3VewZ08eRJPT893dku/zYEDBzA3N8fc3Jw5c+aQl5fHjh07iIiI0Gn/vLw8RCKRWiJRcYPk0NDQcom3A5XiwSk0MmKeXF6p2ZpXr14lMjISPT09rKysGD58eFVT2nJQZfgqm0pa8Z3x9mbdunVcuHBB56w/iUSCl5cXbdq0eadYwCUPjwq7dt6Od0FRPV3nzp1xc3Pjo48+YtKkSTRq1Ahzc3NCQkKoX78+SUlJapqGhYWF9O7dm/DwcJ3jTs+fP0cikXDz5k0ePXpE27ZtEYvFJCQkaI2lPXnyhLFjx2Jubo7BvzJpT548WeS2bNu2aMAzNVW/v2J90rZtS3Rvvk1KSoqaqEBsbCxr1qxh1apVmJiYYGZmxpAhQypFmuxtrl27RkREBIGBgULfPZVKRUpKCk2aNBEmR99//z329vY6N6Zt27at1p6K78L+/fvx8vIiOjoaHx8f+vTpQ25uLtnZ2VhZWan1ACwNkUgkeAsKCwvp2bMnDRs2rFBj3Mr6PX9rY/NemsdmZ2czcuRIrK2t0dPTo1mzZoJubxUlU2X4KptKmCG+Fos51LIlnTt3xt/fHxMTE6pXr067du2YNm0a27dv5/r162qz7ZycHCFB5F3iYwA/pKWRU9FavjfiXSqVis8//xy5XM6YMWM0ZqSvX7/m2LFj1K5dGz8/PywtLalVqxaDBw9my5Yt3L9/n5SUFIKCgnRyT82YMYMOHToIxszU1LTUwWb+/PlCuUhx01019+qjRzBvXlGGalxc0f9583TqSPEmqampTJ48GdAsYbhx4waurq40aNAAmUxGy5YtSU9Pr9TVgUqlYtOmTTg4ONC7d2+mT59OzZo1NVY/o0aNwsbGpszMzt9++w2JRFLu1XhJ/PHHHyQlJeHu7s6ePXuAolV469atadCgAZmZmSQlJWlt8qoNkUjE48ePyc/Pp1OnTkRGRuqU3KU107KSPDj3a9emYcOG5Xpfysu2bdvw9fVFLBbj6urKqlWrqmoCS6DK8FU2lRATKDQyUhtc8/LyuHr1Kps2bWLSpEkkJCTg4eGBqakpwcHBQi89kUjEkSNH3knS6uHDh8ycOZOBYjGqt1c7ZfypzMz42M+Pbdu28dNPPxEREUHt2rW5cOFCqeeMjo4mPT2d/Px8MjIymD9/PvHx8djY2ODt7U1QUBAKhYIzZ86UeG+3bt3C1NQUKysrGjdujL29vVo9nTZUKhVDhw4VDJ+np2eF37fS+PjjjwXZNG0lDJmZmdSrV4/OnTuzevVqgoOD8fb2ZunSpRVbpZTAixcviI2NRU9Pj48++kjDTfn69WtsbW3p1KlTqccZNmxYhfvlvUl+fj4LFy4UMhbf9mwolUqmTp2Kq6srs2fPJiYmRqfjikQifv31V9q0aUOrVq10ihVfuHABIyMj/Pz86N+/Pxs2bOD69esoK0ncQNmlC+7u7uXqdl9Rbt++TWJiIgYGBpiamtKnT59SO0ToxDu0JfsnUmX43gfvKPl1wMICX19fmjVrRkxMDK1bt9YqQ5aVlSU0uiw2fHK5nGrVqtGwYUMGDBjAsmXLOHbsWKlf/L///ptZs2ZRo0YNQTHG0tKS/YmJZIvFZbs934h3mZiYCIakevXqfPXVV2XOOn19fbUaKaVSyeXLl0lLS6NWrVro6+ujUCjo0qULq1at4tq1a2RmZjJu3DhMTU3x9vZm7NixeHh46CTp9ezZMzw9PRk/fjzm5uZ07969zH0qwpdffklycnKpJQzZ2dkkJibSrFkznj17xokTJ2jfvj02NjYMGzasXGnwJfH9998jk8nYunUrDRo0ICQkRKNucu7cuRgZGZUo8/b8+XNsbGy09vYrDydOnMDf35/mzZuXeW9bt27F1tYWU1NTndzeYrGYhg0b0rZtW51d/i9evEBfX1/47opEIsRiMcfi4t495m1qCvPmsXz5chITE3W6nsqgoKCA1NRUZDIZYrGYevXqaazmHz16VKqA+7u0JfsnU2X43gfvkBqfb2hInTd+fMV/ixYt0jjNy5cvadiwIb169SI9PR0DAwOg6Mt85MgRli5dSr9+/QgPD8fS0hIHBweio6MZOXIkX3zxBWfPniU7O5szZ86oufxMTExISkrC2NiYb6dNQ9m6NTkiEXlvF7e/Fe/KyMhALperXbeRkVGpPyyVSoWZmZlOK5tly5ZhZ2fHjBkzaN++PVZWVojFYtzc3DAzM6N169bUrFmz9B/yv1AqlcTGxpKSkgIUFbZnZmaWuV9F+Pbbb4mJiSEtLa3UEobCwkKGDBlCzZo1BeN47949JkyYgEwmIzY2lv3791fIffXTTz8hl8s5ePAgUHT/X3zxBXZ2dmoKKH/99RempqZERUVpXV3PmzdPLRGpvDx69EjoN7h161advRMXLlzA1NSUxMTEUu8/KysLkUhEixYtyhR+ePHiBXv27GHkyJEEBQWhp6cnGDwrKyt2796Ns7FxpYgb8OgR2dnZyOXy/4oY9XfffUdwcDBisRiFQsG8efNQKpWCWo/WUpF3aEv2T6fK8L0vKqDVmS0SkbtkCdOnT9eYeb49U/v7778JCwujX79+KJVKFixYgLW1dYmXo1KpuHv3Lnv27GHOnDl06dKFwMBATE1N8fLyws/PT81YVatWDXNzc/Lz80lPT8fRyIgHI0ZojXdlZWWRkpKCnZ0d8+fPF1Z9YrGYHTt2lPo2PX36tNTrfptly5Zhbm6OtbU1AwcO5NSpU7Rv3x5LS0tMTEywsrIiLi6OefPm8cMPP5QY75w6dSqNGzd+53ioLpw8eZKwsDB8fHzKVP9XqVQsWLAAR0dHNS3NnJwcPvvsMwICAvD19WX58uU6x9gePHiAi4sLX375pcZzxZqX9vb2guall5cX/v7+GiUE+fn5ODk5cf78eZ3O+yZKpVJoRjxixIgKuXA//vhjbG1tad26tdZ7//vvv2nQoAFisZhDhw5pPJ+Tk8OhQ4eYOHEiYWFhmJubExERwcyZMzl9+jSjRo1CX18fd3d3PvnkE8zMzKhZsyYF8fGVJm4wffp0evfuXe57ryz++usvkpOTMTY2xtDQUGjqXKtWLXVX8ztoDf8vUGX43iflmDHlGRiwPTISKJr5+/j4CIbI3NwciURCQkICly9f5tmzZ4SEhDBo0CBh9tu/f3+11jK6kp+fz4YNG7C2tqZ27drCOY2NjTE1NSUyMpIaNWpgbm7OnTt3NGboe/fuxdXVlR49egjag97e3hgaGtK+fXtq1apVauHxxYsXdeoY//jxY8aPH4+trS3R0dFIJBJOnz7N06dPMTY2JjQ0lJcvX/Lw4UO2bdvG0KFDCQwMxMLCgqioKGbMmMH3339PTk4Ou3btwsnJSaeC6Mrg559/xsnJicDAQJ1XOFu2bEEmk2m4uFUqFceOHaNdu3bY2toyYsSIUouZX7x4QUBAQJldDs6ePUtISAgNGzYkISGB1NRUjd59GzduVGuIrCvnz58nNDSU+vXrv1PG4dOnT7G0tKR79+7UqlWL27dvqz1Xt25dBg8ejJGREXv37iU/P59Tp07x4Ycf0qxZM8zNzQkPD2fSpEkcPnxYI6Z44cIFYmJiiI2NxdPTEysrqyK9zEoUN3jy5EmluIrfleIuHW9OrkNDQ4vGk/ck5vBPosrwvW90SI0vSEgg0tpaLS71008/oaenh0wmIz09HW9vb/z8/LC1tcXGxobu3burDaItWrQos+GpNg4fPix0nJ4/fz4SiYR9+/aRnZ1Nv379aN68OQYGBigUChwcHLCysiI8PJwuXbpQu3ZtFAoF27dvVzvm/v372b9/PyqViunTp+Pr61viD33Xrl3ExsaWeH1vGrwBAwYIMlP79u1DKpXi7OyMg4NDiQkMz54949tvv2XMmDHUq1cPU1NTDA0N6dGjB/v379e59c678Oeff2JkZMRnn31Wrv2OHz+OXC4vsXvD3bt3GTduHFKplPj4eA4ePKj2ncjLyyMqKooBAwboZHALCwtZuXIllpaW+Pr6Mm/ePMLCwigoKEClUlG3bt1ypeQ/f/6cIUOGYGdnx+eff14pGYbNmzdn69atLF26FDs7O44ePUpmZiYBAQGMHDmSc+fOYWBgQHBwMJaWlgQHBzNq1Cj27t1b6metUqn49NNPkUqlTJkyhcTERLp160b37t0xMTFhQ6NGZFfECGhZAQ0bNkznbhbvk+K4qbm5ueDm9fT05M+wMFSVWM70T6TK8P2nKCU1fvXq1cRp0bbcs2ePoNCel5fHtGnT0NfXx8nJSWjaWty1vVatWrQt5xduz549yGQyjhw5wqhRo6hRo4ZaUsO5c+dwdHTE2tqavXv3AkWGaOzYsVhYWBAUFER4eDjW1tbY2dkRFRXF8OHDWbNmDRkZGYI7as6cOXh6emp0mIeixqgDBgzQ2F6SwSvm77//pmbNmohEIpYsWaLT/b58+RJfX1+GDx/OlClTaNKkCebm5tStW5eRI0fyzTff6NT+qbxcvXoVkUhUoQLja9eu4e7uzrRp00o0XtnZ2Xz66af4+/tTo0YNVqxYQVZWFt26dSMhIaHcReanT5/G3NwcR0dH/P39mTlzJseOHcPb21sn46VSqVi/fj0KhYJ+/fpV6nu6cuVKIev04MGDWFtbC4ba1tYWX19fDAwMGDJkiM7nvXnzJs2aNSMkJITLly8TGRmJSCTCwsJCWBF5eHhwd/z4Sol53b17F1tb23Lpor4P9u7dy7fffsuJEye4evUqN27cYPPSpeRWkoDFP5kqw/dfRqVSERgYWGLz2GIyMzPx9/dn6NChdO/eHQcHBxITEwUJLplMVq5Z5LZt25DL5Zw8eZKuXbtSv359jcxPpVKJiYkJRkZG5OTkcOPGDZo1a0bdunXV4k8qlYo//viD9PR05s2bR/fu3QkODsbU1BQPDw8SEhKIiopCKpUKZQvFjB07Vs0N9/jxYyZMmICtrS39+/fXaiwzMzMJDg6mQYMGNGvWDLlczubNm0u9X5VKRVJSEn369FEzILm5uZw4cYJZs2YRHR2NpaUl/v7+DBo0iM2bN+uUKFMWKSkpGBgYVLjV0sOHD6lbty49e/YsNSapUqk4cuQIrVu3xtTUFHt7e37++edyn6+4Me3XX3+Nn58fhoaGhISE8IkO8ZtffvmFpk2bEhQUxJkzZ8p97rLIyMjA1NSUjh07IpPJ0NfXx8TEhIiICOG7YmFhwcqVK8s8VkFBgeDlWLhwIYWFhahUKpycnNT6Ybq4uPz7szt7FlWbNkX9+IyMtHpwdBE36NKlC3PmzHnn96PSqYQ65OIs1n8yVYbvv8zx48fx8fEpdSb9559/4ufnx9SpU4VB+/Tp09SpU4fQ0FC6du1KcSabLuoW69atQ6FQcPr0aVq2bElcXJzW1UhOTg76+vr4+Pgwa9YsJBIJixYt0nkFUVhYyPXr19m+fTupqakEBwdjYGCAkZER/v7+dOrUiVq1ajFixAjOnTsnrPBKMnhQ1IfOx8eH8ePHY29vz6VLl7hy5QoODg6lFjjPnTuXkJCQMmu6CgoK+PHHH1mwYAEJCQnY2Njg5eVF7969Wbt2Lbdv3y5XnWRxCYNcLi+xREAXXr16RVxcHM2bNy8zMWTFihW4uroyaNAgJBIJiYmJHD58uFzXXdyYtqCggKqYAhQAACAASURBVISEBEQiEcOGDSvReL8pkbZ06dIyMyp15c8//2TDhg306dMHd3d37OzskMlkdO3aFQcHB5YsWcKLFy+Ii4ujSZMmPHr0CGtraxYvXlzqcS9dukSdOnWIiIhQCzFs2rSJ6tWrY2BgQHGGc3EmbDEHDhygYfXqqN5B3ODy5csoFIoKyQq+VypJqaY8bcn+G1QZvv8yHTp0YOnSpSU+f//+fXx8fJgxY4bGc4WFhaxevRo7OztEIhFxcXHY2toyderUEvUfi5tvnjp1itDQ0H83Y9XC119/jYWFBUZGRrRs2VKjzU9FWLt2Lfb29mzZskVoKOrg4ICenh4GBgYEBgbSp08fFi9ezKFDh9QSUH799VdcXFxYtGgRS5YsoXXr1hrPaXN7Hjx4EHt7+wq1AFIqlVy5coVly5bRoUMH7O3tcXJyIjk5mZUrV/LLL7+UalCKSxhq1KhRZkF9WRQUFDBgwAACAwNLjJnu3r0be3t7IeHl1atXrFy5kho1auDv78+nn36qk8t14cKFDBo0CIBBgwbh6emJn58fLi4ufPrpp8LKU6VS8c033+Dq6lqmKLYuPH36lB07djB48GD8/PywsbGhTZs2pKWl8fPPP6NSqZgwYQJmZmZqIt+FhYVMmDABNzc3rK2tS0zmef36NZMmTUImk2n0xXv9+jUSiUTIcoyNjcXOzk5jUhoVFcXatWvf6T4BWrZsyerVq9/5OJVKJSnV6NKW7L9JleH7L3L//n1sbGxKnMHfu3cPLy8vZs+eXeZxRCIRMpmM1NRUunXrhkwmY86cOWoz9IULF+Lu7s7x48epXr06EyZMKHHQfvnyJZ6ensKstzKFlDdv3oxMJqN3797o6enRuXNn7t69y/Pnzzlx4gQrVqxg8ODBNG7cGBsbG2QyGXXr1hWKzI8ePYpCodBIq7979y5eXl7MnDlTuK87d+5gZ2fHkSNHKuXaVSoVN27cYM2aNXTv3h03NzekUilt27ZlyZIlXLhwQVgRK5VKqlevzrFjx6hfv36ZpQy6nn/27Nk4Oztz5coVted++OEHpFIpGRkZWvc7dOgQCQkJSKVSxo4dW7SqLkGR4/z+/QQEBPD06VOqVavGlStXUCgUTJ8+HbFYjJeXF0ePHiUuLo7q1atz+PDhCt1PVlYW6enpjB49mtq1a2NpaUmLFi2YN28e586d0/AuXLp0CblcLpTavM3GjRsRi8W0b99e47mTJ0/i6+tL27ZtNQy0SqWiYcOGiEQiBgwYgFKppKCgQKML+vnz53F0dKyUvnjF4hP/DVmxgwcPEhQUxIgRI9i9e/e/46FVK74q3jdTpkwRZtVvc+fOHdzd3VmwYEGZxzlz5gx6enpcuXKFZs2aERAQwLp162jfvj0KhYKPP/6YKVOm4OPjw3fffYeTk1OpCSHffvstTk5O6Ovr4+fnR4sWLTQyNyvKkydPmDhxIhYWFpiYmKCnp1dm3Grnzp1YW1vTo0cPevbsibOzM/r6+ri6utKqVSvGjx/P+vXruXz5Mnfu3KFmzZqMGzeO7OxsateurSYQ/T74/fffWb9+Pf369cPX1xdra2tiY2Pp3bs3Xl5e5Obm0qpVK3bt2lVp59ywYQMymUwwODdv3sTe3p5vv/22zH1v3brFos6d+dbQkDw9vSKJvLdiNCoTE3bp67OyTx9B0Wb37t2Ympqir68vZAFGRkaWqybv9evXHDlyhMmTJ1O/fn3Mzc1p0qQJM2bM4OTJk6UalLNnz2JnZ8fWrVupV69eiXFxqVSKhYUFM2bMQKVS8fLlS4YMGaI1AxmKsk+Dg4MRiURl/t46derE/Pnzdb7f0ihu7VRWrev74NixYxgbG6Onp4eJiYlQ2F4V46vivZKbm4udnZ1WFYdbt27h6uqqc7biqlWrMDc3B4p+TNu2bcPFxYWOHTuyd+9ePDw8MDQ0FJJgNm3apPU4f/31Fx06dMDT05NJkybh7u7O5MmTSUtLo1evXhW/WYoM3qRJk7C1taVfv37cuXOHL774Aj09vVJXQsVlC8WD3OvXr3F0dOSHH37g5s2b7NixQxCn9vPzw8TEBB8fH6pVq4ZUKqVBgwbcuHGj0tvnlEZmZibbt2/Hzc0NZ2dnLCwssLOzo3Xr1hw5cqTS2sccPXoUmUzGsmXL8PLy0imhAxDqS8tKWVeKikQV7v1LW3Tv3r1q6ibBwcG0adMGT0/PEhvYFhQUcObMGWbNmkVkZCQWFhbUq1ePCRMmcPDgQZ3fi5MnTyKTyYTJw7x58+jXr5/W1zo7O9O7d2/CwsJo0KCB8FhbS6Ljx49TrVo1DA0N6dKlS6nXcPv2bWxtbStVP3X79u3Uq1fvnfR1daWwsJDz58+zePFiEhMTeVMkw9jYuMh9Wwlaw1VZnVWUyPr164n8V8H6m9y4cQNnZ2edG28CjBw5EgcHB7Vt2dnZTJkyBWNjYxwdHZkwYQKGhoY4ODiwYcMGNfeKSqVizZo1yGQyxo8fT05ODm3atMHR0ZEzZ85w+/Zt5BXsJ/b06VPB4H3wwQdqccITJ07g5+eHTCbTqrSxZcsW5HK5mrDv8uXLS637y83N5dKlSyQnJwv1h66urkLZQs+ePVm4cCEHDhzgzz//fG8Dzo0bN5BKpeTk5PD8+XPi4+OJiIggLCwMMzMz6tevz/jx40lPT38nN/KPP/6IkZERTZo00e1eKqjIkbtkCcbGxoLRMzU1RSQSceHCBfbt24enpydt2rThzp07XLx4kYULF9KqVSusrKwICAhgxIgRfPvttxW618P/j73zDovibNs+S+8gW1g60kRQpIkgoKJYUQTErqgRFWOwl0gsKJZojNhiiTGxxx6NmhhjSaIxdhNFjd2o8dEYY6fv/L4/cOdxZYGlJN/7vvE8Dg8Pdmd3Z2Zn57rv+zrL/v0agx8oGRwqFAqtA5ratWvTu3dvunfvjqWlZYkU4TWyVGFhIRkZGVhYWODg4ECtWrUqNHJOT09n7Nixld7/8lBcXIy3tzfff/99jb4vlAwSf/jhB6ZNm0br1q2xtrYWTbjXrl2Lr6+v6H+rMQCvhtfwGx3fG5SL8PBwtm/frvHYr7/+ipOTU6WTuRMSEggICNB4TJ1DFhoaSkBAAAYGBsyZM4d9+/YRHh5OvXr12LZtG7/++itNmzalYcOG/Pzzz0CJ24elpSUymUy8sfj5+WntHZWF8gqeGuvWraNLly788MMPyOVyUSsI8PHHH+Po6Kjh9JGfn4+Li0uF+/Hjjz8il8s5e/YsrVq1olOnTjx48IAjR47w8ccfk56eTkxMDDKZDDs7O5o0acKQIUNYsmQJhw8frhF91bBhw3j33XfFvydNmsSkSZOAEsLJvn37mDRpEs2aNcPCwoLg4GCGDx/Otm3bdM6dKyoqon379iQnJxMYGEhqamr5bMpqOHIIZmaMbtaMOXPmMGnSJKRSKYcOHUKlUvHrr78yf/58/Pz8kEgkyGQyBgwYwKZNmyqXdq4FX331FXK5nO+++67Uc4GBgaUKhiAIKJVKTExMGDFiBM+ePWPu3LkolUoOHToElAxKQkNDcXJyIiQkhNjY2AqXw9WOKzUhb3kdy5YtIy4urtrv8+TJE77++msyMjKIiooSB3sjRozgiy++KHVdTZ48mYYNG5a+3o4fLy3VqMQg6Y1zyxtoxYkTJ3Bzc9MYrZ4/fx5HR8cyXTrKQ2hoqEZkS2FhIV26dCE2NpZJkyZRu3ZtPvvsM7Ffd+HCBbZt24ZSqcTQ0JC0tDSNG+aaNWuoV68effr0ER8bO3YsEydOrHBfHj58yIQJE5BKpWUWPDXef/99Ro8eDZT0KRUKBdu2bWP27Nm4u7uXcu1funQpbdq0Kffz7969i5OTk1hE8/PzSUxMpE2bNqWW1QRB4N69e+zbt4/s7Gz69+9PWFgYFhYWODs707ZtW8aMGcPq1as5ffq0TvE28F8Jw6ui++zsbNLT07Vun5+fz+HDh5kxYwZt2rTB2toaPz8/0tLSWL9+vVYGpyAIDBo0iJYtW1JQUMDTp09p06YNbdu2LdvDsxojeZVEQvHLZIGbN2/SunVrXF1dcXR0xMXFhb59+7J69WoOHz5MXFwcvr6+1SYUbdu2DYVCwZEjR7Q+n5WVxdChQ8W/b9++Tfv27TE2NiY2NlZj2z179iCXy0lJSUEqlVKvXj3atGnDjh078PT0rFBWMHXq1Gov95eFvLw8nWK0Xod6SX3YsGEEBQWJ/dIJEyawd+/eCl2JtK0Q/Pbbb7Rs2ZIxVlaoKrvk+car8w3KQ58+fZg1a5b4t5oxt2bNmiq9n6urK4MHDwZKfkQdOnSgffv2pKWlERAQIDLYCgsLmTt3rtj/io2NZdGiRdSpU4fo6Gix19a+fXsCAgLYvHmz+Bk//PADwcHBZe6DuuDZ2dmRmpqq4aNYFt5++23mz58v/n3y5EnMzc1xdHQspXkrKCjAzc2tzJugepvIyEimTJmi8XhRURG9evWiSZMmOvVnVCoV165dY8eOHUyfPp1u3bqVCgTOzMxky5YtXLp0qdRy26JFi+jUqZPGYytXrtQ51aCoqIiTJ08yd+5cEhISkEqleHh40LdvXz799FOuXr3K9OnTadCggcbxFBYW0r9/f4KDg0vLCmqgd5Orp4entTVSqZTk5GQcHByYO3duqRvoqxKH7t27V0ni8Pnnn2Nvb1+uIbbaA7WoqIglS5Ygk8mYMmUKAQEBGlIXKJmxtWrVCmNjY+RyOV27diU3N5f69etXSNzKzc1FoVBUyQxAV8yYMaPcWCxBELhx4warVq0iNTWVOnXqiCSqmTNncvjw4SprAo8fP87IkSNxdXUVU1q2b9/+Jp3hDWoOf/zxB7a2tiJ9+MyZMyiVyjIJJ7rA2tqaefPm8fz5c2JjY+ncuTPJyck0bdpUo6eiZrfJ5XKaNm2Kg4MDq1atoqCggJUrV+Lu7k5MTAzm5uZYWVlp3FSLioqws7MrNfuoSsFTo3379nzxxRdASbEZPHgwdevWRaFQlNJJLV++nJYtW5b7fkOGDKFDhw5ae5EqlYq0tDQaNmxY5VBOdSDw+vXrycjIID4+ntq1a4uBwCkpKbz//vs4OzuzefNmjYKwY8eOKi9nqVQqcnJyWLx4Md26dcPW1hYDAwM6duzI4sWLycnJEY9ZEASysrJwc3PTvFHXAFuv0NCQtQ0aYGtrS9euXfnss8+Qy+VlCvOfP3/O+PHjkclkZGdn6yxq/+yzz3B0dNRpBuTh4UFgYCDh4eHk5OQAJSsgr/aB9+3bh7OzM4MGDcLf3x9XV1diYmKYN28eUVFRFfZGlyxZQocOHXTa96rir7/+ws7OTlwlePU77969O87OziiVSjp37syCBQs4c+ZMjRC21E41r8aS+fj4/HcDHbyGdXGq+Z+GN4XvH8aMGTPEJZOTJ09ib2+vMbOqCgwNDdm+fTuRkZH07NmTmJgYkpKSNJbmvvzyS5Hdpr7xHzt2jIYNGxIREcGJEycoKCigd+/eGBkZIZPJSt14unfvzscffwyUFLyJEycilUorXfDUaNCgAadOnaKwsJCePXvSpEkTHj9+zMWLF3F2dhZZioWFhdSuXVvs0WjDypUr8fb2Lpc8IQgCo0ePrjAxorJ49uwZR48e5ZNPPiEhIQFLS8tSgcAjRoygXr161U7C3rt3L3K5nK+//ppPP/2Uvn374uHhgVQqJSEhgblz53Lq1Ck+++wzFArFf3tjNajPevz4MfPmzcPT0xNHR0f8/f1LJR28iosXL9KiRQsCAgJKxWu9jsWLF+Pi4sKvv/5a7naFhYXMnDkTMzMzmjdvrlEEGjduTGxsLPn5+YwZMwYnJydWrlyJh4cHU6dOpaioiGHDhmFgYFDhgLO4uBhPT88a0WBWdDw9evQgOjqa+Ph47OzsxFn+ihUruHz58t9GxDp16pRY+MzNzbWbqZfjNfy/EW8K3z+IoqIiXFxcOHXqlBjaqp7xVBUqlQo9PT0CAwPp168fgYGBpKWliTeCu3fv0rlzZ7y8vLT2XFQqFZ9++ilKpZLU1FSaNWtGs2bNiI+PR6FQ0L17d7HXtm7dOtq2bSsWvP79++uUdF4W1GnkHTp0IC4uTuPmefXqVVHSsWLFCpo3b17m+5w6dQqZTCaO+MuDIAhMnToVb2/vUsbXNYG4uDjROu3VQOBOnTphZmamEQg8atQojUDgivDzzz8jl8u1MgBv377N+vXrSUtLw8/PDxsbGxo2bIiFhQVTpkyhuF27mil8rzhyqFQqduzYIRpFT5w4sUzyhyAIbNiwAScnJ/r27auV9DJ37lxq165d4TV1+vRpgoKCaNmyJTt37sTDw0OjKDRr1ozQ0FCCgoLo2LEjBw8exNHRUcNrdOLEiTRu3Bi5XF5u4sTfJTd48eIFBw4cYMqUKaLMw9fXFxMTEz755JO/hUSjDU+ePBFTV8zMzDA1NdU55/F/M94Uvn8QW7dupXHjxhw5cgS5XK6T2LgifP/99+jp6TFw4EA8PDzIzMxEEARUKhUff/wxcrmc8ePHlzsih5K0g7S0NDF9+sKFCzx9+pSsrCykUim9evVi4MCBSCQS+vTpU62CByXLrqampjRt2pTu3btrFbH/9ttveHp6YmdnVybd+8GDB7i5ubFp06ZKff7cuXNxc3PjypUrVdp/bXhVwvA67ty5g1KpFAOBd+7cycyZM+nZsycBAQGYmpri5eVFYmIiEydOZNOmTVy4cEFcHvztt99wdnZm48aN5e7Dw4cPWbhwIVu2bGHlypV069YNQ0ND1tRE0Xs543sdly5dwtbWlh49eoj/Hz16VOv+PX36lJEjRyKXy1myZIk4QJs2bRre3t7l2srl5uby7rvvIpfLxdBcQRCoXbs2Z86c4e7duxw8eBA3NzcMDAwYOnQoX3zxBXK5XOO83b59W1xWPHr0KE5OTsyYMUNrrzIsLIytW7eWe851gToea+zYsURERGBubk54eDhjxoxh586dosawT58+TJs2rdqfpwt+//13atWqhZOTE0+ePOHAgQM1Js7/n443he8fRExMDJMnTxaXqqqLW7du4eDgIGpxlixZApTIIpo0aUJYWFilgj+XLVsm/ij9/f3Zv38/f/31F2PGjMHMzAwTExMUCgXr1q2r9r4fPnwYExMTjdmpNmRnZ2NmZqY1lqe4uJjY2NgqZ5upJRPV9dBUY9iwYYwbN07rcy9evMDExKTM1xYWFnL+/Hk2btzIxIkTSUhIwMvLCzMzM/z9/bGxsSEuLo5du3Zx8+bNMmcgBw8eRE9PTyNdQE9Pj9EvySnVKXqCqWmZjhyLFi2iUaNGPHjwQLTGCwsLY+3atVrdWM6ePUtUVBShoaH069cPPz+/ckkw6likzp07a9iI/ec//yE2NhZHR0eNPpVEIkFfXx9LS8tSJtMpKSmMfynKh5JBScOGDenWrZvGzFv9mVXppf3+++9s2LCBIUOGEBAQgKWlJS1atCAzM5P9+/eXafadk5ODvb19hQPV6uLy5ctYWFjg4+NTI/Zr/9vwpvD9Qzh37hxSqRSpVMrevXur/X5Xr17F3d2d4OBgJBIJW7ZsoaCggKlTpyKVSpk/f36lf7DNmzenW7dujBgxgtWrV2NjY4OxsTFdunTh2rVr3Lt3j8jISExMTBg7dmyVc9bu3LmDq6sr7u7u5S4hFRUV4e3tzdatW6lfvz5jx47V2H7cuHG0aNGiWkkA69evx97enhPVbM4/ffpUg5zwOgRBEOOdKoOHDx+Ky3ojR46kVatWODg4YG1tTXh4OJ06daJz587izV8tMn/1X7169bh/7hz5+vrVKnx5enqkd+vGTz/9VOp7U6lUtGzZUpytFBcXs2PHDlq0aIFSqSQzM7OU76VKpaJ169YYGhrSp08frf3PJ0+ekJaWhpOTU6m2wOXLl5FIJBrHbGxsrFH8Xl/eP3nyJEqlshS7Nzc3l549exISEiKSdeLi4nTS1AqCwJUrV1ixYgV9+/bF09OTWrVqER8fzwcffMDRo0fLteV7He3btxcHsX8HTpw4gYmJyX8T1/+FeFP4/iG0b98ec3PzGjFLvnDhAs7OzgwYMAATExNcXFw4cuQI/v7+xMXFVal3de/ePWxtbQkMDKR3795IpVJSUlIYNmwYUqmUKVOmkJubS05OjvjZUqmUzMzMSlk4XblyBXd3d5KSkirURa1Zs4bo6GgEQeDPP/8kODiYoUOHirZsbm5uOou9y8OOHTuQy+XVIjBokzC8DoVCUanejUqlokuXLiQnJ6NSqXjy5Al79+5l8uTJNGvWDHNzc6ytrTE3NxdnO68WAmNjY3r06CHquYrj41FVsegV6+mRFxfHrFmz8PT0JCAggEWLFmmQiW7fvo1cLuf06dMax5GTk8OgQYOwtbWlV69eHD9+XGTZhoWFcePGDYYMGVIqqX3nzp24uLiQmpqq1VRAEASGDBmiESGUlZUlnovXry9BEGjatGmZ1m6CIDBr1iwcHR1Zu3Yt9vb2WrWbxcXF/PzzzyxcuJDOnTujVCpxcnKiW7duLF68mHPnzlWroBw6dAhPT8+/xWbv22+/xdDQsEI97P91vCl8/wC2bNmCRCKpETNatfxBHUYbEBCAo6MjSqWSDRs2VLkJP3v2bHx9fZFIJPTt21ejh3fz5k2Sk5Nxd3dn69atuLu7k5OTw9WrV+nVqxdyuZzZs2dXSND45ZdfcHR0ZNmyZUyYMIHJkyeXuW1xcTF16tTRWKZ69OgR4eHhdO7cGZlMxsmTJ6t0rNrw7bffIpfLKwwE1gZ1CoM2d5FXUadOHZ21YIIgkJqaio+PDwMHDqRBgwaYm5sTFBREcHAw9vb26OvrY2BggJ+fHxMmTODmzZvcunWLiRMnok7rsLa2FgtBN09PCgwNq1T4nuvpEWdvT58+fVi+fLlogm5ra8tbb73F0aNHxeR1f39/rQXj4cOHfPDBB7i5uSGXy6lTp47GwOXkyZOEhYXRsGFD2rRpg6enZ7kDxbNnz+Lv74+npyeGhoZIJBKGDh0qHu/9+/c1tt++fTv+/v4VrhDs2rULExMTkl5abxUUFPDjjz/y/vvv065dO2xtbfHx8aF///6sWrWq0hmNFUEQBCIiIirdt64IGzduRF9fn97/w5MT/gm8KXx/M3bt2oWFhUUpJ4mq4OjRoygUCpKTk/H29mbZsmUYGhri7e1dZZr8o0ePmDx5MoaGhvj5+Wk4wLyO/fv34+/vj7OzMyNHjhQfz8nJoVOnTjg4OLBw4UKtQtojR45oJKWnpKRop02/xPr162ncuHGpG8rt27cxMzMjMjKyxkfEaiPkyg5QvvnmGwICAiq8+YWHh5dJ5y8oKODo0aN8+OGHdOrUCWtrawwMDGjVqhXJyck0aNAAU1NTDAwMsLW1JSEhgZ07d2o910VFRcjlcl43IQ4ODmZpYCB5BgaVK3zm5iwJCOCDDz5g6dKl9OjRAycnJxwcHOjYsSMdO3bE2dmZBg0a8NFHH9GxY0fRked1FBYW0rlzZwICAmjSpAmOjo5kZWVx//59BEFg9erVWFlZYWZmxttvv611NUGlUjFv3jxkMhkrV65EpVIRFxeHRCKhUaNG9OrVC1dX11Ln19vbW6fe+qVLlzA3N8fGxgZnZ2csLCwICgpi6NChbNmypUalMGVh+/bthISE1FhBXbx4MRKJhBEjRtTI+/1vx5vC9zdi+/btyGQyMfi1Ovjuu++Qy+W0bt2agIAA2rdvj7e3N1ZWVmRlZVX6/R49ekRmZiZSqZSuXbtibW1NYmIiq1atKvd16jBUQ0NDRowYobHUdfLkSdq2bYubmxsrVqwQR9Z79+5FJpNpOPjHxMSUIh2oUVxcTN26ddmzZ4/G4yqVivj4eAYOHEhsbCxdu3atVO9EF5w6dQqlUlkpF51XJQzloW3btiKT98GDB+zYsYNx48aJvooNGjRg0KBBJCYmYmpqikKhwMDAAENDQ+rVq0dmZqbObNrVq1drFD71cuDGjRtFRw6VDukMhUZGXBw2jMzMTI0ILUEQuH79OitXruStt97C09MTKysrHBwcMDU1xcTEhI8++kjjxp2fn09CQgJxcXHijPDs2bMMGDAAa2trnJyc8PLy4sSJEzx48ID+/fvj6OjI+vXrxfe5e/curVu3plGjRmLYbm5uLh07dqRdaCj5WVnciI7mhFIpZgvyxx/Mnz+fVq1aaT1XDx484IsvvmDkyJE0bNgQQ0NDHB0dGTFiBEFBQcTExGhNdvg7oVKp8PX1rXLO4atQZyhOnz69Bvbs/wbeFL6/CVu2bEGhUDBv3jyCgoKqNXLbs2cPMpmMxo0bU7duXaRSKe+99x55eXmYmJhUaobyasHr27cvV65cITs7m969e2NjY6OTqXBeXh5WVlb06tULpVKp0ZeBkh5F06ZN8fHxYcSIEVr7Z56enmWKlDds2KBVOzV16lQaN25MQUEBeXl5xMXFkZCQUGWrprJw/vx5nJycdIr5uXLlSpkSBjVUKhXnz58nLCyM6OhofHx8sLa2plWrVkyePJnPPvuMrKwsQkNDxQJlZWVFp06d+PLLLytFiCkuLmb27NnIZDJkMplG8bO1tf3v9/TSkUNlbMwLLexNlbExVwMDeT85mejoaCwtLTEwMCAmJob09HQ+/vhjjhw5ouEHqWYy9u3bF1tbW/E4OnbsyJdffikahr/KIlSpVCxatAg7OztatWqFi4sLkZGRbNy4kcLCQo4cOUJgYCAxMTEsWrQIpVLJpEmTxAHP48ePGRgUxDEnJwQTk9LuNGZmCCYm7DI25sr69UAJG3rdunUMGjQIPz8/rK2tad26NdOmTWP37t3Y2dmJaQ5FRUUMHz4cb29vLl68qPP3UBNYsWIFrVu3rtZ7vPPOO0gkkkob3/9fx5vC9zdgw4YN2Nvbc/r0adq1a1cl42k1YtUmlwAAIABJREFUtm3bhkwmo06dOsjlcsLCwjSSt/X09HRyTdFW8NQIDw9nxowZhIeH67xfHTt2ZN26dZw4cYLw8HDCwsI0UhPULilGRkZ4eXmxfft2sZCpVCqMjY219gRVKhX+/v6l8t12796No6OjBjmkoKCApKQk2rZtW+P072vXrlG7du0KdU3Dhw8vJWF48eIFBw8eZPr06bRr145atWrh4eGBj48PnTt35vDhw2zevJkuXbpgZ2eHsbExhoaG+Pj4YGFhwYoVK6o0UPr111+JiIigWbNmXL9+nQcPHoiyBkNDQ43laTUeXLjAOAMDNpqYcM7dHVXPnlodOQoKCrCwsGDLli3MmTOHPn36EBISgrm5OW5ubrRv314jEDg/P5+ePXsSFBSEh4eHSLwJCgpi4sSJfPvtt5w6dYqoqCgaN24sxuIUFRWxZcsWmjRpgpOTE9OnT+fq1atERkair69Pz549RSnAvXv3mObsTL6hYYXZgsV6euQbGJBhZ4dMJiMxMZHs7GxOnjyp0fObNWsWPXr0KHWeVqxYgVwuLzN38O9Afn4+jo6OnDlzpkqv79atG/r6+jWiQ/y/hjeFr4axdu1alEolv/zyi06zgfKwbt06ZDIZtWrVwtTUtJRE4ffff0dPT69cBll5BQ9KiCsymYz09PRKCWeXL19O9+7dgZJitWrVKhwcHOjXrx/37t0jOzsbV1dXLl68yI4dO6hfvz5hYWHs3buXu3fvIpPJtL7v5s2bCQ0N1bjxX7lyBblcrtWyrKioiO7du9O8efMytVFVxe3bt6lTpw6TJk3SWojUEoajR4+yceNGhg0bRmhoqChOHjlyJFu3buX27dscO3aM6Oho5HI5RkZGmJqaYmtrS+fOndm+fbsoT/nss88qvZ/FxcXMmTMHqVTKokWLUKlUqFQqhgwZQlBQEP7+/kgkEq16xXHjxiGRSLCzs6NZs2YkJiaWeb02b95cIzpK/dmXL19m27ZtTJkyhc6dO+Pr64upqSm+vr6Ym5sjk8mIjo5m8ODBKBQKlEoldnZ26Onp4e7uzpgxY9i1a1cp5uaZM2fo0KEDEokEd3d3tm/fTs+ePXF1deWjjz5igkxGgZFRpfqVKlNThDLMlCsqNIcPH8bBwYEPPvjgHwmOhRLSmbZCXB5UKhWxsbEYGhpy8ODBv2fH/pfjTeGrQaxcuRIHBwfROmvEiBFVDq5cvnw5tWrVwtDQEF9fX60Shd27d2NkZKT19Y8fP2bKlCnIZDL69OlTpkPJ7NmzSU1NxdPTU8zj0wVq14dXR8tPnjxh1KhRmJmZIZfLxR4MlPwYP//8c3x8fAgKCtI0wn1lm4CAAA1Hm+fPn1O/fn0WLVpU5r6oswejoqJqNB0bSqJfGjRowIgRIxAEgaKiIk6dOsXChQsJCQnBzMwMmUxGfHw877//PocOHSI3N5c7d+7w6aefEhcXh4WFBZaWlujr6yOVSpk2bRrnzp0Tb55Pnz4lKCiIqVOnVnr/Ll26ROPGjWnSpIl4vouLi+nXrx+RkZE8fvyYx48fs3DhwlKvVS+Vq6UPJ0+epGfPnoSHh2td8p40aZKG8Ls85OXl8d1334nRV7Gxsbi6umJsbIyxsbHYBwwPDyclJYXY2FisrKwIDAxk6NChbNq0iUmTJmFlZSUumSqVSpo0aUJaWhrhBgbkVjUstYzMuE8//bRCI/Rbt24RHBxM7969dY6pqg4eP36MnZ1dufFer6KoqIjg4GBMTEyqPFP8N+BN4ashfPLJJzg5OYl9gGfPnlXqgn0VM2fOFLVZgwcPLnN0OXv2bGxtbTUe07XgqRESEsJnn32Gs7NzpUexwcHBGlZiKpWKoUOH4uvrS7Nmzahbt24psX5RURGDBw/GzMyMNm3aaEgStm3bRnBwsLgfgiDQrVs3UlJSKty3V3VhNUlEePToEZs2bcLR0RFHR0esrKzw8/Ojf//+IglGEATy8vLYu3cvw4cPx93dHVNTUywtLbG2tqZLly5s3ryZRYsWlYqeKSwspHXr1gwYMKBS57+4uJi5c+cilUpZsGCBOOsvLCyka9eutGjRosIZ8MiRI9HX10dPTw99fX3efvttVCoV48ePx8vLq9S1s3fvXqKjo3Xav/v371O/fn3GjBnDqFGjRKanXC5n0qRJLF26lL59++Lu7i7KMry8vOjYsSNt2rTBxsYGAwMDDXG6qakpPXr0wMDAgO36+hRXUZOoLSVcpVLh5+dXJuHqVbx48YIuXboQFhb2j3hqjhs3rswsx1eRl5eHl5cXlpaWVTKN/zfhTeGrASxZsgQXFxeN4NSlS5fS8WVwZ2XQs2dP9PX1MTY2Zv3LZnxZSE1NpXbt2kDpgvd6iKs2XLlyBXt7e2bPnk1aWlql93XSpEnijLaoqIg+ffoQGRnJo0ePEASBHTt24OHhQWJiosYPce7cubz99tssWrQIBwcHkpKSOHfuHIGBgRqp9HPnziUoKEjnpWJBEBg+fDiBgYFVErarHThWrVrFwIEDqVevHpaWljRr1ozRo0cTEBBAcnIyhYWF7NmzB29vbz788EOaNm2KqakpdnZ2mJiYUL9+faZOncrp06c1lqG/+OILjXgbQRDo168f7dq1q5T7zJUrV4iKiiIqKkqjOOXl5REfH6/BmizvWE1NTTEyMkIikWBkZISVlZW4H0uXLkWpVPLTTz+Jr3n69CkWFhYVkonu3LmDr6+vaDO3Z88ejI2NCQ8PL6Wtg5JrZ+3atURERGBsbIyBgQEKhQIzMzMNco76X6CjI4WVlWS8/s/UVKOPuXPnTgIDA3UefAiCwPTp03FyctLobf8duHv3LrVq1Sr3mn706BEODg5IpVKt5/gNNPGm8FUTCxcuxM3NTWNZTxAE/P392bdvn87vc+fOHXx8fDA0NMTa2rrC+BaAli1bEhoaytSpU5HJZKSkpOhU8NSYPn06b7/9Ns2aNauSYfbx48fx8/MjLy+PhIQEWrduXWqWkZeXx/Tp05FKpbRt2xYHBwfs7e0JDAxk8uTJXL16ldmzZ2NtbU2tWrXE/T9w4AD29vaVnjELgsD48ePx9/cvZZH1OvLy8vjxxx+ZPXs2CQkJKBQKnJ2d6dq1K/Pnz+fkyZMacok7d+4QFBSEi4sLxsbGmJmZUatWLaysrOjSpQvr168v18btu+++IyoqSvx70qRJhIaG6uyGr9avSaVSsrOzNYrqixcvaNmyJZ07d9bJe3Hv3r3UrVuXY8eOYWhoyPz585k1a5bGe+7atQuZTKZhFRYSElLutXnz5k08PT15//33efToEQMGDMDZ2Zns7Oxys/uePXtGv379cHJyomnTplhYWGBqaqq18N14++1qZwtiZqbhO9qkSZMKB5rasH37duRyeZVDpHVFamoqmZmZWp/7/fffsbW1xcXF5V+RrFATeFP4qgF1jMrrN+eDBw9St25dnUaPKpWKxYsXY2pqKuqgdInXefz4MXK5HGNj40oXPDUCAgLYtWsXVlZWOsXiaNt3hUJB48aNK7zh3rp1iyZNmmjcwCQSCWfOnEEQBBo0aEDXrl2RSqV0794duVxeZU9TdfSQj4+Pxo323r17bNu2jdGjR9O4cWPMzc0JDg4mPT2dzz//vFQyQFFREYcPH2bSpEkEBwdjamoqOqbo6ekxcuRIjh49qrOQ/pdffsHf3x8o6eF6eHjoLIa+evUqTZo0ITIystR3/eTJE6Kjo0lJSdF55timTRs+/fRT/vzzz1LL5a/ixIkTODo6smDBAqDEiPv999/Xuu2VK1dwdXVlwYIFbN++HScnJwYNGiRqPadNm0ZsbKxYXFUqFefOnWPs2LFYWlpibm6OQqGgc+fOzJs3j+zsbPFaMTIyYurUqSUDkRrMFgT46aefcHNzq7Ln67lz5/Dw8GDs2LF/i80YlDB25XJ5qYHlr7/+ioWFBb6+vv9Ks+mq4k3hqyLUnoXaSCedOnXio48+qvA9Lly4QGRkJAqFArlcjo+PT4U+m48fPyYrKwuZTIapqSkDBgyo0v5fvHhRFAdXNRn84cOHyOVywsPDdfrBFxUVYW5uLha9bt26ASXLTPXr10elUnHnzh0cHBwwMzNj2LBhVXbJUKlUjBw5EplMRlJSEp6entja2tK2bVuysrI4cOCA1tHxzZs3WbZsGYmJiVhZWWFvb49CocDS0pJOnTqxcuVKUlNTqVevnkge0RW3bt3C0dGR3bt3Y29vz6VLl3Q6jgULFiCVSvnwww9LneeHDx8SFhZGWlqazv6QOTk5KJVK8vPzOXv2LH5+fuVuf/36dXx9fRk1ahQbN26k/SuZfGpcuHABJycn5syZQ5cuXfDy8ipl4Zabm4u/vz8JCQnEx8dTq1Yt7OzsMDU1ZfDgwVy5ckVjsFhcXIyjoyM2NjYkJCSgVCqpV68ev7i61kzhe3kcSUlJzJ8/X6dzVxb+/PNPYmJiaNeuXaWuicogMTFRg6R0/PhxjI2NiYiI+NeaTVcVbwpfFaDODrtz506p527dukWtWrU0hL2vIz8/n8zMTOzs7AgJCcHe3p6GDRuWu0z25MkTseD17t1btFVauXJllY4hMzOTYcOG0bt37yo5wd+9e5d69eoRHx9fKZHt4MGD0dPTw9LSUpRRBAcHiyn0qampdOrUibt375Keno6dnR3jx4+vkLDy7Nkz9u3bx9SpU2nTpg22trZ4e3sTFhaGnZ0du3fv1npzeP78Obt27SI9PR1PT0+sra1xd3fHwsICPz8/xo8fz6FDh8TZgJq0dP36dXHfde0nPnv2DBMTE2QyGUeOHKlw+2vXrtG0aVMiIiK0iv3VjNORI0dWihjTv39/kUG6Z88enez0Hj58SHR0NB06dNAUwlMSkKtUKhk0aBAKhYJx48aRm5vLixcv2L9/P5mZmWLYap06dTA1NWXixIk0atSImJgYcVb+6NEjTp8+zdatW5k9ezZ+fn6lljkNDAzYZGJSYzM+dYZiTUhhCgsLGTJkCL6+vlVagakIP/30E+7u7hQVFbFnzx4MDAyqPGj9t+NN4asEBEEgMzMTX1/fMrPDMjIyymVgHT58mLp16xIXF0dsbKxoQ1bWD09bwVNDX1+/SpRlQRCoW7cuhw4dQiaTlRv+qQ3Xr1/Hw8OD6dOn8+TJE6ysrHTuLRw7dgw9PT327dvHgwcPaNeuHQYGBixbtowlS5bg5+enMWj47bffSE1NRSqVMnXqVJ4+fYogCPz222+sX7+ed955h6CgICwsLIiMjGTMmDFs375do8H/8ccf4+TkxPnz5xEEgTNnzjBr1iyaN2+Oubk57u7uoidjQkICy5cvL7MX9dFHH4nmxYIgkJGRgZ+fn07svqtXr6KnpycW+bKgdjORSqV88MEHWmfTagJJWRrDsqBO4VDLFT799FP69Omj02vz8vLo0qULpqamYp/v+PHjyGQyGjRoQP369cnOzmbMmDGEh4djbm5OREQEY8eOZefOndy+fZucnBxatGiBvr4+UVFRJCQkEBgYiK2tLZaWlvj7+9O4cWNkMhnW1tYaMUMGBgZ4enryYvJkVNUtfi97fIMGDWLChAk6nz9dsGzZMhQKRY3Ej72O6Oho3nnnHfT19UsxhN9Ad7wpfDpCEATee+89/P39y1x+y8vLQ6FQaB2dqxPO1ZEnMTEx2NnZ0atXL61+k0+ePGHatGlaCx6UzB709PSqtK5/9uxZXFxcOHToEAEBAZV6bU5ODk5OThpLubGxsaWy0sqD2ihYEAQaNWrEzJkzCQgIwNDQkM8//7zU9oWFhWzZskXUJ9nY2KBQKEhMTGTOnDkcOXKkXKbh/fv3SUtLE5mXSqWSOnXqYGNjQ506dRg1ahT79++v8Fyq/RNfFwXPnDkTT0/Pcok4Dx48wMfHB0tLy3JJNzdu3CAmJoZGjRqVaZF148YNPDw8yuy1lYfJkyczcOBA8e9p06bprM2DknNQr1497O3tWbRoESYmJhgZGWFvb4+5uTmNGzemd+/ejBw5klGjRtG1a1fCwsJQKBSYmJhgbW2NhYUFCoWCmJgYJkyYQHp6OomJifj4+Ii9bg8PDxYsWEBKSgoSiQQzMzMyMzNLZpr371ef3GJqyv2cHGxtbf8WFuT333+PUqkkOzu7RsXuaWlp6OnplWkC/ga64U3h0wGCIDB27FgCAgLK9bJctWqVViPcbdu24eTkxMCBA7l16xaNGjXCxsaG0aNHl/pRvFrwevXqVaaf5eHDhzEwMKjS8bz33nuMGjWK8ePHk5GRofPrjh8/jr29PWvXrtV4fN68efTv37/sF96/X2IW3LNnSV/lpXnwgY0bqVu3Lr///jvOzs6MGDECJycnunbtyurVq8nIyKBp06ZYWlpSv3590tLSmD59Oi1btsTR0ZHFixdrLVYFBQUcPHiQd999l+DgYCwtLfHz88Pe3h49PT2ioqL46KOPKq11+uabb6hfv77WG9nChQtxcXHR+n3l5uYSERHBuHHjyvR8FASBJUuWIJPJmDVrVpk900uXLuHq6qpVkF4RcnNzUSgUoj0YlCw96/JegiBw8eJFZs2ahb+/v0jwMTAwwNnZGYVCgbGxMbVr16Z58+b079+frKws1q5dy+HDh/nkk09QKBSEhoYSFxcnJqYHBQUxbNgwVq5cyYEDBwgMDGTw4MHi8e/evRsbG5vSDOnExBI9XlWK3ksd34QJExg0aFClz6OuuHHjBgEBAfTr169G/GQnT56MRCLB3t6+SvFZb/BfvCl8FUAQBNGlvbwenCAIhIaGasgC7ty5Q0JCAnXq1OH777/nr7/+on79+lhYWJTygNS14KmxZMkSLC0tq3Q8Xl5eHD9+nPr16+vUa4ISeYFcLufLL78s9dzVq1dxcHAo3UM7frzkBmVqWmqELpiZkS+RcDMkhJS6denQoQP9+/enTp06GBsbY2RkRGxsLDt37tRKFjhx4gStW7fG3d2dTz/9lAsXLrBo0SI6dOiAtbU1Xl5eBAYGIpVK8fDwYOjQoezZs4eNGzcil8t1Pu5X0b59ez7++OMyn//ss89wcHDQcMApLi4mISGBnj17olKpCAsLK/XZN2/epEWLFjRs2LDcvL5z587h6OhYbpxTeVi+fDnt2rXTeKxjx46il6MgCNy9e5cff/yRNWvWMGTIEMLDw5HL5RgYGKCnp4eZmZlIUPL29sbS0pIZM2Zw8+ZNioqKUKlUXL58mQ0bNjBu3DhiY2MxMzNDX1+foKAg3n33XTZu3MiVK1dYvXq1mN13/fp1vLy8RO2fGoIgaE/gOH68xIGlKoXP3JwX33+PTCb7W3pxr+LZs2d06tSJiIiICuU15WHw4MHo6+vzySefsGrVKlq0aFGDe/nvw5vCVw4EQSA9PZ3Q0NAyyRX79u0jNjaWuXPn4u7uTnFxsShRkMlkTJw4kby8PO7fv4+XlxdmZmYamp8nT54wffp05HK5TgVPjeHDh+Pk5FTpYzp16hQeHh6iR6cubEx1Qnl5vn++vr6awbAvo28qGpUX65WEnH4SGsqiRYs4c+YMRUVFXL58mbi4OJycnJgxY0apz3vy5AlffPEF8fHxmJiYiP0ff39/LCwsaNWqFfPmzdPKnPzqq6+QyWQVBse+CrXvakWyj82bN6NQKPjpp5/EhPDmzZuLM9PWrVuLfpeCILBs2TJkMhkzZ84sl05/8uRJ7O3ttS4F6wJ1X3fbtm2cOHGCzZs3M3v2bBQKBeHh4dSpUwcTExMsLCywsbHByMgIOzs7sW964MABfvjhB1xdXTEyMsLGxoZr166xZs0abGxsiImJISoqCisrK9zc3EhISGDYsGHUqVOHpk2bau2JC4JAcnIyffr0wcnJqfKzWPU1VomiV2RsTOH8+cyfP59OnTpV6VxWFiqViszMTFxcXDh16lSlX5+cnFziVvPS3KGgoAAXF5caDWL+t+FN4SsDagusRo0alTLPfRWrV6/GyMhIFJ6PGTOGxo0bExERIerx7ty5g7OzM+bm5mJ/69WC17Nnz0pHnsTHxxMYGFjp4xo7dizvvvsuixcv1qk5vmbNGuzt7TmhxdvwVYwaNeq/Atsq3JAwNy953StYvXo1BgYGGBsb06FDB7Zt20ZWVhZRUVFYWloSFBREREQEDg4OyOVy5HI57u7ubN68ucK+yv79+5HJZDovGQ0fPlxn39Xdu3cjl8sZOHAg9evX15ixduvWjbVr1/Lbb7+JBgQV6TbVAbmvutqUhadPn/LLL7+wfft25s2bx7Bhw4iPjxetwaytrQkMDKRDhw4kJSVhYmKCj48PZmZmNGjQgGHDhpUKW33+/Dnp6elYWlpiZmZGQkICtra2GBkZ4evrS/v27ZHJZHTr1o0//vgDQRBYuXIlMpmM+fPnl0u137VrF/r6+kycOFGHM6sFOg6wBImEImNj5vn6IpPJsLKyEkOR/yls2bIFmUym8+eqVCpiYmIwMjIqFes1d+5cunTp8nfs5r8CbwqfFqhUKlJTU4mMjKzQ9Hjnzp2ika76X1ZWlmgZdf36deRyOZaWlhw7doynT59Wq+CpERISUmrZqiIIgoC7uztnzpyhXbt2JaGk5WDhwoU4OzuXu/ymxsGDBwkJCeHS2rUUGhtXeQlKbR48c+ZM0blDX18fc3Nz9PX1cXNzE1mczZo1Y/bs2eTk5CAIAoIg8MUXX1CvXj3Cw8MrdM45dOgQcrm8QtcatYRBndGmCyZMmIC+vn4puUlaWhrdu3dHJpMxffr0CkXT+/btQy6Xi6G8eXl5XLx4ka+++orFixczZswYkpOTCQkJQSqVYm5ujp+fH3FxcQwZMoQ5c+awdetWQkJCGDBgACNGjCA0NBQLCwuioqLQ19fnyy+/1LjO//rrLw4cOMCHH35IixYtMDIyQl9fH0NDQ5KSkli0aBHp6ekaGtIHDx4QERFBcnIySUlJ1KtXTyM+SxvUzjBTpkzB3d296gbjL7MFMTUtYWu+zt40NS15/uW1lZ2djYuLCwqFgqZNm7J+/foaz3QsCz///DNubm5kZGSUOyAoKioiMDAQU1NTrefx6dOnyGQyDceoN9AdbwrfayguLqZPnz40adJEJ4r+oUOHxMwzY2Njvv32Wy5evIi5uTlr167FxsYGOzs7Tp48yYwZM6pd8NRwcXHhnXfeqdRrjh49io+PD8+ePcPKyqrMmawgCEybNg1PT89yCSBPnjzhm2++YfLkycTGxqKnp8c3Fhaoqsq0e0k6SEhI4HXtlkKhwN7eHk9PT6RSabmZdcXFxaxbtw4vLy9iYmLK7ecdO3YMhULBli1bytzmo48+IjExscznX4e6H7pu3ToUCgWbNm0CSjSeHh4eODg4lFkUCgsLuXbtGvv27WPo0KGYm5sTGxsrzmxNTEzw8vKiZcuWDBgwgBkzZvD5559z9OhR7t27J56T3377jTVr1jBw4EBq166NRCKhVatWTJ8+nR9++IG8vDz+85//IJVK2b17N1lZWSQlJVG7dm0sLS1p1KgRdevWxc7Ojs6dO+Ps7KyxbHzs2LFSjOA9e/ZgZmaGk5NThfIO9UqC2gs0NTW1fIKULvjjjxIbst69OenoyG9Nm5bKFhQEgcDAQHbu3ElBQQEbN26kRYsWyOVyRo8erZOpQHVx//59oqOjiY+P16r3zcvLw8PDAysrq3IHW++99x6DBw/+O3f1/yzeFL5XUFRURM+ePXXOdnv06BGdOnVCT08Pe3t7sY+Rnp6ORCJBT08PuVzOu+++i1wup0ePHjWW4mxlZSXaSFWEuXPnMnHiRPr27cvEiRP58ssviYmJ0bqtIAiMGjWKevXqafRlBEHg+vXrrFmzhsGDBxMQEICFhQVNmjRh/Pjx7Ny5kz5t21JkaFgtmrnKxISBiYkolUokEon4r0ePHuJN/dChQwQGBtKkSRN++eWXMo+7sLCQTz75BFdXV+Li4jh9+rTW7U6fPo1SqWTdunVaz4c2CUNZOHv2LHK5nAMHDgAlNmVKpZJ+/fohk8lo1aoVb731Fj/88AOrV69mypQp9O3bl6ZNm+Lm5oaxsTGurq74+flhampKamoqq1at4ocffuDWrVtae7KCIHDhwgWWLl0q5tXJ5XI6derEvHnziI+PZ8qUKVy7do0tW7aQkZFB27ZtkUqlGBgYEBsby5gxY/j888/59ddf2bx5M46OjgwZMoTp06dTu3btUgOgwsJCLC0tefToEQUFBYwbNw4HBwd27tzJ8OHD8fPzK/OmrZ5xvbqS8PTpU2rXrq2VPFVZ/PHHH0gkEq2JI99++y1+fn6lZluXL19mzJgxyOVyYmJi2LBhw99qAVZQUMDAgQPx9/fXmLU9evQIpVKJXC6v0Bjh3r171KpV640pdRXwpvC9hDrOpWXLlmUTGF7S8oWePbkbEsIWMzM2hISQGBUlvqagoEBkvamtuTp27FhjBU+NyoRMdujQAQMDA/FmEB4ezpw5c0ptV1xcTP/+/WnUqBH/+c9/+Omnn/jwww9JSkpCqVTi4OBAcnIy2dnZHDt2rNSN4WTXruTr61er8OXq6bE+OJjPP/+chw8folKp+PXXX0uRI4qLi1m6dCkKhYIhQ4bw8OHDMo8/Pz+fBQsWoFQqSU5O1qDzq5GTk6OVMbl3794SCcO9e1olGa/OJm7fvo2zszNLlizh6NGjbNiwgXfffVcs4up8RTMzMyIiIujevTsZGRksX76cffv2cfXqVQoKCli9ejVKpbJMc4KioiJOnDjB3LlzSUhIQCaT4e7uTkpKCsuXLycnJ4dz586xevVqBg4ciKGhIVZWVjg7O9OhQwcmTZrE9u3bWbFihcZy+d27d0lKSqJOnTocOnSIrKysUn6nr6J58+YsW7aM4OBg2rdvr3EDzs7OxsnJSWOwoRb816lTR6s13/fff4+Dg0O5kiFdMHHiRLE3/DoZqGXLluWG/ebn57NhwwaWTrkyAAAgAElEQVRiYmJQKBSMGTOmwmivqkIQBD766CPs7e3Zv38/t2/fxtbWFldXV50NIdLS0mpcgP9vwJvCR0mx6tSpE+3atdMe5/IKLV/1unBW3UNITITjxxk7dqxY9AwNDTEwMNB5ZqYrioqK0NPTK5d08yoyMjLEGaiBgQFGRkal2KO3b9+mcePGuLm5ERERgYWFBYGBgQwZMoR169Zx8+bNCgkjecnJ1Sp64r+X5sG64OHDhwwZMgSFQsHSpUvLZak+f/6c999/H7lcTkpKCteuXdN4/tKlS7i4uGiI80dERXE9MFCrJKPI2JgiQ0N+9vAgPTwcExMTjI2NRSu60NBQzMzMiIuLY/ny5bi4uNC1a9dy46qWLl2Ks7OzRnHOzc3lu+++Iysri5YtW2JlZYW/vz9paWmsXLmSnTt3smzZMjGP0NzcHG9vb7p27Urz5s1p37691mKydOlSUlNTEQSBFStWIJfLycjIIDc3l4yMjHITLgRBoH379piZmbF48WKt18aWLVuQy+V8/fXXFBcXM2DAAEJDQ8stbKNHjyYpKanKou+8vDxsbGzE36BcLhd/06dPn8bJyUnnmdylS5fEDMEWLVqwadOmv2UWuH//fqRSKUZGRvj5+VXqM9Rs4zepDJXDv77w5efn07FjR+Lj47U3uF+yxgQdWGP5BgYMejnLa9euHVu2bNG5OFUGOTk5SCQSnbdfuXKlWIS9vb2pXbs258+fZ/ny5fTt2xdvb28MDQ1RKBRMnDiRb7/9tlyv0TLRvn3NFD4tJsgV4eeff6ZJkyYEBgZy6NChcrd9/PgxkydPxs7OjkGDBml4rl67dg1XV1fGjBnDDz168EJPr8KepUoiIVciYXlICI8fP+b3338nLi6OBg0aaMzafv/9d9zc3HBxcdF6Y1dLYs6cOcPu3bt59913iYyMxNzcnLCwMN555x1mzJjB9OnTSUlJoX79+iIbs2/fvsyfP59Dhw6J311ubi5yubzMvtWkSZNIT08nNjaW4OBgMSlj+PDhBAUFlbnU9uDBAxISEvD09CQkJKTcc/3jjz+iUCgIDg6mRYsWFV5XeXl5+Pv7VznmZ926deJsz8TEBH19fXGG16NHD2a/EkWkK/Lz81m/fj1NmzbF3t6ecePG1Sip5OjRoxgZGWFubk5qamqli2vnzp3Jzs6usf35N+BfXfjy8vKIi4sjKSlJ+8VWRZ2Q8Botv6axdu1aTE1Ndd7+66+/Fke/Xl5emJiY4OHhQe/evfnwww9p0KABvXv3rnIsi4gajoupLARBYMOGDbi4uNCzZ0+tJuJQciO7fPkymzZtolWrVpiamuLj40NwcLBorfW2vj4vKrnfgrk5P6WkIJfLmTx5stZr6sCBA5iampKeni72me7evUvXrl2xtbXFz88PS0tLIiMj6dmzJ2+99RaJiYl4eXlhYWFBeHg4gwcPZvny5Zw8ebLcwNlly5ZpBN++iuLiYho1aoSFhQWzZ88WxeeDBg0qV8Kzd+9enJycGD16NA8ePKgwmPbJkyfi54wfP16nmdzp06eRy+WV9pCFEgLR6tWr6dWrF127duXIkSO8ePGCmzdvYmdnV+3khIsXLzJixAhkMhktW7Zky5Yt2gX2OuKrr77CwMBAJLrEx8cTHR1dqb7diRMncHFxqdZ+/Nvwry18ubm5tG7dms6dO5fpDCFUwxmCCnRv1cGECRNQKBTan7x/n0cZGdyIiuKcuzu77ezIMDTEzdyc9PR0vL29RZbhvXv3RO1WdWNNVCoVt955h4LqJmO/FhBaFTx58oR33nkHa2trkpOTycjIoHfv3kRFReHs7KxhrfXWW28xduxYYmNjsbKyYujQoTz+9tvSS9o6/suVSLj4mqXbq7hx4wb29vZ4eXnh7e2Nl5eXGGobFRVFZGQkDg4O2NraEhMTw6hRo1i7di3nz5+vVNZbWb6iUOIAo06tWLp0KVCyfJ6SkkKTJk20zsry8/MZOXIkzs7OGjKR8oJp79+/T3BwMGlpady9e5ewsDB69+6t04xm2rRptGjRosrX5YIFCxgyZIj497BhwxgzZkyV3ksb8vLyWLt2LdHR0SiVSsaPH19pC7y1a9eir6/PW2+9JT6mUql47733cHNzq5QBffPmzVm9enWlPv/fjH9l4Xvx4gWxsbH06NGjzFnOg+hoiqt6835Jy/+70K1bN3x9fYGSG9apU6fYMGoUx5ycyNMrIYhozERe9iHz2rWjmYUFBQUF3Lx5E29vbzIzM6vcT/nrr7/YsGEDKSkpKBQKonx8KKxu4TM11SCMaMOr1lpr165l2rRp9O/fn+bNm+Ph4YGxsTFOTk6Ehobi7OxMrVq1GDZsGAcPHhSttbTh5s2bvPXWW+wyNq6yJEN47btXqVScPXuWRYsW0aVLF2QyGXp6eqJoXCKRYGhoSMuWLZkwYQJbt27lxo0b1TY23r17N0FBQRrvk5+fz6xRo5hsbs7lsDC+s7bmz7ZtKZ4xg/7x8WUSu3JycggICCApKamUbV9ZwbQ3btzA29ubiRMnivvw4sULOnbsSIsWLSqceRUVFdGoUaMqeZKCZurEn3/+Sa1atcpcAaguzp8/z/Dhw5FKpbRu3ZqtW7dWOPuaN28eEomEcePGaX1+w4YNyGSycmU2r2LPnj3Uq1evRg2x/y/jX1f4nj17RrNmzUhJSdE6gn706BEje/Uir7rLdTrcwKuCR48e4efnh7u7O82bN8fKyoopDg7kGxqiqqAPqZJIyDMw4O6kSbi4uDBv3rxKfbY60mf69OlERkZiZWVFhw4dWLJkyX+p64mJ1dbxCYLAn3/+yYkTJ9i0aROzZ89m8ODBtGnTRsxzk8vlhIWF0bVrV8aNG8fSpUv55ptvuHz5cqmlt6+//hofHx/i4uIq9ma8fx9VVQX46vNsbEx2RgbR0dGYm5tjY2ODXC7HxMQEFxcXJBIJmZmZxMbGYmtrS8uWLcnNza3Ud1ERmjdvrtEnO7tiBd9aWVGgr19qNpuvr0+Bvj7F8fElRK6XEASBhQsXIpPJytRNbt68uVQw7blz53B2dtYa7lpcXMyQIUOoX79+mWxRNS5duoRUKtXZxu9VbNq0ieTkZACysrLo27dvpd+jssjNzWX16tXirP29997Tmtjx3nvvIZFISvn1vo5Tp07h6urK5MmTK5z5CoJAgwYNRDu8Nygf/6rC9/TpU6KionjrrbdKFT1BEET90tZGjRCqG3tSA0t2giBw5coVVq5cKWp+LC0tMTU1JSAggK+++ornc+ZUug/5Qk+PIzpmeT158oStW7fSv39/HB0d8fb2ZtiwYXzzzTdlMmCLqpiVlmdgQFdPT6ysrLCxsSEwMJDExERGjBjBggUL2LlzJzk5OVVisBUUFPDBBx8glUoZN25c2e8xaxbF1Sx8L/T0GCOR4OLiQqdOncjOzua7774TZzl2dnYkJSXRvHlz/vrrL3r06EGzZs2qRijSgjNnzuDo6EhBQQHPnj1jY0xMCUmnojQDiUS0jrt37x7t2rWjYcOG5Q4W/vOf/1CrVi3xxqwms2jTRKohCAIffPABLi4u5eowARYtWkRYWFil+8+7d++mTZs25ObmYm9vX6EtXE0jJyeHoUOHYmdnR5s2bfjiiy8oKipi0KBBWh19ysK9e/do3LgxSUlJFV7369atIzo6mlWrVlWLGftvwL+m8D1+/JiIiAgGDRpUavR0+/Zt4uPjxXDW/18kjby8PA4fPszs2bNJSEhAoVCIFPgFCxZw8uRJioqKsLOzKzFurqZDvbY+pCAInD9/ng8++ICYmBgsLS1p3bo18+fP19nJvmD+fJ5Xcn8KjYw4PXAgp0+f/luYsGrcvXuXlJQUnJycWLduXembQw1990Xdu2v9/Pz8fFH4r57lFRcXM3DgQBo1alRh0rwuSElJYebMmXzzzTdk2NmRX8nl5yITE8ZaWZGRkaETYcLLy4tz586J5t9fffWVTvu5YcMG5HJ5uYGtKpWKli1bkpWVpfPxQ4kmMCoqiqVLl/5/TSl/8eIFK1eupHHjxpiamiKRSCqdrpGfn0+/fv0ICAgoM/Px+fPnzJ49G319fXEJ/Q3Kxr+i8D169IiwsDCGDBmicaMrLi5m4cKFSKVSMjMzyc/P59mzZ1ypW7dmCl8FtPx79+6xbds2Ro8eTUREBObm5oSEhDB06FA2bNhQJqvN2Ni4xLC4BjLJoORHs3PnTnr06IG5uTkuLi4MHjyYnTt3lulg86q11vLly3nvvffo0aMHERERKJVK0l7OfCpc9nxllvFP4siRI4SEhBAZGakhsn4eE1Mj3/3DyEhu3LihsYT54sUL2rRpQ61atUpJLtSOOQEBAWUGHeuC33//HRsbG7p160YHpbLKs+9iExOdCVp9+/alX79+/4+98w6L4vre+LuFZSlKXTqCCqJgw4olFogQG4qV2GJsxIbGXmKM+WJDTSKxYklMYo8t1tg1VmzYS+yoKIhUaVve3x+E+bmh7cJqGp/n2Qf2zsydO2XnnXvuOefSzs5O7+mejh8/Tjs7u2J7QHFxcVQoFHrNbHDhwgX6+vrS09OTx44d06tNhkatVrNly5aUSqXs2rUrra2t2a5dO+7YsUPnnqxGo+E333xDBweHQo8nIiJCiNUFQCMjI0Mfxr+Kf63wTZo0ib1792ZiYiLr1avH0aNHa4ne1atX6efnx2bNmvHGjRvCG5O9vT2Pu7kZRvje6PHlOzksW7aMffv2ZdWqVWlpacm2bdsyIiKChw8f1ilNGkkCYNyFC2WehVoplbJ7q1Y0MzOjh4eHMMvE0aNHqVarGRcXx+PHj3PNmjVaqbUqVaokpNZq2bIl+/fvzxkzZgipteLi4rhkyRJOa9tWr+TB7xqVSsUVK1bQ3t6eYWFheeOK1asb5NrvtrERzpOFhQU9PT1pYWEhxPH179+f3333Hfft28fY2Fg+f/6cSqWSX3zxBb28vHR25Y+Pj+fQoUP57NkzajQahoSE0NTUlOHh4VR27GiQF6OSCA0NpampaanNiTdu3KC7uzu//PLLIs1zP/30E729vYsN33iTW7du0dHRkY0aNfpLTX5KpZK1a9emiYkJr169SjLvBWj16tX08/Oji4sLp0+frvP13r9/P+3s7Lh8+XKSeUnyV65cSaVSyfDwcJqYmDB/3sRyiuZfKXwqlYqWlpY0NjampaWl1kznWVlZnDp1Km1tbbl06VI+ffqUc+fOpb29PXv06JF3c86dW2ZR0cjlvDN4MGfMmMGgoCDh4de/f39GR0fz+vXrpXLVjouLIwCq58wpcxuzJRIebd+e7u7ulEqlwtuiubk5jY2N6eDgwCZNmrBXr16cOnWqkFrr3r17JZrA4uLiaGNjkzeW+kbyYHbokPf3T8mD/0pevXrF8PDwvMwlUinVpewlaYn6H+O7+TlO69Spww4dOvDHH38U/u/bty/btGnDmjVrUqFQUCqV0sHBgU5OTjQxMWHXrl05adIkfvPNN9y4cSOPHTvG27dvMzU1VbifV65cSYlEQrlczpo1a1IikeTNuvHiRZnvj5IctDQaDT/77DO6u7vTycmpTNcgPj6e9evX58CBAwu9t/Ln7hs7dqxO9cXFxdHIyEhnr8i3wevXr1m5cmVWrFix0BRtZF7ihWHDhtHKyoodOnTgzp07SwxbuXPnDqtXr84ePXrQ1NSU5ubmgjfumwH85RTNv1L4jh49SjMzM+bnynR3d6dGo+HRo0dZrVo1dunShb///jt79uwprFOhQgXa2trSw8PDIA+NLIAdGjfmhAkTuH379jLnH8xn586deTe1gcaiztWooWUiAUAnJyeDeBnWqVOnyBivvyOfffYZq1tbM7u0vaRCBCMhIYF169bVsjiEhYVppUXLJzc3l0+fPuWFCxc4YsQIWlpaMjw8nCNGjGC3bt3YvHlzenh4CPPiVa5cmdbW1lrXztjYOC9BtgFe3v7soHXlyhWOHTuWKSkpVKlUDAsLY7169fj8+XMqFIoiH+66kp6eznbt2jEoKKhQR5/ExEQ6OTnpNIHwnj17KBKJ9Ip9NCRJSUm0s7PTKdk0mTfcsGrVKjZq1Iiurq6cMWNGsV6vv//+O2UyGQHQ1NRU6346evRo3gztf+QWLi6/7H8VEUnin0RCAvD998CVK0BqKmBhAdSuDXz8MaBQAAB69uyJTZs2aW3m4eGBrKwszJ8/H0+ePMH8+fPRqFEj7Nu3D0qlEgAgEonQtWtXbN68GejSBdi+Pe8RoCcakQgMDoZk+/YyH+6fmTNnDiIjI/GqWTNg164y1/cLgE6l3FYkEhX7Pf/WEovFWssK+1/X5aX5W9T/b5aJRCIkJibCwsIC36eloZ1KBYnOZ+L/UQM4aGaGUS4uUKvVePz4MSpWrAg7OzvhPDx//hwSiQQODg5a+89vT/56SUlJePToEWrUqIEKFSoI64nFYmg0GqSnp+Pq1atQq9VabahVqxbWS6XwuXSpFEegjaZ3b/zSrRtmzpyJ69evIzc3F7GxsZgxYwZevXqFbdu2oWLFiujSpQu6d++ODz/8sEz7U6lUGD58OGJiYrB79244OTlpLd+9ezdGjBiBy5cvo2LFikXW0759e+zduxdqtbrAffm2efz4MWrXrg1LS0vcuHEDpqamem0fGxuL5cuXY+PGjXjvvfcQFhaGoKAgSCR5d6RGo0GdOnVw/fp14TdmZ2eH+Ph4iMVi4Nw5YPZsYO/evAqzs/+/chOTvGda27bA5MlAw4YGOeZ/Gv8c4dPjYho1bQoAsLS0xMuXL4XVJk6ciO+//x7NmjVDgwYNsGfPHsTExCA3NxdyuRwdO3bExo0b834o584BrVoBmZl6N/U1gFYAnjk5oXLlyqhatSp69+6NwMDAUh9+PoMGDcKRI0dwr0kTYO3aMtd33M0NLR890iqTSqVwcnKCXC6HXC6HkZERjIyMIJFIIJFIhAewRqOBSqVCbm4ucnJykJubK/yvVCqRmZmJ169fQyKRQKPRwMjICDKZTKjvzY9UKtX6m///mx+JRKL1/5vfxWKxVln+9/y/IpFI+K7RaMA8awc0Gg1ycnJw7do1nDhxAmZmZqj66hUOqdWQazR6n88ciQQzAwNxRSbDoUOHUKVKFdSoUUNrn7du3UJOTg58fHyENuQve/Oj0Wjw4sUL3Lx5E7Vr10bFihWF8ri4OMTFxUEikSAnJ0fr2rVp0wbzb9+G9/37Zb4/dgII/lOZiYkJ5HI5fH19YWVlBWtra9y9exc5OTkYOnQoHBwc4OjoCBcXF1hYWOi9T5KYM2cOli1bhj179sDHx0dr+ZAhQ6DRaLBy5cpCt79x4wb8/f2RkpKC5ORkmJiY6N2G0nL9+nU0bNgQHh4euHjxIqRSaanrysjIwIYNG7B8+XIkJCRg8ODBGDBgAK5du4agoCDUrFkTKSkpiI+Ph1qtxqJFizBcLAbGjQOysop/aReJ8p6b8+cDQ4eWuo3/VP4Zwrd0qV4X89bgwTju7Y2wsDCtxZaWlujYsSP27t2LevXqISwsDHK5HB06dECTJk1w5MgRGBkZ4c6dOzh58iSMVq1Ct9OnYaLPKTI1xaU+fVAvOlookkgkmDt3LsaOHavvkRfg/fffR2ZmJk517gxMn679AqAvJibAjBm44O+Pvn374v79+8jJyUG7du0wefJkJCYmFvpJSEhAYmIiXr58CZlMBoVCUejHxsYGn376KX788Uf4+PigYsWKwoM6Ozv7L/mrUqlgbGwMY2NjyOVyvHz5stAeU5hGgwE3b8JED/FTGRvj5sCBuNioESZOnIg+ffrgo48+glwuF/ZnbGyMtWvX4vz581i9erVO9e7fvx99+vTBunXroFAoMGjQIFSsWBHR0dH47rvvMHv2bBgZGWHgwIGIiorK6xn06WOQF6MHzZujxcOHwsMVANzd3eHl5YX09HSkp6fj9evXSElJQUpKCoyNjaFUKqFWq4XeSP5Lh5GRkXAeTE1NYWZmhgoVKqBixYqwsrKClZUVFAoFbG1t4eDggCtXrmDJkiVYu3YtgoKChDalp6ejTp06WLhwITp27FigzQMGDEDlypWxcOFC3Lx5E4o/LEFvm5MnT6J169bw8/PD0aNH83pfBuLixYuIjo7Gxo0bYWRkhMTERJiYmGDx4sXo1KkTtmzZgg5PnsBx/nz9XtZNTf+T4vf3F7580dPzYs53dMSE+/fx58MbNWoUwsPDUaVKFQDA69evER4eDldXV1y8eBGnTp1ChQoV0LRpUzRr1gwdnzyBy8KFEOn5BtWxY0fs2bMHGo0GUqkU58+fR506dUpzBrTw8fFBrVq1sCEqCnBzK5vwyeXA48eAQgGNRoPo6GiMHz8eW7duRZs2bUrcnCTS0tKKFMjExEQcOnRIeOtNTEwEgCKFsrBPxYoVDWqqyu/h5QthWFgYdu3aBc0fAhcYGIhx48bhyZMnuDJsGGYrlTBSq4s1e2oAKCUSfFezJtZWqICYmBi4urrC0tKyUAHOysoqIMAl/U1OTsbx48chkUjQokUL1KtXDyYmJkhNTcXdu3dx4sQJzJ07F2ZmZpDL5bD/4QfU/+UXlKWvozE2xsScHHz9R49ZpVIBAHJzc2FkZKS1rlKphLW1NR4/fgwrKyuhPCUlBU+fPkV8fDyeP3+OFy9e4OXLl0hKSsKrV6+QmpqK1NRUZGRk4PXr18jKykJ2djaUSqUgoPmIxWLBIiCRSJCRkQE3NzdoNBpUqFABVapUgUwmw86dOzF27FgsX74cs2fPhq+vL5ycnODg4GBQMXqTXbt2oXPnzujYsSO2bdv2VvYBAL///ju8vb2FayGVSvHDDz/gQw+PUluoYGoKHDsGNGhg2Mb+jfl7C18ZzI0qY2O0FolwWqmEkZERsv8QiJUrV8LCwgKnTp3CyZMnce3aNdSsWRPNmjVD06ZN0bRp0wLjCjh/Ps/MumdPnsBlZf3/snwza7t2eTbzP26ex48fo3r16iAJT09PXLt2DUOGDMGSJUvK9OOzt7fHwIEDMWvWrDKNQ0IkAkJCgC1btIqVSiWkUqnBxGbz5s347rvvsGfPHgB5LxqF9R6L+uTm5sLW1hYKhQJ2dnYlCqWlpaXO5zchIQEtWrTA7du3AQCmpqZ48OABbGxs4O/vjzZt2uDyqlVY5OwM+wsXQJEo7wXoDyiXQwQI1/6iWIz27dtjwYIF6NWrV5H7PXToECIiIrB3716deqqXL1/G4sWLYWFhgbi4OISEhMDb21tYvmPHDlhaWqJGjRrIzs5GfHw8fj95EvdUKhiX4eedIxKhvkKB6wkJQplEIkGNGjXg5uYGNzc3mJubC+L83XffoU2bNqhXr55OYv7mX2NjY2EM689cvXoVbdu2RefOnREUFISEhAQkJCRg48aNuH37NrKzs2FtbQ13d3c8ePAAubm5MDY2RnJysmBm17zRc883h8tkMsjlcpiYmMDU1FTofVpaWgom3Px7ztHRUTDfVqxYUese++GHH/Dxxx9j4MCBiH7D0vM2mD17Nj7//HOYmJgIwwsKhQIJzZsb/Fnwb+bvLXxleLCrAVz38MBYd3ccP34cubm5APLGJwICAgSha9iwoe5jAImJeY41V68CycmAlRVQqxbQv7/gWPMmX3/9NTQaDcaOHYsff/wRQ4YMQYUKFbBr1y40atRI72MC8h7O0dHR6NOnT5leDN7VW15qaipcXV0RHx8PMzMzvbfPzs4uVhj/LKKvX7+GjY1NiQJ56tQpTJ8+Hc7OzkhKSkJGRgamTp2KiIgIzJgxA7/99hv69++PpUuX4sSJExC9fClc++znz3Hx/n0cSkhAtVmz0H3YMJw9exadO3fGsmXLEBISUuwxXbx4EQMGDEBsbGyx66Wnp2PKlCnYsmULvv32W3Tt2hXXr19HUFAQpk+fjsGDB+Pp06eoVq0aGjVqBLVajRcvXuD3339HgwYNEOPiUurfD0UiJLdqhc09e2LMmDHCOGKbNm0gk8lw7do1PH36FC4uLnB3d4eLiwtu3rwJpVIJX1/fUpmipVJpkcIoFotx+/ZtWFlZoW7dukhPT8fJkycFxzQrKysMGjQIixYtwujRo+Hk5IQFCxagX79+8PHxgVwuh0gkQmZmJlJSUpCeno7U1FSkpaUhPT1d+JuRkSGYbzMzM7VM5CqVqoD5FshzyDEzM4OdnZ1gvrWwsBAENP/Fzd7eHg4ODnB2doazszPkcrne18XNzQ3Pnz/H9OnTMWjQINjY2ECSlGRQ689/gb+v8CUklPliqqRSOKpUSJFKhTGHFi1a4NixYwZsqO5kZGSgY8eOOHbsGHr16oU1a9YU+ZZbFGKxGLGxsahdu3ZeQSlNwe/Srh8QEIDRo0cXOh5jaHJzc/Hy5csixfH58+c4evQoUlNTIZfLkZubC6lUCkdHR7i6ukIsFuPcuXMYMmQI1q1bhyFDhqB169aCYNra2gpmvpiYGIwcORIZGRmIj4/HunXr8MEHH5TYxgcPHqBVq1Z49CenojfZu3cvPvnkEwQEBGD+/PmwtrYWlt29exfvv/8+wsPDkZiYiCNHjuDChQuC+QsAVq1ahQG1apXpxejU7Nno9L//Yc2aNTA2Nkb37t1x7tw5VK1aFQCQlpaGY8eO4eDBgzh48CDi4uIgk8kQERGBNm3aoEqVKjpbDkhCqVQWK4zJycmYPn06RCIRqlatiq1btwq/a6lUCn9/fzx58gQffPABsrOzsW3bNtSoUQPW1tZ6CbBYLC62h5r/m33w4AGePXsGFxcX2NjYQKlUQqVSQalUIjc3VzDX5pep1Wqo1Wqt3ueb458ymaxA79PCwgJWVlawsbGBjY0NvvzyS0HsHRwcsGXLFjQ9ccJg4/0YP770dfyD+PsKX2SkQS5m1qRJOFy/Pg4ePIhff/0VJiYmuHDhguHaWQq2bduGvn37wgls7RcAACAASURBVMjICFu3bkXr1q112i4tLQ0WFhaCOVJAT+efdz2Y/dVXX+H27dtYvnz5O9tnYRw+fBidOnWCTCbDr7/+ivr168Pb2xszZ86El5cX7t69iwEDBuDDDz/E06dPcfbsWTRv3lxLOF+9egVzc3NBCDUaDS5cuACJRIK6deuiX79+qFq1qlbv0tjYWKsdycnJcHNzQ1paWoE2vnz5Ep9++ilOnjyJ5cuXFznWGhcXB39/fzx9+hSzZs3CmDFjQBJGRkbo37///5vcSvlidK5nT3TYvRtbt25Fs2bNAOSJU3FCdufOHdSqVQvdu3fH4cOHYWxsjPfffx/vv/8+/P39DeJkolQq8cknn+Dy5ctYtGgRIiIisH//fiiVSjg6OmL37t3wdXYGvv8eR6Oi4OXoCEcvrwIhT0VBEiqVqkRxnDt3Lvbv349hw4ahYcOGevdus7OzkZGRgYyMDK2e5Z/HNt8MdQGgJZr5rJNI8OGfHLRKRd++wA8/lL2efwB/X+EzkFfaaQ8PrA0K0mu84c1xh8KWGRkZlXkMLDs7G926dcOePXsQHByMTZs2QSaTFbvN8ePH4e/vr/VmL/DHOKR6506o1GoYv/EDoYkJcrKyoAoMhPnMme98EPvOnTvw9/dHXFzcO4+pAvIeFgMHDsSaNWvQuXNnbNq0CVKpFAcPHsSnn36KK1euAACCg4NRo0YNzJo1C9WrV8fKlSvRqlWrAnUlJycjMTERP//8M+bNm4dPPvkERkZG2L17N27evAk3NzfBYzQxMRFyuVxLCG1tbbFmzRrMnj0bDg4OQtnZs2cRERGBXr16ISIiokTTcFhYGFatWgVTU1Pk5uZCpVLB2dkZt27d0jbf/yF+zMqCSIcXoyMdOqDvyZPYu3cvatWqpde5btCgARYuXIimTZvi5s2bQm/w2LFjqFKliiCE7733nt7xbfmQREREhDB2/PLlS3Tq1AkhLi5YWbXqW49fCwkJwc6dO/HLL7+gXbt2pa6nJAoT4Pzedj61a9fGWTs7yA8eLPsOO3QAdu4sez3/AEofZPK2SU01SDVOpqbw8vLSuoHS09O1vuv7tqZWq0v0yNNFWJs3bw4XFxesWbMGFStWxPDhw9G0adMitzl27BiMjY2RkpICuVwOmUz2/4PsDRoAW7Zg8scfo11iIhoaG+O3nTsR2KMHxHXqYF5cHJKlUnz1F3huVatWDaamprh8+TLq1q37Tvd9+/ZttG7dGsnJydiyZYvW+Nu3336LkSNHQiQSYeHChUhISMCWLVvw448/olKlSgVED8gzNdvY2GDfvn1YvHgxjh49Cl9fXwBAREQEbty4gVGjRuH58+f46aef0KpVK6SmphYwuW7YsAEPHz7EtWvXEBcXh9jYWGRmZkIkEiE6Ohrbtm0rcnwyKysL69evx5kzZ+Dv74/Dhw8jODgYGRkZmDt3bsEx66FDgYYNcW/gQFS6dg0yY+NCHbTYti2ibWyw4NgxnDhxAu7u7nqf7+bNm+PEiRNo1qwZvL294e3tjfDwcCiVSpw7dw4HDx7EzJkzcenSJTRs2FAQwvr16+ts9heJRJg2bZpwjTZu3IhRxsaYevt23vh7YeKef7zbtwO//loqq4dGo0HLli0RExOD3377DU2aNNFre30gifT0dDx8+FDr82euXr2KtDZtoP9oYSG84Y37b+df3+N7G913tVqN3NzcUseSFebevn//fjx8+BAKhQL16tWDUqkssE18fDwyMzNhbm4ulBkZGWmJ44sXL+Dq6iqMl9SsWRNyuRxqtRpHjx5F9+7dBZd3Q/R+/zzuURRjxoyBtbU1PvvsM4Nei+L48ssvMWPGDNT/w9T9ZqaP+/fvo1GjRnj06BFu3bqFtm3b4syZM3B1dYWXlxfWrFmD9957r9B6V6xYgRkzZmD//v3w9vYusJwktm/fjjFjxqBhw4aYP38+KlWqpLVOlSpVsG/fPhw+fBjTpk3DiBEjMHnyZBgZGRXwfM3/3Lt3D4cOHRKywaSkpEClUgmWAjMzM9SvX1/wRHzTCxYAunTpgj5BQVjj7w/Rnxy01H37YuSXX+LMmTPYt28f7OzsSnXOf/75Z6xZswY7S+g5ZGRk4NixYzh06BAOHDiAJ0+eoHXr1oIQenp66mQdOHDgAPYEB2NmTg5M9Yy31Uf8VCoVfH19ce/ePZw7d65AUL2+kERKSkoBYXvzQxKVK1eGu7u78Nm8eTNOnz4NU1NT1K5dGxs2bIDbxo3lY3x68vcVPgON8f2TLubJkyfRqVMnZGZmYvXq1QgNDdVa3rFjRzx9+hQXL14EkPfjeVOAHz16hICAABw/fhwjRoxAYGAgmjVrJgjozJkzUatWLfj5+eksymVxCHjz/6ysLDx69AgtW7Y0iNAWtY2RkRGSkpLg7++PGzduYP78+Rg9enSBcz127FiIxWJ8/vnnqFevHiIiItCzZ0+sXLkSGzduxIEDBwq9RgsXLsTXX3+NgwcPwsPDo9jrmZWVhXnz5iEqKgrh4eEYP3680BurWbMmZDIZZDIZVq1aVeyDNDk5GXPmzMHKlSsRFhaGCRMmoEGDBkhJScGpU6fg6uqKx48fY8CAASCJQYMGISUlRRDMuLg4HDlyBEqlEjKZDCS1PF+tra0RGxsLlUqFkSNHolKlSlo9TGtra517Y8+fP4e3tzdevnypV9jO8+fPcejQIRw8eBAHDhyAWCwWRDAgIAD29vaFb3juHLL8/PRKNCCgo2dzZmYmvL29kZKSgqtXr8LV1bXEqksrbG9+LC0tC4j/rFmz8OWXX+Krr77C0KFD85YbwBGw3Kvz78J/9GJqNBoMGTIEq1evRpMmTbBnzx4h7VO9evXg7Oxc5Nv0+vXrsWHDBqxfvx4ODg54/PgxLC0theUHDhzAuHHjEBsba9CxNl0cAtLT0xESEoLFixfDxMSkTEJb3LJ8Lz+xWAxra2uYmZkVEEmpVIoTJ04gICAAt27dgkwmQ0BAAIyMjPD999+je/fu8PDwKCCsu3fvxpEjR4QeXEkinH+OHz16hHHjxuH8+fOYN28e7t69i88//xwDBgzA4sWLixSVrKwsLFq0CJGRkQgJCRHCL0aNGoXFixfj5s2b8PT0FNbPzc1Fr169kJ6ejm3btsHU1BQJCQlo2LAh4uLiQBLvv/8+du3aJYw/Pn78GFOnToVYLEbbtm2F8cs3P2lpaUJWFV0+zZs3x/bt21GzZs1S30937twRxgePHj2KSpUqaY0PmpubAwBetWoFi2PHSpVXVZf4tZcvX8Lb2xtisRg3btwQvGvflrCVRHp6OjIzMwu+CLyFmN5/M39f4QP+0xczNjYW7dq1Q1JSEhYtWoTBgwfD1dUVISEhiIqKKnSbIUOGwMfHBx4eHpg/fz6OHDmitVyj0aBGjRpYtWoVmjdv/i4OQ4vu3bujffv26N+/v8Hrzs3NRceOHbF//36EhYVh1qxZRYrlzz//jJiYGNSvXx87duzAlClTQBJHjhzBlStXEBoaWmDbmJgYxMXFoeEfThEliXNubq4QIJ0viNnZ2UJPyNTUFJUqVUKlSpUKFc3ff/8dJ06cgKurKzp27AhXV1fBG3X37t0IDg7GwIEDC2wrlUoxZcoUxMXFYevWrQgPD8f27dsFh6j83iGQ91Bv164dateujWXLlhWZV1KlUiEpKanI1HV//rx8+RImJiZwcXHREsTiEhAU59ilUqkwadIkAMD58+dx/vx51K9fH8F+fhgxf76WI5feFPFyTBJXr15F06ZNYWZmhjFjxuDZs2clCpubm5tQVhphKzX/gJjevxN/b+H7j1/M/OD3qKgo1KlTB7dv38a8efMwbNiwQtf39PTEli1bsHTpUlStWhXjxo0rsE5UVBROnTqFDRs2vO3mF2DNmjXYtWtX3uwXBuT48ePo2LEjxGIx9u3bh8aNGxe5LknUrFkT48ePx/jx43H06FH4+PggJycHnp6e2Lx5s9b2JPHpp5/i+PHj2L9/P2xtbXVqk0ajERJ2JycnIzIyEhs2bMDo0aORmpqKb7/9Fj4+Ppg8ebKQvzQrKwvnz5/H9u3bhVAAhUIhLDt16hQePHiA7OxstG7dGhqNpshecEpKipC0IT+heD5VqlSBWCxGXFwcbGxs4OnpKSQkN4S5eefOnTh9+jQmTZqEtLQ0pKWlITU1FUlJSUXGWJqamhYpitbW1hgwYACMjY3Rs2dPTJkyBQ8ePED6tGlof/48Sucb+sd1MjbG9Z49cbBuXS1Ru3//PjIyMiCXy9GmTZtCe27vVNh04R8Q0/t34e8tfECpLmaWWIy48HB4LFjw1nLzvUtu376NDz74AA8fPsSwYcOwePHiAus8efIEvr6+eP78Odzd3XHgwAFUr169wHqpqalwd3fHjRs34Ojo+C6aL5CQkIBq1aohISGhxNANXdBoNIJLf4cOHbB169YSs+EfOnQI4eHhkEgkGDlyJAYPHgwAWLJkCfbs2YNdb0z1pFarMXToUFy7dg179uzRMhvrym+//YZBgwahTp06iIqKgoODAwBg5MiROHPmDJ48eYJZs2bB09MTkydPFsbz2rdvLzxU88X3t99+Q9OmTSGVSvH1118Xu1+SmDJlCn755Rc0b94cmzdvxoULF3D9+nVIpVJ8/PHHCA0NRffu3Q1ubk5LS8OjR49gZ2enVU6yWOeo/OmY8megUKvVUKlUyM7Oxr1797SOTyKR4CeRCKGFhfboyWEXF+zo0kUQtOTkZISFhaFZs2Y4fPjwP+sZ8jeP6f3boP8Ufn8BS5aQpqZkSROEikRUyeUMA2hkZER7e3tOmzaNjx8//quPoMwolUoCoEQiYY0aNQoc0w8//MCuXbsyNjaWVatWFSY9LYxPPvmEX3zxxdtucqE0btyYBw8eLHM9d+7cobOzM42Njbl582adtwsODmarVq3Yo0cP4RxlZWXR2dmZ586dE9ZTKpXs3bs3W7VqxfT0dL3bl5qayqFDh9LZ2Znbtm0rsHz27NkcP348N23aRCsrK8pkMk6bNq3AxKlqtZpDhgyhn58fHz9+TGtra96/f1/ndsycOZNSqZQdO3YkSZ45c4b29vZcs2aN3sekKxqNptCJaZVKJTMyMpiUlMSnT5/y/v37vHHjBi9dusTTp0/z6NGj3LdvH3fs2MGNGzfyhx9+YHR0NOfMmUOJRCLc/xKJhA0bNuQeiaRsE+3mfzp0ENq4Y8cOSiQSduvW7a2dn7fOuXNkly55ExGbmBScXFguz1v+xv3+X+OfIXykzhdTExNDhUIhzEgtkUgYGBj4V7e+zFy+fJkikYiPHj1i9erVKZFIOH36dGH5xx9/zEWLFjEiIoKjRo0qtq6rV6/SycmJubm5b7nVBfnf//7H0aNHl6mOWbNmUSwWs379+kxOTtZ5u3v37rFChQp0c3NjSkqKUL5w4UIGBwcL33NyctilSxe2bdu2VDPR79q1i66urhw0aFCR7ZszZw69vLxoa2vLyMhIrlixgk5OThwwYACfP39OMk8o+vbty5YtWzItLY0LFy7U+4Gcnp5OALS3t+eqVatoa2vLnTt36n1M+hISEsJ169YZpK5nz55RJBLRzMyM48aN4/Pnzzlt2jSe9vAwjPD17UuSXL16NcViMT/55BODtPsvJyGBjIzMO74OHfL+RkaWz8DOf5Lw5aPDxRwyZAhFIhEB0MnJiYmJiX9hgw3DmjVraGJiInyfN28epVIpK1euzDt37tDd3Z3Xr19nkyZNuH///hLra9myJTdu3Pg2m1woly5doqenZ6m2TUpKYp06dSiRSBgZGan39oMHD6apqSnPnDkjlGVmZtLR0ZEXL14Uvrdt25YhISHMzs7Wq/6EhAR++OGHrFKlCg8dOlToOsnJyZw0aRLNzMxYrVo1vnr1SliWmprKcePG0dbWlvPmzWPXrl0ZGBjI169fU6VSsXLlyjx16pRebYqIiKC5uTnDwsIoFov53Xff6bV9aVmwYAGHDRtmkLrUajU3bNjAtLQ0kmRGRgYVCgUTxo3Le+Eti+iZmJCRkZw7dy5FIhGnTZtmkDaX8/fmnyd8OrBv3z6KRCLWqVOHCoWCv/zyy1/dpDIzefJk2tnZaZW9ePGCdevWpVgspqmpKZ8/f86KFSvq9MDetGkTW7Ro8baaWyQajYbOzs68ffu2XtutX7+exsbGdHV15b179/Teb3JyMqVSKSdOnKhV/tVXXzEkJIQkmZaWxlatWrF3795UKpU6163RaPjTTz/Rzs6O48aN4+vXrwusk5WVxfnz51OhUHDgwIFcu3Yt/f39C60vNjaWCoWC5ubm3L17N0lyy5Yt9PPz07lN+VSvXp0+Pj50dnZmZGQk7ezsePbsWb3r0ZeYmBjWqlXrrdQdFRXFkJAQvrxxg7llNXfK5ZwxYgRFIhGjoqLeSnvL+fvxrxS+7OxsLliwgNnZ2Tx79iwVCgWPHTv2VzerTHTv3p3e3t6FLuvXrx/FYjEtLS0ZEBCgU325ubl0cnLilStXDNlMnRgyZAgXLFig07o5OTls27YtRSIRP/nkE6rV6lLt84MPPqCdnZ3W9hkZGXRwcODly5eZnJxMPz8/Dho0qMA4W3E8evSIbdu2Za1atRgTE1NguUql4vfff89KlSqxU6dOvH79Okny3Llz9PX1LbD+69evGRgYyG7dunHLli2sUqUKu3TpwgYNGug1lknm/Q4A0NnZWRgX3LlzJxUKBY8ePapXXfqSm5tLc3NzrR6tIVAqlXRxcWFoaCitrKx40d2dmpLG/ovxCThXqRLFYjF/+ukng7aznL83/0rh+zMHDx6kQqEQzFn/RJo0aVKkqPXt25dfffUVbWxsKBKJOHjwYJ0EYsaMGQwLCzN0U0vkl19+YevWrUtc78SJE7SwsKCFhQVPnDhR6v0dOHCAUqmUP//8s1b5vHnz2K1bNyYmJtLX15ejRo0q1inoTdRqNRctWkRbW1v+73//Y05OjtZyjUbDXbt2sWbNmmzatGmB9t+9e5fu7u5aZWlpaWzZsiX79u0r9DizsrIEM+Vnn31WaG+yqPa1aNGCIpFIGDPM59ChQ1QoFNy7d69OdZUWf39/ocdqCO7du8eAgABKpVKOHj2aT548IWNi8hzfSiF8WRIJG4nF3Ldvn8HaWM4/g/+E8JF5piJHR0feuXPnr25KqahSpQoHDhxYoFyj0dDFxYXXrl2jpaUlFy9eTLlcTltb2xLHg+Lj42lpaamXg4gheP36NStUqKDlYPImarWan3zyCUUiEdu2bVtAVPTh+fPntLGxobu7u5aopaen087OjocPH6a3tzenTJmis+jdvHmTzZs3Z9OmTXnjxo0Cy8+cOcOWLVuyRo0a3LFjR6H1vnz5kpaWlsL3/B7nkCFDCry09OzZk59//jl79uxJNzc3bt68udi25uTksGfPnjQ3N2fz5s0LXef06dO0s7Mr8DJgSD7//HNOnjy5zPVcv36dffr0oY2NDe3t7fnjjz9qr5Dv9a2H6GWKxRwukWiN95bz3+E/I3wkuWLFCrq7u+e9Kf7DsLKy4uzZswuU//7773RycuKhQ4fYsGFDknnCEhAQQJFIxNDQ0GLHq0JDQ/nNN9+8tXYXRdu2bblp06YC5ffv36erqyuNjY25fv36Mu1DrVYzKCiInp6eXLZsmdayOXPmsGPHjvTw8ODMmTN1qi83N5czZ86kjY0Nv/322wICdevWLXbt2pUuLi5ctWpVseddpVJRLBZTrVYLPc7w8PACgvbw4UNaW1szNTWVJHn06FHWqlWL/v7+vHbtWoF609PTGRgYyODgYIrF4mKF7dKlS3R0dOT333+v0/Hry4EDB4oUXl04f/48Q0JCaGdnx1mzZnH79u2sUaNG4dYMHUOeNCIRM0UijjQy4q1bt8pwdOX8k/lPCR9Jzp07l97e3nz58uVf3RS9MDIyKtQNffny5ezduzfHjBnDGTNmaC3bsWMHzczMaGFhUWTs3IkTJ+jp6VnqsbPSsnjxYvbr10+rLDIykhKJhHXr1mVSUlKZ9xEZGcn69evTxsaGGRkZQnlqaiqtra3p5OTEr7/+Wqe6zp8/zzp16vCDDz7gw4cPtZY9e/aMYWFhtLW15Zw5c3Q2R1asWJG3bt1izZo1OWnSpEJ7cWPHjuXYsWO1ypRKJRctWkSFQsHw8HChx/7y5Us2btyYAwYM4Jo1a2hkZFTidb158yZdXV25ePFindqsD2lpaTQzM2NWVpZe2x07doxBQUF0cXHhN998I5zPwMBArlq1qugNSwh50hgbc7eJCVuZm/8jX37LMRz/OeEjyQkTJrBx48alCkz+K1Cr1QTAuLi4AstCQ0O5cuVKVqtWjRcuXCiwPCcnh8HBwRSJROzQoUOhY1F16tThr7/++tbaXxgPHz6kQqGgSqVicnIy69WrR7FYzFmzZhmk/jNnztDOzo6DBw8uIBzh4eE0MTFhdHR0ifW8fv2a48ePp52dHX/44QctcUpJSeHUqVNpbW3NcePG6S3WLi4urFy5Mr/88stCRS9foP8stPkkJiYyLCyM9vb2nDt3LmvUqMEJEyZQo9GwWbNmbNSokU7tuH//PqtUqcK5c+fq1X5dqF+/vk7jsxqNhnv27GHz5s1ZtWpVrlixQss7OTY2lk5OTrqFmBQS8pQ+fTq9rK3p4ODwzk375fz9+E8Kn0aj4cCBA9mmTRu9Y7X+Ch4+fMjCkuxoNBra29vz4MGDdHJyKnbc5+DBg7S0tKSZmRm3b9+utWzFihVCZo93Sa1atThz5kwaGxvT2dnZYOOvycnJrFy5MtetW0cbGxutTCfHjh2jSCTSKQ7wyJEj9PDwYM+ePfnixQuhPDs7m19//TXt7OzYv3//AhlKdOHBgweUyWTFJhv4+uuv2bNnzxLr2rJli3AO88d1ZTIZV65cqXN7njx5who1anDq1Kk6j3XqwqhRozhnzpwil6vVam7evJm+vr6sWbMm161bV6iJuHfv3sXWUxz3799nhQoVWLVqVb17n+X8O/lPCh+ZZy7q0qULu3fvrpf7+l/B9u3bKZPJCpTfuHGDbm5u/Oqrrzh48OAS61EqlezVqxdFIhH9/f0F89/r169pY2PDBw8eGLrpxbalatWqBKCzF6ouaDQadu/encOHD+eyZcvYqVMnYdnp06dpZmbGli1bFltHSkoKhwwZQhcXF+7YsUMoV6vV/PHHH+nu7s727dvz6tWrpWrjnTt3WKlSJVarVo0HDhwodB2lUkl3d/cSY+5iYmLo4ODA1atX86effqKzszP9/f0pFov1ikUk8wLw88caDXU9Nm/ezPbt2xcoz83N5Zo1a1i9enU2atSIO3bsKHKf+eOcpempxcbGUi6X09fXV+/zUc6/l/+s8JF5ruL+/v4cMmSIQd9yDU1ERAStra0LlC9evJj9+/env79/gV5ccZw5c4YKhYJyuVyIXxozZgwnTJhgsDaXtH9LS0uamJjQw8PDoHVHR0ezdu3azMzMpI+PjzC2eeTIEdra2rJChQr8/fffi9x+x44ddHZ2ZlhYmOB1qtFouHfvXtapU4d+fn5ligm9du0anZycuGrVKnbp0qVQBx8yTzCaNWtWbF0HDhygra2tljinpaXR3d2dEomE8+bN09sjNjk5mU2bNuWAAQMM8kIYHx9PKysrQdSysrK4ZMkSuru7s3Xr1jxw4ECJv73Ro0cXMFfrwtGjRymVShkQEPDOx7DL+XvznxY+Mu9B0bBhQ4O4Xb8t+vfvz6pVqxYo79atG5ctW0Zzc3O9xyvVajXDwsIoEonYpEkTXrhwgba2tqXKTakPI0eOpEgkYmBgIDMzM2ljY2OwJOLXrl2jra0tb968yUOHDtHb21sQLYVCwb59+/Ljjz8udNvnz5+zR48e9PDw0ArujomJYevWrenl5cWtW7eW6QXp4sWLdHBwEHJYDhw4kMuXL9dap27duvzoo49Yp04dbtmypci6Nm7cWGRiBlNTU06cOJHt2rWjl5eX3nFq6enpDAgIYM+ePQ2Sz9XDw4Nnz57lvHnz6OjoyPbt2+uceu3Vq1e0srIqdHy7OLZu3UqJRKKTqbic/x7/eeEj85wEqlevzvnz5//VTSmU1q1bs2nTplplarWatra2XLp0KT/44INS13358mU6OztTJpPRx8fnreVyfPjwId3c3CiTybTisPr06VMg1KA0vH79Wqv9nTp14rJly7h161ba2dlx7969tLGxKZDuTKPRcM2aNbSzs+PEiRMF4b9z5w67d+9OJycnRkdHl9lMlu9s86aYjRs3rsC4laWlJcViMUUiEVu2bFlo0oUlS5bQycmJsbGxBZadOnWKIpFIGMvatWsXPTw8GBwcrFeqt6ysLHbs2JEdOnQo07hYUlIS69atS3Nzc/bo0YOXLl3Sa/uZM2fyo48+0mubFStWUCwWc8SIEXptV85/h3Lh+4PHjx/Tzc2Nq1ev/qubUoDq1aszNDRUq+zKlSusWrUqP/roIy5atKjM+xg7dixFIhFNTEwYHx9f5vre5Ouvv6ZEImGtWrUKJAxfv349O7wxLUxpGTx4MHv37k2NRsP79+/T2tqaq1evpr29PS9cuMApU6YUGAd9+PAhg4KCWLduXcEjNj4+nkOHDqWNjQ1nzZqlc2hCcRw7dowKhYK7du3SKp85c2aB3KEODg5aM4t8+eWXwjKNRsMZM2awatWqRYpYSEhIAfNxdnY258yZQxsbG06dOlUrtKM4cnNzGRoaSn9/f70tCvHx8ZwwYQKtra3ZrFmzUl3jrKwsOjg46DWWOnv2bIpEor9s2q1y/hmUC98b3Lp1iw4ODoXOn/ZXolAoOHXqVK2yhQsXcuDAgVQoFAZzSrl16xalUiklEolBXNtTU1PZsGFDisXiAjGG+bx69YoVKlQok8Bs2LCBHh4eQvb+cePGMTAwkE5OOxP2MQAAIABJREFUTrx69SoTExO1wgJUKhWjoqIEccvNzWVqaio///xzWltbc8yYMQaL8zxw4AAVCkWhcZRLlizhkCFDtMpcXV0JgCYmJlovNGq1miNGjGCdOnWKfTGxsLAocoaBJ0+esHfv3nR1deWGDRt0MtuqVCoOGjSIfn5+OuXdfPjwIYcPH04rKyuOGDGCDx8+5O3bt1mpUqUSt/0z0dHRbNeunc7rjxkzhiKR6K3EJJbz76Jc+P7E+fPnqVAoePjw4b+6KQJvOqHk07lzZ37xxRf08fEx6L7mzZvH2rVrUyKRsFq1akXGkJXE1q1bKZfL6ejoyJs3bxa7bsuWLQv0hnTl3r17VCgUPH/+PMm8xNOmpqZ0cnISwiMmTpwozLGWP3VT8+bNeevWLebk5DAqKor29vbs169fqY+3MPITQh8/frzQ5evXr2f37t21ymxtbWlkZMQjR44IZTk5Ofzwww/53nvvFevZeO3aNQIo0fvxt99+Y926ddmyZUtevny5xOPQaDQcPXo069aty4Qi5nK7desW+/fvT2tra06cOFErP2hRE9MWh0qlYrVq1bTOQ3H07duXYrGYGzZs0Hkf5fx3KRe+Qjhy5IjWw/SvRiQSaZl71Go1raysOGrUqAKmsrKSlJRES0tLXrp0id7e3pRIJHrNUaZUKtm5c2eKRCL2799fJ2+6efPmcejQoXq3NScnh40aNdLKvtK5c2eampoKAvbixQtaWVnx7t27/PLLL2lra8slS5ZQqVRy3bp1rFy5Mtu1a6eTAOjD5s2bi58C6MUL3howgAccHPKCrHv3JufO5ddTpmjddxkZGQwKCmJwcHCJjkf9+vWjq6urTu1TqVRcunQp7ezsOHz48BKD7zUaDadNm8bq1atrZT25dOkSu3fvTltbW86YMaPIXqG+E9Nu3bqVDRs21KlX2rZtW0qlUp3moSynHLJc+Ipk+/btdHBwKLG38rZJTk4mAC3niosXL9LLy4t169blb7/9ZvB9DhgwQMig8tVXX1EqldLNza3Ec3Hu3DlaW1vT3Ny8yIlYC+PGjRt0dXXV22Ny/Pjx7NChAzUaDTUaDadMmUJjY2Ott/5x48axW7durFmzJtu3b8/Hjx9z//799PX1ZaNGjXTuUejDTz/9RAcHh8IdOWJiyJAQUi6nSiYrOCmqXJ63PCaGSUlJ9PPzY//+/XVyrslPYaYPSUlJHD58OO3s7Lhs2bISQxgiIyNZuXJlbtq0ie3bt6ejoyPnz59f4hjgggULdH650Wg09PPzK3EaJrVazcaNG1Mmk/HcuXM61V1OOWS58BXLd999x0qVKhnM3b40HD58mBKJRKtswYIF7NOnD62trd9KUO6FCxfo6uoq1J2QkCCkFBs1alShvbhPP/1UCIzX1wtQo9GwSpUqOvW6Bg4cyNDQUG7dupUuLi5MTEwUTHEeHh6sVq2aIKD37t2jsbExFQoF165dy3PnzvH999+np6dniTMclJaVK1fS2dlZmHdPCx0TKVMkotrEhF84OHDcuHE6tfPRo0cEUOoclLGxsWzRogV9fX2LTDGm0Wh44MABVqtWjRKJhJ9//rnO11qfiWl/++03Vq1atVgRzsnJoZeXF83MzPSe1LiccsqFrwQWLFjA6tWrF/BGfFdERUWxQoUKWmUdOnTgoEGD2KtXr7e23yZNmhRw8lmxYgVlMhkdHBwEN/tHjx6xSpUqNDIyKpNHbHh4uE6zJLi6utLIyIhisZgrV66kWq3mkCFD2LhxY7Zt25ZLly4lmZeizcLCgl5eXjx79ixDQ0Pp6OjIpUuXGiQ2rTC+/fZbVqpUqfDUa6WYOifXyChvOx3I77WVBY1Gw/Xr19PFxYW9e/cWRFStVnP79u1s1KgRq1evzjVr1nD16tVa90FJ6DMxbXBwMJcUc9xpaWl0cXGhlZUVnz59qtvBlVPOG5QLnw5MmTKFDRo0ELwG3yXDhw/XGrdRKpW0sLBgmzZt9Boz0Ze1a9cWOvFtamoqmzdvTpFIRD8/P4rFYnp7e2vlsiwN+/fvLxCr+GdycnIolUq13P1btWrFli1b8sqVK7S2tmZcXBwHDBhAJycnmpqa8uOPP6aNjQ0jIiJ0duMvDZGRkaxSpUrhHrZlmCyVpqZ5sw6UgLOzc5HB+fqSkZEhJN8ODQ2lj48PfX19+fPPP2v19rds2UI7O7sSg9FzcnJ49OhRVq5cmdWrV6eZmVmRvcobN27Qzs6uyPHM/PkVnZycipzPsZxySqJc+HRAo9EwLCysVGa8stKuXTvWr19f+B4TE0Nvb29WqFDBIFP3FEV2djbt7e0LnWg1PT2dHh4egtu9IcYZs7OzWbFixWJ71levXqVMJhP2a2VlRTs7O+7YsYPjxo1jcHAwnZycOGjQINavX59yuZyjRo0q0hPREGg0Gn7xxRf08vIq2swYElKyebMYsye7dCm2DUlJSQRgsPnlsrOzGR0dzUqVKgnTNxXldbtv374iwzXy+eabbygSiSgWiwmAUqm0yHM1cODAIkNf7t69S3Nzc3p6epYnmy6nTJQLn46oVCr26NGDISEh7zTZbd26dRkcHCx8nzt3Ljt06MAWLVq89X1PnTq1QPaLnTt30sTEhPb29jx79iwDAwMpEonYo0ePMp+X/u3a8XzPnnkejm94OvIP4Zo7dy4BsFq1amzcuDH9/PxoZGRES0tLymQyurm5cfTo0bSzs6NMJisxwXNZ0Wg0nDhxImvVqqXlvq/Fixd5DiulEb38j1wunIPCmDx5stZs7qUlIyOD33zzDV1cXBgUFCSEYezdu5fVqlVj+/btC81zmh+g/8svvwhlb47PZWVlsVatWpRIJARAhUJR6P6fPn1KS0vLQl9+Ll68SGNjYzZo0KA872Y5ZaZc+PQgJyeHgYGBHDBgwDtLau3s7MzRo0cL3z/44AMGBQXpNK1OWYmLi6OVlRXT0tKoVqvZrVs3ikQi9unTR+vhs3PnTpqbm7NixYqlm9fvD09HpVTKbImkSE/H2z/9xKioKPr7+7NHjx60t7cXzJ4mJiasUqUKg4KC2L17d44fP96AZ6IgarWaI0eOZL169fjy5Uump6cXbp6bO7fswmdikje/XBFUrVqV3bp1K/WxpKSkcObMmbSzs2OXLl0K9ZDMyclhZGQkbWxsOGnSpAJenDExMbS3t+f69ev5ww8/0NraWispQb6JEgA7d+5caDsmTpyo9aIVFBTE+fPn89ChQ5RKpQwMDCwXvXIMQrnw6Ul6ejr9/Pze+oM1H3Nzc2GgPzc3lxUqVKCTk1PhXoNvgS5dunDy5Mm0tbWlmZlZkcKWk5MjxO+1a9dOd1OUHp6OGhMTRlapwoEDB3LkyJGC6Sz/ExUVxUePHtHa2vqtmjfzs5k0adJECBYfNGgQ5XI5P/roI549e/b/X4x69y6b6OV/+vYttC2vX7+mSCQqVe82ISGBU6ZMoY2NDfv27avTPfXs2TP269ePzs7OXLt2rdYL4NWrV2llZUUjIyPK5XKuX79ea9tLly5RJBIVmhA+NTVVa+7Eu3fvUi6XC6btDz/8UO/jK6ecoigXvlKQlJREHx+fUk+MqQ8SiURwBDh58iS9vLxYuXLld9bj7NmzJwHwvffe0ymt2JEjR2hlZUVTU9NiZxcgWSpPx2yplOrFiymTySgWiymRSGhsbMywsDDeunWLYWFhnDRpkoGOviBKpZJ9+vRhq1athF5PZmYmAwICCIAikYgymYwVKlTgt99+m2eyNYTwFZHrcs6cOTQzM9PrGOLi4jhq1ChaWVkxLCxMr+TV+Zw6dYr169dn8+bNhXjFX3/9lXK5XHgRee+99wpsd2j9er6ePr2AOXvxF19ozaQwefJkwTQqlUq5detWvdtYTjlFUS58peTJkyd0d3dndHT0W9tHTk4OAQgP2IiICDZr1owjR458a/vM5+nTp/T09KREIqGjo6NeKdzUajX79u1LkUikJRBalMHTMVsiYZCNDRcvXszg4GAhhOHBgwe0trY2WJ7NrKws3r9/nydOnOCmTZu4YMECVqtWjU5OTmzdujW9vb2F8UUTExOt3qdIJMoz6b3lHp+3t7fOs3PcvXuXgwcPppWVFceMGVPqmL98VCoVV6xYQXt7e37yySfs1q2b1rkQi8X/n1f0jcD9P5t+NSYmzAL4qlUrMiaGarWapqamwnk0MTFh5cqVy9TWcsp5k3LhKwN37tyho6NjiRkmSsuFCxcoFouF7wEBAaxevXrpxtH0YNmyZZRKpfTy8mJ8fDwXL17Mrl276l1PTEwM7ezsKJfL+f3332svLIOno1okojI4mA8ePKCNjY0QpjBo0KACybwLIzs7mw8ePODJkye5efNmRkVFcdKkSezXrx/btGlDHx8fWllZUSaTsVKlSvTz82OnTp3o5ubGGjVqMDo6mvv27ePFixd57NgxrlixgvXq1SsgfLNmzXqrY3xKpZJisbjE+fauXr3KXr160cbGhtOmTTN4TOqrV68YHh5OhULBiIgIfvvtt2zUqBEB5A0J6GHOpqkpf/6j92xhYcHhw4fz4MGDek+oW045xSEiSZRTamJjYxEYGIh169bh/fffN2jd33//PYYNG4bMzEzk5OTAxsYGYrEYiYmJMDY2Nui+ACAzMxOBgYE4ffo0Jk6ciFmzZgEA0tPT4ebmhitXrsDFxUWvOjUaDUaMGIFly5ahYcOG2Lt3L6xVKsDNDcjOLn1j5XLMGDgQacbGWLBgAe7du4dGjRrh8OHDyMzMxLNnzxAfH49nz54V+D89PR0ODg5wdHSEs7MzHB0d4eTkJHzyv1tbW0MsFiMzMxOdOnWCTCZDaGgoLl26hHPnzuHSpUtwdXVFw4YN4ejoiMjISBgZGcHW1hb79u1D7dq1gYQEgxwrHj8GFAqt4ujoaISHhyO7iLrPnTuHmTNn4syZMxg9ejSGDRuGihUrlr4dJXD16lWMGjUKr169QlRUFHx9fWGyZg2kEycCmZk615MJ4NbgwagXHf3W2lrOf5y/Wnn/DRw/fpwKhcLg7vMTJkygg4MDyTyX8cqVKxfpEVdW9uzZQ1NTUyoUikJTh40YMYKfffZZqeu/evUqXVxcaGRkxJOdOpW5F5QjlXKiRML33nuPtWrVorGxMcViMV1cXNioUSN27tyZQ4cO5f/+9z+uWrWKe/fuZWxsLBMSEnTyDHz27Bl37NjB8ePH08rKisbGxnR1dWWXLl04Z84cHjp0qEAAtbu7O1u2bFkwO8lbiuNr0KBBgXE0jUbDI0eOsE2bNnR1dWVUVJRB5hTUFY1Gw02bNrFSpUqc0qYN1SYmpTtuHQP3yymnNJQLn4HYuXMn7e3tDept2a1bN2Haofwg6ZUrVxqsfjJvPC40NJQikYihoaFFisLNmzdpb2/P7OzsMu1vwoQJ/NEQY14Af7G05O7du7l9+3ZaW1uXOqA/JSWFBw8e5KxZsxgSEkIXFxdaW1szICCAzs7O/OCDD3RKjZWYmFj4+XsLmVvUajWlUqmQkFuj0XDXrl1s2rQpPT09uWrVqr/UPPj69Wte9/KiqrTXV4fA/XLKKS3lwmdAfvzxR7q6uhpsTrfGjRuzTZs2JMkWLVrQzMyMz549M0jdZN4s7gqFgqamptyzZ0+J6wcEBHDt2rVl3m+Gv79BhC/Bz49k3lxsb85UXhxZWVk8ffo0Fy5cyD59+rBatWo0Nzfne++9xzFjxnD9+vW8d+8eExIS6Ovry9GjRxvGg7YUHqw0NS0yV+eGDRsolUqZm5vLTZs2sW7duqxVqxbXr19f4gwL74R3ELhfTjmlpVz4DMzChQvp6elZ5tyVZJ7pbNCgQczMzKRcLqevr68BWpjHlClTKBaL2axZM51NYdu2bWOTJk3KvO/cnj0NInyaPn1469Yt2traMjU1tcB+lEolL1++zJUrVzIsLIy+vr40NTVlvXr1GBYWxlWrVvHKlSsFMs7Ex8fTx8eHkydPNmzYiJ5OHsUlqG7evDnd3Nzo5eXFxo0b85dffnlnIS468Q4C98spp7SUC99b4PPPP6evr2+Zk+haWloyMjKShw4doqOjI7/44osyty0+Pp5eXl6USqXFZsAvDKVSSVdXV164cEHv/T59+pRLly5l27ZtOVUmY7ZYXKaHYq6RERkZyV69enHmzJn/196dh0VZb3EAPzMDMiMoDDDDIiiRoIK4oJgprpSKpgaYWoJ6s6uhpaKgmZr16A19EFGvu5V4SSXL9XbzYpERkUqu4EWUxSW1gKumBcgy871/zHUKWZzlHYac83ke/tB55/f+3nl0Dr/tHKjVahQWFmLPnj2IiYlBcHAw7Ozs0KlTJ0RFRWH9+vU4fvz4Yw/WX79+HT4+Pli+fLnez6iTH37QTOFJpZov9ke/6KVSzeuNrG9VVFRgw4YNICJ06tQJ6enpLSvgPWTiYxyMGcPK3JtrnkTvvvsu3b59m8aMGUP//ve/SSaTGdROeXk5+fv707Fjx6iqqopGjRplVL8++OADmjlzJnl5edGVK1f03qFpZWVF0dHRtHHjRvrwww+bvBYA5ebm0uHDh+nQoUNUVFREoaGhNHXqVBqxfj3ZBAQYtdNRIhbTB7W1dOjQISopKaHExESytbWloKAgCgoKovfee4969epF9vb2Ord55coVCgkJoVmzZtH8+fMN7luTevcm2rePqKyMKDmZKDeX6O5dIrmcKCCAaOrUers3iTQ7azdv3kxJSUnk5eVFIpGILly4QFZWLfS/8L17wrRz964w7TD2R+aOvE8qlUqFl19+GaNHjzYoebNKpQIR4ebNmwgMDIRcLjc4T2FFRQUGDRoEsVhsdKq10tJSODg4NLiRpLq6Gunp6Zg9eza8vLzg5eWFOXPmID09vX4NPCN2OtYS4bC1NVxdXTF06FAcPnz494PSBrp06RI8PT2xceNGo9oR2n//+18sW7YMzs7OmDhxIs6fP4/Q0FD4+fmZu2tN4xEfa8E48JlQVVUVQkNDMXnyZJ2DVk1NDTp37qwt++Pg4ACxWIzx48cb1IejR4/C1tYWTk5OBk1RNiQqKgoJCQkANDsiU1NT8corr0AulyMoKAjLly9HTk5O01NwRux0rLWxweXdu+Hi4tJwVhg95ebmwt3d3ahCukK7desWYmNj4ejoiGnTptUpbmtra4v4+Hgz9k4HvMbHWjAOfCZWXl6Ofv366bU70MfHB0RU76ddu3Y6J19WqVSIjIyESCTCuHHjBM1qf/DgQTg5OeG5555DmzZtEBoaii1btuidAqt2wwao9PxyrJRIgE2bEBERgdWrVxv9LKdPn4aLi4tJi/rq48qVK4iOjoZcLsebb76J69ev13k9OzsbIpGoWc/mGYR3dbIWjANfM7hz5w4CAgKwYsUKna5fu3YtrK2t6wU+d3d3nUY4Fy5cgIuLC2QyGQ4dOmRs96FWq3H69GksW7YMPXr0gJOTE5ycnLBo0SKdR1x/3Hwyb9487eaTZUolHkgkUD1m2rOWCOUiEfJmz8a5c+fg6upq9Jf/8ePHoVQqW0QC5IsXL2Ly5MlwdHTEW2+91eiu4HHjxsHb27uZe2eYW3378jk+1iJx4Gsmt27dgre3t047KcvKyuqV3HFwcNBpHeudd96BWCxG3759jZoGrKqqQlpaGmbOnAkPDw907NgR8+fPR0ZGBmpqarBjxw6EhoY2+v6ffvoJhw8fxpIlSzB8+HA4OjrCw8MD4eHhiI+Px1dffaUt6fO4nY5qqRTpcjl6ESE8PBxjxoxBUlKSwc8G/F48VZfzi6Z05swZREREQKFQYPny5fWzvjzCwcHBpNUnhHD79m1ERkZirLs7am1sDAt8nLmFmRAHvmZUVFQEd3f3enXKGvIwSTKRpizLlStX6l1z8eJFZGVlAQBKSkrg5+cHiUSC9evXG9S/O3fu4OOPP8b48eNhb2+PZ599FvHx8cjLy6s3TVtRUQGFQoGCggJt5pP4+HiEh4drM58MHz4cS5YswaFDh3Q7eF9aqlnTiYrSlKyJitL8ubQUYWFhmDVrFlq3bg2RSIQDBw4Y9IyAZt1ToVAgPT3d4DaM9d133yE0NBTu7u5Ys2aNTr+k5Ofng4gEqz5hCvv27YObmxtmz56tSR4u8MF9xoTAga+Z5eTkQKlU4siRI01eFxERgbi4OHh5eSEjI6Pe62q1Gn5+frC1tUVSUhKsra3h7e2Na9eu6dWf4uJiJCUlYciQIWjTpg3GjBmDDz74AD///HOD1z/MfLJ+/Xr4+flBLpfDzs4OwcHBiImJwZ49e1BYWCjo2bKH5YZ+/fVXjBo1Cj169IBIJMKIESN0L3j7f4cPH4ZCodDWOGxOarUaaWlpGDhwIJ566ils2bJFrxRwf/nLX9CuXTsT9tBwJSUlGD9+PHx9fZGZmVn3RQEP7jMmBA58ZpCVlQVnZ2ftaE2rpESzG27SJJxQKPDj4MGaPzewwP/pp5/C1tZWOxU6Z84cne6tUqlw8uRJLF68GF27doVSqcSrr76KQ4cO1Vszq6mpQU5OjjbzSWBgIGQyGXr27IkZM2Zg5cqVcHBwaDBripDi4uIQExOD7OxseHh4oLKyEpmZmXB0dETr1q2xd+9endrZu3cvlEolsrOzTdrfR6lUKuzfvx+9e/eGn58fUlJSDDriolQqMXPmTBP00HBqtRq7/7/DdsGCBaioqGj4QiMP7jMmJA58ZnLkyBEolUrk5OQ0WaRT+6UQFqa5Dprzcs7OztqgZ2Njg8TExEbvVVlZic8//xzTp0+Hm5sbOnfujIULFyIrK0ub17GxzSe+vr6IjIzEunXr8P3339f7Yhs9ejS2b99uss+pvLwcTk5OKCwsxMiRI+ucs1OpVJgyZQpEIhEGDBiA+/fvN9pOSkoKXF1dce7cOZP19VE1NTVISUmBn58fevXqhf379xu8u/bmzZsgIr1H9KZ08+ZNjB07Fv7+/rpXJmliOpux5sKBz4x2796Nhfb2mi39Ok4DqTdtwrBhw7Rrf1ZWVrCzs4Ozs3OddaKysjIkJycjLCwMbdu2xYABA7B69WpcunQJQOObT8LCwvD+++/X3XzShLS0NHTv3t1kabO2bduG0aNH4/jx4/D09GxwavDhkQQbGxt8+OGHDbbRrl07QStnNOXBgwfYunUrvL29MXDgQKSlpRn9+cyZMwfOzs4C9dA4arUaO3bsgEKhwJIlS4yu2MFYc+PAZ06bNmlyTup5ju1tR0fMmzcPp06dwpdffgk7Ozu0atUKGzZsQEJCAgYMGIC2bdsiPDwcycnJKCoqqrf5RC6XY9iwYVi8eLHum08aoFKp4OPjY5I1M7Vaja5du+Lo0aMYNmwYtm7d2mQ/3njjDYjFYvTu3VtbZXzdunXo0KEDCgoKBO/fo3777TesWbNGW8qo3lqXETw9PRHVArKYXLt2DSNGjECPHj1w5swZc3eHMYNw4DMXIzKXqP+/1TstLQ1SqVQ75SmVSjFt2jQkJiYiMTERkZGR6NSpE2xtbdG/f3/ExMRg9+7dKCgoEHSEtnbtWkycOFGw9h46duwYunTpgszMTHh5eelUXy4vLw/t27eHtbU1Ro8ejaefflqwMlGNuXv3LpYvXw6FQoGIiAjBMuT8sX0iwoULFwRtVx8qlQpbtmyBs7MzVqxYUT8FHWN/Ihz4zMXIqty/hITUO+AuFou15YumT5+O7du34/z58wZtpNDH3bt34eDgIGitQAAICwvDpk2bEBISolcBXrVajeDgYBBpKhjom1FGVyUlJXjrrbfg6OiIyZMnIy8vzyT3Wbp0Kezt7U3Sti6KioowZMgQBAUFmTX4MiYUDnzmIEA6pwciETxsbODi4gJfX1+0b98eSqUSxcXFZnmkGTNm4L333hOsvatXr8LR0RFHjhyBt7e3ziMMtVqNuLg4dOvWDadOnYKPjw8kEonOWXN0cf36dcyePRtyuRzR0dEm/8x9fHwQFhZm0ns0RKVSYd26dXByckJCQoLJf4FirLlw4DMHARL41rZqhQoBA42xcnJy4O7uLtgU2IIFCxATE4PBgwdjx44dOr1HpVJh1qxZ6N27d53qEe+//z4kEgmefvppFBYWGtyngoICTJs2DXK5HLGxsYKPcBtSWVkJkUhU/+iLiV26dAn9+/dH//79tRuiGHtSiJuj9BF7RE6OUbXoiIgk1dUkKywUqEPGCwgIoI4dO9LBgweNbquiooI++ugjCgwMpBs3blBkZORj36NSqWj69Ol09uxZ+uqrr8jR0VH72qJFi+jGjRtka2tLvr6+tHDhQr36k5ubSy+//DL17duX2rVrRwUFBZSQkEBubm56P5u+Nm7cSDKZjPr162fyexER1dbWUkJCAvXr148mTJhA3377Lfn6+jbLvRlrNuaOvBbphReMGu1pf154wdxPUscnn3yCQYMGGd3O9u3b8cILL2DAgAH4xz/+8djra2pqMGnSJAwZMuSxqb82btwIa2treHh4IDc3t8lrT5w4gdGjR8PV1RWrVq0y+UH9hgQEBOD5559vlntduHABQUFBGDp0KIqKiprlnoyZAwc+c3hCi3RWV1fD3d1dcyjfQGq1GgEBAVi5ciU6der02HWlqqoqREREYMSIEY1nDXnE7du38cwzz0AkEuH111+vc6hcrVYjPT0dISEhaN++PTZs2KBzu0KrqamBWCzGv/71L5Pep7q6GsuXL4ezszO2bNlisjOZjLUUPNVpDt26EUmlRjVRLZHQzwqFQB0ShrW1NU2fPp02bdpkcBsZGRlUW1tLBw8epGXLlpGVlVWj1z548IDCw8O118tkMp3u4ejoSCdOnKDk5GRKTk4mNzc3+uGHH+if//wn9evXj6KjoykyMpIKCgpo1qxZOrcrtJ07d5KVlRWNHDnSZPc4e/Ys9enTh7Kysuj06dM0Y8YMEolEJrsfYy2BCADM3QkgPNCNAAAKn0lEQVSLU1pK1KGDUet8NRIJ9XRyIgcfH5oxYwaNGzfObF/Qf/TTTz+Rn58fXb16lezt7fV+f0REBLm5udHXX39Nubm5JJFIGryuvLycXnzxRXJycqKUlBSytrY2qL/37t2jfv36UV5eHjk4ONDmzZvppZdeavS+zemZZ54hKysrysrKErztqqoqWrFiBW3dupUSEhJo8uTJHPCYxeARnzkolUShoUSGftGIRGQ9diydvXGD5s+fT7t27SJPT0+aO3cu5eXlCdtXPbm5udHw4cNp586der/32rVr9M0339CJEyfo3XffbTT43L9/n0JDQ8nDw4N27dplUNCrrq6mjz76iIKCgsje3p4WL15M1dXVFB0dTZmZmXq3JzS1Wk1nz56lmTNnCt52dnY2BQYGUm5uLp0/f56mTJnCQY9ZFnPPtVosIzK3NFSks7i4GG+//TZcXV0RHByMlJQUs61NZWZmwtfXV++EzAsWLMDYsWPRtWvXRt97584d9OnTB9HR0QYlfK6oqMD69evh6emJ5557DseOHdOuaVVWVmLUqFEQiUR48cUXdcoUYyr79u2DRCIxOKl1QyoqKhAXFwcXFxfs2bOH1/KYxeLAZ04mKNJZXV2Nffv2YdiwYXBycsLcuXNNllGkMWq1Gt26dcPRo0d1fk95eTmcnZ3h7++Pzz77rMFrSktL0aNHD8TExOj9pX3v3j2sXLkSrq6uGDt2bJPVBNLS0tC2bVvY2dnh888/1+s+QhkyZAh69uwpWHuZmZnw8fHBhAkTUFJSIli7jP0ZceAzNxMW6SwqKsKiRYvg4uKCgQMH4uOPP9a7cKuhtm3bhjFjxqCmpgbHjx9v9Lr8/Hzcv38f27dvR1BQELp3797gKOfWrVvw8/PD4sWL9Qp6ZWVlWLp0KZycnPDKK6/ovOO0pqYGEyZMgEgkwrBhw+rVKjQ1qVSKv//970a38+uvv+LNN9+Em5sb9u/fL0DPGPvz48DXEpi4SGdVVRU+/fRTPP/883B2dkZMTAwuXrwo8EPUVVxcDKlUCgcHBxBRnUwqf9SlSxcQEVq1agU3NzccOHCg3jXXrl1Dx44d9Uo7dvPmTcybNw9yuRyvvfaawdUZvvvuOzg5OUEmkyE1NdWgNvT19ddfQyQSGT3Vmp6ejqeeegpRUVGNfv6MWSIOfC1JMxTpLCwsxMKFC+Hi4oJBgwZh165dgtdT27lzJ6ysrCCRSEBEEIlEjaYy6969e51E2z4+PnVSgRUVFcHLywtr1qzR6d7FxcV4/fXXIZfLMWfOHPz4449GP49KpcKrr74KkUiE/v37m+wg+8mTJ5GVlYVRo0ahc+fOBrdz7949TJ8+HR4eHmabqmWsJePAZ6Gqqqqwd+9ehISEQKFQYP78+cjPzxek7atXr6JDhw6wtrbWjuYaM2jQoHpVJjZv3gxAMw3q4eGBTTpM7/7nP/9BVFQUHB0d8fbbb6PUBBW9z549Czc3N7Rq1UqvahG6Gjt2LKysrEBE6NmzJ7755hu92/jiiy/g6emJv/71r/jll18E7yNjTwIOfAwFBQVYsGABlEolBg8ejD179hg9Crx79y769u0LsVgMW1vbRq8bPny4NuBJpVLs3r0bgCbptZub22MTVJ86dQrh4eFQKpX429/+plPVeGOoVCrMnTsXYrEYgYGB2oK3QnjnnXcgEom0o2R7e3udk37fuXMHU6ZMgZeXF7788kvB+sTYk4gDH9OqqqrCJ598gqFDh0KhUCA2NhaXL182uL3q6moMHjwYbdq0afSa/v37g4jg6uqqrZxw+vRp7Zb7xnz77bcYPnw42rVrh6SkJPz2228G99MQ+fn58PLygpWVlc7TsI+TmpqqHfG1adNG5wrnBw8ehLu7O954443H5ipljHHgY424fPky4uLioFAoMHToUKSmphq02UKtVmtGRSUlmnJMkyZp1i8nTQJWrcLt/HwsXbpUu9v0+++/h0KhwIEDB6BWq7F27VrtKE6tVuPIkSMIDg6Gt7c3tm3bJvj6pL6WLl0KiUSCLl26GL2eeO7cORARrK2tkZ2d/djrS0tLMXHiRHTs2BEZGRlG3ZsxS8KBjzXpwYMHSE1NxZAhQ6BUKhEXF1dnh+SePXuwYMGCxo8YZGdrqs1LpfVrED7csRoWBmRn49ixY1AoFDhy5AgAYNWqVSAiLF68GJ999hkCAwPh7++PXbt2taiiqFevXkWnTp0gkUi0xXgTExMxd+5cvdq5ceMGiKjRDSmvvfYaEhISoFarkZqaChcXF8yfP7/Zj1ow9mfHgY/p7NKlS4iNjYVCoUBISAhSU1O1m1ji4+Prv0GPM4q1NjaItbNDeno6ACAjIwMymUy73hUYGIiDBw8KmslEaAkJCbCysoKHhwdsbGwglUpx7ty5xt/wyCi48Nlnkezv3+Au3pMnT0Imk0EqlSIkJARdunRp8nwkY6xxHPiY3h48eIDdu3ejZ8+e2s0YUqkUu3bt+v0iA7LS1EqlwKZNKC4u1gY9IoKNjU3DgbUFunXrFqRSqbbvvXr1qj8abmIUXGNtXWcUDGg21Pj7+2vbVCgUzb6mydiThAMfM9hLL72kDXwPf1JSUozOQ/rWc89BLBbXOQvYp08fcz+uTjZu3AixWFznM1m1atXvFxiQqScpKanO5ywWi3U64sEYa1jjxc4Ye4ySkhLq0KEDOTs7k0KhoOrqamrVqhVRfDxRZaVhjVZWUnzbthSvUmn/Cn+iyll9+vSh2NhYunz5MhUWFlJ+fj4tWrSIXF1dKaq8nESxsUQVFY9vCNBcFxtLZVIp2dnZUefOncnHx4c6d+5MwcHBpn8Yxp5QXI+PCUuAWoMklRJdv07UwgrtGurMmTOUOHEifVhURFK1Wv8GWrcmysgg6t1b+M4xZoG4Hh8TVnKy8W2IRMK000IEBgZSip8ftTL0d8zKSs0omjEmCA58TFg5OcaN9og0X/S5ucL0pyUoLSVxWhqJDQ18ANEXXxCVlQnbL8YsFAc+Jqx794Rp5+5dYdppCXgUzFiLwoGPCcveXph25HJh2mkJeBTMWIvCgY8Jq1s3zeYUY8hkRAEBwvSnJeBRMGMtCgc+JqypU41vAxCmnZaCR8GMtSgc+JiwlEqi0FDNmpQhRCKikSOfmKMMRMSjYMZaGD7Hx4T3ww9EgwfrdlD7UU/imTU+28hYi8IjPia8oCCi1as1QUwfrVtr3vckBT0iHgUz1sLwiI+ZzubNRLGxmh2JTf0zE4k0U3mrVxNFRzdf/5oTj4IZazF4xMdMJzpa84UdFqaZqpPJ6r4uk2n+PixMc92TGvSIeBTMWAvCIz7WPMrKNAewc3M12/Llcs1mjalTLWsKj0fBjJkdBz7GmtupU5rcm198oQlwf6xkIZNpAuLIkUSLFvFIjzET4MDHmLnwKJgxs+DAxxhjzKLw5hbGGGMWhQMfY4wxi8KBjzHGmEXhwMcYY8yicOBjjDFmUTjwMcYYsygc+BhjjFkUDnyMMcYsCgc+xhhjFoUDH2OMMYvCgY8xxphF4cDHGGPMonDgY4wxZlE48DHGGLMoHPgYY4xZFA58jDHGLAoHPsYYYxaFAx9jjDGLwoGPMcaYReHAxxhjzKJw4GOMMWZR/gfWIZ3kLmIftwAAAABJRU5ErkJggg==\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": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'type': 'proposal',\n",
|
||
" 'conviction': 0,\n",
|
||
" 'status': 'candidate',\n",
|
||
" 'age': 0,\n",
|
||
" 'funds_requested': 2066.917035765987,\n",
|
||
" 'trigger': inf}"
|
||
]
|
||
},
|
||
"execution_count": 11,
|
||
"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": 12,
|
||
"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['initial_funds'], initial_values['supply'], sim_config[0]['M']['alpha'],sim_config[0]['M']) for r in funds_array])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0, 0.5, 'Amount of Honey requested(as a Fraction of Funds available)')"
|
||
]
|
||
},
|
||
"execution_count": 13,
|
||
"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['initial_funds'])\n",
|
||
"plt.title('Bar chart of Proposals Funds Requested')\n",
|
||
"plt.xlabel('Proposal identifier')\n",
|
||
"plt.ylabel('Amount of Honey requested(as a Fraction of Funds available)')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0, 0.5, 'Amount of Conviction')"
|
||
]
|
||
},
|
||
"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, 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": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0.5, 55.73999999999998, 'Participant_id')"
|
||
]
|
||
},
|
||
"execution_count": 15,
|
||
"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": 16,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from cadCAD.configuration import Experiment\n",
|
||
"\n",
|
||
"# Create configuration\n",
|
||
"exp = Experiment()\n",
|
||
"\n",
|
||
"exp.append_configs(\n",
|
||
" sim_configs=sim_config,\n",
|
||
" initial_state=state_variables,\n",
|
||
" seeds=1,\n",
|
||
" partial_state_update_blocks=partial_state_update_blocks\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"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: 2\n",
|
||
"Dimensions of the first simulation: (Timesteps, Params, Runs, Vars) = (100, 11, 1, 9)\n",
|
||
"Execution Method: local_simulations\n",
|
||
"SimIDs : [0, 1]\n",
|
||
"SubsetIDs: [0, 0]\n",
|
||
"Ns : [0, 0]\n",
|
||
"ExpIDs : [0, 0]\n",
|
||
"Total execution time: 181.16s\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>14020.01</td>\n",
|
||
" <td>22414.61</td>\n",
|
||
" <td>0.63</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>[0.0, 7.25348560292194, 4014.956894919269, 7.5...</td>\n",
|
||
" <td>[inf, inf, inf, 671285.2675602756, inf, 9130.8...</td>\n",
|
||
" <td>[0.0, 0.0, 0.0, 1.1188242278496905e-05, 0.0, 0...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.50</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.38</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>14020.01</td>\n",
|
||
" <td>22437.03</td>\n",
|
||
" <td>0.62</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>[0.0, 2352.438986571381, 7201.63029422018, 170...</td>\n",
|
||
" <td>[nan, inf, inf, 605419.6639977389, nan, nan, i...</td>\n",
|
||
" <td>[nan, 0.0, 0.0, 0.002823076165732284, nan, nan...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.44</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.37</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>14020.01</td>\n",
|
||
" <td>22459.46</td>\n",
|
||
" <td>0.62</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>[0.0, 4213.813952220331, 10473.030112089516, 2...</td>\n",
|
||
" <td>[nan, inf, inf, 549220.8701254777, nan, nan, i...</td>\n",
|
||
" <td>[nan, 0.0, 0.0, 0.005291355928120064, nan, nan...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.40</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.37</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>14020.01</td>\n",
|
||
" <td>22481.92</td>\n",
|
||
" <td>0.62</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, 1]</td>\n",
|
||
" <td>[0.0, 6968.879088760971, 12915.930301828008, 4...</td>\n",
|
||
" <td>[nan, inf, inf, 500866.9835697105, nan, nan, i...</td>\n",
|
||
" <td>[nan, 0.0, 0.0, 0.008005670775408685, nan, nan...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.33</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.37</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>14020.01</td>\n",
|
||
" <td>22504.41</td>\n",
|
||
" <td>0.62</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, 2]</td>\n",
|
||
" <td>[0.0, 10124.311057508521, 14854.861467350103, ...</td>\n",
|
||
" <td>[nan, inf, inf, 458947.639350347, nan, nan, in...</td>\n",
|
||
" <td>[nan, 0.0, 0.0, 0.010645541610004033, nan, nan...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.33</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.37</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 14020.01 22414.61 0.63 \n",
|
||
"12 14020.01 22437.03 0.62 \n",
|
||
"18 14020.01 22459.46 0.62 \n",
|
||
"24 14020.01 22481.92 0.62 \n",
|
||
"30 14020.01 22504.41 0.62 \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, 1] \n",
|
||
"30 [5, 5, 5, 5, 5, 5, 5, 5, 4, 3, 2, 2] \n",
|
||
"\n",
|
||
" conviction_all \\\n",
|
||
"6 [0.0, 7.25348560292194, 4014.956894919269, 7.5... \n",
|
||
"12 [0.0, 2352.438986571381, 7201.63029422018, 170... \n",
|
||
"18 [0.0, 4213.813952220331, 10473.030112089516, 2... \n",
|
||
"24 [0.0, 6968.879088760971, 12915.930301828008, 4... \n",
|
||
"30 [0.0, 10124.311057508521, 14854.861467350103, ... \n",
|
||
"\n",
|
||
" triggers_all \\\n",
|
||
"6 [inf, inf, inf, 671285.2675602756, inf, 9130.8... \n",
|
||
"12 [nan, inf, inf, 605419.6639977389, nan, nan, i... \n",
|
||
"18 [nan, inf, inf, 549220.8701254777, nan, nan, i... \n",
|
||
"24 [nan, inf, inf, 500866.9835697105, nan, nan, i... \n",
|
||
"30 [nan, inf, inf, 458947.639350347, nan, nan, in... \n",
|
||
"\n",
|
||
" conviction_share_of_trigger_all \\\n",
|
||
"6 [0.0, 0.0, 0.0, 1.1188242278496905e-05, 0.0, 0... \n",
|
||
"12 [nan, 0.0, 0.0, 0.002823076165732284, nan, nan... \n",
|
||
"18 [nan, 0.0, 0.0, 0.005291355928120064, nan, nan... \n",
|
||
"24 [nan, 0.0, 0.0, 0.008005670775408685, nan, nan... \n",
|
||
"30 [nan, 0.0, 0.0, 0.010645541610004033, nan, nan... \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 0.50 0.00 \n",
|
||
"12 0.44 0.00 \n",
|
||
"18 0.40 0.00 \n",
|
||
"24 0.33 0.00 \n",
|
||
"30 0.33 0.00 \n",
|
||
"\n",
|
||
" percentageOfCompletedFundsRequested percentageOfKilledFundsRequested \n",
|
||
"6 0.00 0.38 \n",
|
||
"12 0.00 0.37 \n",
|
||
"18 0.00 0.37 \n",
|
||
"24 0.00 0.37 \n",
|
||
"30 0.00 0.37 \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 0x7f52000e3ed0>"
|
||
]
|
||
},
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"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 0x7f51de60b810>"
|
||
]
|
||
},
|
||
"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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\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 0x7f51aed8d150>"
|
||
]
|
||
},
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot(x='timestep',y=['candidate_count','active_count','completed_count', 'killed_count', 'failed_count'],\n",
|
||
" kind='area')\n",
|
||
"plt.title('Proposal Status')\n",
|
||
"plt.ylabel('count of proposals')\n",
|
||
"plt.legend(ncol = 3,loc='upper center', bbox_to_anchor=(0.5, -0.15))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The above graph shows the number of various types of proposals at a range of timesteps. Ecosystems with more completed proposals will have higher overall agent sentiment than systems with more failed and killed proposals."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.legend.Legend at 0x7f51b045f8d0>"
|
||
]
|
||
},
|
||
"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",
|
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"/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",
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" plt.tight_layout()\n"
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]
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},
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{
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"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"K = 0\n",
|
||
"N = 1\n",
|
||
"\n",
|
||
"snap_plot(nets[K:N], size_scale = 1/300,savefigs=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"On the left side are participants, with the right side of the graph being the proposals. With this graph, we can see the links between the participants and the proposals that they support. The percentage on the right hand are the the amount of the required amount to pass that has been fulfilled.\n",
|
||
"\n",
|
||
"You can move the K and N to different points within the 100 timesteps, 0 indexed, to see how the model evolves overtime. \n",
|
||
"\n",
|
||
"As you can see with the plot above at the start of the simulation, no proposals have been formally supported yet. Below we can see a many interactions between agents and proposals."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 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": 35,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f516f721b50>"
|
||
]
|
||
},
|
||
"execution_count": 35,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep',['total_supply','funds'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f51a85dfb50>"
|
||
]
|
||
},
|
||
"execution_count": 28,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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wv5mVAuXADe5e0fh8I193Lf1r8AF4GFhoZlOAr4AfHPdViYhUkltYzKDeda61bnZqDQbuPqmK5LnV5H0JeKmabRnAkCrSC4ALaiuHiEh9lRwuZ+e+Q3oyqIHGJhKRuLdjTzGA2gxqoGAgInFvW1EoGPRSMKiWgoGIxL1tRQcB6NNJwaA6CgYiEve+fjJQm0F1FAxEJO5VvHB2QmsN1FwdBQMRiXvbivTCWW0UDEQk7m0rKlYVUS0UDEQk7m0rKqaPngxqpGAgInGt4oUzdSutmYKBiMS1HXuKcYc+qiaqkYKBiMS17Xv0wlldKBiISFzLLQy9cKbeRDVTMBCRuLY9eOGsdydVE9VEwUBE4tq2omLat9YLZ7VRMBCRuLat6CC9NSZRrRQMRCSubdcLZ3WiYCAicS23qJjeHfRkUBsFAxGJW0dmOFM1Ua1qDQZmNs/M8sxsbVjaNDPLMbPM4HNJkH6hma0wszXBz/PD9llqZuvD9ukRpLc2s+fNLMvMPjazlIa/TBFpjvL2hl44U7fS2tXlyWA+ML6K9JnunhZ8XgvSdgLfdfczgMnA05X2uSZsn7wgbQqw291PBmYCvz3mqxARqULFPAaa+7h2tQYDd38X2FWXg7n7SnfPDVbXAW3MrHUtu00AngqWXwQuMDOry/lERGrydTDQk0Ftjqfj7c1mdi2QAdzm7rsrbf8X4BN3PxSW9t9mVga8BDzo7g70BbYCuPthMysCuhJ6yjiKmU0FpgL079//OIouIvW1MGMr9//lU8rdo12UWh0uC5VRQ1HUrr7BYDbwAODBz/8Aflyx0cwGE6ruGRe2zzXunmNm7QkFgx8CC47lpO7+JPAkQHp6euz/JorEoRcyttKxTSKXnNEr2kWpkxO7tqN9UmK0ixHz6hUM3H1HxbKZzQGWhK0nAy8D17r7hrB9coKfe83sf4CRhIJBDtAPyDazlkBHoKA+5RKRyCo8UMKKr3Zz09iTuW3cqdEujjSgenUtNbPeYavfA9YG6Z2AV4E73f39sPwtzaxbsJwIXFqxD7CYUGMzwBXAW0H1kYjEmHe+yKfcYexpPaJdFGlgtT4ZmNmzwBigm5llA/cCY8wsjVA10Wbgp0H2m4GTgXvM7J4gbRywH3g9CAQJwD+AOcH2ucDTZpZFqKF64vFflohEwtL1+XRp14phyZ2iXRRpYLUGA3efVEXy3GryPgg8WM2hRlSzTzFwZW3lEJHoKit3lq7PY8ypPUhooQ5/8UZvIItInWRuLWT3gVJVEcUpBQMRqZOl6/NIaGGcN7B7tIsiEaBgICJ18tbneYzo35mObdVNMx4pGIhIrXbsKWZd7h7GnKangnilqX9E5IjPt+9h+aZvjj6zLncPAOervSBuKRiIyBG/emE1a3KKqtw2oHs7Tu3ZvpFLJI1FwUBEADhYUsan2/Yw5exUfjZmwDe2t09qicaQjF8KBiICwNrcIsrKnbNO6kq3E2obbFjijRqQRQSAlVtCAw+n9dfbxc2RgoGIAKGXyvp1aaOngmZKwUBEAMjcUkhav87RLoZEiYKBiLBjTzG5RcWk9VMVUXOlYCAirNxSCMBwtRc0WwoGIsLKrbtJTDAG9e4Q7aJIlCgYiAiZWwoZ1KcjSYkJ0S6KRImCgUgzd7isnDU5RQxXe0GzpmAg0sx9sWMfB0rK1F7QzCkYiDRzmVtDjcfqSdS81SkYmNk8M8szs7VhadPMLMfMMoPPJWHbfm1mWWa23swuCksfH6RlmdmdYempZvZxkP68mbVqqAsUkW/avb+EVVsLWbW1kHe+yKNLu1b079I22sWSKKrr2ETzgd8DCyqlz3T3GeEJZjaI0KT2g4E+wD/M7JRg82PAhUA2sNzMFrv7p8Bvg2M9Z2ZPAFOA2fW4HhGpRfbuA1w66z0KD5QeSbtwUE8NQtfM1SkYuPu7ZpZSx2NOAJ5z90PAJjPLAkYG27LcfSOAmT0HTDCzz4DzgauDPE8B01AwEGlwh8vKufW5TA6XOY9dfSZtWoUqB4Ymq4qouTveUUtvNrNrgQzgNnffDfQFPgrLkx2kAWytlD4K6AoUuvvhKvKLSAP6r398yYqvdvPopOH889De0S6OxJDjaUCeDQwA0oBtwH80SIlqYGZTzSzDzDLy8/MjfTqRuPJ+1k4eW5rFVen9uGxYn2gXR2JMvYOBu+9w9zJ3Lwfm8HVVUA7QLyxrcpBWXXoB0MnMWlZKr+qcT7p7urund++uuVhF6uqzbXu49bmVDOh+AvdeNijaxZEYVO9gYGbhz5jfAyp6Gi0GJppZazNLBQYCy4DlwMCg51ArQo3Mi93dgbeBK4L9JwOL6lsuETna8s27+MEfPqRlixb84YcjaNtKc1rJN9Xpt8LMngXGAN3MLBu4FxhjZmmAA5uBnwK4+zozWwh8ChwGbnL3suA4NwOvAwnAPHdfF5ziDuA5M3sQWAnMbZCrE4lT7s7mggMcLCmrMd+XeXu546XV9OnYhgVTRpLcWd1HpWoW+sO86UlPT/eMjIxoF0MkKpZv3sWVT3xYp7xD+nZg/nUjNWmNAGBmK9w9vXK6nhdFmqCMzaEpKh+dNJxWCdXX9rZsYfzTyV1VNSS10m+ISBO0NreI5M5t1CtIGozGJhJpgtblFDGkT8doF0PiiIKBSBOzp7iUzQUHGNJXE9FIw1EwEGliPsvdA8DgvnoykIajYCDSxKwNgoGqiaQhKRiINDHrcoro2aE13durq6g0HAUDkSZmbW4Rg/VUIA1MwUCkCTlYUkZW3j6G9FHjsTQsBQORJuTz7XsodzUeS8NTMBBpQo40HisYSANTMBBpQtblFNG5bSJ9OiZFuygSZxQMRJqQtblFDOnbUfMVS4NTMBBpIkoOl7N++171JJKIUDAQaSK+2LGX0jJnsHoSSQQoGIg0EauyCwE4Q43HEgEKBiJNxLJNu+jevjUndtVsZdLwFAxEmgB35+ONuxiV2kWNxxIRCgYiTcCWXQfYvqeYUSd1jXZRJE7VGgzMbJ6Z5ZnZ2iq23WZmbmbdgvVfmVlm8FlrZmVm1iXYttnM1gTbMsKO0cXM3jCzL4OfnRvyAkXiwccbdwEwOrVLlEsi8aouTwbzgfGVE82sHzAO2FKR5u7T3T3N3dOAXwPvuPuusN3GBtvDJ2O+E3jT3QcCbwbrIhLmo00FdG3XipN7nBDtokicqjUYuPu7wK4qNs0Ebge8ml0nAc/WoQwTgKeC5aeAy+uwj0iz8vHGXYxUe4FEUL3aDMxsApDj7quq2d6W0NPES2HJDvzdzFaY2dSw9J7uvi1Y3g70rOG8U80sw8wy8vPz61N0kSYne/cBcgoPMkpVRBJBLY91h+CL/i5CVUTV+S7wfqUqorPdPcfMegBvmNnnwVPHEe7uZlbdkwbu/iTwJEB6enq1+UTiSUV7wchUNR5L5NTnyWAAkAqsMrPNQDLwiZn1CsszkUpVRO6eE/zMA14GRgabdphZb4DgZ149yiQSt5Zt2kXHNomc1qt9tIsiceyYg4G7r3H3Hu6e4u4pQDZwprtvBzCzjsB5wKKKfcysnZm1r1gm9FRR0TtpMTA5WJ4cvp+IwMebCvhWShdatFB7gUROXbqWPgt8CJxqZtlmNqWWXb4H/N3d94el9QTeM7NVwDLgVXf/W7DtYeBCM/sS+E6wLiLAjj3FbC44wOiT1F4gkVVrm4G7T6ple0ql9fmEuqOGp20EhlWzfwFwQW3lEIk3j775JS+s2FpjnuLScgBGqb1AIuyYG5BF5PjNf38T//nGF5x1Uld61zJRTY8OSRqpVCJOwUCkkf193XbuW/Ip4wb1ZPb/GUGC2gIkBigYiByHZZt2sX1PcZ3z7ys+zP1L1jEsuROPTByuQCAxQ8FApB6KS8u47y+f8uyyLbVnruTErm354+R02rRKiEDJROpHwUDimnvDv5u4ZdcBbnzmE9bl7uGG8wZwxYjkY9o/uXMbkhIVCCS2KBhI3HpgyafMfW9TRI7dsU0icyenc8Hp1Y6eItKkKBhIXPrLqlzmvreJS87oxSk9G/bN3ZYtjMuH9yW5s2Yck/ihYCBxZ+uuA9z15zWc2T/USJuYoDmcRGqj/yUSV0rLyvn5syvBUCAQOQZ6MpCIWpdbxH1/+ZSDJWWNcr79hw6zced+Hr/mTPp1UTWOSF0pGEjElJaVc9vCVeTtPURav06Ncs7u7Vtz9aj+XHJG70Y5n0i8UDCQiJnzvxv5fPte5lybzoWD1OtGJJapQlUiYvPO/Tzyjy+5eEgvBQKRJkDBQBqcu/N/X1lDq4QWTLtscLSLIyJ1oGoiqbenP/qK3/3t89Ds1mHK3dlfUsaDlw+hZ4eaR+QUkdigYCD19srKHDokJXLR4F7f2JbcuQ1Xj+wfhVKJSH0oGEi9HCwpY3V2IT8+O5VfX3x6tIsjIsdJbQZSL59s2U1pmTP6JM3AJRIP6hQMzGyemeWZ2doqtt1mZm5m3YL1MWZWZGaZweeesLzjzWy9mWWZ2Z1h6alm9nGQ/ryZtWqIi5PI+XhjAS0M0k/sHO2iiEgDqOuTwXxgfOVEM+sHjAMqD+r+v+6eFnzuD/ImAI8BFwODgElmNijI/1tgprufDOwGphzrhUjj+mjTLob07Uj7pMRoF0VEGkCdgoG7vwvsqmLTTOB2vtGfpEojgSx33+juJcBzwAQzM+B84MUg31PA5XUpl0RHcWkZmVsKGZXaJdpFEZEGUu82AzObAOS4+6oqNp9lZqvM7K9mVtHRvC+wNSxPdpDWFSh098OV0qs651QzyzCzjPz8/PoWXY7Tyi2FlJSVMypV7QUi8aJewcDM2gJ3AfdUsfkT4ER3HwbMAl6pf/GO5u5Punu6u6d37969oQ4rx+jjTQWYwbf0ZCASN+r7ZDAASAVWmdlmIBn4xMx6ufsed98H4O6vAYlB43IO0C/sGMlBWgHQycxaVkqXGPXxxl2c3qsDHduovUAkXtQrGLj7Gnfv4e4p7p5CqGrnTHffbma9gnYAzGxkcI4CYDkwMOg51AqYCCz20CS1bwNXBIefDCw6rquSiDl0uIxPtuxm1El6KhCJJ3XtWvos8CFwqpllm1lNvX2uANaa2SrgUWCihxwGbgZeBz4DFrr7umCfO4B/NbMsQm0Ic+t3ORJpq7OLOHS4XO8XiMSZOr2B7O6TatmeErb8e+D31eR7DXitivSNhHobSZicwoO8ujqX8rr01Qq4g+P4MexzLFZu2Q3AyBQ9GYjEEw1HEcOeWLqBpz/6KtrF+IazTupK53Z6L1AknigYxLCsvH0M69eJ564ffUz7hVpsvv7Z0FppXmGRuKNgEMM25O/j3FO606ZVQrSLIiJxTn/ixag9xaXk7T3EgO4nRLsoItIMKBjEqA15+wA4uYeCgYhEnoJBjNqQvx+AAd3bRbkkItIcKBjEqA35+0hMMPp1aRvtoohIM6BgEKM25O3jxK7tSFTPHRFpBPqmiVEb8vepikhEGo2CQQwqLSvnq4IDajwWkUajYBCDvio4wOFyV7dSEWk0CgYxaEN+qFupgoGINBYFgxhUEQxOUpuBiDQSBYMYtCFvPz07tNZk8yLSaBQMYlBW/j41HotIo1IwiDHuzsa8fWovEJFGpWAQY/L3HmLvocMKBiLSqBQMYkyWehKJSBTUGgzMbJ6Z5ZnZ2iq23WZmbmbdgvVrzGy1ma0xsw/MbFhY3s1BeqaZZYSldzGzN8zsy+Bn54a6uKboyAB1PdSTSEQaT10mt5lPaE7jBeGJZtYPGAdsCUveBJzn7rvN7GLgSWBU2Pax7r6z0vHvBN5094fN7M5g/Y5juoom4u5X1vLW53k15tlTXEq7Vgn06pDUSKUSEalDMHD3d80spYpNM4HbgUVheT8I2/4RkFyHMkwAxgTLTwFLidNg8OqabXRp14phyZ1qzHfmiZ2wSM1ZKSJShXpNe2lmE4Acd19Vw5fWFOCvYesO/N3MHPiDuz8ZpPd0923B8nagZw3nnQpMBejfv399ih41B0vK2LW/hClnp3LT2JOjXRwRkaMcczAws7bAXYSqiKrLM5ZQMDg7LPlsd88xsx7AG2b2ubu/G76fu3sQLKoUBJAnAdLT06vNF4tyCg8C0LdTmyiXRETkm7OhT2EAAAnWSURBVOrTm2gAkAqsMrPNhKqCPjGzXgBmNhT4IzDB3QsqdnL3nOBnHvAyMDLYtMPMegf79gZqrlRvonKDYNBHwUBEYtAxBwN3X+PuPdw9xd1TgGzgTHffbmb9gT8DP3T3Lyr2MbN2Zta+YpnQU0VF76TFwORgeTJhbRDx5OtgoIZhEYk9dela+izwIXCqmWWb2ZQast8DdAUer9SFtCfwnpmtApYBr7r734JtDwMXmtmXwHeC9biTW3iQFoZ6CYlITKpLb6JJtWxPCVv+CfCTKvJsBIZVTg+2FQAX1FaOpi678CC9OiTRUtNYikgM0jdTI8ktPKj2AhGJWQoGjSS3sFjBQERiloJBIygvd7YVHaRvZwUDEYlNCgaNYOe+Q5SWuZ4MRCRmKRg0guwjL5ypJ5GIxCYFg0agF85EJNYpGDQCBQMRiXUKBo0gt7CY9kkt6aAJ7kUkRikYNIKcwoMaoE5EYpqCQSPI2a0XzkQktikYNILcooMaoE5EYpqCQYTtP3SYwgOl9O3UNtpFERGploJBhG0r0tDVIhL7FAwiLHu3ZjgTkdinYBBhuYXFgN4xEJHYpmAQYbmFB0loYfRo3zraRRERqZaCQYTlalIbEWkC9A0VYXrhTESaglqnvQQws3nApUCeuw+ptO02YAbQ3d13mpkBjwCXAAeAH7n7J0HeycD/C3Z90N2fCtJHAPOBNsBrwK3u7sd5bVWa9eaXLF6VG4lDV+mrggNcckavRjufiEh91CkYEPqi/j2wIDzRzPoB44AtYckXAwODzyhgNjDKzLoA9wLpgAMrzGyxu+8O8lwPfEwoGIwH/lq/S6pZ9/atGdjzhEgcukqn9GzPpJH9G+18IiL1Uadg4O7vmllKFZtmArcDi8LSJgALgr/sPzKzTmbWGxgDvOHuuwDM7A1gvJktBTq4+0dB+gLgciIUDCaO7M9EfTmLiByl3m0GZjYByHH3VZU29QW2hq1nB2k1pWdXkV7VOaeaWYaZZeTn59e36CIiUkm9goGZtQXuAu5p2OLUzN2fdPd0d0/v3r17Y55aRCSu1ffJYACQCqwys81AMvCJmfUCcoB+YXmTg7Sa0pOrSBcRkUZSr2Dg7mvcvYe7p7h7CqGqnTPdfTuwGLjWQkYDRe6+DXgdGGdmnc2sM6GG59eDbXvMbHTQE+lajm6DEBGRCKtTMDCzZ4EPgVPNLNvMptSQ/TVgI5AFzAFuBAgajh8Algef+ysak4M8fwz22UCEGo9FRKRqFqHu/BGXnp7uGRkZ0S6GiEiTYmYr3D29crreQBYREQUDERFpwtVEZpYPfHUMu3QDdkaoOLGsOV53c7xmaJ7X3RyvGY7vuk9092/0zW+yweBYmVlGVfVk8a45XndzvGZontfdHK8ZInPdqiYSEREFAxERaV7B4MloFyBKmuN1N8drhuZ53c3xmiEC191s2gxERKR6zenJQEREqqFgICIizSMYmNl4M1tvZllmdme0yxMJZtbPzN42s0/NbJ2Z3RqkdzGzN8zsy+Bn52iXtaGZWYKZrTSzJcF6qpl9HNzv582sVbTL2NCCSaNeNLPPzewzMzsr3u+1mf0y+N1ea2bPmllSPN5rM5tnZnlmtjYsrcp7GwwI+mhw/avN7Mz6njfug4GZJQCPEZqOcxAwycwGRbdUEXEYuM3dBwGjgZuC67wTeNPdBwJvBuvx5lbgs7D13wIz3f1kYDdQ08CKTdUjwN/c/TRgGKHrj9t7bWZ9gVuA9GAe9gRgIvF5r+cTmvo3XHX3Nnya4amEphCul7gPBsBIIMvdN7p7CfAcoak544q7b3P3T4LlvYS+HPoSutangmxPEZpSNG6YWTLwz4RGvSUYBv184MUgSzxec0fgXGAugLuXuHshcX6vCU3T28bMWgJtgW3E4b1293eBXZWSq7u3R6YZDqYOrphm+Jg1h2BQ3XSbcSuYr3o48DHQM5gzAmA70DNKxYqU/yI0D3d5sN4VKHT3w8F6PN7vVCAf+O+geuyPZtaOOL7X7p4DzAC2EAoCRcAK4v9eV6ju3jbY91tzCAbNipmdALwE/MLd94Rv81A/4rjpS2xmlwJ57r4i2mVpZC2BM4HZ7j4c2E+lKqE4vNedCf0VnAr0AdrxzaqUZiFS97Y5BIPqptuMO2aWSCgQPOPufw6Sd1Q8NgY/86JVvgj4NnBZMPXqc4SqDB4h9KjcMsgTj/c7G8h294+D9RcJBYd4vtffATa5e767lwJ/JnT/4/1eV6ju3jbY91tzCAbLgYFBr4NWhBqdFke5TA0uqCufC3zm7v8ZtmkxMDlYnkwcTSnq7r929+Rg6tWJwFvufg3wNnBFkC2urhkgmF52q5mdGiRdAHxKHN9rQtVDo82sbfC7XnHNcX2vw1R3b6ubZvjYuXvcf4BLgC8ITan5f6Ndnghd49mEHh1XA5nB5xJCdehvAl8C/wC6RLusEbr+McCSYPkkYBmhaVRfAFpHu3wRuN40ICO4368AneP9XgP3AZ8Da4GngdbxeK+BZwm1i5QSegqcUt29BYxQb8kNwBpCva3qdV4NRyEiIs2imkhERGqhYCAiIgoGIiKiYCAiIigYiIgICgbSzAWjf94YLPcxsxdr2+c4zpVmZpdE6vgix0PBQJq7TsCNAO6e6+5X1JL/eKQRevdDJOboPQNp1sysYhTb9YRe6Dnd3YeY2Y8IjQzZjtDwwDOAVsAPgUPAJe6+y8wGEHrppztwALje3T83syuBe4EyQoOqfYfQi1FtCA0X8BtgCTALGAIkAtPcfVFw7u8BHQkNOvYnd78vwv8U0sy1rD2LSFy7Exji7mnBaK9LwrYNITT6axKhL/I73H24mc0EriU0YuqTwA3u/qWZjQIeJzRG0j3ARe6eY2ad3L3EzO4h9IbozQBm9u+EhtD4sZl1ApaZ2T+Cc48Mzn8AWG5mr7p7RiT/IaR5UzAQqd7bHpobYq+ZFQF/CdLXAEODEWL/CXghNFwOEBoiAeB9YL6ZLSQ0qFpVxhEaaO/fgvUkoH+w/Ia7FwCY2Z8JDTeiYCARo2AgUr1DYcvlYevlhP7vtCA0nn5a5R3d/YbgSeGfgRVmNqKK4xvwL+6+/qjE0H6V629VnysRpQZkae72Au3rs6OH5ovYFLQPVMxHOyxYHuDuH7v7PYQmoulXxbleB34ejMKJmQ0P23ZhMO9tG0JtF+/Xp4widaVgIM1aUBXzfjD5+PR6HOIaYIqZrQLW8fWUqtPNbE1w3A+AVYSGWx5kZplmdhXwAKGG49Vmti5Yr7CM0NwUq4GX1F4gkabeRCIxJuhNdKShWaQx6MlARET0ZCAiInoyEBERFAxERAQFAxERQcFARERQMBAREeD/A4NASu3eN+c7AAAAAElFTkSuQmCC\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": 29,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f51b2972a50>"
|
||
]
|
||
},
|
||
"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',['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": 30,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f51b7459a90>"
|
||
]
|
||
},
|
||
"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',['fractionOfSupplyForVoting'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f51b2815650>"
|
||
]
|
||
},
|
||
"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',['fractionOfSupplyInPool'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f51aa5e0310>"
|
||
]
|
||
},
|
||
"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',['percentageOfActiveProposals','percentageOfCompletedProposals','percentageOfKilledProposals'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f5172ed9350>"
|
||
]
|
||
},
|
||
"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',['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
|
||
}
|