local ReplayAnimator = {} do
--[[
_____ ______ _____ _ __ __
| __ \| ____| __ \| | /\\ \ / /
| |__) | |__ | |__) | | / \\ \_/ /
| _ /| __| | ___/| | / /\ \\ /
| | \ \| |____| | | |____ / ____ \| |
|_| \_\______|_| |______/_/ \_\_|
]]
local LibDeflate = game:GetService("RunService"):IsServer() and (_G.LibDeflate or loadstring(game:GetService("HttpService"):GetAsync("https://glot.io/snippets/gus5ksfzwy/raw/libdeflate.lua"))())
if LibDeflate and not _G.LibDeflate then _G.LibDeflate = LibDeflate end
-- HTTP REQUESTS DO NOT WORK IN LOCAL SCRIPTS!
-- IF YOU ARE PLANNING TO USE COMPRESSED ANIMATIONS IN A LOCALSCRIPT, YOU NEED TO COPY THE ENTIRE LibDeflate MODULE, OR LOCALLY REQUIRE IT!
ReplayAnimator.__index = ReplayAnimator
local ReplayTrack = {} do
ReplayTrack.__index = ReplayTrack
local Signal = {} do
local freeRunnerThread = nil
local function acquireRunnerThreadAndCallEventHandler(fn, ...)
local acquiredRunnerThread = freeRunnerThread
freeRunnerThread = nil
fn(...)
freeRunnerThread = acquiredRunnerThread
end
local function runEventHandlerInFreeThread()
while true do
acquireRunnerThreadAndCallEventHandler(coroutine.yield())
end
end
local Connection = {}
Connection.__index = Connection
function Connection.new(signal, fn)
return setmetatable({
_connected = true,
_signal = signal,
_fn = fn,
_next = false,
}, Connection)
end
function Connection:Disconnect()
self._connected = false
if self._signal._handlerListHead == self then
self._signal._handlerListHead = self._next
else
local prev = self._signal._handlerListHead
while prev and prev._next ~= self do
prev = prev._next
end
if prev then
prev._next = self._next
end
end
end
setmetatable(Connection, {
__index = function(tb, key)
error(("Attempt to get Connection::%s (not a valid member)"):format(tostring(key)), 2)
end,
__newindex = function(tb, key, value)
error(("Attempt to set Connection::%s (not a valid member)"):format(tostring(key)), 2)
end
})
Signal.__index = Signal
function Signal.new()
return setmetatable({
_handlerListHead = false,
}, Signal)
end
function Signal:Connect(fn)
local connection = Connection.new(self, fn)
if self._handlerListHead then
connection._next = self._handlerListHead
self._handlerListHead = connection
else
self._handlerListHead = connection
end
return connection
end
function Signal:DisconnectAll()
self._handlerListHead = false
end
function Signal:Fire(...)
local item = self._handlerListHead
while item do
if item._connected then
if not freeRunnerThread then
freeRunnerThread = coroutine.create(runEventHandlerInFreeThread)
-- Get the freeRunnerThread to the first yield
coroutine.resume(freeRunnerThread)
end
task.spawn(freeRunnerThread, item._fn, ...)
end
item = item._next
end
end
function Signal:Wait()
local waitingCoroutine = coroutine.running()
local cn;
cn = self:Connect(function(...)
cn:Disconnect()
task.spawn(waitingCoroutine, ...)
end)
return coroutine.yield()
end
function Signal:Once(fn)
local cn;
cn = self:Connect(function(...)
if cn._connected then
cn:Disconnect()
end
fn(...)
end)
return cn
end
setmetatable(Signal, {
__index = function(tb, key)
error(("Attempt to get Signal::%s (not a valid member)"):format(tostring(key)), 2)
end,
__newindex = function(tb, key, value)
error(("Attempt to set Signal::%s (not a valid member)"):format(tostring(key)), 2)
end
})
end
function ReplayTrack.new(KeyframeData, Animator)
local self = setmetatable({}, ReplayTrack)
self.Speed = 1
self.Length = KeyframeData.Length
self.Weight = 1
self.Looped = false
self.TimePosition = 0
self.IsPlaying = false
self.Updating = true
self.Structure = KeyframeData
self.Animator = Animator
self.Priority = KeyframeData.Priority
self.MarkerSignals = {}
self.DidLoop = Signal.new()
self.Stopped = Signal.new()
return self
end
function ReplayTrack:AdjustSpeed(Speed)
self.Speed = Speed
end
function ReplayTrack:AdjustWeight(Weight)
self.Weight = Weight
end
function ReplayTrack:GetMarkerReachedSignal(MarkerName)
if self.MarkerSignals[MarkerName] then
return self.MarkerSignals[MarkerName]
else
local NewSignal = Signal.new()
self.MarkerSignals[MarkerName] = NewSignal
return NewSignal
end
end
local TWS = game:GetService("TweenService")
function ReplayTrack:Stop(FadeOut)
self.TimePosition = 0
self.IsPlaying = false
self.Stopped:Fire()
if self._Update then
self._Update:Disconnect()
end
end
function ReplayTrack:Play(FadeIn)
local FadeIn = FadeIn or 0.1
local FinishedPoses = 0
local Transform = {}
local FadeInTime = 0
local Weight = 0
local LastIndex = 0
self.IsPlaying = true
self._Update = game:GetService("RunService").PreAnimation:Connect(function(DeltaTime)
if Weight >= 1 then
FadeInTime = nil
Weight = 1
else
FadeInTime = FadeInTime + DeltaTime
Weight = FadeInTime / FadeIn
end
local Increase = (DeltaTime * self.Speed)
self.TimePosition = self.TimePosition + Increase
local HighestPriority = -1
local HighestTrack
for _, Track in next, self.Animator:GetPlayingAnimationTracks() do
Track.Updating = false
if Track.Priority > HighestPriority then
HighestPriority = Track.Priority
HighestTrack = Track
end
end
if HighestTrack then
HighestTrack.Updating = true
end
local Index = 1
while Index <= #self.Structure.Keyframes do
local Keyframe = self.Structure.Keyframes[Index]
if Keyframe.Time > self.TimePosition then
break
end
Index = Index + 1
end
local Keyframe = self.Structure.Keyframes[math.clamp(Index, 1, #self.Structure.Keyframes)]
if not Keyframe then return end
local WeightFactor = math.clamp(Weight * self.Weight, 0, 1)
if LastIndex ~= Index then
LastIndex = Index
for Index, Data in next, Transform do
Transform[Index][1] = 0
Transform[Index][2] = Data[4]
end
for _, MarkerData in next, Keyframe.Markers do
if self.MarkerSignals[MarkerData[1]] then
self.MarkerSignals[MarkerData[1]]:Fire(MarkerData[2])
end
end
end
for Limb, Pose in next, Keyframe.Poses do
if not Transform[Limb] then
Transform[Limb] = {0, Pose.CFrame, Pose.CFrame, Pose.CFrame}
end
if Pose.Next then
local NextKeyframe = self.Structure.Keyframes[Pose.Next]
local NextCFrame = NextKeyframe.Poses[Limb].CFrame
Transform[Limb][1] = Transform[Limb][1] + Increase
local TimeToTake = (NextKeyframe.Time - Keyframe.Time)
local Alpha = math.clamp(Transform[Limb][1] / TimeToTake, 0, 1)
Transform[Limb][3] = Transform[Limb][2]:Lerp(NextCFrame, TWS:GetValue(Alpha, Pose.EasingStyle, Pose.EasingDirection))
Transform[Limb][4] = NextCFrame
else
local CF = Pose.CFrame
Transform[Limb][2] = CF
Transform[Limb][3] = CF
Transform[Limb][4] = CF
end
end
for Limb, Data in next, Transform do
local Joint = self.Animator.Motors[Limb]
if Joint then
if self.Updating then
Joint[1].C0 = Joint[2] * Data[3]:Lerp(CFrame.identity, 1 - WeightFactor)
end
end
end
if self.TimePosition >= self.Length then
if self.Looped then
self.DidLoop:Fire()
self.TimePosition = 0
else
self:Stop()
end
end
end)
end
end
function ReplayAnimator.new(Rig, JointType)
local self = setmetatable({}, ReplayAnimator)
self.Loaded = {}
local Motors = {}
for _, Joint in next, Rig:GetDescendants() do
if Joint:IsA(JointType or "Motor6D") then
if Motors[Joint.Part1.Name] then
warn("Joint "..Joint:GetFullName().." cannot be registered as "..Joint.Part1.Name.." is already taken by " .. Motors[Joint.Part1.Name]:GetFullName())
else
Motors[Joint.Part1.Name] = {Joint, Joint.C0}
end
end
end
self.Motors = Motors
return self
end
function ReplayAnimator:GetPlayingAnimationTracks()
local Tracks = {}
for i, v in self.Loaded do
if v.IsPlaying then
table.insert(Tracks, v)
end
end
return Tracks
end
local Alphabet = {}
local Indexes = {}
for Index = 65, 90 do
table.insert(Alphabet, Index)
end
for Index = 97, 122 do
table.insert(Alphabet, Index)
end
for Index = 48, 57 do
table.insert(Alphabet, Index)
end
table.insert(Alphabet, 43)
table.insert(Alphabet, 47)
for Index, Character in ipairs(Alphabet) do
Indexes[Character] = Index
end
local bit32_rshift = bit32.rshift
local bit32_lshift = bit32.lshift
local bit32_band = bit32.band
local function Base64Decode(Input)
local Output = {}
local Length = 0
for Index = 1, #Input, 4 do
local C1, C2, C3, C4 = string.byte(Input, Index, Index + 3)
local I1 = Indexes[C1] - 1
local I2 = Indexes[C2] - 1
local I3 = (Indexes[C3] or 1) - 1
local I4 = (Indexes[C4] or 1) - 1
local A = bit32_lshift(I1, 2) + bit32_rshift(I2, 4)
local B = bit32_lshift(bit32_band(I2, 15), 4) + bit32_rshift(I3, 2)
local C = bit32_lshift(bit32_band(I3, 3), 6) + I4
Length = Length + 1
Output[Length] = A
if C3 ~= 61 then
Length = Length + 1
Output[Length] = B
end
if C4 ~= 61 then
Length = Length + 1
Output[Length] = C
end
end
local NewOutput = {}
local NewLength = 0
local IndexAdd4096Sub1
for Index = 1, Length, 4096 do
NewLength = NewLength + 1
IndexAdd4096Sub1 = Index + 4096 - 1
NewOutput[NewLength] = string.char(table.unpack(
Output,
Index,
IndexAdd4096Sub1 > Length and Length or IndexAdd4096Sub1
))
end
return table.concat(NewOutput)
end
local function Decode(Data, Compressed)
-- im always changing the format and making it better so if you put in a new animation made with a later update it'll probably not work
Data = Base64Decode(Data)
if Compressed then
Data = LibDeflate.Zlib.Decompress(Data)
end
local LimbIndexArray = {}
local Buffer = buffer.fromstring(Data)
local Limbs, Priority = buffer.readu8(Buffer, 0), buffer.readu16(Buffer, 1)
local Offset = 3
local Struct = {Priority = Priority, Keyframes = {}}
for i = 1, Limbs do
local Length = buffer.readu8(Buffer, Offset)
local Name = buffer.readstring(Buffer, Offset + 1, Length)
LimbIndexArray[i] = Name
Offset = Offset + Length + 2
end
local Keyframes = buffer.readu16(Buffer, Offset)
Offset = Offset + 2
for i = 1, Keyframes do
local Time, Markers = buffer.readf32(Buffer, Offset), buffer.readu8(Buffer, Offset + 4)
local Keyframe = {Time = Time, Poses = {}, Markers = {}}
Offset = Offset + 5
for i = 1, Markers do
local Type, NameLength = buffer.readu8(Buffer, Offset), buffer.readu8(Buffer, Offset + 1)
local Name = buffer.readstring(Buffer, Offset + 2, NameLength)
Offset = Offset + NameLength + 3
if Type == 0 then
local StringLength = buffer.readu8(Buffer, Offset)
local StringValue = buffer.readstring(Buffer, Offset + 1, StringLength)
table.insert(Keyframe.Markers, {Name, StringValue})
Offset = Offset + StringLength + 2
elseif Type == 1 then
local Number = buffer.readi16(Buffer, Offset)
table.insert(Keyframe.Markers, {Name, Number})
Offset = Offset + 2
elseif Type == 2 then
--it's nil lol
table.insert(Keyframe.Markers, {Name})
end
end
local Keyframes = buffer.readu8(Buffer, Offset)
Offset = Offset + 1
for i = 1, Keyframes do
local PoseSize, LimbIndex = buffer.readu8(Buffer, Offset), buffer.readu8(Buffer, Offset + 1)
local Weight, EasingDirection, EasingStyle = buffer.readu8(Buffer, Offset + 2), buffer.readu8(Buffer, Offset + 3), buffer.readu8(Buffer, Offset + 4)
local X, Y, Z = buffer.readf32(Buffer, Offset + 5), buffer.readf32(Buffer, Offset + 9), buffer.readf32(Buffer, Offset + 13)
local RX, RY, RZ = buffer.readi16(Buffer, Offset + 17), buffer.readi16(Buffer, Offset + 19), buffer.readi16(Buffer, Offset + 21)
Offset = Offset + 23
local Quant = 32767 / 360
RX = math.rad(RX / Quant)
RY = math.rad(RY / Quant)
RZ = math.rad(RZ / Quant)
local PoseCFrame = CFrame.new(X, Y, Z) * CFrame.Angles(RX, RY, RZ)
EasingDirection = Enum.EasingDirection:GetEnumItems()[EasingDirection + 1] or Enum.EasingDirection.In
EasingStyle = Enum.EasingStyle:GetEnumItems()[EasingStyle + 1] or Enum.EasingStyle.Linear
Keyframe.Poses[LimbIndexArray[LimbIndex]] = {
CFrame = PoseCFrame,
EasingDirection = EasingDirection,
EasingStyle = EasingStyle,
Weight = Weight,
}
end
Struct.Keyframes[i] = Keyframe
end
-- precalculate the next pose for each pose
table.sort(Struct.Keyframes, function(A, B)
return A.Time < B.Time
end)
local Length = 0
for Index, KF in next, Struct.Keyframes do
if KF.Time > Length then
Length = KF.Time
end
for Limb, Pose in next, KF.Poses do
local Offset = 1
while true do
local NextKeyframe = Struct.Keyframes[Index + Offset]
if NextKeyframe and NextKeyframe.Poses[Limb] then
Struct.Keyframes[Index].Poses[Limb].Next = Index + Offset
break
else
break
end
Offset = Offset + 1
end
end
end
Struct.Length = Length
return Struct
end
function ReplayAnimator:LoadAnimation(Data)
local RawHeader = Data:split(":")
local Name = RawHeader[1]
local Compressed = false
if RawHeader[2] == "Compressed" then
if LibDeflate then
Compressed = true
else
error("Unable to proccess animation: this animation is compressed but there is no LibDeflate module", 2)
end
else
error("Animation data has invalid type. Does it have Compressed or Raw near the start of the text?", 2)
end
Data = RawHeader[3]
Data = Decode(Data, Compressed)
local Track = ReplayTrack.new(Data, self)
table.insert(self.Loaded, Track)
return Track
end
end
return ReplayAnimator
return {
["HollowPurple"]="HollowPurple:Compressed:eJzMfQl4TOf3/53JzCQiE6RimVChqLWqsZRkZqRoLUWV1lJVa77EWtTW0qL2qhJKUlpLNWiqpa0lkhtUo0goSSihkbGLyUIyWWbuvf/3vHfuvRPvO0mm1f/z6/N4fL9Bcua8Zz+fc45Ozfi8Pj5iVvDr4//HVHtz4v8miP9T/GL4jCnSF+F/agdPmzFzGqPpNX70OGaBV1RW+3BGF6hSMczb/j+wDYc3NU9YN8W4p7CPfjYTqEZfZr8xsG8eftb0xpq6xnr2dXnnHYFe6Mt+6u/ZD6Lqsf3H/Gk6WyfS8kpBoAZ9OWuA3pQx935i7X3LTfP9w3NtrQK16MuF3GDj3oL1poRZaexH3HX1iYBAHfrytIAlYehXPPw+QnPe9tgaEVGnm5Oe+83bswcfLzC292ljvM2/pXlejelptPR705S7duOo228Yp3LTHVftmJ7OK1VJY2puZj+ODDN9Un30rU33MD3q1t7m42dUSYNv7jJeLZoWlNEe0/PdVz3CHHveT8yPTU6MZVYIdwSSHt1+poBP140xO+nxidvCtveJM6I/7NqBP8R8LdJTe99rptc7rzR2HBlvnMzVKd1eiumZFuAVeuVccaLv5ecSG6n/1Hz8CNMT1+Cq6Zc/ZrOjbr+Y9FbuxGc+eAHTg8g0IpoSgJ65Qk1muhemR/rvy+6rw0brJjBTy063WyzRg/jCon9jnMM2Mv7Jt9IEeGF6fg/+ybTvtWzj8jrDjPW4Dxx7yzA9CbOiEsoW7mXhJywv623rdQXT83FkQgJ8oEZLcxI/4bSao2pMzyujbof6Xt6J6TkgTBTsAkEPoytjcriY6KrKz81dQUh+oj2Qn489kp93kPwUW2/XHSjJz9d5z7PoD7D81BDmazapMD3oCdF7VTN1+aWXcSH3iWOKSE8fP3XSB1Gi/Lys3mDplCXLD/wRyM9Lj48ZdnXA9KBXDTt+Zntil1/+SGyqWiikkPKzWxvHXOKjst6V+BPUbivLp9czg6DMtC3VTxAwPasn3008XzzIlDVgjXFB2Yi8QpEeRCaLWIb5wwT3yW5aiumJ7+1ngrd6vv0KU7S+Rl62yB9EtXHtiQ9Mo27/yf7IH1YfJPlj83qv+LQ1PPaExJ9595uzz2XOM/4e/KKxjF+l8RHlec2mfSYkvCYQrYncNoee5M+HQqRl2TVMz+rJin7VyM8wvNNZ5s/hZ5di/UpmFgqHSP60R/qVwzPMGx6914eOCf/pe0VE3JHoOX6mMdtMtwjzxyCs1SxXyfyBVwD+zOI2OhaI9KT1U+gZZA+zjP0L01N7n8ifr/NijUzB8qB+nTA9iMFhiERMTzvVTOEASc+LuuMMIzRPWl0Jf3qsVvgzjy7PG7kwyxdX5feS+GMoeGD4vBOVP6dIeuZo9zPXeKz+Ij3sNzEsshPY0Mzhf/U6IsrPOmuC6XpTnQlMtw/f16F1yPYQfiG2HQ3iL6vX8pgesD3wZWRsjl5x7OCKBEzP2hNFYejhE9EfsT2w4SHsz3V1dWEFPyV4uKRfN3d9xV45V9d8ejZr3IT0q5+oXyWDbiaOqTnUNHPCOuOsssF5dpEe5EZYME2gX6cabsieUkzo1y79vdyzon49HPiy8fLO6Vi/TvMHaPpl8ZpefMIalRUY/sR7gfwI/FrNKfG9kJnE/AH5+ZiLcQwi5eebR5GWXecxPV/nie8F8jMyJ6++TximZ2iXDmFvrNmE30urWkLTL63uAhMopKbEdXPxFyDPID9l/HhNtqJfUfU0ptSU140zkb9oTNLzV6mvhb0ky7MkPyvzHhiKOsv0IAOG9f0Os0TIJOm5pd3BnOJTUzZI9PipW7PIRmB6fIVIzXcq2b8jLcb0LED+fQhJz11Ej/YyQU+N/AeG+Yr9aXtgK+ZPoIpKz+faWETPwv2+Ej3+bV9ikQ3F9GTwAzTvq2X+OPYUGMEFjUX8+UKMN5rpxHhj+LhQU3C1brfLbmN68mN1mB4kz8aykj6Gv16Q4w30C/NnLD3e2KlLRu8Vq9/vyh/lvaZpHir6DvYZ+DML6XsDkj/D7b6Wd/8i+LMZvdcl5b2QEmF6MtF7XSDpKUT8ucDHRDeW5BkpEot+mfYWXDSm2T72CdRgei40yTQiWkw7enYyDecKHk0W6Xm+/R/syPjeLDznjABfS69cTM8660cmhvmE3VvwpmmxrqvwSgvpvYwoHjPaWmxhazI11al+BD3JmrVlLz2eEvyqRE/jnw6w15s2NwMj9hQW+XVgnO/VhkWxqimo3fUwjb1f3gYl3oiJro/1vaiur2XYI1nfId4AfU/X78jdK+o72DSj7ybT+eI09nXurrrpMwQ9KzXdbSeso+IiJXr49MMs+vsmZFVMo2yPfQu0mB7doo1GoAfYVo8fXcTxmB4UvrLojxLRpzb1KetfHGbD9CAjbESWMxG4GeoY5einx/QkzHrG2HJEDRPSF3axcEc1tDqmB55RoqedZpE9pXBxf62rPEOQjP6ScS2P9EuMDy/v/Mm05NgZI/iLrtzvjsVifIh+qAkJLQ7VftHUz53zN6YHSX3i5qkBSfteG43E6nvfu82leAz9YC8cH44U1tPszyTvs0w7YUpwHYk/vxW1KGcPL9LtYX9Snpsje9i6UnsI3AR9Z+j20Bfbw67WkRI9yD6wNYfWNz8ceNg43rZQP1X0FyANS3MGmpB6GJfS47G3UDyWRcZjq/WN8m4p8RgK87G/+JYej9m9BhenWJEumJz0fPfVpyyiCb3XL2ERfCv1JtH+dF65yARpB1iUpdzUsqllkj89KvnTEXxtHYrQgR5bizDziLUnWMeegUn3LDf8P/od0wPKgH4lfPfVycRMIUfQqgl/2k53Xb3RHhM9zDU+VOKNjzXrFPvzvtHXGW8sdcwk4w0/FI/5k/FY88cZhhglHkMfCL9XK3q88TmON0JCnnPNByV7CPlgA5E/SLHlfHAm8hd37AQ9DbwSLC1uEPS8UZhhWBMi22cUC2N7uJ9unwfqNjEnED3dXe2zxB8t8l9xNP/1geNNkj+jEH+WkfzpjuLVlQp/UDxTkf9KQ/40hfef9U03Of9qK9PDCMM1R0V6UNKHzIbWBPyZy413hJXXr2+nG03NitOyA9MJf7EC+Qufl6n6ReHPz9otTALKd4Y9GY8FLDlm3OpRPHYOxWMrqxyPnXEXj81G8RjD3DAr8RjOleHfevETfYtE//VwYAlKK58B45fYkPtB3YvD9Bw/k80iy8DG956cZE9rn1vcCtMDQemX3asnIkUK7c/cL+G9nPJzMhR9XmwPdwjjhCOlmB4QK4meexqT6l1N+rJe4bI870fxczMz+JrkQrvf86L/grARXMjBx1xYURnVf7Wp52vZT/qvM/q9ud8p/quQ24D912jOom5I+q/FmgE21to8aYkkP+2uN5Xtc6CwSrNelJ8J635AtrA6ts/zuC+kfMdVnlszkZYm14n8Qvcow/BDR8l/ueQ7c4UEUn6maA8xd1B8SOVPCuJPsMgfMEvIEP87/kAwJ/Engs6fTxB/frN6x3eW6Dmw9Uf27HaRnnWF7fQTRXpu/9kEfjDEZEaDfX7eSbK+caNOmGUCWd/o4D8j95ryXki/5Pe6RcrzFM1G2z3rlOD+ij/dza4MDza3HLHWuKionf6iqF/9x9RkkevH9vkY4s/Pin5J/DHVT8ve+5jgT7x+f+7XIj1gvEbGrzRtnnqRzecuqstIenpqWFuCNSb6gqv8SPUELcqX74rys83wo+zfoZ7QgpSfiXykZXwmUU9YnR8YdLGTLD9SvHqDmUvLl1/THWJyUD74drhLve7hwHrmjyMTjOuQfx8s8gelrIlG3yEmYNsMZH8ek/anLGhD9s0iwv7s01/IPazYn8Y/zcD2JwnZn3iSPze9JhUfQfbnRYk/2wztZPtcxA+X8i/wXxDPi/Z5khTPu/LnIPIXP5L+Ihr5C1MHSv5F9V8GHdjnsaczJXuobr3cCEU5FFcaj3HnfT8R41X0nxmkFKXRiTW5Nl6MaA/59BIULR1hM0sXJn2dNi4vU7SHH9belyj+BK+Ed4VBJSiok+obEKEAPV2FmUJ4KRGvTtWOVaVqZl3dRfNfZfx7mhSFP5CfSvxpTfqvI8h/nSP91/zy/gs5HGx/8hmq/zqN/OkJHgT//1J9I2noVnf+/SDdv4eT/DEi/nSg+3fmZWo9gcKfHxB/EvjkgGqSfoHhg/wd9L2ZsFEzUInnIVUJWNLNuAT5C5aM52ug/LTpX0Q8X+OhyhARKuv7jp4HE1GikjgW+QtKPN8ax/N/TtwkyTNiQCLoJeTwadyrPmO0TvtsgVzQOAE93AxuP/O9GB+OWKtO+nZ6IltfsyzplSvBD3a+IMuzWIw/mdCIy7bbeWc8thPkOQz4Y+cThBQ78V57dZnMcHWsfp30XnftLeX38hWmabYr8eHz7X3k+HA0yZ/xiD/T/iL86Zz8B4ZmSn1jDvsNfq9GKH6+RPJnhTYO5e/J6ztL/Fk9OZYFRqB/m8DwzRhn/RD9X0grjVA2y+IGlXwg5hcgx+hXKHy7x/x2PwOD6TF3NJkPP/s7+3rnlUl5f0+twZ+R8x30ObH96cKMRX+X4E+mtocqspRhOkjyg1iN5KeZ+ZVR441fFXbXTxP9adsDDVmfuAYgQ8Zg+7q8c/R+wTjSn47yH56br/j388VR2J++j/zpGdI+j9Mctj2yRkT40uS5EZLnIXR5Pky+19GyMEvmZUKeH+aoDB9VWZ4bY3mOib5Pqz8DPR+J9CC2meBTAz1Qf15J0tPLHmbpTK8/j1Hqz3fte7D8mFQz6foF9eeY6JXu8sFN9HxwBum/RvJhlpmZhDy/VfDA8HqnquaDM3A+GKvf42oPlfrYe5pLin5J/gLyweakPVxX4mtZlFGZv0ABAqYnB/mLbJKev7C/uF13tETP4JvNXOLnpVK+DPKjxM+rHHNJ/txSbbDc+ZuaL8d1oMbPx0l6FiD+ZPMMs9m13ivVV7XCeM33ij+F/BT4swD509dJ/nyL+HOW5E8a4k+iUj+U8tMaKip/NmP+RL3Xw9X+1L1yzgihAsN3YXzVUr6DfSmEaUnc/JI6Un1jCdgfqFgcjRQeVD8l+lPdoo7mg48T2ah6nyZ1zx5aMz9ZoseIfDXOv7KFQUwZ2T9trCti9pRe7Xarm4u+ww+W+jvr6f2duaR+fYb0azupX7WQfg1V9EuRZ2p/pz3SLzsfHruXLs/jNddo8kzU5+G9Gpb6WgIrrc+DPEv1ecp7ZeH6fKz+pEmWnzgc/yDZS7jAmZk7Ksk+m6DFi8wZin9mlcwV3wsCHDEGWhL/Fl/N96oK0zMu1GxGT4hCx5VJ3a8d9K9/TrbP6PtiemoyK2jvFaLzVZvRexW62kNJvyDeGK3kp5J9hvx0D/leavReKoo9zA8Piuwsv5d/2wP4vQa7s4fJTHVkD9tK/gK66UiGzCBDmYVD9CMYOf9CpsAEIulj/zEvjcxPD6N8sLXiv6ADDP7rqH+tXF7Jv0Kz1kLRmN2O8q9DpP8yaXib1RqV1VCip+HwcSwywiZEgGlT6dVqG70xPcvrROP8AlKz7/lLdq1Yf768M5/Nj13GvnpwpunInQ3ZE3+T8Qljav7FgsS9VdK2xksvyvqFfiWAjPZgypglKoKeg7prfAYXHmtxp1+bFP2S7OFUpF9TyfeKR+91nXwvIX950FhFv5R+JVW/OmH9iohopfTjYlmGCTZDn6EI5e96RvKnifebt8f1XoM9L/9X8r1u1fa1HM8l3usgei+/1pge0NnrTZfhfDmTu6xmyffSatoXp1m944PCXerz0DwBPMB6x1bvd6R4dYdpXGgWTsua8704vZh/rQxnkrLnb2CXHOtjGnw7wdLmBKZny0nG/FxmKQvR26H812rHivwBsM7Bx1wChEbNmP7MRIq+61oxm4UpwYZwl/oqygGMGXMnGnvyEdoWYr/gpxm7TQe25uFn/Im76uhZ/r1yPzKb6jzYYClKlvtf+15TJaHgwtjRqqrXuquTP3FhEJ9D/DOXSRE2k/QsR/lpD2FU3JsSPVtObkP8CTKjBzJ2so3TfyTm7+jTJo6M720CU7CurF9eJlnf+NqQln22kMjfD+qP5+4W9QuMBXQ8Zk64wM7nE9XptPdqUxxvjYkeqMSHO1hbiwZmEEW9bYj+C5GeZjoVwHCwfkUjes6S9IQhev5Hp2e7Qg8U+oGed/gT6kySnmc0gcVHrFe7PXQXH85Q4kPN2/5Oe7jREUXqlwHpVzNSv6xIv5Yo+gX5KehXD/f2UCtwYzZK/h3F8YlgJ0C/Cji9zwuiPG85eQPjkSCjmsDNlfKvkJDHLORfN3d9mPTw2v77C14i8q/GXIS9jHfGP1Hwg0OxvxB+EHQOwl98rsthDOrSnjXDXepRUjxvUPgD8RhoMdgfiOd3kvxxFEda9BlEPL8yJ69+qhLPA6nAn/70eL5QewnF87OurnGH39hCxyNNoOQXjjDLsStE/HwB5YPnO1UV37IA41ugU+ukZ8TaV1jIl6H3Opp/4DVdrIcjzTXBd4e07BkUP88X8Wzwn1Tf6MN31ASJ/aYJ69qawVRmz6/Nbrtbzbd6Fyd+bHxYIZceBvq+ht8sNCPrG896T1QX8skBjRV81HUW+TtQD2Ob4nk+rEgP8Ab0C2qav3B/PXba56wBqezSnIEoQtll2lorLTvJiulBealpd/Jq7AjDtYdUi8T+MtT+4bMiOWK7MjmqSdUJ/tTSBto/LUxN+eyf4W1c36sVF2bpReJtOPRe26r8Xh858UjL3OUX6xV5hvyrgvxivhBpefMaQU9CQYahRKnPK/FqBfV5/1lJrvxR8GNLNd40/FgMDT/2OqKnz7Vy9gfoKcjLMEwl8WNn6fix1rr9iB6G+YTev1ir+YzWv9hI61/8yWyw3CD7F5MeZRiG0/sXFHomaKH+HBM90SN6qP2UKJQPJv5N0FMN5YN/dKgqPTPwe0VEJLvD+6nVcn0eoj3P8X5t8jMM5s4yPQrej0pPKMb7xUTrJX1Hb1yu3jJCkWfJf4F9/pnUrxmlYZadlwj7vAPZ58OKfR7a5Rccb4yk88dXB/Y5OUCO55HhY9P6NTGDT81D8XwvMT5EusVCjgr0qOypeRfI+PBbFM/XIeP54/4+uWoxPgRjUffK5zie34/ieUq/oL2mWvFtFM+/5dq/+CBK7F+sVvoX8N3ra96W+xePyP5FQtCG7O/J/kWc/kLufqV/AZE/9C+O8AfUiSQ997zGo3hjcf+e7uqZ39H73UOq3O9+qXy/2xWvdYlWn49lUnhuzK9SvAFFb6RIAIwI3c/tqv6N1tkf1Jl1iwJNa08UJSY5AjVaMX5Ggps0fNxRdnmdlUmz0rOsdqWfC/EGEpaENVxM6Qe8FP+EAk24/sP3FsaUEP5rpS5ZtVt7u+773Vzk+Z/Zn6lI3yNJfb+B7M/VDp7ZH+/47h7go3T2fnkbSXmOqhtmaUX2T7P0O3L30fFRwbT+cm8ba902aKJrvXfmhFpmyHkWFd3ze0HtxNtMTIQiBqRBPo76BefE9zpfHIWyRy4Rfdm0SXfz7rD7mB5EC1Kkc4mRCbNMz2u+LGjYSK4/B7V7F74Je4ZfoZ5TE9Oz9sQHMj2jNB+XMPkM80W3J/BIojx/4BqPSfV5wBuPIe1Pmt3X8oisz29E/l3oRK3PU/B1i3F9vvOf181y/PMu7sdBPJbNfePbRZTnjyMdOKWH8kRd7pG6ucifD2vnsoA429FzdhKbdiX3siLP6LsnQPPtnPBFSZornv85XB+bKkwV5pH9uJba/qpNmvRl1Pp8dKFRqs+/efhZ3H+H/PRZ+ypaff4QvT4/2H947kOlPo+yWSw/kzmL+gKtPn/AVmSt13ekFK+OqTmUBbkDLNwEfrpXoZifjgv9xgTWH8x2O+6OPZ6MVwfxv2uGi/Fq9vwO5h09D7JIK9n378yvbjJiekChgRmivv8gxJLx6hXdD2oV33ehtyQ/NYd2YeFzgPys5rtqvvGS/RdiM8aLmpC+O/spffwWm1aGb2M/rP2C6XNtvpW54fRfz6OkqXZSRESEqXvpcb/wVnL8jN7sqIiv20zrx+32TkD+KyJCzpf3vbadHT4uyAxgsVa2d/VLRH8x5a49EaJh4A/ky+lkfjoe5afRlebLmaULcX46nZ4v+2mao3y5tGcPD+0PBb/xA7I/A+n2Z6+H9ic1xec/61fWf6gyDPSwXxmVJccb8ImnBTyH64cXUbwxVuQP+lYsCh1NQKbGvi3vIsmfnSjeeLWAWo/Stpbrh/3HfIHjjS30+qEZ1w+h2++kByU2LPq/4DgTijid0EikB2o/UBsDzGggX6NYa5fr81K9dwh/vfoSsT+Y+5EZ9weh3mvM7FAj6TymZ99ro41Kf3kT85qW0K8R2mRVfnHp763Mcrz6HQu5INKFBF/eJjDie4HtgVmZEWtPGDV8jZJr5fuV8O3WCd31q0R9zyw1yfQMv37Sf3SqHI8p819zmQFkv3KpdrEqsDQmepjZpf4DWFH4SQZ+JrNQ7cSPvYx1C8K0pdy5kv3S/NeSePDYUIXbqfL28S2W5Ue3aCMAc5Nm3TseYOgi1+vgcwI9K4RWzEGyHj5Ct5hpUJaakuDqv6R4vgjlX854Huo/Uv41lZ5/HeMjLTcyifzrJsq/VtLzL0o+2AjnX6kpv7jGh1K9t4z/QFOg6BfQAyyfivLTuqR+/ewIs+y/QtATm/fA8JtCD0rtMT2XmCW0fFmri0X5Mspn/jM8ZOQ/wEPertvY3TxjG/o8Y4bdiT9UyfzZ4pVgiSHxq18UZhheCyHmGXe4m2fcwpziS3vK+DrHnv0YzwaOKlHBH4JYAf4QICocHV9nrhL+0BXP5tY++8/KovULIH6OVfoFUn0D5HksKc+NkPzUv0LUMx/kTwuaqtQzlfzCbb/AxicHtHS1zyjYMcPD7C7MkPCHE9ZNgTInrpG1tM8qmCXSA90giT8PAzZYaluJ+GeI//zcWqJ9hjhvyt0Pcb8gm94v4L2MxeetISEz/9P8IsfD/OLFL3dL9hDweGDXYfg1hRviw2id855XTSWDbhoBbr6f28GMd8j5FzKRGDiyPv0N66jy+RfMoX7ENSyL5p3+KyUMBe/YHq4RMml4m666RsxWdUx0tBQftl7+JUy3Qn85rAPfReXE18Fs5c1dXxlR/Gy8wk0oPVn2hP/yOtqat3m3FvuVp2ebzGe3i/5i/N/3a7yRgulx4oaxfvVmujBq0j7naHeqA8siIg7S7GERP19TrLyXqz2sRdrD57gwS9erhD08iOyziz1Ut16O6bnAUPESvro45hr/66K5/15+eiH5MZHy8xuSH4MH9bEEJD/Nk2562H+fSe8Pbqf3Bz3tv3/p2GeW5y9OhsE7QyAYyD+qdkusPy8wF+H4EOCVTbkO6jJFnqfcFesJO9IjrRmkPC/lMks/4mV8OKRl8F7rhYnCS2WE/ATq8hk/jf+s8671Xsm/C/wqjVXB04L/kup1Dcn3ikb+PYbE007KFwy5Cp5W8qeZFeFpIyKaS/QgOmR8wgPkv3TK/AWEjRLepoicv/hbvcHyF1n/KXx8zHBZ8V/oe2N6jtP9VzfdJuRPQ0Kq/3u81sSyMMsGEq+VlqMyrKtyPG9w4rVK3eEThpD4hIWInn0kPQ8QPdVIeW6E4o3uL8vyrNQzqf24F3XJTE2hedIKyR4+uriGRf8G4sqwofwWlZ9cb8H5MrRVf+L+LD1Yfp4Ifh/In9SNFON5FA7h+JlhPkm6deN+jYd/yPsKAO8H80RdmJrMZnKeqEB7Ub2lLGko58of1/yL8l4L6fVeyL86U+YZc48Z/lb4I72XG/60151F/JkSHBDuol8SPYHKfLcrXutjZH8+J+nZYYu0bEoj5OfjnLz6f4fK9lnC13VRUfsXebg/2Gbeawoe4AAAR3C8cQDly20ZZz+uJRRWTBPWWd3FYzVRPLaSjMfOl4/H6mu+xPHY2/R4TJxnnBL8rEQPrKlA/86UPb+2aUBperUYEU8CZRuoj8H8zj6+m10t4kkQeQDKYntlzzfdvtcnu8/vmJ6EWWk4yIEI7qvSsf5d2sl4EsCBnerbme3N1FC9qCbo2aGL4jtz6cuaSvRALvt7cE0zxBz1imr4vqpy4vmh1TgY9pOYNtufL1gn2h+oPkDH43rTZJNvQIKFe4jpQdGtySeuATge0xHf0YV1WsrzlfA5+/idYAv5KPWsWhQ8//ySs7m/Lhr6f2Q+LgrjIWOinwLeuAXSr7ZkPXMiHW9scIc3hnlhpFbSe715+Gvkv+qbwQa9Z3tf2ndxYGteYmjWALwzZVHZ4LybZD3qsSEt+zFZj9qvPy3Vn6Hey6fPxf2LGP6w+jQZPxd79So+am0zL1Si5/LOn7B+Qb6zvjBQ/5YyTwT6BflOXfukvANkPdNWJ8yyunw9E+gJ9F+Ve56mX3fVxSQ9czRzbVetfRf+z928VdX7gwlKf9BVfgzu8aIJ7vqDMdFPAU97ko4XnU/iDyvF00Z67ZfiMRAQ6O/Ar7r8Id+HYjyWWcqbYN7q4cDDiQ8dDvWrYj0cMUKOx75Pn2HlyXjsU+TtZkv9nSVdlXpLD2FKKeG/dLreqkTNZ83OuMZjMFsg9U85FbV/GkC+1wAh0tKO7J/2RfoVQPZPz9LjsW44Htva6aRZ9qfb8TwjDMJt4p6tniTmX/teU5lBflAKlfgM94kXJ83j+yRBdwTyL9+0gfnjy/MH/Z5QxCUXf8rL+g7VNKDHICwUckukecZQiT9m3VDVC9rUFEcl/v3J+Kdq/h386S7k3//00L+jfJCOf35Ps1/BP8P8TgX45z4ladmdSHn+FcnzFUWe0Y/C8uxLxz9vxfLMMJp/X38G+9yN5I/O+rJhateqxqudEH8ChV8X+Uj8Qfks7qcAf77izZqJSv8CYNpgJnsger4rc/r3KUbYYBQSEmJqqzuRMynbie/NMh7YWiOp88pwU1bJzzXbtpH7F0r+vp4Wz8/xPo7j597hcn7xExS+sX+/UajWG0T7DGYSMMcgpbn0+GcEin+O0utRO1q54I2j8P6o2Sj+qU/GP/M079iSrElDd0jxM3Af6gnQO2vJd1BVF+NnJDcm2OkA9YR0bkLp9ifxz15Ha/DzfFaJ9YQ3Dyv154XXP6rRPFXedwGbwYA/rRgzrZ7gp0NBdVl47CoP5y8o+39KuDCLFzl/8XLBA8P7Hu7/aTPveem9QkJ+ZqfchX5TG+PbhS38zOJ7wXQ0/FCUGhib2LcW1CtfHwvNOm+aW8tiuZMjvxcKHfF7vaHvl/ez+F7QXFwZPsq0NOcCW51PpfUv7nuNL/7dGpVVzV0+WHX9+ps+v2PzaH6nOc4HGaZe+BP7WyDWzVPwNmAP0U9w+nd5Hhbm0ZbXicb2Z0XeBstHKQQ9YTnX67cPk/NlpR6+guYvxH5Tm9KGkr+IiPiOffXgY9CDBF8+QVgj95twLA+iXo8/W2ywy/mgZO7DmM/0xbyM55fkOfxalP8uEc+PgwN5vnIxs4rsp7yhPaQ6XoKI+D8y73kO2+dtg2rR8KKByrwVyI9Uj1qC8sHNpPwMKY609EivCC8K+qXgaRe6x4umpkx+OvixjWS9jnvkCX5sCq73Jge85bovZXmd+nh/3TzbXP07gjM+zJH3181D8fwDEo/UP2hDdhQNj3RawiM9ub/uOKnv+V7DihOQfU6lxWNQHyum18fqkfwp4iMtdrI+FpkvGFSdifrYpYrqY9yYlUYXfwHzleK8cLzXObUTv5GA5RlKnRzX13HbXtG8MCx/gZEncCd/OaL4cSp5XhjsM/oUbFOVXaDMC+u9DMJ6flQctb5RQ5GfJ+sblPnBurZIS4dK6xvoS1h+OlRU3/Cf9SN9/1iktB/AdZ/VTO5D2j6r62W+lozL1H1W98l9VjcYKn4sD+PHGOYnj+j5xB099f+qKj2ZdHoKMT3e8d7/Pj7soMSH5fzFQ5WhJem/JtD1vT32F0H3+tPwUTXK46Oe+j7GC7R5c8BHxeqvuPYvpHo4yPMpRd+hviHhjbuT9DRA8U+7q+X0HfhzIn9o0OdKv0Dq59qZmfT8K4Ep4ENCBnmAD3ezX7TD09hXuRXjw9OXNVDwWi+wwAiY2Rtr53w+1zn37ewEhIgR4ucIfgq3Q8yXp9y1I9v8BQurMNrd2mBJP4bpQYbG9HtwPlvIpRszHs0K+LWDPN8EKTQyrGwjZj2yiAQ9t3V3hB3C2NN2l/w0Efqc4Mj38qd1d8X8AsW9pmY6FehYaD0OOTbRHsKKvYy5ewC4n/iu8PiBv6jv0BRYsymXXWDuaOoq6H2uPivFPy79lMHCUI6g55Gmneo4U9rzKeB/1HT8z0tIv8xVjg9F/QoJuVmF+Tgp3pjqvv+1v9L+VyXzcWL/q15fjau+g9ACNngDv03zi/hekQm/gFvGX+7ElTo2iPkObDdrd/1bFqCJgzQ+uUdE/DxK3hIv76yZBGBMtaOk2r5mcryq7ItbISwh6Wnpncn0FiIiRrruy4V4AzA3U8vvZ4PtgRBvuNnPNji4T3YsuZ9to75u3j0y3tjrbl/usOIUa0SETuIP1Kohj4T3Ws33lPB+gLdBbMZibkLxhhPvhwTXlNZvB4aON9TWyg0T9R1JWSISlqSGw8eZ5patrz68BRXvR9n3tRnlywah9PdIs1wPX89CYxv3hvimqsNqJx7yPZTmRuH53Le4T0t3lzrxUSdDIeJGnzzxlKqM6SXiExCTTVAISE3xS3pU1D5gabC8Lw7mPYGemUKOoKbhkcYyt8u2dvpUogeAayAkwJ8rfIbmBZE/vbLj8fwgmJAArj73WMqXn0tEwQ6LVI89U3Kp8F6GE987MRGGvSD4CuWOq04wUr0uFCDaQE+CMAxpPEHPA61BtZ6fdfW2az3KVb8+q/L+3kVIv2Y9jf29dr6rVZ4/hfn3gCXBGO/nU9Rdmj+Fj4RIxBiy2vYf8/8g6xszA30tX+QReL+z/kyuTsSTwGcEEYceiZv50+qaNsVp1kerj9Hnd1bR53eo8yD9y88TSfEzk+/5/I53vNm1/wV4UVCkrYVqfbjS/4LeDlKPMF/74LyvSf48VzfMcoWszxfqY3ITlfp86+VifX4gd1ddi1b/GW07Zd1/qyENr3WDf0vTScFrPZdZKuO1zpJ4rUyN7ubDbMK/5xU+MGS+JNtDEHXgzyZmDS0/naLbgfevHnG1zwqe5GOp/izh/UQ8yUZa/fl5PszyIon3S8/LMPxEx5NQ9ksE6uKYbL7vwiEe9r9m/Kf9r1j9Inf5ctX31+1mNlj2k/Nf/VG+PNnD+S+vravMcn31MGz/x4KSwC/XOfevbp56Edd/wIQ05E7xX4vyA9yEedja+06xiY9+zCs4S8zDPnbElF3g5fhHsoeHkDXcwVH27ZhU/ZnUlG5P6hckNjsK7X5dSf3yoevXAKRffAFRX81D+nWE1C/AY1Pqqx9q3rH9Zt02iLofG/bFJSrxGMwTSftg3yXt87uPIy2mP4l47H8oPy0Ope4nobwXg+e/Fvfv2M0lfq5CPap9lfezTUbx/DvKfjbk1jA9RfT+l1a3hTmB/EUfiT/IELOLNj6H9xX4FNXQeyvzFyh0xPcU7pb1y9tCvtf39Xwt/uR+v9/L18NnTliH6+Ffctdp9nCSZoYtwVras5sH9rkC+aHY5wrkJ5Benz9lHfbIbf3wQpXrh+qStOycp1M//KxZjIf9plfp9BjIftN37vtNFHp2YHrazKsb/gQeAOrPRfxazaPy+EOp/hyi0CPVn9/J32B5LZXQr7451+s3DKPuGzzgfp9VF9f+DvTf4a03FjbRj1H6O9B/hzZmPfvMvPgq789s5j8/N43sv49A8pNHxj+zNCttN61Xu/3iur+3Urz6Uhpefb4jzLL46eDVY/Vu+5Xfe9Cv9LVEkPJzEtGTXOV9TWK/MmnodXd47AN0PPZQ0h5+iviziMRjX86f5rpfQqGHGj+H6hIYG7KH/rR5Ydjn8D/6vDBl/8+FkjBLegZ1Xvi0kr9L+38G0f276C+C7i3893jaMhRv3KLPm/fyMN5Y3H98JXiS8vvH/js8yRyMJ/msWfy/j1dbu49Xt1Q5XjXgePVLx+dKfhqVCHsgoL88je/t3U3Ek8DGI4jnoTzxMrdZOCrGY8iasLBo7LuvmiY1eZiSM+O3cvEYFMOacd+U3pPnhQGEhuOxhcJU4Sq5n6SurqmqlYobkyHRAw03cOJQ8p/GdapeU6zXId9lBn1fXudKopr71cvp3yMidEnPZR5B8eHypDlpw/ILlf2r4Hlh+fQ0ni/+Q3CNN/A84yF+hfCHiN+AZ5T4U1+3RtVNG6t3i18d4RF+NYjMl8PyBMPzHuJXQ0KoeMgfFTwkmG3wF/Cp/xUeUskHK8BDJg3tFK5ivN8cP3n86JnjGdWLDLNwfx93I8TbKxwhfnIk/j16CXhDh6qOEB/BkLttg6aEKyt9AeCDn7A6f13tPNEB4SIILVSZEgQbV1/A9EApCEBQ8LIhnFnYIY7Mwa5T2PkG2KKJQm8mgZEh7DCWARU+LTOSMagJSFAr1Rohh0sOkOmBIW7ASUAIO4Hb5XVY4zRJbU3AMpD8WGGoRA8MMEFzGpp6Kx02fqpID/xQ0C3gZkdhEGMot2IYt521zAImkaRngWqc8ArHMCX/XsSL6SI+AYm4NyniwyoSce/4Z8JdUmjJpfkiF7JFMdnOtTe4RUdZQagtirTUukht0VlCqSm025ZzRESyclIuDkPKAGu8imta/aoIKUPf3Qwuf9TtPxP13EYvCwkpa5g2Kn8huVKhiDtbvJaXTZKyQneJYCmR6JHfq7dugqqLNjy2zENIPQVSFmSnQuo1KCSa7aFJioi4Y3KBvIBtRj888Sx3gXeONEN5HCppAHlpz2fbysiViNncmeprRUgQw3TDI0Yx0SuTUv+KrfG/NEwP6IgCkTzEzCFHZGdrt6jOFIeE/FbJCTdoif3/OOHWCa90Ke05OdxlZSQoN7Sg/O19dZ1Elwarm6BSDRo8XGhubynqeyGXngichIUQkWVx3NtiCxw+DNL5BMAND+MnADbKWQIGSJkR9q3ZhDtMda1T3/FkTTzwZ5U6is8uGxA0hr4yaZW7lawLnsZK1gTayi0IiaYEyyP6x89shyaFGbbjNVZG9GHPBZyRlEb0L/7TEX24JgMj+pH8CfqIfnBxvLXNPPmkARIUPAIKqyc20U8aNLAv9vCkwQ36COgNdycNbtdtLekX+gwspKvgHEYjaVinkeUZtBe+ZW1ul2OOPGLdVYJQhPCzvVIlCEVtM6IFWpgJ7z4oqVbcTm6xQFsDcLFL+M1CPtlC0HpPUY0VulrruEuhLYr9kSC/UKIykil0u4JIS8NzhH0eXD6FVkoM1BQ6EKfQ9355h15yXequ5Dr3n5Rcn1wBdpwG8YcVw82TMt215A8pLXnJf01VTjq50hOPUsQEMkW8lD/UNUWUSh7ailLENvMmSe+1wPwruzRnnQnPy5Tk+BwX7Q+kh9ACh098nZ9YEibaH9g0jiQ/EWZCppUsshfbMT3wgWAtBxQhNVwrZrPOWTJLB2SOEdbmXRDGqoq9iZB6iVd3zl7sP2ttFVbMAH8qWDHj7/C1eJEr/37Of2Ao8nDFTFerfKIMDtqcns2aAE9bYBvi+57IH2hfglWB3yP4CFsDkT+gjVDEAIjAvZKg0tgS5wrmjbBrJxEJo6mzoze/x1ceCYM5wMY/zWB3CAmql3wxPUCmRI9aE+y4VhQSUqMKKb3rikZKSv8dPaXf7FFKb8fxT0jIJGXk6SCLvg3mz47i76t9K/Jn7YkicDswcmDcyU8qfknkDxz0gKNRp2ebTD1LZpVtLJNWEMIMaSIURZc6NgsTfDA9EFPBHsy4BsPZBGG9qmY1Qn5OecU78myj4jq52mc4gQP2OUqxzxAWwYg+sNyNfT6E7DNlBU9P/0hX++x6IugaaZ8na7bbHlojIsrJz9d5d/FIWEHR/OojxPgQXA+iCVJWYxI3uvBPcSQMZQosWBSUlZj6OooKZz6WUlYc6MBSx58c3mX9asoj1ugXCjK/YN8Vaqrn+xEnlPppbpQdeZw0dKk7/76+yivXd6P45wi5EvFKQYbhGrkSscKTRenL/P79Sruc0jBLUxKCHI/k+bsqr7SriUtUMdETXVc8tPfxMyPZM84o2u6nEVtQSG7gUgbW93mO5IJA8b2WHFsFC78T4YJ0oVeDnOdFiDaEZyPWnkgsWxhp2qyq97htkLxCru6V/iY403Sfn6neXAPTA25W8e/VS9PyY6JVHkBwFtJHdgHiNoiE3B20vms41oUCwZnpfgTiardv3a0ISa6w5eNacp1enJa9uNIWgmvLh1Ky/w2fVElNmRDuAtGWThadLOqu3y/qO0zZLtrYHcfQnew++X1ECBcspJk5oRaLfoLJW6+7OVZckQbNRTiyhn6CqU615vlFzeT4EE4Wob/NfsH/oL5CjjiGa/YUH8hduD/yP4Mge77CMgfxJ8y1RK6813jpBI5riXwuN11qsbjS8zl9BeGAx8cMczpQT+BQSuT38Yr8qCx5JTQAfGAEAlQ1EMXzKwXphBIKq3tiyG80PZ6vYCW0SzwPICKI50eheP4v2kpoQ/ER67BHn1cx3ngCsumqX71RPNadHm9YyBGRCuKNSyg+/MpVv/5ZSwwg/t+kUyG21iq3xHbjlsasqxm0eBXqLZeVeFVqOQOE9GVSfn7iIi0pV4l8eV9+eFCcslJBiecrgJCOPZ0nQcYzSxeygNWCh5nM3/ZKEO3zqb6HTEbfy0aYuVqpnPB3zXeC+UfqaN4pz8sh4U6EcsPG4hs+1tpO/vwCK5gT4I8uCadoJ/y1WptQXUD67LpyXRzpiTN62ebq94ryfOVccWJ+7Ks4P91eNinvrgK5g1lqkOe85+7fWOjA9IBlkEZ61vil5o1X5DlgiZifjucTaStQm6L89G+rd/z/XOmBfPmp0fOlX3LeNA/paZ6U427l+hxy5fosj1auX89fHjTXw5XrV7u5Pel9rconvTeU+lq+ezonva9282wl2UZaPSqRD7NcrrTlU4WVZNlI392OiDyq8ojIH3yk5Tw5IvLOPxgR2drpllRfhS9CCwrgF2b+UbX3Nc6TzPl4fQF8u3acQf0x5xwJO8EiU8CGhAxKupC+9OHm1pge2CsBgSnsq5mg8ivL0ckQSZi9A3q0zDDBKK6YES81i/TM1jRSZXq1mfff6de3fmzebI/066o1JIRKT7WnQc/PfofyFnlIT2pKnFn2FzsTACoMtVkH17raA41zRdo9aYQvMYKbqTpMrgRanz7aupO2Eii7dDEv16OQEcYtw83CZqGIXAnUSLeCGeEVEeHpSA9lZckgW6RlRpVHeipcWTLs0ZcenZiaLp1ArsLJogJkf/Z6dGLqFB8S8vOTkA7RHhKQDrCHbiAdUG8JoUM6LlUZ0sFrY/HK/k4ejji+9B9ByhgMKWOYp3ASo3lJpKVjpScxUOZY0UmMUiw/pT1fdO0XRNVriiFuvxS+oZ8u5jtQxNhyMtgEJYFn7NF558n6xo46kZZXyPrGRv/2ufZW8kjq5qnrMcRtOR0SPViTbXtsHdVmoFnWr10s7BXFE3h8f2aY1E9pJ58o+4bbXpJR6rpyFIxxwhGmp++NMueJxGehwI8S78lJv97aV6vLMXnkG7qb4oloM3OVhNS/rotl7pSGhERJ9EB1Cd4KD9/zGd73NE4I4N/wiY3Q9B/KdWD2i5CF5XWuYMhCyaCxSTnZ++/f60xASJtxSWWPeOdIobgbG+jpKGwVupGQhQk6RnVBNSouogr2WepfeGafk/12560n7XOkO/vcHNnniAhP6blTZXoyED1fVpmeZzE9qSnptBPIFeQXIaS+X6fnFz/ktw76VckvlP4gNb94BecX6cv+u5UT+Q+bGVZ6uHJi26C3XEd6+PR6eIT4Y2WEGLS3khHi1UEbsmdVeNIA/DRshYeRnl/oI8T3vd4rTrDertueBvmFk8zX6CeZG1fZPq8pf5JZOblHXWkXiE8yTwl2K887qyzPi+nyfMNvW14MrT9YoTw3cD1RBvsBYG1AWVn/alk6+UQZbGaGLQ0f8oO4FDFe7TiyjK175XP2QpN3TP63Ii2/iCOF95sXmNr7PMSz0SceX651O0QeWYGtM+g52WZMLBNLGyk8LiwUYqLH0/hTQ+EPnHoA/sBTPsEfaSRsGuLPOpI/j/3W5X1fZf40xPyJygqnQeq/UyD1EIZIkGg3JxY+rBtmySIh9Q/cQ6KpJ+rfsv1mHRA04//UitjkAPm9YOG9tJI+oPx7wUp6IPUb9+/VjHwvb/1iaUWI63tNd/debYovIXke9yQ90IKoh+jZWmV63kX0dCHpqYnoOURfke+WnvRlntCzqWycB/QY9PPzjpP0fECnpy6mJyKiiRIf3kL2uQRuTRj72w77NBfrUdDxA/u8o2cnU4rDUeDncI44HmdPzzbBkknTHwGRlhHiiUTY2zIu9D0Wfue9D9pfaiH3d8CF/DRjN5simNVL/Sl4gOzSzwv8Z23y8IQtJb+4TF9JZvkH+UVpz3LvJZ0kfFZ5L2Qe5ZOEbt7rdfp7NdLPzPvdw/fqan31yRMLFIikZH/cQCSL6vpaRj8diGTfhZ3p/ZT3XPspysr16Y7O9Po8xZ+Oouc7ZfR8h9dCvuMdP5b2Xo3Re31Z/r1AtNy8V0aT+zfu2IkVRSH6SXmpSrzhekKS8l51NO3xe3WlrSDcXNhA/474XpDWe76CEPIdg/9iD1YQztYstIF/D1NOfu6X5efLwhr6/ox0khnLD7SsA+3j8vaQ9AQj//UjOdKj8V+Ve5Y+cqkm5WeuZoYtwxoeu97DFZYjKlwR4uq/YMVeuEcrLFP4bYMaK/HGDTjRiu+xqorn+fxPI+MBwD7DUoLV3NDHznoLioTZRxf7sXAxtVGAryVbHLFetHGJ6ez2pfBHpvvamcyIFnI+CHIwpuZmFP8w6mA/Ml7VnC+79PjPicUuJ4IAVoD/3S7+M+/bXnI+CP0dAPPW5lKEmpI8tzFCDA1V2f5lzP39F6R+QWLLEefxkf1TzEldmyB5JSKUqMQR697CNw6CnkWaDqqpqqB7z7obkW1PH5H9kxyR7aexWCaTI7KXCjMMhcqILOzaB3q20kdkI/CIbEiIrO/ofdle2Qbz78E/GZ8vr+9wN7cCfT+F9H0Tqe9h+hF56Yq+r7N+hPX9Y7q+18Infrtax9DoaYvocZ6MdewpSNyd3LciesbQ6XnNQ3o6I3pGxZWjB2VU/4CeIYieOJKevvrBeX95SE9pzxauI47fTm9ohn87p/BzyX8hU594qm9nEyBAW9m3FrxCnliAlb4DHxL5YA7KBwtaySt9D2ydhrcP59NP7hV79S9OscbqC9zhjf+nxM/KSd0vHF/TT4w/Q/Z3xuYPDfJVTowr9bEK+jt9F772z+xhFecLKCf33NjD37A9TE0ZKr0XipfYK+fqmgOWHDNusy3V9xOcK0ezE2FTNLQy4SShnczfAxpuyH5gI95rrz479w/lJOHlndNx/n6eP0BbyWHxml2ciOJVWZ7HhYryDPHqS6Q8I0tn3OhenvvaqSsIrynyDCc6QJ6X8odp8lMTy3NyAHXEcZ0y4ghpmTTiaLDP92DEsZX//Ny/SDwtjDjmkPRMwyOOXlvPmOUTvycwnh/Z9bBpXFh1P52THi8zxM8wYuTN/er1PYnn75E2O/8wied3cJeL41zx/Eswnv8Uv0I4XuLE++2U8fyjdAtUA7ThsTuqgLdxPcnTnn6Sp0OV8TZldLwNqxXrLVT56YjkZ6UiP3AoGeTncyQ/uZR4HsnPaFJ+BiP5uVFefkCe3coPnHjZNkg+4Y98Hot4g8ERr5QdqjbCWz5xd+VcMV7BE80nOUrFegsKQ1jAbMHtOPaWr+X945gemFe4/aeFhY1Kd4u21Gz0ksvK9SUJ8AnaMReYsQxBT4ZupAAnouuFP9Ffhn97i1+raaKW64cA9RTrCbukET7XFZbeuRssjjNEv6BjTkr9tmEuK4GWOE8+rKHje88yBiEmerTre3UcKb5XqPJesFIcoqsK3iu78f0bBvK9xul75l1X3guW18N7raK/l6+mO3ov/1l33eEBFit4AKmfAniAJZR+HPIXYytdMaOs2HO7YoYRkgNGu65cj2tgwCvXe9gW6heX5w8gU93wZ37jPtkZZQR/pug75WUr/Hkucx7mzxd0/lTD/Pl10YT/bMV5BfgxtyvOU1NG0fjTR+EPfFqAMlbAn1mIPx/S+XOb5M9GOn+8NL1QvJG+7Cn5U+9iwp9+i/zpCQ/9aWlPmT/mjuLKftgd9Qbiz0cKf6SV/cAfK8mfAMSfsDKCnjn6F/Lu01f2H3THn3p9O7hbyVHxiocq1Oc/Kl9PqGTFgy/un04J7uQaryp47E7SSdQtJ4NlPPaz9sV5yVXGY/fxj8y9ReKxIzgLDe8n4rHv/fLhv6/3NkL6VYus90Y/yjC06ehpvfcprND9pDjSsiS9sv6ygo+a636e0Tve66mu1HTtf7W2vmwY0tUzvHHQPRMNvwr1zP1KPA8uH+J5qI+97hF+dWUHKh6SgtfKwvXMNvPec13pizIqrO/vIX3/QFnpC2vO4ewnrNij6Pu+4D7Z9Uh9X6ZvlHdH0fcr5+Zgff+Gru8Or8HFf1hDQsrRU3OouPLPhR7QlqU5AyujJ4tc+bca0fNAoQeWFgI937qnJwXlyyNp9Ix/GisIv9DXzbtF0lPhCsIpwcRKROifwkrECcpJ+EroYRA9M2grEWu4+nfXFcxu6DltTU0Z/ORKaODP+ygeG63ID9AD7/VEP1de2R+Ulv0ufSX0XvqKRjcroQ9b+y583t2JMhXtRNkkh6PKJ8puIv26GULEq8n0fm4oPlEWE/0urd89E/l3l/eS+t0L6O/1U6M+2WbyvaLQe92m97sp75Xn9R56L5jkdNKDlIgFIwPx/GjeVzNKrGfeb74ft3zArbVD9vkkOV/Zkg/1+lnEGz8cWIL7O+jLCZ9as31vt5DncwHTtrfgYuIlfodgI/HGn+ruMIOFbYNk/vjEbZH5Mw/xZ7TCHzjp1HLE2if5I8U/wB9/kj+b9T55fyvxT5X4s7j/B//en75K75/+5mH/NAHPO/hJ+Tv0yiDxg9Tbl58pDBLjDaj1wsp+mN8J5D8qrk+u7N8u9PKbIBAnmcdl+tb4+Ly8Akyad2BUK5gMcmX/QG2manSJd9dA15PMUPwGxJMvv1WYItIDvlQ6IVCH31PchKSnNtNAX4Ok50jmWf8mCj3KSd0VzPckPX21KaoNJckB5eQHRVh4XuYjRX4A8l6J/Iypkvy8enCmU34O0OVnvKhf/2xlZOeVqiSo/oP81PH57SZ/i7A/04paB73pwcrIOHzSqeOT8SqsvIlW4tU5bCN8wh8uK8EJ/1QP4tUxufeUeFU64Q/xakYAZYVcrK0A+dO3JXpsLbawY2rWM5+ezRpjkP/qp7zXmJpDsQxBvvOYzHfaNtiQzZH+Yp/+Qu5h5b0ce97H73USvRcl/7rpNR3lO6kpI2jys5guPx/S5Wcckp+sEor8MDT5OeJefn5H+U5TV/lx9V91Ff918DFnlE5w5ZD+y478F0OeiG5beMywV/FfSDax/Byi+6/Xkf86wacvqwp/6mverog/dRB/viT5sxXxJ9ND/qSmtHDFi56e/awZ5mW+KjwunWRGopgIvThYq9DGvqJgAtkviAnYYLn4kJDnl/zX5/q0lk+wQ7wK/YI73EX6SWaob5T27KCsXN+H8otmZuT3kH4ZJf2CwXLorgE+Khjp1zmafkXS9GuU//Dch8qKxvPFUVi/3kf6dY6kZ5zmgK3Iuv9W227yvHC7cni2O0q+DHh1KV+uQ8+XKfFPNIp/2nagnDSgyk8jHP/8OfGy5C8gr4AVV7DC51Pu2eoPxXlh5BjM0L+AfTI+3EYvJ34epfR4xdXaE0uTPkx7Nj9HWXGFHh6D5X/ga5QMYOT+BQw3gL+4xi8R7pMrru5qF6uaatOXtQmX51N2s8fPNDYDj/jCIfqOjLTfhr1rb4nzL429LO8vEi+xq46v5WA+dQWz0ErSLyMK6PAK5qN0vHEzTWDx31aGCZboWbTxN1ZqLmUU3/BpJdbnAZsAmOPWy+uYBvEDbG+L9d4Pov5C1nw8a/TdZHrHr092xj1MD6DxALgMl7nuqrJ0V1rKK/thlRPMmI1ltqga+RD0HNS+6viuOCa655N4EmDEnsIiP+d+G0hbAQ8A6zM0diqe5FTdMMswEk9yVb9DiufBXwDlEp6tKR1PwiL+jHD1F9I87Apkf4ZX2f5cfLZPdiRpf3boS3Jd7A/Mw4L9SaLbn3tek5D98Y5/50l6wH+50APTtrAkAfzXLPf0dKPTk+EhPTHRnvYrd9L7lSqy/jwmf2hQbY/6ldWFNvOo/FmH+DO4Qv64+vfPPOLPyYr4ExLyDi3eqIAeB0nPumc3ZNcl6fkO0XOFHm9Q6ZlefAL5r9dd42fnSbmjWr4HY1ZL+mUC2DiI+R7ui5Lbcv51FCa64JCekdFWf9/hzC+ehwYIMgNzkt652a7WrROYHpgrAzwt2OcDQg/mATlf0E13nDlf2tU6nMafTeX5I8VjwB9K/bkX4k96MYU/+bkXPeRPRESuu37KZHK+ch69fuhP77/H5k8LOqz0U8CVgDz3rqj/PirOM/5Q6/M6xJ98kj/b6Pw5TefPTSd/hrv2C/4ZPXpEzz6Snl0e0WPB9JT2LHfiV6ofjre9rx+j9JugfljBid92QWnZLYqoJ3730uuHp+n4jaPWbYOGVbGfIuUXFP6sa7ghO6KYgk+45zE+ITlg2L/v77yO6Hm++KngJdKXjaKdZO5Tvr/j2v+i1FenNO6THUXWe2foX/C4/zUgqAktX76N8p3GSr4z5a5dzpczyXzH6JVgGUDmO6MLMwzjlHwHWU4cr8bS49Uhui3MKR6Ftv/+va6i/PRzEt+yR3/Fw35cvDUqi5q/U/pNUv6e7FH+7qbf5CZ/f4jinyGV8Afsj6t+UfL3He75c9RD/rSZ9xToGYPoeb/K9Jyh1xNEekp7EnhayN2+LH9i3BVP+xMd30vB09Z0j6flaSfGAU8bEaH2sP91uEr9L9CvD619DA4P9+10/pMzy/v9jiUCHgnPy/ARumwRvzpzwgWTWObsEFaPO8APszvznXomqIBCHTGTycg5+Ze0ny1x+Dg7jB6YNvAjfAYEy/Pv0grmJcIw4Sh5Eqy7tqVqJhMRsa+SE4CwP6GSk4QjynwtfS9T9ydkk/sT3JwkzNXuYFL4kJCj9P0JH7vbn0BZmf0ZH2aZ+W/3J4grs5OG7nKH16r6idZlVdqPJPXf3exHOo33I00JludTUNzM+rd9ZIJAeb7tK58PvKT3MkJ/EDCjNof5UVOHM37+je28Mpx17NlvuhUQZnk9VzoxhfRrImtrMcK0xvuq4wVlPuWNNZuMcNTsjtBObdcT9CzV1C3zezQqzuS6X0vCz0cX+uh7Mc79AC1cThaNyIsl9b0zypd/IfVd0K93d7JITzuJEWFLsXa1VlZfdY0PK6ivdrZR6qtXaPXV0xXVVz9rdoA+jz9N85A8sTmLPo9/Gtmf/fQTm5R5fDixeYE2bw77sSMi+rju04N5c/T8xkL0Xnplnx7MmwNkOJd+UmV+PV/LrUeVnVRR5s2pJ1VmaCbbjqH89GeTS/8U2U8YzQ715QNVfdTOfYy9TOIa75+Mf3Nvls4h9wnncv2rFYn7hDNLTWb0DXA/5f1rZ/1zUuX5SvS3MX9sQn+mAZkPhunmqXVlUVkEfhU+C5zoeKfKJzpS6PjVRv6LaSc6htBPdMzWfGq7aU3XNXE9WQ0wRsAt+vIpQpxID9TFQJZhHeczvKW4Jtlvasws1QcIxMnqtdei/N9UTlYr9cwFzAdkv2mENlZ1vSQi4m1afWND+f6FVE9wo19lQVXpX7jWN6j6NQnp19Vu11xPdFD2r8KJDtf9q4M82L86LWgeuX/Vt6L9qzHR5ea7pX7BUttcKT917ee6me8+jfjzfYXz3eX7BW7mu8cXH7Eu3N/KtR4u+fd8frjGpvgv2Ocp4QGqV7kefurxMUPNDnJ+oZygoOYXL+J6eGpKyn92shr2EdmU/QAKPRXsI9o2qL7ryVgAzUIgeIT/XROpluMf6FfCl1dxPzrqk/je3Q83WDafJuTnXM7b9TeFyvsllPxrq/ADLf86zjQTYqI9yd/d1DdWony5N62+cU+Kn5+M593kFyeswx4to+0Xddm3DPGzdALHzX7R18ufSJTkZ19BhqF6p6ruWwb8ajbvHT/IFf8s4Vfftk3ST1Pw6pC/w1O6qbc8NqRlB9DrLfvo+Tul3lLi1b34EIo33O4jWk/y52M6/jm/KNKSdrGyfUQSXqLCE+OlPWW8OsQbEl79gbIPH+rhzn1N+ORVQ1Kea+VtsHinEPSE5Fyv3zGMqu9UPLZ44vexu/r8aPJ+AdTnv61yfT44PzxogFKfV/YbV1CfDwlZ7e5k4yb6/nDKyerTXJjl9FVCnlsVPDB82Il6svoU7UQQnGzsan3TdT5Xmo8Ls43Tz1b2XUjzeqtQPJZJyvPnSJ7jCinyXG5/pus8WiopzxpN++KjSN/Pueq75E8r2BfXkORPMrLPyaR9noTsc24nz/bFhYS4PeFmJffPz1P2Vbrunz+YH2lJSq1s/7y0nySHLs8GLM8MM9k1PoREC5SpddlL3kt00glAE5SAgXWdhV5lzv3YsMYAFqkD9O7X0tocysg1YnRrRH+UAFczbNxYpky874BsP+SDRt2iQDZH8FXZtM59wrfl+w631e14W2lMdLVu8r73jtARxfL8K99TY1XL8gyrtiGMHYTkuZ4YH0J0giIaFAh2MX3rnXHXchPTM2LtCVN+rC4JlpwMKb1WJ7qtFM+HoYA3QYyfqXgbvXcy1vcl7uYdqn6CtDUTaWlCngSr/SjD8FXHqs47SPuo5X2eJYN2yvMyN4vG6VswznmirETYTwv4w5yyQ3n1xf4yEhBIW1kUsJhee2ZDdpJVin9wPH92+1JTjm9O3jstZP2CeZmsAansfOQvBpL69aLmvWJzbkgI9d7EE/vMq3Bv4lUyv+ha/t5EJfvMp2i+st2zbhvU23UeH70Zrq9eLVTrDUq+A/gNwPMX0fcnjED54FEyHzyj7E94Er/h5iRqkjVpaJGH/mIP/T7RC6S/uJDXOiimvL+o4D6R6C+2DRroKj+IEWYQRZVtiH6TIOMlYB81hLLbEH/O0vcbv03a55/0R3K3K3iJPn6LsX1+iz+hziTfy6CpUZxgDY+Nr2J9rIKTcsN5lJ9W+aRchfWxiIgIKT8F9B6K4SA/De3B5zB7RHokLDbAosdyr5Vul/u5oXAkHcaba6ofqR3iSW+ULJnG1BzKjgttlBT0qNUzB593xs9FLifYGSaMzN9H68Yy35adbmcxK/WxMNgrALxtyrf1/VXjPOFfaEJm1QTwypbcOPVEUd+hUnHl3CE2YMmopAHpM6ztlP2iyKjCr7BrzNjS97RO/uwMhX3C2H8JIwV7KbFfNE7TTtVAE3TvBXd4pGw6HqlBled3nsAjKfXVCvBIj1bvdreP8ZIyf6HUM6c7mlf5xOYT9UxlPxt1P0ka3kedmvKGpF8Nh3/LBrVriMRxu9Fa9Ia0TwbRgh6lmwnWIoJ+/UbqVyDSr2akfv1aXr9gBfzSnAtsT/4U7f5OY40Xin/Sl5WjB+bx57DfGG8V9dF/K9KDYh829yOzCdYQ7qbT83d9t/TsUuiJqvcppieUTk8TTYntqDU5oFz/C/B1In7V6BF+lYqvG6DgV8E+S/jVycg+XyDpGa+JsxVYS3u+ocw3fcu2PdDQ3PbAVuNfiD/fi/y53lSHhQTKihXwx/a4Mv5895XInxcRf+6S9LTUPEL8iYh4CvveFysnbF3jjQv5Dwznq7zvfQHe984wbyj1+V0srL+EQwWni7pL/EEajH8ohGo/0vlzpFL+wIdBCQHmT2t3/HmI+dPctX4Ity8AQePLZwsXRPmBWANqUTAe78+XFtvKXPd54vrhHWGS/jWyfph7bbv/fbG+CsVrZR5kATOerB9O0m5SlZZ4xw8Id9kvCvhVFIWK9x0ECc/PDh8XagIxB/4k0PkTWFgZf643XYb5E0znTzvNHcSfNvMGuN6bePPws2boe/yK6Dks0oNyQRwkQ5jmhp5PET13Kn2v/FiRniA+lbavoL0m28ZaUb5slveTNML9QYjlvuJb+lz1cu4btJj6j6kJ+MOE57hhzDcOZzz/biIgcGGrybr8B3d+PIXpgSUAAPQEBMGr6o6aD+tI8U+oVA+3C70FLbnf5lVNU1V1dUjIgHAXvFZmqcifvUVGPSvyB9kdFu6nAJmH6fzZ6J4/Xyv8gdX9wJ+aiD+5JH86aTJt8dYvHbku/j0BdB0UaTUfJ/Gn3fVb+CQPsomJL3MXmIbSfZAm0PuCjhmbkR1/5/uXMT2w9ANAoTB0o/dKYD6oJdmfUMjWgD/tmMHCUjtBTwNNDdXn6tt1VZL9gVt8EIvBZ/mG36Q9L9Jzdvvv+AQg4EWbcflcYZlzP1IfE3AU1skdUzezdhbjMSgSwupsmFBfxKX77Gji3I99OxTZIBxvTBWmCit4gp7quhqqbOGzZntd/bvrPnyKf59J9+9u9sXNL78PX8mXqf5dnK/sau0vyc/qybHIcTYywyfersgPrLyEXXrggkB+fqHLz2HyhP8T8gMuDfDq1ZH8PCblp7PmvC3ROipOpgcyPKRfZgCybCzqpP9dkO6jsYCfB/4cQ/T8TNIzik5PvH6/Kz1dflmB6VHR6TFpTttgf4tMD3T3GSbYDHn/ckRPiiDNE0GQjPuDFdCzukJ64B+/3nklpsfGUekxa07aEqyL+zdzNz9Yiz5/kU/ika7Q+wW1Co8ZkhU8EvreWH4S6PHqa3j+YtZVtyfY46p8gv1t5N/fIvs798r3d6p0gv1qN4drfuqKJ/HkHquvpTOZnx7LPWbY5+E91jbzvJ/qfLdrfazvQ5WhWSiBb5ngbr8x1MeisvTu7n+Npt//otwXnlEaZpl3iXqi/jB5/2sYnR4tvv+VmpIi3Zd537iKhdoqCO4MPsNrlGifn8s8gveHQ37xMzfK0cJOzHsG8Rb1WnHeE+78AXAElqI/Y6+ufVDdqV8pYXDmDsCew5hM2n2ZUM1m4Rp/ut0JyX9B3AP+HQorW7mA6t9rnXg2xgxROny0+tx0r9ocsY+Iu9g9/21yH1E+l1y8kJfjVfjB2H8JCwVBui/sJe8jCtENUrXUbhvUT3ovmBDa91pjMzTbRxa11GeJ9gf5UvbD2i+YoCVyHtmfONL++Nb3tSyo1P7sTl6N7c8l7iINr9VPE2tLQvlOP6V/8T3beWVjMzRyBhU10d8RnPtXA/FZXWhhuaGnAaJnYKX0xPf+DM+nXKDTM1izHdGD/qJED/wEmJcBme6j0NN6eR3WT93aBGVpoOdbj+jZoeznl+ZlkrnLahVZH3tL8xWKD1NT5HkZmIB533gGg8XeKl7lU08r3QsA3TIBj25xowv/FukJzTrPGn2HoE+w3VStVlp2TbGeiZw4CrrW4QrWZxqVV3wLGT8Ps0qatz9nezCZqj2+BD0dtO/Yw4pKe8r86bE6jk3r18QMPqNTUQP9Y0HKL2DpIr5xfknhj2v98EE9X0sPkj9J5fmDaMH8OYj4oyP5M0KzFvEnKqul63wTxBsQH14prKGvLeY7MOYLN5ghDGlsf6FgB0mPtnaYpUYukS9v8W+fW7u1vK8S6gkgz9n0+SYN3oe2bZAn80Q6+jzR1ac3T9RmXl+JHuSoUL78nBlqiHWKAvWMSA8sUW93vakJPmIWHf9zBr1X/UrfKzRrLcb/bOeu0/BakZqFtuPWXxfV+2f7M13nhcOrZd0Mv0PEG+uKwoPaebA/E+aFkwOMHu6D3e3RPthTdDybjrYPdrLtTxSvNlHqUbeQPAv4+HMzW7rPdbVzfnCJEea/IEb8ypFcYBX5k1nKoqSmK/vLHwdNFwMiLb1FeQZkDoq0oVFkmuLzbVmYgveDAi3o8H6ht9qrBkHPG5q9pc8URER87Q4PeVT078iNlNtfF1bl/XUrytcPXe8PUt7rB4yH/KzZYnf3Gaveb/qY2WBZTPab2j/KMKz0cP/P1k7fmpX9dbA4D+4WGtO5r3yaa539nWwcb8Cx98+4IqaHSM+8+7qkjyMT8L2kVzKWPrzTqty9ElhGO4JLKjvEO+cZ49AP9sL54EjhlPCRnVIPn8BcVm9L00nxD/tNDFw0xfWEOfyvXkdE+VlnTcD7dkD1fPi+Dq2EF8UVAmf8c1mKf6SwCOB3Vxw7uCJBrs9DKIL+iO2BCSHoua6ujtLWqKzerv3T775qiu3z7UIf/TPKfsg3Dz+L65me4Q/PlMcf7i0Q8YcfIftTn4YXHY38u3fXt8wu9V7AasFHC+RHMhNF/sAkqXTvZi13qORYqYyvg4oXdAE6qHpVqyHuT3j14DNmaOSPC30vafidrgHeRlm/ALcH7xUldGDOkP2Lt3XrGXvpZ83c7oc8Tt8P2emf7oeU9ktUuB9y1tUf3OHDs6uMDzeU+Vo6/lt8+H2MD08OKNevhHo4FOYuFKr1wcr+cOhXQv/0X/UrXevh9d3dm2CYXq74Z+jnwr9NLLT7Pa/gn6HGCv7Czf55M6JnZaX755V9p9T984s1vZF/HxXnX4V74pXkX1xJmIXLoOZflHviQ+n2kHHmX0/pHnTpJeo96MMe3oOeEvxSuKxfP2D7A42K7wr76GeL7wVDXmB/YAVCPfs62r2ts/R7Wx/4h0v7lp+0PycCKPHqaZsNyc9TuKdwi76f/zn9pLzT5H7+Dyraz+8d3851vwR6MzM0tuOVe2QAioD75hAfVu0embQf4Cv/lq73yFDagfnzGT1+7qe5Y3tsjYgwuN7fgV4cGGM//oB2npcTTxuL7++AWTrGPXC8o/h3iA8hFap3f4OlRjKmB3k6M8qwk2BK4nfr9LoxXZzx4ckw8Nd1r5xLnMBkC2so9y90a5jBQkx0M4mes9t/Z9eeCMT7uncV3vU9KN+nPgr7cqGnG27vXvCdGI9BbR6JFbs7+azpi1oWS1Nx/wZkayi1Z6EZmFA9u+CQuK8AnB84Htiiv4r/QR1C8ueC1+Pi4NxRca+6yy88u3/xCc3+7KDfv3CbX5ywhoR8767+fI1WfybusYL/eqPU1zKy0nusyj2pCvb7RURUxh/X/Mtz/uyl3ydyy59ZV7lK6odP3n+n2MMa5euHEn8W5MYZSpT6YSXzaO11Z5maQlTWU9l34UvLT9M9zk9PWMNjH3mI/6n6Pof2+UODnif3OVSIF/WO7+vqL27/2QTny41RvlwqyP4CqoJQMsmi1zeqli9DKQbqG3HIHlLy5bGaT22J1pjoI8o9xFIjDOlArW8Dt776H2J+ERGhM8+cUMsEpcgMh1bjnC9AjjOpV3Y8zi82pPnkfUrWD+O4P0qm8S74FmmfzEhhilQ/XNJVilejdIdUW7SpKfI+mYy5e9g+fk3wPpmiwiH6Vxi53w31H8i/dPabeRkkf76t42u5RO6TSfZncnWtZTyAUv+h7iNqo6lRnI3in1au/aaV4cH4vZiiTtJ8U8eR8Yn3m7fH+PAge1p+EklPSKCvpU8eQc9xf5/caq3lfTLQr4T6Tybdf2nx/QuGyXcnz9R9DtR7Cm72OXyaPy3ocifP7inMuuoWXzeC3r9wg68LIuk5kdc6aKeH+LpHq2+46+/sUPo7Uv4O/Z2xZP5egPhTX+zv/D/mvjwuqrIN+8zKjoqiNWhoLrng1mCmwiCWuZXmi5aYuWTxGoa55JZpua+VC+5avqZhvZRiZS4wqBligoqC5pLCpCniMIAwA8ycM99znzNnwec5MCO+3/f1+/WPv4S759zPc2/XfV1Se4pKlodMFM9H1Lshznde0J6g7AxFvVz/ft0PzSJMHfH38BZ6D38kv4ey+Xx00h9y+zK0iMfm8c+Axybg/Vo7401db2B4bNAD8unp7r5MXxaPPT75Gf58hr6z1giYVyhusiv3+kz3cvE1wZgxyABrYT8ypVX3eDztXSMM2gHVQ5UU5v/J7RfAdBz9UiNssbV3JPpP6Czh51cdW3x8sDGWClekqjB7pmhL6LP2a32JeqMa5D9/kfRGdzk6k/VGVThefWdJp5B0kt6oDF4d9EZjy/6v98cocn/sJ7Y/pte/VIc/8/kh788EfcYNT8afh7Hziyx+3/OVQz+x/JnA05NKJzldegHQS4CSHtqRTzFXbEtq7ntC+Pma+dA3VSHgkfh9z2dupAUOPsfricO5s/4cTu2mNuF4pGBthuJAZVLASg/3QWbg/vMlE2Gafx3rH84ova97VcSPiftNC8j7TaDXn521Q85/Don9H+jX8f4TjfvPVPK+OfgP5XZ/dR/rP73N/Uj+863H/qN+Mv4zPlnGHnv97bkdsK34Fw/tiYtz155a9E//7bE9RP1T7n7dlsZ3Pp7qRP5eiKc8/zzocczB4/saFE//Q9bjGCXGU9GfifG0OxtPE1r2q78+rMz53PfwfKBftyumhn7u4+uxEvRzHf6rLPs90GNtZ7uM8nlP9HO9n5R+rmw/MyNI6G8cHZRl1Osbs/ZcLZ/na6X4eVMf4LOCzHiSvUvpVq6/Ad18yOBe7XnG8EejVNMSrr8x2xiKDqGREZYbXvLTPIzj+htABoreRDb0pzPfKPMbYfb8qepeGV+MDJDbr9zs9n7l5xXxpgNu71d2rW2/ctHQkX0F/NhzknjxMSleLKA/c0zH44W/MtH0Ao6PavfwuG5bODFenCbpsSZTN5iQe4EkvBbsd8vwvSs4e34cwM1PAWq72j/99t5CwR4+/3nW9mHI0m7C/FTkS5Hhe4d8PjuroZz+xWyS/gWx3vnOFm/6rk79C5G/rhb9i4wgz+7XCMtX+P0ahu4Xg98vi0f3ax57v3KX9X3UHvgwO8uVAS57YM3RDXuu1t+et6ynzemjNkr5SUR94Xj1t2K/DvJnTl9vquNN/HvtrfI1GfF+XQNUXyzuienrBZP1ODZoklj+MdnziX6c85HO38vR+cjwyTQizQfhfMLmRnlgjy+y52vcnp5y9qz3yJ4JyJ5dMZ768/82XvQ2e8r/87Xb/D/VHp9Pljms6u0oib4n7HrCf9CGWU99wb2HsLsDbg6I73m0pXIfN8+Ff1BxkoZelrQKxXLtn+UuPHYFsM8AdVJ64yJ94/7hQvzi+bUWOHXURnyeO0Y7g+pXHRfn7vnAfNDfY36kE+Tz8SXhSYAfKTtrjJt8Dny9Q+BzuK1INAWS4lceH7+kfA5dyXwOK9h6Jy6uHX8+gH4A/QtopE4u/9jvfX4etz0V9nMBuvCcPaE0xy7g6yAfU79xzhDVyGTKKWLtgc2IhLv2NFi2mOo/v6RbR2Ge0uTHAYZmV88ZB6N8bGkQId/4zlZg3nAr0oPv1Rh9LwL+x/9Jfa8L5rLVB/o+wudQK3/UZ6T5e3O7r6kzmT+qsCeBz5zIH1XO8kdt20o8Hwk+qub5vCt3PmtJ+Kj1HuOjdsV4gtf639sTNvcJ6C/L6K33DHjXcsEjvfVL5gUpuvrrcSi8Vv5d/Dd239+sCA6Z7YEeRxK677nLPNVbP+A2vs7nMfghh4X0k94vUY8snt8vqJn/zHT8y209spdq6guL+wXE/OcSO69MaCm8h8WfpLP8dWDPgvJBfgspV306MxWesoM7LZGd7ONKj3PfC5B7AN0su5jNvocl3HsInVhYTAK+gh7+90p8xPcQhTQD+q+N45nDyg/x87msOm4rM1MUkc9zvRyf52Q5Ps/VdfJ5SvX6id9rDsvnyXg4Pz1Mnp+2wd/DicXJOk0vz+ancXGB9d936FAVYWpX574Dj7eJrQ1vM2TB7PrrNw1E8d1A1m/y7uGZftO2rYPq0O8G/Biv3w37uRM80u9OFO+XON8h6ncb2fil1/eR4sd4fr8t5c2l/gyoDIA0NkP+fNBtfw4OXFR8nuzPNpI/L7BeM49P7i1nz1sins1ze2BeqfPInlnInpvofhHt2Ui2B/gPj3hkjwz/4UN5e/7h83loPIHvwHAglknx6aV23S+zgbNnZtoL9GXFKlroR6EbbNzw1MvpX+V9WjQ8zHW/ktJynr2eBg9gheJ+9ffeAl8u7NtC/GpLxToXV7v4dt6T7MMGKzargOD9Ef0vSFB9mR+ccygXf28jQf+rGXPU9gzOx9iFmhzgZLB9atv1fYH3RD5GXr+7glpEbSfpf51QfF+ZERRQf3xdFnp/ztUXX+fnwtf1JvNnyvrPUbf9x3P+zJsoPyTq0W8U9ejd4PN8gnr02Vkv8vYc3Llfoo/fQaqPDyNVXh8/9UnYc49kz5fWu+akgEI5vYlPaup3g//AvGAl7j8D5fW73xHnBUClAv7cSw4PAPrductqnA/gaZ/Y+XSVOx+T/PlU9XfXHsAbgz2/eWDP9OIbZHtuk/iawB6KkrXHVS9DE/7x7Akn2zNBzp6NrD3H+fcQ9qgB5w69kT20n99mDo+0MprbZ4Sn9Wl6sqo1vs9ovdi5pC+OR7pPZ9jmiPuMsIkAPyTKucCpqSLsMw5StNEMC/lXHf35mnwgn5H4/V4k9+ch39gbTuT3y8L9+RuWD0SvL5K7X7Nx/A/cry8I+Hl0v9ri98tSsjwkQbxfvB60obb7FRf3gpR/rA79bhn+MRk9hf6Pod/dLl2G732pB3zvMH/fVV++91CWzwqFXpL++xuiPgiwV4D+O+j5LifrgwS0GlwwEtcHmRfQzmJyW/9dqR5qy0LxS0a/8v8R/092Fqb394g9AHKW2uO+3t+Imnp/ddpzENmTu4yKlqkHh7tdDyrJ9aDTvEQ3x6N6MNgZNlcv3a8EPj3Aomwvf4nfL4AiHfZTALrZ0r6OdD5nyecTH/ivYjOJT+8v5R9BBLyo0VqG8udnRLz6UiPQ/UOx7l+V5rOWw2vBmib8FnhRUpivq6tolz1Fxp4rF8KLZdhQNLjg1UzWHsDvoH+N0Ge9W700YEAXAa8FCB10yMYRVBtFsRLH92pfZpY7Qu5NkdvXc78+3YDq0414fUqj+vSa2/rCCRqOXxT7XrAP8sj36nywBfu9nqrP90Lxkd13mCX/vazIn4X9bsC6ttWeYBcJltj+4/2Rhu+vGmBoC5hjf8Ze7sd9L3aT/dm3jOjVMlANEwvCufk7BHE4NtAHOaYarFZ3EPa7IYEae3Ql+l4Ziqs+mD3jNd/a1dbeZl8Sv0Qoud8io5+ypTrCdOIKVl9cKlLo1vUh6KcQv1crjl9inDpKwg8AtEZAhOSkuzpdeBvgJgG+QZASeIqJtPnZBT4rXi/gOpPj509h+stR1zs3OHBeiF8iPmo91VRD4MO/rGhROT75ean/8PtEu2ruE0n9x/19oqmBg6X7RFL/+R33n7fVp5D/rGl7UQ4PeVfEQwJ+jMdDtsfvVwQTb+qF4yFXlwSHZIp4SHFfrxb+3ns/h8j1nyPE/jNQGPD95wzue8Ev5e0J1g7+uw3ef+5R4dR94VH/+QbjdXSAdH7K16eHy+38Pgi0qaAerGVfr6Fb+3pifUrc11vJ4nsDP3L2rXf8kulnGoq36MI8jF/jk4V9K/Q0GuGaAh9INq3WXlC59gu+BUR8JDwhF2inY5boP+jGwKDUMPJeqsn7d9aefuM1UagCSIeltjeLbzRV9XL5cy7weaaB6G0sZXUuJuAPtXOoic5umzL5+w6AUKgv4O9+Qnfzq6ipn4v+OC2A3qs67cDqi06XppRsx+sLB51j284I8y/wIbjvBcxi50Vh30GoL0ZoZyj6a3qb46T4MXS5WfyYj3VOwPciXzf05yHV/0/1ZMtdMT+EUAL+Y2ldmL8Ax48Z/fdbVoj4saDFHH7sPfJ8p426pe0aqr92RQl6E3+lQhwGYsocOt97FB8v7sFvALdK+4B+WeHSLwCS53Vmbt+83eVPi051wvbNI+h59muM675vgF/cm+2PodveDd83X6lNpbxUqp33eXtgUAG+DO/hJ0wnnxKVa75zl01BYN0ukh6qmEa73uclRvRRgIEmPedPqnBBV9YeGCIDsAmA738q36YP+wv9OvAfsGcQNcLpy9kDMgv8+TRSaxSNVQkt/3f6X8vNb+tue6j/ldCyi5RPpjKmdRS8iVnlb/L1O/DtAP8GPJNq+1bLBXL+TNivPBTYqFjRSeC3GX9nLRsvdtAXlb8GEfj9KlH+nBHUXcrf0mJ0myjwn/0ofk0V+CGBJg349Nzc9+Tj1+rAXsXV4n4Trwe0EMUvwr7MSHWe1YbqiwdRIh5A8J8lTJH3LZWrf3iH1YIGf46kGyhe4/wHuG30+p+Mk9YFpPe5ceSu7XnWHijSn1a/AVTnkY1VVkbTAPOfl5H/DCH5j6/ikjIu7pzc/oX7fPiZ8nz4Ng/58H9ZOMUgzN+nsfkzNFLjmWzlQO584LPDkwTtmNF0J3tQNc9ndZTncxjNxGn2cHyeDUf1Qg6YZoxPbZJ+4zZKek+43sOfBX6Jic7TzhgFdt8XaS8qsxzZWd2k/gN6UkCktV/cF358/1mL/Mfmgf9cR/4TFzer/vOvV57c/OuXhQPrmH9B/sPPv2C+PMaj+ddKj+ZfWSj/CeW/F0RH9LyyyzpOm7fPAk6/ILn5aANoGMCX+IDxsX3K3a+/9143Vi+IN0IW2tSnMD/5jks/7jsDfHhgCDNRz3i/11HYj4PLFJ/6kXEitVwR6YXZ85dmm+PTym6bVvD3HQI4JBXQmDvP+Ginq1z8kFmsPhGEoKb0IGa23YVfLUiD+DVj0jqjsmJn6ZvnhfgFnc9vt59KzXAE0n8zAt8p/BH482nnMGcbBvPnPE0vxWlnzwvfRQr113pWjwzyw+nM7ypfzp7R7x5j9Vghtf6LHunYaq+NLwUI0VH0TYWt8CWOcMX7Gp7Pk923AqhSDlXiJPClrFENch5kcpfVdb/gEoFeG6RGnt6v7qT7tZy8zzgC3a+H5oSWHaV8lcCfCfHifvmz/H4lRGzg14IZWCt7UOl/8fx5WpMI03vFWPxKCWxV3KCTUJ/Cplgt+5VqFt+SsGtelNCvGwv9DTjuiP2MSVms5Pm+DMBtDHxfbegX7G2EfaI+6KlE+caEtEz67aqB+TwfGhDGow8zz7iWLvJmvAX9C5G/Zb3zZfw97ITe5z0OiupG4k/4GedPcP97PR5/wgh1AfpevyxsL4cPd5D1vxT4+3OTzOd5Eb0/5Xp38eEvsPzzFCW775nk9r5nqIO472mvue/J441r2fe0ovvVJPqR/S++Xk4W80N4n/n9gil4ftivPN4Uk4P1N/5dZHn6YR/i+/wrSZ8R5qcfXdtZx/7Xo/uDhP2vyCfHr1W2utLDfWECvuU+eV841uLUNfOQ7xQ9IdESPQVowkPg3MmUqHeI+w4wlocW+5f0UUdrUd+KP5+TRYmmpMwa+RjY8/wD21Mv9HHho1az/QQ4n53UD87dhPiO7ntXp15fgy9l4UbuvhvF+w78kMjVWb4Uf4/u+170HjrF+44eVPa+r5PjS3lgLUf1YMvH49OT9lsYlclUgOuJ/1Sep3tGj/Hp7Sbf9wnaHSjfiC07JM1/+PtewXzM6/2B/4h6JWsdjQh6JXSEadY1bL5zyJKn+w3XK8mhiPsyvlrYl7nWd0kd+kRw36V8cQT8M0XFm0pxPTtraZ7ujIf6RBRVgz9zzJfPsvVgx4rmPL8EiPqhcFgXv0Td/JnNrnL8CSlk/syJ6pXWNPOumM6i3tZ3rD0QM/5B9akLHwX82NB7Bv5Vtd1I4nM40jTC1KCUyJ+g7CTwY/N8F0moPiX0N15Uq2yFKJ//lo/v6FxA+BB4FyLP0gnegVx/I6TrXyw2HLKsJDqVGsnZgxxX4NPLzlWaP6vZ/4Hi8kN6YvVeRsr/w8b3OSh7TsH7G4O1vagflHr9dun7LO7LjFOn4Pu581E8fQV/n4+g9/kc/j5/i95ns4jHFvVGie/zN6x+SkbQE+IXfb6+/KKL2X6mXn8pSpxfsP060DIbQw/y66x14W3UURC/kD1pCvoP1VLOHnQQ6a2vHzEyuSvSp1+aVVLZsUY+D0vi0cxD2ztO4f2BGhXOZzezwpki8BtH8PpofbWbFa9rKCpMyvcO/MZw5/0r3gxoRQl6kcCVC2NwP3t4yVX8fGY19TVNx/lJzgZWmlWdhHku8BuDP58lv89Ps/06r6OdpPwkbbWcPQ0rXuf1tuCnQzUFqayffXjJZdyeYGTPa7g9OTXtQYfg4jcm2hPE7p9mZ5U/Gb0tAt9OgaVTyAqcD2REbXwgd5o1kuOf15L2Gac67HZhnxH6zzAaqw7se6fLA2yfMcVaFFIq7jPyeiUnyPGrL8oPNc6wudj3Apsao+/l4hMGP0apCKtP5GefUnKJ/L2oWr8XPKbTIlfV/b2GhXgbhPprEtuPgg8Tx1SrnubwkOhasPUOjJ1j6aUOfTXGZ96WaaTaw9WnFHUcqn0j1Kfjysy+k0KFfi/McwEqOQxlz1acz/ySZhLVA+U/Nc4HFaLs+QRUDObrQWjxw/lAvRxkX19yET+fO8G+pmuW2u4X9LVBvwDO5zL5fPzUYaw/PyH+lnq/hxx/S2zZMYPQj/rGWE7nRrK87HQG1ZHzZ9Dph5APq2qltKZqJq5vHsD816cY57sYfuNQoO85YV6AXN2l5zKJmozvo/XVDlIer6Ko9lL8GOhtwdlOKZ/irxfwbGmg5wL7cW3se0rDufMBdnj+fM43SjW1fYDhWw4HVBbf6ijsx1UviHfpTRDje4lqhC0TxYvr0n6dVL87VeyvSvW7h5L1u/+4iuXzeSWjQr4Q60Gx3qlF32HDLWH/HV0iY6RvM/Z8Pi9/ym+LcD6psL8DOXRP+/DSX7n3B9jBOh9swepFftTIZNLw8/dgYOeBRMFQ5TeutEDk9+sxtrcBduxnMgeVI/HzuaS6YvMqzs6SrU8PkuvT9/H3ueBhvMl6oa76VLqfS3if7Wx9GheHzS/gm51B9Y5rfgH8/LDaD/mqr0f1zoHAp0nzi01y84sya6k58KPl9denDnXGm57B8/m1pfc90qeGfcZ7P/eR8uWK9ft7vD/X5G+ZytfvbuwTDXt4XDc7nFi/E/R3itl9ol0xHaT5POg3wdt1rLzY35VvgAwLcIcDtWYb+7jSpfh9f7lxvCnWjPUPpwWOLm7YyaVXG8LyXdTCh+9URdrOo3w+Tq7+WkOuvwj9+VRFointJnY+uod5uuRwd+uv2Wz9VdV/DH8+3sk7jA+Gc3r9K6xLA0Zz9ReqLWCCxGqkzaseYykX57m83roudHABykAffQ93BlCW66LeeqsD01m8XzpZb/2earLtd1R/KTyYVy6Qn1fG4PPKk+Zput1uzys5PEDusvZS/sNDD1tEwYdZWb7Pvx3Pd/pyGug3wZpjB/um0jdw/xkRlGra+EDwH/58mgSmFDMdeXsiXzk0g/WfIjK/H6MaaMsyb9u68MnwvS/H+d6jH4PvvWz1Lg/5unuS+b6C8XownszXLcP3dYTl6/Y6+px0X+/T+OZRcD7jyof69xL6z2kQeoIWH2fj+3P490pE8d1ehPnz0oBQyzkxvoOEAK9v9SspvsfaTqH4LtgzP+oXlm8HAkNsucq/P7/PWJEK6DRQ6mmJ/EdR054+t84b3kLxNEW0B5gt4f1pHrDIskXcZ8x59i0WL9GUOa08iNtjUk1F9yt9VJoUH14H3vh9lG8E4P5TzMSb8nG88d8W5D9u441baVPQ+5M+6hdSf6yamcn3x+C+i/2xVY5mBH5slP9YrmL2JCH/kfTHxPnyYlJ/TKNNoi4z8ap1fP0O/TReX68/s9lrk9qFh7yBap1S+OPUgXSR8xiX/zC5h40wSO43vn/6G3cn3C+MxPAkbegW1fdFvA16WFk8f6xzhXOVA8tXI7UNFIsV2Vlhcvq5D8j6uQ3J+rmE+cX3KJ42F+Mpfz7XyfVgO3Z+oddvIM9z4+uY50q/185qX9O6K9j7A3yMI3C+FJl57ufsPLe3WdgXPj3kV4hI7P16s/yK3xChPk0FEmxox4TaV5SW2mvUOx3GnGf3hV33C95n6IjA/brhn22ZJd6vcnoEG7/aofuVhN+vAtVC21mz11G/+uNFe1dHmP6N40VPoXx1t9t40WDXPprh/yM+B4hfKdJ9c74/XwufA+G+b0bx/Wsyn8Nlt/kcqth9WNXO7/n7DpNQFguJvlk+vdG7RO3C899kd82hvNxB51NLOHtApJLvry7LnWD+GO+vfkbbqj6X6pVw89Mt6PVZjfdXu2l7gV5JjFB/vdrzjLHg4yZsvnGiPMX3ksA/drTZ1aHsTv4Ie4/SHZw/wzYLrK6AItYPyJ+HcfkGbCKAwiSINc33m1K2RuQfQ+eOHtVM4x5mnzIA9+c8VXBlf1R/teHtAQUtx3eNWLxoVXl/32e47wWuCBrnAKP4xP5c6XrOHoi+kKE0+fG04S6KpwceuPAArQH9ZgRwn9P3vw97ifbAUgCU9leZLcoDOB/aDVVM5fbiqv6CPZ2WXzaq3whk5+8RFfk+cxX8/D0C8lX4cT+K9gC2Dlx9w1OnDANQPhZmdr3PXWAyxRK5TvMNrbjfXsjHINQCB0Ggc4UyHLfngWp7pbdlw60JvD3v9vna2GOsLgoaGX2scwJWcvkzRGvgw4e2/RfV71qK8X2Z+60K85U438W4gP6WfHFfJuHuPPb9WcUcJvUTfNVQX3gdbc3bY21/A3mDL6vXtqTiE59bAr9o5DsNRxlQuWgos0eU7uXOB15PdBjowxw3bAhKNH3OnQ9kSiA8EJ/6keGazynrXu58QBwCQMvQsR7onKvc0hCzR6W2VK63hM0V7EEXyQjPGYDTkyuG+rRQ8vs7rD2AudE5hpceEOMpN8FLM+xG9hzh7IGXHGSdrnwz1bDE5zvbCtEeAOX+nHnI+I5zivIl3J5m6pCqQgu6bNH/K7xx9+Itulc9xBuXrc6U8q/y+LpqZhWfjz3Kb0zIx4ah+n00zm/cGcXTLiK/sZiP1cJvrNcL3+vHAQVGgC8DcCSnItTnLc4eOBf4XnBzoh0Jpb9x3wu41dGra0y4e8xwFn2vu2bX+QwwjPmynxFdUkOYz/bK99sL9fLyplcjAbE43/mu8mYDAr53QNUrJb3Nz4rx1GQc86WS1Vu3V9i8t3L2wPoVqHoBp/k0x6bSPzl7ABt1ekhPY8NRRwzXg+JNzTi8DWyu7csYwi4CXfTeVhUj2oPewkjYkd7sjFXOxu2JUM+tSirR64dI97+g/wPfLKCiAa8fB00weOXAr++S9Zu2yPHhfy+dVw59h+v/bJfTj5tjPYHqi1Cpnjj8HQDvj62M9Qni9ptgzQ72LwADvY1ZWnmEds27C+BSG2FqU0QX5r/EzZfRM2CASw0Ina+Ymb7HuP4G+CR6m/u822eccSI1VjFVg9nTWTuQ7la94VYrqV6bv7IIFl8j91pXeZ/i8GPQm4evAH3f9vTGsiHc+YCayNn/9DcC/CU1KMLUm/te0DQAM8HjGnhpGH17QX8QHlTAoNudocr4AHw+qI6p3lqWu+xVKT6B5+ePqmge8MAp4Mfg7YH/xXrpM5Zd5PQrT5Dny2+pN1qN5qr+wn7TvoyzRjhuSJb32dK8L3DzXNBaB/1lwIyGMzsrunPfS7swz7gyejzKcLcZVgQOLrh3n7XH2n6HAQIP/K2bys2aiR0E/CFosgKqfCyVonB64/sXGqs9xxo2N1TKd5HcfBsLLu5c2d3nnNaFt4mHCMmtYTEZtl2cPfCaH9z5oRGm2OHqwnwzh5dAP8QAlxom9hnOoT4a0X8gp0fXDvnPDMUILaH+sjhiq9qln3WD712KNybsw7ZC7+FzZL53ym2+dw5v3Nss7A/mPLvdCLRqsFyeWLnIZzB3vxZuXMzi+WG0sYeJqLrCnU/Xv25DdW0ER/nCWph/m+NfPTPLaKCo4+yG6Pv0Gr/FYcL5wLQDpAnHUoMU69WYPcO1O2iFPS7uMmle4Ov8Un2RxPe+zfEifj4H6HhT4jXsfL4uiQ7ZLfZ7Z0xax9ZfJdQMcrwAvvfeCd5REv0LGAoAzlTDxDoHce8hfCvoHcLz2oQZZ2si7qMBHwj8uMFOq99+J7aP9vr10AY7SPton1OlOB/IG5rriv6V7dJ/ItcXM9WlpH7CUlJ90dfha5pO7idcJvcTskh8RNBPiIt7RQ7//O0Txj/XUS9nsvUyRQn587atV43oOWPnF+Mr/uvjwh/CehHEU4gAl+xdSrdz3+vLk7+AzC+KwCcNH6D8eQwX36FzDn989dxsQwffoopMMX+GpAWicAfnYuU/eD5WocqsHGIZFvJ8XyGedhHOp5oZzev1Q38Dvhff32hH7m/sx8/nE3Q+g8IJev3E/kYD7Q7qJBOvKhX7P14sHpvd72YSvK+pXPXF32ytg2xK60Jvpm5x9qBsJg2yB6ioIgsn/aM/ztoDIJbztg3GnGevR2YrFysrGgt4bGhEgj06apjzdzuOB1DrFK8rF6T0dmOeIvZXZecp+92ep1DkeYqFxduk3A54PDytlG8523vC7ew7Lj1xrWDPB7Y8XZxHfMug3/Se3D6ahM9cuo/mPp95of9Wyz6czzxens/8mvlaXxn9gnEe6Bcsk9cvIOCjatUvGJ/cNFrCLwH2wDy3mhH0QWBewMfTT1G8eEm0Z3nTraw9a0rjTTPPYf2oEUV/Pe0XIdgj8jUtJsWLhuz+MkU1j5b4DwjXQWDo6mjsfVzj4m/ZbUClRyS03Powb9ORXDwt/sQJuxfGsouvGe7fTjQlnmDtOfSQNvycaQX8RuTY0n2NvV4Q9Eb7jb+TCmSTodQk6n3cnjvaYGq3M2xuiHTfE5rwsKp5z9HZq5zr/1TGfIMyrFus1FRDphdt4s4HRPRQZWQE16q8k2o6c5K1Bx1bVMJduxHQAy1KiptE9hT6h+jfNNja6Er1oqbg9uRpo6jPndlZN6T4cCke4KCID+fnuYAHiMHv+xpHhGktjg+/W/JhyFwRDyDi62rBA6DUljRfDq45XxbnTavk+HL/uUnky5WZVxLmy4vY+XLCrj5RErwNSiohr0ylmI6Ua94Eu4NgJowx8+iJlTHVkv13wAAtPqpwTvJ/yOUb68wRLJ5k5oYV6btvHWpw5YwwrxTf57GUH55vWDUdFAurMoIUT4Z/gzCvvGaeptvh4byyXfpv0n4C7z/QT/AW+wnifIfYT5iH8udleP7coCRP9xY+38mgFpD3PVNY/sMTpHkT2OOlFPy5Dns+RvYswO2hkD1T3LanGztvys7aIzevzBLfZ16fEfKN7m7ryzyiLyx9D/8h5WO72X2QFR7iNwj6OyVMvKnwOhG/0cJD/IZeX+M9BBErAEZE0Ke0q7n3sMXoPez7DC0TO92aThXje6flm6CGNxz/J9U0+TfWnsoYVRR6o2G1OfIzS2LwZQEPyd4vwNf1okJRBYbZc0Ybgz5kb3ONfXzorcJi5wp6graD2nXf9xgqY/5mobZ36EB6s0Pg74303WxcuPElw9S7qabwU6w9325XR0EogR9UWNyraQL3vWD4gfwzDT0maYMoX/SL8fmydhJ6tgM/SiL5TzUzTp1D8p+pfL4q9R9l5aUCXV5d/iPWX8R87BKbjw0LCZLDi/qT8aIVOF50Z2CnOzeLMLzobGtOSNvuQj4GQBm4X6nkfAz0vygUTz3Rz/VsH2RXYAfpPogb+rkl5txlI6R8Vg1HPR0FPAqTrdMCJjhd+Y85bWnRcJbPamH1CMvfDoFfne//tAy5VPB2BYYHSA44w+MhoT//c+Ystj+/hzlM4icBvN9hc0bQ09GP+A/Emlxmr9qgFOZfwOEC8eJT+nu+vwH7O3w+9qY50fTeH1g+9knRFh7PBvt6sC8A3+tXaj0pvr+K8medM6HlE+Dv7V8VYRrmFn8vp4dInFdq2HllUkCBR3qIAt7vUT3Ev3A8Nl2yPGQKrocYWpse4pq26x9vf1l6PoXVvqZCfN49uuS+Lrqnu/vLK1z1e19p/gNDbXS2KP8Jp4oUPH8vW+tA/nOG/rDyRQH/DPkP9FyOdXB29V/E5T/JzXsje04a5xYuS5+Ur224NFPIf6DA5fC0sZQTx9P6aRsotlTlLnsq+hF9fKgv7qP4HqQU6guoB7n4tcvxFO7PW4sTTcvOYv6jR/VFjwhiPXhQjl8iKeCMh/OUILfnKRHoe+k8nKeEzY2R8uHz88HXrZMDPhT58KGogXb2iurXLNfx9ydTd6ngVjn2/qQEnOD14+D9gREmvD9rUX2aTcKPRdqOmb2ONot+hO8dvpcFnc8j+2j89+qMfy+TJdF0IQv7XhHoe7WMwObv+eTv1Y6tB9NHmeX4IaeT9GE3OraQ9WEJ/JB/oPsuwT+Lekm16MNW9W8eLelHwaI71Bin7au8O2iFehDyDZjyD2cS6OlcfQpJDopIRgglY1F92vKEa35abUBfmC0sfcu8Gk/uIex3l9O5qehvofp0Prk+pagfnHFxN+Xew2RyPfg27s9voHpwJF4PXq1ZD/L8/MG11YNlqw+T9xk/5fvzj+4zEu7XKTrC9ADfZ/zdkqc7QN5nPEHqJ8A+I0VNrT+f3hRUn8bjfBcPHoNPb9vW4OhH+Fe5+cWX6pNiPOX789BvGYX7M1MWb6JwvPpYFE9tfYj7cbJ8+NFJ2+q/r3ce1TtF9d3X283mq2vaWgySeRM8xKg4Tsunc5iGXH4I1w2ODdpCHZk8q8b+yD6I6tjXtNXvPUWNeUHenJXpV68NbjDggiufT5DMC5Kp+ST+umSF0RadJMsXZ/KIL64rzm+zpiRYqp8LfHFgzz/y8ybQz7XWf99cRp860RIccs1DfWr0E0j7F75iPgb+zO+nwP7FDNye/PJ4Uy7ODzAV+bOpD5FPWFbPrmz1Pbl4sagmXzev70ng646R5+t+TXwPgSqf5+s+SOonAJ8wetf5fAyeeChCAYD0Dt3PL1TrqpfVUeA/sCenpX9XbcL52f51aX7JOZyfzYu5YctkhPwHfi7Yc5BZ4TzM7XvCSJ7f94zTLleM1KSPyiP5M3yvK+T5oJ48H8zC54NflXQK+cXD+eCatifr6Ee52f9ZRu7/vOVR/6cIxYvDcvv47sevdBS/Uuobvxqw8Ss76wNpfQqNFcC3HHB8qh7A9cP1er0Bxp9Ac7XOud/RzOnCA2xMA5AheuUic+07mY5Ovh8OiVcq/I9ZmYnUZoXwPkPOARwTFLWDmqbC+P0uKzo6VznC5srqje4g643Ox+/XvyviTdPJeqOS+y7V95S97xtuNZLT01yE95/Bng24PX9Y0ftzqS79U56f31Cb/mls2T+k90eH7FlOfn8W1/f9Ca/t/dm2teb5/J/mrjwgqmr/31nZBEwlcbDUSt5zy2oUlWUGXtmvcMs007K0NJ5h+EzJpdJc0pfbK8VU0BK1IpdeWZqpLGouGeC+JOhDJsR1YEAYGGbuvb/zvXfuvQPnXJwr8Pu93p+v4Ms595zzXT4LeX0Ev9G55PWpROvTiew36rE+kr56I+uT1FlWL9d7vcH96P0qxPHPd26rDB96jX/m6wuffeM8zxfYl4Ce+Rj73MD3JD1z8PNtRM/cr0t8MevA6q/5geHlpVL9BSNwqL82kvXMXRrQMzcazSQ8tqyfphK/yKr78IssiM2Tw9vUkPE2ofh9WI3yHyee/7xqYxXjbc4tJvrnGur75wrnS8Y/90xNouVk8/jnGo3e4JHu0U+QwSNB/8fP6/Xh+wnpI4h6lVslvWVPvcFQcn9VRm/5o/p6ldsqGtUbfJXTq/TZF0zqH8J+vUPery34fg2vTbR8fB7br3X19+tI5x+4/RpK3i+en9tzttJ4CHoOH9RGW3aQ4zmOxzOisXjSUod48k9BPwEumqTqboGXWAE/nw36AHAfHqsbUr4D7/+YOvhb5uD4w32BO8u+7C7yhUHvguefnlHXkfrhP9r3W9NHNINf0kayX9JORX5J/lx9GpS8TagHszemZQNWFF18UR2Y3iq3PyNwHQA/BvzKc/Qkx6I6rB5k6VLfs3w9WOgwifix05cfCP42X+y3wPwdzpeOeobywfuZPfX/UrevC0quabH6awaqvyz9ML2vRuuvlKK3hf1KzNyF9ktnhmbq3OqhrS5rBH7uftAbhFbwbdenlWMY9/xrPjSdskDh8iVVWtl6Hq8Fgo5Q+E2MGmd6k+1U/Xx7EX8I0HroKbdjR6o3BmH+X0najY79FTd2DYptgCfh++HvCflhQz+7NxXh2b7G9Tw7oXyDwN/ZxfF30s9Okeqv5YAQAfnC6CQmSXVcqC+moLtwPaS+Mc/RuY4fHIJeJaqmnstGfzXKsOzMGB5PCyQLYPAbjXezBzgWt57UQdRHQjk0x9+Zzl5gf1Hj+EP9FKqv89Tbe4R4wAgNeC0Q8FL6cMBFPp//YZqvGfBj0PrLcpm1ZyX9n1cm7uf4RG3PvVKWh9eDa+jRjiliPRgFukLw/exhRrLRtVg8P+sLVcd14TkpJH9P//r+5veYX4yt87cMuoj1f4Bf8HcSX4/o77nCPb9o1XR+3P+g8xV1kejXppQfh6orMv5wnCf+0BMPcN/4Q6lebgR/OH6HyGcEGD7478DdNa5qe8Br/PsORd/YT/8G/YSYR5zvVxRLfEbg47e/xPtBZ/LzXLjJAQGHkgvT1lYP24ZLfEa4WNHrkh3BHFKvw9+LAk1KzVlreM7dpusjqZ1EfaTWtriw0fX7Ufx72sh9mJCw2Cyuj4Pj50LufZmZqYvXuPn4hzltEqiX29F76P78+gD6E/otlWeGZFfbX7ybytencMnA8B9sz6tcs9hZor5WFCw0p4/EDmP34Hq5hbreqj5scsG9+NT1+xtEPjXgN0IuN5FPHc7hW3rObgb+6dtk/in4lXh/vgzc+Rq/oxn8U5aheL7D47mC4lmh0D8lLdVPoR5+Nh7Pf9B96PcHFo8dxZPgdTw9uHjOLf7v0mvKz/uYjPdTog95HtU7B3A9mZv19SE9/fFl9SHz81rdvx6agDd+1nd2Sf/6eGPQpf6oZp2hvwI9NMAbr3GdaKjvB1phr9LPB/Sur+83MaooS0WfEvT9PPu9Y8/OsZXg73tbxlJzm6mn7wffzxfMCkHfr36/d5XqFZ3R+JMQz/hrp7ihJPSJbfSwgL46Nz9FYwY/O+g/57vSNW6/AOAvJ13n840t51Zb/Xpg/OUl9AHHDD4e+AcyblifYWwkm1tL4C+vUr2gO7fYt+nny8OPzPN8dbijMgz3+nw9wZ2vMZXLoj3qCxDKhLMwk9mt2ct/Pyutmdx8Bzqmvswgl87VmJ65ICMHi3HJtZmu5t8LeGxg6dD/lf0MtzDY+lxRB7CfMEbjFjn84VESnp+IP5TRN5bBH9aR8Ye/cnopFNUM++XhD+K5X0+h/Yryer+e5PbLaJyg6P5ZSprnKscbE+6fOdz9k9Q50VNfAsb58Mu3VN8K2KoV+ebAHwQ66xh62t00vv4Cdwr4i8GAbDfjqpjJ6x8CKgcGXcCY30vPr0lvK9an6O80gQbTALaP+lOez+iWXefieVMbU7e7MqVI7CcA36rNws4cn3pade/AM6zgvwzEaW59mtRPWHhgKddPKCX3E57V/mI/AP6nivC9xPxnMHovXsTzn4pyIr43lzzf6cHlP0ajT4t9zy/daWtoi3/Pk8jfcwT3PUda9U2P56/keKageIIVxjN+R8vGw0Qqiyepc8vFswrFc11hPClFuhaL5wsUz2kF8eRyeoNrPOt3Cb/xllC/w3sB81wevzHV9SL+Xrzh8Le8fgF7LyrQe7FGwm9I+B8i3jgF1e/HmAVDQ0j66tdQPtZFyscANiXoqxfXz8dgfT5rtbLkm5sY3lhl3xiWI+GNwdAezvsOcj72sn4PZWfSUltuv35G+5WvcL/Cc/7P3/dqufcd+AVH2wyP89BfXWntaIbUt7b6hcC1rKAHwpnWgX5vOnovcvH3Qmc4WzwKxx/+ELi3bFN3Yb9ixn66gOPHxTOH1Ffx9yJM68fhn5t3v4T1gf3KvdPV8LXC/crP07ZYPNdQPOkK49k9v78cf/Agme/Zz2u+5/j6fE9BT6+OzC9w6KAf5RjYcuvjROszPdLb/FDA955W6O/5KL4+7zCJlrfweeWHtpCwQgnfIuFXG5lXVi77JJaAjwL+ztr6eAnAk8ymF5H4OwdQPD/h/J3pFbcMTyjk7/ScrWnW/MdzvyKs/Q2xkcr8/ozGlovnbyievgrjWd61Uq6f+XdyP3OL1/3MONvosIekfqY0H2ykn5l+9nGz+P18w9WnKOnP1DE6qo9K8BM3gQUp6FU66B61++vq6SdAefk0GwLZv5b7t6X5V/6V6qB9eeL9HNb7Ne57XkBNp6JwPmO6LknV3zGmMrvp/UzQE44n5/Pzvc7n+X4mRcWS5hc6NlHAr8L8As47lCxwHw5RpCe8pA8Rv0qYXxRxesJosWIlfSROHwB+8RaG0RXy/edvj+ZyenEwnulID2PCBf2xPmAxDqP5GJvqX3fCePwYWmBoGuTYMp41qZn1vku7CPOmKGneNFHwa/OM52tdJ1V36sauyYrwz58p9BP/TSH+maKU4jMXtig+c0zl0abra8nwYXvazhsiyHyQPST8PKzPmEpGzu/45abqjz1fts4Qrkh/rDWqB1vGHxb2a6I13uCj+L14WdKv25B96UR7M3BQ0+2LAoewbv7Fn1mgBgX+etPqRpbflfJVQY/6zY6ri/vZsXz134GXyvZLetQgIQd4rePMjyQ9B9DLzbKmpXbz7LdMjOpkBj2QvCp1YFu+Pw9pAmA0YcYc7oyv+AzXE97UNtGSg+uHLw+KF/z+4Fbot2R+4/rh/WpOWq+1j/PiPoR6kJ/nivWgF/fh0/XvQ6EeDCbfh39w92FCgqy+xEXp+/HUl3iO4I9WkWgpO0HkO/hGE/NVwnkP4Or3o23e9sTb6OeHmAHysLG6Y6D7fYeJH9Q7IBOywfmxbZHg77k+e3A/P07fZpxfj2tLb3DxgMghkJRRoWs6oN9ky39ExPv9MG2SCahz25gv1P0fwPxzR2r9a4eU39gVIFcv/0XyI/Osl8/j84vvfb8tWYLPL67XrDOU9BbrZVTAcfdPBrleHovyDW7e7ZlvAN4Y3hkdE0JN4tcHvDSBiwbHrpz+W+36OkyvKYAtbKWn3HpWfL4BY41R/+kVXJ0r6qWAMDrE8zo1ieqK5xsHdaNVIx0++4zCfqGHChRDzaC3vL7qaQHPBnp6oOUJUIrOzpXlJ8h4tok4nu2toBfLbN0FPmzMyZoUbv71Lm1R/46fr4naX+yV1jGV3uhrCX4TMvpac8j6Wt/b4sJ2SPm8VL83gp/Pz/uw6X6+tdRqywP4+74Eve89Feq9JxcsUtifn3XP91SIJ6/ivOFyX2K9IzsfjEx6zpMPC2cdfJt1jJnqqhbwtNxsBzrvu+hFtaxD5MPC0A3UQ35jlwccoLl40g29zSA9uiRuXk5/y/7W7Y546h+6/XOHUjYcP/akvpDa6whK3qOQX0Dw+/uUjrYsVMQvOCbHLxhT+e/YBvxcHt+SKNTLgNcS9Jan0x+4Ojaq191Qb7m4H4HvuZDEXy7n8D8ZgZsU+gVENNUvQGb+xfsFGI1nFfK/euH7FUzmf22w9Qg7q5D/lTN6RWwD/iCsTzD7vie+DvhWfD9hnmsSvl93XdEW5hJ2vspstwxZEUS+VR5p/rWDuoDun+VmqX+YBaINMD9dx9j0No3b3/MCx++Gc9CN7svu5t+vhIQETg+/doQmx1L+tTXwN0wP/6/0FIeFccezJQrdh9z52sy+zvansfNVoeujOkiFDnpGLv/5hpT/vOd6mYw/bDz/aegHRPieT3Df89E2DwnvV+vRA7KhWAcwwpd1//L7i49bn3YT5xcAKd5Sph1dyucbKLHIBsQiyiZNr5ZEW2wH3PP3O6B3kQ1ixieqzA/4GkX/L1gfAAt3pzIpJx5PgX4d2xfl8/GSP+z3nP4G4MPpqmDBjwxEwkF/AySTZfRpt4f6W4Lw+eARSZ8W3lNJf+MKiV/wrvYd+wFreI7s+bpC4qPJni8Nfr5WoPN1XDpfgPBq9Hzx7+lgL/CrcL4E/OokPJ7+zYFf/YnDr2YE7vWM5/741LXovahpKh8tBL0XxUxa6uym5xudVKstJjzf+AblGwYF+UYml280kz5AW7yfsNf2z7B1CvUBdpbMaZ58rOQKMR97TmE+5rMvytPvBvBjcDZXVYUIfrXQ9gBJaICotHdOLv8Bz5/tD0ZbluF8opCgpWUnJfxYBy3PJxpFX1czeP48UzvLXmCtXDZPkT8RcX3OoPX5GV+fcWh9XlG4PkajU67f+zIZz0/gO4Sh78cP/35ulJ03LFLo331u8Tueet2w3CCIXep8Q3eUx2uB9jOECU/tDLbC2ZkV/AsAqJoJ6kUdnb2ZXB6PBKqE4A2blpoa8x0ziYpUi/o/cIGBKin6y6kIvv6CZ1bEa6mLmX3OtNQB5HzsLbl5U3RT500y+qJV3Lxpede6pu8X+K0T9qsNyg9HKNyv9BFvSP4FX3L6LUAkiLPPDVwg+TsI+i0y/g6XusQXZ9Vh/g5vB8aUF5P0W4j+Dn7ap2tOWtNSHUI+Bv1GeMRhYzKYXj43+Xzs9COF7n7L4f1t6ensaT4fu+7cGgMdkW0VZ7IG0uzNY+cEPFvWkrirnAJ6Nbvcp+dDoj7tn1+vd+djz7MOFxbPDm0fVYhqeddbcvfzh/X7vbBf0O/9F75fBrJ+C/R7k6T7WeLnytzP0O81GqcL6wPa5zA4gY99PnNadV7wL5gHjXhO5jOa7lV3xOHmEz0aDTkr8EFGUg5Xr+tcPFBuQMcRxNo3OI1B9jain4vkl32QHYnzQYbr51CfO+k3q4V47gzvnwWkPLiftzBXfYo07vywmFsfOMUP0yHUKJdYnwLDD3Bk/e0V1+fku+/nFVkgqgwv3ipVhu5mqHt9FkaC0RHnd4P26wV8v/6u7a3KVE04vl6IByDv0AeFwX8mneG7WOd+L0o5vVMUatY0OkR1Xsjn9TnwiwEvmnLB9/aDPevl81Acd6VVrgoxn4/mGTa/ZTmZg2wC7nfzvf40la9OS+0mpydsJ+sJ6732tzqG7h9W8usX8h8ZPeG+nL/VE2tuSN/P4f3wLUM/KomZ7BesdfcTbnIWCzBOi6ZXqBbz+Tyow4PDW2ayMefChcG3PurFxQOPFNpdCDPmPbXKtdZf2K8o9LO5eMzUGPZ4Hca3Ctf6q17URFqfatgfA2PsdKk/5rujIxivmuAlCHWuVMD3nBoUX2aV8nlUX3D5/AyUzxP6Y69pD9vt1kFz28v1M3tK/UzgXzToZ4Ieo4D/merfuyTxOob/2VU9OizgKayfuZm8X29weg6OgbL6JBle65N8VJVoWXn6Xv6wnvm8LF8YvcPC94PePO58wcwph57tO0/n1gMpMYEaOMiLz6RLqX38+lx5TJ/z1dQs7nw9c3H7re34+epCt3Y5JT8piAniqUDnaw1+vnah87VaXbnsD7l+5jFyP/Np/Hy9gOqL3gWYv/BBW5xn/iy8787G+pkTju+X1mcXJyIKxIZ0OjpgO78+oKAM73sVfS5LQ6/XtKFF/Dx4zECj+dGz35cPxvHzubShdiojxgNvGHw/ndnp7BnBH39hpLA+r+qTVMN0oYMmKvJjXdrCfqxzd77fPPVXSPPUX8u7Wkj6YwZJD6ShHuMUgj81WY/RiuqvCdL3I/SjGtVjdAwcLZx3mNjAfBCAER7zQRjLo3LFBFRQmA868flgQcfVxb/j88GtgcVlh/D54EmyX61FM6NmnxVlDE3HSzzEyvK/lOIljEZRb3BJXDrnhwjE6WfskwNnSHr44EcGo17leoMeevhAlQW83yKy3iDMK/ejfPW/pd+bzfV700e0HF704J22hv0K8X79Tn1hFt93ayb0+aBfd5Q+6Ttd4AvfgI5gDMgTv0MPUFXh+diYC5G3r/fA3ovH6Vynm08EYBQo/uD7CUDRxOLvxZconhr0Xpw3efAdwPQHDGp/pruz/vz6QG6Ich9unvIYM7Tmi/p8fPhxR5hi/w24X//vhVlBP/J+/ZBzoo+Q+56nUHuo9rg+2w3dBlVEbVqqrB7shv8PPdidJUktirdRrjeYJHzP4MYENT/QWdcw3dWTNYK+BNSCXDqex85murFuPmwwdPMzYaxaSM+CCZLWPcGGxBd+SAo7gJpFif15+IbgI9RRz1OrVO54NGI/oZD6kZ3LhOdsJ8+b3tJelvqrgLfh503vubp4jVdfgs57tTRvglIIvp9SiohPKOHwCaGDRsrNU9ZKfqMCPnMuPc+VhO9XH1RfRJD7vWl9iHpWhHnKF9w8JaVI1Tx4G4JfwJfW1wyXBijD26SPaCY+bDXOzw2+o5wPG5RcLtdPeIfU7yXq/8j0ez+3/SMsX2G/d0xlmaJ4lPSf16B4DinWp+0p7NcP077N7rekC+dn51P9cuDjfD2YdN0JtHgTlHQBzva2c/h8Z9yD/pbPbZi+em5QrVXTQ3zf8/OWi352BDzSw1pDzX+s+Xl3FPbnU7zu/xSi+3mhtD6C/tgzja0PRcnWO/nkeieGXO+8itc7OyV/NIhH4lc2Uu+kpV4yS/rPXL0DjfiNtMN/L/++o8LYDO8FB7WiEzSXJH8ZUIDYVrEgZ+nZ/PIr3cX3HS4/AAnTTHgtTYnnCzCj8EP07Cw22OHu9z4qxrNdN11Vq43L+FHOf7mBPxrczzL+aDqXv6XyD2/90WT8lxlu/rWzJIbkbwX8pgZ+SQK+91lF+N6ZXuN7+fciZ/R3cu9XMen9+qDh+wXxXEfvl+6it+/XVfL7dRPFk8fEZcj2V2c2tb9ablPeX420thxedLQ13vCwQrzosDC1sD7ol2ZD3QYHewMTpTvC5z9lH+ZwWikgedKNXkWf5vNVlMKaEhK+Ab2UmPGa1dZOfP0FTSf0b+acrBlh8qXb+W161AOv1Zbrr05A56sUx2Mn6ylVBnovZPW6M5qq130LvRce+aqET5DNV+1MUud4KT/8ntOLg/5hWZVvYDvK7bf1CKcXB4lgGRkP8H6ov6UE15f4vT4eYN0USS+uHdn//YA1ueAzk9h/TgG0JfgXRD/NDFW5/Xegdj/4+yZOr+kkPddx2tO/idf7imPe8vmVxx+a+5rMYB0LbaGJRcbWnXNFP2jo5MN+jaG6U9fx/vxl3S/q8Lq4jAWK5pXEfP4lKtEyAp9XPoby+fV9leXzGYH/XX5JjoHNoNfUQZFe0+uN6TVRVGvyvOAlrYqkBzLZ5cL9bkKDY6+9cAfrP1+13w7bh+uBHJXzHzxIBbDJBUe88Nu6f36B2ev9iuL64Yma00K+AULqkj7JsIC+esGP1Qzx8Pok5zXzJH0SyDfgICWcnWOr6l6vnwD91a6MtSZU1EeK/igxk9MnWcesYHfUuucX10R9klH6tapXdBT17T38kmBecA+/pPjas8URzeOXRFGnSHgk0PO0kvF+j+D7lcokWtJwPNIHtpCwazh/sLAx/mBKUQdPP0QgNQDW4l0mXFck4Fe3goMEZxO0kf7d9Xj99Tk+w2S6emu1peiY+D3DqAXGvbvuzAvdFin2f2BgBevzCbWH/YLQf9ZnUJFsXMYV4X5G5xH0BuHyy9pPlzKrKLce44kYeEKg7dqTYewn8f7PVOaNgDUqt76WpM8fVRAd3O20Wy/lvRigPvH87kxqLN7/2a5bpSqtSUgY1ZBfydfvHwn+aA3r92n4frVC+WFQEUEPRLZ+J+Bp1+l2UpeZ5ILdJHxvHfO+oJdb3194qYDv9bwPO9IiPrNh/vwrjtcCf+FjJP1MwPf67Jss+aP9BN8zdxkPdLT1/Ukv8gdhz+DTCmInOCL5/g96yLlZN7SHAh3jXZW8/ymQW2AwDAy2BfRQKlznxidkQn4Ia59dzA5QlQn+3Zpo4bxHaA7SlCMuo4BUf4F+eJZ0voR5HNRfQ/H9KkP5j/0SVn+dt4329HOR/B0a8StB9ZdcPIfI8TyHx9ORPP86VD8eCd/SSD2YkNBy/g5bykPCjiv0d8gZ3XLv18P38X4FJV9sev0O/ItJ+H4dkPgXnvV7o/yLgtga4T5EiRfXD4fB7S26WPArAQoNYH+AetCJKbWrnB5+W3y+WkTbApwU5m/euTA62ML7mwPGQPqeN1NJJL+STNXJmqOrZppFPdjkbDexIXo9M0xdrHbzT5eZIHcGhtAT9LY6G49vgRcpvtWCbGDldGPDnPl/cvEAsgIa3w+98lV2rWtVwAeBbn3IZVyLAfZrIfsde0GFxROrX0uFuJZ3LWj6+ZI572fR+VqHn3eqsfMentNyeL+8svOGjQrxYztLhniJN+bfrybgjaX5KRFv/J1uB3Ua5fOTJL/aTSgbDjMDEKqu+t3AXH4+6NpakQVsZEj1d9ctKK901dMX7Tb2pGnrQzevhtRw8cDLC3g26B+2bXW5/FI3sX9Y6JjL6YuCX/ZGvH/4V+2TNbXWtNTjJH31ZvNra6PYr+3pe+gxQtvMU4/xc7xeTmkfbemO18tFgZsFv7aGeoydSXqMw+zZ1qNtiH5SgJ/fI+Ubwn0I/MoJ+Pc8/26iZf2pe+FbPPV/ZPXMK5et8+yPeeoRbSf7SQ3G8/mVtf6W+Xg+fxjlP0f7EfmnxaR5CuTzOaOveZ53T3zCcqnfIvhfQH9sFmF90HlPviffXKrfZfnmTsZobCunV/mAVJ+Cv6egV3kbr08fDFJdi8P9WOPtp8NGSfpIkr8nsT4djO5DJ8pXP/dSP6oBX9hzfWAeNwOfx1E2UT+qIV+mUE4/qnLZKTIfRLb+ktFvWUmuvwoV1l8FsYdb1C/7RYV+2UHJx1pMryAK7VeEwvvQaNQI8QARlzOlTYyOWcdc02by/dVHC/ea3DbsMU/RJvq7OjeeZLIJEO5Abb6qKbLe5eNBlWOWdlRQDnT5lrne9fvqMXF9gLfJ91cXspF4PKf0t1GitrPkNS/86D39spX50af1IerTHiT5sYLeTuWyz8jvu+gPK6OH73m+Njv9LTv/wPqH/5TeLy/4RAu49z0/ryMJn3kV3T8RZHxmLn//wEcixPMPXbc/51mw9QmrvmXYLeEzYSthv9ZSK0j3T5J+M3WBibRGePLRcjd1NQN4JKWqd+Db/HsK1zbo00KXqaNzQflhHL+658Foy7M4fjU2KLHsqvSeVtGruff0DdqivoznG+9o19tvWPudyjKL84JPuf4YNL630QEBn/HzOPSPGeaV8Kd1oBM03WhMv9d2prWtH44/LKKP1kxnPL7nhZxe7jPsXNbfgeEPjfrnVQ/p8vNa9v5RWn8tGBpl8uAzwrcDGjevMiHazVpx3gS1BSy5H73NNVbkU0cKernRzBHNHZ6fkhL6mBmEPADss+PGTL+bfUR+CnjAQ/48kVnF2lisvujn41S9zh7vvVnYL+hDwd0Dd+IZ+qSvid+vhIRSyEDh/smaSXdT9eHXx5Yh4aMOnK+8Pb4Hxj+Npzs7j0v4KIicw2Oj1RmE46Om6TdQLnVaqsj33FbxIirjBnDJxU3HCb95Pm489gbufYeRyGbmJZea14PlDCV2fZI9aWWSadm1s8XDDnHxLIm7aur145Vs+C/Cam4G93pS5HuimjAT3sgBVCn6H7ZfR/Wd2QnM+B2PC/EAgq92xKNm+IZ+rXpBOF/gZoHWxgTb6K/Ib317UIcyl6QHO30Sz/dcQ19U78HP12Btpb3KWrnMdg99rfvHb0y3/SOsOALT1xraGB4g7Mbr/1fvhed85yDpfob3InRQO8/7WcgPAT/fnpwfltbPD7n5YOD5knm3sPywnf2XsM+l/FDor+4k54fDufyQon5rer4hU3/1uo98g6LmCec9d9PAbDhEcD8fYhZpNBo3fv4rzusGtvJh+oLzLWk+CAwtYAH3cx2tOcjHA0QUYNagA5W9lX5DP1Un3ocS33wuuxnX6w7RF1J/o8f3fMBTXwLkYODH+TOfsK/z5wuOP/RWwa/2QSalpovQ/9GI+myl7L9bGVms//PPwutBo0+K81Opv/EJdQDXSxmuu6CaU1sQu9oLPxfPfP5l/Hx1qyPiE2T8XEIa83MJHZTcdLy6jP/y1crzhtt9lPE95+58RcG8APQYZymYFxDzQ5l5wQpuXnBjV49YMf/pLcYD/KYKnN8EerABXvObfr57wNBawrcIeJsL5PPeg+M3FcQu9wIP6akvQcBDjpf0STz3q1XFLUO61/oSM7n1SUgQ+U3oIs7+Zr3AbxL97IBECTMMGOkr4ze9FxRfVoHzm2bSV9RH8PdrrPa43W5d3nWp3Pezlvz9EOZNPZhoSxSu5/k/aH3GRXg7b+LXxzGQipPRixveVL240LKPDWMU6cWBHnXL6XXPvtPW4FCo152f1wzroyavz13rx4a5XuNp+fWJtNbLx+Z/LuVjUym3XsqD2Wjp7iMf+zqoi5CPccmBOx9bSc7HhmjvoHzsf/9Fu3Bl",
}
