Date: Thu, 28 Mar 2024 11:58:48 +0000 (UTC)
Message-ID: <1012738997.1.1711627128250@6724c7fc0c71>
Subject: Exported From Confluence
MIME-Version: 1.0
Content-Type: multipart/related;
boundary="----=_Part_0_652564110.1711627128230"
------=_Part_0_652564110.1711627128230
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Content-Location: file:///C:/exported.html
Overview
In this study we aim to more rigorously understand whether it is more be=
neficial to optimize the non-bonded interaction parameters of a force field=
on solely pure data, binary mixture data, or a combination of both, with a=
n emphasis here on density (including density
Error rendering macro: No valid license found for LaTeX Math addon
, and excess molar volume=20
Error rendering macro: No valid license found for LaTeX Math addon
) and enthalpy (including enthalpy of vaporization=20
Error rendering macro: No valid license found for LaTeX Math addon
and enthalpy of mixing=20
Error rendering macro: No valid license found for LaTeX Math addon
) data.
We anticipate that training a force field on mixture data will improve i=
ts performance at reproducing mixture properties while slightly degrading i=
ts performance on pure properties. Vice versa, we would expect that trainin=
g on pure properties would improve its performance on pure properties while=
slightly degrading its performance on mixture properties. Here we aim to i=
dentify how much mixture properties improve relative to the degradation of =
pure properties when training on mixtures, compared to how much pure proper=
ties improve relative to the degradation of mixture properties when trainin=
g on pure properties.
In an attempt to make this study as systematic as possible we have chose=
n to design it as if we had all of the data of interest available to us, ra=
ther than just including all data we have available. This will involve sour=
cing data from outside of ThermoML (mainly from the sources reviewed in [1]=
) which, while including a significant amount of information, does not cove=
r a particularly diverse region of chemical space, nor does it=
contain large quantities of certain properties which have historically bee=
n important in force field optimization (namely
Error rendering macro: No valid license found for LaTeX Math addon
. This should enable the results and understandi=
ng generated here to facilitate more long term planning of what data we sho=
uld focus on collecting (either from the literature, our industry partners,=
or in house via directed, automated experiments).
The intention is to keep the scope of the study as tight as possible so =
as to more readily enable the de-convolution of the effects of including di=
fferent data types. As such, this study will be initially limited to system=
s composed of (the two species=
for which we have the most density and enthalpic mixture data available), =
and to data points measured at close to ambient (
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
) conditions. This will then be expanded to other mixtures to ensure =
that the initial results generalise to other types of systems.
In general the studies proposed will proceed by:
-
Sourcing a training set of molecules and selecting particular data point=
s for each system of interest.
-
Optimizing against the training set using ForceBalance in combination wi=
th the OpenFF Evaluator, starting from the openff-1.0.0
force =
field parameters.
-
Benchmarking the optimized force field against a test set of
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
data points measured for an array of alcohols, esters and acids (her=
e=20
Error rendering macro: No valid license found for LaTeX Math addon
is used to indicate a property as a function of the composition of a=
binary mixture). This will be extended to other functionalities as the stu=
dy starts to generalise, such as amines.
Note: The scripts created to facilitate this study can be found in t=
he nistdataselection repository in the studies folder.
Compound Sel=
ection
We enforce the criteria that all compounds selected for the studies must=
have available all of
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
(possibly obtained through the conversion of=20
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
where=20
Error rendering macro: No valid license found for LaTeX Math addon
is not directly available) data.=20
While it has been hypothesized that we should only be interested in choo=
sing molecules so as to achieve a uniform coverage of SMIRKS patterns, this=
may be problematic. The same SMIRKS pattern (especially the ones without s=
pecificity) can match multiple different chemical environments within molec=
ules, and may require different data to be more effectively constrained. Th=
is would likely not be an issue in the regime of an excess of data, but giv=
en the it wo=
uld be good to remove the possibility of this having an effect.
Alcohol-E=
ster (+Acid)
The initial data set selection involved selecting a set of six common al=
cohols (methanol, ethanol, propanol, isopropanol, isobutanol and tert-butan=
ol), and for each alcohol selecting approximately two esters, one larger an=
d one smaller, for which both
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
data is obtainable. The components selected according to this criter=
ia are then intended to be used as the components in the pure data only stu=
dy.
To ensure that the initial results generalise to other classes of system=
s, we aim to extend the study from alcohols and esters (two po=
lar classes of molecules, which are h-bond donor / acceptors and h-bond acc=
eptors respectively) to a broader spectrum of functionalities.
In choosing the extra data, we again enforce the restriction that all mo=
lecules chosen must have available all of
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
. Given difficulties in optimising against=20
Error rendering macro: No valid license found for LaTeX Math addon
as highlighted by the alcohol-ester studies, we choose to remove thi=
s property from the optimisations and only consider it as part of benchmark=
ing.
The number of systems which meets this criteria is somewhat limited, and=
will somewhat restrict which extra functionalities may be included. Ideall=
y, at least three extra classes of mixtures will be considered:
-
Mixtures of a polar and a (much) less polar component. This will complem=
ent the polar-polar alcohol and ester mixtures and ensure that the results =
are not strictly limited to more miscible systems (this could possibly incl=
ude systems where each component is an H-bond accepter).
-
Mixtures of two relatively non-polar liquids. Such systems should be rel=
atively miscible but in a different way to polar mixtures (mainly VdW inter=
actions as opposed to strong H-bonds).
Table 1. The number of unique systems for which the different ty=
pes of data (and combinations of such) are available. The table in=
cludes counts for all combinations of mixtures containing a spectrum of dif=
ferent functionalities (ester, ketone, etc.). Only mixture types with at le=
ast five
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
data point are shown.
Environment 1 |
Environment 2 |
Hmix(x) |
rho(x) |
Hmix(x) + rho(x) |
ester |
halogenated |
123 |
184 |
123 |
ester |
alkane |
104 |
92 |
73 |
ether |
aromatic |
46 |
143 |
30 |
alcohol |
ester |
48 |
134 |
28 |
alcohol |
aromatic |
49 |
212 |
25 |
alcohol |
heterocycle |
28 |
146 |
24 |
alcohol |
ether |
36 |
136 |
23 |
aromatic |
heterocycle |
30 |
100 |
23 |
alcohol |
alkane |
38 |
105 |
21 |
aromatic |
aromatic |
49 |
121 |
21 |
halogenated |
amide |
24 |
37 |
20 |
aromatic |
alkane |
35 |
130 |
16 |
ketone |
heterocycle |
17 |
28 |
15 |
alcohol |
alcohol |
44 |
193 |
15 |
ether |
halogenated |
17 |
66 |
13 |
amine |
aromatic |
14 |
35 |
12 |
halogenated |
heterocycle |
21 |
53 |
11 |
ketone |
amine |
20 |
13 |
10 |
ether |
alkane |
34 |
51 |
9 |
ether |
ketone |
9 |
14 |
9 |
amine |
heterocycle |
11 |
45 |
8 |
amine |
alkane |
16 |
39 |
8 |
heterocycle |
heterocycle |
11 |
16 |
7 |
ester |
ester |
10 |
25 |
6 |
amide |
aromatic |
13 |
62 |
6 |
alcohol |
amine |
10 |
125 |
6 |
alcohol |
halogenated |
7 |
92 |
6 |
ester |
aromatic |
7 |
99 |
6 |
heterocycle |
alkane |
22 |
40 |
5 |
alcohol |
ketone |
38 |
29 |
5 |
As is shown in Table 1., there is only a limited selection of mixture ty=
pes for which there is the requisite data available. In particular, there i=
s only a limited selection of mixtures for which there are 10 or more uniqu=
e substances (the number used for the alcohol-ester study) - the aim is to =
include at least 10 (or as close to this as possible) unique substances per=
set of interaction types in attempt to ensure the results are significant.=
As such, the most promising functionalities to include which meet the ab=
ove threes class of mixtures would be:
The available molecules to select from are listed in the following attac=
hments:
Parameter=
s to Optimize
Alcohol=
-Ester (+Acid)
Data sets containing only alcohols, esters and acids (containing only C,=
H and O) will exercise a total of 18 SMIRNOFF parameters exercised (9 diff=
erent smirks patterns). For these studies we will keep fixed any overly gen=
eric hydrogen parameters, as well as the [#1:1]-[#8] parameter which should=
stay fixed at epsilon=3D0.0, allowing a total of 12 parameters (for 6 diff=
erent smirks patterns) to be optimized.
Exercised but Won=E2=80=99t be Refit:
-
[#1:1]-[#6X4]-[#7,#8,#9,#16,#17,#35]
-
[#1:1]-[#6X3](~[#7,#8,#9,#16,#17,#35])~[#7,#8,#9,#16,#17,#35]
-
[#1:1]-[#8]
Will=
be Refit:
-
[#1:1]-[#6X4]
-
[#6:1]
-
[#6X4:1]
-
[#8:1]
-
[#8X2H0+0:1]
-
[#8X2H1+0:1]
Only Pure Data
We will perform a set of optimizations including only pure densities and=
enthalpies of vaporization as our baseline study, given that this is what =
has been historically used in force field development.
We will train against the same set of compounds as we use in the mixture=
study, and for a single
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
data point for each measured at as close to ambient conditions as po=
ssible in an attempt to keep variability as low as possible. This decision =
was made in order to keep the data set consistent, and to keep focus on the=
predictive power of the respective data types rather than which molecules =
were included.
While Density data for these compounds will be sourced from ThermoML, no=
corresponding enthalpy of vaporization data is available within the data c=
ollection. As such, we intend to source the
Error rendering macro: No valid license found for LaTeX Math addon
data externally, using DIPPR as guide to which data to select, but u=
ltimately retrieving data directly from the original publication source so =
as to avoid infringement issues.
While arguably this training set will be much smaller than the mixture d=
ata set, and hence may lead to overfitting, it is challenging to expand thi=
s set much further while maintaining the desired systematic nature of the s=
tudy. Further, any extra data to include in this study would need to be man=
ually sourced from the literature given the in-availability of
Error rendering macro: No valid license found for LaTeX Math addon
data in ThermoML. In principle however, this baseline study can be e=
xpanded to include compounds outside of the mixture data training sets if i=
t is found that the pure training set is too small to constitute a fair stu=
dy.
Cho=
sen Alcohol-Ester Data Set
Only Mixture D=
ata
We will conduct three sets of independent optimizations on:
-
a training set which includes only binary
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
data points=20
-
a training set which includes only binary
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
data points
-
a training set which includes only binary
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
data points
In principle
Error rendering macro: No valid license found for LaTeX Math addon
and
Error rendering macro: No valid license found for LaTeX Math addon
Error rendering macro: No valid license found for LaTeX Math addon
ould provide the same information content (giv=
en that they are linear combinations of each other), however they will diff=
er slightly in their contributions to a least squares objective function (a=
nd gradient thereof), whereby the information content of=20
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
may be higher as it explicitly includes contributions of pure densit=
ies, while these are implicit in the case of=20
Error rendering macro: No valid license found for LaTeX Math addon
. By doing both optimizations we aim to determine whether there is an=
y practical difference between the two.
The
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
without=20
Error rendering macro: No valid license found for LaTeX Math addon
study will enable us to explore whether the pure densities contribut=
e significantly to constraining the optimization, or whether including=20
Error rendering macro: No valid license found for LaTeX Math addon
by itself would be sufficient. If this is the case:
-
optimizations would require less experimental data as we avoid needing p=
ure densities.
-
we would be able to use
Error rendering macro: No valid license found for LaTeX Math addon
in place of=20
Error rendering macro: No valid license found for LaTeX Math addon
for which there is less data available.
-
optimizations would require less simulations.
Initially we plan to include 10 pairs of molecules in the training set (=
~ 2 different esters for each different alcohol to include), and 3 differen=
t composition (25% 50% and 75%) per pair of molecules (~60 data points in t=
otal). This may be expanded if it is found that this set is too small to of=
fer any significant insight.
C=
hosen Alcohol-Ester Data Set
Pure + Mixtur=
e Data
We will conduct three sets of independent optimizations on:
-
a training set which includes only binary
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
data points
-
a training set which includes only binary
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
data points
-
a training set which includes only binary
Error rendering macro: No valid license found for LaTeX Math addon
+=20
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
data points
Note: We may not end up conducting a number of these studies dependi=
ng on the results of the Only Mixture Data studies.
We aim to use these sub-studies to explore whether pure data is needed t=
o sufficiently constrain the optimization when mixture data is included, wi=
th a focus on whether it is important to include
Error rendering macro: No valid license found for LaTeX Math addon
to constrain cohesive energies, or whether=20
Error rendering macro: No valid license found for LaTeX Math addon
is sufficient.
The training set for these studies would be the union of the training se=
ts used in the Only Pure Data and Only Mixture Data studi=
es.
C=
hosen Alcohol-Ester Data Set
I=
nitial Benchmark Set Selection
The initial benchmark set is expected to be modest in size (~50 pure dat=
a points, ~120 mixture data points) so as to be able to rapidly assess the =
performance of optimisations, but will be complemented by further sets depe=
nding on the outcomes of the initial set.
-
We will be less systematic in the selection of those system=
s to include in the benchmark set, opting instead to aim to curate a set wh=
ich has a diverse set of molecules with pure density, enthalpy of vaporization data points, and binary enthalpy of mixing, =
of , and binary mass density data po=
ints, without enforcing that substances must have all such be available to =
be included (as was the case for the training sets).
-
In order to test how well each of the different produced force fields ge=
neralise, we initially aim to include binary mixtures of alcohols and alcoh=
ols, alcohols and esters (/ acids), and esters (/acids) and esters (/acids)=
.
-
In an attempt to ensure that we are testing the performance of the refit=
parameters, rather than the full Parsley 1.0.0 force field, we will exclud=
e any
again, this will likely be relaxed in future benchmark sets.
-
This set will only contain mixtures whereby neither of the components ap=
pear in the training set. Future data sets may then be complement with mixt=
ures which do partially contain training data to further explore interestin=
g results highlighted by this initial set.
Chosen Alcohol-Ester Study Benchmark Set
The results shown in the page where generated against a data set which c=
ontained
-
~110 pure data points (~60:40 split of
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
, ambient condtions) where none of the substances appeared in the tes=
t set.
-
~320 mixture data points (with roughly equal numbers of
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
data points, ambient conditions, three compositions (~25%, ~50%, ~75=
%) per pair). This included mixtures where neither component appeared in th=
e test set, and alcohol-alcohol and ester-ester mixtures where both compone=
nts appeared in the test set (the train set only included alcohol-ester mix=
tures)
Extended =
Benchmark Set
Similar to the selection of the benchmark set chosen for the initial alc=
ohol and ester study, when selecting the extended benchmark set we opted to=
be less systematic in choosing the individual substances (namely, we did n=
ot require that each substance had available all of the properties of inter=
est) and instead, focused on trying to choose as diverse a set as was possi=
ble (given a limited diversity of the available data) which maximally exerc=
ised the refit parameters.
We endeavoured to select a set which:
-
did not contain exactly on substances which were trained on, but did all=
ow substances where individual components did appear in the training set (e=
.g if the training set included a mixture of pentanol and hexane, the test =
set would be allowed to contain pentanol and heptane and hexanol and hexane=
but not pentanol and hexane).
-
contain substances as distinct as possible from the training set, and fr=
om other molecules in the test set.
The test set is to contain
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
and=20
Error rendering macro: No valid license found for LaTeX Math addon
data points for substances (both pure and binary) composed only of a=
lkanes, alcohols, ethers, esters and ketones.
The selection of the benchmark set proceeds as follows:
-
Filter out all of the data points which were measured for:
-
substances that were included in the training set.
-
molecules not composed of C, O and H.
-
molecules with undefined stereochemistry.
-
long chain ethers or alkanes (these are difficult to pack into a simulat=
ion box and in general take longer to simulate).
-
molecules which contain 1, 3 di-carbonyl functionality where at least on=
e of the carbonyl groups was a ketone. Substances containing such will like=
ly contain mixtures of keto-enol tautomers, but the ratio in which they wil=
l be present isn=E2=80=99t recorded by ThermoML.
-
Cluster all of the available
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
data points based on the chemical environments present in the substa=
nces that the data was measured for (e.g. cluster all ether-ester data, ket=
one-alcohol data etc.)
-
For each type of property (e.g.
Error rendering macro: No valid license found for LaTeX Math addon
) and each pair of environments (e.g. alcohol-ester):
-
Select the substance which is =E2=80=98most distinct=E2=80=99 from the c=
urrently selected training set and the molecules selected for the test set =
of this property and environment.
-
Repeat a. until either 10 substances have been selected, or there are no=
other substances to select from.
Defining =E2=80=98most distinct=E2=80=99
To determine how similar a substance is to another set of substances, we=
defined a distance metric based on a substance finger print.
For any binary substance composed of components a
and b
(represented as [a
, b
]), the substance=
=E2=80=99s finger print is defined as [f(a)
, f(b)
=
] where f(x)
is a function which computes the OpenEye Tr=
ee
finger print of a molecule x
.
The distance between any two substances ([a_1
, b_1 ], [a_2
, b_2
]) is then defined as
min(d(f(a_1), f(a_2)) + d(f(b_1), f(b_2)),
d(f(a=
_1), f(b_1)) + d(f(a_2), f(b_2)))
where d
is the OETanimoto
distance between two =
fingerprints.
The distance between a given substance mixture_a
and a set =
of mixtures mixture_set
is then computed by:
-
Computing the distance between mixture_a
and each mixture i=
n mixture_set
-
Remove the mixture from mixture_set
which is closest to mixture_a and adding the distance between the two to the total di=
stance.
-
Repeating step 2 until all mixtures have been removed from the mix=
ture_set
.
The most distinct molecule from the unselected set is thus chosen by:
-
Selecting the molecule which is 'furthest' away from both the training s=
et and the currently selected test set (which starts off empty), where the =
distance is defined as:
sqrt(compute_distance_with_set(unselected_substance, training_set)=
** 2 +
compute_distance_with_set(unselected_substance, te=
st_set) ** 2)
-
Moving the selected molecule from the unselected set into the test set.<=
/p>
-
Repeat steps 1 and two until either the target number of molecules have<=
br>
been selected, or there are no more unselected molecules to choose from.
The pure substances to include for
Error rendering macro: No valid license found for LaTeX Math addon
,=20
Error rendering macro: No valid license found for LaTeX Math addon
, where then mainly chosen as those components chosen as part of the =
mixture properties where available, and components close to those where not=
possible.
Chosen Set
The final set contains ~48 pure data points and ~ 900 mixture data point=
s.
Questions we want to answe=
r via benchmarking/what benchmark sets can we use to achieve this?
-
In general, to what extent are LJ parameters trained on mixture =
data transferable to other sets of mixture?
-
The first mixture benchmark set (MB1), consisting of heat of va=
porization, mixture density, and excess molar volume of alcohol/ester, alco=
hol/alcohol, alcohol/acid, ester/acid, acid/acid and alcohol/ether mixtures=
that do not have any commonality to the mixtures that we trained =
on.
-
If we train LJ parameters on one type of mixture, how well do th=
ose parameters transfer to other types of mixture?
-
How do benchmarked mixture properties vary as a function of comp=
osition?
-
Through benchmarking, can we identify the extent that transferability af=
fects mixture properties as a function of composition? For example, if we t=
est against alcohol/ether mixtures and we see worse performance as the ethe=
r concentration increases, then maybe the alcohol parameters are good, but =
the ester parameters don=E2=80=99t transfer well to ethers.
-
MB1 will allow us to explore this, since we should have good coverage in=
a range of xA=3D0.2-0.8. We should also consider adding some points in the=
0.9-0.95 mole fraction region, to check on that behavior. This could eithe=
r be as a separate set, or just something we break out in MB1
-
Can we identify a =E2=80=9Cspectrum of transferability=E2=80=9D=
for parameters in mixtures.
-
For example, within a benchmark set composed of mixtures that have at le=
ast one component in the training set (MB2), there are a large number of mi=
xture with tert-butanol. Assuming that tert-butanol is parameterized reason=
ably well, by examining the mixture properties and chemical similarity of t=
he other moieties in these tert-butanol sets, can we identify how different=
a mixture can be before the transferability starts to degrade?
-
To what extent are mixture properties transferable from training=
on pure properties only? To what extent are pure properties transferable f=
rom training on mixture properties only?
-
Can we get a sense of the correlation between performance on mixture pro=
perties and pure properties (does low error in pure density imply low error=
in mixture density)? By benchmarking sets parameterized with only pure and=
only mixture data on MB1 and PB1 (the basic pure data benchmark set), we c=
an analyze this.
-
How do mixtures trained on mixture densities perform on excess m=
olar volumes?
-
By looking at the subset of MB1 that includes excess molar volumes, can =
we accurately reproduce these by training on mixture densities? If we can=
=E2=80=99t, that may point to excess molar volumes not being very useful fo=
r us.
References
[1] Majer, V., Svoboda, V, Enthalpies of Vaporization of Organic Com=
pounds (IUPAC Chemical Data)
------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/175b9007df1c2f2363c373d83ee04c0bc42afe31dd1a33effa20eeacffe304df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==
------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/81d849d2e2172373b19d1a9b08eb39e3f7860a0a6b3f4dd80193ab0d78598327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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/bc256813a9c03d98516d7b7df6a402daeb1260fb2c72b212d457546580a30119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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/1a7ca2f200ebca9cc1e52bd14d2fb7446388c416c8f06dc96d2775bd74aa3d18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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/c5ddfd7d76b4cb67ac5a806e34df4d9942b8e32f1e6fd9c879d4a96ab4da78eb
iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6CAMAAAC/MqoPAAADAFBMVEX19fXv7+98fHx1dXV9fX23
t7eenp5wcHDn5+f09PTz8/Pd3d2SkpLY2Njt7e3Q0NCioqJycnKqqqq7u7uurq6CgoKGhobOzs7D
w8PR0dGNjY3Hx8fj4+PGxsbS0tKoqKgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAABYhwFnAAAETklEQVR4Xu3cDVObSBjA8S0BF5MQo/GtZ+3tfdv7ltfp3Ux7tlat
MTE6CcdCWMhColgD5vL/TTXw7LN0HzeFqWwQAgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAA2wDs7sB7+bNayY0tMHefejm0w3/V8O7aM7znPzt0AO54dWcXbsSNr4diBtXj2uz3WmtmRDSbt
wGoV01+onll/k7a49Er/CF/MndqR3unOxDk8Cid2g1ZMX4eGSg9GrfFDKKbDoKz2QvoGs89bJ/J9
svFeBostMTt9k1m19NyP6eZeq5dvSdRTeiOnuf3+53TzZm8/31In1w7UYTTOtieNjKA+1ju4lftP
U0+faK32/+8bftcNs52fjc16E6W/EZS+jSh9GzVWej0XsFUaK715lL6NKH0bUfo2ovRtROnNabfb
dqgmjZSui32c30lueSOx20j1TZQ+vvGjye4nO8FMiPBmMaEeTZQu2nti1L86Ffo38pcjIfYamfVG
bjyFzr342W51nMOrIIxK98aLd9TrufHUSOnd2/ajeBBB6865fRSiM24v3nmrp/R62L+XOJe55TK+
c5btxOz0TVaoZeB20s1ADvItWiF9gxVrOXf6J/7urn/Sd+05L0vfXCW19LyuK/fdrleycq8kfWNV
rKVi+gs1cl1/Gyh9zaaVln769VzW6yndqVTMtKZB2YG1cMIqy4NrKr3k0rIO27soHAAAAAAAAADw
NnhS2aElwVXUC/rUQNmBBbJ4h31JcBVVtU89NzpWu/9hR8SS4BNe0ue51KGU8lBvJLvRnwMZCjGI
wt1sBVgQ7cbLROZxpZlWk/y7DOWhiltLu5iMQmvMDEYc5A60Lkqe987lab502RHiTJ71Apk9TUbu
+FFaLp6kJ0xwEB9MJa2lXUxGoVUzgznNH2hdlP7JezJfuv4QvjyJvn3I1kLID/PXNK5MUy6YTKOa
l17WxWQUWjUzmDjNU1VLr/g54rvoq5X7HLIQf+tvX6OvP+7fpbHBt6PQ/6cYT5igPtjd/IEN5V3S
jOWt8WDijSS2NkrfKvbTaWyr+UY6KcbHnZZ+W5q4yrWZYLx2zlfz1rIuJqPQGmekg1k80LNVPMPr
1W56mcAXPYbswVL2j/zzw9TVU5PG/8ovgjXJ+mBm+ZzdJWYylrbGaxbMRiX2oFfr//hNHI+6YyGG
Z+L4JrgW/esofPR9f+buzczfLvthezCcZvE/+7PHtNEE+8PoYFfzYxS66KDJKLQKdZ0NJk4bpYN5
toqzHlxMLjqX0YSH3yYX3TT69fg2DIfZ8zb2h+FEP43AxGdXd6qQfHl6cXPR+bKki2YySlvNYC47
UVrZQ15ek7IDv+zsyTVySzOUHaio4hn+VTkfrne/L1wubE9n/IJXLV0lL5/yMUMlL5+yyMG/YhK6
D1mg4OkMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEC5/wAcwBtmn7A7cgAAAABJRU5ErkJg
gg==
------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/e2e1cb2cedf77226e4345dac1b4d1d624e3c4b6b13b3f67ef7bdf4870fa396f0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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/f4d4e3c9e497de543037b8607e664b7788d2fb05b7568d03c8dc95b538905994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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/a8bb1d5579ac80401aee3175df5893168a4649e8203b378fe55d90aa984d85d4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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/12332c6ef002c2bd7d07b7cd0d132a3399cf30ecb66628e68ea6ba108838e1df
iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6CAMAAAC/MqoPAAADAFBMVEX19fXv7+98fHx1dXV9fX23
t7eenp5wcHDn5+f09PTz8/Pd3d2SkpLY2Njt7e3Q0NCioqJycnKqqqq7u7uurq6CgoKGhobOzs7D
w8PR0dGNjY3Hx8fj4+PGxsbS0tKoqKgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAABYhwFnAAAFIUlEQVR4Xu3cC3OiOhQH8AhCqApqtdvuqt3c7/+hrrPtTl+3t9Ot
1Vof3ARIiIH1ameEsv5/M+VxcpLhAMVpQQgBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAACogJoZOAxvvbbN2G+sLOvNjFWYV3c8M/Y7nmPtnFsBrmNGtnFcM3IQlhk4iJ3P
9oi9NiMVRs3Adnumf1AxR/1TOuLS9/ol/LD6yowEF+7c6p+Fc7NByKYfQkml+1N79h6S1cTPqz2T
XmHmdeucfo0XvlJ/syVipleZUUtQv5SLbTvQW2LFlF7KZa7b+SEXn9tdvaVIdTNQhOksXZ6XsgXF
Mc5gW/ujKRAXWqP9zz3hT+phuvKrtKNeRumfBEo/Rij9GJVWejEfYNuUVnr5UPoxQunHCKUfI5R+
jFB6eRqNhhkqSCmli2IXyZ1k25mSk1KqL6P02bPHD3YnXvHXhITPmwnFKKN00miTaefpgoj/yD9O
CWmXctRLufEUWm/kV8NuWv0nP+SlO7PNO+rF3HgqpfTWS2NB3olvv1ovC0Kas8bmnbdiSi+G+X+J
EdUel/GsQboSMdOrLFNLr96Uiz7t6S1CJr3CsrWMrM65d3LinXfq5jHPS6+unFoCp1Wn3XrLyXly
Lye9svasZc/0Dyrlc/1zQOkHttrr0U+vmI/1Ykq39ipmVdBGmYGDsMJ9Hg8uqPScj5ZDON6HwgEA
AAAAAAAAAABAx8yAjpmBcjAzoGNmIIMR4lAm14r5b39RmBnIsPpjtaiFtxibgU9obAbyvP1rRjjW
o5Rqr4Rh3/n6oM8nTb4S0FMeO6Xx3ZphNK+lT8SIvq1GmiTW+younhrheuk8B5NTdkrDtKfEg7Qv
cmSD2l45JiOMC6NNC+JNY2LzxXbI7iIjHVNi9CIY2untIUb94BuNJmLYJh2RczpMGqPx+uoRgAEd
BD51VVKP9oLLbhon1PWCEU3nOZicMrGvVc/EBR3xjkxrUNsrxxRdeWa8++NvyrKo14XWXWRksDYR
hzNd9wnxokk87IgO6LlsdEQeVS/aiRpE3yRJtqi43Gdq32UxOWXie/2qZyI6VRymNajtlWOyeIwR
PeGx+K0ILOolcmR3kZHQvke84D/XbKzWl/w3I5rEsavvY/dOtbnD6+HDUuXe8p+/3moqyRaDafHe
w1noXRM13+pKTGRP6ZUkD/mpBrm9xphXtDFrLm+0XuJ706p7HqZN1ZKciHkr1F6QdOYS90ytpQcz
TpIXgTR+6drR6SvnWUxMGixZME+PaESPaQ1MTZMxWRLjR7mVnHUs6iWOuuweZcR2vMJzvUWnll6g
3BqpaX3lDpVJ8lECtaN/vK/q4hDKedaNqCl9V5V5iMRzdtGoZoM+5t/iuuiQwUKOo3qphdTOpTcn
/efORD3o95O4RJ3+pHvb97weVUlfLH6Zs9M4/13zAnFllHOJpT/Lm2EwUnfWVc9Ea8KvU2JjzYaN
Mb2A1z4N/3GmJB436tXSumt2LT1Yhj/Jnb9U7xMJ59qrB26/vIThpKuSrtaT+V1XxfkGT8K5eD+B
nOdwwof5fUuuqZ6Jx+b98714kYvZsDHm+umV8R1AkgfO+Qff/fy++ah1/8P11PFkWjRj16NeIcPJ
NzOUK3vysXg21mMpFs/GeWu7Y/FsrMfysXg21mPbsZvW/316AgAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAcgf8AZ28TFX7LVdIAAAAASUVORK5CYII=
------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/3dcc1ab4019ad0ff9f62dcaa67b65990d2b457b098be372bc1f43074861ce80a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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/328c2aeec849df4437d41065d6759721b160f13c592c3f2182b741fa2f5df59b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=
------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/d6f2c2f80f77cc7c64b9feb08629bb3f09ff21dc258f64b51ceee064ed3d7adb
iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6CAMAAAC/MqoPAAADAFBMVEX19fXv7+98fHx1dXV9fX23
t7eenp5wcHDn5+f09PTz8/Pd3d2SkpLY2Njt7e3Q0NCioqJycnKqqqq7u7uurq6CgoKGhobOzs7D
w8PR0dGNjY3Hx8fj4+PGxsbS0tKoqKgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAABYhwFnAAAFNElEQVR4Xu3cDVfiOBQG4NDSphRaQVB0ACf7/3/UcEbnqLge1xFB
5KOb9CMNaWXAs7SyvM9IaW9uCBdoOWNjCQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAADgAFT2wH85qZeqxDywN402PHTCnajl67COOZWydewBsS49sYtl6ZC8MPbAXW3/a
Q+ZKjxwwqgc22zH9k4p517+kIy59p53w06pLPeJf2DOjcxbM9AYhm74PJZXuTczpe0CWYy+v9kz6
AdOPW116Ga1cUm+9JaSnHzKtFr96layemL7aEimm9FIOc63mz2T1+aSlthSpqgeKMJmm67NSnkFx
tE+wqfynyRcHWq39//uBr1WDdON3ae96GaV/ESj9GKH0Y1Ra6cV8gW1SWunlQ+nHCKUfI5R+jFD6
MULp5XFdVw8VpJTSRbHz+EyyaU1IrZTqyyh9+uzwN7sZbXgrQoLn9YRilFE6cU/IpPl0QcRv5B8n
hJyU8q6XcuIpMN7Ib9esG50nL+ClW9P1M+rFnHgqpfTGizsn78QzX42XOSH1qbt+5q2Y0ouh/15i
QJXpMo7RSzdCevohy9TSrtaTVY+21RYhk37AsrUMjGbXqdWcbrOqv+d56YcrpxbfalRpq9qwcmbu
5aQfrB1r2TH9k0r5Xv8aUPqeLXea+ukU87VeTOnGTsUsC3pSemAvjGCX6cEFlZ7z1bIPxzspHAAA
AAAAAAAAAADWMT2gYh8G5Mo2mB7YAdMDKqYH/qiY3/YXg+mBzbYufagHpKEeKMVQD/zRWultSqly
URj2nW/3OnxR5xs+PeWxUyrP14iGjkjjP0lPr0Vpi9+zUxqEmX46a0aERH44TEObL8aSpeiZTcn0
TUfk92JKChP/2PqgIqeTpPTDpoo6iyfF6IXfN9MTRIx6/jcaLsRD1+mAdGk/bR34A3oRPd+kJx1U
/PMzEaiT6KWSf7J6Eebz5B7t+R7Vrj3DkqXomUnJ9k1HtB3eFHXlmeqgbdr2r1oyJXztOvnTFtgJ
X/TTNuYR4oSL6KEHtEe7aauY/WPFg6o9fRG7Euk1Pmx8eQK+Fubz5PAxlGFCLFmKnpmUbF85YvJe
sOgx1EFpfCGgOEU8Vxkj2t+vz/nthg3l9oKQt3ARxa6/D+172Uhe+c2M/yY56Vm3J5fkB/9kXfMf
6k7ri9v1fLFyx29/vYmPX55rsdBTsn2TEdsPZ4FzIxPXBjVFEklSFnb/pv+wkKkqpizlWrIQ941A
+ZgysdPEn4cwSSzpt75bSQL8ZW6kL3K4kzkiR+4zCiYWLotX9JRsXyaXV7YZ7gHZQeVuHaec2cQ+
i0NkhyM81543K8ocNzHzLTNlYHwzkU/bIr25cvEpmZ93uvlW9EqT9ZQNfX++L6uVcO2HOC6qgybP
Lk6xK6Si1LtD6fVx57k5llP9yJgfeoyGkiC8+d1Rsj4J/rYmsqUR5vOV1l3Hcdpix2PpbXHb9wfy
vHqaEsnpm6Btxw+P/fxj4bvpoIyQc4Mf5sSRME75RWyi7LDbl+4vgl/k3lvIK4p4o9mo/qim8NEr
s39q6RaJZ34Lj/XR80hciuXu/CUIxtrVOazgYTaSr6OesqFvaxzM4isfrJ5emTro9Wo8u28pKcFM
uVzCfrW3f2H/O6UMquvrR6sibD9odIBYx6K7oRpLsehuqMZysduG2B1YtDVUWrbGoruhGtssHhQA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA4Oj9CwK+CNA8eDcwAAAAAElFTkSu
QmCC
------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/3cb9b69be5483294cf8934142ff1ae359ae0a7acff227633d12c3f387d34d999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=
------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/d59ea144a5c3eb7d72d1c4580e13edc9be1565626064702191ba89d3c6b6df6b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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/f39d15be55aa58ce3cdba1ae17c0060c770ea1bd853f691a7ac1f1f3d6811dc4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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/a94ae4da072aeb1b3950597c17b86c39315d5c9d346da3702049d4522c0535cc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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/b6fc05c5a14743ea940c3ec598a33e0f423b3572bb4806dbdb73b82cfb583aa3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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/b4a2f652c8bbb6e67e951c56c5faf9e3120fe1555098c13118d2b980edb1764b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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/2a83b82150bae20da2eaea1049557fc01f644ce24a013fa08c38fee03c24fe87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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/5760f663b1d0523a70123b3cec6571528976c9888ef0a69d19cd84d5ab488c2c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==
------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/17fc00db8f60bb450dc53da84df7eb52e941e86b52bf17ee2562cfe67db87dbb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==
------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/28ca526694855869299bed2b5d49dbf7e5deb5c20fd93350dc27f5dd08452605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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/45317e348d303acb8e22a34df977908da0b7ecee32d26381fff7b24668b4ce17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------=_Part_0_652564110.1711627128230
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/8d04dc4a33c27ec8458182abc3888beb01f44d31da398fd9a612cb43792810a8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------=_Part_0_652564110.1711627128230--