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14
,
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.
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,
Octo
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20
25
,
p
p
.
3
4
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r
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No
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1
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1
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id
1.
I
NT
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D
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Du
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p
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[
1
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[
2
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I
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[
9
]
–
[
1
1
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.
P
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[
1
2
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–
[
1
4
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
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I
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t J Ar
tif
I
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tell
,
Vo
l.
14
,
No
.
5
,
Octo
b
er
2
0
2
5
:
3
4
8
3
-
3
4
9
2
3484
T
h
ese
m
e
th
o
d
s
ar
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s
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l
lu
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1
6
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an
d
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f
i
tn
ess
f
u
n
ctio
n
u
s
ed
in
th
is
s
tu
d
y
,
wh
er
e
C
is
th
e
p
r
ice
o
f
ea
ch
f
o
o
d
i
n
g
r
ed
ie
n
t.
(
x
)
=
0
.
997
×
(
pe
n
a
l
ty
)
+
0
.
003
×
∑
C
x
(
4
)
T
h
e
weig
h
t
v
alu
es
o
n
th
e
p
en
alty
v
alu
e
an
d
th
e
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s
t
o
f
ea
ch
f
o
o
d
ar
e
n
o
t
co
m
p
ar
a
b
le.
Ho
wev
er
,
th
e
p
r
ev
io
u
s
s
tu
d
y
m
ad
e
a
p
r
o
p
o
r
tio
n
al
ef
f
o
r
t
b
y
ass
ig
n
in
g
weig
h
ts
to
th
e
p
en
alty
v
al
u
e
an
d
c
o
s
t
o
f
0
.
9
9
7
an
d
0
.
0
0
3
,
r
esp
ec
tiv
ely
.
GA
is
a
h
eu
r
is
tic
s
ea
r
ch
tech
n
iq
u
e
in
s
p
ir
e
d
b
y
th
e
p
r
o
ce
s
s
o
f
b
io
lo
g
ical
e
v
o
lu
tio
n
.
T
h
e
r
e
ar
e
s
ix
s
tep
s
to
im
p
lem
en
t
GA:
ch
r
o
m
o
s
o
m
e
r
ep
r
esen
tatio
n
,
in
itial
p
o
p
u
latio
n
,
f
itn
ess
f
u
n
ctio
n
,
s
elec
tio
n
,
cr
o
s
s
o
v
er
,
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
14
,
No
.
5
,
Octo
b
er
2
0
2
5
:
3
4
8
3
-
3
4
9
2
3486
an
d
m
u
tatio
n
.
T
h
e
s
elec
tio
n
p
r
o
ce
s
s
is
ca
r
r
ied
o
u
t
to
s
elec
t
ch
r
o
m
o
s
o
m
es
th
at
will
b
e
u
s
ed
to
p
r
o
d
u
ce
o
f
f
s
p
r
in
g
.
T
h
is
s
elec
tio
n
is
b
ased
o
n
f
itn
ess
v
alu
e
u
s
in
g
th
e
E
liti
s
m
s
elec
t
io
n
m
eth
o
d
s
h
o
wn
in
(
5
)
.
Ρ
(
+
1
)
=
{
x
1
,
…
,
x
Ρ
}
∪
{
x
Ρ
+
1
,
x
Ρ
+
2
,
…
,
x
N
}
(
5
)
Af
ter
war
d
,
a
s
in
g
le
-
p
o
in
t
c
r
o
s
s
o
v
er
p
r
o
ce
s
s
is
p
er
f
o
r
m
e
d
to
p
r
o
d
u
ce
o
f
f
s
p
r
in
g
f
r
o
m
th
e
two
p
a
r
en
t
ch
r
o
m
o
s
o
m
es b
y
co
m
b
in
in
g
p
ar
ts
o
f
th
e
two
ch
r
o
m
o
s
o
m
es,
as sh
o
wn
in
(
6
)
an
d
(
7
)
.
x
=
[
,
,
,
,
…
,
,
]
(
6
)
x
=
[
,
,
,
,
…
,
,
]
(
7
)
Me
an
wh
ile,
th
e
m
u
tatio
n
p
r
o
ce
s
s
is
ca
r
r
ied
o
u
t
t
o
m
ai
n
tain
g
e
n
etic
d
i
v
er
s
ity
in
th
e
p
o
p
u
latio
n
b
y
r
an
d
o
m
ly
ch
an
g
in
g
th
e
v
al
u
es o
f
s
o
m
e
v
ar
iab
les in
th
e
ch
r
o
m
o
s
o
m
es s
h
o
wn
in
(
8
)
.
x
′
=
[
,
,
…
,
ℎ
,
′
,
,
]
(
8
)
PS
O
is
a
p
o
p
u
latio
n
-
b
ased
o
p
tim
izatio
n
alg
o
r
ith
m
i
n
s
p
ir
e
d
b
y
th
e
s
o
cial
b
eh
a
v
io
r
o
f
b
ir
d
s
o
r
f
is
h
s
ea
r
ch
in
g
f
o
r
f
o
o
d
.
E
ac
h
p
ar
t
icle
in
PS
O
r
ep
r
esen
ts
a
p
o
ten
tial
s
o
lu
tio
n
b
y
u
p
d
atin
g
t
h
e
-
th
p
ar
ticle
at
th
e
-
th
iter
atio
n
.
In
(
9
)
an
d
(
1
0
)
c
alcu
late
p
ar
ticle
p
o
s
itio
n
an
d
v
elo
city
.
x
(
)
=
[
,
(
)
,
…
,
,
(
)
]
(
9
)
v
(
)
=
[
,
(
)
,
…
,
,
(
)
]
(
1
0
)
Fu
r
th
er
m
o
r
e
,
f
o
r
v
elo
city
an
d
p
o
s
itio
n
u
p
d
ates,
in
(
1
1
)
a
n
d
(
1
2
)
a
r
e
s
h
o
wn
wh
e
r
e
is
t
h
e
in
er
tia
f
ac
to
r
,
1
an
d
2
ar
e
th
e
ac
ce
ler
atio
n
co
ef
f
icien
ts
f
o
r
co
g
n
itiv
e
an
d
s
o
cial
in
f
lu
en
ce
s
,
1
an
d
2
r
esp
ec
tiv
ely
.
v
(
+
1
)
=
v
(
)
+
1
1
(
p
−
x
(
)
)
+
2
2
(
g
−
x
(
)
)
(
1
1
)
x
(
+
1
)
=
x
(
)
+
v
(
+
1
)
(
1
2
)
Ad
d
itio
n
ally
,
W
O
[
2
1
]
a
n
d
DSA
[
2
2
]
a
r
e
alg
o
r
ith
m
s
th
at
in
co
r
p
o
r
ate
elem
en
ts
f
r
o
m
PS
O.
W
O
ad
d
s
th
e
s
o
cial
b
e
h
av
io
r
an
d
f
ee
d
i
n
g
b
eh
av
io
r
o
f
walr
u
s
es
[
2
3
]
.
Me
an
wh
ile,
DSA
m
o
d
if
ies
s
o
m
e
asp
ec
ts
th
at
r
ef
lect
th
e
u
n
i
q
u
e
b
e
h
av
io
r
o
f
d
u
ck
s
.
T
h
er
ef
o
r
e,
th
e
m
at
h
e
m
atica
l
ca
lcu
latio
n
s
ar
e
s
im
ilar
to
PS
O,
as
s
h
o
wn
b
y
(
9
)
t
o
(
1
2
)
.
2
.
4
.
P
a
ra
m
et
er
inp
ut
T
o
ex
ec
u
te
th
e
m
eth
o
d
,
in
itialize
th
e
in
p
u
t
p
ar
am
eter
s
.
T
h
e
in
p
u
t
p
ar
a
m
eter
s
h
elp
co
n
tr
o
l
th
e
alg
o
r
ith
m
'
s
b
eh
av
io
r
an
d
d
e
ter
m
in
e
th
e
r
esu
ltin
g
s
o
lu
tio
n
'
s
q
u
ality
[
2
4
]
,
[
2
5
]
.
All
f
o
u
r
m
et
h
o
d
s
a
r
e
p
o
p
u
latio
n
-
b
ased
.
T
h
u
s
,
all
m
eth
o
d
s
u
s
e
th
e
s
am
e
p
o
p
u
latio
n
s
ize
an
d
n
u
m
b
er
o
f
it
er
atio
n
s
,
1
0
0
.
T
h
is
co
n
d
itio
n
s
tr
iv
es
f
o
r
ea
ch
m
et
h
o
d
to
o
p
e
r
ate
u
n
d
e
r
th
e
s
am
e
co
n
d
itio
n
s
.
T
h
is
s
tan
d
ar
d
izatio
n
is
ess
en
tial
f
o
r
a
f
air
co
m
p
ar
is
o
n
o
f
t
h
e
m
eth
o
d
'
s
p
er
f
o
r
m
an
ce
i
n
f
in
d
in
g
d
ail
y
m
en
u
s
f
o
r
p
r
e
g
n
an
t
wo
m
en
b
ased
o
n
n
u
t
r
itio
n
al
n
ee
d
s
an
d
co
s
t
co
n
s
tr
ain
ts
.
I
n
ad
d
itio
n
,
s
o
m
e
p
ar
a
m
eter
s
wer
e
ch
o
s
en
b
ased
o
n
th
eir
ef
f
ec
t
iv
en
ess
in
p
r
ev
i
o
u
s
s
tu
d
ies
[
1
8
]
,
[
2
6
]
,
[
2
7
]
th
at
h
av
e
f
o
u
n
d
o
p
tim
al
s
o
lu
tio
n
s
.
T
h
ese
p
ar
am
eter
s
wer
e
ch
o
s
en
to
b
ala
n
ce
ex
p
lo
r
atio
n
an
d
e
x
p
lo
itatio
n
to
f
ac
ilit
ate
ef
f
icien
t
co
n
v
e
r
g
en
ce
to
t
h
e
o
p
tim
al
s
o
lu
ti
o
n
[
2
8
]
,
[
2
9
]
.
T
h
e
in
itializatio
n
o
f
in
p
u
t p
ar
am
et
er
s
u
s
ed
b
y
GA,
PS
O,
DSA,
an
d
W
O
ar
e
s
h
o
wn
in
T
ab
le
3
.
2
.
5
.
E
v
a
lua
t
i
o
n
T
h
e
p
e
r
f
o
r
m
a
n
c
e
o
f
t
h
e
f
o
u
r
m
e
t
h
o
d
s
w
as
e
v
a
l
u
a
t
e
d
t
o
r
e
c
o
m
m
e
n
d
t
h
e
b
es
t
m
et
h
o
d
f
o
r
s
o
l
v
in
g
s
i
m
il
a
r
p
r
o
b
l
e
m
s
.
T
h
e
e
v
al
u
a
t
i
o
n
u
s
ed
a
o
n
e
-
w
a
y
a
n
al
y
s
is
o
f
v
a
r
ia
n
c
e
(
A
NO
V
A
)
a
n
d
T
u
k
e
y
'
s
h
o
n
e
s
t
l
y
s
i
g
n
i
f
i
ca
n
t
d
i
f
f
e
r
e
n
c
e
(
H
S
D
)
t
es
t
i
n
t
h
is
s
tu
d
y
.
A
N
O
V
A
is
u
s
e
d
t
o
s
e
e
i
f
t
h
e
r
e
i
s
a
s
i
g
n
i
f
i
c
a
n
t
d
i
f
f
e
r
e
n
ce
i
n
[
3
0
]
t
h
e
f
i
t
n
e
s
s
r
e
s
u
l
ts
p
r
o
d
u
c
e
d
b
y
G
A
,
P
S
O
,
D
S
A
,
a
n
d
W
O
.
M
e
a
n
w
h
i
l
e
,
T
u
k
e
y
'
s
H
SD
t
es
t
t
o
d
e
t
e
r
m
i
n
e
w
h
i
c
h
m
e
t
h
o
d
s
a
r
e
d
i
f
f
e
r
e
n
t
f
r
o
m
e
a
c
h
o
t
h
e
r
[
3
1
]
.
T
h
i
s
c
al
c
u
l
a
ti
o
n
a
s
s
u
m
es
(
0
)
t
h
a
t
th
e
r
e
i
s
n
o
d
i
f
f
e
r
e
n
c
e
i
n
a
v
e
r
a
g
e
p
e
r
f
o
r
m
a
n
c
e
b
e
t
w
e
e
n
GA
,
PS
O
,
DS
A
,
a
n
d
W
O
.
T
h
e
T
u
k
e
y
'
s
HS
D
t
es
t
s
t
ag
e
c
a
n
b
e
d
o
n
e
i
f
t
h
e
p
-
v
a
l
u
e
<
∝
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
A
u
to
ma
ted
men
u
p
la
n
n
in
g
fo
r
p
r
eg
n
a
n
cy
b
a
s
ed
o
n
n
u
tr
itio
n
a
n
d
b
u
d
g
et
u
s
in
g
…
(
Diva
K
u
r
n
ia
n
in
g
tya
s
)
3487
T
ab
le
3
.
Par
am
eter
i
n
p
u
t
M
e
t
h
o
d
s
P
a
r
a
me
t
e
r
GA
P
o
p
u
l
a
t
i
o
n
s
i
z
e
1
0
0
I
t
e
r
a
t
i
o
n
n
u
m
b
e
r
1
0
0
C
r
o
ss
o
v
e
r
r
a
t
e
0
.
8
M
u
t
a
t
i
o
n
r
a
t
e
0
.
0
1
PSO
S
w
a
r
m si
z
e
1
0
0
I
t
e
r
a
t
i
o
n
n
u
m
b
e
r
1
0
0
I
n
e
r
t
i
a
w
e
i
g
h
t
0
.
5
C
o
g
n
i
t
i
v
e
c
o
e
f
f
i
c
i
e
n
t
1
.
5
S
o
c
i
a
l
c
o
e
f
f
i
c
i
e
n
t
1
.
5
D
S
A
S
w
a
r
m si
z
e
1
0
0
I
t
e
r
a
t
i
o
n
n
u
m
b
e
r
1
0
0
A
t
t
r
a
c
t
i
o
n
f
a
c
t
o
r
0
.
7
C
o
g
n
i
t
i
v
e
c
o
e
f
f
i
c
i
e
n
t
0
.
3
WO
S
w
a
r
m si
z
e
1
0
0
I
t
e
r
a
t
i
o
n
n
u
m
b
e
r
1
0
0
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
B
est
mo
del pa
ra
m
et
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n
d
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Fi
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e
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y
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T
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A
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est
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r
o
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d
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u
t
ati
o
n
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al
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es
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0
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7
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n
d
0
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3
,
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O
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d
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est
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n
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a
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n
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ased
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5
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ased
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if
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est
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n
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ased
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th
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T
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k
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ile
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u
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e
3
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d
W
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ar
e
4
3
9
.
7
3
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3
8
2
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6
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6
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ith
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A)
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in
s
war
m
in
tellig
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(
SI)
[
3
4
]
,
[
3
5
]
.
T
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two
ap
p
r
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o
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izatio
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ile,
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o
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p
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ir
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r
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ates
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ig
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est
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al
o
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v
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o
f
4
3
9
.
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3
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u
r
e
2
(
b
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p
r
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th
e
o
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tim
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ar
am
ete
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s
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e
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r
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s
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ete
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m
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eter
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ateg
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izatio
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u
r
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3
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h
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ased
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s
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le
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R
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o
m
m
e
n
d
atio
n
m
e
n
u
o
f
th
e
b
est m
o
d
el
o
u
t
p
u
ts
M
e
a
l
t
i
m
e
C
o
d
e
M
e
a
l
c
o
d
e
M
e
a
l
n
a
me
M
e
a
l
w
e
i
g
h
t
(
g
r
)
C
a
l
o
r
i
e
s
(
k
c
a
l
)
C
a
r
b
o
h
y
d
r
a
t
e
s
(
g
r
)
P
r
o
t
e
i
n
s
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g
r
)
F
a
t
(
g
r
)
C
o
s
t
(
R
p
)
B
r
e
a
k
f
a
s
t
4
SF
W
h
i
t
e
s
t
i
c
k
y
r
i
c
e
2
0
0
3
2
6
52
6
1
5
,
0
0
0
7
PS
O
n
c
o
m
50
9
3
.
5
11
7
3
1
,
5
0
0
8
AS
Y
e
l
l
o
w
p
i
c
k
l
e
d
t
i
l
a
p
i
a
80
2
6
4
10
14
19
6
,
4
0
0
10
VG
C
u
c
u
m
b
e
r
2
0
0
16
3
0
0
4
,
0
0
0
7
CP
G
u
a
v
a
1
5
0
7
3
.
5
18
1
0
3
,
0
0
0
Lu
n
c
h
4
SF
W
h
i
t
e
s
t
i
c
k
y
r
i
c
e
2
0
0
3
2
6
52
6
1
5
,
0
0
0
7
PS
O
n
c
o
m
50
9
3
.
5
11
7
3
1
,
5
0
0
9
AS
S
t
e
a
m
e
d
c
a
r
p
80
1
6
7
.
2
9
12
9
8
,
0
0
0
10
VG
C
u
c
u
m
b
e
r
2
0
0
16
3
0
0
4
,
0
0
0
9
CP
S
w
e
e
t
o
r
a
n
g
e
1
5
0
6
7
.
5
17
1
0
4
,
8
7
5
D
i
n
n
e
r
6
SF
R
i
c
e
v
e
r
m
i
c
e
l
l
i
2
0
0
6
9
6
1
6
4
9
0
3
,
0
0
0
4
PS
F
r
i
e
d
t
e
mp
e
h
50
1
6
8
4
10
14
1
,
5
0
0
9
AS
S
t
e
a
m
e
d
c
a
r
p
80
1
6
7
.
2
9
12
9
8
,
0
0
0
10
VG
C
u
c
u
m
b
e
r
2
0
0
16
3
0
0
4
,
0
0
0
7
CP
G
u
a
v
a
1
5
0
7
3
.
5
18
1
0
3
,
0
0
0
To
t
a
l
2
5
6
3
.
9
3
8
4
87
61
6
2
,
7
7
5
4.
CO
NCLU
SI
O
N
Nu
tr
itio
n
al
n
ee
d
s
ar
e
ess
en
tial
to
m
ain
tain
m
ater
n
al
an
d
f
eta
l
h
ea
lth
d
u
r
i
n
g
p
r
eg
n
a
n
cy
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wev
er
,
th
e
f
u
lf
ilm
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t
o
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n
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itio
n
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e
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n
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ain
e
d
b
y
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e
b
u
d
g
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o
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h
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tu
d
y
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s
to
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elp
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r
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an
t
wo
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en
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lan
a
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o
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m
en
u
b
y
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n
s
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g
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e
r
eq
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ir
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n
u
tr
itio
n
al
i
n
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with
a
m
i
n
im
u
m
b
u
d
g
et
d
iv
i
d
e
d
in
to
f
iv
e
f
o
o
d
item
ca
teg
o
r
ies:
SF
,
PS
,
AS,
VG,
an
d
C
P.
I
n
ad
d
itio
n
,
th
is
s
tu
d
y
also
tr
ies
to
f
in
d
th
e
b
est
m
eth
o
d
f
r
o
m
f
o
u
r
p
r
o
p
o
s
ed
m
eth
o
d
s
:
GA,
PS
O,
D
SA,
an
d
W
O.
T
h
e
f
o
u
r
m
eth
o
d
s
wer
e
ev
alu
ated
u
s
in
g
th
e
ANOV
A
an
d
T
u
k
e
y
'
s
HSD
te
s
ts
an
d
co
m
p
a
r
in
g
th
e
f
itn
ess
v
alu
es
o
b
tain
e
d
.
T
h
e
ev
al
u
atio
n
r
esu
lts
s
h
o
w
t
h
at
GA
s
ig
n
if
ican
tly
d
if
f
er
s
f
r
o
m
o
th
er
m
o
d
els
with
a
f
itn
ess
v
alu
e
eq
u
al
to
4
3
9
.
7
3
.
GA
ten
d
s
to
h
av
e
m
o
r
e
v
ar
ied
f
itn
ess
r
esu
lts
.
Oth
er
th
an
GA,
th
e
o
th
er
th
r
ee
m
o
d
els
d
o
n
o
t
h
a
v
e
s
ig
n
if
ican
t
d
if
f
e
r
en
ce
s
,
b
u
t
DSA
is
th
e
m
o
s
t
s
u
p
er
i
o
r
m
eth
o
d
co
m
p
ar
ed
t
o
o
t
h
er
s
,
with
a
f
itn
ess
v
alu
e
ca
lcu
lated
at
3
6
7
.
1
8
.
T
h
is
s
tu
d
y
h
as
s
u
cc
ess
f
u
lly
p
r
o
v
i
d
ed
d
aily
m
en
u
r
ec
o
m
m
e
n
d
atio
n
s
to
p
r
eg
n
an
t
w
o
m
en
,
co
n
s
id
er
in
g
n
u
tr
itio
n
al
n
ee
d
s
an
d
b
u
d
g
et.
Ho
wev
e
r
,
it
is
s
till
n
e
ce
s
s
ar
y
to
e
x
p
lo
r
e
v
a
r
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u
s
o
p
t
im
izatio
n
m
eth
o
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d
c
o
m
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i
n
e
th
em
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er
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r
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o
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ig
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ip
b
y
th
e
M
in
istr
y
o
f
Re
se
a
rc
h
,
Tec
h
n
o
l
o
g
y
,
a
n
d
Hi
g
h
e
r
Ed
u
c
a
ti
o
n
,
e
n
a
b
li
n
g
h
e
r
to
c
o
m
p
lete
h
e
r
d
o
c
to
ra
te
th
r
o
u
g
h
a
f
a
st
-
trac
k
p
ro
g
ra
m
with
o
u
t
o
b
tai
n
in
g
a
m
a
ste
r’s
d
e
g
re
e
.
I
n
2
0
2
1
,
s
h
e
a
c
h
iev
e
d
h
e
r
Do
c
t
o
ra
te
in
I
n
d
u
strial
En
g
in
e
e
rin
g
a
t
th
e
De
p
a
rtme
n
t
o
f
In
d
u
strial
E
n
g
i
n
e
e
rin
g
,
F
a
c
u
lt
y
o
f
In
d
u
str
ial
Tec
h
n
o
lo
g
y
a
n
d
S
y
ste
m
s
En
g
i
n
e
e
rin
g
,
I
n
stit
u
t
Te
k
n
o
lo
g
i
S
e
p
u
lu
h
No
p
e
m
b
e
r
(IT
S
).
Re
m
a
rk
a
b
ly
,
s
h
e
e
a
rn
e
d
h
e
r
d
o
c
to
ra
te
a
t
ju
st 2
4
y
e
a
rs
o
f
a
g
e
,
b
e
c
o
m
in
g
t
h
e
y
o
u
n
g
e
st
g
ra
d
u
a
te
to
h
o
ld
t
h
e
ti
tl
e
o
f
"
Do
c
t
o
r
"
.
Cu
rre
n
tl
y
,
h
e
r
re
se
a
rc
h
in
tere
sts
e
n
c
o
m
p
a
ss
o
p
ti
m
iza
ti
o
n
,
s
o
ft
c
o
m
p
u
ti
n
g
,
in
d
u
str
ial
in
fo
rm
a
ti
c
s,
a
n
d
i
n
d
u
strial
a
rti
fic
ial
in
telli
g
e
n
c
e
,
re
flec
ti
n
g
h
e
r
d
y
n
a
m
ic
e
x
p
e
rti
se
in
c
u
tt
i
n
g
-
e
d
g
e
field
s.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
d
iv
a
k
u
@u
b
.
a
c
.
id
.
Na
th
a
n
D
a
u
d
a
n
a
c
ti
v
e
stu
d
e
n
t
e
n
ro
ll
e
d
i
n
th
e
fa
st
-
trac
k
Co
m
p
u
ter
E
n
g
i
n
e
e
rin
g
P
ro
g
ra
m
a
t
U
n
iv
e
rsitas
Bra
wijay
a
'
s
F
a
c
u
lt
y
o
f
Co
m
p
u
ter
S
c
ien
c
e
,
h
e
b
e
g
a
n
h
is
Ba
c
h
e
lo
r'
s
i
n
2
0
2
1
a
n
d
tra
n
siti
o
n
e
d
in
t
o
h
is
m
a
ste
r'
s
in
2
0
2
4
.
He
b
ri
n
g
s
a
we
a
lt
h
o
f
e
x
p
e
rien
c
e
in
re
se
a
rc
h
,
a
c
a
d
e
m
ic
writi
n
g
,
d
a
ta
a
n
a
l
y
sis,
a
n
d
b
u
sin
e
ss
d
e
sig
n
.
His
p
a
rti
c
ip
a
ti
o
n
i
n
n
a
ti
o
n
a
l
c
o
m
p
e
ti
ti
o
n
s
h
a
s
sh
a
rp
e
n
e
d
h
is
p
ro
b
lem
-
so
lv
i
n
g
s
k
il
ls
a
n
d
c
rit
ica
l
th
in
k
in
g
a
b
il
it
ies
.
His
c
u
rre
n
t
re
se
a
rc
h
fo
c
u
se
s
o
n
m
a
c
h
in
e
lea
rn
in
g
a
lg
o
rit
h
m
s,
s
p
e
c
ifi
c
a
ll
y
i
n
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
s
a
p
p
li
e
d
to
t
h
e
h
e
a
lt
h
c
a
re
se
c
to
r,
sh
o
wc
a
sin
g
h
is
d
e
d
i
c
a
ti
o
n
to
le
v
e
ra
g
in
g
AI
fo
r
imp
a
c
tfu
l
so
l
u
ti
o
n
s.
He
is
e
a
g
e
r
to
c
o
n
ti
n
u
e
lea
rn
i
n
g
a
n
d
in
teg
ra
t
e
AI
-
d
riv
e
n
stra
teg
ies
in
to
re
a
l
-
wo
rld
b
u
si
n
e
ss
c
h
a
ll
e
n
g
e
s,
a
imin
g
to
d
ri
v
e
i
n
n
o
v
a
ti
o
n
a
n
d
c
r
e
a
te
las
ti
n
g
p
o
si
ti
v
e
c
h
a
n
g
e
(so
c
io
p
re
n
e
u
rsh
i
p
).
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
n
a
th
a
n
d
a
u
d
@s
tu
d
e
n
t.
u
b
.
a
c
.
i
d
.
K
o
h
e
i
Ar
a
i
is
a
sc
ien
ti
st,
p
r
o
f
e
ss
o
r,
a
n
d
a
u
th
o
r.
He
is
c
u
rre
n
tl
y
P
ro
fe
ss
o
r
a
t
S
a
g
a
Un
iv
e
rsity
,
Ja
p
a
n
a
n
d
Ad
ju
n
c
t
P
ro
f.
o
f
t
h
e
Un
i
v
e
rsity
o
f
Ariz
o
n
a
,
USA
si
n
c
e
1
9
9
8
.
He
re
c
e
iv
e
d
P
h
.
D
.
d
e
g
re
e
in
In
fo
rm
a
ti
o
n
S
c
ien
c
e
fro
m
Ni
h
o
n
Un
i
v
e
rsity
in
J
u
n
e
1
9
8
2
a
n
d
M
.
S
.
d
e
g
re
e
in
El
e
c
tro
n
ics
En
g
in
e
e
rin
g
fro
m
Ni
h
o
n
U
n
iv
e
rsit
y
i
n
M
a
rc
h
1
9
7
4
.
His
c
u
rre
n
t
re
se
a
rc
h
c
o
n
c
e
rn
s
a
re
sa
telli
te
re
m
o
te
se
n
s
in
g
,
ra
d
iati
v
e
tran
sfe
r
e
q
u
a
ti
o
n
,
h
u
m
a
n
-
c
o
m
p
u
ter
in
tera
c
ti
o
n
,
ima
g
e
re
c
o
g
n
i
ti
o
n
a
n
d
u
n
d
e
rsta
n
d
in
g
,
n
o
n
-
li
n
e
a
r
o
p
ti
m
iza
ti
o
n
t
h
e
o
ry
a
n
d
wa
v
e
let
a
n
a
l
y
sis
.
He
h
o
l
d
s
4
2
p
a
ten
ts
a
n
d
re
c
e
iv
e
d
n
u
m
e
ro
u
s
a
wa
rd
s,
in
c
lu
d
in
g
th
e
p
a
ten
t
a
wa
rd
o
f
th
e
y
e
a
r
.
He
h
a
s
b
e
e
n
fe
a
tu
re
d
in
Ja
p
a
n
T
ime
s
a
n
d
I
talian
Ne
ws
p
a
p
e
rs
fo
r
h
is
wo
rk
o
n
e
y
e
s
o
n
ly
c
o
m
p
u
ter
sy
ste
m
.
He
h
a
s
wo
r
k
e
d
o
n
se
v
e
ra
l
g
l
o
b
a
l
re
se
a
rc
h
c
o
ll
a
b
o
ra
ti
o
n
p
r
o
jec
ts
d
u
rin
g
h
is
c
a
re
e
r.
He
wro
te
3
1
b
o
o
k
s
a
n
d
p
u
b
li
sh
e
d
4
9
0
jo
u
rn
a
l
p
a
p
e
rs
a
n
d
3
9
0
o
f
c
o
n
fe
re
n
c
e
p
a
p
e
rs.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
p
m
e
li
n
@te
c
ti
ju
a
n
a
.
m
x
.
Ind
r
ia
ti
is
a
d
isti
n
g
u
ish
e
d
a
c
a
d
e
m
ic
fro
m
th
e
F
a
c
u
lt
y
o
f
Co
m
p
u
ter
S
c
ien
c
e
.
Wi
th
a
ro
b
u
st
b
a
c
k
g
r
o
u
n
d
i
n
c
o
m
p
u
te
r
sc
ien
c
e
,
sh
e
h
a
s
m
a
d
e
sig
n
ifi
c
a
n
t
strid
e
s
in
re
se
a
rc
h
a
n
d
in
n
o
v
a
ti
o
n
.
He
r
wo
r
k
p
rima
ril
y
fo
c
u
se
s
o
n
d
e
v
e
lo
p
in
g
c
u
tt
i
n
g
-
e
d
g
e
tec
h
n
o
lo
g
ies
a
n
d
t
h
e
ir
p
ra
c
ti
c
a
l
a
p
p
li
c
a
ti
o
n
s
t
o
a
d
d
re
ss
re
a
l
-
wo
rld
c
h
a
ll
e
n
g
e
s.
S
h
e
h
a
s
a
u
th
o
re
d
n
u
m
e
ro
u
s
re
se
a
rc
h
p
a
p
e
rs
p
u
b
li
sh
e
d
i
n
p
re
sti
g
io
u
s
jo
u
rn
a
ls
a
n
d
h
a
s
p
re
se
n
ted
h
e
r
fin
d
i
n
g
s
a
t
v
a
rio
u
s
in
ter
n
a
ti
o
n
a
l
c
o
n
fe
re
n
c
e
s.
S
h
e
is k
n
o
w
n
fo
r
h
e
r
c
o
ll
a
b
o
ra
ti
v
e
a
p
p
r
o
a
c
h
,
o
ften
wo
rk
in
g
with
in
terd
isc
ip
li
n
a
r
y
tea
m
s
to
p
u
sh
t
h
e
b
o
u
n
d
a
ries
o
f
c
o
m
p
u
ter
sc
ien
c
e
.
In
a
d
d
it
i
o
n
t
o
h
e
r
re
se
a
r
c
h
,
sh
e
is
d
e
d
ica
t
e
d
to
tea
c
h
in
g
a
n
d
m
e
n
to
ri
n
g
stu
d
e
n
ts.
He
r
e
n
g
a
g
in
g
tea
c
h
in
g
sty
le
a
n
d
c
o
m
m
it
m
e
n
t
t
o
stu
d
e
n
t
su
c
c
e
ss
h
a
v
e
m
a
d
e
h
e
r
a
re
sp
e
c
ted
fi
g
u
re
in
th
e
a
c
a
d
e
m
ic
c
o
m
m
u
n
it
y
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
in
d
riati.
ti
f@u
b
.
a
c
.
id
.
Ma
r
ji
is
a
d
e
d
ica
ted
a
n
d
a
c
c
o
m
p
li
sh
e
d
a
c
a
d
e
m
ic
fro
m
th
e
F
a
c
u
lt
y
o
f
C
o
m
p
u
ter
S
c
ien
c
e
.
Wi
th
a
str
o
n
g
b
a
c
k
g
r
o
u
n
d
i
n
c
o
m
p
u
ter
sc
ien
c
e
a
n
d
a
p
a
ss
io
n
fo
r
re
se
a
rc
h
,
he
h
a
s
m
a
d
e
sig
n
ifi
c
a
n
t
c
o
n
tri
b
u
ti
o
n
s
to
th
e
f
ield
.
His
wo
r
k
f
o
c
u
se
s
o
n
i
n
n
o
v
a
ti
v
e
tec
h
n
o
lo
g
ies
a
n
d
th
e
ir
a
p
p
l
ica
ti
o
n
s,
a
imi
n
g
t
o
so
lv
e
re
a
l
-
wo
rld
p
ro
b
lem
s
th
r
o
u
g
h
a
d
v
a
n
c
e
d
c
o
m
p
u
ti
n
g
so
lu
ti
o
n
s.
He
h
a
s
p
u
b
li
sh
e
d
n
u
m
e
ro
u
s
p
a
p
e
rs
i
n
re
p
u
ta
b
le
jo
u
r
n
a
ls
a
n
d
h
a
s
b
e
e
n
a
n
a
c
ti
v
e
p
a
rti
c
ip
a
n
t
in
v
a
ri
o
u
s
in
ter
n
a
ti
o
n
a
l
c
o
n
fe
re
n
c
e
s.
Kn
o
wn
fo
r
th
e
ir
c
o
ll
a
b
o
ra
ti
v
e
sp
ir
it
,
he
o
ften
wo
rk
s
wit
h
in
terd
isc
ip
l
in
a
ry
tea
m
s
to
p
u
sh
t
h
e
b
o
u
n
d
a
ries
o
f
w
h
a
t
is
p
o
ss
ib
le
i
n
c
o
m
p
u
ter
sc
ien
c
e
.
In
a
d
d
it
i
o
n
t
o
re
se
a
rc
h
,
he
is co
m
m
it
ted
to
tea
c
h
in
g
a
n
d
m
e
n
to
ri
n
g
t
h
e
n
e
x
t
g
e
n
e
ra
ti
o
n
o
f
c
o
m
p
u
ter
sc
ien
ti
sts.
Th
e
y
a
re
k
n
o
wn
fo
r
th
e
ir
e
n
g
a
g
i
n
g
tea
c
h
in
g
sty
le
a
n
d
d
e
d
ica
ti
o
n
t
o
stu
d
e
n
t
su
c
c
e
ss
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
a
rji
@u
b
.
a
c
.
i
d
.
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