Abstract.
Due
to
a
growing
recognition
of
the
need
study
how
ecosystems
and
atmosphere
interact
with
each
other,
many
regional
networks
as
well
global
network
networks,
FLUXNET,
were
formed.
Since
1999,
when
AsiaFlux
was
established,
scientists
in
region
have
been
measuring
flux
densities
energy,
water
vapor,
greenhouse
gas
exchanges
better
evaluate
ecosystem-atmosphere
interactions
understand
their
underlying
mechanisms.
The
includes
natural
managed
that
span
broad
climatic
ecological
gradients,
experience
diverse
management
practices
disturbances.
In
this
ideas
perspectives
paper,
from
view
early
career
researchers
(ECRs),
we
synthesize
key
research
foci
recent
years,
focus
on
latest
conferences,
highlight
selected
discoveries.
While
achieving
significant
milestones,
ECRs
argue
community
should
work
together
emphasize
importance
long-term
observations,
rejuvenate
network’s
shared
open-access
database,
actively
engage
stakeholders.
With
unique
ecosystem
types
Asian
region,
efforts
expertise
can
provide
critical
insights
into
roles
climate
change,
extreme
weather
events,
soil
properties,
vegetation
physiology
structure,
breathing
biosphere.
closing,
hope
paper
inspire
future
generation
Asia
promote
between
across
different
cultures
stages.
Land,
Journal Year:
2025,
Volume and Issue:
14(2), P. 246 - 246
Published: Jan. 24, 2025
Cropland
serves
as
the
most
vital
resource
for
agricultural
production,
while
its
security
is
primarily
threatened
by
abandonment.
Northeast
Guangdong
Province
features
a
fragmented
terrain
and
faces
significant
issue
of
farmland
It
crucial
to
analyze
phenomenon
cropland
abandonment
safeguard
food
security.
However,
due
limitations
in
data
sources
attribution
methods,
previous
studies
struggled
comprehensively
characterize
driving
mechanisms
abandoned
land.
Using
from
Sentinel
time
series
remote-sensing
images,
we
employed
land
use
change
trajectory
method
map
Jiaoling
County
2019
2023.
Furthermore,
proposed
novel
analytical
framework
quantify
influence
pathways
interaction
effects
The
results
indicate
that:
(1)
overall
accuracy
extraction
79.6%.
During
study
period,
rate
showed
trend
“gradual
rise
followed
sharp
decline”,
area
reached
maximum
2021.
southeastern
rural
areas
was
serious
stubborn.
(2)
slope
has
greatest
explanatory
power
abandonment,
total
cultivated
area,
aggregation
index
cropland,
distance
road.
Each
factor
threshold
effect.
(3)
Topography,
location,
agriculture
factors
directly
or
indirectly
affect
rate,
with
direct
influences
0.247,
0.255,
−0.256,
respectively.
research
findings
offer
valuable
scientific
guidance
managing
deepen
our
understanding
formation
mechanisms.
Water,
Journal Year:
2024,
Volume and Issue:
16(15), P. 2199 - 2199
Published: Aug. 2, 2024
Machine
learning
models’
performance
in
simulating
monthly
rainfall–runoff
subtropical
regions
has
not
been
sufficiently
investigated.
In
this
study,
we
evaluate
the
of
six
widely
used
machine
models,
including
Long
Short-Term
Memory
Networks
(LSTMs),
Support
Vector
Machines
(SVMs),
Gaussian
Process
Regression
(GPR),
LASSO
(LR),
Extreme
Gradient
Boosting
(XGB),
and
Light
(LGBM),
against
a
model
(WAPABA
model)
streamflow
across
three
sub-basins
Pearl
River
Basin
(PRB).
The
results
indicate
that
LSTM
generally
demonstrates
superior
capability
than
other
five
models.
Using
previous
month
as
an
input
variable
improves
all
When
compared
with
WAPABA
model,
better
two
sub-basins.
For
simulations
wet
seasons,
shows
slightly
model.
Overall,
study
confirms
suitability
methods
modeling
at
scale
basins
proposes
effective
strategy
for
improving
their
performance.
Polymers,
Journal Year:
2024,
Volume and Issue:
16(23), P. 3368 - 3368
Published: Nov. 29, 2024
The
integration
of
machine
learning
(ML)
into
material
manufacturing
has
driven
advancements
in
optimizing
biopolymer
production
processes.
ML
techniques,
applied
across
various
stages
production,
enable
the
analysis
complex
data
generated
throughout
identifying
patterns
and
insights
not
easily
observed
through
traditional
methods.
As
sustainable
alternatives
to
petrochemical-based
plastics,
biopolymers
present
unique
challenges
due
their
reliance
on
variable
bio-based
feedstocks
processing
conditions.
This
review
systematically
summarizes
current
applications
techniques
aiming
provide
a
comprehensive
reference
for
future
research
while
highlighting
potential
enhance
efficiency,
reduce
costs,
improve
product
quality.
also
shows
role
algorithms,
including
supervised,
unsupervised,
deep
