Nano Architecture of MoS2/ZnO Nanocomposite for Efficient NO2 Gas-sensing Properties
Materials Today Communications,
Год журнала:
2025,
Номер
unknown, С. 111577 - 111577
Опубликована: Янв. 1, 2025
Язык: Английский
Boosting Aeroponic System Development with Plasma and High-Efficiency Tools: AI and IoT—A Review
Agronomy,
Год журнала:
2025,
Номер
15(3), С. 546 - 546
Опубликована: Фев. 23, 2025
Sustainable
agriculture
faces
major
issues
with
resource
efficiency,
nutrient
distribution,
and
plant
health.
Traditional
soil-based
soilless
farming
systems
encounter
including
excessive
water
use,
insufficient
uptake,
nitrogen
deficiency,
restricted
development.
According
to
the
previous
literature,
aeroponic
accelerate
growth
rates,
improve
root
oxygenation,
significantly
enhance
use
particularly
when
paired
both
low-
high-pressure
misting
systems.
However,
despite
these
advantages,
they
also
present
certain
challenges.
A
drawback
is
inefficiency
of
fixation,
resulting
in
availability
heightened
stress
from
uncontrolled
misting,
which
ultimately
reduces
yield.
Many
studies
have
investigated
plasma
uses
cultures;
nevertheless,
however,
its
function
aeroponics
remains
unexplored.
Therefore,
work
aims
thoroughly
investigate
review
integration
plasma-activated
(PAW)
mist
(PAM)
solve
important
problems.
current
literature
discloses
that
PAW
PAM
expand
promote
modulate
microbial
populations,
elevated
crop
yields
enhanced
health,
akin
other
Reactive
oxygen
species
(RONS)
produced
by
treatments
bioavailability,
development,
equilibrium,
alleviating
critical
challenges
aeroponics,
especially
within
fine-mist
settings.
This
further
examines
artificial
intelligence
(AI)
Internet
Things
(IoT)
aeroponics.
Models
driven
AI
enable
accurate
regulation
fertilizer
concentrations,
cycles,
temperature,
humidity,
as
well
real-time
monitoring
predictive
analytics.
IoT-enabled
smart
employ
sensors
for
continuous
gas
detection
(e.g.,
NO2,
O3,
NH3),
providing
automated
modifications
efficiency.
Based
on
a
brief
this
study
concludes
future
technology
IoT
may
address
limitations
The
intelligent
data-driven
control
can
sustainable
efficient
agricultural
production.
research
supports
existing
body
advocates
plasma-based
innovations
solutions
precision
farming.
Язык: Английский
The Fermentation Degree Prediction Model for Tieguanyin Oolong Tea Based on Visual and Sensing Technologies
Foods,
Год журнала:
2025,
Номер
14(6), С. 983 - 983
Опубликована: Март 13, 2025
The
fermentation
of
oolong
tea
is
a
critical
process
that
determines
its
quality
and
flavor.
Current
control
relies
on
makers'
sensory
experience,
which
labor-intensive
time-consuming.
In
this
study,
using
Tieguanyin
as
the
research
object,
features
including
water
loss
rate,
aroma,
image
color,
texture
were
obtained
weight
sensors,
tin
oxide-type
gas
sensor,
visual
acquisition
system.
Support
vector
regression
(SVR),
random
forest
(RF)
machine
learning,
long
short-term
memory
(LSTM)
deep
learning
algorithms
employed
to
establish
models
for
assessing
degree
based
both
single
fused
multi-source
features,
respectively.
results
showed
in
test
set
mean
absolute
error
(MAE)
ranged
from
4.537
6.732,
root
square
(RMSE)
5.980
9.416,
coefficient
determination
(R2)
values
varied
between
0.898
0.959.
contrast,
data
fusion
demonstrated
superior
performance,
with
MAE
reduced
2.232-2.783,
RMSE
2.693-3.969,
R2
increased
0.982-0.991,
confirming
feature
enhanced
characterization
accuracy.
Finally,
Sparrow
Search
Algorithm
(SSA)
was
applied
optimize
models.
After
optimization,
exhibited
ranging
1.703
2.078,
2.258
3.230,
0.988
0.994
set.
application
SSA
further
model
accuracy,
Fusion-SSA-LSTM
demonstrating
best
performance.
enable
online
real-time
monitoring
tea,
contributes
automated
production
tea.
Язык: Английский
Machine Learning Driven Atom‐Thin Materials for Fragrance Sensing
Small,
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 7, 2024
Abstract
Fragrance
plays
a
crucial
role
in
the
daily
lives.
Its
importance
spans
various
sectors,
from
therapeutic
purposes
to
personal
care,
making
understanding
and
accurate
identification
of
fragrances
essential.
To
fully
harness
potential
fragrances,
efficient
precise
fragrance
sensing
are
necessary.
However,
current
sensors
face
several
limitations,
particularly
detecting
differentiating
complex
scent
profiles
with
high
accuracy.
address
these
challenges,
use
atom‐thin
materials
has
emerged
as
groundbreaking
approach.
These
sensors,
characterized
by
their
enhanced
sensitivity
selectivity,
offer
significant
improvements
over
traditional
technology.
Moreover,
integration
Machine
Learning
(ML)
into
opened
new
opportunities
field.
ML
algorithms
applied
facilitate
advancements
four
key
domains:
identification,
discrimination
between
different
improved
detection
thresholds
for
subtle
scents,
prediction
properties.
This
comprehensive
review
delves
synergistic
sensing,
providing
an
in‐depth
analysis
how
technologies
revolutionizing
field,
offering
insights
applications
future
enhancing
utilization
fragrances.
Язык: Английский
Tea Administration Facilitates Immune Homeostasis by Modulating Host Microbiota
Nutrients,
Год журнала:
2024,
Номер
16(21), С. 3675 - 3675
Опубликована: Окт. 29, 2024
Tea,
derived
from
the
young
leaves
and
buds
of
Camellia
sinensis
plant,
is
a
popular
beverage
that
may
influence
host
microbiota.
Its
consumption
has
been
shown
to
promote
growth
beneficial
bacterial
species
while
suppressing
harmful
ones.
Simultaneously,
bacteria
metabolize
tea
compounds,
resulting
in
production
bioactive
molecules.
Consequently,
health
benefits
associated
with
stem
both
favorable
it
nurtures
metabolites
produced
by
these
microbes.
The
gut
microbiota
plays
vital
role
mediating
systemic
immune
homeostasis
linked
consumption,
functioning
through
complex
pathways
involve
gut–lung,
gut–brain,
gut–liver
axes.
Recent
studies
have
sought
establish
connections
between
tea,
its
regulation
via
In
this
paper,
we
aim
summarize
latest
research
findings
field.
Язык: Английский