Abstract
The
rapid
growth
of
the
textile
industry
has
led
to
a
sharp
increase
in
dye-filled
wastewater,
posing
significant
environmental
concern.
Adsorption
is
promising
method
for
dye
removal,
but
traditional
adsorbents
often
fall
short
due
limited
capacity,
lack
sustainability,
and
low
selectivity.
Nanocellulose-based
materials
have
shown
great
potential,
with
some
achieving
high
adsorption
capacities,
such
as
3429.23
mg/g
Congo
Red
on
cellulose-based
aerogel
2282.3
malachite
green
magnetic
nanocellulose-based
adsorbents.
These
follow
various
models,
including
Langmuir
Freundlich
isotherms,
kinetic
models
pseudo-second-order
model
indicating
strong
interactions
target
dyes.
This
review
thoroughly
examines
adsorbents,
exploring
their
types,
properties,
preparation
methods.
analyses
interactions,
factors
influencing
adsorption,
provides
an
in-depth
look
at
kinetics,
thermodynamics.
Also,
this
aims
clarify
true
potential
summarizing
recent
advancements
while
identifying
research
gaps
future
directions
support
further
development
field.
Processes,
Год журнала:
2025,
Номер
13(2), С. 566 - 566
Опубликована: Фев. 17, 2025
Green
materials
are
emerging
as
sustainable
alternatives
in
water
and
wastewater
treatment.
Due
to
their
biodegradability,
renewable
origin
low
toxicity
characteristics,
green
an
alternative
conventional
synthetic
materials.
include
nanomaterials
of
natural
origin,
biopolymers
composites
that
optimize
the
adsorption
removal
contaminants.
The
applications
cellulose
nanofibers,
alginates,
chitosan
lignin
stand
out,
well
functionalized
hydrogels
aerogels
for
heavy
metals,
dyes
organic
analysis
mechanisms
processes
contaminant
modeling
optimization
techniques
included
key
tools
design
these
materials,
allowing
one
predict
properties,
simulate
interactions
customize
solutions.
Despite
sustainability
benefits
they
face
technical
economic
challenges,
such
scalability,
synthesis
costs
experimental
validation.
This
work
concluded
combined
with
tools,
essential
move
towards
more
sustainable,
efficient
environmentally
friendly
treatment
technologies,
aligned
global
objectives
development
climate
change
mitigation.
The American Journal of Chinese Medicine,
Год журнала:
2025,
Номер
unknown, С. 1 - 23
Опубликована: Март 27, 2025
Non-small
cell
lung
cancer
(NSCLC)
is
a
malignancy
that
faces
serious
resistance
challenges
in
treatment.
In
this
study,
we
identified
Piperlongumine
as
promising
therapeutic
candidate
to
overcome
Osimertinib
NSCLC.
We
systematically
investigated
the
inhibitory
effect
of
on
NSCLC
cells
and
confirmed
it
could
effectively
inhibit
vitro
kinase
activity
wild-type
(WT),
exon
19
deletion,
L858R/T790M-mutated
EGFR.
also
found
Piperlongumine-induced
intrinsic
apoptosis
by
interfering
with
EGFR
signaling
pathway,
which
was
characterized
down-regulation
anti-apoptotic
protein
Mcl-1.
Further
mechanistic
studies
revealed
degradation
Mcl-1
dependent
Akt-GSK3[Formula:
see
text]
pathway.
Additionally,
Piperlongumine-promoted
interaction
between
[Formula:
text]-TRCP,
thereby
enhancing
text]-TRCP-mediated
ubiquitination
Furthermore,
significantly
inhibited
tumor
growth
both
Osimertinib-sensitive
resistant
xenograft
models.
These
findings
highlight
potential
an
effective
agent
overcoming
EGFR-targeted
therapy
suggest
new
avenues
for
its
clinical
application
Energy Science & Engineering,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 1, 2025
ABSTRACT
Despite
direct
current
(DC)
microgrids'
benefits
over
alternating
microgrids,
these
systems
confront
several
difficulties.
The
instability
brought
on
by
constant
power
loads
(CPLs)
is
one
of
the
main
challenges.
Because
their
rising
negative
impedance
characteristics,
CPLs
reduce
system
performance.
This
study
looks
at
a
DC
microgrid
that
has
photovoltaic
(PV)
battery
grid
connected
to
CPL.
To
tackle
this
challenge,
disturbance
observer
and
continuous‐time
model
predictive
control
based
type‐3
fuzzy
logic
(T3‐FLSs)
are
applied
bidirectional
DC‐DC
converter.
Even
in
face
load
PV
generation
fluctuations,
method
aims
regulate
nonlinearity
CPL
preserve
stability
across
broad
operating
range.
A
new
learning
scheme
square
root
cubature
Kalman
filter
developed
for
online
deep
identified
T3‐FLS
model.
Finally,
proposed
strategy
compared
with
conventional
method,
which
demonstrates
superiority
suggested
terms
flexibility,
reduced
response
time,
improved
stability.
Tests
were
performed
using
variety
circumstances,
including
variations
load,
assess
system's
All
experiments
simulation
results
MATLAB
software.
Simulation
show
network
very
good
performance
dynamic
response,
precise
tracking,
wide
voltage
fluctuations
about
20%.
algorithm
significantly
impacts
energy
efficiency
stabilizing,
enhancing
adaptability
changing
conditions,
disturbances,
increasing
renewable
integration,
reducing
operational
costs.
