Foods,
Journal Year:
2024,
Volume and Issue:
13(15), P. 2424 - 2424
Published: July 31, 2024
Avocado
oil
is
rich
in
nutrients
beneficial
to
human
health,
such
as
monounsaturated
fatty
acids,
phenolic
compounds,
tocopherol,
and
carotenoids,
with
numerous
possibilities
for
application
industry.
This
review
explores,
through
a
comparative
approach,
the
effectiveness
of
supercritical
extraction
process
an
alternative
conventional
cold-pressing
method,
evaluating
differences
steps
effect
temperature
operating
pressure
on
bioactive
quality
yield.
The
results
reveal
that
avocado
has
yield
like
mechanical
cold
pressing
superior
functional
quality,
especially
relation
α-tocopherol
carotenoids.
For
better
use
efficiency
technology,
maturation
stage,
moisture
content,
fruit
variety,
collection
period
stand
out
essential
factors
be
observed
during
pre-treatment,
they
directly
impact
nutrient
concentration.
In
addition,
technology
enables
full
fruit,
significantly
reducing
waste,
adds
value
agro-industrial
residues
process.
It
produces
edible
free
impurities,
microorganisms,
organic
solvents.
green,
environmentally
friendly
long-term
environmental
economic
advantages
interesting
market.
Coloration Technology,
Journal Year:
2024,
Volume and Issue:
unknown
Published: March 3, 2024
Abstract
The
textile
industry
is
one
of
the
significant
reasons
for
global
water
pollution,
with
dyeing
processes
being
particularly
environmentally
detrimental.
Researchers
have
explored
alternative
approaches
to
address
this
issue,
such
as
using
natural
dyes,
supercritical
fluids
and
so
forth.
In
addition
environment‐friendly
approaches,
reducing
number
experiments
in
studies,
accurate
production
straightaway
artificial
intelligence
(AI),
technologies
present
future
that
will
provide
support.
Reaching
clearer
results
AI
technology
not
necessarily
contribute
technologies.
However,
techniques,
including
neural
networks
(ANNs)
adaptive
neuro
fuzzy
interface
system
(ANFIS)
were
employed
predict
colour
strength
(
K/S
)
dyed
fabric
based
on
process
parameters.
A
comprehensive
experimental
design
involving
pressure,
temperature,
time
variations
was
conducted,
analysed
multi‐factor
analysis
variance
(MANOVA).
study
demonstrates
carbon
dioxide
(scCO
2
madder
polyester
a
promising
friendly
approach.
Additionally,
optimised
ANN
ANFIS
models,
aided
by
genetic
algorithms
(GAs),
exhibit
high
predictive
accuracy
(less
than
3%),
providing
insights
into
impact
parameters
strength.
This
research
underscores
potential
AI‐driven
automation
dyeing,
offering
solutions
dye
formula
prediction,
matching,
defect
detection,
need
human
intervention
these
processes.
Autex Research Journal,
Journal Year:
2024,
Volume and Issue:
24(1)
Published: Jan. 1, 2024
Abstract
Textile
industry
has
a
significant
water
footprint
(WF),
leading
to
various
sustainability
challenges.
This
article
discusses
key
findings
on
the
WF
and
outlines
potential
solutions.
The
industry’s
includes
three
types:
green,
blue,
grey.
manufacturing
is
water-intensive,
with
stages
like
pretreatment,
dyeing,
printing,
finishing.
can
contribute
scarcity
in
some
regions.
Water
pollution
another
critical
challenge,
as
generates
considerable
wastewater
containing
diverse
pollutants
which
harm
ecosystems
pose
risks
public
health.
Different
treatments
reduce
are
studied.
We
have
grouped
innovations
into
five
major
categories
for
conservation
efforts
textile
industry:
To
address
these
challenges,
several
solutions
proposed.
Each
category
offers
pathway
its
environmental
through
conservation.
adoption
of
water-efficient
technologies,
such
low-water
dyeing
recycling,
consumption.
Stricter
policies
control,
along
incentives
sustainable
practices,
encourage
industry-wide
change.
Collaboration
among
stakeholders,
including
industry,
government,
groups,
also
crucial
promoting
reducing
impact.
These
approaches
help
move
toward
more
future.
Further
research
needed
suggested.
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
Polymers,
Journal Year:
2024,
Volume and Issue:
16(11), P. 1567 - 1567
Published: June 1, 2024
PETG
(poly(ethylene
glycol-co-cyclohexane-1,4-dimethanol
terephthalate))
is
an
amorphous
copolymer,
biocompatible,
recyclable,
and
versatile.
Nowadays,
it
being
actively
researched
for
biomedical
applications.
However,
proposals
of
as
a
platform
the
loading
bioactive
compounds
from
natural
extract
are
scarce,
well
effect
supercritical
impregnation
on
this
polymer.
In
work,
filaments
with
Olea
europaea
leaf
was
investigated,
evaluating
pressure
(100–400
bar),
temperature
(35–55
°C),
depressurization
rate
(5–50
bar
min−1)
expansion
degree,
antioxidant
activity,
mechanical
properties
resulting
filaments.
degree
ranged
~3
to
120%,
ranging
2.28
17.96
g
per
100
polymer,
corresponding
oxidation
inhibition
values
7.65
66.55%,
respectively.
The
binary
interaction
between
most
affected
these
properties.
depended
greatly
process
variables.
Tensile
strength
were
similar
or
lower
than
untreated
Young’s
modulus
elongation
at
break
decreased
below
~1000
MPa
~10%,
respectively,
after
scCO2
treatment
impregnation.
extent
decrease
operational
parameters.
Therefore,
higher
activity
different
degrees
obtained
by
adjusting
processing
conditions.
