The Scientific World JOURNAL,
Journal Year:
2025,
Volume and Issue:
2025(1)
Published: Jan. 1, 2025
Background:
Foreign
direct
investment
(FDI)
is
a
steadfast
contributor
to
capital
flows
and
plays
an
indispensable
role
in
driving
economic
advancement
emerging
as
pivotal
avenue
for
financing
growth
Bangladesh.
Therefore,
this
study
identifies
the
factors
that
influence
FDI
inflows
Moreover,
authors
explored
more
appropriate
model
predicting
by
comparing
efficacy
of
other
models’
predictions.
Methods:
This
based
on
secondary
data
over
period
1973
2021
collected
from
publicly
accessible
website
World
Bank.
A
generalized
additive
(GAM)
was
implemented
describing
proper
splines.
The
model’s
performance
assessed
using
modified
R
‐squared,
Bayesian
information
criterion
(BIC),
Akaike
(AIC).
Results:
Findings
depict
significant
nonlinear
relationship
between
Bangladesh’s
key
indicators,
including
GDP,
trade
openness,
external
debt,
gross
formation,
national
income
(GNI)
government
rates
exchange,
total
reserves,
natural
resource
rent.
It
also
observed
GAM
(
2
=
0.987,
I
C
608.03,
B
658.28)
outperforms
multiple
linear
regressions
polynomial
regression
FDI,
emphasizing
superiority
capturing
complex
relationships
improving
predictive
accuracy.
Conclusion:
along
with
covariates
considered
study.
believed
study’s
findings
would
assist
taking
efficient
initiatives
management
proactive
indicator
optimization
empower
resilience
foster
sustainable
growth.
analysis
revealed
its
related
risk
follow
pattern.
recommends
reliable
method
suggest
can
guide
policymakers
developing
strategies
increase
inflows,
stimulate
growth,
ensure
development
Results in Engineering,
Journal Year:
2024,
Volume and Issue:
22, P. 102220 - 102220
Published: May 4, 2024
The
groundwater
(GW)
of
Bangladesh
is
predominantly
contaminated
with
arsenic
(As)
and
iron
(Fe)
which
has
a
bad
impact
on
human
health.
We
tried
to
remove
these
elements
easily
available
mahogany-fruit
(Swietenia
mahagoni)
husk
charcoal
(MHC)
banana
(Musa
acuminata)
peduncle
(BPC).
trial
was
implemented
3
replications
throughout
the
research.
sampled
GW
contained
0.06
mg
As
L-1
4.83
Fe
L-1.
Firstly,
pH
3,
5,
7,
9
250
dose.
MHC
removed
almost
91.05%
at
5.0,
BPC
86.67%
9.
However,
in
case
Fe,
100%
7
9;
same
quantity
Secondly,
contact
times
were
0,
10,
20,
40
minutes
dose
7.0.
maximum
removal
5
minutes.
pseudo-first-order
kinetic,
pseudo-second-order
intra-particle
diffusion
models
considered.
result
showed
that
rate
adsorption
followed
kinetic
model.
Lastly,
adsorbent
doses
50,
150,
250,
350
At
highest
79.47%
for
MHC.
Similarly,
values
79.29%
BPC,
indicating
are
good
heavy
metals
removal.
Heliyon,
Journal Year:
2024,
Volume and Issue:
10(13), P. e33082 - e33082
Published: June 19, 2024
Monitoring
of
groundwater
resources
in
coastal
areas
is
vital
for
human
needs,
agriculture,
ecosystems,
securing
water
supply,
biodiversity,
and
environmental
sustainability.
Although
the
utilization
quality
index
(WQI)
models
has
proven
effective
monitoring
resources,
it
faced
substantial
criticism
due
to
its
inconsistent
outcomes,
prompting
need
more
reliable
assessment
methods.
Therefore,
this
study
addresses
concern
by
employing
data-driven
root
mean
squared
(RMS)
evaluate
Bhola
district
near
Bay
Bengal,
Bangladesh.
To
enhance
reliability
RMS-WQI
model,
research
incorporated
extreme
gradient
boosting
(XGBoost)
machine
learning
(ML)
algorithm.
For
GWQ,
utilized
eleven
crucial
indicators,
including
turbidity
(TURB),
electric
conductivity
(EC),
pH,
total
dissolved
solids
(TDS),
nitrate
(NO3-),
ammonium
(NH4+),
sodium
(Na),
potassium
(K),
magnesium
(Mg),
calcium
(Ca),
iron
(Fe).
In
terms
GW
concentration
K,
Ca
Mg
exceeded
guideline
limit
collected
samples.
The
computed
scores
ranged
from
54.3
72.1,
with
an
average
65.2,
categorizing
all
sampling
sites'
GWQ
as
"fair."
model
reliability,
XGBoost
demonstrated
exceptional
sensitivity
(R2
=
0.97)
predicting
accurately.
Furthermore,
exhibited
minimal
uncertainty
(<1%)
WQI
scores.
These
findings
implied
efficacy
accurately
assessing
areas,
that
would
ultimately
assist
regional
managers
strategic
planners
sustainable
management
resources.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Aug. 11, 2024
Abstract
Evaluation
of
water
quality
is
crucial
for
managing
surface
effectively,
ensuring
its
suitability
human
use,
and
sustaining
the
environment.
In
lower
Danube
River
basin,
various
methods
were
employed
to
assess
irrigation,
drinking,
health
risk
purposes
main
mechanism
control
chemistry.
These
included
indicators
(WQIs),
complex
statistical
analyses,
geographic
information
systems
(GIS),
Monte
Carlo
simulation,
geochemical
modeling.
Physicochemical
analyses
samples
revealed
primarily
Ca–Mg–HCO
3
−
dominant
types.
Principal
component
analysis
(PCA),
ionic
ratios
piper,
chloro
alkaline
index,
Chadha,
Gibbs
diagrams
identified
three
distinct
characteristics
influenced
by
water-rocks
interaction,
evaporation,
ions
exchange,
activities.
The
modeling
showed
water’s
strong
ability
dissolve
gypsum,
halite,
anhydrite
(SI
<
0)
precipitate
aragonite,
dolomite,
calcite
with
saturation
index
(SI)
value
greater
than
0
along
flow
path.
irrigation
(IWQI
=
99.6–107.6),
sodium
adsorption
ratio
(SAR
0.37–0.68),
percentage
(Na%
13.7–18.7),
soluble
(SSP
12.5–17.5),
Potential
Salinity
(PS
0.73–1.6),
Residual
Sodium
Carbonate
(RSC
1.27–0.58)
values
used,
mainly
indicating
acceptable
some
limitations.
was
unsuitable
drinking
based
on
WQI
(WQI
81–104).
Oral
exposure
children
specific
components
a
higher
hazard
(HI
>
1)
compared
adults,
2.1
times
overall
non-carcinogenic
index.
However,
simulation
demonstrated
negligible
iron,
manganese,
nitrate
hazards
both
age
groups.
findings
are
valuable
management
decisions,
contributing
long-term
resource
sustainability.
Journal of Hydrology Regional Studies,
Journal Year:
2024,
Volume and Issue:
51, P. 101660 - 101660
Published: Jan. 19, 2024
National
Sustainable
Development
Agenda
Innovation
Demonstration
Zone
in
Lincang
City,
Southwest
China
Revealing
the
current
water
quality
status
rivers
and
reservoirs
its
drivers
is
crucial
to
achieving
United
Nations
Goal
6
(SDG
6).
We
assessed
spatial-temporal
dynamics
influence
of
natural
socioeconomic
factors
on
index
(WQI)
parameters
using
redundancy
analysis
(RDA)
partial
least
squares
path
model
(PLSPM).
The
results
indicate
following.
(1)
annual
average
values
WQI
City
from
2018
2020
were
92.26,
92.06,
92.45,
respectively.
spring,
summer,
autumn,
winter
92.48,
90.38,
92.68,
93.49,
seasonal
levels
good
or
higher.
However,
spatial
heterogeneity
exists
for
some
City.
(2)
highly
complex.
landscape
composition,
configuration,
pollutant
discharges
are
key
affecting
annually
seasonally,
a
scale
dependence
observed.
(3)
Chemical
physical
directly
affect
WQI,
particularly
at
small
scales
(100
m
500
buffer
zones).
have
strong
inhibitory
effect
(−0.79,
−0.78)
(−0.56,
−0.72),
whereas
weak
promoting
(0.05–0.13).
Landscape
composition
configuration
indirectly
WQI.
In
contrast,
pollution
discharge
impact
through
their
chemical
factors.
These
findings
demonstrate
that
social
interact
multiple
ways,
impacting
reservoirs.
This
interaction
depends
scale.
Therefore,
it
consider
appropriate
distance
future
land
use
planning,
design
planning
Moreover,
controlling
wastewater
industrial
agricultural
activities
domestic
usage
vital
ensuring
high
quality.
Heliyon,
Journal Year:
2024,
Volume and Issue:
10(4), P. e25416 - e25416
Published: Feb. 1, 2024
The
indicators
of
economic
and
sustainable
development
ultimately
significantly
depend
on
carbon
dioxide
(CO2)
emissions
in
every
country.
In
Bangladesh,
there
is
an
increasing
trend
population,
industrialization,
as
well
electricity
demand
generated
from
different
sources,
CO2
emissions.
This
study
explores
the
relationship
between
other
significant
relevant
indicators.
Moreover,
authors
aimed
to
identify
which
model
effective
at
predicting
assess
accuracy
prediction
models.
secondary
data
1971
2020,
was
collected
World
Bank
Bangladesh
Road
Transport
Authority's
publicly
accessible
website.
generalized
additive
(GAM),
polynomial
regression
(PR),
multiple
linear
(MLR)
were
used
for
modeling
performance
evaluated
using
Bayesian
information
criterion
(BIC),
Akaike
(AIC),
Root
mean
square
error
(RMSE),
R-square,
(MSE).
Results
revealed
that
are
few
multicollinearity
problems
datasets
exhibit
a
nonlinear
among
Among
models
considered
this
study,
GAM
has
lowest
value
RMSE
=
0.008,
MSE
0.000063,
AIC
−303.21,
BIC
−266.64
highest
R-squared
0.996
compared
MLR
PR
models,
suggesting
most
appropriate
Bangladesh.
Findings
total
risk
factors
non-linear.
suggests
Generalized
technique
can
be
tool
believed
findings
would
helpful
policymakers
designing
strategies
areas
low-carbon
economy,
encouraging
use
renewable
energy
focusing
technological
advancement
reduces
ensures
environment
