Frontiers in Immunology,
Journal Year:
2022,
Volume and Issue:
13
Published: Feb. 24, 2022
The
coronavirus
disease
2019
(COVID-19)
pandemic
caused
by
the
severe
acute
respiratory
syndrome
2
(SARS-CoV-2)
has
become
a
public
health
emergency
of
international
concern,
and
an
effective
vaccine
is
urgently
needed
to
control
pandemic.
Envelope
(E)
membrane
(M)
proteins
are
highly
conserved
structural
among
SARS-CoV-2
SARS-CoV
have
been
proposed
as
potential
targets
for
development
cross-protective
vaccines.
Here,
synthetic
DNA
vaccines
encoding
E/M
(called
p-SARS-CoV-2-E/M)
were
developed,
mice
immunised
with
three
doses
via
intramuscular
injection
electroporation.
Significant
cellular
immune
responses
elicited,
whereas
no
robust
humoral
immunity
was
detected.
In
addition,
novel
H-2d-restricted
T-cell
epitopes
identified.
Notably,
although
drop
in
lung
tissue
virus
titre
detected
DNA-vaccinated
post-challenge
SARS-CoV-2,
immunisation
either
p-SARS-CoV-2-E
or
p-SARS-CoV-2-M
provided
minor
protection
co-immunisation
p-SARS-CoV-2-E+M
increased
protection.
Therefore,
should
be
considered
candidates
they
may
valuable
optimisation
vaccination
strategies
against
COVID-19.
Applied Soft Computing,
Journal Year:
2023,
Volume and Issue:
143, P. 110377 - 110377
Published: May 5, 2023
Neural
networks
have
been
successfully
employed
in
various
domains
such
as
classification,
regression
and
clustering,
etc.
Generally,
the
back
propagation
(BP)
based
iterative
approaches
are
used
to
train
neural
networks,
however,
it
results
issues
of
local
minima,
sensitivity
learning
rate
slow
convergence.
To
overcome
these
issues,
randomization
random
vector
functional
link
(RVFL)
network
proposed.
RVFL
model
has
several
characteristics
fast
training
speed,
direct
links,
simple
architecture,
universal
approximation
capability,
that
make
a
viable
randomized
network.
This
article
presents
first
comprehensive
review
evolution
model,
which
can
serve
extensive
summary
for
beginners
well
practitioners.
We
discuss
shallow
RVFLs,
ensemble
deep
RVFLs
models.
The
variations,
improvements
applications
models
discussed
detail.
Moreover,
we
different
hyperparameter
optimization
techniques
followed
literature
improve
generalization
performance
model.
Finally,
give
potential
future
research
directions/opportunities
inspire
researchers
RVFL's
architecture
algorithm
further.
Applied Intelligence,
Journal Year:
2021,
Volume and Issue:
51(5), P. 3086 - 3103
Published: Feb. 17, 2021
The
genome
of
the
novel
coronavirus
(COVID-19)
disease
was
first
sequenced
in
January
2020,
approximately
a
month
after
its
emergence
Wuhan,
capital
Hubei
province,
China.
COVID-19
sequencing
is
critical
to
understanding
virus
behavior,
origin,
how
fast
it
mutates,
and
for
development
drugs/vaccines
effective
preventive
strategies.
This
paper
investigates
use
artificial
intelligence
techniques
learn
interesting
information
from
sequences.
Sequential
pattern
mining
(SPM)
applied
on
computer-understandable
corpus
sequences
see
if
hidden
patterns
can
be
found,
which
reveal
frequent
nucleotide
bases
their
relationships
with
each
other.
Second,
sequence
prediction
models
are
evaluate
base(s)
predicted
previous
ones.
Third,
mutation
analysis
sequences,
an
algorithm
designed
find
locations
where
changed
calculate
rate.
Obtained
results
suggest
that
SPM
examine
evolution
variations
strains
respectively.
Heliyon,
Journal Year:
2021,
Volume and Issue:
7(10), P. e08143 - e08143
Published: Oct. 1, 2021
COVID-19
has
produced
a
global
pandemic
affecting
all
over
of
the
world.
Prediction
rate
spread
and
modeling
its
course
have
critical
impact
on
both
health
system
policy
makers.
Indeed,
making
depends
judgments
formed
by
prediction
models
to
propose
new
strategies
measure
efficiency
imposed
policies.
Based
nonlinear
complex
nature
this
disorder
difficulties
in
estimation
virus
transmission
features
using
traditional
epidemic
models,
artificial
intelligence
methods
been
applied
for
spread.
importance
machine
deep
learning
approaches
spreading
trend,
present
study,
we
review
studies
which
used
these
predict
number
cases
COVID-19.
Adaptive
neuro-fuzzy
inference
system,
long
short-term
memory,
recurrent
neural
network
multilayer
perceptron
are
among
mostly
regard.
We
compared
performance
several
Root
means
squared
error
(RMSE),
mean
absolute
(MAE),
R
