Research Square (Research Square),
Год журнала:
2021,
Номер
unknown
Опубликована: Сен. 27, 2021
Abstract
With
the
outbreak
of
COVID-19
pandemic,
many
seismologists
all
over
world
have
noted
a
sharp
(up
to
30-50%)
decrease
in
daily
background
seismic
noise
during
period
from
March
May,
2020
[Lecocqetal.,
2020].
The
authors
studied
influence
self-isolation
regime
introduced
Russian
Federation
30,
[On
declaring
...,
2020]
and,
as
consequence,
restriction
work
public
institutions
and
mobility
population,
on
quality
seismological
observations
at
stations
large
cities
Far
East
for
23,
April
12,
2020.
analyses
records
by
Khabarovsk
Vladivostok
located
busy
parts
accordingly,
strongly
influenced
anthropogenic
impact,
well
it
Yuzhno-Sakhalinsk
station
relatively
«calm»
part
city.
Power
spectra
temporal
variations
microseismic
levels
listed
above
were
constructed
based
data
broadband
seismometers
range
1-20
Hz.
analysis
level
with
population
was
carried
out
basis
index
Yandex,
which
shows
town
activity
selected
period.
main
sources
increased
identified.
Economy of Regions,
Год журнала:
2021,
Номер
17(4), С. 1079 - 1095
Опубликована: Янв. 1, 2021
Considering
the
widespread
of
Covid-19
and
its
impact
on
population
health
in
Russian
regions,
it
is
necessary
to
examine
pandemic
(as
excess
mortality)
regional
socio-economic
development
2020.
Based
a
quantitative
qualitative
model,
study
explains
process
coronavirus
diffusion
at
level,
using
information
from
foreign
publications,
statistics
database
legal
documents
«Consultant
+».
The
concept
spatial
diffusion,
developed
1950s-1980s,
was
chosen
as
research
methodology.
methods
include
cartographic
analysis
monthly
dynamics
spread
regions
regression
differences
mortality
regarding
most
significant
explanatory
variables.
model
across
2020,
while
proposed
«network-place-scaling»
describes
virus.
conducted
confirmed
relationship
between
virus
economic
specialisation
regions.
Simultaneously,
such
widely
discussed
factors
physical
density,
urbanisation
level
per
capita
income
did
not
show
correlation
with
mortality.
revealed
following
results.
There
discrepancy
actual
situation
expected
developments
according
simplified
centre-periphery
model.
important
variables,
explaining
interregional
share
employed
contact-intensive
wholesale
retail
trade
manufacturing
(large
production
teams);
proportion
over
65;
number
facilities
1000
people.
deemed
suitable
for
mechanisms
Future
studies
should
focus
examining
consequences
municipal
large
cities
urban
agglomerations
Russia.
Economies,
Год журнала:
2023,
Номер
11(9), С. 228 - 228
Опубликована: Сен. 5, 2023
In
the
post-pandemic
social
and
economic
conditions,
proper
assessment
of
effectiveness
regional
innovation
systems
(RISs)
becomes
a
key
endeavor.
our
paper,
we
highlight
necessity
to
enhance
set
indicators
used
evaluate
performance
in
countries
with
varying
capabilities.
Specifically,
concentrate
on
examining
case
studies
from
United
States,
Japan,
China,
Czech
Republic,
comparing
their
experiences
current
situation
innovations
Russia
drawing
lessons
for
this
country.
Utilizing
Global
Innovation
Index
(GII)
rankings,
conduct
an
analysis
characteristics
innovative
progress
propose
specific
groups
that
can
evaluating
advancement
different
regions.
Moreover,
determine
need
uniqueness,
flexibility,
adaptability
these
based
state’s
strategic
guidelines
field
potential
territory
as
well
factors
external
internal
influence.
addition,
present
results
bibliometric
network
research
publications
retrieved
Web
Science
(WoS)
database
using
VOSViewer
software
covering
role
shaping
up
national
(NISs)
both
general
terms
specifically
applied
Russia.
Our
might
be
relevant
stakeholders
policymakers
who
are
engaged
promoting
innovation,
development,
sustainable
growth,
academics
working
topics
development.
Japanese Journal of Statistics and Data Science,
Год журнала:
2021,
Номер
5(1), С. 363 - 377
Опубликована: Июнь 7, 2021
A
vast
majority
of
the
countries
are
under
economic
and
health
crises
due
to
current
epidemic
coronavirus
disease
2019
(COVID-19).
The
present
study
analyzes
COVID-19
using
time
series,
an
essential
gizmo
for
knowing
enlargement
infection
its
changing
behavior,
especially
trending
model.
We
consider
autoregressive
model
with
a
non-linear
trend
component
that
approximately
converts
into
linear
spline
function.
function
splits
series
different
piecewise
segments
between
respective
knots
in
form
various
growth
stages
fits
trend.
First,
we
obtain
number
their
locations
identify
transmission
infection.
Then,
estimation
parameters
is
obtained
Bayesian
setup
best-fitted
results
advocate
proposed
appropriately
determines
location
based
on
know
situation
pandemic
country.
GEOGRAPHY ENVIRONMENT SUSTAINABILITY,
Год журнала:
2021,
Номер
14(4), С. 117 - 124
Опубликована: Дек. 29, 2021
The
spread
of
the
2019
novel
coronavirus
disease
(COVID-19)
has
engulfed
world
with
a
rapid,
unexpected,
and
far-reaching
global
crisis.
In
study
COVID-19,
Geographic
Information
Systems
(GIS)
Remote
Sensing
(RS)
have
played
an
important
role
in
many
aspects,
especially
fight
against
COVID-19.
This
review
summarises
102
scientific
papers
on
applications
GIS
RS
studies
COVID-19
pandemic.
this
study,
two
themes
RS-related
are
grouped
into
six
categories
including
spatio-temporal
changes,
WebGISbased
mapping,
correlation
between
natural,
socio-economic
factors,
environmental
impacts.
findings
provide
insight
how
to
apply
new
techniques
(GIS
RS)
better
understand,
manage
evolution
pandemic
effectively
assess
its
Cities,
Год журнала:
2022,
Номер
125, С. 103676 - 103676
Опубликована: Март 23, 2022
The
Covid-19
pandemic,
with
its
epicentres
in
cities,
came
as
the
most
severe
social,
economic
and
financial
shock
of
21st
century.
reconstruction
pandemic
spread
determination
factors
conducive
to
preventing
from
SARS-CoV-2
virus
infections
well
searching
for
ways
combat
it
effects
have
become
subject
many
studies
analyses.
results
presented
this
article
are
part
research.
study
covered
20
large
Polish
cities
different
functions,
set
which:
(1)
course
infection
process
(by
means
a
rarely
used
trajectory
method)
was
determined
temporal
variation
(variance),
(2)
were
classified
terms
similarity
epidemic
(correlation
analysis),
(3)
literature
(using
multivariate
regression
verified.
In
case
investigation
also
carried
out
on
66
cities.
Generally,
relative
number
(per
10,000
inhabitants),
i.e.
intensity
infections,
basis
analysis.
research
has
shown
that
size,
function
location
within
country
no
influence
particular
Unfortunately,
not
possible
identify
could
be
responsible
or
at
least
determine
risk
(no
confirmed
impact
population
density,
level
poverty,
proportion
post-working
age
people's
health).
Thus,
obtained
testify
individual
nature
each
city
other
explanatory
features
than
those
considered
investigation,
effect
synergetic
interaction
more
just
socio-economic
features.
solution
issue
remains
open,
seems,
only
