Functions and regularity of topological spaces

́nski, Zbigniew Duszy

doi:10.5556/j.tkjm.40.2009.37

Cited by 3 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, due to incomplete data on the number of deaths due to SARS-CoV-2 infection, the database was supplemented with archival data, based on the database maintained by Michal Rogalski [64]. These reliable databases are commonly used in many studies that focus on the issue of the COVID-19 pandemic in Poland [65][66][67][68][69][70][71][72][73].…”

Section: Data Source and Processingmentioning

confidence: 99%

Multiscale Geographically Weighted Regression in the Investigation of Local COVID-19 Anomalies Based on Population Age Structure in Poland

Ciski

Rząsa

2023

IJERPH

View full text Add to dashboard Cite

A growing number of various studies focusing on different aspects of the COVID-19 pandemic are emerging as the pandemic continues. Three variables that are most commonly used to describe the course of the COVID-19 pandemic worldwide are the number of confirmed SARS-CoV-2 cases, the number of confirmed COVID-19 deaths, and the number of COVID-19 vaccine doses administered. In this paper, using the multiscale geographically weighted regression, an analysis of the interrelationships between the number of confirmed SARS-CoV-2 cases, the number of confirmed COVID-19 deaths, and the number of COVID-19 vaccine doses administered were conducted. Furthermore, using maps of the local R2 estimates, it was possible to visualize how the relations between the explanatory variables and the dependent variables vary across the study area. Thus, analysis of the influence of demographic factors described by the age structure and gender breakdown of the population over the course of the COVID-19 pandemic was performed. This allowed the identification of local anomalies in the course of the COVID-19 pandemic. Analyses were carried out for the area of Poland. The results obtained may be useful for local authorities in developing strategies to further counter the pandemic.

show abstract

Section: Data Source and Processingmentioning

confidence: 99%

Multiscale Geographically Weighted Regression in the Investigation of Local COVID-19 Anomalies Based on Population Age Structure in Poland

Ciski

Rząsa

2023

IJERPH

View full text Add to dashboard Cite

show abstract

“…The number of cases of SARS-CoV-2 in the counties in Poland was obtained from data collected from reports provided by the University of Warsaw, the Voivodeship Sanitary and Epidemiological Stations, and the County Sanitary and Epidemiological Stations and from materials obtained from requests for access to public information, as well as those collected from reports provided by the Ministry of Health; the database was published by Michal Rogalski and Konrad Kalemba [75][76][77]. This is a reliable source of data, used by many scientific studies examining the issue of the COVID-19 pandemic in Poland [14,[78][79][80][81][82][83][84]. The following, in Figure 2, presents the spatial distribution of the summary of the cases of SARS-CoV-2 in the counties of Poland, as of the end of 2021.…”

Section: Data Source and Processingmentioning

confidence: 99%

Influence of the Demographic, Social, and Environmental Factors on the COVID-19 Pandemic—Analysis of the Local Variations Using Geographically Weighted Regression

Rząsa

Ciski

2022

IJERPH

View full text Add to dashboard Cite

As the COVID-19 pandemic continues, an increasing number of different research studies focusing on various aspects of the pandemic are emerging. Most of the studies focus on the medical aspects of the pandemic, as well as on the impact of COVID-19 on various areas of life; less emphasis is put on analyzing the influence of socio-environmental factors on the spread of the pandemic. In this paper, using the geographically weighted regression method, the extent to which demographic, social, and environmental factors explain the number of cases of SARS-CoV-2 is explored. The research was performed for the case-study area of Poland, considering the administrative division of the country into counties. The results showed that the demographic factors best explained the number of cases of SARS-CoV-2; the social factors explained it to a medium degree; and the environmental factors explained it to the lowest degree. Urban population and the associated higher amount and intensity of human contact are the most influential factors in the development of the COVID-19 pandemic. The analysis of the factors related to the areas burdened by social problems resulting primarily from the economic exclusion revealed that poverty-burdened areas are highly vulnerable to the development of the COVID-19 pandemic. Using maps of the local R2 it was possible to visualize how the relationships between the explanatory variables (for this research—demographic, social, and environmental factors) and the dependent variable (number of cases of SARS-CoV-2) vary across the study area. Through the GWR method, counties were identified as particularly vulnerable to the pandemic because of the problem of economic exclusion. Considering that the COVID-19 pandemic is still ongoing, the results obtained may be useful for local authorities in developing strategies to counter the pandemic.

show abstract

“…These equations coincide with the analysis proposed by Lebiedzik [16] and used in Paluszy nski and Sl owko. [13] Thus, the proposed model can be seen as a generalization of this classical approach, to arbitrary detector number and geometry and curvature effects and non-linearities that may arise for steep slopes. Even without non-linearities, or curvature effect, let us underline that the proposed approach offers much more freedom and robustness to the analysis.…”

Section: Connection With Previous Modellingmentioning

confidence: 99%

“…The phenomena are present for nearly all types of detectors found in SEMs. [11][12][13] However, to faithfully reconstruct the surface, this gray-level intensity has to be converted to surface orientation. Consequently, it has to be predictable.…”

Section: Introductionmentioning

confidence: 99%

A generic topography reconstruction method based on multi‐detector backscattered electron images

Neggers

Héripré

Bonnet

et al. 2022

Strain

View full text Add to dashboard Cite

Surface topographies can be reconstructed from backscattered electron (BSE) images captured from different detector orientations. This article presents a very general approach to this problem, in the spirit of photometric stereo methods, allowing for arbitrary BSE detector number (at least 3) and shapes.The general idea is to both determine the (non-linear) model parameters and compute the surface topography so that the modelled images match at best the acquired ones. Three samples are used for validation of the measured topography with respect to atomic force microscopy (AFM) measurements. Root mean square (RMS) errors in the range of 10-35 nm, or 1-1.5% of total sampleheight, are obtained.

show abstract

Functions and regularity of topological spaces

Abstract: Preservation of regularity, almost regularity, and s-regularity of topological spaces, is considered.

Cited by 3 publications

References 5 publications

Multiscale Geographically Weighted Regression in the Investigation of Local COVID-19 Anomalies Based on Population Age Structure in Poland

Multiscale Geographically Weighted Regression in the Investigation of Local COVID-19 Anomalies Based on Population Age Structure in Poland

Influence of the Demographic, Social, and Environmental Factors on the COVID-19 Pandemic—Analysis of the Local Variations Using Geographically Weighted Regression

A generic topography reconstruction method based on multi‐detector backscattered electron images

Contact Info

Product

Resources

About