scholarly journals Self-Reinforcing Processes Governing Urban Sprawl in Belgium: Evidence over Six Decades

2020 ◽  
Vol 12 (10) ◽  
pp. 4097 ◽  
Author(s):  
Ahmed Mustafa ◽  
Jacques Teller
Keyword(s):  
Linear Regression ◽  
Population Density ◽  
Urban Sprawl ◽  
Urban Dispersion ◽  
Dispersion Degree ◽  
Dispersion Patterns ◽  
Study Country ◽  
Per Capita ◽  
Different Levels ◽  
Over Time

Urban sprawl is widely acknowledged as an environmental and socio-economic challenge worldwide. This study examines urban sprawl in Belgium over six decades from 1950 to 2010. We assume that sprawl is a self-reinforcing process, i.e., sprawl is fueling further sprawl over time. The main objective of this study is to examine this assumption. We measure urban sprawl at four different levels in this study: country, regions, municipalities, and 1-km2 cells. Three sprawl indices are employed: the degree of urban dispersion, degree of urban permeation of the landscape, and built-up land uptake per capita. These three indices consider both the growth of built-up areas and population density to measure the magnitude of sprawl. The drivers of urban sprawl have been analyzed at a 1-km2 level. The examined drivers are previous urban dispersion patterns, distance to urban cores, elevation, and slope degree by means of linear regression. Urban sprawl significantly increased between 1950 and 1980, whereas its increase was more moderate between 1980 and 2010. Urban dispersion and permeation strongly affect the Brussels and Flanders regions. The results show that the increase in the degree of dispersion is locally driven by previous values of dispersion; i.e., it provides an adequate milieu for further dispersion. Therefore, our conclusion is that urban sprawl in Belgium tends to be a self-reinforcing process.

An Analysis of Influencing Factors Relating to Population Aging in China Based on SPSS

2014 ◽  
Vol 644-650 ◽  
pp. 5561-5564
Author(s):  
Zi Heng He ◽  
Yi Dan Sun
Keyword(s):  
Principal Component Analysis ◽  
Linear Regression ◽  
Population Density ◽  
Influencing Factors ◽  
Linear Regression Model ◽  
Health Expenditure ◽  
Population Aging ◽  
Principal Component ◽  
Per Capita Gdp ◽  
Per Capita

In this essay, we analyze possible influencing factors which relate to population agingusing SPSS.In accord with the multivariable linear regression model, we conclude that the health expenditure of government and society along with population density have a significant correlation with population aging. Moreover, according to Principal Component Analysis (PCA), the result indicates that such factors as per capita GDP, citizen consumption and so forth have a prominent influence on population aging, and also analyze different influencing degrees of different factors during different periods.

scholarly journals CO<sub>2</sub> flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression

2007 ◽  
Vol 4 (6) ◽  
pp. 1005-1025 ◽  
Author(s):  
L. Kutzbach ◽  
J. Schneider ◽  
T. Sachs ◽  
M. Giebels ◽  
H. Nykänen ◽  
...  
Keyword(s):  
Linear Regression ◽  
Nonlinear Regression ◽  
Co2 Flux ◽  
Exponential Model ◽  
Co2 Uptake ◽  
Co2 Fluxes ◽  
Closed Chamber ◽  
Exponential Regression ◽  
Closure Time ◽  
Over Time

Abstract. Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach has been justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatlands sites in Finland and a tundra site in Siberia. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. However, a rather large percentage of the exponential regression functions showed curvatures not consistent with the theoretical model which is considered to be caused by violations of the underlying model assumptions. Especially the effects of turbulence and pressure disturbances by the chamber deployment are suspected to have caused unexplainable curvatures. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes. The degree of underestimation increased with increasing CO2 flux strength and was dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.

scholarly journals COVID-19 Mortality Rate and Its Incidence in Latin America: Dependence on Demographic and Economic Variables

2021 ◽  
Vol 18 (13) ◽  
pp. 6900
Author(s):  
Javier Cifuentes-Faura
Keyword(s):  
Latin America ◽  
Mortality Rate ◽  
Population Density ◽  
Life Expectancy ◽  
Latin American ◽  
Positive Influence ◽  
Death Rates ◽  
Per Capita ◽  
Latin American Countries ◽  
Quality Infrastructure

The pandemic caused by COVID-19 has left millions infected and dead around the world, with Latin America being one of the most affected areas. In this work, we have sought to determine, by means of a multiple regression analysis and a study of correlations, the influence of population density, life expectancy, and proportion of the population in vulnerable employment, together with GDP per capita, on the mortality rate due to COVID-19 in Latin American countries. The results indicated that countries with higher population density had lower numbers of deaths. Population in vulnerable employment and GDP showed a positive influence, while life expectancy did not appear to significantly affect the number of COVID-19 deaths. In addition, the influence of these variables on the number of confirmed cases of COVID-19 was analyzed. It can be concluded that the lack of resources can be a major burden for the vulnerable population in combating COVID-19 and that population density can ensure better designed institutions and quality infrastructure to achieve social distancing and, together with effective measures, lower death rates.

scholarly journals Non-Price Criteria for the Evaluation of the Tender Offers in Public Procurement of Ukraine

2020 ◽  
Vol 8 (3) ◽  
pp. 44
Author(s):  
Alexander Baranovsky ◽  
Nataliia Tkachenko ◽  
Vladimer Glonti ◽  
Valentyna Levchenko ◽  
Kateryna Bogatyrova ◽  
...  
Keyword(s):  
Public Procurement ◽  
Well Being ◽  
Gdp Per Capita ◽  
Tender Offers ◽  
Product Categories ◽  
Per Capita ◽  
The Government ◽  
The Impact ◽  
Over Time ◽  
The Eu

Traditionally, public procurement has been associated with the measurement of achieving savings. However, recent research shows that the economic impact of public procurement is not limited only to savings, but by measuring the impact of four capitals—natural, human, social, and economic—on sustainable well-being over time. Ukraine is a country with a very low gross domestic product (GDP) per capita, which exacerbates the problem of the impact of public procurement results on the population’s welfare. Ukrainian public procurement legislation allows customers to apply non-price criteria (the share of non-price criteria cannot be more than 70%), which, together, are taken into account in the formula of the quoted price. The studies show that the effect of the use of non-price criteria depends on the relevance of the method of the evaluation of non-price criteria. The most important non-price criteria for Ukrainian customers by product categories and the methods of their evaluation are analyzed according to the Bi.prozorro.org analytics module. Therefore, it is concluded that the quoted price method, which is used in Ukrainian practice, is not relevant in comparison with the method used in the EU. A survey of the government buyers on the practice of applying non-price criteria was conducted, and the areas of their use were identified.

Canadian Exceptionalism: Explaining Differences over Time in Provincial and Federal Voter Turnout

2001 ◽  
Vol 34 (2) ◽  
pp. 299-319 ◽  
Author(s):  
Donley T. Studlar
Keyword(s):  
Regression Analysis ◽  
Population Density ◽  
Multiple Regression Analysis ◽  
Voter Turnout ◽  
The Political ◽  
Federal Level ◽  
Industrial Democracies ◽  
Different Types ◽  
Over Time ◽  
Cross National

Canada is unusual among advanced industrial democracies in having some provinces which regularly have greater voter turnouts for provincial than for federal elections. Provincial and federal turnouts by province in Canada are analyzed for the 1945-1998 period using multiple regression analysis, both for each set of elections and by comparing differences between the two. Federal turnout has declined over the years but provincial turnout appears to have increased slightly. Although the effects found here largely confirm previous findings about the relative effects of different types of variables found for the Canadian federal level only, several of the political explanations previously supported in cross-national research find less support. Instead, region, population density, months since the last federal or provincial election, and season of the year generally have greater and sometimes more consistent effects. This suggests the need for more studies of turnout in democracies at sub-central levels.

scholarly journals Faculty Publishing Productivity: Comparisons over Time

2006 ◽  
Vol 67 (3) ◽  
pp. 230-239 ◽  
Author(s):  
John M. Budd
Keyword(s):  
Academic Librarians ◽  
Tenure Track ◽  
Data Set ◽  
Part Time Faculty ◽  
Time Period ◽  
Rate Of Increase ◽  
Part Time ◽  
Per Capita ◽  
Time Faculty ◽  
Over Time

Concerns about higher education abound, and these include concerns about productivity. The present study extends two previous examinations of faculty publishing productivity covering the years 1991 to 1993 and 1995 to 1997. Both members of ARL and a group of institutions included in ACRL’s data set are included. For both groups there are some increases in mean total numbers of publications, although the rate of increase has decreased since the second time period. Per capita rates of publication demonstrate an even flatter pattern. In recent years, there have been some changes in the dynamics of universities’ faculties; there are more part-time faculty and more faculty who are not on the tenure track. These factors, coupled with the publishing data, point to activities that all academic librarians should be aware of.

Abstract 3851: Temporal Distribution of Stroke Volumes and Clinical-Diffusion Mismatch in Patients with Proximal Arterial Occlusions

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Raul G Nogueira ◽  
David S Liebeskind ◽  
Leticia M Souza ◽  
Qing Hao ◽  
Karen Furie ◽  
...  
Keyword(s):  
Linear Regression ◽  
Infarct Volume ◽  
Linear Regression Analysis ◽  
Significant Proportion ◽  
Arterial Occlusion ◽  
Reperfusion Therapy ◽  
Poor Correlation ◽  
Lesion Volume ◽  
Collateral Flow ◽  
Over Time

Background and Purpose: Previous studies have demonstrated that the benefit of reperfusion therapy declines over time. The Clinical-Diffusion Mismatch (CDM) model has been suggested as surrogate for salvable tissue in acute ischemic stroke (AIS) patients. We sought to describe the temporal behavior profile of infarct volumes and CDM in patients suffering AIS due to proximal arterial occlusion (PAO). Methods: We performed a retrospective analysis of consecutive AIS patients admitted to two large academic institutions fulfilling the following criteria: (1) Baseline NIHSS ≥8; (2) PAO defined as MCA-M1, intracranial ICA, or tandem cervical + ICA/MCA-M1 occlusion on admission CTA/MRA; and (3) MRI-DWI performed ≤8 hours from time of stroke onset/last seen well (TSO). CDM was defined as baseline NIHSS ≥8 and DWI volume ≤25cc (as proposed by Davalos et al). Linear regression analysis was performed to define the changes on DWI lesion volume on presentation over time. The observed TSO to MRI were broken down into quartiles to look for any differences in the distribution of the baseline variables over time. Results: A total of 132 consecutive patients were identified (mean age, 66±16.8 years; 57% females; mean baseline NIHSS 17.5±5.3; occlusion site: MCA-M1, 64%; intracranial-ICA, 29%; tandem, 5%, mean TSO to DWI, 269.5±105.48 minutes). The mean DWI stroke volume on presentation was 46.7±54.8 cc (range, 0.19-436.1) and 63 (46.7%) patients had CDM. There was no significant changes in age, gender, baseline NIHSS, or occlusion site amongst the different time quartiles. Median infarct volume (cc) increased (quartile #1=8.5; #2=30.1; #3=38.5; #4=29.4) and the chances of having a CDM decreased (p<0.0001) across the different time quartiles. However, there was an overall poor correlation between DWI lesion volume on presentation and TSO to MRI (R-square=0.031, Figure ) and a significant proportion of the patients still had a CDM at later time epochs (#1=91.1%[20/22]; #2=47.8%[11/23]; #3=34.4%[21/61]; #4=42.3%[11/26]). Conclusions: Although infarct volume increases and the amount of penumbral tissue decreases over time, many patients with PAO will still have salvable penumbra at the later time epochs. This reflects individual differences in anatomic and physiological characteristics including the strength of collateral flow and highlights that selected patients may benefit from reperfusion therapy even at the later time windows. Figure : Relationship between Baseline DWI Volume (cc) and Time (minutes). Line is best fitted linear regression model.

Impact of urbanization on per capita energy use and emissions in India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stuti Haldar ◽  
Gautam Sharma
Keyword(s):  
Carbon Dioxide ◽  
Energy Consumption ◽  
Population Density ◽  
Carbon Dioxide Emissions ◽  
Energy Demand ◽  
Energy Use ◽  
Energy Intensity ◽  
Series Data ◽  
Content Type ◽  
Per Capita

Purpose The purpose of this study is to investigate the impacts of urbanization on per capita energy consumption and emissions in India. Design/methodology/approach The present study analyses the effects of urbanization on energy consumption patterns by using the Stochastic Impacts by Regression on Population, Affluence and Technology in India. Time series data from the period of 1960 to 2015 has been considered for the analysis. Variables including Population, GDP per capita, Energy intensity, share of industry in GDP, share of Services in GDP, total energy use and urbanization from World Bank data sources have been used for investigating the relationship between urbanization, affluence and energy use. Findings Energy demand is positively related to affluence (economic growth). Further the results of the analysis also suggest that, as urbanization, GDP and population are bound to increase in the future, consequently resulting in increased carbon dioxide emissions caused by increased energy demand and consumption. Thus, reducing the energy intensity is key to energy security and lower carbon dioxide emissions for India. Research limitations/implications The study will have important policy implications for India’s energy sector transition toward non- conventional, clean energy sources in the wake of growing share of its population residing in urban spaces. Originality/value There are limited number of studies considering the impacts of population density on per capita energy use. So this study also contributes methodologically by establishing per capita energy use as a function of population density and technology (i.e. growth rates of industrial and service sector).

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