Determining the spatial distribution of nursing homes in China: a spatial heterogeneity analysis

2022 ◽  
Author(s):  
Bo Zhang ◽  
Shixiong He ◽  
Xingyu Chen ◽  
Lei Jiang
Keyword(s):  
Spatial Distribution ◽  
Nursing Homes ◽  
Spatial Heterogeneity ◽  
Heterogeneity Analysis

Spatial Distribution of Local Permeabilities in Fibrous Networks

1992 ◽  
Vol 62 (3) ◽  
pp. 151-161 ◽  
Author(s):  
Susan M. Montgomery ◽  
Bernard Miller ◽  
Ludwig Rebenfeld
Keyword(s):  
Spatial Distribution ◽  
Spatial Heterogeneity ◽  
Heterogeneous Networks ◽  
Flow Direction ◽  
Time Dependent ◽  
Dependent Development ◽  
Fabric Structure ◽  
Elliptical Flow ◽  
Fluid Boundary ◽  
Liquid Flows

The shape of a developing radial fluid boundary in the plane of a fabric is a reflection of the structure of the fabric. Homogeneous fabrics, with permeabilities independent of position, yield circular or elliptical flow fronts, depending on the existence of a universally preferred flow direction. Heterogeneous networks yield flow fronts that deviate from this elliptical shape due to spatial variations in permeability. The time-dependent development of the fluid front that occurs when liquid flows radially in the plane of a fabric may be analyzed using Darcy's law to calculate local fabric permeabilities. The resulting spatial distribution of permeabilities is representative of the spatial heterogeneity of the fabric structure. Sample permeability distributions of geotextile fabrics are discussed.

scholarly journals OA 07.06 Innate Genetic Evolution of Lung Cancers and Spatial Heterogeneity: Analysis of Treatment-Naïve Lesions

2017 ◽  
Vol 12 (11) ◽  
pp. S1762-S1763
Author(s):  
K. Suda ◽  
J. Kim ◽  
I. Murakami ◽  
L. Rozeboom ◽  
C. Rivard ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Genetic Evolution ◽  
Lung Cancers ◽  
Treatment Naïve ◽  
Heterogeneity Analysis

scholarly journals How spatial heterogeneity shapes multiscale biochemical reaction network dynamics

2015 ◽  
Vol 12 (104) ◽  
pp. 20141106 ◽  
Author(s):  
Peter Pfaffelhuber ◽  
Lea Popovic
Keyword(s):  
Spatial Distribution ◽  
Spatial Heterogeneity ◽  
Reaction Network ◽  
Stochastic Averaging ◽  
Multiscale Model ◽  
Point Of View ◽  
Rigorous Results ◽  
Biochemical Reaction Network ◽  
Molecular Movement ◽  
Heterogeneous Multiscale

Spatial heterogeneity in cells can be modelled using distinct compartments connected by molecular movement between them. In addition to movement, changes in the amount of molecules are due to biochemical reactions within compartments, often such that some molecular types fluctuate on a slower timescale than others. It is natural to ask the following questions: how sensitive is the dynamics of molecular types to their own spatial distribution, and how sensitive are they to the distribution of others? What conditions lead to effective homogeneity in biochemical dynamics despite heterogeneity in molecular distribution? What kind of spatial distribution is optimal from the point of view of some downstream product? Within a spatially heterogeneous multiscale model, we consider two notions of dynamical homogeneity (full homogeneity and homogeneity for the fast subsystem), and consider their implications under different timescales for the motility of molecules between compartments. We derive rigorous results for their dynamics and long-term behaviour, and illustrate them with examples of a shared pathway, Michaelis–Menten enzymatic kinetics and autoregulating feedbacks. Using stochastic averaging of fast fluctuations to their quasi-steady-state distribution, we obtain simple analytic results that significantly reduce the complexity and expedite simulation of stochastic compartment models of chemical reactions.

scholarly journals Innate Genetic Evolution of Lung Cancers and Spatial Heterogeneity: Analysis of Treatment-Naïve Lesions

2018 ◽  
Vol 13 (10) ◽  
pp. 1496-1507 ◽  
Author(s):  
Kenichi Suda ◽  
Jihye Kim ◽  
Isao Murakami ◽  
Leslie Rozeboom ◽  
Masaki Shimoji ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Genetic Evolution ◽  
Lung Cancers ◽  
Treatment Naïve ◽  
Heterogeneity Analysis

scholarly journals Identification of Dominant Factors Affecting Soil Erosion and Water Yield within Ecological Red Line Areas

2020 ◽  
Vol 12 (3) ◽  
pp. 399 ◽  
Author(s):  
Jiangbo Gao ◽  
Yuan Jiang ◽  
Huan Wang ◽  
Liyuan Zuo
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Spatial Heterogeneity ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Water Yield ◽  
Land Use Type ◽  
Functional Areas ◽  
Red Line

Soil conservation and water retention are important metrics for designating key ecological functional areas and ecological red line (ERL) areas. However, research on the quantitative identification of dominant environmental factors in different ecological red line areas remains relatively inadequate, which is unfavorable for the zone-based management of ecological functional areas. This paper presents a case study of Beijing’s ERL areas. In order to objectively reflect the ecological characteristics of ERL areas in Beijing, which is mainly dominated by mountainous areas, the application of remote sensing data at a high resolution is important for the improvement of model calculation and spatial heterogeneity. Based on multi-source remote sensing data, meteorological and soil observations as well as soil erosion and water yield were calculated using the revised universal soil loss equation (RUSLE) and integrated valuation of ecosystem services and tradeoffs (InVEST) model. Combining the influencing factors, including slope, precipitation, land use type, vegetation coverage, geomorphological type, and elevation, a quantitative attribution analysis was performed on soil erosion and water yield in Beijing’s ERL areas using the geographical detector. The power of each influencing factor and their interaction factors in explaining the spatial distribution of soil erosion or water yield varied significantly among different ERL areas. Vegetation coverage was the dominant factor affecting soil erosion in Beijing’s ERL areas, explaining greater than 30% of its spatial heterogeneity. Land use type could explain the spatial heterogeneity of water yield more than 60%. In addition, the combination of vegetation coverage and slope was found to significantly enhance the spatial distribution of soil erosion (>55% in various ERL areas). The superposition of land use type and slope explained greater than 70% of the spatial distribution for water yield in ERL areas. The geographical detector results indicated that the high soil erosion risk areas and high water yield areas varied significantly among different ERL areas. Thus, in efforts to enhance ERL protection, focus should be placed on the spatial heterogeneity of soil erosion and water yield in different ERL areas.

scholarly journals A Study of the Spatial Heterogeneity of Some Chemical Properties of Terabhor Back Using GIS

2019 ◽  
Vol 27 (1) ◽  
pp. 408-426
Author(s):  
Wurood Amer Abdul Amir ◽  
Amal Radi Jubair
Keyword(s):  
Electrical Conductivity ◽  
Organic Matter ◽  
Spatial Distribution ◽  
Spatial Heterogeneity ◽  
Chemical Properties ◽  
Spherical Model ◽  
Distribution Maps ◽  
American System ◽  
Circular Model ◽  
Random Samples

  Done studying the variability of the soils And the heterogeneity of the characteristics of the soils of the Euphrates, where 6 boreons were described and described the horizons of the pidoons as morphological and fundamental, as well as obtaining random samples on four equal depths 25-0 cm, 50-25 cm, 75-50 cm and 100-75 cm. The results of spatial heterogeneity Turbidity and Spatial Distribution Maps The heterogeneity of all the characteristics of chemical faecal soil is indicated by the results. The results indicate the variance of the horizons in the moving distance that describe the heterogeneity of the chemical properties, Electrical conductivity of EC Ranging between 0.48-5.46 and gypsum Ranging between 0.15 - 4.61 qualities more heterogeneous, and then followed by organic matter Ranging between 0.27-4.50 and CEC Ranging between 18.66-38.42 .                                                                                         The least heterogeneous properties were soil pH Ranging between 7.05- 7.62, followed by calcium carbonate Ranging between 284.28 - 438.71, where the range was high                                                                                                         The results showed that the appropriate model describing the heterogeneity of the chemical properties was the circular model, the appropriate model for describing its variation by 54%, followed by the spherical model of 43% and the gussin model of 4%. The soil of the study according to the modern American system 2014 is classified into two levels: Entisols and Mollisols .                                                                                              

scholarly journals Effects of socio-economic and environmental factors on the spatial heterogeneity of dengue fever investigated at a fine scale

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Yubing Qu ◽  
Xun Shi ◽  
Yong Wang ◽  
Rendong Li ◽  
Liang Lu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Environmental Factors ◽  
Spatial Heterogeneity ◽  
Dengue Fever ◽  
Scan Statistics ◽  
Fine Scale ◽  
Road Density ◽  
Risk Area ◽  
High Risk Area ◽  
Guangzhou City

The spatial pattern of dengue fever cases is the result of complex interactions between the virus, the host and the vector, which may be affected by environmental conditions. The largest outbreak of dengue fever in Guangzhou city, China occurred in 2014 with case numbers 2.7 times the number of cumulative cases since 1978 and a significantly non-random spatial distribution. Selecting Guangzhou City as the study area, we used scan statistics to analyze the spatial heterogeneity of dengue fever and a generalized additive model to evaluate and examine the effects of socio-economic and environmental factors on spatial heterogeneity at a fine scale. The study found that the spatial distribution of dengue fever is highly heterogeneous and various factors differ in relative importance. The junction of the central districts of Guangzhou is a high-risk area with the urban village and urban-rural fringe zone formed by urbanization as important regional factors. The low gross domestic product per capita, the high population density, the high road density were perceived as risk factors. The Asian subtropical coastal area together with the socioeconomic and environmental factors were found to be the key drivers at the fine scale explaining the high spatial heterogeneity of dengue fever in Guangzhou City.

Performance of sheep in simple spatial memory tasks

1997 ◽  
Vol 20 ◽  
pp. 86-87
Author(s):  
G. R. Edwards ◽  
J. A. Newman ◽  
A. J. Parsons ◽  
J. R. Krebs
Keyword(s):  
Spatial Distribution ◽  
Spatial Memory ◽  
Spatial Heterogeneity ◽  
Plant Species ◽  
Spatial Location ◽  
Complex Environments ◽  
Patch Use ◽  
Sward Height ◽  
Vegetation Characteristics ◽  
Preferred Species

Plant species or vegetation characteristics (e.g. sward height) are often distributed in patches within a background of continuous vegetation. Grazing animals exploit this spatial heterogeneity by concentrating their foraging in patches that are of preferred species or in patches that offer high rates of intake (Bazely, 1988). However, little is known of the mechanisms or individual behaviours that animals use to accomplish this preferential patch use. One hypothesis proposed to account for the preferential patch use is that animals remember information about the spatial distribution of the patches they encounter and use this information on subsequent foraging bouts to increase the rate at which they encounter preferred food patches (Bell, 1991). In this study, we tested whether sheep could remember the spatial location of patches in simple and complex environments or whether they needed continually to sample to know what was located in each area.

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