scholarly journals ON THE POPULATION DENSITY DISTRIBUTION ACROSS SPACE: A PROBABILISTIC APPROACH

2013 ◽  
Vol 53 (3) ◽  
pp. 481-510 ◽  
Author(s):  
Ilenia Epifani ◽  
Rosella Nicolini
Keyword(s):  
Population Density ◽  
Density Distribution ◽  
Probabilistic Approach

scholarly journals Population Distribution in the Wake of a Sphere

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1498 ◽  
Author(s):  
Taraprasad Bhowmick ◽  
Yong Wang ◽  
Michele Iovieno ◽  
Gholamhossein Bagheri ◽  
Eberhard Bodenschatz
Keyword(s):  
Reynolds Number ◽  
Spatial Distribution ◽  
Population Density ◽  
Density Distribution ◽  
Population Distribution ◽  
Fluid Velocity ◽  
Three Dimensional ◽  
Wake Flow ◽  
Sample Number ◽  
Scalar Fluxes

The physics of heat and mass transfer from an object in its wake has significant importance in natural phenomena as well as across many engineering applications. Here, we report numerical results on the population density of the spatial distribution of fluid velocity, pressure, scalar concentration, and scalar fluxes of a wake flow past a sphere in the steady wake regime (Reynolds number 25 to 285). Our findings show that the spatial population distributions of the fluid and the transported scalar quantities in the wake follow a Cauchy-Lorentz or Lorentzian trend, indicating a variation in its sample number density inversely proportional to the squared of its magnitude. We observe this universal form of population distribution both in the symmetric wake regime and in the more complex three dimensional wake structure of the steady oblique regime with Reynolds number larger than 225. The population density distribution identifies the increase in dimensionless kinetic energy and scalar fluxes with the increase in Reynolds number, whereas the dimensionless scalar population density shows negligible variation with the Reynolds number. Descriptive statistics in the form of population density distribution of the spatial distribution of the fluid velocity and the transported scalar quantities is important for understanding the transport and local reaction processes in specific regions of the wake, which can be used e.g., for understanding the microphysics of cloud droplets and aerosol interactions, or in the technical flows where droplets interact physically or chemically with the environment.

scholarly journals Resembling Population Density Distribution with Massive Mobile Phone Data

2018 ◽  
Vol 17 ◽  
Author(s):  
Teerayut Horanont ◽  
Thananut Phiboonbanakit ◽  
Santi Phithakkitnukoon
Keyword(s):  
Population Density ◽  
Density Distribution ◽  
Mobile Phone ◽  
Mobile Phone Data

scholarly journals The Relationship between Urban Population Density Distribution and Land Use in Guangzhou, China: A Spatial Spillover Perspective

2021 ◽  
Vol 18 (22) ◽  
pp. 12160
Author(s):  
Yisheng Peng ◽  
Jiahui Liu ◽  
Tianyao Zhang ◽  
Xiangyang Li
Keyword(s):  
Land Use ◽  
Population Density ◽  
Spatial Structure ◽  
Density Distribution ◽  
Rapid Growth ◽  
Urban Population ◽  
Spillover Effects ◽  
Urban Spatial Structure ◽  
Direct Effects ◽  
Spatial Spillover

Urban population density distribution contributes towards a deeper understanding of peoples’ activities patterns and urban vibrancy. The associations between the distribution of urban population density and land use are crucial to improve urban spatial structure. Despite numerous studies on population density distribution and land use, the significance of spatial dependence has attained less attention. Based on the Baidu heat map data and points of interests data in the main urban zone of Guangzhou, China, the current paper first investigated the spatial evolution and temporal distribution characteristics of urban population density and examined the spatial spillover influence of land use on it through spatial correlation analysis methods and the spatial Durbin model. The results show that the urban population density distribution is characterized by aggregation in general and varies on weekends and weekdays. The changes in population density within a day present a trend of “rapid growth-gentle decline-rapid growth-rapid decline”. Furthermore, the spatial spillover effects of land use exist and play the same important roles in population density distribution as the direct effects. Additionally, different types of land use show diverse direct effects and spatial spillover effects at various times. These findings suggest that balancing the population density distribution should consider the indirect effect from neighboring areas, which hopefully provide implications for urban planners and policy makers in utilizing the rational allocation of public resources and regarding optimization of urban spatial structure.

Microfilaria density distribution in the human population and its infectivity index for the mosquito population

Parasitology ◽  
1988 ◽  
Vol 96 (2) ◽  
pp. 265-271 ◽  
Author(s):  
Chai Bin Park
Keyword(s):  
Population Density ◽  
Density Distribution ◽  
Gamma Distribution ◽  
Blood Meal ◽  
Human Population ◽  
Host Population ◽  
Mosquito Population ◽  
Carrier Rate ◽  
Average Volume ◽  
Gamma Distributions

SummaryA new method of computing the infectivity index of microfilariae (mf) for the mosquito population is proposed using the estimated mf density distribution in the human population. The observed density distribution is considered a compound of the Poisson and the gamma distributions. The former distribution describes the probability of a specimen containing a specified number of mf and the latter describes the density distribution of mf in the host population. The mf infectivity index is the probability that a blood meal will include at least 1 mf, conditional on the population-density distribution of mf as specified by the gamma distribution. Actual data indicate that this population-density-based infectivity index can be considerably different from the conventional index based on the survey-density distribution. The level of the carrier rate of mf in a survey is greatly influenced, apart from the sample variation, by the average volume of blood taken from each person. The rate computed on the estimated population-density distribution of mf is convertible to any base amount of blood.

scholarly journals Spatial Estimation of Sika Deer Population Density Distribution

2007 ◽  
Vol 13 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Hiroshi Kondoh ◽  
Koichi Ikeda ◽  
Toru Koizumi
Keyword(s):  
Population Density ◽  
Density Distribution ◽  
Sika Deer ◽  
Spatial Estimation ◽  
Deer Population

scholarly journals Estimating COVID-19 outbreak risk through air travel

2020 ◽  
Author(s):  
Y. Daon ◽  
R.N. Thompson ◽  
U. Obolski
Keyword(s):  
Population Density ◽  
Probabilistic Approach ◽  
Disease Prevalence ◽  
Air Travel ◽  
Control Measures ◽  
Allocation Of Resources ◽  
Density Estimates ◽  
China And India ◽  
Specific Control ◽  
High Threat

AbstractBackgroundCOVID-19 has spread rapidly across the globe during the first several months of 2020, creating a pandemic. Substantial, non-discriminatory limitations have been imposed on air travel to inhibit this spread. As the disease prevalence and incidence will decrease, more specific control measures will be sought so that commercial air travel can continue to operate yet not impose a high threat of COVID-19 resurgence.MethodsWe use modelled global air travel data and population density estimates to analyse the risk posed by 1364 airports to initiate a COVID-19 outbreak. We calculate the risk using a probabilistic approach that considers the volume of air travelers between airports and the R0 of each location, scaled by population density. This exercise is performed globally as well as specifically for two potentially vulnerable locations: Africa and India.ResultsWe show that globally, many of the airports posing the highest risk are in China and India. An outbreak of COVID-19 in Africa is most likely to originate in a passenger travelling from Europe. On the other hand, the highest risk to India is from domestic travellers. Our results are robust to changes in the underlying epidemiological assumptions.ConclusionsVariation in flight volumes and destinations creates a non-uniform distribution of the risk different airports pose to resurgence of a COVID-19 outbreak. We suggest the method presented here as a tool for the estimation of this risk. Our method can be used to inform efficient allocation of resources, such as tests identifying infected passengers, so that they could be differentially deployed in various locations.

Palau's Rare and Threatened Palm Ponapea palauensis (Arecaceae): Population Density, Distribution, and Threat Assessment

2013 ◽  
Vol 67 (4) ◽  
pp. 599-607 ◽  
Author(s):  
Craig M. Costion ◽  
Ann Hillmann-Kitalong ◽  
Steve Perlman ◽  
Will Edwards
Keyword(s):  
Population Density ◽  
Density Distribution ◽  
Threat Assessment

Automated tracking approach with ant colonies for different cell population density distribution

2016 ◽  
Vol 21 (14) ◽  
pp. 3977-3992 ◽  
Author(s):  
Mingli Lu ◽  
Benlian Xu ◽  
Zhengqiang Jiang ◽  
Andong Sheng ◽  
Peiyi Zhu ◽  
...  
Keyword(s):  
Population Density ◽  
Density Distribution ◽  
Cell Population ◽  
Ant Colonies ◽  
Automated Tracking
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