993 resultados para Spatially Expanding Populations


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Discrete stochastic simulations, via techniques such as the Stochastic Simulation Algorithm (SSA) are a powerful tool for understanding the dynamics of chemical kinetics when there are low numbers of certain molecular species. However, an important constraint is the assumption of well-mixedness and homogeneity. In this paper, we show how to use Monte Carlo simulations to estimate an anomalous diffusion parameter that encapsulates the crowdedness of the spatial environment. We then use this parameter to replace the rate constants of bimolecular reactions by a time-dependent power law to produce an SSA valid in cases where anomalous diffusion occurs or the system is not well-mixed (ASSA). Simulations then show that ASSA can successfully predict the temporal dynamics of chemical kinetics in a spatially constrained environment.

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This paper presents a method of spatial sampling based on stratification by Local Moran’s I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.

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The stochastic simulation algorithm was introduced by Gillespie and in a different form by Kurtz. There have been many attempts at accelerating the algorithm without deviating from the behavior of the simulated system. The crux of the explicit τ-leaping procedure is the use of Poisson random variables to approximate the number of occurrences of each type of reaction event during a carefully selected time period, τ. This method is acceptable providing the leap condition, that no propensity function changes “significantly” during any time-step, is met. Using this method there is a possibility that species numbers can, artificially, become negative. Several recent papers have demonstrated methods that avoid this situation. One such method classifies, as critical, those reactions in danger of sending species populations negative. At most, one of these critical reactions is allowed to occur in the next time-step. We argue that the criticality of a reactant species and its dependent reaction channels should be related to the probability of the species number becoming negative. This way only reactions that, if fired, produce a high probability of driving a reactant population negative are labeled critical. The number of firings of more reaction channels can be approximated using Poisson random variables thus speeding up the simulation while maintaining the accuracy. In implementing this revised method of criticality selection we make use of the probability distribution from which the random variable describing the change in species number is drawn. We give several numerical examples to demonstrate the effectiveness of our new method.

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In this study, we consider how Fractional Differential Equations (FDEs) can be used to study the travelling wave phenomena in parabolic equations. As our method is conducted under intracellular environments that are highly crowded, it was discovered that there is a simple relationship between the travelling wave speed and obstacle density.

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The field of bereavement and grief has been expanding to recognise the potential for growth following the loss of a loved one. This study sought to examine the effect of the relationship to the deceased and perceptions of the severity of the trauma on dimensions of posttraumatic growth. Participants were 146 people who had lost either: a) a first degree relative, b) a second degree relative, or c) a non-related friend. Results demonstrated that both severity and the relationship to the bereaved differentiate posttraumatic growth outcomes. For example, participants who had lost a first degree relative reported higher levels of growth than those who had lost a second degree relative. Consistent with previous research in general trauma populations, the more severe the loss was rated, the higher the levels of growth. Implications for practice are discussed.

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This paper investigates a strategy for guiding school-based active travel intervention. School-based active travel programs address the travel behaviors and perceptions of small target populations (i.e., at individual schools) so they can encourage people to walk or bike. Thus, planners need to know as much as possible about the behaviors and perceptions of their target populations. However, existing strategies for modeling travel behavior and segmenting audiences typically work with larger populations and may not capture the attitudinal diversity of smaller groups. This case study used Q technique to identify salient travel-related attitude types among parents at an elementary school in Denver, Colorado; 161 parents presented their perspectives about school travel by rank-ordering 36 statements from strongly disagree to strongly agree in a normalized distribution, single centered around no opinion. Thirty-nine respondents' cases were selected for case-wise cluster analysis in SPSS according to criteria that made them most likely to walk: proximity to school, grade, and bus service. Analysis revealed five core perspectives that were then correlated with the larger respondent pool: optimistic walkers, fair-weather walkers, drivers of necessity, determined drivers, and fence sitters. Core perspectives are presented—characterized by parents' opinions, personal characteristics, and reported travel behaviors—and recommendations are made for possible intervention approaches. The study concludes that Q technique provides a fine-grained assessment of travel behavior for small populations, which would benefit small-scale behavioral interventions

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Continuum, partial differential equation models are often used to describe the collective motion of cell populations, with various types of motility represented by the choice of diffusion coefficient, and cell proliferation captured by the source terms. Previously, the choice of diffusion coefficient has been largely arbitrary, with the decision to choose a particular linear or nonlinear form generally based on calibration arguments rather than making any physical connection with the underlying individual-level properties of the cell motility mechanism. In this work we provide a new link between individual-level models, which account for important cell properties such as varying cell shape and volume exclusion, and population-level partial differential equation models. We work in an exclusion process framework, considering aligned, elongated cells that may occupy more than one lattice site, in order to represent populations of agents with different sizes. Three different idealizations of the individual-level mechanism are proposed, and these are connected to three different partial differential equations, each with a different diffusion coefficient; one linear, one nonlinear and degenerate and one nonlinear and nondegenerate. We test the ability of these three models to predict the population level response of a cell spreading problem for both proliferative and nonproliferative cases. We also explore the potential of our models to predict long time travelling wave invasion rates and extend our results to two dimensional spreading and invasion. Our results show that each model can accurately predict density data for nonproliferative systems, but that only one does so for proliferative systems. Hence great care must be taken to predict density data for with varying cell shape.

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‘Grounded Media’ is a form of art practice focused around the understanding that our ecological crisis is also a cultural crisis, perpetuated by our sense of separation from the material and immaterial ecologies upon which we depend. This misunderstanding of relationships manifests not only as environmental breakdown, but also in the hemorrhaging of our social fabric. ‘Grounded Media’ is consistent with an approach to media art making that I name ‘ecosophical’ and ‘praxis-led’ – which seeks through a range of strategies, to draw attention to the integrity, diversity and efficacy of the biophysical, social and electronic environments of which we are an integral part. It undertakes this through particular choices of location, interaction design,participative strategies and performative direction. This form of working emerged out of the production of two major projects, Grounded Light [8] and Shifting Intimacies [9] and is evident in a recent prototypical wearable art project called In_Step [6]. The following analysis and reflections will assist in promoting new, sustainable roles for media artists who are similarly interested in attuning their practices.

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Airports, whether publicly or privately owned or operated fill both public and private roles. They need to act as public infrastructure providers and as businesses which cover their operating costs. That leads to special governance concerns with respect to consumers and competitors which are only beginning to be addressed. These challenges are highlighted both by shifts in ownership status and by the expansion of roles performed by airports as passenger and cargo volumes continue to increase and as nearby urban areas expand outward towards airports. We survey five ways in which the regulatory shoe doesn‟t quite fit the needs. Our findings suggest that, while ad hoc measures limit political tension, new governance measures are needed.

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In this paper, spatially offset Raman spectroscopy (SORS) is demonstrated for non-invasively investigating the composition of drug mixtures inside an opaque plastic container. The mixtures consisted of three components including a target drug (acetaminophen or phenylephrine hydrochloride) and two diluents (glucose and caffeine). The target drug concentrations ranged from 5% to 100%. After conducting SORS analysis to ascertain the Raman spectra of the concealed mixtures, principal component analysis (PCA) was performed on the SORS spectra to reveal trends within the data. Partial least squares (PLS) regression was used to construct models that predicted the concentration of each target drug, in the presence of the other two diluents. The PLS models were able to predict the concentration of acetaminophen in the validation samples with a root-mean-square error of prediction (RMSEP) of 3.8% and the concentration of phenylephrine hydrochloride with an RMSEP of 4.6%. This work demonstrates the potential of SORS, used in conjunction with multivariate statistical techniques, to perform non-invasive, quantitative analysis on mixtures inside opaque containers. This has applications for pharmaceutical analysis, such as monitoring the degradation of pharmaceutical products on the shelf, in forensic investigations of counterfeit drugs, and for the analysis of illicit drug mixtures which may contain multiple components.