WorldWideScience

Sample records for modeling spatial establishment

  1. Using a data-constrained model of home range establishment to predict abundance in spatially heterogeneous habitats.

    Directory of Open Access Journals (Sweden)

    Mark C Vanderwel

    Full Text Available Mechanistic modelling approaches that explicitly translate from individual-scale resource selection to the distribution and abundance of a larger population may be better suited to predicting responses to spatially heterogeneous habitat alteration than commonly-used regression models. We developed an individual-based model of home range establishment that, given a mapped distribution of local habitat values, estimates species abundance by simulating the number and position of viable home ranges that can be maintained across a spatially heterogeneous area. We estimated parameters for this model from data on red-backed vole (Myodes gapperi abundances in 31 boreal forest sites in Ontario, Canada. The home range model had considerably more support from these data than both non-spatial regression models based on the same original habitat variables and a mean-abundance null model. It had nearly equivalent support to a non-spatial regression model that, like the home range model, scaled an aggregate measure of habitat value from local associations with habitat resources. The home range and habitat-value regression models gave similar predictions for vole abundance under simulations of light- and moderate-intensity partial forest harvesting, but the home range model predicted lower abundances than the regression model under high-intensity disturbance. Empirical regression-based approaches for predicting species abundance may overlook processes that affect habitat use by individuals, and often extrapolate poorly to novel habitat conditions. Mechanistic home range models that can be parameterized against abundance data from different habitats permit appropriate scaling from individual- to population-level habitat relationships, and can potentially provide better insights into responses to disturbance.

  2. Spatial cluster modelling

    CERN Document Server

    Lawson, Andrew B

    2002-01-01

    Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal ...

  3. Establishing the isolated Standard Model

    International Nuclear Information System (INIS)

    Wells, James D.; Zhang, Zhengkang; Zhao, Yue

    2017-02-01

    The goal of this article is to initiate a discussion on what it takes to claim ''there is no new physics at the weak scale,'' namely that the Standard Model (SM) is ''isolated.'' The lack of discovery of beyond the SM (BSM) physics suggests that this may be the case. But to truly establish this statement requires proving all ''connected'' BSM theories are false, which presents a significant challenge. We propose a general approach to quantitatively assess the current status and future prospects of establishing the isolated SM (ISM), which we give a reasonable definition of. We consider broad elements of BSM theories, and show many examples where current experimental results are not sufficient to verify the ISM. In some cases, there is a clear roadmap for the future experimental program, which we outline, while in other cases, further efforts - both theoretical and experimental - are needed in order to robustly claim the establishment of the ISM in the absence of new physics discoveries.

  4. Establishing the isolated Standard Model

    Energy Technology Data Exchange (ETDEWEB)

    Wells, James D.; Zhang, Zhengkang [Michigan Univ., Ann Arbor, MI (United States). Michigan Center for Theoretical Physics; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Zhao, Yue [Michigan Univ., Ann Arbor, MI (United States). Michigan Center for Theoretical Physics

    2017-02-15

    The goal of this article is to initiate a discussion on what it takes to claim ''there is no new physics at the weak scale,'' namely that the Standard Model (SM) is ''isolated.'' The lack of discovery of beyond the SM (BSM) physics suggests that this may be the case. But to truly establish this statement requires proving all ''connected'' BSM theories are false, which presents a significant challenge. We propose a general approach to quantitatively assess the current status and future prospects of establishing the isolated SM (ISM), which we give a reasonable definition of. We consider broad elements of BSM theories, and show many examples where current experimental results are not sufficient to verify the ISM. In some cases, there is a clear roadmap for the future experimental program, which we outline, while in other cases, further efforts - both theoretical and experimental - are needed in order to robustly claim the establishment of the ISM in the absence of new physics discoveries.

  5. Thermodynamic Model of Spatial Memory

    Science.gov (United States)

    Kaufman, Miron; Allen, P.

    1998-03-01

    We develop and test a thermodynamic model of spatial memory. Our model is an application of statistical thermodynamics to cognitive science. It is related to applications of the statistical mechanics framework in parallel distributed processes research. Our macroscopic model allows us to evaluate an entropy associated with spatial memory tasks. We find that older adults exhibit higher levels of entropy than younger adults. Thurstone's Law of Categorical Judgment, according to which the discriminal processes along the psychological continuum produced by presentations of a single stimulus are normally distributed, is explained by using a Hooke spring model of spatial memory. We have also analyzed a nonlinear modification of the ideal spring model of spatial memory. This work is supported by NIH/NIA grant AG09282-06.

  6. Examining the Spatial Distribution of Marijuana Establishments in Colorado

    Science.gov (United States)

    Kerski, Joseph

    2018-01-01

    In this 22-question activity, high school students investigate the spatial distribution of marijuana stores in Colorado using an interactive web map containing stores, centers, highways, population, and other data at several scales. After completing this lesson, students will know and be able to: (1) Use interactive maps, layers, and tools in…

  7. Establishing model credibility involves more than validation

    International Nuclear Information System (INIS)

    Kirchner, T.

    1991-01-01

    One widely used definition of validation is that the quantitative test of the performance of a model through the comparison of model predictions to independent sets of observations from the system being simulated. The ability to show that the model predictions compare well with observations is often thought to be the most rigorous test that can be used to establish credibility for a model in the scientific community. However, such tests are only part of the process used to establish credibility, and in some cases may be either unnecessary or misleading. Naylor and Finger extended the concept of validation to include the establishment of validity for the postulates embodied in the model and the test of assumptions used to select postulates for the model. Validity of postulates is established through concurrence by experts in the field of study that the mathematical or conceptual model contains the structural components and mathematical relationships necessary to adequately represent the system with respect to the goals for the model. This extended definition of validation provides for consideration of the structure of the model, not just its performance, in establishing credibility. Evaluation of a simulation model should establish the correctness of the code and the efficacy of the model within its domain of applicability. (24 refs., 6 figs.)

  8. Competition in spatial location models

    NARCIS (Netherlands)

    Webers, H.M.

    1996-01-01

    Models of spatial competition are designed and analyzed to describe the fact that space, by its very nature, is a source of market power. This field of research, lying at the interface of game theory and economics, has attracted much interest because location problems are related to many aspects of

  9. Establishing statistical models of manufacturing parameters

    International Nuclear Information System (INIS)

    Senevat, J.; Pape, J.L.; Deshayes, J.F.

    1991-01-01

    This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature

  10. A nonlocal spatial model for Lyme disease

    Science.gov (United States)

    Yu, Xiao; Zhao, Xiao-Qiang

    2016-07-01

    This paper is devoted to the study of a nonlocal and time-delayed reaction-diffusion model for Lyme disease with a spatially heterogeneous structure. In the case of a bounded domain, we first prove the existence of the positive steady state and a threshold type result for the disease-free system, and then establish the global dynamics for the model system in terms of the basic reproduction number. In the case of an unbound domain, we obtain the existence of the disease spreading speed and its coincidence with the minimal wave speed. At last, we use numerical simulations to verify our analytic results and investigate the influence of model parameters and spatial heterogeneity on the disease infection risk.

  11. Seedling establishment and physiological responses to temporal and spatial soil moisture changes

    Science.gov (United States)

    Jeremy Pinto; John D. Marshall; Kas Dumroese; Anthony S. Davis; Douglas R. Cobos

    2016-01-01

    In many forests of the world, the summer season (temporal element) brings drought conditions causing low soil moisture in the upper soil profile (spatial element) - a potentially large barrier to seedling establishment. We evaluated the relationship between initial seedling root depth, temporal and spatial changes in soil moisture during drought after...

  12. The quantitative modelling of human spatial habitability

    Science.gov (United States)

    Wise, J. A.

    1985-01-01

    A model for the quantitative assessment of human spatial habitability is presented in the space station context. The visual aspect assesses how interior spaces appear to the inhabitants. This aspect concerns criteria such as sensed spaciousness and the affective (emotional) connotations of settings' appearances. The kinesthetic aspect evaluates the available space in terms of its suitability to accommodate human movement patterns, as well as the postural and anthrometric changes due to microgravity. Finally, social logic concerns how the volume and geometry of available space either affirms or contravenes established social and organizational expectations for spatial arrangements. Here, the criteria include privacy, status, social power, and proxemics (the uses of space as a medium of social communication).

  13. Continuous Spatial Process Models for Spatial Extreme Values

    KAUST Repository

    Sang, Huiyan; Gelfand, Alan E.

    2010-01-01

    process model for extreme values that provides mean square continuous realizations, where the behavior of the surface is driven by the spatial dependence which is unexplained under the latent spatio-temporal specification for the GEV parameters

  14. Establishing an International Soil Modelling Consortium

    Science.gov (United States)

    Vereecken, Harry; Schnepf, Andrea; Vanderborght, Jan

    2015-04-01

    Soil is one of the most critical life-supporting compartments of the Biosphere. Soil provides numerous ecosystem services such as a habitat for biodiversity, water and nutrients, as well as producing food, feed, fiber and energy. To feed the rapidly growing world population in 2050, agricultural food production must be doubled using the same land resources footprint. At the same time, soil resources are threatened due to improper management and climate change. Soil is not only essential for establishing a sustainable bio-economy, but also plays a key role also in a broad range of societal challenges including 1) climate change mitigation and adaptation, 2) land use change 3) water resource protection, 4) biotechnology for human health, 5) biodiversity and ecological sustainability, and 6) combating desertification. Soils regulate and support water, mass and energy fluxes between the land surface, the vegetation, the atmosphere and the deep subsurface and control storage and release of organic matter affecting climate regulation and biogeochemical cycles. Despite the many important functions of soil, many fundamental knowledge gaps remain, regarding the role of soil biota and biodiversity on ecosystem services, the structure and dynamics of soil communities, the interplay between hydrologic and biotic processes, the quantification of soil biogeochemical processes and soil structural processes, the resilience and recovery of soils from stress, as well as the prediction of soil development and the evolution of soils in the landscape, to name a few. Soil models have long played an important role in quantifying and predicting soil processes and related ecosystem services. However, a new generation of soil models based on a whole systems approach comprising all physical, mechanical, chemical and biological processes is now required to address these critical knowledge gaps and thus contribute to the preservation of ecosystem services, improve our understanding of climate

  15. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  16. Recent developments in spatial analysis spatial statistics, behavioural modelling, and computational intelligence

    CERN Document Server

    Getis, Arthur

    1997-01-01

    In recent years, spatial analysis has become an increasingly active field, as evidenced by the establishment of educational and research programs at many universities. Its popularity is due mainly to new technologies and the development of spatial data infrastructures. This book illustrates some recent developments in spatial analysis, behavioural modelling, and computational intelligence. World renown spatial analysts explain and demonstrate their new and insightful models and methods. The applications are in areas of societal interest such as the spread of infectious diseases, migration behaviour, and retail and agricultural location strategies. In addition, there is emphasis on the uses of new technologoies for the analysis of spatial data through the application of neural network concepts.

  17. Continuous Spatial Process Models for Spatial Extreme Values

    KAUST Repository

    Sang, Huiyan

    2010-01-28

    We propose a hierarchical modeling approach for explaining a collection of point-referenced extreme values. In particular, annual maxima over space and time are assumed to follow generalized extreme value (GEV) distributions, with parameters μ, σ, and ξ specified in the latent stage to reflect underlying spatio-temporal structure. The novelty here is that we relax the conditionally independence assumption in the first stage of the hierarchial model, an assumption which has been adopted in previous work. This assumption implies that realizations of the the surface of spatial maxima will be everywhere discontinuous. For many phenomena including, e. g., temperature and precipitation, this behavior is inappropriate. Instead, we offer a spatial process model for extreme values that provides mean square continuous realizations, where the behavior of the surface is driven by the spatial dependence which is unexplained under the latent spatio-temporal specification for the GEV parameters. In this sense, the first stage smoothing is viewed as fine scale or short range smoothing while the larger scale smoothing will be captured in the second stage of the modeling. In addition, as would be desired, we are able to implement spatial interpolation for extreme values based on this model. A simulation study and a study on actual annual maximum rainfall for a region in South Africa are used to illustrate the performance of the model. © 2009 International Biometric Society.

  18. Spatial data quality and coastal spill modelling

    International Nuclear Information System (INIS)

    Li, Y.; Brimicombe, A.J.; Ralphs, M.P.

    1998-01-01

    Issues of spatial data quality are central to the whole oil spill modelling process. Both model and data quality performance issues should be considered as indispensable parts of a complete oil spill model specification and testing procedure. This paper presents initial results of research that will emphasise to modeler and manager alike the practical issues of spatial data quality for coastal oil spill modelling. It is centred around a case study of Jiao Zhou Bay in the People's Republic of China. The implications for coastal oil spill modelling are discussed and some strategies for managing the effects of spatial data quality in the outputs of oil spill modelling are explored. (author)

  19. Spatial Data Web Services Pricing Model Infrastructure

    Science.gov (United States)

    Ozmus, L.; Erkek, B.; Colak, S.; Cankurt, I.; Bakıcı, S.

    2013-08-01

    most important law with related NSDI is the establishment of General Directorate of Geographic Information System under the Ministry of Environment and Urbanism. due to; to do or to have do works and activities with related to the establishment of National Geographic Information Systems (NGIS), usage of NGIS and improvements of NGIS. Outputs of these projects are served to not only public administration but also to Turkish society. Today for example, TAKBIS data (cadastre services) are shared more than 50 institutions by Web services, Tusaga-Aktif system has more than 3800 users who are having real-time GPS data correction, Orthophoto WMS services has been started for two years as a charge of free. Today there is great discussion about data pricing among the institutions. Some of them think that the pricing is storage of the data. Some of them think that the pricing is value of data itself. There is no certain rule about pricing. On this paper firstly, pricing of data storage and later on spatial data pricing models in different countries are investigated to improve institutional understanding in Turkey.

  20. Bayesian Spatial Modelling with R-INLA

    Directory of Open Access Journals (Sweden)

    Finn Lindgren

    2015-02-01

    Full Text Available The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA approach proposed by Rue, Martino, and Chopin (2009 is a computationally effective alternative to MCMC for Bayesian inference. INLA is designed for latent Gaussian models, a very wide and flexible class of models ranging from (generalized linear mixed to spatial and spatio-temporal models. Combined with the stochastic partial differential equation approach (SPDE, Lindgren, Rue, and Lindstrm 2011, one can accommodate all kinds of geographically referenced data, including areal and geostatistical ones, as well as spatial point process data. The implementation interface covers stationary spatial mod- els, non-stationary spatial models, and also spatio-temporal models, and is applicable in epidemiology, ecology, environmental risk assessment, as well as general geostatistics.

  1. Intelligent spatial ecosystem modeling using parallel processors

    International Nuclear Information System (INIS)

    Maxwell, T.; Costanza, R.

    1993-01-01

    Spatial modeling of ecosystems is essential if one's modeling goals include developing a relatively realistic description of past behavior and predictions of the impacts of alternative management policies on future ecosystem behavior. Development of these models has been limited in the past by the large amount of input data required and the difficulty of even large mainframe serial computers in dealing with large spatial arrays. These two limitations have begun to erode with the increasing availability of remote sensing data and GIS systems to manipulate it, and the development of parallel computer systems which allow computation of large, complex, spatial arrays. Although many forms of dynamic spatial modeling are highly amenable to parallel processing, the primary focus in this project is on process-based landscape models. These models simulate spatial structure by first compartmentalizing the landscape into some geometric design and then describing flows within compartments and spatial processes between compartments according to location-specific algorithms. The authors are currently building and running parallel spatial models at the regional scale for the Patuxent River region in Maryland, the Everglades in Florida, and Barataria Basin in Louisiana. The authors are also planning a project to construct a series of spatially explicit linked ecological and economic simulation models aimed at assessing the long-term potential impacts of global climate change

  2. Dynamic spatial panels : models, methods, and inferences

    NARCIS (Netherlands)

    Elhorst, J. Paul

    This paper provides a survey of the existing literature on the specification and estimation of dynamic spatial panel data models, a collection of models for spatial panels extended to include one or more of the following variables and/or error terms: a dependent variable lagged in time, a dependent

  3. Spherical Process Models for Global Spatial Statistics

    KAUST Repository

    Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.

    2017-01-01

    Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture

  4. How informative are spatial CA3 representations established by the dentate gyrus?

    Directory of Open Access Journals (Sweden)

    Erika Cerasti

    2010-04-01

    Full Text Available In the mammalian hippocampus, the dentate gyrus (DG is characterized by sparse and powerful unidirectional projections to CA3 pyramidal cells, the so-called mossy fibers. Mossy fiber synapses appear to duplicate, in terms of the information they convey, what CA3 cells already receive from entorhinal cortex layer II cells, which project both to the dentate gyrus and to CA3. Computational models of episodic memory have hypothesized that the function of the mossy fibers is to enforce a new, well-separated pattern of activity onto CA3 cells, to represent a new memory, prevailing over the interference produced by the traces of older memories already stored on CA3 recurrent collateral connections. Can this hypothesis apply also to spatial representations, as described by recent neurophysiological recordings in rats? To address this issue quantitatively, we estimate the amount of information DG can impart on a new CA3 pattern of spatial activity, using both mathematical analysis and computer simulations of a simplified model. We confirm that, also in the spatial case, the observed sparse connectivity and level of activity are most appropriate for driving memory storage-and not to initiate retrieval. Surprisingly, the model also indicates that even when DG codes just for space, much of the information it passes on to CA3 acquires a non-spatial and episodic character, akin to that of a random number generator. It is suggested that further hippocampal processing is required to make full spatial use of DG inputs.

  5. Individual based model of slug population and spatial dynamics

    NARCIS (Netherlands)

    Choi, Y.H.; Bohan, D.A.; Potting, R.P.J.; Semenov, M.A.; Glen, D.M.

    2006-01-01

    The slug, Deroceras reticulatum, is one of the most important pests of agricultural and horticultural crops in UK and Europe. In this paper, a spatially explicit individual based model (IbM) is developed to study the dynamics of a population of D. reticulatum. The IbM establishes a virtual field

  6. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  7. Location Aggregation of Spatial Population CTMC Models

    Directory of Open Access Journals (Sweden)

    Luca Bortolussi

    2016-10-01

    Full Text Available In this paper we focus on spatial Markov population models, describing the stochastic evolution of populations of agents, explicitly modelling their spatial distribution, representing space as a discrete, finite graph. More specifically, we present a heuristic approach to aggregating spatial locations, which is designed to preserve the dynamical behaviour of the model whilst reducing the computational cost of analysis. Our approach combines stochastic approximation ideas (moment closure, linear noise, with computational statistics (spectral clustering to obtain an efficient aggregation, which is experimentally shown to be reasonably accurate on two case studies: an instance of epidemic spreading and a London bike sharing scenario.

  8. Spatial occupancy models for large data sets

    Science.gov (United States)

    Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.

    2013-01-01

    Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

  9. Evaluating spatial patterns in hydrological modelling

    DEFF Research Database (Denmark)

    Koch, Julian

    the contiguous United Sates (10^6 km2). To this end, the thesis at hand applies a set of spatial performance metrics on various hydrological variables, namely land-surface-temperature (LST), evapotranspiration (ET) and soil moisture. The inspiration for the applied metrics is found in related fields...... is not fully exploited by current modelling frameworks due to the lack of suitable spatial performance metrics. Furthermore, the traditional model evaluation using discharge is found unsuitable to lay confidence on the predicted catchment inherent spatial variability of hydrological processes in a fully...

  10. Crime Modeling using Spatial Regression Approach

    Science.gov (United States)

    Saleh Ahmar, Ansari; Adiatma; Kasim Aidid, M.

    2018-01-01

    Act of criminality in Indonesia increased both variety and quantity every year. As murder, rape, assault, vandalism, theft, fraud, fencing, and other cases that make people feel unsafe. Risk of society exposed to crime is the number of reported cases in the police institution. The higher of the number of reporter to the police institution then the number of crime in the region is increasing. In this research, modeling criminality in South Sulawesi, Indonesia with the dependent variable used is the society exposed to the risk of crime. Modelling done by area approach is the using Spatial Autoregressive (SAR) and Spatial Error Model (SEM) methods. The independent variable used is the population density, the number of poor population, GDP per capita, unemployment and the human development index (HDI). Based on the analysis using spatial regression can be shown that there are no dependencies spatial both lag or errors in South Sulawesi.

  11. A simplified spatial model for BWR stability

    International Nuclear Information System (INIS)

    Berman, Y.; Lederer, Y.; Meron, E.

    2012-01-01

    A spatial reduced order model for the study of BWR stability, based on the phenomenological model of March-Leuba et al., is presented. As one dimensional spatial dependence of the neutron flux, fuel temperature and void fraction is introduced, it is possible to describe both global and regional oscillations of the reactor power. Both linear stability analysis and numerical analysis were applied in order to describe the parameters which govern the model stability. The results were found qualitatively similar to past results. Doppler reactivity feedback was found essential for the explanation of the different regions of the flow-power stability map. (authors)

  12. Fractionating dead reckoning: role of the compass, odometer, logbook, and home base establishment in spatial orientation

    Science.gov (United States)

    Wallace, Douglas G.; Martin, Megan M.; Winter, Shawn S.

    2008-06-01

    Rats use multiple sources of information to maintain spatial orientation. Although previous work has focused on rats’ use of environmental cues, a growing number of studies have demonstrated that rats also use self-movement cues to organize navigation. This review examines the extent that kinematic analysis of naturally occurring behavior has provided insight into processes that mediate dead-reckoning-based navigation. This work supports a role for separate systems in processing self-movement cues that converge on the hippocampus. The compass system is involved in deriving directional information from self-movement cues; whereas, the odometer system is involved in deriving distance information from self-movement cues. The hippocampus functions similar to a logbook in that outward path unique information from the compass and odometer is used to derive the direction and distance of a path to the point at which movement was initiated. Finally, home base establishment may function to reset this system after each excursion and anchor environmental cues to self-movement cues. The combination of natural behaviors and kinematic analysis has proven to be a robust paradigm to investigate the neural basis of spatial orientation.

  13. Spatial scale separation in regional climate modelling

    Energy Technology Data Exchange (ETDEWEB)

    Feser, F.

    2005-07-01

    In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter

  14. Nonparametric Bayesian models for a spatial covariance.

    Science.gov (United States)

    Reich, Brian J; Fuentes, Montserrat

    2012-01-01

    A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.

  15. Research on the decision-making model of land-use spatial optimization

    Science.gov (United States)

    He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

    2009-10-01

    Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

  16. Landscape Modelling and Simulation Using Spatial Data

    Directory of Open Access Journals (Sweden)

    Amjed Naser Mohsin AL-Hameedawi

    2017-08-01

    Full Text Available In this paper a procedure was performed for engendering spatial model of landscape acclimated to reality simulation. This procedure based on combining spatial data and field measurements with computer graphics reproduced using Blender software. Thereafter that we are possible to form a 3D simulation based on VIS ALL packages. The objective was to make a model utilising GIS, including inputs to the feature attribute data. The objective of these efforts concentrated on coordinating a tolerable spatial prototype, circumscribing facilitation scheme and outlining the intended framework. Thus; the eventual result was utilized in simulation form. The performed procedure contains not only data gathering, fieldwork and paradigm providing, but extended to supply a new method necessary to provide the respective 3D simulation mapping production, which authorises the decision makers as well as investors to achieve permanent acceptance an independent navigation system for Geoscience applications.

  17. Spatial Modeling for Resources Framework (SMRF)

    Science.gov (United States)

    Spatial Modeling for Resources Framework (SMRF) was developed by Dr. Scott Havens at the USDA Agricultural Research Service (ARS) in Boise, ID. SMRF was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed. SMRF was developed...

  18. The 3-D global spatial data model foundation of the spatial data infrastructure

    CERN Document Server

    Burkholder, Earl F

    2008-01-01

    Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements. Modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Foundation of the Spatial Data Infrastructure offers a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This groundbreaking spatial model incorporates both a functional model and a stochastic model to connect the physical world to the ECEF rectangular system. Combining horizontal and vertical data into a single, three-dimensional database, this authoritative monograph provides a logical development of theoretical concepts and practical tools that can be used to handle spatial data mo...

  19. Differences in spatial understanding between physical and virtual models

    Directory of Open Access Journals (Sweden)

    Lei Sun

    2014-03-01

    Full Text Available In the digital age, physical models are still used as major tools in architectural and urban design processes. The reason why designers still use physical models remains unclear. In addition, physical and 3D virtual models have yet to be differentiated. The answers to these questions are too complex to account for in all aspects. Thus, this study only focuses on the differences in spatial understanding between physical and virtual models. In particular, it emphasizes on the perception of scale. For our experiment, respondents were shown a physical model and a virtual model consecutively. A questionnaire was then used to ask the respondents to evaluate these models objectively and to establish which model was more accurate in conveying object size. Compared with the virtual model, the physical model tended to enable quicker and more accurate comparisons of building heights.

  20. Spatially explicit modeling in ecology: A review

    Science.gov (United States)

    DeAngelis, Donald L.; Yurek, Simeon

    2017-01-01

    The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.

  1. Control of spatial discretisation in coastal oil spill modelling

    OpenAIRE

    Li, Yang

    2007-01-01

    Spatial discretisation plays an important role in many numerical environmental models. This paper studies the control of spatial discretisation in coastal oil spill modelling with a view to assure the quality of modelling outputs for given spatial data inputs. Spatial data analysis techniques are effective for investigating and improving the spatial discretisation in different phases of the modelling. Proposed methods are implemented and tested with experimental models. A new “Automatic Searc...

  2. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number...... variables of the system. However, this approach disregards any spatial structure of the system, which may potentially change the behaviour drastically. An alternative approach is to construct a cellular automaton with nearest neighbour interactions, or even to model the system as a complex network...... with interactions defined by network topology. In this thesis I first describe three different biological models of ageing and cancer, in which spatial structure is important for the system dynamics. I then turn to describe characteristics of ecosystems consisting of three cyclically interacting species...

  3. Linking spatial and dynamic models for traffic maneuvers

    DEFF Research Database (Denmark)

    Olderog, Ernst-Rüdiger; Ravn, Anders Peter; Wisniewski, Rafal

    2015-01-01

    For traffic maneuvers of multiple vehicles on highways we build an abstract spatial and a concrete dynamic model. In the spatial model we show the safety (collision freedom) of lane-change maneuvers. By linking the spatial and dynamic model via suitable refinements of the spatial atoms to distance...

  4. Developing a modelling for the spatial data infrastructure

    CSIR Research Space (South Africa)

    Hjelmager, J

    2005-07-01

    Full Text Available The Commission on Spatial Data Standards of the International Cartographic Association (ICA) is working on defining spatial models and technical characteristics of a Spatial Data Infrastructure (SDI). To date, this work has been restricted...

  5. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel

    2016-12-19

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  6. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.

    2016-01-01

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  7. Modeling Spatially Unrestricted Pedestrian Traffic on Footbridges

    DEFF Research Database (Denmark)

    Zivanovic, Stana; Pavic, Aleksandar; Ingólfsson, Einar Thór

    2010-01-01

    restricted movement of pedestrians, has kept attracting attention of researchers. However, it is the normal spatially unrestricted pedestrian traffic, and its vertical dynamic loading component, that are most relevant for vibration serviceability checks for most footbridges. Despite the existence of numerous...... design procedures concerned with this loading, the current confidence in its modelling is low due to lack of verification of the models on as-built structures. This is the motivation behind reviewing the existing design procedures for modelling normal pedestrian traffic in this paper and evaluating...

  8. Human Plague Risk: Spatial-Temporal Models

    Science.gov (United States)

    Pinzon, Jorge E.

    2010-01-01

    This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

  9. The quantitative modelling of human spatial habitability

    Science.gov (United States)

    Wise, James A.

    1988-01-01

    A theoretical model for evaluating human spatial habitability (HuSH) in the proposed U.S. Space Station is developed. Optimizing the fitness of the space station environment for human occupancy will help reduce environmental stress due to long-term isolation and confinement in its small habitable volume. The development of tools that operationalize the behavioral bases of spatial volume for visual kinesthetic, and social logic considerations is suggested. This report further calls for systematic scientific investigations of how much real and how much perceived volume people need in order to function normally and with minimal stress in space-based settings. The theoretical model presented in this report can be applied to any size or shape interior, at any scale of consideration, for the Space Station as a whole to an individual enclosure or work station. Using as a point of departure the Isovist model developed by Dr. Michael Benedikt of the U. of Texas, the report suggests that spatial habitability can become as amenable to careful assessment as engineering and life support concerns.

  10. Chapter 4: Establishment of the integrated modelling system

    International Nuclear Information System (INIS)

    1995-01-01

    This chapter summarizes how the Integrated Modelling System has been established. The Danubian Lowland Information System (DLIS) has been developed, providing a central database and Geographical Information System (GIS) with facilities for data storage, maintenance, processing and presentation. In addition, data can be imported and exported in the file formats readable for the applied modelling system

  11. Hybrid Spatial Data Model for Indoor Space: Combined Topology and Grid

    Directory of Open Access Journals (Sweden)

    Zhiyong Lin

    2017-11-01

    Full Text Available The construction and application of an indoor spatial data model is an important prerequisite to meet the requirements of diversified indoor spatial location services. The traditional indoor spatial topology model focuses on the construction of topology information. It has high path analysis and query efficiency, but ignores the spatial location information. The grid model retains the plane position information by grid, but increases the data volume and complexity of the model and reduces the efficiency of the model analysis. This paper presents a hybrid model for interior space based on topology and grid. Based on the spatial meshing and spatial division of the interior space, the model retains the position information and topological connectivity information of the interior space by establishing the connection or affiliation between the grid subspace and the topological subspace. The model improves the speed of interior spatial analysis and solves the problem of the topology information and location information updates not being synchronized. In this study, the A* shortest path query efficiency of typical daily indoor activities under the grid model and the hybrid model were compared for the indoor plane of an apartment and a shopping mall. The results obtained show that the hybrid model is 43% higher than the A* algorithm of the grid model as a result of the existence of topology communication information. This paper provides a useful idea for the establishment of a highly efficient and highly available interior spatial data model.

  12. Spatial Development Modeling Methodology Application Possibilities in Vilnius

    Directory of Open Access Journals (Sweden)

    Lina Panavaitė

    2017-05-01

    Full Text Available In order to control the continued development of high-rise buildings and their irreversible visual impact on the overall silhouette of the city, the great cities of the world introduced new methodological principles to city’s spatial development models. These methodologies and spatial planning guidelines are focused not only on the controlled development of high-rise buildings, but on the spatial modelling of the whole city by defining main development criteria and estimating possible consequences. Vilnius city is no exception, however the re-establishment of independence of Lithuania caused uncontrolled urbanization process, so most of the city development regulations emerged as a consequence of unmanaged processes of investors’ expectations legalization. The importance of consistent urban fabric as well as conservation and representation of city’s most important objects gained attention only when an actual threat of overshadowing them with new architecture along with unmanaged urbanization in the city center or urban sprawl at suburbia, caused by land-use projects, had emerged. Current Vilnius’ spatial planning documents clearly define urban structure and key development principles, however the definitions are relatively abstract, causing uniform building coverage requirements for territories with distinct qualities and simplifying planar designs which do not meet quality standards. The overall quality of urban architecture is not regulated. The article deals with current spatial modeling methods, their individual parts, principles, the criteria for quality assessment and their applicability in Vilnius. The text contains an outline of possible building coverage regulations and impact assessment criteria for new development. The article contains a compendium of requirements for high-quality spatial planning and building design.

  13. Modeling mental spatial reasoning about cardinal directions.

    Science.gov (United States)

    Schultheis, Holger; Bertel, Sven; Barkowsky, Thomas

    2014-01-01

    This article presents research into human mental spatial reasoning with orientation knowledge. In particular, we look at reasoning problems about cardinal directions that possess multiple valid solutions (i.e., are spatially underdetermined), at human preferences for some of these solutions, and at representational and procedural factors that lead to such preferences. The article presents, first, a discussion of existing, related conceptual and computational approaches; second, results of empirical research into the solution preferences that human reasoners actually have; and, third, a novel computational model that relies on a parsimonious and flexible spatio-analogical knowledge representation structure to robustly reproduce the behavior observed with human reasoners. Copyright © 2014 Cognitive Science Society, Inc.

  14. Establishment of modified reversible regional cerebral ischemic models

    International Nuclear Information System (INIS)

    Ji Xunming; Ling Feng; Zhao Xiqing; Xuan Yun; Wang Yueqin; Ling Xiaolan; Chang Hongjun; Zhang Zhiping

    2005-01-01

    Objective: Modifying the method of establishing reversible middle cerebral ischemic models in rats for improvement of the stability and rate of success, so as to raise the reliability of cerebral ischemic study. Methods: Sixty male Wistar rats were randomly divided into two groups, modified and control groups, 30 rats in each group. The method of silicone- tipping on one end of the nylon suture was used to modify the establishment of embolus, and tip-heating method was used to establish the traditional embolus with all the other steps of the procedure just the same. The Zea Longa 5 scoring scale was used to estimate the neurological deficiency while TTC staining method was used to measure and calculate the volume of cerebral infarction. The percentage of successful models with 3-4 grade scorings and the coefficient of the variations of cerebral infarct volume were used to estimate the stability of the models. Results: The rate of success of establishment models in the modification group was significantly higher in comparing with the traditional group (93% vs 60%, χ 2 =9.32, P=0.002). The percentage of model establishment with 3-4 grade neurological scores in modification group was higher than that in the traditional group 96.4% vs 61.2%, χ 2 =9.51, P=0.002). The cerebral infarct volume in modification group and traditional group were (4.1450±0.5019) cm 3 and (3.8435 ± 0.8164) cm 3 , and the coefficients of variation were 12.01% and 21.24% respectively, which indicated that the stability of models was significantly higher in modification group than in the traditional one. Conclusions: The rates of success and stability of the models for reversible focal cerebral ischemia made by the modification method were significantly improved, with decreasing the cost of model creation and increasing the accuracy of study of ischemic cerebral vascular disease. (authors)

  15. A Mathematical Approach to Establishing Constitutive Models for Geomaterials

    Directory of Open Access Journals (Sweden)

    Guang-hua Yang

    2013-01-01

    Full Text Available The mathematical foundation of the traditional elastoplastic constitutive theory for geomaterials is presented from the mathematical point of view, that is, the expression of stress-strain relationship in principal stress/strain space being transformed to the expression in six-dimensional space. A new framework is then established according to the mathematical theory of vectors and tensors, which is applicable to establishing elastoplastic models both in strain space and in stress space. Traditional constitutive theories can be considered as its special cases. The framework also enables modification of traditional constitutive models.

  16. Spatially varying coefficient models in real estate: Eigenvector spatial filtering and alternative approaches

    NARCIS (Netherlands)

    Helbich, M; Griffith, D

    2016-01-01

    Real estate policies in urban areas require the recognition of spatial heterogeneity in housing prices to account for local settings. In response to the growing number of spatially varying coefficient models in housing applications, this study evaluated four models in terms of their spatial patterns

  17. A Computational Model of Spatial Development

    Science.gov (United States)

    Hiraki, Kazuo; Sashima, Akio; Phillips, Steven

    Psychological experiments on children's development of spatial knowledge suggest experience at self-locomotion with visual tracking as important factors. Yet, the mechanism underlying development is unknown. We propose a robot that learns to mentally track a target object (i.e., maintaining a representation of an object's position when outside the field-of-view) as a model for spatial development. Mental tracking is considered as prediction of an object's position given the previous environmental state and motor commands, and the current environment state resulting from movement. Following Jordan & Rumelhart's (1992) forward modeling architecture the system consists of two components: an inverse model of sensory input to desired motor commands; and a forward model of motor commands to desired sensory input (goals). The robot was tested on the `three cups' paradigm (where children are required to select the cup containing the hidden object under various movement conditions). Consistent with child development, without the capacity for self-locomotion the robot's errors are self-center based. When given the ability of self-locomotion the robot responds allocentrically.

  18. Spherical Process Models for Global Spatial Statistics

    KAUST Repository

    Jeong, Jaehong

    2017-11-28

    Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture the spatial and temporal behavior of these global data sets. Though the geodesic distance is the most natural metric for measuring distance on the surface of a sphere, mathematical limitations have compelled statisticians to use the chordal distance to compute the covariance matrix in many applications instead, which may cause physically unrealistic distortions. Therefore, covariance functions directly defined on a sphere using the geodesic distance are needed. We discuss the issues that arise when dealing with spherical data sets on a global scale and provide references to recent literature. We review the current approaches to building process models on spheres, including the differential operator, the stochastic partial differential equation, the kernel convolution, and the deformation approaches. We illustrate realizations obtained from Gaussian processes with different covariance structures and the use of isotropic and nonstationary covariance models through deformations and geographical indicators for global surface temperature data. To assess the suitability of each method, we compare their log-likelihood values and prediction scores, and we end with a discussion of related research problems.

  19. Latent spatial models and sampling design for landscape genetics

    Science.gov (United States)

    Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

    2016-01-01

    We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

  20. Spatially varying dispersion to model breakthrough curves.

    Science.gov (United States)

    Li, Guangquan

    2011-01-01

    Often the water flowing in a karst conduit is a combination of contaminated water entering at a sinkhole and cleaner water released from the limestone matrix. Transport processes in the conduit are controlled by advection, mixing (dilution and dispersion), and retention-release. In this article, a karst transport model considering advection, spatially varying dispersion, and dilution (from matrix seepage) is developed. Two approximate Green's functions are obtained using transformation of variables, respectively, for the initial-value problem and for the boundary-value problem. A numerical example illustrates that mixing associated with strong spatially varying conduit dispersion can cause strong skewness and long tailing in spring breakthrough curves. Comparison of the predicted breakthrough curve against that measured from a dye-tracing experiment between Ames Sink and Indian Spring, Northwest Florida, shows that the conduit dispersivity can be as large as 400 m. Such a large number is believed to imply strong solute interaction between the conduit and the matrix and/or multiple flow paths in a conduit network. It is concluded that Taylor dispersion is not dominant in transport in a karst conduit, and the complicated retention-release process between mobile- and immobile waters may be described by strong spatially varying conduit dispersion. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.

  1. Indoor 3D Route Modeling Based On Estate Spatial Data

    Science.gov (United States)

    Zhang, H.; Wen, Y.; Jiang, J.; Huang, W.

    2014-04-01

    Indoor three-dimensional route model is essential for space intelligence navigation and emergency evacuation. This paper is motivated by the need of constructing indoor route model automatically and as far as possible. By comparing existing building data sources, this paper firstly explained the reason why the estate spatial management data is chosen as the data source. Then, an applicable method of construction three-dimensional route model in a building is introduced by establishing the mapping relationship between geographic entities and their topological expression. This data model is a weighted graph consist of "node" and "path" to express the spatial relationship and topological structure of a building components. The whole process of modelling internal space of a building is addressed by two key steps: (1) each single floor route model is constructed, including path extraction of corridor using Delaunay triangulation algorithm with constrained edge, fusion of room nodes into the path; (2) the single floor route model is connected with stairs and elevators and the multi-floor route model is eventually generated. In order to validate the method in this paper, a shopping mall called "Longjiang New City Plaza" in Nanjing is chosen as a case of study. And the whole building space is constructed according to the modelling method above. By integrating of existing path finding algorithm, the usability of this modelling method is verified, which shows the indoor three-dimensional route modelling method based on estate spatial data in this paper can support indoor route planning and evacuation route design very well.

  2. An Evolutionary Model of Spatial Competition

    DEFF Research Database (Denmark)

    Knudsen, Thorbjørn; Winter, Sidney G.

      This paper sets forth an evolutionary model in which diverse businesses, with diverse offerings, compete in a stylized physical space.  When a business firm attempts to expand its activity, so as to profit further from the capabilities it has developed, it necessarily does so in a "new location...... as well in the new environment as they did in the old; the firm may respond with effort to locate appropriate environments or by modification of its routines.  Tradeoffs are presented between the complexity of a business model and its replication costs,  as well as issues involving response....... Randomly generated firm policies are tested first by a local market environment, and then, if success leads the firm to grow spatially, in a gradually expanding environment.  In the initial experiments reported here, we show that the model generates configurations that reflect features of the exogenous...

  3. Discussion on the establishment of blood glucose fluctuation animal models

    OpenAIRE

    Chun-Liu Gai; Jing-Ru Zhao; Xiao-Long Chen

    2014-01-01

    AIM: To provide the experimental basis for the in vivo study of blood glucose fluctuation injury mechanism, through intraperitoneal injection of glucose to establish blood glucose fluctuation animal models and to simulate blood glucose fluctuation of patients with diabetes.METHODS: Rats were randomly divided into four groups: normal control group(NC), normal fluctuation group(NF), diabetes mellitus group(DM)and diabetes fluctuation group(DF). Diabetic models were induced through intraperitone...

  4. Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable

    NARCIS (Netherlands)

    Elhorst, J. Paul

    2001-01-01

    This paper surveys panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable. In particular, it focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the

  5. Establishing an academic laboratory: mentoring as a business model.

    Science.gov (United States)

    Greco, Valentina

    2014-11-01

    It is a tremendous honor for my group and me to receive the recognition of the 2014 Women in Cell Biology Junior Award. I would like to take the opportunity of this essay to describe my scientific journey, discuss my philosophy about running a group, and propose what I think is a generalizable model to efficiently establish an academic laboratory. This essay is about my view on the critical components that go into establishing a highly functional academic laboratory during the current tough, competitive times. © 2014 Greco.

  6. Establishment of animal model with half-liver cirrhosis

    International Nuclear Information System (INIS)

    Yang Zhenghan; Zhou Cheng; Chen Min; Xie Jingxia; Zhang Yuewu; Hu Bifang; Mo Hongbo; Wu Xiao

    2003-01-01

    Objective: To establish a new cirrhosis model suitable for imaging study. Methods: Via a 4 F catheter, 50-100 μl of carbon tetrachloride was injected into the left or right hepatic artery of 12 dogs fortnightly. Liver functional test, imaging study, and pathological examination were performed in these dogs regularly. Results: As the times of injection increased, necrosis of hepatocytes, fibrosis, and cirrhosis of the liver aggravated. In each dog, cirrhosis was more serious in the half liver with carbon tetrachloride injection than in the other half liver without carbon tetrachloride injection. With this model, it was convenient to perform the imaging study of liver cirrhosis. Conclusion: Animal model with half-liver cirrhosis can be established by combining catheter technique and traditional method

  7. Spatial Stochastic Point Models for Reservoir Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Syversveen, Anne Randi

    1997-12-31

    The main part of this thesis discusses stochastic modelling of geology in petroleum reservoirs. A marked point model is defined for objects against a background in a two-dimensional vertical cross section of the reservoir. The model handles conditioning on observations from more than one well for each object and contains interaction between objects, and the objects have the correct length distribution when penetrated by wells. The model is developed in a Bayesian setting. The model and the simulation algorithm are demonstrated by means of an example with simulated data. The thesis also deals with object recognition in image analysis, in a Bayesian framework, and with a special type of spatial Cox processes called log-Gaussian Cox processes. In these processes, the logarithm of the intensity function is a Gaussian process. The class of log-Gaussian Cox processes provides flexible models for clustering. The distribution of such a process is completely characterized by the intensity and the pair correlation function of the Cox process. 170 refs., 37 figs., 5 tabs.

  8. Theoretical aspects of spatial-temporal modeling

    CERN Document Server

    Matsui, Tomoko

    2015-01-01

    This book provides a modern introductory tutorial on specialized theoretical aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter provides up-to-date coverage of particle association measures that underpin the theoretical properties of recently developed random set methods in space and time otherwise known as the class of probability hypothesis density framework (PHD filters). The second chapter gives an overview of recent advances in Monte Carlo methods for Bayesian filtering in high-dimensional spaces. In particular, the chapter explains how one may extend classical sequential Monte Carlo methods for filtering and static inference problems to high dimensions and big-data applications. The third chapter presents an overview of generalized families of processes that extend the class of Gaussian process models to heavy-tailed families known as alph...

  9. Models and Inference for Multivariate Spatial Extremes

    KAUST Repository

    Vettori, Sabrina

    2017-12-07

    The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing to the developing research field of Extreme-Value Theory. We initially study the performance of existing parametric and non-parametric estimators of extremal dependence for multivariate maxima. As the dimensionality increases, non-parametric estimators are more flexible than parametric methods but present some loss in efficiency that we quantify under various scenarios. We introduce a statistical tool which imposes the required shape constraints on non-parametric estimators in high dimensions, significantly improving their performance. Furthermore, by embedding the tree-based max-stable nested logistic distribution in the Bayesian framework, we develop a statistical algorithm that identifies the most likely tree structures representing the data\\'s extremal dependence using the reversible jump Monte Carlo Markov Chain method. A mixture of these trees is then used for uncertainty assessment in prediction through Bayesian model averaging. The computational complexity of full likelihood inference is significantly decreased by deriving a recursive formula for the nested logistic model likelihood. The algorithm performance is verified through simulation experiments which also compare different likelihood procedures. Finally, we extend the nested logistic representation to the spatial framework in order to jointly model multivariate variables collected across a spatial region. This situation emerges often in environmental applications but is not often considered in the current literature. Simulation experiments show that the new class of multivariate max-stable processes is able to detect both the cross and inner spatial dependence of a number of extreme variables at a relatively low computational cost, thanks to its Bayesian hierarchical

  10. A framework to establish credibility of computational models in biology.

    Science.gov (United States)

    Patterson, Eann A; Whelan, Maurice P

    2017-10-01

    Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  11. Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models

    Science.gov (United States)

    Haslauer, C. P.; Bárdossy, A.

    2017-12-01

    A copula based multivariate framework allows more flexibility to describe different kind of dependences than what is possible using models relying on the confining assumption of symmetric Gaussian models: different quantiles can be modelled with a different degree of dependence; it will be demonstrated how this can be expected given process understanding. maximum likelihood based multivariate quantitative parameter estimation yields stable and reliable results; not only improved results in cross-validation based measures of uncertainty are obtained but also a more realistic spatial structure of uncertainty compared to second order models of dependence; as much information as is available is included in the parameter estimation: incorporation of censored measurements (e.g., below detection limit, or ones that are above the sensitive range of the measurement device) yield to more realistic spatial models; the proportion of true zeros can be jointly estimated with and distinguished from censored measurements which allow estimates about the age of a contaminant in the system; secondary information (categorical and on the rational scale) has been used to improve the estimation of the primary variable; These copula based multivariate statistical techniques are demonstrated based on hydraulic conductivity observations at the Borden (Canada) site, the MADE site (USA), and a large regional groundwater quality data-set in south-west Germany. Fields of spatially distributed K were simulated with identical marginal simulation, identical second order spatial moments, yet substantially differing solute transport characteristics when numerical tracer tests were performed. A statistical methodology is shown that allows the delineation of a boundary layer separating homogenous parts of a spatial data-set. The effects of this boundary layer (macro structure) and the spatial dependence of K (micro structure) on solute transport behaviour is shown.

  12. Modeling strategic investment decisions in spatial markets

    International Nuclear Information System (INIS)

    Lorenczik, Stefan; Malischek, Raimund

    2014-01-01

    Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models. The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market. Results may vary substantially between the different models. The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly.

  13. Spatially explicit modelling of cholera epidemics

    Science.gov (United States)

    Finger, F.; Bertuzzo, E.; Mari, L.; Knox, A. C.; Gatto, M.; Rinaldo, A.

    2013-12-01

    Epidemiological models can provide crucial understanding about the dynamics of infectious diseases. Possible applications range from real-time forecasting and allocation of health care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. We apply a spatially explicit model to the cholera epidemic that struck Haiti in October 2010 and is still ongoing. The dynamics of susceptibles as well as symptomatic and asymptomatic infectives are modelled at the scale of local human communities. Dissemination of Vibrio cholerae through hydrological transport and human mobility along the road network is explicitly taken into account, as well as the effect of rainfall as a driver of increasing disease incidence. The model is calibrated using a dataset of reported cholera cases. We further model the long term impact of several types of interventions on the disease dynamics by varying parameters appropriately. Key epidemiological mechanisms and parameters which affect the efficiency of treatments such as antibiotics are identified. Our results lead to conclusions about the influence of different intervention strategies on the overall epidemiological dynamics.

  14. Modeling strategic investment decisions in spatial markets

    Energy Technology Data Exchange (ETDEWEB)

    Lorenczik, Stefan; Malischek, Raimund [Koeln Univ. (Germany). Energiewirtschaftliches Inst.; Trueby, Johannes [International Energy Agency, 75 - Paris (France)

    2014-04-15

    Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models. The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market. Results may vary substantially between the different models. The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly.

  15. A strategy to establish Food Safety Model Repositories.

    Science.gov (United States)

    Plaza-Rodríguez, C; Thoens, C; Falenski, A; Weiser, A A; Appel, B; Kaesbohrer, A; Filter, M

    2015-07-02

    Transferring the knowledge of predictive microbiology into real world food manufacturing applications is still a major challenge for the whole food safety modelling community. To facilitate this process, a strategy for creating open, community driven and web-based predictive microbial model repositories is proposed. These collaborative model resources could significantly improve the transfer of knowledge from research into commercial and governmental applications and also increase efficiency, transparency and usability of predictive models. To demonstrate the feasibility, predictive models of Salmonella in beef previously published in the scientific literature were re-implemented using an open source software tool called PMM-Lab. The models were made publicly available in a Food Safety Model Repository within the OpenML for Predictive Modelling in Food community project. Three different approaches were used to create new models in the model repositories: (1) all information relevant for model re-implementation is available in a scientific publication, (2) model parameters can be imported from tabular parameter collections and (3) models have to be generated from experimental data or primary model parameters. All three approaches were demonstrated in the paper. The sample Food Safety Model Repository is available via: http://sourceforge.net/projects/microbialmodelingexchange/files/models and the PMM-Lab software can be downloaded from http://sourceforge.net/projects/pmmlab/. This work also illustrates that a standardized information exchange format for predictive microbial models, as the key component of this strategy, could be established by adoption of resources from the Systems Biology domain. Copyright © 2015. Published by Elsevier B.V.

  16. Establishment of animal model of dual liver transplantation in rat.

    Directory of Open Access Journals (Sweden)

    Ying Zhang

    Full Text Available The animal model of the whole-size and reduced-size liver transplantation in both rat and mouse has been successfully established. Because of the difficulties and complexities in microsurgical technology, the animal model of dual liver transplantation was still not established for twelve years since the first human dual liver transplantation has been made a success. There is an essential need to establish this animal model to lay a basic foundation for clinical practice. To study the physiological and histopathological changes of dual liver transplantation, "Y" type vein from the cross part between vena cava and two iliac of donor and "Y' type prosthesis were employed to recanalize portal vein and the bile duct between dual liver grafts and recipient. The dual right upper lobes about 45-50% of the recipient liver volume were taken as donor, one was orthotopically implanted at its original position, the other was rotated 180° sagitally and heterotopically positioned in the left upper quadrant. Microcirculation parameters, liver function, immunohistochemistry and survival were analyzed to evaluate the function of dual liver grafts. No significant difference in the hepatic microcirculatory flow was found between two grafts in the first 90 minutes after reperfusion. Light and electronic microscope showed the liver architecture was maintained without obvious features of cellular destruction and the continuity of the endothelium was preserved. Only 3 heterotopically positioned graft appeared patchy desquamation of endothelial cell, mitochondrial swelling and hepatocytes cytoplasmic vacuolization. Immunohistochemistry revealed there is no difference in hepatocyte activity and the ability of endothelia to contract and relax after reperfusion between dual grafts. Dual grafts made a rapid amelioration of liver function after reperfusion. 7 rats survived more than 7 days with survival rate of 58.3.%. Using "Y" type vein and bile duct prosthesis, we

  17. Rabbit models of cerebral vasospasm established with endovascular puncture

    International Nuclear Information System (INIS)

    Tu Jianfei; Liu Yizhi; Ji Jiansong; Zhao Zhongwei

    2008-01-01

    Objective: To investigate the method of endovascular puncture to establish rabbit models of cerebral vasospasm. Methods: New Zealand white rabbits were divided into 5 groups (12 h, 1 d, 2 d, 3 d and 7 d) randomly, and each group was separated into subarachnoid hemorrhage (SAH) subgroup (n=5) and control subgroup (n=2). cerebral vascular spasm (CVS) models were established after SAH with endovascular puncture. CT scans before and after operation were performed. The internal diameters and the wall thicknesses of posterior communicans artery (PcoA) and basilar artery (BA) were measured with HE stain after the animals were executed. Results: CVS model was successfully eastblished in 35 rabbits (SAH subgroup 25, control subgroup 10), resulting a successful rate of 48.61%. Compared with control subgroup, PcoA and BA showed shrinkage of internal diameters of 43.60% and 51.82% 12 h after SAH, respectively, and the shrinkage appeared as biphasic patterns until the 7th study day with another peaks of 29.32% and 45.19%, respectively. Conclusions: Endovascular puncture is an effective method to establish rabbit of CVS. The death rate of animals can be decreased with the asage of new interventional material and perfection for the details of operation. (authors)

  18. A new cerebral vasospasm model established with endovascular puncture technique

    International Nuclear Information System (INIS)

    Tu Jianfei; Liu Yizhi; Ji Jiansong; Zhao Zhongwei

    2011-01-01

    Objective: To investigate the method of establishing cerebral vasospasm (CVS) models in rabbits by using endovascular puncture technique. Methods: Endovascular puncture procedure was performed in 78 New Zealand white rabbits to produce subarachnoid hemorrhage (SAH). The survival rabbits were randomly divided into seven groups (3 h, 12 h, 1 d, 2 d, 3 d, 7 d and 14 d), with five rabbits in each group for both study group (SAH group) and control group. Cerebral CT scanning was carried out in all rabbits both before and after the operation. The inner diameter and the thickness of vascular wall of both posterior communicating artery (PcoA) and basilar artery (BA) were determined after the animals were sacrificed, and the results were analyzed. Results: Of 78 experimental rabbits, CVS model was successfully established in 45, including 35 of SAH group and 10 control subgroup. The technical success rate was 57.7%. Twelve hours after the procedure, the inner diameter of PcoA and BA in SAH group was decreased by 45.6% and 52.3%, respectively, when compared with these in control group. The vascular narrowing showed biphasic changes, the inner diameter markedly decreased again at the 7th day when the decrease reached its peak to 31.2% and 48.6%, respectively. Conclusion: Endovascular puncture technique is an effective method to establish CVS models in rabbits. The death rate of experimental animals can be decreased if new interventional material is used and the manipulation is carefully performed. (authors)

  19. A physically based analytical spatial air temperature and humidity model

    Science.gov (United States)

    Yang Yang; Theodore A. Endreny; David J. Nowak

    2013-01-01

    Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat...

  20. Models of invasion and establishment of African Mustard (Brassica tournefortii)

    Science.gov (United States)

    Berry, Kristin H.; Gowan, Timothy A.; Miller, David M.; Brooks, Matthew L.

    2015-01-01

    Introduced exotic plants can drive ecosystem change. We studied invasion and establishment ofBrassica tournefortii (African mustard), a noxious weed, in the Chemehuevi Valley, western Sonoran Desert, California. We used long-term data sets of photographs, transects for biomass of annual plants, and densities of African mustard collected at irregular intervals between 1979 and 2009. We suggest that African mustard may have been present in low numbers along the main route of travel, a highway, in the late 1970s; invaded the valley along a major axial valley ephemeral stream channel and the highway; and by 2009, colonized 22 km into the eastern part of the valley. We developed predictive models for invasibility and establishment of African mustard. Both during the initial invasion and after establishment, significant predictor variables of African mustard densities were surficial geology, proximity to the highway and axial valley ephemeral stream channel, and number of small ephemeral stream channels. The axial valley ephemeral stream channel was the most vulnerable of the variables to invasions. Overall, African mustard rapidly colonized and quickly became established in naturally disturbed areas, such as stream channels, where geological surfaces were young and soils were weakly developed. Older geological surfaces (e.g., desert pavements with soils 140,000 to 300,000 years old) were less vulnerable. Microhabitats also influenced densities of African mustard, with densities higher under shrubs than in the interspaces. As African mustard became established, the proportional biomass of native winter annual plants declined. Early control is important because African mustard can colonize and become well established across a valley in 20 yr.

  1. Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study

    Energy Technology Data Exchange (ETDEWEB)

    Deutsch, Jared L., E-mail: jdeutsch@ualberta.ca [University of Alberta, School of Mining and Petroleum Engineering, Department of Civil and Environmental Engineering (Canada); Palmer, Kevin [Teck Resources Limited (Canada); Deutsch, Clayton V.; Szymanski, Jozef [University of Alberta, School of Mining and Petroleum Engineering, Department of Civil and Environmental Engineering (Canada); Etsell, Thomas H. [University of Alberta, Department of Chemical and Materials Engineering (Canada)

    2016-06-15

    High-resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively by measured grade and geomechanical properties constitute an important part of geometallurgy. Geostatistical and other numerical techniques are adapted and developed to construct these high-resolution models accounting for all available data. Important issues that must be addressed include unequal sampling of the metallurgical properties versus grade assays, measurements at different scale, and complex nonlinear averaging of many metallurgical parameters. This paper establishes techniques to address each of these issues with the required implementation details and also demonstrates geometallurgical mineral deposit characterization for a copper–molybdenum deposit in South America. High-resolution models of grades and comminution indices are constructed, checked, and are rigorously validated. The workflow demonstrated in this case study is applicable to many other deposit types.

  2. Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

    Science.gov (United States)

    Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

    2010-12-01

    Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies

  3. Establishing a cat model of acute optic nerve injury

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    BACKGROUND: In order to investigate the progress in optic nerve injury and the following regeneration and repair, many kinds of animal models of optic nerve injury have been established, such as models of acute and chronic ocular hypertension, compression, amputating wound, ischemia reperfusion or hypoxia,intravitreal injection of excitatory amino acids, etc. However, most of these models are established by squeezing intraorbital optic nerve, and suitable for ophthalmology, and there are fewer models suitable for the acute cranial contusion in neurosurgery.OBJECTIVE: To observe the changes of optic nerve after acute injury, and the characteristics of methods for establishing model of acute optic nerve injury in cats.DESIGN: A complete randomized grouping and controlled animal trial.SETTING: Department of Neurosurgery, General Hospital of Ji'nan Military Area Command of Chinese PLA.MATERIALS: Twenty-eight healthy adult cats, common degree, either sex, weighing 2.0 - 3.5 kg, were provided by the animal experimental center of Fudan University. The cats were randomly divided into control group (n =3) and model group (n =25), and 5 cats in the model group were observed at 6 hours and 1,3, 7 and 14 days after injury respectively. JX-2000 biological signal processing system (Department of Physiology, Second Military Medical University of Chinese PLA, Shanghai); Inverted phase contrast microscope (Olympus); Axioplan 2 imaging microgram analytical system (Labsystems).METHODS: The experiments were carried out in the Department of Neurosurgery, General Hospital of Jinan Military Area Command of Chinese PLA from June 2004 to June 2005. The cats in the model groups were made into models of acute optic nerve injury: The cats were anesthetized, then the limbs were fixed in a lateral recumbent position. Pterion approach in human was imitated, the operative incision was made along the line between lateral canthus and tragus, and it could be seen deep along the skull base that white

  4. Spatial variability of biotic and abiotic tree establishment constraints across a treeline ecotone in the Alaska range.

    Science.gov (United States)

    Stueve, Kirk M; Isaacs, Rachel E; Tyrrell, Lucy E; Densmore, Roseann V

    2011-02-01

    Throughout interior Alaska (U.S.A.), a gradual warming trend in mean monthly temperatures occurred over the last few decades (approximatlely 2-4 degrees C). The accompanying increases in woody vegetation at many alpine treeline (hereafter treeline) locations provided an opportunity to examine how biotic and abiotic local site conditions interact to control tree establishment patterns during warming. We devised a landscape ecological approach to investigate these relationships at an undisturbed treeline in the Alaska Range. We identified treeline changes between 1953 (aerial photography) and 2005 (satellite imagery) in a geographic information system (GIS) and linked them with corresponding local site conditions derived from digital terrain data, ancillary climate data, and distance to 1953 trees. Logistic regressions enabled us to rank the importance of local site conditions in controlling tree establishment. We discovered a spatial transition in the importance of tree establishment controls. The biotic variable (proximity to 1953 trees) was the most important tree establishment predictor below the upper tree limit, providing evidence of response lags with the abiotic setting and suggesting that tree establishment is rarely in equilibrium with the physical environment or responding directly to warming. Elevation and winter sun exposure were important predictors of tree establishment at the upper tree limit, but proximity to trees persisted as an important tertiary predictor, indicating that tree establishment may achieve equilibrium with the physical environment. However, even here, influences from the biotic variable may obscure unequivocal correlations with the abiotic setting (including temperature). Future treeline expansion will likely be patchy and challenging to predict without considering the spatial variability of influences from biotic and abiotic local site conditions.

  5. Reducing Spatial Data Complexity for Classification Models

    International Nuclear Information System (INIS)

    Ruta, Dymitr; Gabrys, Bogdan

    2007-01-01

    Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the

  6. Reducing Spatial Data Complexity for Classification Models

    Science.gov (United States)

    Ruta, Dymitr; Gabrys, Bogdan

    2007-11-01

    Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the

  7. Panchromatic SED modelling of spatially resolved galaxies

    Science.gov (United States)

    Smith, Daniel J. B.; Hayward, Christopher C.

    2018-05-01

    We test the efficacy of the energy-balance spectral energy distribution (SED) fitting code MAGPHYS for recovering the spatially resolved properties of a simulated isolated disc galaxy, for which it was not designed. We perform 226 950 MAGPHYS SED fits to regions between 0.2 and 25 kpc in size across the galaxy's disc, viewed from three different sight-lines, to probe how well MAGPHYS can recover key galaxy properties based on 21 bands of UV-far-infrared model photometry. MAGPHYS yields statistically acceptable fits to >99 per cent of the pixels within the r-band effective radius and between 59 and 77 percent of pixels within 20 kpc of the nucleus. MAGPHYS is able to recover the distribution of stellar mass, star formation rate (SFR), specific SFR, dust luminosity, dust mass, and V-band attenuation reasonably well, especially when the pixel size is ≳ 1 kpc, whereas non-standard outputs (stellar metallicity and mass-weighted age) are recovered less well. Accurate recovery is more challenging in the smallest sub-regions of the disc (pixel scale ≲ 1 kpc), where the energy balance criterion becomes increasingly incorrect. Estimating integrated galaxy properties by summing the recovered pixel values, the true integrated values of all parameters considered except metallicity and age are well recovered at all spatial resolutions, ranging from 0.2 kpc to integrating across the disc, albeit with some evidence for resolution-dependent biases. These results must be considered when attempting to analyse the structure of real galaxies with actual observational data, for which the `ground truth' is unknown.

  8. Establishing a business process reference model for Universities

    DEFF Research Database (Denmark)

    Svensson, Carsten; Hvolby, Hans-Henrik

    2012-01-01

    Modern universities are by any standard complex organizations that, from an IT perspective, present a number of unique challenges. This paper will propose establishing a business process reference framework. The benefit to the users would be a better understanding of the system landscape, business......) have gained popularity among organizations in both the private and public sectors. We speculate that this success can be replicated in a university setting. Furthermore the paper will outline how the research group suggests moving ahead with the research which will lead to a reference model....

  9. A reproducible brain tumour model established from human glioblastoma biopsies

    International Nuclear Information System (INIS)

    Wang, Jian; Chekenya, Martha; Bjerkvig, Rolf; Enger, Per Ø; Miletic, Hrvoje; Sakariassen, Per Ø; Huszthy, Peter C; Jacobsen, Hege; Brekkå, Narve; Li, Xingang; Zhao, Peng; Mørk, Sverre

    2009-01-01

    Establishing clinically relevant animal models of glioblastoma multiforme (GBM) remains a challenge, and many commonly used cell line-based models do not recapitulate the invasive growth patterns of patient GBMs. Previously, we have reported the formation of highly invasive tumour xenografts in nude rats from human GBMs. However, implementing tumour models based on primary tissue requires that these models can be sufficiently standardised with consistently high take rates. In this work, we collected data on growth kinetics from a material of 29 biopsies xenografted in nude rats, and characterised this model with an emphasis on neuropathological and radiological features. The tumour take rate for xenografted GBM biopsies were 96% and remained close to 100% at subsequent passages in vivo, whereas only one of four lower grade tumours engrafted. Average time from transplantation to the onset of symptoms was 125 days ± 11.5 SEM. Histologically, the primary xenografts recapitulated the invasive features of the parent tumours while endothelial cell proliferations and necrosis were mostly absent. After 4-5 in vivo passages, the tumours became more vascular with necrotic areas, but also appeared more circumscribed. MRI typically revealed changes related to tumour growth, several months prior to the onset of symptoms. In vivo passaging of patient GBM biopsies produced tumours representative of the patient tumours, with high take rates and a reproducible disease course. The model provides combinations of angiogenic and invasive phenotypes and represents a good alternative to in vitro propagated cell lines for dissecting mechanisms of brain tumour progression

  10. Establishment of selected acute pulmonary thromboembolism model in experimental sheep

    International Nuclear Information System (INIS)

    Fan Jihai; Gu Xiulian; Chao Shengwu; Zhang Peng; Fan Ruilin; Wang Li'na; Wang Lulu; Wang Ling; Li Bo; Chen Taotao

    2010-01-01

    Objective: To establish a selected acute pulmonary thromboembolism model in experimental sheep suitable for animal experiment. Methods: By using Seldinger's technique the catheter sheath was placed in both the femoral vein and femoral artery in ten sheep. Under C-arm DSA guidance the catheter was inserted through the catheter sheath into the pulmonary artery. Via the catheter appropriate amount of sheep autologous blood clots was injected into the selected pulmonary arteries. The selected acute pulmonary thromboembolism model was thus established. Pulmonary angiography was performed to check the results. The pulmonary arterial pressure, femoral artery pressure,heart rates and partial pressure of oxygen in arterial blood (PaO 2 ) were determined both before and after the treatment. The above parameters obtained after the procedure were compared with the recorded parameters measured before the procedure, and the sheep model quality was evaluated. Results: The baseline of pulmonary arterial pressure was (27.30 ± 9.58) mmHg,femoral artery pressure was (126.4 ± 13.72) mmHg, heart rate was (103 ± 15) bpm and PaO 2 was (87.7 ± 12.04) mmHg. Sixty minutes after the injection of (30 ± 5) ml thrombotic agglomerates, the pulmonary arterial pressures rose to (52 ± 49) mmHg, femoral artery pressures dropped to (100 ± 21) mmHg. The heart rates went up to (150 ± 26) bpm. The PaO 2 fell to (25.3 ± 11.2) mmHg. After the procedure the above parameters were significantly different from that measured before the procedure in all ten animals (P < 0.01). The pulmonary arteriography clearly demonstrated that the selected pulmonary arteries were successfully embolized. Conclusion: The anatomy of sheep's femoral veins,vena cava system, pulmonary artery and right heart system are suitable for the establishment of the catheter passage, for this reason, selected acute pulmonary thromboembolism model can be easily created in experimental sheep. The technique is feasible and the model

  11. Consequences of spatial autocorrelation for niche-based models

    DEFF Research Database (Denmark)

    Segurado, P.; Araújo, Miguel B.; Kunin, W. E.

    2006-01-01

    1.  Spatial autocorrelation is an important source of bias in most spatial analyses. We explored the bias introduced by spatial autocorrelation on the explanatory and predictive power of species' distribution models, and make recommendations for dealing with the problem. 2.  Analyses were based o...

  12. Spatial Econometric data analysis: moving beyond traditional models

    NARCIS (Netherlands)

    Florax, R.J.G.M.; Vlist, van der A.J.

    2003-01-01

    This article appraises recent advances in the spatial econometric literature. It serves as the introduction too collection of new papers on spatial econometric data analysis brought together in this special issue, dealing specifically with new extensions to the spatial econometric modeling

  13. Stochastic population oscillations in spatial predator-prey models

    International Nuclear Information System (INIS)

    Taeuber, Uwe C

    2011-01-01

    It is well-established that including spatial structure and stochastic noise in models for predator-prey interactions invalidates the classical deterministic Lotka-Volterra picture of neutral population cycles. In contrast, stochastic models yield long-lived, but ultimately decaying erratic population oscillations, which can be understood through a resonant amplification mechanism for density fluctuations. In Monte Carlo simulations of spatial stochastic predator-prey systems, one observes striking complex spatio-temporal structures. These spreading activity fronts induce persistent correlations between predators and prey. In the presence of local particle density restrictions (finite prey carrying capacity), there exists an extinction threshold for the predator population. The accompanying continuous non-equilibrium phase transition is governed by the directed-percolation universality class. We employ field-theoretic methods based on the Doi-Peliti representation of the master equation for stochastic particle interaction models to (i) map the ensuing action in the vicinity of the absorbing state phase transition to Reggeon field theory, and (ii) to quantitatively address fluctuation-induced renormalizations of the population oscillation frequency, damping, and diffusion coefficients in the species coexistence phase.

  14. The spatial limitations of current neutral models of biodiversity.

    Directory of Open Access Journals (Sweden)

    Rampal S Etienne

    Full Text Available The unified neutral theory of biodiversity and biogeography is increasingly accepted as an informative null model of community composition and dynamics. It has successfully produced macro-ecological patterns such as species-area relationships and species abundance distributions. However, the models employed make many unrealistic auxiliary assumptions. For example, the popular spatially implicit version assumes a local plot exchanging migrants with a large panmictic regional source pool. This simple structure allows rigorous testing of its fit to data. In contrast, spatially explicit models assume that offspring disperse only limited distances from their parents, but one cannot as yet test the significance of their fit to data. Here we compare the spatially explicit and the spatially implicit model, fitting the most-used implicit model (with two levels, local and regional to data simulated by the most-used spatially explicit model (where offspring are distributed about their parent on a grid according to either a radially symmetric Gaussian or a 'fat-tailed' distribution. Based on these fits, we express spatially implicit parameters in terms of spatially explicit parameters. This suggests how we may obtain estimates of spatially explicit parameters from spatially implicit ones. The relationship between these parameters, however, makes no intuitive sense. Furthermore, the spatially implicit model usually fits observed species-abundance distributions better than those calculated from the spatially explicit model's simulated data. Current spatially explicit neutral models therefore have limited descriptive power. However, our results suggest that a fatter tail of the dispersal kernel seems to improve the fit, suggesting that dispersal kernels with even fatter tails should be studied in future. We conclude that more advanced spatially explicit models and tools to analyze them need to be developed.

  15. Establishing a Business Process Reference Model for Universities

    KAUST Repository

    Svensson, Carsten

    2012-09-01

    Modern universities are by any standard complex organizations that, from an IT perspective, present a number of unique challenges. This paper will propose establishing a business process reference framework. The benefit to the users would be a better understanding of the system landscape, business process enablement, collection of performance data and systematic reuse of existing community experience and knowledge. For these reasons reference models such as the SCOR (Supply Chain Operations Reference), DCOR (Design Chain Operations Reference) and ITIL (Information Technology Infrastructure Library) have gained popularity among organizations in both the private and public sectors. We speculate that this success can be replicated in a university setting. Furthermore the paper will outline how the research group suggests moving ahead with the research which will lead to a reference model.

  16. Establishing a Multi-spatial Wireless Sensor Network to Monitor Nitrate Concentrations in Soil Moisture

    Science.gov (United States)

    Haux, E.; Busek, N.; Park, Y.; Estrin, D.; Harmon, T. C.

    2004-12-01

    The use of reclaimed wastewater for irrigation in agriculture can be a significant source of nutrients, in particular nitrogen species, but its use raises concern for groundwater, riparian, and water quality. A 'smart' technology would have the ability to measure wastewater nutrients as they enter the irrigation system, monitor their transport in situ and optimally control inputs with little human intervention, all in real-time. Soil heterogeneity and economic issues require, however, a balance between cost and the spatial and temporal scales of the monitoring effort. Therefore, a wireless and embedded sensor network, deployed in the soil vertically across the horizon, is capable of collecting, processing, and transmitting sensor data. The network consists of several networked nodes or 'pylons', each outfitted with an array of sensors measuring humidity, temperature, precipitation, soil moisture, and aqueous nitrate concentrations. Individual sensor arrays are controlled by a MICA2 mote (Crossbow Technology Inc., San Jose, CA) programmed with TinyOS (University of California, Berkeley, CA) and a Stargate (Crossbow Technology Inc., San Jose, CA) base-station capable of GPRS for data transmission. Results are reported for the construction and testing of a prototypical pylon at the benchtop and in the field.

  17. [Establishment of rat model of psychical erectile dysfunction].

    Science.gov (United States)

    Wang, Qiu-lin; Wang, Shu-ren; Duan, Jin

    2006-01-01

    To set up a method of establishing the animal model of psychical erectile dysfunction with emotional stress. All thirty-six male rats with normal sexual function were divided into three groups, i. e. normal group, model group and demasculinized group randomly according to their weights. The rats in the model group were suspended upside down in midair over the water and irritated repeatedly. Two weeks later, the sexual abilities of all rats, i. e. the times of mounting and intromitting the estrus female rats, the latent period of mounting, intromission and ejaculation, were recorded, and the number of rats that had sexual activities was also counted. And the hemorheology indices of the rats were measured. Compared with the normal rats, the latency of mounting [(152.5 +/- 24.6) s vs (42.4 +/- 9.6) s] and intromission [(437.0 +/- 67.7) s vs (130.8 +/- 39.1) s] of the model rats were longer (P 0.05). The hemorheology indices, e. g. blood viscosity, hematocrit (Hct) and red cell aggregation (RCA), of the model rats was significant higher than that of the normal and demasculinized rats (P erectile dysfunction can be made ideally with psychical stress.

  18. Model for Atmospheric Propagation of Spatially Combined Laser Beams

    Science.gov (United States)

    2016-09-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS by Kum Leong Lee September...MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS 5. FUNDING NUMBERS 6. AUTHOR(S) Kum Leong Lee 7. PERFORMING ORGANIZATION NAME(S) AND...BLANK ii Approved for public release. Distribution is unlimited. MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS Kum Leong Lee

  19. A Spatial Model of the Mere Exposure Effect.

    Science.gov (United States)

    Fink, Edward L.; And Others

    1989-01-01

    Uses a spatial model to examine the relationship between stimulus exposure, cognition, and affect. Notes that this model accounts for cognitive changes that a stimulus may acquire as a result of exposure. Concludes that the spatial model is useful for evaluating the mere exposure effect and that affective change does not require cognitive change.…

  20. A Generalized Dynamic Model of Geared System: Establishment and Application

    Directory of Open Access Journals (Sweden)

    Hui Liu

    2011-12-01

    Full Text Available In order to make the dynamic characteristic simulation of the ordinary and planetary gears drive more accurate and more efficient , a generalized dynamic model of geared system is established including internal and external mesh gears in this paper. It is used to build a mathematical model, which achieves the auto judgment of the gear mesh state. We do not need to concern about active or passive gears any more, and the complicated power flow analysis can be avoided. With the numerical integration computation, the axis orbits diagram and dynamic gear mesh force characteristic are acquired and the results show that the dynamic response of translational displacement is greater when contacting line direction change is considered, and with the quickly change of direction of contacting line, the amplitude of mesh force would be increased, which easily causes the damage to the gear tooth. Moreover, compared with ordinary gear, dynamic responses of planetary gear would be affected greater by the gear backlash. Simulation results show the effectiveness of the generalized dynamic model and the mathematical model.

  1. A reproducible brain tumour model established from human glioblastoma biopsies

    Directory of Open Access Journals (Sweden)

    Li Xingang

    2009-12-01

    Full Text Available Abstract Background Establishing clinically relevant animal models of glioblastoma multiforme (GBM remains a challenge, and many commonly used cell line-based models do not recapitulate the invasive growth patterns of patient GBMs. Previously, we have reported the formation of highly invasive tumour xenografts in nude rats from human GBMs. However, implementing tumour models based on primary tissue requires that these models can be sufficiently standardised with consistently high take rates. Methods In this work, we collected data on growth kinetics from a material of 29 biopsies xenografted in nude rats, and characterised this model with an emphasis on neuropathological and radiological features. Results The tumour take rate for xenografted GBM biopsies were 96% and remained close to 100% at subsequent passages in vivo, whereas only one of four lower grade tumours engrafted. Average time from transplantation to the onset of symptoms was 125 days ± 11.5 SEM. Histologically, the primary xenografts recapitulated the invasive features of the parent tumours while endothelial cell proliferations and necrosis were mostly absent. After 4-5 in vivo passages, the tumours became more vascular with necrotic areas, but also appeared more circumscribed. MRI typically revealed changes related to tumour growth, several months prior to the onset of symptoms. Conclusions In vivo passaging of patient GBM biopsies produced tumours representative of the patient tumours, with high take rates and a reproducible disease course. The model provides combinations of angiogenic and invasive phenotypes and represents a good alternative to in vitro propagated cell lines for dissecting mechanisms of brain tumour progression.

  2. Spatial data modelling and maximum entropy theory

    Czech Academy of Sciences Publication Activity Database

    Klimešová, Dana; Ocelíková, E.

    2005-01-01

    Roč. 51, č. 2 (2005), s. 80-83 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : spatial data classification * distribution function * error distribution Subject RIV: BD - Theory of Information

  3. Establishing psychiatric registrars' competence in psychotherapy: a portfolio based model.

    Science.gov (United States)

    Naidu, T; Ramlall, S

    2008-11-01

    During most of the latter part of the last century, South Africa has followed international trends in the training of psychiatrists. Training programmes have become increasingly focused on the neurobiological aspects of psychiatric disorders with less attention being paid to psychotherapy. This is consistent with developments in psychiatric research. In the clinical arena this manifests as a focus on pharmacological and medically based interventions and a resulting relative inattention to non-pharmacological interventions, most especially psychotherapy. In an effort to address this imbalance there has been an international initiative, over the past two decades, to establish an acceptable level of competence in psychotherapy in the training of psychiatrists. A South African programme is needed that can take account of international trends and adapt them for the local context. In order to produce a programme for establishing competence in psychotherapy for psychiatric registrars at the Nelson R. Mandela School of Medicine, the authors examine directives for the development of psychotherapy skills from international regulatory bodies for graduate medical training and their application. Defining and setting preliminary standards for competence is emphasized. A programme based on five core psychotherapy components using a portfolio based model to facilitate learning and assessment of competence in psychotherapy, is proposed.

  4. [Establishment of mouse endometrial injury model by electrocoagulation].

    Science.gov (United States)

    Hu, Xiaoxiao; Lin, Xiaona; Jiang, Yinshen; Shi, Libing; Wang, Jieyu; Zhao, Lijuan; Zhang, Songying

    2014-12-23

    To establish the murine model of moderate endometrial injury. Electrocoagulation was applied to induce endometrial injury of ICR mice with 0.5 watts power while contralateral uterine cavity acted as control without electrocoagulation. The endometrial histomorphology was observed in 7 days later by microscopy and fetal number of each lateral uterus assessed at 17.5 days after pregnancy. At 7 days post-electrocoagulation, the average endometrial thickness of operating side was significantly thinner than that of control side (1.14 ± 0.08 vs 1.88 ± 0.15 mm, P electrocoagulation injury shows morphologic changes and decreased fertile ability. It has potential uses for animal studies of endometrial injury treatment.

  5. The establishment of animal model of acute massive pulmonary embolism

    International Nuclear Information System (INIS)

    Lu Junliang; Yang Ning; Yang Jianping; Ma Junshan; Zhao Shijun

    2008-01-01

    Objective: To find a way of establishing the model of acute massive pulmonary embolism in dog. Methods: Seven dogs were selected with self-clots made outside the body transferring through a 10 F guiding catheter into the central branch of pulmonary artery via the femoral vein approach on one side and then under pressure monitor of pulmonary artery until the very branch of pulmonary artery was occluded. Blood gas and pulmonary arterial pressure were tested before and after the embolization, Pulmonary artery pressure was continuously monitored together with the examinations of angiography. The bilateral lung specimens were resected for histological examination 12 hours in average after the embolization for comparative study. Results: One animal died of cardiogenic shock after clots injection; the other one presented with tachycardia and premature ventricular beat causing partial recanalization 12 h later. The others were occluded successfully in central branch of pulmonary artery and the pulmonary arterial pressure reached above 50 mmHg after occlusion. Pathologic examination showed the formation of red and mix thrombi within the vascular lumens. Conclusions: This method for making acute massive pulmonary embolism animal model was reliable, feasible and reproducible, and could provide an animal model of acute massive pulmonary embolism for other correlative experiments. (authors)

  6. Establishing endangered species recovery criteria using predictive simulation modeling

    Science.gov (United States)

    McGowan, Conor P.; Catlin, Daniel H.; Shaffer, Terry L.; Gratto-Trevor, Cheri L.; Aron, Carol

    2014-01-01

    Listing a species under the Endangered Species Act (ESA) and developing a recovery plan requires U.S. Fish and Wildlife Service to establish specific and measurable criteria for delisting. Generally, species are listed because they face (or are perceived to face) elevated risk of extinction due to issues such as habitat loss, invasive species, or other factors. Recovery plans identify recovery criteria that reduce extinction risk to an acceptable level. It logically follows that the recovery criteria, the defined conditions for removing a species from ESA protections, need to be closely related to extinction risk. Extinction probability is a population parameter estimated with a model that uses current demographic information to project the population into the future over a number of replicates, calculating the proportion of replicated populations that go extinct. We simulated extinction probabilities of piping plovers in the Great Plains and estimated the relationship between extinction probability and various demographic parameters. We tested the fit of regression models linking initial abundance, productivity, or population growth rate to extinction risk, and then, using the regression parameter estimates, determined the conditions required to reduce extinction probability to some pre-defined acceptable threshold. Binomial regression models with mean population growth rate and the natural log of initial abundance were the best predictors of extinction probability 50 years into the future. For example, based on our regression models, an initial abundance of approximately 2400 females with an expected mean population growth rate of 1.0 will limit extinction risk for piping plovers in the Great Plains to less than 0.048. Our method provides a straightforward way of developing specific and measurable recovery criteria linked directly to the core issue of extinction risk. Published by Elsevier Ltd.

  7. Establishment of an induced rat model of malignant pleural mesothelioma

    International Nuclear Information System (INIS)

    Han Dan; Wu Beihai; Yang Hongsheng; Song Guangyi

    2004-01-01

    Objective: To establish a convenient and practical malignant pleural mesothelioma (MPM) model induced by crocidolite in Da Yao, which has a high induction rate and can be used for imaging and multiple experimental studies and is similar to human MPM. Methods 40 mg of crocidolite suspension was injected into the right chest cavity in 100 Wistar rats in the test group, while same amount of sterilized saline water was injected in 20 rats in the control group. The animals were observed daily , and weighted once a month. CT scanning was performed regularly. When the rats were dead or dying, they were dissected immediately and pathological changes were recorded after CT examination. The experiment lasted for 2 years. Results: The overall induction rate was 71.6%. The survival time of the first MPM rat was 285 days. The mean living span of rats with MPM was (469 ± 21) days. The pathological features of the induced MPMs were multiple morphologically and there were some CT features in different periods. CT imaging could show some MPM features and find the tumour earlier. Conclusion: The cause, positions, tissues and clinical condition of induced tumors were the same as humans. The model had a higher similarity with human MPM in differentiation degree and histological type, and the model can be used to study the mechanism of MPM, to discuss the measures of prevention, and to guide clinical diagnosis and treatment. Multi-morphology of the history from the induced tumors could make up the shortage, which was the difficulty in getting all periods of tissue samples in clinical research and being used in imaging and many kinds of researches. It was a valuable animal model to study MPM. (authors)

  8. Functional inverted Wishart for Bayesian multivariate spatial modeling with application to regional climatology model data.

    Science.gov (United States)

    Duan, L L; Szczesniak, R D; Wang, X

    2017-11-01

    Modern environmental and climatological studies produce multiple outcomes at high spatial resolutions. Multivariate spatial modeling is an established means to quantify cross-correlation among outcomes. However, existing models typically suffer from poor computational efficiency and lack the flexibility to simultaneously estimate auto- and cross-covariance structures. In this article, we undertake a novel construction of covariance by utilizing spectral convolution and by imposing an inverted Wishart prior on the cross-correlation structure. The cross-correlation structure with this functional inverted Wishart prior flexibly accommodates not only positive but also weak or negative associations among outcomes while preserving spatial resolution. Furthermore, the proposed model is computationally efficient and produces easily interpretable results, including the individual autocovariances and full cross-correlation matrices, as well as a partial cross-correlation matrix reflecting the outcome correlation after excluding the effects caused by spatial convolution. The model is examined using simulated data sets under different scenarios. It is also applied to the data from the North American Regional Climate Change Assessment Program, examining long-term associations between surface outcomes for air temperature, pressure, humidity, and radiation, on the land area of the North American West Coast. Results and predictive performance are compared with findings from approaches using convolution only or coregionalization.

  9. Functional inverted Wishart for Bayesian multivariate spatial modeling with application to regional climatology model data

    Science.gov (United States)

    Duan, L. L.; Szczesniak, R. D.; Wang, X.

    2018-01-01

    Modern environmental and climatological studies produce multiple outcomes at high spatial resolutions. Multivariate spatial modeling is an established means to quantify cross-correlation among outcomes. However, existing models typically suffer from poor computational efficiency and lack the flexibility to simultaneously estimate auto- and cross-covariance structures. In this article, we undertake a novel construction of covariance by utilizing spectral convolution and by imposing an inverted Wishart prior on the cross-correlation structure. The cross-correlation structure with this functional inverted Wishart prior flexibly accommodates not only positive but also weak or negative associations among outcomes while preserving spatial resolution. Furthermore, the proposed model is computationally efficient and produces easily interpretable results, including the individual autocovariances and full cross-correlation matrices, as well as a partial cross-correlation matrix reflecting the outcome correlation after excluding the effects caused by spatial convolution. The model is examined using simulated data sets under different scenarios. It is also applied to the data from the North American Regional Climate Change Assessment Program, examining long-term associations between surface outcomes for air temperature, pressure, humidity, and radiation, on the land area of the North American West Coast. Results and predictive performance are compared with findings from approaches using convolution only or coregionalization. PMID:29576735

  10. Modeling spatial processes with unknown extremal dependence class

    KAUST Repository

    Huser, Raphaë l G.; Wadsworth, Jennifer L.

    2017-01-01

    Many environmental processes exhibit weakening spatial dependence as events become more extreme. Well-known limiting models, such as max-stable or generalized Pareto processes, cannot capture this, which can lead to a preference for models

  11. Modeling the spatial reach of the LFP

    DEFF Research Database (Denmark)

    Lindén, Henrik; Tetzlaff, Tom; Potjans, Tobias C

    2011-01-01

    The local field potential (LFP) reflects activity of many neurons in the vicinity of the recording electrode and is therefore useful for studying local network dynamics. Much of the nature of the LFP is, however, still unknown. There are, for instance, contradicting reports on the spatial extent ...

  12. Spatial modeling of potential woody biomass flow

    Science.gov (United States)

    Woodam Chung; Nathaniel Anderson

    2012-01-01

    The flow of woody biomass to end users is determined by economic factors, especially the amount available across a landscape and delivery costs of bioenergy facilities. The objective of this study develop methodology to quantify landscape-level stocks and potential biomass flows using the currently available spatial database road network analysis tool. We applied this...

  13. Modeling fixation locations using spatial point processes.

    Science.gov (United States)

    Barthelmé, Simon; Trukenbrod, Hans; Engbert, Ralf; Wichmann, Felix

    2013-10-01

    Whenever eye movements are measured, a central part of the analysis has to do with where subjects fixate and why they fixated where they fixated. To a first approximation, a set of fixations can be viewed as a set of points in space; this implies that fixations are spatial data and that the analysis of fixation locations can be beneficially thought of as a spatial statistics problem. We argue that thinking of fixation locations as arising from point processes is a very fruitful framework for eye-movement data, helping turn qualitative questions into quantitative ones. We provide a tutorial introduction to some of the main ideas of the field of spatial statistics, focusing especially on spatial Poisson processes. We show how point processes help relate image properties to fixation locations. In particular we show how point processes naturally express the idea that image features' predictability for fixations may vary from one image to another. We review other methods of analysis used in the literature, show how they relate to point process theory, and argue that thinking in terms of point processes substantially extends the range of analyses that can be performed and clarify their interpretation.

  14. Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

    Science.gov (United States)

    Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

    2005-01-01

    Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

  15. The imagine of establishing China nuclear insurance model

    International Nuclear Information System (INIS)

    Wu Yimin

    2010-01-01

    Nuclear power Insurance is one important technique for risk managements of Nuclear power Enterprises. At present, nuclear risk of Nuclear power plants in China has been mainly supported by China Nuclear Insurance pool (hereinafter called CNP) to get coverage from International Nuclear Insurance pool (hereinafter called NIP). CNIP has several advantages to confirm low-cost. Operation, such as large underwriting capacity, international approval and cession, direct writing without agents. However, there are both deficiencies, first, can not get rid of dependence on International markets ; second, in the absence of competition in Self- insurance organizations , tough and opaque premium offer greatly restricted the enthusiasm for Nuclear power plants insuring .But the next ten year is a golden decade for China Nuclear industry development; Nuclear power market is demonstrating tremendous growth potential. With new units put into operation, all kinds of nuclear insurance demand will release when subject-matter insured substantially increase. So, breaking the current bottleneck of China Nuclear Insurance and establishing China Nuclear Insurance (hereinafter called: Nuclear insurance) model adapting to China national conditions will play an important role in Nuclear power development. I made the advice that both domestic nuclear enterprises and general insurance companies initiate a 'Nuclear insurance company'. (authors)

  16. Establishing a model of supratentorial hemorrhage in the piglet

    International Nuclear Information System (INIS)

    Shi Yuanhong; Li Zaiwang; Zhang Suming; Xie Minjie; Meng Xiangwu; Xu Jinzhi; Liu Na; Tang Zhouping

    2010-01-01

    The most common site of hemorrhage is the basal ganglia, which exhibits the obvious neurological deficits. In the present study, we aimed to develop a model of supratentorial intracerebral hemorrhage (ICH) with neurological deficits in piglets (6.0 to 8.8 kg). A pediatric urinary catheter with two passages and one balloon was introduced through a burr hole into the right striatum. All the animals received balloon inflation, which was performed by injecting 2.5 ml saline into the balloon through one passage. Then each piglet in experimental group (n=18) received an injection of 1.0-ml autologous arterial blood through the other passage over 2 min and maintained for 5 min. Then, additional 1.5-ml blood was injected over 15 min. Piglets in control group (n=6) received only balloon inflation without blood injection. CT scanning was performed immediately after surgery. A deep hematoma was successfully induced in 16 out of 18 piglets and the hematoma volume was 1.74±0.22 ml (n=5) at 24 hours after surgery. All the piglets with hematoma had behavioral deficits (lame or could not walk) at 24 hours. Tissue damages, such as cell swelling, necrosis and demyelination, appeared at 24 hours in the brain tissues, adjacent to the hematoma, and was aggravated at 48 hours and ameliorated at 7 days after hematoma induction. In conclusion, we have established a simple model of supratentorial ICH in piglets with marked neurological deficits, which is suitable for study of the pathophysiology and treatment of ICH. (author)

  17. . Redundancy and blocking in the spatial domain: A connectionist model

    Directory of Open Access Journals (Sweden)

    I. P. L. Mc Laren

    2002-01-01

    Full Text Available How can the observations of spatial blocking (Rodrigo, Chamizo, McLaren & Mackintosh, 1997 and cue redundancy (O’Keefe and Conway, 1978 be reconciled within the framework provided by an error-correcting, connectionist account of spatial navigation? I show that an implementation of McLaren’s (1995 better beta model can serve this purpose, and examine some of the implications for spatial learning and memory.

  18. Infection dynamics on spatial small-world network models

    Science.gov (United States)

    Iotti, Bryan; Antonioni, Alberto; Bullock, Seth; Darabos, Christian; Tomassini, Marco; Giacobini, Mario

    2017-11-01

    The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks. We propose a model, called REDS, that extends energy-constrained RGGs to account for the synergic effect of sharing the cost of a link with our neighbors, as is observed in real relational networks. We apply both the standard Watts-Strogatz rewiring procedure and another method that conserves the degree distribution of the network. The second technique was developed to eliminate unwanted forms of spatial correlation between the degree of nodes that are affected by rewiring, limiting the effect on other properties such as clustering and assortativity. We analyze both the statistical properties of these two network types and their epidemiological behavior when used as a substrate for a standard susceptible-infected-susceptible compartmental model. We consider and discuss the differences in properties and behavior between RGGs and REDS as rewiring increases and as infection parameters are changed. We report considerable differences both between the network types and, in the case of REDS, between the two rewiring schemes. We conclude that REDS represent, with the application of these rewiring mechanisms, extremely useful and interesting tools in the study of social and epidemiological phenomena in synthetic complex networks.

  19. Spatial-Temporal Correlation Properties of the 3GPP Spatial Channel Model and the Kronecker MIMO Channel Model

    Directory of Open Access Journals (Sweden)

    Cheng-Xiang Wang

    2007-02-01

    Full Text Available The performance of multiple-input multiple-output (MIMO systems is greatly influenced by the spatial-temporal correlation properties of the underlying MIMO channels. This paper investigates the spatial-temporal correlation characteristics of the spatial channel model (SCM in the Third Generation Partnership Project (3GPP and the Kronecker-based stochastic model (KBSM at three levels, namely, the cluster level, link level, and system level. The KBSM has both the spatial separability and spatial-temporal separability at all the three levels. The spatial-temporal separability is observed for the SCM only at the system level, but not at the cluster and link levels. The SCM shows the spatial separability at the link and system levels, but not at the cluster level since its spatial correlation is related to the joint distribution of the angle of arrival (AoA and angle of departure (AoD. The KBSM with the Gaussian-shaped power azimuth spectrum (PAS is found to fit best the 3GPP SCM in terms of the spatial correlations. Despite its simplicity and analytical tractability, the KBSM is restricted to model only the average spatial-temporal behavior of MIMO channels. The SCM provides more insights of the variations of different MIMO channel realizations, but the implementation complexity is relatively high.

  20. Spatial Uncertainty Model for Visual Features Using a Kinect™ Sensor

    Directory of Open Access Journals (Sweden)

    Jae-Han Park

    2012-06-01

    Full Text Available This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.

  1. Spatial uncertainty model for visual features using a Kinect™ sensor.

    Science.gov (United States)

    Park, Jae-Han; Shin, Yong-Deuk; Bae, Ji-Hun; Baeg, Moon-Hong

    2012-01-01

    This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.

  2. Investigating Spatial Interdependence in E-Bike Choice Using Spatially Autoregressive Model

    Directory of Open Access Journals (Sweden)

    Chengcheng Xu

    2017-08-01

    Full Text Available Increased attention has been given to promoting e-bike usage in recent years. However, the research gap still exists in understanding the effects of spatial interdependence on e-bike choice. This study investigated how spatial interdependence affected the e-bike choice. The Moran’s I statistic test showed that spatial interdependence exists in e-bike choice at aggregated level. Bayesian spatial autoregressive logistic analyses were then used to investigate the spatial interdependence at individual level. Separate models were developed for commuting and non-commuting trips. The factors affecting e-bike choice are different between commuting and non-commuting trips. Spatial interdependence exists at both origin and destination sides of commuting and non-commuting trips. Travellers are more likely to choose e-bikes if their neighbours at the trip origin and destination also travel by e-bikes. And the magnitude of this spatial interdependence is different across various traffic analysis zones. The results suggest that, without considering spatial interdependence, the traditional methods may have biased estimation results and make systematic forecasting errors.

  3. Spreading speed and travelling waves for a spatially discrete SIS epidemic model

    International Nuclear Information System (INIS)

    Zhang, Kate Fang; Zhao Xiaoqiang

    2008-01-01

    This paper is devoted to the study of the asymptotic speed of spread and travelling waves for a spatially discrete SIS epidemic model. By appealing to the theory of spreading speeds and travelling waves for monotonic semiflows, we establish the existence of asymptotic speed of spread and show that it coincides with the minimal wave speed for monotonic travelling waves. This also gives an affirmative answer to an open problem presented by Rass and Radcliffe (2003 Spatial Deterministic Epidemics (Mathematical Surveys and Monographs vol 102) (Providence, RI: American Mathematical Society)) in the case of discrete spatial habitat

  4. Extinction threshold of a population in spatial and stochastic model

    OpenAIRE

    Soroka, Yevheniia; Rublyov, Bogdan

    2016-01-01

    In this study, spatial stochastic and logistic model (SSLM) describing dynamics of a population of a certain species was analysed. The behaviour of the extinction threshold as a function of model parameters was studied. More specifically, we studied how the critical values for the model parameters that separate the cases of extinction and persistence depend on the spatial scales of the competition and dispersal kernels. We compared the simulations and analytical results to examine if and how ...

  5. A spatial Mankiw-Romer-Weil model: Theory and evidence

    OpenAIRE

    Fischer, Manfred M.

    2009-01-01

    This paper presents a theoretical growth model that extends the Mankiw-Romer-Weil [MRW] model by accounting for technological interdependence among regional economies. Interdependence is assumed to work through spatial externalities caused by disembodied knowledge diffusion. The transition from theory to econometrics leads to a reduced-form empirical spatial Durbin model specification that explains the variation in regional levels of per worker output at steady state. A system ...

  6. Spatial Modeling of Deforestation in FMU of Poigar, North Sulawesi

    OpenAIRE

    Ahmad, Afandi; Saleh, Muhammad Buce; Rusolono, Teddy

    2016-01-01

    Forest is a part of the ecosystem that provides environmental services. Deforestation may decrease forest function in an ecosystem. This study aims to build a spatial model of deforestation in a forest management unit (FMU) of Poigar. Deforestation analysis carried out by analyze the change of forest cover into non-forest cover with post classification comparison technique. Driving forces of deforestation carried out by spatial modeling using binary logistic regression models (LRM). Result of...

  7. A model relating Eulerian spatial and temporal velocity correlations

    Science.gov (United States)

    Cholemari, Murali R.; Arakeri, Jaywant H.

    2006-03-01

    In this paper we propose a model to relate Eulerian spatial and temporal velocity autocorrelations in homogeneous, isotropic and stationary turbulence. We model the decorrelation as the eddies of various scales becoming decorrelated. This enables us to connect the spatial and temporal separations required for a certain decorrelation through the ‘eddy scale’. Given either the spatial or the temporal velocity correlation, we obtain the ‘eddy scale’ and the rate at which the decorrelation proceeds. This leads to a spatial separation from the temporal correlation and a temporal separation from the spatial correlation, at any given value of the correlation relating the two correlations. We test the model using experimental data from a stationary axisymmetric turbulent flow with homogeneity along the axis.

  8. Stochastic Spatial Models in Ecology: A Statistical Physics Approach

    Science.gov (United States)

    Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

    2017-11-01

    Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

  9. Modelling the potential spatial distribution of mosquito species using three different techniques

    NARCIS (Netherlands)

    Cianci, D.; Hartemink, N.; Ibáñez-Justicia, A.

    2015-01-01

    Background: Models for the spatial distribution of vector species are important tools in the assessment of the risk of establishment and subsequent spread of vector-borne diseases. The aims of this study are to define the environmental conditions suitable for several mosquito species through species

  10. Updates to the Demographic and Spatial Allocation Models to ...

    Science.gov (United States)

    EPA announced the availability of the draft report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) for a 30-day public comment period. The ICLUS version 2 (v2) modeling tool furthered land change modeling by providing nationwide housing development scenarios up to 2100. ICLUS V2 includes updated population and land use data sets and addressing limitations identified in ICLUS v1 in both the migration and spatial allocation models. The companion user guide describes the development of ICLUS v2 and the updates that were made to the original data sets and the demographic and spatial allocation models. [2017 UPDATE] Get the latest version of ICLUS and stay up-to-date by signing up to the ICLUS mailing list. The GIS tool enables users to run SERGoM with the population projections developed for the ICLUS project and allows users to modify the spatial allocation housing density across the landscape.

  11. An API for Integrating Spatial Context Models with Spatial Reasoning Algorithms

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun

    2006-01-01

    The integration of context-aware applications with spatial context models is often done using a common query language. However, algorithms that estimate and reason about spatial context information can benefit from a tighter integration. An object-oriented API makes such integration possible...... and can help reduce the complexity of algorithms making them easier to maintain and develop. This paper propose an object-oriented API for context models of the physical environment and extensions to a location modeling approach called geometric space trees for it to provide adequate support for location...... modeling. The utility of the API is evaluated in several real-world cases from an indoor location system, and spans several types of spatial reasoning algorithms....

  12. Spatial modeling of households' knowledge about arsenic pollution in Bangladesh.

    Science.gov (United States)

    Sarker, M Mizanur Rahman

    2012-04-01

    Arsenic in drinking water is an important public health issue in Bangladesh, which is affected by households' knowledge about arsenic threats from their drinking water. In this study, spatial statistical models were used to investigate the determinants and spatial dependence of households' knowledge about arsenic risk. The binary join matrix/binary contiguity matrix and inverse distance spatial weight matrix techniques are used to capture spatial dependence in the data. This analysis extends the spatial model by allowing spatial dependence to vary across divisions and regions. A positive spatial correlation was found in households' knowledge across neighboring districts at district, divisional and regional levels, but the strength of this spatial correlation varies considerably by spatial weight. Literacy rate, daily wage rate of agricultural labor, arsenic status, and percentage of red mark tube well usage in districts were found to contribute positively and significantly to households' knowledge. These findings have policy implications both at regional and national levels in mitigating the present arsenic crisis and to ensure arsenic-free water in Bangladesh. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. Using animal models to overcome temporal, spatial and combinatorial challenges in HIV persistence research

    DEFF Research Database (Denmark)

    Denton, Paul W.; Søgaard, Ole Schmeltz; Tolstrup, Martin

    2016-01-01

    Research challenges associated with understanding HIV persistence during antiretroviral therapy can be categorized as temporal, spatial and combinatorial. Temporal research challenges relate to the timing of events during establishment and maintenance of HIV persistence. Spatial research challeng...... for directly addressing these research challenges. The aim of this manuscript is to provide a comprehensive review of these recent translational advances made in animal models of HIV persistence....... will improve our understanding of HIV persistence and move the field closer to achieving eradication of persistent HIV. Given that humanized mice and non-human primate HIV models permit rigorous control of experimental conditions, these models have been used extensively as in vivo research platforms...

  14. Bayesian disease mapping: hierarchical modeling in spatial epidemiology

    National Research Council Canada - National Science Library

    Lawson, Andrew

    2013-01-01

    Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas...

  15. Bayesian disease mapping: hierarchical modeling in spatial epidemiology

    National Research Council Canada - National Science Library

    Lawson, Andrew

    2013-01-01

    .... Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications...

  16. Testing spatial heterogeneity with stock assessment models

    DEFF Research Database (Denmark)

    Jardim, Ernesto; Eero, Margit; Silva, Alexandra

    2018-01-01

    sub-populations and applied to two case studies, North Sea cod (Gadus morua) and Northeast Atlantic sardine (Sardina pilchardus). Considering that the biological components of a population can be partitioned into discrete spatial units, we extended this idea into a property of additivity of sub......, the better the diffusion process will be detected. On the other hand it showed that weak to moderate diffusion processes are not easy to identify and large differences between sub-populations productivities may be confounded with weak diffusion processes. The application to North Sea cod and Atlantic sardine...... exemplified how much insight can be gained. In both cases the results obtained were sufficiently robust to support the regional analysis....

  17. Spatial pattern of diarrhea based on regional economic and environment by spatial autoregressive model

    Science.gov (United States)

    Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy

    2014-10-01

    The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.

  18. On Angular Sampling Methods for 3-D Spatial Channel Models

    DEFF Research Database (Denmark)

    Fan, Wei; Jämsä, Tommi; Nielsen, Jesper Ødum

    2015-01-01

    This paper discusses generating three dimensional (3D) spatial channel models with emphasis on the angular sampling methods. Three angular sampling methods, i.e. modified uniform power sampling, modified uniform angular sampling, and random pairing methods are proposed and investigated in detail....... The random pairing method, which uses only twenty sinusoids in the ray-based model for generating the channels, presents good results if the spatial channel cluster is with a small elevation angle spread. For spatial clusters with large elevation angle spreads, however, the random pairing method would fail...... and the other two methods should be considered....

  19. How does spatial study design influence density estimates from spatial capture-recapture models?

    Directory of Open Access Journals (Sweden)

    Rahel Sollmann

    Full Text Available When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR models present an advance over non-spatial models by accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km(2. Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species.

  20. Spatial Epidemic Modelling in Social Networks

    Science.gov (United States)

    Simoes, Joana Margarida

    2005-06-01

    The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.

  1. Spatial modelling with R-INLA: A review

    KAUST Repository

    Bakka, Haakon; Rue, Haavard; Fuglstad, Geir-Arne; Riebler, Andrea; Bolin, David; Krainski, Elias; Simpson, Daniel; Lindgren, Finn

    2018-01-01

    Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically-sized datasets from scratch is time-consuming, and if changes are made to the model, there is little guarantee that the code performs well. The key advantages of R-INLA are the ease with which complex models can be created and modified, without the need to write complex code, and the speed at which inference can be done even for spatial problems with hundreds of thousands of observations. R-INLA handles latent Gaussian models, where fixed effects, structured and unstructured Gaussian random effects are combined linearly in a linear predictor, and the elements of the linear predictor are observed through one or more likelihoods. The structured random effects can be both standard areal model such as the Besag and the BYM models, and geostatistical models from a subset of the Mat\\'ern Gaussian random fields. In this review, we discuss the large success of spatial modelling with R-INLA and the types of spatial models that can be fitted, we give an overview of recent developments for areal models, and we give an overview of the stochastic partial differential equation (SPDE) approach and some of the ways it can be extended beyond the assumptions of isotropy and separability. In particular, we describe how slight changes to the SPDE approach leads to straight-forward approaches for non-stationary spatial models and non-separable space-time models.

  2. Spatial modelling with R-INLA: A review

    KAUST Repository

    Bakka, Haakon

    2018-02-18

    Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically-sized datasets from scratch is time-consuming, and if changes are made to the model, there is little guarantee that the code performs well. The key advantages of R-INLA are the ease with which complex models can be created and modified, without the need to write complex code, and the speed at which inference can be done even for spatial problems with hundreds of thousands of observations. R-INLA handles latent Gaussian models, where fixed effects, structured and unstructured Gaussian random effects are combined linearly in a linear predictor, and the elements of the linear predictor are observed through one or more likelihoods. The structured random effects can be both standard areal model such as the Besag and the BYM models, and geostatistical models from a subset of the Mat\\\\\\'ern Gaussian random fields. In this review, we discuss the large success of spatial modelling with R-INLA and the types of spatial models that can be fitted, we give an overview of recent developments for areal models, and we give an overview of the stochastic partial differential equation (SPDE) approach and some of the ways it can be extended beyond the assumptions of isotropy and separability. In particular, we describe how slight changes to the SPDE approach leads to straight-forward approaches for non-stationary spatial models and non-separable space-time models.

  3. Modeling structural change in spatial system dynamics: A Daisyworld example.

    Science.gov (United States)

    Neuwirth, C; Peck, A; Simonović, S P

    2015-03-01

    System dynamics (SD) is an effective approach for helping reveal the temporal behavior of complex systems. Although there have been recent developments in expanding SD to include systems' spatial dependencies, most applications have been restricted to the simulation of diffusion processes; this is especially true for models on structural change (e.g. LULC modeling). To address this shortcoming, a Python program is proposed to tightly couple SD software to a Geographic Information System (GIS). The approach provides the required capacities for handling bidirectional and synchronized interactions of operations between SD and GIS. In order to illustrate the concept and the techniques proposed for simulating structural changes, a fictitious environment called Daisyworld has been recreated in a spatial system dynamics (SSD) environment. The comparison of spatial and non-spatial simulations emphasizes the importance of considering spatio-temporal feedbacks. Finally, practical applications of structural change models in agriculture and disaster management are proposed.

  4. A Structural Equation Approach to Models with Spatial Dependence

    NARCIS (Netherlands)

    Oud, Johan H. L.; Folmer, Henk

    We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it

  5. A structural equation approach to models with spatial dependence

    NARCIS (Netherlands)

    Oud, J.H.L.; Folmer, H.

    2008-01-01

    We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it

  6. A Structural Equation Approach to Models with Spatial Dependence

    NARCIS (Netherlands)

    Oud, J.H.L.; Folmer, H.

    2008-01-01

    We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it

  7. Can spatial statistical river temperature models be transferred between catchments?

    Science.gov (United States)

    Jackson, Faye L.; Fryer, Robert J.; Hannah, David M.; Malcolm, Iain A.

    2017-09-01

    There has been increasing use of spatial statistical models to understand and predict river temperature (Tw) from landscape covariates. However, it is not financially or logistically feasible to monitor all rivers and the transferability of such models has not been explored. This paper uses Tw data from four river catchments collected in August 2015 to assess how well spatial regression models predict the maximum 7-day rolling mean of daily maximum Tw (Twmax) within and between catchments. Models were fitted for each catchment separately using (1) landscape covariates only (LS models) and (2) landscape covariates and an air temperature (Ta) metric (LS_Ta models). All the LS models included upstream catchment area and three included a river network smoother (RNS) that accounted for unexplained spatial structure. The LS models transferred reasonably to other catchments, at least when predicting relative levels of Twmax. However, the predictions were biased when mean Twmax differed between catchments. The RNS was needed to characterise and predict finer-scale spatially correlated variation. Because the RNS was unique to each catchment and thus non-transferable, predictions were better within catchments than between catchments. A single model fitted to all catchments found no interactions between the landscape covariates and catchment, suggesting that the landscape relationships were transferable. The LS_Ta models transferred less well, with particularly poor performance when the relationship with the Ta metric was physically implausible or required extrapolation outside the range of the data. A single model fitted to all catchments found catchment-specific relationships between Twmax and the Ta metric, indicating that the Ta metric was not transferable. These findings improve our understanding of the transferability of spatial statistical river temperature models and provide a foundation for developing new approaches for predicting Tw at unmonitored locations across

  8. Spatial Modeling Tools for Cell Biology

    National Research Council Canada - National Science Library

    Przekwas, Andrzej; Friend, Tom; Teixeira, Rodrigo; Chen, Z. J; Wilkerson, Patrick

    2006-01-01

    .... Scientific potentials and military relevance of computational biology and bioinformatics have inspired DARPA/IPTO's visionary BioSPICE project to develop computational framework and modeling tools for cell biology...

  9. Bayesian spatial transformation models with applications in neuroimaging data.

    Science.gov (United States)

    Miranda, Michelle F; Zhu, Hongtu; Ibrahim, Joseph G

    2013-12-01

    The aim of this article is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. The proposed STM include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov random field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. © 2013, The International Biometric Society.

  10. Crash rates analysis in China using a spatial panel model

    Directory of Open Access Journals (Sweden)

    Wonmongo Lacina Soro

    2017-10-01

    Full Text Available The consideration of spatial externalities in traffic safety analysis is of paramount importance for the success of road safety policies. Yet, the quasi-totality of spatial dependence studies on crash rates is performed within the framework of single-equation spatial cross-sectional studies. The present study extends the spatial cross-sectional scheme to a spatial fixed-effects panel model estimated using the maximum likelihood method. The spatial units are the 31 administrative regions of mainland China over the period 2004–2013. The presence of neighborhood effects is evidenced through the Moran's I statistic. Consistent with previous studies, the analysis reveals that omitting the spatial effects in traffic safety analysis is likely to bias the estimation results. The spatial and error lags are all positive and statistically significant suggesting similarities of crash rates pattern in neighboring regions. Some other explanatory variables, such as freight traffic, the length of paved roads and the populations of age 65 and above are related to higher rates while the opposite trend is observed for the Gross Regional Product, the urban unemployment rate and passenger traffic.

  11. Linear multivariate evaluation models for spatial perception of soundscape.

    Science.gov (United States)

    Deng, Zhiyong; Kang, Jian; Wang, Daiwei; Liu, Aili; Kang, Joe Zhengyu

    2015-11-01

    Soundscape is a sound environment that emphasizes the awareness of auditory perception and social or cultural understandings. The case of spatial perception is significant to soundscape. However, previous studies on the auditory spatial perception of the soundscape environment have been limited. Based on 21 native binaural-recorded soundscape samples and a set of auditory experiments for subjective spatial perception (SSP), a study of the analysis among semantic parameters, the inter-aural-cross-correlation coefficient (IACC), A-weighted-equal sound-pressure-level (L(eq)), dynamic (D), and SSP is introduced to verify the independent effect of each parameter and to re-determine some of their possible relationships. The results show that the more noisiness the audience perceived, the worse spatial awareness they received, while the closer and more directional the sound source image variations, dynamics, and numbers of sound sources in the soundscape are, the better the spatial awareness would be. Thus, the sensations of roughness, sound intensity, transient dynamic, and the values of Leq and IACC have a suitable range for better spatial perception. A better spatial awareness seems to promote the preference slightly for the audience. Finally, setting SSPs as functions of the semantic parameters and Leq-D-IACC, two linear multivariate evaluation models of subjective spatial perception are proposed.

  12. SPATIAL MODELLING FOR DESCRIBING SPATIAL VARIABILITY OF SOIL PHYSICAL PROPERTIES IN EASTERN CROATIA

    Directory of Open Access Journals (Sweden)

    Igor Bogunović

    2016-06-01

    Full Text Available The objectives of this study were to characterize the field-scale spatial variability and test several interpolation methods to identify the best spatial predictor of penetration resistance (PR, bulk density (BD and gravimetric water content (GWC in the silty loam soil in Eastern Croatia. The measurements were made on a 25 x 25-m grid which created 40 individual grid cells. Soil properties were measured at the center of the grid cell deep 0-10 cm and 10-20 cm. Results demonstrated that PR and GWC displayed strong spatial dependence at 0-10 cm BD, while there was moderate and weak spatial dependence of PR, BD and GWC at depth of 10-20 cm. Semi-variogram analysis suggests that future sampling intervals for investigated parameters can be increased to 35 m in order to reduce research costs. Additionally, interpolation models recorded similar root mean square values with high predictive accuracy. Results suggest that investigated properties do not have uniform interpolation method implying the need for spatial modelling in the evaluation of these soil properties in Eastern Croatia.

  13. What spatial scales are believable for climate model projections of sea surface temperature?

    Science.gov (United States)

    Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.

    2014-09-01

    Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (coral bleaching frequency and other marine processes linked to SST warming.

  14. Empirical spatial econometric modelling of small scale neighbourhood

    Science.gov (United States)

    Gerkman, Linda

    2012-07-01

    The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.

  15. Spatial memory tasks in rodents: what do they model?

    Science.gov (United States)

    Morellini, Fabio

    2013-10-01

    The analysis of spatial learning and memory in rodents is commonly used to investigate the mechanisms underlying certain forms of human cognition and to model their dysfunction in neuropsychiatric and neurodegenerative diseases. Proper interpretation of rodent behavior in terms of spatial memory and as a model of human cognitive functions is only possible if various navigation strategies and factors controlling the performance of the animal in a spatial task are taken into consideration. The aim of this review is to describe the experimental approaches that are being used for the study of spatial memory in rats and mice and the way that they can be interpreted in terms of general memory functions. After an introduction to the classification of memory into various categories and respective underlying neuroanatomical substrates, I explain the concept of spatial memory and its measurement in rats and mice by analysis of their navigation strategies. Subsequently, I describe the most common paradigms for spatial memory assessment with specific focus on methodological issues relevant for the correct interpretation of the results in terms of cognitive function. Finally, I present recent advances in the use of spatial memory tasks to investigate episodic-like memory in mice.

  16. Unleashing spatially distributed ecohydrology modeling using Big Data tools

    Science.gov (United States)

    Miles, B.; Idaszak, R.

    2015-12-01

    Physically based spatially distributed ecohydrology models are useful for answering science and management questions related to the hydrology and biogeochemistry of prairie, savanna, forested, as well as urbanized ecosystems. However, these models can produce hundreds of gigabytes of spatial output for a single model run over decadal time scales when run at regional spatial scales and moderate spatial resolutions (~100-km2+ at 30-m spatial resolution) or when run for small watersheds at high spatial resolutions (~1-km2 at 3-m spatial resolution). Numerical data formats such as HDF5 can store arbitrarily large datasets. However even in HPC environments, there are practical limits on the size of single files that can be stored and reliably backed up. Even when such large datasets can be stored, querying and analyzing these data can suffer from poor performance due to memory limitations and I/O bottlenecks, for example on single workstations where memory and bandwidth are limited, or in HPC environments where data are stored separately from computational nodes. The difficulty of storing and analyzing spatial data from ecohydrology models limits our ability to harness these powerful tools. Big Data tools such as distributed databases have the potential to surmount the data storage and analysis challenges inherent to large spatial datasets. Distributed databases solve these problems by storing data close to computational nodes while enabling horizontal scalability and fault tolerance. Here we present the architecture of and preliminary results from PatchDB, a distributed datastore for managing spatial output from the Regional Hydro-Ecological Simulation System (RHESSys). The initial version of PatchDB uses message queueing to asynchronously write RHESSys model output to an Apache Cassandra cluster. Once stored in the cluster, these data can be efficiently queried to quickly produce both spatial visualizations for a particular variable (e.g. maps and animations), as well

  17. Establishing 3d numerical reservoir analogues : Modelling the formation of sand bodies in deltaic environments

    NARCIS (Netherlands)

    van der Vegt, H.; Storms, J.E.A.; Walstra, D.J.R.

    2014-01-01

    The assessment and production of hydrocarbon resources incorporates geological models created from core and wireline well data, as well as seismic data. This data is spatially discrete but is used create a spatially continuous model. However, the heterogeneity within depositional environments is on

  18. Implementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord.

    Science.gov (United States)

    Filgueira, Ramon; Grant, Jon; Strand, Øivind

    2014-06-01

    Shellfish carrying capacity is determined by the interaction of a cultured species with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls the exchange of matter between farms and the adjacent areas, which in turn establishes the nutrient supply that supports phytoplankton populations. The complexity of water circulation makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying capacity estimations. This detailed spatial resolution also allows for the study of processes that depend on specific spatial arrangements, e.g., the most suitable location to place farms, which is crucial for marine spatial planning, and consequently for decision support systems. In the present study, a fully spatial physical-biogeochemical model has been combined with scenario building and optimization techniques as a proof of concept of the use of ecosystem modeling as an objective tool to inform marine spatial planning. The object of this exercise was to generate objective knowledge based on an ecosystem approach to establish new mussel aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer, increasing primary production, and consequently, carrying capacity for mussel cultivation. In addition, an optimization tool, parameter estimation (PEST), was applied to the optimal location and mussel standing stock biomass that maximize production, according to a preestablished carrying capacity criterion. Optimization tools allow us to make rational and transparent decisions to solve a well-defined question, decisions that are essential for policy makers. The outcomes of combining ecosystem models with scenario building and optimization facilitate planning based on an ecosystem approach, highlighting the capabilities of ecosystem modeling as a tool for marine spatial planning.

  19. Modelling the effects of spatial variability on radionuclide migration

    International Nuclear Information System (INIS)

    1998-01-01

    The NEA workshop reflect the present status in national waste management program, specifically in spatial variability and performance assessment of geologic disposal sites for deed repository system the four sessions were: Spatial Variability: Its Definition and Significance to Performance Assessment and Site Characterisation; Experience with the Modelling of Radionuclide Migration in the Presence of Spatial Variability in Various Geological Environments; New Areas for Investigation: Two Personal Views; What is Wanted and What is Feasible: Views and Future Plans in Selected Waste Management Organisations. The 26 papers presented on the four oral sessions and on the poster session have been abstracted and indexed individually for the INIS database. (R.P.)

  20. Spatial distance in a technology gap model

    NARCIS (Netherlands)

    Verspagen, B.; Caniëls, M.C.J.

    1999-01-01

    This paper analyses the effect of locally bounded knowledge spillovers on regional differences in growth. A model will be developed that allows spillovers to take place across regions. Certain conditions determine the amount of spillovers a region receives. By use of simulations (with randomised

  1. Properties of spatial Cox process models

    DEFF Research Database (Denmark)

    Møller, Jesper

    Probabilistic properties of Cox processes of relevance for statistical modelling and inference are studied. Particularly, we study the most important classes of Cox processes, including log Gaussian Cox processes, shot noise Cox processes, and permanent Cox processes. We consider moment properties...... and point process operations such as thinning, displacements, and superpositioning. We also discuss how to simulate specific Cox processes....

  2. A random spatial network model based on elementary postulates

    Science.gov (United States)

    Karlinger, Michael R.; Troutman, Brent M.

    1989-01-01

    A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.

  3. Spatial-temporal modeling of malware propagation in networks.

    Science.gov (United States)

    Chen, Zesheng; Ji, Chuanyi

    2005-09-01

    Network security is an important task of network management. One threat to network security is malware (malicious software) propagation. One type of malware is called topological scanning that spreads based on topology information. The focus of this work is on modeling the spread of topological malwares, which is important for understanding their potential damages, and for developing countermeasures to protect the network infrastructure. Our model is motivated by probabilistic graphs, which have been widely investigated in machine learning. We first use a graphical representation to abstract the propagation of malwares that employ different scanning methods. We then use a spatial-temporal random process to describe the statistical dependence of malware propagation in arbitrary topologies. As the spatial dependence is particularly difficult to characterize, the problem becomes how to use simple (i.e., biased) models to approximate the spatially dependent process. In particular, we propose the independent model and the Markov model as simple approximations. We conduct both theoretical analysis and extensive simulations on large networks using both real measurements and synthesized topologies to test the performance of the proposed models. Our results show that the independent model can capture temporal dependence and detailed topology information and, thus, outperforms the previous models, whereas the Markov model incorporates a certain spatial dependence and, thus, achieves a greater accuracy in characterizing both transient and equilibrium behaviors of malware propagation.

  4. Spatial analysis and modelling based on activities

    CSIR Research Space (South Africa)

    Conradie, Dirk CU

    2010-01-01

    Full Text Available (deliberative attitudes) (Pokahr, 2005). The BDI model does not cover emotional and other ‘higher’ human attitudes. KRONOS is a generic Computational Building Simulation (CBS) tool that was developed over the past three years to work on advanced... featured, stable, mature and platform independent with an easy to use C/C++ Application Program Interface (API). It has advanced joint types and integrated collision detection with friction. ODE is particularly useful for simulating vehicles, objects...

  5. Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

    Science.gov (United States)

    Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

    2017-09-11

    Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

  6. Uncertainty in a spatial evacuation model

    Science.gov (United States)

    Mohd Ibrahim, Azhar; Venkat, Ibrahim; Wilde, Philippe De

    2017-08-01

    Pedestrian movements in crowd motion can be perceived in terms of agents who basically exhibit patient or impatient behavior. We model crowd motion subject to exit congestion under uncertainty conditions in a continuous space and compare the proposed model via simulations with the classical social force model. During a typical emergency evacuation scenario, agents might not be able to perceive with certainty the strategies of opponents (other agents) owing to the dynamic changes entailed by the neighborhood of opponents. In such uncertain scenarios, agents will try to update their strategy based on their own rules or their intrinsic behavior. We study risk seeking, risk averse and risk neutral behaviors of such agents via certain game theory notions. We found that risk averse agents tend to achieve faster evacuation time whenever the time delay in conflicts appears to be longer. The results of our simulations also comply with previous work and conform to the fact that evacuation time of agents becomes shorter once mutual cooperation among agents is achieved. Although the impatient strategy appears to be the rational strategy that might lead to faster evacuation times, our study scientifically shows that the more the agents are impatient, the slower is the egress time.

  7. Stability of a spatial model of social interactions

    International Nuclear Information System (INIS)

    Bragard, Jean; Mossay, Pascal

    2016-01-01

    We study a spatial model of social interactions. Though the properties of the spatial equilibrium have been largely discussed in the existing literature, the stability of equilibrium remains an unaddressed issue. Our aim is to fill up this gap by introducing dynamics in the model and by determining the stability of equilibrium. First we derive a variational equation useful for the stability analysis. This allows to study the corresponding eigenvalue problem. While odd modes are shown to be always stable, there is a single even mode of which stability depends on the model parameters. Finally various numerical simulations illustrate our theoretical results.

  8. A spatially explicit model for an Allee effect: why wolves recolonize so slowly in Greater Yellowstone.

    Science.gov (United States)

    Hurford, Amy; Hebblewhite, Mark; Lewis, Mark A

    2006-11-01

    A reduced probability of finding mates at low densities is a frequently hypothesized mechanism for a component Allee effect. At low densities dispersers are less likely to find mates and establish new breeding units. However, many mathematical models for an Allee effect do not make a distinction between breeding group establishment and subsequent population growth. Our objective is to derive a spatially explicit mathematical model, where dispersers have a reduced probability of finding mates at low densities, and parameterize the model for wolf recolonization in the Greater Yellowstone Ecosystem (GYE). In this model, only the probability of establishing new breeding units is influenced by the reduced probability of finding mates at low densities. We analytically and numerically solve the model to determine the effect of a decreased probability in finding mates at low densities on population spread rate and density. Our results suggest that a reduced probability of finding mates at low densities may slow recolonization rate.

  9. Modeling individuals’ cognitive and affective responses in spatial learning behavior

    NARCIS (Netherlands)

    Han, Q.; Arentze, T.A.; Timmermans, H.J.P.; Janssens, D.; Wets, G.; Lo, H.P.; Leung, Stephen C.H.; Tan, Susanna M.L.

    2008-01-01

    Activity-based analysis has slowly shifted gear from analysis of daily activity patterns to analysis and modeling of dynamic activity-travel patterns. In this paper, we describe a dynamic model that is concerned with simulating cognitive and affective responses in spatial learning behavior for a

  10. Modelling firm heterogeneity with spatial 'trends'

    Energy Technology Data Exchange (ETDEWEB)

    Sarmiento, C. [North Dakota State University, Fargo, ND (United States). Dept. of Agricultural Business & Applied Economics

    2004-04-15

    The hypothesis underlying this article is that firm heterogeneity can be captured by spatial characteristics of the firm (similar to the inclusion of a time trend in time series models). The hypothesis is examined in the context of modelling electric generation by coal powered plants in the presence of firm heterogeneity.

  11. Appropriatie spatial scales to achieve model output uncertainty goals

    NARCIS (Netherlands)

    Booij, Martijn J.; Melching, Charles S.; Chen, Xiaohong; Chen, Yongqin; Xia, Jun; Zhang, Hailun

    2008-01-01

    Appropriate spatial scales of hydrological variables were determined using an existing methodology based on a balance in uncertainties from model inputs and parameters extended with a criterion based on a maximum model output uncertainty. The original methodology uses different relationships between

  12. Spatially adaptive mixture modeling for analysis of FMRI time series.

    Science.gov (United States)

    Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe

    2010-04-01

    Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeling activating and nonactivating voxels through independent mixture models (IMM) within each region while hemodynamic response estimation is performed at a regional scale in a nonparametric way. Instead of IMMs, in this paper we take advantage of spatial mixture models (SMM) for their nonlinear spatial regularizing properties. The proposed method is unsupervised and spatially adaptive in the sense that the amount of spatial correlation is automatically tuned from the data and this setting automatically varies across brain regions. In addition, the level of regularization is specific to each experimental condition since both the signal-to-noise ratio and the activation pattern may vary across stimulus types in a given brain region. These aspects require the precise estimation of multiple partition functions of underlying Ising fields. This is addressed efficiently using first path sampling for a small subset of fields and then using a recently developed fast extrapolation technique for the large remaining set. Simulation results emphasize that detection relying on supervised SMM outperforms its IMM counterpart and that unsupervised spatial mixture models achieve similar results without any hand-tuning of the correlation parameter. On real datasets, the gain is illustrated in a localizer fMRI experiment: brain activations appear more spatially resolved using SMM in comparison with classical general linear model (GLM)-based approaches, while estimating a specific parcel-based HRF shape. Our approach therefore validates the treatment of unsmoothed fMRI data without fixed GLM

  13. A Statistical Toolbox For Mining And Modeling Spatial Data

    Directory of Open Access Journals (Sweden)

    D’Aubigny Gérard

    2016-12-01

    Full Text Available Most data mining projects in spatial economics start with an evaluation of a set of attribute variables on a sample of spatial entities, looking for the existence and strength of spatial autocorrelation, based on the Moran’s and the Geary’s coefficients, the adequacy of which is rarely challenged, despite the fact that when reporting on their properties, many users seem likely to make mistakes and to foster confusion. My paper begins by a critical appraisal of the classical definition and rational of these indices. I argue that while intuitively founded, they are plagued by an inconsistency in their conception. Then, I propose a principled small change leading to corrected spatial autocorrelation coefficients, which strongly simplifies their relationship, and opens the way to an augmented toolbox of statistical methods of dimension reduction and data visualization, also useful for modeling purposes. A second section presents a formal framework, adapted from recent work in statistical learning, which gives theoretical support to our definition of corrected spatial autocorrelation coefficients. More specifically, the multivariate data mining methods presented here, are easily implementable on the existing (free software, yield methods useful to exploit the proposed corrections in spatial data analysis practice, and, from a mathematical point of view, whose asymptotic behavior, already studied in a series of papers by Belkin & Niyogi, suggests that they own qualities of robustness and a limited sensitivity to the Modifiable Areal Unit Problem (MAUP, valuable in exploratory spatial data analysis.

  14. A spatial model of mosquito host-seeking behavior.

    Directory of Open Access Journals (Sweden)

    Bree Cummins

    Full Text Available Mosquito host-seeking behavior and heterogeneity in host distribution are important factors in predicting the transmission dynamics of mosquito-borne infections such as dengue fever, malaria, chikungunya, and West Nile virus. We develop and analyze a new mathematical model to describe the effect of spatial heterogeneity on the contact rate between mosquito vectors and hosts. The model includes odor plumes generated by spatially distributed hosts, wind velocity, and mosquito behavior based on both the prevailing wind and the odor plume. On a spatial scale of meters and a time scale of minutes, we compare the effectiveness of different plume-finding and plume-tracking strategies that mosquitoes could use to locate a host. The results show that two different models of chemotaxis are capable of producing comparable results given appropriate parameter choices and that host finding is optimized by a strategy of flying across the wind until the odor plume is intercepted. We also assess the impact of changing the level of host aggregation on mosquito host-finding success near the end of the host-seeking flight. When clusters of hosts are more tightly associated on smaller patches, the odor plume is narrower and the biting rate per host is decreased. For two host groups of unequal number but equal spatial density, the biting rate per host is lower in the group with more individuals, indicative of an attack abatement effect of host aggregation. We discuss how this approach could assist parameter choices in compartmental models that do not explicitly model the spatial arrangement of individuals and how the model could address larger spatial scales and other probability models for mosquito behavior, such as Lévy distributions.

  15. A study of spatial resolution in pollution exposure modelling

    Directory of Open Access Journals (Sweden)

    Gustafsson Susanna

    2007-06-01

    Full Text Available Abstract Background This study is part of several ongoing projects concerning epidemiological research into the effects on health of exposure to air pollutants in the region of Scania, southern Sweden. The aim is to investigate the optimal spatial resolution, with respect to temporal resolution, for a pollutant database of NOx-values which will be used mainly for epidemiological studies with durations of days, weeks or longer periods. The fact that a pollutant database has a fixed spatial resolution makes the choice critical for the future use of the database. Results The results from the study showed that the accuracy between the modelled concentrations of the reference grid with high spatial resolution (100 m, denoted the fine grid, and the coarser grids (200, 400, 800 and 1600 meters improved with increasing spatial resolution. When the pollutant values were aggregated in time (from hours to days and weeks the disagreement between the fine grid and the coarser grids were significantly reduced. The results also illustrate a considerable difference in optimal spatial resolution depending on the characteristic of the study area (rural or urban areas. To estimate the accuracy of the modelled values comparison were made with measured NOx values. The mean difference between the modelled and the measured value were 0.6 μg/m3 and the standard deviation 5.9 μg/m3 for the daily difference. Conclusion The choice of spatial resolution should not considerably deteriorate the accuracy of the modelled NOx values. Considering the comparison between modelled and measured values we estimate that an error due to coarse resolution greater than 1 μg/m3 is inadvisable if a time resolution of one day is used. Based on the study of different spatial resolutions we conclude that for urban areas a spatial resolution of 200–400 m is suitable; and for rural areas the spatial resolution could be coarser (about 1600 m. This implies that we should develop a pollutant

  16. Global sensitivity analysis for models with spatially dependent outputs

    International Nuclear Information System (INIS)

    Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.

    2011-01-01

    The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)

  17. A physically based analytical spatial air temperature and humidity model

    Science.gov (United States)

    Yang, Yang; Endreny, Theodore A.; Nowak, David J.

    2013-09-01

    Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat storage based on semiempirical functions and generates spatially distributed estimates based on inputs of topography, land cover, and the weather data measured at a reference site. The model assumes that for all grids under the same mesoscale climate, grid air temperature and humidity are modified by local variation in absorbed solar radiation and the partitioning of sensible and latent heat. The model uses a reference grid site for time series meteorological data and the air temperature and humidity of any other grid can be obtained by solving the heat flux network equations. PASATH was coupled with the USDA iTree-Hydro water balance model to obtain evapotranspiration terms and run from 20 to 29 August 2010 at a 360 m by 360 m grid scale and hourly time step across a 285 km2 watershed including the urban area of Syracuse, NY. PASATH predictions were tested at nine urban weather stations representing variability in urban topography and land cover. The PASATH model predictive efficiency R2 ranged from 0.81 to 0.99 for air temperature and 0.77 to 0.97 for dew point temperature. PASATH is expected to have broad applications on environmental and ecological models.

  18. Toward micro-scale spatial modeling of gentrification

    Science.gov (United States)

    O'Sullivan, David

    A simple preliminary model of gentrification is presented. The model is based on an irregular cellular automaton architecture drawing on the concept of proximal space, which is well suited to the spatial externalities present in housing markets at the local scale. The rent gap hypothesis on which the model's cell transition rules are based is discussed. The model's transition rules are described in detail. Practical difficulties in configuring and initializing the model are described and its typical behavior reported. Prospects for further development of the model are discussed. The current model structure, while inadequate, is well suited to further elaboration and the incorporation of other interesting and relevant effects.

  19. Modeling Urban Spatial Growth in Mountainous Regions of Western China

    Directory of Open Access Journals (Sweden)

    Guoping Huang

    2017-08-01

    Full Text Available The scale and speed of urbanization in the mountainous regions of western China have received little attention from researchers. These cities are facing rapid population growth and severe environmental degradation. This study analyzed historical urban growth trends in this mountainous region to better understand the interaction between the spatial growth pattern and the mountainous topography. Three major factors—slope, accessibility, and land use type—were studied in light of their relationships with urban spatial growth. With the analysis of historical data as the basis, a conceptual urban spatial growth model was devised. In this model, slope, accessibility, and land use type together create resistance to urban growth, while accessibility controls the sequence of urban development. The model was tested and evaluated using historical data. It serves as a potential tool for planners to envision and assess future urban growth scenarios and their potential environmental impacts to make informed decisions.

  20. Establishment of a chronic activity-based anorexia rat model

    NARCIS (Netherlands)

    Frintrop, Linda; Trinh, Stefanie; Liesbrock, Johanna; Paulukat, Lisa; Kas, Martien J; Tolba, Rene; Konrad, Kerstin; Herpertz-Dahlmann, Beate; Beyer, Cordian; Seitz, Jochen

    2018-01-01

    BACKGROUND: Anorexia nervosa (AN) is often a chronic eating disorder characterised by body image disturbance and low body weight often associated with starvation-induced amenorrhoea and excessive exercise. Activity-based anorexia (ABA) is an animal model representing many somatic aspects of this

  1. Establishment of a chronic activity-based anorexia rat model

    NARCIS (Netherlands)

    Frintrop, Linda; Trinh, Stefanie; Liesbrock, Johanna; Paulukat, Lisa; Kas, Martien J.; Tolba, Rene; Konrad, Kerstin; Herpertz-Dahlmann, Beate; Beyer, Cordian; Seitz, Jochen

    2018-01-01

    AbstractBackground Anorexia nervosa (AN) is often a chronic eating disorder characterised by body image disturbance and low body weight often associated with starvation-induced amenorrhoea and excessive exercise. Activity-based anorexia (ABA) is an animal model representing many somatic aspects of

  2. A Model for Establishing an Astronomy Education Discussion Group

    Science.gov (United States)

    Deming, Grace; Hayes-Gehrke, M.; Zauderer, B. A.; Bovill, M. S.; DeCesar, M.

    2010-01-01

    In October 2005, a group of astronomy faculty and graduate students met to establish departmental support for participants in the UM Center for Teaching Excellence University Teaching and Learning Program. This program seeks to increase graduate students’ understanding of effective teaching methods, awareness of student learning, and appreciation of education as a scholarly pursuit. Our group has facilitated the submission of successful graduate student educational development grant proposals to the Center for Teaching Excellence (CTE). Completion of the CTE program results in a notation on the graduate student's transcript. Our discussion group met monthly during the first two years. The Astronomy Education Review, The Physics Teacher, The Washington Post, The Chronicle of Higher Education, and National Research Council publications were used to provide background for discussion. Beginning in 2007, the group began sponsoring monthly astronomy education lunches during the academic year to which the entire department was invited. Over the past two years, speakers have included graduate students, faculty, and guests, such as Jay Labov from the National Research Council. Topics have included the Astronomy Diagnostic Test, intelligent design versus evolution, active learning techniques, introducing the use of lecture tutorials, using effective demonstrations, confronting student misconceptions, engagement through clickers (or cards), and fostering critical thinking with ranking tasks. The results of an informal evaluation will be presented.

  3. Hydrological model uncertainty due to spatial evapotranspiration estimation methods

    Science.gov (United States)

    Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

    2016-05-01

    Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

  4. Spatial capture-recapture models for search-encounter data

    Science.gov (United States)

    Royle, J. Andrew; Kery, Marc; Guelat, Jerome

    2011-01-01

    1. Spatial capture–recapture models make use of auxiliary data on capture location to provide density estimates for animal populations. Previously, models have been developed primarily for fixed trap arrays which define the observable locations of individuals by a set of discrete points. 2. Here, we develop a class of models for 'search-encounter' data, i.e. for detections of recognizable individuals in continuous space, not restricted to trap locations. In our hierarchical model, detection probability is related to the average distance between individual location and the survey path. The locations are allowed to change over time owing to movements of individuals, and individual locations are related formally by a model describing individual activity or home range centre which is itself regarded as a latent variable in the model. We provide a Bayesian analysis of the model in WinBUGS, and develop a custom MCMC algorithm in the R language. 3. The model is applied to simulated data and to territory mapping data for the Willow Tit from the Swiss Breeding Bird Survey MHB. While the observed density was 15 territories per nominal 1 km2 plot of unknown effective sample area, the model produced a density estimate of 21∙12 territories per square km (95% posterior interval: 17–26). 4. Spatial capture–recapture models are relevant to virtually all animal population studies that seek to estimate population size or density, yet existing models have been proposed mainly for conventional sampling using arrays of traps. Our model for search-encounter data, where the spatial pattern of searching can be arbitrary and may change over occasions, greatly expands the scope and utility of spatial capture–recapture models.

  5. Establishing a Cloud Computing Success Model for Hospitals in Taiwan

    Science.gov (United States)

    Lian, Jiunn-Woei

    2017-01-01

    The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services. PMID:28112020

  6. Establishing a Cloud Computing Success Model for Hospitals in Taiwan.

    Science.gov (United States)

    Lian, Jiunn-Woei

    2017-01-01

    The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services.

  7. Establishing a Cloud Computing Success Model for Hospitals in Taiwan

    Directory of Open Access Journals (Sweden)

    Jiunn-Woei Lian PhD

    2017-01-01

    Full Text Available The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services.

  8. On the Need to Establish an International Soil Modeling Consortium

    Science.gov (United States)

    Vereecken, H.; Vanderborght, J.; Schnepf, A.

    2014-12-01

    Soil is one of the most critical life-supporting compartments of the Biosphere. Soil provides numerous ecosystem services such as a habitat for biodiversity, water and nutrients, as well as producing food, feed, fiber and energy. To feed the rapidly growing world population in 2050, agricultural food production must be doubled using the same land resources footprint. At the same time, soil resources are threatened due to improper management and climate change. Despite the many important functions of soil, many fundamental knowledge gaps remain, regarding the role of soil biota and biodiversity on ecosystem services, the structure and dynamics of soil communities, the interplay between hydrologic and biotic processes, the quantification of soil biogeochemical processes and soil structural processes, the resilience and recovery of soils from stress, as well as the prediction of soil development and the evolution of soils in the landscape, to name a few. Soil models have long played an important role in quantifying and predicting soil processes and related ecosystem services. However, a new generation of soil models based on a whole systems approach comprising all physical, mechanical, chemical and biological processes is now required to address these critical knowledge gaps and thus contribute to the preservation of ecosystem services, improve our understanding of climate-change-feedback processes, bridge basic soil science research and management, and facilitate the communication between science and society. To meet these challenges an international community effort is required, similar to initiatives in systems biology, hydrology, and climate and crop research. Our consortium will bring together modelers and experimental soil scientists at the forefront of new technologies and approaches to characterize soils. By addressing these aims, the consortium will contribute to improve the role of soil modeling as a knowledge dissemination instrument in addressing key

  9. Establishing a Cloud Computing Success Model for Hospitals in Taiwan

    OpenAIRE

    Lian, Jiunn-Woei

    2017-01-01

    The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality...

  10. MDA-based interoperability establishment using language independent information models

    OpenAIRE

    Agostinho C.; Cerny J.; Jardim-Goncalves R.

    2012-01-01

    Part 2: Full Papers; International audience; Nowadays, more and more enterprises realize that one important step to success in their business is to create new and innovative products. Many times the solution to do that is to abandon the idea of an enterprise as an “isolated island”, and get collaboration with others: worldwide non-hierarchical networks are characterized by collaboration and non-centralized decision making. This paper proposes a conceptual model common to the entire business n...

  11. Analysing earthquake slip models with the spatial prediction comparison test

    KAUST Repository

    Zhang, L.; Mai, Paul Martin; Thingbaijam, Kiran Kumar; Razafindrakoto, H. N. T.; Genton, Marc G.

    2014-01-01

    Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.

  12. Analysing earthquake slip models with the spatial prediction comparison test

    KAUST Repository

    Zhang, L.

    2014-11-10

    Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.

  13. Gaussian Process Regression Model in Spatial Logistic Regression

    Science.gov (United States)

    Sofro, A.; Oktaviarina, A.

    2018-01-01

    Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

  14. Personalized medicine for cystic fibrosis: establishing human model systems.

    Science.gov (United States)

    Mou, Hongmei; Brazauskas, Karissa; Rajagopal, Jayaraj

    2015-10-01

    With over 1,500 identifiable mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene that result in distinct functional and phenotypical abnormalities, it is virtually impossible to perform randomized clinical trials to identify the best therapeutics for all patients. Therefore, a personalized medicine approach is essential. The only way to realistically accomplish this is through the development of improved in vitro human model systems. The lack of a readily available and infinite supply of human CFTR-expressing airway epithelial cells is a key bottleneck. We propose that a concerted two-pronged approach is necessary for patient-specific cystic fibrosis research to continue to prosper and realize its potential: (1) more effective culture and differentiation conditions for growing primary human airway and nasal epithelial cells and (2) the development of collective protocols for efficiently differentiating disease- and patient-specific induced pluripotent stem cells (iPSC) into pure populations of adult epithelial cells. Ultimately, we need a personalized human model system for cystic fibrosis with the capacity for uncomplicated bankability, widespread availability, and universal applicability for patient-specific disease modeling, novel pharmacotherapy investigation and screening, and readily executable genetic modification. © 2015 Wiley Periodicals, Inc.

  15. Establishment of reproducible osteosarcoma rat model using orthotopic implantation technique.

    Science.gov (United States)

    Yu, Zhe; Sun, Honghui; Fan, Qingyu; Long, Hua; Yang, Tongtao; Ma, Bao'an

    2009-05-01

    In experimental musculoskeletal oncology, there remains a need for animal models that can be used to assess the efficacy of new and innovative treatment methodologies for bone tumors. Rat plays a very important role in the bone field especially in the evaluation of metabolic bone diseases. The objective of this study was to develop a rat osteosarcoma model for evaluation of new surgical and molecular methods of treatment for extremity sarcoma. One hundred male SD rats weighing 125.45+/-8.19 g were divided into 5 groups and anesthetized intraperitoneally with 10% chloral hydrate. Orthotopic implantation models of rat osteosarcoma were performed by injecting directly into the SD rat femur with a needle for inoculation with SD tumor cells. In the first step of the experiment, 2x10(5) to 1x10(6) UMR106 cells in 50 microl were injected intraosseously into median or distal part of the femoral shaft and the tumor take rate was determined. The second stage consisted of determining tumor volume, correlating findings from ultrasound with findings from necropsia and determining time of survival. In the third stage, the orthotopically implanted tumors and lung nodules were resected entirely, sectioned, and then counter stained with hematoxylin and eosin for histopathologic evaluation. The tumor take rate was 100% for implants with 8x10(5) tumor cells or more, which was much less than the amount required for subcutaneous implantation, with a high lung metastasis rate of 93.0%. Ultrasound and necropsia findings matched closely (r=0.942; p<0.01), which demonstrated that Doppler ultrasonography is a convenient and reliable technique for measuring cancer at any stage. Tumor growth curve showed that orthotopically implanted tumors expanded vigorously with time-lapse, especially in the first 3 weeks. The median time of survival was 38 days and surgical mortality was 0%. The UMR106 cell line has strong carcinogenic capability and high lung metastasis frequency. The present rat

  16. A Bayesian-Based Approach to Marine Spatial Planning: Evaluating Spatial and Temporal Variance in the Provision of Ecosystem Services Before and After the Establishment Oregon's Marine Protected Areas

    Science.gov (United States)

    Black, B.; Harte, M.; Goldfinger, C.

    2017-12-01

    Participating in a ten-year monitoring project to assess the ecological, social, and socioeconomic impacts of Oregon's Marine Protected Areas (MPAs), we have worked in partnership with the Oregon Department of Fish and Wildlife (ODFW) to develop a Bayesian geospatial method to evaluate the spatial and temporal variance in the provision of ecosystem services produced by Oregon's MPAs. Probabilistic (Bayesian) approaches to Marine Spatial Planning (MSP) show considerable potential for addressing issues such as uncertainty, cumulative effects, and the need to integrate stakeholder-held information and preferences into decision making processes. To that end, we have created a Bayesian-based geospatial approach to MSP capable of modelling the evolution of the provision of ecosystem services before and after the establishment of Oregon's MPAs. Our approach permits both planners and stakeholders to view expected impacts of differing policies, behaviors, or choices made concerning Oregon's MPAs and surrounding areas in a geospatial (map) format while simultaneously considering multiple parties' beliefs on the policies or uses in question. We quantify the influence of the MPAs as the shift in the spatial distribution of ecosystem services, both inside and outside the protected areas, over time. Once the MPAs' influence on the provision of coastal ecosystem services has been evaluated, it is possible to view these impacts through geovisualization techniques. As a specific example of model use and output, a user could investigate the effects of altering the habitat preferences of a rockfish species over a prescribed period of time (5, 10, 20 years post-harvesting restrictions, etc.) on the relative intensity of spillover from nearby reserves (please see submitted figure). Particular strengths of our Bayesian-based approach include its ability to integrate highly disparate input types (qualitative or quantitative), to accommodate data gaps, address uncertainty, and to

  17. Spatial modeling of agricultural land use change at global scale

    Science.gov (United States)

    Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

    2014-11-01

    Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling

  18. Spatial risk modelling for water shortage and nitrate pollution in the lower Jordan valley

    International Nuclear Information System (INIS)

    Loibl, W.; Orthofer, R.

    2002-02-01

    This report summarizes the results of the spatial risk modeling activities (work package WP-4.4, 'GIS Risk Modeling') of the INCO-DC project 'Developing Sustainable Water Management in the Jordan Valley'. The project was funded by European Commission's INCO-DC research program. The main objective of the project was to develop the scientific basis for an integral management plan of water resources and their use in the Lower Jordan Valley. The outputs of the project were expected to allow a better understanding of the water management situation, and to provide a sound basis for a better future water management - not only separately in the three countries, but in the overall valley region. The risk modeling was done by the ARCS Seibersdorf research (ARCS), based on information and data provided by the regional partners from Israel (Hebrew University, Jerusalem, HUJ), Palestine (Applied Research Institute, Jerusalem, Bethlehem, ARIJ) and Jordan (EnviroConsult Office, Amman, ECO). The land use classification has been established through a cooperation between ARCS and the Yale University Center for Earth Observation (YUCEO). As a result of the work, the spatial patterns of agricultural and domestic water demand in the Lower Jordan Valley were established, and the spatial dimension of driving forces for water usage and water supply was analyzed. Furthermore, a conceptual model for nitrate leakage (established by HUJ) was translated into a GIS system, and the risks for nitrate pollution of groundwater were quantified. (author)

  19. A spatial emergy model for Alachua County, Florida

    Science.gov (United States)

    Lambert, James David

    A spatial model of the distribution of energy flows and storages in Alachua County, Florida, was created and used to analyze spatial patterns of energy transformation hierarchy in relation to spatial patterns of human settlement. Emergy, the available energy of one kind previously required directly or indirectly to make a product or service, was used as a measure of the quality of the different forms of energy flows and storages. Emergy provides a common unit of measure for comparing the productive contributions of natural processes with those of economic and social processes---it is an alternative to using money for measuring value. A geographic information system was used to create a spatial model and make maps that show the distribution and magnitude of different types of energy and emergy flows and storages occurring in one-hectare land units. Energy transformities were used to convert individual energy flows and storages into emergy units. Maps of transformities were created that reveal a clear spatial pattern of energy transformation hierarchy. The maps display patterns of widely-dispersed areas with lower transformity energy flows and storages, and smaller, centrally-located areas with higher transformities. Energy signature graphs and spatial unit transformities were used to characterize and compare the types and amounts of energy being consumed and stored according to land use classification, planning unit, and neighborhood categories. Emergy ratio maps and spatial unit ratios were created by dividing the values for specific emergy flows or storages by the values for other emergy flows or storages. Spatial context analysis was used to analyze the spatial distribution patterns of mean and maximum values for emergy flows and storages. The modeling method developed for this study is general and applicable to all types of landscapes and could be applied at any scale. An advantage of this general approach is that the results of other studies using this method

  20. An exploration of spatial risk assessment for soil protection: estimating risk and establishing priority areas for soil protection.

    Science.gov (United States)

    Kibblewhite, M G; Bellamy, P H; Brewer, T R; Graves, A R; Dawson, C A; Rickson, R J; Truckell, I; Stuart, J

    2014-03-01

    Methods for the spatial estimation of risk of harm to soil by erosion by water and wind and by soil organic matter decline are explored. Rates of harm are estimated for combinations of soil type and land cover (as a proxy for hazard frequency) and used to estimate risk of soil erosion and loss of soil organic carbon (SOC) for 1 km(2)pixels. Scenarios are proposed for defining the acceptability of risk of harm to soil: the most precautionary one corresponds to no net harm after natural regeneration of soil (i.e. a 1 in 20 chance of exceeding an erosion rate of soils and a carbon stock decline of 0 tha(-1)y(-1) for organic soils). Areas at higher and lower than possible acceptable risk are mapped. The veracity of boundaries is compromised if areas of unacceptable risk are mapped to administrative boundaries. Errors in monitoring change in risk of harm to soil and inadequate information on risk reduction measures' efficacy, at landscape scales, make it impossible to use or monitor quantitative targets for risk reduction adequately. The consequences for priority area definition of expressing varying acceptable risk of harm to soil as a varying probability of exceeding a fixed level of harm, or, a varying level of harm being exceeded with a fixed probability, are discussed. Soil data and predictive models for rates of harm to soil would need considerable development and validation to implement a priority area approach robustly. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Multivariate Receptor Models for Spatially Correlated Multipollutant Data

    KAUST Repository

    Jun, Mikyoung

    2013-08-01

    The goal of multivariate receptor modeling is to estimate the profiles of major pollution sources and quantify their impacts based on ambient measurements of pollutants. Traditionally, multivariate receptor modeling has been applied to multiple air pollutant data measured at a single monitoring site or measurements of a single pollutant collected at multiple monitoring sites. Despite the growing availability of multipollutant data collected from multiple monitoring sites, there has not yet been any attempt to incorporate spatial dependence that may exist in such data into multivariate receptor modeling. We propose a spatial statistics extension of multivariate receptor models that enables us to incorporate spatial dependence into estimation of source composition profiles and contributions given the prespecified number of sources and the model identification conditions. The proposed method yields more precise estimates of source profiles by accounting for spatial dependence in the estimation. More importantly, it enables predictions of source contributions at unmonitored sites as well as when there are missing values at monitoring sites. The method is illustrated with simulated data and real multipollutant data collected from eight monitoring sites in Harris County, Texas. Supplementary materials for this article, including data and R code for implementing the methods, are available online on the journal web site. © 2013 Copyright Taylor and Francis Group, LLC.

  2. A Non-Gaussian Spatial Generalized Linear Latent Variable Model

    KAUST Repository

    Irincheeva, Irina

    2012-08-03

    We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

  3. A Non-Gaussian Spatial Generalized Linear Latent Variable Model

    KAUST Repository

    Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.

    2012-01-01

    We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

  4. Establishment of a porcine model of patent foramen ovale

    International Nuclear Information System (INIS)

    Jiang Weijian; Xiao Xiangsheng

    2007-01-01

    Objective: To investigate the feasibility of developing an animal model of patent foramen ovale (PFO) in piglets by percutaneous atrial septal puncture and balloon dilation. Methods: A standardized percutaneous atrial trans-septal puncture and balloon dilation was conducted in eleven healthy piglets under general anesthesia. A Rups-100 system inserted through a femoral vein was used for the trans-septal puncture, and subsequent balloon dilatation was performed at the puncture site to imitate a PFO. Euthanasia and autopsy were performed on day-1 in 1 piglet (early autopsy), and on day-21 in the remaining 10 piglets (late autopsy). Results: Artificial PFO was successfully created in all piglets and verified by fluoroscopy. No major technical difficulty or complication was encountered except in one which developed mild hemopericardium. In the piglet which had early autopsy, the artificial foramen was measured 0.8 cm x 0.7 cm in cross-section and aggregates of erythrocytes were revealed over its rim under light microscopy. In the late autopsy group (n=10), 7 piglets had the created foramens healed and sealed off; while the other 3 showed relatively small residual lumens measuring 0.1 cm x 0.2 cm, 0.2 cm x 0.2 cm and 0.1 cm x 0.3 cm in cross-section respectively. Histological examination of specimens from the late autopsy group showed variable neointima hyperplasia, loss of neointima, infiltration of lymphocytes, focal hydropic degeneration of cardiac muscle, and focal fibrosis of interstitium at the immediate vicinity of regardless of the course of healing. Conclusion: Artificial creation of PFO in piglets is feasible by percutaneous atrial septal puncture and balloon dilation. This protocol may serve as a research model for PFO-related stroke in human. (authors)

  5. Practical likelihood analysis for spatial generalized linear mixed models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Ribeiro, Paulo Justiniano

    2016-01-01

    We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...

  6. Combining spatial modeling and choice experiments for the optimal spatial allocation of wind turbines

    International Nuclear Information System (INIS)

    Drechsler, Martin; Ohl, Cornelia; Meyerhoff, Juergen; Eichhorn, Marcus; Monsees, Jan

    2011-01-01

    Although wind power is currently the most efficient source of renewable energy, the installation of wind turbines (WT) in landscapes often leads to conflicts in the affected communities. We propose that such conflicts can be mitigated by a welfare-optimal spatial allocation of WT in the landscape so that a given energy target is reached at minimum social costs. The energy target is motivated by the fact that wind power production is associated with relatively low CO 2 emissions. Social costs comprise energy production costs as well as external costs caused by harmful impacts on humans and biodiversity. We present a modeling approach that combines spatially explicit ecological-economic modeling and choice experiments to determine the welfare-optimal spatial allocation of WT in West Saxony, Germany. The welfare-optimal sites balance production and external costs. Results indicate that in the welfare-optimal allocation the external costs represent about 14% of the total costs (production costs plus external costs). Optimizing wind power production without consideration of the external costs would lead to a very different allocation of WT that would marginally reduce the production costs but strongly increase the external costs and thus lead to substantial welfare losses. - Highlights: → We combine modeling and economic valuation to optimally allocate wind turbines. → Welfare-optimal allocation balances energy production costs and external costs. → External costs (impacts on the environment) can be substantial. → Ignoring external costs leads to suboptimal allocations and welfare losses.

  7. Towards a 3d Spatial Urban Energy Modelling Approach

    Science.gov (United States)

    Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

    2013-09-01

    Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies

  8. Bioburden Increases Heterotopic Ossification Formation in an Established Rat Model.

    Science.gov (United States)

    Pavey, Gabriel J; Qureshi, Ammar T; Hope, Donald N; Pavlicek, Rebecca L; Potter, Benjamin K; Forsberg, Jonathan A; Davis, Thomas A

    2015-09-01

    Heterotopic ossification (HO) develops in a majority of combat-related amputations wherein early bacterial colonization has been considered a potential early risk factor. Our group has recently developed a small animal model of trauma-induced HO that incorporates many of the multifaceted injury patterns of combat trauma in the absence of bacterial contamination and subsequent wound colonization. We sought to determine if (1) the presence of bioburden (Acinetobacter baumannii and methicillin-resistant Staphylococcus aureus [MRSA]) increases the magnitude of ectopic bone formation in traumatized muscle after amputation; and (2) what persistent effects bacterial contamination has on late microbial flora within the amputation site. Using a blast-related HO model, we exposed 48 rats to blast overpressure, femur fracture, crush injury, and subsequent immediate transfemoral amputation through the zone of injury. Control injured rats (n = 8) were inoculated beneath the myodesis with phosphate-buffered saline not containing bacteria (vehicle) and treatment rats were inoculated with 1 × 10(6) colony-forming units of A baumannii (n = 20) or MRSA (n = 20). All animals formed HO. Heterotopic ossification was determined by quantitative volumetric measurements of ectopic bone at 12-weeks postinjury using micro-CT and qualitative histomorphometry for assessment of new bone formation in the residual limb. Bone marrow and muscle tissue biopsies were collected from the residual limb at 12 weeks to quantitatively measure the bioburden load and to qualitatively determine the species-level identification of the bacterial flora. At 12 weeks, we observed a greater volume of HO in rats infected with MRSA (68.9 ± 8.6 mm(3); 95% confidence interval [CI], 50.52-85.55) when compared with A baumannii (20.9 ± 3.7 mm(3); 95% CI, 13.61-28.14; p infection but were positive for other strains of bacteria (1.33 × 10(2) ± 0.89 × 10(2); 95% CI, -0.42 × 10(2)-3.08 × 10(2) and 1.25 × 10(6) ± 0

  9. Modelling the Spatial Isotope Variability of Precipitation in Syria

    Energy Technology Data Exchange (ETDEWEB)

    Kattan, Z.; Kattaa, B. [Department of Geology, Atomic Energy Commission of Syria (AECS), Damascus (Syrian Arab Republic)

    2013-07-15

    Attempts were made to model the spatial variability of environmental isotope ({sup 18}O, {sup 2}H and {sup 3}H) compositions of precipitation in syria. Rainfall samples periodically collected on a monthly basis from 16 different stations were used for processing and demonstrating the spatial distributions of these isotopes, together with those of deuterium excess (d) values. Mathematically, the modelling process was based on applying simple polynomial models that take into consideration the effects of major geographic factors (Lon.E., Lat.N., and altitude). The modelling results of spatial distribution of stable isotopes ({sup 18}O and {sup 2}H) were generally good, as shown from the high correlation coefficients (R{sup 2} = 0.7-0.8), calculated between the observed and predicted values. In the case of deuterium excess and tritium distributions, the results were most likely approximates (R{sup 2} = 0.5-0.6). Improving the simulation of spatial isotope variability probably requires the incorporation of other local meteorological factors, such as relative air humidity, precipitation amount and vapour pressure, which are supposed to play an important role in such an arid country. (author)

  10. Design of spatial experiments: Model fitting and prediction

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, V.V.

    1996-03-01

    The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory.

  11. Classifying and comparing spatial models of fire dynamics

    Science.gov (United States)

    Geoffrey J. Cary; Robert E. Keane; Mike D. Flannigan

    2007-01-01

    Wildland fire is a significant disturbance in many ecosystems worldwide and the interaction of fire with climate and vegetation over long time spans has major effects on vegetation dynamics, ecosystem carbon budgets, and patterns of biodiversity. Landscape-Fire-Succession Models (LFSMs) that simulate the linked processes of fire and vegetation development in a spatial...

  12. Thinking Egyptian: Active Models for Understanding Spatial Representation.

    Science.gov (United States)

    Schiferl, Ellen

    This paper highlights how introductory textbooks on Egyptian art inhibit understanding by reinforcing student preconceptions, and demonstrates another approach to discussing space with a classroom exercise and software. The alternative approach, an active model for spatial representation, introduced here was developed by adapting classroom…

  13. Spatially Informed Plant PRA Models for Security Assessment

    International Nuclear Information System (INIS)

    Wheeler, Timothy A.; Thomas, Willard; Thornsbury, Eric

    2006-01-01

    Traditional risk models can be adapted to evaluate plant response for situations where plant systems and structures are intentionally damaged, such as from sabotage or terrorism. This paper describes a process by which traditional risk models can be spatially informed to analyze the effects of compound and widespread harsh environments through the use of 'damage footprints'. A 'damage footprint' is a spatial map of regions of the plant (zones) where equipment could be physically destroyed or disabled as a direct consequence of an intentional act. The use of 'damage footprints' requires that the basic events from the traditional probabilistic risk assessment (PRA) be spatially transformed so that the failure of individual components can be linked to the destruction of or damage to specific spatial zones within the plant. Given the nature of intentional acts, extensive modifications must be made to the risk models to account for the special nature of the 'initiating events' associated with deliberate adversary actions. Intentional acts might produce harsh environments that in turn could subject components and structures to one or more insults, such as structural, fire, flood, and/or vibration and shock damage. Furthermore, the potential for widespread damage from some of these insults requires an approach that addresses the impacts of these potentially severe insults even when they occur in locations distant from the actual physical location of a component or structure modeled in the traditional PRA. (authors)

  14. Rockfall hazard analysis using LiDAR and spatial modeling

    Science.gov (United States)

    Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho

    2010-05-01

    Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.

  15. Spatial variability and parametric uncertainty in performance assessment models

    International Nuclear Information System (INIS)

    Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo

    2011-01-01

    The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)

  16. A spatial haplotype copying model with applications to genotype imputation.

    Science.gov (United States)

    Yang, Wen-Yun; Hormozdiari, Farhad; Eskin, Eleazar; Pasaniuc, Bogdan

    2015-05-01

    Ever since its introduction, the haplotype copy model has proven to be one of the most successful approaches for modeling genetic variation in human populations, with applications ranging from ancestry inference to genotype phasing and imputation. Motivated by coalescent theory, this approach assumes that any chromosome (haplotype) can be modeled as a mosaic of segments copied from a set of chromosomes sampled from the same population. At the core of the model is the assumption that any chromosome from the sample is equally likely to contribute a priori to the copying process. Motivated by recent works that model genetic variation in a geographic continuum, we propose a new spatial-aware haplotype copy model that jointly models geography and the haplotype copying process. We extend hidden Markov models of haplotype diversity such that at any given location, haplotypes that are closest in the genetic-geographic continuum map are a priori more likely to contribute to the copying process than distant ones. Through simulations starting from the 1000 Genomes data, we show that our model achieves superior accuracy in genotype imputation over the standard spatial-unaware haplotype copy model. In addition, we show the utility of our model in selecting a small personalized reference panel for imputation that leads to both improved accuracy as well as to a lower computational runtime than the standard approach. Finally, we show our proposed model can be used to localize individuals on the genetic-geographical map on the basis of their genotype data.

  17. Landform classification using a sub-pixel spatial attraction model to increase spatial resolution of digital elevation model (DEM

    Directory of Open Access Journals (Sweden)

    Marzieh Mokarrama

    2018-04-01

    Full Text Available The purpose of the present study is preparing a landform classification by using digital elevation model (DEM which has a high spatial resolution. To reach the mentioned aim, a sub-pixel spatial attraction model was used as a novel method for preparing DEM with a high spatial resolution in the north of Darab, Fars province, Iran. The sub-pixel attraction models convert the pixel into sub-pixels based on the neighboring pixels fraction values, which can only be attracted by a central pixel. Based on this approach, a mere maximum of eight neighboring pixels can be selected for calculating of the attraction value. In the mentioned model, other pixels are supposed to be far from the central pixel to receive any attraction. In the present study by using a sub-pixel attraction model, the spatial resolution of a DEM was increased. The design of the algorithm is accomplished by using a DEM with a spatial resolution of 30 m (the Advanced Space borne Thermal Emission and Reflection Radiometer; (ASTER and a 90 m (the Shuttle Radar Topography Mission; (SRTM. In the attraction model, scale factors of (S = 2, S = 3, and S = 4 with two neighboring methods of touching (T = 1 and quadrant (T = 2 are applied to the DEMs by using MATLAB software. The algorithm is evaluated by taking the best advantages of 487 sample points, which are measured by surveyors. The spatial attraction model with scale factor of (S = 2 gives better results compared to those scale factors which are greater than 2. Besides, the touching neighborhood method is turned to be more accurate than the quadrant method. In fact, dividing each pixel into more than two sub-pixels decreases the accuracy of the resulted DEM. On the other hand, in these cases DEM, is itself in charge of increasing the value of root-mean-square error (RMSE and shows that attraction models could not be used for S which is greater than 2. Thus considering results, the proposed model is highly capable of

  18. Modern methodology and applications in spatial-temporal modeling

    CERN Document Server

    Matsui, Tomoko

    2015-01-01

    This book provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter deals with non-parametric Bayesian inference via a recently developed framework known as kernel mean embedding which has had a significant influence in machine learning disciplines. The second chapter takes up non-parametric statistical methods for spatial field reconstruction and exceedance probability estimation based on Gaussian process-based models in the context of wireless sensor network data. The third chapter presents signal-processing methods applied to acoustic mood analysis based on music signal analysis. The fourth chapter covers models that are applicable to time series modeling in the domain of speech and language processing. This includes aspects of factor analysis, independent component an...

  19. Stochastic geometry, spatial statistics and random fields models and algorithms

    CERN Document Server

    2015-01-01

    Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.

  20. Analog model for analysis of spatial instability of neutron flux

    International Nuclear Information System (INIS)

    Radanovic, Lj.

    1964-12-01

    The objective of this task was to develop a model for analysing spatial instability of the neutron flux and defining the optimum number and position of regulating rods. The developed model enables calculation of higher harmonics to be taken into account for each type of reactor, to define zones for regulation rods, position and number of points for detecting reactor state, and number and position of the regulating rods

  1. Integrating remote sensing and spatially explicit epidemiological modeling

    Science.gov (United States)

    Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea

    2015-04-01

    Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.

  2. Spatial Temporal Modelling of Particulate Matter for Health Effects Studies

    Science.gov (United States)

    Hamm, N. A. S.

    2016-10-01

    Epidemiological studies of the health effects of air pollution require estimation of individual exposure. It is not possible to obtain measurements at all relevant locations so it is necessary to predict at these space-time locations, either on the basis of dispersion from emission sources or by interpolating observations. This study used data obtained from a low-cost sensor network of 32 air quality monitoring stations in the Dutch city of Eindhoven, which make up the ILM (innovative air (quality) measurement system). These stations currently provide PM10 and PM2.5 (particulate matter less than 10 and 2.5 m in diameter), aggregated to hourly means. The data provide an unprecedented level of spatial and temporal detail for a city of this size. Despite these benefits the time series of measurements is characterized by missing values and noisy values. In this paper a space-time analysis is presented that is based on a dynamic model for the temporal component and a Gaussian process geostatistical for the spatial component. Spatial-temporal variability was dominated by the temporal component, although the spatial variability was also substantial. The model delivered accurate predictions for both isolated missing values and 24-hour periods of missing values (RMSE = 1.4 μg m-3 and 1.8 μg m-3 respectively). Outliers could be detected by comparison to the 95% prediction interval. The model shows promise for predicting missing values, outlier detection and for mapping to support health impact studies.

  3. Spatial modelling and ecology of Echinococcus multilocularis transmission in China.

    Science.gov (United States)

    Danson, F Mark; Giraudoux, Patrick; Craig, Philip S

    2006-01-01

    Recent research in central China has suggested that the most likely transmission mechanism for Echinococcus multilocularis to humans is via domestic dogs which are allowed to roam freely and hunt (infected) small mammals within areas close to villages or in areas of tented pasture. This assertion has led to the hypothesis that there is a landscape control on transmission risk since the proximity of suitable habitat for susceptible small mammals appears to be the key. We have tested this hypothesis in a number of endemic areas in China, notably south Gansu Province and the Tibetan region of western Sichuan Province. The fundamental landscape control is its effect at a regional scale on small mammal species assemblages (susceptible species are not ubiquitous) and, at a local scale, the spatial distributions of small mammal populations. To date the research has examined relationships between landscape composition and patterns of human infection, landscape and small mammal distributions and recently the relationships between landscape and dog infection rates. The key tool to characterize landscape is satellite remote sensing and these data are used as inputs to drive spatial models of transmission risk. This paper reviews the progress that has been made so far in spatial modeling of the ecology of E. multilocularis with particular reference to China, outlines current research issues, and describes a framework for building a spatial-temporal model of transmission ecology.

  4. Single Canonical Model of Reflexive Memory and Spatial Attention

    Science.gov (United States)

    Patel, Saumil S.; Red, Stuart; Lin, Eric; Sereno, Anne B.

    2015-01-01

    Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey’s task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes. PMID:26493949

  5. Chaotic and stable perturbed maps: 2-cycles and spatial models

    Science.gov (United States)

    Braverman, E.; Haroutunian, J.

    2010-06-01

    As the growth rate parameter increases in the Ricker, logistic and some other maps, the models exhibit an irreversible period doubling route to chaos. If a constant positive perturbation is introduced, then the Ricker model (but not the classical logistic map) experiences period doubling reversals; the break of chaos finally gives birth to a stable two-cycle. We outline the maps which demonstrate a similar behavior and also study relevant discrete spatial models where the value in each cell at the next step is defined only by the values at the cell and its nearest neighbors. The stable 2-cycle in a scalar map does not necessarily imply 2-cyclic-type behavior in each cell for the spatial generalization of the map.

  6. Single Canonical Model of Reflexive Memory and Spatial Attention.

    Science.gov (United States)

    Patel, Saumil S; Red, Stuart; Lin, Eric; Sereno, Anne B

    2015-10-23

    Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey's task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes.

  7. Neuromorphic model of magnocellular and parvocellular visual paths: spatial resolution

    International Nuclear Information System (INIS)

    Aguirre, Rolando C; Felice, Carmelo J; Colombo, Elisa M

    2007-01-01

    Physiological studies of the human retina show the existence of at least two visual information processing channels, the magnocellular and the parvocellular ones. Both have different spatial, temporal and chromatic features. This paper focuses on the different spatial resolution of these two channels. We propose a neuromorphic model, so that they match the retina's physiology. Considering the Deutsch and Deutsch model (1992), we propose two configurations (one for each visual channel) of the connection between the retina's different cell layers. The responses of the proposed model have similar behaviour to those of the visual cells: each channel has an optimum response corresponding to a given stimulus size which decreases for larger or smaller stimuli. This size is bigger for the magno path than for the parvo path and, in the end, both channels produce a magnifying of the borders of a stimulus

  8. Multi-Scale Influences of Climate, Spatial Pattern, and Positive Feedback on 20th Century Tree Establishment at Upper Treeline in the Rocky Mountains, USA

    Science.gov (United States)

    Elliott, G. P.

    2009-12-01

    The influences of 20th century climate, spatial pattern of tree establishment, and positive feedback were assessed to gain a more holistic understanding of how broad scale abiotic and local scale biotic components interact to govern upper treeline ecotonal dynamics along a latitudinal gradient (ca. 35°N-45°N) in the Rocky Mountains. Study sites (n = 22) were in the Bighorn, Medicine Bow, Front Range, and Sangre de Cristo mountain ranges. Dendroecological techniques were used for a broad scale analysis of climate at treeline. Five-year age-structure classes were compared with identical five-year bins of 20th century climate data using Spearman’s rank correlation and regime shift analysis. Local scale biotic interactions capable of ameliorating broad scale climate inputs through positive feedback were examined by using Ripley’s K to determine the spatial patterns of tree establishment above timberline. Significant correlations (p Medicine Bow and Sangre de Cristo Mountains primarily contain clustered spatial patterns of trees above timberline, which indicates a strong reliance on the amelioration of abiotic conditions through positive feedback with nearby vegetation. Although clustered spatial patterns likely originate in response to harsh abiotic conditions such as drought or constant strong winds, the local scale biotic interactions within a clustered formation of trees appears to override the immediate influence of broad scale climate. This is evidenced both by a lack of significant correlations between tree establishment and climate in these mountain ranges, as well as the considerable lag times between initial climate regime shifts and corresponding shifts in tree age structure. Taken together, this research suggests that the influence of broad scale climate on upper treeline ecotonal dynamics is contingent on the local scale spatial patterns of tree establishment and related influences of positive feedback. These findings have global implications for our

  9. Modeling spin magnetization transport in a spatially varying magnetic field

    International Nuclear Information System (INIS)

    Picone, Rico A.R.; Garbini, Joseph L.; Sidles, John A.

    2015-01-01

    We present a framework for modeling the transport of any number of globally conserved quantities in any spatial configuration and apply it to obtain a model of magnetization transport for spin-systems that is valid in new regimes (including high-polarization). The framework allows an entropy function to define a model that explicitly respects the laws of thermodynamics. Three facets of the model are explored. First, it is expressed as nonlinear partial differential equations that are valid for the new regime of high dipole-energy and polarization. Second, the nonlinear model is explored in the limit of low dipole-energy (semi-linear), from which is derived a physical parameter characterizing separative magnetization transport (SMT). It is shown that the necessary and sufficient condition for SMT to occur is that the parameter is spatially inhomogeneous. Third, the high spin-temperature (linear) limit is shown to be equivalent to the model of nuclear spin transport of Genack and Redfield (1975) [1]. Differences among the three forms of the model are illustrated by numerical solution with parameters corresponding to a magnetic resonance force microscopy (MRFM) experiment (Degen et al., 2009 [2]; Kuehn et al., 2008 [3]; Sidles et al., 2003 [4]; Dougherty et al., 2000 [5]). A family of analytic, steady-state solutions to the nonlinear equation is derived and shown to be the spin-temperature analog of the Langevin paramagnetic equation and Curie's law. Finally, we analyze the separative quality of magnetization transport, and a steady-state solution for the magnetization is shown to be compatible with Fenske's separative mass transport equation (Fenske, 1932 [6]). - Highlights: • A framework for modeling the transport of conserved magnetic and thermodynamic quantities in any spatial configuration. • A thermodynamically grounded model of spin magnetization transport valid in new regimes, including high-polarization. • Analysis of the separative quality of

  10. Modeling spin magnetization transport in a spatially varying magnetic field

    Energy Technology Data Exchange (ETDEWEB)

    Picone, Rico A.R., E-mail: rpicone@stmartin.edu [Department of Mechanical Engineering, University of Washington, Seattle (United States); Garbini, Joseph L. [Department of Mechanical Engineering, University of Washington, Seattle (United States); Sidles, John A. [Department of Orthopædics, University of Washington, Seattle (United States)

    2015-01-15

    We present a framework for modeling the transport of any number of globally conserved quantities in any spatial configuration and apply it to obtain a model of magnetization transport for spin-systems that is valid in new regimes (including high-polarization). The framework allows an entropy function to define a model that explicitly respects the laws of thermodynamics. Three facets of the model are explored. First, it is expressed as nonlinear partial differential equations that are valid for the new regime of high dipole-energy and polarization. Second, the nonlinear model is explored in the limit of low dipole-energy (semi-linear), from which is derived a physical parameter characterizing separative magnetization transport (SMT). It is shown that the necessary and sufficient condition for SMT to occur is that the parameter is spatially inhomogeneous. Third, the high spin-temperature (linear) limit is shown to be equivalent to the model of nuclear spin transport of Genack and Redfield (1975) [1]. Differences among the three forms of the model are illustrated by numerical solution with parameters corresponding to a magnetic resonance force microscopy (MRFM) experiment (Degen et al., 2009 [2]; Kuehn et al., 2008 [3]; Sidles et al., 2003 [4]; Dougherty et al., 2000 [5]). A family of analytic, steady-state solutions to the nonlinear equation is derived and shown to be the spin-temperature analog of the Langevin paramagnetic equation and Curie's law. Finally, we analyze the separative quality of magnetization transport, and a steady-state solution for the magnetization is shown to be compatible with Fenske's separative mass transport equation (Fenske, 1932 [6]). - Highlights: • A framework for modeling the transport of conserved magnetic and thermodynamic quantities in any spatial configuration. • A thermodynamically grounded model of spin magnetization transport valid in new regimes, including high-polarization. • Analysis of the separative quality of

  11. The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

    Science.gov (United States)

    Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

    2018-05-01

    The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

  12. Modeling molecular mixing in a spatially inhomogeneous turbulent flow

    Science.gov (United States)

    Meyer, Daniel W.; Deb, Rajdeep

    2012-02-01

    Simulations of spatially inhomogeneous turbulent mixing in decaying grid turbulence with a joint velocity-concentration probability density function (PDF) method were conducted. The inert mixing scenario involves three streams with different compositions. The mixing model of Meyer ["A new particle interaction mixing model for turbulent dispersion and turbulent reactive flows," Phys. Fluids 22(3), 035103 (2010)], the interaction by exchange with the mean (IEM) model and its velocity-conditional variant, i.e., the IECM model, were applied. For reference, the direct numerical simulation data provided by Sawford and de Bruyn Kops ["Direct numerical simulation and lagrangian modeling of joint scalar statistics in ternary mixing," Phys. Fluids 20(9), 095106 (2008)] was used. It was found that velocity conditioning is essential to obtain accurate concentration PDF predictions. Moreover, the model of Meyer provides significantly better results compared to the IECM model at comparable computational expense.

  13. A general modeling framework for describing spatially structured population dynamics

    Science.gov (United States)

    Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

    2017-01-01

    Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance

  14. Spatial distribution of emissions to air - the SPREAD model

    Energy Technology Data Exchange (ETDEWEB)

    Plejdrup, M S; Gyldenkaerne, S

    2011-04-15

    The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)

  15. Sparse modeling of spatial environmental variables associated with asthma.

    Science.gov (United States)

    Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

    2015-02-01

    Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Spatial distribution of emissions to air - the SPREAD model

    Energy Technology Data Exchange (ETDEWEB)

    Plejdrup, M.S.; Gyldenkaerne, S.

    2011-04-15

    The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)

  17. Tapered composite likelihood for spatial max-stable models

    KAUST Repository

    Sang, Huiyan

    2014-05-01

    Spatial extreme value analysis is useful to environmental studies, in which extreme value phenomena are of interest and meaningful spatial patterns can be discerned. Max-stable process models are able to describe such phenomena. This class of models is asymptotically justified to characterize the spatial dependence among extremes. However, likelihood inference is challenging for such models because their corresponding joint likelihood is unavailable and only bivariate or trivariate distributions are known. In this paper, we propose a tapered composite likelihood approach by utilizing lower dimensional marginal likelihoods for inference on parameters of various max-stable process models. We consider a weighting strategy based on a "taper range" to exclude distant pairs or triples. The "optimal taper range" is selected to maximize various measures of the Godambe information associated with the tapered composite likelihood function. This method substantially reduces the computational cost and improves the efficiency over equally weighted composite likelihood estimators. We illustrate its utility with simulation experiments and an analysis of rainfall data in Switzerland.

  18. Database modeling to integrate macrobenthos data in Spatial Data Infrastructure

    Directory of Open Access Journals (Sweden)

    José Alberto Quintanilha

    2012-08-01

    Full Text Available Coastal zones are complex areas that include marine and terrestrial environments. Besides its huge environmental wealth, they also attracts humans because provides food, recreation, business, and transportation, among others. Some difficulties to manage these areas are related with their complexity, diversity of interests and the absence of standardization to collect and share data to scientific community, public agencies, among others. The idea to organize, standardize and share this information based on Web Atlas is essential to support planning and decision making issues. The construction of a spatial database integrating the environmental business, to be used on Spatial Data Infrastructure (SDI is illustrated by a bioindicator that indicates the quality of the sediments. The models show the phases required to build Macrobenthos spatial database based on Santos Metropolitan Region as a reference. It is concluded that, when working with environmental data the structuring of knowledge in a conceptual model is essential for their subsequent integration into the SDI. During the modeling process it can be noticed that methodological issues related to the collection process may obstruct or prejudice the integration of data from different studies of the same area. The development of a database model, as presented in this study, can be used as a reference for further research with similar goals.

  19. Tapered composite likelihood for spatial max-stable models

    KAUST Repository

    Sang, Huiyan; Genton, Marc G.

    2014-01-01

    Spatial extreme value analysis is useful to environmental studies, in which extreme value phenomena are of interest and meaningful spatial patterns can be discerned. Max-stable process models are able to describe such phenomena. This class of models is asymptotically justified to characterize the spatial dependence among extremes. However, likelihood inference is challenging for such models because their corresponding joint likelihood is unavailable and only bivariate or trivariate distributions are known. In this paper, we propose a tapered composite likelihood approach by utilizing lower dimensional marginal likelihoods for inference on parameters of various max-stable process models. We consider a weighting strategy based on a "taper range" to exclude distant pairs or triples. The "optimal taper range" is selected to maximize various measures of the Godambe information associated with the tapered composite likelihood function. This method substantially reduces the computational cost and improves the efficiency over equally weighted composite likelihood estimators. We illustrate its utility with simulation experiments and an analysis of rainfall data in Switzerland.

  20. Spatial Modelling of Sediment Transport over the Upper Citarum Catchment

    Directory of Open Access Journals (Sweden)

    Poerbandono

    2006-05-01

    Full Text Available This paper discusses set up of a spatial model applied in Geographic Information System (GIS environment for predicting annual erosion rate and sediment yield of a watershed. The study area is situated in the Upper Citarum Catchment of West Java. Annual sediment yield is considered as product of erosion rate and sediment delivery ratio to be modelled under similar modeling tool. Sediment delivery ratio is estimated on the basis of sediment resident time. The modeling concept is based on the calculation of water flow velocity through sub-catchment surface, which is controlled by topography, rainfall, soil characteristics and various types of land use. Relating velocity to known distance across digital elevation model, sediment resident time can be estimated. Data from relevance authorities are used. Bearing in mind limited knowledge of some governing factors due to lack of observation, the result has shown the potential of GIS for spatially modeling regional sediment transport. Validation of model result is carried out by evaluating measured and computed total sediment yield at the main outlet. Computed total sediment yields for 1994 and 2001 are found to be 1.96×106 and 2.10×106tons/year. They deviate roughly 54 and 8% with respect to those measured in the field. Model response due to land use change observed in 2001 and 1994 is also recognised. Under presumably constant rainfall depth, an increase of overall average annual erosion rate of 11% resulted in an increase of overall average sediment yield of 7%.

  1. Supplementary Material for: Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.

    2016-01-01

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  2. A spatial structural derivative model for ultraslow diffusion

    Directory of Open Access Journals (Sweden)

    Xu Wei

    2017-01-01

    Full Text Available This study investigates the ultraslow diffusion by a spatial structural derivative, in which the exponential function ex is selected as the structural function to construct the local structural derivative diffusion equation model. The analytical solution of the diffusion equation is a form of Biexponential distribution. Its corresponding mean squared displacement is numerically calculated, and increases more slowly than the logarithmic function of time. The local structural derivative diffusion equation with the structural function ex in space is an alternative physical and mathematical modeling model to characterize a kind of ultraslow diffusion.

  3. Spatial modeling of HIV and HSV-2 among women in Kenya with spatially varying coefficients

    Directory of Open Access Journals (Sweden)

    Elphas Okango

    2016-04-01

    Full Text Available Abstract Background Disease mapping has become popular in the field of statistics as a method to explain the spatial distribution of disease outcomes and as a tool to help design targeted intervention strategies. Most of these models however have been implemented with assumptions that may be limiting or altogether lead to less meaningful results and hence interpretations. Some of these assumptions include the linearity, stationarity and normality assumptions. Studies have shown that the linearity assumption is not necessarily true for all covariates. Age for example has been found to have a non-linear relationship with HIV and HSV-2 prevalence. Other studies have made stationarity assumption in that one stimulus e.g. education, provokes the same response in all the regions under study and this is also quite restrictive. Responses to stimuli may vary from region to region due to aspects like culture, preferences and attitudes. Methods We perform a spatial modeling of HIV and HSV-2 among women in Kenya, while relaxing these assumptions i.e. the linearity assumption by allowing the covariate age to have a non-linear effect on HIV and HSV-2 prevalence using the random walk model of order 2 and the stationarity assumption by allowing the rest of the covariates to vary spatially using the conditional autoregressive model. The women data used in this study were derived from the 2007 Kenya AIDS indicator survey where women aged 15–49 years were surveyed. A full Bayesian approach was used and the models were implemented in R-INLA software. Results Age was found to have a non-linear relationship with both HIV and HSV-2 prevalence, and the spatially varying coefficient model provided a significantly better fit for HSV-2. Age-at first sex also had a greater effect on HSV-2 prevalence in the Coastal and some parts of North Eastern regions suggesting either early marriages or child prostitution. The effect of education on HIV prevalence among women was more

  4. Modelling H5N1 in Bangladesh across spatial scales: Model complexity and zoonotic transmission risk

    Directory of Open Access Journals (Sweden)

    Edward M. Hill

    2017-09-01

    Full Text Available Highly pathogenic avian influenza H5N1 remains a persistent public health threat, capable of causing infection in humans with a high mortality rate while simultaneously negatively impacting the livestock industry. A central question is to determine regions that are likely sources of newly emerging influenza strains with pandemic causing potential. A suitable candidate is Bangladesh, being one of the most densely populated countries in the world and having an intensifying farming system. It is therefore vital to establish the key factors, specific to Bangladesh, that enable both continued transmission within poultry and spillover across the human–animal interface. We apply a modelling framework to H5N1 epidemics in the Dhaka region of Bangladesh, occurring from 2007 onwards, that resulted in large outbreaks in the poultry sector and a limited number of confirmed human cases. This model consisted of separate poultry transmission and zoonotic transmission components. Utilising poultry farm spatial and population information a set of competing nested models of varying complexity were fitted to the observed case data, with parameter inference carried out using Bayesian methodology and goodness-of-fit verified by stochastic simulations. For the poultry transmission component, successfully identifying a model of minimal complexity, which enabled the accurate prediction of the size and spatial distribution of cases in H5N1 outbreaks, was found to be dependent on the administration level being analysed. A consistent outcome of non-optimal reporting of infected premises materialised in each poultry epidemic of interest, though across the outbreaks analysed there were substantial differences in the estimated transmission parameters. The zoonotic transmission component found the main contributor to spillover transmission of H5N1 in Bangladesh was found to differ from one poultry epidemic to another. We conclude by discussing possible explanations for

  5. Models of chromatin spatial organisation in the cell nucleus

    Science.gov (United States)

    Nicodemi, Mario

    2014-03-01

    In the cell nucleus chromosomes have a complex architecture serving vital functional purposes. Recent experiments have started unveiling the interaction map of DNA sites genome-wide, revealing different levels of organisation at different scales. The principles, though, which orchestrate such a complex 3D structure remain still mysterious. I will overview the scenario emerging from some classical polymer physics models of the general aspect of chromatin spatial organisation. The available experimental data, which can be rationalised in a single framework, support a picture where chromatin is a complex mixture of differently folded regions, self-organised across spatial scales according to basic physical mechanisms. I will also discuss applications to specific DNA loci, e.g. the HoxB locus, where models informed with biological details, and tested against targeted experiments, can help identifying the determinants of folding.

  6. Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

    Science.gov (United States)

    Le, Phuong Dong; Leonard, Michael; Westra, Seth

    2018-03-01

    Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

  7. Spatial Models of Prebiotic Evolution: Soup Before Pizza?

    Science.gov (United States)

    Scheuring, István; Czárán, Tamás; Szabó, Péter; Károlyi, György; Toroczkai, Zoltán

    2003-10-01

    The problem of information integration and resistance to the invasion of parasitic mutants in prebiotic replicator systems is a notorious issue of research on the origin of life. Almost all theoretical studies published so far have demonstrated that some kind of spatial structure is indispensable for the persistence and/or the parasite resistance of any feasible replicator system. Based on a detailed critical survey of spatial models on prebiotic information integration, we suggest a possible scenario for replicator system evolution leading to the emergence of the first protocells capable of independent life. We show that even the spatial versions of the hypercycle model are vulnerable to selfish parasites in heterogeneous habitats. Contrary, the metabolic system remains persistent and coexistent with its parasites both on heterogeneous surfaces and in chaotically mixing flowing media. Persistent metabolic parasites can be converted to metabolic cooperators, or they can gradually obtain replicase activity. Our simulations show that, once replicase activity emerged, a gradual and simultaneous evolutionary improvement of replicase functionality (speed and fidelity) and template efficiency is possible only on a surface that constrains the mobility of macromolecule replicators. Based on the results of the models reviewed, we suggest that open chaotic flows (`soup') and surface dynamics (`pizza') both played key roles in the sequence of evolutionary events ultimately concluding in the appearance of the first living cell on Earth.

  8. Modeling spatial invasion of Ebola in West Africa.

    Science.gov (United States)

    D'Silva, Jeremy P; Eisenberg, Marisa C

    2017-09-07

    The 2014-2016 Ebola Virus Disease (EVD) epidemic in West Africa was the largest ever recorded, representing a fundamental shift in Ebola epidemiology with unprecedented spatiotemporal complexity. To understand the spatiotemporal dynamics of EVD in West Africa, we developed spatial transmission models using a gravity-model framework at both the national and district-level scales, which we used to compare effectiveness of local interventions (e.g. local quarantine) and long-range interventions (e.g. border-closures). The country-level gravity model captures the epidemic data, including multiple waves of initial epidemic growth observed in Guinea. We found that local-transmission reductions were most effective in Liberia, while long-range transmission was dominant in Sierra Leone. Both models illustrated that interventions in one region result in an amplified protective effect on other regions by preventing spatial transmission. In the district-level model, interventions in the strongest of these amplifying regions reduced total cases in all three countries by over 20%, in spite of the region itself generating only ∼0.1% of total cases. This model structure and associated intervention analysis provide information that can be used by public health policymakers to assist planning and response efforts for future epidemics. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. A modal approach to modeling spatially distributed vibration energy dissipation.

    Energy Technology Data Exchange (ETDEWEB)

    Segalman, Daniel Joseph

    2010-08-01

    The nonlinear behavior of mechanical joints is a confounding element in modeling the dynamic response of structures. Though there has been some progress in recent years in modeling individual joints, modeling the full structure with myriad frictional interfaces has remained an obstinate challenge. A strategy is suggested for structural dynamics modeling that can account for the combined effect of interface friction distributed spatially about the structure. This approach accommodates the following observations: (1) At small to modest amplitudes, the nonlinearity of jointed structures is manifest primarily in the energy dissipation - visible as vibration damping; (2) Correspondingly, measured vibration modes do not change significantly with amplitude; and (3) Significant coupling among the modes does not appear to result at modest amplitudes. The mathematical approach presented here postulates the preservation of linear modes and invests all the nonlinearity in the evolution of the modal coordinates. The constitutive form selected is one that works well in modeling spatially discrete joints. When compared against a mathematical truth model, the distributed dissipation approximation performs well.

  10. Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes

    Science.gov (United States)

    Wiens, J. David; Schumaker, Nathan H.; Inman, Richard D.; Esque, Todd C.; Longshore, Kathleen M.; Nussear, Kenneth E

    2017-01-01

    Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land use and anthropogenic stressors can be incorporated into a spatial demographic model to investigate effects on population dynamics of Golden Eagles (Aquila chrysaetos). Our study focused on a population of Golden Eagles exposed to risks associated with rapid increases in renewable energy development in southern California, U.S.A. We developed a spatially explicit, individual-based simulation model that integrated empirical data on demography of Golden Eagles with spatial data on the arrangement of nesting habitats, prey resources, and planned renewable energy development sites. Our model permitted simulated eagles of different stage-classes to disperse, establish home ranges, acquire prey resources, prospect for breeding sites, and reproduce. The distribution of nesting habitats, prey resources, and threats within each individual's home range influenced movement, reproduction, and survival. We used our model to explore potential effects of alternative disturbance scenarios, and proposed conservation strategies, on the future distribution and abundance of Golden Eagles in the study region. Results from our simulations suggest that probable increases in mortality associated with renewable energy infrastructure (e.g., collisions with wind turbines and vehicles, electrocution on power poles) could have negative consequences for population trajectories, but that site-specific conservation actions could reduce the magnitude of negative effects. Our study demonstrates the use of a flexible and expandable modeling framework to incorporate spatially dependent processes when determining relative effects of proposed management options to Golden Eagles and their habitats.

  11. Bayesian spatial semi-parametric modeling of HIV variation in Kenya.

    Directory of Open Access Journals (Sweden)

    Oscar Ngesa

    Full Text Available Spatial statistics has seen rapid application in many fields, especially epidemiology and public health. Many studies, nonetheless, make limited use of the geographical location information and also usually assume that the covariates, which are related to the response variable, have linear effects. We develop a Bayesian semi-parametric regression model for HIV prevalence data. Model estimation and inference is based on fully Bayesian approach via Markov Chain Monte Carlo (McMC. The model is applied to HIV prevalence data among men in Kenya, derived from the Kenya AIDS indicator survey, with n = 3,662. Past studies have concluded that HIV infection has a nonlinear association with age. In this study a smooth function based on penalized regression splines is used to estimate this nonlinear effect. Other covariates were assumed to have a linear effect. Spatial references to the counties were modeled as both structured and unstructured spatial effects. We observe that circumcision reduces the risk of HIV infection. The results also indicate that men in the urban areas were more likely to be infected by HIV as compared to their rural counterpart. Men with higher education had the lowest risk of HIV infection. A nonlinear relationship between HIV infection and age was established. Risk of HIV infection increases with age up to the age of 40 then declines with increase in age. Men who had STI in the last 12 months were more likely to be infected with HIV. Also men who had ever used a condom were found to have higher likelihood to be infected by HIV. A significant spatial variation of HIV infection in Kenya was also established. The study shows the practicality and flexibility of Bayesian semi-parametric regression model in analyzing epidemiological data.

  12. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    Science.gov (United States)

    Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

    2012-01-01

    Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

  13. Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling

    Science.gov (United States)

    Brakebill, J.W.; Wolock, D.M.; Terziotti, S.E.

    2011-01-01

    Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

  14. A framework for widespread replication of a highly spatially resolved childhood lead exposure risk model.

    Science.gov (United States)

    Kim, Dohyeong; Galeano, M Alicia Overstreet; Hull, Andrew; Miranda, Marie Lynn

    2008-12-01

    Preventive approaches to childhood lead poisoning are critical for addressing this longstanding environmental health concern. Moreover, increasing evidence of cognitive effects of blood lead levels system-based childhood lead exposure risk models, especially if executed at highly resolved spatial scales, can help identify children most at risk of lead exposure, as well as prioritize and direct housing and health-protective intervention programs. However, developing highly resolved spatial data requires labor-and time-intensive geocoding and analytical processes. In this study we evaluated the benefit of increased effort spent geocoding in terms of improved performance of lead exposure risk models. We constructed three childhood lead exposure risk models based on established methods but using different levels of geocoded data from blood lead surveillance, county tax assessors, and the 2000 U.S. Census for 18 counties in North Carolina. We used the results to predict lead exposure risk levels mapped at the individual tax parcel unit. The models performed well enough to identify high-risk areas for targeted intervention, even with a relatively low level of effort on geocoding. This study demonstrates the feasibility of widespread replication of highly spatially resolved childhood lead exposure risk models. The models guide resource-constrained local health and housing departments and community-based organizations on how best to expend their efforts in preventing and mitigating lead exposure risk in their communities.

  15. Propagation dynamics for a spatially periodic integrodifference competition model

    Science.gov (United States)

    Wu, Ruiwen; Zhao, Xiao-Qiang

    2018-05-01

    In this paper, we study the propagation dynamics for a class of integrodifference competition models in a periodic habitat. An interesting feature of such a system is that multiple spreading speeds can be observed, which biologically means different species may have different spreading speeds. We show that the model system admits a single spreading speed, and it coincides with the minimal wave speed of the spatially periodic traveling waves. A set of sufficient conditions for linear determinacy of the spreading speed is also given.

  16. How to get rid of W: a latent variables approach to modelling spatially lagged variables

    NARCIS (Netherlands)

    Folmer, H.; Oud, J.

    2008-01-01

    In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are

  17. How to get rid of W : a latent variables approach to modelling spatially lagged variables

    NARCIS (Netherlands)

    Folmer, Henk; Oud, Johan

    2008-01-01

    In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are

  18. The spatial impact of neighbouring on the exports activities of COMESA countries by using spatial panel models

    Science.gov (United States)

    Hamzalouh, L.; Ismail, M. T.; Rahman, R. A.

    2017-09-01

    In this paper, spatial panel models were used and the method for selecting the best model amongst the spatial fixed effects model and the spatial random effects model to estimate the fitting model by using the robust Hausman test for analysis of the exports pattern of the Common Market for Eastern and Southern African (COMESA) countries. And examine the effects of the interactions of the economic statistic of explanatory variables on the exports of the COMESA. Results indicated that the spatial Durbin model with fixed effects specification should be tested and considered in most cases of this study. After that, the direct and indirect effects among COMESA regions were assessed, and the role of indirect spatial effects in estimating exports was empirically demonstrated. Regarding originality and research value, and to the best of the authors’ knowledge, this is the first attempt to examine exports between COMESA and its member countries through spatial panel models using XSMLE, which is a new command for spatial analysis using STATA.

  19. Combining groundwater quality analysis and a numerical flow simulation for spatially establishing utilization strategies for groundwater and surface water in the Pingtung Plain

    Science.gov (United States)

    Jang, Cheng-Shin; Chen, Ching-Fang; Liang, Ching-Ping; Chen, Jui-Sheng

    2016-02-01

    Overexploitation of groundwater is a common problem in the Pingtung Plain area of Taiwan, resulting in substantial drawdown of groundwater levels as well as the occurrence of severe seawater intrusion and land subsidence. Measures need to be taken to preserve these valuable groundwater resources. This study seeks to spatially determine the most suitable locations for the use of surface water on this plain instead of extracting groundwater for drinking, irrigation, and aquaculture purposes based on information obtained by combining groundwater quality analysis and a numerical flow simulation assuming the planning of manmade lakes and reservoirs to the increase of water supply. The multivariate indicator kriging method is first used to estimate occurrence probabilities, and to rank townships as suitable or unsuitable for groundwater utilization according to water quality standards for drinking, irrigation, and aquaculture. A numerical model of groundwater flow (MODFLOW) is adopted to quantify the recovery of groundwater levels in townships after model calibration when groundwater for drinking and agricultural demands has been replaced by surface water. Finally, townships with poor groundwater quality and significant increases in groundwater levels in the Pingtung Plain are prioritized for the groundwater conservation planning based on the combined assessment of groundwater quality and quantity. The results of this study indicate that the integration of groundwater quality analysis and the numerical flow simulation is capable of establishing sound strategies for joint groundwater and surface water use. Six southeastern townships are found to be suitable locations for replacing groundwater with surface water from manmade lakes or reservoirs to meet drinking, irrigation, and aquaculture demands.

  20. Economic and Environmental Effects of Public Transport Subsidy Policies: a Spatial CGE Model of Beijing

    Directory of Open Access Journals (Sweden)

    Ping Xu

    2018-01-01

    Full Text Available Public transport plays an important role in the environment. This study established a Spatial Computable General Equilibrium (SCGE model to examine the economic and environmental effects of public transport subsidy policies. The model includes firms, consumers, and traffic modules in one framework. Statistical data from Beijing were used in calibration to obtain benchmark equilibrium. Based on the equilibrium, simulations compared citywide social welfare, jobs-housing spatial population distribution, and environmental outputs under four subsidy policies: fare subsidy, cash grants, road expansion, and public transport speedup. Based on the results regarding the effects of public transport policies, conclusions can be drawn about which policies will have greater overall social influence and should therefore be used.

  1. Spatial stochastic regression modelling of urban land use

    International Nuclear Information System (INIS)

    Arshad, S H M; Jaafar, J; Abiden, M Z Z; Latif, Z A; Rasam, A R A

    2014-01-01

    Urbanization is very closely linked to industrialization, commercialization or overall economic growth and development. This results in innumerable benefits of the quantity and quality of the urban environment and lifestyle but on the other hand contributes to unbounded development, urban sprawl, overcrowding and decreasing standard of living. Regulation and observation of urban development activities is crucial. The understanding of urban systems that promotes urban growth are also essential for the purpose of policy making, formulating development strategies as well as development plan preparation. This study aims to compare two different stochastic regression modeling techniques for spatial structure models of urban growth in the same specific study area. Both techniques will utilize the same datasets and their results will be analyzed. The work starts by producing an urban growth model by using stochastic regression modeling techniques namely the Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR). The two techniques are compared to and it is found that, GWR seems to be a more significant stochastic regression model compared to OLS, it gives a smaller AICc (Akaike's Information Corrected Criterion) value and its output is more spatially explainable

  2. Spatial modeling for groundwater arsenic levels in North Carolina.

    Science.gov (United States)

    Kim, Dohyeong; Miranda, Marie Lynn; Tootoo, Joshua; Bradley, Phil; Gelfand, Alan E

    2011-06-01

    To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area.

  3. Modeling spatial processes with unknown extremal dependence class

    KAUST Repository

    Huser, Raphaël G.

    2017-03-17

    Many environmental processes exhibit weakening spatial dependence as events become more extreme. Well-known limiting models, such as max-stable or generalized Pareto processes, cannot capture this, which can lead to a preference for models that exhibit a property known as asymptotic independence. However, weakening dependence does not automatically imply asymptotic independence, and whether the process is truly asymptotically (in)dependent is usually far from clear. The distinction is key as it can have a large impact upon extrapolation, i.e., the estimated probabilities of events more extreme than those observed. In this work, we present a single spatial model that is able to capture both dependence classes in a parsimonious manner, and with a smooth transition between the two cases. The model covers a wide range of possibilities from asymptotic independence through to complete dependence, and permits weakening dependence of extremes even under asymptotic dependence. Censored likelihood-based inference for the implied copula is feasible in moderate dimensions due to closed-form margins. The model is applied to oceanographic datasets with ambiguous true limiting dependence structure.

  4. Spatial Modeling for Groundwater Arsenic Levels in North Carolina

    Science.gov (United States)

    Kim, Dohyeong; Miranda, Marie Lynn; Tootoo, Joshua; Bradley, Phil; Gelfand, Alan E.

    2013-01-01

    To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area. PMID:21528844

  5. Spatially balanced topological interaction grants optimal cohesion in flocking models.

    Science.gov (United States)

    Camperi, Marcelo; Cavagna, Andrea; Giardina, Irene; Parisi, Giorgio; Silvestri, Edmondo

    2012-12-06

    Models of self-propelled particles (SPPs) are an indispensable tool to investigate collective animal behaviour. Originally, SPP models were proposed with metric interactions, where each individual coordinates with neighbours within a fixed metric radius. However, recent experiments on bird flocks indicate that interactions are topological: each individual interacts with a fixed number of neighbours, irrespective of their distance. It has been argued that topological interactions are more robust than metric ones against external perturbations, a significant evolutionary advantage for systems under constant predatory pressure. Here, we test this hypothesis by comparing the stability of metric versus topological SPP models in three dimensions. We show that topological models are more stable than metric ones. We also show that a significantly better stability is achieved when neighbours are selected according to a spatially balanced topological rule, namely when interacting neighbours are evenly distributed in angle around the focal individual. Finally, we find that the minimal number of interacting neighbours needed to achieve fully stable cohesion in a spatially balanced model is compatible with the value observed in field experiments on starling flocks.

  6. Spatial modeling for groundwater arsenic levels in North Carolina

    Science.gov (United States)

    Kim, D.; Miranda, M.L.; Tootoo, J.; Bradley, P.; Gelfand, A.E.

    2011-01-01

    To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area. ?? 2011 American Chemical Society.

  7. Spatial Durbin model analysis macroeconomic loss due to natural disasters

    Science.gov (United States)

    Kusrini, D. E.; Mukhtasor

    2015-03-01

    Magnitude of the damage and losses caused by natural disasters is huge for Indonesia, therefore this study aimed to analyze the effects of natural disasters for macroeconomic losses that occurred in 115 cities/districts across Java during 2012. Based on the results of previous studies it is suspected that it contains effects of spatial dependencies in this case, so that the completion of this case is performed using a regression approach to the area, namely Analysis of Spatial Durbin Model (SDM). The obtained significant predictor variable is population, and predictor variable with a significant weighting is the number of occurrences of disasters, i.e., disasters in the region which have an impact on other neighboring regions. Moran's I index value using the weighted Queen Contiguity also showed significant results, meaning that the incidence of disasters in the region will decrease the value of GDP in other.

  8. Spatial and spatio-temporal bayesian models with R - INLA

    CERN Document Server

    Blangiardo, Marta

    2015-01-01

    Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior Distr

  9. A spatial simulation model for the dispersal of the bluetongue vector Culicoides brevitarsis in Australia.

    Directory of Open Access Journals (Sweden)

    Joel K Kelso

    Full Text Available The spread of Bluetongue virus (BTV among ruminants is caused by movement of infected host animals or by movement of infected Culicoides midges, the vector of BTV. Biologically plausible models of Culicoides dispersal are necessary for predicting the spread of BTV and are important for planning control and eradication strategies.A spatially-explicit simulation model which captures the two underlying population mechanisms, population dynamics and movement, was developed using extensive data from a trapping program for C. brevitarsis on the east coast of Australia. A realistic midge flight sub-model was developed and the annual incursion and population establishment of C. brevitarsis was simulated. Data from the literature was used to parameterise the model.The model was shown to reproduce the spread of C. brevitarsis southwards along the east Australian coastline in spring, from an endemic population to the north. Such incursions were shown to be reliant on wind-dispersal; Culicoides midge active flight on its own was not capable of achieving known rates of southern spread, nor was re-emergence of southern populations due to overwintering larvae. Data from midge trapping programmes were used to qualitatively validate the resulting simulation model.The model described in this paper is intended to form the vector component of an extended model that will also include BTV transmission. A model of midge movement and population dynamics has been developed in sufficient detail such that the extended model may be used to evaluate the timing and extent of BTV outbreaks. This extended model could then be used as a platform for addressing the effectiveness of spatially targeted vaccination strategies or animal movement bans as BTV spread mitigation measures, or the impact of climate change on the risk and extent of outbreaks. These questions involving incursive Culicoides spread cannot be simply addressed with non-spatial models.

  10. A Comparison of Grizzly Bear Demographic Parameters Estimated from Non-Spatial and Spatial Open Population Capture-Recapture Models.

    Science.gov (United States)

    Whittington, Jesse; Sawaya, Michael A

    2015-01-01

    Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal's home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786-1.071) for females, 0.844 (0.703-0.975) for males, and 0.882 (0.779-0.981) for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758-1.024) for females, 0.825 (0.700-0.948) for males, and 0.863 (0.771-0.957) for both sexes. The combination of low densities, low reproductive rates, and predominantly negative population growth

  11. A Comparison of Grizzly Bear Demographic Parameters Estimated from Non-Spatial and Spatial Open Population Capture-Recapture Models.

    Directory of Open Access Journals (Sweden)

    Jesse Whittington

    Full Text Available Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal's home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786-1.071 for females, 0.844 (0.703-0.975 for males, and 0.882 (0.779-0.981 for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758-1.024 for females, 0.825 (0.700-0.948 for males, and 0.863 (0.771-0.957 for both sexes. The combination of low densities, low reproductive rates, and predominantly negative

  12. Towards Quantitative Spatial Models of Seabed Sediment Composition.

    Directory of Open Access Journals (Sweden)

    David Stephens

    Full Text Available There is a need for fit-for-purpose maps for accurately depicting the types of seabed substrate and habitat and the properties of the seabed for the benefits of research, resource management, conservation and spatial planning. The aim of this study is to determine whether it is possible to predict substrate composition across a large area of seabed using legacy grain-size data and environmental predictors. The study area includes the North Sea up to approximately 58.44°N and the United Kingdom's parts of the English Channel and the Celtic Seas. The analysis combines outputs from hydrodynamic models as well as optical remote sensing data from satellite platforms and bathymetric variables, which are mainly derived from acoustic remote sensing. We build a statistical regression model to make quantitative predictions of sediment composition (fractions of mud, sand and gravel using the random forest algorithm. The compositional data is analysed on the additive log-ratio scale. An independent test set indicates that approximately 66% and 71% of the variability of the two log-ratio variables are explained by the predictive models. A EUNIS substrate model, derived from the predicted sediment composition, achieved an overall accuracy of 83% and a kappa coefficient of 0.60. We demonstrate that it is feasible to spatially predict the seabed sediment composition across a large area of continental shelf in a repeatable and validated way. We also highlight the potential for further improvements to the method.

  13. Assessing fit in Bayesian models for spatial processes

    KAUST Repository

    Jun, M.

    2014-09-16

    © 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models\\' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.

  14. Assessing fit in Bayesian models for spatial processes

    KAUST Repository

    Jun, M.; Katzfuss, M.; Hu, J.; Johnson, V. E.

    2014-01-01

    © 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.

  15. Establishment of a tumor neovascularization animal model with biomaterials in rabbit corneal pouch.

    Science.gov (United States)

    Chu, Yu-Ping; Li, Hong-Chuan; Ma, Ling; Xia, Yang

    2018-06-01

    The present animal model of tumor neovascularization most often used by researchers is zebrafish. For studies on human breast cancer cell neovascularization, a new animal model was established to enable a more convenient study of tumor neovascularization. A sodium alginate-gelatin blend gel system was used to design the new animal model. The model was established using rabbit corneal pouch implantation. Then, the animal model was validated by human breast cancer cell lines MCF-7-Kindlin-2 and MCF-7-CMV. The experiment intuitively observed the relationship between tumor and neovascularization, and demonstrated the advantages of this animal model in the study of tumor neovascularization. The use of sodium alginate-gelatin blends to establish tumor neovascularization in a rabbit corneal pouch is a novel and ideal method for the study of neovascularization. It may be a better animal model for expanding the research in this area. Copyright © 2018 Elsevier Inc. All rights reserved.

  16. Bayesian spatial modelling and the significance of agricultural land use to scrub typhus infection in Taiwan.

    Science.gov (United States)

    Wardrop, Nicola A; Kuo, Chi-Chien; Wang, Hsi-Chieh; Clements, Archie C A; Lee, Pei-Fen; Atkinson, Peter M

    2013-11-01

    Scrub typhus is transmitted by the larval stage of trombiculid mites. Environmental factors, including land cover and land use, are known to influence breeding and survival of trombiculid mites and, thus, also the spatial heterogeneity of scrub typhus risk. Here, a spatially autoregressive modelling framework was applied to scrub typhus incidence data from Taiwan, covering the period 2003 to 2011, to provide increased understanding of the spatial pattern of scrub typhus risk and the environmental and socioeconomic factors contributing to this pattern. A clear spatial pattern in scrub typhus incidence was observed within Taiwan, and incidence was found to be significantly correlated with several land cover classes, temperature, elevation, normalized difference vegetation index, rainfall, population density, average income and the proportion of the population that work in agriculture. The final multivariate regression model included statistically significant correlations between scrub typhus incidence and average income (negatively correlated), the proportion of land that contained mosaics of cropland and vegetation (positively correlated) and elevation (positively correlated). These results highlight the importance of land cover on scrub typhus incidence: mosaics of cropland and vegetation represent a transitional land cover type which can provide favourable habitats for rodents and, therefore, trombiculid mites. In Taiwan, these transitional land cover areas tend to occur in less populated and mountainous areas, following the frontier establishment and subsequent partial abandonment of agricultural cultivation, due to demographic and socioeconomic changes. Future land use policy decision-making should ensure that potential public health outcomes, such as modified risk of scrub typhus, are considered.

  17. Modeling spin magnetization transport in a spatially varying magnetic field

    Science.gov (United States)

    Picone, Rico A. R.; Garbini, Joseph L.; Sidles, John A.

    2015-01-01

    We present a framework for modeling the transport of any number of globally conserved quantities in any spatial configuration and apply it to obtain a model of magnetization transport for spin-systems that is valid in new regimes (including high-polarization). The framework allows an entropy function to define a model that explicitly respects the laws of thermodynamics. Three facets of the model are explored. First, it is expressed as nonlinear partial differential equations that are valid for the new regime of high dipole-energy and polarization. Second, the nonlinear model is explored in the limit of low dipole-energy (semi-linear), from which is derived a physical parameter characterizing separative magnetization transport (SMT). It is shown that the necessary and sufficient condition for SMT to occur is that the parameter is spatially inhomogeneous. Third, the high spin-temperature (linear) limit is shown to be equivalent to the model of nuclear spin transport of Genack and Redfield (1975) [1]. Differences among the three forms of the model are illustrated by numerical solution with parameters corresponding to a magnetic resonance force microscopy (MRFM) experiment (Degen et al., 2009 [2]; Kuehn et al., 2008 [3]; Sidles et al., 2003 [4]; Dougherty et al., 2000 [5]). A family of analytic, steady-state solutions to the nonlinear equation is derived and shown to be the spin-temperature analog of the Langevin paramagnetic equation and Curie's law. Finally, we analyze the separative quality of magnetization transport, and a steady-state solution for the magnetization is shown to be compatible with Fenske's separative mass transport equation (Fenske, 1932 [6]).

  18. Toward Accessing Spatial Structure from Building Information Models

    Science.gov (United States)

    Schultz, C.; Bhatt, M.

    2011-08-01

    Data about building designs and layouts is becoming increasingly more readily available. In the near future, service personal (such as maintenance staff or emergency rescue workers) arriving at a building site will have immediate real-time access to enormous amounts of data relating to structural properties, utilities, materials, temperature, and so on. The critical problem for users is the taxing and error prone task of interpreting such a large body of facts in order to extract salient information. This is necessary for comprehending a situation and deciding on a plan of action, and is a particularly serious issue in time-critical and safety-critical activities such as firefighting. Current unifying building models such as the Industry Foundation Classes (IFC), while being comprehensive, do not directly provide data structures that focus on spatial reasoning and spatial modalities that are required for high-level analytical tasks. The aim of the research presented in this paper is to provide computational tools for higher level querying and reasoning that shift the cognitive burden of dealing with enormous amounts of data away from the user. The user can then spend more energy and time in planning and decision making in order to accomplish the tasks at hand. We present an overview of our framework that provides users with an enhanced model of "built-up space". In order to test our approach using realistic design data (in terms of both scale and the nature of the building models) we describe how our system interfaces with IFC, and we conduct timing experiments to determine the practicality of our approach. We discuss general computational approaches for deriving higher-level spatial modalities by focusing on the example of route graphs. Finally, we present a firefighting scenario with alternative route graphs to motivate the application of our framework.

  19. A new spatial multiple discrete-continuous modeling approach to land use change analysis.

    Science.gov (United States)

    2013-09-01

    This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

  20. Spatial generalised linear mixed models based on distances.

    Science.gov (United States)

    Melo, Oscar O; Mateu, Jorge; Melo, Carlos E

    2016-10-01

    Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.

  1. Risk assessment of flood disaster and forewarning model at different spatial-temporal scales

    Science.gov (United States)

    Zhao, Jun; Jin, Juliang; Xu, Jinchao; Guo, Qizhong; Hang, Qingfeng; Chen, Yaqian

    2018-05-01

    Aiming at reducing losses from flood disaster, risk assessment of flood disaster and forewarning model is studied. The model is built upon risk indices in flood disaster system, proceeding from the whole structure and its parts at different spatial-temporal scales. In this study, on the one hand, it mainly establishes the long-term forewarning model for the surface area with three levels of prediction, evaluation, and forewarning. The method of structure-adaptive back-propagation neural network on peak identification is used to simulate indices in prediction sub-model. Set pair analysis is employed to calculate the connection degrees of a single index, comprehensive index, and systematic risk through the multivariate connection number, and the comprehensive assessment is made by assessment matrixes in evaluation sub-model. The comparison judging method is adopted to divide warning degree of flood disaster on risk assessment comprehensive index with forewarning standards in forewarning sub-model and then the long-term local conditions for proposing planning schemes. On the other hand, it mainly sets up the real-time forewarning model for the spot, which introduces the real-time correction technique of Kalman filter based on hydrological model with forewarning index, and then the real-time local conditions for presenting an emergency plan. This study takes Tunxi area, Huangshan City of China, as an example. After risk assessment and forewarning model establishment and application for flood disaster at different spatial-temporal scales between the actual and simulated data from 1989 to 2008, forewarning results show that the development trend for flood disaster risk remains a decline on the whole from 2009 to 2013, despite the rise in 2011. At the macroscopic level, project and non-project measures are advanced, while at the microcosmic level, the time, place, and method are listed. It suggests that the proposed model is feasible with theory and application, thus

  2. Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

    Science.gov (United States)

    Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

    2005-01-01

    This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has

  3. An alternative to the standard spatial econometric approaches in hedonic house price models

    DEFF Research Database (Denmark)

    von Graevenitz, Kathrine; Panduro, Toke Emil

    2015-01-01

    Omitted, misspecified, or mismeasured spatially varying characteristics are a cause for concern in hedonic house price models. Spatial econometrics or spatial fixed effects have become popular ways of addressing these concerns. We discuss the limitations of standard spatial approaches to hedonic...

  4. A Biophysical Neural Model To Describe Spatial Visual Attention

    International Nuclear Information System (INIS)

    Hugues, Etienne; Jose, Jorge V.

    2008-01-01

    Visual scenes have enormous spatial and temporal information that are transduced into neural spike trains. Psychophysical experiments indicate that only a small portion of a spatial image is consciously accessible. Electrophysiological experiments in behaving monkeys have revealed a number of modulations of the neural activity in special visual area known as V4, when the animal is paying attention directly towards a particular stimulus location. The nature of the attentional input to V4, however, remains unknown as well as to the mechanisms responsible for these modulations. We use a biophysical neural network model of V4 to address these issues. We first constrain our model to reproduce the experimental results obtained for different external stimulus configurations and without paying attention. To reproduce the known neuronal response variability, we found that the neurons should receive about equal, or balanced, levels of excitatory and inhibitory inputs and whose levels are high as they are in in vivo conditions. Next we consider attentional inputs that can induce and reproduce the observed spiking modulations. We also elucidate the role played by the neural network to generate these modulations

  5. Establishment of Approximate Analytical Model of Oil Film Force for Finite Length Tilting Pad Journal Bearings

    Directory of Open Access Journals (Sweden)

    Yongliang Wang

    2015-01-01

    Full Text Available Tilting pad bearings offer unique dynamic stability enabling successful deployment of high-speed rotating machinery. The model of dynamic stiffness, damping, and added mass coefficients is often used for rotordynamic analyses, and this method does not suffice to describe the dynamic behaviour due to the nonlinear effects of oil film force under larger shaft vibration or vertical rotor conditions. The objective of this paper is to present a nonlinear oil force model for finite length tilting pad journal bearings. An approximate analytic oil film force model was established by analysing the dynamic characteristic of oil film of a single pad journal bearing using variable separation method under the dynamic π oil film boundary condition. And an oil film force model of a four-tilting-pad journal bearing was established by using the pad assembly technique and considering pad tilting angle. The validity of the model established was proved by analyzing the distribution of oil film pressure and the locus of journal centre for tilting pad journal bearings and by comparing the model established in this paper with the model established using finite difference method.

  6. Spatial and functional modeling of carnivore and insectivore molariform teeth.

    Science.gov (United States)

    Evans, Alistair R; Sanson, Gordon D

    2006-06-01

    The interaction between the two main competing geometric determinants of teeth (the geometry of function and the geometry of occlusion) were investigated through the construction of three-dimensional spatial models of several mammalian tooth forms (carnassial, insectivore premolar, zalambdodont, dilambdodont, and tribosphenic). These models aim to emulate the shape and function of mammalian teeth. The geometric principles of occlusion relating to single- and double-crested teeth are reviewed. Function was considered using engineering principles that relate tooth shape to function. Substantial similarity between the models and mammalian teeth were achieved. Differences between the two indicate the influence of tooth strength, geometric relations between upper and lower teeth (including the presence of the protocone), and wear on tooth morphology. The concept of "autocclusion" is expanded to include any morphological features that ensure proper alignment of cusps on the same tooth and other teeth in the tooth row. It is concluded that the tooth forms examined are auto-aligning, and do not require additional morphological guides for correct alignment. The model of therian molars constructed by Crompton and Sita-Lumsden ([1970] Nature 227:197-199) is reconstructed in 3D space to show that their hypothesis of crest geometry is erroneous, and that their model is a special case of a more general class of models. (c) 2004 Wiley-Liss, Inc.

  7. STATE OF THE ART OF THE LANDSCAPE ARCHITECTURE SPATIAL DATA MODEL FROM A GEOSPATIAL PERSPECTIVE

    Directory of Open Access Journals (Sweden)

    A. Kastuari

    2016-10-01

    Full Text Available Spatial data and information had been used for some time in planning or landscape design. For a long time, architects were using spatial data in the form of topographic map for their designs. This method is not efficient, and it is also not more accurate than using spatial analysis by utilizing GIS. Architects are sometimes also only accentuating the aesthetical aspect for their design, but not taking landscape process into account which could cause the design could be not suitable for its use and its purpose. Nowadays, GIS role in landscape architecture has been formalized by the emergence of Geodesign terminology that starts in Representation Model and ends in Decision Model. The development of GIS could be seen in several fields of science that now have the urgency to use 3 dimensional GIS, such as in: 3D urban planning, flood modeling, or landscape planning. In this fields, 3 dimensional GIS is able to support the steps in modeling, analysis, management, and integration from related data, that describe the human activities and geophysics phenomena in more realistic way. Also, by applying 3D GIS and geodesign in landscape design, geomorphology information can be better presented and assessed. In some research, it is mentioned that the development of 3D GIS is not established yet, either in its 3D data structure, or in its spatial analysis function. This study literature will able to accommodate those problems by providing information on existing development of 3D GIS for landscape architecture, data modeling, the data accuracy, representation of data that is needed by landscape architecture purpose, specifically in the river area.

  8. State of the Art of the Landscape Architecture Spatial Data Model from a Geospatial Perspective

    Science.gov (United States)

    Kastuari, A.; Suwardhi, D.; Hanan, H.; Wikantika, K.

    2016-10-01

    Spatial data and information had been used for some time in planning or landscape design. For a long time, architects were using spatial data in the form of topographic map for their designs. This method is not efficient, and it is also not more accurate than using spatial analysis by utilizing GIS. Architects are sometimes also only accentuating the aesthetical aspect for their design, but not taking landscape process into account which could cause the design could be not suitable for its use and its purpose. Nowadays, GIS role in landscape architecture has been formalized by the emergence of Geodesign terminology that starts in Representation Model and ends in Decision Model. The development of GIS could be seen in several fields of science that now have the urgency to use 3 dimensional GIS, such as in: 3D urban planning, flood modeling, or landscape planning. In this fields, 3 dimensional GIS is able to support the steps in modeling, analysis, management, and integration from related data, that describe the human activities and geophysics phenomena in more realistic way. Also, by applying 3D GIS and geodesign in landscape design, geomorphology information can be better presented and assessed. In some research, it is mentioned that the development of 3D GIS is not established yet, either in its 3D data structure, or in its spatial analysis function. This study literature will able to accommodate those problems by providing information on existing development of 3D GIS for landscape architecture, data modeling, the data accuracy, representation of data that is needed by landscape architecture purpose, specifically in the river area.

  9. Fundamental Frequency and Model Order Estimation Using Spatial Filtering

    DEFF Research Database (Denmark)

    Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll

    2014-01-01

    extend this procedure to account for inharmonicity using unconstrained model order estimation. The simulations show that beamforming improves the performance of the joint estimates of fundamental frequency and the number of harmonics in low signal to interference (SIR) levels, and an experiment......In signal processing applications of harmonic-structured signals, estimates of the fundamental frequency and number of harmonics are often necessary. In real scenarios, a desired signal is contaminated by different levels of noise and interferers, which complicate the estimation of the signal...... parameters. In this paper, we present an estimation procedure for harmonic-structured signals in situations with strong interference using spatial filtering, or beamforming. We jointly estimate the fundamental frequency and the constrained model order through the output of the beamformers. Besides that, we...

  10. Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

    Science.gov (United States)

    Henson, Michael A

    2015-12-01

    Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

  11. Habitat modeling for cetacean management: Spatial distribution in the southern Pelagos Sanctuary (Mediterranean Sea)

    Science.gov (United States)

    Pennino, Maria Grazia; Mérigot, Bastien; Fonseca, Vinícius Prado; Monni, Virginia; Rotta, Andrea

    2017-07-01

    Effective management and conservation of wild populations requires knowledge of their habitats, especially by mean of quantitative analyses of their spatial distributions. The Pelagos Sanctuary is a dedicated marine protected area for Mediterranean marine mammals covering an area of 90,000 km2 in the north-western Mediterranean Sea between Italy, France and the Principate of Monaco. In the south of the Sanctuary, i.e. along the Sardinian coast, a range of diverse human activities (cities, industry, fishery, tourism) exerts several current ad potential threats to cetacean populations. In addition, marine mammals are recognized by the EU Marine Strategy Framework Directive as essential components of sustainable ecosystems. Yet, knowledge on the spatial distribution and ecology of cetaceans in this area is quite scarce. Here we modeled occurrence of the three most abundant species known in the Sanctuary, i.e. the striped dolphin (Stenella coeruleoalba), the bottlenose dolphin (Tursiops truncatus) and the fin whales (Balaenoptera physalus), using sighting data from scientific surveys collected from 2012 to 2014 during summer time. Bayesian site-occupancy models were used to model their spatial distribution in relation to habitat taking into account oceanographic (sea surface temperature, primary production, photosynthetically active radiation, chlorophyll-a concentration) and topographic (depth, slope, distance of the land) variables. Cetaceans responded differently to the habitat features, with higher occurrence predicted in the more productive areas on submarine canyons. These results provide ecological information useful to enhance management plans and establish baseline for future population trend studies.

  12. Spatial Modelling Tools to Integrate Public Health and Environmental Science, Illustrated with Infectious Cryptosporidiosis.

    Science.gov (United States)

    Lal, Aparna

    2016-02-02

    Contemporary spatial modelling tools can help examine how environmental exposures such as climate and land use together with socio-economic factors sustain infectious disease transmission in humans. Spatial methods can account for interactions across global and local scales, geographic clustering and continuity of the exposure surface, key characteristics of many environmental influences. Using cryptosporidiosis as an example, this review illustrates how, in resource rich settings, spatial tools have been used to inform targeted intervention strategies and forecast future disease risk with scenarios of environmental change. When used in conjunction with molecular studies, they have helped determine location-specific infection sources and environmental transmission pathways. There is considerable scope for such methods to be used to identify data/infrastructure gaps and establish a baseline of disease burden in resource-limited settings. Spatial methods can help integrate public health and environmental science by identifying the linkages between the physical and socio-economic environment and health outcomes. Understanding the environmental and social context for disease spread is important for assessing the public health implications of projected environmental change.

  13. Spatial Modelling Tools to Integrate Public Health and Environmental Science, Illustrated with Infectious Cryptosporidiosis

    Directory of Open Access Journals (Sweden)

    Aparna Lal

    2016-02-01

    Full Text Available Contemporary spatial modelling tools can help examine how environmental exposures such as climate and land use together with socio-economic factors sustain infectious disease transmission in humans. Spatial methods can account for interactions across global and local scales, geographic clustering and continuity of the exposure surface, key characteristics of many environmental influences. Using cryptosporidiosis as an example, this review illustrates how, in resource rich settings, spatial tools have been used to inform targeted intervention strategies and forecast future disease risk with scenarios of environmental change. When used in conjunction with molecular studies, they have helped determine location-specific infection sources and environmental transmission pathways. There is considerable scope for such methods to be used to identify data/infrastructure gaps and establish a baseline of disease burden in resource-limited settings. Spatial methods can help integrate public health and environmental science by identifying the linkages between the physical and socio-economic environment and health outcomes. Understanding the environmental and social context for disease spread is important for assessing the public health implications of projected environmental change.

  14. Estimation of spatial uncertainties of tomographic velocity models

    Energy Technology Data Exchange (ETDEWEB)

    Jordan, M.; Du, Z.; Querendez, E. [SINTEF Petroleum Research, Trondheim (Norway)

    2012-12-15

    This research project aims to evaluate the possibility of assessing the spatial uncertainties in tomographic velocity model building in a quantitative way. The project is intended to serve as a test of whether accurate and specific uncertainty estimates (e.g., in meters) can be obtained. The project is based on Monte Carlo-type perturbations of the velocity model as obtained from the tomographic inversion guided by diagonal and off-diagonal elements of the resolution and the covariance matrices. The implementation and testing of this method was based on the SINTEF in-house stereotomography code, using small synthetic 2D data sets. To test the method the calculation and output of the covariance and resolution matrices was implemented, and software to perform the error estimation was created. The work included the creation of 2D synthetic data sets, the implementation and testing of the software to conduct the tests (output of the covariance and resolution matrices which are not implicitly provided by stereotomography), application to synthetic data sets, analysis of the test results, and creating the final report. The results show that this method can be used to estimate the spatial errors in tomographic images quantitatively. The results agree with' the known errors for our synthetic models. However, the method can only be applied to structures in the model, where the change of seismic velocity is larger than the predicted error of the velocity parameter amplitudes. In addition, the analysis is dependent on the tomographic method, e.g., regularization and parameterization. The conducted tests were very successful and we believe that this method could be developed further to be applied to third party tomographic images.

  15. Promoting Model-based Definition to Establish a Complete Product Definition.

    Science.gov (United States)

    Ruemler, Shawn P; Zimmerman, Kyle E; Hartman, Nathan W; Hedberg, Thomas; Feeny, Allison Barnard

    2017-05-01

    The manufacturing industry is evolving and starting to use 3D models as the central knowledge artifact for product data and product definition, or what is known as Model-based Definition (MBD). The Model-based Enterprise (MBE) uses MBD as a way to transition away from using traditional paper-based drawings and documentation. As MBD grows in popularity, it is imperative to understand what information is needed in the transition from drawings to models so that models represent all the relevant information needed for processes to continue efficiently. Finding this information can help define what data is common amongst different models in different stages of the lifecycle, which could help establish a Common Information Model. The Common Information Model is a source that contains common information from domain specific elements amongst different aspects of the lifecycle. To help establish this Common Information Model, information about how models are used in industry within different workflows needs to be understood. To retrieve this information, a survey mechanism was administered to industry professionals from various sectors. Based on the results of the survey a Common Information Model could not be established. However, the results gave great insight that will help in further investigation of the Common Information Model.

  16. Assessing the Global Risk of Establishment of Cydia pomonella (Lepidoptera: Tortricidae) using CLIMEX and MaxEnt Niche Models.

    Science.gov (United States)

    Kumar, Sunil; Neven, Lisa G; Zhu, Hongyu; Zhang, Runzhi

    2015-08-01

    Accurate assessment of insect pest establishment risk is needed by national plant protection organizations to negotiate international trade of horticultural commodities that can potentially carry the pests and result in inadvertent introductions in the importing countries. We used mechanistic and correlative niche models to quantify and map the global patterns of the potential for establishment of codling moth (Cydia pomonella L.), a major pest of apples, peaches, pears, and other pome and stone fruits, and a quarantine pest in countries where it currently does not occur. The mechanistic model CLIMEX was calibrated using species-specific physiological tolerance thresholds, whereas the correlative model MaxEnt used species occurrences and climatic spatial data. Projected potential distribution from both models conformed well to the current known distribution of codling moth. None of the models predicted suitable environmental conditions in countries located between 20°N and 20°S potentially because of shorter photoperiod, and lack of chilling requirement (Japan where codling moth currently does not occur but where its preferred host species (i.e., apple) is present. Average annual temperature and latitude were the main environmental variables associated with codling moth distribution at global level. The predictive models developed in this study present the global risk of establishment of codling moth, and can be used for monitoring potential introductions of codling moth in different countries and by policy makers and trade negotiators in making science-based decisions. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  17. Parameterizing the Spatial Markov Model From Breakthrough Curve Data Alone

    Science.gov (United States)

    Sherman, Thomas; Fakhari, Abbas; Miller, Savannah; Singha, Kamini; Bolster, Diogo

    2017-12-01

    The spatial Markov model (SMM) is an upscaled Lagrangian model that effectively captures anomalous transport across a diverse range of hydrologic systems. The distinct feature of the SMM relative to other random walk models is that successive steps are correlated. To date, with some notable exceptions, the model has primarily been applied to data from high-resolution numerical simulations and correlation effects have been measured from simulated particle trajectories. In real systems such knowledge is practically unattainable and the best one might hope for is breakthrough curves (BTCs) at successive downstream locations. We introduce a novel methodology to quantify velocity correlation from BTC data alone. By discretizing two measured BTCs into a set of arrival times and developing an inverse model, we estimate velocity correlation, thereby enabling parameterization of the SMM in studies where detailed Lagrangian velocity statistics are unavailable. The proposed methodology is applied to two synthetic numerical problems, where we measure all details and thus test the veracity of the approach by comparison of estimated parameters with known simulated values. Our results suggest that our estimated transition probabilities agree with simulated values and using the SMM with this estimated parameterization accurately predicts BTCs downstream. Our methodology naturally allows for estimates of uncertainty by calculating lower and upper bounds of velocity correlation, enabling prediction of a range of BTCs. The measured BTCs fall within the range of predicted BTCs. This novel method to parameterize the SMM from BTC data alone is quite parsimonious, thereby widening the SMM's practical applicability.

  18. The establishment of bilateral external iliac artery stenosis model in experimental canines and its angiographic evaluation

    International Nuclear Information System (INIS)

    Xia Yonghui; Li Weixiao; Bi Yonghua; Xu Ke

    2011-01-01

    Objective: To establish an experimental canine model of bilateral external iliac artery stenosis by surgical method with absorbable suture. Methods: Under general anesthesia bilateral external iliac arteries were partly obstructed (about 50%) with absorbable suture in ten dogs. Three months later angiography was performed to evaluate the arterial stricture degree. Results: Bilateral external iliac artery stenosis model was successfully established in eight dogs and the other two dogs died within two weeks after the procedure. Angiography performed three months after the procedure showed that the stricture degree of arterial lumen was (60.6±12.5)%. Conclusion: Satisfactory experimental canine model of bilateral external iliac artery stenosis can be established by surgical method with absorbable suture. This method can be used for reference when peripheral artery stenosis model is to be prepared in larger animals. (authors)

  19. Learning while (re-)configuring: business model innovation processes in established firms

    NARCIS (Netherlands)

    Berends, J.J.; Smits, A.; Reymen, I.M.M.J.; Podoynitsyna, K.S.

    2016-01-01

    This study addresses the question of how established organizations develop new business models over time, using a process research approach to trace how four business model innovation trajectories unfold. With organizational learning as analytical lens, we discern two process patterns: “drifting”

  20. Spatial Distribution of Hydrologic Ecosystem Service Estimates: Comparing Two Models

    Science.gov (United States)

    Dennedy-Frank, P. J.; Ghile, Y.; Gorelick, S.; Logsdon, R. A.; Chaubey, I.; Ziv, G.

    2014-12-01

    We compare estimates of the spatial distribution of water quantity provided (annual water yield) from two ecohydrologic models: the widely-used Soil and Water Assessment Tool (SWAT) and the much simpler water models from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) toolbox. These two models differ significantly in terms of complexity, timescale of operation, effort, and data required for calibration, and so are often used in different management contexts. We compare two study sites in the US: the Wildcat Creek Watershed (2083 km2) in Indiana, a largely agricultural watershed in a cold aseasonal climate, and the Upper Upatoi Creek Watershed (876 km2) in Georgia, a mostly forested watershed in a temperate aseasonal climate. We evaluate (1) quantitative estimates of water yield to explore how well each model represents this process, and (2) ranked estimates of water yield to indicate how useful the models are for management purposes where other social and financial factors may play significant roles. The SWAT and InVEST models provide very similar estimates of the water yield of individual subbasins in the Wildcat Creek Watershed (Pearson r = 0.92, slope = 0.89), and a similar ranking of the relative water yield of those subbasins (Spearman r = 0.86). However, the two models provide relatively different estimates of the water yield of individual subbasins in the Upper Upatoi Watershed (Pearson r = 0.25, slope = 0.14), and very different ranking of the relative water yield of those subbasins (Spearman r = -0.10). The Upper Upatoi watershed has a significant baseflow contribution due to its sandy, well-drained soils. InVEST's simple seasonality terms, which assume no change in storage over the time of the model run, may not accurately estimate water yield processes when baseflow provides such a strong contribution. Our results suggest that InVEST users take care in situations where storage changes are significant.

  1. Is a matrix exponential specification suitable for the modeling of spatial correlation structures?

    Science.gov (United States)

    Strauß, Magdalena E; Mezzetti, Maura; Leorato, Samantha

    2017-05-01

    This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms.

  2. Spatial Modeling of Risk in Natural Resource Management

    Directory of Open Access Journals (Sweden)

    Peter Jones

    2002-01-01

    Full Text Available Making decisions in natural resource management involves an understanding of the risk and uncertainty of the outcomes, such as crop failure or cattle starvation, and of the normal spread of the expected production. Hedging against poor outcomes often means lack of investment and slow adoption of new methods. At the household level, production instability can have serious effects on income and food security. At the national level, it can have social and economic impacts that may affect all sectors of society. Crop models such as CERES-Maize are excellent tools for assessing weather-related production variability. WATBAL is a water balance model that can provide robust estimates of the potential growing days for a pasture. These models require large quantities of daily weather data that are rarely available. MarkSim is an application for generating synthetic daily weather files by estimating the third-order Markov model parameters from interpolated climate surfaces. The models can then be run for each distinct point on the map. This paper examines the growth of maize and pasture in dryland agriculture in southern Africa. Weather simulators produce independent estimates for each point on the map; however, we know that a spatial coherence of weather exists. We investigated a method of incorporating spatial coherence into MarkSim and show that it increases the variance of production. This means that all of the farmers in a coherent area share poor yields, with important consequences for food security, markets, transport, and shared grazing lands. The long-term aspects of risk are associated with global climate change. We used the results of a Global Circulation Model to extrapolate to the year 2055. We found that low maize yields would become more likely in the marginal areas, whereas they may actually increase in some areas. The same trend was found with pasture growth. We outline areas where further work is required before these tools and methods

  3. Establishing experimental model of human internal carotid artery siphon segment in canine common carotid artery

    International Nuclear Information System (INIS)

    Cui Xuee; Li Minghua; Wang Yongli; Cheng Yingsheng; Li Wenbin

    2005-01-01

    Objective: To study the feasibility of establishing experimental model of human internal carotid artery siphon segment in canine common carotid artery (CCA) by end-to-end anastomoses of one side common carotid artery segment with the other side common carotid artery. Methods: Surgical techniques were used to make siphon model in 8 canines. One side CCA was taken as the parent artery and anastomosing with the cut off contra-lateral CCA segment which has passed through within the S-shaped glass tube. Two weeks after the creation of models angiography showed the model siphons were patent. Results: Experimental models of human internal carotid artery siphon segment were successfully made in all 8 dogs. Conclusions: It is practically feasible to establish experimental canine common carotid artery models of siphon segment simulating human internal carotid artery. (authors)

  4. Evaluating water erosion prediction project model using Cesium-137-derived spatial soil redistribution data

    Science.gov (United States)

    The lack of spatial soil erosion data has been a major constraint on the refinement and application of physically based erosion models. Spatially distributed models can only be thoroughly validated with distributed erosion data. The fallout cesium-137 has been widely used to generate spatial soil re...

  5. Using the gravity model to estimate the spatial spread of vector-borne diseases

    NARCIS (Netherlands)

    Barrios, J.M.; Verstraeten, W.W.; Maes, P.; Aerts, J.; Farifteh, J.; Coppin, P.

    2012-01-01

    The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the

  6. Lessons learned for spatial modelling of ecosystem services in support of ecosystem accounting

    NARCIS (Netherlands)

    Schroter, M.; Remme, R.P.; Sumarga, E.; Barton, D.N.; Hein, L.G.

    2015-01-01

    Assessment of ecosystem services through spatial modelling plays a key role in ecosystem accounting. Spatial models for ecosystem services try to capture spatial heterogeneity with high accuracy. This endeavour, however, faces several practical constraints. In this article we analyse the trade-offs

  7. Unemployment estimation: Spatial point referenced methods and models

    KAUST Repository

    Pereira, Soraia

    2017-06-26

    Portuguese Labor force survey, from 4th quarter of 2014 onwards, started geo-referencing the sampling units, namely the dwellings in which the surveys are carried. This opens new possibilities in analysing and estimating unemployment and its spatial distribution across any region. The labor force survey choose, according to an preestablished sampling criteria, a certain number of dwellings across the nation and survey the number of unemployed in these dwellings. Based on this survey, the National Statistical Institute of Portugal presently uses direct estimation methods to estimate the national unemployment figures. Recently, there has been increased interest in estimating these figures in smaller areas. Direct estimation methods, due to reduced sampling sizes in small areas, tend to produce fairly large sampling variations therefore model based methods, which tend to

  8. Spatial Fleming-Viot models with selection and mutation

    CERN Document Server

    Dawson, Donald A

    2014-01-01

    This book constructs a rigorous framework for analysing selected phenomena in evolutionary theory of populations arising due to the combined effects of migration, selection and mutation in a spatial stochastic population model, namely the evolution towards fitter and fitter types through punctuated equilibria. The discussion is based on a number of new methods, in particular multiple scale analysis, nonlinear Markov processes and their entrance laws, atomic measure-valued evolutions and new forms of duality (for state-dependent mutation and multitype selection) which are used to prove ergodic theorems in this context and are applicable for many other questions and renormalization analysis for a variety of phenomena (stasis, punctuated equilibrium, failure of naive branching approximations, biodiversity) which occur due to the combination of rare mutation, mutation, resampling, migration and selection and make it necessary to mathematically bridge the gap (in the limit) between time and space scales.

  9. Spatial Modeling for Resources Framework (SMRF): A modular framework for developing spatial forcing data for snow modeling in mountain basins

    Science.gov (United States)

    Havens, Scott; Marks, Danny; Kormos, Patrick; Hedrick, Andrew

    2017-12-01

    In the Western US and many mountainous regions of the world, critical water resources and climate conditions are difficult to monitor because the observation network is generally very sparse. The critical resource from the mountain snowpack is water flowing into streams and reservoirs that will provide for irrigation, flood control, power generation, and ecosystem services. Water supply forecasting in a rapidly changing climate has become increasingly difficult because of non-stationary conditions. In response, operational water supply managers have begun to move from statistical techniques towards the use of physically based models. As we begin to transition physically based models from research to operational use, we must address the most difficult and time-consuming aspect of model initiation: the need for robust methods to develop and distribute the input forcing data. In this paper, we present a new open source framework, the Spatial Modeling for Resources Framework (SMRF), which automates and simplifies the common forcing data distribution methods. It is computationally efficient and can be implemented for both research and operational applications. We present an example of how SMRF is able to generate all of the forcing data required to a run physically based snow model at 50-100 m resolution over regions of 1000-7000 km2. The approach has been successfully applied in real time and historical applications for both the Boise River Basin in Idaho, USA and the Tuolumne River Basin in California, USA. These applications use meteorological station measurements and numerical weather prediction model outputs as input. SMRF has significantly streamlined the modeling workflow, decreased model set up time from weeks to days, and made near real-time application of a physically based snow model possible.

  10. Spatial measurement error and correction by spatial SIMEX in linear regression models when using predicted air pollution exposures.

    Science.gov (United States)

    Alexeeff, Stacey E; Carroll, Raymond J; Coull, Brent

    2016-04-01

    Spatial modeling of air pollution exposures is widespread in air pollution epidemiology research as a way to improve exposure assessment. However, there are key sources of exposure model uncertainty when air pollution is modeled, including estimation error and model misspecification. We examine the use of predicted air pollution levels in linear health effect models under a measurement error framework. For the prediction of air pollution exposures, we consider a universal Kriging framework, which may include land-use regression terms in the mean function and a spatial covariance structure for the residuals. We derive the bias induced by estimation error and by model misspecification in the exposure model, and we find that a misspecified exposure model can induce asymptotic bias in the effect estimate of air pollution on health. We propose a new spatial simulation extrapolation (SIMEX) procedure, and we demonstrate that the procedure has good performance in correcting this asymptotic bias. We illustrate spatial SIMEX in a study of air pollution and birthweight in Massachusetts. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  11. Spatial Welfare Economics versus Ecological Footprint: Modeling Agglomeration, Externalities and Trade

    NARCIS (Netherlands)

    Grazi, F.; van den Bergh, J.C.J.M.; Rietveld, P.

    2007-01-01

    A welfare framework for the analysis of the spatial dimensions of sustainability is developed. It covers agglomeration effects, interregional trade, negative environmental externalities, and various land use categories. The model is used to compare rankings of spatial configurations according to

  12. An alternative to the standard spatial econometric approaches in hedonic house price models

    DEFF Research Database (Denmark)

    Veie, Kathrine Lausted; Panduro, Toke Emil

    Hedonic models are subject to spatially correlated errors which are a symptom of omitted spatial variables, mis-specification or mismeasurement. Methods have been developed to address this problem through the use of spatial econometrics or spatial fixed effects. However, often spatial correlation is...... varying characteristics markedly. This suggests that omitted variable bias may remain an important problem. We advocate for an increased use of sensitivity analysis to determine robustness of estimates to different models of the (omitted) spatial processes....

  13. SPATIAL MOTION OF THE MAGELLANIC CLOUDS: TIDAL MODELS RULED OUT?

    International Nuclear Information System (INIS)

    Ruzicka, Adam; Palous, Jan; Theis, Christian

    2009-01-01

    Recently, Kallivayalil et al. derived new values of the proper motion for the Large and Small Magellanic Clouds (LMC and SMC, respectively). The spatial velocities of both Clouds are unexpectedly higher than their previous values resulting from agreement between the available theoretical models of the Magellanic System and the observations of neutral hydrogen (H I) associated with the LMC and the SMC. Such proper motion estimates are likely to be at odds with the scenarios for creation of the large-scale structures in the Magellanic System suggested so far. We investigated this hypothesis for the pure tidal models, as they were the first ones devised to explain the evolution of the Magellanic System, and the tidal stripping is intrinsically involved in every model assuming the gravitational interaction. The parameter space for the Milky Way (MW)-LMC-SMC interaction was analyzed by a robust search algorithm (genetic algorithm) combined with a fast, restricted N-body model of the interaction. Our method extended the known variety of evolutionary scenarios satisfying the observed kinematics and morphology of the Magellanic large-scale structures. Nevertheless, assuming the tidal interaction, no satisfactory reproduction of the H I data available for the Magellanic Clouds was achieved with the new proper motions. We conclude that for the proper motion data by Kallivayalil et al., within their 1σ errors, the dynamical evolution of the Magellanic System with the currently accepted total mass of the MW cannot be explained in the framework of pure tidal models. The optimal value for the western component of the LMC proper motion was found to be μ W lmc ∼> -1.3 mas yr -1 in case of tidal models. It corresponds to the reduction of the Kallivayalil et al. value for μ W lmc by ∼ 40% in its magnitude.

  14. The backbone of a City Information Model (CIM) : Implementing a spatial data model for urban design

    NARCIS (Netherlands)

    Gil, J.A.; Almeida, J.; Duarte, J.P.

    2011-01-01

    We have been witnessing an increased interest in a more holistic approach to urban design practice and education. In this paper we present a spatial data model for urban design that proposes the combination of urban environment feature classes with design process feature classes. This data model is

  15. Image-based quantification and mathematical modeling of spatial heterogeneity in ESC colonies.

    Science.gov (United States)

    Herberg, Maria; Zerjatke, Thomas; de Back, Walter; Glauche, Ingmar; Roeder, Ingo

    2015-06-01

    Pluripotent embryonic stem cells (ESCs) have the potential to differentiate into cells of all three germ layers. This unique property has been extensively studied on the intracellular, transcriptional level. However, ESCs typically form clusters of cells with distinct size and shape, and establish spatial structures that are vital for the maintenance of pluripotency. Even though it is recognized that the cells' arrangement and local interactions play a role in fate decision processes, the relations between transcriptional and spatial patterns have not yet been studied. We present a systems biology approach which combines live-cell imaging, quantitative image analysis, and multiscale, mathematical modeling of ESC growth. In particular, we develop quantitative measures of the morphology and of the spatial clustering of ESCs with different expression levels and apply them to images of both in vitro and in silico cultures. Using the same measures, we are able to compare model scenarios with different assumptions on cell-cell adhesions and intercellular feedback mechanisms directly with experimental data. Applying our methodology to microscopy images of cultured ESCs, we demonstrate that the emerging colonies are highly variable regarding both morphological and spatial fluorescence patterns. Moreover, we can show that most ESC colonies contain only one cluster of cells with high self-renewing capacity. These cells are preferentially located in the interior of a colony structure. The integrated approach combining image analysis with mathematical modeling allows us to reveal potential transcription factor related cellular and intercellular mechanisms behind the emergence of observed patterns that cannot be derived from images directly. © 2015 International Society for Advancement of Cytometry.

  16. Establishment of a rat model of early-stage liver failure and Th17/Treg imbalance

    OpenAIRE

    LI Dong; LU Zhonghua; GAN Jianhe

    2016-01-01

    ObjectiveTo investigate the methods for establishing a rat model of early-stage liver failure and the changes in Th17, Treg, and Th17/Treg after dexamethasone and thymosin interventions. MethodsA total of 64 rats were randomly divided into carbon tetrachloride (CCl4) group and endotoxin [lipopolysaccharide (LPS)]/D-galactosamine (D-GalN) combination group to establish the rat model of early-stage liver failure. The activities of the rats and changes in liver function and whole blood Th17 and ...

  17. Pattern formation through spatial interactions in a modified Daisyworld model

    Science.gov (United States)

    Alberti, Tommaso; Primavera, Leonardo; Lepreti, Fabio; Vecchio, Antonio; Carbone, Vincenzo

    2015-04-01

    The Daisyworld model is based on a hypothetical planet, like the Earth, which receives the radiant energy coming from a Sun-like star, and populated by two kinds of identical plants differing by their colour: white daisies reflecting light and black daisies absorbing light. The interactions and feedbacks between the collective biota of the planet and the incoming radiation form a self-regulating system where the conditions for life are maintained. We investigate a modified version of the Daisyworld model where a spatial dependency on latitude is introduced, and both a variable heat diffusivity along latitude and a simple greenhouse model are included. We show that the spatial interactions between the variables of the system can generate some equilibrium patterns which can locally stabilize the coexistence of the two vegetation types. The feedback on albedo is able to generate new equilibrium solutions which can efficiently self-regulate the planet climate, even for values of the solar luminosity relatively far from the current Earth conditions. The extension to spatial Daisyworld gives room to the possibility of inhomogeneous solar forcing in a curved planet, with explicit differences between poles and equator and the direct use of the heat diffusion equation. As a first approach, to describe a spherical planet, we consider the temperature T(θ,t) and the surface coverage as depending only on time and on latitude θ (-90° ≤ θ ≤ 90°). A second step is the introduction of the greenhouse effect in the model, the process by which outgoing infrared radiation is partly screened by greenhouse gases. This effect can be described by relaxing the black-body radiation hypothesis and by introducing a grayness function g(T) in the heat equation. As a third step, we consider a latitude dependence of the Earth's conductivity, χ = χ(θ). Considering these terms, using spherical coordinates and symmetry with respect to θ, the modified Daisyworld equations reduce to the

  18. Remote sensing, geographical information systems, and spatial modeling for analyzing public transit services

    Science.gov (United States)

    Wu, Changshan

    route maximal covering/shortest path (MRMCSP) model is proposed to address the tradeoff between public transit service quality and access coverage in an established bus-based transit system. Results show that it is possible to improve current transit service quality by eliminating redundant or underutilized service stops. This research illustrates that fine resolution data can be efficiently generated to support urban planning, management and analysis. Further, this detailed data may necessitate the development of new spatial optimization models for use in analysis.

  19. Extending Primitive Spatial Data Models to Include Semantics

    Science.gov (United States)

    Reitsma, F.; Batcheller, J.

    2009-04-01

    Our traditional geospatial data model involves associating some measurable quality, such as temperature, or observable feature, such as a tree, with a point or region in space and time. When capturing data we implicitly subscribe to some kind of conceptualisation. If we can make this explicit in an ontology and associate it with the captured data, we can leverage formal semantics to reason with the concepts represented in our spatial data sets. To do so, we extend our fundamental representation of geospatial data in a data model by including a URI in our basic data model that links it to our ontology defining our conceptualisation, We thus extend Goodchild et al's geo-atom [1] with the addition of a URI: (x, Z, z(x), URI) . This provides us with pixel or feature level knowledge and the ability to create layers of data from a set of pixels or features that might be drawn from a database based on their semantics. Using open source tools, we present a prototype that involves simple reasoning as a proof of concept. References [1] M.F. Goodchild, M. Yuan, and T.J. Cova. Towards a general theory of geographic representation in gis. International Journal of Geographical Information Science, 21(3):239-260, 2007.

  20. Establishing an Improved Kane Dynamic Model for the 7-DOF Reconfigurable Modular Robot

    Directory of Open Access Journals (Sweden)

    Xiao Li

    2017-01-01

    Full Text Available We propose an improved Kane dynamic model theory for the 7-DOF modular robot in this paper, and the model precision is improved by the improved function T′it. We designed three types of progressive modular joints for reconfigurable modular robot that can be used in industrial robot, space robot, and special robot. The Kane dynamic model and the solid dynamic model are established, respectively, for the 7-DOF modular robot. After that, the experimental results are obtained from the simulation experiment of typical task in the established dynamic models. By the analysis model of error, the equation of the improved torque T′it is derived and proposed. And the improved Kane dynamic model is established for the modular robot that used T′it. Based on the experimental data, the undetermined coefficient matrix is five-order linear that was proved in 7-DOF modular robot. And the explicit formulation is solved of the Kane dynamic model and can be used in control system.

  1. Spatial and Temporal Self-Calibration of a Hydroeconomic Model

    Science.gov (United States)

    Howitt, R. E.; Hansen, K. M.

    2008-12-01

    across key nodes on the network and to annual carryover storage at ground and surface water storage facilities. To our knowledge, this is the first hydroeconomic model to perform spatial and temporal calibration simultaneously. The base for the LFN model is CALVIN, a hydroeconomic optimization model of the California water system developed at the University of California, Davis (Draper, et al. 2003). The LFN model, programmed in GAMS, is nonlinear, which permits incorporation of dynamic groundwater pumping costs that reflect head elevation. Hydropower production, also nonlinear in storage levels, could be added in the future. In this paper, we describe model implementation and performance over a sequence of water years drawn from the historical hydrologic record in California. Preliminary findings indicate that calibration occurs within acceptable limits and simulations replicate base case results well. Cai, X., and Wang, D. 2006. "Calibrating Holistic Water Resources-Economic Models." Journal of Water Resources Planning and Management November-December. Draper, A.J., M.W. Jenkins, K.W. Kirby, J.R. Lund, and R.E. Howitt. 2003. "Economic-Engineering Optimization for California Water Management." Journal of Water Resources Planning and Management 129(3):155-164. Howitt, R.E. 1995. "Positive Mathematical Programming." American Journal of Agricultural Economics 77:329-342. Howitt, R.E. 1998. "Self-Calibrating Network Flow Models." Working Paper, Department of Agricultural and Resource Economics, University of California, Davis. October 1998. class="ab'>

  2. Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

    KAUST Repository

    Sang, Huiyan; Jun, Mikyoung; Huang, Jianhua Z.

    2011-01-01

    This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models

  3. Spatial occupancy models applied to atlas data show Southern Ground Hornbills strongly depend on protected areas.

    Science.gov (United States)

    Broms, Kristin M; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L

    2014-03-01

    Determining the range of a species and exploring species--habitat associations are central questions in ecology and can be answered by analyzing presence--absence data. Often, both the sampling of sites and the desired area of inference involve neighboring sites; thus, positive spatial autocorrelation between these sites is expected. Using survey data for the Southern Ground Hornbill (Bucorvus leadbeateri) from the Southern African Bird Atlas Project, we compared advantages and disadvantages of three increasingly complex models for species occupancy: an occupancy model that accounted for nondetection but assumed all sites were independent, and two spatial occupancy models that accounted for both nondetection and spatial autocorrelation. We modeled the spatial autocorrelation with an intrinsic conditional autoregressive (ICAR) model and with a restricted spatial regression (RSR) model. Both spatial models can readily be applied to any other gridded, presence--absence data set using a newly introduced R package. The RSR model provided the best inference and was able to capture small-scale variation that the other models did not. It showed that ground hornbills are strongly dependent on protected areas in the north of their South African range, but less so further south. The ICAR models did not capture any spatial autocorrelation in the data, and they took an order, of magnitude longer than the RSR models to run. Thus, the RSR occupancy model appears to be an attractive choice for modeling occurrences at large spatial domains, while accounting for imperfect detection and spatial autocorrelation.

  4. Accounting for spatial effects in land use regression for urban air pollution modeling.

    Science.gov (United States)

    Bertazzon, Stefania; Johnson, Markey; Eccles, Kristin; Kaplan, Gilaad G

    2015-01-01

    In order to accurately assess air pollution risks, health studies require spatially resolved pollution concentrations. Land-use regression (LUR) models estimate ambient concentrations at a fine spatial scale. However, spatial effects such as spatial non-stationarity and spatial autocorrelation can reduce the accuracy of LUR estimates by increasing regression errors and uncertainty; and statistical methods for resolving these effects--e.g., spatially autoregressive (SAR) and geographically weighted regression (GWR) models--may be difficult to apply simultaneously. We used an alternate approach to address spatial non-stationarity and spatial autocorrelation in LUR models for nitrogen dioxide. Traditional models were re-specified to include a variable capturing wind speed and direction, and re-fit as GWR models. Mean R(2) values for the resulting GWR-wind models (summer: 0.86, winter: 0.73) showed a 10-20% improvement over traditional LUR models. GWR-wind models effectively addressed both spatial effects and produced meaningful predictive models. These results suggest a useful method for improving spatially explicit models. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  5. Variability of effects of spatial climate data aggregation on regional yield simulation by crop models

    NARCIS (Netherlands)

    Hoffmann, H.; Zhao, G.; Bussel, van L.G.J.

    2015-01-01

    Field-scale crop models are often applied at spatial resolutions coarser than that of the arable field. However, little is known about the response of the models to spatially aggregated climate input data and why these responses can differ across models. Depending on the model, regional yield

  6. Multiresolution Network Temporal and Spatial Scheduling Model of Scenic Spot

    Directory of Open Access Journals (Sweden)

    Peng Ge

    2013-01-01

    Full Text Available Tourism is one of pillar industries of the world economy. Low-carbon tourism will be the mainstream direction of the scenic spots' development, and the ω path of low-carbon tourism development is to develop economy and protect environment simultaneously. However, as the tourists' quantity is increasing, the loads of scenic spots are out of control. And the instantaneous overload in some spots caused the image phenomenon of full capacity of the whole scenic spot. Therefore, realizing the real-time schedule becomes the primary purpose of scenic spot’s management. This paper divides the tourism distribution system into several logically related subsystems and constructs a temporal and spatial multiresolution network scheduling model according to the regularity of scenic spots’ overload phenomenon in time and space. It also defines dynamic distribution probability and equivalent dynamic demand to realize the real-time prediction. We define gravitational function between fields and takes it as the utility of schedule, after resolving the transportation model of each resolution, it achieves hierarchical balance between demand and capacity of the system. The last part of the paper analyzes the time complexity of constructing a multiresolution distribution system.

  7. Towards the establishment of nonlinear hidden symmetries of the Skyrme model

    International Nuclear Information System (INIS)

    Herrera-Aguilar, A.; Kanakoglou, K.; Paschalis, J. E.

    2006-01-01

    We present a preliminary attempt to establish the existence of hidden nonlinear symmetries of the SU(N) Skyrme model which could, in principle, lead to the further integration of the system. An explicit illustration is given for the SU(2) symmetry group

  8. Economical analyses of build-operate-transfer model in establishing alternative power plants

    Energy Technology Data Exchange (ETDEWEB)

    Yumurtaci, Zehra [Yildiz Technical University, Department of Mechanical Engineering, Y.T.U. Mak. Fak. Mak. Muh. Bolumu, Besiktas, 34349 Istanbul (Turkey)]. E-mail: zyumur@yildiz.edu.tr; Erdem, Hasan Hueseyin [Yildiz Technical University, Department of Mechanical Engineering, Y.T.U. Mak. Fak. Mak. Muh. Bolumu, Besiktas, 34349 Istanbul (Turkey)

    2007-01-15

    The most widely employed method to meet the increasing electricity demand is building new power plants. The most important issue in building new power plants is to find financial funds. Various models are employed, especially in developing countries, in order to overcome this problem and to find a financial source. One of these models is the build-operate-transfer (BOT) model. In this model, the investor raises all the funds for mandatory expenses and provides financing, builds the plant and, after a certain plant operation period, transfers the plant to the national power organization. In this model, the object is to decrease the burden of power plants on the state budget. The most important issue in the BOT model is the dependence of the unit electricity cost on the transfer period. In this study, the model giving the unit electricity cost depending on the transfer of the plants established according to the BOT model, has been discussed. Unit electricity investment cost and unit electricity cost in relation to transfer period for plant types have been determined. Furthermore, unit electricity cost change depending on load factor, which is one of the parameters affecting annual electricity production, has been determined, and the results have been analyzed. This method can be employed for comparing the production costs of different plants that are planned to be established according to the BOT model, or it can be employed to determine the appropriateness of the BOT model.

  9. Economical analyses of build-operate-transfer model in establishing alternative power plants

    International Nuclear Information System (INIS)

    Yumurtaci, Zehra; Erdem, Hasan Hueseyin

    2007-01-01

    The most widely employed method to meet the increasing electricity demand is building new power plants. The most important issue in building new power plants is to find financial funds. Various models are employed, especially in developing countries, in order to overcome this problem and to find a financial source. One of these models is the build-operate-transfer (BOT) model. In this model, the investor raises all the funds for mandatory expenses and provides financing, builds the plant and, after a certain plant operation period, transfers the plant to the national power organization. In this model, the object is to decrease the burden of power plants on the state budget. The most important issue in the BOT model is the dependence of the unit electricity cost on the transfer period. In this study, the model giving the unit electricity cost depending on the transfer of the plants established according to the BOT model, has been discussed. Unit electricity investment cost and unit electricity cost in relation to transfer period for plant types have been determined. Furthermore, unit electricity cost change depending on load factor, which is one of the parameters affecting annual electricity production, has been determined, and the results have been analyzed. This method can be employed for comparing the production costs of different plants that are planned to be established according to the BOT model, or it can be employed to determine the appropriateness of the BOT model

  10. Modelling 3D spatial objects in a geo-DBMS using a 3D primitive

    Science.gov (United States)

    Arens, Călin; Stoter, Jantien; van Oosterom, Peter

    2005-03-01

    There is a growing interest in modelling the world in three dimensions, both in applications and in science. At the same time, geographical information systems are changing into integrated architecture in which administrative and spatial data are maintained in one environment. It is for this reason that mainstream Data Base Management Systems (DBMSs) have implemented spatial data types according to the 'Simple Feature Specifications for SQL', described by the OpenGeospatial Consortium. However, these specifications are 2D, as indeed are the implementations in DBMSs. At the Section GIS Technology of TU Delft, research has been carried out in which a 3D primitive was implemented in a DBMS (Oracle Spatial). To explore the possibilities and complications, a fairly simple 3D primitive was chosen to start with: a polyhedron. In the future the study will be extended with more complex primitives, the ultimate aim being to build 3D models with features closer to the real world. Besides the data structure, a validation function was developed to check the geometric accuracy of the data. Rules for validation were established and translated into prototype implementations with the aid of literature. In order to manipulate the data, a list of useful 3D functions was specified. Most of these were translated into algorithms, which were implemented in the DBMS. The algorithms for these functions were obtained from the relevant literature. The research also comprised a comparative performance test on spatial indexing in 2D and 3D, using an R-tree. Finally, existing software was used to visualize 3D objects structured with the implemented 3D primitive. This research is a first attempt to implement a true 3D primitive in a DBMS. Future research will focus on extending and improving the implementations and on optimizing maintenance and query of 3D objects in DBMSs.

  11. Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain

    Science.gov (United States)

    Turner, D.P.; Dodson, R.; Marks, D.

    1996-01-01

    Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the

  12. New BRDF Model for Desert and Gobi Using Equivalent Mirror Plane Method, Establishment and Validation

    Science.gov (United States)

    Li, Y.; Rong, Z.

    2017-12-01

    The surface Bidirectional Reflectance Distribution Function (BRDF) is a key parameter that affects the vicarious calibration accuracy of visible channel remote sensing instrument. In the past 30 years, many studies have been made and a variety of models have been established. Among them, the Ross-li model was highly approved and widely used. Unfortunately, the model doesn't suitable for desert and Gobi quite well because of the scattering kernel it contained, needs the factors such as plant height and plant spacing. A new BRDF model for surface without vegetation, which is mainly used in remote sensing vicarious calibration, is established. That was called Equivalent Mirror Plane (EMP) BRDF. It is used to characterize the bidirectional reflectance of the near Lambertian surface. The accuracy of the EMP BRDF model is validated by the directional reflectance data measured on the Dunhuang Gobi and compared to the Ross-li model. Results show that the regression accuracy of the new model is 0.828, which is similar to the Ross-li model (0.825). Because of the simple form (contains only four polynomials) and simple principle (derived by the Fresnel reflection principle, don't include any vegetation parameters), it is more suitable for near Lambertian surface, such as Gobi, desert, Lunar and reference panel. Results also showed that the new model could also maintain a high accuracy and stability in sparse observation, which is very important for the retrieval requirements of daily updating BRDF remote sensing products.

  13. Spatial Preference Modelling for equitable infrastructure provision: an application of Sen's Capability Approach

    Science.gov (United States)

    Wismadi, Arif; Zuidgeest, Mark; Brussel, Mark; van Maarseveen, Martin

    2014-01-01

    To determine whether the inclusion of spatial neighbourhood comparison factors in Preference Modelling allows spatial decision support systems (SDSSs) to better address spatial equity, we introduce Spatial Preference Modelling (SPM). To evaluate the effectiveness of this model in addressing equity, various standardisation functions in both Non-Spatial Preference Modelling and SPM are compared. The evaluation involves applying the model to a resource location-allocation problem for transport infrastructure in the Special Province of Yogyakarta in Indonesia. We apply Amartya Sen's Capability Approach to define opportunity to mobility as a non-income indicator. Using the extended Moran's I interpretation for spatial equity, we evaluate the distribution output regarding, first, `the spatial distribution patterns of priority targeting for allocation' (SPT) and, second, `the effect of new distribution patterns after location-allocation' (ELA). The Moran's I index of the initial map and its comparison with six patterns for SPT as well as ELA consistently indicates that the SPM is more effective for addressing spatial equity. We conclude that the inclusion of spatial neighbourhood comparison factors in Preference Modelling improves the capability of SDSS to address spatial equity. This study thus proposes a new formal method for SDSS with specific attention on resource location-allocation to address spatial equity.

  14. A spatially-averaged mathematical model of kidney branching morphogenesis

    KAUST Repository

    Zubkov, V.S.

    2015-08-01

    © 2015 Published by Elsevier Ltd. Kidney development is initiated by the outgrowth of an epithelial ureteric bud into a population of mesenchymal cells. Reciprocal morphogenetic responses between these two populations generate a highly branched epithelial ureteric tree with the mesenchyme differentiating into nephrons, the functional units of the kidney. While we understand some of the mechanisms involved, current knowledge fails to explain the variability of organ sizes and nephron endowment in mice and humans. Here we present a spatially-averaged mathematical model of kidney morphogenesis in which the growth of the two key populations is described by a system of time-dependant ordinary differential equations. We assume that branching is symmetric and is invoked when the number of epithelial cells per tip reaches a threshold value. This process continues until the number of mesenchymal cells falls below a critical value that triggers cessation of branching. The mathematical model and its predictions are validated against experimentally quantified C57Bl6 mouse embryonic kidneys. Numerical simulations are performed to determine how the final number of branches changes as key system parameters are varied (such as the growth rate of tip cells, mesenchyme cells, or component cell population exit rate). Our results predict that the developing kidney responds differently to loss of cap and tip cells. They also indicate that the final number of kidney branches is less sensitive to changes in the growth rate of the ureteric tip cells than to changes in the growth rate of the mesenchymal cells. By inference, increasing the growth rate of mesenchymal cells should maximise branch number. Our model also provides a framework for predicting the branching outcome when ureteric tip or mesenchyme cells change behaviour in response to different genetic or environmental developmental stresses.

  15. A spatially-averaged mathematical model of kidney branching morphogenesis

    KAUST Repository

    Zubkov, V.S.; Combes, A.N.; Short, K.M.; Lefevre, J.; Hamilton, N.A.; Smyth, I.M.; Little, M.H.; Byrne, H.M.

    2015-01-01

    © 2015 Published by Elsevier Ltd. Kidney development is initiated by the outgrowth of an epithelial ureteric bud into a population of mesenchymal cells. Reciprocal morphogenetic responses between these two populations generate a highly branched epithelial ureteric tree with the mesenchyme differentiating into nephrons, the functional units of the kidney. While we understand some of the mechanisms involved, current knowledge fails to explain the variability of organ sizes and nephron endowment in mice and humans. Here we present a spatially-averaged mathematical model of kidney morphogenesis in which the growth of the two key populations is described by a system of time-dependant ordinary differential equations. We assume that branching is symmetric and is invoked when the number of epithelial cells per tip reaches a threshold value. This process continues until the number of mesenchymal cells falls below a critical value that triggers cessation of branching. The mathematical model and its predictions are validated against experimentally quantified C57Bl6 mouse embryonic kidneys. Numerical simulations are performed to determine how the final number of branches changes as key system parameters are varied (such as the growth rate of tip cells, mesenchyme cells, or component cell population exit rate). Our results predict that the developing kidney responds differently to loss of cap and tip cells. They also indicate that the final number of kidney branches is less sensitive to changes in the growth rate of the ureteric tip cells than to changes in the growth rate of the mesenchymal cells. By inference, increasing the growth rate of mesenchymal cells should maximise branch number. Our model also provides a framework for predicting the branching outcome when ureteric tip or mesenchyme cells change behaviour in response to different genetic or environmental developmental stresses.

  16. Characterization of the spatial and temporal dynamics of the dengue vector population established in urban areas of Fernando de Noronha, a Brazilian oceanic island.

    Science.gov (United States)

    Regis, Lêda N; Acioli, Ridelane Veiga; Silveira, José Constantino; de Melo-Santos, Maria Alice Varjal; da Cunha, Mércia Cristiane Santana; Souza, Fátima; Batista, Carlos Alberto Vieira; Barbosa, Rosângela Maria Rodrigues; de Oliveira, Cláudia Maria Fontes; Ayres, Constância Flávia Junqueira; Monteiro, Antonio Miguel Vieira; Souza, Wayner Vieira

    2014-09-01

    Aedes aegypti has played a major role in the dramatic expansion of dengue worldwide. The failure of control programs in reducing the rhythm of global dengue expansion through vector control suggests the need for studies to support more appropriated control strategies. We report here the results of a longitudinal study on Ae. aegypti population dynamics through continuous egg sampling aiming to characterize the infestation of urban areas of a Brazilian oceanic island, Fernando de Noronha. The spatial and temporal distribution of the dengue vector population in urban areas of the island was described using a monitoring system (SMCP-Aedes) based on a 103-trap network for Aedes egg sampling, using GIS and spatial statistics analysis tools. Mean egg densities were estimated over a 29-month period starting in 2011 and producing monthly maps of mosquito abundance. The system detected continuous Ae. aegypti oviposition in most traps. The high global positive ovitrap index (POI=83.7% of 2815 events) indicated the frequent presence of blood-fed-egg laying females at every sampling station. Egg density (eggs/ovitrap/month) reached peak values of 297.3 (0 - 2020) in May and 295 (0 - 2140) in August 2012. The presence of a stable Ae. aegypti population established throughout the inhabited areas of the island was demonstrated. A strong association between egg abundance and rainfall with a 2-month lag was observed, which combined with a first-order autocorrelation observed in the series of egg counts can provide an important forecasting tool. This first description of the characteristics of the island infestation by the dengue vector provides baseline information to analyze relationships between the spatial distribution of the vector and dengue cases, and to the development of integrated vector control strategies. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Scaling-up spatially-explicit ecological models using graphics processors

    NARCIS (Netherlands)

    Koppel, Johan van de; Gupta, Rohit; Vuik, Cornelis

    2011-01-01

    How the properties of ecosystems relate to spatial scale is a prominent topic in current ecosystem research. Despite this, spatially explicit models typically include only a limited range of spatial scales, mostly because of computing limitations. Here, we describe the use of graphics processors to

  18. Towards a computational spatial knowledge acquisition model in architectural space

    NARCIS (Netherlands)

    Lyu, J.; Vries, de B.; Sun, C.; Sun, C.; Zhang, J.

    2013-01-01

    Abstract. Existing research which is related to spatial knowledge acquisition often shows a limited scope because of the complexity in the cognition process. Research in spatial representation such as space syntax presumes that vision drives movement. This assumption is only true under certain

  19. Including spatial data in nutrient balance modelling on dairy farms

    Science.gov (United States)

    van Leeuwen, Maricke; van Middelaar, Corina; Stoof, Cathelijne; Oenema, Jouke; Stoorvogel, Jetse; de Boer, Imke

    2017-04-01

    The Annual Nutrient Cycle Assessment (ANCA) calculates the nitrogen (N) and phosphorus (P) balance at a dairy farm, while taking into account the subsequent nutrient cycles of the herd, manure, soil and crop components. Since January 2016, Dutch dairy farmers are required to use ANCA in order to increase understanding of nutrient flows and to minimize nutrient losses to the environment. A nutrient balance calculates the difference between nutrient inputs and outputs. Nutrients enter the farm via purchased feed, fertilizers, deposition and fixation by legumes (nitrogen), and leave the farm via milk, livestock, manure, and roughages. A positive balance indicates to which extent N and/or P are lost to the environment via gaseous emissions (N), leaching, run-off and accumulation in soil. A negative balance indicates that N and/or P are depleted from soil. ANCA was designed to calculate average nutrient flows on farm level (for the herd, manure, soil and crop components). ANCA was not designed to perform calculations of nutrient flows at the field level, as it uses averaged nutrient inputs and outputs across all fields, and it does not include field specific soil characteristics. Land management decisions, however, such as the level of N and P application, are typically taken at the field level given the specific crop and soil characteristics. Therefore the information that ANCA provides is likely not sufficient to support farmers' decisions on land management to minimize nutrient losses to the environment. This is particularly a problem when land management and soils vary between fields. For an accurate estimate of nutrient flows in a given farming system that can be used to optimize land management, the spatial scale of nutrient inputs and outputs (and thus the effect of land management and soil variation) could be essential. Our aim was to determine the effect of the spatial scale of nutrient inputs and outputs on modelled nutrient flows and nutrient use efficiencies

  20. The establishment of insulin resistance model in FL83B and L6 cell

    Science.gov (United States)

    Liu, Lanlan; Han, Jizhong; Li, Haoran; Liu, Mengmeng; Zeng, Bin

    2017-10-01

    The insulin resistance models of mouse liver epithelial and rat myoblasts cells were induced by three kinds of inducers: dexamethasone, high insulin and high glucose. The purpose is to select the optimal insulin resistance model, to provide a simple and reliable TR cell model for the study of the pathogenesis of TR and the improvement of TR drugs and functional foods. The MTT method is used for toxicity screening of three compounds, selecting security and suitable concentration. We performed a Glucose oxidase peroxidase (GOD-POD) method involving FL83B and L6 cell with dexamethasone, high insulin and high glucose-induced insulin resistance. Results suggested that FL83B cells with dexamethasone-induced (0.25uM) were established insulin resistance and L6 cells with high-glucose (30mM) and dexamethasone-induced (0.25uM) were established insulin resistance.

  1. Establishment of a new model for culturing rabbit osteoblasts in vitro

    International Nuclear Information System (INIS)

    Cao Xianying; Yin Meizhen; Zhang Lina; Li Shipu; Cao Yang

    2006-01-01

    To establish an experimental model for culturing rabbit osteoblasts in vitro, the osteoblasts were isolated from the calvarial bone of a 15-day old rabbit using a method of culturing the bone pieces in a medium after they had been digested by an enzyme for 15 min. The acquired cells were assayed by cell morphology, alkaline phosphatase activity and production of a mineralized matrix. The results showed that the cells had the morphologic characteristics and some biological behaviours of osteoblasts. Based on the primary isolation of osteoblasts from bone and combining digestion with explants, a novel model for culturing rabbit osteoblasts in vitro was established, which is easy, efficient and effective. This model can be used in many studies of osteogenesis mechanisms and bone replacement materials. (communication)

  2. Establishment of SHG-44 human glioma model in brain of wistar rat with stereotactic technique

    International Nuclear Information System (INIS)

    Hong Xinyu; Luo Yi'nan; Fu Shuanglin; Wang Zhanfeng; Bie Li; Cui Jiale

    2004-01-01

    Objective: To establish solid intracerebral human glioma model in Wistar rat with xenograft methods. Methods: The SHG-44 cells were injected into brain right caudate nucleus of previous immuno-inhibitory Wistar rats with stereotactic technique. The MRI scans were performed at 1 week and 2 weeks later after implantation. After 2 weeks the rats were killed and pathological examination and immunohistologic stain for human GFAP were used. Results: The MRI scan after 1 week of implantation showed the glioma was growing, pathological histochemical examination demonstrated the tumor was glioma. Human GFAP stain was positive. The growth rate of glioma model was about 60%. Conclusion: Solid intracerebral human glioma model in previous immuno-inhibitory Wistar rat is successfully established

  3. Study on specificity of colon carcinoma-associated serum markers and establishment of SVM prediction model

    Directory of Open Access Journals (Sweden)

    Lu Li

    2017-03-01

    Full Text Available We aimed to evaluate the specificity of 12 tumor markers related to colon carcinoma and identify the most sensitive index. Logistic regression and Bhattacharyya distance were used to evaluate the index. Then, different index combinations were used to establish a support vector machine (SVM diagnosis model of malignant colon carcinoma. The accuracy of the model was checked. High accuracy was assumed to indicate the high specificity of the index. Through Logistic regression, three indexes, CEA, HSP60 and CA199, were screened out. Using Bhattacharyya distance, four indexes with the largest Bhattacharyya distance were screened out, including CEA, NSE, AFP, and CA724. The specificity of the combination of the above six indexes was higher than that of other combinations, so did the accuracy of the established SVM identification model. Using Logistic regression and Bhattacharyya distance for detection and establishing an SVM model based on different serum marker combinations can increase diagnostic accuracy, providing a theoretical basis for application of mathematical models in cancer diagnosis.

  4. Development of model pump for establishing hydraulic design of primary sodium pumps in PFBR

    International Nuclear Information System (INIS)

    Chougule, R.J.; Sahasrabudhe, H.G.; Rao, A.S.L.K.; Balchander, K.; Kale, R.D.

    1994-01-01

    Indira Gandhi Centre for Atomic Research, Kalpakkam indicated requirement of indigenous development of primary sodium pump, handling liquid sodium as coolant in Fast Breeder Reactor. The primary sodium pump concept selected in its preliminary design is a vertical, single stage, with single suction impeller, suction facing downwards. The pump is having diffuser, discharge casing and discharge collector. The 1/3 rd size model pump is developed to establish the hydraulic performance of the prototype primary sodium pump. The main objectives were to verify the hydraulic design to operate on low net positive suction head available (NPSHA), no evidence of visible cavitation at available NPSHA, the pump should be designed with a diffuser etc. The model pump PSP 250/40 was designed and successfully developed by Research and Development Division of M/s Kirloskar Brothers Ltd., Kirloskarvadi. The performance testing using model pump was successfully carried out on a closed circuit test rig. The performance of a model pump at three different speeds 1900 rpm, 1456 rpm and 975 rpm was established. The values of hydraulic axial thrust with and without balancing holes on impeller at 1900 rpm was measured. Visual cavitation study at 1900 rpm was carried out to establish the NPSH at bubble free operation of the pump. The tested performance of the model pump is converted to the full scale prototype pump. The predicted performance of prototype pump at 700 rpm was found to be meeting fully with the expected duties. (author). 6 figs., 3 tabs

  5. Real-time distribution of pelagic fish: combining hydroacoustics, GIS and spatial modelling at a fine spatial scale.

    Science.gov (United States)

    Muška, Milan; Tušer, Michal; Frouzová, Jaroslava; Mrkvička, Tomáš; Ricard, Daniel; Seďa, Jaromír; Morelli, Federico; Kubečka, Jan

    2018-03-29

    Understanding spatial distribution of organisms in heterogeneous environment remains one of the chief issues in ecology. Spatial organization of freshwater fish was investigated predominantly on large-scale, neglecting important local conditions and ecological processes. However, small-scale processes are of an essential importance for individual habitat preferences and hence structuring trophic cascades and species coexistence. In this work, we analysed the real-time spatial distribution of pelagic freshwater fish in the Římov Reservoir (Czechia) observed by hydroacoustics in relation to important environmental predictors during 48 hours at 3-h interval. Effect of diurnal cycle was revealed of highest significance in all spatial models with inverse trends between fish distribution and predictors in day and night in general. Our findings highlighted daytime pelagic fish distribution as highly aggregated, with general fish preferences for central, deep and highly illuminated areas, whereas nighttime distribution was more disperse and fish preferred nearshore steep sloped areas with higher depth. This turnover suggests prominent movements of significant part of fish assemblage between pelagic and nearshore areas on a diel basis. In conclusion, hydroacoustics, GIS and spatial modelling proved as valuable tool for predicting local fish distribution and elucidate its drivers, which has far reaching implications for understanding freshwater ecosystem functioning.

  6. An Epidemiological Model of Rift Valley Fever with Spatial Dynamics

    Directory of Open Access Journals (Sweden)

    Tianchan Niu

    2012-01-01

    Full Text Available As a category A agent in the Center for Disease Control bioterrorism list, Rift Valley fever (RVF is considered a major threat to the United States (USA. Should the pathogen be intentionally or unintentionally introduced to the continental USA, there is tremendous potential for economic damages due to loss of livestock, trade restrictions, and subsequent food supply chain disruptions. We have incorporated the effects of space into a mathematical model of RVF in order to study the dynamics of the pathogen spread as affected by the movement of humans, livestock, and mosquitoes. The model accounts for the horizontal transmission of Rift Valley fever virus (RVFV between two mosquito and one livestock species, and mother-to-offspring transmission of virus in one of the mosquito species. Space effects are introduced by dividing geographic space into smaller patches and considering the patch-to-patch movement of species. For each patch, a system of ordinary differential equations models fractions of populations susceptible to, incubating, infectious with, or immune to RVFV. The main contribution of this work is a methodology for analyzing the likelihood of pathogen establishment should an introduction occur into an area devoid of RVF. Examples are provided for general and specific cases to illustrate the methodology.

  7. Environmental Impacts of Large Scale Biochar Application Through Spatial Modeling

    Science.gov (United States)

    Huber, I.; Archontoulis, S.

    2017-12-01

    In an effort to study the environmental (emissions, soil quality) and production (yield) impacts of biochar application at regional scales we coupled the APSIM-Biochar model with the pSIMS parallel platform. So far the majority of biochar research has been concentrated on lab to field studies to advance scientific knowledge. Regional scale assessments are highly needed to assist decision making. The overall objective of this simulation study was to identify areas in the USA that have the most gain environmentally from biochar's application, as well as areas which our model predicts a notable yield increase due to the addition of biochar. We present the modifications in both APSIM biochar and pSIMS components that were necessary to facilitate these large scale model runs across several regions in the United States at a resolution of 5 arcminutes. This study uses the AgMERRA global climate data set (1980-2010) and the Global Soil Dataset for Earth Systems modeling as a basis for creating its simulations, as well as local management operations for maize and soybean cropping systems and different biochar application rates. The regional scale simulation analysis is in progress. Preliminary results showed that the model predicts that high quality soils (particularly those common to Iowa cropping systems) do not receive much, if any, production benefit from biochar. However, soils with low soil organic matter ( 0.5%) do get a noteworthy yield increase of around 5-10% in the best cases. We also found N2O emissions to be spatial and temporal specific; increase in some areas and decrease in some other areas due to biochar application. In contrast, we found increases in soil organic carbon and plant available water in all soils (top 30 cm) due to biochar application. The magnitude of these increases (% change from the control) were larger in soil with low organic matter (below 1.5%) and smaller in soils with high organic matter (above 3%) and also dependent on biochar

  8. Phase transition in a spatial Lotka-Volterra model

    International Nuclear Information System (INIS)

    Szabo, Gyorgy; Czaran, Tamas

    2001-01-01

    Spatial evolution is investigated in a simulated system of nine competing and mutating bacterium strains, which mimics the biochemical war among bacteria capable of producing two different bacteriocins (toxins) at most. Random sequential dynamics on a square lattice is governed by very symmetrical transition rules for neighborhood invasions of sensitive strains by killers, killers by resistants, and resistants by sensitives. The community of the nine possible toxicity/resistance types undergoes a critical phase transition as the uniform transmutation rates between the types decreases below a critical value P c above that all the nine types of strains coexist with equal frequencies. Passing the critical mutation rate from above, the system collapses into one of three topologically identical (degenerated) states, each consisting of three strain types. Of the three possible final states each accrues with equal probability and all three maintain themselves in a self-organizing polydomain structure via cyclic invasions. Our Monte Carlo simulations support that this symmetry-breaking transition belongs to the universality class of the three-state Potts model

  9. Parameterizing the Spatial Markov Model from Breakthrough Curve Data Alone

    Science.gov (United States)

    Sherman, T.; Bolster, D.; Fakhari, A.; Miller, S.; Singha, K.

    2017-12-01

    The spatial Markov model (SMM) uses a correlated random walk and has been shown to effectively capture anomalous transport in porous media systems; in the SMM, particles' future trajectories are correlated to their current velocity. It is common practice to use a priori Lagrangian velocity statistics obtained from high resolution simulations to determine a distribution of transition probabilities (correlation) between velocity classes that govern predicted transport behavior; however, this approach is computationally cumbersome. Here, we introduce a methodology to quantify velocity correlation from Breakthrough (BTC) curve data alone; discretizing two measured BTCs into a set of arrival times and reverse engineering the rules of the SMM allows for prediction of velocity correlation, thereby enabling parameterization of the SMM in studies where Lagrangian velocity statistics are not available. The introduced methodology is applied to estimate velocity correlation from BTCs measured in high resolution simulations, thus allowing for a comparison of estimated parameters with known simulated values. Results show 1) estimated transition probabilities agree with simulated values and 2) using the SMM with estimated parameterization accurately predicts BTCs downstream. Additionally, we include uncertainty measurements by calculating lower and upper estimates of velocity correlation, which allow for prediction of a range of BTCs. The simulated BTCs fall in the range of predicted BTCs. This research proposes a novel method to parameterize the SMM from BTC data alone, thereby reducing the SMM's computational costs and widening its applicability.

  10. Continuous time modelling of dynamical spatial lattice data observed at sparsely distributed times

    DEFF Research Database (Denmark)

    Rasmussen, Jakob Gulddahl; Møller, Jesper

    2007-01-01

    Summary. We consider statistical and computational aspects of simulation-based Bayesian inference for a spatial-temporal model based on a multivariate point process which is only observed at sparsely distributed times. The point processes are indexed by the sites of a spatial lattice......, and they exhibit spatial interaction. For specificity we consider a particular dynamical spatial lattice data set which has previously been analysed by a discrete time model involving unknown normalizing constants. We discuss the advantages and disadvantages of using continuous time processes compared...... with discrete time processes in the setting of the present paper as well as other spatial-temporal situations....

  11. Learning while (re)configuring: Business model innovation processes in established firms

    Science.gov (United States)

    Berends, Hans; Smits, Armand; Reymen, Isabelle; Podoynitsyna, Ksenia

    2016-01-01

    This study addresses the question of how established organizations develop new business models over time, using a process research approach to trace how four business model innovation trajectories unfold. With organizational learning as analytical lens, we discern two process patterns: “drifting” starts with an emphasis on experiential learning and shifts later to cognitive search; “leaping,” in contrast, starts with an emphasis on cognitive search and shifts later to experiential learning. Both drifting and leaping can result in radical business model innovations, while their occurrence depends on whether a new business model takes off from an existing model and when it goes into operation. We discuss the implications of these findings for theory on business models and organizational learning. PMID:28596704

  12. Learning while (re)configuring: Business model innovation processes in established firms.

    Science.gov (United States)

    Berends, Hans; Smits, Armand; Reymen, Isabelle; Podoynitsyna, Ksenia

    2016-08-01

    This study addresses the question of how established organizations develop new business models over time, using a process research approach to trace how four business model innovation trajectories unfold. With organizational learning as analytical lens, we discern two process patterns: "drifting" starts with an emphasis on experiential learning and shifts later to cognitive search; "leaping," in contrast, starts with an emphasis on cognitive search and shifts later to experiential learning. Both drifting and leaping can result in radical business model innovations, while their occurrence depends on whether a new business model takes off from an existing model and when it goes into operation. We discuss the implications of these findings for theory on business models and organizational learning.

  13. Nonuniform grid implicit spatial finite difference method for acoustic wave modeling in tilted transversely isotropic media

    KAUST Repository

    Chu, Chunlei; Stoffa, Paul L.

    2012-01-01

    sampled models onto vertically nonuniform grids. We use a 2D TTI salt model to demonstrate its effectiveness and show that the nonuniform grid implicit spatial finite difference method can produce highly accurate seismic modeling results with enhanced

  14. Spatially-Explicit Bayesian Information Entropy Metrics for Calibrating Landscape Transformation Models

    Directory of Open Access Journals (Sweden)

    Kostas Alexandridis

    2013-06-01

    Full Text Available Assessing spatial model performance often presents challenges related to the choice and suitability of traditional statistical methods in capturing the true validity and dynamics of the predicted outcomes. The stochastic nature of many of our contemporary spatial models of land use change necessitate the testing and development of new and innovative methodologies in statistical spatial assessment. In many cases, spatial model performance depends critically on the spatially-explicit prior distributions, characteristics, availability and prevalence of the variables and factors under study. This study explores the statistical spatial characteristics of statistical model assessment of modeling land use change dynamics in a seven-county study area in South-Eastern Wisconsin during the historical period of 1963–1990. The artificial neural network-based Land Transformation Model (LTM predictions are used to compare simulated with historical land use transformations in urban/suburban landscapes. We introduce a range of Bayesian information entropy statistical spatial metrics for assessing the model performance across multiple simulation testing runs. Bayesian entropic estimates of model performance are compared against information-theoretic stochastic entropy estimates and theoretically-derived accuracy assessments. We argue for the critical role of informational uncertainty across different scales of spatial resolution in informing spatial landscape model assessment. Our analysis reveals how incorporation of spatial and landscape information asymmetry estimates can improve our stochastic assessments of spatial model predictions. Finally our study shows how spatially-explicit entropic classification accuracy estimates can work closely with dynamic modeling methodologies in improving our scientific understanding of landscape change as a complex adaptive system and process.

  15. A novel spatial performance metric for robust pattern optimization of distributed hydrological models

    Science.gov (United States)

    Stisen, S.; Demirel, C.; Koch, J.

    2017-12-01

    Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing

  16. Establishment of mouse neuron and microglial cell co-cultured models and its action mechanism.

    Science.gov (United States)

    Zhang, Bo; Yang, Yunfeng; Tang, Jun; Tao, Yihao; Jiang, Bing; Chen, Zhi; Feng, Hua; Yang, Liming; Zhu, Gang

    2017-06-27

    The objective of this study is to establish a co-culture model of mouse neurons and microglial cells, and to analyze the mechanism of action of oxygen glucose deprivation (OGD) and transient oxygen glucose deprivation (tOGD) preconditioning cell models. Mouse primary neurons and BV2 microglial cells were successfully cultured, and the OGD and tOGD models were also established. In the co-culture of mouse primary neurons and microglial cells, the cell number of tOGD mouse neurons and microglial cells was larger than the OGD cell number, observed by a microscope. CCK-8 assay result showed that at 1h after treatment, the OD value in the control group is lower compared to all the other three groups (P control group compared to other three groups (P neurons cells were cultured. In the meantime mouse BV2 microglia cells were cultured. Two types of cells were co-cultured, and OGD and tOGD cell models were established. There were four groups in the experiment: control group (OGD), treatment group (tOGD+OGD), placebo group (tOGD+OGD+saline) and minocycline intervention group (tOGD+OGD+minocycline). CCK-8 kit was used to detect cell viability and flow cytometry was used to detect apoptosis. In this study, mouse primary neurons and microglial cells were co-cultured. The OGD and tOGD models were established successfully. tOGD was able to effectively protect neurons and microglial cells from damage, and inhibit the apoptosis caused by oxygen glucose deprivation.

  17. Modeling Spatial Data within Object Relational-Databases

    Directory of Open Access Journals (Sweden)

    Iuliana BOTHA

    2011-03-01

    Full Text Available Spatial data can refer to elements that help place a certain object in a certain area. These elements are latitude, longitude, points, geometric figures represented by points, etc. However, when translating these elements into data that can be stored in a computer, it all comes down to numbers. The interesting part that requires attention is how to memorize them in order to obtain fast and various spatial queries. This part is where the DBMS (Data Base Management System that contains the database acts in. In this paper, we analyzed and compared two object-relational DBMS that work with spatial data: Oracle and PostgreSQL.

  18. The dynamic and indirect spatial effects of neighborhood conditions on land value, spatial panel dynamic econometrics model

    Science.gov (United States)

    Fitriani, Rahma; Sumarminingsih, Eni; Astutik, Suci

    2017-05-01

    Land value is the product of past decision of its use leading to its value, as well as the value of the surrounded land. It is also affected by the local characteristic and the spillover development demand of the previous time period. The effect of each factor on land value will have dynamic and spatial virtues. Thus, a spatial panel dynamic model is used to estimate the particular effects. The model will be useful for predicting the future land value or the effect of implemented policy on land value. The objective of this paper is to derive the dynamic and indirect spatial marginal effects of the land characteristic and the spillover development demand on land value. Each effect is the partial derivative of the expected land value based on the spatial dynamic model with respect to each variable, by considering different time period and different location. The results indicate that the instant change of local or neighborhood characteristics on land value affect the local and the immediate neighborhood land value. However, the longer the change take place, the effect will spread further, not only on the immediate neighborhood.

  19. Pair and triplet approximation of a spatial lattice population model with multiscale dispersal using Markov chains for estimating spatial autocorrelation.

    Science.gov (United States)

    Hiebeler, David E; Millett, Nicholas E

    2011-06-21

    We investigate a spatial lattice model of a population employing dispersal to nearest and second-nearest neighbors, as well as long-distance dispersal across the landscape. The model is studied via stochastic spatial simulations, ordinary pair approximation, and triplet approximation. The latter method, which uses the probabilities of state configurations of contiguous blocks of three sites as its state variables, is demonstrated to be greatly superior to pair approximations for estimating spatial correlation information at various scales. Correlations between pairs of sites separated by arbitrary distances are estimated by constructing spatial Markov processes using the information from both approximations. These correlations demonstrate why pair approximation misses basic qualitative features of the model, such as decreasing population density as a large proportion of offspring are dropped on second-nearest neighbors, and why triplet approximation is able to include them. Analytical and numerical results show that, excluding long-distance dispersal, the initial growth rate of an invading population is maximized and the equilibrium population density is also roughly maximized when the population spreads its offspring evenly over nearest and second-nearest neighboring sites. Copyright © 2011 Elsevier Ltd. All rights reserved.

  20. Application of Spatial Regression Models to Income Poverty Ratios in Middle Delta Contiguous Counties in Egypt

    Directory of Open Access Journals (Sweden)

    Sohair F Higazi

    2013-02-01

    Full Text Available Regression analysis depends on several assumptions that have to be satisfied. A major assumption that is never satisfied when variables are from contiguous observations is the independence of error terms. Spatial analysis treated the violation of that assumption by two derived models that put contiguity of observations into consideration. Data used are from Egypt's 2006 latest census, for 93 counties in middle delta seven adjacent Governorates. The dependent variable used is the percent of individuals classified as poor (those who make less than 1$ daily. Predictors are some demographic indicators. Explanatory Spatial Data Analysis (ESDA is performed to examine the existence of spatial clustering and spatial autocorrelation between neighboring counties. The ESDA revealed spatial clusters and spatial correlation between locations. Three statistical models are applied to the data, the Ordinary Least Square regression model (OLS, the Spatial Error Model (SEM and the Spatial Lag Model (SLM.The Likelihood Ratio test and some information criterions are used to compare SLM and SEM to OLS. The SEM model proved to be better than the SLM model. Recommendations are drawn regarding the two spatial models used.

  1. A Behavioral Maturity Model to Establish Knowledge Management in an Organization

    Directory of Open Access Journals (Sweden)

    C. S. Fashami

    2017-06-01

    Full Text Available Modern organizations need intangible assets such as organizational knowledge and human resources to gain competitive advantage in the market. Organizations can provide opportunities for behavioral maturity of managers to establish knowledge management. This study tries to develop a behavioral maturity model for managements to examine effectiveness of knowledge management. The study is conducted in Iran Insurance Company as an empirical case study. Twenty academic and organizational experts are selected for the study. Employees and managers of Iran Insurance Company are used to measure and test conceptual model (behavioral maturity of managers to establish knowledge management. Both interview and questionnaire tools are used to collect data. Fuzzy AHP and PLS methods are used to analyze the collected data. Fuzzy AHP results show that transformational leadership, human and social skills, knowledge orientation, emotional intelligence, trustful climate are identified as highly effective priorities.

  2. Establishment of an animal model of mice with radiation- injured soft tissue blood vessels

    International Nuclear Information System (INIS)

    Wang Daiyou; Yu Dahai; Wu Jiaxiao; Wei Shanliang; Wen Yuming

    2004-01-01

    Objective: The aim of this study was to establish an animal model of mice with radiation-injured soft tissue blood vessels. Methods: Forty male mice were irradiated with 30 Gy on the right leg. After the irradiation was finished each of the 40 male mice was tested with angiography, and its muscle tissues on the bilateral legs were examined with vessel staining assay and electron microscopy. Results: The results showed that the number of vessels on the right leg was less than that on the left leg, the microvessel density, average diameter and average sectional area of the right leg were all lower than those of the left, and the configuration and ultra-structure of vessels were also different between both sides of legs. Conclusion: In the study authors successfully established an animal model of mice with radiation-injured soft tissue blood vessels

  3. Establishment and Characterization of a Tumor Stem Cell-Based Glioblastoma Invasion Model

    DEFF Research Database (Denmark)

    Jensen, Stine Skov; Meyer, Morten; Petterson, Stine Asferg

    2016-01-01

    AIMS: Glioblastoma is the most frequent and malignant brain tumor. Recurrence is inevitable and most likely connected to tumor invasion and presence of therapy resistant stem-like tumor cells. The aim was therefore to establish and characterize a three-dimensional in vivo-like in vitro model taking...... invasion and tumor stemness into account. METHODS: Glioblastoma stem cell-like containing spheroid (GSS) cultures derived from three different patients were established and characterized. The spheroids were implanted in vitro into rat brain slice cultures grown in stem cell medium and in vivo into brains...... of immuno-compromised mice. Invasion was followed in the slice cultures by confocal time-lapse microscopy. Using immunohistochemistry, we compared tumor cell invasion as well as expression of proliferation and stem cell markers between the models. RESULTS: We observed a pronounced invasion into brain slice...

  4. Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model

    NARCIS (Netherlands)

    Velazco, Julio G.; Rodríguez-Álvarez, María Xosé; Boer, Martin P.; Jordan, David R.; Eilers, Paul H.C.; Malosetti, Marcos; Eeuwijk, van Fred A.

    2017-01-01

    Key message: A flexible and user-friendly spatial method called SpATS performed comparably to more elaborate and trial-specific spatial models in a series of sorghum breeding trials. Abstract: Adjustment for spatial trends in plant breeding field trials is essential for efficient evaluation and

  5. Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model

    NARCIS (Netherlands)

    J.G. Velazco (Julio G.); M.X. Rodríguez-Álvarez (María Xosé); M.P. Boer (Martin); D.R. Jordan (David R.); P.H.C. Eilers (Paul); M. Malosetti (Marcos); F. van Eeuwijk (Fred)

    2017-01-01

    markdownabstract_Key message: A flexible and user-friendly spatial method called SpATS performed comparably to more elaborate and trial-specific spatial models in a series of sorghum breeding trials._ __Abstract:__ Adjustment for spatial trends in plant breeding field trials is essential for

  6. Modelling spatial relationship between climatic conditions and annual parasite incidence of malaria in southern part of Sistan&Balouchistan Province of Iran using spatial statistic models

    Directory of Open Access Journals (Sweden)

    Mansour Halimi

    2014-02-01

    Full Text Available Objective: To model spatial relationship between climatic conditions and annual parasite incidence (API of malaria in southern part of Sistan&Balouchistan Province of Iran using spatial statistic models . Methods: A geographical weighted regression model was applied for predicting API by 3 climatic factors in order to model the spatial API of malaria in Sistan&Baluchistan Province of Iran. Results: The results indicated that most important climatic factor for explaining API in Sistan&Baluchistan was annual rainfall being of more importance in southern part of study area such as Chabahar, and Nikshar. The temperature and relative humidity are of the second and third priority respectively. The importance of these two climatic factors is higher in northern part of the studied region. The spatial autocorrelation (Moran ’s I for standard residual of applied geographical weighted regression model is -0.022 which indicated no spatial patterns. Conclusions: This model explained only 0.51 of API spatial variation (R2=0.51. Thus, the nonclimatic factors such as socioeconomic, lifestyle and the neighborhood position of this province with Afghanistan, and Pakistan also should be considered in epidemiological survey of malaria in Sistan&Baluchistan.

  7. Unemployment estimation: Spatial point referenced methods and models

    KAUST Repository

    Pereira, Soraia; Turkman, Kamil Feridun; Correia, Luis; Rue, Haavard

    2017-01-01

    Portuguese Labor force survey, from 4th quarter of 2014 onwards, started geo-referencing the sampling units, namely the dwellings in which the surveys are carried. This opens new possibilities in analysing and estimating unemployment and its spatial

  8. MODEL OF SPATIAL EVALUATION FOR TOURISM ECO-RENT

    Directory of Open Access Journals (Sweden)

    Maja Fredotović

    2011-02-01

    Full Text Available Tourism is extremely interacted with the environment. Taking into account that tourism uses the space and related resources, it seems right to pay for the damages caused to the environment. This is the basis of the tourist spatial eco rent. The paper evaluates the space and resources used by tourism as the basis for the introduction of the tourism eco-rent in the area of Makarska Riviera, a traditional tourism destination. It is divided into three main spatial units: urban areas, bathing zone (beaches, Biokovo Park of Nature. According to natural and geographical reasoning, a number of zones with different spatial values within each spatial unit has been identified. Each unit, i.e. zone was evaluated according to various criteria relevant to the evaluation of space for tourism and tourism development purposes. Having ranked zones within each unit, using the multiriteria ranking method PROMETHEE II, comparative analysis of the obtained results was carried out as well.

  9. Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic

    Directory of Open Access Journals (Sweden)

    Erfan Ayubi

    2017-05-01

    Full Text Available OBJECTIVES The aim of this study was to explore the spatial pattern of female breast cancer (BC incidence at the neighborhood level in Tehran, Iran. METHODS The present study included all registered incident cases of female BC from March 2008 to March 2011. The raw standardized incidence ratio (SIR of BC for each neighborhood was estimated by comparing observed cases relative to expected cases. The estimated raw SIRs were smoothed by a Besag, York, and Mollie spatial model and the spatial empirical Bayesian method. The purely spatial scan statistic was used to identify spatial clusters. RESULTS There were 4,175 incident BC cases in the study area from 2008 to 2011, of which 3,080 were successfully geocoded to the neighborhood level. Higher than expected rates of BC were found in neighborhoods located in northern and central Tehran, whereas lower rates appeared in southern areas. The most likely cluster of higher than expected BC incidence involved neighborhoods in districts 3 and 6, with an observed-to-expected ratio of 3.92 (p<0.001, whereas the most likely cluster of lower than expected rates involved neighborhoods in districts 17, 18, and 19, with an observed-to-expected ratio of 0.05 (p<0.001. CONCLUSIONS Neighborhood-level inequality in the incidence of BC exists in Tehran. These findings can serve as a basis for resource allocation and preventive strategies in at-risk areas.

  10. The Internet addiction components model and personality: establishing construct validity via a nomological network

    OpenAIRE

    Kuss, DJ; Shorter, GW; Van Rooij, AJ; Van de Mheen, D; Griffiths, MD

    2014-01-01

    There is growing concern over excessive and sometimes problematic Internet use. Drawing upon the framework of the components model of addiction (Griffiths, 2005), Internet addiction appears as behavioural addiction characterised by the following symptoms: salience, withdrawal, tolerance, mood modification, relapse and conflict. A number of factors have been associated with an increased risk for Internet addiction, including personality traits. The overall aim of this study was to establish th...

  11. A Behavioral Maturity Model to Establish Knowledge Management in an Organization

    OpenAIRE

    Fashami, C. S.; Babaei, M.

    2017-01-01

    Modern organizations need intangible assets such as organizational knowledge and human resources to gain competitive advantage in the market. Organizations can provide opportunities for behavioral maturity of managers to establish knowledge management. This study tries to develop a behavioral maturity model for managements to examine effectiveness of knowledge management. The study is conducted in Iran Insurance Company as an empirical case study. Twenty academic and organizational experts ar...

  12. 1993-1994 Final technical report for establishing the SECME Model in the District of Columbia

    Energy Technology Data Exchange (ETDEWEB)

    Vickers, R.G.

    1995-12-31

    This is the final report for a program to establish the SECME Model in the District of Columbia. This program has seen the development of a partnership between the District of Columbia Public Schools, the University of the District of Columbia, the Department of Energy, and SECME. This partnership has demonstrated positive achievement in mathematics and science education and learning in students within the District of Columbia.

  13. 1993-1994 Final technical report for establishing the SECME Model in the District of Columbia

    International Nuclear Information System (INIS)

    Vickers, R.G.

    1995-01-01

    This is the final report for a program to establish the SECME Model in the District of Columbia. This program has seen the development of a partnership between the District of Columbia Public Schools, the University of the District of Columbia, the Department of Energy, and SECME. This partnership has demonstrated positive achievement in mathematics and science education and learning in students within the District of Columbia

  14. Establishment of Grain Farmers' Supply Response Model and Empirical Analysis under Minimum Grain Purchase Price Policy

    OpenAIRE

    Zhang, Shuang

    2012-01-01

    Based on farmers' supply behavior theory and price expectations theory, this paper establishes grain farmers' supply response model of two major grain varieties (early indica rice and mixed wheat) in the major producing areas, to test whether the minimum grain purchase price policy can have price-oriented effect on grain production and supply in the major producing areas. Empirical analysis shows that the minimum purchase price published annually by the government has significant positive imp...

  15. Establishment of a large panel of patient-derived preclinical models of human renal cell carcinoma

    OpenAIRE

    Lang, Herv?; B?raud, Claire; Bethry, Audrey; Danilin, Sabrina; Lindner, V?ronique; Coquard, Catherine; Rothhut, Sylvie; Massfelder, Thierry

    2016-01-01

    The objective of the present work was to establish a large panel of preclinical models of human renal cell carcinoma (RCC) directly from patients, faithfully reproducing the biological features of the original tumor. RCC tissues (all stages/subtypes) were collected for 8 years from 336 patients undergoing surgery, xenografted subcutaneously in nude mice, and serially passaged into new mice up to 13 passages. Tissue samples from the primary tumor and tumors grown in mice through passages were ...

  16. Establishing credibility in the environmental models used for safety and licensing calculations in the nuclear industry

    International Nuclear Information System (INIS)

    Davis, P.A.

    1997-01-01

    Models that simulate the transport and behaviour of radionuclides in the environment are used extensively in the nuclear industry for safety and licensing purposes. They are needed to calculate derived release limits for new and operating facilities, to estimate consequences following hypothetical accidents and to help manage a real emergency. But predictions generated for these purposes are essentially meaningless unless they are accompanied by a quantitative estimate of the confidence that can be placed in them. For example, in an emergency where there has been an accidental release of radioactivity to the atmosphere, decisions based on a validated model with small uncertainties would likely be very different from those based on an untested model, or on one with large uncertainties. This paper begins with a discussion of some general methods for establishing the credibility of model predictions. The focus will be on environmental transport models but the principles apply to models of all kinds. Establishing the credibility of a model is not a trivial task, It involves a number of tasks including face validation, verification, experimental validation and sensitivity and uncertainty analyses. The remainder of the paper will present quantitative results relating to the credibility of environmental transport models. Model formation, choice of parameter values and the influence of the user will all be discussed as sources of uncertainty in predictions. The magnitude of uncertainties that must be expected in various applications of the models will be presented. The examples used throughout the paper are drawn largely from recent work carried out in BIOMOVS and VAMP. (DM)

  17. Assessing the potential for establishment of western cherry fruit fly using ecological niche modeling.

    Science.gov (United States)

    Kumar, Sunil; Neven, Lisa G; Yee, Wee L

    2014-06-01

    Sweet cherries, Prunus avium (L.) L., grown in the western United States are exported to many countries around the world. Some of these countries have enforced strict quarantine rules and trade restrictions owing to concerns about the potential establishment and subsequent spread of western cherry fruit fly, Rhagoletis indifferens Curran (Diptera: Tephritidae), a major quarantine pest of sweet cherry. We used 1) niche models (CLIMEX and MaxEnt) to map the climatic suitability, 2) North Carolina State University-Animal and Plant Health Inspection Service Plant Pest Forecasting System to examine chilling requirement, and 3) host distribution and availability to assess the potential for establishment of R. indifferens in areas of western North America where it currently does not exist and eight current or potential fresh sweet cherry markets: Colombia, India, Indonesia, Malaysia, Taiwan, Thailand, Venezuela, and Vietnam. Results from niche models conformed well to the current distribution of R. indifferens in western North America. MaxEnt and CLIMEX models had high performance and predicted climatic suitability in some of the countries (e.g., Andean range in Colombia and Venezuela, northern and northeastern India, central Taiwan, and parts of Vietnam). However, our results showed no potential for establishment of R. indifferens in Colombia, Indonesia, Malaysia, Taiwan, Thailand, Venezuela, and Vietnam when the optimal chilling requirement to break diapause (minimum temperature policy makers.

  18. A rabbit model of fatal hypothyroidism mimicking "myxedema coma" established by microscopic total thyroidectomy.

    Science.gov (United States)

    Ono, Yosuke; Fujita, Masanori; Ono, Sachiko; Ogata, Sho; Tachibana, Shoichi; Tanaka, Yuji

    2016-06-30

    Myxedema coma (MC) is a life-threatening endocrine crisis caused by severe hypothyroidism. However, validated diagnostic criteria and treatment guidelines for MC have not been established owing to its rarity. Therefore, a valid animal model is required to investigate the pathologic and therapeutic aspects of MC. The aim of the present study was to establish an animal model of MC induced by total thyroidectomy. We utilized 14 male New Zealand White rabbits anesthetized via intramuscular ketamine and xylazine administration. A total of 7 rabbits were completely thyroidectomized under a surgical microscope (thyroidectomized group) and the remainder underwent sham operations (control group). The animals in both groups were monitored without thyroid hormone replacement for 15 weeks. Pulse rate, blood pressure, body temperature, and electrocardiograms (ECG) were recorded and blood samples were taken from the jugular vein immediately prior to the thyroidectomy and 2 and 4 weeks after surgery. The thyroidectomized rabbits showed a marked reduction of serum thyroxine levels at 4 weeks after the surgical procedure vs. controls (0.50±0.10 vs. 3.32±0.68 μg/dL, pmyxedema heart. In summary, we have established a rabbit model of fatal hypothyroidism mimicking MC, which may facilitate pathophysiological and molecular investigations of MC and evaluations of new therapeutic interventions.

  19. Establishment and Characterization of a Tumor Stem Cell-Based Glioblastoma Invasion Model.

    Directory of Open Access Journals (Sweden)

    Stine Skov Jensen

    Full Text Available Glioblastoma is the most frequent and malignant brain tumor. Recurrence is inevitable and most likely connected to tumor invasion and presence of therapy resistant stem-like tumor cells. The aim was therefore to establish and characterize a three-dimensional in vivo-like in vitro model taking invasion and tumor stemness into account.Glioblastoma stem cell-like containing spheroid (GSS cultures derived from three different patients were established and characterized. The spheroids were implanted in vitro into rat brain slice cultures grown in stem cell medium and in vivo into brains of immuno-compromised mice. Invasion was followed in the slice cultures by confocal time-lapse microscopy. Using immunohistochemistry, we compared tumor cell invasion as well as expression of proliferation and stem cell markers between the models.We observed a pronounced invasion into brain slice cultures both by confocal time-lapse microscopy and immunohistochemistry. This invasion closely resembled the invasion in vivo. The Ki-67 proliferation indexes in spheroids implanted into brain slices were lower than in free-floating spheroids. The expression of stem cell markers varied between free-floating spheroids, spheroids implanted into brain slices and tumors in vivo.The established invasion model kept in stem cell medium closely mimics tumor cell invasion into the brain in vivo preserving also to some extent the expression of stem cell markers. The model is feasible and robust and we suggest the model as an in vivo-like model with a great potential in glioma studies and drug discovery.

  20. Advanced spatial metrics analysis in cellular automata land use and cover change modeling

    International Nuclear Information System (INIS)

    Zamyatin, Alexander; Cabral, Pedro

    2011-01-01

    This paper proposes an approach for a more effective definition of cellular automata transition rules for landscape change modeling using an advanced spatial metrics analysis. This approach considers a four-stage methodology based on: (i) the search for the appropriate spatial metrics with minimal correlations; (ii) the selection of the appropriate neighborhood size; (iii) the selection of the appropriate technique for spatial metrics application; and (iv) the analysis of the contribution level of each spatial metric for joint use. The case study uses an initial set of 7 spatial metrics of which 4 are selected for modeling. Results show a better model performance when compared to modeling without any spatial metrics or with the initial set of 7 metrics.

  1. Modelling malaria treatment practices in Bangladesh using spatial statistics

    Directory of Open Access Journals (Sweden)

    Haque Ubydul

    2012-03-01

    Full Text Available Abstract Background Malaria treatment-seeking practices vary worldwide and Bangladesh is no exception. Individuals from 88 villages in Rajasthali were asked about their treatment-seeking practices. A portion of these households preferred malaria treatment from the National Control Programme, but still a large number of households continued to use drug vendors and approximately one fourth of the individuals surveyed relied exclusively on non-control programme treatments. The risks of low-control programme usage include incomplete malaria treatment, possible misuse of anti-malarial drugs, and an increased potential for drug resistance. Methods The spatial patterns of treatment-seeking practices were first examined using hot-spot analysis (Local Getis-Ord Gi statistic and then modelled using regression. Ordinary least squares (OLS regression identified key factors explaining more than 80% of the variation in control programme and vendor treatment preferences. Geographically weighted regression (GWR was then used to assess where each factor was a strong predictor of treatment-seeking preferences. Results Several factors including tribal affiliation, housing materials, household densities, education levels, and proximity to the regional urban centre, were found to be effective predictors of malaria treatment-seeking preferences. The predictive strength of each of these factors, however, varied across the study area. While education, for example, was a strong predictor in some villages, it was less important for predicting treatment-seeking outcomes in other villages. Conclusion Understanding where each factor is a strong predictor of treatment-seeking outcomes may help in planning targeted interventions aimed at increasing control programme usage. Suggested strategies include providing additional training for the Building Resources across Communities (BRAC health workers, implementing educational programmes, and addressing economic factors.

  2. Analysing the distribution of synaptic vesicles using a spatial point process model

    DEFF Research Database (Denmark)

    Khanmohammadi, Mahdieh; Waagepetersen, Rasmus; Nava, Nicoletta

    2014-01-01

    functionality by statistically modelling the distribution of the synaptic vesicles in two groups of rats: a control group subjected to sham stress and a stressed group subjected to a single acute foot-shock (FS)-stress episode. We hypothesize that the synaptic vesicles have different spatial distributions...... in the two groups. The spatial distributions are modelled using spatial point process models with an inhomogeneous conditional intensity and repulsive pairwise interactions. Our results verify the hypothesis that the two groups have different spatial distributions....

  3. Bayesian spatial modeling of HIV mortality via zero-inflated Poisson models.

    Science.gov (United States)

    Musal, Muzaffer; Aktekin, Tevfik

    2013-01-30

    In this paper, we investigate the effects of poverty and inequality on the number of HIV-related deaths in 62 New York counties via Bayesian zero-inflated Poisson models that exhibit spatial dependence. We quantify inequality via the Theil index and poverty via the ratios of two Census 2000 variables, the number of people under the poverty line and the number of people for whom poverty status is determined, in each Zip Code Tabulation Area. The purpose of this study was to investigate the effects of inequality and poverty in addition to spatial dependence between neighboring regions on HIV mortality rate, which can lead to improved health resource allocation decisions. In modeling county-specific HIV counts, we propose Bayesian zero-inflated Poisson models whose rates are functions of both covariate and spatial/random effects. To show how the proposed models work, we used three different publicly available data sets: TIGER Shapefiles, Census 2000, and mortality index files. In addition, we introduce parameter estimation issues of Bayesian zero-inflated Poisson models and discuss MCMC method implications. Copyright © 2012 John Wiley & Sons, Ltd.

  4. Spatial Heterogeneity of Soil Nutrients after the Establishment of Caragana intermedia Plantation on Sand Dunes in Alpine Sandy Land of the Tibet Plateau.

    Science.gov (United States)

    Li, Qingxue; Jia, Zhiqing; Zhu, Yajuan; Wang, Yongsheng; Li, Hong; Yang, Defu; Zhao, Xuebin

    2015-01-01

    The Gonghe Basin region of the Tibet Plateau is severely affected by desertification. Compared with other desertified land, the main features of this region is windy, cold and short growing season, resulting in relatively difficult for vegetation restoration. In this harsh environment, identification the spatial distribution of soil nutrients and analysis its impact factors after vegetation establishment will be helpful for understanding the ecological relationship between soil and environment. Therefore, in this study, the 12-year-old C. intermedia plantation on sand dunes was selected as the experimental site. Soil samples were collected under and between shrubs on the windward slopes, dune tops and leeward slopes with different soil depth. Then analyzed soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available nitrogen (AN), available phosphorus (AP) and available potassium (AK). The results showed that the spatial heterogeneity of soil nutrients was existed in C. intermedia plantation on sand dunes. (1) Depth was the most important impact factor, soil nutrients were decreased with greater soil depth. One of the possible reasons is that windblown fine materials and litters were accumulated on surface soil, when they were decomposed, more nutrients were aggregated on surface soil. (2) Topography also affected the distribution of soil nutrients, more soil nutrients distributed on windward slopes. The herbaceous coverage were higher and C. intermedia ground diameter were larger on windward slopes, both of them probably related to the high soil nutrients level for windward slopes. (3) Soil "fertile islands" were formed, and the "fertile islands" were more marked on lower soil nutrients level topography positions, while it decreased towards higher soil nutrients level topography positions. The enrichment ratio (E) for TN and AN were higher than other nutrients, most likely because C. intermedia is a leguminous shrub.

  5. Spatial pattern evaluation of a calibrated national hydrological model - a remote-sensing-based diagnostic approach

    Science.gov (United States)

    Mendiguren, Gorka; Koch, Julian; Stisen, Simon

    2017-11-01

    Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds

  6. Spatial models for context-aware indoor navigation systems: A survey

    Directory of Open Access Journals (Sweden)

    Imad Afyouni

    2012-06-01

    Full Text Available This paper surveys indoor spatial models developed for research fields ranging from mobile robot mapping, to indoor location-based services (LBS, and most recently to context-aware navigation services applied to indoor environments. Over the past few years, several studies have evaluated the potential of spatial models for robot navigation and ubiquitous computing. In this paper we take a slightly different perspective, considering not only the underlying properties of those spatial models, but also to which degree the notion of context can be taken into account when delivering services in indoor environments. Some preliminary recommendations for the development of indoor spatial models are introduced from a context-aware perspective. A taxonomy of models is then presented and assessed with the aim of providing a flexible spatial data model for navigation purposes, and by taking into account the context dimensions.

  7. A spatial error model with continuous random effects and an application to growth convergence

    Science.gov (United States)

    Laurini, Márcio Poletti

    2017-10-01

    We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (β -convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.

  8. Establishment and correction of an Echelle cross-prism spectrogram reduction model

    Science.gov (United States)

    Zhang, Rui; Bayanheshig; Li, Xiaotian; Cui, Jicheng

    2017-11-01

    The accuracy of an echelle cross-prism spectrometer depends on the matching degree between the spectrum reduction model and the actual state of the spectrometer. However, the error of adjustment can change the actual state of the spectrometer and result in a reduction model that does not match. This produces an inaccurate wavelength calibration. Therefore, the calibration of a spectrogram reduction model is important for the analysis of any echelle cross-prism spectrometer. In this study, the spectrogram reduction model of an echelle cross-prism spectrometer was established. The image position laws of a spectrometer that varies with the system parameters were simulated to the influence of the changes in prism refractive index, focal length and so on, on the calculation results. The model was divided into different wavebands. The iterative method, least squares principle and element lamps with known characteristic wavelength were used to calibrate the spectral model in different wavebands to obtain the actual values of the system parameters. After correction, the deviation of actual x- and y-coordinates and the coordinates calculated by the model are less than one pixel. The model corrected by this method thus reflects the system parameters in the current spectrometer state and can assist in accurate wavelength extraction. The instrument installation and adjustment would be guided in model-repeated correction, reducing difficulty of equipment, respectively.

  9. Research on spatial Model and analysis algorithm for nuclear weapons' damage effects

    International Nuclear Information System (INIS)

    Liu Xiaohong; Meng Tao; Du Maohua; Wang Weili; Ji Wanfeng

    2011-01-01

    In order to realize the three dimension visualization of nuclear weapons' damage effects. Aiming at the characteristics of the damage effects data, a new model-MRPCT model is proposed, and this model can carry out the modeling of the three dimension spatial data of the nuclear weapons' damage effects. For the sake of saving on the memory, linear coding method is used to store the MRPCT model. On the basis of Morton code, spatial analysis of the damage effects is completed. (authors)

  10. A modeling approach to establish environmental flow threshold in ungauged semidiurnal tidal river

    Science.gov (United States)

    Akter, A.; Tanim, A. H.

    2018-03-01

    Due to shortage of flow monitoring data in ungauged semidiurnal river, 'environmental flow' (EF) determination based on its key component 'minimum low flow' is always difficult. For EF assessment this study selected a reach immediately after the Halda-Karnafuli confluence, a unique breeding ground for Indian Carp fishes of Bangladesh. As part of an ungauged tidal river, EF threshold establishment faces challenges in changing ecological paradigms with periodic change of tides and hydrologic alterations. This study describes a novel approach through modeling framework comprising hydrological, hydrodynamic and habitat simulation model. The EF establishment was conceptualized according to the hydrologic process of an ungauged semi-diurnal tidal regime in four steps. Initially, a hydrologic model coupled with a hydrodynamic model to simulate flow considering land use changes effect on streamflow, seepage loss of channel, friction dominated tidal decay as well as lack of long term flow characteristics. Secondly, to define hydraulic habitat feature, a statistical analysis on derived flow data was performed to identify 'habitat suitability'. Thirdly, to observe the ecological habitat behavior based on the identified hydrologic alteration, hydraulic habitat features were investigated. Finally, based on the combined habitat suitability index flow alteration and ecological response relationship was established. Then, the obtained EF provides a set of low flow indices of desired regime and thus the obtained discharge against maximum Weighted Usable Area (WUA) was defined as EF threshold for the selected reach. A suitable EF regime condition was obtained within flow range 25-30.1 m3/s i.e., around 10-12% of the mean annual runoff of 245 m3/s and these findings are within researchers' recommendation of minimum flow requirement. Additionally it was observed that tidal characteristics are dominant process in semi-diurnal regime. However, during the study period (2010-2015) the

  11. Development and Symbiosis Establishment in the Cnidarian Endosymbiosis Model Aiptasia sp.

    Science.gov (United States)

    Bucher, Madeline; Wolfowicz, Iliona; Voss, Philipp A; Hambleton, Elizabeth A; Guse, Annika

    2016-01-25

    Symbiosis between photosynthetic algae and heterotrophic organisms is widespread. One prominent example of high ecological relevance is the endosymbiosis between dinoflagellate algae of the genus Symbiodinium and reef-building corals, which typically acquire symbionts anew each generation during larval stages. The tropical sea anemone Aiptasia sp. is a laboratory model system for this endosymbiosis and, similar to corals, produces non-symbiotic larvae that establish symbiosis by phagocytosing Symbiodinium from the environment into the endoderm. Here we generate the first overview of Aiptasia embryogenesis and larval development and establish in situ hybridization to analyze expression patterns of key early developmental regulators. Next, we quantify morphological changes in developing larvae and find a substantial enlargement of the gastric cavity over time. Symbiont acquisition starts soon after mouth formation and symbionts occupy a major portion of the host cell in which they reside. During the first 14 days of development, infection efficiency remains constant while in contrast, localization of phagocytosed symbionts changes, indicating that the occurrence of functional phagocytosing cells may be developmentally regulated. Taken together, here we provide the essential framework to further develop Aiptasia as a model system for the analysis of symbiosis establishment in cnidarian larvae at the molecular level.

  12. A spatial-dynamic value transfer model of economic losses from a biological invasion

    Science.gov (United States)

    Thomas P. Holmes; Andrew M. Liebhold; Kent F. Kovacs; Betsy. Von Holle

    2010-01-01

    Rigorous assessments of the economic impacts of introduced species at broad spatial scales are required to provide credible information to policy makers. We propose that economic models of aggregate damages induced by biological invasions need to link microeconomic analyses of site-specific economic damages with spatial-dynamic models of value change associated with...

  13. Towards models of strategic spatial choice behaviour: theory and application issues

    NARCIS (Netherlands)

    Han, Q.; Timmermans, H.J.P.

    2005-01-01

    Models of spatial choice behaviour have been around in urban planning for decades to assess the feasibility of planning actions or to predict external (competition) effects on existing destinations. The well known spatial interaction models of the 1970s have gradually been replaced by discrete

  14. Computer Games versus Maps before Reading Stories: Priming Readers' Spatial Situation Models

    Science.gov (United States)

    Smith, Glenn Gordon; Majchrzak, Dan; Hayes, Shelley; Drobisz, Jack

    2011-01-01

    The current study investigated how computer games and maps compare as preparation for readers to comprehend and retain spatial relations in text narratives. Readers create situation models of five dimensions: spatial, temporal, causal, goal, and protagonist (Zwaan, Langston, & Graesser 1995). Of these five, readers mentally model the spatial…

  15. A nutritional risk screening model for patients with liver cirrhosis established using discriminant analysis

    Directory of Open Access Journals (Sweden)

    ZHU Binghua

    2017-06-01

    Full Text Available ObjectiveTo establish a nutritional risk screening model for patients with liver cirrhosis using discriminant analysis. MethodsThe clinical data of 273 patients with liver cirrhosis who were admitted to Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from August 2015 to March 2016 were collected. Body height, body weight, upper arm circumference, triceps skinfold thickness, subscapular skinfold thickness, and hand grip strength were measured and recorded, and then body mass index (BMI and upper arm muscle circumference were calculated. Laboratory markers including liver function parameters, renal function parameters, and vitamins were measured. The patients were asked to complete Nutritional Risk Screening 2002 and Malnutrition Universal Screening Tool (MUST, and a self-developed nutritional risk screening pathway was used for nutritional risk classification. Observation scales of the four diagnostic methods in traditional Chinese medicine were used to collect patients′ symptoms and signs. Continuous data were expressed as mean±SD (x±s; an analysis of variance was used for comparison between multiple groups, and the least significant difference t-test was used for further comparison between two groups. Discriminant analysis was used for model establishment, and cross validation was used for model verification. ResultsThe nutritional risk screening pathway for patients with liver cirrhosis was used for the screening of respondents, and there were 49 patients (17.95% in non-risk group, 49 (17.95% in possible-risk group, and 175 (64.10% in risk group. The distance criterion function was used to establish the nutritional risk screening model for patients with liver cirrhosis: D1=-11.885+0.310×BMI+0150×MAC+0.005×P-Alb-0.001×Vit B12+0.103×Vit D-0.89×ascites-0.404×weakness-0.560×hypochondriac pain+0035×dysphoria with feverish sensation (note: if a patient has ascites, weakness, hypochondriac pain

  16. Establishment and validation of the model of molten pool in fast reactor

    International Nuclear Information System (INIS)

    Zhou Shufeng; Luo Rui; Wang Zhou; Shi Xiaobo; Yang Xianyong

    2007-01-01

    Running under the beyond design base accidental condition, sodium boiling and dry-out will soon be brought about in LMFBR. If not stopped timely, the fuel pins of the subassembly will be melt and broken to form a molten pool at the bottom of the subassembly. to present a reasonable analysis about the molten pool accident, a method of establishing model according to the mechanism is selected, by which an integral model of the molten pool is established. Validated on the three power groups of BF1 experiments which belong to the France SCARABEE series experimenters, the model shows good results. After compared with the models of GEYSER and BF2 experiments which had been validated before, some conclusions about mechanism of molten pool are derived. Moreover, through comparing the relative parameters such as the discharged heat and the increment of temperature etc., a reasonable analysis about the type of heat transfer is present, on the basis of which some conclusions are derived as well. (authors)

  17. [Establishment of A Clinical Prediction Model of Prolonged Air Leak 
after Anatomic Lung Resection].

    Science.gov (United States)

    Wu, Xianning; Xu, Shibin; Ke, Li; Fan, Jun; Wang, Jun; Xie, Mingran; Jiang, Xianliang; Xu, Meiqing

    2017-12-20

    Prolonged air leak (PAL) after anatomic lung resection is a common and challenging complication in thoracic surgery. No available clinical prediction model of PAL has been established in China. The aim of this study was to construct a model to identify patients at increased risk of PAL by using preoperative factors exclusively. We retrospectively reviewed clinical data and PAL occurrence of patients after anatomic lung resection, in department of thoracic surgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, from January 2016 to October 2016. 359 patients were in group A, clinical data including age, body mass index (BMI), gender, smoking history, surgical methods, pulmonary function index, pleural adhesion, pathologic diagnosis, side and site of resected lung were analyzed. By using univariate and multivariate analysis, we found the independent predictors of PAL after anatomic lung resection and subsequently established a clinical prediction model. Then, another 112 patients (group B), who underwent anatomic lung resection in different time by different team, were chosen to verify the accuracy of the prediction model. Receiver-operating characteristic (ROC) curve was constructed using the prediction model. Multivariate Logistic regression analysis was used to identify six clinical characteristics [BMI, gender, smoking history, forced expiratory volume in one second to forced vital capacity ratio (FEV1%), pleural adhesion, site of resection] as independent predictors of PAL after anatomic lung resection. The area under the ROC curve for our model was 0.886 (95%CI: 0.835-0.937). The best predictive P value was 0.299 with sensitivity of 78.5% and specificity of 93.2%. Our prediction model could accurately identify occurrence risk of PAL in patients after anatomic lung resection, which might allow for more effective use of intraoperative prophylactic strategies.
.

  18. Establishing gene models from the Pinus pinaster genome using gene capture and BAC sequencing.

    Science.gov (United States)

    Seoane-Zonjic, Pedro; Cañas, Rafael A; Bautista, Rocío; Gómez-Maldonado, Josefa; Arrillaga, Isabel; Fernández-Pozo, Noé; Claros, M Gonzalo; Cánovas, Francisco M; Ávila, Concepción

    2016-02-27

    In the era of DNA throughput sequencing, assembling and understanding gymnosperm mega-genomes remains a challenge. Although drafts of three conifer genomes have recently been published, this number is too low to understand the full complexity of conifer genomes. Using techniques focused on specific genes, gene models can be established that can aid in the assembly of gene-rich regions, and this information can be used to compare genomes and understand functional evolution. In this study, gene capture technology combined with BAC isolation and sequencing was used as an experimental approach to establish de novo gene structures without a reference genome. Probes were designed for 866 maritime pine transcripts to sequence genes captured from genomic DNA. The gene models were constructed using GeneAssembler, a new bioinformatic pipeline, which reconstructed over 82% of the gene structures, and a high proportion (85%) of the captured gene models contained sequences from the promoter regulatory region. In a parallel experiment, the P. pinaster BAC library was screened to isolate clones containing genes whose cDNA sequence were already available. BAC clones containing the asparagine synthetase, sucrose synthase and xyloglucan endotransglycosylase gene sequences were isolated and used in this study. The gene models derived from the gene capture approach were compared with the genomic sequences derived from the BAC clones. This combined approach is a particularly efficient way to capture the genomic structures of gene families with a small number of members. The experimental approach used in this study is a valuable combined technique to study genomic gene structures in species for which a reference genome is unavailable. It can be used to establish exon/intron boundaries in unknown gene structures, to reconstruct incomplete genes and to obtain promoter sequences that can be used for transcriptional studies. A bioinformatics algorithm (GeneAssembler) is also provided as a

  19. Establishment and bronchial arteriography of the models of canine lung cancer

    International Nuclear Information System (INIS)

    Cao Xicai; Wang Xiaodong; Li Bin; Shi Jianguang; Liu Yong; Xu Nanxun; Ma Weijun; Yang Haixian; Bai Jingwen; Li Weidong; Liu Shuping; Liu Anpu

    2003-01-01

    Objective: To investigate the establishment and bronchial arteriography of the models of canine lung cancer, and to facilitate further diagnosis and treatment of lung cancer. Methods: Twenty-two dogs were respectively administrated with 3 ml suspension of lipiodol-ultrafluid mixed with 3- methylcholanthrene (MCA) and diethylnitrosamine (DEN). The suspension was injected into the diaphragmic lobe of right lung with the co-axial catheter through endotracheal intubation. The dogs were randomly divided into 5 groups, group A (4 dogs), B (4), C (4), D (5), and E (5), which were sacrificed after observation for 1, 3, 6, 12, and 18 months, respectively. Then the image analysis and histopathologic examinations were carried out at different period. 5 dogs in group E were examined by bronchial arteriography. Results: Peribronchiolitis and atelectasis appeared at early stage (one month). Chronic granulomatous inflammation and fibrosis of lung tissue were gradually formed after 3 months. Proliferation of stem cells in bronchioles and atypical hyperplasia were found from 6 to 12 months. At last, the squamous carcinoma and bronchioloalveolar carcinoma were induced after 18 months. The lung cancer and precancerous lesion were found in 4 of 5 dogs at the 18 th month. The bronchial arteriography in the 5 dogs showed that 3 bronchial arteries were found as the supplying blood artery to the tumor. Conclusion: The suspension of lipiodol-ultrafluid mixed with MCA and DEN was exactly injected with the co-axial catheter through endotracheal intubation to establish the models of canine lung cancer. The inducible rate of the method was high and the location of lung cancer was accurate. It was affirmed that the blood supply artery of canine lung cancer was bronchial artery. Bronchial arteriography was of momentous significance to the diagnosis of early lung cancer. The establishment of the models of canine lung cancer was significant in the diagnosis and treatment of lung cancer. The models

  20. [Experimental study on establishment of a simple model of rats crush injury-crush syndrome].

    Science.gov (United States)

    Chen, Xi; Liu, Yuehong; Xu, Wei; Qin, Tingwu; Zhao, Luping; Liu, Shuping; Zhang, Yi; Tan, Hong; Zhou, Yu

    2013-01-01

    To establish a repeatable, simple, and effective model of rat crush injury and crush syndrome. A total of 42 female Sprague Dawley rats (2-month-old, (CS) so as to lay a foundation for further study on CS. weighing 160-180 g) were divided randomly into the control group (n=6) and experimental group (n=36). The rats of the experimental group were used to establish the crush injury and CS model in both lower limbs by self-made crush injury mould. The survival rate and hematuria rate were observed after decompression. The biochemical indexes of blood were measured at 2, 4, 8, 12, 24, and 48 hours after decompression. The samples of muscle, kidney, and heart were harvested for morphological observation. There was no treatment in the control group, and the same tests were performed. Seven rats died and 15 rats had hematuria during compression in the experimental group. Swelling of the lower limb and muscle tissue was observed in the survival rats after reperfusion. The liver function test results showed that the levels of alanine transaminase and aspartate aminotransferase in the experimental group were significantly higher than those in the control group (P congestion and swelling, renal tubular epithelial cell degeneration, edema, necrosis, and myoglobin tube type were found in the kidneys; and myocardial structure had no obvious changes. The method of the crush injury and CS model by self-made crush injury mould is a simple and effective procedure and the experimental result is stable. It is a simple method to establish an effective model of rats crush injury and CS.

  1. Towards Measures to Establish the Relevance of Climate Model Output for Decision Support

    Science.gov (United States)

    Clarke, L.; Smith, L. A.

    2007-12-01

    to weight climate model output in the decision process; one obvious example is the question of over what spatial and time averages modelers expect information in current climate distributions to be robust. The IPCC itself suggests continental/seasonal, while distributions over 10's of kilometers/hourly is on offer. Our aim here is not to resolve this discrepancy, but to develop methods with which it can be addressed. This is illustrated in the context of using another physically based, imperfect model setting: using Newton's laws in an actual case of NASA hazard evaluation. Our aim is to develop transparent standards of good practice managing expectations, which will allow model improvements over the next decades to be seen as progress by the users of climate science.

  2. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

    DEFF Research Database (Denmark)

    Demirel, Mehmet C.; Mai, Juliane; Mendiguren Gonzalez, Gorka

    2018-01-01

    Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target...... and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance...

  3. Spatial Inequalities in the Incidence of Colorectal Cancer and Associated Factors in the Neighborhoods of Tehran, Iran: Bayesian Spatial Models

    Directory of Open Access Journals (Sweden)

    Kamyar Mansori

    2018-01-01

    Full Text Available Objectives The aim of this study was to determine the factors associated with the spatial distribution of the incidence of colorectal cancer (CRC in the neighborhoods of Tehran, Iran using Bayesian spatial models. Methods This ecological study was implemented in Tehran on the neighborhood level. Socioeconomic variables, risk factors, and health costs were extracted from the Equity Assessment Study conducted in Tehran. The data on CRC incidence were extracted from the Iranian population-based cancer registry. The Besag-York-Mollié (BYM model was used to identify factors associated with the spatial distribution of CRC incidence. The software programs OpenBUGS version 3.2.3, ArcGIS 10.3, and GeoDa were used for the analysis. Results The Moran index was statistically significant for all the variables studied (p<0.05. The BYM model showed that having a women head of household (median standardized incidence ratio [SIR], 1.63; 95% confidence interval [CI], 1.06 to 2.53, living in a rental house (median SIR, 0.82; 95% CI, 0.71 to 0.96, not consuming milk daily (median SIR, 0.71; 95% CI, 0.55 to 0.94 and having greater household health expenditures (median SIR, 1.34; 95% CI, 1.06 to 1.68 were associated with a statistically significant elevation in the SIR of CRC. The median (interquartile range and mean (standard deviation values of the SIR of CRC, with the inclusion of all the variables studied in the model, were 0.57 (1.01 and 1.05 (1.31, respectively. Conclusions Inequality was found in the spatial distribution of CRC incidence in Tehran on the neighborhood level. Paying attention to this inequality and the factors associated with it may be useful for resource allocation and developing preventive strategies in atrisk areas.

  4. Applying Spatial-Temporal Model and Game Theory to Asymmetric Threat Prediction

    National Research Council Canada - National Science Library

    Wei, Mo; Chen, Genshe; Cruz, Jr., Jose B; Haynes, Leonard; Kruger, Martin

    2007-01-01

    .... In most Command and Control "C2" applications, the existing techniques, such as spatial-temporal point models for ECOA prediction or Discrete Choice Model "DCM", assume that insurgent attack features...

  5. Penultimate modeling of spatial extremes: statistical inference for max-infinitely divisible processes

    KAUST Repository

    Huser, Raphaë l; Opitz, Thomas; Thibaud, Emeric

    2018-01-01

    Extreme-value theory for stochastic processes has motivated the statistical use of max-stable models for spatial extremes. However, fitting such asymptotic models to maxima observed over finite blocks is problematic when the asymptotic stability

  6. Improving the spatial representation of basin hydrology and flow processes in the SWAT model

    OpenAIRE

    Rathjens, Hendrik

    2014-01-01

    This dissertation aims at improving the spatial representation of basin hydrology and flow processes in the SWAT model. Die vorliegende Dissertation stellt die methodischen Grundlage zur räumlich differenzierten Modellierung mit dem Modell SWAT dar.

  7. Spatial Mapping of Agricultural Water Productivity Using the SWAT Model

    Science.gov (United States)

    Thokal, Rajesh Tulshiram; Gorantiwar, S. D.; Kothari, Mahesh; Bhakar, S. R.; Nandwana, B. P.

    2015-03-01

    The Sina river basin is facing both episodic and chronic water shortages due to intensive irrigation development. The main objective of this study was to characterize the hydrologic processes of the Sina river basin and assess crop water productivity using the distributed hydrologic model, SWAT. In the simulation year (1998-1999), the inflow to reservoir from upstream side was the major contributor to the reservoir accounting for 92 % of the total required water release for irrigation purpose (119.5 Mm3), while precipitation accounted for 4.1 Mm3. Annual release of water for irrigation was 119.5 Mm3 out of which 54 % water was diverted for irrigation purpose, 26 % was wasted as conveyance loss, average discharge at the command outlet was estimated as 4 % and annual average ground-water recharge coefficient was in the range of 13-17 %. Various scenarios involving water allocation rule were tested with the goal of increasing economic water productivity values in the Sina Irrigation Scheme. Out of those, only most benefited allocation rule is analyzed in this paper. Crop yield varied from 1.98 to 25.9 t/ha, with the majority of the area between 2.14 and 2.78 t/ha. Yield and WP declined significantly in loamy soils of the irrigation command. Crop productivity in the basin was found in the lower range when compared with potential and global values. The findings suggested that there was a potential to improve further. Spatial variations in yield and WP were found to be very high for the crops grown during rabi season, while those were low for the crops grown during kharif season. The crop yields and WP during kharif season were more in the lower reach of the irrigation commands, where loamy soil is more concentrated. Sorghum in both seasons was most profitable. Sorghum fetched net income fivefold that of sunflower, two and half fold of pearl millet and one and half fold of mung beans as far as crop during kharif season were concerned and it fetched fourfold that of

  8. Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system

    Directory of Open Access Journals (Sweden)

    Daniel Brüderle

    2009-06-01

    Full Text Available Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated.

  9. Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system.

    Science.gov (United States)

    Brüderle, Daniel; Müller, Eric; Davison, Andrew; Muller, Eilif; Schemmel, Johannes; Meier, Karlheinz

    2009-01-01

    Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated.

  10. China’s Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model

    Directory of Open Access Journals (Sweden)

    Qilong Cao

    2017-09-01

    Full Text Available Background: Air pollution has become an important factor restricting China’s economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods: Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM2.5. Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results: It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM2.5 pollutions in the control of other variables. Conclusions: Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables.

  11. China's Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model.

    Science.gov (United States)

    Cao, Qilong; Liang, Ying; Niu, Xueting

    2017-09-18

    Background : Air pollution has become an important factor restricting China's economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods : Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM 2.5 . Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results : It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM 2.5 pollutions in the control of other variables. Conclusions : Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables.

  12. China’s Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model

    Science.gov (United States)

    Cao, Qilong; Liang, Ying; Niu, Xueting

    2017-01-01

    Background: Air pollution has become an important factor restricting China’s economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods: Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM2.5. Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results: It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM2.5 pollutions in the control of other variables. Conclusions: Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables. PMID:28927016

  13. Clozapine and GABA transmission in schizophrenia disease models: establishing principles to guide treatments.

    Science.gov (United States)

    O'Connor, William T; O'Shea, Sean D

    2015-06-01

    Schizophrenia disease models are necessary to elucidate underlying changes and to establish new therapeutic strategies towards a stage where drug efficacy in schizophrenia (against all classes of symptoms) can be predicted. Here we summarise the evidence for a GABA dysfunction in schizophrenia and review the functional neuroanatomy of five pathways implicated in schizophrenia, namely the mesocortical, mesolimbic, ventral striopallidal, dorsal striopallidal and perforant pathways including the role of local GABA transmission and we describe the effect of clozapine on local neurotransmitter release. This review also evaluates psychotropic drug-induced, neurodevelopmental and environmental disease models including their compatibility with brain microdialysis. The validity of disease models including face, construct, etiological and predictive validity and how these models constitute theories about this illness is also addressed. A disease model based on the effect of the abrupt withdrawal of clozapine on GABA release is also described. The review concludes that while no single animal model is entirely successful in reproducing schizophreniform symptomatology, a disease model based on an ability to prevent and/or reverse the abrupt clozapine discontinuation-induced changes in GABA release in brain regions implicated in schizophrenia may be useful for hypothesis testing and for in vivo screening of novel ligands not limited to a single pharmacological class. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Periodicity in spatial data and geostatistical models: autocorrelation between patches

    Science.gov (United States)

    Volker C. Radeloff; Todd F. Miller; Hong S. He; David J. Mladenoff

    2000-01-01

    Several recent studies in landscape ecology have found periodicity in correlograms or semi-variograms calculated, for instance, from spatial data of soils, forests, or animal populations. Some of the studies interpreted this as an indication of regular or periodic landscape patterns. This interpretation is in disagreement with other studies that doubt whether such...

  15. Prediction of water temperature metrics using spatial modelling in ...

    African Journals Online (AJOL)

    Water temperature regime dynamics should be viewed regionally, where regional divisions have an inherent underpinning by an understanding of natural thermal variability. The aim of this research was to link key water temperature metrics to readily-mapped environmental surrogates, and to produce spatial images of ...

  16. Modeling spatial pattern of deforestation using GIS and logistic ...

    African Journals Online (AJOL)

    This study aimed to predict spatial distribution of deforestation and detects factors influencing forest degradation of Northern forests of Ilam province. For this purpose, effects of six factors including distance from road and settlement areas, forest fragmentation index, elevation, slope and distance from the forest edge on the ...

  17. A participatory GIS approach to spatial modeling for slum upgrading ...

    African Journals Online (AJOL)

    The most prominent problem of rapid urbanism in Harare is the development of slums and Epworth is a notable example. The quality of planning and decision making in the participatory slum upgrading initiative can be sustainably improved by well managed processes of spatial and socio-economic data collection. More so ...

  18. Social dynamics interest groups in a model of spatial competition

    NARCIS (Netherlands)

    Tuinstra, J.; Sadiraj, V.; van Winden, F.A.A.M.

    2000-01-01

    A well-known result in spatial voting theory is that, for a one-dimensional issue space and under certain mild conditions, political parties choose platforms coinciding with the median voter's position. This result does not carry over to multi-dimensional issue spaces however, since then an

  19. Using 3D Geometric Models to Teach Spatial Geometry Concepts.

    Science.gov (United States)

    Bertoline, Gary R.

    1991-01-01

    An explanation of 3-D Computer Aided Design (CAD) usage to teach spatial geometry concepts using nontraditional techniques is presented. The software packages CADKEY and AutoCAD are described as well as their usefulness in solving space geometry problems. (KR)

  20. The importance of spatial models for estimating the strength of density dependence

    DEFF Research Database (Denmark)

    Thorson, James T.; Skaug, Hans J.; Kristensen, Kasper

    2014-01-01

    the California Coast. In this case, the nonspatial model estimates implausible oscillatory dynamics on an annual time scale, while the spatial model estimates strong autocorrelation and is supported by model selection tools. We conclude by discussing the importance of improved data archiving techniques, so...... that spatial models can be used to re-examine classic questions regarding the presence and strength of density dependence in wild populations Read More: http://www.esajournals.org/doi/abs/10.1890/14-0739.1...

  1. Establishing an experimental model of photodynamic induced anterior ischemic optic neuropathy

    Institute of Scientific and Technical Information of China (English)

    Runsheng Wang; Xiaodi Wang; Peilin Lü; Jianwei Bai; Jianzhou Wang; Xiaoqin Lei; Xiaoliang Zhou; Hongfen Sun; Aizhu Pan

    2006-01-01

    BACKGROUND: Scholars have supposed to establish animal models of optic neuropathy by pressing and partially amputating optic nerve, increasing intraocular pressure and injecting vasoconstrictor, etc., but the models are greatly different from anterior ischemia optic neuropathy. Therefore, a more ideal method is needed to establish animal model of anterior ischemic optic neuropathy (AION).OBJECTIVE: To establish AION models in rats, observe the functional changes of fundus, fundus fluorescein angiography (FFA), optical coherence tomography (OCT), flash visual evoked potential (F-VEP), and histopathologically confirm its reliability.DESIGN: A randomized control trial.SETTINGS: Department of Ophthalmology, Xi'an Fourth Hospital; Xi'an Institute of Ocular Fundus Diseases.MATERIALS: The experiments were carried out in the research room of Xi'an Institute of Ocular Fundus Diseases from February 2005 to May 2006. Thirty healthy male SD rats of 4-5 weeks old, weighing 140-160 g,were provided by the animal experimental center of the Fourth Military Medical University of Chinese PLA [SCXK (Military)2002-005], and those without eye disease examined by slit lamp and direct ophthalmoscope after mydriasis were enrolled. The conditions for feeding mice without special pathogen were strictly followed.The rats were randomly divided into blank control group (n =5), laser group (n =5), hematoporphyrin derivative (HPD) group and AION group (n =15), each group was numbered randomly. For each rat, the right eye was taken as the experimental eye, and the left one as the control one.METHODS: In the AION group, the rats were injected with HPD (10 mg/kg) via caudal vein, and then the optic discs were exposed to krypton red (647 nm, 80 mV) for 120 s, and the rats were in avoidance of light for 2 weeks postoperatively. Rats in the laser group were only exposed to krypton red (647 nm, 80 mV) for 120 s, and in avoidance of light for 2 weeks postoperatively; Those in the HPD group were only

  2. Spatial autocorrelation method using AR model; Kukan jiko sokanho eno AR model no tekiyo

    Energy Technology Data Exchange (ETDEWEB)

    Yamamoto, H; Obuchi, T; Saito, T [Iwate University, Iwate (Japan). Faculty of Engineering

    1996-05-01

    Examination was made about the applicability of the AR model to the spatial autocorrelation (SAC) method, which analyzes the surface wave phase velocity in a microtremor, for the estimation of the underground structure. In this examination, microtremor data recorded in Morioka City, Iwate Prefecture, was used. In the SAC method, a spatial autocorrelation function with the frequency as a variable is determined from microtremor data observed by circular arrays. Then, the Bessel function is adapted to the spatial autocorrelation coefficient with the distance between seismographs as a variable for the determination of the phase velocity. The result of the AR model application in this study and the results of the conventional BPF and FFT method were compared. It was then found that the phase velocities obtained by the BPF and FFT methods were more dispersed than the same obtained by the AR model. The dispersion in the BPF method is attributed to the bandwidth used in the band-pass filter and, in the FFT method, to the impact of the bandwidth on the smoothing of the cross spectrum. 2 refs., 7 figs.

  3. Establishment and characterization of Roberts syndrome and SC phocomelia model medaka (Oryzias latipes).

    Science.gov (United States)

    Morita, Akihiro; Nakahira, Kumiko; Hasegawa, Taeko; Uchida, Kaoru; Taniguchi, Yoshihito; Takeda, Shunichi; Toyoda, Atsushi; Sakaki, Yoshiyuki; Shimada, Atsuko; Takeda, Hiroyuki; Yanagihara, Itaru

    2012-06-01

    Roberts syndrome and SC phocomelia (RBS/SC) are genetic autosomal recessive syndromes caused by establishment of cohesion 1 homolog 2 ( ESCO 2) mutation. RBS/SC appear to have a variety of clinical features, even with the same mutation of the ESCO2 gene. Here, we established and genetically characterized a medaka model of RBS/SC by reverse genetics. The RBS/SC model was screened from a mutant medaka library produced by the Targeting Induced Local Lesions in Genomes method. The medaka mutant carrying the homozygous mutation at R80S in the conserved region of ESCO2 exhibited clinical variety (i.e. developmental arrest with craniofacial and chromosomal abnormalities and embryonic lethality) as characterized in RBS/SC. Moreover, widespread apoptosis and downregulation of some gene expression, including notch1a, were detected in the R80S mutant. The R80S mutant is the animal model for RBS/SC and a valuable resource that provides the opportunity to extend knowledge of ESCO2. Downregulation of some gene expression in the R80S mutant is an important clue explaining non-correlation between genotype and phenotype in RBS/SC. © 2012 The Authors Development, Growth & Differentiation © 2012 Japanese Society of Developmental Biologists.

  4. Establishment of an orthotopic lung cancer model in nude mice and its evaluation by spiral CT.

    Science.gov (United States)

    Liu, Xiang; Liu, Jun; Guan, Yubao; Li, Huiling; Huang, Liyan; Tang, Hailing; He, Jianxing

    2012-04-01

    To establish a simple and highly efficient orthotopic animal model of lung cancer cell line A549 and evaluate the growth pattern of intrathoracic tumors by spiral CT. A549 cells (5×10(6) mL(-1)) were suspended and inoculated into the right lung of BALB/c nude mice via intrathoracic injection. Nude mice were scanned three times each week by spiral CT after inoculation of lung cancer cell line A549. The survival time and body weight of nude mice as well as tumor invasion and metastasis were examined. Tissue was collected for subsequent histological assay after autopsia of mice. The tumor-forming rate of the orthotopic lung cancer model was 90%. The median survival time was 30.7 (range, 20-41) days. The incidence of tumor metastasis was 100%. The mean tumor diameter and the average CT value gradually increased in a time-dependent manner. The method of establishing the orthotopic lung cancer model through transplanting A549 cells into the lung of nude mice is simple and highly successful. Spiral CT can be used to evaluate intrathoracic tumor growth in nude mice vividly and dynamically.

  5. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

    Science.gov (United States)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2016-02-01

    This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

  6. Establishment and evaluation of a rat model of inhalation lung injury induced by ship smog

    Directory of Open Access Journals (Sweden)

    Xin-xin DUAN

    2018-03-01

    Full Text Available Objective To establish and evaluate a rat model of inhalation lung injury induced by ship smog. Methods A rat model of inhalation lung injury was established by analyzing the composition of ship materials after combustion. Forty- two healthy male Wistar rats were randomly divided into normal control group and 2, 6, 12, 24, 48 and 72h groups (6 eachafter inhalation, these rats were killed at each time point, and the changes of arterial blood gas, coagulation function, the lung water content (% were detected. Macroscopic and microscopic changes in lung tissues were observed to judge the degree of lung injury. Results The main components after combustion of 7 kinds of nonmetal materials on ship included CO, CO2, H2S, NOx and other harmful gases in this study, AIKE in one gas detector was used to monitor O2, CO, CO2 and H2S, and their concentrations remained relatively stable within 15 minutes, and the injury time was 15 minutes. The rats presented with shortness of breath and mouth breathing. Smoke inhalation caused a significant hypoxemia, the concentration of blood COHb reached a peak value 2h and the lung water content (% did 6h after inhalation (P<0.05. It is metabolic acidosis in the early stage after inhalation, but metabolic acidosis combined with respiratory acidosis in the later period. Histopathological observation showed diffuse hemorrhage, edema and inflammatory cell infiltration in the lung tissue as manifestations of lung injury, and the injury did not recover at 72h after inhalation, the change of blood coagulation function was not statistically significant. Conclusion A rat model of inhalation lung injury induced by ship smog has been successfully established, and has the advantages of easy replication, stability and reliability, thus can be used to research and treat inhalation lung injury induced by ship smog in naval war environment and other cases. DOI: 10.11855/j.issn.0577-7402.2018.03.14

  7. Modelling shallow landslide susceptibility by means of a subsurface flow path connectivity index and estimates of soil depth spatial distribution

    Directory of Open Access Journals (Sweden)

    C. Lanni

    2012-11-01

    Full Text Available Topographic index-based hydrological models have gained wide use to describe the hydrological control on the triggering of rainfall-induced shallow landslides at the catchment scale. A common assumption in these models is that a spatially continuous water table occurs simultaneously across the catchment. However, during a rainfall event isolated patches of subsurface saturation form above an impeding layer and their hydrological connectivity is a necessary condition for lateral flow initiation at a point on the hillslope.

    Here, a new hydrological model is presented, which allows us to account for the concept of hydrological connectivity while keeping the simplicity of the topographic index approach. A dynamic topographic index is used to describe the transient lateral flow that is established at a hillslope element when the rainfall amount exceeds a threshold value allowing for (a development of a perched water table above an impeding layer, and (b hydrological connectivity between the hillslope element and its own upslope contributing area. A spatially variable soil depth is the main control of hydrological connectivity in the model. The hydrological model is coupled with the infinite slope stability model and with a scaling model for the rainfall frequency–duration relationship to determine the return period of the critical rainfall needed to cause instability on three catchments located in the Italian Alps, where a survey of soil depth spatial distribution is available. The model is compared with a quasi-dynamic model in which the dynamic nature of the hydrological connectivity is neglected. The results show a better performance of the new model in predicting observed shallow landslides, implying that soil depth spatial variability and connectivity bear a significant control on shallow landsliding.

  8. Establishment of a blunt impact-induced brain injury model in rabbits

    OpenAIRE

    LI Kui; CAO Yun-xing; YANG Yong-qiang; YIN Zhi-yong; ZHAO Hui; WANG Li-jun

    2012-01-01

    【Abstract】 Objective: To establish an animal model to replicate the blunt impact brain injury in forensic medicine. Methods: Twenty-four New Zealand white rabbits were randomly divided into control group (n=4), minor injury group (n=10) and severe injury group (n=10). Based on the BIM-Ⅱ Horizontal Bio-impact Machine, self-designed iron bar was used to produce blunt brain injury. Two rabbits from each injury group were randomly selected to monitor the change of in...

  9. [Etiological analysis and establishment of a discriminant model for lower respiratory tract infections in hospitalized patients].

    Science.gov (United States)

    Chen, Y S; Lin, X H; Li, H R; Hua, Z D; Lin, M Q; Huang, W S; Yu, T; Lyu, H Y; Mao, W P; Liang, Y Q; Peng, X R; Chen, S J; Zheng, H; Lian, S Q; Hu, X L; Yao, X Q

    2017-12-12

    Objective: To analyze the pathogens of lower respiratory tract infection(LRTI) including bacterial, viral and mixed infection, and to establish a discriminant model based on clinical features in order to predict the pathogens. Methods: A total of 243 hospitalized patients with lower respiratory tract infections were enrolled in Fujian Provincial Hospital from April 2012 to September 2015. The clinical data and airway (sputum and/or bronchoalveolar lavage) samples were collected. Microbes were identified by traditional culture (for bacteria), loop-mediated isothermal amplification(LAMP) and gene sequencing (for bacteria and atypical pathogen), or Real-time quantitative polymerase chain reaction (Real-time PCR)for viruses. Finally, a discriminant model was established by using the discriminant analysis methods to help to predict bacterial, viral and mixed infections. Results: Pathogens were detected in 53.9% (131/243) of the 243 cases.Bacteria accounted for 23.5%(57/243, of which 17 cases with the virus, 1 case with Mycoplasma pneumoniae and virus), mainly Pseudomonas Aeruginosa and Klebsiella Pneumonia. Atypical pathogens for 4.9% (12/243, of which 3 cases with the virus, 1 case of bacteria and viruses), all were mycoplasma pneumonia. Viruses for 34.6% (84/243, of which 17 cases of bacteria, 3 cases with Mycoplasma pneumoniae, 1 case with Mycoplasma pneumoniae and bacteria) of the cases, mainly Influenza A virus and Human Cytomegalovirus, and other virus like adenovirus, human parainfluenza virus, respiratory syncytial virus, human metapneumovirus, human boca virus were also detected fewly. Seven parameters including mental status, using antibiotics prior to admission, complications, abnormal breath sounds, neutrophil alkaline phosphatase (NAP) score, pneumonia severity index (PSI) score and CRUB-65 score were enrolled after univariate analysis, and discriminant analysis was used to establish the discriminant model by applying the identified pathogens as the

  10. Establishment and identification of a rabbit model of peritoneal carcinomatosis from gastric cancer

    International Nuclear Information System (INIS)

    Mei, Lie-Jun; Yang, Xiao-Jun; Tang, Li; Hassan, Alaa Hammed al-shammaa; Yonemura, Yutaka; Li, Yan

    2010-01-01

    Gastric cancer peritoneal carcinomatosis is a common clinical problem, but there are no suitable large animal models to study this problem. This study was to establish a stable rabbit peritoneal carcinomatosis model of gastric cancer using VX2 tumor, and analyze the clinico-pathological features. VX2 tumor was implanted into 36 New Zealand rabbits by 3 methods: laparotomic orthotopic injection of cancer cells into the submucosal layer of the stomach (Group A), laparotomic implantation of tumor tissue into the greater omentum immediately beneath the gastric antrum (Group B), and percutaneous injection of tumor cells directly into the peritoneal cavity (Group C), 12 rabbits in each group. The animals were closely observed and detailed clinico-pathological studies were conducted. The success rates of peritoneal carcinomatosis formation were 100% (12/12), 91.7% (11/12) and 58.3% (7/12), respectively, for Groups A, B and C (P = 0.019, A versus C; P = 0.077, B versus C; P = 0.500, A versus B, Fisher's exact test). Two weeks after submucosal cancer cells injection in Group A, ulcerative gastric cancer with peritoneal carcinomatosis showed typical VX2 tumor pathology, with widespread intraperitoneal metastatic nodules, bloody ascites and perspicuous pulmonary metastases. The clinico-pathological progression pattern was very similar to patients of advanced gastric cancer with peritoneal carcinomatosis. Groups B and C showed similar pattern of cancer progression, but less aggressive. First large animal model of peritoneal carcinomatosis from gastric cancer has been established by laparotomic orthotopic injection of VX2 cancer cells into the submucosal layer of the stomach, providing a more suitable model for surgical interventional studies. The clinico-pathological features of this model resemble human peritoneal carcinomatosis

  11. Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

    Directory of Open Access Journals (Sweden)

    Goovaerts Pierre

    2004-07-01

    Full Text Available Abstract Background Complete Spatial Randomness (CSR is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new

  12. New model for gastroenteropancreatic large-cell neuroendocrine carcinoma: establishment of two clinically relevant cell lines.

    Directory of Open Access Journals (Sweden)

    Andreas Krieg

    Full Text Available Recently, a novel WHO-classification has been introduced that divided gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN according to their proliferation index into G1- or G2-neuroendocrine tumors (NET and poorly differentiated small-cell or large-cell G3-neuroendocrine carcinomas (NEC. Our knowledge on primary NECs of the GEP-system is limited due to the rarity of these tumors and chemotherapeutic concepts of highly aggressive NEC do not provide convincing results. The aim of this study was to establish a reliable cell line model for NEC that could be helpful in identifying novel druggable molecular targets. Cell lines were established from liver (NEC-DUE1 or lymph node metastases (NEC-DUE2 from large cell NECs of the gastroesophageal junction and the large intestine, respectively. Morphological characteristics and expression of neuroendocrine markers were extensively analyzed. Chromosomal aberrations were mapped by array comparative genomic hybridization and DNA profiling was analyzed by DNA fingerprinting. In vitro and in vivo tumorigenicity was evaluated and the sensitivity against chemotherapeutic agents assessed. Both cell lines exhibited typical morphological and molecular features of large cell NEC. In vitro and in vivo experiments demonstrated that both cell lines retained their malignant properties. Whereas NEC-DUE1 and -DUE2 were resistant to chemotherapeutic drugs such as cisplatin, etoposide and oxaliplatin, a high sensitivity to 5-fluorouracil was observed for the NEC-DUE1 cell line. Taken together, we established and characterized the first GEP large-cell NEC cell lines that might serve as a helpful tool not only to understand the biology of these tumors, but also to establish novel targeted therapies in a preclinical setup.

  13. Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

    Science.gov (United States)

    Miller, L. D.; Tom, C.; Nualchawee, K.

    1977-01-01

    A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

  14. Estimating the Impact of Urbanization on Air Quality in China Using Spatial Regression Models

    OpenAIRE

    Fang, Chuanglin; Liu, Haimeng; Li, Guangdong; Sun, Dongqi; Miao, Zhuang

    2015-01-01

    Urban air pollution is one of the most visible environmental problems to have accompanied China’s rapid urbanization. Based on emission inventory data from 2014, gathered from 289 cities, we used Global and Local Moran’s I to measure the spatial autorrelation of Air Quality Index (AQI) values at the city level, and employed Ordinary Least Squares (OLS), Spatial Lag Model (SAR), and Geographically Weighted Regression (GWR) to quantitatively estimate the comprehensive impact and spatial variati...

  15. A spatial modeling approach to identify potential butternut restoration sites in Mammoth Cave National Park

    Science.gov (United States)

    Thompson, L.M.; Van Manen, F.T.; Schlarbaum, S.E.; DePoy, M.

    2006-01-01

    Incorporation of disease resistance is nearly complete for several important North American hardwood species threatened by exotic fungal diseases. The next important step toward species restoration would be to develop reliable tools to delineate ideal restoration sites on a landscape scale. We integrated spatial modeling and remote sensing techniques to delineate potential restoration sites for Butternut (Juglans cinerea L.) trees, a hardwood species being decimated by an exotic fungus, in Mammoth Cave National Park (MCNP), Kentucky. We first developed a multivariate habitat model to determine optimum Butternut habitats within MCNP. Habitat characteristics of 54 known Butternut locations were used in combination with eight topographic and land use data layers to calculate an index of habitat suitability based on Mahalanobis distance (D2). We used a bootstrapping technique to test the reliability of model predictions. Based on a threshold value for the D2 statistic, 75.9% of the Butternut locations were correctly classified, indicating that the habitat model performed well. Because Butternut seedlings require extensive amounts of sunlight to become established, we used canopy cover data to refine our delineation of favorable areas for Butternut restoration. Areas with the most favorable conditions to establish Butternut seedlings were limited to 291.6 ha. Our study provides a useful reference on the amount and location of favorable Butternut habitat in MCNP and can be used to identify priority areas for future Butternut restoration. Given the availability of relevant habitat layers and accurate location records, our approach can be applied to other tree species and areas. ?? 2006 Society for Ecological Restoration International.

  16. Matrix Methods and Models of Economic Analysis in the Marketing Activity of Higher Educational Establishments

    Directory of Open Access Journals (Sweden)

    Natalia Stebliuk

    2018-05-01

    Full Text Available On the present stage of the development of educational environment, it is necessary to use the scientific tools for understanding the market patterns of the interaction of demand and supply of educational services, which will allow not only to navigate the consumer preferences but also to form them. It is in these circumstances that it is extremely important to study changes in the volume of demand for educational services in order to adapt them to the system of higher education. The aim of the article is to substantiate the theoretical positions and develop practical recommendations for the definition of the competitive marketing strategy of higher education organizations in the market of educational services with the help of modern approaches and methods of economic-mathematical modeling. The practical significance of the obtained results is the introduction of methodological provisions for forecasting the demand and supply of educational services for higher educational establishments. The complexity and interdependence of managerial problems in the system of higher education require new ideas and approaches, which necessitates the search for new definite solutions, namely: the research paper offers the method of optimal distribution of budgetary places of the university by means of practical application of the theory of system constraints and the theory of fuzzy sets. Along with that, the calculation of the optimal number of students of the corresponding specialty with the help of cluster analysis has been carried out. In addition, an important place for improvement and development is taken by the economics and mathematical methods and methods of linear programming, they are effective means of identifying the most influential factors in achieving the goals of a higher educational establishment and justifying the marketing strategy of its development in modern conditions. To predict the quantitative values of social and economic indicators

  17. Thematic and spatial resolutions affect model-based predictions of tree species distribution.

    Science.gov (United States)

    Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

    2013-01-01

    Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

  18. Establishment of a rat model of portal vein ligation combined with in situ splitting.

    Science.gov (United States)

    Yao, Libin; Li, Chonghui; Ge, Xinlan; Wang, Hongdong; Xu, Kesen; Zhang, Aiqun; Dong, Jiahong

    2014-01-01

    Portal vein ligation (PVL) combined with in situ splitting (ISS) has been shown to induce remarkable liver regeneration in patients. The purpose of this study was to establish a model of PVL+ISS in rats for exploring the possible mechanisms of liver regeneration using these techniques. Rats were randomly assigned to three experimental groups: selective PVL, selective PVL+ISS and sham operation. The hepatic regeneration rate (HRR), Ki-67, liver biochemical determinations and histopathology were assessed at 24, 48, and 72 h and 7 days after the operation. The microcirculation of the median lobes before and after ISS was examined by laser speckle contrast imaging. Meanwhile, cytokines such as TNF-α, IL-6, HGF and HSP70 in regenerating liver lobes at 24 h was investigated by RT-PCR and ELISA. The HRR of PVL+ISS was much higher than that of the PVL at 72 h and 7 days after surgery (pprotein levels of TNF-α, IL-6 and HGF in regenerating liver lobes were higher in the PVL+ISS than the PVL alone. The higher HRR in the PVL+ISS compared with the PVL confirmed that we had successfully established a PVL+ISS model in rats. The possible mechanisms included the reduced microcirculation blood perfusion of the left median lobe and up-regulation of cytokines in the regenerating lobes after ISS.

  19. Establishment and characterization of a differentiated epithelial cell culture model derived from the porcine cervix uteri

    Directory of Open Access Journals (Sweden)

    Miessen Katrin

    2012-03-01

    Full Text Available Abstract Background Cervical uterine epithelial cells maintain a physiological and pathogen-free milieu in the female mammalian reproductive tract and are involved in sperm-epithelium interaction. Easily accessible, differentiated model systems of the cervical epithelium are not yet available to elucidate the underlying molecular mechanisms within these highly specialized cells. Therefore, the aim of the study was to establish a cell culture of the porcine cervical epithelium representing in vivo-like properties of the tissue. Results We tested different isolation methods and culture conditions and validated purity of the cultured cells by immunohistochemistry against keratins. We could reproducibly culture pure epithelial cells from cervical tissue explants. Based on a morphology score and the WST-1 Proliferation Assay, we optimized the growth medium composition. Primary porcine cervical cells performed best in conditioned Ham's F-12, containing 10% FCS, EGF and insulin. After cultivation in an air-liquid interface for three weeks, the cells showed a discontinuously multilayered phenotype. Finally, differentiation was validated via immunohistochemistry against beta catenin. Mucopolysaccharide production could be shown via alcian blue staining. Conclusions We provide the first suitable protocol to establish a differentiated porcine epithelial model of the cervix uteri, based on easily accessible cells using slaughterhouse material.

  20. Establishing an in vivo model of canine prostate carcinoma using the new cell line CT1258

    International Nuclear Information System (INIS)

    Fork, Melani AM; Bullerdiek, Jörn; Nolte, Ingo; Escobar, Hugo Murua; Soller, Jan T; Sterenczak, Katharina A; Willenbrock, Saskia; Winkler, Susanne; Dorsch, Martina; Reimann-Berg, Nicola; Hedrich, Hans J

    2008-01-01

    Prostate cancer is a frequent finding in man. In dogs, malignant disease of the prostate is also of clinical relevance, although it is a less common diagnosis. Even though there are numerous differences in origin and development of the disease, man and dog share many similarities in the pathological presentation. For this reason, the dog might be a useful animal model for prostate malignancies in man. Although prostate cancer is of great importance in veterinary medicine as well as in comparative medicine, there are only few cell lines available. Thus, it was the aim of the present study to determine whether the formerly established prostate carcinoma cell line CT1258 is a suitable tool for in vivo testing, and to distinguish the growth pattern of the induced tumours. For characterisation of the in vivo behaviour of the in vitro established canine prostate carcinoma cell line CT1258, cells were inoculated in 19 NOD.CB17-Prkdc Scid /J (in the following: NOD-Scid) mice, either subcutaneously or intraperitoneally. After sacrifice, the obtained specimens were examined histologically and compared to the pattern of the original tumour in the donor. Cytogenetic investigation was performed. The cell line CT 1258 not only showed to be highly tumourigenic after subcutaneous as well as intraperitoneal inoculation, but also mimicked the behaviour of the original tumour. Tumours induced by inoculation of the cell line CT1258 resemble the situation in naturally occurring prostate carcinoma in the dog, and thus could be used as in vivo model for future studies

  1. Establishment and characterization of a differentiated epithelial cell culture model derived from the porcine cervix uteri.

    Science.gov (United States)

    Miessen, Katrin; Einspanier, Ralf; Schoen, Jennifer

    2012-03-19

    Cervical uterine epithelial cells maintain a physiological and pathogen-free milieu in the female mammalian reproductive tract and are involved in sperm-epithelium interaction. Easily accessible, differentiated model systems of the cervical epithelium are not yet available to elucidate the underlying molecular mechanisms within these highly specialized cells. Therefore, the aim of the study was to establish a cell culture of the porcine cervical epithelium representing in vivo-like properties of the tissue. We tested different isolation methods and culture conditions and validated purity of the cultured cells by immunohistochemistry against keratins. We could reproducibly culture pure epithelial cells from cervical tissue explants. Based on a morphology score and the WST-1 Proliferation Assay, we optimized the growth medium composition. Primary porcine cervical cells performed best in conditioned Ham's F-12, containing 10% FCS, EGF and insulin. After cultivation in an air-liquid interface for three weeks, the cells showed a discontinuously multilayered phenotype. Finally, differentiation was validated via immunohistochemistry against beta catenin. Mucopolysaccharide production could be shown via alcian blue staining. We provide the first suitable protocol to establish a differentiated porcine epithelial model of the cervix uteri, based on easily accessible cells using slaughterhouse material.

  2. [Establishment of model of traditional Chinese medicine injections post-marketing safety monitoring].

    Science.gov (United States)

    Guo, Xin-E; Zhao, Yu-Bin; Xie, Yan-Ming; Zhao, Li-Cai; Li, Yan-Feng; Hao, Zhe

    2013-09-01

    To establish a nurse based post-marketing safety surveillance model for traditional Chinese medicine injections (TCMIs). A TCMIs safety monitoring team and a research hospital team engaged in the research, monitoring processes, and quality control processes were established, in order to achieve comprehensive, timely, accurate and real-time access to research data, to eliminate errors in data collection. A triage system involving a study nurse, as the first point of contact, clinicians and clinical pharmacists was set up in a TCM hospital. Following the specified workflow involving labeling of TCM injections and using improved monitoring forms it was found that there were no missing reports at the ratio of error was zero. A research nurse as the first and main point of contact in post-marketing safety monitoring of TCM as part of a triage model, ensures that research data collected has the characteristics of authenticity, accuracy, timeliness, integrity, and eliminate errors during the process of data collection. Hospital based monitoring is a robust and operable process.

  3. Establishment and application of rat model of acute β-irradiated skin injury

    International Nuclear Information System (INIS)

    Shen Guoliang; Lu Xing'an; Tang Jun; Wang Xiuzhen; Wu Shiliang; Tian Ye

    2006-01-01

    Objective: To establish an experimental rat model of acute β-irradiated skin injury and to study the effects of superoxide dismutase (SOD) on wound healing. Methods: Areas of buttock skin (20 mm x 40 mm) of 40 male SD rats were irradiated with 45 Gy/β-rays generated by linear accelerator, and then the forty rats were divided into two groups randomly: treatment group administrated with SOD (n=20) and control group administrated with normal saline (NS) (n=20). The wound healing time and rate were observed. The pathological changes were observed by light microscopy. The expressions of VEGF (vascular endothelial growth factor) and bFGF (basic fibroblast growth factor) were determined by SP immunohistochemical method. Results: The deep second-degree burns was observed following 45 Gy irradiation. The wound healing time in treatment group was shorter than that of the control group (P<0.05). Strongly positive (+ + +) expression of VEGF, bFGF in treatment group and positive (+ +) expression of VEGF, bFGF in the control group were observed 6 weeks, 7 weeks and 8 weeks after the irradiation, while only weakly positive (+) expressions of VEGF and bFGF in both groups 4 weeks, 5 weeks and 9 weeks after the irradiation. Conclusions: The wound model of acute β-irradiated skin injury in rat was established and used in study of the effect of medicine on wound healing. SOD can promote the wound healing of acute β-irradiated skin injury. (authors)

  4. Establishment of tunnel-boring machine disk cutter rock-breaking model from energy perspective

    Directory of Open Access Journals (Sweden)

    Liwei Song

    2015-12-01

    Full Text Available As the most important cutting tools during tunnel-boring machine tunneling construction process, V-type disk cutter’s rock-breaking mechanism has been researched by many scholars all over the world. Adopting finite element method, this article focused on the interaction between V-type disk cutters and the intact rock to carry out microscopic parameter analysis methods: first, the stress model of rock breaking was established through V-type disk cutter motion trajectory analysis; second, based on the incremental theorem of the elastic–plastic theory, the strain model of the relative changes of rock displacement during breaking process was created. According to the principle of admissible work by energy method of the elastic–plastic theory to analyze energy transfer rules in the process of breaking rock, rock-breaking force of the V-type disk cutter could be regarded as the external force in the rock system. Finally, by taking the rock system as the reference object, the total potential energy equivalent model of rock system was derived to obtain the forces of the three directions acting on V-type disk cutter during the rock-breaking process. This derived model, which has been proved to be effective and scientific through comparisons with some original force models and by comparative analysis with experimental data, also initiates a new research strategy taking the view of the micro elastic–plastic theory to study the rock-breaking mechanism.

  5. Establishment of atherosclerotic model and USPIO enhanced MRI techniques study in rabbits

    International Nuclear Information System (INIS)

    Li Yonggang; Zhu Mo; Dai Yinyu; Chen Jianhua; Guo Liang; Ni Jiankun

    2010-01-01

    Objective: To explore the methods of establishment of atherosclerotic model and USPIO enhanced MRI techniques in rabbits. Methods: Thirty New Zealand male rabbits were divided randomly into two groups: 20 animals in the experiment group, 10 animals in the control group. Animal model of atherosclerosis was induced with aortic balloon endothelial injury and high-fat diet feeding. There was no intervention with the rabbits in control group. MRI examination included plan scan, USPIO enhanced black-blood sequences and white-blood sequence. The features of the plaques was analyzed in the experimental group and the effection on the image quality of different coils, sequences and parameters and a statistical study was also analyzed. Results: Animal model of atherosclerosis was successfully made in 12 rabbits and most plaques located in the abdomen aorta. There were 86 plaques within the scanning scope among which 67 plaques were positive to the Prussian blue staining. The image quality of knee joint coil was better than that of other coils. Although there was no difference in the detection of numbers of AS plaques between USPIO enhanced black-blood sequences and white-blood sequence (P > 0.05), blackblood sequences was superior to white-blood sequence in the demonstration of the components of plaque. Conclusion: The method of aortic balloon endothelial injury and high-fat diet feeding can easily establish the AS model in rabbits with a shorter period and it may be used for controlling the location of the plaques. USPIO enhanced MRI sequences has high sensitivity in the detection of the AS plauqes and can reveal the component of AS plaques. The optimization of MRI techniques is very important in the improvement of the image quality and the detection of the plaques. (authors)

  6. [Establishment of Schatzker classification digital models of tibial plateau fractures and its application on virtual surgery].

    Science.gov (United States)

    Liu, Yong-gang; Zuo, Li-xin; Pei, Guo-xian; Dai, Ke; Sang, Jing-wei

    2013-08-20

    To explore the establishment of Schatzker classification digital model of tibial plateau fractures and its application in virtual surgery. Proximal tibial of one healthy male volunteer was examined with 64-slice spiral computed tomography (CT). The data were processed by software Mimics 10.01 and a model of proximal tibia was reconstructed. According to the Schatzker classification criteria of tibial plateau fractures, each type of fracture model was simulated.Screen-captures of fracture model were saved from different directions.Each type of fracture model was exported as video mode.Fracture model was imported into FreeForm modeling system.With a force feedback device, a surgeon could conduct virtual fracture operation simulation.Utilizing the GHOST of FreeForm modeling system, the software of virtual cutting, fracture reduction and fixation was developed.With a force feedback device PHANTOM, a surgeon could manipulate virtual surgical instruments and fracture classification model and simulate surgical actions such as assembly of surgical instruments, drilling, implantation of screw, reduction of fracture, bone grafting and fracture fixation, etc. The digital fracture model was intuitive, three-dimensional and realistic and it had excellent visual effect.Fracture could be observed and charted from optional direction and angle.Fracture model could rotate 360 ° in the corresponding video mode. The virtual surgical environment had a strong sense of reality, immersion and telepresence as well as good interaction and force feedback function in the FreeForm modeling system. The user could make the corresponding decisions about surgical method and choice of internal fixation according to the specific type of tibial plateau fracture as well as repeated operational practice in virtual surgery system. The digital fracture model of Schatzker classification is intuitive, three-dimensional, realistic and dynamic. The virtual surgery systems of Schatzker classifications make

  7. Linking 3D spatial models of fuels and fire: Effects of spatial heterogeneity on fire behavior

    Science.gov (United States)

    Russell A. Parsons; William E. Mell; Peter McCauley

    2011-01-01

    Crownfire endangers fire fighters and can have severe ecological consequences. Prediction of fire behavior in tree crowns is essential to informed decisions in fire management. Current methods used in fire management do not address variability in crown fuels. New mechanistic physics-based fire models address convective heat transfer with computational fluid dynamics (...

  8. Spatial modelling of population at risk and PM 2.5 exposure index: A ...

    African Journals Online (AJOL)

    However, monitoring, spatial representation and development of associated risk indicators have been major problems undermining formulation of relevant policy on air quality. This study used ... to environmental health. Key Words: Population at risk, PM2.5; Spatial modeling, GIS, Exposure index, environmental health ...

  9. Climate Change and Agricultural Productivity in Sub-Saharan Africa: A Spatial Sample Selection Model

    NARCIS (Netherlands)

    Ward, P.S.; Florax, R.J.G.M.; Flores-Lagunes, A.

    2014-01-01

    Using spatially explicit data, we estimate a cereal yield response function using a recently developed estimator for spatial error models when endogenous sample selection is of concern. Our results suggest that yields across Sub-Saharan Africa will decline with projected climatic changes, and that

  10. Design and Establishment of Quality Model of Fundamental Geographic Information Database

    Science.gov (United States)

    Ma, W.; Zhang, J.; Zhao, Y.; Zhang, P.; Dang, Y.; Zhao, T.

    2018-04-01

    In order to make the quality evaluation for the Fundamental Geographic Information Databases(FGIDB) more comprehensive, objective and accurate, this paper studies and establishes a quality model of FGIDB, which formed by the standardization of database construction and quality control, the conformity of data set quality and the functionality of database management system, and also designs the overall principles, contents and methods of the quality evaluation for FGIDB, providing the basis and reference for carry out quality control and quality evaluation for FGIDB. This paper designs the quality elements, evaluation items and properties of the Fundamental Geographic Information Database gradually based on the quality model framework. Connected organically, these quality elements and evaluation items constitute the quality model of the Fundamental Geographic Information Database. This model is the foundation for the quality demand stipulation and quality evaluation of the Fundamental Geographic Information Database, and is of great significance on the quality assurance in the design and development stage, the demand formulation in the testing evaluation stage, and the standard system construction for quality evaluation technology of the Fundamental Geographic Information Database.

  11. Establishing a coherent and replicable measurement model of the Edinburgh Postnatal Depression Scale.

    Science.gov (United States)

    Martin, Colin R; Redshaw, Maggie

    2018-06-01

    The 10-item Edinburgh Postnatal Depression Scale (EPDS) is an established screening tool for postnatal depression. Inconsistent findings in factor structure and replication difficulties have limited the scope of development of the measure as a multi-dimensional tool. The current investigation sought to robustly determine the underlying factor structure of the EPDS and the replicability and stability of the most plausible model identified. A between-subjects design was used. EPDS data were collected postpartum from two independent cohorts using identical data capture methods. Datasets were examined with confirmatory factor analysis, model invariance testing and systematic evaluation of relational and internal aspects of the measure. Participants were two samples of postpartum women in England assessed at three months (n = 245) and six months (n = 217). The findings showed a three-factor seven-item model of the EPDS offered an excellent fit to the data, and was observed to be replicable in both datasets and invariant as a function of time point of assessment. Some EPDS sub-scale scores were significantly higher at six months. The EPDS is multi-dimensional and a robust measurement model comprises three factors that are replicable. The potential utility of the sub-scale components identified requires further research to identify a role in contemporary screening practice. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  12. Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.

    Science.gov (United States)

    Schudoma, Christian; May, Patrick; Nikiforova, Viktoria; Walther, Dirk

    2010-01-01

    The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts.

  13. Establishment and Characterization of UTI and CAUTI in a Mouse Model.

    Science.gov (United States)

    Conover, Matt S; Flores-Mireles, Ana L; Hibbing, Michael E; Dodson, Karen; Hultgren, Scott J

    2015-06-23

    Urinary tract infections (UTI) are highly prevalent, a significant cause of morbidity and are increasingly resistant to treatment with antibiotics. Females are disproportionately afflicted by UTI: 50% of all women will have a UTI in their lifetime. Additionally, 20-40% of these women who have an initial UTI will suffer a recurrence with some suffering frequent recurrences with serious deterioration in the quality of life, pain and discomfort, disruption of daily activities, increased healthcare costs, and few treatment options other than long-term antibiotic prophylaxis. Uropathogenic Escherichia coli (UPEC) is the primary causative agent of community acquired UTI. Catheter-associated UTI (CAUTI) is the most common hospital acquired infection accounting for a million occurrences in the US annually and dramatic healthcare costs. While UPEC is also the primary cause of CAUTI, other causative agents are of increased significance including Enterococcus faecalis. Here we utilize two well-established mouse models that recapitulate many of the clinical characteristics of these human diseases. For UTI, a C3H/HeN model recapitulates many of the features of UPEC virulence observed in humans including host responses, IBC formation and filamentation. For CAUTI, a model using C57BL/6 mice, which retain catheter bladder implants, has been shown to be susceptible to E. faecalis bladder infection. These representative models are being used to gain striking new insights into the pathogenesis of UTI disease, which is leading to the development of novel therapeutics and management or prevention strategies.

  14. Establishment of a hepatic cirrhosis and portal hypertension model by hepatic arterial perfusion with 80% alcohol.

    Science.gov (United States)

    Wang, Lei; He, Fu-Liang; Liu, Fu-Quan; Yue, Zhen-Dong; Zhao, Hong-Wei

    2015-08-28

    To determine the feasibility and safety of establishing a porcine hepatic cirrhosis and portal hypertension model by hepatic arterial perfusion with 80% alcohol. Twenty-one healthy Guizhou miniature pigs were randomly divided into three experimental groups and three control groups. The pigs in the three experimental groups were subjected to hepatic arterial perfusion with 7, 12 and 17 mL of 80% alcohol, respectively, while those in the three control groups underwent hepatic arterial perfusion with 7, 12 and 17 mL of saline, respectively. Hepatic arteriography and direct portal phlebography were performed on all animals before and after perfusion, and the portal venous pressure and diameter were measured before perfusion, immediately after perfusion, and at 2, 4 and 6 wk after perfusion. The following procedures were performed at different time points: routine blood sampling, blood biochemistry, blood coagulation and blood ammonia tests before surgery, and at 2, 4 and 6 wk after surgery; hepatic biopsy before surgery, within 6 h after surgery, and at 1, 2, 3, 4 and 5 wk after surgery; abdominal enhanced computed tomography examination before surgery and at 6 wk after surgery; autopsy and multi-point sampling of various liver lobes for histological examination at 6 wk after surgery. In experimental group 1, different degrees of hepatic fibrosis were observed, and one pig developed hepatic cirrhosis. In experimental group 2, there were cases of hepatic cirrhosis, different degrees of increased portal venous pressure, and intrahepatic portal venous bypass, but neither extrahepatic portal-systemic bypass circulation nor death occurred. In experimental group 3, two animals died and three animals developed hepatic cirrhosis, and different degrees of increased portal venous pressure and intrahepatic portal venous bypass were also observed, but there was no extrahepatic portal-systemic bypass circulation. It is feasible to establish an animal model of hepatic cirrhosis and

  15. The development and refinement of models of less established and more established high school environmental service-learning programs in Florida

    Science.gov (United States)

    Malikova, Yuliya

    2005-07-01

    Environmental Service-Learning (Env. S-L) appears to show great promise and practitioners tout its benefits, although there have been fewer than ten studies in this emerging area of environmental education. The overall study purpose was to describe the nature, status, and effects of Grade 9--16 Env. S-L programs in Florida, and develop descriptive models of those programs. The purpose of Phase I was to describe these programs and associated partnerships. Based on Phase I results, the purpose of Phase II was to develop, compare, and refine models for less and more established high school programs. This study involved: (1) defining the population of Florida 9--16 Env. S-L programs (Phase I); (2) developing and administering program surveys (Phase I, quantitative); (3) analyzing Phase I survey data and identifications of options for Phase II (Intermediate stage); (4) designing and implementing methodology for further data collection (Phase II, qualitative); (5) refining and finalizing program models (Phase II, descriptive); and (6) summarizing program data, changes, and comparisons. This study revealed that Env. S-L has been practiced in a variety of ways at the high school and college levels in Florida. There, the number of high school programs, and participating teachers and students has been growing. Among others, major program features include block scheduling, indirect S-L activities, external funding sources, and formal and ongoing community partnerships. Findings based on self-reported program assessment results indicate that S-L has had positive effects on students across Furco's S-L outcome domains (i.e., academic achievement/success, school participation/behavior, carrier development, personal development, interpersonal development, ethical/moral development, and development of civic responsibility). Differences existed between less established and more established Env. S-L programs. Less established programs had relatively few participating teachers

  16. Spatial prediction models for landslide hazards: review, comparison and evaluation

    Directory of Open Access Journals (Sweden)

    A. Brenning

    2005-01-01

    Full Text Available The predictive power of logistic regression, support vector machines and bootstrap-aggregated classification trees (bagging, double-bagging is compared using misclassification error rates on independent test data sets. Based on a resampling approach that takes into account spatial autocorrelation, error rates for predicting 'present' and 'future' landslides are estimated within and outside the training area. In a case study from the Ecuadorian Andes, logistic regression with stepwise backward variable selection yields lowest error rates and demonstrates the best generalization capabilities. The evaluation outside the training area reveals that tree-based methods tend to overfit the data.

  17. Predictive spatio-temporal model for spatially sparse global solar radiation data

    International Nuclear Information System (INIS)

    André, Maïna; Dabo-Niang, Sophie; Soubdhan, Ted; Ould-Baba, Hanany

    2016-01-01

    This paper introduces a new approach for the forecasting of solar radiation series at a located station for very short time scale. We built a multivariate model in using few stations (3 stations) separated with irregular distances from 26 km to 56 km. The proposed model is a spatio temporal vector autoregressive VAR model specifically designed for the analysis of spatially sparse spatio-temporal data. This model differs from classic linear models in using spatial and temporal parameters where the available predictors are the lagged values at each station. A spatial structure of stations is defined by the sequential introduction of predictors in the model. Moreover, an iterative strategy in the process of our model will select the necessary stations removing the uninteresting predictors and also selecting the optimal p-order. We studied the performance of this model. The metric error, the relative root mean squared error (rRMSE), is presented at different short time scales. Moreover, we compared the results of our model to simple and well known persistence model and those found in literature. - Highlights: • A spatio-temporal VAR forecast model is used for spatially sparse data solar. • Lags and locations are selected by an optimization strategy. • Definition of spatial ordering of predictors influences forecasting results. • The model shows a better performance predictive at 30 min ahead in our context. • Benchmarking study shows a more accurate forecast at 1 h ahead with spatio-temporal VAR.

  18. Spatial equity analysis on expressway network development in Japan: Empirical approach using the spatial computable general equilibrium model RAEM-light

    NARCIS (Netherlands)

    Koike, A.; Tavasszy, L.; Sato, K.

    2009-01-01

    The authors apply the RAEM-Light model to analyze the distribution of social benefits from expressway network projects from the viewpoint of spatial equity. The RAEM-Light model has some innovative features. The spatial behavior of producers and consumers is explicitly described and is endogenously

  19. [Establish Assessment Model of 18 Years of Age in Chinese Han Population by Mandibular Third Molar].

    Science.gov (United States)

    Fan, Fei; Dai, Xin-hua; Wang, Liang; Li, Yuan; Zhang, Kui; Deng, Zhen-hua

    2016-02-01

    To explore the value of estimating chronologic age based on the grades of mandibular third molar development. To evaluate whether mandibular third molar could be used as an indicator for estimating the age under or over 18 years. The mineralization status of mandibular third molar of 1 845 individuals aged 10 - 30 was graded and marked based on Demirjian's classification of grades reformed by Orhan. Gender difference was examined by t-test. A cubic regression model was established to analyze the correlation between third molar and chronologic age. Each grade of age cumulative distribution diagram and ROC curve was respectively performed to evaluate the relationship between third molar and the age of 18. Using Bayes discriminant analysis, an equation was established for estimating the age of 18. The inner-rater reliability was 0.903. Statistical analysis showed a moderate correlation between age and grade. Significant differences of both genders were found only in grade D and H (P Third molar development shows a high correlation with age, and combined with other indicators, it can be used to estimate the age of 18.

  20. Establishment of primary cultures for mouse ameloblasts as a model of their lifetime

    International Nuclear Information System (INIS)

    Suzawa, Tetsuo; Itoh, Nao; Takahashi, Naoyuki; Katagiri, Takenobu; Morimura, Naoko; Kobayashi, Yasuna; Yamamoto, Toshinori; Kamijo, Ryutaro

    2006-01-01

    To understand how the properties of ameloblasts are spatiotemporally regulated during amelogenesis, two primary cultures of ameloblasts in different stages of differentiation were established from mouse enamel epithelium. Mouse primary ameloblasts (MPAs) prepared from immature enamel epithelium (MPA-I) could proliferate, whereas those from mature enamel epithelium (MPA-M) could not. MPA-M but not MPA-I caused apoptosis during culture. The mRNA expression of amelogenin, a marker of immature ameloblasts, was down-regulated, and that of enamel matrix serine proteiase-1, a marker of mature ameloblasts, was induced in MPA-I during culture. Using green fluorescence protein as a reporter, a visualized reporter system was established to analyze the promoter activity of the amelogenin gene. The region between -1102 bp and -261 bp was required for the reporter expression in MPA-I. These results suggest that MPAs are valuable in vitro models for investigation of ameloblast biology, and that the visualized system is useful for promoter analysis in MPAs

  1. Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

    Science.gov (United States)

    Schumann, Andreas; Oppel, Henning

    2017-04-01

    To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark

  2. Revealing spatially heterogeneous relaxation in a model nanocomposite

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, Shiwang; Bocharova, Vera [Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Mirigian, Stephen; Schweizer, Kenneth S. [Department of Materials Science and Chemistry, Frederick Seitz Materials Research Laboratory, University of Illinois, Urbana, Illinois 61801 (United States); Carrillo, Jan-Michael Y.; Sumpter, Bobby G. [Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Sokolov, Alexei P., E-mail: sokolov@utk.edu [Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Chemistry, Department of Physics and Astronomy, University of Tennessee, Knoxville, Tennessee 37996 (United States)

    2015-11-21

    The detailed nature of spatially heterogeneous dynamics of glycerol-silica nanocomposites is unraveled by combining dielectric spectroscopy with atomistic simulation and statistical mechanical theory. Analysis of the spatial mobility gradient shows no “glassy” layer, but the α-relaxation time near the nanoparticle grows with cooling faster than the α-relaxation time in the bulk and is ∼20 times longer at low temperatures. The interfacial layer thickness increases from ∼1.8 nm at higher temperatures to ∼3.5 nm upon cooling to near bulk T{sub g}. A real space microscopic description of the mobility gradient is constructed by synergistically combining high temperature atomistic simulation with theory. Our analysis suggests that the interfacial slowing down arises mainly due to an increase of the local cage scale barrier for activated hopping induced by enhanced packing and densification near the nanoparticle surface. The theory is employed to predict how local surface densification can be manipulated to control layer dynamics and shear rigidity over a wide temperature range.

  3. A spatial ecosystem and populations dynamics model (SEAPODYM) Modeling of tuna and tuna-like populations

    Science.gov (United States)

    Lehodey, Patrick; Senina, Inna; Murtugudde, Raghu

    2008-09-01

    An enhanced version of the spatial ecosystem and population dynamics model SEAPODYM is presented to describe spatial dynamics of tuna and tuna-like species in the Pacific Ocean at monthly resolution over 1° grid-boxes. The simulations are driven by a bio-physical environment predicted from a coupled ocean physical-biogeochemical model. This new version of SEAPODYM includes expanded definitions of habitat indices, movements, and natural mortality based on empirical evidences. A thermal habitat of tuna species is derived from an individual heat budget model. The feeding habitat is computed according to the accessibility of tuna predator cohorts to different vertically migrating and non-migrating micronekton (mid-trophic) functional groups. The spawning habitat is based on temperature and the coincidence of spawning fish with presence or absence of predators and food for larvae. The successful larval recruitment is linked to spawning stock biomass. Larvae drift with currents, while immature and adult tuna can move of their own volition, in addition to being advected by currents. A food requirement index is computed to adjust locally the natural mortality of cohorts based on food demand and accessibility to available forage components. Together these mechanisms induce bottom-up and top-down effects, and intra- (i.e. between cohorts) and inter-species interactions. The model is now fully operational for running multi-species, multi-fisheries simulations, and the structure of the model allows a validation from multiple data sources. An application with two tuna species showing different biological characteristics, skipjack ( Katsuwonus pelamis) and bigeye ( Thunnus obesus), is presented to illustrate the capacity of the model to capture many important features of spatial dynamics of these two different tuna species in the Pacific Ocean. The actual validation is presented in a companion paper describing the approach to have a rigorous mathematical parameter optimization

  4. Comparative analysis of elements and models of implementation in local-level spatial plans in Serbia

    Directory of Open Access Journals (Sweden)

    Stefanović Nebojša

    2017-01-01

    Full Text Available Implementation of local-level spatial plans is of paramount importance to the development of the local community. This paper aims to demonstrate the importance of and offer further directions for research into the implementation of spatial plans by presenting the results of a study on models of implementation. The paper describes the basic theoretical postulates of a model for implementing spatial plans. A comparative analysis of the application of elements and models of implementation of plans in practice was conducted based on the spatial plans for the local municipalities of Arilje, Lazarevac and Sremska Mitrovica. The analysis includes four models of implementation: the strategy and policy of spatial development; spatial protection; the implementation of planning solutions of a technical nature; and the implementation of rules of use, arrangement and construction of spaces. The main results of the analysis are presented and used to give recommendations for improving the elements and models of implementation. Final deliberations show that models of implementation are generally used in practice and combined in spatial plans. Based on the analysis of how models of implementation are applied in practice, a general conclusion concerning the complex character of the local level of planning is presented and elaborated. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 36035: Spatial, Environmental, Energy and Social Aspects of Developing Settlements and Climate Change - Mutual Impacts and Grant no. III 47014: The Role and Implementation of the National Spatial Plan and Regional Development Documents in Renewal of Strategic Research, Thinking and Governance in Serbia

  5. Establishment of a general NAFLD scoring system for rodent models and comparison to human liver pathology.

    Directory of Open Access Journals (Sweden)

    Wen Liang

    Full Text Available The recently developed histological scoring system for non-alcoholic fatty liver disease (NAFLD by the NASH Clinical Research Network (NASH-CRN has been widely used in clinical settings, but is increasingly employed in preclinical research as well. However, it has not been systematically analyzed whether the human scoring system can directly be converted to preclinical rodent models. To analyze this, we systematically compared human NAFLD liver pathology, using human liver biopsies, with liver pathology of several NAFLD mouse models. Based upon the features pertaining to mouse NAFLD, we aimed at establishing a modified generic scoring system that is applicable to broad spectrum of rodent models.The histopathology of NAFLD was analyzed in several different mouse models of NAFLD to define generic criteria for histological assessment (preclinical scoring system. For validation of this scoring system, 36 slides of mouse livers, covering the whole spectrum of NAFLD, were blindly analyzed by ten observers. Additionally, the livers were blindly scored by one observer during two separate assessments longer than 3 months apart.The criteria macrovesicular steatosis, microvesicular steatosis, hepatocellular hypertrophy, inflammation and fibrosis were generally applicable to rodent NAFLD. The inter-observer reproducibility (evaluated using the Intraclass Correlation Coefficient between the ten observers was high for the analysis of macrovesicular steatosis and microvesicular steatosis (ICC = 0.784 and 0.776, all p<0.001, respectively and moderate for the analysis of hypertrophy and inflammation (ICC = 0.685 and 0.650, all p<0.001, respectively. The intra-observer reproducibility between the different observations of one observer was high for the analysis of macrovesicular steatosis, microvesicular steatosis and hypertrophy (ICC = 0.871, 0.871 and 0.896, all p<0.001, respectively and very high for the analysis of inflammation (ICC = 0.931, p

  6. Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows

    Science.gov (United States)

    Gay-Balmaz, François; Holm, Darryl D.

    2018-01-01

    Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.

  7. Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows

    Science.gov (United States)

    Gay-Balmaz, François; Holm, Darryl D.

    2018-06-01

    Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.

  8. Scaling local species-habitat relations to the larger landscape with a hierarchical spatial count model

    Science.gov (United States)

    Thogmartin, W.E.; Knutson, M.G.

    2007-01-01

    Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species. ?? 2006 Springer Science+Business Media B.V.

  9. Assessing NARCCAP climate model effects using spatial confidence regions

    Directory of Open Access Journals (Sweden)

    J. P. French

    2017-07-01

    Full Text Available We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

  10. Establishing the long-term fuel management scheme using point reactivity model

    International Nuclear Information System (INIS)

    Park, Yong-Soo; Kim, Jae-Hak; Lee, Young-Ouk; Song, Jae-Woong; Zee, Sung-Kyun

    1994-01-01

    A new approach to establish the long-term fuel management scheme is presented in this paper. The point reactivity model is used to predict the core average reactivity. An attempt to calculate batchwise power fraction is introduced through the two-dimensional nodal power algorithm based on the modified one-group diffusion equation and the number of fuel assemblies on the core periphery. Suggested is an empirical formula to estimate the radial leakage reactivity with ripe core design experience reflected. This approach predicts the cycle lengths and the discharge burnups of individual fuel batches up to an equilibrium core when the proper input data such as batch enrichment, batch size, type and content of burnable poison and reloading strategies are given. Eight benchmark calculations demonstrate that the new approach used in this study is reasonably accurate and highly efficient for the purpose of scoping calculation when compared with design code predictions. (author)

  11. Establishing an in vivo model of canine prostate carcinoma using the new cell line CT1258

    Directory of Open Access Journals (Sweden)

    Winkler Susanne

    2008-08-01

    Full Text Available Abstract Background Prostate cancer is a frequent finding in man. In dogs, malignant disease of the prostate is also of clinical relevance, although it is a less common diagnosis. Even though there are numerous differences in origin and development of the disease, man and dog share many similarities in the pathological presentation. For this reason, the dog might be a useful animal model for prostate malignancies in man. Although prostate cancer is of great importance in veterinary medicine as well as in comparative medicine, there are only few cell lines available. Thus, it was the aim of the present study to determine whether the formerly established prostate carcinoma cell line CT1258 is a suitable tool for in vivo testing, and to distinguish the growth pattern of the induced tumours. Methods For characterisation of the in vivo behaviour of the in vitro established canine prostate carcinoma cell line CT1258, cells were inoculated in 19 NOD.CB17-PrkdcScid/J (in the following: NOD-Scid mice, either subcutaneously or intraperitoneally. After sacrifice, the obtained specimens were examined histologically and compared to the pattern of the original tumour in the donor. Cytogenetic investigation was performed. Results The cell line CT 1258 not only showed to be highly tumourigenic after subcutaneous as well as intraperitoneal inoculation, but also mimicked the behaviour of the original tumour. Conclusion Tumours induced by inoculation of the cell line CT1258 resemble the situation in naturally occurring prostate carcinoma in the dog, and thus could be used as in vivo model for future studies.

  12. Establishment of a rat model of portal vein ligation combined with in situ splitting.

    Directory of Open Access Journals (Sweden)

    Libin Yao

    Full Text Available BACKGROUND: Portal vein ligation (PVL combined with in situ splitting (ISS has been shown to induce remarkable liver regeneration in patients. The purpose of this study was to establish a model of PVL+ISS in rats for exploring the possible mechanisms of liver regeneration using these techniques. MATERIALS AND METHODS: Rats were randomly assigned to three experimental groups: selective PVL, selective PVL+ISS and sham operation. The hepatic regeneration rate (HRR, Ki-67, liver biochemical determinations and histopathology were assessed at 24, 48, and 72 h and 7 days after the operation. The microcirculation of the median lobes before and after ISS was examined by laser speckle contrast imaging. Meanwhile, cytokines such as TNF-α, IL-6, HGF and HSP70 in regenerating liver lobes at 24 h was investigated by RT-PCR and ELISA. RESULTS: The HRR of PVL+ISS was much higher than that of the PVL at 72 h and 7 days after surgery (p<0.01. The expression of Ki-67 in hepatocytes in the regenerating liver lobe was stronger in the PVL+ISS group than in the PVL group at 48 and 72 h (p<0.01. There was a significant reduction in microcirculation blood perfusion of the left median lobe before and after ISS. Liver biochemical determinations and histopathology demonstrated more severe hepatocyte injury in the PVL+ISS group. Both the mRNA levels of TNF-α and IL-6 and the protein levels of TNF-α, IL-6 and HGF in regenerating liver lobes were higher in the PVL+ISS than the PVL alone. CONCLUSIONS: The higher HRR in the PVL+ISS compared with the PVL confirmed that we had successfully established a PVL+ISS model in rats. The possible mechanisms included the reduced microcirculation blood perfusion of the left median lobe and up-regulation of cytokines in the regenerating lobes after ISS.

  13. Establishment of Orthotopic Xuanwei Lung Cancer SCID Mouse Model 
and Analysis of Biological Properties

    Directory of Open Access Journals (Sweden)

    Yongchun ZHOU

    2012-08-01

    Full Text Available Background and objective The incidence of Xuanwei lung cancer ranks first in China, and its pathogenesis requires in-depth investigation. This study aims to establish an orthotopic Xuanwei lung cancer severe combined immunodeficiency (SCID mouse model and to provide a basic experimental platform for further study. Methods The Xuanwei lung cancer cell line XWLC-05 was inoculated into the lung tissue of SCID mice in high and low doses. The tumor formation rates, tumor characteristics, spontaneous metastases, and survival times of the mice were observed, taking a subcutaneously transplanted tumor as control. Results The tumor formation rates of the orthotopic transplantation of lung cancer cells in high and low doses were 81% and 83%, respectively, among which mice in the high-dose group appeared cachectic on day 13. Extensive invasion and adhesion were observed in the contralateral lung and thoracic cavity, but no distant metastasis was exhibited. Mice with low-dose cells in the orthotopic transplantation group appeared cachectic and distant metastasis occurred on day 25. The tumor formation rates in the subcutaneous inoculation group by the high and low doses of cells were 100% and 94.5%, respectively, and no distant metastasis was observed. The rate of metastasis within the orthotopic transplantation group and between the orthotopic and subcutaneous inoculation groups showed a significant difference (P<0.05. A significant difference was indicated by the survival rate within and between the groups (P<0.001. Conclusion We successfully established an orthotopic XWLC SCID mouse model, which lays the foundation for a more in-depth study.

  14. [Establishment of the Mathematical Model for PMI Estimation Using FTIR Spectroscopy and Data Mining Method].

    Science.gov (United States)

    Wang, L; Qin, X C; Lin, H C; Deng, K F; Luo, Y W; Sun, Q R; Du, Q X; Wang, Z Y; Tuo, Y; Sun, J H

    2018-02-01

    To analyse the relationship between Fourier transform infrared (FTIR) spectrum of rat's spleen tissue and postmortem interval (PMI) for PMI estimation using FTIR spectroscopy combined with data mining method. Rats were sacrificed by cervical dislocation, and the cadavers were placed at 20 ℃. The FTIR spectrum data of rats' spleen tissues were taken and measured at different time points. After pretreatment, the data was analysed by data mining method. The absorption peak intensity of rat's spleen tissue spectrum changed with the PMI, while the absorption peak position was unchanged. The results of principal component analysis (PCA) showed that the cumulative contribution rate of the first three principal components was 96%. There was an obvious clustering tendency for the spectrum sample at each time point. The methods of partial least squares discriminant analysis (PLS-DA) and support vector machine classification (SVMC) effectively divided the spectrum samples with different PMI into four categories (0-24 h, 48-72 h, 96-120 h and 144-168 h). The determination coefficient ( R ²) of the PMI estimation model established by PLS regression analysis was 0.96, and the root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV) were 9.90 h and 11.39 h respectively. In prediction set, the R ² was 0.97, and the root mean square error of prediction (RMSEP) was 10.49 h. The FTIR spectrum of the rat's spleen tissue can be effectively analyzed qualitatively and quantitatively by the combination of FTIR spectroscopy and data mining method, and the classification and PLS regression models can be established for PMI estimation. Copyright© by the Editorial Department of Journal of Forensic Medicine.

  15. Establishment of animal model for the analysis of cancer cell metastasis during radiotherapy

    International Nuclear Information System (INIS)

    Park, Jong Kuk; Jang, Su Jin; Kang, Sung Wook; Park, Sunhoo; Hwang, Sang-Gu; Kim, Wun-Jae; Kang, Joo Hyun; Um, Hong-Duck

    2012-01-01

    Γ-Ionizing radiation (IR) therapy is one of major therapeutic tools in cancer treatment. Nevertheless, γ-IR therapy failed due to occurrence of metastasis, which constitutes a significant obstacle in cancer treatment. The main aim of this investigation was to construct animal model which present metastasis during radiotherapy in a mouse system in vivo and establishes the molecular mechanisms involved. The C6L transfectant cell line expressing firefly luciferase (fLuc) was treated with γ-IR, followed by immunoblotting, zymography and invasion assay in vitro. We additionally employed the C6L transfectant cell line to construct xenografts in nude mice, which were irradiated with γ-IR. Irradiated xenograft-containing mice were analyzed via survival curves, measurement of tumor size, and bioluminescence imaging in vivo and ex vivo. Metastatic lesions in organs of mice were further assessed using RT-PCR, H & E staining and immunohistochemistry. γ-IR treatment of C6L cells induced epithelial-mesenchymal transition (EMT) and increased cell invasion. In irradiated xenograft-containing mice, tumor sizes were decreased dramatically and survival rates extended. Almost all non-irradiated xenograft-containing control mice had died within 4 weeks. However, we also observed luminescence signals in about 22.5% of γ-IR-treated mice. Intestines or lungs of mice displaying luminescence signals contained several lesions, which expressed the fLuc gene and presented histological features of cancer tissues as well as expression of EMT markers. These findings collectively indicate that occurrences of metastases during γ-IR treatment accompanied induction of EMT markers, including increased MMP activity. Establishment of a murine metastasis model during γ-IR treatment should aid in drug development against cancer metastasis and increase our understanding of the mechanisms underlying the metastatic process

  16. Establishment and characterization of a novel murine model of pancreatic cancer cachexia.

    Science.gov (United States)

    Michaelis, Katherine A; Zhu, Xinxia; Burfeind, Kevin G; Krasnow, Stephanie M; Levasseur, Peter R; Morgan, Terry K; Marks, Daniel L

    2017-10-01

    Cachexia is a complex metabolic and behavioural syndrome lacking effective therapies. Pancreatic ductal adenocarcinoma (PDAC) is one of the most important conditions associated with cachexia, with >80% of PDAC patients suffering from the condition. To establish the cardinal features of a murine model of PDAC-associated cachexia, we characterized the effects of implanting a pancreatic tumour cell line from a syngeneic C57BL/6 KRAS G12D P53 R172H Pdx-Cre +/+ (KPC) mouse. Male and female C57BL/6 mice were inoculated subcutaneously, intraperitoneally, or orthotopically with KPC tumour cells. We performed rigorous phenotypic, metabolic, and behavioural analysis of animals over the course of tumour development. All routes of administration produced rapidly growing tumours histologically consistent with moderate to poorly differentiated PDAC. The phenotype of this model was dependent on route of administration, with orthotopic and intraperitoneal implantation inducing more severe cachexia than subcutaneous implantation. KPC tumour growth decreased food intake, decreased adiposity and lean body mass, and decreased locomotor activity. Muscle catabolism was observed in both skeletal and cardiac muscles, but the dominant catabolic pathway differed between these tissues. The wasting syndrome in this model was accompanied by hypothalamic inflammation, progressively decreasing brown and white adipose tissue uncoupling protein 1 (Ucp1) expression, and increased peripheral inflammation. Haematological and endocrine abnormalities included neutrophil-dominant leukocytosis and anaemia, and decreased serum testosterone. Syngeneic KPC allografts are a robust model for studying cachexia, which recapitulate key features of the PDAC disease process and induce a wide array of cachexia manifestations. This model is therefore ideally suited for future studies exploring the physiological systems involved in cachexia and for preclinical studies of novel therapies. © 2017 The Authors. Journal

  17. Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

    Directory of Open Access Journals (Sweden)

    David W Redding

    Full Text Available Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT, to a spatial Bayesian SDM method (fitted using R-INLA, when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account

  18. Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

    Science.gov (United States)

    Redding, David W; Lucas, Tim C D; Blackburn, Tim M; Jones, Kate E

    2017-01-01

    Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT), to a spatial Bayesian SDM method (fitted using R-INLA), when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account for spatial

  19. Multivariate Receptor Models for Spatially Correlated Multipollutant Data

    KAUST Repository

    Jun, Mikyoung; Park, Eun Sug

    2013-01-01

    The goal of multivariate receptor modeling is to estimate the profiles of major pollution sources and quantify their impacts based on ambient measurements of pollutants. Traditionally, multivariate receptor modeling has been applied to multiple air

  20. Flexible hydrological modeling - Disaggregation from lumped catchment scale to higher spatial resolutions

    Science.gov (United States)

    Tran, Quoc Quan; Willems, Patrick; Pannemans, Bart; Blanckaert, Joris; Pereira, Fernando; Nossent, Jiri; Cauwenberghs, Kris; Vansteenkiste, Thomas

    2015-04-01

    Based on an international literature review on model structures of existing rainfall-runoff and hydrological models, a generalized model structure is proposed. It consists of different types of meteorological components, storage components, splitting components and routing components. They can be spatially organized in a lumped way, or on a grid, spatially interlinked by source-to-sink or grid-to-grid (cell-to-cell) routing. The grid size of the model can be chosen depending on the application. The user can select/change the spatial resolution depending on the needs and/or the evaluation of the accuracy of the model results, or use different spatial resolutions in parallel for different applications. Major research questions addressed during the study are: How can we assure consistent results of the model at any spatial detail? How can we avoid strong or sudden changes in model parameters and corresponding simulation results, when one moves from one level of spatial detail to another? How can we limit the problem of overparameterization/equifinality when we move from the lumped model to the spatially distributed model? The proposed approach is a step-wise one, where first the lumped conceptual model is calibrated using a systematic, data-based approach, followed by a disaggregation step where the lumped parameters are disaggregated based on spatial catchment characteristics (topography, land use, soil characteristics). In this way, disaggregation can be done down to any spatial scale, and consistently among scales. Only few additional calibration parameters are introduced to scale the absolute spatial differences in model parameters, but keeping the relative differences as obtained from the spatial catchment characteristics. After calibration of the spatial model, the accuracies of the lumped and spatial models were compared for peak, low and cumulative runoff total and sub-flows (at downstream and internal gauging stations). For the distributed models, additional

  1. Housing price prediction: parametric versus semi-parametric spatial hedonic models

    Science.gov (United States)

    Montero, José-María; Mínguez, Román; Fernández-Avilés, Gema

    2018-01-01

    House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.

  2. Emergent spatial structures in flocking models: a dynamical system insight.

    Science.gov (United States)

    Caussin, Jean-Baptiste; Solon, Alexandre; Peshkov, Anton; Chaté, Hugues; Dauxois, Thierry; Tailleur, Julien; Vitelli, Vincenzo; Bartolo, Denis

    2014-04-11

    We show that hydrodynamic theories of polar active matter generically possess inhomogeneous traveling solutions. We introduce a unifying dynamical-system framework to establish the shape of these intrinsically nonlinear patterns, and show that they correspond to those hitherto observed in experiments and numerical simulation: periodic density waves, and solitonic bands, or polar-liquid droplets both cruising in isotropic phases. We elucidate their respective multiplicity and mutual relations, as well as their existence domain.

  3. Impact of precipitation spatial resolution on the hydrological response of an integrated distributed water resources model

    DEFF Research Database (Denmark)

    Fu, Suhua; Sonnenborg, Torben; Jensen, Karsten Høgh

    2011-01-01

    Precipitation is a key input variable to hydrological models, and the spatial variability of the input is expected to impact the hydrological response predicted by a distributed model. In this study, the effect of spatial resolution of precipitation on runoff , recharge and groundwater head...... of the total catchment and runoff discharge hydrograph at watershed outlet. On the other hand, groundwater recharge and groundwater head were both aff ected. The impact of the spatial resolution of precipitation input is reduced with increasing catchment size. The effect on stream discharge is relatively low...... was analyzed in the Alergaarde catchment in Denmark. Six different precipitation spatial resolutions were used as inputs to a physically based, distributed hydrological model, the MIKE SHE model. The results showed that the resolution of precipitation input had no apparent effect on annual water balance...

  4. Spatial aspects affecting acidification factors in European acidification modelling

    NARCIS (Netherlands)

    Bellekom, S.; Hettelingh, J. -P.; Aben, J.

    Plain linear models have recently been used in methodologies to model fate and transport for assessing acidification in life cycle impact assessment (LCIA), or in support of air pollution abatement policies. These models originate from a statistical analysis of the relationship between inputs and

  5. The establishment of a multiple sclerosis model for clinical MRI study

    International Nuclear Information System (INIS)

    Zhang Haiqin; Li Kuncheng; Yu Chunshui; Ma Jia; Qin Wen; Ji Zhijuan; Piao Yueshan

    2009-01-01

    Objective: To establish a rat model of multiple sclerosis (MS) for clinical MRI study. Methods: The Lewis (LEW) rats were immunized by myelin oligodendrocyte glycoprotein peptide 35-55 (MOG 35-55 ) emulsified with complete Freunds adjuvant/incomplete Freunds adjuvant. Twenty LEW rats were selected. Group A rats were 5, group B rats were 10 and control group rats were 5. MRI and histopathology analysis were observed on group A and control group, and clinical course were observed on group B. The clinical course was observed and the brain and spinal cord of EAE rats were scanned on 3.0 T MR system with quadrature wrist joint coil on the third day of the acute stage of disease. The T 2 /T 1 weighted images and Gadolinium enhanced T 1 weighted images in 3D volume were obtained respectively. The magnetization transfer ratio (MTR) images were calculated with special software in workstation. Rats were sacrificed within 24 h after MRI, and the histopathological changes of central nervous system were observed. Results: Twice immunization of MOG 35-55 was used and a rat model of MS was successfully induced with all the rats. The model had varied clinical symptoms. The lesions of central nervous system at acute stage on group A (5 rats) were depicted on MRI. The lesions located in the brain and the spinal cord with main manifestation of hyperintensity on T 2 weighed images and hypointensity on T 1 weighted images. Some lesions had Gd-DTPA enhancement, and the value of MTR decreased. The infiltration of mononuclear cells around blood vessels and the extensive distribution of lesions of demyelination in brain and spinal cord were verified by histological examination. Conclusions: Twice immunization of MOG 35-55 could produce a rat model which mimics MS. The model is stable with higher incidence, and the antigen is cheap and obtained easily. The intravital monitoring of brain and spinal cord lesions in MOG 35-55 induced rat model is possible on 3.0 T clinical whole- body MR

  6. [The replacement therapy of rPTH(1-84) in established rat model of hypothyroidism].

    Science.gov (United States)

    Ding, Zhiwei; Li, Tiancheng; Liu, Yuhe; Xiao, Shuifang

    2015-12-01

    To investigate the replacement therapy of rPTH(1-84) (recombinant human parathyroid hormone (1-84)) to hypothyroidism in established rat model. Rat model of hypothyroidism was established by resecting parathyroids. A total of 30 rats with removal of parathyroids were divided into 6 groups randomly, 5 in each group, and applied respectively with saline injection (negative control group), calcitriol treatment (positive control group) and quadripartite PTH administration with dose of 20, 40, 80 and 160 µg/kg (experimental groups). Saline and rPTH(1-84) were injected subcutaneously daily. Calcitriol was gavaged once a day. Sham-operation was conducted in 5 rats of negative control group. To verify the authenticity of the rat model with hypothyroidism, the serum was insolated centrifugally from rat blood that was obtained from angular vein at specific time to measure calcium and phosphorus concentration. Urine in 12 hours was collected by metabolic cages and the calcium concentration was measured. After 10-week drug treatment, the experiment was terminated and bilateral femoral bone and L2-5 lumbar vertebra were removed from rats. Bone mineral density (BMD)of bilateral femoral bone and lumbar vertebra was analyzed by dual X-ray absorptiometry (DXA). The concentration of bone alkaline phosphatase (BALP) in serum was determined by radioimmunoassay. The rat model with hypothyroidism was obtained by excising parathyroid gland and was verified by monitoring calcium and phosphorus concentration subsequently. Administration of rPTH(1-84) in the dose of 80 or 160 µg/kg made serum calcium and phosphorus back to normal levels, with no significant difference between the doses (P>0.05). The BMD in each group of rats with rPTH(1-84) administration was increased significantly (P0.05). Calcium and phosphorus return to normal level by administration of rPTH(1-84) in the dose of 80 µg/kg or 160 µg/kg, with increase in BMD. Calcitriol can return the level of calcium to normal and

  7. Spatial modeling on the upperstream of the Citarum watershed: An application of geoinformatics

    Science.gov (United States)

    Ningrum, Windy Setia; Widyaningsih, Yekti; Indra, Tito Latif

    2017-03-01

    The Citarum watershed is the longest and the largest watershed in West Java, Indonesia, located at 106°51'36''-107°51' E and 7°19'-6°24'S across 10 districts, and serves as the water supply for over 15 million people. In this area, the water criticality index is concerned to reach the balance between water supply and water demand, so that in the dry season, the watershed is still able to meet the water needs of the society along the Citarum river. The objective of this research is to evaluate the water criticality index of Citarum watershed area using spatial model to overcome the spatial dependencies in the data. The result of Lagrange multiplier diagnostics for spatial dependence results are LM-err = 34.6 (p-value = 4.1e-09) and LM-lag = 8.05 (p-value = 0.005), then modeling using Spatial Lag Model (SLM) and Spatial Error Model (SEM) were conducted. The likelihood ratio test show that both of SLM dan SEM model is better than OLS model in modeling water criticality index in Citarum watershed. The AIC value of SLM and SEM model are 78.9 and 51.4, then the SEM model is better than SLM model in predicting water criticality index in Citarum water