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. Extinction rates of established spatial populations

    Science.gov (United States)

    Meerson, Baruch; Sasorov, Pavel V.

    2011-01-01

    This paper deals with extinction of an isolated population caused by intrinsic noise. We model the population dynamics in a “refuge” as a Markov process which involves births and deaths on discrete lattice sites and random migrations between neighboring sites. In extinction scenario I, the zero population size is a repelling fixed point of the on-site deterministic dynamics. In extinction scenario II, the zero population size is an attracting fixed point, corresponding to what is known in ecology as the Allee effect. Assuming a large population size, we develop a WKB (Wentzel-Kramers-Brillouin) approximation to the master equation. The resulting Hamilton’s equations encode the most probable path of the population toward extinction and the mean time to extinction. In the fast-migration limit these equations coincide, up to a canonical transformation, with those obtained, in a different way, by Elgart and Kamenev [Phys. Rev. EPHYADX1539-375510.1103/PhysRevE.70.041106 70, 041106 (2004)]. We classify possible regimes of population extinction with and without an Allee effect and for different types of refuge, and solve several examples analytically and numerically. For a very strong Allee effect, the extinction problem can be mapped into the overdamped limit of the theory of homogeneous nucleation due to Langer [Ann. Phys. (NY)APNYA60003-491610.1016/0003-4916(69)90153-5 54, 258 (1969)]. In this regime, and for very long systems, we predict an optimal refuge size that maximizes the mean time to extinction.

  3. 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 ...

  4. Building dynamic spatial environmental models

    NARCIS (Netherlands)

    Karssenberg, D.J.

    2003-01-01

    An environmental model is a representation or imitation of complex natural phenomena that can be discerned by human cognitive processes. This thesis deals with the type of environmental models referred to as dynamic spatial environmental models. The word ‘spatial’ refers to the geographic domain whi

  5. Regulation mechanisms in spatial stochastic development models

    CERN Document Server

    Finkelshtein, Dmitri

    2008-01-01

    The aim of this paper is to analyze different regulation mechanisms in spatial continuous stochastic development models. We describe the density behavior for models with global mortality and local establishment rates. We prove that the local self-regulation via a competition mechanism (density dependent mortality) may suppress a unbounded growth of the averaged density if the competition kernel is superstable.

  6. 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.

  7. Modeling for spatial multilevel structural data

    Science.gov (United States)

    Min, Suqin; He, Xiaoqun

    2013-03-01

    The traditional multilevel model assumed independence between groups. However, the datasets grouped by geographical units often has spatial dependence. The individual is influenced not only by its region but also by the adjacent regions, and level-2 residual distribution assumption of traditional multilevel model is violated. In order to deal with such spatial multilevel data, we introduce spatial statistics and spatial econometric models into multilevel model, and apply spatial parameters and adjacency matrix in traditional level-2 model to reflect the spatial autocorrelation. Spatial lag model express spatial effects. We build spatial multilevel model which consider both multilevel thinking and spatial correlation.

  8. Spatial monopoly of multi-establishment firms : An empirical study for supermarkets in the Netherlands

    NARCIS (Netherlands)

    Stelder, T.M.

    2012-01-01

    Multi-establishment firms can create local spatial monopolies in the form of clusters of own establishments without competition. This paper examines the existence of spatial monopolies for Dutch supermarkets in 2009. It is found that 23 percent of consumers can be qualified as being locked-in in a s

  9. 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

  10. 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

  11. 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.

  12. 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...

  13. How to Establish Clinical Prediction Models

    Directory of Open Access Journals (Sweden)

    Yong-ho Lee

    2016-03-01

    Full Text Available A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice.

  14. Emergence of Strange Spatial Pattern in a Spatial Epidemic Model

    Institute of Scientific and Technical Information of China (English)

    SUN Gui-Quan; JIN Zhen; LIU Quan-Xing; LI Li

    2008-01-01

    Pattern formation of a spatial epidemic model with nonlinear incidence rate kI2 S/ (1 + αI2) is investigated. Our results show that strange spatial dynamics, i.e., filament-like pattern, can be obtained by both mathematical analysis and numerical simulation, which are different from the previous results in the spatial epidemic model such as stripe-like or spotted or coexistence of both pattern and so on. The obtained results well extend the finding of pattern formation in the epidemic model and may well explain the distribution of the infected of some epidemic.

  15. 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).

  16. 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

  17. Indoorgml - a Standard for Indoor Spatial Modeling

    Science.gov (United States)

    Li, Ki-Joune

    2016-06-01

    With recent progress of mobile devices and indoor positioning technologies, it becomes possible to provide location-based services in indoor space as well as outdoor space. It is in a seamless way between indoor and outdoor spaces or in an independent way only for indoor space. However, we cannot simply apply spatial models developed for outdoor space to indoor space due to their differences. For example, coordinate reference systems are employed to indicate a specific position in outdoor space, while the location in indoor space is rather specified by cell number such as room number. Unlike outdoor space, the distance between two points in indoor space is not determined by the length of the straight line but the constraints given by indoor components such as walls, stairs, and doors. For this reason, we need to establish a new framework for indoor space from fundamental theoretical basis, indoor spatial data models, and information systems to store, manage, and analyse indoor spatial data. In order to provide this framework, an international standard, called IndoorGML has been developed and published by OGC (Open Geospatial Consortium). This standard is based on a cellular notion of space, which considers an indoor space as a set of non-overlapping cells. It consists of two types of modules; core module and extension module. While core module consists of four basic conceptual and implementation modeling components (geometric model for cell, topology between cells, semantic model of cell, and multi-layered space model), extension modules may be defined on the top of the core module to support an application area. As the first version of the standard, we provide an extension for indoor navigation.

  18. 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.

  19. [Prediction of spatial distribution of forest carbon storage in Heilongjiang Province using spatial error model].

    Science.gov (United States)

    Liu, Chang; Li, Feng-Ri; Zhen, Zhen

    2014-10-01

    Abstract: Based on the data from Chinese National Forest Inventory (CNFI) and Key Ecological Benefit Forest Monitoring plots (5075 in total) in Heilongjiang Province in 2010 and concurrent meteorological data coming from 59 meteorological stations located in Heilongjiang, Jilin and Inner Mongolia, this paper established a spatial error model (SEM) by GeoDA using carbon storage as dependent variable and several independent variables, including diameter of living trees (DBH), number of trees per hectare (TPH), elevation (Elev), slope (Slope), and product of precipitation and temperature (Rain_Temp). Global Moran's I was computed for describing overall spatial autocorrelations of model results at different spatial scales. Local Moran's I was calculated at the optimal bandwidth (25 km) to present spatial distribution residuals. Intra-block spatial variances were computed to explain spatial heterogeneity of residuals. Finally, a spatial distribution map of carbon storage in Heilongjiang was visualized based on predictions. The results showed that the distribution of forest carbon storage in Heilongjiang had spatial effect and was significantly influenced by stand, topographic and meteorological factors, especially average DBH. SEM could solve the spatial autocorrelation and heterogeneity well. There were significant spatial differences in distribution of forest carbon storage. The carbon storage was mainly distributed in Zhangguangcai Mountain, Xiao Xing'an Mountain and Da Xing'an Mountain where dense, forests existed, rarely distributed in Songnen Plains, while Wanda Mountain had moderate-level carbon storage.

  20. 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.

  1. Hepatocyte autophagy model established by physical method

    Directory of Open Access Journals (Sweden)

    ZHU Xuemin

    2016-08-01

    Full Text Available ObjectiveTo establish the autophagy model of normal human liver cell line 7702 induced by hypoxia and starvation, and to lay a foundation for further studies on the influence of autophagy on liver function. MethodsThe 7702 cells were selected and incubated with 95% air and 5% CO2 at a temperature of 37 ℃(normal control group. The Binder three-gas incubator was used, with a temperature of 37 ℃, a CO2 concentration of 5%, and an O2 concentration of 0.3% to provide a hypoxic environment, and the serum-free DMEM was used to induce starvation. These cells were divided into 6-, 12-, 18-, and 24-hour hypoxia-starvation groups. Western blot was used to measure the protein expression of Beclin 1, Atg5, and LC3 in the normal control group and experimental groups, RT-qPCR was used to measure the mRNA expression of Beclin 1 and Atg5 in each group, and after transfection of LC3 plasmid, immunofluorescence assay was used to observe autophagy in each group. An analysis of variance was used for comparison of continuous data between groups, and the least significant difference t-test was used for further comparison between any two groups; the chi-square test was used for comparison of categorical data between groups. ResultsThe 6-hour hypoxia-starvation groups had higher protein expression of Beclin 1, Atg5, and LC3 than the normal control group or other treated groups. Compared with all the other groups, the 6-hour hypoxia-starvation group showed significantly increased mRNA expression of Beclin 1 and Atg5, as well as significantly greater increases in the mRNA expression of Beclin 1 and Atg5 (all P<0.05. The hypoxia-starvation groups had significantly lower numbers of autophagosomes than the normal control group, and the 6-hour hypoxia-starvation group had the highest number of autophagosomes (all P<0.05. ConclusionHypoxia and starvation established by physical methods can successfully induce hepatocyte autophagy, which is the most remarkable at 6

  2. Integrated spatial sampling modeling of geospatial data

    Institute of Scientific and Technical Information of China (English)

    LI Lianfa; WANG Jinfeng

    2004-01-01

    Spatial sampling is a necessary and important method for extracting geospatial data and its methodology directly affects the geo-analysis results. Counter to the deficiency of separate models of spatial sampling, this article analyzes three crucial elements of spatial sampling (frame, correlation and decision diagram) and induces its general integrated model. The program of Spatial Sampling Integration (SSI) has been developed with Component Object Model (COM) to realize the general integrated model. In two practical applications, i.e. design of the monitoring network of natural disasters and sampling survey of the areas of non-cultivated land, SSI has produced accurate results at less cost, better realizing the cost-effective goal of sampling toward the geo-objects with spatial correlation. The two cases exemplify expanded application and convenient implementation of the general integrated model with inset components in an integrated environment, which can also be extended to other modeling of spatial analysis.

  3. 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.

  4. Modelling evolution in a spatial continuum

    Science.gov (United States)

    Barton, N. H.; Etheridge, A. M.; Véber, A.

    2013-01-01

    We survey a class of models for spatially structured populations which we have called spatial Λ-Fleming-Viot processes. They arise from a flexible framework for modelling in which the key innovation is that random genetic drift is driven by a Poisson point process of spatial 'events'. We demonstrate how this overcomes some of the obstructions to modelling populations which evolve in two-(and higher-) dimensional spatial continua, how its predictions match phenomena observed in data and how it fits with classical models. Finally we outline some directions for future research.

  5. Local models for spatial analysis

    CERN Document Server

    Lloyd, Christopher D

    2010-01-01

    Focusing on solutions, this second edition provides guidance to a wide variety of real-world problems. The text presents a complete introduction to key concepts and a clear mapping of the methods discussed. It also explores connections between methods. New chapters address spatial patterning in single variables and spatial relations. In addition, every chapter now includes links to key related studies. The author clearly distinguishes between local and global methods and provides more detailed coverage of geographical weighting, image texture measures, local spatial autocorrelation, and multic

  6. 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.

  7. KING GEORGE ISLAND SPATIAL DATA MODEL

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Distribution,interoperability,interactivity,component are four main features of distributed GIS.Based on the principle of hypermap,hypermedia and distributed database,the paper comes up with a kind of distributed spatial data model which is in accordance with those features of distributed GIS.The model takes catalog service as the outline of spatial information globalization,and defines data structure of hypermap node in different level.Based on the model,it is feasible to manage and process distributed spatial information,and integrate multi_source,heterogeneous spatial data into a framework.Traditionally,to retrieve and access spatial data via Internet is only by theme or map name.With the concept of the model,it is possible to retrieve,load,and link spatial data by vector_based graphics on the Internet.

  8. 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.

  9. 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

  10. Continuous-Time Modeling with Spatial Dependence

    NARCIS (Netherlands)

    Oud, J.H.L.; Folmer, H.; Patuelli, R.; Nijkamp, P.

    2012-01-01

    (Spatial) panel data are routinely modeled in discrete time (DT). However, compelling arguments exist for continuous-time (CT) modeling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete

  11. Continuous-Time Modeling with Spatial Dependence

    NARCIS (Netherlands)

    Oud, J.; Folmer, H.; Patuelli, R.; Nijkamp, P.

    (Spatial) panel data are routinely modeled in discrete time (DT). However, compelling arguments exist for continuous-time (CT) modeling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete

  12. Bayesian Spatial Modelling with R-INLA

    OpenAIRE

    Finn Lindgren; Håvard Rue

    2015-01-01

    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...

  13. Evaluating spatial patterns in hydrological modelling

    DEFF Research Database (Denmark)

    Koch, Julian

    of spatial information in a holistic assessment. Opposed, statistical measures typically only address a limited amount of spatial information. A web-based survey and a citizen science project are employed to quantify the collective perceptive skills of humans aiming at benchmarking spatial metrics...... of environmental science, such as meteorology, geostatistics or geography. In total, seven metrics are evaluated with respect to their capability to quantitatively compare spatial patterns. The human visual perception is often considered superior to computer based measures, because it integrates various dimensions...... with respect to their capability to mimic human evaluations. This PhD thesis aims at expanding the standard toolbox of spatial model evaluation with innovative metrics that adequately compare spatial patterns. Driven by the rise of more complex model structures and the increase of suitable remote sensing...

  14. A neuromorphic model of spatial lookahead planning.

    Science.gov (United States)

    Ivey, Richard; Bullock, Daniel; Grossberg, Stephen

    2011-04-01

    In order to create spatial plans in a complex and changing world, organisms need to rapidly adapt to novel configurations of obstacles that impede simple routes to goal acquisition. Some animals can mentally create successful multistep spatial plans in new visuo-spatial layouts that preclude direct, one-segment routes to goal acquisition. Lookahead multistep plans can, moreover, be fully developed before an animal executes any step in the plan. What neural computations suffice to yield preparatory multistep lookahead plans during spatial cognition of an obstructed two-dimensional scene? To address this question, we introduce a novel neuromorphic system for spatial lookahead planning in which a feasible sequence of actions is prepared before movement begins. The proposed system combines neurobiologically plausible mechanisms of recurrent shunting competitive networks, visuo-spatial diffusion, and inhibition-of-return. These processes iteratively prepare a multistep trajectory to the desired goal state in the presence of obstacles. The planned trajectory can be stored using a primacy gradient in a sequential working memory and enacted by a competitive queuing process. The proposed planning system is compared with prior planning models. Simulation results demonstrate system robustness to environmental variations. Notably, the model copes with many configurations of obstacles that lead other visuo-spatial planning models into selecting undesirable or infeasible routes. Our proposal is inspired by mechanisms of spatial attention and planning in primates. Accordingly, our simulation results are compared with neurophysiological and behavioral findings from relevant studies of spatial lookahead behavior.

  15. 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

  16. The welfare benefit of a home's location: an empirical comparison of spatial and non-spatial model estimates

    Science.gov (United States)

    Koschinsky, Julia; Lozano-Gracia, Nancy; Piras, Gianfranco

    2012-07-01

    This article compares results from non-spatial and new spatial methods to examine the reliability of welfare estimates (direct and multiplier effects) for locational housing attributes in Seattle, WA. In particular, we assess if OLS with spatial fixed effects is able to account for the spatial structure in a way that represents a viable alternative to spatial econometric methods. We find that while OLS with spatial fixed effects accounts for more of the spatial structure than simple OLS, it does not account for all of the spatial structure. It thus does not present a viable alternative to the spatial methods. Similar to existing comparisons between results from non-spatial and established spatial methods, we also find that OLS generates higher coefficient and direct effect estimates for both structural and locational housing characteristics than spatial methods do. OLS with spatial fixed effects is closer to the spatial estimates than OLS without fixed effects but remains higher. Finally, a comparison of the direct effects with locally weighted regression results highlights spatial threshold effects that are missed in the global models. Differences between spatial estimators are almost negligible in this study.

  17. Spatial Statistical Network Models for Stream and River Temperature in the Chesapeake Bay Watershed, USA

    Science.gov (United States)

    Regional temperature models are needed for characterizing and mapping stream thermal regimes, establishing reference conditions, predicting future impacts and identifying critical thermal refugia. Spatial statistical models have been developed to improve regression modeling techn...

  18. Spatial Statistical Procedures to Validate Input Data in Energy Models

    Energy Technology Data Exchange (ETDEWEB)

    Johannesson, G.; Stewart, J.; Barr, C.; Brady Sabeff, L.; George, R.; Heimiller, D.; Milbrandt, A.

    2006-01-01

    Energy modeling and analysis often relies on data collected for other purposes such as census counts, atmospheric and air quality observations, economic trends, and other primarily non-energy related uses. Systematic collection of empirical data solely for regional, national, and global energy modeling has not been established as in the abovementioned fields. Empirical and modeled data relevant to energy modeling is reported and available at various spatial and temporal scales that might or might not be those needed and used by the energy modeling community. The incorrect representation of spatial and temporal components of these data sets can result in energy models producing misleading conclusions, especially in cases of newly evolving technologies with spatial and temporal operating characteristics different from the dominant fossil and nuclear technologies that powered the energy economy over the last two hundred years. Increased private and government research and development and public interest in alternative technologies that have a benign effect on the climate and the environment have spurred interest in wind, solar, hydrogen, and other alternative energy sources and energy carriers. Many of these technologies require much finer spatial and temporal detail to determine optimal engineering designs, resource availability, and market potential. This paper presents exploratory and modeling techniques in spatial statistics that can improve the usefulness of empirical and modeled data sets that do not initially meet the spatial and/or temporal requirements of energy models. In particular, we focus on (1) aggregation and disaggregation of spatial data, (2) predicting missing data, and (3) merging spatial data sets. In addition, we introduce relevant statistical software models commonly used in the field for various sizes and types of data sets.

  19. Spatial Statistical Procedures to Validate Input Data in Energy Models

    Energy Technology Data Exchange (ETDEWEB)

    Lawrence Livermore National Laboratory

    2006-01-27

    Energy modeling and analysis often relies on data collected for other purposes such as census counts, atmospheric and air quality observations, economic trends, and other primarily non-energy-related uses. Systematic collection of empirical data solely for regional, national, and global energy modeling has not been established as in the above-mentioned fields. Empirical and modeled data relevant to energy modeling is reported and available at various spatial and temporal scales that might or might not be those needed and used by the energy modeling community. The incorrect representation of spatial and temporal components of these data sets can result in energy models producing misleading conclusions, especially in cases of newly evolving technologies with spatial and temporal operating characteristics different from the dominant fossil and nuclear technologies that powered the energy economy over the last two hundred years. Increased private and government research and development and public interest in alternative technologies that have a benign effect on the climate and the environment have spurred interest in wind, solar, hydrogen, and other alternative energy sources and energy carriers. Many of these technologies require much finer spatial and temporal detail to determine optimal engineering designs, resource availability, and market potential. This paper presents exploratory and modeling techniques in spatial statistics that can improve the usefulness of empirical and modeled data sets that do not initially meet the spatial and/or temporal requirements of energy models. In particular, we focus on (1) aggregation and disaggregation of spatial data, (2) predicting missing data, and (3) merging spatial data sets. In addition, we introduce relevant statistical software models commonly used in the field for various sizes and types of data sets.

  20. On spatially explicit models of cholera epidemics

    National Research Council Canada - National Science Library

    Bertuzzo, E; Casagrandi, R; Gatto, M; Rodriguez-Iturbe, I; Rinaldo, A

    2010-01-01

    We generalize a recently proposed model for cholera epidemics that accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having...

  1. SIMULATION MODELING SLOW SPATIALLY HETER- OGENEOUS COAGULATION

    Directory of Open Access Journals (Sweden)

    P. A. Zdorovtsev

    2013-01-01

    Full Text Available A new model of spatially inhomogeneous coagulation, i.e. formation of larger clusters by joint interaction of smaller ones, is under study. The results of simulation are compared with known analytical and numerical solutions.

  2. Spatial averaging infiltration model for layered soil

    Institute of Scientific and Technical Information of China (English)

    HU HePing; YANG ZhiYong; TIAN FuQiang

    2009-01-01

    To quantify the influences of soil heterogeneity on infiltration, a spatial averaging infiltration model for layered soil (SAI model) is developed by coupling the spatial averaging approach proposed by Chen et al. and the Generalized Green-Ampt model proposed by Jia et al. In the SAI model, the spatial heterogeneity along the horizontal direction is described by a probability distribution function, while that along the vertical direction is represented by the layered soils. The SAI model is tested on a typical soil using Monte Carlo simulations as the base model. The results show that the SAI model can directly incorporate the influence of spatial heterogeneity on infiltration on the macro scale. It is also found that the homogeneous assumption of soil hydraulic conductivity along the horizontal direction will overestimate the infiltration rate, while that along the vertical direction will underestimate the infiltration rate significantly during rainstorm periods. The SAI model is adopted in the spatial averaging hydrological model developed by the authors, and the results prove that it can be applied in the macro-scale hydrological and land surface process modeling in a promising way.

  3. Spatial averaging infiltration model for layered soil

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    To quantify the influences of soil heterogeneity on infiltration, a spatial averaging infiltration model for layered soil (SAI model) is developed by coupling the spatial averaging approach proposed by Chen et al. and the Generalized Green-Ampt model proposed by Jia et al. In the SAI model, the spatial hetero- geneity along the horizontal direction is described by a probability distribution function, while that along the vertical direction is represented by the layered soils. The SAI model is tested on a typical soil using Monte Carlo simulations as the base model. The results show that the SAI model can directly incorporate the influence of spatial heterogeneity on infiltration on the macro scale. It is also found that the homogeneous assumption of soil hydraulic conductivity along the horizontal direction will overes- timate the infiltration rate, while that along the vertical direction will underestimate the infiltration rate significantly during rainstorm periods. The SAI model is adopted in the spatial averaging hydrological model developed by the authors, and the results prove that it can be applied in the macro-scale hy- drological and land surface process modeling in a promising way.

  4. 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.

  5. Evaluating spatial patterns in hydrological modelling

    DEFF Research Database (Denmark)

    Koch, Julian

    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...... 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...

  6. Performance of Information Criteria for Spatial Models.

    Science.gov (United States)

    Lee, Hyeyoung; Ghosh, Sujit K

    2009-01-01

    Model choice is one of the most crucial aspect in any statistical data analysis. It is well known that most models are just an approximation to the true data generating process but among such model approximations it is our goal to select the "best" one. Researchers typically consider a finite number of plausible models in statistical applications and the related statistical inference depends on the chosen model. Hence model comparison is required to identify the "best" model among several such candidate models. This article considers the problem of model selection for spatial data. The issue of model selection for spatial models has been addressed in the literature by the use of traditional information criteria based methods, even though such criteria have been developed based on the assumption of independent observations. We evaluate the performance of some of the popular model selection critera via Monte Carlo simulation experiments using small to moderate samples. In particular, we compare the performance of some of the most popular information criteria such as Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Corrected AIC (AICc) in selecting the true model. The ability of these criteria to select the correct model is evaluated under several scenarios. This comparison is made using various spatial covariance models ranging from stationary isotropic to nonstationary models.

  7. Uncertainty in spatially explicit animal dispersal models

    Science.gov (United States)

    Mooij, Wolf M.; DeAngelis, Donald L.

    2003-01-01

    Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three levels of complexity: (1) an event-based binomial model that considers only the occurrence of mortality or arrival, (2) a temporally explicit exponential model that employs mortality and arrival rates, and (3) a spatially explicit grid-walk model that simulates the movement of animals through an artificial landscape. Each model was fitted to the same set of field data. A first objective of the paper is to illustrate how the maximum-likelihood method can be used in all three cases to estimate the means and confidence limits for the relevant model parameters, given a particular set of data on dispersal survival. Using this framework we show that the structure of the uncertainty for all three models is strikingly similar. In fact, the results of our unified approach imply that spatially explicit dispersal models, which take advantage of information on landscape details, suffer less from uncertainly than do simpler models. Moreover, we show that the proposed strategy of model development safeguards one from error propagation in these more complex models. Finally, our approach shows that all models related to animal dispersal, ranging from simple to complex, can be related in a hierarchical fashion, so that the various approaches to modeling such dispersal can be viewed from a unified perspective.

  8. Spatial interactions in agent-based modeling

    CERN Document Server

    Ausloos, Marcel; Merlone, Ugo

    2014-01-01

    Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or directly with each other. In such an approach, higher-order variables such as commodity prices, population dynamics or even institutions, are not exogenously specified but instead are seen as the results of interactions. It is highlighted in the chapter that the understanding of patterns emerging from such spatial interaction between agents is a key problem as much as their description through analytical or simulation means. The chapter reviews different approaches for modeling agents' behavior, taking into account either explicit spatial (lattice based) structures or networks. Some emphasis is placed on recent ABM as applied to the description of the dynamics of the geographical distribution o...

  9. A Needs Assessment Model for Establishing Personnel Training Priorities.

    Science.gov (United States)

    Gable, Robert K.; And Others

    1981-01-01

    The article presents the Special Education Needs Assessment Priorities model which establishes training priorities for both regular and special educators. The model consists of four stages: identification of competencies, development of discrepancies, setting training priorities, and resource allocation. (SB)

  10. Uncertainty in spatially explicit animal dispersal models

    NARCIS (Netherlands)

    Mooij, W.M.; DeAngelis, D.L.

    2003-01-01

    Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three level

  11. Integrated statistical modelling of spatial landslide probability

    Science.gov (United States)

    Mergili, M.; Chu, H.-J.

    2015-09-01

    Statistical methods are commonly employed to estimate spatial probabilities of landslide release at the catchment or regional scale. Travel distances and impact areas are often computed by means of conceptual mass point models. The present work introduces a fully automated procedure extending and combining both concepts to compute an integrated spatial landslide probability: (i) the landslide inventory is subset into release and deposition zones. (ii) We employ a simple statistical approach to estimate the pixel-based landslide release probability. (iii) We use the cumulative probability density function of the angle of reach of the observed landslide pixels to assign an impact probability to each pixel. (iv) We introduce the zonal probability i.e. the spatial probability that at least one landslide pixel occurs within a zone of defined size. We quantify this relationship by a set of empirical curves. (v) The integrated spatial landslide probability is defined as the maximum of the release probability and the product of the impact probability and the zonal release probability relevant for each pixel. We demonstrate the approach with a 637 km2 study area in southern Taiwan, using an inventory of 1399 landslides triggered by the typhoon Morakot in 2009. We observe that (i) the average integrated spatial landslide probability over the entire study area corresponds reasonably well to the fraction of the observed landside area; (ii) the model performs moderately well in predicting the observed spatial landslide distribution; (iii) the size of the release zone (or any other zone of spatial aggregation) influences the integrated spatial landslide probability to a much higher degree than the pixel-based release probability; (iv) removing the largest landslides from the analysis leads to an enhanced model performance.

  12. Evaluating correlative and mechanistic niche models for assessing the risk of pest establishment

    Science.gov (United States)

    Ecological niche modeling was used to assess the risk of establishment of western cherry fruit fly, Rhagoletis indifferens Curran (Diptera: Tephritidae), in sweet cherry, Prunus avium (L.) L., in the commercial cherry-growing areas of California. We integrated species occurrence records and spatial...

  13. Spatially random models, estimation theory, and robot arm dynamics

    Science.gov (United States)

    Rodriguez, G.

    1987-01-01

    Spatially random models provide an alternative to the more traditional deterministic models used to describe robot arm dynamics. These alternative models can be used to establish a relationship between the methodologies of estimation theory and robot dynamics. A new class of algorithms for many of the fundamental robotics problems of inverse and forward dynamics, inverse kinematics, etc. can be developed that use computations typical in estimation theory. The algorithms make extensive use of the difference equations of Kalman filtering and Bryson-Frazier smoothing to conduct spatial recursions. The spatially random models are very easy to describe and are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. The models can also be used to generate numerically the composite multibody system inertia matrix. This is done without resorting to the more common methods of deterministic modeling involving Lagrangian dynamics, Newton-Euler equations, etc. These methods make substantial use of human knowledge in derivation and minipulation of equations of motion for complex mechanical systems.

  14. Stochastic spatial models of plant diseases

    CERN Document Server

    Brown, D H

    2001-01-01

    I present three models of plant--pathogen interactions. The models are stochastic and spatially explicit at the scale of individual plants. For each model, I use a version of pair approximation or moment closure along with a separation of timescales argument to determine the effects of spatial clustering on threshold structure. By computing the spatial structure early in an invasion, I find explicit corrections to mean field theory. In the first chapter, I present a lattice model of a disease that is not directly lethal to its host, but affects its ability to compete with neighbors. I use a type of pair approximation to determine conditions for invasions and coexistence. In the second chapter, I study a basic SIR epidemic point process in continuous space. I implement a multiplicative moment closure scheme to compute the threshold transmission rate as a function of spatial parameters. In the final chapter, I model the evolution of pathogen resistance when two plant species share a pathogen. Evolution may lead...

  15. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    . Such systems are known to be stabilized by spatial structure. Finally, I analyse data from a large mobile phone network and show that people who are topologically close in the network have similar communication patterns. This main part of the thesis is based on six different articles, which I have co...... 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...

  16. Spatially explicit non-Mendelian diploid model

    CERN Document Server

    Lanchier, N; 10.1214/09-AAP598

    2009-01-01

    We introduce a spatially explicit model for the competition between type $a$ and type $b$ alleles. Each vertex of the $d$-dimensional integer lattice is occupied by a diploid individual, which is in one of three possible states or genotypes: $aa$, $ab$ or $bb$. We are interested in the long-term behavior of the gene frequencies when Mendel's law of segregation does not hold. This results in a voter type model depending on four parameters; each of these parameters measures the strength of competition between genes during meiosis. We prove that with or without a spatial structure, type $a$ and type $b$ alleles coexist at equilibrium when homozygotes are poor competitors. The inclusion of a spatial structure, however, reduces the parameter region where coexistence occurs.

  17. Network analysis of rat spatial cognition: behaviorally-established symmetry in a physically asymmetrical environment.

    Directory of Open Access Journals (Sweden)

    Shahaf Weiss

    Full Text Available BACKGROUND: We set out to solve two inherent problems in the study of animal spatial cognition (i What is a "place"?; and (ii whether behaviors that are not revealed as differing by one methodology could be revealed as different when analyzed using a different approach. METHODOLOGY: We applied network analysis to scrutinize spatial behavior of rats tested in either a symmetrical or asymmetrical layout of 4, 8, or 12 objects placed along the perimeter of a round arena. We considered locations as the units of the network (nodes, and passes between locations as the links within the network. PRINCIPAL FINDINGS: While there were only minor activity differences between rats tested in the symmetrical or asymmetrical object layouts, network analysis revealed substantial differences. Viewing 'location' as a cluster of stopping coordinates, the key locations (large clusters of stopping coordinates were at the objects in both layouts with 4 objects. However, in the asymmetrical layout with 4 objects, additional key locations were spaced by the rats between the objects, forming symmetry among the key locations. It was as if the rats had behaviorally imposed symmetry on the physically asymmetrical environment. Based on a previous finding that wayfinding is easier in symmetrical environments, we suggest that when the physical attributes of the environment were not symmetrical, the rats established a symmetric layout of key locations, thereby acquiring a more legible environment despite its complex physical structure. CONCLUSIONS AND SIGNIFICANCE: The present study adds a behavioral definition for "location", a term that so far has been mostly discussed according to its physical attributes or neurobiological correlates (e.g.--place and grid neurons. Moreover, network analysis enabled the assessment of the importance of a location, even when that location did not display any distinctive physical properties.

  18. Network analysis of rat spatial cognition: behaviorally-established symmetry in a physically asymmetrical environment.

    Science.gov (United States)

    Weiss, Shahaf; Yaski, Osnat; Eilam, David; Portugali, Juval; Blumenfeld-Lieberthal, Efrat

    2012-01-01

    We set out to solve two inherent problems in the study of animal spatial cognition (i) What is a "place"?; and (ii) whether behaviors that are not revealed as differing by one methodology could be revealed as different when analyzed using a different approach. We applied network analysis to scrutinize spatial behavior of rats tested in either a symmetrical or asymmetrical layout of 4, 8, or 12 objects placed along the perimeter of a round arena. We considered locations as the units of the network (nodes), and passes between locations as the links within the network. While there were only minor activity differences between rats tested in the symmetrical or asymmetrical object layouts, network analysis revealed substantial differences. Viewing 'location' as a cluster of stopping coordinates, the key locations (large clusters of stopping coordinates) were at the objects in both layouts with 4 objects. However, in the asymmetrical layout with 4 objects, additional key locations were spaced by the rats between the objects, forming symmetry among the key locations. It was as if the rats had behaviorally imposed symmetry on the physically asymmetrical environment. Based on a previous finding that wayfinding is easier in symmetrical environments, we suggest that when the physical attributes of the environment were not symmetrical, the rats established a symmetric layout of key locations, thereby acquiring a more legible environment despite its complex physical structure. The present study adds a behavioral definition for "location", a term that so far has been mostly discussed according to its physical attributes or neurobiological correlates (e.g.--place and grid neurons). Moreover, network analysis enabled the assessment of the importance of a location, even when that location did not display any distinctive physical properties.

  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. 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...

  1. Modeling Spatially Unrestricted Pedestrian Traffic on Footbridges

    DEFF Research Database (Denmark)

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

    2010-01-01

    The research into modelling walking-induced dynamic loading and its effects on footbridge structures and people using them has been intensified in the last decade after some high profile vibration serviceability failures. In particular, the crowd induced loading, characterised by spatially...... 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...

  2. Modelling spatial density using continuous wavelet transforms

    Indian Academy of Sciences (India)

    D Sudheer Reddy; N Gopal Reddy; A K Anilkumar

    2013-02-01

    Due to increase in the satelite launch activities from many countries around the world the orbital debris issue has become a major concern for the space agencies to plan a collision-free orbit design. The risk of collisions is calculated using the in situ measurements and available models. Spatial density models are useful in understanding the long-term likelihood of a collision in a particular region of space and also helpful in pre-launch orbit planning. In this paper, we present a method of estimating model parameters such as number of peaks and peak locations of spatial density model using continuous wavelets. The proposed methodology was experimented with two line element data and the results are presented.

  3. Integrating GIS and Spatial Statistical Analysis to Establish Evaluation Model of Regional Sustainable Development: A Case Study in Myingyan Myanmar%基于GIS与空间统计分析的可持续发展度量方法研究——以缅甸Myingyan District为例

    Institute of Scientific and Technical Information of China (English)

    张显峰; 崔伟宏

    2001-01-01

    利用空间信息系统所提供的强大空间数据处理和分析能力,并将之与统计分析软件包的统计分析功能进行有效的集成,建立了基于空间统计分析的可持续发展定量分析评价模型(SBSA)。从在缅甸中部Myingyan县的应用实例来看,该模型能够揭示影响Myingyan县可持续发展能力的主导因子,通过对这些因子和可持续发展综合指数的定量化、空间化的分析,为政府部门规划区域综合发展方案,制定发展政策提供很好的决策支持。%Due to the complexity of sustainable development, the selectionof index system is very difficult and all these make it tough to collect, process and interpret data for the indexes. Consequently some of the methods of SD evaluation are less operational. This paper discuss a new approach by means of which the powerful analytical functions of GIS are integrated with the statistical analysis function of statistical software to establish a spatial statistical analysis model (SBSA) for Myingyan sustainable development. This model has some advantages as follows: (1) Being able to assimilate spatial data with statistical data, (2) The number of indexes is free of limitations, so the SBSA model is powerful in its operational ablility; (3) To break the limitation of administration boundary for evaluation unit, and extract the principal factors and their spatial distribution which affect regional sustainable development potential. The implementation of SBSA model shows that three principal factors (PF) affecting the potential capacity of the sustainable development in Myingyan District are food provision, physical condition and population pressure on environment. The analysis and interpretation of the three PFs provide decision and planning support for Myingyan government.

  4. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    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....... Such systems are known to be stabilized by spatial structure. Finally, I analyse data from a large mobile phone network and show that people who are topologically close in the network have similar communication patterns. This main part of the thesis is based on six different articles, which I have co...

  5. Evolutionary establishment of moral and double moral standards through spatial interactions

    CERN Document Server

    Helbing, Dirk; Perc, Matjaz; Szabo, Gyorgy

    2010-01-01

    Situations where individuals have to contribute to joint efforts or share scarce resources are ubiquitous. Yet, without proper mechanisms to ensure cooperation, the evolutionary pressure to maximize individual success tends to create a tragedy of the commons (such as over-fishing or the destruction of our environment). This contribution addresses a number of related puzzles of human behavior with an evolutionary game theoretical approach as it has been successfully used to explain the behavior of other biological species many times, from bacteria to vertebrates. Our agent-based model distinguishes individuals applying four different behavioral strategies: non-cooperative individuals ("defectors"), cooperative individuals abstaining from punishment efforts (called "cooperators" or "second-order free-riders"), cooperators who punish non-cooperative behavior ("moralists"), and defectors, who punish other defectors despite being non-cooperative themselves ("immoralists"). By considering spatial interactions with ...

  6. 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.

  7. 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...

  8. 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...

  9. 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.

  10. Research of ERP model system of spatial data warehouse

    Institute of Scientific and Technical Information of China (English)

    CHEN Xue-long; WANG Yan-zhang

    2004-01-01

    The broad sharing of spatial information is demanded in the infrastructure construction of spatial data in our country. And the spatial data warehouse realizes the effective management and sharing of spatial information serving as an efficient tool. This article proposes ERP model system that of general-decision-oriented for constructing spatial data warehouse from the aspect of decision application. In the end of article, the construction process of spatial data warehouse based on ERP model system is discussed.

  11. Spatial Aggregation: Data Model and Implementation

    CERN Document Server

    Gomez, Leticia; Kuijpers, Bart; Vaisman, Alejandro

    2007-01-01

    Data aggregation in Geographic Information Systems (GIS) is only marginally present in commercial systems nowadays, mostly through ad-hoc solutions. In this paper, we first present a formal model for representing spatial data. This model integrates geographic data and information contained in data warehouses external to the GIS. We define the notion of geometric aggregation, a general framework for aggregate queries in a GIS setting. We also identify the class of summable queries, which can be efficiently evaluated by precomputing the overlay of two or more of the thematic layers involved in the query. We also sketch a language, denoted GISOLAP-QL, for expressing queries that involve GIS and OLAP features. In addition, we introduce Piet, an implementation of our proposal, that makes use of overlay precomputation for answering spatial queries (aggregate or not). Our experimental evaluation showed that for a certain class of geometric queries with or without aggregation, overlay precomputation outperforms R-tre...

  12. 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).

  13. 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.

  14. [Establishment and evaluation of animal model with methamphetamine poisoning].

    Science.gov (United States)

    Xu, Jing; Zhou, Xiao-Li; Zhang, Hao; Deng, Chong; Zhang, Yan; Li, Zhen

    2009-08-01

    Amphetamine-type stimulants (ATS) is the most widespread narcotics in the 21st century. The methamphetamine's intoxication mechanism, psychological dependence, drug resistance and therapeutic drug development are the hot spots in current research. Establishment of animal model with methamphetamine poisoning is the basic for the relative studies, the normalization and standardization of the animal model settles the foundation for methamphetamine's further research. This article reviews the animal model of methamphetamine poisoning in China and abroad, the brief history of the acute, subacute and chronic animal model of methamphetamine poisoning, as well as the principles and methods of the animal model establishment and its evaluation criteria. The necessity, significance and its scientific expansion of performing experimental research on the methamphetamine poisoning animal model are also discussed.

  15. Isard's contributions to spatial interaction modeling

    Science.gov (United States)

    O'Kelly, M. E.

    . This short review, surveys Isard's role in promoting what has become known as spatial interaction modeling. Some contextual information on the milieu from which his work emerged is given, together with a selected number of works that are judged to have been influenced (directly and indirectly) by his work. It is suggested that this burgeoning field owes a lot to the foundations laid in the gravity model chapter of ``Methods''. The review is supplemented by a rather extensive bibliography of additional works that are indicative of the breadth of the impact of this field.

  16. 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.

  17. Estimation of Spatial Dynamic Nonparametric Durbin Models with Fixed Effects

    Science.gov (United States)

    Qian, Minghui; Hu, Ridong; Chen, Jianwei

    2016-01-01

    Spatial panel data models have been widely studied and applied in both scientific and social science disciplines, especially in the analysis of spatial influence. In this paper, we consider the spatial dynamic nonparametric Durbin model (SDNDM) with fixed effects, which takes the nonlinear factors into account base on the spatial dynamic panel…

  18. Modeling the impact of spatial relationships on horizontal curve safety.

    Science.gov (United States)

    Findley, Daniel J; Hummer, Joseph E; Rasdorf, William; Zegeer, Charles V; Fowler, Tyler J

    2012-03-01

    The curved segments of roadways are more hazardous because of the additional centripetalforces exerted on a vehicle, driver expectations, and other factors. The safety of a curve is dependent on various factors, most notably by geometric factors, but the location of a curve in relation to other curves is also thought to influence the safety of those curves because of a driver's expectation to encounter additional curves. The link between an individual curve's geometric characteristics and its safety performance has been established, but spatial considerations are typically not included in a safety analysis. The spatial considerations included in this research consisted of four components: distance to adjacent curves, direction of turn of the adjacent curves, and radius and length of the adjacent curves. The primary objective of this paper is to quantify the spatial relationship between adjacent horizontal curves and horizontal curve safety using a crash modification factor. Doing so enables a safety professional to more accurately estimate safety to allocate funding to reduce or prevent future collisions and more efficiently design new roadway sections to minimize crash risk where there will be a series of curves along a route. The most important finding from this research is the statistical significance of spatial considerations for the prediction of horizontal curve safety. The distances to adjacent curves were found to be a reliable predictor of observed collisions. This research recommends a model which utilizes spatial considerations for horizontal curve safety prediction in addition to current Highway Safety Manual prediction capabilities using individual curve geometric features.

  19. Modeling the spatial reach of the LFP.

    Science.gov (United States)

    Lindén, Henrik; Tetzlaff, Tom; Potjans, Tobias C; Pettersen, Klas H; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

    2011-12-08

    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 of the region generating the LFP. Here, we use a detailed biophysical modeling approach to investigate the size of the contributing region by simulating the LFP from a large number of neurons around the electrode. We find that the size of the generating region depends on the neuron morphology, the synapse distribution, and the correlation in synaptic activity. For uncorrelated activity, the LFP represents cells in a small region (within a radius of a few hundred micrometers). If the LFP contributions from different cells are correlated, the size of the generating region is determined by the spatial extent of the correlated activity.

  20. Spatial Database Modeling for Indoor Navigation Systems

    Science.gov (United States)

    Gotlib, Dariusz; Gnat, Miłosz

    2013-12-01

    For many years, cartographers are involved in designing GIS and navigation systems. Most GIS applications use the outdoor data. Increasingly, similar applications are used inside buildings. Therefore it is important to find the proper model of indoor spatial database. The development of indoor navigation systems should utilize advanced teleinformation, geoinformatics, geodetic and cartographical knowledge. The authors present the fundamental requirements for the indoor data model for navigation purposes. Presenting some of the solutions adopted in the world they emphasize that navigation applications require specific data to present the navigation routes in the right way. There is presented original solution for indoor data model created by authors on the basis of BISDM model. Its purpose is to expand the opportunities for use in indoor navigation.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. A Process Model for Establishing Business Process Crowdsourcing

    Directory of Open Access Journals (Sweden)

    Nguyen Hoang Thuan

    2017-06-01

    Full Text Available Crowdsourcing can be an organisational strategy to distribute work to Internet users and harness innovation, information, capacities, and variety of business endeavours. As crowdsourcing is different from other business strategies, organisations are often unsure as to how to best structure different crowdsourcing activities and integrate them with other organisational business processes. To manage this problem, we design a process model guiding how to establish business process crowdsourcing. The model consists of seven components covering the main activities of crowdsourcing processes, which are drawn from a knowledge base incorporating diverse knowledge sources in the domain. The built model is evaluated using case studies, suggesting the adequateness and utility of the model.

  6. 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

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. A Process Model for Establishing Business Process Crowdsourcing

    OpenAIRE

    Nguyen Hoang Thuan; Pedro Antunes; David Johnstone

    2017-01-01

    Crowdsourcing can be an organisational strategy to distribute work to Internet users and harness innovation, information, capacities, and variety of business endeavours. As crowdsourcing is different from other business strategies, organisations are often unsure as to how to best structure different crowdsourcing activities and integrate them with other organisational business processes. To manage this problem, we design a process model guiding how to establish business process crowdsourcing....

  12. 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

  13. Establishment of mathematical moment model in twin casting rolling rolls

    Institute of Scientific and Technical Information of China (English)

    孙斌煜; 苑世剑; 张洪; 杜艳平; 张芳萍

    2002-01-01

    In continuous casting rolling process, the deformed body is different from the hot rolling strip. The metal in casting rolling zone is first assumed to be viscous fluid and the mathematical model of casting rolling force is established, then the calculating formula for casting rolling torque is derived. In addition, considering the effects of deforming cone and appendant torque of rotary junctions sealing ring, the calculating model which accords with casting rolling condition is found out. Theoretical formula is proved by experiment.

  14. 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.

  15. 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...

  16. Establishing of the Transplanted Animal Models for Human Lung Cancer

    Institute of Scientific and Technical Information of China (English)

    Xingli Zhang; Jinchang Wu

    2009-01-01

    Lung cancer is the leading cause of cancer mortality worldwide.Even with the applications of excision,radiotherapy,chemotherapy,and gene therapy,the 5 year survival rate is only 15% in the USA.Clinically relevant laboratory animal models of the disease could greatly facilitate understanding of the pathogenesis of lung cancer,its progression,invasion and metastasis.Transplanted lung cancer models are of special interest and are widely used today.Such models are essential tools in accelerating development of new therapies for lung cancer.In this communication we will present a brief overview of the hosts,sites and pathways used to establish transplanted animal lung tumor models.

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

    Science.gov (United States)

    Stueve, K.M.; Isaacs, R.E.; Tyrrell, L.E.; Densmore, R.V.

    2011-01-01

    Throughout interior Alaska (USA), a gradual warming trend in mean monthly temperatures occurred over the last few decades (;2-48C). 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. ?? 2011 by the Ecological Society of America.

  18. 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.

  19. 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

  20. The establishment of reliability model for LED lamps

    Science.gov (United States)

    Jian, Hao; Lei, Jing; Yao, Wang; Qun, Gao; Hongliang, Ke; Xiaoxun, Wang; Yanchao, Zhang; Qiang, Sun; Zhijun, Xu

    2016-07-01

    In order to verify which of the distributions and established methods of reliability model are more suitable for the analysis of the accelerated aging of LED lamp, three established methods (approximate method, analytical method and two-stage method) of reliability model are used to analyze the experimental data under the condition of the Weibull distribution and Lognormal distribution, in this paper. Ten LED lamps are selected for the accelerated aging experiment and the luminous fluxes are measured at an accelerated aging temperature. AIC information criterion is adopted in the evaluation of the models. The results show that the accuracies of the analytical method and the two-stage method are higher than that of the approximation method, with the widths of confidence intervals of unknown parameters of the reliability model being the smallest for the two-stage method. In a comparison between the two types of distributions, the accuracies are nearly identical. Project supported by the National High Technology Research and Development Program of China (Nos. 2015AA03A101, 2013AA03A116), the Cuican Project of Chinese Academy of Sciences (No. KZCC-EW-102), and the Jilin Province Science and Technology Development Plan Item (No. 20130206018GX).

  1. Establishing the colitis-associated cancer progression mouse models.

    Science.gov (United States)

    Zheng, Haiming; Lu, Zhanjun; Wang, Ruhua; Chen, Niwei; Zheng, Ping

    2016-12-01

    Inflammatory bowel disease (IBD) has been reported as an important inducer of colorectal cancer (CRC). The most malignant IBD-associated CRC type has been highlighted as colitis-associated cancer (CAC). However, lack of CAC cases and difficulties of the long follow-up research have challenged researchers in molecular mechanism probing. Here, we established pre-CAC mouse models (dextran sulfate sodium [DSS] group and azoxymethane [AOM] group) and CAC mouse model (DSS/AOM group) to mimic human CAC development through singly or combinational treatment with DSS and AOM followed by disease activity index analysis. We found that these CAC mice showed much more severe disease phenotype, including serious diarrhea, body weight loss, rectal prolapse and bleeding, bloody stool, tumor burden, and bad survival. By detecting expression patterns of several therapeutic targets-Apc, p53, Kras, and TNF-α-in these mouse models through western blot, histology analysis, qRT-PCR, and ELISA methods, we found that the oncogene Kras expression remained unchanged, while the tumor suppressors-Apc and p53 expression were both significantly downregulated with malignancy progression from pre-CAC to CAC, and TNF-α level was elevated the most in CAC mice blood which is of potential clinical use. These data indicated the successful establishment of CAC development mouse models, which mimics human CAC well both in disease phenotype and molecular level, and highlighted the promoting role of inflammation in CAC progression. This useful tool will facilitate the further study in CAC molecular mechanism.

  2. A Model of Colonic Crypts using SBML Spatial

    Directory of Open Access Journals (Sweden)

    Carlo Maj

    2013-09-01

    Full Text Available The Spatial Processes package enables an explicit definition of a spatial environment on top of the normal dynamic modeling SBML capabilities. The possibility of an explicit representation of spatial dynamics increases the representation power of SBML. In this work we used those new SBML features to define an extensive model of colonic crypts composed of the main cellular types (from stem cells to fully differentiated cells, alongside their spatial dynamics.

  3. Establishment of novel rat models for premalignant breast disease

    Institute of Scientific and Technical Information of China (English)

    Wang Feng; Ma Zhongbing; Wang Fei; Fu Qinye; Fang Yunzhi; Zhang Qiang; Gao Dezong

    2014-01-01

    Background Breast cancer has become one of the most common malignant tumors among females over the past several years.Breast carcinogenesis is a continuous process,which is featured by the normal epithelium progressing to premalignant lesions and then to invasive breast cancer (IBC).Targeting premalignant lesions is an effective strategy to prevent breast cancer.The establishment of animal models is critical to study the mechanisms of breast carcinogenesis,which will facilitate research on breast cancer prevention and drug behaviors.In this study,we established a feasible chemically-induced rat model of premalignant breast cancer.Methods Following the administration of the drugs (carcinogen,estrogen,and progestogen) to Sprague-Dawley (SD) rats,tumors or suspicious tumors were identified by palpation or ultrasound imaging,and were surgically excised for pathological evaluation.A series of four consecutive steps were carried out in order to determine the carcinogen:7,12-dimethylbenzaanthracene (DMBA) or 1-methyl-1-nitrosourea,the route of carcinogen administration,the administration period of estrogen and progestogen,and the DMBA dosage.Results Stable premalignant lesions can be induced in SD rats on administration of DMBA (15 mg/kg,administered three times) followed by administration of female hormones 5-day cycle.Results were confirmed by ultrasound and palpation.Conclusion Under the premise of drug dose and cycle,DMBA combined with estrogen and progestogen can be used as a SD rat model for breast premalignant lesions.

  4. Mathematical Modeling of spatial disease variables by Spatial Fuzzy Logic for Spatial Decision Support Systems

    Science.gov (United States)

    Platz, M.; Rapp, J.; Groessler, M.; Niehaus, E.; Babu, A.; Soman, B.

    2014-11-01

    A Spatial Decision Support System (SDSS) provides support for decision makers and should not be viewed as replacing human intelligence with machines. Therefore it is reasonable that decision makers are able to use a feature to analyze the provided spatial decision support in detail to crosscheck the digital support of the SDSS with their own expertise. Spatial decision support is based on risk and resource maps in a Geographic Information System (GIS) with relevant layers e.g. environmental, health and socio-economic data. Spatial fuzzy logic allows the representation of spatial properties with a value of truth in the range between 0 and 1. Decision makers can refer to the visualization of the spatial truth of single risk variables of a disease. Spatial fuzzy logic rules that support the allocation of limited resources according to risk can be evaluated with measure theory on topological spaces, which allows to visualize the applicability of this rules as well in a map. Our paper is based on the concept of a spatial fuzzy logic on topological spaces that contributes to the development of an adaptive Early Warning And Response System (EWARS) providing decision support for the current or future spatial distribution of a disease. It supports the decision maker in testing interventions based on available resources and apply risk mitigation strategies and provide guidance tailored to the geo-location of the user via mobile devices. The software component of the system would be based on open source software and the software developed during this project will also be in the open source domain, so that an open community can build on the results and tailor further work to regional or international requirements and constraints. A freely available EWARS Spatial Fuzzy Logic Demo was developed wich enables a user to visualize risk and resource maps based on individual data in several data formats.

  5. Stochastic population oscillations in spatial predator-prey models

    Energy Technology Data Exchange (ETDEWEB)

    Taeuber, Uwe C, E-mail: tauber@vt.edu [Department of Physics, Virginia Tech, Blacksburg, VA 24061-0435 (United States)

    2011-09-15

    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.

  6. 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.

  7. [Establishment of prostatic hyperplasia model with castration beagle canines].

    Science.gov (United States)

    Wu, Jian-Hui; Sun, Zu-Yue; Zhu, Yan; Zhong, En-Hong; He, Gui-Lin; Liu, Gui-Ming

    2003-09-01

    To establish a prostatic hyperplasia model with Beagle canines. Twenty-four two-year-old male Beagle canines were divided into treatment and control groups at random and were administrated testosterone propionate (TP) through intramuscular injection two months after castration. Three treatment groups were given 0.8, 2.5 and 7.5 mg/kg TP respectively, and the control was given the same volume of vehicle. Two months later, half of the animals were killed and the serum and prostate were prepared. After the wet weight and volume of prostate were measured, the dihydrotestosterone (DHT) level of serum and prostate were detected with DHT radioimmunoassay (RIA) kit, and paraffine section from canine prostate was stained by the HE methods. Pictures were taken by digital camera under microscope, and all the pictures were analyzed by computer for epithelial cell height and acinar luminal area of prostate with micro image analysis software. The canine prostate volume was measured with ultrasonic diagnosis instrument before castration, at two months after castration and at two months after being given TP. The ultrasonic results showed that the prostate volumes of all the canines were smaller at two months after castration than before castration (P canines became higher with the increase of TP dose. The results of micro image analysis showed that the acinar luminal area of prostate was enlarged, and the epithelial cell height increased with larger dose of TP. It is practicable to establish prostatic hyperplasia model in Beagle canines after two months of TP administration.

  8. 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 perspecti

  9. Spatially explicit fate modelling of nanomaterials in natural waters

    NARCIS (Netherlands)

    Quik, J.T.K.; Klein, de J.J.M.; Koelmans, A.A.

    2015-01-01

    Site specific exposure assessments for engineered nanoparticles (ENPs) require spatially explicit fate models, which however are not yet available. Here we present an ENP fate model (NanoDUFLOW) that links ENP specific process descriptions to a spatially explicit hydrological model. The link enables

  10. Mining multilevel spatial association rules with cloud models

    Institute of Scientific and Technical Information of China (English)

    YANG Bin; ZHU Zhong-ying

    2005-01-01

    The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates the vague and random use of linguistic terms in a unified way. With these models, spatial and nonspatial attribute values are well generalized at multiple levels, allowing discovery of strong spatial association rules.Combining the cloud model based method with Apriori algorithms for mining association rules from a spatial database shows benefits in being effective and flexible.

  11. 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.

  12. The establishment of the evaluation model for pupil's lunch suppliers

    Science.gov (United States)

    Lo, Chih-Yao; Hou, Cheng-I.; Ma, Rosa

    2011-10-01

    The aim of this study is the establishment of the evaluation model for the government-controlled private suppliers for school lunches in the public middle and primary schools in Miao-Li County. After finishing the literature search and the integration of the opinions from anonymous experts by Modified Delphi Method, the grade forms from relevant schools in and outside the Miao-Li County will firstly be collected and the delaminated structures for evaluation be constructed. Then, the data analysis will be performed on those retrieved questionnaires designed in accordance with the Analytic Hierarchy Process (AHP). Finally, the evaluation form for the government-controlled private suppliers can be constructed and presented in the hope of benefiting the personnel in charge of school meal purchasing.

  13. 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 ...... 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.......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...

  14. Functional-Coefficient Spatial Durbin Models with Nonparametric Spatial Weights: An Application to Economic Growth

    Directory of Open Access Journals (Sweden)

    Mustafa Koroglu

    2016-02-01

    Full Text Available This paper considers a functional-coefficient spatial Durbin model with nonparametric spatial weights. Applying the series approximation method, we estimate the unknown functional coefficients and spatial weighting functions via a nonparametric two-stage least squares (or 2SLS estimation method. To further improve estimation accuracy, we also construct a second-step estimator of the unknown functional coefficients by a local linear regression approach. Some Monte Carlo simulation results are reported to assess the finite sample performance of our proposed estimators. We then apply the proposed model to re-examine national economic growth by augmenting the conventional Solow economic growth convergence model with unknown spatial interactive structures of the national economy, as well as country-specific Solow parameters, where the spatial weighting functions and Solow parameters are allowed to be a function of geographical distance and the countries’ openness to trade, respectively.

  15. Modelling spatial vagueness based on type-2 fuzzy set

    Institute of Scientific and Technical Information of China (English)

    DU Guo-ning; ZHU Zhong-ying

    2006-01-01

    The modelling and formal characterization of spatial vagueness plays an increasingly important role in the implementation of Geographic Information System (GIS). The concepts involved in spatial objects of GIS have been investigated and acknowledged as being vague and ambiguous. Models and methods which describe and handle fuzzy or vague (rather than crisp or determinate) spatial objects, will be more necessary in GIS. This paper proposes a new method for modelling spatial vagueness based on type-2 fuzzy set, which is distinguished from the traditional type-1 fuzzy methods and more suitable for describing and implementing the vague concepts and objects in GIS.

  16. 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.

  17. Establishment and evaluation of a new severe hepatic trauma model

    Directory of Open Access Journals (Sweden)

    Can-rong LU

    2011-12-01

    Full Text Available Objective To establish and evaluate a severe hepatic trauma model.Methods Eleven Chinese miniature swine for experiments were used in the current study.Using the self-made explosive-actuated device(MT-1,the explosive substance was prepared from 0.4 g black gunpowder and was placed on the diaphragmatic surface of the target hepatic lobe after the miniature swine had received celiotomy.Protective isolation for adjacent structure was then conducted,and then "fire".The parenchyma area(S was destroyed,and the mean arterial pressure(MAP and blood loss(V were measured to evaluate the local injury of the model animals and the changes of hemodynamics after being injured.Results The area(S of the destroyed parenchyma was 12.19±2.28 cm2.MAP presents the linear decline from 2 min to 7 min in the early stage post injury,with a decreasing rate of 6.58±2.30 mmHg/min and a period of 7.22±0.37 min when dropped to half.Blood loss was 466±79 ml when MAP drops to half of the level before injury.Treatment was not initiated for the first three animals and the time to death was between 23 min and 31 min.Conclusions The prepared model of severe hepatic trauma miniature swine corresponds with grade IV(AAST in human.The current model can be used to study war and traffic accident traumas due to its good repeatability and strong controllability.

  18. Establishment of mice model with human viral hepatitis B

    Science.gov (United States)

    Gao, Li-Fen; Sun, Wen-Sheng; Ma, Chun-Hong; Liu, Su-Xia; Wang, Xiao-Yan; Zhang, Li-Ning; Cao, Ying-Lin; Zhu, Fa-Liang; Liu, Yu-Gang

    2004-01-01

    AIM: To establish a mice model of hepatitis B by using HBV-transgenic mice, and to transfer HBV-specific cytotoxic T lymphocytes (CTL) induced from syngeneic BALB/c mice immunized by a eukaryotic expression vector containing HBV complete genome DNA. METHODS: HBV DNA was obtained from digested pBR322-2HBV and ligated with the vector pcDNA3. Recombinant pcDNA3-HBV was identified by restriction endonuclease assay and transfected into human hepatoma cell line HepG2 with lipofectin. ELISA was used to detect the expression of HBsAg in culture supernatant, and RT-PCR to determine the existence of HBV PreS1 mRNA. BALB/c mice were immunized with pcDNA3-HBV or pcDNA3 by intramuscular injection. ELISA was used to detect the expression of HBsAb in serum. MTT assay was used to measure non-specific or specific proliferation ability and specific killing activity of spleen lymphocytes. Lymphocytes from immunized mice were transferred into HBV-transgenic mice (2.5 × 107 per mouse). Forty-eight hours later, the level of serum protein and transaminase was detected with biochemical method, liver and kidney were sectioned and stained by HE to observe the pathological changes. RESULTS: By enzyme digestion with Eco RI, Xho I and Hind III, the recombinant pcDNA3-HBV was verified to contain a single copy of HBV genome, which was inserted in the positive direction. HepG2 cells transfected with the recombinant could stably express PreS1 mRNA and HBsAg. After immunized by pcDNA3-HBV for 4 weeks, HBsAb was detected in the serum of BALB/c mice. The potential of spleen lymphocytes for both non-specific and specific proliferation and the specific killing activity against target cells were enhanced. The transgenic mice in model group had no significant changes in the level of serum protein but had an obvious increase of ALT and AST. The liver had obvious pathological changes, while the kidney had no evident damage. CONCLUSION: A eukaryotic expression vector pcDNA3-HBV containing HBV complete

  19. Book review: Statistical Analysis and Modelling of Spatial Point Patterns

    DEFF Research Database (Denmark)

    Møller, Jesper

    2009-01-01

    Statistical Analysis and Modelling of Spatial Point Patterns by J. Illian, A. Penttinen, H. Stoyan and D. Stoyan. Wiley (2008), ISBN 9780470014912......Statistical Analysis and Modelling of Spatial Point Patterns by J. Illian, A. Penttinen, H. Stoyan and D. Stoyan. Wiley (2008), ISBN 9780470014912...

  20. Proximal soil sensing to parameterize spatial environmental modeling

    Science.gov (United States)

    Spatially explicit models are important tools to understand the effects of the interaction of management and landscape factors on water and soil quality. One challenge to application of such models is the need to know spatially-distributed values for input parameters. Some such data can come from av...

  1. Consequences of spatial autocorrelation for niche-based models

    DEFF Research Database (Denmark)

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

    2006-01-01

    variables, as measured by Moran's I, was analysed and compared between models. The effects of systematic subsampling of the data set and the inclusion of a contagion term to deal with spatial autocorrelation in models were assessed with projections made with GLM, as it was with this method that estimates...... were vulnerable to the effects of spatial autocorrelation. 5.  The procedures utilized to reduce the effects of spatial autocorrelation had varying degrees of success. Subsampling was partially effective in avoiding the inflation effect, whereas the inclusion of a contagion term fully eliminated......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...

  2. A spatial interaction model with spatially structured origin and destination effects

    Science.gov (United States)

    LeSage, James P.; Llano, Carlos

    2013-07-01

    We introduce a Bayesian hierarchical regression model that extends the traditional least-squares regression model used to estimate gravity or spatial interaction relations involving origin-destination flows. Spatial interaction models attempt to explain variation in flows from n origin regions to n destination regions resulting in a sample of N = n 2 observations that reflect an n by n flow matrix converted to a vector. Explanatory variables typically include origin and destination characteristics as well as distance between each region and all other regions. Our extension introduces latent spatial effects parameters structured to follow a spatial autoregressive process. Individual effects parameters are included in the model to reflect latent or unobservable influences at work that are unique to each region treated as an origin and destination. That is, we estimate 2 n individual effects parameters using the sample of N = n 2 observations. We illustrate the method using a sample of commodity flows between 18 Spanish regions during the 2002 period.

  3. Establishment of intramedullary spinal cord glioma model in rats

    Institute of Scientific and Technical Information of China (English)

    REN Tian-jian; WANG Zhong-cheng; ZHANG Ya-zhuo; LI Dan; WANG Hong-yun; LI Zhen-zong

    2010-01-01

    Background Treating intramedullary spinal cord gliomas is a big challenge because of limited options, high recurrence rate and poor prognosis. An intramedullary glioma model is prerequisite for testing new treatments. This paper describes the establishment of a rodent intramedullary glioma model and presents functional progression, neuroimaging and histopathological characterization of the tumour model.Methods Fischer344 rats (n=24) were randomized into two groups. Group 1 (n=16) received a 5 μl intramedullary implantation of 9L gliosarcomal (105) cells. Group 2 (n=8) received a 5 μl intramedullary injection of Dulbecco's modified Eagle medium. The rats were anesthetized, the spinous process of the T10 vertebra and the ligamentum flavum were removed to expose the T10-11 intervertebral space and an intramedullary injection was conducted into the spinal cord. The rats were evaluated preoperatively and daily postoperatively for neurological deficits using the Basso, Beattie and Bresnahan scale. High resolution magnetic resonance images were acquired preoperatively and weekly postoperatively.When score equal to 0, rats were sacrificed for histopathological examination.Results Rats implanted with 9L gliosarcoma cells had a statistically significant median onset of hind limb paraplegia at (16.0±0.4) days, compared with rats in the control group in which neurological deficits were absent. Imaging and pathological cross sections confirmed intramedullary 9L gliosarcoma invading the spinal cord. Rats in the control group showed no significant functional, radiological or histopathological findings of tumour.Conclusions Rats implanted with 9L cells regularly develop paraplegia in a reliable and reproducible manner. The progression of neurological deficits, neuroimaging and histopathological characteristics of intramedullary spinal cord gliomas in rats is comparable with the behaviour of infiltrative intramedullary spinal cord gliomas in patients.

  4. Emergent universe in spatially flat cosmological model

    CERN Document Server

    Zhang, Kaituo; Yu, Hongwei

    2013-01-01

    The scenario of an emergent universe provides a promising resolution to the big bang singularity in universes with positive or negative spatial curvature. It however remains unclear whether the scenario can be successfully implemented in a spatially flat universe which seems to be favored by present cosmological observations. In this paper, we study the stability of Einstein static state solutions in a spatially flat Shtanov-Sahni braneworld scenario. With a negative dark radiation term included and assuming a scalar field as the only matter energy component, we find that the universe can stay at an Einstein static state past eternally and then evolve to an inflation phase naturally as the scalar field climbs up its potential slowly. In addition, we also propose a concrete potential of the scalar field that realizes this scenario.

  5. A formal model for access control with supporting spatial context

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hong; HE YePing; SHI ZhiGuo

    2007-01-01

    There is an emerging recognition of the importance of utilizing contextual information in authorization decisions. Controlling access to resources in the field of wireless and mobile networking require the definition of a formal model for access control with supporting spatial context. However, traditional RBAC model does not specify these spatial requirements. In this paper, we extend the existing RBAC model and propose the SC-RBAC model that utilizes spatial and location-based information in security policy definitions. The concept of spatial role is presented,and the role is assigned a logical location domain to specify the spatial boundary.Roles are activated based on the current physical position of the user which obtained from a specific mobile terminal. We then extend SC-RBAC to deal with hierarchies, modeling permission, user and activation inheritance, and prove that the hierarchical spatial roles are capable of constructing a lattice which is a means for articulate multi-level security policy and more suitable to control the information flow security for safety-critical location-aware information systems. Next, constrained SC-RBAC allows express various spatial separations of duty constraints,location-based cardinality and temporal constraints for specify fine-grained spatial semantics that are typical in location-aware systems. Finally, we introduce 9 invariants for the constrained SC-RBAC and its basic security theorem is proven. The constrained SC-RBAC provides the foundation for applications in need of the constrained spatial context aware access control.

  6. 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...... distribution, and the correlation in synaptic activity. For uncorrelated activity, the LFP represents cells in a small region (within a radius of a few hundred micrometers). If the LFP contributions from different cells are correlated, the size of the generating region is determined by the spatial extent...

  7. 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.

  8. [Establishment of osteoblast primary cilia model removed by chloral hyrate].

    Science.gov (United States)

    Ma, Xiao-ni; Shi, Wen-gui; Xie, Yan-fang; Ma, Hui-ping; Ge, Bao-feng; Zhen, Ping; Chen, Ke-ming

    2015-06-01

    To establish osteoblast model, primary cilla model was removed by chloral hyrate, observe effects of osteoblast primary cilla moved on enhancing ALP staining and calcified nodules staining in electromagnetic field. Three 3-day-old male SD rats weighed between 6 and 9 g were killed, cranial osteoblast was drawed and adherencing cultured respectively. Cells were subcultured and randomly divided into 4 groups until reach to fusion states. The four groups included chloral hydrate non-involved group (control group), 2 mM, 4 mM and 8 mM chloral hydrate group, and cultured in 37 °C, 5% CO2 incubator for 72 h. Morphology of primary cilla was observed by laser confocal scanning microscope, and incidence of osteoblast primary cilia was analyzed by Image-Pro Plus 6.0 software. Cells in the correct concentration group which can removed cillia most effectively were selected and divided into 3 groups, including control group (C), Electromagnetic fields group (EMFs), and EMFs with 4 mM chloral hydrate group. DMEM nutrient solution contained 10%FBS were added into three groups and cultured for 9 days and formation of ALP were observed by histochemical staining of alkaline phosphatase. After 12 days' cultivation, formation of mineralization nodes was observed by alizarin red staining. Compared with control group and 2mM chloral hydrate group,4 mM chloral hydrate group could effectively remove osteoblast primary cilla (P<0.01). Removal of osteoblast primary cilla could weaken the formation of ALP and mineralization nodes in osteoblast in EMFS. Compared with EMFs group, the area of ALP and mineralization nodes in EMFs with 4 mM chloral hydrate group were decreased obviously (P<0.01). 4mM chloral hydrate could effectively remove osteoblast primary cilia. Primary cilla participate in EMFs promoting formation of ALP and mineralization nodes in osteoblast and provide new ideas for exploring mechanism of EMFs promoting osteoblast maturation and mineralization.

  9. Modelling spatial patterns of economic activity in the Netherlands

    CERN Document Server

    Yang, Jung-Hun; Frenken, Koen; Van Oort, Frank; Visser, Evert-Jan

    2012-01-01

    Understanding how spatial configurations of economic activity emerge is important when formulating spatial planning and economic policy. Not only micro-simulation and agent-based model such as UrbanSim, ILUMAS and SIMFIRMS, but also Simon's model of hierarchical concentration have widely applied, for this purpose. These models, however, have limitations with respect to simulating structural changes in spatial economic systems and the impact of proximity. The present paper proposes a model of firm development that is based on behavioural rules such as growth, closure, spin-off and relocation. An important aspect of the model is that locational preferences of firms are based on agglomeration advantages, accessibility of markets and congestion, allowing for a proper description of concentration and deconcentration tendencies. By comparing the outcomes of the proposed model with real world data, we will calibrate the parameters and assess how well the model predicts existing spatial configurations and decide. The...

  10. Spatial emission modelling for residential wood combustion in Denmark

    DEFF Research Database (Denmark)

    Plejdrup, Marlene Schmidt; Nielsen, Ole-Kenneth; Brandt, Jørgen

    2016-01-01

    Residential wood combustion (RWC) is a major contributor to atmospheric pollution especially for particulate matter. Air pollution has significant impact on human health, and it is therefore important to know the human exposure. For this purpose, it is necessary with a detailed high resolution...... spatial distribution of emissions. In previous studies as well as in the model previously used in Denmark, the spatial resolution is limited, e.g. municipality or county level. Further, in many cases models are mainly relying on population density data as the spatial proxy for distributing the emissions....... This paper describes the new Danish model for high resolution spatial distribution of emissions from RWC to air. The new spatial emission model is based on information regarding building type, and primary and supplementary heating installations from the Danish Building and Dwelling Register (BBR), which...

  11. Error Threshold for Spatially Resolved Evolution in the Quasispecies Model

    Energy Technology Data Exchange (ETDEWEB)

    Altmeyer, S.; McCaskill, J. S.

    2001-06-18

    The error threshold for quasispecies in 1, 2, 3, and {infinity} dimensions is investigated by stochastic simulation and analytically. The results show a monotonic decrease in the maximal sustainable error probability with decreasing diffusion coefficient, independently of the spatial dimension. It is thereby established that physical interactions between sequences are necessary in order for spatial effects to enhance the stabilization of biological information. The analytically tractable behavior in an {infinity} -dimensional (simplex) space provides a good guide to the spatial dependence of the error threshold in lower dimensional Euclidean space.

  12. Free-streaming radiation in cosmological models with spatial curvature

    Science.gov (United States)

    Wilson, M. L.

    1982-01-01

    The effects of spatial curvature on radiation anisotropy are examined for the standard Friedmann-Robertson-Walker model universes. The effect of curvature is found to be very important when considering fluctuations with wavelengths comparable to the horizon. It is concluded that the behavior of radiation fluctuations in models with spatial curvature is quite different from that in spatially flat models, and that models with negative curvature are most strikingly different. It is therefore necessary to take the curvature into account in careful studies of the anisotropy of the microwave background.

  13. Establishment of an animal model of dural venous sinus embolism

    Institute of Scientific and Technical Information of China (English)

    Peixian Zhang; Chongzhi Zhang; Yi Qin; Quanrui Ma; Jianying Du; Ying Cai

    2008-01-01

    BACKGROUND: The pathological mechanism of secondary brain lesion following an embolism remains unclear. The establishment of an animal model that imitates the clinical pathophysiological processes is crucial to better study this disease during a certain time window.OBJECTIVE: To establish a new animal model of dural venous sinus embolism that is simple, has a high success rate, and emulates the pathophysiological course of clinical disease.DESIGN, TIME AND SETTING: A randomized block design trial was performed at the Department of Anatomy, Ningxia Medical College between March and December 2007.MATERIALS: Fifty-eight healthy, adult, Sprague Dawley rats were used in the present study. Plastic emboli, with a total length of 0.4cm, were self-made. Each plastic embolus had a conical anterior segment; the largest diameter being 0.12cm. The posterior segment became gradually thin and flat, with a width of 0.2cm and length of 0.1cm.METHODS: The fifty-eight rats were randomly divided into three groups: control (n=6), embolism (n=26), and sham-embolism (n=26) groups. In the embolism group, a solid embolus was slowly inserted and fixed into the posterior part of the superior sagittal sinus against the flow of blood. The posterior segment was detained outside the superior sagittal sinus for fixing. In the sham-embolism group, rats were subjected only to sinus sagittalis superior exposure. In the control group, rats received no treatments. In both the embolism and the sham-embolism groups, the rat brains were resected at 6 hours, 1,3, and 5 days post-surgery.MAIN OUTCOME MEASURES: (1) Brain surface appearance in the embolism and sham-embolism groups. (2) Thrombosis in the embolism group. (3) Cerebrospinal fluid content in the above-mentioned two groups.RESULTS: In the embolism group, the model success rate was 92%(24/26). There was visible thrombosis in the superior sagittal sinus. Cerebral edema was noticeable under a microscope. These changes were visible at 6 hours after

  14. Establishing a National Coastal Change Model for Scotland

    Science.gov (United States)

    Fitton, James; Hansom, Jim; Rennie, Alistair

    2015-04-01

    The Climate Change (Scotland) Act 2009 requires the development of an Adaptation Programme to take forward the risks identified within the UK's Climate Change Risk Assessment (UK-CCRA). The UK-CCRA anticipates increases in sea level, coastal erosion and coastal flooding to increasingly affect Scotland's soft coastlines and the assets found on these coasts. Shoreline Management Plans have been produced for only short sections of the Scottish coast which limits the information available to coastal managers. Consequently a National Coastal Change Assessment (NCCA) has been commissioned by the Scottish Government and is supported by a number of agencies. The assessment aims to create a shared evidence base to support more sustainable coastal and terrestrial planning decisions in the light of a changing climate. The NCCA aims to establish historic coastal change by extracting the georectified coastline position from OS 2nd Edition Country Series maps (1892-1905) and to then compare it to both the 1970's and current coastal position (updated by LiDAR datasets where available) in order to estimate past erosion/accretion rates. Using the historic coastal change rates the coastline position can then be projected into the future, albeit mediated by a Coastal Erosion Susceptibility Model (CESM) whose function is to limit erosion to areas where the hinterland is susceptible to erosion. The CESM is a national GIS assessment at 50 m raster resolution which models the physical susceptibility of the coast. The model uses a range of data (elevation, rockhead elevation, proximity to the coast, wave exposure, sediment accretion, and coastal defences) which are ranked and amalgamated into a single raster dataset reflecting erosion susceptibility. Using the erosion rates combined with a number of socioeconomic datasets, key assets at risk from future coastal erosion can be identified. The NCCA aims to inform existing strategic planning (Shoreline Management Plans, Flood Risk Management

  15. Establishment of Helicobacter pylori infection model in Mongolian gerbils

    Institute of Scientific and Technical Information of China (English)

    Jie Yan; Yi-Hui Luo; Ya-Fei Mao

    2004-01-01

    AIM: To establish a stable and reliable model of Helicobacter pyloriinfection model in Mongolian gerbils and to observe pathological changes in gastric mucosa in infected animals. METHODS: Mongolian gerbils were randomly divided into 18 groups; 6 groups were infected with Hpylori clinical strain Y06 (n=6, groups Y), 6 groups were infected with H pylori strain NCTC11637 (n=6, groups N), and 6 uninfected groups as negative controls (n=4,, groups C). Hpylorisuspensions at the concentrations of 2 x 108 and 2x 109 CFU/mL of strain NCTC11637 and strain Y06 were prepared. The animals in three groups N and in three groups Y were orally challenged once with 0.5 mL of the low concentration of the bacterial suspension. The animals in another three groups N and in another three groups Y were orally challenged with 0.5 mL of the high concentration of the bacterial suspension for 3times at the intervals of 24 h, respectively. For the negative controls, the animals in six groups C were orally given with the same volume of Brucella broth at the corresponding inoculating time. The animals were killed after 2nd, 4th and 6th week after the last challenge and the gastric mucosal specimens were taken for urease test, bacterial isolation, pathological and immunohistochemical examinations.RESULTS: Positive isolation rates of Hpyloriin the animals of groups Y at the 2nd, 4th and 6th week after one challenge were 0%, 16.7% and 66.7%, while in the animals of groups N were 0%, 0% and 16.7%, respectively. Positive isolation rates of H pyloriin the animals of groups Y at the 2nd, 4thand 6th week after three challenges were 66.7%, 100% and 100%, while in the animals of groups N were 66.7%, 66.7% and 100%, respectively. In animals with positive isolation of Hpylori, the bacterium was found to colonized on the surface of gastric mucosal cells and in the gastric pits, and the gastric mucosal lamina propria was infiltrated with inflammatory cells.CONCLUSION: By using H pylori suspension at high

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

    Directory of Open Access Journals (Sweden)

    Wu Hanguang

    2007-01-01

    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.

  17. 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.

  18. Methodological characteristics in establishing rat models of poststroke depression

    Institute of Scientific and Technical Information of China (English)

    Fuyou Liu; Shi Yang; Weiyin Chen; Jinyu Wang; Yi Tang; Guanxiang Zhu

    2006-01-01

    wondering among squares, times for upright grooming; Passive avoidance test: total number of shocks, duration of being shocked; ③ Contents of NE, 5-HT and dopamine in brain.RESULTS: Six rats died and 3 rats failed in the model establishment, and finally 36 rats were involved in the analysis of results. ① 22 stroke rats were evaluated by the Longa 5-grade standard (including 9 in the stroke group and 13 in the PSD group), the scores at 4, 8 and 24 hours after consciousness were 2.58±0.69, 2.32±0.58 and 1.37±0.60, respectively. ② 20 stroke rats were evaluated by the horizontal round rod test (including 8 in the stroke group and 12 in the PSD group), and the time stayed on the rod at 1, 3 and 5 days after stroke were (110.94±31.40), (149.53±16.56) and (169.88±8.44) s, respectively. ③ The body masses at 7 and 14 days after stroke were significantly lower in the PSD group than the normal control group [(348.8±47.7), (390.9±22.9) g,P< 0.05; (321.7±43.8), (392.6±23.5) g, P< 0.01]. ④ The amount of saccharin-water consumption was significantly lower in the PSD group than the normal control group [(8.48±1.15), (113.0±11.8) mL/kg, P < 0.01].⑤The PSD rats had reduced activities in the open-field test and passive avoidance deficits, which were obviously different from those in the normal control group (P< 0.05). ⑥ The NE and 5-HT contents in bilateral frontoparietal cortexes and brain stem in the PSD group were significantly decreased as compared with those in the normal control group (P < 0.05); The contents of dopamine in left frontoparietal cortex and brain stem were also obviously lower than those in the normal control group (P< 0.05).CONCLUSION: It is correct and feasible to induce PSD rat model by giving separating raising and stress to rat models of focal cerebral ischemia established by thread embolization of internal carotid artery.

  19. Estimation of exposure to toxic releases using spatial interaction modeling

    Directory of Open Access Journals (Sweden)

    Conley Jamison F

    2011-03-01

    Full Text Available Abstract Background The United States Environmental Protection Agency's Toxic Release Inventory (TRI data are frequently used to estimate a community's exposure to pollution. However, this estimation process often uses underdeveloped geographic theory. Spatial interaction modeling provides a more realistic approach to this estimation process. This paper uses four sets of data: lung cancer age-adjusted mortality rates from the years 1990 through 2006 inclusive from the National Cancer Institute's Surveillance Epidemiology and End Results (SEER database, TRI releases of carcinogens from 1987 to 1996, covariates associated with lung cancer, and the EPA's Risk-Screening Environmental Indicators (RSEI model. Results The impact of the volume of carcinogenic TRI releases on each county's lung cancer mortality rates was calculated using six spatial interaction functions (containment, buffer, power decay, exponential decay, quadratic decay, and RSEI estimates and evaluated with four multivariate regression methods (linear, generalized linear, spatial lag, and spatial error. Akaike Information Criterion values and P values of spatial interaction terms were computed. The impacts calculated from the interaction models were also mapped. Buffer and quadratic interaction functions had the lowest AIC values (22298 and 22525 respectively, although the gains from including the spatial interaction terms were diminished with spatial error and spatial lag regression. Conclusions The use of different methods for estimating the spatial risk posed by pollution from TRI sites can give different results about the impact of those sites on health outcomes. The most reliable estimates did not always come from the most complex methods.

  20. 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

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

    NARCIS (Netherlands)

    Cianci, Daniela; Hartemink, Nienke; Ibáñez-Justicia, Adolfo

    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

  2. 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.

  3. 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.

  4. Establishment of a sensitized canine model for kidney transplantation

    Institute of Scientific and Technical Information of China (English)

    XIE Sen; XIA Sui-sheng; TANG Li-gong; CHENG Jun; CHEN Zhi-shui; ZHENG Shan-gen

    2005-01-01

    Objective:To establish a sensitized canine model for kidney transplantation. Methods:12 male dogs were averagely grouped as donors and recipients. A small number of donor canine lymphocytes was infused into different anatomic locations of a paired canine recipient for each time and which was repeated weekly. Specific immune sensitization was monitored by means of Complement Dependent Cytotoxicity (CDC) and Mixed Lymphocyte Culture (MLC) test. When CDC test conversed to be positive and MLC test showed a significant proliferation of reactive lymphocytes of canine recipients, the right kidneys of the paired dogs were excised and transplanted to each other concurrently. Injury of renal allograft function was scheduled determined by ECT dynamic kidney photography and pathologic investigation. Results :CDC test usually conversed to be positive and reactive lymphocytes of canine recipients were also observed to be proliferated significantly in MLC test after 3 to 4 times of canine donor lymphocyte infusions. Renal allograft function deterioration occurred 4 d post-operatively in 4 of 6 canine recipients, in contrast to none in control dogs. Pathologic changes suggested antibody-mediated rejection (delayed) or acute rejection in 3 excised renal allograft of sensitized dogs. Seven days after operation, all sensitized dogs had lost graft function, pathologic changes of which showed that the renal allografts were seriously rejected. 2 of 3 dogs in control group were also acutely rejected. Conclusion:A convenient method by means of repeated stimulation of canine lymphocyte may induce specific immune sensitization in canine recipients. Renal allografts in sensitized dogs will be earlier rejected and result in a more deteriorated graft function.

  5. Full feature data model for spatial information network integration

    Institute of Scientific and Technical Information of China (English)

    DENG Ji-qiu; BAO Guang-shu

    2006-01-01

    In allusion to the difficulty of integrating data with different models in integrating spatial information,the characteristics of raster structure, vector structure and mixed model were analyzed, and a hierarchical vectorraster integrative full feature model was put forward by integrating the advantage of vector and raster model and using the object-oriented method. The data structures of the four basic features, i.e. point, line, surface and solid,were described. An application was analyzed and described, and the characteristics of this model were described. In this model, all objects in the real world are divided into and described as features with hierarchy, and all the data are organized in vector. This model can describe data based on feature, field, network and other models, and avoid the disadvantage of inability to integrate data based on different models and perform spatial analysis on them in spatial information integration.

  6. FUEL3-D: A Spatially Explicit Fractal Fuel Distribution Model

    Science.gov (United States)

    Russell A. Parsons

    2006-01-01

    Efforts to quantitatively evaluate the effectiveness of fuels treatments are hampered by inconsistencies between the spatial scale at which fuel treatments are implemented and the spatial scale, and detail, with which we model fire and fuel interactions. Central to this scale inconsistency is the resolution at which variability within the fuel bed is considered. Crown...

  7. An Improved Direction Relation Detection Model for Spatial Objects

    Institute of Scientific and Technical Information of China (English)

    FENG Yucai; YI Baolin

    2004-01-01

    Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries.

  8. Comparison of spatial extreme value models for snow depth extremes in Austria

    Science.gov (United States)

    Schellander, Harald; Hell, Tobias

    2017-04-01

    In Alpine regions like Austria a spatial representation of extreme snow depth is of crucial importance for numerous purposes such as the designing of construction projects. Extreme value theory builds the well-established foundation of modeling extremes. Two different approaches for the spatial modeling of snow depth extremes have been extensively investigated lately: Smooth Spatial Modeling (Blanchet and Lehning, 2010) and different classes of max-stable processes (Blanchet and Davison, 2011; Nicolet et al., 2015), both outperforming classical interpolation techniques. While max-stable models are generally considered as improvement over smooth modeling, the methods have not been compared in the context of extreme snow depth. In the present study a great variety of different GEV models is fitted to seasonal snow depth maxima measured at more than 200 Austrian weather stations. Return levels of smooth spatial models and several max-stable representations (Schlather, Brown-Resnick, Geometric Gaussian, Extremal-t) and covariance models (Powered Exponential, Brown, Whittle-Matern), also allowing for anisotropic extremal dependence are compared by a modified Anderson-Darling score and a normalized RMSE. Preliminary results show, that for snow depth extremes in Austria smooth spatial modeling and a version with extremal coefficients as covariates deliver slightly better scores than (an)-isotropic max-stable models.

  9. Study on spatial temporal model in property management information system

    Institute of Scientific and Technical Information of China (English)

    李良宝; 李晓东

    2004-01-01

    Time is an important dimension for information in the geographical information system. Data, such as the historical state of target property space and related events causing the state to be changed, should be saved as important files. This should be applied to property management. This paper designs and constructs a spatial temporal model, which is suitable to the property data changing management and spatial temporal query by analyzing the basic types and characteristics of property management spatial changing time and date. This model uses current and historical situational layers to organize and set up the relationship between current situation data and historical dates according to spatial temporal topological relations in property entities. By using Map Basic, housing property management and spatial query is realized.

  10. Scale-based spatial data model for GIS

    Institute of Scientific and Technical Information of China (English)

    WEI Zu-kuan

    2004-01-01

    Being the primary media of geographical information and the elementary objects manipulated, almost all of maps adopt the layer-based model to represent geographic information in the existent GIS. However, it is difficult to extend the map represented in layer-based model. Furthermore, in Web-Based GIS, It is slow to transmit the spatial data for map viewing. In this paper, for solving the questions above, we have proposed a new method for representing the spatial data. That is scale-based model. In this model we represent maps in three levels: scale-view, block, and spatial object, and organize the maps in a set of map layers, named Scale-View, which associates some given scales.Lastly, a prototype Web-Based GIS using the proposed spatial data representation is described briefly.

  11. Spatial modelling of wind speed around windbreaks

    NARCIS (Netherlands)

    Vigiak, O.; Sterk, G.; Warren, A.; Hagen, L.J.

    2003-01-01

    This paper presents a model to integrate windbreak shelter effects into a Geographic Information System (GIS). The GIS procedure incorporates the 1999 version windbreak sub-model of the Wind Erosion Prediction System (WEPS). Windbreak shelter is modeled in terms of friction velocity reduction, which

  12. Modeling signalized intersection safety with corridor-level spatial correlations.

    Science.gov (United States)

    Guo, Feng; Wang, Xuesong; Abdel-Aty, Mohamed A

    2010-01-01

    Intersections in close spatial proximity along a corridor should be considered as correlated due to interacted traffic flows as well as similar road design and environmental characteristics. It is critical to incorporate this spatial correlation for assessing the true safety impacts of risk factors. In this paper, several Bayesian models were developed to model the crash data from 170 signalized intersections in the state of Florida. The safety impacts of risk factors such as geometric design features, traffic control, and traffic flow characteristics were evaluated. The Poisson and Negative Binomial Bayesian models with non-informative priors were fitted but the focus is to incorporate spatial correlations among intersections. Two alternative models were proposed to capture this correlation: (1) a mixed effect model in which the corridor-level correlation is incorporated through a corridor-specific random effect and (2) a conditional autoregressive model in which the magnitude of correlations is determined by spatial distances among intersections. The models were compared using the Deviance Information Criterion. The results indicate that the Poisson spatial model provides the best model fitting. Analysis of the posterior distributions of model parameters indicated that the size of intersection, the traffic conditions by turning movement, and the coordination of signal phase have significant impacts on intersection safety.

  13. 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.

  14. Validating a spatially distributed hydrological model with soil morphology data

    Directory of Open Access Journals (Sweden)

    T. Doppler

    2013-10-01

    Full Text Available Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas

  15. Spatial emission modelling for residential wood combustion in Denmark

    Science.gov (United States)

    Plejdrup, Marlene S.; Nielsen, Ole-Kenneth; Brandt, Jørgen

    2016-11-01

    Residential wood combustion (RWC) is a major contributor to atmospheric pollution especially for particulate matter. Air pollution has significant impact on human health, and it is therefore important to know the human exposure. For this purpose, it is necessary with a detailed high resolution spatial distribution of emissions. In previous studies as well as in the model previously used in Denmark, the spatial resolution is limited, e.g. municipality or county level. Further, in many cases models are mainly relying on population density data as the spatial proxy for distributing the emissions. This paper describes the new Danish model for high resolution spatial distribution of emissions from RWC to air. The new spatial emission model is based on information regarding building type, and primary and supplementary heating installations from the Danish Building and Dwelling Register (BBR), which holds detailed data for all buildings in Denmark. The new model provides a much more accurate distribution of emissions than the previous model used in Denmark, as the resolution has been increased from municipality level to a 1 km × 1 km resolution, and the distribution key has been significantly improved so that it no longer puts an excessive weight on population density. The new model has been verified for the city of Copenhagen, where emissions estimated using both the previous and the new model have been compared to the emissions estimated in a case study. This comparison shows that the new model with the developed weighting factors (76 ton PM2.5) is in good agreement with the case study (95 ton PM2.5), and that the new model has improved the spatial emission distribution significantly compared to the previous model (284 ton PM2.5). Additionally, a sensitivity analysis was done to illustrate the impact of the weighting factors on the result, showing that the new model independently of the weighting factors chosen produce a more accurate result than the old model.

  16. Spatial Error Metrics for Oceanographic Model Verification

    Science.gov (United States)

    2012-02-01

    quantitatively and qualitatively for this oceano - graphic data and successfully separates the model error into displacement and intensity components. This... oceano - graphic models as well, though one would likely need to make special modifications to handle the often-used nonuniform spacing between depth layers

  17. Learning Anatomy: Do New Computer Models Improve Spatial Understanding?

    Science.gov (United States)

    Garg, Amit; Norman, Geoff; Spero, Lawrence; Taylor, Ian

    1999-01-01

    Assesses desktop-computer models that rotate in virtual three-dimensional space. Compares spatial learning with a computer carpal-bone model horizontally rotating at 10-degree views with the same model rotating at 90-degree views. (Author/CCM)

  18. 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 poss

  19. 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 poss

  20. Spatially dependent polya tree modeling for survival data.

    Science.gov (United States)

    Zhao, Luping; Hanson, Timothy E

    2011-06-01

    With the proliferation of spatially oriented time-to-event data, spatial modeling in the survival context has received increased recent attention. A traditional way to capture a spatial pattern is to introduce frailty terms in the linear predictor of a semiparametric model, such as proportional hazards or accelerated failure time. We propose a new methodology to capture the spatial pattern by assuming a prior based on a mixture of spatially dependent Polya trees for the baseline survival in the proportional hazards model. Thanks to modern Markov chain Monte Carlo (MCMC) methods, this approach remains computationally feasible in a fully hierarchical Bayesian framework. We compare the spatially dependent mixture of Polya trees (MPT) approach to the traditional spatial frailty approach, and illustrate the usefulness of this method with an analysis of Iowan breast cancer survival data from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. Our method provides better goodness of fit over the traditional alternatives as measured by log pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and full sample score (FSS) statistics. © 2010, The International Biometric Society.

  1. 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

  2. Restricted spatial regression in practice: Geostatistical models, confounding, and robustness under model misspecification

    Science.gov (United States)

    Hanks, Ephraim M.; Schliep, Erin M.; Hooten, Mevin B.; Hoeting, Jennifer A.

    2015-01-01

    In spatial generalized linear mixed models (SGLMMs), covariates that are spatially smooth are often collinear with spatially smooth random effects. This phenomenon is known as spatial confounding and has been studied primarily in the case where the spatial support of the process being studied is discrete (e.g., areal spatial data). In this case, the most common approach suggested is restricted spatial regression (RSR) in which the spatial random effects are constrained to be orthogonal to the fixed effects. We consider spatial confounding and RSR in the geostatistical (continuous spatial support) setting. We show that RSR provides computational benefits relative to the confounded SGLMM, but that Bayesian credible intervals under RSR can be inappropriately narrow under model misspecification. We propose a posterior predictive approach to alleviating this potential problem and discuss the appropriateness of RSR in a variety of situations. We illustrate RSR and SGLMM approaches through simulation studies and an analysis of malaria frequencies in The Gambia, Africa.

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. Upscaling of Mixing Processes using a Spatial Markov Model

    Science.gov (United States)

    Bolster, Diogo; Sund, Nicole; Porta, Giovanni

    2016-11-01

    The Spatial Markov model is a model that has been used to successfully upscale transport behavior across a broad range of spatially heterogeneous flows, with most examples to date coming from applications relating to porous media. In its most common current forms the model predicts spatially averaged concentrations. However, many processes, including for example chemical reactions, require an adequate understanding of mixing below the averaging scale, which means that knowledge of subscale fluctuations, or closures that adequately describe them, are needed. Here we present a framework, consistent with the Spatial Markov modeling framework, that enables us to do this. We apply and present it as applied to a simple example, a spatially periodic flow at low Reynolds number. We demonstrate that our upscaled model can successfully predict mixing by comparing results from direct numerical simulations to predictions with our upscaled model. To this end we focus on predicting two common metrics of mixing: the dilution index and the scalar dissipation. For both metrics our upscaled predictions very closely match observed values from the DNS. This material is based upon work supported by NSF Grants EAR-1351625 and EAR-1417264.

  11. Spatially correlated disturbances in a locally dispersing population model.

    Science.gov (United States)

    Hiebeler, David

    2005-01-01

    The basic contact process in continuous time is studied, where instead of single occupied sites becoming empty independently, larger-scale disturbance events simultaneously remove the population from contiguous blocks of sites. Stochastic spatial simulations and pair approximations were used to investigate the model. Increasing the spatial scale of disturbance events increases spatial clustering of the population and variability in growth rates within localized regions, reduces the effective overall population density, and increases the critical reproductive rate necessary for the population to persist. Pair approximations yield a closed-form analytic expression for equilibrium population density and the critical value necessary for persistence.

  12. Toward the Establishment of a Common Framework for Model Evaluation

    DEFF Research Database (Denmark)

    Olesen, H. R.

    1996-01-01

    Proceedings of the Twenty-first NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its Application, held November 6-10 1995, in Baltimore, Maryland.......Proceedings of the Twenty-first NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its Application, held November 6-10 1995, in Baltimore, Maryland....

  13. Gilbert's Behavior Engineering Model: Contemporary Support for an Established Theory

    Science.gov (United States)

    Crossman, Donna Cangelosi

    2010-01-01

    This study was an effort to add to the body of research surrounding Gilbert's Behavior Engineering Model (BEM). The model was tested to determine its ability to explain factor relationships of organizational safety culture in a high-risk work environment. Three contextual variables were measured: communication, resource availability, and…

  14. Spatial Modeling Tools for Cell Biology

    Science.gov (United States)

    2006-10-01

    34 iv Figure 5.1: Computational results for a diffusion problem on planar square thin film............ 36 Figure 5.2... Wisc . Open Microscopy Env. Pre-CoBi Model Lib. CFDRC CoBi Tools CFDRC CoBi Tools Simulation Environment JigCell Tools Figure 4.1: Cell biology

  15. 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...

  16. 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 propertie...

  17. Spatial capture-recapture models allowing Markovian transience or dispersal

    Science.gov (United States)

    Royle, J. Andrew; Fuller, Angela K.; Sutherland, Chris

    2016-01-01

    Spatial capture–recapture (SCR) models are a relatively recent development in quantitative ecology, and they are becoming widely used to model density in studies of animal populations using camera traps, DNA sampling and other methods which produce spatially explicit individual encounter information. One of the core assumptions of SCR models is that individuals possess home ranges that are spatially stationary during the sampling period. For many species, this assumption is unlikely to be met and, even for species that are typically territorial, individuals may disperse or exhibit transience at some life stages. In this paper we first conduct a simulation study to evaluate the robustness of estimators of density under ordinary SCR models when dispersal or transience is present in the population. Then, using both simulated and real data, we demonstrate that such models can easily be described in the BUGS language providing a practical framework for their analysis, which allows us to evaluate movement dynamics of species using capture–recapture data. We find that while estimators of density are extremely robust, even to pathological levels of movement (e.g., complete transience), the estimator of the spatial scale parameter of the encounter probability model is confounded with the dispersal/transience scale parameter. Thus, use of ordinary SCR models to make inferences about density is feasible, but interpretation of SCR model parameters in relation to movement should be avoided. Instead, when movement dynamics are of interest, such dynamics should be parameterized explicitly in the model.

  18. Capturing Multivariate Spatial Dependence: Model, Estimate and then Predict

    OpenAIRE

    Cressie, Noel; Burden, Sandy; Davis, Walter; Krivitsky, Pavel N.; Mokhtarian, Payam; Suesse, Thomas; Zammit-Mangion, Andrew

    2015-01-01

    Physical processes rarely occur in isolation, rather they influence and interact with one another. Thus, there is great benefit in modeling potential dependence between both spatial locations and different processes. It is the interaction between these two dependencies that is the focus of Genton and Kleiber's paper under discussion. We see the problem of ensuring that any multivariate spatial covariance matrix is nonnegative definite as important, but we also see it as a means to an end. Tha...

  19. Establishment of a new tropospheric delay correction model over China area

    Science.gov (United States)

    Song, Shuli; Zhu, Wenyao; Chen, Qinming; Liou, Yueian

    2011-12-01

    The tropospheric delay is one of the main error sources for radio navigation technologies and other ground- or space-based earth observation systems. In this paper, the spatial and temporal variations of the zenith tropospheric delay (ZTD), especially their dependence on altitude over China region, are analyzed using ECMWF (European Centre for Medium-Range Weather Forecast) pressure-level atmospheric data in 2004 and the ZTD series in 1999-2007 measured at 28 GPS stations from the Crustal Movement Observation Network of China (CMONC). A new tropospheric delay correction model (SHAO) is derived and a regional realization of this model for China region named SHAO-C is established. In SHAO-C model, ZTD is modeled directly by a cosine function together with an initial value and an amplitude at a reference height in each grid, and the variation of ZTD along altitude is fitted with a second-order polynomial. The coefficients of SHAO-C are generated using the meteorology data in China area and given at two degree latitude and longitude interval, featuring regional characteristics in order to facilitate a wide range of navigation and other surveying applications in and around China. Compared with the EGNOS (European Geostationary Navigation Overlay Service) model, which has been used globally and recommended by the European Union Wide Area Augmentation System, the ZTD prediction (in form of spatial and temporal projection) accuracy of the SHAO-C model is significantly improved over China region, especially at stations of higher altitudes. The reasons for the improvement are: (1) the reference altitude of SHAO-C parameters are given at the average height of each grid, and (2) more detailed description of complicated terrain variations in China is incorporated in the model. Therefore, the accumulated error at higher altitude can be reduced considerably. In contrast, the ZTD has to be calculated from the mean sea level with EGNOS and other models. Compared with the direct

  20. Primary Establishment of EWE Model in Caohai Nature Reserve

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    According to environmental data,Ecopath with Ecosim (EWE) model can quantitatively describe the energy flow in the production and consumption of function components of system by using trophodynamics,and accurately assess the biomass and stable state of aquatic ecosystem.In the paper,the basic principle and parameters of EWE model were introduced firstly,and the relationship between Q/B (the important parameter of EWE model) and basic life indices of fish was discussed,then the current study and typical r...

  1. Spatial Bayesian hierarchical modelling of extreme sea states

    Science.gov (United States)

    Clancy, Colm; O'Sullivan, John; Sweeney, Conor; Dias, Frédéric; Parnell, Andrew C.

    2016-11-01

    A Bayesian hierarchical framework is used to model extreme sea states, incorporating a latent spatial process to more effectively capture the spatial variation of the extremes. The model is applied to a 34-year hindcast of significant wave height off the west coast of Ireland. The generalised Pareto distribution is fitted to declustered peaks over a threshold given by the 99.8th percentile of the data. Return levels of significant wave height are computed and compared against those from a model based on the commonly-used maximum likelihood inference method. The Bayesian spatial model produces smoother maps of return levels. Furthermore, this approach greatly reduces the uncertainty in the estimates, thus providing information on extremes which is more useful for practical applications.

  2. GIS application on spatial landslide analysis using statistical based models

    Science.gov (United States)

    Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred F.

    2009-09-01

    This paper presents the assessment results of spatially based probabilistic three models using Geoinformation Techniques (GIT) for landslide susceptibility analysis at Penang Island in Malaysia. Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and supported with field surveys. Maps of the topography, soil type, lineaments and land cover were constructed from the spatial data sets. There are ten landslide related factors were extracted from the spatial database and the frequency ratio, fuzzy logic, and bivariate logistic regression coefficients of each factor was computed. Finally, landslide susceptibility maps were drawn for study area using frequency ratios, fuzzy logic and bivariate logistic regression models. For verification, the results of the analyses were compared with actual landslide locations in study area. The verification results show that bivariate logistic regression model provides slightly higher prediction accuracy than the frequency ratio and fuzzy logic models.

  3. 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.

  4. Was Thebes Necessary? Contingency in Spatial Modelling

    CERN Document Server

    Evans, Tim S

    2016-01-01

    When data is poor we resort to theory modelling. This is a two-step process. We have first to identify the appropriate type of model for the system under consideration and then to tailor it to the specifics of the case. To understand settlement formation, which is the concern of this paper, this not only involves choosing input parameter values such as site separations but also input functions which characterises the ease of travel between sites. Although the generic behaviour of the model is understood, the details are not. Different choices will necessarily lead to different outputs (for identical inputs). We can only proceed if choices that are "close" give outcomes are similar. Where there are local differences it suggests that there was no compelling reason for one outcome rather than the other. If these differences are important for the historic record we may interpret this as sensitivity to contingency. We re-examine the rise of Greek city states as first formulated by Rihll and Wilson in 1979, initial...

  5. Comparing spatial and temporal transferability of hydrological model parameters

    Science.gov (United States)

    Patil, Sopan D.; Stieglitz, Marc

    2015-06-01

    Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal aspects of catchment hydrological variability.

  6. Spatial mixture multiscale modeling for aggregated health data.

    Science.gov (United States)

    Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

    2016-09-01

    One of the main goals in spatial epidemiology is to study the geographical pattern of disease risks. For such purpose, the convolution model composed of correlated and uncorrelated components is often used. However, one of the two components could be predominant in some regions. To investigate the predominance of the correlated or uncorrelated component for multiple scale data, we propose four different spatial mixture multiscale models by mixing spatially varying probability weights of correlated (CH) and uncorrelated heterogeneities (UH). The first model assumes that there is no linkage between the different scales and, hence, we consider independent mixture convolution models at each scale. The second model introduces linkage between finer and coarser scales via a shared uncorrelated component of the mixture convolution model. The third model is similar to the second model but the linkage between the scales is introduced through the correlated component. Finally, the fourth model accommodates for a scale effect by sharing both CH and UH simultaneously. We applied these models to real and simulated data, and found that the fourth model is the best model followed by the second model.

  7. Establishing a business process reference model for Universities

    DEFF Research Database (Denmark)

    Svensson, Carsten; Hvolby, Hans-Henrik

    2012-01-01

    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...

  8. Modelling the spatial distribution of ammonia emissions in the UK

    Energy Technology Data Exchange (ETDEWEB)

    Hellsten, S. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom); Institute of Geography, School of Geosciences, University of Edinburgh, Drummond Street, Edinburgh EH8 9XP (United Kingdom); IVL Swedish Environmental Research Institute Ltd, P.O. Box 5302, SE-400 14 Gothenburg (Sweden)], E-mail: sofie.hellsten@ivl.se; Dragosits, U. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom); Place, C.J. [Institute of Geography, School of Geosciences, University of Edinburgh, Drummond Street, Edinburgh EH8 9XP (United Kingdom); Vieno, M. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom); Institute of Atmospheric and Environmental Science, School of GeoSciences, University of Edinburgh, Crew Building, The King' s buildings, West Mains Road, Edinburgh EH9 3JN (United Kingdom); Dore, A.J. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom); Misselbrook, T.H. [Institute of Grassland and Environmental Research, North Wyke, Okehampton, Exeter EX 2SB (United Kingdom); Tang, Y.S.; Sutton, M.A. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom)

    2008-08-15

    Ammonia emissions (NH{sub 3}) are characterised by a high spatial variability at a local scale. When modelling the spatial distribution of NH{sub 3} emissions, it is important to provide robust emission estimates, since the model output is used to assess potential environmental impacts, e.g. exceedance of critical loads. The aim of this study was to provide a new, updated spatial NH{sub 3} emission inventory for the UK for the year 2000, based on an improved modelling approach and the use of updated input datasets. The AENEID model distributes NH{sub 3} emissions from a range of agricultural activities, such as grazing and housing of livestock, storage and spreading of manures, and fertilizer application, at a 1-km grid resolution over the most suitable landcover types. The results of the emission calculation for the year 2000 are analysed and the methodology is compared with a previous spatial emission inventory for 1996. - It is important to provide robust estimates of the spatial distribution of ammonia emissions, since the model output is used to assess potential environmental impacts, e.g. through the exceedance of critical loads.

  9. Spatial flood extent modelling. A performance based comparison

    NARCIS (Netherlands)

    Werner, M.G.F.

    2004-01-01

    The rapid development of Geographical Information Systems (GIS) has together with the inherent spatial nature of hydrological modelling led to an equally rapid development in the integration between GIS and hydrological models. The advantages of integration are particularly apparent in flood extent

  10. Three-stage approach for dynamic traffic temporal-spatial model

    Institute of Scientific and Technical Information of China (English)

    陆化普; 孙智源; 屈闻聪

    2016-01-01

    In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model (DTTS) is established. With consideration of the temporal correlation, spatial correlation and historical correlation, a basic DTTS model is built. And a three-stage approach is put forward for the simplification and calibration of the basic DTTS model. Through critical sections pre-selection and critical time pre-selection, the first stage reduces the variable number of the basic DTTS model. In the second stage, variable coefficient calibration is implemented based on basic model simplification and stepwise regression analysis. Aimed at dynamic noise estimation, the characteristics of noise are summarized and an extreme learning machine is presented in the third stage. A case study based on a real-world road network in Beijing, China, is carried out to test the efficiency and applicability of proposed DTTS model and the three-stage approach.

  11. Distributed multi-criteria model evaluation and spatial association analysis

    Science.gov (United States)

    Scherer, Laura; Pfister, Stephan

    2015-04-01

    Model performance, if evaluated, is often communicated by a single indicator and at an aggregated level; however, it does not embrace the trade-offs between different indicators and the inherent spatial heterogeneity of model efficiency. In this study, we simulated the water balance of the Mississippi watershed using the Soil and Water Assessment Tool (SWAT). The model was calibrated against monthly river discharge at 131 measurement stations. Its time series were bisected to allow for subsequent validation at the same gauges. Furthermore, the model was validated against evapotranspiration which was available as a continuous raster based on remote sensing. The model performance was evaluated for each of the 451 sub-watersheds using four different criteria: 1) Nash-Sutcliffe efficiency (NSE), 2) percent bias (PBIAS), 3) root mean square error (RMSE) normalized to standard deviation (RSR), as well as 4) a combined indicator of the squared correlation coefficient and the linear regression slope (bR2). Conditions that might lead to a poor model performance include aridity, a very flat and steep relief, snowfall and dams, as indicated by previous research. In an attempt to explain spatial differences in model efficiency, the goodness of the model was spatially compared to these four phenomena by means of a bivariate spatial association measure which combines Pearson's correlation coefficient and Moran's index for spatial autocorrelation. In order to assess the model performance of the Mississippi watershed as a whole, three different averages of the sub-watershed results were computed by 1) applying equal weights, 2) weighting by the mean observed river discharge, 3) weighting by the upstream catchment area and the square root of the time series length. Ratings of model performance differed significantly in space and according to efficiency criterion. The model performed much better in the humid Eastern region than in the arid Western region which was confirmed by the

  12. Establishment of ocean dumping area capacity assessment model

    Institute of Scientific and Technical Information of China (English)

    WANG Zhizu; ZUO Juncheng; XU Ren; JIN Zuowen; CHEN Meixiang

    2016-01-01

    Dumping area capacity is mainly affected by the hydrodynamic process (tidal sediment, storm surge and wave, etc.) as well as the size and depth of dumping area. Based on three-dimensional ocean circulation model known as FVCOM (Finite Volume Coast and Ocean Model) and the stochastic dynamic statistical analysis model, taking advantage of dumping ground topography evolution and dumping quantity, the author aims to discuss the influence of hydrodynamic processes and dumping activity so as to built a new model of ocean dumping area capacity. With the data of depth and dumped amount in the dumping area, the changes of bottom topographic which caused by tidal current under the natural condition based on the FVCOM hydrodynamic and sediment module, the author strive to analyze the statistical relation of the changes for dumping amount, tidal current and bottom topographic. Through real data to fit revision coefficient values, which will be regarded as topographic changes reference value affected by wave and storm surges. Thus taking this evaluation as the long-term changes in the dumping capacity. In the premise of setting up the threshold of bottom topographic changes, the dumping area capacity is calculated. Take Yangtze Estuary No. 1 dumping area as an example, As the water depth reduces by 0.5 m annually, the dumping area capacity is about 6.7 million m3/a, the model results are in reasonable agreement with the actual amount. Then the model is validated in Luoyuan Bay dumping area, Shengsishangchuan Mountain dumping area, Dongding dumping area, Dongshan dumping area, and Wenzhou Port dumping area, it is turns out the results are similar to that of the actual observations.

  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.

    Science.gov (United States)

    Cummins, Bree; Cortez, Ricardo; Foppa, Ivo M; Walbeck, Justin; Hyman, James M

    2012-01-01

    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 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.

  16. Establishment of a novel cellular model for myxofibrosarcoma heterogeneity

    Science.gov (United States)

    Lohberger, Birgit; Stuendl, Nicole; Leithner, Andreas; Rinner, Beate; Sauer, Stefan; Kashofer, Karl; Liegl-Atzwanger, Bernadette

    2017-01-01

    Human cancers frequently display substantial intra-tumoural heterogeneity in virtually all distinguishable phenotypic features, such as cellular morphology, gene expression, and metastatic potential. In order to investigate tumour heterogeneity in myxofibrosarcoma, we established a novel myxofibrosarcoma cell line with two well defined sub-clones named MUG-Myx2a and MUG-Myx2b. The parental tumour tissue and both MUG-Myx2 cell lines showed the same STR profile. The fact that MUG-Myx2a showed higher proliferation activity, faster migration and enhanced tumourigenicity was of particular interest. NGS mutation analysis revealed corresponding mutations in the FGFR3, KIT, KDR and TP53 genes. In contrast, the MUG-Myx2a cell lines showed an additional PTEN mutation. Analysis of CNV uncovered a highly aberrant karyotype with frequent losses and gains in the tumour sample. The two MUG-Myx2 cell lines share several CNV features of the tumour tissue, while some CNVs are present only in the two cell lines. Furthermore, certain CNV gains and losses that are exclusive to either MUG-Myx2a or MUG-Myx2b, distinguish the two cell lines. As it is currently not possible to purchase two different sarcoma cell lines derived from the same patient, the novel myxofibrosarcoma cell lines MUG-Myx2a and MUG-Myx2b will be useful tools to study pathogenesis, tumour heterogeneity and treatment options. PMID:28304377

  17. Preclinical models for neuroblastoma: establishing a baseline for treatment.

    Directory of Open Access Journals (Sweden)

    Tal Teitz

    Full Text Available BACKGROUND: Preclinical models of pediatric cancers are essential for testing new chemotherapeutic combinations for clinical trials. The most widely used genetic model for preclinical testing of neuroblastoma is the TH-MYCN mouse. This neuroblastoma-prone mouse recapitulates many of the features of human neuroblastoma. Limitations of this model include the low frequency of bone marrow metastasis, the lack of information on whether the gene expression patterns in this system parallels human neuroblastomas, the relatively slow rate of tumor formation and variability in tumor penetrance on different genetic backgrounds. As an alternative, preclinical studies are frequently performed using human cell lines xenografted into immunocompromised mice, either as flank implant or orthtotopically. Drawbacks of this system include the use of cell lines that have been in culture for years, the inappropriate microenvironment of the flank or difficult, time consuming surgery for orthotopic transplants and the absence of an intact immune system. PRINCIPAL FINDINGS: Here we characterize and optimize both systems to increase their utility for preclinical studies. We show that TH-MYCN mice develop tumors in the paraspinal ganglia, but not in the adrenal, with cellular and gene expression patterns similar to human NB. In addition, we present a new ultrasound guided, minimally invasive orthotopic xenograft method. This injection technique is rapid, provides accurate targeting of the injected cells and leads to efficient engraftment. We also demonstrate that tumors can be detected, monitored and quantified prior to visualization using ultrasound, MRI and bioluminescence. Finally we develop and test a "standard of care" chemotherapy regimen. This protocol, which is based on current treatments for neuroblastoma, provides a baseline for comparison of new therapeutic agents. SIGNIFICANCE: The studies suggest that use of both the TH-NMYC model of neuroblastoma and the

  18. 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.

  19. Modelling the emergence of spatial patterns of economic activity

    CERN Document Server

    Yang, Jung-Hun; Frenken, Koen

    2012-01-01

    Understanding how spatial configurations of economic activity emerge is important when formulating spatial planning and economic policy. A simple model was proposed by Simon, who assumed that firms grow at a rate proportional to their size, and that new divisions of firms with certain probabilities relocate to other firms or to new centres of economic activity. Simon's model produces realistic results in the sense that the sizes of economic centres follow a Zipf distribution, which is also observed in reality. It lacks realism in the sense that mechanisms such as cluster formation, congestion (defined as an overly high density of the same activities) and dependence on the spatial distribution of external parties (clients, labour markets) are ignored. The present paper proposed an extension of the Simon model that includes both centripetal and centrifugal forces. Centripetal forces are included in the sense that firm divisions are more likely to settle in locations that offer a higher accessibility to other fi...

  20. Spatial distribution of emissions to air – the SPREAD model

    DEFF Research Database (Denmark)

    Plejdrup, Marlene Schmidt; Gyldenkærne, Steen

    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...

  1. Spatial correlations in bed load transport: evidence, importance, and modelling

    CERN Document Server

    Heyman, J; Mettra, F; Ancey, C

    2016-01-01

    This article examines the spatial {dynamics of bed load particles} in water. We focus particularly on the fluctuations of particle activity, which is defined as the number of moving particles per unit bed {length}. Based on a stochastic model recently proposed by \\citet{Ancey2013}, we derive the second moment of particle activity analytically; that is the spatial correlation functions of particle activity. From these expressions, we show that large moving particle clusters can develop spatially. Also, we provide evidence that fluctuations of particle activity are scale-dependent. Two characteristic lengths emerge from the model: a saturation length $\\ell_{sat}$ describing the length needed for a perturbation in particle activity to relax to the homogeneous solution, and a correlation length $\\ell_c$ describing the typical size of moving particle clusters. A dimensionless P\\'eclet number can also be defined according to the transport model. Three different experimental data sets are used to test the theoretica...

  2. Random spatial processes and geostatistical models for soil variables

    Science.gov (United States)

    Lark, R. M.

    2009-04-01

    Geostatistical models of soil variation have been used to considerable effect to facilitate efficient and powerful prediction of soil properties at unsampled sites or over partially sampled regions. Geostatistical models can also be used to investigate the scaling behaviour of soil process models, to design sampling strategies and to account for spatial dependence in the random effects of linear mixed models for spatial variables. However, most geostatistical models (variograms) are selected for reasons of mathematical convenience (in particular, to ensure positive definiteness of the corresponding variables). They assume some underlying spatial mathematical operator which may give a good description of observed variation of the soil, but which may not relate in any clear way to the processes that we know give rise to that observed variation in the real world. In this paper I shall argue that soil scientists should pay closer attention to the underlying operators in geostatistical models, with a view to identifying, where ever possible, operators that reflect our knowledge of processes in the soil. I shall illustrate how this can be done in the case of two problems. The first exemplar problem is the definition of operators to represent statistically processes in which the soil landscape is divided into discrete domains. This may occur at disparate scales from the landscape (outcrops, catchments, fields with different landuse) to the soil core (aggregates, rhizospheres). The operators that underly standard geostatistical models of soil variation typically describe continuous variation, and so do not offer any way to incorporate information on processes which occur in discrete domains. I shall present the Poisson Voronoi Tessellation as an alternative spatial operator, examine its corresponding variogram, and apply these to some real data. The second exemplar problem arises from different operators that are equifinal with respect to the variograms of the

  3. Image categorization based on spatial visual vocabulary model

    Science.gov (United States)

    Wang, Yuxin; He, Changqin; Guo, He; Feng, Zhen; Jia, Qi

    2010-08-01

    In this paper, we propose an approach to recognize scene categories by means of a novel method named spatial visual vocabulary. Firstly, we hierarchically divide images into sub regions and construct the spatial visual vocabulary by grouping the low-level features collected from every corresponding spatial sub region into a specified number of clusters using k-means algorithm. To recognize the category of a scene, the visual vocabulary distributions of all spatial sub regions are concatenated to form a global feature vector. The classification is obtained using LIBSVM, a support vector machine classifier. Our goal is to find a universal framework which is applicable to various types of features, so two kinds of features are used in the experiments: "V1-like" filters and PACT features. In almost all experimental cases, the proposed model achieves superior results. Source codes are available by email.

  4. 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.

  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.

  6. Establishment of a chronic left ventricular aneurysm model in rabbit

    Institute of Scientific and Technical Information of China (English)

    Cang-Song XIAO; Chang-Qing GAO; Li-Bing LI; Yao WANG; Tao ZHAO; Wei-Hua YE; Chong-Lei REN; Zhi-Yong LIU; Yang WU

    2014-01-01

    Objectives To establish a cost-effective and reproducible procedure for induction of chronic left ventricular aneurysm (LVA) in rabbits. Methods Acute myocardial infarction (AMI) was induced in 35 rabbits via concomitant ligation of the left anterior descending (LAD) coronary artery and the circumflex (Cx) branch at the middle portion. Development of AMI was co n-firmed by ST segment elevation and akinesis of the occluded area. Echocardiography, pathological evaluation, and agar i n-tra-chamber casting were utilized to validate the formation of LVA four weeks after the surgery. Left ventricular end systolic pressure (LVESP) and diastolic pressure (LVEDP) were measured before, immediately after and four weeks after ligation. D i-mensions of the ventricular chamber, thickness of the interventricular septum (IVS) and the left ventricular posterior wall (LVPW) left ventricular end diastolic volume (LVEDV) and systolic volume (LVESV), and ejection fraction (EF) were recorded by echo-cardiography. Results Thirty one (88.6%) rabbits survived myocardial infarction and 26 of them developed aneurysm (83.9%). The mean area of aneurysm was 33.4% ± 2.4% of the left ventricle. LVEF markedly decreased after LVA formation, whereas LVEDV, LVESV and the thickness of IVS as well as the dimension of ventricular chamber from apex to mitral valve annulus significantly increased. LVESP immediately dropped after ligation and recovered to a small extent after LVA formation. LVEDP progressively increased after ligation till LVA formation. Areas in the left ventricle (LV) that underwent fibrosis included the apex, anterior wall and lateral wall but not IVS. Agar intra-chamber cast showed that the bulging of LV wall was prominent in the area of aneurysm. Conclusions Ligation of LAD and Cx at the middle portion could induce develo pment of LVA at a mean area ratio of 33.4%±2.4%which involves the apex, anterior wall and lateral wall of the LV.

  7. 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

  8. Establishment and analysis of global gridded Tm Ts relationship model

    Institute of Scientific and Technical Information of China (English)

    Zeying Lan; Bao Zhang; Yichao Geng

    2016-01-01

    In ground-based GPS meteorology, Tm is a key parameter to calculate the conversion factor that can convert the zenith wet delay (ZWD) to precipitable water vapor (PWV). It is generally acknowledged that Tm is in an approximate linear relationship with surface temperature Ts, and the relationship presents regional variation. This paper employed sliding average method to calculate correlation coefficients and linear regression co-efficients between Tm and Ts at every 2? ? 2.5? grid point using Ts data from European Centre for Medium-Range Weather Forecasts (ECMWF) and Tm data from “GGOS Atmo-sphere”, yielding the grid and bilinear interpolation-based TmGrid model. Tested by Tm and Ts grid data, Constellation Observation System of Meteorology, Ionosphere, and Climate (COSMIC) data and radiosonde data, the TmGrid model shows a higher accuracy relative to the Bevis Tm ? Ts relationship which is widely used nowadays. The TmGrid model will be of certain practical value in high-precision PWV calculation.

  9. 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.

  10. 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.

  11. 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; ptechnique 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 osteosarcoma model was shown to be feasible: the take rate was high, surgical mortality was

  12. Forecasting unconventional resource productivity - A spatial Bayesian model

    Science.gov (United States)

    Montgomery, J.; O'sullivan, F.

    2015-12-01

    Today's low prices mean that unconventional oil and gas development requires ever greater efficiency and better development decision-making. Inter and intra-field variability in well productivity, which is a major contemporary driver of uncertainty regarding resource size and its economics is driven by factors including geological conditions, well and completion design (which companies vary as they seek to optimize their performance), and uncertainty about the nature of fracture propagation. Geological conditions are often not be well understood early on in development campaigns, but nevertheless critical assessments and decisions must be made regarding the value of drilling an area and the placement of wells. In these situations, location provides a reasonable proxy for geology and the "rock quality." We propose a spatial Bayesian model for forecasting acreage quality, which improves decision-making by leveraging available production data and provides a framework for statistically studying the influence of different parameters on well productivity. Our approach consists of subdividing a field into sections and forming prior distributions for productivity in each section based on knowledge about the overall field. Production data from wells is used to update these estimates in a Bayesian fashion, improving model accuracy far more rapidly and with less sensitivity to outliers than a model that simply establishes an "average" productivity in each section. Additionally, forecasts using this model capture the importance of uncertainty—either due to a lack of information or for areas that demonstrate greater geological risk. We demonstrate the forecasting utility of this method using public data and also provide examples of how information from this model can be combined with knowledge about a field's geology or changes in technology to better quantify development risk. This approach represents an important shift in the way that production data is used to guide

  13. ECoS, a framework for modelling hierarchical spatial systems.

    Science.gov (United States)

    Harris, John R W; Gorley, Ray N

    2003-10-01

    A general framework for modelling hierarchical spatial systems has been developed and implemented as the ECoS3 software package. The structure of this framework is described, and illustrated with representative examples. It allows the set-up and integration of sets of advection-diffusion equations representing multiple constituents interacting in a spatial context. Multiple spaces can be defined, with zero, one or two-dimensions and can be nested, and linked through constituent transfers. Model structure is generally object-oriented and hierarchical, reflecting the natural relations within its real-world analogue. Velocities, dispersions and inter-constituent transfers, together with additional functions, are defined as properties of constituents to which they apply. The resulting modular structure of ECoS models facilitates cut and paste model development, and template model components have been developed for the assembly of a range of estuarine water quality models. Published examples of applications to the geochemical dynamics of estuaries are listed.

  14. Area-to-point Kriging in spatial hedonic pricing models

    Science.gov (United States)

    Yoo, E.-H.; Kyriakidis, P. C.

    2009-12-01

    This paper proposes a geostatistical hedonic price model in which the effects of location on house values are explicitly modeled. The proposed geostatistical approach, namely area-to-point Kriging with External Drift (A2PKED), can take into account spatial dependence and spatial heteroskedasticity, if they exist. Furthermore, this approach has significant implications in situations where exhaustive area-averaged housing price data are available in addition to a subset of individual housing price data. In the case study, we demonstrate that A2PKED substantially improves the quality of predictions using apartment sale transaction records that occurred in Seoul, South Korea, during 2003. The improvement is illustrated via a comparative analysis, where predicted values obtained from different models, including two traditional regression-based hedonic models and a point-support geostatistical model, are compared to those obtained from the A2PKED model.

  15. 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.

  16. Modeling of Spatially Correlated Energetic Disorder in Organic Semiconductors.

    Science.gov (United States)

    Kordt, Pascal; Andrienko, Denis

    2016-01-12

    Mesoscale modeling of organic semiconductors relies on solving an appropriately parametrized master equation. Essential ingredients of the parametrization are site energies (driving forces), which enter the charge transfer rate between pairs of neighboring molecules. Site energies are often Gaussian-distributed and are spatially correlated. Here, we propose an algorithm that generates these energies with a given Gaussian distribution and spatial correlation function. The method is tested on an amorphous organic semiconductor, DPBIC, illustrating that the accurate description of correlations is essential for the quantitative modeling of charge transport in amorphous mesophases.

  17. Allergic disorders: A model for establishing how to prevent commondisease

    Directory of Open Access Journals (Sweden)

    Akiko Yamasaki

    2004-01-01

    Full Text Available Allergy to common agents, such as plant pollens, dust mites and foods, is termed atopy. Atopy is the principal cause of the chronic inflammatory diseases of eczema (the skin, hayfever (the nose and asthma (the lungs in children and young adults. Atopy affects millions of individuals in Japan and other developed countries and is a major source of chronic ill health in childhood and of major health expenditure. Current treatments only control symptoms and there is an urgent need for a more fundamental understanding of the origins of atopy in order to plan more effective treatment and prevention. This may become a useful model for other common multifactorial disease.

  18. Spatial modes in one-dimensional models for capillary jets

    Science.gov (United States)

    Guerrero, J.; González, H.; García, F. J.

    2016-03-01

    One-dimensional (1D) models are widely employed to simplify the analysis of axisymmetric capillary jets. These models postulate that, for slender deformations of the free surface, the radial profile of the axial velocity can be approximated as uniform (viscous slice, averaged, and Cosserat models) or parabolic (parabolic model). In classical works on spatial stability analysis with 1D models, considerable misinterpretation was generated about the modes yielded by each model. The already existing physical analysis of three-dimensional (3D) axisymmetric spatial modes enables us to relate these 1D spatial modes to the exact 3D counterparts. To do so, we address the surface stimulation problem, which can be treated as linear, by considering the effect of normal and tangential stresses to perturb the jet. A Green's function for a spatially local stimulation having a harmonic time dependence provides the general formalism to describe any time-periodic stimulation. The Green's function of this signaling problem is known to be a superposition of the spatial modes, but in fact these modes are of fundamental nature, i.e., not restricted to the surface stimulation problem. The smallness of the wave number associated with each mode is the criterion to validate or invalidate the 1D approaches. The proposed axial-velocity profiles (planar or parabolic) also have a remarkable influence on the outcomes of each 1D model. We also compare with the classical 3D results for (i) conditions for absolute instability, and (ii) the amplitude of the unstable mode resulting from both normal and tangential surface stress stimulation. Incidentally, as a previous task, we need to re-deduce 1D models in order to include eventual stresses of various possible origins (electrohydrodynamic, thermocapillary, etc.) applied on the free surface, which were not considered in the previous general formulations.

  19. Management model application at nested spatial levels in Mediterranean Basins

    Science.gov (United States)

    Lo Porto, Antonio; De Girolamo, Anna Maria; Froebrich, Jochen

    2014-05-01

    In the EU Water Framework Directive (WFD) implementation processes, hydrological and water quality models can be powerful tools that allow to design and test alternative management strategies, as well as judging their general feasibility and acceptance. Although in recent decades several models have been developed, their use in Mediterranean basins, where rivers have a temporary character, is quite complex and there is limited information in literature which can facilitate model applications and result evaluations in this region. The high spatial variability which characterizes rainfall events, soil hydrological properties and land uses of Mediterranean basin makes more difficult to simulate hydrological and water quality in this region than in other Countries. This variability also has several implications in modeling simulations results especially when simulations at different spatial scale are needed for watershed management purpose. It is well known that environmental processes operating at different spatial scale determine diverse impacts on water quality status (hydrological, chemical, ecological). Hence, the development of management strategies have to include both large scale (watershed) and local spatial scales approaches (e.g. stream reach). This paper presents the results of a study which analyzes how the spatial scale affects the results of hydrologic process and water quality of model simulations in a Mediterranean watershed. Several aspects involved in modeling hydrological and water quality processes at different spatial scale for river basin management are investigated including model data requirements, data availability, model results and uncertainty. A hydrologic and water quality model (SWAT) was used to simulate hydrologic processes and water quality at different spatial scales in the Candelaro river basin (Puglia, S-E Italy) and to design management strategies to reach as possible WFD goals. When studying a basin to assess its current status

  20. Establishment of a rat model for canine necrotizing meningoencephalitis (NME).

    Science.gov (United States)

    Park, E-S; Uchida, K; Nakayama, H

    2014-11-01

    The pathogenesis of necrotizing meningoencephalitis (NME), necrotizing leukoencephalitis (NLE), and granulomatous meningoencephalomyelitis (GME) is still uncertain, although they are considered immune-mediated diseases. The purpose of the present study is to generate a rodent model(s) of these diseases. Rats were injected with rat cerebral or cerebellar homogenate. Rats injected with cerebral homogenate (Cbr) exhibited vacuolar or malacic changes mainly in the cerebral cortex. CD3-positive T cells and Iba-1-positive and CD163-negative microglia infiltrated and activated around the lesions. IgG deposited in the glial fibrillary acid protein (GFAP)-positive glia limitans from the early phase, and CD3-positive T cells attached to GFAP-positive astrocytes. Autoantibodies against GFAP were detected in the sera. These pathological features of Cbr rats were consistent with those of canine NME. In contrast, rats injected with cerebral homogenate (Cbe) exhibited demyelinating lesions with inflammatory reactions in the cerebellum, brainstem, and spinal cord. The presence of demyelination and autoantibodies against myelin proteins in Cbe rats was similar to murine experimental autoimmune encephalitis and differed from NME, NLE, and GME. All the present findings indicate that autoantibodies together with microglia and T cells may play a major role in the pathogenesis of idiopathic canine meningoencephalomyelitis. © The Author(s) 2014.

  1. Spatial Reasoning Training Through Light Curves Of Model Asteroids

    Science.gov (United States)

    Ziffer, Julie; Nakroshis, Paul A.; Rudnick, Benjamin T.; Brautigam, Maxwell J.; Nelson, Tyler W.

    2015-11-01

    Recent research has demonstrated that spatial reasoning skills, long known to be crucial to math and science success, are teachable. Even short stints of training can improve spatial reasoning skills among students who lack them (Sorby et al., 2006). Teaching spatial reasoning is particularly valuable to women and minorities who, through societal pressure, often doubt their spatial reasoning skill (Hill et al., 2010). We have designed a hands on asteroid rotation lab that provides practice in spatial reasoning tasks while building the student’s understanding of photometry. For our tool, we mount a model asteroid, with any shape of our choosing, on a slowly rotating motor shaft, whose speed is controlled by the experimenter. To mimic an asteroid light curve, we place the model asteroid in a dark box, shine a movable light source upon our asteroid, and record the light reflected onto a moveable camera. Students may then observe changes in the light curve that result from varying a) the speed of rotation, b) the model asteroid’s orientation with respect to the motor axis, c) the model asteroid’s shape or albedo, and d) the phase angle. After practicing with our tool, students are asked to pair new objects to their corresponding light curves. To correctly pair objects to their light curves, students must imagine how light scattering off of a three dimensional rotating object is imaged on a ccd sensor plane, and then reduced to a series of points on a light curve plot. Through the use of our model asteroid, the student develops confidence in spatial reasoning skills.

  2. A Spatial Lattice Model Applied for Meteorological Visualization and Analysis

    Directory of Open Access Journals (Sweden)

    Mingyue Lu

    2017-03-01

    Full Text Available Meteorological information has obvious spatial-temporal characteristics. Although it is meaningful to employ a geographic information system (GIS to visualize and analyze the meteorological information for better identification and forecasting of meteorological weather so as to reduce the meteorological disaster loss, modeling meteorological information based on a GIS is still difficult because meteorological elements generally have no stable shape or clear boundary. To date, there are still few GIS models that can satisfy the requirements of both meteorological visualization and analysis. In this article, a spatial lattice model based on sampling particles is proposed to support both the representation and analysis of meteorological information. In this model, a spatial sampling particle is regarded as the basic element that contains the meteorological information, and the location where the particle is placed with the time mark. The location information is generally represented using a point. As these points can be extended to a surface in two dimensions and a voxel in three dimensions, if these surfaces and voxels can occupy a certain space, then this space can be represented using these spatial sampling particles with their point locations and meteorological information. In this case, the full meteorological space can then be represented by arranging numerous particles with their point locations in a certain structure and resolution, i.e., the spatial lattice model, and extended at a higher resolution when necessary. For practical use, the meteorological space is logically classified into three types of spaces, namely the projection surface space, curved surface space, and stereoscopic space, and application-oriented spatial lattice models with different organization forms of spatial sampling particles are designed to support the representation, inquiry, and analysis of meteorological information within the three types of surfaces. Cases

  3. 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

  4. Model Establishment for Simulating Soil Organic Carbon Dynamics

    Institute of Scientific and Technical Information of China (English)

    HUANG Yao; LIU Shi-liang; SHEN Qi-rong; ZONG Liang-gang

    2002-01-01

    Assuming that decomposition of organic matter in soils follows the first-order kinetics reaction,a computer model was developed to simulate soil organic matter dynamics. Organic matter in soils is divided up into two parts that include incorporated organic carbon from crop residues or other organic fertilizer and soil intrinsic carbon. The incorporated organic carbon was assumed to consist of two components, labile-C and resistant-C. The model was represented by a differential equation of dCi/dt = Ki× fT × fw × fs × Ci ( i = l,r, S ) and an integral equation of Cit = Cio × EXP ( Ki X fT X fw X fs X t ). Effect of soil parameters of temperature, moisture and texture on the decomposition was functioned by the fT, fw and fs, respectively.Data from laboratory incubation experiments were used to determine the first-order decay rate Ki and the fraction of labile-C of crop residues by employing a nonlinear method. The values of K for the components of labile-C and resistant-C and the soil intrinsic carbon were evaluated to be 0. 025,0. 080 × 10-2 and 0. 065 ×10-3d-1, respectively. The labile-C fraction of wheat straw, wheat roots, rice straw and rice roots were0.50, 0.25, 0.40 and 0.20, respectively. These values are related to the initial residue carbon-to-nitrogen ratio ( C/N) and lignin content.

  5. 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.

  6. Spatial object model[l]ing in fuzzy topological spaces : with applications to land cover change

    NARCIS (Netherlands)

    Tang, Xinming

    2004-01-01

    The central topic of this thesis focuses on the accommodation of fuzzy spatial objects in a GIS. Several issues are discussed theoretically and practically, including the definition of fuzzy spatial objects, the topological relations between them, the modeling of fuzzy spatial objects, the generatio

  7. 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.

  8. Mixtures of Polya trees for flexible spatial frailty survival modelling.

    Science.gov (United States)

    Zhao, Luping; Hanson, Timothy E; Carlin, Bradley P

    2009-06-01

    Mixtures of Polya trees offer a very flexible nonparametric approach for modelling time-to-event data. Many such settings also feature spatial association that requires further sophistication, either at the point level or at the lattice level. In this paper, we combine these two aspects within three competing survival models, obtaining a data analytic approach that remains computationally feasible in a fully hierarchical Bayesian framework using Markov chain Monte Carlo methods. We illustrate our proposed methods with an analysis of spatially oriented breast cancer survival data from the Surveillance, Epidemiology and End Results program of the National Cancer Institute. Our results indicate appreciable advantages for our approach over competing methods that impose unrealistic parametric assumptions, ignore spatial association or both.

  9. Noncausal spatial prediction filtering based on an ARMA model

    Institute of Scientific and Technical Information of China (English)

    Liu Zhipeng; Chen Xiaohong; Li Jingye

    2009-01-01

    Conventional f-x prediction filtering methods are based on an autoregressive model. The error section is first computed as a source noise but is removed as additive noise to obtain the signal, which results in an assumption inconsistency before and after filtering. In this paper, an autoregressive, moving-average model is employed to avoid the model inconsistency. Based on the ARMA model, a noncasual prediction filter is computed and a self-deconvolved projection filter is used for estimating additive noise in order to suppress random noise. The 1-D ARMA model is also extended to the 2-D spatial domain, which is the basis for noncasual spatial prediction filtering for random noise attenuation on 3-D seismic data. Synthetic and field data processing indicate this method can suppress random noise more effectively and preserve the signal simultaneously and does much better than other conventional prediction filtering methods.

  10. Heterogeneity Confounds Establishment of "a" Model Microbial Strain.

    Science.gov (United States)

    Keller, Nancy P

    2017-02-21

    Aspergillus fumigatus is a ubiquitous environmental mold and the leading cause of diverse human diseases ranging from allergenic bronchopulmonary aspergillosis (ABPA) to invasive pulmonary aspergillosis (IPA). Experimental investigations of the biology and virulence of this opportunistic pathogen have historically used a few type strains; however, it is increasingly observed with this fungus that heterogeneity among isolates potentially confounds the use of these reference isolates. Illustrating this point, Kowalski et al. (mBio 7:e01515-16, 2016, https://doi.org/10.1128/mBio.01515-16) demonstrated that variation in 16 environmental and clinical isolates of A. fumigatus correlated virulence with fitness in low oxygen, whereas Fuller et al. (mBio 7:e01517-16, 2016, https://doi.org/10.1128/mBio.01517-16) showed wide variation in light responses at a physiological and protein functionality level in 15 A. fumigatus isolates. In both studies, two commonly used type strains, Af293 and CEA10, displayed significant differences in physiological responses to abiotic stimuli and virulence in a murine model of IPA.

  11. Spatial cognition and crime: the study of mental models of spatial relations in crime analysis.

    Science.gov (United States)

    Luini, Lorenzo P; Scorzelli, Marco; Mastroberardino, Serena; Marucci, Francesco S

    2012-08-01

    Several studies employed different algorithms in order to investigate criminal's spatial behaviour and to identify mental models and cognitive strategies related to it. So far, a number of geographic profiling (GP) software have been implemented to analyse mobility and its relation to the way criminals are using spatial environment when committing a crime. Since crimes are usually perpetrated in the offender's high-awareness areas, those cognitive maps can be employed to create a map of the criminal's operating area to help investigators to circumscribe search areas. The aim of the present study was to verify accuracy of simple statistical analysis in predicting spatial mobility of a group of 30 non-criminal subjects. Results showed that statistics such as Mean Centre and Standard Distance were accurate in elaborating a GP for each subject according to the mobility area provided. Future analysis will be implemented using mobility information of criminal subjects and location-based software to verify whether there is a cognitive spatial strategy employed by them when planning and committing a crime.

  12. Millimeter wave imaging system modeling: spatial frequency domain calculation versus spatial domain calculation.

    Science.gov (United States)

    Qi, Feng; Tavakol, Vahid; Ocket, Ilja; Xu, Peng; Schreurs, Dominique; Wang, Jinkuan; Nauwelaers, Bart

    2010-01-01

    Active millimeter wave imaging systems have become a promising candidate for indoor security applications and industrial inspection. However, there is a lack of simulation tools at the system level. We introduce and evaluate two modeling approaches that are applied to active millimeter wave imaging systems. The first approach originates in Fourier optics and concerns the calculation in the spatial frequency domain. The second approach is based on wave propagation and corresponds to calculation in the spatial domain. We compare the two approaches in the case of both rough and smooth objects and point out that the spatial frequency domain calculation may suffer from a large error in amplitude of 50% in the case of rough objects. The comparison demonstrates that the concepts of point-spread function and f-number should be applied with careful consideration in coherent millimeter wave imaging systems. In the case of indoor applications, the near-field effect should be considered, and this is included in the spatial domain calculation.

  13. Transferability of Models for Estimating Paddy Rice Biomass from Spatial Plant Height Data

    Directory of Open Access Journals (Sweden)

    Nora Tilly

    2015-07-01

    Full Text Available It is known that plant height is a suitable parameter for estimating crop biomass. The aim of this study was to confirm the validity of spatial plant height data, which is derived from terrestrial laser scanning (TLS, as a non-destructive estimator for biomass of paddy rice on the field scale. Beyond that, the spatial and temporal transferability of established biomass regression models were investigated to prove the robustness of the method and evaluate the suitability of linear and exponential functions. In each growing season of two years, three campaigns were carried out on a field experiment and on a farmer’s conventionally managed field. Crop surface models (CSMs were generated from the TLS-derived point clouds for calculating plant height with a very high spatial resolution of 1 cm. High coefficients of determination between CSM-derived and manually measured plant heights (R2: 0.72 to 0.91 confirm the applicability of the approach. Yearly averaged differences between the measurements were ~7% and ~9%. Biomass regression models were established from the field experiment data sets, based on strong coefficients of determination between plant height and dry biomass (R2: 0.66 to 0.86 and 0.65 to 0.84 for linear and exponential models, respectively. The spatial and temporal transferability of the models to the farmer’s conventionally managed fields is supported by strong coefficients of determination between estimated and measured values (R2: 0.60 to 0.90 and 0.56 to 0.85 for linear and exponential models, respectively. Hence, the suitability of TLS-derived spatial plant height as a non-destructive estimator for biomass of paddy rice on the field scale was verified and the transferability demonstrated.

  14. Spatial optimum collocation model of urban land and its algorithm

    Science.gov (United States)

    Kong, Xiangqiang; Li, Xinyun

    2007-06-01

    Optimizing the allocation of urban land is that layout and fix position the various types of land-use in space, maximize the overall benefits of urban space (including economic, social, environment) using a certain method and technique. There is two problems need to deal with in optimizing the allocation of urban land in the technique: one is the quantitative structure, the other is the space structure. In allusion to these problems, according to the principle of spatial coordination, a kind of new optimum collocation model about urban land was put forward in this text. In the model, we give a target function and a set of "soft" constraint conditions, and the area proportions of various types of land-use are restricted to the corresponding allowed scope. Spatial genetic algorithm is used to manipulate and calculate the space of urban land, the optimum spatial collocation scheme can be gradually approached, in which the three basic operations of reproduction, crossover and mutation are all operated on the space. Taking the built-up areas of Jinan as an example, we did the spatial optimum collocation experiment of urban land, the spatial aggregation of various types is better, and an approving result was got.

  15. Multidimensional Big Spatial Data Modeling Through A Case Study: Lte Rf Subsystem Power Consumption Modeling

    DEFF Research Database (Denmark)

    Antón Castro, Francesc/François; Musiige, Deogratius; Mioc, Darka

    2016-01-01

    This paper presents a case study for comparing different multidimensional mathematical modeling methodologies used in multidimensional spatial big data modeling and proposing a new technique. An analysis of multidimensional modeling approaches (neural networks, polynomial interpolation and homotopy...

  16. A theory and a computational model of spatial reasoning with preferred mental models.

    Science.gov (United States)

    Ragni, Marco; Knauff, Markus

    2013-07-01

    Inferences about spatial arrangements and relations like "The Porsche is parked to the left of the Dodge and the Ferrari is parked to the right of the Dodge, thus, the Porsche is parked to the left of the Ferrari," are ubiquitous. However, spatial descriptions are often interpretable in many different ways and compatible with several alternative mental models. This article suggests that individuals tackle such indeterminate multiple-model problems by constructing a single, simple, and typical mental model but neglect other possible models. The model that first comes to reasoners' minds is the preferred mental model. It helps save cognitive resources but also leads to reasoning errors and illusory inferences. The article presents a preferred model theory and an instantiation of this theory in the form of a computational model, preferred inferences in reasoning with spatial mental models (PRISM). PRISM can be used to simulate and explain how preferred models are constructed, inspected, and varied in a spatial array that functions as if it were a spatial working memory. A spatial focus inserts tokens into the array, inspects the array to find new spatial relations, and relocates tokens in the array to generate alternative models of the problem description, if necessary. The article also introduces a general measure of difficulty based on the number of necessary focus operations (rather than the number of models). A comparison with results from psychological experiments shows that the theory can explain preferences, errors, and the difficulty of spatial reasoning problems.

  17. Function modeling improves the efficiency of spatial modeling using big data from remote sensing

    Science.gov (United States)

    John Hogland; Nathaniel Anderson

    2017-01-01

    Spatial modeling is an integral component of most geographic information systems (GISs). However, conventional GIS modeling techniques can require substantial processing time and storage space and have limited statistical and machine learning functionality. To address these limitations, many have parallelized spatial models using multiple coding libraries and have...

  18. 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.

  19. Lateral specialization in unilateral spatial neglect: a cognitive robotics model.

    Science.gov (United States)

    Conti, Daniela; Di Nuovo, Santo; Cangelosi, Angelo; Di Nuovo, Alessandro

    2016-08-01

    In this paper, we present the experimental results of an embodied cognitive robotic approach for modelling the human cognitive deficit known as unilateral spatial neglect (USN). To this end, we introduce an artificial neural network architecture designed and trained to control the spatial attentional focus of the iCub robotic platform. Like the human brain, the architecture is divided into two hemispheres and it incorporates bio-inspired plasticity mechanisms, which allow the development of the phenomenon of the specialization of the right hemisphere for spatial attention. In this study, we validate the model by replicating a previous experiment with human patients affected by the USN and numerical results show that the robot mimics the behaviours previously exhibited by humans. We also simulated recovery after the damage to compare the performance of each of the two hemispheres as additional validation of the model. Finally, we highlight some possible advantages of modelling cognitive dysfunctions of the human brain by means of robotic platforms, which can supplement traditional approaches for studying spatial impairments in humans.

  20. Spatial modeling on the nutrient retention of an estuary wetland

    NARCIS (Netherlands)

    Li, X.; Xiao, D.; Jongman, R.H.G.; Harms, W.B.; Bregt, A.K.

    2003-01-01

    There is a great potential to use the estuary wetland as a final filter for nutrient enriched river water, and reduce the possibility of coastal water eutrophication. Based upon field data, spatial models were designed on a stepwise basis to simulate the nutrient reduction function of the wetland in

  1. 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.

  2. 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....

  3. DESIGNING AN EFFECTIVE ORGANIZATIONAL EMPLOYEE MOTIVATION SYSTEM BASED ON ABCD MODEL FOR HOTEL ESTABLISHMENTS

    National Research Council Canada - National Science Library

    Onur Çakir; Meryem Akoglan Kozak

    2017-01-01

    .... Factor analyses and importance-satisfaction analysis were utilized to interpret data. CFA results demonstrated that ABCD model performed well in explaining employee motivation phenomenon in hotel establishments...

  4. 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...

  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, respectiv......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...... 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. Comparing spatial and temporal transferability of hydrological model parameters

    Science.gov (United States)

    Patil, Sopan; Stieglitz, Marc

    2015-04-01

    Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. In our view, such comparison is especially pertinent in the context of increasing appeal and popularity of the "trading space for time" approaches that are proposed for assessing the hydrological implications of anthropogenic climate change. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal

  7. 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.

  8. 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.

  9. Spatial distribution of emissions to air – the SPREAD model

    DEFF Research Database (Denmark)

    Plejdrup, Marlene Schmidt; Gyldenkærne, Steen

    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...... 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...

  10. Uniqueness of Petrov type D spatially inhomogeneous irrotational silent models

    CERN Document Server

    Apostolopoulos, P S; Apostolopoulos, Pantelis S; Carot, Jaume

    2006-01-01

    The consistency of the constraint with the evolution equations for spatially inhomogeneous and irrotational silent (SIIS) models of Petrov type I, demands that the former are preserved along the timelike congruence represented by the velocity of the dust fluid, leading to an infinite set of non-trivial constraints. This fact has been used to conjecture that the resulting models correspond to the spatially homogeneous (SH) models of Bianchi type I, at least for the case where the cosmological constant vanish. By exploiting the full set of the constraint equations as expressed in the 1+3 covariant formalism and using elements from the theory of the spacelike congruences, we provide a direct and simple proof of this conjecture for vacuum and dust fluid models, which shows that the Szekeres family of solutions represents the most general class of SIIS models. The suggested procedure also shows that, the uniqueness of the spatially inhomogeneous and irrotational models of Petrov type D is not affected by the prese...

  11. 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.

  12. Space in multi-agent systems modelling spatial processes

    Directory of Open Access Journals (Sweden)

    Petr Rapant

    2007-06-01

    Full Text Available Need for modelling of spatial processes arise in the spehere of geoinformation systems in the last time. Some processes (espetially natural ones can be modeled by means of using external tools, e. g. for modelling of contaminant transport in the environment. But in the case of socio-economic processes suitable tools interconnected with GIS are still in quest of reserch and development. One of the candidate technologies are so called multi-agent systems. Their theory is developed quite well, but they lack suitable means for dealing with space. This article deals with this problem and proposes solution for the field of a road transport modelling.

  13. Beyond the French Flag Model: Exploiting Spatial and Gene Regulatory Interactions for Positional Information

    Science.gov (United States)

    Hillenbrand, Patrick; Gerland, Ulrich; Tkačik, Gašper

    2016-01-01

    A crucial step in the early development of multicellular organisms involves the establishment of spatial patterns of gene expression which later direct proliferating cells to take on different cell fates. These patterns enable the cells to infer their global position within a tissue or an organism by reading out local gene expression levels. The patterning system is thus said to encode positional information, a concept that was formalized recently in the framework of information theory. Here we introduce a toy model of patterning in one spatial dimension, which can be seen as an extension of Wolpert’s paradigmatic “French Flag” model, to patterning by several interacting, spatially coupled genes subject to intrinsic and extrinsic noise. Our model, a variant of an Ising spin system, allows us to systematically explore expression patterns that optimally encode positional information. We find that optimal patterning systems use positional cues, as in the French Flag model, together with gene-gene interactions to generate combinatorial codes for position which we call “Counter” patterns. Counter patterns can also be stabilized against noise and variations in system size or morphogen dosage by longer-range spatial interactions of the type invoked in the Turing model. The simple setup proposed here qualitatively captures many of the experimentally observed properties of biological patterning systems and allows them to be studied in a single, theoretically consistent framework. PMID:27676252

  14. A spatial operator algebra for manipulator modeling and control

    Science.gov (United States)

    Rodriguez, G.; Kreutz, K.; Milman, M.

    1988-01-01

    A powerful new spatial operator algebra for modeling, control, and trajectory design of manipulators is discussed along with its implementation in the Ada programming language. Applications of this algebra to robotics include an operator representation of the manipulator Jacobian matrix; the robot dynamical equations formulated in terms of the spatial algebra, showing the complete equivalence between the recursive Newton-Euler formulations to robot dynamics; the operator factorization and inversion of the manipulator mass matrix which immediately results in O(N) recursive forward dynamics algorithms; the joint accelerations of a manipulator due to a tip contact force; the recursive computation of the equivalent mass matrix as seen at the tip of a manipulator; and recursive forward dynamics of a closed chain system. Finally, additional applications and current research involving the use of the spatial operator algebra are discussed in general terms.

  15. Classification of missing values in spatial data using spin models

    CERN Document Server

    Žukovič, Milan; 10.1103/PhysRevE.80.011116

    2013-01-01

    A problem of current interest is the estimation of spatially distributed processes at locations where measurements are missing. Linear interpolation methods rely on the Gaussian assumption, which is often unrealistic in practice, or normalizing transformations, which are successful only for mild deviations from the Gaussian behavior. We propose to address the problem of missing values estimation on two-dimensional grids by means of spatial classification methods based on spin (Ising, Potts, clock) models. The "spin" variables provide an interval discretization of the process values, and the spatial correlations are captured in terms of interactions between the spins. The spins at the unmeasured locations are classified by means of the "energy matching" principle: the correlation energy of the entire grid (including prediction sites) is estimated from the sample-based correlations. We investigate the performance of the spin classifiers in terms of computational speed, misclassification rate, class histogram an...

  16. Spatial-angular modeling of ground-based biaxial lidar

    Science.gov (United States)

    Agishev, Ravil R.

    1997-10-01

    Results of spatial-angular LIDAR modeling based on an efficiency criterion introduced are represented. Their analysis shows that a low spatial-angular efficiency of traditional VIS and NIR systems is a main cause of a low S/BR ratio at the photodetector input. It determines the considerable measurements errors and the following low accuracy of atmospheric optical parameters retrieval. As we have shown, the most effective protection against intensive sky background radiation for ground-based biaxial LIDAR's consist in forming of their angular field according to spatial-angular efficiency criterion G. Some effective approaches to high G-parameter value achievement to achieve the receiving system optimization are discussed.

  17. Modelling spatial patterns of urban growth in Africa.

    Science.gov (United States)

    Linard, Catherine; Tatem, Andrew J; Gilbert, Marius

    2013-10-01

    The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5-10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.

  18. Modelling spatial patterns of urban growth in Africa

    Science.gov (United States)

    Linard, Catherine; Tatem, Andrew J.; Gilbert, Marius

    2013-01-01

    The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers. PMID:25152552

  19. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Aguirre, Rolando C [Departamento de Luminotecnia, Luz y Vision, FACET, Universidad Nacional de Tucuman, Tucuman (Argentina); Felice, Carmelo J [Departamento de BioingenierIa, FACET, Universidad Nacional de Tucuman Argentina, Tucuman (Argentina); Colombo, Elisa M [Departamento de Luminotecnia, Luz y Vision, FACET, Universidad Nacional de Tucuman, Tucuman (Argentina)

    2007-11-15

    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.

  1. Spatial probabilistic pulsatility model for enhancing photoplethysmographic imaging systems

    Science.gov (United States)

    Amelard, Robert; Clausi, David A.; Wong, Alexander

    2016-11-01

    Photoplethysmographic imaging (PPGI) is a widefield noncontact biophotonic technology able to remotely monitor cardiovascular function over anatomical areas. Although spatial context can provide insight into physiologically relevant sampling locations, existing PPGI systems rely on coarse spatial averaging with no anatomical priors for assessing arterial pulsatility. Here, we developed a continuous probabilistic pulsatility model for importance-weighted blood pulse waveform extraction. Using a data-driven approach, the model was constructed using a 23 participant sample with a large demographic variability (11/12 female/male, age 11 to 60 years, BMI 16.4 to 35.1 kg·m-2). Using time-synchronized ground-truth blood pulse waveforms, spatial correlation priors were computed and projected into a coaligned importance-weighted Cartesian space. A modified Parzen-Rosenblatt kernel density estimation method was used to compute the continuous resolution-agnostic probabilistic pulsatility model. The model identified locations that consistently exhibited pulsatility across the sample. Blood pulse waveform signals extracted with the model exhibited significantly stronger temporal correlation (W=35,pbpm].

  2. Formation of regular spatial patterns in ratio-dependent predator-prey model driven by spatial colored-noise

    OpenAIRE

    Liu, Quan-Xing; Jin, Zhen

    2006-01-01

    Results are reported concerning the formation of spatial patterns in the two-species ratio-dependent predator-prey model driven by spatial colored-noise. The results show that there is a critical value with respect to the intensity of spatial noise for this system when the parameters are in the Turing space, above which the regular spatial patterns appear in two dimensions, but under which there are not regular spatial patterns produced. In particular, we investigate in two-dimensional space ...

  3. Testing in a Random Effects Panel Data Model with Spatially Correlated Error Components and Spatially Lagged Dependent Variables

    Directory of Open Access Journals (Sweden)

    Ming He

    2015-11-01

    Full Text Available We propose a random effects panel data model with both spatially correlated error components and spatially lagged dependent variables. We focus on diagnostic testing procedures and derive Lagrange multiplier (LM test statistics for a variety of hypotheses within this model. We first construct the joint LM test for both the individual random effects and the two spatial effects (spatial error correlation and spatial lag dependence. We then provide LM tests for the individual random effects and for the two spatial effects separately. In addition, in order to guard against local model misspecification, we derive locally adjusted (robust LM tests based on the Bera and Yoon principle (Bera and Yoon, 1993. We conduct a small Monte Carlo simulation to show the good finite sample performances of these LM test statistics and revisit the cigarette demand example in Baltagi and Levin (1992 to illustrate our testing procedures.

  4. Modified Spatial Channel Model for MIMO Wireless Systems

    Directory of Open Access Journals (Sweden)

    Pekka Kyösti

    2007-12-01

    Full Text Available The third generation partnership Project's (3GPP spatial channel model (SCM is a stochastic channel model for MIMO systems. Due to fixed subpath power levels and angular directions, the SCM model does not show the degree of variation which is encountered in real channels. In this paper, we propose a modified SCM model which has random subpath powers and directions and still produces Laplace shape angular power spectrum. Simulation results on outage MIMO capacity with basic and modified SCM models show that the modified SCM model gives constantly smaller capacity values. Accordingly, it seems that the basic SCM gives too small correlation between MIMO antennas. Moreover, the variance in capacity values is larger using the proposed SCM model. Simulation results were supported by the outage capacity results from a measurement campaign conducted in the city centre of Oulu, Finland.

  5. Modeling and analysis of Schistosoma Argonaute protein molecular spatial conformation

    Institute of Scientific and Technical Information of China (English)

    Jianhua Zhang; Zhigang Shang; Xiaohui Zhang; Yuntao Zhang

    2011-01-01

    Objective: To analyze the amino acid sequence composition, secondary structure, the spatial conformation of its domain and other characteristics of Argonaute protein. Methods:Bioinformatics tools and the internet server were used. Firstly, the amino acid sequence composition features of the Argonaute protein were analyzed, and the phylogenetic tree was constructed. Secondly, Argonaute protein’s distribution of secondary structure and its physicochemical properties were predicted. Lastly, the protein functional expression form of the domain group was established through the Phyre-based analysis on the spatial conformation of Argonaute protein domains. Results: 593 amino acids were encoded by Argonaute protein, the phylogenetic tree was constructed, and Argonaute protein’s distribution of secondary structure and its physicochemical properties were obtained through analysis. In addition, the functional expression form which comprised the N-terminal PAZ domain and C-terminal Piwi domain for the Argonaute protein was obtained with Phyre. Conclusions: The information relationship between the structure and function of the Argonaute protein can be initially established with bioinformatics tools and the internet server, and this provides the theoretical basis for further clarifying the function of Schistosoma Argonaute protein.

  6. Spatial Modeling of Iron Transformations Within Artificial Soil Aggregates

    Science.gov (United States)

    Kausch, M.; Meile, C.; Pallud, C.

    2008-12-01

    Structured soils exhibit significant variations in transport characteristics at the aggregate scale. Preferential flow occurs through macropores while predominantly diffusive exchange takes place in intra-aggregate micropores. Such environments characterized by mass transfer limitations are conducive to the formation of small-scale chemical gradients and promote strong spatial variation in processes controlling the fate of redox-sensitive elements such as Fe. In this study, we present a reactive transport model used to spatially resolve iron bioreductive processes occurring within a spherical aggregate at the interface between advective and diffusive domains. The model is derived from current conceptual models of iron(hydr)oxide (HFO) transformations and constrained by literature and experimental data. Data were obtained from flow-through experiments on artificial soil aggregates inoculated with Shewanella putrefaciens strain CN32, and include the temporal evolution of the bulk solution composition, as well as spatial information on the final solid phase distribution within aggregates. With all iron initially in the form of ferrihydrite, spatially heterogeneous formation of goethite/lepidocrocite, magnetite and siderite was observed during the course of the experiments. These transformations were reproduced by the model, which ascribes a central role to divalent iron as a driver of HFO transformations and master variable in the rate laws of the considered reaction network. The predicted dissolved iron breakthrough curves also match the experimental ones closely. Thus, the computed chemical concentration fields help identify factors governing the observed trends in the solid phase distribution patterns inside the aggregate. Building on a mechanistic description of transformation reactions, fluid flow and solute transport, the model was able to describe the observations and hence illustrates the importance of small-scale gradients and dynamics of bioreductive

  7. 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.

  8. 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)

  9. 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.

  10. 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.

  11. 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%.

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

    KAUST Repository

    Krupskii, Pavel

    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.

  13. Think continuous: Markovian Gaussian models in spatial statistics

    CERN Document Server

    Simpson, Daniel; Rue, Håvard

    2011-01-01

    Gaussian Markov random fields (GMRFs) are frequently used as computationally efficient models in spatial statistics. Unfortunately, it has traditionally been difficult to link GMRFs with the more traditional Gaussian random field models as the Markov property is difficult to deploy in continuous space. Following the pioneering work of Lindgren et al. (2011), we expound on the link between Markovian Gaussian random fields and GMRFs. In particular, we discuss the theoretical and practical aspects of fast computation with continuously specified Markovian Gaussian random fields, as well as the clear advantages they offer in terms of clear, parsimonious and interpretable models of anisotropy and non-stationarity.

  14. Spatial emission modelling for residential wood combustion in Denmark

    DEFF Research Database (Denmark)

    Plejdrup, Marlene Schmidt; Nielsen, Ole-Kenneth; Brandt, Jørgen

    2016-01-01

    Residential wood combustion (RWC) is a major contributor to atmospheric pollution especially for particulate matter. Air pollution has significant impact on human health, and it is therefore important to know the human exposure. For this purpose, it is necessary with a detailed high resolution...... model with the developed weighting factors (76 ton PM2.5) is in good agreement with the case study (95 ton PM2.5), and that the new model has improved the spatial emission distribution significantly compared to the previous model (284 ton PM2.5). Additionally, a sensitivity analysis was done...

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

    Science.gov (United States)

    Hill, Edward M; House, Thomas; Dhingra, Madhur S; Kalpravidh, Wantanee; Morzaria, Subhash; Osmani, Muzaffar G; Yamage, Mat; Xiao, Xiangming; Gilbert, Marius; Tildesley, Michael J

    2017-09-01

    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 these discrepancies in

  16. 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

  17. Forecasting the behaviour of complex landslides with a spatially distributed hydrological model

    Directory of Open Access Journals (Sweden)

    J.-P. Malet

    2005-01-01

    Full Text Available The relationships between rainfall, hydrology and landslide movement are often difficult to establish. In this context, ground-water flow analyses and dynamic modelling can help to clarify these complex relations, simulate the landslide hydrological behaviour in real or hypothetical situations, and help to forecast future scenarios based on environmental change. The primary objective of this study is to investigate the possibility of including more temporal and spatial information in landslide hydrology forecasting, by using a physically based spatially distributed model. Results of the hydrological and geomorphological investigation of the Super-Sauze earthflow, one of the persistently active landslide occurring in clay-rich material of the French Alps, are presented. Field surveys, continuous monitoring and interpretation of the data have shown that, in such material, the groundwater level fluctuates on a seasonal time scale, with a strong influence of the unsaturated zone. Therefore a coupled unsaturated/saturated model, incorporating Darcian saturated flow, fissure flow and meltwater flow is needed to adequately represent the landslide hydrology. The conceptual model is implemented in a 2.5-D spatially distributed hydrological model. The model is calibrated and validated on a multi-parameters database acquired on the site since 1997. The complex time-dependent and three-dimensional groundwater regime is well described, in both the short- and long-term. The hydrological model is used to forecast the future hydrological behaviour of the earthflow in response to potential environmental changes.

  18. Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models

    Science.gov (United States)

    Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea

    2014-05-01

    Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans 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. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.

  19. Spatial uncertainty assessment in modelling reference evapotranspiration at regional scale

    Directory of Open Access Journals (Sweden)

    G. Buttafuoco

    2010-07-01

    Full Text Available Evapotranspiration is one of the major components of the water balance and has been identified as a key factor in hydrological modelling. For this reason, several methods have been developed to calculate the reference evapotranspiration (ET0. In modelling reference evapotranspiration it is inevitable that both model and data input will present some uncertainty. Whatever model is used, the errors in the input will propagate to the output of the calculated ET0. Neglecting information about estimation uncertainty, however, may lead to improper decision-making and water resources management. One geostatistical approach to spatial analysis is stochastic simulation, which draws alternative and equally probable, realizations of a regionalized variable. Differences between the realizations provide a measure of spatial uncertainty and allow to carry out an error propagation analysis. Among the evapotranspiration models, the Hargreaves-Samani model was used.

    The aim of this paper was to assess spatial uncertainty of a monthly reference evapotranspiration model resulting from the uncertainties in the input attributes (mainly temperature at regional scale. A case study was presented for Calabria region (southern Italy. Temperature data were jointly simulated by conditional turning bands simulation with elevation as external drift and 500 realizations were generated.

    The ET0 was then estimated for each set of the 500 realizations of the input variables, and the ensemble of the model outputs was used to infer the reference evapotranspiration probability distribution function. This approach allowed to delineate the areas characterized by greater uncertainty, to improve supplementary sampling strategies and ET0 value predictions.

  20. 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...

  1. Representing spatial information in a computational model for network management

    Science.gov (United States)

    Blaisdell, James H.; Brownfield, Thomas F.

    1994-01-01

    While currently available relational database management systems (RDBMS) allow inclusion of spatial information in a data model, they lack tools for presenting this information in an easily comprehensible form. Computer-aided design (CAD) software packages provide adequate functions to produce drawings, but still require manual placement of symbols and features. This project has demonstrated a bridge between the data model of an RDBMS and the graphic display of a CAD system. It is shown that the CAD system can be used to control the selection of data with spatial components from the database and then quickly plot that data on a map display. It is shown that the CAD system can be used to extract data from a drawing and then control the insertion of that data into the database. These demonstrations were successful in a test environment that incorporated many features of known working environments, suggesting that the techniques developed could be adapted for practical use.

  2. An exactly solvable, spatial model of mutation accumulation in cancer

    Science.gov (United States)

    Paterson, Chay; Nowak, Martin A.; Waclaw, Bartlomiej

    2016-12-01

    One of the hallmarks of cancer is the accumulation of driver mutations which increase the net reproductive rate of cancer cells and allow them to spread. This process has been studied in mathematical models of well mixed populations, and in computer simulations of three-dimensional spatial models. But the computational complexity of these more realistic, spatial models makes it difficult to simulate realistically large and clinically detectable solid tumours. Here we describe an exactly solvable mathematical model of a tumour featuring replication, mutation and local migration of cancer cells. The model predicts a quasi-exponential growth of large tumours, even if different fragments of the tumour grow sub-exponentially due to nutrient and space limitations. The model reproduces clinically observed tumour growth times using biologically plausible rates for cell birth, death, and migration rates. We also show that the expected number of accumulated driver mutations increases exponentially in time if the average fitness gain per driver is constant, and that it reaches a plateau if the gains decrease over time. We discuss the realism of the underlying assumptions and possible extensions of the model.

  3. A marginal revenue equilibrium model for spatial water allocation

    Institute of Scientific and Technical Information of China (English)

    王劲峰; 刘昌明; 王智勇; 于静洁

    2002-01-01

    The outside water is transported into the water-shorted area. It is allocated among many sub-areas that composed the water-shorted area, in order to maximize the total benefit from the input water for the areas. This paper presents a model for spatial water allocation based on the marginal revenue of water utilization, taking the six southern districts of Hebei Province as an example.

  4. Spatial memory impairments in a prediabetic rat model

    OpenAIRE

    Soares,E.; Prediger, R. D.; Nunes, S.; A.A. Castro; Viana, S .D.; Lemos, C.; C. M. Souza; Agostinho, P; Cunha, R. A.; E. Carvalho; Ribeiro, C. A. Fontes; Reis, F.; PEREIRA, F. C.

    2013-01-01

    Diabetes is associated with an increased risk for brain disorders, namely cognitive impairments associated with hippocampal dysfunction underlying diabetic encephalopathy. However, the impact of a prediabetic state on cognitive function is unknown. Therefore, we now investigated whether spatial learning and memory deficits and the underlying hippocampal dysfunction were already present in a prediabetic animal model. Adult Wistar rats drinking high-sucrose (HSu) diet (35% sucrose solution duri...

  5. Rule-based spatial modeling with diffusing, geometrically constrained molecules

    Directory of Open Access Journals (Sweden)

    Lohel Maiko

    2010-06-01

    Full Text Available Abstract Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS, we have chosen an already existing formalism (BioNetGen for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Results Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules. When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. Conclusions We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial

  6. Rule-based spatial modeling with diffusing, geometrically constrained molecules

    OpenAIRE

    Lohel Maiko; Lenser Thorsten; Ibrahim Bashar; Gruenert Gerd; Hinze Thomas; Dittrich Peter

    2010-01-01

    Abstract Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction net...

  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. 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.

  9. Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling1

    Science.gov (United States)

    Brakebill, JW; Wolock, DM; Terziotti, SE

    2011-01-01

    Abstract 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. PMID:22457575

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

    Science.gov (United States)

    Brakebill, Jw; Wolock, Dm; Terziotti, Se

    2011-10-01

    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.

  11. A hierarchical model for spatial capture-recapture data

    Science.gov (United States)

    Royle, J. Andrew; Young, K.V.

    2008-01-01

    Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.

  12. 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.

  13. Evaluation of Spatial Agreement of Distinct Landslide Prediction Models

    Science.gov (United States)

    Sterlacchini, Simone; Bordogna, Gloria; Frigerio, Ivan

    2013-04-01

    The aim of the study was to assess the degree of spatial agreement of different predicted patterns in a majority of coherent landslide prediction maps with almost similar success and prediction rate curves. If two or more models have a similar performance, the choice of the best one is not a trivial operation and cannot be based on success and prediction rate curves only. In fact, it may happen that two or more prediction maps with similar accuracy and predictive power do not have the same degree of agreement in terms of spatial predicted patterns. The selected study area is the high Valtellina valley, in North of Italy, covering a surface of about 450 km2 where mapping of historical landslides is available. In order to assess landslide susceptibility, we applied the Weights of Evidence (WofE) modeling technique implemented by USGS by means of ARC-SDM tool. WofE efficiently investigate the spatial relationships among past events and multiple predisposing factors, providing useful information to identify the most probable location of future landslide occurrences. We have carried out 13 distinct experiments by changing the number of morphometric and geo-environmental explanatory variables in each experiment with the same training set and thus generating distinct models of landslide prediction, computing probability degrees of occurrence of landslides in each pixel. Expert knowledge and previous results from indirect statistically-based methods suggested slope, land use, and geology the best "driving controlling factors". The Success Rate Curve (SRC) was used to estimate how much the results of each model fit the occurrence of landslides used for the training of the models. The Prediction Rate Curve (PRC) was used to estimate how much the model predict the occurrence of landslides in the validation set. We found that the performances were very similar for different models. Also the dendrogram of the Cohen's kappa statistic and Principal Component Analysis (PCA) were

  14. Spatial self-organization in hybrid models of multicellular adhesion

    Science.gov (United States)

    Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

    2016-10-01

    Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

  15. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    Science.gov (United States)

    Hwang, Y.; Clark, M.; 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.

  16. Combining Spatial and Telemetric Features for Learning Animal Movement Models

    CERN Document Server

    Kapicioglu, Berk; Wikelski, Martin; Broderick, Tamara

    2012-01-01

    We introduce a new graphical model for tracking radio-tagged animals and learning their movement patterns. The model provides a principled way to combine radio telemetry data with an arbitrary set of userdefined, spatial features. We describe an efficient stochastic gradient algorithm for fitting model parameters to data and demonstrate its effectiveness via asymptotic analysis and synthetic experiments. We also apply our model to real datasets, and show that it outperforms the most popular radio telemetry software package used in ecology. We conclude that integration of different data sources under a single statistical framework, coupled with appropriate parameter and state estimation procedures, produces both accurate location estimates and an interpretable statistical model of animal movement.

  17. Induced gelation in a two-site spatial coagulation model

    OpenAIRE

    Siegmund-Schultze, Rainer; Wagner, Wolfgang

    2006-01-01

    A two-site spatial coagulation model is considered. Particles of masses $m$ and $n$ at the same site form a new particle of mass $m+n$ at rate $mn$. Independently, particles jump to the other site at a constant rate. The limit (for increasing particle numbers) of this model is expected to be nondeterministic after the gelation time, namely, one or two giant particles randomly jump between the two sites. Moreover, a new effect of induced gelation is observed--the gelation happening at the site...

  18. Spatial Pattern of an Epidemic Model with Cross-diffusion

    Institute of Scientific and Technical Information of China (English)

    LI Li; JIN Zhen; SUN Gui-Quan

    2008-01-01

    Pattern formation of a spatial epidemic model with both serf- and cross-diffusion is investigated. From the Turing theory, it is well known that Thring pattern formation cannot occur for the equal self-diffusion coefficients.However, combined with cross-diffusion, the system will show emergence of isolated groups, i.e., stripe-like or spotted or coexistence of both, which we show by both mathematical ana/ysis and numerical simulations. Our study shows that the interaction of self- and cross-diffusion can be considered as an important mechanism for the appearance of complex spatiotemporal dynamics in epidemic models.

  19. Modeling spatial accessibility to parks: a national study

    Directory of Open Access Journals (Sweden)

    Lu Hua

    2011-05-01

    Full Text Available Abstract Background Parks provide ideal open spaces for leisure-time physical activity and important venues to promote physical activity. The spatial configuration of parks, the number of parks and their spatial distribution across neighborhood areas or local regions, represents the basic park access potential for their residential populations. A new measure of spatial access to parks, population-weighted distance (PWD to parks, combines the advantages of current park access approaches and incorporates the information processing theory and probability access surface model to more accurately quantify residential population's potential spatial access to parks. Results The PWD was constructed at the basic level of US census geography - blocks - using US park and population data. This new measure of population park accessibility was aggregated to census tract, county, state and national levels. On average, US residential populations are expected to travel 6.7 miles to access their local neighborhood parks. There are significant differences in the PWD to local parks among states. The District of Columbia and Connecticut have the best access to local neighborhood parks with PWD of 0.6 miles and 1.8 miles, respectively. Alaska, Montana, and Wyoming have the largest PWDs of 62.0, 37.4, and 32.8 miles, respectively. Rural states in the western and Midwestern US have lower neighborhood park access, while urban states have relatively higher park access. Conclusions The PWD to parks provides a consistent platform for evaluating spatial equity of park access and linking with population health outcomes. It could be an informative evaluation tool for health professionals and policy makers. This new method could be applied to quantify geographic accessibility of other types of services or destinations, such as food, alcohol, and tobacco outlets.

  20. 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.

  1. 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.

  2. The Effect of 3D-Modeling Training on Students' Spatial Reasoning Relative to Gender and Grade

    Science.gov (United States)

    Šafhalter, Andrej; Vukman, Karin Bakracevic; Glodež, Srecko

    2016-01-01

    The aim of this research was to establish whether gender and age have an impact on spatial reasoning and its development through the use of 3D modeling. The study was conducted on a sample of 196 children from sixth to ninth grade, of whom 95 represented the experimental group and 101 the control group. The experimental group received 3D modeling…

  3. Spatial Model of Deforestation in Sumatra Islands Using Typological Approach

    Directory of Open Access Journals (Sweden)

    Nurdin Sulistiyono

    2015-12-01

    Full Text Available High rate of deforestation occurred in Sumatra Islands had been allegedly triggered by various factors. This study examined how the deforestation pattern was related to the typology of the area, as well as how the deforestation is being affected by many factors such as physical, biological, and socio-economic of the local community. The objective of this study was to formulate a spatial model of deforestation based on triggering factors within each typology in Sumatra Islands. The typology classes were developed on the basis of socio-economic factors using the standardized-euclidean distance measure and the memberships of each cluster was determined using the furthest neighbor method. The logistic regression method was used for modeling and estimating the spatial distribution of deforestation.Two deforestation typologies were distinguished in this study, namely typology 1 (regencies/cities with low deforestation rate and typology 2 (regencies/cities with high deforestation rate. The study found that growth rate of farm households could be used to assign each regencies or cities in Sumatra Islands into their corresponding typology. The resulted spatial model of deforestation from logistic regression analysis were logit (deforestation = 1.355 + (0.012*total of farm households – (0.08*elevation – (0.019*distance from road for typology 1 and logit (deforestation = 1.714 + (0.007*total of farm households – (0.021*slope – (0.051*elevation – (0.038* distance from road + (0.039* distance from river for typology 2, respectively. The accuracy test of deforestation model in 2000–2006 showed overall accuracy of 68.52% (typology 1 and 74.49% (typology 2, while model of deforestation in 2006–2012 showed overall accuracy of 65.37% (typology 1 and 72.24% (typology 2, respectively.

  4. Transient,spatially-varied recharge for groundwater modeling

    Science.gov (United States)

    Assefa, Kibreab; Woodbury, Allan

    2013-04-01

    This study is aimed at producing spatially and temporally varying groundwater recharge for transient groundwater modeling in a pilot watershed in the North Okanagan, Canada. The recharge modeling is undertaken by using a Richard's equation based finite element code (HYDRUS-1D) [Simunek et al., 2002], ArcGISTM [ESRI, 2011], ROSETTA [Schaap et al., 2001], in situ observations of soil temperature and soil moisture and a long term gridded climate data [Nielsen et al., 2010]. The public version of HYDUS-1D [Simunek et al., 2002] and another beta version with a detailed freezing and thawing module [Hansson et al., 2004] are first used to simulate soil temperature, snow pack and soil moisture over a one year experimental period. Statistical analysis of the results show both versions of HYDRUS-1D reproduce observed variables to the same degree. Correlation coefficients for soil temperature simulation were estimated at 0.9 and 0.8, at depths of 10 cm and 50 cm respectively; and for soil moisture, 0.8 and 0.6 at 10 cm and 50 cm respectively. This and other standard measures of model performance (root mean square error and average error) showed a promising performance of the HYDRUS-1D code in our pilot watershed. After evaluating model performance using field data and ROSETTA derived soil hydraulic parameters, the HYDRUS-1D code is coupled with ArcGISTM to produce spatially and temporally varying recharge maps throughout the Deep Creek watershed. Temporal and spatial analysis of 25 years daily recharge results at various representative points across the study watershed reveal significant temporal and spatial variations; average recharge estimated at 77.8 ± 50.8mm /year. This significant variation over the years, caused by antecedent soil moisture condition and climatic condition, illustrates the common flaw of assigning a constant percentage of precipitation throughout the simulation period. Groundwater recharge modeling has previously been attempted in the Okanagan Basin

  5. 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

  6. 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.

  7. 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 climate were confined to the Front Range, where a positive correlation exists with summer (June-Aug) and cool season (Nov-Apr) temperature range (Tmax-Tmin). Additionally, trees in the Front Range are almost exclusively situated in a random spatial pattern above timberline (4/5 sites). Random spatial patterns imply that positive feedback is of minimal importance and that trees are more closely aligned with broad scale changes in abiotic conditions. This tight coupling between climate and treeline vegetation in the Front Range helps explain synchronous ecological (tree establishment) and climate regime shifts (temperature) during the early 1950s. Similar to the Front Range, a majority of trees at upper treeline in the Bighorn Mountains are in a random spatial pattern, but their existence appears to be dependent on shelter availability in the lee of boulders. This contingency helps explain the lag time between a regime shift to more favorable temperatures and subsequent peaks in tree establishment. The Medicine Bow and Sangre de Cristo

  8. Joint Modeling of Multiple Crimes: A Bayesian Spatial Approach

    Directory of Open Access Journals (Sweden)

    Hongqiang Liu

    2017-01-01

    Full Text Available A multivariate Bayesian spatial modeling approach was used to jointly model the counts of two types of crime, i.e., burglary and non-motor vehicle theft, and explore the geographic pattern of crime risks and relevant risk factors. In contrast to the univariate model, which assumes independence across outcomes, the multivariate approach takes into account potential correlations between crimes. Six independent variables are included in the model as potential risk factors. In order to fully present this method, both the multivariate model and its univariate counterpart are examined. We fitted the two models to the data and assessed them using the deviance information criterion. A comparison of the results from the two models indicates that the multivariate model was superior to the univariate model. Our results show that population density and bar density are clearly associated with both burglary and non-motor vehicle theft risks and indicate a close relationship between these two types of crime. The posterior means and 2.5% percentile of type-specific crime risks estimated by the multivariate model were mapped to uncover the geographic patterns. The implications, limitations and future work of the study are discussed in the concluding section.

  9. Anchor cell signaling and vulval precursor cell positioning establish a reproducible spatial context during C. elegans vulval induction.

    Science.gov (United States)

    Grimbert, Stéphanie; Tietze, Kyria; Barkoulas, Michalis; Sternberg, Paul W; Félix, Marie-Anne; Braendle, Christian

    2016-08-01

    How cells coordinate their spatial positioning through intercellular signaling events is poorly understood. Here we address this topic using Caenorhabditis elegans vulval patterning during which hypodermal vulval precursor cells (VPCs) adopt distinct cell fates determined by their relative positions to the gonadal anchor cell (AC). LIN-3/EGF signaling by the AC induces the central VPC, P6.p, to adopt a 1° vulval fate. Exact alignment of AC and VPCs is thus critical for correct fate patterning, yet, as we show here, the initial AC-VPC positioning is both highly variable and asymmetric among individuals, with AC and P6.p only becoming aligned at the early L3 stage. Cell ablations and mutant analysis indicate that VPCs, most prominently 1° cells, move towards the AC. We identify AC-released LIN-3/EGF as a major attractive signal, which therefore plays a dual role in vulval patterning (cell alignment and fate induction). Additionally, compromising Wnt pathway components also induces AC-VPC alignment errors, with loss of posterior Wnt signaling increasing stochastic vulval centering on P5.p. Our results illustrate how intercellular signaling reduces initial spatial variability in cell positioning to generate reproducible interactions across tissues.

  10. May We Identify The Spatial Variability of Soil Hydraulic Properties Based On Measurements With "spatial Tdr"? A) Model Study

    Science.gov (United States)

    Zehe, E.; Becker, R.; Schädel, W.

    A dynamic system left without external disturbances, will always tend to a stable equilibrium state that is consistent with the internal physics. For natural soils such an equilibrium state is reached when the gradients of the total hydraulic potential tend to zero. This statement is still valid for heterogeneous soils, because the hydraulic po- tential is an intensive state variable and therefore continuous at discontinuities of the pore space. In contrary the soil water content is as an extensive property discontinu- ous at discontinuities of the pore space. Hence, a small scale soil moisture pattern that persists if the soil state tends to hydraulic equilibrium, reflects the lateral small scale variability of the pore space. The objectives of our study are to show a) whether and how we could use TDR observations to identify the small scale variability of the pore space. For that purpose we analyse artificial TDR measurements, taken from physi- cally based simulations of soil water dynamics in heterogeneous media. b) We want to introduce a new TDR technology which we call "Spatial TDR", that is suitable for that purposes. To produce the artificial TDR-datasets we generate random fields of soil porosity and saturated hydraulic conductivity with different statistical properties based on field data in a Luvisol and simulate artificial water dynamics in this model soil based on Richards-equation. Within this model soil we define several hypothetical "Spatial TDR" clusters, that differ in the lateral spacing and the number of the probes, in the temporal resolution of the hypothetical measurements and in the assumed mea- surement accuracy. If the model soil approaches hydraulic equilibrium, the remaining soil moisture pattern will be dominated by the statistical properties of the porosity. In contrary the variability of the hydraulic conductivity will dominate the soil moisture patterns during infiltration events. The hypothetical Spatial TDR measurements within the

  11. Modeling temporal and spatial variability of crop yield

    Science.gov (United States)

    Bonetti, S.; Manoli, G.; Scudiero, E.; Morari, F.; Putti, M.; Teatini, P.

    2014-12-01

    In a world of increasing food insecurity the development of modeling tools capable of supporting on-farm decision making processes is highly needed to formulate sustainable irrigation practices in order to preserve water resources while maintaining adequate crop yield. The design of these practices starts from the accurate modeling of soil-plant-atmosphere interaction. We present an innovative 3D Soil-Plant model that couples 3D hydrological soil dynamics with a mechanistic description of plant transpiration and photosynthesis, including a crop growth module. Because of its intrinsically three dimensional nature, the model is able to capture spatial and temporal patterns of crop yield over large scales and under various climate and environmental factors. The model is applied to a 25 ha corn field in the Venice coastland, Italy, that has been continuously monitored over the years 2010 and 2012 in terms of both hydrological dynamics and yield mapping. The model results satisfactorily reproduce the large variability observed in maize yield (from 2 to 15 ton/ha). This variability is shown to be connected to the spatial heterogeneities of the farmland, which is characterized by several sandy paleo-channels crossing organic-rich silty soils. Salt contamination of soils and groundwater in a large portion of the area strongly affects the crop yield, especially outside the paleo-channels, where measured salt concentrations are lower than the surroundings. The developed model includes a simplified description of the effects of salt concentration in soil water on transpiration. The results seem to capture accurately the effects of salt concentration and the variability of the climatic conditions occurred during the three years of measurements. This innovative modeling framework paves the way to future large scale simulations of farmland dynamics.

  12. GIS-Based Analytical Tools for Transport Planning: Spatial Regression Models for Transportation Demand Forecast

    Directory of Open Access Journals (Sweden)

    Simone Becker Lopes

    2014-04-01

    Full Text Available Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included. This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

  13. 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

  14. 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

  15. 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.

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

    NARCIS (Netherlands)

    Berends, H.; Smits, A.A.J.; Reymen, I.; Podoynitsyna, K.

    2013-01-01

    Although business model innovation may be a significant source of competitive advantage, the process of business model innovation has received scant attention in research. Therefore, we address the question of how established organizations develop and refine new configurations of business model

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

    NARCIS (Netherlands)

    Berends, H.; Smits, A.A.J.; Reymen, I.; Podoynitsyna, K.

    2013-01-01

    Although business model innovation may be a significant source of competitive advantage, the process of business model innovation has received scant attention in research. Therefore, we address the question of how established organizations develop and refine new configurations of business model comp

  18. The initial establishment of the tectonic block motion model of China from space geodetic data

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Using the velocity fields of 28 GPS sites in China and its contiguous area and International Terrestrial Reference Frame ITRF96, an initial tectonic block motion model of China was established. The model was quite consistent with those obtained from the geologic data. The model could show the sketch of China crustal horizontal motion.

  19. A Computational Model of Human-Robot Spatial Interactions Based on a Qualitative Trajectory Calculus

    Directory of Open Access Journals (Sweden)

    Christian Dondrup

    2015-03-01

    Full Text Available In this paper we propose a probabilistic sequential model of Human-Robot Spatial Interaction (HRSI using a well-established Qualitative Trajectory Calculus (QTC to encode HRSI between a human and a mobile robot in a meaningful, tractable, and systematic manner. Our key contribution is to utilise QTC as a state descriptor and model HRSI as a probabilistic sequence of such states. Apart from the sole direction of movements of human and robot modelled by QTC, attributes of HRSI like proxemics and velocity profiles play vital roles for the modelling and generation of HRSI behaviour. In this paper, we particularly present how the concept of proxemics can be embedded in QTC to facilitate richer models. To facilitate reasoning on HRSI with qualitative representations, we show how we can combine the representational power of QTC with the concept of proxemics in a concise framework, enriching our probabilistic representation by implicitly modelling distances. We show the appropriateness of our sequential model of QTC by encoding different HRSI behaviours observed in two spatial interaction experiments. We classify these encounters, creating a comparative measurement, showing the representational capabilities of the model.

  20. Combining microsimulation and spatial interaction models for retail location analysis

    Science.gov (United States)

    Nakaya, Tomoki; Fotheringham, A. Stewart; Hanaoka, Kazumasa; Clarke, Graham; Ballas, Dimitris; Yano, Keiji

    2007-12-01

    Although the disaggregation of consumers is crucial in understanding the fragmented markets that are dominant in many developed countries, it is not always straightforward to carry out such disaggregation within conventional retail modelling frameworks due to the limitations of data. In particular, consumer grouping based on sampled data is not assured to link with the other statistics that are vital in estimating sampling biases and missing variables in the sampling survey. To overcome this difficulty, we propose a useful combination of spatial interaction modelling and microsimulation approaches for the reliable estimation of retail interactions based on a sample survey of consumer behaviour being linked with other areal statistics. We demonstrate this approach by building an operational retail interaction model to estimate expenditure flows from households to retail stores in a local city in Japan, Kusatsu City.

  1. Spatial model for transmission of mosquito-borne diseases

    Science.gov (United States)

    Kon, Cynthia Mui Lian; Labadin, Jane

    2015-05-01

    In this paper, a generic model which takes into account spatial heterogeneity for the dynamics of mosquito-borne diseases is proposed. The dissemination of the disease is described by a system of reaction-diffusion partial differential equations. Host human and vector mosquito populations are divided into susceptible and infectious classes. Diffusion is considered to occur in all classes of both populations. Susceptible humans are infected when bitten by infectious mosquitoes. Susceptible mosquitoes bite infectious humans and become infected. The biting rate of mosquitoes is considered to be density dependent on the total human population in different locations. The system is solved numerically and results are shown.

  2. 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 (<60 d at ≤10°C) in these areas for codling moth to break diapause. Models predicted suitable conditions in South Korea and 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.

  3. 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

  4. A Spatial Clustering Approach for Stochastic Fracture Network Modelling

    Science.gov (United States)

    Seifollahi, S.; Dowd, P. A.; Xu, C.; Fadakar, A. Y.

    2014-07-01

    Fracture network modelling plays an important role in many application areas in which the behaviour of a rock mass is of interest. These areas include mining, civil, petroleum, water and environmental engineering and geothermal systems modelling. The aim is to model the fractured rock to assess fluid flow or the stability of rock blocks. One important step in fracture network modelling is to estimate the number of fractures and the properties of individual fractures such as their size and orientation. Due to the lack of data and the complexity of the problem, there are significant uncertainties associated with fracture network modelling in practice. Our primary interest is the modelling of fracture networks in geothermal systems and, in this paper, we propose a general stochastic approach to fracture network modelling for this application. We focus on using the seismic point cloud detected during the fracture stimulation of a hot dry rock reservoir to create an enhanced geothermal system; these seismic points are the conditioning data in the modelling process. The seismic points can be used to estimate the geographical extent of the reservoir, the amount of fracturing and the detailed geometries of fractures within the reservoir. The objective is to determine a fracture model from the conditioning data by minimizing the sum of the distances of the points from the fitted fracture model. Fractures are represented as line segments connecting two points in two-dimensional applications or as ellipses in three-dimensional (3D) cases. The novelty of our model is twofold: (1) it comprises a comprehensive fracture modification scheme based on simulated annealing and (2) it introduces new spatial approaches, a goodness-of-fit measure for the fitted fracture model, a measure for fracture similarity and a clustering technique for proposing a locally optimal solution for fracture parameters. We use a simulated dataset to demonstrate the application of the proposed approach

  5. Spatial transferability of landscape-based hydrological models

    Science.gov (United States)

    Gao, Hongkai; Hrachowitz, Markus; Fenicia, Fabrizio; Gharari, Shervan; Sriwongsitanon, Nutchanart; Savenije, Hubert

    2015-04-01

    Landscapes, mainly distinguished by land surface topography and vegetation cover, are crucial in defining runoff generation mechanisms, interception capacity and transpiration processes. Landscapes information provides modelers with a way to take into account catchment heterogeneity, while simultaneously keeping model complexity low. A landscape-based hydrological modelling framework (FLEX-Topo), with parallel model structures, was developed and tested in various catchments with diverse climate, topography and land cover conditions. Landscape classification is the basic and most crucial procedure to create a tailor-made model for a certain catchment, as it explicitly relates hydrologic similarity to landscape similarity, which is the base of this type of models. Therefore, the study catchment is classified into different landscapes units that fulfil similar hydrological function, based on classification criteria such as the height above the nearest drainage, slope, aspect and land cover. At present, to suggested model includes four distinguishable landscapes: hillslopes, terraces/plateaus, riparian areas, and glacierized areas. Different parallel model structures are then associated with the different landscape units to describe their different dominant runoff generation mechanisms. These hydrological units are parallel and only connected by groundwater reservoir. The transferability of this landscape-based model can then be compared with the transferability of a lumped model. In this study, FLEX-Topo was developed and tested in three study sites: two cold-arid catchments in China (the upper Heihe River and the Urumqi Glacier No1 catchment), and one tropical catchment in Thailand (the upper Ping River). Stringent model tests indicate that FLEX-Topo, allowing for more process heterogeneity than lumped model formulations, exhibits higher capabilities to be spatially transferred. Furthermore, the simulated water balances, including internal fluxes, hydrograph

  6. Spatial air pollution modelling for a West-African town

    Directory of Open Access Journals (Sweden)

    Sirak Zenebe Gebreab

    2015-11-01

    Full Text Available Land use regression (LUR modelling is a common approach used in European and Northern American epidemiological studies to assess urban and traffic related air pollution exposures. Studies applying LUR in Africa are lacking. A need exists to understand if this approach holds for an African setting, where urban features, pollutant exposures and data availability differ considerably from other continents. We developed a parsimonious regression model based on 48-hour nitrogen dioxide (NO2 concentrations measured at 40 sites in Kaédi, a medium sized West-African town, and variables generated in a geographic information system (GIS. Road variables and settlement land use characteristics were found to be important predictors of 48-hour NO2 concentration in the model. About 68% of concentration variability in the town was explained by the model. The model was internally validated by leave-one-out cross-validation and it was found to perform moderately well. Furthermore, its parameters were robust to sampling variation. We applied the model at 100 m pixels to create a map describing the broad spatial pattern of NO2 across Kaédi. In this research, we demonstrated the potential for LUR as a valid, cost-effective approach for air pollution modelling and mapping in an African town. If the methodology were to be adopted by environmental and public health authorities in these regions, it could provide a quick assessment of the local air pollution burden and potentially support air pollution policies and guidelines.

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. Integrated hydrologic modeling: Effects of spatial scale, discretization and initialization

    Science.gov (United States)

    Seck, A.; Welty, C.; Maxwell, R. M.

    2011-12-01

    Groundwater discharge contributes significantly to the annual flows of Chesapeake Bay tributaries and is presumed to contribute to the observed lag time between the implementation of management actions and the environmental response in the Chesapeake Bay. To investigate groundwater fluxes and flow paths and interaction with surface flow, we have developed a fully distributed integrated hydrologic model of the Chesapeake Bay Watershed using ParFlow. Here we present a comparison of model spatial resolution and initialization methods. We have studied the effect of horizontal discretization on overland flow processes at a range of scales. Three nested model domains have been considered: the Monocacy watershed (5600 sq. km), the Potomac watershed (92000 sq. km) and the Chesapeake Bay watershed (400,000 sq. km). Models with homogeneous subsurface and topographically-derived slopes were evaluated at 500-m, 1000-m, 2000-m, and 4000-m grid resolutions. Land surface slopes were derived from resampled DEMs and corrected using stream networks. Simulation results show that the overland flow processes are reasonably well represented with a resolution up to 2000 m. We observe that the effects of horizontal resolution dissipate with larger scale models. Using a homogeneous model that includes subsurface and surface terrain characteristics, we have evaluated various initialization methods for the integrated Monocacy watershed model. This model used several options for water table depths and two rainfall forcing methods including (1) a synthetic rainfall-recession cycle corresponding to the region's average annual rainfall rate, and (2) an initial shut-off of rainfall forcing followed by a rainfall-recession cycling. Results show the dominance of groundwater generated runoff during a first phase of the simulation followed by a convergence towards more balanced runoff generation mechanisms. We observe that the influence of groundwater runoff increases in dissected relief areas

  12. 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.

  13. Spatial Modeling in The Coastal Area of East Java Province

    Science.gov (United States)

    Fadlilah Kurniawati, Ummi

    2017-07-01

    The existence of gaps that occur between regions, shows that it is a reasonable process considering that each region has different initial endowment factors. The first step that can be done to controll disparity is know what is the benchmark of the gap. The revenue growth indicator is one of benchmark for measuring regional disparities. The regional output is represented by the gross domestic regional income per capita. Concerning the phenomenon of regional disparity, East Java Province is concentrated in the north-south part, especially in coastal areas is an early indication of the gap. This is what prompted the analysis of predictor factors affecting the disparity in East Java Coastal Areas through a spatial modeling approach. Spatial modeling is done on the consideration that there are different local characteristics or potentials in each regency / city. Factors Economic growth, social factors, and physical development factors are the main factors in this study will be described in derived variables to obtain a clear picture of the influence of each factor to the disparity that occurred in the Coastal Region of East Java Province.

  14. Spatial Model of Sky Brightness Magnitude in Langkawi Island, Malaysia

    Science.gov (United States)

    Redzuan Tahar, Mohammad; Kamarudin, Farahana; Umar, Roslan; Khairul Amri Kamarudin, Mohd; Hazmin Sabri, Nor; Ahmad, Karzaman; Rahim, Sobri Abdul; Sharul Aikal Baharim, Mohd

    2017-03-01

    Sky brightness is an essential topic in the field of astronomy, especially for optical astronomical observations that need very clear and dark sky conditions. This study presents the spatial model of sky brightness magnitude in Langkawi Island, Malaysia. Two types of Sky Quality Meter (SQM) manufactured by Unihedron are used to measure the sky brightness on a moonless night (or when the Moon is below the horizon), when the sky is cloudless and the locations are at least 100 m from the nearest light source. The selected locations are marked by their GPS coordinates. The sky brightness data obtained in this study were interpolated and analyzed using a Geographic Information System (GIS), thus producing a spatial model of sky brightness that clearly shows the dark and bright sky areas in Langkawi Island. Surprisingly, our results show the existence of a few dark sites nearby areas of high human activity. The sky brightness of 21.45 mag arcsec{}-2 in the Johnson-Cousins V-band, as the average of sky brightness equivalent to 2.8 × {10}-4{cd} {{{m}}}-2 over the entire island, is an indication that the island is, overall, still relatively dark. However, the amount of development taking place might reduce the number in the near future as the island is famous as a holiday destination.

  15. Spatial Model of Sky Brightness Magnitude in Langkawi Island, Malaysia

    Science.gov (United States)

    Redzuan Tahar, Mohammad; Kamarudin, Farahana; Umar, Roslan; Khairul Amri Kamarudin, Mohd; Sabri, Nor Hazmin; Ahmad, Karzaman; Rahim, Sobri Abdul; Sharul Aikal Baharim, Mohd

    2017-03-01

    Sky brightness is an essential topic in the field of astronomy, especially for optical astronomical observations that need very clear and dark sky conditions. This study presents the spatial model of sky brightness magnitude in Langkawi Island, Malaysia. Two types of Sky Quality Meter (SQM) manufactured by Unihedron are used to measure the sky brightness on a moonless night (or when the Moon is below the horizon), when the sky is cloudless and the locations are at least 100 m from the nearest light source. The selected locations are marked by their GPS coordinates. The sky brightness data obtained in this study were interpolated and analyzed using a Geographic Information System (GIS), thus producing a spatial model of sky brightness that clearly shows the dark and bright sky areas in Langkawi Island. Surprisingly, our results show the existence of a few dark sites nearby areas of high human activity. The sky brightness of 21.45 mag arcsec{}-2 in the Johnson-Cousins V-band, as the average of sky brightness equivalent to 2.8 × {10}-4{cd} {{{m}}}-2 over the entire island, is an indication that the island is, overall, still relatively dark. However, the amount of development taking place might reduce the number in the near future as the island is famous as a holiday destination.

  16. Moving from spatially segregated to transparent motion: A modelling approach.

    Science.gov (United States)

    Durant, Szonya; Donoso-Barrera, Alejandra; Tan, Sovira; Johnston, Alan

    2006-03-22

    Motion transparency, in which patterns of moving elements group together to give the impression of lacy overlapping surfaces, provides an important challenge to models of motion perception. It has been suggested that we perceive transparent motion when the shape of the velocity histogram of the stimulus is bimodal. To investigate this further, random-dot kinematogram motion sequences were created to simulate segregated (perceptually spatially separated) and transparent (perceptually overlapping) motion. The motion sequences were analysed using the multi-channel gradient model (McGM) to obtain the speed and direction at every pixel of each frame of the motion sequences. The velocity histograms obtained were found to be quantitatively similar and all were bimodal. However, the spatial and temporal properties of the velocity field differed between segregated and transparent stimuli. Transparent stimuli produced patches of rightward and leftward motion that varied in location over time. This demonstrates that we can successfully differentiate between these two types of motion on the basis of the time varying local velocity field. However, the percept of motion transparency cannot be based simply on the presence of a bimodal velocity histogram.

  17. Spatially-explicit models of global tree density

    Science.gov (United States)

    Glick, Henry B.; Bettigole, Charlie; Maynard, Daniel S.; Covey, Kristofer R.; Smith, Jeffrey R.; Crowther, Thomas W.

    2016-08-01

    Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services.

  18. Hierarchical spatial capture-recapture models: Modeling population density from stratified populations

    Science.gov (United States)

    Royle, J. Andrew; Converse, Sarah J.

    2014-01-01

    Capture–recapture studies are often conducted on populations that are stratified by space, time or other factors. In this paper, we develop a Bayesian spatial capture–recapture (SCR) modelling framework for stratified populations – when sampling occurs within multiple distinct spatial and temporal strata.We describe a hierarchical model that integrates distinct models for both the spatial encounter history data from capture–recapture sampling, and also for modelling variation in density among strata. We use an implementation of data augmentation to parameterize the model in terms of a latent categorical stratum or group membership variable, which provides a convenient implementation in popular BUGS software packages.We provide an example application to an experimental study involving small-mammal sampling on multiple trapping grids over multiple years, where the main interest is in modelling a treatment effect on population density among the trapping grids.Many capture–recapture studies involve some aspect of spatial or temporal replication that requires some attention to modelling variation among groups or strata. We propose a hierarchical model that allows explicit modelling of group or strata effects. Because the model is formulated for individual encounter histories and is easily implemented in the BUGS language and other free software, it also provides a general framework for modelling individual effects, such as are present in SCR models.

  19. 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.

  20. Establishment of Statistical Model for Precipitation Prediction in the Flood Season in China

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The research aimed to establish the regression model which was used to predict the precipitation in the flood season in China.[Method] Based on statistical model,North Atlantic oscillation index and the sea surface temperature index in development and declining stages of ENSO were used to predict East Asian summer monsoon index.After the stations were divided into 16 zones,the same factors were used to establish the regression model predicting the station precipitation in the flood season in Chi...

  1. Establishment of a superficial skin infection model in mice by using Staphylococcus aureus and Streptococcus pyogenes.

    Science.gov (United States)

    Kugelberg, Elisabeth; Norström, Tobias; Petersen, Thomas K; Duvold, Tore; Andersson, Dan I; Hughes, Diarmaid

    2005-08-01

    A new animal model for the purpose of studying superficial infections is presented. In this model an infection is established by disruption of the skin barrier by partial removal of the epidermal layer by tape stripping and subsequent application of the pathogens Staphylococcus aureus and Streptococcus pyogenes. The infection and the infection route are purely topical, in contrast to those used in previously described animal models in mice, such as the skin suture-wound model, where the infection is introduced into the deeper layers of the skin. Thus, the present model is considered more biologically relevant for the study of superficial skin infections in mice and humans. Established topical antibiotic treatments are shown to be effective. The procedures involved in the model are simple, a feature that increases throughput and reproducibility. This new model should be applicable to the evaluation of novel antimicrobial treatments of superficial infections caused by S. aureus and S. pyogenes.

  2. Spatial-temporal assessment of climate model drifts

    Science.gov (United States)

    Zanchettin, Davide; Woldeyes Arisido, Maeregu; Gaetan, Carlo; Rubino, Angelo

    2016-04-01

    Decadal climate forecasts with full-field initialized coupled climate models are affected by a growing error signal that develops due to the adjustment of the simulations from the assimilated state consistent with observations to the state consistent with the biased model's climatology. Sea-surface temperature (SST) drifts and biases are a major concern due to the central role of SST properties for the dynamical coupling between the atmosphere and the ocean, and for the associated variability. Therefore, strong SST drifts complicate the initialization and assessment of decadal climate prediction experiments, and can be detrimental for their overall quality. We propose a dynamic linear model based on a state-space approach and developed within a Bayesian hierarchical framework for probabilistic assessment of spatial and temporal characteristics of SST drifts in ensemble climate simulations. The state-space approach uses unobservable state variables to directly model the processes generating the observed variability. The statistical model is based on a sequential definition of the process having a conditional dependency only on the previous time step, which therefore corresponds to the Kalman filter formulas. In our formulation, the statistical model distinguishes between seasonal and longer-term drift components, and between large-scale and local drifts. We apply the Bayesian method to make inferences on the variance components of the Gaussian errors in both the observation and system equations of the state-space model. To this purpose, we draw samples from their posterior distributions using a Monte Carlo Markov Chain simulation technique with a Gibbs sampler. In this contribution we illustrate a first application of the model using the MiKlip prototype system for decadal climate predictions. We focus on the tropical Atlantic Ocean - a region where climate models are typically affected by a severe warm SST bias - to demonstrate how our approach allows for a more

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

    NARCIS (Netherlands)

    Berends, H.; Smits, A.A.J.; Reymen, I.; Podoynitsyna, K.

    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”

  4. Establishment of C6 brain glioma models through stereotactic technique for laser interstitial thermotherapy research

    Directory of Open Access Journals (Sweden)

    Jian Shi

    2015-01-01

    Conclusion: The rat C6 brain glioma model established in the study was a perfect model to study LITT of glioma. Infrared thermograph technique measured temperature conveniently and effectively. The technique is noninvasive, and the obtained data could be further processed using software used in LITT research. To measure deep-tissue temperature, combining thermocouple with infrared thermograph technique would present better results.

  5. Modelling Spatial Patterns of Vegetation in Desert Sand Dunes

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    A stochastic numerical approach was developed to model the actual standing biomass in the sand dunes of the northwestern Negev (Israel) and probable boundary conditions that may be responsible for the vegetation patterns investigated in detail. Our results for several variables characteristic for the prevailing climate, geomorphology, hydrology and biologicy at four measurement stations along a transect from northwest to southeast allowed for the development of a stochastic model for biomass distribution over the entire sand dune field (mesoscale) and at Nizzana experimental station (microscale). With this equation it was possible to compute andinterpolate a biomass index value for each grid point on the mesoscale and micro scale. The spatial distribution of biomass is negatively linked to distance from the sea, to rainfall and relief energy.

  6. 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...

  7. Cartographic Modeling: Computer-assisted Analysis of Spatially Defined Neighborhoods

    Science.gov (United States)

    Berry, J. K.; Tomlin, C. D.

    1982-01-01

    Cartographic models addressing a wide variety of applications are composed of fundamental map processing operations. These primitive operations are neither data base nor application-specific. By organizing the set of operations into a mathematical-like structure, the basis for a generalized cartographic modeling framework can be developed. Among the major classes of primitive operations are those associated with reclassifying map categories, overlaying maps, determining distance and connectivity, and characterizing cartographic neighborhoods. The conceptual framework of cartographic modeling is established and techniques for characterizing neighborhoods are used as a means of demonstrating some of the more sophisticated procedures of computer-assisted map analysis. A cartographic model for assessing effective roundwood supply is briefly described as an example of a computer analysis. Most of the techniques described have been implemented as part of the map analysis package developed at the Yale School of Forestry and Environmental Studies.

  8. Residential environment index system and evaluation model established by subjective and objective methods

    Institute of Scientific and Technical Information of China (English)

    GE Jian(葛坚); HOKAO Kazunori

    2004-01-01

    In this research, the residential environment index system and evaluation model were established by means of subjective and objective methods. The methodology for establishing the evaluation system for residential environment was first analyzed; then the subjective evaluation data-base was established by questionnaire survey; and at the same time, the objective evaluation data-base was constructed by Geographic Information System (GIS); and then the related equation system between subjective and objective system was developed by multiple regression analysis. This research could benefit evaluation of the residential environment quality for various purposes, and also provide important rudimentary data-base for the development and improvement of residential environment for officials. Furthermore, the index system and evaluation model established in this research could construct a strong relation between subjective evaluation and objective data; and thus could provide a comprehensive, efficient and effective methodology for the evaluation of residential environment.

  9. A Top-Down Spatially Resolved Electrical Load Model

    Directory of Open Access Journals (Sweden)

    Martin Robinius

    2017-03-01

    Full Text Available The increasing deployment of variable renewable energy sources (VRES is changing the source regime in the electrical energy sector. However, VRES feed-in from wind turbines and photovoltaic systems is dependent on the weather and only partially predictable. As a result, existing energy sector models must be re-evaluated and adjusted as necessary. In long-term forecast models, the expansion of VRES must be taken into account so that future local overloads can be identified and measures taken. This paper focuses on one input factor for electrical energy models: the electrical load. We compare two different types to describe this, namely vertical grid load and total load. For the total load, an approach for a spatially-resolved electrical load model is developed and applied at the municipal level in Germany. This model provides detailed information about the load at a quarterly-hour resolution across 11,268 German municipalities. In municipalities with concentrations of energy-intensive industry, high loads are expected, which our simulation reproduces with a good degree of accuracy. Our results also show that municipalities with energy-intensive industry have a higher simulated electric load than neighboring municipalities that do not host energy-intensive industries. The underlying data was extracted from publically accessible sources and therefore the methodology introduced is also applicable to other countries.

  10. Spatial Modelling of Solar energy Potential in Kenya

    Directory of Open Access Journals (Sweden)

    Francis Omondi Oloo

    2015-06-01

    Full Text Available Solar energy is one of the readily available renewable energy resources in the developing countries within the tropical region. Kenya is one of the countries which receive an average of approximately 6.5 sunshine hours in a single day throughout the year. However, there is slow adoption of solar energy resources in the country due to limited information on the spatial variability solar energy potential. This study aims at assessing the potential of photovoltaic solar energy in Kenya. The factors that influence incident solar radiation which were considered in this task included atmospheric transmissivity and topography. The influence of atmospheric transmissivity was factored in by modelling monthly transmissivity factors from a combination of cloud cover, diffuse ratios and the effect of altitude. The contribution of topography was included by applying hemispherical viewshed analysis to determine the amount of incident global radiation on the surface based on the orientation of the terrain. GIS concepts were used to integrate the spatial datasets from different themes. The results showed that, about 70% of the land area in Kenya has the potential of receiving approximately 5kWh/m2/day throughout the year. In outline, this work successfully assessed the spatio-temporal variability in the characteristics of solar energy potential in Kenya and can be used as a basis for policy support in the country.

  11. Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models

    CERN Document Server

    Hughes, John

    2010-01-01

    Non-gaussian spatial data are very common in many disciplines. For instance, count data are common in disease mapping, and binary data are common in ecology. When fitting spatial regressions for such data, one needs to account for dependence to ensure reliable inference for the regression coefficients. The spatial generalized linear mixed model (SGLMM) offers a very popular and flexible approach to modeling such data, but the SGLMM suffers from three major shortcomings: (1) uninterpretability of parameters due to spatial confounding, (2) variance inflation due to spatial confounding, and (3) high-dimensional spatial random effects that make fully Bayesian inference for such models computationally challenging. We propose a new parameterization of the SGLMM that alleviates spatial confounding and speeds computation by greatly reducing the dimension of the spatial random effects. We illustrate the application of our approach to simulated binary, count, and Gaussian spatial datasets, and to a large infant mortali...

  12. Modelling cell polarization driven by synthetic spatially graded Rac activation.

    Directory of Open Access Journals (Sweden)

    William R Holmes

    Full Text Available The small GTPase Rac is known to be an important regulator of cell polarization, cytoskeletal reorganization, and motility of mammalian cells. In recent microfluidic experiments, HeLa cells endowed with appropriate constructs were subjected to gradients of the small molecule rapamycin leading to synthetic membrane recruitment of a Rac activator and direct graded activation of membrane-associated Rac. Rac activation could thus be triggered independent of upstream signaling mechanisms otherwise responsible for transducing activating gradient signals. The response of the cells to such stimulation depended on exceeding a threshold of activated Rac. Here we develop a minimal reaction-diffusion model for the GTPase network alone and for GTPase-phosphoinositide crosstalk that is consistent with experimental observations for the polarization of the cells. The modeling suggests that mutual inhibition is a more likely mode of cell polarization than positive feedback of Rac onto its own activation. We use a new analytical tool, Local Perturbation Analysis, to approximate the partial differential equations by ordinary differential equations for local and global variables. This method helps to analyze the parameter space and behaviour of the proposed models. The models and experiments suggest that (1 spatially uniform stimulation serves to sensitize a cell to applied gradients. (2 Feedback between phosphoinositides and Rho GTPases sensitizes a cell. (3 Cell lengthening/flattening accompanying polarization can increase the sensitivity of a cell and stabilize an otherwise unstable polarization.

  13. 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

  14. Modeling inter-subject variability in fMRI activation location: A Bayesian hierarchical spatial model

    Science.gov (United States)

    Xu, Lei; Johnson, Timothy D.; Nichols, Thomas E.; Nee, Derek E.

    2010-01-01

    Summary The aim of this work is to develop a spatial model for multi-subject fMRI data. There has been extensive work on univariate modeling of each voxel for single and multi-subject data, some work on spatial modeling of single-subject data, and some recent work on spatial modeling of multi-subject data. However, there has been no work on spatial models that explicitly account for inter-subject variability in activation locations. In this work, we use the idea of activation centers and model the inter-subject variability in activation locations directly. Our model is specified in a Bayesian hierarchical frame work which allows us to draw inferences at all levels: the population level, the individual level and the voxel level. We use Gaussian mixtures for the probability that an individual has a particular activation. This helps answer an important question which is not addressed by any of the previous methods: What proportion of subjects had a significant activity in a given region. Our approach incorporates the unknown number of mixture components into the model as a parameter whose posterior distribution is estimated by reversible jump Markov Chain Monte Carlo. We demonstrate our method with a fMRI study of resolving proactive interference and show dramatically better precision of localization with our method relative to the standard mass-univariate method. Although we are motivated by fMRI data, this model could easily be modified to handle other types of imaging data. PMID:19210732

  15. Improvements of Surgical Technique in Establishment of Rat Orthotopic Pulmonary Transplantation Model Using Cuffs

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In order to establish more simple and effective rat orthotopic lung transplantation models, 20 rats were divided into donor and recipient groups. Rat lung transplantation models were established by using improved cuff technique. All the 10 operations were accomplished successfully.The mean operative time of recipients was 45±4 min. The survival time was over 30 days after lung transplantation. The checks of X-ray were almost ncrmal. There was no significant difference in the blood gas analysis before and after clipping the right hilum (P>. 05). This method is more simple,applicable and requires less time.

  16. A PRELIMINARY STUDY ON THE ESTABLISHMENT OF OCEAN TIDE MODELS OVER THE SOUTH CHINA SEA FROM T/P ALTIMETRY

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    On the basis of the characteristic of the perfect spatial distribution of th e T/P altimeter data,a spatial harmonic tidal analysis is performed,which tran sfers tidal harmonic constants H and g of each constituent into a pair o f parame ters:the cosine part U and sine part V.And each part is expanded into a po lynomi al.The polynomial coefficients are estimated with altimeter data upon the least squares criteria.Thus the models of principal tidal waves in the South China S ea are established.72 cycles of T/P data from cycle 11 through 82 ar e included in the calculation.The models are evaluated with different approache s and data set.The conclusions are that the tide modes can provide partial tide amplitudes with 3 cm accuracy,and that phase lags deviation of those tides w ith amplitude large than 10 cm are within ±10°.

  17. Establishing formal state space models via quantization for quantum control systems

    Institute of Scientific and Technical Information of China (English)

    Dong Daoyi; Chen Zonghai

    2005-01-01

    Formal state space models of quantum control systems are deduced and a scheme to establish formal state space models via quantization could been obtained for quantum control systems is proposed. State evolution of quantum control systems must accord with Schrodinger equations, so it is foremost to obtain Hamiltonian operators of systems. There are corresponding relations between operators of quantum systems and corresponding physical quantities of classical systems,such as momentum, energy and Hamiltonian, so Schrodinger equation models of corresponding quantum control systems via quantization could been obtained from classical control systems, and then establish formal state space models through the suitable transformation from Schrodinger equations for these quantum control systems. This method provides a new kind of path for modeling in quantum control.

  18. Representing spatial and temporal complexity in ecohydrological models: a meta-analysis focusing on groundwater - surface water interactions

    Science.gov (United States)

    McDonald, Karlie; Mika, Sarah; Kolbe, Tamara; Abbott, Ben; Ciocca, Francesco; Marruedo, Amaia; Hannah, David; Schmidt, Christian; Fleckenstein, Jan; Karuse, Stefan

    2016-04-01

    simplifications scientists apply to investigate the GW-SW ecohydrological interface. We investigated the type of modelling approaches applied across different scales (site, reach, catchment, nested catchments) and assessed the simplifications in environmental conditions and complexity that are commonly made in model configuration. Understanding the theoretical concepts that underpin these current modelling approaches is critical for scientists to develop measures to derive predictions from realistic environmental conditions at management relevant scales and establish best-practice modelling approaches for improving the scientific understanding and management of the GW-SW interface. Additionally, the assessment of current modelling approaches informs our proposed framework for the progress of GW-SW models in the future. The framework presented aims to increase future scientific, technological and management integration and the identification of research priorities to allow spatial and temporal complexity to be better incorporated into GW-SW models.

  19. Spatial Segregation, Redistribution and Welfare: A Theoretical Model

    Directory of Open Access Journals (Sweden)

    Tommaso Gabrieli

    2016-03-01

    Full Text Available This paper develops a theoretical model focusing on the effect that different neighborhood compositions can have on the formation of individual beliefs about economic opportunities. Specifically we highlight two effects that spatial segregation may have: (1 it can efficiently separate the individual effort choices of highly and low productive individuals, (2 it may imply that the median voter imposes a level of redistribution that is inefficient from the aggregate point of view. The trade-off implies that segregated and non-segregated cities may present very similar levels of aggregate welfare. We employ this framework to discuss how the structure of cities can play a role in the determination of US-type and Europe-type politico-economic equilibria and the implications for planning policies.

  20. 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.

  1. Parameter estimation in a spatial unit root autoregressive model

    CERN Document Server

    Baran, Sándor

    2011-01-01

    Spatial autoregressive model $X_{k,\\ell}=\\alpha X_{k-1,\\ell}+\\beta X_{k,\\ell-1}+\\gamma X_{k-1,\\ell-1}+\\epsilon_{k,\\ell}$ is investigated in the unit root case, that is when the parameters are on the boundary of the domain of stability that forms a tetrahedron with vertices $(1,1,-1), \\ (1,-1,1),\\ (-1,1,1)$ and $(-1,-1,-1)$. It is shown that the limiting distribution of the least squares estimator of the parameters is normal and the rate of convergence is $n$ when the parameters are in the faces or on the edges of the tetrahedron, while on the vertices the rate is $n^{3/2}$.

  2. Simplified Spatially-distributed Model for Inundation Simulations

    Science.gov (United States)

    Hsu, M. H.; Huang, C. J.; Su, Y. H.; Chen, A. S.

    2009-04-01

    Although traditional inundation models have been applied with good accuracy in Taiwan, they usually require a long computing time for simulations. However, the meteorological and geographical conditions in Taiwan frequently cause inundation within a short time period when storm occurs. The lead-time for emergency response in too short to indicate the areas with high flood risks for evacuation by using the traditional inundation models. The study established an inundation model for Taiwan and integrated the QPESUMS system which constructed and developed by the Central Weather Bureau. The radar precipitations by the QPESUMS system, as well as the rain-gauge records, are considered in the inundation model for real-time simulations. The precipitation data of typhoon NARI were simulated and evaluated different scale of grid size that the accuracy and efficiency of model would be suggested for practical applications. The Keelung River basin is adopted as the study areas of the inundation model. By use of QPESUMS radar precipitation for the typhoon HAITANG and KROSA, the inundation simulations can be calculated in a short time. The model will be executed in the future, to simulate the flood scenarios induced by the occurring and the forecasted rainfalls. The inundation will be predicted in 1-3 hours ahead to help the emergency managers taking proper strategies for disaster mitigations. Traditional inundation models have been widely applied with good accuracy to many studies in Taiwan. The main drawback of these models is that extraordinary requirement of computing time, which causes the obstacle for real-time applications. The meteorological and geographical conditions in Taiwan frequently result in flashfloods within short time periods when storms occur. The lead time for emergency response is too short to indicate the areas with high flood risks by using the traditional inundation models.

  3. 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.

  4. 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.

  5. 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

  6. Modeling the spatial dynamics of regional land use: the clue-s model

    NARCIS (Netherlands)

    Verburg, P.H.; Soepboer, W.; Veldkamp, A.; Limpiada, R.; Espaldon, V.; Mastura, S.S.A.

    2002-01-01

    Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S

  7. 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

  8. 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.

  9. Evaluating stream health based environmental justice model performance at different spatial scales

    Science.gov (United States)

    Daneshvar, Fariborz; Nejadhashemi, A. Pouyan; Zhang, Zhen; Herman, Matthew R.; Shortridge, Ashton; Marquart-Pyatt, Sandra

    2016-07-01

    This study evaluated the effects of spatial resolution on environmental justice analysis concerning stream health. The Saginaw River Basin in Michigan was selected since it is an area of concern in the Great Lakes basin. Three Bayesian Conditional Autoregressive (CAR) models (ordinary regression, weighted regression and spatial) were developed for each stream health measure based on 17 socioeconomic and physiographical variables at three census levels. For all stream health measures, spatial models had better performance compared to the two non-spatial ones at the census tract and block group levels. Meanwhile no spatial dependency was found at the county level. Multilevel Bayesian CAR models were also developed to understand the spatial dependency at the three levels. Results showed that considering level interactions improved models' prediction. Residual plots also showed that models developed at the block group and census tract (in contrary to county level models) are able to capture spatial variations.

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

    Science.gov (United States)

    Cianci, Daniela; Hartemink, Nienke; Ibáñez-Justicia, Adolfo

    2015-02-27

    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 distribution modelling techniques, and to compare the results produced with the different techniques. Three different modelling techniques, i.e., non-linear discriminant analysis, random forest and generalised linear model, were used to investigate the environmental suitability in the Netherlands for three indigenous mosquito species (Culiseta annulata, Anopheles claviger and Ochlerotatus punctor). Results obtained with the three statistical models were compared with regard to: (i) environmental suitability maps, (ii) environmental variables associated with occurrence, (iii) model evaluation. The models indicated that precipitation, temperature and population density were associated with the occurrence of Cs. annulata and An. claviger, whereas land surface temperature and vegetation indices were associated with the presence of Oc. punctor. The maps produced with the three different modelling techniques showed consistent spatial patterns for each species, but differences in the ranges of the predictions. Non-linear discriminant analysis had lower predictions than other methods. The model with the best classification skills for all the species was the random forest model, with specificity values ranging from 0.89 to 0.91, and sensitivity values ranging from 0.64 to 0.95. We mapped the environmental suitability for three mosquito species with three different modelling techniques. For each species, the maps showed consistent spatial patterns, but the level of predicted environmental suitability differed; NLDA gave lower predicted probabilities of presence than the other two methods. The variables selected as important in the models were in agreement with the existing knowledge about

  11. S4: A Spatial-Spectral model for Speckle Suppression

    CERN Document Server

    Fergus, Rob; Oppenheimer, Rebecca; Brenner, Douglas; Pueyo, Laurent

    2014-01-01

    High dynamic-range imagers aim to block out or null light from a very bright primary star to make it possible to detect and measure far fainter companions; in real systems a small fraction of the primary light is scattered, diffracted, and unocculted. We introduce S4, a flexible data-driven model for the unocculted (and highly speckled) light in the P1640 spectroscopic coronograph. The model uses Principal Components Analysis (PCA) to capture the spatial structure and wavelength dependence of the speckles but not the signal produced by any companion. Consequently, the residual typically includes the companion signal. The companion can thus be found by filtering this error signal with a fixed companion model. The approach is sensitive to companions that are of order a percent of the brightness of the speckles, or up to $10^{-7}$ times the brightness of the primary star. This outperforms existing methods by a factor of 2-3 and is close to the shot-noise physical limit.

  12. S4: A spatial-spectral model for speckle suppression

    Energy Technology Data Exchange (ETDEWEB)

    Fergus, Rob [Department of Computer Science, New York University, New York, NY 10003 (United States); Hogg, David W. [Center for Cosmology and Particle Physics, Department of Physics, New York University, New York, NY 10003 (United States); Oppenheimer, Rebecca; Brenner, Douglas [Department of Astrophysics, American Museum of Natural History, New York, NY 10024-5192 (United States); Pueyo, Laurent, E-mail: fergus@cs.nyu.edu [Space Telescope Science Institute, Baltimore, MD 21218 (United States)

    2014-10-20

    High dynamic range imagers aim to block or eliminate light from a very bright primary star in order to make it possible to detect and measure far fainter companions; in real systems, a small fraction of the primary light is scattered, diffracted, and unocculted. We introduce S4, a flexible data-driven model for the unocculted (and highly speckled) light in the P1640 spectroscopic coronagraph. The model uses principal components analysis (PCA) to capture the spatial structure and wavelength dependence of the speckles, but not the signal produced by any companion. Consequently, the residual typically includes the companion signal. The companion can thus be found by filtering this error signal with a fixed companion model. The approach is sensitive to companions that are of the order of a percent of the brightness of the speckles, or up to 10{sup –7} times the brightness of the primary star. This outperforms existing methods by a factor of two to three and is close to the shot-noise physical limit.

  13. [Establishment of 3-dimensional finite element model of human knee joint and its biomechanics].

    Science.gov (United States)

    Yuan, Ping; Wang, Wanchun

    2010-01-01

    To establish a 3-dimensional (3-D) finite element knee model in healthy Chinese males, to verify the validity of the model, and to analyze the biomechanics of this model under axial load, flexion moment, varus/valgus torque, and internal/external axial torque. A set of consecutive transectional computerized tomography images of normal male knee joints in upright weight-bearing position was selected. With image processing and inversion technology, the 3-D finite element model of the normal knee joint was established through the software ABAQOUS/STANDARD Version-6.5.Biomechanical analysis of this model was processed under axial load, flexion moment, varus/valgus torque, and internal/external axial torque. A 3-D finite element model of healthy Chinese males was successfully established. The ranges of motion of varus and valgus were both small and the difference between them has no statistical significance (P>0.05). The motion of internal and external rotation of the knee took place only in flexion situation.The range of motion of external rotation was larger than that of internal rotation in the same knee (Pknee resembles the actual knee segments. It can imitate the knee response to different loads. This model could be used for further study on knee biomechanics.

  14. GIS Spatial-Temporal Modeling of Water Systems in Greater Toronto Area, Canada

    Institute of Scientific and Technical Information of China (English)

    Cheng Qiuming; Zhang George; Lu Cindy; Ko Connie

    2004-01-01

    Modeling landscape with high-resolution digital elevation model (DEM) in a geographic information system can provide essential morphological and structural information for modeling surface processes such as geomorphologic process and water systems. This paper introduces several DEM-based spatial analysis processes applied to characterize spatial distribution and their interactions of ground and surface water systems in the Greater Toronto Area (GTA), Canada. The stream networks and drainage basin systems were derived from the DEM with 30 m resolution and the regularities of the surface stream and drainage patterns were modeled from a statistical/multifractal point of view. Together with the elevation and slope of topography, other attributes defined from modeling the stream system, and drainage networks were used to associate geological, hydrological and topographical features to water flow in river systems and the spatial locations of artesian aquifers in the study area. Stream flow data derived from daily flow measurements recorded at river gauging stations for multi-year period were decomposed into "drainage-area dependent" and "drainage-area independent" flow components by two-step "frequency" and "spatial" analysis processes. The latter component was further demonstrated to relate most likely to the ground water discharge. An independent analysis was conducted to model the distribution of aquifers with information derived from the records of water wells. The focus was given on quantification of the likelihood of ground water discharge to river and ponds through flowing wells, springs and seepages. It has been shown that the Oak Ridges Moraine (ORM) is a unique glacial deposit that serves as a recharge layer and that the aquifers in the ORM underlain by Hilton Tills and later deposits exposed near the steep slope zone of the ridges of ORM provide significant discharge to the surface water systems (river flow and ponds) through flowing wells, springs and

  15. Establishment of a new dynamic RRC model in smoke toxicity evaluation and engineering application

    Institute of Scientific and Technical Information of China (English)

    YANG Lizhong; FANG Tingyong; ZHOU Xiaodong; FENG Wenxing; HUANG Rui; ZHAI Guanglong; FAN Weicheng

    2005-01-01

    It is by now a well established fact that the overwhelming hazard from fire is smoke as far as the death of people in the fire is concerned. There are many methodologies for addressing the smoke toxicity component of fire hazard such as CO stochastic model,FED (fractional effective dose) model, FEC (fractional effective concentration) model, N-gas model and so on. None of these models can reflect spatio-temporal variation of the smoke concentration. A new dynamic smoke toxicity evaluation model, RRC (respiration, route and concentration) model, is proposed in this paper concerning the three decisive factors in real fire such as the respiration, movement route of people and the distribution of smoke concentration in the building. Furthermore, an example of the model is presented.

  16. A critical study of quality parameters in health care establishment: developing an integrated quality model

    NARCIS (Netherlands)

    Azam, M.; Rahman, Z.; Talib, F.; Singh, K.J.

    2012-01-01

    PURPOSE: The purpose of this article is to identify and critically analyze healthcare establishment (HCE) quality parameters described in the literature. It aims to propose an integrated quality model that includes technical quality and associated supportive quality parameters to achieve optimum

  17. Establishment of an animal model of non-transthoracic cardiopulmonary bypass in rats

    Institute of Scientific and Technical Information of China (English)

    SHANG Hong-wei; XIAO Ying-bin; LIU Mei; CHEN Lin

    2005-01-01

    Objective: To establish an animal model of non-transthoracic cardiopulmonary bypass (CPB) in rats. Methods: Ten adult male Sprague-Dawlay rats, weighing 350-500 g, were used in this study. CPB was established in these animals through cannulating the left carotid and right jugular vein for arterial perfusion and venous return. The components of perfusion circuit, especially the miniature oxygenator and cannula, were specially designed and improved. The mean arterial pressure was measured with a blood pressure meter through cannulating the left femoral artery. The hemodynamic and blood gas parameters were also monitored. Results: The rat model of non-transthoracic CPB was established successfully. The hemodynamical parameters were changed within an acceptable region during CPB. The miniature oxygenator was sufficient to meet the standard of satisfactory CPB.Conclusions: The rat model of non-transthoracic CPB established through the carotid and jugular cannulation is feasible, easily operated, safe, reliable, and economic. It is an ideal model for the pathophysiological research of CPB.

  18. Surgical technique: establishing a pre-clinical large animal model to test aortic valve leaflet substitute

    Science.gov (United States)

    Knirsch, Walter; Cesarovic, Niko; Krüger, Bernard; Schmiady, Martin; Frauenfelder, Thomas; Frese, Laura; Dave, Hitendu; Hoerstrup, Simon Philipp; Hübler, Michael

    2016-01-01

    To overcome current limitations of valve substitutes and tissue substitutes the technology of tissue engineering (TE) continues to offer new perspectives in congenital cardiac surgery. We report our experiences and results implanting a decellularized TE patch in nine sheep in orthotropic position as aortic valve leaflet substitute. Establishing the animal model, feasibility, cardiopulmonary bypass issues and operative technique are highlighted. PMID:28149571

  19. Establishment of a uremic apolipoprotein E knockout mouse model to explore the mechanism of uremic atherosclerosis

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Objective To establish a uremic apoE-/-mouse model to observe serum biochemical parameters and features of aortic root atherosclerosis (AS) in the model. Methods A uremic model was induced surgically in apoE-/- mice:electrocautery of the right kidney at 8 weeks of age and nephrectomy (NX) of the left one 2 weeks later. Control mice were sham-operated. Two weeks after NX,renal functions were detected in the uremic and control mice to evaluate the efficiency of the model. After 10 weeks of NX,blood samples we...

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

    OpenAIRE

    Berends, JJ Hans; Smits, AAJ Armand; Reymen, IMMJ Isabelle; Podoynitsyna, KS 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. B...

  1. Establishment of Comprehensive Evaluation Model of the New Generation Migrant Workers' Employability

    OpenAIRE

    GAO, Jianli; ZHANG, Tongquan

    2013-01-01

    Through literature research and expert interviews, we extract 10 variables influencing the new generation migrant workers' employability, and establish the comprehensive evaluation model of the new generation migrant workers' employability. Using factor analysis, we derive that the model includes three factors: skill literacy, relationship literacy and basic literacy. The weights of each factor are 0.580, 0.244 and 0.174 8, respectively. Skill literacy is affected by skill level, learning abi...

  2. A simple iterative model accurately captures complex trapline formation by bumblebees across spatial scales and flower arrangements.

    Science.gov (United States)

    Reynolds, Andrew M; Lihoreau, Mathieu; Chittka, Lars

    2013-01-01

    Pollinating bees develop foraging circuits (traplines) to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1) the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2) that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3) the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model); 4) the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5) the instability of visitation schedules in some spatial configurations of flowers; 6) the observation that in some flower arrays, bees' visitation schedules are highly individually different; 7) the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments.

  3. A simple iterative model accurately captures complex trapline formation by bumblebees across spatial scales and flower arrangements.

    Directory of Open Access Journals (Sweden)

    Andrew M Reynolds

    Full Text Available Pollinating bees develop foraging circuits (traplines to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1 the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2 that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3 the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model; 4 the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5 the instability of visitation schedules in some spatial configurations of flowers; 6 the observation that in some flower arrays, bees' visitation schedules are highly individually different; 7 the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments.

  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.

  5. ESTABLISHMENT OF 3D FEM MODEL OF MULTI-PASS SPINNING

    Institute of Scientific and Technical Information of China (English)

    ZHAN Mei; ZHOU Qiang; YANG He; ZHANG Jinhui

    2007-01-01

    In order to improve the computational accuracy and efficiency, it is necessary to establish a reasonable 3D FEM model for multi-pass spinning including not only spinning process but also springback and annealing processes. A numerical model for multi-pass spinning is established using the combination of explicit and implicit FEM, with the advantages of them in accuracy and efficiency. The procedures for model establishment are introduced in detail, and the model is validated. The application of the 3D FEM model to a two-pass spinning shows the following: The field variables such as the stress, strahl and wall thickness during the whole spinning process can be obtained, not only during spinning process but also during springback and annealing processes, and the trends of their distributions and variations are in good agreement with a practical multi-spinning process. Thus the 3D FEM model for multi-pass spinning may be a helpful tool for determination and optimization of process Parameters of multi-pass spinning process.

  6. Generalization-based discovery of spatial association rules with linguistic cloud models

    Institute of Scientific and Technical Information of China (English)

    杨斌; 田永青; 朱仲英

    2004-01-01

    Extraction of interesting and general spatial association rules from large spatial databases is an important task in the development of spatial database systems. In this paper, we investigate the generalization-based knowledge discovery mechanism that integrates attribute-oriented induction on nonspatial data and spatial merging and generalization on spatial data. Furthermore, we present linguistic cloud models for knowledge representation and uncertainty handling to enhance current generalization-based method. With these models, spatial and nonspatial attribute values are well generalized at higher-concept levels, allowing discovery of strong spatial association rules. Combining the cloud model based generalization method with Apriori algorithm for mining association rules from a spatial database shows the benefits in effectiveness and flexibility.

  7. A spatial stochastic programming model for timber and core area management under risk of fires

    Science.gov (United States)

    Yu Wei; Michael Bevers; Dung Nguyen; Erin Belval

    2014-01-01

    Previous stochastic models in harvest scheduling seldom address explicit spatial management concerns under the influence of natural disturbances. We employ multistage stochastic programming models to explore the challenges and advantages of building spatial optimization models that account for the influences of random stand-replacing fires. Our exploratory test models...

  8. Predicting Cumulative Watershed Effects using Spatially Explicit Models

    Science.gov (United States)

    MacDonald, L. H.; Litschert, S.

    2004-12-01

    Cumulative watershed effects /(CWEs/) result from the combined effects of land disturbances distributed over both space and time. They are of concern because changes in flow and sediment yields can adversely affect aquatic habitat, channel morphology, water yields, and water quality. The assessment procedures currently used by agencies such as the U.S. Forest Service generally rely on a lumped approach to quantify disturbance, despite the widespread recognition that site conditions and location do matter! The overall goal of our work is to develop spatially-explicit models to quantify changes in flow and sediment yields. Key objectives include: use of readily available GIS data; ease of use for resource managers with minimal GIS experience; modularity so that models can be added or updated; and allowing users to select the models and values for key parameters. The DeltaQ model calculates changes in peak, median, and low flows due to forest management activities and fires. Inputs include GIS data with disturbance polygons, an initial change in flow rate, and the time to recovery. Data from paired watershed studies are provided to help guide the user. The initial version of FORest Erosion Simulation Tools /(FOREST/) calculates sediment production from forest harvest, fires, and unpaved roads. Additional modules are being developed to deliver this sediment to the stream channel and route it to downstream locations. In accordance with our objectives, the user can predict sediment production rates using different empirical equations, assign an initial sediment production rate and a specified linear recovery period, or develop a look-up table based on local knowledge, published values, or data from other models such as WEPP. The required GIS layers vary according to the model/(s/) selected, but generally include past disturbances /(e.g., fires and timber harvest/), roads, and elevation. Outputs include GIS layers and text files that can be subjected to additional

  9. Spatial dependence of entanglement renormalization in XY model

    Science.gov (United States)

    Usman, M.; Ilyas, Asif; Khan, Khalid

    2017-09-01

    In this article, a comparative study of the renormalization of entanglement in one-, two- and three-dimensional space and its relation with quantum phase transition (QPT) near the critical point is presented by implementing the quantum renormalization group (QRG) method using numerical techniques. Adopting the Kadanoff's block approach, numerical results for the concurrence are obtained for the spin {-}1/2 XY model in all the spatial dimensions. The results show similar qualitative behavior as we move from the lower to the higher dimensions in space, but the number of iterations reduces for achieving the QPT in the thermodynamic limit. We find that in the two-dimensional and three-dimensional spin {-}1/2 XY model, maximum value of the concurrence reduce by the factor of 1 / n (n=2,3) with reference to the maximum value of one-dimensional case. Moreover, we study the scaling behavior and the entanglement exponent. We compare the results for one-, two- and three-dimensional cases and illustrate how the system evolves near the critical point.

  10. 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.

  11. Rural Poverty Dynamics and Refugee Communities in South Africa: A Spatial-Temporal Model.

    Science.gov (United States)

    Sartorius, Kurt; Sartorius, Benn; Tollman, Stephen; Schatz, Enid; Kirsten, Johann; Collinson, Mark

    2013-01-01

    The assimilation of refugees into their host community economic structures is often problematic. The paper investigates the ability of refugees in rural South Africa to accumulate assets over time relative to their host community. Bayesian spatial-temporal modelling was employed to analyse a longitudinal database that indicated that the asset accumulation rate of former Mozambican refugee households was similar to their host community; however, they were unable to close the wealth gap. A series of geo-statistical wealth maps illustrate that there is a spatial element to the higher levels of absolute poverty in the former refugee villages. The primary reason for this is their physical location in drier conditions that are established further away from facilities and infrastructure. Neighbouring South African villages in close proximity, however, display lower levels of absolute poverty, suggesting that the spatial location of the refugees only partially explains their disadvantaged situation. In this regard, the results indicate that the wealth of former refugee households continues to be more compromised by higher mortality levels, poorer education, and less access to high-return employment opportunities. The long-term impact of low initial asset status appears to be perpetuated in this instance by difficulties in obtaining legal status in order to access state pensions, facilities, and opportunities. The usefulness of the results is that they can be used to sharpen the targeting of differentiated policy in a given geographical area for refugee communities in rural Africa. Copyright © 2011 John Wiley & Sons, Ltd.

  12. 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

  13. [Study on the methods for establishing virtual three-dimensional models of cerebral arteries with the three-dimensional moulding software].

    Science.gov (United States)

    Wei, Xin; Xie, Xiaodong; Wang, Chaohua

    2007-12-01

    This study was conducted to establish the methods of virtual three-dimensional cerebral arteries models by use of three-dimensional moulding software. The virtual models of the cerebral arteries were established using the three-dimensional moulding software of 3D Studio MAX R3 with 46 cases of normal cerebral DSA image as the original. The results showed there was similarity in appearance between the virtual cerebral arteries and DSA image. This is of benefit to understanding the vascular three-dimensional spatial relation in visual sense. Several models of different variant anatomy could be easily established on the copy files of the virtual cerebral arteries model. The virtual model could help learners to create and increase the three-dimensional space concept of arteries and aneurysms in clinical teaching. The results indicated that the virtual three-dimensional cerebral arteries models could display the three-dimensional spatial relation of the cerebral arterial system distinctly, and could serve as a morphologic foundation in the researches on vascular disease.

  14. Richly parameterized linear models additive, time series, and spatial models using random effects

    CERN Document Server

    Hodges, James S

    2013-01-01

    A First Step toward a Unified Theory of Richly Parameterized Linear ModelsUsing mixed linear models to analyze data often leads to results that are mysterious, inconvenient, or wrong. Further compounding the problem, statisticians lack a cohesive resource to acquire a systematic, theory-based understanding of models with random effects.Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects takes a first step in developing a full theory of richly parameterized models, which would allow statisticians to better understand their analysis results. The aut

  15. Establishment of a Model of Combined Pancreas-Kidney Transplantation in Pig

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Objective To establish a model of combined pancreas-kidney transplantation in pig. Methods A renoportal end-to-end anastomoses between the left renal vein and the distal end of portal vein were performed. Only two vascular end-to-side anastomoses between the donor portal vein and recipient inferior vena cava, and between the donor aortic segment including the celiac, superior mesenteric, and left renal arteries and recipient abdominal aorta were constructed. Pancreas exocrine drainage was established with duodenocystostomy. The ureterostomosis of the graft was performed. Results Satisfactory results were obtained in 11 pigs. Conclusion The method for combined pancreas-kidney transplantation was reliable.

  16. Experimental study on the establishment and maintenance of brain death model with pigs

    Institute of Scientific and Technical Information of China (English)

    ZHANG Shuijun; SHI Jihua; ZHAI Wenlong; SONG Yan; CHEN Shi

    2007-01-01

    It remains controversial that after the transplantation of using grafts from brain-dead donors,organs injury and rejection can influence the effects of transplantation.This study sought to explore methods of establishing a stable brain death(BD)model using Bama mini pigs and to maintain the brain-dead state for a comparatively long period to provide a model for investigating changes in brain death.Sixteen anesthetized Bama mini pigs were randomized into a control group(n=5)and a BD group(n=11).Intracranial pressure (ICP)was increased in a modified,slow,and intermittent way to establish BD.Respiration and circulation were sustained during the brain-dead state.Hemodynamic changes were monitored during the experiment.In the BD group,10 pigs met the requirements for brain death and 1 died of cardiopulmonary complications following an increase in ICP.Brain death was maintained for more than 48 hours with artificial life support.During the experiment,the heart rate and blood pressure showed characteristic changes due to increased ICP.Prior to BD being established,a"tic reaction"inevitably occurred.We used an improved method of increasing ICP to establish a stable BD model.The BD state could be maintained for more than 48 hours with effective respiratory and circulatory support.Disappearance of the tic reaction was considered to be one of the verified indexes for BD via encephalic pressure increase.

  17. Use of Radarsat-2 and Landsat TM Images for Spatial Parameterization of Manning’s Roughness Coefficient in Hydraulic Modeling

    Directory of Open Access Journals (Sweden)

    Joseph Mtamba

    2015-01-01

    Full Text Available Vegetation resistance influences water flow in floodplains. Characterization of vegetation for hydraulic modeling includes the description of the spatial variability of vegetation type, height and density. In this research, we explored the use of dual polarized Radarsat-2 wide swath mode backscatter coefficients (σ° and Landsat 5 TM to derive spatial hydraulic roughness. The spatial roughness parameterization included four steps: (i land use classification from Landsat 5 TM; (ii establishing a relationship between σ° statistics and vegetation parameters; (iii relative surface roughness (Ks determination from Synthetic Aperture Radar (SAR backscatter temporal variability; (iv derivation of the spatial distribution of the spatial hydraulic roughness both from Manning’s roughness coefficient look up table (LUT and relative surface roughness. Hydraulic simulations were performed using the FLO-2D hydrodynamic model to evaluate model performance under three different hydraulic modeling simulations results with different Manning’s coefficient parameterizations, which includes SWL1, SWL2 and SWL3. SWL1 is simulated water levels with optimum floodplain roughness (np with channel roughness nc = 0.03 m−1/3/s; SWL2 is simulated water levels with calibrated values for both floodplain roughness np = 0.65 m−1/3/s and channel roughness nc = 0.021 m−1/3/s; and SWL3 is simulated water levels with calibrated channel roughness nc and spatial Manning’s coefficients as derived with aid of relative surface roughness. The model performance was evaluated using Nash-Sutcliffe model efficiency coefficient (E and coefficient of determination (R2, based on water levels measured at a gauging station in the wetland. The overall performance of scenario SWL1 was characterized with E = 0.75 and R2 = 0.95, which was improved in SWL2 to E = 0.95 and R2 = 0.99. When spatially distributed Manning values derived from SAR relative surface values were parameterized in

  18. 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.

  19. 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.

  20. A Bayesian spatial random parameters Tobit model for analyzing crash rates on roadway segments.

    Science.gov (United States)

    Zeng, Qiang; Wen, Huiying; Huang, Helai; Abdel-Aty, Mohamed

    2017-03-01

    This study develops a Bayesian spatial random parameters Tobit model to analyze crash rates on road segments, in which both spatial correlation between adjacent sites and unobserved heterogeneity across observations are accounted for. The crash-rate data for a three-year period on road segments within a road network in Florida, are collected to compare the performance of the proposed model with that of a (fixed parameters) Tobit model and a spatial (fixed parameters) Tobit model in the Bayesian context. Significant spatial effect is found in both spatial models and the results of Deviance Information Criteria (DIC) show that the inclusion of spatial correlation in the Tobit regression considerably improves model fit, which indicates the reasonableness of considering cross-segment spatial correlation. The spatial random parameters Tobit regression has lower DIC value than does the spatial Tobit regression, suggesting that accommodating the unobserved heterogeneity is able to further improve model fit when the spatial correlation has been considered. Moreover, the random parameters Tobit model provides a more comprehensive understanding of the effect of speed limit on crash rates than does its fixed parameters counterpart, which suggests that it could be considered as a good alternative for crash rate analysis.

  1. 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.

  2. 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.

  3. The problem with total error models in establishing performance specifications and a simple remedy.

    Science.gov (United States)

    Krouwer, Jan S

    2016-08-01

    A recent issue in this journal revisited performance specifications since the Stockholm conference. Of the three recommended methods, two use total error models to establish performance specifications. It is shown that the most commonly used total error model - the Westgard model - is deficient, yet even more complete models fail to capture all errors that comprise total error. Moreover, total error models are often set at 95% of results, which leave 5% of results as unspecified. Glucose meter performance standards are used to illustrate these problems. The Westgard model is useful to asses assay performance but not to set performance specifications. Total error can be used to set performance specifications if the specifications include 100% of the results.

  4. 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

  5. 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

  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. 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

  8. Cognitive Process Modeling of Spatial Ability: The Assembling Objects Task

    Science.gov (United States)

    Ivie, Jennifer L.; Embretson, Susan E.

    2010-01-01

    Spatial ability tasks appear on many intelligence and aptitude tests. Although the construct validity of spatial ability tests has often been studied through traditional correlational methods, such as factor analysis, less is known about the cognitive processes involved in solving test items. This study examines the cognitive processes involved in…

  9. Establishment of rat model of combined kidney-adrenal gland allotransplantation

    Institute of Scientific and Technical Information of China (English)

    Yanjun Shi; Ruipeng Jia; Jiageng Zhu; Guangcheng Zhou

    2006-01-01

    Objective: To establish a rat model of combined kidney-adrenal gland and allotransplantation, and to explore the immunoprotecive effect of the transplanted adrenal gland on the transplanted kidney in the combined transplantation.Methods: SD rats 160 served as donors and recipients. The combined kidney-adrenal gland allotransplantation was performed.Infusion was conducted and prepared at prime position ,and the kidney and adrenal gland were at the left side. Direct vascular anastomosis and operation of connecting ureter attached part of bladder with the bladder were conducted. The kidney pedicle of the right side was ligated. Results: A stable and mature rat model of combined transplantation was established. The warm ischemia time was 30 seconds, and the cold ischemia time was 90-120min. The average time was 100 min. The operation time was 150 min.The survival time of the recipients was 21 days. The successful rate of the operation was 75%. Conclusion: The model of the combined kidney-adrenal gland allotransplantation can be established with higher successful rate. The model can be used to explore that transplanted adrenal gland may have immunoprotecive effect on the transplanted kidney in the combined transplantation.

  10. Spatial distribution of mineral dust single scattering albedo based on DREAM model

    Science.gov (United States)

    Kuzmanoski, Maja; Ničković, Slobodan; Ilić, Luka

    2016-04-01

    Mineral dust comprises a significant part of global aerosol burden. There is a large uncertainty in estimating role of dust in Earth's climate system, partly due to poor characterization of its optical properties. Single scattering albedo is one of key optical properties determining radiative effects of dust particles. While it depends on dust particle sizes, it is also strongly influenced by dust mineral composition, particularly the content of light-absorbing iron oxides and the mixing state (external or internal). However, an assumption of uniform dust composition is typically used in models. To better represent single scattering albedo in dust atmospheric models, required to increase accuracy of dust radiative effect estimates, it is necessary to include information on particle mineral content. In this study, we present the spatial distribution of dust single scattering albedo based on the Dust Regional Atmospheric Model (DREAM) with incorporated particle mineral composition. The domain of the model covers Northern Africa, Middle East and the European continent, with horizontal resolution set to 1/5°. It uses eight particle size bins within the 0.1-10 μm radius range. Focusing on dust episode of June 2010, we analyze dust single scattering albedo spatial distribution over the model domain, based on particle sizes and mineral composition from model output; we discuss changes in this optical property after long-range transport. Furthermore, we examine how the AERONET-derived aerosol properties respond to dust mineralogy. Finally we use AERONET data to evaluate model-based single scattering albedo. Acknowledgement We would like to thank the AERONET network and the principal investigators, as well as their staff, for establishing and maintaining the AERONET sites used in this work.

  11. Establishing the psychometric properties of constructs in a community-based participatory research conceptual model.

    Science.gov (United States)

    Oetzel, John G; Zhou, Chuan; Duran, Bonnie; Pearson, Cynthia; Magarati, Maya; Lucero, Julie; Wallerstein, Nina; Villegas, Malia

    2015-01-01

    The purpose of this study is to establish the psychometric properties of 22 measures from a community-based participatory research (CBPR) conceptual model. The design of this study was an online, cross-sectional survey of academic and community partners involved in a CPBR project. CPBR projects (294) in the United States with federal funding in 2009. Of the 404 academic and community partners invited, 312 (77.2%) participated. Of the 200 principal investigators/project directors invited, 138 (69.0%) participated. Twenty-two measures of CBPR context, group dynamics, methods, and health-related outcomes were examined. Confirmatory factor analysis to establish factorial validity and Pearson correlations to establish convergent and divergent validity were used. Confirmatory factor analysis demonstrated strong factorial validity for the 22 constructs. Pearson correlations (p < .001) supported the convergent and divergent validity of the measures. Internal consistency was strong, with 18 of 22 measures achieving at least a .78 Cronbach α. CBPR is a key approach for health promotion in underserved communities and/or communities of color, yet the basic psychometric properties of CBPR constructs have not been well established. This study provides evidence of the factorial, convergent, and discriminant validity and the internal consistency of 22 measures related to the CBPR conceptual model. Thus, these measures can be used with confidence by both CBPR practitioners and researchers to evaluate their own CBPR partnerships and to advance the science of CBPR.

  12. A Spatially Distributed Hydrological Model For The Okavango Delta, Botswana

    Science.gov (United States)

    Bauer, P.; Kinzelbach, W.; Thabeng, G.

    2003-04-01

    The Okavango Delta is a large (˜30 000 km^2) inland delta situated in northern Botswana. It is subject to annual flooding due to the strong seasonality of the inflowing Okavango River and of local rainfall. The inflowing waters spread out over vast perennial and seasonal floodplains and partially infiltrate into the underlying sand aquifer. Ultimately, the water is consumed by evapotranspiration, there is no significant outflow from the Delta. The system's response to the annual flood in the Okavango River as well as local rainfall and evapotranspiration is modelled within a finite difference scheme based on MODFLOW. The wetland and the underlying sand aquifer are incorporated as two separate layers. In the superficial layer, either steady uniform channel flow (Darcy-Weisbach equation) or potential flow (Darcy flow) can be chosen on a cell-by-cell basis. The coarse spatial resolution does not capture the small-scale variation in the topographic elevation. Therefore, upscaling techniques are applied to incorporate the statistics of that variation into effective parameters for the hydraulic conductivity, the storage coefficient and the evapotranspiration. Modelled flooding patterns are compared with flooding patterns derived from NOAA-AVHRR and other remote sensing data (1 km resolution). Good correspondence between the two is achieved based on parameters chosen according to prior knowledge and field data. Global indicators like the average size of the Delta and the temporal variance of its size are closely reproduced. Ultimately, the remotely sensed flooding patterns will be used to calibrate the model. Apart from flooding patterns, model outputs include cell-by-cell flow terms. Water balances can be calculated for arbitrary sub-regions of the grid. Other monitoring data like water levels in rivers and boreholes as well as discharges at gauging points may be used for validation of the model. The Okavango Delta is one of the prime conservation areas in Africa and a

  13. Identifying Spatially Variable Sensitivity of Model Predictions and Calibrations

    Science.gov (United States)

    McKenna, S. A.; Hart, D. B.

    2005-12-01

    Stochastic inverse modeling provides an ensemble of stochastic property fields, each calibrated to measured steady-state and transient head data. These calibrated fields are used as input for predictions of other processes (e.g., contaminant transport, advective travel time). Use of the entire ensemble of fields transfers spatial uncertainty in hydraulic properties to uncertainty in the predicted performance measures. A sampling-based sensitivity coefficient is proposed to determine the sensitivity of the performance measures to the uncertain values of hydraulic properties at every cell in the model domain. The basis of this sensitivity coefficient is the Spearman rank correlation coefficient. Sampling-based sensitivity coefficients are demonstrated using a recent set of transmissivity (T) fields created through a stochastic inverse calibration process for the Culebra dolomite in the vicinity of the WIPP site in southeastern New Mexico. The stochastic inverse models were created using a unique approach to condition a geologically-based conceptual model of T to measured T values via a multiGaussian residual field. This field is calibrated to both steady-state and transient head data collected over an 11 year period. Maps of these sensitivity coefficients provide a means of identifying the locations in the study area to which both the value of the model calibration objective function and the predicted travel times to a regulatory boundary are most sensitive to the T and head values. These locations can be targeted for deployment of additional long-term monitoring resources. Comparison of areas where the calibration objective function and the travel time have high sensitivity shows that these are not necessarily coincident with regions of high uncertainty. The sampling-based sensitivity coefficients are compared to analytically derived sensitivity coefficients at the 99 pilot point locations. Results of the sensitivity mapping exercise are being used in combination

  14. Phase transition in a spatial Lotka-Volterra model

    Energy Technology Data Exchange (ETDEWEB)

    Szabo, Gyorgy; Czaran, Tamas

    2001-06-01

    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{sub 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.

  15. Phase transition in a spatial Lotka-Volterra model.

    Science.gov (United States)

    Szabó, G; Czárán, T

    2001-06-01

    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.

  16. Spatial Double Generalized Beta Regression Models: Extensions and Application to Study Quality of Education in Colombia

    Science.gov (United States)

    Cepeda-Cuervo, Edilberto; Núñez-Antón, Vicente

    2013-01-01

    In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models' setting. Finally, we motivate…

  17. Spatial and Temporal Behaviors in a Modified Evolution Model Based on Small World Network

    Institute of Scientific and Technical Information of China (English)

    ZHAO Xiao-Wei; ZHOU Li-Ming; CHEN Tian-Lun

    2004-01-01

    In this paper, we introduce a new modified evolution model on a small world network. In our model,the spatial and temporal correlations and the spatial-temporal evolve pattern of mutating nodes exhibit some particular behaviors different from those of the original BS evolution model. More importantly, these behaviors will change with φ, the density of short paths in our network.

  18. Spatial Double Generalized Beta Regression Models: Extensions and Application to Study Quality of Education in Colombia

    Science.gov (United States)

    Cepeda-Cuervo, Edilberto; Núñez-Antón, Vicente

    2013-01-01

    In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models' setting. Finally, we…

  19. 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.

  20. Establishment of Mus Skin Photo-damage Model by 8-MOP plus UVA Irradiation

    Institute of Scientific and Technical Information of China (English)

    LIANG Hong; LI Jiawen; ZHANG Li

    2007-01-01

    To establish a simple and reliable animal model of skin photo-damage, 20 mice were treated with 8-MOP and exposed to UVA (UVA 320-400 nm) for 24 h. After irradiation, the structure of the epidermis and dermis, collagen fibers, elastic fibers were observed by using HE staining and Weigert technique and compared with the normal controls. The acanthosis and epidemis proliferation with accompanying hyperkeratosis and parakeratosis were observed. Inflammatory infiltration was noted in the dermis. The elastic fibers became coarse, irregularly arranged and clustered, with their number increased. The collagen fibers showed obvious degeneration and some amorphous materials could also be observed. The blood vessels were irregularly dilated and vascular walls were thickened, with infiltration of inflammatory cells. It is concluded that murine photodamage model can be quickly, conveniently and reliably established by means of 8-MOP/UVA.

  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 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

    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......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...... 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...

  3. 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...

  4. 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.

  5. Establishment of risk model for pancreatic cancer in Chinese Han population

    Institute of Scientific and Technical Information of China (English)

    Xing-Hua Lu; Li Wang; Hui Li; Jia-Ming Qian; Rui-Xue Deng; Lu Zhou

    2006-01-01

    AIM: To investigate risk factors for pancreatic cancer and establish a risk model for Han population.METHODS: This population-based case-control study was carried out from January 2002 to April 2004. One hundred and nineteen pancreatic cancer patients and 238 healthy people completed the questionnaire which was used for risk factor analysis. Logistic regression analysis was used to calculate odds ratio (ORs), 95%confidence intervals (Cis) and β value, which were further used to establish the risk model.RESULTS: According to the study, people who have smoked more than 17 pack-years had a higher risk to develop pancreatic cancer compared to non-smokers or light smokers (not more than 17 pack-years) (OR 1.98;95% CI 1.11-3.49, P=0.017). More importantly, heavy smokers in men had increased risk for developing pancreatic cancer (OR 2.11; 95%CI 1.18-3.78, P=0.012)than women. Heavy alcohol drinkers (>20 cup-years)had increased risk for pancreatic cancer (OR 3.68;95%CI 1.60-8.44). Daily diet with high meat intak was also linked to pancreatic cancer. Moreover, 18.5% of the pancreatic cancer patients had diabetes mellitus compared to the control group of 5.8% (P= 0.0003). Typical symptoms of pancreatic cancer were anorexia, upper abdominal pain, bloating, jaundice and weight loss. Each risk factor was assigned a value to represent its impor tance associated with pancreatic cancer. Subsequently by adding all the points together, a risk scoring model was established with a value higher than 45 as being at risk to develop pancreatic cancer.CONCLUSION: Smoking, drinking, high meat diet and diabetes are major risk factors for pancreatic cancer. A risk model for pancreatic cancer in Chinese Hah population has been established with an 88.9% sensitivity and a 97.6% specificity.

  6. 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, pcontrols. Of the 7 rabbits with severe hypothyroidism, 6 died from 4 to 14 weeks after the thyroidectomy possibly owing to heart failure, because histopathologic examinations revealed a myxedema 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.

  7. Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model

    Science.gov (United States)

    Berezowski, T.; Nossent, J.; Chormański, J.; Batelaan, O.

    2015-04-01

    As the availability of spatially distributed data sets for distributed rainfall-runoff modelling is strongly increasing, more attention should be paid to the influence of the quality of the data on the calibration. While a lot of progress has been made on using distributed data in simulations of hydrological models, sensitivity of spatial data with respect to model results is not well understood. In this paper we develop a spatial sensitivity analysis method for spatial input data (snow cover fraction - SCF) for a distributed rainfall-runoff model to investigate when the model is differently subjected to SCF uncertainty in different zones of the model. The analysis was focussed on the relation between the SCF sensitivity and the physical and spatial parameters and processes of a distributed rainfall-runoff model. The methodology is tested for the Biebrza River catchment, Poland, for which a distributed WetSpa model is set up to simulate 2 years of daily runoff. The sensitivity analysis uses the Latin-Hypercube One-factor-At-a-Time (LH-OAT) algorithm, which employs different response functions for each spatial parameter representing a 4 × 4 km snow zone. The results show that the spatial patterns of sensitivity can be easily interpreted by co-occurrence of different environmental factors such as geomorphology, soil texture, land use, precipitation and temperature. Moreover, the spatial pattern of sensitivity under different response functions is related to different spatial parameters and physical processes. The results clearly show that the LH-OAT algorithm is suitable for our spatial sensitivity analysis approach and that the SCF is spatially sensitive in the WetSpa model. The developed method can be easily applied to other models and other spatial data.

  8. 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.

  9. 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.

  10. Assessing the performance of the independence method in modeling spatial extreme rainfall

    Science.gov (United States)

    Zheng, Feifei; Thibaud, Emeric; Leonard, Michael; Westra, Seth

    2015-09-01

    Spatial statistical methods are often employed to improve precision when estimating marginal distributions of extreme rainfall. Methods such as max-stable and copula models parameterize the spatial dependence and provide a continuous spatial representation. Alternatively, the independence method can be used to estimate marginal parameters without the need for parameterizing the spatial dependence, and this method has been under-utilized in hydrologic applications. This paper investigates the effectiveness of the independence method for marginal parameter estimation of spatially dependent extremes. Its performance is compared with three spatial dependence models (max-stable Brown-Resnick, max-stable Schlather, and Gaussian copula) by means of a simulation study. The independence method is statistically robust in estimating parameters and their associated confidence intervals for spatial extremes with various underlying dependence structures. The spatial dependence models perform comparably with the independence method when the spatial dependence structure is correctly specified; otherwise they exhibit considerably worse performance. We conclude that the independence method is more appealing for modeling the marginal distributions of spatial extremes (e.g., regional estimation of trends in rainfall extremes) due to its greater robustness and simplicity. The four statistical methods are illustrated using a spatial data set comprising 69 subdaily rainfall series from the Greater Sydney region, Australia.

  11. 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.

  12. Modelling of the education quality of a high schools in Sumenep Regency using spatial structural equation modelling

    Science.gov (United States)

    Anekawati, Anik; Widjanarko Otok, Bambang; Purhadi; Sutikno

    2017-09-01

    In some cases, education research often involves the latent variables that have a causal relationship as well as a spatial effect. Therefore, it requires a statistical analysis technique called spatial structural equation modelling (spatial SEM). In this research, a spatial SEM was developed to model the quality of education in high schools in Sumenep Regency. This model was improved after the evaluation of an outer and inner model of the model scheme centroid, factor and path since some indicators were not valid. The path scheme model showed better results compared to the other schemes since all of its indicators were valid and its value of R-square increased. Furthermore, only the model of path scheme was tested for spatial effects. The result of the identification test of spatial effects on the inner model using a robust Lagrange multiplier test (using queen contiguity) showed that the education quality model leads to a spatial autoregressive model (SAR in SEM) with a significance level α of 5%, while the model of school infrastructure has no significant spatial effects. The improved model of SAR in SEM, the R2 value obtained was 47.33%, so that it is clear that data variation can be explained by the model of SAR in SEM for the quality of education in high schools.

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

    Science.gov (United States)

    Ayubi, Erfan; Mansournia, Mohammad Ali; Motlagh, Ali Ghanbari; Mosavi-Jarrahi, Alireza; Hosseini, Ali; Yazdani, Kamran

    2017-01-01

    The aim of this study was to explore the spatial pattern of female breast cancer (BC) incidence at the neighborhood level in Tehran, Iran. 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. 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). 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.

  14. 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 < or = 3 degree C for at least 15 wk) was used as the criterion for whether establishment can occur. Furthermore, these countries have no host plant species available for R. indifferens. Our results can be used to make scientifically informed international trade decisions and negotiations by policy makers.

  15. Establishment of constitutive relationship model for 2519 aluminum alloy based on BP artificial neural network

    Institute of Scientific and Technical Information of China (English)

    LIN Qi-quan; PENG Da-shu; ZHU Yuan-zhi

    2005-01-01

    An isothermal compressive experiment using Gleeble 1500 thermal simulator was studied to acquire flow stress at different deformation temperatures, strains and strain rates. The artificial neural networks with the error back propagation(BP) algorithm was used to establish constitutive model of 2519 aluminum alloy based on the experiment data. The model results show that the systematical error is small(δ=3.3%) when the value of objective function is 0.2, the number of nodes in the hidden layer is 5 and the learning rate is 0.1. Flow stresses of the material under various thermodynamic conditions are predicted by the neural network model, and the predicted results correspond with the experimental results. A knowledge-based constitutive relation model is developed.

  16. [Analysis on establishment and affecting factors of qi stagnation and blood stasis rat model].

    Science.gov (United States)

    Wang, Tingting; Jia, Cheng; Chen, Yu; Li, Xin; Cheng, Jiayi

    2012-06-01

    To study on the method for establishing the Qi stagnation and blood stasis rat model and analyze the affecting factors. The orthogonal design was adopted to study the influences of joint stimulations including noise, light, electricity, ice water bath, tail-clamping on model rats. The 'flying spot' method was used to dynamically simulate blood flow velocity in microcirculation. the pressure sensing technology of MOTO was adopted to detect hemorheology-related indicators. And the coagulation method was used to detect blood coagulation-related indicators. Compared with the negative control group, all model groups showed significant reduction in the blood flow velocity in mesenteric microcirculation and increase in the whole blood viscosity at high, medium and low shear rate, the plasma viscosity and the fibrinogen content in four blood coagulation indicators. Noise, light, electricity, tail-clamping, bondage and icewater-bath make significant impact on model rats.

  17. Establishing Performance Evaluation Model with Queuing Theory in NoC

    Directory of Open Access Journals (Sweden)

    Tao He

    2013-10-01

    Full Text Available The transmission delay is an important index of the system performance of NoC (Network on Chip. Although the method of simulation-based can get accurate transmission delay, the simulation requires time consuming and a large number of test vectors. Especially in the study of some algorithms, such as mapping algorithms, buffer allocation algorithm, the simulation method is not applicable. To solve the above problems, the paper uses queuing theory to study the establishment of a NoC delay model. The model considers the limited buffer of routing unit and virtual channel technology for network transmission delay and proposes solving algorithm of the delay model based on reverse deduction method. The simulation shows that this model used to analyze the application-specific data transmission delay has smaller average error (reduced by 8% and higher evaluation efficiency (increased by more than 30 times, which provide designers an efficient method of performance evaluation.  

  18. Establishing a structured animal model for screening anti-psychological drugs of schizophrenia

    Institute of Scientific and Technical Information of China (English)

    Liang Li; Zhemeng Wu

    2014-01-01

    Although some traditional animal models for studying schizophrenia have been wildly used,many problems remain in their credibility and validity.We propose that structured animal models with the integration of multiple symptom-inducing factors are be better in simulating the symptoms of schizophrenia and represent the new direction of the future ani-mal-model development.In this article,we review previous studies in this line of research and emphasize the importance of combining the behavior paradigm of the structured top-down attentional modulation of prepulse inhibition with multiple path-ogenic factors related to schizophrenia to establish a new model generation,which will be of great significance in investigating both the pathogenesis and the treatment of schizophrenia.

  19. Study on Lumped Kinetic Model for FDFCC I. Establishment of Model

    Institute of Scientific and Technical Information of China (English)

    Wu Feiyue; Weng Huixin; Luo Shixian

    2008-01-01

    According to the process features and the reaction mechanism of FDFCC technology, its two reaction subsystems, one for heavy oil riser reactor, the other for gasoline riser reactor, were respectively studied. Correspondingly, a 12-lump kinetic model for heavy oil FCC and a 9-lump kinetic model for gasoline catalytic upgrading were presented. Based on this work, mathematical correlation of the lumps in the feeds and products involved in the reaction subsystems and those of the overall reaction system were analyzed in detail. Then, a combined kinetic model for FDFCC, which was based on the data recovered from a commercial unit, was put forward. The reaction performance embodied by the kinetic constants for the combined model of FDFCC was in accordance with catalytic cracking reaction mechanism. The model-calculated values were close to the data obtained in commercial scale. The model was easy to be applied in practice and could also provide some theoretical groundwork for further research on kinetic model for FDFCC.

  20. 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.

  1. Modeling spatial relation in skin lesion images by the graph walk kernel.

    Science.gov (United States)

    Situ, Ning; Wadhawan, Tarun; Yuan, Xiaojing; Zouridakis, George

    2010-01-01

    Early skin cancer detection with the help of dermoscopic images is becoming more and more important. Previous methods generally ignored the spatial relation of the pixels or regions inside the lesion. We propose to employ a graph representation of the skin lesion to model the spatial relation. We then use the graph walk kernel, a similarity measure between two graphs, to build a classifier based on support vector machines for melanoma detection. In experiments, we compare the sensitivities and specificities of models with and without spatial information. Experimental results show that the model with spatial information performs the best in both sensitivity and specificity. Statistical test indicates that the improvement is significant.

  2. Elastin exhibits a distinctive temporal and spatial pattern of distribution in the developing chick limb in association with the establishment of the cartilaginous skeleton.

    Science.gov (United States)

    Hurle, J M; Corson, G; Daniels, K; Reiter, R S; Sakai, L Y; Solursh, M

    1994-09-01

    In this work we have analyzed the presence of elastic components in the extracellular matrices of the developing chick leg bud. The distributions of elastin and fibrillin were studied immunohistochemically in whole-mount preparations using confocal laser microscopy. The association of these constituents of the elastic matrix with other components of the extracellular matrix was also studied, using several additional antibodies. Our results reveal the transient presence of an elastin-rich scaffold of extracellular matrix fibrillar material in association with the establishment of the cartilaginous skeleton of the leg bud. The scaffold consisted of elastin-positive fibers extending from the ectodermal surface of the limb to the central cartilage-forming regions and between adjacent cartilages. Fibrillin immunolabeling was negative in this fibrillar scaffold while other components of the extracellular matrix including: tenascin, laminin and collagens type I, type III and type VI; appeared codistributed with elastin in some regions of the scaffold. Progressive changes in the spatial pattern of distribution of the elastin-positive scaffold were detected in explant cultures in which one expects a modification in the mechanical stresses of the tissues related to growth. A scaffold of elastin comparable to that found in vivo was also observed in high-density micromass cultures of isolated limb mesodermal cells. In this case the elastic fibers are observed filling the spaces located between the cartilaginous nodules. The fibers become reoriented and attach to the ectodermal basal surface when an ectodermal fragment is located at the top of the growing micromass. Our results suggest that the formation of the cartilaginous skeleton of the limb involves the segregation of the undifferentiated limb mesenchyme into chondrogenic and elastogenic cell lineages. Further, a role for the elastic fiber scaffold in coordinating the size and the spatial location of the cartilaginous

  3. 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.

  4. Scaling precipitation input to spatially distributed hydrological models by measured snow distribution

    OpenAIRE

    2016-01-01

    Accurate knowledge on snow distribution in alpine terrain is crucial for various applicationssuch as flood risk assessment, avalanche warning or managing water supply and hydro-power.To simulate the seasonal snow cover development in alpine terrain, the spatially distributed,physics-based model Alpine3D is suitable. The model is typically driven by spatial interpolationsof observations from automatic weather stations (AWS), leading to errors in the spatial distributionof atmospheric forcing. ...

  5. A sensitivity analysis using different spatial resolution terrain models and flood inundation models

    Science.gov (United States)

    Papaioannou, George; Aronica, Giuseppe T.; Loukas, Athanasios; Vasiliades, Lampros

    2014-05-01

    The impact of terrain spatial resolution and accuracy on the hydraulic flood modeling can pervade the water depth and the flood extent accuracy. Another significant factor that can affect the hydraulic flood modeling outputs is the selection of the hydrodynamic models (1D,2D,1D/2D). Human mortality, ravaged infrastructures and other damages can be derived by extreme flash flood events that can be prevailed in lowlands at suburban and urban areas. These incidents make the necessity of a detailed description of the terrain and the use of advanced hydraulic models essential for the accurate spatial distribution of the flooded areas. In this study, a sensitivity analysis undertaken using different spatial resolution of Digital Elevation Models (DEMs) and several hydraulic modeling approaches (1D, 2D, 1D/2D) including their effect on the results of river flow modeling and mapping of floodplain. Three digital terrain models (DTMs) were generated from the different elevation variation sources: Terrestrial Laser Scanning (TLS) point cloud data, classic land surveying and digitization of elevation contours from 1:5000 scale topographic maps. HEC-RAS and MIKE 11 are the 1-dimensional hydraulic models that are used. MLFP-2D (Aronica et al., 1998) and MIKE 21 are the 2-dimensional hydraulic models. The last case consist of the integration of MIKE 11/MIKE 21 where 1D-MIKE 11 and 2D-MIKE 21 hydraulic models are coupled through the MIKE FLOOD platform. The validation process of water depths and flood extent is achieved through historical flood records. Observed flood inundation areas in terms of simulated maximum water depth and flood extent were used for the validity of each application result. The methodology has been applied in the suburban section of Xerias river at Volos-Greece. Each dataset has been used to create a flood inundation map for different cross-section configurations using different hydraulic models. The comparison of resulting flood inundation maps indicates

  6. Establishment of a cell model for screening antibody drugs against rheumatoid arthritis with ADCC and CDC.

    Science.gov (United States)

    Yan, Li; Hu, Rui; Tu, Song; Cheng, Wen-Jun; Zheng, Qiong; Wang, Jun-Wen; Kan, Wu-Sheng; Ren, Yi-Jun

    2015-01-01

    TNFα played a dominant role in the development and progression of rheumatoid arthritis (RA). Clinical trials proved the efficacies of anti-TNFα agents for curing RA. However, most researchers were concentrating on their abilities of neutralizing TNFα, the potencies of different anti-TNFα agents varied a lot due to the antibody-dependent cell-mediated cytotoxicity (ADCC) or complement dependent cytotoxicity (CDC). For better understanding and differentiating the potentiality of various candidate anti-TNF reagents at the stage of new drug research and development, present study established a cell model expressing the transmembrane TNFα for usage in in vitro ADCC or CDC assay, meanwhile, the assay protocol described here could provide guidelines for screening macromolecular antibody drugs. A stable cell subline bearing transmembrane TNFα was first established by conventional transfection method, the expression of transmembrane TNFα was approved by flow cytometer, and the performance of the stable subline in ADCC and CDC assay was evaluated, using human peripheral blood mononuclear cells as effector cells, and Adalimumab as the anti-TNFα reagent. The stable cell subline demonstrated high level of surface expression of transmembrane TNFα, and Adalimumab exerted both ADCC and CDC effects on this cell model. In conclusion, the stable cell line we established in present research could be used in ADCC or CDC assay for screening antibody drugs, which would provide in-depth understanding of the potencies of candidate antibody drugs in addition to the traditional TNFα neutralizing assay.

  7. Spatial Modeling of Flood Sea Tides (Case Study: East Coast Semarang)

    OpenAIRE

    Muhammad Aris Marfai

    2004-01-01

    The aims of this research are 1) to construct a spatial model of tidal flood hazard, 2) to do hazard analysis of tidal flood. Spatial modelling has been generated using Geographic Information System (GIS) software and ILWIS software was seleccted to do the model operation. Neighborhood function and digital elevation model (DEM) have been applied on the modelling calculation process. DEM data was correted and menipulated using map calculation on the digital form. Tidal flood hazard analysis ha...

  8. 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.

  9. 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

  10. Spatial and Activities Models of Airport Based on GIS and Dynamic Model

    Science.gov (United States)

    Masri, R. M.; Purwaamijaya, I. M.

    2017-02-01

    The purpose of research were (1) a conceptual, functional model designed and implementation for spatial airports, (2) a causal, flow diagrams and mathematical equations made for airport activity, (3) obtained information on the conditions of space and activities at airports assessment, (4) the space and activities evaluation at airports based on national and international airport services standards, (5) options provided to improve the spatial and airport activities performance become the international standards airport. Descriptive method is used for the research. Husein Sastranegara Airport in Bandung, West Java, Indonesia was study location. The research was conducted on September 2015 to April 2016. A spatial analysis is used to obtain runway, taxiway and building airport geometric information. A system analysis is used to obtain the relationship between components in airports, dynamic simulation activity at airports and information on the results tables and graphs of dynamic model. Airport national and international standard could not be fulfilled by spatial and activity existing condition of Husein Sastranegara. Idea of re-location program is proposed as problem solving for constructing new airport which could be serving international air transportation.

  11. Improved Cuff Technique for Establishing a Mouse-Rat Heterotopic Cardiac Xenotransplantation Model.

    Science.gov (United States)

    Li, C; Qi, F; Liu, T; Wang, H; Wang, P-Z

    2015-01-01

    The small animal model of cardiac transplantation is the most common model in organ transplantation studies. The cervical heterotopic transplantation is widely performed because this allows for direct observation of the graft heartbeat and contributes to early prediction of graft rejection. A mouse-rat cervical heterotopic cardiac xenotransplantation model was modified with respect to the anesthesia method, cardiac graft harvesting method, and perioperative treatment. These improvements ensure the stability and reliability of xenotransplantation models for in vivo studies of immune-mediated graft rejection. After establishing isoflurane inhalation anesthesia, the donors' hearts were harvested. The experimental method involved separate ligation of the left and right superior venae cavae; the other blood vessels were ligated in a cluster. Both the donor and recipient animals were placed on a heating pad intraoperatively to maintain a body temperature of 37-40 °C. The model establishment was divided into 3 stages: practice, stabilization, and stereotyping. The surgical success rate and operation time were recorded. Specimens were harvested at different time points for histopathological examination. The anesthetic effect of isoflurane was well maintained, and no animals died of adverse anesthetic events. Body temperature was maintained at 37-40 °C which effectively shortened the time to restoration. The modification of the cardiac graft harvesting method is conducive to rebeating of the donor heart. The success rates in the stabilization and stereotyping stages were significantly higher than that in the practice stage (P rat cervical heterotopic cardiac xenotransplantation model is the ideal animal model for studying xenograft rejection. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. A spatial simulation model for forest succession in the Upper Mississippi River floodplain

    Science.gov (United States)

    Yin, Y.; Wu, Y.; Bartell, S.M.

    2009-01-01

    A Markov-chain transition model (FORSUM) and Monte Carlo simulations were used to simulate the succession patterns and predict a long-term impact of flood on the forest structure and growth in the floodplain of the Upper Mississippi River and Illinois River. Model variables, probabilities, functions, and parameters were derived from the analysis of two comprehensive field surveys conducted in this floodplain. This modeling approach describes the establishment, growth, competition, and death of individual trees for modeled species on a 10,000-ha landscape with spatial resolution of 1 ha. The succession characteristics of each Monte Carlo simulation are summed up to describe forest development and dynamics on a landscape level. FORSUM simulated the impacts of flood intensity and frequency on species composition and dynamics in the Upper Mississippi River floodplain ecosystem. The model provides a useful tool for testing hypotheses about forest succession and enables ecologists and managers to evaluate the impacts of flood disturbances and ecosystem restoration on forest succession. The simulation results suggest that the Markov-chain Monte Carlo method is an efficient tool to help organize the existing data and knowledge of forest succession into a system of quantitative predictions for the Upper Mississippi River floodplain ecosystem. ?? 2009 Elsevier B.V.

  13. Establishment and use of surgical rat models for assessment of organ specific in vivo clearance.

    Science.gov (United States)

    Vestergaard, Bill

    2016-06-01

    Knowledge of clearance plays a key role in the development of new drug entities, especially in the development of improved analogues for treatment of chronic conditions. Improved pharmacokinetic properties can be used to increase dosing interval and thereby improve patient compliance. This will lead to improved treatment outcome or decreased risk of treatment failure when treating chronic conditions. Therefore, animal models for assessment of organ-specific clearance are of great value in preclinical drug development. These models can be used to obtain insights into the relative importance of a clearance organ and thereby guide drug design of new analogues in early drug discovery. The current PhD project was undertaken to explore surgical in vivo models, which could be used in the assessment of the relative importance of major clearance organs. It was the aim of the PhD project to establish and validate both a nephrectomy model and a hepatectomy model as tools to investigate relative importance of renal and hepatic clearance. Furthermore, the project aim was to investigate renal clearance of rFVIIa and rhGH using a nephrectomy model in rats. The thesis is composed of a short theoretical background, a literature review, two papers based on experimental work as well as experimental work not included in the papers. Chapter one is an introduction with the specific aims and hypotheses. The chapters from two to five contain theoretical background of the clearance concept, anatomical and physiological description of clearance organs and a brief overview of potential clearance models including in vivo models. Chapters six through nine highlight the experimental work with the results obtained during the PhD project. Lastly, the chapters from ten to twelve contain a general discussion, conclusion and perspectives of the current thesis. Paper I "Nephrectomized and hepatectomized animal models as tools in preclinical pharmacokinetics" provides a literature review of animal

  14. Remembering the Past and Imagining the Future: A Neural Model of Spatial Memory and Imagery

    Science.gov (United States)

    Byrne, Patrick; Becker, Suzanna; Burgess, Neil

    2007-01-01

    The authors model the neural mechanisms underlying spatial cognition, integrating neuronal systems and behavioral data, and address the relationships between long-term memory, short-term memory, and imagery, and between egocentric and allocentric and visual and ideothetic representations. Long-term spatial memory is modeled as attractor dynamics…

  15. Quantification of the effect of spatially varying environmental contaminants into a cost model for soil remediation

    NARCIS (Netherlands)

    Broos, J.M.; Aarts, L.; Tooren, C.F.; Stein, A.

    1999-01-01

    In this study we investigated the effects of spatial variability of soil contaminants on cost calculations for soil remediation. Most cost models only provide a single figure, whereas spatial variability is one of the sources to contribute to the uncertainty. A cost model is applied to a study site

  16. Spatial Prediction of Coxiella burnetii Outbreak Exposure via Notified Case Counts in a Dose-Response Model.

    Science.gov (United States)

    Brooke, Russell J; Kretzschmar, Mirjam E E; Hackert, Volker; Hoebe, Christian J P A; Teunis, Peter F M; Waller, Lance A

    2017-01-01

    We develop a novel approach to study an outbreak of Q fever in 2009 in the Netherlands by combining a human dose-response model with geostatistics prediction to relate probability of infection and associated probability of illness to an effective dose of Coxiella burnetii. The spatial distribution of the 220 notified cases in the at-risk population are translated into a smooth spatial field of dose. Based on these symptomatic cases, the dose-response model predicts a median of 611 asymptomatic infections (95% range: 410, 1,084) for the 220 reported symptomatic cases in the at-risk population; 2.78 (95% range: 1.86, 4.93) asymptomatic infections for each reported case. The low attack rates observed during the outbreak range from (Equation is included in full-text article.)to (Equation is included in full-text article.). The estimated peak levels of exposure extend to the north-east from the point source with an increasing proportion of asymptomatic infections further from the source. Our work combines established methodology from model-based geostatistics and dose-response modeling allowing for a novel approach to study outbreaks. Unobserved infections and the spatially varying effective dose can be predicted using the flexible framework without assuming any underlying spatial structure of the outbreak process. Such predictions are important for targeting interventions during an outbreak, estimating future disease burden, and determining acceptable risk levels.

  17. 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 ex......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...

  18. 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.

  19. 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.

  20. The Establishment and Development of Finite Element Model of Human Cervical Vertebra and Its Application Example

    Institute of Scientific and Technical Information of China (English)

    SHEN Xiao-wen; YU Hang-ping; ZOU Wei

    2008-01-01

    .The incidence rate of cervical spondylosis is high,and due to the complicacy of cervical vertebra structure, irregularity of shapes and non-uniformity of components, sometimes it's difficult to achieve planned objectives by experiments in vitro through stress and strain analysis. Besides, the biomechanical factors are of vital significance in the cause of spinal disorders. In this paper the author makes a summary of the present modeling of human cervical vertebra and describes the major methods of establishing the finite element model of human cervical vertebra through several self-constructed models. With the advance of computer technology, the finite element methods have been rapidly developed in cervical vertebra biomechanical researches and have became a major approach for biomechanical researches to simulate more and more clinical conditions.

  1. Modeling of Task Establishment and Allocation for Collaborative Virtual Maintenance Training of Complex Equipment

    Directory of Open Access Journals (Sweden)

    Xiangyang Li

    2012-09-01

    Full Text Available In this study, we propose the maintenance task establishment method based on fault simulation models. Maintenance task allocation model based on Multi-Agent System and High Level Architecture is presented to manage and coordinate the dynamic task allocating process of multi operators and it can make the intelligent decision for their collaborative maintenance operation at each step. Object information template is designed with the Extensible Markup Language to perform interactive communication of the heterogeneous data and information in the different models of collaborative virtual maintenance training system, which ensures the efficient share of the data resource for the collaborative maintenance operations. Finally, the simulation research on a mechanical-electronic-hydraulic integrated subsystem in complex equipment is done and the simulation execution and results show the effectiveness of the proposed methods.

  2. [Establishment and evaluation of a dynamic in vitro intestinal absorption model of lipid formulations].

    Science.gov (United States)

    Liu, Ying; Yi, Tao; Di, Huan; Xiao, Lu; He, Ji-Kui

    2011-08-01

    A new dynamic in vitro intestinal absorption model for screening and evaluating lipid formulations was established by means of the characteristics of the intestinal digestion and absorption of the lipid formulations. This model was composed of two systems, including intestinal digestion and the intestinal tissue culture, which drew the evaluation method of intestinal absorption into the in vitro lipolysis model. The influence of several important model parameters such as Ca2+, D-glucose, K+ on the two systems of this model has been investigated. The results showed that increasing of Ca2+ concentration could be significantly conductive to intestinal digestion. The increasing of D-glucose concentration could stepped significantly down the decay of the intestinal activity. K+ was able to maintain intestinal activity, but the influence of different concentration levels on the decay of the intestinal activity was of no significant difference. Thus the model parameters were set up as follows: Ca2+ for 10 mmol x L(-1), D-glucose for 15 mmol x L(-1) and K+ for 5.5 mmol x L(-1). Type I lipid formulation was evaluated with this model, and there was a significant correlation between the absorption curve in vitro and absorption curve in vivo of rats (r = 0.995 6, P lipid formulations.

  3. Establishment of the model of vascular endothelial cell membrane chromatography and its preliminary application

    Institute of Scientific and Technical Information of China (English)

    LI YiPing; HE LangChong

    2007-01-01

    A model of vascular endothelial cell membrane chromatography was established by using an ECV304 cell membrane stationary phase (ECV304 CMSP) prepared by immobilizing the ECV304 cell membrane onto the surface of silica carrier. The surface and chromatographic characteristics of ECV304 CMSP were studied. The active component from Caulophyllum robustum was screened by using the model of vascular endothelial cell membrane chromatography. The interaction between the active component and membrane receptor was determined by using a replace experiments. The effect of the active component was tested by using tube formation of ECV304 cell. The results indicated that the model of ECV304 cell membrane chromatograph (ECV304 CMC) can stimulate the interaction between drug and receptor in vitro and the retention characteristics of taspine as active component was similar to that of model molecule in the model of ECV304 CMC. And therefore, taspine acted on VEGFR2 and inhibited the tube formation of ECV304 cell induced by VEGF. This model can be used to screen definite active component as a screening model.

  4. Spatial Decision Support Applications Based on Three-Dimensional City Models

    Institute of Scientific and Technical Information of China (English)

    LI Chaokui; ZHU Qing; ZHANG Yeting; HUANG Duo; ZHAO Jie; CHEN Songlin

    2004-01-01

    The basic mathematic models, such as the statistic model, the time-serial model, the spatial dynamic model etc., and some typical analysis methods based on 3DCM are proposed and discussed. A few typical spatial decision making methods integrating the spatial analysis and the basic mathematical models are also introduced, e.g. Visual impact assessment, dispersion of noise immissions, base station plan for wireless communication. In addition, a new idea of expectation of further applications and add-in-value service of 3DCM is promoted. As an example, the sunshine analysis is studied and some helpful conclusions are drawn.

  5. A sequential point process model and Bayesian inference for spatial point patterns with linear structures

    DEFF Research Database (Denmark)

    Møller, Jesper; Rasmussen, Jakob Gulddahl

    2012-01-01

    point’ an ‘independent cluster point’ or a ‘dependent cluster point’. The background and independent cluster points are thought to exhibit ‘complete spatial randomness’, whereas the dependent cluster points are likely to occur close to previous cluster points. We demonstrate the flexibility of the model......We introduce a flexible spatial point process model for spatial point patterns exhibiting linear structures, without incorporating a latent line process. The model is given by an underlying sequential point process model. Under this model, the points can be of one of three types: a ‘background...

  6. A Soil Moisture-Heat Based Early Establishment Model of Riparian White Alder (Alnus rhombifolia)

    Science.gov (United States)

    Jablkowski, P.; Johnson, E. A.; Martin, Y. E.

    2013-12-01

    Establishment of fluvially dispersed seeds on accreted gravel-sand bars is limited by water availability in streams. Past establishment models have used the stream/water table recession rate, and maximum root growth rate to determine the elevation limit of seedling establishment. This approach neglects the role of the saturated-unsaturated vadose zone in providing water to recently germinated seedlings, the physical processes that determine the soil moisture content, and the effect moisture deficit has on seedling root growth. This study combines a soil moisture-heat budget and a seedling root growth model that responds to soil moisture availability to find the elevation limit of establishment of white alder (Alnus rhombifolia) on vertically accreted bars along the south fork Eel River in the Angelo Coast Range Reserve, California. To establish successfully, seedling roots must maintain a connection with sufficient moisture to avoid water stress. This will depend on the elevation of the bar, the stream recession rate, the root growth rate, and the diurnal cycle of soil moisture. A one-dimensional moisture-heat budget of the top 15 centimeters of sediment was validated at two locations characterized by sand and clay-gravel textures respectively, using soil moisture and temperature measurements at 5, 10 and 15 cm, net radiation, air temperature, humidity, wind velocity and precipitation measured during spring-summer stream recession. Two patterns in soil water content were apparent: an average daily moisture decrease at each depth driven by stream/water table recession, and a diurnal pattern of isothermal liquid and vapour flux increasing soil water content in the upper 15 cm between 12:00 pm and 5:00 pm PDT. To determine seedling root growth rates, white alder seedlings were grown in growth chambers under a range of reduced matric potentials using polyethylene glycol. Root length measurements were made at 4 hour intervals and a quadratic equation was fit to the root

  7. Reciprocating and Screw Compressor semi-empirical models for establishing minimum energy performance standards

    Science.gov (United States)

    Javed, Hassan; Armstrong, Peter

    2015-08-01

    The efficiency bar for a Minimum Equipment Performance Standard (MEPS) generally aims to minimize energy consumption and life cycle cost of a given chiller type and size category serving a typical load profile. Compressor type has a significant chiller performance impact. Performance of screw and reciprocating compressors is expressed in terms of pressure ratio and speed for a given refrigerant and suction density. Isentropic efficiency for a screw compressor is strongly affected by under- and over-compression (UOC) processes. The theoretical simple physical UOC model involves a compressor-specific (but sometimes unknown) volume index parameter and the real gas properties of the refrigerant used. Isentropic efficiency is estimated by the UOC model and a bi-cubic, used to account for flow, friction and electrical losses. The unknown volume index, a smoothing parameter (to flatten the UOC model peak) and bi-cubic coefficients are identified by curve fitting to minimize an appropriate residual norm. Chiller performance maps are produced for each compressor type by selecting optimized sub-cooling and condenser fan speed options in a generic component-based chiller model. SEER is the sum of hourly load (from a typical building in the climate of interest) and specific power for the same hourly conditions. An empirical UAE cooling load model, scalable to any equipment capacity, is used to establish proposed UAE MEPS. Annual electricity use and cost, determined from SEER and annual cooling load, and chiller component cost data are used to find optimal chiller designs and perform life-cycle cost comparison between screw and reciprocating compressor-based chillers. This process may be applied to any climate/load model in order to establish optimized MEPS for any country and/or region.

  8. Individual-based lattice model for spatial spread of epidemics

    Directory of Open Access Journals (Sweden)

    Henryk Fuks

    2001-01-01

    Full Text Available We present a lattice gas cellular automaton (LGCA to study spatial and temporal dynamics of an epidemic of SIR (susceptible-infected-removed type. The automaton is fully discrete, i.e., space, time and number of individuals are discrete variables. The automaton can be applied to study spread of epidemics in both human and animal populations. We investigate effects of spatial inhomogeneities in initial distribution of infected and vaccinated populations on the dynamics of epidemic of SIR type. We discuss vaccination strategies which differ only in spatial distribution of vaccinated individuals. Also, we derive an approximate, mean-field type description of the automaton, and discuss differences between the mean-field dynamics and the results ofLGCA simulation.

  9. Sensitivity of the Baltic Sea level prediction to spatial model resolution

    Science.gov (United States)

    Kowalewski, Marek; Kowalewska-Kalkowska, Halina

    2017-09-01

    The three-dimensional hydrodynamic model of the Baltic Sea (M3D) and its new parallel version (PM3D), developed at the Institute of Oceanography, University of Gdańsk in Poland, was tested to establish a grid resolution adequate for the Baltic Sea level prediction. Four outputs of the M3D/PM3D, calculated with spatial resolution varying from 3 NM to 0.5 NM, were validated by comparing the results with hourly sea level readings collected at 9 Baltic gauges in 2010-2015. The spatial resolution of 1 NM applied to the Baltic Sea resulted in a distinct improvement of agreement between the calculated and observed distributions of data. An increase in the resolution to 0.5 NM in the southern Baltic Sea improved the model quality further, as indicated by the lowest variability, the highest correlation and the highest percentage of water level simulations within the range of ± 0.15 m difference relative to readings. The increase in horizontal resolution allowed to improve the fit between the observed water levels and those calculated by the PM3D in the cases of rapid sea level fluctuations, such as those registered in January 2012. The model performed slightly worse for stations with larger ranges of water level oscillations. As parallel calculations were used in the PM3D, the time necessary for computing the simulations was significantly reduced, which allowed to apply the high-resolution grid also to the operational version of the model.

  10. Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization.

    Directory of Open Access Journals (Sweden)

    Erick J Canales-Rodríguez

    Full Text Available Spherical deconvolution (SD methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data.

  11. Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization.

    Science.gov (United States)

    Canales-Rodríguez, Erick J; Daducci, Alessandro; Sotiropoulos, Stamatios N; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond

    2015-01-01

    Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data.

  12. Evaluating the Value of High Spatial Resolution in National Capacity Expansion Models using ReEDS

    Energy Technology Data Exchange (ETDEWEB)

    Krishnan, Venkat; Cole, Wesley

    2016-11-14

    Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERC region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.

  13. An optimized method of vessel dissection in establishment of the rat aortic transplantation model.

    Science.gov (United States)

    Luo, Ming; Qiu, Feng; Qiu, Jianxin; Liu, Yong; Fan, Yu; Guo, Yifeng

    2011-07-01

    The high demand for microsurgical skills in those without a strong microsurgery background limits the application of the rat aortic transplant model to transplantation research. In this study, we established a rat aortic transplant model using a hydrodissection technique as a minimal-touch technique in vessel dissection. Eighty male Sprague Dawley rats were randomly divided into two groups with equal numbers. In the experimental group, abdominal aortas were harvested using hydrodissection; in the control group, instrumental dissection was used. The harvested aortas were transplanted orthotopically. The mean harvesting and implanting time in the experimental group was significantly lower than that of the control group (11.8 ± 1.51 versus 23.8 ± 3.38 minutes, P Surgical complications in the control group included inferior vena cava injury (2/20), arterial vasospasm (3/20), and arterial wall hemorrhage (1/10). None of these complications were observed in the hydrodissection group. The overall frequency of surgical complications in the hydrodissection group was significantly lower than that in the control group ( P technique is a fast and safe method of vessel dissection. This technique requires less microsurgical skills and optimizes the establishment of the rat aortic transplant model. © Thieme Medical Publishers.

  14. Establishing a rat model of spastic cerebral palsy by targeted ethanol injection

    Institute of Scientific and Technical Information of China (English)

    Yadong Yu; Liang Li; Xinzhong Shao; Fangtao Tian; Qinglu Sun

    2013-01-01

    Spastic cerebral palsy is general y considered to result from cerebral cortical or pyramidal tract damage. Here, we precisely targeted the left pyramidal tract of 2-month-old Sprague-Dawley rats placed on a stereotaxic instrument under intraperitoneal anesthesia. Based on the rat brain ste-reotaxic map, a 1-mm hole was made 10 mm posterior to bregma and 0.8 mm left of sagittal suture. A microsyringe was inserted perpendicularly to the surface of the brain to a depth of 9.7 mm, and 15μL of ethanol was slowly injected to establish a rat model of spastic cerebral palsy. After modeling, the rats appeared to have necrotic voids in the pyramidal tract and exhibited typical signs and symptoms of flexion spasms that lasted for a long period of time. These findings indicate that this is an effective and easy method of establishing a rat model of spastic cerebral palsy with good re-producibility. Ethanol as a chemical ablation agent specifical y and thoroughly damages the pyra-midal tract, and therefore, the animals display flexion spasms, which are a typical symptom of the disease.

  15. 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.

  16. Spatial Distribution of the Errors in Modeling the Mid-Latitude Critical Frequencies by Different Models

    Science.gov (United States)

    Kilifarska, N. A.

    There are some models that describe the spatial distribution of greatest frequency yielding reflection from the F2 ionospheric layer (foF2). However, the distribution of the models' errors over the globe and how they depend on seasons, solar activity, etc., are unknown till this time. So the aim of the present paper is to compare the accuracy in describing the latitudinal and longitudinal variation of the mid-latitude maximum electron density, of CCIR, URSI, and a new created theoretical model. A comparison between the above mentioned models and all available from Boulder's data bank VI data (among 35 deg and 70 deg) have been made. Data for three whole years with different solar activity - 1976 (F_10.7 = 73.6), 1981 (F_10.7 = 20.6), 1983 (F_10.7 = 119.6) have been compared. The final results show that: 1. the areas with greatest and smallest errors depend on UT, season and solar activity; 2. the error distribution of CCIR and URSI models are very similar and are not coincident with these ones of theoretical model. The last result indicates that the theoretical model, described briefly bellow, may be a real alternative to the empirical CCIR and URSI models. The different spatial distribution of the models' errors gives a chance for the users to choose the most appropriate model, depending on their needs. Taking into account that the theoretical models have equal accuracy in region with many or without any ionosonde station, this result shows that our model can be used to improve the global mapping of the mid-latitude ionosphere. Moreover, if Re values of the input aeronomical parameters (neutral composition, temperatures and winds), are used - it may be expected that this theoretical model can be applied for Re or almost Re-time mapping of the main ionospheric parameters (foF2 and hmF2).

  17. Model tests to establish a design method for TLP-tether systems

    Energy Technology Data Exchange (ETDEWEB)

    Sekita, K.; Sakai, M.

    1984-05-01

    Model tests were conducted in regular and random waves with a view to establishing a design method for tension leg platform (TLP)-tether systems. Linearized and nonlinear analytical methods were used, and the calculated values were compared with measured values. The nonlinear method was used in analyzing a TLPtether system under such critical sea conditions as would cause the tethers to snatch - a situation that should be avoided in the design of TLP tethers - and under unstable conditions with all tethers at one corner of the TLP broken off. The results of these investigations are reported in this paper.

  18. 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.

  19. 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

  20. 3D reconstruction of carotid atherosclerotic plaque: comparison between spatial compound ultrasound models and anatomical models

    DEFF Research Database (Denmark)

    Lind, Bo L.; Fagertun, Jens; Wilhjelm, Jens E.;

    2007-01-01

    This study deals with the creation of 3D models that can work as a tool for discriminating between tissue and background in the development of tissue classification methods. Ten formalin-fixed atherosclerotic carotid plaques removed by endarterectomy were scanned with 3D multi-angle spatial...... compound ultrasound (US) and subsequently sliced and photographed to produce a 3D anatomical data set. Outlines in the ultrasound data were found by means of active contours and combined into 10 3D ultrasound models. The plaque regions of the anatomical photographs were outlined manually and then combined...... into 10 3D anatomical models. The volumes of the anatomical models correlated with the volume found by a water displacement method (r = 0.95), except for an offset. The models were compared in three ways. Visual inspection showed quite good agreement between the models. The volumes of the ultrasound...

  1. [Establishment of a model for evaluating hypolipidemic effect in HepG2 cells].

    Science.gov (United States)

    Niu, Yucun; Lü, Na; Li, Ying; Zhao, Dan; Sun, Changhao

    2010-03-01

    To establish a model of evaluating hypolipidemic effect in vitro. Adding cholesterol to the culture medium for HepG2 cells to induce a hypercholesterolemia model. The content of cellular cholesterol and the expression of protein regulating cholesterol metabolism in HepG2 cells were determined. The validation of the model was identified by lovastatin, a widely used cholesterol-lowering drug. Free fatty acid was added to the culture medium for HepG2 cells to induce a hypertriglyceridemia model. The content of cellular triglyceride and the absorption rate of free fatty acid were determined. The validation of the model was identified by fenofibrate, a triglyceride-lowering drug. Cellular cholesterol content was increased and the expression of HMG-CoA redutase, SREBP-2 and LDLR were decreased after adding cholesterol and 25-hydrocholesterol to the culture medium. Cellular cholesterol was decreased and the expression of SREBP-2 and LDLR were up-regulated by Lovastatin. The absorption of oleic acid in cells was up to 40% after adding oleic acid (50 micromol) to the culture medium for 6 h. The absorption of free fatty acid was increased but the content of cellular triglyceride was not increased in cells by Fenofibrate. This model might be an effective method for screening and assessing functional factors for lowing plasma lipids.

  2. Establishment of a Novel Simplified Surgical Model of Acute Liver Failure in the Cynomolgus Monkey

    Directory of Open Access Journals (Sweden)

    Lei Cai

    2016-01-01

    Full Text Available Models using large animals that are suitable for studying artificial liver support system (ALSS are urgently needed. Presently available acute liver failure (ALF models mainly involve pigs or dogs. Establishment of current surgical ALF models (hepatectomy/devascularization requires either very good surgical skills or multistep processes—even multiple stages of surgery. Therefore, it is necessary to develop a simplified surgical method. Here we report a novel simplified surgical ALF model using cynomolgus monkeys. Six monkeys underwent portal-right renal venous shunt combined with common bile duct ligation and transection (PRRS + CBDLT. Postoperatively, the monkeys had progressively increased listlessness, loss of appetite, and obvious jaundice. Blood biochemistry levels (Amm, ALT, AST, TBiL, DBiL, ALP, LDH, CK, and Cr and prothrombin time (PT were significantly increased (all P<0.01 and albumin (ALB was markedly reduced (P<0.01 compared with baseline values. Histological examination of liver specimens on postoperative day 10 revealed cholestasis and inflammation. PRRS + CBDLT produced ALF that closely correlated with clinical situations. Compared with other surgical or drug ALF models, ours was simplified and animals were hemodynamically stable. This model could provide a good platform for further research on ALSS, especially regarding their detoxification functions.

  3. A More Complete Model for TCP Connections Established between One Server and Many Receivers

    Institute of Scientific and Technical Information of China (English)

    LINYu; CHENGShiduan; WUHaitao; WANGChonggang

    2003-01-01

    Different from previous TCP (transmis-sion control program) modeling works, this paper presents a more complete analytical model of multiple TCP con-nections established between a busy server and multiple receivers under two distinct cases: the case there is suffi-cient bandwidth and the case there is a bandwidth bottle-neck link between the server and receivers. In the former case, the server will become the bottleneck of the whole system, and TCP behaviors are different from the model presented before. However, in the latter case, multiple TCP connections will share the bandwidth of the bottle-neck link. Based on the analysis of working flows in the system and a M/G/1 queueing model, the RTT and long-term TCP throughput formulae are derived in terms of number of TCPs, packet loss rate, and end-to-end delay.And the effect of maximum window size is also investi-gated. The simulation results confirm that new model is more accurate than previous model.

  4. Predicting hydrological signatures in ungauged catchments using spatial interpolation, index model, and rainfall-runoff modelling

    Science.gov (United States)

    Zhang, Yongqiang; Vaze, Jai; Chiew, Francis H. S.; Teng, Jin; Li, Ming

    2014-09-01

    Understanding a catchment's behaviours in terms of its underlying hydrological signatures is a fundamental task in surface water hydrology. It can help in water resource management, catchment classification, and prediction of runoff time series. This study investigated three approaches for predicting six hydrological signatures in southeastern Australia. These approaches were (1) spatial interpolation with three weighting schemes, (2) index model that estimates hydrological signatures using catchment characteristics, and (3) classical rainfall-runoff modelling. The six hydrological signatures fell into two categories: (1) long-term aggregated signatures - annual runoff coefficient, mean of log-transformed daily runoff, and zero flow ratio, and (2) signatures obtained from daily flow metrics - concavity index, seasonality ratio of runoff, and standard deviation of log-transformed daily flow. A total of 228 unregulated catchments were selected, with half the catchments randomly selected as gauged (or donors) for model building and the rest considered as ungauged (or receivers) to evaluate performance of the three approaches. The results showed that for two long-term aggregated signatures - the log-transformed daily runoff and runoff coefficient, the index model and rainfall-runoff modelling performed similarly, and were better than the spatial interpolation methods. For the zero flow ratio, the index model was best and the rainfall-runoff modelling performed worst. The other three signatures, derived from daily flow metrics and considered to be salient flow characteristics, were best predicted by the spatial interpolation methods of inverse distance weighting (IDW) and kriging. Comparison of flow duration curves predicted by the three approaches showed that the IDW method was best. The results found here provide guidelines for choosing the most appropriate approach for predicting hydrological behaviours at large scales.

  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. Mechanistic modeling study on process optimization and precursor utilization with atmospheric spatial atomic layer deposition

    Energy Technology Data Exchange (ETDEWEB)

    Deng, Zhang; He, Wenjie; Duan, Chenlong [State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Chen, Rong, E-mail: rongchen@mail.hust.edu.cn [State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Shan, Bin [State Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China)

    2016-01-15

    Spatial atomic layer deposition (SALD) is a promising technology with the aim of combining the advantages of excellent uniformity and conformity of temporal atomic layer deposition (ALD), and an industrial scalable and continuous process. In this manuscript, an experimental and numerical combined model of atmospheric SALD system is presented. To establish the connection between the process parameters and the growth efficiency, a quantitative model on reactant isolation, throughput, and precursor utilization is performed based on the separation gas flow rate, carrier gas flow rate, and precursor mass fraction. The simulation results based on this model show an inverse relation between the precursor usage and the carrier gas flow rate. With the constant carrier gas flow, the relationship of precursor usage and precursor mass fraction follows monotonic function. The precursor concentration, regardless of gas velocity, is the determinant factor of the minimal residual time. The narrow gap between precursor injecting heads and the substrate surface in general SALD system leads to a low Péclet number. In this situation, the gas diffusion act as a leading role in the precursor transport in the small gap rather than the convection. Fluid kinetics from the numerical model is independent of the specific structure, which is instructive for the SALD geometry design as well as its process optimization.

  7. 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.

  8. 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)

  9. Modeling Spatial Maps Inspired by the Hippocampal System

    Science.gov (United States)

    2015-08-24

    Abstract How the hippocampus encodes both spatial and nonspatial information at the cellular network level remains a largely unresolved problem...system is self-contained and provides quantitative information about the stability and speed of sequential memory retrieval in the original network ...dynamics reduction method developed here provides a concise characterization of the transient nonlinear dynamics of a class of asymmetric networks

  10. Spatial Modeling in Environmental and Public Health Research

    Directory of Open Access Journals (Sweden)

    Michael Jerrett

    2010-03-01

    Full Text Available This paper has two aims: (1 to summarize various geographic information science methods; and (2 to provide a review of studies that have employed such methods. Though not meant to be a comprehensive review, this paper explains when certain methods are useful in epidemiological studies and also serves as an overview of the growing field of spatial epidemiology.

  11. 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.

  12. Hitchhikers on trade routes: A phenology model estimates the probabilities of gypsy moth introduction and establishment.

    Science.gov (United States)

    Gray, David R

    2010-12-01

    As global trade increases so too does the probability of introduction of alien species to new locations. Estimating the probability of an alien species introduction and establishment following introduction is a necessary step in risk estimation (probability of an event times the consequences, in the currency of choice, of the event should it occur); risk estimation is a valuable tool for reducing the risk of biological invasion with limited resources. The Asian gypsy moth, Lymantria dispar (L.), is a pest species whose consequence of introduction and