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Sample records for modeling spatial establishment

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

    Directory of Open Access Journals (Sweden)

    Mark C Vanderwel

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

  2. Spatial cluster modelling

    CERN Document Server

    Lawson, Andrew B

    2002-01-01

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

  3. Establishing the isolated Standard Model

    International Nuclear Information System (INIS)

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

    2017-02-01

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

  4. Establishing the isolated standard model

    Science.gov (United States)

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

    2017-07-01

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

  5. Prenatal p,p'-DDE exposure and establishment of lateralization and spatial orientation in Mexican preschooler.

    Science.gov (United States)

    Osorio-Valencia, Erika; Torres-Sánchez, Luisa; López-Carrillo, Lizbeth; Cebrián, Mariano E; Rothenberg, Stephen J; Hernández Chávez, María del Carmen; Schnaas, Lourdes

    2015-03-01

    Prenatal exposure to p,p'-DDE is associated with impairments in motor development during the first year of life, with no related repercussions on mental or motor development at 12-30 months and with impairments in cognitive areas, but not in perceptual and motor areas at preschool age. However, its association with particular psychomotor factors, such as establishment of lateralization and spatial orientation, essential elements to the overall learning and specifically reading, writing and spelling in preschoolers, has not been independently evaluated, since cognitive and motor areas have only been explored globally. To determine the association between prenatal exposure to p,p'-DDE and the establishment of lateralization and spatial orientation in children 5 years of age. Establishment of lateralization and spatial orientation was evaluated using the McCarthy Scale of Children's Abilities, with 167 children 5 years of age who participated in a birth cohort in the state of Morelos, Mexico. The information available for each child included: serum concentrations of p,p'-DDE of the mother during at least one trimester of pregnancy, mothers' intelligence quotients, stimulation at home and anthropometry. A logistic regression model was used to calculate the association between prenatal exposure to p,p'-DDE and lateralization and a multiple linear regression model was used for the association with spatial orientation. A two-fold increase in p,p'-DDE in lipid base during the second trimester of pregnancy was associated with a significant reduction, -0.18 points (95% CI -0.41; 0.04, in the spatial orientation index, with no impairment in the establishment of hemispheric dominance. Attending preschool and the maternal intelligence quotient were the main determinants of spatial orientation and the establishment of hemispheric dominance. Prenatal exposure to p,p'-DDE may affect the 5 year old's ability to identify spatial orientation of oneself and surrounding objects. Given

  6. 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.

  7. Examining the Spatial Distribution of Marijuana Establishments in Colorado

    Science.gov (United States)

    Kerski, Joseph

    2018-01-01

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

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

    NARCIS (Netherlands)

    Stelder, T.M.

    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

  9. 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...

  10. 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).

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Spatial Uncertainty Analysis of Ecological Models

    Energy Technology Data Exchange (ETDEWEB)

    Jager, H.I.; Ashwood, T.L.; Jackson, B.L.; King, A.W.

    2000-09-02

    The authors evaluated the sensitivity of a habitat model and a source-sink population model to spatial uncertainty in landscapes with different statistical properties and for hypothetical species with different habitat requirements. Sequential indicator simulation generated alternative landscapes from a source map. Their results showed that spatial uncertainty was highest for landscapes in which suitable habitat was rare and spatially uncorrelated. Although, they were able to exert some control over the degree of spatial uncertainty by varying the sampling density drawn from the source map, intrinsic spatial properties (i.e., average frequency and degree of spatial autocorrelation) played a dominant role in determining variation among realized maps. To evaluate the ecological significance of landscape variation, they compared the variation in predictions from a simple habitat model to variation among landscapes for three species types. Spatial uncertainty in predictions of the amount of source habitat depended on both the spatial life history characteristics of the species and the statistical attributes of the synthetic landscapes. Species differences were greatest when the landscape contained a high proportion of suitable habitat. The predicted amount of source habitat was greater for edge-dependent (interior) species in landscapes with spatially uncorrelated(correlated) suitable habitat. A source-sink model demonstrated that, although variation among landscapes resulted in relatively little variation in overall population growth rate, this spatial uncertainty was sufficient in some situations, to produce qualitatively different predictions about population viability (i.e., population decline vs. increase).

  18. 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

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

    Directory of Open Access Journals (Sweden)

    Erika Cerasti

    2010-04-01

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

  20. Individual based model of slug population and spatial dynamics

    NARCIS (Netherlands)

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

    2006-01-01

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

  1. Location Aggregation of Spatial Population CTMC Models

    Directory of Open Access Journals (Sweden)

    Luca Bortolussi

    2016-10-01

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

  2. 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

  3. 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...

  4. Spatial Allocator for air quality modeling

    Science.gov (United States)

    The Spatial Allocator is a set of tools that helps users manipulate and generate data files related to emissions and air quality modeling without requiring the use of a commercial Geographic Information System.

  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. Crime Modeling using Spatial Regression Approach

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2008-06-01

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

  8. Using Spatial Gradients to Model Localization Phenomena

    Energy Technology Data Exchange (ETDEWEB)

    D.J.Bammann; D.Mosher; D.A.Hughes; N.R.Moody; P.R.Dawson

    1999-07-01

    We present the final report on a Laboratory-Directed Research and Development project, Using Spatial Gradients to Model Localization Phenomena, performed during the fiscal years 1996 through 1998. The project focused on including spatial gradients in the temporal evolution equations of the state variables that describe hardening in metal plasticity models. The motivation was to investigate the numerical aspects associated with post-bifurcation mesh dependent finite element solutions in problems involving damage or crack propagation as well as problems in which strain Localizations occur. The addition of the spatial gradients introduces a mathematical length scale that eliminates the mesh dependency of the solution. In addition, new experimental techniques were developed to identify the physical mechanism associated with the numerical length scale.

  9. Landscape Modelling and Simulation Using Spatial Data

    Directory of Open Access Journals (Sweden)

    Amjed Naser Mohsin AL-Hameedawi

    2017-08-01

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

  10. Spatial Model of Deforestation in Kalimantan from 2000 to 2013

    OpenAIRE

    Judin Purwanto; Teddy Rusolono; Lilik Budi Prasetyo

    2015-01-01

    Forestry sector is the biggest carbon emission contributor in Indonesia which is mainly caused by deforestation. A significant area of forest cover still can be found in Kalimantan Island (one of the largest island in Indonesia) although an alarming rates deforestation is also exist. This study was purposed to established spatial model of deforestation in Kalimantan islands. This information is expected to provide options to develop sustainable forest management in Kalimantan trou...

  11. Spatial Modeling for Resources Framework (SMRF)

    Science.gov (United States)

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

  12. Testing spatial heterogeneity with stock assessment models

    DEFF Research Database (Denmark)

    Jardim, Ernesto; Eero, Margit; Silva, Alexandra

    2018-01-01

    This paper describes a methodology that combines meta-population theory and stock assessment models to gain insights about spatial heterogeneity of the meta-population in an operational time frame. The methodology was tested with stochastic simulations for different degrees of connectivity betwee...

  13. 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...

  14. 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...... 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...

  15. 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.

  16. 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...

  17. 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.

  18. A Spatially Extended Model for Residential Segregation

    Directory of Open Access Journals (Sweden)

    Antonio Aguilera

    2007-01-01

    Full Text Available We analyze urban spatial segregation phenomenon in terms of the income distribution over a population, and an inflationary parameter weighting the evolution of housing prices. For this, we develop a discrete spatially extended model based on a multiagent approach. In our model, the mobility of socioeconomic agents is driven only by the housing prices. Agents exchange location in order to fit their status to the cost of their housing. On the other hand, the price of a particular house depends on the status of its tenant, and on the neighborhood mean lodging cost weighted by a control parameter. The agent's dynamics converges to a spatially organized configuration, whose regularity is measured by using an entropy-like indicator. This simple model provides a dynamical process organizing the virtual city, in a way that the population inequality and the inflationary parameter determine the degree of residential segregation in the final stage of the process, in agreement with the segregation-inequality thesis put forward by Douglas Massey.

  19. Establishment of modified reversible regional cerebral ischemic models

    International Nuclear Information System (INIS)

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

    2005-01-01

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

  20. Spatially explicit non-Mendelian diploid model

    OpenAIRE

    Lanchier, N.; Neuhauser, C.

    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 comp...

  1. A Mathematical Approach to Establishing Constitutive Models for Geomaterials

    Directory of Open Access Journals (Sweden)

    Guang-hua Yang

    2013-01-01

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

  2. 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.

  3. Modeling mental spatial reasoning about cardinal directions.

    Science.gov (United States)

    Schultheis, Holger; Bertel, Sven; Barkowsky, Thomas

    2014-01-01

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

  4. 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.

  5. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    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......When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number...... of different factors influence the time development of the system. This often makes it challenging to construct a mathematical model from which to draw conclusions. One traditional way of capturing the dynamics in a mathematical model is to formulate a set of coupled differential equations for the essential...

  6. 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.

  7. Spherical Process Models for Global Spatial Statistics

    KAUST Repository

    Jeong, Jaehong

    2017-11-28

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

  8. 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.

  9. Spatial Simulation of the Dynamics of Establishment of Secondary Forest in Abandoned Pasture in the Central Amazon

    Science.gov (United States)

    Rebel, K. T.; Riha, S. J.; Rondon, M. A.; Feldpausch, T. R.; Fernandes, E. C.

    2001-05-01

    In the Amazon, approximately 35 million hectares of primary forest that was converted to pasture is now being abandoned. This represents about 70% of all pastureland that was previously established. The dynamics of reconversion of this land to secondary forest is of interest because the length of time required for pasture to convert to secondary forest will impact net primary productivity and the amount of carbon being stored on abandoned pastures. In addition, the length of time required for pasture to convert to secondary forest may depend on the size of the pasture, whether it is surrounded by primary or secondary forest, and on pasture productivity at the time of abandonment. Pasture productivity at the time of abandonment will depend primarily on the age structure of the pasture grasses and on weediness, which are influenced by grazing and fire history. Also, an understanding of the dynamics of conversion of pastureland to forest can serve as the basis for management strategies to inhibit pasture conversion. A spatial, dynamic model of the conversion of pasture to secondary forest was developed using the PCRaster Dynamic Modeling Package. This software provides a computer language specially developed for modeling temporal and spatial processes in a GIS, and is well suited for the development of ecological, dynamic models. The model of pasture conversion is implemented for the central Amazon. We assume that succession involves only three plant types: pasture grass, weeds and woody plants. The pasture grass is parameterized for Brachiaria (brizantha, humidicola), the weeds for Borreria and Rolandra, and the woody plants for Vismia spp. The model uses a 1m x 1m grid and 2-month time step. Each initial plant and each surviving propagule is referred to as a plant and only occupies one grid cell. A number of values are calculated for each grid cell for each time-step. These include whether vegetation is present and, if so, which species, the age of the species, the

  10. A strategy to establish Food Safety Model Repositories.

    Science.gov (United States)

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

    2015-07-02

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

  11. 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.

  12. 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...

  13. 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

  14. Models and Inference for Multivariate Spatial Extremes

    KAUST Repository

    Vettori, Sabrina

    2017-12-07

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

  15. 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.

  16. Modeling strategic investment decisions in spatial markets

    International Nuclear Information System (INIS)

    Lorenczik, Stefan; Malischek, Raimund

    2014-01-01

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

  17. The Role of Visuo-Spatial Abilities in Recall of Spatial Descriptions: A Mediation Model

    Science.gov (United States)

    Meneghetti, Chiara; De Beni, Rossana; Pazzaglia, Francesca; Gyselinck, Valerie

    2011-01-01

    This research investigates how visuo-spatial abilities (such as mental rotation--MR--and visuo-spatial working memory--VSWM--) work together to influence the recall of environmental descriptions. We tested a mediation model in which VSWM was assumed to mediate the relationship between MR and spatial text recall. First, 120 participants were…

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

    Science.gov (United States)

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

    2015-01-01

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

  19. Spatial models of Northern Bobwhite populations for conservation planning

    Science.gov (United States)

    Twedt, Daniel J.; Wilson, R. Randy; Keister, Amy S.

    2007-01-01

    Since 1980, northern bobwhite (Colinus virginianus) range-wide populations declined 3.9% annually. Within the West Gulf Coastal Plain Bird Conservation Region in the south-central United States, populations of this quail species have declined 6.8% annually. These declines sparked calls for land use change and prompted implementation of various conservation practices. However, to effectively reverse these declines and restore northern bobwhite to their former population levels, habitat conservation and management efforts must target establishment and maintenance of sustainable populations. To provide guidance for conservation and restoration of habitat capable of supporting sustainable northern bobwhite populations in the West Gulf Coastal Plain, we modeled their spatial distribution using landscape characteristics derived from 1992 National Land Cover Data and bird detections, from 1990 to 1994, along 10-stop Breeding Bird Survey route segments. Four landscape metrics influenced detections of northern bobwhite: detections were greater in areas with more grassland and increased aggregation of agricultural lands, but detections were reduced in areas with increased density of land cover edge and grassland edge. Using these landscape metrics, we projected the abundance and spatial distribution of northern bobwhite populations across the entire West Gulf Coastal Plain. Predicted populations closely approximated abundance estimates from a different cadre of concurrently collected data but model predictions did not accurately reflect bobwhite detections along species-specific call-count routes in Arkansas and Louisiana. Using similar methods, we also projected northern bobwhite population distribution circa 1980 based on Land Use Land Cover data and bird survey data from 1976 to 1984. We compared our 1980 spatial projections with our spatial estimate of 1992 populations to identify areas of population change. Additionally, we used our projection of the spatial

  20. Spatial Situation Models and Text Comprehension.

    Science.gov (United States)

    Haenggi, Dieter; And Others

    1995-01-01

    Reports findings from three experiments designed to show how readers inferred spatial information relevant to a story character's movements through a previously memorized layout of a fictional building. Examines how inference measures are related to spatial imagery. (HB)

  1. 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...

  2. Spectral Modelling for Spatial Network Analysis

    NARCIS (Netherlands)

    Nourian, P.; Rezvani, S.; Sariyildiz, I.S.; van der Hoeven, F.D.; Attar, Ramtin; Chronis, Angelos; Hanna, Sean; Turrin, Michela

    2016-01-01

    Spatial Networks represent the connectivity structure between units of space as a weighted graph whose links are weighted as to the strength of connections. In case of urban spatial networks, the units of space correspond closely to streets and in architectural spatial networks the units correspond

  3. 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

  4. Reducing Spatial Data Complexity for Classification Models

    International Nuclear Information System (INIS)

    Ruta, Dymitr; Gabrys, Bogdan

    2007-01-01

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

  5. Establishment of a cerebral schistosomiasis experimental model in rabbits.

    Science.gov (United States)

    Wang, Peng; Wang, Dan; Chen, Shi-Jie; Wu, Ming-Can; Cheng, Xiang-Lin; Li, Jun-Chuan; Chen, Ting-Xuan; Zhu, Zhan-Sheng

    2011-04-01

    The present study aimed to establish a cerebral schistosomiasis model in rabbits, to provide a valuable tool for morphological analysis, clinical manifestation observation, as well as investigations into immunological reactions and pathogenesis of focal inflammatory reaction in neuroschistosomiasis (NS). Sixty New Zealand rabbits were randomly assigned into operation, sham-operation and normal groups. Rabbits in the operation group received direct injection of dead schistosome eggs into the brain, while their counterparts in the sham-operation group received saline injection. Rabbits in the normal group received no treatment. Base on the clinical manifestations, rabbits were sacrificed on days 3, 5, 7, 10, 20, and 30 post injection, and brain samples were sectioned and stained with hematoxylin-eosin. Sections were observed under the microscope. The rabbits in the operation group exhibited various neurological symptoms, including anorexy, partial and general seizures, and paralysis. The morphological analysis showed several schistosome eggs in the nervous tissue on day 3 post operation, with very mild inflammation. On days 7-10 post operation, several schistosome eggs were localized in proximity to red blood cells with many neutrophilic granulocytes and eosinophilic granulocytes around them. The schistosome eggs developed into the productive granuloma stage on days 14-20 post operation. On day 30, the schistosome eggs were found to be in the healing-by-fibrosis stage, and the granuloma area was replaced by fibrillary glia through astrocytosis. The sham-operation group and the normal group showed negative results. This method might be used to establish the cerebral schistosomiasis experimental model. Several factors need to be considered in establishing this model, such as the antigenic property of eggs, the time of scarification, and the clinical manifestations.

  6. Spatial regression-based model specifications for exogenous and endogenous spatial interaction

    OpenAIRE

    Manfred M Fischer; James P. LeSage

    2014-01-01

    Spatial interaction models represent a class of models that are used for modelling origin-destination flow data. The focus of this paper is on the log-normal version of the model. In this context, we consider spatial econometric specifications that can be used to accommodate two types of dependence scenarios, one involving endogenous interaction and the other exogenous interaction. These model specifications replace the conventional assumption of independence between origin-destination flows ...

  7. Panchromatic SED modelling of spatially resolved galaxies

    Science.gov (United States)

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

    2018-05-01

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

  8. Establishing a business process reference model for Universities

    DEFF Research Database (Denmark)

    Svensson, Carsten; Hvolby, Hans-Henrik

    2012-01-01

    Modern universities are by any standard complex organizations that, from an IT perspective, present a number of unique challenges. This paper will propose establishing a business process reference framework. The benefit to the users would be a better understanding of the system landscape, business...... 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....

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. A modeling framework for the establishment and spread of invasive species in heterogeneous environments.

    Science.gov (United States)

    Lustig, Audrey; Worner, Susan P; Pitt, Joel P W; Doscher, Crile; Stouffer, Daniel B; Senay, Senait D

    2017-10-01

    Natural and human-induced events are continuously altering the structure of our landscapes and as a result impacting the spatial relationships between individual landscape elements and the species living in the area. Yet, only recently has the influence of the surrounding landscape on invasive species spread started to be considered. The scientific community increasingly recognizes the need for broader modeling framework that focuses on cross-study comparisons at different spatiotemporal scales. Using two illustrative examples, we introduce a general modeling framework that allows for a systematic investigation of the effect of habitat change on invasive species establishment and spread. The essential parts of the framework are (i) a mechanistic spatially explicit model (a modular dispersal framework-MDIG) that allows population dynamics and dispersal to be modeled in a geographical information system (GIS), (ii) a landscape generator that allows replicated landscape patterns with partially controllable spatial properties to be generated, and (iii) landscape metrics that depict the essential aspects of landscape with which dispersal and demographic processes interact. The modeling framework provides functionality for a wide variety of applications ranging from predictions of the spatiotemporal spread of real species and comparison of potential management strategies, to theoretical investigation of the effect of habitat change on population dynamics. Such a framework allows to quantify how small-grain landscape characteristics, such as habitat size and habitat connectivity, interact with life-history traits to determine the dynamics of invasive species spread in fragmented landscape. As such, it will give deeper insights into species traits and landscape features that lead to establishment and spread success and may be key to preventing new incursions and the development of efficient monitoring, surveillance, control or eradication programs.

  14. 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

  15. The practicalities of establishing a porcine isolated heart model.

    Science.gov (United States)

    Pavey, Warren; Raisis, Anthea; Dunne, Ben; Van Laeken, Els; Jenkinson, Charles; Vincent, Viji; Baird, Peter; Prince, Stuart; Ho, Kwok M; Merry, Christopher; Gilfillan, Ian

    2017-12-01

    The isolated heart apparatus is over 100 years old, but remains a useful research tool today. While designs of many large animal systems have been described in the literature, trouble-shooting and refining such a model to yield a stable, workable system has not been previously described. This paper outlines the issues, in tabular form, that our group encountered in developing our own porcine isolated heart rig with the aim of assisting other workers in the field planning similar work. The paper also highlights some of the modern applications of the isolated heart apparatus. Methods Landrace pigs (50-80 kg) were used in a pilot project to develop the model. The model was then used in a study examining the effects of various cardioplegic solutions on function after reanimation of porcine hearts. During the two projects, non-protocol issues were documented as well as their solutions. These were aggregated in this paper. Issues faced by the group without explicit literature solutions included pig size selection, animal acclimatisation, porcine transoesophageal echocardiography, cannulation and phlebotomy for cross-clamping, cardioplegia delivery, heart suspension and rig tuning. Prior recognition of issues and possible solutions faced by workers establishing a porcine isolated heart system will speed progress towards a useable system for research. The isolated heart apparatus remains applicable in transplant, ischaemia reperfusion, heart failure and organ preservation research.

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  17. Modeling spatial variation in avian survival and residency probabilities

    Science.gov (United States)

    Saracco, James F.; Royle, J. Andrew; DeSante, David F.; Gardner, Beth

    2010-01-01

    The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.

  18. Spatial data modelling and maximum entropy theory

    Czech Academy of Sciences Publication Activity Database

    Klimešová, Dana; Ocelíková, E.

    2005-01-01

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

  19. Adaptive Gaussian Predictive Process Models for Large Spatial Datasets

    Science.gov (United States)

    Guhaniyogi, Rajarshi; Finley, Andrew O.; Banerjee, Sudipto; Gelfand, Alan E.

    2011-01-01

    Large point referenced datasets occur frequently in the environmental and natural sciences. Use of Bayesian hierarchical spatial models for analyzing these datasets is undermined by onerous computational burdens associated with parameter estimation. Low-rank spatial process models attempt to resolve this problem by projecting spatial effects to a lower-dimensional subspace. This subspace is determined by a judicious choice of “knots” or locations that are fixed a priori. One such representation yields a class of predictive process models (e.g., Banerjee et al., 2008) for spatial and spatial-temporal data. Our contribution here expands upon predictive process models with fixed knots to models that accommodate stochastic modeling of the knots. We view the knots as emerging from a point pattern and investigate how such adaptive specifications can yield more flexible hierarchical frameworks that lead to automated knot selection and substantial computational benefits. PMID:22298952

  20. Topological models and frameworks for 3D spatial objects

    Science.gov (United States)

    Zlatanova, Siyka; Rahman, Alias Abdul; Shi, Wenzhong

    2004-05-01

    Topology is one of the mechanisms to describe relationships between spatial objects. Thus, it is the basis for many spatial operations. Models utilizing the topological properties of spatial objects are usually called topological models, and are considered by many researchers as the best suited for complex spatial analysis (i.e., the shortest path search). A number of topological models for two-dimensional and 2.5D spatial objects have been implemented (or are under consideration) by GIS and DBMS vendors. However, when we move to one more dimension (i.e., three-dimensions), the complexity of the relationships increases, and this requires new approaches, rules and representations. This paper aims to give an overview of the 3D topological models presented in the literature, and to discuss generic issues related to 3D modeling. The paper also considers models in object-oriented (OO) environments. Finally, future trends for research and development in this area are highlighted.

  1. Uncertainties in spatially aggregated predictions from a logistic regression model

    NARCIS (Netherlands)

    Horssen, P.W. van; Pebesma, E.J.; Schot, P.P.

    2002-01-01

    This paper presents a method to assess the uncertainty of an ecological spatial prediction model which is based on logistic regression models, using data from the interpolation of explanatory predictor variables. The spatial predictions are presented as approximate 95% prediction intervals. The

  2. Practical likelihood analysis for spatial generalized linear mixed models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Ribeiro, Paulo Justiniano

    2016-01-01

    , respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...

  3. The imagine of establishing China nuclear insurance model

    International Nuclear Information System (INIS)

    Wu Yimin

    2010-01-01

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

  4. Spatial and Temporal Low-Dimensional Models for Fluid Flow

    Science.gov (United States)

    Kalb, Virginia

    2008-01-01

    A document discusses work that obtains a low-dimensional model that captures both temporal and spatial flow by constructing spatial and temporal four-mode models for two classic flow problems. The models are based on the proper orthogonal decomposition at two reference Reynolds numbers. Model predictions are made at an intermediate Reynolds number and compared with direct numerical simulation results at the new Reynolds number.

  5. Spatial modeling of potential woody biomass flow

    Science.gov (United States)

    Woodam Chung; Nathaniel Anderson

    2012-01-01

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

  6. 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.

  7. Infection dynamics on spatial small-world network models

    Science.gov (United States)

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

    2017-11-01

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

  8. 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.

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

    International Nuclear Information System (INIS)

    Zhang, Kate Fang; Zhao Xiaoqiang

    2008-01-01

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

  10. 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.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Chengcheng Xu

    2017-08-01

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

  13. 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...

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

    Science.gov (United States)

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

    2017-11-01

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

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

    Science.gov (United States)

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

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

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun

    2006-01-01

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

  17. Applications of spatial statistical network models to stream data

    Science.gov (United States)

    Isaak, Daniel J.; Peterson, Erin E.; Ver Hoef, Jay M.; Wenger, Seth J.; Falke, Jeffrey A.; Torgersen, Christian E.; Sowder, Colin; Steel, E. Ashley; Fortin, Marie-Josée; Jordan, Chris E.; Ruesch, Aaron S.; Som, Nicholas; Monestiez, Pascal

    2014-01-01

    Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., nonindependence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.

  18. Bayesian disease mapping: hierarchical modeling in spatial epidemiology

    National Research Council Canada - National Science Library

    Lawson, Andrew

    2013-01-01

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

  19. Bayesian disease mapping: hierarchical modeling in spatial epidemiology

    National Research Council Canada - National Science Library

    Lawson, Andrew

    2013-01-01

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

  20. Network Formation Models With Costs for Establishing Links

    NARCIS (Netherlands)

    Slikker, M.; van den Nouweland, C.G.A.M.

    1999-01-01

    In this paper we study endogenous formation of communication networks in situations where the economic possibilities of groups of players can be described by a cooperative game. We concentrate on the in uence that the existence of costs for establishing communication links has on the communication

  1. A latent parameter node-centric model for spatial networks.

    Directory of Open Access Journals (Sweden)

    Nicholas D Larusso

    Full Text Available Spatial networks, in which nodes and edges are embedded in space, play a vital role in the study of complex systems. For example, many social networks attach geo-location information to each user, allowing the study of not only topological interactions between users, but spatial interactions as well. The defining property of spatial networks is that edge distances are associated with a cost, which may subtly influence the topology of the network. However, the cost function over distance is rarely known, thus developing a model of connections in spatial networks is a difficult task. In this paper, we introduce a novel model for capturing the interaction between spatial effects and network structure. Our approach represents a unique combination of ideas from latent variable statistical models and spatial network modeling. In contrast to previous work, we view the ability to form long/short-distance connections to be dependent on the individual nodes involved. For example, a node's specific surroundings (e.g. network structure and node density may make it more likely to form a long distance link than other nodes with the same degree. To capture this information, we attach a latent variable to each node which represents a node's spatial reach. These variables are inferred from the network structure using a Markov Chain Monte Carlo algorithm. We experimentally evaluate our proposed model on 4 different types of real-world spatial networks (e.g. transportation, biological, infrastructure, and social. We apply our model to the task of link prediction and achieve up to a 35% improvement over previous approaches in terms of the area under the ROC curve. Additionally, we show that our model is particularly helpful for predicting links between nodes with low degrees. In these cases, we see much larger improvements over previous models.

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

    Science.gov (United States)

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

    2014-10-01

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

  3. From spatial ecology to spatial epidemiology: modeling spatial distributions of different cancer types with principal coordinates of neighbor matrices.

    Science.gov (United States)

    Voutilainen, Ari; Tolppanen, Anna-Maija; Vehviläinen-Julkunen, Katri; Sherwood, Paula R

    2014-01-01

    Epidemiology and ecology share many fundamental research questions. Here we describe how principal coordinates of neighbor matrices (PCNM), a method from spatial ecology, can be applied to spatial epidemiology. PCNM is based on geographical distances among sites and can be applied to any set of sites providing a good coverage of a study area. In the present study, PCNM eigenvectors corresponding to positive autocorrelation were used as explanatory variables in linear regressions to model incidences of eight most common cancer types in Finnish municipalities (n = 320). The dataset was provided by the Finnish Cancer Registry and it included altogether 615,839 cases between 1953 and 2010. PCNM resulted in 165 vectors with a positive eigenvalue. The first PCNM vector corresponded to the wavelength of hundreds of kilometers as it contrasted two main subareas so that municipalities located in southwestern Finland had the highest positive site scores and those located in midwestern Finland had the highest negative scores in that vector. Correspondingly, the 165(th) PCNM vector indicated variation mainly between the two small municipalities located in South Finland. The vectors explained 13 - 58% of the spatial variation in cancer incidences. The number of outliers having standardized residual > |3| was very low, one to six per model, and even lower, zero to two per model, according to Chauvenet's criterion. The spatial variation of prostate cancer was best captured (adjusted r (2) = 0.579). PCNM can act as a complementary method to causal modeling to achieve a better understanding of the spatial structure of both the response and explanatory variables, and to assess the spatial importance of unmeasured explanatory factors. PCNM vectors can be used as proxies for demographics and causative agents to deal with autocorrelation, multicollinearity, and confounding variables. PCNM may help to extend spatial epidemiology to areas with limited availability of

  4. 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.

  5. Spatial Modeling Tools for Cell Biology

    Science.gov (United States)

    2006-10-01

    of the cells total volume. The cytosol contains thousands of enzymes that are responsible for the catalyzation of glycolysis and gluconeogenesis ... dog , swine and pig models [Pantely, 1990, 1991; Stanley 1992]. In these studies, blood flow through the left anterior descending (LAD) coronary...perfusion. In conclusion, even thought our model falls within the (rather large) error bounds of experimental dog , pig and swine models, the

  6. Spatial modelling with R-INLA: A review

    KAUST Repository

    Bakka, Haakon

    2018-02-18

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

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

    Science.gov (United States)

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

    2015-03-01

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

  8. Spatial emission modelling for residential wood combustion in Denmark

    DEFF Research Database (Denmark)

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

    2016-01-01

    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...

  9. 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

  10. Was Thebes Necessary? Contingency in Spatial Modelling

    OpenAIRE

    Evans, Tim S.; Rivers, Ray J.

    2016-01-01

    When data are poor, we resort to theory modeling. 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 article, this involves choosing not only input parameter values such as site separations but also input functions that characterizes the ease of travel between sites. Although the generic behavior of the model i...

  11. 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....

  12. Establishment and characterization of a reconstructed Chinese human epidermis model.

    Science.gov (United States)

    Qiu, J; Zhong, L; Zhou, M; Chen, D; Huang, X; Chen, J; Chen, M; Ni, H; Cai, Z

    2016-02-01

    In vitro reconstructed human epidermis is a powerful tool for both basic research and industrial applications in dermatology, pharmacology and the cosmetic field. By growing keratinocytes of Chinese origin on a collagen matrix after a submerged culture followed by an air-liquid interface culture, an in vitro reconstructed Chinese human epidermis model was obtained. This Chinese epidermis model was further characterized. The reconstructed human epidermis model (China EpiSkin model) exhibits morphological features similar to native skin and shows similar expression profile of proliferation (Ki67) and differentiation (K14 and K10 cytokeratins, filaggrin) markers. Corneodesmosomes, lamellar lipids, desmosomes, keratohyalin granules, keratin filaments and membrane-coating granules are also observed at the ultrastructure level. Moreover, China EpiSkin model contains most of the major lipid classes normally found in the native skin and potentially could present the properties of skin barrier. More importantly, the model production achieves high reproducibility and low intra- and inter-batch variations. This is the first reconstructed Chinese human epidermis model reported to meet the high quality standard with industrialized production criteria. This China EpiSkin model can be used for both skin research and safety assessment in vitro. © 2015 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

  13. Sensor placement for calibration of spatially varying model parameters

    Science.gov (United States)

    Nath, Paromita; Hu, Zhen; Mahadevan, Sankaran

    2017-08-01

    This paper presents a sensor placement optimization framework for the calibration of spatially varying model parameters. To account for the randomness of the calibration parameters over space and across specimens, the spatially varying parameter is represented as a random field. Based on this representation, Bayesian calibration of spatially varying parameter is investigated. To reduce the required computational effort during Bayesian calibration, the original computer simulation model is substituted with Kriging surrogate models based on the singular value decomposition (SVD) of the model response and the Karhunen-Loeve expansion (KLE) of the spatially varying parameters. A sensor placement optimization problem is then formulated based on the Bayesian calibration to maximize the expected information gain measured by the expected Kullback-Leibler (K-L) divergence. The optimization problem needs to evaluate the expected K-L divergence repeatedly which requires repeated calibration of the spatially varying parameter, and this significantly increases the computational effort of solving the optimization problem. To overcome this challenge, an approximation for the posterior distribution is employed within the optimization problem to facilitate the identification of the optimal sensor locations using the simulated annealing algorithm. A heat transfer problem with spatially varying thermal conductivity is used to demonstrate the effectiveness of the proposed method.

  14. Empirical spatial econometric modelling of small scale neighbourhood

    Science.gov (United States)

    Gerkman, Linda

    2012-07-01

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

  15. An Evolutionary Model of Spatial Competition

    DEFF Research Database (Denmark)

    Knudsen, Thorbjørn; Winter, Sidney G.

    to environmental change.  Formally, the model builds on the NK framework for organizational analysis, with firm policy choices and environmental conditions represented by segments of a string of N bits; it joins this structure to an abstract representation of space based on the idea of a cellular automaton......  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......" - sometimes close-by existing activity, but often not. The model representation reflects the fact that the physical space in which economic activity takes place is far from homogeneous. The firm then confronts both the challenge of replicating its routines and the hazard that existing routines may not work...

  16. On spatial mutation-selection models

    Energy Technology Data Exchange (ETDEWEB)

    Kondratiev, Yuri, E-mail: kondrat@math.uni-bielefeld.de [Fakultät für Mathematik, Universität Bielefeld, Postfach 100131, 33501 Bielefeld (Germany); Kutoviy, Oleksandr, E-mail: kutoviy@math.uni-bielefeld.de, E-mail: kutovyi@mit.edu [Fakultät für Mathematik, Universität Bielefeld, Postfach 100131, 33501 Bielefeld (Germany); Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Minlos, Robert, E-mail: minl@iitp.ru; Pirogov, Sergey, E-mail: pirogov@proc.ru [IITP, RAS, Bolshoi Karetnyi 19, Moscow (Russian Federation)

    2013-11-15

    We discuss the selection procedure in the framework of mutation models. We study the regulation for stochastically developing systems based on a transformation of the initial Markov process which includes a cost functional. The transformation of initial Markov process by cost functional has an analytic realization in terms of a Kimura-Maruyama type equation for the time evolution of states or in terms of the corresponding Feynman-Kac formula on the path space. The state evolution of the system including the limiting behavior is studied for two types of mutation-selection models.

  17. 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.

  18. Properties of spatial Cox process models

    DEFF Research Database (Denmark)

    Møller, Jesper

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

  19. Modelling spatial density using continuous wavelet transforms

    Indian Academy of Sciences (India)

    Space debris; wavelets; Mexican hat; Laplace distribution; random search; parameter estimation. ... Author Affiliations. D Sudheer Reddy1 N Gopal Reddy2 A K Anilkumar3. Digital Mapping and Modelling Division, Advanced Data Processing Research Institute, Secunderabad 500 009, India; Department of Mathematics, ...

  20. Modelling spatial density using continuous wavelet transforms

    Indian Academy of Sciences (India)

    A K ANILKUMAR3. 1Digital Mapping and Modelling Division, Advanced Data Processing Research .... probability of conjunction is very high and the miss distance between active satellite and debri object is less ... particularly helpful in tackling problems involving signal identification and detection of hidden transients (hard ...

  1. A random spatial network model based on elementary postulates

    Science.gov (United States)

    Karlinger, Michael R.; Troutman, Brent M.

    1989-01-01

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

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

    Science.gov (United States)

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

    2017-09-11

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

  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. A Unified 3D Spatial Data Model for Surface and Subsurface Spatial ...

    African Journals Online (AJOL)

    A simulation of the above, on and below 3D spatial models for man-made constructions at differ-ent LoDs is presented. A simulation of this with regards to mining and cadastre is also presented. The model presented can be adopted in realising 3D GIS for mining and 3D cadastre can be realised in Ghana. Further work is ...

  5. Stochastic Dynamics on Hypergraphs and the Spatial Majority Rule Model

    Science.gov (United States)

    Lanchier, N.; Neufer, J.

    2013-04-01

    This article starts by introducing a new theoretical framework to model spatial systems which is obtained from the framework of interacting particle systems by replacing the traditional graphical structure that defines the network of interactions with a structure of hypergraph. This new perspective is more appropriate to define stochastic spatial processes in which large blocks of vertices may flip simultaneously, which is then applied to define a spatial version of the Galam's majority rule model. In our spatial model, each vertex of the lattice has one of two possible competing opinions, say opinion 0 and opinion 1, as in the popular voter model. Hyperedges are updated at rate one, which results in all the vertices in the hyperedge changing simultaneously their opinion to the majority opinion of the hyperedge. In the case of a tie in hyperedges with even size, a bias is introduced in favor of type 1, which is motivated by the principle of social inertia. Our analytical results along with simulations and heuristic arguments suggest that, in any spatial dimensions and when the set of hyperedges consists of the collection of all n×⋯× n blocks of the lattice, opinion 1 wins when n is even while the system clusters when n is odd, which contrasts with results about the voter model in high dimensions for which opinions coexist. This is fully proved in one dimension while the rest of our analysis focuses on the cases when n=2 and n=3 in two dimensions.

  6. Appropriatie spatial scales to achieve model output uncertainty goals

    NARCIS (Netherlands)

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

    2008-01-01

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

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

    NARCIS (Netherlands)

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

    2018-01-01

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

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

    NARCIS (Netherlands)

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

    2018-01-01

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

  9. A Model for Establishing an Astronomy Education Discussion Group

    Science.gov (United States)

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

    2010-01-01

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

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

    Science.gov (United States)

    Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe

    2010-04-01

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

  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. 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.

  13. 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.

  14. 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.

  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. 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

  17. 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.

  18. Toward micro-scale spatial modeling of gentrification

    Science.gov (United States)

    O'Sullivan, David

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

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

    Science.gov (United States)

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

    2009-05-01

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

  20. 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.

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

    DEFF Research Database (Denmark)

    Plejdrup, Marlene Schmidt; Gyldenkærne, Steen

    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......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...

  2. 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.

  3. 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.

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

    Science.gov (United States)

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

    2011-01-01

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

  5. 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.

  6. Gaussian Process Regression Model in Spatial Logistic Regression

    Science.gov (United States)

    Sofro, A.; Oktaviarina, A.

    2018-01-01

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

  7. Human papillomaviruses and carcinogenesis: well-established and novel models.

    Science.gov (United States)

    Viarisio, Daniele; Gissmann, Lutz; Tommasino, Massimo

    2017-10-01

    Human papillomaviruses (HPVs) infect the cutaneous or mucosal epithelia and are classified phylogenetically as genera and species. Persistent infections by the mucosal high-risk (HR) HPV types from genus alpha are associated with cancer development of the genital and upper respiratory tracts. The products of two early genes, E6 and E7, are the major HR HPV oncoproteins, being essential in all steps of the carcinogenic process. Cutaneous beta HPV types are proposed, together with ultraviolet (UV) radiation, to promote non-melanoma skin cancer development. However, in contrast to the HR HPV types, beta HPV types appear to be required only at an early stage of carcinogenesis, facilitating the accumulation of UV-induced DNA mutations. Although findings in experimental models also suggest that beta HPV types and other carcinogens may synergize in the induction of malignancies, these possibilities need to be confirmed in human studies. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Establishment of a porcine model of patent foramen ovale

    International Nuclear Information System (INIS)

    Jiang Weijian; Xiao Xiangsheng

    2007-01-01

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

  9. Establishment of a porcine model of patent foramen ovale.

    Science.gov (United States)

    Jiang, Wei-jian; Ma, Ning; Xu, Xiao-Tong; Xiao, Xiang-Sheng

    2006-01-01

    To investigate the feasibility of developing an animal model of patent foramen ovale (PFO) in piglets by percutaneous atrial septal puncture and balloon dilation. A standardized percutaneous atrial trans-septal puncture and balloon dilation was conducted in 11 healthy piglets under general anesthesia. A Rups-100 system inserted through a femoral vein was used for the transseptal puncture, and subsequent balloon dilatation was performed at the puncture site to imitate a PFO. Euthanasia and autopsy were performed on day 1 in one piglet (early autopsy), and on day 21 in the remaining ten piglets (late autopsy). Artificial PFO was successfully created in all piglets and verified by fluoroscopy. No major technical difficulty or complication was encountered except in one which developed mild hemopericardium. In the piglet that had early autopsy, the artificial foramen was measured 0.8 x 0.7 cm(2) in cross-section and aggregates of erythrocytes were revealed over its rim under light microscopy. In the late autopsy group (n=10), seven piglets had the created foramens healed and sealed off, while the other three showed relatively small residual lumens measured 0.1 x 0.2 cm(2), 0.2 x 0.2 cm(2) and 0.1 x 0.3 cm(2) in cross-section, respectively. Histological examination of specimens from the late autopsy group showed variable neointima hyperplasia, cardiac muscle necrosis and focal fibrosis at the puncture site, regardless of the course of healing. Artificial creation of PFO in piglets is feasible by percutaneous atrial septal puncture and balloon dilation. This protocol may serve as a research model for PFO-related stroke in human.

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

    International Nuclear Information System (INIS)

    Loibl, W.; Orthofer, R.

    2002-02-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

  12. Spatial and Temporal Clustering in a Simple Earthquake Asperity Model

    Science.gov (United States)

    Tiampo, K. F.; Kazemian, J.; Dominguez, R.; Klein, W.

    2016-12-01

    Natural earthquake fault systems are highly heterogeneous in space, the result of inhomogeneities that are a function of the variety of materials of different strengths. However, despite their inhomogeneous nature, real faults are often modeled as spatially homogeneous systems. Here we present a simple earthquake fault model based on the Olami-Feder-Christensen (OFC) and Rundle-Jackson-Brown (RJB) cellular automata models with long-range interactions that incorporates asperities, or stronger sites, into the lattice (Rundle and Jackson, 1977; Olami et al., 1992). These asperity cells are significantly stronger than the surrounding lattice sites but eventually rupture when the applied stress reaches their higher threshold stress. The introduction of these spatial heterogeneities results in spatial and temporal clustering in the model similar to that seen in natural fault systems. We observe sequences of activity that begin with a gradually accelerating number of larger events, or foreshocks, prior to a large event, followed by a tail of decreasing activity, or aftershocks. These recurrent large events occur at regular intervals and the characteristic time between events and their magnitude are a function of the stress dissipation parameter. The relative length of the foreshock to aftershock sequence depends on the amount of stress dissipation in the system. This work provides further evidence that the spatial and temporal patterns observed in natural seismicity are strongly influenced by the underlying physical properties and are not solely the result of a simple cascade mechanism. We find that the scaling depends not only on the amount of damage, but also on the spatial distribution of that damage (Dominguez et al., 2011; Kazemian et al., 2014). Here we compare the modeled sequences to those of natural earthquake sequences from California and around the world in order to investigate the interplay between cascade dynamics and spatial structure.

  13. Establishment of Pediatric Medication Therapy Management: A Proposed Model

    Directory of Open Access Journals (Sweden)

    Sandra Benavides

    2016-01-01

    Full Text Available Ongoing healthcare reform calls for increased accessibility, enhanced delivery, and improved quality of healthcare. Children and adolescents are experiencing a rise in the prevalence in chronic diseases leading to an increased utilization of medications. The increased use of chronic medications can lead to more medication errors or adverse drug events, particularly in children and adolescents using multiple chronic medications. These ongoing changes expand opportunities for a pharmacist to become further integrated in the inter-professional healthcare delivery for pediatric patients, particularly in an ambulatory or community setting. To date, a systemic process for the provision of medication therapy management (MTM services in pediatric patients has not been elucidated. The purpose of this paper is to describe a proposed model for delivering pediatric MTM. Furthermore, based on the available literature related to pediatric patients at risk for medication errors, adverse drug reactions, and subsequently-increased utilization of emergency departments and hospitalizations, a set of criteria is proposed for further research investigation.

  14. An image-computable psychophysical spatial vision model.

    Science.gov (United States)

    Schütt, Heiko H; Wichmann, Felix A

    2017-10-01

    A large part of classical visual psychophysics was concerned with the fundamental question of how pattern information is initially encoded in the human visual system. From these studies a relatively standard model of early spatial vision emerged, based on spatial frequency and orientation-specific channels followed by an accelerating nonlinearity and divisive normalization: contrast gain-control. Here we implement such a model in an image-computable way, allowing it to take arbitrary luminance images as input. Testing our implementation on classical psychophysical data, we find that it explains contrast detection data including the ModelFest data, contrast discrimination data, and oblique masking data, using a single set of parameters. Leveraging the advantage of an image-computable model, we test our model against a recent dataset using natural images as masks. We find that the model explains these data reasonably well, too. To explain data obtained at different presentation durations, our model requires different parameters to achieve an acceptable fit. In addition, we show that contrast gain-control with the fitted parameters results in a very sparse encoding of luminance information, in line with notions from efficient coding. Translating the standard early spatial vision model to be image-computable resulted in two further insights: First, the nonlinear processing requires a denser sampling of spatial frequency and orientation than optimal coding suggests. Second, the normalization needs to be fairly local in space to fit the data obtained with natural image masks. Finally, our image-computable model can serve as tool in future quantitative analyses: It allows optimized stimuli to be used to test the model and variants of it, with potential applications as an image-quality metric. In addition, it may serve as a building block for models of higher level processing.

  15. 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.

  16. ALADYN - a spatially explicit, allelic model for simulating adaptive dynamics.

    Science.gov (United States)

    Schiffers, Katja H; Travis, Justin Mj

    2014-12-01

    ALADYN is a freely available cross-platform C++ modeling framework for stochastic simulation of joint allelic and demographic dynamics of spatially-structured populations. Juvenile survival is linked to the degree of match between an individual's phenotype and the local phenotypic optimum. There is considerable flexibility provided for the demography of the considered species and the genetic architecture of the traits under selection. ALADYN facilitates the investigation of adaptive processes to spatially and/or temporally changing conditions and the resulting niche and range dynamics. To our knowledge ALADYN is so far the only model that allows a continuous resolution of individuals' locations in a spatially explicit landscape together with the associated patterns of selection.

  17. 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.

  18. A spatial and temporal continuous surface-subsurface hydrologic model

    Science.gov (United States)

    Xiao, Qing-Fu; Ustin, Susan L.; Wallender, Wesley W.

    1996-12-01

    A hydrologic model integrating surface-subsurface processes was developed based on spatial and temporal continuity theory. The raster-based mass balance hydrologic model consists of several submodels which determine spatial and temporal patterns in precipitation, surface flow, infiltration, subsurface flow, and the linkages between these submodels. Model parameters and variables are derived directly or indirectly from satellite remote sensing data, topographic maps, soil maps, literature, and weather station data and are stored in a Geographic Information System (GIS) database used for visualization. Surface resolution of cells in the model is 20 m by 20 m (pixel resolution of the Systeme Probatoire d'Observation de la Terre (SPOT) satellite image) over a 2511 km2 study area around the Crazy Mountains, Alaska, a watershed on the Arctic Circle draining into the Yukon River. The outputs from this model illustrate the interaction of physical and biologic factors on the partitioning of hydrologic components in a complex landscape.

  19. A spatial mark–resight model augmented with telemetry data

    Science.gov (United States)

    Sollmann, Rachel; Gardner, Beth; Parsons, Arielle W.; Stocking, Jessica J.; McClintock, Brett T.; Simons, Theodore R.; Pollock, Kenneth H.; O’Connell, Allan F.

    2013-01-01

    Abundance and population density are fundamental pieces of information for population ecology and species conservation, but they are difficult to estimate for rare and elusive species. Mark-resight models are popular for estimating population abundance because they are less invasive and expensive than traditional mark-recapture. However, density estimation using mark-resight is difficult because the area sampled must be explicitly defined, historically using ad-hoc approaches. We develop a spatial mark-resight model for estimating population density that combines spatial resighting data and telemetry data. Incorporating telemetry data allows us to inform model parameters related to movement and individual location. Our model also allows 2. The model presented here will have widespread utility in future applications, especially for species that are not naturally marked.

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

    Science.gov (United States)

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

    2014-03-01

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

  1. 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 homoto...

  2. 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...

  3. 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.

  4. 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.

  5. 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.

  6. New advances in spatial network modelling: towards evolutionary algorithms

    NARCIS (Netherlands)

    Reggiani, A; Nijkamp, P.; Sabella, E.

    2001-01-01

    This paper discusses analytical advances in evolutionary methods with a view towards their possible applications in the space-economy. For this purpose, we present a brief overview and illustration of models actually available in the spatial sciences which attempt to map the complex patterns of

  7. Classifying and comparing spatial models of fire dynamics

    Science.gov (United States)

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

    2007-01-01

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

  8. Modelling spatial anisotropy of gold concentration data using GIS ...

    Indian Academy of Sciences (India)

    linear trends are interpreted to represent major fault zones that exerted a prinicipal control on gold mineralization and therefore ... concentration data are particularly useful in the field of mineral exploration. Keywords. Structural control .... the variogram is the most com- monly used tool for modelling spatial structure and.

  9. 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

  10. Testing for spatial error dependence in probit models

    NARCIS (Netherlands)

    Amaral, P. V.; Anselin, L.; Arribas-Bel, D.

    2013-01-01

    In this note, we compare three test statistics that have been suggested to assess the presence of spatial error autocorrelation in probit models. We highlight the differences between the tests proposed by Pinkse and Slade (J Econom 85(1):125-254, 1998), Pinkse (Asymptotics of the Moran test and a

  11. Spatial variability and parametric uncertainty in performance assessment models

    International Nuclear Information System (INIS)

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

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Marzieh Mokarrama

    2018-04-01

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

  13. 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...

  14. A spatial model to predict the incidence of neural tube defects

    Directory of Open Access Journals (Sweden)

    Li Lianfa

    2012-11-01

    Full Text Available Abstract Background Environmental exposure may play an important role in the incidences of neural tube defects (NTD of birth defects. Their influence on NTD may likely be non-linear; few studies have considered spatial autocorrelation of residuals in the estimation of NTD risk. We aimed to develop a spatial model based on generalized additive model (GAM plus cokriging to examine and model the expected incidences of NTD and make the inference of the incidence risk. Methods We developed a spatial model to predict the expected incidences of NTD at village level in Heshun County, Shanxi Province, China, a region with high NTD cases. GAM was used to establish linear and non-linear relationships between local covariates and the expected NTD incidences. We examined the following village-level covariates in the model: projected coordinates, soil types, lithodological classes, distance to watershed, rivers, faults and major roads, annual average fertilizer uses, fruit and vegetable production, gross domestic product, and the number of doctors. The residuals from GAM were assumed to be spatially auto-correlative and cokriged with regional residuals to improve the prediction. Our approach was compared with three other models, universal kriging, generalized linear regression and GAM. Cross validation was conducted for validation. Results Our model predicted the expected incidences of NTD well, with a good CV R2 of 0.80. Important predictive factors included the fertilizer uses, locations of the centroid of each village, the shortest distance to rivers and faults and lithological classes with significant spatial autocorrelation of residuals. Our model out-performed the other three methods by 16% or more in term of R2. Conclusions The variance explained by our model was approximately 80%. This modeling approach is useful for NTD epidemiological studies and intervention planning.

  15. 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.

  16. Modelling the Spatial Distribution of Wind Energy Resources in Latvia

    Science.gov (United States)

    Aniskevich, S.; Bezrukovs, V.; Zandovskis, U.; Bezrukovs, D.

    2017-12-01

    The paper studies spatial wind energy flow distribution in Latvia based on wind speed measurements carried out at an altitude of 10 m over a period of two years, from 2015 to 2016. The measurements, with 1 min increments, were carried out using certified measuring instruments installed at 22 observation stations of the Latvian National Hydrometeorological and Climatological Service of the Latvian Environment, Geology and Meteorology Centre (LEGMC). The models of the spatial distribution of averaged wind speed and wind energy density were developed using the method of spatial interpolation based on the historical measurement results and presented in the form of colour contour maps with a 1×1 km resolution. The paper also provides the results of wind speed spatial distribution modelling using a climatological reanalysis ERA5 at the altitudes of 10, 54, 100 and 136 m with a 31×31 km resolution. The analysis includes the comparison of actual wind speed measurement results with the outcomes of ERA5 modelling for meteorological observation stations in Ainazi, Daugavpils, Priekuli, Saldus and Ventspils.

  17. Spatial Linear Mixed Models with Covariate Measurement Errors.

    Science.gov (United States)

    Li, Yi; Tang, Haicheng; Lin, Xihong

    2009-01-01

    Spatial data with covariate measurement errors have been commonly observed in public health studies. Existing work mainly concentrates on parameter estimation using Gibbs sampling, and no work has been conducted to understand and quantify the theoretical impact of ignoring measurement error on spatial data analysis in the form of the asymptotic biases in regression coefficients and variance components when measurement error is ignored. Plausible implementations, from frequentist perspectives, of maximum likelihood estimation in spatial covariate measurement error models are also elusive. In this paper, we propose a new class of linear mixed models for spatial data in the presence of covariate measurement errors. We show that the naive estimators of the regression coefficients are attenuated while the naive estimators of the variance components are inflated, if measurement error is ignored. We further develop a structural modeling approach to obtaining the maximum likelihood estimator by accounting for the measurement error. We study the large sample properties of the proposed maximum likelihood estimator, and propose an EM algorithm to draw inference. All the asymptotic properties are shown under the increasing-domain asymptotic framework. We illustrate the method by analyzing the Scottish lip cancer data, and evaluate its performance through a simulation study, all of which elucidate the importance of adjusting for covariate measurement errors.

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

    Science.gov (United States)

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

    2006-01-01

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

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

    OpenAIRE

    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 efficiently solve spatially explicit ecological models at large spatial scale using the CUDA language extension. We explain this technique by implementing three classical models of spatial self-org...

  20. 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.

  1. Exploring regional economic convergence in Romania. A spatial modeling approach

    Directory of Open Access Journals (Sweden)

    Zizi GOSCHIN

    2017-12-01

    Full Text Available This paper explores spatial economic convergence in Romania, from the perspective of real GDP/capita, and examines how the shock of the recent economic crisis has affected the convergence process. Given the presence of spatial autocorrelation in the values of GDP per capita, we address the question of convergence in terms of both classic and spatial regression models, thus filling a gap in the Romanian literature on this topic. The empirical results seem to provide support for both absolute and relative beta divergence in GDP/capita, as well as sigma divergence among Romanian counties on the long run. This is the consequence of the two-speed regional development, with the capital region and some large cities thriving by attracting human capital and FDIs, while the lagging regions are systematically left behind. Failing to validate the neoclassical approach on convergence, our results rather support the new divergence theory based on polarization and centre-periphery inequality.

  2. 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

  3. Spatial dynamics of a periodic population model with dispersal

    International Nuclear Information System (INIS)

    Jin Yu; Zhao Xiaoqiang

    2009-01-01

    This paper is devoted to the study of spatial dynamics of a class of periodic integro-differential equations which describe the population dispersal process via a dispersal kernel. By appealing to the theory of asymptotic speeds of spread and travelling waves for monotonic periodic semiflows, we establish the existence of the spreading speed c * and the nonexistence of continuous periodic travelling wave solutions with wave speed c * . We also prove the existence of left-continuous periodic travelling waves with wave speed c ≥ c * . In the autonomous case, the continuity of monotonic wave profiles with wave speed c ≥ c * is obtained

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

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

    Science.gov (United States)

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

    2015-10-23

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

  6. Analytical model of reactive transport processes with spatially variable coefficients.

    Science.gov (United States)

    Simpson, Matthew J; Morrow, Liam C

    2015-05-01

    Analytical solutions of partial differential equation (PDE) models describing reactive transport phenomena in saturated porous media are often used as screening tools to provide insight into contaminant fate and transport processes. While many practical modelling scenarios involve spatially variable coefficients, such as spatially variable flow velocity, v(x), or spatially variable decay rate, k(x), most analytical models deal with constant coefficients. Here we present a framework for constructing exact solutions of PDE models of reactive transport. Our approach is relevant for advection-dominant problems, and is based on a regular perturbation technique. We present a description of the solution technique for a range of one-dimensional scenarios involving constant and variable coefficients, and we show that the solutions compare well with numerical approximations. Our general approach applies to a range of initial conditions and various forms of v(x) and k(x). Instead of simply documenting specific solutions for particular cases, we present a symbolic worksheet, as supplementary material, which enables the solution to be evaluated for different choices of the initial condition, v(x) and k(x). We also discuss how the technique generalizes to apply to models of coupled multispecies reactive transport as well as higher dimensional problems.

  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 Medicine Bow and Sangre de Cristo Mountains primarily contain clustered spatial patterns of trees above timberline, which indicates a strong reliance on the amelioration of abiotic conditions through positive feedback with nearby vegetation. Although clustered spatial patterns likely originate in response to harsh abiotic conditions such as drought or constant strong winds, the local scale biotic interactions within a clustered formation of trees appears to override the immediate influence of broad scale climate. This is evidenced both by a lack of significant correlations between tree establishment and climate in these mountain ranges, as well as the considerable lag times between initial climate regime shifts and corresponding shifts in tree age structure. Taken together, this research suggests that the influence of broad scale climate on upper treeline ecotonal dynamics is contingent on the local scale spatial patterns of tree establishment and related influences of positive feedback. These findings have global implications for our

  8. 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.

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

    Science.gov (United States)

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

    2015-02-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

  12. 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)

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. On Spatially Explicit Models of Cholera Epidemics: Hydrologic controls, environmental drivers, human-mediated transmissions (Invited)

    Science.gov (United States)

    Rinaldo, A.; Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.

    2010-12-01

    A recently proposed model for cholera epidemics is examined. The model accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having different topologies. The vehicle of infection (Vibrio cholerae) is transported through the network links which are thought of as hydrological connections among susceptible communities. The mathematical tools used are borrowed from general schemes of reactive transport on river networks acting as the environmental matrix for the circulation and mixing of water-borne pathogens. The results of a large-scale application to the Kwa Zulu (Natal) epidemics of 2001-2002 will be discussed. Useful theoretical results derived in the spatially-explicit context will also be reviewed (like e.g. the exact derivation of the speed of propagation for traveling fronts of epidemics on regular lattices endowed with uniform population density). Network effects will be discussed. The analysis of the limit case of uniformly distributed population density proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. To that extent, it is shown that the ratio between spreading and disease outbreak timescales proves the crucial parameter. The relevance of our results lies in the major differences potentially arising between the predictions of spatially explicit models and traditional compartmental models of the SIR-like type. Our results suggest that in many cases of real-life epidemiological interest timescales of disease dynamics may trigger outbreaks that significantly depart from the predictions of compartmental models. Finally, a view on further developments includes: hydrologically improved aquatic reservoir models for pathogens; human mobility patterns affecting disease propagation; double-peak emergence and seasonality in the spatially explicit epidemic context.

  18. 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...

  19. Approximate Bayesian computation for spatial SEIR(S) epidemic models.

    Science.gov (United States)

    Brown, Grant D; Porter, Aaron T; Oleson, Jacob J; Hinman, Jessica A

    2018-02-01

    Approximate Bayesia n Computation (ABC) provides an attractive approach to estimation in complex Bayesian inferential problems for which evaluation of the kernel of the posterior distribution is impossible or computationally expensive. These highly parallelizable techniques have been successfully applied to many fields, particularly in cases where more traditional approaches such as Markov chain Monte Carlo (MCMC) are impractical. In this work, we demonstrate the application of approximate Bayesian inference to spatially heterogeneous Susceptible-Exposed-Infectious-Removed (SEIR) stochastic epidemic models. These models have a tractable posterior distribution, however MCMC techniques nevertheless become computationally infeasible for moderately sized problems. We discuss the practical implementation of these techniques via the open source ABSEIR package for R. The performance of ABC relative to traditional MCMC methods in a small problem is explored under simulation, as well as in the spatially heterogeneous context of the 2014 epidemic of Chikungunya in the Americas. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Spatial and spatio-temporal models with R-INLA.

    Science.gov (United States)

    Blangiardo, Marta; Cameletti, Michela; Baio, Gianluca; Rue, Håvard

    2013-12-01

    During the last three decades, Bayesian methods have developed greatly in the field of epidemiology. Their main challenge focusses around computation, but the advent of Markov Chain Monte Carlo methods (MCMC) and in particular of the WinBUGS software has opened the doors of Bayesian modelling to the wide research community. However model complexity and database dimension still remain a constraint. Recently the use of Gaussian random fields has become increasingly popular in epidemiology as very often epidemiological data are characterised by a spatial and/or temporal structure which needs to be taken into account in the inferential process. The Integrated Nested Laplace Approximation (INLA) approach has been developed as a computationally efficient alternative to MCMC and the availability of an R package (R-INLA) allows researchers to easily apply this method. In this paper we review the INLA approach and present some applications on spatial and spatio-temporal data.

  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. Unsupervised Posture Modeling Based on Spatial-Temporal Movement Features

    Science.gov (United States)

    Yan, Chunjuan

    Traditional posture modeling for human action recognition is based on silhouette segmentation, which is subject to the noise from illumination variation and posture occlusions and shadow interruptions. In this paper, we extract spatial temporal movement features from human actions and adopt unsupervised clustering method for salient posture learning. First, spatial-temporal interest points (STIPs) were extracted according to the properties of human movement, and then, histogram of gradient was built to describe the distribution of STIPs in each frame for a single pose. In addition, the training samples were clustered by non-supervised classification method. Moreover, the salient postures were modeled with GMM according to Expectation Maximization (EM) estimation. The experiment results proved that our method can effectively and accurately recognize human's action postures.

  3. 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.

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

    Science.gov (United States)

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

    2017-01-01

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

  5. 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.

  6. 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.

  7. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    Science.gov (United States)

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

    2012-01-01

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

  8. Modeling the spatial structure of hog production in Denmark

    DEFF Research Database (Denmark)

    Larue, Solène; Abildtrup, Jens; Schmitt, Bertrand

    , the interaction between the location of hog production and slaughterhouses. It is the assumption that the location of slaughterhouses is influenced by the location of the primary producers, implying that this variable is endogenous, whereas the location of primary producers is independent of the location...... of slaughterhouses. This is due to the fact that transportation costs of pigs are paid by the cooperatives owning the slaughterhouses. This assumption is tested applying a spatial econometric model. The model is estimated for 1989, 1999 and 2004. In the latter period, it is the hypothesis that the demand for export...

  9. 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.

  10. 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. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  11. Modeling spatial processes with unknown extremal dependence class

    KAUST Repository

    Huser, Raphaël G.

    2017-03-17

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

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

    Science.gov (United States)

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

    2012-12-06

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

  13. Dynamic Optimization of Ecosystem Services: A Comparative Analysis of Non-Spatial and Spatially-Explicit Models

    OpenAIRE

    Yun, Seong Do; Gramig, Benjamin M.

    2014-01-01

    This study develops and solves a stochastic, multi-year, discrete space-time model that allows the comparative analysis between non-spatial and spatially explicit models. The solution to this model implies the Stochastic Space-Time Natural Enemy-adjusted Economic Threshold (SST-NEET) to guide the choice of the optimal level of a pest that warrants management intervention. Using numerical simulation experiments over a generated synthetic geography, we derive three major conclusions. First, a u...

  14. Utility of the CIPP Model for Evaluating an Established Career Program in a Community College.

    Science.gov (United States)

    Hecht, Alfred R.

    How useful is Stufflebeam's Context, Input, Process, Product (CIPP) model for evaluating an established career program in a community college? On the basis of a case study, advantages of using CIPP include: comprehensiveness, flexibility, integration and decision-orientation. Implementation problems include: establishing procedures for delineating…

  15. 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

  16. Spatial succession modeling of biological communities: a multi-model approach.

    Science.gov (United States)

    Zhang, WenJun; Wei, Wu

    2009-11-01

    Strong spatial correlation may exist in the spatial succession of biological communities, and the spatial succession can be mathematically described. It was confirmed by our study on spatial succession of both plant and arthropod communities along a linear transect of natural grassland. Both auto-correlation and cross-correlation analyses revealed that the succession of plant and arthropod communities exhibited a significant spatial correlation, and the spatial correlation for plant community succession was stronger than arthropod community succession. Theoretically it should be reasonable to infer a site's community composition from the last site in the linear transect. An artificial neural network for state space modeling (ANNSSM) was developed in present study. An algorithm (i.e., Importance Detection Method (IDM)) for determining the relative importance of input variables was proposed. The relative importance for plant families Gramineae, Compositae and Leguminosae, and arthropod orders Homoptera, Diptera and Orthoptera, were detected and analyzed using IDM. ANNSSM performed better than multivariate linear regression and ordinary differential equation, while ordinary differential equation exhibited the worst performance in the simulation and prediction of spatial succession of biological communities. A state transition probability model (STPM) was proposed to simulate the state transition process of biological communities. STPM performed better than multinomial logistic regression in the state transition modeling. We suggested a novel multi-model framework, i.e., the joint use of ANNSSM and STPM, to predict the spatial succession of biological communities. In this framework, ANNSSM and STPM can be separately used to simulate the continuous and discrete dynamics.

  17. 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…

  18. Score, pseudo-score and residual diagnostics for goodness-of-fit of spatial point process models

    DEFF Research Database (Denmark)

    Baddeley, Adrian; Rubak, Ege H.; Møller, Jesper

    theoretical support to the established practice of using functional summary statistics such as Ripley’s K-function, when testing for complete spatial randomness; and they provide new tools such as the compensator of the K-function for testing other fitted models. The results also support localisation methods...

  19. Roads as Channels of Centrifugal Policy Transfer: A Spatial Interaction Model Revised

    Directory of Open Access Journals (Sweden)

    Katarzyna Kopczewska

    2013-10-01

    Full Text Available This paper proposes a methodology for measuring the spatial effects of roads and the seats of local authorities on the diffusion of business activity, which usually follows distance decay patterns from core to periphery. Regional development policies, pursued by regional authorities, directed at local units and designed to support local economies, are implemented by means of a centrifugal diffusion process. This invisible flow of policy is modeled using a one-way spatial interaction model represented by a multinomial distance decay function for the integrated spatial dataset. The research results indicate that NUTS5 (Nomenclature of Territorial Units for Statistics units (gminas perform better in terms of saturation with business activity when NUTS4 seats of authority are established there than when they are established near international roads. The natural diffusion process from core cities to the periphery covers approximately 25–30 km, and the presence of international roads extends this range by 20 km. The results confirm the hypothesis of an endogenous growth pattern.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Sustainable Street Vendors Spatial Zoning Models in Surakarta

    Science.gov (United States)

    Rahayu, M. J.; Putri, R. A.; Rini, E. F.

    2018-02-01

    Various strategies that have been carried out by Surakarta’s government to organize street vendors have not achieved the goal of street vendors’ arrangement comprehensively. The street vendors arrangement strategy consists of physical (spatial) and non-physical. One of the physical arrangements is to define the street vendor’s zoning. Based on the street vendors’ characteristics, there are two alternative locations of stabilization (as one kind of street vendors’ arrangement) that can be used. The aim of this study is to examine those alternative locations to set the street vendor’s zoning models. Quatitative method is used to formulate the spatial zoning model. The street vendor’s zoning models are formulated based on two approaches, which are the distance to their residences and previous trading locations. Geographic information system is used to indicate all street vendors’ residences and trading locations based on their type of goods. Through proximity point distance tool on ArcGIS, we find the closeness of residential location and previous trading location with the alternative location of street vendors’ stabilization. The result shows that the location was chosen by the street vendors to sell their goods mainly consider the proximity to their homes. It also shows street vendor’s zoning models which based on the type of street vendor’s goods.

  6. Towards Quantitative Spatial Models of Seabed Sediment Composition.

    Directory of Open Access Journals (Sweden)

    David Stephens

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

  7. Spatial modelling and mapping of female genital mutilation in Kenya

    Science.gov (United States)

    2014-01-01

    Background Female genital mutilation/cutting (FGM/C) is still prevalent in several communities in Kenya and other areas in Africa, as well as being practiced by some migrants from African countries living in other parts of the world. This study aimed at detecting clustering of FGM/C in Kenya, and identifying those areas within the country where women still intend to continue the practice. A broader goal of the study was to identify geographical areas where the practice continues unabated and where broad intervention strategies need to be introduced. Methods The prevalence of FGM/C was investigated using the 2008 Kenya Demographic and Health Survey (KDHS) data. The 2008 KDHS used a multistage stratified random sampling plan to select women of reproductive age (15–49 years) and asked questions concerning their FGM/C status and their support for the continuation of FGM/C. A spatial scan statistical analysis was carried out using SaTScan™ to test for statistically significant clustering of the practice of FGM/C in the country. The risk of FGM/C was also modelled and mapped using a hierarchical spatial model under the Integrated Nested Laplace approximation approach using the INLA library in R. Results The prevalence of FGM/C stood at 28.2% and an estimated 10.3% of the women interviewed indicated that they supported the continuation of FGM. On the basis of the Deviance Information Criterion (DIC), hierarchical spatial models with spatially structured random effects were found to best fit the data for both response variables considered. Age, region, rural–urban classification, education, marital status, religion, socioeconomic status and media exposure were found to be significantly associated with FGM/C. The current FGM/C status of a woman was also a significant predictor of support for the continuation of FGM/C. Spatial scan statistics confirm FGM clusters in the North-Eastern and South-Western regions of Kenya (p < 0.001). Conclusion This suggests that the

  8. 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

  9. MATHEMATICAL MODEL OF INTEGRAL CRITERION OF COMPETITION POTENTIAL OF MARITIME-RIVER HIGHER EDUCATIONAL ESTABLISHMENT.

    OpenAIRE

    Y.G. Yakusevich; L.D. Gerganov

    2012-01-01

    The competitive potential (CP) of maritime-river higher educational establishment in the conditions of a modern market of educational service is analyzed. The model of strategic resources (SR) is formalized. The mathematical model of an integral criterion of the competitive potential of higher educational establishment on the basis of Guermeyer’s method is built. It is proved that the discreteness of competitive edges is a reason of the formation of fuzzy resources and requires the cons...

  10. Spatial-temporal modelling of fMRI data through spatially regularized mixture of hidden process models.

    Science.gov (United States)

    Shen, Yuan; Mayhew, Stephen D; Kourtzi, Zoe; Tiňo, Peter

    2014-01-01

    Previous work investigated a range of spatio-temporal constraints for fMRI data analysis to provide robust detection of neural activation. We present a mixture-based method for the spatio-temporal modelling of fMRI data. This approach assumes that fMRI time series are generated by a probabilistic superposition of a small set of spatio-temporal prototypes (mixture components). Each prototype comprises a temporal model that explains fMRI signals on a single voxel and the model's "region of influence" through a spatial prior over the voxel space. As the key ingredient of our temporal model, the Hidden Process Model (HPM) framework proposed in Hutchinson et al. (2009) is adopted to infer the overlapping cognitive processes triggered by stimuli. Unlike the original HPM framework, we use a parametric model of Haemodynamic Response Function (HRF) so that biological constraints are naturally incorporated in the HRF estimation. The spatial priors are defined in terms of a parameterised distribution. Thus, the total number of parameters in the model does not depend on the number of voxels. The resulting model provides a conceptually principled and computationally efficient approach to identify spatio-temporal patterns of neural activation from fMRI data, in contrast to most conventional approaches in the literature focusing on the detection of spatial patterns. We first verify the proposed model in a controlled experimental setting using synthetic data. The model is further validated on real fMRI data obtained from a rapid event-related visual recognition experiment (Mayhew et al., 2012). Our model enables us to evaluate in a principled manner the variability of neural activations within individual regions of interest (ROIs). The results strongly suggest that, compared with occipitotemporal regions, the frontal ones are less homogeneous, requiring two HPM prototypes per region. Despite the rapid event-related experimental design, the model is capable of disentangling the

  11. MATHEMATICAL MODEL OF INTEGRAL CRITERION OF COMPETITION POTENTIAL OF MARITIME-RIVER HIGHER EDUCATIONAL ESTABLISHMENT.

    Directory of Open Access Journals (Sweden)

    Y.G. Yakusevich

    2012-07-01

    Full Text Available The competitive potential (CP of maritime-river higher educational establishment in the conditions of a modern market of educational service is analyzed. The model of strategic resources (SR is formalized. The mathematical model of an integral criterion of the competitive potential of higher educational establishment on the basis of Guermeyer’s method is built. It is proved that the discreteness of competitive edges is a reason of the formation of fuzzy resources and requires the construction of the functions belonging to competition potential of higher educational establishment.

  12. Establishment and evaluation of acute pulmonary embolism model in rabbit monitored with echocardiography

    International Nuclear Information System (INIS)

    Cong Dengli; Yu Xiaofeng; Qu Shaochun; Cong Zhibin

    2010-01-01

    Objective: To establish acute pulmonary embolism (APE) model in rabbit under echocardiography, and compare with the pathological results, and explore the feasibility of establishment of APE model monitored with echocardiography. Methods: APE models were established in 25 healthy Japanese white rabbits. The rabbit models of APE were created by right external jugular vena catheter using gelatin sponge monitored with echocardiography. Gelatin sponge emboli, 2 mm x 2 mm x 10 mm each, following with 5 mL physiologic saline were injected separately to right atrium via the right external jugular vein, which could make these emboli embolize pulmonary artery following blood stream. And the pulmonary artery systolic pressure was detected. Then the lung tissues slices near embolism place were detected by pathology after the model rabbits were dissected. Results: Twenty-three rabbit models with APE were successfully established from twenty-five healthy rabbits. However, one rabbit was unexpectedly dead because of anesthesia, another rabbit was dead owing to acute congestive heart failure of cor dextrum by emboli stagnation in cor dextrum. The echocardiogram of rabbits before and after model establishment showed that the pulmonary artery systolic pressure was significantly increased after APE, the main pulmonary artery, the left pulmonary artery and the right pulmonary artery were passively expanded. The right ventricle was increased and left ventricle was decreased oppositely, interventricular septum expanded toward left ventricle. there was significant difference compared with pre-embolism (P< 0.01). Gelatin sponge emboli in the pulmonary artery were detected by pathological detection. Conclusion: The method to establish APE model monitored with echocardiography is simple and feasible. It could be used as one of methods to establish APE model, animal. (authors)

  13. A Spatial Model of the Biomass to Energy Cycle

    DEFF Research Database (Denmark)

    Möller, Bernd

    2003-01-01

    by location. This paper aims to contribute to the development of a biomass to energy evaluation and mapping system, using geographical information systems (GIS). A GIS-based in-forest residue model considers forest growth and choice of harvest method. Data from a sawmill survey is used to assess sawmill resi......-dues. For both sources the costs of road transportation have been modelled using spatial cost allocation. As emphasis has been on using public data, the model is still a rough es-timate, which could be improved using forest industry data and refined algorithms. As a first result, the cost distribution...... and the costs of accumulated amounts of wood residues can now be calculated almost instantly for each location in the country. It is assumed that this approach will facilitate the assessment of future biomass markets....

  14. Modelling spatial-temporal and coordinative parameters in swimming.

    Science.gov (United States)

    Seifert, L; Chollet, D

    2009-07-01

    This study modelled the changes in spatial-temporal and coordinative parameters through race paces in the four swimming strokes. The arm and leg phases in simultaneous strokes (butterfly and breaststroke) and the inter-arm phases in alternating strokes (crawl and backstroke) were identified by video analysis to calculate the time gaps between propulsive phases. The relationships among velocity, stroke rate, stroke length and coordination were modelled by polynomial regression. Twelve elite male swimmers swam at four race paces. Quadratic regression modelled the changes in spatial-temporal and coordinative parameters with velocity increases for all four strokes. First, the quadratic regression between coordination and velocity showed changes common to all four strokes. Notably, the time gaps between the key points defining the beginning and end of the stroke phases decreased with increases in velocity, which led to decreases in glide times and increases in the continuity between propulsive phases. Conjointly, the quadratic regression among stroke rate, stroke length and velocity was similar to the changes in coordination, suggesting that these parameters may influence coordination. The main practical application for coaches and scientists is that ineffective time gaps can be distinguished from those that simply reflect an individual swimmer's profile by monitoring the glide times within a stroke cycle. In the case of ineffective time gaps, targeted training could improve the swimmer's management of glide time.

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

    Directory of Open Access Journals (Sweden)

    Yongliang Wang

    2015-01-01

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

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

    Science.gov (United States)

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

    2018-05-01

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

  17. 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

  18. 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.

  19. Spatial memory impairments in a prediabetic rat model.

    Science.gov (United States)

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

    2013-10-10

    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 during 9 weeks) were compared to controls' drinking water. HSu rats exhibited fasting normoglycemia accompanied by hyperinsulinemia and hypertriglyceridemia in the fed state, and insulin resistance with impaired glucose tolerance confirming them as a prediabetic rodent model. HSu rats displayed a poorer performance in hippocampal-dependent short- and long-term spatial memory performance, assessed with the modified Y-maze and Morris water maze tasks, respectively; this was accompanied by a reduction of insulin receptor-β density with normal levels of insulin receptor substrate-1 pSer636/639, and decreased hippocampal glucocorticoid receptor levels without changes of the plasma corticosterone levels. Importantly, HSu animals exhibited increased hippocampal levels of AMPA and NMDA receptor subunits GluA1 and GLUN1, respectively, whereas the levels of protein markers related to nerve terminals (synaptophysin) and oxidative stress/inflammation (HNE, RAGE, TNF-α) remained unaltered. These findings indicate that 9 weeks of sucrose consumption resulted in a metabolic condition suggestive of a prediabetic state, which translated into short- and long-term spatial memory deficits accompanied by alterations in hippocampal glutamatergic neurotransmission and abnormal glucocorticoid signaling. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

  20. 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.

  1. 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...

  2. 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.

  3. A Biophysical Neural Model To Describe Spatial Visual Attention

    International Nuclear Information System (INIS)

    Hugues, Etienne; Jose, Jorge V.

    2008-01-01

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

  4. 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.

    2016-01-01

    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. PMID:27529613

  5. 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.

  6. Spatial assignment of emissions using a new locomotive emissions model.

    Science.gov (United States)

    Gould, Gregory M; Niemeier, Deb A

    2011-07-01

    Estimates of fuel use and air pollutant emissions from freight rail currently rely highly on aggregate methods and largely obsolete data which offer little insight into contemporary air quality problems. Because the freight industry is for the most part privately held and data are closely guarded for competitive reasons, the challenge is to produce robust estimates using current reporting requirements, while accurately portraying the spatial nature of freight rail impacts. This research presents a new spatially resolved model for estimating air pollutant emissions (hydrocarbons, carbon monoxide, nitrogen oxides, particulate matter less than 10 μm in diameter, sulfur dioxide, and carbon dioxide) from locomotives. Emission estimates are based on track segment level data including track grade, type of train traffic (bulk, intermodal, or manifest) and the local locomotive fleet (EPA tier certification level and fuel efficiency). We model the California Class I freight rail system and compare our results to regional estimates from the California Air Resources Board and to estimates following U.S. Environmental Protection Agency guidance. We find that our results vary considerably from the other methods depending on the region or corridor analyzed. We also find large differences in fuel and emission intensity for individual rail corridors.

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

    Science.gov (United States)

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

    2015-08-01

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

  8. Establishment and characterization of uterine sarcoma and carcinosarcoma patient-derived xenograft models

    NARCIS (Netherlands)

    Cuppens, Tine; Depreeuw, Jeroen; Annibali, Daniela; Thomas, Debby; Hermans, Els; Gommé, Ellen; Trinh, Xuan Bich; Debruyne, David; Moerman, Philippe; Lambrechts, Diether; Amant, Frédéric

    2017-01-01

    Uterine sarcomas (US) and carcinosarcomas (CS) are rare, aggressive cancers. The lack of reliable preclinical models hampers the search for new treatment strategies and predictive biomarkers. To this end, we established and characterized US and CS patient-derived xenograft (PDX) models. Tumor

  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. A spatially structured metapopulation model within a stochastic environment.

    Science.gov (United States)

    Smith, Andrew G

    2017-09-01

    Populations often exist, either by choice or by external pressure, in a fragmented way, referred to as a metapopulation. Typically, the dynamics accounted for within metapopulation models are assumed to be static. For example, patch occupancy models often assume that the colonisation and extinction rates do not change, while spatially structured models often assume that the rates of births, deaths and migrations do not depend on time. While some progress has been made when these dynamics are changing deterministically, less is known when the changes are stochastic. It can be quite common that the environment a population inhabits determines how these dynamics change over time. Changes to this environment can have a large impact on the survival probability of a population and such changes will often be stochastic. The typical metapopulation model allows for catastrophes that could eradicate most, if not all, individuals on an entire patch. It is this type of phenomenon that this article addresses. A Markov process is developed that models the number of individuals on each patch within a metapopulation. An approximation for the original model is presented in the form of a piecewise-deterministic Markov process and the approximation is analysed to present conditions for extinction. Copyright © 2017 Elsevier Inc. All rights reserved.

  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. The contemporary model of prison architecture: Spatial response to the re-socialization programme

    Directory of Open Access Journals (Sweden)

    Fikfak Alenka

    2015-01-01

    Full Text Available The history of prison architecture concerns the development of various design formats. In contemporary terms, punishment and re-socialization are the two equally important purposes of a prison institution. Rightfully, the contemporary model of prison architecture may be viewed, inter alia, as a spatial response to the re-socialization programme. Based on a comprehensive literature review, critical discussion, and scientific description, this paper defines the main qualitative elements of prison architecture, which responds to the requirements for re-socialization of inmates, and further explains the way in which each response is provided. From these architectural and design attributes, a list of 30 indicators of the spatial response to re-socialization was established. Furthermore, by using the derived indicators, a comparative analysis of four contemporary European prisons was conducted. The results showed both similarities and differences in the spatial response to the re-socialization programme, indicating that the spatial potential for re-socialization of inmates may be developed by using various approaches to prison design.

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

    International Nuclear Information System (INIS)

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

    2005-01-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

  16. Establishing a microscopic model for nonfullerene organic solar cells: Self-accumulation effect of charges

    OpenAIRE

    Yao, Yao

    2018-01-01

    A one-dimensional many-body model is established to mimic the charge distribution and dynamics in nonfullerene organic solar cells. Two essential issues are taken into account in the model: The alternating donor and acceptor structure and the local imbalance of electron and hole densities. The alternating structure is beneficial for the direct generation of charge transfer state which enhances the local imbalance of charges. The most remarkable outcome of the model is that, due to the strong ...

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

    Science.gov (United States)

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

    2017-05-01

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

  18. Modelling Spatial and Temporal Fault Zone Evolution in Basement Rocks

    Science.gov (United States)

    Lunn, R. J.; Willson, J. P.; Shipton, Z. K.

    2006-12-01

    There is considerable industrial interest in assessing the permeability of faults for the purpose of oil and gas production, deep well injection of waste liquids, underground storage of natural gas and disposal of radioactive waste. Prior estimation of fault hydraulic properties is highly error prone. Faults zones are formed through a complex interaction of mechanical, hydraulic and chemical processes and their permeability varies considerably over both space and time. Algorithms for predicting fault seal potential using throw and host rock property data exist for clay-rich fault seals but are contentious. In the case of crystalline rocks and sand-sand contacts, no such algorithms exist. In any case, the study of fault growth processes does not suggest that there is a clear or simple relationship between fault throw and the fault zone permeability. To improve estimates of fault zone permeability, it is important to understand the underlying hydro-mechanical processes of fault zone formation. In this research, we explore the spatial and temporal evolution of fault zones through development and application of a 2D hydro-mechanical finite element model. The development of fault zone damage is simulated perpendicular to the main slip surface using a fully coupled solution of Navier's equation for mechanical deformation and Darcy's Law/conservation of fluid mass for subsurface fluid flow. The model is applied to study development of fault zones in basement rocks, based on the conceptual model of S. J. Martell, J. Struct. Geol. 12(7):869-882, 1990. We simulate the evolution of fault zones from pre-existing joints and explore controls on the growth rate and locations of multiple splay fractures which link-up to form complex damage zones. We are the first researchers to successfully simulate the temporal and spatial evolution of multiple wing cracks, tertiary fracturing, antithetic fractures propagating into the compressive region, infill fracturing between faults and

  19. Model establishing and performance analysis of service stratum traffic in the integrated sensing network

    Science.gov (United States)

    Ge, Zhiqun; Wang, Ying; Zhang, Xiaolu; Zheng, Yu; Zhao, Xinqun; Sun, Xiaohan

    2017-01-01

    We propose a time-division hybrid-user data flow model scheme based on semi-Markov state-transition algorithm for multiclass business and service in Integrated Sensing Network (ISN). Two typical flow models, visual sense and auditory sense service models, are set up due to the real situation of service stratum traffic, respectively. The experimental system based on the Asynchronous Optical Packet Switching (AOPS) network simulation platform is established for the feasibility of the proposed data flow model. The results show that the proposed models achieve reasonable packet loss rate and delay time in the case of different business and service levels.

  20. 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

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

    Science.gov (United States)

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

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

    NARCIS (Netherlands)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

  5. Spatial Extent Models for Natural Language Phrases Involving Directional Containment

    NARCIS (Netherlands)

    Singh, G.; de By, R.A.

    2015-01-01

    We study the problem of assigning a spatial extent to a text phrase such as central northern California', with the objective of allowing spatial interpretations of natural language, and consistency testing of complex utterances that involve multiple phrases from which spatial extent can be derived.

  6. 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.

  7. 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.

  8. Unemployment estimation: Spatial point referenced methods and models

    KAUST Repository

    Pereira, Soraia

    2017-06-26

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

  9. 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

  10. The formulation and estimation of a spatial skew-normal generalized ordered-response model.

    Science.gov (United States)

    2016-06-01

    This paper proposes a new spatial generalized ordered response model with skew-normal kernel error terms and an : associated estimation method. It contributes to the spatial analysis field by allowing a flexible and parametric skew-normal : distribut...

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

    NARCIS (Netherlands)

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

    2007-01-01

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

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

    International Nuclear Information System (INIS)

    Ruzicka, Adam; Palous, Jan; Theis, Christian

    2009-01-01

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

  13. The role of empathy in establishing rapport in the consultation: a new model.

    Science.gov (United States)

    Norfolk, Tim; Birdi, Kamal; Walsh, Deirdre

    2007-07-01

    Considerable research has been conducted recently into the notion of patient-centred consulting. The primary goal of this approach is to establish a clear understanding of the patient's perspective on his or her problem, and to allow this understanding to inform both the explanation and planning stages of the consultation. The quality of this understanding is largely determined by the empathic accuracy achieved by the doctor; the primary benefit is a therapeutic rapport between doctor and patient. To highlight the role of empathy and communication skills in establishing rapport, we initially developed a model which seeks to draw the various motivational and skill elements identified in separate research papers into a comprehensive model of the journey towards shared understanding between doctor and patient. We then conducted an initial validation of the model via qualitative analysis involving general practitioners (GPs) and clinical psychologists. The validation offered encouraging support for the principal elements of the model. Specific suggestions for clarification and extension were then incorporated in a revised model. The model appears to capture the dynamic process of establishing a therapeutic relationship (rapport) between doctor and patient, defined by the quality of the doctor's understanding of the patient's perspective on his or her problem. Arguably, the most important contribution of the model is to highlight the fact that 'empathy' and consequent 'rapport' are not mystical or exclusive concepts but, rather, involve the use of specific skills accessible at some level by all.

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

    Science.gov (United States)

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

    2015-04-01

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

  15. 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 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.

  16. Establishing a nurse practitioner model to enhance continuity between palliative care settings.

    Science.gov (United States)

    O'Connor, Margaret; Palfreyman, Stacey; Le, Brian; Lau, Rosalind

    2016-12-01

    Nurse practitioners (NP) are relatively new in Australia with national registration achieved in 2010. Most NP-related literature is about establishing models and scope of practice. This paper reports on the establishment and 12-month evaluation of an NP model of care, between inpatient and community palliative care services, developed to coordinate client care between hospital and home. To enhance patient outcomes, in hospital or home; to enhance professional relationships between services and facilitate effective discharges and admissions between services. Both services worked together to develop an evaluation framework, based on agreed key performance indicators. The NP model contributed to earlier discharges from hospital and fewer hospital admissions for those being cared for at home. There are developing opportunities to strengthen professional relationships through clinical and educational collaboration. The model has benefited both patient care and clinical cooperation between services.

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

    International Nuclear Information System (INIS)

    Yumurtaci, Zehra; Erdem, Hasan Hueseyin

    2007-01-01

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

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  19. 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

  20. Registration procedure model for establishing a WFOE in the People's Republic of China

    OpenAIRE

    Polajžer, Boštjan; Markič, Mirko

    2013-01-01

    The purpose of this article is to present research outcomes and to compare the establishment of a limited liability company in the European setting and China, and, hence, design a uniform model that could serve to future investors as a framework or instructions for registering a fully foreign owned enterprise in China. A comparative theoretical study of company registration models in the selected European countries was used, on the basis of which we observed that registering a limited liabili...

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

    Science.gov (United States)

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

    2008-12-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  3. 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...

  4. Panchromatic SED modelling of spatially-resolved galaxies

    Science.gov (United States)

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

    2018-02-01

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

  5. 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.

  6. Working models for spatial distribution and level of Mars' seismicity

    Science.gov (United States)

    Knapmeyer, M.; Oberst, J.; Hauber, E.; Wählisch, M.; Deuchler, C.; Wagner, R.

    2006-11-01

    We present synthetic catalogs of Mars quakes, intended to be used for performance assessments of future seismic networks on the planet. We have compiled a new inventory of compressional and extensional tectonic faults for the planet Mars, comprising 8500 faults with a total length of 680,000 km. The faults were mapped on the basis of Mars Orbiting Laser Altimeter (MOLA) shaded relief. Hence we expect to have assembled a homogeneous data set, not biased by illumination and viewing conditions of image data. Updated models of Martian crater statistics and geological maps were used to assign new maximum ages to all faults. On the basis of the fault catalog, spatial distributions of seismicity were simulated, using assumptions on the available annual seismic moment budget, the moment-frequency relationship, and a relation between rupture length and released moment. We have constructed five different models of Martian seismicity, predicting an annual moment release between 3.42 × 1016 Nm and 4.78 × 1018 Nm and up to 572 events with magnitudes greater than 4 per year as upper limit end-member case. Most events are expected on the Tharsis shield, but minor seismic centers are expected south of Hellas and north of Utopia Planitia.

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

    Science.gov (United States)

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

    2005-03-01

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

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

    International Nuclear Information System (INIS)

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

    1994-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Lu Li

    2017-03-01

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

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

    Science.gov (United States)

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

    2017-10-01

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

  11. 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.

  12. 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.

  13. 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

  14. Spatial object modeling in fuzzy topological spaces: with applications to land cover change

    NARCIS (Netherlands)

    Tang, Xinming; 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

  15. 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

  16. 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.

  17. Effects of species diversity on establishment and coexistence: a phylloplane fungal community model system.

    Science.gov (United States)

    Stohr, S N; Dighton, J

    2004-10-01

    A model system was devised, evaluating the influence that species diversity (species richness) has on fungal establishment and coexistence. Seven members of the fungal phylloplane community of Vaccinium macrocarpon (American cranberry) were selected to assess how species diversity affected development and coexistence of another community member, Pestalotia vaccinii. Pestalotia was engaged in competitive interactions on 1% Malt Extract Agar (MEA) petri dishes with each of the seven individual saprotrophs (two-way interaction), in random combinations with three of the seven saprotrophs (four-way interaction), and in random combinations with five of the seven saprotrophs (six-way interaction). The saprotrophic fungi used in this study were Aspergillus sp., Alternaria alternata, Cladosporium cladosporoides, Curvularia lunata, Epicoccum purpuracens, Penicillium sp., and Pithomyces chartarum. We hypothesized that species diversity would have a significant impact on the establishment and coexistence of Pestalotia vaccinii in culture. In an effort to minimize density-dependent effects, the number of viable spores employed in the three types of interactions was kept constant. Target spore concentrations of 50 viable spores of P. vaccinii and 50 saprotroph spores were used, regardless of the number of species involved in the interaction. This proved to be a very important factor in the experiment. As our results show, species diversity had little or no effect on the establishment and coexistence of Pestalotia vaccinii; however, spore density played an extremely important role in the establishment and development of fungal propagules in our model.

  18. MODELING SPATIAL TREE PATTERNS IN THE TAPAJÓS FOREST USING INTERFEROMETRIC HEIGHT

    Directory of Open Access Journals (Sweden)

    João R. dos Santos

    2005-04-01

    Full Text Available The spatial distribution of very large trees in primary Amazon forest is extracted from a digital model of interferometric forest height by an approach of local maximum filtering. The spatial point patterns of very large trees are modeled by a series of Markov point process models. Spatial distribution is regular, and interaction decreases with distance; very large trees are shown to exert repulsive interaction with their neighboring very large trees.

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

    Science.gov (United States)

    Huber, I.; Archontoulis, S.

    2017-12-01

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

  20. 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.

  1. 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…

  2. 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.

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  4. 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.

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

    Science.gov (United States)

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

    2017-12-01

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

  6. Establishment of probabilistic model for Salmonella Enteritidis growth and inactivation under acid and osmotic pressure

    Directory of Open Access Journals (Sweden)

    Yujiao Shi

    2017-12-01

    Full Text Available The growth and survival characteristic of Salmonella Enteritidis under acidic and osmotic conditions were studied. Meanwhile, a probabilistic model based on the theory of cell division and mortality was established to predict the growth or inactivation of S. Enteritidis. The experimental results demonstrated that the growth curves of planktonic and detached cells showed a significant difference (p < 0.05 under four conditions, including pH5.0 + 0.0%NaCl, pH7.0 + 4.0%NaCl, pH6.0 + 4.0%NaCl, and pH5.0 + 4.0%NaCl. And the established primary and secondary models could describe the growth of S. enteritis well by estimating four mathematics evaluation indexes, including determination coefficient (R2, root mean square error (RMSE, accuracy factor (Af and bias factor (Bf. Moreover, sequential treatment of 15% NaCl stress followed by pH 4.5 stress was the best condition to inactivate S. Enteritidis in 10 h at 25 °C. The probabilistic model with Logistical or Weibullian form could also predict the inactivation of S. Enteritidis well, thus realize the unification of predictive model to some extent or generalization of inactivation model. Furthermore, the primary 4-parameter probabilistic model or generalized inactivation model had slightly higher applicability and reliability to describe the growth or inactivation of S. Enteritidis than Baranyi model or exponential inactivation model within the experimental range in this study. Keywords: Acid, Osmotic pressure, Salmonella Enteritidis, Probabilistic model, Unification, Generalization

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

    International Nuclear Information System (INIS)

    Davis, P.A.

    1997-01-01

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

  8. Modeling Spatial and Temporal Fault Zone Evolution in Basement Rocks

    Science.gov (United States)

    Lunn, R. J.; Moir, H.; Shipton, Z. K.; Willson, J. P.

    2007-05-01

    There is considerable industrial interest in assessing the permeability of faults for the purpose of oil and gas production, deep well injection of waste liquids, underground storage of natural gas and disposal of radioactive waste. Deterministic prior estimation of fault hydraulic properties is highly error prone. Faults zones are formed through a complex interaction of mechanical, hydraulic and chemical processes and their permeability varies considerably over both space and time. Algorithms for predicting fault seal potential using throw and host rock property data exist for clay-rich fault seals but are contentious. In the case of crystalline rocks and sand-sand contacts, no such algorithms exist. In any case, the study of fault growth processes does not suggest that there is a clear or simple relationship between fault throw and the fault zone permeability. To improve estimates of fault zone permeability, it is important to understand the underlying hydro-mechanical processes of fault zone formation. In this research, we explore the spatial and temporal evolution of fault zones through development and application of a 2D hydro-mechanical finite element model. The temporal development of fault zone damage is simulated perpendicular to the main slip surface using Navier's equation for mechanical deformation. The model is applied to study development of fault zones in basement rocks. We simulate the evolution of fault zones from pre-existing joints and explore controls on the growth rate and locations of multiple splay fractures which link-up to form complex damage zones. We explore the temporal evolution of the stress field surrounding the fault tip for both propagation of isolated small faults and for fault linkage Results from these simulations have been validated using outcrop data.

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

    OpenAIRE

    Fashami, C. S.; Babaei, M.

    2017-01-01

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

  10. 1993-1994 Final technical report for establishing the SECME Model in the District of Columbia

    International Nuclear Information System (INIS)

    Vickers, R.G.

    1995-01-01

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

  11. 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.

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

    OpenAIRE

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

    2014-01-01

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

  13. Spatial smoothing in Bayesian models: a comparison of weights matrix specifications and their impact on inference.

    Science.gov (United States)

    Duncan, Earl W; White, Nicole M; Mengersen, Kerrie

    2017-12-16

    When analysing spatial data, it is important to account for spatial autocorrelation. In Bayesian statistics, spatial autocorrelation is commonly modelled by the intrinsic conditional autoregressive prior distribution. At the heart of this model is a spatial weights matrix which controls the behaviour and degree of spatial smoothing. The purpose of this study is to review the main specifications of the spatial weights matrix found in the literature, and together with some new and less common specifications, compare the effect that they have on smoothing and model performance. The popular BYM model is described, and a simple solution for addressing the identifiability issue among the spatial random effects is provided. Seventeen different definitions of the spatial weights matrix are defined, which are classified into four classes: adjacency-based weights, and weights based on geographic distance, distance between covariate values, and a hybrid of geographic and covariate distances. These last two definitions embody the main novelty of this research. Three synthetic data sets are generated, each representing a different underlying spatial structure. These data sets together with a real spatial data set from the literature are analysed using the models. The models are evaluated using the deviance information criterion and Moran's I statistic. The deviance information criterion indicated that the model which uses binary, first-order adjacency weights to perform spatial smoothing is generally an optimal choice for achieving a good model fit. Distance-based weights also generally perform quite well and offer similar parameter interpretations. The less commonly explored options for performing spatial smoothing generally provided a worse model fit than models with more traditional approaches to smoothing, but usually outperformed the benchmark model which did not conduct spatial smoothing. The specification of the spatial weights matrix can have a colossal impact on model

  14. Establishment of a rice transgene flow model for predicting maximum distances of gene flow in southern China.

    Science.gov (United States)

    Yao, Kemin; Hu, Ning; Chen, Wanlong; Li, Renzhong; Yuan, Qianhua; Wang, Feng; Qian, Qian; Jia, Shirong

    2008-01-01

    We aimed to establish a rice gene flow model based on (i) the Gaussian plume model, (ii) data from a three-location x 3-yr field experiment on transgene flow to common rice cultivars (Oryza sativa), male sterile (ms) lines (O. sativa) and common wild rice (Oryza rufipogon), and (iii) 32-yr historical meteorological data collected from 38 meteorological stations in southern China during the rice flowering period. The concept of the gene flow coefficient (GFC) is proposed; that is, the ratio of the transgene flow frequency (G%) obtained from field experiments to the aggregated pollen dispersal frequency (P%) calculated based on the pollen dispersal model. The maximum distances of gene flow (MDGF) to traditional rice cultivars, ms lines, and common wild rice at a threshold value of either 1.0 or 0.1% were determined. The MDGF and its spatial distribution in southern China show that the gene flow pattern is significantly affected by the monsoon climate, the topography, and the outcrossing ability of recipients. We believe that the information provided in this study will be useful for the risk assessment of transgenic rice in other rice-growing regions.

  15. 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.

  16. Modeling Spatial Data within Object Relational-Databases

    Directory of Open Access Journals (Sweden)

    Iuliana BOTHA

    2011-03-01

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

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

    Science.gov (United States)

    Fitriani, Rahma; Sumarminingsih, Eni; Astutik, Suci

    2017-05-01

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

  18. 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.

  19. [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.

  20. [Biological characteristics of an established model of ovarian cancer in mice and its homologous cell lines].

    Science.gov (United States)

    Zhang, Zheng-Mao; Zhang, Chao; Zhang, Feng-Hua; Shan, Bao-En; Nakagawa, Shinsaku

    2006-06-01

    There are no specific methods for early diagnosis of ovarian cancer, recurrence prevention and drug-resistance. The experimental mouse model of ovarian cancer could help to reveal the biological and genetic features of ovarian cancer, and provide rational basis for further intervention strategy. This study was to establish a model of ovarian cancer in mice and homologous cell line, and analyze its biological characteristics. Ovarian cancer was developed in 8-week-old female F1 (C57BL/6N x C3H/He) mice by a single whole-body neutron irradiation of 2.7 Gy from a (252)Cf source. A metastatic cell line was established through serial subcutaneous transplantation of the primary tumor for 11 generations, and then tumor cells were transferred to in vitro cultivation. These cells were cloned for more than 6 months. The biological characteristics of the tumors and the homologous cell line were determined by cellular and molecular biological techniques. The grafted tumors in mice were successively passaged for 11 generations with a successful inoculation rate of 96% during 23 months. A tumor cell line OV99 isolated from the grafted tumors was established after 6 months and grew steadily. Morphologic characters and ultrastructures of OV99 cells were accorded with those of ovarian cancer epithelia. The chromosomal analysis of OV99 cells revealed aneuploid pattern of 76 chromosomes. Flow cytometry (FCM) and reverse transcription-polymerase chain reaction (RT-PCR) showed same features between OV99 cells and positive control ovarian cancer cell line OVHM, including distribution of cell cycle, rapid growth rate and the expression of P21, P185, P53, proliferating nuclear cell antigen (PCNA) and Cyclin D proteins, and MAGE-1 and MAGE-3 mRNA. Establishment of the ovarian carcinoma animal model in mice and OV99, a cell line owns biologic characteristics of ovarian cancer cells, provides experimental materials for further investigation of ovarian carcinoma.

  1. A modeling approach to establish environmental flow threshold in ungauged semidiurnal tidal river

    Science.gov (United States)

    Akter, A.; Tanim, A. H.

    2018-03-01

    Due to shortage of flow monitoring data in ungauged semidiurnal river, 'environmental flow' (EF) determination based on its key component 'minimum low flow' is always difficult. For EF assessment this study selected a reach immediately after the Halda-Karnafuli confluence, a unique breeding ground for Indian Carp fishes of Bangladesh. As part of an ungauged tidal river, EF threshold establishment faces challenges in changing ecological paradigms with periodic change of tides and hydrologic alterations. This study describes a novel approach through modeling framework comprising hydrological, hydrodynamic and habitat simulation model. The EF establishment was conceptualized according to the hydrologic process of an ungauged semi-diurnal tidal regime in four steps. Initially, a hydrologic model coupled with a hydrodynamic model to simulate flow considering land use changes effect on streamflow, seepage loss of channel, friction dominated tidal decay as well as lack of long term flow characteristics. Secondly, to define hydraulic habitat feature, a statistical analysis on derived flow data was performed to identify 'habitat suitability'. Thirdly, to observe the ecological habitat behavior based on the identified hydrologic alteration, hydraulic habitat features were investigated. Finally, based on the combined habitat suitability index flow alteration and ecological response relationship was established. Then, the obtained EF provides a set of low flow indices of desired regime and thus the obtained discharge against maximum Weighted Usable Area (WUA) was defined as EF threshold for the selected reach. A suitable EF regime condition was obtained within flow range 25-30.1 m3/s i.e., around 10-12% of the mean annual runoff of 245 m3/s and these findings are within researchers' recommendation of minimum flow requirement. Additionally it was observed that tidal characteristics are dominant process in semi-diurnal regime. However, during the study period (2010-2015) the

  2. MODEL OF SPATIAL EVALUATION FOR TOURISM ECO-RENT

    Directory of Open Access Journals (Sweden)

    Maja Fredotović

    2011-02-01

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

  3. Disaggregation, aggregation and spatial scaling in hydrological modelling

    Science.gov (United States)

    Becker, Alfred; Braun, Peter

    1999-04-01

    A typical feature of the land surface is its heterogeneity in terms of the spatial variability of land surface characteristics and parameters controlling physical/hydrological, biological, and other related processes. Different forms and degrees of heterogeneity need to be taken into account in hydrological modelling. The first part of the article concerns the conditions under which a disaggregation of the land surface into subareas of uniform or "quasihomogeneous" behaviour (hydrotopes or hydrological response units - HRUs) is indispensable. In a case study in northern Germany, it is shown that forests in contrast to arable land, areas with shallow groundwater in contrast to those with deep, water surfaces and sealed areas should generally be distinguished (disaggregated) in modelling, whereas internal heterogeneities within these hydrotopes can be assessed statistically, e.g., by areal distribution functions (soil water holding capacity, hydraulic conductivity, etc.). Models with hydrotope-specific parameters can be applied to calculate the "vertical" processes (fluxes, storages, etc.), and this, moreover, for hydrotopes of different area, and even for groups of distributed hydrotopes in a reference area (hydrotope classes), provided that the meteorological conditions are similar. Thus, a scaling problem does not really exist in this process domain. The primary domain for the application of scaling laws is that of lateral flows in landscapes and river basins. This is illustrated in the second part of the article, where results of a case study in Bavaria/Germany are presented and discussed. It is shown that scaling laws can be applied efficiently for the determination of the Instantaneous Unit Hydrograph (IUH) of the surface runoff system in river basins: simple scaling for basins larger than 43 km 2, and multiple scaling for smaller basins. Surprisingly, only two parameters were identified as important in the derived relations: the drainage area and, in some

  4. Establishment and characterization of uterine sarcoma and carcinosarcoma patient-derived xenograft models.

    Science.gov (United States)

    Cuppens, Tine; Depreeuw, Jeroen; Annibali, Daniela; Thomas, Debby; Hermans, Els; Gommé, Ellen; Trinh, Xuan Bich; Debruyne, David; Moerman, Philippe; Lambrechts, Diether; Amant, Frédéric

    2017-09-01

    Uterine sarcomas (US) and carcinosarcomas (CS) are rare, aggressive cancers. The lack of reliable preclinical models hampers the search for new treatment strategies and predictive biomarkers. To this end, we established and characterized US and CS patient-derived xenograft (PDX) models. Tumor fragments of US and CS were subcutaneously implanted into immunocompromised mice. Engrafted xenograft and original tumors were compared by means of histology, immunohistochemistry, whole-genome low-coverage sequencing for copy number variations, and RNA sequencing. Of 13 implanted leiomyosarcomas (LMS), 10 engrafted (engraftment rate of 77%). Also 2 out of 7 CS (29%) and one high-grade US (not otherwise specified) models were successfully established. LMS xenografts showed high histological similarity to their corresponding human tumors. Expression of desmin and/or H-caldesmon was detected in 8/10 LMS PDX models. We noticed that in CS models, characterized by the concomitant presence of a mesenchymal and an epithelial component, the relative distribution of the components is varying over the generations, as confirmed by changes in vimentin and cytokeratin expression. The similarity in copy number profiles between original and xenograft tumors ranged from 57.7% to 98.2% for LMS models and from 47.4 to 65.8% for CS models. Expression pattern stability was assessed by clustering RNA expression levels of original and xenograft tumors. Six xenografts clustered together with their original tumor, while 3 (all LMS) clustered apart. We present here a panel of clinically annotated uterine sarcoma and carcinosarcoma PDX models, which will be a useful tool for preclinical testing of new therapies. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Collaborative spatial analysis and modelling in a research environment

    CSIR Research Space (South Africa)

    Naudé, A

    2006-02-01

    Full Text Available of an open-source geoportal and geospatial content management framework (adapted for low-bandwidth environments), customisable spatial analysis workbenches (providing guidance and tools for geoprocesses such as spatial disaggregation) and the formulation... resources and processes. In these two sections, the concept of a knowledge geoportal is introduced. A knowledge geoportal includes the notion of customisable workbenches, aimed at addressing the other key problems seen in Figure 1. Further...

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

    Directory of Open Access Journals (Sweden)

    Erfan Ayubi

    2017-05-01

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

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

    International Nuclear Information System (INIS)

    Zamyatin, Alexander; Cabral, Pedro

    2011-01-01

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

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

    Science.gov (United States)

    Musal, Muzaffer; Aktekin, Tevfik

    2013-01-30

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

  9. 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.

  10. Prediction of peanut protein solubility based on the evaluation model established by supervised principal component regression.

    Science.gov (United States)

    Wang, Li; Liu, Hongzhi; Liu, Li; Wang, Qiang; Li, Shurong; Li, Qizhai

    2017-03-01

    Supervised principal component regression (SPCR) analysis was adopted to establish the evaluation model of peanut protein solubility. Sixty-six peanut varieties were analysed in the present study. Results showed there was intimate correlation between protein solubility and other indexes. At 0.05 level, these 11 indexes, namely crude fat, crude protein, total sugar, cystine, arginine, conarachin I, 37.5kDa, 23.5kDa, 15.5kDa, protein extraction rate, and kernel ratio, were correlated with protein solubility and were extracted to for establishing the SPCR model. At 0.01 level, a simper model was built between the four indexes (crude protein, cystine, conarachin I, and 15.5kDa) and protein solubility. Verification results showed that the coefficients between theoretical and experimental values were 0.815 (psolubility effectively. The application of models was more convenient and efficient than traditional determination method. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Mendiguren, Gorka; Koch, Julian; Stisen, Simon

    2017-11-01

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

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

    Science.gov (United States)

    Laurini, Márcio Poletti

    2017-10-01

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

  13. [Establishment of A Clinical Prediction Model of Prolonged Air Leak 
after Anatomic Lung Resection].

    Science.gov (United States)

    Wu, Xianning; Xu, Shibin; Ke, Li; Fan, Jun; Wang, Jun; Xie, Mingran; Jiang, Xianliang; Xu, Meiqing

    2017-12-20

    Prolonged air leak (PAL) after anatomic lung resection is a common and challenging complication in thoracic surgery. No available clinical prediction model of PAL has been established in China. The aim of this study was to construct a model to identify patients at increased risk of PAL by using preoperative factors exclusively. We retrospectively reviewed clinical data and PAL occurrence of patients after anatomic lung resection, in department of thoracic surgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, from January 2016 to October 2016. 359 patients were in group A, clinical data including age, body mass index (BMI), gender, smoking history, surgical methods, pulmonary function index, pleural adhesion, pathologic diagnosis, side and site of resected lung were analyzed. By using univariate and multivariate analysis, we found the independent predictors of PAL after anatomic lung resection and subsequently established a clinical prediction model. Then, another 112 patients (group B), who underwent anatomic lung resection in different time by different team, were chosen to verify the accuracy of the prediction model. Receiver-operating characteristic (ROC) curve was constructed using the prediction model. Multivariate Logistic regression analysis was used to identify six clinical characteristics [BMI, gender, smoking history, forced expiratory volume in one second to forced vital capacity ratio (FEV1%), pleural adhesion, site of resection] as independent predictors of PAL after anatomic lung resection. The area under the ROC curve for our model was 0.886 (95%CI: 0.835-0.937). The best predictive P value was 0.299 with sensitivity of 78.5% and specificity of 93.2%. Our prediction model could accurately identify occurrence risk of PAL in patients after anatomic lung resection, which might allow for more effective use of intraoperative prophylactic strategies.
.

  14. Towards Measures to Establish the Relevance of Climate Model Output for Decision Support

    Science.gov (United States)

    Clarke, L.; Smith, L. A.

    2007-12-01

    to weight climate model output in the decision process; one obvious example is the question of over what spatial and time averages modelers expect information in current climate distributions to be robust. The IPCC itself suggests continental/seasonal, while distributions over 10's of kilometers/hourly is on offer. Our aim here is not to resolve this discrepancy, but to develop methods with which it can be addressed. This is illustrated in the context of using another physically based, imperfect model setting: using Newton's laws in an actual case of NASA hazard evaluation. Our aim is to develop transparent standards of good practice managing expectations, which will allow model improvements over the next decades to be seen as progress by the users of climate science.

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

    Directory of Open Access Journals (Sweden)

    Qingxue Li

    Full Text Available 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

  16. 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.

  17. 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.

  18. Impact of climate change on river flooding assessed with different spatial model resolutions

    NARCIS (Netherlands)

    Booij, Martijn J.

    2005-01-01

    The impact of climate change on flooding in the river Meuse is assessed on a daily basis using spatially and temporally changed climate patterns and a hydrological model with three different spatial resolutions. This is achieved by selecting a hydrological modelling framework and implementing

  19. Computer Games versus Maps before Reading Stories: Priming Readers' Spatial Situation Models

    Science.gov (United States)

    Smith, Glenn Gordon; Majchrzak, Dan; Hayes, Shelley; Drobisz, Jack

    2011-01-01

    The current study investigated how computer games and maps compare as preparation for readers to comprehend and retain spatial relations in text narratives. Readers create situation models of five dimensions: spatial, temporal, causal, goal, and protagonist (Zwaan, Langston, & Graesser 1995). Of these five, readers mentally model the spatial…

  20. Model predictive control for optimal treatment in a spatial cancer game

    NARCIS (Netherlands)

    Javier Muros, Francisco; M. Maestre, Jose; You, Li; Stankova, Katerina

    2018-01-01

    This work focuses on modeling tumorigenesis as a spatial evolutionary game and on finding optimal cancer treatment using a model predictive control approach. Extending a nonspatial cancer game from the literature into a spatial setting, we consider a solid tumor composed of cells of two different

  1. A spatial-dynamic value transfer model of economic losses from a biological invasion

    Science.gov (United States)

    Thomas P. Holmes; Andrew M. Liebhold; Kent F. Kovacs; Betsy. Von Holle

    2010-01-01

    Rigorous assessments of the economic impacts of introduced species at broad spatial scales are required to provide credible information to policy makers. We propose that economic models of aggregate damages induced by biological invasions need to link microeconomic analyses of site-specific economic damages with spatial-dynamic models of value change associated with...

  2. Establishment of an orthotopic lung cancer model in nude mice and its evaluation by spiral CT.

    Science.gov (United States)

    Liu, Xiang; Liu, Jun; Guan, Yubao; Li, Huiling; Huang, Liyan; Tang, Hailing; He, Jianxing

    2012-04-01

    To establish a simple and highly efficient orthotopic animal model of lung cancer cell line A549 and evaluate the growth pattern of intrathoracic tumors by spiral CT. A549 cells (5×10(6) mL(-1)) were suspended and inoculated into the right lung of BALB/c nude mice via intrathoracic injection. Nude mice were scanned three times each week by spiral CT after inoculation of lung cancer cell line A549. The survival time and body weight of nude mice as well as tumor invasion and metastasis were examined. Tissue was collected for subsequent histological assay after autopsia of mice. The tumor-forming rate of the orthotopic lung cancer model was 90%. The median survival time was 30.7 (range, 20-41) days. The incidence of tumor metastasis was 100%. The mean tumor diameter and the average CT value gradually increased in a time-dependent manner. The method of establishing the orthotopic lung cancer model through transplanting A549 cells into the lung of nude mice is simple and highly successful. Spiral CT can be used to evaluate intrathoracic tumor growth in nude mice vividly and dynamically.

  3. A spatial- and age-structured assessment model to estimate the ...

    African Journals Online (AJOL)

    , thereby indirectly negatively impacting juvenile abalone which rely on the urchins for shelter. A model is developed for abalone that is an extension of more standard age-structured assessment models because it explicitly takes spatial effects ...

  4. Improving the spatial representation of basin hydrology and flow processes in the SWAT model

    OpenAIRE

    Rathjens, Hendrik

    2014-01-01

    This dissertation aims at improving the spatial representation of basin hydrology and flow processes in the SWAT model. Die vorliegende Dissertation stellt die methodischen Grundlage zur räumlich differenzierten Modellierung mit dem Modell SWAT dar.

  5. Spatial prediction of N2O emissions in pasture: a Bayesian model averaging analysis.

    Directory of Open Access Journals (Sweden)

    Xiaodong Huang

    Full Text Available Nitrous oxide (N2O is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2 field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

  6. [Etiological analysis and establishment of a discriminant model for lower respiratory tract infections in hospitalized patients].

    Science.gov (United States)

    Chen, Y S; Lin, X H; Li, H R; Hua, Z D; Lin, M Q; Huang, W S; Yu, T; Lyu, H Y; Mao, W P; Liang, Y Q; Peng, X R; Chen, S J; Zheng, H; Lian, S Q; Hu, X L; Yao, X Q

    2017-12-12

    Objective: To analyze the pathogens of lower respiratory tract infection(LRTI) including bacterial, viral and mixed infection, and to establish a discriminant model based on clinical features in order to predict the pathogens. Methods: A total of 243 hospitalized patients with lower respiratory tract infections were enrolled in Fujian Provincial Hospital from April 2012 to September 2015. The clinical data and airway (sputum and/or bronchoalveolar lavage) samples were collected. Microbes were identified by traditional culture (for bacteria), loop-mediated isothermal amplification(LAMP) and gene sequencing (for bacteria and atypical pathogen), or Real-time quantitative polymerase chain reaction (Real-time PCR)for viruses. Finally, a discriminant model was established by using the discriminant analysis methods to help to predict bacterial, viral and mixed infections. Results: Pathogens were detected in 53.9% (131/243) of the 243 cases.Bacteria accounted for 23.5%(57/243, of which 17 cases with the virus, 1 case with Mycoplasma pneumoniae and virus), mainly Pseudomonas Aeruginosa and Klebsiella Pneumonia. Atypical pathogens for 4.9% (12/243, of which 3 cases with the virus, 1 case of bacteria and viruses), all were mycoplasma pneumonia. Viruses for 34.6% (84/243, of which 17 cases of bacteria, 3 cases with Mycoplasma pneumoniae, 1 case with Mycoplasma pneumoniae and bacteria) of the cases, mainly Influenza A virus and Human Cytomegalovirus, and other virus like adenovirus, human parainfluenza virus, respiratory syncytial virus, human metapneumovirus, human boca virus were also detected fewly. Seven parameters including mental status, using antibiotics prior to admission, complications, abnormal breath sounds, neutrophil alkaline phosphatase (NAP) score, pneumonia severity index (PSI) score and CRUB-65 score were enrolled after univariate analysis, and discriminant analysis was used to establish the discriminant model by applying the identified pathogens as the

  7. Modelling malaria incidence by an autoregressive distributed lag model with spatial component.

    Science.gov (United States)

    Laguna, Francisco; Grillet, María Eugenia; León, José R; Ludeña, Carenne

    2017-08-01

    The influence of climatic variables on the dynamics of human malaria has been widely highlighted. Also, it is known that this mosquito-borne infection varies in space and time. However, when the data is spatially incomplete most popular spatio-temporal methods of analysis cannot be applied directly. In this paper, we develop a two step methodology to model the spatio-temporal dependence of malaria incidence on local rainfall, temperature, and humidity as well as the regional sea surface temperatures (SST) in the northern coast of Venezuela. First, we fit an autoregressive distributed lag model (ARDL) to the weekly data, and then, we adjust a linear separable spacial vectorial autoregressive model (VAR) to the residuals of the ARDL. Finally, the model parameters are tuned using a Markov Chain Monte Carlo (MCMC) procedure derived from the Metropolis-Hastings algorithm. Our results show that the best model to account for the variations of malaria incidence from 2001 to 2008 in 10 endemic Municipalities in North-Eastern Venezuela is a logit model that included the accumulated local precipitation in combination with the local maximum temperature of the preceding month as positive regressors. Additionally, we show that although malaria dynamics is highly heterogeneous in space, a detailed analysis of the estimated spatial parameters in our model yield important insights regarding the joint behavior of the disease incidence across the different counties in our study. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Spatial Inequalities in the Incidence of Colorectal Cancer and Associated Factors in the Neighborhoods of Tehran, Iran: Bayesian Spatial Models.

    Science.gov (United States)

    Mansori, Kamyar; Solaymani-Dodaran, Masoud; Mosavi-Jarrahi, Alireza; Motlagh, Ali Ganbary; Salehi, Masoud; Delavari, Alireza; Asadi-Lari, Mohsen

    2018-01-01

    The aim of this study was to determine the factors associated with the spatial distribution of the incidence of colorectal cancer (CRC) in the neighborhoods of Tehran, Iran using Bayesian spatial models. This ecological study was implemented in Tehran on the neighborhood level. Socioeconomic variables, risk factors, and health costs were extracted from the Equity Assessment Study conducted in Tehran. The data on CRC incidence were extracted from the Iranian population-based cancer registry. The Besag-York-Mollié (BYM) model was used to identify factors associated with the spatial distribution of CRC incidence. The software programs OpenBUGS version 3.2.3, ArcGIS 10.3, and GeoDa were used for the analysis. The Moran index was statistically significant for all the variables studied (p<0.05). The BYM model showed that having a women head of household (median standardized incidence ratio [SIR], 1.63; 95% confidence interval [CI], 1.06 to 2.53), living in a rental house (median SIR, 0.82; 95% CI, 0.71 to 0.96), not consuming milk daily (median SIR, 0.71; 95% CI, 0.55 to 0.94) and having greater household health expenditures (median SIR, 1.34; 95% CI, 1.06 to 1.68) were associated with a statistically significant elevation in the SIR of CRC. The median (interquartile range) and mean (standard deviation) values of the SIR of CRC, with the inclusion of all the variables studied in the model, were 0.57 (1.01) and 1.05 (1.31), respectively. Inequality was found in the spatial distribution of CRC incidence in Tehran on the neighborhood level. Paying attention to this inequality and the factors associated with it may be useful for resource allocation and developing preventive strategies in atrisk areas.

  9. Spatial Inequalities in the Incidence of Colorectal Cancer and Associated Factors in the Neighborhoods of Tehran, Iran: Bayesian Spatial Models

    Directory of Open Access Journals (Sweden)

    Kamyar Mansori

    2018-01-01

    Full Text Available Objectives The aim of this study was to determine the factors associated with the spatial distribution of the incidence of colorectal cancer (CRC in the neighborhoods of Tehran, Iran using Bayesian spatial models. Methods This ecological study was implemented in Tehran on the neighborhood level. Socioeconomic variables, risk factors, and health costs were extracted from the Equity Assessment Study conducted in Tehran. The data on CRC incidence were extracted from the Iranian population-based cancer registry. The Besag-York-Mollié (BYM model was used to identify factors associated with the spatial distribution of CRC incidence. The software programs OpenBUGS version 3.2.3, ArcGIS 10.3, and GeoDa were used for the analysis. Results The Moran index was statistically significant for all the variables studied (p<0.05. The BYM model showed that having a women head of household (median standardized incidence ratio [SIR], 1.63; 95% confidence interval [CI], 1.06 to 2.53, living in a rental house (median SIR, 0.82; 95% CI, 0.71 to 0.96, not consuming milk daily (median SIR, 0.71; 95% CI, 0.55 to 0.94 and having greater household health expenditures (median SIR, 1.34; 95% CI, 1.06 to 1.68 were associated with a statistically significant elevation in the SIR of CRC. The median (interquartile range and mean (standard deviation values of the SIR of CRC, with the inclusion of all the variables studied in the model, were 0.57 (1.01 and 1.05 (1.31, respectively. Conclusions Inequality was found in the spatial distribution of CRC incidence in Tehran on the neighborhood level. Paying attention to this inequality and the factors associated with it may be useful for resource allocation and developing preventive strategies in atrisk areas.

  10. 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

  11. Predictive modeling of marine benthic macrofauna and its use to inform spatial monitoring design.

    Science.gov (United States)

    Dowd, Michael; Grant, Jon; Lu, Lin

    2014-06-01

    This study undertakes ecological analysis focused on predictive modelling and design for spatial sampling. The approaches are applied to a set of coastal marine benthic macrofaunal observations, and associated environmental data, measured at 48 sites in St Anns Bay, Nova Scotia, Canada. A multivariate generalized least-squares regression was used to establish a predictive relationship between benthic fauna and the environment. Five ecological indices derived from faunal composition (abundance, richness, species number, diversity, AMBI) were treated as a multivariate response, and 10 environmental variables as candidate predictors. The multivariate regression also incorporated the effects of spatial autocorrelation. Predictive relationships were highly significant, and variable selection identified three key environmental predictors (median sediment grain size, porosity, and sulfide). Using these baseline data, we developed a procedure to identify a reduced sampling design for long-term monitoring of benthic faunal health. The procedure is based on a sequential (backward elimination) algorithm to identify the set of sites that contributed most to the overall information. This study provides a general and comprehensive statistical framework for treating environmental monitoring and sampling design. It can be extended beyond the statistical framework used, and applied to a range of ecological applications.

  12. 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

  13. 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.

  14. 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

    , 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......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...

  15. 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.

  16. 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.

  17. A participatory GIS approach to spatial modeling for slum upgrading ...

    African Journals Online (AJOL)

    The most prominent problem of rapid urbanism in Harare is the development of slums and Epworth is a notable example. The quality of planning and decision making in the participatory slum upgrading initiative can be sustainably improved by well managed processes of spatial and socio-economic data collection. More so ...

  18. Modelling the spatial distribution of linear landscape elements in Europe

    NARCIS (Netherlands)

    Zanden, van der E.H.; Verburg, P.H.; Mücher, C.A.

    2013-01-01

    Linear landscape elements, such as ditches, hedgerows, lines of trees and field margins, provide important habitats and ecosystem services and function as ecological infrastructure for species within agricultural landscapes. Spatial maps of the distribution of these elements are needed to better

  19. Selecting one among many referents in spatial situation models

    NARCIS (Netherlands)

    Bower, G.H.; Rinck, M.

    2001-01-01

    Five experiments related to anaphor resolution to a classic memory variable, namely, interference created by multiple uses of a given object-concept, and by spatial distance of the referent from the reader's focus of attention. Participants memorized a diagram of a building with rooms containing

  20. Social dynamics interest groups in a model of spatial competition

    NARCIS (Netherlands)

    Tuinstra, J.; Sadiraj, V.; van Winden, F.A.A.M.

    2000-01-01

    A well-known result in spatial voting theory is that, for a one-dimensional issue space and under certain mild conditions, political parties choose platforms coinciding with the median voter's position. This result does not carry over to multi-dimensional issue spaces however, since then an

  1. Prediction of water temperature metrics using spatial modelling in ...

    African Journals Online (AJOL)

    Water temperature regime dynamics should be viewed regionally, where regional divisions have an inherent underpinning by an understanding of natural thermal variability. The aim of this research was to link key water temperature metrics to readily-mapped environmental surrogates, and to produce spatial images of ...

  2. 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)

  3. Modeling spatial pattern of deforestation using GIS and logistic ...

    African Journals Online (AJOL)

    This study aimed to predict spatial distribution of deforestation and detects factors influencing forest degradation of Northern forests of Ilam province. For this purpose, effects of six factors including distance from road and settlement areas, forest fragmentation index, elevation, slope and distance from the forest edge on the ...

  4. Establishment and Application of Coalmine Gas Prediction Model Based on Multi-Sensor Data Fusion Technology

    Directory of Open Access Journals (Sweden)

    Wenyu Lv

    2014-04-01

    Full Text Available Undoubtedly an accident involving gas is one of the greater disasters that can occur in a coalmine, thus being able to predict when an accident involving gas might occur is an essential aspect in loss prevention and the reduction of safety hazards. However, the traditional methods concerning gas safety prediction is hindered by multi-objective and non-continuous problem. The coalmine gas prediction model based on multi-sensor data fusion technology (CGPM-MSDFT was established through analysis of accidents involving gas using artificial neural network to fuse multi- sensor data, using an improved algorithm designed to train the network and using an early stop method to resolve the over-fitting problem, the network test and field application results show that this model can provide a new direction for research into predicting the likelihood of a gas related incident within a coalmine. It will have a broad application prospect in coal mining.

  5. Establishment of tunnel-boring machine disk cutter rock-breaking model from energy perspective

    Directory of Open Access Journals (Sweden)

    Liwei Song

    2015-12-01

    Full Text Available As the most important cutting tools during tunnel-boring machine tunneling construction process, V-type disk cutter’s rock-breaking mechanism has been researched by many scholars all over the world. Adopting finite element method, this article focused on the interaction between V-type disk cutters and the intact rock to carry out microscopic parameter analysis methods: first, the stress model of rock breaking was established through V-type disk cutter motion trajectory analysis; second, based on the incremental theorem of the elastic–plastic theory, the strain model of the relative changes of rock displacement during breaking process was created. According to the principle of admissible work by energy method of the elastic–plastic theory to analyze energy transfer rules in the process of breaking rock, rock-breaking force of the V-type disk cutter could be regarded as the external force in the rock system. Finally, by taking the rock system as the reference object, the total potential energy equivalent model of rock system was derived to obtain the forces of the three directions acting on V-type disk cutter during the rock-breaking process. This derived model, which has been proved to be effective and scientific through comparisons with some original force models and by comparative analysis with experimental data, also initiates a new research strategy taking the view of the micro elastic–plastic theory to study the rock-breaking mechanism.

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

    Science.gov (United States)

    Azam, Mohammad; Rahman, Zillur; Talib, Faisal; Singh, K J

    2012-01-01

    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 patient satisfaction. The authors use an extensive in-depth healthcare quality literature review, discerning gaps via a critical analysis in relation to their overall impact on patient management, while identifying an integrated quality model acceptable to hospital staff. The article provides insights into contemporary HCE quality parameters by critically analyzing relevant literature. It also evolves and proposes an integrated HCE-quality model. Owing to HCE confidentiality, especially regarding patient data, information cannot be accessed. The integrated quality model parameters have practical utility for healthcare service managers. However, further studies may be required to refine and integrate newer parameters to ensure continuous quality improvement. This article adds a new perspective to understanding quality parameters and suggests an integrated quality model that has practical value for maintaining HCE service quality to benefit many stakeholders.

  7. Establishing a Numerical Modeling Framework for Hydrologic Engineering Analyses of Extreme Storm Events

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xiaodong; Hossain, Faisal; Leung, L. Ruby

    2017-08-01

    In this study a numerical modeling framework for simulating extreme storm events was established using the Weather Research and Forecasting (WRF) model. Such a framework is necessary for the derivation of engineering parameters such as probable maximum precipitation that are the cornerstone of large water management infrastructure design. Here this framework was built based on a heavy storm that occurred in Nashville (USA) in 2010, and verified using two other extreme storms. To achieve the optimal setup, several combinations of model resolutions, initial/boundary conditions (IC/BC), cloud microphysics and cumulus parameterization schemes were evaluated using multiple metrics of precipitation characteristics. The evaluation suggests that WRF is most sensitive to IC/BC option. Simulation generally benefits from finer resolutions up to 5 km. At the 15km level, NCEP2 IC/BC produces better results, while NAM IC/BC performs best at the 5km level. Recommended model configuration from this study is: NAM or NCEP2 IC/BC (depending on data availability), 15km or 15km-5km nested grids, Morrison microphysics and Kain-Fritsch cumulus schemes. Validation of the optimal framework suggests that these options are good starting choices for modeling extreme events similar to the test cases. This optimal framework is proposed in response to emerging engineering demands of extreme storm events forecasting and analyses for design, operations and risk assessment of large water infrastructures.

  8. Establishment of a multi-species biofilm model to evaluate chlorhexidine efficacy.

    Science.gov (United States)

    Touzel, R E; Sutton, J M; Wand, M E

    2016-02-01

    Chronic infections, for example, diabetic foot ulcers, have a large impact in terms of patient morbidity and mortality. These wounds are characterized by complex polymicrobial communities of bacteria, which may include a number of difficult-to-eradicate multidrug-resistant pathogens. To establish a multi-species biofilm model to test the efficacy of chlorhexidine and chlorhexidine-containing formulas in eradication of polymicrobial biofilms. A Centers for Disease Control and Prevention bioreactor was used to establish a multi-species biofilm incorporating Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus and Enterococcus faecalis with equal numbers of each pathogen. This model was used to test the effectiveness of chlorhexidine at controlling the pre-formed biofilm. Chlorhexidine digluconate (CHD) was added to the bioreactor at a range of concentrations. K. pneumoniae and P. aeruginosa survived within multi-species biofilms, up to and including 4% CHD, whereas S. aureus was reduced to below the level of detection at 1%. Wiping the biofilm-containing coupons from the bioreactor with chlorhexidine-containing medical wipes resulted in >3 to 8log10 reduction), but had minimal effect (<3log10) against the other species tested. The study demonstrates that the effectiveness of chlorhexidine may be limited in settings where it is required to act on multi-species biofilms. This may compromise the ability of chlorhexidine to control the infection and spread of these pathogens. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

  9. Establishing an in vivo model of canine prostate carcinoma using the new cell line CT1258

    International Nuclear Information System (INIS)

    Fork, Melani AM; Bullerdiek, Jörn; Nolte, Ingo; Escobar, Hugo Murua; Soller, Jan T; Sterenczak, Katharina A; Willenbrock, Saskia; Winkler, Susanne; Dorsch, Martina; Reimann-Berg, Nicola; Hedrich, Hans J

    2008-01-01

    Prostate cancer is a frequent finding in man. In dogs, malignant disease of the prostate is also of clinical relevance, although it is a less common diagnosis. Even though there are numerous differences in origin and development of the disease, man and dog share many similarities in the pathological presentation. For this reason, the dog might be a useful animal model for prostate malignancies in man. Although prostate cancer is of great importance in veterinary medicine as well as in comparative medicine, there are only few cell lines available. Thus, it was the aim of the present study to determine whether the formerly established prostate carcinoma cell line CT1258 is a suitable tool for in vivo testing, and to distinguish the growth pattern of the induced tumours. For characterisation of the in vivo behaviour of the in vitro established canine prostate carcinoma cell line CT1258, cells were inoculated in 19 NOD.CB17-Prkdc Scid /J (in the following: NOD-Scid) mice, either subcutaneously or intraperitoneally. After sacrifice, the obtained specimens were examined histologically and compared to the pattern of the original tumour in the donor. Cytogenetic investigation was performed. The cell line CT 1258 not only showed to be highly tumourigenic after subcutaneous as well as intraperitoneal inoculation, but also mimicked the behaviour of the original tumour. Tumours induced by inoculation of the cell line CT1258 resemble the situation in naturally occurring prostate carcinoma in the dog, and thus could be used as in vivo model for future studies

  10. [Establishment of model of traditional Chinese medicine injections post-marketing safety monitoring].

    Science.gov (United States)

    Guo, Xin-E; Zhao, Yu-Bin; Xie, Yan-Ming; Zhao, Li-Cai; Li, Yan-Feng; Hao, Zhe

    2013-09-01

    To establish a nurse based post-marketing safety surveillance model for traditional Chinese medicine injections (TCMIs). A TCMIs safety monitoring team and a research hospital team engaged in the research, monitoring processes, and quality control processes were established, in order to achieve comprehensive, timely, accurate and real-time access to research data, to eliminate errors in data collection. A triage system involving a study nurse, as the first point of contact, clinicians and clinical pharmacists was set up in a TCM hospital. Following the specified workflow involving labeling of TCM injections and using improved monitoring forms it was found that there were no missing reports at the ratio of error was zero. A research nurse as the first and main point of contact in post-marketing safety monitoring of TCM as part of a triage model, ensures that research data collected has the characteristics of authenticity, accuracy, timeliness, integrity, and eliminate errors during the process of data collection. Hospital based monitoring is a robust and operable process.

  11. Establishment of a rat model of portal vein ligation combined with in situ splitting.

    Science.gov (United States)

    Yao, Libin; Li, Chonghui; Ge, Xinlan; Wang, Hongdong; Xu, Kesen; Zhang, Aiqun; Dong, Jiahong

    2014-01-01

    Portal vein ligation (PVL) combined with in situ splitting (ISS) has been shown to induce remarkable liver regeneration in patients. The purpose of this study was to establish a model of PVL+ISS in rats for exploring the possible mechanisms of liver regeneration using these techniques. Rats were randomly assigned to three experimental groups: selective PVL, selective PVL+ISS and sham operation. The hepatic regeneration rate (HRR), Ki-67, liver biochemical determinations and histopathology were assessed at 24, 48, and 72 h and 7 days after the operation. The microcirculation of the median lobes before and after ISS was examined by laser speckle contrast imaging. Meanwhile, cytokines such as TNF-α, IL-6, HGF and HSP70 in regenerating liver lobes at 24 h was investigated by RT-PCR and ELISA. The HRR of PVL+ISS was much higher than that of the PVL at 72 h and 7 days after surgery (pprotein levels of TNF-α, IL-6 and HGF in regenerating liver lobes were higher in the PVL+ISS than the PVL alone. The higher HRR in the PVL+ISS compared with the PVL confirmed that we had successfully established a PVL+ISS model in rats. The possible mechanisms included the reduced microcirculation blood perfusion of the left median lobe and up-regulation of cytokines in the regenerating lobes after ISS.

  12. Establishment of a blue light damage model of human retinal pigment epithelial cells in vitro.

    Science.gov (United States)

    Su, G; Cai, S J; Gong, X; Wang, L L; Li, H H; Wang, L M

    2016-06-24

    To establish a blue-light damage model of human retinal pigment epithelium (RPE). Fourth-generation human RPE cells were randomly divided into two groups. In group A, cells were exposed to blue light (2000 ± 500 lux) for 0 (control), 3, 6, 9, and 12 h, and cell culture was stopped after 12 h. In group B, cells were exposed to blue light at the same intensity and time periods, but cell culture was stopped after 24 h. TdT-mediated dUTP nick-end labeling (TUNEL) assay was performed to determine the most suitable illuminating time with apoptotic index. Flow cytometry was used to determine apoptotic ratio of RPEs. In group A, the apoptotic index of cells that received 6, 9 and 12 h of blue light was higher than that of control. The apoptotic index of cells receiving 9 and 12 h was higher than that of 6 h (P = 0.000). In group B, the apoptotic index and RPE cell apoptosis ratio of cells exposed to 6, 9 and 12 h of blue light were higher than that of 3 h (P = 0.000); and cells receiving 9 and 12 h had higher values than that of 6 h. This study demonstrated that the best conditions to establish a blue light damage model of human retinal pigment epithelial cells in vitro are 2000 ± 500 lux light intensity for 6 h, with 24 h of cell culture post-exposure.

  13. Establishment and characterization of a differentiated epithelial cell culture model derived from the porcine cervix uteri

    Directory of Open Access Journals (Sweden)

    Miessen Katrin

    2012-03-01

    Full Text Available Abstract Background Cervical uterine epithelial cells maintain a physiological and pathogen-free milieu in the female mammalian reproductive tract and are involved in sperm-epithelium interaction. Easily accessible, differentiated model systems of the cervical epithelium are not yet available to elucidate the underlying molecular mechanisms within these highly specialized cells. Therefore, the aim of the study was to establish a cell culture of the porcine cervical epithelium representing in vivo-like properties of the tissue. Results We tested different isolation methods and culture conditions and validated purity of the cultured cells by immunohistochemistry against keratins. We could reproducibly culture pure epithelial cells from cervical tissue explants. Based on a morphology score and the WST-1 Proliferation Assay, we optimized the growth medium composition. Primary porcine cervical cells performed best in conditioned Ham's F-12, containing 10% FCS, EGF and insulin. After cultivation in an air-liquid interface for three weeks, the cells showed a discontinuously multilayered phenotype. Finally, differentiation was validated via immunohistochemistry against beta catenin. Mucopolysaccharide production could be shown via alcian blue staining. Conclusions We provide the first suitable protocol to establish a differentiated porcine epithelial model of the cervix uteri, based on easily accessible cells using slaughterhouse material.

  14. Establishment and characterization of a differentiated epithelial cell culture model derived from the porcine cervix uteri.

    Science.gov (United States)

    Miessen, Katrin; Einspanier, Ralf; Schoen, Jennifer

    2012-03-19

    Cervical uterine epithelial cells maintain a physiological and pathogen-free milieu in the female mammalian reproductive tract and are involved in sperm-epithelium interaction. Easily accessible, differentiated model systems of the cervical epithelium are not yet available to elucidate the underlying molecular mechanisms within these highly specialized cells. Therefore, the aim of the study was to establish a cell culture of the porcine cervical epithelium representing in vivo-like properties of the tissue. We tested different isolation methods and culture conditions and validated purity of the cultured cells by immunohistochemistry against keratins. We could reproducibly culture pure epithelial cells from cervical tissue explants. Based on a morphology score and the WST-1 Proliferation Assay, we optimized the growth medium composition. Primary porcine cervical cells performed best in conditioned Ham's F-12, containing 10% FCS, EGF and insulin. After cultivation in an air-liquid interface for three weeks, the cells showed a discontinuously multilayered phenotype. Finally, differentiation was validated via immunohistochemistry against beta catenin. Mucopolysaccharide production could be shown via alcian blue staining. We provide the first suitable protocol to establish a differentiated porcine epithelial model of the cervix uteri, based on easily accessible cells using slaughterhouse material.

  15. A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation

    Directory of Open Access Journals (Sweden)

    T. Skaugen

    2016-09-01

    Full Text Available Snow is an important and complicated element in hydrological modelling. The traditional catchment hydrological model with its many free calibration parameters, also in snow sub-models, is not a well-suited tool for predicting conditions for which it has not been calibrated. Such conditions include prediction in ungauged basins and assessing hydrological effects of climate change. In this study, a new model for the spatial distribution of snow water equivalent (SWE, parameterized solely from observed spatial variability of precipitation, is compared with the current snow distribution model used in the operational flood forecasting models in Norway. The former model uses a dynamic gamma distribution and is called Snow Distribution_Gamma, (SD_G, whereas the latter model has a fixed, calibrated coefficient of variation, which parameterizes a log-normal model for snow distribution and is called Snow Distribution_Log-Normal (SD_LN. The two models are implemented in the parameter parsimonious rainfall–runoff model Distance Distribution Dynamics (DDD, and their capability for predicting runoff, SWE and snow-covered area (SCA is tested and compared for 71 Norwegian catchments. The calibration period is 1985–2000 and validation period is 2000–2014. Results show that SD_G better simulates SCA when compared with MODIS satellite-derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" and giving spurious positive trends in SWE, typical for SD_LN, is prevented. The precision of runoff simulations using SD_G is slightly inferior, with a reduction in Nash–Sutcliffe and Kling–Gupta efficiency criterion of 0.01, but it is shown that the high precision in runoff prediction using SD_LN is accompanied with erroneous simulations of SWE.

  16. [Establishment of Schatzker classification digital models of tibial plateau fractures and its application on virtual surgery].

    Science.gov (United States)

    Liu, Yong-gang; Zuo, Li-xin; Pei, Guo-xian; Dai, Ke; Sang, Jing-wei

    2013-08-20

    To explore the establishment of Schatzker classification digital model of tibial plateau fractures and its application in virtual surgery. Proximal tibial of one healthy male volunteer was examined with 64-slice spiral computed tomography (CT). The data were processed by software Mimics 10.01 and a model of proximal tibia was reconstructed. According to the Schatzker classification criteria of tibial plateau fractures, each type of fracture model was simulated.Screen-captures of fracture model were saved from different directions.Each type of fracture model was exported as video mode.Fracture model was imported into FreeForm modeling system.With a force feedback device, a surgeon could conduct virtual fracture operation simulation.Utilizing the GHOST of FreeForm modeling system, the software of virtual cutting, fracture reduction and fixation was developed.With a force feedback device PHANTOM, a surgeon could manipulate virtual surgical instruments and fracture classification model and simulate surgical actions such as assembly of surgical instruments, drilling, implantation of screw, reduction of fracture, bone grafting and fracture fixation, etc. The digital fracture model was intuitive, three-dimensional and realistic and it had excellent visual effect.Fracture could be observed and charted from optional direction and angle.Fracture model could rotate 360 ° in the corresponding video mode. The virtual surgical environment had a strong sense of reality, immersion and telepresence as well as good interaction and force feedback function in the FreeForm modeling system. The user could make the corresponding decisions about surgical method and choice of internal fixation according to the specific type of tibial plateau fracture as well as repeated operational practice in virtual surgery system. The digital fracture model of Schatzker classification is intuitive, three-dimensional, realistic and dynamic. The virtual surgery systems of Schatzker classifications make

  17. Spatial variability in compartmental fate modelling : Linking fugacity models and GIS.

    Science.gov (United States)

    Wania, F

    1996-03-01

    A new approach is presented which is designed to address the spatial heterogeneity of the environment in compartmental mass balance models of chemical fate in the environment. It rests on the assumption of chemical equilibration within one phase despite prevailing environmental heterogeneity. Composite D- and Z-values are derived from sub-unit specific environmental parameters and are used to solve mass balance equations which can be adopted essentially unchanged from existing compartmental fugacity models. With the resulting common fugacity value for each compartment, sub-unit specific concentrations and process rates can be calculated. The approach is illustrated using the QWASI lake model to calculate the fate of hexachlorobenzene in a hypothetical lake sub-divided in four distinct sub-units. The approach allows the subdivision of each compartment in a large number of sub-units with distinct environmental characteristics without substantially increasing model complexity. This is a necessary condition for linking fugacity models to geographical information systems.

  18. A Unified 3D Spatial Data Model for Surface and Subsurface Spatial ...

    African Journals Online (AJOL)

    user

    surface. LoD maps for surface and subsurface integration exist for most city centres but the 3D component is lacking and this ... the integration of surface and subsurface models are discussed and a geometric, topological 3D object oriented model is sug- gested. .... dimensional (3D) continuous geological stratigraphy,.

  19. Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

    Directory of Open Access Journals (Sweden)

    Goovaerts Pierre

    2004-07-01

    Full Text Available Abstract Background Complete Spatial Randomness (CSR is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new

  20. Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

    Science.gov (United States)

    Miller, L. D.; Tom, C.; Nualchawee, K.

    1977-01-01

    A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

  1. Spatial Multiplication Model as an alternative to the Point Model in Neutron Multiplicity Counting

    Energy Technology Data Exchange (ETDEWEB)

    Hauck, Danielle K. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Henzl, Vladimir [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2014-03-26

    The point model is commonly used in neutron multiplicity counting to relate the correlated neutron detection rates (singles, doubles, triples) to item properties (mass, (α,n) reaction rate and neutron multiplication). The point model assumes that the probability that a neutron will induce fission is a constant across the physical extent of the item. However, in reality, neutrons near the center of an item have a greater probability of inducing fission then items near the edges. As a result, the neutron multiplication has a spatial distribution.

  2. Estimating the Impact of Urbanization on Air Quality in China Using Spatial Regression Models

    OpenAIRE

    Fang, Chuanglin; Liu, Haimeng; Li, Guangdong; Sun, Dongqi; Miao, Zhuang

    2015-01-01

    Urban air pollution is one of the most visible environmental problems to have accompanied China’s rapid urbanization. Based on emission inventory data from 2014, gathered from 289 cities, we used Global and Local Moran’s I to measure the spatial autorrelation of Air Quality Index (AQI) values at the city level, and employed Ordinary Least Squares (OLS), Spatial Lag Model (SAR), and Geographically Weighted Regression (GWR) to quantitatively estimate the comprehensive impact and spatial variati...

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

    DEFF Research Database (Denmark)

    Møller, Jesper; Rasmussen, Jakob Gulddahl

    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, i.e. each new point is generated given the previous points. Under this model...... points is such that the dependent cluster point is likely to occur closely to a previous cluster point. We demonstrate the flexibility of the model for producing point patterns with linear structures, and propose to use the model as the likelihood in a Bayesian setting when analyzing a spatial point...... pattern exhibiting linear structures but where the exact mechanism responsible for the formations of lines is unknown. We illustrate this methodology by analyzing two spatial point pattern data sets (locations of bronze age graves in Denmark and locations of mountain tops in Spain) without knowing which...

  4. Establishing a coherent and replicable measurement model of the Edinburgh Postnatal Depression Scale.

    Science.gov (United States)

    Martin, Colin R; Redshaw, Maggie

    2018-03-23

    The 10-item Edinburgh Postnatal Depression Scale (EPDS) is an established screening tool for postnatal depression. Inconsistent findings in factor structure and replication difficulties have limited the scope of development of the measure as a multi-dimensional tool. The current investigation sought to robustly determine the underlying factor structure of the EPDS and the replicability and stability of the most plausible model identified. A between-subjects design was used. EPDS data were collected postpartum from two independent cohorts using identical data capture methods. Datasets were examined with confirmatory factor analysis, model invariance testing and systematic evaluation of relational and internal aspects of the measure. Participants were two samples of postpartum women in England assessed at three months (n = 245) and six months (n = 217). The findings showed a three-factor seven-item model of the EPDS offered an excellent fit to the data, and was observed to be replicable in both datasets and invariant as a function of time point of assessment. Some EPDS sub-scale scores were significantly higher at six months. The EPDS is multi-dimensional and a robust measurement model comprises three factors that are replicable. The potential utility of the sub-scale components identified requires further research to identify a role in contemporary screening practice. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  5. Sparse modeling of spatial environmental variables associated with asthma

    OpenAIRE

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

    2014-01-01

    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 5–50 years over a three-year period. Each patient’s ...

  6. Modeling Spatial Maps Inspired by the Hippocampal System

    Science.gov (United States)

    2015-08-24

    landmark cues and path integration based on self-motion ( dead - reckoning ). The path integration system is probably separate from the megamap itself but...system is known to use two types of information for determining spatial location, namely, landmark cues and path integration based on self-motion ( dead ... reckoning ). The path integration system is probably separate from the megamap itself but provides an input to the map. One key requirement for

  7. Spatial modeling of bicycle activity at signalized intersections

    OpenAIRE

    Strauss, Jillian; Miranda-Moreno, Luis F.

    2013-01-01

    This paper presents a methodology to investigate the link between bicycle activity and built environment, road and transit network characteristics, and bicycle facilities while also accounting for spatial autocorrelation between intersections. The methodology includes the normalization of manual cyclist counts to average seasonal daily volumes (ASDV), taking into account temporal variations and using hourly, daily, and monthly expansion factors obtained from automatic bicycle count data. To c...

  8. An efficient strategy for establishing a model of sensorineural deafness in rats

    Directory of Open Access Journals (Sweden)

    Long Ma

    2015-01-01

    Full Text Available Ototoxic drugs can be used to produce a loss of cochlear hair cells to create animal models of deafness. However, to the best of our knowledge, there is no report on the establishment of a rat deafness model through the combined application of aminoglycosides and loop diuretics. The aim of this study was to use single or combined administration of furosemide and kanamycin sulfate to establish rat models of deafness. The rats received intravenous injections of different doses of furosemide and/or intramuscular injections of kanamycin sulfate. The auditory brainstem response was measured to determine the hearing threshold after drug application. Immunocytochemistry and confocal microscopy were performed to evaluate inner ear morphology. In the group receiving combined administration of furosemide and kanamycin, the auditory brainstem response threshold showed significant elevation 3 days after administration, higher than that produced by furosemide or kanamycin alone. The hair cells showed varying degrees of injury, from the apical turn to the basal turn of the cochlea and from the outer hair cells to the inner hair cells. The spiral ganglion cells maintained a normal morphology during the first week after the hair cells completely disappeared, and then gradually degenerated. After 2 months, the majority of spiral ganglion cells disappeared, but a few remained. These findings demonstrate that the combined administration of furosemide and kanamycin has a synergistic ototoxic effect, and that these drugs can produce hair cell loss and hearing loss in rats. These findings suggest that even in patients with severe deafness, electronic cochlear implants may partially restore hearing.

  9. The development and refinement of models of less established and more established high school environmental service-learning programs in Florida

    Science.gov (United States)

    Malikova, Yuliya

    2005-07-01

    Environmental Service-Learning (Env. S-L) appears to show great promise and practitioners tout its benefits, although there have been fewer than ten studies in this emerging area of environmental education. The overall study purpose was to describe the nature, status, and effects of Grade 9--16 Env. S-L programs in Florida, and develop descriptive models of those programs. The purpose of Phase I was to describe these programs and associated partnerships. Based on Phase I results, the purpose of Phase II was to develop, compare, and refine models for less and more established high school programs. This study involved: (1) defining the population of Florida 9--16 Env. S-L programs (Phase I); (2) developing and administering program surveys (Phase I, quantitative); (3) analyzing Phase I survey data and identifications of options for Phase II (Intermediate stage); (4) designing and implementing methodology for further data collection (Phase II, qualitative); (5) refining and finalizing program models (Phase II, descriptive); and (6) summarizing program data, changes, and comparisons. This study revealed that Env. S-L has been practiced in a variety of ways at the high school and college levels in Florida. There, the number of high school programs, and participating teachers and students has been growing. Among others, major program features include block scheduling, indirect S-L activities, external funding sources, and formal and ongoing community partnerships. Findings based on self-reported program assessment results indicate that S-L has had positive effects on students across Furco's S-L outcome domains (i.e., academic achievement/success, school participation/behavior, carrier development, personal development, interpersonal development, ethical/moral development, and development of civic responsibility). Differences existed between less established and more established Env. S-L programs. Less established programs had relatively few participating teachers

  10. Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration.

    Science.gov (United States)

    Schliess, Freimut; Hoehme, Stefan; Henkel, Sebastian G; Ghallab, Ahmed; Driesch, Dominik; Böttger, Jan; Guthke, Reinhard; Pfaff, Michael; Hengstler, Jan G; Gebhardt, Rolf; Häussinger, Dieter; Drasdo, Dirk; Zellmer, Sebastian

    2014-12-01

    The impairment of hepatic metabolism due to liver injury has high systemic relevance. However, it is difficult to calculate the impairment of metabolic capacity from a specific pattern of liver damage with conventional techniques. We established an integrated metabolic spatial-temporal model (IM) using hepatic ammonia detoxification as a paradigm. First, a metabolic model (MM) based on mass balancing and mouse liver perfusion data was established to describe ammonia detoxification and its zonation. Next, the MM was combined with a spatial-temporal model simulating liver tissue damage and regeneration after CCl4 intoxication. The resulting IM simulated and visualized whether, where, and to what extent liver damage compromised ammonia detoxification. It allowed us to enter the extent and spatial patterns of liver damage and then calculate the outflow concentrations of ammonia, glutamine, and urea in the hepatic vein. The model was validated through comparisons with (1) published data for isolated, perfused livers with and without CCl4 intoxication and (2) a set of in vivo experiments. Using the experimentally determined portal concentrations of ammonia, the model adequately predicted metabolite concentrations over time in the hepatic vein during toxin-induced liver damage and regeneration in rodents. Further simulations, especially in combination with a simplified model of blood circulation with three ammonia-detoxifying compartments, indicated a yet unidentified process of ammonia consumption during liver regeneration and revealed unexpected concomitant changes in amino acid metabolism in the liver and at extrahepatic sites. The IM of hepatic ammonia detoxification considerably improves our understanding of the metabolic impact of liver disease and highlights the importance of integrated modeling approaches on the way toward virtual organisms. © 2014 The Authors. Hepatology published by Wiley on behalf of the American Association for the Study of Liver Diseases.

  11. Climate Change and Agricultural Productivity in Sub-Saharan Africa: A Spatial Sample Selection Model

    NARCIS (Netherlands)

    Ward, P.S.; Florax, R.J.G.M.; Flores-Lagunes, A.

    2014-01-01

    Using spatially explicit data, we estimate a cereal yield response function using a recently developed estimator for spatial error models when endogenous sample selection is of concern. Our results suggest that yields across Sub-Saharan Africa will decline with projected climatic changes, and that

  12. [Establish Assessment Model of 18 Years of Age in Chinese Han Population by Mandibular Third Molar].

    Science.gov (United States)

    Fan, Fei; Dai, Xin-hua; Wang, Liang; Li, Yuan; Zhang, Kui; Deng, Zhen-hua

    2016-02-01

    To explore the value of estimating chronologic age based on the grades of mandibular third molar development. To evaluate whether mandibular third molar could be used as an indicator for estimating the age under or over 18 years. The mineralization status of mandibular third molar of 1 845 individuals aged 10 - 30 was graded and marked based on Demirjian's classification of grades reformed by Orhan. Gender difference was examined by t-test. A cubic regression model was established to analyze the correlation between third molar and chronologic age. Each grade of age cumulative distribution diagram and ROC curve was respectively performed to evaluate the relationship between third molar and the age of 18. Using Bayes discriminant analysis, an equation was established for estimating the age of 18. The inner-rater reliability was 0.903. Statistical analysis showed a moderate correlation between age and grade. Significant differences of both genders were found only in grade D and H (P Third molar development shows a high correlation with age, and combined with other indicators, it can be used to estimate the age of 18.

  13. Establishment of primary cultures for mouse ameloblasts as a model of their lifetime

    International Nuclear Information System (INIS)

    Suzawa, Tetsuo; Itoh, Nao; Takahashi, Naoyuki; Katagiri, Takenobu; Morimura, Naoko; Kobayashi, Yasuna; Yamamoto, Toshinori; Kamijo, Ryutaro

    2006-01-01

    To understand how the properties of ameloblasts are spatiotemporally regulated during amelogenesis, two primary cultures of ameloblasts in different stages of differentiation were established from mouse enamel epithelium. Mouse primary ameloblasts (MPAs) prepared from immature enamel epithelium (MPA-I) could proliferate, whereas those from mature enamel epithelium (MPA-M) could not. MPA-M but not MPA-I caused apoptosis during culture. The mRNA expression of amelogenin, a marker of immature ameloblasts, was down-regulated, and that of enamel matrix serine proteiase-1, a marker of mature ameloblasts, was induced in MPA-I during culture. Using green fluorescence protein as a reporter, a visualized reporter system was established to analyze the promoter activity of the amelogenin gene. The region between -1102 bp and -261 bp was required for the reporter expression in MPA-I. These results suggest that MPAs are valuable in vitro models for investigation of ameloblast biology, and that the visualized system is useful for promoter analysis in MPAs

  14. Establishment of a general NAFLD scoring system for rodent models and comparison to human liver pathology.

    Directory of Open Access Journals (Sweden)

    Wen Liang

    Full Text Available The recently developed histological scoring system for non-alcoholic fatty liver disease (NAFLD by the NASH Clinical Research Network (NASH-CRN has been widely used in clinical settings, but is increasingly employed in preclinical research as well. However, it has not been systematically analyzed whether the human scoring system can directly be converted to preclinical rodent models. To analyze this, we systematically compared human NAFLD liver pathology, using human liver biopsies, with liver pathology of several NAFLD mouse models. Based upon the features pertaining to mouse NAFLD, we aimed at establishing a modified generic scoring system that is applicable to broad spectrum of rodent models.The histopathology of NAFLD was analyzed in several different mouse models of NAFLD to define generic criteria for histological assessment (preclinical scoring system. For validation of this scoring system, 36 slides of mouse livers, covering the whole spectrum of NAFLD, were blindly analyzed by ten observers. Additionally, the livers were blindly scored by one observer during two separate assessments longer than 3 months apart.The criteria macrovesicular steatosis, microvesicular steatosis, hepatocellular hypertrophy, inflammation and fibrosis were generally applicable to rodent NAFLD. The inter-observer reproducibility (evaluated using the Intraclass Correlation Coefficient between the ten observers was high for the analysis of macrovesicular steatosis and microvesicular steatosis (ICC = 0.784 and 0.776, all p<0.001, respectively and moderate for the analysis of hypertrophy and inflammation (ICC = 0.685 and 0.650, all p<0.001, respectively. The intra-observer reproducibility between the different observations of one observer was high for the analysis of macrovesicular steatosis, microvesicular steatosis and hypertrophy (ICC = 0.871, 0.871 and 0.896, all p<0.001, respectively and very high for the analysis of inflammation (ICC = 0.931, p

  15. Linking 3D spatial models of fuels and fire: Effects of spatial heterogeneity on fire behavior

    Science.gov (United States)

    Russell A. Parsons; William E. Mell; Peter McCauley

    2011-01-01

    Crownfire endangers fire fighters and can have severe ecological consequences. Prediction of fire behavior in tree crowns is essential to informed decisions in fire management. Current methods used in fire management do not address variability in crown fuels. New mechanistic physics-based fire models address convective heat transfer with computational fluid dynamics (...

  16. Evaluating habitat suitability for the establishment of Monochamus spp. through climate-based niche modeling.

    Science.gov (United States)

    Estay, Sergio A; Labra, Fabio A; Sepulveda, Roger D; Bacigalupe, Leonardo D

    2014-01-01

    Pine sawyer beetle species of the genus Monochamus are vectors of the nematode pest Bursaphelenchus xylophilus. The introduction of these species into new habitats is a constant threat for those regions where the forestry industry depends on conifers, and especially on species of Pinus. To obtain information about the potential risk of establishment of these insects in Chile, we performed climate-based niche modeling using data for five North American and four Eurasian Monochamus species using a Maxent approach. The most important variables that account for current distribution of these species are total annual precipitation and annual and seasonal average temperatures, with some differences between North American and Eurasian species. Projections of potential geographic distribution in Chile show that all species could occupy at least 37% of the area between 30° and 53°S, where industrial plantations of P. radiata are concentrated. Our results indicated that Chile seems more suitable for Eurasian than for North American species.

  17. LIDAR Point Cloud Data Extraction and Establishment of 3D Modeling of Buildings

    Science.gov (United States)

    Zhang, Yujuan; Li, Xiuhai; Wang, Qiang; Liu, Jiang; Liang, Xin; Li, Dan; Ni, Chundi; Liu, Yan

    2018-01-01

    This paper takes the method of Shepard’s to deal with the original LIDAR point clouds data, and generate regular grid data DSM, filters the ground point cloud and non ground point cloud through double least square method, and obtains the rules of DSM. By using region growing method for the segmentation of DSM rules, the removal of non building point cloud, obtaining the building point cloud information. Uses the Canny operator to extract the image segmentation is needed after the edges of the building, uses Hough transform line detection to extract the edges of buildings rules of operation based on the smooth and uniform. At last, uses E3De3 software to establish the 3D model of buildings.

  18. Evaluation of three different methods to establish animal models of Acanthamoeba keratitis.

    Science.gov (United States)

    Ren, Meiyu; Wu, Xinyi

    2010-01-01

    To produce animal models of Acanthamoeba keratitis and to evaluate the advantages and adaptation range of each of the three methods employed. Mice and Wistar rats in three groups of 15 rats and 15 mice each were used to establish the models. Right corneas in group A were scratched and challenged with Acanthamoeba. Those in group B were scratched and covered with contact lenses incubated with Acanthamoeba. Those in group C received an intrastromal injection of Acanthamoeba. Five rats and 5 mice in each group were used for histopathological investigations and the other 10 in each group were used for clinical evaluation. The models were evaluated by slit lamp examination, microscopic examination and culture of corneal scrapings, HE staining of corneal sections, and pathological scoring of the infections. Four rats and 6 mice in group A, 7 rats and 8 mice in group B, and 10 rats and 10 mice in group C developed typical Acanthamoeba keratitis. Corneal scratching alone has the lowest infection rate, while scratching and then covering with contaminated contact lenses has a moderate rate of infection and most closely mimics what happens in most human infections. Intrastromal injection of Acanthamoeba gives a much higher infection rate and more severe Acanthamoeba keratitis.

  19. Predictive spatio-temporal model for spatially sparse global solar radiation data

    International Nuclear Information System (INIS)

    André, Maïna; Dabo-Niang, Sophie; Soubdhan, Ted; Ould-Baba, Hanany

    2016-01-01

    This paper introduces a new approach for the forecasting of solar radiation series at a located station for very short time scale. We built a multivariate model in using few stations (3 stations) separated with irregular distances from 26 km to 56 km. The proposed model is a spatio temporal vector autoregressive VAR model specifically designed for the analysis of spatially sparse spatio-temporal data. This model differs from classic linear models in using spatial and temporal parameters where the available predictors are the lagged values at each station. A spatial structure of stations is defined by the sequential introduction of predictors in the model. Moreover, an iterative strategy in the process of our model will select the necessary stations removing the uninteresting predictors and also selecting the optimal p-order. We studied the performance of this model. The metric error, the relative root mean squared error (rRMSE), is presented at different short time scales. Moreover, we compared the results of our model to simple and well known persistence model and those found in literature. - Highlights: • A spatio-temporal VAR forecast model is used for spatially sparse data solar. • Lags and locations are selected by an optimization strategy. • Definition of spatial ordering of predictors influences forecasting results. • The model shows a better performance predictive at 30 min ahead in our context. • Benchmarking study shows a more accurate forecast at 1 h ahead with spatio-temporal VAR.

  20. Establishing an in vivo model of canine prostate carcinoma using the new cell line CT1258

    Directory of Open Access Journals (Sweden)

    Winkler Susanne

    2008-08-01

    Full Text Available Abstract Background Prostate cancer is a frequent finding in man. In dogs, malignant disease of the prostate is also of clinical relevance, although it is a less common diagnosis. Even though there are numerous differences in origin and development of the disease, man and dog share many similarities in the pathological presentation. For this reason, the dog might be a useful animal model for prostate malignancies in man. Although prostate cancer is of great importance in veterinary medicine as well as in comparative medicine, there are only few cell lines available. Thus, it was the aim of the present study to determine whether the formerly established prostate carcinoma cell line CT1258 is a suitable tool for in vivo testing, and to distinguish the growth pattern of the induced tumours. Methods For characterisation of the in vivo behaviour of the in vitro established canine prostate carcinoma cell line CT1258, cells were inoculated in 19 NOD.CB17-PrkdcScid/J (in the following: NOD-Scid mice, either subcutaneously or intraperitoneally. After sacrifice, the obtained specimens were examined histologically and compared to the pattern of the original tumour in the donor. Cytogenetic investigation was performed. Results The cell line CT 1258 not only showed to be highly tumourigenic after subcutaneous as well as intraperitoneal inoculation, but also mimicked the behaviour of the original tumour. Conclusion Tumours induced by inoculation of the cell line CT1258 resemble the situation in naturally occurring prostate carcinoma in the dog, and thus could be used as in vivo model for future studies.

  1. [Establishment of the Mathematical Model for PMI Estimation Using FTIR Spectroscopy and Data Mining Method].

    Science.gov (United States)

    Wang, L; Qin, X C; Lin, H C; Deng, K F; Luo, Y W; Sun, Q R; Du, Q X; Wang, Z Y; Tuo, Y; Sun, J H

    2018-02-01

    To analyse the relationship between Fourier transform infrared (FTIR) spectrum of rat's spleen tissue and postmortem interval (PMI) for PMI estimation using FTIR spectroscopy combined with data mining method. Rats were sacrificed by cervical dislocation, and the cadavers were placed at 20 ℃. The FTIR spectrum data of rats' spleen tissues were taken and measured at different time points. After pretreatment, the data was analysed by data mining method. The absorption peak intensity of rat's spleen tissue spectrum changed with the PMI, while the absorption peak position was unchanged. The results of principal component analysis (PCA) showed that the cumulative contribution rate of the first three principal components was 96%. There was an obvious clustering tendency for the spectrum sample at each time point. The methods of partial least squares discriminant analysis (PLS-DA) and support vector machine classification (SVMC) effectively divided the spectrum samples with different PMI into four categories (0-24 h, 48-72 h, 96-120 h and 144-168 h). The determination coefficient ( R ²) of the PMI estimation model established by PLS regression analysis was 0.96, and the root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV) were 9.90 h and 11.39 h respectively. In prediction set, the R ² was 0.97, and the root mean square error of prediction (RMSEP) was 10.49 h. The FTIR spectrum of the rat's spleen tissue can be effectively analyzed qualitatively and quantitatively by the combination of FTIR spectroscopy and data mining method, and the classification and PLS regression models can be established for PMI estimation. Copyright© by the Editorial Department of Journal of Forensic Medicine.

  2. Establishment of a rat model of portal vein ligation combined with in situ splitting.

    Directory of Open Access Journals (Sweden)

    Libin Yao

    Full Text Available BACKGROUND: Portal vein ligation (PVL combined with in situ splitting (ISS has been shown to induce remarkable liver regeneration in patients. The purpose of this study was to establish a model of PVL+ISS in rats for exploring the possible mechanisms of liver regeneration using these techniques. MATERIALS AND METHODS: Rats were randomly assigned to three experimental groups: selective PVL, selective PVL+ISS and sham operation. The hepatic regeneration rate (HRR, Ki-67, liver biochemical determinations and histopathology were assessed at 24, 48, and 72 h and 7 days after the operation. The microcirculation of the median lobes before and after ISS was examined by laser speckle contrast imaging. Meanwhile, cytokines such as TNF-α, IL-6, HGF and HSP70 in regenerating liver lobes at 24 h was investigated by RT-PCR and ELISA. RESULTS: The HRR of PVL+ISS was much higher than that of the PVL at 72 h and 7 days after surgery (p<0.01. The expression of Ki-67 in hepatocytes in the regenerating liver lobe was stronger in the PVL+ISS group than in the PVL group at 48 and 72 h (p<0.01. There was a significant reduction in microcirculation blood perfusion of the left median lobe before and after ISS. Liver biochemical determinations and histopathology demonstrated more severe hepatocyte injury in the PVL+ISS group. Both the mRNA levels of TNF-α and IL-6 and the protein levels of TNF-α, IL-6 and HGF in regenerating liver lobes were higher in the PVL+ISS than the PVL alone. CONCLUSIONS: The higher HRR in the PVL+ISS compared with the PVL confirmed that we had successfully established a PVL+ISS model in rats. The possible mechanisms included the reduced microcirculation blood perfusion of the left median lobe and up-regulation of cytokines in the regenerating lobes after ISS.

  3. Establishment of a rat model of craniocerebral blast injury induced by cabin explosion

    Directory of Open Access Journals (Sweden)

    Yan-teng LI

    2017-10-01

    Full Text Available Objective To establish a rat model of craniocerebral blast injury caused by the shock wave of cabin explosion. Methods Fifty male adult Sprague–Dawley rats were randomly divided into 5 groups (10 each: 3g, 5g, 8g TNT with vest groups, 5g TNT without vest group and control group. Uncased explosives of different equivalent were suspended in the cabin center. After anesthesia, with exception of control group, the rats were placed in prone position about 31 cm below the explosive, facing the explosive with or without vest. After the explosion, the survived rats were observed, serological and pathological examinations were performed at 3h, 1d and 3d after the explosion. Results In terms of tissue damage and mortality, compared with the control group, no obvious injury formed in rats of the 3g TNT with vest group, and all of them survived; Rats in 5g TNT with vest group showed mild lung injury, brain tissue edema, enlarged blood vessel, patchy hemorrhage on the brain surface, and with a mortality of 30%; Rats in 8g TNT with vest group showed serious organ damage with a mortality of 80%; Rats in 5g TNT without vest group suffered from severe lung injury, almost all died right after the explosion. Therefore, rats in 5g TNT with vest group were more in line with the experimental needs. Further serum and pathologic examinations showed that the brain water content increased, the serum neuron specific enolase (NSE and S-100β protein also increased markedly, and necrotic or apoptotic changes happened in the cortex and hippocampus neurons. Conclusion A stable animal model of craniocerebral blast injury may be established with rats in the case of chest and abdomen protected and then exposed to 5g TNT explosion in cabin. DOI: 10.11855/j.issn.0577-7402.2017.09.13

  4. [Establishment and Improvement of Portable X-Ray Fluorescence Spectrometer Detection Model Based on Wavelet Transform].

    Science.gov (United States)

    Li, Fang; Wang, Ji-hua; Lu, An-xiang; Han, Ping

    2015-04-01

    The concentration of Cr, Cu, Zn, As and Pb in soil was tested by portable X-ray fluorescence spectrometer. Each sample was tested for 3 times, then after using wavelet threshold noise filtering method for denoising and smoothing the spectra, a standard curve for each heavy metal was established according to the standard values of heavy metals in soil and the corresponding counts which was the average of the 3 processed spectra. The signal to noise ratio (SNR), mean square error (MSE) and information entropy (H) were taken to assess the effects of denoising when using wavelet threshold noise filtering method for determining the best wavelet basis and wavelet decomposition level. Some samples with different concentrations and H3 B03 (blank) were chosen to retest this instrument to verify its stability. The results show that: the best denoising result was obtained with the coif3 wavelet basis at the decomposition level of 3 when using the wavelet transform method. The determination coefficient (R2) range of the instrument is 0.990-0.996, indicating that a high degree of linearity was found between the contents of heavy metals in soil and each X-ray fluorescence spectral characteristic peak intensity with the instrument measurement within the range (0-1,500 mg · kg(-1)). After retesting and calculating, the results indicate that all the detection limits of the instrument are below the soil standards at national level. The accuracy of the model has been effectively improved, and the instrument also shows good precision with the practical application of wavelet transform to the establishment and improvement of X-ray fluorescence spectrometer detection model. Thus the instrument can be applied in on-site rapid screening of heavy metal in contaminated soil.

  5. Establishment of animal model for the analysis of cancer cell metastasis during radiotherapy

    International Nuclear Information System (INIS)

    Park, Jong Kuk; Jang, Su Jin; Kang, Sung Wook; Park, Sunhoo; Hwang, Sang-Gu; Kim, Wun-Jae; Kang, Joo Hyun; Um, Hong-Duck

    2012-01-01

    Γ-Ionizing radiation (IR) therapy is one of major therapeutic tools in cancer treatment. Nevertheless, γ-IR therapy failed due to occurrence of metastasis, which constitutes a significant obstacle in cancer treatment. The main aim of this investigation was to construct animal model which present metastasis during radiotherapy in a mouse system in vivo and establishes the molecular mechanisms involved. The C6L transfectant cell line expressing firefly luciferase (fLuc) was treated with γ-IR, followed by immunoblotting, zymography and invasion assay in vitro. We additionally employed the C6L transfectant cell line to construct xenografts in nude mice, which were irradiated with γ-IR. Irradiated xenograft-containing mice were analyzed via survival curves, measurement of tumor size, and bioluminescence imaging in vivo and ex vivo. Metastatic lesions in organs of mice were further assessed using RT-PCR, H & E staining and immunohistochemistry. γ-IR treatment of C6L cells induced epithelial-mesenchymal transition (EMT) and increased cell invasion. In irradiated xenograft-containing mice, tumor sizes were decreased dramatically and survival rates extended. Almost all non-irradiated xenograft-containing control mice had died within 4 weeks. However, we also observed luminescence signals in about 22.5% of γ-IR-treated mice. Intestines or lungs of mice displaying luminescence signals contained several lesions, which expressed the fLuc gene and presented histological features of cancer tissues as well as expression of EMT markers. These findings collectively indicate that occurrences of metastases during γ-IR treatment accompanied induction of EMT markers, including increased MMP activity. Establishment of a murine metastasis model during γ-IR treatment should aid in drug development against cancer metastasis and increase our understanding of the mechanisms underlying the metastatic process

  6. Establishment of Orthotopic Xuanwei Lung Cancer SCID Mouse Model 
and Analysis of Biological Properties

    Directory of Open Access Journals (Sweden)

    Yongchun ZHOU

    2012-08-01

    Full Text Available Background and objective The incidence of Xuanwei lung cancer ranks first in China, and its pathogenesis requires in-depth investigation. This study aims to establish an orthotopic Xuanwei lung cancer severe combined immunodeficiency (SCID mouse model and to provide a basic experimental platform for further study. Methods The Xuanwei lung cancer cell line XWLC-05 was inoculated into the lung tissue of SCID mice in high and low doses. The tumor formation rates, tumor characteristics, spontaneous metastases, and survival times of the mice were observed, taking a subcutaneously transplanted tumor as control. Results The tumor formation rates of the orthotopic transplantation of lung cancer cells in high and low doses were 81% and 83%, respectively, among which mice in the high-dose group appeared cachectic on day 13. Extensive invasion and adhesion were observed in the contralateral lung and thoracic cavity, but no distant metastasis was exhibited. Mice with low-dose cells in the orthotopic transplantation group appeared cachectic and distant metastasis occurred on day 25. The tumor formation rates in the subcutaneous inoculation group by the high and low doses of cells were 100% and 94.5%, respectively, and no distant metastasis was observed. The rate of metastasis within the orthotopic transplantation group and between the orthotopic and subcutaneous inoculation groups showed a significant difference (P<0.05. A significant difference was indicated by the survival rate within and between the groups (P<0.001. Conclusion We successfully established an orthotopic XWLC SCID mouse model, which lays the foundation for a more in-depth study.

  7. Developing a modelling for the spatial data infrastructure

    CSIR Research Space (South Africa)

    Hjelmager, J

    2005-07-01

    Full Text Available . The models cannot be seen as a final result, but more as a small step towards a model that defines the previously mentioned overall model of the SDI and its technical characteristics. During the model development process, the roles of the different actors...

  8. [The replacement therapy of rPTH(1-84) in established rat model of hypothyroidism].

    Science.gov (United States)

    Ding, Zhiwei; Li, Tiancheng; Liu, Yuhe; Xiao, Shuifang

    2015-12-01

    To investigate the replacement therapy of rPTH(1-84) (recombinant human parathyroid hormone (1-84)) to hypothyroidism in established rat model. Rat model of hypothyroidism was established by resecting parathyroids. A total of 30 rats with removal of parathyroids were divided into 6 groups randomly, 5 in each group, and applied respectively with saline injection (negative control group), calcitriol treatment (positive control group) and quadripartite PTH administration with dose of 20, 40, 80 and 160 µg/kg (experimental groups). Saline and rPTH(1-84) were injected subcutaneously daily. Calcitriol was gavaged once a day. Sham-operation was conducted in 5 rats of negative control group. To verify the authenticity of the rat model with hypothyroidism, the serum was insolated centrifugally from rat blood that was obtained from angular vein at specific time to measure calcium and phosphorus concentration. Urine in 12 hours was collected by metabolic cages and the calcium concentration was measured. After 10-week drug treatment, the experiment was terminated and bilateral femoral bone and L2-5 lumbar vertebra were removed from rats. Bone mineral density (BMD)of bilateral femoral bone and lumbar vertebra was analyzed by dual X-ray absorptiometry (DXA). The concentration of bone alkaline phosphatase (BALP) in serum was determined by radioimmunoassay. The rat model with hypothyroidism was obtained by excising parathyroid gland and was verified by monitoring calcium and phosphorus concentration subsequently. Administration of rPTH(1-84) in the dose of 80 or 160 µg/kg made serum calcium and phosphorus back to normal levels, with no significant difference between the doses (P>0.05). The BMD in each group of rats with rPTH(1-84) administration was increased significantly (Prats of maximum rPTH(1-84) injection group (160 µg/kg) were higher than those of normal control group (Prats treated with calcitriol had normal calcium levels and showed the increase of BMD and phosphorus

  9. Comparative analysis of elements and models of implementation in local-level spatial plans in Serbia

    Directory of Open Access Journals (Sweden)

    Stefanović Nebojša

    2017-01-01

    Full Text Available Implementation of local-level spatial plans is of paramount importance to the development of the local community. This paper aims to demonstrate the importance of and offer further directions for research into the implementation of spatial plans by presenting the results of a study on models of implementation. The paper describes the basic theoretical postulates of a model for implementing spatial plans. A comparative analysis of the application of elements and models of implementation of plans in practice was conducted based on the spatial plans for the local municipalities of Arilje, Lazarevac and Sremska Mitrovica. The analysis includes four models of implementation: the strategy and policy of spatial development; spatial protection; the implementation of planning solutions of a technical nature; and the implementation of rules of use, arrangement and construction of spaces. The main results of the analysis are presented and used to give recommendations for improving the elements and models of implementation. Final deliberations show that models of implementation are generally used in practice and combined in spatial plans. Based on the analysis of how models of implementation are applied in practice, a general conclusion concerning the complex character of the local level of planning is presented and elaborated. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 36035: Spatial, Environmental, Energy and Social Aspects of Developing Settlements and Climate Change - Mutual Impacts and Grant no. III 47014: The Role and Implementation of the National Spatial Plan and Regional Development Documents in Renewal of Strategic Research, Thinking and Governance in Serbia

  10. Revealing spatially heterogeneous relaxation in a model nanocomposite

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, Shiwang; Bocharova, Vera [Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Mirigian, Stephen; Schweizer, Kenneth S. [Department of Materials Science and Chemistry, Frederick Seitz Materials Research Laboratory, University of Illinois, Urbana, Illinois 61801 (United States); Carrillo, Jan-Michael Y.; Sumpter, Bobby G. [Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Sokolov, Alexei P., E-mail: sokolov@utk.edu [Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Chemistry, Department of Physics and Astronomy, University of Tennessee, Knoxville, Tennessee 37996 (United States)

    2015-11-21

    The detailed nature of spatially heterogeneous dynamics of glycerol-silica nanocomposites is unraveled by combining dielectric spectroscopy with atomistic simulation and statistical mechanical theory. Analysis of the spatial mobility gradient shows no “glassy” layer, but the α-relaxation time near the nanoparticle grows with cooling faster than the α-relaxation time in the bulk and is ∼20 times longer at low temperatures. The interfacial layer thickness increases from ∼1.8 nm at higher temperatures to ∼3.5 nm upon cooling to near bulk T{sub g}. A real space microscopic description of the mobility gradient is constructed by synergistically combining high temperature atomistic simulation with theory. Our analysis suggests that the interfacial slowing down arises mainly due to an increase of the local cage scale barrier for activated hopping induced by enhanced packing and densification near the nanoparticle surface. The theory is employed to predict how local surface densification can be manipulated to control layer dynamics and shear rigidity over a wide temperature range.

  11. Temporal and spatial distribution characteristics of water resources in Guangdong Province based on a cloud model

    Directory of Open Access Journals (Sweden)

    Qi Zhou

    2015-10-01

    Full Text Available With a focus on the difficulty of quantitatively describing the degree of nonuniformity of temporal and spatial distributions of water resources, quantitative research was carried out on the temporal and spatial distribution characteristics of water resources in Guangdong Province from 1956 to 2000 based on a cloud model. The spatial variation of the temporal distribution characteristics and the temporal variation of the spatial distribution characteristics were both analyzed. In addition, the relationships between the numerical characteristics of the cloud model of temporal and spatial distributions of water resources and precipitation were also studied. The results show that, using a cloud model, it is possible to intuitively describe the temporal and spatial distribution characteristics of water resources in cloud images. Water resources in Guangdong Province and their temporal and spatial distribution characteristics are differentiated by their geographic locations. Downstream and coastal areas have a larger amount of water resources with greater uniformity and stronger stability in terms of temporal distribution. Regions with more precipitation possess larger amounts of water resources, and years with more precipitation show greater nonuniformity in the spatial distribution of water resources. The correlation between the nonuniformity of the temporal distribution and local precipitation is small, and no correlation is found between the stability of the nonuniformity of the temporal and spatial distributions of water resources and precipitation. The amount of water resources in Guangdong Province shows an increasing trend from 1956 to 2000, the nonuniformity of the spatial distribution of water resources declines, and the stability of the nonuniformity of the spatial distribution of water resources is enhanced.

  12. Spatial attention systems in spatial neglect.

    Science.gov (United States)

    Karnath, Hans-Otto

    2015-08-01

    It has been established that processes relating to 'spatial attention' are implemented at cortical level by goal-directed (top-down) and stimulus-driven (bottom-up) networks. Spatial neglect in brain-damaged individuals has been interpreted as a distinguished exemplar for a disturbance of these processes. The present paper elaborates this assumption. Functioning of the two attentional networks seem to dissociate in spatial neglect; behavioral studies of patients' orienting and exploration behavior point to a disturbed stimulus-driven but preserved goal-directed attention system. When a target suddenly appears somewhere in space, neglect patients demonstrate disturbed detection and orienting if it is located in contralesional direction. In contrast, if neglect patients explore a scene with voluntarily, top-down controlled shifts of spatial attention, they perform movements that are oriented into all spatial directions without any direction-specific disturbances. The paper thus argues that not the top-down control of spatial attention itself, rather a body-related matrix on top of which this process is executed, seems affected. In that sense, the traditional role of spatial neglect as a stroke model for 'spatial attention' requires adjustment. Beyond its insights into the human stimulus-driven attentional system, the disorder most notably provides vistas in how our brain encodes topographical information and organizes spatially oriented action - including the top-down control of spatial attention - in relation to body position. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Laparoscopic training model using fresh human cadavers without the establishment of penumoperitoneum

    Directory of Open Access Journals (Sweden)

    Ernesto Sasaki Imakuma

    2016-01-01

    Full Text Available Background: Laparoscopy is a well-established alternative to open surgery for treating many diseases. Although laparoscopy has many advantages, it is also associated with disadvantages, such as slow learning curves and prolonged operation time. Fresh frozen cadavers may be an interesting resource for laparoscopic training, and many institutions have access to cadavers. One of the main obstacles for the use of cadavers as a training model is the difficulty in introducing a sufficient pneumoperitoneum to distend the abdominal wall and provide a proper working space. The purpose of this study was to describe a fresh human cadaver model for laparoscopic training without requiring a pneumoperitoneum. Materials and Methods and Results: A fake abdominal wall device was developed to allow for laparoscopic training without requiring a pneumoperitoneum in cadavers. The device consists of a table-mounted retractor, two rail clamps, two independent frame arms, two adjustable handle and rotating features, and two frames of the abdominal wall. A handycam is fixed over a frame arm, positioned and connected through a USB connection to a television and dissector; scissors and other laparoscopic materials are positioned inside trocars. The laparoscopic procedure is thus simulated. Conclusion: Cadavers offer a very promising and useful model for laparoscopic training. We developed a fake abdominal wall device that solves the limitation of space when performing surgery on cadavers and removes the need to acquire more costly laparoscopic equipment. This model is easily accessible at institutions in developing countries, making it one of the most promising tools for teaching laparoscopy.

  14. Establishment of virtual three-dimensional model for intravascular interventional devices and its clinical value

    International Nuclear Information System (INIS)

    Wei Xin; Zhong Liming; Xie Xiaodong; Wang Chaohua; You Jian; Hu Hong; Hu Kongqiong; Zhao Xiaowei

    2012-01-01

    Objective: To explore virtual three-dimensional (3D) model for intravascular interventional devices,the method of preoperative simulation and its value in clinical work. Methods: The virtual models including catheter, guide wire, stent and coil were established by using the 3D moulding software of 3D Studio MAX R3. The interventional preoperative simulation was performed on personal computer including 21 patients of cerebral aneurysm embolization (anterior communicating artery 5, posterior communicating artery 10,middle cerebral artery 3, internal carotid artery 2, and vertebral artery 1), during interventional procedures, the surgeon relied on the simulation results for plastic micro-guide wire, catheter and the release of micro-coils and stents. Results: (1) All the virtual instruments and real instruments had similar shape,the overall tine for constructing virtual model was about 20 hours. The preoperative simulation took 50 to 80 minutes. (2) The simulation result of catheter insertion in the 18 cases had relevant value to guide micro-catheter, molding micro-guide wire tip, and shortened the operating time. For embolization, the simulation results of filling coil and releasing stent were similar to surgical results in 76% of the patients (16/21). (3)For teaching and training, 93% (38/41) of doctors in training believed that preoperative simulation facilitated the understanding of surgery. Conclusions: The method of virtual model of intravascular interventional devices was reliable. The preoperative simulation results could be used to guide practical clinical operation with relatively high degree of similarity, and could play a role in promoting researches on interventional virtual operations. (authors)

  15. Establishment of a mouse model with misregulated chromosome condensation due to defective Mcph1 function.

    Directory of Open Access Journals (Sweden)

    Marc Trimborn

    Full Text Available Mutations in the human gene MCPH1 cause primary microcephaly associated with a unique cellular phenotype with premature chromosome condensation (PCC in early G2 phase and delayed decondensation post-mitosis (PCC syndrome. The gene encodes the BRCT-domain containing protein microcephalin/BRIT1. Apart from its role in the regulation of chromosome condensation, the protein is involved in the cellular response to DNA damage. We report here on the first mouse model of impaired Mcph1-function. The model was established based on an embryonic stem cell line from BayGenomics (RR0608 containing a gene trap in intron 12 of the Mcph1 gene deleting the C-terminal BRCT-domain of the protein. Although residual wild type allele can be detected by quantitative real-time PCR cell cultures generated from mouse tissues bearing the homozygous gene trap mutation display the cellular phenotype of misregulated chromosome condensation that is characteristic for the human disorder, confirming defective Mcph1 function due to the gene trap mutation. While surprisingly the DNA damage response (formation of repair foci, chromosomal breakage, and G2/M checkpoint function after irradiation appears to be largely normal in cell cultures derived from Mcph1(gt/gt mice, the overall survival rates of the Mcph1(gt/gt animals are significantly reduced compared to wild type and heterozygous mice. However, we could not detect clear signs of premature malignant disease development due to the perturbed Mcph1 function. Moreover, the animals show no obvious physical phenotype and no reduced fertility. Body and brain size are within the range of wild type controls. Gene expression on RNA and protein level did not reveal any specific pattern of differentially regulated genes. To the best of our knowledge this represents the first mammalian transgenic model displaying a defect in mitotic chromosome condensation and is also the first mouse model for impaired Mcph1-function.

  16. The establishment of MELCOR/SNAP model of Chinshan nuclear power plant for Ultimate Response Guideline

    Energy Technology Data Exchange (ETDEWEB)

    Hsu, Wen-Sheng, E-mail: wshsu@ess.nthu.edu.tw [Nuclear Science and Technology Development Center, Institute of Nuclear Engineering and Science, National Tsing Hua University, Nuclear and New Energy Education and Research Foundation, No. 101, Section 2, Kuang Fu Rd., HsinChu 30013, Taiwan, ROC (China); Chiang, Yu, E-mail: s101013702@m101.nthu.edu.tw [Nuclear Science and Technology Development Center, Institute of Nuclear Engineering and Science, National Tsing Hua University, Nuclear and New Energy Education and Research Foundation, No. 101, Section 2, Kuang Fu Rd., HsinChu 30013, Taiwan, ROC (China); Wang, Jong-Rong, E-mail: jongrongwang@gmail.com [Nuclear Science and Technology Development Center, Institute of Nuclear Engineering and Science, National Tsing Hua University, Nuclear and New Energy Education and Research Foundation, No. 101, Section 2, Kuang Fu Rd., HsinChu 30013, Taiwan, ROC (China); Wang, Ting-Yi, E-mail: minired1119@gmail.com [Nuclear Science and Technology Development Center, Institute of Nuclear Engineering and Science, National Tsing Hua University, Nuclear and New Energy Education and Research Foundation, No. 101, Section 2, Kuang Fu Rd., HsinChu 30013, Taiwan, ROC (China); Wang, Te-Chuan, E-mail: tcwang@iner.gov.tw [Institute of Nuclear Energy Research Atomic Energy Council, R.O.C., 1000, Wenhua Road Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan (China); Teng, Jyh-Tong, E-mail: jyhtong@cycu.edu.tw [Department of Mechanical Engineering, Chung Yuan Christian University, 200, Chung Pei Rd, Chung Li 32023, Taiwan, ROC (China); Chen, Shao-Wen, E-mail: chensw@mx.nthu.edu.tw [Nuclear Science and Technology Development Center, Institute of Nuclear Engineering and Science, National Tsing Hua University, Nuclear and New Energy Education and Research Foundation, No. 101, Section 2, Kuang Fu Rd., HsinChu 30013, Taiwan, ROC (China); and others

    2017-01-15

    Highlights: • The establishment of a MELCOR/SNAP model of Chinshan (BWR/4). • MELCOR/SNAP model was used to estimate the effectiveness of URG for Chinshan. • The MELCOR results were compared to MAAP, TRACE and PCTRAN. • URG is a new method to prevent a Fukushima-like accident. • The low raw water (150 GPM) can make the cladding temperature below 1088.7 K. - Abstract: After Fukushima Daiichi disaster, the safety analysis of severe accidents became one of the safety concerns in Taiwan. The Emergency Operating Procedure (EOP) cannot cope with a multiple system failure situation under a severe accident since it is a “Symptom-basis” procedure. To deal with that, Taiwan Power Company built up a new strategy for Fukushima-like accident called Ultimate Response Guideline (URG). It is a simple strategy with three main conditions: loss of regular motor driven injection system, loss of all AC power and tsunami/earthquake warning. If two of three happen, the operating procedure will change from EOP to URG and start the main works by following the strategy. There are three main works in URG: controlled-depressurization, line up low pressure injection water and prepare containment venting. In this study, MELCOR2.1 was used to calculate the cases of URG and checked the goal of the strategy that prevents the accident or not. There were three steps in this research. First, a model of Chinshan nuclear power plant (NPP) was built. Second, one was the case with URG and the other was not by using the above MELCOR model. The results were compared to MAAP5.0, TRACE and PCTRAN. Finally, some sensitivity studies of depressurization and water injection rate were done.

  17. Establishment and validation for the theoretical model of the vehicle airbag

    Science.gov (United States)

    Zhang, Junyuan; Jin, Yang; Xie, Lizhe; Chen, Chao

    2015-05-01

    The current design and optimization of the occupant restraint system (ORS) are based on numerous actual tests and mathematic simulations. These two methods are overly time-consuming and complex for the concept design phase of the ORS, though they're quite effective and accurate. Therefore, a fast and directive method of the design and optimization is needed in the concept design phase of the ORS. Since the airbag system is a crucial part of the ORS, in this paper, a theoretical model for the vehicle airbag is established in order to clarify the interaction between occupants and airbags, and further a fast design and optimization method of airbags in the concept design phase is made based on the proposed theoretical model. First, the theoretical expression of the simplified mechanical relationship between the airbag's design parameters and the occupant response is developed based on classical mechanics, then the momentum theorem and the ideal gas state equation are adopted to illustrate the relationship between airbag's design parameters and occupant response. By using MATLAB software, the iterative algorithm method and discrete variables are applied to the solution of the proposed theoretical model with a random input in a certain scope. And validations by MADYMO software prove the validity and accuracy of this theoretical model in two principal design parameters, the inflated gas mass and vent diameter, within a regular range. This research contributes to a deeper comprehension of the relation between occupants and airbags, further a fast design and optimization method for airbags' principal parameters in the concept design phase, and provides the range of the airbag's initial design parameters for the subsequent CAE simulations and actual tests.

  18. Can inducible resistance in plants cause herbivore aggregations? Spatial patterns in an inducible plant/herbivore model

    OpenAIRE

    Anderson, KE; Inouye, BD; Underwood, N

    2015-01-01

    © 2015 by the Ecological Society of America. Many theories regarding the evolution of inducible resistance in plants have an implicit spatial component, but most relevant population dynamic studies ignore spatial dynamics. We examined a spatially explicit model of plant inducible resistance and herbivore population dynamics to explore how realistic features of resistance and herbivore responses influence spatial patterning. Both transient and persistent spatial patterns developed in all model...

  19. Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

    Directory of Open Access Journals (Sweden)

    David W Redding

    Full Text Available Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT, to a spatial Bayesian SDM method (fitted using R-INLA, when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account

  20. Housing price prediction: parametric versus semi-parametric spatial hedonic models

    Science.gov (United States)

    Montero, José-María; Mínguez, Román; Fernández-Avilés, Gema

    2018-01-01

    House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.

  1. Predictability of locomotion: Effects on updating of spatial situation models during narrative comprehension

    NARCIS (Netherlands)

    Dutke, S.; Rinck, M.

    2006-01-01

    We investigated how the updating of spatial situation models during narrative comprehension depends on the interaction of cognitive abilities and text characteristics. Participants with low verbal and visuospatial abilities and participants with high abilities read narratives in which the

  2. Impact of precipitation spatial resolution on the hydrological response of an integrated distributed water resources model

    DEFF Research Database (Denmark)

    Fu, Suhua; Sonnenborg, Torben; Jensen, Karsten Høgh

    2011-01-01

    Precipitation is a key input variable to hydrological models, and the spatial variability of the input is expected to impact the hydrological response predicted by a distributed model. In this study, the effect of spatial resolution of precipitation on runoff , recharge and groundwater head...... was analyzed in the Alergaarde catchment in Denmark. Six different precipitation spatial resolutions were used as inputs to a physically based, distributed hydrological model, the MIKE SHE model. The results showed that the resolution of precipitation input had no apparent effect on annual water balance...... of the total catchment and runoff discharge hydrograph at watershed outlet. On the other hand, groundwater recharge and groundwater head were both aff ected. The impact of the spatial resolution of precipitation input is reduced with increasing catchment size. The effect on stream discharge is relatively low...

  3. Establishment of an animal model for chronic gastritis with Helicobacter pylori: potential model for long-term observations.

    Science.gov (United States)

    Fujioka, T; Kubota, T; Shuto, R; Kodama, R; Murakami, K; Perparim, K; Nasu, M

    1994-12-01

    To assess the suitability of an established experimental model for chronic gastritis associated with Helicobacter pylori for use in long-term observations. In a 3-year follow-up study of acute gastritis induced by H. pylori using an established experimental model with Japanese monkeys, we compared H. pylori-infected animals (n = 6) with a non-infected control group (n = 7). Colonization by H. pylori, gastritis scores, volume of intracellular periodic acid-Schiff-positive substances and the height of antral glands were investigated every 3 months for 3 years and compared with those of a control group. In the infected group, persistent colonization with H. pylori was demonstrated by culture and histological examinations. Gastritis scores were significantly higher than those of the control group, and the histological findings were quite similar to those of chronic active gastritis observed in humans. Simultaneously, significant decreases in the contents of periodic acid-Schiff-positive substances and in the height of antral glands were also demonstrated in infected animals. In Japanese monkeys, persistent colonization with H. pylori caused chronic gastritis quite similar to that observed in humans, thus providing a suitable animal model for evaluating the long-term prognosis of H. pylori infection.

  4. Spatial modeling on the upperstream of the Citarum watershed: An application of geoinformatics

    Science.gov (United States)

    Ningrum, Windy Setia; Widyaningsih, Yekti; Indra, Tito Latif

    2017-03-01

    The Citarum watershed is the longest and the largest watershed in West Java, Indonesia, located at 106°51'36''-107°51' E and 7°19'-6°24'S across 10 districts, and serves as the water supply for over 15 million people. In this area, the water criticality index is concerned to reach the balance between water supply and water demand, so that in the dry season, the watershed is still able to meet the water needs of the society along the Citarum river. The objective of this research is to evaluate the water criticality index of Citarum watershed area using spatial model to overcome the spatial dependencies in the data. The result of Lagrange multiplier diagnostics for spatial dependence results are LM-err = 34.6 (p-value = 4.1e-09) and LM-lag = 8.05 (p-value = 0.005), then modeling using Spatial Lag Model (SLM) and Spatial Error Model (SEM) were conducted. The likelihood ratio test show that both of SLM dan SEM model is better than OLS model in modeling water criticality index in Citarum watershed. The AIC value of SLM and SEM model are 78.9 and 51.4, then the SEM model is better than SLM model in predicting water criticality index in Citarum watershed.

  5. Establishment of 9L/F344 rat intracerebral glioma model of brain tumor stem cells

    Directory of Open Access Journals (Sweden)

    Zong-yu XIAO

    2015-04-01

    Full Text Available Objective To establish the 9L/F344 rat intracerebral glioma model of brain tumor stem cells.  Methods Rat 9L gliosarcoma stem-like cells were cultured in serum-free suspension. The expression of CD133 and nestin were tested by immunohistochemistry. A total of 48 inbredline male F344 rats were randomly divided into 2 groups, and 9L tumor sphere cells and 9L monolayer cells were respectively implanted into the right caudate nucleus of F344 rats in 2 groups. Survival time was observed and determined using the method of Kaplan-Meier survival analysis. Fourteen days after implantation or when the rats were dying, their brains were perfused and sectioned for HE staining, and CD133 and nestin were detected by immunohistochemistry.  Results Rat 9L tumor spheres were formed with suspension culture in serum-free medium. The gliomas formed in both groups were invasive without obvious capsule. More new vessels, bleeding and necrosis could be detected in 9L tumor spheres group. The tumor cells in both groups were positive for CD133 and nestin. There was no significant difference in the expression of CD133 and nestin between 2 groups (P > 0.05, for all. According to the expression of nestin, the tumors formed by 9L tumor sphere cells were more invasive. The median survival time of the rats bearing 9L tumor sphere cells was 15 d (95%CI: 15.219-15.781, and the median survival time of the rats bearing 9L monolayer cells was 21 d (95%CI: 20.395-21.605. There was significant difference between 2 groups (χ2 = 12.800, P = 0.000.  Conclusions 9L/F344 rat intracerebral glioma model of brain tumor stem cells is successfully established, which provides a glioma model for the future research. DOI: 10.3969/j.issn.1672-6731.2015.04.012

  6. The Establishment and Characteristics of Rat Model of Atherosclerosis Induced by Hyperuricemia

    Directory of Open Access Journals (Sweden)

    Zhen Liu

    2016-01-01

    Full Text Available Epidemiological studies have identified hyperuricemia as an independent risk factor for cardiovascular disease. However, the mechanism whereby hyperuricemia causes atherosclerosis remains unclear. The objective of the study was to establish a new rat model of hyperuricemia-induced atherosclerosis. Wistar-Kyoto rats were randomly allocated to either a normal diet (ND, high-fat diet (HFD, or high-adenine diet (HAD, followed by sacrifice 4, 8, or 12 weeks later. Serum uric acid and lipid levels were analyzed, pathologic changes in the aorta were observed by hematoxylin and eosin staining, and mRNA expression was evaluated by quantitative real-time polymerase chain reaction. Serum uric acid and TC were significantly increased in the HAD group at 4 weeks compared with the ND group, but there was no significant difference in serum uric acid between the ND and HFD groups. Aorta calcification occurred earlier and was more severe in the HAD group, compared with the HFD group. Proliferating cell nuclear antigen, monocyte chemotactic factor-1, intercellular adhesion molecule-1, and vascular cell adhesion molecule-1 mRNA levels were increased in the HFD and HAD groups compared with the ND group. This new animal model will be a useful tool for investigating the mechanisms responsible for hyperuricemia-induced atherosclerosis.

  7. Establishment of a head injury by club model in rabbits and experimental conditions

    International Nuclear Information System (INIS)

    Cao Yunxing; Xi Huanjiu; Zhang Jing; Li Hongwei; Yin Zhiyong; Zhao Hui

    2013-01-01

    Objective: To establish an animal model to replicate the injury by club in forensic medicine. Methods: Twenty-four New Zealand white rabbits were divided into control group (n=4), minor injury group (n=10), and severe injury group (n=10). Based on the BIM-Ⅱ Horizontal Bio-impact Machine, a self-designed iron bar was used to produce head injury by club. Six hours after injury, all the rabbits were subjected to a CT examination and dissected to observe the injury morphology and undergo routine pathological examination. Four control, six minor and severe rabbits were given moisture content examination. Results: Varying degrees of positive signs of the nervous system were observed in all the injured rabbits within 6 hours. The mortality rate was 1/10 in the minor injury group and 6/10 in the severe injury group. The morphological changes consisted of different levels of scalp hematoma, skull fracture, epidural hematoma, subdural hematoma, subarachnoid hemorrhage and brain injury. The difference in moisture content between the three groups was of statistical significance. Conclusion: Under the rigidly-controlled experimental condition, this animal model produces good reproducibility and stable results. Meanwhile, it can simulate the morphology of injury by club and be used to study the mechanism of injury by club in forensic medicine. (authors)

  8. [Establishment of animal model for elucidating the mechanism of intoxication by the poisonous mushroom Clitocybe acromelalga].

    Science.gov (United States)

    Fukuwatari, T; Sugimoto, E; Yokoyama, K; Shibata, K

    2001-06-01

    Dietary intake of a poisonous mushroom, Clitocybe acromelalga, causes acromelalgia. The symptom continues for over a month. Some papers reported that treatment with nicotinic acid is effective. We have established an animal model to elucidate the mechanism of toxicity of the poisonous mushroom Clitocybe acromelalga. Diet containing Clitocybe acromelalga was fed to niacin-deficient rats for 24 hours (designated as day 0). The food intake decreased to about one-half compared with that of day before, and body weight loss was noted. Although the diet was returned to the control diet on day 1, the food intake did not recover until day 7, and body weight gain was not seen until day 6. A severe symptom resembling acromelalgia in humans started to appear on day 3. This is the first report of an animal model for the intoxication of Clitocybe acromelalga in humans. Since no similar symptom resembling human intoxication was seen in a previous rodent study, the niacin-free/tryptophan-limited diet used in the present study may have contributed to the result.

  9. Establish susceptibility and risk assessment models for rainfall-induced landslide: A case in Central Taiwan

    Science.gov (United States)

    Wu, Chunhung; Huang, Jyuntai

    2017-04-01

    Most of the landslide cases in Taiwan were triggered by rainfall or earthquake events. The heavy rainfall in the typhoon seasons, from June to October, causes the landslide hazard more serious. Renai Towhship is of the most large landslide cases after 2009 Typhoon Morakot (from Aug. 5 to Aug. 10, 2009) in Taiwan. Around 2,744 landslides cases with the total landslide area of 21.5 km2 (landslide ratio =1.8%), including 26 large landslide cases, induced after 2009 Typhoon Morakot in Renai Towhship. The area of each large landslides case is more than 0.1 km2, and the area of the largest case is around 0.96 km2. 58% of large landslide cases locate in the area with metamorphosed sandstone. The mean slope of 26 large landslide cases ranges from 15 degree to 56 degree, and the accumulated rainfall during 2009 Typhoon Morakot ranges from 530 mm to 937 mm. Three methods, including frequency ratio method (abbreviated as FR), weights of evidence method (abbreviated as WOE), and logistic regression method (abbreviated as LR), are used in this study to establish the landslides susceptibility in the Renai Township, Nantou County, Taiwan. Eight landslide related-factors, including elevation, slope, aspect, geology, land use, distance to drainage, distance to fault, accumulation rainfall during 2009 Typhoon Morakot, are used to establish the landslide susceptibility models in this study. The landslide inventory after 2009 Typhoon Morakot is also used to test the model performance in this study. The mean accumulated rainfall in Renai Township during 2009 typhoon Morakot was around 735 mm with the maximum 1-hr, 3-hrs, and 6-hrs rainfall intensity of 44 mm/1-hr, 106 mm/3-hrs and 204 mm/6-hrs, respectively. The range of original susceptibility values established by three methods are 4.0 to 20.9 for FR, -33.8 to -16.1 for WOE, and -41.7 to 5.7 for LR, and the mean landslide susceptibility value are 8.0, -24.6 and 0.38, respectively. The AUC values are 0.815 for FR, 0.816 for WOE, and 0

  10. Emergent spatial structures in flocking models: a dynamical system insight.

    Science.gov (United States)

    Caussin, Jean-Baptiste; Solon, Alexandre; Peshkov, Anton; Chaté, Hugues; Dauxois, Thierry; Tailleur, Julien; Vitelli, Vincenzo; Bartolo, Denis

    2014-04-11

    We show that hydrodynamic theories of polar active matter generically possess inhomogeneous traveling solutions. We introduce a unifying dynamical-system framework to establish the shape of these intrinsically nonlinear patterns, and show that they correspond to those hitherto observed in experiments and numerical simulation: periodic density waves, and solitonic bands, or polar-liquid droplets both cruising in isotropic phases. We elucidate their respective multiplicity and mutual relations, as well as their existence domain.

  11. Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

    Science.gov (United States)

    Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

    2010-01-01

    Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

  12. Integrated Modeling of Spatial and Temporal Heterogeneities and Decisions Induced by Catastrophic Events

    OpenAIRE

    Ermolieva, T.Y.; Fischer, G.; Obersteiner, M.

    2003-01-01

    This paper discusses an integrated model capable of dealing with spatial and temporal heterogeneities induced by extreme events, in particular weather related catastrophes. The model can be used for quite different problems which take explicitly into account the specifics of catastrophic risks: highly mutually dependent losses, inherent capacity of information, the need for long-term perspectives (temporal heterogeneity) and geographically explicit analyses (spatial heterogeneity) with respec...

  13. Impact imaging of aircraft composite structure based on a model-independent spatial-wavenumber filter.

    Science.gov (United States)

    Qiu, Lei; Liu, Bin; Yuan, Shenfang; Su, Zhongqing

    2016-01-01

    The spatial-wavenumber filtering technique is an effective approach to distinguish the propagating direction and wave mode of Lamb wave in spatial-wavenumber domain. Therefore, it has been gradually studied for damage evaluation in recent years. But for on-line impact monitoring in practical application, the main problem is how to realize the spatial-wavenumber filtering of impact signal when the wavenumber of high spatial resolution cannot be measured or the accurate wavenumber curve cannot be modeled. In this paper, a new model-independent spatial-wavenumber filter based impact imaging method is proposed. In this method, a 2D cross-shaped array constructed by two linear piezoelectric (PZT) sensor arrays is used to acquire impact signal on-line. The continuous complex Shannon wavelet transform is adopted to extract the frequency narrowband signals from the frequency wideband impact response signals of the PZT sensors. A model-independent spatial-wavenumber filter is designed based on the spatial-wavenumber filtering technique. Based on the designed filter, a wavenumber searching and best match mechanism is proposed to implement the spatial-wavenumber filtering of the frequency narrowband signals without modeling, which can be used to obtain a wavenumber-time image of the impact relative to a linear PZT sensor array. By using the two wavenumber-time images of the 2D cross-shaped array, the impact direction can be estimated without blind angle. The impact distance relative to the 2D cross-shaped array can be calculated by using the difference of time-of-flight between the frequency narrowband signals of two different central frequencies and the corresponding group velocities. The validations performed on a carbon fiber composite laminate plate and an aircraft composite oil tank show a good impact localization accuracy of the model-independent spatial-wavenumber filter based impact imaging method. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

    Science.gov (United States)

    Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

  15. Cosmological backreaction within the Szekeres model and emergence of spatial curvature

    Science.gov (United States)

    Bolejko, Krzysztof

    2017-06-01

    This paper discusses the phenomenon of backreaction within the Szekeres model. Cosmological backreaction describes how the mean global evolution of the Universe deviates from the Friedmannian evolution. The analysis is based on models of a single cosmological environment and the global ensemble of the Szekeres models (of the Swiss-Cheese-type and Styrofoam-type). The obtained results show that non-linear growth of cosmic structures is associated with the growth of the spatial curvature ΩScript R (in the FLRW limit ΩScript R → Ωk). If averaged over global scales the result depends on the assumed global model of the Universe. Within the Swiss-Cheese model, which does have a fixed background, the volume average follows the evolution of the background, and the global spatial curvature averages out to zero (the background model is the ΛCDM model, which is spatially flat). In the Styrofoam-type model, which does not have a fixed background, the mean evolution deviates from the spatially flat ΛCDM model, and the mean spatial curvature evolves from ΩScript R =0 at the CMB to ΩScript R ~ 0.1 at 0z =. If the Styrofoam-type model correctly captures evolutionary features of the real Universe then one should expect that in our Universe, the spatial curvature should build up (local growth of cosmic structures) and its mean global average should deviate from zero (backreaction). As a result, this paper predicts that the low-redshift Universe should not be spatially flat (i.e. Ωk ≠ 0, even if in the early Universe Ωk = 0) and therefore when analysing low-z cosmological data one should keep Ωk as a free parameter and independent from the CMB constraints.

  16. Cosmological backreaction within the Szekeres model and emergence of spatial curvature

    Energy Technology Data Exchange (ETDEWEB)

    Bolejko, Krzysztof, E-mail: krzysztof.bolejko@sydney.edu.au [Sydney Institute for Astronomy, School of Physics A28, The University of Sydney, Sydney, NSW, 2006 (Australia)

    2017-06-01

    This paper discusses the phenomenon of backreaction within the Szekeres model. Cosmological backreaction describes how the mean global evolution of the Universe deviates from the Friedmannian evolution. The analysis is based on models of a single cosmological environment and the global ensemble of the Szekeres models (of the Swiss-Cheese-type and Styrofoam-type). The obtained results show that non-linear growth of cosmic structures is associated with the growth of the spatial curvature Ω{sub R} (in the FLRW limit Ω{sub R} → Ω {sub k} ). If averaged over global scales the result depends on the assumed global model of the Universe. Within the Swiss-Cheese model, which does have a fixed background, the volume average follows the evolution of the background, and the global spatial curvature averages out to zero (the background model is the ΛCDM model, which is spatially flat). In the Styrofoam-type model, which does not have a fixed background, the mean evolution deviates from the spatially flat ΛCDM model, and the mean spatial curvature evolves from Ω{sub R} =0 at the CMB to Ω{sub R} ∼ 0.1 at 0 z =. If the Styrofoam-type model correctly captures evolutionary features of the real Universe then one should expect that in our Universe, the spatial curvature should build up (local growth of cosmic structures) and its mean global average should deviate from zero (backreaction). As a result, this paper predicts that the low-redshift Universe should not be spatially flat (i.e. Ω {sub k} ≠ 0, even if in the early Universe Ω {sub k} = 0) and therefore when analysing low- z cosmological data one should keep Ω {sub k} as a free parameter and independent from the CMB constraints.

  17. A Spatial Model of Erosion and Sedimentation on Continental Margins

    National Research Council Canada - National Science Library

    Pratson, Lincoln

    1999-01-01

    .... A computer model that simulates the evolution of continental slope morphology under the interaction of sedimentation, slope failure, and sediment flow erosion has been constructed and validated...

  18. Establishment of a murine graft-versus-myeloma model using allogeneic stem cell transplantation.

    Directory of Open Access Journals (Sweden)

    Marilène Binsfeld

    Full Text Available Multiple myeloma (MM is a malignant plasma cell disorder with poor long-term survival and high recurrence rates. Despite evidence of graft-versus-myeloma (GvM effects, the use of allogeneic hematopoietic stem cell transplantation (allo-SCT remains controversial in MM. In the current study, we investigated the anti-myeloma effects of allo-SCT from B10.D2 mice into MHC-matched myeloma-bearing Balb/cJ mice, with concomitant development of chronic graft-versus-host disease (GvHD.Balb/cJ mice were injected intravenously with luciferase-transfected MOPC315.BM cells, and received an allogeneic (B10.D2 donor or autologous (Balb/cJ donor transplant 30 days later. We observed a GvM effect in 94% of the allogeneic transplanted mice, as the luciferase signal completely disappeared after transplantation, whereas all the autologous transplanted mice showed myeloma progression. Lower serum paraprotein levels and lower myeloma infiltration in bone marrow and spleen in the allogeneic setting confirmed the observed GvM effect. In addition, the treated mice also displayed chronic GvHD symptoms. In vivo and in vitro data suggested the involvement of effector memory CD4 and CD8 T cells associated with the GvM response. The essential role of CD8 T cells was demonstrated in vivo where CD8 T-cell depletion of the graft resulted in reduced GvM effects. Finally, TCR Vβ spectratyping analysis identified Vβ families within CD4 and CD8 T cells, which were associated with both GvM effects and GvHD, whereas other Vβ families within CD4 T cells were associated exclusively with either GvM or GvHD responses.We successfully established an immunocompetent murine model of graft-versus-myeloma. This is the first murine GvM model using immunocompetent mice that develop MM which closely resembles human MM disease and that are treated after disease establishment with an allo-SCT. Importantly, using TCR Vβ spectratyping, we also demonstrated the presence of GvM unique responses

  19. BAYESIAN SPATIAL-TEMPORAL MODELING OF ECOLOGICAL ZERO-INFLATED COUNT DATA.

    Science.gov (United States)

    Wang, Xia; Chen, Ming-Hui; Kuo, Rita C; Dey, Dipak K

    2015-01-01

    A Bayesian hierarchical model is developed for count data with spatial and temporal correlations as well as excessive zeros, uneven sampling intensities, and inference on missing spots. Our contribution is to develop a model on zero-inflated count data that provides flexibility in modeling spatial patterns in a dynamic manner and also improves the computational efficiency via dimension reduction. The proposed methodology is of particular importance for studying species presence and abundance in the field of ecological sciences. The proposed model is employed in the analysis of the survey data by the Northeast Fisheries Sciences Center (NEFSC) for estimation and prediction of the Atlantic cod in the Gulf of Maine - Georges Bank region. Model comparisons based on the deviance information criterion and the log predictive score show the improvement by the proposed spatial-temporal model.

  20. [Establishment of risk evaluation model of peritoneal metastasis in gastric cancer and its predictive value].

    Science.gov (United States)

    Zhao, Junjie; Zhou, Rongjian; Zhang, Qi; Shu, Ping; Li, Haojie; Wang, Xuefei; Shen, Zhenbin; Liu, Fenglin; Chen, Weidong; Qin, Jing; Sun, Yihong

    2017-01-25

    To establish an evaluation model of peritoneal metastasis in gastric cancer, and to assess its clinical significance. Clinical and pathologic data of the consecutive cases of gastric cancer admitted between April 2015 and December 2015 in Department of General Surgery, Zhongshan Hospital of Fudan University were analyzed retrospectively. A total of 710 patients were enrolled in the study after 18 patients with other distant metastasis were excluded. The correlations between peritoneal metastasis and different factors were studied through univariate (Pearson's test or Fisher's exact test) and multivariate analyses (Binary Logistic regression). Independent predictable factors for peritoneal metastasis were combined to establish a risk evaluation model (nomogram). The nomogram was created with R software using the 'rms' package. In the nomogram, each factor had different scores, and every patient could have a total score by adding all the scores of each factor. A higher total score represented higher risk of peritoneal metastasis. Receiver operating characteristic (ROC) curve analysis was used to compare the sensitivity and specificity of the established nomogram. Delong. Delong. Clarke-Pearson test was used to compare the difference of the area under the curve (AUC). The cut-off value was determined by the AUC, when the ROC curve had the biggest AUC, the model had the best sensitivity and specificity. Among 710 patients, 47 patients had peritoneal metastasis (6.6%), including 30 male (30/506, 5.9%) and 17 female (17/204, 8.3%); 31 were ≥ 60 years old (31/429, 7.2%); 38 had tumor ≥ 3 cm(38/461, 8.2%). Lauren classification indicated that 2 patients were intestinal type(2/245, 0.8%), 8 patients were mixed type(8/208, 3.8%), 11 patients were diffuse type(11/142, 7.7%), and others had no associated data. CA19-9 of 13 patients was ≥ 37 kU/L(13/61, 21.3%); CA125 of 11 patients was ≥ 35 kU/L(11/36, 30.6%); CA72-4 of 11 patients was ≥ 10 kU/L(11/39, 28

  1. Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models

    Science.gov (United States)

    Gopalaswamy, Arjun M.; Royle, J. Andrew; Hines, James E.; Singh, Pallavi; Jathanna, Devcharan; Kumar, N. Samba; Karanth, K. Ullas

    2012-01-01

    1. The advent of spatially explicit capture-recapture models is changing the way ecologists analyse capture-recapture data. However, the advantages offered by these new models are not fully exploited because they can be difficult to implement. 2. To address this need, we developed a user-friendly software package, created within the R programming environment, called SPACECAP. This package implements Bayesian spatially explicit hierarchical models to analyse spatial capture-recapture data. 3. Given that a large number of field biologists prefer software with graphical user interfaces for analysing their data, SPACECAP is particularly useful as a tool to increase the adoption of Bayesian spatially explicit capture-recapture methods in practice.

  2. Spatial uncertainty modeling of fuzzy information in images for pattern classification.

    Directory of Open Access Journals (Sweden)

    Tuan D Pham

    Full Text Available The modeling of the spatial distribution of image properties is important for many pattern recognition problems in science and engineering. Mathematical methods are needed to quantify the variability of this spatial distribution based on which a decision of classification can be made in an optimal sense. However, image properties are often subject to uncertainty due to both incomplete and imprecise information. This paper presents an integrated approach for estimating the spatial uncertainty of vagueness in images using the theory of geostatistics and the calculus of probability measures of fuzzy events. Such a model for the quantification of spatial uncertainty is utilized as a new image feature extraction method, based on which classifiers can be trained to perform the task of pattern recognition. Applications of the proposed algorithm to the classification of various types of image data suggest the usefulness of the proposed uncertainty modeling technique for texture feature extraction.

  3. A spatial and nonstationary model for the frequency of extreme rainfall events

    DEFF Research Database (Denmark)

    Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

    2013-01-01

    of extreme rainfall events, a statistical model is tested for this purpose. The model is built on the theory of generalized linear models and uses Poisson regression solved by generalized estimation equations. Spatial and temporal explanatory variables can be included simultaneously, and their relative...

  4. Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

    Science.gov (United States)

    Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.

    2014-01-01

    Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

  5. Spatial landscape model to characterize biological diversity using R statistical computing environment.

    Science.gov (United States)

    Singh, Hariom; Garg, R D; Karnatak, Harish C; Roy, Arijit

    2018-01-15

    Due to urbanization and population growth, the degradation of natural forests and associated biodiversity are now widely recognized as a global environmental concern. Hence, there is an urgent need for rapid assessment and monitoring of biodiversity on priority using state-of-art tools and technologies. The main purpose of this research article is to develop and implement a new methodological approach to characterize biological diversity using spatial model developed during the study viz. Spatial Biodiversity Model (SBM). The developed model is scale, resolution and location independent solution for spatial biodiversity richness modelling. The platform-independent computation model is based on parallel computation. The biodiversity model based on open-source software has been implemented on R statistical computing platform. It provides information on high disturbance and high biological richness areas through different landscape indices and site specific information (e.g. forest fragmentation (FR), disturbance index (DI) etc.). The model has been developed based on the case study of Indian landscape; however it can be implemented in any part of the world. As a case study, SBM has been tested for Uttarakhand state in India. Inputs for landscape ecology are derived through multi-criteria decision making (MCDM) techniques in an interactive command line environment. MCDM with sensitivity analysis in spatial domain has been carried out to illustrate the model stability and robustness. Furthermore, spatial regression analysis has been made for the validation of the output. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil

    Directory of Open Access Journals (Sweden)

    Werneck Guilherme L.

    2002-01-01

    Full Text Available Most ecologic studies use geographical areas as units of observation. Because data from areas close to one another tend to be more alike than those from distant areas, estimation of effect size and confidence intervals should consider spatial autocorrelation of measurements. In this report we demonstrate a method for modeling spatial autocorrelation within a mixed model framework, using data on environmental and socioeconomic determinants of the incidence of visceral leishmaniasis (VL in the city of Teresina, Piauí, Brazil. A model with a spherical covariance structure indicated significant spatial autocorrelation in the data and yielded a better fit than one assuming independent observations. While both models showed a positive association between VL incidence and residence in a favela (slum or in areas with green vegetation, values for the fixed effects and standard errors differed substantially between the models. Exploration of the data's spatial correlation structure through the semivariogram should precede the use of these models. Our findings support the hypothesis of spatial dependence of VL rates and indicate that it might be useful to model spatial correlation in order to obtain more accurate point and standard error estimates.

  7. Chaos induced by breakup of waves in a spatial epidemic model with nonlinear incidence rate

    International Nuclear Information System (INIS)

    Sun, Gui-Quan; Jin, Zhen; Liu, Quan-Xing; Li, Li

    2008-01-01

    Spatial epidemiology is the study of spatial variation in disease risk or incidence, including the spatial patterns of the population. The spread of diseases in human populations can exhibit large scale patterns, underlining the need for spatially explicit approaches. In this paper, the spatiotemporal complexity of a spatial epidemic model with nonlinear incidence rate, which includes the behavioral changes and crowding effect of the infective individuals, is investigated. Based on both theoretical analysis and computer simulations, we find out when, under the parameters which can guarantee a stable limit cycle in the non-spatial model, spiral and target waves can emerge. Moreover, two different kinds of breakup of waves are shown. Specifically, the breakup of spiral waves is from the core and the breakup of target waves is from the far-field, and both kinds of waves become irregular patterns at last. Our results reveal that the spatiotemporal chaos is induced by the breakup of waves. The results obtained confirm that diffusion can form spiral waves, target waves or spatial chaos of high population density, which enrich the findings of spatiotemporal dynamics in the epidemic model

  8. A review of techniques for spatial modeling in geographical, conservation and landscape genetics.

    Science.gov (United States)

    Diniz-Filho, José Alexandre Felizola; Nabout, João Carlos; de Campos Telles, Mariana Pires; Soares, Thannya Nascimento; Rangel, Thiago Fernando L V B

    2009-04-01

    Most evolutionary processes occur in a spatial context and several spatial analysis techniques have been employed in an exploratory context. However, the existence of autocorrelation can also perturb significance tests when data is analyzed using standard correlation and regression techniques on modeling genetic data as a function of explanatory variables. In this case, more complex models incorporating the effects of autocorrelation must be used. Here we review those models and compared their relative performances in a simple simulation, in which spatial patterns in allele frequencies were generated by a balance between random variation within populations and spatially-structured gene flow. Notwithstanding the somewhat idiosyncratic behavior of the techniques evaluated, it is clear that spatial autocorrelation affects Type I errors and that standard linear regression does not provide minimum variance estimators. Due to its flexibility, we stress that principal coordinate of neighbor matrices (PCNM) and related eigenvector mapping techniques seem to be the best approaches to spatial regression. In general, we hope that our review of commonly used spatial regression techniques in biology and ecology may aid population geneticists towards providing better explanations for population structures dealing with more complex regression problems throughout geographic space.

  9. Spatial vulnerability units - expert-based spatial modelling of socio-economic vulnerability in the Salzach catchment, Austria

    Science.gov (United States)

    Kienberger, S.; Lang, S.; Zeil, P.

    2009-05-01

    The assessment of vulnerability has moved to centre-stage of the debate between different scientific disciplines related to climate change and disaster risk management. Composed by a combination of social, economical, physical and environmental factors the assessment implies combining different domains as well as quantitative with qualitative data and makes it therefore a challenge to identify an integrated metric for vulnerability. In this paper we define vulnerability in the context of climate change, targeting the hazard "flood". The developed methodology is being tested in the Salzach river catchment in Austria, which is largely prone to floods. The proposed methodology allows the spatial quantification of vulnerability and the identification of vulnerability units. These units build upon the geon concept which acts as a framework for the regionalization of continuous spatial information according to defined parameters of homogeneity. Using geons, we are capable of transforming singular domains of information on specific systemic components to policy-relevant, conditioned information. Considering the fact that vulnerability is not directly measurable and due to its complex dimension and social construction an expert-based approach has been chosen. Established methodologies such as Multicriteria Decision Analysis, Delphi exercises and regionalization approaches are being integrated. The method not only enables the assessment of vulnerability independent from administrative boundaries, but also applies an aggregation mode which reflects homogenous vulnerability units. This supports decision makers to reflect on complex issues such as vulnerability. Next to that, the advantage is to decompose the units to their underlying domains. Feedback from disaster management experts indicates that the approach helps to improve the design of measures aimed at strengthening preparedness and mitigation. From this point of view, we reach a step closer towards validation of the

  10. A Poisson regression approach for modelling spatial autocorrelation between geographically referenced observations.

    Science.gov (United States)

    Mohebbi, Mohammadreza; Wolfe, Rory; Jolley, Damien

    2011-10-03

    Analytic methods commonly used in epidemiology do not account for spatial correlation between observations. In regression analyses, omission of that autocorrelation can bias parameter estimates and yield incorrect standard error estimates. We used age standardised incidence ratios (SIRs) of esophageal cancer (EC) from the Babol cancer registry from 2001 to 2005, and extracted socioeconomic indices from the Statistical Centre of Iran. The following models for SIR were used: (1) Poisson regression with agglomeration-specific nonspatial random effects; (2) Poisson regression with agglomeration-specific spatial random effects. Distance-based and neighbourhood-based autocorrelation structures were used for defining the spatial random effects and a pseudolikelihood approach was applied to estimate model parameters. The Bayesian information criterion (BIC), Akaike's information criterion (AIC) and adjusted pseudo R2, were used for model comparison. A Gaussian semivariogram with an effective range of 225 km best fit spatial autocorrelation in agglomeration-level EC incidence. The Moran's I index was greater than its expected value indicating systematic geographical clustering of EC. The distance-based and neighbourhood-based Poisson regression estimates were generally similar. When residual spatial dependence was modelled, point and interval estimates of covariate effects were different to those obtained from the nonspatial Poisson model. The spatial pattern evident in the EC SIR and the observation that point estimates and standard errors differed depending on the modelling approach indicate the importance of accounting for residual spatial correlation in analyses of EC incidence in the Caspian region of Iran. Our results also illustrate that spatial smoothing must be applied with care.

  11. A poisson regression approach for modelling spatial autocorrelation between geographically referenced observations

    Directory of Open Access Journals (Sweden)

    Jolley Damien

    2011-10-01

    Full Text Available Abstract Background Analytic methods commonly used in epidemiology do not account for spatial correlation between observations. In regression analyses, omission of that autocorrelation can bias parameter estimates and yield incorrect standard error estimates. Methods We used age standardised incidence ratios (SIRs of esophageal cancer (EC from the Babol cancer registry from 2001 to 2005, and extracted socioeconomic indices from the Statistical Centre of Iran. The following models for SIR were used: (1 Poisson regression with agglomeration-specific nonspatial random effects; (2 Poisson regression with agglomeration-specific spatial random effects. Distance-based and neighbourhood-based autocorrelation structures were used for defining the spatial random effects and a pseudolikelihood approach was applied to estimate model parameters. The Bayesian information criterion (BIC, Akaike's information criterion (AIC and adjusted pseudo R2, were used for model comparison. Results A Gaussian semivariogram with an effective range of 225 km best fit spatial autocorrelation in agglomeration-level EC incidence. The Moran's I index was greater than its expected value indicating systematic geographical clustering of EC. The distance-based and neighbourhood-based Poisson regression estimates were generally similar. When residual spatial dependence was modelled, point and interval estimates of covariate effects were different to those obtained from the nonspatial Poisson model. Conclusions The spatial pattern evident in the EC SIR and the observation that point estimates and standard errors differed depending on the modelling approach indicate the importance of accounting for residual spatial correlation in analyses of EC incidence in the Caspian region of Iran. Our results also illustrate that spatial smoothing must be applied with care.

  12. Trap configuration and spacing influences parameter estimates in spatial capture-recapture models.

    Directory of Open Access Journals (Sweden)

    Catherine C Sun

    Full Text Available An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation. We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.

  13. Trap configuration and spacing influences parameter estimates in spatial capture-recapture models.

    Science.gov (United States)

    Sun, Catherine C; Fuller, Angela K; Royle, J Andrew

    2014-01-01

    An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.

  14. [ESTABLISHMENT OF A NEW RADIUS DEFECT MODEL BASED ON ULNA ANATOMICAL MEASUREMENT IN RABBITS].

    Science.gov (United States)

    Liu, Hanjiang; Guo, Ying; Mei, Wei

    2016-02-01

    To introduce a new bone defect model based on the anatomical measurement of radius and ulna in rabbits for offering a standard model for further tissue engineering research. Fifteen healthy 4-month-old New Zealand rabbits were selected for anatomic measurement and radiological measurement of the radius and ulna. Another 30 healthy 4-month-old New Zealand rabbits were randomly divided into groups A, B, and C (n=10). The radius bone defect was created bilaterally in 3 groups. In group A, the periosteum and interosseous membranes were fully removed with jig-saw by approach between extensor carpi radialis muscle and musculus extensor digitorum. The periosteum and interosseous membranes were fully removed in group B, and only periosteum was removed in group C with electric-saw by approach between extensor carpi radialis muscle and flexor digitorum profundus based on anatomical analysis results of ulnar and radial measurement. The gross observation, X-ray, micro-CT three-dimensional reconstruction, bone mineral density (BMD), and bone mineral content (BMC) were observed and recorded at immediate and 15 weeks after operation. HE staining and Masson staining were performed to observe bone formation in the defect areas. Blood vessel injury (1 rabbit), tendon injury (2 rabbits), postoperative hematoma (1 rabbit), and infection (1 rabbit) occurred in group A, postoperative infection (1 rabbit) in group C, and no postoperative complications in group B; the complication rate of group A (50%) was significantly higher than that of groups B (0%) and C (10%) (P0.05). HE staining and Masson staining results showed bone formation in group A, with structure disturbance and sclerosis. New bone formed in groups B and C, cartilage cells were observed in the center of bone cells. The radius bone defect model established by approach between extensor carpi radialis muscle and flexor digitorum profundus is an ideal model because of better exposures, less intra-operative blood loss, less

  15. A simple method for establishing an ostrich model of femoral head osteonecrosis and collapse.

    Science.gov (United States)

    Jiang, Wenxue; Wang, Pengfei; Wan, Yanlin; Xin, Dasen; Fan, Meng

    2015-05-21

    . This study indicates that an animal model of osteonecrotic femoral head progressing to collapse can be established via a simplified method of cryosurgery. This model possesses histological features that are similar to those of humans; thus, it can be used as an ideal animal model for the study of femoral head necrosis.

  16. A model to establish the monetary value of the man-sievert for public exposure

    International Nuclear Information System (INIS)

    Schneider, T.; Schieber, C.; Eeckhoudt, L.; Godfroid, P.

    2000-01-01

    The implementation of cost-benefit analysis for the optimisation of radiation protection relies on the adoption of a monetary value of the man-sievert. From the economic point of view, the monetary value of the man-sievert can be seen as a function reflecting the individual and collective preferences associated with the level of exposures and the specificity of the exposure situations. It must thus integrate several dimensions: one dimension, which is independent of the exposure situation, is related to the potential health effects associated with the level of exposure; other dimensions are related to social and equity consideration, reflecting the characteristics of exposure situation: distribution of individual exposures, individual and social risk perception,... In the case of occupational exposure, CEPN has developed a model to define the monetary values of the man-sievert according to the level of individual exposure. This model has been used by some European nuclear utilities for setting their own values to be used in the process of radiological protection optimisation for workers. The question arising now concerns the establishment of this value for public exposure. For this purpose, we have considered one of the main differences between public and worker exposures: i.e. the existence of compensation systems for the radiation induced health effects if they occur for the workers. In the case of public exposure, such systems do not exist, mainly due to the absence of a permanent individual monitoring of exposures and to the low level of individual exposure. A theoretical model was developed to evaluate the willingness to pay to reduce the probability of occurrence of a radiation induced health effects (i.e. to reduce the level of exposure). It shows that, because of the absence of a compensation system for the public, this willingness to pay should be higher when the probability is reduced for the public than for the workers. The result of the numerical

  17. Usage of Fuzzy Spatial Theory for Modelling of Terrain Passability

    Directory of Open Access Journals (Sweden)

    Alois Hofmann

    2013-01-01

    Full Text Available Geographic support of decision-making processes is based on various geographic products, usually in digital form, which come from various foundations and sources. Each product can be characterized by its quality or by its utility value for the given type of task or group of tasks, for which the product is used. They also usually have different characteristics and thus can very significantly influence the resulting analytical material. The aim of the paper is to contribute to the solution of the question of how it is possible to work with diverse spatial geographic information so that the user has an idea about the resulting product. The concept of fuzzy sets is used for representation of classes, whose boundaries are not clearly (not sharply set, namely, the fuzzy approach in overlaying operations realized in ESRI ArcGIS environment. The paper is based on a research project which is being solved at the Faculty of Military Technologies of the University of Defence. The research deals with the influence of geographic and climatic factors on the activity of armed forces and the Integrated Rescue System.

  18. Spatial Modelling of Land Price in The Semarang City

    Science.gov (United States)

    Widjonarko, W.

    2018-02-01

    Land has a very important role in supporting the population activity in both urban and rural areas. Demand for land tends to increase due to the increase in population, on the other hand the availability of land is limited. The increasing demand of land also occurred in the city of Semarang due to population growth and economic activity growth. The increasing demand for land in Semarang City has caused a shift in spatial demand patterns. The shift in land demand is due to limited supply of land in the area near to the city center, and the price become unaffordable for some residents of Semarang City. Due to the limitation of land supply in the city center has affected to the increasing demand of land in the suburbs. This phenomenon causes an increase in the price of land in the periphery of Semarang, and forms a land price pattern that resembles a circus tent, especially at a new center of activity on the periphery.

  19. Spatially Resolved Spectral Powder Analysis: Experiments and Modeling.

    Science.gov (United States)

    Scheibelhofer, Otto; Wahl, Patrick R; Larchevêque, Boris; Chauchard, Fabien; Khinast, Johannes G

    2018-01-01

    Understanding the behavior of light in granular media is necessary for determining the sample size, shape, and weight when probing using fiber optic setups. This is required for a correct estimate of the active pharmaceutical ingredient content in a pharmaceutical blend via near-infrared spectroscopy. Several strategies to describe the behavior of light in granular and turbid media exist. A common approach is the Monte-Carlo simulation of individual photons and their description using mean free path lengths for scattering and absorption. In this work, we chose a complementary method by approximating these parameters via real physical counterparts, i.e., the particle size, shape, and density and the resulting chord lengths. Additionally, the wavelength dependence of refractive indices is incorporated. The obtained results were compared with those obtained in an experimental setup that included the SAM-Spec Felin probe head by Indatech for detecting spatially resolved spectra of samples. Our method facilitates the interpretation of the acquired experimental results by contrasting the optical response, the physical particle attributes, and the simulation results.

  20. Toward establishing model organisms for marine protists: Successful transfection protocols for Parabodo caudatus (Kinetoplastida: Excavata).

    Science.gov (United States)

    Gomaa, Fatma; Garcia, Paulo A; Delaney, Jennifer; Girguis, Peter R; Buie, Cullen R; Edgcomb, Virginia P

    2017-09-01

    We developed protocols for, and demonstrated successful transfection of, the free-living kinetoplastid flagellate Parabodo caudatus with three plasmids carrying a fluorescence reporter gene (pEF-GFP with the EF1 alpha promoter, pUB-GFP with Ubiquitin C promoter, and pEYFP-Mitotrap with CMV promoter). We evaluated three electroporation approaches: (1) a square-wave electroporator designed for eukaryotes, (2) a novel microfluidic transfection system employing hydrodynamically-controlled electric field waveforms, and (3) a traditional exponential decay electroporator. We found the microfluidic device provides a simple and efficient platform to quickly test a wide range of electric field parameters to find the optimal set of conditions for electroporation of target species. It also allows for processing large sample volumes (>10 ml) within minutes, increasing throughput 100 times over cuvettes. Fluorescence signal from the reporter gene was detected a few hours after transfection and persisted for 3 days in cells transfected by pEF-GFP and pUB-GFP plasmids and for at least 5 days post-transfection for cells transfected with pEYFP-Mitotrap. Expression of the reporter genes (GFP and YFP) was also confirmed using reverse transcription-PCR (RT-PCR). This work opens the door for further efforts with this taxon and close relatives toward establishing model systems for genome editing. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

  1. Iron Biochemistry is Correlated with Amyloid Plaque Morphology in an Established Mouse Model of Alzheimer's Disease.

    Science.gov (United States)

    Telling, Neil D; Everett, James; Collingwood, Joanna F; Dobson, Jon; van der Laan, Gerrit; Gallagher, Joseph J; Wang, Jian; Hitchcock, Adam P

    2017-10-19

    A signature characteristic of Alzheimer's disease (AD) is aggregation of amyloid-beta (Aβ) fibrils in the brain. Nevertheless, the links between Aβ and AD pathology remain incompletely understood. It has been proposed that neurotoxicity arising from aggregation of the Aβ 1-42 peptide can in part be explained by metal ion binding interactions. Using advanced X-ray microscopy techniques at sub-micron resolution, we investigated relationships between iron biochemistry and AD pathology in intact cortex from an established mouse model over-producing Aβ. We found a direct correlation of amyloid plaque morphology with iron, and evidence for the formation of an iron-amyloid complex. We also show that iron biomineral deposits in the cortical tissue contain the mineral magnetite, and provide evidence that Aβ-induced chemical reduction of iron could occur in vivo. Our observations point to the specific role of iron in amyloid deposition and AD pathology, and may impact development of iron-modifying therapeutics for AD. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. [Establishment and validation of a neonatal pig model of hemolytic jaundice].

    Science.gov (United States)

    Li, Yong-Fu; Ma, Yue-Lan; Nie, Ling; Chen, Shuan; Jin, Mei-Fang; Wang, San-Lan

    2016-05-01

    To establish a neonatal pig model of hemolytic jaundice. Twelve seven-day-old purebred Yorkshire pigs were randomly divided into an experimental group and a control group (n=6 each). Immunization of New Zealand white rabbits was used to prepare rabbit anti-porcine red blood cell antibodies, and rabbit anti-porcine red blood cell serum was separated. The neonatal pigs in the experimental group were given an intravenous injection of rabbit anti-porcine red blood cell serum (5 mL), and those in the control group were given an intravenous injection of normal saline (5 mL). Venous blood samples were collected every 6 hours for routine blood test and liver function evaluation. The experimental group had a significantly higher serum bilirubin level than the control group at 18 hours after the injection of rabbit anti-porcine red blood cell serum (64±30 μmol/L vs 20±4 μmol/L; Pjaundice simulates the pathological process of human hemolytic jaundice well and provides good biological and material bases for further investigation of neonatal hemolysis.

  3. [Establishment and mechanisms of chemical interaction between phosphate monomer and zirconia model].

    Science.gov (United States)

    Zhicen, Lu; Haifeng, Xie; Feimin, Zhang; Huaiqin, Zhang; Chen, Chen

    2017-04-01

    To analyze chemical mechanism of bonding improvement of zirconia via 10-methacryloyloxydecyl dihydrogen phosphate (MDP) conditioning. Various models were created for tetragonal zirconia crystals, molecular MDP, and MDP complex, and tetragonal zirconia crystal. Thermodynamic methods were used to analyze configuration between MDP and tetragonal zirconia crystal through calculation of their Gibbs free energy values and equilibrium constants. Two potential configurations (double- and single-coordinate) may occur between MDP and ZrO2 crystal clusters. Thermodynamic calculations showed that -147.761 and -158.073 kJ·mol⁻¹ Gibbs free energy were required to form single- and double-coordinate configurations; their negative signs indicate that reactions for both configurations can occur. Equilibrium constant for single-coordinate configuration was 7.72×10²⁵, which was less than that of double-coordinate configuration (4.95×10²⁷), suggesting that the latter was more stable. MDP can spontaneously establish a double-coordinate configuration with zirconia.
.

  4. Establishment of a biophysical model to optimize endoscopic targeting of magnetic nanoparticles for cancer treatment.

    Science.gov (United States)

    Roeth, Anjali A; Slabu, Ioana; Baumann, Martin; Alizai, Patrick H; Schmeding, Maximilian; Guentherodt, Gernot; Schmitz-Rode, Thomas; Neumann, Ulf P

    2017-01-01

    Superparamagnetic iron oxide nanoparticles (SPION) may be used for local tumor treatment by coupling them to a drug and accumulating them locally with magnetic field traps, that is, a combination of permanent magnets and coils. Thereafter, an alternating magnetic field generates heat which may be used to release the thermosensitively bound drug and for hyperthermia. Until today, only superficial tumors can be treated with this method. Our aim was to transfer this method into an endoscopic setting to also reach the majority of tumors located inside the body. To find the ideal endoscopic magnetic field trap, which accumulates the most SPION, we first developed a biophysical model considering anatomical as well as physical conditions. Entities of choice were esophageal and prostate cancer. The magnetic susceptibilities of different porcine and rat tissues were measured with a superconducting quantum interference device. All tissues showed diamagnetic behavior. The evaluation of clinical data (computed tomography scan, endosonography, surgical reports, pathological evaluation) of patients gave insight into the topographical relationship between the tumor and its surroundings. Both were used to establish the biophysical model of the tumors and their surroundings, closely mirroring the clinical situation, in which we could virtually design, place and evaluate different electromagnetic coil configurations to find optimized magnetic field traps for each tumor entity. By simulation, we could show that the efficiency of the magnetic field traps can be enhanced by 38-fold for prostate and 8-fold for esophageal cancer. Therefore, our approach of endoscopic targeting is an improvement of the magnetic drug-targeting setups for SPION tumor therapy as it holds the possibility of reaching tumors inside the body in a minimal-invasive way. Future animal experiments must prove these findings in vivo.

  5. Stochastic ecological network occupancy (SENO) models: a new tool for modeling ecological networks across spatial scales

    Science.gov (United States)

    Lafferty, Kevin D.; Dunne, Jennifer A.

    2010-01-01

    Stochastic ecological network occupancy (SENO) models predict the probability that species will occur in a sample of an ecological network. In this review, we introduce SENO models as a means to fill a gap in the theoretical toolkit of ecologists. As input, SENO models use a topological interaction network and rates of colonization and extinction (including consumer effects) for each species. A SENO model then simulates the ecological network over time, resulting in a series of sub-networks that can be used to identify commonly encountered community modules. The proportion of time a species is present in a patch gives its expected probability of occurrence, whose sum across species gives expected species richness. To illustrate their utility, we provide simple examples of how SENO models can be used to investigate how topological complexity, species interactions, species traits, and spatial scale affect communities in space and time. They can categorize species as biodiversity facilitators, contributors, or inhibitors, making this approach promising for ecosystem-based management of invasive, threatened, or exploited species.

  6. The importance of spatial models for estimating the strength of density dependence

    DEFF Research Database (Denmark)

    Thorson, James T.; Skaug, Hans J.; Kristensen, Kasper

    2014-01-01

    for an entire population. However, it is increasingly recognized that spatial heterogeneity in population densities has implications for population and community dynamics. We therefore adapt the Gompertz model to approximate local densities over continuous space instead of population-wide abundance...... the California Coast. In this case, the nonspatial model estimates implausible oscillatory dynamics on an annual time scale, while the spatial model estimates strong autocorrelation and is supported by model selection tools. We conclude by discussing the importance of improved data archiving techniques, so...

  7. Can spatial data substitute temporal data in phenological modelling? A survey using birch flowering.

    Science.gov (United States)

    Jochner, Susanne; Caffarra, Amelia; Menzel, Annette

    2013-12-01

    In addition to the evaluation of long-term series, the analysis of spatial gradients, such as urbanization gradients, may be helpful in assessing phenological responses to global warming. But are phenological responses of birch (Betula pendula Roth) assessed by temperature variations comparable over time and space and can spatially calibrated models predict long-term phenological data adequately? We calibrated and tested linear regression models and the process-based DORMPHOT model on phenological and temperature data sampled along an urbanization gradient in 2010 and 2011 in the German cities Munich and Ingolstadt (spatial data). Additionally, we analysed data from the German Meteorological Service for the period 1991-2010 (long-term data). The model comparison showed that the DORMPHOT model performed better than the linear model. Therefore, the importance of forcing and chilling sums as well as photoperiod, factors which were all considered in the DORMPHOT model, was evident. Models calibrated on spatial data produced good predictions of spatial data, but they were less adequate for predicting long-term data. Therefore, a time-for-space substitution might not always be appropriate. This finding was also confirmed by a comparison of temperature response rates. The rate of change in the spatial data (-4.4 days °C(-1)) did not match the changes observed in the long-term data (-1.9 days °C(-1)). Consequently, it is important not to generalize results derived from one specific study method, but their inherent methodological, spatial and temporal peculiarities have to be considered.

  8. APPLICATION OF SPATIAL MODELLING APPROACHES, SAMPLING STRATEGIES AND 3S TECHNOLOGY WITHIN AN ECOLGOCIAL FRAMWORK

    Directory of Open Access Journals (Sweden)

    H.-C. Chen

    2012-07-01

    Full Text Available How to effectively describe ecological patterns in nature over broader spatial scales and build a modeling ecological framework has become an important issue in ecological research. We test four modeling methods (MAXENT, DOMAIN, GLM and ANN to predict the potential habitat of Schima superba (Chinese guger tree, CGT with different spatial scale in the Huisun study area in Taiwan. Then we created three sampling design (from small to large scales for model development and validation by different combinations of CGT samples from aforementioned three sites (Tong-Feng watershed, Yo-Shan Mountain, and Kuan-Dau watershed. These models combine points of known occurrence and topographic variables to infer CGT potential spatial distribution. Our assessment revealed that the method performance from highest to lowest was: MAXENT, DOMAIN, GLM and ANN on small spatial scale. The MAXENT and DOMAIN two models were the most capable for predicting the tree's potential habitat. However, the outcome clearly indicated that the models merely based on topographic variables performed poorly on large spatial extrapolation from Tong-Feng to Kuan-Dau because the humidity and sun illumination of the two watersheds are affected by their microterrains and are quite different from each other. Thus, the models developed from topographic variables can only be applied within a limited geographical extent without a significant error. Future studies will attempt to use variables involving spectral information associated with species extracted from high spatial, spectral resolution remotely sensed data, especially hyperspectral image data, for building a model so that it can be applied on a large spatial scale.

  9. Visual spatial localization and the two-process model

    OpenAIRE

    Uddin, Muhammad Kamal

    2006-01-01

    This review paper begins with a brief history of research on localization followed by its definition and classification. It also presents important parameters of localization and factors that affect localization. The paper gives an overview of the two-process model and highlights its limitations. A careful review exposed inadequacies in the model in particular and in localization research in general warranting a clear need for further investigations. Here the author reports findings of his se...

  10. Evaluation of spatial models to predict vulnerability of forest birds to brood parasitism by cowbirds

    Science.gov (United States)

    Gustafson, E.J.; Knutson, M.G.; Niemi, G.J.; Friberg, M.

    2002-01-01

    We constructed alternative spatial models at two scales to predict Brown-headed Cowbird (Molothrus ater) parasitism rates from land cover maps. The local-scale models tested competing hypotheses about the relationship between cowbird parasitism and distance of host nests from a forest edge (forest-nonforest boundary). The landscape models tested competing hypotheses about how landscape features (e.g., forests, agricultural fields) interact to determine rates of cowbird parasitism. The models incorporate spatial neighborhoods with a radius of 2.5 km in their formulation, reflecting the scale of the majority of cowbird commuting activity. Field data on parasitism by cowbirds (parasitism rate and number of cowbird eggs per nest) were collected at 28 sites in the Driftless Area Ecoregion of Wisconsin, Minnesota, and Iowa and were compared to the predictions of the alternative models. At the local scale, there was a significant positive relationship between cowbird parasitism and mean distance of nest sites from the forest edge. At the landscape scale, the best fitting models were the forest-dependent and forest-fragmentation-dependent models, in which more heavily forested and less fragmented landscapes had higher parasitism rates. However, much of the explanatory power of these models results from the inclusion of the local-scale relationship in these models. We found lower rates of cowbird parasitism than did most Midwestern studies, and we identified landscape patterns of cowbird parasitism that are opposite to those reported in several other studies of Midwestern songbirds. We caution that cowbird parasitism patterns can be unpredictable, depending upon ecoregional location and the spatial extent, and that our models should be tested in other ecoregions before they are applied there. Our study confirms that cowbird biology has a strong spatial component, and that improved spatial models applied at multiple spatial scales will be required to predict the effects of

  11. Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

    Science.gov (United States)

    Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

    2016-04-01

    Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model

  12. Extending Spatial Interaction Models with Agents for Understanding Relationships in a Dynamic Retail Market

    Directory of Open Access Journals (Sweden)

    Mark Birkin

    2011-01-01

    Full Text Available For many years, effective model-based representations of the dynamics and evolution of urban spatial structure have proved elusive. While some progress has been made through the deployment of spatial interaction models, these approaches have been limited by the difficulty of representing behavioural mechanisms and processes. In this paper, it is demonstrated that evolutionary models grounded in the principles of spatial interaction are compatible with the more novel approaches of agent-based modelling. The incorporation of agents provides a much more flexible means for the representation of behavioural mechanisms. The paper illustrates the way in which three more complicated situations can be handled through the fusion of spatial interaction and agent modelling perspectives. These situations comprise discontinuous evolution (in which structural adjustment takes place in discrete steps, and not as a continuously smooth process; nonequilibrium dynamics (in which the underlying system parameters continue to evolve through time; the incorporation of new decision variables (which we illustrate through the addition of land rents into the model. The conclusion of the paper is that the combination of spatial interaction and agent-based modelling methods provides encouraging prospects for the social simulation of real urban systems.

  13. Accounting for and predicting the influence of spatial autocorrelation in water quality modeling

    Science.gov (United States)

    Miralha, L.; Kim, D.

    2017-12-01

    Although many studies have attempted to investigate the spatial trends of water quality, more attention is yet to be paid to the consequences of considering and ignoring the spatial autocorrelation (SAC) that exists in water quality parameters. Several studies have mentioned the importance of accounting for SAC in water quality modeling, as well as the differences in outcomes between models that account for and ignore SAC. However, the capacity to predict the magnitude of such differences is still ambiguous. In this study, we hypothesized that SAC inherently possessed by a response variable (i.e., water quality parameter) influences the outcomes of spatial modeling. We evaluated whether the level of inherent SAC is associated with changes in R-Squared, Akaike Information Criterion (AIC), and residual SAC (rSAC), after accounting for SAC during modeling procedure. The main objective was to analyze if water quality parameters with higher Moran's I values (inherent SAC measure) undergo a greater increase in R² and a greater reduction in both AIC and rSAC. We compared a non-spatial model (OLS) to two spatial regression approaches (spatial lag and error models). Predictor variables were the principal components of topographic (elevation and slope), land cover, and hydrological soil group variables. We acquired these data from federal online sources (e.g. USGS). Ten watersheds were selected, each in a different state of the USA. Results revealed that water quality parameters with higher inherent SAC showed substantial increase in R² and decrease in rSAC after performing spatial regressions. However, AIC values did not show significant changes. Overall, the higher the level of inherent SAC in water quality variables, the greater improvement of model performance. This indicates a linear and direct relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. Therefore, our study suggests that the inherent level of

  14. Development of a Discrete Spatial-Temporal SEIR Simulator for Modeling Infectious Diseases

    Energy Technology Data Exchange (ETDEWEB)

    McKenna, S.A.

    2000-11-01

    Multiple techniques have been developed to model the temporal evolution of infectious diseases. Some of these techniques have also been adapted to model the spatial evolution of the disease. This report examines the application of one such technique, the SEIR model, to the spatial and temporal evolution of disease. Applications of the SEIR model are reviewed briefly and an adaptation to the traditional SEIR model is presented. This adaptation allows for modeling the spatial evolution of the disease stages at the individual level. The transmission of the disease between individuals is modeled explicitly through the use of exposure likelihood functions rather than the global transmission rate applied to populations in the traditional implementation of the SEIR model. These adaptations allow for the consideration of spatially variable (heterogeneous) susceptibility and immunity within the population. The adaptations also allow for modeling both contagious and non-contagious diseases. The results of a number of numerical experiments to explore the effect of model parameters on the spread of an example disease are presented.

  15. A dynamic phase transition model for spatial agglomeration processes.

    Science.gov (United States)

    Weidlich, W; Haag, G

    1987-11-01

    A nonlinear model of population migration is presented in order to provide a dynamic explanation for the formation of metropolitan areas. "In Section 2 the model is introduced in terms of the rate equations for the mean values of the regional population numbers with specifically chosen individual transition rates. Section 3 gives a survey of concepts and results for the convenience of the reader not interested in the details of the mathematical derivations. Section 4 derives the stationary solutions of the rate equations, that is, the equilibria of the system. Section 5 treats the time dependent solutions of the model equations focussing on the exact analytic solutions along so-called symmetry paths. Section 6 analyzes the dynamic stability of the symmetry path solutions and decides which stationary states are unstable and which are stable equilibrium states." excerpt

  16. Influence of Regional Climate Model spatial resolution on wind climates

    Science.gov (United States)

    Pryor, S. C.; Barthelmie, R. J.; Nikulin, G.; Jones, C.

    2010-12-01

    Global and regional climate models are being run at increasingly fine horizontal and vertical resolution with the goal of increased skill. However, relatively few studies have quantified the change in modeled wind climates that derives from applying a Regional Climate Model (RCM) at varying resolutions, and the response to varying resolution may be highly non-linear since most models run in climate mode are hydrostatic. Thus, herein we examine the influence of grid-resolution on modelled wind speeds and gusts and derived extremes thereof over southern Scandinavia using output from the Rossby Centre (RCA3) RCM run at four different resolutions from 50 x 50 km to 6 x 6 km, and with two different vertical grid-spacings. Domain averaged fifty-year return period wind speeds and wind gusts derived using the method of moments approach to compute the Gumbel parameters, increase with resolution (Table 1), though the change is strongly mediated by the model grid-cell surface characteristics. Power spectra of the 3-hourly model time-step ‘instantaneous’ wind speeds and daily wind gusts at all four resolutions show clear peaks in the variance associated with bi-annual, annual, seasonal and synoptic frequencies. The variance associated with these peaks is enhanced with increased resolution, though not in a monotonic fashion, and is more marked in wind gusts than wind speeds. Relative to in situ observations, the model generally underestimates the variance, particularly associated with the synoptic time scale, even for the highest resolution simulations. There is some evidence to suggest that the change in the power spectra with horizontal resolution is less marked in the transition from 12.5 km to 6.25 km, than from 50 to 25 km, or 25 km to 12.5 km.Table 1. Domain averaged mean annual wind speed (U), 50-year return period extreme wind speed (U50yr) and wind gust (Gust50yr) (m/s) from the four RCA3 simulations at different resolution based on output from 1987-2008. The

  17. Modeling urban growth and spatial structure in Nanjing, China with GIS and remote sensing

    Science.gov (United States)

    Luo, Jun

    This research focuses on the use of GIS, remote sensing and spatial modeling for studies on urban growth and spatial structure. Previous studies on urban growth modeling have not elaborated the spatial heterogeneity of urban growth pattern, which, however, is well recognized. The census population data is widely used for investigating urban spatial structure, but it has inherent various problems which can lead to biased analysis results. Studies on urban growth and spatial structure of Chinese cities remain limited due to the data availability and methodology development. In this dissertation, I initiate a new analysis framework and a new method to address these critical issues through a case study of Nanjing, China. The study first set up urban land expansion models for Nanjing in the period of 1988-2000. Landsat imageries are processed and classified to provide land use data in 1988 and 2000. GIS data are used to provide spatial variables inputs for the land use conversion models. A combined land use data sampling is conducted to obtain land use sample points for the proposed models. Classic logistic regression is used to reveal the urban land expansion from a global view. Furthermore, a logistic geographically weighted regression (GWR) model is set up to reveal the local variations of influence of spatial factors on urban land expansion. The study finds that the logistic GWR significantly improved the global logistic regression model and verifies that the influences of explanatory variables of urban growth are spatially varying. An urban growth probability surface is then generated based on the variable and parameter surfaces. This new framework for analyzing urban growth pattern may open a new direction for urban growth modeling. Second, the dissertation develops a new method, which utilizes detailed urban land parcel and building data to generate population surface of Nanjing in 2000. With this method, populations of small areas at intraurban level can be

  18. A statistical model for spatial patterns of Buruli ulcer in the Amansie West district, Ghana

    Science.gov (United States)

    Duker, Alfred A.; Stein, Alfred; Hale, Martin

    2006-06-01

    Buruli ulcer (BU), a skin ulceration caused by Mycobacterium ulcerans (MU), is the second most widespread mycobacterium infection in Ghana. Its infection pathway is possibly related to the potable and agricultural water supply. This study aims to identify environmental factors that influence infection in a part of Ghana. It examines the significance of contaminated surface drainage channels and groundwater using conditional autoregressive (CAR) statistical modelling. This type of modelling implies that the spatial pattern of BU incidence in one community depends on the influence of the environment in neighbouring communities. Covariates were included to assess the spatial relationship between environmental risk factors and BU incidence in the study area. The study reveals an association between (a) the mean As content of soil and spatial distribution of BU and (b) the distance to sites of gold mining and spatial distribution of BU. We conclude that both arsenic in the natural environment and gold mining influence BU infection.

  19. The spatial spread of schistosomiasis: A multidimensional network model applied to Saint-Louis region, Senegal

    Science.gov (United States)

    Ciddio, Manuela; Mari, Lorenzo; Sokolow, Susanne H.; De Leo, Giulio A.; Casagrandi, Renato; Gatto, Marino

    2017-10-01

    Schistosomiasis is a parasitic, water-related disease that is prevalent in tropical and subtropical areas of the world, causing severe and chronic consequences especially among children. Here we study the spatial spread of this disease within a network of connected villages in the endemic region of the Lower Basin of the Senegal River, in Senegal. The analysis is performed by means of a spatially explicit metapopulation model that couples local-scale eco-epidemiological dynamics with spatial mechanisms related to human mobility (estimated from anonymized mobile phone records), snail dispersal and hydrological transport of schistosome larvae along the main water bodies of the region. Results show that the model produces epidemiological patterns consistent with field observations, and point out the key role of spatial connectivity on the spread of the disease. These findings underline the importance of considering different transport pathways in order to elaborate disease control strategies that can be effective within a network of connected populations.

  20. Competition for marine space: modelling the Baltic Sea fisheries and effort displacement under spatial restrictions

    DEFF Research Database (Denmark)

    Bastardie, Francois; Nielsen, J. Rasmus; Eigaard, Ole Ritzau

    2015-01-01

    to fishery and from vessel to vessel. The impact assessment of new spatial plans involving fisheries should be based on quantitative bioeconomic analyses that take into account individual vessel decisions, and trade-offs in cross-sector conflicting interests.Weuse a vessel-oriented decision-support tool (the...... DISPLACE model) to combine stochastic variations in spatial fishing activities with harvested resource dynamics in scenario projections. The assessment computes economic and stock status indicators by modelling the activity of Danish, Swedish, and German vessels (.12 m) in the international western Baltic...... Sea commercial fishery, together with the underlying size-based distribution dynamics of the main fishery resources of sprat, herring, and cod. The outcomes of alternative scenarios for spatial effort displacement are exemplified by evaluating the fishers’s abilities to adapt to spatial plans under...

  1. Modeling spatial-temporal operations with context-dependent associative memories.

    Science.gov (United States)

    Mizraji, Eduardo; Lin, Juan

    2015-10-01

    We organize our behavior and store structured information with many procedures that require the coding of spatial and temporal order in specific neural modules. In the simplest cases, spatial and temporal relations are condensed in prepositions like "below" and "above", "behind" and "in front of", or "before" and "after", etc. Neural operators lie beneath these words, sharing some similarities with logical gates that compute spatial and temporal asymmetric relations. We show how these operators can be modeled by means of neural matrix memories acting on Kronecker tensor products of vectors. The complexity of these memories is further enhanced by their ability to store episodes unfolding in space and time. How does the brain scale up from the raw plasticity of contingent episodic memories to the apparent stable connectivity of large neural networks? We clarify this transition by analyzing a model that flexibly codes episodic spatial and temporal structures into contextual markers capable of linking different memory modules.

  2. Using an autologistic regression model to identify spatial risk factors and spatial risk patterns of hand, foot and mouth disease (HFMD) in Mainland China

    Science.gov (United States)

    2014-01-01

    Background There have been large-scale outbreaks of hand, foot and mouth disease (HFMD) in Mainland China over the last decade. These events varied greatly across the country. It is necessary to identify the spatial risk factors and spatial distribution patterns of HFMD for public health control and prevention. Climate risk factors associated with HFMD occurrence have been recognized. However, few studies discussed the socio-economic determinants of HFMD risk at a space scale. Methods HFMD records in Mainland China in May 2008 were collected. Both climate and socio-economic factors were selected as potential risk exposures of HFMD. Odds ratio (OR) was used to identify the spatial risk factors. A spatial autologistic regression model was employed to get OR values of each exposures and model the spatial distribution patterns of HFMD risk. Results Results showed that both climate and socio-economic variables were spatial risk factors for HFMD transmission in Mainland China. The statistically significant risk factors are monthly average precipitation (OR = 1.4354), monthly average temperature (OR = 1.379), monthly average wind speed (OR = 1.186), the number of industrial enterprises above designated size (OR = 17.699), the population density (OR = 1.953), and the proportion of student population (OR = 1.286). The spatial autologistic regression model has a good goodness of fit (ROC = 0.817) and prediction accuracy (Correct ratio = 78.45%) of HFMD occurrence. The autologistic regression model also reduces the contribution of the residual term in the ordinary logistic regression model significantly, from 17.25 to 1.25 for the odds ratio. Based on the prediction results of the spatial model, we obtained a map of the probability of HFMD occurrence that shows the spatial distribution pattern and local epidemic risk over Mainland China. Conclusions The autologistic regression model was used to identify spatial risk factors and model spatial risk patterns of HFMD. HFMD

  3. Using an autologistic regression model to identify spatial risk factors and spatial risk patterns of hand, foot and mouth disease (HFMD) in Mainland China.

    Science.gov (United States)

    Bo, Yan-Chen; Song, Chao; Wang, Jin-Feng; Li, Xiao-Wen

    2014-04-14

    There have been large-scale outbreaks of hand, foot and mouth disease (HFMD) in Mainland China over the last decade. These events varied greatly across the country. It is necessary to identify the spatial risk factors and spatial distribution patterns of HFMD for public health control and prevention. Climate risk factors associated with HFMD occurrence have been recognized. However, few studies discussed the socio-economic determinants of HFMD risk at a space scale. HFMD records in Mainland China in May 2008 were collected. Both climate and socio-economic factors were selected as potential risk exposures of HFMD. Odds ratio (OR) was used to identify the spatial risk factors. A spatial autologistic regression model was employed to get OR values of each exposures and model the spatial distribution patterns of HFMD risk. Results showed that both climate and socio-economic variables were spatial risk factors for HFMD transmission in Mainland China. The statistically significant risk factors are monthly average precipitation (OR = 1.4354), monthly average temperature (OR = 1.379), monthly average wind speed (OR = 1.186), the number of industrial enterprises above designated size (OR = 17.699), the population density (OR = 1.953), and the proportion of student population (OR = 1.286). The spatial autologistic regression model has a good goodness of fit (ROC = 0.817) and prediction accuracy (Correct ratio = 78.45%) of HFMD occurrence. The autologistic regression model also reduces the contribution of the residual term in the ordinary logistic regression model significantly, from 17.25 to 1.25 for the odds ratio. Based on the prediction results of the spatial model, we obtained a map of the probability of HFMD occurrence that shows the spatial distribution pattern and local epidemic risk over Mainland China. The autologistic regression model was used to identify spatial risk factors and model spatial risk patterns of HFMD. HFMD occurrences were found to be spatially

  4. Spatial modeling of geographic inequalities in infant and child mortality across Nepal.

    Science.gov (United States)

    Chin, Brian; Montana, Livia; Basagaña, Xavier

    2011-07-01

    A survival regression model that allows for spatially correlated random effects is used to predict the hazard of dying among 12,714 children born between 1996 and 2006 in Nepal. The maps of fitted hazard rates show that even after accounting for individual and community-level covariates, a residual spatial pattern in infant mortality remains, with higher mortality concentrated in parts of Nepal's Far-Western and Mid-Western development regions. Results suggest a need to consider health policies and programs that reach children in spatially concentrated high-mortality areas. Copyright © 2011 Elsevier Ltd. All rights reserved.