Spatial Evolutionary Games of Interaction among Generic Cancer Cells

DEFF Research Database (Denmark)

Bach, Lars Arve; Sumpter, David J.T.; Alsner, Jan

2003-01-01

Evolutionary game models of cellular interactions have shown that heterogeneity in the cellular genotypic composition is maintained through evolution to stable coexistence of growth-promoting and non-promoting cell types. We generalise these mean-field models and relax the assumption of perfect...... mixing of cells by instead implementing an individual-based model that includes the stochastic and spatial effects likely to occur in tumours. The scope for coexistence of genotypic strategies changed with the inclusion of explicit space and stochasticity. The spatial models show some interesting...... deviations from their mean-field counterparts, for example the possibility of altruistic (paracrine) cell strategies to thrive. Such effects can however, be highly sensitive to model implementation and the more realistic models with semi-synchronous and stochastic updating do not show evolution of altruism...

Spatial evolutionary games of interaction among generic cancer cells

DEFF Research Database (Denmark)

Bach, L.A.; Sumpter, D.J.T.; Alsner, J.

2003-01-01

Evolutionary game models of cellular interactions have shown that heterogeneity in the cellular genotypic composition is maintained through evolution to stable coexistence of growth-promoting and non-promoting cell types. We generalise these mean-field models and relax the assumption of perfect m...... at a cellular level. This study thus points a new direction towards more plausible spatial tumour modelling and the understanding of cancerous growth....

Spatial channel interactions in cochlear implants

Science.gov (United States)

Tang, Qing; Benítez, Raul; Zeng, Fan-Gang

2011-08-01

The modern multi-channel cochlear implant is widely considered to be the most successful neural prosthesis owing to its ability to restore partial hearing to post-lingually deafened adults and to allow essentially normal language development in pre-lingually deafened children. However, the implant performance varies greatly in individuals and is still limited in background noise, tonal language understanding, and music perception. One main cause for the individual variability and the limited performance in cochlear implants is spatial channel interaction from the stimulating electrodes to the auditory nerve and brain. Here we systematically examined spatial channel interactions at the physical, physiological, and perceptual levels in the same five modern cochlear implant subjects. The physical interaction was examined using an electric field imaging technique, which measured the voltage distribution as a function of the electrode position in the cochlea in response to the stimulation of a single electrode. The physiological interaction was examined by recording electrically evoked compound action potentials as a function of the electrode position in response to the stimulation of the same single electrode position. The perceptual interactions were characterized by changes in detection threshold as well as loudness summation in response to in-phase or out-of-phase dual-electrode stimulation. To minimize potentially confounding effects of temporal factors on spatial channel interactions, stimulus rates were limited to 100 Hz or less in all measurements. Several quantitative channel interaction indexes were developed to define and compare the width, slope and symmetry of the spatial excitation patterns derived from these physical, physiological and perceptual measures. The electric field imaging data revealed a broad but uniformly asymmetrical intracochlear electric field pattern, with the apical side producing a wider half-width and shallower slope than the basal

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.

Bayesian Inference of Ecological Interactions from Spatial Data

Directory of Open Access Journals (Sweden)

Christopher R. Stephens

2017-11-01

Full Text Available The characterization and quantification of ecological interactions and the construction of species’ distributions and their associated ecological niches are of fundamental theoretical and practical importance. In this paper, we discuss a Bayesian inference framework, which, using spatial data, offers a general formalism within which ecological interactions may be characterized and quantified. Interactions are identified through deviations of the spatial distribution of co-occurrences of spatial variables relative to a benchmark for the non-interacting system and based on a statistical ensemble of spatial cells. The formalism allows for the integration of both biotic and abiotic factors of arbitrary resolution. We concentrate on the conceptual and mathematical underpinnings of the formalism, showing how, using the naive Bayes approximation, it can be used to not only compare and contrast the relative contribution from each variable, but also to construct species’ distributions and ecological niches based on an arbitrary variable type. We also show how non-linear interactions between distinct niche variables can be identified and the degree of confounding between variables accounted for.

Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.

Science.gov (United States)

Endert, A; Fiaux, P; North, C

2012-12-01

Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.

Towards models of strategic spatial choice behaviour: theory and application issues

NARCIS (Netherlands)

Han, Q.; Timmermans, H.J.P.

2005-01-01

Models of spatial choice behaviour have been around in urban planning for decades to assess the feasibility of planning actions or to predict external (competition) effects on existing destinations. The well known spatial interaction models of the 1970s have gradually been replaced by discrete

Discrete choice models for commuting interactions

DEFF Research Database (Denmark)

Rouwendal, Jan; Mulalic, Ismir; Levkovich, Or

An emerging quantitative spatial economics literature models commuting interactions by a gravity equation that is mathematically equivalent to a multinomial logit model. This model is widely viewed as restrictive because of the independence of irrelevant alternatives (IIA) property that links sub...

Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases

Directory of Open Access Journals (Sweden)

Jean-Marie Aerts

2012-11-01

Full Text Available The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases.

Impact of spatial organization on a novel auxotrophic interaction among soil microbes.

Science.gov (United States)

Jiang, Xue; Zerfaß, Christian; Feng, Song; Eichmann, Ruth; Asally, Munehiro; Schäfer, Patrick; Soyer, Orkun S

2018-06-01

A key prerequisite to achieve a deeper understanding of microbial communities and to engineer synthetic ones is to identify the individual metabolic interactions among key species and how these interactions are affected by different environmental factors. Deciphering the physiological basis of species-species and species-environment interactions in spatially organized environments requires reductionist approaches using ecologically and functionally relevant species. To this end, we focus here on a defined system to study the metabolic interactions in a spatial context among the plant-beneficial endophytic fungus Serendipita indica, and the soil-dwelling model bacterium Bacillus subtilis. Focusing on the growth dynamics of S. indica under defined conditions, we identified an auxotrophy in this organism for thiamine, which is a key co-factor for essential reactions in the central carbon metabolism. We found that S. indica growth is restored in thiamine-free media, when co-cultured with B. subtilis. The success of this auxotrophic interaction, however, was dependent on the spatial and temporal organization of the system; the beneficial impact of B. subtilis was only visible when its inoculation was separated from that of S. indica either in time or space. These findings describe a key auxotrophic interaction in the soil among organisms that are shown to be important for plant ecosystem functioning, and point to the potential importance of spatial and temporal organization for the success of auxotrophic interactions. These points can be particularly important for engineering of minimal functional synthetic communities as plant seed treatments and for vertical farming under defined conditions.

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

DEFF Research Database (Denmark)

Khanmohammadi, Mahdieh; Waagepetersen, Rasmus; Nava, Nicoletta

2014-01-01

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

Spatial Attention and Audiovisual Interactions in Apparent Motion

Science.gov (United States)

Sanabria, Daniel; Soto-Faraco, Salvador; Spence, Charles

2007-01-01

In this study, the authors combined the cross-modal dynamic capture task (involving the horizontal apparent movement of visual and auditory stimuli) with spatial cuing in the vertical dimension to investigate the role of spatial attention in cross-modal interactions during motion perception. Spatial attention was manipulated endogenously, either…

Enhanced effects of biotic interactions on predicting multispecies spatial distribution of submerged macrophytes after eutrophication.

Science.gov (United States)

Song, Kun; Cui, Yichong; Zhang, Xijin; Pan, Yingji; Xu, Junli; Xu, Kaiqin; Da, Liangjun

2017-10-01

Water eutrophication creates unfavorable environmental conditions for submerged macrophytes. In these situations, biotic interactions may be particularly important for explaining and predicting the submerged macrophytes occurrence. Here, we evaluate the roles of biotic interactions in predicting spatial occurrence of submerged macrophytes in 1959 and 2009 for Dianshan Lake in eastern China, which became eutrophic since the 1980s. For the four common species occurred in 1959 and 2009, null species distribution models based on abiotic variables and full models based on both abiotic and biotic variables were developed using generalized linear model (GLM) and boosted regression trees (BRT) to determine whether the biotic variables improved the model performance. Hierarchical Bayesian-based joint species distribution models capable of detecting paired biotic interactions were established for each species in both periods to evaluate the changes in the biotic interactions. In most of the GLM and BRT models, the full models showed better performance than the null models in predicting the species presence/absence, and the relative importance of the biotic variables in the full models increased from less than 50% in 1959 to more than 50% in 2009 for each species. Moreover, co-occurrence correlation of each paired species interaction was higher in 2009 than that in 1959. The findings suggest biotic interactions that tend to be positive play more important roles in the spatial distribution of multispecies assemblages of macrophytes and should be included in prediction models to improve prediction accuracy when forecasting macrophytes' distribution under eutrophication stress.

Verbal-spatial and visuospatial coding of power-space interactions.

Science.gov (United States)

Dai, Qiang; Zhu, Lei

2018-05-10

A power-space interaction, which denotes the phenomenon that people responded faster to powerful words when they are placed higher in a visual field and faster to powerless words when they are placed lower in a visual field, has been repeatedly found. The dominant explanation of this power-space interaction is that it results from a tight correspondence between the representation of power and visual space (i.e., a visuospatial coding account). In the present study, we demonstrated that the interaction between power and space could be also based on a verbal-spatial coding in absence of any vertical spatial information. Additionally, the verbal-spatial coding was dominant in driving the power-space interaction when verbal space was contrasted with the visual space. Copyright © 2018 Elsevier Inc. All rights reserved.

FIND: difFerential chromatin INteractions Detection using a spatial Poisson process.

Science.gov (United States)

Djekidel, Mohamed Nadhir; Chen, Yang; Zhang, Michael Q

2018-02-12

Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio. © 2018 Djekidel et al.; Published by Cold Spring Harbor Laboratory Press.

Interspecific bacterial interactions are reflected in multispecies biofilm spatial organization

DEFF Research Database (Denmark)

Liu, Wenzheng; Røder, Henriette Lyng; Madsen, Jonas Stenløkke

2016-01-01

not only the enabling sub-populations. However, the specific molecular mechanisms of cellular processes affecting spatial organization, and vice versa, are poorly understood and very complex to unravel. Therefore, detailed description of the spatial organization of individual bacterial cells...... environments. Species residing in these complex bacterial communities usually interact both intra- and interspecifically. Such interactions are considered to not only be fundamental in shaping overall biomass and the spatial distribution of cells residing in multispecies biofilms, but also to result......, industrial, and clinical implications. This review briefly presents the state of the art of studying interspecies interactions and spatial organization of multispecies communities, aiming to support theoretical and practical arguments for further advancement of this field....

Modulation of the Object/Background Interaction by Spatial Frequency

Directory of Open Access Journals (Sweden)

Yanju Ren

2011-05-01

Full Text Available With regard to the relationship between object and background perception in the natural scene images, functional isolation hypothesis and interactive hypothesis were proposed. Based on previous studies, the present study investigated the role of spatial frequency in the relationship between object and background perception in the natural scene images. In three experiments, participants reported the object, background, or both after seeing each picture for 500 ms followed by a mask. The authors found that (a backgrounds were identified more accurately when they contained a consistent rather than an inconsistent object, independently of spatial frequency; (b objects were identified more accurately in a consistent than an inconsistent background under the condition of low spatial frequencies but not high spatial frequencies; (c spatial frequency modulation remained when both objects and backgrounds were reported simultaneously. The authors conclude that object/background interaction is partially dependent on spatial frequency.

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 ...

Spatial Sound and Multimodal Interaction in Immersive Environments

DEFF Research Database (Denmark)

Grani, Francesco; Overholt, Daniel; Erkut, Cumhur

2015-01-01

primary problem areas: 1) creation of interactive spatial audio experiences for immersive virtual and augmented reality scenarios, and 2) production and mixing of spatial audio for cinema, music, and other artistic contexts. Several ongoing research projects are described, wherein the latest developments...

Urban strategy: Noise mapping in instrument for interactive spatial planning

NARCIS (Netherlands)

Borst, H.C.; Salomons, E.M.; Lohman, W.J.A.; Zhou, H.; Miedema, H.M.E.

2009-01-01

Spatial planning in urban areas is complex. Besides noise from different source types, many other aspects play a role. In order to support local authorities and others involved in spatial planning, TNO has developed an interactive instrument: 'Urban Strategy', which integrates a detailed interactive

Nonlinear interaction model of subsonic jet noise.

Science.gov (United States)

Sandham, Neil D; Salgado, Adriana M

2008-08-13

Noise generation in a subsonic round jet is studied by a simplified model, in which nonlinear interactions of spatially evolving instability modes lead to the radiation of sound. The spatial mode evolution is computed using linear parabolized stability equations. Nonlinear interactions are found on a mode-by-mode basis and the sound radiation characteristics are determined by solution of the Lilley-Goldstein equation. Since mode interactions are computed explicitly, it is possible to find their relative importance for sound radiation. The method is applied to a single stream jet for which experimental data are available. The model gives Strouhal numbers of 0.45 for the most amplified waves in the jet and 0.19 for the dominant sound radiation. While in near field axisymmetric and the first azimuthal modes are both important, far-field sound is predominantly axisymmetric. These results are in close correspondence with experiment, suggesting that the simplified model is capturing at least some of the important mechanisms of subsonic jet noise.

Spatial Interaction Modeling to Identify Potentially Exposed Populations during RDD or IND Terrorism Incidents

International Nuclear Information System (INIS)

Regens, J.L.; Gunter, J.T.; Gupta, S.

2009-01-01

Homeland Security Presidential Directive no.5 (HSPD-5) Management of Domestic Incidents and Department of Homeland Security (DHS) Planning Guidance for Protection and Recovery Following Radiological Dispersal Device (RDD) and Improvised Nuclear Device (IND) Incidents underscore the need to delineate radiological emergency guidance applicable to remedial action and recovery following an RDD or IND incident. Rapid delineation of the population potentially exposed to ionizing radiation from fallout during terrorist incidents involving RDDs or low-yield nuclear devices (≤ 20 KT) is necessary for effective medical response and incident management as part of the recovery process. This paper illustrates the application of spatial interaction models to allocate population data for a representative U.S. urban area (≅1.3M people; 1,612.27 km 2 area) at a geographical scale relevant for accurately estimating risk given dose concentrations. Estimated total dose equivalents (TEDE) are calculated for isopleths moving away from the detonation point for typical release scenarios. Population is estimated within the TEDE zones using Euclidean distances between zip code polygon centroids generated in ArcGIS version 9.1 with distance decay determined by regression analysis to apportion origin-destination pairs to a population count and density matrix on a spatial basis for daytime and night-time release scenarios. (authors)

Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

Science.gov (United States)

Liu, Da; Li, Jianxun

2016-12-16

Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

Numerical Simulation of a Grinding Process Model for the Spatial Work-pieces: Development of Modeling Techniques

Directory of Open Access Journals (Sweden)

S. A. Voronov

2015-01-01

Full Text Available The article presents a literature review in simulation of grinding processes. It takes into consideration the statistical, energy based, and imitation approaches to simulation of grinding forces. Main stages of interaction between abrasive grains and machined surface are shown. The article describes main approaches to the geometry modeling of forming new surfaces when grinding. The review of approaches to the chip and pile up effect numerical modeling is shown. Advantages and disadvantages of grain-to-surface interaction by means of finite element method and molecular dynamics method are considered. The article points out that it is necessary to take into consideration the system dynamics and its effect on the finished surface. Structure of the complex imitation model of grinding process dynamics for flexible work-pieces with spatial surface geometry is proposed from the literature review. The proposed model of spatial grinding includes the model of work-piece dynamics, model of grinding wheel dynamics, phenomenological model of grinding forces based on 3D geometry modeling algorithm. Model gives the following results for spatial grinding process: vibration of machining part and grinding wheel, machined surface geometry, static deflection of the surface and grinding forces under various cutting conditions.

Interspecific bacterial interactions are reflected in multispecies biofilm spatial organization

Directory of Open Access Journals (Sweden)

Wenzheng Liu

2016-08-01

Full Text Available Interspecies interactions are essential for the persistence and development of any kind of complex community, and microbial biofilms are no exception. Multispecies biofilms are structured and spatially defined communities that have received much attention due to their omnipresence in natural environments. Species residing in these complex bacterial communities usually interact both intra- and interspecifically. Such interactions are considered to not only be fundamental in shaping overall biomass and the spatial distribution of cells residing in multispecies biofilms, but also to result in coordinated regulation of gene expression in the different species present. These communal interactions often lead to emergent properties in biofilms, such as enhanced tolerance against antibiotics, host immune responses and other stresses, which have been shown to provide benefits to all biofilm members not only the enabling sub-populations. However, the specific molecular mechanisms of cellular processes affecting spatial organization, and vice versa, are poorly understood and very complex to unravel. Therefore, detailed description of the spatial organization of individual bacterial cells in multispecies communities can be an alternative strategy to reveal the nature of interspecies interactions of constituent species. Closing the gap between visual observation and biological processes may become crucial for resolving biofilm related problems, which is of utmost importance to environmental, industrial, and clinical implications. This review briefly presents the state of the art of studying interspecies interactions and spatial organization of multispecies communities, aiming to support theoretical and practical arguments for further advancement of this field.

Models of the Dynamics of Spatially Separated Broadband Electromagnetic Fields Interacting with Resonant Atoms

Science.gov (United States)

Basharov, A. M.

2018-03-01

The Markov model of spontaneous emission of an atom localized in a spatial region with a broadband electromagnetic field with zero photon density is considered in the conditions of coupling of the electromagnetic field with the broadband field of a neighboring space. The evolution operator of the system and the kinetic equation for the atom are obtained. It is shown that the field coupling constant affects the rate of spontaneous emission of the atom, but is not manifested in the atomic frequency shift. The analytic expression for the radiative decay constant for the atom is found to be analogous in a certain sense to the expression for the decay constant for a singly excited localized ensemble of identical atoms in the conditions when the effect of stabilization of its excited state by the Stark interaction with the vacuum broadband electromagnetic field is manifested. The model is formulated based on quantum stochastic differential equations of the non- Wiener type and the generalized algebra of the Ito differential of quantum random processes.

Stochastic population oscillations in spatial predator-prey models

International Nuclear Information System (INIS)

Taeuber, Uwe C

2011-01-01

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

A family of spatial interaction models incorporating information flows and choice set constraints applied to U.S. interstate labor flows.

Science.gov (United States)

Smith, T R; Slater, P B

1981-01-01

"A new family of migration models belonging to the elimination by aspects family is examined, with the spatial interaction model shown to be a special case. The models have simple forms; they incorporate information flow processes and choice set constraints; they are free of problems raised by the Luce Choice Axiom; and are capable of generating intransitive flows. Preliminary calibrations using the Continuous Work History Sample [time] series data indicate that the model fits the migration data well, while providing estimates of interstate job message flows. The preliminary calculations also indicate that care is needed in assuming that destination [attraction] are independent of origins." excerpt

Analyzing the Effects of Spatial Interaction among City Clusters on Urban Growth—Case of Wuhan Urban Agglomeration

Directory of Open Access Journals (Sweden)

Ronghui Tan

2016-08-01

Full Text Available For the past two decades, China’s urbanization has attracted increasing attention from scholars around the world. Numerous insightful studies have attempted to determine the socioeconomic causes of the rapid urban growth in Chinese cities. However, most of these studies regarded each city as a single entity, with few considering inter-city relationships. The present study uses a gravity-based model to measure the spatial interaction among city clusters in the Wuhan urban agglomeration (WUA, which is one of China’s most rapidly urbanizing regions. The effects of spatial interaction on urban growth area were also analyzed. Empirical results indicate that, similar to urban population or employment in secondary and tertiary industries in the WUA from 2000 to 2005, the spatial interaction among city clusters is one of the main drivers of urban growth. In fact, this study finds the effects of spatial interaction as the only socioeconomic factor that affected the spatial expansion from 2005 to 2010. This finding suggests that population migration and information and commodity flows showed greater influence than the socioeconomic drivers of each city did on promoting urbanization in the WUA during this period. We thus argue that spatial interaction among city clusters should be a consideration in future regional planning.

Bose-Einstein condensates with spatially inhomogeneous interaction and bright solitons

International Nuclear Information System (INIS)

Shin, H.J.; Radha, R.; Kumar, V. Ramesh

2011-01-01

In this Letter, we investigate the dynamics of Bose-Einstein Condensates (BECs) with spatially inhomogeneous interaction and generate bright solitons for the condensates by solving the associated mean field description governed by the Gross-Pitaevskii (GP) equation. We then investigate the properties of BECs in an optical lattice and periodic potential. We show that the GP equation in an optical lattice potential is integrable provided the interaction strength between the atoms varies periodically in space. The model discussed in the Letter offers the luxury of choosing the form of the lattice without destroying the integrability. Besides, we have also brought out the possible ramifications of the integrable model in the condensates of quasi-particles. -- Highlights: → We generate bright solitons for the collisionally inhomogeneous BECs. → We then study their properties in an optical lattice and periodic potential. → The model may have wider ramifications in the BECs of quasi-particles.

Prefrontal-hippocampal interactions for spatial navigation.

Science.gov (United States)

Ito, Hiroshi T

2018-04-01

Animals have the ability to navigate to a desired location by making use of information about environmental landmarks and their own movements. While decades of neuroscience research have identified neurons in the hippocampus and parahippocampal structures that represent an animal's position in space, it is still largely unclear how an animal can choose the next movement direction to reach a desired goal. As the goal destination is typically located somewhere outside of the range of sensory perception, the animal is required to rely on the internal metric of space to estimate the direction and distance of the destination to plan a next action. Therefore, the hippocampal spatial map should interact with action-planning systems in other cortical regions. In accordance with this idea, several recent studies have indicated the importance of functional interactions between the hippocampus and the prefrontal cortex for goal-directed navigation. In this paper, I will review these studies and discuss how an animal can estimate its future positions correspond to a next movement. Investigation of the navigation problem may further provide general insights into internal models of the brain for action planning. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

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.

Modeling object pursuit for 3D interactive tasks in virtual reality

NARCIS (Netherlands)

Liu, L.; Liere, van R.

2011-01-01

Models of interaction tasks are quantitative descriptions of relationships between human temporal performance and the spatial characteristics of the interactive tasks. Examples include Fitts' law for modeling the pointing task and Accot and Zhai's steering law for the path steering task, etc. Models

Spatial interaction models from Irish commuting data: variations in trip length by occupation and gender

Science.gov (United States)

O'Kelly, Morton E.; Niedzielski, Michael A.; Gleeson, Justin

2012-10-01

Core and peripheral contrasts in journey-to-work trip length can be interpreted as imputing the relative value of origin and destination accessibility (yielding theoretical proxies for rent and wages). Because the main variables are shown to be critically dependent on spatial structure, they may be interpreted as showing the shadow prices due to comparative location. There is also a unifying connection between these results and the existing literature on many dimensions: rent gradients, accessibility, and emissivity. In an empirical example, the advantages of a panoramic view of national commuting statistics are shown, using an Irish data set. Variations in the rates of participation in trip making by location, occupation, and gender are examined. Places that emit more trips than would be expected from their relative location are identified. Further, examining ways in which such emissivity is sensitive to a change in trip length highlights the regions where trips could possibly be adjusted to produce a shorter average trip length or which might be especially sensitive to reduction in employment. A careful reinterpretation of one of the key outputs from a calibrated spatial interaction model is shown to be consistent with the declining rent gradient expected from Alonso's theory of land use.

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.

Spatial competition for biogas production using insights from retail location models

DEFF Research Database (Denmark)

Bojesen, Mikkel; Birkin, M.; Clarke, G.

2014-01-01

production sector. Through a two-step approach by combining a location-allocation model with a production constrained spatial interaction model, this paper addresses the dual problem of determining optimal location and production capacity. What-if scenarios, in combination with the strategic economic...

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...

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

DEFF Research Database (Denmark)

Rasmussen, Jakob Gulddahl; Møller, Jesper

2007-01-01

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

Stochastic heterogeneous interaction promotes cooperation in spatial prisoner's dilemma game.

Directory of Open Access Journals (Sweden)

Ping Zhu

Full Text Available Previous studies mostly investigate player's cooperative behavior as affected by game time-scale or individual diversity. In this paper, by involving both time-scale and diversity simultaneously, we explore the effect of stochastic heterogeneous interaction. In our model, the occurrence of game interaction between each pair of linked player obeys a random probability, which is further described by certain distributions. Simulations on a 4-neighbor square lattice show that the cooperation level is remarkably promoted when stochastic heterogeneous interaction is considered. The results are then explained by investigating the mean payoffs, the mean boundary payoffs and the transition probabilities between cooperators and defectors. We also show some typical snapshots and evolution time series of the system. Finally, the 8-neighbor square lattice and BA scale-free network results indicate that the stochastic heterogeneous interaction can be robust against different network topologies. Our work may sharpen the understanding of the joint effect of game time-scale and individual diversity on spatial games.

Multilayer networks reveal the spatial structure of seed-dispersal interactions across the Great Rift landscapes.

Science.gov (United States)

Timóteo, Sérgio; Correia, Marta; Rodríguez-Echeverría, Susana; Freitas, Helena; Heleno, Ruben

2018-01-10

Species interaction networks are traditionally explored as discrete entities with well-defined spatial borders, an oversimplification likely impairing their applicability. Using a multilayer network approach, explicitly accounting for inter-habitat connectivity, we investigate the spatial structure of seed-dispersal networks across the Gorongosa National Park, Mozambique. We show that the overall seed-dispersal network is composed by spatially explicit communities of dispersers spanning across habitats, functionally linking the landscape mosaic. Inter-habitat connectivity determines spatial structure, which cannot be accurately described with standard monolayer approaches either splitting or merging habitats. Multilayer modularity cannot be predicted by null models randomizing either interactions within each habitat or those linking habitats; however, as habitat connectivity increases, random processes become more important for overall structure. The importance of dispersers for the overall network structure is captured by multilayer versatility but not by standard metrics. Highly versatile species disperse many plant species across multiple habitats, being critical to landscape functional cohesion.

Investigating “Locality” of Intra-Urban Spatial Interactions in New York City Using Foursquare Data

Directory of Open Access Journals (Sweden)

Yeran Sun

2016-03-01

Full Text Available Thanks to the increasing popularity of location-based social networks, a large amount of user-generated geo-referenced check-in data is now available, and such check-in data is becoming a new data source in the study of mobility and travel. Conventionally, spatial interactions between places were measured based on the trips made between them. This paper empirically investigates the use of social media data (i.e., Foursquare data to study the “locality” of such intra-urban spatial interactions in New York City, and specifically: (i the level of “locality” of spatial interactions; (ii the impacts of personal characteristics on “locality” of spatial interaction and finally; (iii the heterogeneity in spatial distribution of “local” interactions. The results of this study indicate that: (1 spatial interactions show a high degree of locality; (2 gender does not have a considerable impact on the locality of spatial interactions and finally; (3 “local” interactions likely cluster in some places within the research city.

Towards a 3d Spatial Urban Energy Modelling Approach

Science.gov (United States)

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

2013-09-01

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

Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model.

Science.gov (United States)

Gürsoy, Gamze; Xu, Yun; Liang, Jie

2017-07-01

Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.

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

Spatial structure of single and interacting Mn acceptors in GaAs

Science.gov (United States)

Koenraad, Paul

2005-03-01

Ferromagnetic semiconductors such as Ga1-xMnxAs are receiving a lot of attention at the moment because of their application in spintronic devices. However, despite intense study of deep acceptors in III-V semiconductors such as MnGa, little information has been obtained on their electronic properties at the atomic scale. Yet the spatial shape of the Mn acceptor state will influence the hole-mediated Mn-Mn coupling and thus all of the magnetic properties of ferromagnetic semiconductors such as Ga1-xMnxAs. This study presents an experimental and theoretical description of the spatial symmetry of the Mn acceptor wave-function in GaAs. We present measurements of the spatial mapping of the anisotropic wavefunction of a hole localized at a Mn acceptor. To achieve this, we have used the STM tip not only to image the Mn acceptor but also to manipulate its charge state A^0/A^- at room temperature. Within an envelope function effective mass model (EFM) the anisotropy in the acceptor wave-function can be traced to the influence of the cubic symmetry of the GaAs crystal which selects specific d-states that mix into the ground state due to the spin-orbit interaction in the valence band. Comparison with calculations based on a tight-binding model (TBM) for the Mn acceptor structure supports this conclusion. Using the same experimental and theoretical approach we furthermore explored the interaction between Mn acceptors directly by analyzing close Mn-Mn pairs, which were separated by less than 2 nm. We will discuss some implications of these results for Mn delta-doped layers grown on differently oriented growth surfaces.

Quadratic spatial soliton interactions

Science.gov (United States)

Jankovic, Ladislav

Quadratic spatial soliton interactions were investigated in this Dissertation. The first part deals with characterizing the principal features of multi-soliton generation and soliton self-reflection. The second deals with two beam processes leading to soliton interactions and collisions. These subjects were investigated both theoretically and experimentally. The experiments were performed by using potassium niobate (KNBO 3) and periodically poled potassium titanyl phosphate (KTP) crystals. These particular crystals were desirable for these experiments because of their large nonlinear coefficients and, more importantly, because the experiments could be performed under non-critical-phase-matching (NCPM) conditions. The single soliton generation measurements, performed on KNBO3 by launching the fundamental component only, showed a broad angular acceptance bandwidth which was important for the soliton collisions performed later. Furthermore, at high input intensities multi-soliton generation was observed for the first time. The influence on the multi-soliton patterns generated of the input intensity and beam symmetry was investigated. The combined experimental and theoretical efforts indicated that spatial and temporal noise on the input laser beam induced multi-soliton patterns. Another research direction pursued was intensity dependent soliton routing by using of a specially engineered quadratically nonlinear interface within a periodically poled KTP sample. This was the first time demonstration of the self-reflection phenomenon in a system with a quadratic nonlinearity. The feature investigated is believed to have a great potential for soliton routing and manipulation by engineered structures. A detailed investigation was conducted on two soliton interaction and collision processes. Birth of an additional soliton resulting from a two soliton collision was observed and characterized for the special case of a non-planar geometry. A small amount of spiraling, up to 30

Thermodynamic Model of Spatial Memory

Science.gov (United States)

Kaufman, Miron; Allen, P.

1998-03-01

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

Modeling molecular mixing in a spatially inhomogeneous turbulent flow

Science.gov (United States)

Meyer, Daniel W.; Deb, Rajdeep

2012-02-01

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

A Spatially Explicit Dual-Isotope Approach to Map Regions of Plant-Plant Interaction after Exotic Plant Invasion.

Directory of Open Access Journals (Sweden)

Christine Hellmann

Full Text Available Understanding interactions between native and invasive plant species in field settings and quantifying the impact of invaders in heterogeneous native ecosystems requires resolving the spatial scale on which these processes take place. Therefore, functional tracers are needed that enable resolving the alterations induced by exotic plant invasion in contrast to natural variation in a spatially explicit way. 15N isoscapes, i.e., spatially referenced representations of stable nitrogen isotopic signatures, have recently provided such a tracer. However, different processes, e.g. water, nitrogen or carbon cycles, may be affected at different spatial scales. Thus multi-isotope studies, by using different functional tracers, can potentially return a more integrated picture of invader impact. This is particularly true when isoscapes are submitted to statistical methods suitable to find homogeneous subgroups in multivariate data such as cluster analysis. Here, we used model-based clustering of spatially explicit foliar δ15N and δ13C isoscapes together with N concentration of a native indicator species, Corema album, to map regions of influence in a Portuguese dune ecosystem invaded by the N2-fixing Acacia longifolia. Cluster analysis identified regions with pronounced alterations in N budget and water use efficiency in the native species, with a more than twofold increase in foliar N, and δ13C and δ15N enrichment of up to 2‰ and 8‰ closer to the invader, respectively. Furthermore, clusters of multiple functional tracers indicated a spatial shift from facilitation through N addition in the proximity of the invader to competition for resources other than N in close contact. Finding homogeneous subgroups in multi-isotope data by means of model-based cluster analysis provided an effective tool for detecting spatial structure in processes affecting plant physiology and performance. The proposed method can give an objective measure of the spatial extent

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.

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...

Characterization and spatial modeling of urban sprawl in the Wuhan Metropolitan Area, China

Science.gov (United States)

Zeng, Chen; Liu, Yaolin; Stein, Alfred; Jiao, Limin

2015-02-01

Urban sprawl has led to environmental problems and large losses of arable land in China. In this study, we monitor and model urban sprawl by means of a combination of remote sensing, geographical information system and spatial statistics. We use time-series data to explore the potential socio-economic driving forces behind urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions. The methodology is applied to the city of Wuhan, China, for the period from 1990 to 2013. The results reveal that the built-up land has expanded and has dispersed in urban clusters. Population growth, and economic and transportation development are still the main causes of urban sprawl; however, when they have developed to certain levels, the area affected by construction in urban areas (Jian Cheng Qu (JCQ)) and the area of cultivated land (ACL) tend to be stable. Spatial regression models are shown to be superior to the traditional models. The interaction among districts with the same administrative status is stronger than if one of those neighbors is in the city center and the other in the suburban area. The expansion of urban built-up land is driven by the socio-economic development at the same period, and greatly influenced by its spatio-temporal neighbors. We conclude that the integration of remote sensing, a geographical information system, and spatial statistics offers an excellent opportunity to explore the spatio-temporal variation and interactions among the districts in the sprawling metropolitan areas. Relevant regulations to control the urban sprawl process are suggested accordingly.

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.

Thematic and spatial resolutions affect model-based predictions of tree species distribution.

Science.gov (United States)

Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

Spatial Impairment and Memory in Genetic Disorders: Insights from Mouse Models

Directory of Open Access Journals (Sweden)

Sang Ah Lee

2017-02-01

Full Text Available Research across the cognitive and brain sciences has begun to elucidate some of the processes that guide navigation and spatial memory. Boundary geometry and featural landmarks are two distinct classes of environmental cues that have dissociable neural correlates in spatial representation and follow different patterns of learning. Consequently, spatial navigation depends both on the type of cue available and on the type of learning provided. We investigated this interaction between spatial representation and memory by administering two different tasks (working memory, reference memory using two different environmental cues (rectangular geometry, striped landmark in mouse models of human genetic disorders: Prader-Willi syndrome (PWScrm+/p− mice, n = 12 and Beta-catenin mutation (Thr653Lys-substituted mice, n = 12. This exploratory study provides suggestive evidence that these models exhibit different abilities and impairments in navigating by boundary geometry and featural landmarks, depending on the type of memory task administered. We discuss these data in light of the specific deficits in cognitive and brain function in these human syndromes and their animal model counterparts.

Evidence of political yardstick competition in France using a two-regime spatial Durbin model with fixed effects

NARCIS (Netherlands)

Elhorst, J. Paul; Freret, Sandy

2009-01-01

This research proposes a two-regime spatial Durbin model with spatial and time-period fixed effects to test for political yardstick competition and exclude any other explanation that might produce spatial interaction effects among the dependent variable, the independent variables, or the error term.

Sustaining plants and people: traditional Q'eqchi' Maya botanical knowledge and interactive spatial modeling in prioritizing conservation of medicinal plants for culturally relative holistic health promotion.

Science.gov (United States)

Pesek, Todd; Abramiuk, Marc; Garagic, Denis; Fini, Nick; Meerman, Jan; Cal, Victor

2009-03-01

Ethnobotanical surveys were conducted to locate culturally important, regionally scarce, and disappearing medicinal plants via a novel participatory methodology which involves healer-expert knowledge in interactive spatial modeling to prioritize conservation efforts and thus facilitate health promotion via medicinal plant resource sustained availability. These surveys, conducted in the Maya Mountains, Belize, generate ethnobotanical, ecological, and geospatial data on species which are used by Q'eqchi' Maya healers in practice. Several of these mountainous species are regionally scarce and the healers are expressing difficulties in finding them for use in promotion of community health and wellness. Based on healers' input, zones of highest probability for locating regionally scarce, disappearing, and culturally important plants in their ecosystem niches can be facilitated by interactive modeling. In the present study, this is begun by choosing three representative species to train an interactive predictive model. Model accuracy was then assessed statistically by testing for independence between predicted occurrence and actual occurrence of medicinal plants. A high level of accuracy was achieved using a small set of exemplar data. This work demonstrates the potential of combining ethnobotany and botanical spatial information with indigenous ecosystems concepts and Q'eqchi' Maya healing knowledge via predictive modeling. Through this approach, we may identify regions where species are located and accordingly promote for prioritization and application of in situ and ex situ conservation strategies to protect them. This represents a significant step toward facilitating sustained culturally relative health promotion as well as overall enhanced ecological integrity to the region and the earth.

Bayesian Spatial Modelling with R-INLA

Directory of Open Access Journals (Sweden)

Finn Lindgren

2015-02-01

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

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Science.gov (United States)

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-02-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally

Visualisation and research strategy for computational spatial and structural design interaction

NARCIS (Netherlands)

Peeten, D.; Hofmeyer, H.; Thabet, W

2010-01-01

A research engine is under development for studying the interaction of spatial and structural design processes. The design processes are being implemented as two separate configurable transformation steps; a conversion step and an optimisation step. A significant part of the spatial-to-structural

Advances in nonmarket valuation econometrics: Spatial heterogeneity in hedonic pricing models and preference heterogeneity in stated preference models

Science.gov (United States)

Yoo, Jin Woo

In my 1st essay, the study explores Pennsylvania residents. willingness to pay for development of renewable energy technologies such as solar power, wind power, biomass electricity, and other renewable energy using a choice experiment method. Principle component analysis identified 3 independent attitude components that affect the variation of preference, a desire for renewable energy and environmental quality and concern over cost. The results show that urban residents have a higher desire for environmental quality and concern less about cost than rural residents and consequently have a higher willingness to pay to increase renewable energy production. The results of sub-sample analysis show that a representative respondent in rural (urban) Pennsylvania is willing to pay 3.8(5.9) and 4.1(5.7)/month for increasing the share of Pennsylvania electricity generated from wind power and other renewable energy by 1 percent point, respectively. Mean WTP for solar and biomass electricity was not significantly different from zero. In my second essay, heterogeneity of individual WTP for various renewable energy technologies is investigated using several different variants of the multinomial logit model: a simple MNL with interaction terms, a latent class choice model, a random parameter mixed logit choice model, and a random parameter-latent class choice model. The results of all models consistently show that respondents. preference for individual renewable technology is heterogeneous, but the degree of heterogeneity differs for different renewable technologies. In general, the random parameter logit model with interactions and a hybrid random parameter logit-latent class model fit better than other models and better capture respondents. heterogeneity of preference for renewable energy. The impact of the land under agricultural conservation easement (ACE) contract on the values of nearby residential properties is investigated using housing sales data in two Pennsylvania

Herbivore-induced plant volatiles and tritrophic interactions across spatial scales.

Science.gov (United States)

Aartsma, Yavanna; Bianchi, Felix J J A; van der Werf, Wopke; Poelman, Erik H; Dicke, Marcel

2017-12-01

Herbivore-induced plant volatiles (HIPVs) are an important cue used in herbivore location by carnivorous arthropods such as parasitoids. The effects of plant volatiles on parasitoids have been well characterised at small spatial scales, but little research has been done on their effects at larger spatial scales. The spatial matrix of volatiles ('volatile mosaic') within which parasitoids locate their hosts is dynamic and heterogeneous. It is shaped by the spatial pattern of HIPV-emitting plants, the concentration, chemical composition and breakdown of the emitted HIPV blends, and by environmental factors such as wind, turbulence and vegetation that affect transport and mixing of odour plumes. The volatile mosaic may be exploited differentially by different parasitoid species, in relation to species traits such as sensory ability to perceive volatiles and the physical ability to move towards the source. Understanding how HIPVs influence parasitoids at larger spatial scales is crucial for our understanding of tritrophic interactions and sustainable pest management in agriculture. However, there is a large gap in our knowledge on how volatiles influence the process of host location by parasitoids at the landscape scale. Future studies should bridge the gap between the chemical and behavioural ecology of tritrophic interactions and landscape ecology. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

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)

Self-Organized Societies: On the Sakoda Model of Social Interactions

Directory of Open Access Journals (Sweden)

Pablo Medina

2017-01-01

Full Text Available We characterize the behavior and the social structures appearing from a model of general social interaction proposed by Sakoda. The model consists of two interacting populations in a two-dimensional periodic lattice with empty sites. It contemplates a set of simple rules that combine attitudes, ranges of interactions, and movement decisions. We analyze the evolution of the 45 different interaction rules via a Potts-like energy function which drives the system irreversibly to an equilibrium or a steady state. We discuss the robustness of the social structures, dynamical behaviors, and the existence of spatial long range order in terms of the social interactions and the equilibrium energy.

Models of chromatin spatial organisation in the cell nucleus

Science.gov (United States)

Nicodemi, Mario

2014-03-01

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

Some dynamical aspects of interacting quintessence model

Science.gov (United States)

Choudhury, Binayak S.; Mondal, Himadri Shekhar; Chatterjee, Devosmita

2018-04-01

In this paper, we consider a particular form of coupling, namely B=σ (\\dot{ρ _m}-\\dot{ρ _φ }) in spatially flat (k=0) Friedmann-Lemaitre-Robertson-Walker (FLRW) space-time. We perform phase-space analysis for this interacting quintessence (dark energy) and dark matter model for different numerical values of parameters. We also show the phase-space analysis for the `best-fit Universe' or concordance model. In our analysis, we observe the existence of late-time scaling attractors.

Intelligent spatial ecosystem modeling using parallel processors

International Nuclear Information System (INIS)

Maxwell, T.; Costanza, R.

1993-01-01

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

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.

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.

Modeling strategic investment decisions in spatial markets

Energy Technology Data Exchange (ETDEWEB)

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

2014-04-15

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

Residual analysis for spatial point processes

DEFF Research Database (Denmark)

Baddeley, A.; Turner, R.; Møller, Jesper

We define residuals for point process models fitted to spatial point pattern data, and propose diagnostic plots based on these residuals. The techniques apply to any Gibbs point process model, which may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Ou...... or covariate effects. Q-Q plots of the residuals are effective in diagnosing interpoint interaction. Some existing ad hoc statistics of point patterns (quadrat counts, scan statistic, kernel smoothed intensity, Berman's diagnostic) are recovered as special cases....

Research Techniques Made Simple: Emerging Methods to Elucidate Protein Interactions through Spatial Proximity.

Science.gov (United States)

Che, Yonglu; Khavari, Paul A

2017-12-01

Interactions between proteins are essential for fundamental cellular processes, and the diversity of such interactions enables the vast variety of functions essential for life. A persistent goal in biological research is to develop assays that can faithfully capture different types of protein interactions to allow their study. A major step forward in this direction came with a family of methods that delineates spatial proximity of proteins as an indirect measure of protein-protein interaction. A variety of enzyme- and DNA ligation-based methods measure protein co-localization in space, capturing novel interactions that were previously too transient or low affinity to be identified. Here we review some of the methods that have been successfully used to measure spatially proximal protein-protein interactions. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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....

Using Spatial Semantics and Interactions to Identify Urban Functional Regions

Directory of Open Access Journals (Sweden)

Yandong Wang

2018-03-01

Full Text Available The spatial structures of cities have changed dramatically with rapid socio-economic development in ways that are not well understood. To support urban structural analysis and rational planning, we propose a framework to identify urban functional regions and quantitatively explore the intensity of the interactions between them, thus increasing the understanding of urban structures. A method for the identification of functional regions via spatial semantics is proposed, which involves two steps: (1 the study area is classified into three types of functional regions using taxi origin/destination (O/D flows; and (2 the spatial semantics for the three types of functional regions are demonstrated based on point-of-interest (POI categories. To validate the existence of urban functional regions, we explored the intensity of interactions quantitatively between them. A case study using POI data and taxi trajectory data from Beijing validates the proposed framework. The results show that the proposed framework can be used to identify urban functional regions and promotes an enhanced understanding of urban structures.

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

Science.gov (United States)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

Quantifying long-term evolution of intra-urban spatial interactions

Science.gov (United States)

Sun, Lijun; Jin, Jian Gang; Axhausen, Kay W.; Lee, Der-Horng; Cebrian, Manuel

2015-01-01

Understanding the long-term impact that changes in a city's transportation infrastructure have on its spatial interactions remains a challenge. The difficulty arises from the fact that the real impact may not be revealed in static or aggregated mobility measures, as these are remarkably robust to perturbations. More generally, the lack of longitudinal, cross-sectional data demonstrating the evolution of spatial interactions at a meaningful urban scale also hinders us from evaluating the sensitivity of movement indicators, limiting our capacity to understand the evolution of urban mobility in depth. Using very large mobility records distributed over 3 years, we quantify the impact of the completion of a metro line extension: the Circle Line (CCL) in Singapore. We find that the commonly used movement indicators are almost identical before and after the project was completed. However, in comparing the temporal community structure across years, we do observe significant differences in the spatial reorganization of the affected geographical areas. The completion of CCL enables travellers to re-identify their desired destinations collectively with lower transport cost, making the community structure more consistent. These changes in locality are dynamic and characterized over short timescales, offering us a different approach to identify and analyse the long-term impact of new infrastructures on cities and their evolution dynamics. PMID:25551142

Spatial variation in near-ground radiation and low temperature. Interactions with forest vegetation

Energy Technology Data Exchange (ETDEWEB)

Blennow, K.

1997-10-01

Low temperature has a large impact on the survival and distribution of plants. Interactive effects with high irradiance lead to cold-induced photo inhibition, which may impact on the establishment and growth of tree seedlings. In this thesis, novel approaches are applied for relating the spatial variability in low temperature and irradiance to photosynthetic performance and growth of tree seedlings, and for modelling the micro- and local-scale spatial variations in low temperature for heterogeneous terrain. The methodologies include the development and use of a digital image analysis system for hemispherical photographs, the use of Geographic Information Systems (GIS) and statistical methods, field data acquisition of meteorological elements, plant structure, growth and photosynthetic performance. Temperature and amounts of intercepted direct radiant energy for seedlings on clear days (IDRE) were related to chlorophyll a fluorescence, and the dry weight of seedlings. The combination of increased IDRE with reduced minimum temperatures resulted in persistent and strong photo inhibition as the season progressed, with likely implications for the establishment of tree seedlings at forest edges, and within shelter wood. For models of spatial distribution of low air temperature, the sky view factor was used to parameterize the radiative cooling, whilst drainage, ponding and stagnation of cold air, and thermal properties of the ground were all considered. The models hint at which scales and processes govern the development of spatial variations in low temperature for the construction of corresponding mechanistic models. The methodology is well suited for detecting areas that will be frost prone after clearing of forest and for comparing the magnitudes of impacts on low air temperature of forest management practices, such as shelter wood and soil preparation. The results can be used to formulate ground rules for use in practical forestry 141 refs, 5 figs, 1 tab

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

NARCIS (Netherlands)

Helbich, M; Griffith, D

2016-01-01

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

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...

Spatially Distributed, Coupled Modeling of Plant Growth, Nitrogen and Water Fluxes in an Alpine Catchment

Science.gov (United States)

Schneider, K.

2001-12-01

Carbon, water and nitrogen fluxes are closely coupled. They interact and have many feedbacks. Human interference, in particular through land use management and global change strongly modifies these fluxes. Increasing demands and conflicting interests result in an increasing need for regulation targeting different aspects of the system. Without being their main target, many of these measures directly affect water quantity, quality and availability. Improved management and planning of our water resources requires the development of integrated tools, in particular since interactions of the involved environmental and social systems often lead to unexpected or adverse results. To investigate the effect of plant growth, land use management and global change on water fluxes and quality, the PROcess oriented Modular EnvironmenT and Vegetation Model (PROMET-V) was developed. PROMET-V models the spatial patterns and temporal course of water, carbon and nitrogen fluxes using process oriented and mechanistic model components. The hydrological model is based on the Penman-Monteith approach, it uses a plant-physiological model to calculate the canopy conductance, and a multi-layer soil water model. Plant growth for different vegetation is modelled by calculating canopy photosynthesis, respiration, phenology and allocation. Plant growth and water fluxes are coupled directly through photosynthesis and transpiration. Many indirect feedbacks and interactions occur due to their mutual dependency upon leaf area, root distribution, water and nutrient availability for instance. PROMET-V calculates nitrogen fluxes and transformations. The time step used depends upon the modelled process and varies from 1 hour to 1 day. The kernel model is integrated in a raster GIS system for spatially distributed modelling. PROMET-V was tested in a pre-alpine landscape (Ammer river, 709 km**2, located in Southern Germany) which is characterized by small scale spatial heterogeneities of climate, soil and

Spatial occupancy models for large data sets

Science.gov (United States)

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

2013-01-01

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

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

Science.gov (United States)

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

Interacting viscous ghost tachyon, K-essence and dilaton scalar field models of dark energy

International Nuclear Information System (INIS)

Karami, K; Fahimi, K

2013-01-01

We study the correspondence between the interacting viscous ghost dark energy model with the tachyon, K-essence and dilaton scalar field models in the framework of Einstein gravity. We consider a spatially non-flat FRW universe filled with interacting viscous ghost dark energy and dark matter. We reconstruct both the dynamics and potential of these scalar field models according to the evolutionary behavior of the interacting viscous ghost dark energy model, which can describe the accelerated expansion of the universe. Our numerical results show that the interaction and viscosity have opposite effects on the evolutionary properties of the ghost scalar field models. (paper)

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.

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.

Spatial modelling with R-INLA: A review

KAUST Repository

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

2018-01-01

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

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.

Statistical pairwise interaction model of stock market

Science.gov (United States)

Bury, Thomas

2013-03-01

Financial markets are a classical example of complex systems as they are compound by many interacting stocks. As such, we can obtain a surprisingly good description of their structure by making the rough simplification of binary daily returns. Spin glass models have been applied and gave some valuable results but at the price of restrictive assumptions on the market dynamics or they are agent-based models with rules designed in order to recover some empirical behaviors. Here we show that the pairwise model is actually a statistically consistent model with the observed first and second moments of the stocks orientation without making such restrictive assumptions. This is done with an approach only based on empirical data of price returns. Our data analysis of six major indices suggests that the actual interaction structure may be thought as an Ising model on a complex network with interaction strengths scaling as the inverse of the system size. This has potentially important implications since many properties of such a model are already known and some techniques of the spin glass theory can be straightforwardly applied. Typical behaviors, as multiple equilibria or metastable states, different characteristic time scales, spatial patterns, order-disorder, could find an explanation in this picture.

Spatial interactions database development for effective probabilistic risk assessment

International Nuclear Information System (INIS)

Liming, J. K.; Dunn, R. F.

2008-01-01

In preparation for a subsequent probabilistic risk assessment (PRA) fire risk analysis update, the STP Nuclear Operating Company (STPNOC) is updating its spatial interactions database (SID). This work is being performed to support updating the spatial interactions analysis (SIA) initially performed for the original South Texas Project Electric Generating Station (STPEGS) probabilistic safely assessment (PSA) and updated in the STPEGS Level 2 PSA and IPE Report. S/A is a large-scope screening analysis performed for nuclear power plant PRA that serves as a prerequisite basis for more detailed location-dependent, hazard-spec analyses in the PRA, such as fire risk analysis, flooding risk analysis, etc. SIA is required to support the 'completeness' argument for the PRA scope. The objectives of the current SID development effort are to update the spatial interactions analysis data, to the greatest degree practical, to be consistent with the following: the as-built plant as of December 31, 2007 the in-effect STPNOC STPEGS Units 1 and 2 PRA the current technology and intent of NUREG/CR-6850 guidance for lire risk analysis database support the requirements for PRA SIA, including fire and flooding risk analysis, established by NRC Regulatory Guide 1.200 and the ASME PRA Standard (ASME RA-S-2002 updated through ASME RA-Sc-2007,) This paper presents the approach and methodology for state-of-the-art SID development and applications, including an overview of the SIA process for nuclear power plant PRA. The paper shows how current relational database technology and existing, conventional station information sources can be employed to collect, process, and analyze spatial interactions data for the plant in an effective and efficient manner to meet the often challenging requirements of industry guidelines and standards such as NUREG/CR-6850, NRC Regulatory Guide 1.200, and ASME RA-S-2002 (updated through ASME RA-Sc 2007). This paper includes tables and figures illustrating how SIA

The stock-flow model of spatial data infrastructure development refined by fuzzy logic.

Science.gov (United States)

Abdolmajidi, Ehsan; Harrie, Lars; Mansourian, Ali

2016-01-01

The system dynamics technique has been demonstrated to be a proper method by which to model and simulate the development of spatial data infrastructures (SDI). An SDI is a collaborative effort to manage and share spatial data at different political and administrative levels. It is comprised of various dynamically interacting quantitative and qualitative (linguistic) variables. To incorporate linguistic variables and their joint effects in an SDI-development model more effectively, we suggest employing fuzzy logic. Not all fuzzy models are able to model the dynamic behavior of SDIs properly. Therefore, this paper aims to investigate different fuzzy models and their suitability for modeling SDIs. To that end, two inference and two defuzzification methods were used for the fuzzification of the joint effect of two variables in an existing SDI model. The results show that the Average-Average inference and Center of Area defuzzification can better model the dynamics of SDI development.

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago.

Science.gov (United States)

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E; Pellissier, Loïc

2018-03-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns.

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago

Science.gov (United States)

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E.

2018-01-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns. PMID:29657753

Delineation of spatial-temporal patterns of groundwater/surface-water interaction along a river reach (Aa River, Belgium) with transient thermal modeling

Science.gov (United States)

Anibas, Christian; Tolche, Abebe Debele; Ghysels, Gert; Nossent, Jiri; Schneidewind, Uwe; Huysmans, Marijke; Batelaan, Okke

2017-12-01

Among the advances made in analytical and numerical analysis methods to quantify groundwater/surface-water interaction, one methodology that stands out is the use of heat as an environmental tracer. A large data set of river and riverbed temperature profiles from the Aa River in Belgium has been used to examine the spatial-temporal variations of groundwater/surface-water interaction. Exchange fluxes were calculated with the numerical heat-transport code STRIVE. The code was applied in transient mode to overcome previous limitations of steady-state analysis, and allowed for the calculation of model quality. In autumn and winter the mean exchange fluxes reached -90 mm d-1, while in spring and early summer fluxes were -42 mm d-1. Predominantly gaining conditions occurred along the river reach; however, in a few areas the direction of flow changed in time. The river banks showed elevated fluxes up to a factor of 3 compared to the center of the river. Higher fluxes were detected in the upstream section of the reach. Due to the influence of exchange fluxes along the river banks, larger temporal variations were found in the downstream section. The exchange fluxes at the river banks seemed more driven by variable local exchange flows, while the center of the river was dominated by deep and steady regional groundwater flows. These spatial and temporal differences in groundwater/surface-water exchange show the importance of long-term investigations on the driving forces of hyporheic processes across different scales.

Delineation of spatial-temporal patterns of groundwater/surface-water interaction along a river reach (Aa River, Belgium) with transient thermal modeling

Science.gov (United States)

Anibas, Christian; Tolche, Abebe Debele; Ghysels, Gert; Nossent, Jiri; Schneidewind, Uwe; Huysmans, Marijke; Batelaan, Okke

2018-05-01

Among the advances made in analytical and numerical analysis methods to quantify groundwater/surface-water interaction, one methodology that stands out is the use of heat as an environmental tracer. A large data set of river and riverbed temperature profiles from the Aa River in Belgium has been used to examine the spatial-temporal variations of groundwater/surface-water interaction. Exchange fluxes were calculated with the numerical heat-transport code STRIVE. The code was applied in transient mode to overcome previous limitations of steady-state analysis, and allowed for the calculation of model quality. In autumn and winter the mean exchange fluxes reached -90 mm d-1, while in spring and early summer fluxes were -42 mm d-1. Predominantly gaining conditions occurred along the river reach; however, in a few areas the direction of flow changed in time. The river banks showed elevated fluxes up to a factor of 3 compared to the center of the river. Higher fluxes were detected in the upstream section of the reach. Due to the influence of exchange fluxes along the river banks, larger temporal variations were found in the downstream section. The exchange fluxes at the river banks seemed more driven by variable local exchange flows, while the center of the river was dominated by deep and steady regional groundwater flows. These spatial and temporal differences in groundwater/surface-water exchange show the importance of long-term investigations on the driving forces of hyporheic processes across different scales.

Spatial data quality and coastal spill modelling

International Nuclear Information System (INIS)

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

1998-01-01

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

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

Science.gov (United States)

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

Control of spatial discretisation in coastal oil spill modelling

OpenAIRE

Li, Yang

2007-01-01

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

Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

Science.gov (United States)

Žukovič, Milan; Hristopulos, Dionissios T.

2009-02-01

A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of

Representing climate, disturbance, and vegetation interactions in landscape models

Science.gov (United States)

Robert E. Keane; Donald McKenzie; Donald A. Falk; Erica A.H. Smithwick; Carol Miller; Lara-Karena B. Kellogg

2015-01-01

The prospect of rapidly changing climates over the next century calls for methods to predict their effects on myriad, interactive ecosystem processes. Spatially explicit models that simulate ecosystem dynamics at fine (plant, stand) to coarse (regional, global) scales are indispensable tools for meeting this challenge under a variety of possible futures. A special...

Spatial heterogeneity of plant-soil feedback affects root interactions and interspecific competition.

Science.gov (United States)

Hendriks, Marloes; Ravenek, Janneke M; Smit-Tiekstra, Annemiek E; van der Paauw, Jan Willem; de Caluwe, Hannie; van der Putten, Wim H; de Kroon, Hans; Mommer, Liesje

2015-08-01

Plant-soil feedback is receiving increasing interest as a factor influencing plant competition and species coexistence in grasslands. However, we do not know how spatial distribution of plant-soil feedback affects plant below-ground interactions. We investigated the way in which spatial heterogeneity of soil biota affects competitive interactions in grassland plant species. We performed a pairwise competition experiment combined with heterogeneous distribution of soil biota using four grassland plant species and their soil biota. Patches were applied as quadrants of 'own' and 'foreign' soils from all plant species in all pairwise combinations. To evaluate interspecific root responses, species-specific root biomass was quantified using real-time PCR. All plant species suffered negative soil feedback, but strength was species-specific, reflected by a decrease in root growth in own compared with foreign soil. Reduction in root growth in own patches by the superior plant competitor provided opportunities for inferior competitors to increase root biomass in these patches. These patterns did not cascade into above-ground effects during our experiment. We show that root distributions can be determined by spatial heterogeneity of soil biota, affecting plant below-ground competitive interactions. Thus, spatial heterogeneity of soil biota may contribute to plant species coexistence in species-rich grasslands. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Longitudinal patterns and response lengths of algae in riverine ecosystems: A model analysis emphasising benthic-pelagic interactions.

Science.gov (United States)

Jäger, Christoph G; Borchardt, Dietrich

2018-04-07

In riverine ecosystems primary production is principally possible in two habitats: in the benthic layer by sessile algae and in the surface water by planktonic algae being transported downstream. The relevance of these two habitats generally changes along the rivers' continuum. However, analyses of the interaction of algae in these two habitats and their controlling factors in riverine ecosystems are, so far, very rare. We use a simplified advection-diffusion model system combined with ecological process kinetics to analyse the interaction of benthic and planktonic algae and nutrients along idealised streams and rivers at regional to large scales. Because many of the underlying processes affecting algal dynamics are influenced by depth, we focus particularly on the impact of river depth on this interaction. At constant environmental conditions all state variables approach stable spatial equilibria along the river, independent of the boundary conditions at the upstream end. Because our model is very robust against changes of turbulent diffusion and stream velocity, these spatial equilibria can be analysed by a simplified ordinary differential equation (ode) version of our model. This model variant reveals that at shallower river depths, phytoplankton can exist only when it is subsidised by detaching benthic algae, and in turn, at deeper river depths, benthic algae can exist only in low biomasses which are subsidised by sinking planktonic algae. We generalise the spatial dynamics of the model system using different conditions at the upstream end of the model, which mimic various natural or anthropogenic factors (pristine source, dam, inflow of a waste water treatment plant, and dilution from e.g. a tributary) and analyse how these scenarios influence different aspects of the longitudinal spatial dynamics of the full spatial model: the relation of spatial equilibrium to spatial maximum, the distance to the spatial maximum, and the response length. Generally, our

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

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.

The spatial limitations of current neutral models of biodiversity.

Directory of Open Access Journals (Sweden)

Rampal S Etienne

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

Evaluating spatial patterns in hydrological modelling

DEFF Research Database (Denmark)

Koch, Julian

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

Individual Differences in Verbal and Spatial Stroop Tasks: Interactive Role of Handedness and Domain

Directory of Open Access Journals (Sweden)

Mariagrazia Capizzi

2017-11-01

Full Text Available A longstanding debate in psychology concerns the relation between handedness and cognitive functioning. The present study aimed to contribute to this debate by comparing performance of right- and non-right-handers on verbal and spatial Stroop tasks. Previous studies have shown that non-right-handers have better inter-hemispheric interaction and greater access to right hemisphere processes. On this ground, we expected performance of right- and non-right-handers to differ on verbal and spatial Stroop tasks. Specifically, relative to right-handers, non-right-handers should have greater Stroop effect in the color-word Stroop task, for which inter-hemispheric interaction does not seem to be advantageous to performance. By contrast, non-right-handers should be better able to overcome interference in the spatial Stroop task. This is for their preferential access to the right hemisphere dealing with spatial material and their greater inter-hemispheric interaction with the left hemisphere hosting Stroop task processes. Our results confirmed these predictions, showing that handedness and the underlying brain asymmetries may be a useful variable to partly explain individual differences in executive functions.

Spatially telescoping measurements for improved characterization of groundwater-surface water interactions

Science.gov (United States)

Kikuchi, Colin; Ferre, Ty P.A.; Welker, Jeffery M.

2012-01-01

The suite of measurement methods available to characterize fluxes between groundwater and surface water is rapidly growing. However, there are few studies that examine approaches to design of field investigations that include multiple methods. We propose that performing field measurements in a spatially telescoping sequence improves measurement flexibility and accounts for nested heterogeneities while still allowing for parsimonious experimental design. We applied this spatially telescoping approach in a study of ground water-surface water (GW-SW) interaction during baseflow conditions along Lucile Creek, located near Wasilla, Alaska. Catchment-scale data, including channel geomorphic indices and hydrogeologic transects, were used to screen areas of potentially significant GW-SW exchange. Specifically, these data indicated increasing groundwater contribution from a deeper regional aquifer along the middle to lower reaches of the stream. This initial assessment was tested using reach-scale estimates of groundwater contribution during baseflow conditions, including differential discharge measurements and the use of chemical tracers analyzed in a three-component mixing model. The reach-scale measurements indicated a large increase in discharge along the middle reaches of the stream accompanied by a shift in chemical composition towards a regional groundwater end member. Finally, point measurements of vertical water fluxes -- obtained using seepage meters as well as temperature-based methods -- were used to evaluate spatial and temporal variability of GW-SW exchange within representative reaches. The spatial variability of upward fluxes, estimated using streambed temperature mapping at the sub-reach scale, was observed to vary in relation to both streambed composition and the magnitude of groundwater contribution from differential discharge measurements. The spatially telescoping approach improved the efficiency of this field investigation. Beginning our assessment

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

Science.gov (United States)

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

2018-05-01

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

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

NARCIS (Netherlands)

Elhorst, J. Paul

2001-01-01

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

Spatially varying dispersion to model breakthrough curves.

Science.gov (United States)

Li, Guangquan

2011-01-01

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

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

Science.gov (United States)

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

2005-01-01

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

Spatial patterns and temporal dynamics of global scale climate-groundwater interactions

Science.gov (United States)

Cuthbert, M. O.; Gleeson, T. P.; Moosdorf, N.; Schneider, A. C.; Hartmann, J.; Befus, K. M.; Lehner, B.

2017-12-01

The interactions between groundwater and climate are important to resolve in both space and time as they influence mass and energy transfers at Earth's land surface. Despite the significance of these processes, little is known about the spatio-temporal distribution of such interactions globally, and many large-scale climate, hydrological and land surface models oversimplify groundwater or exclude it completely. In this study we bring together diverse global geomatic data sets to map spatial patterns in the sensitivity and degree of connectedness between the water table and the land surface, and use the output from a global groundwater model to assess the locations where the lateral import or export of groundwater is significant. We also quantify the groundwater response time, the characteristic time for groundwater systems to respond to a change in boundary conditions, and map its distribution globally to assess the likely dynamics of groundwater's interaction with climate. We find that more than half of the global land surface significantly exports or imports groundwater laterally. Nearly 40% of Earth's landmass has water tables that are strongly coupled to topography with water tables shallow enough to enable a bi-directional exchange of moisture with the climate system. However, only a small proportion (around 12%) of such regions have groundwater response times of 100 years or less and have groundwater fluxes that would significantly respond to rapid environmental changes over this timescale. We last explore fundamental relationships between aridity, groundwater response times and groundwater turnover times. Our results have wide ranging implications for understanding and modelling changes in Earth's water and energy balance and for informing robust future water management and security decisions.

Continuous Spatial Process Models for Spatial Extreme Values

KAUST Repository

Sang, Huiyan; Gelfand, Alan E.

2010-01-01

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

Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models

Science.gov (United States)

Haslauer, C. P.; Bárdossy, A.

2017-12-01

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

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

Process of optimization of retail trade spatial development with application of locational-alocational models

Directory of Open Access Journals (Sweden)

Kukrika Milan

2008-01-01

Full Text Available This article gives a simple and brief scope of structure and usage of location-allocation models in territory planning of retail network, trying to show the main shortage of some given models and the primary direction of their future improving. We give an inspection of theirs main usage and give an explanation of basic factors that models take in consideration during the process of demand allocation. Location-allocation models are an important segment of development of spatial retail network optimization process. Their future improvement is going towards their approximation and integration with spatial-interaction models. In this way, much better methodology of planning and directing spatial development of trade general. Methodology which we have used in this research paper is based on the literature and research projects in the area. Using this methodology in analyzing parts of Serbian territory through usage of location-allocation models, showed the need for creating special software for calculating matrix with recursions. Considering the fact that the integration of location-allocation models with GIS still didn't occur, all the results acquired during the calculation of methaformula has been brought into ArcGIS 9.2 software and presented as maps.

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

Kinetic Models for Topological Nearest-Neighbor Interactions

Science.gov (United States)

Blanchet, Adrien; Degond, Pierre

2017-12-01

We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal and human behavior. Precisely, the system consists of a finite number of particles characterized by their positions and velocities. At random times a randomly chosen particle, the follower, adopts the velocity of its closest neighbor, the leader. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit kinetic equation is a non-standard spatial diffusion equation for the particle distribution function. We also study the case wherein the particles interact with their K closest neighbors and show that the corresponding kinetic equation is the same. Finally, we prove that these models can be seen as a singular limit of the smooth rank-based model previously studied in Blanchet and Degond (J Stat Phys 163:41-60, 2016). The proofs are based on a combinatorial interpretation of the rank as well as some concentration of measure arguments.

A minimal spatial cell lineage model of epithelium: tissue stratification and multi-stability

Science.gov (United States)

Yeh, Wei-Ting; Chen, Hsuan-Yi

2018-05-01

A minimal model which includes spatial and cell lineage dynamics for stratified epithelia is presented. The dependence of tissue steady state on cell differentiation models, cell proliferation rate, cell differentiation rate, and other parameters are studied numerically and analytically. Our minimal model shows some important features. First, we find that morphogen or mechanical stress mediated interaction is necessary to maintain a healthy stratified epithelium. Furthermore, comparing with tissues in which cell differentiation can take place only during cell division, tissues in which cell division and cell differentiation are decoupled can achieve relatively higher degree of stratification. Finally, our model also shows that in the presence of short-range interactions, it is possible for a tissue to have multiple steady states. The relation between our results and tissue morphogenesis or lesion is discussed.

DISPLACE: a dynamic, individual-based model for spatial fishing planning and effort displacement: Integrating underlying fish population models

DEFF Research Database (Denmark)

Bastardie, Francois; Nielsen, J. Rasmus; Miethe, Tanja

or to the alteration of individual fishing patterns. We demonstrate that integrating the spatial activity of vessels and local fish stock abundance dynamics allow for interactions and more realistic predictions of fishermen behaviour, revenues and stock abundance......We previously developed a spatially explicit, individual-based model (IBM) evaluating the bio-economic efficiency of fishing vessel movements between regions according to the catching and targeting of different species based on the most recent high resolution spatial fishery data. The main purpose...... was to test the effects of alternative fishing effort allocation scenarios related to fuel consumption, energy efficiency (value per litre of fuel), sustainable fish stock harvesting, and profitability of the fisheries. The assumption here was constant underlying resource availability. Now, an advanced...

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.

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.

Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

International Nuclear Information System (INIS)

Žukovič, Milan; Hristopulos, Dionissios T

2009-01-01

A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the N c -state Potts model, each point is assigned to one of N c classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of

Interactive effects of morphine and dopaminergic compounds on spatial working memory in rhesus monkeys

Institute of Scientific and Technical Information of China (English)

Jian-Hong Wang; Joshua Dominie Rizak; Yan-Mei Chen; Liang Li; Xin-Tian Hu; Yuan-Ye Ma

2013-01-01

Opiates and dopamine (DA) play key roles in learning and memory in humans and animals.Although interactions between these neurotransmitters have been found,their functional roles remain to be fully elucidated,and their dysfunction may contribute to human diseases and addiction.Here we investigated the interactions of morphine and dopaminergic neurotransmitter systems with respect to learning and memory in rhesus monkeys by using the Wisconsin General Test Apparatus (WGTA) delayed-response task.Morphine and DA agonists (SKF-38393,apomorphine and bromocriptine) or DA antagonists (SKF-83566,haloperidol and sulpiride) were co-administered to the monkeys 30 min prior to the task.We found that dose-patterned co-administration of morphine with D1 or D2 antagonists or agonists reversed the impaired spatial working memory induced by morphine or the compounds alone.For example,morphine at 0.01 mg/kg impaired spatial working memory,while morphine (0.01 mg/kg) and apomorphine (0.01 or 0.06 mg/kg) co-treatment ameliorated this effect.Our findings suggest that the interactions between morphine and dopaminergic compounds influence spatial working memory in rhesus monkeys.A better understanding of these interactive relationships may provide insights into human addiction.

The Effects of Spatial Enclosure on Social Interaction Between Older Adults With Dementia and Young Children.

Science.gov (United States)

Cerruti, Minyoung S; Shepley, Mardelle M

2016-04-01

To examine the impact of spatial enclosures on social interaction between older adults with early stage dementia and young children. Intergenerational interaction through meaningful activities can promote positive affects and behaviors of children and older adults. The development of social interaction is closely related to the physical environment in association with personal competence of older adults with dementia and young children. However, minimal attention has been given to the role of physical environment in influencing intergenerational interaction. A quasi-experiment examined the functional relationship between the amount of spatial enclosure and the types of social behaviors of older adults with dementia and young children. Semi-structured interviews, aided by a photographic simulation, were developed to explore the participants' perceptions of and experiences with the different degrees of spatial enclosure. Findings showed that the semienclosed spatial plan impacted both prosocial and antisocial behaviors of older adults with dementia in their interactions with young children. This apparent discrepancy was associated with two conflicting perceptions: a sense of openness and the lack of control due to distraction created by the loose visual boundary. There was no correlation between the elder-child neutral behaviors and the degrees of spatial enclosure. This study suggests that spaces with moderate openness without visual and acoustic distraction are the most desirable to promote prosocial behaviors of older adults with dementia and young children. Additionally, elder-child prosocial behaviors were likely facilitated by specific design features such as adequate personal space, the perception of openness, and possible spaces that provide both prospect and refuge in relation to spatial enclosure. © The Author(s) 2016.

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

Spatial structure arising from neighbour-dependent bias in collective cell movement.

Science.gov (United States)

Binny, Rachelle N; Haridas, Parvathi; James, Alex; Law, Richard; Simpson, Matthew J; Plank, Michael J

2016-01-01

Mathematical models of collective cell movement often neglect the effects of spatial structure, such as clustering, on the population dynamics. Typically, they assume that individuals interact with one another in proportion to their average density (the mean-field assumption) which means that cell-cell interactions occurring over short spatial ranges are not accounted for. However, in vitro cell culture studies have shown that spatial correlations can play an important role in determining collective behaviour. Here, we take a combined experimental and modelling approach to explore how individual-level interactions give rise to spatial structure in a moving cell population. Using imaging data from in vitro experiments, we quantify the extent of spatial structure in a population of 3T3 fibroblast cells. To understand how this spatial structure arises, we develop a lattice-free individual-based model (IBM) and simulate cell movement in two spatial dimensions. Our model allows an individual's direction of movement to be affected by interactions with other cells in its neighbourhood, providing insights into how directional bias generates spatial structure. We consider how this behaviour scales up to the population level by using the IBM to derive a continuum description in terms of the dynamics of spatial moments. In particular, we account for spatial correlations between cells by considering dynamics of the second spatial moment (the average density of pairs of cells). Our numerical results suggest that the moment dynamics description can provide a good approximation to averaged simulation results from the underlying IBM. Using our in vitro data, we estimate parameters for the model and show that it can generate similar spatial structure to that observed in a 3T3 fibroblast cell population.

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.

Generalized information fusion and visualization using spatial voting and data modeling

Science.gov (United States)

Jaenisch, Holger M.; Handley, James W.

2013-05-01

We present a novel and innovative information fusion and visualization framework for multi-source intelligence (multiINT) data using Spatial Voting (SV) and Data Modeling. We describe how different sources of information can be converted into numerical form for further processing downstream, followed by a short description of how this information can be fused using the SV grid. As an illustrative example, we show the modeling of cyberspace as cyber layers for the purpose of tracking cyber personas. Finally we describe a path ahead for creating interactive agile networks through defender customized Cyber-cubes for network configuration and attack visualization.

A hierarchical spatial model of avian abundance with application to Cerulean Warblers

Science.gov (United States)

Thogmartin, Wayne E.; Sauer, John R.; Knutson, Melinda G.

2004-01-01

Surveys collecting count data are the primary means by which abundance is indexed for birds. These counts are confounded, however, by nuisance effects including observer effects and spatial correlation between counts. Current methods poorly accommodate both observer and spatial effects because modeling these spatially autocorrelated counts within a hierarchical framework is not practical using standard statistical approaches. We propose a Bayesian approach to this problem and provide as an example of its implementation a spatial model of predicted abundance for the Cerulean Warbler (Dendroica cerulea) in the Prairie-Hardwood Transition of the upper midwestern United States. We used an overdispersed Poisson regression with fixed and random effects, fitted by Markov chain Monte Carlo methods. We used 21 years of North American Breeding Bird Survey counts as the response in a loglinear function of explanatory variables describing habitat, spatial relatedness, year effects, and observer effects. The model included a conditional autoregressive term representing potential correlation between adjacent route counts. Categories of explanatory habitat variables in the model included land cover composition and configuration, climate, terrain heterogeneity, and human influence. The inherent hierarchy in the model was from counts occurring, in part, as a function of observers within survey routes within years. We found that the percentage of forested wetlands, an index of wetness potential, and an interaction between mean annual precipitation and deciduous forest patch size best described Cerulean Warbler abundance. Based on a map of relative abundance derived from the posterior parameter estimates, we estimated that only 15% of the species' population occurred on federal land, necessitating active engagement of public landowners and state agencies in the conservation of the breeding habitat for this species. Models of this type can be applied to any data in which the response

Testing a dynamic-field account of interactions between spatial attention and spatial working memory.

Science.gov (United States)

Johnson, Jeffrey S; Spencer, John P

2016-05-01

Studies examining the relationship between spatial attention and spatial working memory (SWM) have shown that discrimination responses are faster for targets appearing at locations that are being maintained in SWM, and that location memory is impaired when attention is withdrawn during the delay. These observations support the proposal that sustained attention is required for successful retention in SWM: If attention is withdrawn, memory representations are likely to fail, increasing errors. In the present study, this proposal was reexamined in light of a neural-process model of SWM. On the basis of the model's functioning, we propose an alternative explanation for the observed decline in SWM performance when a secondary task is performed during retention: SWM representations drift systematically toward the location of targets appearing during the delay. To test this explanation, participants completed a color discrimination task during the delay interval of a spatial-recall task. In the critical shifting-attention condition, the color stimulus could appear either toward or away from the midline reference axis, relative to the memorized location. We hypothesized that if shifting attention during the delay leads to the failure of SWM representations, there should be an increase in the variance of recall errors, but no change in directional errors, regardless of the direction of the shift. Conversely, if shifting attention induces drift of SWM representations-as predicted by the model-systematic changes in the patterns of spatial-recall errors should occur that would depend on the direction of the shift. The results were consistent with the latter possibility-recall errors were biased toward the locations of discrimination targets appearing during the delay.

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.

Interacting agegraphic dark energy models in non-flat universe

International Nuclear Information System (INIS)

Sheykhi, Ahmad

2009-01-01

A so-called 'agegraphic dark energy' was recently proposed to explain the dark energy-dominated universe. In this Letter, we generalize the agegraphic dark energy models to the universe with spatial curvature in the presence of interaction between dark matter and dark energy. We show that these models can accommodate w D =-1 crossing for the equation of state of dark energy. In the limiting case of a flat universe, i.e. k=0, all previous results of agegraphic dark energy in flat universe are restored.

Social Content Recommendation Based on Spatial-Temporal Aware Diffusion Modeling in Social Networks

Directory of Open Access Journals (Sweden)

Farman Ullah

2016-09-01

Full Text Available User interactions in online social networks (OSNs enable the spread of information and enhance the information dissemination process, but at the same time they exacerbate the information overload problem. In this paper, we propose a social content recommendation method based on spatial-temporal aware controlled information diffusion modeling in OSNs. Users interact more frequently when they are close to each other geographically, have similar behaviors, and fall into similar demographic categories. Considering these facts, we propose multicriteria-based social ties relationship and temporal-aware probabilistic information diffusion modeling for controlled information spread maximization in OSNs. The proposed social ties relationship modeling takes into account user spatial information, content trust, opinion similarity, and demographics. We suggest a ranking algorithm that considers the user ties strength with friends and friends-of-friends to rank users in OSNs and select highly influential injection nodes. These nodes are able to improve social content recommendations, minimize information diffusion time, and maximize information spread. Furthermore, the proposed temporal-aware probabilistic diffusion process categorizes the nodes and diffuses the recommended content to only those users who are highly influential and can enhance information dissemination. The experimental results show the effectiveness of the proposed scheme.

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.

Spatial effects in meta-foodwebs.

Science.gov (United States)

Barter, Edmund; Gross, Thilo

2017-08-30

In ecology it is widely recognised that many landscapes comprise a network of discrete patches of habitat. The species that inhabit the patches interact with each other through a foodweb, the network of feeding interactions. The meta-foodweb model proposed by Pillai et al. combines the feeding relationships at each patch with the dispersal of species between patches, such that the whole system is represented by a network of networks. Previous work on meta-foodwebs has focussed on landscape networks that do not have an explicit spatial embedding, but in real landscapes the patches are usually distributed in space. Here we compare the dispersal of a meta-foodweb on Erdős-Rényi networks, that do not have a spatial embedding, and random geometric networks, that do have a spatial embedding. We found that local structure and large network distances in spatially embedded networks, lead to meso-scale patterns of patch occupation by both specialist and omnivorous species. In particular, we found that spatial separations make the coexistence of competing species more likely. Our results highlight the effects of spatial embeddings for meta-foodweb models, and the need for new analytical approaches to them.

Selective 4D modelling framework for spatial-temporal land information management system

Science.gov (United States)

Doulamis, Anastasios; Soile, Sofia; Doulamis, Nikolaos; Chrisouli, Christina; Grammalidis, Nikos; Dimitropoulos, Kosmas; Manesis, Charalambos; Potsiou, Chryssy; Ioannidis, Charalabos

2015-06-01

This paper introduces a predictive (selective) 4D modelling framework where only the spatial 3D differences are modelled at the forthcoming time instances, while regions of no significant spatial-temporal alterations remain intact. To accomplish this, initially spatial-temporal analysis is applied between 3D digital models captured at different time instances. So, the creation of dynamic change history maps is made. Change history maps indicate spatial probabilities of regions needed further 3D modelling at forthcoming instances. Thus, change history maps are good examples for a predictive assessment, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 4D Land Information Management System (LIMS) is implemented using open interoperable standards based on the CityGML framework. CityGML allows the description of the semantic metadata information and the rights of the land resources. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 4D LIMS digital parcels and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics. An application is made to detect the change through time of a 3D block of plots in an urban area of Athens, Greece. Starting with an accurate 3D model of the buildings in 1983, a change history map is created using automated dense image matching on aerial photos of 2010. For both time instances meshes are created and through their comparison the changes are detected.

Spatially Extended Habitat Modification by Intertidal Reef-Building Bivalves has Implications for Consumer-Resource Interactions

NARCIS (Netherlands)

van der Zee, E.M.; van der Heide, T.; Donadi, S.; Eklöf, J.S.; Eriksson, B.K.; Olff, H.; van der Veer, H.W.; Piersma, T.

2012-01-01

Ecosystem engineers can strongly modify habitat structure and resource availability across space. In theory, this should alter the spatial distributions of trophically interacting species. In this article, we empirically investigated the importance of spatially extended habitat modification by

Spatially extended habitat modification by intertidal reef-building bivalves has implications for consumer-resource interactions

NARCIS (Netherlands)

van der Zee, Els M.; van der Heide, Tjisse; Donadi, Serena; Eklöf, Johan S.; Eriksson, Britas Klemens; Olff, Han; van der Veer, Henk W.; Piersma, Theunis

Ecosystem engineers can strongly modify habitat structure and resource availability across space. In theory, this should alter the spatial distributions of trophically interacting species. In this article, we empirically investigated the importance of spatially extended habitat modification by

Channel-facilitated molecular transport: The role of strength and spatial distribution of interactions

Energy Technology Data Exchange (ETDEWEB)

Uppulury, Karthik, E-mail: karthik.uppulury@gmail.com [Department of Chemistry, Texas Tech University, Lubbock, TX 79409 (United States); Kolomeisky, Anatoly B. [Department of Chemistry, Department of Chemical and Biomolecular Engineering, Center for Theoretical Biological Physics, Rice University, Houston, TX 77005 (United States)

2016-12-20

Highlights: • Molecular flux strongly depends on the strength of the molecule-pore interactions. • There exists an optimal molecule-pore interaction potential for maximal flux. • Volume of interactions depends inversely on the strength for maximal flux. • Stronger interactions need more number of attractive sites for maximal flux. • Channels with few special sites need more attractive sites for higher flux. - Abstract: Molecular transport across channels and pores is critically important for multiple natural and industrial processes. Recent advances in single-molecule techniques have allowed researchers to probe translocation through nanopores with unprecedented spatial and temporal resolution. However, our understanding of the mechanisms of channel-facilitated molecular transport is still not complete. We present a theoretical approach that investigates the role of molecular interactions in the transport through channels. It is based on the discrete-state stochastic analysis that provides a fully analytical description of this complex process. It is found that a spatial distribution of the interactions strongly influences the translocation dynamics. We predict that there is the optimal distribution that leads to the maximal flux through the channel. It is also argued that the channel transport depends on the strength of the molecule-pore interactions, on the shape of interaction potentials and on the relative contributions of entrance and diffusion processes in the system. These observations are discussed using simple physical-chemical arguments.

Channel-facilitated molecular transport: The role of strength and spatial distribution of interactions

International Nuclear Information System (INIS)

Uppulury, Karthik; Kolomeisky, Anatoly B.

2016-01-01

Highlights: • Molecular flux strongly depends on the strength of the molecule-pore interactions. • There exists an optimal molecule-pore interaction potential for maximal flux. • Volume of interactions depends inversely on the strength for maximal flux. • Stronger interactions need more number of attractive sites for maximal flux. • Channels with few special sites need more attractive sites for higher flux. - Abstract: Molecular transport across channels and pores is critically important for multiple natural and industrial processes. Recent advances in single-molecule techniques have allowed researchers to probe translocation through nanopores with unprecedented spatial and temporal resolution. However, our understanding of the mechanisms of channel-facilitated molecular transport is still not complete. We present a theoretical approach that investigates the role of molecular interactions in the transport through channels. It is based on the discrete-state stochastic analysis that provides a fully analytical description of this complex process. It is found that a spatial distribution of the interactions strongly influences the translocation dynamics. We predict that there is the optimal distribution that leads to the maximal flux through the channel. It is also argued that the channel transport depends on the strength of the molecule-pore interactions, on the shape of interaction potentials and on the relative contributions of entrance and diffusion processes in the system. These observations are discussed using simple physical-chemical arguments.

LANDIS 4.0 users guide. LANDIS: a spatially explicit model of forest landscape disturbance, management, and succession

Science.gov (United States)

Hong S. He; Wei Li; Brian R. Sturtevant; Jian Yang; Bo Z. Shang; Eric J. Gustafson; David J. Mladenoff

2005-01-01

LANDIS 4.0 is new-generation software that simulates forest landscape change over large spatial and temporal scales. It is used to explore how disturbances, succession, and management interact to determine forest composition and pattern. Also describes software architecture, model assumptions and provides detailed instructions on the use of the model.

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.

Spatial structure arising from neighbour-dependent bias in collective cell movement

Directory of Open Access Journals (Sweden)

Rachelle N. Binny

2016-02-01

Full Text Available Mathematical models of collective cell movement often neglect the effects of spatial structure, such as clustering, on the population dynamics. Typically, they assume that individuals interact with one another in proportion to their average density (the mean-field assumption which means that cell–cell interactions occurring over short spatial ranges are not accounted for. However, in vitro cell culture studies have shown that spatial correlations can play an important role in determining collective behaviour. Here, we take a combined experimental and modelling approach to explore how individual-level interactions give rise to spatial structure in a moving cell population. Using imaging data from in vitro experiments, we quantify the extent of spatial structure in a population of 3T3 fibroblast cells. To understand how this spatial structure arises, we develop a lattice-free individual-based model (IBM and simulate cell movement in two spatial dimensions. Our model allows an individual’s direction of movement to be affected by interactions with other cells in its neighbourhood, providing insights into how directional bias generates spatial structure. We consider how this behaviour scales up to the population level by using the IBM to derive a continuum description in terms of the dynamics of spatial moments. In particular, we account for spatial correlations between cells by considering dynamics of the second spatial moment (the average density of pairs of cells. Our numerical results suggest that the moment dynamics description can provide a good approximation to averaged simulation results from the underlying IBM. Using our in vitro data, we estimate parameters for the model and show that it can generate similar spatial structure to that observed in a 3T3 fibroblast cell population.

Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore

Directory of Open Access Journals (Sweden)

Jan Huwald

2013-07-01

Full Text Available A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models.

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.

Bistability, Spatial Interaction, and the Distribution of Tropical Forests and Savannas

NARCIS (Netherlands)

Staal, Arie; Dekker, Stefan C.; Xu, Chi; Nes, van Egbert H.

2016-01-01

Recent work has indicated that tropical forest and savanna can be alternative stable states under a range of climatic conditions. However, dynamical systems theory suggests that in case of strong spatial interactions between patches of forest and savanna, a boundary between both states is only

A model for spatial variations in life expectancy; mortality in Chinese regions in 2000

Directory of Open Access Journals (Sweden)

Congdon Peter

2007-05-01

Full Text Available Abstract Background Life expectancy in China has been improving markedly but health gains have been uneven and there is inequality in survival chances between regions and in rural as against urban areas. This paper applies a statistical modelling approach to mortality data collected in conjunction with the 2000 Census to formally assess spatial mortality contrasts in China. The modelling approach provides interpretable summary parameters (e.g. the relative mortality risk in rural as against urban areas and is more parsimonious in terms of parameters than the conventional life table model. Results Predictive fit is assessed both globally and at the level of individual five year age groups. A proportional model (age and area effects independent has a worse fit than one allowing age-area interactions following a bilinear form. The best fit is obtained by allowing for child and oldest age mortality rates to vary spatially. Conclusion There is evidence that age (21 age groups and area (31 Chinese administrative divisions are not proportional (i.e. independent mortality risk factors. In fact, spatial contrasts are greatest at young ages. There is a pronounced rural survival disadvantage, and large differences in life expectancy between provinces.

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

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

Directory of Open Access Journals (Sweden)

Jesse Whittington

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

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

Reducing Spatial Data Complexity for Classification Models

Science.gov (United States)

Ruta, Dymitr; Gabrys, Bogdan

2007-11-01

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

Required spatial resolution of hydrological models to evaluate urban flood resilience measures

Science.gov (United States)

Gires, A.; Giangola-Murzyn, A.; Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.

2012-04-01

During a flood in urban area, several non-linear processes (rainfall, surface runoff, sewer flow, and sub-surface flow) interact. Fully distributed hydrological models are a useful tool to better understand these complex interactions between natural processes and man built environment. Developing an efficient model is a first step to improve the understanding of flood resilience in urban area. Given that the previously mentioned underlying physical phenomenon exhibit different relevant scales, determining the required spatial resolution of such model is tricky but necessary issue. For instance such model should be able to properly represent large scale effects of local scale flood resilience measures such as stop logs. The model should also be as simple as possible without being simplistic. In this paper we test two types of model. First we use an operational semi-distributed model over a 3400 ha peri-urban area located in Seine-Saint-Denis (North-East of Paris). In this model, the area is divided into sub-catchments of average size 17 ha that are considered as homogenous, and only the sewer discharge is modelled. The rainfall data, whose resolution is 1 km is space and 5 min in time, comes from the C-band radar of Trappes, located in the West of Paris, and operated by Météo-France. It was shown that the spatial resolution of both the model and the rainfall field did not enable to fully grasp the small scale rainfall variability. To achieve this, first an ensemble of realistic rainfall fields downscaled to a resolution of 100 m is generated with the help of multifractal space-time cascades whose characteristic exponents are estimated on the available radar data. Second the corresponding ensemble of sewer hydrographs is simulated by inputting each rainfall realization to the model. It appears that the probability distribution of the simulated peak flow exhibits a power-law behaviour. This indicates that there is a great uncertainty associated with small scale

Encouraging Spatial Talk: Using Children's Museums to Bolster Spatial Reasoning

Science.gov (United States)

Polinsky, Naomi; Perez, Jasmin; Grehl, Mora; McCrink, Koleen

2017-01-01

Longitudinal spatial language intervention studies have shown that greater exposure to spatial language improves children's performance on spatial tasks. Can short naturalistic, spatial language interactions also evoke improved spatial performance? In this study, parents were asked to interact with their child at a block wall exhibit in a…

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.

A Spatial Model of the Mere Exposure Effect.

Science.gov (United States)

Fink, Edward L.; And Others

1989-01-01

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

Model for Atmospheric Propagation of Spatially Combined Laser Beams

Science.gov (United States)

2016-09-01

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

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

Science.gov (United States)

Filgueira, Ramon; Grant, Jon; Strand, Øivind

2014-06-01

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

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.

Developing a modelling for the spatial data infrastructure

CSIR Research Space (South Africa)

Hjelmager, J

2005-07-01

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

Search for quark contact interactions and extra spatial dimensions using dijet angular distributions in proton-proton collisions at $\\sqrt{s}$ = 8 TeV

CERN Document Server

Khachatryan, Vardan; Tumasyan, Armen; Adam, Wolfgang; Bergauer, Thomas; Dragicevic, Marko; Erö, Janos; Friedl, Markus; Fruehwirth, Rudolf; Ghete, Vasile Mihai; Hartl, Christian; Hörmann, Natascha; Hrubec, Josef; Jeitler, Manfred; Kiesenhofer, Wolfgang; Knünz, Valentin; Krammer, Manfred; Krätschmer, Ilse; Liko, Dietrich; Mikulec, Ivan; Rabady, Dinyar; Rahbaran, Babak; Rohringer, Herbert; Schöfbeck, Robert; Strauss, Josef; Treberer-Treberspurg, Wolfgang; Waltenberger, Wolfgang; Wulz, Claudia-Elisabeth; Mossolov, Vladimir; Shumeiko, Nikolai; Suarez Gonzalez, Juan; Alderweireldt, Sara; Bansal, Monika; Bansal, Sunil; Cornelis, Tom; De Wolf, Eddi A; Janssen, Xavier; Knutsson, Albert; Lauwers, Jasper; Luyckx, Sten; Ochesanu, Silvia; Rougny, Romain; Van De Klundert, Merijn; Van Haevermaet, Hans; Van Mechelen, Pierre; Van Remortel, Nick; Van Spilbeeck, Alex; Blekman, Freya; Blyweert, Stijn; D'Hondt, Jorgen; Daci, Nadir; Heracleous, Natalie; Keaveney, James; Lowette, Steven; Maes, Michael; Olbrechts, Annik; Python, Quentin; Strom, Derek; Tavernier, Stefaan; Van Doninck, Walter; Van Mulders, Petra; Van Onsem, Gerrit Patrick; Villella, Ilaria; Caillol, Cécile; Clerbaux, Barbara; De Lentdecker, Gilles; Dobur, Didar; Favart, Laurent; Gay, Arnaud; Grebenyuk, Anastasia; Léonard, Alexandre; Mohammadi, Abdollah; Perniè, Luca; Reis, Thomas; Seva, Tomislav; Thomas, Laurent; Vander Velde, Catherine; Vanlaer, Pascal; Wang, Jian; Zenoni, Florian; Adler, Volker; Beernaert, Kelly; Benucci, Leonardo; Cimmino, Anna; Costantini, Silvia; Crucy, Shannon; Dildick, Sven; Fagot, Alexis; Garcia, Guillaume; Mccartin, Joseph; Ocampo Rios, Alberto Andres; Ryckbosch, Dirk; Salva Diblen, Sinem; Sigamani, Michael; Strobbe, Nadja; Thyssen, Filip; Tytgat, Michael; Yazgan, Efe; Zaganidis, Nicolas; Basegmez, Suzan; Beluffi, Camille; Bruno, Giacomo; Castello, Roberto; Caudron, Adrien; Ceard, Ludivine; Da Silveira, Gustavo Gil; Delaere, Christophe; Du Pree, Tristan; Favart, Denis; Forthomme, Laurent; Giammanco, Andrea; Hollar, Jonathan; Jafari, Abideh; Jez, Pavel; Komm, Matthias; Lemaitre, Vincent; Nuttens, Claude; Pagano, Davide; Perrini, Lucia; Pin, Arnaud; Piotrzkowski, Krzysztof; Popov, Andrey; Quertenmont, Loic; Selvaggi, Michele; Vidal Marono, Miguel; Vizan Garcia, Jesus Manuel; Beliy, Nikita; Caebergs, Thierry; Daubie, Evelyne; Hammad, Gregory Habib; Aldá Júnior, Walter Luiz; Alves, Gilvan; Brito, Lucas; Correa Martins Junior, Marcos; Dos Reis Martins, Thiago; Mora Herrera, Clemencia; Pol, Maria Elena; Carvalho, Wagner; Chinellato, Jose; Custódio, Analu; Melo Da Costa, Eliza; De Jesus Damiao, Dilson; De Oliveira Martins, Carley; Fonseca De Souza, Sandro; Malbouisson, Helena; Matos Figueiredo, Diego; Mundim, Luiz; Nogima, Helio; Prado Da Silva, Wanda Lucia; Santaolalla, Javier; Santoro, Alberto; Sznajder, Andre; Tonelli Manganote, Edmilson José; Vilela Pereira, Antonio; Bernardes, Cesar Augusto; Dogra, Sunil; Tomei, Thiago; De Moraes Gregores, Eduardo; Mercadante, Pedro G; Novaes, Sergio F; Padula, Sandra; Aleksandrov, Aleksandar; Genchev, Vladimir; Iaydjiev, Plamen; Marinov, Andrey; Piperov, Stefan; Rodozov, Mircho; Sultanov, Georgi; Vutova, Mariana; Dimitrov, Anton; Glushkov, Ivan; Hadjiiska, Roumyana; Kozhuharov, Venelin; Litov, Leander; Pavlov, Borislav; Petkov, Peicho; Bian, Jian-Guo; Chen, Guo-Ming; Chen, He-Sheng; Chen, Mingshui; Cheng, Tongguang; Du, Ran; Jiang, Chun-Hua; Plestina, Roko; Romeo, Francesco; Tao, Junquan; Wang, Zheng; Asawatangtrakuldee, Chayanit; Ban, Yong; Li, Qiang; Liu, Shuai; Mao, Yajun; Qian, Si-Jin; Wang, Dayong; Zou, Wei; Avila, Carlos; Chaparro Sierra, Luisa Fernanda; Florez, Carlos; Gomez, Juan Pablo; Gomez Moreno, Bernardo; Sanabria, Juan Carlos; Godinovic, Nikola; Lelas, Damir; Polic, Dunja; Puljak, Ivica; Antunovic, Zeljko; Kovac, Marko; Brigljevic, Vuko; Kadija, Kreso; Luetic, Jelena; Mekterovic, Darko; Sudic, Lucija; Attikis, Alexandros; Mavromanolakis, Georgios; Mousa, Jehad; Nicolaou, Charalambos; Ptochos, Fotios; Razis, Panos A; Bodlak, Martin; Finger, Miroslav; Finger Jr, Michael; Assran, Yasser; Elgammal, Sherif; Mahmoud, Mohammed; Radi, Amr; Kadastik, Mario; Murumaa, Marion; Raidal, Martti; Tiko, Andres; Eerola, Paula; Fedi, Giacomo; Voutilainen, Mikko; Härkönen, Jaakko; Karimäki, Veikko; Kinnunen, Ritva; Kortelainen, Matti J; Lampén, Tapio; Lassila-Perini, Kati; Lehti, Sami; Lindén, Tomas; Luukka, Panja-Riina; Mäenpää, Teppo; Peltola, Timo; Tuominen, Eija; Tuominiemi, Jorma; Tuovinen, Esa; Wendland, Lauri; Talvitie, Joonas; Tuuva, Tuure; Besancon, Marc; Couderc, Fabrice; Dejardin, Marc; Denegri, Daniel; Fabbro, Bernard; Faure, Jean-Louis; Favaro, Carlotta; Ferri, Federico; Ganjour, Serguei; Givernaud, Alain; Gras, Philippe; Hamel de Monchenault, Gautier; Jarry, Patrick; Locci, Elizabeth; Malcles, Julie; Rander, John; Rosowsky, André; Titov, Maksym; Baffioni, Stephanie; Beaudette, Florian; Busson, Philippe; Charlot, Claude; Dahms, Torsten; Dalchenko, Mykhailo; Dobrzynski, Ludwik; Filipovic, Nicolas; Florent, Alice; Granier de Cassagnac, Raphael; Mastrolorenzo, Luca; Miné, Philippe; Mironov, Camelia; Naranjo, Ivo Nicolas; Nguyen, Matthew; Ochando, Christophe; Paganini, Pascal; Regnard, Simon; Salerno, Roberto; Sauvan, Jean-Baptiste; Sirois, Yves; Veelken, Christian; Yilmaz, Yetkin; Zabi, Alexandre; Agram, Jean-Laurent; Andrea, Jeremy; Aubin, Alexandre; Bloch, Daniel; Brom, Jean-Marie; Chabert, Eric Christian; Collard, Caroline; Conte, Eric; Fontaine, Jean-Charles; Gelé, Denis; Goerlach, Ulrich; Goetzmann, Christophe; Le Bihan, Anne-Catherine; Van Hove, Pierre; Gadrat, Sébastien; Beauceron, Stephanie; Beaupere, Nicolas; Boudoul, Gaelle; Bouvier, Elvire; Brochet, Sébastien; Carrillo Montoya, Camilo Andres; Chasserat, Julien; Chierici, Roberto; Contardo, Didier; Depasse, Pierre; El Mamouni, Houmani; Fan, Jiawei; Fay, Jean; Gascon, Susan; Gouzevitch, Maxime; Ille, Bernard; Kurca, Tibor; Lethuillier, Morgan; Mirabito, Laurent; Perries, Stephane; Ruiz Alvarez, José David; Sabes, David; Sgandurra, Louis; Sordini, Viola; Vander Donckt, Muriel; Verdier, Patrice; Viret, Sébastien; Xiao, Hong; Tsamalaidze, Zviad; Autermann, Christian; Beranek, Sarah; Bontenackels, Michael; Edelhoff, Matthias; Feld, Lutz; Heister, Arno; Hindrichs, Otto; Klein, Katja; Ostapchuk, Andrey; Raupach, Frank; Sammet, Jan; Schael, Stefan; Weber, Hendrik; Wittmer, Bruno; Zhukov, Valery; Ata, Metin; Brodski, Michael; Dietz-Laursonn, Erik; Duchardt, Deborah; Erdmann, Martin; Fischer, Robert; Güth, Andreas; Hebbeker, Thomas; Heidemann, Carsten; Hoepfner, Kerstin; Klingebiel, Dennis; Knutzen, Simon; Kreuzer, Peter; Merschmeyer, Markus; Meyer, Arnd; Millet, Philipp; Olschewski, Mark; Padeken, Klaas; Papacz, Paul; Reithler, Hans; Schmitz, Stefan Antonius; Sonnenschein, Lars; Teyssier, Daniel; Thüer, Sebastian; Weber, Martin; Cherepanov, Vladimir; Erdogan, Yusuf; Flügge, Günter; Geenen, Heiko; Geisler, Matthias; Haj Ahmad, Wael; Hoehle, Felix; Kargoll, Bastian; Kress, Thomas; Kuessel, Yvonne; Künsken, Andreas; Lingemann, Joschka; Nowack, Andreas; Nugent, Ian Michael; Perchalla, Lars; Pooth, Oliver; Stahl, Achim; Asin, Ivan; Bartosik, Nazar; Behr, Joerg; Behrenhoff, Wolf; Behrens, Ulf; Bell, Alan James; Bergholz, Matthias; Bethani, Agni; Borras, Kerstin; Burgmeier, Armin; Cakir, Altan; Calligaris, Luigi; Campbell, Alan; Choudhury, Somnath; Costanza, Francesco; Diez Pardos, Carmen; Dolinska, Ganna; Dooling, Samantha; Dorland, Tyler; Eckerlin, Guenter; Eckstein, Doris; Eichhorn, Thomas; Flucke, Gero; Garay Garcia, Jasone; Geiser, Achim; Gunnellini, Paolo; Hauk, Johannes; Hempel, Maria; Horton, Dean; Jung, Hannes; Kalogeropoulos, Alexis; Kasemann, Matthias; Katsas, Panagiotis; Kieseler, Jan; Kleinwort, Claus; Korol, Ievgen; Krücker, Dirk; Lange, Wolfgang; Leonard, Jessica; Lipka, Katerina; Lobanov, Artur; Lohmann, Wolfgang; Lutz, Benjamin; Mankel, Rainer; Marfin, Ihar; Melzer-Pellmann, Isabell-Alissandra; Meyer, Andreas Bernhard; Mittag, Gregor; Mnich, Joachim; Mussgiller, Andreas; Naumann-Emme, Sebastian; Nayak, Aruna; Novgorodova, Olga; Ntomari, Eleni; Perrey, Hanno; Pitzl, Daniel; Placakyte, Ringaile; Raspereza, Alexei; Ribeiro Cipriano, Pedro M; Roland, Benoit; Ron, Elias; Sahin, Mehmet Özgür; Salfeld-Nebgen, Jakob; Saxena, Pooja; Schmidt, Ringo; Schoerner-Sadenius, Thomas; Schröder, Matthias; Seitz, Claudia; Spannagel, Simon; Vargas Trevino, Andrea Del Rocio; Walsh, Roberval; Wissing, Christoph; Aldaya Martin, Maria; Blobel, Volker; Centis Vignali, Matteo; Draeger, Arne-Rasmus; Erfle, Joachim; Garutti, Erika; Goebel, Kristin; Görner, Martin; Haller, Johannes; Hoffmann, Malte; Höing, Rebekka Sophie; Kirschenmann, Henning; Klanner, Robert; Kogler, Roman; Lange, Jörn; Lapsien, Tobias; Lenz, Teresa; Marchesini, Ivan; Ott, Jochen; Peiffer, Thomas; Perieanu, Adrian; Pietsch, Niklas; Poehlsen, Jennifer; Pöhlsen, Thomas; Rathjens, Denis; Sander, Christian; Schettler, Hannes; Schleper, Peter; Schlieckau, Eike; Schmidt, Alexander; Seidel, Markus; Sola, Valentina; Stadie, Hartmut; Steinbrück, Georg; Troendle, Daniel; Usai, Emanuele; Vanelderen, Lukas; Vanhoefer, Annika; Barth, Christian; Baus, Colin; Berger, Joram; Böser, Christian; Butz, Erik; Chwalek, Thorsten; De Boer, Wim; Descroix, Alexis; Dierlamm, Alexander; Feindt, Michael; Frensch, Felix; Giffels, Manuel; Gilbert, Andrew; Hartmann, Frank; Hauth, Thomas; Husemann, Ulrich; Katkov, Igor; Kornmayer, Andreas; Kuznetsova, Ekaterina; Lobelle Pardo, Patricia; Mozer, Matthias Ulrich; Müller, Thomas; Nürnberg, Andreas; Quast, Gunter; Rabbertz, Klaus; Ratnikov, Fedor; Röcker, Steffen; Simonis, Hans-Jürgen; Stober, Fred-Markus Helmut; Ulrich, Ralf; Wagner-Kuhr, Jeannine; Wayand, Stefan; Weiler, Thomas; Wolf, Roger; Anagnostou, Georgios; Daskalakis, Georgios; Geralis, Theodoros; Giakoumopoulou, Viktoria Athina; Kyriakis, Aristotelis; Loukas, Demetrios; Markou, Athanasios; Markou, Christos; Psallidas, Andreas; Topsis-Giotis, Iasonas; Agapitos, Antonis; Kesisoglou, Stilianos; Panagiotou, Apostolos; Saoulidou, Niki; Stiliaris, Efstathios; Aslanoglou, Xenofon; Evangelou, Ioannis; Flouris, Giannis; Foudas, Costas; Kokkas, Panagiotis; Manthos, Nikolaos; Papadopoulos, Ioannis; Paradas, Evangelos; Strologas, John; Bencze, Gyorgy; Hajdu, Csaba; Hidas, Pàl; Horvath, Dezso; Sikler, Ferenc; Veszpremi, Viktor; Vesztergombi, Gyorgy; Zsigmond, Anna Julia; Beni, Noemi; Czellar, Sandor; Karancsi, János; Molnar, Jozsef; Palinkas, Jozsef; Szillasi, Zoltan; Makovec, Alajos; Raics, Peter; Trocsanyi, Zoltan Laszlo; Ujvari, Balazs; Swain, Sanjay Kumar; Beri, Suman Bala; Bhatnagar, Vipin; Gupta, Ruchi; Bhawandeep, Bhawandeep; Kalsi, Amandeep Kaur; Kaur, Manjit; Kumar, Ramandeep; Mittal, Monika; Nishu, Nishu; Singh, Jasbir; Kumar, Ashok; Kumar, Arun; Ahuja, Sudha; Bhardwaj, Ashutosh; Choudhary, Brajesh C; Kumar, Ajay; Malhotra, Shivali; Naimuddin, Md; Ranjan, Kirti; Sharma, Varun; Banerjee, Sunanda; Bhattacharya, Satyaki; Chatterjee, Kalyanmoy; Dutta, Suchandra; Gomber, Bhawna; Jain, Sandhya; Jain, Shilpi; Khurana, Raman; Modak, Atanu; Mukherjee, Swagata; Roy, Debarati; Sarkar, Subir; Sharan, Manoj; Abdulsalam, Abdulla; Dutta, Dipanwita; Kailas, Swaminathan; Kumar, Vineet; Mohanty, Ajit Kumar; Pant, Lalit Mohan; Shukla, Prashant; Topkar, Anita; Aziz, Tariq; Banerjee, Sudeshna; Bhowmik, Sandeep; Chatterjee, Rajdeep Mohan; Dewanjee, Ram Krishna; Dugad, Shashikant; Ganguly, Sanmay; Ghosh, Saranya; Guchait, Monoranjan; Gurtu, Atul; Kole, Gouranga; Kumar, Sanjeev; Maity, Manas; Majumder, Gobinda; Mazumdar, Kajari; Mohanty, Gagan Bihari; Parida, Bibhuti; Sudhakar, Katta; Wickramage, Nadeesha; Bakhshiansohi, Hamed; Behnamian, Hadi; Etesami, Seyed Mohsen; Fahim, Ali; Goldouzian, Reza; Khakzad, Mohsen; Mohammadi Najafabadi, Mojtaba; Naseri, Mohsen; Paktinat Mehdiabadi, Saeid; Rezaei Hosseinabadi, Ferdos; Safarzadeh, Batool; Zeinali, Maryam; Felcini, Marta; Grunewald, Martin; Abbrescia, Marcello; Calabria, Cesare; Chhibra, Simranjit Singh; Colaleo, Anna; Creanza, Donato; De Filippis, Nicola; De Palma, Mauro; Fiore, Luigi; Iaselli, Giuseppe; Maggi, Giorgio; Maggi, Marcello; My, Salvatore; Nuzzo, Salvatore; Pompili, Alexis; Pugliese, Gabriella; Radogna, Raffaella; Selvaggi, Giovanna; Sharma, Archana; Silvestris, Lucia; Venditti, Rosamaria; Abbiendi, Giovanni; Benvenuti, Alberto; Bonacorsi, Daniele; Braibant-Giacomelli, Sylvie; Brigliadori, Luca; Campanini, Renato; Capiluppi, Paolo; Castro, Andrea; Cavallo, Francesca Romana; Codispoti, Giuseppe; Cuffiani, Marco; Dallavalle, Gaetano-Marco; Fabbri, Fabrizio; Fanfani, Alessandra; Fasanella, Daniele; Giacomelli, Paolo; Grandi, Claudio; Guiducci, Luigi; Marcellini, Stefano; Masetti, Gianni; Montanari, Alessandro; Navarria, Francesco; Perrotta, Andrea; Primavera, Federica; Rossi, Antonio; Rovelli, Tiziano; Siroli, Gian Piero; Tosi, Nicolò; Travaglini, Riccardo; Albergo, Sebastiano; Cappello, Gigi; Chiorboli, Massimiliano; Costa, Salvatore; Giordano, Ferdinando; Potenza, Renato; Tricomi, Alessia; Tuve, Cristina; Barbagli, Giuseppe; Ciulli, Vitaliano; Civinini, Carlo; D'Alessandro, Raffaello; Focardi, Ettore; Gallo, Elisabetta; Gonzi, Sandro; Gori, Valentina; Lenzi, Piergiulio; Meschini, Marco; Paoletti, Simone; Sguazzoni, Giacomo; Tropiano, Antonio; Benussi, Luigi; Bianco, Stefano; Fabbri, Franco; Piccolo, Davide; Ferretti, Roberta; Ferro, Fabrizio; Lo Vetere, Maurizio; Robutti, Enrico; Tosi, Silvano; Dinardo, Mauro Emanuele; Fiorendi, Sara; Gennai, Simone; Gerosa, Raffaele; Ghezzi, Alessio; Govoni, Pietro; Lucchini, Marco Toliman; Malvezzi, Sandra; Manzoni, Riccardo Andrea; Martelli, Arabella; Marzocchi, Badder; Menasce, Dario; Moroni, Luigi; Paganoni, Marco; Pedrini, Daniele; Ragazzi, Stefano; Redaelli, Nicola; Tabarelli de Fatis, Tommaso; Buontempo, Salvatore; Cavallo, Nicola; Di Guida, Salvatore; Fabozzi, Francesco; Iorio, Alberto Orso Maria; Lista, Luca; Meola, Sabino; Merola, Mario; Paolucci, Pierluigi; Azzi, Patrizia; Bacchetta, Nicola; Bisello, Dario; Branca, Antonio; Carlin, Roberto; Checchia, Paolo; Dall'Osso, Martino; Dorigo, Tommaso; Dosselli, Umberto; Galanti, Mario; Gasparini, Fabrizio; Gasparini, Ugo; Giubilato, Piero; Gozzelino, Andrea; Kanishchev, Konstantin; Lacaprara, Stefano; Margoni, Martino; Meneguzzo, Anna Teresa; Pazzini, Jacopo; Pozzobon, Nicola; Ronchese, Paolo; Simonetto, Franco; Torassa, Ezio; Tosi, Mia; Zotto, Pierluigi; Zucchetta, Alberto; Zumerle, Gianni; Gabusi, Michele; Ratti, Sergio P; Re, Valerio; Riccardi, Cristina; Salvini, Paola; Vitulo, Paolo; Biasini, Maurizio; Bilei, Gian Mario; Ciangottini, Diego; Fanò, Livio; Lariccia, Paolo; Mantovani, Giancarlo; Menichelli, Mauro; Saha, Anirban; Santocchia, Attilio; Spiezia, Aniello; Androsov, Konstantin; Azzurri, Paolo; Bagliesi, Giuseppe; Bernardini, Jacopo; Boccali, Tommaso; Broccolo, Giuseppe; Castaldi, Rino; Ciocci, Maria Agnese; Dell'Orso, Roberto; Donato, Silvio; Fiori, Francesco; Foà, Lorenzo; Giassi, Alessandro; Grippo, Maria Teresa; Ligabue, Franco; Lomtadze, Teimuraz; Martini, Luca; Messineo, Alberto; Moon, Chang-Seong; Palla, Fabrizio; Rizzi, Andrea; Savoy-Navarro, Aurore; Serban, Alin Titus; Spagnolo, Paolo; Squillacioti, Paola; Tenchini, Roberto; Tonelli, Guido; Venturi, Andrea; Verdini, Piero Giorgio; Vernieri, Caterina; Barone, Luciano; Cavallari, Francesca; D'imperio, Giulia; Del Re, Daniele; Diemoz, Marcella; Jorda, Clara; Longo, Egidio; Margaroli, Fabrizio; Meridiani, Paolo; Micheli, Francesco; Nourbakhsh, Shervin; Organtini, Giovanni; Paramatti, Riccardo; Rahatlou, Shahram; Rovelli, Chiara; Santanastasio, Francesco; Soffi, Livia; Traczyk, Piotr; Amapane, Nicola; Arcidiacono, Roberta; Argiro, Stefano; Arneodo, Michele; Bellan, Riccardo; Biino, Cristina; Cartiglia, Nicolo; Casasso, Stefano; Costa, Marco; Degano, Alessandro; Demaria, Natale; Finco, Linda; Mariotti, Chiara; Maselli, Silvia; Migliore, Ernesto; Monaco, Vincenzo; Musich, Marco; Obertino, Maria Margherita; Ortona, Giacomo; Pacher, Luca; Pastrone, Nadia; Pelliccioni, Mario; Pinna Angioni, Gian Luca; Potenza, Alberto; Romero, Alessandra; Ruspa, Marta; Sacchi, Roberto; Solano, Ada; Staiano, Amedeo; Tamponi, Umberto; Belforte, Stefano; Candelise, Vieri; Casarsa, Massimo; Cossutti, Fabio; Della Ricca, Giuseppe; Gobbo, Benigno; La Licata, Chiara; Marone, Matteo; Schizzi, Andrea; Umer, Tomo; Zanetti, Anna; Chang, Sunghyun; Kropivnitskaya, Anna; Nam, Soon-Kwon; Kim, Dong Hee; Kim, Gui Nyun; Kim, Min Suk; Kong, Dae Jung; Lee, Sangeun; Oh, Young Do; Park, Hyangkyu; Sakharov, Alexandre; Son, Dong-Chul; Kim, Tae Jeong; Kim, Jae Yool; Song, Sanghyeon; Choi, Suyong; Gyun, Dooyeon; Hong, Byung-Sik; Jo, Mihee; Kim, Hyunchul; Kim, Yongsun; Lee, Byounghoon; Lee, Kyong Sei; Park, Sung Keun; Roh, Youn; Choi, Minkyoo; Kim, Ji Hyun; Park, Inkyu; Ryu, Geonmo; Ryu, Min Sang; Choi, Young-Il; Choi, Young Kyu; Goh, Junghwan; Kim, Donghyun; Kwon, Eunhyang; Lee, Jongseok; Seo, Hyunkwan; Yu, Intae; Juodagalvis, Andrius; Komaragiri, Jyothsna Rani; Md Ali, Mohd Adli Bin; Casimiro Linares, Edgar; Castilla-Valdez, Heriberto; De La Cruz-Burelo, Eduard; Heredia-de La Cruz, Ivan; Hernandez-Almada, Alberto; Lopez-Fernandez, Ricardo; Sánchez Hernández, Alberto; Carrillo Moreno, Salvador; Vazquez Valencia, Fabiola; Pedraza, Isabel; Salazar Ibarguen, Humberto Antonio; Morelos Pineda, Antonio; Krofcheck, David; Butler, Philip H; Reucroft, Steve; Ahmad, Ashfaq; Ahmad, Muhammad; Hassan, Qamar; Hoorani, Hafeez R; Khan, Wajid Ali; Khurshid, Taimoor; Shoaib, Muhammad; Bialkowska, Helena; Bluj, Michal; Boimska, Bożena; Frueboes, Tomasz; Górski, Maciej; Kazana, Malgorzata; Nawrocki, Krzysztof; Romanowska-Rybinska, Katarzyna; Szleper, Michal; Zalewski, Piotr; Brona, Grzegorz; Bunkowski, Karol; Cwiok, Mikolaj; Dominik, Wojciech; Doroba, Krzysztof; Kalinowski, Artur; Konecki, Marcin; Krolikowski, Jan; Misiura, Maciej; Olszewski, Michał; Wolszczak, Weronika; Bargassa, Pedrame; Beirão Da Cruz E Silva, Cristóvão; Faccioli, Pietro; Ferreira Parracho, Pedro Guilherme; Gallinaro, Michele; Lloret Iglesias, Lara; Nguyen, Federico; Rodrigues Antunes, Joao; Seixas, Joao; Varela, Joao; Vischia, Pietro; Bunin, Pavel; Gavrilenko, Mikhail; Golutvin, Igor; Gorbunov, Ilya; Karjavin, Vladimir; Konoplyanikov, Viktor; Lanev, Alexander; Malakhov, Alexander; Matveev, Viktor; Moisenz, Petr; Palichik, Vladimir; Perelygin, Victor; Savina, Maria; Shmatov, Sergey; Shulha, Siarhei; Skatchkov, Nikolai; Smirnov, Vitaly; Zarubin, Anatoli; Golovtsov, Victor; Ivanov, Yury; Kim, Victor; Levchenko, Petr; Murzin, Victor; Oreshkin, Vadim; Smirnov, Igor; Sulimov, Valentin; Uvarov, Lev; Vavilov, Sergey; Vorobyev, Alexey; Vorobyev, Andrey; Andreev, Yuri; Dermenev, Alexander; Gninenko, Sergei; Golubev, Nikolai; Kirsanov, Mikhail; Krasnikov, Nikolai; Pashenkov, Anatoli; Tlisov, Danila; Toropin, Alexander; Epshteyn, Vladimir; Gavrilov, Vladimir; Lychkovskaya, Natalia; Popov, Vladimir; Pozdnyakov, Ivan; Safronov, Grigory; Semenov, Sergey; Spiridonov, Alexander; Stolin, Viatcheslav; Vlasov, Evgueni; Zhokin, Alexander; Andreev, Vladimir; Azarkin, Maksim; Dremin, Igor; Kirakosyan, Martin; Leonidov, Andrey; Mesyats, Gennady; Rusakov, Sergey V; Vinogradov, Alexey; Belyaev, Andrey; Boos, Edouard; Bunichev, Viacheslav; Dubinin, Mikhail; Dudko, Lev; Ershov, Alexander; Klyukhin, Vyacheslav; Kodolova, Olga; Lokhtin, Igor; Obraztsov, Stepan; Perfilov, Maxim; Petrushanko, Sergey; Savrin, Viktor; Azhgirey, Igor; Bayshev, Igor; Bitioukov, Sergei; Kachanov, Vassili; Kalinin, Alexey; Konstantinov, Dmitri; Krychkine, Victor; Petrov, Vladimir; Ryutin, Roman; Sobol, Andrei; Tourtchanovitch, Leonid; Troshin, Sergey; Tyurin, Nikolay; Uzunian, Andrey; Volkov, Alexey; Adzic, Petar; Ekmedzic, Marko; Milosevic, Jovan; Rekovic, Vladimir; Alcaraz Maestre, Juan; Battilana, Carlo; Calvo, Enrique; Cerrada, Marcos; Chamizo Llatas, Maria; Colino, Nicanor; De La Cruz, Begona; Delgado Peris, Antonio; Domínguez Vázquez, Daniel; Escalante Del Valle, Alberto; Fernandez Bedoya, Cristina; Fernández Ramos, Juan Pablo; Flix, Jose; Fouz, Maria Cruz; Garcia-Abia, Pablo; Gonzalez Lopez, Oscar; Goy Lopez, Silvia; Hernandez, Jose M; Josa, Maria Isabel; Navarro De Martino, Eduardo; Pérez-Calero Yzquierdo, Antonio María; Puerta Pelayo, Jesus; Quintario Olmeda, Adrián; Redondo, Ignacio; Romero, Luciano; Senghi Soares, Mara; Albajar, Carmen; de Trocóniz, Jorge F; Missiroli, Marino; Moran, Dermot; Brun, Hugues; Cuevas, Javier; Fernandez Menendez, Javier; Folgueras, Santiago; Gonzalez Caballero, Isidro; Brochero Cifuentes, Javier Andres; Cabrillo, Iban Jose; Calderon, Alicia; Duarte Campderros, Jordi; Fernandez, Marcos; Gomez, Gervasio; Graziano, Alberto; Lopez Virto, Amparo; Marco, Jesus; Marco, Rafael; Martinez Rivero, Celso; Matorras, Francisco; Munoz Sanchez, Francisca Javiela; Piedra Gomez, Jonatan; Rodrigo, Teresa; Rodríguez-Marrero, Ana Yaiza; Ruiz-Jimeno, Alberto; Scodellaro, Luca; Vila, Ivan; Vilar Cortabitarte, Rocio; Abbaneo, Duccio; Auffray, Etiennette; Auzinger, Georg; Bachtis, Michail; Baillon, Paul; Ball, Austin; Barney, David; Benaglia, Andrea; Bendavid, Joshua; Benhabib, Lamia; Benitez, Jose F; Bernet, Colin; Bloch, Philippe; Bocci, Andrea; Bonato, Alessio; Bondu, Olivier; Botta, Cristina; Breuker, Horst; Camporesi, Tiziano; Cerminara, Gianluca; Colafranceschi, Stefano; D'Alfonso, Mariarosaria; D'Enterria, David; Dabrowski, Anne; David Tinoco Mendes, Andre; De Guio, Federico; De Roeck, Albert; De Visscher, Simon; Di Marco, Emanuele; Dobson, Marc; Dordevic, Milos; Dorney, Brian; Dupont-Sagorin, Niels; Elliott-Peisert, Anna; Eugster, Jürg; Franzoni, Giovanni; Funk, Wolfgang; Gigi, Dominique; Gill, Karl; Giordano, Domenico; Girone, Maria; Glege, Frank; Guida, Roberto; Gundacker, Stefan; Guthoff, Moritz; Hammer, Josef; Hansen, Magnus; Harris, Philip; Hegeman, Jeroen; Innocente, Vincenzo; Janot, Patrick; Kousouris, Konstantinos; Krajczar, Krisztian; Lecoq, Paul; Lourenco, Carlos; Magini, Nicolo; Malgeri, Luca; Mannelli, Marcello; Marrouche, Jad; Masetti, Lorenzo; Meijers, Frans; Mersi, Stefano; Meschi, Emilio; Moortgat, Filip; Morovic, Srecko; Mulders, Martijn; Musella, Pasquale; Orsini, Luciano; Pape, Luc; Perez, Emmanuelle; Perrozzi, Luca; Petrilli, Achille; Petrucciani, Giovanni; Pfeiffer, Andreas; Pierini, Maurizio; Pimiä, Martti; Piparo, Danilo; Plagge, Michael; Racz, Attila; Rolandi, Gigi; Rovere, Marco; Sakulin, Hannes; Schäfer, Christoph; Schwick, Christoph; Sharma, Archana; Siegrist, Patrice; Silva, Pedro; Simon, Michal; Sphicas, Paraskevas; Spiga, Daniele; Steggemann, Jan; Stieger, Benjamin; Stoye, Markus; Takahashi, Yuta; Treille, Daniel; Tsirou, Andromachi; Veres, Gabor Istvan; Wardle, Nicholas; Wöhri, Hermine Katharina; Wollny, Heiner; Zeuner, Wolfram Dietrich; Bertl, Willi; Deiters, Konrad; Erdmann, Wolfram; Horisberger, Roland; Ingram, Quentin; Kaestli, Hans-Christian; Kotlinski, Danek; Langenegger, Urs; Renker, Dieter; Rohe, Tilman; Bachmair, Felix; Bäni, Lukas; Bianchini, Lorenzo; Buchmann, Marco-Andrea; Casal, Bruno; Chanon, Nicolas; Dissertori, Günther; Dittmar, Michael; Donegà, Mauro; Dünser, Marc; Eller, Philipp; Grab, Christoph; Hits, Dmitry; Hoss, Jan; Lustermann, Werner; Mangano, Boris; Marini, Andrea Carlo; Martinez Ruiz del Arbol, Pablo; Masciovecchio, Mario; Meister, Daniel; Mohr, Niklas; Nägeli, Christoph; Nessi-Tedaldi, Francesca; Pandolfi, Francesco; Pauss, Felicitas; Peruzzi, Marco; Quittnat, Milena; Rebane, Liis; Rossini, Marco; Starodumov, Andrei; Takahashi, Maiko; Theofilatos, Konstantinos; Wallny, Rainer; Weber, Hannsjoerg Artur; Amsler, Claude; Canelli, Maria Florencia; Chiochia, Vincenzo; De Cosa, Annapaola; Hinzmann, Andreas; Hreus, Tomas; Kilminster, Benjamin; Lange, Clemens; Millan Mejias, Barbara; Ngadiuba, Jennifer; Robmann, Peter; Ronga, Frederic Jean; Taroni, Silvia; Verzetti, Mauro; Yang, Yong; Cardaci, Marco; Chen, Kuan-Hsin; Ferro, Cristina; Kuo, Chia-Ming; Lin, Willis; Lu, Yun-Ju; Volpe, Roberta; Yu, Shin-Shan; Chang, Paoti; Chang, You-Hao; Chang, Yu-Wei; Chao, Yuan; Chen, Kai-Feng; Chen, Po-Hsun; Dietz, Charles; Grundler, Ulysses; Hou, George Wei-Shu; Kao, Kai-Yi; Lei, Yeong-Jyi; Liu, Yueh-Feng; Lu, Rong-Shyang; Majumder, Devdatta; Petrakou, Eleni; Tzeng, Yeng-Ming; Wilken, Rachel; Asavapibhop, Burin; Singh, Gurpreet; Srimanobhas, Norraphat; Suwonjandee, Narumon; Adiguzel, Aytul; Bakirci, Mustafa Numan; Cerci, Salim; Dozen, Candan; Dumanoglu, Isa; Eskut, Eda; Girgis, Semiray; Gokbulut, Gul; Gurpinar, Emine; Hos, Ilknur; Kangal, Evrim Ersin; Kayis Topaksu, Aysel; Onengut, Gulsen; Ozdemir, Kadri; Ozturk, Sertac; Polatoz, Ayse; Sunar Cerci, Deniz; Tali, Bayram; Topakli, Huseyin; Vergili, Mehmet; Akin, Ilina Vasileva; Bilin, Bugra; Bilmis, Selcuk; Gamsizkan, Halil; Isildak, Bora; Karapinar, Guler; Ocalan, Kadir; Sekmen, Sezen; Surat, Ugur Emrah; Yalvac, Metin; Zeyrek, Mehmet; Albayrak, Elif Asli; Gülmez, Erhan; Kaya, Mithat; Kaya, Ozlem; Yetkin, Taylan; Cankocak, Kerem; Vardarlı, Fuat Ilkehan; Levchuk, Leonid; Sorokin, Pavel; Brooke, James John; Clement, Emyr; Cussans, David; Flacher, Henning; Goldstein, Joel; Grimes, Mark; Heath, Greg P; Heath, Helen F; Jacob, Jeson; Kreczko, Lukasz; Lucas, Chris; Meng, Zhaoxia; Newbold, Dave M; Paramesvaran, Sudarshan; Poll, Anthony; Sakuma, Tai; Senkin, Sergey; Smith, Vincent J; Williams, Thomas; Bell, Ken W; Belyaev, Alexander; Brew, Christopher; Brown, Robert M; Cockerill, David JA; Coughlan, John A; Harder, Kristian; Harper, Sam; Olaiya, Emmanuel; Petyt, David; Shepherd-Themistocleous, Claire; Thea, Alessandro; Tomalin, Ian R; Womersley, William John; Worm, Steven; Baber, Mark; Bainbridge, Robert; Buchmuller, Oliver; Burton, Darren; Colling, David; Cripps, Nicholas; Cutajar, Michael; Dauncey, Paul; Davies, Gavin; Della Negra, Michel; Dunne, Patrick; Ferguson, William; Fulcher, Jonathan; Futyan, David; Hall, Geoffrey; Iles, Gregory; Jarvis, Martyn; Karapostoli, Georgia; Kenzie, Matthew; Lane, Rebecca; Lucas, Robyn; Lyons, Louis; Magnan, Anne-Marie; Malik, Sarah; Mathias, Bryn; Nash, Jordan; Nikitenko, Alexander; Pela, Joao; Pesaresi, Mark; Petridis, Konstantinos; Raymond, David Mark; Rogerson, Samuel; Rose, Andrew; Seez, Christopher; Sharp, Peter; Tapper, Alexander; Vazquez Acosta, Monica; Virdee, Tejinder; Zenz, Seth Conrad; Cole, Joanne; Hobson, Peter R; Khan, Akram; Kyberd, Paul; Leggat, Duncan; Leslie, Dawn; Martin, William; Reid, Ivan; Symonds, Philip; Teodorescu, Liliana; Turner, Mark; Dittmann, Jay; Hatakeyama, Kenichi; Kasmi, Azeddine; Liu, Hongxuan; Scarborough, Tara; Charaf, Otman; Cooper, Seth; Henderson, Conor; Rumerio, Paolo; Avetisyan, Aram; Bose, Tulika; Fantasia, Cory; Lawson, Philip; Richardson, Clint; Rohlf, James; St John, Jason; Sulak, Lawrence; Alimena, Juliette; Berry, Edmund; Bhattacharya, Saptaparna; Christopher, Grant; Cutts, David; Demiragli, Zeynep; Dhingra, Nitish; Ferapontov, Alexey; Garabedian, Alex; Heintz, Ulrich; Kukartsev, Gennadiy; Laird, Edward; Landsberg, Greg; Luk, Michael; Narain, Meenakshi; Segala, Michael; Sinthuprasith, Tutanon; Speer, Thomas; Swanson, Joshua; Breedon, Richard; Breto, Guillermo; Calderon De La Barca Sanchez, Manuel; Chauhan, Sushil; Chertok, Maxwell; Conway, John; Conway, Rylan; Cox, Peter Timothy; Erbacher, Robin; Gardner, Michael; Ko, Winston; Lander, Richard; Miceli, Tia; Mulhearn, Michael; Pellett, Dave; Pilot, Justin; Ricci-Tam, Francesca; Searle, Matthew; Shalhout, Shalhout; Smith, John; Squires, Michael; Stolp, Dustin; Tripathi, Mani; Wilbur, Scott; Yohay, Rachel; Cousins, Robert; Everaerts, Pieter; Farrell, Chris; Hauser, Jay; Ignatenko, Mikhail; Rakness, Gregory; Takasugi, Eric; Valuev, Vyacheslav; Weber, Matthias; Burt, Kira; Clare, Robert; Ellison, John Anthony; Gary, J William; Hanson, Gail; Heilman, Jesse; Ivova Rikova, Mirena; Jandir, Pawandeep; Kennedy, Elizabeth; Lacroix, Florent; Long, Owen Rosser; Luthra, Arun; Malberti, Martina; Olmedo Negrete, Manuel; Shrinivas, Amithabh; Sumowidagdo, Suharyo; Wimpenny, Stephen; Branson, James G; Cerati, Giuseppe Benedetto; Cittolin, Sergio; D'Agnolo, Raffaele Tito; Holzner, André; Kelley, Ryan; Klein, Daniel; Letts, James; Macneill, Ian; Olivito, Dominick; Padhi, Sanjay; Palmer, Christopher; Pieri, Marco; Sani, Matteo; Sharma, Vivek; Simon, Sean; Sudano, Elizabeth; Tadel, Matevz; Tu, Yanjun; Vartak, Adish; Welke, Charles; Würthwein, Frank; Yagil, Avraham; Barge, Derek; Bradmiller-Feld, John; Campagnari, Claudio; Danielson, Thomas; Dishaw, Adam; Dutta, Valentina; Flowers, Kristen; Franco Sevilla, Manuel; Geffert, Paul; George, Christopher; Golf, Frank; Gouskos, Loukas; Incandela, Joe; Justus, Christopher; Mccoll, Nickolas; Richman, Jeffrey; Stuart, David; To, Wing; West, Christopher; Yoo, Jaehyeok; Apresyan, Artur; Bornheim, Adolf; Bunn, Julian; Chen, Yi; Duarte, Javier; Mott, Alexander; Newman, Harvey B; Pena, Cristian; Rogan, Christopher; Spiropulu, Maria; Timciuc, Vladlen; Vlimant, Jean-Roch; Wilkinson, Richard; Xie, Si; Zhu, Ren-Yuan; Azzolini, Virginia; Calamba, Aristotle; Carlson, Benjamin; Ferguson, Thomas; Iiyama, Yutaro; Paulini, Manfred; Russ, James; Vogel, Helmut; Vorobiev, Igor; Cumalat, John Perry; Ford, William T; Gaz, Alessandro; Krohn, Michael; Luiggi Lopez, Eduardo; Nauenberg, Uriel; Smith, James; Stenson, Kevin; Ulmer, Keith; Wagner, Stephen Robert; Alexander, James; Chatterjee, Avishek; Chaves, Jorge; Chu, Jennifer; Dittmer, Susan; Eggert, Nicholas; Mirman, Nathan; Nicolas Kaufman, Gala; Patterson, Juliet Ritchie; Ryd, Anders; Salvati, Emmanuele; Skinnari, Louise; Sun, Werner; Teo, Wee Don; Thom, Julia; Thompson, Joshua; Tucker, Jordan; Weng, Yao; Winstrom, Lucas; Wittich, Peter; Winn, Dave; Abdullin, Salavat; Albrow, Michael; Anderson, Jacob; Apollinari, Giorgio; Bauerdick, Lothar AT; Beretvas, Andrew; Berryhill, Jeffrey; Bhat, Pushpalatha C; Bolla, Gino; Burkett, Kevin; Butler, Joel Nathan; Cheung, Harry; Chlebana, Frank; Cihangir, Selcuk; Elvira, Victor Daniel; Fisk, Ian; Freeman, Jim; Gao, Yanyan; Gottschalk, Erik; Gray, Lindsey; Green, Dan; Grünendahl, Stefan; Gutsche, Oliver; Hanlon, Jim; Hare, Daryl; Harris, Robert M; Hirschauer, James; Hooberman, Benjamin; Jindariani, Sergo; Johnson, Marvin; Joshi, Umesh; Kaadze, Ketino; Klima, Boaz; Kreis, Benjamin; Kwan, Simon; Linacre, Jacob; Lincoln, Don; Lipton, Ron; Liu, Tiehui; Lykken, Joseph; Maeshima, Kaori; Marraffino, John Michael; Martinez Outschoorn, Verena Ingrid; Maruyama, Sho; Mason, David; McBride, Patricia; Merkel, Petra; Mishra, Kalanand; Mrenna, Stephen; Musienko, Yuri; Nahn, Steve; Newman-Holmes, Catherine; O'Dell, Vivian; Prokofyev, Oleg; Sexton-Kennedy, Elizabeth; Sharma, Seema; Soha, Aron; Spalding, William J; Spiegel, Leonard; Taylor, Lucas; Tkaczyk, Slawek; Tran, Nhan Viet; Uplegger, Lorenzo; Vaandering, Eric Wayne; Vidal, Richard; Whitbeck, Andrew; Whitmore, Juliana; Yang, Fan; Acosta, Darin; Avery, Paul; Bortignon, Pierluigi; Bourilkov, Dimitri; Carver, Matthew; Curry, David; Das, Souvik; De Gruttola, Michele; Di Giovanni, Gian Piero; Field, Richard D; Fisher, Matthew; Furic, Ivan-Kresimir; Hugon, Justin; Konigsberg, Jacobo; Korytov, Andrey; Kypreos, Theodore; Low, Jia Fu; Matchev, Konstantin; Milenovic, Predrag; Mitselmakher, Guenakh; Muniz, Lana; Rinkevicius, Aurelijus; Shchutska, Lesya; Snowball, Matthew; Sperka, David; Yelton, John; Zakaria, Mohammed; Hewamanage, Samantha; Linn, Stephan; Markowitz, Pete; Martinez, German; Rodriguez, Jorge Luis; Adams, Todd; Askew, Andrew; Bochenek, Joseph; Diamond, Brendan; Haas, Jeff; Hagopian, Sharon; Hagopian, Vasken; Johnson, Kurtis F; Prosper, Harrison; Veeraraghavan, Venkatesh; Weinberg, Marc; Baarmand, Marc M; Hohlmann, Marcus; Kalakhety, Himali; Yumiceva, Francisco; Adams, Mark Raymond; Apanasevich, Leonard; Bazterra, Victor Eduardo; Berry, Douglas; Betts, Russell Richard; Bucinskaite, Inga; Cavanaugh, Richard; Evdokimov, Olga; Gauthier, Lucie; Gerber, Cecilia Elena; Hofman, David Jonathan; Khalatyan, Samvel; Kurt, Pelin; Moon, Dong Ho; O'Brien, Christine; Silkworth, Christopher; Turner, Paul; Varelas, Nikos; Bilki, Burak; Clarida, Warren; Dilsiz, Kamuran; Duru, Firdevs; Haytmyradov, Maksat; Merlo, Jean-Pierre; Mermerkaya, Hamit; Mestvirishvili, Alexi; Moeller, Anthony; Nachtman, Jane; Ogul, Hasan; Onel, Yasar; Ozok, Ferhat; Penzo, Aldo; Rahmat, Rahmat; Sen, Sercan; Tan, Ping; Tiras, Emrah; Wetzel, James; Yi, Kai; Barnett, Bruce Arnold; Blumenfeld, Barry; Bolognesi, Sara; Fehling, David; Gritsan, Andrei; Maksimovic, Petar; Martin, Christopher; Swartz, Morris; Baringer, Philip; Bean, Alice; Benelli, Gabriele; Bruner, Christopher; Kenny III, Raymond Patrick; Malek, Magdalena; Murray, Michael; Noonan, Daniel; Sanders, Stephen; Sekaric, Jadranka; Stringer, Robert; Wang, Quan; Wood, Jeffrey Scott; Chakaberia, Irakli; Ivanov, Andrew; Khalil, Sadia; Makouski, Mikhail; Maravin, Yurii; Saini, Lovedeep Kaur; Shrestha, Shruti; Skhirtladze, Nikoloz; Svintradze, Irakli; Gronberg, Jeffrey; Lange, David; Rebassoo, Finn; Wright, Douglas; Baden, Drew; Belloni, Alberto; Calvert, Brian; Eno, Sarah Catherine; Gomez, Jaime; Hadley, Nicholas John; Kellogg, Richard G; Kolberg, Ted; Lu, Ying; Marionneau, Matthieu; Mignerey, Alice; Pedro, Kevin; Skuja, Andris; Tonjes, Marguerite; Tonwar, Suresh C; Apyan, Aram; Barbieri, Richard; Bauer, Gerry; Busza, Wit; Cali, Ivan Amos; Chan, Matthew; Di Matteo, Leonardo; Gomez Ceballos, Guillelmo; Goncharov, Maxim; Gulhan, Doga; Klute, Markus; Lai, Yue Shi; Lee, Yen-Jie; Levin, Andrew; Luckey, Paul David; Ma, Teng; Paus, Christoph; Ralph, Duncan; Roland, Christof; Roland, Gunther; Stephans, George; Stöckli, Fabian; Sumorok, Konstanty; Velicanu, Dragos; Veverka, Jan; Wyslouch, Bolek; Yang, Mingming; Zanetti, Marco; Zhukova, Victoria; Dahmes, Bryan; Gude, Alexander; Kao, Shih-Chuan; Klapoetke, Kevin; Kubota, Yuichi; Mans, Jeremy; Pastika, Nathaniel; Rusack, Roger; Singovsky, Alexander; Tambe, Norbert; Turkewitz, Jared; Acosta, John Gabriel; Oliveros, Sandra; Avdeeva, Ekaterina; Bloom, Kenneth; Bose, Suvadeep; Claes, Daniel R; Dominguez, Aaron; Gonzalez Suarez, Rebeca; Keller, Jason; Knowlton, Dan; Kravchenko, Ilya; Lazo-Flores, Jose; Malik, Sudhir; Meier, Frank; Snow, Gregory R; Zvada, Marian; Dolen, James; Godshalk, Andrew; Iashvili, Ia; Kharchilava, Avto; Kumar, Ashish; Rappoccio, Salvatore; Alverson, George; Barberis, Emanuela; Baumgartel, Darin; Chasco, Matthew; Haley, Joseph; Massironi, Andrea; Morse, David Michael; Nash, David; Orimoto, Toyoko; Trocino, Daniele; Wang, Ren-Jie; Wood, Darien; Zhang, Jinzhong; Hahn, Kristan Allan; Kubik, Andrew; Mucia, Nicholas; Odell, Nathaniel; Pollack, Brian; Pozdnyakov, Andrey; Schmitt, Michael Henry; Stoynev, Stoyan; Sung, Kevin; Velasco, Mayda; Won, Steven; Brinkerhoff, Andrew; Chan, Kwok Ming; Drozdetskiy, Alexey; Hildreth, Michael; Jessop, Colin; Karmgard, Daniel John; Kellams, Nathan; Lannon, Kevin; Luo, Wuming; Lynch, Sean; Marinelli, Nancy; Pearson, Tessa; Planer, Michael; Ruchti, Randy; Valls, Nil; Wayne, Mitchell; Wolf, Matthias; Woodard, Anna; Antonelli, Louis; Brinson, Jessica; Bylsma, Ben; Durkin, Lloyd Stanley; Flowers, Sean; Hart, Andrew; Hill, Christopher; Hughes, Richard; Kotov, Khristian; Ling, Ta-Yung; Puigh, Darren; Rodenburg, Marissa; Smith, Geoffrey; Winer, Brian L; Wolfe, Homer; Wulsin, Howard Wells; Driga, Olga; Elmer, Peter; Hardenbrook, Joshua; Hebda, Philip; Hunt, Adam; Koay, Sue Ann; Lujan, Paul; Marlow, Daniel; Medvedeva, Tatiana; Mooney, Michael; Olsen, James; Piroué, Pierre; Quan, Xiaohang; Saka, Halil; Stickland, David; Tully, Christopher; Werner, Jeremy Scott; Zuranski, Andrzej; Brownson, Eric; Mendez, Hector; Ramirez Vargas, Juan Eduardo; Barnes, Virgil E; Benedetti, Daniele; Bortoletto, Daniela; De Mattia, Marco; Gutay, Laszlo; Hu, Zhen; Jha, Manoj; Jones, Matthew; Jung, Kurt; Kress, Matthew; Leonardo, Nuno; Lopes Pegna, David; Maroussov, Vassili; Miller, David Harry; Neumeister, Norbert; Radburn-Smith, Benjamin Charles; Shi, Xin; Shipsey, Ian; Silvers, David; Svyatkovskiy, Alexey; Wang, Fuqiang; Xie, Wei; Xu, Lingshan; Yoo, Hwi Dong; Zablocki, Jakub; Zheng, Yu; Parashar, Neeti; Stupak, John; Adair, Antony; Akgun, Bora; Ecklund, Karl Matthew; Geurts, Frank JM; Li, Wei; Michlin, Benjamin; Padley, Brian Paul; Redjimi, Radia; Roberts, Jay; Zabel, James; Betchart, Burton; Bodek, Arie; Covarelli, Roberto; de Barbaro, Pawel; Demina, Regina; Eshaq, Yossof; Ferbel, Thomas; Garcia-Bellido, Aran; Goldenzweig, Pablo; Han, Jiyeon; Harel, Amnon; Khukhunaishvili, Aleko; Korjenevski, Sergey; Petrillo, Gianluca; Vishnevskiy, Dmitry; Ciesielski, Robert; Demortier, Luc; Goulianos, Konstantin; Lungu, Gheorghe; Mesropian, Christina; Arora, Sanjay; Barker, Anthony; Chou, John Paul; Contreras-Campana, Christian; Contreras-Campana, Emmanuel; Duggan, Daniel; Ferencek, Dinko; Gershtein, Yuri; Gray, Richard; Halkiadakis, Eva; Hidas, Dean; Kaplan, Steven; Lath, Amitabh; Panwalkar, Shruti; Park, Michael; Patel, Rishi; Salur, Sevil; Schnetzer, Steve; Somalwar, Sunil; Stone, Robert; Thomas, Scott; Thomassen, Peter; Walker, Matthew; Rose, Keith; Spanier, Stefan; York, Andrew; Bouhali, Othmane; Castaneda Hernandez, Alfredo; Eusebi, Ricardo; Flanagan, Will; Gilmore, Jason; Kamon, Teruki; Khotilovich, Vadim; Krutelyov, Vyacheslav; Montalvo, Roy; Osipenkov, Ilya; Pakhotin, Yuriy; Perloff, Alexx; Roe, Jeffrey; Rose, Anthony; Safonov, Alexei; Suarez, Indara; Tatarinov, Aysen; Akchurin, Nural; Cowden, Christopher; Damgov, Jordan; Dragoiu, Cosmin; Dudero, Phillip Russell; Faulkner, James; Kovitanggoon, Kittikul; Kunori, Shuichi; Lee, Sung Won; Libeiro, Terence; Volobouev, Igor; Appelt, Eric; Delannoy, Andrés G; Greene, Senta; Gurrola, Alfredo; Johns, Willard; Maguire, Charles; Mao, Yaxian; Melo, Andrew; Sharma, Monika; Sheldon, Paul; Snook, Benjamin; Tuo, Shengquan; Velkovska, Julia; Arenton, Michael Wayne; Boutle, Sarah; Cox, Bradley; Francis, Brian; Goodell, Joseph; Hirosky, Robert; Ledovskoy, Alexander; Li, Hengne; Lin, Chuanzhe; Neu, Christopher; Wood, John; Clarke, Christopher; Harr, Robert; Karchin, Paul Edmund; Kottachchi Kankanamge Don, Chamath; Lamichhane, Pramod; Sturdy, Jared; Belknap, Donald; Carlsmith, Duncan; Cepeda, Maria; Dasu, Sridhara; Dodd, Laura; Duric, Senka; Friis, Evan; Hall-Wilton, Richard; Herndon, Matthew; Hervé, Alain; Klabbers, Pamela; Lanaro, Armando; Lazaridis, Christos; Levine, Aaron; Loveless, Richard; Mohapatra, Ajit; Ojalvo, Isabel; Perry, Thomas; Pierro, Giuseppe Antonio; Polese, Giovanni; Ross, Ian; Sarangi, Tapas; Savin, Alexander; Smith, Wesley H; Taylor, Devin; Verwilligen, Piet; Vuosalo, Carl; Woods, Nathaniel

2015-04-24

A search is presented for quark contact interactions and extra spatial dimensions in proton-proton collisions at $\\sqrt{s}$ = 8 TeV using dijet angular distributions. The search is based on a data set corresponding to an integrated luminosity of 19.7 fb$^{-1}$ collected by the CMS detector at the CERN LHC. Dijet angular distributions are found to be in agreement with the perturbative QCD predictions that include electroweak corrections. Limits on the contact interaction scale from a variety of models at next-to-leading order in QCD corrections are obtained. A benchmark model in which only left-handed quarks participate is excluded up to a scale of 9.0 (11.7) TeV for destructive (constructive) interference at 95% confidence level. Lower limits between 6.0 and 8.4 TeV on the scale of virtual graviton exchange are extracted for the Arkani-Hamed--Dimopoulos--Dvali model of extra spatial dimensions.

Estimating spatial accessibility to facilities on the regional scale: an extended commuting-based interaction potential model

Directory of Open Access Journals (Sweden)

Charreire Hélène

2011-01-01

Full Text Available Abstract Background There is growing interest in the study of the relationships between individual health-related behaviours (e.g. food intake and physical activity and measurements of spatial accessibility to the associated facilities (e.g. food outlets and sport facilities. The aim of this study is to propose measurements of spatial accessibility to facilities on the regional scale, using aggregated data. We first used a potential accessibility model that partly makes it possible to overcome the limitations of the most frequently used indices such as the count of opportunities within a given neighbourhood. We then propose an extended model in order to take into account both home and work-based accessibility for a commuting population. Results Potential accessibility estimation provides a very different picture of the accessibility levels experienced by the population than the more classical "number of opportunities per census tract" index. The extended model for commuters increases the overall accessibility levels but this increase differs according to the urbanisation level. Strongest increases are observed in some rural municipalities with initial low accessibility levels. Distance to major urban poles seems to play an essential role. Conclusions Accessibility is a multi-dimensional concept that should integrate some aspects of travel behaviour. Our work supports the evidence that the choice of appropriate accessibility indices including both residential and non-residential environmental features is necessary. Such models have potential implications for providing relevant information to policy-makers in the field of public health.

CMEIAS-Aided Microscopy of the Spatial Ecology of Individual Bacterial Interactions Involving Cell-to-Cell Communication within Biofilms

Directory of Open Access Journals (Sweden)

Frank B. Dazzo

2012-05-01

Full Text Available This paper describes how the quantitative analytical tools of CMEIAS image analysis software can be used to investigate in situ microbial interactions involving cell-to-cell communication within biofilms. Various spatial pattern analyses applied to the data extracted from the 2-dimensional coordinate positioning of individual bacterial cells at single-cell resolution indicate that microbial colonization within natural biofilms is not a spatially random process, but rather involves strong positive interactions between communicating cells that influence their neighbors’ aggregated colonization behavior. Geostatistical analysis of the data provide statistically defendable estimates of the micrometer scale and interpolation maps of the spatial heterogeneity and local intensity at which these microbial interactions autocorrelate with their spatial patterns of distribution. Including in situ image analysis in cell communication studies fills an important gap in understanding the spatially dependent microbial ecophysiology that governs the intensity of biofilm colonization and its unique architecture.

Investigating Public Facility Characteristics from a Spatial Interaction Perspective: A Case Study of Beijing Hospitals Using Taxi Data

Directory of Open Access Journals (Sweden)

Xiaoqing Kong

2017-02-01

Full Text Available Services provided by public facilities are essential to people’s lives and are closely associated with human mobility. Traditionally, public facility access characteristics, such as accessibility, equity issues and service areas, are investigated mainly based on static data (census data, travel surveys and particular records, such as medical records. Currently, the advent of big data offers an unprecedented opportunity to obtain large-scale human mobility data, which can be used to study the characteristics of public facilities from the spatial interaction perspective. Intuitively, spatial interaction characteristics and service areas of different types and sizes of public facilities are different, but how different remains an open question, so we, in turn, examine this question. Based on spatial interaction, we classify public facilities and explore the differences in facilities. In the research, based on spatial interaction extracted from taxi data, we introduce an unsupervised classification method to classify 78 hospitals in 6 districts of Beijing, and the results better reflect the type of hospital. The findings are of great significance for optimizing the spatial configuration of medical facilities or other types of public facilities, allocating public resources reasonably and relieving traffic pressure.

Intelligent judgements over health risks in a spatial agent-based model.

Science.gov (United States)

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

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.

Spatial housing economics: a survey

OpenAIRE

Meen, Geoff

2016-01-01

This introduction to the Virtual Special Issue surveys the development of spatial housing economics from its roots in neo-classical theory, through more recent developments in social interactions modelling, and touching on the role of institutions, path dependence and economic history. The survey also points to some of the more promising future directions for the subject that are beginning to appear in the literature. The survey covers elements hedonic models, spatial econometrics, neighbourh...

A Spatial Allocation Procedure to Downscale Regional Crop Production Estimates from an Integrated Assessment Model

Science.gov (United States)

Moulds, S.; Djordjevic, S.; Savic, D.

2017-12-01

The Global Change Assessment Model (GCAM), an integrated assessment model, provides insight into the interactions and feedbacks between physical and human systems. The land system component of GCAM, which simulates land use activities and the production of major crops, produces output at the subregional level which must be spatially downscaled in order to use with gridded impact assessment models. However, existing downscaling routines typically consider cropland as a homogeneous class and do not provide information about land use intensity or specific management practices such as irrigation and multiple cropping. This paper presents a spatial allocation procedure to downscale crop production data from GCAM to a spatial grid, producing a time series of maps which show the spatial distribution of specific crops (e.g. rice, wheat, maize) at four input levels (subsistence, low input rainfed, high input rainfed and high input irrigated). The model algorithm is constrained by available cropland at each time point and therefore implicitly balances extensification and intensification processes in order to meet global food demand. It utilises a stochastic approach such that an increase in production of a particular crop is more likely to occur in grid cells with a high biophysical suitability and neighbourhood influence, while a fall in production will occur more often in cells with lower suitability. User-supplied rules define the order in which specific crops are downscaled as well as allowable transitions. A regional case study demonstrates the ability of the model to reproduce historical trends in India by comparing the model output with district-level agricultural inventory data. Lastly, the model is used to predict the spatial distribution of crops globally under various GCAM scenarios.

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.

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.

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

Interactive Installations for Spatial Access to Artistic Sketchbooks

DEFF Research Database (Denmark)

Christiansen, Henning; Laursen, Bjørn

2017-01-01

A book is a book – or is it? With present-day, aordable technology, we can scale a book to become a spatial object, or even a space in itself, of almost arbitrary size. We describe our design of and experiences with a generic interactive installation, called Viskbook, that provides a convincing...... illusion of oversize books, allowing the spectator to turn over the pages using natural and intuitive gestures. It provides a new media for exhibiting books in museums and elsewhere. It can be used for vulnerable and irreplaceable unique books, that otherwise would remain in the safe-box, and for books...

Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations.

Directory of Open Access Journals (Sweden)

Tatiana Shashkova

Full Text Available Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes.In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery.The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial

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

Science.gov (United States)

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

2015-06-01

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

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.

Astronomical bounds on a cosmological model allowing a general interaction in the dark sector

Science.gov (United States)

Pan, Supriya; Mukherjee, Ankan; Banerjee, Narayan

2018-06-01

Non-gravitational interaction between two barotropic dark fluids, namely the pressureless dust and the dark energy in a spatially flat Friedmann-Lemaître-Robertson-Walker model, has been discussed. It is shown that for the interactions that are linear in terms the energy densities of the dark components and their first order derivatives, the net energy density is governed by a second-order differential equation with constant coefficients. Taking a generalized interaction, which includes a number of already known interactions as special cases, the dynamics of the universe is described for three types of the dark energy equation of state, namely that of interacting quintessence, interacting vacuum energy density, and interacting phantom. The models have been constrained using the standard cosmological probes, Supernovae Type Ia data from joint light curve analysis and the observational Hubble parameter data. Two geometric tests, the cosmographic studies, and the Om diagnostic have been invoked so as to ascertain the behaviour of the present model vis-a-vis the Λ-cold dark matter model. We further discussed the interacting scenarios taking into account the thermodynamic considerations.

A model relating Eulerian spatial and temporal velocity correlations

Science.gov (United States)

Cholemari, Murali R.; Arakeri, Jaywant H.

2006-03-01

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

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups

Science.gov (United States)

Capitán, José A.; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

Time-dependent density functional theory (TD-DFT) coupled with reference interaction site model self-consistent field explicitly including spatial electron density distribution (RISM-SCF-SEDD)

Energy Technology Data Exchange (ETDEWEB)

Yokogawa, D., E-mail: d.yokogawa@chem.nagoya-u.ac.jp [Department of Chemistry, Graduate School of Science, Nagoya University, Chikusa, Nagoya 464-8602 (Japan); Institute of Transformative Bio-Molecules (WPI-ITbM), Nagoya University, Chikusa, Nagoya 464-8602 (Japan)

2016-09-07

Theoretical approach to design bright bio-imaging molecules is one of the most progressing ones. However, because of the system size and computational accuracy, the number of theoretical studies is limited to our knowledge. To overcome the difficulties, we developed a new method based on reference interaction site model self-consistent field explicitly including spatial electron density distribution and time-dependent density functional theory. We applied it to the calculation of indole and 5-cyanoindole at ground and excited states in gas and solution phases. The changes in the optimized geometries were clearly explained with resonance structures and the Stokes shift was correctly reproduced.

Interactions between the spatial and temporal stimulus factors that influence multisensory integration in human performance.

Science.gov (United States)

Stevenson, Ryan A; Fister, Juliane Krueger; Barnett, Zachary P; Nidiffer, Aaron R; Wallace, Mark T

2012-05-01

In natural environments, human sensory systems work in a coordinated and integrated manner to perceive and respond to external events. Previous research has shown that the spatial and temporal relationships of sensory signals are paramount in determining how information is integrated across sensory modalities, but in ecologically plausible settings, these factors are not independent. In the current study, we provide a novel exploration of the impact on behavioral performance for systematic manipulations of the spatial location and temporal synchrony of a visual-auditory stimulus pair. Simple auditory and visual stimuli were presented across a range of spatial locations and stimulus onset asynchronies (SOAs), and participants performed both a spatial localization and simultaneity judgment task. Response times in localizing paired visual-auditory stimuli were slower in the periphery and at larger SOAs, but most importantly, an interaction was found between the two factors, in which the effect of SOA was greater in peripheral as opposed to central locations. Simultaneity judgments also revealed a novel interaction between space and time: individuals were more likely to judge stimuli as synchronous when occurring in the periphery at large SOAs. The results of this study provide novel insights into (a) how the speed of spatial localization of an audiovisual stimulus is affected by location and temporal coincidence and the interaction between these two factors and (b) how the location of a multisensory stimulus impacts judgments concerning the temporal relationship of the paired stimuli. These findings provide strong evidence for a complex interdependency between spatial location and temporal structure in determining the ultimate behavioral and perceptual outcome associated with a paired multisensory (i.e., visual-auditory) stimulus.

Discrete Variational Approach for Modeling Laser-Plasma Interactions

Science.gov (United States)

Reyes, J. Paxon; Shadwick, B. A.

2014-10-01

The traditional approach for fluid models of laser-plasma interactions begins by approximating fields and derivatives on a grid in space and time, leading to difference equations that are manipulated to create a time-advance algorithm. In contrast, by introducing the spatial discretization at the level of the action, the resulting Euler-Lagrange equations have particular differencing approximations that will exactly satisfy discrete versions of the relevant conservation laws. For example, applying a spatial discretization in the Lagrangian density leads to continuous-time, discrete-space equations and exact energy conservation regardless of the spatial grid resolution. We compare the results of two discrete variational methods using the variational principles from Chen and Sudan and Brizard. Since the fluid system conserves energy and momentum, the relative errors in these conserved quantities are well-motivated physically as figures of merit for a particular method. This work was supported by the U. S. Department of Energy under Contract No. DE-SC0008382 and by the National Science Foundation under Contract No. PHY-1104683.

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

Directory of Open Access Journals (Sweden)

Imad Afyouni

2012-06-01

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

The impact of spatial resolution on resolving spatial precipitation patterns in the Himalayas

OpenAIRE

Bonekamp, P.N.J.; Collier, S.E.; Immerzeel, W.W.

2017-01-01

Frequently used gridded meteorological datasets poorly represent precipitation in the Himalaya due to their relatively low spatial resolution and the associated coarse representation of the complex topography. Dynamical downscaling using high-resolution atmospheric models may improve the accuracy and quality of the precipitation fields, as simulations at higher spatial resolution are more capable of resolving the interaction between the topography and the atmosphere. However, most physics par...

Spatial-temporal modeling of malware propagation in networks.

Science.gov (United States)

Chen, Zesheng; Ji, Chuanyi

2005-09-01

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

Consequences of spatial autocorrelation for niche-based models

DEFF Research Database (Denmark)

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

2006-01-01

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

Testing a Dynamic Field Account of Interactions between Spatial Attention and Spatial Working Memory

Science.gov (United States)

Johnson, Jeffrey S.; Spencer, John P.

2016-01-01

Studies examining the relationship between spatial attention and spatial working memory (SWM) have shown that discrimination responses are faster for targets appearing at locations that are being maintained in SWM, and that location memory is impaired when attention is withdrawn during the delay. These observations support the proposal that sustained attention is required for successful retention in SWM: if attention is withdrawn, memory representations are likely to fail, increasing errors. In the present study, this proposal is reexamined in light of a neural process model of SWM. On the basis of the model's functioning, we propose an alternative explanation for the observed decline in SWM performance when a secondary task is performed during retention: SWM representations drift systematically toward the location of targets appearing during the delay. To test this explanation, participants completed a color-discrimination task during the delay interval of a spatial recall task. In the critical shifting attention condition, the color stimulus could appear either toward or away from the memorized location relative to a midline reference axis. We hypothesized that if shifting attention during the delay leads to the failure of SWM representations, there should be an increase in the variance of recall errors but no change in directional error, regardless of the direction of the shift. Conversely, if shifting attention induces drift of SWM representations—as predicted by the model—there should be systematic changes in the pattern of spatial recall errors depending on the direction of the shift. Results were consistent with the latter possibility—recall errors were biased toward the location of discrimination targets appearing during the delay. PMID:26810574

Unleashing spatially distributed ecohydrology modeling using Big Data tools

Science.gov (United States)

Miles, B.; Idaszak, R.

2015-12-01

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

Spatial scale separation in regional climate modelling

Energy Technology Data Exchange (ETDEWEB)

Feser, F.

2005-07-01

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

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

Directory of Open Access Journals (Sweden)

Zhiyong Lin

2017-11-01

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

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands

Science.gov (United States)

Baldwin, Robert F.; Leonard, Paul B.

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands.

Science.gov (United States)

Baldwin, Robert F; Leonard, Paul B

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our

Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

Science.gov (United States)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2013-12-01

Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale

Interacting fermions in one spatial dimensions

International Nuclear Information System (INIS)

Wolf, D.

1982-01-01

This thesis contains in its first part a critical survey about the method of the bosonization of fermi fields in one spatial dimension and its application to the Luttinger and the massive Thirring model. The first chapter served for the explanation of the term of the unitary inequivalence. Thereby two generally valid facts could be demonstrated very illustratively by the example of a fermion algebra and its representations, namely first that infinite, direct product space are not separable, and second that weak equivalence of the vacua is equivalent to the unitary equivalence of the corresponding representations of the field algebra. In the second part the statement first studied by Luther (1976) and since then often cited, that the continuum limit of the Heisenberg model is the massive Thirring model. It is concluded that it can up to today not be considered as proved although indications for its validity can be found. (orig./HSI) [de

Uncertainties in soil-plant interactions in advanced models for long-timescale dose assessment

Energy Technology Data Exchange (ETDEWEB)

Klos, R. [Aleksandria Sciences Ltd. (United Kingdom); Limer, L. [Limer Scientific Ltd. (United Kingdom); Perez-Sanchez, D. [Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas - CIEMAT (Spain); Xu, S.; Andersson, P. [Swedish Radiation Safty Authority (Sweden)

2014-07-01

Traditional models for long-timescale dose assessment are generally conceptually straightforward, featuring one, two or three spatial compartments in the soil column and employing data based on annually averaged parameters for climate characteristics. The soil-plant system is usually modelled using concentration ratios. The justification for this approach is that the timescales relevant to the geologic disposal of radioactive waste are so long that simple conceptual models are necessary to account for the inherent uncertainties over the timescale of the dose assessment. In the past few years, attention has been given to more detailed 'advanced' models for use dose assessment that have a high degree of site-specific detail. These recognise more features, events and processes since they have higher spatial and temporal resolution. This modelling approach has been developed to account for redox sensitive radionuclides, variability of the water table position and accumulation in non-agricultural ecosystems prior to conversion to an agricultural ecosystem. The models feature higher spatial and temporal resolution in the soil column (up to ten layers with spatially varying k{sub d}s dependent on soil conditions) and monthly rather than annually averaged parameters. Soil-plant interaction is treated as a dynamic process, allowing for root uptake as a function of time and depth, according to the root profile. Uncertainty in dose assessment models associated with the treatment of prior accumulations in agricultural soils has demonstrated the importance of the model's representation of the soil-plant interaction. The treatment of root uptake as a dynamic process as opposed to a simple concentration ratio implies a potentially important difference despite the dynamic soil-plant transfer rate being based on established concentration ratio values. These discrepancies have also appeared in the results from the higher spatio-temporal resolution models. This paper

MESOI, an interactive atmospheric dispersion model for emergency response applications

International Nuclear Information System (INIS)

Ramsdell, J.V.; Athey, G.F.; Glantz, C.S.

1984-01-01

MESOI is an interactive atmospheric dispersion model that has been developed for use by the U.S. Department of Energy, and the U.S. Nuclear Regulatory Commission in responding to emergencies at nuclear facilities. MESOI uses both straight-line Gaussian plume and Lagrangian trajectory Gaussian puff models to estimate time-integrated ground-level air and surface concentrations. Puff trajectories are determined from temporally and spatially varying horizontal wind fields that are defined in 3 dimensions. Other processes treated in MESOI include dry deposition, wet deposition and radioactive decay

MESOI, an interactive atmospheric dispersion model for emergency response applications

International Nuclear Information System (INIS)

Ramsdell, J.V.; Athey, G.F.; Glantz, C.S.

1983-12-01

MESOI is an interactive atmospheric despersion model that has been developed for use by the US Department of Energy, and the US Nuclear Regulatory Commission in responding to emergencies at nuclear facilities. MESOI uses both straight-line Gaussian plume and Lagrangian trajectory Gaussian puff models to estimate time-integrated ground-level air and surface concentrations. Puff trajectories are determined from temporally and spatially varying horizontal wind fields that are defined in 3 dimensions. Other processes treated in MESOI include dry deposition, wet deposition and radioactive decay. 9 references

Bringing VR and spatial 3D interaction to the masses through video games.

Science.gov (United States)

LaViola, Joseph J

2008-01-01

This article examines why innovations such as the Sony EyeToy and Nintendo Wii have been so successful and discusses the research opportunities presented by the latest commercial push for spatial 3D interaction in games.

A simplified spatial model for BWR stability

International Nuclear Information System (INIS)

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

2012-01-01

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

Global sensitivity analysis for models with spatially dependent outputs

International Nuclear Information System (INIS)

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

2011-01-01

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

Drivers potentially influencing host-bat fly interactions in anthropogenic neotropical landscapes at different spatial scales.

Science.gov (United States)

Hernández-Martínez, Jacqueline; Morales-Malacara, Juan B; Alvarez-Añorve, Mariana Yolotl; Amador-Hernández, Sergio; Oyama, Ken; Avila-Cabadilla, Luis Daniel

2018-05-21

The anthropogenic modification of natural landscapes, and the consequent changes in the environmental conditions and resources availability at multiple spatial scales can affect complex species interactions involving key-stone species such as bat-parasite interactions. In this study, we aimed to identify the drivers potentially influencing host-bat fly interactions at different spatial scales (at the host, vegetation stand and landscape level), in a tropical anthropogenic landscape. For this purpose, we mist-netted phyllostomid and moormopid bats and collected the bat flies (streblids) parasitizing them in 10 sites representing secondary and old growth forest. In general, the variation in fly communities largely mirrored the variation in bat communities as a result of the high level of specialization characterizing host-bat fly interaction networks. Nevertheless, we observed that: (1) bats roosting dynamics can shape bat-streblid interactions, modulating parasite prevalence and the intensity of infestation; (2) a degraded matrix could favor crowding and consequently the exchange of ectoparasites among bat species, lessening the level of specialization of the interaction networks and promoting novel interactions; and (3) bat-fly interaction can also be shaped by the dilution effect, as a decrease in bat diversity could be associated with a potential increase in the dissemination and prevalence of streblids.

A study of spatial resolution in pollution exposure modelling

Directory of Open Access Journals (Sweden)

Gustafsson Susanna

2007-06-01

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

Baryons and baryonic matter in four-fermion interaction models

International Nuclear Information System (INIS)

Urlichs, K.

2007-01-01

In this work we discuss baryons and baryonic matter in simple four-fermion interaction theories, the Gross-Neveu model and the Nambu-Jona-Lasinio model in 1+1 and 2+1 space-time dimensions. These models are designed as toy models for dynamical symmetry breaking in strong interaction physics. Pointlike interactions (''four-fermion'' interactions) between quarks replace the full gluon mediated interaction of quantum chromodynamics. We consider the limit of a large number of fermion flavors, where a mean field approach becomes exact. This method is formulated in the language of relativistic many particle theory and is equivalent to the Hartree-Fock approximation. In 1+1 dimensions, we generalize known results on the ground state to the case where chiral symmetry is broken explicitly by a bare mass term. For the Gross-Neveu model, we derive an exact self-consistent solution for the finite density ground state, consisting of a one-dimensional array of equally spaced potential wells, a baryon crystal. For the Nambu- Jona-Lasinio model we apply the derivative expansion technique to calculate the total energy in powers of derivatives of the mean field. In a picture akin to the Skyrme model of nuclear physics, the baryon emerges as a topological soliton. The solution for both the single baryon and dense baryonic matter is given in a systematic expansion in powers of the pion mass. The solution of the Hartree-Fock problem is more complicated in 2+1 dimensions. In the massless Gross-Neveu model we derive an exact self-consistent solution by extending the baryon crystal of the 1+1 dimensional model, maintaining translational invariance in one spatial direction. This one-dimensional configuration is energetically degenerate to the translationally invariant solution, a hint in favor of a possible translational symmetry breakdown by more general geometrical structures. In the Nambu-Jona-Lasinio model, topological soliton configurations induce a finite baryon number. In contrast

Baryons and baryonic matter in four-fermion interaction models

Energy Technology Data Exchange (ETDEWEB)

Urlichs, K.

2007-02-23

In this work we discuss baryons and baryonic matter in simple four-fermion interaction theories, the Gross-Neveu model and the Nambu-Jona-Lasinio model in 1+1 and 2+1 space-time dimensions. These models are designed as toy models for dynamical symmetry breaking in strong interaction physics. Pointlike interactions (''four-fermion'' interactions) between quarks replace the full gluon mediated interaction of quantum chromodynamics. We consider the limit of a large number of fermion flavors, where a mean field approach becomes exact. This method is formulated in the language of relativistic many particle theory and is equivalent to the Hartree-Fock approximation. In 1+1 dimensions, we generalize known results on the ground state to the case where chiral symmetry is broken explicitly by a bare mass term. For the Gross-Neveu model, we derive an exact self-consistent solution for the finite density ground state, consisting of a one-dimensional array of equally spaced potential wells, a baryon crystal. For the Nambu- Jona-Lasinio model we apply the derivative expansion technique to calculate the total energy in powers of derivatives of the mean field. In a picture akin to the Skyrme model of nuclear physics, the baryon emerges as a topological soliton. The solution for both the single baryon and dense baryonic matter is given in a systematic expansion in powers of the pion mass. The solution of the Hartree-Fock problem is more complicated in 2+1 dimensions. In the massless Gross-Neveu model we derive an exact self-consistent solution by extending the baryon crystal of the 1+1 dimensional model, maintaining translational invariance in one spatial direction. This one-dimensional configuration is energetically degenerate to the translationally invariant solution, a hint in favor of a possible translational symmetry breakdown by more general geometrical structures. In the Nambu-Jona-Lasinio model, topological soliton configurations induce a finite baryon

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

Mansour Halimi

2014-02-01

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

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.

The Relationship Between Spatial Configuration and Social Interaction in High-Rise Flats: A Case Study On The Jatinegara Barat in Jakarta.

Directory of Open Access Journals (Sweden)

Ridwana Rifan

2018-01-01

The results of this study indicate that: (1 the relationship of spatial configuration to social interaction level in Jatinegara Barat flats can be positive or negative. (2 Positive relationships are found on the1st and 2ndfloor areas. High configuration values with high interaction levels are found in shared spaces on the 1st and 2nd floors with characteristics such as open space, large space, and availability of interaction supporting elements, while low configuration values with low interaction levels are found in more confined spaces such as private spaces and narrow corridors. (3 Negative relationships are found in the corridor and shared space in front of the elevator on each typical floors. Shared space in front of the elevator that has high spatial configuration value with large area show a low level of social interaction. While corridor with lower configuration value with the narrow area but have supporting elements such as chairs, mats, and shops have a higher level of social interaction. (4 This study shows that in the case of the relationship between spatial configuration and social interaction, availability of interaction supporting elements has greater influence rather than any other spatial factors.

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...

Biotic interactions in the face of climate change: a comparison of three modelling approaches.

Directory of Open Access Journals (Sweden)

Anja Jaeschke

Full Text Available Climate change is expected to alter biotic interactions, and may lead to temporal and spatial mismatches of interacting species. Although the importance of interactions for climate change risk assessments is increasingly acknowledged in observational and experimental studies, biotic interactions are still rarely incorporated in species distribution models. We assessed the potential impacts of climate change on the obligate interaction between Aeshna viridis and its egg-laying plant Stratiotes aloides in Europe, based on an ensemble modelling technique. We compared three different approaches for incorporating biotic interactions in distribution models: (1 We separately modelled each species based on climatic information, and intersected the future range overlap ('overlap approach'. (2 We modelled the potential future distribution of A. viridis with the projected occurrence probability of S. aloides as further predictor in addition to climate ('explanatory variable approach'. (3 We calibrated the model of A. viridis in the current range of S. aloides and multiplied the future occurrence probabilities of both species ('reference area approach'. Subsequently, all approaches were compared to a single species model of A. viridis without interactions. All approaches projected a range expansion for A. viridis. Model performance on test data and amount of range gain differed depending on the biotic interaction approach. All interaction approaches yielded lower range gains (up to 667% lower than the model without interaction. Regarding the contribution of algorithm and approach to the overall uncertainty, the main part of explained variation stems from the modelling algorithm, and only a small part is attributed to the modelling approach. The comparison of the no-interaction model with the three interaction approaches emphasizes the importance of including obligate biotic interactions in projective species distribution modelling. We recommend the use of

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.

Interactive spatial multimedia for communication of art in the physical museum space

DEFF Research Database (Denmark)

Kortbek, Karen Johanne; Grønbæk, Kaj

2008-01-01

of the artworks we apply three spatial multimedia techniques where the only interaction device needed is the human body. The three techniques are: 1) spatially bounded audio; 2) floor-based multimedia; 3) multimedia interior. The paper describes the application of these techniques for communication of information...... without disturbing the art works. This has usually been limited to individual audio guides. In our case we strive to achieve holistic and social experiences with seamless transitions between art experience and communication related to the artworks. To reach a holistic experience with minimal disturbance...... in a Mariko Mori exhibition. The multimedia installations and their implementation are described. It is argued that the utilization of the spatial multimedia techniques support holistic and social art experience. The multimedia installations were in function for a three and a half month exhibition period...

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.

Multidimensional extended spatial evolutionary games.

Science.gov (United States)

Krześlak, Michał; Świerniak, Andrzej

2016-02-01

The goal of this paper is to study the classical hawk-dove model using mixed spatial evolutionary games (MSEG). In these games, played on a lattice, an additional spatial layer is introduced for dependence on more complex parameters and simulation of changes in the environment. Furthermore, diverse polymorphic equilibrium points dependent on cell reproduction, model parameters, and their simulation are discussed. Our analysis demonstrates the sensitivity properties of MSEGs and possibilities for further development. We discuss applications of MSEGs, particularly algorithms for modelling cell interactions during the development of tumours. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial interactions reveal inhibitory cortical networks in human amblyopia.

Science.gov (United States)

Wong, Erwin H; Levi, Dennis M; McGraw, Paul V

2005-10-01

Humans with amblyopia have a well-documented loss of sensitivity for first-order, or luminance defined, visual information. Recent studies show that they also display a specific loss of sensitivity for second-order, or contrast defined, visual information; a type of image structure encoded by neurons found predominantly in visual area A18/V2. In the present study, we investigate whether amblyopia disrupts the normal architecture of spatial interactions in V2 by determining the contrast detection threshold of a second-order target in the presence of second-order flanking stimuli. Adjacent flanks facilitated second-order detectability in normal observers. However, in marked contrast, they suppressed detection in each eye of the majority of amblyopic observers. Furthermore, strabismic observers with no loss of visual acuity show a similar pattern of detection suppression. We speculate that amblyopia results in predominantly inhibitory cortical interactions between second-order neurons.

The properties of genome conformation and spatial gene interaction and regulation networks of normal and malignant human cell types.

Directory of Open Access Journals (Sweden)

Zheng Wang

Full Text Available The spatial conformation of a genome plays an important role in the long-range regulation of genome-wide gene expression and methylation, but has not been extensively studied due to lack of genome conformation data. The recently developed chromosome conformation capturing techniques such as the Hi-C method empowered by next generation sequencing can generate unbiased, large-scale, high-resolution chromosomal interaction (contact data, providing an unprecedented opportunity to investigate the spatial structure of a genome and its applications in gene regulation, genomics, epigenetics, and cell biology. In this work, we conducted a comprehensive, large-scale computational analysis of this new stream of genome conformation data generated for three different human leukemia cells or cell lines by the Hi-C technique. We developed and applied a set of bioinformatics methods to reliably generate spatial chromosomal contacts from high-throughput sequencing data and to effectively use them to study the properties of the genome structures in one-dimension (1D and two-dimension (2D. Our analysis demonstrates that Hi-C data can be effectively applied to study tissue-specific genome conformation, chromosome-chromosome interaction, chromosomal translocations, and spatial gene-gene interaction and regulation in a three-dimensional genome of primary tumor cells. Particularly, for the first time, we constructed genome-scale spatial gene-gene interaction network, transcription factor binding site (TFBS - TFBS interaction network, and TFBS-gene interaction network from chromosomal contact information. Remarkably, all these networks possess the properties of scale-free modular networks.

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.

Provincial-level spatial statistical modelling of the change in per capita disposable Family Income in Spain, 1975-1983

Directory of Open Access Journals (Sweden)

Daniel A. Griffith

1998-02-01

Full Text Available Computational simplifications for a space-time autoregressive response model specification are explored for the change in Spain's per capita disposable family income between 1975 and 1983. The geographic resolution for this analysis is the provincial partitioning of part of the Iberian peninsula into Spain's 47 coterminous provinces coupled with its 3 island clusters provinces. In keeping with the Paelinckian tradition of spatial econometrics, exploration focuses on both new spatial econometric estimators and model specifications that emphasize the capturing of spatial dependency effects in the mean response term. One goal of this analysis is to differentiate between spatial, temporal, and space-time interaction information contained in the per capita disposable family income data. A second objective of the application is to illustrate the utility of extending computational simplifications from the spatial to the space-time domain. And a third purpose is to gain some substantive insights into the economic development of one country in a changing Europe. A serendipitous outcome of this investigation is a detailed analysis of locational information latent in Spain's regionally disaggregated per capita disposable family income.

Integrating remote sensing and spatially explicit epidemiological modeling

Science.gov (United States)

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

2015-04-01

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

A spatial ecosystem and populations dynamics model (SEAPODYM) Modeling of tuna and tuna-like populations

Science.gov (United States)

Lehodey, Patrick; Senina, Inna; Murtugudde, Raghu

2008-09-01

An enhanced version of the spatial ecosystem and population dynamics model SEAPODYM is presented to describe spatial dynamics of tuna and tuna-like species in the Pacific Ocean at monthly resolution over 1° grid-boxes. The simulations are driven by a bio-physical environment predicted from a coupled ocean physical-biogeochemical model. This new version of SEAPODYM includes expanded definitions of habitat indices, movements, and natural mortality based on empirical evidences. A thermal habitat of tuna species is derived from an individual heat budget model. The feeding habitat is computed according to the accessibility of tuna predator cohorts to different vertically migrating and non-migrating micronekton (mid-trophic) functional groups. The spawning habitat is based on temperature and the coincidence of spawning fish with presence or absence of predators and food for larvae. The successful larval recruitment is linked to spawning stock biomass. Larvae drift with currents, while immature and adult tuna can move of their own volition, in addition to being advected by currents. A food requirement index is computed to adjust locally the natural mortality of cohorts based on food demand and accessibility to available forage components. Together these mechanisms induce bottom-up and top-down effects, and intra- (i.e. between cohorts) and inter-species interactions. The model is now fully operational for running multi-species, multi-fisheries simulations, and the structure of the model allows a validation from multiple data sources. An application with two tuna species showing different biological characteristics, skipjack ( Katsuwonus pelamis) and bigeye ( Thunnus obesus), is presented to illustrate the capacity of the model to capture many important features of spatial dynamics of these two different tuna species in the Pacific Ocean. The actual validation is presented in a companion paper describing the approach to have a rigorous mathematical parameter optimization

Spherical Process Models for Global Spatial Statistics

KAUST Repository

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

2017-01-01

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

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

Science.gov (United States)

Lal, Aparna

2016-02-02

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

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

Directory of Open Access Journals (Sweden)

Aparna Lal

2016-02-01

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

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

Flexible hydrological modeling - Disaggregation from lumped catchment scale to higher spatial resolutions

Science.gov (United States)

Tran, Quoc Quan; Willems, Patrick; Pannemans, Bart; Blanckaert, Joris; Pereira, Fernando; Nossent, Jiri; Cauwenberghs, Kris; Vansteenkiste, Thomas

2015-04-01

Based on an international literature review on model structures of existing rainfall-runoff and hydrological models, a generalized model structure is proposed. It consists of different types of meteorological components, storage components, splitting components and routing components. They can be spatially organized in a lumped way, or on a grid, spatially interlinked by source-to-sink or grid-to-grid (cell-to-cell) routing. The grid size of the model can be chosen depending on the application. The user can select/change the spatial resolution depending on the needs and/or the evaluation of the accuracy of the model results, or use different spatial resolutions in parallel for different applications. Major research questions addressed during the study are: How can we assure consistent results of the model at any spatial detail? How can we avoid strong or sudden changes in model parameters and corresponding simulation results, when one moves from one level of spatial detail to another? How can we limit the problem of overparameterization/equifinality when we move from the lumped model to the spatially distributed model? The proposed approach is a step-wise one, where first the lumped conceptual model is calibrated using a systematic, data-based approach, followed by a disaggregation step where the lumped parameters are disaggregated based on spatial catchment characteristics (topography, land use, soil characteristics). In this way, disaggregation can be done down to any spatial scale, and consistently among scales. Only few additional calibration parameters are introduced to scale the absolute spatial differences in model parameters, but keeping the relative differences as obtained from the spatial catchment characteristics. After calibration of the spatial model, the accuracies of the lumped and spatial models were compared for peak, low and cumulative runoff total and sub-flows (at downstream and internal gauging stations). For the distributed models, additional

A nonlocal spatial model for Lyme disease

Science.gov (United States)

Yu, Xiao; Zhao, Xiao-Qiang

2016-07-01

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

Evolution of interactions and cooperation in the spatial prisoner's dilemma game.

Directory of Open Access Journals (Sweden)

Chunyan Zhang

Full Text Available We study the evolution of cooperation in the spatial prisoner's dilemma game where players are allowed to establish new interactions with others. By employing a simple coevolutionary rule entailing only two crucial parameters, we find that different selection criteria for the new interaction partners as well as their number vitally affect the outcome of the game. The resolution of the social dilemma is most probable if the selection favors more successful players and if their maximally attainable number is restricted. While the preferential selection of the best players promotes cooperation irrespective of game parametrization, the optimal number of new interactions depends somewhat on the temptation to defect. Our findings reveal that the "making of new friends" may be an important activity for the successful evolution of cooperation, but also that partners must be selected carefully and their number limited.

Spatial interaction creates period-doubling bifurcation and chaos of urbanization

International Nuclear Information System (INIS)

Chen Yanguang

2009-01-01

This paper provides a new way of looking at complicated dynamics of simple mathematical models. The complicated behavior of simple equations is one of the headstreams of chaos theory. However, a recent study based on dynamical equations of urbanization shows that there are still some undiscovered secrets behind the simple mathematical models such as logistic equation. The rural-urban interaction model can also display varied kinds of complicated dynamics, including period-doubling bifurcation and chaos. The two-dimension map of urbanization presents the same dynamics as that from the one-dimension logistic map. In theory, the logistic equation can be derived from the two-population interaction model. This seems to suggest that the complicated behavior of simple models results from interaction rather than pure intrinsic randomicity. In light of this idea, the classical predator-prey interaction model can be revised to explain the complex dynamics of logistic equation in physical and social sciences.

Spatial evolutionary epidemiology of spreading epidemics.

Science.gov (United States)

Lion, S; Gandon, S

2016-10-26

Most spatial models of host-parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. © 2016 The Author(s).

The quantitative modelling of human spatial habitability

Science.gov (United States)

Wise, James A.

1988-01-01

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

Hydrological model uncertainty due to spatial evapotranspiration estimation methods

Science.gov (United States)

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

2016-05-01

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

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.

Tapered composite likelihood for spatial max-stable models

KAUST Repository

Sang, Huiyan; Genton, Marc G.

2014-01-01

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

Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions.

Science.gov (United States)

Lehnert, Teresa; Timme, Sandra; Pollmächer, Johannes; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-01-01

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely

Statistical mechanics of spatial evolutionary games

International Nuclear Information System (INIS)

Miekisz, Jacek

2004-01-01

We discuss the long-run behaviour of stochastic dynamics of many interacting players in spatial evolutionary games. In particular, we investigate the effect of the number of players and the noise level on the stochastic stability of Nash equilibria. We discuss similarities and differences between systems of interacting players maximizing their individual payoffs and particles minimizing their interaction energy. We use concepts and techniques of statistical mechanics to study game-theoretic models. In order to obtain results in the case of the so-called potential games, we analyse the thermodynamic limit of the appropriate models of interacting particles

Contextual interactions in grating plaid configurations are explained by natural image statistics and neural modeling

Directory of Open Access Journals (Sweden)

Udo Alexander Ernst

2016-10-01

Full Text Available Processing natural scenes requires the visual system to integrate local features into global object descriptions. To achieve coherent representations, the human brain uses statistical dependencies to guide weighting of local feature conjunctions. Pairwise interactions among feature detectors in early visual areas may form the early substrate of these local feature bindings. To investigate local interaction structures in visual cortex, we combined psychophysical experiments with computational modeling and natural scene analysis. We first measured contrast thresholds for 2x2 grating patch arrangements (plaids, which differed in spatial frequency composition (low, high or mixed, number of grating patch co-alignments (0, 1 or 2, and inter-patch distances (1° and 2° of visual angle. Contrast thresholds for the different configurations were compared to the prediction of probability summation (PS among detector families tuned to the four retinal positions. For 1° distance the thresholds for all configurations were larger than predicted by PS, indicating inhibitory interactions. For 2° distance, thresholds were significantly lower compared to PS when the plaids were homogeneous in spatial frequency and orientation, but not when spatial frequencies were mixed or there was at least one misalignment. Next, we constructed a neural population model with horizontal laminar structure, which reproduced the detection thresholds after adaptation of connection weights. Consistent with prior work, contextual interactions were medium-range inhibition and long-range, orientation-specific excitation. However, inclusion of orientation-specific, inhibitory interactions between populations with different spatial frequency preferences were crucial for explaining detection thresholds. Finally, for all plaid configurations we computed their likelihood of occurrence in natural images. The likelihoods turned out to be inversely related to the detection thresholds obtained

A spatial emergy model for Alachua County, Florida

Science.gov (United States)

Lambert, James David

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

Bayesian spatial transformation models with applications in neuroimaging data.

Science.gov (United States)

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

2013-12-01

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

Spatially-varying surface roughness and ground-level air quality in an operational dispersion model

International Nuclear Information System (INIS)

Barnes, M.J.; Brade, T.K.; MacKenzie, A.R.; Whyatt, J.D.; Carruthers, D.J.; Stocker, J.; Cai, X.; Hewitt, C.N.

2014-01-01

Urban form controls the overall aerodynamic roughness of a city, and hence plays a significant role in how air flow interacts with the urban landscape. This paper reports improved model performance resulting from the introduction of variable surface roughness in the operational air-quality model ADMS-Urban (v3.1). We then assess to what extent pollutant concentrations can be reduced solely through local reductions in roughness. The model results suggest that reducing surface roughness in a city centre can increase ground-level pollutant concentrations, both locally in the area of reduced roughness and downwind of that area. The unexpected simulation of increased ground-level pollutant concentrations implies that this type of modelling should be used with caution for urban planning and design studies looking at ventilation of pollution. We expect the results from this study to be relevant for all atmospheric dispersion models with urban-surface parameterisations based on roughness. -- Highlights: • Spatially variable roughness improved performance of an operational model. • Scenario modelling explored effect of reduced roughness on air pollution. • Reducing surface roughness can increase modelled ground-level pollution. • Damped vertical mixing outweighs increased horizontal advection in model study. • Result should hold for any model with a land-surface coupling based on roughness. -- Spatially varying roughness improves model simulations of urban air pollutant dispersion. Reducing roughness does not always decrease ground-level pollution concentrations

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

OpenAIRE

Fischer, Manfred M.

2009-01-01

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

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.

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.

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.

An improved public goods game model with reputation effect on the spatial lattices

International Nuclear Information System (INIS)

Zhou, Tianwei; Ding, Shuai; Fan, Wenjuan; Wang, Hao

2016-01-01

Highlights: • The reputation effect is added into the spatial public goods game model. • The individual utility is calculated as a combination of payoff and reputation. • The individual reputation will be adaptively modified as the system evolves. • The larger the reputation factor, the higher the cooperation level. - Abstract: How to model the evolution of cooperation within the population is an important and interdisciplinary issue across the academia. In this paper, we propose an improved public goods game model with reputation effect on spatial lattices to investigate the evolution of cooperation regarding the allocation of public resources. In our model, we modify the individual utility or fitness as a product of the present payoff and reputation-related power function, and strategy update adopts a Fermi-like probability function during the game evolution. Meanwhile, for an interaction between a pair of partners, the reputation of a cooperative agent will be accrued beyond two units, but the defective player will decrease his reputation by one unit. Extensive Monte Carlo numerical simulations indicate the introduction of reputation will foster the formation of cooperative clusters, and greatly enhance the level of public cooperation on the spatial lattices. The larger reputation factor leads to the higher cooperation level since the reputation effect will be enormously embedded into the utility evaluation under this scenario. The current results are vastly beneficial to understand the persistence and emergence of cooperation among many natural, social and synthetic systems, and also provide some useful suggestions to devise the feasible social governance measures and modes for the public resources or affairs.

Competition in spatial location models

NARCIS (Netherlands)

Webers, H.M.

1996-01-01

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

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.

Factor Copula Models for Replicated Spatial Data

KAUST Repository

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

2016-01-01

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

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.

Independence and interaction of luminance and chromatic contributions to spatial hyperacuity performance.

Science.gov (United States)

Cooper, Bonnie; Lee, Barry B

2014-04-01

Here we test interactions of luminance and chromatic input to spatial hyperacuity mechanisms. First, we tested alignment of luminance and chromatic gratings matched or mismatched in contrast polarity or grating type. Thresholds with matched gratings were low while all mismatched pairs were elevated. Second, we determined alignment acuity as a function of luminance or chromatic contrast alone or in the presence of constant contrast components of the other type. For in-phase components, performance followed the envelope of the more sensitive mechanism. However, polarity reversals revealed an asymmetric effect for luminance and chromatic conditions, which suggested that luminance can override chromatic mechanisms in hyperacuity; we interpret these findings in the context of spatial mechanisms.

Interacting dark sector with transversal interaction

Energy Technology Data Exchange (ETDEWEB)

Chimento, Luis P.; Richarte, Martín G. [Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and IFIBA, CONICET, Ciudad Universitaria, Pabellón I, Buenos Aires 1428 (Argentina)

2015-03-26

We investigate the interacting dark sector composed of dark matter, dark energy, and dark radiation for a spatially flat Friedmann-Robertson-Walker (FRW) background by introducing a three-dimensional internal space spanned by the interaction vector Q and solve the source equation for a linear transversal interaction. Then, we explore a realistic model with dark matter coupled to a scalar field plus a decoupled radiation term, analyze the amount of dark energy in the radiation era and find that our model is consistent with the recent measurements of cosmic microwave background anisotropy coming from Planck along with the future constraints achievable by CMBPol experiment.

Simple spatial scaling rules behind complex cities.

Science.gov (United States)

Li, Ruiqi; Dong, Lei; Zhang, Jiang; Wang, Xinran; Wang, Wen-Xu; Di, Zengru; Stanley, H Eugene

2017-11-28

Although most of wealth and innovation have been the result of human interaction and cooperation, we are not yet able to quantitatively predict the spatial distributions of three main elements of cities: population, roads, and socioeconomic interactions. By a simple model mainly based on spatial attraction and matching growth mechanisms, we reveal that the spatial scaling rules of these three elements are in a consistent framework, which allows us to use any single observation to infer the others. All numerical and theoretical results are consistent with empirical data from ten representative cities. In addition, our model can also provide a general explanation of the origins of the universal super- and sub-linear aggregate scaling laws and accurately predict kilometre-level socioeconomic activity. Our work opens a new avenue for uncovering the evolution of cities in terms of the interplay among urban elements, and it has a broad range of applications.

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

Science.gov (United States)

Sarker, M Mizanur Rahman

2012-04-01

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

Spatial memory tasks in rodents: what do they model?

Science.gov (United States)

Morellini, Fabio

2013-10-01

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

Spatial modelling of disease using data- and knowledge-driven approaches.

Science.gov (United States)

Stevens, Kim B; Pfeiffer, Dirk U

2011-09-01

The purpose of spatial modelling in animal and public health is three-fold: describing existing spatial patterns of risk, attempting to understand the biological mechanisms that lead to disease occurrence and predicting what will happen in the medium to long-term future (temporal prediction) or in different geographical areas (spatial prediction). Traditional methods for temporal and spatial predictions include general and generalized linear models (GLM), generalized additive models (GAM) and Bayesian estimation methods. However, such models require both disease presence and absence data which are not always easy to obtain. Novel spatial modelling methods such as maximum entropy (MAXENT) and the genetic algorithm for rule set production (GARP) require only disease presence data and have been used extensively in the fields of ecology and conservation, to model species distribution and habitat suitability. Other methods, such as multicriteria decision analysis (MCDA), use knowledge of the causal factors of disease occurrence to identify areas potentially suitable for disease. In addition to their less restrictive data requirements, some of these novel methods have been shown to outperform traditional statistical methods in predictive ability (Elith et al., 2006). This review paper provides details of some of these novel methods for mapping disease distribution, highlights their advantages and limitations, and identifies studies which have used the methods to model various aspects of disease distribution. Copyright © 2011. Published by Elsevier Ltd.

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

Science.gov (United States)

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

2016-04-01

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

Spatially Explicit Modeling Reveals Cephalopod Distributions Match Contrasting Trophic Pathways in the Western Mediterranean Sea.

Directory of Open Access Journals (Sweden)

Patricia Puerta

Full Text Available Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla and sea surface temperature (SST, and trophic (prey density conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents

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

High-precision spatial localization of mouse vocalizations during social interaction.

Science.gov (United States)

Heckman, Jesse J; Proville, Rémi; Heckman, Gert J; Azarfar, Alireza; Celikel, Tansu; Englitz, Bernhard

2017-06-07

Mice display a wide repertoire of vocalizations that varies with age, sex, and context. Especially during courtship, mice emit ultrasonic vocalizations (USVs) of high complexity, whose detailed structure is poorly understood. As animals of both sexes vocalize, the study of social vocalizations requires attributing single USVs to individuals. The state-of-the-art in sound localization for USVs allows spatial localization at centimeter resolution, however, animals interact at closer ranges, involving tactile, snout-snout exploration. Hence, improved algorithms are required to reliably assign USVs. We develop multiple solutions to USV localization, and derive an analytical solution for arbitrary vertical microphone positions. The algorithms are compared on wideband acoustic noise and single mouse vocalizations, and applied to social interactions with optically tracked mouse positions. A novel, (frequency) envelope weighted generalised cross-correlation outperforms classical cross-correlation techniques. It achieves a median error of ~1.4 mm for noise and ~4-8.5 mm for vocalizations. Using this algorithms in combination with a level criterion, we can improve the assignment for interacting mice. We report significant differences in mean USV properties between CBA mice of different sexes during social interaction. Hence, the improved USV attribution to individuals lays the basis for a deeper understanding of social vocalizations, in particular sequences of USVs.

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.

Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

Directory of Open Access Journals (Sweden)

Richard P Mann

2012-01-01

Full Text Available Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis. We show that these exhibit a stereotypical 'phase transition', whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have 'memory' of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture fine scale rules of interaction, which are primarily mediated by physical contact. Conversely, the Markovian self-propelled particle model captures the fine scale rules of interaction but fails to reproduce global dynamics. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.

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.

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.

Multi-physics modeling of plasma-material interactions

Science.gov (United States)

Lasa, Ane; Green, David; Canik, John; Younkin, Timothy; Blondel, Sophie; Wirth, Brian; Drobny, Jon; Curreli, Davide

2017-10-01

Plasma-material interactions (PMI) can degrade both plasma and material properties. Often, PMI modeling focuses on either the plasma or surface. Here, we present an integrated model with high-fidelity codes coupled within the IPS framework that self-consistently addresses PMI. The model includes, calculation of spatially resolved influx of plasma and impurities to the surface and their implantation; surface erosion and roughening; evolution of implanted species and sub-surface composition; and transport of eroded particles across the plasma and their re-deposition. The model is applied and successfully compared to dedicated PISCES linear device experiments, where a tungsten (W) target was exposed to helium (He) plasma. The present contribution will focus on the analysis of W erosion, He retention and sub-surface gas bubble and surface composition evolution, under the different He plasma conditions across the surface that are calculated by impurity transport modeling. Impact of code coupling, reflected as interplay between surface erosion, fuel / impurity implantation and retention, and evolution of target composition, as well as sensitivity of these processes to plasma exposure conditions is also analyzed in detail. This work is supported by the US DOE under contract DE-AC05-00OR22725.

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.

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.

Modelling the Spatial Isotope Variability of Precipitation in Syria

Energy Technology Data Exchange (ETDEWEB)

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

2013-07-15

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

Modelling temporal and spatial dynamics of benthic fauna in North-West-European shelf seas

Science.gov (United States)

Lessin, Gennadi; Bruggeman, Jorn; Artioli, Yuri; Butenschön, Momme; Blackford, Jerry

2017-04-01

Benthic zones of shallow shelf seas receive high amounts of organic material. Physical processes such as resuspension, as well as complex transformations mediated by diverse faunal and microbial communities, define fate of this material, which can be returned to the water column, reworked within sediments or ultimately buried. In recent years, numerical models of various complexity and serving different goals have been developed and applied in order to better understand and predict dynamics of benthic processes. ERSEM includes explicit parameterisations of several groups of benthic biota, which makes it particularly applicable for studies of benthic biodiversity, biological interactions within sediments and benthic-pelagic coupling. To assess model skill in reproducing temporal (inter-annual and seasonal) dynamics of major benthic macrofaunal groups, 1D model simulation results were compared with data from the Western Channel Observatory (WCO) benthic survey. The benthic model was forced with organic matter deposition rates inferred from observed phytoplankton abundance and model parameters were subsequently recalibrated. Based on model results and WCO data comparison, deposit-feeders exert clear seasonal variability, while for suspension-feeders inter-annual variability is more pronounced. Spatial distribution of benthic fauna was investigated using results of a full-scale NEMO-ERSEM hindcast simulation of the North-West European Shelf Seas area, covering the period of 1981-2014. Results suggest close relationship between spatial distribution of biomass of benthic faunal functional groups in relation to bathymetry, hydrodynamic conditions and organic matter supply. Our work highlights that it is feasible to construct, implement and validate models that explicitly include functional groups of benthic macrofauna. Moreover, the modelling approach delivers detailed information on benthic biogeochemistry and food-web at spatial and temporal scales that are unavailable

Impact of soil-vegetation-atmosphere interactions on the spatial rainfall distribution in the Central Sahel

Directory of Open Access Journals (Sweden)

Marcus Breil

2017-10-01

Full Text Available In a Regional Climate Model (RCM the interactions between the land surface and the atmosphere are described by a Soil-Vegetation-Atmosphere-Transfer Model (SVAT. In the presented study two SVATs of different complexity (TERRA-ML and VEG3D are coupled to the RCM COSMO-CLM (CCLM to investigate the impact of different representations of soil-vegetation-atmosphere interactions on the West African Monsoon (WAM system. In contrast to TERRA-ML, VEG3D comprises a more detailed description of the land-atmosphere coupling by including a vegetation layer in its structural design, changing the treatment of radiation and turbulent fluxes. With these two different model systems (CCLM-TERRA-ML and CCLM-VEG3D climate simulations are performed for West Africa and analyzed. The study reveals that the simulated spatial distribution of rainfall in the Sahel region is substantially affected by the chosen SVAT. Compared to CCLM-TERRA-ML, the application of CCLM-VEG3D results in higher near surface temperatures in the Sahel region during the rainy season. This implies a southward expansion of the Saharian heat-low. Consequently, the mean position of the African Easterly Jet (AEJ is also shifted to the south, leading to a southward displacement of tracks for Mesoscale Convective Systems (MCS, developing in connection with the AEJ. As a result, less precipitation is produced in the Sahel region, increasing the agreement with observations. These analyses indicate that soil-vegetation-atmosphere interactions impact the West African Monsoon system and highlight the benefit of using a more complex SVAT to simulate its dynamics.

PROBABILISTIC MODEL OF BEAM–PLASMA INTERACTION IN RANDOMLY INHOMOGENEOUS PLASMA

International Nuclear Information System (INIS)

Voshchepynets, A.; Krasnoselskikh, V.; Artemyev, A.; Volokitin, A.

2015-01-01

We propose a new model that describes beam–plasma interaction in the presence of random density fluctuations with a known probability distribution. We use the property that, for the given frequency, the probability distribution of the density fluctuations uniquely determines the probability distribution of the phase velocity of waves. We present the system as discrete and consisting of small, equal spatial intervals with a linear density profile. This approach allows one to estimate variations in wave energy density and particle velocity, depending on the density gradient on any small spatial interval. Because the characteristic time for the evolution of the electron distribution function and the wave energy is much longer than the time required for a single wave–particle resonant interaction over a small interval, we determine the description for the relaxation process in terms of averaged quantities. We derive a system of equations, similar to the quasi-linear approximation, with the conventional velocity diffusion coefficient D and the wave growth rate γ replaced by the average in phase space, by making use of the probability distribution for phase velocities and by assuming that the interaction in each interval is independent of previous interactions. Functions D and γ are completely determined by the distribution function for the amplitudes of the fluctuations. For the Gaussian distribution of the density fluctuations, we show that the relaxation process is determined by the ratio of beam velocity to plasma thermal velocity, the dispersion of the fluctuations, and the width of the beam in the velocity space

Stochastic modeling of mode interactions via linear parabolized stability equations

Science.gov (United States)

Ran, Wei; Zare, Armin; Hack, M. J. Philipp; Jovanovic, Mihailo

2017-11-01

Low-complexity approximations of the Navier-Stokes equations have been widely used in the analysis of wall-bounded shear flows. In particular, the parabolized stability equations (PSE) and Floquet theory have been employed to capture the evolution of primary and secondary instabilities in spatially-evolving flows. We augment linear PSE with Floquet analysis to formally treat modal interactions and the evolution of secondary instabilities in the transitional boundary layer via a linear progression. To this end, we leverage Floquet theory by incorporating the primary instability into the base flow and accounting for different harmonics in the flow state. A stochastic forcing is introduced into the resulting linear dynamics to model the effect of nonlinear interactions on the evolution of modes. We examine the H-type transition scenario to demonstrate how our approach can be used to model nonlinear effects and capture the growth of the fundamental and subharmonic modes observed in direct numerical simulations and experiments.

Spatially Informed Plant PRA Models for Security Assessment

International Nuclear Information System (INIS)

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

2006-01-01

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

Land-atmosphere interaction patterns in southeastern South America using satellite products and climate models

Science.gov (United States)

Spennemann, P. C.; Salvia, M.; Ruscica, R. C.; Sörensson, A. A.; Grings, F.; Karszenbaum, H.

2018-02-01

In regions of strong Land-Atmosphere (L-A) interaction, soil moisture (SM) conditions can impact the atmosphere through modulating the land surface fluxes. The importance of the identification of L-A interaction regions lies in the potential improvement of the weather/seasonal forecast and the better understanding of the physical mechanisms involved. This study aims to compare the terrestrial segment of the L-A interaction from satellite products and climate models, motivated by previous modeling studies pointing out southeastern South America (SESA) as a L-A hotspot during austral summer. In addition, the L-A interaction under dry or wet anomalous conditions over SESA is analyzed. To identify L-A hotspots the AMSRE-LPRM SM and MODIS land surface temperature products; coupled climate models and uncoupled land surface models were used. SESA highlights as a strong L-A interaction hotspot when employing different metrics, temporal scales and independent datasets, showing consistency between models and satellite estimations. Both AMSRE-LPRM bands (X and C) are consistent showing a strong L-A interaction hotspot over the Pampas ecoregion. Intensification and a larger spatial extent of the L-A interaction for dry summers was observed in both satellite products and models compared to wet summers. These results, which were derived from measured physical variables, are encouraging and promising for future studies analyzing L-A interactions. L-A interaction analysis is proposed here as a meeting point between remote sensing and climate modelling communities of Argentina, within a region with the highest agricultural and livestock production of the continent, but with an important lack of in-situ SM observations.

Gender-specific spatial interactions on Dutch regional labour markets and the gender employment gap

NARCIS (Netherlands)

Noback, Inge; Broersma, Lourens; Van Dijk, Jouke

2013-01-01

Gender-specific spatial interactions on Dutch regional labour markets and the gender employment gap, Regional Studies. This paper analyses gender-specific employment rates and the gender employment gap in Dutch municipalities for 2002. The novelty of this analysis is that it takes into account the

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.

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.

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

Science.gov (United States)

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

1996-01-01

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

Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

Directory of Open Access Journals (Sweden)

Richard P Mann

Full Text Available Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis. We show that these exhibit a stereotypical 'phase transition', whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have 'memory' of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture the observed locality of interactions. Traditional self-propelled particle models fail to capture the fine scale dynamics of the system. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics, while maintaining a biologically plausible perceptual range. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.

Spatial distributions of niche-constructing populations

Directory of Open Access Journals (Sweden)

Xiaozhuo Han

2015-12-01

Full Text Available Niche construction theory regards organisms not only as the object of natural selection but also an active subject that can change their own selective pressure through eco-evolutionary feedbacks. Through reviewing the existing works on the theoretical models of niche construction, here we present the progress made on how niche construction influences genetic structure of spatially structured populations and the spatial-temporal dynamics of metapopulations, with special focuses on mathematical models and simulation methods. The majority of results confirmed that niche construction can significantly alter the evolutionary trajectories of structured populations. Organism-environmental interactions induced by niche construction can have profound influence on the dynamics, competition and diversity of metapopulations. It can affect fine-scale spatially distribution of species and spatial heterogeneity of the environment. We further propose a few research directions with potentials, such as applying adaptive dynamics or spatial game theory to explore the effect of niche construction on phenotypic evolution and diversification.

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.

A spatial socio-ecosystem approach to analyse human-environment interactions on climate change adaptation for water resources management

Science.gov (United States)

Giupponi, Carlo; Mojtahed, Vahid

2017-04-01

Global climate and socio-economic drivers determine the future patterns of the allocation and the trade of resources and commodities in all markets. The agricultural sector is an emblematic case in which natural (e.g. climate), social (e.g. demography) and economic (e.g. the market) drivers of change interact, determining the evolution of social and ecological systems (or simply socio-ecosystems; SES) over time. In order to analyse the dynamics and possible future evolutions of SES, the combination of local complex systems and global drivers and trends require the development of multiscale approaches. At global level, climatic general circulation models (CGM) and computable general equilibrium or partial equilibrium models have been used for many years to explore the effects of global trends and generate future climate and socio-economic scenarios. Al local level, the inherent complexity of SESs and their spatial and temporal variabilities require different modelling approaches of physical/environmental sub-systems (e.g. field scale crop modelling, GIS-based models, etc.) and of human agency decision makers (e.g. agent based models). Global and local models have different assumption, limitations, constrains, etc., but in some cases integration is possible and several attempts are in progress to couple different models within the so-called Integrated Assessment Models. This work explores an innovative proposal to integrate the global and local approaches, where agent-based models (ABM) are used to simulate spatial (i.e. grid-based) and temporal dynamics of land and water resource use spatial and temporal dynamics, under the effect of global drivers. We focus in particular on how global change may affect land-use allocation at the local to regional level, under the influence of limited natural resources, land and water in particular. We specifically explore how constrains and competition for natural resources may induce non-linearities and discontinuities in socio

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...

Io's Magnetospheric Interaction: An MHD Model with Day-Night Asymmetry

Science.gov (United States)

Kabin, K.; Combi, M. R.; Gombosi, T. I.; DeZeeuw, D. L.; Hansen, K. C.; Powell, K. G.

2001-01-01

In this paper we present the results of all improved three-dimensional MHD model for Io's interaction with Jupiter's magnetosphere. We have included the day-night asymmetry into the spatial distribution of our mass-loading, which allowed us to reproduce several smaller features or the Galileo December 1995 data set. The calculation is performed using our newly modified description of the pick-up processes that accounts for the effects of the corotational electric field existing in the Jovian magnetosphere. This change in the formulation of the source terms for the MHD equations resulted in significant improvements in the comparison with the Galileo measurements. We briefly discuss the limitations of our model and possible future improvements.

Asymmetric biotic interactions and abiotic niche differences revealed by a dynamic joint species distribution model.

Science.gov (United States)

Lany, Nina K; Zarnetske, Phoebe L; Schliep, Erin M; Schaeffer, Robert N; Orians, Colin M; Orwig, David A; Preisser, Evan L

2018-05-01

A species' distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co-occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species' abundance on other species in the community. Accounting for dependence among co-occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions. © 2018 by the Ecological Society of America.

Modelling wetland-groundwater interactions in the boreal Kälväsvaara esker, Northern Finland

Science.gov (United States)

Jaros, Anna; Rossi, Pekka; Ronkanen, Anna-Kaisa; Kløve, Bjørn

2016-04-01

Many types of boreal peatland ecosystems such as alkaline fens, aapa mires and Fennoscandia spring fens rely on the presence of groundwater. In these ecosystems groundwater creates unique conditions for flora and fauna by providing water, nutrients and constant water temperature enriching local biodiversity. The groundwater-peatland interactions and their dynamics are not, however, in many cases fully understood and their measurement and quantification is difficult due to highly heterogeneous structure of peatlands and large spatial extend of these ecosystems. Understanding of these interactions and their changes due to anthropogenic impact on groundwater resources would benefit the protection of the groundwater dependent peatlands. The groundwater-peatland interactions were investigated using the fully-integrated physically-based groundwater-surface water code HydroGeoSphere in a case study of the Kälväsvaara esker aquifer, Northern Finland. The Kälväsvaara is a geologically complex esker and it is surrounded by vast aapa mire system including alkaline and springs fens. In addition, numerous small springs occur in the discharge zone of the esker. In order to quantify groundwater-peatland interactions a simple steady-state model was built and results were evaluated using expected trends and field measurements. The employed model reproduced relatively well spatially distributed hydrological variables such as soil water content, water depths and groundwater-surface water exchange fluxes within the wetland and esker areas. The wetlands emerged in simulations as a result of geological and topographical conditions. They could be identified by high saturation levels at ground surface and by presence of shallow ponded water over some areas. The model outputs exhibited also strong surface water-groundwater interactions in some parts of the aapa system. These areas were noted to be regions of substantial diffusive groundwater discharge by the earlier studies. In

Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

Science.gov (United States)

Schumann, Andreas; Oppel, Henning

2017-04-01

To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark

The importance of spatial ability and mental models in learning anatomy

Science.gov (United States)

Chatterjee, Allison K.

As a foundational course in medical education, gross anatomy serves to orient medical and veterinary students to the complex three-dimensional nature of the structures within the body. Understanding such spatial relationships is both fundamental and crucial for achievement in gross anatomy courses, and is essential for success as a practicing professional. Many things contribute to learning spatial relationships; this project focuses on a few key elements: (1) the type of multimedia resources, particularly computer-aided instructional (CAI) resources, medical students used to study and learn; (2) the influence of spatial ability on medical and veterinary students' gross anatomy grades and their mental models; and (3) how medical and veterinary students think about anatomy and describe the features of their mental models to represent what they know about anatomical structures. The use of computer-aided instruction (CAI) by gross anatomy students at Indiana University School of Medicine (IUSM) was assessed through a questionnaire distributed to the regional centers of the IUSM. Students reported using internet browsing, PowerPoint presentation software, and email on a daily bases to study gross anatomy. This study reveals that first-year medical students at the IUSM make limited use of CAI to study gross anatomy. Such studies emphasize the importance of examining students' use of CAI to study gross anatomy prior to development and integration of electronic media into the curriculum and they may be important in future decisions regarding the development of alternative learning resources. In order to determine how students think about anatomical relationships and describe the features of their mental models, personal interviews were conducted with select students based on students' ROT scores. Five typologies of the characteristics of students' mental models were identified and described: spatial thinking, kinesthetic approach, identification of anatomical structures

Modeling spatial processes with unknown extremal dependence class

KAUST Repository

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

2017-01-01

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

The impact of design-based modeling instruction on seventh graders' spatial abilities and model-based argumentation

Science.gov (United States)

McConnell, William J.

Due to the call of current science education reform for the integration of engineering practices within science classrooms, design-based instruction is receiving much attention in science education literature. Although some aspect of modeling is often included in well-known design-based instructional methods, it is not always a primary focus. The purpose of this study was to better understand how design-based instruction with an emphasis on scientific modeling might impact students' spatial abilities and their model-based argumentation abilities. In the following mixed-method multiple case study, seven seventh grade students attending a secular private school in the Mid-Atlantic region of the United States underwent an instructional intervention involving design-based instruction, modeling and argumentation. Through the course of a lesson involving students in exploring the interrelatedness of the environment and an animal's form and function, students created and used multiple forms of expressed models to assist them in model-based scientific argument. Pre/post data were collected through the use of The Purdue Spatial Visualization Test: Rotation, the Mental Rotation Test and interviews. Other data included a spatial activities survey, student artifacts in the form of models, notes, exit tickets, and video recordings of students throughout the intervention. Spatial abilities tests were analyzed using descriptive statistics while students' arguments were analyzed using the Instrument for the Analysis of Scientific Curricular Arguments and a behavior protocol. Models were analyzed using content analysis and interviews and all other data were coded and analyzed for emergent themes. Findings in the area of spatial abilities included increases in spatial reasoning for six out of seven participants, and an immense difference in the spatial challenges encountered by students when using CAD software instead of paper drawings to create models. Students perceived 3D printed

A componential model of human interaction with graphs: 1. Linear regression modeling

Science.gov (United States)

Gillan, Douglas J.; Lewis, Robert

1994-01-01

Task analyses served as the basis for developing the Mixed Arithmetic-Perceptual (MA-P) model, which proposes (1) that people interacting with common graphs to answer common questions apply a set of component processes-searching for indicators, encoding the value of indicators, performing arithmetic operations on the values, making spatial comparisons among indicators, and repsonding; and (2) that the type of graph and user's task determine the combination and order of the components applied (i.e., the processing steps). Two experiments investigated the prediction that response time will be linearly related to the number of processing steps according to the MA-P model. Subjects used line graphs, scatter plots, and stacked bar graphs to answer comparison questions and questions requiring arithmetic calculations. A one-parameter version of the model (with equal weights for all components) and a two-parameter version (with different weights for arithmetic and nonarithmetic processes) accounted for 76%-85% of individual subjects' variance in response time and 61%-68% of the variance taken across all subjects. The discussion addresses possible modifications in the MA-P model, alternative models, and design implications from the MA-P model.

Urban land use decouples plant-herbivore-parasitoid interactions at multiple spatial scales.

Directory of Open Access Journals (Sweden)

Amanda E Nelson

Full Text Available Intense urban and agricultural development alters habitats, increases fragmentation, and may decouple trophic interactions if plants or animals cannot disperse to needed resources. Specialist insects represent a substantial proportion of global biodiversity and their fidelity to discrete microhabitats provides a powerful framework for investigating organismal responses to human land use. We sampled site occupancy and densities for two plant-herbivore-parasitoid systems from 250 sites across a 360 km2 urban/agricultural landscape to ask whether and how human development decouples interactions between trophic levels. We compared patterns of site occupancy, host plant density, herbivory and parasitism rates of insects at two trophic levels with respect to landcover at multiple spatial scales. Geospatial analyses were used to identify landcover characters predictive of insect distributions. We found that herbivorous insect densities were decoupled from host tree densities in urban landcover types at several spatial scales. This effect was amplified for the third trophic level in one of the two insect systems: despite being abundant regionally, a parasitoid species was absent from all urban/suburban landcover even where its herbivore host was common. Our results indicate that human land use patterns limit distributions of specialist insects. Dispersal constraints associated with urban built development are specifically implicated as a limiting factor.

Nonparametric Bayesian models for a spatial covariance.

Science.gov (United States)

Reich, Brian J; Fuentes, Montserrat

2012-01-01

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

Spatially Uniform ReliefF (SURF for computationally-efficient filtering of gene-gene interactions

Directory of Open Access Journals (Sweden)

Greene Casey S

2009-09-01

Full Text Available Abstract Background Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF, which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF. Results SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm. Conclusion Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be

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.

SeiVis: An interactive visual subsurface modeling application

KAUST Repository

Hollt, Thomas; Freiler, Wolfgang; Gschwantner, Fritz M.; Doleisch, Helmut; Heinemann, Gabor F.; Hadwiger, Markus

2012-01-01

The most important resources to fulfill today’s energy demands are fossil fuels, such as oil and natural gas. When exploiting hydrocarbon reservoirs, a detailed and credible model of the subsurface structures is crucial in order to minimize economic and ecological risks. Creating such a model is an inverse problem: reconstructing structures from measured reflection seismics. The major challenge here is twofold: First, the structures in highly ambiguous seismic data are interpreted in the time domain. Second, a velocity model has to be built from this interpretation to match the model to depth measurements from wells. If it is not possible to obtain a match at all positions, the interpretation has to be updated, going back to the first step. This results in a lengthy back and forth between the different steps, or in an unphysical velocity model in many cases. This paper presents a novel, integrated approach to interactively creating subsurface models from reflection seismics. It integrates the interpretation of the seismic data using an interactive horizon extraction technique based on piecewise global optimization with velocity modeling. Computing and visualizing the effects of changes to the interpretation and velocity model on the depth-converted model on the fly enables an integrated feedback loop that enables a completely new connection of the seismic data in time domain and well data in depth domain. Using a novel joint time/depth visualization, depicting side-by-side views of the original and the resulting depth-converted data, domain experts can directly fit their interpretation in time domain to spatial ground truth data. We have conducted a domain expert evaluation, which illustrates that the presented workflow enables the creation of exact subsurface models much more rapidly than previous approaches. © 2012 IEEE.

SeiVis: An interactive visual subsurface modeling application

KAUST Repository

Hollt, Thomas

2012-12-01

The most important resources to fulfill today’s energy demands are fossil fuels, such as oil and natural gas. When exploiting hydrocarbon reservoirs, a detailed and credible model of the subsurface structures is crucial in order to minimize economic and ecological risks. Creating such a model is an inverse problem: reconstructing structures from measured reflection seismics. The major challenge here is twofold: First, the structures in highly ambiguous seismic data are interpreted in the time domain. Second, a velocity model has to be built from this interpretation to match the model to depth measurements from wells. If it is not possible to obtain a match at all positions, the interpretation has to be updated, going back to the first step. This results in a lengthy back and forth between the different steps, or in an unphysical velocity model in many cases. This paper presents a novel, integrated approach to interactively creating subsurface models from reflection seismics. It integrates the interpretation of the seismic data using an interactive horizon extraction technique based on piecewise global optimization with velocity modeling. Computing and visualizing the effects of changes to the interpretation and velocity model on the depth-converted model on the fly enables an integrated feedback loop that enables a completely new connection of the seismic data in time domain and well data in depth domain. Using a novel joint time/depth visualization, depicting side-by-side views of the original and the resulting depth-converted data, domain experts can directly fit their interpretation in time domain to spatial ground truth data. We have conducted a domain expert evaluation, which illustrates that the presented workflow enables the creation of exact subsurface models much more rapidly than previous approaches. © 2012 IEEE.

SeiVis: An Interactive Visual Subsurface Modeling Application.

Science.gov (United States)

Hollt, T; Freiler, W; Gschwantner, F; Doleisch, H; Heinemann, G; Hadwiger, M

2012-12-01

The most important resources to fulfill today's energy demands are fossil fuels, such as oil and natural gas. When exploiting hydrocarbon reservoirs, a detailed and credible model of the subsurface structures is crucial in order to minimize economic and ecological risks. Creating such a model is an inverse problem: reconstructing structures from measured reflection seismics. The major challenge here is twofold: First, the structures in highly ambiguous seismic data are interpreted in the time domain. Second, a velocity model has to be built from this interpretation to match the model to depth measurements from wells. If it is not possible to obtain a match at all positions, the interpretation has to be updated, going back to the first step. This results in a lengthy back and forth between the different steps, or in an unphysical velocity model in many cases. This paper presents a novel, integrated approach to interactively creating subsurface models from reflection seismics. It integrates the interpretation of the seismic data using an interactive horizon extraction technique based on piecewise global optimization with velocity modeling. Computing and visualizing the effects of changes to the interpretation and velocity model on the depth-converted model on the fly enables an integrated feedback loop that enables a completely new connection of the seismic data in time domain and well data in depth domain. Using a novel joint time/depth visualization, depicting side-by-side views of the original and the resulting depth-converted data, domain experts can directly fit their interpretation in time domain to spatial ground truth data. We have conducted a domain expert evaluation, which illustrates that the presented workflow enables the creation of exact subsurface models much more rapidly than previous approaches.

China's Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model.

Science.gov (United States)

Cao, Qilong; Liang, Ying; Niu, Xueting

2017-09-18

Background : Air pollution has become an important factor restricting China's economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods : Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM 2.5 . Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results : It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM 2.5 pollutions in the control of other variables. Conclusions : Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables.

Stochastic population dynamics in spatially extended predator-prey systems

Science.gov (United States)

Dobramysl, Ulrich; Mobilia, Mauro; Pleimling, Michel; Täuber, Uwe C.

2018-02-01

Spatially extended population dynamics models that incorporate demographic noise serve as case studies for the crucial role of fluctuations and correlations in biological systems. Numerical and analytic tools from non-equilibrium statistical physics capture the stochastic kinetics of these complex interacting many-particle systems beyond rate equation approximations. Including spatial structure and stochastic noise in models for predator-prey competition invalidates the neutral Lotka-Volterra population cycles. Stochastic models yield long-lived erratic oscillations stemming from a resonant amplification mechanism. Spatially extended predator-prey systems display noise-stabilized activity fronts that generate persistent correlations. Fluctuation-induced renormalizations of the oscillation parameters can be analyzed perturbatively via a Doi-Peliti field theory mapping of the master equation; related tools allow detailed characterization of extinction pathways. The critical steady-state and non-equilibrium relaxation dynamics at the predator extinction threshold are governed by the directed percolation universality class. Spatial predation rate variability results in more localized clusters, enhancing both competing species’ population densities. Affixing variable interaction rates to individual particles and allowing for trait inheritance subject to mutations induces fast evolutionary dynamics for the rate distributions. Stochastic spatial variants of three-species competition with ‘rock-paper-scissors’ interactions metaphorically describe cyclic dominance. These models illustrate intimate connections between population dynamics and evolutionary game theory, underscore the role of fluctuations to drive populations toward extinction, and demonstrate how space can support species diversity. Two-dimensional cyclic three-species May-Leonard models are characterized by the emergence of spiraling patterns whose properties are elucidated by a mapping onto a complex

Elucidating the interaction between light competition and herbivore feeding patterns using functional–structural plant modelling

Science.gov (United States)

de Vries, Jorad; Poelman, Erik H; Anten, Niels; Evers, Jochem B

2018-01-01

Abstract Background and Aims Plants usually compete with neighbouring plants for resources such as light as well as defend themselves against herbivorous insects. This requires investment of limiting resources, resulting in optimal resource distribution patterns and trade-offs between growth- and defence-related traits. A plant’s competitive success is determined by the spatial distribution of its resources in the canopy. The spatial distribution of herbivory in the canopy in turn differs between herbivore species as the level of herbivore specialization determines their response to the distribution of resources and defences in the canopy. Here, we investigated to what extent competition for light affects plant susceptibility to herbivores with different feeding preferences. Methods To quantify interactions between herbivory and competition, we developed and evaluated a 3-D spatially explicit functional–structural plant model for Brassica nigra that mechanistically simulates competition in a dynamic light environment, and also explicitly models leaf area removal by herbivores with different feeding preferences. With this novel approach, we can quantitatively explore the extent to which herbivore feeding location and light competition interact in their effect on plant performance. Key Results Our results indicate that there is indeed a strong interaction between levels of plant–plant competition and herbivore feeding preference. When plants did not compete, herbivory had relatively small effects irrespective of feeding preference. Conversely, when plants competed, herbivores with a preference for young leaves had a strong negative effect on the competitiveness and subsequent performance of the plant, whereas herbivores with a preference for old leaves did not. Conclusions Our study predicts how plant susceptibility to herbivory depends on the composition of the herbivore community and the level of plant competition, and highlights the importance of considering

Elucidating the interaction between light competition and herbivore feeding patterns using functional-structural plant modelling.

Science.gov (United States)

de Vries, Jorad; Poelman, Erik H; Anten, Niels; Evers, Jochem B

2018-01-24

Plants usually compete with neighbouring plants for resources such as light as well as defend themselves against herbivorous insects. This requires investment of limiting resources, resulting in optimal resource distribution patterns and trade-offs between growth- and defence-related traits. A plant's competitive success is determined by the spatial distribution of its resources in the canopy. The spatial distribution of herbivory in the canopy in turn differs between herbivore species as the level of herbivore specialization determines their response to the distribution of resources and defences in the canopy. Here, we investigated to what extent competition for light affects plant susceptibility to herbivores with different feeding preferences. To quantify interactions between herbivory and competition, we developed and evaluated a 3-D spatially explicit functional-structural plant model for Brassica nigra that mechanistically simulates competition in a dynamic light environment, and also explicitly models leaf area removal by herbivores with different feeding preferences. With this novel approach, we can quantitatively explore the extent to which herbivore feeding location and light competition interact in their effect on plant performance. Our results indicate that there is indeed a strong interaction between levels of plant-plant competition and herbivore feeding preference. When plants did not compete, herbivory had relatively small effects irrespective of feeding preference. Conversely, when plants competed, herbivores with a preference for young leaves had a strong negative effect on the competitiveness and subsequent performance of the plant, whereas herbivores with a preference for old leaves did not. Our study predicts how plant susceptibility to herbivory depends on the composition of the herbivore community and the level of plant competition, and highlights the importance of considering the full range of dynamics in plant-plant-herbivore interactions

Spatial Modeling of Deforestation in FMU of Poigar, North Sulawesi

OpenAIRE

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

2016-01-01

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

On the spatial dynamics and oscillatory behavior of a predator-prey model based on cellular automata and local particle swarm optimization.

Science.gov (United States)

Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan

2013-11-07

A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.

Spatiality of ethnic identity and construction of sociopolitical interaction in South Sudan

Directory of Open Access Journals (Sweden)

Kon K. Madut

2017-11-01

Full Text Available This article explores the complexity of the spatial construction of ethnicity, identity, and sociopolitical interaction among South Sudanese ethnic groups. The article focuses on the interplay between social interaction and the construction of ethnic identity as they affect the notion of human interaction and welfare. The narratives are based on the political sociology of South Sudan after its independence from Sudan and challenges endured in the process of sociopolitical transformation towards the reconstruction of national identity and peaceful coexistence. This discourse gives meaning to visible and invisible ethno-cultural constructions that shaped the norms of social and political interactions among various ethnic groups in the country. The analysis concluded that South Sudan society is socially, politically, and culturally constructed along ethnicized communities with variant perceptions of group and regional identities based on both primordial ties and instrumentalists’ perceptions. These unique characteristics of spaces and construction of social structure has created multi-faceted challenges in the process of social, economic and political reconstruction after the independent of South Sudan in July 2011.

Automating an integrated spatial data-mining model for landfill site selection

Science.gov (United States)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Aziz, Hamidi Abdul

2017-10-01

An integrated programming environment represents a robust approach to building a valid model for landfill site selection. One of the main challenges in the integrated model is the complicated processing and modelling due to the programming stages and several limitations. An automation process helps avoid the limitations and improve the interoperability between integrated programming environments. This work targets the automation of a spatial data-mining model for landfill site selection by integrating between spatial programming environment (Python-ArcGIS) and non-spatial environment (MATLAB). The model was constructed using neural networks and is divided into nine stages distributed between Matlab and Python-ArcGIS. A case study was taken from the north part of Peninsular Malaysia. 22 criteria were selected to utilise as input data and to build the training and testing datasets. The outcomes show a high-performance accuracy percentage of 98.2% in the testing dataset using 10-fold cross validation. The automated spatial data mining model provides a solid platform for decision makers to performing landfill site selection and planning operations on a regional scale.

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.

Spatial modeling of agricultural land use change at global scale

Science.gov (United States)

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

2014-11-01

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

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

DEFF Research Database (Denmark)

Veie, Kathrine Lausted; Panduro, Toke Emil

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

Practical likelihood analysis for spatial generalized linear mixed models

DEFF Research Database (Denmark)

Bonat, W. H.; Ribeiro, Paulo Justiniano

2016-01-01

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

Modeling mode interactions in boundary layer flows via the Parabolized Floquet Equations

OpenAIRE

Ran, Wei; Zare, Armin; Hack, M. J. Philipp; Jovanović, Mihailo R.

2017-01-01

In this paper, we develop a linear model to study interactions between different modes in slowly-growing boundary layer flows. Our method consists of two steps. First, we augment the Blasius boundary layer profile with a disturbance field resulting from the linear Parabolized Stability Equations (PSE) to obtain the modified base flow; and, second, we combine Floquet analysis with the linear PSE to capture the spatial evolution of flow fluctuations. This procedure yields the Parabolized Floque...

Extinction threshold of a population in spatial and stochastic model

OpenAIRE

Soroka, Yevheniia; Rublyov, Bogdan

2016-01-01

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

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

On Angular Sampling Methods for 3-D Spatial Channel Models

DEFF Research Database (Denmark)

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

2015-01-01

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

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.

Spatial scale effects in environmental risk-factor modelling for diseases

Directory of Open Access Journals (Sweden)

Ram K. Raghavan

2013-05-01

Full Text Available Studies attempting to identify environmental risk factors for diseases can be seen to extract candidate variables from remotely sensed datasets, using a single buffer-zone surrounding locations from where disease status are recorded. A retrospective case-control study using canine leptospirosis data was conducted to verify the effects of changing buffer-zones (spatial extents on the risk factors derived. The case-control study included 94 case dogs predominantly selected based on positive polymerase chain reaction (PCR test for leptospires in urine, and 185 control dogs based on negative PCR. Land cover features from National Land Cover Dataset (NLCD and Kansas Gap Analysis Program (KS GAP around geocoded addresses of cases/controls were extracted using multiple buffers at every 500 m up to 5,000 m, and multivariable logistic models were used to estimate the risk of different land cover variables to dogs. The types and statistical significance of risk factors identified changed with an increase in spatial extent in both datasets. Leptospirosis status in dogs was significantly associated with developed high-intensity areas in models that used variables extracted from spatial extents of 500-2000 m, developed medium-intensity areas beyond 2,000 m and up to 3,000 m, and evergreen forests beyond 3,500 m and up to 5,000 m in individual models in the NLCD. Significant associations were seen in urban areas in models that used variables extracted from spatial extents of 500-2,500 m and forest/woodland areas beyond 2,500 m and up to 5,000 m in individual models in Kansas gap analysis programme datasets. The use of ad hoc spatial extents can be misleading or wrong, and the determination of an appropriate spatial extent is critical when extracting environmental variables for studies. Potential work-arounds for this problem are discussed.

The mARM3D spatially distributed soil evolution model: Three-dimensional model framework and analysis of hillslope and landform responses

Science.gov (United States)

Cohen, Sagy; Willgoose, Garry; Hancock, Greg

2010-10-01

We present a three-dimensional landscape-pedogenesis model, mARM3D (matrices ARMOUR 3D), which simulates soil evolution as a function of erosion and pedogenic processes. The model simulates the discretized soil profile for points on a spatial grid. The approach, using transition matrices, is computationally efficient and allows the simulation of large-scale spatial coupling and long-term soil evolution. We study the effect of the depth-dependent soil-weathering rate (i.e., the rate of soil particle breakdown) and bedrock-lowering rate (i.e., the rate of conversion of bedrock to soil). The difference in depth-dependent weathering functions has a significant effect on the in-profile soil properties through depth, specifically particle size grading. However, the depth dependency has a relatively minor effect on the surface properties of the soil profile, with all weathering functions generating very similar surface properties. The surface properties were a function of the cumulative amount of weathering (i.e., the integral of the weathering function over exhumation) with finer surface grading for higher weathering rates. Soil thickness could be estimated without explicitly modeling soil thickness. Thickness was negatively correlated with surface median grain size. As thickness decreases, the surface grading coarsens. This was driven by surface erosion, where as surface grading coarsens, erosion decreases and the soil deepens. Weathering and erosion interact to spatially organize the surface soil grading with a log-log relationship between surface grading, contributing area, and local slope. This relationship was independent of the weathering function. This relationship might be useful for the spatial description of soil properties in digital soil mapping.

Magnetic interaction between spatially extended superconducting tunnel junctions

DEFF Research Database (Denmark)

Grønbech-Jensen, Niels; Samuelsen, Mogens Rugholm

2002-01-01

A general description of magnetic interactions between superconducting tunnel junctions is given. The description covers a wide range of possible experimental systems, and we explicitly explore two experimentally relevant limits of coupled junctions. One is the limit of junctions with tunneling...... been considered through arrays of superconducting weak links based on semiconductor quantum wells with superconducting electrodes. We use the model to make direct interpretations of the published experiments and thereby propose that long-range magnetic interactions are responsible for the reported...

Role of the thalamic nucleus reuniens in mediating interactions between the hippocampus and medial prefrontal cortex during spatial working memory

Directory of Open Access Journals (Sweden)

Amy L Griffin

2015-03-01

Full Text Available Despite decades of research, the neural mechanisms of spatial working memory remain poorly understood. Although the dorsal hippocampus is known to be critical for memory-guided behavior, experimental evidence suggests that spatial working memory depends not only on the hippocampus itself, but also on the circuit comprised of the hippocampus and the medial prefrontal cortex (mPFC. Disruption of hippocampal-mPFC interactions may result in failed transfer of spatial and contextual information processed by the hippocampus to the circuitry in mPFC responsible for decision making and goal-directed behavior. Oscillatory synchrony between the hippocampus and mPFC has been shown to increase in tasks with high spatial working memory demand. However, the mechanisms and circuitry supporting hippocampal-mPFC interactions during these tasks is unknown. The midline thalamic nucleus reuniens (RE is reciprocally connected to both the hippocampus and the mPFC and has been shown to be critical for a variety of working memory tasks. Therefore, it is likely that hippocampal-mPFC oscillatory synchrony is modulated by RE activity. This article will review the anatomical connections between the hippocampus, mPFC and RE along with the behavioral studies that have investigated the effects of RE disruption on working memory task performance. The article will conclude with suggestions for future directions aimed at identifying the specific role of the RE in regulating functional interactions between the hippocampus and the PFC and investigating the degree to which these interactions contribute to spatial working memory.

Multi-Scale Analysis of Regional Inequality based on Spatial Field Model: A Case Study of China from 2000 to 2012

Directory of Open Access Journals (Sweden)

Shasha Lu

2015-10-01

Full Text Available A large body of recent studies—from both inside and outside of China—are devoted to the understanding of China’s regional inequality. The current study introduces “the spatial field model” to achieve comprehensive evaluation and multi-scale analysis of regional inequality. The model is based on the growth pole theory, regional interaction theory, and energy space theory. The spatial field is an abstract concept that defines the potential energy difference that is formed in the process of a regional growth pole driving the economic development of peripheral areas through transportation and communication corridors. The model is able to provide potentially more precise regional inequality estimates and generates isarithmic maps that will provide highly intuitive and visualized presentations. The model is applied to evaluate the spatiotemporal pattern of economic inequality in China from 2000 to 2012 amongst internal eastern-central-western regions as well as north-south regions at three geographical scales—i.e., inter-province, inter-city, and inter-county. The results indicate that the spatial field model could comprehensively evaluate regional inequality, provide aesthetically pleasing and highly adaptable presentations based on a pixel-based raster, and realise the multi-scale analyses of the regional inequality. The paper also investigates the limitations and extensions of the spatial field model in future application.

Ecological and evolutionary consequences of tri-trophic interactions: Spatial variation and effects of plant density.

Science.gov (United States)

Abdala-Roberts, Luis; Parra-Tabla, Víctor; Moreira, Xoaquín; Ramos-Zapata, José

2017-02-01

The factors driving variation in species interactions are often unknown, and few studies have made a link between changes in interactions and the strength of selection. We report on spatial variation in functional responses by a seed predator (SP) and its parasitic wasps associated with the herb Ruellia nudiflora . We assessed the influence of plant density on consumer responses and determined whether density effects and spatial variation in functional responses altered natural selection by these consumers on the plant. We established common gardens at two sites in Yucatan, Mexico, and planted R. nudiflora at two densities in each garden. We recorded fruit output and SP and parasitoid attack; calculated relative fitness (seed number) under scenarios of three trophic levels (accounting for SP and parasitoid effects), two trophic levels (accounting for SP but not parasitoid effects), and one trophic level (no consumer effects); and compared selection strength on fruit number under these scenarios across sites and densities. There was spatial variation in SP recruitment, whereby the SP functional response was negatively density-dependent at one site but density-independent at the other; parasitoid responses were density-independent and invariant across sites. Site variation in SP attack led, in turn, to differences in SP selection on fruit output, and parasitoids did not alter SP selection. There were no significant effects of density at either site. Our results provide a link between consumer functional responses and consumer selection on plants, which deepens our understanding of geographic variation in the evolutionary outcomes of multitrophic interactions. © 2017 Botanical Society of America.

Normal modes and possibility of spatially inhomogeneous phases for a 2D ferromagnet with biquadratic and magnetoelastic interactions

International Nuclear Information System (INIS)

Fridman, Yu.A.; Klevets, Ph.N.; Matyunin, D.A.

2006-01-01

Influence of the magnetodipolar interaction on the phase states of a 2D non-Heisenberg ferromagnet is investigated. It is shown that in the system considered both the homogeneous states (ferromagnetic or quadrupolar) and the spatially inhomogeneous ones can be realized. At this the spatial inhomogeneity is related with the distribution of the quadrupolar order parameters

The influence of photon depth of interaction and non-collinear spread of annihilation photons on PET image spatial resolution

International Nuclear Information System (INIS)

Sanchez-Crespo, Alejandro; Larsson, Stig A.

2006-01-01

The quality of PET imaging is impaired by parallax errors. These errors produce misalignment between the projected location of the true origin of the annihilation event and the line of response determined by the coincidence detection system. Parallax errors are due to the varying depths of photon interaction (DOI) within the scintillator and the non-collinear (NC) emission of the annihilation photons. The aim of this work was to address the problems associated with the DOI and the NC spread of annihilation photons and to develop a quantitative model to assess their impact on image spatial resolution losses for various commonly used scintillators and PET geometries. A theoretical model based on Monte Carlo simulations was developed to assess the relative influence of DOI and the NC spread of annihilation photons on PET spatial resolution for various scintillator materials (BGO, LSO, LuAP, GSO, NaI) and PET geometries. The results demonstrate good agreement between simulated, experimental and published overall spatial resolution for some commercial systems, with maximum differences around 1 mm in both 2D and 3D mode. The DOI introduces an impairment of non-stationary spatial resolution along the radial direction, which can be very severe at peripheral positions. As an example, the radial spatial resolution loss due to DOI increased from 1.3 mm at the centre to 6.7 mm at 20 cm from the centre of a BGO camera with a 412-mm radius in 2D mode. Including the NC, the corresponding losses were 3.0 mm at the centre and 7.3 mm 20 cm from the centre. Without a DOI detection technique, it seems difficult to improve PET spatial resolution and increase sensitivity by reducing the detector ring radius or by extending the detector in the axial direction. Much effort is expended on the design and configuration of smaller detector elements but more effort should be devoted to the DOI complexity. (orig.)

Analysing earthquake slip models with the spatial prediction comparison test

KAUST Repository

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

2014-01-01

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

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.

Hyperon-nucleon and hyperon-hyperon interaction in the quark cluster model

International Nuclear Information System (INIS)

Straub, U.

1988-01-01

The nonrelativistic quark cluster model is used for the description of the hyperon-nucleon and hyperon-hyperon interaction. The different mass of the quarks is consistently regarded in the Hamiltonian and in the shape of the spatial wave functions of the quarks. The six-quark wave function is completely antisymmetrisized. By means of the resonating-group method the dynamic equations for the determination of the binding and scattering states of the six-quark problem are formulated. The corresponding resonating-group kernels are explicitely given. We calculate the lambda-nucleon and sigma-nucleon interaction. The sigma-nucleon scattering in the isospin (T=3/2) channel can be treated in a one-channel calculation. The sigma-nucleon (T=1/2) interaction and the lambda-nucleon interaction are studied in a coupled two-channel calculation. From a fit of the experimental lambda-nucleon interaction cross section the strength of the sigma-meson exchange is determined. The calculation of the sigma-nucleon scattering follows then completely parameterless. The agreement of the theory with the experiment is good. Subsequently the cluster model with this parameter is applied to the dihyperon which is a possibly bound state of two up quarks, two down quarks, and two strange quarks. We solve for this a coupled three-channel calculation. The cluster model presented here gives a binding energy of the dihyperon of (20±5) MeV below the lambda-lambda threshold. The mass of the dihyperon is predicted by this as (2211±5) MeV. (orig.) [de

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

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

Science.gov (United States)

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

2009-10-01

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

Spatial and functional modeling of carnivore and insectivore molariform teeth.

Science.gov (United States)

Evans, Alistair R; Sanson, Gordon D

2006-06-01

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

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.

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...

Videogame interventions and spatial ability interactions.

Science.gov (United States)

Redick, Thomas S; Webster, Sean B

2014-01-01

Numerous research studies have been conducted on the use of videogames as tools to improve one's cognitive abilities. While meta-analyses and qualitative reviews have provided evidence that some aspects of cognition such as spatial imagery are modified after exposure to videogames, other evidence has shown that matrix reasoning measures of fluid intelligence do not show evidence of transfer from videogame training. In the current work, we investigate the available evidence for transfer specifically to nonverbal intelligence and spatial ability measures, given recent research that these abilities may be most sensitive to training on cognitive and working memory tasks. Accordingly, we highlight a few studies that on the surface provide evidence for transfer to spatial abilities, but a closer look at the pattern of data does not reveal a clean interpretation of the results. We discuss the implications of these results in relation to research design and statistical analysis practices.

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

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.

A Non-Gaussian Spatial Generalized Linear Latent Variable Model

KAUST Repository

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

2012-01-01

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

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.

Spatial equity analysis on expressway network development in Japan: Empirical approach using the spatial computable general equilibrium model RAEM-light

NARCIS (Netherlands)

Koike, A.; Tavasszy, L.; Sato, K.

2009-01-01

The authors apply the RAEM-Light model to analyze the distribution of social benefits from expressway network projects from the viewpoint of spatial equity. The RAEM-Light model has some innovative features. The spatial behavior of producers and consumers is explicitly described and is endogenously

Human-scale interaction for virtual model displays: a clear case for real tools

Science.gov (United States)

Williams, George C.; McDowall, Ian E.; Bolas, Mark T.

1998-04-01

We describe a hand-held user interface for interacting with virtual environments displayed on a Virtual Model Display. The tool, constructed entirely of transparent materials, is see-through. We render a graphical counterpart of the tool on the display and map it one-to-one with the real tool. This feature, combined with a capability for touch- sensitive, discrete input, results in a useful spatial input device that is visually versatile. We discuss the tool's design and interaction techniques it supports. Briefly, we look at the human factors issues and engineering challenges presented by this tool and, in general, by the class of hand-held user interfaces that are see-through.