Stability of a spatial model of social interactions
International Nuclear Information System (INIS)
Bragard, Jean; Mossay, Pascal
2016-01-01
We study a spatial model of social interactions. Though the properties of the spatial equilibrium have been largely discussed in the existing literature, the stability of equilibrium remains an unaddressed issue. Our aim is to fill up this gap by introducing dynamics in the model and by determining the stability of equilibrium. First we derive a variational equation useful for the stability analysis. This allows to study the corresponding eigenvalue problem. While odd modes are shown to be always stable, there is a single even mode of which stability depends on the model parameters. Finally various numerical simulations illustrate our theoretical results.
Spatially balanced topological interaction grants optimal cohesion in flocking models.
Camperi, Marcelo; Cavagna, Andrea; Giardina, Irene; Parisi, Giorgio; Silvestri, Edmondo
2012-12-06
Models of self-propelled particles (SPPs) are an indispensable tool to investigate collective animal behaviour. Originally, SPP models were proposed with metric interactions, where each individual coordinates with neighbours within a fixed metric radius. However, recent experiments on bird flocks indicate that interactions are topological: each individual interacts with a fixed number of neighbours, irrespective of their distance. It has been argued that topological interactions are more robust than metric ones against external perturbations, a significant evolutionary advantage for systems under constant predatory pressure. Here, we test this hypothesis by comparing the stability of metric versus topological SPP models in three dimensions. We show that topological models are more stable than metric ones. We also show that a significantly better stability is achieved when neighbours are selected according to a spatially balanced topological rule, namely when interacting neighbours are evenly distributed in angle around the focal individual. Finally, we find that the minimal number of interacting neighbours needed to achieve fully stable cohesion in a spatially balanced model is compatible with the value observed in field experiments on starling flocks.
Pattern formation through spatial interactions in a modified Daisyworld model
Alberti, Tommaso; Primavera, Leonardo; Lepreti, Fabio; Vecchio, Antonio; Carbone, Vincenzo
2015-04-01
The Daisyworld model is based on a hypothetical planet, like the Earth, which receives the radiant energy coming from a Sun-like star, and populated by two kinds of identical plants differing by their colour: white daisies reflecting light and black daisies absorbing light. The interactions and feedbacks between the collective biota of the planet and the incoming radiation form a self-regulating system where the conditions for life are maintained. We investigate a modified version of the Daisyworld model where a spatial dependency on latitude is introduced, and both a variable heat diffusivity along latitude and a simple greenhouse model are included. We show that the spatial interactions between the variables of the system can generate some equilibrium patterns which can locally stabilize the coexistence of the two vegetation types. The feedback on albedo is able to generate new equilibrium solutions which can efficiently self-regulate the planet climate, even for values of the solar luminosity relatively far from the current Earth conditions. The extension to spatial Daisyworld gives room to the possibility of inhomogeneous solar forcing in a curved planet, with explicit differences between poles and equator and the direct use of the heat diffusion equation. As a first approach, to describe a spherical planet, we consider the temperature T(θ,t) and the surface coverage as depending only on time and on latitude θ (-90° ≤ θ ≤ 90°). A second step is the introduction of the greenhouse effect in the model, the process by which outgoing infrared radiation is partly screened by greenhouse gases. This effect can be described by relaxing the black-body radiation hypothesis and by introducing a grayness function g(T) in the heat equation. As a third step, we consider a latitude dependence of the Earth's conductivity, χ = χ(θ). Considering these terms, using spherical coordinates and symmetry with respect to θ, the modified Daisyworld equations reduce to the
Modelling of spatially complex human-ecosystem, rural-urban and rich-poor interactions
CSIR Research Space (South Africa)
Naude, AH
2008-06-01
Full Text Available The paper outlines the challenges of modelling and assessing spatially complex human-ecosystem interactions, and the need to simultaneously consider rural-urban and rich-poor interactions. The context for exploring these challenges is South Africa...
Directory of Open Access Journals (Sweden)
Guanpeng Dong
Full Text Available This paper develops a methodology for extending multilevel modelling to incorporate spatial interaction effects. The motivation is that classic multilevel models are not specifically spatial. Lower level units may be nested into higher level ones based on a geographical hierarchy (or a membership structure--for example, census zones into regions but the actual locations of the units and the distances between them are not directly considered: what matters is the groupings but not how close together any two units are within those groupings. As a consequence, spatial interaction effects are neither modelled nor measured, confounding group effects (understood as some sort of contextual effect that acts 'top down' upon members of a group with proximity effects (some sort of joint dependency that emerges between neighbours. To deal with this, we incorporate spatial simultaneous autoregressive processes into both the outcome variable and the higher level residuals. To assess the performance of the proposed method and the classic multilevel model, a series of Monte Carlo simulations are conducted. The results show that the proposed method performs well in retrieving the true model parameters whereas the classic multilevel model provides biased and inefficient parameter estimation in the presence of spatial interactions. An important implication of the study is to be cautious of an apparent neighbourhood effect in terms of both its magnitude and statistical significance if spatial interaction effects at a lower level are suspected. Applying the new approach to a two-level land price data set for Beijing, China, we find significant spatial interactions at both the land parcel and district levels.
Probing interaction and spatial curvature in the holographic dark energy model
International Nuclear Information System (INIS)
Li, Miao; Li, Xiao-Dong; Wang, Shuang; Wang, Yi; Zhang, Xin
2009-01-01
In this paper we place observational constraints on the interaction and spatial curvature in the holographic dark energy model. We consider three kinds of phenomenological interactions between holographic dark energy and matter, i.e., the interaction term Q is proportional to the energy densities of dark energy (ρ Λ ), matter (ρ m ), and matter plus dark energy (ρ m +ρ Λ ). For probing the interaction and spatial curvature in the holographic dark energy model, we use the latest observational data including the type Ia supernovae (SNIa) Constitution data, the shift parameter of the cosmic microwave background (CMB) given by the five-year Wilkinson Microwave Anisotropy Probe (WMAP5) observations, and the baryon acoustic oscillation (BAO) measurement from the Sloan Digital Sky Survey (SDSS). Our results show that the interaction and spatial curvature in the holographic dark energy model are both rather small. Besides, it is interesting to find that there exists significant degeneracy between the phenomenological interaction and the spatial curvature in the holographic dark energy model
Spatial interaction models facility location using game theory
D'Amato, Egidio; Pardalos, Panos
2017-01-01
Facility location theory develops the idea of locating one or more facilities by optimizing suitable criteria such as minimizing transportation cost, or capturing the largest market share. The contributions in this book focus an approach to facility location theory through game theoretical tools highlighting situations where a location decision is faced by several decision makers and leading to a game theoretical framework in non-cooperative and cooperative methods. Models and methods regarding the facility location via game theory are explored and applications are illustrated through economics, engineering, and physics. Mathematicians, engineers, economists and computer scientists working in theory, applications and computational aspects of facility location problems using game theory will find this book useful.
Ben Cheikh, Bassem; Bor-Angelier, Catherine; Racoceanu, Daniel
2017-03-01
Breast carcinomas are cancers that arise from the epithelial cells of the breast, which are the cells that line the lobules and the lactiferous ducts. Breast carcinoma is the most common type of breast cancer and can be divided into different subtypes based on architectural features and growth patterns, recognized during a histopathological examination. Tumor microenvironment (TME) is the cellular environment in which tumor cells develop. Being composed of various cell types having different biological roles, TME is recognized as playing an important role in the progression of the disease. The architectural heterogeneity in breast carcinomas and the spatial interactions with TME are, to date, not well understood. Developing a spatial model of tumor architecture and spatial interactions with TME can advance our understanding of tumor heterogeneity. Furthermore, generating histological synthetic datasets can contribute to validating, and comparing analytical methods that are used in digital pathology. In this work, we propose a modeling method that applies to different breast carcinoma subtypes and TME spatial distributions based on mathematical morphology. The model is based on a few morphological parameters that give access to a large spectrum of breast tumor architectures and are able to differentiate in-situ ductal carcinomas (DCIS) and histological subtypes of invasive carcinomas such as ductal (IDC) and lobular carcinoma (ILC). In addition, a part of the parameters of the model controls the spatial distribution of TME relative to the tumor. The validation of the model has been performed by comparing morphological features between real and simulated images.
Spatial structures in a simple model of population dynamics for parasite-host interactions
Energy Technology Data Exchange (ETDEWEB)
Dong, J. J.; Skinner, B.; Breecher, N.; Schmittmann, B.; Zia, R. K. P.
2015-08-01
Spatial patterning can be crucially important for understanding the behavior of interacting populations. Here we investigate a simple model of parasite and host populations in which parasites are random walkers that must come into contact with a host in order to reproduce. We focus on the spatial arrangement of parasites around a single host, and we derive using analytics and numerical simulations the necessary conditions placed on the parasite fecundity and lifetime for the populations long-term survival. We also show that the parasite population can be pushed to extinction by a large drift velocity, but, counterintuitively, a small drift velocity generally increases the parasite population.
Directory of Open Access Journals (Sweden)
Cristina Calcagno
2011-09-01
Full Text Available Arbuscular mycorrhiza (AM is the most wide-spread plant-fungus symbiosis on earth. Investigating this kind of symbiosis is considered one of the most promising ways to develop methods to nurture plants in more natural manners, avoiding the complex chemical productions used nowadays to produce artificial fertilizers. In previous work we used the Calculus of Wrapped Compartments (CWC to investigate different phases of the AM symbiosis. In this paper, we continue this line of research by modelling the colonisation of the plant root cells by the fungal hyphae spreading in the soil. This study requires the description of some spatial interaction. Although CWC has no explicit feature modelling a spatial geometry, the compartment labelling feature can be effectively exploited to define a discrete surface topology outlining the relevant sectors which determine the spatial properties of the system under consideration. Different situations and interesting spatial properties can be modelled and analysed in such a lightweight framework (which has not an explicit notion of geometry with coordinates and spatial metrics, thus exploiting the existing CWC simulation tool.
A spatiotemporal model for the LTE uplink: Spatially interacting tandem queues approach
Gharbieh, Mohammad
2017-07-31
With the proliferation of the Internet-of-things (IoT), there is an undeniable consensus that cellular LTE networks will have to support a dramatically larger number of uplink connections. This is true since most of the devices to be added incur machine-type communications which is dominantly upstream. Can current LTE network withstand this challenge? To answer this question, the joint performance of random access process and the uplink data transmission should be investigated. These two problems have been classically treated in the literature in a disjoint fashion. In this paper, they are jointly analyzed as an inseparable couple. To do that, a tandem queuing model is adopted whereby devices are represented as spatially interacting queues. The interaction between queues is governed by the mutual inter-cell and intra-cell interference. To that end, a joint stochastic geometry and queueing theory model is exploited to study this problem and a spatiotemporal analytical model is developed accordingly. Network stability and scalability are two prime performance criteria for performance assessment. In light of these two criteria, the developed model is poised to offer valuable insights into efficient access and resource allocation strategies.
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.
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)
Quadratic spatial soliton interactions
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
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.
de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål
2017-01-01
The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial
Directory of Open Access Journals (Sweden)
Oliver Schürer
2018-01-01
Full Text Available When using assistive systems, the consideration of individual and cultural meaning is crucial for the utility and acceptance of technology. Orientation, communication and interaction are rooted in perception and therefore always happen in material space. We understand that a major problem lies in the difference between human and technical perception of space. Cultural policies are based on meanings including their spatial situation and their rich relationships. Therefore, we have developed an approach where the different perception systems share a hybrid spatial model that is generated by artificial intelligence—a joint effort by humans and assistive systems. The aim of our project is to create a spatial model of cultural meaning based on interaction between humans and robots. We define the role of humanoid robots as becoming our companions. This calls for technical systems to include still inconceivable human and cultural agendas for the perception of space. In two experiments, we tested a first prototype of the communication module that allows a humanoid to learn cultural meanings through a machine learning system. Interaction is achieved by non-verbal and natural-language communication between humanoids and test persons. This helps us to better understand how a spatial model of cultural meaning can be developed.
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 ...
Measuring directional urban spatial interaction in China: A migration perspective.
Li, Fangzhou; Feng, Zhiming; Li, Peng; You, Zhen
2017-01-01
The study of urban spatial interaction is closely linked to that of economic geography, urban planning, regional development, and so on. Currently, this topic is generating a great deal of interest among researchers who are striving to find accurate ways to measure urban spatial interaction. Classical spatial interaction models lack theoretical guidance and require complicated parameter-adjusting processes. The radiation model, however, as proposed by Simini et al. with rigorous formula derivation, can simulate directional urban spatial interaction. We applied the radiation model in China to simulate the directional migration number among 337 nationwide research units, comprising 4 municipalities and 333 prefecture-level cities. We then analyzed the overall situation in Chinese cities, the interaction intensity hierarchy, and the prime urban agglomerations from the perspective of migration. This was done to ascertain China's urban spatial interaction and regional development from 2000 to 2010 to reveal ground realities.
Spatial computing in interactive architecture
S.O. Dulman (Stefan); M. Krezer; L. Hovestad
2014-01-01
htmlabstractDistributed computing is the theoretical foundation for applications and technologies like interactive architecture, wearable computing, and smart materials. It evolves continuously, following needs rising from scientific developments, novel uses of technology, or simply the curiosity to
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
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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.
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.
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.
Prefrontal-hippocampal interactions for spatial navigation.
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.
Spatial channel interactions in cochlear implants
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
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.
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 Models and Networks of Living Systems
DEFF Research Database (Denmark)
Juul, Jeppe Søgaard
When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number...... variables of the system. However, this approach disregards any spatial structure of the system, which may potentially change the behaviour drastically. An alternative approach is to construct a cellular automaton with nearest neighbour interactions, or even to model the system as a complex network...... with interactions defined by network topology. In this thesis I first describe three different biological models of ageing and cancer, in which spatial structure is important for the system dynamics. I then turn to describe characteristics of ecosystems consisting of three cyclically interacting species...
Thermodynamic Model of Spatial Memory
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.
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 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...
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
Competition in spatial location models
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
Spatial Attention and Audiovisual Interactions in Apparent Motion
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…
Urban strategy: Noise mapping in instrument for interactive spatial planning
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
Spatially explicit modeling in ecology: A review
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.
Using the gravity model to estimate the spatial spread of vector-borne diseases
Barrios, J.M.; Verstraeten, W.W.; Maes, P.; Aerts, J.; Farifteh, J.; Coppin, P.
2012-01-01
The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the
Videogame interventions and spatial ability interactions
Directory of Open Access Journals (Sweden)
Thomas S. Redick
2014-03-01
Full Text Available 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.
Videogame interventions and spatial ability interactions.
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.
Continuous Spatial Process Models for Spatial Extreme Values
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
Loehman, Rachel A.; Keane, Robert E.; Holsinger, Lisa M.; Wu, Zhiwei
2016-01-01
ContextInteractions among disturbances, climate, and vegetation influence landscape patterns and ecosystem processes. Climate changes, exotic invasions, beetle outbreaks, altered fire regimes, and human activities may interact to produce landscapes that appear and function beyond historical analogs.ObjectivesWe used the mechanistic ecosystem-fire process model FireBGCv2 to model interactions of wildland fire, mountain pine beetle (Dendroctonus ponderosae), and white pine blister rust (Cronartium ribicola) under current and future climates, across three diverse study areas.MethodsWe assessed changes in tree basal area as a measure of landscape response over a 300-year simulation period for the Crown of the Continent in north-central Montana, East Fork of the Bitterroot River in western Montana, and Yellowstone Central Plateau in western Wyoming, USA.ResultsInteracting disturbances reduced overall basal area via increased tree mortality of host species. Wildfire decreased basal area more than beetles or rust, and disturbance interactions modeled under future climate significantly altered landscape basal area as compared with no-disturbance and current climate scenarios. Responses varied among landscapes depending on species composition, sensitivity to fire, and pathogen and beetle suitability and susceptibility.ConclusionsUnderstanding disturbance interactions is critical for managing landscapes because forest responses to wildfires, pathogens, and beetle attacks may offset or exacerbate climate influences, with consequences for wildlife, carbon, and biodiversity.
Directory of Open Access Journals (Sweden)
Naamah Bloch
Full Text Available The ability to visualize the ongoing events of a computational model of biology is critical, both in order to see the dynamics of the biological system in action and to enable interaction with the model from which one can observe the resulting behavior. To this end, we have built a new interactive animation tool, SimuLife, for visualizing reactive models of cellular biology. SimuLife is web-based, and is freely accessible at http://simulife.weizmann.ac.il/. We have used SimuLife to animate a model that describes the development of a cancerous tumor, based on the individual components of the system and its environment. This has helped in understanding the dynamics of the tumor and its surrounding blood vessels, and in verifying the behavior, fine-tuning the model accordingly, and learning in which way different factors affect the tumor.
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 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...
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.
Directory of Open Access Journals (Sweden)
K. Blomme
2017-01-01
Full Text Available Numerous publications address the petrogenesis of the partially dolomitized Latemar carbonate platform, Italy. A common factor is interpretation of geochemical data in terms of heating via regional igneous activity that provided kinetically favorable conditions for replacement dolomitization. New field, petrographic, XRD, and geochemical data demonstrate a spatial, temporal, and geochemical link between replacement dolomite and local mafic igneous dikes that pervasively intrude the platform. Dikes are dominated by strongly altered plagioclase and clinopyroxene. Significantly, where ferroan dolomite is present, it borders dikes. We hypothesize that seawater interacted with mafic minerals, causing Fe enrichment in the fluid that subsequently participated in dolomitization. This hypothesis was tested numerically through thermodynamic (MELTS, Arxim-GEM and reactive flow (Arxim-LMA simulations. Results confirm that seawater becomes Fe-enriched during interaction with clinopyroxene (diopside-hedenbergite and plagioclase (anorthite-albite-orthoclase solid solutions. Reaction of modified seawater with limestone causes ferroan and nonferroan replacement dolomitization. Dolomite quantities are strongly influenced by temperature. At 40 to 80°C, ferroan dolomite proportions decrease with increasing temperature, indicating that Latemar dolomitization likely occurred at lower temperatures. This relationship between igneous dikes and dolomitization may have general significance due to the widespread association of carbonates with rifting-related igneous environments.
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....
Spatially varying dispersion to model breakthrough curves.
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.
Continuous Spatial Process Models for Spatial Extreme Values
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.
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.
Model Checking Feature Interactions
DEFF Research Database (Denmark)
Le Guilly, Thibaut; Olsen, Petur; Pedersen, Thomas
2015-01-01
This paper presents an offline approach to analyzing feature interactions in embedded systems. The approach consists of a systematic process to gather the necessary information about system components and their models. The model is first specified in terms of predicates, before being refined to t...... to timed automata. The consistency of the model is verified at different development stages, and the correct linkage between the predicates and their semantic model is checked. The approach is illustrated on a use case from home automation....
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)
A spatial theory for emergent multiple predator-prey interactions in food webs.
Northfield, Tobin D; Barton, Brandon T; Schmitz, Oswald J
2017-09-01
Predator-prey interaction is inherently spatial because animals move through landscapes to search for and consume food resources and to avoid being consumed by other species. The spatial nature of species interactions necessitates integrating spatial processes into food web theory and evaluating how predators combine to impact their prey. Here, we present a spatial modeling approach that examines emergent multiple predator effects on prey within landscapes. The modeling is inspired by the habitat domain concept derived from empirical synthesis of spatial movement and interactions studies. Because these principles are motivated by synthesis of short-term experiments, it remains uncertain whether spatial contingency principles hold in dynamical systems. We address this uncertainty by formulating dynamical systems models, guided by core habitat domain principles, to examine long-term multiple predator-prey spatial dynamics. To describe habitat domains, we use classical niche concepts describing resource utilization distributions, and assume species interactions emerge from the degree of overlap between species. The analytical results generally align with those from empirical synthesis and present a theoretical framework capable of demonstrating multiple predator effects that does not depend on the small spatial or temporal scales typical of mesocosm experiments, and help bridge between empirical experiments and long-term dynamics in natural systems.
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...
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.
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
Dynamic spatial panels : models, methods, and inferences
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
International Nuclear Information System (INIS)
Iachello, F.; Arima, A.
1987-01-01
The book gives an account of some of the properties of the interacting boson model. The model was introduced in 1974 to describe in a unified way the collective properties of nuclei. The book presents the mathematical techniques used to analyse the structure of the model. The mathematical framework of the model is discussed in detail. The book also contains all the formulae that have been developed throughout the years to account for collective properties of nuclei. These formulae can be used by experimentalists to compare their data with the predictions of the model. (U.K.)
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.
Spherical Process Models for Global Spatial Statistics
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
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.
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.
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.
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
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
Energy Technology Data Exchange (ETDEWEB)
Generoso, S.
2004-12-15
Aerosols influence the Earth radiative budget both through their direct (scattering and absorption of solar radiation) and indirect (impacts on cloud microphysics) effects. The anthropogenic perturbation due to aerosol emissions is of the same order of magnitude than the one due to greenhouse gases, but less well known. To improve our knowledge, we need to better know aerosol spatial and temporal distributions. Indeed, aerosol modeling still suffers from large uncertainties in sources and transport, while satellite observations are incomplete (no detection in the presence of clouds, no information on the vertical distribution or on the chemical nature). Moreover, field campaigns are localized in space and time. This study aims to reduce uncertainties in aerosol distributions, developing assimilation of satellite data into a chemical transport model. The basic idea is to combine information obtained from spatial observation (optical thickness) and modeling studies (aerosol types, vertical distribution). In this study, we assimilate data from the POLDER space-borne instrument into the LMDz-INCA model. The results show the advantage of merging information from different sources. In many regions, the method reduces uncertainties on aerosol distribution (reduction of RMS error). An application of the method to the study of aerosol impact on cloud microphysics is shown. (author)
Hierarchical modeling and analysis for spatial data
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
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.
Modeling structural change in spatial system dynamics: A Daisyworld example.
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.
Spatial occupancy models for large data sets
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.
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...
Classifying and comparing spatial models of fire dynamics
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...
Crime Modeling using Spatial Regression Approach
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.
Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data.
Directory of Open Access Journals (Sweden)
Yu Liu
Full Text Available The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.
Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data.
Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong
2014-01-01
The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.
Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data
Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong
2014-01-01
The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips. PMID:24465849
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.
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)
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.
Can spatial statistical river temperature models be transferred between catchments?
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 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
Nonparametric Bayesian models for a spatial covariance.
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.
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.
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.
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.
Spatial Modeling for Resources Framework (SMRF)
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...
The 3-D global spatial data model foundation of the spatial data infrastructure
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...
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...
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
Modeling molecular mixing in a spatially inhomogeneous turbulent flow
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.
Directory of Open Access Journals (Sweden)
Jemyung Lee
2017-11-01
Full Text Available Diversity of regional industry is regarded as a key factor for regional development, as it has a positive relationship with economic stability, which attracts population. This paper focuses on how the spatial imbalance of industrial diversity contributes to the population change caused by inter-regional migration. This paper introduces a spatial interaction model for the Geographic Information System (GIS-based simulation of the spatial interactions to evaluate the demographic attraction force. The proposed model adopts the notions of gravity, entropy, and virtual work. An industrial classification by profit level is introduced and its diversity is quantified with the entropy of information theory. The introduced model is applied to the cases of 207 regions in South Korea. Spatial interactions are simulated with an optimized model and their resultant forces, the demographic attraction forces, are compared with observed net migration for verification. The results show that the evaluated attraction forces from industrial diversity have a very significant, positive, and moderate relationship with net migration, while other conventional factors of industry, population, economy, and the job market do not. This paper concludes that the geographical quality of industrial diversity has positive and significant effects on population change by migration.
Spatial interactions reveal inhibitory cortical networks in human amblyopia.
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.
Control of spatial discretisation in coastal oil spill modelling
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...
A nonlocal spatial model for Lyme disease
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.
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...
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...
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...
Factor Copula Models for Replicated Spatial Data
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
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.
Modeling Spatially Unrestricted Pedestrian Traffic on Footbridges
DEFF Research Database (Denmark)
Zivanovic, Stana; Pavic, Aleksandar; Ingólfsson, Einar Thór
2010-01-01
restricted movement of pedestrians, has kept attracting attention of researchers. However, it is the normal spatially unrestricted pedestrian traffic, and its vertical dynamic loading component, that are most relevant for vibration serviceability checks for most footbridges. Despite the existence of numerous...... design procedures concerned with this loading, the current confidence in its modelling is low due to lack of verification of the models on as-built structures. This is the motivation behind reviewing the existing design procedures for modelling normal pedestrian traffic in this paper and evaluating...
Human Plague Risk: Spatial-Temporal Models
Pinzon, Jorge E.
2010-01-01
This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).
The quantitative modelling of human spatial habitability
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.
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.
Spatial Distribution of Flower Color Induced by Interspecific Sexual Interaction.
Directory of Open Access Journals (Sweden)
Yuma Takahashi
Full Text Available Understanding the mechanisms shaping the spatiotemporal distribution of species has long been a central concern of ecology and evolutionary biology. Contemporary patterns of plant assemblies suggest that sexual interactions among species, i.e., reproductive interference, lead to the exclusive distributions of closely related species that share pollinators. However, the fitness consequences and the initial ecological/evolutionary responses to reproductive interference remain unclear in nature, since reproductive isolation or allopatric distribution has already been achieved in the natural community. In Japan, three species of blue-eyed grasses (Sisyrinchium with incomplete reproductive isolation have recently colonized and occur sympatrically. Two of them are monomorphic with white flowers, whereas the other exhibits heritable color polymorphism (white and purple morphs. Here we investigated the effects of the presence of two monomorphic species on the distribution and reproductive success of color morphs. The frequency and reproductive success of white morphs decreased in area where monomorphic species were abundant, while those of purple morphs did not. The rate of hybridization between species was higher in white morphs than in the purple ones. Resource competition and habitat preference seemed not to contribute to the spatial distribution and reproductive success of two morphs. Our results supported that color-dependent reproductive interference determines the distribution of flower color polymorphism in a habitat, implying ecological sorting promoted by pollinator-mediated reproductive interference. Our study helps us to understand the evolution and spatial structure of flower color in a community.
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.
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)
Impact of spatial organization on a novel auxotrophic interaction among soil microbes.
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.
Towards models of strategic spatial choice behaviour: theory and application issues
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
Testing a Dynamic Field Account of Interactions between Spatial Attention and Spatial Working Memory
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
The quantitative modelling of human spatial habitability
Wise, J. A.
1985-01-01
A model for the quantitative assessment of human spatial habitability is presented in the space station context. The visual aspect assesses how interior spaces appear to the inhabitants. This aspect concerns criteria such as sensed spaciousness and the affective (emotional) connotations of settings' appearances. The kinesthetic aspect evaluates the available space in terms of its suitability to accommodate human movement patterns, as well as the postural and anthrometric changes due to microgravity. Finally, social logic concerns how the volume and geometry of available space either affirms or contravenes established social and organizational expectations for spatial arrangements. Here, the criteria include privacy, status, social power, and proxemics (the uses of space as a medium of social communication).
Modeling mental spatial reasoning about cardinal directions.
Schultheis, Holger; Bertel, Sven; Barkowsky, Thomas
2014-01-01
This article presents research into human mental spatial reasoning with orientation knowledge. In particular, we look at reasoning problems about cardinal directions that possess multiple valid solutions (i.e., are spatially underdetermined), at human preferences for some of these solutions, and at representational and procedural factors that lead to such preferences. The article presents, first, a discussion of existing, related conceptual and computational approaches; second, results of empirical research into the solution preferences that human reasoners actually have; and, third, a novel computational model that relies on a parsimonious and flexible spatio-analogical knowledge representation structure to robustly reproduce the behavior observed with human reasoners. Copyright © 2014 Cognitive Science Society, Inc.
Interactive Dimensioning of Parametric Models
Kelly, T.
2015-06-22
We propose a solution for the dimensioning of parametric and procedural models. Dimensioning has long been a staple of technical drawings, and we present the first solution for interactive dimensioning: A dimension line positioning system that adapts to the view direction, given behavioral properties. After proposing a set of design principles for interactive dimensioning, we describe our solution consisting of the following major components. First, we describe how an author can specify the desired interactive behavior of a dimension line. Second, we propose a novel algorithm to place dimension lines at interactive speeds. Third, we introduce multiple extensions, including chained dimension lines, controls for different parameter types (e.g. discrete choices, angles), and the use of dimension lines for interactive editing. Our results show the use of dimension lines in an interactive parametric modeling environment for architectural, botanical, and mechanical models.
Towards a 3d Spatial Urban Energy Modelling Approach
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
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
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....
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
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.
Spherical Process Models for Global Spatial Statistics
Jeong, Jaehong
2017-11-28
Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture the spatial and temporal behavior of these global data sets. Though the geodesic distance is the most natural metric for measuring distance on the surface of a sphere, mathematical limitations have compelled statisticians to use the chordal distance to compute the covariance matrix in many applications instead, which may cause physically unrealistic distortions. Therefore, covariance functions directly defined on a sphere using the geodesic distance are needed. We discuss the issues that arise when dealing with spherical data sets on a global scale and provide references to recent literature. We review the current approaches to building process models on spheres, including the differential operator, the stochastic partial differential equation, the kernel convolution, and the deformation approaches. We illustrate realizations obtained from Gaussian processes with different covariance structures and the use of isotropic and nonstationary covariance models through deformations and geographical indicators for global surface temperature data. To assess the suitability of each method, we compare their log-likelihood values and prediction scores, and we end with a discussion of related research problems.
Latent spatial models and sampling design for landscape genetics
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.
Models of chromatin spatial organisation in the cell nucleus
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.
Strong interactions - quark models
International Nuclear Information System (INIS)
Goto, M.; Ferreira, P.L.
1979-01-01
The variational method is used for the PSI and upsilon family spectra reproduction from the quark model, through several phenomenological potentials, viz.: linear, linear plus coulomb term and logarithmic. (L.C.) [pt
An Evolutionary Model of Spatial Competition
DEFF Research Database (Denmark)
Knudsen, Thorbjørn; Winter, Sidney G.
This paper sets forth an evolutionary model in which diverse businesses, with diverse offerings, compete in a stylized physical space. When a business firm attempts to expand its activity, so as to profit further from the capabilities it has developed, it necessarily does so in a "new location...... as well in the new environment as they did in the old; the firm may respond with effort to locate appropriate environments or by modification of its routines. Tradeoffs are presented between the complexity of a business model and its replication costs, as well as issues involving response....... Randomly generated firm policies are tested first by a local market environment, and then, if success leads the firm to grow spatially, in a gradually expanding environment. In the initial experiments reported here, we show that the model generates configurations that reflect features of the exogenous...
Some dynamical aspects of interacting quintessence model
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.
Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable
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
Theoretical aspects of spatial-temporal modeling
Matsui, Tomoko
2015-01-01
This book provides a modern introductory tutorial on specialized theoretical aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter provides up-to-date coverage of particle association measures that underpin the theoretical properties of recently developed random set methods in space and time otherwise known as the class of probability hypothesis density framework (PHD filters). The second chapter gives an overview of recent advances in Monte Carlo methods for Bayesian filtering in high-dimensional spaces. In particular, the chapter explains how one may extend classical sequential Monte Carlo methods for filtering and static inference problems to high dimensions and big-data applications. The third chapter presents an overview of generalized families of processes that extend the class of Gaussian process models to heavy-tailed families known as alph...
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....
Nonlinear interaction model of subsonic jet noise.
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.
Models and Inference for Multivariate Spatial Extremes
Vettori, Sabrina
2017-12-07
The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing to the developing research field of Extreme-Value Theory. We initially study the performance of existing parametric and non-parametric estimators of extremal dependence for multivariate maxima. As the dimensionality increases, non-parametric estimators are more flexible than parametric methods but present some loss in efficiency that we quantify under various scenarios. We introduce a statistical tool which imposes the required shape constraints on non-parametric estimators in high dimensions, significantly improving their performance. Furthermore, by embedding the tree-based max-stable nested logistic distribution in the Bayesian framework, we develop a statistical algorithm that identifies the most likely tree structures representing the data\\'s extremal dependence using the reversible jump Monte Carlo Markov Chain method. A mixture of these trees is then used for uncertainty assessment in prediction through Bayesian model averaging. The computational complexity of full likelihood inference is significantly decreased by deriving a recursive formula for the nested logistic model likelihood. The algorithm performance is verified through simulation experiments which also compare different likelihood procedures. Finally, we extend the nested logistic representation to the spatial framework in order to jointly model multivariate variables collected across a spatial region. This situation emerges often in environmental applications but is not often considered in the current literature. Simulation experiments show that the new class of multivariate max-stable processes is able to detect both the cross and inner spatial dependence of a number of extreme variables at a relatively low computational cost, thanks to its Bayesian hierarchical
Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models
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.
Spatially explicit modelling of cholera epidemics
Finger, F.; Bertuzzo, E.; Mari, L.; Knox, A. C.; Gatto, M.; Rinaldo, A.
2013-12-01
Epidemiological models can provide crucial understanding about the dynamics of infectious diseases. Possible applications range from real-time forecasting and allocation of health care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. We apply a spatially explicit model to the cholera epidemic that struck Haiti in October 2010 and is still ongoing. The dynamics of susceptibles as well as symptomatic and asymptomatic infectives are modelled at the scale of local human communities. Dissemination of Vibrio cholerae through hydrological transport and human mobility along the road network is explicitly taken into account, as well as the effect of rainfall as a driver of increasing disease incidence. The model is calibrated using a dataset of reported cholera cases. We further model the long term impact of several types of interventions on the disease dynamics by varying parameters appropriately. Key epidemiological mechanisms and parameters which affect the efficiency of treatments such as antibiotics are identified. Our results lead to conclusions about the influence of different intervention strategies on the overall epidemiological dynamics.
A physically based analytical spatial air temperature and humidity model
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...
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.
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.
Attention Modulates Visual-Tactile Interaction in Spatial Pattern Matching
Göschl, Florian; Engel, Andreas K.; Friese, Uwe
2014-01-01
Factors influencing crossmodal interactions are manifold and operate in a stimulus-driven, bottom-up fashion, as well as via top-down control. Here, we evaluate the interplay of stimulus congruence and attention in a visual-tactile task. To this end, we used a matching paradigm requiring the identification of spatial patterns that were concurrently presented visually on a computer screen and haptically to the fingertips by means of a Braille stimulator. Stimulation in our paradigm was always bimodal with only the allocation of attention being manipulated between conditions. In separate blocks of the experiment, participants were instructed to (a) focus on a single modality to detect a specific target pattern, (b) pay attention to both modalities to detect a specific target pattern, or (c) to explicitly evaluate if the patterns in both modalities were congruent or not. For visual as well as tactile targets, congruent stimulus pairs led to quicker and more accurate detection compared to incongruent stimulation. This congruence facilitation effect was more prominent under divided attention. Incongruent stimulation led to behavioral decrements under divided attention as compared to selectively attending a single sensory channel. Additionally, when participants were asked to evaluate congruence explicitly, congruent stimulation was associated with better performance than incongruent stimulation. Our results extend previous findings from audiovisual studies, showing that stimulus congruence also resulted in behavioral improvements in visuotactile pattern matching. The interplay of stimulus processing and attentional control seems to be organized in a highly flexible fashion, with the integration of signals depending on both bottom-up and top-down factors, rather than occurring in an ‘all-or-nothing’ manner. PMID:25203102
Attention modulates visual-tactile interaction in spatial pattern matching.
Directory of Open Access Journals (Sweden)
Florian Göschl
Full Text Available Factors influencing crossmodal interactions are manifold and operate in a stimulus-driven, bottom-up fashion, as well as via top-down control. Here, we evaluate the interplay of stimulus congruence and attention in a visual-tactile task. To this end, we used a matching paradigm requiring the identification of spatial patterns that were concurrently presented visually on a computer screen and haptically to the fingertips by means of a Braille stimulator. Stimulation in our paradigm was always bimodal with only the allocation of attention being manipulated between conditions. In separate blocks of the experiment, participants were instructed to (a focus on a single modality to detect a specific target pattern, (b pay attention to both modalities to detect a specific target pattern, or (c to explicitly evaluate if the patterns in both modalities were congruent or not. For visual as well as tactile targets, congruent stimulus pairs led to quicker and more accurate detection compared to incongruent stimulation. This congruence facilitation effect was more prominent under divided attention. Incongruent stimulation led to behavioral decrements under divided attention as compared to selectively attending a single sensory channel. Additionally, when participants were asked to evaluate congruence explicitly, congruent stimulation was associated with better performance than incongruent stimulation. Our results extend previous findings from audiovisual studies, showing that stimulus congruence also resulted in behavioral improvements in visuotactile pattern matching. The interplay of stimulus processing and attentional control seems to be organized in a highly flexible fashion, with the integration of signals depending on both bottom-up and top-down factors, rather than occurring in an 'all-or-nothing' manner.
Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.
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
Statistical pairwise interaction model of stock market
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.
Modelling land surface - atmosphere interactions
DEFF Research Database (Denmark)
Rasmussen, Søren Højmark
representation of groundwater in the hydrological model is found to important and this imply resolving the small river valleys. Because, the important shallow groundwater is found in the river valleys. If the model does not represent the shallow groundwater then the area mean surface flux calculation......The study is investigates modelling of land surface – atmosphere interactions in context of fully coupled climatehydrological model. With a special focus of under what condition a fully coupled model system is needed. Regional climate model inter-comparison projects as ENSEMBLES have shown bias...... by the hydrological model is found to be insensitive to model resolution. Furthermore, this study highlights the effect of bias precipitation by regional climate model and it implications for hydrological modelling....
Spatial-structural interaction and strain energy structural optimisation
Hofmeyer, H.; Davila Delgado, J.M.; Borrmann, A.; Geyer, P.; Rafiq, Y.; Wilde, de P.
2012-01-01
A research engine iteratively transforms spatial designs into structural designs and vice versa. Furthermore, spatial and structural designs are optimised. It is suggested to optimise a structural design by evaluating the strain energy of its elements and by then removing, adding, or changing the
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.
Spatial Data Web Services Pricing Model Infrastructure
Ozmus, L.; Erkek, B.; Colak, S.; Cankurt, I.; Bakıcı, S.
2013-08-01
most important law with related NSDI is the establishment of General Directorate of Geographic Information System under the Ministry of Environment and Urbanism. due to; to do or to have do works and activities with related to the establishment of National Geographic Information Systems (NGIS), usage of NGIS and improvements of NGIS. Outputs of these projects are served to not only public administration but also to Turkish society. Today for example, TAKBIS data (cadastre services) are shared more than 50 institutions by Web services, Tusaga-Aktif system has more than 3800 users who are having real-time GPS data correction, Orthophoto WMS services has been started for two years as a charge of free. Today there is great discussion about data pricing among the institutions. Some of them think that the pricing is storage of the data. Some of them think that the pricing is value of data itself. There is no certain rule about pricing. On this paper firstly, pricing of data storage and later on spatial data pricing models in different countries are investigated to improve institutional understanding in Turkey.
The joy of interactive modeling
Donchyts, Gennadii; Baart, Fedor; van Dam, Arthur; Jagers, Bert
2013-04-01
The conventional way of working with hydrodynamical models usually consists of the following steps: 1) define a schematization (e.g., in a graphical user interface, or by editing input files) 2) run model from start to end 3) visualize results 4) repeat any of the previous steps. This cycle commonly takes up from hours to several days. What if we can make this happen instantly? As most of the research done using numerical models is in fact qualitative and exploratory (Oreskes et al., 1994), why not use these models as such? How can we adapt models so that we can edit model input, run and visualize results at the same time? More and more, interactive models become available as online apps, mainly for demonstration and educational purposes. These models often simplify the physics behind flows and run on simplified model geometries, particularly when compared with state-of-the-art scientific simulation packages. Here we show how the aforementioned conventional standalone models ("static, run once") can be transformed into interactive models. The basic concepts behind turning existing (conventional) model engines into interactive engines are the following. The engine does not run the model from start to end, but is always available in memory, and can be fed by new boundary conditions, or state changes at any time. The model can be run continuously, per step, or up to a specified time. The Hollywood principle dictates how the model engine is instructed from 'outside', instead of the model engine taking all necessary actions on its own initiative. The underlying techniques that facilitate these concepts are introspection of the computation engine, which exposes its state variables, and control functions, e.g. for time stepping, via a standardized interface, such as BMI (Peckam et. al., 2012). In this work we have used a shallow water flow model engine D-Flow Flexible Mesh. The model was converted from executable to a library, and coupled to the graphical modelling
Interactive differential equations modeling program
International Nuclear Information System (INIS)
Rust, B.W.; Mankin, J.B.
1976-01-01
Due to the recent emphasis on mathematical modeling, many ecologists are using mathematics and computers more than ever, and engineers, mathematicians and physical scientists are now included in ecological projects. However, the individual ecologist, with intuitive knowledge of the system, still requires the means to critically examine and adjust system models. An interactive program was developed with the primary goal of allowing an ecologist with minimal experience in either mathematics or computers to develop a system model. It has also been used successfully by systems ecologists, engineers, and mathematicians. This program was written in FORTRAN for the DEC PDP-10, a remote terminal system at Oak Ridge National Laboratory. However, with relatively minor modifications, it can be implemented on any remote terminal system with a FORTRAN IV compiler, or equivalent. This program may be used to simulate any phenomenon which can be described as a system of ordinary differential equations. The program allows the user to interactively change system parameters and/or initial conditions, to interactively select a set of variables to be plotted, and to model discontinuities in the state variables and/or their derivatives. One of the most useful features to the non-computer specialist is the ability to interactively address the system parameters by name and to interactively adjust their values between simulations. These and other features are described in greater detail
Panchromatic SED modelling of spatially resolved galaxies
Smith, Daniel J. B.; Hayward, Christopher C.
2018-05-01
We test the efficacy of the energy-balance spectral energy distribution (SED) fitting code MAGPHYS for recovering the spatially resolved properties of a simulated isolated disc galaxy, for which it was not designed. We perform 226 950 MAGPHYS SED fits to regions between 0.2 and 25 kpc in size across the galaxy's disc, viewed from three different sight-lines, to probe how well MAGPHYS can recover key galaxy properties based on 21 bands of UV-far-infrared model photometry. MAGPHYS yields statistically acceptable fits to >99 per cent of the pixels within the r-band effective radius and between 59 and 77 percent of pixels within 20 kpc of the nucleus. MAGPHYS is able to recover the distribution of stellar mass, star formation rate (SFR), specific SFR, dust luminosity, dust mass, and V-band attenuation reasonably well, especially when the pixel size is ≳ 1 kpc, whereas non-standard outputs (stellar metallicity and mass-weighted age) are recovered less well. Accurate recovery is more challenging in the smallest sub-regions of the disc (pixel scale ≲ 1 kpc), where the energy balance criterion becomes increasingly incorrect. Estimating integrated galaxy properties by summing the recovered pixel values, the true integrated values of all parameters considered except metallicity and age are well recovered at all spatial resolutions, ranging from 0.2 kpc to integrating across the disc, albeit with some evidence for resolution-dependent biases. These results must be considered when attempting to analyse the structure of real galaxies with actual observational data, for which the `ground truth' is unknown.
Interacting boson model with surface delta interaction between nucleons
International Nuclear Information System (INIS)
Druce, C.; Moszkowski, S.A.
1984-01-01
The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. The authors have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson proton-boson interaction for the case of degenerate orbits
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.
Introduction to interacting boson model
International Nuclear Information System (INIS)
Goutte, D.
1986-01-01
A very simple presentation of the interacting boson model is first given. The two computerized models which are presented allow, with few parameters, to reproduce an impressive quantity of data characterizing the deformed nuclei. Their excitation spectra, the reduced transition probabilities, the quadrupolar moments, the two nucleon transfer experiment results, ... Then a specific application of the model is given: radial extension reproduction of nuclear functions. It is shown first how the electron inelastic scattering allows to measure observables related to these radial functions, the transition charge densities, then, on some examples, how the model allows to reproduce them [fr
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...
Spatial Econometric data analysis: moving beyond traditional models
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
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.
FIND: difFerential chromatin INteractions Detection using a spatial Poisson process.
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.
Model for Atmospheric Propagation of Spatially Combined Laser Beams
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
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.
A Spatial Model of the Mere Exposure Effect.
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.…
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
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
Interactions of collimation, sampling and filtering on spect spatial resolution
International Nuclear Information System (INIS)
Tsui, B.M.W.; Jaszczak, R.J.
1984-01-01
The major factors which affect the spatial resolution of single-photon emission computer tomography (SPECT) include collimation, sampling and filtering. A theoretical formulation is presented to describe the relationship between these factors and their effects on the projection data. Numerical calculations were made using commercially available SPECT systems and imaging parameters. The results provide an important guide for proper selection of the collimator-detector design, the imaging and the reconstruction parameters to avoid unnecessary spatial resolution degradation and aliasing artifacts in the reconstructed image. In addition, the understanding will help in the fair evaluation of different SPECT systems under specific imaging conditions
Spatial data modelling and maximum entropy theory
Czech Academy of Sciences Publication Activity Database
Klimešová, Dana; Ocelíková, E.
2005-01-01
Roč. 51, č. 2 (2005), s. 80-83 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : spatial data classification * distribution function * error distribution Subject RIV: BD - Theory of Information
Shape Displays: Spatial Interaction with Dynamic Physical Form.
Leithinger, Daniel; Follmer, Sean; Olwal, Alex; Ishii, Hiroshi
2015-01-01
Shape displays are an emerging class of devices that emphasize actuation to enable rich physical interaction, complementing concepts in virtual and augmented reality. The ability to render form introduces new opportunities to touch, grasp, and manipulate dynamic physical content and tangible objects, in both nearby and remote environments. This article presents novel hardware, interaction techniques, and applications, which point to the potential for extending the ways that we traditionally interact with the physical world, empowered by digital computation.
Spatial interactions among ecosystem services in an urbanizing agricultural watershed.
Qiu, Jiangxiao; Turner, Monica G
2013-07-16
Understanding spatial distributions, synergies, and tradeoffs of multiple ecosystem services (benefits people derive from ecosystems) remains challenging. We analyzed the supply of 10 ecosystem services for 2006 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) Where are areas of high and low supply of individual ecosystem services, and are these areas spatially concordant across services? (ii) Where on the landscape are the strongest tradeoffs and synergies among ecosystem services located? (iii) For ecosystem service pairs that experience tradeoffs, what distinguishes locations that are "win-win" exceptions from other locations? Spatial patterns of high supply for multiple ecosystem services often were not coincident; locations where six or more services were produced at high levels (upper 20th percentile) occupied only 3.3% of the landscape. Most relationships among ecosystem services were synergies, but tradeoffs occurred between crop production and water quality. Ecosystem services related to water quality and quantity separated into three different groups, indicating that management to sustain freshwater services along with other ecosystem services will not be simple. Despite overall tradeoffs between crop production and water quality, some locations were positive for both, suggesting that tradeoffs are not inevitable everywhere and might be ameliorated in some locations. Overall, we found that different areas of the landscape supplied different suites of ecosystem services, and their lack of spatial concordance suggests the importance of managing over large areas to sustain multiple ecosystem services.
Stochastic hyperfine interactions modeling library
Zacate, Matthew O.; Evenson, William E.
2011-04-01
The stochastic hyperfine interactions modeling library (SHIML) provides a set of routines to assist in the development and application of stochastic models of hyperfine interactions. The library provides routines written in the C programming language that (1) read a text description of a model for fluctuating hyperfine fields, (2) set up the Blume matrix, upon which the evolution operator of the system depends, and (3) find the eigenvalues and eigenvectors of the Blume matrix so that theoretical spectra of experimental techniques that measure hyperfine interactions can be calculated. The optimized vector and matrix operations of the BLAS and LAPACK libraries are utilized; however, there was a need to develop supplementary code to find an orthonormal set of (left and right) eigenvectors of complex, non-Hermitian matrices. In addition, example code is provided to illustrate the use of SHIML to generate perturbed angular correlation spectra for the special case of polycrystalline samples when anisotropy terms of higher order than A can be neglected. Program summaryProgram title: SHIML Catalogue identifier: AEIF_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIF_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPL 3 No. of lines in distributed program, including test data, etc.: 8224 No. of bytes in distributed program, including test data, etc.: 312 348 Distribution format: tar.gz Programming language: C Computer: Any Operating system: LINUX, OS X RAM: Varies Classification: 7.4 External routines: TAPP [1], BLAS [2], a C-interface to BLAS [3], and LAPACK [4] Nature of problem: In condensed matter systems, hyperfine methods such as nuclear magnetic resonance (NMR), Mössbauer effect (ME), muon spin rotation (μSR), and perturbed angular correlation spectroscopy (PAC) measure electronic and magnetic structure within Angstroms of nuclear probes through the hyperfine interaction. When
Drug-model membrane interactions
International Nuclear Information System (INIS)
Deniz, Usha K.
1994-01-01
In the present day world, drugs play a very important role in medicine and it is necessary to understand their mode of action at the molecular level, in order to optimise their use. Studies of drug-biomembrane interactions are essential for gaining such as understanding. However, it would be prohibitively difficult to carry out such studies, since biomembranes are highly complex systems. Hence, model membranes (made up of these lipids which are important components of biomembranes) of varying degrees of complexity are used to investigate drug-membrane interactions. Bio- as well as model-membranes undergo a chain melting transition when heated, the chains being in a disordered state above the transition point, T CM . This transition is of physiological importance since biomembranes select their components such that T CM is less than the ambient temperature but not very much so, so that membrane flexibility is ensured and porosity, avoided. The influence of drugs on the transition gives valuable clues about various parameters such as the location of the drug in the membrane. Deep insights into drug-membrane interactions are obtained by observing the effect of drugs on membrane structure and the mobilities of the various groups in lipids, near T CM . Investigation of such changes have been carried out with several drugs, using techniques such as DSC, XRD and NMR. The results indicate that the drug-membrane interaction not only depends on the nature of drug and lipids but also on the form of the model membrane - stacked bilayer or vesicles. The light that these results shed on the nature of drug-membrane interactions is discussed. (author). 13 refs., 13 figs., 1 tab
Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.
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.
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
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 and functional modeling of carnivore and insectivore molariform teeth.
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.
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.
Spatial structure of single and interacting Mn acceptors in GaAs
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.
Modeling spatial processes with unknown extremal dependence class
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
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...
Bringing VR and spatial 3D interaction to the masses through video games.
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.
Visualisation and research strategy for computational spatial and structural design interaction
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
Modeling the spatial reach of the LFP
DEFF Research Database (Denmark)
Lindén, Henrik; Tetzlaff, Tom; Potjans, Tobias C
2011-01-01
The local field potential (LFP) reflects activity of many neurons in the vicinity of the recording electrode and is therefore useful for studying local network dynamics. Much of the nature of the LFP is, however, still unknown. There are, for instance, contradicting reports on the spatial extent ...
Spatial modeling of potential woody biomass flow
Woodam Chung; Nathaniel Anderson
2012-01-01
The flow of woody biomass to end users is determined by economic factors, especially the amount available across a landscape and delivery costs of bioenergy facilities. The objective of this study develop methodology to quantify landscape-level stocks and potential biomass flows using the currently available spatial database road network analysis tool. We applied this...
Modeling fixation locations using spatial point processes.
Barthelmé, Simon; Trukenbrod, Hans; Engbert, Ralf; Wichmann, Felix
2013-10-01
Whenever eye movements are measured, a central part of the analysis has to do with where subjects fixate and why they fixated where they fixated. To a first approximation, a set of fixations can be viewed as a set of points in space; this implies that fixations are spatial data and that the analysis of fixation locations can be beneficially thought of as a spatial statistics problem. We argue that thinking of fixation locations as arising from point processes is a very fruitful framework for eye-movement data, helping turn qualitative questions into quantitative ones. We provide a tutorial introduction to some of the main ideas of the field of spatial statistics, focusing especially on spatial Poisson processes. We show how point processes help relate image properties to fixation locations. In particular we show how point processes naturally express the idea that image features' predictability for fixations may vary from one image to another. We review other methods of analysis used in the literature, show how they relate to point process theory, and argue that thinking in terms of point processes substantially extends the range of analyses that can be performed and clarify their interpretation.
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...
Thematic and spatial resolutions affect model-based predictions of tree species distribution.
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.
. Redundancy and blocking in the spatial domain: A connectionist model
Directory of Open Access Journals (Sweden)
I. P. L. Mc Laren
2002-01-01
Full Text Available How can the observations of spatial blocking (Rodrigo, Chamizo, McLaren & Mackintosh, 1997 and cue redundancy (OKeefe and Conway, 1978 be reconciled within the framework provided by an error-correcting, connectionist account of spatial navigation? I show that an implementation of McLarens (1995 better beta model can serve this purpose, and examine some of the implications for spatial learning and memory.
Representing climate, disturbance, and vegetation interactions in landscape models
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...
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.
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.
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.
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.
Extinction threshold of a population in spatial and stochastic model
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 ...
A spatial Mankiw-Romer-Weil model: Theory and evidence
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 Modeling of Deforestation in FMU of Poigar, North Sulawesi
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...
A model relating Eulerian spatial and temporal velocity correlations
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.
Nanoscale tissue engineering: spatial control over cell-materials interactions
Wheeldon, Ian; Farhadi, Arash; Bick, Alexander G.; Jabbari, Esmaiel; Khademhosseini, Ali
2011-01-01
Cells interact with the surrounding environment by making tens to hundreds of thousands of nanoscale interactions with extracellular signals and features. The goal of nanoscale tissue engineering is to harness the interactions through nanoscale biomaterials engineering in order to study and direct cellular behaviors. Here, we review the nanoscale tissue engineering technologies for both two- and three-dimensional studies (2- and 3D), and provide a holistic overview of the field. Techniques that can control the average spacing and clustering of cell adhesion ligands are well established and have been highly successful in describing cell adhesion and migration in 2D. Extension of these engineering tools to 3D biomaterials has created many new hydrogel and nanofiber scaffolds technologies that are being used to design in vitro experiments with more physiologically relevant conditions. Researchers are beginning to study complex cell functions in 3D, however, there is a need for biomaterials systems that provide fine control over the nanoscale presentation of bioactive ligands in 3D. Additionally, there is a need for 2- and 3D techniques that can control the nanoscale presentation of multiple bioactive ligands and the temporal changes in cellular microenvironment. PMID:21451238
Nanoscale tissue engineering: spatial control over cell-materials interactions
International Nuclear Information System (INIS)
Wheeldon, Ian; Farhadi, Arash; Bick, Alexander G; Khademhosseini, Ali; Jabbari, Esmaiel
2011-01-01
Cells interact with the surrounding environment by making tens to hundreds of thousands of nanoscale interactions with extracellular signals and features. The goal of nanoscale tissue engineering is to harness these interactions through nanoscale biomaterials engineering in order to study and direct cellular behavior. Here, we review two- and three-dimensional (2- and 3D) nanoscale tissue engineering technologies, and provide a holistic overview of the field. Techniques that can control the average spacing and clustering of cell adhesion ligands are well established and have been highly successful in describing cell adhesion and migration in 2D. Extension of these engineering tools to 3D biomaterials has created many new hydrogel and nanofiber scaffold technologies that are being used to design in vitro experiments with more physiologically relevant conditions. Researchers are beginning to study complex cell functions in 3D. However, there is a need for biomaterials systems that provide fine control over the nanoscale presentation of bioactive ligands in 3D. Additionally, there is a need for 2- and 3D techniques that can control the nanoscale presentation of multiple bioactive ligands and that can control the temporal changes in the cellular microenvironment. (topical review)
Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.
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.
Stochastic Spatial Models in Ecology: A Statistical Physics Approach
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.
Updates to the Demographic and Spatial Allocation Models to ...
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.
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....
Spatial modeling of households' knowledge about arsenic pollution in Bangladesh.
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.
Verbal-spatial and visuospatial coding of power-space interactions.
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.
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.
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.
Bayesian disease mapping: hierarchical modeling in spatial epidemiology
National Research Council Canada - National Science Library
Lawson, Andrew
2013-01-01
Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas...
Bayesian disease mapping: hierarchical modeling in spatial epidemiology
National Research Council Canada - National Science Library
Lawson, Andrew
2013-01-01
.... Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications...
Measurement error models with interactions
Midthune, Douglas; Carroll, Raymond J.; Freedman, Laurence S.; Kipnis, Victor
2016-01-01
An important use of measurement error models is to correct regression models for bias due to covariate measurement error. Most measurement error models assume that the observed error-prone covariate (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$W$\\end{document}) is a linear function of the unobserved true covariate (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$X$\\end{document}) plus other covariates (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$Z$\\end{document}) in the regression model. In this paper, we consider models for \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$W$\\end{document} that include interactions between \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$X$\\end{document} and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$Z$\\end{document}. We derive the conditional distribution of
Testing spatial heterogeneity with stock assessment models
DEFF Research Database (Denmark)
Jardim, Ernesto; Eero, Margit; Silva, Alexandra
2018-01-01
sub-populations and applied to two case studies, North Sea cod (Gadus morua) and Northeast Atlantic sardine (Sardina pilchardus). Considering that the biological components of a population can be partitioned into discrete spatial units, we extended this idea into a property of additivity of sub......, the better the diffusion process will be detected. On the other hand it showed that weak to moderate diffusion processes are not easy to identify and large differences between sub-populations productivities may be confounded with weak diffusion processes. The application to North Sea cod and Atlantic sardine...... exemplified how much insight can be gained. In both cases the results obtained were sufficiently robust to support the regional analysis....
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.
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....
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.
Spatial Epidemic Modelling in Social Networks
Simoes, Joana Margarida
2005-06-01
The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.
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.
How cognitive heuristics can explain social interactions in spatial movement.
Seitz, Michael J; Bode, Nikolai W F; Köster, Gerta
2016-08-01
The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as 'stop if another step would lead to a collision' or 'follow the person in front'. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour. © 2016 The Author(s).
Spatial modelling with R-INLA: A review
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
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.
Spatial patterns and temporal dynamics of global scale climate-groundwater interactions
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.
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.
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
A Structural Equation Approach to Models with Spatial Dependence
Oud, Johan H. L.; Folmer, Henk
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it
A structural equation approach to models with spatial dependence
Oud, J.H.L.; Folmer, H.
2008-01-01
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it
A Structural Equation Approach to Models with Spatial Dependence
Oud, J.H.L.; Folmer, H.
2008-01-01
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it
International Nuclear Information System (INIS)
Druce, C.H.; Moszkowski, S.A.
1986-01-01
The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. We have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson-proton-boson interaction for the case of degenerate orbits. A connection is made between these coefficients and the parameters of the interaction boson model Hamiltonian. A link between the latter parameters and the single boson energies is suggested
Energy Technology Data Exchange (ETDEWEB)
Druce, C.H.; Moszkowski, S.A.
1986-01-01
The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. We have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson-proton-boson interaction for the case of degenerate orbits. A connection is made between these coefficients and the parameters of the interaction boson model Hamiltonian. A link between the latter parameters and the single boson energies is suggested.
Spatial Modeling Tools for Cell Biology
National Research Council Canada - National Science Library
Przekwas, Andrzej; Friend, Tom; Teixeira, Rodrigo; Chen, Z. J; Wilkerson, Patrick
2006-01-01
.... Scientific potentials and military relevance of computational biology and bioinformatics have inspired DARPA/IPTO's visionary BioSPICE project to develop computational framework and modeling tools for cell biology...
Bayesian spatial transformation models with applications in neuroimaging data.
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.
Crash rates analysis in China using a spatial panel model
Directory of Open Access Journals (Sweden)
Wonmongo Lacina Soro
2017-10-01
Full Text Available The consideration of spatial externalities in traffic safety analysis is of paramount importance for the success of road safety policies. Yet, the quasi-totality of spatial dependence studies on crash rates is performed within the framework of single-equation spatial cross-sectional studies. The present study extends the spatial cross-sectional scheme to a spatial fixed-effects panel model estimated using the maximum likelihood method. The spatial units are the 31 administrative regions of mainland China over the period 2004–2013. The presence of neighborhood effects is evidenced through the Moran's I statistic. Consistent with previous studies, the analysis reveals that omitting the spatial effects in traffic safety analysis is likely to bias the estimation results. The spatial and error lags are all positive and statistically significant suggesting similarities of crash rates pattern in neighboring regions. Some other explanatory variables, such as freight traffic, the length of paved roads and the populations of age 65 and above are related to higher rates while the opposite trend is observed for the Gross Regional Product, the urban unemployment rate and passenger traffic.
Linear multivariate evaluation models for spatial perception of soundscape.
Deng, Zhiyong; Kang, Jian; Wang, Daiwei; Liu, Aili; Kang, Joe Zhengyu
2015-11-01
Soundscape is a sound environment that emphasizes the awareness of auditory perception and social or cultural understandings. The case of spatial perception is significant to soundscape. However, previous studies on the auditory spatial perception of the soundscape environment have been limited. Based on 21 native binaural-recorded soundscape samples and a set of auditory experiments for subjective spatial perception (SSP), a study of the analysis among semantic parameters, the inter-aural-cross-correlation coefficient (IACC), A-weighted-equal sound-pressure-level (L(eq)), dynamic (D), and SSP is introduced to verify the independent effect of each parameter and to re-determine some of their possible relationships. The results show that the more noisiness the audience perceived, the worse spatial awareness they received, while the closer and more directional the sound source image variations, dynamics, and numbers of sound sources in the soundscape are, the better the spatial awareness would be. Thus, the sensations of roughness, sound intensity, transient dynamic, and the values of Leq and IACC have a suitable range for better spatial perception. A better spatial awareness seems to promote the preference slightly for the audience. Finally, setting SSPs as functions of the semantic parameters and Leq-D-IACC, two linear multivariate evaluation models of subjective spatial perception are proposed.
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.
Empirical spatial econometric modelling of small scale neighbourhood
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.
Spatial memory tasks in rodents: what do they model?
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.
Unleashing spatially distributed ecohydrology modeling using Big Data tools
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
Modelling the effects of spatial variability on radionuclide migration
International Nuclear Information System (INIS)
1998-01-01
The NEA workshop reflect the present status in national waste management program, specifically in spatial variability and performance assessment of geologic disposal sites for deed repository system the four sessions were: Spatial Variability: Its Definition and Significance to Performance Assessment and Site Characterisation; Experience with the Modelling of Radionuclide Migration in the Presence of Spatial Variability in Various Geological Environments; New Areas for Investigation: Two Personal Views; What is Wanted and What is Feasible: Views and Future Plans in Selected Waste Management Organisations. The 26 papers presented on the four oral sessions and on the poster session have been abstracted and indexed individually for the INIS database. (R.P.)
Spatial distance in a technology gap model
Verspagen, B.; Caniëls, M.C.J.
1999-01-01
This paper analyses the effect of locally bounded knowledge spillovers on regional differences in growth. A model will be developed that allows spillovers to take place across regions. Certain conditions determine the amount of spillovers a region receives. By use of simulations (with randomised
Properties of spatial Cox process models
DEFF Research Database (Denmark)
Møller, Jesper
Probabilistic properties of Cox processes of relevance for statistical modelling and inference are studied. Particularly, we study the most important classes of Cox processes, including log Gaussian Cox processes, shot noise Cox processes, and permanent Cox processes. We consider moment properties...... and point process operations such as thinning, displacements, and superpositioning. We also discuss how to simulate specific Cox processes....
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
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
A Spatial Model of Erosion and Sedimentation on Continental Margins
National Research Council Canada - National Science Library
Pratson, Lincoln
1999-01-01
.... A computer model that simulates the evolution of continental slope morphology under the interaction of sedimentation, slope failure, and sediment flow erosion has been constructed and validated...
A random spatial network model based on elementary postulates
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.
Spatial-temporal modeling of malware propagation in networks.
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.
Spatial analysis and modelling based on activities
CSIR Research Space (South Africa)
Conradie, Dirk CU
2010-01-01
Full Text Available (deliberative attitudes) (Pokahr, 2005). The BDI model does not cover emotional and other ‘higher’ human attitudes. KRONOS is a generic Computational Building Simulation (CBS) tool that was developed over the past three years to work on advanced... featured, stable, mature and platform independent with an easy to use C/C++ Application Program Interface (API). It has advanced joint types and integrated collision detection with friction. ODE is particularly useful for simulating vehicles, objects...
Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D
2017-09-11
Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.
Uncertainty in a spatial evacuation model
Mohd Ibrahim, Azhar; Venkat, Ibrahim; Wilde, Philippe De
2017-08-01
Pedestrian movements in crowd motion can be perceived in terms of agents who basically exhibit patient or impatient behavior. We model crowd motion subject to exit congestion under uncertainty conditions in a continuous space and compare the proposed model via simulations with the classical social force model. During a typical emergency evacuation scenario, agents might not be able to perceive with certainty the strategies of opponents (other agents) owing to the dynamic changes entailed by the neighborhood of opponents. In such uncertain scenarios, agents will try to update their strategy based on their own rules or their intrinsic behavior. We study risk seeking, risk averse and risk neutral behaviors of such agents via certain game theory notions. We found that risk averse agents tend to achieve faster evacuation time whenever the time delay in conflicts appears to be longer. The results of our simulations also comply with previous work and conform to the fact that evacuation time of agents becomes shorter once mutual cooperation among agents is achieved. Although the impatient strategy appears to be the rational strategy that might lead to faster evacuation times, our study scientifically shows that the more the agents are impatient, the slower is the egress time.
The stock-flow model of spatial data infrastructure development refined by fuzzy logic.
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.
An analytical model for interactive failures
International Nuclear Information System (INIS)
Sun Yong; Ma Lin; Mathew, Joseph; Zhang Sheng
2006-01-01
In some systems, failures of certain components can interact with each other, and accelerate the failure rates of these components. These failures are defined as interactive failure. Interactive failure is a prevalent cause of failure associated with complex systems, particularly in mechanical systems. The failure risk of an asset will be underestimated if the interactive effect is ignored. When failure risk is assessed, interactive failures of an asset need to be considered. However, the literature is silent on previous research work in this field. This paper introduces the concepts of interactive failure, develops an analytical model to analyse this type of failure quantitatively, and verifies the model using case studies and experiments
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.
Modeling individuals’ cognitive and affective responses in spatial learning behavior
Han, Q.; Arentze, T.A.; Timmermans, H.J.P.; Janssens, D.; Wets, G.; Lo, H.P.; Leung, Stephen C.H.; Tan, Susanna M.L.
2008-01-01
Activity-based analysis has slowly shifted gear from analysis of daily activity patterns to analysis and modeling of dynamic activity-travel patterns. In this paper, we describe a dynamic model that is concerned with simulating cognitive and affective responses in spatial learning behavior for a
Modelling firm heterogeneity with spatial 'trends'
Energy Technology Data Exchange (ETDEWEB)
Sarmiento, C. [North Dakota State University, Fargo, ND (United States). Dept. of Agricultural Business & Applied Economics
2004-04-15
The hypothesis underlying this article is that firm heterogeneity can be captured by spatial characteristics of the firm (similar to the inclusion of a time trend in time series models). The hypothesis is examined in the context of modelling electric generation by coal powered plants in the presence of firm heterogeneity.
Appropriatie spatial scales to achieve model output uncertainty goals
Booij, Martijn J.; Melching, Charles S.; Chen, Xiaohong; Chen, Yongqin; Xia, Jun; Zhang, Hailun
2008-01-01
Appropriate spatial scales of hydrological variables were determined using an existing methodology based on a balance in uncertainties from model inputs and parameters extended with a criterion based on a maximum model output uncertainty. The original methodology uses different relationships between
Spatially adaptive mixture modeling for analysis of FMRI time series.
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
Modeling object pursuit for 3D interactive tasks in virtual reality
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
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.
A Statistical Toolbox For Mining And Modeling Spatial Data
Directory of Open Access Journals (Sweden)
D’Aubigny Gérard
2016-12-01
Full Text Available Most data mining projects in spatial economics start with an evaluation of a set of attribute variables on a sample of spatial entities, looking for the existence and strength of spatial autocorrelation, based on the Moran’s and the Geary’s coefficients, the adequacy of which is rarely challenged, despite the fact that when reporting on their properties, many users seem likely to make mistakes and to foster confusion. My paper begins by a critical appraisal of the classical definition and rational of these indices. I argue that while intuitively founded, they are plagued by an inconsistency in their conception. Then, I propose a principled small change leading to corrected spatial autocorrelation coefficients, which strongly simplifies their relationship, and opens the way to an augmented toolbox of statistical methods of dimension reduction and data visualization, also useful for modeling purposes. A second section presents a formal framework, adapted from recent work in statistical learning, which gives theoretical support to our definition of corrected spatial autocorrelation coefficients. More specifically, the multivariate data mining methods presented here, are easily implementable on the existing (free software, yield methods useful to exploit the proposed corrections in spatial data analysis practice, and, from a mathematical point of view, whose asymptotic behavior, already studied in a series of papers by Belkin & Niyogi, suggests that they own qualities of robustness and a limited sensitivity to the Modifiable Areal Unit Problem (MAUP, valuable in exploratory spatial data analysis.
Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models
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.
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.
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
Interaction Modeling at PROS Research Center
Panach , José ,; Aquino , Nathalie; PASTOR , Oscar
2011-01-01
Part 1: Long and Short Papers; International audience; This paper describes how the PROS Research Center deals with interaction in the context of a model-driven approach for the development of information systems. Interaction is specified in a conceptual model together with the structure and behavior of the system. Major achievements and current research challenges of PROS in the field of interaction modeling are presented.
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)
A physically based analytical spatial air temperature and humidity model
Yang, Yang; Endreny, Theodore A.; Nowak, David J.
2013-09-01
Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat storage based on semiempirical functions and generates spatially distributed estimates based on inputs of topography, land cover, and the weather data measured at a reference site. The model assumes that for all grids under the same mesoscale climate, grid air temperature and humidity are modified by local variation in absorbed solar radiation and the partitioning of sensible and latent heat. The model uses a reference grid site for time series meteorological data and the air temperature and humidity of any other grid can be obtained by solving the heat flux network equations. PASATH was coupled with the USDA iTree-Hydro water balance model to obtain evapotranspiration terms and run from 20 to 29 August 2010 at a 360 m by 360 m grid scale and hourly time step across a 285 km2 watershed including the urban area of Syracuse, NY. PASATH predictions were tested at nine urban weather stations representing variability in urban topography and land cover. The PASATH model predictive efficiency R2 ranged from 0.81 to 0.99 for air temperature and 0.77 to 0.97 for dew point temperature. PASATH is expected to have broad applications on environmental and ecological models.
Toward micro-scale spatial modeling of gentrification
O'Sullivan, David
A simple preliminary model of gentrification is presented. The model is based on an irregular cellular automaton architecture drawing on the concept of proximal space, which is well suited to the spatial externalities present in housing markets at the local scale. The rent gap hypothesis on which the model's cell transition rules are based is discussed. The model's transition rules are described in detail. Practical difficulties in configuring and initializing the model are described and its typical behavior reported. Prospects for further development of the model are discussed. The current model structure, while inadequate, is well suited to further elaboration and the incorporation of other interesting and relevant effects.
Gender-specific spatial interactions on Dutch regional labour markets and the gender employment gap
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
Bistability, Spatial Interaction, and the Distribution of Tropical Forests and Savannas
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
Interactive Dimensioning of Parametric Models
Kelly, T.; Wonka, Peter; Mueller, P.
2015-01-01
that adapts to the view direction, given behavioral properties. After proposing a set of design principles for interactive dimensioning, we describe our solution consisting of the following major components. First, we describe how an author can specify
Jiang, Chong; Zhang, Haiyan; Zhang, Zhidong
2018-02-01
Human demands for natural resources have significantly changed the natural landscape and induced ecological degradation and associated ecosystem services. An understanding of the patterns, interactions, and drivers of ecosystem services is essential for the ecosystem management and guiding targeted land use policy-making. The Losses Plateau (LP) provides ecosystem services including the carbon sequestration and soil retention, and exerts tremendous impacts on the midstream and downstream of the Yellow River. Three dominant ecosystem services between 2000 and 2012 within the LP were presented based on multiple source datasets and biophysical models. In addition, paired ecosystem services interactions were quantified using the correlation analysis and constraint line approach. The main conclusions are as follows. It was observed that the warming and wetting climate and ecological program jointly promoted the vegetation growth and carbon sequestration. The increasing precipitation throughout 2000-2012 was related to the soil retention and hydrological regulation fluctuations. The vegetation restoration played a positive role in the soil retention enhancement, thus substantially reduced water and sediment yields. The relationships between ecosystem services were not only correlations (tradeoffs or synergies), but rather constraint effects. The constraint effects between the three paired ecosystem services could be classified as the negative convex (carbon sequestration vs. hydrological regulation) and hump-shaped (soil retention vs. carbon sequestration and soil retention vs. hydrological regulation), and the coefficients of determination for the entire LP were 0.78, 0.84, and 0.65, respectively. In the LP, the rainfall (water availability) was the key constraint factor that affected the relationships between the paired ecosystem services. The spatially explicit mapping of ecosystem services and interaction analyses utilizing constraint line approach enriched the
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.
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.
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.
Hydrological model uncertainty due to spatial evapotranspiration estimation methods
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.
Spatial capture-recapture models for search-encounter data
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.
Analysing earthquake slip models with the spatial prediction comparison test
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
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.
Gaussian Process Regression Model in Spatial Logistic Regression
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.
Spatial modeling of agricultural land use change at global scale
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
A spatial emergy model for Alachua County, Florida
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
Multivariate Receptor Models for Spatially Correlated Multipollutant Data
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.
Hedge, Craig; Oberauer, Klaus; Leonards, Ute
2015-11-01
We examined the relationship between the attentional selection of perceptual information and of information in working memory (WM) through four experiments, using a spatial WM-updating task. Participants remembered the locations of two objects in a matrix and worked through a sequence of updating operations, each mentally shifting one dot to a new location according to an arrow cue. Repeatedly updating the same object in two successive steps is typically faster than switching to the other object; this object switch cost reflects the shifting of attention in WM. In Experiment 1, the arrows were presented in random peripheral locations, drawing perceptual attention away from the selected object in WM. This manipulation did not eliminate the object switch cost, indicating that the mechanisms of perceptual selection do not underlie selection in WM. Experiments 2a and 2b corroborated the independence of selection observed in Experiment 1, but showed a benefit to reaction times when the placement of the arrow cue was aligned with the locations of relevant objects in WM. Experiment 2c showed that the same benefit also occurs when participants are not able to mark an updating location through eye fixations. Together, these data can be accounted for by a framework in which perceptual selection and selection in WM are separate mechanisms that interact through a shared spatial priority map.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
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.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
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.
Semantic models for adaptive interactive systems
Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle
2013-01-01
Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using
Using Interaction Scenarios to Model Information Systems
DEFF Research Database (Denmark)
Bækgaard, Lars; Bøgh Andersen, Peter
The purpose of this paper is to define and discuss a set of interaction primitives that can be used to model the dynamics of socio-technical activity systems, including information systems, in a way that emphasizes structural aspects of the interaction that occurs in such systems. The primitives...... a number of case studies that indicate that interaction primitives can be useful modeling tools for supplementing conventional flow-oriented modeling of business processes....... are based on a unifying, conceptual definition of the disparate interaction types - a robust model of the types. The primitives can be combined and may thus represent mediated interaction. We present a set of visualizations that can be used to define multiple related interactions and we present and discuss...
Herbivore-induced plant volatiles and tritrophic interactions across spatial scales.
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.
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...
International Nuclear Information System (INIS)
Drechsler, Martin; Ohl, Cornelia; Meyerhoff, Juergen; Eichhorn, Marcus; Monsees, Jan
2011-01-01
Although wind power is currently the most efficient source of renewable energy, the installation of wind turbines (WT) in landscapes often leads to conflicts in the affected communities. We propose that such conflicts can be mitigated by a welfare-optimal spatial allocation of WT in the landscape so that a given energy target is reached at minimum social costs. The energy target is motivated by the fact that wind power production is associated with relatively low CO 2 emissions. Social costs comprise energy production costs as well as external costs caused by harmful impacts on humans and biodiversity. We present a modeling approach that combines spatially explicit ecological-economic modeling and choice experiments to determine the welfare-optimal spatial allocation of WT in West Saxony, Germany. The welfare-optimal sites balance production and external costs. Results indicate that in the welfare-optimal allocation the external costs represent about 14% of the total costs (production costs plus external costs). Optimizing wind power production without consideration of the external costs would lead to a very different allocation of WT that would marginally reduce the production costs but strongly increase the external costs and thus lead to substantial welfare losses. - Highlights: → We combine modeling and economic valuation to optimally allocate wind turbines. → Welfare-optimal allocation balances energy production costs and external costs. → External costs (impacts on the environment) can be substantial. → Ignoring external costs leads to suboptimal allocations and welfare losses.
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.
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.
Fragmentary model of exchange interactions
Kotov, V M
2000-01-01
This article makes attempt to refusal from using neutrino for explanation continuous distribution of beta particle energy by conversion to characteristic exchange interaction particles in nucleolus. It is taking formulation for nuclear position with many different fragments. It is computing half-value period of spontaneous fission of heavy nucleolus. (author)
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.
The modeling of predator-prey interactions
Muhammad Shakil; H. A. Wahab; Muhammad Naeem, et al.
2015-01-01
In this paper, we aim to study the interactions between the territorial animals like foxes and the rabbits. The territories for the foxes are considered to be the simple cells. The interactions between predator and its prey are represented by the chemical reactions which obey the mass action law. In this sense, we apply the mass action law for predator prey models and the quasi chemical approach is applied for the interactions between the predator and its prey to develop the modeled equations...
Modeling multimodal human-computer interaction
Obrenovic, Z.; Starcevic, D.
2004-01-01
Incorporating the well-known Unified Modeling Language into a generic modeling framework makes research on multimodal human-computer interaction accessible to a wide range off software engineers. Multimodal interaction is part of everyday human discourse: We speak, move, gesture, and shift our gaze
Directory of Open Access Journals (Sweden)
Alana Grech
Full Text Available BACKGROUND: The Queensland East Coast Otter Trawl Fishery (ECOTF for penaeid shrimp fishes within Australia's Great Barrier Reef World Heritage Area (GBRWHA. The past decade has seen the implementation of conservation and fisheries management strategies to reduce the impact of the ECOTF on the seabed and improve biodiversity conservation. New information from electronic vessel location monitoring systems (VMS provides an opportunity to review the interactions between the ECOTF and spatial closures for biodiversity conservation. METHODOLOGY AND RESULTS: We used fishing metrics and spatial information on the distribution of closures and modelled VMS data in a geographical information system (GIS to assess change in effort of the trawl fishery from 2001-2009 and to quantify the exposure of 70 reef, non-reef and deep water bioregions to trawl fishing. The number of trawlers and the number of days fished almost halved between 2001 and 2009 and new spatial closures introduced in 2004 reduced the area zoned available for trawl fishing by 33%. However, we found that there was only a relatively minor change in the spatial footprint of the fishery as a result of new spatial closures. Non-reef bioregions benefited the most from new spatial closures followed by deep and reef bioregions. CONCLUSIONS/SIGNIFICANCE: Although the catch of non target species remains an issue of concern for fisheries management, the small spatial footprint of the ECOTF relative to the size of the GBRWHA means that the impact on benthic habitats is likely to be negligible. The decline in effort as a result of fishing industry structural adjustment, increasing variable costs and business decisions of fishers is likely to continue a trend to fish only in the most productive areas. This will provide protection for most benthic habitats without any further legislative or management intervention.
Gravitational interactions of integrable models
International Nuclear Information System (INIS)
Abdalla, E.; Abdalla, M.C.B.
1995-10-01
We couple non-linear σ-models to Liouville gravity, showing that integrability properties of symmetric space models still hold for the matter sector. Using similar arguments for the fermionic counterpart, namely Gross-Neveu-type models, we verify that such conclusions must also hold for them, as recently suggested. (author). 18 refs
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.
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)
Design of spatial experiments: Model fitting and prediction
Energy Technology Data Exchange (ETDEWEB)
Fedorov, V.V.
1996-03-01
The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory.
Thinking Egyptian: Active Models for Understanding Spatial Representation.
Schiferl, Ellen
This paper highlights how introductory textbooks on Egyptian art inhibit understanding by reinforcing student preconceptions, and demonstrates another approach to discussing space with a classroom exercise and software. The alternative approach, an active model for spatial representation, introduced here was developed by adapting classroom…
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)
Rockfall hazard analysis using LiDAR and spatial modeling
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.
Individual based model of slug population and spatial dynamics
Choi, Y.H.; Bohan, D.A.; Potting, R.P.J.; Semenov, M.A.; Glen, D.M.
2006-01-01
The slug, Deroceras reticulatum, is one of the most important pests of agricultural and horticultural crops in UK and Europe. In this paper, a spatially explicit individual based model (IbM) is developed to study the dynamics of a population of D. reticulatum. The IbM establishes a virtual field
Differences in spatial understanding between physical and virtual models
Directory of Open Access Journals (Sweden)
Lei Sun
2014-03-01
Full Text Available In the digital age, physical models are still used as major tools in architectural and urban design processes. The reason why designers still use physical models remains unclear. In addition, physical and 3D virtual models have yet to be differentiated. The answers to these questions are too complex to account for in all aspects. Thus, this study only focuses on the differences in spatial understanding between physical and virtual models. In particular, it emphasizes on the perception of scale. For our experiment, respondents were shown a physical model and a virtual model consecutively. A questionnaire was then used to ask the respondents to evaluate these models objectively and to establish which model was more accurate in conveying object size. Compared with the virtual model, the physical model tended to enable quicker and more accurate comparisons of building heights.
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.)
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.
A spatial haplotype copying model with applications to genotype imputation.
Yang, Wen-Yun; Hormozdiari, Farhad; Eskin, Eleazar; Pasaniuc, Bogdan
2015-05-01
Ever since its introduction, the haplotype copy model has proven to be one of the most successful approaches for modeling genetic variation in human populations, with applications ranging from ancestry inference to genotype phasing and imputation. Motivated by coalescent theory, this approach assumes that any chromosome (haplotype) can be modeled as a mosaic of segments copied from a set of chromosomes sampled from the same population. At the core of the model is the assumption that any chromosome from the sample is equally likely to contribute a priori to the copying process. Motivated by recent works that model genetic variation in a geographic continuum, we propose a new spatial-aware haplotype copy model that jointly models geography and the haplotype copying process. We extend hidden Markov models of haplotype diversity such that at any given location, haplotypes that are closest in the genetic-geographic continuum map are a priori more likely to contribute to the copying process than distant ones. Through simulations starting from the 1000 Genomes data, we show that our model achieves superior accuracy in genotype imputation over the standard spatial-unaware haplotype copy model. In addition, we show the utility of our model in selecting a small personalized reference panel for imputation that leads to both improved accuracy as well as to a lower computational runtime than the standard approach. Finally, we show our proposed model can be used to localize individuals on the genetic-geographical map on the basis of their genotype data.
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
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.
Modern methodology and applications in spatial-temporal modeling
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...
Stochastic geometry, spatial statistics and random fields models and algorithms
2015-01-01
Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.
Analog model for analysis of spatial instability of neutron flux
International Nuclear Information System (INIS)
Radanovic, Lj.
1964-12-01
The objective of this task was to develop a model for analysing spatial instability of the neutron flux and defining the optimum number and position of regulating rods. The developed model enables calculation of higher harmonics to be taken into account for each type of reactor, to define zones for regulation rods, position and number of points for detecting reactor state, and number and position of the regulating rods
Integrating remote sensing and spatially explicit epidemiological modeling
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.
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.
Spatial Temporal Modelling of Particulate Matter for Health Effects Studies
Hamm, N. A. S.
2016-10-01
Epidemiological studies of the health effects of air pollution require estimation of individual exposure. It is not possible to obtain measurements at all relevant locations so it is necessary to predict at these space-time locations, either on the basis of dispersion from emission sources or by interpolating observations. This study used data obtained from a low-cost sensor network of 32 air quality monitoring stations in the Dutch city of Eindhoven, which make up the ILM (innovative air (quality) measurement system). These stations currently provide PM10 and PM2.5 (particulate matter less than 10 and 2.5 m in diameter), aggregated to hourly means. The data provide an unprecedented level of spatial and temporal detail for a city of this size. Despite these benefits the time series of measurements is characterized by missing values and noisy values. In this paper a space-time analysis is presented that is based on a dynamic model for the temporal component and a Gaussian process geostatistical for the spatial component. Spatial-temporal variability was dominated by the temporal component, although the spatial variability was also substantial. The model delivered accurate predictions for both isolated missing values and 24-hour periods of missing values (RMSE = 1.4 μg m-3 and 1.8 μg m-3 respectively). Outliers could be detected by comparison to the 95% prediction interval. The model shows promise for predicting missing values, outlier detection and for mapping to support health impact studies.
Spatial modelling and ecology of Echinococcus multilocularis transmission in China.
Danson, F Mark; Giraudoux, Patrick; Craig, Philip S
2006-01-01
Recent research in central China has suggested that the most likely transmission mechanism for Echinococcus multilocularis to humans is via domestic dogs which are allowed to roam freely and hunt (infected) small mammals within areas close to villages or in areas of tented pasture. This assertion has led to the hypothesis that there is a landscape control on transmission risk since the proximity of suitable habitat for susceptible small mammals appears to be the key. We have tested this hypothesis in a number of endemic areas in China, notably south Gansu Province and the Tibetan region of western Sichuan Province. The fundamental landscape control is its effect at a regional scale on small mammal species assemblages (susceptible species are not ubiquitous) and, at a local scale, the spatial distributions of small mammal populations. To date the research has examined relationships between landscape composition and patterns of human infection, landscape and small mammal distributions and recently the relationships between landscape and dog infection rates. The key tool to characterize landscape is satellite remote sensing and these data are used as inputs to drive spatial models of transmission risk. This paper reviews the progress that has been made so far in spatial modeling of the ecology of E. multilocularis with particular reference to China, outlines current research issues, and describes a framework for building a spatial-temporal model of transmission ecology.
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...
Deep Predictive Models in Interactive Music
Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim
2018-01-01
Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...
Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands.
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
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
Indoor 3D Route Modeling Based On Estate Spatial Data
Zhang, H.; Wen, Y.; Jiang, J.; Huang, W.
2014-04-01
Indoor three-dimensional route model is essential for space intelligence navigation and emergency evacuation. This paper is motivated by the need of constructing indoor route model automatically and as far as possible. By comparing existing building data sources, this paper firstly explained the reason why the estate spatial management data is chosen as the data source. Then, an applicable method of construction three-dimensional route model in a building is introduced by establishing the mapping relationship between geographic entities and their topological expression. This data model is a weighted graph consist of "node" and "path" to express the spatial relationship and topological structure of a building components. The whole process of modelling internal space of a building is addressed by two key steps: (1) each single floor route model is constructed, including path extraction of corridor using Delaunay triangulation algorithm with constrained edge, fusion of room nodes into the path; (2) the single floor route model is connected with stairs and elevators and the multi-floor route model is eventually generated. In order to validate the method in this paper, a shopping mall called "Longjiang New City Plaza" in Nanjing is chosen as a case of study. And the whole building space is constructed according to the modelling method above. By integrating of existing path finding algorithm, the usability of this modelling method is verified, which shows the indoor three-dimensional route modelling method based on estate spatial data in this paper can support indoor route planning and evacuation route design very well.
Single Canonical Model of Reflexive Memory and Spatial Attention
Patel, Saumil S.; Red, Stuart; Lin, Eric; Sereno, Anne B.
2015-01-01
Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey’s task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes. PMID:26493949
Chaotic and stable perturbed maps: 2-cycles and spatial models
Braverman, E.; Haroutunian, J.
2010-06-01
As the growth rate parameter increases in the Ricker, logistic and some other maps, the models exhibit an irreversible period doubling route to chaos. If a constant positive perturbation is introduced, then the Ricker model (but not the classical logistic map) experiences period doubling reversals; the break of chaos finally gives birth to a stable two-cycle. We outline the maps which demonstrate a similar behavior and also study relevant discrete spatial models where the value in each cell at the next step is defined only by the values at the cell and its nearest neighbors. The stable 2-cycle in a scalar map does not necessarily imply 2-cyclic-type behavior in each cell for the spatial generalization of the map.
Single Canonical Model of Reflexive Memory and Spatial Attention.
Patel, Saumil S; Red, Stuart; Lin, Eric; Sereno, Anne B
2015-10-23
Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey's task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes.
Neuromorphic model of magnocellular and parvocellular visual paths: spatial resolution
International Nuclear Information System (INIS)
Aguirre, Rolando C; Felice, Carmelo J; Colombo, Elisa M
2007-01-01
Physiological studies of the human retina show the existence of at least two visual information processing channels, the magnocellular and the parvocellular ones. Both have different spatial, temporal and chromatic features. This paper focuses on the different spatial resolution of these two channels. We propose a neuromorphic model, so that they match the retina's physiology. Considering the Deutsch and Deutsch model (1992), we propose two configurations (one for each visual channel) of the connection between the retina's different cell layers. The responses of the proposed model have similar behaviour to those of the visual cells: each channel has an optimum response corresponding to a given stimulus size which decreases for larger or smaller stimuli. This size is bigger for the magno path than for the parvo path and, in the end, both channels produce a magnifying of the borders of a stimulus
Spatial heterogeneity, frequency-dependent selection and polymorphism in host-parasite interactions
Directory of Open Access Journals (Sweden)
Tellier Aurélien
2011-11-01
Full Text Available Abstract Background Genomic and pathology analysis has revealed enormous diversity in genes involved in disease, including those encoding host resistance and parasite effectors (also known in plant pathology as avirulence genes. It has been proposed that such variation may persist when an organism exists in a spatially structured metapopulation, following the geographic mosaic of coevolution. Here, we study gene-for-gene relationships governing the outcome of plant-parasite interactions in a spatially structured system and, in particular, investigate the population genetic processes which maintain balanced polymorphism in both species. Results Following previous theory on the effect of heterogeneous environments on maintenance of polymorphism, we analysed a model with two demes in which the demes have different environments and are coupled by gene flow. Environmental variation is manifested by different coefficients of natural selection, the costs to the host of resistance and to the parasite of virulence, the cost to the host of being diseased and the cost to an avirulent parasite of unsuccessfully attacking a resistant host. We show that migration generates negative direct frequency-dependent selection, a condition for maintenance of stable polymorphism in each deme. Balanced polymorphism occurs preferentially if there is heterogeneity for costs of resistance and virulence alleles among populations and to a lesser extent if there is variation in the cost to the host of being diseased. We show that the four fitness costs control the natural frequency of oscillation of host resistance and parasite avirulence alleles. If demes have different costs, their frequencies of oscillation differ and when coupled by gene flow, there is amplitude death of the oscillations in each deme. Numerical simulations show that for a multiple deme island model, costs of resistance and virulence need not to be present in each deme for stable polymorphism to occur
A Method for Model Checking Feature Interactions
DEFF Research Database (Denmark)
Pedersen, Thomas; Le Guilly, Thibaut; Ravn, Anders Peter
2015-01-01
This paper presents a method to check for feature interactions in a system assembled from independently developed concurrent processes as found in many reactive systems. The method combines and refines existing definitions and adds a set of activities. The activities describe how to populate the ...... the definitions with models to ensure that all interactions are captured. The method is illustrated on a home automation example with model checking as analysis tool. In particular, the modelling formalism is timed automata and the analysis uses UPPAAL to find interactions....
Directory of Open Access Journals (Sweden)
Yuhong He
2014-09-01
Full Text Available Recent studies indicate that positive relationships between invasive plants and soil can contribute to further plant invasions. However, it remains unclear whether these relations remain unchanged throughout the growing season. In this study, spatial sequences of field observations along a transect were used to reveal seasonal interactions and spatially covarying relations between one common invasive shrub (Tartarian Honeysuckle, Lonicera tatarica and soil moisture in a tall grassland habitat. Statistical analysis over the transect shows that the contrast between soil moisture in shrub and herbaceous patches vary with season and precipitation. Overall, a negatively covarying relationship between shrub and soil moisture (i.e., drier surface soils at shrub microsites exists during the very early growing period (e.g., May, while in summer a positively covarying phenomenon (i.e., wetter soils under shrubs is usually evident, but could be weakened or vanish during long precipitation-free periods. If there is sufficient rainfall, surface soil moisture and leaf area index (LAI often spatially covary with significant spatial oscillations at an invariant scale (which is governed by the shrub spatial pattern and is about 8 m, but their phase relation in space varies with season, consistent with the seasonal variability of the co-varying phenomena between shrub invasion and soil water content. The findings are important for establishing a more complete picture of how shrub invasion affects soil moisture.
Porous models for wave-seabed interactions
Energy Technology Data Exchange (ETDEWEB)
Jeng, Dong-Sheng [Shanghai Jiaotong Univ., SH (China)
2013-02-01
Detailed discussion about the phenomenon of wave-seabed interactions. Novel models for wave-induced seabed response. Intensive theoretical derivations for wave-seabed interactions. Practical examples for engineering applications. ''Porous Models for Wave-seabed Interactions'' discusses the Phenomenon of wave-seabed interactions, which is a vital issue for coastal and geotechnical engineers involved in the design of foundations for marine structures such as pipelines, breakwaters, platforms, etc. The most important sections of this book will be the fully detailed theoretical models of wave-seabed interaction problem, which are particularly useful for postgraduate students and junior researchers entering the discipline of marine geotechnics and offshore engineering. This book also converts the research outcomes of theoretical studies to engineering applications that will provide front-line engineers with practical and effective tools in the assessment of seabed instability in engineering design.
The Monash University Interactive Simple Climate Model
Dommenget, D.
2013-12-01
The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.
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
The Color Mutation Model for soft interaction
International Nuclear Information System (INIS)
Hwa, R.C.
1998-01-01
A comprehensive model for soft interaction is presented. It overcomes all the shortcomings of the existing models - in particular, the failure of Fritiof and Venus models in predicting the correct multiplicity fluctuations as observed in the intermittency data. The Color Mutation Model incorporates all the main features of hadronic interaction: eikonal formalism, parton model, evolution in color space according to QCD, branching of color neutral clusters, contraction due to confinement forces, dynamical self-similarity, resonance production, and power-law behavior of factorial moments. (author)
Modeling spin magnetization transport in a spatially varying magnetic field
International Nuclear Information System (INIS)
Picone, Rico A.R.; Garbini, Joseph L.; Sidles, John A.
2015-01-01
We present a framework for modeling the transport of any number of globally conserved quantities in any spatial configuration and apply it to obtain a model of magnetization transport for spin-systems that is valid in new regimes (including high-polarization). The framework allows an entropy function to define a model that explicitly respects the laws of thermodynamics. Three facets of the model are explored. First, it is expressed as nonlinear partial differential equations that are valid for the new regime of high dipole-energy and polarization. Second, the nonlinear model is explored in the limit of low dipole-energy (semi-linear), from which is derived a physical parameter characterizing separative magnetization transport (SMT). It is shown that the necessary and sufficient condition for SMT to occur is that the parameter is spatially inhomogeneous. Third, the high spin-temperature (linear) limit is shown to be equivalent to the model of nuclear spin transport of Genack and Redfield (1975) [1]. Differences among the three forms of the model are illustrated by numerical solution with parameters corresponding to a magnetic resonance force microscopy (MRFM) experiment (Degen et al., 2009 [2]; Kuehn et al., 2008 [3]; Sidles et al., 2003 [4]; Dougherty et al., 2000 [5]). A family of analytic, steady-state solutions to the nonlinear equation is derived and shown to be the spin-temperature analog of the Langevin paramagnetic equation and Curie's law. Finally, we analyze the separative quality of magnetization transport, and a steady-state solution for the magnetization is shown to be compatible with Fenske's separative mass transport equation (Fenske, 1932 [6]). - Highlights: • A framework for modeling the transport of conserved magnetic and thermodynamic quantities in any spatial configuration. • A thermodynamically grounded model of spin magnetization transport valid in new regimes, including high-polarization. • Analysis of the separative quality of
Modeling spin magnetization transport in a spatially varying magnetic field
Energy Technology Data Exchange (ETDEWEB)
Picone, Rico A.R., E-mail: rpicone@stmartin.edu [Department of Mechanical Engineering, University of Washington, Seattle (United States); Garbini, Joseph L. [Department of Mechanical Engineering, University of Washington, Seattle (United States); Sidles, John A. [Department of Orthopædics, University of Washington, Seattle (United States)
2015-01-15
We present a framework for modeling the transport of any number of globally conserved quantities in any spatial configuration and apply it to obtain a model of magnetization transport for spin-systems that is valid in new regimes (including high-polarization). The framework allows an entropy function to define a model that explicitly respects the laws of thermodynamics. Three facets of the model are explored. First, it is expressed as nonlinear partial differential equations that are valid for the new regime of high dipole-energy and polarization. Second, the nonlinear model is explored in the limit of low dipole-energy (semi-linear), from which is derived a physical parameter characterizing separative magnetization transport (SMT). It is shown that the necessary and sufficient condition for SMT to occur is that the parameter is spatially inhomogeneous. Third, the high spin-temperature (linear) limit is shown to be equivalent to the model of nuclear spin transport of Genack and Redfield (1975) [1]. Differences among the three forms of the model are illustrated by numerical solution with parameters corresponding to a magnetic resonance force microscopy (MRFM) experiment (Degen et al., 2009 [2]; Kuehn et al., 2008 [3]; Sidles et al., 2003 [4]; Dougherty et al., 2000 [5]). A family of analytic, steady-state solutions to the nonlinear equation is derived and shown to be the spin-temperature analog of the Langevin paramagnetic equation and Curie's law. Finally, we analyze the separative quality of magnetization transport, and a steady-state solution for the magnetization is shown to be compatible with Fenske's separative mass transport equation (Fenske, 1932 [6]). - Highlights: • A framework for modeling the transport of conserved magnetic and thermodynamic quantities in any spatial configuration. • A thermodynamically grounded model of spin magnetization transport valid in new regimes, including high-polarization. • Analysis of the separative quality of
Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago.
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
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
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.
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.
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
A general modeling framework for describing spatially structured population dynamics
Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan
2017-01-01
Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance
Spatial distribution of emissions to air - the SPREAD model
Energy Technology Data Exchange (ETDEWEB)
Plejdrup, M S; Gyldenkaerne, S
2011-04-15
The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)
Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.
Spatial distribution of emissions to air - the SPREAD model
Energy Technology Data Exchange (ETDEWEB)
Plejdrup, M.S.; Gyldenkaerne, S.
2011-04-15
The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)
Tapered composite likelihood for spatial max-stable models
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.
Database modeling to integrate macrobenthos data in Spatial Data Infrastructure
Directory of Open Access Journals (Sweden)
José Alberto Quintanilha
2012-08-01
Full Text Available Coastal zones are complex areas that include marine and terrestrial environments. Besides its huge environmental wealth, they also attracts humans because provides food, recreation, business, and transportation, among others. Some difficulties to manage these areas are related with their complexity, diversity of interests and the absence of standardization to collect and share data to scientific community, public agencies, among others. The idea to organize, standardize and share this information based on Web Atlas is essential to support planning and decision making issues. The construction of a spatial database integrating the environmental business, to be used on Spatial Data Infrastructure (SDI is illustrated by a bioindicator that indicates the quality of the sediments. The models show the phases required to build Macrobenthos spatial database based on Santos Metropolitan Region as a reference. It is concluded that, when working with environmental data the structuring of knowledge in a conceptual model is essential for their subsequent integration into the SDI. During the modeling process it can be noticed that methodological issues related to the collection process may obstruct or prejudice the integration of data from different studies of the same area. The development of a database model, as presented in this study, can be used as a reference for further research with similar goals.
Tapered composite likelihood for spatial max-stable models
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.
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.
N-barN interaction theoretical models
International Nuclear Information System (INIS)
Loiseau, B.
1991-12-01
In the framework of antinucleon-nucleon interaction theoretical models, our present understanding on the N-barN interaction is discussed, either from quark- or/and meson- and baryon-degrees of freedom, by considering the N-barN annihilation into mesons and the N-barN elastic and charge-exchange scattering. (author) 52 refs., 11 figs., 2 tabs
Numerical modeling of magma-repository interactions
Bokhove, Onno
2001-01-01
This report explains the numerical programs behind a comprehensive modeling effort of magma-repository interactions. Magma-repository interactions occur when a magma dike with high-volatile content magma ascends through surrounding rock and encounters a tunnel or drift filled with either a magmatic
Spatial Modelling of Sediment Transport over the Upper Citarum Catchment
Directory of Open Access Journals (Sweden)
Poerbandono
2006-05-01
Full Text Available This paper discusses set up of a spatial model applied in Geographic Information System (GIS environment for predicting annual erosion rate and sediment yield of a watershed. The study area is situated in the Upper Citarum Catchment of West Java. Annual sediment yield is considered as product of erosion rate and sediment delivery ratio to be modelled under similar modeling tool. Sediment delivery ratio is estimated on the basis of sediment resident time. The modeling concept is based on the calculation of water flow velocity through sub-catchment surface, which is controlled by topography, rainfall, soil characteristics and various types of land use. Relating velocity to known distance across digital elevation model, sediment resident time can be estimated. Data from relevance authorities are used. Bearing in mind limited knowledge of some governing factors due to lack of observation, the result has shown the potential of GIS for spatially modeling regional sediment transport. Validation of model result is carried out by evaluating measured and computed total sediment yield at the main outlet. Computed total sediment yields for 1994 and 2001 are found to be 1.96×106 and 2.10×106tons/year. They deviate roughly 54 and 8% with respect to those measured in the field. Model response due to land use change observed in 2001 and 1994 is also recognised. Under presumably constant rainfall depth, an increase of overall average annual erosion rate of 11% resulted in an increase of overall average sediment yield of 7%.
Supplementary Material for: Factor Copula Models for Replicated Spatial Data
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.
A spatial structural derivative model for ultraslow diffusion
Directory of Open Access Journals (Sweden)
Xu Wei
2017-01-01
Full Text Available This study investigates the ultraslow diffusion by a spatial structural derivative, in which the exponential function ex is selected as the structural function to construct the local structural derivative diffusion equation model. The analytical solution of the diffusion equation is a form of Biexponential distribution. Its corresponding mean squared displacement is numerically calculated, and increases more slowly than the logarithmic function of time. The local structural derivative diffusion equation with the structural function ex in space is an alternative physical and mathematical modeling model to characterize a kind of ultraslow diffusion.
Modeling of soil-water-structure interaction
DEFF Research Database (Denmark)
Tang, Tian
as the developed nonlinear soil displacements and stresses under monotonic and cyclic loading. With the FVM nonlinear coupled soil models as a basis, multiphysics modeling of wave-seabed-structure interaction is carried out. The computations are done in an open source code environment, OpenFOAM, where FVM models...
Jackson, Doug; Vandermeer, John; Perfecto, Ivette; Philpott, Stacy M
2014-01-01
Spatial structure can have a profound, but often underappreciated, effect on the temporal dynamics of ecosystems. Here we report on a counterintuitive increase in the population of a tree-nesting ant, Azteca sericeasur, in response to a drastic reduction in the number of potential nesting sites. This surprising result is comprehensible when viewed in the context of the self-organized spatial dynamics of the ants and their effect on the ants' dispersal-limited natural enemies. Approximately 30% of the trees in the study site, a coffee agroecosystem in southern Mexico, were pruned or felled over a two-year period, and yet the abundance of the ant nests more than doubled over the seven-year study. Throughout the transition, the spatial distribution of the ants maintained a power-law distribution - a signal of spatial self organization - but the local clustering of the nests was reduced post-pruning. A cellular automata model incorporating the changed spatial structure of the ants and the resulting partial escape from antagonists reproduced the observed increase in abundance, highlighting how self-organized spatial dynamics can profoundly influence the responses of ecosystems to perturbations.
Directory of Open Access Journals (Sweden)
Doug Jackson
Full Text Available Spatial structure can have a profound, but often underappreciated, effect on the temporal dynamics of ecosystems. Here we report on a counterintuitive increase in the population of a tree-nesting ant, Azteca sericeasur, in response to a drastic reduction in the number of potential nesting sites. This surprising result is comprehensible when viewed in the context of the self-organized spatial dynamics of the ants and their effect on the ants' dispersal-limited natural enemies. Approximately 30% of the trees in the study site, a coffee agroecosystem in southern Mexico, were pruned or felled over a two-year period, and yet the abundance of the ant nests more than doubled over the seven-year study. Throughout the transition, the spatial distribution of the ants maintained a power-law distribution - a signal of spatial self organization - but the local clustering of the nests was reduced post-pruning. A cellular automata model incorporating the changed spatial structure of the ants and the resulting partial escape from antagonists reproduced the observed increase in abundance, highlighting how self-organized spatial dynamics can profoundly influence the responses of ecosystems to perturbations.
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 modeling of HIV and HSV-2 among women in Kenya with spatially varying coefficients
Directory of Open Access Journals (Sweden)
Elphas Okango
2016-04-01
Full Text Available Abstract Background Disease mapping has become popular in the field of statistics as a method to explain the spatial distribution of disease outcomes and as a tool to help design targeted intervention strategies. Most of these models however have been implemented with assumptions that may be limiting or altogether lead to less meaningful results and hence interpretations. Some of these assumptions include the linearity, stationarity and normality assumptions. Studies have shown that the linearity assumption is not necessarily true for all covariates. Age for example has been found to have a non-linear relationship with HIV and HSV-2 prevalence. Other studies have made stationarity assumption in that one stimulus e.g. education, provokes the same response in all the regions under study and this is also quite restrictive. Responses to stimuli may vary from region to region due to aspects like culture, preferences and attitudes. Methods We perform a spatial modeling of HIV and HSV-2 among women in Kenya, while relaxing these assumptions i.e. the linearity assumption by allowing the covariate age to have a non-linear effect on HIV and HSV-2 prevalence using the random walk model of order 2 and the stationarity assumption by allowing the rest of the covariates to vary spatially using the conditional autoregressive model. The women data used in this study were derived from the 2007 Kenya AIDS indicator survey where women aged 15–49 years were surveyed. A full Bayesian approach was used and the models were implemented in R-INLA software. Results Age was found to have a non-linear relationship with both HIV and HSV-2 prevalence, and the spatially varying coefficient model provided a significantly better fit for HSV-2. Age-at first sex also had a greater effect on HSV-2 prevalence in the Coastal and some parts of North Eastern regions suggesting either early marriages or child prostitution. The effect of education on HIV prevalence among women was more
Syndetic model of fundamental interactions
Directory of Open Access Journals (Sweden)
Ernest Ma
2015-02-01
Full Text Available The standard model of quarks and leptons is extended to connect three outstanding issues in particle physics and astrophysics: (1 the absence of strong CP nonconservation, (2 the existence of dark matter, and (3 the mechanism of nonzero neutrino masses, and that of the first family of quarks and leptons, all in the context of having only one Higgs boson in a renormalizable theory. Some phenomenological implications are discussed.
Electron scattering in the interacting boson model
Dieperink, AEL; Iachello, F; Rinat, A; Creswell, C
1978-01-01
It is suggested that the interacting boson model be used in the analysis of electron scattering data. Qualitative features of the expected behavior of the inelastic excitation of some 2 ÷ states inthe transitional Sm-Nd region are discussed
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.
Functional Modeling of Neural-Glia Interaction
DEFF Research Database (Denmark)
Postnov, D.E.; Brazhe, N.A.; Sosnovtseva, Olga
2012-01-01
Functional modeling is an approach that focuses on the representation of the qualitative dynamics of the individual components (e.g. cells) of a system and on the structure of the interaction network.......Functional modeling is an approach that focuses on the representation of the qualitative dynamics of the individual components (e.g. cells) of a system and on the structure of the interaction network....
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
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)
Assessing NARCCAP climate model effects using spatial confidence regions
Directory of Open Access Journals (Sweden)
J. P. French
2017-07-01
Full Text Available We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.
Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations
Le, Phuong Dong; Leonard, Michael; Westra, Seth
2018-03-01
Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.
Spatial Models of Prebiotic Evolution: Soup Before Pizza?
Scheuring, István; Czárán, Tamás; Szabó, Péter; Károlyi, György; Toroczkai, Zoltán
2003-10-01
The problem of information integration and resistance to the invasion of parasitic mutants in prebiotic replicator systems is a notorious issue of research on the origin of life. Almost all theoretical studies published so far have demonstrated that some kind of spatial structure is indispensable for the persistence and/or the parasite resistance of any feasible replicator system. Based on a detailed critical survey of spatial models on prebiotic information integration, we suggest a possible scenario for replicator system evolution leading to the emergence of the first protocells capable of independent life. We show that even the spatial versions of the hypercycle model are vulnerable to selfish parasites in heterogeneous habitats. Contrary, the metabolic system remains persistent and coexistent with its parasites both on heterogeneous surfaces and in chaotically mixing flowing media. Persistent metabolic parasites can be converted to metabolic cooperators, or they can gradually obtain replicase activity. Our simulations show that, once replicase activity emerged, a gradual and simultaneous evolutionary improvement of replicase functionality (speed and fidelity) and template efficiency is possible only on a surface that constrains the mobility of macromolecule replicators. Based on the results of the models reviewed, we suggest that open chaotic flows (`soup') and surface dynamics (`pizza') both played key roles in the sequence of evolutionary events ultimately concluding in the appearance of the first living cell on Earth.
Mathematical models for plant-herbivore interactions
Feng, Zhilan; DeAngelis, Donald L.
2017-01-01
Mathematical Models of Plant-Herbivore Interactions addresses mathematical models in the study of practical questions in ecology, particularly factors that affect herbivory, including plant defense, herbivore natural enemies, and adaptive herbivory, as well as the effects of these on plant community dynamics. The result of extensive research on the use of mathematical modeling to investigate the effects of plant defenses on plant-herbivore dynamics, this book describes a toxin-determined functional response model (TDFRM) that helps explains field observations of these interactions. This book is intended for graduate students and researchers interested in mathematical biology and ecology.
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
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
Characterization and spatial modeling of urban sprawl in the Wuhan Metropolitan Area, China
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.
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.
Modeling spatial invasion of Ebola in West Africa.
D'Silva, Jeremy P; Eisenberg, Marisa C
2017-09-07
The 2014-2016 Ebola Virus Disease (EVD) epidemic in West Africa was the largest ever recorded, representing a fundamental shift in Ebola epidemiology with unprecedented spatiotemporal complexity. To understand the spatiotemporal dynamics of EVD in West Africa, we developed spatial transmission models using a gravity-model framework at both the national and district-level scales, which we used to compare effectiveness of local interventions (e.g. local quarantine) and long-range interventions (e.g. border-closures). The country-level gravity model captures the epidemic data, including multiple waves of initial epidemic growth observed in Guinea. We found that local-transmission reductions were most effective in Liberia, while long-range transmission was dominant in Sierra Leone. Both models illustrated that interventions in one region result in an amplified protective effect on other regions by preventing spatial transmission. In the district-level model, interventions in the strongest of these amplifying regions reduced total cases in all three countries by over 20%, in spite of the region itself generating only ∼0.1% of total cases. This model structure and associated intervention analysis provide information that can be used by public health policymakers to assist planning and response efforts for future epidemics. Copyright © 2017 Elsevier Ltd. All rights reserved.
A modal approach to modeling spatially distributed vibration energy dissipation.
Energy Technology Data Exchange (ETDEWEB)
Segalman, Daniel Joseph
2010-08-01
The nonlinear behavior of mechanical joints is a confounding element in modeling the dynamic response of structures. Though there has been some progress in recent years in modeling individual joints, modeling the full structure with myriad frictional interfaces has remained an obstinate challenge. A strategy is suggested for structural dynamics modeling that can account for the combined effect of interface friction distributed spatially about the structure. This approach accommodates the following observations: (1) At small to modest amplitudes, the nonlinearity of jointed structures is manifest primarily in the energy dissipation - visible as vibration damping; (2) Correspondingly, measured vibration modes do not change significantly with amplitude; and (3) Significant coupling among the modes does not appear to result at modest amplitudes. The mathematical approach presented here postulates the preservation of linear modes and invests all the nonlinearity in the evolution of the modal coordinates. The constitutive form selected is one that works well in modeling spatially discrete joints. When compared against a mathematical truth model, the distributed dissipation approximation performs well.
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.
Vector-Interaction-Enhanced Bag Model
Cierniak, Mateusz; Klähn, Thomas; Fischer, Tobias; Bastian, Niels-Uwe
2018-02-01
A commonly applied quark matter model in astrophysics is the thermodynamic bag model (tdBAG). The original MIT bag model approximates the effect of quark confinement, but does not explicitly account for the breaking of chiral symmetry, an important property of Quantum Chromodynamics (QCD). It further ignores vector repulsion. The vector-interaction-enhanced bag model (vBag) improves the tdBAG approach by accounting for both dynamical chiral symmetry breaking and repulsive vector interactions. The latter is of particular importance to studies of dense matter in beta-equilibriumto explain the two solar mass maximum mass constraint for neutron stars. The model is motivated by analyses of QCD based Dyson-Schwinger equations (DSE), assuming a simple quark-quark contact interaction. Here, we focus on the study of hybrid neutron star properties resulting from the application of vBag and will discuss possible extensions.
Spatial interpolation schemes of daily precipitation for hydrologic modeling
Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.
2012-01-01
Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.
Quantifying long-term evolution of intra-urban spatial interactions
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
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.
Propagation dynamics for a spatially periodic integrodifference competition model
Wu, Ruiwen; Zhao, Xiao-Qiang
2018-05-01
In this paper, we study the propagation dynamics for a class of integrodifference competition models in a periodic habitat. An interesting feature of such a system is that multiple spreading speeds can be observed, which biologically means different species may have different spreading speeds. We show that the model system admits a single spreading speed, and it coincides with the minimal wave speed of the spatially periodic traveling waves. A set of sufficient conditions for linear determinacy of the spreading speed is also given.
How to get rid of W: a latent variables approach to modelling spatially lagged variables
Folmer, H.; Oud, J.
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
How to get rid of W : a latent variables approach to modelling spatially lagged variables
Folmer, Henk; Oud, Johan
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
A minimal spatial cell lineage model of epithelium: tissue stratification and multi-stability
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.
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...
Relativistic direct interaction and hadron models
International Nuclear Information System (INIS)
Biswas, T.
1984-01-01
Direct interaction theories at a nonrelativistic level have been used successfully in several areas earlier (e.g. nuclear physics). But for hadron spectroscopy relativistic effects are important and hence the need for a relativistic direct interaction theory arises. It is the goal of this thesis to suggest such a theory which has the simplicity and the flexibility required for phenomenological model building. In general the introduction of relativity in a direct interaction theory is shown to be non-trivial. A first attempt leads to only an approximate form for allowed interactions. Even this is far too complex for phenomenological applicability. To simplify the model an extra spacelike particle called the vertex is introduced in any set of physical (timelike) particles. The vertex model is successfully used to fit and to predict experimental data on hadron spectra, γ and psi states fit very well with an interaction function inspired by QCD. Light mesons also fit reasonably well. Better forms of hyperfine interaction functions would be needed to improve the fitting of light mesons. The unexpectedly low pi meson mass is partially explained. Baryon ground states are fitted with unprecedented accuracy with very few adjustable parameters. For baryon excited states it is shown that better QCD motivated interaction functions are needed for a fit. Predictions for bb states in e + e - experiments are made to assist current experiments
Spatial stochastic regression modelling of urban land use
International Nuclear Information System (INIS)
Arshad, S H M; Jaafar, J; Abiden, M Z Z; Latif, Z A; Rasam, A R A
2014-01-01
Urbanization is very closely linked to industrialization, commercialization or overall economic growth and development. This results in innumerable benefits of the quantity and quality of the urban environment and lifestyle but on the other hand contributes to unbounded development, urban sprawl, overcrowding and decreasing standard of living. Regulation and observation of urban development activities is crucial. The understanding of urban systems that promotes urban growth are also essential for the purpose of policy making, formulating development strategies as well as development plan preparation. This study aims to compare two different stochastic regression modeling techniques for spatial structure models of urban growth in the same specific study area. Both techniques will utilize the same datasets and their results will be analyzed. The work starts by producing an urban growth model by using stochastic regression modeling techniques namely the Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR). The two techniques are compared to and it is found that, GWR seems to be a more significant stochastic regression model compared to OLS, it gives a smaller AICc (Akaike's Information Corrected Criterion) value and its output is more spatially explainable
Spatial modeling for groundwater arsenic levels in North Carolina.
Kim, Dohyeong; Miranda, Marie Lynn; Tootoo, Joshua; Bradley, Phil; Gelfand, Alan E
2011-06-01
To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area.
Modeling spatial processes with unknown extremal dependence class
Huser, Raphaël G.
2017-03-17
Many environmental processes exhibit weakening spatial dependence as events become more extreme. Well-known limiting models, such as max-stable or generalized Pareto processes, cannot capture this, which can lead to a preference for models that exhibit a property known as asymptotic independence. However, weakening dependence does not automatically imply asymptotic independence, and whether the process is truly asymptotically (in)dependent is usually far from clear. The distinction is key as it can have a large impact upon extrapolation, i.e., the estimated probabilities of events more extreme than those observed. In this work, we present a single spatial model that is able to capture both dependence classes in a parsimonious manner, and with a smooth transition between the two cases. The model covers a wide range of possibilities from asymptotic independence through to complete dependence, and permits weakening dependence of extremes even under asymptotic dependence. Censored likelihood-based inference for the implied copula is feasible in moderate dimensions due to closed-form margins. The model is applied to oceanographic datasets with ambiguous true limiting dependence structure.
Spatial Modeling for Groundwater Arsenic Levels in North Carolina
Kim, Dohyeong; Miranda, Marie Lynn; Tootoo, Joshua; Bradley, Phil; Gelfand, Alan E.
2013-01-01
To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area. PMID:21528844
Spatial modeling for groundwater arsenic levels in North Carolina
Kim, D.; Miranda, M.L.; Tootoo, J.; Bradley, P.; Gelfand, A.E.
2011-01-01
To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area. ?? 2011 American Chemical Society.
Spatial Durbin model analysis macroeconomic loss due to natural disasters
Kusrini, D. E.; Mukhtasor
2015-03-01
Magnitude of the damage and losses caused by natural disasters is huge for Indonesia, therefore this study aimed to analyze the effects of natural disasters for macroeconomic losses that occurred in 115 cities/districts across Java during 2012. Based on the results of previous studies it is suspected that it contains effects of spatial dependencies in this case, so that the completion of this case is performed using a regression approach to the area, namely Analysis of Spatial Durbin Model (SDM). The obtained significant predictor variable is population, and predictor variable with a significant weighting is the number of occurrences of disasters, i.e., disasters in the region which have an impact on other neighboring regions. Moran's I index value using the weighted Queen Contiguity also showed significant results, meaning that the incidence of disasters in the region will decrease the value of GDP in other.
Spatial and spatio-temporal bayesian models with R - INLA
Blangiardo, Marta
2015-01-01
Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior Distr
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.
Modeling of hydrogen interactions with beryllium
Energy Technology Data Exchange (ETDEWEB)
Longhurst, G.R. [Lockheed Martin Idaho Technologies Co., Idaho Falls, ID (United States)
1998-01-01
In this paper, improved mathematical models are developed for hydrogen interactions with beryllium. This includes the saturation effect observed for high-flux implantation of ions from plasmas and retention of tritium produced from neutronic transmutations in beryllium. Use of the models developed is justified by showing how they can replicated experimental data using the TMAP4 tritium transport code. (author)
Interacting p- Boson model with isospin
International Nuclear Information System (INIS)
Chen, C.H.-T.
A description of collective states in self-conjugate nuclei is proposed, both odd-odd and even-even, in terms of an interacting isoscalar p-boson model. Within this model, two limiting cases can be identified with the anharmonic vibrator and axial rotor limits of the classical geometrical description. (Author) [pt
Learning models of activities involving interacting objects
DEFF Research Database (Denmark)
Manfredotti, Cristina; Pedersen, Kim Steenstrup; Hamilton, Howard J.
2013-01-01
We propose the LEMAIO multi-layer framework, which makes use of hierarchical abstraction to learn models for activities involving multiple interacting objects from time sequences of data concerning the individual objects. Experiments in the sea navigation domain yielded learned models that were t...
The Spiral-Interactive Program Evaluation Model.
Khaleel, Ibrahim Adamu
1988-01-01
Describes the spiral interactive program evaluation model, which is designed to evaluate vocational-technical education programs in secondary schools in Nigeria. Program evaluation is defined; utility oriented and process oriented models for evaluation are described; and internal and external evaluative factors and variables that define each…
An introduction to the interacting boson model
International Nuclear Information System (INIS)
Iachello, F.
1981-01-01
This chapter introduces an alternative, algebraic, description of the properties of nuclei with several particles outside the closed shells. Focuses on the group theory of the interacting boson model. Discusses the group structure of the boson Hamiltonian; subalgebras; the classification of states; dynamical symmetry; electromagnetic transition rates; transitional classes; and general cases. Omits a discussion of the latest developments (e.g., the introduction of proton and neutron degrees of freedom); the spectra of odd-A nuclei; and the bosonfermion model. Concludes that the major new feature of the interacting boson model is the introduction and systematic exploitation of algebraic techniques, which allows a simple and detailed description of many nuclear properties
International Nuclear Information System (INIS)
Pery, Emilie
2007-01-01
This research activity aims at developing and validating a multimodal spectroscopy method in elastic scattering and auto-fluorescence to characterize biological tissues in vitro and in vivo. It is articulated in four axes. At first, instrumentation is considered with the development, the engineering and the experimental characterization of a fibers bimodal, multi-points spectrometry system allowing the acquisition of spectra in vivo (variable distances, fast acquisition). Secondly, the optical properties of tissues are modelled with the development and the experimental validation on phantoms of a photons propagation simulation algorithm in turbid media and multi-fluorescent. Thirdly, an experimental study has been conducted ex vivo on fresh and cryo-preserved arterial rings. It confirms the complementarity of spectroscopic measurements in elastic scattering and auto-fluorescence, and validates the method of multi-modality spectroscopy and the simulation of photons propagation algorithm. Results have well proved a correlation between rheological and optical properties. Finally, one second experimental study in vivo related to a pre-clinical tumoral model of bladder has been carried out. It highlights a significant difference in diffuse reflectance and/or auto-fluorescence and/or intrinsic fluorescence between healthy, inflammatory and tumoral tissues, on the basis of specific wavelength. The results of not supervised classification show that the combination of various spectroscopic approaches increases the reliability of the diagnosis. (author) [fr
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
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.
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.
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.
Stochastic modeling of mode interactions via linear parabolized stability equations
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.
Multisite Interactions in Lattice-Gas Models
Einstein, T. L.; Sathiyanarayanan, R.
For detailed applications of lattice-gas models to surface systems, multisite interactions often play at least as significant a role as interactions between pairs of adatoms that are separated by a few lattice spacings. We recall that trio (3-adatom, non-pairwise) interactions do not inevitably create phase boundary asymmetries about half coverage. We discuss a sophisticated application to an experimental system and describe refinements in extracting lattice-gas energies from calculations of total energies of several different ordered overlayers. We describe how lateral relaxations complicate matters when there is direct interaction between the adatoms, an issue that is important when examining the angular dependence of step line tensions. We discuss the connector model as an alternative viewpoint and close with a brief account of recent work on organic molecule overlayers.
Generalized information fusion and visualization using spatial voting and data modeling
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.
Cranking model and attenuation of Coriolis interaction
International Nuclear Information System (INIS)
Lyutorovich, N.A.
1987-01-01
Description of rotational bands of odd deformed nuclei in the self-consistent Cranking model (SCM) is given. Causes of attenuation of the Coriolis interaction in the nuclei investigated are studied, and account of bound of one-particle degrees of freedom with rotation of the Hartree-Fock-Bogolyubov (HFB) self-consistent method is introduced additionally to SCM for qualitative agreement with experimental data. Merits and shortages of SCM in comparison with the quadruparticle-rotor (QR) model are discussed. All know ways for constructing the Hamiltonian QR model (or analog of such Hamiltonian) on the basis of the microscopic theory are shown to include two more approximations besides others: quasi-particle-rotational interaction leading to pair break is taken into account in the second order of the perturbation theory; some exchange diagrams are neglected among diagrams of the second order according to this interaction. If one makes the same approximations in SCM instead of HFB method, then the dependence of level energies on spin obtained in this case is turned out to be close to the results of the QR model. Besides, the problem on renormalization of matrix elements of quasi-rotational interaction occurs in such nonself-consistent approach as in the QR model. In so far as the similar problem does not occur in SCM, one can make the conclusion that the problem of attenuation of Coriolis interaction involves the approximations given above
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
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
Towards Quantitative Spatial Models of Seabed Sediment Composition.
Directory of Open Access Journals (Sweden)
David Stephens
Full Text Available There is a need for fit-for-purpose maps for accurately depicting the types of seabed substrate and habitat and the properties of the seabed for the benefits of research, resource management, conservation and spatial planning. The aim of this study is to determine whether it is possible to predict substrate composition across a large area of seabed using legacy grain-size data and environmental predictors. The study area includes the North Sea up to approximately 58.44°N and the United Kingdom's parts of the English Channel and the Celtic Seas. The analysis combines outputs from hydrodynamic models as well as optical remote sensing data from satellite platforms and bathymetric variables, which are mainly derived from acoustic remote sensing. We build a statistical regression model to make quantitative predictions of sediment composition (fractions of mud, sand and gravel using the random forest algorithm. The compositional data is analysed on the additive log-ratio scale. An independent test set indicates that approximately 66% and 71% of the variability of the two log-ratio variables are explained by the predictive models. A EUNIS substrate model, derived from the predicted sediment composition, achieved an overall accuracy of 83% and a kappa coefficient of 0.60. We demonstrate that it is feasible to spatially predict the seabed sediment composition across a large area of continental shelf in a repeatable and validated way. We also highlight the potential for further improvements to the method.
Assessing fit in Bayesian models for spatial processes
Jun, M.
2014-09-16
© 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models\\' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.
Assessing fit in Bayesian models for spatial processes
Jun, M.; Katzfuss, M.; Hu, J.; Johnson, V. E.
2014-01-01
© 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.
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.
Interactive wood combustion for botanical tree models
Pirk, Sören
2017-11-22
We present a novel method for the combustion of botanical tree models. Tree models are represented as connected particles for the branching structure and a polygonal surface mesh for the combustion. Each particle stores biological and physical attributes that drive the kinetic behavior of a plant and the exothermic reaction of the combustion. Coupled with realistic physics for rods, the particles enable dynamic branch motions. We model material properties, such as moisture and charring behavior, and associate them with individual particles. The combustion is efficiently processed in the surface domain of the tree model on a polygonal mesh. A user can dynamically interact with the model by initiating fires and by inducing stress on branches. The flames realistically propagate through the tree model by consuming the available resources. Our method runs at interactive rates and supports multiple tree instances in parallel. We demonstrate the effectiveness of our approach through numerous examples and evaluate its plausibility against the combustion of real wood samples.
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
Modeling spin magnetization transport in a spatially varying magnetic field
Picone, Rico A. R.; Garbini, Joseph L.; Sidles, John A.
2015-01-01
We present a framework for modeling the transport of any number of globally conserved quantities in any spatial configuration and apply it to obtain a model of magnetization transport for spin-systems that is valid in new regimes (including high-polarization). The framework allows an entropy function to define a model that explicitly respects the laws of thermodynamics. Three facets of the model are explored. First, it is expressed as nonlinear partial differential equations that are valid for the new regime of high dipole-energy and polarization. Second, the nonlinear model is explored in the limit of low dipole-energy (semi-linear), from which is derived a physical parameter characterizing separative magnetization transport (SMT). It is shown that the necessary and sufficient condition for SMT to occur is that the parameter is spatially inhomogeneous. Third, the high spin-temperature (linear) limit is shown to be equivalent to the model of nuclear spin transport of Genack and Redfield (1975) [1]. Differences among the three forms of the model are illustrated by numerical solution with parameters corresponding to a magnetic resonance force microscopy (MRFM) experiment (Degen et al., 2009 [2]; Kuehn et al., 2008 [3]; Sidles et al., 2003 [4]; Dougherty et al., 2000 [5]). A family of analytic, steady-state solutions to the nonlinear equation is derived and shown to be the spin-temperature analog of the Langevin paramagnetic equation and Curie's law. Finally, we analyze the separative quality of magnetization transport, and a steady-state solution for the magnetization is shown to be compatible with Fenske's separative mass transport equation (Fenske, 1932 [6]).
Modeling of interaction effects in granular systems
International Nuclear Information System (INIS)
El-Hilo, M.; Shatnawy, M.; Al-Rsheed, A.
2000-01-01
Interaction effects on the magnetic behavior of granular solid systems are examined using a numerical model which is capable of predicting the field, temperature and time dependence of magnetization. In this work, interaction effects on the temperature dependence of time viscosity coefficient S(T) and formation of minor hysteresis loops have been studied. The results for the time- and temperature dependence of remanence ratio have showed that the distribution of energy barriers f(ΔE) obtained depend critically on the strength and nature of interactions. These interactions-based changes in f(ΔE) can easily give a temperature-independent behavior of S(T) when these changes give a 1/ΔE behavior to the distribution of energy barriers. Thus, conclusions about macroscopic quantum tunneling must be carefully drawn when the temperature dependence of S(T) is used to probe for MQT effects. For minor hysteresis effects, the result shows that for the non-interacting case, no minor hysteresis loops occur and the loops are only predicted when the interaction field is positive. From these predictions, minor loops will form when the interaction field is strong enough to magnetize some moments during the recoil process back to zero field. Thus, these minor loops are originated from interaction driving irreversible changes along the recoil curve and the irreversible component of magnetization has no direct influence on the formation of these minor loops
Quark interchange model of baryon interactions
Energy Technology Data Exchange (ETDEWEB)
Maslow, J.N.
1983-01-01
The strong interactions at low energy are traditionally described by meson field theories treating hadrons as point-like particles. Here a mesonic quark interchange model (QIM) is presented which takes into account the finite size of the baryons and the internal quark structure of hadrons. The model incorporates the basic quark-gluon coupling of quantum chromodynamics (QCD) and the MIT bag model for color confinement. Because the quark-gluon coupling constant is large and it is assumed that confinement excludes overlap of hadronic quark bags except at high momenta, a non-perturbative method of nuclear interactions is presented. The QIM allows for exchange of quark quantum numbers at the bag boundary between colliding hadrons mediated at short distances by a gluon exchange between two quarks within the hadronic interior. This generates, via a Fierz transformation, an effective space-like t channel exchange of color singlet (q anti-q) states that can be identified with the low lying meson multiplets. Thus, a one boson exchange (OBE) model is obtained that allows for comparison with traditional phenomenological models of nuclear scattering. Inclusion of strange quarks enables calculation of YN scattering. The NN and YN coupling constants and the nucleon form factors show good agreement with experimental values as do the deuteron low energy data and the NN low energy phase shifts. Thus, the QIM provides a simple model of strong interactions that is chirally invariant, includes confinement and allows for an OBE form of hadronic interaction at low energies and momentum transfers.
Quark interchange model of baryon interactions
International Nuclear Information System (INIS)
Maslow, J.N.
1983-01-01
The strong interactions at low energy are traditionally described by meson field theories treating hadrons as point-like particles. Here a mesonic quark interchange model (QIM) is presented which takes into account the finite size of the baryons and the internal quark structure of hadrons. The model incorporates the basic quark-gluon coupling of quantum chromodynamics (QCD) and the MIT bag model for color confinement. Because the quark-gluon coupling constant is large and it is assumed that confinement excludes overlap of hadronic quark bags except at high momenta, a non-perturbative method of nuclear interactions is presented. The QIM allows for exchange of quark quantum numbers at the bag boundary between colliding hadrons mediated at short distances by a gluon exchange between two quarks within the hadronic interior. This generates, via a Fierz transformation, an effective space-like t channel exchange of color singlet (q anti-q) states that can be identified with the low lying meson multiplets. Thus, a one boson exchange (OBE) model is obtained that allows for comparison with traditional phenomenological models of nuclear scattering. Inclusion of strange quarks enables calculation of YN scattering. The NN and YN coupling constants and the nucleon form factors show good agreement with experimental values as do the deuteron low energy data and the NN low energy phase shifts. Thus, the QIM provides a simple model of strong interactions that is chirally invariant, includes confinement and allows for an OBE form of hadronic interaction at low energies and momentum transfers
Toward Accessing Spatial Structure from Building Information Models
Schultz, C.; Bhatt, M.
2011-08-01
Data about building designs and layouts is becoming increasingly more readily available. In the near future, service personal (such as maintenance staff or emergency rescue workers) arriving at a building site will have immediate real-time access to enormous amounts of data relating to structural properties, utilities, materials, temperature, and so on. The critical problem for users is the taxing and error prone task of interpreting such a large body of facts in order to extract salient information. This is necessary for comprehending a situation and deciding on a plan of action, and is a particularly serious issue in time-critical and safety-critical activities such as firefighting. Current unifying building models such as the Industry Foundation Classes (IFC), while being comprehensive, do not directly provide data structures that focus on spatial reasoning and spatial modalities that are required for high-level analytical tasks. The aim of the research presented in this paper is to provide computational tools for higher level querying and reasoning that shift the cognitive burden of dealing with enormous amounts of data away from the user. The user can then spend more energy and time in planning and decision making in order to accomplish the tasks at hand. We present an overview of our framework that provides users with an enhanced model of "built-up space". In order to test our approach using realistic design data (in terms of both scale and the nature of the building models) we describe how our system interfaces with IFC, and we conduct timing experiments to determine the practicality of our approach. We discuss general computational approaches for deriving higher-level spatial modalities by focusing on the example of route graphs. Finally, we present a firefighting scenario with alternative route graphs to motivate the application of our framework.
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
A new spatial multiple discrete-continuous modeling approach to land use change analysis.
2013-09-01
This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...
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.
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
Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study
Energy Technology Data Exchange (ETDEWEB)
Deutsch, Jared L., E-mail: jdeutsch@ualberta.ca [University of Alberta, School of Mining and Petroleum Engineering, Department of Civil and Environmental Engineering (Canada); Palmer, Kevin [Teck Resources Limited (Canada); Deutsch, Clayton V.; Szymanski, Jozef [University of Alberta, School of Mining and Petroleum Engineering, Department of Civil and Environmental Engineering (Canada); Etsell, Thomas H. [University of Alberta, Department of Chemical and Materials Engineering (Canada)
2016-06-15
High-resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively by measured grade and geomechanical properties constitute an important part of geometallurgy. Geostatistical and other numerical techniques are adapted and developed to construct these high-resolution models accounting for all available data. Important issues that must be addressed include unequal sampling of the metallurgical properties versus grade assays, measurements at different scale, and complex nonlinear averaging of many metallurgical parameters. This paper establishes techniques to address each of these issues with the required implementation details and also demonstrates geometallurgical mineral deposit characterization for a copper–molybdenum deposit in South America. High-resolution models of grades and comminution indices are constructed, checked, and are rigorously validated. The workflow demonstrated in this case study is applicable to many other deposit types.
Spatial generalised linear mixed models based on distances.
Melo, Oscar O; Mateu, Jorge; Melo, Carlos E
2016-10-01
Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.
Modelling of molten fuel/concrete interactions
International Nuclear Information System (INIS)
Muir, J.F.; Benjamin, A.S.
1980-01-01
A computer program modelling the interaction between molten core materials and structural concrete (CORCON) is being developed to provide quantitative estimates of fuel-melt accident consequences suitable for risk assessment of light water reactors. The principal features of CORCON are reviewed. Models developed for the principal interaction phenomena, inter-component heat transfer, concrete erosion, and melt/gas chemical reactions, are described. Alternative models for the controlling phenomenon, heat transfer from the molten pool to the surrounding concrete, are presented. These models, formulated in conjunction with the development of CORCON, are characterized by the presence or absence of either a gas film or viscous layer of molten concrete at the melt/concrete interface. Predictions of heat transfer based on these models compare favorably with available experimental data
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
Interactive Visual Analysis within Dynamic Ocean Models
Butkiewicz, T.
2012-12-01
The many observation and simulation based ocean models available today can provide crucial insights for all fields of marine research and can serve as valuable references when planning data collection missions. However, the increasing size and complexity of these models makes leveraging their contents difficult for end users. Through a combination of data visualization techniques, interactive analysis tools, and new hardware technologies, the data within these models can be made more accessible to domain scientists. We present an interactive system that supports exploratory visual analysis within large-scale ocean flow models. The currents and eddies within the models are illustrated using effective, particle-based flow visualization techniques. Stereoscopic displays and rendering methods are employed to ensure that the user can correctly perceive the complex 3D structures of depth-dependent flow patterns. Interactive analysis tools are provided which allow the user to experiment through the introduction of their customizable virtual dye particles into the models to explore regions of interest. A multi-touch interface provides natural, efficient interaction, with custom multi-touch gestures simplifying the otherwise challenging tasks of navigating and positioning tools within a 3D environment. We demonstrate the potential applications of our visual analysis environment with two examples of real-world significance: Firstly, an example of using customized particles with physics-based behaviors to simulate pollutant release scenarios, including predicting the oil plume path for the 2010 Deepwater Horizon oil spill disaster. Secondly, an interactive tool for plotting and revising proposed autonomous underwater vehicle mission pathlines with respect to the surrounding flow patterns predicted by the model; as these survey vessels have extremely limited energy budgets, designing more efficient paths allows for greater survey areas.
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.
Modelling Safe Interface Interactions in Web Applications
Brambilla, Marco; Cabot, Jordi; Grossniklaus, Michael
Current Web applications embed sophisticated user interfaces and business logic. The original interaction paradigm of the Web based on static content pages that are browsed by hyperlinks is, therefore, not valid anymore. In this paper, we advocate a paradigm shift for browsers and Web applications, that improves the management of user interaction and browsing history. Pages are replaced by States as basic navigation nodes, and Back/Forward navigation along the browsing history is replaced by a full-fledged interactive application paradigm, supporting transactions at the interface level and featuring Undo/Redo capabilities. This new paradigm offers a safer and more precise interaction model, protecting the user from unexpected behaviours of the applications and the browser.
Directory of Open Access Journals (Sweden)
Nadine Tinne
Full Text Available The emerging use of femtosecond lasers with high repetition rates in the MHz regime together with limited scan speed implies possible mutual optical and dynamical interaction effects of the individual cutting spots. In order to get more insight into the dynamics a time-resolved photographic analysis of the interaction of cavitation bubbles is presented. Particularly, we investigated the influence of fs-laser pulses and their resulting bubble dynamics with various spatial as well as temporal separations. Different time courses of characteristic interaction effects between the cavitation bubbles were observed depending on pulse energy and spatio-temporal pulse separation. These ranged from merely no interaction to the phenomena of strong water jet formation. Afterwards, the mechanisms are discussed regarding their impact on the medical application of effective tissue cutting lateral to the laser beam direction with best possible axial precision: the mechanical forces of photodisruption as well as the occurring water jet should have low axial extend and a preferably lateral priority. Furthermore, the overall efficiency of energy conversion into controlled mechanical impact should be maximized compared to the transmitted pulse energy and unwanted long range mechanical side effects, e.g. shock waves, axial jet components. In conclusion, these experimental results are of great importance for the prospective optimization of the ophthalmic surgical process with high-repetition rate fs-lasers.
High-precision spatial localization of mouse vocalizations during social interaction.
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.
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.
Large-scale changes in network interactions as a physiological signature of spatial neglect.
Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L; Callejas, Alicia; Astafiev, Serguei V; Metcalf, Nicholas V; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z; Carter, Alex R; Shulman, Gordon L; Corbetta, Maurizio
2014-12-01
networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
An alternative to the standard spatial econometric approaches in hedonic house price models
DEFF Research Database (Denmark)
von Graevenitz, Kathrine; Panduro, Toke Emil
2015-01-01
Omitted, misspecified, or mismeasured spatially varying characteristics are a cause for concern in hedonic house price models. Spatial econometrics or spatial fixed effects have become popular ways of addressing these concerns. We discuss the limitations of standard spatial approaches to hedonic...
New aspects of the interacting boson model
International Nuclear Information System (INIS)
Nadzakov, E.G.; Mikhajlov, I.N.
1987-01-01
In the framework of the boson space extension called interacting multiboson model: conserving the model basic dynamic symmetries, the s p d f boson model is considered. It does not destruct the intermediate mass nuclei simple description, and at the same time includes the number of levels and transitions, inaccessible to the usual s d boson model. Its applicability, even in a brief version, to the recently observed asymmetric nuclear shape effect in the Ra-Th-U region (and in other regions) with possible octupole and dipole deformation is demonstrated. It is done by reproducing algebraically the yrast lines of nuclei with vibrational, transitional and rotational spectra
A Biophysical Neural Model To Describe Spatial Visual Attention
International Nuclear Information System (INIS)
Hugues, Etienne; Jose, Jorge V.
2008-01-01
Visual scenes have enormous spatial and temporal information that are transduced into neural spike trains. Psychophysical experiments indicate that only a small portion of a spatial image is consciously accessible. Electrophysiological experiments in behaving monkeys have revealed a number of modulations of the neural activity in special visual area known as V4, when the animal is paying attention directly towards a particular stimulus location. The nature of the attentional input to V4, however, remains unknown as well as to the mechanisms responsible for these modulations. We use a biophysical neural network model of V4 to address these issues. We first constrain our model to reproduce the experimental results obtained for different external stimulus configurations and without paying attention. To reproduce the known neuronal response variability, we found that the neurons should receive about equal, or balanced, levels of excitatory and inhibitory inputs and whose levels are high as they are in in vivo conditions. Next we consider attentional inputs that can induce and reproduce the observed spiking modulations. We also elucidate the role played by the neural network to generate these modulations
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.
Directory of Open Access Journals (Sweden)
M. Liu
2013-11-01
Full Text Available Topography exerts influence on the spatial precipitation distribution over different scales, known typically at the large scale as the orographic effect, and at the small scale as the wind-drift rainfall (WDR effect. At the intermediate scale (1~10 km, which is characterized by secondary mountain valleys, topography also demonstrates some effect on the precipitation pattern. This paper investigates such intermediate-scale topographic effects on precipitation patterns, focusing on narrow-steep valleys in the complex terrain of southern Germany, based on the daily observations over a 48 yr period (1960~2007 from a high-density rain-gauge network covering two sub-areas, Baden-Wuerttemberg (BW and Bavaria (BY. Precipitation data at the valley and non-valley stations are compared under consideration of the daily general circulation patterns (CPs classified by a fuzzy rule-based algorithm. Scatter plots of precipitation against elevation demonstrate a different behavior of valley stations comparing to non-valley stations. A detailed study of the precipitation time series for selected station triplets, each consisting of a valley station, a mountain station and an open station have been investigated by statistical analysis with the Kolmogorov–Smirnov (KS test supplemented by the One-way analysis of variance (One-way ANOVA and a graphical comparison of the mean precipitation amounts. The results show an interaction of valley orientation and the direction of the CPs at the intermediate scale, i.e. when the valley is shielded from the CP which carries the precipitation, the precipitation amount within the valley is comparable to that on the mountain crest, and both larger than the precipitation at the open station. When the valley is open to the CP, the precipitation within the valley is similar to the open station but much less than that on the mountain. Such phenomenon where the precipitation is "blind" to the valleys at the intermediate scale
Modelling hadronic interactions in HEP MC generators
Skands, Peter
2015-01-01
HEP event generators aim to describe high-energy collisions in full exclusive detail. They combine perturbative matrix elements and parton showers with dynamical models of less well-understood phenomena such as hadronization, diffraction, and the so-called underlying event. We briefly summarise some of the main concepts relevant to the modelling of soft/inclusive hadron interactions in MC generators, in particular PYTHIA, with emphasis on questions recently highlighted by LHC data.
Interacting dark energy model and thermal stability
Energy Technology Data Exchange (ETDEWEB)
Bhandari, Pritikana; Haldar, Sourav; Chakraborty, Subenoy [Jadavpur University, Department of Mathematics, Kolkata, West Bengal (India)
2017-12-15
In the background of the homogeneous and isotropic FLRW model, the thermodynamics of the interacting DE fluid is investigated in the present work. By studying the thermodynamical parameters, namely the heat capacities and the compressibilities, both thermal and mechanical stability are discussed and the restrictions on the equation of state parameter of the dark fluid are analyzed. (orig.)
Intuitionistic preference modeling and interactive decision making
Xu, Zeshui
2014-01-01
This book offers an in-depth and comprehensive introduction to the priority methods of intuitionistic preference relations, the consistency and consensus improving procedures for intuitionistic preference relations, the approaches to group decision making based on intuitionistic preference relations, the approaches and models for interactive decision making with intuitionistic fuzzy information, and the extended results in interval-valued intuitionistic fuzzy environments.
QSO evolution in the interaction model
International Nuclear Information System (INIS)
De Robertis, M.
1985-01-01
QSO evolution is investigated according to the interaction hypothesis described most recently by Stockton (1982), in which activity results from an interaction between two galaxies resulting in the transfer of gas onto a supermassive black hole (SBH) at the center of at least one participant. Explicit models presented here for interactions in cluster environments show that a peak QSO population can be formed in this way at zroughly-equal2--3, with little activity prior to this epoch. Calculated space densities match those inferred from observations for this epoch. Substantial density evolution is expected in such models, since, after virialization, conditions in the cores of rich clusters lead to the depletion of gas-rich systems through ram-pressure stripping. Density evolution parameters of 6--12 are easily accounted for. At smaller redshifts, however, QSOs should be found primarily in poor clusters or groups. Probability estimates provided by this model are consistent with local estimates for the observed number of QSOs per interaction. Significant luminosity-dependent evolution might also be expected in these models. It is suggested that the mean SBH mass increases with lookback time, leading to a statistical brightening with redshift. Undoubtedly, both forms of evolution contribute to the overall QSO luminosity function
Sphericity in the interacting boson model
International Nuclear Information System (INIS)
Ogata, H.
1977-01-01
The interacting boson model (IBM) of Arima and Iachello is examined. The transition between the rotational and vibrational modes of even-even nuclei is presented as a function of a sphericity parameter, which is determined primarily from yrast band spectra. The backbending feature is reasonably reproduced. (author)
Electron scattering in the interacting boson model
International Nuclear Information System (INIS)
Dieperink, A.E.L.; Iachello, F.; Creswell, C.
1978-01-01
It is suggested that the interacting boson model be used in the analysis of electron scattering data. Qualitative features of the expected behavior of the inelastic excitation of some 2 + states in the transitional Sm-Nd region are discussed. (Auth.)
Interacting dark energy model and thermal stability
International Nuclear Information System (INIS)
Bhandari, Pritikana; Haldar, Sourav; Chakraborty, Subenoy
2017-01-01
In the background of the homogeneous and isotropic FLRW model, the thermodynamics of the interacting DE fluid is investigated in the present work. By studying the thermodynamical parameters, namely the heat capacities and the compressibilities, both thermal and mechanical stability are discussed and the restrictions on the equation of state parameter of the dark fluid are analyzed. (orig.)
A fashion model with social interaction
Nakayama, Shoichiro; Nakamura, Yasuyuki
2004-06-01
In general, it is difficult to investigate social phenomena mathematically or quantitatively due to non-linear interactions. Statistical physics can provide powerful methods for studying social phenomena with interactions, and could be very useful for them. In this study, we take a focus on fashion as a social phenomenon with interaction. The social interaction considered here are “bandwagon effect” and “snob effect.” In the bandwagon effect, the correlation between one's behavior and others is positive. People feel fashion weary or boring when it is overly popular. This is the snob effect. It is assumed that the fashion phenomenon is formed by the aggregation of individual's binary choice, that is, the fashion is adopted or not. We formulate the fashion phenomenon as the logit model, which is based on the random utility theory in social science, especially economics. The model derived here basically has the similarity with the pioneering model by Weidlich (Phys. Rep. 204 (1991) 1), which was derived from the master equation, the Langevin equation, or the Fokker-Planck equation. This study seems to give the behavioral or behaviormetrical foundation to his model. As a result of dynamical analysis, it is found that in the case that both the bandwagon effect and the snob effect work, periodic or chaotic behavior of fashion occurs under certain conditions.
Directory of Open Access Journals (Sweden)
Yamini Kashimshetty
Full Text Available Tropical lowland rain forest (TLRF biodiversity is under threat from anthropogenic factors including deforestation which creates forest fragments of different sizes that can further undergo various internal patterns of logging. Such interventions can modify previous equilibrium abundance and spatial distribution patterns of offspring recruitment and/or pollen dispersal. Little is known about how these aspects of deforestation and fragmentation might synergistically affect TLRF tree recovery demographics and population genetics in newly formed forest fragments. To investigate these TLRF anthropogenic disturbance processes we used the computer program NEWGARDEN (NG, which models spatially-explicit, individual-based plant populations, to simulate 10% deforestation in six different spatial logging patterns for the plant functional type of a long-lived TLRF canopy tree species. Further, each logging pattern was analyzed under nine varying patterns of offspring versus pollen dispersal distances that could have arisen post-fragmentation. Results indicated that gene dispersal condition (especially via offspring had a greater effect on population growth and genetic diversity retention (explaining 98.5% and 88.8% of the variance respectively than spatial logging pattern (0.2% and 4.7% respectively, with 'Near' distance dispersal maximizing population growth and genetic diversity relative to distant dispersal. Within logged regions of the fragment, deforestation patterns closer to fragment borders more often exhibited lower population recovery rates and founding genetic diversity retention relative to more centrally located logging. These results suggest newly isolated fragments have populations that are more sensitive to the way in which their offspring and pollen dispersers are affected than the spatial pattern in which subsequent logging occurs, and that large variation in the recovery rates of different TLRF tree species attributable to altered gene
Kashimshetty, Yamini; Pelikan, Stephan; Rogstad, Steven H
2015-01-01
Tropical lowland rain forest (TLRF) biodiversity is under threat from anthropogenic factors including deforestation which creates forest fragments of different sizes that can further undergo various internal patterns of logging. Such interventions can modify previous equilibrium abundance and spatial distribution patterns of offspring recruitment and/or pollen dispersal. Little is known about how these aspects of deforestation and fragmentation might synergistically affect TLRF tree recovery demographics and population genetics in newly formed forest fragments. To investigate these TLRF anthropogenic disturbance processes we used the computer program NEWGARDEN (NG), which models spatially-explicit, individual-based plant populations, to simulate 10% deforestation in six different spatial logging patterns for the plant functional type of a long-lived TLRF canopy tree species. Further, each logging pattern was analyzed under nine varying patterns of offspring versus pollen dispersal distances that could have arisen post-fragmentation. Results indicated that gene dispersal condition (especially via offspring) had a greater effect on population growth and genetic diversity retention (explaining 98.5% and 88.8% of the variance respectively) than spatial logging pattern (0.2% and 4.7% respectively), with 'Near' distance dispersal maximizing population growth and genetic diversity relative to distant dispersal. Within logged regions of the fragment, deforestation patterns closer to fragment borders more often exhibited lower population recovery rates and founding genetic diversity retention relative to more centrally located logging. These results suggest newly isolated fragments have populations that are more sensitive to the way in which their offspring and pollen dispersers are affected than the spatial pattern in which subsequent logging occurs, and that large variation in the recovery rates of different TLRF tree species attributable to altered gene dispersal
Fundamental Frequency and Model Order Estimation Using Spatial Filtering
DEFF Research Database (Denmark)
Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2014-01-01
extend this procedure to account for inharmonicity using unconstrained model order estimation. The simulations show that beamforming improves the performance of the joint estimates of fundamental frequency and the number of harmonics in low signal to interference (SIR) levels, and an experiment......In signal processing applications of harmonic-structured signals, estimates of the fundamental frequency and number of harmonics are often necessary. In real scenarios, a desired signal is contaminated by different levels of noise and interferers, which complicate the estimation of the signal...... parameters. In this paper, we present an estimation procedure for harmonic-structured signals in situations with strong interference using spatial filtering, or beamforming. We jointly estimate the fundamental frequency and the constrained model order through the output of the beamformers. Besides that, we...
Estimation of spatial uncertainties of tomographic velocity models
Energy Technology Data Exchange (ETDEWEB)
Jordan, M.; Du, Z.; Querendez, E. [SINTEF Petroleum Research, Trondheim (Norway)
2012-12-15
This research project aims to evaluate the possibility of assessing the spatial uncertainties in tomographic velocity model building in a quantitative way. The project is intended to serve as a test of whether accurate and specific uncertainty estimates (e.g., in meters) can be obtained. The project is based on Monte Carlo-type perturbations of the velocity model as obtained from the tomographic inversion guided by diagonal and off-diagonal elements of the resolution and the covariance matrices. The implementation and testing of this method was based on the SINTEF in-house stereotomography code, using small synthetic 2D data sets. To test the method the calculation and output of the covariance and resolution matrices was implemented, and software to perform the error estimation was created. The work included the creation of 2D synthetic data sets, the implementation and testing of the software to conduct the tests (output of the covariance and resolution matrices which are not implicitly provided by stereotomography), application to synthetic data sets, analysis of the test results, and creating the final report. The results show that this method can be used to estimate the spatial errors in tomographic images quantitatively. The results agree with' the known errors for our synthetic models. However, the method can only be applied to structures in the model, where the change of seismic velocity is larger than the predicted error of the velocity parameter amplitudes. In addition, the analysis is dependent on the tomographic method, e.g., regularization and parameterization. The conducted tests were very successful and we believe that this method could be developed further to be applied to third party tomographic images.
Gulland, E.-K.; Veenendaal, B.; Schut, A. G. T.
2012-07-01
Problem-solving knowledge and skills are an important attribute of spatial sciences graduates. The challenge of higher education is to build a teaching and learning environment that enables students to acquire these skills in relevant and authentic applications. This study investigates the effectiveness of traditional face-to-face teaching and online learning technologies in supporting the student learning of problem-solving and computer programming skills, techniques and solutions. The student cohort considered for this study involves students in the surveying as well as geographic information science (GISc) disciplines. Also, students studying across a range of learning modes including on-campus, distance and blended, are considered in this study. Student feedback and past studies reveal a lack of student interest and engagement in problem solving and computer programming. Many students do not see such skills as directly relevant and applicable to their perceptions of what future spatial careers hold. A range of teaching and learning methods for both face-to-face teaching and distance learning were introduced to address some of the perceived weaknesses of the learning environment. These included initiating greater student interaction in lectures, modifying assessments to provide greater feedback and student accountability, and the provision of more interactive and engaging online learning resources. The paper presents and evaluates the teaching methods used to support the student learning environment. Responses of students in relation to their learning experiences were collected via two anonymous, online surveys and these results were analysed with respect to student pass and retention rates. The study found a clear distinction between expectations and engagement of surveying students in comparison to GISc students. A further outcome revealed that students who were already engaged in their learning benefited the most from the interactive learning resources and
Directory of Open Access Journals (Sweden)
E.-K. Gulland
2012-07-01
Full Text Available Problem-solving knowledge and skills are an important attribute of spatial sciences graduates. The challenge of higher education is to build a teaching and learning environment that enables students to acquire these skills in relevant and authentic applications. This study investigates the effectiveness of traditional face-to-face teaching and online learning technologies in supporting the student learning of problem-solving and computer programming skills, techniques and solutions. The student cohort considered for this study involves students in the surveying as well as geographic information science (GISc disciplines. Also, students studying across a range of learning modes including on-campus, distance and blended, are considered in this study. Student feedback and past studies reveal a lack of student interest and engagement in problem solving and computer programming. Many students do not see such skills as directly relevant and applicable to their perceptions of what future spatial careers hold. A range of teaching and learning methods for both face-to-face teaching and distance learning were introduced to address some of the perceived weaknesses of the learning environment. These included initiating greater student interaction in lectures, modifying assessments to provide greater feedback and student accountability, and the provision of more interactive and engaging online learning resources. The paper presents and evaluates the teaching methods used to support the student learning environment. Responses of students in relation to their learning experiences were collected via two anonymous, online surveys and these results were analysed with respect to student pass and retention rates. The study found a clear distinction between expectations and engagement of surveying students in comparison to GISc students. A further outcome revealed that students who were already engaged in their learning benefited the most from the interactive
Spatial attention interacts with serial-order retrieval from verbal working memory.
van Dijck, Jean-Philippe; Abrahamse, Elger L; Majerus, Steve; Fias, Wim
2013-09-01
The ability to maintain the serial order of events is recognized as a major function of working memory. Although general models of working memory postulate a close link between working memory and attention, such a link has so far not been proposed specifically for serial-order working memory. The present study provided the first empirical demonstration of a direct link between serial order in verbal working memory and spatial selective attention. We show that the retrieval of later items of a sequence stored in working memory-compared with that of earlier items-produces covert attentional shifts toward the right. This observation suggests the conceptually surprising notion that serial-order working memory, even for nonspatially defined verbal items, draws on spatial attention.
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 hierarchical spatial model of avian abundance with application to Cerulean Warblers
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
Parameterizing the Spatial Markov Model From Breakthrough Curve Data Alone
Sherman, Thomas; Fakhari, Abbas; Miller, Savannah; Singha, Kamini; Bolster, Diogo
2017-12-01
The spatial Markov model (SMM) is an upscaled Lagrangian model that effectively captures anomalous transport across a diverse range of hydrologic systems. The distinct feature of the SMM relative to other random walk models is that successive steps are correlated. To date, with some notable exceptions, the model has primarily been applied to data from high-resolution numerical simulations and correlation effects have been measured from simulated particle trajectories. In real systems such knowledge is practically unattainable and the best one might hope for is breakthrough curves (BTCs) at successive downstream locations. We introduce a novel methodology to quantify velocity correlation from BTC data alone. By discretizing two measured BTCs into a set of arrival times and developing an inverse model, we estimate velocity correlation, thereby enabling parameterization of the SMM in studies where detailed Lagrangian velocity statistics are unavailable. The proposed methodology is applied to two synthetic numerical problems, where we measure all details and thus test the veracity of the approach by comparison of estimated parameters with known simulated values. Our results suggest that our estimated transition probabilities agree with simulated values and using the SMM with this estimated parameterization accurately predicts BTCs downstream. Our methodology naturally allows for estimates of uncertainty by calculating lower and upper bounds of velocity correlation, enabling prediction of a range of BTCs. The measured BTCs fall within the range of predicted BTCs. This novel method to parameterize the SMM from BTC data alone is quite parsimonious, thereby widening the SMM's practical applicability.
Understanding and modelling Man-Machine Interaction
International Nuclear Information System (INIS)
Cacciabue, P.C.
1991-01-01
This paper gives an overview of the current state of the art in man machine systems interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to design and analysis of Man-Machine Interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans and their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (author)
Understanding and modelling man-machine interaction
International Nuclear Information System (INIS)
Cacciabue, P.C.
1996-01-01
This paper gives an overview of the current state of the art in man-machine system interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to the design and analysis of man-machine interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans an their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (orig.)
Selective 4D modelling framework for spatial-temporal land information management system
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.
Geometrical analysis of the interacting boson model
International Nuclear Information System (INIS)
Dieperink, A.E.L.
1983-01-01
The Interacting Boson Model is considered, in relation with geometrical models and the application of mean field techniques to algebraic models, in three lectures. In the first, several methods are reviewed to establish a connection between the algebraic formulation of collective nuclear properties in terms of the group SU(6) and the geometric approach. In the second lecture the geometric interpretation of new degrees of freedom that arise in the neutron-proton IBA is discussed, and in the third one some further applications of algebraic techniques to the calculation of static and dynamic collective properties are presented. (U.K.)
Localisation in a Growth Model with Interaction
Costa, M.; Menshikov, M.; Shcherbakov, V.; Vachkovskaia, M.
2018-05-01
This paper concerns the long term behaviour of a growth model describing a random sequential allocation of particles on a finite cycle graph. The model can be regarded as a reinforced urn model with graph-based interaction. It is motivated by cooperative sequential adsorption, where adsorption rates at a site depend on the configuration of existing particles in the neighbourhood of that site. Our main result is that, with probability one, the growth process will eventually localise either at a single site, or at a pair of neighbouring sites.
Infection dynamics on spatial small-world network models
Iotti, Bryan; Antonioni, Alberto; Bullock, Seth; Darabos, Christian; Tomassini, Marco; Giacobini, Mario
2017-11-01
The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks. We propose a model, called REDS, that extends energy-constrained RGGs to account for the synergic effect of sharing the cost of a link with our neighbors, as is observed in real relational networks. We apply both the standard Watts-Strogatz rewiring procedure and another method that conserves the degree distribution of the network. The second technique was developed to eliminate unwanted forms of spatial correlation between the degree of nodes that are affected by rewiring, limiting the effect on other properties such as clustering and assortativity. We analyze both the statistical properties of these two network types and their epidemiological behavior when used as a substrate for a standard susceptible-infected-susceptible compartmental model. We consider and discuss the differences in properties and behavior between RGGs and REDS as rewiring increases and as infection parameters are changed. We report considerable differences both between the network types and, in the case of REDS, between the two rewiring schemes. We conclude that REDS represent, with the application of these rewiring mechanisms, extremely useful and interesting tools in the study of social and epidemiological phenomena in synthetic complex networks.
Impact of self interaction on the evolution of cooperation in social spatial dilemmas
International Nuclear Information System (INIS)
Ding, Chenxi; Wang, Juan; Zhang, Ying
2016-01-01
Highlights: • A self interaction mechanism is integrated into two classical game models (PDG and SDG). • An additional payoff will be awarded into the cooperative agents for the payoff calculation. • Beyond the fixed interaction strength, distributed interaction strength is considered. • The collective cooperation can be drastically elevated into a higher level. - Abstract: In this paper, a new self interaction mechanism is integrated into two typical pairwise models including the prisoner’s dilemma and snowdrift games, where an additional payoff will be awarded into the cooperative agents. In the prisoner’s dilemma game, we take three types of additional payoffs into account, to be a fixed constant, a random value situated within the positive unilateral interval and a random one uniformly distributed within a bilateral interval. Large quantities of numerical simulations indicate the promotion of cooperation can be very noticeable whether in the case of von Neumann neighborhood or Moore neighborhood. In the meantime, the self interaction will also be extended into the snowdrift game in which two equilibria exist, and the outcomes clearly show that the collective cooperation is still drastically elevated into a higher level. Current results demonstrate that the self interaction might become a potential and effective means to enhance the behavior of cooperation, and be helpful for us to deeply understand the widespread persistence and emergence of cooperation within many animal and human being societies.
Spatial Distribution of Hydrologic Ecosystem Service Estimates: Comparing Two Models
Dennedy-Frank, P. J.; Ghile, Y.; Gorelick, S.; Logsdon, R. A.; Chaubey, I.; Ziv, G.
2014-12-01
We compare estimates of the spatial distribution of water quantity provided (annual water yield) from two ecohydrologic models: the widely-used Soil and Water Assessment Tool (SWAT) and the much simpler water models from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) toolbox. These two models differ significantly in terms of complexity, timescale of operation, effort, and data required for calibration, and so are often used in different management contexts. We compare two study sites in the US: the Wildcat Creek Watershed (2083 km2) in Indiana, a largely agricultural watershed in a cold aseasonal climate, and the Upper Upatoi Creek Watershed (876 km2) in Georgia, a mostly forested watershed in a temperate aseasonal climate. We evaluate (1) quantitative estimates of water yield to explore how well each model represents this process, and (2) ranked estimates of water yield to indicate how useful the models are for management purposes where other social and financial factors may play significant roles. The SWAT and InVEST models provide very similar estimates of the water yield of individual subbasins in the Wildcat Creek Watershed (Pearson r = 0.92, slope = 0.89), and a similar ranking of the relative water yield of those subbasins (Spearman r = 0.86). However, the two models provide relatively different estimates of the water yield of individual subbasins in the Upper Upatoi Watershed (Pearson r = 0.25, slope = 0.14), and very different ranking of the relative water yield of those subbasins (Spearman r = -0.10). The Upper Upatoi watershed has a significant baseflow contribution due to its sandy, well-drained soils. InVEST's simple seasonality terms, which assume no change in storage over the time of the model run, may not accurately estimate water yield processes when baseflow provides such a strong contribution. Our results suggest that InVEST users take care in situations where storage changes are significant.
Is a matrix exponential specification suitable for the modeling of spatial correlation structures?
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.
Iachini, Tina; Pagliaro, Stefano; Ruggiero, Gennaro
2015-10-01
Near body distance is a key component of action and social interaction. Recent research has shown that peripersonal space (reachability-distance for acting with objects) and interpersonal space (comfort-distance for interacting with people) share common mechanisms and reflect the social valence of stimuli. The social psychological literature has demonstrated that information about morality is crucial because it affects impression formation and the intention to approach-avoid others. Here we explore whether peripersonal/interpersonal spaces are modulated by moral information. Thirty-six participants interacted with male/female virtual confederates described by moral/immoral/neutral sentences. The modulation of body space was measured by reachability-distance and comfort-distance while participants stood still or walked toward virtual confederates. Results showed that distance expanded with immorally described confederates and contracted with morally described confederates. This pattern was present in both spaces, although it was stronger in comfort-distance. Consistent with an embodied cognition approach, the findings suggest that high-level socio-cognitive processes are linked to sensorimotor-spatial processes. Copyright © 2015. Published by Elsevier B.V.
Directory of Open Access Journals (Sweden)
Yuwei Wang
2018-01-01
Full Text Available Grassland ecosystems worldwide are confronted with degradation. It is of great importance to understand long-term trajectory patterns of grassland vegetation by advanced analytical models. This study proposes a new approach called a binary logistic regression model with neighborhood interactions, or BLR-NIs, which is based on binary logistic regression (BLR, but fully considers the spatio-temporally localized spatial associations or characterization of neighborhood interactions (NIs in the patterns of grassland vegetation. The BLR-NIs model was applied to a modeled vegetation degradation of grasslands in the Xilin river basin, Inner Mongolia, China. Residual trend analysis on the normalized difference vegetation index (RESTREND-NDVI, which excluded the climatic impact on vegetation dynamics, was adopted as a preprocessing step to derive three human-induced trajectory patterns (vegetation degradation, vegetation recovery, and no significant change in vegetation during two consecutive periods, T1 (2000–2008 and T2 (2007–2015. Human activities, including livestock grazing intensity and transportation accessibility measured by road network density, were included as explanatory variables for vegetation degradation, which was defined for locations if vegetation recovery or no significant change in vegetation in T1 and vegetation degradation in T2 were observed. Our work compared the results of BLR-NIs and the traditional BLR model that did not consider NIs. The study showed that: (1 both grazing intensity and road density had a positive correlation to vegetation degradation based on the traditional BLR model; (2 only road density was found to positively correlate to vegetation degradation by the BLR-NIs model; NIs appeared to be critical factors to predict vegetation degradation; and (3 including NIs in the BLR model improved the model performance substantially. The study provided evidence for the importance of including localized spatial
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.
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.
Modelling temporal and spatial dynamics of benthic fauna in North-West-European shelf seas
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
Spatial Modeling of Risk in Natural Resource Management
Directory of Open Access Journals (Sweden)
Peter Jones
2002-01-01
Full Text Available Making decisions in natural resource management involves an understanding of the risk and uncertainty of the outcomes, such as crop failure or cattle starvation, and of the normal spread of the expected production. Hedging against poor outcomes often means lack of investment and slow adoption of new methods. At the household level, production instability can have serious effects on income and food security. At the national level, it can have social and economic impacts that may affect all sectors of society. Crop models such as CERES-Maize are excellent tools for assessing weather-related production variability. WATBAL is a water balance model that can provide robust estimates of the potential growing days for a pasture. These models require large quantities of daily weather data that are rarely available. MarkSim is an application for generating synthetic daily weather files by estimating the third-order Markov model parameters from interpolated climate surfaces. The models can then be run for each distinct point on the map. This paper examines the growth of maize and pasture in dryland agriculture in southern Africa. Weather simulators produce independent estimates for each point on the map; however, we know that a spatial coherence of weather exists. We investigated a method of incorporating spatial coherence into MarkSim and show that it increases the variance of production. This means that all of the farmers in a coherent area share poor yields, with important consequences for food security, markets, transport, and shared grazing lands. The long-term aspects of risk are associated with global climate change. We used the results of a Global Circulation Model to extrapolate to the year 2055. We found that low maize yields would become more likely in the marginal areas, whereas they may actually increase in some areas. The same trend was found with pasture growth. We outline areas where further work is required before these tools and methods
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
The lack of spatial soil erosion data has been a major constraint on the refinement and application of physically based erosion models. Spatially distributed models can only be thoroughly validated with distributed erosion data. The fallout cesium-137 has been widely used to generate spatial soil re...
Lessons learned for spatial modelling of ecosystem services in support of ecosystem accounting
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
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.
Ostoja, Steven M.; Schupp, Eugene W.; Klinger, Rob
2013-01-01
Granivore foraging decisions affect consumer success and determine the quantity and spatial pattern of seed survival. These decisions are influenced by environmental variation at spatial scales ranging from landscapes to local foraging patches. In a field experiment, the effects of seed patch variation across three spatial scales on seed removal by western harvester ants Pogonomyrmex occidentalis were evaluated. At the largest scale we assessed harvesting in different plant communities, at the intermediate scale we assessed harvesting at different distances from ant mounds, and at the smallest scale we assessed the effects of interactions among seed species in local seed neighborhoods on seed harvesting (i.e. resource–consumer interface). Selected seed species were presented alone (monospecific treatment) and in mixture with Bromus tectorum (cheatgrass; mixture treatment) at four distances from P. occidentalis mounds in adjacent intact sagebrush and non-native cheatgrass-dominated communities in the Great Basin, Utah, USA. Seed species differed in harvest, with B. tectorum being least preferred. Large and intermediate scale variation influenced harvest. More seeds were harvested in sagebrush than in cheatgrass-dominated communities (largest scale), and the quantity of seed harvested varied with distance from mounds (intermediate-scale), although the form of the distance effect differed between plant communities. At the smallest scale, seed neighborhood affected harvest, but the patterns differed among seed species considered. Ants harvested fewer seeds from mixed-seed neighborhoods than from monospecific neighborhoods, suggesting context dependence and potential associational resistance. Further, the effects of plant community and distance from mound on seed harvest in mixtures differed from their effects in monospecific treatments. Beyond the local seed neighborhood, selection of seed resources is better understood by simultaneously evaluating removal at
Unemployment estimation: Spatial point referenced methods and models
Pereira, Soraia
2017-06-26
Portuguese Labor force survey, from 4th quarter of 2014 onwards, started geo-referencing the sampling units, namely the dwellings in which the surveys are carried. This opens new possibilities in analysing and estimating unemployment and its spatial distribution across any region. The labor force survey choose, according to an preestablished sampling criteria, a certain number of dwellings across the nation and survey the number of unemployed in these dwellings. Based on this survey, the National Statistical Institute of Portugal presently uses direct estimation methods to estimate the national unemployment figures. Recently, there has been increased interest in estimating these figures in smaller areas. Direct estimation methods, due to reduced sampling sizes in small areas, tend to produce fairly large sampling variations therefore model based methods, which tend to
Spatial Fleming-Viot models with selection and mutation
Dawson, Donald A
2014-01-01
This book constructs a rigorous framework for analysing selected phenomena in evolutionary theory of populations arising due to the combined effects of migration, selection and mutation in a spatial stochastic population model, namely the evolution towards fitter and fitter types through punctuated equilibria. The discussion is based on a number of new methods, in particular multiple scale analysis, nonlinear Markov processes and their entrance laws, atomic measure-valued evolutions and new forms of duality (for state-dependent mutation and multitype selection) which are used to prove ergodic theorems in this context and are applicable for many other questions and renormalization analysis for a variety of phenomena (stasis, punctuated equilibrium, failure of naive branching approximations, biodiversity) which occur due to the combination of rare mutation, mutation, resampling, migration and selection and make it necessary to mathematically bridge the gap (in the limit) between time and space scales.
Evolution of altruism in spatial prisoner's dilemma: Intra- and inter-cellular interactions
Yokoi, Hiroki; Uehara, Takashi; Sakata, Tomoyuki; Naito, Hiromi; Morita, Satoru; Tainaka, Kei-ichi
2014-12-01
Iterated prisoner's dilemma game is carried out on lattice with “colony” structure. Each cell is regarded as a colony which contains plural players with an identical strategy. Both intra- and inter-cellular interactions are assumed. In the former a player plays with all other players in the same colony, while in the latter he plays with one player each from adjacent colonies. Spatial patterns among four typical strategies exhibit various dynamics and winners. Both theory and simulation reveal that All Cooperation (AC) wins, when the members of colony or the intensity of noise increases. This result explains the evolution of altruism in animal societies, even though errors easily occur in animal communications.
Nadell, Carey D; Ricaurte, Deirdre; Yan, Jing; Drescher, Knut; Bassler, Bonnie L
2017-01-13
Bacteria often live in biofilms, which are microbial communities surrounded by a secreted extracellular matrix. Here, we demonstrate that hydrodynamic flow and matrix organization interact to shape competitive dynamics in Pseudomonas aeruginosa biofilms. Irrespective of initial frequency, in competition with matrix mutants, wild-type cells always increase in relative abundance in planar microfluidic devices under simple flow regimes. By contrast, in microenvironments with complex, irregular flow profiles - which are common in natural environments - wild-type matrix-producing and isogenic non-producing strains can coexist. This result stems from local obstruction of flow by wild-type matrix producers, which generates regions of near-zero shear that allow matrix mutants to locally accumulate. Our findings connect the evolutionary stability of matrix production with the hydrodynamics and spatial structure of the surrounding environment, providing a potential explanation for the variation in biofilm matrix secretion observed among bacteria in natural environments.
Comet 73P Measurements of Solar Wind Interactions, Cometary Ion Pickup, and Spatial Distribution
Gilbert, J. A.; Lepri, S. T.; Rubin, M.; Combi, M. R.; Zurbuchen, T.
2015-12-01
Several fragments of Comet 73P/Schwassmann-Wachmann 3 passed near the Earth following a 2006 disintegration episode. Unique measurements regarding the charge state composition and the elemental abundances of both cometary and heliospheric plasma were made during this time by both the ACE/SWICS and Wind/STICS sensors. As the solar wind passed through the neutral cometary coma, it experienced charge exchange that was observed as an increase in the ratio of He+/He++. In addition, particles originating from fragments trailing the major cometary objects were ionized and picked up by the solar wind. The cometary material can be identified by the concentrations of water-group pickup ions having a mass-per-charge ratio of 16-18 amu/e, indicating that these are actively sublimating fragments. Here we present an analysis of cometary composition, spatial distribution, directionality, and heliospheric interactions with a focus on Helium, Carbon (C/O), and water-group ions.
Havens, Scott; Marks, Danny; Kormos, Patrick; Hedrick, Andrew
2017-12-01
In the Western US and many mountainous regions of the world, critical water resources and climate conditions are difficult to monitor because the observation network is generally very sparse. The critical resource from the mountain snowpack is water flowing into streams and reservoirs that will provide for irrigation, flood control, power generation, and ecosystem services. Water supply forecasting in a rapidly changing climate has become increasingly difficult because of non-stationary conditions. In response, operational water supply managers have begun to move from statistical techniques towards the use of physically based models. As we begin to transition physically based models from research to operational use, we must address the most difficult and time-consuming aspect of model initiation: the need for robust methods to develop and distribute the input forcing data. In this paper, we present a new open source framework, the Spatial Modeling for Resources Framework (SMRF), which automates and simplifies the common forcing data distribution methods. It is computationally efficient and can be implemented for both research and operational applications. We present an example of how SMRF is able to generate all of the forcing data required to a run physically based snow model at 50-100 m resolution over regions of 1000-7000 km2. The approach has been successfully applied in real time and historical applications for both the Boise River Basin in Idaho, USA and the Tuolumne River Basin in California, USA. These applications use meteorological station measurements and numerical weather prediction model outputs as input. SMRF has significantly streamlined the modeling workflow, decreased model set up time from weeks to days, and made near real-time application of a physically based snow model possible.
Modeling of interaction effects in granular systems
El-Hilo, M; Al-Rsheed, A
2000-01-01
Interaction effects on the magnetic behavior of granular solid systems are examined using a numerical model which is capable of predicting the field, temperature and time dependence of magnetization. In this work, interaction effects on the temperature dependence of time viscosity coefficient S(T) and formation of minor hysteresis loops have been studied. The results for the time- and temperature dependence of remanence ratio have showed that the distribution of energy barriers f(DELTA E) obtained depend critically on the strength and nature of interactions. These interactions-based changes in f(DELTA E) can easily give a temperature-independent behavior of S(T) when these changes give a 1/DELTA E behavior to the distribution of energy barriers. Thus, conclusions about macroscopic quantum tunneling must be carefully drawn when the temperature dependence of S(T) is used to probe for MQT effects. For minor hysteresis effects, the result shows that for the non-interacting case, no minor hysteresis loops occur an...
Discrete Variational Approach for Modeling Laser-Plasma Interactions
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.
A two-particle exchange interaction model
International Nuclear Information System (INIS)
Lyubina, Julia; Mueller, Karl-Hartmut; Wolf, Manfred; Hannemann, Ullrich
2010-01-01
The magnetisation reversal of two interacting particles was investigated within a simple model describing exchange coupling of magnetically uniaxial single-domain particles. Depending on the interaction strength W, the reversal may be cooperative or non-cooperative. A non-collinear reversal mode is obtained even for two particles with parallel easy axes. The model yields different phenomena as observed in spring magnets such as recoil hysteresis in the second quadrant of the field-magnetisation-plane, caused by exchange bias, as well as the mentioned reversal-rotation mode. The Wohlfarth's remanence analysis performed on aggregations of such pairs of interacting particles shows that the deviation δM(H m ) usually being considered as a hallmark of magnetic interaction vanishes for all maximum applied fields H m not only at W=0, but also for sufficiently large values of W. Furthermore, this so-called δM-plot depends on whether the sample is ac-field or thermally demagnetised.
A two-particle exchange interaction model
Energy Technology Data Exchange (ETDEWEB)
Lyubina, Julia, E-mail: j.lyubina@ifw-dresden.d [IFW Dresden, Institute for Metallic Materials, P.O. Box 270016, D-01171 Dresden (Germany); Mueller, Karl-Hartmut; Wolf, Manfred; Hannemann, Ullrich [IFW Dresden, Institute for Metallic Materials, P.O. Box 270016, D-01171 Dresden (Germany)
2010-10-15
The magnetisation reversal of two interacting particles was investigated within a simple model describing exchange coupling of magnetically uniaxial single-domain particles. Depending on the interaction strength W, the reversal may be cooperative or non-cooperative. A non-collinear reversal mode is obtained even for two particles with parallel easy axes. The model yields different phenomena as observed in spring magnets such as recoil hysteresis in the second quadrant of the field-magnetisation-plane, caused by exchange bias, as well as the mentioned reversal-rotation mode. The Wohlfarth's remanence analysis performed on aggregations of such pairs of interacting particles shows that the deviation {delta}M(H{sub m}) usually being considered as a hallmark of magnetic interaction vanishes for all maximum applied fields H{sub m} not only at W=0, but also for sufficiently large values of W. Furthermore, this so-called {delta}M-plot depends on whether the sample is ac-field or thermally demagnetised.
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.
Grazi, F.; van den Bergh, J.C.J.M.; Rietveld, P.
2007-01-01
A welfare framework for the analysis of the spatial dimensions of sustainability is developed. It covers agglomeration effects, interregional trade, negative environmental externalities, and various land use categories. The model is used to compare rankings of spatial configurations according to
Motion Model Employment using interacting Motion Model Algorithm
DEFF Research Database (Denmark)
Hussain, Dil Muhammad Akbar
2006-01-01
The paper presents a simulation study to track a maneuvering target using a selective approach in choosing Interacting Multiple Models (IMM) algorithm to provide a wider coverage to track such targets. Initially, there are two motion models in the system to track a target. Probability of each m...
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....
The backbone of a City Information Model (CIM) : Implementing a spatial data model for urban design
Gil, J.A.; Almeida, J.; Duarte, J.P.
2011-01-01
We have been witnessing an increased interest in a more holistic approach to urban design practice and education. In this paper we present a spatial data model for urban design that proposes the combination of urban environment feature classes with design process feature classes. This data model is
Microscopic foundation of the interacting boson model
International Nuclear Information System (INIS)
Arima, Akito
1994-01-01
A microscopic foundation of the interacting boson model is described. The importance of monopole and quadrupole pairs of nucleons is emphasized. Those pairs are mapped onto the s and d bosons. It is shown that this mapping provides a good approximation in vibrational and transitional nuclei. In appendix, it is shown that the monopole pair of electrons plays possibly an important role in metal clusters. (orig.)
Interactive Procedural Modelling of Coherent Waterfall Scenes
Emilien , Arnaud; Poulin , Pierre; Cani , Marie-Paule; Vimont , Ulysse
2015-01-01
International audience; Combining procedural generation and user control is a fundamental challenge for the interactive design of natural scenery. This is particularly true for modelling complex waterfall scenes where, in addition to taking charge of geometric details, an ideal tool should also provide a user with the freedom to shape the running streams and falls, while automatically maintaining physical plausibility in terms of flow network, embedding into the terrain, and visual aspects of...
Extending Primitive Spatial Data Models to Include Semantics
Reitsma, F.; Batcheller, J.
2009-04-01
Our traditional geospatial data model involves associating some measurable quality, such as temperature, or observable feature, such as a tree, with a point or region in space and time. When capturing data we implicitly subscribe to some kind of conceptualisation. If we can make this explicit in an ontology and associate it with the captured data, we can leverage formal semantics to reason with the concepts represented in our spatial data sets. To do so, we extend our fundamental representation of geospatial data in a data model by including a URI in our basic data model that links it to our ontology defining our conceptualisation, We thus extend Goodchild et al's geo-atom [1] with the addition of a URI: (x, Z, z(x), URI) . This provides us with pixel or feature level knowledge and the ability to create layers of data from a set of pixels or features that might be drawn from a database based on their semantics. Using open source tools, we present a prototype that involves simple reasoning as a proof of concept. References [1] M.F. Goodchild, M. Yuan, and T.J. Cova. Towards a general theory of geographic representation in gis. International Journal of Geographical Information Science, 21(3):239-260, 2007.
SeiVis: An interactive visual subsurface modeling application
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
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.
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.
Modeling Users' Experiences with Interactive Systems
Karapanos, Evangelos
2013-01-01
Over the past decade the field of Human-Computer Interaction has evolved from the study of the usability of interactive products towards a more holistic understanding of how they may mediate desired human experiences. This book identifies the notion of diversity in usersʼ experiences with interactive products and proposes methods and tools for modeling this along two levels: (a) interpersonal diversity in usersʽ responses to early conceptual designs, and (b) the dynamics of usersʼ experiences over time. The Repertory Grid Technique is proposed as an alternative to standardized psychometric scales for modeling interpersonal diversity in usersʼ responses to early concepts in the design process, and new Multi-Dimensional Scaling procedures are introduced for modeling such complex quantitative data. iScale, a tool for the retrospective assessment of usersʼ experiences over time is proposed as an alternative to longitudinal field studies, and a semi-automated technique for the analysis of the elicited exper...
Oil transformation sector modelling: price interactions
International Nuclear Information System (INIS)
Maurer, A.
1992-01-01
A global oil and oil product prices evolution model is proposed that covers the transformation sector incidence and the final user price establishment together with price interactions between gaseous and liquid hydrocarbons. High disparities among oil product prices in the various consumer zones (North America, Western Europe, Japan) are well described and compared with the low differences between oil supply prices in these zones. Final user price fluctuations are shown to be induced by transformation differences and competition; natural gas market is also modelled
Spatial and Temporal Self-Calibration of a Hydroeconomic Model
Howitt, R. E.; Hansen, K. M.
2008-12-01
across key nodes on the network and to annual carryover storage at ground and surface water storage facilities. To our knowledge, this is the first hydroeconomic model to perform spatial and temporal calibration simultaneously. The base for the LFN model is CALVIN, a hydroeconomic optimization model of the California water system developed at the University of California, Davis (Draper, et al. 2003). The LFN model, programmed in GAMS, is nonlinear, which permits incorporation of dynamic groundwater pumping costs that reflect head elevation. Hydropower production, also nonlinear in storage levels, could be added in the future. In this paper, we describe model implementation and performance over a sequence of water years drawn from the historical hydrologic record in California. Preliminary findings indicate that calibration occurs within acceptable limits and simulations replicate base case results well. Cai, X., and Wang, D. 2006. "Calibrating Holistic Water Resources-Economic Models." Journal of Water Resources Planning and Management November-December. Draper, A.J., M.W. Jenkins, K.W. Kirby, J.R. Lund, and R.E. Howitt. 2003. "Economic-Engineering Optimization for California Water Management." Journal of Water Resources Planning and Management 129(3):155-164. Howitt, R.E. 1995. "Positive Mathematical Programming." American Journal of Agricultural Economics 77:329-342. Howitt, R.E. 1998. "Self-Calibrating Network Flow Models." Working Paper, Department of Agricultural and Resource Economics, University of California, Davis. October 1998. class="ab'>
Sang, Huiyan; Jun, Mikyoung; Huang, Jianhua Z.
2011-01-01
This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models
Modeling of intracerebral interictal epileptic discharges: Evidence for network interactions.
Meesters, Stephan; Ossenblok, Pauly; Colon, Albert; Wagner, Louis; Schijns, Olaf; Boon, Paul; Florack, Luc; Fuster, Andrea
2018-06-01
The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. A network approach is promising in case of complex epilepsies. Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Kinetic Models for Topological Nearest-Neighbor Interactions
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.
Image-based quantification and mathematical modeling of spatial heterogeneity in ESC colonies.
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.
Broms, Kristin M; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L
2014-03-01
Determining the range of a species and exploring species--habitat associations are central questions in ecology and can be answered by analyzing presence--absence data. Often, both the sampling of sites and the desired area of inference involve neighboring sites; thus, positive spatial autocorrelation between these sites is expected. Using survey data for the Southern Ground Hornbill (Bucorvus leadbeateri) from the Southern African Bird Atlas Project, we compared advantages and disadvantages of three increasingly complex models for species occupancy: an occupancy model that accounted for nondetection but assumed all sites were independent, and two spatial occupancy models that accounted for both nondetection and spatial autocorrelation. We modeled the spatial autocorrelation with an intrinsic conditional autoregressive (ICAR) model and with a restricted spatial regression (RSR) model. Both spatial models can readily be applied to any other gridded, presence--absence data set using a newly introduced R package. The RSR model provided the best inference and was able to capture small-scale variation that the other models did not. It showed that ground hornbills are strongly dependent on protected areas in the north of their South African range, but less so further south. The ICAR models did not capture any spatial autocorrelation in the data, and they took an order, of magnitude longer than the RSR models to run. Thus, the RSR occupancy model appears to be an attractive choice for modeling occurrences at large spatial domains, while accounting for imperfect detection and spatial autocorrelation.
Accounting for spatial effects in land use regression for urban air pollution modeling.
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.
Hoffmann, H.; Zhao, G.; Bussel, van L.G.J.
2015-01-01
Field-scale crop models are often applied at spatial resolutions coarser than that of the arable field. However, little is known about the response of the models to spatially aggregated climate input data and why these responses can differ across models. Depending on the model, regional yield