Spatial interactions in agent-based modeling
Ausloos, Marcel; Merlone, Ugo
2014-01-01
Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or directly with each other. In such an approach, higher-order variables such as commodity prices, population dynamics or even institutions, are not exogenously specified but instead are seen as the results of interactions. It is highlighted in the chapter that the understanding of patterns emerging from such spatial interaction between agents is a key problem as much as their description through analytical or simulation means. The chapter reviews different approaches for modeling agents' behavior, taking into account either explicit spatial (lattice based) structures or networks. Some emphasis is placed on recent ABM as applied to the description of the dynamics of the geographical distribution o...
Isard's contributions to spatial interaction modeling
O'Kelly, M. E.
. This short review, surveys Isard's role in promoting what has become known as spatial interaction modeling. Some contextual information on the milieu from which his work emerged is given, together with a selected number of works that are judged to have been influenced (directly and indirectly) by his work. It is suggested that this burgeoning field owes a lot to the foundations laid in the gravity model chapter of ``Methods''. The review is supplemented by a rather extensive bibliography of additional works that are indicative of the breadth of the impact of this field.
Estimation of exposure to toxic releases using spatial interaction modeling
Directory of Open Access Journals (Sweden)
Conley Jamison F
2011-03-01
Full Text Available Abstract Background The United States Environmental Protection Agency's Toxic Release Inventory (TRI data are frequently used to estimate a community's exposure to pollution. However, this estimation process often uses underdeveloped geographic theory. Spatial interaction modeling provides a more realistic approach to this estimation process. This paper uses four sets of data: lung cancer age-adjusted mortality rates from the years 1990 through 2006 inclusive from the National Cancer Institute's Surveillance Epidemiology and End Results (SEER database, TRI releases of carcinogens from 1987 to 1996, covariates associated with lung cancer, and the EPA's Risk-Screening Environmental Indicators (RSEI model. Results The impact of the volume of carcinogenic TRI releases on each county's lung cancer mortality rates was calculated using six spatial interaction functions (containment, buffer, power decay, exponential decay, quadratic decay, and RSEI estimates and evaluated with four multivariate regression methods (linear, generalized linear, spatial lag, and spatial error. Akaike Information Criterion values and P values of spatial interaction terms were computed. The impacts calculated from the interaction models were also mapped. Buffer and quadratic interaction functions had the lowest AIC values (22298 and 22525 respectively, although the gains from including the spatial interaction terms were diminished with spatial error and spatial lag regression. Conclusions The use of different methods for estimating the spatial risk posed by pollution from TRI sites can give different results about the impact of those sites on health outcomes. The most reliable estimates did not always come from the most complex methods.
A spatial interaction model with spatially structured origin and destination effects
LeSage, James P.; Llano, Carlos
2013-07-01
We introduce a Bayesian hierarchical regression model that extends the traditional least-squares regression model used to estimate gravity or spatial interaction relations involving origin-destination flows. Spatial interaction models attempt to explain variation in flows from n origin regions to n destination regions resulting in a sample of N = n 2 observations that reflect an n by n flow matrix converted to a vector. Explanatory variables typically include origin and destination characteristics as well as distance between each region and all other regions. Our extension introduces latent spatial effects parameters structured to follow a spatial autoregressive process. Individual effects parameters are included in the model to reflect latent or unobservable influences at work that are unique to each region treated as an origin and destination. That is, we estimate 2 n individual effects parameters using the sample of N = n 2 observations. We illustrate the method using a sample of commodity flows between 18 Spanish regions during the 2002 period.
Combining microsimulation and spatial interaction models for retail location analysis
Nakaya, Tomoki; Fotheringham, A. Stewart; Hanaoka, Kazumasa; Clarke, Graham; Ballas, Dimitris; Yano, Keiji
2007-12-01
Although the disaggregation of consumers is crucial in understanding the fragmented markets that are dominant in many developed countries, it is not always straightforward to carry out such disaggregation within conventional retail modelling frameworks due to the limitations of data. In particular, consumer grouping based on sampled data is not assured to link with the other statistics that are vital in estimating sampling biases and missing variables in the sampling survey. To overcome this difficulty, we propose a useful combination of spatial interaction modelling and microsimulation approaches for the reliable estimation of retail interactions based on a sample survey of consumer behaviour being linked with other areal statistics. We demonstrate this approach by building an operational retail interaction model to estimate expenditure flows from households to retail stores in a local city in Japan, Kusatsu City.
Modeling complex spatial dynamics of two-population interaction in urbanization process
Chen, Yanguang
2013-01-01
This paper is mainly devoted to lay an empirical foundation for further research on complex spatial dynamics of two-population interaction. Based on the US population census data, a rural and urban population interaction model is developed. Subsequently a logistic equation on percentage urban is derived from the urbanization model so that spatial interaction can be connected mathematically with logistic growth. The numerical experiment by using the discretized urban-rural population interaction model of urbanization shows a period-doubling bifurcation and chaotic behavior, which is identical in patterns to those from the simple mathematical models of logistic growth in ecology. This suggests that the complicated dynamics of logistic growth may come from some kind of the nonlinear interaction. The results from this study help to understand urbanization, urban-rural population interaction, chaotic dynamics, and spatial complexity of geographical systems.
Directory of Open Access Journals (Sweden)
Mark Birkin
2011-01-01
Full Text Available For many years, effective model-based representations of the dynamics and evolution of urban spatial structure have proved elusive. While some progress has been made through the deployment of spatial interaction models, these approaches have been limited by the difficulty of representing behavioural mechanisms and processes. In this paper, it is demonstrated that evolutionary models grounded in the principles of spatial interaction are compatible with the more novel approaches of agent-based modelling. The incorporation of agents provides a much more flexible means for the representation of behavioural mechanisms. The paper illustrates the way in which three more complicated situations can be handled through the fusion of spatial interaction and agent modelling perspectives. These situations comprise discontinuous evolution (in which structural adjustment takes place in discrete steps, and not as a continuously smooth process; nonequilibrium dynamics (in which the underlying system parameters continue to evolve through time; the incorporation of new decision variables (which we illustrate through the addition of land rents into the model. The conclusion of the paper is that the combination of spatial interaction and agent-based modelling methods provides encouraging prospects for the social simulation of real urban systems.
Weak Gravity Conjecture and Holographic Dark Energy Model with Interaction and Spatial Curvature
Institute of Scientific and Technical Information of China (English)
SUN Cheng-Yi
2011-01-01
In the paper, we apply the weak gravity conjecture to the holographic quintessence model of dark energy.Three different holographic dark energy models are considered: without the interaction in the non-flat universe; with interaction in the flat universe; with interaction in the non-flat universe. We find that only in the models with the spatial curvature and interaction term proportional to the energy density of matter, it is possible for the weak gravity conjecture to be satisfied. And it seems that the weak gravity conjecture favors an open universe and the decaying of matter into dark energy.
Dong, Guanpeng; Harris, Richard; Jones, Kelvyn; Yu, Jianhui
2015-01-01
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. PMID:26086913
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.
Calcagno, Cristina; Damiani, Ferruccio; Drocco, Maurizio; Sciacca, Eva; Spinella, Salvatore; Troina, Angelo; 10.4204/EPTCS.67.3
2011-01-01
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 ligh...
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.
Hillenbrand, Patrick; Gerland, Ulrich; Tkačik, Gašper
2016-01-01
A crucial step in the early development of multicellular organisms involves the establishment of spatial patterns of gene expression which later direct proliferating cells to take on different cell fates. These patterns enable the cells to infer their global position within a tissue or an organism by reading out local gene expression levels. The patterning system is thus said to encode positional information, a concept that was formalized recently in the framework of information theory. Here we introduce a toy model of patterning in one spatial dimension, which can be seen as an extension of Wolpert’s paradigmatic “French Flag” model, to patterning by several interacting, spatially coupled genes subject to intrinsic and extrinsic noise. Our model, a variant of an Ising spin system, allows us to systematically explore expression patterns that optimally encode positional information. We find that optimal patterning systems use positional cues, as in the French Flag model, together with gene-gene interactions to generate combinatorial codes for position which we call “Counter” patterns. Counter patterns can also be stabilized against noise and variations in system size or morphogen dosage by longer-range spatial interactions of the type invoked in the Turing model. The simple setup proposed here qualitatively captures many of the experimentally observed properties of biological patterning systems and allows them to be studied in a single, theoretically consistent framework. PMID:27676252
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 ., Forsyth, G., Mans, G. and Hugo, W. (2008) Modeling of spatially complex human-ecosystem, rural-urban snd rich-poor interactions. Paper submitted to International Conference: “Studying, Modelling and Sense Making of Planet Earth”; 1 – 6 June, 2008... human-ecosystem, rural-urban snd rich-poor interactions. Paper submitted to International Conference: “Studying, Modelling and Sense Making of Planet Earth”; 1 – 6 June, 2008, Department of Geography, University of the Aegean. 2 Initially, most...
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 Computational Model of Human-Robot Spatial Interactions Based on a Qualitative Trajectory Calculus
Directory of Open Access Journals (Sweden)
Christian Dondrup
2015-03-01
Full Text Available In this paper we propose a probabilistic sequential model of Human-Robot Spatial Interaction (HRSI using a well-established Qualitative Trajectory Calculus (QTC to encode HRSI between a human and a mobile robot in a meaningful, tractable, and systematic manner. Our key contribution is to utilise QTC as a state descriptor and model HRSI as a probabilistic sequence of such states. Apart from the sole direction of movements of human and robot modelled by QTC, attributes of HRSI like proxemics and velocity profiles play vital roles for the modelling and generation of HRSI behaviour. In this paper, we particularly present how the concept of proxemics can be embedded in QTC to facilitate richer models. To facilitate reasoning on HRSI with qualitative representations, we show how we can combine the representational power of QTC with the concept of proxemics in a concise framework, enriching our probabilistic representation by implicitly modelling distances. We show the appropriateness of our sequential model of QTC by encoding different HRSI behaviours observed in two spatial interaction experiments. We classify these encounters, creating a comparative measurement, showing the representational capabilities of the model.
Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa.
Wesolowski, Amy; O'Meara, Wendy Prudhomme; Eagle, Nathan; Tatem, Andrew J; Buckee, Caroline O
2015-07-01
Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations.
Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa.
Directory of Open Access Journals (Sweden)
Amy Wesolowski
2015-07-01
Full Text Available Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations.
Sheynikhovich, Denis; Arleo, Angelo
2010-12-13
In contrast to predictions derived from the associative learning theory, a number of behavioral studies suggested the absence of competition between geometric cues and landmarks in some experimental paradigms. In parallel to these studies, neurobiological experiments suggested the existence of separate independent memory systems which may not always interact according to classic associative principles. In this paper we attempt to combine these two lines of research by proposing a model of spatial learning that is based on the theory of multiple memory systems. In our model, a place-based locale strategy uses activities of modeled hippocampal place cells to drive navigation to a hidden goal, while a stimulus-response taxon strategy, presumably mediated by the dorso-lateral striatum, learns landmark-approaching behavior. A strategy selection network, proposed to reside in the prefrontal cortex, implements a simple reinforcement learning rule to switch behavioral strategies. The model is used to reproduce the results of a behavioral experiment in which an interaction between a landmark and geometric cues was studied. We show that this model, built on the basis of neurobiological data, can explain the lack of competition between the landmark and geometry, potentiation of geometry learning by the landmark, and blocking. Namely, we propose that the geometry potentiation is a consequence of cooperation between memory systems during learning, while blocking is due to competition between the memory systems during action selection.
Dynamic Panel Data Models Featuring Endogenous Interaction and Spatially Correlated Errors
Jacobs, J.P.A.M.; Ligthart, J.E.; Vrijburg, H.
2009-01-01
We extend the three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian, and Prucha (2007), which corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the dependent variable as additional explanatory variables.
McDonald, Karlie; Mika, Sarah; Kolbe, Tamara; Abbott, Ben; Ciocca, Francesco; Marruedo, Amaia; Hannah, David; Schmidt, Christian; Fleckenstein, Jan; Karuse, Stefan
2016-04-01
Sub-surface hydrologic processes are highly dynamic, varying spatially and temporally with strong links to the geomorphology and hydrogeologic properties of an area. This spatial and temporal complexity is a critical regulator of biogeochemical and ecological processes within the interface groundwater - surface water (GW-SW) ecohydrological interface and adjacent ecosystems. Many GW-SW models have attempted to capture this spatial and temporal complexity with varying degrees of success. The incorporation of spatial and temporal complexity within GW-SW model configuration is important to investigate interactions with transient storage and subsurface geology, infiltration and recharge, and mass balance of exchange fluxes at the GW-SW ecohydrological interface. Additionally, characterising spatial and temporal complexity in GW-SW models is essential to derive predictions using realistic environmental conditions. In this paper we conduct a systematic Web of Science meta-analysis of conceptual, hydrodynamic, and reactive and heat transport models of the GW-SW ecohydrological interface since 2004 to explore how these models handled spatial and temporal complexity. The freshwater - groundwater ecohydrological interface was the most commonly represented in publications between 2004 and 2014 with 91% of papers followed by marine 6% and estuarine systems with 3% of papers. Of the GW-SW models published since 2004, the 52% have focused on hydrodynamic processes and heat and reactive transport). Within the hydrodynamic subset, 25% of models focused on a vertical depth of limitations of incorporating spatial and temporal variability into GW-SW models are identified as the inclusion of woody debris, carbon sources, subsurface geological structures and bioclogging into model parameterization. The technological limitations influence the types of models applied, such as hydrostatic coupled models and fully intrinsic saturated and unsaturated models, and the assumptions or
Spatial experiences and interaction design
DEFF Research Database (Denmark)
Dalsgård, Peter
2006-01-01
IT is rapidly spreading to non-desktop environments, and is increasingly being used for post-functional purposes. Recent contributions within the field of interaction design have indicated a tight coupling between physico-spatial and experiential issues, both on a technological and on a theoretical...... level. However, interaction design and HCI yet has little to offer designers working with physico-spatial and experiential issues in practical design cases. In this paper, I argue that experiments that explore spatial and experiential aspects are crucial in developing the practice of interaction design....... These aspects may be brought to the forefront by engaging in, reflecting upon, and reporting from physico-spatial design experiments, and by making spatial and experience-oriented design representations part of the design process. These experiments may be supported by design representations inspired...
Brown, D
2003-01-01
The analysis follows an earlier paper - Brown (2003) - which analysed a moving disturbance using a directed cyclic graph defined as Interrelated Fluctuating Entities (IFEs) of /STATE/, /SPACE/, /alphaTIME/, /betaTIME/. This paper provides a statistical analysis of the alternative positions in space and state of an IFE for a defined total time magnitude. The probability for a freely moving entity interacting in a particular spatial position is calculated and a formulation is derived for the minimum locus of uncertainty in position and momentum. The model has proven amenable to computer modelling (the assistance of University College London Computer Science department is gratefully acknowledged). A computer model is available on request.
Spatial modelling of brief and long interactions between T cells and dendritic cells.
Beltman, Joost B; Marée, Athanasius F M; de Boer, Rob J
2007-06-01
In the early phases of an immune response, T cells of appropriate antigen specificity become activated by antigen-presenting cells in secondary lymphoid organs. Two-photon microscopy imaging experiments have shown that this stimulation occurs in distinct stages during which T cells exhibit different motilities and interactions with dendritic cells (DCs). In this paper, we utilize the Cellular Potts Model, a model formalism that takes cell shapes and cellular interactions explicitly into account, to simulate the dynamics of, and interactions between, T cells and DCs in the lymph node paracortex. Our three-dimensional simulations suggest that the initial decrease in T-cell motility after antigen appearance is due to "stop signals" transmitted by activated DCs to T cells. The long-lived interactions that occur at a later stage can only be explained by the presence of both stop signals and a high adhesion between specific T cells and antigen-bearing DCs. Furthermore, our results indicate that long-lasting contacts with T cells are promoted when DCs retract dendrites that detect a specific contact at lower velocities than other dendrites. Finally, by performing long simulations (after prior fitting to short time scale data) we are able to provide an estimate of the average contact duration between T cells and DCs.
Shao, Yang
This research focuses on the application of remote sensing, geographic information systems, statistical modeling, and spatial analysis to examine the dynamics of urban land cover, urban structure, and population-environment interactions in Bangkok, Thailand, with an emphasis on rural-to-urban migration from rural Nang Rong District, Northeast Thailand to the primate city of Bangkok. The dissertation consists of four main sections: (1) development of remote sensing image classification and change-detection methods for characterizing imperviousness for Bangkok, Thailand from 1993-2002; (2) development of 3-D urban mapping methods, using high spatial resolution IKONOS satellite images, to assess high-rises and other urban structures; (3) assessment of urban spatial structure from 2-D and 3-D perspectives; and (4) an analysis of the spatial clustering of migrants from Nang Rong District in Bangkok and the neighborhood environments of migrants' locations. Techniques are developed to improve the accuracy of the neural network classification approach for the analysis of remote sensing data, with an emphasis on the spectral unmixing problem. The 3-D building heights are derived using the shadow information on the high-resolution IKONOS image. The results from the 2-D and 3-D mapping are further examined to assess urban structure and urban feature identification. This research contributes to image processing of remotely-sensed images and urban studies. The rural-urban migration process and migrants' settlement patterns are examined using spatial statistics, GIS, and remote sensing perspectives. The results show that migrants' spatial clustering in urban space is associated with the source village and a number of socio-demographic variables. In addition, the migrants' neighborhood environments in urban setting are modeled using a set of geographic and socio-demographic variables, and the results are scale-dependent.
Scherngell, Thomas
2010-01-01
The focus of this study is on cross-region R&D collaboration networks in the EU Framework Programmes (FP's). In contrast to most other empirical studies in this field, we shift attention to regions as units of analysis, i.e. we use aggregated data on research collaborations at the regional level. The objective is to identify determinants of cross-region collaboration patterns. In particular, we are interested whether geographical and technological distances are significant determinants of interregional cooperation. Further we investigate differences between intra-industry networks and public research networks (i.e. universities and research organisations). The European coverage is achieved by using data on 255 NUTS-2 regions of the 25 pre-2007 EU member-states, as well as Norway and Switzerland. We adopt a Poisson spatial interaction modelling perspective to analyse these questions. The dependent variable is the intensity of collaborative interactions between two regions, the independent variables are reg...
Naito, A. T.; Cairns, D. M.; Feldman, R. M.; Grant, W. E.
2014-12-01
Shrub expansion is one of the most recognized components of terrestrial Arctic change. While experimental work has provided valuable insights into its fine-scale drivers and implications, the contribution of shrub reproductive characteristics to their spatial patterns is poorly understood at broader scales. Building upon our previous work in river valleys in northern Alaska, we developed a C#-based spatially-explicit model that simulates historic landscape-scale shrub establishment between the 1970s and the late 2000s on a yearly time-step while accounting for parameters relating to different reproduction modes (clonal development with and without the "mass effect" and short-distance dispersal), as well as the presence and absence of the interaction of hydrologic constraints using the topographic wetness index. We examined these treatments on floodplains, valley slopes, and interfluves in the Ayiyak, Colville, and Kurupa River valleys. After simulating 30 landscape realizations using each parameter combination, we quantified the spatial characteristics (patch density, edge density, patch size variability, area-weighted shape index, area-weighted fractal dimension index, and mean distance between patches) of the resulting shrub patches on the simulation end date using FRAGSTATS. We used Principal Components Analysis to determine which treatments produced spatial characteristics most similar to those observed in the late 2000s. Based upon our results, we hypothesize that historic shrub expansion in northern Alaska has been driven in part by clonal reproduction with the "mass effect" or short-distance dispersal (sexual reproductive strategy, this model may facilitate predictions regarding future Arctic vegetation patterns.
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 ...
Watanabe, Tomoaki; Nagata, Koji
2016-11-01
The mixing volume model (MVM), which is a mixing model for molecular diffusion in Lagrangian simulations of turbulent mixing problems, is proposed based on the interactions among spatially distributed particles in a finite volume. The mixing timescale in the MVM is derived by comparison between the model and the subgrid scale scalar variance equation. A-priori test of the MVM is conducted based on the direct numerical simulations of planar jets. The MVM is shown to predict well the mean effects of the molecular diffusion under various conditions. However, a predicted value of the molecular diffusion term is positively correlated to the exact value in the DNS only when the number of the mixing particles is larger than two. Furthermore, the MVM is tested in the hybrid implicit large-eddy-simulation/Lagrangian-particle-simulation (ILES/LPS). The ILES/LPS with the present mixing model predicts well the decay of the scalar variance in planar jets. This work was supported by JSPS KAKENHI Nos. 25289030 and 16K18013. The numerical simulations presented in this manuscript were carried out on the high performance computing system (NEC SX-ACE) in the Japan Agency for Marine-Earth Science and Technology.
Erfanifard, Y.; Khosravi, E.
2015-12-01
Evaluating the interactions of woody plants has been a major research topic of ecological investigations in arid ecosystems. Plant-plant interactions can shift from positive (facilitation) to negative (competition) depending on levels of environmental stress and determine the spatial pattern of plants. The spatial distribution analysis of plants via different summary statistics can reveal the interactions of plants and how they influence one another. An aggregated distribution indicates facilitative interactions among plants, while dispersion of species reflects their competition for scarce resources. This study was aimed to explore the intraspecific interactions of eshnan (Seidlitzia rosmarinus) shrubs in arid lands, central Iran, using different summary statistics (i.e., pair correlation function g(r), O-ring function O(r), nearest neighbour distribution function D(r), spherical contact distribution function Hs(r)). The observed pattern of shrubs showed significant spatial heterogeneity as compared to inhomogeneous Poisson process (α=0.05). The results of g(r) and O(r) revealed the significant aggregation of eshnan shrubs up to scale of 3 m (α=0.05). The results of D(r) and Hs(r) also showed that maximum distance to nearest shrub was 6 m and the distribution of the sizes of gaps was significantly different from random distribution up to this spatial scale. In general, it was concluded that there were positive interactions between eshnan shrubs at small scales and they were aggregated due to their intraspecific facilitation effects in the study area.
Scherngell, Thomas; 10.1111/j.1435-5957.2008.00215.x
2010-01-01
The last few years have witnessed an increasing interest in the geography of innovation. As noted by Autant-Bernard et al. (2007a), the geographical dimension of innovation deserves further attention by analysing such phenomena as R&D collaborations. In this study we focus on cross-region R&D collaborations in Europe. The European coverage is achieved by using data on collaborative R&D projects funded by the EU Framework Programmes (FPs) between organisation that are located in 255 NUTS-2 regions of the 25 pre-2007 EU member-states, as well as Norway and Switzerland. The objective is to identify separation effects - such as geographical or technological effects - on the constitution of cross-region collaborative R&D activities. We specify a Poisson spatial interaction model to analyse these questions. The dependent variable is the intensity of cross-region R&D collaborations, the independent variables include origin, destination and separation characteristics of interaction. The results pr...
Mobile Spatial Tools for Fluid Interaction
Isenberg, Tobias; Nix, Simon; Schwarz, Martin; Miede, André; Scott, Stacey D.; Carpendale, Sheelagh
2007-01-01
Fluid interaction techniques are increasingly important for effective work on interactive displays such as tabletops. We introduce mobile spatial tools to support such fluid interaction by affecting the properties of objects in the interface spatially rather than temporally. Our tools allow us to co
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.
Anibas, Christian; Debele Tolche, Abebe; Ghysels, Gert; Schneidewind, Uwe; Nossent, Jiri; Touhidul Mustafa, Syed Md; Huysmans, Marijke; Batelaan, Okke
2017-04-01
The quantification of groundwater-surface water interaction is an important challenge for hydrologists and ecologists. Within the last decade, many new analytical and numerical estimation methods have been developed, including heat tracer techniques. In a number of publications, their sources of errors were investigated, and future directions for the research in groundwater-surface water exchange were discussed. To improve our respective knowledge of the Belgian lowland Aa River we reinvestigate temperature data which was gathered in the river bed and used for the quantification of the 1D vertical groundwater-surface water exchange. By assuming a thermal steady state of the river bed temperature distribution, Anibas et al. (2011) were unable to use the full potential of the entire large data set. The analysis tool STRIVE is modified to use the river water temperature time series as the upper model boundary. This transient thermal set up overcomes many of the limitations of the steady state assumption and allows for the analysis of vertical 1D exchange fluxes in space and time. Results of about 380 transient simulations covering a period of more than 1.5 years show high absolute changes in exchange fluxes in the upstream part of the river. However, in the downstream part, the relative changes in fluxes are larger. The 26 spatially distributed thermal profiles along the river reach are interpolated using kriging based on variograms calculated from the temperature dataset. Results indicate gaining conditions for most locations and most of the time. Few places in the downstream part show losing conditions in late winter and early spring. While in autumn and winter the mean exchange fluxes can be -90 mmd-1, in spring to early summer fluxes are only -42 mmd-1. The river bed near the banks shows elevated fluxes compared to the center of the river. Probably driven by regional groundwater flow, the river bed near the left and right bank shows fluxes respectively a factor 3
Halu, Arda; Bianconi, Ginestra
2013-01-01
Spatial networks range from the brain networks, to transportation networks and infrastructures. Recently interacting and multiplex networks are attracting great attention because their dynamics and robustness cannot be understood without treating at the same time several networks. Here we present maximal entropy ensembles of spatial multiplex and spatial interacting networks that can be used in order to model spatial multilayer network structures and to build null models of real datasets. We show that spatial multiplex naturally develop a significant overlap of the links, a noticeable property of many multiplexes that can affect significantly the dynamics taking place on them. Additionally, we characterize ensembles of spatial interacting networks and we analyse the structure of interacting airport and railway networks in India, showing the effect of space in determining the link probability.
Interaction of spatial photorefractive solitons
DEFF Research Database (Denmark)
Królikowski, W.; Denz, C.; Stepken, A.
1998-01-01
beam or the complete annihilation of some of them, depending on the relative phase of the interacting beams. In the case of mutually incoherent solitons, we show that the photorefractive nonlinearity leads to an anomalous interaction between solitons. Theoretical and experimental results reveal...... that a soliton pair may experience both attractive and repulsive forces; depending on their mutual separation. We also show that strong attraction leads to periodic collision or helical motion of solitons depending on initial conditions....
Detto, Matteo; Muller-Landau, Helene C
2016-12-01
Spatial interactions are widely acknowledged to play a significant role in sustaining diversity in ecological communities. However, theoretical work on this topic has focused on how spatial processes affect coexistence of species that differ in their strategies, with less attention to how spatial processes matter when competitors are equivalent. Furthermore, though it is recognized that models with local dispersal and local competition may sustain higher diversities of equivalent competitors than models in which these are not both localized, there is debate as to whether this reflects merely equalizing effects or whether there is also a stabilizing component. In this study, we explore how dispersal limitation and nonspecific local competition influence the outcome of species coexistence in communities driven by stochastic drift. We demonstrate that space alone acts as a stabilizing factor in a continuous space model with local dispersal and competition, as individuals of rare species on average experience lower total neighborhood densities, causing per capita reproductive rates to decrease systematically with increasing abundance. These effects prolong time to extinction in a closed system and enhance species diversity in an open system with constant immigration. Fundamentally, these stabilizing effects are obtained when dispersal limitation interacts with local competition to generate fluctuations in population growth rates. Thus this effect can be considered a fluctuating mechanism similar to spatial or temporal storage effects, but generated purely endogenously without requiring any exogenous environmental variability or species dissimilarities.
SIMULATION MODELING SLOW SPATIALLY HETER- OGENEOUS COAGULATION
Directory of Open Access Journals (Sweden)
P. A. Zdorovtsev
2013-01-01
Full Text Available A new model of spatially inhomogeneous coagulation, i.e. formation of larger clusters by joint interaction of smaller ones, is under study. The results of simulation are compared with known analytical and numerical solutions.
Life stages: interactions and spatial patterns.
Robertson, Suzanne L; Cushing, J M; Costantino, R F
2012-02-01
In many stage-structured species, different life stages often occupy separate spatial niches in a heterogeneous environment. Life stages of the giant flour beetle Tribolium brevicornis (Leconte), in particular adults and pupae, occupy different locations in a homogeneous habitat. This unique spatial pattern does not occur in the well-studied stored grain pests T. castaneum (Herbst) and T. confusum (Duval). We propose density dependent dispersal as a causal mechanism for this spatial pattern. We model and explore the spatial dynamics of T. brevicornis with a set of four density dependent integrodifference and difference equations. The spatial model exhibits multiple attractors: a spatially uniform attractor and a patchy attractor with pupae and adults spatially separated. The model attractors are consistent with experimental observations.
Gürsoy, Gamze; Xu, Yun
2017-01-01
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. PMID:28704374
Directory of Open Access Journals (Sweden)
Charreire Hélène
2011-01-01
Full Text Available Abstract Background There is growing interest in the study of the relationships between individual health-related behaviours (e.g. food intake and physical activity and measurements of spatial accessibility to the associated facilities (e.g. food outlets and sport facilities. The aim of this study is to propose measurements of spatial accessibility to facilities on the regional scale, using aggregated data. We first used a potential accessibility model that partly makes it possible to overcome the limitations of the most frequently used indices such as the count of opportunities within a given neighbourhood. We then propose an extended model in order to take into account both home and work-based accessibility for a commuting population. Results Potential accessibility estimation provides a very different picture of the accessibility levels experienced by the population than the more classical "number of opportunities per census tract" index. The extended model for commuters increases the overall accessibility levels but this increase differs according to the urbanisation level. Strongest increases are observed in some rural municipalities with initial low accessibility levels. Distance to major urban poles seems to play an essential role. Conclusions Accessibility is a multi-dimensional concept that should integrate some aspects of travel behaviour. Our work supports the evidence that the choice of appropriate accessibility indices including both residential and non-residential environmental features is necessary. Such models have potential implications for providing relevant information to policy-makers in the field of public health.
KING GEORGE ISLAND SPATIAL DATA MODEL
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Distribution,interoperability,interactivity,component are four main features of distributed GIS.Based on the principle of hypermap,hypermedia and distributed database,the paper comes up with a kind of distributed spatial data model which is in accordance with those features of distributed GIS.The model takes catalog service as the outline of spatial information globalization,and defines data structure of hypermap node in different level.Based on the model,it is feasible to manage and process distributed spatial information,and integrate multi_source,heterogeneous spatial data into a framework.Traditionally,to retrieve and access spatial data via Internet is only by theme or map name.With the concept of the model,it is possible to retrieve,load,and link spatial data by vector_based graphics on the Internet.
Multisensory Interactions across Spatial Location and Temporal Synchrony
Directory of Open Access Journals (Sweden)
Ryan A Stevenson
2011-10-01
Full Text Available The process of integrating information across sensory modalities is highly dependent upon a number of stimulus characteristics, including spatial and temporal coincidence, as well as effectiveness. Typically, these properties have been studied in isolation, but recent evidence suggests that they are interactive. This study focuses on interactions between the spatial location and temporal synchrony of stimuli. Participants were presented with simple audiovisual in parametrically varied locations, and with parametrically varied stimulus onset asynchronies (SOAs. Participants performed spatial location and perceived simultaneity tasks (PSS. Accuracies and response times were measured. Accuracies of spatial localization were dependent upon spatial location, with no effect of SOA and interaction seen, however, RT analysis showed an effect of SOA and an interaction; more peripheral presentations showed greater slowing of RT in asynchronous conditions, and fewer violations of the race model. With the PSS tasks, effects of SOA and spatial location were found in the responses, as well as an interaction between the two. Peripheral stimuli were more likely to be judged as synchronous, a difference seen particularly with long SOAs. These results suggest that the commonly studied principles of integration are indeed interactive, and that these interactions have measureable behavioral implications.
Building dynamic spatial environmental models
Karssenberg, D.J.
2003-01-01
An environmental model is a representation or imitation of complex natural phenomena that can be discerned by human cognitive processes. This thesis deals with the type of environmental models referred to as dynamic spatial environmental models. The word spatial refers to the geographic domain whi
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
Spatial Models and Networks of Living Systems
DEFF Research Database (Denmark)
Juul, Jeppe Søgaard
. Such systems are known to be stabilized by spatial structure. Finally, I analyse data from a large mobile phone network and show that people who are topologically close in the network have similar communication patterns. This main part of the thesis is based on six different articles, which I have co...... variables of the system. However, this approach disregards any spatial structure of the system, which may potentially change the behaviour drastically. An alternative approach is to construct a cellular automaton with nearest neighbour interactions, or even to model the system as a complex network...... with interactions defined by network topology. In this thesis I first describe three different biological models of ageing and cancer, in which spatial structure is important for the system dynamics. I then turn to describe characteristics of ecosystems consisting of three cyclically interacting species...
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.
Modeling for spatial multilevel structural data
Min, Suqin; He, Xiaoqun
2013-03-01
The traditional multilevel model assumed independence between groups. However, the datasets grouped by geographical units often has spatial dependence. The individual is influenced not only by its region but also by the adjacent regions, and level-2 residual distribution assumption of traditional multilevel model is violated. In order to deal with such spatial multilevel data, we introduce spatial statistics and spatial econometric models into multilevel model, and apply spatial parameters and adjacency matrix in traditional level-2 model to reflect the spatial autocorrelation. Spatial lag model express spatial effects. We build spatial multilevel model which consider both multilevel thinking and spatial correlation.
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...
Interactive Teaching Tools for Spatial Sampling
Directory of Open Access Journals (Sweden)
Adrian Bowman
2010-10-01
Full Text Available The statistical analysis of data which is measured over a spatial region is well established as a scientific tool which makes considerable contributions to a wide variety of application areas. Further development of these tools also remains a central part of the research scene in statistics. However, understanding of the concepts involved often benefits from an intuitive and experimental approach, as well as a formal description of models and methods. This paper describes software which is intended to assist in this understanding. The role of simulation is advocated, in order to explain the meaning of spatial correlation and to interpret the parameters involved in standard models. Realistic scenarios where decisions on the locations of sampling points in a spatial setting are required are also described. Students are provided with a variety of sampling strategies and invited to select the most appropriate one in two different settings. One involves water sampling in the lagoon of the Mururoa Atoll while the other involves sea bed sampling in a Scottish firth. Once a student has decided on a sampling strategy, simulated data are provided for further analysis. This extends the range of teaching activity from the analysis of data collected by others to involvement in data collection and the need to grapple with issues of design. It is argued that this approach has significant benefits in learning.
Spatial Models and Networks of Living Systems
DEFF Research Database (Denmark)
Juul, Jeppe Søgaard
variables of the system. However, this approach disregards any spatial structure of the system, which may potentially change the behaviour drastically. An alternative approach is to construct a cellular automaton with nearest neighbour interactions, or even to model the system as a complex network....... Such systems are known to be stabilized by spatial structure. Finally, I analyse data from a large mobile phone network and show that people who are topologically close in the network have similar communication patterns. This main part of the thesis is based on six different articles, which I have co...
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
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
Spatially varying color distributions for interactive multilabel segmentation.
Nieuwenhuis, Claudia; Cremers, Daniel
2013-05-01
We propose a method for interactive multilabel segmentation which explicitly takes into account the spatial variation of color distributions. To this end, we estimate a joint distribution over color and spatial location using a generalized Parzen density estimator applied to each user scribble. In this way, we obtain a likelihood for observing certain color values at a spatial coordinate. This likelihood is then incorporated in a Bayesian MAP estimation approach to multiregion segmentation which in turn is optimized using recently developed convex relaxation techniques. These guarantee global optimality for the two-region case (foreground/background) and solutions of bounded optimality for the multiregion case. We show results on the GrabCut benchmark, the recently published Graz benchmark, and on the Berkeley segmentation database which exceed previous approaches such as GrabCut, the Random Walker, Santner's approach, TV-Seg, and interactive graph cuts in accuracy. Our results demonstrate that taking into account the spatial variation of color models leads to drastic improvements for interactive image segmentation.
Stochastic spatial models of plant diseases
Brown, D H
2001-01-01
I present three models of plant--pathogen interactions. The models are stochastic and spatially explicit at the scale of individual plants. For each model, I use a version of pair approximation or moment closure along with a separation of timescales argument to determine the effects of spatial clustering on threshold structure. By computing the spatial structure early in an invasion, I find explicit corrections to mean field theory. In the first chapter, I present a lattice model of a disease that is not directly lethal to its host, but affects its ability to compete with neighbors. I use a type of pair approximation to determine conditions for invasions and coexistence. In the second chapter, I study a basic SIR epidemic point process in continuous space. I implement a multiplicative moment closure scheme to compute the threshold transmission rate as a function of spatial parameters. In the final chapter, I model the evolution of pathogen resistance when two plant species share a pathogen. Evolution may lead...
Proximal soil sensing to parameterize spatial environmental modeling
Spatially explicit models are important tools to understand the effects of the interaction of management and landscape factors on water and soil quality. One challenge to application of such models is the need to know spatially-distributed values for input parameters. Some such data can come from av...
Shenkarev, Zakhar O; Paramonov, Alexander S; Lyukmanova, Ekaterina N; Gizatullina, Albina K; Zhuravleva, Anastasia V; Tagaev, Andrey A; Yakimenko, Zoya A; Telezhinskaya, Irina N; Kirpichnikov, Mikhail P; Ovchinnikova, Tatiana V; Arseniev, Alexander S
2013-05-01
Antiamoebin I (Aam-I) is a membrane-active peptaibol antibiotic isolated from fungal species belonging to the genera Cephalosporium, Emericellopsis, Gliocladium, and Stilbella. In comparison with other 16-amino acid-residue peptaibols, e.g., zervamicin IIB (Zrv-IIB), Aam-I possesses relatively weak biological and channel-forming activities. In MeOH solution, Aam-I demonstrates fast cooperative transitions between right-handed and left-handed helical conformation of the N-terminal (1-8) region. We studied Aam-I spatial structure and backbone dynamics in the membrane-mimicking environment (DMPC/DHPC bicelles)(1) ) by heteronuclear (1) H,(13) C,(15) N-NMR spectroscopy. Interaction with the bicelles stabilizes the Aam-I right-handed helical conformation retaining significant intramolecular mobility on the ms-μs time scale. Extensive ms-μs dynamics were also detected in the DPC and DHPC micelles and DOPG nanodiscs. In contrast, Zrv-IIB in the DPC micelles demonstrates appreciably lesser mobility on the μs-ms time scale. Titration with Mn(2+) and 16-doxylstearate paramagnetic probes revealed Aam-I binding to the bicelle surface with the N-terminus slightly immersed into hydrocarbon region. Fluctuations of the Aam-I helix between surface-bound and transmembrane (TM) state were observed in the nanodisc membranes formed from the short-chain (diC12 : 0) DLPC/DLPG lipids. All the obtained experimental data are in agreement with the barrel-stave model of TM pore formation, similarly to the mechanism proposed for Zrv-IIB and other peptaibols. The observed extensive intramolecular dynamics explains the relatively low activity of Aam-I.
Dark Spatial Soliton Interaction in Nonlinear Kerr Medium
Institute of Scientific and Technical Information of China (English)
LuchuanWANG; QinliangFAN
1998-01-01
The dark spatial soliton interaction in nonlinear Kerr medium has been studied in this paper.The problem has been solved by the use of the slowly varying envelope approximation in solving coupled nonlinear Schroedinger equations.The perturbation nature of dark spatial soliton interaction has been described and some of their key properties has been discussed as well in the paper.
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
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
Interplay of Bacterial Interactions and Spatial Organisation in Multispecies Biofilms
DEFF Research Database (Denmark)
Liu, Wenzheng
understanding of interspecies interactions and molecular mechanisms behind these activities of complex communities in combina-tion with omics technologies. Manuscript I demonstrates the apparent and predictable correlation between interspecific interactions and spatial organization of microbes in mul...... of member species’ spatial organization on biofilm formation and community assembly. The observations from Manuscript II suggest that low abundance key species can significantly impact the spatial organization and hereby stabilize the func-tion and composition of complex microbiomes. Manuscript III...
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.
Emergence of Strange Spatial Pattern in a Spatial Epidemic Model
Institute of Scientific and Technical Information of China (English)
SUN Gui-Quan; JIN Zhen; LIU Quan-Xing; LI Li
2008-01-01
Pattern formation of a spatial epidemic model with nonlinear incidence rate kI2 S/ (1 + αI2) is investigated. Our results show that strange spatial dynamics, i.e., filament-like pattern, can be obtained by both mathematical analysis and numerical simulation, which are different from the previous results in the spatial epidemic model such as stripe-like or spotted or coexistence of both pattern and so on. The obtained results well extend the finding of pattern formation in the epidemic model and may well explain the distribution of the infected of some epidemic.
Spatial positioning : method development for spatial analysis of interaction in buildings
Markhede, Henrik
2010-01-01
In offices, knowledge sharing largely depends on everyday face-to-face interaction patterns. These interaction patterns may depend on how employees move through the office space. This thesis explores how these spatial relations influence individual choices with respect to employee movements or routes. Space syntax related research has shown a strong relationship between spatial configuration and pedestrian movement in cities, yet field of space syntax has not applied spatial analysis to the o...
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.
FUEL3-D: A Spatially Explicit Fractal Fuel Distribution Model
Russell A. Parsons
2006-01-01
Efforts to quantitatively evaluate the effectiveness of fuels treatments are hampered by inconsistencies between the spatial scale at which fuel treatments are implemented and the spatial scale, and detail, with which we model fire and fuel interactions. Central to this scale inconsistency is the resolution at which variability within the fuel bed is considered. Crown...
Loehman, Rachel; 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.
Capturing Multivariate Spatial Dependence: Model, Estimate and then Predict
Cressie, Noel; Burden, Sandy; Davis, Walter; Krivitsky, Pavel N.; Mokhtarian, Payam; Suesse, Thomas; Zammit-Mangion, Andrew
2015-01-01
Physical processes rarely occur in isolation, rather they influence and interact with one another. Thus, there is great benefit in modeling potential dependence between both spatial locations and different processes. It is the interaction between these two dependencies that is the focus of Genton and Kleiber's paper under discussion. We see the problem of ensuring that any multivariate spatial covariance matrix is nonnegative definite as important, but we also see it as a means to an end. Tha...
Directory of Open Access Journals (Sweden)
Mustafa Koroglu
2016-02-01
Full Text Available This paper considers a functional-coefficient spatial Durbin model with nonparametric spatial weights. Applying the series approximation method, we estimate the unknown functional coefficients and spatial weighting functions via a nonparametric two-stage least squares (or 2SLS estimation method. To further improve estimation accuracy, we also construct a second-step estimator of the unknown functional coefficients by a local linear regression approach. Some Monte Carlo simulation results are reported to assess the finite sample performance of our proposed estimators. We then apply the proposed model to re-examine national economic growth by augmenting the conventional Solow economic growth convergence model with unknown spatial interactive structures of the national economy, as well as country-specific Solow parameters, where the spatial weighting functions and Solow parameters are allowed to be a function of geographical distance and the countries’ openness to trade, respectively.
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.
Stochastic heterogeneous interaction promotes cooperation in spatial prisoner's dilemma game.
Zhu, Ping; Wei, Guiyi
2014-01-01
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.
Integrated spatial sampling modeling of geospatial data
Institute of Scientific and Technical Information of China (English)
LI Lianfa; WANG Jinfeng
2004-01-01
Spatial sampling is a necessary and important method for extracting geospatial data and its methodology directly affects the geo-analysis results. Counter to the deficiency of separate models of spatial sampling, this article analyzes three crucial elements of spatial sampling (frame, correlation and decision diagram) and induces its general integrated model. The program of Spatial Sampling Integration (SSI) has been developed with Component Object Model (COM) to realize the general integrated model. In two practical applications, i.e. design of the monitoring network of natural disasters and sampling survey of the areas of non-cultivated land, SSI has produced accurate results at less cost, better realizing the cost-effective goal of sampling toward the geo-objects with spatial correlation. The two cases exemplify expanded application and convenient implementation of the general integrated model with inset components in an integrated environment, which can also be extended to other modeling of spatial analysis.
Optical Spatial Solitons and Their Interactions: Universality and Diversity.
Stegeman; Segev
1999-11-19
Spatial solitons, beams that do not spread owing to diffraction when they propagate, have been demonstrated to exist by virtue of a variety of nonlinear self-trapping mechanisms. Despite the diversity of these mechanisms, many of the features of soliton interactions and collisions are universal. Spatial solitons exhibit a richness of phenomena not found with temporal solitons in fibers, including effects such as fusion, fission, annihilation, and stable orbiting in three dimensions. Here the current state of knowledge on spatial soliton interactions is reviewed.
Auditory-visual spatial interaction and modularity
Radeau, M
1994-02-01
The results of dealing with the conditions for pairing visual and auditory data coming from spatially separate locations argue for cognitive impenetrability and computational autonomy, the pairing rules being the Gestalt principles of common fate and proximity. Other data provide evidence for pairing with several properties of modular functioning. Arguments for domain specificity are inferred from comparison with audio-visual speech. Suggestion of innate specification can be found in developmental data indicating that the grouping of visual and auditory signals is supported very early in life by the same principles that operate in adults. Support for a specific neural architecture comes from neurophysiological studies of the bimodal (auditory-visual) neurons of the cat superior colliculus. Auditory-visual pairing thus seems to present the four main properties of the Fodorian module.
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.
Modelling evolution in a spatial continuum
Barton, N. H.; Etheridge, A. M.; Véber, A.
2013-01-01
We survey a class of models for spatially structured populations which we have called spatial Λ-Fleming-Viot processes. They arise from a flexible framework for modelling in which the key innovation is that random genetic drift is driven by a Poisson point process of spatial 'events'. We demonstrate how this overcomes some of the obstructions to modelling populations which evolve in two-(and higher-) dimensional spatial continua, how its predictions match phenomena observed in data and how it fits with classical models. Finally we outline some directions for future research.
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
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...... 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...
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....
Local models for spatial analysis
Lloyd, Christopher D
2010-01-01
Focusing on solutions, this second edition provides guidance to a wide variety of real-world problems. The text presents a complete introduction to key concepts and a clear mapping of the methods discussed. It also explores connections between methods. New chapters address spatial patterning in single variables and spatial relations. In addition, every chapter now includes links to key related studies. The author clearly distinguishes between local and global methods and provides more detailed coverage of geographical weighting, image texture measures, local spatial autocorrelation, and multic
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.
Directory of Open Access Journals (Sweden)
Sander Land
2015-08-01
Full Text Available Biophysical models of cardiac tension development provide a succinct representation of our understanding of force generation in the heart. The link between protein kinetics and interactions that gives rise to high cooperativity is not yet fully explained from experiments or previous biophysical models. We propose a biophysical ODE-based representation of cross-bridge (XB, tropomyosin and troponin within a contractile regulatory unit (RU to investigate the mechanisms behind cooperative activation, as well as the role of cooperativity in dynamic tension generation across different species. The model includes cooperative interactions between regulatory units (RU-RU, between crossbridges (XB-XB, as well more complex interactions between crossbridges and regulatory units (XB-RU interactions. For the steady-state force-calcium relationship, our framework predicts that: (1 XB-RU effects are key in shifting the half-activation value of the force-calcium relationship towards lower [Ca(2+], but have only small effects on cooperativity. (2 XB-XB effects approximately double the duty ratio of myosin, but do not significantly affect cooperativity. (3 RU-RU effects derived from the long-range action of tropomyosin are a major factor in cooperative activation, with each additional unblocked RU increasing the rate of additional RU's unblocking. (4 Myosin affinity for short (1-4 RU unblocked stretches of actin of is very low, and the resulting suppression of force at low [Ca(2+] is a major contributor in the biphasic force-calcium relationship. We also reproduce isometric tension development across mouse, rat and human at physiological temperature and pacing rate, and conclude that species differences require only changes in myosin affinity and troponin I/troponin C affinity. Furthermore, we show that the calcium dependence of the rate of tension redevelopment k(tr is explained by transient blocking of RU's by a temporary decrease in XB-RU effects.
Spatial Sound and Multimodal Interaction in Immersive Environments
DEFF Research Database (Denmark)
Grani, Francesco; Overholt, Daniel; Erkut, Cumhur
2015-01-01
are discussed. These include elements in which we have provided sonic interaction in virtual environments, interactivity with volumetric sound sources using VBAP and Wave Field Synthesis (WFS), and binaural sound for virtual environments and spatial audio mixing. We show that the variety of approaches presented......Spatial sound and interactivity are key elements of investigation at the Sound And Music Computing master program at Aalborg University Copenhagen. We present a collection of research directions and recent results from work in these areas, with the focus on our multi- faceted approaches to two...
Interaction English Teaching Model
Institute of Scientific and Technical Information of China (English)
穆宇娜
2013-01-01
Malash—Thomas pointed out“Interaction is a process in which people and things act upon each other through their ac⁃tions.”According to different subjects, interaction can be divided into human-computer interaction, people-people interaction and learner-content interaction. According to different forms, interactions can be divided into one-one interaction, one-more interac⁃tion and more-more interaction.“Interaction Education”means that teachers are leading parts and students are the center of class. During teaching process, teachers must lead students to discover. Demands from students can encourage teachers to inspire con⁃versely.Thus it can form a close communication between teachers and students. Teaching and learning are realized in a happy and harmonious atmosphere. Successful English teaching must take new bilateral teaching as the first part, which should let the func⁃tion of the two most important elements develop fully. Teachers should grasp opportunities to guide. Teaching methods need to be flexible, and contents of teaching need to be vivid;students should be keen to think, to participate actively, and can break the tradi⁃tion to produce fresh ideas, and in that situation the capability of students can develop fully. The educational model refers to the simplified description of detailed teaching activities. Possessing dual functions of theory and practice, the educational model is the manifestation of theoretical teaching method. The combination of interaction and educational model which are mentioned above form the“interactive teaching”model. With the coming of economic globalization and integration of science and technology, now communications are increasing with each passing day. If you want to take part in or to get in touch with others, you must use lan⁃guage. English has been learnt for 10 years in Middle school and in college, but it can’t be spoken very fluently. That is a realistic picture as the result of an
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.
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.
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
Continuous-Time Modeling with Spatial Dependence
Oud, J.H.L.; Folmer, H.; Patuelli, R.; Nijkamp, P.
2012-01-01
(Spatial) panel data are routinely modeled in discrete time (DT). However, compelling arguments exist for continuous-time (CT) modeling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete
Continuous-Time Modeling with Spatial Dependence
Oud, J.; Folmer, H.; Patuelli, R.; Nijkamp, P.
(Spatial) panel data are routinely modeled in discrete time (DT). However, compelling arguments exist for continuous-time (CT) modeling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete
Bayesian Spatial Modelling with R-INLA
Finn Lindgren; Håvard Rue
2015-01-01
The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA) approach proposed by Rue, Martino, and Chopin (2009) is a computationally effective alternative to MCMC for Bayesian inference. INLA is designed for latent Gaussian models, a very wide and flexible class of models ranging from (generalized) linear mixed to spatial and spatio-temporal models. Combined with the stochastic...
Enhancement of Laser Power Efficiency by Control of Spatial Hole Burning Interactions
Ge, Li; Tureci, Hakan E
2014-01-01
The laser is an out-of-equilibrium nonlinear wave system where the interplay of the cavity geometry and nonlinear wave interactions, mediated by the gain medium, determines the self-organized oscillation frequencies and the associated spatial field patterns. In the steady state, a constant energy flux flows through the laser from the pump to the far field, with the ratio of the total output power to the input power determining the power-efficiency. While nonlinear wave interactions have been modeled and well understood since the early days of laser theory, their impact on the power-efficiency of a laser system is poorly understood. Here, we show that spatial hole burning interactions generally decrease the power efficiency. We then demonstrate how spatial hole burning interactions can be controlled by a spatially tailored pump profile, thereby boosting the power-efficiency, in some cases by orders of magnitude.
Directory of Open Access Journals (Sweden)
Ming Wang
Full Text Available Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly, Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies' behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies' movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by
Amelogenin-Ameloblastin Spatial Interaction around Maturing Enamel Rods.
Mazumder, P; Prajapati, S; Bapat, R; Moradian-Oldak, J
2016-08-01
Amelogenin and ameloblastin are 2 extracellular matrix proteins that are essential for the proper development of enamel. We recently reported that amelogenin and ameloblastin colocalized during the secretory stage of enamel formation when nucleation of enamel crystallites occurs. Direct interactions between the 2 proteins have been also demonstrated in our in vitro studies. Here, we explore interactions between their fragments during enamel maturation. We applied in vivo immunofluorescence imaging, quantitative co-localization analysis, and a new FRET (fluorescence resonance energy transfer) technique to demonstrate ameloblastin and amelogenin interaction in the maturing mouse enamel. Using immunochemical analysis of protein samples extracted from 8-d-old (P8) first molars from mice as a model for maturation-stage enamel, we identified the ~17-kDa ameloblastin (Ambn-N) and the TRAP (tyrosine-rich amelogenin peptide) fragments. We used Ambn-N18 and Ambn-M300 antibodies raised against the N-terminal and C-terminal segments of ameloblastin, as well as Amel-FL and Amel-C19 antibodies against full-length recombinant mouse amelogenin (rM179) and C-terminal amelogenin, respectively. In transverse sections, co-localization images of N-terminal fragments of amelogenin and ameloblastin around the prism boundary revealed the "fish net" pattern of the enamel matrix. Using in vivo FRET microscopy, we further demonstrated spatial interactions between amelogenin and ameloblastin N-terminal fragments. In the maturing mouse enamel, the association of these residual protein fragments created a discontinuity between enamel rods, which we suggest is important for support and maintenance of enamel rods and eventual contribution to unique enamel mechanical properties. We present data that support cooperative functions of enamel matrix proteins in mediating the structural hierarchy of enamel and that contribute to our efforts to design and develop enamel biomimetic material.
Yokogawa, D.
2016-09-01
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.
Evaluating spatial patterns in hydrological modelling
DEFF Research Database (Denmark)
Koch, Julian
of spatial information in a holistic assessment. Opposed, statistical measures typically only address a limited amount of spatial information. A web-based survey and a citizen science project are employed to quantify the collective perceptive skills of humans aiming at benchmarking spatial metrics...... of environmental science, such as meteorology, geostatistics or geography. In total, seven metrics are evaluated with respect to their capability to quantitatively compare spatial patterns. The human visual perception is often considered superior to computer based measures, because it integrates various dimensions...... with respect to their capability to mimic human evaluations. This PhD thesis aims at expanding the standard toolbox of spatial model evaluation with innovative metrics that adequately compare spatial patterns. Driven by the rise of more complex model structures and the increase of suitable remote sensing...
Spatial-domain interactions between ultra-weak optical beams
Khadka, Utsab; Xiao, Min
2013-01-01
We have observed the spatial interactions between two ultra-weak optical beams that are initially collinear and non-overlapping. The weak beams are steered towards each other by a spatially varying cross-Kerr refractive index waveguide written by a strong laser beam in a three-level atomic medium utilizing quantum coherence. After being brought together, the weak beams show controllable phase-dependent outcomes. This is the first observation of soliton-like interactions between weak beams and can be useful for all-optically tunable beam-combining, switching and gates for weak photonic signals.
Interaction dynamics of spatially separated cavitation bubbles in water
Tinne, Nadine; Schumacher, Silvia; Nuzzo, Valeria; Arnold, Cord L.; Lubatschowski, Holger; Ripken, Tammo
2010-11-01
We present a high-speed photographic analysis of the interaction of cavitation bubbles generated in two spatially separated regions by femtosecond laser-induced optical breakdown in water. Depending on the relative energies of the femtosecond laser pulses and their spatial separation, different kinds of interactions, such as a flattening and deformation of the bubbles, asymmetric water flows, and jet formation were observed. The results presented have a strong impact on understanding and optimizing the cutting effect of modern femtosecond lasers with high repetition rates (>1 MHz).
A neuromorphic model of spatial lookahead planning.
Ivey, Richard; Bullock, Daniel; Grossberg, Stephen
2011-04-01
In order to create spatial plans in a complex and changing world, organisms need to rapidly adapt to novel configurations of obstacles that impede simple routes to goal acquisition. Some animals can mentally create successful multistep spatial plans in new visuo-spatial layouts that preclude direct, one-segment routes to goal acquisition. Lookahead multistep plans can, moreover, be fully developed before an animal executes any step in the plan. What neural computations suffice to yield preparatory multistep lookahead plans during spatial cognition of an obstructed two-dimensional scene? To address this question, we introduce a novel neuromorphic system for spatial lookahead planning in which a feasible sequence of actions is prepared before movement begins. The proposed system combines neurobiologically plausible mechanisms of recurrent shunting competitive networks, visuo-spatial diffusion, and inhibition-of-return. These processes iteratively prepare a multistep trajectory to the desired goal state in the presence of obstacles. The planned trajectory can be stored using a primacy gradient in a sequential working memory and enacted by a competitive queuing process. The proposed planning system is compared with prior planning models. Simulation results demonstrate system robustness to environmental variations. Notably, the model copes with many configurations of obstacles that lead other visuo-spatial planning models into selecting undesirable or infeasible routes. Our proposal is inspired by mechanisms of spatial attention and planning in primates. Accordingly, our simulation results are compared with neurophysiological and behavioral findings from relevant studies of spatial lookahead behavior.
Spatial interactions determine temporal feature integration as revealed by unmasking
Directory of Open Access Journals (Sweden)
Michael H. Herzog
2006-01-01
Full Text Available Feature integration is one of the most fundamental problems in neuroscience. In a recent contribution, we showed that a trailing grating can diminish the masking effects one vernier exerts on another, preceding vernier. Here, we show that this temporal unmasking depends on neural spatial interactions related to the trailing grating. Hence, our paradigm allows us to study the spatio-temporal interactions underlying feature integration.
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
Directory of Open Access Journals (Sweden)
Paul Grégory
2010-07-01
Full Text Available Abstract Background Sub-cellular structures interact in numerous direct and indirect ways in order to fulfill cellular functions. While direct molecular interactions crucially depend on spatial proximity, other interactions typically result in spatial correlations between the interacting structures. Such correlations are the target of microscopy-based co-localization analysis, which can provide hints of potential interactions. Two complementary approaches to co-localization analysis can be distinguished: intensity correlation methods capitalize on pattern discovery, whereas object-based methods emphasize detection power. Results We first reinvestigate the classical co-localization measure in the context of spatial point pattern analysis. This allows us to unravel the set of implicit assumptions inherent to this measure and to identify potential confounding factors commonly ignored. We generalize object-based co-localization analysis to a statistical framework involving spatial point processes. In this framework, interactions are understood as position co-dependencies in the observed localization patterns. The framework is based on a model of effective pairwise interaction potentials and the specification of a null hypothesis for the expected pattern in the absence of interaction. Inferred interaction potentials thus reflect all significant effects that are not explained by the null hypothesis. Our model enables the use of a wealth of well-known statistical methods for analyzing experimental data, as demonstrated on synthetic data and in a case study considering virus entry into live cells. We show that the classical co-localization measure typically under-exploits the information contained in our data. Conclusions We establish a connection between co-localization and spatial interaction of sub-cellular structures by formulating the object-based interaction analysis problem in a spatial statistics framework based on nearest-neighbor distance
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)
Surface water - groundwater interactions at different spatial and temporal scales
DEFF Research Database (Denmark)
Sebök, Éva
in lowland catchments, mainly exploring and assessing Distributed Temperature Sensing (DTS) which by detecting variability in temperatures at the Sediment-Water Interface (SWI) can indirectly map variability in groundwater discharge at several spatial and temporal scales. On the small-scale (...As there is a growing demand for the protection and optimal management of both the surface water and groundwater resources, the understanding of their exchange processes is of great importance. This PhD study aimed at describing the natural spatial and temporal variability of these interactions...... detected large spatial variability in SWI temperatures with scattered high-discharge sites in a stream and also in a lake where discharge fluxes were estimated by vertical temperature profiles and seepage meter measurements. On the kilometre scale DTS indicated less spatial variability in streambed...
Spatial games with cyclic interactions: the response of empty sites
Brown, Bart; Pleimling, Michel
2015-03-01
Predator-prey models of the May-Leonard family employ empty sites in a spatial setting as an intermediate step in the reproduction process. This requirement makes the number and arrangement of empty sites important to the formation of space-time patterns. We study the density of empty sites in a stochastic predator-prey model in which the species compete in a cyclic way in two dimensions. In some cases systems of this type quickly form domains of neutral species after which all predation, and therefore, reproduction occur near the interface of competing domains. Using Monte Carlo simulations we investigate the relationship of this density of empty sites to the time-dependent domain length. We further explore the dynamics by introducing perturbations to the interaction rates of the system after which we measure the perturbed density, i.e. the response of empty sites, as the system relaxes. A dynamical scaling behavior is observed in the response of empty sites. This work is supported by the US National Science Foundation through Grant DMR-1205309.
On spatially explicit models of cholera epidemics
National Research Council Canada - National Science Library
Bertuzzo, E; Casagrandi, R; Gatto, M; Rodriguez-Iturbe, I; Rinaldo, A
2010-01-01
We generalize a recently proposed model for cholera epidemics that accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having...
Spatial averaging infiltration model for layered soil
Institute of Scientific and Technical Information of China (English)
HU HePing; YANG ZhiYong; TIAN FuQiang
2009-01-01
To quantify the influences of soil heterogeneity on infiltration, a spatial averaging infiltration model for layered soil (SAI model) is developed by coupling the spatial averaging approach proposed by Chen et al. and the Generalized Green-Ampt model proposed by Jia et al. In the SAI model, the spatial heterogeneity along the horizontal direction is described by a probability distribution function, while that along the vertical direction is represented by the layered soils. The SAI model is tested on a typical soil using Monte Carlo simulations as the base model. The results show that the SAI model can directly incorporate the influence of spatial heterogeneity on infiltration on the macro scale. It is also found that the homogeneous assumption of soil hydraulic conductivity along the horizontal direction will overestimate the infiltration rate, while that along the vertical direction will underestimate the infiltration rate significantly during rainstorm periods. The SAI model is adopted in the spatial averaging hydrological model developed by the authors, and the results prove that it can be applied in the macro-scale hydrological and land surface process modeling in a promising way.
Spatial averaging infiltration model for layered soil
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
To quantify the influences of soil heterogeneity on infiltration, a spatial averaging infiltration model for layered soil (SAI model) is developed by coupling the spatial averaging approach proposed by Chen et al. and the Generalized Green-Ampt model proposed by Jia et al. In the SAI model, the spatial hetero- geneity along the horizontal direction is described by a probability distribution function, while that along the vertical direction is represented by the layered soils. The SAI model is tested on a typical soil using Monte Carlo simulations as the base model. The results show that the SAI model can directly incorporate the influence of spatial heterogeneity on infiltration on the macro scale. It is also found that the homogeneous assumption of soil hydraulic conductivity along the horizontal direction will overes- timate the infiltration rate, while that along the vertical direction will underestimate the infiltration rate significantly during rainstorm periods. The SAI model is adopted in the spatial averaging hydrological model developed by the authors, and the results prove that it can be applied in the macro-scale hy- drological and land surface process modeling in a promising way.
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
is not fully exploited by current modelling frameworks due to the lack of suitable spatial performance metrics. Furthermore, the traditional model evaluation using discharge is found unsuitable to lay confidence on the predicted catchment inherent spatial variability of hydrological processes in a fully...... the contiguous United Sates (10^6 km2). To this end, the thesis at hand applies a set of spatial performance metrics on various hydrological variables, namely land-surface-temperature (LST), evapotranspiration (ET) and soil moisture. The inspiration for the applied metrics is found in related fields...
Modeling signalized intersection safety with corridor-level spatial correlations.
Guo, Feng; Wang, Xuesong; Abdel-Aty, Mohamed A
2010-01-01
Intersections in close spatial proximity along a corridor should be considered as correlated due to interacted traffic flows as well as similar road design and environmental characteristics. It is critical to incorporate this spatial correlation for assessing the true safety impacts of risk factors. In this paper, several Bayesian models were developed to model the crash data from 170 signalized intersections in the state of Florida. The safety impacts of risk factors such as geometric design features, traffic control, and traffic flow characteristics were evaluated. The Poisson and Negative Binomial Bayesian models with non-informative priors were fitted but the focus is to incorporate spatial correlations among intersections. Two alternative models were proposed to capture this correlation: (1) a mixed effect model in which the corridor-level correlation is incorporated through a corridor-specific random effect and (2) a conditional autoregressive model in which the magnitude of correlations is determined by spatial distances among intersections. The models were compared using the Deviance Information Criterion. The results indicate that the Poisson spatial model provides the best model fitting. Analysis of the posterior distributions of model parameters indicated that the size of intersection, the traffic conditions by turning movement, and the coordination of signal phase have significant impacts on intersection safety.
Spatial and temporal interactions of sympatric mountain lions in Arizona
Nicholson, Kerry L.; Krausman, Paul R.; Munguia-Vega, Adrian; Culver, Melanie
2011-01-01
Spatial and temporal interactions among individual members of populations can have direct applications to habitat management of mountain lions (Puma concolor). Our objectives were to evaluate home range overlap and spatial/temporal use of overlap zones (OZ) of mountain lions in Arizona. We incorporated spatial data with genetic analyses to assess relatedness between mountain lions with overlapping home ranges. We recorded the space use patterns of 29 radio-collared mountain lions in Arizona from August 2005 to August 2008. We genotyped 28 mountain lions and estimated the degree of relatedness among individuals. For 26 pairs of temporally overlapping mountain lions, 18 overlapped spatially and temporally and eight had corresponding genetic information. Home range overlap ranged from 1.18% to 46.38% (x̄=2443, SE = 2.96). Male–male pairs were located within 1 km of each other on average, 0.04% of the time, whereas male–female pairs on average were 3.0%. Two male–male pairs exhibited symmetrical spatial avoidance and two symmetrical spatial attractions to the OZ. We observed simultaneous temporal attraction in three male–male pairs and four male–female pairs. Individuals from Tucson were slightly related to one another within the population (n = 13, mean R = 0.0373 ± 0.0151) whereas lions from Payson (n = 6, mean R = -0.0079 ± 0.0356) and Prescott (n = 9, mean R = -0.0242 ± 0.0452) were not as related. Overall, males were less related to other males (n = 20, mean R = -0.0495 ± 0.0161) than females were related to other females (n = 8, mean R = 0.0015 ± 0.0839). Genetic distance was positively correlated with geographic distance (r2 = 0.22, P = 0.001). Spatial requirements and interactions influence social behavior and can play a role in determining population density.
Performance of Information Criteria for Spatial Models.
Lee, Hyeyoung; Ghosh, Sujit K
2009-01-01
Model choice is one of the most crucial aspect in any statistical data analysis. It is well known that most models are just an approximation to the true data generating process but among such model approximations it is our goal to select the "best" one. Researchers typically consider a finite number of plausible models in statistical applications and the related statistical inference depends on the chosen model. Hence model comparison is required to identify the "best" model among several such candidate models. This article considers the problem of model selection for spatial data. The issue of model selection for spatial models has been addressed in the literature by the use of traditional information criteria based methods, even though such criteria have been developed based on the assumption of independent observations. We evaluate the performance of some of the popular model selection critera via Monte Carlo simulation experiments using small to moderate samples. In particular, we compare the performance of some of the most popular information criteria such as Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Corrected AIC (AICc) in selecting the true model. The ability of these criteria to select the correct model is evaluated under several scenarios. This comparison is made using various spatial covariance models ranging from stationary isotropic to nonstationary models.
Uncertainty in spatially explicit animal dispersal models
Mooij, Wolf M.; DeAngelis, Donald L.
2003-01-01
Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three levels of complexity: (1) an event-based binomial model that considers only the occurrence of mortality or arrival, (2) a temporally explicit exponential model that employs mortality and arrival rates, and (3) a spatially explicit grid-walk model that simulates the movement of animals through an artificial landscape. Each model was fitted to the same set of field data. A first objective of the paper is to illustrate how the maximum-likelihood method can be used in all three cases to estimate the means and confidence limits for the relevant model parameters, given a particular set of data on dispersal survival. Using this framework we show that the structure of the uncertainty for all three models is strikingly similar. In fact, the results of our unified approach imply that spatially explicit dispersal models, which take advantage of information on landscape details, suffer less from uncertainly than do simpler models. Moreover, we show that the proposed strategy of model development safeguards one from error propagation in these more complex models. Finally, our approach shows that all models related to animal dispersal, ranging from simple to complex, can be related in a hierarchical fashion, so that the various approaches to modeling such dispersal can be viewed from a unified perspective.
Spatial coincidence modulates interaction between visual and somatosensory evoked potentials.
Schürmann, Martin; Kolev, Vasil; Menzel, Kristina; Yordanova, Juliana
2002-05-07
The time course of interaction between concurrently applied visual and somatosensory stimulation with respect to evoked potentials (EPs) was studied. Visual stimuli, either in the left or right hemifield, and electric stimuli to the left wrist were delivered either alone or simultaneously. Visual and somatosensory EPs were summed and compared to bimodal EPs (BiEP, response to actual combination of both modalities). Temporal coincidence of stimuli lead to sub-additive or over-additive amplitudes in BiEPs in several time windows between 75 and 275 ms. Additional effects of spatial coincidence (left wrist with left hemifield) were found between 75 and 300 ms and beyond 450 ms. These interaction effects hint at a temporo-spatial pattern of multiple brain areas participating in the process of multimodal integration.
Regulation mechanisms in spatial stochastic development models
Finkelshtein, Dmitri
2008-01-01
The aim of this paper is to analyze different regulation mechanisms in spatial continuous stochastic development models. We describe the density behavior for models with global mortality and local establishment rates. We prove that the local self-regulation via a competition mechanism (density dependent mortality) may suppress a unbounded growth of the averaged density if the competition kernel is superstable.
Uncertainty in spatially explicit animal dispersal models
Mooij, W.M.; DeAngelis, D.L.
2003-01-01
Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three level
Integrated statistical modelling of spatial landslide probability
Mergili, M.; Chu, H.-J.
2015-09-01
Statistical methods are commonly employed to estimate spatial probabilities of landslide release at the catchment or regional scale. Travel distances and impact areas are often computed by means of conceptual mass point models. The present work introduces a fully automated procedure extending and combining both concepts to compute an integrated spatial landslide probability: (i) the landslide inventory is subset into release and deposition zones. (ii) We employ a simple statistical approach to estimate the pixel-based landslide release probability. (iii) We use the cumulative probability density function of the angle of reach of the observed landslide pixels to assign an impact probability to each pixel. (iv) We introduce the zonal probability i.e. the spatial probability that at least one landslide pixel occurs within a zone of defined size. We quantify this relationship by a set of empirical curves. (v) The integrated spatial landslide probability is defined as the maximum of the release probability and the product of the impact probability and the zonal release probability relevant for each pixel. We demonstrate the approach with a 637 km2 study area in southern Taiwan, using an inventory of 1399 landslides triggered by the typhoon Morakot in 2009. We observe that (i) the average integrated spatial landslide probability over the entire study area corresponds reasonably well to the fraction of the observed landside area; (ii) the model performs moderately well in predicting the observed spatial landslide distribution; (iii) the size of the release zone (or any other zone of spatial aggregation) influences the integrated spatial landslide probability to a much higher degree than the pixel-based release probability; (iv) removing the largest landslides from the analysis leads to an enhanced model performance.
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
Energy Technology Data Exchange (ETDEWEB)
Borkowski, L S; Jacyna-Onyszkiewicz, Z, E-mail: lsb@man.poznan.p [Faculty of Physics, Adam Mickiewicz University, Umultowska 85, 61-614 Poznan (Poland)
2009-03-01
We study the Ising model of a ferromagnetic nanopyramid deposited on a ferromagnetic substrate. The interaction between the pyramid and the substrate is calculated in terms of the reduced-state (density) operator. The spatial distribution of fluctuations of the molecular field and magnetization is obtained within the Gaussian approximation.
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.
mapview - Interactive viewing of spatial data in R
Appelhans, Tim; Detsch, Florian; Reudenbach, Cristoph; Woellauer, Stefan
2016-04-01
In this talk we would like to introduce mapview, an R package designed to aid researchers during their work-flow of spatial data analysis. The package was initially developed within the framework of the DFG funded research group "KiLi - Kilimanjaro ecosystems under global change: Linking biodiversity, biotic interactions and biogeochemical ecosystem processes" but has quickly developed into a general purpose spatial data viewer. mapview provides some powerful tools for interactive visualization of standard spatial data in R. It has support for all Spatial*(DataFrame) objects as well as all Raster* objects. It is designed so that one function call - mapview(x) - is all you need to view the data interactively. Adding layers to existing views is very easy and we have taken great care in providing suitable defaults for features such as background maps or coloring but things can be customized flexibly (and permanently) to suit different needs. Even though mapview is for most parts based on the leaflet package, it is far more than just a convenience wrapper around leaflet functionality. mapview provides additional features for handling big data sets (up to several million points) as well as some specialized functionality to view and compare rasters of any size with arbitrary coordinate reference systems. Given that mapview is merely a bridge between R and the underlying leaflet.js javascript library, mapview can be used to produce web-maps by simply providing the path to a designated folder. This talk will be a live demonstration of some of the key features of mapview.
Flow mapping and multivariate visualization of large spatial interaction data.
Guo, Diansheng
2009-01-01
Spatial interactions (or flows), such as population migration and disease spread, naturally form a weighted location-to-location network (graph). Such geographically embedded networks (graphs) are usually very large. For example, the county-to-county migration data in the U.S. has thousands of counties and about a million migration paths. Moreover, many variables are associated with each flow, such as the number of migrants for different age groups, income levels, and occupations. It is a challenging task to visualize such data and discover network structures, multivariate relations, and their geographic patterns simultaneously. This paper addresses these challenges by developing an integrated interactive visualization framework that consists three coupled components: (1) a spatially constrained graph partitioning method that can construct a hierarchy of geographical regions (communities), where there are more flows or connections within regions than across regions; (2) a multivariate clustering and visualization method to detect and present multivariate patterns in the aggregated region-to-region flows; and (3) a highly interactive flow mapping component to map both flow and multivariate patterns in the geographic space, at different hierarchical levels. The proposed approach can process relatively large data sets and effectively discover and visualize major flow structures and multivariate relations at the same time. User interactions are supported to facilitate the understanding of both an overview and detailed patterns.
Ridge Regression for Interactive Models.
Tate, Richard L.
1988-01-01
An exploratory study of the value of ridge regression for interactive models is reported. Assuming that the linear terms in a simple interactive model are centered to eliminate non-essential multicollinearity, a variety of common models, representing both ordinal and disordinal interactions, are shown to have "orientations" that are favorable to…
ECoS, a framework for modelling hierarchical spatial systems.
Harris, John R W; Gorley, Ray N
2003-10-01
A general framework for modelling hierarchical spatial systems has been developed and implemented as the ECoS3 software package. The structure of this framework is described, and illustrated with representative examples. It allows the set-up and integration of sets of advection-diffusion equations representing multiple constituents interacting in a spatial context. Multiple spaces can be defined, with zero, one or two-dimensions and can be nested, and linked through constituent transfers. Model structure is generally object-oriented and hierarchical, reflecting the natural relations within its real-world analogue. Velocities, dispersions and inter-constituent transfers, together with additional functions, are defined as properties of constituents to which they apply. The resulting modular structure of ECoS models facilitates cut and paste model development, and template model components have been developed for the assembly of a range of estuarine water quality models. Published examples of applications to the geochemical dynamics of estuaries are listed.
Perception of social interactions for spatially scrambled biological motion.
Thurman, Steven M; Lu, Hongjing
2014-01-01
It is vitally important for humans to detect living creatures in the environment and to analyze their behavior to facilitate action understanding and high-level social inference. The current study employed naturalistic point-light animations to examine the ability of human observers to spontaneously identify and discriminate socially interactive behaviors between two human agents. Specifically, we investigated the importance of global body form, intrinsic joint movements, extrinsic whole-body movements, and critically, the congruency between intrinsic and extrinsic motions. Motion congruency is hypothesized to be particularly important because of the constraint it imposes on naturalistic action due to the inherent causal relationship between limb movements and whole body motion. Using a free response paradigm in Experiment 1, we discovered that many naïve observers (55%) spontaneously attributed animate and/or social traits to spatially-scrambled displays of interpersonal interaction. Total stimulus motion energy was strongly correlated with the likelihood that an observer would attribute animate/social traits, as opposed to physical/mechanical traits, to the scrambled dot stimuli. In Experiment 2, we found that participants could identify interactions between spatially-scrambled displays of human dance as long as congruency was maintained between intrinsic/extrinsic movements. Violating the motion congruency constraint resulted in chance discrimination performance for the spatially-scrambled displays. Finally, Experiment 3 showed that scrambled point-light dancing animations violating this constraint were also rated as significantly less interactive than animations with congruent intrinsic/extrinsic motion. These results demonstrate the importance of intrinsic/extrinsic motion congruency for biological motion analysis, and support a theoretical framework in which early visual filters help to detect animate agents in the environment based on several fundamental
Investigation of Retinal Spatial Interaction Using mfERG Stimulation
Directory of Open Access Journals (Sweden)
Patrick H. W. Chu
2011-05-01
Full Text Available Introduction: Adaptation is one of the key characteristic of our vision which can maximize the visual function. It applies to both spatial and temporal characteristics. The fast flickering stimulation characteristics of the multifocal electroretinogram (mfERG can be applied to analyze retinal interactions between flashes and to investigate retinal temporal processing mechanism. Besides, its localized stimulus pattern can also be used as a tool for investigation of retinal spatial interaction. Methods: The mfERG recordings were obtained from 13 eyes of 9, normal, six-week-old Yorkshire pigs. The control mfERG was measured using the pattern consisting of 103 nonscaled hexagons, where each hexagon will follow a pre-set m-sequence. Nine isolated hexagons from the 103 nonscaled pattern were chosen in the masking mfERG stimulation, where the remaining hexagons were kept at constant luminance. First-order and the second-order kernel responses were analyzed, which represent the outer and inner retinal responses, respectively. Results: The second-order kernel response amplitude from the visual streak region showed a significant enhancement under the masking stimulation. Conclusions: The enhancement found under the masking condition indicates that the retinal signal will be suppressed under surrounding flicker stimulation, and this spatial inhibitory mechanism may originate from the inner retina.
Visible Geology - Interactive online geologic block modelling
Cockett, R.
2012-12-01
Geology is a highly visual science, and many disciplines require spatial awareness and manipulation. For example, interpreting cross-sections, geologic maps, or plotting data on a stereonet all require various levels of spatial abilities. These skills are often not focused on in undergraduate geoscience curricula and many students struggle with spatial relations, manipulations, and penetrative abilities (e.g. Titus & Horsman, 2009). A newly developed program, Visible Geology, allows for students to be introduced to many geologic concepts and spatial skills in a virtual environment. Visible Geology is a web-based, three-dimensional environment where students can create and interrogate their own geologic block models. The program begins with a blank model, users then add geologic beds (with custom thickness and color) and can add geologic deformation events like tilting, folding, and faulting. Additionally, simple intrusive dikes can be modelled, as well as unconformities. Students can also explore the interaction of geology with topography by drawing elevation contours to produce their own topographic models. Students can not only spatially manipulate their model, but can create cross-sections and boreholes to practice their visual penetrative abilities. Visible Geology is easy to access and use, with no downloads required, so it can be incorporated into current, paper-based, lab activities. Sample learning activities are being developed that target introductory and structural geology curricula with learning objectives such as relative geologic history, fault characterization, apparent dip and thickness, interference folding, and stereonet interpretation. Visible Geology provides a richly interactive, and immersive environment for students to explore geologic concepts and practice their spatial skills.; Screenshot of Visible Geology showing folding and faulting interactions on a ridge topography.
Spatially explicit non-Mendelian diploid model
Lanchier, N; 10.1214/09-AAP598
2009-01-01
We introduce a spatially explicit model for the competition between type $a$ and type $b$ alleles. Each vertex of the $d$-dimensional integer lattice is occupied by a diploid individual, which is in one of three possible states or genotypes: $aa$, $ab$ or $bb$. We are interested in the long-term behavior of the gene frequencies when Mendel's law of segregation does not hold. This results in a voter type model depending on four parameters; each of these parameters measures the strength of competition between genes during meiosis. We prove that with or without a spatial structure, type $a$ and type $b$ alleles coexist at equilibrium when homozygotes are poor competitors. The inclusion of a spatial structure, however, reduces the parameter region where coexistence occurs.
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...
Modeling Spatially Unrestricted Pedestrian Traffic on Footbridges
DEFF Research Database (Denmark)
Zivanovic, Stana; Pavic, Aleksandar; Ingólfsson, Einar Thór
2010-01-01
The research into modelling walking-induced dynamic loading and its effects on footbridge structures and people using them has been intensified in the last decade after some high profile vibration serviceability failures. In particular, the crowd induced loading, characterised by spatially...... restricted movement of pedestrians, has kept attracting attention of researchers. However, it is the normal spatially unrestricted pedestrian traffic, and its vertical dynamic loading component, that are most relevant for vibration serviceability checks for most footbridges. Despite the existence of numerous...... design procedures concerned with this loading, the current confidence in its modelling is low due to lack of verification of the models on as-built structures. This is the motivation behind reviewing the existing design procedures for modelling normal pedestrian traffic in this paper and evaluating...
Modelling spatial density using continuous wavelet transforms
Indian Academy of Sciences (India)
D Sudheer Reddy; N Gopal Reddy; A K Anilkumar
2013-02-01
Due to increase in the satelite launch activities from many countries around the world the orbital debris issue has become a major concern for the space agencies to plan a collision-free orbit design. The risk of collisions is calculated using the in situ measurements and available models. Spatial density models are useful in understanding the long-term likelihood of a collision in a particular region of space and also helpful in pre-launch orbit planning. In this paper, we present a method of estimating model parameters such as number of peaks and peak locations of spatial density model using continuous wavelets. The proposed methodology was experimented with two line element data and the results are presented.
The effects of spatial scale on trophic interactions
Koppel, J. van de; Bardgett, R.D.; Bengtsson, J.; Rodriguez-Barrueco, C.; Rietkerk, M.G.; Wassen, M.J.; Wolters, V.
2005-01-01
Food chain models have dominated empirical studies of trophic interactions in the past decades, and have lead to important insights into the factors that control ecological communities. Despite the importance of food chain models in instigating ecological investigations, many empirical studies still
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.
Institute of Scientific and Technical Information of China (English)
李山; 王铮; 钟章奇
2012-01-01
Spatial interaction between tourist origin and destination is a key factor affecting tourist behavior and tourism industry. Usually, such a spatial interaction was described by gravity models. However, tourism gravity models used to adopt power deterrence function to describe the spatial friction effect, which is an analogy with Newton's gravity model, are hard to overcome some inherent defects. Therefore, Wilson's model with exponential deterrence function becomes a possible alternative. Based on Wilson's model, a basic form of tourism gravity model is presented with three main explanatory variables: attractiveness of tourist destination, emissiveness of tourist origin, and spatial damping between the destination and origin. Two coefficients, a (income elasticity) and β (spatial damping) in this model are also need to be evaluated. We used the traditional regression method to estimate the value of a. As to p, two new methods, "population particle pattern method" and "integral method on tourist amount" are used to estimate it. The results show that: 1) α = 0.64 and β = 0.00322 are at the national average level in the 2000s; 2) a becomes larger as the field-pixel becomes smaller. For provincial, municipal, county, and township levels, the values of β are 0.00044, 0.0014, 0.0044 and 0.014, respectively; 3) affected by spatial damping, the average travel radius of domestic residents is about 300 km. By the application of this model, attractiveness of each province of China and provincial tourist market shares of Chengdu city are calculated. The results show that: 1) from 2004 to 2008, the average tourism attraction of Sichuan, Liaoning and Yunnan rank the top three, while Ningxia, Qinghai and Inner Mongolia rank the bottom three; 2) from 1999 to 2008, in terms of tourism attraction at provincial level, Xizang has the biggest increase in the ranking, while Shanghai has the greatest decline in the ranking. 3) The results of theoretical calculation on Chengdu city
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...
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...
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.
Research of ERP model system of spatial data warehouse
Institute of Scientific and Technical Information of China (English)
CHEN Xue-long; WANG Yan-zhang
2004-01-01
The broad sharing of spatial information is demanded in the infrastructure construction of spatial data in our country. And the spatial data warehouse realizes the effective management and sharing of spatial information serving as an efficient tool. This article proposes ERP model system that of general-decision-oriented for constructing spatial data warehouse from the aspect of decision application. In the end of article, the construction process of spatial data warehouse based on ERP model system is discussed.
Spatial Aggregation: Data Model and Implementation
Gomez, Leticia; Kuijpers, Bart; Vaisman, Alejandro
2007-01-01
Data aggregation in Geographic Information Systems (GIS) is only marginally present in commercial systems nowadays, mostly through ad-hoc solutions. In this paper, we first present a formal model for representing spatial data. This model integrates geographic data and information contained in data warehouses external to the GIS. We define the notion of geometric aggregation, a general framework for aggregate queries in a GIS setting. We also identify the class of summable queries, which can be efficiently evaluated by precomputing the overlay of two or more of the thematic layers involved in the query. We also sketch a language, denoted GISOLAP-QL, for expressing queries that involve GIS and OLAP features. In addition, we introduce Piet, an implementation of our proposal, that makes use of overlay precomputation for answering spatial queries (aggregate or not). Our experimental evaluation showed that for a certain class of geometric queries with or without aggregation, overlay precomputation outperforms R-tre...
Classification of missing values in spatial data using spin models
Žukovič, Milan; 10.1103/PhysRevE.80.011116
2013-01-01
A problem of current interest is the estimation of spatially distributed processes at locations where measurements are missing. Linear interpolation methods rely on the Gaussian assumption, which is often unrealistic in practice, or normalizing transformations, which are successful only for mild deviations from the Gaussian behavior. We propose to address the problem of missing values estimation on two-dimensional grids by means of spatial classification methods based on spin (Ising, Potts, clock) models. The "spin" variables provide an interval discretization of the process values, and the spatial correlations are captured in terms of interactions between the spins. The spins at the unmeasured locations are classified by means of the "energy matching" principle: the correlation energy of the entire grid (including prediction sites) is estimated from the sample-based correlations. We investigate the performance of the spin classifiers in terms of computational speed, misclassification rate, class histogram an...
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).
Evaluating stream health based environmental justice model performance at different spatial scales
Daneshvar, Fariborz; Nejadhashemi, A. Pouyan; Zhang, Zhen; Herman, Matthew R.; Shortridge, Ashton; Marquart-Pyatt, Sandra
2016-07-01
This study evaluated the effects of spatial resolution on environmental justice analysis concerning stream health. The Saginaw River Basin in Michigan was selected since it is an area of concern in the Great Lakes basin. Three Bayesian Conditional Autoregressive (CAR) models (ordinary regression, weighted regression and spatial) were developed for each stream health measure based on 17 socioeconomic and physiographical variables at three census levels. For all stream health measures, spatial models had better performance compared to the two non-spatial ones at the census tract and block group levels. Meanwhile no spatial dependency was found at the county level. Multilevel Bayesian CAR models were also developed to understand the spatial dependency at the three levels. Results showed that considering level interactions improved models' prediction. Residual plots also showed that models developed at the block group and census tract (in contrary to county level models) are able to capture spatial variations.
Su, Qi; Li, Aming; Wang, Long
2017-02-01
Spatial reciprocity is generally regarded as a positive rule facilitating the evolution of cooperation. However, a few recent studies show that, in the snowdrift game, spatial structure still could be detrimental to cooperation. Here we propose a model of multiple interactive dynamics, where each individual can cooperate and defect simultaneously against different neighbors. We realize individuals' multiple interactions simply by endowing them with strategies relevant to probabilities, and every one decides to cooperate or defect with a probability. With multiple interactive dynamics, the cooperation level in square lattices is higher than that in the well-mixed case for a wide range of cost-to-benefit ratio r, implying that spatial structure favors cooperative behavior in the snowdrift game. Moreover, in square lattices, the most favorable strategy follows a simple relation of r, which confers theoretically the average evolutionary frequency of cooperative behavior. We further extend our study to various homogeneous and heterogeneous networks, which demonstrates the robustness of our results. Here multiple interactive dynamics stabilizes the positive role of spatial structure on the evolution of cooperation and individuals' distinct reactions to different neighbors can be a new line in understanding the emergence of cooperation.
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.
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.
Indoorgml - a Standard for Indoor Spatial Modeling
Li, Ki-Joune
2016-06-01
With recent progress of mobile devices and indoor positioning technologies, it becomes possible to provide location-based services in indoor space as well as outdoor space. It is in a seamless way between indoor and outdoor spaces or in an independent way only for indoor space. However, we cannot simply apply spatial models developed for outdoor space to indoor space due to their differences. For example, coordinate reference systems are employed to indicate a specific position in outdoor space, while the location in indoor space is rather specified by cell number such as room number. Unlike outdoor space, the distance between two points in indoor space is not determined by the length of the straight line but the constraints given by indoor components such as walls, stairs, and doors. For this reason, we need to establish a new framework for indoor space from fundamental theoretical basis, indoor spatial data models, and information systems to store, manage, and analyse indoor spatial data. In order to provide this framework, an international standard, called IndoorGML has been developed and published by OGC (Open Geospatial Consortium). This standard is based on a cellular notion of space, which considers an indoor space as a set of non-overlapping cells. It consists of two types of modules; core module and extension module. While core module consists of four basic conceptual and implementation modeling components (geometric model for cell, topology between cells, semantic model of cell, and multi-layered space model), extension modules may be defined on the top of the core module to support an application area. As the first version of the standard, we provide an extension for indoor navigation.
Spatial interaction in the run-off process
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Patrice Langlois
2002-05-01
Full Text Available The level of risk is defined by two standards : uncertainty and vulnerability. The latter is commonly estimated by an overlay of the different information layers, in order to obtain a local quantitative measure of the exposed properties. This approach is convenient for hazardous events clearly delimited and without any spatial diffusion, such as landslides or soil pollution. This approach is however soon bounded in the case of a dynamic process, such as the hydrological hazard. The overlay of different data gives a valuable appreciation of the streaming surfaces, but this remains insufficient to express the spatial dynamics of the flow. The global sensibility of a basin is not merely the sum of the local sensibilities. The global hazard is defined by the spatial organisation of the production or infiltration areas, and by their mutual relations, which validates the cellular automata approach to measure the level of organisation of the sensitive areas and to model the diffusion of the flows between these areas.
Estimation of Spatial Dynamic Nonparametric Durbin Models with Fixed Effects
Qian, Minghui; Hu, Ridong; Chen, Jianwei
2016-01-01
Spatial panel data models have been widely studied and applied in both scientific and social science disciplines, especially in the analysis of spatial influence. In this paper, we consider the spatial dynamic nonparametric Durbin model (SDNDM) with fixed effects, which takes the nonlinear factors into account base on the spatial dynamic panel…
Interactive Management and Updating of Spatial Data Bases
French, P.; Taylor, M.
1982-01-01
The decision making process, whether for power plant siting, load forecasting or energy resource planning, invariably involves a blend of analytical methods and judgement. Management decisions can be improved by the implementation of techniques which permit an increased comprehension of results from analytical models. Even where analytical procedures are not required, decisions can be aided by improving the methods used to examine spatially and temporally variant data. How the use of computer aided planning (CAP) programs and the selection of a predominant data structure, can improve the decision making process is discussed.
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 the spatial reach of the LFP.
Lindén, Henrik; Tetzlaff, Tom; Potjans, Tobias C; Pettersen, Klas H; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T
2011-12-08
The local field potential (LFP) reflects activity of many neurons in the vicinity of the recording electrode and is therefore useful for studying local network dynamics. Much of the nature of the LFP is, however, still unknown. There are, for instance, contradicting reports on the spatial extent of the region generating the LFP. Here, we use a detailed biophysical modeling approach to investigate the size of the contributing region by simulating the LFP from a large number of neurons around the electrode. We find that the size of the generating region depends on the neuron morphology, the synapse distribution, and the correlation in synaptic activity. For uncorrelated activity, the LFP represents cells in a small region (within a radius of a few hundred micrometers). If the LFP contributions from different cells are correlated, the size of the generating region is determined by the spatial extent of the correlated activity.
Spatial Database Modeling for Indoor Navigation Systems
Gotlib, Dariusz; Gnat, Miłosz
2013-12-01
For many years, cartographers are involved in designing GIS and navigation systems. Most GIS applications use the outdoor data. Increasingly, similar applications are used inside buildings. Therefore it is important to find the proper model of indoor spatial database. The development of indoor navigation systems should utilize advanced teleinformation, geoinformatics, geodetic and cartographical knowledge. The authors present the fundamental requirements for the indoor data model for navigation purposes. Presenting some of the solutions adopted in the world they emphasize that navigation applications require specific data to present the navigation routes in the right way. There is presented original solution for indoor data model created by authors on the basis of BISDM model. Its purpose is to expand the opportunities for use in indoor navigation.
Spatial Pattern of an Epidemic Model with Cross-diffusion
Institute of Scientific and Technical Information of China (English)
LI Li; JIN Zhen; SUN Gui-Quan
2008-01-01
Pattern formation of a spatial epidemic model with both serf- and cross-diffusion is investigated. From the Turing theory, it is well known that Thring pattern formation cannot occur for the equal self-diffusion coefficients.However, combined with cross-diffusion, the system will show emergence of isolated groups, i.e., stripe-like or spotted or coexistence of both, which we show by both mathematical ana/ysis and numerical simulations. Our study shows that the interaction of self- and cross-diffusion can be considered as an important mechanism for the appearance of complex spatiotemporal dynamics in epidemic models.
Management model application at nested spatial levels in Mediterranean Basins
Lo Porto, Antonio; De Girolamo, Anna Maria; Froebrich, Jochen
2014-05-01
and anthropogenic pressures acting on it to define management policies, three spatial levels must be taken into account: the basin, sub-basin and reach level. The common experience showed that different issues can be properly assessed and handled at these three levels. Furthermore different difficulties and problems affect modeling at the same spatial levels. The basin scale is the geographical unit (as required by the WFD) in which coherent management policy must be designed and a Program of Measures must be implemented. At this spatial level a comprehensive understanding of processes acting in the basin area is synthesized (i.e. nutrient loads delivered to the sea). In Mediterranean region land use is commonly very fragmented and also because of complex geomorphology the use of remote sensing can be not easy or sufficient to derive reliable land use maps of agricultural areas. The sub-basin level (processes can be assessed. It is sufficiently narrow to observe peculiarities of geomorphology and water works (i.e. check dams, water abstractions) that can greatly interact with natural flow. At this level modeling often fails in simulating actual streamflow. At local scale field observations can help also to overcome recorded flow measurements inconsistencies, due to the difficulties in metering low flows (i.e. rivulets can detour and skip flow meters) that often lead to underestimate extreme low flow. The modeling of Mediterranean river basins is then rather a challenge and the understanding of potential issues inherent in the focusing on different spatial levels must be recognized.
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
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.
Spatial Economics Model Predicting Transport Volume
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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.
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.
Trophic interactions induce spatial self-organization of microbial consortia on rough surfaces.
Wang, Gang; Or, Dani
2014-10-24
The spatial context of microbial interactions common in natural systems is largely absent in traditional pure culture-based microbiology. The understanding of how interdependent microbial communities assemble and coexist in limited spatial domains remains sketchy. A mechanistic model of cell-level interactions among multispecies microbial populations grown on hydrated rough surfaces facilitated systematic evaluation of how trophic dependencies shape spatial self-organization of microbial consortia in complex diffusion fields. The emerging patterns were persistent irrespective of initial conditions and resilient to spatial and temporal perturbations. Surprisingly, the hydration conditions conducive for self-assembly are extremely narrow and last only while microbial cells remain motile within thin aqueous films. The resulting self-organized microbial consortia patterns could represent optimal ecological templates for the architecture that underlie sessile microbial colonies on natural surfaces. Understanding microbial spatial self-organization offers new insights into mechanisms that sustain small-scale soil microbial diversity; and may guide the engineering of functional artificial microbial consortia.
One spatial dimensional finite volume three-body interaction for a short-range potential
Guo, Peng
2016-01-01
In this work, we use McGuire's model to describe scattering of three spinless identical particles in one spatial dimension, we first present analytic solutions of Faddeev's equation for scattering of three spinless particles in free space. The three particles interaction in finite volume is derived subsequently, and the quantization conditions by matching wave functions in free space and finite volume are presented in terms of two-body scattering phase shifts. The quantization conditions obtained in this work for short range interaction are L\\"uscher's formula like and consistent with Yang's results in \\cite{Yang:1967bm}.
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
Soliton interactions of integrable models
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Ruan Hangyu E-mail: hyruan@mail.nbip.net; Chen Yixin
2003-08-01
The solution of integrable (n+1)-dimensional KdV system in bilinear form yields a dromion solution that is localized in all directions. The interactions between two dromions are studied both in analytical and in numerical for three (n+1)-dimensional KdV-type equations (n=1, 2, 3). The same interactive properties between two dromions (solitons) are revealed for these models. The interactions between two dromions (solitons) may be elastic or inelastic for different form of solutions.
Soliton interactions of integrable models
Ruan Hang Yu
2003-01-01
The solution of integrable (n+1)-dimensional KdV system in bilinear form yields a dromion solution that is localized in all directions. The interactions between two dromions are studied both in analytical and in numerical for three (n+1)-dimensional KdV-type equations (n=1, 2, 3). The same interactive properties between two dromions (solitons) are revealed for these models. The interactions between two dromions (solitons) may be elastic or inelastic for different form of solutions.
Spatial self-organization in hybrid models of multicellular adhesion
Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard
2016-10-01
Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.
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...
Directory of Open Access Journals (Sweden)
Xiang Huang
2016-08-01
Full Text Available This paper presents a multiple artificial neural networks (MANN method with interaction noise for estimating the occurrence probabilities of different classes at any site in space. The MANN consists of several independent artificial neural networks, the number of which is determined by the neighbors around the target location. In the proposed algorithm, the conditional or pre-posterior (multi-point probabilities are viewed as output nodes, which can be estimated by weighted combinations of input nodes: two-point transition probabilities. The occurrence probability of a certain class at a certain location can be easily computed by the product of output probabilities using Bayes’ theorem. Spatial interaction or redundancy information can be measured in the form of interaction noises. Prediction results show that the method of MANN with interaction noise has a higher classification accuracy than the traditional Markov chain random fields (MCRF model and can successfully preserve small-scale features.
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.
Spatial Modeling of Iron Transformations Within Artificial Soil Aggregates
Kausch, M.; Meile, C.; Pallud, C.
2008-12-01
Structured soils exhibit significant variations in transport characteristics at the aggregate scale. Preferential flow occurs through macropores while predominantly diffusive exchange takes place in intra-aggregate micropores. Such environments characterized by mass transfer limitations are conducive to the formation of small-scale chemical gradients and promote strong spatial variation in processes controlling the fate of redox-sensitive elements such as Fe. In this study, we present a reactive transport model used to spatially resolve iron bioreductive processes occurring within a spherical aggregate at the interface between advective and diffusive domains. The model is derived from current conceptual models of iron(hydr)oxide (HFO) transformations and constrained by literature and experimental data. Data were obtained from flow-through experiments on artificial soil aggregates inoculated with Shewanella putrefaciens strain CN32, and include the temporal evolution of the bulk solution composition, as well as spatial information on the final solid phase distribution within aggregates. With all iron initially in the form of ferrihydrite, spatially heterogeneous formation of goethite/lepidocrocite, magnetite and siderite was observed during the course of the experiments. These transformations were reproduced by the model, which ascribes a central role to divalent iron as a driver of HFO transformations and master variable in the rate laws of the considered reaction network. The predicted dissolved iron breakthrough curves also match the experimental ones closely. Thus, the computed chemical concentration fields help identify factors governing the observed trends in the solid phase distribution patterns inside the aggregate. Building on a mechanistic description of transformation reactions, fluid flow and solute transport, the model was able to describe the observations and hence illustrates the importance of small-scale gradients and dynamics of bioreductive
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
Energy Technology Data Exchange (ETDEWEB)
Taeuber, Uwe C, E-mail: tauber@vt.edu [Department of Physics, Virginia Tech, Blacksburg, VA 24061-0435 (United States)
2011-09-15
It is well-established that including spatial structure and stochastic noise in models for predator-prey interactions invalidates the classical deterministic Lotka-Volterra picture of neutral population cycles. In contrast, stochastic models yield long-lived, but ultimately decaying erratic population oscillations, which can be understood through a resonant amplification mechanism for density fluctuations. In Monte Carlo simulations of spatial stochastic predator-prey systems, one observes striking complex spatio-temporal structures. These spreading activity fronts induce persistent correlations between predators and prey. In the presence of local particle density restrictions (finite prey carrying capacity), there exists an extinction threshold for the predator population. The accompanying continuous non-equilibrium phase transition is governed by the directed-percolation universality class. We employ field-theoretic methods based on the Doi-Peliti representation of the master equation for stochastic particle interaction models to (i) map the ensuing action in the vicinity of the absorbing state phase transition to Reggeon field theory, and (ii) to quantitatively address fluctuation-induced renormalizations of the population oscillation frequency, damping, and diffusion coefficients in the species coexistence phase.
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
Parmentier, Fabrice B R; Andrés, Pilar; Elford, Greg; Jones, Dylan M
2006-05-01
This study investigates whether memory for sequences of spatial locations can be represented hierarchically, that is, as successive groups containing the order of constituent locations. Two grouping manipulations are used: Temporal grouping, based on the verbal serial memory literature, and spatial grouping, based on recent empirical work on visuo-spatial serial memory. In Experiment 1, we examine the relationship between spatial grouping and temporal order and showed that recall performance increases when both temporal and spatial organization correlate, but decreases when they clash. Experiments 2 and 3 show that the latter result is confounded by differences in path length (length of spatial path defined by the locations) between conditions, and that no effect of the spatial organization is observed when path length is controlled for. In Experiment 4, an alternative method to spatial grouping, temporal grouping, is used to induce hierarchical organization. A recall advantage is found in the temporal grouping condition. The results suggest that hierarchical representations can be imposed on order information for visuo-spatial sequences, either when participants have pre-existing knowledge about the form of the path formed by the sequence or when temporal boundaries delimit chunks; that increased path length is the cause of the performance decrement observed when dots from separate spatial groups are presented successively; and that path length and more generally sequence characteristics should be taken into account in designing future research on visuo-spatial serial memory.
A Model of Colonic Crypts using SBML Spatial
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Carlo Maj
2013-09-01
Full Text Available The Spatial Processes package enables an explicit definition of a spatial environment on top of the normal dynamic modeling SBML capabilities. The possibility of an explicit representation of spatial dynamics increases the representation power of SBML. In this work we used those new SBML features to define an extensive model of colonic crypts composed of the main cellular types (from stem cells to fully differentiated cells, alongside their spatial dynamics.
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.
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.
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.
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 interaction of spatial scale and predator-prey functional response
Blaine, T.W.; DeAngelis, D.L.
1997-01-01
Predator-prey models with a prey-dependent functional response have the property that the prey equilibrium value is determined only by predator characteristics. However, in observed natural systems (for instance, snail-periphyton interactions in streams) the equilibrium periphyton biomass has been shown experimentally to be influenced by both snail numbers and levels of available limiting nutrient in the water. Hypothesizing that the observed patchiness in periphyton in streams may be part of the explanation for the departure of behavior of the equilibrium biomasses from predictions of the prey-dependent response of the snail-periphyton system, we developed and analyzed a spatially-explicit model of periphyton in which snails were modeled as individuals in their movement and feeding, and periphyton was modeled as patches or spatial cells. Three different assumptions on snail movement were used: (1) random movement between spatial cells, (2) tracking by snails of local abundances of periphyton, and (3) delayed departure of snails from cells to reduce costs associated with movement. Of these assumptions, only the third strategy, based on an herbivore strategy of staying in one patch until local periphyton biomass concentration falls below a certain threshold amount, produced results in which both periphyton and snail biomass increased with nutrient input. Thus, if data are averaged spatially over the whole system, we expect that a ratio-dependent functional response may be observed if the herbivore behaves according to the third assumption. Both random movement and delayed cell departure had the result that spatial heterogeneity of periphyton increased with nutrient input.
Interactive Dimensioning of Parametric Models
Kelly, T.
2015-05-01
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. © 2015 The Author(s) Computer Graphics Forum © 2015 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.
Modelling land surface - atmosphere interactions
DEFF Research Database (Denmark)
Rasmussen, Søren Højmark
related to inaccurate land surface modelling, e.g. enhanced warm bias in warm dry summer months. Coupling the regional climate model to a hydrological model shows the potential of improving the surface flux simulations in dry periods and the 2 m air temperature in general. In the dry periods......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...... 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...
Continuous time modelling of dynamical spatial lattice data observed at sparsely distributed times
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl; Møller, Jesper
2007-01-01
Summary. We consider statistical and computational aspects of simulation-based Bayesian inference for a spatial-temporal model based on a multivariate point process which is only observed at sparsely distributed times. The point processes are indexed by the sites of a spatial lattice, and they ex......Summary. We consider statistical and computational aspects of simulation-based Bayesian inference for a spatial-temporal model based on a multivariate point process which is only observed at sparsely distributed times. The point processes are indexed by the sites of a spatial lattice......, and they exhibit spatial interaction. For specificity we consider a particular dynamical spatial lattice data set which has previously been analysed by a discrete time model involving unknown normalizing constants. We discuss the advantages and disadvantages of using continuous time processes compared...
Interactive modeling of storm impact
van Rooijen, A.; Baart, F.; Roelvink, J. A.; Donchyts, G.; Scheel, F.; de Boer, W.
2014-12-01
In the past decades the impact of storms on the coastal zone has increasingly drawn the attention of policy makers and coastal planners, engineers and researchers. The mean reason for this interest is the high density of the world's population living near the ocean, in combination with climate change. Due to sea level rise and extremer weather conditions, many of the world's coastlines are becoming more vulnerable to the potential of flooding. Currently it is common practice to predict storm impact using physics-based numerical models. The numerical model utilizes several inputs (e.g. bathymetry, waves, surge) to calculate the impact on the coastline. Traditionally, the numerical modeller takes the following three steps: schematization/model setup, running and post-processing. This process generally has a total feedback time in the order of hours to days, and is suitable for so-called confirmatory modelling.However, often models are applied as an exploratory tool, in which the effect of e.g. different hydraulic conditions, or measures is investigated. The above described traditional work flow is not the most efficient method for exploratory modelling. Interactive modelling lets users adjust a simulation while running. For models typically used for storm impact studies (e.g. XBeach, Delft3D, D-Flow FM), the user can for instance change the storm surge level, wave conditions, or add a measure such as a nourishment or a seawall. The model will take the adjustments into account immediately, and will directly compute the effect. Using this method, tools can be developed in which stakeholders (e.g. coastal planners, policy makers) are in control and together evaluate ideas by interacting with the model. Here we will show initial results for interactive modelling with a storm impact model.
Platz, M.; Rapp, J.; Groessler, M.; Niehaus, E.; Babu, A.; Soman, B.
2014-11-01
A Spatial Decision Support System (SDSS) provides support for decision makers and should not be viewed as replacing human intelligence with machines. Therefore it is reasonable that decision makers are able to use a feature to analyze the provided spatial decision support in detail to crosscheck the digital support of the SDSS with their own expertise. Spatial decision support is based on risk and resource maps in a Geographic Information System (GIS) with relevant layers e.g. environmental, health and socio-economic data. Spatial fuzzy logic allows the representation of spatial properties with a value of truth in the range between 0 and 1. Decision makers can refer to the visualization of the spatial truth of single risk variables of a disease. Spatial fuzzy logic rules that support the allocation of limited resources according to risk can be evaluated with measure theory on topological spaces, which allows to visualize the applicability of this rules as well in a map. Our paper is based on the concept of a spatial fuzzy logic on topological spaces that contributes to the development of an adaptive Early Warning And Response System (EWARS) providing decision support for the current or future spatial distribution of a disease. It supports the decision maker in testing interventions based on available resources and apply risk mitigation strategies and provide guidance tailored to the geo-location of the user via mobile devices. The software component of the system would be based on open source software and the software developed during this project will also be in the open source domain, so that an open community can build on the results and tailor further work to regional or international requirements and constraints. A freely available EWARS Spatial Fuzzy Logic Demo was developed wich enables a user to visualize risk and resource maps based on individual data in several data formats.
A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data
Directory of Open Access Journals (Sweden)
Weifeng Li
2014-01-01
Full Text Available The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning. This study aimed to analyze the spatial interaction based on the large-scale mobile phone data. The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics. A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement. The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association. A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application. The spatial interaction patterns and the representative features proved the rationality of the proposed framework.
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 perspecti
Interactive graphics for geometry modeling
Wozny, M. J.
1984-01-01
An interactive vector capability to create geometry and a raster color shaded rendering capability to sample and verify interim geometric design steps through color snapshots is described. The development is outlined of the underlying methodology which facilitates computer aided engineering and design. At present, raster systems cannot match the interactivity and line-drawing capability of refresh vector systems. Consequently, an intermediate step in mechanical design is used to create objects interactively on the vector display and then scan convert the wireframe model to render it as a color shaded object on a raster display. Several algorithms are presented for rendering such objects. Superquadric solid primitive extend the class of primitives normally used in solid modelers.
Model Checking Interactive Markov Chains
Neuhausser, M.; Zhang, Lijun; Esparza, J.; Majumdar, R.
2010-01-01
Hermanns has introduced interactive Markov chains (IMCs) which arise as an orthogonal extension of labelled transition systems and continuous-time Markov chains (CTMCs). IMCs enjoy nice compositional aggregation properties which help to minimize the state space incrementally. However, the model chec
Modeling Interactions in Small Groups
Heise, David R.
2013-01-01
A new theory of interaction within small groups posits that group members initiate actions when tension mounts between the affective meanings of their situational identities and impressions produced by recent events. Actors choose partners and behaviors so as to reduce the tensions. A computer model based on this theory, incorporating reciprocal…
Modeling temporal and spatial variability of crop yield
Bonetti, S.; Manoli, G.; Scudiero, E.; Morari, F.; Putti, M.; Teatini, P.
2014-12-01
In a world of increasing food insecurity the development of modeling tools capable of supporting on-farm decision making processes is highly needed to formulate sustainable irrigation practices in order to preserve water resources while maintaining adequate crop yield. The design of these practices starts from the accurate modeling of soil-plant-atmosphere interaction. We present an innovative 3D Soil-Plant model that couples 3D hydrological soil dynamics with a mechanistic description of plant transpiration and photosynthesis, including a crop growth module. Because of its intrinsically three dimensional nature, the model is able to capture spatial and temporal patterns of crop yield over large scales and under various climate and environmental factors. The model is applied to a 25 ha corn field in the Venice coastland, Italy, that has been continuously monitored over the years 2010 and 2012 in terms of both hydrological dynamics and yield mapping. The model results satisfactorily reproduce the large variability observed in maize yield (from 2 to 15 ton/ha). This variability is shown to be connected to the spatial heterogeneities of the farmland, which is characterized by several sandy paleo-channels crossing organic-rich silty soils. Salt contamination of soils and groundwater in a large portion of the area strongly affects the crop yield, especially outside the paleo-channels, where measured salt concentrations are lower than the surroundings. The developed model includes a simplified description of the effects of salt concentration in soil water on transpiration. The results seem to capture accurately the effects of salt concentration and the variability of the climatic conditions occurred during the three years of measurements. This innovative modeling framework paves the way to future large scale simulations of farmland dynamics.
Spatially explicit fate modelling of nanomaterials in natural waters
Quik, J.T.K.; Klein, de J.J.M.; Koelmans, A.A.
2015-01-01
Site specific exposure assessments for engineered nanoparticles (ENPs) require spatially explicit fate models, which however are not yet available. Here we present an ENP fate model (NanoDUFLOW) that links ENP specific process descriptions to a spatially explicit hydrological model. The link enables
Mining multilevel spatial association rules with cloud models
Institute of Scientific and Technical Information of China (English)
YANG Bin; ZHU Zhong-ying
2005-01-01
The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates the vague and random use of linguistic terms in a unified way. With these models, spatial and nonspatial attribute values are well generalized at multiple levels, allowing discovery of strong spatial association rules.Combining the cloud model based method with Apriori algorithms for mining association rules from a spatial database shows benefits in being effective and flexible.
Liu, Chang; Li, Feng-Ri; Zhen, Zhen
2014-10-01
Abstract: Based on the data from Chinese National Forest Inventory (CNFI) and Key Ecological Benefit Forest Monitoring plots (5075 in total) in Heilongjiang Province in 2010 and concurrent meteorological data coming from 59 meteorological stations located in Heilongjiang, Jilin and Inner Mongolia, this paper established a spatial error model (SEM) by GeoDA using carbon storage as dependent variable and several independent variables, including diameter of living trees (DBH), number of trees per hectare (TPH), elevation (Elev), slope (Slope), and product of precipitation and temperature (Rain_Temp). Global Moran's I was computed for describing overall spatial autocorrelations of model results at different spatial scales. Local Moran's I was calculated at the optimal bandwidth (25 km) to present spatial distribution residuals. Intra-block spatial variances were computed to explain spatial heterogeneity of residuals. Finally, a spatial distribution map of carbon storage in Heilongjiang was visualized based on predictions. The results showed that the distribution of forest carbon storage in Heilongjiang had spatial effect and was significantly influenced by stand, topographic and meteorological factors, especially average DBH. SEM could solve the spatial autocorrelation and heterogeneity well. There were significant spatial differences in distribution of forest carbon storage. The carbon storage was mainly distributed in Zhangguangcai Mountain, Xiao Xing'an Mountain and Da Xing'an Mountain where dense, forests existed, rarely distributed in Songnen Plains, while Wanda Mountain had moderate-level carbon storage.
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
Kurtulus, Aytac
2013-01-01
The aim of this study was to investigate the effects of web-based interactive virtual tours on the development of prospective mathematics teachers' spatial skills. The study was designed based on experimental method. The "one-group pre-test post-test design" of this method was taken as the research model. The study was conducted with 3rd year…
An API for Integrating Spatial Context Models with Spatial Reasoning Algorithms
DEFF Research Database (Denmark)
Kjærgaard, Mikkel Baun
2006-01-01
The integration of context-aware applications with spatial context models is often done using a common query language. However, algorithms that estimate and reason about spatial context information can benefit from a tighter integration. An object-oriented API makes such integration possible and ...... modeling. The utility of the API is evaluated in several real-world cases from an indoor location system, and spans several types of spatial reasoning algorithms.......The integration of context-aware applications with spatial context models is often done using a common query language. However, algorithms that estimate and reason about spatial context information can benefit from a tighter integration. An object-oriented API makes such integration possible...
Institute of Scientific and Technical Information of China (English)
WU Wenjie; ZHANG Wenzhong; JIN Fengjun; DENG Yu
2009-01-01
This paper aims to explore urban geography with a new perspective. Endowed with the urban geography connotations, an improved data field model is employed to integrate temporal dimension into spatial process of cities in a typical region in this article. Taking the Beijing-Shanghai Corridor including 18 cities as an example, the authors chose the city centricity index (CCI) and the spatial data field model to analyze the evolution process and features of sub-region and urban spatial interaction in this corridor based on the data of 1991, 1996 and 2002. Through the analysis, we found that: 1) with the improvement of the urbanization level and the development of urban economy, the cities' CCI grew, the urban spatial radiative potential enhanced and the radiative range expanded gradually, which reflects the urban spatial interaction's intensity has been increasing greatly; 2) although the spatial interaction intensity among the cities and sub-regions in the Beijing-Shanghai Corridor was growing constantly, the gap of the spatial interaction strength among different cities and sub-regions was widening, and the spatial division between the developed areas and the less developed areas was obvious; and 3) the intensity of the spatial interaction of Beijing, Shanghai and their urban agglomerations was far greater than that in small cities of other parts of the corridor, and it may have a strong drive force on the choice of spatial location of the economic activities.
Anisotropic exchange-interaction model: From the Potts model to the exchange-interaction model
King, T. C.; Chen, H. H.
1995-04-01
A spin model called the anisotropic exchange-interaction model is proposed. The Potts model, the exchange-interaction model, and the spin-1/2 anisotropic Heisenberg model are special cases of the proposed model. Thermodynamic properties of the model on the bcc and the fcc lattices are determined by the constant-coupling approximation.
Cosmological models with interacting components and mass-varying neutrinos
Collodel, Lucas G
2012-01-01
A model for a homogeneous and isotropic spatially flat Universe, composed of baryons, radiation, neutrinos, dark matter and dark energy is analyzed. We infer that dark energy (considered to behave as a scalar field) interacts with dark matter (either by the Wetterich model, or by the Anderson and Carroll model) and with neutrinos by a model proposed by Brookfield et al.. The latter is understood to have a mass-varying behavior. We show that for a very-softly varying field, both interacting models for dark matter give the same results. The models reproduce the expected red-shift performances of the present behavior of the Universe.
Modelling spatial vagueness based on type-2 fuzzy set
Institute of Scientific and Technical Information of China (English)
DU Guo-ning; ZHU Zhong-ying
2006-01-01
The modelling and formal characterization of spatial vagueness plays an increasingly important role in the implementation of Geographic Information System (GIS). The concepts involved in spatial objects of GIS have been investigated and acknowledged as being vague and ambiguous. Models and methods which describe and handle fuzzy or vague (rather than crisp or determinate) spatial objects, will be more necessary in GIS. This paper proposes a new method for modelling spatial vagueness based on type-2 fuzzy set, which is distinguished from the traditional type-1 fuzzy methods and more suitable for describing and implementing the vague concepts and objects in GIS.
Spatial interactions among ecosystem services in an urbanizing agricultural watershed
Qiu, Jiangxiao; Turner, Monica G.
2013-01-01
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. PMID:23818612
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.
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
Book review: Statistical Analysis and Modelling of Spatial Point Patterns
DEFF Research Database (Denmark)
Møller, Jesper
2009-01-01
Statistical Analysis and Modelling of Spatial Point Patterns by J. Illian, A. Penttinen, H. Stoyan and D. Stoyan. Wiley (2008), ISBN 9780470014912......Statistical Analysis and Modelling of Spatial Point Patterns by J. Illian, A. Penttinen, H. Stoyan and D. Stoyan. Wiley (2008), ISBN 9780470014912...
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.
Consequences of spatial autocorrelation for niche-based models
DEFF Research Database (Denmark)
Segurado, P.; Araújo, Miguel B.; Kunin, W. E.
2006-01-01
variables, as measured by Moran's I, was analysed and compared between models. The effects of systematic subsampling of the data set and the inclusion of a contagion term to deal with spatial autocorrelation in models were assessed with projections made with GLM, as it was with this method that estimates...... were vulnerable to the effects of spatial autocorrelation. 5. The procedures utilized to reduce the effects of spatial autocorrelation had varying degrees of success. Subsampling was partially effective in avoiding the inflation effect, whereas the inclusion of a contagion term fully eliminated......1. Spatial autocorrelation is an important source of bias in most spatial analyses. We explored the bias introduced by spatial autocorrelation on the explanatory and predictive power of species' distribution models, and make recommendations for dealing with the problem. 2. Analyses were based...
Emergent universe in spatially flat cosmological model
Zhang, Kaituo; Yu, Hongwei
2013-01-01
The scenario of an emergent universe provides a promising resolution to the big bang singularity in universes with positive or negative spatial curvature. It however remains unclear whether the scenario can be successfully implemented in a spatially flat universe which seems to be favored by present cosmological observations. In this paper, we study the stability of Einstein static state solutions in a spatially flat Shtanov-Sahni braneworld scenario. With a negative dark radiation term included and assuming a scalar field as the only matter energy component, we find that the universe can stay at an Einstein static state past eternally and then evolve to an inflation phase naturally as the scalar field climbs up its potential slowly. In addition, we also propose a concrete potential of the scalar field that realizes this scenario.
A formal model for access control with supporting spatial context
Institute of Scientific and Technical Information of China (English)
ZHANG Hong; HE YePing; SHI ZhiGuo
2007-01-01
There is an emerging recognition of the importance of utilizing contextual information in authorization decisions. Controlling access to resources in the field of wireless and mobile networking require the definition of a formal model for access control with supporting spatial context. However, traditional RBAC model does not specify these spatial requirements. In this paper, we extend the existing RBAC model and propose the SC-RBAC model that utilizes spatial and location-based information in security policy definitions. The concept of spatial role is presented,and the role is assigned a logical location domain to specify the spatial boundary.Roles are activated based on the current physical position of the user which obtained from a specific mobile terminal. We then extend SC-RBAC to deal with hierarchies, modeling permission, user and activation inheritance, and prove that the hierarchical spatial roles are capable of constructing a lattice which is a means for articulate multi-level security policy and more suitable to control the information flow security for safety-critical location-aware information systems. Next, constrained SC-RBAC allows express various spatial separations of duty constraints,location-based cardinality and temporal constraints for specify fine-grained spatial semantics that are typical in location-aware systems. Finally, we introduce 9 invariants for the constrained SC-RBAC and its basic security theorem is proven. The constrained SC-RBAC provides the foundation for applications in need of the constrained spatial context aware access control.
Modeling the spatial reach of the LFP
DEFF Research Database (Denmark)
Lindén, Henrik; Tetzlaff, Tom; Potjans, Tobias C
2011-01-01
The local field potential (LFP) reflects activity of many neurons in the vicinity of the recording electrode and is therefore useful for studying local network dynamics. Much of the nature of the LFP is, however, still unknown. There are, for instance, contradicting reports on the spatial extent...... distribution, and the correlation in synaptic activity. For uncorrelated activity, the LFP represents cells in a small region (within a radius of a few hundred micrometers). If the LFP contributions from different cells are correlated, the size of the generating region is determined by the spatial extent...
Interactive Computer Administration of a Spatial Reasoning Test.
1980-04-01
Scheinfeld, 1968; MacCoby & Jacklin, 1974), it was of interest to determine whether sex differences existed for this test. Thus, a t test was used to compare...better spatial ability (Garai & Scheinfeld, 1968; MacCoby & Jacklin, 1974) and restructuring ability ( MacCoby , 1966; Sweeney, i953; Terman & Tyler, 1954... MacCoby ,i9eC; Terman & Tyler, 154; Tyler, 1965) and better in perceptual speed and fluency (Garai & Scheinfeld, 1968). The failure to obtain sex
Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas
2017-01-01
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. PMID:28190948
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
Stress can affect the brain functionality in many ways. As the synaptic vesicles have a major role in nervous signal transportation in synapses, their distribution in relationship to the active zone is very important in studying the neuron responses. We study the effect of stress on brain functio...... 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....
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.
Spatial heterogeneity of plant–soil feedback affects root interactions and interspecific competition
Hendriks, M.; Ravenek, J.; Smit-Tiekstra, A.E.; Paauw, van der J.W.M.; Caluwe, de H.; Putten, van der W.H.; Kroon, de H.; Mommer, L.
2015-01-01
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 heterogeneit
Modelling spatial patterns of economic activity in the Netherlands
Yang, Jung-Hun; Frenken, Koen; Van Oort, Frank; Visser, Evert-Jan
2012-01-01
Understanding how spatial configurations of economic activity emerge is important when formulating spatial planning and economic policy. Not only micro-simulation and agent-based model such as UrbanSim, ILUMAS and SIMFIRMS, but also Simon's model of hierarchical concentration have widely applied, for this purpose. These models, however, have limitations with respect to simulating structural changes in spatial economic systems and the impact of proximity. The present paper proposes a model of firm development that is based on behavioural rules such as growth, closure, spin-off and relocation. An important aspect of the model is that locational preferences of firms are based on agglomeration advantages, accessibility of markets and congestion, allowing for a proper description of concentration and deconcentration tendencies. By comparing the outcomes of the proposed model with real world data, we will calibrate the parameters and assess how well the model predicts existing spatial configurations and decide. The...
Spatial emission modelling for residential wood combustion in Denmark
DEFF Research Database (Denmark)
Plejdrup, Marlene Schmidt; Nielsen, Ole-Kenneth; Brandt, Jørgen
2016-01-01
Residential wood combustion (RWC) is a major contributor to atmospheric pollution especially for particulate matter. Air pollution has significant impact on human health, and it is therefore important to know the human exposure. For this purpose, it is necessary with a detailed high resolution...... spatial distribution of emissions. In previous studies as well as in the model previously used in Denmark, the spatial resolution is limited, e.g. municipality or county level. Further, in many cases models are mainly relying on population density data as the spatial proxy for distributing the emissions....... This paper describes the new Danish model for high resolution spatial distribution of emissions from RWC to air. The new spatial emission model is based on information regarding building type, and primary and supplementary heating installations from the Danish Building and Dwelling Register (BBR), which...
Thematic and spatial resolutions affect model-based predictions of tree species distribution.
Directory of Open Access Journals (Sweden)
Yu Liang
Full Text Available 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.
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.
Free-streaming radiation in cosmological models with spatial curvature
Wilson, M. L.
1982-01-01
The effects of spatial curvature on radiation anisotropy are examined for the standard Friedmann-Robertson-Walker model universes. The effect of curvature is found to be very important when considering fluctuations with wavelengths comparable to the horizon. It is concluded that the behavior of radiation fluctuations in models with spatial curvature is quite different from that in spatially flat models, and that models with negative curvature are most strikingly different. It is therefore necessary to take the curvature into account in careful studies of the anisotropy of the microwave background.
Krueger, Juliane; Royal, David W.; Fister, Matthew C.; Wallace, Mark T.
2009-01-01
Previous work has established that the spatial receptive fields (SRFs) of multisensory neurons in the cerebral cortex are strikingly heterogeneous, and that SRF architecture plays an important deterministic role in sensory responsiveness and multisensory integrative capacities. The initial part of this contribution serves to review these findings detailing the key features of SRF organization in cortical multisensory populations by highlighting work from the cat anterior ectosylvian sulcus (AES). In addition, we have recently conducted parallel studies designed to examine SRF architecture in the classic model for multisensory studies, the cat superior colliculus (SC), and we present some of the preliminary observations from the SC here. An examination of individual SC neurons revealed marked similarities between their unisensory (i.e., visual and auditory) SRFs, as well as between these unisensory SRFs and the multisensory SRF. Despite these similarities within individual neurons, different SC neurons had SRFs that ranged from a single area of greatest activation (hot spot) to multiple and spatially discrete hot spots. Similar to cortical multisensory neurons, the interactive profile of SC neurons was correlated strongly to SRF architecture, closely following the principle of inverse effectiveness. Thus, large and often superadditive multisensory response enhancements were typically seen at SRF locations where visual and auditory stimuli were weakly effective. Conversely, subadditive interactions were seen at SRF locations where stimuli were highly effective. Despite the unique functions characteristic of cortical and subcortical multisensory circuits, our results suggest a strong mechanistic interrelationship between SRF microarchitecture and integrative capacity. PMID:19698773
Naujokaitis-Lewis, Ilona R; Curtis, Janelle M R; Arcese, Peter; Rosenfeld, Jordan
2009-02-01
Population viability analysis (PVA) is an effective framework for modeling species- and habitat-recovery efforts, but uncertainty in parameter estimates and model structure can lead to unreliable predictions. Integrating complex and often uncertain information into spatial PVA models requires that comprehensive sensitivity analyses be applied to explore the influence of spatial and nonspatial parameters on model predictions. We reviewed 87 analyses of spatial demographic PVA models of plants and animals to identify common approaches to sensitivity analysis in recent publications. In contrast to best practices recommended in the broader modeling community, sensitivity analyses of spatial PVAs were typically ad hoc, inconsistent, and difficult to compare. Most studies applied local approaches to sensitivity analyses, but few varied multiple parameters simultaneously. A lack of standards for sensitivity analysis and reporting in spatial PVAs has the potential to compromise the ability to learn collectively from PVA results, accurately interpret results in cases where model relationships include nonlinearities and interactions, prioritize monitoring and management actions, and ensure conservation-planning decisions are robust to uncertainties in spatial and nonspatial parameters. Our review underscores the need to develop tools for global sensitivity analysis and apply these to spatial PVA.
Integrated hydrologic modeling: Effects of spatial scale, discretization and initialization
Seck, A.; Welty, C.; Maxwell, R. M.
2011-12-01
Groundwater discharge contributes significantly to the annual flows of Chesapeake Bay tributaries and is presumed to contribute to the observed lag time between the implementation of management actions and the environmental response in the Chesapeake Bay. To investigate groundwater fluxes and flow paths and interaction with surface flow, we have developed a fully distributed integrated hydrologic model of the Chesapeake Bay Watershed using ParFlow. Here we present a comparison of model spatial resolution and initialization methods. We have studied the effect of horizontal discretization on overland flow processes at a range of scales. Three nested model domains have been considered: the Monocacy watershed (5600 sq. km), the Potomac watershed (92000 sq. km) and the Chesapeake Bay watershed (400,000 sq. km). Models with homogeneous subsurface and topographically-derived slopes were evaluated at 500-m, 1000-m, 2000-m, and 4000-m grid resolutions. Land surface slopes were derived from resampled DEMs and corrected using stream networks. Simulation results show that the overland flow processes are reasonably well represented with a resolution up to 2000 m. We observe that the effects of horizontal resolution dissipate with larger scale models. Using a homogeneous model that includes subsurface and surface terrain characteristics, we have evaluated various initialization methods for the integrated Monocacy watershed model. This model used several options for water table depths and two rainfall forcing methods including (1) a synthetic rainfall-recession cycle corresponding to the region's average annual rainfall rate, and (2) an initial shut-off of rainfall forcing followed by a rainfall-recession cycling. Results show the dominance of groundwater generated runoff during a first phase of the simulation followed by a convergence towards more balanced runoff generation mechanisms. We observe that the influence of groundwater runoff increases in dissected relief areas
Directory of Open Access Journals (Sweden)
Wu Hanguang
2007-01-01
Full Text Available The performance of multiple-input multiple-output (MIMO systems is greatly influenced by the spatial-temporal correlation properties of the underlying MIMO channels. This paper investigates the spatial-temporal correlation characteristics of the spatial channel model (SCM in the Third Generation Partnership Project (3GPP and the Kronecker-based stochastic model (KBSM at three levels, namely, the cluster level, link level, and system level. The KBSM has both the spatial separability and spatial-temporal separability at all the three levels. The spatial-temporal separability is observed for the SCM only at the system level, but not at the cluster and link levels. The SCM shows the spatial separability at the link and system levels, but not at the cluster level since its spatial correlation is related to the joint distribution of the angle of arrival (AoA and angle of departure (AoD. The KBSM with the Gaussian-shaped power azimuth spectrum (PAS is found to fit best the 3GPP SCM in terms of the spatial correlations. Despite its simplicity and analytical tractability, the KBSM is restricted to model only the average spatial-temporal behavior of MIMO channels. The SCM provides more insights of the variations of different MIMO channel realizations, but the implementation complexity is relatively high.
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.
Quantization of a billiard model for interacting particles
Papenbrock, T; Papenbrock, Thomas; Prosen, Tomaz
2000-01-01
We consider a billiard model of a self-bound, interacting three-body system in two spatial dimensions. Numerical studies show that the classical dynamics is chaotic. The corresponding quantum system displays spectral fluctuations that exhibit small deviations from random matrix theory predictions. These can be understood in terms of scarring caused by a 1-parameter family of orbits inside the collinear manifold.
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.
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.
Sponge interactions with spatial competitors in the Spermonde Archipelago
Voogd, de N.J.; Becking, L.E.; Hoeksema, B.W.; Noor, A.; Soest, van R.W.M.
2003-01-01
This study describes the in situ effects of four bioactive sponges on their neighbours at three different locations and two depths in the Spermonde Archipelago, SW Sulawesi, Indonesia. The natural rates of interaction between the sponge species and eight possible competitive invertebrate groups were
Sponge interactions with spatial competitors in the Spermonde Archipelago
Voogd, de N.J.; Becking, L.E.; Hoeksema, B.W.; Noor, A.; Soest, van R.W.M.
2003-01-01
This study describes the in situ effects of four bioactive sponges on their neighbours at three different locations and two depths in the Spermonde Archipelago, SW Sulawesi, Indonesia. The natural rates of interaction between the sponge species and eight possible competitive invertebrate groups were
Error Threshold for Spatially Resolved Evolution in the Quasispecies Model
Energy Technology Data Exchange (ETDEWEB)
Altmeyer, S.; McCaskill, J. S.
2001-06-18
The error threshold for quasispecies in 1, 2, 3, and {infinity} dimensions is investigated by stochastic simulation and analytically. The results show a monotonic decrease in the maximal sustainable error probability with decreasing diffusion coefficient, independently of the spatial dimension. It is thereby established that physical interactions between sequences are necessary in order for spatial effects to enhance the stabilization of biological information. The analytically tractable behavior in an {infinity} -dimensional (simplex) space provides a good guide to the spatial dependence of the error threshold in lower dimensional Euclidean space.
Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification
Liu, Da; Li, Jianxun
2016-01-01
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. PMID:27999259
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.
Full feature data model for spatial information network integration
Institute of Scientific and Technical Information of China (English)
DENG Ji-qiu; BAO Guang-shu
2006-01-01
In allusion to the difficulty of integrating data with different models in integrating spatial information,the characteristics of raster structure, vector structure and mixed model were analyzed, and a hierarchical vectorraster integrative full feature model was put forward by integrating the advantage of vector and raster model and using the object-oriented method. The data structures of the four basic features, i.e. point, line, surface and solid,were described. An application was analyzed and described, and the characteristics of this model were described. In this model, all objects in the real world are divided into and described as features with hierarchy, and all the data are organized in vector. This model can describe data based on feature, field, network and other models, and avoid the disadvantage of inability to integrate data based on different models and perform spatial analysis on them in spatial information integration.
An Improved Direction Relation Detection Model for Spatial Objects
Institute of Scientific and Technical Information of China (English)
FENG Yucai; YI Baolin
2004-01-01
Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries.
Spatial Statistical Procedures to Validate Input Data in Energy Models
Energy Technology Data Exchange (ETDEWEB)
Johannesson, G.; Stewart, J.; Barr, C.; Brady Sabeff, L.; George, R.; Heimiller, D.; Milbrandt, A.
2006-01-01
Energy modeling and analysis often relies on data collected for other purposes such as census counts, atmospheric and air quality observations, economic trends, and other primarily non-energy related uses. Systematic collection of empirical data solely for regional, national, and global energy modeling has not been established as in the abovementioned fields. Empirical and modeled data relevant to energy modeling is reported and available at various spatial and temporal scales that might or might not be those needed and used by the energy modeling community. The incorrect representation of spatial and temporal components of these data sets can result in energy models producing misleading conclusions, especially in cases of newly evolving technologies with spatial and temporal operating characteristics different from the dominant fossil and nuclear technologies that powered the energy economy over the last two hundred years. Increased private and government research and development and public interest in alternative technologies that have a benign effect on the climate and the environment have spurred interest in wind, solar, hydrogen, and other alternative energy sources and energy carriers. Many of these technologies require much finer spatial and temporal detail to determine optimal engineering designs, resource availability, and market potential. This paper presents exploratory and modeling techniques in spatial statistics that can improve the usefulness of empirical and modeled data sets that do not initially meet the spatial and/or temporal requirements of energy models. In particular, we focus on (1) aggregation and disaggregation of spatial data, (2) predicting missing data, and (3) merging spatial data sets. In addition, we introduce relevant statistical software models commonly used in the field for various sizes and types of data sets.
Spatial Statistical Procedures to Validate Input Data in Energy Models
Energy Technology Data Exchange (ETDEWEB)
Lawrence Livermore National Laboratory
2006-01-27
Energy modeling and analysis often relies on data collected for other purposes such as census counts, atmospheric and air quality observations, economic trends, and other primarily non-energy-related uses. Systematic collection of empirical data solely for regional, national, and global energy modeling has not been established as in the above-mentioned fields. Empirical and modeled data relevant to energy modeling is reported and available at various spatial and temporal scales that might or might not be those needed and used by the energy modeling community. The incorrect representation of spatial and temporal components of these data sets can result in energy models producing misleading conclusions, especially in cases of newly evolving technologies with spatial and temporal operating characteristics different from the dominant fossil and nuclear technologies that powered the energy economy over the last two hundred years. Increased private and government research and development and public interest in alternative technologies that have a benign effect on the climate and the environment have spurred interest in wind, solar, hydrogen, and other alternative energy sources and energy carriers. Many of these technologies require much finer spatial and temporal detail to determine optimal engineering designs, resource availability, and market potential. This paper presents exploratory and modeling techniques in spatial statistics that can improve the usefulness of empirical and modeled data sets that do not initially meet the spatial and/or temporal requirements of energy models. In particular, we focus on (1) aggregation and disaggregation of spatial data, (2) predicting missing data, and (3) merging spatial data sets. In addition, we introduce relevant statistical software models commonly used in the field for various sizes and types of data sets.
Study on spatial temporal model in property management information system
Institute of Scientific and Technical Information of China (English)
李良宝; 李晓东
2004-01-01
Time is an important dimension for information in the geographical information system. Data, such as the historical state of target property space and related events causing the state to be changed, should be saved as important files. This should be applied to property management. This paper designs and constructs a spatial temporal model, which is suitable to the property data changing management and spatial temporal query by analyzing the basic types and characteristics of property management spatial changing time and date. This model uses current and historical situational layers to organize and set up the relationship between current situation data and historical dates according to spatial temporal topological relations in property entities. By using Map Basic, housing property management and spatial query is realized.
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.
Scale-based spatial data model for GIS
Institute of Scientific and Technical Information of China (English)
WEI Zu-kuan
2004-01-01
Being the primary media of geographical information and the elementary objects manipulated, almost all of maps adopt the layer-based model to represent geographic information in the existent GIS. However, it is difficult to extend the map represented in layer-based model. Furthermore, in Web-Based GIS, It is slow to transmit the spatial data for map viewing. In this paper, for solving the questions above, we have proposed a new method for representing the spatial data. That is scale-based model. In this model we represent maps in three levels: scale-view, block, and spatial object, and organize the maps in a set of map layers, named Scale-View, which associates some given scales.Lastly, a prototype Web-Based GIS using the proposed spatial data representation is described briefly.
Spatial modelling of wind speed around windbreaks
Vigiak, O.; Sterk, G.; Warren, A.; Hagen, L.J.
2003-01-01
This paper presents a model to integrate windbreak shelter effects into a Geographic Information System (GIS). The GIS procedure incorporates the 1999 version windbreak sub-model of the Wind Erosion Prediction System (WEPS). Windbreak shelter is modeled in terms of friction velocity reduction, which
Enhancing Multi-Agent Based Simulation with Human-Agents Interactive Spatial Behaviour
Chen, Yee Ming; Shiu, Hung-Ming
2009-01-01
We are exploring the enhancement of models of agent behaviour with more "human-like" decision making strategies than are presently available. Our motivation is to developed with a view to as the decision analysis and support for electric taxi company under the mission of energy saving and reduction of CO2, in particular car-pool and car-sharing management policies. In order to achieve the object of decision analysis for user, we provide a human-agents interactive spatial behaviour to support user making decision real time. We adopt passenger average waiting time and electric taxi average idle time as the performance measures and decision support fro electric taxi company. Finally, according to the analysis result, we demonstrate that our multi-agent simulation and GUI can help users or companies quickly make a quality and accurate decision to reduce the decision-making cost and time.
Interaction dynamics of multiple autonomous mobile robots in bounded spatial domains
Wang, P. K. C.
1989-01-01
A general navigation strategy for multiple autonomous robots in a bounded domain is developed analytically. Each robot is modeled as a spherical particle (i.e., an effective spatial domain about the center of mass); its interactions with other robots or with obstacles and domain boundaries are described in terms of the classical many-body problem; and a collision-avoidance strategy is derived and combined with homing, robot-robot, and robot-obstacle collision-avoidance strategies. Results from homing simulations involving (1) a single robot in a circular domain, (2) two robots in a circular domain, and (3) one robot in a domain with an obstacle are presented in graphs and briefly characterized.
Evolutionary establishment of moral and double moral standards through spatial interactions
Helbing, Dirk; Perc, Matjaz; Szabo, Gyorgy
2010-01-01
Situations where individuals have to contribute to joint efforts or share scarce resources are ubiquitous. Yet, without proper mechanisms to ensure cooperation, the evolutionary pressure to maximize individual success tends to create a tragedy of the commons (such as over-fishing or the destruction of our environment). This contribution addresses a number of related puzzles of human behavior with an evolutionary game theoretical approach as it has been successfully used to explain the behavior of other biological species many times, from bacteria to vertebrates. Our agent-based model distinguishes individuals applying four different behavioral strategies: non-cooperative individuals ("defectors"), cooperative individuals abstaining from punishment efforts (called "cooperators" or "second-order free-riders"), cooperators who punish non-cooperative behavior ("moralists"), and defectors, who punish other defectors despite being non-cooperative themselves ("immoralists"). By considering spatial interactions with ...
How does spatial study design influence density estimates from spatial capture-recapture models?
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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.
Behavioural and neural interaction between spatial inhibition of return and the Simon effect
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Pengfei eWang
2013-09-01
Full Text Available It has been well documented that the anatomically independent attention networks in the human brain interact functionally to achieve goal-directed behaviours. By combining spatial inhibition of return (IOR which implicates the orienting network with some executive function tasks (e.g., the Stroop and the flanker effects which implicate the executive network, researchers consistently found that the interference effects are significantly reduced at cued compared to uncued locations, indicating the functional interaction between the two attention networks. However, a unique, but consistent, effect is observed when spatial IOR is combined with the Simon effect: the Simon effect is significantly higher at the cued than uncued locations. To investigate the neural substrates underlying this phenomenon, we orthogonally combined the spatial IOR with the Simon effect in the present event-related fMRI study. Our behavioural data replicated previous results by showing larger Simon effect at the cued location. At the neural level, we found shared spatial representation system between spatial IOR and the Simon effect in bilateral posterior parietal cortex; spatial IOR specifically activated bilateral superior parietal cortex while the Simon effect specifically activated bilateral middle frontal cortex. Moreover, left precentral gyrus was involved in the neural interaction between spatial IOR and the Simon effect by showing significantly higher neural activity in the ‘Cued_Congruent’ condition. Taken together, our results suggest that due to the shared spatial representation system in the posterior parietal cortex, responses were significantly facilitated when spatial IOR and the Simon effect relied on the same spatial representations, i.e., in the ‘Cued_Congruent’ condition. Correspondingly, the sensorimotor system was significantly involved in the ‘Cued_Congruent’ condition to fasten the responses, which indirectly resulted in the enhanced Simon
Validating a spatially distributed hydrological model with soil morphology data
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T. Doppler
2013-10-01
Full Text Available Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas
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Iswar Das
2016-01-01
Full Text Available Landslides are common but complex natural hazards. They occur on the Earth’s surface following a mass movement process. This study applies the multitype Strauss point process model to analyze the spatial distributions of small and large landslides along with geoenvironmental covariates. It addresses landslides as a set of irregularly distributed point-type locations within a spatial region. Their intensity and spatial interactions are analyzed by means of the distance correlation functions, model fitting, and simulation. We use as a dataset the landslide occurrences for 28 years from a landslide prone road corridor in the Indian Himalayas. The landslides are investigated for their spatial character, that is, whether they show inhibition or occur as a regular or a clustered point pattern, and for their interaction with landslides in the neighbourhood. Results show that the covariates lithology, land cover, road buffer, drainage density, and terrain units significantly improved model fitting. A comparison of the output made with logistic regression model output showed a superior prediction performance for the multitype Strauss model. We compared results of this model with the multitype/hard core Strauss point process model that further improved the modeling. Results from the study can be used to generate landslide susceptibility scenarios. The paper concludes that a multitype Strauss point process model enriches the set of statistical tools that can comprehensively analyze landslide data.
Spatial emission modelling for residential wood combustion in Denmark
Plejdrup, Marlene S.; Nielsen, Ole-Kenneth; Brandt, Jørgen
2016-11-01
Residential wood combustion (RWC) is a major contributor to atmospheric pollution especially for particulate matter. Air pollution has significant impact on human health, and it is therefore important to know the human exposure. For this purpose, it is necessary with a detailed high resolution spatial distribution of emissions. In previous studies as well as in the model previously used in Denmark, the spatial resolution is limited, e.g. municipality or county level. Further, in many cases models are mainly relying on population density data as the spatial proxy for distributing the emissions. This paper describes the new Danish model for high resolution spatial distribution of emissions from RWC to air. The new spatial emission model is based on information regarding building type, and primary and supplementary heating installations from the Danish Building and Dwelling Register (BBR), which holds detailed data for all buildings in Denmark. The new model provides a much more accurate distribution of emissions than the previous model used in Denmark, as the resolution has been increased from municipality level to a 1 km × 1 km resolution, and the distribution key has been significantly improved so that it no longer puts an excessive weight on population density. The new model has been verified for the city of Copenhagen, where emissions estimated using both the previous and the new model have been compared to the emissions estimated in a case study. This comparison shows that the new model with the developed weighting factors (76 ton PM2.5) is in good agreement with the case study (95 ton PM2.5), and that the new model has improved the spatial emission distribution significantly compared to the previous model (284 ton PM2.5). Additionally, a sensitivity analysis was done to illustrate the impact of the weighting factors on the result, showing that the new model independently of the weighting factors chosen produce a more accurate result than the old model.
Spatial Error Metrics for Oceanographic Model Verification
2012-02-01
quantitatively and qualitatively for this oceano - graphic data and successfully separates the model error into displacement and intensity components. This... oceano - graphic models as well, though one would likely need to make special modifications to handle the often-used nonuniform spacing between depth layers
Learning Anatomy: Do New Computer Models Improve Spatial Understanding?
Garg, Amit; Norman, Geoff; Spero, Lawrence; Taylor, Ian
1999-01-01
Assesses desktop-computer models that rotate in virtual three-dimensional space. Compares spatial learning with a computer carpal-bone model horizontally rotating at 10-degree views with the same model rotating at 90-degree views. (Author/CCM)
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 poss
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 poss
Spatially dependent polya tree modeling for survival data.
Zhao, Luping; Hanson, Timothy E
2011-06-01
With the proliferation of spatially oriented time-to-event data, spatial modeling in the survival context has received increased recent attention. A traditional way to capture a spatial pattern is to introduce frailty terms in the linear predictor of a semiparametric model, such as proportional hazards or accelerated failure time. We propose a new methodology to capture the spatial pattern by assuming a prior based on a mixture of spatially dependent Polya trees for the baseline survival in the proportional hazards model. Thanks to modern Markov chain Monte Carlo (MCMC) methods, this approach remains computationally feasible in a fully hierarchical Bayesian framework. We compare the spatially dependent mixture of Polya trees (MPT) approach to the traditional spatial frailty approach, and illustrate the usefulness of this method with an analysis of Iowan breast cancer survival data from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. Our method provides better goodness of fit over the traditional alternatives as measured by log pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and full sample score (FSS) statistics. © 2010, The International Biometric Society.
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.
Spatially resolved stellar, dust and gas properties of the post-interacting Whirlpool Galaxy system
Cooper, Erin Mentuch; Foyle, Kelly; Bendo, George; Koda, Jin; Baes, Marten; Boquien, Médéric; Boselli, Alessandro; Ciesla, Laure; Cooray, Asantha; Eales, Steve; Galametz, Maud; Lebouteiller, Vianney; Parkin, Tara; Roussel, Hélène; Sauvage, Marc; Spinoglio, Luigi; Smith, Matthew W L
2012-01-01
Using infrared imaging from the Herschel Space Observatory, observed as part of the VNGS, we investigate the spatially resolved dust properties of the interacting Whirlpool galaxy system (NGC 5194 and NGC 5195), on physical scales of 1 kpc. Spectral energy distribution modelling of the new infrared images in combination with archival optical, near- through mid-infrared images confirms that both galaxies underwent a burst of star formation ~370-480 Myr ago and provides spatially resolved maps of the stellar and dust mass surface densities. The resulting average dust-to-stellar mass ratios are comparable to other spiral and spheroidal galaxies studied with Herschel, with NGC 5194 at log M(dust)/M(star)= -2.5+/-0.2 and NGC 5195 at log M(dust)/M(star)= -3.5+/-0.3. The dust-to-stellar mass ratio is constant across NGC 5194 suggesting the stellar and dust components are coupled. In contrast, the mass ratio increases with radius in NGC 5195 with decreasing stellar mass density. Archival mass surface density maps of ...
Spatially Uniform ReliefF (SURF for computationally-efficient filtering of gene-gene interactions
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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
Majka, M.; Góra, P. F.
2017-02-01
The collectivity in the simultaneous diffusion of many particles, i.e. the interdependence of stochastic forces affecting different particles in the same solution, is a largely overlooked phenomenon with no well-established theory. Recently, we have proposed a novel type of thermodynamically consistent Langevin dynamics driven by spatially correlated noise (SCN) that can contribute to the understanding of this problem. This model draws a link between the theory of effective interactions in binary colloidal mixtures and the properties of SCN. In the current article, we review this model from the perspective of collective diffusion and generalize it to the case of multiple (N > 2) particles. Since our theory of SCN-driven Langevin dynamics has certain issues that could not be resolved within this framework, in this article we also provide another approach to the problem of collectivity. We discuss the multi-particle Mori-Zwanzig model, which is fully microscopically consistent. Indeed, we show that this model supplies a lot of information, complementary to the SCN-based approach, e.g. it predicts the deterministic dynamics of the relative distance between the particles, it provides an approximation for non-equilibrium effective interactions and predicts the collective sub-diffusion of tracers in the group. These results provide the short-range, inertial limit of the earlier model and agree with its predictions under some general conditions. In this article we also review the origin of SCN and its consequences for a variety of physical systems, with emphasis on the colloids.
Hanks, Ephraim M.; Schliep, Erin M.; Hooten, Mevin B.; Hoeting, Jennifer A.
2015-01-01
In spatial generalized linear mixed models (SGLMMs), covariates that are spatially smooth are often collinear with spatially smooth random effects. This phenomenon is known as spatial confounding and has been studied primarily in the case where the spatial support of the process being studied is discrete (e.g., areal spatial data). In this case, the most common approach suggested is restricted spatial regression (RSR) in which the spatial random effects are constrained to be orthogonal to the fixed effects. We consider spatial confounding and RSR in the geostatistical (continuous spatial support) setting. We show that RSR provides computational benefits relative to the confounded SGLMM, but that Bayesian credible intervals under RSR can be inappropriately narrow under model misspecification. We propose a posterior predictive approach to alleviating this potential problem and discuss the appropriateness of RSR in a variety of situations. We illustrate RSR and SGLMM approaches through simulation studies and an analysis of malaria frequencies in The Gambia, Africa.
Interactive Modelling of Molecular Structures
Rustad, J. R.; Kreylos, O.; Hamann, B.
2004-12-01
The "Nanotech Construction Kit" (NCK) [1] is a new project aimed at improving the understanding of molecular structures at a nanometer-scale level by visualization and interactive manipulation. Our very first prototype is a virtual-reality program allowing the construction of silica and carbon structures from scratch by assembling them one atom at a time. In silica crystals or glasses, the basic building block is an SiO4 unit, with the four oxygen atoms arranged around the central silicon atom in the shape of a regular tetrahedron. Two silicate units can connect to each other by their silicon atoms covalently bonding to one shared oxygen atom. Geometrically, this means that two tetrahedra can link at their vertices. Our program is based on geometric representations and uses simple force fields to simulate the interaction of building blocks, such as forming/breaking of bonds and repulsion. Together with stereoscopic visualization and direct manipulation of building blocks using wands or data gloves, this enables users to create realistic and complex molecular models in short amounts of time. The NCK can either be used as a standalone tool, to analyze or experiment with molecular structures, or it can be used in combination with "traditional" molecular dynamics (MD) simulations. In a first step, the NCK can create initial configurations for subsequent MD simulation. In a more evolved setup, the NCK can serve as a visual front-end for an ongoing MD simulation, visualizing changes in simulation state in real time. Additionally, the NCK can be used to change simulation state on-the-fly, to experiment with different simulation conditions, or force certain events, e.g., the forming of a bond, and observe the simulation's reaction. [1] http://graphics.cs.ucdavis.edu/~okreylos/ResDev/NanoTech
Exactly solved models of interacting dark matter and dark energy
Chimento, Luis P
2012-01-01
We introduce an effective one-fluid description of the interacting dark sector in a spatially flat Friedmann-Robertson-Walker space-time and investigate the stability of the power-law solutions. We find the "source equation" for the total energy density and determine the energy density of each dark component. We study linear and nonlinear interactions which depend on the dark matter and dark energy densities, their first derivatives, the total energy density with its derivatives up to second order and the scale factor. We solve the evolution equations of the dark components for both interactions, examine exhaustively several examples and show cases where the problem of the coincidence is alleviated. We show that a generic nonlinear interaction gives rise to the "relaxed Chaplygin gas model" whose effective equation of state includes the variable modified Chaplygin gas model while some others nonlinear interactions yield de Sitter and power-law scenarios.
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 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.
Directory of Open Access Journals (Sweden)
Katherine Elizabeth Vytal
2013-03-01
Full Text Available Anxiety can be distracting, disruptive, and incapacitating. Despite problems with empirical replication of this phenomenon, one fruitful avenue of study has emerged from working memory (WM experiments where a translational method of anxiety induction (risk of shock has been shown to disrupt spatial and verbal WM performance. Performance declines when resources (e.g., spatial attention, executive function devoted to goal-directed behaviors are consumed by anxiety. Importantly, it has been shown that anxiety-related impairments in verbal WM depend on task difficulty, suggesting that cognitive load may be an important consideration in the interaction between anxiety and cognition. Here we use both spatial and verbal WM paradigms to probe the effect of cognitive load on anxiety-induced WM impairment across task modality. Subjects performed a series of spatial and verbal n-back tasks of increasing difficulty (1, 2, and 3-back while they were safe or at risk for shock. Startle reflex was used to probe anxiety. Results demonstrate that induced-anxiety differentially impacts verbal and spatial WM, such that low and medium-load verbal WM is more susceptible to anxiety-related disruption relative to high-load, and spatial WM is disrupted regardless of task difficulty. Anxiety impacts both verbal and spatial processes, as described by correlations between anxiety and performance impairment, albeit the effect on spatial WM is consistent across load. Demanding WM tasks may exert top-down control over higher-order cortical resources engaged by anxious apprehension, however high-load spatial WM may continue to experience additional competition from anxiety-related changes in spatial attention, resulting in impaired performance. By describing this disruption across task modalities, these findings inform current theories of emotion-cognition interactions and may facilitate development of clinical interventions that seek to target cognitive impairments associated
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
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.
Irving, D. H.; Rasheed, M.; O'Doherty, N.
2010-12-01
The efficient storage, retrieval and interactive use of subsurface data present great challenges in geodata management. Data volumes are typically massive, complex and poorly indexed with inadequate metadata. Derived geomodels and interpretations are often tightly bound in application-centric and proprietary formats; open standards for long-term stewardship are poorly developed. Consequently current data storage is a combination of: complex Logical Data Models (LDMs) based on file storage formats; 2D GIS tree-based indexing of spatial data; and translations of serialised memory-based storage techniques into disk-based storage. Whilst adequate for working at the mesoscale over a short timeframes, these approaches all possess technical and operational shortcomings: data model complexity; anisotropy of access; scalability to large and complex datasets; and weak implementation and integration of metadata. High performance hardware such as parallelised storage and Relational Database Management System (RDBMS) have long been exploited in many solutions but the underlying data structure must provide commensurate efficiencies to allow multi-user, multi-application and near-realtime data interaction. We present an open Spatially-Registered Data Structure (SRDS) built on Massively Parallel Processing (MPP) database architecture implemented by a ANSI SQL 2008 compliant RDBMS. We propose a LDM comprising a 3D Earth model that is decomposed such that each increasing Level of Detail (LoD) is achieved by recursively halving the bin size until it is less than the error in each spatial dimension for that data point. The value of an attribute at that point is stored as a property of that point and at that LoD. It is key to the numerical efficiency of the SRDS that it is under-pinned by a power-of-two relationship thus precluding the need for computationally intensive floating point arithmetic. Our approach employed a tightly clustered MPP array with small clusters of storage
Upscaling of Mixing Processes using a Spatial Markov Model
Bolster, Diogo; Sund, Nicole; Porta, Giovanni
2016-11-01
The Spatial Markov model is a model that has been used to successfully upscale transport behavior across a broad range of spatially heterogeneous flows, with most examples to date coming from applications relating to porous media. In its most common current forms the model predicts spatially averaged concentrations. However, many processes, including for example chemical reactions, require an adequate understanding of mixing below the averaging scale, which means that knowledge of subscale fluctuations, or closures that adequately describe them, are needed. Here we present a framework, consistent with the Spatial Markov modeling framework, that enables us to do this. We apply and present it as applied to a simple example, a spatially periodic flow at low Reynolds number. We demonstrate that our upscaled model can successfully predict mixing by comparing results from direct numerical simulations to predictions with our upscaled model. To this end we focus on predicting two common metrics of mixing: the dilution index and the scalar dissipation. For both metrics our upscaled predictions very closely match observed values from the DNS. This material is based upon work supported by NSF Grants EAR-1351625 and EAR-1417264.
Spatially correlated disturbances in a locally dispersing population model.
Hiebeler, David
2005-01-01
The basic contact process in continuous time is studied, where instead of single occupied sites becoming empty independently, larger-scale disturbance events simultaneously remove the population from contiguous blocks of sites. Stochastic spatial simulations and pair approximations were used to investigate the model. Increasing the spatial scale of disturbance events increases spatial clustering of the population and variability in growth rates within localized regions, reduces the effective overall population density, and increases the critical reproductive rate necessary for the population to persist. Pair approximations yield a closed-form analytic expression for equilibrium population density and the critical value necessary for persistence.
Spatial Modeling Tools for Cell Biology
2006-10-01
34 iv Figure 5.1: Computational results for a diffusion problem on planar square thin film............ 36 Figure 5.2... Wisc . Open Microscopy Env. Pre-CoBi Model Lib. CFDRC CoBi Tools CFDRC CoBi Tools Simulation Environment JigCell Tools Figure 4.1: Cell biology
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...
Properties of spatial Cox process models
DEFF Research Database (Denmark)
Møller, Jesper
Probabilistic properties of Cox processes of relevance for statistical modelling and inference are studied. Particularly, we study the most important classes of Cox processes, including log Gaussian Cox processes, shot noise Cox processes, and permanent Cox processes. We consider moment propertie...
Interaction field modeling of mini-UAV swarm
Liou, William W.; Ro, Kapseong; Szu, Harold
2006-05-01
A behavior-based, simple interaction model inspired by molecular interaction field depicted by the Lennard-Jones function is examined for the averaged interaction in swarming. The modeled kinematic equation of motion contains only one variable, instead of a multiple state variable dependence a more complete dynamics entails. The model assumes a spatial distribution of the potential associate with the swarm. The model has been applied to examine the formation of swarm and the results are reported. The modeling can be reflected in an equilibrium theory for the operation of a swarm of mini-UAVs pioneered by Szu, where every member serves the mission while exploiting other's loss, resulting in a zero-sum game among the team members.
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.
Spatial capture-recapture models allowing Markovian transience or dispersal
Royle, J. Andrew; Fuller, Angela K.; Sutherland, Chris
2016-01-01
Spatial capture–recapture (SCR) models are a relatively recent development in quantitative ecology, and they are becoming widely used to model density in studies of animal populations using camera traps, DNA sampling and other methods which produce spatially explicit individual encounter information. One of the core assumptions of SCR models is that individuals possess home ranges that are spatially stationary during the sampling period. For many species, this assumption is unlikely to be met and, even for species that are typically territorial, individuals may disperse or exhibit transience at some life stages. In this paper we first conduct a simulation study to evaluate the robustness of estimators of density under ordinary SCR models when dispersal or transience is present in the population. Then, using both simulated and real data, we demonstrate that such models can easily be described in the BUGS language providing a practical framework for their analysis, which allows us to evaluate movement dynamics of species using capture–recapture data. We find that while estimators of density are extremely robust, even to pathological levels of movement (e.g., complete transience), the estimator of the spatial scale parameter of the encounter probability model is confounded with the dispersal/transience scale parameter. Thus, use of ordinary SCR models to make inferences about density is feasible, but interpretation of SCR model parameters in relation to movement should be avoided. Instead, when movement dynamics are of interest, such dynamics should be parameterized explicitly in the model.
Spatial Bayesian hierarchical modelling of extreme sea states
Clancy, Colm; O'Sullivan, John; Sweeney, Conor; Dias, Frédéric; Parnell, Andrew C.
2016-11-01
A Bayesian hierarchical framework is used to model extreme sea states, incorporating a latent spatial process to more effectively capture the spatial variation of the extremes. The model is applied to a 34-year hindcast of significant wave height off the west coast of Ireland. The generalised Pareto distribution is fitted to declustered peaks over a threshold given by the 99.8th percentile of the data. Return levels of significant wave height are computed and compared against those from a model based on the commonly-used maximum likelihood inference method. The Bayesian spatial model produces smoother maps of return levels. Furthermore, this approach greatly reduces the uncertainty in the estimates, thus providing information on extremes which is more useful for practical applications.
GIS application on spatial landslide analysis using statistical based models
Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred F.
2009-09-01
This paper presents the assessment results of spatially based probabilistic three models using Geoinformation Techniques (GIT) for landslide susceptibility analysis at Penang Island in Malaysia. Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and supported with field surveys. Maps of the topography, soil type, lineaments and land cover were constructed from the spatial data sets. There are ten landslide related factors were extracted from the spatial database and the frequency ratio, fuzzy logic, and bivariate logistic regression coefficients of each factor was computed. Finally, landslide susceptibility maps were drawn for study area using frequency ratios, fuzzy logic and bivariate logistic regression models. For verification, the results of the analyses were compared with actual landslide locations in study area. The verification results show that bivariate logistic regression model provides slightly higher prediction accuracy than the frequency ratio and fuzzy logic models.
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.
Was Thebes Necessary? Contingency in Spatial Modelling
Evans, Tim S
2016-01-01
When data is poor we resort to theory modelling. This is a two-step process. We have first to identify the appropriate type of model for the system under consideration and then to tailor it to the specifics of the case. To understand settlement formation, which is the concern of this paper, this not only involves choosing input parameter values such as site separations but also input functions which characterises the ease of travel between sites. Although the generic behaviour of the model is understood, the details are not. Different choices will necessarily lead to different outputs (for identical inputs). We can only proceed if choices that are "close" give outcomes are similar. Where there are local differences it suggests that there was no compelling reason for one outcome rather than the other. If these differences are important for the historic record we may interpret this as sensitivity to contingency. We re-examine the rise of Greek city states as first formulated by Rihll and Wilson in 1979, initial...
Comparing spatial and temporal transferability of hydrological model parameters
Patil, Sopan D.; Stieglitz, Marc
2015-06-01
Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal aspects of catchment hydrological variability.
Spatial mixture multiscale modeling for aggregated health data.
Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin
2016-09-01
One of the main goals in spatial epidemiology is to study the geographical pattern of disease risks. For such purpose, the convolution model composed of correlated and uncorrelated components is often used. However, one of the two components could be predominant in some regions. To investigate the predominance of the correlated or uncorrelated component for multiple scale data, we propose four different spatial mixture multiscale models by mixing spatially varying probability weights of correlated (CH) and uncorrelated heterogeneities (UH). The first model assumes that there is no linkage between the different scales and, hence, we consider independent mixture convolution models at each scale. The second model introduces linkage between finer and coarser scales via a shared uncorrelated component of the mixture convolution model. The third model is similar to the second model but the linkage between the scales is introduced through the correlated component. Finally, the fourth model accommodates for a scale effect by sharing both CH and UH simultaneously. We applied these models to real and simulated data, and found that the fourth model is the best model followed by the second model.
Modelling the spatial distribution of ammonia emissions in the UK
Energy Technology Data Exchange (ETDEWEB)
Hellsten, S. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom); Institute of Geography, School of Geosciences, University of Edinburgh, Drummond Street, Edinburgh EH8 9XP (United Kingdom); IVL Swedish Environmental Research Institute Ltd, P.O. Box 5302, SE-400 14 Gothenburg (Sweden)], E-mail: sofie.hellsten@ivl.se; Dragosits, U. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom); Place, C.J. [Institute of Geography, School of Geosciences, University of Edinburgh, Drummond Street, Edinburgh EH8 9XP (United Kingdom); Vieno, M. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom); Institute of Atmospheric and Environmental Science, School of GeoSciences, University of Edinburgh, Crew Building, The King' s buildings, West Mains Road, Edinburgh EH9 3JN (United Kingdom); Dore, A.J. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom); Misselbrook, T.H. [Institute of Grassland and Environmental Research, North Wyke, Okehampton, Exeter EX 2SB (United Kingdom); Tang, Y.S.; Sutton, M.A. [Centre for Ecology and Hydrology Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB (United Kingdom)
2008-08-15
Ammonia emissions (NH{sub 3}) are characterised by a high spatial variability at a local scale. When modelling the spatial distribution of NH{sub 3} emissions, it is important to provide robust emission estimates, since the model output is used to assess potential environmental impacts, e.g. exceedance of critical loads. The aim of this study was to provide a new, updated spatial NH{sub 3} emission inventory for the UK for the year 2000, based on an improved modelling approach and the use of updated input datasets. The AENEID model distributes NH{sub 3} emissions from a range of agricultural activities, such as grazing and housing of livestock, storage and spreading of manures, and fertilizer application, at a 1-km grid resolution over the most suitable landcover types. The results of the emission calculation for the year 2000 are analysed and the methodology is compared with a previous spatial emission inventory for 1996. - It is important to provide robust estimates of the spatial distribution of ammonia emissions, since the model output is used to assess potential environmental impacts, e.g. through the exceedance of critical loads.
Fundamental x-ray interaction limits in diagnostic imaging detectors: spatial resolution.
Hajdok, G; Battista, J J; Cunningham, I A
2008-07-01
The practice of diagnostic x-ray imaging has been transformed with the emergence of digital detector technology. Although digital systems offer many practical advantages over conventional film-based systems, their spatial resolution performance can be a limitation. The authors present a Monte Carlo study to determine fundamental resolution limits caused by x-ray interactions in four converter materials: Amorphous silicon (a-Si), amorphous selenium, cesium iodide, and lead iodide. The "x-ray interaction" modulation transfer function (MTF) was determined for each material and compared in terms of the 50% MTF spatial frequency and Wagner's effective aperture for incident photon energies between 10 and 150 keV and various converter thicknesses. Several conclusions can be drawn from their Monte Carlo study. (i) In low-Z (a-Si) converters, reabsorption of Compton scatter x rays limits spatial resolution with a sharp MTF drop at very low spatial frequencies (x rays plays a dominant role, resulting in a mid-frequency (1-5 cycles/mm) MTF drop. (ii) Coherent scatter plays a minor role in the x-ray interaction MTF. (iii) The spread of energy due to secondary electron (e.g., photoelectrons) transport is significant only at very high spatial frequencies. (iv) Unlike the spread of optical light in phosphors, the spread of absorbed energy from x-ray interactions does not significantly degrade spatial resolution as converter thickness is increased. (v) The effective aperture results reported here represent fundamental spatial resolution limits of the materials tested and serve as target benchmarks for the design and development of future digital x-ray detectors.
Spatial flood extent modelling. A performance based comparison
Werner, M.G.F.
2004-01-01
The rapid development of Geographical Information Systems (GIS) has together with the inherent spatial nature of hydrological modelling led to an equally rapid development in the integration between GIS and hydrological models. The advantages of integration are particularly apparent in flood extent
How to Represent 100-meter Spatial Heterogeneity in Earth System Models
Chaney, Nathaniel; Shevliakova, Elena; Malyshev, Sergey
2016-04-01
Terrestrial ecosystems play a pivotal 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 (~100 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 hyperresolution 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 or hydrologic response units (HRUs). The novel Geophysical Fluid Dynamics Laboratory (GFDL) LM3-TiHy-PPA land model is then used to simulate these HRUs 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.
Distributed multi-criteria model evaluation and spatial association analysis
Scherer, Laura; Pfister, Stephan
2015-04-01
Model performance, if evaluated, is often communicated by a single indicator and at an aggregated level; however, it does not embrace the trade-offs between different indicators and the inherent spatial heterogeneity of model efficiency. In this study, we simulated the water balance of the Mississippi watershed using the Soil and Water Assessment Tool (SWAT). The model was calibrated against monthly river discharge at 131 measurement stations. Its time series were bisected to allow for subsequent validation at the same gauges. Furthermore, the model was validated against evapotranspiration which was available as a continuous raster based on remote sensing. The model performance was evaluated for each of the 451 sub-watersheds using four different criteria: 1) Nash-Sutcliffe efficiency (NSE), 2) percent bias (PBIAS), 3) root mean square error (RMSE) normalized to standard deviation (RSR), as well as 4) a combined indicator of the squared correlation coefficient and the linear regression slope (bR2). Conditions that might lead to a poor model performance include aridity, a very flat and steep relief, snowfall and dams, as indicated by previous research. In an attempt to explain spatial differences in model efficiency, the goodness of the model was spatially compared to these four phenomena by means of a bivariate spatial association measure which combines Pearson's correlation coefficient and Moran's index for spatial autocorrelation. In order to assess the model performance of the Mississippi watershed as a whole, three different averages of the sub-watershed results were computed by 1) applying equal weights, 2) weighting by the mean observed river discharge, 3) weighting by the upstream catchment area and the square root of the time series length. Ratings of model performance differed significantly in space and according to efficiency criterion. The model performed much better in the humid Eastern region than in the arid Western region which was confirmed by the
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.
A spatial model of mosquito host-seeking behavior.
Cummins, Bree; Cortez, Ricardo; Foppa, Ivo M; Walbeck, Justin; Hyman, James M
2012-01-01
Mosquito host-seeking behavior and heterogeneity in host distribution are important factors in predicting the transmission dynamics of mosquito-borne infections such as dengue fever, malaria, chikungunya, and West Nile virus. We develop and analyze a new mathematical model to describe the effect of spatial heterogeneity on the contact rate between mosquito vectors and hosts. The model includes odor plumes generated by spatially distributed hosts, wind velocity, and mosquito behavior based on both the prevailing wind and the odor plume. On a spatial scale of meters and a time scale of minutes, we compare the effectiveness of different plume-finding and plume-tracking strategies that mosquitoes could use to locate a host. The results show that two different models of chemotaxis are capable of producing comparable results given appropriate parameter choices and that host finding is optimized by a strategy of flying across the wind until the odor plume is intercepted. We also assess the impact of changing the level of host aggregation on mosquito host-finding success near the end of the host-seeking flight. When clusters of hosts are more tightly associated on smaller patches, the odor plume is narrower and the biting rate per host is decreased. For two host groups of unequal number but equal spatial density, the biting rate per host is lower in the group with more individuals, indicative of an attack abatement effect of host aggregation. We discuss how this approach could assist parameter choices in compartmental models that do not explicitly model the spatial arrangement of individuals and how the model could address larger spatial scales and other probability models for mosquito behavior, such as Lévy distributions.
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.
Phenomenological analysis of the interacting boson model
Hatch, R. L.; Levit, S.
1982-01-01
The classical Hamiltonian of the interacting boson model is defined and expressed in terms of the conventional quadrupole variables. This is used in the analyses of the dynamics in the various limits of the model. The purpose is to determine the range and the features of the collective phenomena which the interacting boson model is capable of describing. In the commonly used version of the interacting boson model with one type of the s and d bosons and quartic interactions, this capability has certain limitations and the model should be used with care. A more sophisticated version of the interacting boson model with neutron and proton bosons is not discussed. NUCLEAR STRUCTURE Interacting bosons, classical IBM Hamiltonian in quadrupole variables, phenomenological content of the IBM and its limitations.
Koschinsky, Julia; Lozano-Gracia, Nancy; Piras, Gianfranco
2012-07-01
This article compares results from non-spatial and new spatial methods to examine the reliability of welfare estimates (direct and multiplier effects) for locational housing attributes in Seattle, WA. In particular, we assess if OLS with spatial fixed effects is able to account for the spatial structure in a way that represents a viable alternative to spatial econometric methods. We find that while OLS with spatial fixed effects accounts for more of the spatial structure than simple OLS, it does not account for all of the spatial structure. It thus does not present a viable alternative to the spatial methods. Similar to existing comparisons between results from non-spatial and established spatial methods, we also find that OLS generates higher coefficient and direct effect estimates for both structural and locational housing characteristics than spatial methods do. OLS with spatial fixed effects is closer to the spatial estimates than OLS without fixed effects but remains higher. Finally, a comparison of the direct effects with locally weighted regression results highlights spatial threshold effects that are missed in the global models. Differences between spatial estimators are almost negligible in this study.
Spatially random models, estimation theory, and robot arm dynamics
Rodriguez, G.
1987-01-01
Spatially random models provide an alternative to the more traditional deterministic models used to describe robot arm dynamics. These alternative models can be used to establish a relationship between the methodologies of estimation theory and robot dynamics. A new class of algorithms for many of the fundamental robotics problems of inverse and forward dynamics, inverse kinematics, etc. can be developed that use computations typical in estimation theory. The algorithms make extensive use of the difference equations of Kalman filtering and Bryson-Frazier smoothing to conduct spatial recursions. The spatially random models are very easy to describe and are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. The models can also be used to generate numerically the composite multibody system inertia matrix. This is done without resorting to the more common methods of deterministic modeling involving Lagrangian dynamics, Newton-Euler equations, etc. These methods make substantial use of human knowledge in derivation and minipulation of equations of motion for complex mechanical systems.
Identification of protein-RNA interaction sites using the information of spatial adjacent residues
Directory of Open Access Journals (Sweden)
Cheng Yong-Mei
2011-10-01
Full Text Available Abstract Background Protein-RNA interactions play an important role in numbers of fundamental cellular processes such as RNA splicing, transport and translation, protein synthesis and certain RNA-mediated enzymatic processes. The more knowledge of Protein-RNA recognition can not only help to understand the regulatory mechanism, the site-directed mutagenesis and regulation of RNA–protein complexes in biological systems, but also have a vitally effecting for rational drug design. Results Based on the information of spatial adjacent residues, novel feature extraction methods were proposed to predict protein-RNA interaction sites with SVM-KNN classifier. The total accuracies of spatial adjacent residue profile feature and spatial adjacent residues weighted accessibility solvent area feature are 78%, 67.07% respectively in 5-fold cross-validation test, which are 1.4%, 3.79% higher than that of sequence neighbour residue profile feature and sequence neighbour residue accessibility solvent area feature. Conclusions The results indicate that the performance of feature extraction method using the spatial adjacent information is superior to the sequence neighbour information approach. The performance of SVM-KNN classifier is little better than that of SVM. The feature extraction method of spatial adjacent information with SVM-KNN is very effective for identifying protein-RNA interaction sites and may at least play a complimentary role to the existing methods.
Modelling the emergence of spatial patterns of economic activity
Yang, Jung-Hun; Frenken, Koen
2012-01-01
Understanding how spatial configurations of economic activity emerge is important when formulating spatial planning and economic policy. A simple model was proposed by Simon, who assumed that firms grow at a rate proportional to their size, and that new divisions of firms with certain probabilities relocate to other firms or to new centres of economic activity. Simon's model produces realistic results in the sense that the sizes of economic centres follow a Zipf distribution, which is also observed in reality. It lacks realism in the sense that mechanisms such as cluster formation, congestion (defined as an overly high density of the same activities) and dependence on the spatial distribution of external parties (clients, labour markets) are ignored. The present paper proposed an extension of the Simon model that includes both centripetal and centrifugal forces. Centripetal forces are included in the sense that firm divisions are more likely to settle in locations that offer a higher accessibility to other fi...
Spatial distribution of emissions to air – the SPREAD model
DEFF Research Database (Denmark)
Plejdrup, Marlene Schmidt; Gyldenkærne, Steen
The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark’s obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long......-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according...... to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously...
Spatial correlations in bed load transport: evidence, importance, and modelling
Heyman, J; Mettra, F; Ancey, C
2016-01-01
This article examines the spatial {dynamics of bed load particles} in water. We focus particularly on the fluctuations of particle activity, which is defined as the number of moving particles per unit bed {length}. Based on a stochastic model recently proposed by \\citet{Ancey2013}, we derive the second moment of particle activity analytically; that is the spatial correlation functions of particle activity. From these expressions, we show that large moving particle clusters can develop spatially. Also, we provide evidence that fluctuations of particle activity are scale-dependent. Two characteristic lengths emerge from the model: a saturation length $\\ell_{sat}$ describing the length needed for a perturbation in particle activity to relax to the homogeneous solution, and a correlation length $\\ell_c$ describing the typical size of moving particle clusters. A dimensionless P\\'eclet number can also be defined according to the transport model. Three different experimental data sets are used to test the theoretica...
Random spatial processes and geostatistical models for soil variables
Lark, R. M.
2009-04-01
Geostatistical models of soil variation have been used to considerable effect to facilitate efficient and powerful prediction of soil properties at unsampled sites or over partially sampled regions. Geostatistical models can also be used to investigate the scaling behaviour of soil process models, to design sampling strategies and to account for spatial dependence in the random effects of linear mixed models for spatial variables. However, most geostatistical models (variograms) are selected for reasons of mathematical convenience (in particular, to ensure positive definiteness of the corresponding variables). They assume some underlying spatial mathematical operator which may give a good description of observed variation of the soil, but which may not relate in any clear way to the processes that we know give rise to that observed variation in the real world. In this paper I shall argue that soil scientists should pay closer attention to the underlying operators in geostatistical models, with a view to identifying, where ever possible, operators that reflect our knowledge of processes in the soil. I shall illustrate how this can be done in the case of two problems. The first exemplar problem is the definition of operators to represent statistically processes in which the soil landscape is divided into discrete domains. This may occur at disparate scales from the landscape (outcrops, catchments, fields with different landuse) to the soil core (aggregates, rhizospheres). The operators that underly standard geostatistical models of soil variation typically describe continuous variation, and so do not offer any way to incorporate information on processes which occur in discrete domains. I shall present the Poisson Voronoi Tessellation as an alternative spatial operator, examine its corresponding variogram, and apply these to some real data. The second exemplar problem arises from different operators that are equifinal with respect to the variograms of the
Image categorization based on spatial visual vocabulary model
Wang, Yuxin; He, Changqin; Guo, He; Feng, Zhen; Jia, Qi
2010-08-01
In this paper, we propose an approach to recognize scene categories by means of a novel method named spatial visual vocabulary. Firstly, we hierarchically divide images into sub regions and construct the spatial visual vocabulary by grouping the low-level features collected from every corresponding spatial sub region into a specified number of clusters using k-means algorithm. To recognize the category of a scene, the visual vocabulary distributions of all spatial sub regions are concatenated to form a global feature vector. The classification is obtained using LIBSVM, a support vector machine classifier. Our goal is to find a universal framework which is applicable to various types of features, so two kinds of features are used in the experiments: "V1-like" filters and PACT features. In almost all experimental cases, the proposed model achieves superior results. Source codes are available by email.
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.
The Effects of Spatial Density on the Social Interaction of Preschool Children with Disabilities
Driscoll, Coralie; Carter, Mark
2010-01-01
There has been limited research on the effects of spatial density on the social interaction of preschool children, particularly those with disabilities. Further, findings of existing studies need to be viewed cautiously due to a number of methodological difficulties including contrived small groupings of children and atypical intervention…
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 e
Area-to-point Kriging in spatial hedonic pricing models
Yoo, E.-H.; Kyriakidis, P. C.
2009-12-01
This paper proposes a geostatistical hedonic price model in which the effects of location on house values are explicitly modeled. The proposed geostatistical approach, namely area-to-point Kriging with External Drift (A2PKED), can take into account spatial dependence and spatial heteroskedasticity, if they exist. Furthermore, this approach has significant implications in situations where exhaustive area-averaged housing price data are available in addition to a subset of individual housing price data. In the case study, we demonstrate that A2PKED substantially improves the quality of predictions using apartment sale transaction records that occurred in Seoul, South Korea, during 2003. The improvement is illustrated via a comparative analysis, where predicted values obtained from different models, including two traditional regression-based hedonic models and a point-support geostatistical model, are compared to those obtained from the A2PKED model.
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.
Modeling of Spatially Correlated Energetic Disorder in Organic Semiconductors.
Kordt, Pascal; Andrienko, Denis
2016-01-12
Mesoscale modeling of organic semiconductors relies on solving an appropriately parametrized master equation. Essential ingredients of the parametrization are site energies (driving forces), which enter the charge transfer rate between pairs of neighboring molecules. Site energies are often Gaussian-distributed and are spatially correlated. Here, we propose an algorithm that generates these energies with a given Gaussian distribution and spatial correlation function. The method is tested on an amorphous organic semiconductor, DPBIC, illustrating that the accurate description of correlations is essential for the quantitative modeling of charge transport in amorphous mesophases.
Spatial modes in one-dimensional models for capillary jets
Guerrero, J.; González, H.; García, F. J.
2016-03-01
One-dimensional (1D) models are widely employed to simplify the analysis of axisymmetric capillary jets. These models postulate that, for slender deformations of the free surface, the radial profile of the axial velocity can be approximated as uniform (viscous slice, averaged, and Cosserat models) or parabolic (parabolic model). In classical works on spatial stability analysis with 1D models, considerable misinterpretation was generated about the modes yielded by each model. The already existing physical analysis of three-dimensional (3D) axisymmetric spatial modes enables us to relate these 1D spatial modes to the exact 3D counterparts. To do so, we address the surface stimulation problem, which can be treated as linear, by considering the effect of normal and tangential stresses to perturb the jet. A Green's function for a spatially local stimulation having a harmonic time dependence provides the general formalism to describe any time-periodic stimulation. The Green's function of this signaling problem is known to be a superposition of the spatial modes, but in fact these modes are of fundamental nature, i.e., not restricted to the surface stimulation problem. The smallness of the wave number associated with each mode is the criterion to validate or invalidate the 1D approaches. The proposed axial-velocity profiles (planar or parabolic) also have a remarkable influence on the outcomes of each 1D model. We also compare with the classical 3D results for (i) conditions for absolute instability, and (ii) the amplitude of the unstable mode resulting from both normal and tangential surface stress stimulation. Incidentally, as a previous task, we need to re-deduce 1D models in order to include eventual stresses of various possible origins (electrohydrodynamic, thermocapillary, etc.) applied on the free surface, which were not considered in the previous general formulations.
Spatial Reasoning Training Through Light Curves Of Model Asteroids
Ziffer, Julie; Nakroshis, Paul A.; Rudnick, Benjamin T.; Brautigam, Maxwell J.; Nelson, Tyler W.
2015-11-01
Recent research has demonstrated that spatial reasoning skills, long known to be crucial to math and science success, are teachable. Even short stints of training can improve spatial reasoning skills among students who lack them (Sorby et al., 2006). Teaching spatial reasoning is particularly valuable to women and minorities who, through societal pressure, often doubt their spatial reasoning skill (Hill et al., 2010). We have designed a hands on asteroid rotation lab that provides practice in spatial reasoning tasks while building the student’s understanding of photometry. For our tool, we mount a model asteroid, with any shape of our choosing, on a slowly rotating motor shaft, whose speed is controlled by the experimenter. To mimic an asteroid light curve, we place the model asteroid in a dark box, shine a movable light source upon our asteroid, and record the light reflected onto a moveable camera. Students may then observe changes in the light curve that result from varying a) the speed of rotation, b) the model asteroid’s orientation with respect to the motor axis, c) the model asteroid’s shape or albedo, and d) the phase angle. After practicing with our tool, students are asked to pair new objects to their corresponding light curves. To correctly pair objects to their light curves, students must imagine how light scattering off of a three dimensional rotating object is imaged on a ccd sensor plane, and then reduced to a series of points on a light curve plot. Through the use of our model asteroid, the student develops confidence in spatial reasoning skills.
A Spatial Lattice Model Applied for Meteorological Visualization and Analysis
Directory of Open Access Journals (Sweden)
Mingyue Lu
2017-03-01
Full Text Available Meteorological information has obvious spatial-temporal characteristics. Although it is meaningful to employ a geographic information system (GIS to visualize and analyze the meteorological information for better identification and forecasting of meteorological weather so as to reduce the meteorological disaster loss, modeling meteorological information based on a GIS is still difficult because meteorological elements generally have no stable shape or clear boundary. To date, there are still few GIS models that can satisfy the requirements of both meteorological visualization and analysis. In this article, a spatial lattice model based on sampling particles is proposed to support both the representation and analysis of meteorological information. In this model, a spatial sampling particle is regarded as the basic element that contains the meteorological information, and the location where the particle is placed with the time mark. The location information is generally represented using a point. As these points can be extended to a surface in two dimensions and a voxel in three dimensions, if these surfaces and voxels can occupy a certain space, then this space can be represented using these spatial sampling particles with their point locations and meteorological information. In this case, the full meteorological space can then be represented by arranging numerous particles with their point locations in a certain structure and resolution, i.e., the spatial lattice model, and extended at a higher resolution when necessary. For practical use, the meteorological space is logically classified into three types of spaces, namely the projection surface space, curved surface space, and stereoscopic space, and application-oriented spatial lattice models with different organization forms of spatial sampling particles are designed to support the representation, inquiry, and analysis of meteorological information within the three types of surfaces. Cases
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.
Spatial object model[l]ing in fuzzy topological spaces : with applications to land cover change
Tang, Xinming
2004-01-01
The central topic of this thesis focuses on the accommodation of fuzzy spatial objects in a GIS. Several issues are discussed theoretically and practically, including the definition of fuzzy spatial objects, the topological relations between them, the modeling of fuzzy spatial objects, the generatio
Fourier Analysis of an Expanded Gravity Model for Spatio-Temporal Interactions
Chen, Yanguang
2013-01-01
Fourier analysis and cross-correlation function are successfully applied to improving the conventional gravity model of interaction between cities by introducing a time variable to the attraction measures (e.g., city sizes). The traditional model assumes spatial interaction as instantaneous, while the new model considers the interaction as a temporal process and measures it as an aggregation over a period of time. By doing so, the new model not only is more theoretically sound, but also enables us to integrate the analysis of temporal process into spatial interaction modeling. Based on cross-correlation function, the developed model is calibrated by Fourier analysis techniques, and the computation process is demonstrated in four steps. The paper uses a simple case study to illustrate the approach to modeling the interurban interaction, and highlight the relationship between the new model and the conventional gravity model.
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.
Mixtures of Polya trees for flexible spatial frailty survival modelling.
Zhao, Luping; Hanson, Timothy E; Carlin, Bradley P
2009-06-01
Mixtures of Polya trees offer a very flexible nonparametric approach for modelling time-to-event data. Many such settings also feature spatial association that requires further sophistication, either at the point level or at the lattice level. In this paper, we combine these two aspects within three competing survival models, obtaining a data analytic approach that remains computationally feasible in a fully hierarchical Bayesian framework using Markov chain Monte Carlo methods. We illustrate our proposed methods with an analysis of spatially oriented breast cancer survival data from the Surveillance, Epidemiology and End Results program of the National Cancer Institute. Our results indicate appreciable advantages for our approach over competing methods that impose unrealistic parametric assumptions, ignore spatial association or both.
Noncausal spatial prediction filtering based on an ARMA model
Institute of Scientific and Technical Information of China (English)
Liu Zhipeng; Chen Xiaohong; Li Jingye
2009-01-01
Conventional f-x prediction filtering methods are based on an autoregressive model. The error section is first computed as a source noise but is removed as additive noise to obtain the signal, which results in an assumption inconsistency before and after filtering. In this paper, an autoregressive, moving-average model is employed to avoid the model inconsistency. Based on the ARMA model, a noncasual prediction filter is computed and a self-deconvolved projection filter is used for estimating additive noise in order to suppress random noise. The 1-D ARMA model is also extended to the 2-D spatial domain, which is the basis for noncasual spatial prediction filtering for random noise attenuation on 3-D seismic data. Synthetic and field data processing indicate this method can suppress random noise more effectively and preserve the signal simultaneously and does much better than other conventional prediction filtering methods.
Interaction dynamics of temporal and spatial separated cavitation bubbles in water
Tinne, N.; Ripken, T.; Lubatschowski, H.
2010-02-01
The LASIK procedure is a well established laser based treatment in ophthalmology. Nowadays it includes a cutting of the corneal tissue bases on ultra short pulses which are focused below the tissue surface to create an optical breakdown and hence a dissection of the tissue. The energy of the laser pulse is absorbed by non-linear processes that result in an expansion of a cavitation bubble and rupturing of the tissue. Due to a reduction of the duration of treatment the current development of ultra short laser systems points to higher repetition rates. This in turn results in a probable interaction between different cavitation bubbles of adjacent optical breakdowns. While the interaction of one single laser pulse with biological tissue is analyzed reasonably well experimentally and theoretically, the interaction of several spatial and temporal following pulses is scarcely determined yet. We present a high-speed photography analysis of cavitation bubble interaction for two spatial separated laser-induced optical breakdowns varying the laser pulse energy as well as the spatial distance. Depending on a change of these parameters different kinds of interactions such as a flattening and deformation of bubble shape, asymmetric water streams and jet formation were observed. The results of this research can be used to comprehend and optimize the cutting effect of ultra short pulse laser systems with high repetition rates (> 1 MHz).
NN Interaction in Chiral Constituent Quark Models
Valcarce, A; González, P
2003-01-01
We review the actual state in the description of the NN interaction by means of chiral constituent quark models. We present a series of relevant features that are nicely explained within the quark model framework.
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
Spatial-mode-interaction-induced dispersive-waves and their active tuning in microresonators
Yang, Qi-Fan; Yang, Ki Youl; Vahala, Kerry
2016-01-01
The nonlinear propagation of optical pulses in dielectric waveguides and resonators provides a laboratory to investigate a wide range of remarkable interactions. Many of the resulting phenomena find applications in optical systems. One example is dispersive wave generation, the optical analog of Cherenkov radiation. These waves have an essential role in fiber spectral broadeners that are routinely used in spectrocopy and metrology. Dispersive waves form when a soliton pulse begins to radiate power as a result of higher-order dispersion. Recently, dispersive wave generation in microcavities has been reported by phase matching the waves to dissipative Kerr cavity (DKC) solitons. Here, it is shown that spatial mode interactions within a microcavity can also be used to induce dispersive waves. These interactions are normally avoided altogether in DKC soliton generation. The soliton self frequency shift is also shown to induce fine tuning control of the dispersive wave frequency. Both this mechanism and spatial mo...
Spatial cognition and crime: the study of mental models of spatial relations in crime analysis.
Luini, Lorenzo P; Scorzelli, Marco; Mastroberardino, Serena; Marucci, Francesco S
2012-08-01
Several studies employed different algorithms in order to investigate criminal's spatial behaviour and to identify mental models and cognitive strategies related to it. So far, a number of geographic profiling (GP) software have been implemented to analyse mobility and its relation to the way criminals are using spatial environment when committing a crime. Since crimes are usually perpetrated in the offender's high-awareness areas, those cognitive maps can be employed to create a map of the criminal's operating area to help investigators to circumscribe search areas. The aim of the present study was to verify accuracy of simple statistical analysis in predicting spatial mobility of a group of 30 non-criminal subjects. Results showed that statistics such as Mean Centre and Standard Distance were accurate in elaborating a GP for each subject according to the mobility area provided. Future analysis will be implemented using mobility information of criminal subjects and location-based software to verify whether there is a cognitive spatial strategy employed by them when planning and committing a crime.
Qi, Feng; Tavakol, Vahid; Ocket, Ilja; Xu, Peng; Schreurs, Dominique; Wang, Jinkuan; Nauwelaers, Bart
2010-01-01
Active millimeter wave imaging systems have become a promising candidate for indoor security applications and industrial inspection. However, there is a lack of simulation tools at the system level. We introduce and evaluate two modeling approaches that are applied to active millimeter wave imaging systems. The first approach originates in Fourier optics and concerns the calculation in the spatial frequency domain. The second approach is based on wave propagation and corresponds to calculation in the spatial domain. We compare the two approaches in the case of both rough and smooth objects and point out that the spatial frequency domain calculation may suffer from a large error in amplitude of 50% in the case of rough objects. The comparison demonstrates that the concepts of point-spread function and f-number should be applied with careful consideration in coherent millimeter wave imaging systems. In the case of indoor applications, the near-field effect should be considered, and this is included in the spatial domain calculation.
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.
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.
Interactive Water Resources Modeling and Model Use: An Overview
Loucks, Daniel P.; Kindler, Janusz; Fedra, Kurt
1985-02-01
This serves as an introduction for the following sequence of five papers on interactive water resources and environmental management, policy modeling, and model use. We review some important shortcomings of many management and policy models and argue for improved human-computer-model interaction and communication. This interaction can lead to more effective model use which in turn should facilitate the exploration, analysis, and synthesis of alternative designs, plans, and policies by those directly involved in the planning, management, or policy making process. Potential advantages of interactive modeling and model use, as well as some problems and research needs, are discussed.
Spatial optimum collocation model of urban land and its algorithm
Kong, Xiangqiang; Li, Xinyun
2007-06-01
Optimizing the allocation of urban land is that layout and fix position the various types of land-use in space, maximize the overall benefits of urban space (including economic, social, environment) using a certain method and technique. There is two problems need to deal with in optimizing the allocation of urban land in the technique: one is the quantitative structure, the other is the space structure. In allusion to these problems, according to the principle of spatial coordination, a kind of new optimum collocation model about urban land was put forward in this text. In the model, we give a target function and a set of "soft" constraint conditions, and the area proportions of various types of land-use are restricted to the corresponding allowed scope. Spatial genetic algorithm is used to manipulate and calculate the space of urban land, the optimum spatial collocation scheme can be gradually approached, in which the three basic operations of reproduction, crossover and mutation are all operated on the space. Taking the built-up areas of Jinan as an example, we did the spatial optimum collocation experiment of urban land, the spatial aggregation of various types is better, and an approving result was got.
String Interactions in c=1 Matrix Model
De Boer, J; Verlinde, E; Yee, J T; Boer, Jan de; Sinkovics, Annamaria; Verlinde, Erik; Yee, Jung-Tay
2004-01-01
We study string interactions in the fermionic formulation of the c=1 matrix model. We give a precise nonperturbative description of the rolling tachyon state in the matrix model, and discuss S-matrix elements of the c=1 string. As a first step to study string interactions, we compute the interaction of two decaying D0-branes in terms of free fermions. This computation is compared with the string theory cylinder diagram using the rolling tachyon ZZ boundary states.
DEFF Research Database (Denmark)
Antón Castro, Francesc/François; Musiige, Deogratius; Mioc, Darka
2016-01-01
This paper presents a case study for comparing different multidimensional mathematical modeling methodologies used in multidimensional spatial big data modeling and proposing a new technique. An analysis of multidimensional modeling approaches (neural networks, polynomial interpolation and homotopy...
A theory and a computational model of spatial reasoning with preferred mental models.
Ragni, Marco; Knauff, Markus
2013-07-01
Inferences about spatial arrangements and relations like "The Porsche is parked to the left of the Dodge and the Ferrari is parked to the right of the Dodge, thus, the Porsche is parked to the left of the Ferrari," are ubiquitous. However, spatial descriptions are often interpretable in many different ways and compatible with several alternative mental models. This article suggests that individuals tackle such indeterminate multiple-model problems by constructing a single, simple, and typical mental model but neglect other possible models. The model that first comes to reasoners' minds is the preferred mental model. It helps save cognitive resources but also leads to reasoning errors and illusory inferences. The article presents a preferred model theory and an instantiation of this theory in the form of a computational model, preferred inferences in reasoning with spatial mental models (PRISM). PRISM can be used to simulate and explain how preferred models are constructed, inspected, and varied in a spatial array that functions as if it were a spatial working memory. A spatial focus inserts tokens into the array, inspects the array to find new spatial relations, and relocates tokens in the array to generate alternative models of the problem description, if necessary. The article also introduces a general measure of difficulty based on the number of necessary focus operations (rather than the number of models). A comparison with results from psychological experiments shows that the theory can explain preferences, errors, and the difficulty of spatial reasoning problems.
Function modeling improves the efficiency of spatial modeling using big data from remote sensing
John Hogland; Nathaniel Anderson
2017-01-01
Spatial modeling is an integral component of most geographic information systems (GISs). However, conventional GIS modeling techniques can require substantial processing time and storage space and have limited statistical and machine learning functionality. To address these limitations, many have parallelized spatial models using multiple coding libraries and have...
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.
Lateral specialization in unilateral spatial neglect: a cognitive robotics model.
Conti, Daniela; Di Nuovo, Santo; Cangelosi, Angelo; Di Nuovo, Alessandro
2016-08-01
In this paper, we present the experimental results of an embodied cognitive robotic approach for modelling the human cognitive deficit known as unilateral spatial neglect (USN). To this end, we introduce an artificial neural network architecture designed and trained to control the spatial attentional focus of the iCub robotic platform. Like the human brain, the architecture is divided into two hemispheres and it incorporates bio-inspired plasticity mechanisms, which allow the development of the phenomenon of the specialization of the right hemisphere for spatial attention. In this study, we validate the model by replicating a previous experiment with human patients affected by the USN and numerical results show that the robot mimics the behaviours previously exhibited by humans. We also simulated recovery after the damage to compare the performance of each of the two hemispheres as additional validation of the model. Finally, we highlight some possible advantages of modelling cognitive dysfunctions of the human brain by means of robotic platforms, which can supplement traditional approaches for studying spatial impairments in humans.
Spatial modeling on the nutrient retention of an estuary wetland
Li, X.; Xiao, D.; Jongman, R.H.G.; Harms, W.B.; Bregt, A.K.
2003-01-01
There is a great potential to use the estuary wetland as a final filter for nutrient enriched river water, and reduce the possibility of coastal water eutrophication. Based upon field data, spatial models were designed on a stepwise basis to simulate the nutrient reduction function of the wetland in
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.
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....
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.
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.
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.
Stevenson, Ryan A.; Fister, Juliane Krueger; Barnett, Zachary P.; Nidiffer, Aaron R.; Wallace, Mark T.
2012-01-01
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 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. PMID:22447249
From site measurements to spatial modelling - multi-criteria model evaluation
Gottschalk, Pia; Roers, Michael; Wechsung, Frank
2015-04-01
Hydrological models are traditionally evaluated at gauge stations for river runoff which is assumed to be the valid and global test for model performance. One model output is assumed to reflect the performance of all implemented processes and parameters. It neglects the complex interactions of landscape processes which are actually simulated by the model but not tested. The application of a spatial hydrological model however offers a vast potential of evaluation aspects which shall be presented here with the example of the eco-hydrological model SWIM. We present current activities to evaluate SWIM at the lysimeter site Brandis, the eddy-co-variance site Gebesee and with spatial crop yields of Germany to constrain model performance additionally to river runoff. The lysimeter site is used to evaluate actuall evapotranspiration, total runoff below the soil profile and crop yields. The eddy-covariance site Gebesee offers data to study crop growth via net-ecosystem carbon exchange and actuall evapotranspiration. The performance of the vegetation module is tested via spatial crop yields at county level of Germany. Crop yields are an indirect measure of crop growth which is an important driver of the landscape water balance and therefore eventually determines river runoff as well. First results at the lysimeter site show that simulated soil water dynamics are less sensitive to soil type than measured soil water dynamics. First results from the simulation of actuall evapotranspiration and carbon exchange at Gebesee show a satisfactorily model performance with however difficulties to capture initial vegetation growth in spring. The latter is a hint at problems capturing winter growth conditions and subsequent impacts on crop growth. This is also reflected in the performance of simulated crop yields for Germany where the model reflects crop yields of silage maize much better than of winter wheat. With the given approach we would like to highlight the advantages and
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)
Modeling graphene-substrate interactions
Amlaki, T.
2016-01-01
In this thesis I focussed on the interactions between graphene-like materials (grapheme and germanene) and various substrates. The attractive properties of graphene like a high carrier mobility, its single-atomic thickness and its theoretical magic have made graphene a very popular and promising can
Modeling graphene-substrate interactions
Amlaki, Taher
2016-01-01
In this thesis I focussed on the interactions between graphene-like materials (grapheme and germanene) and various substrates. The attractive properties of graphene like a high carrier mobility, its single-atomic thickness and its theoretical magic have made graphene a very popular and promising can
Bartosova, Alena; Arheimer, Berit; Capell, Rene; Donnelly, Chantal; Strömqvist, Johan
2016-04-01
Nutrient transport models are important tools for large scale assessments of macro-nutrient fluxes (nitrogen, phosphorus) and thus can serve as support tool for environmental assessment and management. Results from model applications over large areas, i.e. from major river basin to continental scales can fill a gap where monitoring data is not available. Here, we present results from the pan-European rainfall-runoff and nutrient transfer model E-HYPE, which is based on open data sources. We investigate the ability of the E-HYPE model to replicate the spatial and temporal variations found in observed time-series of riverine N and P concentrations, and illustrate the model usefulness for nutrient source detection, trend analyses, and scenario modelling. The results show spatial patterns in N concentration in rivers across Europe which can be used to further our understanding of nutrient issues across the European continent. E-HYPE results show hot spots with highest concentrations of total nitrogen in Western Europe along the North Sea coast. Source apportionment was performed to rank sources of nutrient inflow from land to sea along the European coast. An integrated dynamic model as E-HYPE also allows us to investigate impacts of climate change and measure programs, which was illustrated in a couple of scenarios for the Baltic Sea. Comparing model results with observations shows large uncertainty in many of the data sets and the assumptions used in the model set-up, e.g. point source release estimates. However, evaluation of model performance at a number of measurement sites in Europe shows that mean N concentration levels are generally well simulated. P levels are less well predicted which is expected as the variability of P concentrations in both time and space is higher. Comparing model performance with model set-ups using local data for the Weaver River (UK) did not result in systematically better model performance which highlights the complexity of model
Income per capita inequality in China: The Role of Economic Geography and Spatial Interactions
Hering, Laura; Poncet, Sandra
2010-01-01
ED EPS; International audience; This paper contributes to the analysis of growing income disparities within China. Based on a structural model of economic geography using data on per capita income, we evaluate the extent to which market proximity and spatial dependence can explain growing income inequality between Chinese cities. We rely on a data set of 195 Chinese cities between 1995 and 2002. Our econometric specification incorporates an explicit consideration of spatial dependence effects...
Spatial Heterogeneity of Cortical Receptive Fields and Its Impact on Multisensory Interactions
Carriere, Brian N.; Royal, David W.; Wallace, Mark T.
2013-01-01
Investigations of multisensory processing at the level of the single neuron have illustrated the importance of the spatial and temporal relationship of the paired stimuli and their relative effectiveness in determining the product of the resultant interaction. Although these principles provide a good first-order description of the interactive process, they were derived by treating space, time, and effectiveness as independent factors. In the anterior ectosylvian sulcus (AES) of the cat, previous work hinted that the spatial receptive field (SRF) architecture of multisensory neurons might play an important role in multisensory processing due to differences in the vigor of responses to identical stimuli placed at different locations within the SRF. In this study the impact of SRF architecture on cortical multisensory processing was investigated using semichronic single-unit electrophysiological experiments targeting a multisensory domain of the cat AES. The visual and auditory SRFs of AES multisensory neurons exhibited striking response heterogeneity, with SRF architecture appearing to play a major role in the multisensory interactions. The deterministic role of SRF architecture was tightly coupled to the manner in which stimulus location modulated the responsiveness of the neuron. Thus multisensory stimulus combinations at weakly effective locations within the SRF resulted in large (often superadditive) response enhancements, whereas combinations at more effective spatial locations resulted in smaller (additive/subadditive) interactions. These results provide important insights into the spatial organization and processing capabilities of cortical multisensory neurons, features that may provide important clues as to the functional roles played by this area in spatially directed perceptual processes. PMID:18287544
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...
Practical likelihood analysis for spatial generalized linear mixed models
DEFF Research Database (Denmark)
Bonat, W. H.; Ribeiro, Paulo Justiniano
2016-01-01
We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are, respectiv......We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...
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.
Comparing spatial and temporal transferability of hydrological model parameters
Patil, Sopan; Stieglitz, Marc
2015-04-01
Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. In our view, such comparison is especially pertinent in the context of increasing appeal and popularity of the "trading space for time" approaches that are proposed for assessing the hydrological implications of anthropogenic climate change. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal
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.
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.
Spatial distribution of emissions to air – the SPREAD model
DEFF Research Database (Denmark)
Plejdrup, Marlene Schmidt; Gyldenkærne, Steen
The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark’s obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long...... to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously...
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.
Bianchi, F.J.J.A.; Hon¿k, A.; Werf, van der W.
2007-01-01
Changes in land use affect species interactions and population dynamics by modifying the spatial template of trophic interaction and the availability of resources in time and space. We developed a process-based spatially explicit model for evaluating the effects of land use on species viability by
Decision Accuracy and the Role of Spatial Interaction in Opinion Dynamics
Torney, Colin J.; Levin, Simon A.; Couzin, Iain D.
2013-04-01
The opinions and actions of individuals within interacting groups are frequently determined by both social and personal information. When sociality (or the pressure to conform) is strong and individual preferences are weak, groups will remain cohesive until a consensus decision is reached. When group decisions are subject to a bias, representing for example private information known by some members of the population or imperfect information known by all, then the accuracy achieved for a fixed level of bias will increase with population size. In this work we determine how the scaling between accuracy and group size can be related to the microscopic properties of the decision-making process. By simulating a spatial model of opinion dynamics we show that the relationship between the instantaneous fraction of leaders in the population ( L), system size ( N), and accuracy depends on the frequency of individual opinion switches and the level of population viscosity. When social mixing is slow, and individual opinion changes are frequent, accuracy is determined by the absolute number of informed individuals. As mixing rates increase, or the rate of opinion updates decrease, a transition occurs to a regime where accuracy is determined by the value of L√{ N}. We investigate the transition between different scaling regimes analytically by examining a well-mixed limit.
Stretched String with Self-Interaction at High Resolution: Spatial Sizes and Saturation
Qian, Yachao
2014-01-01
We model the (holographic) QCD Pomeron as a long and stretched (fixed impact parameter) transverse quantum string in flat $D_\\perp=3$ dimensions. After discretizing the string in $N$ string bits, we analyze its length, mass and spatial distribution for large $N$ or low-x ($x=1/N$), and away from its Hagedorn point. The string bit distribution shows sizable asymmetries in the transverse plane that may translate to azimuthal asymmetries in primordial particle production in the Pomeron kinematics, and the flow moments in minimum bias $pp$ and $pA$ events. At moderately low-x and relatively small string self-interactions $g_s\\approx \\alpha_s$ (the gauge coupling), a pre-saturation phase is identified whereby the string transverse area undergoes a first order transition from a large diffusive growth to a small fixed size area set by few string lengths $l_s$. This phase amounts to a saturation of the cross section within the Froissart bound. For lower values of $x$ the transverse string bit density is shown to incr...
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.
Uniqueness of Petrov type D spatially inhomogeneous irrotational silent models
Apostolopoulos, P S; Apostolopoulos, Pantelis S; Carot, Jaume
2006-01-01
The consistency of the constraint with the evolution equations for spatially inhomogeneous and irrotational silent (SIIS) models of Petrov type I, demands that the former are preserved along the timelike congruence represented by the velocity of the dust fluid, leading to an infinite set of non-trivial constraints. This fact has been used to conjecture that the resulting models correspond to the spatially homogeneous (SH) models of Bianchi type I, at least for the case where the cosmological constant vanish. By exploiting the full set of the constraint equations as expressed in the 1+3 covariant formalism and using elements from the theory of the spacelike congruences, we provide a direct and simple proof of this conjecture for vacuum and dust fluid models, which shows that the Szekeres family of solutions represents the most general class of SIIS models. The suggested procedure also shows that, the uniqueness of the spatially inhomogeneous and irrotational models of Petrov type D is not affected by the prese...
Allen, C.D.
2007-01-01
Ecosystem patterns and disturbance processes at one spatial scale often interact with processes at another scale, and the result of such cross-scale interactions can be nonlinear dynamics with thresholds. Examples of cross-scale pattern-process relationships and interactions among forest dieback, fire, and erosion are illustrated from northern New Mexico (USA) landscapes, where long-term studies have recently documented all of these disturbance processes. For example, environmental stress, operating on individual trees, can cause tree death that is amplified by insect mortality agents to propagate to patch and then landscape or even regional-scale forest dieback. Severe drought and unusual warmth in the southwestern USA since the late 1990s apparently exceeded species-specific physiological thresholds for multiple tree species, resulting in substantial vegetation mortality across millions of hectares of woodlands and forests in recent years. Predictions of forest dieback across spatial scales are constrained by uncertainties associated with: limited knowledge of species-specific physiological thresholds; individual and site-specific variation in these mortality thresholds; and positive feedback loops between rapidly-responding insect herbivore populations and their stressed plant hosts, sometimes resulting in nonlinear "pest" outbreak dynamics. Fire behavior also exhibits nonlinearities across spatial scales, illustrated by changes in historic fire regimes where patch-scale grazing disturbance led to regional-scale collapse of surface fire activity and subsequent recent increases in the scale of extreme fire events in New Mexico. Vegetation dieback interacts with fire activity by modifying fuel amounts and configurations at multiple spatial scales. Runoff and erosion processes are also subject to scale-dependent threshold behaviors, exemplified by ecohydrological work in semiarid New Mexico watersheds showing how declines in ground surface cover lead to non
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.
A method to visualize the evolution of multiple interacting spatial systems
Heitzler, Magnus; Hackl, Jürgen; Adey, Bryan T.; Iosifescu-Enescu, Ionut; Lam, Juan Carlos; Hurni, Lorenz
2016-07-01
Integrated modeling approaches are being increasingly used to simulate the behavior of, and the interaction between, several interdependent systems. They are becoming more and more important in many fields, including, but not being limited to, civil engineering, hydrology and climate impact research. It is beneficial when using these approaches to be able to visualize both, the intermediary and final results of scenario-based analyses that are conducted in both, space and time. This requires appropriate visualization techniques that enable to efficiently navigate between multiple such scenarios. In recent years, several innovative visualization techniques have been developed that allow for such navigation purposes. These techniques, however, are limited to the representation of one system at a time. Improvements are possible with respect to the ability to visualize the results related to multiple scenarios for multiple interdependent spatio-temporal systems. To address this issue, existing multi-scenario navigation techniques based on small multiples and line graphs are extended by multiple system representations and inter-system impact representations. This not only allows to understand the evolution of the systems under consideration but also eases identifying events where one system influences another system significantly. In addition, the concept of selective branching is described that allows to remove otherwise redundant information from the visualization by considering the logical and temporal dependencies between these systems. This visualization technique is applied to a risk assessment methodology that allows to determine how different environmental systems (i.e. precipitation, flooding, and landslides) influence each other as well as how their impact on civil infrastructure affects society. The results of this work are concepts for improved visualization techniques for multiple interacting spatial systems. The successful validation with domain experts of
Space in multi-agent systems modelling spatial processes
Directory of Open Access Journals (Sweden)
Petr Rapant
2007-06-01
Full Text Available Need for modelling of spatial processes arise in the spehere of geoinformation systems in the last time. Some processes (espetially natural ones can be modeled by means of using external tools, e. g. for modelling of contaminant transport in the environment. But in the case of socio-economic processes suitable tools interconnected with GIS are still in quest of reserch and development. One of the candidate technologies are so called multi-agent systems. Their theory is developed quite well, but they lack suitable means for dealing with space. This article deals with this problem and proposes solution for the field of a road transport modelling.
A spatial operator algebra for manipulator modeling and control
Rodriguez, G.; Kreutz, K.; Milman, M.
1988-01-01
A powerful new spatial operator algebra for modeling, control, and trajectory design of manipulators is discussed along with its implementation in the Ada programming language. Applications of this algebra to robotics include an operator representation of the manipulator Jacobian matrix; the robot dynamical equations formulated in terms of the spatial algebra, showing the complete equivalence between the recursive Newton-Euler formulations to robot dynamics; the operator factorization and inversion of the manipulator mass matrix which immediately results in O(N) recursive forward dynamics algorithms; the joint accelerations of a manipulator due to a tip contact force; the recursive computation of the equivalent mass matrix as seen at the tip of a manipulator; and recursive forward dynamics of a closed chain system. Finally, additional applications and current research involving the use of the spatial operator algebra are discussed in general terms.
Spatial-angular modeling of ground-based biaxial lidar
Agishev, Ravil R.
1997-10-01
Results of spatial-angular LIDAR modeling based on an efficiency criterion introduced are represented. Their analysis shows that a low spatial-angular efficiency of traditional VIS and NIR systems is a main cause of a low S/BR ratio at the photodetector input. It determines the considerable measurements errors and the following low accuracy of atmospheric optical parameters retrieval. As we have shown, the most effective protection against intensive sky background radiation for ground-based biaxial LIDAR's consist in forming of their angular field according to spatial-angular efficiency criterion G. Some effective approaches to high G-parameter value achievement to achieve the receiving system optimization are discussed.
Modeling of soil-water-structure interaction
DEFF Research Database (Denmark)
Tang, Tian
to dynamic ocean waves. The goal of this research project is to develop numerical soil models for computing realistic seabed response in the interacting offshore environment, where ocean waves, seabed and offshore structure highly interact with each other. The seabed soil models developed are based...... 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...... of Computational Fluid Dynamics (CFD) and structural mechanics are available. The interaction in the system is modeled in a 1-way manner: First detailed free surface CFD calculations are executed to obtain a realistic wave field around a given structure. Then the dynamic structural response, due to the motions...
Modelling spatial patterns of urban growth in Africa.
Linard, Catherine; Tatem, Andrew J; Gilbert, Marius
2013-10-01
The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5-10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.
Modelling spatial patterns of urban growth in Africa
Linard, Catherine; Tatem, Andrew J.; Gilbert, Marius
2013-01-01
The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers. PMID:25152552
An Interactive Whiteboard Model Survey: Reliable Development
Directory of Open Access Journals (Sweden)
Bih-Yaw Shih
2012-04-01
Full Text Available Applications and practices of interactive whiteboards (IWBs in school learning is important focus and development trend for developmented countries in recent years. There are rare researches and discussions about IWB teaching materials for course teaching and teaching effectiveness. As for the aspect of academic studies, there is more practical teaching sharing for subjects such as language learning, mathematical learning and physical science learning; however, it is rarely seen empirical research on the application of IWB for educational acceptances of interactive whiteboards. Based on its imporatances, we summarize previous literatures to establish a theoretical model for interactive whiteboards (IWBs. Variables in this model are then discussed to find out the interaction between each other. The contribution of the study develops an innovative model for educational acceptances of interactive whiteboards using hybrid TAM, ECM, and Flow models.
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.
Modeling the impact of spatial relationships on horizontal curve safety.
Findley, Daniel J; Hummer, Joseph E; Rasdorf, William; Zegeer, Charles V; Fowler, Tyler J
2012-03-01
The curved segments of roadways are more hazardous because of the additional centripetalforces exerted on a vehicle, driver expectations, and other factors. The safety of a curve is dependent on various factors, most notably by geometric factors, but the location of a curve in relation to other curves is also thought to influence the safety of those curves because of a driver's expectation to encounter additional curves. The link between an individual curve's geometric characteristics and its safety performance has been established, but spatial considerations are typically not included in a safety analysis. The spatial considerations included in this research consisted of four components: distance to adjacent curves, direction of turn of the adjacent curves, and radius and length of the adjacent curves. The primary objective of this paper is to quantify the spatial relationship between adjacent horizontal curves and horizontal curve safety using a crash modification factor. Doing so enables a safety professional to more accurately estimate safety to allocate funding to reduce or prevent future collisions and more efficiently design new roadway sections to minimize crash risk where there will be a series of curves along a route. The most important finding from this research is the statistical significance of spatial considerations for the prediction of horizontal curve safety. The distances to adjacent curves were found to be a reliable predictor of observed collisions. This research recommends a model which utilizes spatial considerations for horizontal curve safety prediction in addition to current Highway Safety Manual prediction capabilities using individual curve geometric features.
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.
Neuromorphic model of magnocellular and parvocellular visual paths: spatial resolution
Energy Technology Data Exchange (ETDEWEB)
Aguirre, Rolando C [Departamento de Luminotecnia, Luz y Vision, FACET, Universidad Nacional de Tucuman, Tucuman (Argentina); Felice, Carmelo J [Departamento de BioingenierIa, FACET, Universidad Nacional de Tucuman Argentina, Tucuman (Argentina); Colombo, Elisa M [Departamento de Luminotecnia, Luz y Vision, FACET, Universidad Nacional de Tucuman, Tucuman (Argentina)
2007-11-15
Physiological studies of the human retina show the existence of at least two visual information processing channels, the magnocellular and the parvocellular ones. Both have different spatial, temporal and chromatic features. This paper focuses on the different spatial resolution of these two channels. We propose a neuromorphic model, so that they match the retina's physiology. Considering the Deutsch and Deutsch model (1992), we propose two configurations (one for each visual channel) of the connection between the retina's different cell layers. The responses of the proposed model have similar behaviour to those of the visual cells: each channel has an optimum response corresponding to a given stimulus size which decreases for larger or smaller stimuli. This size is bigger for the magno path than for the parvo path and, in the end, both channels produce a magnifying of the borders of a stimulus.
Spatial probabilistic pulsatility model for enhancing photoplethysmographic imaging systems
Amelard, Robert; Clausi, David A.; Wong, Alexander
2016-11-01
Photoplethysmographic imaging (PPGI) is a widefield noncontact biophotonic technology able to remotely monitor cardiovascular function over anatomical areas. Although spatial context can provide insight into physiologically relevant sampling locations, existing PPGI systems rely on coarse spatial averaging with no anatomical priors for assessing arterial pulsatility. Here, we developed a continuous probabilistic pulsatility model for importance-weighted blood pulse waveform extraction. Using a data-driven approach, the model was constructed using a 23 participant sample with a large demographic variability (11/12 female/male, age 11 to 60 years, BMI 16.4 to 35.1 kg·m-2). Using time-synchronized ground-truth blood pulse waveforms, spatial correlation priors were computed and projected into a coaligned importance-weighted Cartesian space. A modified Parzen-Rosenblatt kernel density estimation method was used to compute the continuous resolution-agnostic probabilistic pulsatility model. The model identified locations that consistently exhibited pulsatility across the sample. Blood pulse waveform signals extracted with the model exhibited significantly stronger temporal correlation (W=35,pbpm].
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
Liu, Quan-Xing; Jin, Zhen
2006-01-01
Results are reported concerning the formation of spatial patterns in the two-species ratio-dependent predator-prey model driven by spatial colored-noise. The results show that there is a critical value with respect to the intensity of spatial noise for this system when the parameters are in the Turing space, above which the regular spatial patterns appear in two dimensions, but under which there are not regular spatial patterns produced. In particular, we investigate in two-dimensional space ...
Interactive Presentation of Geo-Spatial Climate Data in Multi-Display Environments
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Christian Eichner
2015-04-01
Full Text Available The visual analysis of complex geo-spatial data is a challenging task. Typically, different views are used to communicate different aspects. With changing topics of interest, however, novel views are required. This leads to dynamically changing presentations of multiple views. This paper introduces a novel approach to support such scenarios. It allows for a spontaneous incorporation of views from different sources and to automatically layout these views in a multi-display environment. Furthermore, we introduce an enhanced undo/redo mechanism for this setting, which records user interactions and, in this way, enables swift reconfigurations of displayed views. Hence, users can fluently switch the focus of visual analysis without extensive manual interactions. We demonstrate our approach by the particular use case of discussing geo-spatial climate data.
Spatial heterogeneity, frequency-dependent selection and polymorphism in host-parasite interactions
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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
Interactive marine spatial planning: siting tidal energy arrays around the Mull of Kintyre.
Alexander, Karen A; Janssen, Ron; Arciniegas, Gustavo; O'Higgins, Timothy G; Eikelboom, Tessa; Wilding, Thomas A
2012-01-01
The rapid development of the offshore renewable energy sector has led to an increased requirement for Marine Spatial Planning (MSP) and, increasingly, this is carried out in the context of the 'ecosystem approach' (EA) to management. We demonstrate a novel method to facilitate implementation of the EA. Using a real-time interactive mapping device (touch-table) and stakeholder workshops we gathered data and facilitated negotiation of spatial trade-offs at a potential site for tidal renewable energy off the Mull of Kintyre (Scotland). Conflicts between the interests of tidal energy developers and commercial and recreational users of the area were identified, and use preferences and concerns of stakeholders were highlighted. Social, cultural and spatial issues associated with conversion of common pool to private resource were also revealed. The method identified important gaps in existing spatial data and helped to fill these through interactive user inputs. The workshops developed a degree of consensus between conflicting users on the best areas for potential development suggesting that this approach should be adopted during MSP.
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
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)
Ming He
2015-11-01
Full Text Available We propose a random effects panel data model with both spatially correlated error components and spatially lagged dependent variables. We focus on diagnostic testing procedures and derive Lagrange multiplier (LM test statistics for a variety of hypotheses within this model. We first construct the joint LM test for both the individual random effects and the two spatial effects (spatial error correlation and spatial lag dependence. We then provide LM tests for the individual random effects and for the two spatial effects separately. In addition, in order to guard against local model misspecification, we derive locally adjusted (robust LM tests based on the Bera and Yoon principle (Bera and Yoon, 1993. We conduct a small Monte Carlo simulation to show the good finite sample performances of these LM test statistics and revisit the cigarette demand example in Baltagi and Levin (1992 to illustrate our testing procedures.
Two-component Fermions in Optical Lattice with Spatially Alternating Interactions
Hoang, Anh-Tuan; Nguyen, Thi-Hai-Yen; Tran, Thi-Thu-Trang; Le, Duc-Anh
2016-10-01
We investigate two-component mass-imbalanced fermions in an optical lattice with spatially modulated interactions by using two-site dynamical mean field theory. At half-filling and zero temperature, the phase diagram of the system is analytically obtained, in which the metallic region is reduced with increasing the mass imbalance. The ground-state properties of the fermionic system are discussed from the behaviors of both the spin-dependent quasi-particle weight at the Fermi level and the double occupancy for each sublattice as functions of the local interaction strengths for various values of the mass imbalance.
Investigating the spatial and temporal modulation of visuotactile interactions in older adults.
Couth, Samuel; Gowen, Emma; Poliakoff, Ellen
2016-05-01
Previous research has shown that spatially and temporally disparate multisensory events are more likely to interact for older adults. For visuotactile interactions, this suggests that the representation of peripersonal space is expanded and temporal perception within this space is less precise. Previously, visuotactile space has been found to expand horizontally into the opposite hemispace, and here we sought to replicate and extend this by exploring both horizontal and vertical space from the hand. Moreover, we investigated whether both spatial and temporal domains are affected for an individual, which have previously been measured using distinct tasks and different participants. We presented a modified cross-modal congruency task (Poole et al. in Multisens Res. doi: 10.1163/22134808-00002475 , 2015a) to thirty older participants (age range 65-85 years), with unisensory tactile performance equated for each individual. For the temporal manipulation, the timings of visual distractors and tactile targets were offset. For the spatial manipulation, visual distractors were presented from multiple positions in ipsilateral and contralateral hemispaces. Whilst the temporal modulation of visuotactile interactions for older adults was equivalent to that observed in young adults, spatial modulation was reduced; significant visuotactile interactions were observed for visual distractors presented in the same and opposite hemispace to the stimulated hand, in the lower visual field. This suggests an expanded representation of visuotactile space surrounding the hand in older adults, which occurs horizontally into the contralateral hemispace only, rather than expanding both vertically and horizontally. This is likely to have consequences for perception of space and goal-directed action in ageing.
Modified Spatial Channel Model for MIMO Wireless Systems
Directory of Open Access Journals (Sweden)
Pekka Kyösti
2007-12-01
Full Text Available Ã¯Â»Â¿The third generation partnership Project's (3GPP spatial channel model (SCM is a stochastic channel model for MIMO systems. Due to fixed subpath power levels and angular directions, the SCM model does not show the degree of variation which is encountered in real channels. In this paper, we propose a modified SCM model which has random subpath powers and directions and still produces Laplace shape angular power spectrum. Simulation results on outage MIMO capacity with basic and modified SCM models show that the modified SCM model gives constantly smaller capacity values. Accordingly, it seems that the basic SCM gives too small correlation between MIMO antennas. Moreover, the variance in capacity values is larger using the proposed SCM model. Simulation results were supported by the outage capacity results from a measurement campaign conducted in the city centre of Oulu, Finland.
Spatial patterns of cutaneous vibration during whole-hand haptic interactions
Hayward, Vincent; Visell, Yon
2016-01-01
We investigated the propagation patterns of cutaneous vibration in the hand during interactions with touched objects. Prior research has highlighted the importance of vibrotactile signals during haptic interactions, but little is known of how vibrations propagate throughout the hand. Furthermore, the extent to which the patterns of vibrations reflect the nature of the objects that are touched, and how they are touched, is unknown. Using an apparatus comprised of an array of accelerometers, we mapped and analyzed spatial distributions of vibrations propagating in the skin of the dorsal region of the hand during active touch, grasping, and manipulation tasks. We found these spatial patterns of vibration to vary systematically with touch interactions and determined that it is possible to use these data to decode the modes of interaction with touched objects. The observed vibration patterns evolved rapidly in time, peaking in intensity within a few milliseconds, fading within 20–30 ms, and yielding interaction-dependent distributions of energy in frequency bands that span the range of vibrotactile sensitivity. These results are consistent with findings in perception research that indicate that vibrotactile information distributed throughout the hand can transmit information regarding explored and manipulated objects. The results may further clarify the role of distributed sensory resources in the perceptual recovery of object attributes during active touch, may guide the development of approaches to robotic sensing, and could have implications for the rehabilitation of the upper extremity. PMID:27035957
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.
Visuo-haptic interactions in unilateral spatial neglect: the crossmodal Judd illusion
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Flavia eMancini
2011-11-01
Full Text Available Unilateral spatial neglect has been mainly investigated in the visual modality; only a few studies compared spatial neglect in different sensory modalities, and explored their multisensory interactions, with controversial results. We investigated the integration between vision and haptics, through a bisection task of a crossmodal length illusion, the Judd variant of the Müller-Lyer illusion. We examined right-brain-damaged patients with (n=7 and without (n=7 left unilateral spatial neglect, and neurologically unimpaired participants (n=14 in the bisection of Judd stimuli under visual, haptic, and visuo-haptic presentation. Neglect patients showed the characteristic rightward bias in the bisection of a baseline stimulus in the visual modality, but not in the haptic and visuo-haptic conditions. The illusory effects were preserved in each group and in each modality, indicating that the processing of the length illusion is independent of the presence of deficits of spatial attention and representation. Spatial neglect can be modality-specific, but visual and tactile sensory inputs are properly integrated.
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.
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)
Dynamical Models of Dyadic Interactions with Delay
Bielczyk, Natalia; Płatkowski, Tadeusz
2012-01-01
When interpersonal interactions between individuals are described by the (discrete or continuous) dynamical systems, the interactions are usually assumed to be instantaneous: the rates of change of the actual states of the actors at given instant of time are assumed to depend on their states at the same time. In reality the natural time delay should be included in the corresponding models. We investigate a general class of linear models of dyadic interactions with a constant discrete time delay. We prove that in such models the changes of stability of the stationary points from instability to stability or vice versa occur for various intervals of the parameters which determine the intensity of interactions. The conditions guaranteeing arbitrary number (zero, one ore more) of switches are formulated and the relevant theorems are proved. A systematic analysis of all generic cases is carried out. It is obvious that the dynamics of interactions depend both on the strength of reactions of partners on their own sta...
Database modeling to integrate macrobenthos data in Spatial Data Infrastructure
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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
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.
Spatial Modelling of Sediment Transport over the Upper Citarum Catchment
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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
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.
Think continuous: Markovian Gaussian models in spatial statistics
Simpson, Daniel; Rue, Håvard
2011-01-01
Gaussian Markov random fields (GMRFs) are frequently used as computationally efficient models in spatial statistics. Unfortunately, it has traditionally been difficult to link GMRFs with the more traditional Gaussian random field models as the Markov property is difficult to deploy in continuous space. Following the pioneering work of Lindgren et al. (2011), we expound on the link between Markovian Gaussian random fields and GMRFs. In particular, we discuss the theoretical and practical aspects of fast computation with continuously specified Markovian Gaussian random fields, as well as the clear advantages they offer in terms of clear, parsimonious and interpretable models of anisotropy and non-stationarity.
Spatial emission modelling for residential wood combustion in Denmark
DEFF Research Database (Denmark)
Plejdrup, Marlene Schmidt; Nielsen, Ole-Kenneth; Brandt, Jørgen
2016-01-01
Residential wood combustion (RWC) is a major contributor to atmospheric pollution especially for particulate matter. Air pollution has significant impact on human health, and it is therefore important to know the human exposure. For this purpose, it is necessary with a detailed high resolution...... model with the developed weighting factors (76 ton PM2.5) is in good agreement with the case study (95 ton PM2.5), and that the new model has improved the spatial emission distribution significantly compared to the previous model (284 ton PM2.5). Additionally, a sensitivity analysis was done...
Matrix models with Penner interaction inspired by interacting ribonucleic acid
Indian Academy of Sciences (India)
Pradeep Bhadola; N Deo
2015-02-01
The Penner interaction known in studies of moduli space of punctured Riemann surfaces is introduced and studied in the context of random matrix model of homo RNA. An analytic derivation of the generating function is given and the corresponding partition function is derived numerically. An additional dependence of the structure combinatorics factor on (related to the size of the matrix and the interaction strength) is obtained. This factor has a strong effect on the structure combinatorics in the low regime. Databases are scanned for real ribonucleic acid (RNA) structures and pairing information for these RNA structures is computationally extracted. Then the genus is calculated for every structure and plotted as a function of length. The genus distribution function is compared with the prediction from the nonlinear (NL) model. The specific heat and distribution of structure with temperature calculated from the NL model shows that the NL inter-action is biased towards planar structures. The second derivative of specific heat changes phase from a double peaked function for small to a single peak for large . Detailed analysis reveals the presence of the double peak only for genus 0 structures, the higher genii behave normally with . Comparable behaviour is found in studies involving interactions of RNA with osmolytes and monovalent cations in unfolding experiments.
Cho, Sung-Won; Kwak, Sungwook; Woolley, Thomas E; Lee, Min-Jung; Kim, Eun-Jung; Baker, Ruth E; Kim, Hee-Jin; Shin, Jeon-Soo; Tickle, Cheryll; Maini, Philip K; Jung, Han-Sung
2011-05-01
Each vertebrate species displays specific tooth patterns in each quadrant of the jaw: the mouse has one incisor and three molars, which develop at precise locations and at different times. The reason why multiple teeth form in the jaw of vertebrates and the way in which they develop separately from each other have been extensively studied, but the genetic mechanism governing the spatial patterning of teeth still remains to be elucidated. Sonic hedgehog (Shh) is one of the key signaling molecules involved in the spatial patterning of teeth and other ectodermal organs such as hair, vibrissae and feathers. Sostdc1, a secreted inhibitor of the Wnt and Bmp pathways, also regulates the spatial patterning of teeth and hair. Here, by utilizing maternal transfer of 5E1 (an anti-Shh antibody) to mouse embryos through the placenta, we show that Sostdc1 is downstream of Shh signaling and suggest a Wnt-Shh-Sostdc1 negative feedback loop as a pivotal mechanism controlling the spatial patterning of teeth. Furthermore, we propose a new reaction-diffusion model in which Wnt, Shh and Sostdc1 act as the activator, mediator and inhibitor, respectively, and confirm that such interactions can generate the tooth pattern of a wild-type mouse and can explain the various tooth patterns produced experimentally.
Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models
Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea
2014-05-01
Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.
Spatial uncertainty assessment in modelling reference evapotranspiration at regional scale
Directory of Open Access Journals (Sweden)
G. Buttafuoco
2010-07-01
Full Text Available Evapotranspiration is one of the major components of the water balance and has been identified as a key factor in hydrological modelling. For this reason, several methods have been developed to calculate the reference evapotranspiration (ET_{0}. In modelling reference evapotranspiration it is inevitable that both model and data input will present some uncertainty. Whatever model is used, the errors in the input will propagate to the output of the calculated ET_{0}. Neglecting information about estimation uncertainty, however, may lead to improper decision-making and water resources management. One geostatistical approach to spatial analysis is stochastic simulation, which draws alternative and equally probable, realizations of a regionalized variable. Differences between the realizations provide a measure of spatial uncertainty and allow to carry out an error propagation analysis. Among the evapotranspiration models, the Hargreaves-Samani model was used.
The aim of this paper was to assess spatial uncertainty of a monthly reference evapotranspiration model resulting from the uncertainties in the input attributes (mainly temperature at regional scale. A case study was presented for Calabria region (southern Italy. Temperature data were jointly simulated by conditional turning bands simulation with elevation as external drift and 500 realizations were generated.
The ET_{0} was then estimated for each set of the 500 realizations of the input variables, and the ensemble of the model outputs was used to infer the reference evapotranspiration probability distribution function. This approach allowed to delineate the areas characterized by greater uncertainty, to improve supplementary sampling strategies and ET_{0} value predictions.
'spup' - an R package for uncertainty propagation in spatial environmental modelling
Sawicka, Kasia; Heuvelink, Gerard
2016-04-01
Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected static and interactive visualization methods that are understandable by non-experts with limited background in
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...
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.
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...
Representing spatial information in a computational model for network management
Blaisdell, James H.; Brownfield, Thomas F.
1994-01-01
While currently available relational database management systems (RDBMS) allow inclusion of spatial information in a data model, they lack tools for presenting this information in an easily comprehensible form. Computer-aided design (CAD) software packages provide adequate functions to produce drawings, but still require manual placement of symbols and features. This project has demonstrated a bridge between the data model of an RDBMS and the graphic display of a CAD system. It is shown that the CAD system can be used to control the selection of data with spatial components from the database and then quickly plot that data on a map display. It is shown that the CAD system can be used to extract data from a drawing and then control the insertion of that data into the database. These demonstrations were successful in a test environment that incorporated many features of known working environments, suggesting that the techniques developed could be adapted for practical use.
An exactly solvable, spatial model of mutation accumulation in cancer
Paterson, Chay; Nowak, Martin A.; Waclaw, Bartlomiej
2016-12-01
One of the hallmarks of cancer is the accumulation of driver mutations which increase the net reproductive rate of cancer cells and allow them to spread. This process has been studied in mathematical models of well mixed populations, and in computer simulations of three-dimensional spatial models. But the computational complexity of these more realistic, spatial models makes it difficult to simulate realistically large and clinically detectable solid tumours. Here we describe an exactly solvable mathematical model of a tumour featuring replication, mutation and local migration of cancer cells. The model predicts a quasi-exponential growth of large tumours, even if different fragments of the tumour grow sub-exponentially due to nutrient and space limitations. The model reproduces clinically observed tumour growth times using biologically plausible rates for cell birth, death, and migration rates. We also show that the expected number of accumulated driver mutations increases exponentially in time if the average fitness gain per driver is constant, and that it reaches a plateau if the gains decrease over time. We discuss the realism of the underlying assumptions and possible extensions of the model.
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.
A marginal revenue equilibrium model for spatial water allocation
Institute of Scientific and Technical Information of China (English)
王劲峰; 刘昌明; 王智勇; 于静洁
2002-01-01
The outside water is transported into the water-shorted area. It is allocated among many sub-areas that composed the water-shorted area, in order to maximize the total benefit from the input water for the areas. This paper presents a model for spatial water allocation based on the marginal revenue of water utilization, taking the six southern districts of Hebei Province as an example.
Spatial memory impairments in a prediabetic rat model
Soares,E.; Prediger, R. D.; Nunes, S.; A.A. Castro; Viana, S .D.; Lemos, C.; C. M. Souza; Agostinho, P; Cunha, R. A.; E. Carvalho; Ribeiro, C. A. Fontes; Reis, F.; PEREIRA, F. C.
2013-01-01
Diabetes is associated with an increased risk for brain disorders, namely cognitive impairments associated with hippocampal dysfunction underlying diabetic encephalopathy. However, the impact of a prediabetic state on cognitive function is unknown. Therefore, we now investigated whether spatial learning and memory deficits and the underlying hippocampal dysfunction were already present in a prediabetic animal model. Adult Wistar rats drinking high-sucrose (HSu) diet (35% sucrose solution duri...
Rule-based spatial modeling with diffusing, geometrically constrained molecules
Directory of Open Access Journals (Sweden)
Lohel Maiko
2010-06-01
Full Text Available Abstract Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS, we have chosen an already existing formalism (BioNetGen for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Results Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules. When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. Conclusions We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial
Rule-based spatial modeling with diffusing, geometrically constrained molecules
Lohel Maiko; Lenser Thorsten; Ibrahim Bashar; Gruenert Gerd; Hinze Thomas; Dittrich Peter
2010-01-01
Abstract Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction net...
Information Retrieval Interaction: an Analysis of Models
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Farahnaz Sadoughi
2012-03-01
Full Text Available Information searching process is an interactive process; thus users has control on searching process, and they can manage the results of the search process. In this process, user's question became more mature, according to retrieved results. In addition, on the side of the information retrieval system, there are some processes that could not be realized, unless by user. Practically, this issue, is egregious in “Interaction” -i.e. process of user connection to other system elements- and in “Relevance judgment”. This paper had a glance to existence of “Interaction” in information retrieval, in first. Then the tradition model of information retrieval and its strenght and weak points were reviewed. Finally, the current models of interactive information retrieval includes: Belkin episodic model, Ingwersen cognitive model, Sarasevic stratified model, and Spinks interactive feedback model were elucidated.
Assessing NARCCAP climate model effects using spatial confidence regions
French, Joshua P.; McGinnis, Seth; Schwartzman, Armin
2017-07-01
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.
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.
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.
Advances in modeling of biomolecular interactions
Institute of Scientific and Technical Information of China (English)
Cong-zhongCAI; Ze-rongLI; Wan-luWANG; Yu-zongCHEN
2004-01-01
Modeling of molecular interactions is increasingly used in life science research and biotechnology development.Examples are computer aided drug design, prediction of protein interactions with other molecules, and simulation of networks of biomolecules in a particular process in human body. This article reviews recent progress in the related fields and provides a brief overview on the methods used in molecular modeling of biological systems.
A Heuristic Molecular Model of Hydrophobic Interactions
Hummer, G; Garde, S; Garcia, A.E.; Pohorille, A; Pratt, L.R.
1995-01-01
Hydrophobic interactions provide driving forces for protein folding, membrane formation, and oil-water separation. Motivated by information theory, the poorly understood nonpolar solute interactions in water are investigated. A simple heuristic model of hydrophobic effects in terms of density fluctuations is developed. This model accounts quantitatively for the central hydrophobic phenomena of cavity formation and association of inert gas solutes; it therefore clarifies the underlying physics...
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.
Cárcamo, P. Francisco; Gaymer, Carlos F.
2013-12-01
Marine protected areas are not established in an institutional and governance vacuum and managers should pay attention to the wider social-ecological system in which they are immersed. This article examines Islas Choros-Damas Marine Reserve, a small marine protected area located in a highly productive and biologically diverse coastal marine ecosystem in northern Chile, and the interactions between human, institutional, and ecological dimensions beyond those existing within its boundaries. Through documents analysis, surveys, and interviews, we described marine reserve implementation (governing system) and the social and natural ecosystem-to-be-governed. We analyzed the interactions and the connections between the marine reserve and other spatially explicit conservation and/or management measures existing in the area and influencing management outcomes and governance. A top-down approach with poor stakeholder involvement characterized the implementation process. The marine reserve is highly connected with other spatially explicit measures and with a wider social-ecological system through various ecological processes and socio-economic interactions. Current institutional interactions with positive effects on the management and governance are scarce, although several potential interactions may be developed. For the study area, any management action must recognize interferences from outside conditions and consider some of them (e.g., ecotourism management) as cross-cutting actions for the entire social-ecological system. We consider that institutional interactions and the development of social networks are opportunities to any collective effort aiming to improve governance of Islas Choros-Damas marine reserve. Communication of connections and interactions between marine protected areas and the wider social-ecological system (as described in this study) is proposed as a strategy to improve stakeholder participation in Chilean marine protected areas.
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.
Uppulury, Karthik; Kolomeisky, Anatoly B.
2016-12-01
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.
A hierarchical model for spatial capture-recapture data
Royle, J. Andrew; Young, K.V.
2008-01-01
Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.
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.
Modeling of Laser Material Interactions
Garrison, Barbara
2009-03-01
Irradiation of a substrate by laser light initiates the complex chemical and physical process of ablation where large amounts of material are removed. Ablation has been successfully used in techniques such as nanolithography and LASIK surgery, however a fundamental understanding of the process is necessary in order to further optimize and develop applications. To accurately describe the ablation phenomenon, a model must take into account the multitude of events which occur when a laser irradiates a target including electronic excitation, bond cleavage, desorption of small molecules, ongoing chemical reactions, propagation of stress waves, and bulk ejection of material. A coarse grained molecular dynamics (MD) protocol with an embedded Monte Carlo (MC) scheme has been developed which effectively addresses each of these events during the simulation. Using the simulation technique, thermal and chemical excitation channels are separately studied with a model polymethyl methacrylate system. The effects of the irradiation parameters and reaction pathways on the process dynamics are investigated. The mechanism of ablation for thermal processes is governed by a critical number of bond breaks following the deposition of energy. For the case where an absorbed photon directly causes a bond scission, ablation occurs following the rapid chemical decomposition of material. The study provides insight into the influence of thermal and chemical processes in polymethyl methacrylate and facilitates greater understanding of the complex nature of polymer ablation.
A spatial model for conflict incorporating within- and between-actor effects
Knipl, Diána; Davies, Toby; Baudains, Peter
2017-10-01
The application of ecological models to human conflict scenarios has given rise to a number of models which describe antagonistic relationships between adversaries. Recent work demonstrates that the spatial disaggregation of such models is not only well-motivated but also gives rise to interesting dynamic behaviour, particularly with respect to the spatial distribution of resources. One feature which is largely absent from previous models, however, is the ability of an adversary to coordinate activity across its various locations. Most immediately, this corresponds to the notion of 'support' - the reallocation of resources from one site to another according to need - which plays an important role in real-world conflict. In this paper, we generalise a spatially-disaggregated form of the classic Richardson model of conflict escalation by adding a cross-location interaction term for the within-adversary dynamics at each location. We explore the model analytically, giving conditions for the stability of the balanced equilibrium state. We then also carry out a number of numerical simulations which correspond to stylised real-world conflict scenarios. Potential further applications of the model, and its implications for policy, are then discussed.
Evaluation of Spatial Agreement of Distinct Landslide Prediction Models
Sterlacchini, Simone; Bordogna, Gloria; Frigerio, Ivan
2013-04-01
The aim of the study was to assess the degree of spatial agreement of different predicted patterns in a majority of coherent landslide prediction maps with almost similar success and prediction rate curves. If two or more models have a similar performance, the choice of the best one is not a trivial operation and cannot be based on success and prediction rate curves only. In fact, it may happen that two or more prediction maps with similar accuracy and predictive power do not have the same degree of agreement in terms of spatial predicted patterns. The selected study area is the high Valtellina valley, in North of Italy, covering a surface of about 450 km2 where mapping of historical landslides is available. In order to assess landslide susceptibility, we applied the Weights of Evidence (WofE) modeling technique implemented by USGS by means of ARC-SDM tool. WofE efficiently investigate the spatial relationships among past events and multiple predisposing factors, providing useful information to identify the most probable location of future landslide occurrences. We have carried out 13 distinct experiments by changing the number of morphometric and geo-environmental explanatory variables in each experiment with the same training set and thus generating distinct models of landslide prediction, computing probability degrees of occurrence of landslides in each pixel. Expert knowledge and previous results from indirect statistically-based methods suggested slope, land use, and geology the best "driving controlling factors". The Success Rate Curve (SRC) was used to estimate how much the results of each model fit the occurrence of landslides used for the training of the models. The Prediction Rate Curve (PRC) was used to estimate how much the model predict the occurrence of landslides in the validation set. We found that the performances were very similar for different models. Also the dendrogram of the Cohen's kappa statistic and Principal Component Analysis (PCA) were
Spatial interpolation schemes of daily precipitation for hydrologic modeling
Hwang, Y.; Clark, M.; Rajagopalan, B.; Leavesley, G.
2012-01-01
Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.
Combining Spatial and Telemetric Features for Learning Animal Movement Models
Kapicioglu, Berk; Wikelski, Martin; Broderick, Tamara
2012-01-01
We introduce a new graphical model for tracking radio-tagged animals and learning their movement patterns. The model provides a principled way to combine radio telemetry data with an arbitrary set of userdefined, spatial features. We describe an efficient stochastic gradient algorithm for fitting model parameters to data and demonstrate its effectiveness via asymptotic analysis and synthetic experiments. We also apply our model to real datasets, and show that it outperforms the most popular radio telemetry software package used in ecology. We conclude that integration of different data sources under a single statistical framework, coupled with appropriate parameter and state estimation procedures, produces both accurate location estimates and an interpretable statistical model of animal movement.
Induced gelation in a two-site spatial coagulation model
Siegmund-Schultze, Rainer; Wagner, Wolfgang
2006-01-01
A two-site spatial coagulation model is considered. Particles of masses $m$ and $n$ at the same site form a new particle of mass $m+n$ at rate $mn$. Independently, particles jump to the other site at a constant rate. The limit (for increasing particle numbers) of this model is expected to be nondeterministic after the gelation time, namely, one or two giant particles randomly jump between the two sites. Moreover, a new effect of induced gelation is observed--the gelation happening at the site...
Evolution of interactions and cooperation in the spatial prisoner's dilemma game.
Zhang, Chunyan; Zhang, Jianlei; Xie, Guangming; Wang, Long; Perc, Matjaž
2011-01-01
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.
Evolution of interactions and cooperation in the spatial prisoner's dilemma game
Zhang, Chunyan; Xie, Guangming; Wang, Long; Perc, Matjaz; 10.1371/journal.pone.0026724
2011-01-01
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.
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.
Kalligiannaki, Evangelia; Plechac, Petr
2012-01-01
We propose a hierarchy of multi-level kinetic Monte Carlo methods for sampling high-dimensional, stochastic lattice particle dynamics with complex interactions. The method is based on the efficient coupling of different spatial resolution levels, taking advantage of the low sampling cost in a coarse space and by developing local reconstruction strategies from coarse-grained dynamics. Microscopic reconstruction corrects possibly significant errors introduced through coarse-graining, leading to the controlled-error approximation of the sampled stochastic process. In this manner, the proposed multi-level algorithm overcomes known shortcomings of coarse-graining of particle systems with complex interactions such as combined long and short-range particle interactions and/or complex lattice geometries. Specifically, we provide error analysis for the approximation of long-time stationary dynamics in terms of relative entropy and prove that information loss in the multi-level methods is growing linearly in time, whic...
Electroweak and Strong Interactions Phenomenology, Concepts, Models
Scheck, Florian
2012-01-01
Electroweak and Strong Interaction: Phenomenology, Concepts, Models, begins with relativistic quantum mechanics and some quantum field theory which lay the foundation for the rest of the text. The phenomenology and the physics of the fundamental interactions are emphasized through a detailed discussion of the empirical fundamentals of unified theories of strong, electromagnetic, and weak interactions. The principles of local gauge theories are described both in a heuristic and a geometric framework. The minimal standard model of the fundamental interactions is developed in detail and characteristic applications are worked out. Possible signals of physics beyond that model, notably in the physics of neutrinos are also discussed. Among the applications scattering on nucleons and on nuclei provide salient examples. Numerous exercises with solutions make the text suitable for advanced courses or individual study. This completely updated revised new edition contains an enlarged chapter on quantum chromodynamics an...
Modeling spatial accessibility to parks: a national study
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Lu Hua
2011-05-01
Full Text Available Abstract Background Parks provide ideal open spaces for leisure-time physical activity and important venues to promote physical activity. The spatial configuration of parks, the number of parks and their spatial distribution across neighborhood areas or local regions, represents the basic park access potential for their residential populations. A new measure of spatial access to parks, population-weighted distance (PWD to parks, combines the advantages of current park access approaches and incorporates the information processing theory and probability access surface model to more accurately quantify residential population's potential spatial access to parks. Results The PWD was constructed at the basic level of US census geography - blocks - using US park and population data. This new measure of population park accessibility was aggregated to census tract, county, state and national levels. On average, US residential populations are expected to travel 6.7 miles to access their local neighborhood parks. There are significant differences in the PWD to local parks among states. The District of Columbia and Connecticut have the best access to local neighborhood parks with PWD of 0.6 miles and 1.8 miles, respectively. Alaska, Montana, and Wyoming have the largest PWDs of 62.0, 37.4, and 32.8 miles, respectively. Rural states in the western and Midwestern US have lower neighborhood park access, while urban states have relatively higher park access. Conclusions The PWD to parks provides a consistent platform for evaluating spatial equity of park access and linking with population health outcomes. It could be an informative evaluation tool for health professionals and policy makers. This new method could be applied to quantify geographic accessibility of other types of services or destinations, such as food, alcohol, and tobacco outlets.
Vedder, Lindsey C.; Hall, Joseph M.; Jabrouin, Kimberly R.; Savage, Lisa M.
2015-01-01
Background Many alcoholics display moderate to severe cognitive dysfunction accompanied by brain pathology. A factor confounded with prolonged heavy alcohol consumption is poor nutrition and many alcoholics are thiamine deficient. Thus, thiamine deficiency (TD) has emerged as a key factor underlying alcohol–related brain damage (ARBD). TD in humans can lead to Wernicke Encephalitis that can progress into Wernicke–Korsakoff Syndrome and these disorders have a high prevalence among alcoholics. Animal models are critical for determining the exact contributions of ethanol- and TD-induced neurotoxicity, as well as the interactions of those factors to brain and cognitive dysfunction. Methods Adult rats were randomly assigned to one of six treatment conditions: Chronic ethanol treatment (CET) where rats consumed a 20% v/v solution of ethanol over 6 months; Severe pyrithiamine-induced TD (PTD-MAS); Moderate PTD (PTD-EAS); Moderate PTD followed by CET (PTD-CET); Moderate PTD during CET (CET-PTD); Pair-fed control (PF). After recovery from treatment, all rats were tested on spontaneous alternation and attentional set-shifting. After behavioral testing, brains were harvested for determination of mature brain-derived neurotrophic factor (BDNF) and thalamic pathology. Results Moderate TD combined with CET, regardless of treatment order, produced significant impairments in spatial memory, cognitive flexibility and reductions in brain plasticity as measured by BDNF levels in the frontal cortex and hippocampus. These alterations are greater than those seen in moderate TD alone and the synergistic effects of moderate TD with CET leads to a unique cognitive profile. However, CET did not exacerbate thalamic pathology seen after moderate TD. Conclusions These data support the emerging theory that subclinical TD during chronic heavy alcohol consumption is critical for the development of significant cognitive impairment associated with ARBD. PMID:26419807
Kinetic Gaussian Model with Long-Range Interactions
Institute of Scientific and Technical Information of China (English)
KONGXiang-Mu; YANGZhan-Ru
2004-01-01
In this paper dynamical critical phenomena of the Gaussian model with long-range interactions decayingas 1/rd+δ (δ>0) on d-dimensional hypercubic lattices (d = 1, 2, and 3) are studied. First, the critical points are exactly calculated, and it is found that the critical points depend on the value of δ and the range of interactions. Then the critical dynamics is considered. We calculate the time evolutions of the local magnetizations and the spin-spin correlation functions, and further the dynamic critical exponents are obtained. For one-, two- and three-dimensional lattices, it is found that the dynamic critical exponents are all z = 2 if δ > 2, which agrees with the result when only considering nearest neighboring interactions, and that they are all δ if 0 < δ < 2. It shows that the dynamic critical exponents are independent of the spatial dimensionality but depend on the value of δ.
Kinetic Gaussian Model with Long-Range Interactions
Institute of Scientific and Technical Information of China (English)
KONG Xiang-Mu; YANG Zhan-Ru
2004-01-01
In this paper dynamical critical phenomena of the Gaussian model with long-range interactions decaying as 1/rd+δ (δ＞ 0) on d-dimensional hypercubic lattices (d = 1, 2, and 3) are studied. First, the critical points are exactly calculated, and it is found that the critical points depend on the value of δ and the range of interactions. Then the critical dynamics is considered. We calculate the time evolutions of the local magnetizations and the spin-spin correlation functions, and further the dynamic critical exponents are obtained. For one-, two- and three-dimensional lattices, it is found that the dynamic critical exponents are all z = 2 if δ＞ 2, which agrees with the result when only considering nearest neighboring interactions, and that they are all δ if 0 ＜δ＜ 2. It shows that the dynamic critical exponents are independent of the spatial dimensionality but depend on the value of δ.
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
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.
Queenborough, Simon A; Burslem, David F R P; Garwood, Nancy C; Valencia, Renato
2007-09-01
Factors affecting survival and recruitment of 3531 individually mapped seedlings of Myristicaceae were examined over three years in a highly diverse neotropical rain forest, at spatial scales of 1-9 m and 25 ha. We found convincing evidence of a community compensatory trend (CCT) in seedling survival (i.e., more abundant species had higher seedling mortality at the 25-ha scale), which suggests that density-dependent mortality may contribute to the spatial dynamics of seedling recruitment. Unlike previous studies, we demonstrate that the CCT was not caused by differences in microhabitat preferences or life history strategy among the study species. In local neighborhood analyses, the spatial autocorrelation of seedling survival was important at small spatial scales (1-5 m) but decayed rapidly with increasing distance. Relative seedling height had the greatest effect on seedling survival. Conspecific seedling density had a more negative effect on survival than heterospecific seedling density and was stronger and extended farther in rare species than in common species. Taken together, the CCT and neighborhood analyses suggest that seedling mortality is coupled more strongly to the landscape-scale abundance of conspecific large trees in common species and the local density of conspecific seedlings in rare species. We conclude that negative density dependence could promote species coexistence in this rain forest community but that the scale dependence of interactions differs between rare and common species.
Fan, Zhencheng; Weng, Yitong; Chen, Guowen; Liao, Hongen
2017-07-01
Three-dimensional (3D) visualization of preoperative and intraoperative medical information becomes more and more important in minimally invasive surgery. We develop a 3D interactive surgical visualization system using mobile spatial information acquisition and autostereoscopic display for surgeons to observe surgical target intuitively. The spatial information of regions of interest (ROIs) is captured by the mobile device and transferred to a server for further image processing. Triangular patches of intraoperative data with texture are calculated with a dimension-reduced triangulation algorithm and a projection-weighted mapping algorithm. A point cloud selection-based warm-start iterative closest point (ICP) algorithm is also developed for fusion of the reconstructed 3D intraoperative image and the preoperative image. The fusion images are rendered for 3D autostereoscopic display using integral videography (IV) technology. Moreover, 3D visualization of medical image corresponding to observer's viewing direction is updated automatically using mutual information registration method. Experimental results show that the spatial position error between the IV-based 3D autostereoscopic fusion image and the actual object was 0.38±0.92mm (n=5). The system can be utilized in telemedicine, operating education, surgical planning, navigation, etc. to acquire spatial information conveniently and display surgical information intuitively. Copyright © 2017 Elsevier Inc. All rights reserved.
Spatial audition in a static virtual environment: the role of auditory-visual interaction
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Isabelle Viaud-Delmon
2009-04-01
Full Text Available The integration of the auditory modality in virtual reality environments is known to promote the sensations of immersion and presence. However it is also known from psychophysics studies that auditory-visual interaction obey to complex rules and that multisensory conflicts may disrupt the adhesion of the participant to the presented virtual scene. It is thus important to measure the accuracy of the auditory spatial cues reproduced by the auditory display and their consistency with the spatial visual cues. This study evaluates auditory localization performances under various unimodal and auditory-visual bimodal conditions in a virtual reality (VR setup using a stereoscopic display and binaural reproduction over headphones in static conditions. The auditory localization performances observed in the present study are in line with those reported in real conditions, suggesting that VR gives rise to consistent auditory and visual spatial cues. These results validate the use of VR for future psychophysics experiments with auditory and visual stimuli. They also emphasize the importance of a spatially accurate auditory and visual rendering for VR setups.
Spatial Model of Deforestation in Sumatra Islands Using Typological Approach
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Nurdin Sulistiyono
2015-12-01
Full Text Available High rate of deforestation occurred in Sumatra Islands had been allegedly triggered by various factors. This study examined how the deforestation pattern was related to the typology of the area, as well as how the deforestation is being affected by many factors such as physical, biological, and socio-economic of the local community. The objective of this study was to formulate a spatial model of deforestation based on triggering factors within each typology in Sumatra Islands. The typology classes were developed on the basis of socio-economic factors using the standardized-euclidean distance measure and the memberships of each cluster was determined using the furthest neighbor method. The logistic regression method was used for modeling and estimating the spatial distribution of deforestation.Two deforestation typologies were distinguished in this study, namely typology 1 (regencies/cities with low deforestation rate and typology 2 (regencies/cities with high deforestation rate. The study found that growth rate of farm households could be used to assign each regencies or cities in Sumatra Islands into their corresponding typology. The resulted spatial model of deforestation from logistic regression analysis were logit (deforestation = 1.355 + (0.012*total of farm households – (0.08*elevation – (0.019*distance from road for typology 1 and logit (deforestation = 1.714 + (0.007*total of farm households – (0.021*slope – (0.051*elevation – (0.038* distance from road + (0.039* distance from river for typology 2, respectively. The accuracy test of deforestation model in 2000–2006 showed overall accuracy of 68.52% (typology 1 and 74.49% (typology 2, while model of deforestation in 2006–2012 showed overall accuracy of 65.37% (typology 1 and 72.24% (typology 2, respectively.
Transient,spatially-varied recharge for groundwater modeling
Assefa, Kibreab; Woodbury, Allan
2013-04-01
This study is aimed at producing spatially and temporally varying groundwater recharge for transient groundwater modeling in a pilot watershed in the North Okanagan, Canada. The recharge modeling is undertaken by using a Richard's equation based finite element code (HYDRUS-1D) [Simunek et al., 2002], ArcGISTM [ESRI, 2011], ROSETTA [Schaap et al., 2001], in situ observations of soil temperature and soil moisture and a long term gridded climate data [Nielsen et al., 2010]. The public version of HYDUS-1D [Simunek et al., 2002] and another beta version with a detailed freezing and thawing module [Hansson et al., 2004] are first used to simulate soil temperature, snow pack and soil moisture over a one year experimental period. Statistical analysis of the results show both versions of HYDRUS-1D reproduce observed variables to the same degree. Correlation coefficients for soil temperature simulation were estimated at 0.9 and 0.8, at depths of 10 cm and 50 cm respectively; and for soil moisture, 0.8 and 0.6 at 10 cm and 50 cm respectively. This and other standard measures of model performance (root mean square error and average error) showed a promising performance of the HYDRUS-1D code in our pilot watershed. After evaluating model performance using field data and ROSETTA derived soil hydraulic parameters, the HYDRUS-1D code is coupled with ArcGISTM to produce spatially and temporally varying recharge maps throughout the Deep Creek watershed. Temporal and spatial analysis of 25 years daily recharge results at various representative points across the study watershed reveal significant temporal and spatial variations; average recharge estimated at 77.8 ± 50.8mm /year. This significant variation over the years, caused by antecedent soil moisture condition and climatic condition, illustrates the common flaw of assigning a constant percentage of precipitation throughout the simulation period. Groundwater recharge modeling has previously been attempted in the Okanagan Basin
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
Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore
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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.
Supermodel - Interactive Ensemble of Low-dimensional Models
Basnarkov, Lasko; Duane, Gregory; Kocarev, Ljupco
2013-04-01
The accuracy of numerical weather prediction is steadily increasing due to the advances in different scientific disciplines. One of them aims at understanding the physics that underlies the atmospheric dynamics. Although the basic laws are well known there is large room for improvement in modeling various small scale processes. Currently they are generally parametrized and thus we are facing dozens of atmospheric models that are used in different meteorological centers around the world. The models are based on the same fluid dynamics laws, but generally differ in spatial resolution, parametrisation of the unresolved processes and also in the corresponding parameter values. Another key factor that contributes to the prediction improvement is the increase of the available computational power. As one consequence the grid resolution is getting smaller. As another, the contemporary numerical weather prediction schemes consider combinations of the outputs of the ensembles of models -- different perturbations of the same model or even different models. Considering interactive ensembles- with dynamical exchange of information between models that run simultaneously-is a novel approach toward improving the weather forecast or climate projection. Although flux exchange between different ocean and atmospheric models has some history, coupling different atmospheric models is rather new. The coupling schemes can be different and the first approaches are those that combine corresponding dynamical variables or tendency components. In this work we present an example with an artificial toy model- the Lorenz 96 model-that shares some properties with the atmosphere. As reality (the atmosphere) we consider one Lorenz 96 class III system, while as its imperfect models are taken three class II systems that have different forcing terms. The interactive ensemble has tendencies that are weighted combinations of the individual models' tendencies. The weights are obtained with statistical
Spatial Impairment and Memory in Genetic Disorders: Insights from Mouse Models
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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 Impairment and Memory in Genetic Disorders: Insights from Mouse Models
Lee, Sang Ah; Tucci, Valter; Vallortigara, Giorgio
2017-01-01
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. PMID:28208764
Mean field analysis of a spatial stochastic model of a gene regulatory network.
Sturrock, M; Murray, P J; Matzavinos, A; Chaplain, M A J
2015-10-01
A gene regulatory network may be defined as a collection of DNA segments which interact with each other indirectly through their RNA and protein products. Such a network is said to contain a negative feedback loop if its products inhibit gene transcription, and a positive feedback loop if a gene product promotes its own production. Negative feedback loops can create oscillations in mRNA and protein levels while positive feedback loops are primarily responsible for signal amplification. It is often the case in real biological systems that both negative and positive feedback loops operate in parameter regimes that result in low copy numbers of gene products. In this paper we investigate the spatio-temporal dynamics of a single feedback loop in a eukaryotic cell. We first develop a simplified spatial stochastic model of a canonical feedback system (either positive or negative). Using a Gillespie's algorithm, we compute sample trajectories and analyse their corresponding statistics. We then derive a system of equations that describe the spatio-temporal evolution of the stochastic means. Subsequently, we examine the spatially homogeneous case and compare the results of numerical simulations with the spatially explicit case. Finally, using a combination of steady-state analysis and data clustering techniques, we explore model behaviour across a subregion of the parameter space that is difficult to access experimentally and compare the parameter landscape of our spatio-temporal and spatially-homogeneous models.
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...
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)
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...
Joint Modeling of Multiple Crimes: A Bayesian Spatial Approach
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Hongqiang Liu
2017-01-01
Full Text Available A multivariate Bayesian spatial modeling approach was used to jointly model the counts of two types of crime, i.e., burglary and non-motor vehicle theft, and explore the geographic pattern of crime risks and relevant risk factors. In contrast to the univariate model, which assumes independence across outcomes, the multivariate approach takes into account potential correlations between crimes. Six independent variables are included in the model as potential risk factors. In order to fully present this method, both the multivariate model and its univariate counterpart are examined. We fitted the two models to the data and assessed them using the deviance information criterion. A comparison of the results from the two models indicates that the multivariate model was superior to the univariate model. Our results show that population density and bar density are clearly associated with both burglary and non-motor vehicle theft risks and indicate a close relationship between these two types of crime. The posterior means and 2.5% percentile of type-specific crime risks estimated by the multivariate model were mapped to uncover the geographic patterns. The implications, limitations and future work of the study are discussed in the concluding section.
Interacting Dark Energy Models -- Scalar Linear Perturbations
Perico, E L D
2016-01-01
We extend the dark sector interacting models assuming the dark energy as the sum of independent contributions $\\rho_{\\Lambda} =\\sum_i\\rho_{\\Lambda i}$, associated with (and interacting with) each of the $i$ material species. We derive the linear scalar perturbations for two interacting dark energy scenarios, modeling its cosmic evolution and identifying their different imprints in the CMB and matter power spectrum. Our treatment was carried out for two phenomenological motivated expressions of the dark energy density, $\\rho_\\Lambda(H^2)$ and $\\rho_\\Lambda(R)$. The $\\rho_\\Lambda(H^2)$ description turned out to be a full interacting model, i.e., the dark energy interacts with everyone material species in the universe, whereas the $\\rho_\\Lambda(R)$ description only leads to interactions between dark energy and the non-relativistic matter components; which produces different imprints of the two models on the matter power spectrum. A comparison with the Planck 2015 data was made in order to constrain the free para...
Directory of Open Access Journals (Sweden)
Simone Becker Lopes
2014-04-01
Full Text Available Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included. This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.
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
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
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.
Stochastic Local Interaction (SLI) model: Bridging machine learning and geostatistics
Hristopulos, Dionissios T.
2015-12-01
Machine learning and geostatistics are powerful mathematical frameworks for modeling spatial data. Both approaches, however, suffer from poor scaling of the required computational resources for large data applications. We present the Stochastic Local Interaction (SLI) model, which employs a local representation to improve computational efficiency. SLI combines geostatistics and machine learning with ideas from statistical physics and computational geometry. It is based on a joint probability density function defined by an energy functional which involves local interactions implemented by means of kernel functions with adaptive local kernel bandwidths. SLI is expressed in terms of an explicit, typically sparse, precision (inverse covariance) matrix. This representation leads to a semi-analytical expression for interpolation (prediction), which is valid in any number of dimensions and avoids the computationally costly covariance matrix inversion.
Linear systems modeling of adaptive optics in the spatial-frequency domain.
Ellerbroek, Brent L
2005-02-01
Spatial-frequency domain techniques have traditionally been applied to obtain estimates for the independent effects of a variety of individual error sources in adaptive optics (AO). Overall system performance is sometimes estimated by introducing the approximation that these individual error terms are statistically independent, so that their magnitudes may be summed in quadrature. More accurate evaluation methods that account for the correlations between the individual error sources have required Monte Carlo simulations or large matrix calculations that can take much longer to compute, particularly as the order of the AO system increases beyond a few hundred degrees of freedom. We describe an approach to evaluating AO system performance in the spatial-frequency domain that is relatively computationally efficient but still accounts for many of the interactions between the fundamental error sources in AO. We exploit the fact that (in the limits of an infinite aperture and geometrical optics) all the basic wave-front propagation, sensing, and correction processes that describe the behavior of an AO system are spatial-filtering operations in the Fourier domain. Essentially all classical wave-front control algorithms and evaluation formulas are expressed in terms of these filters and may therefore be evaluated one spatial-frequency component at a time. Performance estimates for very-high-order AO systems may be obtained in 1 to 2 orders of magnitude less time than needed when detailed simulations or analytical models in the spatial domain are used, with a relative discrepancy of 5% to 10% for typical sample problems.
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.
Modelling earthquake interaction and seismicity statistics
Steacy, S.; Hetherington, A.
2009-04-01
The effects of earthquake interaction and fault complexity on seismicity statistics are investigated in a 3D model composed of a number of cellular automata (each representing an individual fault) distributed in a volume. Each automaton is assigned a fractal distribution of strength. Failure occurs when the 3D Coulomb stress on any cell exceeds its strength and stress transfer during simulated earthquake rupture is via nearest-neighbor rules formulated to give realistic stress concentrations. An event continues until all neighboring cells whose stresses exceed their strengths have ruptured and the size of the event is determined from its area and stress drop. Long-range stress interactions are computed following the termination of simulated ruptures using a boundary element code. In practice, these stress perturbations are only computed for events above a certain size (e.g. a threshold length of 10 km) and stresses are updated on nearby structures. Events which occur as a result of these stress interactions are considered to be "triggered" earthquakes and they, in turn, can trigger further seismic activity. The threshold length for computing interaction stresses is a free parameter and hence interaction can be "turned off" by setting this to an unrealistically high value. We consider 3 synthetic fault networks of increasing degrees of complexity - modelled on the North Anatolian fault system, the structures in the San Francisco Bay Area, and the Southern California fault network. We find that the effect of interaction is dramatically different in networks of differing complexity. In the North Anatolian analogue, for example, interaction leads to a decreased number of events, increased b-values, and an increase in recurrence intervals. In the Bay Area model, by contrast, we observe that interaction increases the number of events, decreases the b-values, and has little effect on recurrence intervals. For all networks, we find that interaction can activate mis
Parrish, Robert M; Sherrill, C David
2014-07-28
We develop a physically-motivated assignment of symmetry adapted perturbation theory for intermolecular interactions (SAPT) into atom-pairwise contributions (the A-SAPT partition). The basic precept of A-SAPT is that the many-body interaction energy components are computed normally under the formalism of SAPT, following which a spatially-localized two-body quasiparticle interaction is extracted from the many-body interaction terms. For electrostatics and induction source terms, the relevant quasiparticles are atoms, which are obtained in this work through the iterative stockholder analysis (ISA) procedure. For the exchange, induction response, and dispersion terms, the relevant quasiparticles are local occupied orbitals, which are obtained in this work through the Pipek-Mezey procedure. The local orbital atomic charges obtained from ISA additionally allow the terms involving local orbitals to be assigned in an atom-pairwise manner. Further summation over the atoms of one or the other monomer allows for a chemically intuitive visualization of the contribution of each atom and interaction component to the overall noncovalent interaction strength. Herein, we present the intuitive development and mathematical form for A-SAPT applied in the SAPT0 approximation (the A-SAPT0 partition). We also provide an efficient series of algorithms for the computation of the A-SAPT0 partition with essentially the same computational cost as the corresponding SAPT0 decomposition. We probe the sensitivity of the A-SAPT0 partition to the ISA grid and convergence parameter, orbital localization metric, and induction coupling treatment, and recommend a set of practical choices which closes the definition of the A-SAPT0 partition. We demonstrate the utility and computational tractability of the A-SAPT0 partition in the context of side-on cation-π interactions and the intercalation of DNA by proflavine. A-SAPT0 clearly shows the key processes in these complicated noncovalent interactions, in
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.
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...... then successfully applied to activity recognition, activity simulation and multi-target tracking. Our method compares favourably with respect to previously reported results using Hidden Markov Models and Relational Particle Filtering....
3D Kidney Segmentation from Abdominal Images Using Spatial-Appearance Models
Khalifa, Fahmi; Soliman, Ahmed; Gimel'farb, Georgy
2017-01-01
Kidney segmentation is an essential step in developing any noninvasive computer-assisted diagnostic system for renal function assessment. This paper introduces an automated framework for 3D kidney segmentation from dynamic computed tomography (CT) images that integrates discriminative features from the current and prior CT appearances into a random forest classification approach. To account for CT images' inhomogeneities, we employ discriminate features that are extracted from a higher-order spatial model and an adaptive shape model in addition to the first-order CT appearance. To model the interactions between CT data voxels, we employed a higher-order spatial model, which adds the triple and quad clique families to the traditional pairwise clique family. The kidney shape prior model is built using a set of training CT data and is updated during segmentation using not only region labels but also voxels' appearances in neighboring spatial voxel locations. Our framework performance has been evaluated on in vivo dynamic CT data collected from 20 subjects and comprises multiple 3D scans acquired before and after contrast medium administration. Quantitative evaluation between manually and automatically segmented kidney contours using Dice similarity, percentage volume differences, and 95th-percentile bidirectional Hausdorff distances confirms the high accuracy of our approach.
DEFF Research Database (Denmark)
Bardram, Jakob; Hansen, Thomas Riisgaard; Søgaard, Mads
2006-01-01
coordinate highly cooperative work in such a critical setting. In this paper we propose a novel way of supporting coordination in this hectic and time-critical environment. AwareMedia is a system which promotes social, spatial, and temporal awareness in combination with a shared messaging system. AwareMedia...... runs on large interactive displays situated around the hospital, and it is designed especially to support coordination at an operation ward. We present the design, implementation, and deployment of AwareMedia and based on preliminary data from our on-going deployment, we discuss how AwareMedia...
Arkhipov, R. M.; Arkhipov, M. V.; Pakhomov, A. V.; Babushkin, I.; Rosanov, N. N.
2017-09-01
Recently, the possibility of the creation, erasing and ultrafast control of polarization and population inversion gratings by sequences of few-cycle bipolar pulses interacting with a medium in a resonant and coherent way was predicted. In this case, the overlapping of pulses in the medium is not needed for the creation of gratings. In this paper, we study the possibility of the ultrafast creation and control of spatial periodic gratings in a resonant medium when subcycle unipolar pulses (that is ones containing the constant spectral component of an electric field) propagate in the coherent regime.
Streched String with Self-Interaction at the Hagedorn Point: Spatial Sizes and Black Hole
Qian, Yachao
2015-01-01
We analyze the length, mass and spatial distribution of a discretized transverse string in $D_\\perp$ dimensions with fixed end-points near its Hagedorn temperature. We suggest that such a string may dominate the (holographic) Pomeron kinematics for dipole-dipole scattering at intermediate and small impact parameters. Attractive self-string interactions cause the transverse string size to contract away from its diffusive size, a mechanism reminiscent of the string-black-hole transmutation. The string shows sizable asymmetries in the transverse plane that translate to primordial azimuthal asymmetries in the stringy particle production in the Pomeron kinematics for current pp and pA collisions at collider energies.
DEFF Research Database (Denmark)
Bardram, Jakob; Hansen, Thomas Riisgaard; Søgaard, Mads
2006-01-01
coordinate highly cooperative work in such a critical setting. In this paper we propose a novel way of supporting coordination in this hectic and time-critical environment. AwareMedia is a system which promotes social, spatial, and temporal awareness in combination with a shared messaging system. AwareMedia...... runs on large interactive displays situated around the hospital, and it is designed especially to support coordination at an operation ward. We present the design, implementation, and deployment of AwareMedia and based on preliminary data from our on-going deployment, we discuss how AwareMedia...
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
Anderson, Douglas J.; Kobryn, Halina T.; Norman, Brad M.; Bejder, Lars; Tyne, Julian A.; Loneragan, Neil R.
2014-07-01
As with other nature-based tourism ventures, whale shark tourism is expanding rapidly worldwide, which highlights the need to understand more about the nature of these activities. Records of interactions between tour operators and whale sharks at Ningaloo Reef, Western Australia (22.5°S, 113.5°E) were obtained from the Western Australian Department of Parks and Wildlife from 2006 to 2010 and evaluated to determine the scale of the tourism operations and the spatial and temporal distribution of interactions. The number of whale shark tours at Ningaloo increased by approx. 70% (520-886 tours per year) and the number of interactions with whale sharks by 370% between 2006 (694) and 2010 (3254). The locations of whale shark interactions recorded in logbooks (2006-2009) and electronic monitoring systems (2009 and 2010) were used to plot the smoothed densities of tour operator interactions with whale sharks. Generalised linear models were used to investigate how the presence/absence and number of whale shark interactions at North and South Ningaloo were influenced by the distance to the reef crest, the distance to passages and their interaction terms for the aggregated five-year data set. Over the five years, distance to the reef crest was the best predictor of the presence/absence of whale shark interactions at both North (interactions concentrated within 3 km of the reef crest) and South Ningaloo (interactions within 6 km of the reef crest) followed by distance to passages. The reef passages are very significant areas for tourism interactions with whale sharks at Ningaloo. The distribution of interactions at North and South Ningaloo varied from year to year, particularly in the strong La Niña year of 2010, when average sea surface temperatures remained above 24 °C and whale sharks were observed much later in the year than previously (late August). This study demonstrates the value of the data collected by the tour operators at Ningaloo Reef and managed by a
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 model for transmission of mosquito-borne diseases
Kon, Cynthia Mui Lian; Labadin, Jane
2015-05-01
In this paper, a generic model which takes into account spatial heterogeneity for the dynamics of mosquito-borne diseases is proposed. The dissemination of the disease is described by a system of reaction-diffusion partial differential equations. Host human and vector mosquito populations are divided into susceptible and infectious classes. Diffusion is considered to occur in all classes of both populations. Susceptible humans are infected when bitten by infectious mosquitoes. Susceptible mosquitoes bite infectious humans and become infected. The biting rate of mosquitoes is considered to be density dependent on the total human population in different locations. The system is solved numerically and results are shown.
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.
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
Tague, C.
2007-12-01
One of the primary roles of modeling in critical zone research studies is to provide a framework for integrating field measurements and theory and for generalizing results across space and time. In the Southern Sierra Critical Zone Observatory (SCZO), significant spatial heterogeneity associated with mountainous terrain combined with high inter-annual and seasonal variation in climate, necessitates the use of spatial-temporal models for generating landscape scale understanding and predictions. Science questions related to coupled hydrologic and biogeochemical fluxes within the critical zone require a framework that can account for multiple and interacting processes. One of the core tools for the SCZO will be RHESSYs (Regional hydro-ecologic simulation system). RHESSys is an existing GIS-based model of hydrology and biogeochemical cycling. For the SCZO, we use RHESSys as an open-source, objected oriented model that can be extended to incorporate findings from field-based monitoring and analysis. We use the model as a framework for data assimilation, spatial-temporal interpolation, prediction, and scenario and hypothesis generation. Here we demonstrate the use of RHESSys as a hypothesis generation tool. We show how initial RHESSys predictions can be used to estimate when and where connectivity within the critical zone will lead to significant spatial or temporal gradients in vegetation carbon and moisture fluxes. We use the model to explore the potential implications of heterogeneity in critical zone controls on hydrologic processes at two scales: micro and macro. At the micro scale, we examine the role of preferential flowpaths. At the macro scale we consider the importance of upland-riparian zone connectivity. We show how the model can be used to design efficient field experiments by, a-priori providing quantitative estimate of uncertainty and highlighting when and where measurements might most effectively reduce that uncertainty.
SOFTWARE RELIABILITY MODEL FOR COMPONENT INTERACTION MODE
Institute of Scientific and Technical Information of China (English)
Wang Qiang; Lu Yang; Xu Zijun; Han Jianghong
2011-01-01
With the rapid progress of component technology,the software development methodology of gathering a large number of components for designing complex software systems has matured.But,how to assess the application reliability accurately with the information of system architecture and the components reliabilities together has become a knotty problem.In this paper,the defects in formal description of software architecture and the limitations in existed model assumptions are both analyzed.Moreover,a new software reliability model called Component Interaction Mode (CIM) is proposed.With this model,the problem for existed component-based software reliability analysis models that cannot deal with the cases of component interaction with non-failure independent and non-random control transition is resolved.At last,the practice examples are presented to illustrate the effectiveness of this model
The limits of splitting: a framework to test model spatial distribution
Lobligeois, F.; Andréassian, V.; Perrin, C.; Loumagne, C.
2012-04-01
When it comes to deciding of the necessary spatial representation of a catchment, hydrologists need to choose between spatially lumped and spatially distributed approaches. This decision is not trivial: on the one hand, lumped models have proved both efficient and robust over the years (moreover their relatively low number of parameters limits the numerical problems such as secondary optima, parameter interaction, poor sensitivity); on the other hand many hydrologists believe that distributed models could potentially have a greater ability to take into account the spatial heterogeneity of both rainfall and land surface. Few attempts have been made to test rigorously alternative distributed schemes (see the discussion of semi-lumped and semi-distributed alternatives in Andréassian et al. (2004)). The purpose of our work was to identify whether an optimum level of spatialisation exists: to investigate "the limits of splitting" (Beven, 1996). We propose a framework to evaluate the effect of the distribution over a large set of 181 French catchments, using a newly available high resolution rainfall product of Météo France, combining radar data and raingage measurements. Five grid sizes are studied, as catchments are splitted into 1, 2, 4, 8 and 16 sub-catchments and streamflow simulation results are analysed in validation mode. For each type of basin, we study the trend of model efficiency with the number of sub-catchments. We find paradoxical results: while some catchments clearly benefit from the distribution, others show opposite trends. The large variability between basins underlines the necessity to have enough case studies to reach a robust conclusion. Andréassian, V. et al., 2004. Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: a theoretical study using chimera watersheds. Water Resour. Res., 40(5): W05209, doi: 10.1029/2003WR002854. Beven, K., 1996. The limits of splitting: hydrology. The Science of the
Spatial learning and action planning in a prefrontal cortical network model.
Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo
2011-05-01
The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive "insight" capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates.
Spatial learning and action planning in a prefrontal cortical network model.
Directory of Open Access Journals (Sweden)
Louis-Emmanuel Martinet
2011-05-01
Full Text Available The interplay between hippocampus and prefrontal cortex (PFC is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive "insight" capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates.
A Spatial Clustering Approach for Stochastic Fracture Network Modelling
Seifollahi, S.; Dowd, P. A.; Xu, C.; Fadakar, A. Y.
2014-07-01
Fracture network modelling plays an important role in many application areas in which the behaviour of a rock mass is of interest. These areas include mining, civil, petroleum, water and environmental engineering and geothermal systems modelling. The aim is to model the fractured rock to assess fluid flow or the stability of rock blocks. One important step in fracture network modelling is to estimate the number of fractures and the properties of individual fractures such as their size and orientation. Due to the lack of data and the complexity of the problem, there are significant uncertainties associated with fracture network modelling in practice. Our primary interest is the modelling of fracture networks in geothermal systems and, in this paper, we propose a general stochastic approach to fracture network modelling for this application. We focus on using the seismic point cloud detected during the fracture stimulation of a hot dry rock reservoir to create an enhanced geothermal system; these seismic points are the conditioning data in the modelling process. The seismic points can be used to estimate the geographical extent of the reservoir, the amount of fracturing and the detailed geometries of fractures within the reservoir. The objective is to determine a fracture model from the conditioning data by minimizing the sum of the distances of the points from the fitted fracture model. Fractures are represented as line segments connecting two points in two-dimensional applications or as ellipses in three-dimensional (3D) cases. The novelty of our model is twofold: (1) it comprises a comprehensive fracture modification scheme based on simulated annealing and (2) it introduces new spatial approaches, a goodness-of-fit measure for the fitted fracture model, a measure for fracture similarity and a clustering technique for proposing a locally optimal solution for fracture parameters. We use a simulated dataset to demonstrate the application of the proposed approach
Spatial transferability of landscape-based hydrological models
Gao, Hongkai; Hrachowitz, Markus; Fenicia, Fabrizio; Gharari, Shervan; Sriwongsitanon, Nutchanart; Savenije, Hubert
2015-04-01
Landscapes, mainly distinguished by land surface topography and vegetation cover, are crucial in defining runoff generation mechanisms, interception capacity and transpiration processes. Landscapes information provides modelers with a way to take into account catchment heterogeneity, while simultaneously keeping model complexity low. A landscape-based hydrological modelling framework (FLEX-Topo), with parallel model structures, was developed and tested in various catchments with diverse climate, topography and land cover conditions. Landscape classification is the basic and most crucial procedure to create a tailor-made model for a certain catchment, as it explicitly relates hydrologic similarity to landscape similarity, which is the base of this type of models. Therefore, the study catchment is classified into different landscapes units that fulfil similar hydrological function, based on classification criteria such as the height above the nearest drainage, slope, aspect and land cover. At present, to suggested model includes four distinguishable landscapes: hillslopes, terraces/plateaus, riparian areas, and glacierized areas. Different parallel model structures are then associated with the different landscape units to describe their different dominant runoff generation mechanisms. These hydrological units are parallel and only connected by groundwater reservoir. The transferability of this landscape-based model can then be compared with the transferability of a lumped model. In this study, FLEX-Topo was developed and tested in three study sites: two cold-arid catchments in China (the upper Heihe River and the Urumqi Glacier No1 catchment), and one tropical catchment in Thailand (the upper Ping River). Stringent model tests indicate that FLEX-Topo, allowing for more process heterogeneity than lumped model formulations, exhibits higher capabilities to be spatially transferred. Furthermore, the simulated water balances, including internal fluxes, hydrograph
Identifying and modeling the structural discontinuities of human interactions
Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo
2017-04-01
The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.
Interaction between Two-Dimensional White-Light Photovoltaic Dark Spatial Solitons
Institute of Scientific and Technical Information of China (English)
LIU Zhao-Hong; LIU Si-Min; GUO Ru; GAO Yuan-Mei; SONG Tao; ZHU Nan; QU Di
2007-01-01
Using fully incoherent white light emitted from an incandescent bulb (a line source) and amplitude mask, we study experimentally the interaction between two 2D white-light photovoltaic dark spatial solitons with three different separations (40 μm, 50 μm and 60 μm) and arrangement directions (parallel to, perpendicular to and tilted at 45° with respect to the crystalline c axis) propagating in parallel in close proximity in self-defocusing LiNbO3:Fe crystal. Experimental results reveal that a 2D white-light dark soliton pair only experiences attractive forces when their mutual separation is sufficiently small (＜ 60 μm), and the degree of the attraction depends on their mutual separation and their arrangement direction. When the separation is larger than 60 μm, the interaction is not evident.
How spatial is hyperspace? Interacting with hypertext documents: cognitive processes and concepts.
Boechler, P M
2001-02-01
The World Wide Web provides us with a widely accessible technology, fast access to massive amounts of information and services, and the opportunity for personal interaction with numerous individuals simultaneously. Underlying and influencing all of these activities is our basic conceptualization of this new environment; an environment we can view as having a cognitive component (hyperspace) and a social component (cyberspace). This review argues that cognitive psychologists have a key role to play in the identification and analysis of how the processes of the mind interact with the Web. The body of literature on cognitive processes provides us with knowledge about spatial perceptions, strategies for navigation in space, memory functions and limitations, and the formation of mental representations of environments. Researchers of human cognition can offer established methodologies and conceptual frameworks toward investigation of the cognitions involved in the use of electronic environments like the Web.
A Heuristic Molecular Model of Hydrophobic Interactions
Hummer, G; García, A E; Pohorille, A; Pratt, L R
1995-01-01
Hydrophobic interactions provide driving forces for protein folding, membrane formation, and oil-water separation. Motivated by information theory, the poorly understood nonpolar solute interactions in water are investigated. A simple heuristic model of hydrophobic effects in terms of density fluctuations is developed. This model accounts quantitatively for the central hydrophobic phenomena of cavity formation and association of inert gas solutes; it therefore clarifies the underlying physics of hydrophobic effects and permits important applications to conformational equilibria of nonpolar solutes and hydrophobic residues in biopolymers.
The standard model of electroweak interactions
Pich, Antonio
1994-01-01
What follows is an updated version of the lectures given at the CERN Academic Training (November 1993) and at the Jaca Winter Meeting (February 1994). The aim is to provide a pedagogical introduction to the Standard Model of electroweak interactions. After briefly reviewing the empirical considerations which lead to the construction of the Standard Model Lagrangian, the particle content, structure and symmetries of the theory are discussed. Special emphasis is given to the many phenomenological tests (universality, flavour-changing neutral currents, precision measurements, quark mixing, etc.) which have established this theoretical framework as the Standard Theory of electroweak interactions.
Spatial air pollution modelling for a West-African town
Directory of Open Access Journals (Sweden)
Sirak Zenebe Gebreab
2015-11-01
Full Text Available Land use regression (LUR modelling is a common approach used in European and Northern American epidemiological studies to assess urban and traffic related air pollution exposures. Studies applying LUR in Africa are lacking. A need exists to understand if this approach holds for an African setting, where urban features, pollutant exposures and data availability differ considerably from other continents. We developed a parsimonious regression model based on 48-hour nitrogen dioxide (NO2 concentrations measured at 40 sites in Kaédi, a medium sized West-African town, and variables generated in a geographic information system (GIS. Road variables and settlement land use characteristics were found to be important predictors of 48-hour NO2 concentration in the model. About 68% of concentration variability in the town was explained by the model. The model was internally validated by leave-one-out cross-validation and it was found to perform moderately well. Furthermore, its parameters were robust to sampling variation. We applied the model at 100 m pixels to create a map describing the broad spatial pattern of NO2 across Kaédi. In this research, we demonstrated the potential for LUR as a valid, cost-effective approach for air pollution modelling and mapping in an African town. If the methodology were to be adopted by environmental and public health authorities in these regions, it could provide a quick assessment of the local air pollution burden and potentially support air pollution policies and guidelines.
Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations.
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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
Naimi, B.; Skidmore, A.K.; Groen, T.A.; Hamm, N.A.S.
2011-01-01
Aim To investigate the impact of positional uncertainty in species occurrences on the predictions of seven commonly used species distribution models (SDMs), and explore its interaction with spatial autocorrelation in predictors. Methods A series of artificial datasets covering 155 scenarios includin
Global Quantitative Modeling of Chromatin Factor Interactions
Zhou, Jian; Troyanskaya, Olga G.
2014-01-01
Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896
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...
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Léa Harvey
Full Text Available Spatial heterogeneity in the strength of trophic interactions is a fundamental property of food web spatial dynamics. The feeding effort of herbivores should reflect adaptive decisions that only become rewarding when foraging gains exceed 1 the metabolic costs, 2 the missed opportunity costs of not foraging elsewhere, and 3 the foraging costs of anti-predator behaviour. Two aspects of these costs remain largely unexplored: the link between the strength of plant-herbivore interactions and the spatial scale of food-quality assessment, and the predator-prey spatial game. We modeled the foraging effort of free-ranging plains bison (Bison bison bison in winter, within a mosaic of discrete meadows. Spatial patterns of bison herbivory were largely driven by a search for high net energy gains and, to a lesser degree, by the spatial game with grey wolves (Canis lupus. Bison decreased local feeding effort with increasing metabolic and missed opportunity costs. Bison herbivory was most consistent with a broad-scale assessment of food patch quality, i.e., bison grazed more intensively in patches with a low missed opportunity cost relative to other patches available in the landscape. Bison and wolves had a higher probability of using the same meadows than expected randomly. This co-occurrence indicates wolves are ahead in the spatial game they play with bison. Wolves influenced bison foraging at fine scale, as bison tended to consume less biomass at each feeding station when in meadows where the risk of a wolf's arrival was relatively high. Also, bison left more high-quality vegetation in large than small meadows. This behavior does not maximize their energy intake rate, but is consistent with bison playing a shell game with wolves. Our assessment of bison foraging in a natural setting clarifies the complex nature of plant-herbivore interactions under predation risk, and reveals how spatial patterns in herbivory emerge from multi-scale landscape
Harvey, Léa; Fortin, Daniel
2013-01-01
Spatial heterogeneity in the strength of trophic interactions is a fundamental property of food web spatial dynamics. The feeding effort of herbivores should reflect adaptive decisions that only become rewarding when foraging gains exceed 1) the metabolic costs, 2) the missed opportunity costs of not foraging elsewhere, and 3) the foraging costs of anti-predator behaviour. Two aspects of these costs remain largely unexplored: the link between the strength of plant-herbivore interactions and the spatial scale of food-quality assessment, and the predator-prey spatial game. We modeled the foraging effort of free-ranging plains bison (Bison bison bison) in winter, within a mosaic of discrete meadows. Spatial patterns of bison herbivory were largely driven by a search for high net energy gains and, to a lesser degree, by the spatial game with grey wolves (Canis lupus). Bison decreased local feeding effort with increasing metabolic and missed opportunity costs. Bison herbivory was most consistent with a broad-scale assessment of food patch quality, i.e., bison grazed more intensively in patches with a low missed opportunity cost relative to other patches available in the landscape. Bison and wolves had a higher probability of using the same meadows than expected randomly. This co-occurrence indicates wolves are ahead in the spatial game they play with bison. Wolves influenced bison foraging at fine scale, as bison tended to consume less biomass at each feeding station when in meadows where the risk of a wolf's arrival was relatively high. Also, bison left more high-quality vegetation in large than small meadows. This behavior does not maximize their energy intake rate, but is consistent with bison playing a shell game with wolves. Our assessment of bison foraging in a natural setting clarifies the complex nature of plant-herbivore interactions under predation risk, and reveals how spatial patterns in herbivory emerge from multi-scale landscape heterogeneity.
Spatial Modeling in The Coastal Area of East Java Province
Fadlilah Kurniawati, Ummi
2017-07-01
The existence of gaps that occur between regions, shows that it is a reasonable process considering that each region has different initial endowment factors. The first step that can be done to controll disparity is know what is the benchmark of the gap. The revenue growth indicator is one of benchmark for measuring regional disparities. The regional output is represented by the gross domestic regional income per capita. Concerning the phenomenon of regional disparity, East Java Province is concentrated in the north-south part, especially in coastal areas is an early indication of the gap. This is what prompted the analysis of predictor factors affecting the disparity in East Java Coastal Areas through a spatial modeling approach. Spatial modeling is done on the consideration that there are different local characteristics or potentials in each regency / city. Factors Economic growth, social factors, and physical development factors are the main factors in this study will be described in derived variables to obtain a clear picture of the influence of each factor to the disparity that occurred in the Coastal Region of East Java Province.
Spatial Model of Sky Brightness Magnitude in Langkawi Island, Malaysia
Redzuan Tahar, Mohammad; Kamarudin, Farahana; Umar, Roslan; Khairul Amri Kamarudin, Mohd; Hazmin Sabri, Nor; Ahmad, Karzaman; Rahim, Sobri Abdul; Sharul Aikal Baharim, Mohd
2017-03-01
Sky brightness is an essential topic in the field of astronomy, especially for optical astronomical observations that need very clear and dark sky conditions. This study presents the spatial model of sky brightness magnitude in Langkawi Island, Malaysia. Two types of Sky Quality Meter (SQM) manufactured by Unihedron are used to measure the sky brightness on a moonless night (or when the Moon is below the horizon), when the sky is cloudless and the locations are at least 100 m from the nearest light source. The selected locations are marked by their GPS coordinates. The sky brightness data obtained in this study were interpolated and analyzed using a Geographic Information System (GIS), thus producing a spatial model of sky brightness that clearly shows the dark and bright sky areas in Langkawi Island. Surprisingly, our results show the existence of a few dark sites nearby areas of high human activity. The sky brightness of 21.45 mag arcsec{}-2 in the Johnson-Cousins V-band, as the average of sky brightness equivalent to 2.8 × {10}-4{cd} {{{m}}}-2 over the entire island, is an indication that the island is, overall, still relatively dark. However, the amount of development taking place might reduce the number in the near future as the island is famous as a holiday destination.