WorldWideScience

Sample records for stochastic spatio-temporal dynamic

  1. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

    Science.gov (United States)

    Schöll, Eckehard

    2005-08-01

    Nonlinear transport phenomena are an increasingly important aspect of modern semiconductor research. This volume deals with complex nonlinear dynamics, pattern formation, and chaotic behavior in such systems. It bridges the gap between two well-established fields: the theory of dynamic systems and nonlinear charge transport in semiconductors. This unified approach helps reveal important electronic transport instabilities. The initial chapters lay a general framework for the theoretical description of nonlinear self-organized spatio-temporal patterns, such as current filaments, field domains, fronts, and analysis of their stability. Later chapters consider important model systems in detail: impact ionization induced impurity breakdown, Hall instabilities, superlattices, and low-dimensional structures. State-of-the-art results include chaos control, spatio-temporal chaos, multistability, pattern selection, activator-inhibitor kinetics, and global coupling, linking fundamental issues to electronic device applications. This book will be of great value to semiconductor physicists and nonlinear scientists alike.

  2. Large scale stochastic spatio-temporal modelling with PCRaster

    NARCIS (Netherlands)

    Karssenberg, D.J.; Drost, N.; Schmitz, O.; Jong, K. de; Bierkens, M.F.P.

    2013-01-01

    PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model

  3. Estimating spatio-temporal dynamics of size-structured populations

    DEFF Research Database (Denmark)

    Kristensen, Kasper; Thygesen, Uffe Høgsbro; Andersen, Ken Haste

    2014-01-01

    with simple stock dynamics, to estimate simultaneously how size distributions and spatial distributions develop in time. We demonstrate the method for a cod population sampled by trawl surveys. Particular attention is paid to correlation between size classes within each trawl haul due to clustering...... of individuals with similar size. The model estimates growth, mortality and reproduction, after which any aspect of size-structure, spatio-temporal population dynamics, as well as the sampling process can be probed. This is illustrated by two applications: 1) tracking the spatial movements of a single cohort...

  4. Spatio-temporal dynamics of the tropical rain forest

    Energy Technology Data Exchange (ETDEWEB)

    Chave, J. [CEN Saclay, Gif-sur-Yvette (France). Service de Physique de l' Etat Condense

    2000-07-01

    Mechanisms which drive the dynamics of forest ecosystems are complex, from seedling establishment to pollination, and seed dispersal by animals, running water or wind. These processes are more complex when the ecosystem shelters a large number of species and of vegetative forms, as it is the case in the tropical rainforest. To take them into account, we must develop and use models. I present a review of the fundamental mechanisms for the of a natural forest dynamics - photosynthesis, tree growth, recruitment and mortality - as well as a description of the past and of the present of tropical rainforests. This information is used to develop a spatially-explicit and individual-based forest model. Simplified models are deduced from it, and they serve to address more specific issues, such as the resilience of the forest to climate disturbances, or savanna-forest dynamics. The last topic is related to the spatio-temporal description of tropical plant biodiversity. A detailed introduction to the problem is provided, and models accounting for the maintenance of diversity are compared. These models include non spatial as well a spatial approaches (branching anihilating random walks and voter model with mutation). (orig.)

  5. Spatio-temporal diffusion of dynamic PET images

    International Nuclear Information System (INIS)

    Tauber, C; Chalon, S; Guilloteau, D; Stute, S; Buvat, I; Chau, M; Spiteri, P

    2011-01-01

    Positron emission tomography (PET) images are corrupted by noise. This is especially true in dynamic PET imaging where short frames are required to capture the peak of activity concentration after the radiotracer injection. High noise results in a possible bias in quantification, as the compartmental models used to estimate the kinetic parameters are sensitive to noise. This paper describes a new post-reconstruction filter to increase the signal-to-noise ratio in dynamic PET imaging. It consists in a spatio-temporal robust diffusion of the 4D image based on the time activity curve (TAC) in each voxel. It reduces the noise in homogeneous areas while preserving the distinct kinetics in regions of interest corresponding to different underlying physiological processes. Neither anatomical priors nor the kinetic model are required. We propose an automatic selection of the scale parameter involved in the diffusion process based on a robust statistical analysis of the distances between TACs. The method is evaluated using Monte Carlo simulations of brain activity distributions. We demonstrate the usefulness of the method and its superior performance over two other post-reconstruction spatial and temporal filters. Our simulations suggest that the proposed method can be used to significantly increase the signal-to-noise ratio in dynamic PET imaging.

  6. Spatio-temporal dynamics of security investments in an interdependent risk environment

    Science.gov (United States)

    Shafi, Kamran; Bender, Axel; Zhong, Weicai; Abbass, Hussein A.

    2012-10-01

    In a globalised world where risks spread through contagion, the decision of an entity to invest in securing its premises from stochastic risks no longer depends solely on its own actions but also on the actions of other interacting entities in the system. This phenomenon is commonly seen in many domains including airline, logistics and computer security and is referred to as Interdependent Security (IDS). An IDS game models this decision problem from a game-theoretic perspective and deals with the behavioural dynamics of risk-reduction investments in such settings. This paper enhances this model and investigates the spatio-temporal aspects of the IDS games. The spatio-temporal dynamics are studied using simple replicator dynamics on a variety of network structures and for various security cost tradeoffs that lead to different Nash equilibria in an IDS game. The simulation results show that the neighbourhood configuration has a greater effect on the IDS game dynamics than network structure. An in-depth empirical analysis of game dynamics is carried out on regular graphs, which leads to the articulation of necessary and sufficient conditions for dominance in IDS games under spatial constraints.

  7. A full time-domain approach to spatio-temporal dynamics of semiconductor lasers. II. Spatio-temporal dynamics

    Science.gov (United States)

    Böhringer, Klaus; Hess, Ortwin

    The spatio-temporal dynamics of novel semiconductor lasers is discussed on the basis of a space- and momentum-dependent full time-domain approach. To this means the space-, time-, and momentum-dependent Full-Time Domain Maxwell Semiconductor Bloch equations, derived and discussed in our preceding paper I [K. Böhringer, O. Hess, A full time-domain approach to spatio-temporal dynamics of semiconductor lasers. I. Theoretical formulation], are solved by direct numerical integration. Focussing on the device physics of novel semiconductor lasers that profit, in particular, from recent advances in nanoscience and nanotechnology, we discuss the examples of photonic band edge surface emitting lasers (PBE-SEL) and semiconductor disc lasers (SDLs). It is demonstrated that photonic crystal effects can be obtained for finite crystal structures, and leading to a significant improvement in laser performance such as reduced lasing thresholds. In SDLs, a modern device concept designed to increase the power output of surface-emitters in combination with near-diffraction-limited beam quality, we explore the complex interplay between the intracavity optical fields and the quantum well gain material in SDL structures. Our simulations reveal the dynamical balance between carrier generation due to pumping into high energy states, momentum relaxation of carriers, and stimulated recombination from states near the band edge. Our full time-domain approach is shown to also be an excellent framework for the modelling of the interaction of high-intensity femtosecond and picosecond pulses with semiconductor nanostructures. It is demonstrated that group velocity dispersion, dynamical gain saturation and fast self-phase modulation (SPM) are the main causes for the induced changes and asymmetries in the amplified pulse shape and spectrum of an ultrashort high-intensity pulse. We attest that the time constants of the intraband scattering processes are critical to gain recovery. Moreover, we present

  8. Spatio-temporal and stochastic modelling of severe acute respiratory syndrome

    Directory of Open Access Journals (Sweden)

    Poh-Chin Lai

    2013-11-01

    Full Text Available This study describes the development of a spatio-temporal disease model based on the episodes of severe acute respiratory syndrome (SARS that took place in Hong Kong in 2003. In contrast to conventional, deterministic modelling approaches, the model described here is predominantly spatial. It incorporates stochastic processing of environmental and social variables that interact in space and time to affect the patterns of disease transmission in a community. The model was validated through a comparative assessment between actual and modelled distribution of diseased locations. Our study shows that the inclusion of location-specific characteristics satisfactorily replicates the spatial dynamics of an infectious disease. The Pearson’s correlation coefficients for five trials based on 3-day aggregation of disease counts for 1-3, 4-6 and 7-9 day forecasts were 0.57- 0.95, 0.54-0.86 and 0.57-0.82, respectively, while the correlation based on 5-day aggregation for the 1-5 day forecast was 0.55- 0.94 and 0.58-0.81 for the 6-10 day forecast. The significant and strong relationship between actual results and forecast is encouraging for the potential development of an early warning system for detecting this type of disease outbreaks.

  9. Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

    DEFF Research Database (Denmark)

    Frelat, Romain; Lindegren, Martin; Dencker, Tim Spaanheden

    2017-01-01

    it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered...... by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii...

  10. Spatio-temporal Dynamics and Mechanisms of Stress Granule Assembly.

    Directory of Open Access Journals (Sweden)

    Daisuke Ohshima

    2015-06-01

    Full Text Available Stress granules (SGs are non-membranous cytoplasmic aggregates of mRNAs and related proteins, assembled in response to environmental stresses such as heat shock, hypoxia, endoplasmic reticulum (ER stress, chemicals (e.g. arsenite, and viral infections. SGs are hypothesized as a loci of mRNA triage and/or maintenance of proper translation capacity ratio to the pool of mRNAs. In brain ischemia, hippocampal CA3 neurons, which are resilient to ischemia, assemble SGs. In contrast, CA1 neurons, which are vulnerable to ischemia, do not assemble SGs. These results suggest a critical role SG plays in regards to cell fate decisions. Thus SG assembly along with its dynamics should determine the cell fate. However, the process that exactly determines the SG assembly dynamics is largely unknown. In this paper, analyses of experimental data and computer simulations were used to approach this problem. SGs were assembled as a result of applying arsenite to HeLa cells. The number of SGs increased after a short latent period, reached a maximum, then decreased during the application of arsenite. At the same time, the size of SGs grew larger and became localized at the perinuclear region. A minimal mathematical model was constructed, and stochastic simulations were run to test the modeling. Since SGs are discrete entities as there are only several tens of them in a cell, commonly used deterministic simulations could not be employed. The stochastic simulations replicated observed dynamics of SG assembly. In addition, these stochastic simulations predicted a gamma distribution relative to the size of SGs. This same distribution was also found in our experimental data suggesting the existence of multiple fusion steps in the SG assembly. Furthermore, we found that the initial steps in the SG assembly process and microtubules were critical to the dynamics. Thus our experiments and stochastic simulations presented a possible mechanism regulating SG assembly.

  11. Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

    gauges in the model area. The spatio-temporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatio-temporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying onprecipitation output......Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...

  12. Investigating fine-scale spatio-temporal predator-prey patterns in dynamic marine ecosystems: a functional data analysis approach

    NARCIS (Netherlands)

    Embling, C.B.; Illian, J.; Armstrong, E.; van der Kooij, J.; Sharples, J.; Camphuysen, K.C.J.; Scott, B.E.

    2012-01-01

    1. Spatial management of marine ecosystems requires detailed knowledge of spatio-temporal mechanisms linking physical and biological processes. Tidal currents, the main driver of ecosystem dynamics in temperate coastal ecosystems, influence predator foraging ecology by affecting prey distribution

  13. Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium.

    Science.gov (United States)

    Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

    2017-09-01

    Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

  14. Spatio-temporal cell dynamics in tumour spheroid irradiation

    International Nuclear Information System (INIS)

    Kempf, H.; Bleicher, M.; Meyer-Hermann, M.; Kempf, H.; Bleicher, M.; Kempf, H.; Meyer-Hermann, M.

    2010-01-01

    Multicellular tumour spheroids are realistic in vitro systems in radiation research that integrate cell-cell interaction and cell cycle control by factors in the medium. The dynamic reaction inside a tumour spheroid triggered by radiation is not well understood. Of special interest is the amount of cell cycle synchronization which could be triggered by irradiation, since this would allow follow-up irradiations to exploit the increased sensitivity of certain cell cycle phases. In order to investigate these questions we need to support irradiation experiments with mathematical models. In this article a new model is introduced combining the dynamics of tumour growth and irradiation treatments. The tumour spheroid growth is modelled using an agent-based Delaunay/Voronoi hybrid model in which the cells are represented by weighted dynamic vertices. Cell properties like full cell cycle dynamics are included. In order to be able to distinguish between different cell reactions in response to irradiation quality we introduce a probabilistic model for damage dynamics. The overall cell survival from this model is in agreement with predictions from the linear-quadratic model. Our model can describe the growth of avascular tumour spheroids in agreement to experimental results. Using the probabilistic model for irradiation damage dynamics the classic 'four Rs' of radiotherapy can be studied in silico. We found a pronounced reactivation of the tumour spheroid in response to irradiation. A majority of the surviving cells is synchronized in their cell cycle progression after irradiation. The cell synchronization could be actively triggered and should be exploited in an advanced fractionation scheme. Thus it has been demonstrated that our model could be used to understand the dynamics of tumour growth after irradiation and to propose optimized fractionation schemes in cooperation with experimental investigations. (authors)

  15. Spatio-temporal dynamics of a pulsed microwave argon plasma: ignition and afterglow

    International Nuclear Information System (INIS)

    Carbone, Emile; Sadeghi, Nader; Vos, Erik; Hübner, Simon; Van Veldhuizen, Eddie; Van Dijk, Jan; Nijdam, Sander; Kroesen, Gerrit

    2015-01-01

    In this paper, a detailed investigation of the spatio-temporal dynamics of a pulsed microwave plasma is presented. The plasma is ignited inside a dielectric tube in a repetitively pulsed regime at pressures ranging from 1 up to 100 mbar with pulse repetition frequencies from 200 Hz up to 500 kHz. Various diagnostic techniques are employed to obtain the main plasma parameters both spatially and with high temporal resolution. Thomson scattering is used to obtain the electron density and mean electron energy at fixed positions in the dielectric tube. The temporal evolution of the two resonant and two metastable argon 4s states are measured by laser diode absorption spectroscopy. Nanosecond time-resolved imaging of the discharge allows us to follow the spatio-temporal evolution of the discharge with high temporal and spatial resolution. Finally, the temporal evolution of argon 4p and higher states is measured by optical emission spectroscopy. The combination of these various diagnostics techniques gives deeper insight on the plasma dynamics during pulsed microwave plasma operation from low to high pressure regimes. The effects of the pulse repetition frequency on the plasma ignition dynamics are discussed and the plasma-off time is found to be the relevant parameter for the observed ignition modes. Depending on the delay between two plasma pulses, the dynamics of the ionization front are found to be changing dramatically. This is also reflected in the dynamics of the electron density and temperature and argon line emission from the plasma. On the other hand, the (quasi) steady state properties of the plasma are found to depend only weakly on the pulse repetition frequency and the afterglow kinetics present an uniform spatio-temporal behavior. However, compared to continuous operation, the time-averaged metastable and resonant state 4s densities are found to be significantly larger around a few kHz pulsing frequency. (paper)

  16. A general science-based framework for dynamical spatio-temporal models

    Science.gov (United States)

    Wikle, C.K.; Hooten, M.B.

    2010-01-01

    Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

  17. Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

    Science.gov (United States)

    Chang, Fi-John; Chen, Pin-An; Chang, Li-Chiu; Tsai, Yu-Hsuan

    2016-08-15

    This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

    2017-01-01

    Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...... gauges in the model area. The spatiotemporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatiotemporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying on precipitation output...

  19. Spatio-temporal correlations in models of collective motion ruled by different dynamical laws.

    Science.gov (United States)

    Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas S; Melillo, Stefania; Viale, Massimiliano

    2016-11-15

    Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.

  20. Spatio-temporal dynamics of the penetration resistance of recultivated soils formed after open cast mining

    Directory of Open Access Journals (Sweden)

    A. V. Zhukov

    2016-01-01

    Full Text Available On the basis of studying the spatio-temporal dynamics of soil penetration resistance we proved the existence of the technozem ecomorphs as above horizon soil formations. Research was carried out at a research center for study of recultivation processes in Ordzhonikidze city. Measurement of soils penetration was made in field conditions using an Eijkelkamp penetrometer on a regular grid at depths of up to50 cmwith intervals of5 cm. Calculation of average values and degrees of variation was performed by means of descriptive statistical tools. The extent of soil penetration spatial dependence was assessed and the existence of ecomorphs was proved by means of geostatistical analysis. The degree of associativity of spatial distribution of indicators of a soil body in different years of research was established by means of correlation analysis. The level of variation in space and in time of  technozem penetration generated on loess-like loams, grey-green, red-brown clays, and also pedozems was revealed. The degree of spatial dependence of  technozem penetration within soil layers and also the linear sizes of ecomorphs as above horizon soil structures was established. The time dynamics of  penetration of various recultozems were described. As a result of research into the spatio-temporal dynamics of penetration of technozems, data confirming the hypothesis of the existence of ecomorphs as above horizon morphological soil formations were obtained. An ecomorphic approach to the study of the morphological structure of technozems is proposed. The comparative characteristics of ecomorphs from various types of technozem are presented. The results obtained solve the problem of combining the higher and lowest levels in the hierarchical system of soil organisation as a natural body, which should raise the efficiency of the analysis of relations of morphological elements as a basis for detailed reconstruction of recultivation processes, soil formation, and

  1. A customized light sheet microscope to measure spatio-temporal protein dynamics in small model organisms.

    Directory of Open Access Journals (Sweden)

    Matthias Rieckher

    Full Text Available We describe a customizable and cost-effective light sheet microscopy (LSM platform for rapid three-dimensional imaging of protein dynamics in small model organisms. The system is designed for high acquisition speeds and enables extended time-lapse in vivo experiments when using fluorescently labeled specimens. We demonstrate the capability of the setup to monitor gene expression and protein localization during ageing and upon starvation stress in longitudinal studies in individual or small groups of adult Caenorhabditis elegans nematodes. The system is equipped to readily perform fluorescence recovery after photobleaching (FRAP, which allows monitoring protein recovery and distribution under low photobleaching conditions. Our imaging platform is designed to easily switch between light sheet microscopy and optical projection tomography (OPT modalities. The setup permits monitoring of spatio-temporal expression and localization of ageing biomarkers of subcellular size and can be conveniently adapted to image a wide range of small model organisms and tissue samples.

  2. The surface chemistry determines the spatio-temporal interaction dynamics of quantum dots in atherosclerotic lesions.

    Science.gov (United States)

    Uhl, Bernd; Hirn, Stephanie; Mildner, Karina; Coletti, Raffaele; Massberg, Steffen; Reichel, Christoph A; Rehberg, Markus; Zeuschner, Dagmar; Krombach, Fritz

    2018-03-01

    To optimize the design of nanoparticles for diagnosis or therapy of vascular diseases, it is mandatory to characterize the determinants of nano-bio interactions in vascular lesions. Using ex vivo and in vivo microscopy, we analyzed the interactive behavior of quantum dots with different surface functionalizations in atherosclerotic lesions of ApoE-deficient mice. We demonstrate that quantum dots with different surface functionalizations exhibit specific interactive behaviors with distinct molecular and cellular components of the injured vessel wall. Moreover, we show a role for fibrinogen in the regulation of the spatio-temporal interaction dynamics in atherosclerotic lesions. Our findings emphasize the relevance of surface chemistry-driven nano-bio interactions on the differential in vivo behavior of nanoparticles in diseased tissue.

  3. Spatio-temporal dynamics of the white-eye square superlattice pattern in dielectric barrier discharge

    International Nuclear Information System (INIS)

    Wei, Lingyan; Dong, Lifang; Feng, Jianyu; Liu, Weibo; Fan, Weili; Pan, Yuyang

    2016-01-01

    We report on the first investigation of the white-eye square superlattice pattern (WESSP) in a dielectric barrier discharge system. The evolution of patterns with increasing voltage is given. A phase diagram of WESSP as functions of gas pressure p and argon concentration φ is presented. The spatio-temporal dynamics of the WESSP is studied by using an intensified charge-coupled device camera and photomultipliers. Results show that the WESSP consists of four different transient sublattices, whose discharge sequence is small spots—spots on the line—halos—central spots in each half voltage cycle. The discharge moment and position of each sublattice are dependent upon the field of the wall charges produced by all sublattices discharged previously. (paper)

  4. Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period.

    Science.gov (United States)

    Nigsch, Annette; Costard, Solenne; Jones, Bryony A; Pfeiffer, Dirk U; Wieland, Barbara

    2013-03-01

    African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncertain how fast the virus would be able to spread within the unrestricted European trading area if it were introduced into the EU. This project therefore aimed to develop a model for the spread of ASF within and between the 27 Member States (MS) of the EU during the high risk period (HRP) and to identify MS during that period would most likely contribute to ASF spread ("super-spreaders") or MS that would most likely receive cases from other MS ("super-receivers"). A stochastic spatio-temporal state-transition model using simulated individual farm records was developed to assess silent ASF virus spread during different predefined HRPs of 10-60 days duration. Infection was seeded into farms of different pig production types in each of the 27 MS. Direct pig-to-pig transmission and indirect transmission routes (pig transport lorries and professional contacts) were considered the main pathways during the early stages of an epidemic. The model was parameterised using data collated from EUROSTAT, TRACES, a questionnaire sent to MS, and the scientific literature. Model outputs showed that virus circulation was generally limited to 1-2 infected premises per outbreak (95% IQR: 1-4; maximum: 10) with large breeder farms as index case resulting in most infected premises. Seven MS caused between-MS spread due to intra-Community trade during the first 10 days after seeding infection. For a HRP of 60 days from virus introduction, movements of infected pigs will originate at least once from 16 MS, with 6 MS spreading ASF in more than 10% of iterations. Two thirds of all intra-Community spread was linked to six trade links only. Denmark, the Netherlands, Lithuania and Latvia were identified

  5. Spatio-temporal patterns of soil erosion and suspended sediment dynamics in the Mekong River Basin.

    Science.gov (United States)

    Suif, Zuliziana; Fleifle, Amr; Yoshimura, Chihiro; Saavedra, Oliver

    2016-10-15

    Understanding of the distribution patterns of sediment erosion, concentration and transport in river basins is critically important as sediment plays a major role in river basin hydrophysical and ecological processes. In this study, we proposed an integrated framework for the assessment of sediment dynamics, including soil erosion (SE), suspended sediment load (SSL) and suspended sediment concentration (SSC), and applied this framework to the Mekong River Basin. The Revised Universal Soil Loss Equation (RUSLE) model was adopted with a geographic information system to assess SE and was coupled with a sediment accumulation and a routing scheme to simulate SSL. This framework also analyzed Landsat imagery captured between 1987 and 2000 together with ground observations to interpolate spatio-temporal patterns of SSC. The simulated SSL results from 1987 to 2000 showed the relative root mean square error of 41% and coefficient of determination (R(2)) of 0.89. The polynomial relationship of the near infrared exoatmospheric reflectance and the band 4 wavelength (760-900nm) to the observed SSC at 9 sites demonstrated the good agreement (overall relative RMSE=5.2%, R(2)=0.87). The result found that the severe SE occurs in the upper (China and Lao PDR) and lower (western part of Vietnam) regions. The SSC in the rainy season (June-November) showed increasing and decreasing trends longitudinally in the upper (China and Lao PDR) and lower regions (Cambodia), respectively, while the longitudinal profile of SSL showed a fluctuating trend along the river in the early rainy season. Overall, the results described the unique spatio-temporal patterns of SE, SSL and SSC in the Mekong River Basin. Thus, the proposed integrated framework is useful for elucidating complex process of sediment generation and transport in the land and river systems of large river basins. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Spatio-temporal data analytics for wind energy integration

    CERN Document Server

    Yang, Lei; Zhang, Junshan

    2014-01-01

    This SpringerBrief presents spatio-temporal data analytics for wind energy integration using stochastic modeling and optimization methods. It explores techniques for efficiently integrating renewable energy generation into bulk power grids. The operational challenges of wind, and its variability are carefully examined. A spatio-temporal analysis approach enables the authors to develop Markov-chain-based short-term forecasts of wind farm power generation. To deal with the wind ramp dynamics, a support vector machine enhanced Markov model is introduced. The stochastic optimization of economic di

  7. Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.

    Science.gov (United States)

    Börlin, Christoph S; Lang, Verena; Hamacher-Brady, Anne; Brady, Nathan R

    2014-09-10

    Autophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies. We applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3

  8. Somatic growth dynamics of West Atlantic hawksbill sea turtles: a spatio-temporal perspective

    Science.gov (United States)

    Bjorndal, Karen A.; Chaloupka, Milani; Saba, Vincent S.; Diez, Carlos E.; van Dam, Robert P.; Krueger, Barry H.; Horrocks, Julia A.; Santos, Armando J.B.; Bellini, Cláudio; Marcovaldi, Maria A.G.; Nava, Mabel; Willis, Sue; Godley, Brendan J.; Gore, Shannon; Hawkes, Lucy A.; McGowan, Andrew; Witt, Matthew J.; Stringell, Thomas B.; Sanghera, Amdeep; Richardson, Peter B.; Broderick, Annette C.; Phillips, Quinton; Calosso, Marta C.; Claydon, John A.B.; Blumenthal, Janice; Moncada, Felix; Nodarse, Gonzalo; Medina, Yosvani; Dunbar, Stephen G.; Wood, Lawrence D.; Lagueux, Cynthia J.; Campbell, Cathi L.; Meylan, Anne B.; Meylan, Peter A.; Burns Perez, Virginia R.; Coleman, Robin A.; Strindberg, Samantha; Guzmán-H, Vicente; Hart, Kristen M.; Cherkiss, Michael S.; Hillis-Starr, Zandy; Lundgren, Ian; Boulon, Ralf H.; Connett, Stephen; Outerbridge, Mark E.; Bolten, Alan B.

    2016-01-01

    Somatic growth dynamics are an integrated response to environmental conditions. Hawksbill sea turtles (Eretmochelys imbricata) are long-lived, major consumers in coral reef habitats that move over broad geographic areas (hundreds to thousands of kilometers). We evaluated spatio-temporal effects on hawksbill growth dynamics over a 33-yr period and 24 study sites throughout the West Atlantic and explored relationships between growth dynamics and climate indices. We compiled the largest ever data set on somatic growth rates for hawksbills – 3541 growth increments from 1980 to 2013. Using generalized additive mixed model analyses, we evaluated 10 covariates, including spatial and temporal variation, that could affect growth rates. Growth rates throughout the region responded similarly over space and time. The lack of a spatial effect or spatio-temporal interaction and the very strong temporal effect reveal that growth rates in West Atlantic hawksbills are likely driven by region-wide forces. Between 1997 and 2013, mean growth rates declined significantly and steadily by 18%. Regional climate indices have significant relationships with annual growth rates with 0- or 1-yr lags: positive with the Multivariate El Niño Southern Oscillation Index (correlation = 0.99) and negative with Caribbean sea surface temperature (correlation = −0.85). Declines in growth rates between 1997 and 2013 throughout the West Atlantic most likely resulted from warming waters through indirect negative effects on foraging resources of hawksbills. These climatic influences are complex. With increasing temperatures, trajectories of decline of coral cover and availability in reef habitats of major prey species of hawksbills are not parallel. Knowledge of how choice of foraging habitats, prey selection, and prey abundance are affected by warming water temperatures is needed to understand how climate change will affect productivity of consumers that live in association with coral reefs. Main

  9. Integrating Future Land Use Scenarios to Evaluate the Spatio-Temporal Dynamics of Landscape Ecological Security

    Directory of Open Access Journals (Sweden)

    Yi Lu

    2016-11-01

    Full Text Available Urban ecological security is the basic principle of national ecological security. However, analyses of the spatial and temporal dynamics of ecological security remain limited, especially those that consider different scenarios of urban development. In this study, an integrated method is proposed that combines the Conversion of Land Use and its Effects (CLUE-S model with the Pressure–State–Response (P-S-R framework to assess landscape ecological security (LES in Huangshan City, China under two scenarios. Our results suggest the following conclusions: (1 the spatial and temporal dynamics of ecological security are closely related to the urbanization process; (2 although the average values of landscape ecological security are similar under different scenarios, the areas of relatively high security levels vary considerably; and (3 spatial heterogeneity in ecological security exists between different districts and counties, and the city center and its vicinity may face relatively serious declines in ecological security in the future. Overall, the proposed method not only illustrates the spatio-temporal dynamics of landscape ecological security under different scenarios but also reveals the anthropogenic effects on ecosystems by differentiating between causes, effects, and human responses at the landscape scale. This information is of great significance to decision-makers for future urban planning and management.

  10. Dynamic computed tomography based on spatio-temporal analysis in acute stroke: Preliminary study

    Energy Technology Data Exchange (ETDEWEB)

    Park, Ha Young; Pyeon, Do Yeong; Kim, Da Hye; Jung, Young Jin [Dongseo University, Busan (Korea, Republic of)

    2016-12-15

    Acute stroke is a one of common disease that require fast diagnosis and treatment to save patients life. however, the acute stroke may cause lifelong disability due to brain damage with no prompt surgical procedure. In order to diagnose the Stroke, brain perfusion CT examination and possible rapid implementation of 3D angiography has been widely used. However, a low-dose technique should be applied for the examination since a lot of radiation exposure to the patient may cause secondary damage for the patients. Therefore, the degradation of the measured CT images may interferes with a clinical check in that blood vessel shapes o n the CT image are significantly affected by gaussian noise. In this study, we employed the spatio-temporal technique to analyze dynamic (brain perfusion) CT data to improve an image quality for successful clinical diagnosis. As a results, proposed technique could remove gaussian noise successfully, demonstrated a possibility of new image segmentation technique for CT angiography. Qualitative evaluation was conducted by skilled radiological technologists, indicated significant quality improvement of dynamic CT images. the proposed technique will be useful tools as a clinical application for brain perfusion CT examination.

  11. Spatio-temporal dynamics of impulse responses to figure motion in optic flow neurons.

    Directory of Open Access Journals (Sweden)

    Yu-Jen Lee

    Full Text Available White noise techniques have been used widely to investigate sensory systems in both vertebrates and invertebrates. White noise stimuli are powerful in their ability to rapidly generate data that help the experimenter decipher the spatio-temporal dynamics of neural and behavioral responses. One type of white noise stimuli, maximal length shift register sequences (m-sequences, have recently become particularly popular for extracting response kernels in insect motion vision. We here use such m-sequences to extract the impulse responses to figure motion in hoverfly lobula plate tangential cells (LPTCs. Figure motion is behaviorally important and many visually guided animals orient towards salient features in the surround. We show that LPTCs respond robustly to figure motion in the receptive field. The impulse response is scaled down in amplitude when the figure size is reduced, but its time course remains unaltered. However, a low contrast stimulus generates a slower response with a significantly longer time-to-peak and half-width. Impulse responses in females have a slower time-to-peak than males, but are otherwise similar. Finally we show that the shapes of the impulse response to a figure and a widefield stimulus are very similar, suggesting that the figure response could be coded by the same input as the widefield response.

  12. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    Science.gov (United States)

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  13. Dynamical Properties of Transient Spatio-Temporal Patterns in Bacterial Colony of Proteus mirabilis

    Science.gov (United States)

    Watanabe, Kazuhiko; Wakita, Jun-ichi; Itoh, Hiroto; Shimada, Hirotoshi; Kurosu, Sayuri; Ikeda, Takemasa; Yamazaki, Yoshihiro; Matsuyama, Tohey; Matsushita, Mitsugu

    2002-02-01

    Spatio-temporal patterns emerged inside a colony of bacterial species Proteus mirabilis on the surface of nutrient-rich semisolid agar medium have been investigated. We observed various patterns composed of the following basic types: propagating stripe, propagating stripe with fixed dislocation, expanding and shrinking target, and rotating spiral. The remarkable point is that the pattern changes immediately when we alter the position for observation, but it returns to the original if we restore the observing position within a few minutes. We further investigated mesoscopic and microscopic properties of the spatio-temporal patterns. It turned out that whenever the spatio-temporal patterns are observed in a colony, the areas are composed of two superimposed monolayers of elongated bacterial cells. In each area they are aligned almost parallel with each other like a two-dimensional nematic liquid crystal, and move collectively and independently of another layer. It has been found that the observed spatio-temporal patterns are explained as the moiré effect.

  14. Spatio-temporal dynamics of cod nursery areas in the Baltic Sea

    Science.gov (United States)

    Hinrichsen, H.-H.; von Dewitz, B.; Lehmann, A.; Bergström, U.; Hüssy, K.

    2017-06-01

    In this study the drift of eastern Baltic cod larvae and juveniles spawned within the historical eastern Baltic cod spawning grounds was investigated by detailed drift model simulations for the years 1971-2010, to examine the spatio-temporal dynamics of environmental suitability in the nursery areas of juvenile cod settlement. The results of the long-term model scenario runs, where juvenile cod were treated as simulated passively drifting particles, enabled us to find strong indications for long-term variations of settlement and potentially the reproduction success of the historically important eastern Baltic cod nursery grounds. Only low proportions of juveniles hatched in the Arkona Basin and in the Gotland Basin were able to settle in their respective spawning ground. Ocean currents were either unfavorable for the juveniles to reach suitable habitats or transported the juveniles to nursery grounds of neighboring subdivisions. Juveniles which hatched in the Bornholm Basin were most widely dispersed and showed the highest settlement probability, while the second highest settlement probability and horizontal dispersal was observed for juveniles originating from the Gdansk Deep. In a long-term perspective, wind-driven transport of larvae/juveniles positively affected the settlement success predominately in the Bornholm Basin and in the Bay of Gdansk. The Bornholm Basin has the potential to contribute on average 54% and the Bay of Gdansk 11% to the production of juveniles in the Baltic Sea. Furthermore, transport of juveniles surviving to the age of settlement with origin in the Bornholm Basin contributed on average 13 and 11% to the total settlement in the Arkona Basin and in the Gdansk Deep, respectively. The time-series of the simulated occupied juvenile cod habitat in the Bornholm Basin and in the Gdansk Deep showed a similar declining trend as the Fulton's K condition factor of demersal 1-group cod, which may confirm the importance of oxygen-dependent habitat

  15. Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

    Science.gov (United States)

    Daya Sagar, B. S.

    2005-01-01

    Spatio-temporal patterns of small water bodies (SWBs) under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs) controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

  16. Nonparametric evaluation of dynamic disease risk: a spatio-temporal kernel approach.

    Directory of Open Access Journals (Sweden)

    Zhijie Zhang

    Full Text Available Quantifying the distributions of disease risk in space and time jointly is a key element for understanding spatio-temporal phenomena while also having the potential to enhance our understanding of epidemiologic trajectories. However, most studies to date have neglected time dimension and focus instead on the "average" spatial pattern of disease risk, thereby masking time trajectories of disease risk. In this study we propose a new idea titled "spatio-temporal kernel density estimation (stKDE" that employs hybrid kernel (i.e., weight functions to evaluate the spatio-temporal disease risks. This approach not only can make full use of sample data but also "borrows" information in a particular manner from neighboring points both in space and time via appropriate choice of kernel functions. Monte Carlo simulations show that the proposed method performs substantially better than the traditional (i.e., frequency-based kernel density estimation (trKDE which has been used in applied settings while two illustrative examples demonstrate that the proposed approach can yield superior results compared to the popular trKDE approach. In addition, there exist various possibilities for improving and extending this method.

  17. Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

    Directory of Open Access Journals (Sweden)

    B. S. Daya Sagar

    2005-01-01

    Full Text Available Spatio-temporal patterns of small water bodies (SWBs under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

  18. The Ecuadorian Artisanal Fishery for Large Pelagics: Species Composition and Spatio-Temporal Dynamics.

    Directory of Open Access Journals (Sweden)

    Jimmy Martínez-Ortiz

    Full Text Available The artisanal fisheries of Ecuador operate within one of the most dynamic and productive marine ecosystems of the world. This study investigates the catch composition of the Ecuadorian artisanal fishery for large pelagic fishes, including aspects of its spatio-temporal dynamics. The analyses of this study are based on the most extensive dataset available to date for this fishery: a total of 106,963 trip-landing inspection records collected at its five principal ports during 2008 ‒ 2012. Ecuadorian artisanal fisheries remove a substantial amount of biomass from the upper trophic-level predatory fish community of the eastern tropical Pacific Ocean. It is estimated that at least 135 thousand metric tons (mt (about 15.5 million fish were landed in the five principal ports during the study period. The great novelty of Ecuadorian artisanal fisheries is the "oceanic-artisanal" fleet component, which consists of mother-ship (nodriza boats with their towed fiber-glass skiffs (fibras operating with pelagic longlines. This fleet has fully expanded into oceanic waters as far offshore as 100°W, west of the Galapagos Archipelago. It is estimated that nodriza operations produce as much as 80% of the total catches of the artisanal fishery. The remainder is produced by independent fibras operating in inshore waters with pelagic longlines and/or surface gillnets. A multivariate regression tree analysis was used to investigate spatio-environmental effects on the nodriza fleet (n = 6,821 trips. The catch species composition of the nodriza fleet is strongly influenced by the northwesterly circulation of the Humboldt Current along the coast of Peru and its associated cold waters masses. The target species and longline gear-type used by nodrizas change seasonally with the incursion of cool waters (< 25°C from the south and offshore. During this season, dolphinfish (Coryphaena hippurus dominates the catches. However, in warmer waters, the fishery changes to tuna

  19. The Ecuadorian Artisanal Fishery for Large Pelagics: Species Composition and Spatio-Temporal Dynamics.

    Science.gov (United States)

    Martínez-Ortiz, Jimmy; Aires-da-Silva, Alexandre M; Lennert-Cody, Cleridy E; Maunder, Mark N

    2015-01-01

    The artisanal fisheries of Ecuador operate within one of the most dynamic and productive marine ecosystems of the world. This study investigates the catch composition of the Ecuadorian artisanal fishery for large pelagic fishes, including aspects of its spatio-temporal dynamics. The analyses of this study are based on the most extensive dataset available to date for this fishery: a total of 106,963 trip-landing inspection records collected at its five principal ports during 2008 ‒ 2012. Ecuadorian artisanal fisheries remove a substantial amount of biomass from the upper trophic-level predatory fish community of the eastern tropical Pacific Ocean. It is estimated that at least 135 thousand metric tons (mt) (about 15.5 million fish) were landed in the five principal ports during the study period. The great novelty of Ecuadorian artisanal fisheries is the "oceanic-artisanal" fleet component, which consists of mother-ship (nodriza) boats with their towed fiber-glass skiffs (fibras) operating with pelagic longlines. This fleet has fully expanded into oceanic waters as far offshore as 100°W, west of the Galapagos Archipelago. It is estimated that nodriza operations produce as much as 80% of the total catches of the artisanal fishery. The remainder is produced by independent fibras operating in inshore waters with pelagic longlines and/or surface gillnets. A multivariate regression tree analysis was used to investigate spatio-environmental effects on the nodriza fleet (n = 6,821 trips). The catch species composition of the nodriza fleet is strongly influenced by the northwesterly circulation of the Humboldt Current along the coast of Peru and its associated cold waters masses. The target species and longline gear-type used by nodrizas change seasonally with the incursion of cool waters (< 25°C) from the south and offshore. During this season, dolphinfish (Coryphaena hippurus) dominates the catches. However, in warmer waters, the fishery changes to tuna

  20. Synchronizing spatio-temporal chaos with imperfect models: A stochastic surface growth picture

    International Nuclear Information System (INIS)

    Pazó, Diego; López, Juan M.; Rodríguez, Miguel A.; Gallego, Rafael

    2014-01-01

    We study the synchronization of two spatially extended dynamical systems where the models have imperfections. We show that the synchronization error across space can be visualized as a rough surface governed by the Kardar-Parisi-Zhang equation with both upper and lower bounding walls corresponding to nonlinearities and model discrepancies, respectively. Two types of model imperfections are considered: parameter mismatch and unresolved fast scales, finding in both cases the same qualitative results. The consistency between different setups and systems indicates that the results are generic for a wide family of spatially extended systems

  1. Demand-supply dynamics in tourism systems: A spatio-temporal GIS analysis. The Alberta ski industry case study

    Science.gov (United States)

    Bertazzon, Stefania

    The present research focuses on the interaction of supply and demand of down-hill ski tourism in the province of Alberta. The main hypothesis is that the demand for skiing depends on the socio-economic and demographic characteristics of the population living in the province and outside it. A second, consequent hypothesis is that the development of ski resorts (supply) is a response to the demand for skiing. From the latter derives the hypothesis of a dynamic interaction between supply (ski resorts) and demand (skiers). Such interaction occurs in space, within a range determined by physical distance and the means available to overcome it. The above hypotheses implicitly define interactions that take place in space and evolve over time. The hypotheses are tested by temporal, spatial, and spatio-temporal regression models, using the best available data and the latest commercially available software. The main purpose of this research is to explore analytical techniques to model spatial, temporal, and spatio-temporal dynamics in the context of regional science. The completion of the present research has produced more significant contributions than was originally expected. Many of the unexpected contributions resulted from theoretical and applied needs arising from the application of spatial regression models. Spatial regression models are a new and largely under-applied technique. The models are fairly complex and a considerable amount of preparatory work is needed, prior to their specification and estimation. Most of this work is specific to the field of application. The originality of the solutions devised is increased by the lack of applications in the field of tourism. The scarcity of applications in other fields adds to their value for other applications. The estimation of spatio-temporal models has been only partially attained in the present research. This apparent limitation is due to the novelty and complexity of the analytical methods applied. This opens new

  2. A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

    Science.gov (United States)

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-06-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.

  3. Spatio-temporal pattern formation, fractals, and chaos in conceptual ecological models as applied to coupled plankton-fish dynamics

    International Nuclear Information System (INIS)

    Medvinskii, Aleksandr B; Tikhonova, Irina A; Tikhonov, D A; Ivanitskii, Genrikh R; Petrovskii, Sergei V; Li, B.-L.; Venturino, E; Malchow, H

    2002-01-01

    The current turn-of-the-century period witnesses the intensive use of the bioproducts of the World Ocean while at the same time calling for precautions to preserve its ecological stability. This requires that biophysical processes in aquatic systems be comprehensively explored and new methods for monitoring their dynamics be developed. While aquatic and terrestrial ecosystems have much in common in terms of their mathematical description, there are essential differences between them. For example, the mobility of oceanic plankton is mainly controlled by diffusion processes, whereas terrestrial organisms naturally enough obey totally different laws. This paper is focused on the processes underlying the dynamics of spatially inhomogeneous plankton communities. We demonstrate that conceptual reaction-diffusion mathematical models are an appropriate tool for investigating both complex spatio-temporal plankton dynamics and the fractal properties of planktivorous fish school walks. (reviews of topical problems)

  4. Spatio-temporal image correlation spectroscopy and super-resolution microscopy to quantify molecular dynamics in T cells.

    Science.gov (United States)

    Ashdown, George W; Owen, Dylan M

    2018-02-02

    Many cellular processes are regulated by the spatio-temporal organisation of signalling complexes, cytoskeletal components and membranes. One such example is at the T cell immunological synapse where the retrograde flow of cortical filamentous (F)-actin from the synapse periphery drives signalling protein microclusters towards the synapse centre. The density of this mesh however, makes visualisation and analysis of individual actin fibres difficult due to the resolution limit of conventional microscopy. Recently, super-resolution methods such as structured illumination microscopy (SIM) have surpassed this resolution limit. Here, we apply SIM to better visualise the dense cortical actin meshwork in T cell synapses formed against activating, antibody-coated surfaces and image under total-internal reflection fluorescence (TIRF) illumination. To analyse the observed molecular flows, and the relationship between them, we apply spatio-temporal image correlation spectroscopy (STICS) and its cross-correlation variant (STICCS). We show that the dynamic cortical actin mesh can be visualised with unprecedented detail and that STICS/STICCS can output accurate, quantitative maps of molecular flow velocity and directionality from such data. We find that the actin flow can be disrupted using small molecule inhibitors of actin polymerisation. This combination of imaging and quantitative analysis may provide an important new tool for researchers to investigate the molecular dynamics at cellular length scales. Here we demonstrate the retrograde flow of F-actin which may be important for the clustering and dynamics of key signalling proteins within the plasma membrane, a phenomenon which is vital to correct T cell activation and therefore the mounting of an effective immune response. Copyright © 2018. Published by Elsevier Inc.

  5. Complete mitochondrial genome sequences of Korean native horse from Jeju Island: uncovering the spatio-temporal dynamics.

    Science.gov (United States)

    Yoon, Sook Hee; Kim, Jaemin; Shin, Donghyun; Cho, Seoae; Kwak, Woori; Lee, Hak-Kyo; Park, Kyoung-Do; Kim, Heebal

    2017-04-01

    The Korean native horse (Jeju horse) is one of the most important animals in Korean historical, cultural, and economical viewpoints. In the early 1980s, the Jeju horse was close to extinction. The aim of this study is to explore the phylogenomics of Korean native horse focusing on spatio-temporal dynamics. We determined complete mitochondrial genome sequences for the first Korean native (n = 6) and additional Mongolian (n = 2) horses. Those sequences were analyzed together with 143 published ones using Bayesian coalescent approach as well as three different phylogenetic analysis methods, Bayesian inference, maximum likelihood, and neighbor-joining methods. The phylogenomic trees revealed that the Korean native horses had multiple origins and clustered together with some horses from four European and one Middle Eastern breeds. Our phylogenomic analyses also supported that there was no apparent association between breed or geographic location and the evolution of global horses. Time of the most recent common ancestor of the Korean native horse was approximately 13,200-63,200 years, which was much younger than 0.696 My of modern horses. Additionally, our results showed that all global horse lineages including Korean native horse existed prior to their domestication events occurred in about 6000-10,000 years ago. This is the first study on phylogenomics of the Korean native horse focusing on spatio-temporal dynamics. Our findings increase our understanding of the domestication history of the Korean native horses, and could provide useful information for horse conservation projects as well as for horse genomics, emergence, and the geographical distribution.

  6. Spatio-temporal dynamics of ocean conditions and forage taxa reveal regional structuring of seabird–prey relationships.

    Science.gov (United States)

    Santora, Jarrod A; Schroeder, Isaac D; Field, John C; Wells, Brian K; Sydeman, William J

    Studies of predator–prey demographic responses and the physical drivers of such relationships are rare, yet essential for predicting future changes in the structure and dynamics of marine ecosystems. Here, we hypothesize that predator–prey relationships vary spatially in association with underlying physical ocean conditions, leading to observable changes in demographic rates, such as reproduction. To test this hypothesis, we quantified spatio-temporal variability in hydrographic conditions, krill, and forage fish to model predator (seabird) demographic responses over 18 years (1990–2007). We used principal component analysis and spatial correlation maps to assess coherence among ocean conditions, krill, and forage fish, and generalized additive models to quantify interannual variability in seabird breeding success relative to prey abundance. The first principal component of four hydrographic measurements yielded an index that partitioned “warm/weak upwelling” and “cool/strong upwelling” years. Partitioning of krill and forage fish time series among shelf and oceanic regions yielded spatially explicit indicators of prey availability. Krill abundance within the oceanic region was remarkably consistent between years, whereas krill over the shelf showed marked interannual fluctuations in relation to ocean conditions. Anchovy abundance varied on the shelf, and was greater in years of strong stratification, weak upwelling and warmer temperatures. Spatio-temporal variability of juvenile forage fish co-varied strongly with each other and with krill, but was weakly correlated with hydrographic conditions. Demographic responses between seabirds and prey availability revealed spatially variable associations indicative of the dynamic nature of “predator–habitat” relationships. Quantification of spatially explicit demographic responses, and their variability through time, demonstrate the possibility of delineating specific critical areas where the

  7. Integrating real-time and manual monitored data to predict hillslope soil moisture dynamics with high spatio-temporal resolution using linear and non-linear models

    Science.gov (United States)

    Spatio-temporal variability of soil moisture (') is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time ' monitoring methods. This restricted the comprehensive and intensive examination of ' dynamic...

  8. Stability and dynamics of spatio-temporal structures. Progress report, September 15, 1993--September 14, 1994

    Energy Technology Data Exchange (ETDEWEB)

    Riecke, H.

    1994-05-01

    Goal is to contribute to understanding of localized spatial and spatio-temporal structures far from thermodynamic equilibrium. Here we report on our progress in the study of three classes of systems. (1) We have studied cellular flame structures arising in a circular burner. Using numerical computations we have found a number of traveling-wave structures in which different cells undergo different motion. Most strikingly, we have found a localized wave traveling through the array of steady cells. Results are interpreted using various asymptotic approaches. They are in qualitative agreement with recent experiments. (2) We have continued our investigation of localized waves in binary-mixture convection. Starting from the extended Ginzburg-Landau equations introduced earlier, we have derived equations of motion for interacting fronts connecting the conductive and the convective state. These equations reveal a repulsive interaction between the fronts which implies a new localization mechanism for waves. It is solely due to the long-wavelength mode specific to the extended Ginzburg-Landau equations. The stability properties of the resulting localized waves are in qualitative agreement with very recent experiments. (3) We have extended our investigation of domain structures to include their temporal evolution.

  9. A Model of the Spatio-temporal Dynamics of Drosophila Eye Disc Development.

    Science.gov (United States)

    Fried, Patrick; Sánchez-Aragón, Máximo; Aguilar-Hidalgo, Daniel; Lehtinen, Birgitta; Casares, Fernando; Iber, Dagmar

    2016-09-01

    Patterning and growth are linked during early development and have to be tightly controlled to result in a functional tissue or organ. During the development of the Drosophila eye, this linkage is particularly clear: the growth of the eye primordium mainly results from proliferating cells ahead of the morphogenetic furrow (MF), a moving signaling wave that sweeps across the tissue from the posterior to the anterior side, that induces proliferating cells anterior to it to differentiate and become cell cycle quiescent in its wake. Therefore, final eye disc size depends on the proliferation rate of undifferentiated cells and on the speed with which the MF sweeps across the eye disc. We developed a spatio-temporal model of the growing eye disc based on the regulatory interactions controlled by the signals Decapentaplegic (Dpp), Hedgehog (Hh) and the transcription factor Homothorax (Hth) and explored how the signaling patterns affect the movement of the MF and impact on eye disc growth. We used published and new quantitative data to parameterize the model. In particular, two crucial parameter values, the degradation rate of Hth and the diffusion coefficient of Hh, were measured. The model is able to reproduce the linear movement of the MF and the termination of growth of the primordium. We further show that the model can explain several mutant phenotypes, but fails to reproduce the previously observed scaling of the Dpp gradient in the anterior compartment.

  10. A Model of the Spatio-temporal Dynamics of Drosophila Eye Disc Development.

    Directory of Open Access Journals (Sweden)

    Patrick Fried

    2016-09-01

    Full Text Available Patterning and growth are linked during early development and have to be tightly controlled to result in a functional tissue or organ. During the development of the Drosophila eye, this linkage is particularly clear: the growth of the eye primordium mainly results from proliferating cells ahead of the morphogenetic furrow (MF, a moving signaling wave that sweeps across the tissue from the posterior to the anterior side, that induces proliferating cells anterior to it to differentiate and become cell cycle quiescent in its wake. Therefore, final eye disc size depends on the proliferation rate of undifferentiated cells and on the speed with which the MF sweeps across the eye disc. We developed a spatio-temporal model of the growing eye disc based on the regulatory interactions controlled by the signals Decapentaplegic (Dpp, Hedgehog (Hh and the transcription factor Homothorax (Hth and explored how the signaling patterns affect the movement of the MF and impact on eye disc growth. We used published and new quantitative data to parameterize the model. In particular, two crucial parameter values, the degradation rate of Hth and the diffusion coefficient of Hh, were measured. The model is able to reproduce the linear movement of the MF and the termination of growth of the primordium. We further show that the model can explain several mutant phenotypes, but fails to reproduce the previously observed scaling of the Dpp gradient in the anterior compartment.

  11. Swim-training changes the spatio-temporal dynamics of skeletogenesis in zebrafish larvae (Danio rerio.

    Directory of Open Access Journals (Sweden)

    Ansa W Fiaz

    Full Text Available Fish larvae experience many environmental challenges during development such as variation in water velocity, food availability and predation. The rapid development of structures involved in feeding, respiration and swimming increases the chance of survival. It has been hypothesized that mechanical loading induced by muscle forces plays a role in prioritizing the development of these structures. Mechanical loading by muscle forces has been shown to affect larval and embryonic bone development in vertebrates, but these investigations were limited to the appendicular skeleton. To explore the role of mechanical load during chondrogenesis and osteogenesis of the cranial, axial and appendicular skeleton, we subjected zebrafish larvae to swim-training, which increases physical exercise levels and presumably also mechanical loads, from 5 until 14 days post fertilization. Here we show that an increased swimming activity accelerated growth, chondrogenesis and osteogenesis during larval development in zebrafish. Interestingly, swim-training accelerated both perichondral and intramembranous ossification. Furthermore, swim-training prioritized the formation of cartilage and bone structures in the head and tail region as well as the formation of elements in the anal and dorsal fins. This suggests that an increased swimming activity prioritized the development of structures which play an important role in swimming and thereby increasing the chance of survival in an environment where water velocity increases. Our study is the first to show that already during early zebrafish larval development, skeletal tissue in the cranial, axial and appendicular skeleton is competent to respond to swim-training due to increased water velocities. It demonstrates that changes in water flow conditions can result into significant spatio-temporal changes in skeletogenesis.

  12. Spatio-temporal dynamics of global H5N1 outbreaks match bird migration patterns

    Directory of Open Access Journals (Sweden)

    Yali Si

    2009-11-01

    Full Text Available The global spread of highly pathogenic avian influenza H5N1 in poultry, wild birds and humans, poses a significant pandemic threat and a serious public health risk. An efficient surveillance and disease control system relies on the understanding of the dispersion patterns and spreading mechanisms of the virus. A space-time cluster analysis of H5N1 outbreaks was used to identify spatio-temporal patterns at a global scale and over an extended period of time. Potential mechanisms explaining the spread of the H5N1 virus, and the role of wild birds, were analyzed. Between December 2003 and December 2006, three global epidemic phases of H5N1 influenza were identified. These H5N1 outbreaks showed a clear seasonal pattern, with a high density of outbreaks in winter and early spring (i.e., October to March. In phase I and II only the East Asia Australian flyway was affected. During phase III, the H5N1 viruses started to appear in four other flyways: the Central Asian flyway, the Black Sea Mediterranean flyway, the East Atlantic flyway and the East Africa West Asian flyway. Six disease cluster patterns along these flyways were found to be associated with the seasonal migration of wild birds. The spread of the H5N1 virus, as demonstrated by the space-time clusters, was associated with the patterns of migration of wild birds. Wild birds may therefore play an important role in the spread of H5N1 over long distances. Disease clusters were also detected at sites where wild birds are known to overwinter and at times when migratory birds were present. This leads to the suggestion that wild birds may also be involved in spreading the H5N1 virus over short distances.

  13. Evolution of predator dispersal in relation to spatio-temporal prey dynamics: how not to get stuck in the wrong place!

    Directory of Open Access Journals (Sweden)

    Justin M J Travis

    Full Text Available The eco-evolutionary dynamics of dispersal are recognised as key in determining the responses of populations to environmental changes. Here, by developing a novel modelling approach, we show that predators are likely to have evolved to emigrate more often and become more selective over their destination patch when their prey species exhibit spatio-temporally complex dynamics. We additionally demonstrate that the cost of dispersal can vary substantially across space and time. Perhaps as a consequence of current environmental change, many key prey species are currently exhibiting major shifts in their spatio-temporal dynamics. By exploring similar shifts in silico, we predict that predator populations will be most vulnerable when prey dynamics shift from stable to complex. The more sophisticated dispersal rules, and greater variance therein, that evolve under complex dynamics will enable persistence across a broader range of prey dynamics than the rules which evolve under relatively stable prey conditions.

  14. Frontiers in Fluctuation Spectroscopy: Measuring protein dynamics and protein spatio-temporal connectivity

    Science.gov (United States)

    Digman, Michelle

    Fluorescence fluctuation spectroscopy has evolved from single point detection of molecular diffusion to a family of microscopy imaging correlation tools (i.e. ICS, RICS, STICS, and kICS) useful in deriving spatial-temporal dynamics of proteins in living cells The advantage of the imaging techniques is the simultaneous measurement of all points in an image with a frame rate that is increasingly becoming faster with better sensitivity cameras and new microscopy modalities such as the sheet illumination technique. A new frontier in this area is now emerging towards a high level of mapping diffusion rates and protein dynamics in the 2 and 3 dimensions. In this talk, I will discuss the evolution of fluctuation analysis from the single point source to mapping diffusion in whole cells and the technology behind this technique. In particular, new methods of analysis exploit correlation of molecular fluctuations originating from measurement of fluctuation correlations at distant points (pair correlation analysis) and methods that exploit spatial averaging of fluctuations in small regions (iMSD). For example the pair correlation fluctuation (pCF) analyses done between adjacent pixels in all possible radial directions provide a window into anisotropic molecular diffusion. Similar to the connectivity atlas of neuronal connections from the MRI diffusion tensor imaging these new tools will be used to map the connectome of protein diffusion in living cells. For biological reaction-diffusion systems, live single cell spatial-temporal analysis of protein dynamics provides a mean to observe stochastic biochemical signaling in the context of the intracellular environment which may lead to better understanding of cancer cell invasion, stem cell differentiation and other fundamental biological processes. National Institutes of Health Grant P41-RRO3155.

  15. Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

    Science.gov (United States)

    Jung, Minju; Hwang, Jungsik; Tani, Jun

    2015-01-01

    It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

  16. Spatio-temporal dynamics of a fish predator: Density-dependent and hydrographic effects on Baltic Sea cod population.

    Directory of Open Access Journals (Sweden)

    Valerio Bartolino

    Full Text Available Understanding the mechanisms of spatial population dynamics is crucial for the successful management of exploited species and ecosystems. However, the underlying mechanisms of spatial distribution are generally complex due to the concurrent forcing of both density-dependent species interactions and density-independent environmental factors. Despite the high economic value and central ecological importance of cod in the Baltic Sea, the drivers of its spatio-temporal population dynamics have not been analytically investigated so far. In this paper, we used an extensive trawl survey dataset in combination with environmental data to investigate the spatial dynamics of the distribution of the Eastern Baltic cod during the past three decades using Generalized Additive Models. The results showed that adult cod distribution was mainly affected by cod population size, and to a minor degree by small-scale hydrological factors and the extent of suitable reproductive areas. As population size decreases, the cod population concentrates to the southern part of the Baltic Sea, where the preferred more marine environment conditions are encountered. Using the fitted models, we predicted the Baltic cod distribution back to the 1970s and a temporal index of cod spatial occupation was developed. Our study will contribute to the management and conservation of this important resource and of the ecosystem where it occurs, by showing the forces shaping its spatial distribution and therefore the potential response of the population to future exploitation and environmental changes.

  17. Cdc42 and RhoA reveal different spatio-temporal dynamics upon local stimulation with Semaphorin-3A

    Directory of Open Access Journals (Sweden)

    Federico eIseppon

    2015-08-01

    Full Text Available Small RhoGTPases, such as Cdc42 and RhoA, are key players in integrating external cues and intracellular signaling pathways that regulate growth cone (GC motility. Indeed, Cdc42 is involved in actin polymerization and filopodia formation, whereas RhoA induces GC collapse and neurite retraction through actomyosin contraction. In this study we employed Förster Resonance Energy Transfer (FRET microscopy to study the spatio-temporal dynamics of Cdc42 and RhoA in GCs in response to local Semaphorin-3A stimulation obtained with lipid vesicles filled with Semaphorin-3A and positioned near the selected GC using optical tweezers. We found that Cdc42 and RhoA were activated at the leading edge of NG108-15 neuroblastoma cells during spontaneous cycles of protrusion and retraction, respectively. The release of Semaphorin-3A brought to a progressive activation of RhoA within 30 seconds from the stimulus in the central region of the GC that collapsed and retracted. In contrast, the same stimulation evoked waves of Cdc42 activation propagating away from the stimulated region. A more localized stimulation obtained with Sema3A coated beads placed on the GC, led to Cdc42 active waves that propagated in a retrograde manner with a mean period of 70 seconds, and followed by GC retraction. Therefore, Semaphorin-3A activates both Cdc42 and RhoA with a complex and different spatial-temporal dynamics.

  18. Spatio-Temporal Dynamics of Viruses are Differentially Affected by Parasitoids Depending on the Mode of Transmission

    Directory of Open Access Journals (Sweden)

    Elisa Viñuela

    2012-11-01

    Full Text Available Relationships between agents in multitrophic systems are complex and very specific. Insect-transmitted plant viruses are completely dependent on the behaviour and distribution patterns of their vectors. The presence of natural enemies may directly affect aphid behaviour and spread of plant viruses, as the escape response of aphids might cause a potential risk for virus dispersal. The spatio-temporal dynamics of Cucumber mosaic virus (CMV and Cucurbit aphid-borne yellows virus (CABYV, transmitted by Aphis gossypii in a non-persistent and persistent manner, respectively, were evaluated at short and long term in the presence and absence of the aphid parasitoid, Aphidius colemani. SADIE methodology was used to study the distribution patterns of both the virus and its vector, and their degree of association. Results suggested that parasitoids promoted aphid dispersion at short term, which enhanced CMV spread, though consequences of parasitism suggest potential benefits for disease control at long term. Furthermore, A. colemani significantly limited the spread and incidence of the persistent virus CABYV at long term. The impact of aphid parasitoids on the dispersal of plant viruses with different transmission modes is discussed.

  19. Imaging the spatio-temporal dynamics of supragranular activity in the rat somatosensory cortex in response to stimulation of the paws.

    Directory of Open Access Journals (Sweden)

    M L Morales-Botello

    Full Text Available We employed voltage-sensitive dye (VSD imaging to investigate the spatio-temporal dynamics of the responses of the supragranular somatosensory cortex to stimulation of the four paws in urethane-anesthetized rats. We obtained the following main results. (1 Stimulation of the contralateral forepaw evoked VSD responses with greater amplitude and smaller latency than stimulation of the contralateral hindpaw, and ipsilateral VSD responses had a lower amplitude and greater latency than contralateral responses. (2 While the contralateral stimulation initially activated only one focus, the ipsilateral stimulation initially activated two foci: one focus was typically medial to the focus activated by contralateral stimulation and was stereotaxically localized in the motor cortex; the other focus was typically posterior to the focus activated by contralateral stimulation and was stereotaxically localized in the somatosensory cortex. (3 Forepaw and hindpaw somatosensory stimuli activated large areas of the sensorimotor cortex, well beyond the forepaw and hindpaw somatosensory areas of classical somatotopic maps, and forepaw stimuli activated larger cortical areas with greater activation velocity than hindpaw stimuli. (4 Stimulation of the forepaw and hindpaw evoked different cortical activation dynamics: forepaw responses displayed a clear medial directionality, whereas hindpaw responses were much more uniform in all directions. In conclusion, this work offers a complete spatio-temporal map of the supragranular VSD cortical activation in response to stimulation of the paws, showing important somatotopic differences between contralateral and ipsilateral maps as well as differences in the spatio-temporal activation dynamics in response to forepaw and hindpaw stimuli.

  20. Spatio-Temporal Rule Mining

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo; Pedersen, Torben Bach

    2005-01-01

    Recent advances in communication and information technology, such as the increasing accuracy of GPS technology and the miniaturization of wireless communication devices pave the road for Location-Based Services (LBS). To achieve high quality for such services, spatio-temporal data mining techniques...... are needed. In this paper, we describe experiences with spatio-temporal rule mining in a Danish data mining company. First, a number of real world spatio-temporal data sets are described, leading to a taxonomy of spatio-temporal data. Second, the paper describes a general methodology that transforms...... the spatio-temporal rule mining task to the traditional market basket analysis task and applies it to the described data sets, enabling traditional association rule mining methods to discover spatio-temporal rules for LBS. Finally, unique issues in spatio-temporal rule mining are identified and discussed....

  1. Dynamics of spatio-temporal cellular structures Henri Bénard centenary review

    CERN Document Server

    Guyon, Etienne; Wesfreid, J E

    2006-01-01

    The impact of Benard's discovery on 20th century physics is crucial to any modern research area such as fluid dynamics, nonlinear dynamics, and non-equilibrium thermodynamics, just to name a few. This centenary review shows the broad scope and development including modern applications, edited and written by experts in the field.

  2. INFORMATION MINING OF SPATIO-TEMPORAL EVOLUTION OF LAKES BASED ON MULTIPLE DYNAMIC MEASUREMENTS

    Directory of Open Access Journals (Sweden)

    W. Feng

    2017-09-01

    Full Text Available Lakes are important water resources and integral parts of the natural ecosystem, and it is of great significance to study the evolution of lakes. The area of each lake increased and decreased at the same time in natural condition, only but the net change of lakes’ area is the result of the bidirectional evolution of lakes. In this paper, considering the effects of net fragmentation, net attenuation, swap change and spatial invariant part in lake evolution, a comprehensive evaluation indexes of lake dynamic evolution were defined,. Such degree contains three levels of measurement: 1 the swap dynamic degree (SDD reflects the space activity of lakes in the study period. 2 the attenuation dynamic degree (ADD reflects the net attenuation of lakes into non-lake areas. 3 the fragmentation dynamic degree (FDD reflects the trend of lakes to be divided and broken into smaller lakes. Three levels of dynamic measurement constitute the three-dimensional "Swap - attenuation – fragmentation" dynamic evolution measurement system of lakes. To show its effectiveness, the dynamic measurement was applied to lakes in Jianghan Plain, the middle Yangtze region of China for a more detailed analysis of lakes from 1984 to 2014. In combination with spatial-temporal location characteristics of lakes, the hidden information in lake evolution in the past 30 years can be revealed.

  3. Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese; Hansen, Lars Kai

    2016-01-01

    the functional dynamics of the brain. Solving the inverse problem of EEG is however highly ill-posed as there are many more potential locations of the EEG generators than EEG measurement points. Several well-known properties of brain dynamics can be exploited to alleviate this problem. More short ranging......Electroencephalography (EEG) can capture brain dynamics in high temporal resolution. By projecting the scalp EEG signal back to its origin in the brain also high spatial resolution can be achieved. Source localized EEG therefore has potential to be a very powerful tool for understanding...

  4. The spatio-temporal dynamic pattern of rural domestic solid waste discharge of China and its challenges.

    Science.gov (United States)

    Tian, Guangjin; Kong, Lingqiang; Liu, Xiaojuan; Yuan, Wenping

    2018-04-01

    At present, construction of rural domestic waste treatment facilities is seriously lagging, and in many cases, treatment facilities do not yet exist in some villages of China. Serious rural waste pollution has not only impacted the quality of surface water and groundwater but also the atmosphere and the living environment of farmers of China. There are relatively few studies of rural domestic waste pollution, especially with respect to the spatio-temporal dynamic pattern of rural domestic waste discharge. Using survey data and income per capita, we calculated rural domestic waste discharge per capita per day. From this, we calculated provincial rural domestic waste discharge. According to our study, rural domestic waste discharge was 1.42 × 10 8 t/year in 2000. This number increased to 2.3 × 10 8 t/year in 2006 and to 2.47 × 10 8 t/year in 2010. Rural domestic waste increased dramatically while the actual rural population and the proportion of the rural population declined. When examining the eight regions, the rural domestic waste discharge of northeastern China, Qinghai-Tibet, middle China, and southwestern China had increased dramatically, while that of northern China, southern China, and eastern China increased relatively slowly. The economies of northern China, southern China, and eastern China are more developed; their rural domestic waste discharge has been high since 2000 and has continued to increase slowly. In northeastern China, Qinghai-Tibet, middle China, and southwestern China, rural domestic waste discharge was low in 2000; however, in the ten-year period from 2000 to 2010, their rural domestic waste discharge increased dramatically.

  5. Tracing the spatio-temporal dynamics of endangered fin whales (Balaenoptera physalus) within baleen whale (Mysticeti) lineages: a mitogenomic perspective.

    Science.gov (United States)

    Yu, Jihyun; Nam, Bo-Hye; Yoon, Joon; Kim, Eun Bae; Park, Jung Youn; Kim, Heebal; Yoon, Sook Hee

    2017-12-01

    To explore the spatio-temporal dynamics of endangered fin whales (Balaenoptera physalus) within the baleen whale (Mysticeti) lineages, we analyzed 148 published mitochondrial genome sequences of baleen whales. We used a Bayesian coalescent approach as well as Bayesian inferences and maximum likelihood methods. The results showed that the fin whales had a single maternal origin, and that there is a significant correlation between geographic location and evolution of global fin whales. The most recent common female ancestor of this species lived approximately 9.88 million years ago (Mya). Here, North Pacific fin whales first appeared about 7.48 Mya, followed by a subsequent divergence in Southern Hemisphere approximately 6.63 Mya and North Atlantic about 4.42 Mya. Relatively recently, approximately 1.76 and 1.42 Mya, there were two additional occurrences of North Pacific populations; one originated from the Southern Hemisphere and the other from an uncertain location. The evolutionary rate of this species was 1.002 × 10 -3 substitutions/site/My. Our Bayesian skyline plot illustrates that the fin whale population has the rapid expansion event since ~ 2.5 Mya, during the Quaternary glaciation stage. Additionally, this study indicates that the fin whale has a sister group relationship with humpback whale (Meganoptera novaeangliae) within the baleen whale lineages. Of the 16 genomic regions, NADH5 showed the most powerful signal for baleen whale phylogenetics. Interestingly, fin whales have 16 species-specific amino acid residues in eight mitochondrial genes: NADH2, COX2, COX3, ATPase6, ATPase8, NADH4, NADH5, and Cytb.

  6. Spatio-temporal dynamics and laterality effects of face inversion, feature presence and configuration, and face outline

    Directory of Open Access Journals (Sweden)

    Ksenija eMarinkovic

    2014-11-01

    Full Text Available Although a crucial role of the fusiform gyrus in face processing has been demonstrated with a variety of methods, converging evidence suggests that face processing involves an interactive and overlapping processing cascade in distributed brain areas. Here we examine the spatio-temporal stages and their functional tuning to face inversion, presence and configuration of inner features, and face contour in healthy subjects during passive viewing. Anatomically-constrained magnetoencephalography (aMEG combines high-density whole-head MEG recordings and distributed source modeling with high-resolution structural MRI. Each person's reconstructed cortical surface served to constrain noise-normalized minimum norm inverse source estimates. The earliest activity was estimated to the occipital cortex at ~100 ms after stimulus onset and was sensitive to an initial coarse level visual analysis. Activity in the right-lateralized ventral temporal area (inclusive of the fusiform gyrus peaked at ~160ms and was largest to inverted faces. Images containing facial features in the veridical and rearranged configuration irrespective of the facial outline elicited intermediate level activity. The M160 stage may provide structural representations necessary for downstream distributed areas to process identity and emotional expression. However, inverted faces additionally engaged the left ventral temporal area at ~180 ms and were uniquely subserved by bilateral processing. This observation is consistent with the dual route model and spared processing of inverted faces in prosopagnosia. The subsequent deflection, peaking at ~240ms in the anterior temporal areas bilaterally, was largest to normal, upright faces. It may reflect initial engagement of the distributed network subserving individuation and familiarity. These results support dynamic models suggesting that processing of unfamiliar faces in the absence of a cognitive task is subserved by a distributed and

  7. Spatio-Temporal Dynamics of Asymptomatic Malaria: Bridging the Gap Between Annual Malaria Resurgences in a Sahelian Environment.

    Science.gov (United States)

    Coulibaly, Drissa; Travassos, Mark A; Tolo, Youssouf; Laurens, Matthew B; Kone, Abdoulaye K; Traore, Karim; Sissoko, Mody; Niangaly, Amadou; Diarra, Issa; Daou, Modibo; Guindo, Boureima; Rebaudet, Stanislas; Kouriba, Bourema; Dessay, Nadine; Piarroux, Renaud; Plowe, Christopher V; Doumbo, Ogobara K; Thera, Mahamadou A; Gaudart, Jean

    2017-12-01

    In areas of seasonal malaria transmission, the incidence rate of malaria infection is presumed to be near zero at the end of the dry season. Asymptomatic individuals may constitute a major parasite reservoir during this time. We conducted a longitudinal analysis of the spatio-temporal distribution of clinical malaria and asymptomatic parasitemia over time in a Malian town to highlight these malaria transmission dynamics. For a cohort of 300 rural children followed over 2009-2014, periodicity and phase shift between malaria and rainfall were determined by spectral analysis. Spatial risk clusters of clinical episodes or carriage were identified. A nested-case-control study was conducted to assess the parasite carriage factors. Malaria infection persisted over the entire year with seasonal peaks. High transmission periods began 2-3 months after the rains began. A cluster with a low risk of clinical malaria in the town center persisted in high and low transmission periods. Throughout 2009-2014, cluster locations did not vary from year to year. Asymptomatic and gametocyte carriage were persistent, even during low transmission periods. For high transmission periods, the ratio of asymptomatic to clinical cases was approximately 0.5, but was five times higher during low transmission periods. Clinical episodes at previous high transmission periods were a protective factor for asymptomatic carriage, but carrying parasites without symptoms at a previous high transmission period was a risk factor for asymptomatic carriage. Stable malaria transmission was associated with sustained asymptomatic carriage during dry seasons. Control strategies should target persistent low-level parasitemia clusters to interrupt transmission.

  8. Microscale spatio-temporal patterns of oxygen dynamics in permeable intertidal sediments (Skallingen, Denmark)

    DEFF Research Database (Denmark)

    Walpersdorf, Eva Christine; Andersen, Thorbjørn Joest; Elberling, Bo

     Intertidal permeable sediments are, even more than subtidal sediments (Cook et al. 2007), subject to extreme dynamics due to fast changing environ-mental conditions during inundation and emergence. In such systems, a quasi steady state is rarely reached. Integrative in-situ studies covering...

  9. Variation in predator foraging behavior changes predator-prey spatio-temporal dynamics

    Science.gov (United States)

    1. Foraging underlies the ability of all animals to acquire essential resources and, thus, provides a critical link to understanding population dynamics. A key issue is how variation in foraging behavior affects foraging efficiency and predator-prey interactions in spatially-heterogeneous environmen...

  10. Femtosecond laser spectroscopy of spins: Magnetization dynamics in thin magnetic films with spatio-temporal resolution

    International Nuclear Information System (INIS)

    Carpene, E.; Mancini, E.; Dallera, C.; Puppin, E.; De Silvestri, S.

    2010-01-01

    Based on the Magneto-Optical Kerr Effect (MOKE), we have developed an experimental set-up that allows us to fully characterize the magnetization dynamics in thin magnetic films by measuring all three real space components of the magnetization vector M. By means of the pump-probe technique it is possible to extract the time dependence of each individual projection with sub-picosecond resolution. This method has been exploited to investigate the temporal evolution of the magnetization (modulus and orientation) induced by an ultrashort laser pulse in thin epitaxial iron films. According to our results, we deduced that the initial, sub-picosecond demagnetization is established at the electronic level through electron-magnon excitations. The subsequent dynamics is characterized by a precessional motion on the 100 ps time scale, around an effective, time-dependent magnetic field. Following the full dynamics of M, the temporal evolution of the magneto-crystalline anisotropy constant can be unambiguously determined, providing the experimental evidence that the precession is triggered by the rapid, optically-induced misalignment between the magnetization vector and the effective magnetic field. These results suggest a possible pathway toward the ultrarapid switching of the magnetization.

  11. Spatio-temporal dynamics of maize yield water constraints under climate change in Spain.

    Science.gov (United States)

    Ferrero, Rosana; Lima, Mauricio; Gonzalez-Andujar, Jose Luis

    2014-01-01

    Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent "hot-spots" in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity.

  12. Spatio-temporal dynamics of word selection in speech production: Insights from electrocorticography

    Directory of Open Access Journals (Sweden)

    Stephanie K Ries

    2015-04-01

    Our results suggest that the posterior inferior LTC is involved in word selection as semantic concepts become available. Posterior medial and left PFC regions may be involved in trial-by-trial top-down control over LTC to help overcome interference caused by semantically-related alternatives in word selection. The single-case result supports this hypothesis and suggests that the posterior medial PFC plays a causal role in resolving this interference in word selection. Lastly, the sensitivity to semantic interference of the post-vocal onset posterior LTC activity suggests the semantic interference effect does not only reflect word selection difficulty but is also present at post-selection stages such as verbal response monitoring. In sum, this study reveals a dynamic network of interacting brain regions that support word selection in language production.

  13. Spatio-temporal dynamics of maize yield water constraints under climate change in Spain.

    Directory of Open Access Journals (Sweden)

    Rosana Ferrero

    Full Text Available Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent "hot-spots" in future climate change projections. Our new approach allowed us to: (1 evaluate new structural properties such as the stability of crop yield dynamics, (2 detect nonlinear responses to climate change (thresholds and discontinuities, challenging the usual linear way of thinking, and (3 examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity.

  14. Beach-dune dynamics: Spatio-temporal patterns of aeolian sediment transport under complex offshore airflow

    Science.gov (United States)

    Lynch, K.; Jackson, D.; Delgado-Fernandez, I.; Cooper, J. A.; Baas, A. C.; Beyers, M.

    2010-12-01

    This study examines sand transport and wind speed across a beach at Magilligan Strand, Northern Ireland, under offshore wind conditions. Traditionally the offshore component of local wind regimes has been ignored when quantifying beach-dune sediment budgets, with the sheltering effect of the foredune assumed to prohibit grain entrainment on the adjoining beach. Recent investigations of secondary airflow patterns over coastal dunes have suggested this may not be the case, that the turbulent nature of the airflow in these zones enhances sediment transport potential. Beach sediment may be delivered to the dune toe by re-circulating eddies under offshore winds in coastal areas, which may explain much of the dynamics of aeolian dunes on coasts where the dominant wind direction is offshore. The present study investigated aeolian sediment transport patterns under an offshore wind event. Empirical data were collected using load cell traps, for aeolian sediment transport, co-located with 3-D ultrasonic anemometers. The instrument positioning on the sub-aerial beach was informed by prior analysis of the airflow patterns using computational fluid dynamics. The array covered a total beach area of 90 m alongshore by 65 m cross-shore from the dune crest. Results confirm that sediment transport occurred in the ‘sheltered’ area under offshore winds. Over short time and space scales the nature of the transport is highly complex; however, preferential zones for sand entrainment may be identified. Alongshore spatial heterogeneity of sediment transport seems to show a relationship to undulations in the dune crest, while temporal and spatial variations may also be related to the position of the airflow reattachment zone. These results highlight the important feedbacks between flow characteristics and transport in a complex three dimensional surface.

  15. Spatio-temporal dynamics of action-effect associations in oculomotor control.

    Science.gov (United States)

    Riechelmann, Eva; Pieczykolan, Aleksandra; Horstmann, Gernot; Herwig, Arvid; Huestegge, Lynn

    2017-10-01

    While there is ample evidence that actions are guided by anticipating their effects (ideomotor control) in the manual domain, much less is known about the underlying characteristics and dynamics of effect-based oculomotor control. Here, we address three open issues. 1) Is action-effect anticipation in oculomotor control reflected in corresponding spatial saccade characteristics in inanimate environments? 2) Does the previously reported dependency of action latency on the temporal effect delay (action-effect interval) also occur in the oculomotor domain? 3) Which temporal effect delay is optimally suited to develop strong action-effect associations over time in the oculomotor domain? Participants executed left or right free-choice saccades to peripheral traffic lights, causing an (immediate or delayed) action-contingent light switch in the upper vs. lower part of the traffic light. Results indicated that saccades were spatially shifted toward the location of the upcoming change, indicating anticipation of the effect (location). Saccade latency was affected by effect delay, suggesting that corresponding time information is integrated into event representations. Finally, delayed (vs. immediate) effects were more effective in strengthening action-effect associations over the course of the experiment, likely due to greater saliency of perceptual changes occurring during target fixation as opposed to changes during saccades (saccadic suppression). Overall, basic principles underlying ideomotor control appear to generalize to the oculomotor domain. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Spatio-temporal dynamics of the mirror neuron system during social intentions.

    Science.gov (United States)

    Cacioppo, Stephanie; Bolmont, Mylene; Monteleone, George

    2017-10-27

    Previous research has shown that specific goals and intentions influence a person's allocation of social attention. From a neural viewpoint, a growing body of evidence suggests that the inferior fronto-parietal network, including the mirror neuron system, plays a role in the planning and the understanding of motor intentions. However, it is unclear whether and when the mirror neuron system plays a role in social intentions. Combining a behavioral task with electrical neuroimaging in 22 healthy male participants, the current study investigates whether the temporal brain dynamic of the mirror neuron system differs during two types of social intentions i.e., lust vs. romantic intentions. Our results showed that 62% of the stimuli evoking lustful intentions also evoked romantic intentions, and both intentions were sustained by similar activations of the inferior frontal gyrus and the inferior parietal lobule/angular gyrus for the first 432 ms after stimulus onset. Intentions to not love or not lust, on the other hand, were characterized by earlier differential activations of the inferior fronto-parietal network i.e., as early as 244 ms after stimulus onset. These results suggest that the mirror neuron system may not only code for the motor correlates of intentions, but also for the social meaning of intentions and its valence at both early/automatic and later/more elaborative stages of information processing.

  17. Spatio-temporal dynamics of surface water quality in a Portuguese peri-urban catchment

    Science.gov (United States)

    Ferreira, Carla; Walsh, Rory; Coelho, Celeste; Ferreira, António

    2016-04-01

    Urban development poses great pressure on water resources, but the impact of different land-uses on streamwater quality in partly urbanized catchments is not well understood. Focussing on a Portuguese peri-urban catchment, this paper explores the impact of a mosaic of different urban and non-urban land-uses on streamwater quality, and the influence of a seasonal Mediterranean climate on pollutant dynamics. The catchment has a 40% urban cover, dispersed amongst patches of woodland (56%) and agricultural fields (4%). Apart from the catchment outlet, streamwater quality was assessed at three sub-catchment sites: (i) Porto Bordalo, encompassing a 39% urban area with a new major road; (ii) Espírito Santo, draining a sub-catchment with 49% urban cover, mostly comprising detached houses surrounded by gardens; and (iii) Quinta, with a 25% urban cover. The Porto Bordalo sub-catchment is underlain by limestone, whereas the Espírito Santo and Quinta sub-catchments overlie sandstone. Water quality variables (notably nutrients, heavy metals and COD) were assessed for samples collected at different stages in the storm hydrograph responses to ten rainfall events occurring between October 2011 and March 2013. Urban areas had great impacts on COD, with highest median concentrations in Espírito Santo (18.0 mg L-1) and lowest in Quinta (9.5 mgL-1). In Espírito Santo, the management of gardens triggered greatest median concentrations of N-NO3 (1.46 mgL-1, purban patterns and storm drainage system, should help enable urban planners to minimize adverse impacts of urbanization on water quality.

  18. Stochastic spatio-temporal model of coral cover as a function of herbivorous grazers, water quality, and coral demographics

    Science.gov (United States)

    Neuhausler, R.; Robinson, M.; Bruna, M.

    2017-12-01

    Over the last 60 years we have seen an increased amount of ecological regime shifts in tropical coastal zones, from coral reefs to macroalgae dominated states, as a result of natural and anthropogenic stresses. However, these shifts are not always immediate- macroalgae are generally present in coral reefs, with their distribution regulated by herbivorous fish. This is especially true in Moorea, French Polynesia, where macroalgae are shown to flourish in spaces that provide refuge from roaming herbivores. While there are currently modeling efforts in projecting ecological regime shifts in Moorea, temporal deterministic models have been utilized, which fail to capture metastability between multiple steady states and can have issues when dealing with very small populations. To address these concerns, we build on these models to account for spatial variations and individual organisms, as well as stochasticity. Our model can project the percent cover of coral, macroalgae, and algae turf as a function of herbivorous grazers, water quality, and coral demographics. Grazers, included as individual fish (particles), evolve according to a kinetic model and interact with neighbouring benthic assemblages, represented as nodes. Water quality and coral demographics are input parameters that can vary over time, allowing our model to be run for temporally changing scenarios and to be adjusted for different reefs. We plan to engage with previous Moorea Reef Resilience Models through a comparative analysis of our models' outcomes and existing Moorea data. Coupling projective models with available data is useful for informing environmental policy and advancing the modeling field.

  19. Quantitative methods for stochastic high frequency spatio-temporal and non-linear analysis: Assessing health effects of exposure to extreme ambient temperature

    Science.gov (United States)

    Liss, Alexander

    Extreme weather events, such as heat waves and cold spells, cause substantial excess mortality and morbidity in the vulnerable elderly population, and cost billions of dollars. The accurate and reliable assessment of adverse effects of extreme weather events on human health is crucial for environmental scientists, economists, and public health officials to ensure proper protection of vulnerable populations and efficient allocation of scarce resources. However, the methodology for the analysis of large national databases is yet to be developed. The overarching objective of this dissertation is to examine the effect of extreme weather on the elderly population of the Conterminous US (ConUS) with respect to seasonality in temperature in different climatic regions by utilizing heterogeneous high frequency and spatio-temporal resolution data. To achieve these goals the author: 1) incorporated dissimilar stochastic high frequency big data streams and distinct data types into the integrated data base for use in analytical and decision support frameworks; 2) created an automated climate regionalization system based on remote sensing and machine learning to define climate regions for the Conterminous US; 3) systematically surveyed the current state of the art and identified existing gaps in the scientific knowledge; 4) assessed the dose-response relationship of exposure to temperature extremes on human health in relatively homogeneous climate regions using different statistical models, such as parametric and non-parametric, contemporaneous and asynchronous, applied to the same data; 5) assessed seasonal peak timing and synchronization delay of the exposure and the disease within the framework of contemporaneous high frequency harmonic time series analysis and modification of the effect by the regional climate; 6) modeled using hyperbolic functional form non-linear properties of the effect of exposure to extreme temperature on human health. The proposed climate

  20. Statistical methods for spatio-temporal systems

    CERN Document Server

    Finkenstadt, Barbel

    2006-01-01

    Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities.Contributed by leading researchers in the field, each self-contained chapter starts with an introduction of the topic and progresses to recent research results. Presenting specific examples of epidemic data of bovine tuberculosis, gastroenteric disease, and the U.K. foot-and-mouth outbreak, the first chapter uses stochastic models, such as point process models, to provide the probabilistic backbone that facilitates statistical inference from data. The next chapter discusses the critical issue of modeling random growth objects in diverse biological systems, such as bacteria colonies, tumors, and plant populations. The subsequent chapter examines data transformation tools using examples from ecology and air quality data, followed by a chapter on space-time co...

  1. The Voronoi spatio-temporal data structure

    Science.gov (United States)

    Mioc, Darka

    2002-04-01

    Current GIS models cannot integrate the temporal dimension of spatial data easily. Indeed, current GISs do not support incremental (local) addition and deletion of spatial objects, and they can not support the temporal evolution of spatial data. Spatio-temporal facilities would be very useful in many GIS applications: harvesting and forest planning, cadastre, urban and regional planning, and emergency planning. The spatio-temporal model that can overcome these problems is based on a topological model---the Voronoi data structure. Voronoi diagrams are irregular tessellations of space, that adapt to spatial objects and therefore they are a synthesis of raster and vector spatial data models. The main advantage of the Voronoi data structure is its local and sequential map updates, which allows us to automatically record each event and performed map updates within the system. These map updates are executed through map construction commands that are composed of atomic actions (geometric algorithms for addition, deletion, and motion of spatial objects) on the dynamic Voronoi data structure. The formalization of map commands led to the development of a spatial language comprising a set of atomic operations or constructs on spatial primitives (points and lines), powerful enough to define the complex operations. This resulted in a new formal model for spatio-temporal change representation, where each update is uniquely characterized by the numbers of newly created and inactivated Voronoi regions. This is used for the extension of the model towards the hierarchical Voronoi data structure. In this model, spatio-temporal changes induced by map updates are preserved in a hierarchical data structure that combines events and corresponding changes in topology. This hierarchical Voronoi data structure has an implicit time ordering of events visible through changes in topology, and it is equivalent to an event structure that can support temporal data without precise temporal

  2. DynaPop-X: A population dynamics model applied to spatio-temporal exposure assessment - Implementation aspects from the CRISMA project

    Science.gov (United States)

    Aubrecht, Christoph; Steinnocher, Klaus; Humer, Heinrich; Huber, Hermann

    2014-05-01

    In the context of proactive disaster risk as well as immediate situational crisis management knowledge of locational social aspects in terms of spatio-temporal population distribution dynamics is considered among the most important factors for disaster impact minimization (Aubrecht et al., 2013a). This applies to both the pre-event stage for designing appropriate preparedness measures and to acute crisis situations when an event chain actually unfolds for efficient situation-aware response. The presented DynaPop population dynamics model is developed at the interface of those interlinked crisis stages and aims at providing basic input for social impact evaluation and decision support in crisis management. The model provides the starting point for assessing population exposure dynamics - thus here labeled as DynaPop-X - which can either be applied in a sense of illustrating the changing locations and numbers of affected people at different stages during an event or as ex-ante estimations of probable and maximum expected clusters of affected population (Aubrecht et al., 2013b; Freire & Aubrecht, 2012). DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation (Ahola et al., 2007; Bhaduri, 2008; Cockings et al., 2010). We will present ongoing developments particularly focusing on the implementation logic of the model using the emikat software tool, a data management system initially designed for inventorying and analysis of spatially resolved regional air pollutant emission scenarios. This study was performed in the framework of the EU CRISMA project. CRISMA is funded from the European Community's Seventh Framework Programme FP7/2007-2013 under grant agreement no. 284552. REFERENCES Ahola, T., Virrantaus, K., Krisp, J

  3. Trends in spatio-temporal dynamics of visceral leishmaniasis cases in a highly-endemic focus of Bihar, India: an investigation based on GIS tools.

    Science.gov (United States)

    Mandal, Rakesh; Kesari, Shreekant; Kumar, Vijay; Das, Pradeep

    2018-04-02

    Visceral leishmaniasis (VL) in Bihar State (India) continues to be endemic, despite the existence of effective treatment and a vector control program to control disease morbidity. A clear understanding of spatio-temporal distribution of VL may improve surveillance and control implementation. This study explored the trends in spatio-temporal dynamics of VL endemicity at a meso-scale level in Vaishali District, based on geographical information systems (GIS) tools and spatial statistical analysis. A GIS database was used to integrate the VL case data from the study area between 2009 and 2014. All cases were spatially linked at a meso-scale level. Geospatial techniques, such as GIS-layer overlaying and mapping, were employed to visualize and detect the spatio-temporal patterns of a VL endemic outbreak across the district. The spatial statistic Moran's I Index (Moran's I) was used to simultaneously evaluate spatial-correlation between endemic villages and the spatial distribution patterns based on both the village location and the case incidence rate (CIR). Descriptive statistics such as mean, standard error, confidence intervals and percentages were used to summarize the VL case data. There were 624 endemic villages with 2719 (average 906 cases/year) VL cases during 2012-2014. The Moran's I revealed a cluster pattern (P < 0.05) of CIR distribution at the meso-scale level. On average, 68 villages were newly-endemic each year. Of which 93.1% of villages' endemicity were found to have occurred on the peripheries of the previous year endemic villages. The mean CIR of the endemic villages that were peripheral to the following year newly-endemic villages, compared to all endemic villages of the same year, was higher (P < 0.05). The results show that the VL endemicity of new villages tends to occur on the periphery of villages endemic in the previous year. High-CIR plays a major role in the spatial dispersion of the VL cases between non-endemic and endemic villages

  4. Spatio-Temporal Dynamics of Exploited Groundfish Species Assemblages Faced to Environmental and Fishing Forcings: Insights from the Mauritanian Exclusive Economic Zone.

    Directory of Open Access Journals (Sweden)

    Saïkou Oumar Kidé

    Full Text Available Environmental changes and human activities can have strong impacts on biodiversity and ecosystem functioning. This study investigates how, from a quantitative point of view, simultaneously both environmental and anthropogenic factors affect species composition and abundance of exploited groundfish assemblages (i.e. target and non-target species at large spatio-temporal scales. We aim to investigate (1 the spatial and annual stability of groundfish assemblages, (2 relationships between these assemblages and structuring factors in order to better explain the dynamic of the assemblages' structure. The Mauritanian Exclusive Economic Zone (MEEZ is of particular interest as it embeds a productive ecosystem due to upwelling, producing abundant and diverse resources which constitute an attractive socio-economic development. We applied the multi-variate and multi-table STATICO method on a data set consisting of 854 hauls collected during 14-years (1997-2010 from scientific trawl surveys (species abundance, logbooks of industrial fishery (fishing effort, sea surface temperature and chlorophyll a concentration as environmental variables. Our results showed that abiotic factors drove four main persistent fish assemblages. Overall, chlorophyll a concentration and sea surface temperature mainly influenced the structure of assemblages of coastal soft bottoms and those of the offshore near rocky bottoms where upwellings held. While highest levels of fishing effort were located in the northern permanent upwelling zone, effects of this variable on species composition and abundances of assemblages were relatively low, even if not negligible in some years and areas. The temporal trajectories between environmental and fishing conditions and assemblages did not match for all the entire time series analyzed in the MEEZ, but interestingly for some specific years and areas. The quantitative approach used in this work may provide to stakeholders, scientists and fishers a

  5. Spatio-temporal spawning and larval dynamics of a zebra mussel (Dreissena polymorpha) population in a North Texas Reservoir: implications for invasions in the southern United States

    Science.gov (United States)

    Churchill, Christopher John

    2013-01-01

    Zebra mussels were first observed in Texas in 2009 in a reservoir (Lake Texoma) on the Texas-Oklahoma border. In 2012, an established population was found in a near-by reservoir, Ray Roberts Lake, and in June 2013, settled mussels were detected in a third north Texas reservoir, Lake Lewisville. An established population was detected in Belton Lake in September 2013. With the exception of Louisiana, these occurrences in Texas mark the current southern extent of the range of this species in the United States. Previous studies indicate that zebra mussel populations could be affected by environmental conditions, especially increased temperatures and extreme droughts, which are characteristic of surface waters of the southern and southwestern United States. Data collected during the first three years (2010–12) of a long-term monitoring program were analyzed to determine if spatio-temporal zebra mussel spawning and larval dynamics were related to physicochemical water properties in Lake Texoma. Reproductive output of the local population was significantly related to water temperature and lake elevation. Estimated mean date of first spawn in Lake Texoma was approximately 1.5 months earlier and peak veliger densities were observed two months earlier than in Lake Erie. Annual maximum veliger density declined significantly during the study period (p mussels in littoral zones. Veliger spatial distributions were associated with physicochemical stratification characteristics. Veligers were observed in the deepest oxygenated water after lake stratification, which occurred in late spring. Results of this study indicate environmental conditions can influence variability of population sizes and spatial distributions of zebra mussels along the current southern frontier of their geographic range. Although the future population size trajectory and geographic range are uncertain, increased temperatures and intermittent, extreme droughts likely will affect spatio-temporal dynamics of

  6. Spatio-temporal Assessment of Land Use/ Land Cover Dynamics and Urban Heat Island of Jaipur City using Satellite Data

    Science.gov (United States)

    Jalan, S.; Sharma, K.

    2014-11-01

    Urban Heat Island (UHI) refers to the phenomena of higher surface temperature occurring in urban areas as compared to the surrounding countryside attributable to urbanization. Spatio-temporal changes in UHI can be quantified through Land Surface Temperature (LST) derived from satellite imageries. Spatial variations in LST occur due to complexity of land surface - combination of impervious surface materials, vegetation, exposed soils as well as water surfaces. Jaipur city has observed rapid urbanization over the last decade. Due to rising population pressure the city has expanded considerably in areal extent and has also observed substantial land use/land cover (LULC) changes. The paper aims to determine changes in the LST and UHI phenomena for Jaipur city over the period from 2000 to 2011 and analyzes the spatial distribution and temporal variation of LST in context of changes in LULC. Landsat 7 ETM+ (2000) and Landsat 5 TM (2011) images of summer season have been used. Results reveal that Jaipur city has witnessed considerable growth in built up area at the cost of greener patches over the last decade, which has had clear impact on variation in LST. There has been an average rise of 2.99 °C in overall summer temperature. New suburbs of the city record 2° to 4 °C increase in LST. LST change is inversely related to change in vegetation cover and positively related to extent of built up area. The study concludes that UHI of Jaipur city has intensified and extended over new areas.

  7. Dynamic Assessment on the Landscape Patterns and Spatio-temporal Change in the mainstream of Tarim River

    Science.gov (United States)

    Zhang, Hui; Xue, Lianqing; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Wei, Guanghui

    2018-01-01

    The Tarim River (TR), as the longest inland river at an arid area in China, is a typical regions of vegetation variation research and plays a crucial role in the sustainable development of regional ecological environment. In this paper, the newest dataset of MODND1M NDVI, at a resolution of 500m, were applied to calculate vegetation index in growing season during the period 2000-2015. Using a vegetation coverage index, a trend line analysis, and the local spatial autocorrelation analysis, this paper investigated the landscape patterns and spatio-temporal variation of vegetation coverage at regional and pixel scales over mainstream of the Tarim River, Xinjiang. The results showed that (1) The bare land area on both sides of Tarim River appeared to have a fluctuated downward trend and there were two obvious valley values in 2005 and 2012. (2) Spatially, the vegetation coverage improved areas is mostly distributed in upstream and the degraded areas is mainly distributed in the left bank of midstream and the end of Tarim River during 2000-2005. (3) The local spatial auto-correlation analysis revealed that vegetation coverage was spatially positive autocorrelated and spatial concentrated. The high-high self-related areas are mainly distributed in upstream, where vegetation cover are relatively good, and the low-low self-related areas are mostly with lower vegetation cover in the lower reaches of Tarim River.

  8. Modelling spatio-temporal variability of Mytilus edulis (L.) growth by forcing a dynamic energy budget model with satellite-derived environmental data

    Science.gov (United States)

    Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline

    2011-11-01

    In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.

  9. A million-plus neuron model of the hippocampal dentate gyrus: Dependency of spatio-temporal network dynamics on topography.

    Science.gov (United States)

    Hendrickson, Phillip J; Yu, Gene J; Song, Dong; Berger, Theodore W

    2015-01-01

    This paper describes a million-plus granule cell compartmental model of the rat hippocampal dentate gyrus, including excitatory, perforant path input from the entorhinal cortex, and feedforward and feedback inhibitory input from dentate interneurons. The model includes experimentally determined morphological and biophysical properties of granule cells, together with glutamatergic AMPA-like EPSP and GABAergic GABAA-like IPSP synaptic excitatory and inhibitory inputs, respectively. Each granule cell was composed of approximately 200 compartments having passive and active conductances distributed throughout the somatic and dendritic regions. Modeling excitatory input from the entorhinal cortex was guided by axonal transport studies documenting the topographical organization of projections from subregions of the medial and lateral entorhinal cortex, plus other important details of the distribution of glutamatergic inputs to the dentate gyrus. Results showed that when medial and lateral entorhinal cortical neurons maintained Poisson random firing, dentate granule cells expressed, throughout the million-cell network, a robust, non-random pattern of spiking best described as spatiotemporal "clustering". To identify the network property or properties responsible for generating such firing "clusters", we progressively eliminated from the model key mechanisms such as feedforward and feedback inhibition, intrinsic membrane properties underlying rhythmic burst firing, and/or topographical organization of entorhinal afferents. Findings conclusively identified topographical organization of inputs as the key element responsible for generating a spatio-temporal distribution of clustered firing. These results uncover a functional organization of perforant path afferents to the dentate gyrus not previously recognized: topography-dependent clusters of granule cell activity as "functional units" that organize the processing of entorhinal signals.

  10. Nonlinear spatio-temporal filtering of dynamic PET data using a four-dimensional Gaussian filter and expectation-maximization deconvolution

    International Nuclear Information System (INIS)

    Floberg, J M; Holden, J E

    2013-01-01

    We introduce a method for denoising dynamic PET data, spatio-temporal expectation-maximization (STEM) filtering, that combines four-dimensional Gaussian filtering with EM deconvolution. The initial Gaussian filter suppresses noise at a broad range of spatial and temporal frequencies and EM deconvolution quickly restores the frequencies most important to the signal. We aim to demonstrate that STEM filtering can improve variance in both individual time frames and in parametric images without introducing significant bias. We evaluate STEM filtering with a dynamic phantom study, and with simulated and human dynamic PET studies of a tracer with reversible binding behaviour, [C-11]raclopride, and a tracer with irreversible binding behaviour, [F-18]FDOPA. STEM filtering is compared to a number of established three and four-dimensional denoising methods. STEM filtering provides substantial improvements in variance in both individual time frames and in parametric images generated with a number of kinetic analysis techniques while introducing little bias. STEM filtering does bias early frames, but this does not affect quantitative parameter estimates. STEM filtering is shown to be superior to the other simple denoising methods studied. STEM filtering is a simple and effective denoising method that could be valuable for a wide range of dynamic PET applications. (paper)

  11. Does my brain want what my eyes like? - How food liking and choice influence spatio-temporal brain dynamics of food viewing.

    Science.gov (United States)

    Bielser, Marie-Laure; Crézé, Camille; Murray, Micah M; Toepel, Ulrike

    2016-12-01

    How food valuation and decision-making influence the perception of food is of major interest to better understand food intake behavior and, by extension, body weight management. Our study investigated behavioral responses and spatio-temporal brain dynamics by means of visual evoked potentials (VEPs) in twenty-two normal-weight participants when viewing pairs of food photographs. Participants rated how much they liked each food item (valuation) and subsequently chose between the two alternative food images. Unsurprisingly, strongly liked foods were also chosen most often. Foods were rated faster as strongly liked than as mildly liked or disliked irrespective of whether they were subsequently chosen over an alternative. Moreover, strongly liked foods were subsequently also chosen faster than the less liked alternatives. Response times during valuation and choice were positively correlated, but only when foods were liked; the faster participants rated foods as strongly liked, the faster they were in choosing the food item over an alternative. VEP modulations by the level of liking attributed as well as the subsequent choice were found as early as 135-180ms after food image onset. Analyses of neural source activity patterns over this time interval revealed an interaction between liking and the subsequent choice within the insula, dorsal frontal and superior parietal regions. The neural responses to food viewing were found to be modulated by the attributed level of liking only when foods were chosen, not when they were dismissed for an alternative. Therein, the responses to disliked foods were generally greater than those to foods that were liked more. Moreover, the responses to disliked but chosen foods were greater than responses to disliked foods which were subsequently dismissed for an alternative offer. Our findings show that the spatio-temporal brain dynamics to food viewing are immediately influenced both by how much foods are liked and by choices taken on them

  12. Spatio-Temporal Data Construction

    Directory of Open Access Journals (Sweden)

    Hai Ha Le

    2013-08-01

    Full Text Available On the route to a spatio-temporal geoscience information system, an appropriate data model for geo-objects in space and time has been developed. In this model, geo-objects are represented as sequences of geometries and properties with continuous evolution in each time interval. Because geomodeling software systems usually model objects at specific time instances, we want to interpolate the geometry and properties from two models of an object with only geometrical constraints (no physical or mechanical constraints. This process is called spatio-temporal data construction or morphological interpolation of intermediate geometries. This paper is strictly related to shape morphing, shape deformation, cross-parameterization and compatible remeshing and is only concerned with geological surfaces. In this study, two main sub-solutions construct compatible meshes and find trajectories in which vertices of the mesh evolve. This research aims to find an algorithm to construct spatio-temporal data with some constraints from the geosciences, such as cutting surfaces by faulting or fracturing phenomena and evolving boundaries attached to other surfaces. Another goal of this research is the implementation of the algorithm in a software product, namely a gOcad plug-in. The four main procedures of the algorithm are cutting the surfaces, setting up constraints, partitioning and calculating the parameterizations and trajectories. The software has been tested to construct data for a salt dome and other surfaces in regard to the geological processes of faulting, deposition and erosion. The result of this research is an algorithm and software for the construction of spatio-temporal data.

  13. Compressing spatio-temporal trajectories

    DEFF Research Database (Denmark)

    Gudmundsson, Joachim; Katajainen, Jyrki; Merrick, Damian

    2009-01-01

    such that the most common spatio-temporal queries can still be answered approximately after the compression has taken place. In the process, we develop an implementation of the Douglas–Peucker path-simplification algorithm which works efficiently even in the case where the polygonal path given as input is allowed...... to self-intersect. For a polygonal path of size n, the processing time is O(nlogkn) for k=2 or k=3 depending on the type of simplification....

  14. Modeling the spatio-temporal dynamics of porcine reproductive & respiratory syndrome cases at farm level using geographical distance and pig trade network matrices.

    Science.gov (United States)

    Amirpour Haredasht, Sara; Polson, Dale; Main, Rodger; Lee, Kyuyoung; Holtkamp, Derald; Martínez-López, Beatriz

    2017-06-07

    Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating infectious diseases for the swine industry. A better understanding of the disease dynamics and the transmission pathways under diverse epidemiological scenarios is a key for the successful PRRS control and elimination in endemic settings. In this paper we used a two step parameter-driven (PD) Bayesian approach to model the spatio-temporal dynamics of PRRS and predict the PRRS status on farm in subsequent time periods in an endemic setting in the US. For such purpose we used information from a production system with 124 pig sites that reported 237 PRRS cases from 2012 to 2015 and from which the pig trade network and geographical location of farms (i.e., distance was used as a proxy of airborne transmission) was available. We estimated five PD models with different weights namely: (i) geographical distance weight which contains the inverse distance between each pair of farms in kilometers, (ii) pig trade weight (PT ji ) which contains the absolute number of pig movements between each pair of farms, (iii) the product between the distance weight and the standardized relative pig trade weight, (iv) the product between the standardized distance weight and the standardized relative pig trade weight, and (v) the product of the distance weight and the pig trade weight. The model that included the pig trade weight matrix provided the best fit to model the dynamics of PRRS cases on a 6-month basis from 2012 to 2015 and was able to predict PRRS outbreaks in the subsequent time period with an area under the ROC curve (AUC) of 0.88 and the accuracy of 85% (105/124). The result of this study reinforces the importance of pig trade in PRRS transmission in the US. Methods and results of this study may be easily adapted to any production system to characterize the PRRS dynamics under diverse epidemic settings to more timely support decision-making.

  15. Quantifying the Spatio-Temporal Dynamics of Rural Settlements and the Associated Impacts on Land Use in an Undeveloped Area of China

    Directory of Open Access Journals (Sweden)

    Jie Wang

    2018-05-01

    Full Text Available Rapid urbanization and economic growth in China have accelerated changes in rural settlements and associated land-use types that are expected to alter ecological services and the environment. Relevant studies of the dynamics of rural settlements and corresponding rural land-use changes are in short supply, however, especially in undeveloped areas in China. This study, therefore, investigated the spatio-temporal dynamics of rural settlements and their impacts on other land-use types by using 30 m rural settlement status and dynamic maps from the end of the 1980s to 2010. These maps were generated by visual interpretation with strict product quality control and accuracy. Henan province was selected as a case study of undeveloped regions in China. We examined in particular how the expansion of rural settlements affected cultivated lands and the processes of rural settlement urbanization. This study looked at three periods: the end of the 1980s–2000, 2000–2010, and the end of the 1980s–2010, with two spatial scales of province and prefecture city. Major findings about the rural settlements in Henan from the end of the 1980s to 2010 include (1 the area of rural settlements grew continuously, although the increasing trend slowed; (2 the expansion of rural settlements showed a negative trend contrary to the trend of the urbanization of rural settlements; (3 rural settlement expansion occupied considerable expanse of cultivated lands, which accounted for up to 96% of the total expansion lands; (4 urbanization of rural settlements was the main mode by which rural residential lands vanished, accounting for more than 98% of the lost lands. This study can provide suggestions for the conservation and sustainability of the rural environment and inform reasonable policies on rural development.

  16. Learning large-scale dynamic discrete choice models of spatio-temporal preferences with application to migratory pastoralism in East Africa

    Science.gov (United States)

    Understanding spatio-temporal resource preferences is paramount in the design of policies for sustainable development. Unfortunately, resource preferences are often unknown to policy-makers and have to be inferred from data. In this paper we consider the problem of inferring agents’ preferences fro...

  17. Spatio-temporal dynamics of relativistic electron bunches during the micro bunching instability: study of the Synchrotron Soleil and UVSOR storage rings

    International Nuclear Information System (INIS)

    Roussel, Eleonore

    2014-01-01

    Relativistic electron bunches circulating in storage rings are used to produce intense radiation from far-infrared to X-rays. However, above a density threshold value, the interaction between the electron bunch and its own radiation can lead to a spatio-temporal instability called micro bunching instability. This instability is characterized by a strong emission of coherent THz radiation (typically 105 times stronger than the classical synchrotron radiation) which is a signature of the presence of microstructures (at mm scale) in the electron bunch. This instability is known to be a fundamental limitation of the operation of synchrotron light sources at high beam current. In this thesis, we have focused on this instability from a nonlinear dynamics point of view by combining experimental studies carried out at the Synchrotron Soleil and UVSOR storage rings with numerical studies mainly based on the Vlasov-Fokker-Planck equation. In a first step, due to the very indirect nature of the experimental observations, we have sought to deduce information on the microstructure wavenumber either by looking at the temporal evolution of the THz signal emitted during the instability or by studying the response of the electron bunch to a laser perturbation. In a second step, we have achieved direct, real time observations of the microstructures dynamics through two new, very different, detection techniques: a thin-film superconductor-based detector at UVSOR, and a spectrally-encoded electro-optic detection technique at Soleil. These new available experimental observations have allowed severe comparisons with the theoretical models. (author)

  18. Spatio-temporal dynamics and transition from asymptotic equilibrium to bounded oscillations in Chrysomya albiceps (Diptera, Calliphoridae

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    Wesley Augusto Conde Godoy

    2001-07-01

    Full Text Available The sensitivity of parameters that govern the stability of population size in Chrysomya albiceps and describe its spatial dynamics was evaluated in this study. The dynamics was modeled using a density-dependent model of population growth. Our simulations show that variation in fecundity and mainly in survival has marked effect on the dynamics and indicates the possibility of transitions from one-point equilibrium to bounded oscillations. C. albiceps exhibits a two-point limit cycle, but the introduction of diffusive dispersal induces an evident qualitative shift from two-point limit cycle to a one fixed-point dynamics. Population dynamics of C. albiceps is here compared to dynamics of Cochliomyia macellaria, C. megacephala and C. putoria.

  19. Monitoring of the Spatio-Temporal Dynamics of the Floods in the Guayas Watershed (Ecuadorian Pacific Coast Using Global Monitoring ENVISAT ASAR Images and Rainfall Data

    Directory of Open Access Journals (Sweden)

    Frédéric Frappart

    2017-01-01

    Full Text Available The floods are an annual phenomenon on the Pacific Coast of Ecuador and can become devastating during El Niño years, especially in the Guayas watershed (32,300 km2, the largest drainage basin of the South American western side of the Andes. As limited information on flood extent in this basin is available, this study presents a monitoring of the spatio-temporal dynamics of floods in the Guayas Basin, between 2005 and 2008, using a change detection method applied to ENVISAT ASAR Global Monitoring SAR images acquired at a spatial resolution of 1 km. The method is composed of three steps. First, a supervised classification was performed to identify pixels of open water present in the Guayas Basin. Then, the separability of their radar signature from signatures of other classes was determined during the four dry seasons from 2005 to 2008. In the end, standardized anomalies of backscattering coefficient were computed during the four wet seasons of the study period to detect changes between dry and wet seasons. Different thresholds were tested to identify the flooded areas in the watershed using external information from the Dartmouth Flood Observatory. A value of −2.30 ± 0.05 was found suitable to estimate the number of inundated pixels and limit the number of false detection (below 10%. Using this threshold, monthly maps of inundation were estimated during the wet season (December to May from 2004 to 2008. The most frequently inundated areas were found to be located along the Babahoyo River, a tributary in the east of the basin. Large interannual variability in the flood extent is observed at the flood peak (from 50 to 580 km2, consistent with the rainfall in the Guayas watershed during the study period.

  20. Multiscale Spatio-Temporal Dynamics of Economic Development in an Interprovincial Boundary Region: Junction Area of Tibetan Plateau, Hengduan Mountain, Yungui Plateau and Sichuan Basin, Southwestern China Case

    Directory of Open Access Journals (Sweden)

    Jifei Zhang

    2016-02-01

    Full Text Available An interprovincial boundary region is a new subject of economic disparity study in China. This study explored the multi-scale spatio-temporal dynamics of economic development from 1995 to 2010 in the interprovincial boundary region of Sichuan-Yunnan-Guizhou, a mountain area and also the junction area of Tibetan Plateau, Hengduan Mountain, Yungui Plateau and Sichuan Basin in southwestern China. A quantitative study on county GDP per capita for different scales of administrative regions was conducted using the Theil index, Markov chains, a geographic information system and exploratory spatial data analysis. Results indicated that the economic disparity was closely related with geographical unit scale in the study area: the smaller the unit, the bigger the disparity, and the regional inequality gradually weakened over time. Moreover, significant positive spatial autocorrelation and clustering of economic development were also found. The spatial pattern of economic development presented approximate circle structure with two cores in the southwest and northeast. The Panxi region in the southwest core and a part of Hilly Sichuan Basin in the northeast core were considered to be hot spots of economic development. Most areas in the east and central region were persistently trapped in the low level of a balanced development state, with a poverty trap being formed in the central and south part. Geographical conditions and location, administrative barriers and the lack of effective growth poles may be the main reasons for the entire low level of balanced development. Our findings suggest that in order to achieve a high level of balanced development, attention should be paid beyond developing transportation and other infrastructure. Breaking down the rigid shackles of administrative districts that hinder trans-provincial cooperation and promoting new regional poles in the Yunnan-Guizhou region may have great significance for the study area.

  1. Short spatio-temporal variations in the population dynamics and biology of the deep-water rose shrimp Parapenaeus longirostris (Decapoda: Crustacea in the western Mediterranean

    Directory of Open Access Journals (Sweden)

    Beatriz Guijarro

    2009-03-01

    Full Text Available The deep-water rose shrimp Parapenaeus longirostris is a demersal decapod crustacean that is commercially exploited by trawl fleets. The present work compares its population dynamics, biology and condition in two locations (southern and north-western Mallorca in the Balearic Islands, western Mediterranean, separated by a distance of 120 km with different environmental conditions and explores the relationships between the species and certain environmental factors. Six multidisciplinary bimonthly surveys were carried out during 2003 and 2004 in these two locations (between 150 and 750 m depth in order to collect data on the demersal species with bottom trawl, the hydrography (temperature and salinity with CTD casts, and trophic resources (zooplankton in the water column and suprabenthos with Bongo net and Macer-GIROQ sledge respectively and sediments with a Shipeck dredge. The trawl fleets from both locations were monitored by monthly on board sampling and daily landings obtained from sales bills. Additional data was obtained from other trawl surveys. Temporal differences were detected both annually, with a decreasing trend over the last years in species abundance, and seasonally, in the biological indexes analysed. Bathymetric differences were also found in abundance, mean length, sex-ratio and condition of females. There were clear differences between the two locations studied, with higher abundance, condition and mean length and a lower length at first maturity for females in the north-western location. Trophic conditions could act as a link between geo-physical and biological changes. These short spatio-temporal differences could be due to the higher productivity found at this location, with higher density of preferred prey for the studied species together with adequate seafloor topography, sediment composition and hydrographical characteristics.

  2. Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data

    Science.gov (United States)

    Manzo, Ciro; Braga, Federica; Zaggia, Luca; Brando, Vittorio Ernesto; Giardino, Claudia; Bresciani, Mariano; Bassani, Cristiana

    2018-04-01

    This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013-2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

  3. Spatio-temporal organization of dynamics in a two-dimensional periodically driven vortex flow: A Lagrangian flow network perspective.

    Science.gov (United States)

    Lindner, Michael; Donner, Reik V

    2017-03-01

    We study the Lagrangian dynamics of passive tracers in a simple model of a driven two-dimensional vortex resembling real-world geophysical flow patterns. Using a discrete approximation of the system's transfer operator, we construct a directed network that describes the exchange of mass between distinct regions of the flow domain. By studying different measures characterizing flow network connectivity at different time-scales, we are able to identify the location of dynamically invariant structures and regions of maximum dispersion. Specifically, our approach allows us to delimit co-existing flow regimes with different dynamics. To validate our findings, we compare several network characteristics to the well-established finite-time Lyapunov exponents and apply a receiver operating characteristic analysis to identify network measures that are particularly useful for unveiling the skeleton of Lagrangian chaos.

  4. Spatio-temporal dynamics of regulating ecosystem services in Europe – The role of past and future land use change

    NARCIS (Netherlands)

    Sturck, J.; Schulp, C.J.E.; Verburg, P.H.

    2015-01-01

    Land use is a main driver for changes in supply and demand of regulating ecosystem services (ES). Most current ES inventories are static and do not address dynamics of ES supply resulting from historic and future land use change. This paper analyzes the role of land use change for the supply of two

  5. Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

    Directory of Open Access Journals (Sweden)

    T. Blume

    2009-07-01

    Full Text Available Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale and binary indicator maps (for the long-term and hillslope scale. Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to

  6. Spatio-temporal morphology changes in and quenching effects on the 2D spreading dynamics of cell colonies in both plain and methylcellulose-containing culture media.

    Science.gov (United States)

    Muzzio, N E; Pasquale, M A; Huergo, M A C; Bolzán, A E; González, P H; Arvia, A J

    2016-06-01

    To deal with complex systems, microscopic and global approaches become of particular interest. Our previous results from the dynamics of large cell colonies indicated that their 2D front roughness dynamics is compatible with the standard Kardar-Parisi-Zhang (KPZ) or the quenched KPZ equations either in plain or methylcellulose (MC)-containing gel culture media, respectively. In both cases, the influence of a non-uniform distribution of the colony constituents was significant. These results encouraged us to investigate the overall dynamics of those systems considering the morphology and size, the duplication rate, and the motility of single cells. For this purpose, colonies with different cell populations (N) exhibiting quasi-circular and quasi-linear growth fronts in plain and MC-containing culture media are investigated. For small N, the average radial front velocity and its change with time depend on MC concentration. MC in the medium interferes with cell mitosis, contributes to the local enlargement of cells, and increases the distribution of spatio-temporal cell density heterogeneities. Colony spreading in MC-containing media proceeds under two main quenching effects, I and II; the former mainly depending on the culture medium composition and structure and the latter caused by the distribution of enlarged local cell domains. For large N, colony spreading occurs at constant velocity. The characteristics of cell motility, assessed by measuring their trajectories and the corresponding velocity field, reflect the effect of enlarged, slow-moving cells and the structure of the medium. Local average cell size distribution and individual cell motility data from plain and MC-containing media are qualitatively consistent with the predictions of both the extended cellular Potts models and the observed transition of the front roughness dynamics from a standard KPZ to a quenched KPZ. In this case, quenching effects I and II cooperate and give rise to the quenched

  7. Effects of Changing Weather, Oceanographic Conditions, and Land Uses on Spatio-Temporal Variation of Sedimentation Dynamics along Near-Shore Coral Reefs

    Directory of Open Access Journals (Sweden)

    Abimarie Otaño-Cruz

    2017-08-01

    Full Text Available Sedimentation is a critical threat to coral reefs worldwide. Major land use alteration at steep, highly erodible semi-arid islands accelerates the potential of soil erosion, runoff, and sedimentation stress to nearshore coral reefs during extreme rainfall events. The goal of this study was to assess spatio-temporal variation of sedimentation dynamics across nearshore coral reefs as a function of land use patterns, weather and oceanographic dynamics, to identify marine ecosystem conservation strategies. Sediment was collected at a distance gradient from shore at Bahia Tamarindo (BTA and Punta Soldado (PSO coral reefs at Culebra Island, Puerto Rico. Sediment texture and composition were analyzed by dry sieving and loss-on-ignition techniques, and were contrasted with environmental variables for the research period (February 2014 to April 2015. Rainfall and oceanographic data were analyzed to address their potential role on affecting sediment distribution with BEST BIO-ENV, RELATE correlation, and linear regression analysis. A significant difference in sedimentation rate was observed by time and distance from shore (PERMANOVA, p < 0.0100, mostly attributed to higher sediment exposure at reef zones closer to shore due to strong relationships with coastal runoff. Sedimentation rate positively correlated with strong rainfall events (Rho = 0.301, p = 0.0400 associated with storms and rainfall intensity exceeding 15 mm/h. At BTA, sediment deposited were mostly composed of sand, suggesting a potential influence of resuspension produced by waves and swells. In contrast, PSO sediments were mostly composed of silt-clay and terrigenous material, mainly attributed to a deforestation event that occurred at adjacent steep sub-watershed during the study period. Spatial and temporal variation of sedimentation pulses and terrigenous sediment input implies that coral reefs exposure to sediment stress is determined by local land use patterns, weather, and

  8. Protein Charge and Mass Contribute to the Spatio-temporal Dynamics of Protein-Protein Interactions in a Minimal Proteome

    Science.gov (United States)

    Xu, Yu; Wang, Hong; Nussinov, Ruth; Ma, Buyong

    2013-01-01

    We constructed and simulated a ‘minimal proteome’ model using Langevin dynamics. It contains 206 essential protein types which were compiled from the literature. For comparison, we generated six proteomes with randomized concentrations. We found that the net charges and molecular weights of the proteins in the minimal genome are not random. The net charge of a protein decreases linearly with molecular weight, with small proteins being mostly positively charged and large proteins negatively charged. The protein copy numbers in the minimal genome have the tendency to maximize the number of protein-protein interactions in the network. Negatively charged proteins which tend to have larger sizes can provide large collision cross-section allowing them to interact with other proteins; on the other hand, the smaller positively charged proteins could have higher diffusion speed and are more likely to collide with other proteins. Proteomes with random charge/mass populations form less stable clusters than those with experimental protein copy numbers. Our study suggests that ‘proper’ populations of negatively and positively charged proteins are important for maintaining a protein-protein interaction network in a proteome. It is interesting to note that the minimal genome model based on the charge and mass of E. Coli may have a larger protein-protein interaction network than that based on the lower organism M. pneumoniae. PMID:23420643

  9. Spatio-Temporal Saliency Perception via Hypercomplex Frequency Spectral Contrast

    Directory of Open Access Journals (Sweden)

    Zhiqiang Tian

    2013-03-01

    Full Text Available Salient object perception is the process of sensing the salient information from the spatio-temporal visual scenes, which is a rapid pre-attention mechanism for the target location in a visual smart sensor. In recent decades, many successful models of visual saliency perception have been proposed to simulate the pre-attention behavior. Since most of the methods usually need some ad hoc parameters or high-cost preprocessing, they are difficult to rapidly detect salient object or be implemented by computing parallelism in a smart sensor. In this paper, we propose a novel spatio-temporal saliency perception method based on spatio-temporal hypercomplex spectral contrast (HSC. Firstly, the proposed HSC algorithm represent the features in the HSV (hue, saturation and value color space and features of motion by a hypercomplex number. Secondly, the spatio-temporal salient objects are efficiently detected by hypercomplex Fourier spectral contrast in parallel. Finally, our saliency perception model also incorporates with the non-uniform sampling, which is a common phenomenon of human vision that directs visual attention to the logarithmic center of the image/video in natural scenes. The experimental results on the public saliency perception datasets demonstrate the effectiveness of the proposed approach compared to eleven state-of-the-art approaches. In addition, we extend the proposed model to moving object extraction in dynamic scenes, and the proposed algorithm is superior to the traditional algorithms.

  10. Spatio-temporal dynamics of multimodal EEG-fNIRS signals in the loss and recovery of consciousness under sedation using midazolam and propofol.

    Directory of Open Access Journals (Sweden)

    Seul-Ki Yeom

    Full Text Available On sedation motivated by the clinical needs for safety and reliability, recent studies have attempted to identify brain-specific signatures for tracking patient transition into and out of consciousness, but the differences in neurophysiological effects between 1 the sedative types and 2 the presence/absence of surgical stimulations still remain unclear. Here we used multimodal electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS measurements to observe electrical and hemodynamic responses during sedation simultaneously. Forty healthy volunteers were instructed to push the button to administer sedatives in response to auditory stimuli every 9-11 s. To generally illustrate brain activity at repetitive transition points at the loss of consciousness (LOC and the recovery of consciousness (ROC, patient-controlled sedation was performed using two different sedatives (midazolam (MDZ and propofol (PPF under two surgical conditions. Once consciousness was lost via sedatives, we observed gradually increasing EEG power at lower frequencies (15 Hz, as well as spatially increased EEG powers in the delta and lower alpha bands, and particularly also in the upper alpha rhythm, at the frontal and parieto-occipital areas over time. During ROC from unconsciousness, these spatio-temporal changes were reversed. Interestingly, the level of consciousness was switched on/off at significantly higher effect-site concentrations of sedatives in the brain according to the use of surgical stimuli, but the spatio-temporal EEG patterns were similar, regardless of the sedative used. We also observed sudden phase shifts in fronto-parietal connectivity at the LOC and the ROC as critical points. fNIRS measurement also revealed mild hemodynamic fluctuations. Compared with general anesthesia, our results provide insights into critical hallmarks of sedative-induced (unconsciousness, which have similar spatio-temporal EEG-fNIRS patterns regardless of the stage and

  11. Spatio-temporal reasoning and decision support tools

    OpenAIRE

    Renso, Chiara; Wachowicz, Monica

    2014-01-01

    Currently, mobility data is revolutionizing the traditional fields of spatio-temporal reasoning and decision making analysis, not only to scale-up to the large and growing data volumes, but also to address complex questions related to change, trends, duration, and evolution. In mobility data, space and time are inextricably linked, since humans, robots and systems that dynamically act, and interact within social networks, are embedded in space, and any change is often the result of actions an...

  12. Spatio-temporal patterns in simple models of marine systems

    Science.gov (United States)

    Feudel, U.; Baurmann, M.; Gross, T.

    2009-04-01

    Spatio-temporal patterns in marine systems are a result of the interaction of population dynamics with physical transport processes. These physical transport processes can be either diffusion processes in marine sediments or in the water column. We study the dynamics of one population of bacteria and its nutrient in in a simplified model of a marine sediments, taking into account that the considered bacteria possess an active as well as an inactive state, where activation is processed by signal molecules. Furthermore the nutrients are transported actively by bioirrigation and passively by diffusion. It is shown that under certain conditions Turing patterns can occur which yield heterogeneous spatial patterns of the species. The influence of bioirrigation on Turing patterns leads to the emergence of ''hot spots``, i.e. localized regions of enhanced bacterial activity. All obtained patterns fit quite well to observed patterns in laboratory experiments. Spatio-temporal patterns appear in a predator-prey model, used to describe plankton dynamics. These patterns appear due to the simultaneous emergence of Turing patterns and oscillations in the species abundance in the neighborhood of a Turing-Hopf bifurcation. We observe a large variety of different patterns where i) stationary heterogeneous patterns (e.g. hot and cold spots) compete with spatio-temporal patterns ii) slowly moving patterns are embedded in an oscillatory background iii) moving fronts and spiral waves appear.

  13. Spatio-Temporal Data Exchange Standards

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Schmidt, Albrecht

    2003-01-01

    We believe that research that concerns aspects of spatio-temporal data management may benefit from taking into account the various standards for spatio-temporal data formats. For example, this may contribute to rendering prototype software “open” and more readily useful. This paper thus identifies...... and briefly surveys standardization in relation to primarily the exchange and integration of spatio-temporal data. An overview of several data exchange languages is offered, along with reviews their potential for facilitating the collection of test data and the leveraging of prototypes. The standards, most...... of which are XML-based, lend themselves to the integration of prototypes into middleware architectures, e.g., as Web services....

  14. Spatio-temporal modeling for residential burglary

    NARCIS (Netherlands)

    Mahfoud, M.; Bhulai, Sandjai; van der Mei, R.D.; Bhulai, Sandjai; Kardaras, Dimitris

    2017-01-01

    Spatio-temporal modeling is widely recognized as a promising means for predicting crime patterns. Despite their enormous potential, the available methods are still in their infancy. A lot of research focuses on crime hotspot detection and geographic crime clusters, while a systematic approach to

  15. A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates

    OpenAIRE

    Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

    2013-01-01

    The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implem...

  16. Assessing global vegetation activity using spatio-temporal Bayesian modelling

    Science.gov (United States)

    Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

    2016-04-01

    This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support

  17. Use of remote sensing, geographic information systems, and spatial statistics to assess spatio-temporal population dynamics of Heterodera glycines and soybean yield quantity and quality

    Science.gov (United States)

    Moreira, Antonio Jose De Araujo

    Soybean, Glycine max (L.) Merr., is an important source of oil and protein worldwide, and soybean cyst nematode (SCN), Heterodera glycines, is among the most important yield-limiting factors in soybean production worldwide. Early detection of SCN is difficult because soybean plants infected by SCN often do not exhibit visible symptoms. It was hypothesized, however, that reflectance data obtained by remote sensing from soybean canopies may be used to detect plant stress caused by SCN infection. Moreover, reflectance measurements may be related to soybean growth and yield. Two field experiments were conducted from 2000 to 2002 to study the relationships among reflectance data, quantity and quality of soybean yield, and SCN population densities. The best relationships between reflectance and the quantity of soybean grain yield occurred when reflectance data were obtained late August to early September. Similarly, reflectance was best related to seed oil and seed protein content and seed size when measured during late August/early September. Grain quality-reflectance relationships varied spatially and temporally. Reflectance measured early or late in the season had the best relationships with SCN population densities measured at planting. Soil properties likely affected reflectance measurements obtained at the beginning of the season and somehow may have been related to SCN population densities at planting. Reflectance data obtained at the end of the growing season likely was affected by early senescence of SCN-infected soybeans. Spatio-temporal aspects of SCN population densities in both experiments were assessed using spatial statistics and regression analyses. In the 2000 and 2001 growing seasons, spring-to-fall changes in SCN population densities were best related to SCN population densities at planting for both experiments. However, within-season changes in SCN population densities were best related to SCN population densities at harvest for both experiments in

  18. What Is Spatio-Temporal Data Warehousing?

    Science.gov (United States)

    Vaisman, Alejandro; Zimányi, Esteban

    In the last years, extending OLAP (On-Line Analytical Processing) systems with spatial and temporal features has attracted the attention of the GIS (Geographic Information Systems) and database communities. However, there is no a commonly agreed definition of what is a spatio-temporal data warehouse and what functionality such a data warehouse should support. Further, the solutions proposed in the literature vary considerably in the kind of data that can be represented as well as the kind of queries that can be expressed. In this paper we present a conceptual framework for defining spatio-temporal data warehouses using an extensible data type system. We also define a taxonomy of different classes of queries of increasing expressive power, and show how to express such queries using an extension of the tuple relational calculus with aggregated functions.

  19. A Hybrid Approach Combining the Multi-Temporal Scale Spatio-Temporal Network with the Continuous Triangular Model for Exploring Dynamic Interactions in Movement Data: A Case Study of Football

    Directory of Open Access Journals (Sweden)

    Pengdong Zhang

    2018-01-01

    Full Text Available Benefiting from recent advantages in location-aware technologies, movement data are becoming ubiquitous. Hence, numerous research topics with respect to movement data have been undertaken. Yet, the research of dynamic interactions in movement data is still in its infancy. In this paper, we propose a hybrid approach combining the multi-temporal scale spatio-temporal network (MTSSTN and the continuous triangular model (CTM for exploring dynamic interactions in movement data. The approach mainly includes four steps: first, the relative trajectory calculus (RTC is used to derive three types of interaction patterns; second, for each interaction pattern, a corresponding MTSSTN is generated; third, for each MTSSTN, the interaction intensity measures and three centrality measures (i.e., degree, betweenness and closeness are calculated; finally, the results are visualized at multiple temporal scales using the CTM and analyzed based on the generated CTM diagrams. Based on the proposed approach, three distinctive aims can be achieved for each interaction pattern at multiple temporal scales: (1 exploring the interaction intensities between any two individuals; (2 exploring the interaction intensities among multiple individuals, and (3 exploring the importance of each individual and identifying the most important individuals. The movement data obtained from a real football match are used as a case study to validate the effectiveness of the proposed approach. The results demonstrate that the proposed approach is useful in exploring dynamic interactions in football movement data and discovering insightful information.

  20. Multiscale recurrence analysis of spatio-temporal data

    Science.gov (United States)

    Riedl, M.; Marwan, N.; Kurths, J.

    2015-12-01

    The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

  1. AN ADAPTIVE ORGANIZATION METHOD OF GEOVIDEO DATA FOR SPATIO-TEMPORAL ASSOCIATION ANALYSIS

    Directory of Open Access Journals (Sweden)

    C. Wu

    2015-07-01

    Full Text Available Public security incidents have been increasingly challenging to address with their new features, including large-scale mobility, multi-stage dynamic evolution, spatio-temporal concurrency and uncertainty in the complex urban environment, which require spatio-temporal association analysis among multiple regional video data for global cognition. However, the existing video data organizational methods that view video as a property of the spatial object or position in space dissever the spatio-temporal relationship of scattered video shots captured from multiple video channels, limit the query functions on interactive retrieval between a camera and its video clips and hinder the comprehensive management of event-related scattered video shots. GeoVideo, which maps video frames onto a geographic space, is a new approach to represent the geographic world, promote security monitoring in a spatial perspective and provide a highly feasible solution to this problem. This paper analyzes the large-scale personnel mobility in public safety events and proposes a multi-level, event-related organization method with massive GeoVideo data by spatio-temporal trajectory. This paper designs a unified object identify(ID structure to implicitly store the spatio-temporal relationship of scattered video clips and support the distributed storage management of massive cases. Finally, the validity and feasibility of this method are demonstrated through suspect tracking experiments.

  2. Research on Process-oriented Spatio-temporal Data Model

    Directory of Open Access Journals (Sweden)

    XUE Cunjin

    2016-02-01

    Full Text Available According to the analysis of the present status and existing problems of spatio-temporal data models developed in last 20 years,this paper proposes a process-oriented spatio-temporal data model (POSTDM,aiming at representing,organizing and storing continuity and gradual geographical entities. The dynamic geographical entities are graded and abstracted into process objects series from their intrinsic characteristics,which are process objects,process stage objects,process sequence objects and process state objects. The logical relationships among process entities are further studied and the structure of UML models and storage are also designed. In addition,through the mechanisms of continuity and gradual changes impliedly recorded by process objects,and the modes of their procedure interfaces offered by the customized ObjcetStorageTable,the POSTDM can carry out process representation,storage and dynamic analysis of continuity and gradual geographic entities. Taking a process organization and storage of marine data as an example,a prototype system (consisting of an object-relational database and a functional analysis platform is developed for validating and evaluating the model's practicability.

  3. Spatio-temporal statistical models with applications to atmospheric processes

    International Nuclear Information System (INIS)

    Wikle, C.K.

    1996-01-01

    This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model

  4. Nonlinear system identification NARMAX methods in the time, frequency, and spatio-temporal domains

    CERN Document Server

    Billings, Stephen A

    2013-01-01

    Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) modelThe orthogonal least squares algorithm that allows models to be built term by

  5. Spatio-Temporal Process Simulation of Dam-Break Flood Based on SPH

    Science.gov (United States)

    Wang, H.; Ye, F.; Ouyang, S.; Li, Z.

    2018-04-01

    On the basis of introducing the SPH (Smooth Particle Hydrodynamics) simulation method, the key research problems were given solutions in this paper, which ere the spatial scale and temporal scale adapting to the GIS(Geographical Information System) application, the boundary condition equations combined with the underlying surface, and the kernel function and parameters applicable to dam-break flood simulation. In this regards, a calculation method of spatio-temporal process emulation with elaborate particles for dam-break flood was proposed. Moreover the spatio-temporal process was dynamic simulated by using GIS modelling and visualization. The results show that the method gets more information, objectiveness and real situations.

  6. Spatio-temporal intermittency on the sandpile

    International Nuclear Information System (INIS)

    Erzan, A.; Sinha, S.

    1990-08-01

    The self-organized critical state exhibited by a sandpile model is shown to correspond to motion on an attractor characterized by an invariant distribution of the height variable. The largest Lyapunov exponent is equal to zero. The model nonetheless displays intermittent chaos, with a multifractal distribution of local expansion coefficients in history space. Laminar spatio-temporal regions are interrupted by chaotic bursts caused by avalanches. We introduce the concept of local histories in configuration space and show that their expansion parameters also exhibit a multifractal distribution in time and space. (author). 22 refs, 5 figs

  7. State estimation of spatio-temporal phenomena

    Science.gov (United States)

    Yu, Dan

    This dissertation addresses the state estimation problem of spatio-temporal phenomena which can be modeled by partial differential equations (PDEs), such as pollutant dispersion in the atmosphere. After discretizing the PDE, the dynamical system has a large number of degrees of freedom (DOF). State estimation using Kalman Filter (KF) is computationally intractable, and hence, a reduced order model (ROM) needs to be constructed first. Moreover, the nonlinear terms, external disturbances or unknown boundary conditions can be modeled as unknown inputs, which leads to an unknown input filtering problem. Furthermore, the performance of KF could be improved by placing sensors at feasible locations. Therefore, the sensor scheduling problem to place multiple mobile sensors is of interest. The first part of the dissertation focuses on model reduction for large scale systems with a large number of inputs/outputs. A commonly used model reduction algorithm, the balanced proper orthogonal decomposition (BPOD) algorithm, is not computationally tractable for large systems with a large number of inputs/outputs. Inspired by the BPOD and randomized algorithms, we propose a randomized proper orthogonal decomposition (RPOD) algorithm and a computationally optimal RPOD (RPOD*) algorithm, which construct an ROM to capture the input-output behaviour of the full order model, while reducing the computational cost of BPOD by orders of magnitude. It is demonstrated that the proposed RPOD* algorithm could construct the ROM in real-time, and the performance of the proposed algorithms on different advection-diffusion equations. Next, we consider the state estimation problem of linear discrete-time systems with unknown inputs which can be treated as a wide-sense stationary process with rational power spectral density, while no other prior information needs to be known. We propose an autoregressive (AR) model based unknown input realization technique which allows us to recover the input

  8. Spatio-temporal map generalizations with the hierarchical Voronoi data structure

    DEFF Research Database (Denmark)

    Mioc, Darka; Anton, François; Gold, Christopher M.

    implemented in commercial GIS systems. In this research, we used the Voronoi spatial data model for map generalizations. We were able to demonstrate that the map generalization does not affect only spatial objects (points, lines or polygons), but also the events corresponding to the creation and modification...... their spatio-temporal characteristics and their dynamic behaviour....

  9. Spatio-temporal interpolation of soil water, temperature, and electrical conductivity in 3D + T

    NARCIS (Netherlands)

    Gasch, C.K.; Hengl, Tom; Gräler, Benedikt; Meyer, Hanna; Magney, T.S.; Brown, D.J.

    2015-01-01

    The paper describes a framework for modeling dynamic soil properties in 3-dimensions and time (3D + T) using soil data collected with automated sensor networks as a case study. Two approaches to geostatistical modeling and spatio-temporal predictions are described: (1) 3D + T predictive modeling

  10. Spatio-Temporal Modeling of Neuron Fields

    DEFF Research Database (Denmark)

    Lund, Adam

    The starting point and focal point for this thesis was stochastic dynamical modelling of neuronal imaging data with the declared objective of drawing inference, within this model framework, in a large-scale (high-dimensional) data setting. Implicitly this objective entails carrying out three...... be achieved if the scale of the data is taken into consideration throughout i) - iii). The strategy in this project was, relying on a space and time continuous stochastic modelling approach, to obtain a stochastic functional differential equation on a Hilbert space. By decomposing the drift operator...... of this SFDE such that each component is essentially represented by a smooth function of time and space and expanding these component functions in a tensor product basis we implicitly reduce the number of model parameters. In addition, the component-wise tensor representation induce a corresponding component...

  11. Spatio-temporal scaling of channels in braided streams.

    Science.gov (United States)

    A.G. Hunt; G.E. Grant; V.K. Gupta

    2006-01-01

    The spatio-temporal scaling relationship for individual channels in braided streams is shown to be identical to the spatio-temporal scaling associated with constant Froude number, e.g., Fr = l. A means to derive this relationship is developed from a new theory of sediment transport. The mechanism by which the Fr = l condition apparently governs the scaling seems to...

  12. Cartography in the Age of Spatio-temporal Big Data

    Directory of Open Access Journals (Sweden)

    WANG Jiayao

    2017-10-01

    Full Text Available Cartography is an ancient science with almost the same long history as the world's oldest culture.Since ancient times,the movement and change of anything and any phenomena,including human activities,have been carried out in a certain time and space.The development of science and technology and the progress of social civilization have made social management and governance more and more dependent on time and space.The information source,theme,content,carrier,form,production methods and application methods of map are different in different historical periods,so that its all-round value is different. With the arrival of the big data age,the scientific paradigm has now entered the era of "data-intensive" paradigm,so is the cartography,with obvious characteristics of big data science.All big data are caused by movement and change of all things and phenomena in the geographic world,so they have space and time characteristics and thus cannot be separated from the spatial reference and time reference.Therefore,big data is big spatio-temporal data essentially.Since the late 1950s and early 1960s,modern cartography,that is,the cartography in the information age,takes spatio-temporal data as the object,and focuses on the processing and expression of spatio-temporal data,but not in the face of the large scale multi-source heterogeneous and multi-dimensional dynamic data flow(or flow datafrom sky to the sea.The real-time dynamic nature,the theme pertinence,the content complexity,the carrier diversification,the expression form personalization,the production method modernization,the application ubiquity of the map,is incomparable in the past period,which leads to the great changes of the theory,technology and application system of cartography.And all these changes happen to occur in the 60 years since the late 1950s and early 1960s,so this article was written to commemorate the 60th anniversary of the "Acta Geodaetica et Cartographica Sinica".

  13. Spatio-temporal dynamics of phytoplankton and primary production in Lake Tanganyika using a MODIS based bio-optical time series

    DEFF Research Database (Denmark)

    Bergamino, N; Horion, Stéphanie; Stenuite, S

    2010-01-01

    dynamics throughout the lake. In the present work, daily MODIS-AQUA satellite measurements were used to estimate chlorophyll-a concentrations and the diffuse attenuation coefficient (K490) for surface waters. The spatial regionalisation of Lake Tanganyika, based on Empirical Orthogonal Functions...

  14. Influenza A virus evolution and spatio-temporal dynamics in eurasian wild birds: A phylogenetic and phylogeographical study of whole-genome sequence data

    NARCIS (Netherlands)

    N.S. Lewis (Nicola); J.H. Verhagen (Josanne); Z. Javakhishvili (Zurab); C.A. Russell (Colin); P. Lexmond (Pascal); K.B. Westgeest (Kim); T.M. Bestebroer (Theo); R.A. Halpin (Rebecca); X. Lin (Xudong); A. Ransier (Amy); N.B. Fedorova (Nadia B.); T.B. Stockwell (Timothy B.); N. Latorre-Margalef (Neus); B. Olsen (Björn); G.J.D. Smith (Gavin); J. Bahl (Justin); D.E. Wentworth (David E.); J. Waldenström (Jonas); R.A.M. Fouchier (Ron); M.T. de Graaf (Marieke)

    2015-01-01

    textabstractLow pathogenic avian influenza A viruses (IAVs) have a natural host reservoir in wild waterbirds and the potential to spread to other host species. Here, we investigated the evolutionary, spatial and temporal dynamics of avian IAVs in Eurasian wild birds. We used whole-genome sequences

  15. Spatio-temporal behaviour of medium-range ensemble forecasts

    Science.gov (United States)

    Kipling, Zak; Primo, Cristina; Charlton-Perez, Andrew

    2010-05-01

    Using the recently-developed mean-variance of logarithms (MVL) diagram, together with the TIGGE archive of medium-range ensemble forecasts from nine different centres, we present an analysis of the spatio-temporal dynamics of their perturbations, and show how the differences between models and perturbation techniques can explain the shape of their characteristic MVL curves. We also consider the use of the MVL diagram to compare the growth of perturbations within the ensemble with the growth of the forecast error, showing that there is a much closer correspondence for some models than others. We conclude by looking at how the MVL technique might assist in selecting models for inclusion in a multi-model ensemble, and suggest an experiment to test its potential in this context.

  16. Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

    Science.gov (United States)

    Diao, Chunyuan

    In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of

  17. A Computational Model Based on Multi-Regional Calcium Imaging Represents the Spatio-Temporal Dynamics in a Caenorhabditis elegans Sensory Neuron.

    Directory of Open Access Journals (Sweden)

    Masahiro Kuramochi

    Full Text Available Due to the huge number of neuronal cells in the brain and their complex circuit formation, computer simulation of neuronal activity is indispensable to understanding whole brain dynamics. Recently, various computational models have been developed based on whole-brain calcium imaging data. However, these analyses monitor only the activity of neuronal cell bodies and treat the cells as point unit. This point-neuron model is inexpensive in computational costs, but the model is unrealistically simplistic at representing intact neural activities in the brain. Here, we describe a novel three-unit Ordinary Differential Equation (ODE model based on the neuronal responses derived from a Caenorhabditis elegans salt-sensing neuron. We recorded calcium responses in three regions of the ASER neuron using a simple downstep of NaCl concentration. Our simple ODE model generated from a single recording can adequately reproduce and predict the temporal responses of each part of the neuron to various types of NaCl concentration changes. Our strategy which combines a simple recording data and an ODE mathematical model may be extended to realistically understand whole brain dynamics by computational simulation.

  18. Spatio-Temporal Dynamics in Land Use and Habitat Fragmentation within a Protected Area Dedicated to Tourism in a Sudanian Savanna of West Africa

    Directory of Open Access Journals (Sweden)

    Dimobe Kangbéni

    2017-01-01

    Full Text Available Nazinga Game Ranch (NGR is a reserve in Burkina Faso involving local communities for securing biodiversity through sustainable management. Yet, its ecosystems are threatened by increasing number of elephants and illegal human activities. Renowned as a model of wildlife participatory management, NGR has mainly been studied for its animal wildlife only. The aim of this study was to uncover ecological effects of recent land management on savanna habitats including tourism, and to conclude on more sustainable options, land use/land cover (LULC changes and vegetation dynamics in NGR were analyzed. This was accomplished with multi-temporal change detection using Landsat images of 1984, 2002 and 2013 to map seven representative LULC classification categories, and quantitative indices of landscape metrics. The results showed that the LULC dynamics in NGR from 1984 to 2013 was mainly characterized by an expansion of gallery forest, tree savanna and agricultural area and a reduction of shrub savanna, woodland and bare soils. From 2002 to 2013, fragmentation in all land cover types increased at the landscape level, whereas at the class level, it decreased for woodland. Our findings provided evidence of habitat degradation in NGR, due to extensive agriculture, tourism and growing of elephants’ population. According to the original management goals and the purposes of the reserve, both fauna and tourism are to be maintained and sustained in a sustainable way. Adaptation of land use and targeted wildlife management are the main requirements for avoiding further degradation of vegetation and thus of the existence basis of local inhabitants, animals and tourism.

  19. Spatio-Temporal Analysis of Vegetation Dynamics in Relation to Shifting Inundation and Fire Regimes: Disentangling Environmental Variability from Land Management Decisions in a Southern African Transboundary Watershed

    Directory of Open Access Journals (Sweden)

    Narcisa G. Pricope

    2015-07-01

    Full Text Available Increasing temperatures and wildfire incidence and decreasing precipitation and river runoff in southern Africa are predicted to have a variety of impacts on the ecology, structure, and function of semi-arid savannas, which provide innumerable livelihood resources for millions of people. This paper builds on previous research that documents change in inundation and fire regimes in the Chobe River Basin (CRB in Namibia and Botswana and proposes to demonstrate a methodology that can be applied to disentangle the effect of environmental variability from land management decisions on changing and ecologically sensitive savanna ecosystems in transboundary contexts. We characterized the temporal dynamics (1985–2010 of vegetation productivity for the CRB using proxies of vegetation productivity and examine the relative importance of shifts in flooding and fire patterns to vegetation dynamics and effects of the association of phases of the El Niño—Southern Oscillation (ENSO on vegetation greenness. Our results indicate that vegetation in these semi-arid environments is highly responsive to climatic fluctuations and the long-term trend is one of increased but heterogeneous vegetation cover. The increased cover and heterogeneity during the growing season is especially noted in communally-managed areas of Botswana where long-term fire suppression has been instituted, in contrast to communal areas in Namibia where heterogeneity in vegetation cover is mostly increasing primarily outside of the growing season and may correspond to mosaic early dry season burns. Observed patterns of increased vegetation productivity and heterogeneity may relate to more frequent and intense burning and higher spatial variability in surface water availability from both precipitation and regional inundation patterns, with implications for global environmental change and adaptation in subsistence-based communities.

  20. Spatio-temporal scaling effects on longshore sediment transport pattern along the nearshore zone

    Science.gov (United States)

    Khorram, Saeed; Ergil, Mustafa

    2018-03-01

    A measure of uncertainties, entropy has been employed in such different applications as coastal engineering probability inferences. Entropy sediment transport integration theories present novel visions in coastal analyses/modeling the application and development of which are still far-reaching. Effort has been made in the present paper to propose a method that needs an entropy-power index for spatio-temporal patterns analyses. Results have shown that the index is suitable for marine/hydrological ecosystem components analyses based on a beach area case study. The method makes use of six Makran Coastal monthly data (1970-2015) and studies variables such as spatio-temporal patterns, LSTR (long-shore sediment transport rate), wind speed, and wave height all of which are time-dependent and play considerable roles in terrestrial coastal investigations; the mentioned variables show meaningful spatio-temporal variability most of the time, but explanation of their combined performance is not easy. Accordingly, the use of an entropy-power index can show considerable signals that facilitate the evaluation of water resources and will provide an insight regarding hydrological parameters' interactions at scales as large as beach areas. Results have revealed that an STDDPI (entropy based spatio-temporal disorder dynamics power index) can simulate wave, long-shore sediment transport rate, and wind when granulometry, concentration, and flow conditions vary.

  1. A Spatio-Temporal Enhanced Metadata Model for Interdisciplinary Instant Point Observations in Smart Cities

    Directory of Open Access Journals (Sweden)

    Nengcheng Chen

    2017-02-01

    Full Text Available Due to the incomprehensive and inconsistent description of spatial and temporal information for city data observed by sensors in various fields, it is a great challenge to share the massive, multi-source and heterogeneous interdisciplinary instant point observation data resources. In this paper, a spatio-temporal enhanced metadata model for point observation data sharing was proposed. The proposed Data Meta-Model (DMM focused on the spatio-temporal characteristics and formulated a ten-tuple information description structure to provide a unified and spatio-temporal enhanced description of the point observation data. To verify the feasibility of the point observation data sharing based on DMM, a prototype system was established, and the performance improvement of Sensor Observation Service (SOS for the instant access and insertion of point observation data was realized through the proposed MongoSOS, which is a Not Only SQL (NoSQL SOS based on the MongoDB database and has the capability of distributed storage. For example, the response time of the access and insertion for navigation and positioning data can be realized at the millisecond level. Case studies were conducted, including the gas concentrations monitoring for the gas leak emergency response and the smart city public vehicle monitoring based on BeiDou Navigation Satellite System (BDS used for recording the dynamic observation information. The results demonstrated the versatility and extensibility of the DMM, and the spatio-temporal enhanced sharing for interdisciplinary instant point observations in smart cities.

  2. Contribution of hydrological data to the understanding of the spatio-temporal dynamics of F-specific RNA bacteriophages in river water during rainfall-runoff events.

    Science.gov (United States)

    Fauvel, Blandine; Cauchie, Henry-Michel; Gantzer, Christophe; Ogorzaly, Leslie

    2016-05-01

    Heavy rainfall events were previously reported to bring large amounts of microorganisms in surface water, including viruses. However, little information is available on the origin and transport of viral particles in water during such rain events. In this study, an integrative approach combining microbiological and hydrological measurements was investigated to appreciate the dynamics and origins of F-specific RNA bacteriophage fluxes during two distinct rainfall-runoff events. A high frequency sampling (automatic sampler) was set up to monitor the F-specific RNA bacteriophages fluxes at a fine temporal scale during the whole course of the rainfall-runoff events. A total of 276 rainfall-runoff samples were collected and analysed using both infectivity and RT-qPCR assays. The results highlight an increase of 2.5 log10 and 1.8 log10 of infectious F-specific RNA bacteriophage fluxes in parallel of an increase of the water flow levels for both events. Faecal pollution was characterised as being mainly from anthropic origin with a significant flux of phage particles belonging to the genogroup II. At the temporal scale, two successive distinct waves of phage pollution were established and identified through the hydrological measurements. The first arrival of phages in the water column was likely to be linked to the resuspension of riverbed sediments that was responsible for a high input of genogroup II. Surface runoff contributed further to the second input of phages, and more particularly of genogroup I. In addition, an important contribution of infectious phage particles has been highlighted. These findings imply the existence of a close relationship between the risk for human health and the viral contamination of flood water. Copyright © 2016 Luxembourg institute of Science and Technology. Published by Elsevier Ltd.. All rights reserved.

  3. Spatio-Temporal Dynamics of Land-Use and Land-Cover in the Mu Us Sandy Land, China, Using the Change Vector Analysis Technique

    Directory of Open Access Journals (Sweden)

    Arnon Karnieli

    2014-09-01

    Full Text Available The spatial extent of desertified vs. rehabilitated areas in the Mu Us Sandy Land, China, was explored. The area is characterized by complex landscape changes that were caused by different drivers, either natural or anthropogenic, interacting with each other, and resulting in multiple consequences. Two biophysical variables, NDVI, positively correlated with vegetation cover, and albedo, positively correlated with cover of exposed sands, were computed from a time series of merged NOAA-AVHRR and MODIS images (1981 to 2010. Generally, throughout the study period, NDVI increased and albedo decreased. Improved understanding of spatial and temporal dynamics of these environmental processes was achieved by using the Change Vector Analysis (CVA technique applied to NDVI and albedo data extracted from four sets of consecutive Landsat images, several years apart. Changes were detected for each time step, as well as over the entire period (1978 to 2007. Four categories of land cover were created—vegetation, exposed sands, water bodies and wetlands. The CVA’s direction and magnitude enable detecting and quantifying finer changes compared to separate NDVI or albedo difference/ratio images and result in pixel-based maps of the change. Each of the four categories has a biophysical meaning that was validated in selected hot-spots, employing very high spatial resolution images (e.g., Ikonos. Selection of images, taking into account inter and intra annual variability of rainfall, enables differentiating between short-term conservancies (e.g., drought and long-term alterations. NDVI and albedo, although comparable to tasseled cap’s brightness and greenness indices, have the advantage of being computed using reflectance values extracted from various Landsat platforms since the early 1970s. It is shown that, over the entire study period, the majority of the Mu Us Sandy Land area remained unchanged. Part of the area (6%, mainly in the east, was under human

  4. Sex & vision I: Spatio-temporal resolution

    Directory of Open Access Journals (Sweden)

    Abramov Israel

    2012-09-01

    Full Text Available Abstract Background Cerebral cortex has a very large number of testosterone receptors, which could be a basis for sex differences in sensory functions. For example, audition has clear sex differences, which are related to serum testosterone levels. Of all major sensory systems only vision has not been examined for sex differences, which is surprising because occipital lobe (primary visual projection area may have the highest density of testosterone receptors in the cortex. We have examined a basic visual function: spatial and temporal pattern resolution and acuity. Methods We tested large groups of young adults with normal vision. They were screened with a battery of standard tests that examined acuity, color vision, and stereopsis. We sampled the visual system’s contrast-sensitivity function (CSF across the entire spatio-temporal space: 6 spatial frequencies at each of 5 temporal rates. Stimuli were gratings with sinusoidal luminance profiles generated on a special-purpose computer screen; their contrast was also sinusoidally modulated in time. We measured threshold contrasts using a criterion-free (forced-choice, adaptive psychophysical method (QUEST algorithm. Also, each individual’s acuity limit was estimated by fitting his or her data with a model and extrapolating to find the spatial frequency corresponding to 100% contrast. Results At a very low temporal rate, the spatial CSF was the canonical inverted-U; but for higher temporal rates, the maxima of the spatial CSFs shifted: Observers lost sensitivity at high spatial frequencies and gained sensitivity at low frequencies; also, all the maxima of the CSFs shifted by about the same amount in spatial frequency. Main effect: there was a significant (ANOVA sex difference. Across the entire spatio-temporal domain, males were more sensitive, especially at higher spatial frequencies; similarly males had significantly better acuity at all temporal rates. Conclusion As with other sensory systems

  5. Stochastic dynamics and irreversibility

    CERN Document Server

    Tomé, Tânia

    2015-01-01

    This textbook presents an exposition of stochastic dynamics and irreversibility. It comprises the principles of probability theory and the stochastic dynamics in continuous spaces, described by Langevin and Fokker-Planck equations, and in discrete spaces, described by Markov chains and master equations. Special concern is given to the study of irreversibility, both in systems that evolve to equilibrium and in nonequilibrium stationary states. Attention is also given to the study of models displaying phase transitions and critical phenomema both in thermodynamic equilibrium and out of equilibrium. These models include the linear Glauber model, the Glauber-Ising model, lattice models with absorbing states such as the contact process and those used in population dynamic and spreading of epidemic, probabilistic cellular automata, reaction-diffusion processes, random sequential adsorption and dynamic percolation. A stochastic approach to chemical reaction is also presented.The textbook is intended for students of ...

  6. Spatio-temporal problems of locomotion control

    International Nuclear Information System (INIS)

    Smolyaninov, Vladimir V

    2000-01-01

    The problem of the spatio-temporal construction of legged movements involves structural freedoms due to the multi-link structure of the extremities, kinematic freedoms of the stepping cycle, and interextremity coordination freedoms, whose purposive organization is established by means of appropriate synergies, i.e. additional functional links the brain's control system forms. The main focus of attention in this work is on the kinematic and coordination synergies of the legged movements of humans and animals. The comparative historical analysis of experimental data and modelling metaphors concentrates on obtaining a unified description, whereas the ultimate mathematical metaphor reduces to space-time geometry, with base step synergies as its invariants. Thus, the concept of a synergetic organization for biomechanical movement freedoms is transformed to the geochronometry concept, actually a modification of Minkowskian geometry. To determine the spectrum of possible geochronometries, the consequences of a generalized 'postulate of a constant speed of light' are studied and different models of wave chronometers compared. (reviews of topical problems)

  7. Spatio-temporal patterns of coral recruitment at Vamizi Island ...

    African Journals Online (AJOL)

    Spatio-temporal patterns of coral recruitment at Vamizi Island, Quirimbas Archipelago, Mozambique. ... Spatial and temporal patterns of recruitment of reef corals were assessed for the first time in Mozambique ... AJOL African Journals Online.

  8. Spatio-temporal evolution of forest fires in Portugal

    Science.gov (United States)

    Tonini, Marj; Pereira, Mário G.; Parente, Joana

    2017-04-01

    A key issue in fire management is the ability to explore and try to predict where and when fires are more likely to occur. This information can be useful to understand the triggering factors of ignitions and for planning strategies to reduce forest fires, to manage the sources of ignition and to identify areas and frame period at risk. Therefore, producing maps displaying forest fires location and their occurrence in time can be of great help for accurately forecasting these hazardous events. In a fire prone country as Portugal, where thousands of events occurs each year, it is involved to drive information about fires over densities and recurrences just by looking at the original arrangement of the mapped ignition points or burnt areas. In this respect, statistical methods originally developed for spatio-temporal stochastic point processes can be employed to find a structure within these large datasets. In the present study, the authors propose an approach to analyze and visualize the evolution in space and in time of forest fires occurred in Portugal during a long frame period (1990 - 2013). Data came from the Portuguese mapped burnt areas official geodatabase (by the Institute for the Conservation of Nature and Forests), which is the result of interpreted satellite measurements. The following statistical analyses were performed: the geographically-weighted summary statistics, to analyze the local variability of the average burned area; the space-time Kernel density, to elaborate smoothed density surfaces representing over densities of fires classed by size and on North vs South region. Finally, we emploied the volume rendering thecnique to visualize the spatio-temporal evolution of these events into a unique map: this representation allows visually inspecting areas and time-step more affected from a high aggregation of forest fires. It results that during the whole investigated period over densities are mainly located in the northern regions, while in the

  9. Markovian Limit of a Spatio-Temporal Correlated Open Systems

    Science.gov (United States)

    Monnai, T.

    Large fluctuation of Brownian particles is affected by the finiteness of the correlation length of the background noise field. Indeed a Fokker—Planck equation is derived in a Markovian limit of a spatio-temporal short correlated noise. Corresponding kinetic quantities are renormalized due to the spatio-temporal memory. We also investigate the case of open system by connecting a thermostat to the system.

  10. Stochastic Switching Dynamics

    DEFF Research Database (Denmark)

    Simonsen, Maria

    This thesis treats stochastic systems with switching dynamics. Models with these characteristics are studied from several perspectives. Initially in a simple framework given in the form of stochastic differential equations and, later, in an extended form which fits into the framework of sliding...... mode control. It is investigated how to understand and interpret solutions to models of switched systems, which are exposed to discontinuous dynamics and uncertainties (primarily) in the form of white noise. The goal is to gain knowledge about the performance of the system by interpreting the solution...

  11. Visualization and assessment of spatio-temporal covariance properties

    KAUST Repository

    Huang, Huang

    2017-11-23

    Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random fields in geostatistical data. For second-order stationary random fields, there exist subclasses of covariance functions that assume a simpler spatio-temporal dependence structure with separability and full symmetry. However, it is challenging to visualize and assess separability and full symmetry from spatio-temporal observations. In this work, we propose a functional data analysis approach that constructs test functions using the cross-covariances from time series observed at each pair of spatial locations. These test functions of temporal lags summarize the properties of separability or symmetry for the given spatial pairs. We use functional boxplots to visualize the functional median and the variability of the test functions, where the extent of departure from zero at all temporal lags indicates the degree of non-separability or asymmetry. We also develop a rank-based nonparametric testing procedure for assessing the significance of the non-separability or asymmetry. Essentially, the proposed methods only require the analysis of temporal covariance functions. Thus, a major advantage over existing approaches is that there is no need to estimate any covariance matrix for selected spatio-temporal lags. The performances of the proposed methods are examined by simulations with various commonly used spatio-temporal covariance models. To illustrate our methods in practical applications, we apply it to real datasets, including weather station data and climate model outputs.

  12. Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform

    International Nuclear Information System (INIS)

    Tascikaraoglu, Akin; Sanandaji, Borhan M.; Poolla, Kameshwar; Varaiya, Pravin

    2016-01-01

    Highlights: • We propose a spatio-temporal approach for wind speed forecasting. • The method is based on a combination of Wavelet decomposition and structured-sparse recovery. • Our analyses confirm that low-dimensional structures govern the interactions between stations. • Our method particularly shows improvements for profiles with high ramps. • We examine our approach on real data and illustrate its superiority over a set of benchmark models. - Abstract: Integration of renewable energy resources into the power grid is essential in achieving the envisioned sustainable energy future. Stochasticity and intermittency characteristics of renewable energies, however, present challenges for integrating these resources into the existing grid in a large scale. Reliable renewable energy integration is facilitated by accurate wind forecasts. In this paper, we propose a novel wind speed forecasting method which first utilizes Wavelet Transform (WT) for decomposition of the wind speed data into more stationary components and then uses a spatio-temporal model on each sub-series for incorporating both temporal and spatial information. The proposed spatio-temporal forecasting approach on each sub-series is based on the assumption that there usually exists an intrinsic low-dimensional structure between time series data in a collection of meteorological stations. Our approach is inspired by Compressive Sensing (CS) and structured-sparse recovery algorithms. Based on detailed case studies, we show that the proposed approach based on exploiting the sparsity of correlations between a large set of meteorological stations and decomposing time series for higher-accuracy forecasts considerably improve the short-term forecasts compared to the temporal and spatio-temporal benchmark methods.

  13. Learning of spatio-temporal codes in a coupled oscillator system.

    Science.gov (United States)

    Orosz, Gábor; Ashwin, Peter; Townley, Stuart

    2009-07-01

    In this paper, we consider a learning strategy that allows one to transmit information between two coupled phase oscillator systems (called teaching and learning systems) via frequency adaptation. The dynamics of these systems can be modeled with reference to a number of partially synchronized cluster states and transitions between them. Forcing the teaching system by steady but spatially nonhomogeneous inputs produces cyclic sequences of transitions between the cluster states, that is, information about inputs is encoded via a "winnerless competition" process into spatio-temporal codes. The large variety of codes can be learned by the learning system that adapts its frequencies to those of the teaching system. We visualize the dynamics using "weighted order parameters (WOPs)" that are analogous to "local field potentials" in neural systems. Since spatio-temporal coding is a mechanism that appears in olfactory systems, the developed learning rules may help to extract information from these neural ensembles.

  14. Climate-driven changes to the spatio-temporal distribution of the parasitic nematode, Haemonchus contortus, in sheep in Europe.

    Science.gov (United States)

    Rose, Hannah; Caminade, Cyril; Bolajoko, Muhammad Bashir; Phelan, Paul; van Dijk, Jan; Baylis, Matthew; Williams, Diana; Morgan, Eric R

    2016-03-01

    Recent climate change has resulted in changes to the phenology and distribution of invertebrates worldwide. Where invertebrates are associated with disease, climate variability and changes in climate may also affect the spatio-temporal dynamics of disease. Due to its significant impact on sheep production and welfare, the recent increase in diagnoses of ovine haemonchosis caused by the nematode Haemonchus contortus in some temperate regions is particularly concerning. This study is the first to evaluate the impact of climate change on H. contortus at a continental scale. A model of the basic reproductive quotient of macroparasites, Q0 , adapted to H. contortus and extended to incorporate environmental stochasticity and parasite behaviour, was used to simulate Pan-European spatio-temporal changes in H. contortus infection pressure under scenarios of climate change. Baseline Q0 simulations, using historic climate observations, reflected the current distribution of H. contortus in Europe. In northern Europe, the distribution of H. contortus is currently limited by temperatures falling below the development threshold during the winter months and within-host arrested development is necessary for population persistence over winter. In southern Europe, H. contortus infection pressure is limited during the summer months by increased temperature and decreased moisture. Compared with this baseline, Q0 simulations driven by a climate model ensemble predicted an increase in H. contortus infection pressure by the 2080s. In northern Europe, a temporal range expansion was predicted as the mean period of transmission increased by 2-3 months. A bimodal seasonal pattern of infection pressure, similar to that currently observed in southern Europe, emerges in northern Europe due to increasing summer temperatures and decreasing moisture. The predicted patterns of change could alter the epidemiology of H. contortus in Europe, affect the future sustainability of contemporary

  15. Spatio-temporal Dynamics of Land-use and Land-cover Change: A Multi-agent Simulation Model and Its Application to an Upland Watershed in Central Vietnam

    Science.gov (United States)

    Le, Q.; Vlek, P. L.; Park, S.

    2005-12-01

    Land-use and land-cover change (LUCC) is an essential environmental process that should be monitored and prognosticated to provide a basis for better land management policy. However, LUCC modeling is a challenge due to the complex nature and unexpected behavior of both human drivers and natural constraints. This paper presents a multi-agent-based model to simulate spatio-temporal land-use changes and the interdependent socio-economic dynamics emerging from the complex socio-ecological interactions at micro levels resulting from land-use policy interventions. The model provides land-use scenarios under alternative policy to support decisions on land management for improved rural livelihoods while protecting the environment. In the multi-agent simulation model, the human community is represented by household agents (heterogeneous farming households) with their profiles and decision-making mechanisms about land use. The household profile defines the five asset dimensions of household livelihood (e.g., social, human, financial, natural and physical assets). The land-use decision-making program works by taking inputs from the household profile, perceived spatial environmental attributes, and introduced policies. The decision-making program is a logical procedure that combines a land-use choice model (multi-nominal logistic choices) and anthropological rules. The landscape environment is represented by landscape agents (congruent land patches of 30mx30m) with their state variables and ecological response mechanisms to environmental changes and human interventions. State variables of landscape agents correspond to spatial GIS-raster layers of biophysical, economic, and institutional variables. Ecological mechanisms of landscape agents are represented by internal sub-models of agricultural and forest productivity dynamics, which work in response to the current state, history, and spatial neighbourhood of the landscape agents. A multi-agent based protocol coordinates the

  16. Economic agglomerations and spatio-temporal cycles in a spatial growth model with capital transport cost

    Science.gov (United States)

    Juchem Neto, J. P.; Claeyssen, J. C. R.; Pôrto Júnior, S. S.

    2018-03-01

    In this paper we introduce capital transport cost in a unidimensional spatial Solow-Swan model of economic growth with capital-induced labor migration, considered in an unbounded domain. Proceeding with a stability analysis, we show that there is a critical value for the capital transport cost where the dynamic behavior of the economy changes, provided that the intensity of capital-induced labor migration is strong enough. On the one hand, if the capital transport cost is higher than this critical value, the spatially homogeneous equilibrium of coexistence of the model is stable, and the economy converges to this spatially homogeneous state in the long run; on the other hand, if transport cost is lower than this critical value, the equilibrium is unstable, and the economy may develop different spatio-temporal dynamics, including the formation of stable economic agglomerations and spatio-temporal economic cycles, depending on the other parameters in the model. Finally, numerical simulations support the results of the stability analysis, and illustrate the spatio-temporal dynamics generated by the model, suggesting that the economy as a whole benefits from the formation of economic agglomerations and cycles, with a higher capital transport cost reducing this gain.

  17. Stochastic ice stream dynamics.

    Science.gov (United States)

    Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca

    2016-08-09

    Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.

  18. How spatio-temporal habitat connectivity affects amphibian genetic structure.

    Science.gov (United States)

    Watts, Alexander G; Schlichting, Peter E; Billerman, Shawn M; Jesmer, Brett R; Micheletti, Steven; Fortin, Marie-Josée; Funk, W Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A

    2015-01-01

    Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

  19. How spatio-temporal habitat connectivity affects amphibian genetic structure

    Science.gov (United States)

    Watts, Alexander G.; Schlichting, P; Billerman, S; Jesmer, B; Micheletti, S; Fortin, M.-J.; Funk, W.C.; Hapeman, P; Muths, Erin L.; Murphy, M.A.

    2015-01-01

    Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

  20. STSE: Spatio-Temporal Simulation Environment Dedicated to Biology

    Directory of Open Access Journals (Sweden)

    Gerber Susanne

    2011-04-01

    Full Text Available Abstract Background Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. Results The Spatio-Temporal Simulation Environment (STSE is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images. STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts

  1. STSE: Spatio-Temporal Simulation Environment Dedicated to Biology.

    Science.gov (United States)

    Stoma, Szymon; Fröhlich, Martina; Gerber, Susanne; Klipp, Edda

    2011-04-28

    Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. The Spatio-Temporal Simulation Environment (STSE) is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI) tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images). STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS) and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts of the STSE design and workflow. We

  2. Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance

    Directory of Open Access Journals (Sweden)

    Sebastian Meyer

    2017-05-01

    Full Text Available The availability of geocoded health data and the inherent temporal structure of communicable diseases have led to an increased interest in statistical models and software for spatio-temporal data with epidemic features. The open source R package surveillance can handle various levels of aggregation at which infective events have been recorded: individual-level time-stamped geo-referenced data (case reports in either continuous space or discrete space, as well as counts aggregated by period and region. For each of these data types, the surveillance package implements tools for visualization, likelihoood inference and simulation from recently developed statistical regression frameworks capturing endemic and epidemic dynamics. Altogether, this paper is a guide to the spatio-temporal modeling of epidemic phenomena, exemplified by analyses of public health surveillance data on measles and invasive meningococcal disease.

  3. Evaluation of spatio-temporal Bayesian models for the spread of infectious diseases in oil palm.

    Science.gov (United States)

    Denis, Marie; Cochard, Benoît; Syahputra, Indra; de Franqueville, Hubert; Tisné, Sébastien

    2018-02-01

    In the field of epidemiology, studies are often focused on mapping diseases in relation to time and space. Hierarchical modeling is a common flexible and effective tool for modeling problems related to disease spread. In the context of oil palm plantations infected by the fungal pathogen Ganoderma boninense, we propose and compare two spatio-temporal hierarchical Bayesian models addressing the lack of information on propagation modes and transmission vectors. We investigate two alternative process models to study the unobserved mechanism driving the infection process. The models help gain insight into the spatio-temporal dynamic of the infection by identifying a genetic component in the disease spread and by highlighting a spatial component acting at the end of the experiment. In this challenging context, we propose models that provide assumptions on the unobserved mechanism driving the infection process while making short-term predictions using ready-to-use software. Copyright © 2018 Elsevier Ltd. All rights reserved.

  4. Real time eye tracking using Kalman extended spatio-temporal context learning

    Science.gov (United States)

    Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu

    2017-06-01

    Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

  5. The use of spatio-temporal correlation to forecast critical transitions

    Science.gov (United States)

    Karssenberg, Derek; Bierkens, Marc F. P.

    2010-05-01

    Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in

  6. Spatio-temporal networks: reachability, centrality and robustness.

    Science.gov (United States)

    Williams, Matthew J; Musolesi, Mirco

    2016-06-01

    Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks.

  7. Aspects of second-order analysis of structured inhomogeneous spatio-temporal processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad

    2012-01-01

    Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for general inhomogeneous spatio-temporal point processes and for inhomogeneous spatio-temporal Cox processes. Assuming spatio......-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio-temporal Gaussian process. Another...... concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data....

  8. Second-order analysis of structured inhomogeneous spatio-temporal point processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad

    Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for first general inhomogeneous spatio-temporal point processes and second inhomogeneous spatio-temporal Cox processes. Assuming...... spatio-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates e.g. to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio......-temporal Gaussian process. Another concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data (the UK 2001 epidemic foot and mouth disease data)....

  9. Spatio-temporal Eigenvector Filtering: Application on Bioenergy Crop Impacts

    Science.gov (United States)

    Wang, M.; Kamarianakis, Y.; Georgescu, M.

    2017-12-01

    A suite of 10-year ensemble-based simulations was conducted to investigate the hydroclimatic impacts due to large-scale deployment of perennial bioenergy crops across the continental United States. Given the large size of the simulated dataset (about 60Tb), traditional hierarchical spatio-temporal statistical modelling cannot be implemented for the evaluation of physics parameterizations and biofuel impacts. In this work, we propose a filtering algorithm that takes into account the spatio-temporal autocorrelation structure of the data while avoiding spatial confounding. This method is used to quantify the robustness of simulated hydroclimatic impacts associated with bioenergy crops to alternative physics parameterizations and observational datasets. Results are evaluated against those obtained from three alternative Bayesian spatio-temporal specifications.

  10. DETERMINING SPATIO-TEMPORAL CADASTRAL DATA REQUIREMENT FOR INFRASTRUCTURE OF LADM FOR TURKEY

    Directory of Open Access Journals (Sweden)

    M. Alkan

    2016-06-01

    Full Text Available Nowadays, the nature of land title and cadastral (LTC data in the Turkey is dynamic from a temporal perspective which depends on the LTC operations. Functional requirements with respect to the characteristics are investigated based upon interviews of professionals in public and private sectors. These are; Legal authorities, Land Registry and Cadastre offices, Highway departments, Foundations, Ministries of Budget, Transportation, Justice, Public Works and Settlement, Environment and Forestry, Agriculture and Rural Affairs, Culture and Internal Affairs, State Institute of Statistics (SIS, execution offices, tax offices, real estate offices, private sector, local governments and banks. On the other hand, spatio-temporal LTC data very important component for creating infrastructure of Land Administration Model (LADM. For this reason, spatio-temporal LTC data needs for LADM not only updated but also temporal. The investigations ended up with determine temporal analyses of LTC data, traditional LTC system and tracing temporal analyses in traditional LTC system. In the traditional system, the temporal analyses needed by all these users could not be performed in a rapid and reliable way. The reason for this is that the traditional LTC system is a manual archiving system. The aims and general contents of this paper: (1 define traditional LTC system of Turkey; (2 determining the need for spatio-temporal LTC data and analyses for core domain model for LADM. As a results of temporal and spatio-temporal analysis LTC data needs, new system design is important for the Turkish LADM model. Designing and realizing an efficient and functional Temporal Geographic Information Systems (TGIS is inevitable for the Turkish LADM core infrastructure. Finally this paper outcome is creating infrastructure for design and develop LADM for Turkey.

  11. Determining Spatio-Temporal Cadastral Data Requirement for Infrastructure of Ladm for Turkey

    Science.gov (United States)

    Alkan, M.; Polat, Z. A.

    2016-06-01

    Nowadays, the nature of land title and cadastral (LTC) data in the Turkey is dynamic from a temporal perspective which depends on the LTC operations. Functional requirements with respect to the characteristics are investigated based upon interviews of professionals in public and private sectors. These are; Legal authorities, Land Registry and Cadastre offices, Highway departments, Foundations, Ministries of Budget, Transportation, Justice, Public Works and Settlement, Environment and Forestry, Agriculture and Rural Affairs, Culture and Internal Affairs, State Institute of Statistics (SIS), execution offices, tax offices, real estate offices, private sector, local governments and banks. On the other hand, spatio-temporal LTC data very important component for creating infrastructure of Land Administration Model (LADM). For this reason, spatio-temporal LTC data needs for LADM not only updated but also temporal. The investigations ended up with determine temporal analyses of LTC data, traditional LTC system and tracing temporal analyses in traditional LTC system. In the traditional system, the temporal analyses needed by all these users could not be performed in a rapid and reliable way. The reason for this is that the traditional LTC system is a manual archiving system. The aims and general contents of this paper: (1) define traditional LTC system of Turkey; (2) determining the need for spatio-temporal LTC data and analyses for core domain model for LADM. As a results of temporal and spatio-temporal analysis LTC data needs, new system design is important for the Turkish LADM model. Designing and realizing an efficient and functional Temporal Geographic Information Systems (TGIS) is inevitable for the Turkish LADM core infrastructure. Finally this paper outcome is creating infrastructure for design and develop LADM for Turkey.

  12. Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia

    Science.gov (United States)

    Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu

    2011-01-01

    Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,pQueensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430

  13. Spatio-temporal patterns of tree establishment are indicative of biotic interactions during early invasion of a montane meadow

    Science.gov (United States)

    J.M. Rice; C.B. Halpern; J.A. Antos; J.A. Jones

    2012-01-01

    Tree invasions of grasslands are occurring globally, with profound consequences for ecosystem structure and function. We explore the spatio-temporal dynamics of tree invasion of a montane meadow in the Cascade Mountains of Oregon, where meadow loss is a conservation concern. We examine the early stages of invasion, where extrinsic and intrinsic processes can be clearly...

  14. Spatio-Temporal Data Mining for Location-Based Services

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo

    . The objectives of the presented thesis are three-fold. First, to extend popular data mining methods to the spatio-temporal domain. Second, to demonstrate the usefulness of the extended methods and the derived knowledge in promising LBS examples. Finally, to eliminate privacy concerns in connection with spatio......-temporal data mining by devising systems for privacy-preserving location data collection and mining.......Location-Based Services (LBS) are continuously gaining popularity. Innovative LBSes integrate knowledge about the users into the service. Such knowledge can be derived by analyzing the location data of users. Such data contain two unique dimensions, space and time, which need to be analyzed...

  15. Spatio-temporal databases complex motion pattern queries

    CERN Document Server

    Vieira, Marcos R

    2013-01-01

    This brief presents several new query processing techniques, called complex motion pattern queries, specifically designed for very large spatio-temporal databases of moving objects. The brief begins with the definition of flexible pattern queries, which are powerful because of the integration of variables and motion patterns. This is followed by a summary of the expressive power of patterns and flexibility of pattern queries. The brief then present the Spatio-Temporal Pattern System (STPS) and density-based pattern queries. STPS databases contain millions of records with information about mobi

  16. Spatio-temporal modeling of nonlinear distributed parameter systems

    CERN Document Server

    Li, Han-Xiong

    2011-01-01

    The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s

  17. Estimating the state of large spatio-temporally chaotic systems

    International Nuclear Information System (INIS)

    Ott, E.; Hunt, B.R.; Szunyogh, I.; Zimin, A.V.; Kostelich, E.J.; Corazza, M.; Kalnay, E.; Patil, D.J.; Yorke, J.A.

    2004-01-01

    We consider the estimation of the state of a large spatio-temporally chaotic system from noisy observations and knowledge of a system model. Standard state estimation techniques using the Kalman filter approach are not computationally feasible for systems with very many effective degrees of freedom. We present and test a new technique (called a Local Ensemble Kalman Filter), generally applicable to large spatio-temporally chaotic systems for which correlations between system variables evaluated at different points become small at large separation between the points

  18. Dynamics of stochastic systems

    CERN Document Server

    Klyatskin, Valery I

    2005-01-01

    Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in fluid and subjected to random molecular bombardment laid the foundation for modern stochastic calculus and statistical physics. Other important examples include turbulent transport and diffusion of particle-tracers (pollutants), or continuous densities (''''oil slicks''''), wave propagation and scattering in randomly inhomogeneous media, for instance light or sound propagating in the turbulent atmosphere.Such models naturally render to statistical description, where the input parameters and solutions are expressed by random processes and fields.The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of ...

  19. MODELLING AND SIMULATION OF A NEUROPHYSIOLOGICAL EXPERIMENT BY SPATIO-TEMPORAL POINT PROCESSES

    Directory of Open Access Journals (Sweden)

    Viktor Beneš

    2011-05-01

    Full Text Available We present a stochastic model of an experimentmonitoring the spiking activity of a place cell of hippocampus of an experimental animal moving in an arena. Doubly stochastic spatio-temporal point process is used to model and quantify overdispersion. Stochastic intensity is modelled by a Lévy based random field while the animal path is simplified to a discrete random walk. In a simulation study first a method suggested previously is used. Then it is shown that a solution of the filtering problem yields the desired inference to the random intensity. Two approaches are suggested and the new one based on finite point process density is applied. Using Markov chain Monte Carlo we obtain numerical results from the simulated model. The methodology is discussed.

  20. Spatio-temporal point process filtering methods with an application

    Czech Academy of Sciences Publication Activity Database

    Frcalová, B.; Beneš, V.; Klement, Daniel

    2010-01-01

    Roč. 21, 3-4 (2010), s. 240-252 ISSN 1180-4009 R&D Projects: GA AV ČR(CZ) IAA101120604 Institutional research plan: CEZ:AV0Z50110509 Keywords : cox point process * filtering * spatio-temporal modelling * spike Subject RIV: BA - General Mathematics Impact factor: 0.750, year: 2010

  1. Spatio-temporal analysis of Salmonella surveillance data in Thailand

    DEFF Research Database (Denmark)

    Coutinho Calado Domingues, Ana Rita; Vieira, Antonio; Hendriksen, Rene S.

    2014-01-01

    This study evaluates the usefulness of spatio-temporal statistical tools to detect outbreaks using routine surveillance data where limited epidemiological information is available. A dataset from 2002 to 2007 containing information regarding date, origin, source and serotype of 29 586 Salmonella ...

  2. On spatio-temporal Lévy based Cox processes

    DEFF Research Database (Denmark)

    Prokesova, Michaela; Hellmund, Gunnar; Jensen, Eva Bjørn Vedel

    2006-01-01

    The paper discusses a new class of models for spatio-temporal Cox point processes. In these models, the driving field is defined by means of an integral of a weight function with respect to a Lévy basis. The relations to other Cox process models studied previously are discussed and formulas for t...

  3. Spatio-temporal joins on symbolic indoor tracking data

    DEFF Research Database (Denmark)

    Lu, Hua; Yang, Bin; Jensen, Christian S.

    2011-01-01

    and studies probabilistic, spatio-temporal joins on historical indoor tracking data. Two meaningful types of join are defined. They return object pairs that satisfy spatial join predicates either at a time point or during a time interval. The predicates considered include “same X,” where X is a semantic...

  4. Control and characterization of spatio-temporal disorder in ...

    Indian Academy of Sciences (India)

    characterizing the type of spatio-temporal disorder that is embodied in this disordered ... The results from this experiment will shed light on the more general questions ... sponds to only odd or even multiples of the common frequency, ω0. Thus ...

  5. Simultaneous spatio-temporal focusing for tissue manipulation

    Directory of Open Access Journals (Sweden)

    Squier J.

    2013-11-01

    Full Text Available Simultaneous spatiotemporal focusing (SSTF is applied to lens tissue and compared directly with standard femtosecond micromachining of the tissue at the same numerical aperture. Third harmonic generation imaging is used for spatio-temporal characterization of the processing conditions obtained with both a standard and SSTF focus.

  6. Symbolic analysis of spatio-temporal systems: The measurement problem

    International Nuclear Information System (INIS)

    Brown, R.; Tang, Xianzhu; Tracy, E.R.

    1996-01-01

    We consider the problem of measuring physical quantities using time-series observations. The approach taken is to validate theoretical models which are derived heuristically or from first principles. The fitting of parameters in such models constitutes the measurement. This is a basic problem in measurement science and a wide array of tools are available. However, an important gap in the present toolkit exists when the system of interest, and hence the models used, exhibit chaotic or turbulent behavior. The development of reliable schemes for analyzing such signals is necessary before one can claim to have a quantitative understanding of the underlying physics. In experimental situations, the number of independently measured time-series is limited, but the number of dynamical degrees of freedom can be large. In addition, the signals of interest will typically be embedded in a noisy background. In the symbol statistics approach, the time-series is coarse-grained and converted into a long, symbol stream. The probability of occurrence of various symbol sequences of fixed length constitutes the symbol statistics. These statistics contain a wealth of information about the underlying dynamics and, as we shall discuss, can be used to validate models. Previously, we have applied this symbolic approach to low dimensional systems with great success. The symbol statistics are robust up to noise/signal ∼20%. At higher noise levels the symbol statistics are biased, but in a relatively simple manner. By including the noise characteristics into the model, we were able to use the symbol statistics to measure parameters even when signal/noise is ∼ O(1). More recently, we have extended the symbolic approach to spatio-temporal systems. We have considered both coupled-map lattices and the complex Ginzburg-Landau equation. This equation arises generically near the onset of instabilities

  7. Spatio-temporal coupling of EEG signals in epilepsy

    Science.gov (United States)

    Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

    2011-05-01

    Approximately 1% of the world's population suffer from epileptic seizures throughout their lives that mostly come without sign or warning. Thus, epilepsy is the most common chronical disorder of the neurological system. In the past decades, the problem of detecting a pre-seizure state in epilepsy using EEG signals has been addressed in many contributions by various authors over the past two decades. Up to now, the goal of identifying an impending epileptic seizure with sufficient specificity and reliability has not yet been achieved. Cellular Nonlinear Networks (CNN) are characterized by local couplings of dynamical systems of comparably low complexity. Thus, they are well suited for an implementation as highly parallel analogue processors. Programmable sensor-processor realizations of CNN combine high computational power comparable to tera ops of digital processors with low power consumption. An algorithm allowing an automated and reliable detection of epileptic seizure precursors would be a"huge step" towards the vision of an implantable seizure warning device that could provide information to patients and for a time/event specific treatment directly in the brain. Recent contributions have shown that modeling of brain electrical activity by solutions of Reaction-Diffusion-CNN as well as the application of a CNN predictor taking into account values of neighboring electrodes may contribute to the realization of a seizure warning device. In this paper, a CNN based predictor corresponding to a spatio-temporal filter is applied to multi channel EEG data in order to identify mutual couplings for different channels which lead to a enhanced prediction quality. Long term EEG recordings of different patients are considered. Results calculated for these recordings with inter-ictal phases as well as phases with seizures will be discussed in detail.

  8. Effective and efficient analysis of spatio-temporal data

    Science.gov (United States)

    Zhang, Zhongnan

    Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen

  9. A Mixed Land Cover Spatio-temporal Data Model Based on Object-oriented and Snapshot

    Directory of Open Access Journals (Sweden)

    LI Yinchao

    2016-07-01

    Full Text Available Spatio-temporal data model (STDM is one of the hot topics in the domains of spatio-temporal database and data analysis. There is a common view that a universal STDM is always of high complexity due to the various situation of spatio-temporal data. In this article, a mixed STDM is proposed based on object-oriented and snapshot models for modelling and analyzing landcover change (LCC. This model uses the object-oriented STDM to describe the spatio-temporal processes of land cover patches and organize their spatial and attributive properties. In the meantime, it uses the snapshot STDM to present the spatio-temporal distribution of LCC on the whole via snapshot images. The two types of models are spatially and temporally combined into a mixed version. In addition to presenting the spatio-temporal events themselves, this model could express the transformation events between different classes of spatio-temporal objects. It can be used to create database for historical data of LCC, do spatio-temporal statistics, simulation and data mining with the data. In this article, the LCC data in Heilongjiang province is used for case study to validate spatio-temporal data management and analysis abilities of mixed STDM, including creating database, spatio-temporal query, global evolution analysis and patches spatio-temporal process expression.

  10. Approximate spatio-temporal top-k publish/subscribe

    KAUST Repository

    Chen, Lisi; Shang, Shuo

    2018-01-01

    Location-based publish/subscribe plays a significant role in mobile information disseminations. In this light, we propose and study a novel problem of processing location-based top-k subscriptions over spatio-temporal data streams. We define a new type of approximate location-based top-k subscription, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription, that continuously feeds users with relevant spatio-temporal messages by considering textual similarity, spatial proximity, and information freshness. Different from existing location-based top-k subscriptions, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription can automatically adjust the triggering condition by taking the triggering score of other subscriptions into account. The group filtering efficacy can be substantially improved by sacrificing the publishing result quality with a bounded guarantee. We conduct extensive experiments on two real datasets to demonstrate the performance of the developed solutions.

  11. Spatial and spatio-temporal bayesian models with R - INLA

    CERN Document Server

    Blangiardo, Marta

    2015-01-01

    Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior Distr

  12. Approximate spatio-temporal top-k publish/subscribe

    KAUST Repository

    Chen, Lisi

    2018-04-26

    Location-based publish/subscribe plays a significant role in mobile information disseminations. In this light, we propose and study a novel problem of processing location-based top-k subscriptions over spatio-temporal data streams. We define a new type of approximate location-based top-k subscription, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription, that continuously feeds users with relevant spatio-temporal messages by considering textual similarity, spatial proximity, and information freshness. Different from existing location-based top-k subscriptions, Approximate Temporal Spatial-Keyword Top-k (ATSK) Subscription can automatically adjust the triggering condition by taking the triggering score of other subscriptions into account. The group filtering efficacy can be substantially improved by sacrificing the publishing result quality with a bounded guarantee. We conduct extensive experiments on two real datasets to demonstrate the performance of the developed solutions.

  13. A Spatio-Temporal Analysis of Mitochondrial DNA Haplogroup I

    Directory of Open Access Journals (Sweden)

    Revesz Peter Z.

    2016-01-01

    Full Text Available The recent recovery of ancient DNA from a growing number of human samples shows that mitochondrial DNA haplogroup I was introduced to Europe after the end of the Last Glacial Maximum. This paper provides a spatio-temporal analysis of the various subhaplogroups of mitochondrial DNA I. The study suggests that haplogroup I diversified into haplogroups I1, I2’3, I4 and I5 at specific regions in Eurasia and then spread southward to Crete and Egypt.

  14. Reliable Collaborative Filtering on Spatio-Temporal Privacy Data

    Directory of Open Access Journals (Sweden)

    Zhen Liu

    2017-01-01

    Full Text Available Lots of multilayer information, such as the spatio-temporal privacy check-in data, is accumulated in the location-based social network (LBSN. When using the collaborative filtering algorithm for LBSN location recommendation, one of the core issues is how to improve recommendation performance by combining the traditional algorithm with the multilayer information. The existing approaches of collaborative filtering use only the sparse user-item rating matrix. It entails high computational complexity and inaccurate results. A novel collaborative filtering-based location recommendation algorithm called LGP-CF, which takes spatio-temporal privacy information into account, is proposed in this paper. By mining the users check-in behavior pattern, the dataset is segmented semantically to reduce the data size that needs to be computed. Then the clustering algorithm is used to obtain and narrow the set of similar users. User-location bipartite graph is modeled using the filtered similar user set. Then LGP-CF can quickly locate the location and trajectory of users through message propagation and aggregation over the graph. Through calculating users similarity by spatio-temporal privacy data on the graph, we can finally calculate the rating of recommendable locations. Experiments results on the physical clusters indicate that compared with the existing algorithms, the proposed LGP-CF algorithm can make recommendations more accurately.

  15. Introduction to stochastic dynamic programming

    CERN Document Server

    Ross, Sheldon M; Lukacs, E

    1983-01-01

    Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the

  16. Mitigating Spam Using Spatio-Temporal Reputation

    Science.gov (United States)

    2010-01-01

    scalable; computation can occur in near real-time and over 500,000 emails can be scored an hour. 1 Introduction Roughly 90% of the total volume of email on...Sokolsky, and J. M. Smith. Dynamic trust management. IEEE Computer (Special Issue on Trust Mangement ), 2009. [11] P. Boykins and B. Roychowdhury

  17. Spatio-temporal spike train analysis for large scale networks using the maximum entropy principle and Monte Carlo method

    International Nuclear Information System (INIS)

    Nasser, Hassan; Cessac, Bruno; Marre, Olivier

    2013-01-01

    Understanding the dynamics of neural networks is a major challenge in experimental neuroscience. For that purpose, a modelling of the recorded activity that reproduces the main statistics of the data is required. In the first part, we present a review on recent results dealing with spike train statistics analysis using maximum entropy models (MaxEnt). Most of these studies have focused on modelling synchronous spike patterns, leaving aside the temporal dynamics of the neural activity. However, the maximum entropy principle can be generalized to the temporal case, leading to Markovian models where memory effects and time correlations in the dynamics are properly taken into account. In the second part, we present a new method based on Monte Carlo sampling which is suited for the fitting of large-scale spatio-temporal MaxEnt models. The formalism and the tools presented here will be essential to fit MaxEnt spatio-temporal models to large neural ensembles. (paper)

  18. McMaster Mesonet soil moisture dataset: description and spatio-temporal variability analysis

    Directory of Open Access Journals (Sweden)

    K. C. Kornelsen

    2013-04-01

    Full Text Available This paper introduces and describes the hourly, high-resolution soil moisture dataset continuously recorded by the McMaster Mesonet located in the Hamilton-Halton Watershed in Southern Ontario, Canada. The McMaster Mesonet consists of a network of time domain reflectometer (TDR probes collecting hourly soil moisture data at six depths between 10 cm and 100 cm at nine locations per site, spread across four sites in the 1250 km2 watershed. The sites for the soil moisture arrays are designed to further improve understanding of soil moisture dynamics in a seasonal climate and to capture soil moisture transitions in areas that have different topography, soil and land cover. The McMaster Mesonet soil moisture constitutes a unique database in Canada because of its high spatio-temporal resolution. In order to provide some insight into the dominant processes at the McMaster Mesonet sites, a spatio-temporal and temporal stability analysis were conducted to identify spatio-temporal patterns in the data and to suggest some physical interpretation of soil moisture variability. It was found that the seasonal climate of the Great Lakes Basin causes a transition in soil moisture patterns at seasonal timescales. During winter and early spring months, and at the meadow sites, soil moisture distribution is governed by topographic redistribution, whereas following efflorescence in the spring and summer, soil moisture spatial distribution at the forested site was also controlled by vegetation canopy. Analysis of short-term temporal stability revealed that the relative difference between sites was maintained unless there was significant rainfall (> 20 mm or wet conditions a priori. Following a disturbance in the spatial soil moisture distribution due to wetting, the relative soil moisture pattern re-emerged in 18 to 24 h. Access to the McMaster Mesonet data can be provided by visiting www.hydrology.mcmaster.ca/mesonet.

  19. A Fresh Look at Spatio-Temporal Remote Sensing Data: Data Formats, Processing Flow, and Visualization

    Science.gov (United States)

    Gens, R.

    2017-12-01

    With increasing number of experimental and operational satellites in orbit, remote sensing based mapping and monitoring of the dynamic Earth has entered into the realm of `big data'. Just the Landsat series of satellites provide a near continuous archive of 45 years of data. The availability of such spatio-temporal datasets has created opportunities for long-term monitoring diverse features and processes operating on the Earth's terrestrial and aquatic systems. Processes such as erosion, deposition, subsidence, uplift, evapotranspiration, urbanization, land-cover regime shifts can not only be monitored and change can be quantified using time-series data analysis. This unique opportunity comes with new challenges in management, analysis, and visualization of spatio-temporal datasets. Data need to be stored in a user-friendly format, and relevant metadata needs to be recorded, to allow maximum flexibility for data exchange and use. Specific data processing workflows need to be defined to support time-series analysis for specific applications. Value-added data products need to be generated keeping in mind the needs of the end-users, and using best practices in complex data visualization. This presentation systematically highlights the various steps for preparing spatio-temporal remote sensing data for time series analysis. It showcases a prototype workflow for remote sensing based change detection that can be generically applied while preserving the application-specific fidelity of the datasets. The prototype includes strategies for visualizing change over time. This has been exemplified using a time-series of optical and SAR images for visualizing the changing glacial, coastal, and wetland landscapes in parts of Alaska.

  20. Dynamic Stochastic Superresolution of sparsely observed turbulent systems

    International Nuclear Information System (INIS)

    Branicki, M.; Majda, A.J.

    2013-01-01

    Real-time capture of the relevant features of the unresolved turbulent dynamics of complex natural systems from sparse noisy observations and imperfect models is a notoriously difficult problem. The resulting lack of observational resolution and statistical accuracy in estimating the important turbulent processes, which intermittently send significant energy to the large-scale fluctuations, hinders efficient parameterization and real-time prediction using discretized PDE models. This issue is particularly subtle and important when dealing with turbulent geophysical systems with an vast range of interacting spatio-temporal scales and rough energy spectra near the mesh scale of numerical models. Here, we introduce and study a suite of general Dynamic Stochastic Superresolution (DSS) algorithms and show that, by appropriately filtering sparse regular observations with the help of cheap stochastic exactly solvable models, one can derive stochastically ‘superresolved’ velocity fields and gain insight into the important characteristics of the unresolved dynamics, including the detection of the so-called black swans. The DSS algorithms operate in Fourier domain and exploit the fact that the coarse observation network aliases high-wavenumber information into the resolved waveband. It is shown that these cheap algorithms are robust and have significant skill on a test bed of turbulent solutions from realistic nonlinear turbulent spatially extended systems in the presence of a significant model error. In particular, the DSS algorithms are capable of successfully capturing time-localized extreme events in the unresolved modes, and they provide good and robust skill for recovery of the unresolved processes in terms of pattern correlation. Moreover, we show that DSS improves the skill for recovering the primary modes associated with the sparse observation mesh which is equally important in applications. The skill of the various DSS algorithms depends on the energy spectrum

  1. Using climate information to understand the spatio-temporal heterogeneity of a chikungunya outbreak in the presence of widespread asymptomatic infection

    Science.gov (United States)

    Dommar, C. J.; Lowe, R.; Robinson, M.; Rodó, X.

    2013-12-01

    The emergence and persistence of human pathogens in the environment represents a constant threat to society, with global implications for human health, economies and ecosystems. Of particular concern are vector-borne diseases, such as dengue, malaria and chikungunya, which are increasing across their traditional ranges and continuing to infiltrate new regions. This unprecedented situation has been partly attributed to the increase in global temperatures in recent decades which has allowed non-native mosquito species to invade and successfully colonise previously inhospitable environments The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. In turn, vector populations are thought to be driven by external environmental variables, such as precipitation and temperature. Furthermore, the ability of asymptomatic individuals to successfully transmit the infection and evade control measures can undermine public health interventions. We employed a stochastic model, which explicitly included asymptomatic and undocumented laboratory confirmed cases, and applied it to a documented outbreak in Cambodia in 2012 (Trapeang Roka village, Kampong Speu Province). The resulting estimate of the reproduction number was considerably higher than values obtained for previous outbreaks and highlights the importance of asymptomatic transmission. Subsequently, we develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals alone is

  2. Climate-driven mathematical models to understand the spatio-temporal heterogeneity of a chikungunya outbreak in the presence of widespread asymptomatic infection

    Science.gov (United States)

    Dommar, Carlos J.; Robinson, Marguerite; Lowe, Rachel; Conan, Anne; Buchy, Philippe; Tarantola, Arnaud; Rodó, Xavier

    2014-05-01

    The emergence and persistence of human pathogens in the environment represents a constant threat to society, with global implications for human health, economies and ecosystems. Of particular concern are vector-borne diseases, such as dengue, malaria and chikungunya, which are increasing across their traditional ranges and continuing to infiltrate new regions. This unprecedented situation has been partly attributed to the increase in global temperatures in recent decades which has allowed non-native mosquito species to invade and successfully colonise previously inhospitable environments. The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. In turn, vector populations are thought to be driven by external environmental variables, such as precipitation and temperature. Furthermore, the ability of asymptomatic individuals to successfully transmit the infection and evade control measures can undermine public health interventions. We employed a stochastic model, which explicitly included asymptomatic and undocumented laboratory confirmed cases, and applied it to a documented outbreak in Cambodia in 2012 (Trapeang Roka village, Kampong Speu Province). The resulting estimate of the reproduction number was considerably higher than values obtained for previous outbreaks and highlights the importance of asymptomatic transmission. Subsequently, we develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals alone is

  3. Stochastic runaway of dynamical systems

    International Nuclear Information System (INIS)

    Pfirsch, D.; Graeff, P.

    1984-10-01

    One-dimensional, stochastic, dynamical systems are well studied with respect to their stability properties. Less is known for the higher dimensional case. This paper derives sufficient and necessary criteria for the asymptotic divergence of the entropy (runaway) and sufficient ones for the moments of n-dimensional, stochastic, dynamical systems. The crucial implication is the incompressibility of their flow defined by the equations of motion in configuration space. Two possible extensions to compressible flow systems are outlined. (orig.)

  4. Modeling and Statistical Analysis of the Spatio-Temporal Patterns of Seasonal Influenza in Israel

    Science.gov (United States)

    Katriel, Guy; Yaari, Rami; Roll, Uri; Stone, Lewi

    2012-01-01

    Background Seasonal influenza outbreaks are a serious burden for public health worldwide and cause morbidity to millions of people each year. In the temperate zone influenza is predominantly seasonal, with epidemics occurring every winter, but the severity of the outbreaks vary substantially between years. In this study we used a highly detailed database, which gave us both temporal and spatial information of influenza dynamics in Israel in the years 1998–2009. We use a discrete-time stochastic epidemic SIR model to find estimates and credible confidence intervals of key epidemiological parameters. Findings Despite the biological complexity of the disease we found that a simple SIR-type model can be fitted successfully to the seasonal influenza data. This was true at both the national levels and at the scale of single cities.The effective reproductive number Re varies between the different years both nationally and among Israeli cities. However, we did not find differences in Re between different Israeli cities within a year. R e was positively correlated to the strength of the spatial synchronization in Israel. For those years in which the disease was more “infectious”, then outbreaks in different cities tended to occur with smaller time lags. Our spatial analysis demonstrates that both the timing and the strength of the outbreak within a year are highly synchronized between the Israeli cities. We extend the spatial analysis to demonstrate the existence of high synchrony between Israeli and French influenza outbreaks. Conclusions The data analysis combined with mathematical modeling provided a better understanding of the spatio-temporal and synchronization dynamics of influenza in Israel and between Israel and France. Altogether, we show that despite major differences in demography and weather conditions intra-annual influenza epidemics are tightly synchronized in both their timing and magnitude, while they may vary greatly between years. The predominance of

  5. Stochastic population dynamics in spatially extended predator-prey systems

    Science.gov (United States)

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

    2018-02-01

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

  6. Visual search of cyclic spatio-temporal events

    Science.gov (United States)

    Gautier, Jacques; Davoine, Paule-Annick; Cunty, Claire

    2018-05-01

    The analysis of spatio-temporal events, and especially of relationships between their different dimensions (space-time-thematic attributes), can be done with geovisualization interfaces. But few geovisualization tools integrate the cyclic dimension of spatio-temporal event series (natural events or social events). Time Coil and Time Wave diagrams represent both the linear time and the cyclic time. By introducing a cyclic temporal scale, these diagrams may highlight the cyclic characteristics of spatio-temporal events. However, the settable cyclic temporal scales are limited to usual durations like days or months. Because of that, these diagrams cannot be used to visualize cyclic events, which reappear with an unusual period, and don't allow to make a visual search of cyclic events. Also, they don't give the possibility to identify the relationships between the cyclic behavior of the events and their spatial features, and more especially to identify localised cyclic events. The lack of possibilities to represent the cyclic time, outside of the temporal diagram of multi-view geovisualization interfaces, limits the analysis of relationships between the cyclic reappearance of events and their other dimensions. In this paper, we propose a method and a geovisualization tool, based on the extension of Time Coil and Time Wave, to provide a visual search of cyclic events, by allowing to set any possible duration to the diagram's cyclic temporal scale. We also propose a symbology approach to push the representation of the cyclic time into the map, in order to improve the analysis of relationships between space and the cyclic behavior of events.

  7. Spatio-temporal imaging of the hemoglobin in the compressed breast with diffuse optical tomography

    Science.gov (United States)

    Boverman, Gregory; Fang, Qianqian; Carp, Stefan A.; Miller, Eric L.; Brooks, Dana H.; Selb, Juliette; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.

    2007-07-01

    We develop algorithms for imaging the time-varying optical absorption within the breast given diffuse optical tomographic data collected over a time span that is long compared to the dynamics of the medium. Multispectral measurements allow for the determination of the time-varying total hemoglobin concentration and of oxygen saturation. To facilitate the image reconstruction, we decompose the hemodynamics in time into a linear combination of spatio-temporal basis functions, the coefficients of which are estimated using all of the data simultaneously, making use of a Newton-based nonlinear optimization algorithm. The solution of the extremely large least-squares problem which arises in computing the Newton update is obtained iteratively using the LSQR algorithm. A Laplacian spatial regularization operator is applied, and, in addition, we make use of temporal regularization which tends to encourage similarity between the images of the spatio-temporal coefficients. Results are shown for an extensive simulation, in which we are able to image and quantify localized changes in both total hemoglobin concentration and oxygen saturation. Finally, a breast compression study has been performed for a normal breast cancer screening subject, using an instrument which allows for highly accurate co-registration of multispectral diffuse optical measurements with an x-ray tomosynthesis image of the breast. We are able to quantify the global return of blood to the breast following compression, and, in addition, localized changes are observed which correspond to the glandular region of the breast.

  8. Stochastic dynamics and control

    CERN Document Server

    Sun, Jian-Qiao; Zaslavsky, George

    2006-01-01

    This book is a result of many years of author's research and teaching on random vibration and control. It was used as lecture notes for a graduate course. It provides a systematic review of theory of probability, stochastic processes, and stochastic calculus. The feedback control is also reviewed in the book. Random vibration analyses of SDOF, MDOF and continuous structural systems are presented in a pedagogical order. The application of the random vibration theory to reliability and fatigue analysis is also discussed. Recent research results on fatigue analysis of non-Gaussian stress proc

  9. Spatio-Temporal Encoding in Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik

    2005-01-01

    In this dissertation two methods for spatio-temporal encoding in medical ultrasound imaging are investigated. The first technique is based on a frequency division approach. Here, the available spectrum of the transducer is divided into a set of narrow bands. A waveform is designed for each band...... the signal to noise ratio and simultaneously the penetration depth so that the medical doctor can image deeper lying structures. The method is tested both experimentally and in simulation and has also evaluated for the purpose of blood flow estimation. The work presented is based on four papers which...

  10. Scalable Top-k Spatio-Temporal Term Querying

    DEFF Research Database (Denmark)

    Skovsgaard, Anders; Sidlauskas, Darius; Jensen, Christian Søndergaard

    2014-01-01

    With the rapidly increasing deployment of Internet-connected, location-aware mobile devices, very large and increasing amounts of geo-tagged and timestamped user-generated content, such as microblog posts, are being generated. We present indexing, update, and query processing techniques...... that are capable of providing the top-k terms seen in posts in a user-specified spatio-temporal range. The techniques enable interactive response times in the millisecond range in a realistic setting where the arrival rate of posts exceeds today's average tweet arrival rate by a factor of 4-10. The techniques...

  11. Image sequence analysis using spatio-temporal texture

    International Nuclear Information System (INIS)

    Sengupta, S.K.; Clark, G.A.; Barnes, F.L.; Schaich, P.C.

    1994-01-01

    The authors have developed and coded an algorithm for motion pattern classification based on spatio-temporal texture. The algorithm has been implemented and tested for the detection of wakes in simulated data with a relatively low signal-to-noise ratio (0.7 dB). Using a open-quote hold one out close-quote method, a detection probability of 100% with a 0% false alarm rate has been achieved on the limited number of samples (47 in each category) tested. The actual detection can be displayed in the form of a movie that can effectively show the submarine tracks based on the detected wake locations

  12. Spatio-temporal analysis of blood perfusion by imaging photoplethysmography

    Science.gov (United States)

    Zaunseder, Sebastian; Trumpp, Alexander; Ernst, Hannes; Förster, Michael; Malberg, Hagen

    2018-02-01

    Imaging photoplethysmography (iPPG) has attracted much attention over the last years. The vast majority of works focuses on methods to reliably extract the heart rate from videos. Only a few works addressed iPPGs ability to exploit spatio-temporal perfusion pattern to derive further diagnostic statements. This work directs at the spatio-temporal analysis of blood perfusion from videos. We present a novel algorithm that bases on the two-dimensional representation of the blood pulsation (perfusion map). The basic idea behind the proposed algorithm consists of a pairwise estimation of time delays between photoplethysmographic signals of spatially separated regions. The probabilistic approach yields a parameter denoted as perfusion speed. We compare the perfusion speed versus two parameters, which assess the strength of blood pulsation (perfusion strength and signal to noise ratio). Preliminary results using video data with different physiological stimuli (cold pressure test, cold face test) show that all measures are influenced by those stimuli (some of them with statistical certainty). The perfusion speed turned out to be more sensitive than the other measures in some cases. However, our results also show that the intraindividual stability and interindividual comparability of all used measures remain critical points. This work proves the general feasibility of employing the perfusion speed as novel iPPG quantity. Future studies will address open points like the handling of ballistocardiographic effects and will try to deepen the understanding of the predominant physiological mechanisms and their relation to the algorithmic performance.

  13. Dynamic stochastic optimization

    CERN Document Server

    Ermoliev, Yuri; Pflug, Georg

    2004-01-01

    Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic­ itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec­ tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci­ sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu­ tions. Objective an...

  14. Semi-supervised tracking of extreme weather events in global spatio-temporal climate datasets

    Science.gov (United States)

    Kim, S. K.; Prabhat, M.; Williams, D. N.

    2017-12-01

    Deep neural networks have been successfully applied to solve problem to detect extreme weather events in large scale climate datasets and attend superior performance that overshadows all previous hand-crafted methods. Recent work has shown that multichannel spatiotemporal encoder-decoder CNN architecture is able to localize events in semi-supervised bounding box. Motivated by this work, we propose new learning metric based on Variational Auto-Encoders (VAE) and Long-Short-Term-Memory (LSTM) to track extreme weather events in spatio-temporal dataset. We consider spatio-temporal object tracking problems as learning probabilistic distribution of continuous latent features of auto-encoder using stochastic variational inference. For this, we assume that our datasets are i.i.d and latent features is able to be modeled by Gaussian distribution. In proposed metric, we first train VAE to generate approximate posterior given multichannel climate input with an extreme climate event at fixed time. Then, we predict bounding box, location and class of extreme climate events using convolutional layers given input concatenating three features including embedding, sampled mean and standard deviation. Lastly, we train LSTM with concatenated input to learn timely information of dataset by recurrently feeding output back to next time-step's input of VAE. Our contribution is two-fold. First, we show the first semi-supervised end-to-end architecture based on VAE to track extreme weather events which can apply to massive scaled unlabeled climate datasets. Second, the information of timely movement of events is considered for bounding box prediction using LSTM which can improve accuracy of localization. To our knowledge, this technique has not been explored neither in climate community or in Machine Learning community.

  15. Extensive spatio-temporal assessment of flood events by application of pair-copulas

    Directory of Open Access Journals (Sweden)

    M. Schulte

    2015-06-01

    Full Text Available Although the consequences of floods are strongly related to their peak discharges, a statistical classification of flood events that only depends on these peaks may not be sufficient for flood risk assessments. In many cases, the flood risk depends on a number of event characteristics. In case of an extreme flood, the whole river basin may be affected instead of a single watershed, and there will be superposition of peak discharges from adjoining catchments. These peaks differ in size and timing according to the spatial distribution of precipitation and watershed-specific processes of flood formation. Thus, the spatial characteristics of flood events should be considered as stochastic processes. Hence, there is a need for a multivariate statistical approach that represents the spatial interdependencies between floods from different watersheds and their coincidences. This paper addresses the question how these spatial interdependencies can be quantified. Each flood event is not only assessed with regard to its local conditions but also according to its spatio-temporal pattern within the river basin. In this paper we characterise the coincidence of floods by trivariate Joe-copula and pair-copulas. Their ability to link the marginal distributions of the variates while maintaining their dependence structure characterizes them as an adequate method. The results indicate that the trivariate copula model is able to represent the multivariate probabilities of the occurrence of simultaneous flood peaks well. It is suggested that the approach of this paper is very useful for the risk-based design of retention basins as it accounts for the complex spatio-temporal interactions of floods.

  16. Stochastic dynamics of new inflation

    International Nuclear Information System (INIS)

    Nakao, Ken-ichi; Nambu, Yasusada; Sasaki, Misao.

    1988-07-01

    We investigate thoroughly the dynamics of an inflation-driving scalar field in terms of an extended version of the stochastic approach proposed by Starobinsky and discuss the spacetime structure of the inflationary universe. To avoid any complications which might arise due to quantum gravity, we concentrate our discussions on the new inflationary universe scenario in which all the energy scales involved are well below the planck mass. The investigation is done both analytically and numerically. In particular, we present a full numerical analysis of the stochastic scalar field dynamics on the phase space. Then implications of the results are discussed. (author)

  17. Assessment of spatio-temporal gait parameters from trunk accelerations during human walking

    NARCIS (Netherlands)

    Zijlstra, W; Hof, AL

    2003-01-01

    This paper studies the feasibility of an analysis of spatio-temporal gait parameters based upon accelerometry. To this purpose, acceleration patterns of the trunk and their relationships with spatio-temporal gait parameters were analysed in healthy subjects. Based on model predictions of the body's

  18. A spatio-temporal analysis of suicide in El Salvador.

    Science.gov (United States)

    Carcach, Carlos

    2017-04-20

    In 2012, international statistics showed El Salvador's suicide rate as 40th in the world and the highest in Latin America. Over the last 15 years, national statistics show the suicide death rate declining as opposed to an increasing rate of homicide. Though completed suicide is an important social and health issue, little is known about its prevalence, incidence, etiology and spatio-temporal behavior. The primary objective of this study was to examine completed suicide and homicide using the stream analogy to lethal violence within a spatio-temporal framework. A Bayesian model was applied to examine the spatio-temporal evolution of the tendency of completed suicide over homicide in El Salvador. Data on numbers of suicides and homicides at the municipal level were obtained from the Instituto de Medicina Legal (IML) and population counts, from the Dirección General de Estadística y Censos (DIGESTYC), for the period of 2002 to 2012. Data on migration were derived from the 2007 Population Census, and inequality data were obtained from a study by Damianović, Valenzuela and Vera. The data reveal a stable standardized rate of total lethal violence (completed suicide plus homicide) across municipalities over time; a decline in suicide; and a standardized suicide rate decreasing with income inequality but increasing with social isolation. Municipalities clustered in terms of both total lethal violence and suicide standardized rates. Spatial effects for suicide were stronger among municipalities located in the north-east and center-south sides of the country. New clusters of municipalities with large suicide standardized rates were detected in the north-west, south-west and center-south regions, all of which are part of time-stable clusters of homicide. Prevention efforts to reduce income inequality and mitigate the negative effects of weak relational systems should focus upon municipalities forming time-persistent clusters with a large rate of death by suicide. In

  19. A spatio-temporal analysis of suicide in El Salvador

    Directory of Open Access Journals (Sweden)

    Carlos Carcach

    2017-04-01

    Full Text Available Abstract Background In 2012, international statistics showed El Salvador’s suicide rate as 40th in the world and the highest in Latin America. Over the last 15 years, national statistics show the suicide death rate declining as opposed to an increasing rate of homicide. Though completed suicide is an important social and health issue, little is known about its prevalence, incidence, etiology and spatio-temporal behavior. The primary objective of this study was to examine completed suicide and homicide using the stream analogy to lethal violence within a spatio-temporal framework. Methods A Bayesian model was applied to examine the spatio-temporal evolution of the tendency of completed suicide over homicide in El Salvador. Data on numbers of suicides and homicides at the municipal level were obtained from the Instituto de Medicina Legal (IML and population counts, from the Dirección General de Estadística y Censos (DIGESTYC, for the period of 2002 to 2012. Data on migration were derived from the 2007 Population Census, and inequality data were obtained from a study by Damianović, Valenzuela and Vera. Results The data reveal a stable standardized rate of total lethal violence (completed suicide plus homicide across municipalities over time; a decline in suicide; and a standardized suicide rate decreasing with income inequality but increasing with social isolation. Municipalities clustered in terms of both total lethal violence and suicide standardized rates. Conclusions Spatial effects for suicide were stronger among municipalities located in the north-east and center-south sides of the country. New clusters of municipalities with large suicide standardized rates were detected in the north-west, south-west and center-south regions, all of which are part of time-stable clusters of homicide. Prevention efforts to reduce income inequality and mitigate the negative effects of weak relational systems should focus upon municipalities forming time

  20. Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets

    KAUST Repository

    Zhang, Bohai

    2014-01-01

    Various continuously-indexed spatio-temporal process models have been constructed to characterize spatio-temporal dependence structures, but the computational complexity for model fitting and predictions grows in a cubic order with the size of dataset and application of such models is not feasible for large datasets. This article extends the full-scale approximation (FSA) approach by Sang and Huang (2012) to the spatio-temporal context to reduce computational complexity. A reversible jump Markov chain Monte Carlo (RJMCMC) algorithm is proposed to select knots automatically from a discrete set of spatio-temporal points. Our approach is applicable to nonseparable and nonstationary spatio-temporal covariance models. We illustrate the effectiveness of our method through simulation experiments and application to an ozone measurement dataset.

  1. Spatio-temporal heterogeneity of riparian soil morphology in a restored floodplain

    Science.gov (United States)

    Fournier, B.; Guenat, C.; Bullinger-Weber, G.; Mitchell, E. A. D.

    2013-10-01

    Floodplains have been intensively altered in industrialized countries, but are now increasingly being restored. It is therefore important to assess the effect of these restoration projects on the aquatic and terrestrial components of ecosystems. However, despite being functionally crucial components of terrestrial ecosystems, soils are generally overlooked in floodplain restoration assessments. We studied the spatio-temporal heterogeneity of soil morphology in a restored (riverbed widening) river reach along the River Thur (Switzerland) using three criteria (soil diversity, dynamism and typicality) and their associated indicators. We hypothesized that these criteria would correctly discriminate the post-restoration changes in soil morphology, and that these changes correspond to patterns of vascular plant diversity. Soil diversity and dynamism increased 5 yr after the restoration, but some typical soils of braided rivers were still missing. Soil typicality and dynamism were correlated to vegetation changes. These results suggest a limited success of the project, in agreement with evaluations carried out at the same site using other, more resource-demanding, methods (e.g., soil fauna, fish diversity, ecosystem functioning). Soil morphology provides structural and functional information on floodplain ecosystems. The spatio-temporal heterogeneity of soil morphology represents a cost-efficient ecological indicator that could easily be integrated into rapid assessment protocols of floodplain and river restoration projects. The follow-up assessment after several major floods (≥ HQ20) should take place to allow for testing the longer-term validity of our conclusion for the River Thur site. More generally, it would be useful to apply the soil morphology indicator approach in different settings to test its broader applicability.

  2. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel

    2017-10-13

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  3. A spatio-temporal extension to the map cube operator

    Science.gov (United States)

    Alzate, Juan C.; Moreno, Francisco J.; Echeverri, Jaime

    2012-09-01

    OLAP (On Line Analytical Processing) is a set of techniques and operators to facilitate the data analysis usually stored in a data warehouse. In this paper, we extend the functionality of an OLAP operator known as Map Cube with the definition and incorporation of a function that allows the formulation of spatio-temporal queries. For example, consider a data warehouse about crimes that includes data about the places where the crimes were committed. Suppose we want to find and visualize the trajectory (a trajectory is just the path that an object follows through space as a function of time) of the crimes of a suspect beginning with his oldest crime and ending with his most recent one. In order to meet this requirement, we extend the Map Cube operator.

  4. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel; Genton, Marc G.

    2017-01-01

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  5. Spatio-temporal observations of the tertiary ozone maximum

    Directory of Open Access Journals (Sweden)

    V. F. Sofieva

    2009-07-01

    Full Text Available We present spatio-temporal distributions of the tertiary ozone maximum (TOM, based on GOMOS (Global Ozone Monitoring by Occultation of Stars ozone measurements in 2002–2006. The tertiary ozone maximum is typically observed in the high-latitude winter mesosphere at an altitude of ~72 km. Although the explanation for this phenomenon has been found recently – low concentrations of odd-hydrogen cause the subsequent decrease in odd-oxygen losses – models have had significant deviations from existing observations until recently. Good coverage of polar night regions by GOMOS data has allowed for the first time to obtain spatial and temporal observational distributions of night-time ozone mixing ratio in the mesosphere.

    The distributions obtained from GOMOS data have specific features, which are variable from year to year. In particular, due to a long lifetime of ozone in polar night conditions, the downward transport of polar air by the meridional circulation is clearly observed in the tertiary ozone maximum time series. Although the maximum tertiary ozone mixing ratio is achieved close to the polar night terminator (as predicted by the theory, TOM can be observed also at very high latitudes, not only in the beginning and at the end, but also in the middle of winter. We have compared the observational spatio-temporal distributions of the tertiary ozone maximum with that obtained using WACCM (Whole Atmosphere Community Climate Model and found that the specific features are reproduced satisfactorily by the model.

    Since ozone in the mesosphere is very sensitive to HOx concentrations, energetic particle precipitation can significantly modify the shape of the ozone profiles. In particular, GOMOS observations have shown that the tertiary ozone maximum was temporarily destroyed during the January 2005 and December 2006 solar proton events as a result of the HOx enhancement from the increased ionization.

  6. Patterns of urban violent injury: a spatio-temporal analysis.

    Directory of Open Access Journals (Sweden)

    Michael Cusimano

    2010-01-01

    Full Text Available Injury related to violent acts is a problem in every society. Although some authors have examined the geography of violent crime, few have focused on the spatio-temporal patterns of violent injury and none have used an ambulance dataset to explore the spatial characteristics of injury. The purpose of this study was to describe the combined spatial and temporal characteristics of violent injury in a large urban centre.Using a geomatics framework and geographic information systems software, we studied 4,587 ambulance dispatches and 10,693 emergency room admissions for violent injury occurrences among adults (aged 18-64 in Toronto, Canada, during 2002 and 2004, using population-based datasets. We created kernel density and choropleth maps for 24-hour periods and four-hour daily time periods and compared location of ambulance dispatches and patient residences with local land use and socioeconomic characteristics. We used multivariate regressions to control for confounding factors. We found the locations of violent injury and the residence locations of those injured were both closely related to each other and clearly clustered in certain parts of the city characterised by high numbers of bars, social housing units, and homeless shelters, as well as lower household incomes. The night and early morning showed a distinctive peak in injuries and a shift in the location of injuries to a "nightlife" district. The locational pattern of patient residences remained unchanged during those times.Our results demonstrate that there is a distinctive spatio-temporal pattern in violent injury reflected in the ambulance data. People injured in this urban centre more commonly live in areas of social deprivation. During the day, locations of injury and locations of residences are similar. However, later at night, the injury location of highest density shifts to a "nightlife" district, whereas the residence locations of those most at risk of injury do not change.

  7. Spatio-temporal clustering of wildfires in Portugal

    Science.gov (United States)

    Costa, R.; Pereira, M. G.; Caramelo, L.; Vega Orozco, C.; Kanevski, M.

    2012-04-01

    Several studies have shown that wildfires in Portugal presenthigh temporal as well as high spatial variability (Pereira et al., 2005, 2011). The identification and characterization of spatio-temporal clusters contributes to a comprehensivecharacterization of the fire regime and to improve the efficiency of fire prevention and combat activities. The main goalsin this studyare: (i) to detect the spatio-temporal clusters of burned area; and, (ii) to characterize these clusters along with the role of human and environmental factors. The data were supplied by the National Forest Authority(AFN, 2011) and comprises: (a)the Portuguese Rural Fire Database, PRFD, (Pereira et al., 2011) for the 1980-2007period; and, (b) the national mapping burned areas between 1990 and 2009. In this work, in order to complement the more common cluster analysis algorithms, an alternative approach based onscan statistics and on the permutation modelwas used. This statistical methodallows the detection of local excess events and to test if such an excess can reasonably have occurred by chance.Results obtained for different simulations performed for different spatial and temporal windows are presented, compared and interpreted.The influence of several fire factors such as (climate, vegetation type, etc.) is also assessed. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005:"Synoptic patterns associated with large summer forest fires in Portugal".Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 AFN, 2011: AutoridadeFlorestalNacional (National Forest Authority). Available at http://www.afn.min-agricultura.pt/portal.

  8. High Spatio-Temporal Resolution Bathymetry Estimation and Morphology

    Science.gov (United States)

    Bergsma, E. W. J.; Conley, D. C.; Davidson, M. A.; O'Hare, T. J.

    2015-12-01

    In recent years, bathymetry estimates using video images have become increasingly accurate. With the cBathy code (Holman et al., 2013) fully operational, bathymetry results with 0.5 metres accuracy have been regularly obtained at Duck, USA. cBathy is based on observations of the dominant frequencies and wavelengths of surface wave motions and estimates the depth (and hence allows inference of bathymetry profiles) based on linear wave theory. Despite the good performance at Duck, large discrepancies were found related to tidal elevation and camera height (Bergsma et al., 2014) and on the camera boundaries. A tide dependent floating pixel and camera boundary solution have been proposed to overcome these issues (Bergsma et al., under review). The video-data collection is set estimate depths hourly on a grid with resolution in the order of 10x25 meters. Here, the application of the cBathy at Porthtowan in the South-West of England is presented. Hourly depth estimates are combined and analysed over a period of 1.5 years (2013-2014). In this work the focus is on the sub-tidal region, where the best cBathy results are achieved. The morphology of the sub-tidal bar is tracked with high spatio-temporal resolution on short and longer time scales. Furthermore, the impact of the storm and reset (sudden and large changes in bathymetry) of the sub-tidal area is clearly captured with the depth estimations. This application shows that the high spatio-temporal resolution of cBathy makes it a powerful tool for coastal research and coastal zone management.

  9. H.264/AVC digital fingerprinting based on spatio-temporal just noticeable distortion

    Science.gov (United States)

    Ait Saadi, Karima; Bouridane, Ahmed; Guessoum, Abderrezak

    2014-01-01

    This paper presents a robust adaptive embedding scheme using a modified Spatio-Temporal noticeable distortion (JND) model that is designed for tracing the distribution of the H.264/AVC video content and protecting them from unauthorized redistribution. The Embedding process is performed during coding process in selected macroblocks type Intra 4x4 within I-Frame. The method uses spread-spectrum technique in order to obtain robustness against collusion attacks and the JND model to dynamically adjust the embedding strength and control the energy of the embedded fingerprints so as to ensure their imperceptibility. Linear and non linear collusion attacks are performed to show the robustness of the proposed technique against collusion attacks while maintaining visual quality unchanged.

  10. Spatio-temporal pattern formation in predator-prey systems with fitness taxis

    DEFF Research Database (Denmark)

    Heilmann, Irene T.; Thygesen, Uffe Høgsbro; Sørensen, Mads Peter

    2018-01-01

    We pose a spatial predator–prey model in which the movement of animals is not purely diffusive, but also contains a drift term in the direction of higher specific growth rates. We refer to this as fitness taxis. We conduct a linear stability analysis of the resulting coupled reaction–advection–di......We pose a spatial predator–prey model in which the movement of animals is not purely diffusive, but also contains a drift term in the direction of higher specific growth rates. We refer to this as fitness taxis. We conduct a linear stability analysis of the resulting coupled reaction...... of diffusive motion, is ecologically plausible, and provides an alternative mechanism for formation of patterns in spatially explicit ecosystem models, with emphasis on non-stationary spatio-temporal dynamics....

  11. Spatio-temporal correlations in the Manna model in one, three and five dimensions

    Science.gov (United States)

    Willis, Gary; Pruessner, Gunnar

    2018-02-01

    Although the paradigm of criticality is centered around spatial correlations and their anomalous scaling, not many studies of self-organized criticality (SOC) focus on spatial correlations. Often, integrated observables, such as avalanche size and duration, are used, not least as to avoid complications due to the unavoidable lack of translational invariance. The present work is a survey of spatio-temporal correlation functions in the Manna Model of SOC, measured numerically in detail in d = 1,3 and 5 dimensions and compared to theoretical results, in particular relating them to “integrated” observables such as avalanche size and duration scaling, that measure them indirectly. Contrary to the notion held by some of SOC models organizing into a critical state by re-arranging their spatial structure avalanche by avalanche, which may be expected to result in large, nontrivial, system-spanning spatial correlations in the quiescent state (between avalanches), correlations of inactive particles in the quiescent state have a small amplitude that does not and cannot increase with the system size, although they display (noisy) power law scaling over a range linear in the system size. Self-organization, however, does take place as the (one-point) density of inactive particles organizes into a particular profile that is asymptotically independent of the driving location, also demonstrated analytically in one dimension. Activity and its correlations, on the other hand, display nontrivial long-ranged spatio-temporal scaling with exponents that can be related to established results, in particular avalanche size and duration exponents. The correlation length and amplitude are set by the system size (confirmed analytically for some observables), as expected in systems displaying finite size scaling. In one dimension, we find some surprising inconsistencies of the dynamical exponent. A (spatially extended) mean field theory (MFT) is recovered, with some corrections, in five

  12. A hybrid spatio-temporal data indexing method for trajectory databases.

    Science.gov (United States)

    Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

    2014-07-21

    In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

  13. A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

    Directory of Open Access Journals (Sweden)

    Shengnan Ke

    2014-07-01

    Full Text Available In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

  14. A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

    Science.gov (United States)

    Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

    2014-01-01

    In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type. PMID:25051028

  15. Building spatio-temporal database model based on ontological approach using relational database environment

    International Nuclear Information System (INIS)

    Mahmood, N.; Burney, S.M.A.

    2017-01-01

    Everything in this world is encapsulated by space and time fence. Our daily life activities are utterly linked and related with other objects in vicinity. Therefore, a strong relationship exist with our current location, time (including past, present and future) and event through with we are moving as an object also affect our activities in life. Ontology development and its integration with database are vital for the true understanding of the complex systems involving both spatial and temporal dimensions. In this paper we propose a conceptual framework for building spatio-temporal database model based on ontological approach. We have used relational data model for modelling spatio-temporal data content and present our methodology with spatio-temporal ontological accepts and its transformation into spatio-temporal database model. We illustrate the implementation of our conceptual model through a case study related to cultivated land parcel used for agriculture to exhibit the spatio-temporal behaviour of agricultural land and related entities. Moreover, it provides a generic approach for designing spatiotemporal databases based on ontology. The proposed model is capable to understand the ontological and somehow epistemological commitments and to build spatio-temporal ontology and transform it into a spatio-temporal data model. Finally, we highlight the existing and future research challenges. (author)

  16. Diffusive spatio-temporal noise in a first-passage time model for intracellular calcium release

    KAUST Repository

    Flegg, Mark B.

    2013-01-01

    The intracellular release of calcium from the endoplasmic reticulum is controlled by ion channels. The resulting calcium signals exhibit a rich spatio-temporal signature, which originates at least partly from microscopic fluctuations. While stochasticity in the gating transition of ion channels has been incorporated into many models, the distribution of calcium is usually described by deterministic reaction-diffusion equations. Here we test the validity of the latter modeling approach by using two different models to calculate the frequency of localized calcium signals (calcium puffs) from clustered IP3 receptor channels. The complexity of the full calcium system is here limited to the basic opening mechanism of the ion channels and, in the mathematical reduction simplifies to the calculation of a first passage time. Two models are then studied: (i) a hybrid model, where channel gating is treated stochastically, while calcium concentration is deterministic and (ii) a fully stochastic model with noisy channel gating and Brownian calcium ion motion. The second model utilises the recently developed two-regime method [M. B. Flegg, S. J. Chapman, and R. Erban, "The two-regime method for optimizing stochastic reaction-diffusion simulations," J. R. Soc., Interface 9, 859-868 (2012)] in order to simulate a large domain with precision required only near the Ca2+ absorbing channels. The expected time for a first channel opening that results in a calcium puff event is calculated. It is found that for a large diffusion constant, predictions of the interpuff time are significantly overestimated using the model (i) with a deterministic non-spatial calcium variable. It is thus demonstrated that the presence of diffusive noise in local concentrations of intracellular Ca2+ ions can substantially influence the occurrence of calcium signals. The presented approach and results may also be relevant for other cell-physiological first-passage time problems with small ligand concentration

  17. Dynamical and hamiltonian dilations of stochastic processes

    International Nuclear Information System (INIS)

    Baumgartner, B.; Gruemm, H.-R.

    1982-01-01

    This is a study of the problem, which stochastic processes could arise from dynamical systems by loss of information. The notions of ''dilation'' and ''approximate dilation'' of a stochastic process are introduced to give exact definitions of this particular relationship. It is shown that every generalized stochastic process is approximately dilatable by a sequence of dynamical systems, but for stochastic processes in full generality one needs nets. (Author)

  18. Initial spatio-temporal domain expansion of the Modelfest database

    Science.gov (United States)

    Carney, Thom; Mozaffari, Sahar; Sun, Sean; Johnson, Ryan; Shirvastava, Sharona; Shen, Priscilla; Ly, Emma

    2013-03-01

    The first Modelfest group publication appeared in the SPIE Human Vision and Electronic Imaging conference proceedings in 1999. "One of the group's goals is to develop a public database of test images with threshold data from multiple laboratories for designing and testing HVS (Human Vision Models)." After extended discussions the group selected a set of 45 static images thought to best meet that goal and collected psychophysical detection data which is available on the WEB and presented in the 2000 SPIE conference proceedings. Several groups have used these datasets to test spatial modeling ideas. Further discussions led to the preliminary stimulus specification for extending the database into the temporal domain which was published in the 2002 conference proceeding. After a hiatus of 12 years, some of us have collected spatio-temporal thresholds on an expanded stimulus set of 41 video clips; the original specification included 35 clips. The principal change involved adding one additional spatial pattern beyond the three originally specified. The stimuli consisted of 4 spatial patterns, Gaussian Blob, 4 c/d Gabor patch, 11.3 c/d Gabor patch and a 2D white noise patch. Across conditions the patterns were temporally modulated over a range of approximately 0-25 Hz as well as temporal edge and pulse modulation conditions. The display and data collection specifications were as specified by the Modelfest groups in the 2002 conference proceedings. To date seven subjects have participated in this phase of the data collection effort, one of which also participated in the first phase of Modelfest. Three of the spatio-temporal stimuli were identical to conditions in the original static dataset. Small differences in the thresholds were evident and may point to a stimulus limitation. The temporal CSF peaked between 4 and 8 Hz for the 0 c/d (Gaussian blob) and 4 c/d patterns. The 4 c/d and 11.3 c/d Gabor temporal CSF was low pass while the 0 c/d pattern was band pass. This

  19. Nutrients and toxin producing phytoplankton control algal blooms - a spatio-temporal study in a noisy environment.

    Science.gov (United States)

    Sarkar, Ram Rup; Malchow, Horst

    2005-12-01

    A phytoplankton-zooplankton prey-predator model has been investigated for temporal, spatial and spatio-temporal dissipative pattern formation in a deterministic and noisy environment, respectively. The overall carrying capacity for the phytoplankton population depends on the nutrient level. The role of nutrient concentrations and toxin producing phytoplankton for controlling the algal blooms has been discussed. The local analysis yields a number of stationary and/or oscillatory regimes and their combinations. Correspondingly interesting is the spatio-temporal behaviour, modelled by stochastic reaction-diffusion equations. The present study also reveals the fact that the rate of toxin production by toxin producing phytoplankton (TPP) plays an important role for controlling oscillations in the plankton system. We also observe that different mortality functions of zooplankton due to TPP have significant influence in controlling oscillations, coexistence, survival or extinction of the zoo-plankton population. External noise can enhance the survival and spread of zooplankton that would go extinct in the deterministic system due to a high rate of toxin production.

  20. The dynamics of stochastic processes

    DEFF Research Database (Denmark)

    Basse-O'Connor, Andreas

    In the present thesis the dynamics of stochastic processes is studied with a special attention to the semimartingale property. This is mainly motivated by the fact that semimartingales provide the class of the processes for which it is possible to define a reasonable stochastic calculus due...... to the Bichteler-Dellacherie Theorem. The semimartingale property of Gaussian processes is characterized in terms of their covariance function, spectral measure and spectral representation. In addition, representation and expansion of filtration results are provided as well. Special attention is given to moving...... average processes, and when the driving process is a Lévy or a chaos process the semimartingale property is characterized in the filtration spanned by the driving process and in the natural filtration when the latter is a Brownian motion. To obtain some of the above results an integrability of seminorm...

  1. Stochastic dynamics of dengue epidemics.

    Science.gov (United States)

    de Souza, David R; Tomé, Tânia; Pinho, Suani T R; Barreto, Florisneide R; de Oliveira, Mário J

    2013-01-01

    We use a stochastic Markovian dynamics approach to describe the spreading of vector-transmitted diseases, such as dengue, and the threshold of the disease. The coexistence space is composed of two structures representing the human and mosquito populations. The human population follows a susceptible-infected-recovered (SIR) type dynamics and the mosquito population follows a susceptible-infected-susceptible (SIS) type dynamics. The human infection is caused by infected mosquitoes and vice versa, so that the SIS and SIR dynamics are interconnected. We develop a truncation scheme to solve the evolution equations from which we get the threshold of the disease and the reproductive ratio. The threshold of the disease is also obtained by performing numerical simulations. We found that for certain values of the infection rates the spreading of the disease is impossible, for any death rate of infected mosquitoes.

  2. Spatio-temporal variability in western Baltic cod early life stage survival mediated by egg buoyancy, hydrography and hydrodynamics

    DEFF Research Database (Denmark)

    Hinrichsen, H-H.; Hüssy, K.; Huwer, B.

    2012-01-01

    Spatio-temporal variability in western Baltic cod early life stage survival mediated by egg buoyancy, hydrography and hydrodynamics. – ICES Journal of Marine Science, 69: 1744–1752.To disentangle the effects of different drivers on recruitment variability of marine fish, a spatially and temporally...... explicit understanding of both the spawning stock size and the early life stage dynamics is required. The objectives of this study are to assess the transport of western Baltic cod early life stages as well as the variability in environmentally-mediated survival along drift routes in relation to both...

  3. Self-organization of spatio-temporal earthquake clusters

    Directory of Open Access Journals (Sweden)

    S. Hainzl

    2000-01-01

    Full Text Available Cellular automaton versions of the Burridge-Knopoff model have been shown to reproduce the power law distribution of event sizes; that is, the Gutenberg-Richter law. However, they have failed to reproduce the occurrence of foreshock and aftershock sequences correlated with large earthquakes. We show that in the case of partial stress recovery due to transient creep occurring subsequently to earthquakes in the crust, such spring-block systems self-organize into a statistically stationary state characterized by a power law distribution of fracture sizes as well as by foreshocks and aftershocks accompanying large events. In particular, the increase of foreshock and the decrease of aftershock activity can be described by, aside from a prefactor, the same Omori law. The exponent of the Omori law depends on the relaxation time and on the spatial scale of transient creep. Further investigations concerning the number of aftershocks, the temporal variation of aftershock magnitudes, and the waiting time distribution support the conclusion that this model, even "more realistic" physics in missed, captures in some ways the origin of the size distribution as well as spatio-temporal clustering of earthquakes.

  4. Exploring the spatio-temporal neural basis of face learning

    Science.gov (United States)

    Yang, Ying; Xu, Yang; Jew, Carol A.; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

    2017-01-01

    Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150–250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150–250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces. PMID:28570739

  5. Spatio-temporal effects of low impact development practices

    Science.gov (United States)

    Gilroy, Kristin L.; McCuen, Richard H.

    2009-04-01

    SummaryThe increase in land development and urbanization experienced in the US and worldwide is causing environmental degradation. Traditional off-site stormwater management does not protect small streams. To mitigate the negative effects of land development, best management practices (BMPs) are being implemented into stormwater management policies for the purposes of controlling minor flooding and improving water quality. Unfortunately, the effectiveness of BMPs has not been extensively studied. The purpose of this research was to analyze the effects of both location and quantity of two types of BMPs: cisterns and bioretention pits. A spatio-temporal model of a microwatershed was developed to determine the effects of BMPs on single-family, townhome, and commercial lots. The effects of development and the BMPs on peak runoff rates and volumes were compared to pre-development conditions. The results show that cisterns alone are capable of controlling rooftop runoff for small storms. Both the spatial location and the volume of BMP storage on a microwatershed influences the effectiveness of BMPs. The volume of BMP storage is positively correlated to the percent reduction in the peak discharge rate and total runoff volume; however, location is a factor in the peak reduction and a maximum volume of effective storage for both hydrologic metrics does exist. These results provide guidelines for developing stormwater management policies that can potentially reduce pollution of first-order streams, lower the cost and maintenance requirements, enhance aesthetics, and increase safety.

  6. Spatio-Temporal Analysis to Predict Environmental Influence on Malaria

    Science.gov (United States)

    Baig, S.; Sarfraz, M. S.

    2018-05-01

    Malaria is a vector borne disease which is a major cause of morbidity and mortality. It is one of the major diseases in the category of infectious diseases. The survival and bionomics of malaria is affected by environmental factors such as climatic, demographic and land-use/land-cover etc. Currently, a very few under developing countries are using Geo-informatics approaches to control this disease. Gujrat a district of Pakistan, is still under threat of malaria disease. Current research is carried on malaria incidents obtained from District Executive Officer of Health Gujrat. The objective of this study was to explore the spatio-temporal patterns of malaria in district Gujrat and to identify the areas being affected by Malaria. Furthermore, it has been also analyzed the relationship between malaria incident and environmental factors in highly favorable zones. Data is analyzed based on spatial and temporal patterns using (Moran's I). Moreover cluster and hot spots analysis were performed on the incident data. This study shows positive correlation with rainfall, vegetation index, population density and water bodies; while it shows positive and negative correlation with temperature in different seasons. However, variation between amount of vegetation and water bodies were observed. Finding of this research can help the decision makers to take preventive measures and reduce the morbidity and mortality related with malaria in Gujrat, Pakistan.

  7. Vehicle Trajectory Estimation Using Spatio-Temporal MCMC

    Directory of Open Access Journals (Sweden)

    Francois Bardet

    2010-01-01

    Full Text Available This paper presents an algorithm for modeling and tracking vehicles in video sequences within one integrated framework. Most of the solutions are based on sequential methods that make inference according to current information. In contrast, we propose a deferred logical inference method that makes a decision according to a sequence of observations, thus processing a spatio-temporal search on the whole trajectory. One of the drawbacks of deferred logical inference methods is that the solution space of hypotheses grows exponentially related to the depth of observation. Our approach takes into account both the kinematic model of the vehicle and a driver behavior model in order to reduce the space of the solutions. The resulting proposed state model explains the trajectory with only 11 parameters. The solution space is then sampled with a Markov Chain Monte Carlo (MCMC that uses a model-driven proposal distribution in order to control random walk behavior. We demonstrate our method on real video sequences from which we have ground truth provided by a RTK GPS (Real-Time Kinematic GPS. Experimental results show that the proposed algorithm outperforms a sequential inference solution (particle filter.

  8. Transfer of spatio-temporal multifractal properties of rainfall to simulated surface runoff

    Science.gov (United States)

    Gires, Auguste; Giangola-Murzyn, Agathe; Richard, Julien; Abbes, Jean-Baptiste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Willinger, Bernard; Cardinal, Hervé; Thouvenot, Thomas

    2014-05-01

    In this paper we suggest to use scaling laws and more specifically Universal Multifractals (UM) to analyse in a spatio-temporal framework both the radar rainfall and the simulated surface runoff. Such tools have been extensively used to analyse and simulate geophysical fields extremely variable over wide range of spatio-temporal scales such as rainfall, but have not often if ever been applied to surface runoff. Such novel combined analysis helps to improve the understanding of the rainfall-runoff relationship. Two catchments of the chair "Hydrology for resilient cities" sponsored by Véolia, and of the European Interreg IV RainGain project are used. They are both located in the Paris area: a 144 ha flat urban area in the Seine-Saint-Denis County, and a 250 ha urban area with a significant portion of forest located on a steep hillside of the Bièvre River. A fully distributed urban hydrological model currently under development called Multi-Hydro is implemented to represent the catchments response. It consists in an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. The fully distributed model is tested with pixels of size 5, 10 and 20 m. In a first step the model is validated for three rainfall events that occurred in 2010 and 2011, for which the Météo-France radar mosaic with a resolution of 1 km in space and 5 min in time is available. These events generated significant surface runoff and some local flooding. The sensitivity of the model to the rainfall resolution is briefly checked by stochastically generating an ensemble of realistic downscaled rainfall fields (obtained by continuing the underlying cascade process which is observed on the available range of scales) and inputting them into the model. The impact is significant on both the simulated sewer flow and surface runoff. Then rainfall fields are generated with the help of discrete multifractal cascades and inputted in the

  9. Spatio-temporal distribution of soil-transmitted helminth infections in Brazil.

    Science.gov (United States)

    Chammartin, Frédérique; Guimarães, Luiz H; Scholte, Ronaldo Gc; Bavia, Mara E; Utzinger, Jürg; Vounatsou, Penelope

    2014-09-18

    In Brazil, preventive chemotherapy targeting soil-transmitted helminthiasis is being scaled-up. Hence, spatially explicit estimates of infection risks providing information about the current situation are needed to guide interventions. Available high-resolution national model-based estimates either rely on analyses of data restricted to a given period of time, or on historical data collected over a longer period. While efforts have been made to take into account the spatial structure of the data in the modelling approach, little emphasis has been placed on the temporal dimension. We extracted georeferenced survey data on the prevalence of infection with soil-transmitted helminths (i.e. Ascaris lumbricoides, hookworm and Trichuris trichiura) in Brazil from the Global Neglected Tropical Diseases (GNTD) database. Selection of the most important predictors of infection risk was carried out using a Bayesian geostatistical approach and temporal models that address non-linearity and correlation of the explanatory variables. The spatial process was estimated through a predictive process approximation. Spatio-temporal models were built on the selected predictors with integrated nested Laplace approximation using stochastic partial differential equations. Our models revealed that, over the past 20 years, the risk of soil-transmitted helminth infection has decreased in Brazil, mainly because of the reduction of A. lumbricoides and hookworm infections. From 2010 onwards, we estimate that the infection prevalences with A. lumbricoides, hookworm and T. trichiura are 3.6%, 1.7% and 1.4%, respectively. We also provide a map highlighting municipalities in need of preventive chemotherapy, based on a predicted soil-transmitted helminth infection risk in excess of 20%. The need for treatments in the school-aged population at the municipality level was estimated at 1.8 million doses of anthelminthic tablets per year. The analysis of the spatio-temporal aspect of the risk of infection

  10. How about a Bayesian M/EEG imaging method correcting for incomplete spatio-temporal priors

    DEFF Research Database (Denmark)

    Stahlhut, Carsten; Attias, Hagai T.; Sekihara, Kensuke

    2013-01-01

    previous spatio-temporal inverse M/EEG models, the proposed model benefits of consisting of two source terms, namely, a spatio-temporal pattern term limiting the source configuration to a spatio-temporal subspace and a source correcting term to pick up source activity not covered by the spatio......-temporal prior belief. We have tested the model on both artificial data and real EEG data in order to demonstrate the efficacy of the model. The model was tested at different SNRs (-10.0,-5.2, -3.0, -1.0, 0, 0.8, 3.0 dB) using white noise. At all SNRs the sAquavit performs best in AUC measure, e.g. at SNR=0d...

  11. Diffusive spatio-temporal noise in a first-passage time model for intracellular calcium release

    KAUST Repository

    Flegg, Mark B.; Rüdiger, Sten; Erban, Radek

    2013-01-01

    The intracellular release of calcium from the endoplasmic reticulum is controlled by ion channels. The resulting calcium signals exhibit a rich spatio-temporal signature, which originates at least partly from microscopic fluctuations. While

  12. Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

    KAUST Repository

    Sun, Ying; Genton, Marc G.

    2011-01-01

    This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio

  13. Plant diversity increases spatio?temporal niche complementarity in plant?pollinator interactions

    OpenAIRE

    Venjakob, Christine; Klein, Alexandra?Maria; Ebeling, Anne; Tscharntke, Teja; Scherber, Christoph

    2016-01-01

    Ongoing biodiversity decline impairs ecosystem processes, including pollination. Flower visitation, an important indicator of pollination services, is influenced by plant species richness. However, the spatio-temporal responses of different pollinator groups to plant species richness have not yet been analyzed experimentally. Here, we used an experimental plant species richness gradient to analyze plant-pollinator interactions with an unprecedented spatio-temporal resolution. We observed four...

  14. SPAN: spike pattern association neuron for learning spatio-temporal sequences

    OpenAIRE

    Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

    2012-01-01

    Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN — a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the prec...

  15. Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

    OpenAIRE

    Le Wang; Xuhuan Duan; Qilin Zhang; Zhenxing Niu; Gang Hua; Nanning Zheng

    2018-01-01

    Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action localization detector Segment-tube, which consists of sequences of per-frame segmentation masks. The proposed Segment-tube detector can temporally pinpoint the starting/ending frame of each action category in the presence of preceding/subsequent interference actions in untrimmed videos. Simultaneously, the Segment-tube detector produces per-fr...

  16. Spatio-temporal Model of Endogenous ROS and Raft-Dependent WNT/Beta-Catenin Signaling Driving Cell Fate Commitment in Human Neural Progenitor Cells

    Science.gov (United States)

    Haack, Fiete; Lemcke, Heiko; Ewald, Roland; Rharass, Tareck; Uhrmacher, Adelinde M.

    2015-01-01

    Canonical WNT/β-catenin signaling is a central pathway in embryonic development, but it is also connected to a number of cancers and developmental disorders. Here we apply a combined in-vitro and in-silico approach to investigate the spatio-temporal regulation of WNT/β-catenin signaling during the early neural differentiation process of human neural progenitors cells (hNPCs), which form a new prospect for replacement therapies in the context of neurodegenerative diseases. Experimental measurements indicate a second signal mechanism, in addition to canonical WNT signaling, being involved in the regulation of nuclear β-catenin levels during the cell fate commitment phase of neural differentiation. We find that the biphasic activation of β-catenin signaling observed experimentally can only be explained through a model that combines Reactive Oxygen Species (ROS) and raft dependent WNT/β-catenin signaling. Accordingly after initiation of differentiation endogenous ROS activates DVL in a redox-dependent manner leading to a transient activation of down-stream β-catenin signaling, followed by continuous auto/paracrine WNT signaling, which crucially depends on lipid rafts. Our simulation studies further illustrate the elaborate spatio-temporal regulation of DVL, which, depending on its concentration and localization, may either act as direct inducer of the transient ROS/β-catenin signal or as amplifier during continuous auto-/parcrine WNT/β-catenin signaling. In addition we provide the first stochastic computational model of WNT/β-catenin signaling that combines membrane-related and intracellular processes, including lipid rafts/receptor dynamics as well as WNT- and ROS-dependent β-catenin activation. The model’s predictive ability is demonstrated under a wide range of varying conditions for in-vitro and in-silico reference data sets. Our in-silico approach is realized in a multi-level rule-based language, that facilitates the extension and modification of the

  17. Pollination Biology and Spatio-Temporal Structuring of Some Major Acacia Species (Leguminosae) of the Arabian Peninsula

    International Nuclear Information System (INIS)

    Adgaba, N.; Alghamidi, A.; Tadesse, Y.; Getachew, A.; Ansari, M. J.

    2016-01-01

    Acacias are the dominant woody plant species distributed over the vast tracts of land throughout the Arabian Peninsula. However, information on spatio-temporal structuring and pollination biology of the species is not precisely available. To determine whether any variations exist among the Acacia species in their temporal distribution, their flowering period was determined through monitoring the commencing, peaking and ending of flowering of each species. Moreover, if any variations exist in release of floral rewards among the different co-existing and co-flowering species as mechanisms of partitioning of pollinators, to minimize competition for pollination, the progress of their anthesis over time was recorded by scoring polyads to anthers ratio at different hours of a day. In addition, the amount and dynamics of nectar sugar per inflorescence (N =225/species) was determined following flower nectar sugar washing technique. Types and frequencies of flower visitors and their preferences were determined by recording the visitors 6 times a day. The current study revealed that the Acacia species of the Arabian Peninsula are spatio-temporally structured: some species co-exist yet have different flowering seasons, whereas others co-exist, flowering concurrently yet exhibit a shift in their time of peak flowering and in the time at which the peak pollen is released during the day. This study demonstrates that all Acacia species examined secrete a considerable amount of nectar (2.24+-1.72 -10.02+-4.0mg/inflorescence) which serves as a floral reward for pollinators. Insects of the Order Hymenoptera are the most prevalent visitors to Acacia species in the region. The variations in spatio-temporal structuring of the Acaciaspecies could be due to their adaptation of reducing competition for pollinators and minimizing hetero-specific pollen transfer. (author)

  18. Spatio-temporal evolution of the L → H and H → L transitions

    International Nuclear Information System (INIS)

    Miki, K.; Diamond, P.H.; Kosuga, Y.; Zhao, K.J.; Fedorczak, N.; Malkov, M.; Lee, C.; Tynan, G.; Gürcan, Ö.D.; Xu, G.S.; Estrada, T.; McDonald, D.; Schmitz, L.

    2013-01-01

    Understanding the L → H and H → L transitions is crucial to successful ITER operation. In this paper we present novel theoretical and modelling study results on the spatio-temporal dynamics of the transition. We place a special emphasis on the role of zonal flows and the micro → macro connection between dynamics and the power threshold (P T ) dependences. The model studied evolves five coupled fields in time and one space dimension, in simplified geometry. The content of this paper is (a) the model fundamentals and the space–time evolution during the L → I → H transition, (b) the physics origin of the well-known ∇B-drift asymmetry in P T , (c) the role of heat avalanches in the intrinsic variability of the L → H transition, (d) the dynamics of the H → L back transition and the physics of hysteresis, (e) conclusion and discussion, with a special emphasis on the implications of transition dynamics for the L → H power threshold scalings. (paper)

  19. Real-Time Earthquake Monitoring with Spatio-Temporal Fields

    Science.gov (United States)

    Whittier, J. C.; Nittel, S.; Subasinghe, I.

    2017-10-01

    With live streaming sensors and sensor networks, increasingly large numbers of individual sensors are deployed in physical space. Sensor data streams are a fundamentally novel mechanism to deliver observations to information systems. They enable us to represent spatio-temporal continuous phenomena such as radiation accidents, toxic plumes, or earthquakes almost as instantaneously as they happen in the real world. Sensor data streams discretely sample an earthquake, while the earthquake is continuous over space and time. Programmers attempting to integrate many streams to analyze earthquake activity and scope need to write code to integrate potentially very large sets of asynchronously sampled, concurrent streams in tedious application code. In previous work, we proposed the field stream data model (Liang et al., 2016) for data stream engines. Abstracting the stream of an individual sensor as a temporal field, the field represents the Earth's movement at the sensor position as continuous. This simplifies analysis across many sensors significantly. In this paper, we undertake a feasibility study of using the field stream model and the open source Data Stream Engine (DSE) Apache Spark(Apache Spark, 2017) to implement a real-time earthquake event detection with a subset of the 250 GPS sensor data streams of the Southern California Integrated GPS Network (SCIGN). The field-based real-time stream queries compute maximum displacement values over the latest query window of each stream, and related spatially neighboring streams to identify earthquake events and their extent. Further, we correlated the detected events with an USGS earthquake event feed. The query results are visualized in real-time.

  20. Predicting BCI subject performance using probabilistic spatio-temporal filters.

    Directory of Open Access Journals (Sweden)

    Heung-Il Suk

    Full Text Available Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI has become increasingly popular. In this work, we discuss a novel, fully Bayesian-and thereby probabilistic-framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythms-a phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects' performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject 'prototypes' (like μ - or β -rhythm type subjects or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session.

  1. Spatio-temporal dynamics of pneumonia in bighorn sheep.

    Science.gov (United States)

    Cassirer, E Frances; Plowright, Raina K; Manlove, Kezia R; Cross, Paul C; Dobson, Andrew P; Potter, Kathleen A; Hudson, Peter J

    2013-05-01

    1. Bighorn sheep mortality related to pneumonia is a primary factor limiting population recovery across western North America, but management has been constrained by an incomplete understanding of the disease. We analysed patterns of pneumonia-caused mortality over 14 years in 16 interconnected bighorn sheep populations to gain insights into underlying disease processes. 2. We observed four age-structured classes of annual pneumonia mortality patterns: all-age, lamb-only, secondary all-age and adult-only. Although there was considerable variability within classes, overall they differed in persistence within and impact on populations. Years with pneumonia-induced mortality occurring simultaneously across age classes (i.e. all-age) appeared to be a consequence of pathogen invasion into a naïve population and resulted in immediate population declines. Subsequently, low recruitment due to frequent high mortality outbreaks in lambs, probably due to association with chronically infected ewes, posed a significant obstacle to population recovery. Secondary all-age events occurred in previously exposed populations when outbreaks in lambs were followed by lower rates of pneumonia-induced mortality in adults. Infrequent pneumonia events restricted to adults were usually of short duration with low mortality. 3. Acute pneumonia-induced mortality in adults was concentrated in fall and early winter around the breeding season when rams are more mobile and the sexes commingle. In contrast, mortality restricted to lambs peaked in summer when ewes and lambs were concentrated in nursery groups. 4. We detected weak synchrony in adult pneumonia between adjacent populations, but found no evidence for landscape-scale extrinsic variables as drivers of disease. 5. We demonstrate that there was a >60% probability of a disease event each year following pneumonia invasion into bighorn sheep populations. Healthy years also occurred periodically, and understanding the factors driving these apparent fade-out events may be the key to managing this disease. Our data and modelling indicate that pneumonia can have greater impacts on bighorn sheep populations than previously reported, and we present hypotheses about processes involved for testing in future investigations and management. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

  2. EEG Based Inference of Spatio-Temporal Brain Dynamics

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese

    Electroencephalography (EEG) provides a measure of brain activity and has improved our understanding of the brain immensely. However, there is still much to be learned and the full potential of EEG is yet to be realized. In this thesis we suggest to improve the information gain of EEG using three...... different approaches; 1) by recovery of the EEG sources, 2) by representing and inferring the propagation path of EEG sources, and 3) by combining EEG with functional magnetic resonance imaging (fMRI). The common goal of the methods, and thus of this thesis, is to improve the spatial dimension of EEG...... recovery ability. The forward problem describes the propagation of neuronal activity in the brain to the EEG electrodes on the scalp. The geometry and conductivity of the head layers are normally required to model this path. We propose a framework for inferring forward models which is based on the EEG...

  3. Spatio-temporal analysis of landuse dynamics in Upper Opa ...

    African Journals Online (AJOL)

    To accomplish this, Landsat TM 1986, ETM 2002 and OLI 2014 were acquired from the USGS Earth Explorer in Global Land Cover Facility (GLCF) web site and subjected to supervised classification using the Anderson classification Scheme. Six land use/landcover classes were identified: Built-up, Bareland, Riparian, ...

  4. Spatio-temporal dynamics of an active, polar, viscoelastic ring.

    Science.gov (United States)

    Marcq, Philippe

    2014-04-01

    Constitutive equations for a one-dimensional, active, polar, viscoelastic liquid are derived by treating the strain field as a slow hydrodynamic variable. Taking into account the couplings between strain and polarity allowed by symmetry, the hydrodynamics of an active, polar, viscoelastic body include an evolution equation for the polarity field that generalizes the damped Kuramoto-Sivashinsky equation. Beyond thresholds of the active coupling coefficients between the polarity and the stress or the strain rate, bifurcations of the homogeneous state lead first to stationary waves, then to propagating waves of the strain, stress and polarity fields. I argue that these results are relevant to living matter, and may explain rotating actomyosin rings in cells and mechanical waves in epithelial cell monolayers.

  5. STABILITY AND DYNAMICS OF SPATIO-TEMPORAL STRUCTURES

    Energy Technology Data Exchange (ETDEWEB)

    Hermann Riecke

    2005-10-21

    This document constitutes the final report for the grant. It provides a complete list of publications and presentations that arose from the project as well as a brief description of the highlights of the research results. The research funded by this grant has provided insights into the spontaneous formation of structures of increasing complexity in systems driven far from thermodynamic equilibrium. A classic example of such a system is thermally driven convection in a horizontal fluid layer. Highlights of the research are: (1) explanation of the localized traveling wave pulses observed in binary-mixture convection, (2) explanation of the localized waves in electroconvection, (3) introduction of a new diagnostics for spatially and temporally chaotic states, which is based on the statistics of defect trajectories, (4) prediction of complex states in thermally driven convection in rotating systems. Additional contributions provided insight into the localization mechanism for oscillons, the prediction of a new localization mechanism for traveling waves based on a resonant periodic forcing, and an analysis of the stability of quasi-periodic patterns.

  6. Spatio-temporal dynamics of pneumonia in bighorn sheep

    Science.gov (United States)

    Cassirer, E. Frances; Plowright, Raina K.; Manlove, Kezia R.; Cross, Paul C.; Dobson, Andrew P.; Potter, Kathleen A.; Hudson, Peter J.

    2013-01-01

    Bighorn sheep mortality related to pneumonia is a primary factor limiting population recovery across western North America, but management has been constrained by an incomplete understanding of the disease. We analysed patterns of pneumonia-caused mortality over 14 years in 16 interconnected bighorn sheep populations to gain insights into underlying disease processes. 2. We observed four age-structured classes of annual pneumonia mortality patterns: all-age, lamb-only, secondary all-age and adult-only. Although there was considerable variability within classes, overall they differed in persistence within and impact on populations. Years with pneumonia-induced mortality occurring simultaneously across age classes (i.e. all-age) appeared to be a consequence of pathogen invasion into a naïve population and resulted in immediate population declines. Subsequently, low recruitment due to frequent high mortality outbreaks in lambs, probably due to association with chronically infected ewes, posed a significant obstacle to population recovery. Secondary all-age events occurred in previously exposed populations when outbreaks in lambs were followed by lower rates of pneumonia-induced mortality in adults. Infrequent pneumonia events restricted to adults were usually of short duration with low mortality. 3. Acute pneumonia-induced mortality in adults was concentrated in fall and early winter around the breeding season when rams are more mobile and the sexes commingle. In contrast, mortality restricted to lambs peaked in summer when ewes and lambs were concentrated in nursery groups. 4. We detected weak synchrony in adult pneumonia between adjacent populations, but found no evidence for landscape-scale extrinsic variables as drivers of disease. 5. We demonstrate that there was a >60% probability of a disease event each year following pneumonia invasion into bighorn sheep populations. Healthy years also occurred periodically, and understanding the factors driving these apparent fade-out events may be the key to managing this disease. Our data and modelling indicate that pneumonia can have greater impacts on bighorn sheep populations than previously reported, and we present hypotheses about processes involved for testing in future investigations and management.

  7. Spatio-temporal analysis of brain electrical activity in epilepsy based on cellular nonlinear networks

    Science.gov (United States)

    Gollas, Frank; Tetzlaff, Ronald

    2009-05-01

    Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio-temporal

  8. Research on nonlinear stochastic dynamical price model

    International Nuclear Information System (INIS)

    Li Jiaorui; Xu Wei; Xie Wenxian; Ren Zhengzheng

    2008-01-01

    In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies

  9. Geometric integrators for stochastic rigid body dynamics

    KAUST Repository

    Tretyakov, Mikhail

    2016-01-05

    Geometric integrators play an important role in simulating dynamical systems on long time intervals with high accuracy. We will illustrate geometric integration ideas within the stochastic context, mostly on examples of stochastic thermostats for rigid body dynamics. The talk will be mainly based on joint recent work with Rusland Davidchak and Tom Ouldridge.

  10. Geometric integrators for stochastic rigid body dynamics

    KAUST Repository

    Tretyakov, Mikhail

    2016-01-01

    Geometric integrators play an important role in simulating dynamical systems on long time intervals with high accuracy. We will illustrate geometric integration ideas within the stochastic context, mostly on examples of stochastic thermostats for rigid body dynamics. The talk will be mainly based on joint recent work with Rusland Davidchak and Tom Ouldridge.

  11. Dying like rabbits: general determinants of spatio-temporal variability in survival.

    Science.gov (United States)

    Tablado, Zulima; Revilla, Eloy; Palomares, Francisco

    2012-01-01

    1. Identifying general patterns of how and why survival rates vary across space and time is necessary to truly understand population dynamics of a species. However, this is not an easy task given the complexity and interactions of processes involved, and the interpopulation differences in main survival determinants. 2. Here, using European rabbits (Oryctolagus cuniculus) as a model and information from local studies, we investigated whether we could make inferences about trends and drivers of survival of a species that are generalizable to large spatio-temporal scales. To do this, we first focused on overall survival and then examined cause-specific mortalities, mainly predation and diseases, which may lead to those patterns. 3. Our results show that within the large-scale variability in rabbit survival, there exist general patterns that are explained by the integration of factors previously known to be important at the local level (i.e. age, climate, diseases, predation or density dependence). We found that both inter- and intrastudy survival rates increased in magnitude and decreased in variability as rabbits grow old, although this tendency was less pronounced in populations with epidemic diseases. Some causes leading to these higher mortalities in young rabbits could be the stronger effect of rainfall at those ages, as well as, other death sources like malnutrition or infanticide. 4. Predation is also greater for newborns and juveniles, especially in population without diseases. Apart from the effect of diseases, predation patterns also depended on factors, such as, density, season, and type and density of predators. Finally, we observed that infectious diseases also showed general relationships with climate, breeding (i.e. new susceptible rabbits) and age, although the association type varied between myxomatosis and rabbit haemorrhagic disease. 5. In conclusion, large-scale patterns of spatio-temporal variability in rabbit survival emerge from the combination

  12. Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

    Science.gov (United States)

    Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

    2016-04-01

    Diamantaras, K.: 'Programming and architecture of parallel processing systems', 1st Edition, Eds. Kleidarithmos, 2011 [4] NVIDIA.: 'NVidia CUDA C Programming Guide', version 5.0, NVidia (reference book) [5] Konstantaras, A.: 'Classification of Distinct Seismic Regions and Regional Temporal Modelling of Seismicity in the Vicinity of the Hellenic Seismic Arc', IEEE Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6 (4), pp. 1857-1863, 2013 [6] Konstantaras, A. Varley, M.R.,. Valianatos, F., Collins, G. and Holifield, P.: 'Recognition of electric earthquake precursors using neuro-fuzzy models: methodology and simulation results', Proc. IASTED International Conference on Signal Processing Pattern Recognition and Applications (SPPRA 2002), Crete, Greece, 2002, pp 303-308, 2002 [7] Konstantaras, A., Katsifarakis, E., Maravelakis, E., Skounakis, E., Kokkinos, E. and Karapidakis, E.: 'Intelligent Spatial-Clustering of Seismicity in the Vicinity of the Hellenic Seismic Arc', Earth Science Research, vol. 1 (2), pp. 1-10, 2012 [8] Georgoulas, G., Konstantaras, A., Katsifarakis, E., Stylios, C.D., Maravelakis, E. and Vachtsevanos, G.: '"Seismic-Mass" Density-based Algorithm for Spatio-Temporal Clustering', Expert Systems with Applications, vol. 40 (10), pp. 4183-4189, 2013 [9] Konstantaras, A. J.: 'Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters', Earth Science Informatics, 2015 (In Press, see: www.scopus.com) [10] Drakatos, G. and Latoussakis, J.: 'A catalog of aftershock sequences in Greece (1971-1997): Their spatial and temporal characteristics', Journal of Seismology, vol. 5, pp. 137-145, 2001

  13. A Kinect based sign language recognition system using spatio-temporal features

    Science.gov (United States)

    Memiş, Abbas; Albayrak, Songül

    2013-12-01

    This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

  14. On the angle between the first and second Lyapunov vectors in spatio-temporal chaos

    International Nuclear Information System (INIS)

    Pazó, D; López, J M; Rodríguez, M A

    2013-01-01

    In a dynamical system the first Lyapunov vector (LV) is associated with the largest Lyapunov exponent and indicates—at any point on the attractor—the direction of maximal growth in tangent space. The LV corresponding to the second largest Lyapunov exponent generally points in a different direction, but tangencies between both vectors can in principle occur. Here we find that the probability density function (PDF) of the angle ψ spanned by the first and second LVs should be expected to be approximately symmetric around π/4 and to peak at 0 and π/2. Moreover, for small angles we uncover a scaling law for the PDF Q of ψ l = ln ψ with the system size L: Q(ψ l ) = L −1/2 f(ψ l L −1/2 ). We give a theoretical argument that justifies this scaling form and also explains why it should be universal (irrespective of the system details) for spatio-temporal chaos in one spatial dimension. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Lyapunov analysis: from dynamical systems theory to applications’. (paper)

  15. A Cubesat enabled Spatio-Temporal Enhancement Method (CESTEM) utilizing Planet, Landsat and MODIS data

    KAUST Repository

    Houborg, Rasmus

    2018-03-19

    Satellite sensing in the visible to near-infrared (VNIR) domain has been the backbone of land surface monitoring and characterization for more than four decades. However, a limitation of conventional single-sensor satellite missions is their limited capacity to observe land surface dynamics at the very high spatial and temporal resolutions demanded by a wide range of applications. One solution to this spatio-temporal divide is an observation strategy based on the CubeSat standard, which facilitates constellations of small, inexpensive satellites. Repeatable near-daily image capture in RGB and near-infrared (NIR) bands at 3–4 m resolution has recently become available via a constellation of >130 CubeSats operated commercially by Planet. While the observing capacity afforded by this system is unprecedented, the relatively low radiometric quality and cross-sensor inconsistencies represent key challenges in the realization of their full potential as a game changer in Earth observation. To address this issue, we developed a Cubesat Enabled Spatio-Temporal Enhancement Method (CESTEM) that uses a multi-scale machine-learning technique to correct for radiometric inconsistencies between CubeSat acquisitions. The CESTEM produces Landsat 8 consistent atmospherically corrected surface reflectances in blue, green, red, and NIR bands, but at the spatial scale and temporal frequency of the CubeSat observations. An application of CESTEM over an agricultural dryland system in Saudi Arabia demonstrated CubeSat-based reproduction of Landsat 8 consistent VNIR data with an overall relative mean absolute deviation of 1.6% or better, even when the Landsat 8 and CubeSat acquisitions were temporally displaced by >32 days. The consistently high retrieval accuracies were achieved using a multi-scale target sampling scheme that draws Landsat 8 reference data from a series of scenes by using MODIS-consistent surface reflectance time series to quantify relative changes in Landsat

  16. Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach.

    Science.gov (United States)

    Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

    2015-12-30

    Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

  17. Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach

    Directory of Open Access Journals (Sweden)

    Zhaoyuan Yu

    2015-12-01

    Full Text Available Passive infrared (PIR motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

  18. Hierarchical Bayesian Spatio-Temporal Analysis of Climatic and Socio-Economic Determinants of Rocky Mountain Spotted Fever.

    Directory of Open Access Journals (Sweden)

    Ram K Raghavan

    Full Text Available This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio-economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio-temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio-economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main-effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C in the region, and the relevance of these factors in the context of climate-change impacts on tick-borne diseases are discussed.

  19. Hierarchical Bayesian Spatio-Temporal Analysis of Climatic and Socio-Economic Determinants of Rocky Mountain Spotted Fever.

    Science.gov (United States)

    Raghavan, Ram K; Goodin, Douglas G; Neises, Daniel; Anderson, Gary A; Ganta, Roman R

    2016-01-01

    This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio-economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio-temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio-economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main-effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C) in the region, and the relevance of these factors in the context of climate-change impacts on tick-borne diseases are discussed.

  20. Stability Switches, Hopf Bifurcations, and Spatio-temporal Patterns in a Delayed Neural Model with Bidirectional Coupling

    Science.gov (United States)

    Song, Yongli; Zhang, Tonghua; Tadé, Moses O.

    2009-12-01

    The dynamical behavior of a delayed neural network with bi-directional coupling is investigated by taking the delay as the bifurcating parameter. Some parameter regions are given for conditional/absolute stability and Hopf bifurcations by using the theory of functional differential equations. As the propagation time delay in the coupling varies, stability switches for the trivial solution are found. Conditions ensuring the stability and direction of the Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. We also discuss the spatio-temporal patterns of bifurcating periodic oscillations by using the symmetric bifurcation theory of delay differential equations combined with representation theory of Lie groups. In particular, we obtain that the spatio-temporal patterns of bifurcating periodic oscillations will alternate according to the change of the propagation time delay in the coupling, i.e., different ranges of delays correspond to different patterns of neural activities. Numerical simulations are given to illustrate the obtained results and show the existence of bursts in some interval of the time for large enough delay.

  1. Brazilian Amazonia Deforestation Detection Using Spatio-Temporal Scan Statistics

    Science.gov (United States)

    Vieira, C. A. O.; Santos, N. T.; Carneiro, A. P. S.; Balieiro, A. A. S.

    2012-07-01

    The spatio-temporal models, developed for analyses of diseases, can also be used for others fields of study, including concerns about forest and deforestation. The aim of this paper is to quantitatively check priority areas in order to combat deforestation on the Amazon forest, using the space-time scan statistic. The study area location is at the south of the Amazonas State and cover around 297.183 kilometre squares, including the municipality of Boca do Acre, Labrea, Canutama, Humaita, Manicore, Novo Aripuana e Apui County on the north region of Brazil. This area has showed a significant change for land cover, which has increased the number of deforestation's alerts. Therefore this situation becomes a concern and gets more investigation, trying to stop factors that increase the number of cases in the area. The methodology includes the location and year that deforestation's alert occurred. These deforestation's alerts are mapped by the DETER (Detection System of Deforestation in Real Time in Amazonia), which is carry out by the Brazilian Space Agency (INPE). The software SatScanTM v7.0 was used in order to define space-time permutation scan statistic for detection of deforestation cases. The outcome of this experiment shows an efficient model to detect space-time clusters of deforestation's alerts. The model was efficient to detect the location, the size, the order and characteristics about activities at the end of the experiments. Two clusters were considered actives and kept actives up to the end of the study. These clusters are located in Canutama and Lábrea County. This quantitative spatial modelling of deforestation warnings allowed: firstly, identifying actives clustering of deforestation, in which the environment government official are able to concentrate their actions; secondly, identifying historic clustering of deforestation, in which the environment government official are able to monitoring in order to avoid them to became actives again; and finally

  2. BRAZILIAN AMAZONIA DEFORESTATION DETECTION USING SPATIO-TEMPORAL SCAN STATISTICS

    Directory of Open Access Journals (Sweden)

    C. A. O. Vieira

    2012-07-01

    Full Text Available The spatio-temporal models, developed for analyses of diseases, can also be used for others fields of study, including concerns about forest and deforestation. The aim of this paper is to quantitatively check priority areas in order to combat deforestation on the Amazon forest, using the space-time scan statistic. The study area location is at the south of the Amazonas State and cover around 297.183 kilometre squares, including the municipality of Boca do Acre, Labrea, Canutama, Humaita, Manicore, Novo Aripuana e Apui County on the north region of Brazil. This area has showed a significant change for land cover, which has increased the number of deforestation's alerts. Therefore this situation becomes a concern and gets more investigation, trying to stop factors that increase the number of cases in the area. The methodology includes the location and year that deforestation’s alert occurred. These deforestation's alerts are mapped by the DETER (Detection System of Deforestation in Real Time in Amazonia, which is carry out by the Brazilian Space Agency (INPE. The software SatScanTM v7.0 was used in order to define space-time permutation scan statistic for detection of deforestation cases. The outcome of this experiment shows an efficient model to detect space-time clusters of deforestation’s alerts. The model was efficient to detect the location, the size, the order and characteristics about activities at the end of the experiments. Two clusters were considered actives and kept actives up to the end of the study. These clusters are located in Canutama and Lábrea County. This quantitative spatial modelling of deforestation warnings allowed: firstly, identifying actives clustering of deforestation, in which the environment government official are able to concentrate their actions; secondly, identifying historic clustering of deforestation, in which the environment government official are able to monitoring in order to avoid them to became

  3. Spatio-temporal coherent control of atomic systems: weak to strong field transition and breaking of symmetry in 2D maps

    Energy Technology Data Exchange (ETDEWEB)

    Suchowski, H; Natan, A; Bruner, B D; Silberberg, Y [Physics of Complex Systems, Weizmann Institute of Science, Rehovot (Israel)], E-mail: haim.suchowski@weizmann.ac.il

    2008-04-14

    Coherent control of resonant and non-resonant two-photon absorption processes was examined using a spatio-temporal pulse-shaping technique. By utilizing a combination of temporal focusing and femtosecond pulse-shaping techniques, we spatially control multiphoton absorption processes in a completely deterministic manner. Distinctive symmetry properties emerge through two-dimensional mapping of spatio-temporal data. These symmetries break down in the transition to strong fields, revealing details of strong-field effects such as power broadenings and dynamic Stark shifts. We also present demonstrations of chirp-dependent population transfer in atomic rubidium, as well as the spatial separation of resonant and non-resonant excitation pathways in atomic caesium.

  4. Spatio-temporal coherent control of atomic systems: weak to strong field transition and breaking of symmetry in 2D maps

    International Nuclear Information System (INIS)

    Suchowski, H; Natan, A; Bruner, B D; Silberberg, Y

    2008-01-01

    Coherent control of resonant and non-resonant two-photon absorption processes was examined using a spatio-temporal pulse-shaping technique. By utilizing a combination of temporal focusing and femtosecond pulse-shaping techniques, we spatially control multiphoton absorption processes in a completely deterministic manner. Distinctive symmetry properties emerge through two-dimensional mapping of spatio-temporal data. These symmetries break down in the transition to strong fields, revealing details of strong-field effects such as power broadenings and dynamic Stark shifts. We also present demonstrations of chirp-dependent population transfer in atomic rubidium, as well as the spatial separation of resonant and non-resonant excitation pathways in atomic caesium

  5. Research on spatio-temporal database techniques for spatial information service

    Science.gov (United States)

    Zhao, Rong; Wang, Liang; Li, Yuxiang; Fan, Rongshuang; Liu, Ping; Li, Qingyuan

    2007-06-01

    Geographic data should be described by spatial, temporal and attribute components, but the spatio-temporal queries are difficult to be answered within current GIS. This paper describes research into the development and application of spatio-temporal data management system based upon GeoWindows GIS software platform which was developed by Chinese Academy of Surveying and Mapping (CASM). Faced the current and practical requirements of spatial information application, and based on existing GIS platform, one kind of spatio-temporal data model which integrates vector and grid data together was established firstly. Secondly, we solved out the key technique of building temporal data topology, successfully developed a suit of spatio-temporal database management system adopting object-oriented methods. The system provides the temporal data collection, data storage, data management and data display and query functions. Finally, as a case study, we explored the application of spatio-temporal data management system with the administrative region data of multi-history periods of China as the basic data. With all the efforts above, the GIS capacity of management and manipulation in aspect of time and attribute of GIS has been enhanced, and technical reference has been provided for the further development of temporal geographic information system (TGIS).

  6. Bayesian spatio-temporal analysis and geospatial risk factors of human monocytic ehrlichiosis.

    Directory of Open Access Journals (Sweden)

    Ram K Raghavan

    Full Text Available Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005-2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER], and socio-economic conditions (US Census Bureau were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005-2012, and identified poverty status, relative humidity, and an interactive factor, 'diurnal temperature range x mixed forest area' as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases.

  7. VISUALIZATION OF SPATIO-TEMPORAL RELATIONS IN MOVEMENT EVENT USING MULTI-VIEW

    Directory of Open Access Journals (Sweden)

    K. Zheng

    2017-09-01

    Full Text Available Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

  8. Visualization of Spatio-Temporal Relations in Movement Event Using Multi-View

    Science.gov (United States)

    Zheng, K.; Gu, D.; Fang, F.; Wang, Y.; Liu, H.; Zhao, W.; Zhang, M.; Li, Q.

    2017-09-01

    Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

  9. Spatio-temporal Hotelling observer for signal detection from image sequences.

    Science.gov (United States)

    Caucci, Luca; Barrett, Harrison H; Rodriguez, Jeffrey J

    2009-06-22

    Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection.

  10. Research of Cadastral Data Modelling and Database Updating Based on Spatio-temporal Process

    Directory of Open Access Journals (Sweden)

    ZHANG Feng

    2016-02-01

    Full Text Available The core of modern cadastre management is to renew the cadastre database and keep its currentness,topology consistency and integrity.This paper analyzed the changes and their linkage of various cadastral objects in the update process.Combined object-oriented modeling technique with spatio-temporal objects' evolution express,the paper proposed a cadastral data updating model based on the spatio-temporal process according to people's thought.Change rules based on the spatio-temporal topological relations of evolution cadastral spatio-temporal objects are drafted and further more cascade updating and history back trace of cadastral features,land use and buildings are realized.This model implemented in cadastral management system-ReGIS.Achieved cascade changes are triggered by the direct driving force or perceived external events.The system records spatio-temporal objects' evolution process to facilitate the reconstruction of history,change tracking,analysis and forecasting future changes.

  11. Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI

    Science.gov (United States)

    Ruiz-Pérez, Guiomar; Koch, Julian; Manfreda, Salvatore; Caylor, Kelly; Francés, Félix

    2017-12-01

    Ecohydrological modeling studies in developing countries, such as sub-Saharan Africa, often face the problem of extensive parametrical requirements and limited available data. Satellite remote sensing data may be able to fill this gap, but require novel methodologies to exploit their spatio-temporal information that could potentially be incorporated into model calibration and validation frameworks. The present study tackles this problem by suggesting an automatic calibration procedure, based on the empirical orthogonal function, for distributed ecohydrological daily models. The procedure is tested with the support of remote sensing data in a data-scarce environment - the upper Ewaso Ngiro river basin in Kenya. In the present application, the TETIS-VEG model is calibrated using only NDVI (Normalized Difference Vegetation Index) data derived from MODIS. The results demonstrate that (1) satellite data of vegetation dynamics can be used to calibrate and validate ecohydrological models in water-controlled and data-scarce regions, (2) the model calibrated using only satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet and (3) the proposed automatic calibration methodology works satisfactorily and it allows for a straightforward incorporation of spatio-temporal data into the calibration and validation framework of a model.

  12. Presentation of spatio-temporal data in the context of information capacity and visual suggestiveness

    Science.gov (United States)

    Cybulski, Paweł

    2014-12-01

    The aim of this article is to present the concept of information capacity and visual suggestiveness as a map characteristic on the example of two maps of human migration. From this viewpoint the literature study has been performed. Proposed by the author the features of cartographic visualization are an attempt to establish cartographic pragmatics and find the way to increase effectiveness of dynamic maps with large information capacity. Among the works on cartographic pragmatics, muliaspectuality of spatio-temporal data the proposed solution has not been taken so far, and refers to the map design problematic. Celem rozważań było podsumowanie wiedzy dotyczącej projektowania dynamicznych opracowań przestrzennych oraz ich klasyfi kacja ze względu na ilość zmiennych grafi cznych oraz dynamicznych, które mogą zostać użyte w procesie geowizualizacji. Zróżnicowanie ilości zmiennych grafi cznych i dynamicznych w przestrzennych wizualizacjach autor proponuje nazywać pojemnością wizualną prezentacji. Autor stawia również hipotezę, że im większą pojemność wizualną stosujemy tym bardziej sugestywne musi być to przestawienie, aby efektywność przekazywania informacji była zachowana

  13. A Visual Analytics Approach for Extracting Spatio-Temporal Urban Mobility Information from Mobile Network Traffic

    Directory of Open Access Journals (Sweden)

    Euro Beinat

    2012-11-01

    Full Text Available In this paper we present a visual analytics approach for deriving spatio-temporal patterns of collective human mobility from a vast mobile network traffic data set. More than 88 million movements between pairs of radio cells—so-called handovers—served as a proxy for more than two months of mobility within four urban test areas in Northern Italy. In contrast to previous work, our approach relies entirely on visualization and mapping techniques, implemented in several software applications. We purposefully avoid statistical or probabilistic modeling and, nonetheless, reveal characteristic and exceptional mobility patterns. The results show, for example, surprising similarities and symmetries amongst the total mobility and people flows between the test areas. Moreover, the exceptional patterns detected can be associated to real-world events such as soccer matches. We conclude that the visual analytics approach presented can shed new light on large-scale collective urban mobility behavior and thus helps to better understand the “pulse” of dynamic urban systems.

  14. Spatio-Temporal Changes in Structure for a Mediterranean Urban Forest: Santiago, Chile 2002 to 2014

    Directory of Open Access Journals (Sweden)

    Francisco J. Escobedo

    2016-06-01

    Full Text Available There is little information on how urban forest ecosystems in South America and Mediterranean climates change across both space and time. This study statistically and spatially analyzed the spatio-temporal dynamics of Santiago, Chile’s urban forest using tree and plot-level data from permanent plots from 2002 to 2014. We found mortality, ingrowth, and tree cover remained stable over the analysis period and similar patterns were observed for basal area (BA and biomass. However, tree cover increased, and was greater in the highest socioeconomic stratum neighborhoods while it dropped in the medium and low strata. Growth rates for the five most common tree species averaged from 0.12 to 0.36 cm·year−1. Spatially, tree biomass and BA were greater in the affluent, northeastern sections of the city and in southwest peri-urban areas. Conversely, less affluent central, northwest, and southern areas showed temporal losses in BA and biomass. Overall, we found that Santiago’s urban forest follows similar patterns as in other parts of the world; affluent areas tend to have more and better managed urban forests than poorer areas, and changes are primarily influenced by social and ecological drivers. Nonetheless, care is warranted when comparing urban forest structural metrics measured with similar sampling-monitoring approaches across ecologically disparate regions and biomes.

  15. Quantitative measurement of intracellular transport of nanocarriers by spatio-temporal image correlation spectroscopy

    International Nuclear Information System (INIS)

    Coppola, S; Pozzi, D; De Sanctis, S Candeloro; Caracciolo, G; Digman, M A; Gratton, E

    2013-01-01

    Spatio-temporal image correlation spectroscopy (STICS) is a powerful technique for assessing the nature of particle motion in complex systems although it has been rarely used to investigate the intracellular dynamics of nanocarriers so far. Here we introduce a method for characterizing the mode of motion of nanocarriers and for quantifying their transport parameters on different length scales from single-cell to subcellular level. Using this strategy we were able to study the mechanisms responsible for the intracellular transport of DOTAP–DOPC/DNA (DOTAP: 1,2-dioleoyl-3-trimethylammonium-propane; DOPC: dioleoylphosphocholine) and DC-Chol–DOPE/DNA (DC-Chol: 3β-[N-(N,N-dimethylaminoethane)-carbamoyl] cholesterol; DOPE: dioleoylphosphatidylethanolamine) lipoplexes in CHO-K1 (CHO: Chinese hamster ovary) live cells. Measurement of both diffusion coefficients and velocity vectors (magnitude and direction) averaged over regions of the cell revealed the presence of distinct modes of motion. Lipoplexes diffused slowly on the cell surface (diffusion coefficient: D ≈ 0.003 μm 2 s −1 ). In the cytosol, the lipoplexes’ motion was characterized by active transport with average velocity v ≈ 0.03 μm 2 s −1 and random motion. The method permitted us to generate an intracellular transport map showing several regions of concerted motion of lipoplexes. (paper)

  16. Quantitative measurement of intracellular transport of nanocarriers by spatio-temporal image correlation spectroscopy

    Science.gov (United States)

    Coppola, S.; Pozzi, D.; Candeloro De Sanctis, S.; Digman, M. A.; Gratton, E.; Caracciolo, G.

    2013-03-01

    Spatio-temporal image correlation spectroscopy (STICS) is a powerful technique for assessing the nature of particle motion in complex systems although it has been rarely used to investigate the intracellular dynamics of nanocarriers so far. Here we introduce a method for characterizing the mode of motion of nanocarriers and for quantifying their transport parameters on different length scales from single-cell to subcellular level. Using this strategy we were able to study the mechanisms responsible for the intracellular transport of DOTAP-DOPC/DNA (DOTAP: 1,2-dioleoyl-3-trimethylammonium-propane; DOPC: dioleoylphosphocholine) and DC-Chol-DOPE/DNA (DC-Chol: 3β-[N-(N,N-dimethylaminoethane)-carbamoyl] cholesterol; DOPE: dioleoylphosphatidylethanolamine) lipoplexes in CHO-K1 (CHO: Chinese hamster ovary) live cells. Measurement of both diffusion coefficients and velocity vectors (magnitude and direction) averaged over regions of the cell revealed the presence of distinct modes of motion. Lipoplexes diffused slowly on the cell surface (diffusion coefficient: D ≈ 0.003 μm2 s-1). In the cytosol, the lipoplexes’ motion was characterized by active transport with average velocity v ≈ 0.03 μm2 s-1 and random motion. The method permitted us to generate an intracellular transport map showing several regions of concerted motion of lipoplexes.

  17. Assessment of long-term spatio-temporal radiofrequency electromagnetic field exposure.

    Science.gov (United States)

    Aerts, Sam; Wiart, Joe; Martens, Luc; Joseph, Wout

    2018-02-01

    As both the environment and telecommunications networks are inherently dynamic, our exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) at an arbitrary location is not at all constant in time. In this study, more than a year's worth of measurement data collected in a fixed low-cost exposimeter network distributed over an urban environment was analysed and used to build, for the first time, a full spatio-temporal surrogate model of outdoor exposure to downlink Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) signals. Though no global trend was discovered over the measuring period, the difference in measured exposure between two instances could reach up to 42dB (a factor 12,000 in power density). Furthermore, it was found that, taking into account the hour and day of the measurement, the accuracy of the surrogate model in the area under study was improved by up to 50% compared to models that neglect the daily temporal variability of the RF signals. However, further study is required to assess the extent to which the results obtained in the considered environment can be extrapolated to other geographic locations. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Controlling spatio-temporal extreme events by decreasing the localized energy

    International Nuclear Information System (INIS)

    Du Lin; Xu Wei; Li Zhanguo; Zhou Bingchang

    2011-01-01

    The problem of controlling extreme events in spatially extended dynamical systems is investigated in this Letter. Based on observations of the system state, the control technique we proposed locally decreases the spatial energy of the amplitude in the vicinity of the highest burst, without needs of any knowledge or prediction of the system model. Considering the specific Complex Ginzburg-Landau equation, we provide theoretical analysis for designing the localized state feedback controller. More exactly, a simple control law by varying a damping parameter at control region is chose to achieve the control. Numerical simulations and statistic analysis demonstrate that extreme events can be efficiently suppressed by our strategy. In particular, the cost of the control and the tolerant time delay in applying the control is considered in detail. - Highlights: → We propose a local control scheme to suppress spatio-temporal extreme events. → The control is address by decreasing the spatial energy of the system locally. → The detail control law is to apply localized state feedback based on observations. → The cost of the control increases with the size of the control region exponentially. → The tolerant delay of the control is about 5-6 times of lifetime of extreme events.

  19. Effect of spatio-temporal noise in the Eddington factor on the scalar flux

    International Nuclear Information System (INIS)

    Prinja, Anil K.

    2015-01-01

    Highlights: • Spatio-temporal Gaussian noise is considered in the Eddington factor simulating noise in the low-order equation associated with a hybrid numerical solution technique for the transport equation. • A closed equation for the mean scalar flux is obtained that is accurate for small correlation times and exact in the white noise limit. • The equation for the mean scalar flux contains a fourth-order spatial derivative that is a consequence of the noise. • The fourth-order term is shown to destabilize all perturbations with wavelengths less than a critical value that depends on the noise amplitude, correlation length and time. • An asymptotic solution is shown to be possible for small noise amplitude. - Abstract: Spatial and temporal noise in the Eddington factor, simulating noise arising in hybrid numerical schemes, is modeled as a Gaussian stochastic process and its effect on the scalar flux investigated theoretically. In the small correlation time limit, a nonstandard closed equation for the mean scalar flux is obtained that contains a fourth order derivative of the scalar flux. In an infinite medium setting, this term is shown to have a destabilizing effect on the solution. Specifically, any spatial Fourier mode with wavelength smaller than a critical value, which depends on the noise characteristics, amplifies in time without bound, in contrast to the corresponding nonrandom case which is dissipative for all modes. An asymptotic solution is obtained which shows that the noise effect disappears at late times and the scalar flux limits to the deterministic solution.

  20. Spatio-Temporal Data Analysis at Scale Using Models Based on Gaussian Processes

    Energy Technology Data Exchange (ETDEWEB)

    Stein, Michael [Univ. of Chicago, IL (United States)

    2017-03-13

    Gaussian processes are the most commonly used statistical model for spatial and spatio-temporal processes that vary continuously. They are broadly applicable in the physical sciences and engineering and are also frequently used to approximate the output of complex computer models, deterministic or stochastic. We undertook research related to theory, computation, and applications of Gaussian processes as well as some work on estimating extremes of distributions for which a Gaussian process assumption might be inappropriate. Our theoretical contributions include the development of new classes of spatial-temporal covariance functions with desirable properties and new results showing that certain covariance models lead to predictions with undesirable properties. To understand how Gaussian process models behave when applied to deterministic computer models, we derived what we believe to be the first significant results on the large sample properties of estimators of parameters of Gaussian processes when the actual process is a simple deterministic function. Finally, we investigated some theoretical issues related to maxima of observations with varying upper bounds and found that, depending on the circumstances, standard large sample results for maxima may or may not hold. Our computational innovations include methods for analyzing large spatial datasets when observations fall on a partially observed grid and methods for estimating parameters of a Gaussian process model from observations taken by a polar-orbiting satellite. In our application of Gaussian process models to deterministic computer experiments, we carried out some matrix computations that would have been infeasible using even extended precision arithmetic by focusing on special cases in which all elements of the matrices under study are rational and using exact arithmetic. The applications we studied include total column ozone as measured from a polar-orbiting satellite, sea surface temperatures over the

  1. Stochastic properties of the Friedman dynamical system

    International Nuclear Information System (INIS)

    Szydlowski, M.; Heller, M.; Golda, Z.

    1985-01-01

    Some mathematical aspects of the stochastic cosmology are discussed in the corresponding ordinary Friedman world models. In particulare, it is shown that if the strong and Lorentz energy conditions are known, or the potential function is given, or a stochastic measure is suitably defined then the structure of the phase plane of the Friedman dynamical system is determined. 11 refs., 2 figs. (author)

  2. Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

    KAUST Repository

    Sun, Ying

    2011-10-24

    This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio-temporal dependence and the 1.5 times the 50% central region empirical outlier detection rule. Then, we propose to simulate observations without outliers on the basis of a robust estimator of the covariance function of the data. We select the constant factor in the functional boxplot to control the probability of correctly detecting no outliers. Finally, we apply the selected factor to the functional boxplot of the original data. As applications, the factor selection procedure and the adjusted functional boxplots are demonstrated on sea surface temperatures, spatio-temporal precipitation and general circulation model (GCM) data. The outlier detection performance is also compared before and after the factor adjustment. © 2011 John Wiley & Sons, Ltd.

  3. Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia

    Directory of Open Access Journals (Sweden)

    Mohammad Nur Shodiq

    2016-03-01

    Full Text Available Spatio temporal data clustering is challenge task. The result of clustering data are utilized to investigate the seismic parameters. Seismic parameters are used to describe the characteristics of earthquake behavior. One of the effective technique to study multidimensional spatio temporal data is visualization. But, visualization of multidimensional data is complicated problem. Because, this analysis consists of observed data cluster and seismic parameters. In this paper, we propose a visualization system, called as IES (Indonesia Earthquake System, for cluster analysis, spatio temporal analysis, and visualize the multidimensional data of seismic parameters. We analyze the cluster analysis by using automatic clustering, that consists of get optimal number of cluster and Hierarchical K-means clustering. We explore the visual cluster and multidimensional data in low dimensional space visualization. We made experiment with observed data, that consists of seismic data around Indonesian archipelago during 2004 to 2014. Keywords: Clustering, visualization, multidimensional data, seismic parameters.

  4. Review of complex networks application in hydroclimatic extremes with an implementation to characterize spatio-temporal drought propagation in continental USA

    Science.gov (United States)

    Konapala, Goutam; Mishra, Ashok

    2017-12-01

    The quantification of spatio-temporal hydroclimatic extreme events is a key variable in water resources planning, disaster mitigation, and preparing climate resilient society. However, quantification of these extreme events has always been a great challenge, which is further compounded by climate variability and change. Recently complex network theory was applied in earth science community to investigate spatial connections among hydrologic fluxes (e.g., rainfall and streamflow) in water cycle. However, there are limited applications of complex network theory for investigating hydroclimatic extreme events. This article attempts to provide an overview of complex networks and extreme events, event synchronization method, construction of networks, their statistical significance and the associated network evaluation metrics. For illustration purpose, we apply the complex network approach to study the spatio-temporal evolution of droughts in Continental USA (CONUS). A different drought threshold leads to a new drought event as well as different socio-economic implications. Therefore, it would be interesting to explore the role of thresholds on spatio-temporal evolution of drought through network analysis. In this study, long term (1900-2016) Palmer drought severity index (PDSI) was selected for spatio-temporal drought analysis using three network-based metrics (i.e., strength, direction and distance). The results indicate that the drought events propagate differently at different thresholds associated with initiation of drought events. The direction metrics indicated that onset of mild drought events usually propagate in a more spatially clustered and uniform approach compared to onsets of moderate droughts. The distance metric shows that the drought events propagate for longer distance in western part compared to eastern part of CONUS. We believe that the network-aided metrics utilized in this study can be an important tool in advancing our knowledge on drought

  5. Spatio-temporal pattern analysis for evaluation of the spread of human infections with avian influenza A(H7N9) virus in China, 2013-2014.

    Science.gov (United States)

    Dong, Wen; Yang, Kun; Xu, Quanli; Liu, Lin; Chen, Juan

    2017-10-24

    A large number (n = 460) of A(H7N9) human infections have been reported in China from March 2013 through December 2014, and H7N9 outbreaks in humans became an emerging issue for China health, which have caused numerous disease outbreaks in domestic poultry and wild bird populations, and threatened human health severely. The aims of this study were to investigate the directional trend of the epidemic and to identify the significant presence of spatial-temporal clustering of influenza A(H7N9) human cases between March 2013 and December 2014. Three distinct epidemic phases of A(H7N9) human infections were identified in this study. In each phase, standard deviational ellipse analysis was conducted to examine the directional trend of disease spreading, and retrospective space-time permutation scan statistic was then used to identify the spatio-temporal cluster patterns of H7N9 outbreaks in humans. The ever-changing location and the increasing size of the three identified standard deviational ellipses showed that the epidemic moved from east to southeast coast, and hence to some central regions, with a future epidemiological trend of continue dispersing to more central regions of China, and a few new human cases might also appear in parts of the western China. Furthermore, A(H7N9) human infections were clustering in space and time in the first two phases with five significant spatio-temporal clusters (p < 0.05), but there was no significant cluster identified in phase III. There was a new epidemiologic pattern that the decrease in significant spatio-temporal cluster of A(H7N9) human infections was accompanied with an obvious spatial expansion of the outbreaks during the study period, and identification of the spatio-temporal patterns of the epidemic can provide valuable insights for better understanding the spreading dynamics of the disease in China.

  6. Evolution of spatio-temporal drought characteristics: validation, projections and effect of adaptation scenarios

    Science.gov (United States)

    Vidal, J.-P.; Martin, E.; Kitova, N.; Najac, J.; Soubeyroux, J.-M.

    2012-08-01

    Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, such as mean duration, mean affected area and total magnitude. This paper addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) Are downscaled climate projections able to simulate spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century? (3) How to use standardized drought indices to represent theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-yr multilevel and multiscale drought reanalysis over France. Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index and the Standardized Soil Wetness Index, respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well simulated by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals, either retrospective or prospective. The perceived spatio-temporal characteristics of drought events derived from these theoretical adaptation scenarios show much reduced changes, but they call for more realistic scenarios at both the catchment and national scale in order to accurately assess the combined effect of

  7. Unravelling spatio-temporal evapotranspiration patterns in topographically complex landscapes

    Science.gov (United States)

    Metzen, Daniel; Sheridan, Gary; Nyman, Petter; Lane, Patrick

    2016-04-01

    Vegetation co-evolves with soils and topography under a given long-term climatic forcing. Previous studies demonstrated a strong eco-hydrologic feedback between topography, vegetation and energy and water fluxes. Slope orientation (aspect and gradient) alter the magnitude of incoming solar radiation resulting in larger evaporative losses and less water availability on equator-facing slopes. Furthermore, non-local water inputs from upslope areas potentially contribute to available water at downslope positions. The combined effect of slope orientation and drainage position creates complex spatial patterns in biological productivity and pedogenesis, which in turn alter the local hydrology. In complex upland landscapes, topographic alteration of incoming radiation can cause substantial aridity index (ratio of potential evapotranspiration to precipitation) variations over small spatial extents. Most of the upland forests in south-east Australia are located in an aridity index (AI) range of 1-2, around the energy limited to water limited boundary, where forested systems are expected to be most sensitive to AI changes. In this research we aim to improve the fundamental understanding of spatio-temporal evolution of evapotranspiration (ET) patterns in complex terrain, accounting for local topographic effects on system properties (e.g. soil depth, sapwood area, leaf area) and variation in energy and water exchange processes due to slope orientation and drainage position. Six measurement plots were set-up in a mixed species eucalypt forest on a polar and equatorial-facing hillslope (AI ˜1.3 vs. 1.8) at varying drainage position (ridge, mid-slope, gully), while minimizing variations in other factors, e.g. geology and weather patterns. Sap flow, soil water content, incoming solar radiation and throughfall were continuously monitored at field sites spanning a wide range of soil depth (0.5 - >3m), maximum tree heights (17 - 51m) and LAI (1.2 - 4.6). Site-specific response curves

  8. Using a weather generator to downscale spatio-temporal precipitation at urban scale

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Christensen, Ole Bøssing; Arnbjerg-Nielsen, Karsten

    In recent years, urban flooding has occurred in Denmark due to very local extreme precipitation events with very short lifetime. Several of these floods have been among the most severe ever experienced. The current study demonstrates the applicability of the Spatio-Temporal Neyman-Scott Rectangular...... the observed spatio-temporal differences at very fine scale for all measured parameters. For downscaling, perturbation with a climate change signal, precipitation from four different regional climate model simulations has been analysed. The analysed models are two runs from the ENSEMBLES (RACMO...

  9. Stochastic Thermodynamics: A Dynamical Systems Approach

    Directory of Open Access Journals (Sweden)

    Tanmay Rajpurohit

    2017-12-01

    Full Text Available In this paper, we develop an energy-based, large-scale dynamical system model driven by Markov diffusion processes to present a unified framework for statistical thermodynamics predicated on a stochastic dynamical systems formalism. Specifically, using a stochastic state space formulation, we develop a nonlinear stochastic compartmental dynamical system model characterized by energy conservation laws that is consistent with statistical thermodynamic principles. In particular, we show that the difference between the average supplied system energy and the average stored system energy for our stochastic thermodynamic model is a martingale with respect to the system filtration. In addition, we show that the average stored system energy is equal to the mean energy that can be extracted from the system and the mean energy that can be delivered to the system in order to transfer it from a zero energy level to an arbitrary nonempty subset in the state space over a finite stopping time.

  10. Spatio-Temporal Variation in Water Quality of Orle River Basin, S.W. ...

    African Journals Online (AJOL)

    Spatio-Temporal Variation in Water Quality of Orle River Basin, S.W. Nigeria. ... Abstract. The water quality of small streams in Auchi area of Edo State, S.W. Nigeria was investigated with a view to ... and ecosystems. The study was carried out

  11. Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets

    KAUST Repository

    Zhang, Bohai; Sang, Huiyan; Huang, Jianhua Z.

    2014-01-01

    of dataset and application of such models is not feasible for large datasets. This article extends the full-scale approximation (FSA) approach by Sang and Huang (2012) to the spatio-temporal context to reduce computational complexity. A reversible jump Markov

  12. Spatio-Temporal Layout of Human Actions for Improved Bag-of-Words Action Detection

    NARCIS (Netherlands)

    Burghouts, G.J.; Schutte, K.

    2013-01-01

    We investigate how human action recognition can be improved by considering spatio-temporal layout of actions. From literature, we adopt a pipeline consisting of STIP features, a random forest to quantize the features into histograms, and an SVM classifier. Our goal is to detect 48 human actions,

  13. A Spatio-Temporal Based Estimation of Sequestered Carbon in the ...

    African Journals Online (AJOL)

    The vegetation in the Tarkwa Mining Area (TMA) has experienced changes as a result of population growth, urbanization, mining activities and illegal chainsaw operations and this has led to an increase in temperature over the past years. Therefore, studying its forest biomass carbon (C) stock and its spatio-temporal ...

  14. Displaced calibration of PM10 measurements using spatio-temporal models

    Directory of Open Access Journals (Sweden)

    Daniela Cocchi

    2007-12-01

    Full Text Available PM10 monitoring networks are equipped with heterogeneous samplers. Some of these samplers are known to underestimate true levels of concentrations (non-reference samplers. In this paper we propose a hierarchical spatio-temporal Bayesian model for the calibration of measurements recorded using non-reference samplers, by borrowing strength from non co-located reference sampler measurements.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  16. Effects of Spatio-Temporal Aliasing on Pilot Performance in Active Control Tasks

    Science.gov (United States)

    Zaal, Peter; Sweet, Barbara

    2010-01-01

    Spatio-temporal aliasing affects pilot performance and control behavior. For increasing refresh rates: 1) Significant change in control behavior: a) Increase in visual gain and neuromuscular frequency. b) Decrease in visual time delay. 2) Increase in tracking performance: a) Decrease in RMSe. b) Increase in crossover frequency.

  17. [Spatio-temporal variations of origin, distribution and diffusion of Oncomelania hupensis in Yangtze River Basin].

    Science.gov (United States)

    Deng, Chen; Li-Yong, Wen

    2017-10-24

    As the only intermediate host of Schistosoma japonicum, Oncomelania hupensis in China is mainly distributed in the Yangtze River Basin. The origin of the O. hupensis and the spatio-temporal variations of its distribution and diffusion in the Yangtze River Basin and the influencing factors, as well as significances in schistosomiasis elimination in China are reviewed in this paper.

  18. Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series

    Science.gov (United States)

    Lu, Meng; Pebesma, Edzer; Sanchez, Alber; Verbesselt, Jan

    2016-07-01

    Growing availability of long-term satellite imagery enables change modeling with advanced spatio-temporal statistical methods. Multidimensional arrays naturally match the structure of spatio-temporal satellite data and can provide a clean modeling process for complex spatio-temporal analysis over large datasets. Our study case illustrates the detection of breakpoints in MODIS imagery time series for land cover change in the Brazilian Amazon using the BFAST (Breaks For Additive Season and Trend) change detection framework. BFAST includes an Empirical Fluctuation Process (EFP) to alarm the change and a change point time locating process. We extend the EFP to account for the spatial autocorrelation between spatial neighbors and assess the effects of spatial correlation when applying BFAST on satellite image time series. In addition, we evaluate how sensitive EFP is to the assumption that its time series residuals are temporally uncorrelated, by modeling it as an autoregressive process. We use arrays as a unified data structure for the modeling process, R to execute the analysis, and an array database management system to scale computation. Our results point to BFAST as a robust approach against mild temporal and spatial correlation, to the use of arrays to ease the modeling process of spatio-temporal change, and towards communicable and scalable analysis.

  19. A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets

    KAUST Repository

    Xu, Ganggang

    2015-01-01

    When spatio-temporal datasets are large, the computational burden can lead to failures in the implementation of traditional geostatistical tools. In this paper, we propose a computationally efficient Bayesian hierarchical spatio-temporal model in which the spatial dependence is approximated by a Gaussian Markov random field (GMRF) while the temporal correlation is described using a vector autoregressive model. By introducing an auxiliary lattice on the spatial region of interest, the proposed method is not only able to handle irregularly spaced observations in the spatial domain, but it is also able to bypass the missing data problem in a spatio-temporal process. Because the computational complexity of the proposed Markov chain Monte Carlo algorithm is of the order O(n) with n the total number of observations in space and time, our method can be used to handle very large spatio-temporal datasets with reasonable CPU times. The performance of the proposed model is illustrated using simulation studies and a dataset of precipitation data from the coterminous United States.

  20. Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution

    NARCIS (Netherlands)

    Kilibarda, M.; Hengl, T.; Heuvelink, G.B.M.; Graler, B.; Pebesma, E.; Tadic, M.P.; Bajat, B.

    2014-01-01

    Combined Global Surface Summary of Day and European Climate Assessment and Dataset daily meteorological data sets (around 9000 stations) were used to build spatio-temporal geostatistical models and predict daily air temperature at ground resolution of 1km for the global land mass. Predictions in

  1. A hierarchical Bayesian spatio-temporal model to forecast trapped particle fluxes over the SAA region

    Czech Academy of Sciences Publication Activity Database

    Suparta, W.; Gusrizal, G.; Kudela, Karel; Isa, Z.

    2017-01-01

    Roč. 28, č. 3 (2017), s. 357-370 ISSN 1017-0839 R&D Projects: GA MŠk EF15_003/0000481 Institutional support: RVO:61389005 Keywords : trapped particle * spatio-temporal * hierarchical Bayesian * forecasting Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 0.752, year: 2016

  2. Probabilistic M/EEG source imaging from sparse spatio-temporal event structure

    DEFF Research Database (Denmark)

    Stahlhut, Carsten; Attias, Hagai T.; Wipf, David

    While MEG and EEG source imaging methods have to tackle a severely ill-posed problem their success can be stated as their ability to constrain the solutions using appropriate priors. In this paper we propose a hierarchical Bayesian model facilitating spatio-temporal patterns through the use of bo...

  3. Spatio-temporal aspects of gated residential security estates in non-metropolitan Western Cape

    CSIR Research Space (South Africa)

    Spocter, M

    2011-04-01

    Full Text Available . This research attempts to address this research gap by focusing on the spatio-temporal aspects of non-metropolitan gated residential security estates in the Western Cape Province. It was found that most non-metropolitan gated residential security estates were...

  4. Spatio-temporal population genetics of the Danish pine marten (Martes martes)

    DEFF Research Database (Denmark)

    Pertoldi, Cino; Barker, Stuart F.; Madsen, Aksel Bo

    2008-01-01

    A spatio-temporal study of genetic variation in the Danish pine marten (Martes martes) populations from the Jutland peninsula and from the island of Sealand was performed using 11 microsatellite markers. Samples obtained from 1892 to 2003 were subdivided into historical (prior to 1970) and recent...

  5. Spatio-temporal resolved diagnostics of the single filament barrier discharge in air

    International Nuclear Information System (INIS)

    Wagner, H.E.; Brandenburg, R.; Michel, P.; Kozlov, K.V.

    2001-01-01

    First experimental results on the spatio-temporal development of single filaments of DBDs in dry air at atmospheric pressure are presented. The measurements allow a detailed visualisation and interpretation of the streamer development. In combination with the kinetic model they are used to get information on the spatiotemporal development of the reduced field-strength E/n, too

  6. A test for stationarity of spatio-temporal random fields on planar and spherical domains

    KAUST Repository

    Jun, Mikyoung; Genton, Marc G.

    2012-01-01

    A formal test for weak stationarity of spatial and spatio-temporal random fields is proposed. We consider the cases where the spatial domain is planar or spherical, and we do not require distributional assumptions for the random fields. The method

  7. A spatio-temporal autocorrelation change detection approach using hyper-temporal satellite data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2013-07-01

    Full Text Available -1 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia 21-26 July 2013 A SPATIO-TEMPORAL AUTOCORRELATION CHANGE DETECTION APPROACH USING HYPER-TEMPORAL SATELLITE DATA yzW. Kleynhans, yz,B.P Salmon,zK. J. Wessels...

  8. A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets

    KAUST Repository

    Xu, Ganggang; Liang, Faming; Genton, Marc G.

    2015-01-01

    method is not only able to handle irregularly spaced observations in the spatial domain, but it is also able to bypass the missing data problem in a spatio-temporal process. Because the computational complexity of the proposed Markov chain Monte Carlo

  9. A FRAMEWORK FOR ONLINE SPATIO-TEMPORAL DATA VISUALIZATION BASED ON HTML5

    Directory of Open Access Journals (Sweden)

    B. Mao

    2012-07-01

    Full Text Available Web is entering a new phase – HTML5. New features of HTML5 should be studied for online spatio-temporal data visualization. In the proposed framework, spatio-temporal data is stored in the data server and is sent to user browsers with WebSocket. Public geo-data such as Internet digital map is integrated into the browsers. Then animation is implemented through the canvas object defined by the HTML5 specification. To simulate the spatio-temporal data source, we collected the daily location of 15 users with GPS tracker. The current positions of the users are collected every minute and are recorded in a file. Based on this file, we generate a real time spatio-temporal data source which sends out current user location every second.By enlarging the real time scales by 60 times, we can observe the movement clearly. The data transmitted with WebSocket is the coordinates of users' current positions, which will can be demonstrated in client browsers.

  10. Mortality in Danish Swine herds: Spatio-temporal clusters and risk factors

    DEFF Research Database (Denmark)

    Lopes Antunes, Ana Carolina; Ersbøll, Annette Kjær; Bihrmann, Kristine

    2017-01-01

    -temporal analysis included data description for spatial, temporal, and spatio-temporal cluster analysis for three age groups: weaners (up to 30 kg), sows and finishers. Logistic regression models were used to assess the potential factors associated with finisher and weaner herds being included within multiple...

  11. Towards operational hydrology for a thorough spatio-temporal exploration of the Critical Zone

    Science.gov (United States)

    Chatton, Eliot; Labasque, Thierry; Guillou, Aurélie; Aquilina, Luc; Bour, Olivier; Le Borgne, Tanguy; Longuevergne, Laurent

    2017-04-01

    Over the last century, the Critical Zone faced remarkable climate and land use changes increasing the pressures on the Hydrosphere and giving rise to numerous environmental consequences in terms of water quantity and quality. From now on, the Critical Zone must face the challenge to supply 9 billion people with quality food and safe drinking water in a context of global warming. For the Hydrosphere, this challenge could be addressed with a better understanding of the dynamics and resilience of aquatic environments (rivers, lakes, groundwaters, oceans). In view of the spatial and temporal variety and variability of flow dynamics and biogeochemical reactions occurring in the Hydrosphere a new investigation method is needed. This study approaches the concept of "operational hydrology" aiming to enhance either the spatio-temporal distribution and the quality of environmental data for a thorough exploration of the Hydrosphere. To illustrate our approach, we present natural and anthropogenic dissolved gas data (He, Ne, Ar, Kr, Xe, N2, O2, CO2, CH4, N2O, H2, BTEX, and some VOCs) measured in situ with a CF-MIMS (Chatton et al, 2016) installed in a mobile laboratory arranged in an all-terrain truck (CRITEX-Lab). This ongoing work focuses on groundwater and the field investigation of residence time distributions, recharge processes (origins), water flow paths and mixing, biogeochemical reactivity and contamination (sources). The rationale behind "operational hydrology" could be applied to the field measurement at high-frequency of many other environmental parameters (temperature, cations, anions, isotopes, micro-organisms) not only for the investigation of groundwaters but also rivers, lakes and oceans. Eliot Chatton, Thierry Labasque, Jérôme de La Bernardie, Nicolas Guihéneuf, Olivier Bour and Luc Aquilina; Field Continuous Measurement of Dissolved Gases with a CF-MIMS: Applications to the Physics and Biogeochemistry of Groundwater Flow; Environmental Science

  12. Spatio-Temporal Diffusion Pattern and Hotspot Detection of Dengue in Chachoengsao Province, Thailand

    Directory of Open Access Journals (Sweden)

    Phaisarn Jeefoo

    2010-12-01

    Full Text Available In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999–2007 was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group, data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall, spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999–2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well.

  13. Long-term spatio-temporal changes in a West African bushmeat trade system.

    Science.gov (United States)

    McNamara, J; Kusimi, J M; Rowcliffe, J M; Cowlishaw, G; Brenyah, A; Milner-Gulland, E J

    2015-10-01

    Landscapes in many developing countries consist of a heterogeneous matrix of mixed agriculture and forest. Many of the generalist species in this matrix are increasingly traded in the bushmeat markets of West and Central Africa. However, to date there has been little quantification of how the spatial configuration of the landscape influences the urban bushmeat trade over time. As anthropogenic landscapes become the face of rural West Africa, understanding the dynamics of these systems has important implications for conservation and landscape management. The bushmeat production of an area is likely to be defined by landscape characteristics such as habitat disturbance, hunting pressure, level of protection, and distance to market. We explored (SSG, tense) the role of these four characteristics in the spatio-temporal dynamics of the commercial bushmeat trade around the city of Kumasi, Ghana, over 27 years (1978 to 2004). We used geographic information system methods to generate maps delineating the spatial characteristics of the landscapes. These data were combined with spatially explicit market data collected in the main fresh bushmeat market in Kumasi to explore the relationship between trade volume (measured in terms of number of carcasses) and landscape characteristics. Over time, rodents, specifically cane rats (Thryonomys swinderianus), became more abundant in the trade relative to ungulates and the catchment area of the bushmeat market expanded. Areas of intermediate disturbance supplied more bushmeat, but protected areas had no effect. Heavily hunted areas showed significant declines in bushmeat supply over time. Our results highlight the role that low intensity, heterogeneous agricultural landscapes can play in providing ecosystem services, such as bushmeat, and therefore the importance of incorporating bushmeat into ecosystem service mapping exercises. Our results also indicate that even where high bushmeat production is possible, current harvest levels may

  14. Quantifying relative fishing impact on fish populations based on spatio-temporal overlap of fishing effort and stock density

    DEFF Research Database (Denmark)

    Vinther, Morten; Eero, Margit

    2013-01-01

    Evaluations of the effects of management measures on fish populations are usually based on the analyses of population dynamics and estimates of fishing mortality from stock assessments. However, this approach may not be applicable in all cases, in particular for data-limited stocks, which may...... GAM analyses to predict local cod densities and combine this with spatio-temporal data of fishing effort based on VMS (Vessel Monitoring System). To quantify local fishing impact on the stock, retention probability of the gears is taken into account. The results indicate a substantial decline...... in the impact of the Danish demersal trawl fleet on cod in the Kattegat in recent years, due to a combination of closed areas, introduction of selective gears and changes in overall effort....

  15. Metallurgy in the Czech Republic: a spatio-temporal view

    Directory of Open Access Journals (Sweden)

    J. Suchacek

    2017-01-01

    Full Text Available The objective of this paper is to introduce the stochastic input-output model of the impact of metallurgy sector on the Czech economy. Contrary to original input-output model, which is of deterministic nature, we reckon with interval estimates of the development of metallurgy sector. They help us to surpass deterministic impediments when analyzing and forecasting the possible developmental tendencies of metallurgy sector in various economies.

  16. Annotating spatio-temporal datasets for meaningful analysis in the Web

    Science.gov (United States)

    Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

    2014-05-01

    More and more environmental datasets that vary in space and time are available in the Web. This comes along with an advantage of using the data for other purposes than originally foreseen, but also with the danger that users may apply inappropriate analysis procedures due to lack of important assumptions made during the data collection process. In order to guide towards a meaningful (statistical) analysis of spatio-temporal datasets available in the Web, we have developed a Higher-Order-Logic formalism that captures some relevant assumptions in our previous work [1]. It allows to proof on meaningful spatial prediction and aggregation in a semi-automated fashion. In this poster presentation, we will present a concept for annotating spatio-temporal datasets available in the Web with concepts defined in our formalism. Therefore, we have defined a subset of the formalism as a Web Ontology Language (OWL) pattern. It allows capturing the distinction between the different spatio-temporal variable types, i.e. point patterns, fields, lattices and trajectories, that in turn determine whether a particular dataset can be interpolated or aggregated in a meaningful way using a certain procedure. The actual annotations that link spatio-temporal datasets with the concepts in the ontology pattern are provided as Linked Data. In order to allow data producers to add the annotations to their datasets, we have implemented a Web portal that uses a triple store at the backend to store the annotations and to make them available in the Linked Data cloud. Furthermore, we have implemented functions in the statistical environment R to retrieve the RDF annotations and, based on these annotations, to support a stronger typing of spatio-temporal datatypes guiding towards a meaningful analysis in R. [1] Stasch, C., Scheider, S., Pebesma, E., Kuhn, W. (2014): "Meaningful spatial prediction and aggregation", Environmental Modelling & Software, 51, 149-165.

  17. Design and implementation of segment oriented spatio-temporal model in urban panoramic maps

    Science.gov (United States)

    Li, Haiting; Fei, Lifan; Peng, Qingshan; Li, Yanhong

    2009-10-01

    Object-oriented spatio-temporal model is directed by human cognition that each object has what/where/when attributes. The precise and flexible structure of such models supports multi-semantics of space and time. This paper reviews current research of spatio-temporal models using object-oriented approach and proposed a new spatio-temporal model based on segmentation in order to resolve the updating problem of some special GIS system by taking advantages of object-oriented spatio-temporal model and adopting category theory. Category theory can be used as a unifying framework for specifying complex systems and it provides rules on how objects may be joined. It characterizes the segments of object through mappings between them. The segment-oriented spatio-temporal model designed for urban panoramic maps is described and implemented. We take points and polylines as objects in this model in the management of panoramic map data. For the randomness of routes which transportation vehicle adopts each time, road objects in this model are split into some segments by crossing points. The segments still remains polyline type, but the splitting makes it easier to update the panoramic data when new photos are captured. This model is capable of eliminating redundant data and accelerating data access when panoramas are unchanged. For evaluation purpose, the data types and operations are designed and implemented in PostgreSQL and the results of experiments come out to prove that this model is efficient and expedient in the application of urban panoramic maps.

  18. Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences.

    Science.gov (United States)

    Gracia, Enrique; López-Quílez, Antonio; Marco, Miriam; Lila, Marisol

    2017-10-18

    'Place' matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk. We conducted a 12-year (2004-2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units, we used 552 census block groups. Cases were geocoded using the family address. Neighborhood-level characteristics analyzed included three indicators of neighborhood disadvantage-neighborhood economic status, neighborhood education level, and levels of policing activity-, immigrant concentration, and residential instability. Bayesian spatio-temporal modelling and disease mapping methods were used to provide area-specific risk estimations. Results from a spatio-temporal autoregressive model showed that neighborhoods with low levels of economic and educational status, with high levels of policing activity, and high immigrant concentration had higher levels of substantiated child maltreatment risk. Disease mapping methods were used to analyze areas of excess risk. Results showed chronic spatial patterns of high child maltreatment risk during the years analyzed, as well as stability over time in areas of low risk. Areas with increased or decreased child maltreatment risk over the years were also observed. A spatio-temporal epidemiological approach to study the geographical patterns, trends over time, and the contextual determinants of child maltreatment risk can provide a useful method to inform policy and action. This method can offer a more accurate description of the problem, and help to inform more

  19. Modeling noninvasive neurostimulation in epilepsy as stochastic interference in brain networks.

    Science.gov (United States)

    Stamoulis, Catherine; Chang, Bernard S

    2013-05-01

    Noninvasive brain stimulation is one of very few potential therapies for medically refractory epilepsy. However, its efficacy remains suboptimal and its therapeutic value has not been consistently assessed. This is in part due to the nonoptimized spatio-temporal application of stimulation protocols for seizure prevention or arrest, and incomplete knowledge of the neurodynamics of seizure evolution. Through simulations, this study investigated electroencephalography (EEG)-guided, stochastic interference with aberrantly coordinated neuronal networks, to prevent seizure onset or interrupt a propagating partial seizure, and prevent it from spreading to large areas of the brain. Brain stimulation was modeled as additive white or band-limited noise, and simulations using real EEGs and data generated from a network of integrate-and-fire neuronal ensembles were used to quantify spatio-temporal noise effects. It was shown that additive stochastic signals (noise) may destructively interfere with network dynamics and decrease or abolish synchronization associated with progressively coupled networks. Furthermore, stimulation parameters, particularly amplitude and spatio-temporal application, may be optimized based on patient-specific neurodynamics estimated directly from noninvasive EEGs.

  20. Dynamic and stochastic multi-project planning

    CERN Document Server

    Melchiors, Philipp

    2015-01-01

    This book deals with dynamic and stochastic methods for multi-project planning. Based on the idea of using queueing networks for the analysis of dynamic-stochastic multi-project environments this book addresses two problems: detailed scheduling of project activities, and integrated order acceptance and capacity planning. In an extensive simulation study, the book thoroughly investigates existing scheduling policies. To obtain optimal and near optimal scheduling policies new models and algorithms are proposed based on the theory of Markov decision processes and Approximate Dynamic programming.

  1. Spatio-temporal variability of aerosols in the tropics relationship with atmospheric and oceanic environments

    Science.gov (United States)

    Zuluaga-Arias, Manuel D.

    2011-12-01

    Earth's radiation budget is directly influenced by aerosols through the absorption of solar radiation and subsequent heating of the atmosphere. Aerosols modulate the hydrological cycle indirectly by modifying cloud properties, precipitation and ocean heat storage. In addition, polluting aerosols impose health risks in local, regional and global scales. In spite of recent advances in the study of aerosols variability, uncertainty in their spatio-temporal distributions still presents a challenge in the understanding of climate variability. For example, aerosol loading varies not only from year to year but also on higher frequency intraseasonal time scales producing strong variability on local and regional scales. An assessment of the impact of aerosol variability requires long period measurements of aerosols at both regional and global scales. The present dissertation compiles a large database of remotely sensed aerosol loading in order to analyze its spatio-temporal variability, and how this load interacts with different variables that characterize the dynamic and thermodynamic states of the environment. Aerosol Index (AI) and Aerosol Optical Depth (AOD) were used as measures of the atmospheric aerosol load. In addition, atmospheric and oceanic satellite observations, and reanalysis datasets is used in the analysis to investigate aerosol-environment interactions. A diagnostic study is conducted to produce global and regional aerosol satellite climatologies, and to analyze and compare the validity of aerosol retrievals. We find similarities and differences between the aerosol distributions over various regions of the globe when comparing the different satellite retrievals. A nonparametric approach is also used to examine the spatial distribution of the recent trends in aerosol concentration. A significant positive trend was found over the Middle East, Arabian Sea and South Asian regions strongly influenced by increases in dust events. Spectral and composite analyses

  2. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

    Science.gov (United States)

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

    Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

  3. Effects of wide step walking on swing phase hip muscle forces and spatio-temporal gait parameters.

    Science.gov (United States)

    Bajelan, Soheil; Nagano, Hanatsu; Sparrow, Tony; Begg, Rezaul K

    2017-07-01

    Human walking can be viewed essentially as a continuum of anterior balance loss followed by a step that re-stabilizes balance. To secure balance an extended base of support can be assistive but healthy young adults tend to walk with relatively narrower steps compared to vulnerable populations (e.g. older adults and patients). It was, therefore, hypothesized that wide step walking may enhance dynamic balance at the cost of disturbed optimum coupling of muscle functions, leading to additional muscle work and associated reduction of gait economy. Young healthy adults may select relatively narrow steps for a more efficient gait. The current study focused on the effects of wide step walking on hip abductor and adductor muscles and spatio-temporal gait parameters. To this end, lower body kinematic data and ground reaction forces were obtained using an Optotrak motion capture system and AMTI force plates, respectively, while AnyBody software was employed for muscle force simulation. A single step of four healthy young male adults was captured during preferred walking and wide step walking. Based on preferred walking data, two parallel lines were drawn on the walkway to indicate 50% larger step width and participants targeted the lines with their heels as they walked. In addition to step width that defined walking conditions, other spatio-temporal gait parameters including step length, double support time and single support time were obtained. Average hip muscle forces during swing were modeled. Results showed that in wide step walking step length increased, Gluteus Minimus muscles were more active while Gracilis and Adductor Longus revealed considerably reduced forces. In conclusion, greater use of abductors and loss of adductor forces were found in wide step walking. Further validation is needed in future studies involving older adults and other pathological populations.

  4. Identifying Spatio-Temporal Landslide Hotspots on North Island, New Zealand, by Analyzing Historical and Recent Aerial Photography

    Directory of Open Access Journals (Sweden)

    Daniel Hölbling

    2016-11-01

    Full Text Available Accurate mapping of landslides and the reliable identification of areas most affected by landslides are essential for advancing the understanding of landslide erosion processes. Remote sensing data provides a valuable source of information on the spatial distribution and location of landslides. In this paper we present an approach for identifying landslide-prone “hotspots” and their spatio-temporal variability by analyzing historical and recent aerial photography from five different dates, ranging from 1944 to 2011, for a study site near the town of Pahiatua, southeastern North Island, New Zealand. Landslide hotspots are identified from the distribution of semi-automatically detected landslides using object-based image analysis (OBIA, and compared to hotspots derived from manually mapped landslides. When comparing the overlapping areas of the semi-automatically and manually mapped landslides the accuracy values of the OBIA results range between 46% and 61% for the producer’s accuracy and between 44% and 77% for the user’s accuracy. When evaluating whether a manually digitized landslide polygon is only intersected to some extent by any semi-automatically mapped landslide, we observe that for the natural-color images the landslide detection rate is 83% for 2011 and 93% for 2005; for the panchromatic images the values are slightly lower (67% for 1997, 74% for 1979, and 72% for 1944. A comparison of the derived landslide hotspot maps shows that the distribution of the manually identified landslides and those mapped with OBIA is very similar for all periods; though the results also reveal that mapping landslide tails generally requires visual interpretation. Information on the spatio-temporal evolution of landslide hotspots can be useful for the development of location-specific, beneficial intervention measures and for assessing landscape dynamics.

  5. Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran.

    Science.gov (United States)

    Eybpoosh, Sana; Bahrampour, Abbas; Karamouzian, Mohammad; Azadmanesh, Kayhan; Jahanbakhsh, Fatemeh; Mostafavi, Ehsan; Zolala, Farzaneh; Haghdoost, Ali Akbar

    2016-01-01

    HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug

  6. Automated Flight Routing Using Stochastic Dynamic Programming

    Science.gov (United States)

    Ng, Hok K.; Morando, Alex; Grabbe, Shon

    2010-01-01

    Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

  7. Dynamics of a Stochastic Intraguild Predation Model

    Directory of Open Access Journals (Sweden)

    Zejing Xing

    2016-04-01

    Full Text Available Intraguild predation (IGP is a widespread ecological phenomenon which occurs when one predator species attacks another predator species with which it competes for a shared prey species. The objective of this paper is to study the dynamical properties of a stochastic intraguild predation model. We analyze stochastic persistence and extinction of the stochastic IGP model containing five cases and establish the sufficient criteria for global asymptotic stability of the positive solutions. This study shows that it is possible for the coexistence of three species under the influence of environmental noise, and that the noise may have a positive effect for IGP species. A stationary distribution of the stochastic IGP model is established and it has the ergodic property, suggesting that the time average of population size with the development of time is equal to the stationary distribution in space. Finally, we show that our results may be extended to two well-known biological systems: food chains and exploitative competition.

  8. Spatio-temporal precipitation climatology over complex terrain using a censored additive regression model.

    Science.gov (United States)

    Stauffer, Reto; Mayr, Georg J; Messner, Jakob W; Umlauf, Nikolaus; Zeileis, Achim

    2017-06-15

    Flexible spatio-temporal models are widely used to create reliable and accurate estimates for precipitation climatologies. Most models are based on square root transformed monthly or annual means, where a normal distribution seems to be appropriate. This assumption becomes invalid on a daily time scale as the observations involve large fractions of zero observations and are limited to non-negative values. We develop a novel spatio-temporal model to estimate the full climatological distribution of precipitation on a daily time scale over complex terrain using a left-censored normal distribution. The results demonstrate that the new method is able to account for the non-normal distribution and the large fraction of zero observations. The new climatology provides the full climatological distribution on a very high spatial and temporal resolution, and is competitive with, or even outperforms existing methods, even for arbitrary locations.

  9. Control of spatio-temporal on-off intermittency in random driving diffusively coupled map lattices

    International Nuclear Information System (INIS)

    Ziabakhsh Deilami, M.; Rahmani Cherati, Z.; Jahed Motlagh, M.R.

    2009-01-01

    In this paper, we propose feedback methods for controlling spatio-temporal on-off intermittency which is an aperiodic switching between an 'off' state and an 'on' state. Diffusively coupled map lattice with spatially non-uniform random driving is used for showing spatio-temporal on-off intermittency. For this purpose, we apply three different feedbacks. First, we use a linear feedback which is a simple method but has a long transient time. To overcome this problem, two nonlinear feedbacks based on prediction strategy are proposed. An important advantage of the methods is that the feedback signal is vanished when control is realized. Simulation results show that all methods have suppressed the chaotic behavior.

  10. Towards human behavior recognition based on spatio temporal features and support vector machines

    Science.gov (United States)

    Ghabri, Sawsen; Ouarda, Wael; Alimi, Adel M.

    2017-03-01

    Security and surveillance are vital issues in today's world. The recent acts of terrorism have highlighted the urgent need for efficient surveillance. There is indeed a need for an automated system for video surveillance which can detect identity and activity of person. In this article, we propose a new paradigm to recognize an aggressive human behavior such as boxing action. Our proposed system for human activity detection includes the use of a fusion between Spatio Temporal Interest Point (STIP) and Histogram of Oriented Gradient (HoG) features. The novel feature called Spatio Temporal Histogram Oriented Gradient (STHOG). To evaluate the robustness of our proposed paradigm with a local application of HoG technique on STIP points, we made experiments on KTH human action dataset based on Multi Class Support Vector Machines classification. The proposed scheme outperforms basic descriptors like HoG and STIP to achieve 82.26% us an accuracy value of classification rate.

  11. A test for stationarity of spatio-temporal random fields on planar and spherical domains

    KAUST Repository

    Jun, Mikyoung

    2012-01-01

    A formal test for weak stationarity of spatial and spatio-temporal random fields is proposed. We consider the cases where the spatial domain is planar or spherical, and we do not require distributional assumptions for the random fields. The method can be applied to univariate or to multivariate random fields. Our test is based on the asymptotic normality of certain statistics that are functions of estimators of covariances at certain spatial and temporal lags under weak stationarity. Simulation results for spatial as well as spatio-temporal cases on the two types of spatial domains are reported. We describe the results of testing the stationarity of Pacific wind data, and of testing the axial symmetry of climate model errors for surface temperature using the NOAA GFDL model outputs and the observations from the Climate Research Unit in East Anglia and the Hadley Centre.

  12. Effects of climate change adaptation scenarios on perceived spatio-temporal characteristics of drought events

    Science.gov (United States)

    Vidal, J.-P.; Martin, E.; Kitova, N.; Najac, J.; Soubeyroux, J.-M.

    2012-04-01

    Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, like mean duration, mean affected area and total magnitude. This study addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) Are downscaled climate projections able to reproduce spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century under different emissions scenarios? (3) How would perceived drought characteristics evolve under theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-year multilevel and multiscale drought reanalysis over France (Vidal et al., 2010). Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index (SPI) and the Standardized Soil Wetness Index (SSWI), respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well reproduced by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century under all considered emissions scenarios, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals. The two scenarios differ by the way the transient adaptation is performed for a given date in the future, with reference to the normals over either the previous 30-year window ("retrospective

  13. A model for optimizing file access patterns using spatio-temporal parallelism

    Energy Technology Data Exchange (ETDEWEB)

    Boonthanome, Nouanesengsy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Patchett, John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Geveci, Berk [Kitware Inc., Clifton Park, NY (United States); Ahrens, James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bauer, Andy [Kitware Inc., Clifton Park, NY (United States); Chaudhary, Aashish [Kitware Inc., Clifton Park, NY (United States); Miller, Ross G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shipman, Galen M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2013-01-01

    For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible file access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.

  14. Quantification of annual wildfire risk; A spatio-temporal point process approach.

    Directory of Open Access Journals (Sweden)

    Paula Pereira

    2013-10-01

    Full Text Available Policy responses for local and global firemanagement depend heavily on the proper understanding of the fire extent as well as its spatio-temporal variation across any given study area. Annual fire risk maps are important tools for such policy responses, supporting strategic decisions such as location-allocation of equipment and human resources. Here, we define risk of fire in the narrow sense as the probability of its occurrence without addressing the loss component. In this paper, we study the spatio-temporal point patterns of wildfires and model them by a log Gaussian Cox processes. Themean of predictive distribution of randomintensity function is used in the narrow sense, as the annual fire risk map for next year.

  15. Spatio-Temporal Image Correlation Spectroscopy Measurements of Flow Demonstrated in Microfluidic Channels

    Science.gov (United States)

    Rossow, Molly; Mantulin, William W.; Gratton, Enrico

    2009-01-01

    Accurate blood flow measurements during surgery can improve the operations chance of success. We developed Near-infrared Spatio-Temporal Image Spectroscopy (NIR-STICS), which has the potential to make blood flow measurements that are difficult to accomplish with existing methods. Specifically, we propose the technique and we show feasibility on phantom measurements. NIR-STICS has the potential of measuring the fluid velocity in small blood vessels (less than 1mm in diameter) and of creating a map of blood flow rates over an area of approximately 1cm2. NIR-STICS employs near-infrared spectroscopy to probe inside blood vessel walls and spatio-temporal image correlation spectroscopy to directly—without the use of a model—extract fluid velocity from the fluctuations within an image. Here we present computer simulations and experiments on a phantom system that demonstrate the effectiveness of NIR-STICS. PMID:19405744

  16. Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

    Science.gov (United States)

    Manga, Edna; Awang, Norhashidah

    2016-06-01

    This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.

  17. Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models

    DEFF Research Database (Denmark)

    Yang, Bin; Guo, Chenjuan; Jensen, Christian S.

    2013-01-01

    of such time series offers insight into the underlying system and enables prediction of system behavior. While the techniques presented in the paper apply more generally, we consider the case of transportation systems and aim to predict travel cost from GPS tracking data from probe vehicles. Specifically, each...... road segment has an associated travel-cost time series, which is derived from GPS data. We use spatio-temporal hidden Markov models (STHMM) to model correlations among different traffic time series. We provide algorithms that are able to learn the parameters of an STHMM while contending...... with the sparsity, spatio-temporal correlation, and heterogeneity of the time series. Using the resulting STHMM, near future travel costs in the transportation network, e.g., travel time or greenhouse gas emissions, can be inferred, enabling a variety of routing services, e.g., eco-routing. Empirical studies...

  18. DSTiPE Algorithm for Fuzzy Spatio-Temporal Risk Calculation in Wireless Environments

    Energy Technology Data Exchange (ETDEWEB)

    Kurt Derr; Milos Manic

    2008-09-01

    Time and location data play a very significant role in a variety of factory automation scenarios, such as automated vehicles and robots, their navigation, tracking, and monitoring, to services of optimization and security. In addition, pervasive wireless capabilities combined with time and location information are enabling new applications in areas such as transportation systems, health care, elder care, military, emergency response, critical infrastructure, and law enforcement. A person/object in proximity to certain areas for specific durations of time may pose a risk hazard either to themselves, others, or the environment. This paper presents a novel fuzzy based spatio-temporal risk calculation DSTiPE method that an object with wireless communications presents to the environment. The presented Matlab based application for fuzzy spatio-temporal risk cluster extraction is verified on a diagonal vehicle movement example.

  19. How innate is locomotion in precocial animals? A study on the early development of spatio-temporal gait variables and gait symmetry in piglets.

    Science.gov (United States)

    Vanden Hole, Charlotte; Goyens, Jana; Prims, Sara; Fransen, Erik; Ayuso Hernando, Miriam; Van Cruchten, Steven; Aerts, Peter; Van Ginneken, Chris

    2017-08-01

    Locomotion is one of the most important ecological functions in animals. Precocial animals, such as pigs, are capable of independent locomotion shortly after birth. This raises the question whether coordinated movement patterns and the underlying muscular control in these animals is fully innate or whether there still exists a rapid maturation. We addressed this question by studying gait development in neonatal pigs through the analysis of spatio-temporal gait characteristics during locomotion at self-selected speed. To this end, we made video recordings of piglets walking along a corridor at several time points (from 0 h to 96 h). After digitization of the footfalls, we analysed self-selected speed and spatio-temporal characteristics (e.g. stride and step lengths, stride frequency and duty factor) to study dynamic similarity, intralimb coordination and interlimb coordination. To assess the variability of the gait pattern, left-right asymmetry was studied. To distinguish neuromotor maturation from effects caused by growth, both absolute and normalized data (according to the dynamic similarity concept) were included in the analysis. All normalized spatio-temporal variables reached stable values within 4 h of birth, with most of them showing little change after the age of 2 h. Most asymmetry indices showed stable values, hovering around 10%, within 8 h of birth. These results indicate that coordinated movement patterns are not entirely innate, but that a rapid neuromotor maturation, potentially also the result of the rearrangement or recombination of existing motor modules, takes place in these precocial animals. © 2017. Published by The Company of Biologists Ltd.

  20. The spatio-temporal structure of electrostatic turbulence in the WEGA stellarator

    International Nuclear Information System (INIS)

    Marsen, Stefan

    2008-03-01

    The main object of this work is to provide a detailed characterisation of electrostatic turbulence in WEGA and to identify the underlying instability mechanism driving turbulence. The spatio-temporal structure of turbulence is studied using multiple Langmuir probes providing a sufficiently high spatial and temporal resolution. Turbulence in WEGA is dominated by drift wave dynamics. The phase shift between density and potential fluctuations is close to zero, fluctuations are mainly driven by the density gradient, and the phase velocity of turbulent structures points in the direction of the electron diamagnetic drift. The structure of turbulence is studied mainly in the plasma edge region inside the last closed flux surface. WEGA can be operated in two regimes differing in the magnetic field strength by almost one order of magnitude (57 mT and 500 mT, respectively). At 57 mT large structures with a poloidal extent comparable to the machine dimensions are observed, whereas at 500 mT turbulent structures are much smaller. The poloidal structure size scales nearly linearly with the inverse magnetic field strength. This scaling may be argued to be related to the drift wave dispersion scale, ρ s =√(m i k B T e )/(qB). However, the structure size remains unchanged when the ion mass is changed by using different discharge gases. Inside the last closed flux surface the poloidal E x B drift in WEGA is negligible. The three-dimensional structure is studied in detail using probes which are toroidally separated but aligned along connecting magnetic field lines. A small but finite parallel wavenumber is found. The ratio between the average parallel and perpendicular wavenumber is in the order of anti κ parallel / anti κ θ ∼ 10 -2 . The parallel phase velocity of turbulent structures is in-between the ion sound velocity and the Alfven velocity. In the parallel dynamics a fundamental difference between the two operational regimes at different magnetic field strength is

  1. Stochastic integer programming by dynamic programming

    NARCIS (Netherlands)

    Lageweg, B.J.; Lenstra, J.K.; Rinnooy Kan, A.H.G.; Stougie, L.; Ermoliev, Yu.; Wets, R.J.B.

    1988-01-01

    Stochastic integer programming is a suitable tool for modeling hierarchical decision situations with combinatorial features. In continuation of our work on the design and analysis of heuristics for such problems, we now try to find optimal solutions. Dynamic programming techniques can be used to

  2. A hierarchical Bayesian spatio-temporal model for extreme precipitation events

    KAUST Repository

    Ghosh, Souparno; Mallick, Bani K.

    2011-01-01

    We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..

  3. Role of Temporal Diversity in Inferring Social Ties Based on Spatio-Temporal Data

    OpenAIRE

    Desai, Deshana; Nisar, Harsh; Bhardawaj, Rishab

    2016-01-01

    The last two decades have seen a tremendous surge in research on social networks and their implications. The studies includes inferring social relationships, which in turn have been used for target advertising, recommendations, search customization etc. However, the offline experiences of human, the conversations with people and face-to-face interactions that govern our lives interactions have received lesser attention. We introduce DAIICT Spatio-Temporal Network (DSSN), a spatiotemporal data...

  4. Emergence of Complex Spatio-Temporal Behavior in Nonlinear Field Theories

    International Nuclear Information System (INIS)

    Gleiser, Marcelo; Howell, Rafael C.

    2006-01-01

    We investigate the emergence of time-dependent nonperturbative configurations during the evolution of nonlinear scalar field models with symmetric and asymmetric double-well potentials. Complex spatio-temporal behavior emerges as the system seeks to establish equipartition after a fast quench. We show that fast quenches may dramatically modify the decay rate of metastable states in first order phase transitions. We discuss possible applications in condensed matter systems and early universe cosmology

  5. A hierarchical Bayesian spatio-temporal model for extreme precipitation events

    KAUST Repository

    Ghosh, Souparno

    2011-03-01

    We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..

  6. Novel evaluation metrics for sparse spatio-temporal point process hotspot predictions - a crime case study

    OpenAIRE

    Adepeju, M.; Rosser, G.; Cheng, T.

    2016-01-01

    Many physical and sociological processes are represented as discrete events in time and space. These spatio-temporal point processes are often sparse, meaning that they cannot be aggregated and treated with conventional regression models. Models based on the point process framework may be employed instead for prediction purposes. Evaluating the predictive performance of these models poses a unique challenge, as the same sparseness prevents the use of popular measures such as the root mean squ...

  7. [Epidemiologic and spatio-temporal characteristics of hepatitis E in China, 2004-2014].

    Science.gov (United States)

    Liu, Z Q; Zuo, J L; Yan, Q; Fang, Q W; Zhang, T J

    2017-10-10

    Objective: To describe and analyze the epidemiologic and spatio-temporal characteristics of hepatitis E in China from 2004 to 2014. Methods: Data on the incidence of hepatitis E in 31 provinces (municipality and autonomous region) from 2004 to 2014, were collected. Empirical Mode Decomposition (EMD) was applied to decompose the time-series data to accurately describe the trend of hepatitis E incidence. Mathematic model was used to estimate the annual change of incidence in each age group and the whole province. Software ArcGIS 10.1 and SaTScan 9.01 were used to analyze the spatio-temporal clusters. Results: During 2004-2014, a total of 245 414 hepatitis E cases were reported in China. The overall incidence showed a slight increase ( OR =1.05, 95 %CI : 1.03-1.10). Incidence rates on hepatitis E were discovered different across the provinces, with significant increase appearing in the southern, central and northwestern areas. The highest increase was seen in the elderly, especially in the 65-69 and 70-74 year-olds. Results from the Local spatial autocorrelation analysis showed that the "high-high cluster" was moving from the north to the south and the "low-low cluster" disappeared as time went by. Data from Spatio-temporal scanning showed that there were five spatio-temporal clustering areas across the country. Conclusion: The overall incidence of hepatitis E was on the rise from 2004 to 2014, in China, but with differences seen across the areas and age groups.

  8. Global asymptotic behavior in a Lotka–Volterra competition system with spatio-temporal delays

    International Nuclear Information System (INIS)

    Zhang, Jia-Fang; Chen, Heshan

    2014-01-01

    This paper is concerned with a Lotka–Volterra competition system with spatio-temporal delays. By using the linearization method, we show the local asymptotic behavior of the nonnegative steady-state solutions. Especially, the global asymptotic stability of the positive steady-state solution is investigated by the method of upper and lower solutions. The result of global asymptotic stability implies that the system has no nonconstant positive steady-state solution

  9. UNDERSTANDING THE SPATIO-TEMPORAL PATTERN OF FIRE DISTURBANCE IN THE EASTERN MONGOLIA USING MODIS PRODUCT

    OpenAIRE

    Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

    2018-01-01

    Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire dis...

  10. Pattern selection and spatio-temporal transition to chaos in Ginzburg-Landau equation

    Energy Technology Data Exchange (ETDEWEB)

    Nozaki, K; Bekki, N

    1983-07-01

    It is shown that a modulationally unstable pattern is selected and propagates into an initially unstable motionless state in the 1-D generalized Ginzburg-Landau equation. A further spatio-temporal transition occurs with a sharp interface from the selected unstable pattern to a stabilized pattern or a chaotic state. The distinct transition makes a coherent structure to coexist with a chaotic state. 12 refs., 4 figs.

  11. Spatio-temporal regulation of ADAR editing during development in porcine neural tissues

    DEFF Research Database (Denmark)

    Venø, Morten Trillingsgaard; Bramsen, Jesper Bertram; Bendixen, Christian

    2012-01-01

    Editing by ADAR enzymes is essential for mammalian life. Still, knowledge of the spatio-temporal editing patterns in mammals is limited. By use of 454 amplicon sequencing we examined the editing status of 12 regionally extracted mRNAs from porcine developing brain encompassing a total of 64...... putative ADAR editing sites. In total 24 brain tissues, dissected from up to five regions from embryonic gestation day 23, 42, 60, 80, 100 and 115, were examined for editing....

  12. Discovery of spatio-temporal patterns from location-based social networks

    Science.gov (United States)

    Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

    2016-03-01

    Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

  13. Comparison of feature extraction methods within a spatio-temporal land cover change detection framework

    CSIR Research Space (South Africa)

    Kleynhans, W

    2011-07-01

    Full Text Available OF FEATURE EXTRACTION METHODS WITHIN A SPATIO-TEMPORAL LAND COVER CHANGE DETECTION FRAMEWORK ??W. Kleynhans,, ??B.P. Salmon, ?J.C. Olivier, ?K.J. Wessels, ?F. van den Bergh ? Electrical, Electronic and Computer Engi- neering University of Pretoria, South... Bergh, and K. Steenkamp, ?Improving land cover class separation using an extended Kalman filter on MODIS NDVI time series data,? IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 2, pp. 381?385, Apr. 2010. ...

  14. Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

    KAUST Repository

    Xie, Le

    2014-01-01

    We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

  15. On the expected value and variance for an estimator of the spatio-temporal product density function

    DEFF Research Database (Denmark)

    Rodríguez-Corté, Francisco J.; Ghorbani, Mohammad; Mateu, Jorge

    Second-order characteristics are used to analyse the spatio-temporal structure of the underlying point process, and thus these methods provide a natural starting point for the analysis of spatio-temporal point process data. We restrict our attention to the spatio-temporal product density function......, and develop a non-parametric edge-corrected kernel estimate of the product density under the second-order intensity-reweighted stationary hypothesis. The expectation and variance of the estimator are obtained, and closed form expressions derived under the Poisson case. A detailed simulation study is presented...... to compare our close expression for the variance with estimated ones for Poisson cases. The simulation experiments show that the theoretical form for the variance gives acceptable values, which can be used in practice. Finally, we apply the resulting estimator to data on the spatio-temporal distribution...

  16. Sparse learning of stochastic dynamical equations

    Science.gov (United States)

    Boninsegna, Lorenzo; Nüske, Feliks; Clementi, Cecilia

    2018-06-01

    With the rapid increase of available data for complex systems, there is great interest in the extraction of physically relevant information from massive datasets. Recently, a framework called Sparse Identification of Nonlinear Dynamics (SINDy) has been introduced to identify the governing equations of dynamical systems from simulation data. In this study, we extend SINDy to stochastic dynamical systems which are frequently used to model biophysical processes. We prove the asymptotic correctness of stochastic SINDy in the infinite data limit, both in the original and projected variables. We discuss algorithms to solve the sparse regression problem arising from the practical implementation of SINDy and show that cross validation is an essential tool to determine the right level of sparsity. We demonstrate the proposed methodology on two test systems, namely, the diffusion in a one-dimensional potential and the projected dynamics of a two-dimensional diffusion process.

  17. Optimizing Cruising Routes for Taxi Drivers Using a Spatio-Temporal Trajectory Model

    Directory of Open Access Journals (Sweden)

    Liang Wu

    2017-11-01

    Full Text Available Much of the taxi route-planning literature has focused on driver strategies for finding passengers and determining the hot spot pick-up locations using historical global positioning system (GPS trajectories of taxis based on driver experience, distance from the passenger drop-off location to the next passenger pick-up location and the waiting times at recommended locations for the next passenger. The present work, however, considers the average taxi travel speed mined from historical taxi GPS trajectory data and the allocation of cruising routes to more than one taxi driver in a small-scale region to neighboring pick-up locations. A spatio-temporal trajectory model with load balancing allocations is presented to not only explore pick-up/drop-off information but also provide taxi drivers with cruising routes to the recommended pick-up locations. In simulation experiments, our study shows that taxi drivers using cruising routes recommended by our spatio-temporal trajectory model can significantly reduce the average waiting time and travel less distance to quickly find their next passengers, and the load balancing strategy significantly alleviates road loads. These objective measures can help us better understand spatio-temporal traffic patterns and guide taxi navigation.

  18. Spatio-temporal modeling of 210Pb transportation in lake environments

    International Nuclear Information System (INIS)

    Kuelahci, Fatih; Sen, Zekai

    2009-01-01

    Radioactive particle movement analysis in any environment gives valuable information about the effects of the concerned environment on the particle and the transportation phenomenon. In this study, the spatio-temporal point cumulative semivariogram (STPCSV) approach is proposed for the analysis of the spatio-temporal changes in the radioactive particle movement within a surface water body. This methodology is applied to the 210 Pb radioactive isotope measurements at 44 stations, which are determined beforehand in order to characterize the Keban Dam water environment on the Euphrates River in the southeastern part of Turkey. It considers the contributions coming from all the stations and provides information about the spatio-temporal behavior of 210 Pb in the water environment. After having identified the radii of influences at each station it is possible to draw maps for further interpretations. In order to see holistically the spatial changes of the radioisotope after 1st, 3rd and 5th hours, the radius of influence maps are prepared and interpreted accordingly.

  19. Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

    Science.gov (United States)

    Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

    2010-08-01

    Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

  20. Analysis and modelling of spatio-temporal properties of daily rainfall over the Danube basin

    Science.gov (United States)

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

    Central and Eastern Europe are prone to severe floods due to heavy rainfall that cause societal and economic damages, ranging from agriculture to water resources, from the insurance/reinsurance sector to the energy industry. To improve the flood risk analysis, a better characterisation and modelling of the rainfall patterns over this area, which involves the Danube river watershed, is strategically important. In this study, we analyse the spatio-temporal properties of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe through different lagged and non-lagged indices of associations that quantify both the overall dependence and extreme dependence of pairwise observations. We also show that these measures are linked to each other and can be written in a unique and coherent notation within the copula framework. Moreover, the lagged version of these measures allows exploring some important spatio-temporal properties of the rainfall fields. The exploratory analysis is complemented by the preliminary results of a spatio-temporal rainfall simulation performed via a compound model based upon the Generalized Additive Models for Location, Scale and Shape (GAMLSS) and meta-elliptical multivariate distributions.

  1. The Review of Visual Analysis Methods of Multi-modal Spatio-temporal Big Data

    Directory of Open Access Journals (Sweden)

    ZHU Qing

    2017-10-01

    Full Text Available The visual analysis of spatio-temporal big data is not only the state-of-art research direction of both big data analysis and data visualization, but also the core module of pan-spatial information system. This paper reviews existing visual analysis methods at three levels:descriptive visual analysis, explanatory visual analysis and exploratory visual analysis, focusing on spatio-temporal big data's characteristics of multi-source, multi-granularity, multi-modal and complex association.The technical difficulties and development tendencies of multi-modal feature selection, innovative human-computer interaction analysis and exploratory visual reasoning in the visual analysis of spatio-temporal big data were discussed. Research shows that the study of descriptive visual analysis for data visualizationis is relatively mature.The explanatory visual analysis has become the focus of the big data analysis, which is mainly based on interactive data mining in a visual environment to diagnose implicit reason of problem. And the exploratory visual analysis method needs a major break-through.

  2. SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING

    OpenAIRE

    N. Mou; N. Mou; J. Li; L. Zhang; W. Liu; Y. Xu

    2017-01-01

    Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according t...

  3. Structured spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... dataset consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  4. A Stochastic Model for Malaria Transmission Dynamics

    Directory of Open Access Journals (Sweden)

    Rachel Waema Mbogo

    2018-01-01

    Full Text Available Malaria is one of the three most dangerous infectious diseases worldwide (along with HIV/AIDS and tuberculosis. In this paper we compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in malaria transmission dynamics. Relationships between the basic reproduction number for malaria transmission dynamics between humans and mosquitoes and the extinction thresholds of corresponding continuous-time Markov chain models are derived under certain assumptions. The stochastic model is formulated using the continuous-time discrete state Galton-Watson branching process (CTDSGWbp. The reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or die out. Thresholds for disease extinction from stochastic models contribute crucial knowledge on disease control and elimination and mitigation of infectious diseases. Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models. In particular, we find that malaria outbreak is more likely if the disease is introduced by infected mosquitoes as opposed to infected humans. These insights demonstrate the importance of a policy or intervention focusing on controlling the infected mosquito population if the control of malaria is to be realized.

  5. Spatio-temporal Background Models for Outdoor Surveillance

    Directory of Open Access Journals (Sweden)

    Pless Robert

    2005-01-01

    Full Text Available Video surveillance in outdoor areas is hampered by consistent background motion which defeats systems that use motion to identify intruders. While algorithms exist for masking out regions with motion, a better approach is to develop a statistical model of the typical dynamic video appearance. This allows the detection of potential intruders even in front of trees and grass waving in the wind, waves across a lake, or cars moving past. In this paper we present a general framework for the identification of anomalies in video, and a comparison of statistical models that characterize the local video dynamics at each pixel neighborhood. A real-time implementation of these algorithms runs on an 800 MHz laptop, and we present qualitative results in many application domains.

  6. Experimental devices for the spatio-temporal characterization of femtosecond high-power laser chains

    International Nuclear Information System (INIS)

    Gallet, Valentin

    2014-01-01

    One of the advantages of high-power femtosecond lasers (TW-PW) is to obtain, at the focus of a focusing optic, very high intensities up to 10 22 W.cm -2 (i.e. an electric field of 2.7 PV.m -1 . Therefore, these lasers chains necessarily deliver beams with large diameter (up to 40 cm) and very short pulses (of the order of tens of femto-seconds). As a consequence, the spatial and temporal properties of the pulse are generally not independent. Such dependence, called spatial-temporal coupling has the effect of increasing the pulse duration and the size of the focal spot, which can lead to a significant reduction of the maximum intensity at the focus. Metrology devices commonly used on these high-power femtosecond lasers allow retrieving the spatial and temporal profiles of the pulse only in an independent manner. The aim of this thesis was to develop techniques for measuring spatio-temporal couplings in order to quantify their effect and correct them in order to obtain the maximum intensity at focus. First of all, we adapted an existing technique of spatio-temporal characterization to the measurement of TW lasers. To avoid the issues induced at the focus, such as those related to jittering, measurements were performed on the collimated beam. By adding a reference source to the original device, we managed to take into account the measurement artifacts due to thermal and mechanical variations affecting the interferometer. With this improvement, it was possible to reconstruct the complete spatio-temporal profile of the beam, particularly its wavefront. However, the limitations imposed by this technique led to the development of a new measurement device. Based on a cross-correlation, this technique consists of making the laser beam to interfere with a part of itself, small enough not to be spatio-temporally distorted. We have also implemented a variant of this device for a single-shot measurement along one transverse dimension of the pulse. Using these techniques, we

  7. Stochastic control theory dynamic programming principle

    CERN Document Server

    Nisio, Makiko

    2015-01-01

    This book offers a systematic introduction to the optimal stochastic control theory via the dynamic programming principle, which is a powerful tool to analyze control problems. First we consider completely observable control problems with finite horizons. Using a time discretization we construct a nonlinear semigroup related to the dynamic programming principle (DPP), whose generator provides the Hamilton–Jacobi–Bellman (HJB) equation, and we characterize the value function via the nonlinear semigroup, besides the viscosity solution theory. When we control not only the dynamics of a system but also the terminal time of its evolution, control-stopping problems arise. This problem is treated in the same frameworks, via the nonlinear semigroup. Its results are applicable to the American option price problem. Zero-sum two-player time-homogeneous stochastic differential games and viscosity solutions of the Isaacs equations arising from such games are studied via a nonlinear semigroup related to DPP (the min-ma...

  8. Dynamic optimization deterministic and stochastic models

    CERN Document Server

    Hinderer, Karl; Stieglitz, Michael

    2016-01-01

    This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

  9. Globe Browsing: Contextualized Spatio-Temporal Planetary Surface Visualization.

    Science.gov (United States)

    Bladin, Karl; Axelsson, Emil; Broberg, Erik; Emmart, Carter; Ljung, Patric; Bock, Alexander; Ynnerman, Anders

    2017-08-29

    Results of planetary mapping are often shared openly for use in scientific research and mission planning. In its raw format, however, the data is not accessible to non-experts due to the difficulty in grasping the context and the intricate acquisition process. We present work on tailoring and integration of multiple data processing and visualization methods to interactively contextualize geospatial surface data of celestial bodies for use in science communication. As our approach handles dynamic data sources, streamed from online repositories, we are significantly shortening the time between discovery and dissemination of data and results. We describe the image acquisition pipeline, the pre-processing steps to derive a 2.5D terrain, and a chunked level-of-detail, out-of-core rendering approach to enable interactive exploration of global maps and high-resolution digital terrain models. The results are demonstrated for three different celestial bodies. The first case addresses high-resolution map data on the surface of Mars. A second case is showing dynamic processes, such as concurrent weather conditions on Earth that require temporal datasets. As a final example we use data from the New Horizons spacecraft which acquired images during a single flyby of Pluto. We visualize the acquisition process as well as the resulting surface data. Our work has been implemented in the OpenSpace software [8], which enables interactive presentations in a range of environments such as immersive dome theaters, interactive touch tables, and virtual reality headsets.

  10. The two-regime method for optimizing stochastic reaction-diffusion simulations

    KAUST Repository

    Flegg, M. B.; Chapman, S. J.; Erban, R.

    2011-01-01

    Spatial organization and noise play an important role in molecular systems biology. In recent years, a number of software packages have been developed for stochastic spatio-temporal simulation, ranging from detailed molecular-based approaches

  11. Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

    Science.gov (United States)

    Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

    2014-08-01

    As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good

  12. Harmonics rejection in pixelated interferograms using spatio-temporal demodulation.

    Science.gov (United States)

    Padilla, J M; Servin, M; Estrada, J C

    2011-09-26

    Pixelated phase-mask interferograms have become an industry standard in spatial phase-shifting interferometry. These pixelated interferograms allow full wavefront encoding using a single interferogram. This allows the study of fast dynamic events in hostile mechanical environments. Recently an error-free demodulation method for ideal pixelated interferograms was proposed. However, non-ideal conditions in interferometry may arise due to non-linear response of the CCD camera, multiple light paths in the interferometer, etc. These conditions generate non-sinusoidal fringes containing harmonics which degrade the phase estimation. Here we show that two-dimensional Fourier demodulation of pixelated interferograms rejects most harmonics except the complex ones at {-3(rd), +5(th), -7(th), +9(th), -11(th),…}. We propose temporal phase-shifting to remove these remaining harmonics. In particular, a 2-step phase-shifting algorithm is used to eliminate the -3(rd) and +5(th) complex harmonics, while a 3-step one is used to remove the -3(rd), +5harmonics. © 2011 Optical Society of America

  13. Computational Methods in Stochastic Dynamics Volume 2

    CERN Document Server

    Stefanou, George; Papadopoulos, Vissarion

    2013-01-01

    The considerable influence of inherent uncertainties on structural behavior has led the engineering community to recognize the importance of a stochastic approach to structural problems. Issues related to uncertainty quantification and its influence on the reliability of the computational models are continuously gaining in significance. In particular, the problems of dynamic response analysis and reliability assessment of structures with uncertain system and excitation parameters have been the subject of continuous research over the last two decades as a result of the increasing availability of powerful computing resources and technology.   This book is a follow up of a previous book with the same subject (ISBN 978-90-481-9986-0) and focuses on advanced computational methods and software tools which can highly assist in tackling complex problems in stochastic dynamic/seismic analysis and design of structures. The selected chapters are authored by some of the most active scholars in their respective areas and...

  14. Stochastic beam dynamics in storage rings

    International Nuclear Information System (INIS)

    Pauluhn, A.

    1993-12-01

    In this thesis several approaches to stochastic dynamics in storage rings are investigated. In the first part the theory of stochastic differential equations and Fokker-Planck equations is used to describe the processes which have been assumed to be Markov processes. The mathematical theory of Markov processes is well known. Nevertheless, analytical solutions can be found only in special cases and numerical algorithms are required. Several numerical integration schemes for stochastic differential equations will therefore be tested in analytical solvable examples and then applied to examples from accelerator physics. In particular the stochastically perturbed synchrotron motion is treated. For the special case of a double rf system several perturbation theoretical methods for deriving the Fokker-Planck equation in the action variable are used and compared with numerical results. The second part is concerned with the dynamics of electron storage rings. Due to the synchrotron radiation the electron motion is influenced by damping and exciting forces. An algorithm for the computation of the density function in the phase space of such a dissipative stochastically excited system is introduced. The density function contains all information of a process, e.g. it determines the beam dimensions and the lifetime of a stored electron beam. The new algorithm consists in calculating a time propagator for the density function. By means of this propagator the time evolution of the density is modelled very computing time efficient. The method is applied to simple models of the beam-beam interaction (one-dimensional, round beams) and the results of the density calculations are compared with results obtained from multiparticle tracking. Furthermore some modifications of the algorithm are introduced to improve its efficiency concerning computing time and storage requirements. Finally, extensions to two-dimensional beam-beam models are described. (orig.)

  15. Spatio-temporal powder formation and trapping in RF silane plasmas using 2-D polarization-sensitive laser scattering

    International Nuclear Information System (INIS)

    Dorier, J.L.; Hollenstein, C.; Howling, A.A.

    1994-09-01

    Powder formation studies in deposition plasmas are motivated by the need to reduce contamination in the plasma and films. Models for the force acting upon particles in rf discharges suffer from a lack of quantitative experimental data for comparison in the case of silane-containing plasmas. In this work, a cross-section of the parallel-plate capacitor discharge is illuminated with a polarized beam-expanded laser and global spatio-temporal scattered light and extinction are recorded by CCD cameras. Spatially-regular periodic bright/dark zones due to constructive/destructive Mie interference are visible over large regions of the powder layers, which shows the uniform nature of particle growth in silane plasmas. For particles trapped in an argon plasma, as for steady-state conditions in silane, spatial size segregation is demonstrated by fringes which reverse according to the polarisation of scattered light. The method allow a self-consistent estimation of particle size and number density throughout the discharge volume from which strong particle Coulomb coupling (Γ>40) is suggested to influence powder dynamics. Correction must be made to the plasma emission profile for the extinction by powder. In conclusion, this global diagnostics improves understanding of particle growth and dynamics in silane rf discharges and provides experimental input for testing the validity of models. (author) 6 figs., 43 refs

  16. Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

    Science.gov (United States)

    Xia, Jiangzhou; Liu, Shuguang; Liang, Shunlin; Chen, Yang; Xu, Wenfang; Yuan, Wenping

    2014-01-01

    Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

  17. Spatial and spatio-temporal analysis of malaria in the state of Acre, western Amazon, Brazil

    Directory of Open Access Journals (Sweden)

    Leonardo Augusto Kohara Melchior

    2016-11-01

    Full Text Available Since 2005, the State of Acre, western Amazon, Brazil, has reported the highest annual parasite incidence (API of malaria among the Brazilian states. This study examines malaria incidence in Acre using spatial and spatio-temporal analysis based on an ecological time series study analyzing malaria cases and deaths for the time period 1992- 2014 and using secondary data. API indexes were calculated by age, sex, parasite species, ratio of Plasmodium vivax to P. falciparum malaria, malaria mortality rate and case fatality rate. SaTScan was used to detect spatial and spatio-temporal clusters of malaria cases and data were represented in the form of choropleth maps. A high-risk cluster of malaria was detected in Vale do Juruá and three low-risk clusters in Vale do Acre for both parasite species. Those younger than 19 years of age and females showed a high incidence of malaria in Vale do Juruá, but working-age males were the most affected in Vale do Acre. The malaria mortality rate showed a decreasing trend across the state, while the case fatality rate increased only in the micro-region of Rio Branco during the study period. We conclude that malaria is a focal disease in Acre showing different spatial and spatio-temporal patterns of cases and deaths that vary by age, sex, and parasite species. Malaria incidence is thought to be influenced by factors related to regional characteristics; therefore, appropriate disease and vector control strategies must be implemented at each locality.

  18. Fast multidimensional ensemble empirical mode decomposition for the analysis of big spatio-temporal datasets.

    Science.gov (United States)

    Wu, Zhaohua; Feng, Jiaxin; Qiao, Fangli; Tan, Zhe-Min

    2016-04-13

    In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal-spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders. © 2016 The Authors.

  19. Bayesian spatio-temporal modelling of tobacco-related cancer mortality in Switzerland

    Directory of Open Access Journals (Sweden)

    Verena Jürgens

    2013-05-01

    Full Text Available Tobacco smoking is a main cause of disease in Switzerland; lung cancer being the most common cancer mortality in men and the second most common in women. Although disease-specific mortality is decreasing in men, it is steadily increasing in women. The four language regions in this country might play a role in this context as they are influenced in different ways by the cultural and social behaviour of neighbouring countries. Bayesian hierarchical spatio-temporal, negative binomial models were fitted on subgroup-specific death rates indirectly standardized by national references to explore age- and gender-specific spatio-temporal patterns of mortality due to lung cancer and other tobacco-related cancers in Switzerland for the time period 1969-2002. Differences influenced by linguistic region and life in rural or urban areas were also accounted for. Male lung cancer mortality was found to be rather homogeneous in space, whereas women were confirmed to be more affected in urban regions. Compared to the German-speaking part, female mortality was higher in the French-speaking part of the country, a result contradicting other reports of similar comparisons between France and Germany. The spatio-temporal patterns of mortality were similar for lung cancer and other tobacco-related cancers. The estimated mortality maps can support the planning in health care services and evaluation of a national tobacco control programme. Better understanding of spatial and temporal variation of cancer of the lung and other tobacco-related cancers may help in allocating resources for more effective screening, diagnosis and therapy. The methodology can be applied to similar studies in other settings.

  20. Spatio-temporal Analysis of the Genetic Diversity of Arctic Rabies Viruses and Their Reservoir Hosts in Greenland.

    Directory of Open Access Journals (Sweden)

    Dennis Hanke

    2016-07-01

    Full Text Available There has been limited knowledge on spatio-temporal epidemiology of zoonotic arctic fox rabies among countries bordering the Arctic, in particular Greenland. Previous molecular epidemiological studies have suggested the occurrence of one particular arctic rabies virus (RABV lineage (arctic-3, but have been limited by a low number of available samples preventing in-depth high resolution phylogenetic analysis of RABVs at that time. However, an improved knowledge of the evolution, at a molecular level, of the circulating RABVs and a better understanding of the historical perspective of the disease in Greenland is necessary for better direct control measures on the island. These issues have been addressed by investigating the spatio-temporal genetic diversity of arctic RABVs and their reservoir host, the arctic fox, in Greenland using both full and partial genome sequences. Using a unique set of 79 arctic RABV full genome sequences from Greenland, Canada, USA (Alaska and Russia obtained between 1977 and 2014, a description of the historic context in relation to the genetic diversity of currently circulating RABV in Greenland and neighboring Canadian Northern territories has been provided. The phylogenetic analysis confirmed delineation into four major arctic RABV lineages (arctic 1-4 with viruses from Greenland exclusively grouping into the circumpolar arctic-3 lineage. High resolution analysis enabled distinction of seven geographically distinct subclades (3.I - 3.VII with two subclades containing viruses from both Greenland and Canada. By combining analysis of full length RABV genome sequences and host derived sequences encoding mitochondrial proteins obtained simultaneously from brain tissues of 49 arctic foxes, the interaction of viruses and their hosts was explored in detail. Such an approach can serve as a blueprint for analysis of infectious disease dynamics and virus-host interdependencies. The results showed a fine-scale spatial population

  1. Nambu mechanics for stochastic magnetization dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Thibaudeau, Pascal, E-mail: pascal.thibaudeau@cea.fr [CEA DAM/Le Ripault, BP 16, F-37260 Monts (France); Nussle, Thomas, E-mail: thomas.nussle@cea.fr [CEA DAM/Le Ripault, BP 16, F-37260 Monts (France); CNRS-Laboratoire de Mathématiques et Physique Théorique (UMR 7350), Fédération de Recherche “Denis Poisson” (FR2964), Département de Physique, Université de Tours, Parc de Grandmont, F-37200 Tours (France); Nicolis, Stam, E-mail: stam.nicolis@lmpt.univ-tours.fr [CNRS-Laboratoire de Mathématiques et Physique Théorique (UMR 7350), Fédération de Recherche “Denis Poisson” (FR2964), Département de Physique, Université de Tours, Parc de Grandmont, F-37200 Tours (France)

    2017-06-15

    Highlights: • The LLG equation can be formulated in the framework of dissipative Nambu mechanics. • A master equation is derived for the spin dynamics for additive/multiplicative noises. • The derived stochastic equations are compared to moment equations obtained by closures. - Abstract: The Landau–Lifshitz–Gilbert (LLG) equation describes the dynamics of a damped magnetization vector that can be understood as a generalization of Larmor spin precession. The LLG equation cannot be deduced from the Hamiltonian framework, by introducing a coupling to a usual bath, but requires the introduction of additional constraints. It is shown that these constraints can be formulated elegantly and consistently in the framework of dissipative Nambu mechanics. This has many consequences for both the variational principle and for topological aspects of hidden symmetries that control conserved quantities. We particularly study how the damping terms of dissipative Nambu mechanics affect the consistent interaction of magnetic systems with stochastic reservoirs and derive a master equation for the magnetization. The proposals are supported by numerical studies using symplectic integrators that preserve the topological structure of Nambu equations. These results are compared to computations performed by direct sampling of the stochastic equations and by using closure assumptions for the moment equations, deduced from the master equation.

  2. Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

    Science.gov (United States)

    Varlamova, Eugenia V.; Solovyev, Vladimir S.

    2017-11-01

    Study of spatio-temporal variations of NDVI (Normalized Difference Vegetation Index) and phenological parameters of Eastern Siberia vegetation cover under global warming was carried out on AVHRR/NOAA data (1982-2014). Trend maps of NDVI and annual variations of phenological parameters and NDVI are analyzed. A method based on stable transition of air temperature through +5°C was used to estimate the beginning, end and the length of the growing season. Correlation between NDVI and phenological parameters, surface air temperature and precipitation are discussed.

  3. A spatio-temporal process data model for characterizing marine disasters

    International Nuclear Information System (INIS)

    Jiang, B; Gao, T; Zhang, X; Huang, X

    2014-01-01

    Marine disasters are a more prevalent problem in China than in many other countries. Based on the development of a status quo of China's marine disaster the space-time process model is used. The model uses the ocean's temperature field, salinity field, water density field, surface wind field, wave field and other four-dimensional spatio-temporal quantities. This paper studies that model in detail. This study aims at using the theory to provide support during marine disasters in an effort to prevent or decrease their frequency in the future

  4. An adaptive spatio-temporal smoothing model for estimating trends and step changes in disease risk

    OpenAIRE

    Rushworth, Alastair; Lee, Duncan; Sarran, Christophe

    2014-01-01

    Statistical models used to estimate the spatio-temporal pattern in disease\\ud risk from areal unit data represent the risk surface for each time period with known\\ud covariates and a set of spatially smooth random effects. The latter act as a proxy\\ud for unmeasured spatial confounding, whose spatial structure is often characterised by\\ud a spatially smooth evolution between some pairs of adjacent areal units while other\\ud pairs exhibit large step changes. This spatial heterogeneity is not c...

  5. Joint level-set and spatio-temporal motion detection for cell segmentation.

    Science.gov (United States)

    Boukari, Fatima; Makrogiannis, Sokratis

    2016-08-10

    Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan

  6. Principles for statistical inference on big spatio-temporal data from climate models

    KAUST Repository

    Castruccio, Stefano

    2018-02-24

    The vast increase in size of modern spatio-temporal datasets has prompted statisticians working in environmental applications to develop new and efficient methodologies that are still able to achieve inference for nontrivial models within an affordable time. Climate model outputs push the limits of inference for Gaussian processes, as their size can easily be larger than 10 billion data points. Drawing from our experience in a set of previous work, we provide three principles for the statistical analysis of such large datasets that leverage recent methodological and computational advances. These principles emphasize the need of embedding distributed and parallel computing in the inferential process.

  7. Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China

    Directory of Open Access Journals (Sweden)

    Yanxia Wang

    2014-05-01

    Full Text Available Ischemic heart disease (IHD is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents and the standardized rate (the observed cases standardized by the expected cases of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013–2015 to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction

  8. Assimilation of spatio-temporal distribution of radionuclides in early phase of radiation accident

    Czech Academy of Sciences Publication Activity Database

    Hofman, Radek; Šmídl, Václav

    2010-01-01

    Roč. 18, 7/8 (2010), s. 226-228 ISSN 1210-7085 R&D Projects: GA MŠk(CZ) 1M0572; GA ČR(CZ) GA102/07/1596 Institutional research plan: CEZ:AV0Z10750506 Keywords : decision support * early phase * Gaussian model * radioactive pollution transport Subject RIV: DL - Nuclear Waste, Radioactive Pollution ; Quality http://library.utia.cas.cz/separaty/2010/AS/hofman-assimilation of spatio-temporal distribution of radionuclides in early phase of radiation accident .pdf

  9. Principles for statistical inference on big spatio-temporal data from climate models

    KAUST Repository

    Castruccio, Stefano; Genton, Marc G.

    2018-01-01

    The vast increase in size of modern spatio-temporal datasets has prompted statisticians working in environmental applications to develop new and efficient methodologies that are still able to achieve inference for nontrivial models within an affordable time. Climate model outputs push the limits of inference for Gaussian processes, as their size can easily be larger than 10 billion data points. Drawing from our experience in a set of previous work, we provide three principles for the statistical analysis of such large datasets that leverage recent methodological and computational advances. These principles emphasize the need of embedding distributed and parallel computing in the inferential process.

  10. On the genesis of spatio-temporal self-organized structures in plasma devices

    International Nuclear Information System (INIS)

    Talasman, S.J.; Sanduloviciu, M.

    1995-01-01

    The genesis of luminous sharply defined nearly spherical space charges structures formed in an Argon plasma column was experimental investigated. The results reveal spatio-temporal characteristics proper to systems resulting after a self-organization process. Their phenomenology involves electrical charges separation produced by symmetry breaking and spatial separation of the excitation and ionization cross sections functions in a region where electrons are accelerated and, as a result, the appearance of electrostatic forces that, acting as long range correlations, assures, together with dissipative effects, its stability. (Author) 8 Figs., 31 Refs

  11. Spatio-Temporal Patterns in Colonies of Rod-Shaped Bacteria

    Science.gov (United States)

    Kitsunezaki, S.

    In incubation experiments of bacterial colonies of Proteus Mirabilis, macroscopic spatio-temporal patterns, such as turbulent and unidirectional spiral patterns, appear in colonies. Considering only kinetic propeties of rod-shaped bacteria, we propose a phenomenological model for the directional and positional distributions. As the average density increases, homogeneous states bifurcate sub-critically into nonuniform states exhibiting localized collective motion, and spiral patterns appear for sufficiently large density. These patterns result from interactions between the local bacteria densities and the order parameter representing collective motion. Our model can be described by reduced equations using a perturbative method for large density. The unidirectionality of sprial rotation is also discussed.

  12. Hybrid Differential Dynamic Programming with Stochastic Search

    Science.gov (United States)

    Aziz, Jonathan; Parker, Jeffrey; Englander, Jacob

    2016-01-01

    Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASAs Dawn mission. The Dawn trajectory was designed with the DDP-based Static Dynamic Optimal Control algorithm used in the Mystic software. Another recently developed method, Hybrid Differential Dynamic Programming (HDDP) is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.

  13. The spatio-temporal structure of electrostatic turbulence in the WEGA stellarator

    Energy Technology Data Exchange (ETDEWEB)

    Marsen, Stefan

    2008-03-15

    The main object of this work is to provide a detailed characterisation of electrostatic turbulence in WEGA and to identify the underlying instability mechanism driving turbulence. The spatio-temporal structure of turbulence is studied using multiple Langmuir probes providing a sufficiently high spatial and temporal resolution. Turbulence in WEGA is dominated by drift wave dynamics. The phase shift between density and potential fluctuations is close to zero, fluctuations are mainly driven by the density gradient, and the phase velocity of turbulent structures points in the direction of the electron diamagnetic drift. The structure of turbulence is studied mainly in the plasma edge region inside the last closed flux surface. WEGA can be operated in two regimes differing in the magnetic field strength by almost one order of magnitude (57 mT and 500 mT, respectively). At 57 mT large structures with a poloidal extent comparable to the machine dimensions are observed, whereas at 500 mT turbulent structures are much smaller. The poloidal structure size scales nearly linearly with the inverse magnetic field strength. This scaling may be argued to be related to the drift wave dispersion scale, {rho}{sub s}={radical}(m{sub i}k{sub B}T{sub e})/(qB). However, the structure size remains unchanged when the ion mass is changed by using different discharge gases. Inside the last closed flux surface the poloidal E x B drift in WEGA is negligible. The three-dimensional structure is studied in detail using probes which are toroidally separated but aligned along connecting magnetic field lines. A small but finite parallel wavenumber is found. The ratio between the average parallel and perpendicular wavenumber is in the order of anti {kappa} {sub parallel} / anti {kappa}{sub {theta}} {approx} 10{sup -2}. The parallel phase velocity of turbulent structures is in-between the ion sound velocity and the Alfven velocity. In the parallel dynamics a fundamental difference between the two

  14. Stochastic and deterministic processes regulate spatio-temporal variation in seed bank diversity

    Science.gov (United States)

    Alejandro A. Royo; Todd E. Ristau

    2013-01-01

    Seed banks often serve as reservoirs of taxonomic and genetic diversity that buffer plant populations and influence post-disturbance vegetation trajectories; yet evaluating their importance requires understanding how their composition varies within and across spatial and temporal scales (α- and β-diversity). Shifts in seed bank diversity are strongly...

  15. The critical role of Golgi cells in regulating spatio-temporal integration and plasticity at the cerebellum input stage

    Directory of Open Access Journals (Sweden)

    2008-07-01

    Full Text Available After the discovery at the end of the 19th century (Golgi, 1883, the Golgi cell was precisely described by S.R. y Cajal (see Cajal, 1987, 1995 and functionally identified as an inhibitory interneuron 50 years later by J.C. Eccles and colleagues (Eccles e al., 1967. Then, its role has been casted by Marr (1969 within the Motor Learning Theory as a codon size regulator of granule cell activity. It was immediately clear that Golgi cells had to play a critical role, since they are the main inhibitory interneuron of the granular layer and control activity of as many as 100 millions granule cells. In vitro, Golgi cells show pacemaking, resonance, phase-reset and rebound-excitation in the theta-frequency band. These properties are likely to impact on their activity in vivo, which shows irregular spontaneous beating modulated by sensory inputs and burst responses to punctuate stimulation followed by a silent pause. Moreover, investigations have given insight into Golgi cells connectivity within the cerebellar network and on their impact on the spatio-temporal organization of activity. It turns out that Golgi cells can control both the temporal dynamics and the spatial distribution of information transmitted through the cerebellar network. Moreover, Golgi cells regulate the induction of long-term synaptic plasticity at the mossy fiber - granule cell synapse. Thus, the concept is emerging that Golgi cells are of critical importance for regulating granular layer network activity bearing important consequences for cerebellar computation as a whole.

  16. Mobile acoustic transects miss rare bat species: implications of survey method and spatio-temporal sampling for monitoring bats

    Directory of Open Access Journals (Sweden)

    Elizabeth C. Braun de Torrez

    2017-11-01

    Full Text Available Due to increasing threats facing bats, long-term monitoring protocols are needed to inform conservation strategies. Effective monitoring should be easily repeatable while capturing spatio-temporal variation. Mobile acoustic driving transect surveys (‘mobile transects’ have been touted as a robust, cost-effective method to monitor bats; however, it is not clear how well mobile transects represent dynamic bat communities, especially when used as the sole survey approach. To assist biologists who must select a single survey method due to resource limitations, we assessed the effectiveness of three acoustic survey methods at detecting species richness in a vast protected area (Everglades National Park: (1 mobile transects, (2 stationary surveys that were strategically located by sources of open water and (3 stationary surveys that were replicated spatially across the landscape. We found that mobile transects underrepresented bat species richness compared to stationary surveys across all major vegetation communities and in two distinct seasons (dry/cool and wet/warm. Most critically, mobile transects failed to detect three rare bat species, one of which is federally endangered. Spatially replicated stationary surveys did not estimate higher species richness than strategically located stationary surveys, but increased the rate at which species were detected in one vegetation community. The survey strategy that detected maximum species richness and the highest mean nightly species richness with minimal effort was a strategically located stationary detector in each of two major vegetation communities during the wet/warm season.

  17. Stability switches, oscillatory multistability, and spatio-temporal patterns of nonlinear oscillations in recurrently delay coupled neural networks.

    Science.gov (United States)

    Song, Yongli; Makarov, Valeri A; Velarde, Manuel G

    2009-08-01

    A model of time-delay recurrently coupled spatially segregated neural assemblies is here proposed. We show that it operates like some of the hierarchical architectures of the brain. Each assembly is a neural network with no delay in the local couplings between the units. The delay appears in the long range feedforward and feedback inter-assemblies communications. Bifurcation analysis of a simple four-units system in the autonomous case shows the richness of the dynamical behaviors in a biophysically plausible parameter region. We find oscillatory multistability, hysteresis, and stability switches of the rest state provoked by the time delay. Then we investigate the spatio-temporal patterns of bifurcating periodic solutions by using the symmetric local Hopf bifurcation theory of delay differential equations and derive the equation describing the flow on the center manifold that enables us determining the direction of Hopf bifurcations and stability of the bifurcating periodic orbits. We also discuss computational properties of the system due to the delay when an external drive of the network mimicks external sensory input.

  18. Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data.

    Science.gov (United States)

    Ashdown, George; Pandžić, Elvis; Cope, Andrew; Wiseman, Paul; Owen, Dylan

    2015-12-17

    Filamentous-actin plays a crucial role in a majority of cell processes including motility and, in immune cells, the formation of a key cell-cell interaction known as the immunological synapse. F-actin is also speculated to play a role in regulating molecular distributions at the membrane of cells including sub-membranous vesicle dynamics and protein clustering. While standard light microscope techniques allow generalized and diffraction-limited observations to be made, many cellular and molecular events including clustering and molecular flow occur in populations at length-scales far below the resolving power of standard light microscopy. By combining total internal reflection fluorescence with the super resolution imaging method structured illumination microscopy, the two-dimensional molecular flow of F-actin at the immune synapse of T cells was recorded. Spatio-temporal image correlation spectroscopy (STICS) was then applied, which generates quantifiable results in the form of velocity histograms and vector maps representing flow directionality and magnitude. This protocol describes the combination of super-resolution imaging and STICS techniques to generate flow vectors at sub-diffraction levels of detail. This technique was used to confirm an actin flow that is symmetrically retrograde and centripetal throughout the periphery of T cells upon synapse formation.

  19. Understanding spatio-temporal mobility patterns for seniors, child/student and adult using smart card data

    Science.gov (United States)

    Huang, X.; Tan, J.

    2014-11-01

    Commutes in urban areas create interesting travel patterns that are often stored in regional transportation databases. These patterns can vary based on the day of the week, the time of the day, and commuter type. This study proposes methods to detect underlying spatio-temporal variability among three groups of commuters (senior citizens, child/students, and adults) using data mining and spatial analytics. Data from over 36 million individual trip records collected over one week (March 2012) on the Singapore bus and Mass Rapid Transit (MRT) system by the fare collection system were used. Analyses of such data are important for transportation and landuse designers and contribute to a better understanding of urban dynamics. Specifically, descriptive statistics, network analysis, and spatial analysis methods are presented. Descriptive variables were proposed such as density and duration to detect temporal features of people. A directed weighted graph G ≡ (N , L, W) was defined to analyze the global network properties of every pair of the transportation link in the city during an average workday for all three categories. Besides, spatial interpolation and spatial statistic tools were used to transform the discrete network nodes into structured human movement landscape to understand the role of transportation systems in urban areas. The travel behaviour of the three categories follows a certain degree of temporal and spatial universality but also displays unique patterns within their own specialties. Each category is characterized by their different peak hours, commute distances, and specific locations for travel on weekdays.

  20. Mobile acoustic transects miss rare bat species: implications of survey method and spatio-temporal sampling for monitoring bats.

    Science.gov (United States)

    Braun de Torrez, Elizabeth C; Wallrichs, Megan A; Ober, Holly K; McCleery, Robert A

    2017-01-01

    Due to increasing threats facing bats, long-term monitoring protocols are needed to inform conservation strategies. Effective monitoring should be easily repeatable while capturing spatio-temporal variation. Mobile acoustic driving transect surveys ('mobile transects') have been touted as a robust, cost-effective method to monitor bats; however, it is not clear how well mobile transects represent dynamic bat communities, especially when used as the sole survey approach. To assist biologists who must select a single survey method due to resource limitations, we assessed the effectiveness of three acoustic survey methods at detecting species richness in a vast protected area (Everglades National Park): (1) mobile transects, (2) stationary surveys that were strategically located by sources of open water and (3) stationary surveys that were replicated spatially across the landscape. We found that mobile transects underrepresented bat species richness compared to stationary surveys across all major vegetation communities and in two distinct seasons (dry/cool and wet/warm). Most critically, mobile transects failed to detect three rare bat species, one of which is federally endangered. Spatially replicated stationary surveys did not estimate higher species richness than strategically located stationary surveys, but increased the rate at which species were detected in one vegetation community. The survey strategy that detected maximum species richness and the highest mean nightly species richness with minimal effort was a strategically located stationary detector in each of two major vegetation communities during the wet/warm season.

  1. Spatio-Temporal Variations and Source Apportionment of Water Pollution in Danjiangkou Reservoir Basin, Central China

    Directory of Open Access Journals (Sweden)

    Pan Chen

    2015-05-01

    Full Text Available Understanding the spatio-temporal variation and the potential source of water pollution could greatly improve our knowledge of human impacts on the environment. In this work, data of 11 water quality indices were collected during 2012–2014 at 10 monitoring sites in the mainstream and major tributaries of the Danjiangkou Reservoir Basin, Central China. The fuzzy comprehensive assessment (FCA, the cluster analysis (CA and the discriminant analysis (DA were used to assess the water pollution status and analyze its spatio-temporal variation. Ten sites were classified by the high pollution (HP region and the low pollution (LP region, while 12 months were divided into the wet season and the dry season. It was found that the HP region was mainly in the small tributaries with small drainage areas and low average annual discharges, and it was also found that most of these rivers went through urban areas with industrial and domestic sewages input into the water body. Principal component analysis/factor analysis (PCA/FA was applied to reveal potential pollution sources, whereas absolute principal component score-multiple linear regression (APCS-MLR was used to identify their contributions to each water quality variable. The study area was found as being generally affected by industrial and domestic sewage. Furthermore, the HP region was polluted by chemical industries, and the LP region was influenced by agricultural and livestock sewage.

  2. Spatio-Temporal Database of Places Located in the Border Area

    Directory of Open Access Journals (Sweden)

    Albina Mościcka

    2018-03-01

    Full Text Available As a result of changes in boundaries, the political affiliation of locations also changes. Data on such locations are now collected in datasets with reference to the present or to the past space. Therefore, they can refer to localities that either no longer exist, have a different name now, or lay outside of the current borders of the country. Moreover, thematic data describing the past are related to events, customs, items that are always “somewhere”. Storytelling about the past is incomplete without knowledge about the places in which the given story has happened. Therefore, the objective of the article is to discuss the concept of spatio-temporal database for border areas as an “engine” for visualization of thematic data in time-oriented geographical space. The paper focuses on studying the place names on the Polish-Ukrainian border, analyzing the changes that have occurred in this area over the past 80 years (where there were three different countries during this period, and defining the changeability rules. As a result of the research, the architecture of spatio-temporal databases is defined, as well as the rules for using them for data geovisualisation in historical context.

  3. Statistical study of spatio-temporal distribution of precursor solar flares associated with major flares

    Science.gov (United States)

    Gyenge, N.; Ballai, I.; Baranyi, T.

    2016-07-01

    The aim of the present investigation is to study the spatio-temporal distribution of precursor flares during the 24 h interval preceding M- and X-class major flares and the evolution of follower flares. Information on associated (precursor and follower) flares is provided by Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). Flare list, while the major flares are observed by the Geostationary Operational Environmental Satellite (GOES) system satellites between 2002 and 2014. There are distinct evolutionary differences between the spatio-temporal distributions of associated flares in about one-day period depending on the type of the main flare. The spatial distribution was characterized by the normalized frequency distribution of the quantity δ (the distance between the major flare and its precursor flare normalized by the sunspot group diameter) in four 6 h time intervals before the major event. The precursors of X-class flares have a double-peaked spatial distribution for more than half a day prior to the major flare, but it changes to a lognormal-like distribution roughly 6 h prior to the event. The precursors of M-class flares show lognormal-like distribution in each 6 h subinterval. The most frequent sites of the precursors in the active region are within a distance of about 0.1 diameter of sunspot group from the site of the major flare in each case. Our investigation shows that the build-up of energy is more effective than the release of energy because of precursors.

  4. Detecting spatio-temporal modes in multivariate data by entropy field decomposition

    International Nuclear Information System (INIS)

    Frank, Lawrence R; Galinsky, Vitaly L

    2016-01-01

    A new data analysis method that addresses a general problem of detecting spatio-temporal variations in multivariate data is presented. The method utilizes two recent and complimentary general approaches to data analysis, information field theory (IFT) and entropy spectrum pathways (ESPs). Both methods reformulate and incorporate Bayesian theory, thus use prior information to uncover underlying structure of the unknown signal. Unification of ESP and IFT creates an approach that is non-Gaussian and nonlinear by construction and is found to produce unique spatio-temporal modes of signal behavior that can be ranked according to their significance, from which space–time trajectories of parameter variations can be constructed and quantified. Two brief examples of real world applications of the theory to the analysis of data bearing completely different, unrelated nature, lacking any underlying similarity, are also presented. The first example provides an analysis of resting state functional magnetic resonance imaging data that allowed us to create an efficient and accurate computational method for assessing and categorizing brain activity. The second example demonstrates the potential of the method in the application to the analysis of a strong atmospheric storm circulation system during the complicated stage of tornado development and formation using data recorded by a mobile Doppler radar. Reference implementation of the method will be made available as a part of the QUEST toolkit that is currently under development at the Center for Scientific Computation in Imaging. (paper)

  5. Spatio-temporal models of mental processes from fMRI.

    Science.gov (United States)

    Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

    2011-07-15

    Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

  6. A Hybrid Method for Interpolating Missing Data in Heterogeneous Spatio-Temporal Datasets

    Directory of Open Access Journals (Sweden)

    Min Deng

    2016-02-01

    Full Text Available Space-time interpolation is widely used to estimate missing or unobserved values in a dataset integrating both spatial and temporal records. Although space-time interpolation plays a key role in space-time modeling, existing methods were mainly developed for space-time processes that exhibit stationarity in space and time. It is still challenging to model heterogeneity of space-time data in the interpolation model. To overcome this limitation, in this study, a novel space-time interpolation method considering both spatial and temporal heterogeneity is developed for estimating missing data in space-time datasets. The interpolation operation is first implemented in spatial and temporal dimensions. Heterogeneous covariance functions are constructed to obtain the best linear unbiased estimates in spatial and temporal dimensions. Spatial and temporal correlations are then considered to combine the interpolation results in spatial and temporal dimensions to estimate the missing data. The proposed method is tested on annual average temperature and precipitation data in China (1984–2009. Experimental results show that, for these datasets, the proposed method outperforms three state-of-the-art methods—e.g., spatio-temporal kriging, spatio-temporal inverse distance weighting, and point estimation model of biased hospitals-based area disease estimation methods.

  7. Spatio-Temporal Series Remote Sensing Image Prediction Based on Multi-Dictionary Bayesian Fusion

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-11-01

    Full Text Available Contradictions in spatial resolution and temporal coverage emerge from earth observation remote sensing images due to limitations in technology and cost. Therefore, how to combine remote sensing images with low spatial yet high temporal resolution as well as those with high spatial yet low temporal resolution to construct images with both high spatial resolution and high temporal coverage has become an important problem called spatio-temporal fusion problem in both research and practice. A Multi-Dictionary Bayesian Spatio-Temporal Reflectance Fusion Model (MDBFM has been proposed in this paper. First, multiple dictionaries from regions of different classes are trained. Second, a Bayesian framework is constructed to solve the dictionary selection problem. A pixel-dictionary likehood function and a dictionary-dictionary prior function are constructed under the Bayesian framework. Third, remote sensing images before and after the middle moment are combined to predict images at the middle moment. Diverse shapes and textures information is learned from different landscapes in multi-dictionary learning to help dictionaries capture the distinctions between regions. The Bayesian framework makes full use of the priori information while the input image is classified. The experiments with one simulated dataset and two satellite datasets validate that the MDBFM is highly effective in both subjective and objective evaluation indexes. The results of MDBFM show more precise details and have a higher similarity with real images when dealing with both type changes and phenology changes.

  8. Spatio-temporal analysis of Modified Omori law in Bayesian framework

    Science.gov (United States)

    Rezanezhad, V.; Narteau, C.; Shebalin, P.; Zoeller, G.; Holschneider, M.

    2017-12-01

    This work presents a study of the spatio temporal evolution of the modified Omori parameters in southern California in then time period of 1981-2016. A nearest-neighbor approach is applied for earthquake clustering. This study targets small mainshocks and corresponding big aftershocks ( 2.5 ≤ mmainshocks ≤ 4.5 and 1.8 ≤ maftershocks ≤ 2.8 ). We invert for the spatio temporal behavior of c and p values (especially c) all over the area using a MCMC based maximum likelihood estimator. As parameterizing families we use Voronoi cells with randomly distributed cell centers. Considering that c value represents a physical character like stress change we expect to see a coherent c value pattern over seismologically coacting areas. This correlation of c valus can actually be seen for the San Andreas, San Jacinto and Elsinore faults. Moreover, the depth dependency of c value is studied which shows a linear behavior of log(c) with respect to aftershock's depth within 5 to 15 km depth.

  9. Spatio-temporal epidemiology of the cholera outbreak in Papua New Guinea, 2009-2011.

    Science.gov (United States)

    Horwood, Paul F; Karl, Stephan; Mueller, Ivo; Jonduo, Marinjho H; Pavlin, Boris I; Dagina, Rosheila; Ropa, Berry; Bieb, Sibauk; Rosewell, Alexander; Umezaki, Masahiro; Siba, Peter M; Greenhill, Andrew R

    2014-08-20

    Cholera continues to be a devastating disease in many developing countries where inadequate safe water supply and poor sanitation facilitate spread. From July 2009 until late 2011 Papua New Guinea experienced the first outbreak of cholera recorded in the country, resulting in >15,500 cases and >500 deaths. Using the national cholera database, we analysed the spatio-temporal distribution and clustering of the Papua New Guinea cholera outbreak. The Kulldorff space-time permutation scan statistic, contained in the software package SatScan v9.2 was used to describe the first 8 weeks of the outbreak in Morobe Province before cholera cases spread throughout other regions of the country. Data were aggregated at the provincial level to describe the spread of the disease to other affected provinces. Spatio-temporal and cluster analyses revealed that the outbreak was characterized by three distinct phases punctuated by explosive propagation of cases when the outbreak spread to a new region. The lack of road networks across most of Papua New Guinea is likely to have had a major influence on the slow spread of the disease during this outbreak. Identification of high risk areas and the likely mode of spread can guide government health authorities to formulate public health strategies to mitigate the spread of the disease through education campaigns, vaccination, increased surveillance in targeted areas and interventions to improve water, sanitation and hygiene.

  10. Spatio-temporal flow maps for visualizing movement and contact patterns

    Directory of Open Access Journals (Sweden)

    Bing Ni

    2017-03-01

    Full Text Available The advanced telecom technologies and massive volumes of intelligent mobile phone users have yielded a huge amount of real-time data of people’s all-in-one telecommunication records, which we call telco big data. With telco data and the domain knowledge of an urban city, we are now able to analyze the movement and contact patterns of humans in an unprecedented scale. Flow map is widely used to display the movements of humans from one single source to multiple destinations by representing locations as nodes and movements as edges. However, it fails the task of visualizing both movement and contact data. In addition, analysts often need to compare and examine the patterns side by side, and do various quantitative analysis. In this work, we propose a novel spatio-temporal flow map layout to visualize when and where people from different locations move into the same places and make contact. We also propose integrating the spatiotemporal flow maps into existing spatiotemporal visualization techniques to form a suite of techniques for visualizing the movement and contact patterns. We report a potential application the proposed techniques can be applied to. The results show that our design and techniques properly unveil hidden information, while analysis can be achieved efficiently. Keywords: Spatio-temporal data, Flow map, Urban mobility

  11. BUILDING A BILLION SPATIO-TEMPORAL OBJECT SEARCH AND VISUALIZATION PLATFORM

    Directory of Open Access Journals (Sweden)

    D. Kakkar

    2017-10-01

    Full Text Available With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA has developed a prototype spatio-temporal visualization platform called the Billion Object Platform or BOP. The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. The BOP is now loaded with the latest billion geo-tweets, and is fed a real-time stream of about 1 million tweets per day. The geo-tweets are enriched with sentiment and census/admin boundary codes when they enter the system. The system is open source and is currently hosted on Massachusetts Open Cloud (MOC, an OpenStack environment with all components deployed in Docker orchestrated by Kontena. This paper will provide an overview of the BOP architecture, which is built on an open source stack consisting of Apache Lucene, Solr, Kafka, Zookeeper, Swagger, scikit-learn, OpenLayers, and AngularJS. The paper will further discuss the approach used for harvesting, enriching, streaming, storing, indexing, visualizing and querying a billion streaming geo-tweets.

  12. Building a Billion Spatio-Temporal Object Search and Visualization Platform

    Science.gov (United States)

    Kakkar, D.; Lewis, B.

    2017-10-01

    With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA) has developed a prototype spatio-temporal visualization platform called the Billion Object Platform or BOP. The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. The BOP is now loaded with the latest billion geo-tweets, and is fed a real-time stream of about 1 million tweets per day. The geo-tweets are enriched with sentiment and census/admin boundary codes when they enter the system. The system is open source and is currently hosted on Massachusetts Open Cloud (MOC), an OpenStack environment with all components deployed in Docker orchestrated by Kontena. This paper will provide an overview of the BOP architecture, which is built on an open source stack consisting of Apache Lucene, Solr, Kafka, Zookeeper, Swagger, scikit-learn, OpenLayers, and AngularJS. The paper will further discuss the approach used for harvesting, enriching, streaming, storing, indexing, visualizing and querying a billion streaming geo-tweets.

  13. The Spatio-Temporal Characteristics and Modeling Research of Inter-Provincial Migration in China

    Directory of Open Access Journals (Sweden)

    Xiaomei Fan

    2018-02-01

    Full Text Available The national census data during 1995 and 2000 and during 2005 and 2010 are selected in this paper to make an analysis of the spatio-temporal characteristics of the inter-provincial population migration in China. In addition, the general regression model, the extension regression model considering the historical dependent variable and the spatial lag model are established based on the gravity model to make the regression model on China’s inter-provincial population migration over two periods of time. The results show that: (1 the inter-provincial population migration increases rapidly in size with strong geographical proximity; (2 China’s inter-provincial population migration is still in the primary stage of the general process of population migration. In other words, the inter-provincial population emigration and immigration levels have increased greatly with the economic development; (3 Statistically, the inter-provincial population migration is negatively correlated with the level of economic development in the emigrant place and the migration distance and positively correlated with the level of economic development in the immigrant place and the population scale in the emigrant and immigrant places; and (4 The spatio-temporal factor is an important explanatory variable of population migration. The introduction of the historical dependent variable and the spatial lag factor can improve the regression effect of the gravity model greatly, and the historical variable and the spatial factor have strong explanatory power for the inter-provincial population migration.

  14. Spatio-temporal patterns of Cu contamination in mosses using geostatistical estimation

    International Nuclear Information System (INIS)

    Martins, Anabela; Figueira, Rui; Sousa, António Jorge; Sérgio, Cecília

    2012-01-01

    Several recent studies have reported temporal trends in metal contamination in mosses, but such assessments did not evaluate uncertainty in temporal changes, therefore providing weak statistical support for time comparisons. Furthermore, levels of contaminants in the environment change in both space and time, requiring space-time modelling methods for map estimation. We propose an indicator of spatial and temporal variation based on space-time estimation by indicator kriging, where uncertainty at each location is estimated from the local distribution function, thereby calculating variability intervals for comparison between several biomonitoring dates. This approach was exemplified using copper concentrations in mosses from four Portuguese surveys (1992, 1997, 2002 and 2006). Using this approach, we identified a general decrease in copper contamination, but spatial patterns were not uniform, and from the uncertainty intervals, changes could not be considered significant in the majority of the study area. - Highlights: ► We estimated copper contamination in mosses by spatio-temporal kriging between 1992 and 2006. ► We determined local distribution functions to define variation intervals at each location. ► Significance of temporal changes is assessed using an indicator based on uncertainty interval. ► There is general decrease in copper contamination, but spatial patterns are not uniform. - The contamination of copper in mosses was estimated by spatio-temporal kriging, with determination of uncertainty classes in the temporal variation.

  15. Spatio-Temporal Parameters\\' Changes in Gait of Male Elderly Subjects

    Directory of Open Access Journals (Sweden)

    Heydar Sadeghi

    2010-03-01

    Full Text Available Objectives: The purpose of this study was to compare spatio-temporal gait parameters between elderly and young male subjects. Methods & Materials: 57 able-bodied elderly (72±5.5 years and 57 healthy young (25±8.5 years subjects participated in this study. A four segment model consist of trunk, hip, shank, and foot with 10 reflective markers were used to define lower limbs. Kinematic data collected using four high speed video based cameras at a sampling frequency of 90 Hz.The t-testfor independent samples (α≤0.05 applied for statistical analysis. Results: Significant differences showed longer stance phase (2%, longer push-of time (4%, slower cadence (13%, slower speed (28% and shorter step length (15% for elderly in comparison with young subjects, though no significant differences were seen in double supporttime between two groups. Conclusion: Due to results, spatio-temporal changes are mainly attributed to the age-related decreases in muscular flexibility, joints>ranges of motion and neuromuscular control in elderly people.

  16. OFDM Radar Space-Time Adaptive Processing by Exploiting Spatio-Temporal Sparsity

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Satyabrata [ORNL

    2013-01-01

    We propose a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly-moving target using an orthogonal frequency division multiplexing (OFDM) radar. We observe that the target and interference spectra are inherently sparse in the spatio-temporal domain. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data and produces an equivalent performance as the other existing STAP techniques. In addition, the use of an OFDM signal increases the frequency diversity of our system, as different scattering centers of a target resonate at different frequencies, and thus improves the target detectability. First, we formulate a realistic sparse-measurement model for an OFDM radar considering both the clutter and jammer as the interfering sources. Then, we apply a residual sparse-recovery technique based on the LASSO estimator to estimate the target and interference covariance matrices, and subsequently compute the optimal STAP-filter weights. Our numerical results demonstrate a comparative performance analysis of the proposed sparse-STAP algorithm with four other existing STAP methods. Furthermore, we discover that the OFDM-STAP filter-weights are adaptable to the frequency-variabilities of the target and interference responses, in addition to the spatio-temporal variabilities. Hence, by better utilizing the frequency variabilities, we propose an adaptive OFDM-waveform design technique, and consequently gain a significant amount of STAP-performance improvement.

  17. Spatio-temporal distribution of fecal indicators in three rivers of the Haihe River Basin, China.

    Science.gov (United States)

    Wang, Yawei; Chen, Yanan; Zheng, Xiang; Gui, Chengmin; Wei, Yuansong

    2017-04-01

    Because of their significant impact on public health, waterborne pathogens, especially bacteria and viruses, are frequently monitored in surface water to assess microbial quality of water bodies. However, more than one billion people worldwide currently lack access to safe drinking water, and a diversity of waterborne outbreaks caused by pathogens is reported in nations at all levels of economic development. Spatio-temporal distribution of conventional pollutants and five pathogenic microorganisms were discussed for the Haihe River Basin. Land use and socio-economic assessments were coupled with comprehensive water quality monitoring. Physical, chemical, and biological parameters were measured at 20 different sites in the watershed for 1 year, including pH, temperature, conductivity, dissolved oxygen, turbidity, chemical oxygen demand, ammonia-N, total and fecal coliforms, E. coli, and Enterococcus. The results highlighted the high spatio-temporal variability in pathogen distribution at watershed scale: high concentration of somatic coliphages and fecal indicator bacteria in March and December and their very low concentration in June and September. All pathogens were positively correlated to urban/rural residential/industrial land and negatively correlated to other four land use types. Microbial pollution was greatly correlated with population density, urbanization rate, and percentage of the tertiary industry in the gross domestic product. In the future, river microbial risk control strategy should focus more on the effective management of secondary effluent of wastewater treatment plant and land around rivers.

  18. A Spatio-Temporal Building Exposure Database and Information Life-Cycle Management Solution

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2017-04-01

    Full Text Available With an ever-increasing volume and complexity of data collected from a variety of sources, the efficient management of geospatial information becomes a key topic in disaster risk management. For example, the representation of assets exposed to natural disasters is subjected to changes throughout the different phases of risk management reaching from pre-disaster mitigation to the response after an event and the long-term recovery of affected assets. Spatio-temporal changes need to be integrated into a sound conceptual and technological framework able to deal with data coming from different sources, at varying scales, and changing in space and time. Especially managing the information life-cycle, the integration of heterogeneous information and the distributed versioning and release of geospatial information are important topics that need to become essential parts of modern exposure modelling solutions. The main purpose of this study is to provide a conceptual and technological framework to tackle the requirements implied by disaster risk management for describing exposed assets in space and time. An information life-cycle management solution is proposed, based on a relational spatio-temporal database model coupled with Git and GeoGig repositories for distributed versioning. Two application scenarios focusing on the modelling of residential building stocks are presented to show the capabilities of the implemented solution. A prototype database model is shared on GitHub along with the necessary scenario data.

  19. Measurement of traffic parameters in image sequence using spatio-temporal information

    International Nuclear Information System (INIS)

    Lee, Daeho; Park, Youngtae

    2008-01-01

    This paper proposes a novel method for measurement of traffic parameters, such as the number of passed vehicles, velocity and occupancy rate, by video image analysis. The method is based on a region classification followed by spatio-temporal image analysis. Local detection region images in traffic lanes are classified into one of four categories: the road, the vehicle, the reflection and the shadow, by using statistical and structural features. Misclassification at a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. This capability of error correction results in the accurate estimation of traffic parameters even in high traffic congestion. Also headlight detection is employed for nighttime operation. Experimental results show that the accuracy is more than 94% in our test database of diverse operating conditions such as daytime, shadowy daytime, highway, urban way, rural way, rainy day, snowy day, dusk and nighttime. The average processing time is 30 ms per frame when four traffic lanes are processed, and real-time operation could be realized while ensuring robust detection performance even for high-speed vehicles up to 150 km h −1

  20. Robust seismicity forecasting based on Bayesian parameter estimation for epidemiological spatio-temporal aftershock clustering models.

    Science.gov (United States)

    Ebrahimian, Hossein; Jalayer, Fatemeh

    2017-08-29

    In the immediate aftermath of a strong earthquake and in the presence of an ongoing aftershock sequence, scientific advisories in terms of seismicity forecasts play quite a crucial role in emergency decision-making and risk mitigation. Epidemic Type Aftershock Sequence (ETAS) models are frequently used for forecasting the spatio-temporal evolution of seismicity in the short-term. We propose robust forecasting of seismicity based on ETAS model, by exploiting the link between Bayesian inference and Markov Chain Monte Carlo Simulation. The methodology considers the uncertainty not only in the model parameters, conditioned on the available catalogue of events occurred before the forecasting interval, but also the uncertainty in the sequence of events that are going to happen during the forecasting interval. We demonstrate the methodology by retrospective early forecasting of seismicity associated with the 2016 Amatrice seismic sequence activities in central Italy. We provide robust spatio-temporal short-term seismicity forecasts with various time intervals in the first few days elapsed after each of the three main events within the sequence, which can predict the seismicity within plus/minus two standard deviations from the mean estimate within the few hours elapsed after the main event.

  1. Spatio-Temporal Distribution of Landslides in Java and the Triggering Factors

    Directory of Open Access Journals (Sweden)

    Danang Sri Hadmoko

    2017-07-01

    Full Text Available Java Island, the most populated island of Indonesia, is prone to landslide disasters. Their occurrence and impact have increased mainly as the result of natural factors, aggravated by human imprint. This paper is intended to analyse: (1 the spatio-temporal variation of landslides in Java during short term and long-term periods, and (2 their causative factors such as rainfall, topography, geology, earthquakes, and land-use. The evaluation spatially and temporally of historical landslides and consequences were based on the landslide database covering the period of 1981 – 2007 in the GIS environment. Database showed that landslides distributed unevenly between West Java (67 %, Central Java (29 % and East Java (4 %. Slope failures were most abundant on the very intensively weathered zone of old volcanic materials on slope angles of 30O – 40O. Rainfall threshold analysis showed that shallow landslides and deep-seated landslides were triggered by rainfall events of 300 – 600 mm and > 600 mm respectively of antecedent rainfall during 30 consecutive days, and many cases showed that the landslides were not always initiated by intense rainfall during the landslide day. Human interference plays an important role in landslide occurrence through land conversion from natural forest to dryland agriculture which was the host of most of landslides in Java. These results and methods can be used as valuable information on the spatio-temporal characteristics of landslides in Java and their relationship with causative factors, thereby providing a sound basis for landslide investigation in more detail.

  2. Span: spike pattern association neuron for learning spatio-temporal spike patterns.

    Science.gov (United States)

    Mohemmed, Ammar; Schliebs, Stefan; Matsuda, Satoshi; Kasabov, Nikola

    2012-08-01

    Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations can be performed on them. Using this conversion, it is possible to apply the well-known Widrow-Hoff rule directly to the transformed spike trains in order to adjust the synaptic weights and to achieve a desired input/output spike behavior of the neuron. In the presented experimental analysis, the proposed learning algorithm is evaluated regarding its learning capabilities, its memory capacity, its robustness to noisy stimuli and its classification performance. Differences and similarities of SPAN regarding two related algorithms, ReSuMe and Chronotron, are discussed.

  3. Stochastic Dynamics through Hierarchically Embedded Markov Chains.

    Science.gov (United States)

    Vasconcelos, Vítor V; Santos, Fernando P; Santos, Francisco C; Pacheco, Jorge M

    2017-02-03

    Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects-such as mutations in evolutionary dynamics and a random exploration of choices in social systems-including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

  4. Lectures on Dynamics of Stochastic Systems

    CERN Document Server

    Klyatskin, Valery I

    2010-01-01

    Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. Models naturally render to statistical description, where random processes and fields express the input parameters and solutions. The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of the system and initial data. This book is a revised a

  5. Convergence of Sample Path Optimal Policies for Stochastic Dynamic Programming

    National Research Council Canada - National Science Library

    Fu, Michael C; Jin, Xing

    2005-01-01

    .... These results have practical implications for Monte Carlo simulation-based solution approaches to stochastic dynamic programming problems where it is impractical to extract the explicit transition...

  6. Identifying food deserts and swamps based on relative healthy food access: a spatio-temporal Bayesian approach.

    Science.gov (United States)

    Luan, Hui; Law, Jane; Quick, Matthew

    2015-12-30

    Obesity and other adverse health outcomes are influenced by individual- and neighbourhood-scale risk factors, including the food environment. At the small-area scale, past research has analysed spatial patterns of food environments for one time period, overlooking how food environments change over time. Further, past research has infrequently analysed relative healthy food access (RHFA), a measure that is more representative of food purchasing and consumption behaviours than absolute outlet density. This research applies a Bayesian hierarchical model to analyse the spatio-temporal patterns of RHFA in the Region of Waterloo, Canada, from 2011 to 2014 at the small-area level. RHFA is calculated as the proportion of healthy food outlets (healthy outlets/healthy + unhealthy outlets) within 4-km from each small-area. This model measures spatial autocorrelation of RHFA, temporal trend of RHFA for the study region, and spatio-temporal trends of RHFA for small-areas. For the study region, a significant decreasing trend in RHFA is observed (-0.024), suggesting that food swamps have become more prevalent during the study period. For small-areas, significant decreasing temporal trends in RHFA were observed for all small-areas. Specific small-areas located in south Waterloo, north Kitchener, and southeast Cambridge exhibited the steepest decreasing spatio-temporal trends and are classified as spatio-temporal food swamps. This research demonstrates a Bayesian spatio-temporal modelling approach to analyse RHFA at the small-area scale. Results suggest that food swamps are more prevalent than food deserts in the Region of Waterloo. Analysing spatio-temporal trends of RHFA improves understanding of local food environment, highlighting specific small-areas where policies should be targeted to increase RHFA and reduce risk factors of adverse health outcomes such as obesity.

  7. Characterizing the Spatio-Temporal Pattern of Land Surface Temperature through Time Series Clustering: Based on the Latent Pattern and Morphology

    Directory of Open Access Journals (Sweden)

    Huimin Liu

    2018-04-01

    Full Text Available Land Surface Temperature (LST is a critical component to understand the impact of urbanization on the urban thermal environment. Previous studies were inclined to apply only one snapshot to analyze the pattern and dynamics of LST without considering the non-stationarity in the temporal domain, or focus on the diurnal, seasonal, and annual pattern analysis of LST which has limited support for the understanding of how LST varies with the advancing of urbanization. This paper presents a workflow to extract the spatio-temporal pattern of LST through time series clustering by focusing on the LST of Wuhan, China, from 2002 to 2017 with a 3-year time interval with 8-day MODerate-resolution Imaging Spectroradiometer (MODIS satellite image products. The Latent pattern of LST (LLST generated by non-parametric Multi-Task Gaussian Process Modeling (MTGP and the Multi-Scale Shape Index (MSSI which characterizes the morphology of LLST are coupled for pattern recognition. Specifically, spatio-temporal patterns are discovered after the extraction of spatial patterns conducted by the incorporation of k -means and the Back-Propagation neural networks (BP-Net. The spatial patterns of the 6 years form a basic understanding about the corresponding temporal variances. For spatio-temporal pattern recognition, LLSTs and MSSIs of the 6 years are regarded as geo-referenced time series. Multiple algorithms including traditional k -means with Euclidean Distance (ED, shape-based k -means with the constrained Dynamic Time Warping ( c DTW distance measure, and the Dynamic Time Warping Barycenter Averaging (DBA centroid computation method ( k - c DBA and k -shape are applied. Ten external indexes are employed to evaluate the performance of the three algorithms and reveal k - c DBA as the optimal time series clustering algorithm for our study. The study area is divided into 17 geographical time series clusters which respectively illustrate heterogeneous temporal dynamics of LST

  8. Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

    KAUST Repository

    Jaleel, Hassan; Shamma, Jeff S.

    2018-01-01

    dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through

  9. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Science.gov (United States)

    Medyńska-Gulij, Beata; Cybulski, Paweł

    2016-06-01

    This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

  10. Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

    Directory of Open Access Journals (Sweden)

    Medyńska-Gulij Beata

    2016-06-01

    Full Text Available This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

  11. Spatio-temporal coherence of free-electron laser radiation in the extreme ultraviolet determined by a Michelson interferometer

    Energy Technology Data Exchange (ETDEWEB)

    Hilbert, V.; Rödel, C.; Zastrau, U., E-mail: ulf.zastrau@uni-jena.de [Institut für Optik und Quantenelektronik, Friedrich-Schiller-Universität, Max-Wien-Platz 1, 07743 Jena (Germany); Brenner, G.; Düsterer, S.; Dziarzhytski, S.; Harmand, M.; Przystawik, A.; Redlin, H.; Toleikis, S. [Deutsches Elektronen-Synchrotron DESY, Notkestrasse 85, 22607 Hamburg (Germany); Döppner, T.; Ma, T. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550 (United States); Fletcher, L. [Department of Physics, University of California, Berkeley, California 94720 (United States); Förster, E. [Institut für Optik und Quantenelektronik, Friedrich-Schiller-Universität, Max-Wien-Platz 1, 07743 Jena (Germany); Helmholtz-Institut Jena, Fröbelstieg 3, 07743 Jena (Germany); Glenzer, S. H.; Lee, H. J. [SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025 (United States); Hartley, N. J. [Department of Physics, Clarendon Laboratory, University of Oxford, Parks Road, Oxford OX1 3PU (United Kingdom); Kazak, L.; Komar, D.; Skruszewicz, S. [Institut für Physik, Universität Rostock, 18051 Rostock (Germany); and others

    2014-09-08

    A key feature of extreme ultraviolet (XUV) radiation from free-electron lasers (FELs) is its spatial and temporal coherence. We measured the spatio-temporal coherence properties of monochromatized FEL pulses at 13.5 nm using a Michelson interferometer. A temporal coherence time of (59±8) fs has been determined, which is in good agreement with the spectral bandwidth given by the monochromator. Moreover, the spatial coherence in vertical direction amounts to about 15% of the beam diameter and about 12% in horizontal direction. The feasibility of measuring spatio-temporal coherence properties of XUV FEL radiation using interferometric techniques advances machine operation and experimental studies significantly.

  12. Structured Spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    2010-01-01

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  13. Nonlinear and stochastic dynamics of coherent structures

    DEFF Research Database (Denmark)

    Rasmussen, Kim

    1997-01-01

    This Thesis deals with nonlinear and stochastic dynamics in systems which can be described by nonlinear Schrödinger models. Basically three different models are investigated. The first is the continuum nonlinear Schröndinger model in one and two dimensions generalized by a tunable degree of nonli......This Thesis deals with nonlinear and stochastic dynamics in systems which can be described by nonlinear Schrödinger models. Basically three different models are investigated. The first is the continuum nonlinear Schröndinger model in one and two dimensions generalized by a tunable degree...... introduces the nonlinear Schrödinger model in one and two dimensions, discussing the soliton solutions in one dimension and the collapse phenomenon in two dimensions. Also various analytical methods are described. Then a derivation of the nonlinear Schrödinger equation is given, based on a Davydov like...... system described by a tight-binding Hamiltonian and a harmonic lattice coupled b y a deformation-type potential. This derivation results in a two-dimensional nonline ar Schrödinger model, and considering the harmonic lattice to be in thermal contact with a heat bath w e show that the nonlinear...

  14. Improvement of image velocimetry based on a spatio-temporal correlation method; Jikukan sokan ni motozuku ryushi gazo sokudoba keisokuho no kaiseki seino kaizen

    Energy Technology Data Exchange (ETDEWEB)

    Yamada, H. [Tokuyama College of Technology, Yamaguchi (Japan); Arifuku, T. [Komatsu Ltd., Tokyo (Japan); Koga, K. [Yamaguchi University, Yamaguchi (Japan). Faculty of Engineering

    1998-05-31

    In the image velocimetry, it is generally required to detect the various velocity in each position of the flow field. But the maximum velocity which the usual velocimetry can detect has been limited in about 1 pixel per frame. Then, in order to measure the wide range of velocity vectors from the dynamic image, the improvement of performance in the image velocimetry based on a spatio-temporal correlation method would be attempted by enlarging the analytical region and by interpolating the new frame. The analytical performance of velocimetry was estimated by measuring the velocity from the flow dynamic image made artificially on the personal computer so as to simulate the flow of fluid containing a lot of small particles. As the results, the velocity range of the improved velocimetry became larger than that of the usual velocimetry. 21 refs., 13 figs., 1 tab.

  15. Spatio-temporal foreshock activity during stick-slip experiments of large rock samples

    Science.gov (United States)

    Tsujimura, Y.; Kawakata, H.; Fukuyama, E.; Yamashita, F.; Xu, S.; Mizoguchi, K.; Takizawa, S.; Hirano, S.

    2016-12-01

    Foreshock activity has sometimes been reported for large earthquakes, and has been roughly classified into the following two classes. For shallow intraplate earthquakes, foreshocks occurred in the vicinity of the mainshock hypocenter (e.g., Doi and Kawakata, 2012; 2013). And for intraplate subduction earthquakes, foreshock hypocenters migrated toward the mainshock hypocenter (Kato, et al., 2012; Yagi et al., 2014). To understand how foreshocks occur, it is useful to investigate the spatio-temporal activities of foreshocks in the laboratory experiments under controlled conditions. We have conducted stick-slip experiments by using a large-scale biaxial friction apparatus at NIED in Japan (e.g., Fukuyama et al., 2014). Our previous results showed that stick-slip events repeatedly occurred in a run, but only those later events were preceded by foreshocks. Kawakata et al. (2014) inferred that the gouge generated during the run was an important key for foreshock occurrence. In this study, we proceeded to carry out stick-slip experiments of large rock samples whose interface (fault plane) is 1.5 meter long and 0.5 meter wide. After some runs to generate fault gouge between the interface. In the current experiments, we investigated spatio-temporal activities of foreshocks. We detected foreshocks from waveform records of 3D array of piezo-electric sensors. Our new results showed that more than three foreshocks (typically about twenty) had occurred during each stick-slip event, in contrast to the few foreshocks observed during previous experiments without pre-existing gouge. Next, we estimated the hypocenter locations of the stick-slip events, and found that they were located near the opposite end to the loading point. In addition, we observed a migration of foreshock hypocenters toward the hypocenter of each stick-slip event. This suggests that the foreshock activity observed in our current experiments was similar to that for the interplate earthquakes in terms of the

  16. Spatio-temporal transmission patterns of black-band disease in a coral community.

    Directory of Open Access Journals (Sweden)

    Assaf Zvuloni

    Full Text Available BACKGROUND: Transmission mechanisms of black-band disease (BBD in coral reefs are poorly understood, although this disease is considered to be one of the most widespread and destructive coral infectious diseases. The major objective of this study was to assess transmission mechanisms of BBD in the field based on the spatio-temporal patterns of the disease. METHODOLOGY/PRINCIPAL FINDINGS: 3,175 susceptible and infected corals were mapped over an area of 10x10 m in Eilat (northern Gulf of Aqaba, Red Sea and the distribution of the disease was examined monthly throughout almost two full disease cycles (June 2006-December 2007. Spatial and spatio-temporal analyses were applied to infer the transmission pattern of the disease and to calculate key epidemiological parameters such as (basic reproduction number. We show that the prevalence of the disease is strongly associated with high water temperature. When water temperatures rise and disease prevalence increases, infected corals exhibit aggregated distributions on small spatial scales of up to 1.9 m. Additionally, newly-infected corals clearly appear in proximity to existing infected corals and in a few cases in direct contact with them. We also present and test a model of water-borne infection, indicating that the likelihood of a susceptible coral becoming infected is defined by its spatial location and by the relative spatial distribution of nearby infected corals found in the site. CONCLUSIONS/SIGNIFICANCE: Our results provide evidence that local transmission, but not necessarily by direct contact, is likely to be an important factor in the spread of the disease over the tested spatial scale. In the absence of potential disease vectors with limited mobility (e.g., snails, fireworms in the studied site, water-borne infection is likely to be a significant transmission mechanism of BBD. Our suggested model of water-borne transmission supports this hypothesis. The spatio-temporal analysis also points

  17. Challenges for modelling spatio-temporal variations of malaria risk in Malawi

    Science.gov (United States)

    Lowe, R.; Chirombo, J.; Tompkins, A. M.

    2012-04-01

    Malaria is the leading cause of morbidity and mortality in Malawi with more than 6 million episodes reported each year. Malaria poses a huge economic burden to Malawi in terms of the direct cost of treating malaria patients and also indirect costs resulting from workdays lost in agriculture and industry and absenteeism from school. Malawi implements malaria control activities within the Roll Back Malaria framework, with the objective to provide those most at risk (i.e. children under five years, pregnant woman and individuals with suppressed immune systems) access to personal and community protective measures. However, at present there is no mechanism by which to target the most 'at risk' populations ahead of an impending epidemic. Malaria transmission is influenced by variations in meteorological conditions, which impact the biology of the mosquito and the availability of breeding sites, but also socio-economic conditions such as levels of urbanisation, poverty and education, which influence human vulnerability and vector habitat. The many potential drivers of malaria, both extrinsic, such as climate, and intrinsic, such as population immunity are often difficult to disentangle. This presents a challenge for modelling of malaria risk in space and time. Using an age-stratified spatio-temporal dataset of malaria cases at the district level from July 2004 - June 2011, we use a spatio-temporal modelling framework to model variations in malaria risk in Malawi. Climatic and topographic variations are accounted for using an interpolation method to relate gridded products to administrative districts. District level data is tested in the model to account for confounding factors, including the proportion of the population living in urban areas; residing in traditional housing; with no toilet facilities; who do not attend school, etc, the number of health facilities per population and yearly estimates of insecticide-treated mosquito net distribution. In order to account for

  18. Spatio-temporal variation in δ13CDIC of a tropical eutrophic estuary (Cochin estuary, India) and adjacent Arabian Sea

    Science.gov (United States)

    Bhavya, P. S.; Kumar, Sanjeev; Gupta, G. V. M.; Sudharma, K. V.; Sudheesh, V.

    2018-02-01

    Carbon isotopic composition of dissolved inorganic carbon (δ13CDIC) in the Cochin estuary, a tropical eutrophic estuary along the southwest coast of India, and the adjacent coastal Arabian Sea was measured to understand spatio-temporal variability in sources and processes controlling inorganic carbon (C) dynamics in this estuarine-coastal system. δ13CDIC in the Cochin estuary showed wide variation during three different seasons (premonsoon: - 12.2 to - 3.26‰; monsoon: - 13.6 to - 5.69‰; and postmonsoon: - 6.34 to + 0.79‰). Detailed mixing curve approximation modeling along with relationships of δ13CDIC with dissolved oxygen and nutrients suggest dominant role of freshwater mixing and degassing of CO2 on DIC dynamics during wet seasons (premonsoon and monsoon). Excess CO2 brought in by rivers and in situ production due to respiration in the Cochin estuary result into one of the highest pCO2 observed in estuarine systems, leading to its degassing. During postmonsoon, a relatively dry period with high salinity, calcite precipitation was a major process with calcite saturation index > 1 at few locations. Relatively lower average surface values of δ13CDIC in the coastal Arabian Sea (premonsoon: + 0.95‰; monsoon: + 0.88‰; and postmonsoon: + 0.66‰) compared to the predicted open ocean value along with mixing curve modeling suggest dominance of respiration/organic matter (OM) degradation over primary productivity. Estuarine influence on coastal DIC dynamics was observed in nearshore region ( 10 km), whereas evidence of upwelling was found at farther locations.

  19. On some descriptive and predictive methods for the dynamics of cancer growth

    Directory of Open Access Journals (Sweden)

    Iulian T. Vlad

    2015-09-01

    Full Text Available Cancer is a widely spread disease that affects a large proportion of the human population, and many research teams are developing algorithms to help medics to understand this disease. In particular, tumor growth has been studied from different viewpoints and several mathematical models have been proposed. In this paper, we review a set of comprehensive and modern tools that are useful for prediction of cancer growth in space and time. We comment on three alternative approaches. We first consider spatio-temporal stochastic processes within a Bayesian framework to model spatial heterogeneity, temporal dependence and spatio-temporal interactions amongst the pixels, providing a general modeling framework for such dynamics. We then consider predictions based on geometric properties of plane curves and vectors, and propose two methods of geometric prediction. Finally we focus on functional data analysis to statistically compare tumor contour evolutions. We also analyze real data on brain tumor.

  20. Spatio-temporal modelling of rainfall in the Murray-Darling Basin

    Science.gov (United States)

    Nowak, Gen; Welsh, A. H.; O'Neill, T. J.; Feng, Lingbing

    2018-02-01

    The Murray-Darling Basin (MDB) is a large geographical region in southeastern Australia that contains many rivers and creeks, including Australia's three longest rivers, the Murray, the Murrumbidgee and the Darling. Understanding rainfall patterns in the MDB is very important due to the significant impact major events such as droughts and floods have on agricultural and resource productivity. We propose a model for modelling a set of monthly rainfall data obtained from stations in the MDB and for producing predictions in both the spatial and temporal dimensions. The model is a hierarchical spatio-temporal model fitted to geographical data that utilises both deterministic and data-derived components. Specifically, rainfall data at a given location are modelled as a linear combination of these deterministic and data-derived components. A key advantage of the model is that it is fitted in a step-by-step fashion, enabling appropriate empirical choices to be made at each step.

  1. Spatio-temporal characteristics of self-pulse in hollow cathode discharge

    International Nuclear Information System (INIS)

    Jing, Ha; He, Shoujie

    2015-01-01

    The characteristics of self-pulse in hollow cathode discharge at low pressure have been investigated. The voltage-current (V-I) curves, the influence of ballast resistor on the self-pulses, and the evolution of current and voltage are measured. Both the axial and radial spatio-temporal discharge images of self-pulse are recorded. The results show that there exists the hysteresis effect in the present hollow cathode discharge. The high value of ballast resistors is favourable for the observation of self-pulses. The process of the self-pulse can be divided into three stages from the temporal discharge images, i.e., the pre-discharge, the transition from mainly axial electric field to mainly radial electric field, and the decaying process. The self-pulse is suggested to originate from the mode transition of the discharge in essence

  2. Spatio-temporal chaos and thermal noise in Josephson junction series arrays

    International Nuclear Information System (INIS)

    Dominguez, D.; Cerdeira, H.A.

    1995-01-01

    We study underdamped Josephson junction series arrays that are globally coupled through a resistive shunting load and driven by an rf bias current. We find that they can be an experimental realization of many phenomena currently studied in globally coupled logistic map. Depending on the bias current the array can show Shapiro steps but also spatio-temporal chaos or ''turbulence'' in the IV characteristics. In the turbulent phase there is a saturation of the broad band noise for a large number of junctions. This corresponds to a break down of the law of large numbers as seen in globally coupled maps. We study this phenomenon as a function of thermal noise. We find that when increasing the temperature the broad band noise decreases. (author). 8 refs, 1 fig

  3. Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

    Science.gov (United States)

    Tarabalka, Yuliya; Charpiat, Guillaume; Brucker, Ludovic; Menze, Bjoern H.

    2014-01-01

    We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

  4. A collaborative large spatio-temporal data visual analytics architecture for emergence response

    International Nuclear Information System (INIS)

    Guo, D; Li, J; Zhou, Y; Cao, H

    2014-01-01

    The unconventional emergency, usually outbreaks more suddenly, and is diffused more quickly, but causes more secondary damage and derives more disaster than what it is usually expected. The data volume and urgency of emergency exceeds the capacity of current emergency management systems. In this paper, we propose a three-tier collaborative spatio-temporal visual analysis architecture to support emergency management. The prototype system, based on cloud computation environment, supports aggregation of massive unstructured and semi-structured data, integration of various computing model sand algorithms; collaborative visualization and visual analytics among users with a diversity of backgrounds. The distributed data in 100TB scale is integrated in a unified platform and shared with thousands of experts and government agencies by nearly 100 models. The users explore, visualize and analyse the big data and make a collaborative countermeasures to emergencies

  5. Laser-Based Spatio-Temporal Characterisation of Port Fuel Injection (PFI Sprays

    Directory of Open Access Journals (Sweden)

    C. T. N. Anand

    2010-06-01

    Full Text Available In the present work, detailed laser-based diagnostic experiments were conducted to characterise the spray from low pressure 2-hole and 4-hole Port Fuel Injection (PFI injectors. The main objective of the work included obtaining quantitative information of the spatio-temporal spray structure of such low-pressure gasoline sprays. A novel approach involving a combination of techniques such as Mie scattering, Granulometry, and Laser Sheet Dropsizing (LSD was used to study the spray structure. The droplet sizes, distributions with time, Sauter Mean Diameters (SMD, droplet velocities, cone angles and spray tip penetrations of the sprays from the injectors were determined. The spray from these injectors is found to be ‘pencil like’ and not dispersed as in high pressure sprays. The application of the above mentioned techniques provides two-dimensional SMD contours of the entire spray at different instants of time, with reasonable accuracy.

  6. FACILITATING INTEGRATED SPATIO-TEMPORAL VISUALIZATION AND ANALYSIS OF HETEROGENEOUS ARCHAEOLOGICAL AND PALAEOENVIRONMENTAL RESEARCH DATA

    Directory of Open Access Journals (Sweden)

    C. Willmes

    2012-07-01

    Full Text Available In the context of the Collaborative Research Centre 806 "Our way to Europe" (CRC806, a research database is developed for integrating data from the disciplines of archaeology, the geosciences and the cultural sciences to facilitate integrated access to heterogeneous data sources. A practice-oriented data integration concept and its implementation is presented in this contribution. The data integration approach is based on the application of Semantic Web Technology and is applied to the domains of archaeological and palaeoenvironmental data. The aim is to provide integrated spatio-temporal access to an existing wealth of data to facilitate research on the integrated data basis. For the web portal of the CRC806 research database (CRC806-Database, a number of interfaces and applications have been evaluated, developed and implemented for exposing the data to interactive analysis and visualizations.

  7. VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data.

    Science.gov (United States)

    Chen, Wei; Huang, Zhaosong; Wu, Feiran; Zhu, Minfeng; Guan, Huihua; Maciejewski, Ross

    2017-10-02

    Urban data is massive, heterogeneous, and spatio-temporal, posing a substantial challenge for visualization and analysis. In this paper, we design and implement a novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data. Our approach allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features. Through our approach, the analyst is able to select, filter, aggregate across multiple data sources and extract information that would be hidden to a single data subset. To illustrate the effectiveness of our approach, we provide case studies on a real urban dataset that contains the cyber-, physical-, and socialinformation of 14 million citizens over 22 days.

  8. Spatio-temporal model based optimization framework to design future hydrogen infrastructure networks

    International Nuclear Information System (INIS)

    Konda, N.V.S.; Shah, N.; Brandon, N.P.

    2009-01-01

    A mixed integer programming (MIP) spatio-temporal model was used to design hydrogen infrastructure networks for the Netherlands. The detailed economic analysis was conducted using a multi-echelon model of the entire hydrogen supply chain, including feed, production, storage, and transmission-distribution systems. The study considered various near-future and commercially available technologies. A multi-period model was used to design evolutionary hydrogen supply networks in coherence with growing demand. A scenario-based analysis was conducted in order to account for uncertainties in future demand. The study showed that competitive hydrogen networks can be designed for any conceivable scenario. It was concluded that the multi-period model presented significant advantages in relation to decision-making over long time-horizons

  9. The spatio-temporal Development of Copenhagen's bicycle infrastructure 1912-2013

    DEFF Research Database (Denmark)

    Carstensen, Trine Agervig; Olafsson, Anton Stahl; Bech, Nynne Marie

    2015-01-01

    Cycling plays an important role in low-carbon transitions. Around the globe, cities are constructing bicycle infrastructure. The city of Copenhagen has a bicycle-friendly infrastructure celebrated for its fine-meshed network. This study documents the spatio-temporal development of Copenhagen......’s bicycle infrastructure and explores how the development corresponds to other processes of urban transformation. The study builds on historical maps of bicycle infrastructure that are digitised into geographical information, which allows for a comprehensive analysis of the formation of the network....... In search for identifying drivers, the study analyses the city’s spatial growth pattern, migration pattern, development of road network and changes in the transport culture. Analyses reveal that the bicycle infrastructure expanded at a relatively constant pace during distinct periods of urban transformation...

  10. Spatio-temporal distribution of global solar radiation for Mexico using GOES data

    Science.gov (United States)

    Bonifaz, R.; Cuahutle, M.; Valdes, M.; Riveros, D.

    2013-05-01

    Increased need of sustainable and renewable energies around the world requires studies about the amount and distribution of such types of energies. Global solar radiation distribution in space and time is a key component on order to know the availability of the energy for different applications. Using GOES hourly data, the heliosat model was implemented for Mexico. Details about the model and its components are discussed step by stem an once obtained the global solar radiation images, different time datasets (hourly, daily, monthly and seasonal) were built in order to know the spatio-temporal behavior of this type of energy. Preliminary maps of the available solar global radiation energy for Mexico are presented, the amount and variation of the solar radiation by regions are analyzed and discussed. Future work includes a better parametrization of the model using calibrated ground stations data and more use of more complex models for better results.

  11. Spatio-temporal regulation of circular RNA expression during porcine embryonic brain development

    DEFF Research Database (Denmark)

    Venø, Morten T; Hansen, Thomas B; Venø, Susanne T

    2015-01-01

    BACKGROUND: Recently, thousands of circular RNAs (circRNAs) have been discovered in various tissues and cell types from human, mouse, fruit fly and nematodes. However, expression of circRNAs across mammalian brain development has never been examined. RESULTS: Here we profile the expression of circ......RNA in five brain tissues at up to six time-points during fetal porcine development, constituting the first report of circRNA in the brain development of a large animal. An unbiased analysis reveals a highly complex regulation pattern of thousands of circular RNAs, with a distinct spatio-temporal expression...... are functionally conserved between mouse and human. Furthermore, we observe that "hot-spot" genes produce multiple circRNA isoforms, which are often differentially expressed across porcine brain development. A global comparison of porcine circRNAs reveals that introns flanking circularized exons are longer than...

  12. Estimating Activity Patterns Using Spatio-temporal Data of Cellphone Networks

    Directory of Open Access Journals (Sweden)

    Zahedi Seyedmostafa

    2016-01-01

    Full Text Available The tendency towards using activity-based models to predict trip demand has increased dramatically over recent years, but these models have suffered insufficient data for calibration. This paper discusses ways to process the cellphone spatio-temporal data in a manner that makes it comprehensible for traffic interpretations and proposes methods on how to infer urban mobility and activity patterns from the aforementioned data. Movements of each subscriber is described by a sequence of stays and trips and each stay is labeled by an activity. The type of activities are estimated using features such as land use, duration of stay, frequency of visit, arrival time to that activity and its distance from home. Finally, the chains of trips are identified and different patterns that citizens follow to participate in activities are determined. The data comprises 144 million records of the location of 300,000 citizens of Shiraz at five-minute intervals.

  13. Spatio-Temporal Analysis of Human Activities in Indoor Environments through Mobile Sensing

    DEFF Research Database (Denmark)

    Prentow, Thor Siiger

    with the intuition and personal experience of the planners. Lack of real-time information on task execution has made it difficult to adapt to changes in the schedules, such as delays or suddenly occurring urgent tasks. The recent advances in methods and devices for mobile sensing provides opportunities...... methods for spatio-temporal analysis of human activities in indoor environments based on mobile sensing. The methods aim to improve scheduling and facility utilization by providing information on the used route networks, transportation modes, travel times, and the flow of people through buildings....... The methods are based on large-scale real-time indoor positioning through the use of existing WiFi infrastructures, which allows for easy deployment even in very large building complexes. The methods are designed for real-time operation, which enables them to detect and adjust to changes as they occur...

  14. Spatio-temporal features for tracking and quadruped/biped discrimination

    Science.gov (United States)

    Rickman, Rick; Copsey, Keith; Bamber, David C.; Page, Scott F.

    2012-05-01

    Techniques such as SIFT and SURF facilitate efficient and robust image processing operations through the use of sparse and compact spatial feature descriptors and show much potential for defence and security applications. This paper considers the extension of such techniques to include information from the temporal domain, to improve utility in applications involving moving imagery within video data. In particular, the paper demonstrates how spatio-temporal descriptors can be used very effectively as the basis of a target tracking system and as target discriminators which can distinguish between bipeds and quadrupeds. Results using sequences of video imagery of walking humans and dogs are presented, and the relative merits of the approach are discussed.

  15. Nonlinear and Stochastic Dynamics in the Heart

    Science.gov (United States)

    Qu, Zhilin; Hu, Gang; Garfinkel, Alan; Weiss, James N.

    2014-01-01

    In a normal human life span, the heart beats about 2 to 3 billion times. Under diseased conditions, a heart may lose its normal rhythm and degenerate suddenly into much faster and irregular rhythms, called arrhythmias, which may lead to sudden death. The transition from a normal rhythm to an arrhythmia is a transition from regular electrical wave conduction to irregular or turbulent wave conduction in the heart, and thus this medical problem is also a problem of physics and mathematics. In the last century, clinical, experimental, and theoretical studies have shown that dynamical theories play fundamental roles in understanding the mechanisms of the genesis of the normal heart rhythm as well as lethal arrhythmias. In this article, we summarize in detail the nonlinear and stochastic dynamics occurring in the heart and their links to normal cardiac functions and arrhythmias, providing a holistic view through integrating dynamics from the molecular (microscopic) scale, to the organelle (mesoscopic) scale, to the cellular, tissue, and organ (macroscopic) scales. We discuss what existing problems and challenges are waiting to be solved and how multi-scale mathematical modeling and nonlinear dynamics may be helpful for solving these problems. PMID:25267872

  16. Nonlinear and stochastic dynamics in the heart

    Energy Technology Data Exchange (ETDEWEB)

    Qu, Zhilin, E-mail: zqu@mednet.ucla.edu [Department of Medicine (Cardiology), David Geffen School of Medicine, University of California, Los Angeles, CA 90095 (United States); Hu, Gang [Department of Physics, Beijing Normal University, Beijing 100875 (China); Garfinkel, Alan [Department of Medicine (Cardiology), David Geffen School of Medicine, University of California, Los Angeles, CA 90095 (United States); Department of Integrative Biology and Physiology, University of California, Los Angeles, CA 90095 (United States); Weiss, James N. [Department of Medicine (Cardiology), David Geffen School of Medicine, University of California, Los Angeles, CA 90095 (United States); Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095 (United States)

    2014-10-10

    In a normal human life span, the heart beats about 2–3 billion times. Under diseased conditions, a heart may lose its normal rhythm and degenerate suddenly into much faster and irregular rhythms, called arrhythmias, which may lead to sudden death. The transition from a normal rhythm to an arrhythmia is a transition from regular electrical wave conduction to irregular or turbulent wave conduction in the heart, and thus this medical problem is also a problem of physics and mathematics. In the last century, clinical, experimental, and theoretical studies have shown that dynamical theories play fundamental roles in understanding the mechanisms of the genesis of the normal heart rhythm as well as lethal arrhythmias. In this article, we summarize in detail the nonlinear and stochastic dynamics occurring in the heart and their links to normal cardiac functions and arrhythmias, providing a holistic view through integrating dynamics from the molecular (microscopic) scale, to the organelle (mesoscopic) scale, to the cellular, tissue, and organ (macroscopic) scales. We discuss what existing problems and challenges are waiting to be solved and how multi-scale mathematical modeling and nonlinear dynamics may be helpful for solving these problems.

  17. Nonlinear and stochastic dynamics in the heart

    International Nuclear Information System (INIS)

    Qu, Zhilin; Hu, Gang; Garfinkel, Alan; Weiss, James N.

    2014-01-01

    In a normal human life span, the heart beats about 2–3 billion times. Under diseased conditions, a heart may lose its normal rhythm and degenerate suddenly into much faster and irregular rhythms, called arrhythmias, which may lead to sudden death. The transition from a normal rhythm to an arrhythmia is a transition from regular electrical wave conduction to irregular or turbulent wave conduction in the heart, and thus this medical problem is also a problem of physics and mathematics. In the last century, clinical, experimental, and theoretical studies have shown that dynamical theories play fundamental roles in understanding the mechanisms of the genesis of the normal heart rhythm as well as lethal arrhythmias. In this article, we summarize in detail the nonlinear and stochastic dynamics occurring in the heart and their links to normal cardiac functions and arrhythmias, providing a holistic view through integrating dynamics from the molecular (microscopic) scale, to the organelle (mesoscopic) scale, to the cellular, tissue, and organ (macroscopic) scales. We discuss what existing problems and challenges are waiting to be solved and how multi-scale mathematical modeling and nonlinear dynamics may be helpful for solving these problems

  18. Participatory Bluetooth Sensing: A Method for Acquiring Spatio-Temporal Data about Participant Mobility and Interactions at Large Scale Events

    DEFF Research Database (Denmark)

    Stopczynski, Arkadiusz; Larsen, Jakob Eg; Jørgensen, Sune Lehmann

    2013-01-01

    for collecting spatio-temporal data about participant mobility and social interactions uses the capabilities of Bluetooth capable smartphones carried by participants. As a proof-of-concept we present a field study with deployment of the method in a large music festival with 130 000 participants where a small...

  19. Clonal mobility and its implications for spatio-temporal patterns of plant communities: what do we need to know next?

    Czech Academy of Sciences Publication Activity Database

    Zobel, M.; Moora, M.; Herben, Tomáš

    2010-01-01

    Roč. 119, č. 5 (2010), s. 802-806 ISSN 0030-1299 Institutional research plan: CEZ:AV0Z60050516 Keywords : clonal mobility * spatio-temporal patterns * plant communities Subject RIV: EF - Botanics Impact factor: 3.393, year: 2010

  20. Characteristics of juvenile survivors reveal spatio-temporal differences in early life stage survival of Baltic cod

    DEFF Research Database (Denmark)

    Huwer, Bastian; Hinrichsen, H.H.; Böttcher, U.

    2014-01-01

    with previous modeling studies on the survival chances of early-stage larvae and with general spatio-temporal patterns of larval prey availability suggests that differences in survival are related to food availability during the early larval stage. Results are discussed in relation to the recruitment process...

  1. Spatio-temporal encoding using narrow-band linear frequency modulated signals in synthetic aperture ultrasound imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik; Jensen, Jørgen Arendt

    2005-01-01

    In this paper a method for spatio-temporal encoding is presented for synthetic transmit aperture ultrasound imaging (STA). The purpose is to excite several transmitters at the same time in order to transmit more acoustic energy in every single transmission. When increasing the transmitted acousti...

  2. Spatio-temporal spectra in the logarithmic layer of wall turbulence: large-eddy simulations and simple models

    NARCIS (Netherlands)

    Wilczek, Michael; Stevens, Richard Johannes Antonius Maria; Meneveau, Charles

    2015-01-01

    Motivated by the need to characterize the spatio-temporal structure of turbulence in wall-bounded flows, we study wavenumber–frequency spectra of the streamwise velocity component based on large-eddy simulation (LES) data. The LES data are used to measure spectra as a function of the two

  3. Hierarchical Bayesian modeling of spatio-temporal patterns of lung cancer incidence risk in Georgia, USA: 2000-2007

    Science.gov (United States)

    Yin, Ping; Mu, Lan; Madden, Marguerite; Vena, John E.

    2014-10-01

    Lung cancer is the second most commonly diagnosed cancer in both men and women in Georgia, USA. However, the spatio-temporal patterns of lung cancer risk in Georgia have not been fully studied. Hierarchical Bayesian models are used here to explore the spatio-temporal patterns of lung cancer incidence risk by race and gender in Georgia for the period of 2000-2007. With the census tract level as the spatial scale and the 2-year period aggregation as the temporal scale, we compare a total of seven Bayesian spatio-temporal models including two under a separate modeling framework and five under a joint modeling framework. One joint model outperforms others based on the deviance information criterion. Results show that the northwest region of Georgia has consistently high lung cancer incidence risk for all population groups during the study period. In addition, there are inverse relationships between the socioeconomic status and the lung cancer incidence risk among all Georgian population groups, and the relationships in males are stronger than those in females. By mapping more reliable variations in lung cancer incidence risk at a relatively fine spatio-temporal scale for different Georgian population groups, our study aims to better support healthcare performance assessment, etiological hypothesis generation, and health policy making.

  4. Spatio-temporal variability of the North Sea cod recruitment in relation to temperature and zooplankton.

    Directory of Open Access Journals (Sweden)

    Delphine Nicolas

    Full Text Available The North Sea cod (Gadus morhua, L. stock has continuously declined over the past four decades linked with overfishing and climate change. Changes in stock structure due to overfishing have made the stock largely dependent on its recruitment success, which greatly relies on environmental conditions. Here we focus on the spatio-temporal variability of cod recruitment in an effort to detect changes during the critical early life stages. Using International Bottom Trawl Survey (IBTS data from 1974 to 2011, a major spatio-temporal change in the distribution of cod recruits was identified in the late 1990s, characterized by a pronounced decrease in the central and southeastern North Sea stock. Other minor spatial changes were also recorded in the mid-1980s and early 1990s. We tested whether the observed changes in recruits distribution could be related with direct (i.e. temperature and/or indirect (i.e. changes in the quantity and quality of zooplankton prey effects of climate variability. The analyses were based on spatially-resolved time series, i.e. sea surface temperature (SST from the Hadley Center and zooplankton records from the Continuous Plankton Recorder Survey. We showed that spring SST increase was the main driver for the most recent decrease in cod recruitment. The late 1990s were also characterized by relatively low total zooplankton biomass, particularly of energy-rich zooplankton such as the copepod Calanus finmarchicus, which have further contributed to the decline of North Sea cod recruitment. Long-term spatially-resolved observations were used to produce regional distribution models that could further be used to predict the abundance of North Sea cod recruits based on temperature and zooplankton food availability.

  5. Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

    Science.gov (United States)

    Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

    2017-06-01

    The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

  6. Spatio-temporal Variability of Albedo and its Impact on Glacier Melt Modelling

    Science.gov (United States)

    Kinnard, C.; Mendoza, C.; Abermann, J.; Petlicki, M.; MacDonell, S.; Urrutia, R.

    2017-12-01

    Albedo is an important variable for the surface energy balance of glaciers, yet its representation within distributed glacier mass-balance models is often greatly simplified. Here we study the spatio-temporal evolution of albedo on Glacier Universidad, central Chile (34°S, 70°W), using time-lapse terrestrial photography, and investigate its effect on the shortwave radiation balance and modelled melt rates. A 12 megapixel digital single-lens reflex camera was setup overlooking the glacier and programmed to take three daily images of the glacier during a two-year period (2012-2014). One image was chosen for each day with no cloud shading on the glacier. The RAW images were projected onto a 10m resolution digital elevation model (DEM), using the IMGRAFT software (Messerli and Grinsted, 2015). A six-parameter camera model was calibrated using a single image and a set of 17 ground control points (GCPs), yielding a georeferencing accuracy of accounting for possible camera movement over time. The reflectance values from the projected image were corrected for topographic and atmospheric influences using a parametric solar irradiation model, following a modified algorithm based on Corripio (2004), and then converted to albedo using reference albedo measurements from an on-glacier automatic weather station (AWS). The image-based albedo was found to compare well with independent albedo observations from a second AWS in the glacier accumulation area. Analysis of the albedo maps showed that the albedo is more spatially-variable than the incoming solar radiation, making albedo a more important factor of energy balance spatial variability. The incorporation of albedo maps within an enhanced temperature index melt model revealed that the spatio-temporal variability of albedo is an important factor for the calculation of glacier-wide meltwater fluxes.

  7. Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

    Science.gov (United States)

    Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

    2017-04-01

    Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

  8. Spatio-Temporal Simulation and Analysis of Regional Ecological Security Based on Lstm

    Science.gov (United States)

    Gong, C.; Qi, L.; Heming, L.; Karimian, H.; Yuqin, M.

    2017-10-01

    Region is a complicated system, where human, nature and society interact and influence. Quantitative modeling and simulation of ecology in the region are the key to realize the strategy of regional sustainable development. Traditional machine learning methods have made some achievements in the modeling of regional ecosystems, but it is difficult to determine the learning characteristics and to realize spatio-temporal simulation. Deep learning does not need prior identification of training characteristics, have excellent feature learning ability, can improve the accuracy of model prediction, so the use of deep learning model has a significant advantage. Therefore, we use net primary productivity (NPP), atmospheric optical depth (AOD), moderate-resolution imaging spectrometer (MODIS), Normalized Difference Vegetation Index (NDVI), landcover and population data, and use LSTM to do spatio-temporal simulation. We conduct spatial analysis and driving force analysis. The conclusions are as follows: the ecological deficit of northwestern Henan and urban communities such as Zhengzhou is higher. The reason of former lies in the weak land productivity of the Loess Plateau, the irrational crop cultivation mode. The latter lies in the high consumption of resources in the large urban agglomeration; The positive trend of Henan ecological development from 2013 is mainly due to the effective environmental protection policy in the 12th five-year plan; The main driver of the sustained ecological deficit growth of Henan in 2004-2013 is high-speed urbanization, increasing population and goods consumption. This article provides relevant basic scientific support and reference for the regional ecological scientific management and construction.

  9. SPATIO-TEMPORAL SIMULATION AND ANALYSIS OF REGIONAL ECOLOGICAL SECURITY BASED ON LSTM

    Directory of Open Access Journals (Sweden)

    C. Gong

    2017-10-01

    Full Text Available Region is a complicated system, where human, nature and society interact and influence. Quantitative modeling and simulation of ecology in the region are the key to realize the strategy of regional sustainable development. Traditional machine learning methods have made some achievements in the modeling of regional ecosystems, but it is difficult to determine the learning characteristics and to realize spatio-temporal simulation. Deep learning does not need prior identification of training characteristics, have excellent feature learning ability, can improve the accuracy of model prediction, so the use of deep learning model has a significant advantage. Therefore, we use net primary productivity (NPP, atmospheric optical depth (AOD, moderate-resolution imaging spectrometer (MODIS, Normalized Difference Vegetation Index (NDVI, landcover and population data, and use LSTM to do spatio-temporal simulation. We conduct spatial analysis and driving force analysis. The conclusions are as follows: the ecological deficit of northwestern Henan and urban communities such as Zhengzhou is higher. The reason of former lies in the weak land productivity of the Loess Plateau, the irrational crop cultivation mode. The latter lies in the high consumption of resources in the large urban agglomeration; The positive trend of Henan ecological development from 2013 is mainly due to the effective environmental protection policy in the 12th five-year plan; The main driver of the sustained ecological deficit growth of Henan in 2004-2013 is high-speed urbanization, increasing population and goods consumption. This article provides relevant basic scientific support and reference for the regional ecological scientific management and construction.

  10. Adaptive OFDM Waveform Design for Spatio-Temporal-Sparsity Exploited STAP Radar

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Satyabrata [ORNL

    2017-11-01

    In this chapter, we describe a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly moving target using an orthogonal frequency division multiplexing (OFDM) radar. The motivation of employing an OFDM signal is that it improves the target-detectability from the interfering signals by increasing the frequency diversity of the system. However, due to the addition of one extra dimension in terms of frequency, the adaptive degrees-of-freedom in an OFDM-STAP also increases. Therefore, to avoid the construction a fully adaptive OFDM-STAP, we develop a sparsity-based STAP algorithm. We observe that the interference spectrum is inherently sparse in the spatio-temporal domain, as the clutter responses occupy only a diagonal ridge on the spatio-temporal plane and the jammer signals interfere only from a few spatial directions. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data compared to the other existing STAP techniques, and produces nearly optimum STAP performance. In addition to designing the STAP filter, we optimally design the transmit OFDM signals by maximizing the output signal-to-interference-plus-noise ratio (SINR) in order to improve the STAP performance. The computation of output SINR depends on the estimated value of the interference covariance matrix, which we obtain by applying the sparse recovery algorithm. Therefore, we analytically assess the effects of the synthesized OFDM coefficients on the sparse recovery of the interference covariance matrix by computing the coherence measure of the sparse measurement matrix. Our numerical examples demonstrate the achieved STAP-performance due to sparsity-based technique and adaptive waveform design.

  11. a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

    Science.gov (United States)

    Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

    2017-09-01

    Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

  12. Automated detection of qualitative spatio-temporal features in electrocardiac activation maps.

    Science.gov (United States)

    Ironi, Liliana; Tentoni, Stefania

    2007-02-01

    This paper describes a piece of work aiming at the realization of a tool for the automated interpretation of electrocardiac maps. Such maps can capture a number of electrical conduction pathologies, such as arrhytmia, that can be missed by the analysis of traditional electrocardiograms. But, their introduction into the clinical practice is still far away as their interpretation requires skills that belongs to very few experts. Then, an automated interpretation tool would bridge the gap between the established research outcome and clinical practice with a consequent great impact on health care. Qualitative spatial reasoning can play a crucial role in the identification of spatio-temporal patterns and salient features that characterize the heart electrical activity. We adopted the spatial aggregation (SA) conceptual framework and an interplay of numerical and qualitative information to extract features from epicardial maps, and to make them available for reasoning tasks. Our focus is on epicardial activation isochrone maps as they are a synthetic representation of spatio-temporal aspects of the propagation of the electrical excitation. We provide a computational SA-based methodology to extract, from 3D epicardial data gathered over time, (1) the excitation wavefront structure, and (2) the salient features that characterize wavefront propagation and visually correspond to specific geometric objects. The proposed methodology provides a robust and efficient way to identify salient pieces of information in activation time maps. The hierarchical structure of the abstracted geometric objects, crucial in capturing the prominent information, facilitates the definition of general rules necessary to infer the correlation between pathophysiological patterns and wavefront structure and propagation.

  13. Spatio-temporal regulation of Hsp90-ligand complex leads to immune activation.

    Directory of Open Access Journals (Sweden)

    Yasuaki eTamura

    2016-05-01

    Full Text Available Hsp90 is the most abundant cytosolic HSP and is known to act as a molecular chaperone. We found that an Hsp90-cancer antigen peptide complex was efficiently cross-presented by human monocyte-derived dendritic cells and induced peptide-specific cytotoxic T lymphocytes. Furthermore, we observed that the internalized Hsp90-peptide complex was strictly sorted to the Rab5+, EEA1+ static early endosome and the Hsp90-chaperoned peptide was processed and bound to MHC class I molecules through a endosome-recycling pathway. We also found that extracellular Hsp90 complexed with CpG-A or self-DNA stimulates production of a large amount of IFN-α from pDCs via static early endosome targeting. Thus, extracellular Hsp90 can target the antigen or nucleic acid to a static early endosome by spatio-temporal regulation. Moreover, we showed that Hsp90 associates with and delivers TLR7/9 from the ER to early endosomes for ligand recognition. Hsp90 inhibitor, geldanamycin derivative inhibited the Hsp90 association with TLR7/9, resulting in inhibition IFN-α production, leading to improvement of SLE symptoms. Interstingly, we observed that serum Hsp90 is clearly increased in patients with active SLE compared with that in patients with inactive disease. Serum Hsp90 detected in SLE patients binds to self-DNA and/or anti-DNA Ab, thus leading to stimulation of pDCs to produce IFN-α. Thus, Hsp90 plays a crucial role in the pathogenesis of SLE and that an Hsp90 inhibitor will therefore provide a new therapeutic approach to SLE and other nucleic acid-related autoimmune diseases. We will discuss how spatio-temporal regulation of Hsp90-ligand complexes within antigen-presenting cells affects the innate immunity and adaptive immunity.

  14. Spatio-temporal changes in total annual rainfall and the annual number of rainy days

    International Nuclear Information System (INIS)

    Limjirakan, Sangchan; Limsakul, Atsamon

    2007-01-01

    Full text: Full text: Rainfall variability is a critical factor for Thailand's socioeconomic development. Thus, enhancing understanding of rainfall mechanisms and variability is of paramount importance for effective strategies in tackling the severe droughts/floods which are memorable and a recurring problem in Thailand. Through this study, we have examined the variability of total annual rainfall (R,otai) and the annual number of rainy days (Rday) in Thailand during 1951-2003, using an Empirical Orthogonal Function (EOF) analysis. The primary objective is to determine the dominant spatio-temporal patterns, and to illustrate their connection with the El Nino-Southern Oscillation (ENSO). The results reveal that the first two EOF modes, which explain nearly half of the total variance, show a good coherence of spatio-temporal structures. A salient feature of the leading modes of R,otal and Rday in Thailand is that their temporal coefficients exhibit significant relations to the ENSO. On an interannual timescale, the leading modes tended to be greater (lower) than normal during the La Nina (El Nino) phase of the ENSO. Changes in the Walker circulation appear to be the dominant mechanism whereby the ENSO exerts its influence on rainfall variability in Thailand. For an interdecadal timescale, there is evidence of the unusual and persistent deficit in Rtar accompanied by a concomitant reduction of Ranrd over the last three decades. The recent drought-like condition has been closely associated with the shift in the ENSO towards more El Nino events since the late 1970s, and coincided with the high global mean temperature. These natural/anthropogenic-induced climatic changes have important implications for rainfall forecasting, and consequently for water resource and agricultural planning and management in Thailand

  15. Spatio-temporal manipulation of small GTPase activity at subcellular level and on timescale of seconds in living cells.

    Science.gov (United States)

    DeRose, Robert; Pohlmeyer, Christopher; Umeda, Nobuhiro; Ueno, Tasuku; Nagano, Tetsuo; Kuo, Scot; Inoue, Takanari

    2012-03-09

    Dynamic regulation of the Rho family of small guanosine triphosphatases (GTPases) with great spatiotemporal precision is essential for various cellular functions and events(1, 2). Their spatiotemporally dynamic nature has been revealed by visualization of their activity and localization in real time(3). In order to gain deeper understanding of their roles in diverse cellular functions at the molecular level, the next step should be perturbation of protein activities at a precise subcellular location and timing. To achieve this goal, we have developed a method for light-induced, spatio-temporally controlled activation of small GTPases by combining two techniques: (1) rapamycin-induced FKBP-FRB heterodimerization and (2) a photo-caging method of rapamycin. With the use of rapamycin-mediated FKBP-FRB heterodimerization, we have developed a method for rapidly inducible activation or inactivation of small GTPases including Rac(4), Cdc42(4), RhoA(4) and Ras(5), in which rapamycin induces translocation of FKBP-fused GTPases, or their activators, to the plasma membrane where FRB is anchored. For coupling with this heterodimerization system, we have also developed a photo-caging system of rapamycin analogs. A photo-caged compound is a small molecule whose activity is suppressed with a photocleavable protecting group known as a caging group. To suppress heterodimerization activity completely, we designed a caged rapamycin that is tethered to a macromolecule such that the resulting large complex cannot cross the plasma membrane, leading to virtually no background activity as a chemical dimerizer inside cells(6). Figure 1 illustrates a scheme of our system. With the combination of these two systems, we locally recruited a Rac activator to the plasma membrane on a timescale of seconds and achieved light-induced Rac activation at the subcellular level(6).

  16. Analysis of the Mediterranean fruit fly [Ceratitis capitata (Wiedemann)] spatio-temporal distribution in relation to sex and female mating status for precision IPM.

    Science.gov (United States)

    Sciarretta, Andrea; Tabilio, Maria Rosaria; Lampazzi, Elena; Ceccaroli, Claudio; Colacci, Marco; Trematerra, Pasquale

    2018-01-01

    The Mediterranean fruit fly (medfly), Ceratitis capitata (Wiedemann), is a key pest of fruit crops in many tropical, subtropical and mild temperate areas worldwide. The economic importance of this fruit fly is increasing due to its invasion of new geographical areas. Efficient control and eradication efforts require adequate information regarding C. capitata adults in relation to environmental and physiological cues. This would allow effective characterisation of the population spatio-temporal dynamic of the C. capitata population at both the orchard level and the area-wide landscape. The aim of this study was to analyse population patterns of adult medflies caught using two trapping systems in a peach orchard located in central Italy. They were differentiated by adult sex (males or females) and mating status of females (unmated or mated females) to determine the spatio-temporal dynamic and evaluate the effect of cultivar and chemical treatments on trap catches. Female mating status was assessed by spermathecal dissection and a blind test was carried out to evaluate the reliability of the technique. Geostatistical methods, variogram and kriging, were used to produce distributional maps. Results showed a strong correlation between the distribution of males and unmated females, whereas males versus mated females and unmated females versus mated females showed a lower correlation. Both cultivar and chemical treatments had significant effects on trap catches, showing associations with sex and female mating status. Medfly adults showed aggregated distributions in the experimental field, but hot spots locations varied. The spatial pattern of unmated females reflected that of males, whereas mated females were largely distributed around ripening or ripe fruit. The results give relevant insights into pest management. Mated females may be distributed differently to unmated females and the identification of male hot spots through monitoring would allow localisation of virgin

  17. Environmental versus demographic variability in stochastic predator–prey models

    International Nuclear Information System (INIS)

    Dobramysl, U; Täuber, U C

    2013-01-01

    In contrast to the neutral population cycles of the deterministic mean-field Lotka–Volterra rate equations, including spatial structure and stochastic noise in models for predator–prey interactions yields complex spatio-temporal structures associated with long-lived erratic population oscillations. Environmental variability in the form of quenched spatial randomness in the predation rates results in more localized activity patches. Our previous study showed that population fluctuations in rare favorable regions in turn cause a remarkable increase in the asymptotic densities of both predators and prey. Very intriguing features are found when variable interaction rates are affixed to individual particles rather than lattice sites. Stochastic dynamics with demographic variability in conjunction with inheritable predation efficiencies generate non-trivial time evolution for the predation rate distributions, yet with overall essentially neutral optimization. (paper)

  18. Dynamics of non-holonomic systems with stochastic transport

    Science.gov (United States)

    Holm, D. D.; Putkaradze, V.

    2018-01-01

    This paper formulates a variational approach for treating observational uncertainty and/or computational model errors as stochastic transport in dynamical systems governed by action principles under non-holonomic constraints. For this purpose, we derive, analyse and numerically study the example of an unbalanced spherical ball rolling under gravity along a stochastic path. Our approach uses the Hamilton-Pontryagin variational principle, constrained by a stochastic rolling condition, which we show is equivalent to the corresponding stochastic Lagrange-d'Alembert principle. In the example of the rolling ball, the stochasticity represents uncertainty in the observation and/or error in the computational simulation of the angular velocity of rolling. The influence of the stochasticity on the deterministically conserved quantities is investigated both analytically and numerically. Our approach applies to a wide variety of stochastic, non-holonomically constrained systems, because it preserves the mathematical properties inherited from the variational principle.

  19. Dynamic analysis of stochastic transcription cycles.

    Directory of Open Access Journals (Sweden)

    Claire V Harper

    2011-04-01

    Full Text Available In individual mammalian cells the expression of some genes such as prolactin is highly variable over time and has been suggested to occur in stochastic pulses. To investigate the origins of this behavior and to understand its functional relevance, we quantitatively analyzed this variability using new mathematical tools that allowed us to reconstruct dynamic transcription rates of different reporter genes controlled by identical promoters in the same living cell. Quantitative microscopic analysis of two reporter genes, firefly luciferase and destabilized EGFP, was used to analyze the dynamics of prolactin promoter-directed gene expression in living individual clonal and primary pituitary cells over periods of up to 25 h. We quantified the time-dependence and cyclicity of the transcription pulses and estimated the length and variation of active and inactive transcription phases. We showed an average cycle period of approximately 11 h and demonstrated that while the measured time distribution of active phases agreed with commonly accepted models of transcription, the inactive phases were differently distributed and showed strong memory, with a refractory period of transcriptional inactivation close to 3 h. Cycles in transcription occurred at two distinct prolactin-promoter controlled reporter genes in the same individual clonal or primary cells. However, the timing of the cycles was independent and out-of-phase. For the first time, we have analyzed transcription dynamics from two equivalent loci in real-time in single cells. In unstimulated conditions, cells showed independent transcription dynamics at each locus. A key result from these analyses was the evidence for a minimum refractory period in the inactive-phase of transcription. The response to acute signals and the result of manipulation of histone acetylation was consistent with the hypothesis that this refractory period corresponded to a phase of chromatin remodeling which significantly

  20. Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression.

    Science.gov (United States)

    Serag, Ahmed; Aljabar, Paul; Ball, Gareth; Counsell, Serena J; Boardman, James P; Rutherford, Mary A; Edwards, A David; Hajnal, Joseph V; Rueckert, Daniel

    2012-02-01

    Medical imaging has shown that, during early development, the brain undergoes more changes in size, shape and appearance than at any other time in life. A better understanding of brain development requires a spatio-temporal atlas that characterizes the dynamic changes during this period. In this paper we present an approach for constructing a 4D atlas of the developing brain, between 28 and 44 weeks post-menstrual age at time of scan, using T1 and T2 weighted MR images from 204 premature neonates. The method used for the creation of the average 4D atlas utilizes non-rigid registration between all pairs of images to eliminate bias in the atlas toward any of the original images. In addition, kernel regression is used to produce age-dependent anatomical templates. A novelty in our approach is the use of a time-varying kernel width, to overcome the variations in the distribution of subjects at different ages. This leads to an atlas that retains a consistent level of detail at every time-point. Comparisons between the resulting atlas and atlases constructed using affine and non-rigid registration are presented. The resulting 4D atlas has greater anatomic definition than currently available 4D atlases created using various affine and non-rigid registration approaches, an important factor in improving registrations between the atlas and individual subjects. Also, the resulting 4D atlas can serve as a good representative of the population of interest as it reflects both global and local changes. The atlas is publicly available at www.brain-development.org. Copyright © 2011 Elsevier Inc. All rights reserved.